From 06c0756109873714b4e09b3264df058d28a6632c Mon Sep 17 00:00:00 2001 From: anvy Date: Mon, 14 Apr 2025 11:43:36 +0200 Subject: [PATCH 01/27] add playground nb for strokes graph --- momepy/strokegraph.ipynb | 194 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 194 insertions(+) create mode 100644 momepy/strokegraph.ipynb diff --git a/momepy/strokegraph.ipynb b/momepy/strokegraph.ipynb new file mode 100644 index 00000000..d38fa942 --- /dev/null +++ b/momepy/strokegraph.ipynb @@ -0,0 +1,194 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Playground for strokes graph" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import geopandas as gpd\n", + "import matplotlib.pyplot as plt\n", + "import momepy\n", + "import networkx as nx\n", + "import folium" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", + "streets = momepy.remove_false_nodes(streets)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "streets.head()\n", + "streets[\"id\"] = streets.index" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ax = streets.plot(figsize=(8, 8), column=\"id\", cmap = \"Accent\")\n", + "ax.set_axis_off()\n", + "ax.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "graph = momepy.gdf_to_nx(streets, approach=\"primal\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# f, ax = plt.subplots(1, 3, figsize=(18, 6), sharex=True, sharey=True)\n", + "# streets.plot(color=\"#e32e00\", ax=ax[0])\n", + "# for i, facet in enumerate(ax):\n", + "# facet.set_title((\"Streets\", \"Primal graph\", \"Overlay\")[i])\n", + "# facet.axis(\"off\")\n", + "# nx.draw(\n", + "# graph, {n: [n[0], n[1]] for n in list(graph.nodes)}, ax=ax[1], node_size=15\n", + "# )\n", + "# streets.plot(color=\"#e32e00\", ax=ax[2], zorder=-1)\n", + "# nx.draw(\n", + "# graph, {n: [n[0], n[1]] for n in list(graph.nodes)}, ax=ax[2], node_size=15\n", + "# )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "points, lines = momepy.nx_to_gdf(graph, points=True, lines=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# fig, ax = plt.subplots(1,1)\n", + "# lines.plot(ax=ax)\n", + "# points.plot(ax=ax)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "coins = momepy.COINS(lines)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "stroke_attribute = coins.stroke_attribute()\n", + "stroke_gdf = coins.stroke_gdf()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", + "stroke_gdf[\"edge_ids\"] = stroke_gdf.stroke_id.apply(lambda x: list(lines.iloc[stroke_attribute[stroke_attribute == x].index][\"id\"]))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "stroke_gdf.head(10)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "d = nx.get_edge_attributes(graph, \"id\")\n", + "d = {v:k for k,v in d.items()}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "graph.edges[d[0]]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Set2\")\n", + "# lines.explore(m=m, column = \"id\", name = \"lines\")\n", + "# folium.LayerControl().add_to(m)\n", + "# m" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "simplification", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 512a18a62925d53a6382a2cc9ce092b2df28dd9f Mon Sep 17 00:00:00 2001 From: anvy Date: Mon, 14 Apr 2025 13:53:00 +0200 Subject: [PATCH 02/27] from input to primal graph with stroke attrs --- momepy/strokegraph.ipynb | 128 +++++++++++++++++++++++---------------- 1 file changed, 76 insertions(+), 52 deletions(-) diff --git a/momepy/strokegraph.ipynb b/momepy/strokegraph.ipynb index d38fa942..9d53a20d 100644 --- a/momepy/strokegraph.ipynb +++ b/momepy/strokegraph.ipynb @@ -13,6 +13,7 @@ "metadata": {}, "outputs": [], "source": [ + "# import libraries\n", "import geopandas as gpd\n", "import matplotlib.pyplot as plt\n", "import momepy\n", @@ -21,13 +22,10 @@ ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", - "streets = momepy.remove_false_nodes(streets)" + "Import example data set" ] }, { @@ -36,19 +34,29 @@ "metadata": {}, "outputs": [], "source": [ - "streets.head()\n", - "streets[\"id\"] = streets.index" + "# read in toy graph (Bubenec)\n", + "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", + "streets = momepy.remove_false_nodes(streets)\n", + "# streets[\"id\"] = streets.index\n", + "\n", + "# ax = streets.plot(figsize=(8, 8), column=\"id\", cmap = \"Accent\")\n", + "# ax.set_axis_off()\n", + "# ax.legend()" ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "ax = streets.plot(figsize=(8, 8), column=\"id\", cmap = \"Accent\")\n", - "ax.set_axis_off()\n", - "ax.legend()" + "Workflow (will be wrapped in function later)\n", + "\n", + "- [ ] input is a set of linestrings\n", + "- [ ] remove false nodes \n", + "- [ ] convert linestrings to primal graph\n", + "- [ ] get points and lines gdf from primal graph\n", + "- [ ] run COINS on lines gdf to find strokes\n", + "- [ ] add mapping of strokeID:edgeIDs to stroke gdf (use momepy's **edge ID**, not indexing)\n", + "- [ ] add stroke attribute to each edge on primal graph" ] }, { @@ -57,7 +65,9 @@ "metadata": {}, "outputs": [], "source": [ - "graph = momepy.gdf_to_nx(streets, approach=\"primal\")" + "# define variable defaults (will be arguments passed to future function)\n", + "angle_threshold=0\n", + "flow_mode=False" ] }, { @@ -66,18 +76,37 @@ "metadata": {}, "outputs": [], "source": [ - "# f, ax = plt.subplots(1, 3, figsize=(18, 6), sharex=True, sharey=True)\n", - "# streets.plot(color=\"#e32e00\", ax=ax[0])\n", - "# for i, facet in enumerate(ax):\n", - "# facet.set_title((\"Streets\", \"Primal graph\", \"Overlay\")[i])\n", - "# facet.axis(\"off\")\n", - "# nx.draw(\n", - "# graph, {n: [n[0], n[1]] for n in list(graph.nodes)}, ax=ax[1], node_size=15\n", - "# )\n", - "# streets.plot(color=\"#e32e00\", ax=ax[2], zorder=-1)\n", - "# nx.draw(\n", - "# graph, {n: [n[0], n[1]] for n in list(graph.nodes)}, ax=ax[2], node_size=15\n", - "# )" + "# remove false nodes\n", + "streets = momepy.remove_false_nodes(streets)\n", + "\n", + "# add unique edge ID to streets, already HERE!\n", + "streets[\"edge_id\"] = streets.index\n", + "\n", + "# make primal graph\n", + "graph = momepy.gdf_to_nx(streets, approach=\"primal\")\n", + "\n", + "# get gdfs of points and lines\n", + "points, lines = momepy.nx_to_gdf(graph, points=True, lines=True)\n", + "\n", + "# make coins\n", + "coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", + "\n", + "# get gdfs from COINS class\n", + "stroke_attribute = coins.stroke_attribute()\n", + "stroke_gdf = coins.stroke_gdf()\n", + "\n", + "# add stroke_id column\n", + "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", + "\n", + "# add edge_ids column (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", + "stroke_gdf[\"edge_ids\"] = stroke_gdf.stroke_id.apply(\n", + " lambda x: list(\n", + " lines.iloc[\n", + " stroke_attribute[stroke_attribute == x].index][\"edge_id\"]\n", + " )\n", + ")\n", + "\n", + "stroke_gdf.head()" ] }, { @@ -86,7 +115,10 @@ "metadata": {}, "outputs": [], "source": [ - "points, lines = momepy.nx_to_gdf(graph, points=True, lines=True)" + "# make dictionary for primal graph, edge_id:edge_name\n", + "d = nx.get_edge_attributes(graph, \"edge_id\")\n", + "d = {v:k for k,v in d.items()}\n", + "d" ] }, { @@ -95,9 +127,10 @@ "metadata": {}, "outputs": [], "source": [ - "# fig, ax = plt.subplots(1,1)\n", - "# lines.plot(ax=ax)\n", - "# points.plot(ax=ax)" + "# for each edge, add \"stroke_id\" as attribute to graph\n", + "for _, row in stroke_gdf.iterrows():\n", + " for e in row.edge_ids: \n", + " graph.edges[d[e]][\"stroke_id\"] = row.stroke_id" ] }, { @@ -106,7 +139,8 @@ "metadata": {}, "outputs": [], "source": [ - "coins = momepy.COINS(lines)" + "d_strokes = nx.get_edge_attributes(graph, \"stroke_id\")\n", + "d_edges = nx.get_edge_attributes(graph, \"edge_id\")" ] }, { @@ -115,8 +149,8 @@ "metadata": {}, "outputs": [], "source": [ - "stroke_attribute = coins.stroke_attribute()\n", - "stroke_gdf = coins.stroke_gdf()" + "edges_strokes = {d_edges[k]:d_strokes[k] for k in d_edges} \n", + "edges_strokes" ] }, { @@ -125,17 +159,17 @@ "metadata": {}, "outputs": [], "source": [ - "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", - "stroke_gdf[\"edge_ids\"] = stroke_gdf.stroke_id.apply(lambda x: list(lines.iloc[stroke_attribute[stroke_attribute == x].index][\"id\"]))" + "# m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Set2\")\n", + "# lines.explore(m=m, column = \"id\", name = \"lines\")\n", + "# folium.LayerControl().add_to(m)\n", + "# m" ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "stroke_gdf.head(10)" + "***" ] }, { @@ -143,31 +177,21 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "d = nx.get_edge_attributes(graph, \"id\")\n", - "d = {v:k for k,v in d.items()}" - ] + "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "graph.edges[d[0]]" - ] + "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "# m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Set2\")\n", - "# lines.explore(m=m, column = \"id\", name = \"lines\")\n", - "# folium.LayerControl().add_to(m)\n", - "# m" - ] + "source": [] } ], "metadata": { From 6ebaa17d1a32f09e928534ab9d64c09fd89f1f7b Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Mon, 14 Apr 2025 15:27:44 +0200 Subject: [PATCH 03/27] Add clse notebook --- momepy/strokegraph_clse.ipynb | 868 ++++++++++++++++++++++++++++++++++ 1 file changed, 868 insertions(+) create mode 100644 momepy/strokegraph_clse.ipynb diff --git a/momepy/strokegraph_clse.ipynb b/momepy/strokegraph_clse.ipynb new file mode 100644 index 00000000..3a39c4d1 --- /dev/null +++ b/momepy/strokegraph_clse.ipynb @@ -0,0 +1,868 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Playground for strokes graph" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [], + "source": [ + "import geopandas as gpd\n", + "import matplotlib.pyplot as plt\n", + "import momepy\n", + "import networkx as nx\n", + "import folium\n", + "from itertools import combinations\n", + "from collections import Counter\n", + "import shapely" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [], + "source": [ + "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [], + "source": [ + "# Clean data\n", + "streets = momepy.remove_false_nodes(streets)\n", + "# Add fixed ID to each edge\n", + "streets[\"id\"] = streets.index\n", + "# Transform into primal graph\n", + "G_primal = momepy.gdf_to_nx(streets, approach=\"primal\")\n", + "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)\n", + "# Use COINS on primal graph edges\n", + "coins = momepy.COINS(lines_primal)\n", + "# List the stroke for each edge\n", + "stroke_attribute = coins.stroke_attribute()\n", + "# List each edge for each stroke\n", + "stroke_gdf = coins.stroke_gdf()\n", + "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", + "stroke_gdf[\"edge_ids\"] = stroke_gdf.stroke_id.apply(lambda x: list(lines_primal.iloc[stroke_attribute[stroke_attribute == x].index][\"id\"]))\n", + "# Dictionary mapping to each edge ID the edge index\n", + "d = {val:lines_primal[lines_primal[\"id\"] == val].index.values[0] for val in lines_primal[\"id\"]}\n", + "# Add stroke ID to each edge\n", + "nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[d[G_primal.edges[e][\"id\"]]]) for e in G_primal.edges}, \"stroke_id\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [], + "source": [ + "# m = stroke_gdf.explore(tiles=\"cartodb-positron\", column=\"stroke_id\", cmap=\"tab10\", name=\"strokes\")\n", + "# lines_primal.explore(m=m, column=\"id\", name = \"lines\", cmap=\"viridis\")\n", + "# folium.LayerControl().add_to(m)\n", + "# m" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [], + "source": [ + "# points, lines = momepy.nx_to_gdf(G_primal, points=True, lines=True)\n", + "# m = stroke_gdf.explore(tiles=\"cartodb-positron\", column=\"stroke_id\", cmap=\"Set2\", name=\"strokes\")\n", + "# lines.explore(m=m, column=\"stroke_id\", name = \"lines\", cmap=\"Set2\")\n", + "# folium.LayerControl().add_to(m)\n", + "# m" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "G_dual = nx.Graph()\n", + "G_dual.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", + "# Create a node for each stroke with the right features\n", + "G_dual.add_nodes_from([[val, {attr:(list(stroke_gdf[stroke_gdf[\"stroke_id\"] == val][attr])[0] if attr != \"geometry\" else stroke_gdf[stroke_gdf[\"stroke_id\"] == val].geometry[val]) for attr in list(stroke_gdf)}] for val in list(stroke_gdf[\"stroke_id\"])])\n", + "# For all node, put its geometry at the center of the LineString\n", + "for n in G_dual.nodes:\n", + " G_dual.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", + " G_dual.nodes[n][\"x\"] = G_dual.nodes[n][\"geometry\"].xy[0]\n", + " G_dual.nodes[n][\"y\"] = G_dual.nodes[n][\"geometry\"].xy[1]\n", + "# Add an edge between the strokes that are intersectin in at least one node from the primal graph\n", + "for n in G_primal.nodes:\n", + " # Check the number of strokes at the node\n", + " strokes_present = [v for _, _, v in G_primal.edges(n, data=\"stroke_id\", keys=False)]\n", + " if len(set(strokes_present)) > 1:\n", + " # If more than one, check all the pairs of strokes possible\n", + " pairs = list(combinations(set(strokes_present), 2))\n", + " for p in pairs:\n", + " # Count the occurences of the strokes\n", + " strokes_counting = [i for i in strokes_present if i in p]\n", + " # If there is no edge between the strokes, add one\n", + " if not G_dual.has_edge(p[0], p[1]):\n", + " G_dual.add_edge(p[0], p[1], geometry=shapely.LineString([G_dual.nodes[p[0]][\"geometry\"], G_dual.nodes[p[1]][\"geometry\"]]), counter=Counter(strokes_counting))\n", + " else:\n", + " G_dual.edges[p[0], p[1]][\"counter\"].update(strokes_counting)" + ] + }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_72363/343906018.py:1: UserWarning: Approach is not set. Defaulting to 'primal'.\n", + " points_dual, lines_dual = momepy.nx_to_gdf(G_dual, points=True, lines=True)\n" + ] + }, + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 130, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "points_dual, lines_dual = momepy.nx_to_gdf(G_dual, points=True, lines=True)\n", + "m = stroke_gdf.explore(tiles=\"cartodb-positron\", column=\"stroke_id\", cmap=\"tab10\", name=\"strokes\")\n", + "points_primal.explore(m=m, name=\"points_primal\")\n", + "lines_primal.explore(m=m, name=\"lines_primal\")\n", + "points_dual.explore(m=m, color=\"black\", marker_kwds={\"radius\":10}, name=\"points_dual\")\n", + "lines_dual.explore(m=m, color=\"blue\", name=\"lines_dual\")\n", + "folium.LayerControl().add_to(m)\n", + "m" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "momepy_dev", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.10" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From de362e4ee61fbaf082bdff1d987d66454e42a13d Mon Sep 17 00:00:00 2001 From: anvy Date: Mon, 14 Apr 2025 15:27:51 +0200 Subject: [PATCH 04/27] update workflow input>stroke_graph --- momepy/strokegraph.ipynb | 1486 +++++++++++++++++++++++++++++++++++++- 1 file changed, 1464 insertions(+), 22 deletions(-) diff --git a/momepy/strokegraph.ipynb b/momepy/strokegraph.ipynb index 9d53a20d..67f0e300 100644 --- a/momepy/strokegraph.ipynb +++ b/momepy/strokegraph.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -18,7 +18,9 @@ "import matplotlib.pyplot as plt\n", "import momepy\n", "import networkx as nx\n", - "import folium" + "import folium\n", + "from itertools import combinations\n", + "from shapely import LineString" ] }, { @@ -30,14 +32,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "# read in toy graph (Bubenec)\n", "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", - "streets = momepy.remove_false_nodes(streets)\n", - "# streets[\"id\"] = streets.index\n", "\n", "# ax = streets.plot(figsize=(8, 8), column=\"id\", cmap = \"Accent\")\n", "# ax.set_axis_off()\n", @@ -61,7 +61,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -72,9 +72,113 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
n_segmentsgeometryrep_pointstroke_idedge_ids
stroke_group
08LINESTRING (1603278.899 6463669.186, 1603283.7...POINT (1603374.663 6464077.898)0[0, 3, 15, 27]
117LINESTRING (1603537.194 6464558.112, 1603557.6...POINT (1603707.107 6464238.854)1[11, 28, 2, 30]
25LINESTRING (1603413.206 6464228.73, 1603274.45...POINT (1603149.929 6464130.225)2[4, 5, 6]
35LINESTRING (1603287.304 6464587.705, 1603286.8...POINT (1603342.343 6464406.368)3[26]
419LINESTRING (1603077.5 6464475.323, 1603085.515...POINT (1603237.049 6464133.622)4[1, 12, 14, 25]
\n", + "
" + ], + "text/plain": [ + " n_segments geometry \\\n", + "stroke_group \n", + "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", + "1 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", + "2 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", + "3 5 LINESTRING (1603287.304 6464587.705, 1603286.8... \n", + "4 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", + "\n", + " rep_point stroke_id edge_ids \n", + "stroke_group \n", + "0 POINT (1603374.663 6464077.898) 0 [0, 3, 15, 27] \n", + "1 POINT (1603707.107 6464238.854) 1 [11, 28, 2, 30] \n", + "2 POINT (1603149.929 6464130.225) 2 [4, 5, 6] \n", + "3 POINT (1603342.343 6464406.368) 3 [26] \n", + "4 POINT (1603237.049 6464133.622) 4 [1, 12, 14, 25] " + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# remove false nodes\n", "streets = momepy.remove_false_nodes(streets)\n", @@ -94,6 +198,7 @@ "# get gdfs from COINS class\n", "stroke_attribute = coins.stroke_attribute()\n", "stroke_gdf = coins.stroke_gdf()\n", + "stroke_gdf[\"rep_point\"] = stroke_gdf.geometry.apply(lambda x: x.interpolate(0.5, normalized=True))\n", "\n", "# add stroke_id column\n", "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", @@ -111,9 +216,112 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{0: ((1603585.6402153103, 6464428.773867372),\n", + " (1603413.2063240695, 6464228.730248732),\n", + " 0),\n", + " 11: ((1603585.6402153103, 6464428.773867372),\n", + " (1603650.450422848, 6464368.600601688),\n", + " 0),\n", + " 28: ((1603585.6402153103, 6464428.773867372),\n", + " (1603537.1939729159, 6464558.11228298),\n", + " 0),\n", + " 2: ((1603413.2063240695, 6464228.730248732),\n", + " (1603607.3029882177, 6464181.852772597),\n", + " 0),\n", + " 3: ((1603413.2063240695, 6464228.730248732),\n", + " (1603363.557831175, 6464031.88480676),\n", + " 0),\n", + " 4: ((1603413.2063240695, 6464228.730248732),\n", + " (1603226.9576840235, 6464160.158361825),\n", + " 0),\n", + " 26: ((1603413.2063240695, 6464228.730248732),\n", + " (1603287.303979983, 6464587.704889874),\n", + " 0),\n", + " 1: ((1603268.502117987, 6464060.781328565),\n", + " (1603363.557831175, 6464031.88480676),\n", + " 0),\n", + " 12: ((1603268.502117987, 6464060.781328565),\n", + " (1603226.9576840235, 6464160.158361825),\n", + " 0),\n", + " 20: ((1603268.502117987, 6464060.781328565),\n", + " (1603146.6963311615, 6463924.630126579),\n", + " 0),\n", + " 14: ((1603363.557831175, 6464031.88480676),\n", + " (1603558.489391506, 6463985.80677705),\n", + " 0),\n", + " 15: ((1603363.557831175, 6464031.88480676),\n", + " (1603317.7832565615, 6463836.796863219),\n", + " 0),\n", + " 16: ((1603607.3029882177, 6464181.852772597),\n", + " (1603650.450422848, 6464368.600601688),\n", + " 0),\n", + " 30: ((1603607.3029882177, 6464181.852772597),\n", + " (1603650.450422848, 6464368.600601688),\n", + " 1),\n", + " 17: ((1603607.3029882177, 6464181.852772597),\n", + " (1603558.489391506, 6463985.80677705),\n", + " 0),\n", + " 5: ((1603226.9576840235, 6464160.158361825),\n", + " (1603039.9632033885, 6464087.491175889),\n", + " 0),\n", + " 25: ((1603226.9576840235, 6464160.158361825),\n", + " (1603077.5001356844, 6464475.322968743),\n", + " 0),\n", + " 6: ((1603039.9632033885, 6464087.491175889),\n", + " (1602887.2996537155, 6464029.975730775),\n", + " 0),\n", + " 7: ((1603039.9632033885, 6464087.491175889),\n", + " (1602970.3773896934, 6464268.058242684),\n", + " 0),\n", + " 8: ((1603039.9632033885, 6464087.491175889),\n", + " (1603090.513384159, 6463971.106984773),\n", + " 0),\n", + " 19: ((1603090.513384159, 6463971.106984773),\n", + " (1602959.8799617135, 6463839.712475327),\n", + " 0),\n", + " 21: ((1603090.513384159, 6463971.106984773),\n", + " (1603146.6963311615, 6463924.630126579),\n", + " 0),\n", + " 9: ((1603317.7832565615, 6463836.796863219),\n", + " (1603202.3783404578, 6463872.287568242),\n", + " 0),\n", + " 24: ((1603317.7832565615, 6463836.796863219),\n", + " (1603513.6499006122, 6463789.557147608),\n", + " 0),\n", + " 27: ((1603317.7832565615, 6463836.796863219),\n", + " (1603278.8993584276, 6463669.185595578),\n", + " 0),\n", + " 10: ((1603202.3783404578, 6463872.287568242),\n", + " (1603071.956425043, 6463729.978565),\n", + " 0),\n", + " 22: ((1603202.3783404578, 6463872.287568242),\n", + " (1603146.6963311615, 6463924.630126579),\n", + " 0),\n", + " 29: ((1603650.450422848, 6464368.600601688),\n", + " (1603706.3884669733, 6464617.783583014),\n", + " 0),\n", + " 13: ((1603513.6499006122, 6463789.557147608),\n", + " (1603795.889337571, 6463785.444077063),\n", + " 0),\n", + " 18: ((1603513.6499006122, 6463789.557147608),\n", + " (1603558.489391506, 6463985.80677705),\n", + " 0),\n", + " 23: ((1603513.6499006122, 6463789.557147608),\n", + " (1603473.6416756227, 6463625.487127112),\n", + " 0)}" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# make dictionary for primal graph, edge_id:edge_name\n", "d = nx.get_edge_attributes(graph, \"edge_id\")\n", @@ -123,7 +331,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -135,7 +343,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -145,31 +353,508 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ - "edges_strokes = {d_edges[k]:d_strokes[k] for k in d_edges} \n", - "edges_strokes" + "edges_strokes = {d_edges[k]:d_strokes[k] for k in d_edges} " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Set2\")\n", - "# lines.explore(m=m, column = \"id\", name = \"lines\")\n", - "# folium.LayerControl().add_to(m)\n", - "# m" + "m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Reds\", style_kwds={\"weight\":8})\n", + "lines.explore(m=m, column = \"edge_id\", name = \"lines\", cmap = \"Blues\", style_kwds={\"weight\":8})\n", + "folium.LayerControl().add_to(m)\n", + "m" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "***" + "* Now we have a primal graph `graph` where each edge has the attributes `edge_id` and `stroke_id`\n", + "* We have this information also in `stroke_gdf`\n", + "* Each stroke (each line in stroke_gdf) will be a node of the stroke graph" ] }, { @@ -179,6 +864,763 @@ "outputs": [], "source": [] }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "NodeDataView({0: {'edge_ids': [0, 3, 15, 27], 'geometry': , 'x': 1603374.6625343116, 'y': 6464077.898491419}, 1: {'edge_ids': [11, 28, 2, 30], 'geometry': , 'x': 1603707.1065106073, 'y': 6464238.853991265}, 2: {'edge_ids': [4, 5, 6], 'geometry': , 'x': 1603149.9288811635, 'y': 6464130.224503239}, 3: {'edge_ids': [26], 'geometry': , 'x': 1603342.3426854417, 'y': 6464406.368225728}, 4: {'edge_ids': [1, 12, 14, 25], 'geometry': , 'x': 1603237.0487682838, 'y': 6464133.622486805}, 5: {'edge_ids': [20], 'geometry': , 'x': 1603207.5969886228, 'y': 6463992.707728057}, 6: {'edge_ids': [16, 17, 29, 18, 23], 'geometry': , 'x': 1603592.2349246691, 'y': 6464121.336160048}, 7: {'edge_ids': [7, 8, 21, 9, 24, 22, 13], 'geometry': , 'x': 1603264.6577362637, 'y': 6463848.97596353}, 8: {'edge_ids': [19], 'geometry': , 'x': 1603028.737187382, 'y': 6463900.594576759}, 9: {'edge_ids': [10], 'geometry': , 'x': 1603137.4077031056, 'y': 6463800.908382258}})" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stroke_graph = nx.Graph()\n", + "stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", + "stroke_graph.graph[\"approach\"] = graph.graph[\"approach\"]\n", + "stroke_graph.add_nodes_from(\n", + " [\n", + " (\n", + " row.stroke_id, \n", + " {\n", + " \"edge_ids\": row.edge_ids,\n", + " \"geometry\": row.rep_point,\n", + " \"x\": row.rep_point.xy[0][0],\n", + " \"y\": row.rep_point.xy[1][0],\n", + " }\n", + " ) for _, row in stroke_gdf.iterrows()\n", + " ]\n", + ")\n", + "# node names are the stroke IDs.\n", + "# each node has the attribute \"edge_ids\".\n", + "stroke_graph.nodes(data=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "to find the edges of the stroke graph, we look at the primal graph's nodes and the stroke_ids of their adjacent edges" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1603585.6402153103, 6464428.773867372)\n", + "[0, 1, 1] {0, 1}\n", + "(0, 1)\n", + "\n", + "\n", + "(1603413.2063240695, 6464228.730248732)\n", + "[0, 1, 0, 2, 3] {0, 1, 2, 3}\n", + "(0, 1)\n", + "(0, 1) already in graph!\n", + "(0, 2)\n", + "(0, 3)\n", + "(1, 2)\n", + "(1, 3)\n", + "(2, 3)\n", + "\n", + "\n", + "(1603268.502117987, 6464060.781328565)\n", + "[4, 4, 5] {4, 5}\n", + "(4, 5)\n", + "\n", + "\n", + "(1603363.557831175, 6464031.88480676)\n", + "[4, 0, 4, 0] {0, 4}\n", + "(0, 4)\n", + "\n", + "\n", + "(1603607.3029882177, 6464181.852772597)\n", + "[1, 6, 1, 6] {1, 6}\n", + "(1, 6)\n", + "\n", + "\n", + "(1603226.9576840235, 6464160.158361825)\n", + "[2, 2, 4, 4] {2, 4}\n", + "(2, 4)\n", + "\n", + "\n", + "(1603039.9632033885, 6464087.491175889)\n", + "[2, 2, 7, 7] {2, 7}\n", + "(2, 7)\n", + "\n", + "\n", + "(1602887.2996537155, 6464029.975730775)\n", + "[2] {2}\n", + "\n", + "\n", + "(1602970.3773896934, 6464268.058242684)\n", + "[7] {7}\n", + "\n", + "\n", + "(1603090.513384159, 6463971.106984773)\n", + "[7, 8, 7] {8, 7}\n", + "(8, 7)\n", + "\n", + "\n", + "(1603317.7832565615, 6463836.796863219)\n", + "[7, 0, 7, 0] {0, 7}\n", + "(0, 7)\n", + "\n", + "\n", + "(1603202.3783404578, 6463872.287568242)\n", + "[7, 9, 7] {9, 7}\n", + "(9, 7)\n", + "\n", + "\n", + "(1603071.956425043, 6463729.978565)\n", + "[9] {9}\n", + "\n", + "\n", + "(1603650.450422848, 6464368.600601688)\n", + "[1, 6, 1, 6] {1, 6}\n", + "(1, 6)\n", + "(1, 6) already in graph!\n", + "\n", + "\n", + "(1603513.6499006122, 6463789.557147608)\n", + "[7, 6, 6, 7] {6, 7}\n", + "(6, 7)\n", + "\n", + "\n", + "(1603795.889337571, 6463785.444077063)\n", + "[7] {7}\n", + "\n", + "\n", + "(1603558.489391506, 6463985.80677705)\n", + "[4, 6, 6] {4, 6}\n", + "(4, 6)\n", + "\n", + "\n", + "(1602959.8799617135, 6463839.712475327)\n", + "[8] {8}\n", + "\n", + "\n", + "(1603146.6963311615, 6463924.630126579)\n", + "[5, 7, 7] {5, 7}\n", + "(5, 7)\n", + "\n", + "\n", + "(1603473.6416756227, 6463625.487127112)\n", + "[6] {6}\n", + "\n", + "\n", + "(1603077.5001356844, 6464475.322968743)\n", + "[4] {4}\n", + "\n", + "\n", + "(1603287.303979983, 6464587.704889874)\n", + "[3] {3}\n", + "\n", + "\n", + "(1603278.8993584276, 6463669.185595578)\n", + "[0] {0}\n", + "\n", + "\n", + "(1603537.1939729159, 6464558.11228298)\n", + "[1] {1}\n", + "\n", + "\n", + "(1603706.3884669733, 6464617.783583014)\n", + "[6] {6}\n", + "\n", + "\n" + ] + } + ], + "source": [ + "for n in graph.nodes:\n", + " print(n)\n", + " es = list(graph.edges(n, keys=True))\n", + " stroke_list = [graph.edges[e][\"stroke_id\"] for e in es]\n", + " stroke_set = set(stroke_list)\n", + " print(stroke_list, stroke_set)\n", + " # for all size2 combinations from stroke_set\n", + " for c in combinations(stroke_set, 2):\n", + " print(c)\n", + " continuities = {}\n", + " for s in c:\n", + " continuities[s] = stroke_list.count(s)\n", + " if c not in stroke_graph.edges:\n", + " edge_geom = LineString(\n", + " [\n", + " stroke_graph.nodes[c[0]][\"geometry\"],\n", + " stroke_graph.nodes[c[1]][\"geometry\"]\n", + " ]\n", + " )\n", + " stroke_graph.add_edge(c[0], c[1], continuities=continuities, geometry=edge_geom)\n", + " else:\n", + " for s in c:\n", + " stroke_graph.edges[c][\"continuities\"][s] += continuities[s]\n", + " print(c, \"already in graph!\")\n", + " print(\"\\n\")\n", + "# we want to add edges for all stroke IDs that co-occur on edges that share the same node in the primal graph\n", + "# [0, 1, 1] means: stroke0 has an endpoint here; stroke1 has a throughpoint here; we add the edge [0,1] in the strokes_graph, with the attribute \n", + "# stroke = {0: \"end\", 1: \"through\"}\n", + "\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "EdgeDataView([(0, 1, {'continuities': {0: 3, 1: 3}, 'geometry': }), (0, 2, {'continuities': {0: 2, 2: 1}, 'geometry': }), (0, 3, {'continuities': {0: 2, 3: 1}, 'geometry': }), (0, 4, {'continuities': {0: 2, 4: 2}, 'geometry': }), (0, 7, {'continuities': {0: 2, 7: 2}, 'geometry': }), (1, 2, {'continuities': {1: 1, 2: 1}, 'geometry': }), (1, 3, {'continuities': {1: 1, 3: 1}, 'geometry': }), (1, 6, {'continuities': {1: 4, 6: 4}, 'geometry': }), (2, 3, {'continuities': {2: 1, 3: 1}, 'geometry': }), (2, 4, {'continuities': {2: 2, 4: 2}, 'geometry': }), (2, 7, {'continuities': {2: 2, 7: 2}, 'geometry': }), (4, 5, {'continuities': {4: 2, 5: 1}, 'geometry': }), (4, 6, {'continuities': {4: 1, 6: 2}, 'geometry': }), (5, 7, {'continuities': {5: 1, 7: 2}, 'geometry': }), (6, 7, {'continuities': {6: 2, 7: 2}, 'geometry': }), (7, 8, {'continuities': {8: 1, 7: 2}, 'geometry': }), (7, 9, {'continuities': {9: 1, 7: 2}, 'geometry': })])" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stroke_graph.edges(data=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "# get gdfs of points and lines\n", + "points_strokes, lines_strokes = momepy.nx_to_gdf(stroke_graph, points=True, lines=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "lines_strokes[\"random_id\"] = lines_strokes.index" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "10" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(stroke_gdf)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[(0, 1, {'continuities': {0: 3, 1: 3}, 'geometry': }), (0, 2, {'continuities': {0: 2, 2: 1}, 'geometry': }), (0, 3, {'continuities': {0: 2, 3: 1}, 'geometry': }), (0, 4, {'continuities': {0: 2, 4: 2}, 'geometry': }), (0, 7, {'continuities': {0: 2, 7: 2}, 'geometry': }), (1, 2, {'continuities': {1: 1, 2: 1}, 'geometry': }), (1, 3, {'continuities': {1: 1, 3: 1}, 'geometry': }), (1, 6, {'continuities': {1: 4, 6: 4}, 'geometry': }), (2, 3, {'continuities': {2: 1, 3: 1}, 'geometry': }), (2, 4, {'continuities': {2: 2, 4: 2}, 'geometry': }), (2, 7, {'continuities': {2: 2, 7: 2}, 'geometry': }), (4, 5, {'continuities': {4: 2, 5: 1}, 'geometry': }), (4, 6, {'continuities': {4: 1, 6: 2}, 'geometry': }), (5, 7, {'continuities': {5: 1, 7: 2}, 'geometry': }), (6, 7, {'continuities': {6: 2, 7: 2}, 'geometry': }), (7, 8, {'continuities': {8: 1, 7: 2}, 'geometry': }), (7, 9, {'continuities': {9: 1, 7: 2}, 'geometry': })]\n" + ] + }, + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(stroke_graph.edges(data=True))\n", + "m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"tab20c\", style_kwds={\"weight\":8})\n", + "lines_strokes.explore(m=m, \n", + " #column = \"random_id\", \n", + " name = \"stroke_lines\", \n", + " #cmap = \"Blues\", \n", + " style_kwds={\"weight\":8})\n", + "points_strokes.explore(m=m, marker_kwds={\"radius\":20}, name =\"stroke nodes\", color = \"orange\", opacity=0.2)\n", + "folium.LayerControl().add_to(m)\n", + "m" + ] + }, { "cell_type": "code", "execution_count": null, From cc0442e503244bef2c731cab4dc7a27d08f623d8 Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Mon, 14 Apr 2025 18:07:03 +0200 Subject: [PATCH 05/27] Add angles, wrong angles for now --- momepy/strokegraph_clse.ipynb | 818 ++++------------------------------ 1 file changed, 89 insertions(+), 729 deletions(-) diff --git a/momepy/strokegraph_clse.ipynb b/momepy/strokegraph_clse.ipynb index 3a39c4d1..267ab7f0 100644 --- a/momepy/strokegraph_clse.ipynb +++ b/momepy/strokegraph_clse.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -54,14 +54,15 @@ "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", "stroke_gdf[\"edge_ids\"] = stroke_gdf.stroke_id.apply(lambda x: list(lines_primal.iloc[stroke_attribute[stroke_attribute == x].index][\"id\"]))\n", "# Dictionary mapping to each edge ID the edge index\n", - "d = {val:lines_primal[lines_primal[\"id\"] == val].index.values[0] for val in lines_primal[\"id\"]}\n", + "d_lines_primal_id2idx = {val:list(lines_primal[lines_primal[\"id\"] == val].index)[0] for val in lines_primal[\"id\"]}\n", "# Add stroke ID to each edge\n", - "nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[d[G_primal.edges[e][\"id\"]]]) for e in G_primal.edges}, \"stroke_id\")\n" + "nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[d_lines_primal_id2idx[G_primal.edges[e][\"id\"]]]) for e in G_primal.edges}, \"stroke_id\")\n", + "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)\n" ] }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -73,765 +74,124 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ - "# points, lines = momepy.nx_to_gdf(G_primal, points=True, lines=True)\n", "# m = stroke_gdf.explore(tiles=\"cartodb-positron\", column=\"stroke_id\", cmap=\"Set2\", name=\"strokes\")\n", "# lines.explore(m=m, column=\"stroke_id\", name = \"lines\", cmap=\"Set2\")\n", "# folium.LayerControl().add_to(m)\n", "# m" ] }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "G_dual = momepy.gdf_to_nx(lines_primal, approach=\"dual\", angles=True)\n", + "d_nodes_dual_id2idx = {G_dual.nodes[n][\"id\"]:n for n in G_dual.nodes}\n", + "d_lines_primal_idx2id = {v:k for k,v in d_lines_primal_id2idx.items()}\n", + "lines_primal[\"angles\"] = [[(G_dual.nodes[v][\"id\"], d[\"angle\"]) for _, v, d in G_dual.edges(d_nodes_dual_id2idx[d_lines_primal_idx2id[idx]], data=True)] for idx in list(lines_primal.index)]" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "angles_strokes_all = []\n", + "for idx in list(stroke_gdf.index):\n", + " array = list(lines_primal[lines_primal[\"id\"].isin(stroke_gdf.iloc[idx][\"edge_ids\"])][\"angles\"])\n", + " flat_array = []\n", + " for arr in array:\n", + " for val in arr:\n", + " flat_array.append(val)\n", + " angles_strokes_singular = {}\n", + " for val in flat_array:\n", + " stroke_id = int(lines_primal.iloc[d_lines_primal_id2idx[val[0]]][\"stroke_id\"])\n", + " if stroke_id == idx:\n", + " pass\n", + " elif stroke_id not in angles_strokes_singular:\n", + " angles_strokes_singular[stroke_id] = [val[1]]\n", + " else:\n", + " angles_strokes_singular[stroke_id].append(val[1])\n", + " angles_strokes_all.append(angles_strokes_singular)\n", + "stroke_gdf[\"angles_with_strokes\"] = angles_strokes_all" + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "G_dual = nx.Graph()\n", - "G_dual.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", + "G_stroke = nx.Graph()\n", + "G_stroke.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", "# Create a node for each stroke with the right features\n", - "G_dual.add_nodes_from([[val, {attr:(list(stroke_gdf[stroke_gdf[\"stroke_id\"] == val][attr])[0] if attr != \"geometry\" else stroke_gdf[stroke_gdf[\"stroke_id\"] == val].geometry[val]) for attr in list(stroke_gdf)}] for val in list(stroke_gdf[\"stroke_id\"])])\n", + "G_stroke.add_nodes_from([[val, {attr:(list(stroke_gdf[stroke_gdf[\"stroke_id\"] == val][attr])[0] if attr != \"geometry\" else stroke_gdf[stroke_gdf[\"stroke_id\"] == val].geometry[val]) for attr in list(stroke_gdf)}] for val in list(stroke_gdf[\"stroke_id\"])])\n", "# For all node, put its geometry at the center of the LineString\n", - "for n in G_dual.nodes:\n", - " G_dual.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", - " G_dual.nodes[n][\"x\"] = G_dual.nodes[n][\"geometry\"].xy[0]\n", - " G_dual.nodes[n][\"y\"] = G_dual.nodes[n][\"geometry\"].xy[1]\n", - "# Add an edge between the strokes that are intersectin in at least one node from the primal graph\n", - "for n in G_primal.nodes:\n", - " # Check the number of strokes at the node\n", - " strokes_present = [v for _, _, v in G_primal.edges(n, data=\"stroke_id\", keys=False)]\n", - " if len(set(strokes_present)) > 1:\n", - " # If more than one, check all the pairs of strokes possible\n", - " pairs = list(combinations(set(strokes_present), 2))\n", - " for p in pairs:\n", - " # Count the occurences of the strokes\n", - " strokes_counting = [i for i in strokes_present if i in p]\n", - " # If there is no edge between the strokes, add one\n", - " if not G_dual.has_edge(p[0], p[1]):\n", - " G_dual.add_edge(p[0], p[1], geometry=shapely.LineString([G_dual.nodes[p[0]][\"geometry\"], G_dual.nodes[p[1]][\"geometry\"]]), counter=Counter(strokes_counting))\n", - " else:\n", - " G_dual.edges[p[0], p[1]][\"counter\"].update(strokes_counting)" + "for n in G_stroke.nodes:\n", + " G_stroke.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", + " G_stroke.nodes[n][\"x\"] = G_stroke.nodes[n][\"geometry\"].xy[0]\n", + " G_stroke.nodes[n][\"y\"] = G_stroke.nodes[n][\"geometry\"].xy[1]\n", + "for n in G_stroke.nodes:\n", + " for k in stroke_gdf.iloc[n][\"angles_with_strokes\"]:\n", + " G_stroke.add_edge(n, k, geometry = shapely.LineString(counting = sum(stroke_gdf.iloc[n][\"angles_with_strokes\"][k]), angles = stroke_gdf.iloc[n][\"angles_with_strokes\"][k])" ] }, { "cell_type": "code", - "execution_count": 130, + "execution_count": 68, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_72363/343906018.py:1: UserWarning: Approach is not set. Defaulting to 'primal'.\n", - " points_dual, lines_dual = momepy.nx_to_gdf(G_dual, points=True, lines=True)\n" + "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_8655/1971550804.py:1: UserWarning: Approach is not set. Defaulting to 'primal'.\n", + " points_stroke, lines_stroke = momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n" ] }, { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 130, - "metadata": {}, - "output_type": "execute_result" + "ename": "ValueError", + "evalue": "Assigning CRS to a GeoDataFrame without a geometry column is not supported. Use GeoDataFrame.set_geometry to set the active geometry column.", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:517\u001b[39m, in \u001b[36mGeoDataFrame.crs\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 516\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m517\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mgeometry\u001b[49m.crs\n\u001b[32m 518\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/pandas/core/generic.py:6299\u001b[39m, in \u001b[36mNDFrame.__getattr__\u001b[39m\u001b[34m(self, name)\u001b[39m\n\u001b[32m 6298\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[name]\n\u001b[32m-> \u001b[39m\u001b[32m6299\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mobject\u001b[39;49m\u001b[43m.\u001b[49m\u001b[34;43m__getattribute__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:253\u001b[39m, in \u001b[36mGeoDataFrame._get_geometry\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 247\u001b[39m msg += (\n\u001b[32m 248\u001b[39m \u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mThere are no existing columns with geometry data type. You can \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 249\u001b[39m \u001b[33m\"\u001b[39m\u001b[33madd a geometry column as the active geometry column with \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 250\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mdf.set_geometry. \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 251\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m253\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(msg)\n\u001b[32m 254\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[\u001b[38;5;28mself\u001b[39m._geometry_column_name]\n", + "\u001b[31mAttributeError\u001b[39m: You are calling a geospatial method on the GeoDataFrame, but the active geometry column to use has not been set. \nThere are no existing columns with geometry data type. You can add a geometry column as the active geometry column with df.set_geometry. ", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/pandas/core/generic.py:6325\u001b[39m, in \u001b[36mNDFrame.__setattr__\u001b[39m\u001b[34m(self, name, value)\u001b[39m\n\u001b[32m 6324\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m6325\u001b[39m existing = \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 6326\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(existing, Index):\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/pandas/core/generic.py:6299\u001b[39m, in \u001b[36mNDFrame.__getattr__\u001b[39m\u001b[34m(self, name)\u001b[39m\n\u001b[32m 6298\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[name]\n\u001b[32m-> \u001b[39m\u001b[32m6299\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mobject\u001b[39;49m\u001b[43m.\u001b[49m\u001b[34;43m__getattribute__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:519\u001b[39m, in \u001b[36mGeoDataFrame.crs\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 518\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m519\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\n\u001b[32m 520\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mThe CRS attribute of a GeoDataFrame without an active \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 521\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mgeometry column is not defined. Use GeoDataFrame.set_geometry \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 522\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mto set the active geometry column.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 523\u001b[39m )\n", + "\u001b[31mAttributeError\u001b[39m: The CRS attribute of a GeoDataFrame without an active geometry column is not defined. Use GeoDataFrame.set_geometry to set the active geometry column.", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[31mValueError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[68]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m points_stroke, lines_stroke = \u001b[43mmomepy\u001b[49m\u001b[43m.\u001b[49m\u001b[43mnx_to_gdf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mG_stroke\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpoints\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlines\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[32m 2\u001b[39m m = stroke_gdf.explore(tiles=\u001b[33m\"\u001b[39m\u001b[33mcartodb-positron\u001b[39m\u001b[33m\"\u001b[39m, column=\u001b[33m\"\u001b[39m\u001b[33mstroke_id\u001b[39m\u001b[33m\"\u001b[39m, cmap=\u001b[33m\"\u001b[39m\u001b[33mtab10\u001b[39m\u001b[33m\"\u001b[39m, name=\u001b[33m\"\u001b[39m\u001b[33mstrokes\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 3\u001b[39m points_primal.explore(m=m, name=\u001b[33m\"\u001b[39m\u001b[33mpoints_primal\u001b[39m\u001b[33m\"\u001b[39m)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Desktop/PhD/Code/momepy/momepy/utils.py:569\u001b[39m, in \u001b[36mnx_to_gdf\u001b[39m\u001b[34m(net, points, lines, spatial_weights, nodeID)\u001b[39m\n\u001b[32m 566\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m nid, n \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(net):\n\u001b[32m 567\u001b[39m net.nodes[n][nodeID] = nid\n\u001b[32m--> \u001b[39m\u001b[32m569\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_primal_to_gdf\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 570\u001b[39m \u001b[43m \u001b[49m\u001b[43mnet\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 571\u001b[39m \u001b[43m \u001b[49m\u001b[43mpoints\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpoints\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 572\u001b[39m \u001b[43m \u001b[49m\u001b[43mlines\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlines\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 573\u001b[39m \u001b[43m \u001b[49m\u001b[43mspatial_weights\u001b[49m\u001b[43m=\u001b[49m\u001b[43mspatial_weights\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 574\u001b[39m \u001b[43m \u001b[49m\u001b[43mnode_id\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnodeID\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 575\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Desktop/PhD/Code/momepy/momepy/utils.py:441\u001b[39m, in \u001b[36m_primal_to_gdf\u001b[39m\u001b[34m(net, points, lines, spatial_weights, node_id)\u001b[39m\n\u001b[32m 438\u001b[39m weights.transform = \u001b[33m\"\u001b[39m\u001b[33mb\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 440\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m lines \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m441\u001b[39m gdf_edges = \u001b[43m_lines_to_gdf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnet\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpoints\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnode_id\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 443\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m points \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m lines \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[32m 444\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m spatial_weights \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Desktop/PhD/Code/momepy/momepy/utils.py:417\u001b[39m, in \u001b[36m_lines_to_gdf\u001b[39m\u001b[34m(net, points, node_id)\u001b[39m\n\u001b[32m 414\u001b[39m gdf_edges[\u001b[33m\"\u001b[39m\u001b[33mnode_end\u001b[39m\u001b[33m\"\u001b[39m] = [net.nodes[e][node_id] \u001b[38;5;28;01mfor\u001b[39;00m e \u001b[38;5;129;01min\u001b[39;00m ends]\n\u001b[32m 416\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33mcrs\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m net.graph:\n\u001b[32m--> \u001b[39m\u001b[32m417\u001b[39m \u001b[43mgdf_edges\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcrs\u001b[49m = net.graph[\u001b[33m\"\u001b[39m\u001b[33mcrs\u001b[39m\u001b[33m\"\u001b[39m]\n\u001b[32m 418\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33mindex_position\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m gdf_edges.columns:\n\u001b[32m 419\u001b[39m gdf_edges = gdf_edges.sort_values(\u001b[33m\"\u001b[39m\u001b[33mindex_position\u001b[39m\u001b[33m\"\u001b[39m).drop(\n\u001b[32m 420\u001b[39m columns=\u001b[33m\"\u001b[39m\u001b[33mindex_position\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 421\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:223\u001b[39m, in \u001b[36mGeoDataFrame.__setattr__\u001b[39m\u001b[34m(self, attr, val)\u001b[39m\n\u001b[32m 221\u001b[39m \u001b[38;5;28mobject\u001b[39m.\u001b[34m__setattr__\u001b[39m(\u001b[38;5;28mself\u001b[39m, attr, val)\n\u001b[32m 222\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m223\u001b[39m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[34;43m__setattr__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mattr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mval\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/pandas/core/generic.py:6341\u001b[39m, in \u001b[36mNDFrame.__setattr__\u001b[39m\u001b[34m(self, name, value)\u001b[39m\n\u001b[32m 6333\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m, ABCDataFrame) \u001b[38;5;129;01mand\u001b[39;00m (is_list_like(value)):\n\u001b[32m 6334\u001b[39m warnings.warn(\n\u001b[32m 6335\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mPandas doesn\u001b[39m\u001b[33m'\u001b[39m\u001b[33mt allow columns to be \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 6336\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mcreated via a new attribute name - see \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m (...)\u001b[39m\u001b[32m 6339\u001b[39m stacklevel=find_stack_level(),\n\u001b[32m 6340\u001b[39m )\n\u001b[32m-> \u001b[39m\u001b[32m6341\u001b[39m \u001b[38;5;28;43mobject\u001b[39;49m\u001b[43m.\u001b[49m\u001b[34;43m__setattr__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:529\u001b[39m, in \u001b[36mGeoDataFrame.crs\u001b[39m\u001b[34m(self, value)\u001b[39m\n\u001b[32m 527\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"Sets the value of the crs\"\"\"\u001b[39;00m\n\u001b[32m 528\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._geometry_column_name \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m529\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m 530\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mAssigning CRS to a GeoDataFrame without a geometry column is not \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 531\u001b[39m \u001b[33m\"\u001b[39m\u001b[33msupported. Use GeoDataFrame.set_geometry to set the active \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 532\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mgeometry column.\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 533\u001b[39m )\n\u001b[32m 535\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m.geometry.values, \u001b[33m\"\u001b[39m\u001b[33mcrs\u001b[39m\u001b[33m\"\u001b[39m):\n\u001b[32m 536\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.crs \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "\u001b[31mValueError\u001b[39m: Assigning CRS to a GeoDataFrame without a geometry column is not supported. Use GeoDataFrame.set_geometry to set the active geometry column." + ] } ], "source": [ - "points_dual, lines_dual = momepy.nx_to_gdf(G_dual, points=True, lines=True)\n", + "points_stroke, lines_stroke = momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n", "m = stroke_gdf.explore(tiles=\"cartodb-positron\", column=\"stroke_id\", cmap=\"tab10\", name=\"strokes\")\n", "points_primal.explore(m=m, name=\"points_primal\")\n", "lines_primal.explore(m=m, name=\"lines_primal\")\n", - "points_dual.explore(m=m, color=\"black\", marker_kwds={\"radius\":10}, name=\"points_dual\")\n", - "lines_dual.explore(m=m, color=\"blue\", name=\"lines_dual\")\n", + "points_stroke.explore(m=m, color=\"black\", marker_kwds={\"radius\":10}, name=\"points_stroke\")\n", + "lines_stroke.explore(m=m, color=\"blue\", name=\"lines_stroke\")\n", "folium.LayerControl().add_to(m)\n", "m" ] From 0128adf8a2a4dfa57175680264f696d78aed8c22 Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Fri, 9 May 2025 17:55:08 +0200 Subject: [PATCH 06/27] remove useless indexing and create graph w attribute, angle still wrong --- momepy/strokegraph_clse.ipynb | 882 ++++++++++++++++++++++++++++++---- 1 file changed, 794 insertions(+), 88 deletions(-) diff --git a/momepy/strokegraph_clse.ipynb b/momepy/strokegraph_clse.ipynb index 267ab7f0..a9194610 100644 --- a/momepy/strokegraph_clse.ipynb +++ b/momepy/strokegraph_clse.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 165, "metadata": {}, "outputs": [], "source": [ @@ -18,14 +18,15 @@ "import momepy\n", "import networkx as nx\n", "import folium\n", - "from itertools import combinations\n", + "from itertools import combinations, product\n", "from collections import Counter\n", - "import shapely" + "import shapely\n", + "from momepy.utils import _angle" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 166, "metadata": {}, "outputs": [], "source": [ @@ -34,16 +35,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 167, "metadata": {}, "outputs": [], "source": [ "# Clean data\n", "streets = momepy.remove_false_nodes(streets)\n", - "# Add fixed ID to each edge\n", - "streets[\"id\"] = streets.index\n", "# Transform into primal graph\n", - "G_primal = momepy.gdf_to_nx(streets, approach=\"primal\")\n", + "G_primal = momepy.gdf_to_nx(streets, approach=\"primal\", preserve_index=True)\n", "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)\n", "# Use COINS on primal graph edges\n", "coins = momepy.COINS(lines_primal)\n", @@ -51,75 +50,67 @@ "stroke_attribute = coins.stroke_attribute()\n", "# List each edge for each stroke\n", "stroke_gdf = coins.stroke_gdf()\n", - "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", - "stroke_gdf[\"edge_ids\"] = stroke_gdf.stroke_id.apply(lambda x: list(lines_primal.iloc[stroke_attribute[stroke_attribute == x].index][\"id\"]))\n", - "# Dictionary mapping to each edge ID the edge index\n", - "d_lines_primal_id2idx = {val:list(lines_primal[lines_primal[\"id\"] == val].index)[0] for val in lines_primal[\"id\"]}\n", + "stroke_gdf[\"edge_ids\"] = [stroke_attribute[stroke_attribute == stroke_id].index.values for stroke_id in stroke_gdf.index.values]\n", "# Add stroke ID to each edge\n", - "nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[d_lines_primal_id2idx[G_primal.edges[e][\"id\"]]]) for e in G_primal.edges}, \"stroke_id\")\n", - "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)\n" + "nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[G_primal.edges[e][\"index_position\"]]) for e in G_primal.edges}, \"stroke_id\")\n", + "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 168, "metadata": {}, "outputs": [], "source": [ - "# m = stroke_gdf.explore(tiles=\"cartodb-positron\", column=\"stroke_id\", cmap=\"tab10\", name=\"strokes\")\n", - "# lines_primal.explore(m=m, column=\"id\", name = \"lines\", cmap=\"viridis\")\n", + "# stroke_gdf_viz = stroke_gdf.copy()\n", + "# stroke_gdf_viz[\"id\"] = stroke_gdf_viz.index\n", + "# lines_primal_viz = lines_primal.copy()\n", + "# lines_primal_viz[\"edge_id\"] = lines_primal.index\n", + "# m = stroke_gdf_viz.explore(tiles=\"cartodb-positron\", column=\"id\", cmap=\"Set2\", name=\"strokes\")\n", + "# lines_primal_viz.explore(m=m, column=\"stroke_id\", name = \"lines\", cmap=\"Set2\")\n", "# folium.LayerControl().add_to(m)\n", "# m" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 169, "metadata": {}, - "outputs": [], - "source": [ - "# m = stroke_gdf.explore(tiles=\"cartodb-positron\", column=\"stroke_id\", cmap=\"Set2\", name=\"strokes\")\n", - "# lines.explore(m=m, column=\"stroke_id\", name = \"lines\", cmap=\"Set2\")\n", - "# folium.LayerControl().add_to(m)\n", - "# m" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "n_segments 8\n", + "geometry LINESTRING (1603278.8993584276 6463669.1855955...\n", + "edge_ids [0, 3, 15, 27]\n", + "Name: 0, dtype: object" + ] + }, + "execution_count": 169, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "G_dual = momepy.gdf_to_nx(lines_primal, approach=\"dual\", angles=True)\n", - "d_nodes_dual_id2idx = {G_dual.nodes[n][\"id\"]:n for n in G_dual.nodes}\n", - "d_lines_primal_idx2id = {v:k for k,v in d_lines_primal_id2idx.items()}\n", - "lines_primal[\"angles\"] = [[(G_dual.nodes[v][\"id\"], d[\"angle\"]) for _, v, d in G_dual.edges(d_nodes_dual_id2idx[d_lines_primal_idx2id[idx]], data=True)] for idx in list(lines_primal.index)]" + "stroke_gdf.loc[stroke_gdf.index.values[0]]" ] }, { "cell_type": "code", - "execution_count": 62, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "angles_strokes_all = []\n", - "for idx in list(stroke_gdf.index):\n", - " array = list(lines_primal[lines_primal[\"id\"].isin(stroke_gdf.iloc[idx][\"edge_ids\"])][\"angles\"])\n", - " flat_array = []\n", - " for arr in array:\n", - " for val in arr:\n", - " flat_array.append(val)\n", - " angles_strokes_singular = {}\n", - " for val in flat_array:\n", - " stroke_id = int(lines_primal.iloc[d_lines_primal_id2idx[val[0]]][\"stroke_id\"])\n", - " if stroke_id == idx:\n", - " pass\n", - " elif stroke_id not in angles_strokes_singular:\n", - " angles_strokes_singular[stroke_id] = [val[1]]\n", - " else:\n", - " angles_strokes_singular[stroke_id].append(val[1])\n", - " angles_strokes_all.append(angles_strokes_singular)\n", - "stroke_gdf[\"angles_with_strokes\"] = angles_strokes_all" + "def _find_geom(linestring_1, linestring_2, point):\n", + " if point == linestring_1.coords[0]:\n", + " geom_1 = linestring_1.coords[1]\n", + " else:\n", + " geom_1 = linestring_1.coords[-2]\n", + " if point == linestring_2.coords[0]:\n", + " geom_2 = linestring_2.coords[1]\n", + " else:\n", + " geom_2 = linestring_2.coords[-2] \n", + " return geom_1, geom_2" ] }, { @@ -128,68 +119,783 @@ "metadata": {}, "outputs": [], "source": [ + "# Create stroke graph\n", "G_stroke = nx.Graph()\n", "G_stroke.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", "# Create a node for each stroke with the right features\n", - "G_stroke.add_nodes_from([[val, {attr:(list(stroke_gdf[stroke_gdf[\"stroke_id\"] == val][attr])[0] if attr != \"geometry\" else stroke_gdf[stroke_gdf[\"stroke_id\"] == val].geometry[val]) for attr in list(stroke_gdf)}] for val in list(stroke_gdf[\"stroke_id\"])])\n", + "G_stroke.add_nodes_from([[int(idx), {(attr if attr != \"geometry\" else \"geometry_stroke\"):stroke_gdf.loc[idx][attr] for attr in list(stroke_gdf)}] for idx in stroke_gdf.index.values])\n", "# For all node, put its geometry at the center of the LineString\n", "for n in G_stroke.nodes:\n", " G_stroke.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", " G_stroke.nodes[n][\"x\"] = G_stroke.nodes[n][\"geometry\"].xy[0]\n", " G_stroke.nodes[n][\"y\"] = G_stroke.nodes[n][\"geometry\"].xy[1]\n", + " G_stroke.nodes[n][\"length\"] = G_stroke.nodes[n][\"geometry_stroke\"].length\n", + "# Find strokes intersecting\n", + "for n in G_primal.nodes:\n", + " strokes_present = [G_primal.edges[e][\"stroke_id\"] for e in G_primal.edges(n, keys=True)]\n", + " # If strokes intersecting, add the edge if not already present\n", + " if len(set(strokes_present)) > 1:\n", + " for u, v in combinations(set(strokes_present), 2):\n", + " # Find all edges touching the node for both strokes checked\n", + " edges_u = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == u]\n", + " edges_v = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == v]\n", + " angle_list = []\n", + " angle_dict = {}\n", + " # Choose the smallest list as number of angles kept\n", + " chosen, other = sorted([edges_u, edges_v], key=len)\n", + " # Find the angles\n", + " for ce, oe in list(product(chosen, other)):\n", + " point = [G_primal.nodes[n][\"x\"], G_primal.nodes[n][\"y\"]]\n", + " gc, go = _find_geom(G_primal.edges[ce][\"geometry\"], G_primal.edges[oe][\"geometry\"], point)\n", + " if ce in angle_dict:\n", + " angle_dict[ce].append(_angle(gc, point, go))\n", + " else:\n", + " angle_dict[ce]= [_angle(gc, point, go)]\n", + " # Keep the smallest angles\n", + " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", + " # TODO solve angles\n", + " if G_stroke.has_edge(u, v):\n", + " G_stroke.edges[u, v][\"angles\"] += angle_list\n", + " G_stroke.edges[u, v][\"number_connections\"] = len(G_stroke.edges[u, v][\"angles\"])\n", + " else:\n", + " G_stroke.add_edge(u, v, geometry = shapely.LineString([G_stroke.nodes[u][\"geometry\"], G_stroke.nodes[v][\"geometry\"]]), number_connections=len(angle_list), angles=angle_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 221, + "metadata": {}, + "outputs": [], + "source": [ + "nx.set_node_attributes(G_stroke, nx.betweenness_centrality(G_stroke), \"stroke_betweenness\")\n", + "nx.set_node_attributes(G_stroke, nx.closeness_centrality(G_stroke), \"stroke_closeness\")\n", + "nx.set_node_attributes(G_stroke, dict(nx.degree(G_stroke)), \"stroke_degree\")\n", "for n in G_stroke.nodes:\n", - " for k in stroke_gdf.iloc[n][\"angles_with_strokes\"]:\n", - " G_stroke.add_edge(n, k, geometry = shapely.LineString(counting = sum(stroke_gdf.iloc[n][\"angles_with_strokes\"][k]), angles = stroke_gdf.iloc[n][\"angles_with_strokes\"][k])" + " G_stroke.nodes[n][\"stroke_connectivity\"] = sum([G_stroke.edges[e][\"number_connections\"] for e in G_stroke.edges(n)])\n", + " G_stroke.nodes[n][\"stroke_access\"] = G_stroke.nodes[n][\"stroke_connectivity\"] - G_stroke.nodes[n][\"stroke_degree\"]\n", + " angles = [val for e in G_stroke.edges(n) if G_stroke.edges[e][\"angles\"] for val in G_stroke.edges[e][\"angles\"]]\n", + " G_stroke.nodes[n][\"stroke_orthogonality\"] = sum(angles) / G_stroke.nodes[n][\"stroke_connectivity\"]\n", + " G_stroke.nodes[n][\"stroke_:spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]" ] }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 222, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_8655/1971550804.py:1: UserWarning: Approach is not set. Defaulting to 'primal'.\n", + "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_27796/2550495861.py:5: UserWarning: Approach is not set. Defaulting to 'primal'.\n", " points_stroke, lines_stroke = momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n" ] }, { - "ename": "ValueError", - "evalue": "Assigning CRS to a GeoDataFrame without a geometry column is not supported. Use GeoDataFrame.set_geometry to set the active geometry column.", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:517\u001b[39m, in \u001b[36mGeoDataFrame.crs\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 516\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m517\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mgeometry\u001b[49m.crs\n\u001b[32m 518\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m:\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/pandas/core/generic.py:6299\u001b[39m, in \u001b[36mNDFrame.__getattr__\u001b[39m\u001b[34m(self, name)\u001b[39m\n\u001b[32m 6298\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[name]\n\u001b[32m-> \u001b[39m\u001b[32m6299\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mobject\u001b[39;49m\u001b[43m.\u001b[49m\u001b[34;43m__getattribute__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:253\u001b[39m, in \u001b[36mGeoDataFrame._get_geometry\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 247\u001b[39m msg += (\n\u001b[32m 248\u001b[39m \u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mThere are no existing columns with geometry data type. You can \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 249\u001b[39m \u001b[33m\"\u001b[39m\u001b[33madd a geometry column as the active geometry column with \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 250\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mdf.set_geometry. \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 251\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m253\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(msg)\n\u001b[32m 254\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[\u001b[38;5;28mself\u001b[39m._geometry_column_name]\n", - "\u001b[31mAttributeError\u001b[39m: You are calling a geospatial method on the GeoDataFrame, but the active geometry column to use has not been set. \nThere are no existing columns with geometry data type. You can add a geometry column as the active geometry column with df.set_geometry. ", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/pandas/core/generic.py:6325\u001b[39m, in \u001b[36mNDFrame.__setattr__\u001b[39m\u001b[34m(self, name, value)\u001b[39m\n\u001b[32m 6324\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m6325\u001b[39m existing = \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 6326\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(existing, Index):\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/pandas/core/generic.py:6299\u001b[39m, in \u001b[36mNDFrame.__getattr__\u001b[39m\u001b[34m(self, name)\u001b[39m\n\u001b[32m 6298\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[name]\n\u001b[32m-> \u001b[39m\u001b[32m6299\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mobject\u001b[39;49m\u001b[43m.\u001b[49m\u001b[34;43m__getattribute__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:519\u001b[39m, in \u001b[36mGeoDataFrame.crs\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 518\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m519\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\n\u001b[32m 520\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mThe CRS attribute of a GeoDataFrame without an active \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 521\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mgeometry column is not defined. Use GeoDataFrame.set_geometry \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 522\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mto set the active geometry column.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 523\u001b[39m )\n", - "\u001b[31mAttributeError\u001b[39m: The CRS attribute of a GeoDataFrame without an active geometry column is not defined. Use GeoDataFrame.set_geometry to set the active geometry column.", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[31mValueError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[68]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m points_stroke, lines_stroke = \u001b[43mmomepy\u001b[49m\u001b[43m.\u001b[49m\u001b[43mnx_to_gdf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mG_stroke\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpoints\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlines\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[32m 2\u001b[39m m = stroke_gdf.explore(tiles=\u001b[33m\"\u001b[39m\u001b[33mcartodb-positron\u001b[39m\u001b[33m\"\u001b[39m, column=\u001b[33m\"\u001b[39m\u001b[33mstroke_id\u001b[39m\u001b[33m\"\u001b[39m, cmap=\u001b[33m\"\u001b[39m\u001b[33mtab10\u001b[39m\u001b[33m\"\u001b[39m, name=\u001b[33m\"\u001b[39m\u001b[33mstrokes\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 3\u001b[39m points_primal.explore(m=m, name=\u001b[33m\"\u001b[39m\u001b[33mpoints_primal\u001b[39m\u001b[33m\"\u001b[39m)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Desktop/PhD/Code/momepy/momepy/utils.py:569\u001b[39m, in \u001b[36mnx_to_gdf\u001b[39m\u001b[34m(net, points, lines, spatial_weights, nodeID)\u001b[39m\n\u001b[32m 566\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m nid, n \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(net):\n\u001b[32m 567\u001b[39m net.nodes[n][nodeID] = nid\n\u001b[32m--> \u001b[39m\u001b[32m569\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_primal_to_gdf\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 570\u001b[39m \u001b[43m \u001b[49m\u001b[43mnet\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 571\u001b[39m \u001b[43m \u001b[49m\u001b[43mpoints\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpoints\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 572\u001b[39m \u001b[43m \u001b[49m\u001b[43mlines\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlines\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 573\u001b[39m \u001b[43m \u001b[49m\u001b[43mspatial_weights\u001b[49m\u001b[43m=\u001b[49m\u001b[43mspatial_weights\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 574\u001b[39m \u001b[43m \u001b[49m\u001b[43mnode_id\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnodeID\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 575\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Desktop/PhD/Code/momepy/momepy/utils.py:441\u001b[39m, in \u001b[36m_primal_to_gdf\u001b[39m\u001b[34m(net, points, lines, spatial_weights, node_id)\u001b[39m\n\u001b[32m 438\u001b[39m weights.transform = \u001b[33m\"\u001b[39m\u001b[33mb\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 440\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m lines \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m441\u001b[39m gdf_edges = \u001b[43m_lines_to_gdf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnet\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpoints\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnode_id\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 443\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m points \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m lines \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[32m 444\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m spatial_weights \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Desktop/PhD/Code/momepy/momepy/utils.py:417\u001b[39m, in \u001b[36m_lines_to_gdf\u001b[39m\u001b[34m(net, points, node_id)\u001b[39m\n\u001b[32m 414\u001b[39m gdf_edges[\u001b[33m\"\u001b[39m\u001b[33mnode_end\u001b[39m\u001b[33m\"\u001b[39m] = [net.nodes[e][node_id] \u001b[38;5;28;01mfor\u001b[39;00m e \u001b[38;5;129;01min\u001b[39;00m ends]\n\u001b[32m 416\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33mcrs\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m net.graph:\n\u001b[32m--> \u001b[39m\u001b[32m417\u001b[39m \u001b[43mgdf_edges\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcrs\u001b[49m = net.graph[\u001b[33m\"\u001b[39m\u001b[33mcrs\u001b[39m\u001b[33m\"\u001b[39m]\n\u001b[32m 418\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33mindex_position\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m gdf_edges.columns:\n\u001b[32m 419\u001b[39m gdf_edges = gdf_edges.sort_values(\u001b[33m\"\u001b[39m\u001b[33mindex_position\u001b[39m\u001b[33m\"\u001b[39m).drop(\n\u001b[32m 420\u001b[39m columns=\u001b[33m\"\u001b[39m\u001b[33mindex_position\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 421\u001b[39m )\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:223\u001b[39m, in \u001b[36mGeoDataFrame.__setattr__\u001b[39m\u001b[34m(self, attr, val)\u001b[39m\n\u001b[32m 221\u001b[39m \u001b[38;5;28mobject\u001b[39m.\u001b[34m__setattr__\u001b[39m(\u001b[38;5;28mself\u001b[39m, attr, val)\n\u001b[32m 222\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m223\u001b[39m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[34;43m__setattr__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mattr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mval\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/pandas/core/generic.py:6341\u001b[39m, in \u001b[36mNDFrame.__setattr__\u001b[39m\u001b[34m(self, name, value)\u001b[39m\n\u001b[32m 6333\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m, ABCDataFrame) \u001b[38;5;129;01mand\u001b[39;00m (is_list_like(value)):\n\u001b[32m 6334\u001b[39m warnings.warn(\n\u001b[32m 6335\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mPandas doesn\u001b[39m\u001b[33m'\u001b[39m\u001b[33mt allow columns to be \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 6336\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mcreated via a new attribute name - see \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m (...)\u001b[39m\u001b[32m 6339\u001b[39m stacklevel=find_stack_level(),\n\u001b[32m 6340\u001b[39m )\n\u001b[32m-> \u001b[39m\u001b[32m6341\u001b[39m \u001b[38;5;28;43mobject\u001b[39;49m\u001b[43m.\u001b[49m\u001b[34;43m__setattr__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniforge3/envs/momepy_dev/lib/python3.12/site-packages/geopandas/geodataframe.py:529\u001b[39m, in \u001b[36mGeoDataFrame.crs\u001b[39m\u001b[34m(self, value)\u001b[39m\n\u001b[32m 527\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"Sets the value of the crs\"\"\"\u001b[39;00m\n\u001b[32m 528\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._geometry_column_name \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m529\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m 530\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mAssigning CRS to a GeoDataFrame without a geometry column is not \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 531\u001b[39m \u001b[33m\"\u001b[39m\u001b[33msupported. Use GeoDataFrame.set_geometry to set the active \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 532\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mgeometry column.\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 533\u001b[39m )\n\u001b[32m 535\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m.geometry.values, \u001b[33m\"\u001b[39m\u001b[33mcrs\u001b[39m\u001b[33m\"\u001b[39m):\n\u001b[32m 536\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.crs \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "\u001b[31mValueError\u001b[39m: Assigning CRS to a GeoDataFrame without a geometry column is not supported. Use GeoDataFrame.set_geometry to set the active geometry column." - ] + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 222, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ + "stroke_gdf_viz = stroke_gdf.copy()\n", + "stroke_gdf_viz[\"id\"] = stroke_gdf_viz.index\n", + "lines_primal_viz = lines_primal.copy()\n", + "lines_primal_viz[\"edge_id\"] = lines_primal.index\n", "points_stroke, lines_stroke = momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n", - "m = stroke_gdf.explore(tiles=\"cartodb-positron\", column=\"stroke_id\", cmap=\"tab10\", name=\"strokes\")\n", + "m = stroke_gdf_viz.explore(tiles=\"cartodb-positron\", column=\"id\", cmap=\"tab10\", name=\"strokes\")\n", "points_primal.explore(m=m, name=\"points_primal\")\n", - "lines_primal.explore(m=m, name=\"lines_primal\")\n", + "lines_primal_viz.explore(m=m, name=\"lines_primal\")\n", "points_stroke.explore(m=m, color=\"black\", marker_kwds={\"radius\":10}, name=\"points_stroke\")\n", "lines_stroke.explore(m=m, color=\"blue\", name=\"lines_stroke\")\n", "folium.LayerControl().add_to(m)\n", From 07b2e1605891006bdfd3ef5db27e8cf32d284344 Mon Sep 17 00:00:00 2001 From: anvy Date: Mon, 12 May 2025 16:43:01 +0200 Subject: [PATCH 07/27] update strokegraph nb: finished workflow (angles tbd) --- momepy/strokegraph.ipynb | 2249 ++++++++++++++++++++++++++++---------- 1 file changed, 1649 insertions(+), 600 deletions(-) diff --git a/momepy/strokegraph.ipynb b/momepy/strokegraph.ipynb index 67f0e300..860a9375 100644 --- a/momepy/strokegraph.ipynb +++ b/momepy/strokegraph.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -20,7 +20,35 @@ "import networkx as nx\n", "import folium\n", "from itertools import combinations\n", - "from shapely import LineString" + "from shapely import LineString\n", + "import numpy as np\n", + "import math\n", + "import collections\n", + "import warnings\n", + "from collections import Counter" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# https://carto.com/carto-colors/ > Prism\n", + "colors_list = [\n", + " \"#5F4690\",\n", + " \"#1D6996\",\n", + " \"#38A6A5\",\n", + " \"#0F8554\",\n", + " \"#73AF48\",\n", + " \"#EDAD08\",\n", + " \"#E17C05\",\n", + " \"#CC503E\",\n", + " \"#94346E\",\n", + " \"#6F4070\",\n", + " \"#994E95\",\n", + " \"#666666\"\n", + "]" ] }, { @@ -32,16 +60,12 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# read in toy graph (Bubenec)\n", - "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", - "\n", - "# ax = streets.plot(figsize=(8, 8), column=\"id\", cmap = \"Accent\")\n", - "# ax.set_axis_off()\n", - "# ax.legend()" + "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")" ] }, { @@ -59,9 +83,14 @@ "- [ ] add stroke attribute to each edge on primal graph" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -72,7 +101,160 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
geometrymm_lennode_startnode_endmy_index
0LINESTRING (1603585.64 6464428.774, 1603413.20...264.103950010
1LINESTRING (1603268.502 6464060.781, 1603296.8...99.751190231
2LINESTRING (1603607.303 6464181.853, 1603592.8...199.746503142
3LINESTRING (1603363.558 6464031.885, 1603376.5...203.014090133
4LINESTRING (1603413.206 6464228.73, 1603274.45...198.482724154
\n", + "
" + ], + "text/plain": [ + " geometry mm_len node_start \\\n", + "0 LINESTRING (1603585.64 6464428.774, 1603413.20... 264.103950 0 \n", + "1 LINESTRING (1603268.502 6464060.781, 1603296.8... 99.751190 2 \n", + "2 LINESTRING (1603607.303 6464181.853, 1603592.8... 199.746503 1 \n", + "3 LINESTRING (1603363.558 6464031.885, 1603376.5... 203.014090 1 \n", + "4 LINESTRING (1603413.206 6464228.73, 1603274.45... 198.482724 1 \n", + "\n", + " node_end my_index \n", + "0 1 0 \n", + "1 3 1 \n", + "2 4 2 \n", + "3 3 3 \n", + "4 5 4 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# remove false nodes\n", + "streets = momepy.remove_false_nodes(streets)\n", + "\n", + "# add unique edge ID to streets, already HERE!\n", + "# streets[\"edge_id\"] = streets.index\n", + "\n", + "# make primal graph\n", + "graph = momepy.gdf_to_nx(\n", + " streets, \n", + " preserve_index=True, # index of lines gdf should be referring to EXACTLY THE SAME ELEMENT as index of streets gdf\n", + " approach=\"primal\"\n", + ")\n", + "\n", + "# get gdfs of points and lines\n", + "points, lines = momepy.nx_to_gdf(graph, points=True, lines=True)\n", + "\n", + "# # asserting that our edge indeces didn't get messed up\n", + "# assert(len(lines) == len(streets))\n", + "\n", + "# for i, row in lines.iterrows():\n", + "# assert(row[\"geometry\"] == streets.loc[i,\"geometry\"])\n", + "\n", + "lines[\"my_index\"] = lines.index # just for plotting TODO remove later\n", + "\n", + "# each row is an edge\n", + "lines.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(1,1, figsize=(8,8))\n", + "lines.plot(ax=ax, column=\"my_index\", cmap=\"tab20\", lw=3, legend=True, zorder=0)\n", + "points.plot(ax=ax, color = \"black\", zorder=1)\n", + "ax.set_axis_off()\n", + "plt.title(\"Input: edges\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -100,7 +282,6 @@ " geometry\n", " rep_point\n", " stroke_id\n", - " edge_ids\n", " \n", " \n", " stroke_group\n", @@ -108,7 +289,6 @@ " \n", " \n", " \n", - " \n", " \n", " \n", " \n", @@ -118,39 +298,34 @@ " LINESTRING (1603278.899 6463669.186, 1603283.7...\n", " POINT (1603374.663 6464077.898)\n", " 0\n", - " [0, 3, 15, 27]\n", " \n", " \n", " 1\n", - " 17\n", - " LINESTRING (1603537.194 6464558.112, 1603557.6...\n", - " POINT (1603707.107 6464238.854)\n", + " 19\n", + " LINESTRING (1603077.5 6464475.323, 1603085.515...\n", + " POINT (1603237.049 6464133.622)\n", " 1\n", - " [11, 28, 2, 30]\n", " \n", " \n", " 2\n", - " 5\n", - " LINESTRING (1603413.206 6464228.73, 1603274.45...\n", - " POINT (1603149.929 6464130.225)\n", + " 17\n", + " LINESTRING (1603537.194 6464558.112, 1603557.6...\n", + " POINT (1603707.107 6464238.854)\n", " 2\n", - " [4, 5, 6]\n", " \n", " \n", " 3\n", " 5\n", - " LINESTRING (1603287.304 6464587.705, 1603286.8...\n", - " POINT (1603342.343 6464406.368)\n", + " LINESTRING (1603413.206 6464228.73, 1603274.45...\n", + " POINT (1603149.929 6464130.225)\n", " 3\n", - " [26]\n", " \n", " \n", " 4\n", - " 19\n", - " LINESTRING (1603077.5 6464475.323, 1603085.515...\n", - " POINT (1603237.049 6464133.622)\n", + " 14\n", + " LINESTRING (1602970.377 6464268.058, 1602974.0...\n", + " POINT (1603264.658 6463848.976)\n", " 4\n", - " [1, 12, 14, 25]\n", " \n", " \n", "\n", @@ -160,38 +335,26 @@ " n_segments geometry \\\n", "stroke_group \n", "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", - "1 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", - "2 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", - "3 5 LINESTRING (1603287.304 6464587.705, 1603286.8... \n", - "4 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", - "\n", - " rep_point stroke_id edge_ids \n", - "stroke_group \n", - "0 POINT (1603374.663 6464077.898) 0 [0, 3, 15, 27] \n", - "1 POINT (1603707.107 6464238.854) 1 [11, 28, 2, 30] \n", - "2 POINT (1603149.929 6464130.225) 2 [4, 5, 6] \n", - "3 POINT (1603342.343 6464406.368) 3 [26] \n", - "4 POINT (1603237.049 6464133.622) 4 [1, 12, 14, 25] " + "1 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", + "2 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", + "3 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", + "4 14 LINESTRING (1602970.377 6464268.058, 1602974.0... \n", + "\n", + " rep_point stroke_id \n", + "stroke_group \n", + "0 POINT (1603374.663 6464077.898) 0 \n", + "1 POINT (1603237.049 6464133.622) 1 \n", + "2 POINT (1603707.107 6464238.854) 2 \n", + "3 POINT (1603149.929 6464130.225) 3 \n", + "4 POINT (1603264.658 6463848.976) 4 " ] }, - "execution_count": 21, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# remove false nodes\n", - "streets = momepy.remove_false_nodes(streets)\n", - "\n", - "# add unique edge ID to streets, already HERE!\n", - "streets[\"edge_id\"] = streets.index\n", - "\n", - "# make primal graph\n", - "graph = momepy.gdf_to_nx(streets, approach=\"primal\")\n", - "\n", - "# get gdfs of points and lines\n", - "points, lines = momepy.nx_to_gdf(graph, points=True, lines=True)\n", - "\n", "# make coins\n", "coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", "\n", @@ -203,166 +366,288 @@ "# add stroke_id column\n", "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", "\n", - "# add edge_ids column (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", - "stroke_gdf[\"edge_ids\"] = stroke_gdf.stroke_id.apply(\n", - " lambda x: list(\n", - " lines.iloc[\n", - " stroke_attribute[stroke_attribute == x].index][\"edge_id\"]\n", - " )\n", - ")\n", - "\n", "stroke_gdf.head()" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
n_segmentsgeometryrep_pointstroke_idedge_indeces
stroke_group
08LINESTRING (1603278.899 6463669.186, 1603283.7...POINT (1603374.663 6464077.898)0[0, 3, 15, 27]
119LINESTRING (1603077.5 6464475.323, 1603085.515...POINT (1603237.049 6464133.622)1[1, 12, 14, 25]
217LINESTRING (1603537.194 6464558.112, 1603557.6...POINT (1603707.107 6464238.854)2[2, 11, 28, 30]
35LINESTRING (1603413.206 6464228.73, 1603274.45...POINT (1603149.929 6464130.225)3[4, 5, 6]
414LINESTRING (1602970.377 6464268.058, 1602974.0...POINT (1603264.658 6463848.976)4[7, 8, 9, 13, 21, 22, 24]
\n", + "
" + ], "text/plain": [ - "{0: ((1603585.6402153103, 6464428.773867372),\n", - " (1603413.2063240695, 6464228.730248732),\n", - " 0),\n", - " 11: ((1603585.6402153103, 6464428.773867372),\n", - " (1603650.450422848, 6464368.600601688),\n", - " 0),\n", - " 28: ((1603585.6402153103, 6464428.773867372),\n", - " (1603537.1939729159, 6464558.11228298),\n", - " 0),\n", - " 2: ((1603413.2063240695, 6464228.730248732),\n", - " (1603607.3029882177, 6464181.852772597),\n", - " 0),\n", - " 3: ((1603413.2063240695, 6464228.730248732),\n", - " (1603363.557831175, 6464031.88480676),\n", - " 0),\n", - " 4: ((1603413.2063240695, 6464228.730248732),\n", - " (1603226.9576840235, 6464160.158361825),\n", - " 0),\n", - " 26: ((1603413.2063240695, 6464228.730248732),\n", - " (1603287.303979983, 6464587.704889874),\n", - " 0),\n", - " 1: ((1603268.502117987, 6464060.781328565),\n", - " (1603363.557831175, 6464031.88480676),\n", - " 0),\n", - " 12: ((1603268.502117987, 6464060.781328565),\n", - " (1603226.9576840235, 6464160.158361825),\n", - " 0),\n", - " 20: ((1603268.502117987, 6464060.781328565),\n", - " (1603146.6963311615, 6463924.630126579),\n", - " 0),\n", - " 14: ((1603363.557831175, 6464031.88480676),\n", - " (1603558.489391506, 6463985.80677705),\n", - " 0),\n", - " 15: ((1603363.557831175, 6464031.88480676),\n", - " (1603317.7832565615, 6463836.796863219),\n", - " 0),\n", - " 16: ((1603607.3029882177, 6464181.852772597),\n", - " (1603650.450422848, 6464368.600601688),\n", - " 0),\n", - " 30: ((1603607.3029882177, 6464181.852772597),\n", - " (1603650.450422848, 6464368.600601688),\n", - " 1),\n", - " 17: ((1603607.3029882177, 6464181.852772597),\n", - " (1603558.489391506, 6463985.80677705),\n", - " 0),\n", - " 5: ((1603226.9576840235, 6464160.158361825),\n", - " (1603039.9632033885, 6464087.491175889),\n", - " 0),\n", - " 25: ((1603226.9576840235, 6464160.158361825),\n", - " (1603077.5001356844, 6464475.322968743),\n", - " 0),\n", - " 6: ((1603039.9632033885, 6464087.491175889),\n", - " (1602887.2996537155, 6464029.975730775),\n", - " 0),\n", - " 7: ((1603039.9632033885, 6464087.491175889),\n", - " (1602970.3773896934, 6464268.058242684),\n", - " 0),\n", - " 8: ((1603039.9632033885, 6464087.491175889),\n", - " (1603090.513384159, 6463971.106984773),\n", - " 0),\n", - " 19: ((1603090.513384159, 6463971.106984773),\n", - " (1602959.8799617135, 6463839.712475327),\n", - " 0),\n", - " 21: ((1603090.513384159, 6463971.106984773),\n", - " (1603146.6963311615, 6463924.630126579),\n", - " 0),\n", - " 9: ((1603317.7832565615, 6463836.796863219),\n", - " (1603202.3783404578, 6463872.287568242),\n", - " 0),\n", - " 24: ((1603317.7832565615, 6463836.796863219),\n", - " (1603513.6499006122, 6463789.557147608),\n", - " 0),\n", - " 27: ((1603317.7832565615, 6463836.796863219),\n", - " (1603278.8993584276, 6463669.185595578),\n", - " 0),\n", - " 10: ((1603202.3783404578, 6463872.287568242),\n", - " (1603071.956425043, 6463729.978565),\n", - " 0),\n", - " 22: ((1603202.3783404578, 6463872.287568242),\n", - " (1603146.6963311615, 6463924.630126579),\n", - " 0),\n", - " 29: ((1603650.450422848, 6464368.600601688),\n", - " (1603706.3884669733, 6464617.783583014),\n", - " 0),\n", - " 13: ((1603513.6499006122, 6463789.557147608),\n", - " (1603795.889337571, 6463785.444077063),\n", - " 0),\n", - " 18: ((1603513.6499006122, 6463789.557147608),\n", - " (1603558.489391506, 6463985.80677705),\n", - " 0),\n", - " 23: ((1603513.6499006122, 6463789.557147608),\n", - " (1603473.6416756227, 6463625.487127112),\n", - " 0)}" + " n_segments geometry \\\n", + "stroke_group \n", + "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", + "1 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", + "2 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", + "3 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", + "4 14 LINESTRING (1602970.377 6464268.058, 1602974.0... \n", + "\n", + " rep_point stroke_id \\\n", + "stroke_group \n", + "0 POINT (1603374.663 6464077.898) 0 \n", + "1 POINT (1603237.049 6464133.622) 1 \n", + "2 POINT (1603707.107 6464238.854) 2 \n", + "3 POINT (1603149.929 6464130.225) 3 \n", + "4 POINT (1603264.658 6463848.976) 4 \n", + "\n", + " edge_indeces \n", + "stroke_group \n", + "0 [0, 3, 15, 27] \n", + "1 [1, 12, 14, 25] \n", + "2 [2, 11, 28, 30] \n", + "3 [4, 5, 6] \n", + "4 [7, 8, 9, 13, 21, 22, 24] " ] }, - "execution_count": 22, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# make dictionary for primal graph, edge_id:edge_name\n", - "d = nx.get_edge_attributes(graph, \"edge_id\")\n", - "d = {v:k for k,v in d.items()}\n", - "d" + "# add edge_ids column (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", + "stroke_gdf[\"edge_indeces\"] = stroke_gdf.stroke_id.apply(\n", + " lambda x: list(stroke_attribute[stroke_attribute==x].index)\n", + ")\n", + "\n", + "stroke_gdf.head()" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "# for each edge, add \"stroke_id\" as attribute to graph\n", - "for _, row in stroke_gdf.iterrows():\n", - " for e in row.edge_ids: \n", - " graph.edges[d[e]][\"stroke_id\"] = row.stroke_id" + "fig, ax = plt.subplots(1,1, figsize=(10,10))\n", + "for stroke_id in stroke_gdf.stroke_id:\n", + " stroke_gdf[stroke_gdf.stroke_id==stroke_id].plot(ax=ax, lw=3, label=stroke_id, zorder=0, color=colors_list[stroke_id])\n", + "points.plot(ax=ax, color = \"black\", zorder=1)\n", + "ax.set_axis_off()\n", + "ax.legend(title=\"Generated: stroke IDs\")\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ - "d_strokes = nx.get_edge_attributes(graph, \"stroke_id\")\n", - "d_edges = nx.get_edge_attributes(graph, \"edge_id\")" + "# make dictionary for primal graph: d={edge_index:edge_name}\n", + "# where edge_name (in momepy language) is the corresponding node tuple\n", + "d_name2index = nx.get_edge_attributes(graph, \"index_position\")\n", + "d_index2name = {v:k for k,v in d_name2index.items()}\n", + "\n", + "# for each edge, add \"stroke_id\" as attribute to graph\n", + "for _, row in stroke_gdf.iterrows():\n", + " for edge_index in row.edge_indeces: \n", + " graph.edges[d_index2name[edge_index]][\"stroke_id\"] = row.stroke_id\n", + "\n", + "# getting dicts of edge name : stroke ID, and edge index : stroke id # TODO: one of them might be obsolete?\n", + "d_name2stroke = nx.get_edge_attributes(graph, \"stroke_id\")\n", + "d_index2stroke = {d_name2index[k]:v for k,v in d_name2stroke.items()} " ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 11, "metadata": {}, - "outputs": [], - "source": [ - "edges_strokes = {d_edges[k]:d_strokes[k] for k in d_edges} " - ] - }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
geometrymm_lennode_startnode_endmy_index
0LINESTRING (1603585.64 6464428.774, 1603413.20...264.103950010
1LINESTRING (1603268.502 6464060.781, 1603296.8...99.751190231
2LINESTRING (1603607.303 6464181.853, 1603592.8...199.746503142
3LINESTRING (1603363.558 6464031.885, 1603376.5...203.014090133
4LINESTRING (1603413.206 6464228.73, 1603274.45...198.482724154
\n", + "
" + ], + "text/plain": [ + " geometry mm_len node_start \\\n", + "0 LINESTRING (1603585.64 6464428.774, 1603413.20... 264.103950 0 \n", + "1 LINESTRING (1603268.502 6464060.781, 1603296.8... 99.751190 2 \n", + "2 LINESTRING (1603607.303 6464181.853, 1603592.8... 199.746503 1 \n", + "3 LINESTRING (1603363.558 6464031.885, 1603376.5... 203.014090 1 \n", + "4 LINESTRING (1603413.206 6464228.73, 1603274.45... 198.482724 1 \n", + "\n", + " node_end my_index \n", + "0 1 0 \n", + "1 3 1 \n", + "2 4 2 \n", + "3 3 3 \n", + "4 5 4 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lines.head()" + ] + }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -395,7 +680,7 @@ " <meta name="viewport" content="width=device-width,\n", " initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />\n", " <style>\n", - " #map_ef7357925cb53e53304c4b778d7693b5 {\n", + " #map_9051cbfe5b4c076be108ec9d20e27e42 {\n", " position: relative;\n", " width: 100.0%;\n", " height: 100.0%;\n", @@ -442,14 +727,14 @@ "<body>\n", " \n", " \n", - " <div class="folium-map" id="map_ef7357925cb53e53304c4b778d7693b5" ></div>\n", + " <div class="folium-map" id="map_9051cbfe5b4c076be108ec9d20e27e42" ></div>\n", " \n", "</body>\n", "<script>\n", " \n", " \n", - " var map_ef7357925cb53e53304c4b778d7693b5 = L.map(\n", - " "map_ef7357925cb53e53304c4b778d7693b5",\n", + " var map_9051cbfe5b4c076be108ec9d20e27e42 = L.map(\n", + " "map_9051cbfe5b4c076be108ec9d20e27e42",\n", " {\n", " center: [50.102935750000015, 14.403062600000004],\n", " crs: L.CRS.EPSG3857,\n", @@ -458,28 +743,28 @@ " preferCanvas: false,\n", " }\n", " );\n", - " L.control.scale().addTo(map_ef7357925cb53e53304c4b778d7693b5);\n", + " L.control.scale().addTo(map_9051cbfe5b4c076be108ec9d20e27e42);\n", "\n", " \n", "\n", " \n", " \n", - " var tile_layer_1c129d5d3ca5c01b49b9853cf43c5bb4 = L.tileLayer(\n", + " var tile_layer_ae2fd0e7f9d32293dab73f890576a178 = L.tileLayer(\n", " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",\n", " {"attribution": "\\u0026copy; \\u003ca href=\\"https://www.openstreetmap.org/copyright\\"\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\"https://carto.com/attributions\\"\\u003eCARTO\\u003c/a\\u003e", "detectRetina": false, "maxZoom": 20, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}\n", " );\n", " \n", " \n", - " tile_layer_1c129d5d3ca5c01b49b9853cf43c5bb4.addTo(map_ef7357925cb53e53304c4b778d7693b5);\n", + " tile_layer_ae2fd0e7f9d32293dab73f890576a178.addTo(map_9051cbfe5b4c076be108ec9d20e27e42);\n", " \n", " \n", - " map_ef7357925cb53e53304c4b778d7693b5.fitBounds(\n", + " map_9051cbfe5b4c076be108ec9d20e27e42.fitBounds(\n", " [[50.10007700000001, 14.398981599999999], [50.10579450000001, 14.407143600000008]],\n", " {}\n", " );\n", " \n", " \n", - " function geo_json_4492eef1ce432dba2afbd7e795b9e634_styler(feature) {\n", + " function geo_json_cff39fc4687a13617618a9bebc8e6a77_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#fff5f0", "fillColor": "#fff5f0", "fillOpacity": 0.5, "weight": 8};\n", @@ -503,58 +788,58 @@ " return {"color": "#67000d", "fillColor": "#67000d", "fillOpacity": 0.5, "weight": 8};\n", " }\n", " }\n", - " function geo_json_4492eef1ce432dba2afbd7e795b9e634_highlighter(feature) {\n", + " function geo_json_cff39fc4687a13617618a9bebc8e6a77_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_4492eef1ce432dba2afbd7e795b9e634_pointToLayer(feature, latlng) {\n", + " function geo_json_cff39fc4687a13617618a9bebc8e6a77_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_4492eef1ce432dba2afbd7e795b9e634_styler(feature)\n", + " let style = geo_json_cff39fc4687a13617618a9bebc8e6a77_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_4492eef1ce432dba2afbd7e795b9e634_onEachFeature(feature, layer) {\n", + " function geo_json_cff39fc4687a13617618a9bebc8e6a77_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_4492eef1ce432dba2afbd7e795b9e634.resetStyle(e.target);\n", + " geo_json_cff39fc4687a13617618a9bebc8e6a77.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_4492eef1ce432dba2afbd7e795b9e634_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_cff39fc4687a13617618a9bebc8e6a77_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_4492eef1ce432dba2afbd7e795b9e634 = L.geoJson(null, {\n", - " onEachFeature: geo_json_4492eef1ce432dba2afbd7e795b9e634_onEachFeature,\n", + " var geo_json_cff39fc4687a13617618a9bebc8e6a77 = L.geoJson(null, {\n", + " onEachFeature: geo_json_cff39fc4687a13617618a9bebc8e6a77_onEachFeature,\n", " \n", - " style: geo_json_4492eef1ce432dba2afbd7e795b9e634_styler,\n", - " pointToLayer: geo_json_4492eef1ce432dba2afbd7e795b9e634_pointToLayer,\n", + " style: geo_json_cff39fc4687a13617618a9bebc8e6a77_styler,\n", + " pointToLayer: geo_json_cff39fc4687a13617618a9bebc8e6a77_pointToLayer,\n", " });\n", "\n", - " function geo_json_4492eef1ce432dba2afbd7e795b9e634_add (data) {\n", - " geo_json_4492eef1ce432dba2afbd7e795b9e634\n", + " function geo_json_cff39fc4687a13617618a9bebc8e6a77_add (data) {\n", + " geo_json_cff39fc4687a13617618a9bebc8e6a77\n", " .addData(data);\n", " }\n", - " geo_json_4492eef1ce432dba2afbd7e795b9e634_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fff5f0", "edge_ids": "[0, 3, 15, 27]", "n_segments": 8, "stroke_group": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fee3d6", "edge_ids": "[11, 28, 2, 30]", "n_segments": 17, "stroke_group": 1, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fcc4ad", "edge_ids": "[4, 5, 6]", "n_segments": 5, "stroke_group": 2, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fca082", "edge_ids": "[26]", "n_segments": 5, "stroke_group": 3, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#fb7c5c", "edge_ids": "[1, 12, 14, 25]", "n_segments": 19, "stroke_group": 4, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#f6553c", "edge_ids": "[20]", "n_segments": 3, "stroke_group": 5, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e32f27", "edge_ids": "[16, 17, 29, 18, 23]", "n_segments": 13, "stroke_group": 6, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#c2161b", "edge_ids": "[7, 8, 21, 9, 24, 22, 13]", "n_segments": 14, "stroke_group": 7, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#9d0d14", "edge_ids": "[19]", "n_segments": 3, "stroke_group": 8, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#67000d", "edge_ids": "[10]", "n_segments": 2, "stroke_group": 9, "stroke_id": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_cff39fc4687a13617618a9bebc8e6a77_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fff5f0", "edge_indeces": "[0, 3, 15, 27]", "n_segments": 8, "stroke_group": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fee3d6", "edge_indeces": "[1, 12, 14, 25]", "n_segments": 19, "stroke_group": 1, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fcc4ad", "edge_indeces": "[2, 11, 28, 30]", "n_segments": 17, "stroke_group": 2, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fca082", "edge_indeces": "[4, 5, 6]", "n_segments": 5, "stroke_group": 3, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#fb7c5c", "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "n_segments": 14, "stroke_group": 4, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#f6553c", "edge_indeces": "[10]", "n_segments": 2, "stroke_group": 5, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e32f27", "edge_indeces": "[16, 17, 18, 23, 29]", "n_segments": 13, "stroke_group": 6, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#c2161b", "edge_indeces": "[19]", "n_segments": 3, "stroke_group": 7, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#9d0d14", "edge_indeces": "[20]", "n_segments": 3, "stroke_group": 8, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#67000d", "edge_indeces": "[26]", "n_segments": 5, "stroke_group": 9, "stroke_id": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_4492eef1ce432dba2afbd7e795b9e634.bindTooltip(\n", + " geo_json_cff39fc4687a13617618a9bebc8e6a77.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", " let handleObject = feature=>typeof(feature)=='object' ? JSON.stringify(feature) : feature;\n", - " let fields = ["stroke_group", "n_segments", "stroke_id", "edge_ids"];\n", - " let aliases = ["stroke_group", "n_segments", "stroke_id", "edge_ids"];\n", + " let fields = ["stroke_group", "n_segments", "stroke_id", "edge_indeces"];\n", + " let aliases = ["stroke_group", "n_segments", "stroke_id", "edge_indeces"];\n", " let table = '<table>' +\n", " String(\n", " fields.map(\n", @@ -572,45 +857,45 @@ " ,{"className": "foliumtooltip", "sticky": true});\n", " \n", " \n", - " geo_json_4492eef1ce432dba2afbd7e795b9e634.addTo(map_ef7357925cb53e53304c4b778d7693b5);\n", + " geo_json_cff39fc4687a13617618a9bebc8e6a77.addTo(map_9051cbfe5b4c076be108ec9d20e27e42);\n", " \n", " \n", - " var color_map_6f3d14160ef69676908aa6125eec6ff6 = {};\n", + " var color_map_1df84f1684aed76bf8aca0832c15525c = {};\n", "\n", " \n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.color = d3.scale.threshold()\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.color = d3.scale.threshold()\n", " .domain([0.0, 0.018036072144288578, 0.036072144288577156, 0.05410821643286573, 0.07214428857715431, 0.09018036072144289, 0.10821643286573146, 0.12625250501002003, 0.14428857715430862, 0.1623246492985972, 0.18036072144288579, 0.19839679358717435, 0.21643286573146292, 0.23446893787575152, 0.25250501002004005, 0.27054108216432865, 0.28857715430861725, 0.3066132264529058, 0.3246492985971944, 0.342685370741483, 0.36072144288577157, 0.3787575150300601, 0.3967935871743487, 0.4148296593186373, 0.43286573146292584, 0.45090180360721444, 0.46893787575150303, 0.48697394789579157, 0.5050100200400801, 0.5230460921843687, 0.5410821643286573, 0.5591182364729459, 0.5771543086172345, 0.5951903807615231, 0.6132264529058116, 0.6312625250501002, 0.6492985971943888, 0.6673346693386774, 0.685370741482966, 0.7034068136272545, 0.7214428857715431, 0.7394789579158316, 0.7575150300601202, 0.7755511022044088, 0.7935871743486974, 0.811623246492986, 0.8296593186372746, 0.8476953907815631, 0.8657314629258517, 0.8837675350701403, 0.9018036072144289, 0.9198396793587175, 0.9378757515030061, 0.9559118236472945, 0.9739478957915831, 0.9919839679358717, 1.0100200400801602, 1.028056112224449, 1.0460921843687374, 1.0641282565130261, 1.0821643286573146, 1.1002004008016033, 1.1182364729458918, 1.1362725450901803, 1.154308617234469, 1.1723446893787575, 1.1903807615230462, 1.2084168336673347, 1.2264529058116231, 1.2444889779559118, 1.2625250501002003, 1.280561122244489, 1.2985971943887775, 1.3166332665330662, 1.3346693386773547, 1.3527054108216432, 1.370741482965932, 1.3887775551102204, 1.406813627254509, 1.4248496993987976, 1.4428857715430863, 1.4609218436873748, 1.4789579158316633, 1.496993987975952, 1.5150300601202404, 1.5330661322645291, 1.5511022044088176, 1.5691382765531061, 1.5871743486973948, 1.6052104208416833, 1.623246492985972, 1.6412825651302605, 1.6593186372745492, 1.6773547094188377, 1.6953907815631262, 1.7134268537074149, 1.7314629258517034, 1.749498997995992, 1.7675350701402806, 1.785571142284569, 1.8036072144288577, 1.8216432865731462, 1.839679358717435, 1.8577154308617234, 1.8757515030060121, 1.8937875751503006, 1.911823647294589, 1.9298597194388778, 1.9478957915831663, 1.965931863727455, 1.9839679358717435, 2.002004008016032, 2.0200400801603204, 2.038076152304609, 2.056112224448898, 2.0741482965931866, 2.092184368737475, 2.1102204408817635, 2.1282565130260522, 2.1462925851703405, 2.164328657314629, 2.182364729458918, 2.2004008016032066, 2.218436873747495, 2.2364729458917836, 2.2545090180360723, 2.2725450901803605, 2.2905811623246493, 2.308617234468938, 2.3266533066132267, 2.344689378757515, 2.3627254509018036, 2.3807615230460923, 2.3987975951903806, 2.4168336673346693, 2.434869739478958, 2.4529058116232463, 2.470941883767535, 2.4889779559118237, 2.5070140280561124, 2.5250501002004007, 2.5430861723446894, 2.561122244488978, 2.5791583166332663, 2.597194388777555, 2.6152304609218437, 2.6332665330661325, 2.6513026052104207, 2.6693386773547094, 2.687374749498998, 2.7054108216432864, 2.723446893787575, 2.741482965931864, 2.7595190380761525, 2.7775551102204408, 2.7955911823647295, 2.813627254509018, 2.8316633266533064, 2.849699398797595, 2.867735470941884, 2.8857715430861726, 2.903807615230461, 2.9218436873747495, 2.9398797595190382, 2.9579158316633265, 2.975951903807615, 2.993987975951904, 3.012024048096192, 3.030060120240481, 3.0480961923847696, 3.0661322645290583, 3.0841683366733466, 3.1022044088176353, 3.120240480961924, 3.1382765531062122, 3.156312625250501, 3.1743486973947896, 3.1923847695390783, 3.2104208416833666, 3.2284569138276553, 3.246492985971944, 3.2645290581162323, 3.282565130260521, 3.3006012024048097, 3.3186372745490984, 3.3366733466933867, 3.3547094188376754, 3.372745490981964, 3.3907815631262523, 3.408817635270541, 3.4268537074148298, 3.444889779559118, 3.4629258517034067, 3.4809619238476954, 3.498997995991984, 3.5170340681362724, 3.535070140280561, 3.55310621242485, 3.571142284569138, 3.5891783567134268, 3.6072144288577155, 3.625250501002004, 3.6432865731462925, 3.661322645290581, 3.67935871743487, 3.697394789579158, 3.715430861723447, 3.7334669338677355, 3.7515030060120242, 3.7695390781563125, 3.787575150300601, 3.80561122244489, 3.823647294589178, 3.841683366733467, 3.8597194388777556, 3.8777555110220443, 3.8957915831663326, 3.9138276553106213, 3.93186372745491, 3.9498997995991982, 3.967935871743487, 3.9859719438877756, 4.004008016032064, 4.022044088176353, 4.040080160320641, 4.05811623246493, 4.076152304609218, 4.094188376753507, 4.112224448897796, 4.130260521042084, 4.148296593186373, 4.166332665330661, 4.18436873747495, 4.202404809619239, 4.220440881763527, 4.238476953907815, 4.2565130260521045, 4.274549098196393, 4.292585170340681, 4.31062124248497, 4.328657314629258, 4.346693386773547, 4.364729458917836, 4.382765531062124, 4.400801603206413, 4.4188376753507015, 4.43687374749499, 4.454909819639279, 4.472945891783567, 4.490981963927855, 4.509018036072145, 4.527054108216433, 4.545090180360721, 4.56312625250501, 4.5811623246492985, 4.599198396793587, 4.617234468937876, 4.635270541082164, 4.653306613226453, 4.671342685370742, 4.68937875751503, 4.707414829659319, 4.725450901803607, 4.7434869739478955, 4.761523046092185, 4.779559118236473, 4.797595190380761, 4.81563126252505, 4.833667334669339, 4.851703406813627, 4.869739478957916, 4.887775551102204, 4.905811623246493, 4.923847695390782, 4.94188376753507, 4.959919839679359, 4.977955911823647, 4.995991983967936, 5.014028056112225, 5.032064128256513, 5.050100200400801, 5.0681362725450905, 5.086172344689379, 5.104208416833667, 5.122244488977956, 5.140280561122244, 5.158316633266533, 5.176352705410822, 5.19438877755511, 5.212424849699399, 5.2304609218436875, 5.248496993987976, 5.266533066132265, 5.284569138276553, 5.302605210420841, 5.320641282565131, 5.338677354709419, 5.356713426853707, 5.374749498997996, 5.3927855711422845, 5.410821643286573, 5.428857715430862, 5.44689378757515, 5.4649298597194385, 5.482965931863728, 5.501002004008016, 5.519038076152305, 5.537074148296593, 5.5551102204408815, 5.573146292585171, 5.591182364729459, 5.609218436873747, 5.627254509018036, 5.645290581162325, 5.663326653306613, 5.681362725450902, 5.69939879759519, 5.717434869739479, 5.735470941883768, 5.753507014028056, 5.771543086172345, 5.789579158316633, 5.807615230460922, 5.825651302605211, 5.843687374749499, 5.861723446893787, 5.8797595190380765, 5.897795591182365, 5.915831663326653, 5.933867735470942, 5.95190380761523, 5.969939879759519, 5.987975951903808, 6.006012024048096, 6.024048096192384, 6.0420841683366735, 6.060120240480962, 6.078156312625251, 6.096192384769539, 6.114228456913827, 6.132264529058117, 6.150300601202405, 6.168336673346693, 6.186372745490982, 6.2044088176352705, 6.222444889779559, 6.240480961923848, 6.258517034068136, 6.2765531062124245, 6.294589178356714, 6.312625250501002, 6.330661322645291, 6.348697394789579, 6.3667334669338675, 6.384769539078157, 6.402805611222445, 6.420841683366733, 6.438877755511022, 6.456913827655311, 6.474949899799599, 6.492985971943888, 6.511022044088176, 6.529058116232465, 6.547094188376754, 6.565130260521042, 6.58316633266533, 6.601202404809619, 6.619238476953908, 6.637274549098197, 6.655310621242485, 6.673346693386773, 6.6913827655310625, 6.709418837675351, 6.727454909819639, 6.745490981963928, 6.763527054108216, 6.781563126252505, 6.799599198396794, 6.817635270541082, 6.83567134268537, 6.8537074148296595, 6.871743486973948, 6.889779559118236, 6.907815631262525, 6.925851703406813, 6.943887775551103, 6.961923847695391, 6.979959919839679, 6.997995991983968, 7.0160320641282565, 7.034068136272545, 7.052104208416834, 7.070140280561122, 7.0881763527054105, 7.1062124248497, 7.124248496993988, 7.142284569138276, 7.160320641282565, 7.1783567134268536, 7.196392785571143, 7.214428857715431, 7.232464929859719, 7.250501002004008, 7.268537074148297, 7.286573146292585, 7.304609218436874, 7.322645290581162, 7.340681362725451, 7.35871743486974, 7.376753507014028, 7.394789579158316, 7.412825651302605, 7.430861723446894, 7.448897795591182, 7.466933867735471, 7.484969939879759, 7.5030060120240485, 7.521042084168337, 7.539078156312625, 7.557114228456914, 7.575150300601202, 7.593186372745491, 7.61122244488978, 7.629258517034068, 7.647294589178356, 7.6653306613226455, 7.683366733466934, 7.701402805611222, 7.719438877755511, 7.7374749498997994, 7.755511022044089, 7.773547094188377, 7.791583166332665, 7.809619238476954, 7.8276553106212425, 7.845691382765531, 7.86372745490982, 7.881763527054108, 7.8997995991983965, 7.917835671342686, 7.935871743486974, 7.953907815631262, 7.971943887775551, 7.98997995991984, 8.008016032064129, 8.026052104208416, 8.044088176352705, 8.062124248496994, 8.080160320641282, 8.098196392785571, 8.11623246492986, 8.134268537074147, 8.152304609218437, 8.170340681362726, 8.188376753507015, 8.206412825651302, 8.224448897795591, 8.24248496993988, 8.260521042084168, 8.278557114228457, 8.296593186372746, 8.314629258517034, 8.332665330661323, 8.350701402805612, 8.3687374749499, 8.386773547094188, 8.404809619238478, 8.422845691382765, 8.440881763527054, 8.458917835671343, 8.47695390781563, 8.49498997995992, 8.513026052104209, 8.531062124248496, 8.549098196392785, 8.567134268537075, 8.585170340681362, 8.603206412825651, 8.62124248496994, 8.639278557114228, 8.657314629258517, 8.675350701402806, 8.693386773547093, 8.711422845691382, 8.729458917835672, 8.74749498997996, 8.765531062124248, 8.783567134268537, 8.801603206412826, 8.819639278557114, 8.837675350701403, 8.855711422845692, 8.87374749498998, 8.891783567134269, 8.909819639278558, 8.927855711422845, 8.945891783567134, 8.963927855711423, 8.98196392785571, 9.0])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.x = d3.scale.linear()\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.x = d3.scale.linear()\n", " .domain([0.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.legend = L.control({position: 'topright'});\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.legend.addTo(map_ef7357925cb53e53304c4b778d7693b5);\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.legend = L.control({position: 'topright'});\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.legend.addTo(map_9051cbfe5b4c076be108ec9d20e27e42);\n", "\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.xAxis = d3.svg.axis()\n", - " .scale(color_map_6f3d14160ef69676908aa6125eec6ff6.x)\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.xAxis = d3.svg.axis()\n", + " .scale(color_map_1df84f1684aed76bf8aca0832c15525c.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.9176470588235294, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1.8352941176470587, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.7529411764705882, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.6705882352941175, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 4.588235294117647, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.5058823529411764, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 6.423529411764706, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 7.341176470588235, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 8.258823529411766, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.g = color_map_6f3d14160ef69676908aa6125eec6ff6.svg.append("g")\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.g = color_map_1df84f1684aed76bf8aca0832c15525c.svg.append("g")\n", " .attr("class", "key")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.g.selectAll("rect")\n", - " .data(color_map_6f3d14160ef69676908aa6125eec6ff6.color.range().map(function(d, i) {\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.g.selectAll("rect")\n", + " .data(color_map_1df84f1684aed76bf8aca0832c15525c.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_6f3d14160ef69676908aa6125eec6ff6.x(color_map_6f3d14160ef69676908aa6125eec6ff6.color.domain()[i - 1]) : color_map_6f3d14160ef69676908aa6125eec6ff6.x.range()[0],\n", - " x1: i < color_map_6f3d14160ef69676908aa6125eec6ff6.color.domain().length ? color_map_6f3d14160ef69676908aa6125eec6ff6.x(color_map_6f3d14160ef69676908aa6125eec6ff6.color.domain()[i]) : color_map_6f3d14160ef69676908aa6125eec6ff6.x.range()[1],\n", + " x0: i ? color_map_1df84f1684aed76bf8aca0832c15525c.x(color_map_1df84f1684aed76bf8aca0832c15525c.color.domain()[i - 1]) : color_map_1df84f1684aed76bf8aca0832c15525c.x.range()[0],\n", + " x1: i < color_map_1df84f1684aed76bf8aca0832c15525c.color.domain().length ? color_map_1df84f1684aed76bf8aca0832c15525c.x(color_map_1df84f1684aed76bf8aca0832c15525c.color.domain()[i]) : color_map_1df84f1684aed76bf8aca0832c15525c.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -620,129 +905,129 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_6f3d14160ef69676908aa6125eec6ff6.g.call(color_map_6f3d14160ef69676908aa6125eec6ff6.xAxis).append("text")\n", + " color_map_1df84f1684aed76bf8aca0832c15525c.g.call(color_map_1df84f1684aed76bf8aca0832c15525c.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", " .text("stroke_id");\n", " \n", - " function geo_json_a07f9d5ae8a37d823af8862b527e6188_styler(feature) {\n", + " function geo_json_381800b304ce6270e2a875ed29271f7a_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#f7fbff", "fillColor": "#f7fbff", "fillOpacity": 0.5, "weight": 8};\n", " case "1": \n", - " return {"color": "#a1cbe2", "fillColor": "#a1cbe2", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#f1f7fd", "fillColor": "#f1f7fd", "fillOpacity": 0.5, "weight": 8};\n", " case "2": \n", - " return {"color": "#084285", "fillColor": "#084285", "fillOpacity": 0.5, "weight": 8};\n", - " case "3": \n", " return {"color": "#eaf2fb", "fillColor": "#eaf2fb", "fillOpacity": 0.5, "weight": 8};\n", - " case "4": \n", + " case "3": \n", " return {"color": "#e3eef9", "fillColor": "#e3eef9", "fillOpacity": 0.5, "weight": 8};\n", - " case "5": \n", + " case "4": \n", " return {"color": "#dceaf6", "fillColor": "#dceaf6", "fillOpacity": 0.5, "weight": 8};\n", + " case "5": \n", + " return {"color": "#d6e6f4", "fillColor": "#d6e6f4", "fillOpacity": 0.5, "weight": 8};\n", " case "6": \n", - " return {"color": "#0a539e", "fillColor": "#0a539e", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#d0e1f2", "fillColor": "#d0e1f2", "fillOpacity": 0.5, "weight": 8};\n", " case "7": \n", - " return {"color": "#f1f7fd", "fillColor": "#f1f7fd", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#caddf0", "fillColor": "#caddf0", "fillOpacity": 0.5, "weight": 8};\n", " case "8": \n", - " return {"color": "#94c4df", "fillColor": "#94c4df", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#c1d9ed", "fillColor": "#c1d9ed", "fillOpacity": 0.5, "weight": 8};\n", " case "10": \n", - " return {"color": "#79b5d9", "fillColor": "#79b5d9", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#abd0e6", "fillColor": "#abd0e6", "fillOpacity": 0.5, "weight": 8};\n", " case "11": \n", - " return {"color": "#6caed6", "fillColor": "#6caed6", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#a1cbe2", "fillColor": "#a1cbe2", "fillOpacity": 0.5, "weight": 8};\n", " case "12": \n", - " return {"color": "#60a7d2", "fillColor": "#60a7d2", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#94c4df", "fillColor": "#94c4df", "fillOpacity": 0.5, "weight": 8};\n", " case "13": \n", - " return {"color": "#08306b", "fillColor": "#08306b", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#87bddc", "fillColor": "#87bddc", "fillOpacity": 0.5, "weight": 8};\n", " case "14": \n", - " return {"color": "#549fcd", "fillColor": "#549fcd", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#79b5d9", "fillColor": "#79b5d9", "fillOpacity": 0.5, "weight": 8};\n", " case "15": \n", - " return {"color": "#d6e6f4", "fillColor": "#d6e6f4", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#6caed6", "fillColor": "#6caed6", "fillOpacity": 0.5, "weight": 8};\n", " case "16": \n", - " return {"color": "#105ba4", "fillColor": "#105ba4", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#60a7d2", "fillColor": "#60a7d2", "fillOpacity": 0.5, "weight": 8};\n", " case "17": \n", - " return {"color": "#d0e1f2", "fillColor": "#d0e1f2", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#549fcd", "fillColor": "#549fcd", "fillOpacity": 0.5, "weight": 8};\n", " case "18": \n", - " return {"color": "#caddf0", "fillColor": "#caddf0", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#4a98c9", "fillColor": "#4a98c9", "fillOpacity": 0.5, "weight": 8};\n", " case "19": \n", - " return {"color": "#c1d9ed", "fillColor": "#c1d9ed", "fillOpacity": 0.5, "weight": 8};\n", - " case "20": \n", " return {"color": "#3f8fc5", "fillColor": "#3f8fc5", "fillOpacity": 0.5, "weight": 8};\n", + " case "20": \n", + " return {"color": "#3787c0", "fillColor": "#3787c0", "fillOpacity": 0.5, "weight": 8};\n", " case "21": \n", " return {"color": "#2e7ebc", "fillColor": "#2e7ebc", "fillOpacity": 0.5, "weight": 8};\n", " case "22": \n", - " return {"color": "#b7d4ea", "fillColor": "#b7d4ea", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#2575b7", "fillColor": "#2575b7", "fillOpacity": 0.5, "weight": 8};\n", " case "23": \n", - " return {"color": "#1764ab", "fillColor": "#1764ab", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#1d6cb1", "fillColor": "#1d6cb1", "fillOpacity": 0.5, "weight": 8};\n", " case "24": \n", - " return {"color": "#084a91", "fillColor": "#084a91", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#1764ab", "fillColor": "#1764ab", "fillOpacity": 0.5, "weight": 8};\n", " case "25": \n", - " return {"color": "#abd0e6", "fillColor": "#abd0e6", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#105ba4", "fillColor": "#105ba4", "fillOpacity": 0.5, "weight": 8};\n", " case "26": \n", - " return {"color": "#2575b7", "fillColor": "#2575b7", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#0a539e", "fillColor": "#0a539e", "fillOpacity": 0.5, "weight": 8};\n", " case "27": \n", - " return {"color": "#083877", "fillColor": "#083877", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#084a91", "fillColor": "#084a91", "fillOpacity": 0.5, "weight": 8};\n", " case "28": \n", - " return {"color": "#87bddc", "fillColor": "#87bddc", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#084285", "fillColor": "#084285", "fillOpacity": 0.5, "weight": 8};\n", " case "29": \n", - " return {"color": "#4a98c9", "fillColor": "#4a98c9", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#083877", "fillColor": "#083877", "fillOpacity": 0.5, "weight": 8};\n", " case "30": \n", - " return {"color": "#1d6cb1", "fillColor": "#1d6cb1", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#08306b", "fillColor": "#08306b", "fillOpacity": 0.5, "weight": 8};\n", " default:\n", - " return {"color": "#3787c0", "fillColor": "#3787c0", "fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#b7d4ea", "fillColor": "#b7d4ea", "fillOpacity": 0.5, "weight": 8};\n", " }\n", " }\n", - " function geo_json_a07f9d5ae8a37d823af8862b527e6188_highlighter(feature) {\n", + " function geo_json_381800b304ce6270e2a875ed29271f7a_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_a07f9d5ae8a37d823af8862b527e6188_pointToLayer(feature, latlng) {\n", + " function geo_json_381800b304ce6270e2a875ed29271f7a_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_a07f9d5ae8a37d823af8862b527e6188_styler(feature)\n", + " let style = geo_json_381800b304ce6270e2a875ed29271f7a_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_a07f9d5ae8a37d823af8862b527e6188_onEachFeature(feature, layer) {\n", + " function geo_json_381800b304ce6270e2a875ed29271f7a_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_a07f9d5ae8a37d823af8862b527e6188.resetStyle(e.target);\n", + " geo_json_381800b304ce6270e2a875ed29271f7a.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_a07f9d5ae8a37d823af8862b527e6188_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_381800b304ce6270e2a875ed29271f7a_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_a07f9d5ae8a37d823af8862b527e6188 = L.geoJson(null, {\n", - " onEachFeature: geo_json_a07f9d5ae8a37d823af8862b527e6188_onEachFeature,\n", + " var geo_json_381800b304ce6270e2a875ed29271f7a = L.geoJson(null, {\n", + " onEachFeature: geo_json_381800b304ce6270e2a875ed29271f7a_onEachFeature,\n", " \n", - " style: geo_json_a07f9d5ae8a37d823af8862b527e6188_styler,\n", - " pointToLayer: geo_json_a07f9d5ae8a37d823af8862b527e6188_pointToLayer,\n", + " style: geo_json_381800b304ce6270e2a875ed29271f7a_styler,\n", + " pointToLayer: geo_json_381800b304ce6270e2a875ed29271f7a_pointToLayer,\n", " });\n", "\n", - " function geo_json_a07f9d5ae8a37d823af8862b527e6188_add (data) {\n", - " geo_json_a07f9d5ae8a37d823af8862b527e6188\n", + " function geo_json_381800b304ce6270e2a875ed29271f7a_add (data) {\n", + " geo_json_381800b304ce6270e2a875ed29271f7a\n", " .addData(data);\n", " }\n", - " geo_json_a07f9d5ae8a37d823af8862b527e6188_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#f7fbff", "edge_id": 0, "mm_len": 264.1039496246775, "node_end": 1, "node_start": 0}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#a1cbe2", "edge_id": 11, "mm_len": 88.92430548419476, "node_end": 13, "node_start": 0}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#084285", "edge_id": 28, "mm_len": 138.23490844748363, "node_end": 23, "node_start": 0}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#eaf2fb", "edge_id": 2, "mm_len": 199.74650338337847, "node_end": 4, "node_start": 1}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#e3eef9", "edge_id": 3, "mm_len": 203.01409000575802, "node_end": 3, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#dceaf6", "edge_id": 4, "mm_len": 198.48272399064462, "node_end": 5, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#0a539e", "edge_id": 26, "mm_len": 382.50195042922803, "node_end": 21, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#f1f7fd", "edge_id": 1, "mm_len": 99.75118962647376, "node_end": 3, "node_start": 2}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#94c4df", "edge_id": 12, "mm_len": 107.88014814146449, "node_end": 5, "node_start": 2}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#3787c0", "edge_id": 20, "mm_len": 182.6849740039611, "node_end": 18, "node_start": 2}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "#79b5d9", "edge_id": 14, "mm_len": 200.30351738673852, "node_end": 16, "node_start": 3}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "#6caed6", "edge_id": 15, "mm_len": 200.3861708266132, "node_end": 10, "node_start": 3}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "#60a7d2", "edge_id": 16, "mm_len": 191.66755798860544, "node_end": 13, "node_start": 4}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "#08306b", "edge_id": 30, "mm_len": 317.85221640975095, "node_end": 13, "node_start": 4}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "#549fcd", "edge_id": 17, "mm_len": 202.03167967950094, "node_end": 16, "node_start": 4}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "#d6e6f4", "edge_id": 5, "mm_len": 200.61768541143937, "node_end": 6, "node_start": 5}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "#105ba4", "edge_id": 25, "mm_len": 351.1551873514152, "node_end": 20, "node_start": 5}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "17", "properties": {"__folium_color": "#d0e1f2", "edge_id": 6, "mm_len": 163.14628203947333, "node_end": 7, "node_start": 6}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "18", "properties": {"__folium_color": "#caddf0", "edge_id": 7, "mm_len": 193.51137206831748, "node_end": 8, "node_start": 6}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"__folium_color": "#c1d9ed", "edge_id": 8, "mm_len": 127.80086449751786, "node_end": 9, "node_start": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "20", "properties": {"__folium_color": "#3f8fc5", "edge_id": 19, "mm_len": 187.49184699173748, "node_end": 17, "node_start": 9}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"__folium_color": "#2e7ebc", "edge_id": 21, "mm_len": 72.91516907666792, "node_end": 18, "node_start": 9}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"__folium_color": "#b7d4ea", "edge_id": 9, "mm_len": 122.5319618088215, "node_end": 11, "node_start": 10}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "23", "properties": {"__folium_color": "#1764ab", "edge_id": 24, "mm_len": 201.4861168351184, "node_end": 14, "node_start": 10}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "24", "properties": {"__folium_color": "#084a91", "edge_id": 27, "mm_len": 172.0624733749828, "node_end": 22, "node_start": 10}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "25", "properties": {"__folium_color": "#abd0e6", "edge_id": 10, "mm_len": 193.04063727323836, "node_end": 12, "node_start": 11}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "26", "properties": {"__folium_color": "#2575b7", "edge_id": 22, "mm_len": 76.42465276315266, "node_end": 18, "node_start": 11}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "27", "properties": {"__folium_color": "#083877", "edge_id": 29, "mm_len": 255.8228880811063, "node_end": 24, "node_start": 13}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "28", "properties": {"__folium_color": "#87bddc", "edge_id": 13, "mm_len": 282.6905386499787, "node_end": 15, "node_start": 14}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "29", "properties": {"__folium_color": "#4a98c9", "edge_id": 18, "mm_len": 201.30697205908257, "node_end": 16, "node_start": 14}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "30", "properties": {"__folium_color": "#1d6cb1", "edge_id": 23, "mm_len": 168.88041067114747, "node_end": 19, "node_start": 14}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_381800b304ce6270e2a875ed29271f7a_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#f7fbff", "mm_len": 264.1039496246775, "my_index": 0, "node_end": 1, "node_start": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#f1f7fd", "mm_len": 99.75118962647376, "my_index": 1, "node_end": 3, "node_start": 2}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#eaf2fb", "mm_len": 199.74650338337847, "my_index": 2, "node_end": 4, "node_start": 1}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#e3eef9", "mm_len": 203.01409000575802, "my_index": 3, "node_end": 3, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#dceaf6", "mm_len": 198.48272399064462, "my_index": 4, "node_end": 5, "node_start": 1}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#d6e6f4", "mm_len": 200.61768541143937, "my_index": 5, "node_end": 6, "node_start": 5}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#d0e1f2", "mm_len": 163.14628203947333, "my_index": 6, "node_end": 7, "node_start": 6}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#caddf0", "mm_len": 193.51137206831748, "my_index": 7, "node_end": 8, "node_start": 6}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#c1d9ed", "mm_len": 127.80086449751786, "my_index": 8, "node_end": 9, "node_start": 6}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#b7d4ea", "mm_len": 122.5319618088215, "my_index": 9, "node_end": 11, "node_start": 10}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "#abd0e6", "mm_len": 193.04063727323836, "my_index": 10, "node_end": 12, "node_start": 11}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "#a1cbe2", "mm_len": 88.92430548419476, "my_index": 11, "node_end": 13, "node_start": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "#94c4df", "mm_len": 107.88014814146449, "my_index": 12, "node_end": 5, "node_start": 2}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "#87bddc", "mm_len": 282.6905386499787, "my_index": 13, "node_end": 15, "node_start": 14}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "#79b5d9", "mm_len": 200.30351738673852, "my_index": 14, "node_end": 16, "node_start": 3}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "#6caed6", "mm_len": 200.3861708266132, "my_index": 15, "node_end": 10, "node_start": 3}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "#60a7d2", "mm_len": 191.66755798860544, "my_index": 16, "node_end": 13, "node_start": 4}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"__folium_color": "#549fcd", "mm_len": 202.03167967950094, "my_index": 17, "node_end": 16, "node_start": 4}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"__folium_color": "#4a98c9", "mm_len": 201.30697205908257, "my_index": 18, "node_end": 16, "node_start": 14}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"__folium_color": "#3f8fc5", "mm_len": 187.49184699173748, "my_index": 19, "node_end": 17, "node_start": 9}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"__folium_color": "#3787c0", "mm_len": 182.6849740039611, "my_index": 20, "node_end": 18, "node_start": 2}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"__folium_color": "#2e7ebc", "mm_len": 72.91516907666792, "my_index": 21, "node_end": 18, "node_start": 9}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"__folium_color": "#2575b7", "mm_len": 76.42465276315266, "my_index": 22, "node_end": 18, "node_start": 11}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"__folium_color": "#1d6cb1", "mm_len": 168.88041067114747, "my_index": 23, "node_end": 19, "node_start": 14}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"__folium_color": "#1764ab", "mm_len": 201.4861168351184, "my_index": 24, "node_end": 14, "node_start": 10}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"__folium_color": "#105ba4", "mm_len": 351.1551873514152, "my_index": 25, "node_end": 20, "node_start": 5}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"__folium_color": "#0a539e", "mm_len": 382.50195042922803, "my_index": 26, "node_end": 21, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"__folium_color": "#084a91", "mm_len": 172.0624733749828, "my_index": 27, "node_end": 22, "node_start": 10}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"__folium_color": "#084285", "mm_len": 138.23490844748363, "my_index": 28, "node_end": 23, "node_start": 0}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"__folium_color": "#083877", "mm_len": 255.8228880811063, "my_index": 29, "node_end": 24, "node_start": 13}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"__folium_color": "#08306b", "mm_len": 317.85221640975095, "my_index": 30, "node_end": 13, "node_start": 4}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_a07f9d5ae8a37d823af8862b527e6188.bindTooltip(\n", + " geo_json_381800b304ce6270e2a875ed29271f7a.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", " let handleObject = feature=>typeof(feature)=='object' ? JSON.stringify(feature) : feature;\n", - " let fields = ["edge_id", "mm_len", "node_start", "node_end"];\n", - " let aliases = ["edge_id", "mm_len", "node_start", "node_end"];\n", + " let fields = ["mm_len", "node_start", "node_end", "my_index"];\n", + " let aliases = ["mm_len", "node_start", "node_end", "my_index"];\n", " let table = '<table>' +\n", " String(\n", " fields.map(\n", @@ -760,45 +1045,45 @@ " ,{"className": "foliumtooltip", "sticky": true});\n", " \n", " \n", - " geo_json_a07f9d5ae8a37d823af8862b527e6188.addTo(map_ef7357925cb53e53304c4b778d7693b5);\n", + " geo_json_381800b304ce6270e2a875ed29271f7a.addTo(map_9051cbfe5b4c076be108ec9d20e27e42);\n", " \n", " \n", - " var color_map_8424586fdb62868ff228abdfe0ff0bc5 = {};\n", + " var color_map_e983af2216d0ab651a2d7db296a715ed = {};\n", "\n", " \n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.color = d3.scale.threshold()\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.color = d3.scale.threshold()\n", " .domain([0.0, 0.06012024048096192, 0.12024048096192384, 0.18036072144288579, 0.24048096192384769, 0.30060120240480964, 0.36072144288577157, 0.42084168336673344, 0.48096192384769537, 0.5410821643286573, 0.6012024048096193, 0.6613226452905812, 0.7214428857715431, 0.781563126252505, 0.8416833667334669, 0.9018036072144289, 0.9619238476953907, 1.0220440881763526, 1.0821643286573146, 1.1422845691382766, 1.2024048096192386, 1.2625250501002003, 1.3226452905811623, 1.3827655310621243, 1.4428857715430863, 1.503006012024048, 1.56312625250501, 1.623246492985972, 1.6833667334669338, 1.7434869739478958, 1.8036072144288577, 1.8637274549098197, 1.9238476953907815, 1.9839679358717435, 2.0440881763527052, 2.1042084168336674, 2.164328657314629, 2.224448897795591, 2.284569138276553, 2.344689378757515, 2.404809619238477, 2.464929859719439, 2.5250501002004007, 2.585170340681363, 2.6452905811623246, 2.7054108216432864, 2.7655310621242486, 2.8256513026052104, 2.8857715430861726, 2.9458917835671343, 3.006012024048096, 3.0661322645290583, 3.12625250501002, 3.186372745490982, 3.246492985971944, 3.306613226452906, 3.3667334669338675, 3.4268537074148298, 3.4869739478957915, 3.5470941883767537, 3.6072144288577155, 3.6673346693386772, 3.7274549098196395, 3.787575150300601, 3.847695390781563, 3.907815631262525, 3.967935871743487, 4.028056112224449, 4.0881763527054105, 4.148296593186373, 4.208416833667335, 4.268537074148297, 4.328657314629258, 4.38877755511022, 4.448897795591182, 4.509018036072145, 4.569138276553106, 4.629258517034068, 4.68937875751503, 4.749498997995992, 4.809619238476954, 4.869739478957916, 4.929859719438878, 4.98997995991984, 5.050100200400801, 5.110220440881764, 5.170340681362726, 5.2304609218436875, 5.290581162324649, 5.350701402805611, 5.410821643286573, 5.470941883767535, 5.531062124248497, 5.591182364729459, 5.651302605210421, 5.7114228456913825, 5.771543086172345, 5.831663326653307, 5.891783567134269, 5.95190380761523, 6.012024048096192, 6.072144288577154, 6.132264529058117, 6.192384769539078, 6.25250501002004, 6.312625250501002, 6.372745490981964, 6.432865731462926, 6.492985971943888, 6.55310621242485, 6.613226452905812, 6.673346693386773, 6.733466933867735, 6.793587174348698, 6.8537074148296595, 6.913827655310621, 6.973947895791583, 7.034068136272545, 7.094188376753507, 7.154308617234469, 7.214428857715431, 7.274549098196393, 7.3346693386773545, 7.394789579158316, 7.454909819639279, 7.515030060120241, 7.575150300601202, 7.635270541082164, 7.695390781563126, 7.755511022044089, 7.81563126252505, 7.875751503006012, 7.935871743486974, 7.995991983967936, 8.056112224448897, 8.11623246492986, 8.176352705410821, 8.236472945891784, 8.296593186372746, 8.356713426853707, 8.41683366733467, 8.47695390781563, 8.537074148296593, 8.597194388777556, 8.657314629258517, 8.71743486973948, 8.77755511022044, 8.837675350701403, 8.897795591182364, 8.957915831663327, 9.01803607214429, 9.07815631262525, 9.138276553106213, 9.198396793587174, 9.258517034068136, 9.318637274549099, 9.37875751503006, 9.438877755511022, 9.498997995991983, 9.559118236472946, 9.619238476953909, 9.67935871743487, 9.739478957915832, 9.799599198396793, 9.859719438877756, 9.919839679358718, 9.97995991983968, 10.040080160320642, 10.100200400801603, 10.160320641282565, 10.220440881763528, 10.280561122244489, 10.340681362725451, 10.400801603206412, 10.460921843687375, 10.521042084168336, 10.581162324649299, 10.641282565130261, 10.701402805611222, 10.761523046092185, 10.821643286573146, 10.881763527054108, 10.94188376753507, 11.002004008016032, 11.062124248496994, 11.122244488977955, 11.182364729458918, 11.24248496993988, 11.302605210420841, 11.362725450901804, 11.422845691382765, 11.482965931863728, 11.54308617234469, 11.603206412825651, 11.663326653306614, 11.723446893787575, 11.783567134268537, 11.843687374749498, 11.90380761523046, 11.963927855711423, 12.024048096192384, 12.084168336673347, 12.144288577154308, 12.20440881763527, 12.264529058116233, 12.324649298597194, 12.384769539078157, 12.444889779559118, 12.50501002004008, 12.565130260521043, 12.625250501002004, 12.685370741482966, 12.745490981963927, 12.80561122244489, 12.865731462925853, 12.925851703406813, 12.985971943887776, 13.046092184368737, 13.1062124248497, 13.16633266533066, 13.226452905811623, 13.286573146292586, 13.346693386773547, 13.40681362725451, 13.46693386773547, 13.527054108216433, 13.587174348697395, 13.647294589178356, 13.707414829659319, 13.76753507014028, 13.827655310621243, 13.887775551102205, 13.947895791583166, 14.008016032064129, 14.06813627254509, 14.128256513026052, 14.188376753507015, 14.248496993987976, 14.308617234468938, 14.3687374749499, 14.428857715430862, 14.488977955911823, 14.549098196392785, 14.609218436873748, 14.669338677354709, 14.729458917835672, 14.789579158316633, 14.849699398797595, 14.909819639278558, 14.969939879759519, 15.030060120240481, 15.090180360721442, 15.150300601202405, 15.210420841683367, 15.270541082164328, 15.330661322645291, 15.390781563126252, 15.450901803607215, 15.511022044088177, 15.571142284569138, 15.6312625250501, 15.691382765531062, 15.751503006012024, 15.811623246492985, 15.871743486973948, 15.93186372745491, 15.991983967935871, 16.052104208416832, 16.112224448897795, 16.172344689378757, 16.23246492985972, 16.292585170340683, 16.352705410821642, 16.412825651302605, 16.472945891783567, 16.53306613226453, 16.593186372745492, 16.65330661322645, 16.713426853707414, 16.773547094188377, 16.83366733466934, 16.893787575150302, 16.95390781563126, 17.014028056112224, 17.074148296593187, 17.13426853707415, 17.194388777555112, 17.25450901803607, 17.314629258517034, 17.374749498997996, 17.43486973947896, 17.49498997995992, 17.55511022044088, 17.615230460921843, 17.675350701402806, 17.73547094188377, 17.795591182364728, 17.85571142284569, 17.915831663326653, 17.975951903807616, 18.03607214428858, 18.096192384769537, 18.1563126252505, 18.216432865731463, 18.276553106212425, 18.336673346693388, 18.396793587174347, 18.45691382765531, 18.517034068136272, 18.577154308617235, 18.637274549098198, 18.697394789579157, 18.75751503006012, 18.817635270541082, 18.877755511022045, 18.937875751503007, 18.997995991983966, 19.05811623246493, 19.118236472945892, 19.178356713426854, 19.238476953907817, 19.298597194388776, 19.35871743486974, 19.4188376753507, 19.478957915831664, 19.539078156312627, 19.599198396793586, 19.65931863727455, 19.71943887775551, 19.779559118236474, 19.839679358717436, 19.899799599198396, 19.95991983967936, 20.02004008016032, 20.080160320641284, 20.140280561122246, 20.200400801603205, 20.260521042084168, 20.32064128256513, 20.380761523046093, 20.440881763527056, 20.501002004008015, 20.561122244488978, 20.62124248496994, 20.681362725450903, 20.741482965931862, 20.801603206412825, 20.861723446893787, 20.92184368737475, 20.981963927855713, 21.04208416833667, 21.102204408817634, 21.162324649298597, 21.22244488977956, 21.282565130260522, 21.34268537074148, 21.402805611222444, 21.462925851703407, 21.52304609218437, 21.583166332665332, 21.64328657314629, 21.703406813627254, 21.763527054108216, 21.82364729458918, 21.88376753507014, 21.9438877755511, 22.004008016032063, 22.064128256513026, 22.12424849699399, 22.18436873747495, 22.24448897795591, 22.304609218436873, 22.364729458917836, 22.4248496993988, 22.48496993987976, 22.54509018036072, 22.605210420841683, 22.665330661322646, 22.725450901803608, 22.78557114228457, 22.84569138276553, 22.905811623246493, 22.965931863727455, 23.026052104208418, 23.08617234468938, 23.14629258517034, 23.206412825651302, 23.266533066132265, 23.326653306613228, 23.386773547094187, 23.44689378757515, 23.507014028056112, 23.567134268537075, 23.627254509018037, 23.687374749498996, 23.74749498997996, 23.80761523046092, 23.867735470941884, 23.927855711422847, 23.987975951903806, 24.04809619238477, 24.10821643286573, 24.168336673346694, 24.228456913827657, 24.288577154308616, 24.34869739478958, 24.40881763527054, 24.468937875751504, 24.529058116232466, 24.589178356713425, 24.649298597194388, 24.70941883767535, 24.769539078156313, 24.829659318637276, 24.889779559118235, 24.949899799599198, 25.01002004008016, 25.070140280561123, 25.130260521042086, 25.190380761523045, 25.250501002004007, 25.31062124248497, 25.370741482965933, 25.430861723446895, 25.490981963927855, 25.551102204408817, 25.61122244488978, 25.671342685370742, 25.731462925851705, 25.791583166332664, 25.851703406813627, 25.91182364729459, 25.971943887775552, 26.03206412825651, 26.092184368737474, 26.152304609218437, 26.2124248496994, 26.272545090180362, 26.33266533066132, 26.392785571142284, 26.452905811623246, 26.51302605210421, 26.57314629258517, 26.63326653306613, 26.693386773547093, 26.753507014028056, 26.81362725450902, 26.87374749498998, 26.93386773547094, 26.993987975951903, 27.054108216432866, 27.11422845691383, 27.17434869739479, 27.23446893787575, 27.294589178356713, 27.354709418837675, 27.414829659318638, 27.4749498997996, 27.53507014028056, 27.595190380761522, 27.655310621242485, 27.715430861723448, 27.77555110220441, 27.83567134268537, 27.895791583166332, 27.955911823647295, 28.016032064128257, 28.07615230460922, 28.13627254509018, 28.196392785571142, 28.256513026052104, 28.316633266533067, 28.37675350701403, 28.43687374749499, 28.49699398797595, 28.557114228456914, 28.617234468937877, 28.677354709418836, 28.7374749498998, 28.79759519038076, 28.857715430861724, 28.917835671342687, 28.977955911823646, 29.03807615230461, 29.09819639278557, 29.158316633266534, 29.218436873747496, 29.278557114228455, 29.338677354709418, 29.39879759519038, 29.458917835671343, 29.519038076152306, 29.579158316633265, 29.639278557114228, 29.69939879759519, 29.759519038076153, 29.819639278557116, 29.879759519038075, 29.939879759519037, 30.0])\n", " .range(['#f7fbffff', '#f7fbffff', '#f6faffff', '#f6faffff', '#f5fafeff', '#f5fafeff', '#f5f9feff', '#f5f9feff', '#f4f9feff', '#f4f9feff', '#f3f8feff', '#f3f8feff', '#f2f8fdff', '#f2f8fdff', '#f2f7fdff', '#f2f7fdff', '#f1f7fdff', '#f1f7fdff', '#f0f6fdff', '#f0f6fdff', '#eff6fcff', '#eff6fcff', '#eef5fcff', '#eef5fcff', '#eef5fcff', '#eef5fcff', '#edf4fcff', '#edf4fcff', '#ecf4fbff', '#ecf4fbff', '#ebf3fbff', '#ebf3fbff', '#eaf3fbff', '#eaf3fbff', '#eaf2fbff', '#eaf2fbff', '#e9f2faff', '#e9f2faff', '#e8f1faff', '#e7f1faff', '#e7f1faff', '#e7f0faff', '#e7f0faff', '#e6f0faff', '#e6f0f9ff', '#e5eff9ff', '#e5eff9ff', '#e4eff9ff', '#e4eff9ff', '#e3eef9ff', '#e3eef9ff', '#e3eef8ff', '#e3eef8ff', '#e2edf8ff', '#e2edf8ff', '#e1edf8ff', '#e1edf8ff', '#e0ecf8ff', '#e0ecf8ff', '#dfecf7ff', '#dfecf7ff', '#dfebf7ff', '#dfebf7ff', '#deebf7ff', '#deebf7ff', '#ddeaf7ff', '#ddeaf7ff', '#dceaf6ff', '#dceaf6ff', '#dce9f6ff', '#dce9f6ff', '#dbe9f6ff', '#dbe9f6ff', '#dae8f6ff', '#dae8f6ff', '#d9e8f5ff', '#d9e8f5ff', '#d9e7f5ff', '#d8e7f5ff', '#d8e7f5ff', '#d7e7f5ff', '#d7e6f5ff', '#d6e6f5ff', '#d6e6f4ff', '#d6e5f4ff', '#d6e5f4ff', '#d5e5f4ff', '#d5e5f4ff', '#d4e4f4ff', '#d4e4f4ff', '#d3e4f3ff', '#d3e4f3ff', '#d3e3f3ff', '#d3e3f3ff', '#d2e3f3ff', '#d2e3f3ff', '#d1e2f3ff', '#d1e2f3ff', '#d0e2f2ff', '#d0e2f2ff', '#d0e1f2ff', '#d0e1f2ff', '#cfe1f2ff', '#cfe1f2ff', '#cee0f2ff', '#cee0f2ff', '#cde0f1ff', '#cde0f1ff', '#cddff1ff', '#cddff1ff', '#ccdff1ff', '#ccdff1ff', '#cbdef1ff', '#cbdef1ff', '#cadef0ff', '#cadef0ff', '#caddf0ff', '#c9ddf0ff', '#c9ddf0ff', '#c8ddf0ff', '#c8dcf0ff', '#c7dcf0ff', '#c7dcefff', '#c7dcefff', '#c7dbefff', '#c6dbefff', '#c5dbefff', '#c4daefff', '#c4daeeff', '#c3daeeff', '#c3daeeff', '#c2d9eeff', '#c2d9eeff', '#c1d9edff', '#c0d9edff', '#bfd8edff', '#bfd8edff', '#bed8ecff', '#bed8ecff', '#bdd7ecff', '#bdd7ecff', '#bcd7ebff', '#bbd7ebff', '#bad6ebff', '#bad6ebff', '#b9d6eaff', '#b9d6eaff', '#b8d5eaff', '#b8d5eaff', '#b7d4eaff', '#b6d4eaff', '#b5d4e9ff', '#b5d4e9ff', '#b4d3e9ff', '#b4d3e9ff', '#b3d3e8ff', '#b2d3e8ff', '#b2d2e8ff', '#b1d2e8ff', '#b0d2e7ff', '#afd2e7ff', '#afd1e7ff', '#aed1e7ff', '#aed1e7ff', '#add1e7ff', '#add0e6ff', '#acd0e6ff', '#abd0e6ff', '#aacfe6ff', '#aacfe5ff', '#a9cfe5ff', '#a9cfe5ff', '#a8cee4ff', '#a7cee4ff', '#a6cee4ff', '#a6cee4ff', '#a5cde3ff', '#a5cde3ff', '#a4cce3ff', '#a4cce3ff', '#a3cce3ff', '#a2cce3ff', '#a1cbe2ff', '#a1cbe2ff', '#a0cbe2ff', '#a0cbe2ff', '#9fcae1ff', '#9ecae1ff', '#9dcae1ff', '#9dcae1ff', '#9cc9e1ff', '#9bc9e1ff', '#9ac8e0ff', '#99c8e0ff', '#99c7e0ff', '#98c7e0ff', '#97c6dfff', '#96c6dfff', '#95c5dfff', '#94c5dfff', '#94c4dfff', '#93c4dfff', '#92c4deff', '#91c4deff', '#91c3deff', '#90c3deff', '#8fc2deff', '#8dc1deff', '#8dc1ddff', '#8cc0ddff', '#8bc0ddff', '#8abfddff', '#8abfddff', '#89beddff', '#88bedcff', '#87bddcff', '#86bddcff', '#85bcdcff', '#85bcdcff', '#84bcdbff', '#83bcdbff', '#82bbdbff', '#82bbdbff', '#81badbff', '#80badbff', '#7fb9daff', '#7eb9daff', '#7db8daff', '#7cb8daff', '#7cb7daff', '#7bb7daff', '#7ab6d9ff', '#79b6d9ff', '#79b5d9ff', '#78b5d9ff', '#77b5d9ff', '#76b5d9ff', '#75b4d8ff', '#74b4d8ff', '#74b3d8ff', '#73b3d8ff', '#72b2d8ff', '#71b2d8ff', '#71b1d7ff', '#70b1d7ff', '#6fb0d7ff', '#6eafd7ff', '#6dafd7ff', '#6caed7ff', '#6baed6ff', '#6aaed6ff', '#6aaed6ff', '#69add6ff', '#69add5ff', '#68acd5ff', '#67acd5ff', '#66abd5ff', '#66abd4ff', '#65aad4ff', '#65aad4ff', '#64a9d3ff', '#64a9d3ff', '#63a8d3ff', '#62a8d3ff', '#61a7d2ff', '#60a7d2ff', '#60a7d2ff', '#5fa7d2ff', '#5fa6d1ff', '#5ea6d1ff', '#5da5d1ff', '#5ca5d1ff', '#5ca4d0ff', '#5ba4d0ff', '#5ba3d0ff', '#5aa3d0ff', '#5aa2cfff', '#59a2cfff', '#58a1cfff', '#57a1cfff', '#57a0ceff', '#56a0ceff', '#56a0ceff', '#55a0ceff', '#549fcdff', '#539ecdff', '#539ecdff', '#529dcdff', '#529dccff', '#519cccff', '#509cccff', '#4f9bccff', '#4f9bcbff', '#4e9acbff', '#4e9acbff', '#4d99cbff', '#4c99caff', '#4b98caff', '#4b98caff', '#4a98c9ff', '#4998c9ff', '#4997c9ff', '#4897c9ff', '#4896c8ff', '#4796c8ff', '#4695c8ff', '#4595c8ff', '#4594c7ff', '#4494c7ff', '#4493c7ff', '#4393c7ff', '#4292c6ff', '#4192c6ff', '#4191c6ff', '#4091c6ff', '#4090c5ff', '#3f90c5ff', '#3f8fc5ff', '#3e8fc5ff', '#3e8ec4ff', '#3d8ec4ff', '#3d8dc4ff', '#3c8dc4ff', '#3c8cc3ff', '#3b8bc3ff', '#3b8bc2ff', '#3a8ac2ff', '#3a8ac2ff', '#3989c2ff', '#3989c1ff', '#3888c1ff', '#3888c1ff', '#3787c1ff', '#3787c0ff', '#3686c0ff', '#3686c0ff', '#3585c0ff', '#3485bfff', '#3484bfff', '#3384bfff', '#3383beff', '#3283beff', '#3282beff', '#3182beff', '#3181bdff', '#3081bdff', '#3080bdff', '#2f80bdff', '#2f7fbcff', '#2e7fbcff', '#2e7ebcff', '#2d7ebcff', '#2d7dbbff', '#2c7dbbff', '#2c7cbaff', '#2b7cbaff', '#2b7bbaff', '#2a7bbaff', '#2a7ab9ff', '#297ab9ff', '#2979b9ff', '#2878b9ff', '#2777b8ff', '#2676b8ff', '#2676b8ff', '#2575b8ff', '#2575b7ff', '#2474b7ff', '#2474b7ff', '#2373b7ff', '#2373b6ff', '#2272b6ff', '#2272b6ff', '#2171b6ff', '#2171b5ff', '#2070b5ff', '#2070b4ff', '#206fb4ff', '#1f6fb4ff', '#1f6eb4ff', '#1e6eb3ff', '#1e6db2ff', '#1d6db2ff', '#1d6cb1ff', '#1c6cb1ff', '#1c6bb0ff', '#1c6bb0ff', '#1c6ab0ff', '#1b6ab0ff', '#1b69afff', '#1a69afff', '#1a68aeff', '#1968aeff', '#1967adff', '#1967adff', '#1966adff', '#1866adff', '#1865acff', '#1765acff', '#1764abff', '#1663abff', '#1663aaff', '#1562aaff', '#1562a9ff', '#1561a9ff', '#1561a9ff', '#1460a9ff', '#1460a8ff', '#135fa8ff', '#135fa7ff', '#125ea7ff', '#125ea6ff', '#125da6ff', '#125da6ff', '#115ca6ff', '#105ca5ff', '#105ba5ff', '#0f5ba4ff', '#0f5aa4ff', '#0e5aa3ff', '#0e59a3ff', '#0e59a2ff', '#0e58a2ff', '#0d58a2ff', '#0d57a1ff', '#0c57a1ff', '#0c56a0ff', '#0b56a0ff', '#0b559fff', '#0a559fff', '#0a549eff', '#0a549eff', '#0a539eff', '#09539eff', '#09529dff', '#08529dff', '#08519cff', '#08509cff', '#08509bff', '#084f9aff', '#084f99ff', '#084e99ff', '#084e98ff', '#084d97ff', '#084d96ff', '#084c96ff', '#084c95ff', '#084b94ff', '#084b93ff', '#084a92ff', '#084a91ff', '#084991ff', '#084990ff', '#08488fff', '#08488eff', '#08478eff', '#08478dff', '#08468cff', '#08468bff', '#08458aff', '#08458aff', '#084489ff', '#084488ff', '#084387ff', '#084387ff', '#084286ff', '#084285ff', '#084184ff', '#084184ff', '#084083ff', '#083f82ff', '#083e81ff', '#083e81ff', '#083d80ff', '#083d7fff', '#083c7eff', '#083b7dff', '#083b7cff', '#083a7bff', '#083a7aff', '#08397aff', '#083979ff', '#083878ff', '#083877ff', '#083777ff', '#083776ff', '#083675ff', '#083674ff', '#083574ff', '#083573ff', '#083472ff', '#083471ff', '#083371ff', '#083370ff', '#08326fff', '#08326eff', '#08316dff', '#08316dff', '#08306cff', '#08306bff']);\n", " \n", "\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.x = d3.scale.linear()\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.x = d3.scale.linear()\n", " .domain([0.0, 30.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.legend = L.control({position: 'topright'});\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.legend.addTo(map_ef7357925cb53e53304c4b778d7693b5);\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.legend = L.control({position: 'topright'});\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.legend.addTo(map_9051cbfe5b4c076be108ec9d20e27e42);\n", "\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.xAxis = d3.svg.axis()\n", - " .scale(color_map_8424586fdb62868ff228abdfe0ff0bc5.x)\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.xAxis = d3.svg.axis()\n", + " .scale(color_map_e983af2216d0ab651a2d7db296a715ed.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.0588235294117645, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 6.117647058823529, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 9.176470588235293, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 12.235294117647058, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 15.294117647058824, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 18.352941176470587, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 21.41176470588235, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 24.470588235294116, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 27.529411764705884, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.g = color_map_8424586fdb62868ff228abdfe0ff0bc5.svg.append("g")\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.g = color_map_e983af2216d0ab651a2d7db296a715ed.svg.append("g")\n", " .attr("class", "key")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.g.selectAll("rect")\n", - " .data(color_map_8424586fdb62868ff228abdfe0ff0bc5.color.range().map(function(d, i) {\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.g.selectAll("rect")\n", + " .data(color_map_e983af2216d0ab651a2d7db296a715ed.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_8424586fdb62868ff228abdfe0ff0bc5.x(color_map_8424586fdb62868ff228abdfe0ff0bc5.color.domain()[i - 1]) : color_map_8424586fdb62868ff228abdfe0ff0bc5.x.range()[0],\n", - " x1: i < color_map_8424586fdb62868ff228abdfe0ff0bc5.color.domain().length ? color_map_8424586fdb62868ff228abdfe0ff0bc5.x(color_map_8424586fdb62868ff228abdfe0ff0bc5.color.domain()[i]) : color_map_8424586fdb62868ff228abdfe0ff0bc5.x.range()[1],\n", + " x0: i ? color_map_e983af2216d0ab651a2d7db296a715ed.x(color_map_e983af2216d0ab651a2d7db296a715ed.color.domain()[i - 1]) : color_map_e983af2216d0ab651a2d7db296a715ed.x.range()[0],\n", + " x1: i < color_map_e983af2216d0ab651a2d7db296a715ed.color.domain().length ? color_map_e983af2216d0ab651a2d7db296a715ed.x(color_map_e983af2216d0ab651a2d7db296a715ed.color.domain()[i]) : color_map_e983af2216d0ab651a2d7db296a715ed.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -808,42 +1093,42 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_8424586fdb62868ff228abdfe0ff0bc5.g.call(color_map_8424586fdb62868ff228abdfe0ff0bc5.xAxis).append("text")\n", + " color_map_e983af2216d0ab651a2d7db296a715ed.g.call(color_map_e983af2216d0ab651a2d7db296a715ed.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", - " .text("edge_id");\n", + " .text("my_index");\n", " \n", - " var layer_control_203e3f9ca5c61e6f2e3b88bbbdd0dc1f_layers = {\n", + " var layer_control_6731a9314faf60b8d88f084a5cb96581_layers = {\n", " base_layers : {\n", - " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_1c129d5d3ca5c01b49b9853cf43c5bb4,\n", + " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_ae2fd0e7f9d32293dab73f890576a178,\n", " },\n", " overlays : {\n", - " "strokes" : geo_json_4492eef1ce432dba2afbd7e795b9e634,\n", - " "lines" : geo_json_a07f9d5ae8a37d823af8862b527e6188,\n", + " "strokes" : geo_json_cff39fc4687a13617618a9bebc8e6a77,\n", + " "lines" : geo_json_381800b304ce6270e2a875ed29271f7a,\n", " },\n", " };\n", - " let layer_control_203e3f9ca5c61e6f2e3b88bbbdd0dc1f = L.control.layers(\n", - " layer_control_203e3f9ca5c61e6f2e3b88bbbdd0dc1f_layers.base_layers,\n", - " layer_control_203e3f9ca5c61e6f2e3b88bbbdd0dc1f_layers.overlays,\n", + " let layer_control_6731a9314faf60b8d88f084a5cb96581 = L.control.layers(\n", + " layer_control_6731a9314faf60b8d88f084a5cb96581_layers.base_layers,\n", + " layer_control_6731a9314faf60b8d88f084a5cb96581_layers.overlays,\n", " {"autoZIndex": true, "collapsed": true, "position": "topright"}\n", - " ).addTo(map_ef7357925cb53e53304c4b778d7693b5);\n", + " ).addTo(map_9051cbfe5b4c076be108ec9d20e27e42);\n", "\n", " \n", "</script>\n", "</html>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen>" ], "text/plain": [ - "" + "" ] }, - "execution_count": 26, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Reds\", style_kwds={\"weight\":8})\n", - "lines.explore(m=m, column = \"edge_id\", name = \"lines\", cmap = \"Blues\", style_kwds={\"weight\":8})\n", + "lines.explore(m=m, column = \"my_index\", name = \"lines\", cmap = \"Blues\", style_kwds={\"weight\":8})\n", "folium.LayerControl().add_to(m)\n", "m" ] @@ -859,202 +1144,846 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 54, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "def _angle_cos(a, b, c):\n", + " \"\"\"\n", + " Measure the angle between a-b, b-c (in degrees).\n", + " \"\"\"\n", + " ba = [a[0]-b[0],a[1]-b[1]]\n", + " bc = [c[0]-b[0],c[1]-b[1]]\n", + " # np.dot(ba, bc) # ba[0]*bc[0] + ba[1]*bc[1]\n", + " # np.linalg.norm(ba) # np.sqrt(ba[0]**2+ba[1]**2)\n", + " # np.linalg.norm(bc) # np.sqrt(bc[0]**2+bc[1]**2)\n", + " theta_rad = math.acos(np.dot(ba,bc)/(np.linalg.norm(ba)*np.linalg.norm(bc)))\n", + " theta_deg = np.degrees(theta_rad)\n", + " return theta_deg\n", + "\n", + "def get_segment(geom, n):\n", + " '''\n", + " geom... linestring.\n", + " n.... coordinate of start-or-end node on linestring.\n", + " returns: coordinate tuple (n, adjacent-to-n), in THAT ORDER\n", + " (ie. if n is start node, returns coords in position 0 and 1;\n", + " if n is end node, reutnrs coords in position n, n-1\n", + " )\n", + " '''\n", + " coords = [c for c in geom.coords]\n", + " index_n = coords.index(n)\n", + " if index_n == 0:\n", + " return coords[0:2]\n", + " elif index_n == len(coords)-1:\n", + " return [coords[index_n], coords[index_n-1]]\n", + " else:\n", + " raise ValueError(\"Node not on end of edge?\")\n", + "\n", + "# use angles_gdf length to add to connectivity of strokes (nodes)\n", + "def get_connectivity(angles_gdf):\n", + " if len(angles_gdf)==4:\n", + " return 2\n", + " elif len(angles_gdf) in [2,3]:\n", + " return 1\n", + " else:\n", + " raise ValueError(\"Unexpected number of edge segments in angles_gdf\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "NodeDataView({0: {'edge_indeces': [0, 3, 15, 27], 'geometry': , 'geometry_stroke': , 'x': 1603374.6625343116, 'y': 6464077.898491419, 'connectivity': 0}, 1: {'edge_indeces': [1, 12, 14, 25], 'geometry': , 'geometry_stroke': , 'x': 1603237.0487682838, 'y': 6464133.622486805, 'connectivity': 0}, 2: {'edge_indeces': [2, 11, 28, 30], 'geometry': , 'geometry_stroke': , 'x': 1603707.1065106073, 'y': 6464238.853991265, 'connectivity': 0}, 3: {'edge_indeces': [4, 5, 6], 'geometry': , 'geometry_stroke': , 'x': 1603149.9288811635, 'y': 6464130.224503239, 'connectivity': 0}, 4: {'edge_indeces': [7, 8, 9, 13, 21, 22, 24], 'geometry': , 'geometry_stroke': , 'x': 1603264.6577362637, 'y': 6463848.97596353, 'connectivity': 0}, 5: {'edge_indeces': [10], 'geometry': , 'geometry_stroke': , 'x': 1603137.4077031056, 'y': 6463800.908382258, 'connectivity': 0}, 6: {'edge_indeces': [16, 17, 18, 23, 29], 'geometry': , 'geometry_stroke': , 'x': 1603592.2349246691, 'y': 6464121.336160048, 'connectivity': 0}, 7: {'edge_indeces': [19], 'geometry': , 'geometry_stroke': , 'x': 1603028.737187382, 'y': 6463900.594576759, 'connectivity': 0}, 8: {'edge_indeces': [20], 'geometry': , 'geometry_stroke': , 'x': 1603207.5969886228, 'y': 6463992.707728057, 'connectivity': 0}, 9: {'edge_indeces': [26], 'geometry': , 'geometry_stroke': , 'x': 1603342.3426854417, 'y': 6464406.368225728, 'connectivity': 0}})" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stroke_graph = nx.Graph()\n", + "stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", + "stroke_graph.graph[\"approach\"] = graph.graph[\"approach\"]\n", + "stroke_graph.add_nodes_from(\n", + " [\n", + " (\n", + " row.stroke_id, \n", + " {\n", + " \"edge_indeces\": row.edge_indeces,\n", + " \"geometry\": row.rep_point,\n", + " \"geometry_stroke\": row.geometry,\n", + " \"x\": row.rep_point.xy[0][0],\n", + " \"y\": row.rep_point.xy[1][0],\n", + " \"connectivity\": 0\n", + " }\n", + " ) for _, row in stroke_gdf.iterrows()\n", + " ]\n", + ")\n", + "# node names are the stroke IDs.\n", + "# each node has the attribute \"edge_indeces\".\n", + "stroke_graph.nodes(data=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "to find the **edges** of the stroke graph, we look at the primal `graph`'s nodes and the stroke_ids of their adjacent edges" + ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 74, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Node: 0\n", + "Adjacent strokes (list): [0, 2, 2]\n", + "Adjacent strokes (uniques): {0, 2}\n", + "Checking edge: (0, 2)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 2])\n", + "angles: [88.68317271320804]\n", + "(0, 2) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 1\n", + "Adjacent strokes (list): [0, 2, 0, 3, 9]\n", + "Adjacent strokes (uniques): {0, 9, 2, 3}\n", + "Checking edge: (0, 9)\n" + ] + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgcAAAGTCAYAAAC8vrHzAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABUAElEQVR4nO3dd1xV9f8H8NdlXfaWjYoLlKniAFyIaK6faZZmhdouG2bDhjnKcnwbmqVlmWLmyJxZai7cIIii4p5MQdkyLuOe3x/IjSMo68K5F17Px4PHI47n3vsG4sPrns/7fD4yQRAEEBEREd2nI3UBREREpFkYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGASIPl5eVh6tSpaNOmDYyMjBAYGIjo6GipyyIiDaaOcYPhgEiDvfjii9izZw9+++03nD17FoMHD8agQYOQnJwsdWlEpKHUMW7IuPESkWYqLCyEmZkZtm3bhuHDh6uO+/n5YcSIEZg7d66E1RGRJlLXuKHXWAUSNSdFRUUoLi5u8PMIggCZTCY6JpfLIZfLq5xbWlqKsrIyGBoaio4bGRnhyJEjDa6FiBqXusYNoPZjh7rGDV45IKpBUVERrK2tUVhY2ODnMjU1xb1790THZs2ahdmzZ1d7fmBgIAwMDLB27VrY29tj3bp1CAsLQ8eOHXHp0qUG10NEjUOd4wZQt7FDHeMGwwFRDXJzc2FhYYEJEybAwMCg3s9TXFyMtWvXIjExEebm5qrjD7tyAADXrl3D888/j0OHDkFXVxfdunVDp06dEBsbi/Pnz9e7FiJqXOoaN4C6jx3qGDc4rUBUSwYGBg3+JQcAc3Nz0S/4o7Rv3x4HDx5Efn4+cnNz4ejoiHHjxsHNza3BdRBR41PXuAHUfuxQx7jBuxWItICJiQkcHR2RlZWF3bt3Y9SoUVKXREQariHjBq8cEGmw3bt3QxAEuLu74+rVq3j//ffh7u6OyZMnS10aEWkodYwbvHJApMFycnIwZcoUeHh4ICwsDH369MG///4LfX19qUsjIg2ljnGDVw6INNhTTz2Fp556SuoyiEiLqGPc4JUDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIg1VWlqKGTNmwM3NDUZGRmjXrh0+++wzKJVKqUsjIg2lrnFDr5HqI6IGWrBgAX788UeEh4fD09MTMTExmDx5MiwsLPD2229LXR4RaSB1jRsMB0Qa6vjx4xg1ahSGDx8OAGjbti3WrVuHmJgYiSsjIk2lrnGD0wpETSw3N1f0oVAoqj2vT58+2LdvHy5fvgwAiIuLw5EjRzBs2LCmLJeINERtxg51jRu8ckDUxFxdXUWfz5o1C7Nnz65y3vTp05GTkwMPDw/o6uqirKwMX3zxBZ5++ukmqpSINEltxg51jRsMB0RNLDExEebm5qrP5XJ5tedt2LABa9aswdq1a+Hp6YnTp09j6tSpcHJywsSJE5uqXCLSELUZO9Q1bjAcEDUxc3Nz0S/4w7z//vv48MMPMX78eACAt7c3bt26hXnz5jEcELVAtRk71DVusOeASEMVFBRAR0f8K6qrq8tbGYnoodQ1bvDKAZGGGjlyJL744gu0bt0anp6eOHXqFL755hs8//zzUpdGRBpKXeMGwwFRLfWx2ANjef0vthUolFhVh/OXLFmCTz/9FK+//jrS09Ph5OSEV155BTNnzqx3DUTUtBo6bgB1GzvUNW7IBEEQ6lwpUQuSm5sLCwsL/PK2c4PDwYuLk5GTk1OrngMi0l7qGjcAacYO9hwQERGRCMMBERERiag1HHz33XeQyWTw8vJ66DkymUy0aENERARkMhkiIiIa/Pr//PNPtYvJqMOqVasgk8m0ZunatWvXYtGiRVKXUYU6f94VFi1ahDFjxsDNzQ0ymQwDBgxQ23MTEbVEag0Hv/76KwAgPj4eUVFR6nzqWvnnn38wZ86cJn9dTaSp4aAx/Pjjj7h16xYGDhyIVq1aSV0OEZHWU1s4iImJQVxcnGqzhxUrVqjrqRuFIAgoLCyUugxSg/Pnz+PkyZNYsWIF7OzspC6HiEjrqS0cVISB+fPnIzAwEOvXr0dBQYG6nh4FBQV477334ObmBkNDQ1hbW8Pf3x/r1q0DAEyaNAk//PADgPKpi4qPmzdvqo698cYb+PHHH9G5c2fI5XKEh4cDAI4cOYKQkBCYmZnB2NgYgYGB+Pvvv2usKTU1Fd27d0fHjh1x5coVAOUdqhV1GhgYwNnZGVOnTkV+fr7osRs3bkSvXr1gYWEBY2NjtGvXrlb3of7www/o168f7OzsYGJiAm9vbyxcuBAlJSWqcwYMGIC///4bt27dEn0vHqVt27YYMWIEdu3ahW7dusHIyAgeHh6qq0GVnTt3DqNGjYKVlRUMDQ3h5+en+l5WdvHiRTz22GMwNjaGra0tXn31VeTl5VX7+nv37kVISAjMzc1hbGyMoKAg7Nu3r8bvB4AqC34QEVHDqGWdg8LCQqxbtw49evSAl5cXnn/+ebz44ovYuHGj2pZ5nTZtGn777TfMnTsXXbt2RX5+Ps6dO4eMjAwAwKeffor8/Hz8+eefOH78uOpxjo6Oqv/eunUrDh8+jJkzZ8LBwQF2dnY4ePAgQkND4ePjgxUrVkAul2Pp0qUYOXIk1q1bh3HjxlVbz7lz5zBs2DC4uLjg+PHjsLW1RUFBAfr374+kpCR8/PHH8PHxQXx8PGbOnImzZ89i7969kMlkOH78OMaNG4dx48Zh9uzZMDQ0xK1bt7B///4avw/Xrl3DhAkTVOEjLi4OX3zxBS5evKj6Q7506VK8/PLLuHbtGrZs2VLr73FcXBzeffddfPjhh7C3t8cvv/yCF154AR06dEC/fv0AAJcuXUJgYCDs7Ozw3XffwcbGBmvWrMGkSZOQlpaGDz74AACQlpaG/v37Q19fH0uXLoW9vT1+//13vPHGG1Ved82aNQgLC8OoUaMQHh4OfX19/PTTTxgyZAh2796NkJCQWn8NRETUcGoJB3/++SdycnLwwgsvAADGjRuHqVOnYsWKFWoLB0ePHsXgwYPxzjvvqI5VTGEAQPv27WFvbw8A6N27d7XPce/ePZw9exZWVlaqYwEBAbCyskJERARMTU0BACNGjICfnx/ee+89PPXUU1Xede/duxdPPPEEBg8ejN9++w2GhoYAyhsyz5w5g6ioKPj7+wMAQkJC4OzsjLFjx2LXrl0YOnQojh07BkEQ8OOPP8LCwkL1vJMmTarx+/DNN9+o/lupVKJv376wsbHB5MmT8fXXX8PKygpdunSBpaUl5HL5Q78X1bl79y6OHj2K1q1bAwD69euHffv2Ye3atapwMHv2bBQXF+PAgQOqHcKGDRuG7OxszJkzB6+88gosLCzw7bff4s6dOzh16hR8fX0BAEOHDsXgwYORkJCges2CggK8/fbbGDFihCjIDBs2DN26dcPHH38sSf8KEVFLppbrsStWrICRkZFqowdTU1M8+eSTOHz4sOpye0P17NkTO3fuxIcffoiIiIh69QsMHDhQFAzy8/MRFRWFsWPHqoIBUL4O9XPPPYekpCRcunRJ9Bzh4eEYNmwYXnzxRfzxxx+qYAAAO3bsgJeXF/z8/FBaWqr6GDJkiKhDv0ePHgCAp556Cn/88QeSk5Nr/TWcOnUK//d//wcbGxvo6upCX18fYWFhKCsrU+3fXV9+fn6qYAAAhoaG6NSpE27duqU6tn//foSEhFTZOnTSpEkoKChQXbU5cOAAPD09VcGgwoQJE0SfHzt2DJmZmZg4caLoe6ZUKvHYY48hOjq6ypQMERE1rgaHg6tXr+LQoUMYPnw4BEFAdnY2srOzMXbsWACods66Pr777jtMnz4dW7duRXBwMKytrfH444/XKXxUnmIAgKysLAiCUOU4ADg5OQGAatqiwvr162FkZIQXX3yxyhWFtLQ0nDlzBvr6+qIPMzMzCIKAu3fvAih/R75161aUlpYiLCwMLi4u8PLyUvVPPExCQgL69u2L5ORkLF68GIcPH0Z0dLSq16KhDZY2NjZVjsnlctHzZmRk1Or7lZGRAQcHhyrnPXgsLS0NADB27Ngq37cFCxZAEARkZmbW/4siIqI6a/C0wq+//gpBEPDnn3/izz//rPLv4eHhmDt3LnR1dRv0OiYmJpgzZw7mzJmDtLQ01VWEkSNH4uLFi7V6jgf/mFtZWUFHRwepqalVzk1JSQEA2Nraio7//vvv+PTTT9G/f3/8+++/8PPzU/2bra0tjIyMHhqIKj/XqFGjMGrUKCgUCkRGRmLevHmYMGEC2rZti4CAgGofv3XrVuTn52Pz5s1o06aN6vjp06cf+XWrk42NTa2+XzY2Nrh9+3aV8x48VnH+kiVLHjoFUjFdRERETaNB4aCsrAzh4eFo3749fvnllyr/vmPHDnz99dfYuXMnRowY0ZCXErG3t8ekSZMQFxeHRYsWoaCgAMbGxpDL5QDK30EbGRnV+DwmJibo1asXNm/ejK+++kr1GKVSiTVr1sDFxQWdOnUSPcba2hp79+7FiBEjEBwcjJ07d6r+qI0YMQJffvklbGxs4ObmVquvRS6Xo3///rC0tMTu3btx6tSph4aDinBT8XUC5bdk/vzzz9U+b2PcqhkSEoItW7YgJSVFdbUAAFavXg1jY2PV9yI4OBgLFy5EXFycaGph7dq1oucLCgqCpaUlzp8/X22zIhERNb0GhYOdO3ciJSUFCxYsqHZVOi8vL3z//fdYsWJFg8NBr169MGLECPj4+MDKygoXLlzAb7/9hoCAABgbGwMAvL29AQALFizA0KFDoaurCx8fHxgYGDz0eefNm4fQ0FAEBwfjvffeg4GBAZYuXYpz585h3bp11d4CaGZmhl27dmHMmDEIDQ3F9u3bERwcjKlTp2LTpk3o168f3nnnHfj4+ECpVCIhIQH//vsv3n33XfTq1QszZ85EUlISQkJC4OLiguzsbCxevBj6+vro37//Q2sNDQ2FgYEBnn76aXzwwQcoKirCsmXLkJWVVeVcb29vbN68GcuWLUP37t2ho6OjapJsiFmzZmHHjh0IDg7GzJkzYW1tjd9//x1///03Fi5cqGqwnDp1Kn799VcMHz4cc+fOVd2t8OBVHlNTUyxZsgQTJ05EZmYmxo4dCzs7O9y5cwdxcXG4c+cOli1b9siaYmJiVLes5ubmqq5kAeX9HZWvshARUc0aFA5WrFgBAwMDTJ48udp/t7W1xejRo/Hnn38iLS2tQZeHBw4ciO3bt+Pbb79FQUEBnJ2dERYWhk8++UR1zoQJE3D06FEsXboUn332GQRBwI0bN9C2bduHPm///v2xf/9+zJo1C5MmTYJSqYSvry+2b9/+yEBjZGSEbdu2YcKECRg2bBg2bdqEYcOG4fDhw5g/fz6WL1+OGzduwMjICK1bt8agQYNUdfTq1QsxMTGYPn067ty5A0tLS/j7+2P//v3w9PR86Gt6eHhg06ZNmDFjBsaMGQMbGxtMmDAB06ZNw9ChQ0Xnvv3224iPj8fHH3+MnJwcCIIAdWzA6e7ujmPHjuHjjz/GlClTUFhYiM6dO2PlypWiuy0cHBxw8OBBvP3223jttddgbGyM0aNH4/vvv8eoUaNEz/nss8+idevWWLhwIV555RXk5eXBzs4Ofn5+tbqD4/vvv6+yzsKTTz4JAFXqIiKimnHLZqIacMtmIqorbtlMREREzQrDAREREYkwHBAREZEIwwERNVhUVBRGjx6N1q1bQy6Xw97eHgEBAXj33XdF5y1duhSrVq1qlBomTZokWulUSocPH4ZcLhetLgoAsbGxGDRoEExNTWFpaYkxY8bg+vXrDXqt3bt3IygoCEZGRrCwsMDIkSMRHx8vOqekpATt27dvlG3cv/zyS2zdulXtz9tQs2fPrnHDubrIy8vDBx98gMGDB6NVq1aQyWSYPXu22p5f0zAcEFGD/P333wgMDERubi4WLlyIf//9F4sXL0ZQUBA2bNggOrcxw4GmEAQBU6dOxUsvvSS6jfbixYsYMGAAiouL8ccff+DXX3/F5cuX0bdvX9y5c6der7Vt2zYMHToUdnZ22LRpE3788UdcuXIFffv2xbVr11Tn6evrY+bMmfjss8+qrPraUJoaDtQtIyMDy5cvh0KhwOOPPy51OY1OLRsvEVHLtXDhQri5uWH37t3Q0/tvSBk/fjwWLlxY7+ctKSmBTCYTPac22LVrF2JjY6ss+DVz5kzI5XLs2LFD1XFeseX7V199hQULFtT5taZPn65a06TiXXJgYCA6deqEmTNn4vfff1ed+/TTT2PatGn46aef8PHHHzfgK2yZ2rRpg6ysLMhkMty9e7fahf+aE145IKIGycjIgK2tbbV/xHV0/hti2rZti/j4eBw8eBAymQwymUy19kdERARkMhl+++03vPvuu3B2doZcLsfVq1cBlC/T7uvrC0NDQ1hbW2P06NG4cOFCjbUdPXoUtra2GDFihGoDrytXrmDChAmws7ODXC5H586dVfuTVFAqlZg7dy7c3d1hZGQES0tL+Pj4YPHixTW+5rJly9CjRw+4u7urjpWWlmLHjh144oknRLeitWnTBsHBwXXaWr1CRkYGLl26hKFDh4oun7dp0wZeXl7YunUrysrKVMcNDAwwbtw4LF++vMY1T4qKivDuu+/Cz88PFhYWsLa2RkBAALZt2yY6TyaTIT8/H+Hh4aqfaXUL4lW4efMmZDIZvvrqK3zzzTdwc3ODqakpAgICEBkZWeX87du3qxa6MzMzQ2hoqGpzt8r+/vtv+Pn5QS6Xw83NDV999VW1ry8IApYuXQo/Pz8YGRnBysoKY8eOrdXUTsXX11IwHBBRgwQEBCAqKgpvvfUWoqKiUFJSUu15W7ZsQbt27dC1a1ccP34cx48fr/JH8aOPPkJCQgJ+/PFH/PXXX7Czs8O8efPwwgsvwNPTE5s3b8bixYtx5swZBAQEPHLjtT/++AMhISF46qmnsG3bNpiYmOD8+fPo0aMHzp07h6+//ho7duzA8OHD8dZbb2HOnDmqxy5cuBCzZ8/G008/jb///hsbNmzACy+8gOzs7Ed+L4qLi7F3714EBweLjl+7dg2FhYXw8fGp8hgfHx9cvXoVRUVFj3zu6l4LEC+nXkEul6OgoEA0tQAAAwYMwK1bt3Du3LlHPrdCoUBmZibee+89bN26FevWrUOfPn0wZswYrF69WnXe8ePHYWRkhGHDhql+pkuXLq2x9h9++AF79uzBokWL8PvvvyM/Px/Dhg1DTk6O6py1a9di1KhRMDc3x7p167BixQpkZWVhwIABOHLkiOq8ffv2YdSoUTAzM8P69evxv//9D3/88QdWrlxZ5XVfeeUVTJ06FYMGDcLWrVuxdOlSxMfHIzAwULUJHJXTrut1RKRx5s+fj4sXL2LJkiVYsmQJ9PX10aNHD4wcORJvvPGGqkmwa9euMDIygrm5+UM32Wrfvj02btyo+jw7Oxuff/45hg0bJrpMP2DAAHTs2BGzZ88WXTqvsGDBAnzyySf48ssv8cEHH6iOT5s2DWZmZjhy5IjqHXxoaCgUCgXmz5+Pt956C1ZWVjh69Ci8vb1FDWdDhgyp8Xtx+vRpFBYWolu3bqLjFfP81tbWVR5jbW0NQRCQlZVV7Y6nD2Nvbw9ra2scPXpUdDw7O1v1x//B/oKKuiq+voexsLAQ/XEtKytDSEgIsrKysGjRIoSFhQEAevfuDR0dHbRq1eqhP9PqmJmZYceOHaoN+ZycnNCzZ0/s3LkT48ePh1KpxPvvvw9vb2/s3LlTdQVq2LBhaN++PaZPn676uj/55BPY29tjz549MDQ0BFD+s3pwZdzIyEj8/PPP+PrrrzFt2jTV8b59+6JTp0745ptv6jW101zxygERNYiNjY1q+/D58+dj1KhRuHz5Mj766CN4e3urtiqvjSeeeEL0+fHjx1FYWFhlCWxXV1cMHDgQ+/btEx0XBAGvvPIKZs2ahbVr14qCQVFREfbt24fRo0fD2NgYpaWlqo9hw4ahqKhIdWm7Z8+eiIuLw+uvv47du3cjNze3VvVX7E5qZ2dX7b8/6rJ0XS9Z6+joYMqUKdi3bx8+//xzpKen4+rVq3j22WdRUFCgOqeyirqSk5NrfP6NGzciKCgIpqam0NPTg76+PlasWFGr6ZyaDB8+XLRTb8UVlYq7Oy5duoSUlBQ899xzoq/B1NQUTzzxBCIjI1FQUID8/HxER0djzJgxqmAAlIePkSNHil5zx44dkMlkePbZZ0U/ewcHB/j6+iIiIqLBX1dzwnBARGrh7++P6dOnY+PGjUhJScE777yDmzdv1qkp8cF3zhXvfKt7R+3k5FTlnXFxcTE2bNgAT0/PKvuNZGRkoLS0VHV1o/LHsGHDAEAVZD766CN89dVXiIyMxNChQ2FjY4OQkBDExMQ8sv6KnVAr/6ECygNU5a+nsszMTMhkMlhaWj7yuaszc+ZMvPPOO6rNzTp27AgAqv1unJ2dRedX1FXTjq2bN2/GU089BWdnZ6xZswbHjx9HdHQ0nn/++TpPf1Sn4vtRofKOukDNP3elUomsrCxkZWVBqVTCwcGhynkPHktLS4MgCLC3t6/y84+MjKxTiG0JOK1ARGqnr6+PWbNm4dtvv61xfruyB989V/wRSU1NrXJuSkoKbG1tRcfkcjkOHDiAIUOGYNCgQdi1axesrKwAAFZWVtDV1cVzzz2HKVOmVPv6FVut6+npYdq0aZg2bRqys7Oxd+9efPzxxxgyZAgSExNVO8E+qKKezMxM0fH27dvDyMgIZ8+erfKYs2fPokOHDlUCRW3o6enhm2++wWeffYYbN27A1tYWjo6OGDJkCNzc3ODi4iI6v6KuB79vD1qzZg3c3NywYcMG0c9EoVDUucb6qOnnrqOjAysrKwiCAJlMhtu3b1c578Fjtra2kMlkqjUoHlTdsZaMVw6IqEGqG8ABqC4/Ozk5qY7J5fIa37VWFhAQACMjI6xZs0Z0PCkpCfv370dISEiVx3Tt2hUHDx5EUlISBgwYgPT0dACAsbExgoODcerUKfj4+MDf37/Kx4PvaAHA0tISY8eOxZQpU5CZmanaHrw6nTt3BoAqjYB6enoYOXIkNm/ejLy8PNXxhIQEHDhwAGPGjKn196Q6pqam8Pb2hqOjI2JjY7Fv3z68/fbbVc6r6Mrv0qXLI59PJpPBwMBAFAxu375d5W4FoO4/09pwd3eHs7Mz1q5dK7qzIj8/H5s2bVLdwWBiYoKePXti8+bNoisaeXl5+Ouvv0TPOWLECAiCgOTk5Gp/9o/qwWiJeOWAiBpkyJAhcHFxwciRI+Hh4QGlUonTp0/j66+/hqmpqeiPlLe3N9avX48NGzagXbt2MDQ0fOSgbGlpiU8//RQff/wxwsLC8PTTTyMjIwNz5syBoaEhZs2aVe3jOnfujMOHD2PQoEHo168f9u7dCxcXFyxevBh9+vRB37598dprr6Ft27bIy8vD1atX8ddff2H//v0AgJEjR8LLywv+/v5o1aoVbt26hUWLFqFNmzaqS/fVcXFxQbt27RAZGYm33npL9G9z5sxBjx49MGLECHz44YcoKirCzJkzYWtrW2UlyQEDBuDgwYM13nIYERGB6Oho+Pj4QBAEnDhxAgsWLMBjjz2GN954o8r5kZGR0NXVRb9+/R75vCNGjMDmzZvx+uuvY+zYsUhMTMTnn38OR0fHKneIeHt7IyIiAn/99RccHR1hZmYmuo2zPnR0dLBw4UI888wzGDFiBF555RUoFAr873//Q3Z2NubPn6869/PPP8djjz2G0NBQvPvuuygrK8OCBQtgYmIiuoITFBSEl19+GZMnT0ZMTAz69esHExMTpKam4siRI/D29sZrr732yLp27tyJ/Px8VcA7f/48/vzzTwDlzZIPu6KkjRgOiKhBZsyYgW3btuHbb79FamoqFAoFHB0dMWjQIHz00Ueqd9NA+R/I1NRUvPTSS8jLy0ObNm0e+U4cKJ//t7Ozw3fffYcNGzbAyMgIAwYMwJdffvnIP9Tt2rVTBYS+ffti37596NKlC2JjY/H5559jxowZSE9Ph6WlJTp27KjqOwCA4OBgbNq0Cb/88gtyc3Ph4OCA0NBQfPrpp9DX139kvc888wy+//57KBQK0aVqDw8PREREYPr06Rg7diz09PQwcOBAfPXVV2jVqpXoOe7du1ftPPqDDAwMsGnTJsydOxcKhQIdO3bEZ599hrfeekvU8Fdh69atGDZsWI39DZMnT0Z6ejp+/PFH/Prrr2jXrh0+/PBDJCUliW75BIDFixdjypQpGD9+PAoKCtC/f3+1NPdNmDABJiYmmDdvHsaNGwddXV307t0bBw4cQGBgoOq80NBQbN26FTNmzMC4cePg4OCA119/HYWFhVVq/emnn9C7d2/89NNPWLp0KZRKJZycnBAUFISePXvWWNNrr70mWhJ748aNqrtrbty4UeUOCW0mE2qKpkQtnLr2Za/rnuxt27atsjY/ALz++utVFu0hzZGSkgI3NzesXr0a48aNq/Pj8/LyYG1tjUWLFj20N6I+rl27ho4dO2L37t0IDQ1V2/NS9dQ1bgDSjB3sOSDSUNHR0UhNTVV97NmzBwDw5JNPSlwZPYqTkxOmTp2KL774Akqlss6PP3ToEJydnfHSSy+pta65c+ciJCSEwaAFUMfYwWkFIg314KXm+fPno3379ujfv79EFVFtzZgxA8bGxkhOToarq2udHjt8+HAMHz5crfWUlpaiffv2+Oijj9T6vKSZ1DF2MBwQNbEHF9SRy+U13kZVXFyMNWvWYNq0aS1qfXdtZWZm9tBmSSno6elhxowZUpdBDdSUYwenFYiamKurKywsLFQf8+bNq/ExW7duRXZ2dpWVAomo5WjKsYNXDoiaWGJioqipqDaLr6xYsQJDhw4VrRlARC1LU44dDAdETczc3LxWHccVbt26hb1792Lz5s2NWBURabqmHDs4rUCk4VauXAk7Ozu1N6kRUfPWkLGD4YBIgymVSqxcuRITJ06Enh4v9BFR7TR07GA4INJge/fuRUJCAp5//nmpSyEiLdLQsYNvRYg02ODBg2tcX5+I6EENHTt45YCIiIhEGA6IiIhIhOGAiIiIRNhzQFRLfbulwMy4/ksX5xWwd4CopWnouAFIM3bwygE1OxezbktdAhFpmdT8HGQpCqQuQ2MwHFCzEn7hOEK3LsbP8YelLoWItERecRHC9qzE438vw628DKnL0QgMB9Rs7Eu8iE+jtkOAgKLSUqnLISItUKosw2sRa3Eh6zZyiwuhK+OfRYDhgJqJ+IwUvB6xFkpBwLiO/njDZ4DUJRGRhhMEAZ9GbkdE8mUY6upjZchEuJhaSV2WRmA4IK2Xkp+DsL2rkF9ajD6OHTA/cHSd9i0nopbpp3OH8dulKMggww/9x8OvlavUJWkMhgPSavdKFJi0dxXSCnLRydIOPwU/A30dXanLIiIN9/fNs5gb8w8AYFbP4RjSxlPiijQLwwFprVJlGV47sBbnM1PRysgU4YMmwUJuJHVZRKThYu8k4K1DGwAAEz0C8EKXIIkr0jwMB6SVBEHAzKi/cCD5kmqu0NXMWuqyiEjDJeRlYvLecCjKShHi4oE5vUZwGrIaDAeklX6OP4LVFyMhgwxL+o/jXCER1ShbUYCwPSuRUZQPL2snLB3wNPQ4DVkthgPSOjtvncPn0eVzhZ/2GIahbbwkroiINF1xWSle3r8GV3PuwMHYHCsHTYSJvlzqsjQWwwFplVN3EvHmwQ0QIGCiR2+85NlH6pKISMMJgoDpxzbj2O3rMNEzwOrQSXA0sZC6LI3GcEBaI/H+XGFRWQkGurhjTq+RnCskohp9F7cfG6/GQlemgx+Dn0EXayepS9J4DAekFXIUhQjbswp3i+7B09oRSwdM4FwhEdVoy7XT+N+pPQCAub3/D8Eu7hJXpB0YDkjjFZeV4uUDa3AlJx0OxuZYNWgSTDlXSEQ1iLp9A+8e2QgAeMWrH57z6C1xRdqD4YA0miAI+Oj4FhxNvca5QiKqtes5d/DC/t9QrCzDsDZe+MT/MalL0ioMB6TRlpw5gA1XTkJHJsPSARM4V0hENcosykfYnlXIVhTAz9YVi/s9BR1uqFQn/G6Rxtp6/TQWxv4LAJjbexRCXD0kroiINF1RaQme37caN/My4GpqhZWDwmCkZyB1WVqn2YaD4uJiHD58GL/88gsEQZC6HKqjE2k3Me3w/blCz74I41whNZGUlBSsW7cO0dHRUpdCdaQUlJh2ZCNi0m/B3MAQq0Mno5WRmdRlaaVmGw7Kysrwxx9/IDo6GteuXZO6HKqD6zl38fy+1ShWluGx1p74pMdQqUuiFuTMmTOIiIjAvn37pC6F6uh/sXuw/cYZ6Ml08HPws+hoaSd1SVqr2YYDIyMj9OjRAwBw+PBhiauh2iqfK1ypmitc0n8c5wqpSQUEBEBHRwc3btxAUlKS1OVQLa2/HI0lZw4AAP4X9ASCnDpIXJF2a9ajbt++fQEAJ0+eRH5+vsTVUE2KSkvwwv25QhdTS84VkiQsLCzg5+cHgG8stMXhlCv48NgWAMDbvgPxZMfuElek/Zp1OGjbti1cXFxQUlKCqKgoqcuhR1AKSrx79E9Ec66QNEDFG4vIyEgUFxdLXA09yqWsNLy8fw1KBSUeb+eH97qGSl1Ss9Csw4FMJlP9kh8+fJiNiRrsq9g92HY9DnoyHSwPfhadLO2lLolaMA8PD9ja2qKoqAgxMTFSl0MPkV6Qh7A9K5FXokAv+7b4us9YLqmuJs06HABAr169oK+vj5SUFFy/fl3qcqgaG67E4Lv7c4ULgsagD+cKSWI6Ojro06d8Uy9OLWimwtJiTN4XjuT8bLiZ2+KXgc9BrqsndVnNRrMPB2xM1GxHUq5i+tHNAIC3fIIxrqO/xBURlQsMDISOjg6uX7+O5ORkqcuhSsqUSrxxcD3i7ibBSm6M1aGTYGVoInVZzUqzDwfAf/OHMTExbEzUIJez0/DygfK5wlHtfPF+t8FSl0SkYmFhAV9fXwDAoUOHJK6GKpsb8w92J5yHXFcPv4aEwc3cVuqSmp0WEQ7c3NzYmKhh7hSWzxXmFhehp31bfB3EucLqJCcn49lnn4WNjQ2MjY3h5+eHkydPSl1Wi9GvXz8AQFRUFBsTNcSqC8fxc/wRAMA3fZ5ED/u20hakgdQxbrSIcCCTyUTzh2xMlFZhaTEm7Q1H0r1stDWzwS8Dn4Ohnr7UZWmcrKwsBAUFQV9fHzt37sT58+fx9ddfw9LSUurSWgwPDw/Y2NigsLCQoUwD7Eu8iJlR2wEA07sNwah2vhJXpHnUNW60mO6NXr16YdOmTarGxPbt20tdUotUplTizYMbKs0VToY15wqrtWDBAri6umLlypWqY23btpWuoBaoojFx27ZtOHz4MAICAqQuqcU6l5GM1yLWQikIGN/RH2/4DJC6JI2krnGjRVw5AABjY2P4+5c3u7ExUTpfxuzEroR4GOjoYkVIGNpZtLy5wtzcXNGHQqGo9rzt27fD398fTz75JOzs7NC1a1f8/PPPTVwtBQUFQUdHB9euXWNjokRS8nMwcW84CkqL0cexA+YFjm6R05C1GTvUNW60mHAAiBsTCwoKJK6m5Vl9MRI/xZcHs2/6PomeLXSu0NXVFRYWFqqPefPmVXve9evXsWzZMnTs2BG7d+/Gq6++irfeegurV69u4opbNgsLC/j4+AAAjhw5InE1Lc+9EgUm7V2FtIJcdLK0w0/Bz0BfR1fqsiRRm7FDXeNGi5lWAIB27drByckJKSkpiIqKQnBwsNQltRj7Ei9iRuQ2AMAH3Qbj8XZ+0hYkocTERJibm6s+l8vl1Z6nVCrh7++PL7/8EgDQtWtXxMfHY9myZQgLC2uSWqlcv379cPr0aURGRmL06NEwMOCy3k2hVFmGVw/8jvOZqWhlZIrVoZNhITeSuizJ1GbsUNe40aKuHMhkMlX3MRsTm875zBS8fn+ucFzH7njTp2WHMnNzc9HHw8KBo6MjunTpIjrWuXNnJCQkNEWZVEnnzp1hY2ODgoICNiY2EUEQ8GnkdkQkX4ahrj5WhkyEi6mV1GVJqjZjh7rGjRYVDoD/VkxMTk7GjRs3pC6n2UvJz0HYnlXILy1GkGN7zAtomXOF9REUFIRLly6Jjl2+fBlt2rSRqKKWiysmNr3l8Yfx26UoyCDD9/3Hw6+Vq9QlaQV1jRstLhywMbHp3CtRYPLeVbh9f65wefCzMODyprX2zjvvIDIyEl9++SWuXr2KtWvXYvny5ZgyZYrUpbVIFSsmXrt2DSkpKVKX06z9ffMs5kbvBADM7DkMj7XxlLgi7aGucaPFhQPgv8bE6OhoFBYWSlxN81SqLMPrEWsRn5kKW0NThA+a1KLnCuujR48e2LJlC9atWwcvLy98/vnnWLRoEZ555hmpS2uRLC0tVY2JfGPReGLvJOCtQxsgQMBEjwC82KWP1CVpFXWNGy3ybVzlxsTIyEg2JqqZIAiYFfUX9iddKp8rHDQRrmbWUpellUaMGIERI0ZIXQbd17dvXzYmNqKEvEw8v3c1FGWlGOjijjm9RnAash7UMW60yCsH3Mq5cf1y/gjCL0ZCBhmW9B+HrpwrpGaiS5cuqsbE2NhYqctpVrIVBZi4ZxXuFt2Dp7Ujlg2YAL0WesuiJmiR4QAQNybevHlT6nKajZ23zuGzE/8AAGb0GIqhbbwkrohIfXR0dBAUFASAUwvqVFxWilcO/I4rOelwMDbHqkGTYKJf/V081DRabDgwMTFB9+7dAfCXXF1O3UnEmwfL5wrDPHrjZc++UpdEpHYVjYlXr15lY6IaCIKAD49twdHUazDRM8Dq0ElwNLGQuqwWr8WGA4CNieqUmJeJyXvDUVRWgmBnd3zWayTnCqlZsrKygre3NwCumKgO38Xtxx9XT0JXpoNlwc+gi7WT1CURWng4aN++PRwdHVFcXIwTJ05IXY7WylEUYuLe8rnCLtaOWBbMuUJq3ireWBw/fhwlJSUSV6O9tlw7jf+d2gMAmNv7/zDQxV3iiqhCiw4HlRsTDx06xMbEeqiYK7ycnQ77+3OFppwrpGbO09MT1tbWXDGxAaJu38C7RzYCAF7x6ofnPHpLXBFV1qLDAQD07t0b+vr6SEpKYmNiHQmCgI+Ob8WR1Ksw1jPA6kGT4MS5QmoBuGJiw1zPuYMX9v+GYmUZhrbxxCf+j0ldEj2gxYcDNibW3/dnIrDhSgx0ZDIsGzABnjacK6SWIzAwEDKZDFevXkVqaqrU5WiNzKJ8hO1ZhWxFAfxsXfFdv3HQkbX4P0Uahz8RsDGxPrZeP40FsbsBAJ/3+j+EuHpIXBFR07KysuKKiXVUVFqCF/atxs28DLiaWmHloDAY6XEhKU3UIldIfFBFY2JqaipOnDiB/v37S12SRjuRdhPTDpfPFb7s2QcTOwdIXFHTmFfiDIOS+ufp4hIlgCT1FUSS69u3L+Li4lQrJurr60tdksZSCkq8e+RPRKffgrmBIcJDJ6GVkZnUZTW6ho4bgDRjB68coLwxsfL8IRsTH+5G7l28sG81ipVleKy1Jz7xHyZ1SUSS8fT0hJWVFfLz87liYg3+F7sH227EQU+mg5+Dn0UnS3upS6JHYDi4LyAgAHp6ekhMTMStW7ekLkcjZd2fK8xSFMDX1gVL+o+Drg7/F6KWi42JtbP+cjSWnDkAAFgYNAZBTh0krohqwpH9PjYmPpqirBQv7P8NN3LvwsXUEitDJnKukAhAUFAQZDIZrly5gtu3b0tdjsY5nHIFHx7bAgB423cgnuroL3FFVBsMB5WwMbF6giDg3SN/4kTazfK5wkGTYWfc/OcKiWqj8oqJfGMhdikrDS/vX4NSQYnH2/nhva6hUpdEtcRwUEmHDh3g4OAAhUKB6OhoqcvRGF+d2oOt109DT6aD5cHPwt2Kc4VElXHFxKrSC/Iwce9K5JUo0NO+Lb7uM5ZLqmsRhoNKHtzKmYA/rsRgcdx+AMD8wNHow7lCoiq8vLxUjYmnTp2SuhzJFZYWY/K+cCTdy4abuS1WDHwOcl3eHKdNGA4e0Lt3b+jp6SEhIaHFr5h4NOUqPji6GQDwpk8wxnfqIXFFRJqJWzn/p0ypxBsH1yPubhKs5MZYHToJVoYmUpdFdcRw8ABTU1N069YNQMv+Jb+cnYaXDpTPFY5y88X73ThXSPQoFY2Jly9fbtGNiV/E/IPdCedhoKOLX0PC4GZuK3VJVA8MB9Wo3JhYVFQkcTVN705hHibuWYXc4iL0sGuDr/uM5fKmRDWwtraGl5cXgJa7lXP4heNYHl/+tX/b9yn0sG8rbUFUbxzxq9GxY0fY29tDoVC0uK2cC0uLMXnvaiTey0JbMxusCAmDoR5XfSOqjYo3FseOHWtxjYn7Ei/i06jtAIDp3YZgVDtfiSuihmA4qEZLbUxUCkq8dWgDTt9NhKXcGKtDJ8Oac4VEtVa5MfH06dNSl9Nk4jNS8FrEWigFAeM6+uMNnwFSl0QNxHDwEBUrJiYkJLSYFRO/iNmFnbfiYaCjixUDn0M7C84VEtWFrq5ui2tMTMnPQdjeVSgoLUYfxw6YHziatyw2AwwHD2FqaoquXbsCaBm/5L9djMRP5w4BAL7u8yR6ObhJXBGRdqpoTLx06RLS0tKkLqdR3StRYNLeVUgryEUnSzv8FPwM9HV0pS6L1IDh4BH69esHADhx4kSzbkzcn3QJn0RuAwC83zUUo9v7SVsQkRar3JjYnN9YlCrL8NqBtTifmYpWRqYIHzQJFnIjqcsiNWE4eITKjYnNdcXE85kpeO3A71AKAp7q0B1v+Q6UuiQirdfcV0wUBAEzo/7CgeRLMNTVx8qQiXA1s5a6LFIjhoNHaO6Nian5OQjbswr5pcUIcmzPuUIiNfHy8oKlpSXu3bvXLBsTl8cfxuqLkZBBhu/7j4dfK1epSyI1YzioQUVj4q1bt5CQkCB1OWpTMVd4uyAXHS3ssDz4WRhweVMitWjOjYn/3DyHudE7AQAzew7DY208Ja6IGgPDQQ2aY2NiqbIMr0esRXxmKmwNTREeyrlCInXr06dPs2tMPHUnEW8d2gABAiZ69MaLXfpIXRI1EoaDWqiYWoiKitL6xkRBEDAragf2J12CXFcPvw4KQ2vOFRKpnbW1NTw9y99VN4cVExPyMjF5bziKykow0MUdc3qN5DRkM8ZwUAudOnWCnZ0dFAoFYmJipC6nQX45fwThF49DBhmW9BuPbq1aS10SUbPVXFZMzFEUYuKeVbhbdA+e1o5YNmAC9HjLYrPGcFALzaUxcdeteHx24h8AwIweQzGsrZfEFdGjzJ49GzKZTPTh4OAgdVlUB97e3qrGxLi4OKnLqZfislK8fGANruSkw8HYHKsGTYKJvlzqsugh1DVuMBzUUkBAAHR1dXHz5k2tbEw8fScRbxxcDwECnnPvhZc9+0pdEtWCp6cnUlNTVR9nz56VuiSqA21vTBQEAR8e24KjqddgomeA1aGT4GhiIXVZVAN1jBsMB7VkZmamakzUtvnDxLxMTN5XPlcY7OyOz3v/H+cKtYSenh4cHBxUH61atZK6JKqjihUTL168iPT0dKnLqZMlZw7gj6snoSOTYVnwM+hi7SR1SVQL6hg3GA7qQBsbE3MUhZi4dxXuFN5DZysHLAvmXKHUcnNzRR8KheKh5165cgVOTk5wc3PD+PHjcf369SaslNTBxsZG1ZioTVcPtl4/jYWx/wIA5vYehYEu7hJXRLUdO9QxbjAc1IG7uzvs7OxQVFSkFY2JJcoyvBrxOy5np8Pe2BzhoZNhyrlCybm6usLCwkL1MW/evGrP69WrF1avXo3du3fj559/xu3btxEYGIiMjIwmrpgaqvKKiaWlpRJXU7Oo2zcw7fBGAMArnn0R5tFb4ooIqN3Yoa5xg6ve1IFMJkOfPn2wefNmHD58GH36aO49vhVzhYdTrsJYzwDhgybCiXOFGiExMRHm5uaqz+Xy6gPb0KFDVf/t7e2NgIAAtG/fHuHh4Zg2bVqj10nq4+3tDQsLC+Tk5CAuLg7du3eXuqSHup5zFy/s/w3FyjIMbeOJT3oMrflB1CRqM3aoa9zglYM6qtyYmJiYKHU5D/XD2QhsuBJTPlc4YAK8bJylLonuMzc3F308LBw8yMTEBN7e3rhy5UojV0jqpi2NiZlF+QjbsxLZigL42briu37joCPjnwlNUZ+xo77jBn/qdWRubg4/Pz8AmvtLvu16HOaf3A0A+KzX/yHE1UPiikgdFAoFLly4AEdHR6lLoXqoaEy8cOEC7ty5I3U5VRSVluCFfatxMy8DrqZWWDkoDEZ6BlKXRQ1U33GD4aAeKjcmPqqZTArRaTcx7Uj5XOFLnn0wqXOAxBVRfb333ns4ePAgbty4gaioKIwdOxa5ubmYOHGi1KVRPdja2qJLly4ANO+NhVJQ4t0jfyI6/RbMDQwRHjoJrYzMpC6L6kFd4wbDQT1oamPijdy7eH7faijKSjGkdRfM8B8mdUnUAElJSXj66afh7u6OMWPGwMDAAJGRkWjTpo3UpVE9VV4xUZMaE7+K3YNtN+KgJ9PB8uBn0cnSXuqSqJ7UNW6wIbEedHR0RI2JFXOJUsoqykfYnlXIUhTA19YFS/qNh64Os582W79+vdQlkJr5+PjA3Nwcubm5GtOYuP5yNL47cwAAsDBoDPo4dZC4ImoIdY0b/OtRTxWNiTdu3JC8MVFRVooX9/+GG7l34WJqiZUhE2Gsz7lCIk2jaY2JR1Ku4sNjWwAAb/sOxFMd/SWuiDQFw0E9VW5MlHLFREEQ8O6RPxGVdhNm+nKED5oMO2POFRJpqoqtnKVuTLycnYaXD6xBqaDEqHa+eK9rqGS1kOZhOGiAivnDyMhIFBcXS1LDV6f2YOv10+VzhQOfhbsV5wqJNJmtrS06d+4MQLo3FukFeQjbsxK5xUXoad8W3/R5kkuqkwjDQQO4u7vD1tYWRUVFiI6ObvLX/+NKDBbH7QcAzA8cjb5OHZu8BiKqu8qNiWVlZU362oWlxZi8LxxJ97LhZm6LFQOfg1yX7WckxnDQADo6OpJt5Xw05So+OLoZAPCmTzDGd+rRpK9PRPXn6+srakxsKmVKJd48uAFxd5NgJTdG+KBJsDI0abLXJ+3BcNBAgYGB0NHRwY0bN5CUlNQkr3klOx0v3Z8r/D83H7zfjXOFRNpEqsbEL2L+wa6EeBjo6GJFSBjaWdg22WuTdmE4aKCmXjHxTuF/c4U97Nrgmz5PcnlTIi1UsTfL+fPncffu3UZ/vfALx7E8vrzH4Zu+T6KnfdtGf03SXvyrogaVV0xszMbEwtISPL9vNRLvZaGNmQ1WhITBUE+/0V6PiBpP5RUTG7sxcV/iRXwatR0A8EG3wXi8nV+jvh5pP4YDNfDw8ICtrS0KCwsbbcVEpaDE24c24NSdRFjKjfFb6CRYc66QSKtVvLE4evRoozUmxmek4PWItVAKAsZ19MebPsGN8jrUvDAcqEFTNCZ+GbML/9w6Vz5XOPA5tLNo1SivQ0RNp7EbE1PycxC2dxXyS4vRx7ED5geO5i2LVCsMB2oSEBAAHR0dXL9+HcnJyWp97jUXo/DjuUMAgK/7PIleDm5qfX4ikoauri4CAwMBqP+Nxb0SBSbtXYW0glx0srTDT8HPQF9HV62vQc0Xw4GaWFhYNEpj4oGkS/gkchsA4L2uoRjd3k9tz01E0qtoTLxw4YLaGhNLlWV47cBanM9MRSsjU4QPmgQLuZFanptaBoYDNVJ3Y+L5zBS8euB3lAlKPNmhG972Hdjg5yQizdKqVSt07twZgiCopTFREATMjPoLB5IvwVBXH7+GTISrmbUaKqWWhOFAjTw8PGBjY4OCggKcPHmyQc91uyAXE/eEI7+0GIEO7bAgcAznComaKXWumPhz/BGsvhgJGWRY0n8curZyVUeJ1MJwzUw1qtjKedu2bTh8+DACAgLq9Tz5JQpM2rMKqQU56GDRCssHPgsDLm8quY8XvgwzXcN6Pz6vrAirMFONFVFz4evrCzMzM+Tk5ODMmTPo2rVrvZ5n561z+Dz6HwDApz2GYWgbL3WWSfXQ0HEDkGbs4JUDNQsKCoKOjg6uXbtWr8bEMqUSr0esw7nMFNgYmmB16GRYyo0boVIi0hR6enoNbkw8dScRbx7cAAECJnr0xkuefdRZIrUwDAdqZmFhAV9fXwB1X9hEEATMOvEX9iVdhFxXDysHTURrzhUStQgVUwv1WTExMS8Tk/eGo6isBANd3DGn10hOQ1KDMBw0gvpu5bzi/FGsunAcMsjwXb9x6NaqdWOVSEQapnJj4tGjR2v9uBxFIcL2rMLdonvwtHbE0gEToMdbFqmBGA4aQefOnVWNibGxsbV6zO5b8Zhz4m8AwCf+QzG8rXdjlkhEGqiuKyYWl5Xi5QNrcCUnHQ7G5lg1aBJM9eWNXSa1AAwHjaCiMREADh06VOP5cXeT8Mah9RAg4Fn3XnjFq29jl0hEGqhyY+LZs2cfea4gCPjo+BYcTb0GEz0DhA+aBEcTiyaqlJo7hoNGUrGV87Vr15CSkvLQ85LuZWHS3lUoLC3BAOdOmNv7/zhXSNRC6enpqe5yqqkxccmZA9hw5SR0ZDIsHTABnjZOTVEitRAMB43E0tISPj4+AB7+S55bXISJe1bhTuE9dLZywDLOFRK1eBVTC/Hx8cjIyKj2nK3XT2Nh7L8AgLm9RyHE1aPJ6qOWgeGgET2qMbFEWYZXDqzBpew02BubI3zQJJgZNOxeWCLSfnZ2dvDw8HhoY+KJtJuYdngjAOBlzz4I8+jd1CVSC8Bw0Ii6dOlSbWOiIAj46NgWHE65CmM9A4QPmggnU0vpCiUijfKwxsTrOXfx/L7VKFaW4bHWnpjRY5hUJVIzx3DQiHR0dBAUFARAPLXww9mDWH8l5v5c4dPwsnGWqkQi0kB+fn4wMzNDdnY2zp07BwDIKspH2J6VyFYUwNfWBUv6j4OOjEM4NQ7+n9XIKlZMvHr1KlJSUrD9ehzmn9wFAJjTcyQGuXaWuEIi0jSVGxMPHTqEotISvLD/N9zMy4CLqSVWDZoIIz0Diauk5ozhoJFVbkzc9O8/eOdI+Vzhi12CMLlLoJSlEZEGq7gdOj4+HtP+XYMTaTdhbmCI1aGT0crITOLqqLljOGgCFfOHcSeiYXovC0Nad8GnPYZLXBURaTJ7e3u4u7tDEARciDkNPZkOlgc/i06W9lKXRi0At/prRPfuKRB3KgUnozOhIzODoTwbP8esg21iBO4mn4Bx52AYdx4AXVMbqUslIg3UuUdXXE5LQpGRDAuCxqCPUwepS6IWguFAzUqKyxAfn4ZTMUm4dPEOlEoBAGBs2A+nnW4iq3gHLFMvIif1InL2LwNkMshdfWHUeQCMOwfDyL0fdI3MJf4qiEgTJFnpYYe7Pno5tMO4jv5Sl0MtCKcV1ECpFHD1yl38sS4On83cg7WrY3HhfDqUSgEurhbwCXHAti7RuOuSg5AF5+H05iZYDnoDBs6egCBAkXAa2bsXIWXRKFybYouEzwJQcKl+27ZS8zVv3jzIZDJMnTpV6lKoiRy/fR2QybjIEdVbfccNXjlogNSUXJw6mYxTJ5ORk1OkOm5lZYSu/s7o2t0Z9vZm+ObUXhTdKcFgx87QM7WGaffHYdr9cQBAaU4aCi4cQOHFCBRcOICStKsoun4COoamEn1VpImio6OxfPlyVXMrNX+lyrLycAAgyLG9xNWQNmrIuMFwUEc52YU4fSoFsTHJSE3JVR03MtKHj58junV3Rhs3a+jo/Lc/wrHb1wAAgQ5Vf8H1LOxh3ns8zHuPBwCUZCSg8GIE5K6+jfyVkLa4d+8ennnmGfz888+YO3eu1OVQEzmXkYK8EgXMDQzhZc19E6huGjpuMBzUQlFRKc6dScWpk8m4euUuhPI2AujqytC5iz26+jvDo7Md9PWr7otQWFqM2PQEAEBgLdK/vk1r6AeFqbV+0iy5ubmiz+VyOeTyh2+zO2XKFAwfPhyDBg1iOGhBjt2/atDb3g26OpwBprqNHQ0dNxgOHqKsTInLl+7g1MlkxJ+9jZISperf2rpZoZu/C3x8HWFs8uiFSGLSb6FYWQZHYwu4mfOuBAJcXV1Fn8+aNQuzZ8+u9tz169cjNjYW0dHRTVAZaZKjqfevOHJKge6r7dihjnGD4aASQRCQlJiD2JgkxJ1Kwb17/22WZNvKBN39XeDXzQk2tia1fs5jqeXpP9CxHbdiJgBAYmIizM3/uyPlYck/MTERb7/9Nv79918YGnJTrpakuKwU0Wk3ATAc0H9qM3aoa9xgOACQmVGAUyeTEXsyCXfS81XHTUwN4NfVCd38XeDialGvP+4V6Z8NRVTB3Nxc9Av+MCdPnkR6ejq6d++uOlZWVoZDhw7h+++/h0KhgK4ut/hujuLuJqGgtBjWchN4WHHRIypXm7FDXeNGiw0HBQXFOHM6FbExybh5I1N1XE9fB55eDujm74xO7q2gq1v/ub57JQrE3U0CwPRPdRcSEoKzZ8+Kjk2ePBkeHh6YPn06g0EzVvGmIsCxHTdXojpR17jRosJBaWkZLpxPx6mYZFw4n46ysvI+ApkMaN/BFt38neHl4wBDQ321vF7U7RsoE5RoY2YNF1MrtTwntRxmZmbw8vISHTMxMYGNjU2V49S8HOMVR6ondY0bzT4cKJUCbt3MQmxMEs6cTkVhYYnq3xydzNC1uwu6dnOChaWR2l/7GBuKiKiOikpLcPJO+R1ODAcklWYbDtLT7iH2ZBJOnUxGVmah6ri5hRxduzmjm78LHJ0ad5niiluRqlvfgKg+IiIipC6BGtnJOwlQlJXC3sgM7cxtpS6HmoH6jBvNKhzcy1PcX6AoCUmJOarjBnJd+Pg6omt3F7TvYCNaoKixZCkKcC4jBUD5nQpERLVR+Yoj73AiqWh9OCguLkP8uduIjUnClUt3VRsd6ejI0MmjFbp1d0YXLwcYGDRt81bk7esQIKCDRSvYG3MjJSKqHa5vQJpAK8OBUing2pW7iI1JxtmzqShWlKn+zbW1Jbp1d4ZvVyeYmj181bnGVrG+AecMiai28ksUOH0nEQDHDpKWVoWDlORcxJ5MwunYZOTmKFTHra2NVRsd2dlpxoZFbEYkoro6kXYTpYISrqZWaG1mLXU51IJpfDjIzi7E6ZPJiD2ZjNupearjRsb68PVzur/RkZVGzc3dKczDpew0AECAA/sNiKh2/ptS4LhB0tLIcFBUVIKzceV9BNevZVTa6EgHXTzt0NXfBR6dW0FPTzMXgTl+f0qhi7UjrA1rv9QyEbVsFVs0Bzp2kLgSauk0JhyUlSlx6eL9jY7O3UZppY2O3Npbo1t3Z3j7OsLY+NEbHWkCLplMRHWVoyjE2YxkAEAgrziSxCQNB4IgIDEhG7ExyYg7lYL8/P82OrKzM0U3f2f4dXeGtbWxhFXW3X/rG/AXnIhqJyrtBpSCgHbmtnA0sZC6HGrhJAkHGXfzEXsyGadOJuPunf82OjI1NYBfN2d083eGs0v9NjqSWkp+Dm7k3oWOTIZeDAdEVEu84kiapMnCQX5+Mc6cTkFsTDJu3cxSHdc30IWXtwO6dXdGh062DdroSBNU3KXgbeMMcwNus0tEtcP1DUiTNGo4KCkpw4X4NJw6mYyLF9JRVlbeWSiTAR062qKbvws8vR1gaKgxrQ8Nxg1TiKiuMoru4WLWbQC8w4k0g9r/KiuVAm5cz8Spk+UbHRUVlar+zcnZHN38XeDb1QkWFs3vXbUgCLw0SER1VnGHk4eVA2yNNGOtFmrZ1BYO0m7nqfoIsrP+2+jI0tIQXbuXL1Dk4Ni8lxFOuJeJ5Pxs6OvoooddW6nLISItwSZm0jRqCQfFxWX47tsjKCkuX8bY0FAP3r6O6ObvDLd2TbPRkSaouGrQtZUrjPU1/5ZLItIMvOJImkYt4cDAoHzXw4KCEnT3d0bnLvbQb+KNjjRBxX4KnDMkotq6XZCLazl3IIMMvRzcpC6HCIAapxWeetpXK289VBdBENiMSER19t8dTk6wlGvXmi7UfKntvsGWHAwA4GrOHaQX5kGuq4durVpLXQ4RaQnewkiaSLsXFdAgFenf364NDPX0Ja6GiLQFd3AlTcRwoCZsKCKiukrIy0TivSzoyXTQ076t1OUQqTSf1YckpBSU/+2m5sBw0Fx9H+IOeQPmhBWKAuCyGgsirVdx1cDX1gWm+nKJq6HG0NBxA5Bm7OCVAzW4mHUbWYoCGOsZwLeVi9TlEJGWqFjfgFccSdMwHKhBxZRCL3s36Ou0vFs4iajuuKIqaTKGAzWoWN8g0JHrGxBR7VzPvYu0glwY6Oiim10bqcshEmE4aKBSZRkieWmQiOqoot+gu10bGPEOJ9IwDAcNdC4jBXklClgYGMLT2knqcohIS3BKgTQZw0EDVfyC93ZoB10dfjuJqGZKQVlpOpLhgDQP/5o1EBcwIaK6upSVjkxFPoz09OFnyzucSPMwHDRAcVkpTqTfBMD1DYio9o6mXgUA9LRrCwNdLjdDmofhoAFO301CYWkJbAxN4G5lJ3U5RKQlVIum8YojaSiGgwZQTSk4tIeOjN9KIqpZmfK/FVXZjEiain/RGuC/3dS4vgGp37Jly+Dj4wNzc3OYm5sjICAAO3fulLosaqBzmSnILS6Cmb4cXja8w4nUS13jBsNBPRWWluBk+i0ATP/UOFxcXDB//nzExMQgJiYGAwcOxKhRoxAfHy91adQAxyrd4aTHFVVJzdQ1brATpp5i02+hWFkGe2NzuJnbSl0ONUMjR44Uff7FF19g2bJliIyMhKenp0RVUUPxiiM1JnWNGwwH9VR5AROZTCZxNaRNcnNzRZ/L5XLI5Y/eka+srAwbN25Efn4+AgICGrM8akQlyjKcSLsJgFccqe7qOnY0ZNzgtEI9cTc1qi9XV1dYWFioPubNm/fQc8+ePQtTU1PI5XK8+uqr2LJlC7p06dKE1ZI6xd1JQkFpMazkxvCwcpC6HNIytR071DFu8MpBPdwrUeD0nUQAQKADLw1S3SQmJsLc3Fz1+aOSv7u7O06fPo3s7Gxs2rQJEydOxMGDBxkQtFTF+gYBDu14hxPVWW3HDnWMGwwH9XAi7SZKBSVam1rD1cxa6nJIy1R0EdeGgYEBOnToAADw9/dHdHQ0Fi9ejJ9++qkxS6RGwiuO1BC1HTvUMW4wutbDMTYUkUQEQYBCoZC6DKqHotISxPAOJ5JAfcYNXjmoB+6nQE3h448/xtChQ+Hq6oq8vDysX78eERER2LVrl9SlUT2cvJMARVkp7IzM0N6ildTlUDOlrnGD4aCOshUFOJeZAoDhgBpXWloannvuOaSmpsLCwgI+Pj7YtWsXQkNDpS6N6qHymwre4USNRV3jBsNBHUXdvgGlIKC9RSs4GNdu3pioPlasWCF1CaRGnI6kpqCucYM9B3VUeX0DIqLaKCgpxqn7dzhx7CBtwHBQR8e4mxoR1dGJ9PI7nFxMLdHalHc4keZjOKiDjKJ7uJh1GwDXNyCi2jua8t8Oruw3IG3AcFAHx1PLrxp0tnKAtaGJxNUQkbY4dpt3OJF2YTiog6O8hZGI6ii3uAhnM5IBcOwg7cFwUAdsRiSiuoq6fR1KQYCbuS2cTCykLoeoVhgOaik1PwfXc+9CRyZDL3s3qcshIi3BNxWkjRgOaqniLgVvG2dYyI0kroaItIVqOpJNzKRFGA5q6dj93dQCHZj+iah2MovyceH+HU4BXPyItAjDQS0du3+nQpATwwER1U7FFUd3S3u0MjKTuBqi2mM4qIWEvEwk3suCnkwHPezaSF0OEWkJbtJG2orhoBYqfsG7tnKFib5c4mqISFscYzMiaSmGg1rg+gZEVFe3C3JxNecOZJChtwPvcCLtwnBQA0EQeGmQiOqsYkVVLxsnWMqNJa6GqG4YDmpwPfcu0grzINfVQ/dWraUuh4i0xNGKO5z4poK0EMNBDSqmFLq3ag1DPX2JqyEibVFxhxPXNyBtxHBQAzYUEVFdJeZlIuFeJnRlOujFfgPSQgwHj6AUlP+lf4YDIqqlivUNfG1dYMo7nEgLMRw8wsWsNGQq8mGsZwBfWxepyyEiLcErjqTtGA4eoeIXvKd9Wxjo6klcDRFpA0EQuNkSaT2Gg0fgLYxEVFc3cu/idkEuDHR00Z0rqpKWYjh4CEEQEHsnEQDTPxHVXuydBABAN7vWMOIdTqSleK38IWQyGY4/+QFi0m/By9pJ6nKISEuM7dAdPe3dkFtcKHUpRPXGcPAIRnoG6OvUUeoyiEjLtDazlroEogZhOCCqpYnZ42FqIKv34+8VC/hOjfUQkeZr6LgBSDN2sOeAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6INNS8efPQo0cPmJmZwc7ODo8//jguXbokdVlEpMHUNW4wHBBpqIMHD2LKlCmIjIzEnj17UFpaisGDByM/P1/q0ohIQ6lr3OA6B0QaateuXaLPV65cCTs7O5w8eRL9+vWTqCoi0mTqGjcYDoiaWG5uruhzuVwOuVxe4+NycnIAANbWXH2PqCWqz9hR33GD0wpETczV1RUWFhaqj3nz5tX4GEEQMG3aNPTp0wdeXl5NUCURaZq6jh0NGTd45YCoiSUmJsLc3Fz1eW2uGrzxxhs4c+YMjhw50pilEZEGq+vY0ZBxg+GAqImZm5uLfsFr8uabb2L79u04dOgQXFxcGrEyItJkdRk7GjpuMBwQaShBEPDmm29iy5YtiIiIgJubm9QlEZGGU9e4wXBApKGmTJmCtWvXYtu2bTAzM8Pt27cBABYWFjAyMpK4OiLSROoaN9iQSKShli1bhpycHAwYMACOjo6qjw0bNkhdGhFpKHWNG7xyQKShBEGQugQi0jLqGjd45YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiET0pC6ASFuM6PM2dIzk9X68slABrFukvoKISOM1dNwApBk7eOWAiIiIRBgOiDTUoUOHMHLkSDg5OUEmk2Hr1q1Sl0REWkAdYwfDAZGGys/Ph6+vL77//nupSyEiLaKOsYM9B0RNLDc3V/S5XC6HXF51TnLo0KEYOnRoU5VFRBquKccOXjkgamKurq6wsLBQfcybN0/qkohICzTl2MErB0RNLDExEebm5qrPq0v+REQPasqxg+GAqImZm5uLfsGJiGqjKccOTisQERGRCMMBERERiXBagUhD3bt3D1evXlV9fuPGDZw+fRrW1tZo3bq1hJURkSZTx9jBcECkoWJiYhAcHKz6fNq0aQCAiRMnYtWqVRJVRUSaTh1jB8MBkYYaMGAABEGQugwi0jLqGDvYc0BEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcECk4ZYuXQo3NzcYGhqie/fuOHz4sNQlEZGGa+i4wXBApME2bNiAqVOn4pNPPsGpU6fQt29fDB06FAkJCVKXRkQaSh3jBsMBkQb75ptv8MILL+DFF19E586dsWjRIri6umLZsmVSl0ZEGkod44ZeI9ZH1KwIhQooG/h4AMjNzRUdl8vlkMvlVc4vLi7GyZMn8eGHH4qODx48GMeOHWtAJUTUVBo6blQ8B1C7sUNd4wbDAVENDAwM4ODggNvvNfzduqmpKVxdXUXHZs2ahdmzZ1c59+7duygrK4O9vb3ouL29PW7fvt3gWoio8ahz3ABqP3aoa9xgOCCqgaGhIW7cuIHi4uIGP5cgCJDJZKJj1V01qOzB86t7DiLSLOocN4C6jx0NHTcYDohqwdDQEIaGhk36mra2ttDV1a2S9tPT06u8KyAizaPN4wYbEok0lIGBAbp37449e/aIju/ZsweBgYESVUVEmkxd4wavHBBpsGnTpuG5556Dv78/AgICsHz5ciQkJODVV1+VujQi0lDqGDcYDog02Lhx45CRkYHPPvsMqamp8PLywj///IM2bdpIXRoRaSh1jBsyQRCERqyRiIiItAx7DoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISOT/AZBWi5j0mjJbAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [62.52031121665544]\n", + "(0, 9) added\n", + "Checking edge: (0, 2)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [63.647466378271766]\n", + "(0, 2) already in graph, angles = [88.68317271320804]\n", + "(0, 2) already in graph, angles updated = [88.68317271320804, 63.647466378271766]\n", + "Checking edge: (0, 3)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [55.78135886136459]\n", + "(0, 3) added\n", + "Checking edge: (9, 2)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 2\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 1])\n", + "angles: [126.1677775949272]\n", + "(9, 2) added\n", + "Checking edge: (9, 3)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 2\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 1])\n", + "angles: [88.08366041995446]\n", + "(9, 3) added\n", + "Checking edge: (2, 3)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 2\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 1])\n", + "angles: [145.74856198511836]\n", + "(2, 3) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 2\n", + "Adjacent strokes (list): [1, 1, 8]\n", + "Adjacent strokes (uniques): {8, 1}\n", + "Checking edge: (8, 1)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [107.29030340175414]\n", + "(8, 1) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 3\n", + "Adjacent strokes (list): [1, 0, 1, 0]\n", + "Adjacent strokes (uniques): {0, 1}\n", + "Checking edge: (0, 1)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [[90.12528714780073, 89.74560192447649], [90.24732195021957, 89.88178897750322]]\n", + "(0, 1) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 4\n", + "Adjacent strokes (list): [2, 6, 2, 6]\n", + "Adjacent strokes (uniques): {2, 6}\n", + "Checking edge: (2, 6)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [[94.78903631548253, 84.23886881283048], [81.14186114900058, 99.83023372268642]]\n", + "(2, 6) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 5\n", + "Adjacent strokes (list): [3, 3, 1, 1]\n", + "Adjacent strokes (uniques): {1, 3}\n", + "Checking edge: (1, 3)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [[90.46915502723192, 89.57504791798526], [89.58581817377714, 90.36997888100568]]\n", + "(1, 3) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 6\n", + "Adjacent strokes (list): [3, 3, 4, 4]\n", + "Adjacent strokes (uniques): {3, 4}\n", + "Checking edge: (3, 4)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [[89.83847705650136, 91.21166198882482], [89.75197989966416, 89.19788105500966]]\n", + "(3, 4) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 7\n", + "Adjacent strokes (list): [3]\n", + "Adjacent strokes (uniques): {3}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 8\n", + "Adjacent strokes (list): [4]\n", + "Adjacent strokes (uniques): {4}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 9\n", + "Adjacent strokes (list): [4, 7, 4]\n", + "Adjacent strokes (uniques): {4, 7}\n", + "Checking edge: (4, 7)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [91.62276842306488]\n", + "(4, 7) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 10\n", + "Adjacent strokes (list): [4, 0, 4, 0]\n", + "Adjacent strokes (uniques): {0, 4}\n", + "Checking edge: (0, 4)\n" + ] + }, { "data": { + "image/png": "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", "text/plain": [ - "NodeDataView({0: {'edge_ids': [0, 3, 15, 27], 'geometry': , 'x': 1603374.6625343116, 'y': 6464077.898491419}, 1: {'edge_ids': [11, 28, 2, 30], 'geometry': , 'x': 1603707.1065106073, 'y': 6464238.853991265}, 2: {'edge_ids': [4, 5, 6], 'geometry': , 'x': 1603149.9288811635, 'y': 6464130.224503239}, 3: {'edge_ids': [26], 'geometry': , 'x': 1603342.3426854417, 'y': 6464406.368225728}, 4: {'edge_ids': [1, 12, 14, 25], 'geometry': , 'x': 1603237.0487682838, 'y': 6464133.622486805}, 5: {'edge_ids': [20], 'geometry': , 'x': 1603207.5969886228, 'y': 6463992.707728057}, 6: {'edge_ids': [16, 17, 29, 18, 23], 'geometry': , 'x': 1603592.2349246691, 'y': 6464121.336160048}, 7: {'edge_ids': [7, 8, 21, 9, 24, 22, 13], 'geometry': , 'x': 1603264.6577362637, 'y': 6463848.97596353}, 8: {'edge_ids': [19], 'geometry': , 'x': 1603028.737187382, 'y': 6463900.594576759}, 9: {'edge_ids': [10], 'geometry': , 'x': 1603137.4077031056, 'y': 6463800.908382258}})" + "
" ] }, - "execution_count": 27, "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "stroke_graph = nx.Graph()\n", - "stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", - "stroke_graph.graph[\"approach\"] = graph.graph[\"approach\"]\n", - "stroke_graph.add_nodes_from(\n", - " [\n", - " (\n", - " row.stroke_id, \n", - " {\n", - " \"edge_ids\": row.edge_ids,\n", - " \"geometry\": row.rep_point,\n", - " \"x\": row.rep_point.xy[0][0],\n", - " \"y\": row.rep_point.xy[1][0],\n", - " }\n", - " ) for _, row in stroke_gdf.iterrows()\n", - " ]\n", - ")\n", - "# node names are the stroke IDs.\n", - "# each node has the attribute \"edge_ids\".\n", - "stroke_graph.nodes(data=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "to find the edges of the stroke graph, we look at the primal graph's nodes and the stroke_ids of their adjacent edges" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ + "output_type": "display_data" + }, { "name": "stdout", "output_type": "stream", "text": [ - "(1603585.6402153103, 6464428.773867372)\n", - "[0, 1, 1] {0, 1}\n", - "(0, 1)\n", - "\n", - "\n", - "(1603413.2063240695, 6464228.730248732)\n", - "[0, 1, 0, 2, 3] {0, 1, 2, 3}\n", - "(0, 1)\n", - "(0, 1) already in graph!\n", - "(0, 2)\n", - "(0, 3)\n", - "(1, 2)\n", - "(1, 3)\n", - "(2, 3)\n", - "\n", - "\n", - "(1603268.502117987, 6464060.781328565)\n", - "[4, 4, 5] {4, 5}\n", - "(4, 5)\n", - "\n", - "\n", - "(1603363.557831175, 6464031.88480676)\n", - "[4, 0, 4, 0] {0, 4}\n", - "(0, 4)\n", - "\n", - "\n", - "(1603607.3029882177, 6464181.852772597)\n", - "[1, 6, 1, 6] {1, 6}\n", - "(1, 6)\n", - "\n", - "\n", - "(1603226.9576840235, 6464160.158361825)\n", - "[2, 2, 4, 4] {2, 4}\n", - "(2, 4)\n", - "\n", - "\n", - "(1603039.9632033885, 6464087.491175889)\n", - "[2, 2, 7, 7] {2, 7}\n", - "(2, 7)\n", - "\n", - "\n", - "(1602887.2996537155, 6464029.975730775)\n", - "[2] {2}\n", - "\n", - "\n", - "(1602970.3773896934, 6464268.058242684)\n", - "[7] {7}\n", - "\n", - "\n", - "(1603090.513384159, 6463971.106984773)\n", - "[7, 8, 7] {8, 7}\n", - "(8, 7)\n", - "\n", - "\n", - "(1603317.7832565615, 6463836.796863219)\n", - "[7, 0, 7, 0] {0, 7}\n", - "(0, 7)\n", - "\n", - "\n", - "(1603202.3783404578, 6463872.287568242)\n", - "[7, 9, 7] {9, 7}\n", - "(9, 7)\n", - "\n", - "\n", - "(1603071.956425043, 6463729.978565)\n", - "[9] {9}\n", + "angles_gdf len 4\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [[90.29328808503493, 90.43376966492825], [89.84379058832397, 89.42915166171285]]\n", + "(0, 4) added\n", + "**************************************************************\n", + " \n", + " \n", "\n", + "Node: 11\n", + "Adjacent strokes (list): [4, 5, 4]\n", + "Adjacent strokes (uniques): {4, 5}\n", + "Checking edge: (4, 5)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [91.18142429639235]\n", + "(4, 5) added\n", + "**************************************************************\n", + " \n", + " \n", "\n", - "(1603650.450422848, 6464368.600601688)\n", - "[1, 6, 1, 6] {1, 6}\n", - "(1, 6)\n", - "(1, 6) already in graph!\n", - "\n", - "\n", - "(1603513.6499006122, 6463789.557147608)\n", - "[7, 6, 6, 7] {6, 7}\n", - "(6, 7)\n", - "\n", - "\n", - "(1603795.889337571, 6463785.444077063)\n", - "[7] {7}\n", - "\n", - "\n", - "(1603558.489391506, 6463985.80677705)\n", - "[4, 6, 6] {4, 6}\n", - "(4, 6)\n", - "\n", - "\n", - "(1602959.8799617135, 6463839.712475327)\n", - "[8] {8}\n", - "\n", - "\n", - "(1603146.6963311615, 6463924.630126579)\n", - "[5, 7, 7] {5, 7}\n", - "(5, 7)\n", - "\n", + "Node: 12\n", + "Adjacent strokes (list): [5]\n", + "Adjacent strokes (uniques): {5}\n", + "**************************************************************\n", + " \n", + " \n", "\n", - "(1603473.6416756227, 6463625.487127112)\n", - "[6] {6}\n", + "Node: 13\n", + "Adjacent strokes (list): [2, 6, 2, 6]\n", + "Adjacent strokes (uniques): {2, 6}\n", + "Checking edge: (2, 6)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [[132.83556629096833, 48.92275878691167], [59.79419820769666, 118.44747671442332]]\n", + "(2, 6) already in graph, angles = [[94.78903631548253, 84.23886881283048], [81.14186114900058, 99.83023372268642]]\n", + "(2, 6) already in graph, angles updated = [[94.78903631548253, 84.23886881283048], [81.14186114900058, 99.83023372268642], [132.83556629096833, 48.92275878691167], [59.79419820769666, 118.44747671442332]]\n", + "**************************************************************\n", + " \n", + " \n", "\n", + "Node: 14\n", + "Adjacent strokes (list): [4, 6, 6, 4]\n", + "Adjacent strokes (uniques): {4, 6}\n", + "Checking edge: (4, 6)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [[87.26341801197296, 93.7165388156464], [90.3973936094473, 88.62264956293333]]\n", + "(4, 6) added\n", + "**************************************************************\n", + " \n", + " \n", "\n", - "(1603077.5001356844, 6464475.322968743)\n", - "[4] {4}\n", + "Node: 15\n", + "Adjacent strokes (list): [4]\n", + "Adjacent strokes (uniques): {4}\n", + "**************************************************************\n", + " \n", + " \n", "\n", + "Node: 16\n", + "Adjacent strokes (list): [1, 6, 6]\n", + "Adjacent strokes (uniques): {1, 6}\n", + "Checking edge: (1, 6)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 2])\n", + "angles: [90.39785291117907]\n", + "(1, 6) added\n", + "**************************************************************\n", + " \n", + " \n", "\n", - "(1603287.303979983, 6464587.704889874)\n", - "[3] {3}\n", + "Node: 17\n", + "Adjacent strokes (list): [7]\n", + "Adjacent strokes (uniques): {7}\n", + "**************************************************************\n", + " \n", + " \n", "\n", + "Node: 18\n", + "Adjacent strokes (list): [8, 4, 4]\n", + "Adjacent strokes (uniques): {8, 4}\n", + "Checking edge: (8, 4)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 2])\n", + "angles: [90.34989164828197]\n", + "(8, 4) added\n", + "**************************************************************\n", + " \n", + " \n", "\n", - "(1603278.8993584276, 6463669.185595578)\n", - "[0] {0}\n", + "Node: 19\n", + "Adjacent strokes (list): [6]\n", + "Adjacent strokes (uniques): {6}\n", + "**************************************************************\n", + " \n", + " \n", "\n", + "Node: 20\n", + "Adjacent strokes (list): [1]\n", + "Adjacent strokes (uniques): {1}\n", + "**************************************************************\n", + " \n", + " \n", "\n", - "(1603537.1939729159, 6464558.11228298)\n", - "[1] {1}\n", + "Node: 21\n", + "Adjacent strokes (list): [9]\n", + "Adjacent strokes (uniques): {9}\n", + "**************************************************************\n", + " \n", + " \n", "\n", + "Node: 22\n", + "Adjacent strokes (list): [0]\n", + "Adjacent strokes (uniques): {0}\n", + "**************************************************************\n", + " \n", + " \n", "\n", - "(1603706.3884669733, 6464617.783583014)\n", - "[6] {6}\n", + "Node: 23\n", + "Adjacent strokes (list): [2]\n", + "Adjacent strokes (uniques): {2}\n", + "**************************************************************\n", + " \n", + " \n", "\n", + "Node: 24\n", + "Adjacent strokes (list): [6]\n", + "Adjacent strokes (uniques): {6}\n", + "**************************************************************\n", + " \n", + " \n", "\n" ] } ], "source": [ "for n in graph.nodes:\n", - " print(n)\n", + "\n", + " node_id = graph.nodes[n][\"nodeID\"] # TODO Remove (only for plotting now)\n", + " print(f\"Node: {node_id}\")\n", + " \n", " es = list(graph.edges(n, keys=True))\n", " stroke_list = [graph.edges[e][\"stroke_id\"] for e in es]\n", " stroke_set = set(stroke_list)\n", - " print(stroke_list, stroke_set)\n", + " \n", + " print(\"Adjacent strokes (list):\", stroke_list)\n", + " print(\"Adjacent strokes (uniques):\", stroke_set)\n", + " \n", " # for all size2 combinations from stroke_set\n", " for c in combinations(stroke_set, 2):\n", - " print(c)\n", - " continuities = {}\n", + " \n", + " print(\"Checking edge:\", c)\n", + " \n", + " # get angles at that primal node for this 2-stroke combination c\n", + " es = list(graph.edges(n, keys=True))\n", + " stroke_ids = [graph.edges[e][\"stroke_id\"] for e in es]\n", + " geoms = [graph.edges[e][\"geometry\"] for e in es]\n", + " segments = [get_segment(geom, n) for geom in geoms] # extracting only edge segments that touch this node\n", + " angles_gdf = gpd.GeoDataFrame(\n", + " {\n", + " \"stroke_id\": stroke_ids,\n", + " \"segment\": segments,\n", + " \"geometry\": [LineString(x) for x in segments]\n", + " }\n", + " )\n", + "\n", + " # TODO plots can be removed later\n", + " fig, axs = plt.subplots(1,2, sharex=True, sharey=True)\n", + " ax = axs[0]\n", + " angles_gdf.plot(ax=ax, column=\"stroke_id\", legend=True, cmap = \"Dark2\")\n", + " ax.set_title(f\"All strokes at node {node_id}\")\n", + " ax.set_axis_off()\n", + "\n", + " # filter out only those linestring that belong to current 2-stroke edge\n", + " angles_gdf = angles_gdf[angles_gdf.stroke_id.isin(c)].reset_index(drop=True)\n", + " \n", + " # TODO plots can be removed later\n", + " ax = axs[1]\n", + " angles_gdf.plot(ax=ax, column=\"stroke_id\", legend=True, cmap = \"Dark2\")\n", + " ax.set_title(f\"Strokes {c} at node {node_id}\")\n", + " ax.set_axis_off()\n", + " \n", + " plt.show()\n", + " \n", + "\n", + " if len(angles_gdf)==2:\n", + "\n", + " print(\"angles_gdf len 2\")\n", + " # connectivity equals 1 here\n", + " connectivity = 1\n", + "\n", + " # angle between 2 strokes is just angle between \n", + " # the 2 linestrings in the gdf:\n", + " row_a = angles_gdf.loc[0]\n", + " row_b = angles_gdf.loc[1]\n", + " angles = [\n", + " _angle_cos(\n", + " row_a.segment[1],\n", + " row_a.segment[0],\n", + " row_b.segment[1]\n", + " )\n", + " ]\n", + "\n", + " elif len(angles_gdf)==3:\n", + "\n", + " print(\"angles_gdf len 3\")\n", + "\n", + " # connectivity equals 1 here\n", + " connectivity = 1\n", + "\n", + " # the iteration has to go through the stroke that appears TWICE\n", + " stroke_count = dict(Counter(angles_gdf.stroke_id))\n", + " stroke_count = {v:k for k,v in stroke_count.items()}\n", + " \n", + " # separate angles_gdf into 2 separate gdf (one for each stroke)\n", + " angles_stroke_a = angles_gdf[angles_gdf[\"stroke_id\"]==stroke_count[1]].copy()\n", + " angles_stroke_b = angles_gdf[angles_gdf[\"stroke_id\"]==stroke_count[2]].copy()\n", + "\n", + " angles = []\n", + " # there is only ONE row_a stroke segment\n", + " for i, row_a in angles_stroke_a.iterrows():\n", + " angles_stroke = []\n", + " # iterate through BOTH stroke b segments\n", + " for j, row_b in angles_stroke_b.iterrows():\n", + " assert row_a.segment[0] == row_b.segment[0]\n", + " # compute angle between stroke a and stroke b segments\n", + " # and add to list of current angles\n", + " angles_stroke.append(_angle_cos(\n", + " row_a.segment[1],\n", + " row_a.segment[0],\n", + " row_b.segment[1])\n", + " )\n", + " # keep the smaller of the 2 angles to add to list of angles for the stroke pair\n", + " angles.append(min(angles_stroke))\n", + "\n", + " elif len(angles_gdf)==4:\n", + " print(\"angles_gdf len 4\")\n", + "\n", + " # connectivity equals 2 here\n", + " connectivity = 2\n", + "\n", + " # separate angles_gdf into 2 separate gdf (one for each stroke)\n", + " angles_stroke_a = angles_gdf[angles_gdf[\"stroke_id\"]==c[0]].copy()\n", + " angles_stroke_b = angles_gdf[angles_gdf[\"stroke_id\"]==c[1]].copy()\n", + "\n", + " angles = []\n", + " # iterate through stroke a segments\n", + " for i, row_a in angles_stroke_a.iterrows():\n", + " angles_stroke = []\n", + " # iterate through stroke b segments\n", + " for j, row_b in angles_stroke_b.iterrows():\n", + " assert row_a.segment[0] == row_b.segment[0]\n", + " # compute angle between stroke a and stroke b segments\n", + " # and add to list of current angles\n", + " angles_stroke.append(_angle_cos(\n", + " row_a.segment[1],\n", + " row_a.segment[0],\n", + " row_b.segment[1])\n", + " )\n", + " # keep BOTH ANGLES to add to list of angles for this stroke pair\n", + " angles.append(angles_stroke)\n", + " \n", + "\n", + " else:\n", + " ValueError(f\"Length of angles_gdf expected to be in [2,3,4], but is {len(angle_gdf)}\")\n", + "\n", + " #### now that we have connectivity and angles, \n", + " print(f\"connectivity: {connectivity}\")\n", + " print(\"Counter values:\", Counter(angles_gdf.stroke_id).values())\n", + " print(\"angles:\", angles)\n", + "\n", + " # connectivity is added at stroke node level:\n", " for s in c:\n", - " continuities[s] = stroke_list.count(s)\n", + " stroke_graph.nodes[s][\"connectivity\"] += connectivity\n", + "\n", + " # and edge (or update edge info) at stroke edge level:\n", " if c not in stroke_graph.edges:\n", " edge_geom = LineString(\n", " [\n", @@ -1062,90 +1991,104 @@ " stroke_graph.nodes[c[1]][\"geometry\"]\n", " ]\n", " )\n", - " stroke_graph.add_edge(c[0], c[1], continuities=continuities, geometry=edge_geom)\n", + " stroke_graph.add_edge(\n", + " c[0],\n", + " c[1],\n", + " geometry=edge_geom,\n", + " angles=angles\n", + " )\n", + " print(f\"{c} added\")\n", + "\n", " else:\n", - " for s in c:\n", - " stroke_graph.edges[c][\"continuities\"][s] += continuities[s]\n", - " print(c, \"already in graph!\")\n", - " print(\"\\n\")\n", + " print(f\"{c} already in graph, angles =\", stroke_graph.edges[c][\"angles\"])\n", + " stroke_graph.edges[c][\"angles\"] += angles\n", + " print(f\"{c} already in graph, angles updated =\", stroke_graph.edges[c][\"angles\"])\n", + " print(\"**************************************************************\\n \\n \\n\")\n", "# we want to add edges for all stroke IDs that co-occur on edges that share the same node in the primal graph\n", "# [0, 1, 1] means: stroke0 has an endpoint here; stroke1 has a throughpoint here; we add the edge [0,1] in the strokes_graph, with the attribute \n", "# stroke = {0: \"end\", 1: \"through\"}\n", - "\n", " " ] }, { "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "EdgeDataView([(0, 1, {'continuities': {0: 3, 1: 3}, 'geometry': }), (0, 2, {'continuities': {0: 2, 2: 1}, 'geometry': }), (0, 3, {'continuities': {0: 2, 3: 1}, 'geometry': }), (0, 4, {'continuities': {0: 2, 4: 2}, 'geometry': }), (0, 7, {'continuities': {0: 2, 7: 2}, 'geometry': }), (1, 2, {'continuities': {1: 1, 2: 1}, 'geometry': }), (1, 3, {'continuities': {1: 1, 3: 1}, 'geometry': }), (1, 6, {'continuities': {1: 4, 6: 4}, 'geometry': }), (2, 3, {'continuities': {2: 1, 3: 1}, 'geometry': }), (2, 4, {'continuities': {2: 2, 4: 2}, 'geometry': }), (2, 7, {'continuities': {2: 2, 7: 2}, 'geometry': }), (4, 5, {'continuities': {4: 2, 5: 1}, 'geometry': }), (4, 6, {'continuities': {4: 1, 6: 2}, 'geometry': }), (5, 7, {'continuities': {5: 1, 7: 2}, 'geometry': }), (6, 7, {'continuities': {6: 2, 7: 2}, 'geometry': }), (7, 8, {'continuities': {8: 1, 7: 2}, 'geometry': }), (7, 9, {'continuities': {9: 1, 7: 2}, 'geometry': })])" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "stroke_graph.edges(data=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, + "execution_count": 70, "metadata": {}, "outputs": [], "source": [ - "# get gdfs of points and lines\n", - "points_strokes, lines_strokes = momepy.nx_to_gdf(stroke_graph, points=True, lines=True)\n" + "# OUTDATED VERSION: CONTINUITY ADDED TO EDGES (I THINK THIS IS WRONG? anvy)\n", + "# for n in graph.nodes:\n", + " \n", + "# print(\"Node:\", graph.nodes[n][\"nodeID\"])\n", + " \n", + "# es = list(graph.edges(n, keys=True))\n", + "# stroke_list = [graph.edges[e][\"stroke_id\"] for e in es]\n", + "# stroke_set = set(stroke_list)\n", + " \n", + "# print(\"Adjacent strokes (list):\", stroke_list)\n", + "# print(\"Adjacent strokes (uniques):\", stroke_set)\n", + " \n", + "# # for all size2 combinations from stroke_set\n", + "# for c in combinations(stroke_set, 2):\n", + "# print(\"Checking edge:\", c)\n", + "# continuities = {}\n", + "# for s in c: # s is the stroke ID\n", + "# continuities[s] = stroke_list.count(s)\n", + "# print(\"continuities\", continuities)\n", + "# angle = None # TODO\n", + "# if c not in stroke_graph.edges:\n", + "# edge_geom = LineString(\n", + "# [\n", + "# stroke_graph.nodes[c[0]][\"geometry\"],\n", + "# stroke_graph.nodes[c[1]][\"geometry\"]\n", + "# ]\n", + "# )\n", + "# stroke_graph.add_edge(\n", + "# c[0],\n", + "# c[1],\n", + "# continuities=continuities,\n", + "# geometry=edge_geom,\n", + "# angles=[angle]\n", + "# )\n", + "# print(f\"{c} added, continuities={continuities}\")\n", + "# else:\n", + "# for s in c:\n", + "# stroke_graph.edges[c][\"continuities\"][s] += continuities[s]\n", + "# stroke_graph.edges[c][\"angles\"].append(angle)\n", + "# print(f\"{c} already in graph, continuities=\", stroke_graph.edges[c][\"continuities\"])\n", + "# print(\"\\n\")\n", + "# # we want to add edges for all stroke IDs that co-occur on edges that share the same node in the primal graph\n", + "# # [0, 1, 1] means: stroke0 has an endpoint here; stroke1 has a throughpoint here; we add the edge [0,1] in the strokes_graph, with the attribute \n", + "# # stroke = {0: \"end\", 1: \"through\"}\n", + " " ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "lines_strokes[\"random_id\"] = lines_strokes.index" + "# get gdfs of points and lines\n", + "points_strokes, lines_strokes = momepy.nx_to_gdf(stroke_graph, points=True, lines=True)\n", + "# and also one with the prinal stroke geoms\n", + "points_strokes_primal = points_strokes.copy()\n", + "points_strokes_primal=points_strokes_primal.set_geometry(\"geometry_stroke\")\n", + "points_strokes_primal=points_strokes_primal.set_crs(points_strokes.crs)" ] }, { - "cell_type": "code", - "execution_count": 32, + "cell_type": "markdown", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "len(stroke_gdf)" + "**Final result for now**" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 102, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[(0, 1, {'continuities': {0: 3, 1: 3}, 'geometry': }), (0, 2, {'continuities': {0: 2, 2: 1}, 'geometry': }), (0, 3, {'continuities': {0: 2, 3: 1}, 'geometry': }), (0, 4, {'continuities': {0: 2, 4: 2}, 'geometry': }), (0, 7, {'continuities': {0: 2, 7: 2}, 'geometry': }), (1, 2, {'continuities': {1: 1, 2: 1}, 'geometry': }), (1, 3, {'continuities': {1: 1, 3: 1}, 'geometry': }), (1, 6, {'continuities': {1: 4, 6: 4}, 'geometry': }), (2, 3, {'continuities': {2: 1, 3: 1}, 'geometry': }), (2, 4, {'continuities': {2: 2, 4: 2}, 'geometry': }), (2, 7, {'continuities': {2: 2, 7: 2}, 'geometry': }), (4, 5, {'continuities': {4: 2, 5: 1}, 'geometry': }), (4, 6, {'continuities': {4: 1, 6: 2}, 'geometry': }), (5, 7, {'continuities': {5: 1, 7: 2}, 'geometry': }), (6, 7, {'continuities': {6: 2, 7: 2}, 'geometry': }), (7, 8, {'continuities': {8: 1, 7: 2}, 'geometry': }), (7, 9, {'continuities': {9: 1, 7: 2}, 'geometry': })]\n" - ] - }, { "data": { "text/html": [ @@ -1176,7 +2119,7 @@ " <meta name="viewport" content="width=device-width,\n", " initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />\n", " <style>\n", - " #map_150925926b6515bf456753c981c35968 {\n", + " #map_9b85d4d24a17fd4c7f7140653644c714 {\n", " position: relative;\n", " width: 100.0%;\n", " height: 100.0%;\n", @@ -1239,14 +2182,14 @@ "<body>\n", " \n", " \n", - " <div class="folium-map" id="map_150925926b6515bf456753c981c35968" ></div>\n", + " <div class="folium-map" id="map_9b85d4d24a17fd4c7f7140653644c714" ></div>\n", " \n", "</body>\n", "<script>\n", " \n", " \n", - " var map_150925926b6515bf456753c981c35968 = L.map(\n", - " "map_150925926b6515bf456753c981c35968",\n", + " var map_9b85d4d24a17fd4c7f7140653644c714 = L.map(\n", + " "map_9b85d4d24a17fd4c7f7140653644c714",\n", " {\n", " center: [50.102935750000015, 14.403062600000004],\n", " crs: L.CRS.EPSG3857,\n", @@ -1255,28 +2198,28 @@ " preferCanvas: false,\n", " }\n", " );\n", - " L.control.scale().addTo(map_150925926b6515bf456753c981c35968);\n", + " L.control.scale().addTo(map_9b85d4d24a17fd4c7f7140653644c714);\n", "\n", " \n", "\n", " \n", " \n", - " var tile_layer_5c406c4d0fba1ff0c6b00cc2a258846f = L.tileLayer(\n", + " var tile_layer_670fbb082a54e988eff33fb7763336e0 = L.tileLayer(\n", " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",\n", " {"attribution": "\\u0026copy; \\u003ca href=\\"https://www.openstreetmap.org/copyright\\"\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\"https://carto.com/attributions\\"\\u003eCARTO\\u003c/a\\u003e", "detectRetina": false, "maxZoom": 20, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}\n", " );\n", " \n", " \n", - " tile_layer_5c406c4d0fba1ff0c6b00cc2a258846f.addTo(map_150925926b6515bf456753c981c35968);\n", + " tile_layer_670fbb082a54e988eff33fb7763336e0.addTo(map_9b85d4d24a17fd4c7f7140653644c714);\n", " \n", " \n", - " map_150925926b6515bf456753c981c35968.fitBounds(\n", + " map_9b85d4d24a17fd4c7f7140653644c714.fitBounds(\n", " [[50.10007700000001, 14.398981599999999], [50.10579450000001, 14.407143600000008]],\n", " {}\n", " );\n", " \n", " \n", - " function geo_json_3fa45e69a7590c080a82d482bb078138_styler(feature) {\n", + " function geo_json_6f59948f50a81aaf649c171aae804855_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#3182bd", "fillColor": "#3182bd", "fillOpacity": 0.5, "weight": 8};\n", @@ -1300,58 +2243,59 @@ " return {"color": "#d9d9d9", "fillColor": "#d9d9d9", "fillOpacity": 0.5, "weight": 8};\n", " }\n", " }\n", - " function geo_json_3fa45e69a7590c080a82d482bb078138_highlighter(feature) {\n", + " function geo_json_6f59948f50a81aaf649c171aae804855_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_3fa45e69a7590c080a82d482bb078138_pointToLayer(feature, latlng) {\n", + " function geo_json_6f59948f50a81aaf649c171aae804855_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_3fa45e69a7590c080a82d482bb078138_styler(feature)\n", + " let style = geo_json_6f59948f50a81aaf649c171aae804855_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_3fa45e69a7590c080a82d482bb078138_onEachFeature(feature, layer) {\n", + " function geo_json_6f59948f50a81aaf649c171aae804855_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_3fa45e69a7590c080a82d482bb078138.resetStyle(e.target);\n", + " geo_json_6f59948f50a81aaf649c171aae804855.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_3fa45e69a7590c080a82d482bb078138_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_6f59948f50a81aaf649c171aae804855_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_3fa45e69a7590c080a82d482bb078138 = L.geoJson(null, {\n", - " onEachFeature: geo_json_3fa45e69a7590c080a82d482bb078138_onEachFeature,\n", + " var geo_json_6f59948f50a81aaf649c171aae804855 = L.geoJson(null, {\n", + " onEachFeature: geo_json_6f59948f50a81aaf649c171aae804855_onEachFeature,\n", " \n", - " style: geo_json_3fa45e69a7590c080a82d482bb078138_styler,\n", - " pointToLayer: geo_json_3fa45e69a7590c080a82d482bb078138_pointToLayer,\n", + " style: geo_json_6f59948f50a81aaf649c171aae804855_styler,\n", + " pointToLayer: geo_json_6f59948f50a81aaf649c171aae804855_pointToLayer,\n", + " opacity: 0.5,\n", " });\n", "\n", - " function geo_json_3fa45e69a7590c080a82d482bb078138_add (data) {\n", - " geo_json_3fa45e69a7590c080a82d482bb078138\n", + " function geo_json_6f59948f50a81aaf649c171aae804855_add (data) {\n", + " geo_json_6f59948f50a81aaf649c171aae804855\n", " .addData(data);\n", " }\n", - " geo_json_3fa45e69a7590c080a82d482bb078138_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#3182bd", "edge_ids": "[0, 3, 15, 27]", "n_segments": 8, "stroke_group": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#9ecae1", "edge_ids": "[11, 28, 2, 30]", "n_segments": 17, "stroke_group": 1, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#e6550d", "edge_ids": "[4, 5, 6]", "n_segments": 5, "stroke_group": 2, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fdae6b", "edge_ids": "[26]", "n_segments": 5, "stroke_group": 3, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#31a354", "edge_ids": "[1, 12, 14, 25]", "n_segments": 19, "stroke_group": 4, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#c7e9c0", "edge_ids": "[20]", "n_segments": 3, "stroke_group": 5, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#9e9ac8", "edge_ids": "[16, 17, 29, 18, 23]", "n_segments": 13, "stroke_group": 6, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#dadaeb", "edge_ids": "[7, 8, 21, 9, 24, 22, 13]", "n_segments": 14, "stroke_group": 7, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#969696", "edge_ids": "[19]", "n_segments": 3, "stroke_group": 8, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#d9d9d9", "edge_ids": "[10]", "n_segments": 2, "stroke_group": 9, "stroke_id": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_6f59948f50a81aaf649c171aae804855_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#3182bd", "connectivity": 8, "edge_indeces": "[0, 3, 15, 27]", "nodeID": 0, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#9ecae1", "connectivity": 6, "edge_indeces": "[1, 12, 14, 25]", "nodeID": 1, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#e6550d", "connectivity": 8, "edge_indeces": "[2, 11, 28, 30]", "nodeID": 2, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fdae6b", "connectivity": 7, "edge_indeces": "[4, 5, 6]", "nodeID": 3, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#31a354", "connectivity": 9, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "nodeID": 4, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#c7e9c0", "connectivity": 1, "edge_indeces": "[10]", "nodeID": 5, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#9e9ac8", "connectivity": 7, "edge_indeces": "[16, 17, 18, 23, 29]", "nodeID": 6, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#dadaeb", "connectivity": 1, "edge_indeces": "[19]", "nodeID": 7, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#969696", "connectivity": 2, "edge_indeces": "[20]", "nodeID": 8, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#d9d9d9", "connectivity": 3, "edge_indeces": "[26]", "nodeID": 9, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_3fa45e69a7590c080a82d482bb078138.bindTooltip(\n", + " geo_json_6f59948f50a81aaf649c171aae804855.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", " let handleObject = feature=>typeof(feature)=='object' ? JSON.stringify(feature) : feature;\n", - " let fields = ["stroke_group", "n_segments", "stroke_id", "edge_ids"];\n", - " let aliases = ["stroke_group", "n_segments", "stroke_id", "edge_ids"];\n", + " let fields = ["edge_indeces", "x", "y", "connectivity", "nodeID"];\n", + " let aliases = ["edge_indeces", "x", "y", "connectivity", "nodeID"];\n", " let table = '<table>' +\n", " String(\n", " fields.map(\n", @@ -1369,45 +2313,45 @@ " ,{"className": "foliumtooltip", "sticky": true});\n", " \n", " \n", - " geo_json_3fa45e69a7590c080a82d482bb078138.addTo(map_150925926b6515bf456753c981c35968);\n", + " geo_json_6f59948f50a81aaf649c171aae804855.addTo(map_9b85d4d24a17fd4c7f7140653644c714);\n", " \n", " \n", - " var color_map_889e540fb8a4c317625a9a1be57867b0 = {};\n", + " var color_map_f6983a3cfa0d1cf2bf662c859347b82b = {};\n", "\n", " \n", - " color_map_889e540fb8a4c317625a9a1be57867b0.color = d3.scale.threshold()\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.color = d3.scale.threshold()\n", " .domain([0.0, 0.018036072144288578, 0.036072144288577156, 0.05410821643286573, 0.07214428857715431, 0.09018036072144289, 0.10821643286573146, 0.12625250501002003, 0.14428857715430862, 0.1623246492985972, 0.18036072144288579, 0.19839679358717435, 0.21643286573146292, 0.23446893787575152, 0.25250501002004005, 0.27054108216432865, 0.28857715430861725, 0.3066132264529058, 0.3246492985971944, 0.342685370741483, 0.36072144288577157, 0.3787575150300601, 0.3967935871743487, 0.4148296593186373, 0.43286573146292584, 0.45090180360721444, 0.46893787575150303, 0.48697394789579157, 0.5050100200400801, 0.5230460921843687, 0.5410821643286573, 0.5591182364729459, 0.5771543086172345, 0.5951903807615231, 0.6132264529058116, 0.6312625250501002, 0.6492985971943888, 0.6673346693386774, 0.685370741482966, 0.7034068136272545, 0.7214428857715431, 0.7394789579158316, 0.7575150300601202, 0.7755511022044088, 0.7935871743486974, 0.811623246492986, 0.8296593186372746, 0.8476953907815631, 0.8657314629258517, 0.8837675350701403, 0.9018036072144289, 0.9198396793587175, 0.9378757515030061, 0.9559118236472945, 0.9739478957915831, 0.9919839679358717, 1.0100200400801602, 1.028056112224449, 1.0460921843687374, 1.0641282565130261, 1.0821643286573146, 1.1002004008016033, 1.1182364729458918, 1.1362725450901803, 1.154308617234469, 1.1723446893787575, 1.1903807615230462, 1.2084168336673347, 1.2264529058116231, 1.2444889779559118, 1.2625250501002003, 1.280561122244489, 1.2985971943887775, 1.3166332665330662, 1.3346693386773547, 1.3527054108216432, 1.370741482965932, 1.3887775551102204, 1.406813627254509, 1.4248496993987976, 1.4428857715430863, 1.4609218436873748, 1.4789579158316633, 1.496993987975952, 1.5150300601202404, 1.5330661322645291, 1.5511022044088176, 1.5691382765531061, 1.5871743486973948, 1.6052104208416833, 1.623246492985972, 1.6412825651302605, 1.6593186372745492, 1.6773547094188377, 1.6953907815631262, 1.7134268537074149, 1.7314629258517034, 1.749498997995992, 1.7675350701402806, 1.785571142284569, 1.8036072144288577, 1.8216432865731462, 1.839679358717435, 1.8577154308617234, 1.8757515030060121, 1.8937875751503006, 1.911823647294589, 1.9298597194388778, 1.9478957915831663, 1.965931863727455, 1.9839679358717435, 2.002004008016032, 2.0200400801603204, 2.038076152304609, 2.056112224448898, 2.0741482965931866, 2.092184368737475, 2.1102204408817635, 2.1282565130260522, 2.1462925851703405, 2.164328657314629, 2.182364729458918, 2.2004008016032066, 2.218436873747495, 2.2364729458917836, 2.2545090180360723, 2.2725450901803605, 2.2905811623246493, 2.308617234468938, 2.3266533066132267, 2.344689378757515, 2.3627254509018036, 2.3807615230460923, 2.3987975951903806, 2.4168336673346693, 2.434869739478958, 2.4529058116232463, 2.470941883767535, 2.4889779559118237, 2.5070140280561124, 2.5250501002004007, 2.5430861723446894, 2.561122244488978, 2.5791583166332663, 2.597194388777555, 2.6152304609218437, 2.6332665330661325, 2.6513026052104207, 2.6693386773547094, 2.687374749498998, 2.7054108216432864, 2.723446893787575, 2.741482965931864, 2.7595190380761525, 2.7775551102204408, 2.7955911823647295, 2.813627254509018, 2.8316633266533064, 2.849699398797595, 2.867735470941884, 2.8857715430861726, 2.903807615230461, 2.9218436873747495, 2.9398797595190382, 2.9579158316633265, 2.975951903807615, 2.993987975951904, 3.012024048096192, 3.030060120240481, 3.0480961923847696, 3.0661322645290583, 3.0841683366733466, 3.1022044088176353, 3.120240480961924, 3.1382765531062122, 3.156312625250501, 3.1743486973947896, 3.1923847695390783, 3.2104208416833666, 3.2284569138276553, 3.246492985971944, 3.2645290581162323, 3.282565130260521, 3.3006012024048097, 3.3186372745490984, 3.3366733466933867, 3.3547094188376754, 3.372745490981964, 3.3907815631262523, 3.408817635270541, 3.4268537074148298, 3.444889779559118, 3.4629258517034067, 3.4809619238476954, 3.498997995991984, 3.5170340681362724, 3.535070140280561, 3.55310621242485, 3.571142284569138, 3.5891783567134268, 3.6072144288577155, 3.625250501002004, 3.6432865731462925, 3.661322645290581, 3.67935871743487, 3.697394789579158, 3.715430861723447, 3.7334669338677355, 3.7515030060120242, 3.7695390781563125, 3.787575150300601, 3.80561122244489, 3.823647294589178, 3.841683366733467, 3.8597194388777556, 3.8777555110220443, 3.8957915831663326, 3.9138276553106213, 3.93186372745491, 3.9498997995991982, 3.967935871743487, 3.9859719438877756, 4.004008016032064, 4.022044088176353, 4.040080160320641, 4.05811623246493, 4.076152304609218, 4.094188376753507, 4.112224448897796, 4.130260521042084, 4.148296593186373, 4.166332665330661, 4.18436873747495, 4.202404809619239, 4.220440881763527, 4.238476953907815, 4.2565130260521045, 4.274549098196393, 4.292585170340681, 4.31062124248497, 4.328657314629258, 4.346693386773547, 4.364729458917836, 4.382765531062124, 4.400801603206413, 4.4188376753507015, 4.43687374749499, 4.454909819639279, 4.472945891783567, 4.490981963927855, 4.509018036072145, 4.527054108216433, 4.545090180360721, 4.56312625250501, 4.5811623246492985, 4.599198396793587, 4.617234468937876, 4.635270541082164, 4.653306613226453, 4.671342685370742, 4.68937875751503, 4.707414829659319, 4.725450901803607, 4.7434869739478955, 4.761523046092185, 4.779559118236473, 4.797595190380761, 4.81563126252505, 4.833667334669339, 4.851703406813627, 4.869739478957916, 4.887775551102204, 4.905811623246493, 4.923847695390782, 4.94188376753507, 4.959919839679359, 4.977955911823647, 4.995991983967936, 5.014028056112225, 5.032064128256513, 5.050100200400801, 5.0681362725450905, 5.086172344689379, 5.104208416833667, 5.122244488977956, 5.140280561122244, 5.158316633266533, 5.176352705410822, 5.19438877755511, 5.212424849699399, 5.2304609218436875, 5.248496993987976, 5.266533066132265, 5.284569138276553, 5.302605210420841, 5.320641282565131, 5.338677354709419, 5.356713426853707, 5.374749498997996, 5.3927855711422845, 5.410821643286573, 5.428857715430862, 5.44689378757515, 5.4649298597194385, 5.482965931863728, 5.501002004008016, 5.519038076152305, 5.537074148296593, 5.5551102204408815, 5.573146292585171, 5.591182364729459, 5.609218436873747, 5.627254509018036, 5.645290581162325, 5.663326653306613, 5.681362725450902, 5.69939879759519, 5.717434869739479, 5.735470941883768, 5.753507014028056, 5.771543086172345, 5.789579158316633, 5.807615230460922, 5.825651302605211, 5.843687374749499, 5.861723446893787, 5.8797595190380765, 5.897795591182365, 5.915831663326653, 5.933867735470942, 5.95190380761523, 5.969939879759519, 5.987975951903808, 6.006012024048096, 6.024048096192384, 6.0420841683366735, 6.060120240480962, 6.078156312625251, 6.096192384769539, 6.114228456913827, 6.132264529058117, 6.150300601202405, 6.168336673346693, 6.186372745490982, 6.2044088176352705, 6.222444889779559, 6.240480961923848, 6.258517034068136, 6.2765531062124245, 6.294589178356714, 6.312625250501002, 6.330661322645291, 6.348697394789579, 6.3667334669338675, 6.384769539078157, 6.402805611222445, 6.420841683366733, 6.438877755511022, 6.456913827655311, 6.474949899799599, 6.492985971943888, 6.511022044088176, 6.529058116232465, 6.547094188376754, 6.565130260521042, 6.58316633266533, 6.601202404809619, 6.619238476953908, 6.637274549098197, 6.655310621242485, 6.673346693386773, 6.6913827655310625, 6.709418837675351, 6.727454909819639, 6.745490981963928, 6.763527054108216, 6.781563126252505, 6.799599198396794, 6.817635270541082, 6.83567134268537, 6.8537074148296595, 6.871743486973948, 6.889779559118236, 6.907815631262525, 6.925851703406813, 6.943887775551103, 6.961923847695391, 6.979959919839679, 6.997995991983968, 7.0160320641282565, 7.034068136272545, 7.052104208416834, 7.070140280561122, 7.0881763527054105, 7.1062124248497, 7.124248496993988, 7.142284569138276, 7.160320641282565, 7.1783567134268536, 7.196392785571143, 7.214428857715431, 7.232464929859719, 7.250501002004008, 7.268537074148297, 7.286573146292585, 7.304609218436874, 7.322645290581162, 7.340681362725451, 7.35871743486974, 7.376753507014028, 7.394789579158316, 7.412825651302605, 7.430861723446894, 7.448897795591182, 7.466933867735471, 7.484969939879759, 7.5030060120240485, 7.521042084168337, 7.539078156312625, 7.557114228456914, 7.575150300601202, 7.593186372745491, 7.61122244488978, 7.629258517034068, 7.647294589178356, 7.6653306613226455, 7.683366733466934, 7.701402805611222, 7.719438877755511, 7.7374749498997994, 7.755511022044089, 7.773547094188377, 7.791583166332665, 7.809619238476954, 7.8276553106212425, 7.845691382765531, 7.86372745490982, 7.881763527054108, 7.8997995991983965, 7.917835671342686, 7.935871743486974, 7.953907815631262, 7.971943887775551, 7.98997995991984, 8.008016032064129, 8.026052104208416, 8.044088176352705, 8.062124248496994, 8.080160320641282, 8.098196392785571, 8.11623246492986, 8.134268537074147, 8.152304609218437, 8.170340681362726, 8.188376753507015, 8.206412825651302, 8.224448897795591, 8.24248496993988, 8.260521042084168, 8.278557114228457, 8.296593186372746, 8.314629258517034, 8.332665330661323, 8.350701402805612, 8.3687374749499, 8.386773547094188, 8.404809619238478, 8.422845691382765, 8.440881763527054, 8.458917835671343, 8.47695390781563, 8.49498997995992, 8.513026052104209, 8.531062124248496, 8.549098196392785, 8.567134268537075, 8.585170340681362, 8.603206412825651, 8.62124248496994, 8.639278557114228, 8.657314629258517, 8.675350701402806, 8.693386773547093, 8.711422845691382, 8.729458917835672, 8.74749498997996, 8.765531062124248, 8.783567134268537, 8.801603206412826, 8.819639278557114, 8.837675350701403, 8.855711422845692, 8.87374749498998, 8.891783567134269, 8.909819639278558, 8.927855711422845, 8.945891783567134, 8.963927855711423, 8.98196392785571, 9.0])\n", " .range(['#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff']);\n", " \n", "\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.x = d3.scale.linear()\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.x = d3.scale.linear()\n", " .domain([0.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.legend = L.control({position: 'topright'});\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.legend.addTo(map_150925926b6515bf456753c981c35968);\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.legend = L.control({position: 'topright'});\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.legend.addTo(map_9b85d4d24a17fd4c7f7140653644c714);\n", "\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.xAxis = d3.svg.axis()\n", - " .scale(color_map_889e540fb8a4c317625a9a1be57867b0.x)\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.xAxis = d3.svg.axis()\n", + " .scale(color_map_f6983a3cfa0d1cf2bf662c859347b82b.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', '', 1.35, '', '', 2.7, '', '', 4.05, '', '', 5.4, '', '', 6.75, '', '', 8.1, '', '']);\n", "\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.g = color_map_889e540fb8a4c317625a9a1be57867b0.svg.append("g")\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.g = color_map_f6983a3cfa0d1cf2bf662c859347b82b.svg.append("g")\n", " .attr("class", "key")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.g.selectAll("rect")\n", - " .data(color_map_889e540fb8a4c317625a9a1be57867b0.color.range().map(function(d, i) {\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.g.selectAll("rect")\n", + " .data(color_map_f6983a3cfa0d1cf2bf662c859347b82b.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_889e540fb8a4c317625a9a1be57867b0.x(color_map_889e540fb8a4c317625a9a1be57867b0.color.domain()[i - 1]) : color_map_889e540fb8a4c317625a9a1be57867b0.x.range()[0],\n", - " x1: i < color_map_889e540fb8a4c317625a9a1be57867b0.color.domain().length ? color_map_889e540fb8a4c317625a9a1be57867b0.x(color_map_889e540fb8a4c317625a9a1be57867b0.color.domain()[i]) : color_map_889e540fb8a4c317625a9a1be57867b0.x.range()[1],\n", + " x0: i ? color_map_f6983a3cfa0d1cf2bf662c859347b82b.x(color_map_f6983a3cfa0d1cf2bf662c859347b82b.color.domain()[i - 1]) : color_map_f6983a3cfa0d1cf2bf662c859347b82b.x.range()[0],\n", + " x1: i < color_map_f6983a3cfa0d1cf2bf662c859347b82b.color.domain().length ? color_map_f6983a3cfa0d1cf2bf662c859347b82b.x(color_map_f6983a3cfa0d1cf2bf662c859347b82b.color.domain()[i]) : color_map_f6983a3cfa0d1cf2bf662c859347b82b.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -1417,69 +2361,81 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_889e540fb8a4c317625a9a1be57867b0.g.call(color_map_889e540fb8a4c317625a9a1be57867b0.xAxis).append("text")\n", + " color_map_f6983a3cfa0d1cf2bf662c859347b82b.g.call(color_map_f6983a3cfa0d1cf2bf662c859347b82b.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", - " .text("stroke_id");\n", + " .text("nodeID");\n", " \n", - " function geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_styler(feature) {\n", + " function geo_json_931be271f6d6d54c5558dcdbbeac5feb_styler(feature) {\n", " switch(feature.id) {\n", + " case "0": case "2": \n", + " return {"color": "#08519c", "fillColor": "#08519c", "fillOpacity": 0.5, "weight": 2};\n", + " case "1": \n", + " return {"color": "#4292c6", "fillColor": "#4292c6", "fillOpacity": 0.5, "weight": 2};\n", + " case "3": case "6": \n", + " return {"color": "#2171b5", "fillColor": "#2171b5", "fillOpacity": 0.5, "weight": 2};\n", + " case "4": \n", + " return {"color": "#08306b", "fillColor": "#08306b", "fillOpacity": 0.5, "weight": 2};\n", + " case "5": case "7": \n", + " return {"color": "#f7fbff", "fillColor": "#f7fbff", "fillOpacity": 0.5, "weight": 2};\n", + " case "8": \n", + " return {"color": "#dfebf7", "fillColor": "#dfebf7", "fillOpacity": 0.5, "weight": 2};\n", " default:\n", - " return {"fillOpacity": 0.5, "weight": 8};\n", + " return {"color": "#c7dbef", "fillColor": "#c7dbef", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_highlighter(feature) {\n", + " function geo_json_931be271f6d6d54c5558dcdbbeac5feb_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_pointToLayer(feature, latlng) {\n", - " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", + " function geo_json_931be271f6d6d54c5558dcdbbeac5feb_pointToLayer(feature, latlng) {\n", + " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 10, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_styler(feature)\n", + " let style = geo_json_931be271f6d6d54c5558dcdbbeac5feb_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_onEachFeature(feature, layer) {\n", + " function geo_json_931be271f6d6d54c5558dcdbbeac5feb_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2.resetStyle(e.target);\n", + " geo_json_931be271f6d6d54c5558dcdbbeac5feb.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_931be271f6d6d54c5558dcdbbeac5feb_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2 = L.geoJson(null, {\n", - " onEachFeature: geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_onEachFeature,\n", + " var geo_json_931be271f6d6d54c5558dcdbbeac5feb = L.geoJson(null, {\n", + " onEachFeature: geo_json_931be271f6d6d54c5558dcdbbeac5feb_onEachFeature,\n", " \n", - " style: geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_styler,\n", - " pointToLayer: geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_pointToLayer,\n", + " style: geo_json_931be271f6d6d54c5558dcdbbeac5feb_styler,\n", + " pointToLayer: geo_json_931be271f6d6d54c5558dcdbbeac5feb_pointToLayer,\n", " });\n", "\n", - " function geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_add (data) {\n", - " geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2\n", + " function geo_json_931be271f6d6d54c5558dcdbbeac5feb_add (data) {\n", + " geo_json_931be271f6d6d54c5558dcdbbeac5feb\n", " .addData(data);\n", " }\n", - " geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"continuities": "{0: 3, 1: 3}", "node_end": 1, "node_start": 0, "random_id": 0}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "1", "properties": {"continuities": "{0: 2, 2: 1}", "node_end": 2, "node_start": 0, "random_id": 1}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "2", "properties": {"continuities": "{0: 2, 3: 1}", "node_end": 3, "node_start": 0, "random_id": 2}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"continuities": "{0: 2, 4: 2}", "node_end": 4, "node_start": 0, "random_id": 3}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"continuities": "{0: 2, 7: 2}", "node_end": 7, "node_start": 0, "random_id": 4}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "5", "properties": {"continuities": "{1: 1, 2: 1}", "node_end": 2, "node_start": 1, "random_id": 5}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "6", "properties": {"continuities": "{1: 1, 3: 1}", "node_end": 3, "node_start": 1, "random_id": 6}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"continuities": "{1: 4, 6: 4}", "node_end": 6, "node_start": 1, "random_id": 7}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "8", "properties": {"continuities": "{2: 1, 3: 1}", "node_end": 3, "node_start": 2, "random_id": 8}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "9", "properties": {"continuities": "{2: 2, 4: 2}", "node_end": 4, "node_start": 2, "random_id": 9}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "10", "properties": {"continuities": "{2: 2, 7: 2}", "node_end": 7, "node_start": 2, "random_id": 10}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401858879914098, 50.102192963132694]], "type": "LineString"}, "id": "11", "properties": {"continuities": "{4: 2, 5: 1}", "node_end": 5, "node_start": 4, "random_id": 11}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "12", "properties": {"continuities": "{4: 1, 6: 2}", "node_end": 6, "node_start": 4, "random_id": 12}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "13", "properties": {"continuities": "{5: 1, 7: 2}", "node_end": 7, "node_start": 5, "random_id": 13}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.405314141282124, 50.102934111376484], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "14", "properties": {"continuities": "{6: 2, 7: 2}", "node_end": 7, "node_start": 6, "random_id": 14}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.400252154982407, 50.101662206397165], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "15", "properties": {"continuities": "{8: 1, 7: 2}", "node_end": 8, "node_start": 7, "random_id": 15}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.401228358834482, 50.10108780709868], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"continuities": "{9: 1, 7: 2}", "node_end": 9, "node_start": 7, "random_id": 16}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_931be271f6d6d54c5558dcdbbeac5feb_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "#08519c", "connectivity": 8}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "#4292c6", "connectivity": 6}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "#08519c", "connectivity": 8}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "#2171b5", "connectivity": 7}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "#08306b", "connectivity": 9}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "#f7fbff", "connectivity": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "#2171b5", "connectivity": 7}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "#f7fbff", "connectivity": 1}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "#dfebf7", "connectivity": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "#c7dbef", "connectivity": 3}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2.bindTooltip(\n", + " geo_json_931be271f6d6d54c5558dcdbbeac5feb.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", " let handleObject = feature=>typeof(feature)=='object' ? JSON.stringify(feature) : feature;\n", - " let fields = ["continuities", "node_start", "node_end", "random_id"];\n", - " let aliases = ["continuities", "node_start", "node_end", "random_id"];\n", + " let fields = ["connectivity"];\n", + " let aliases = ["connectivity"];\n", " let table = '<table>' +\n", " String(\n", " fields.map(\n", @@ -1497,68 +2453,117 @@ " ,{"className": "foliumtooltip", "sticky": true});\n", " \n", " \n", - " geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2.addTo(map_150925926b6515bf456753c981c35968);\n", + " geo_json_931be271f6d6d54c5558dcdbbeac5feb.addTo(map_9b85d4d24a17fd4c7f7140653644c714);\n", " \n", " \n", - " function geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_styler(feature) {\n", + " var color_map_0ec71509f6790eee86ba9cafb7a35ecc = {};\n", + "\n", + " \n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.color = d3.scale.threshold()\n", + " .domain([1.0, 1.0160320641282565, 1.032064128256513, 1.0480961923847696, 1.0641282565130261, 1.0801603206412826, 1.0961923847695392, 1.1122244488977957, 1.128256513026052, 1.1442885771543085, 1.160320641282565, 1.1763527054108216, 1.1923847695390781, 1.2084168336673347, 1.2244488977955912, 1.2404809619238477, 1.2565130260521042, 1.2725450901803608, 1.2885771543086173, 1.3046092184368738, 1.3206412825651301, 1.3366733466933867, 1.3527054108216432, 1.3687374749498997, 1.3847695390781563, 1.4008016032064128, 1.4168336673346693, 1.4328657314629258, 1.4488977955911824, 1.464929859719439, 1.4809619238476954, 1.496993987975952, 1.5130260521042085, 1.529058116232465, 1.5450901803607215, 1.561122244488978, 1.5771543086172346, 1.5931863727454911, 1.6092184368737477, 1.625250501002004, 1.6412825651302605, 1.657314629258517, 1.6733466933867736, 1.68937875751503, 1.7054108216432866, 1.7214428857715431, 1.7374749498997994, 1.753507014028056, 1.7695390781563125, 1.785571142284569, 1.8016032064128256, 1.817635270541082, 1.8336673346693386, 1.8496993987975952, 1.8657314629258517, 1.8817635270541082, 1.8977955911823647, 1.9138276553106213, 1.9298597194388778, 1.9458917835671343, 1.9619238476953909, 1.9779559118236474, 1.993987975951904, 2.0100200400801604, 2.026052104208417, 2.0420841683366735, 2.05811623246493, 2.0741482965931866, 2.090180360721443, 2.1062124248496996, 2.122244488977956, 2.1382765531062127, 2.154308617234469, 2.1703406813627257, 2.1863727454909823, 2.202404809619239, 2.2184368737474953, 2.2344689378757514, 2.250501002004008, 2.2665330661322645, 2.282565130260521, 2.2985971943887775, 2.314629258517034, 2.3306613226452906, 2.346693386773547, 2.3627254509018036, 2.37875751503006, 2.3947895791583167, 2.4108216432865732, 2.4268537074148298, 2.4428857715430863, 2.4589178356713424, 2.474949899799599, 2.4909819639278554, 2.507014028056112, 2.5230460921843685, 2.539078156312625, 2.5551102204408815, 2.571142284569138, 2.5871743486973946, 2.603206412825651, 2.6192384769539077, 2.635270541082164, 2.6513026052104207, 2.6673346693386772, 2.6833667334669338, 2.6993987975951903, 2.715430861723447, 2.7314629258517034, 2.74749498997996, 2.7635270541082164, 2.779559118236473, 2.7955911823647295, 2.811623246492986, 2.8276553106212425, 2.843687374749499, 2.8597194388777556, 2.875751503006012, 2.8917835671342687, 2.907815631262525, 2.9238476953907817, 2.9398797595190382, 2.9559118236472948, 2.9719438877755513, 2.987975951903808, 3.004008016032064, 3.0200400801603204, 3.036072144288577, 3.0521042084168335, 3.06813627254509, 3.0841683366733466, 3.100200400801603, 3.1162324649298596, 3.132264529058116, 3.1482965931863727, 3.164328657314629, 3.1803607214428857, 3.1963927855711423, 3.212424849699399, 3.2284569138276553, 3.244488977955912, 3.2605210420841684, 3.276553106212425, 3.2925851703406814, 3.308617234468938, 3.3246492985971945, 3.340681362725451, 3.3567134268537075, 3.372745490981964, 3.3887775551102206, 3.404809619238477, 3.4208416833667337, 3.43687374749499, 3.4529058116232463, 3.468937875751503, 3.4849699398797593, 3.501002004008016, 3.5170340681362724, 3.533066132264529, 3.5490981963927855, 3.565130260521042, 3.5811623246492985, 3.597194388777555, 3.6132264529058116, 3.629258517034068, 3.6452905811623246, 3.661322645290581, 3.6773547094188377, 3.693386773547094, 3.7094188376753507, 3.7254509018036073, 3.741482965931864, 3.7575150300601203, 3.773547094188377, 3.7895791583166334, 3.80561122244489, 3.8216432865731464, 3.837675350701403, 3.8537074148296595, 3.869739478957916, 3.8857715430861726, 3.9018036072144286, 3.917835671342685, 3.9338677354709417, 3.9498997995991982, 3.9659318637274548, 3.9819639278557113, 3.997995991983968, 4.014028056112224, 4.030060120240481, 4.046092184368737, 4.062124248496994, 4.07815631262525, 4.094188376753507, 4.110220440881763, 4.1262525050100205, 4.142284569138276, 4.158316633266534, 4.174348697394789, 4.190380761523047, 4.206412825651302, 4.22244488977956, 4.238476953907815, 4.254509018036073, 4.270541082164328, 4.286573146292586, 4.302605210420841, 4.318637274549099, 4.3346693386773545, 4.350701402805611, 4.3667334669338675, 4.382765531062124, 4.398797595190381, 4.414829659318637, 4.430861723446894, 4.44689378757515, 4.462925851703407, 4.478957915831663, 4.49498997995992, 4.511022044088176, 4.527054108216433, 4.543086172344689, 4.559118236472946, 4.575150300601202, 4.591182364729459, 4.6072144288577155, 4.623246492985972, 4.6392785571142285, 4.655310621242485, 4.671342685370742, 4.687374749498998, 4.703406813627255, 4.719438877755511, 4.735470941883768, 4.751503006012024, 4.767535070140281, 4.783567134268537, 4.799599198396793, 4.81563126252505, 4.831663326653306, 4.847695390781563, 4.863727454909819, 4.8797595190380765, 4.895791583166332, 4.9118236472945895, 4.927855711422845, 4.943887775551103, 4.959919839679358, 4.975951903807616, 4.991983967935871, 5.008016032064128, 5.024048096192384, 5.040080160320641, 5.056112224448897, 5.072144288577154, 5.0881763527054105, 5.104208416833667, 5.1202404809619235, 5.13627254509018, 5.152304609218437, 5.168336673346693, 5.18436873747495, 5.200400801603206, 5.216432865731463, 5.232464929859719, 5.248496993987976, 5.264529058116232, 5.280561122244489, 5.296593186372745, 5.312625250501002, 5.328657314629258, 5.344689378757515, 5.3607214428857715, 5.376753507014028, 5.3927855711422845, 5.408817635270541, 5.424849699398798, 5.440881763527054, 5.456913827655311, 5.472945891783567, 5.488977955911824, 5.50501002004008, 5.521042084168337, 5.537074148296593, 5.55310621242485, 5.569138276553106, 5.585170340681363, 5.601202404809619, 5.617234468937876, 5.6332665330661325, 5.649298597194389, 5.6653306613226455, 5.681362725450902, 5.697394789579159, 5.713426853707415, 5.729458917835672, 5.745490981963928, 5.761523046092185, 5.777555110220441, 5.793587174348698, 5.809619238476954, 5.825651302605211, 5.841683366733467, 5.857715430861724, 5.87374749498998, 5.889779559118236, 5.905811623246493, 5.921843687374749, 5.937875751503006, 5.953907815631262, 5.969939879759519, 5.985971943887775, 6.002004008016032, 6.018036072144288, 6.034068136272545, 6.050100200400801, 6.066132264529058, 6.082164328657314, 6.098196392785571, 6.114228456913827, 6.130260521042084, 6.1462925851703405, 6.162324649298597, 6.1783567134268536, 6.19438877755511, 6.210420841683367, 6.226452905811623, 6.24248496993988, 6.258517034068136, 6.274549098196393, 6.290581162324649, 6.306613226452906, 6.322645290581162, 6.338677354709419, 6.354709418837675, 6.370741482965932, 6.386773547094188, 6.402805611222445, 6.4188376753507015, 6.434869739478958, 6.4509018036072145, 6.466933867735471, 6.482965931863728, 6.498997995991984, 6.515030060120241, 6.531062124248497, 6.547094188376754, 6.56312625250501, 6.579158316633267, 6.595190380761523, 6.61122244488978, 6.627254509018036, 6.643286573146293, 6.659318637274549, 6.675350701402806, 6.6913827655310625, 6.707414829659319, 6.7234468937875755, 6.739478957915832, 6.755511022044089, 6.771543086172345, 6.787575150300601, 6.803607214428857, 6.819639278557114, 6.83567134268537, 6.851703406813627, 6.867735470941883, 6.88376753507014, 6.8997995991983965, 6.915831663326653, 6.9318637274549095, 6.947895791583166, 6.963927855711423, 6.979959919839679, 6.995991983967936, 7.012024048096192, 7.028056112224449, 7.044088176352705, 7.060120240480962, 7.076152304609218, 7.092184368737475, 7.108216432865731, 7.124248496993988, 7.140280561122244, 7.156312625250501, 7.1723446893787575, 7.188376753507014, 7.2044088176352705, 7.220440881763527, 7.236472945891784, 7.25250501002004, 7.268537074148297, 7.284569138276553, 7.30060120240481, 7.316633266533066, 7.332665330661323, 7.348697394789579, 7.364729458917836, 7.380761523046092, 7.396793587174349, 7.412825651302605, 7.428857715430862, 7.4448897795591185, 7.460921843687375, 7.4769539078156315, 7.492985971943888, 7.509018036072145, 7.525050100200401, 7.541082164328658, 7.557114228456914, 7.573146292585171, 7.589178356713427, 7.605210420841684, 7.62124248496994, 7.637274549098197, 7.653306613226453, 7.669338677354709, 7.6853707414829655, 7.701402805611222, 7.717434869739479, 7.733466933867735, 7.749498997995992, 7.765531062124248, 7.781563126252505, 7.797595190380761, 7.813627254509018, 7.829659318637274, 7.845691382765531, 7.861723446893787, 7.877755511022044, 7.8937875751503, 7.909819639278557, 7.925851703406813, 7.94188376753507, 7.9579158316633265, 7.973947895791583, 7.98997995991984, 8.006012024048097, 8.022044088176353, 8.038076152304608, 8.054108216432866, 8.070140280561123, 8.086172344689379, 8.102204408817634, 8.118236472945892, 8.13426853707415, 8.150300601202405, 8.16633266533066, 8.182364729458918, 8.198396793587175, 8.214428857715431, 8.230460921843687, 8.246492985971944, 8.262525050100201, 8.278557114228457, 8.294589178356713, 8.31062124248497, 8.326653306613228, 8.342685370741483, 8.358717434869739, 8.374749498997996, 8.390781563126254, 8.40681362725451, 8.422845691382765, 8.438877755511022, 8.45490981963928, 8.470941883767535, 8.486973947895791, 8.503006012024048, 8.519038076152306, 8.535070140280562, 8.551102204408817, 8.567134268537075, 8.58316633266533, 8.599198396793586, 8.615230460921843, 8.6312625250501, 8.647294589178356, 8.663326653306612, 8.67935871743487, 8.695390781563127, 8.711422845691382, 8.727454909819638, 8.743486973947896, 8.759519038076153, 8.775551102204409, 8.791583166332664, 8.807615230460922, 8.823647294589179, 8.839679358717435, 8.85571142284569, 8.871743486973948, 8.887775551102205, 8.90380761523046, 8.919839679358716, 8.935871743486974, 8.951903807615231, 8.967935871743487, 8.983967935871743, 9.0])\n", + " .range(['#f7fbffff', '#f7fbffff', '#f6faffff', '#f6faffff', '#f5fafeff', '#f5fafeff', '#f5f9feff', '#f5f9feff', '#f4f9feff', '#f4f9feff', '#f3f8feff', '#f3f8feff', '#f2f8fdff', '#f2f8fdff', '#f2f7fdff', '#f2f7fdff', '#f1f7fdff', '#f1f7fdff', '#f0f6fdff', '#f0f6fdff', '#eff6fcff', '#eff6fcff', '#eef5fcff', '#eef5fcff', '#eef5fcff', '#eef5fcff', '#edf4fcff', '#edf4fcff', '#ecf4fbff', '#ecf4fbff', '#ebf3fbff', '#ebf3fbff', '#eaf3fbff', '#eaf3fbff', '#eaf2fbff', '#eaf2fbff', '#e9f2faff', '#e9f2faff', '#e8f1faff', '#e7f1faff', '#e7f1faff', '#e7f0faff', '#e7f0faff', '#e6f0faff', '#e6f0f9ff', '#e5eff9ff', '#e5eff9ff', '#e4eff9ff', '#e4eff9ff', '#e3eef9ff', '#e3eef9ff', '#e3eef8ff', '#e3eef8ff', '#e2edf8ff', '#e2edf8ff', '#e1edf8ff', '#e1edf8ff', '#e0ecf8ff', '#e0ecf8ff', '#dfecf7ff', '#dfecf7ff', '#dfebf7ff', '#dfebf7ff', '#deebf7ff', '#deebf7ff', '#ddeaf7ff', '#ddeaf7ff', '#dceaf6ff', '#dceaf6ff', '#dce9f6ff', '#dce9f6ff', '#dbe9f6ff', '#dbe9f6ff', '#dae8f6ff', '#dae8f6ff', '#d9e8f5ff', '#d9e8f5ff', '#d9e7f5ff', '#d8e7f5ff', '#d8e7f5ff', '#d7e7f5ff', '#d7e6f5ff', '#d6e6f5ff', '#d6e6f4ff', '#d6e5f4ff', '#d6e5f4ff', '#d5e5f4ff', '#d5e5f4ff', '#d4e4f4ff', '#d4e4f4ff', '#d3e4f3ff', '#d3e4f3ff', '#d3e3f3ff', '#d3e3f3ff', '#d2e3f3ff', '#d2e3f3ff', '#d1e2f3ff', '#d1e2f3ff', '#d0e2f2ff', '#d0e2f2ff', '#d0e1f2ff', '#d0e1f2ff', '#cfe1f2ff', '#cfe1f2ff', '#cee0f2ff', '#cee0f2ff', '#cde0f1ff', '#cde0f1ff', '#cddff1ff', '#cddff1ff', '#ccdff1ff', '#ccdff1ff', '#cbdef1ff', '#cbdef1ff', '#cadef0ff', '#cadef0ff', '#caddf0ff', '#c9ddf0ff', '#c9ddf0ff', '#c8ddf0ff', '#c8dcf0ff', '#c7dcf0ff', '#c7dcefff', '#c7dcefff', '#c7dbefff', '#c6dbefff', '#c5dbefff', '#c4daefff', '#c4daeeff', '#c3daeeff', '#c3daeeff', '#c2d9eeff', '#c2d9eeff', '#c1d9edff', '#c0d9edff', '#bfd8edff', '#bfd8edff', '#bed8ecff', '#bed8ecff', '#bdd7ecff', '#bdd7ecff', '#bcd7ebff', '#bbd7ebff', '#bad6ebff', '#bad6ebff', '#b9d6eaff', '#b9d6eaff', '#b8d5eaff', '#b8d5eaff', '#b7d4eaff', '#b6d4eaff', '#b5d4e9ff', '#b5d4e9ff', '#b4d3e9ff', '#b4d3e9ff', '#b3d3e8ff', '#b2d3e8ff', '#b2d2e8ff', '#b1d2e8ff', '#b0d2e7ff', '#afd2e7ff', '#afd1e7ff', '#aed1e7ff', '#aed1e7ff', '#add1e7ff', '#add0e6ff', '#acd0e6ff', '#abd0e6ff', '#aacfe6ff', '#aacfe5ff', '#a9cfe5ff', '#a9cfe5ff', '#a8cee4ff', '#a7cee4ff', '#a6cee4ff', '#a6cee4ff', '#a5cde3ff', '#a5cde3ff', '#a4cce3ff', '#a4cce3ff', '#a3cce3ff', '#a2cce3ff', '#a1cbe2ff', '#a1cbe2ff', '#a0cbe2ff', '#a0cbe2ff', '#9fcae1ff', '#9ecae1ff', '#9dcae1ff', '#9dcae1ff', '#9cc9e1ff', '#9bc9e1ff', '#9ac8e0ff', '#99c8e0ff', '#99c7e0ff', '#98c7e0ff', '#97c6dfff', '#96c6dfff', '#95c5dfff', '#94c5dfff', '#94c4dfff', '#93c4dfff', '#92c4deff', '#91c4deff', '#91c3deff', '#90c3deff', '#8fc2deff', '#8dc1deff', '#8dc1ddff', '#8cc0ddff', '#8bc0ddff', '#8abfddff', '#8abfddff', '#89beddff', '#88bedcff', '#87bddcff', '#86bddcff', '#85bcdcff', '#85bcdcff', '#84bcdbff', '#83bcdbff', '#82bbdbff', '#82bbdbff', '#81badbff', '#80badbff', '#7fb9daff', '#7eb9daff', '#7db8daff', '#7cb8daff', '#7cb7daff', '#7bb7daff', '#7ab6d9ff', '#79b6d9ff', '#79b5d9ff', '#78b5d9ff', '#77b5d9ff', '#76b5d9ff', '#75b4d8ff', '#74b4d8ff', '#74b3d8ff', '#73b3d8ff', '#72b2d8ff', '#71b2d8ff', '#71b1d7ff', '#70b1d7ff', '#6fb0d7ff', '#6eafd7ff', '#6dafd7ff', '#6caed7ff', '#6baed6ff', '#6aaed6ff', '#6aaed6ff', '#69add6ff', '#69add5ff', '#68acd5ff', '#67acd5ff', '#66abd5ff', '#66abd4ff', '#65aad4ff', '#65aad4ff', '#64a9d3ff', '#64a9d3ff', '#63a8d3ff', '#62a8d3ff', '#61a7d2ff', '#60a7d2ff', '#60a7d2ff', '#5fa7d2ff', '#5fa6d1ff', '#5ea6d1ff', '#5da5d1ff', '#5ca5d1ff', '#5ca4d0ff', '#5ba4d0ff', '#5ba3d0ff', '#5aa3d0ff', '#5aa2cfff', '#59a2cfff', '#58a1cfff', '#57a1cfff', '#57a0ceff', '#56a0ceff', '#56a0ceff', '#55a0ceff', '#549fcdff', '#539ecdff', '#539ecdff', '#529dcdff', '#529dccff', '#519cccff', '#509cccff', '#4f9bccff', '#4f9bcbff', '#4e9acbff', '#4e9acbff', '#4d99cbff', '#4c99caff', '#4b98caff', '#4b98caff', '#4a98c9ff', '#4998c9ff', '#4997c9ff', '#4897c9ff', '#4896c8ff', '#4796c8ff', '#4695c8ff', '#4595c8ff', '#4594c7ff', '#4494c7ff', '#4493c7ff', '#4393c7ff', '#4292c6ff', '#4192c6ff', '#4191c6ff', '#4091c6ff', '#4090c5ff', '#3f90c5ff', '#3f8fc5ff', '#3e8fc5ff', '#3e8ec4ff', '#3d8ec4ff', '#3d8dc4ff', '#3c8dc4ff', '#3c8cc3ff', '#3b8bc3ff', '#3b8bc2ff', '#3a8ac2ff', '#3a8ac2ff', '#3989c2ff', '#3989c1ff', '#3888c1ff', '#3888c1ff', '#3787c1ff', '#3787c0ff', '#3686c0ff', '#3686c0ff', '#3585c0ff', '#3485bfff', '#3484bfff', '#3384bfff', '#3383beff', '#3283beff', '#3282beff', '#3182beff', '#3181bdff', '#3081bdff', '#3080bdff', '#2f80bdff', '#2f7fbcff', '#2e7fbcff', '#2e7ebcff', '#2d7ebcff', '#2d7dbbff', '#2c7dbbff', '#2c7cbaff', '#2b7cbaff', '#2b7bbaff', '#2a7bbaff', '#2a7ab9ff', '#297ab9ff', '#2979b9ff', '#2878b9ff', '#2777b8ff', '#2676b8ff', '#2676b8ff', '#2575b8ff', '#2575b7ff', '#2474b7ff', '#2474b7ff', '#2373b7ff', '#2373b6ff', '#2272b6ff', '#2272b6ff', '#2171b6ff', '#2171b5ff', '#2070b5ff', '#2070b4ff', '#206fb4ff', '#1f6fb4ff', '#1f6eb4ff', '#1e6eb3ff', '#1e6db2ff', '#1d6db2ff', '#1d6cb1ff', '#1c6cb1ff', '#1c6bb0ff', '#1c6bb0ff', '#1c6ab0ff', '#1b6ab0ff', '#1b69afff', '#1a69afff', '#1a68aeff', '#1968aeff', '#1967adff', '#1967adff', '#1966adff', '#1866adff', '#1865acff', '#1765acff', '#1764abff', '#1663abff', '#1663aaff', '#1562aaff', '#1562a9ff', '#1561a9ff', '#1561a9ff', '#1460a9ff', '#1460a8ff', '#135fa8ff', '#135fa7ff', '#125ea7ff', '#125ea6ff', '#125da6ff', '#125da6ff', '#115ca6ff', '#105ca5ff', '#105ba5ff', '#0f5ba4ff', '#0f5aa4ff', '#0e5aa3ff', '#0e59a3ff', '#0e59a2ff', '#0e58a2ff', '#0d58a2ff', '#0d57a1ff', '#0c57a1ff', '#0c56a0ff', '#0b56a0ff', '#0b559fff', '#0a559fff', '#0a549eff', '#0a549eff', '#0a539eff', '#09539eff', '#09529dff', '#08529dff', '#08519cff', '#08509cff', '#08509bff', '#084f9aff', '#084f99ff', '#084e99ff', '#084e98ff', '#084d97ff', '#084d96ff', '#084c96ff', '#084c95ff', '#084b94ff', '#084b93ff', '#084a92ff', '#084a91ff', '#084991ff', '#084990ff', '#08488fff', '#08488eff', '#08478eff', '#08478dff', '#08468cff', '#08468bff', '#08458aff', '#08458aff', '#084489ff', '#084488ff', '#084387ff', '#084387ff', '#084286ff', '#084285ff', '#084184ff', '#084184ff', '#084083ff', '#083f82ff', '#083e81ff', '#083e81ff', '#083d80ff', '#083d7fff', '#083c7eff', '#083b7dff', '#083b7cff', '#083a7bff', '#083a7aff', '#08397aff', '#083979ff', '#083878ff', '#083877ff', '#083777ff', '#083776ff', '#083675ff', '#083674ff', '#083574ff', '#083573ff', '#083472ff', '#083471ff', '#083371ff', '#083370ff', '#08326fff', '#08326eff', '#08316dff', '#08316dff', '#08306cff', '#08306bff']);\n", + " \n", + "\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.x = d3.scale.linear()\n", + " .domain([1.0, 9.0])\n", + " .range([0, 450 - 50]);\n", + "\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.legend = L.control({position: 'topright'});\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.legend.addTo(map_9b85d4d24a17fd4c7f7140653644c714);\n", + "\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.xAxis = d3.svg.axis()\n", + " .scale(color_map_0ec71509f6790eee86ba9cafb7a35ecc.x)\n", + " .orient("top")\n", + " .tickSize(1)\n", + " .tickValues([1.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1.815686274509804, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.631372549019608, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.447058823529412, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 4.262745098039216, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.078431372549019, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.894117647058824, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 6.709803921568628, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 7.525490196078431, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 8.341176470588234, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", + "\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " .attr("id", 'legend')\n", + " .attr("width", 450)\n", + " .attr("height", 40);\n", + "\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.g = color_map_0ec71509f6790eee86ba9cafb7a35ecc.svg.append("g")\n", + " .attr("class", "key")\n", + " .attr("transform", "translate(25,16)");\n", + "\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.g.selectAll("rect")\n", + " .data(color_map_0ec71509f6790eee86ba9cafb7a35ecc.color.range().map(function(d, i) {\n", + " return {\n", + " x0: i ? color_map_0ec71509f6790eee86ba9cafb7a35ecc.x(color_map_0ec71509f6790eee86ba9cafb7a35ecc.color.domain()[i - 1]) : color_map_0ec71509f6790eee86ba9cafb7a35ecc.x.range()[0],\n", + " x1: i < color_map_0ec71509f6790eee86ba9cafb7a35ecc.color.domain().length ? color_map_0ec71509f6790eee86ba9cafb7a35ecc.x(color_map_0ec71509f6790eee86ba9cafb7a35ecc.color.domain()[i]) : color_map_0ec71509f6790eee86ba9cafb7a35ecc.x.range()[1],\n", + " z: d\n", + " };\n", + " }))\n", + " .enter().append("rect")\n", + " .attr("height", 40 - 30)\n", + " .attr("x", function(d) { return d.x0; })\n", + " .attr("width", function(d) { return d.x1 - d.x0; })\n", + " .style("fill", function(d) { return d.z; });\n", + "\n", + " color_map_0ec71509f6790eee86ba9cafb7a35ecc.g.call(color_map_0ec71509f6790eee86ba9cafb7a35ecc.xAxis).append("text")\n", + " .attr("class", "caption")\n", + " .attr("y", 21)\n", + " .text("connectivity");\n", + " \n", + " function geo_json_e3671f10a0e0f04262b2243c63eb123f_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", - " return {"color": "orange", "fillColor": "orange", "fillOpacity": 0.5, "weight": 2};\n", + " return {"color": "black", "fillColor": "black", "fillOpacity": 0.5, "weight": 4};\n", " }\n", " }\n", - " function geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_highlighter(feature) {\n", + " function geo_json_e3671f10a0e0f04262b2243c63eb123f_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_pointToLayer(feature, latlng) {\n", - " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 20, "stroke": true, "weight": 3};\n", + " function geo_json_e3671f10a0e0f04262b2243c63eb123f_pointToLayer(feature, latlng) {\n", + " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_styler(feature)\n", + " let style = geo_json_e3671f10a0e0f04262b2243c63eb123f_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_onEachFeature(feature, layer) {\n", + " function geo_json_e3671f10a0e0f04262b2243c63eb123f_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_df2cdbed92b203a5ca76bb9cea8f88e0.resetStyle(e.target);\n", + " geo_json_e3671f10a0e0f04262b2243c63eb123f.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_e3671f10a0e0f04262b2243c63eb123f_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_df2cdbed92b203a5ca76bb9cea8f88e0 = L.geoJson(null, {\n", - " onEachFeature: geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_onEachFeature,\n", + " var geo_json_e3671f10a0e0f04262b2243c63eb123f = L.geoJson(null, {\n", + " onEachFeature: geo_json_e3671f10a0e0f04262b2243c63eb123f_onEachFeature,\n", " \n", - " style: geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_styler,\n", - " pointToLayer: geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_pointToLayer,\n", - " opacity: 0.2,\n", + " style: geo_json_e3671f10a0e0f04262b2243c63eb123f_styler,\n", + " pointToLayer: geo_json_e3671f10a0e0f04262b2243c63eb123f_pointToLayer,\n", " });\n", "\n", - " function geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_add (data) {\n", - " geo_json_df2cdbed92b203a5ca76bb9cea8f88e0\n", + " function geo_json_e3671f10a0e0f04262b2243c63eb123f_add (data) {\n", + " geo_json_e3671f10a0e0f04262b2243c63eb123f\n", " .addData(data);\n", " }\n", - " geo_json_df2cdbed92b203a5ca76bb9cea8f88e0_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "orange", "edge_ids": "[0, 3, 15, 27]", "nodeID": 0, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "1", "properties": {"__folium_color": "orange", "edge_ids": "[11, 28, 2, 30]", "nodeID": 1, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "2", "properties": {"__folium_color": "orange", "edge_ids": "[4, 5, 6]", "nodeID": 2, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "3", "properties": {"__folium_color": "orange", "edge_ids": "[26]", "nodeID": 3, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "4", "properties": {"__folium_color": "orange", "edge_ids": "[1, 12, 14, 25]", "nodeID": 4, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "5", "properties": {"__folium_color": "orange", "edge_ids": "[20]", "nodeID": 5, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "orange", "edge_ids": "[16, 17, 29, 18, 23]", "nodeID": 6, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "7", "properties": {"__folium_color": "orange", "edge_ids": "[7, 8, 21, 9, 24, 22, 13]", "nodeID": 7, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "8", "properties": {"__folium_color": "orange", "edge_ids": "[19]", "nodeID": 8, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "9", "properties": {"__folium_color": "orange", "edge_ids": "[10]", "nodeID": 9, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_e3671f10a0e0f04262b2243c63eb123f_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "black", "angles": "[88.68317271320804, 63.647466378271766]"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "black", "angles": "[62.52031121665544]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "black", "angles": "[55.78135886136459]"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "black", "angles": "[[90.12528714780073, 89.74560192447649], [90.24732195021957, 89.88178897750322]]"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "black", "angles": "[[90.29328808503493, 90.43376966492825], [89.84379058832397, 89.42915166171285]]"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "black", "angles": "[107.29030340175414]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "black", "angles": "[[90.46915502723192, 89.57504791798526], [89.58581817377714, 90.36997888100568]]"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "black", "angles": "[90.39785291117907]"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "black", "angles": "[126.1677775949272]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "black", "angles": "[145.74856198511836]"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "black", "angles": "[[94.78903631548253, 84.23886881283048], [81.14186114900058, 99.83023372268642], [132.83556629096833, 48.92275878691167], [59.79419820769666, 118.44747671442332]]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "black", "angles": "[88.08366041995446]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "black", "angles": "[[89.83847705650136, 91.21166198882482], [89.75197989966416, 89.19788105500966]]"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "black", "angles": "[91.62276842306488]"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "black", "angles": "[91.18142429639235]"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "black", "angles": "[[87.26341801197296, 93.7165388156464], [90.3973936094473, 88.62264956293333]]"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "black", "angles": "[90.34989164828197]"}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_df2cdbed92b203a5ca76bb9cea8f88e0.bindTooltip(\n", + " geo_json_e3671f10a0e0f04262b2243c63eb123f.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", " let handleObject = feature=>typeof(feature)=='object' ? JSON.stringify(feature) : feature;\n", - " let fields = ["edge_ids", "x", "y", "nodeID"];\n", - " let aliases = ["edge_ids", "x", "y", "nodeID"];\n", + " let fields = ["angles"];\n", + " let aliases = ["angles"];\n", " let table = '<table>' +\n", " String(\n", " fields.map(\n", @@ -1576,47 +2581,62 @@ " ,{"className": "foliumtooltip", "sticky": true});\n", " \n", " \n", - " geo_json_df2cdbed92b203a5ca76bb9cea8f88e0.addTo(map_150925926b6515bf456753c981c35968);\n", + " geo_json_e3671f10a0e0f04262b2243c63eb123f.addTo(map_9b85d4d24a17fd4c7f7140653644c714);\n", " \n", " \n", - " var layer_control_13bf76aaec6fe218f2511f593064bbfb_layers = {\n", + " var layer_control_0db9e3a06a8c01283c36b18b5d244d29_layers = {\n", " base_layers : {\n", - " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_5c406c4d0fba1ff0c6b00cc2a258846f,\n", + " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_670fbb082a54e988eff33fb7763336e0,\n", " },\n", " overlays : {\n", - " "strokes" : geo_json_3fa45e69a7590c080a82d482bb078138,\n", - " "stroke_lines" : geo_json_fbd9cdc8e6a91159c82e1eb12058c3b2,\n", - " "stroke nodes" : geo_json_df2cdbed92b203a5ca76bb9cea8f88e0,\n", + " "strokes (original geoms)" : geo_json_6f59948f50a81aaf649c171aae804855,\n", + " "stroke nodes" : geo_json_931be271f6d6d54c5558dcdbbeac5feb,\n", + " "Stroke graph edges" : geo_json_e3671f10a0e0f04262b2243c63eb123f,\n", " },\n", " };\n", - " let layer_control_13bf76aaec6fe218f2511f593064bbfb = L.control.layers(\n", - " layer_control_13bf76aaec6fe218f2511f593064bbfb_layers.base_layers,\n", - " layer_control_13bf76aaec6fe218f2511f593064bbfb_layers.overlays,\n", + " let layer_control_0db9e3a06a8c01283c36b18b5d244d29 = L.control.layers(\n", + " layer_control_0db9e3a06a8c01283c36b18b5d244d29_layers.base_layers,\n", + " layer_control_0db9e3a06a8c01283c36b18b5d244d29_layers.overlays,\n", " {"autoZIndex": true, "collapsed": true, "position": "topright"}\n", - " ).addTo(map_150925926b6515bf456753c981c35968);\n", + " ).addTo(map_9b85d4d24a17fd4c7f7140653644c714);\n", "\n", " \n", "</script>\n", "</html>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen>" ], "text/plain": [ - "" + "" ] }, - "execution_count": 33, + "execution_count": 102, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "print(stroke_graph.edges(data=True))\n", - "m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"tab20c\", style_kwds={\"weight\":8})\n", - "lines_strokes.explore(m=m, \n", - " #column = \"random_id\", \n", - " name = \"stroke_lines\", \n", - " #cmap = \"Blues\", \n", - " style_kwds={\"weight\":8})\n", - "points_strokes.explore(m=m, marker_kwds={\"radius\":20}, name =\"stroke nodes\", color = \"orange\", opacity=0.2)\n", + "m = points_strokes_primal.explore(\n", + " tiles=\"cartodb.positron\",\n", + " column = \"nodeID\",\n", + " name = \"strokes (original geoms)\",\n", + " cmap = \"tab20c\", \n", + " style_kwds={\"weight\":8},\n", + " opacity=0.5\n", + ")\n", + "points_strokes[[\"geometry\", \"connectivity\"]].explore(\n", + " m=m,\n", + " marker_kwds={\"radius\":10}, \n", + " name =\"stroke nodes\",\n", + " column = \"connectivity\", \n", + " cmap = \"Blues\"\n", + " #opacity=0.2\n", + " )\n", + "\n", + "lines_strokes[[\"geometry\", \"angles\"]].explore(m=m, \n", + " name = \"Stroke graph edges\",\n", + " color = \"black\",\n", + " style_kwds={\"weight\":4},\n", + "\n", + ")\n", "folium.LayerControl().add_to(m)\n", "m" ] @@ -1628,6 +2648,35 @@ "outputs": [], "source": [] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**We want as final output:**\n", + "\n", + "A networkx `Graph()` object (undirected, simple)\n", + "\n", + "* nodes represent strokes,\n", + "* edges represent stroke connections (intersecting, ie crossing or touching)\n", + "\n", + "* edges: attributes: \n", + " * angles \n", + " * number of connections\n", + "* nodes: attributes:\n", + " *should be inheriting from all primal edge attrs, at least:*\n", + " * geometry\n", + " * length\n", + "\n", + "***\n", + "\n", + "next step: functions to add attrs on the nodes (strokes):\n", + "* degree, closeness, betweenness (by def nx) \n", + "* connectivity == number of angles (total nr of connections, min=degree)\n", + "* access (abs diff connectivity-degree)\n", + "* spacing = length / connectivity\n", + "* orthogonality = average angle (sum of angles / connectivity)" + ] + }, { "cell_type": "code", "execution_count": null, From 80e17543e89f723755a80864fcdc86df1ad4467d Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Wed, 14 May 2025 11:22:03 +0200 Subject: [PATCH 08/27] updated angle function --- momepy/strokegraph_clse.ipynb | 293 ++++++++++++++++++---------------- 1 file changed, 151 insertions(+), 142 deletions(-) diff --git a/momepy/strokegraph_clse.ipynb b/momepy/strokegraph_clse.ipynb index a9194610..7c16aa8f 100644 --- a/momepy/strokegraph_clse.ipynb +++ b/momepy/strokegraph_clse.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 165, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -19,14 +19,13 @@ "import networkx as nx\n", "import folium\n", "from itertools import combinations, product\n", - "from collections import Counter\n", "import shapely\n", - "from momepy.utils import _angle" + "import numpy as np" ] }, { "cell_type": "code", - "execution_count": 166, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -35,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 167, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -58,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": 168, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -74,7 +73,7 @@ }, { "cell_type": "code", - "execution_count": 169, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -86,7 +85,7 @@ "Name: 0, dtype: object" ] }, - "execution_count": 169, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -97,25 +96,34 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 64, "metadata": {}, "outputs": [], "source": [ - "def _find_geom(linestring_1, linestring_2, point):\n", - " if point == linestring_1.coords[0]:\n", - " geom_1 = linestring_1.coords[1]\n", - " else:\n", - " geom_1 = linestring_1.coords[-2]\n", - " if point == linestring_2.coords[0]:\n", - " geom_2 = linestring_2.coords[1]\n", + "def find_geom(linestring, point):\n", + " if point == linestring.coords[0]:\n", + " geom = [np.array(val) for val in linestring.coords[:2]]\n", " else:\n", - " geom_2 = linestring_2.coords[-2] \n", - " return geom_1, geom_2" + " geom = [np.array(val) for val in linestring.coords[-2:]]\n", + " return np.array(geom[0] - geom[1])" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "def angle(a, b):\n", + " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", + " if angle > 90:\n", + " angle = 180 - angle\n", + " return angle" + ] + }, + { + "cell_type": "code", + "execution_count": 66, "metadata": {}, "outputs": [], "source": [ @@ -146,11 +154,12 @@ " # Find the angles\n", " for ce, oe in list(product(chosen, other)):\n", " point = [G_primal.nodes[n][\"x\"], G_primal.nodes[n][\"y\"]]\n", - " gc, go = _find_geom(G_primal.edges[ce][\"geometry\"], G_primal.edges[oe][\"geometry\"], point)\n", + " gc = find_geom(G_primal.edges[ce][\"geometry\"], point)\n", + " go = find_geom(G_primal.edges[oe][\"geometry\"], point)\n", " if ce in angle_dict:\n", - " angle_dict[ce].append(_angle(gc, point, go))\n", + " angle_dict[ce].append(angle(gc, go))\n", " else:\n", - " angle_dict[ce]= [_angle(gc, point, go)]\n", + " angle_dict[ce]= [angle(gc, go)]\n", " # Keep the smallest angles\n", " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", " # TODO solve angles\n", @@ -163,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": 221, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -175,19 +184,19 @@ " G_stroke.nodes[n][\"stroke_access\"] = G_stroke.nodes[n][\"stroke_connectivity\"] - G_stroke.nodes[n][\"stroke_degree\"]\n", " angles = [val for e in G_stroke.edges(n) if G_stroke.edges[e][\"angles\"] for val in G_stroke.edges[e][\"angles\"]]\n", " G_stroke.nodes[n][\"stroke_orthogonality\"] = sum(angles) / G_stroke.nodes[n][\"stroke_connectivity\"]\n", - " G_stroke.nodes[n][\"stroke_:spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]" + " G_stroke.nodes[n][\"stroke_spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]" ] }, { "cell_type": "code", - "execution_count": 222, + "execution_count": 68, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_27796/2550495861.py:5: UserWarning: Approach is not set. Defaulting to 'primal'.\n", + "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_54955/2550495861.py:5: UserWarning: Approach is not set. Defaulting to 'primal'.\n", " points_stroke, lines_stroke = momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n" ] }, @@ -221,7 +230,7 @@ " <meta name="viewport" content="width=device-width,\n", " initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />\n", " <style>\n", - " #map_ad3194be1d4b4ed379b89a6a54007ae8 {\n", + " #map_3f909620e838580f27f572a1d038b48d {\n", " position: relative;\n", " width: 100.0%;\n", " height: 100.0%;\n", @@ -316,14 +325,14 @@ "<body>\n", " \n", " \n", - " <div class="folium-map" id="map_ad3194be1d4b4ed379b89a6a54007ae8" ></div>\n", + " <div class="folium-map" id="map_3f909620e838580f27f572a1d038b48d" ></div>\n", " \n", "</body>\n", "<script>\n", " \n", " \n", - " var map_ad3194be1d4b4ed379b89a6a54007ae8 = L.map(\n", - " "map_ad3194be1d4b4ed379b89a6a54007ae8",\n", + " var map_3f909620e838580f27f572a1d038b48d = L.map(\n", + " "map_3f909620e838580f27f572a1d038b48d",\n", " {\n", " center: [50.102935750000015, 14.403062600000004],\n", " crs: L.CRS.EPSG3857,\n", @@ -335,13 +344,13 @@ "\n", " }\n", " );\n", - " L.control.scale().addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " L.control.scale().addTo(map_3f909620e838580f27f572a1d038b48d);\n", "\n", " \n", "\n", " \n", " \n", - " var tile_layer_e307cfd7926aabb694ab68e0f7887cbf = L.tileLayer(\n", + " var tile_layer_f5905899af281f8109c1a377e3604417 = L.tileLayer(\n", " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",\n", " {\n", " "minZoom": 0,\n", @@ -358,16 +367,16 @@ " );\n", " \n", " \n", - " tile_layer_e307cfd7926aabb694ab68e0f7887cbf.addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " tile_layer_f5905899af281f8109c1a377e3604417.addTo(map_3f909620e838580f27f572a1d038b48d);\n", " \n", " \n", - " map_ad3194be1d4b4ed379b89a6a54007ae8.fitBounds(\n", + " map_3f909620e838580f27f572a1d038b48d.fitBounds(\n", " [[50.10007700000001, 14.398981599999999], [50.10579450000001, 14.407143600000008]],\n", " {}\n", " );\n", " \n", " \n", - " function geo_json_39a0e618cb8207c62b0b8473869f6bf3_styler(feature) {\n", + " function geo_json_0c2b53ed2c454e26c2a746abec90c455_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#1f77b4", "fillColor": "#1f77b4", "fillOpacity": 0.5, "weight": 2};\n", @@ -391,54 +400,54 @@ " return {"color": "#17becf", "fillColor": "#17becf", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_39a0e618cb8207c62b0b8473869f6bf3_highlighter(feature) {\n", + " function geo_json_0c2b53ed2c454e26c2a746abec90c455_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_39a0e618cb8207c62b0b8473869f6bf3_pointToLayer(feature, latlng) {\n", + " function geo_json_0c2b53ed2c454e26c2a746abec90c455_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_39a0e618cb8207c62b0b8473869f6bf3_styler(feature)\n", + " let style = geo_json_0c2b53ed2c454e26c2a746abec90c455_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_39a0e618cb8207c62b0b8473869f6bf3_onEachFeature(feature, layer) {\n", + " function geo_json_0c2b53ed2c454e26c2a746abec90c455_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_39a0e618cb8207c62b0b8473869f6bf3.resetStyle(e.target);\n", + " geo_json_0c2b53ed2c454e26c2a746abec90c455.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_39a0e618cb8207c62b0b8473869f6bf3_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_0c2b53ed2c454e26c2a746abec90c455_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_39a0e618cb8207c62b0b8473869f6bf3 = L.geoJson(null, {\n", - " onEachFeature: geo_json_39a0e618cb8207c62b0b8473869f6bf3_onEachFeature,\n", + " var geo_json_0c2b53ed2c454e26c2a746abec90c455 = L.geoJson(null, {\n", + " onEachFeature: geo_json_0c2b53ed2c454e26c2a746abec90c455_onEachFeature,\n", " \n", - " style: geo_json_39a0e618cb8207c62b0b8473869f6bf3_styler,\n", - " pointToLayer: geo_json_39a0e618cb8207c62b0b8473869f6bf3_pointToLayer,\n", + " style: geo_json_0c2b53ed2c454e26c2a746abec90c455_styler,\n", + " pointToLayer: geo_json_0c2b53ed2c454e26c2a746abec90c455_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_39a0e618cb8207c62b0b8473869f6bf3_add (data) {\n", - " geo_json_39a0e618cb8207c62b0b8473869f6bf3\n", + " function geo_json_0c2b53ed2c454e26c2a746abec90c455_add (data) {\n", + " geo_json_0c2b53ed2c454e26c2a746abec90c455\n", " .addData(data);\n", " }\n", - " geo_json_39a0e618cb8207c62b0b8473869f6bf3_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#1f77b4", "edge_ids": "[ 0 3 15 27]", "id": 0, "n_segments": 8, "stroke_group": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ff7f0e", "edge_ids": "[ 1 12 14 25]", "id": 1, "n_segments": 19, "stroke_group": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#2ca02c", "edge_ids": "[ 2 11 28 30]", "id": 2, "n_segments": 17, "stroke_group": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#d62728", "edge_ids": "[4 5 6]", "id": 3, "n_segments": 5, "stroke_group": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#9467bd", "edge_ids": "[ 7 8 9 13 21 22 24]", "id": 4, "n_segments": 14, "stroke_group": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#8c564b", "edge_ids": "[10]", "id": 5, "n_segments": 2, "stroke_group": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e377c2", "edge_ids": "[16 17 18 23 29]", "id": 6, "n_segments": 13, "stroke_group": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#7f7f7f", "edge_ids": "[19]", "id": 7, "n_segments": 3, "stroke_group": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#bcbd22", "edge_ids": "[20]", "id": 8, "n_segments": 3, "stroke_group": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#17becf", "edge_ids": "[26]", "id": 9, "n_segments": 5, "stroke_group": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_0c2b53ed2c454e26c2a746abec90c455_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#1f77b4", "edge_ids": "[ 0 3 15 27]", "id": 0, "n_segments": 8, "stroke_group": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ff7f0e", "edge_ids": "[ 1 12 14 25]", "id": 1, "n_segments": 19, "stroke_group": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#2ca02c", "edge_ids": "[ 2 11 28 30]", "id": 2, "n_segments": 17, "stroke_group": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#d62728", "edge_ids": "[4 5 6]", "id": 3, "n_segments": 5, "stroke_group": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#9467bd", "edge_ids": "[ 7 8 9 13 21 22 24]", "id": 4, "n_segments": 14, "stroke_group": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#8c564b", "edge_ids": "[10]", "id": 5, "n_segments": 2, "stroke_group": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e377c2", "edge_ids": "[16 17 18 23 29]", "id": 6, "n_segments": 13, "stroke_group": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#7f7f7f", "edge_ids": "[19]", "id": 7, "n_segments": 3, "stroke_group": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#bcbd22", "edge_ids": "[20]", "id": 8, "n_segments": 3, "stroke_group": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#17becf", "edge_ids": "[26]", "id": 9, "n_segments": 5, "stroke_group": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_39a0e618cb8207c62b0b8473869f6bf3.bindTooltip(\n", + " geo_json_0c2b53ed2c454e26c2a746abec90c455.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -465,46 +474,46 @@ "});\n", " \n", " \n", - " geo_json_39a0e618cb8207c62b0b8473869f6bf3.addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " geo_json_0c2b53ed2c454e26c2a746abec90c455.addTo(map_3f909620e838580f27f572a1d038b48d);\n", " \n", " \n", - " var color_map_863e16ede569cbbc311a5ab3c1a7a7bf = {};\n", + " var color_map_6adb0a80ec42c643a51b8b6009a2586a = {};\n", "\n", " \n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.color = d3.scale.threshold()\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.color = d3.scale.threshold()\n", " .domain([0.0, 0.018036072144288578, 0.036072144288577156, 0.05410821643286573, 0.07214428857715431, 0.09018036072144289, 0.10821643286573146, 0.12625250501002003, 0.14428857715430862, 0.1623246492985972, 0.18036072144288579, 0.19839679358717435, 0.21643286573146292, 0.23446893787575152, 0.25250501002004005, 0.27054108216432865, 0.28857715430861725, 0.3066132264529058, 0.3246492985971944, 0.342685370741483, 0.36072144288577157, 0.3787575150300601, 0.3967935871743487, 0.4148296593186373, 0.43286573146292584, 0.45090180360721444, 0.46893787575150303, 0.48697394789579157, 0.5050100200400801, 0.5230460921843687, 0.5410821643286573, 0.5591182364729459, 0.5771543086172345, 0.5951903807615231, 0.6132264529058116, 0.6312625250501002, 0.6492985971943888, 0.6673346693386774, 0.685370741482966, 0.7034068136272545, 0.7214428857715431, 0.7394789579158316, 0.7575150300601202, 0.7755511022044088, 0.7935871743486974, 0.811623246492986, 0.8296593186372746, 0.8476953907815631, 0.8657314629258517, 0.8837675350701403, 0.9018036072144289, 0.9198396793587175, 0.9378757515030061, 0.9559118236472945, 0.9739478957915831, 0.9919839679358717, 1.0100200400801602, 1.028056112224449, 1.0460921843687374, 1.0641282565130261, 1.0821643286573146, 1.1002004008016033, 1.1182364729458918, 1.1362725450901803, 1.154308617234469, 1.1723446893787575, 1.1903807615230462, 1.2084168336673347, 1.2264529058116231, 1.2444889779559118, 1.2625250501002003, 1.280561122244489, 1.2985971943887775, 1.3166332665330662, 1.3346693386773547, 1.3527054108216432, 1.370741482965932, 1.3887775551102204, 1.406813627254509, 1.4248496993987976, 1.4428857715430863, 1.4609218436873748, 1.4789579158316633, 1.496993987975952, 1.5150300601202404, 1.5330661322645291, 1.5511022044088176, 1.5691382765531061, 1.5871743486973948, 1.6052104208416833, 1.623246492985972, 1.6412825651302605, 1.6593186372745492, 1.6773547094188377, 1.6953907815631262, 1.7134268537074149, 1.7314629258517034, 1.749498997995992, 1.7675350701402806, 1.785571142284569, 1.8036072144288577, 1.8216432865731462, 1.839679358717435, 1.8577154308617234, 1.8757515030060121, 1.8937875751503006, 1.911823647294589, 1.9298597194388778, 1.9478957915831663, 1.965931863727455, 1.9839679358717435, 2.002004008016032, 2.0200400801603204, 2.038076152304609, 2.056112224448898, 2.0741482965931866, 2.092184368737475, 2.1102204408817635, 2.1282565130260522, 2.1462925851703405, 2.164328657314629, 2.182364729458918, 2.2004008016032066, 2.218436873747495, 2.2364729458917836, 2.2545090180360723, 2.2725450901803605, 2.2905811623246493, 2.308617234468938, 2.3266533066132267, 2.344689378757515, 2.3627254509018036, 2.3807615230460923, 2.3987975951903806, 2.4168336673346693, 2.434869739478958, 2.4529058116232463, 2.470941883767535, 2.4889779559118237, 2.5070140280561124, 2.5250501002004007, 2.5430861723446894, 2.561122244488978, 2.5791583166332663, 2.597194388777555, 2.6152304609218437, 2.6332665330661325, 2.6513026052104207, 2.6693386773547094, 2.687374749498998, 2.7054108216432864, 2.723446893787575, 2.741482965931864, 2.7595190380761525, 2.7775551102204408, 2.7955911823647295, 2.813627254509018, 2.8316633266533064, 2.849699398797595, 2.867735470941884, 2.8857715430861726, 2.903807615230461, 2.9218436873747495, 2.9398797595190382, 2.9579158316633265, 2.975951903807615, 2.993987975951904, 3.012024048096192, 3.030060120240481, 3.0480961923847696, 3.0661322645290583, 3.0841683366733466, 3.1022044088176353, 3.120240480961924, 3.1382765531062122, 3.156312625250501, 3.1743486973947896, 3.1923847695390783, 3.2104208416833666, 3.2284569138276553, 3.246492985971944, 3.2645290581162323, 3.282565130260521, 3.3006012024048097, 3.3186372745490984, 3.3366733466933867, 3.3547094188376754, 3.372745490981964, 3.3907815631262523, 3.408817635270541, 3.4268537074148298, 3.444889779559118, 3.4629258517034067, 3.4809619238476954, 3.498997995991984, 3.5170340681362724, 3.535070140280561, 3.55310621242485, 3.571142284569138, 3.5891783567134268, 3.6072144288577155, 3.625250501002004, 3.6432865731462925, 3.661322645290581, 3.67935871743487, 3.697394789579158, 3.715430861723447, 3.7334669338677355, 3.7515030060120242, 3.7695390781563125, 3.787575150300601, 3.80561122244489, 3.823647294589178, 3.841683366733467, 3.8597194388777556, 3.8777555110220443, 3.8957915831663326, 3.9138276553106213, 3.93186372745491, 3.9498997995991982, 3.967935871743487, 3.9859719438877756, 4.004008016032064, 4.022044088176353, 4.040080160320641, 4.05811623246493, 4.076152304609218, 4.094188376753507, 4.112224448897796, 4.130260521042084, 4.148296593186373, 4.166332665330661, 4.18436873747495, 4.202404809619239, 4.220440881763527, 4.238476953907815, 4.2565130260521045, 4.274549098196393, 4.292585170340681, 4.31062124248497, 4.328657314629258, 4.346693386773547, 4.364729458917836, 4.382765531062124, 4.400801603206413, 4.4188376753507015, 4.43687374749499, 4.454909819639279, 4.472945891783567, 4.490981963927855, 4.509018036072145, 4.527054108216433, 4.545090180360721, 4.56312625250501, 4.5811623246492985, 4.599198396793587, 4.617234468937876, 4.635270541082164, 4.653306613226453, 4.671342685370742, 4.68937875751503, 4.707414829659319, 4.725450901803607, 4.7434869739478955, 4.761523046092185, 4.779559118236473, 4.797595190380761, 4.81563126252505, 4.833667334669339, 4.851703406813627, 4.869739478957916, 4.887775551102204, 4.905811623246493, 4.923847695390782, 4.94188376753507, 4.959919839679359, 4.977955911823647, 4.995991983967936, 5.014028056112225, 5.032064128256513, 5.050100200400801, 5.0681362725450905, 5.086172344689379, 5.104208416833667, 5.122244488977956, 5.140280561122244, 5.158316633266533, 5.176352705410822, 5.19438877755511, 5.212424849699399, 5.2304609218436875, 5.248496993987976, 5.266533066132265, 5.284569138276553, 5.302605210420841, 5.320641282565131, 5.338677354709419, 5.356713426853707, 5.374749498997996, 5.3927855711422845, 5.410821643286573, 5.428857715430862, 5.44689378757515, 5.4649298597194385, 5.482965931863728, 5.501002004008016, 5.519038076152305, 5.537074148296593, 5.5551102204408815, 5.573146292585171, 5.591182364729459, 5.609218436873747, 5.627254509018036, 5.645290581162325, 5.663326653306613, 5.681362725450902, 5.69939879759519, 5.717434869739479, 5.735470941883768, 5.753507014028056, 5.771543086172345, 5.789579158316633, 5.807615230460922, 5.825651302605211, 5.843687374749499, 5.861723446893787, 5.8797595190380765, 5.897795591182365, 5.915831663326653, 5.933867735470942, 5.95190380761523, 5.969939879759519, 5.987975951903808, 6.006012024048096, 6.024048096192384, 6.0420841683366735, 6.060120240480962, 6.078156312625251, 6.096192384769539, 6.114228456913827, 6.132264529058117, 6.150300601202405, 6.168336673346693, 6.186372745490982, 6.2044088176352705, 6.222444889779559, 6.240480961923848, 6.258517034068136, 6.2765531062124245, 6.294589178356714, 6.312625250501002, 6.330661322645291, 6.348697394789579, 6.3667334669338675, 6.384769539078157, 6.402805611222445, 6.420841683366733, 6.438877755511022, 6.456913827655311, 6.474949899799599, 6.492985971943888, 6.511022044088176, 6.529058116232465, 6.547094188376754, 6.565130260521042, 6.58316633266533, 6.601202404809619, 6.619238476953908, 6.637274549098197, 6.655310621242485, 6.673346693386773, 6.6913827655310625, 6.709418837675351, 6.727454909819639, 6.745490981963928, 6.763527054108216, 6.781563126252505, 6.799599198396794, 6.817635270541082, 6.83567134268537, 6.8537074148296595, 6.871743486973948, 6.889779559118236, 6.907815631262525, 6.925851703406813, 6.943887775551103, 6.961923847695391, 6.979959919839679, 6.997995991983968, 7.0160320641282565, 7.034068136272545, 7.052104208416834, 7.070140280561122, 7.0881763527054105, 7.1062124248497, 7.124248496993988, 7.142284569138276, 7.160320641282565, 7.1783567134268536, 7.196392785571143, 7.214428857715431, 7.232464929859719, 7.250501002004008, 7.268537074148297, 7.286573146292585, 7.304609218436874, 7.322645290581162, 7.340681362725451, 7.35871743486974, 7.376753507014028, 7.394789579158316, 7.412825651302605, 7.430861723446894, 7.448897795591182, 7.466933867735471, 7.484969939879759, 7.5030060120240485, 7.521042084168337, 7.539078156312625, 7.557114228456914, 7.575150300601202, 7.593186372745491, 7.61122244488978, 7.629258517034068, 7.647294589178356, 7.6653306613226455, 7.683366733466934, 7.701402805611222, 7.719438877755511, 7.7374749498997994, 7.755511022044089, 7.773547094188377, 7.791583166332665, 7.809619238476954, 7.8276553106212425, 7.845691382765531, 7.86372745490982, 7.881763527054108, 7.8997995991983965, 7.917835671342686, 7.935871743486974, 7.953907815631262, 7.971943887775551, 7.98997995991984, 8.008016032064129, 8.026052104208416, 8.044088176352705, 8.062124248496994, 8.080160320641282, 8.098196392785571, 8.11623246492986, 8.134268537074147, 8.152304609218437, 8.170340681362726, 8.188376753507015, 8.206412825651302, 8.224448897795591, 8.24248496993988, 8.260521042084168, 8.278557114228457, 8.296593186372746, 8.314629258517034, 8.332665330661323, 8.350701402805612, 8.3687374749499, 8.386773547094188, 8.404809619238478, 8.422845691382765, 8.440881763527054, 8.458917835671343, 8.47695390781563, 8.49498997995992, 8.513026052104209, 8.531062124248496, 8.549098196392785, 8.567134268537075, 8.585170340681362, 8.603206412825651, 8.62124248496994, 8.639278557114228, 8.657314629258517, 8.675350701402806, 8.693386773547093, 8.711422845691382, 8.729458917835672, 8.74749498997996, 8.765531062124248, 8.783567134268537, 8.801603206412826, 8.819639278557114, 8.837675350701403, 8.855711422845692, 8.87374749498998, 8.891783567134269, 8.909819639278558, 8.927855711422845, 8.945891783567134, 8.963927855711423, 8.98196392785571, 9.0])\n", " .range(['#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff']);\n", " \n", "\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.x = d3.scale.linear()\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.x = d3.scale.linear()\n", " .domain([0.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.legend = L.control({position: 'topright'});\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.legend.addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.legend = L.control({position: 'topright'});\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.legend.addTo(map_3f909620e838580f27f572a1d038b48d);\n", "\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.xAxis = d3.svg.axis()\n", - " .scale(color_map_863e16ede569cbbc311a5ab3c1a7a7bf.x)\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.xAxis = d3.svg.axis()\n", + " .scale(color_map_6adb0a80ec42c643a51b8b6009a2586a.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', 1.8, '', 3.6, '', 5.4, '', 7.2, '', 9.0, '']);\n", "\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.g = color_map_863e16ede569cbbc311a5ab3c1a7a7bf.svg.append("g")\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.g = color_map_6adb0a80ec42c643a51b8b6009a2586a.svg.append("g")\n", " .attr("class", "key")\n", " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.g.selectAll("rect")\n", - " .data(color_map_863e16ede569cbbc311a5ab3c1a7a7bf.color.range().map(function(d, i) {\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.g.selectAll("rect")\n", + " .data(color_map_6adb0a80ec42c643a51b8b6009a2586a.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_863e16ede569cbbc311a5ab3c1a7a7bf.x(color_map_863e16ede569cbbc311a5ab3c1a7a7bf.color.domain()[i - 1]) : color_map_863e16ede569cbbc311a5ab3c1a7a7bf.x.range()[0],\n", - " x1: i < color_map_863e16ede569cbbc311a5ab3c1a7a7bf.color.domain().length ? color_map_863e16ede569cbbc311a5ab3c1a7a7bf.x(color_map_863e16ede569cbbc311a5ab3c1a7a7bf.color.domain()[i]) : color_map_863e16ede569cbbc311a5ab3c1a7a7bf.x.range()[1],\n", + " x0: i ? color_map_6adb0a80ec42c643a51b8b6009a2586a.x(color_map_6adb0a80ec42c643a51b8b6009a2586a.color.domain()[i - 1]) : color_map_6adb0a80ec42c643a51b8b6009a2586a.x.range()[0],\n", + " x1: i < color_map_6adb0a80ec42c643a51b8b6009a2586a.color.domain().length ? color_map_6adb0a80ec42c643a51b8b6009a2586a.x(color_map_6adb0a80ec42c643a51b8b6009a2586a.color.domain()[i]) : color_map_6adb0a80ec42c643a51b8b6009a2586a.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -514,66 +523,66 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_863e16ede569cbbc311a5ab3c1a7a7bf.g.call(color_map_863e16ede569cbbc311a5ab3c1a7a7bf.xAxis).append("text")\n", + " color_map_6adb0a80ec42c643a51b8b6009a2586a.g.call(color_map_6adb0a80ec42c643a51b8b6009a2586a.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", " .attr("fill", "black")\n", " .text("id");\n", " \n", - " function geo_json_bae06981bface585152ad88fc1a65341_styler(feature) {\n", + " function geo_json_223be950705750efd2fb109cc6a4119b_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_bae06981bface585152ad88fc1a65341_highlighter(feature) {\n", + " function geo_json_223be950705750efd2fb109cc6a4119b_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_bae06981bface585152ad88fc1a65341_pointToLayer(feature, latlng) {\n", + " function geo_json_223be950705750efd2fb109cc6a4119b_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_bae06981bface585152ad88fc1a65341_styler(feature)\n", + " let style = geo_json_223be950705750efd2fb109cc6a4119b_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_bae06981bface585152ad88fc1a65341_onEachFeature(feature, layer) {\n", + " function geo_json_223be950705750efd2fb109cc6a4119b_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_bae06981bface585152ad88fc1a65341.resetStyle(e.target);\n", + " geo_json_223be950705750efd2fb109cc6a4119b.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_bae06981bface585152ad88fc1a65341_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_223be950705750efd2fb109cc6a4119b_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_bae06981bface585152ad88fc1a65341 = L.geoJson(null, {\n", - " onEachFeature: geo_json_bae06981bface585152ad88fc1a65341_onEachFeature,\n", + " var geo_json_223be950705750efd2fb109cc6a4119b = L.geoJson(null, {\n", + " onEachFeature: geo_json_223be950705750efd2fb109cc6a4119b_onEachFeature,\n", " \n", - " style: geo_json_bae06981bface585152ad88fc1a65341_styler,\n", - " pointToLayer: geo_json_bae06981bface585152ad88fc1a65341_pointToLayer,\n", + " style: geo_json_223be950705750efd2fb109cc6a4119b_styler,\n", + " pointToLayer: geo_json_223be950705750efd2fb109cc6a4119b_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_bae06981bface585152ad88fc1a65341_add (data) {\n", - " geo_json_bae06981bface585152ad88fc1a65341\n", + " function geo_json_223be950705750efd2fb109cc6a4119b_add (data) {\n", + " geo_json_223be950705750efd2fb109cc6a4119b\n", " .addData(data);\n", " }\n", - " geo_json_bae06981bface585152ad88fc1a65341_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.40525490000001, 50.1047055, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [14.40525490000001, 50.1047055], "type": "Point"}, "id": "0", "properties": {"nodeID": 0, "x": 1603585.6402153103, "y": 6464428.773867372}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.1035529, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [14.403705899999995, 50.1035529], "type": "Point"}, "id": "1", "properties": {"nodeID": 1, "x": 1603413.2063240695, "y": 6464228.730248732}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10258519999999, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [14.402405999999988, 50.10258519999999], "type": "Point"}, "id": "2", "properties": {"nodeID": 2, "x": 1603268.502117987, "y": 6464060.781328565}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [14.403259899999986, 50.10241870000001], "type": "Point"}, "id": "3", "properties": {"nodeID": 3, "x": 1603363.557831175, "y": 6464031.88480676}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [14.405449500000003, 50.10328279999999], "type": "Point"}, "id": "4", "properties": {"nodeID": 4, "x": 1603607.3029882177, "y": 6464181.852772597}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [14.402032799999994, 50.10315780000001], "type": "Point"}, "id": "5", "properties": {"nodeID": 5, "x": 1603226.9576840235, "y": 6464160.158361825}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [14.400352999999992, 50.102739099999994], "type": "Point"}, "id": "6", "properties": {"nodeID": 6, "x": 1603039.9632033885, "y": 6464087.491175889}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.398981599999999, 50.1024077], "geometry": {"coordinates": [14.398981599999999, 50.1024077], "type": "Point"}, "id": "7", "properties": {"nodeID": 7, "x": 1602887.2996537155, "y": 6464029.975730775}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.103779500000016, 14.39972789999999, 50.103779500000016], "geometry": {"coordinates": [14.39972789999999, 50.103779500000016], "type": "Point"}, "id": "8", "properties": {"nodeID": 8, "x": 1602970.3773896934, "y": 6464268.058242684}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.102068500000016, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [14.400807100000003, 50.102068500000016], "type": "Point"}, "id": "9", "properties": {"nodeID": 9, "x": 1603090.513384159, "y": 6463971.106984773}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [14.402848699999991, 50.101294599999996], "type": "Point"}, "id": "10", "properties": {"nodeID": 10, "x": 1603317.7832565615, "y": 6463836.796863219}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.10149909999998, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [14.401812000000007, 50.10149909999998], "type": "Point"}, "id": "11", "properties": {"nodeID": 11, "x": 1603202.3783404578, "y": 6463872.287568242}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.400640399999995, 50.100679099999994], "geometry": {"coordinates": [14.400640399999995, 50.100679099999994], "type": "Point"}, "id": "12", "properties": {"nodeID": 12, "x": 1603071.956425043, "y": 6463729.978565}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [14.405837099999994, 50.10435879999999], "type": "Point"}, "id": "13", "properties": {"nodeID": 13, "x": 1603650.450422848, "y": 6464368.600601688}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [14.404608199999993, 50.10102239999999], "type": "Point"}, "id": "14", "properties": {"nodeID": 14, "x": 1603513.6499006122, "y": 6463789.557147608}, "type": "Feature"}, {"bbox": [14.407143600000008, 50.10099869999999, 14.407143600000008, 50.10099869999999], "geometry": {"coordinates": [14.407143600000008, 50.10099869999999], "type": "Point"}, "id": "15", "properties": {"nodeID": 15, "x": 1603795.889337571, "y": 6463785.444077063}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [14.405011000000012, 50.1021532], "type": "Point"}, "id": "16", "properties": {"nodeID": 16, "x": 1603558.489391506, "y": 6463985.80677705}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.399633600000007, 50.10131139999999], "geometry": {"coordinates": [14.399633600000007, 50.10131139999999], "type": "Point"}, "id": "17", "properties": {"nodeID": 17, "x": 1602959.8799617135, "y": 6463839.712475327}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.401311799999997, 50.101800699999984], "geometry": {"coordinates": [14.401311799999997, 50.101800699999984], "type": "Point"}, "id": "18", "properties": {"nodeID": 18, "x": 1603146.6963311615, "y": 6463924.630126579}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404248800000007, 50.10007700000001], "geometry": {"coordinates": [14.404248800000007, 50.10007700000001], "type": "Point"}, "id": "19", "properties": {"nodeID": 19, "x": 1603473.6416756227, "y": 6463625.487127112}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1049737, 14.400690199999993, 50.1049737], "geometry": {"coordinates": [14.400690199999993, 50.1049737], "type": "Point"}, "id": "20", "properties": {"nodeID": 20, "x": 1603077.5001356844, "y": 6464475.322968743}, "type": "Feature"}, {"bbox": [14.402574900000001, 50.105621199999995, 14.402574900000001, 50.105621199999995], "geometry": {"coordinates": [14.402574900000001, 50.105621199999995], "type": "Point"}, "id": "21", "properties": {"nodeID": 21, "x": 1603287.303979983, "y": 6464587.704889874}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402499399999995, 50.100328799999986], "geometry": {"coordinates": [14.402499399999995, 50.100328799999986], "type": "Point"}, "id": "22", "properties": {"nodeID": 22, "x": 1603278.8993584276, "y": 6463669.185595578}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1054507, 14.404819700000001, 50.1054507], "geometry": {"coordinates": [14.404819700000001, 50.1054507], "type": "Point"}, "id": "23", "properties": {"nodeID": 23, "x": 1603537.1939729159, "y": 6464558.11228298}, "type": "Feature"}, {"bbox": [14.406339600000006, 50.10579450000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [14.406339600000006, 50.10579450000001], "type": "Point"}, "id": "24", "properties": {"nodeID": 24, "x": 1603706.3884669733, "y": 6464617.783583014}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_223be950705750efd2fb109cc6a4119b_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.40525490000001, 50.1047055, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [14.40525490000001, 50.1047055], "type": "Point"}, "id": "0", "properties": {"nodeID": 0, "x": 1603585.6402153103, "y": 6464428.773867372}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.1035529, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [14.403705899999995, 50.1035529], "type": "Point"}, "id": "1", "properties": {"nodeID": 1, "x": 1603413.2063240695, "y": 6464228.730248732}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10258519999999, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [14.402405999999988, 50.10258519999999], "type": "Point"}, "id": "2", "properties": {"nodeID": 2, "x": 1603268.502117987, "y": 6464060.781328565}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [14.403259899999986, 50.10241870000001], "type": "Point"}, "id": "3", "properties": {"nodeID": 3, "x": 1603363.557831175, "y": 6464031.88480676}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [14.405449500000003, 50.10328279999999], "type": "Point"}, "id": "4", "properties": {"nodeID": 4, "x": 1603607.3029882177, "y": 6464181.852772597}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [14.402032799999994, 50.10315780000001], "type": "Point"}, "id": "5", "properties": {"nodeID": 5, "x": 1603226.9576840235, "y": 6464160.158361825}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [14.400352999999992, 50.102739099999994], "type": "Point"}, "id": "6", "properties": {"nodeID": 6, "x": 1603039.9632033885, "y": 6464087.491175889}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.398981599999999, 50.1024077], "geometry": {"coordinates": [14.398981599999999, 50.1024077], "type": "Point"}, "id": "7", "properties": {"nodeID": 7, "x": 1602887.2996537155, "y": 6464029.975730775}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.103779500000016, 14.39972789999999, 50.103779500000016], "geometry": {"coordinates": [14.39972789999999, 50.103779500000016], "type": "Point"}, "id": "8", "properties": {"nodeID": 8, "x": 1602970.3773896934, "y": 6464268.058242684}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.102068500000016, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [14.400807100000003, 50.102068500000016], "type": "Point"}, "id": "9", "properties": {"nodeID": 9, "x": 1603090.513384159, "y": 6463971.106984773}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [14.402848699999991, 50.101294599999996], "type": "Point"}, "id": "10", "properties": {"nodeID": 10, "x": 1603317.7832565615, "y": 6463836.796863219}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.10149909999998, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [14.401812000000007, 50.10149909999998], "type": "Point"}, "id": "11", "properties": {"nodeID": 11, "x": 1603202.3783404578, "y": 6463872.287568242}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.400640399999995, 50.100679099999994], "geometry": {"coordinates": [14.400640399999995, 50.100679099999994], "type": "Point"}, "id": "12", "properties": {"nodeID": 12, "x": 1603071.956425043, "y": 6463729.978565}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [14.405837099999994, 50.10435879999999], "type": "Point"}, "id": "13", "properties": {"nodeID": 13, "x": 1603650.450422848, "y": 6464368.600601688}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [14.404608199999993, 50.10102239999999], "type": "Point"}, "id": "14", "properties": {"nodeID": 14, "x": 1603513.6499006122, "y": 6463789.557147608}, "type": "Feature"}, {"bbox": [14.407143600000008, 50.10099869999999, 14.407143600000008, 50.10099869999999], "geometry": {"coordinates": [14.407143600000008, 50.10099869999999], "type": "Point"}, "id": "15", "properties": {"nodeID": 15, "x": 1603795.889337571, "y": 6463785.444077063}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [14.405011000000012, 50.1021532], "type": "Point"}, "id": "16", "properties": {"nodeID": 16, "x": 1603558.489391506, "y": 6463985.80677705}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.399633600000007, 50.10131139999999], "geometry": {"coordinates": [14.399633600000007, 50.10131139999999], "type": "Point"}, "id": "17", "properties": {"nodeID": 17, "x": 1602959.8799617135, "y": 6463839.712475327}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.401311799999997, 50.101800699999984], "geometry": {"coordinates": [14.401311799999997, 50.101800699999984], "type": "Point"}, "id": "18", "properties": {"nodeID": 18, "x": 1603146.6963311615, "y": 6463924.630126579}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404248800000007, 50.10007700000001], "geometry": {"coordinates": [14.404248800000007, 50.10007700000001], "type": "Point"}, "id": "19", "properties": {"nodeID": 19, "x": 1603473.6416756227, "y": 6463625.487127112}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1049737, 14.400690199999993, 50.1049737], "geometry": {"coordinates": [14.400690199999993, 50.1049737], "type": "Point"}, "id": "20", "properties": {"nodeID": 20, "x": 1603077.5001356844, "y": 6464475.322968743}, "type": "Feature"}, {"bbox": [14.402574900000001, 50.105621199999995, 14.402574900000001, 50.105621199999995], "geometry": {"coordinates": [14.402574900000001, 50.105621199999995], "type": "Point"}, "id": "21", "properties": {"nodeID": 21, "x": 1603287.303979983, "y": 6464587.704889874}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402499399999995, 50.100328799999986], "geometry": {"coordinates": [14.402499399999995, 50.100328799999986], "type": "Point"}, "id": "22", "properties": {"nodeID": 22, "x": 1603278.8993584276, "y": 6463669.185595578}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1054507, 14.404819700000001, 50.1054507], "geometry": {"coordinates": [14.404819700000001, 50.1054507], "type": "Point"}, "id": "23", "properties": {"nodeID": 23, "x": 1603537.1939729159, "y": 6464558.11228298}, "type": "Feature"}, {"bbox": [14.406339600000006, 50.10579450000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [14.406339600000006, 50.10579450000001], "type": "Point"}, "id": "24", "properties": {"nodeID": 24, "x": 1603706.3884669733, "y": 6464617.783583014}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_bae06981bface585152ad88fc1a65341.bindTooltip(\n", + " geo_json_223be950705750efd2fb109cc6a4119b.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -600,63 +609,63 @@ "});\n", " \n", " \n", - " geo_json_bae06981bface585152ad88fc1a65341.addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " geo_json_223be950705750efd2fb109cc6a4119b.addTo(map_3f909620e838580f27f572a1d038b48d);\n", " \n", " \n", - " function geo_json_c2b54c20a83aabe517060cb36164c1d5_styler(feature) {\n", + " function geo_json_56d94515e567fb4a3c72716557b8d795_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_c2b54c20a83aabe517060cb36164c1d5_highlighter(feature) {\n", + " function geo_json_56d94515e567fb4a3c72716557b8d795_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_c2b54c20a83aabe517060cb36164c1d5_pointToLayer(feature, latlng) {\n", + " function geo_json_56d94515e567fb4a3c72716557b8d795_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_c2b54c20a83aabe517060cb36164c1d5_styler(feature)\n", + " let style = geo_json_56d94515e567fb4a3c72716557b8d795_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_c2b54c20a83aabe517060cb36164c1d5_onEachFeature(feature, layer) {\n", + " function geo_json_56d94515e567fb4a3c72716557b8d795_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_c2b54c20a83aabe517060cb36164c1d5.resetStyle(e.target);\n", + " geo_json_56d94515e567fb4a3c72716557b8d795.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_c2b54c20a83aabe517060cb36164c1d5_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_56d94515e567fb4a3c72716557b8d795_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_c2b54c20a83aabe517060cb36164c1d5 = L.geoJson(null, {\n", - " onEachFeature: geo_json_c2b54c20a83aabe517060cb36164c1d5_onEachFeature,\n", + " var geo_json_56d94515e567fb4a3c72716557b8d795 = L.geoJson(null, {\n", + " onEachFeature: geo_json_56d94515e567fb4a3c72716557b8d795_onEachFeature,\n", " \n", - " style: geo_json_c2b54c20a83aabe517060cb36164c1d5_styler,\n", - " pointToLayer: geo_json_c2b54c20a83aabe517060cb36164c1d5_pointToLayer,\n", + " style: geo_json_56d94515e567fb4a3c72716557b8d795_styler,\n", + " pointToLayer: geo_json_56d94515e567fb4a3c72716557b8d795_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_c2b54c20a83aabe517060cb36164c1d5_add (data) {\n", - " geo_json_c2b54c20a83aabe517060cb36164c1d5\n", + " function geo_json_56d94515e567fb4a3c72716557b8d795_add (data) {\n", + " geo_json_56d94515e567fb4a3c72716557b8d795\n", " .addData(data);\n", " }\n", - " geo_json_c2b54c20a83aabe517060cb36164c1d5_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"edge_id": 0, "mm_len": 264.1039496246775, "node_end": 1, "node_start": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"edge_id": 1, "mm_len": 99.75118962647376, "node_end": 3, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"edge_id": 2, "mm_len": 199.74650338337847, "node_end": 4, "node_start": 1, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"edge_id": 3, "mm_len": 203.01409000575802, "node_end": 3, "node_start": 1, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"edge_id": 4, "mm_len": 198.48272399064462, "node_end": 5, "node_start": 1, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"edge_id": 5, "mm_len": 200.61768541143937, "node_end": 6, "node_start": 5, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"edge_id": 6, "mm_len": 163.14628203947333, "node_end": 7, "node_start": 6, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"edge_id": 7, "mm_len": 193.51137206831748, "node_end": 8, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"edge_id": 8, "mm_len": 127.80086449751786, "node_end": 9, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"edge_id": 9, "mm_len": 122.5319618088215, "node_end": 11, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"edge_id": 10, "mm_len": 193.04063727323836, "node_end": 12, "node_start": 11, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"edge_id": 11, "mm_len": 88.92430548419476, "node_end": 13, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"edge_id": 12, "mm_len": 107.88014814146449, "node_end": 5, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"edge_id": 13, "mm_len": 282.6905386499787, "node_end": 15, "node_start": 14, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"edge_id": 14, "mm_len": 200.30351738673852, "node_end": 16, "node_start": 3, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"edge_id": 15, "mm_len": 200.3861708266132, "node_end": 10, "node_start": 3, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"edge_id": 16, "mm_len": 191.66755798860544, "node_end": 13, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"edge_id": 17, "mm_len": 202.03167967950094, "node_end": 16, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"edge_id": 18, "mm_len": 201.30697205908257, "node_end": 16, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"edge_id": 19, "mm_len": 187.49184699173748, "node_end": 17, "node_start": 9, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"edge_id": 20, "mm_len": 182.6849740039611, "node_end": 18, "node_start": 2, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"edge_id": 21, "mm_len": 72.91516907666792, "node_end": 18, "node_start": 9, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"edge_id": 22, "mm_len": 76.42465276315266, "node_end": 18, "node_start": 11, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"edge_id": 23, "mm_len": 168.88041067114747, "node_end": 19, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"edge_id": 24, "mm_len": 201.4861168351184, "node_end": 14, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"edge_id": 25, "mm_len": 351.1551873514152, "node_end": 20, "node_start": 5, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"edge_id": 26, "mm_len": 382.50195042922803, "node_end": 21, "node_start": 1, "stroke_id": 9}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"edge_id": 27, "mm_len": 172.0624733749828, "node_end": 22, "node_start": 10, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"edge_id": 28, "mm_len": 138.23490844748363, "node_end": 23, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"edge_id": 29, "mm_len": 255.8228880811063, "node_end": 24, "node_start": 13, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"edge_id": 30, "mm_len": 317.85221640975095, "node_end": 13, "node_start": 4, "stroke_id": 2}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_56d94515e567fb4a3c72716557b8d795_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"edge_id": 0, "mm_len": 264.1039496246775, "node_end": 1, "node_start": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"edge_id": 1, "mm_len": 99.75118962647376, "node_end": 3, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"edge_id": 2, "mm_len": 199.74650338337847, "node_end": 4, "node_start": 1, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"edge_id": 3, "mm_len": 203.01409000575802, "node_end": 3, "node_start": 1, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"edge_id": 4, "mm_len": 198.48272399064462, "node_end": 5, "node_start": 1, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"edge_id": 5, "mm_len": 200.61768541143937, "node_end": 6, "node_start": 5, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"edge_id": 6, "mm_len": 163.14628203947333, "node_end": 7, "node_start": 6, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"edge_id": 7, "mm_len": 193.51137206831748, "node_end": 8, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"edge_id": 8, "mm_len": 127.80086449751786, "node_end": 9, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"edge_id": 9, "mm_len": 122.5319618088215, "node_end": 11, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"edge_id": 10, "mm_len": 193.04063727323836, "node_end": 12, "node_start": 11, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"edge_id": 11, "mm_len": 88.92430548419476, "node_end": 13, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"edge_id": 12, "mm_len": 107.88014814146449, "node_end": 5, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"edge_id": 13, "mm_len": 282.6905386499787, "node_end": 15, "node_start": 14, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"edge_id": 14, "mm_len": 200.30351738673852, "node_end": 16, "node_start": 3, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"edge_id": 15, "mm_len": 200.3861708266132, "node_end": 10, "node_start": 3, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"edge_id": 16, "mm_len": 191.66755798860544, "node_end": 13, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"edge_id": 17, "mm_len": 202.03167967950094, "node_end": 16, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"edge_id": 18, "mm_len": 201.30697205908257, "node_end": 16, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"edge_id": 19, "mm_len": 187.49184699173748, "node_end": 17, "node_start": 9, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"edge_id": 20, "mm_len": 182.6849740039611, "node_end": 18, "node_start": 2, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"edge_id": 21, "mm_len": 72.91516907666792, "node_end": 18, "node_start": 9, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"edge_id": 22, "mm_len": 76.42465276315266, "node_end": 18, "node_start": 11, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"edge_id": 23, "mm_len": 168.88041067114747, "node_end": 19, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"edge_id": 24, "mm_len": 201.4861168351184, "node_end": 14, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"edge_id": 25, "mm_len": 351.1551873514152, "node_end": 20, "node_start": 5, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"edge_id": 26, "mm_len": 382.50195042922803, "node_end": 21, "node_start": 1, "stroke_id": 9}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"edge_id": 27, "mm_len": 172.0624733749828, "node_end": 22, "node_start": 10, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"edge_id": 28, "mm_len": 138.23490844748363, "node_end": 23, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"edge_id": 29, "mm_len": 255.8228880811063, "node_end": 24, "node_start": 13, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"edge_id": 30, "mm_len": 317.85221640975095, "node_end": 13, "node_start": 4, "stroke_id": 2}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_c2b54c20a83aabe517060cb36164c1d5.bindTooltip(\n", + " geo_json_56d94515e567fb4a3c72716557b8d795.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -683,63 +692,63 @@ "});\n", " \n", " \n", - " geo_json_c2b54c20a83aabe517060cb36164c1d5.addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " geo_json_56d94515e567fb4a3c72716557b8d795.addTo(map_3f909620e838580f27f572a1d038b48d);\n", " \n", " \n", - " function geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_styler(feature) {\n", + " function geo_json_b4699a2640fa07c6cb89f04625ff435a_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"color": "black", "fillColor": "black", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_highlighter(feature) {\n", + " function geo_json_b4699a2640fa07c6cb89f04625ff435a_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_pointToLayer(feature, latlng) {\n", + " function geo_json_b4699a2640fa07c6cb89f04625ff435a_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 10, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_styler(feature)\n", + " let style = geo_json_b4699a2640fa07c6cb89f04625ff435a_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_onEachFeature(feature, layer) {\n", + " function geo_json_b4699a2640fa07c6cb89f04625ff435a_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d.resetStyle(e.target);\n", + " geo_json_b4699a2640fa07c6cb89f04625ff435a.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_b4699a2640fa07c6cb89f04625ff435a_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d = L.geoJson(null, {\n", - " onEachFeature: geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_onEachFeature,\n", + " var geo_json_b4699a2640fa07c6cb89f04625ff435a = L.geoJson(null, {\n", + " onEachFeature: geo_json_b4699a2640fa07c6cb89f04625ff435a_onEachFeature,\n", " \n", - " style: geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_styler,\n", - " pointToLayer: geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_pointToLayer,\n", + " style: geo_json_b4699a2640fa07c6cb89f04625ff435a_styler,\n", + " pointToLayer: geo_json_b4699a2640fa07c6cb89f04625ff435a_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_add (data) {\n", - " geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d\n", + " function geo_json_b4699a2640fa07c6cb89f04625ff435a_add (data) {\n", + " geo_json_b4699a2640fa07c6cb89f04625ff435a\n", " .addData(data);\n", " }\n", - " geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "black", "edge_ids": "[ 0 3 15 27]", "geometry_stroke": "LINESTRING (1603278.8993584276 6463669.185595578, 1603283.7306243288 6463690.028353462, 1603314.4436718386 6463822.409720818, 1603317.7832565615 6463836.796863219, 1603361.0308787343 6464021.107210826, 1603363.557831175 6464031.88480676, 1603376.5042879563 6464085.530021086, 1603413.2063240695 6464228.730248732, 1603585.6402153103 6464428.773867372)", "length": 839.5666838320316, "n_segments": 8, "nodeID": 0, "stroke_:spacing": 104.94583547900395, "stroke_access": 3, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 8, "stroke_degree": 5, "stroke_orthogonality": 69.3883651804331, "x": "array(\\u0027d\\u0027, [1603374.6625343116])", "y": "array(\\u0027d\\u0027, [6464077.898491419])"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "black", "edge_ids": "[ 1 12 14 25]", "geometry_stroke": "LINESTRING (1603077.5001356844 6464475.322968743, 1603085.5151390221 6464462.305855976, 1603095.1999347198 6464446.563854833, 1603122.5066058137 6464393.870890386, 1603135.486458439 6464371.013077857, 1603149.2010197043 6464359.054839547, 1603152.6964517166 6464350.116544929, 1603156.9933840595 6464339.130265876, 1603161.5797470808 6464327.415055399, 1603223.2396130317 6464169.912161903, 1603226.9576840235 6464160.158361825, 1603232.3010195831 6464146.100413868, 1603255.644716802 6464084.749030368, 1603268.502117987 6464060.781328565, 1603296.8217964454 6464047.851641227, 1603349.1085612718 6464035.338499875, 1603363.557831175 6464031.88480676, 1603376.025614145 6464028.934416787, 1603544.6523787973 6463989.069544387, 1603558.489391506 6463985.80677705)", "length": 759.0900425060918, "n_segments": 19, "nodeID": 1, "stroke_:spacing": 126.51500708434862, "stroke_access": 2, "stroke_betweenness": 0.08796296296296295, "stroke_closeness": 0.5625, "stroke_connectivity": 6, "stroke_degree": 4, "stroke_orthogonality": 69.54399401604321, "x": "array(\\u0027d\\u0027, [1603237.0487682838])", "y": "array(\\u0027d\\u0027, [6464133.622486805])"}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "black", "edge_ids": "[ 2 11 28 30]", "geometry_stroke": "LINESTRING (1603537.1939729159 6464558.11228298, 1603557.6878911697 6464504.984705836, 1603561.7399206352 6464494.466839611, 1603564.634227396 6464481.987738368, 1603585.6402153103 6464428.773867372, 1603603.0951114655 6464413.0145736905, 1603641.889954006 6464381.218380466, 1603650.450422848 6464368.600601688, 1603664.8217691095 6464355.097690451, 1603676.1429613235 6464344.076693036, 1603680.7181923958 6464326.616686098, 1603697.6387549953 6464272.223619222, 1603722.7079043242 6464183.866016789, 1603618.7800277183 6464181.019706178, 1603607.3029882177 6464181.852772597, 1603592.8871141581 6464183.935439011, 1603433.8783535103 6464223.419421798, 1603413.2063240695 6464228.730248732)", "length": 744.7579337248078, "n_segments": 17, "nodeID": 2, "stroke_:spacing": 93.09474171560097, "stroke_access": 4, "stroke_betweenness": 0.04629629629629629, "stroke_closeness": 0.5294117647058824, "stroke_connectivity": 8, "stroke_degree": 4, "stroke_orthogonality": 57.19645753289334, "x": "array(\\u0027d\\u0027, [1603707.1065106073])", "y": "array(\\u0027d\\u0027, [6464238.853991265])"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "black", "edge_ids": "[4 5 6]", "geometry_stroke": "LINESTRING (1603413.2063240695 6464228.730248732, 1603274.457710744 6464178.659351781, 1603226.9576840235 6464160.158361825, 1603039.9632033885 6464087.491175889, 1602902.3166530235 6464035.130236932, 1602887.2996537155 6464029.975730775)", "length": 562.2466914415573, "n_segments": 5, "nodeID": 3, "stroke_:spacing": 80.32095592022247, "stroke_access": 2, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 7, "stroke_degree": 5, "stroke_orthogonality": 70.46868260334638, "x": "array(\\u0027d\\u0027, [1603149.9288811635])", "y": "array(\\u0027d\\u0027, [6464130.224503239])"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "black", "edge_ids": "[ 7 8 9 13 21 22 24]", "geometry_stroke": "LINESTRING (1602970.3773896934 6464268.058242684, 1602974.0843287394 6464258.443173138, 1603039.9632033885 6464087.491175889, 1603074.7839401108 6463991.950499589, 1603090.513384159 6463971.106984773, 1603146.6963311615 6463924.630126579, 1603157.794884393 6463914.581579376, 1603202.3783404578 6463872.287568242, 1603217.2506244255 6463859.844110653, 1603317.7832565615 6463836.796863219, 1603334.948722044 6463832.631704839, 1603497.3304632641 6463793.166932718, 1603513.6499006122 6463789.557147608, 1603542.0029749167 6463784.4895673115, 1603795.889337571 6463785.444077063)", "length": 1077.3606756995746, "n_segments": 14, "nodeID": 4, "stroke_:spacing": 119.70674174439718, "stroke_access": 3, "stroke_betweenness": 0.5046296296296297, "stroke_closeness": 0.75, "stroke_connectivity": 9, "stroke_degree": 6, "stroke_orthogonality": 84.31903208885441, "x": "array(\\u0027d\\u0027, [1603264.6577362637])", "y": "array(\\u0027d\\u0027, [6463848.97596353])"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "black", "edge_ids": "[10]", "geometry_stroke": "LINESTRING (1603071.956425043 6463729.978565, 1603089.0217029832 6463747.749702545, 1603202.3783404578 6463872.287568242)", "length": 193.04063727323836, "n_segments": 2, "nodeID": 5, "stroke_:spacing": 193.04063727323836, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 87.60977577529626, "x": "array(\\u0027d\\u0027, [1603137.4077031056])", "y": "array(\\u0027d\\u0027, [6463800.908382258])"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "black", "edge_ids": "[16 17 18 23 29]", "geometry_stroke": "LINESTRING (1603706.3884669733 6464617.783583014, 1603705.7539458754 6464597.632755783, 1603681.3749773917 6464489.555035355, 1603678.970476391 6464477.214790825, 1603675.6865514126 6464464.336524226, 1603674.2282660832 6464458.799917089, 1603650.450422848 6464368.600601688, 1603607.3029882177 6464181.852772597, 1603558.489391506 6463985.80677705, 1603513.6499006122 6463789.557147608, 1603480.142733884 6463653.653349537, 1603478.918219486 6463648.325535514, 1603477.8829482212 6463643.67454756, 1603473.6416756227 6463625.487127112)", "length": 1019.7095084794428, "n_segments": 13, "nodeID": 6, "stroke_:spacing": 145.67278692563468, "stroke_access": 4, "stroke_betweenness": 0.06712962962962961, "stroke_closeness": 0.6, "stroke_connectivity": 7, "stroke_degree": 3, "stroke_orthogonality": 61.210166482080595, "x": "array(\\u0027d\\u0027, [1603592.2349246691])", "y": "array(\\u0027d\\u0027, [6464121.336160048])"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "black", "edge_ids": "[19]", "geometry_stroke": "LINESTRING (1602959.8799617135 6463839.712475327, 1602973.3607520477 6463844.207379333, 1602987.0753133134 6463853.041000848, 1603090.513384159 6463971.106984773)", "length": 187.49184699173748, "n_segments": 3, "nodeID": 7, "stroke_:spacing": 187.49184699173748, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 48.7782715761349, "x": "array(\\u0027d\\u0027, [1603028.737187382])", "y": "array(\\u0027d\\u0027, [6463900.594576759])"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "black", "edge_ids": "[20]", "geometry_stroke": "LINESTRING (1603146.6963311615 6463924.630126579, 1603157.0490438067 6463936.205929175, 1603258.3275165292 6464049.413615812, 1603268.502117987 6464060.781328565)", "length": 182.6849740039611, "n_segments": 3, "nodeID": 8, "stroke_:spacing": 91.34248700198054, "stroke_access": 0, "stroke_betweenness": 0.020833333333333332, "stroke_closeness": 0.5, "stroke_connectivity": 2, "stroke_degree": 2, "stroke_orthogonality": 76.7355776933224, "x": "array(\\u0027d\\u0027, [1603207.5969886228])", "y": "array(\\u0027d\\u0027, [6463992.707728057])"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "black", "edge_ids": "[26]", "geometry_stroke": "LINESTRING (1603287.303979983 6464587.704889874, 1603286.8809659188 6464556.602281818, 1603337.5981259246 6464418.98505148, 1603340.9265786987 6464409.959912292, 1603345.6687890065 6464397.932193951, 1603413.2063240695 6464228.730248732)", "length": 382.50195042922803, "n_segments": 5, "nodeID": 9, "stroke_:spacing": 127.50065014307602, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.5, "stroke_connectivity": 3, "stroke_degree": 3, "stroke_orthogonality": 60.62784756793311, "x": "array(\\u0027d\\u0027, [1603342.3426854417])", "y": "array(\\u0027d\\u0027, [6464406.368225728])"}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_b4699a2640fa07c6cb89f04625ff435a_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "black", "edge_ids": "[ 0 3 15 27]", "geometry_stroke": "LINESTRING (1603278.8993584276 6463669.185595578, 1603283.7306243288 6463690.028353462, 1603314.4436718386 6463822.409720818, 1603317.7832565615 6463836.796863219, 1603361.0308787343 6464021.107210826, 1603363.557831175 6464031.88480676, 1603376.5042879563 6464085.530021086, 1603413.2063240695 6464228.730248732, 1603585.6402153103 6464428.773867372)", "length": 839.5666838320316, "n_segments": 8, "nodeID": 0, "stroke_:spacing": 104.94583547900395, "stroke_access": 3, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 8, "stroke_degree": 5, "stroke_orthogonality": 61.889319613560986, "x": "array(\\u0027d\\u0027, [1603374.6625343116])", "y": "array(\\u0027d\\u0027, [6464077.898491419])"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "black", "edge_ids": "[ 1 12 14 25]", "geometry_stroke": "LINESTRING (1603077.5001356844 6464475.322968743, 1603085.5151390221 6464462.305855976, 1603095.1999347198 6464446.563854833, 1603122.5066058137 6464393.870890386, 1603135.486458439 6464371.013077857, 1603149.2010197043 6464359.054839547, 1603152.6964517166 6464350.116544929, 1603156.9933840595 6464339.130265876, 1603161.5797470808 6464327.415055399, 1603223.2396130317 6464169.912161903, 1603226.9576840235 6464160.158361825, 1603232.3010195831 6464146.100413868, 1603255.644716802 6464084.749030368, 1603268.502117987 6464060.781328565, 1603296.8217964454 6464047.851641227, 1603349.1085612718 6464035.338499875, 1603363.557831175 6464031.88480676, 1603376.025614145 6464028.934416787, 1603544.6523787973 6463989.069544387, 1603558.489391506 6463985.80677705)", "length": 759.0900425060918, "n_segments": 19, "nodeID": 1, "stroke_:spacing": 126.51500708434862, "stroke_access": 2, "stroke_betweenness": 0.08796296296296295, "stroke_closeness": 0.5625, "stroke_connectivity": 6, "stroke_degree": 4, "stroke_orthogonality": 83.69254851816929, "x": "array(\\u0027d\\u0027, [1603237.0487682838])", "y": "array(\\u0027d\\u0027, [6464133.622486805])"}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "black", "edge_ids": "[ 2 11 28 30]", "geometry_stroke": "LINESTRING (1603537.1939729159 6464558.11228298, 1603557.6878911697 6464504.984705836, 1603561.7399206352 6464494.466839611, 1603564.634227396 6464481.987738368, 1603585.6402153103 6464428.773867372, 1603603.0951114655 6464413.0145736905, 1603641.889954006 6464381.218380466, 1603650.450422848 6464368.600601688, 1603664.8217691095 6464355.097690451, 1603676.1429613235 6464344.076693036, 1603680.7181923958 6464326.616686098, 1603697.6387549953 6464272.223619222, 1603722.7079043242 6464183.866016789, 1603618.7800277183 6464181.019706178, 1603607.3029882177 6464181.852772597, 1603592.8871141581 6464183.935439011, 1603433.8783535103 6464223.419421798, 1603413.2063240695 6464228.730248732)", "length": 744.7579337248078, "n_segments": 17, "nodeID": 2, "stroke_:spacing": 93.09474171560097, "stroke_access": 4, "stroke_betweenness": 0.04629629629629629, "stroke_closeness": 0.5294117647058824, "stroke_connectivity": 8, "stroke_degree": 4, "stroke_orthogonality": 58.853128911121644, "x": "array(\\u0027d\\u0027, [1603707.1065106073])", "y": "array(\\u0027d\\u0027, [6464238.853991265])"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "black", "edge_ids": "[4 5 6]", "geometry_stroke": "LINESTRING (1603413.2063240695 6464228.730248732, 1603274.457710744 6464178.659351781, 1603226.9576840235 6464160.158361825, 1603039.9632033885 6464087.491175889, 1602902.3166530235 6464035.130236932, 1602887.2996537155 6464029.975730775)", "length": 562.2466914415573, "n_segments": 5, "nodeID": 3, "stroke_:spacing": 80.32095592022247, "stroke_access": 2, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 7, "stroke_degree": 5, "stroke_orthogonality": 67.41154917006796, "x": "array(\\u0027d\\u0027, [1603149.9288811635])", "y": "array(\\u0027d\\u0027, [6464130.224503239])"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "black", "edge_ids": "[ 7 8 9 13 21 22 24]", "geometry_stroke": "LINESTRING (1602970.3773896934 6464268.058242684, 1602974.0843287394 6464258.443173138, 1603039.9632033885 6464087.491175889, 1603074.7839401108 6463991.950499589, 1603090.513384159 6463971.106984773, 1603146.6963311615 6463924.630126579, 1603157.794884393 6463914.581579376, 1603202.3783404578 6463872.287568242, 1603217.2506244255 6463859.844110653, 1603317.7832565615 6463836.796863219, 1603334.948722044 6463832.631704839, 1603497.3304632641 6463793.166932718, 1603513.6499006122 6463789.557147608, 1603542.0029749167 6463784.4895673115, 1603795.889337571 6463785.444077063)", "length": 1077.3606756995746, "n_segments": 14, "nodeID": 4, "stroke_:spacing": 119.70674174439718, "stroke_access": 3, "stroke_betweenness": 0.5046296296296297, "stroke_closeness": 0.75, "stroke_connectivity": 9, "stroke_degree": 6, "stroke_orthogonality": 76.90795995185228, "x": "array(\\u0027d\\u0027, [1603264.6577362637])", "y": "array(\\u0027d\\u0027, [6463848.97596353])"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "black", "edge_ids": "[10]", "geometry_stroke": "LINESTRING (1603071.956425043 6463729.978565, 1603089.0217029832 6463747.749702545, 1603202.3783404578 6463872.287568242)", "length": 193.04063727323836, "n_segments": 2, "nodeID": 5, "stroke_:spacing": 193.04063727323836, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 87.60977577529626, "x": "array(\\u0027d\\u0027, [1603137.4077031056])", "y": "array(\\u0027d\\u0027, [6463800.908382258])"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "black", "edge_ids": "[16 17 18 23 29]", "geometry_stroke": "LINESTRING (1603706.3884669733 6464617.783583014, 1603705.7539458754 6464597.632755783, 1603681.3749773917 6464489.555035355, 1603678.970476391 6464477.214790825, 1603675.6865514126 6464464.336524226, 1603674.2282660832 6464458.799917089, 1603650.450422848 6464368.600601688, 1603607.3029882177 6464181.852772597, 1603558.489391506 6463985.80677705, 1603513.6499006122 6463789.557147608, 1603480.142733884 6463653.653349537, 1603478.918219486 6463648.325535514, 1603477.8829482212 6463643.67454756, 1603473.6416756227 6463625.487127112)", "length": 1019.7095084794428, "n_segments": 13, "nodeID": 6, "stroke_:spacing": 145.67278692563468, "stroke_access": 4, "stroke_betweenness": 0.06712962962962961, "stroke_closeness": 0.6, "stroke_connectivity": 7, "stroke_degree": 3, "stroke_orthogonality": 72.94921342069121, "x": "array(\\u0027d\\u0027, [1603592.2349246691])", "y": "array(\\u0027d\\u0027, [6464121.336160048])"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "black", "edge_ids": "[19]", "geometry_stroke": "LINESTRING (1602959.8799617135 6463839.712475327, 1602973.3607520477 6463844.207379333, 1602987.0753133134 6463853.041000848, 1603090.513384159 6463971.106984773)", "length": 187.49184699173748, "n_segments": 3, "nodeID": 7, "stroke_:spacing": 187.49184699173748, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 78.26155769686821, "x": "array(\\u0027d\\u0027, [1603028.737187382])", "y": "array(\\u0027d\\u0027, [6463900.594576759])"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "black", "edge_ids": "[20]", "geometry_stroke": "LINESTRING (1603146.6963311615 6463924.630126579, 1603157.0490438067 6463936.205929175, 1603258.3275165292 6464049.413615812, 1603268.502117987 6464060.781328565)", "length": 182.6849740039611, "n_segments": 3, "nodeID": 8, "stroke_:spacing": 91.34248700198054, "stroke_access": 0, "stroke_betweenness": 0.020833333333333332, "stroke_closeness": 0.5, "stroke_connectivity": 2, "stroke_degree": 2, "stroke_orthogonality": 74.69091059653624, "x": "array(\\u0027d\\u0027, [1603207.5969886228])", "y": "array(\\u0027d\\u0027, [6463992.707728057])"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "black", "edge_ids": "[26]", "geometry_stroke": "LINESTRING (1603287.303979983 6464587.704889874, 1603286.8809659188 6464556.602281818, 1603337.5981259246 6464418.98505148, 1603340.9265786987 6464409.959912292, 1603345.6687890065 6464397.932193951, 1603413.2063240695 6464228.730248732)", "length": 382.50195042922803, "n_segments": 5, "nodeID": 9, "stroke_:spacing": 127.50065014307602, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.5, "stroke_connectivity": 3, "stroke_degree": 3, "stroke_orthogonality": 59.82941708655712, "x": "array(\\u0027d\\u0027, [1603342.3426854417])", "y": "array(\\u0027d\\u0027, [6464406.368225728])"}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d.bindTooltip(\n", + " geo_json_b4699a2640fa07c6cb89f04625ff435a.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -766,63 +775,63 @@ "});\n", " \n", " \n", - " geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d.addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " geo_json_b4699a2640fa07c6cb89f04625ff435a.addTo(map_3f909620e838580f27f572a1d038b48d);\n", " \n", " \n", - " function geo_json_b4ec85b136b49ead414b7f9330771dcb_styler(feature) {\n", + " function geo_json_f3c73a92a2d430c6cbea06e79ebad19a_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"color": "blue", "fillColor": "blue", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_b4ec85b136b49ead414b7f9330771dcb_highlighter(feature) {\n", + " function geo_json_f3c73a92a2d430c6cbea06e79ebad19a_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_b4ec85b136b49ead414b7f9330771dcb_pointToLayer(feature, latlng) {\n", + " function geo_json_f3c73a92a2d430c6cbea06e79ebad19a_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_b4ec85b136b49ead414b7f9330771dcb_styler(feature)\n", + " let style = geo_json_f3c73a92a2d430c6cbea06e79ebad19a_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_b4ec85b136b49ead414b7f9330771dcb_onEachFeature(feature, layer) {\n", + " function geo_json_f3c73a92a2d430c6cbea06e79ebad19a_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_b4ec85b136b49ead414b7f9330771dcb.resetStyle(e.target);\n", + " geo_json_f3c73a92a2d430c6cbea06e79ebad19a.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_b4ec85b136b49ead414b7f9330771dcb_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_f3c73a92a2d430c6cbea06e79ebad19a_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_b4ec85b136b49ead414b7f9330771dcb = L.geoJson(null, {\n", - " onEachFeature: geo_json_b4ec85b136b49ead414b7f9330771dcb_onEachFeature,\n", + " var geo_json_f3c73a92a2d430c6cbea06e79ebad19a = L.geoJson(null, {\n", + " onEachFeature: geo_json_f3c73a92a2d430c6cbea06e79ebad19a_onEachFeature,\n", " \n", - " style: geo_json_b4ec85b136b49ead414b7f9330771dcb_styler,\n", - " pointToLayer: geo_json_b4ec85b136b49ead414b7f9330771dcb_pointToLayer,\n", + " style: geo_json_f3c73a92a2d430c6cbea06e79ebad19a_styler,\n", + " pointToLayer: geo_json_f3c73a92a2d430c6cbea06e79ebad19a_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_b4ec85b136b49ead414b7f9330771dcb_add (data) {\n", - " geo_json_b4ec85b136b49ead414b7f9330771dcb\n", + " function geo_json_f3c73a92a2d430c6cbea06e79ebad19a_add (data) {\n", + " geo_json_f3c73a92a2d430c6cbea06e79ebad19a\n", " .addData(data);\n", " }\n", - " geo_json_b4ec85b136b49ead414b7f9330771dcb_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "blue", "angles": "[40.212341316065846, 90.03279687624627]", "node_end": 2, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "blue", "angles": "[36.134980718680964]", "node_end": 9, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "blue", "angles": "[29.396028363390087]", "node_end": 3, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "blue", "angles": "[89.87471285219925, 89.7526780497804]", "node_end": 1, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "blue", "angles": "[89.54717385542591, 90.15620941167606]", "node_end": 4, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "blue", "angles": "[65.68797883939557]", "node_end": 8, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "blue", "angles": "[89.54706268184327, 69.13355147175304]", "node_end": 3, "node_start": 1, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "blue", "angles": "[13.267980201287713]", "node_end": 6, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "blue", "angles": "[53.8322224050728]", "node_end": 9, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "blue", "angles": "[34.25143801488167]", "node_end": 3, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "blue", "angles": "[13.478468651053788, 108.36660375349902, 55.84526596075068, 61.55252328557667]", "node_end": 6, "node_start": 2, "number_connections": 4}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "blue", "angles": "[91.91633958004554]", "node_end": 9, "node_start": 3, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "blue", "angles": "[88.7883380111752, 90.24802010033585]", "node_end": 4, "node_start": 3, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "blue", "angles": "[48.7782715761349]", "node_end": 7, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "blue", "angles": "[87.60977577529626]", "node_end": 5, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "blue", "angles": "[86.35771713184363, 89.6026063905527]", "node_end": 6, "node_start": 4, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "blue", "angles": "[87.78317654724924]", "node_end": 8, "node_start": 4, "number_connections": 1}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_f3c73a92a2d430c6cbea06e79ebad19a_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "blue", "angles": "[np.float64(62.30218235695145), np.float64(63.647466378271766)]", "node_end": 2, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "blue", "angles": "[np.float64(36.134980718680936)]", "node_end": 9, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "blue", "angles": "[np.float64(27.958640647426915)]", "node_end": 3, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "blue", "angles": "[np.float64(88.89258170115896), np.float64(89.75267804978043)]", "node_end": 1, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "blue", "angles": "[np.float64(63.27660557215604), np.float64(63.14942148406139)]", "node_end": 4, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "blue", "angles": "[np.float64(61.612799132873675)]", "node_end": 8, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "blue", "angles": "[np.float64(83.02522839160721), np.float64(89.58581817377714)]", "node_end": 3, "node_start": 1, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.2861856598184)]", "node_end": 6, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "blue", "angles": "[np.float64(53.8322224050728)]", "node_end": 9, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "blue", "angles": "[np.float64(35.68882573084483)]", "node_end": 3, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "blue", "angles": "[np.float64(88.60150429340734), np.float64(59.79419820769667), np.float64(47.16443370903166), np.float64(59.79419820769667)]", "node_end": 6, "node_start": 2, "number_connections": 4}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.52104813591764)]", "node_end": 9, "node_start": 3, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "blue", "angles": "[np.float64(74.19659813624955), np.float64(71.90468497465247)]", "node_end": 4, "node_start": 3, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "blue", "angles": "[np.float64(78.26155769686821)]", "node_end": 7, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "blue", "angles": "[np.float64(87.60977577529626)]", "node_end": 5, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "blue", "angles": "[np.float64(76.65791615429069), np.float64(89.34605771289704)]", "node_end": 6, "node_start": 4, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "blue", "angles": "[np.float64(87.76902206019881)]", "node_end": 8, "node_start": 4, "number_connections": 1}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_b4ec85b136b49ead414b7f9330771dcb.bindTooltip(\n", + " geo_json_f3c73a92a2d430c6cbea06e79ebad19a.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -849,40 +858,40 @@ "});\n", " \n", " \n", - " geo_json_b4ec85b136b49ead414b7f9330771dcb.addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " geo_json_f3c73a92a2d430c6cbea06e79ebad19a.addTo(map_3f909620e838580f27f572a1d038b48d);\n", " \n", " \n", - " var layer_control_15e3bca38cae8c2d44ea44f779d11987_layers = {\n", + " var layer_control_07b3220eb5854db7a99acbf874b52fdd_layers = {\n", " base_layers : {\n", - " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_e307cfd7926aabb694ab68e0f7887cbf,\n", + " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_f5905899af281f8109c1a377e3604417,\n", " },\n", " overlays : {\n", - " "strokes" : geo_json_39a0e618cb8207c62b0b8473869f6bf3,\n", - " "points_primal" : geo_json_bae06981bface585152ad88fc1a65341,\n", - " "lines_primal" : geo_json_c2b54c20a83aabe517060cb36164c1d5,\n", - " "points_stroke" : geo_json_e1ffbcac9a4daf0aeae1ac07f11ba10d,\n", - " "lines_stroke" : geo_json_b4ec85b136b49ead414b7f9330771dcb,\n", + " "strokes" : geo_json_0c2b53ed2c454e26c2a746abec90c455,\n", + " "points_primal" : geo_json_223be950705750efd2fb109cc6a4119b,\n", + " "lines_primal" : geo_json_56d94515e567fb4a3c72716557b8d795,\n", + " "points_stroke" : geo_json_b4699a2640fa07c6cb89f04625ff435a,\n", + " "lines_stroke" : geo_json_f3c73a92a2d430c6cbea06e79ebad19a,\n", " },\n", " };\n", - " let layer_control_15e3bca38cae8c2d44ea44f779d11987 = L.control.layers(\n", - " layer_control_15e3bca38cae8c2d44ea44f779d11987_layers.base_layers,\n", - " layer_control_15e3bca38cae8c2d44ea44f779d11987_layers.overlays,\n", + " let layer_control_07b3220eb5854db7a99acbf874b52fdd = L.control.layers(\n", + " layer_control_07b3220eb5854db7a99acbf874b52fdd_layers.base_layers,\n", + " layer_control_07b3220eb5854db7a99acbf874b52fdd_layers.overlays,\n", " {\n", " "position": "topright",\n", " "collapsed": true,\n", " "autoZIndex": true,\n", "}\n", - " ).addTo(map_ad3194be1d4b4ed379b89a6a54007ae8);\n", + " ).addTo(map_3f909620e838580f27f572a1d038b48d);\n", "\n", " \n", "</script>\n", "</html>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen>" ], "text/plain": [ - "" + "" ] }, - "execution_count": 222, + "execution_count": 68, "metadata": {}, "output_type": "execute_result" } From b2b7bdcc8ce69d432dbee85c068aaab78011f894 Mon Sep 17 00:00:00 2001 From: anvy Date: Wed, 14 May 2025 13:41:17 +0200 Subject: [PATCH 09/27] update anvy nb (final angle comp) --- momepy/strokegraph.ipynb | 2326 +++----------------------------------- 1 file changed, 163 insertions(+), 2163 deletions(-) diff --git a/momepy/strokegraph.ipynb b/momepy/strokegraph.ipynb index 860a9375..64c1bb73 100644 --- a/momepy/strokegraph.ipynb +++ b/momepy/strokegraph.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -23,14 +23,13 @@ "from shapely import LineString\n", "import numpy as np\n", "import math\n", - "import collections\n", - "import warnings\n", + "import pickle\n", "from collections import Counter" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -60,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -90,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -101,103 +100,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
geometrymm_lennode_startnode_endmy_index
0LINESTRING (1603585.64 6464428.774, 1603413.20...264.103950010
1LINESTRING (1603268.502 6464060.781, 1603296.8...99.751190231
2LINESTRING (1603607.303 6464181.853, 1603592.8...199.746503142
3LINESTRING (1603363.558 6464031.885, 1603376.5...203.014090133
4LINESTRING (1603413.206 6464228.73, 1603274.45...198.482724154
\n", - "
" - ], - "text/plain": [ - " geometry mm_len node_start \\\n", - "0 LINESTRING (1603585.64 6464428.774, 1603413.20... 264.103950 0 \n", - "1 LINESTRING (1603268.502 6464060.781, 1603296.8... 99.751190 2 \n", - "2 LINESTRING (1603607.303 6464181.853, 1603592.8... 199.746503 1 \n", - "3 LINESTRING (1603363.558 6464031.885, 1603376.5... 203.014090 1 \n", - "4 LINESTRING (1603413.206 6464228.73, 1603274.45... 198.482724 1 \n", - "\n", - " node_end my_index \n", - "0 1 0 \n", - "1 3 1 \n", - "2 4 2 \n", - "3 3 3 \n", - "4 5 4 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# remove false nodes\n", "streets = momepy.remove_false_nodes(streets)\n", @@ -229,20 +134,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(1,1, figsize=(8,8))\n", "lines.plot(ax=ax, column=\"my_index\", cmap=\"tab20\", lw=3, legend=True, zorder=0)\n", @@ -254,106 +148,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
n_segmentsgeometryrep_pointstroke_id
stroke_group
08LINESTRING (1603278.899 6463669.186, 1603283.7...POINT (1603374.663 6464077.898)0
119LINESTRING (1603077.5 6464475.323, 1603085.515...POINT (1603237.049 6464133.622)1
217LINESTRING (1603537.194 6464558.112, 1603557.6...POINT (1603707.107 6464238.854)2
35LINESTRING (1603413.206 6464228.73, 1603274.45...POINT (1603149.929 6464130.225)3
414LINESTRING (1602970.377 6464268.058, 1602974.0...POINT (1603264.658 6463848.976)4
\n", - "
" - ], - "text/plain": [ - " n_segments geometry \\\n", - "stroke_group \n", - "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", - "1 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", - "2 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", - "3 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", - "4 14 LINESTRING (1602970.377 6464268.058, 1602974.0... \n", - "\n", - " rep_point stroke_id \n", - "stroke_group \n", - "0 POINT (1603374.663 6464077.898) 0 \n", - "1 POINT (1603237.049 6464133.622) 1 \n", - "2 POINT (1603707.107 6464238.854) 2 \n", - "3 POINT (1603149.929 6464130.225) 3 \n", - "4 POINT (1603264.658 6463848.976) 4 " - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# make coins\n", "coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", @@ -371,121 +168,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
n_segmentsgeometryrep_pointstroke_idedge_indeces
stroke_group
08LINESTRING (1603278.899 6463669.186, 1603283.7...POINT (1603374.663 6464077.898)0[0, 3, 15, 27]
119LINESTRING (1603077.5 6464475.323, 1603085.515...POINT (1603237.049 6464133.622)1[1, 12, 14, 25]
217LINESTRING (1603537.194 6464558.112, 1603557.6...POINT (1603707.107 6464238.854)2[2, 11, 28, 30]
35LINESTRING (1603413.206 6464228.73, 1603274.45...POINT (1603149.929 6464130.225)3[4, 5, 6]
414LINESTRING (1602970.377 6464268.058, 1602974.0...POINT (1603264.658 6463848.976)4[7, 8, 9, 13, 21, 22, 24]
\n", - "
" - ], - "text/plain": [ - " n_segments geometry \\\n", - "stroke_group \n", - "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", - "1 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", - "2 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", - "3 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", - "4 14 LINESTRING (1602970.377 6464268.058, 1602974.0... \n", - "\n", - " rep_point stroke_id \\\n", - "stroke_group \n", - "0 POINT (1603374.663 6464077.898) 0 \n", - "1 POINT (1603237.049 6464133.622) 1 \n", - "2 POINT (1603707.107 6464238.854) 2 \n", - "3 POINT (1603149.929 6464130.225) 3 \n", - "4 POINT (1603264.658 6463848.976) 4 \n", - "\n", - " edge_indeces \n", - "stroke_group \n", - "0 [0, 3, 15, 27] \n", - "1 [1, 12, 14, 25] \n", - "2 [2, 11, 28, 30] \n", - "3 [4, 5, 6] \n", - "4 [7, 8, 9, 13, 21, 22, 24] " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# add edge_ids column (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", "stroke_gdf[\"edge_indeces\"] = stroke_gdf.stroke_id.apply(\n", @@ -497,20 +182,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtUAAAMWCAYAAAA+uHrFAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3xUZdYH8N+dmt57DwRSSWhJCBB6kSaKiOCKuq5usYG+6+6+W1xXd3W7oL7qusWCq4KIiqBSBQIEUkhCEpIQ0nvvZSYzc98/AhOeSa935s75fj5+3Htyb+bIhuTkmfOch+N5ngchhBBCCCFkzCRCJ0AIIYQQQoipo6KaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGSTeQn02q16OnpmchPSciIyOVySKVSodMghBBCiJmakKKa53lUV1ejubl5Ij4dIWPi4OAADw8PcBwndCqEEEIIMTMTUlTfKqjd3NxgZWVFRQ2ZUjzPo7OzE7W1tQAAT09PgTMihBBCiLkZd1Gt1Wr1BbWzs/NE5ETIqFlaWgIAamtr4ebmRq0ghBBCCJlS496oeKuH2srKatzJEDIet74Gqa+fEEIIIVNtwqZ/UMsHERp9DRJCCCFEKDRSjxBCCCGEkHGioloAAQEB2LNnj9BpDOi9996Dg4OD0GkQQgghhJiUSS+qq6ursWvXLgQFBcHCwgLu7u5YvHgx3n77bXR2dk72y08YYy6EjTk3AFi2bBl2797NXHMcB47joFQq4e3tjU2bNuHQoUPCJUkIIYQQMg6TWlQXFhZizpw5OH78OF5++WWkpaXh5MmTeOaZZ/DVV1/h5MmTk/nyw+J5HhqNRtAcpopWq4VOpxM6Db3HHnsMVVVVuHHjBj777DOEhYVh+/bt+OEPfyh0aoQQQgghozapRfXjjz8OmUyGlJQUbNu2DaGhoZg1axbuueceHD16FJs2bdLf29LSgh/+8Idwc3ODnZ0dVqxYgYyMDP3HX3jhBcyePRv79u1DQEAA7O3tsX37drS1tenv4Xkef/7znzFt2jRYWloiKioKBw8e1H/8zJkz4DgOx44dw/z586FUKpGQkICCggJs3rwZ7u7usLGxQXR0NFPwL1u2DCUlJXjmmWf0K6y3XLx4EUuWLIGlpSV8fX3x9NNPo6OjQ//x2tpabNq0CZaWlggMDMR///vfMf1ZvvDCC/Dz84NSqYSXlxeefvrpIXO71cZx5MgRhIWFQalUoqSkBE1NTXjwwQfh6OgIKysrrFu3Dvn5+YO+bkNDA2JiYnDnnXeiu7t72D/jkbKysoKHhwd8fX2xYMEC/OlPf8I//vEP/POf/9T/2avVajz55JPw9PSEhYUFAgIC8Morr4zhT48QQgghZHJNWlHd0NCA48eP44knnoC1tfWA99wqAHmex4YNG1BdXY2vv/4aqampmDt3LlauXInGxkb9/QUFBfjiiy9w5MgRHDlyBGfPnsUf//hH/cd//etf491338Vbb72F7OxsPPPMM3jggQdw9uxZ5nV/9rOf4ZVXXkFOTg4iIyPR3t6O9evX4+TJk0hLS8PatWuxadMmlJaWAgAOHToEHx8fvPjii6iqqkJVVRUAIDMzE2vXrsWWLVtw9epV7N+/H+fPn8eTTz6pf62HH34YxcXFOH36NA4ePIg333xTf0jJ7fcsW7Zs0D/LgwcP4tVXX8U//vEP5Ofn44svvsCsWbOGzA0AOjs78corr+Bf//oXsrOz4ebmhocffhgpKSk4fPgwEhMTwfM81q9fP+AYuvLycsTHxyMkJASHDh2ChYXFiP+Mx+Khhx6Co6Ojvg3ktddew+HDh3HgwAHk5eXhww8/REBAwLhfhxBCCCFkwvHj1NXVxV+7do3v6upi4pcuXeIB8IcOHWLizs7OvLW1NW9tbc3/7Gc/43me50+dOsXb2dnx3d3dzL3Tp0/n//GPf/A8z/O//e1veSsrK761tVX/8eeee46PjY3leZ7n29vbeQsLC/7ixYvM5/jBD37A79ixg+d5nv/uu+94APwXX3wx7H9XWFgY//rrr+uv/f39+VdffZW5Z+fOnfwPf/hDJpaQkMBLJBK+q6uLz8vL4wHwly5d0n88JyeHB8B8rl/84hf8zp07B83lb3/7Gz9z5kxerVYP+PGBcnv33Xd5AHx6ero+dv36dR4Af+HCBX2svr6et7S05A8cOKB/zt7ens/Ly+P9/Pz4p556itfpdDzPj+zPeCBLly7ld+3aNej17WJjY/l169bxPM/zTz31FL9ixQr96w9nsK9FQgghhJDJNiHHlA/FcHZwUlISdDodvve970GlUgEAUlNT0d7e3u9Exq6uLhQUFOivAwICYGtrq7/29PTUr/peu3YN3d3dWL16NfM51Go15syZw8Tmz5/PXHd0dOB3v/sdjhw5gsrKSmg0GnR1delXqgeTmpqKGzduMC0dPM9Dp9OhqKgI169fh0wmY14vJCSk33SN4Voa7r33XuzZswfTpk3DHXfcgfXr12PTpk2QyYb+v0+hUCAyMlJ/nZOTA5lMhtjYWH3M2dkZwcHByMnJ0ce6urqwePFi7NixA3v37tXHR/NnPFY8z+u/Zh5++GGsXr0awcHBuOOOO7Bx40asWbNmQl6HEEIIIWQiTVpRHRQUBI7jkJuby8SnTZsGoO9YaQDQ6XTw9PTEmTNn+n2e2wtQuVzOfIzjOP3mu1v/Pnr0KLy9vZn7lEolc23YjvLcc8/h2LFj+Otf/4qgoCBYWlpi69atUKvVQ/436nQ6/OhHP9L3N9/Oz88PeXl5+jzHw9fXF3l5eThx4gROnjyJxx9/HH/5y19w9uzZfn8mt7O0tGRem+f5Ae+7vZAFev+8Vq1ahaNHj+K5556Dj48PgNH9GY+FVqtFfn4+oqOjAQBz585FUVERvvnmG5w8eRLbtm3DqlWrxtTDTQghhBAymSatqHZ2dsbq1avxxhtv4Kmnnhq0rxroLZ6qq6shk8nG3DN7azNeaWkpli5dOqpnExIS8PDDD+Puu+8GALS3t6O4uJi5R6FQQKvV9ss7OzsbQUFBA37e0NBQaDQapKSkICYmBgCQl5eH5ubmUeUH9BbId955J+6880488cQTCAkJQWZmJubOnTtgbgMJCwuDRqPB5cuXsXDhQgC9ve/Xr19HaGio/j6JRIJ9+/bh/vvvx4oVK3DmzBl4eXmN6894JN5//300NTXhnnvu0cfs7Oxw33334b777sPWrVtxxx13oLGxEU5OThP++oQQQgghYzWp7R9vvvkmFi1ahPnz5+OFF15AZGQkJBIJkpOTkZubi3nz5gEAVq1ahbi4ONx1113405/+hODgYFRWVuLrr7/GXXfd1a9dYyC2trb46U9/imeeeQY6nQ6LFy9Ga2srLl68CBsbGzz00EODPhsUFIRDhw5h06ZN4DgOv/nNb/qNnwsICMC5c+ewfft2KJVKuLi44Oc//zkWLFiAJ554Ao899hisra2Rk5ODEydO4PXXX9e3LTz22GN45513IJPJsHv3bmaVHgD+93//FxUVFfjggw8GzO+9996DVqtFbGwsrKyssG/fPlhaWsLf33/Q3AYyY8YMbN68GY899hj+8Y9/wNbWFr/4xS/g7e2NzZs3M/dKpVL897//xY4dO/SFtYeHx5j/jA11dnaiuroaGo0GFRUVOHToEF599VX85Cc/wfLlywEAr776Kjw9PTF79mxIJBJ8+umn8PDwoMNpCCGEEGJ8xtuUPdzmsMrKSv7JJ5/kAwMDeblcztvY2PAxMTH8X/7yF76jo0N/X2trK//UU0/xXl5evFwu5319ffnvfe97fGlpKc/zvRsVo6KimM/96quv8v7+/vprnU7H7927lw8ODublcjnv6urKr127lj979izP830bFZuampjPU1RUxC9fvpy3tLTkfX19+TfeeKPfZrrExEQ+MjKSVyqV/O1/bElJSfzq1at5Gxsb3tramo+MjOT/8Ic/6D9eVVXFb9iwgVcqlbyfnx//wQcf9NtY+NBDD/FLly4d9M/4888/52NjY3k7Ozve2tqaX7BgAX/y5Mkhc7u14dBQY2Mjv3PnTt7e3p63tLTk165dy1+/fl3/ccPnenp6+C1btvChoaF8TU3NsH/GAxlooyIAHgCvUCh4T09PfuPGjf02tb7zzjv87NmzeWtra97Ozo5fuXIlf+XKlUFfhzYqEkIIIUQoHM8P0mg7Qt3d3SgqKkJgYCAsLCwmoMwnZGzoa5EQQgghQpn0Y8oJIYQQQggROyqqCSGEEEIIGScqqgkhhBBCCBknKqoJIYQQQggZJyqqCSGEEEIIGadJP6acEEIIIYSMjVarRUJCAqqqquDp6Yn4+HhIpVKh0yIDoKKaEEIIIcQIHTp0CLt27UJ5ebk+5uPjg71792LLli0CZkYGQu0fhBBCCCFG5tChQ9i6dStTUANARUUFtm7dikOHDgmUGRkMFdWEEEIIIUZEq9Vi165dGOh8vlux3bt3Q6vVTnVqZAhUVIvMm2++qT9RcN68eUhISBA6JUIIIYSMQkJCQr8V6tvxPI+ysjL6GW9kqKgWkf3792P37t341a9+hbS0NMTHx2PdunUoLS0VOjVCCCGEjFBVVdWE3kemBhXVIvL3v/8dP/jBD/Doo48iNDQUe/bsga+vL9566y2hUyOEEELICHl6ek7ofWRq0PSPEWpt7pzS17NzsBrV/Wq1GqmpqfjFL37BxNesWYOLFy9OZGqEEEIImUTx8fHw8fFBRUU5BmirBsdx8PHxQXx8/NQnRwZFRfUIPX3fP6f09d47tmtU99fX10Or1cLd3Z2Ju7u7o7q6eiJTI4QQQsgkkkql2Lt3L7ZuvQccgNvrao7jAAB79uyhedVGhto/RObWX7ZbeJ7vFyOEEEKIcduyZQv2/fkpeNiycR8fHxw8eJDmVBshWqkWCRcXF0il0n6r0rW1tf1WrwkhhBBi/DYvjcTCp2RIKuVR2w54Tw/H5j9doRVqI0Ur1SKhUCgwb948nDhxgomfOHECCxcuFCgrQgghhIwVr+mGVMIhLkCCzRESLAr3oILaiNFK9Qi9tv8xoVMY1rPPPoudO3di/vz5iIuLwzvvvIPS0lL8+Mc/Fjo1QgghhIwS39PFXHMyC4EyISNBRfUIjXYahxDuu+8+NDQ04MUXX0RVVRUiIiLw9ddfw9/fX+jUCCGEEDJKvKabueZkSoEyISNBRbXIPP7443j88ceFToMQQggh49S/qKaVamNGPdWEEEIIIUaI16iYayqqjRsV1YQQQgghRohWqk0LFdWEEEIIIUaIimrTQkU1IYQQQogRoo2KpoWKakIIIYQQI6RpLGSuJRb2AmVCRoKKakIIIYQQI6NTd0Jdlc7EFN7zhEmGjAiN1COEmD2tVouEhARUVVXB09MT8fHxdGoZIURQ6spUQKfpC3ASKLyjhUuIDIuKakKIWTt06BB27dqF8vJyfczHxwd79+7Fli1bBMyMEGLOVKWJzLXcIxISpY1A2ZCRoPYPQojZOnToELZu3coU1ABQUVGBrVu34tChQwJlRggxd+qyS8y10neBQJmQkaKimhBilrRaLXbt2gWe5/t97FZs9+7d0Gq1U50aIcTM8TwPValBUe1HRbWxo6JaRM6dO4dNmzbBy8sLHMfhiy++EDolQoxWQkJCvxXq2/E8j7KyMiQkJExhVoQQAmgab0DXWc/ElH5xAmVDRoqKahHp6OhAVFQU3njjDaFTIcToVVVVTeh9hBAyUQz7qSU2HpA6BAiTDBkx2qgoIuvWrcO6deuEToMQk+Dp6Tmh9xFCyERRl11mrpW+seA4TqBsyEhRUT1CDW1dU/p6zraWU/p6hJib+Ph4+Pj4oKKiYsC+ao7j4OPjg/j4eAGyI4SYM8OVamr9MA1UVI/QnJ+/N6WvV/rmT6b09QgxN1KpFHv37sXWrVv7fYxD74rQnj17aF41IWRK6bpb0FObzcSoqDYN1FNNCDFbW7ZswcGDB2FrYcvEPdw9cPDgQZpTTQiZcqryJOD2d8+kCig85wiXEBkxWqkmhJi1LVu24PLKJBSU30CHugPWCmu88t4rmDF7htCpEULMkNpglJ7Caw44uYVA2ZDRoKKaEEJ0gI+jr/5SJpcLmAwhxJyp+h36Qq0fpoKK6hFK+9PDQqcwrPb2dty4cUN/XVRUhPT0dDg5OcHPz0/AzAgxbjqdjrmWSGiXPSFk6vE6LVSGkz/o0BeTQUX1CJnCNI6UlBQsX75cf/3ss88CAB566CG89957AmVFiPHTaQ2KailtNyGETL2e2mvgVa1MTEHHk5sMKqpFZNmyZQOOBiOEDK3/SjUV1YSQqWc4n1rq4A+ZnZdA2ZDRop8chBCzxvM8eB37yyitVBNChKAqM5hPTavUJoV+chBCzJrhKjVARTUhRBh06Itpo58chBCzxmv7t0xRUU0ImWrajjpoGm4wMSqqTQv95CCEmDWtVtsvRj3VhJCpZjj1g5NbQe4+S6BsyFjQTw5CiFkz7KcGaKWaEDL11AatHwqfaHBSmidhSugnByHErNFKNSHEGPQ/9IU2KZoa+hWIEGLWaKWaiIFWq0VCQgKqqqrg6emJ+Ph4SKVSodMiI8Rre6CuSGFi1E9teqioJoSYNVqpJqbu0KFD2LVrF8rLy/UxHx8f7N27F1u2bBEwMzJS6uqr4Hu6mJjCN1agbMhY0U8OQohZo5VqYsoOHTqErVu3MgU1AFRUVGDr1q04dOiQQJmR0TDsp5a5zITUylmgbMhY0U8OQohZ02ppTjUxTVqtFrt27RrwJN1bsd27dw/4bgwxLjSfWhzoJ4dIvPLKK4iOjoatrS3c3Nxw1113IS8vT+i0CDF6PBXVxEQlJCT0W6G+Hc/zKCsrQ0JCwhRmRcai/yZFKqpNEf3kEImzZ8/iiSeewKVLl3DixAloNBqsWbMGHR0dQqdGiFEbaKWaAydAJoSMTlVV1YTeR4ShaSmHtqWMiVE/tWmijYoj1NTdPaWv52hhMar7v/32W+b63XffhZubG1JTU7FkyZKJTI0QUbG06f937UbGDYREhwiQDSEj5+npOaH3EWGoDVapOQt7yF1DBcqGjAcV1SO0/vOp3eyRuOP+cT3f0tICAHBycpqIdAgRLTsnO/jM8EF5ft/b6MnHU6ioJkYvPj4ePj4+qKioGLCvmuM4+Pj4ID4+XoDsyEipSvvPp+ZoApFJov/XRIjneTz77LNYvHgxIiIihE6HEKMXvWY+c3014Sq6O6f23SlCRksqlWLv3r29F9zALUt79uyhedVGjg59EQ8qqkXoySefxNWrV/Hxxx8LnQohJmHuyrnM5sQeVQ8yzmYImBEhI7NlyxYcPHgQXl5eTFzh7ITde/bQnGojp+vpgroqjYkp/aioNlXU/iEyTz31FA4fPoxz587Bx8dH6HQIMQm2jrYIjQ1F9sVsfSz5eApi19FmIWL8tmzZgs2bN+ORt97Exbw8yB0cYBcSghpHR/A8D26QVWwiPHXlFUDb0xfgJFB4RwuXEBkXKqpH6Ou7jfu3fZ7n8dRTT+Hzzz/HmTNnEBgYKHRKhJiU6DXzmaL6RvoNNFY3wsmD9iUQ4yeVSvHU1ntx/bvT+lhhSwuuNTYg3NlFwMzIUAwPfZG7R0BiYSdQNmS8qKgeodFO45hqTzzxBD766CN8+eWXsLW1RXV1NQDA3t4elpaWAmdHiPGLiIuApY0lutr7jgpOOZGCNTvXCJgVISM3190dXtbWqLxtlOqRwkIqqo1Yv35qOvTFpFFPtUi89dZbaGlpwbJly+Dp6an/Z//+/UKnRohJkClkmLNiDhNLPp4y4FQFQoyRhOOwYdo0JnaipATdGo1AGZGh8Dw/wOQPajkzZVRUiwTP8wP+8/DDDwudGiEmI3oN28tYV16HkpwSgbIhZPQ2BE5jji7q6OnB6bJSwfIhg9M0FULXUcvEFLRSbdKoqCaEkJsCwvzh6uPKxJKOJQuUDSGj525tjViDw16OFBYKlA0ZimE/tcTaDTLHaYPcTUwBFdWEEHITx3H9ZlannU6DRk1vnxPTsXHadOY6rbYWZW1tAmVDBqMqu8xcK31jaVKLiaOimhBCbjNvNVtUd7V3ITsxe5C7CTE+8d7esFcomdiRwgKBsiGDURmsVNMmRdNHRTUhhNzG2cMJQbODmFjScWoBIaZDIZXijsAAJvZ1URE0Op0wCZF+dN2t6KnJYmLUT236qKgmhBADhi0gOZdz0NZEb58T07HJoAWkvqsLl6uqBMqGGFJXJAP8bb/kSOVQeM0VLiEyIaioJoQQA1FLoiBXyvXXOq0OV06nDfEEIcZluoMDwpydmdhX1AJiNAxH6Sk8Z0MipzMlTB0V1YQQYsDC2gKR8ZFMLJmmgBATs9FgZvX5igo0dnUNcjeZSv0OffGl1g8xoKKaEEIGYNgCUp5fjqoievucmI7Vfv5QSqX6ay3P45viYuESIgAAXqcb4CTFBQJlQyYSFdWEEDKAmXNnwt7FnonRajUxJTYKBVb4+jGxI4UFdEqowHrqcsB3tzAxhS8V1WJARTUhhAxAIpVg3qp5TCzlZCp0WpqgQEzHpunshsXi1lZkNdQLlA0BALXBfGqpvS9k9j4CZUMmEhXVIvHWW28hMjISdnZ2sLOzQ1xcHL755huh0yLEpBm2gLQ2tOL6lesCZUPI6M12dYWPjQ0T+6qATlgUkqrMYD41rVKLBhXVIuHj44M//vGPSElJQUpKClasWIHNmzcjO5sOrSBkrDwDPeEzg11BohYQYko4jut3wuKp0hJ09vQIlBGhQ1/ESyZ0AqaivqNl+JsmkIu1/fA33WbTpk3M9R/+8Ae89dZbuHTpEsLDwycyNULMSvTaaJTnl+uvr57PRHdHNyysLQTMipCRWx8YiHcyr0J3s5e6U6PB6bLSfsU2mXzazgZo6tl3u+jQF/GgonqEgvY+OqWv1/zLT8f8rFarxaeffoqOjg7ExdFfVkLGY+6KOfjyrS/1vdQ9qh5knMtA7LpYgTMjZGRcrawQ5+mJC5WV+thXBYVUVAvAsJ+ak1tC4RE5yN3E1FD7h4hkZmbCxsYGSqUSP/7xj/H5558jLCxM6LQIMWm2jrYIjQ1lYknUAkJMjGEBfbW+DsWtU/sOLOnf+qHwng9OKh/kbmJqqKgWkeDgYKSnp+PSpUv4yU9+goceegjXrl0TOi1CTF7MmmjmuiCjAA3VjQJlQ8joLfb2hqOSbVk6QhsWp1z/Q19ok6KYUFEtIgqFAkFBQZg/fz5eeeUVREVFYe/evUKnRYjJC48Lh6UNe4Rw6okUgbIhZPRkEgnWBQYysW+Ki6DR0YjIqcJrNVCXs+9yUT+1uFBP9Qjd2PUvoVMYNZ7noVKphE6DEJMnU8gwZ8UcXDx8UR9LPp6C1Q+sBsdxAmZGyMhtmjYNH+Xm6K8bu7txsbISS3xoRvJU6KnJBN/TycSUvrQ3Q0yoqB6h0U7jmGq//OUvsW7dOvj6+qKtrQ2ffPIJzpw5g2+//Vbo1AgRhZi10UxRXVdeh+JrJQgMDxAuKUJGIcDeHhEuLsiq7zv85avCAiqqp4hhP7XMOQhSa1eBsiGTgdo/RKKmpgY7d+5EcHAwVq5cicuXL+Pbb7/F6tWrhU6NEFHwD/WHqw/7AzD5OG1YJKZlk8GGxcTKStR3dQmUjXmh+dTiR0W1SPz73/9GcXExVCoVamtrcfLkSSqoCZlAHMchei27YTHtdBp61HSIBjEdK/38YCnre5Nay/P4pqhIwIzMR/9NilRUiw0V1YQQMkLzV81jrrvau5CdSKeWEtNhLZdjpZ8fEztSWAD+5sEwZHJoWiuhbS5hYgrqpxYdKqoJIWSEnDycEDQ7iIklH6cpIMS0GM6sLm1rQ0ZdnUDZmAe1wSo1p7SD3I3OkRAbKqoJIWQUDFtAci7noK2pTaBsCBm9SBcX+NnaMbGvCgsEysY8qEoNWz9iwUmkAmVDJgsV1YQQMgpRSyIhV/adgKbT6nDl1BUBMyJkdDiOw6bp05jY6dJSdPTQ/oDJoioz2KRIh76IEhXVhBAyChZWFoiMj2Ri1AJCTM36gEBIb5ux3q3V4mRJyRBPkLHie7qhrkxjYgo/KqrFiIpqQggZpRiDFpDy/HJUFVUJlA0ho+dkaYlFXt5MjFpAJoe6Kg3QqvsCHAelT4xwCZFJQ0U1IYSM0ow5M2Dvwh4IlXyMZlYT07LRoAUku6EBhS3NwiQjYobzqeVu4ZBYGPeBcmRsqKgmhJBRkkglmGcwXi/lZCp0Wp1AGREyenGeXnC2sGBiRwoKBcpGvPrNp6ZDX0SLimpCCBmD6DXzmevWhlbkpV4XKBtCRk8mkWB9ILta/U1xEXq0WoEyEh+e5/tN/qD51OJFRTUhhIyBZ6AnfGf6MLEUOracmJiN09iiulmlwvnKCoGyER9tczF07dVMjFaqxYuKapF65ZVXwHEcdu/eLXQqhIjW/DXshsWr5zPR3dEtUDaEjJ6fnR1mu7oysSOF1AIyUQz7qSVWLpA5BQ1yNzF1VFSLUHJyMt555x1ERkYOfzMhZMzmrZwLibTv22iPqgfpZzMEzIiQ0TM8YfFSVRVqOzsFykZcVGWXmWul3wJwt40yJOJCRfUItauap/SfMefZ3o7vfe97+Oc//wlHR8eJ+wMghPRj42CDsFj2qOFkagEhJmaFnx+sZDL9tY7n8XURrVZPBMOVagUd+iJqsuFvIQDwwjc7pvT1/nrXN2N67oknnsCGDRuwatUq/P73v5/grAghhqLXzEfWxSz9dUFGARqqGuDs6SxgVoSMnKVMhlX+/jhc0Den+lhxMR4OjxAwK9OnU7Wjp/oqE6N+anGjlWoR+eSTT3DlyhW88sorQqdCiNkIjwuHla0VE0s5kSpQNoSMjeEUkOLWVjR10/6A8VBXJAP8bWM2JTIovOYN/gAxeVRUi0RZWRl27dqFDz/8EBYGc0cJIZNHppBhzvI5TCz5eDJ4nhcoI0JGL9zZGRZSKRPLrK8XKBtx6DdKz3M2JAqrQe4mYkBFtUikpqaitrYW8+bNg0wmg0wmw9mzZ/Haa69BJpNBS3NHCZk00WvZmdX1FfUozi4WJhlCxkAmkSDcxYWJZdTVCZSNOBge+kL91OJHPdUj9MK6j4VOYUgrV65EZmYmE/v+97+PkJAQ/PznP4fUYAWCEDJx/EP94errirqyviIk+XgyAiMCBcyKkNGJdHFFak2N/vpqPRXVY8XzPNTl7KZlJR36InpUVI+QjdJB6BSGZGtri4gIdlOJtbU1nJ2d+8UJIROL4zhEr4nG1//+Wh9L+y4ddz95N+QKuYCZETJyka7sSnVeYyNUWi2UtCgzatrWcug62fYZpU/0IHcTsaD2D0IImQDzV7EbkLrau5B9MVugbAgZvVkurpDcNkO5R6dDbmODgBmZLnVlGnPNWdhD6kjvXIkdFdUidubMGezZs0foNAgxC04eTpgxhz0pjWZWE1NiLZdjur09E6O+6rExLKoVnnPo0BczQEU1IYRMEMNjy3Mu56KtqU2gbAgZvVkGR5ZfpaJ6TNRVhkX1bGESIVOKimpiknieR1tbGxoaGtDW1kbjy4hRiFoSCYWFQn+t0+mQeuqKgBkRMjpRLmxRnVZbiy6NRqBsTFdPZTpzrfCaLUgeZGpRUU1MTlNTEzIzM5GXl4eioiLk5eUhMzMTLS0tQqdGzJyFlQUi42cxsRRqASEmZK67O9NX3anR4FRpiYAZmR5tew20bZVMTOE5Z5C7iZhQUU1MSlNTEwoKCqBWq5m4Wq1GWVkZOjs7BcqMkF7RBi0g5fkVqCysHORuQoyLi6UlFnh6MrEvbzu+nAxPXZXOXHNyK8hcZgqTDJlSVFQTk8HzPMrKyoa8p7GxkQ66IYKaMWcG7F3YzV7Jx1MEyoaQ0btz+nTmOqu+HoUtzcIkY4LUFWzLl9wzCpyExhKaAyqqiclob2/vt0JtSKvVIjU1dYoyIqQ/iVSC+avZ8XqpJ1Lolz1iMhZ5ecPZwoKJfXmDVqtHSlVynrmm1g/zQUU1MRnDFdS31NbWTnImhAxt/mr22PLWxjZcT80XKBtCRkcmkWDDtGlM7NviIqjoF8Nh8Ro1VCUXmJhFQLxA2ZCpRkU1MRkKhWL4mwC4ublNciaEDM0z0BO+M32YWPIx2rBITMemaWwLSKtajTPDtN8RQF2RAr6H3dujDFwqUDZkqlFRTUyGjY3NsIW1VCrFvHnzhryHkKkQvZbdsJh5PhPdHd0CZUPI6PjY2mK+uzsTO1xwQ6BsTEd30RnmWu4+C1Jrl4FvJqJDRTUxGRzHwdfXd8h7LKxtIZXShhAivLkr5kIi7fsW26PuQfrZDAEzImR0Nk9nTwi9UluL0tZWgbIxDd2FZ5hri2nLBMmDCIOKapF44YUXwHEc84+Hh4fQaU04R0dHTJ8+vf+KtUQKqbUjVLwExbU0r5oIz8bBBmGxYUyMWkCIKVni4wN7hZKJHabxeoPie7qhKktkYtT6YV6oqBaR8PBwVFVV6f/JzMwUOqVJ4ejoiFmzZiE4OBg+fv6QO7hD4ewNicICPA/s/TqFTlgkRsGwBaTgagEaqhoEyoaQ0VFIpVgfGMjEvi4qRA9tWByQqvwyoFH1BTgJLAKWCJcQmXIyoRMwFTpV3ZS+nkTpOvxNBmQymShXpwfCcRxsbW1ha2sLXt6Outa+jSHpJbU4lHQd98QGC5ghIUD4gjBY2Vqhs63v6zPlRCrWPrhGwKwIGbk7g6bj47xc/XWTSoWEigqs8PMTMCvjZNj6ofCcDYmlgyC5EGFQUT1CzUen9huI05auUT+Tn58PLy8vKJVKxMbG4uWXX8Y0g7FIYuRmb4XmThXUmh597PefXcTKCH84WFsM8SQhk0umkGHuijk4/2XfiK3k48lYs3M1uNuOgibEWAXY2WO2qyvS6/oWlg4X3KCiegCqorPMtTJwmSB5EOFQ+4dIxMbG4oMPPsCxY8fwz3/+E9XV1Vi4cCEaGsT/VrNUIoG3ow0Ta2jvxh+/vCxQRoT0mW9wbHl9RT2Ks4uFSYaQMbjTYMNiUnU1qtrbBcrGOOlU7b3tH7exmEb91OaGimqRWLduHe655x7MmjULq1atwtGjRwEA77//vsCZTQ07KyVsLNnNix+dv4YrRdUCZURIL/9QP7j6su1cycdpwyIxHct9fWErl+uveQCHC2nD4u1UJecBbd+7pZDIoPSnQ1/MDRXVImVtbY1Zs2YhP998TnFztbOCxOAd9V9+fA4arU6YhAhBb/9/jMFqddp36ehR9wzyBCHGxUImw9oAdsPikcJCaHT0vfWW7sLvmGulbywkSptB7iZiRT3VI+SwoVToFEZFpVIhJycH8fHm85uyQiaFrSU7/ulaeQPeO5OJR1dGCZQVIb3Hlh/999f66672LmRfzMbsZbOFS4qQUdg8fToO5l/XX9d3dSGxqhLx3j5DPGU+ugtOMdfKacsFyoQIiYrqERrLNI6p9NOf/hSbNm2Cn58famtr8fvf/x6tra146KGHhE5tStlYyDHNzR4VLX0n1/3tSDI2zJ0OT0daNSDCcHR3xIw5QchP6zuRLvl4MhXVxGQEOToizNkZ127bp3O4oICKagDajjr0VF9lYhbTVgiUDREStX+IRHl5OXbs2IHg4GBs2bIFCoUCly5dgr+/v9CpTSmO47B7w3wm1qHqwQsHLwzyBCFTI9qgBSTnci7aGtsEyoaQ0ds8fTpzfbGyErWdnYPcbT4MWz84hTWUPjECZUOEREW1SHzyySeorKyEWq1GRUUFPvvsM4SFhQ3/oAjN8nPD9kWhTOybtEKczioRKCNCgMglkVBY9G2m1el0SD19RcCMCBmdVX7+sJL1vcGt43kcLSwUMCPj0K+fOmAJOJlikLuJmFFRTUTpfzcvgJMNO6P6N/sT0EWbw4hALKwsEBk/i4nRseXElFjJ5Vht8O7n4cIC6Mz8BNvugtPMtQX1U5stKqqJKDnaWOBXd8cxsbKGNrz+Da0MEuEYHltecaMClQWVAmVDyOgZzqyu7uhAUnWVQNkIT9NUBG1TEROzmE791OaKimoiWlsXBCMmyJOJ/eNkOvKrmgTKiJi7GbNnwN7Fnokln0gRKBtCRi/UyQkzHByY2OEC851Z3V3Atn5IrF0hd4sQKBsiNCqqiWhxHIc/bF8CmaTvy7xHq8OvPzkH3szfriTCkEglmL96HhNLPZECrVYrUEaEjA7Hcf1Wq8+Vl6Oxq0ugjIRlOErPYtpycBIqrcwV/T9PRC3YywmPrWJnVCfmV+JQ0vVBniBkchlOAWltbMP1VPp6JKZjbUAAlFKp/lrL8/i6qGiIJ8SJ1+nQXXSGidEoPfNGRTURvV3r5sHHyZaJ/eVwElQ9tDpIpp5HgAd8g32ZWPIxagEhpsNWocAKXz8mdriwwOzeAeypyYSuo46JUT+1eaOimoielVKO321bzMQqm9rx0flrAmVEzF30GnaWeub5THS1m+fb58Q0bQ5iZ1aXtbUhrbZWoGyEYThKT+Y4DTLHAGGSIUaBimpiFlbN8keswabFN46lolNFI/bI1Ju7ci4k0tt6/dU9yDibIWBGhIxOpIsrAuzsmNiXBTcGuVuc+o3So1Vqs0dFNTELHMfhuTtjmVhdaxfeP5slUEbEnNnY2yBsAXs4U/JxagEhpqN3wyK7Wn2mrAwtKpVAGU0tXqOGqiSBiSlpPrXZo6KamI2YIE8sC2N7Wd86kYbWLvP4IUCMi+GGxYKrBWioahAoG0JGb11gIOS3TbpQ63T4ttg8NiyqypPAqzuYGB36QqioFpGKigo88MADcHZ2hpWVFWbPno3U1FSh0zIq/7Mphrlu7lDhX6euCpQNMWfhC8JgZWfFxGi1mpgSB6UFlvr4MLHDBeaxYbG7kG39kHtEQWrtIlA2xFhQUS0STU1NWLRoEeRyOb755htcu3YNf/vb3+BgMKTf3EX5u+GOqEAm9q/TGWhq7xYoI2KuZAoZ5i6fw8RSjqeYRUFCxMNwZnVhSwsy6+sFymbqqPr1U68UKBNiTGRCJ2AqtAZjcyab1Np1VPf/6U9/gq+vL9599119LCAgYIKzEof/2RSNY1eLcKt2ae/uwVsn0vBLg2PNCZls89dE4/yXF/TX9ZX1KMoqwrRZ0wTMipCRm+fuDm8bG1S0t+tjhwsKEOk6up9hpkSnaoOqPImJWUyn1g9CRfWIVfzRe0pfz+8l9ajuP3z4MNauXYt7770XZ8+ehbe3Nx5//HE89thjk5Sh6Qr2csbm+TPwRXK+PvbemSw8uiIKbvZWQzxJyMTyD/WDm68basv6RpElH0+hopqYDAnHYdO06Xj7au/0Gl6nw8FvvoZ3fj4CfX0RHx8P6W0HxYiBqjgB0Gn6AlI5lP6LB3+AmA1q/xCJwsJCvPXWW5gxYwaOHTuGH//4x3j66afxwQcfCJ2aUXp2QzSkEk5/3d2jwRvHrgiYETFHHMf1m1md9l0aetQ06pGYjg3TpkHKcWhMSkba07uQ8eJLeOTBB7F8+XIEBATg0KFDQqc4oQznUyt9F0CisBYoG2JMqKgWCZ1Oh7lz5+Lll1/GnDlz8KMf/QiPPfYY3nrrLaFTM0oBbva4Ny6EiX10PhsVjW0CZUTM1fzV88Fxt/2C19GNrAs06pGYDhdLS7jeKMD1PXugbmxkPlZRUYGtW7eKqrDuLjjFXNPR5OQWKqpFwtPTE2Fh7Nzb0NBQlJaWCpSR8du1bh4UstvGQWl02PsNTUshU8vR3RFBs9nNXjQFhJgSrVaLi2++OeDHbm283b17N7Ra7VSmNSm07TXoqWF/6aVDX8gt1FM9Qt6/qBA6hSEtWrQIeXl5TOz69evw9/cXKCPj5+1ki/sXh+O9M5n62KeJufjJ6tkIdHMQLjFidqLXzEd+Wl+Pf25SLtoa22DrZCtgVoSMTEJCAmqrqgb9OM/zKCsrQ0JCApYtWzZ1iU0Cw9YPTmkLhff8Qe4m5oZWqkdIau06pf+M1jPPPINLly7h5Zdfxo0bN/DRRx/hnXfewRNPPDEJfxri8eTaubCQ9/1uqdXxePUorRKSqRW5JBIKC4X+WqfTIfUUvWtCTEPVEAX1WO4zZv36qQPiwUnlAmVDjA0V1SIRHR2Nzz//HB9//DEiIiLw0ksvYc+ePfje974ndGpGzc3eCg8vi2BiX6bkI6+STrYjU8fCygKR8ZFMjFpAiKlQSG1GdJ+np+ckZzK5eJ5HN82nJkOgolpENm7ciMzMTHR3dyMnJ4fG6Y3QT1bPge1tq4Q8D/ztq2QBMyLmKHot+xZyxY0KVBZUCpQNISPT2tyJi0fqYKV0GPI+pbMzrGfOnJqkJommqRDa5hImRkeTk9tRUU3MnqONBR5dya4SfptRhIyS2kGeIGTizZg9A/Yu9kws+Tj9ckeMl1qlwWsvHEFDTRtiQu4e8l7/nTvxPwnncNqEN88brlJLbNwhdwsXKBtijKioJgTAoyui4GCtZGJ/+yppkLsJmXgSqQTzDWZWp55MFcXEBCI+Oh2Pf/7lOG7k9PZJ+7tHYVnU92Fn7cTcp3B2wszdu+EUE40enQ6/vnAeB69fFyLlcet3NPm05cw4TEKoqCYEgK2lAj9ZPYeJnblWhqQbpr+xhpiO6NVsUd3a2IbrqaZZgBBx++y9i0hOyGdicyIWobCwCN999x0++ugjHDt5ErsPfganmGj9PTyAv6Wm4B9XM/Tj9kwBr9Ohu+gME6N+amKIimpCbnp4WQRc7SyZ2F8OXzapb/zEtHkEeMA32JeJJR2jFhBiXM58nYWj+9mNtBZWCjzz0mY4u9lh2bJl2LFjB9asXImXlyzB3UFB/T7He9nZ+GNyEjQ63VSlPS491RnQdbIb2KmfmhiiopqQmywVcjy5dh4Tu3yjCgm55QJlRMxRzNpo5jrrfBa62rsEyoYQVlZqCT543aC3WMLhyV+vh2+gS7/7pRIJnpsfjUdnzer3scMFBfjl+QR0azSTlu9E6S5k/5tlTkGQOfgJlA0xVlRUE3Kb+xeHwduJHQ/1l8NJtFpNpsycFXMglUn11z3qHqSfzRAwI0J6lRfX443ffw2djv1++OBTKxAxb/CDxjiOww8iZuHn0TGQGPQgJ1RU4OnvTqNFpZqUnCdKdwE7n5pOUSQDoaKakNso5VLsWsf2tWaU1OLE1WJhEiJmx8beBmELwpgYTQEhQmtu6MDff/0lujvVTHz9tnlYtj5ikKdYdwUF4eXFi6GQSpl4Zn09fnLyJGo6OiYs34nEa1RQlSQwMWr9IAOhopoQA/csmIkAV3a02V+/Suq3OkPIZIk2mAJSeLUQ9ZX1AmVDzJ2quwd7fnsYjXXtTDxmyQxs/f6iUX2upT6+eG35ctjK2VMIi1pb8IPjx5BVb3xf56qyy+B7bmvB4jgopy0TLB9ivKioJsSAXCrFsxvZoia3shFHrtwQKCNibsJiw2BlZ8XEUk7QCYtk6um0Orz9yrcozmfn9geFeuLRn66BRDL6kXJRrm54a9VquFqyG8Mburvx+KmTOFpYOK6cJ1p3wSnmWu45G1IrZ4GyIcaMimpCBnDnvBkI9mLnrf79SDI0WtPYqU5Mm0whw9wVc5lY8vEU6u0nU+7jdxKQdoktcl097fH0CxuhUMrG/HmnOzjgndVr4G9nx8R7dDr8/vIlvHblitFMBukuNOinnkb91GRgVFSLSEBAADiO6/fPE088IXRqJkci4fDTjTFMrLC2BYeSaGYwmRqGLSANlQ24kVEgUDbEHJ34Mh0nvkhnYtY2Sjz70mbYOVgN/NAoeFhb453VaxDj4dHvYx/n5eKnZ8+iTa0e4Mmpo+tuhbqC3dNAmxTJYKioFpHk5GRUVVXp/zlx4gQA4N577xU4M9O0JioAkX6uTGzP0RSoeuiEOzL5/EL84O7vzsQuHUkUKBtibtIuFeKjt88xMalMgqd+uxGevo4T9jp2CgX+tnQZ7gsO7vexy9VVePT4MZS0tk7Y641Wd/E5QHfb93ypAkq/0fWRE/NBRfUI9bQ0T+k/Y+Hq6goPDw/9P0eOHMH06dOxdOnSif3DMBMcx+G5O9nV6vLGNuy/mCNQRsSccByHBesXMLGMc1fR0WqcExKIeBTn1+Ktl78Bb7A5+wfPrkZIpM+Ev55MIsHuufPwy5hYyCRsWVLa1oZHjx9DYmXlhL/uSKgMWj+UfnGQKMa/Sk/EaewNUWbm6sObp/T15n1+dlzPq9VqfPjhh3j22WfBcaPfSEJ6LQn1RUyQJ3Nc+WvfpuLeuGBYKuRDPEnI+EWvnY8j/zoC7c13RzQ9GqQcT8HSrfSLMpkcDbVt2PP8YahV7IEsd+2MxcKVIZP62pumT4e/nR3+93wCGru79fH2nh789NxZPBE1GztCQqb0Z5rhJkXqpyZDoZVqkfriiy/Q3NyMhx9+WOhUTBrHcXhuE7taXdvSiQ/OZguUETEnNvY2iFwcycQufX2ZNiySSdHVocKrz3+J5kb23ZCFK0Ow+XuxU5JDpKsr/rNmLYId2RYTHc/j9fQ0vHgpESrt1LTgaduq0VN7jYlRPzUZChXVIvXvf/8b69atg5eXl9CpmLzYGV5YEurLxN48nob2bmE30BDzELeBbQGpKqpCSU6JQNkQsdJotPi/P3yD8qIGJh4c6Y3v7145pavD7tbWeHvVaqzy638M+LfFxXj81EnUdXZOeh6GR5NzSjsovOZN+usS00VFtQiVlJTg5MmTePTRR4VORTQMV6ubOrrx79NXBcqGmJOgOUFw9mJn4iYeuSRQNkSMeJ7Hh/93Blmp7C9rHj6OePr5jZArpr5T1EImw4sLF+FHkVH9PnatoQGPHD+Gaw0NAzw5cfqN0gtcAk5KXbNkcPTVMUKR730pdAoj9u6778LNzQ0bNmwQOhXRiApww5rIABy/7bjyd05m4KGlEXCwthAuMSJ6EokEC9YvwNF/HdXH0r5Lw91P3AUL+tojE+Cbg1dw5ussJmZrb4lnf78Z1rbCfY1xHIeHw8Mx3d4eLyReRKemr8+7vqsLPzl5Av8bE4s7AgMn/LV5nkd3AbtSbTF95YS/DhEXWqkeIbm9w5T+M1Y6nQ7vvvsuHnroIchk9DvTRPrpphjc/g5oW7ca/ziZLlg+xHzE3BENyW1TEdTdaqSeuiJgRkQskhPyceBf55mYTC7Frhc2wc3TXqCsWPE+PvjnmjXwtrFh4mqdDr+7lIj/S0+DdoIPitE03oC2pYyJWUxbPqGvQcSHimqROXnyJEpLS/HII48InYrohHg74855QUzsP99loq518nv7iHmzd7ZH+MJwJpZIM6vJON3IqcI7fz7WL/7Dn61FUJinABkNbpq9A/69Zi3mubn3+9iHOTn4WcI5tE/gQTGGq9RSW0/IXEMn7PMTcaKiWmTWrFkDnucxc+ZMoVMRpWc2REMq6Vuu7lJr8H/HaMWQTL64jXHMdXl+Ocryyga5m5Ch1Va1YO9vv0KPmp2kse0HixCzZIZAWQ3NXqnEnuXLsXVG/59vFysr8eiJ4yhrm5iDYgyLauW05TSelgyLimpCRmGauwO2xrInf32YkI3iuhaBMiLmImR+MBzd2TFjF2m1moxBR1s3Xv3Nl2hr6WLiS9dFYN29xj3dQiaR4H/mz8cvomP6HRRT0tqKHxw7hstVVYM8PTK8TgtV0RkmRqP0yEhQUU3IKO1aPx9y6W39rRodXvmcihsyuSRSSb8TFq+cuoLuzu5BniCkP02PFq+/eBRVZU1MPGKeH3Y+ucxkVmM3BwXh9eUr4KBUMvG2nh48e/YMPsnNHfM8956qDOi62D8fOvSFjAQV1YSMko+zLR5eNouJfZNehEvXhTlGl5iP2HUxzIZFVZcKV2jDIhkhnufx7p5TyL1azsR9Ap3xxK/WQyaTCpTZ2Mx2c8N/1t6BGQ4OTFzH89ibdgV/uHwZ6jEcFGN4iqLMZSZk9hN/PDsRHyqqCRmDp9fNg6PBOLMXP7sw4TvQCbmdg6sDwuLCmBhtWCQjdfi/SbhwMoeJ2TtZ4ZkX74SltXKQp4ybp7U1/rF6DZb7+vb72NGiQjxx+hQauroGeHJw/eZT0yo1GSEqqgkZA3srJf5nYzQTyyqrx2eXrwuUETEXCw02LJZdpw2LZHgXT+Xi833soUEKpQzPvHgnnN3sBMpqYljKZPj9osV4dNasfh/Lqq/HI8ePIbexcUSfi+/phqqEHTFI/dRkpKioJmSM7l8chhme7MaxP315GR3dPQJlRMxBSHQIHNwcmFjiUVqtJoPLy6zAv/9+golxHPCTX65DwIz+I+pMkYTj8IOIWXhlcTwsDc5oqO3sxI9OnsCJkuJhP4+q7BJ4zW37FDgJLAKXTnC2RKyoqCZkjGRSCZ6/ZyETq2vtxFsn0gTKiJiDgTYspp68AlWXSqCMiDGrKmvCay98Ba2GbU27/8dLMWfBNIGymjzLfH3xzqrV8LC2ZuJqrRbPX7yItzMyoBtiA6NhP7XCay4klo6D3E0Ii4pqQsZhaZgflof7MbF/nExHRWObQBkRc7BgfSy42+alq7pUuHKafpkjrNbmTvz9N1+io539hWv1XbOx+q7ZwiQ1BYIcHfGfNWsx29Wt38fev5aNnyecQ0fPwO8o9u+nplMUychRUU3IOP16y0LmQBhVjxZ//OLSEE8QMj4Org4IX8CesHjxq4sCZUOMkVqtwWsvHEFdFTtDf/aCQOz4YbxAWU0dRwsLvLZ8Oe4OCur3sfMVFfjxyRP9TmDUdTVDXZHCxCymr5zUPIm4UFFNyDjN8HTEzni2wPky5QZSC6sFyoiYg7iNbAtIWV4Zyq7ThkUC6HQ8/vWX47iRwx6C4h/khh//4g5IpObxo18uleJn0TF4bn40pAbzt280N2PPFXYcZXfxOYC/rU1GpoTCj90YTMhQzONvlhnQaDT49a9/jcDAQFhaWmLatGl48cUXoaMRb1PimQ3RsLNUMLEXD16ATje2wwcIGU5oTCgcXB2YWOJReoeEAJ+9dxFJ5/KZmJOrDZ558U5YGHyfMgdbZszAa8tXwF7Bjg08WlSIhIq+md39jib3WwSJ3HJKciTiQEW1SPzpT3/C22+/jTfeeAM5OTn485//jL/85S94/fXXhU7NLDjaWGD3+vlMLK24FodT8wd5gpDxkUglWLAhlomlnkylDYtm7uw3WTi636CFwUqBZ17aDAdn60GeEr+57u7455o1sJbLmfgfk5LQour9O9NdyBbV1E9NRks2/C0EALqa2qf09SwdbUZ1f2JiIjZv3owNGzYAAAICAvDxxx8jJSVlmCfJRHlwaQT2JWSjqLavh/GVzy9hbVQgLBXyIZ4kZGxi18Xi2AfHwd98R0TVqULa6TQs2LBgmCeJGGWlluD919jCUCLh8OSv18M30EWgrIyHr60tds2Zi5eTLutjjd3d+GtKMn47KxCaulzmfuqnJqNFRfUI/WfNr6b09Z5I3juq+xcvXoy3334b169fx8yZM5GRkYHz589jz549k5Mg6Uchk+JXW+Lw6Nvf6mNVzR1452QGdhmsYhMyERzdHBEWG4rsxGv62MUjiVRUm6Hy4nr83++/7tdy9uBTKxAxz1+grIzPxmnTcKa8DBcrK/Wxk6Wl2NidCs/b7uMsHKDwmjP1CRKTRu0fIvHzn/8cO3bsQEhICORyOebMmYPdu3djx44dQqdmVlbPCsCiYG8m9ubxNFQ3dwiUERG7hZvYWemluaUozy8f5G4iRs0NHXj1N4fR1clOs1i/bR6WrY8QKCvjxHEc/jcmFraKvt5yXqfD0c/ex5dZOiQW66DV8bAIXApOIhUwU2KKqKgWif379+PDDz/ERx99hCtXruD999/HX//6V7z//vtCp2ZWOI7D8/csguS2neZdag1e/jwR/BAHDhAyViExIf03LB6hDYvmQtXdgz2/PYyGWnY2fnT8DGz9/iKBsjJuLpaW+Om83ncPG5OSkfb0Lrz0Vhqe/kKL7R9qseh1DY6X0oEvZPSoqBaJ5557Dr/4xS+wfft2zJo1Czt37sQzzzyDV155RejUzE6ojzPuWxjCxL5IzsfPPjyDHq1WoKyIWEmlUsSuZzcsppxMoQ2LZkCn1eHtV75FcX4tEw8K9cRjz62BRMIN8iRZ7e8Pr8JCXN+zB+rGRuZj1W3Azl/+C4cOHRIoO2KqqKd6hB45/gehUxhSZ2cnJBL2dySpVEoj9QTy000x+Cr1Btq7+07t2p+Yi8qmdrz92FrYmuFYKzJ5FqyLxfF9BhsWv0vHAoNim4jLJ/9MQNqlQibm6mmPp1/YCIWSfrwPRafT4dJbbw/4MR4AB2D37t3YvHkzpFJqAyEjQ3/rRmi00zim2qZNm/CHP/wBfn5+CA8PR1paGv7+97/jkUceETo1s+RqZ4U/bF+C3e+fwu1dHwm55dj69y/w3uPr4WnkX1PEdDi6OyI0JhTXLt22YfGri1RUi9jJLzNw/PN0JmZto8QzL94JOwcrYZIyIQkJCaisqBj04zzPo6ysDAkJCVi2bNnUJUZMGrV/iMTrr7+OrVu34vHHH0doaCh++tOf4kc/+hFeeukloVMzW3fHzMQ7j90BCzn7u2tORQM2/+UQrpXXC5QZEaOFm9iT30pzS1F+Y/CigZiu9EuF+O/bZ5mYVCbBU7/dCC8/J4GyMi1VVVXD3zSK+wgBqKgWDVtbW+zZswclJSXo6upCQUEBfv/730OhoDYDIa2dHYj9u++Es40FE69u7sDWv3+Bs9dKBcqMiE1obCjsXeyZ2KUjiQJlQyZLcX4t3nz5G32rzy2PPLMKIZE+AmVlejw9PYe/CUCdjN7QJyNHRTUhk2xOoDu++Nk9mO7uwMTbu3vw8Jtf45MLOcIkRkRFKpX2a/dIoRMWRaWhtg17nj8MtUrDxDc/EItFq0IFyso0xcfHw8fHB9wQezkVzk7Y36PGseKiqUuMmDQqqgmZAv4udvj8p3cjeroHE9fqePzsv2fwl8OXaeQeGbcF6xeAu61K6O7oRvqZdOESIhOmq0OFV5//Es2N7Mz7hStDcNcD1Ds/WlKpFHv37gX43k2JAwnY+SB0HIffJSbiUH7+lOZHTBMV1YRMEQdrC/z36U3YNC+o38de//YKdr93CqoeGrlHxq53wyI7zvHiV9QCYuq0Wh3+7w/foLyogYkHR3rj+7tXMr9IkZHbsmUL/vmIPzxs2bi9uxtm7t4Np5hoAL3TQP6SkowPrmVPfZLEpFBRTcgUspDL8Pr3V+Ena/off/t5cj7+fPiyAFkRMYnbyG5YLMkpQQVtWDRZPM9j3xvfISu1hIl7+Djiqd9shFxBPb9jpe1sxGqvSlx4SoZPHpDitbukOLb/TdSXV+DxnQ/0u/+tjAy8mZ5O7yqSQVFRTcgUk0g4/O9dC/DyjiXMyYsA8MHZLDR3Ug8sGbuwuLB+GxYTj9IJi6bqm4NXcObrLCZma2+JZ1+6EzZ2FoM8RUZCXdb790Iq4RAXIMFds62wessPIJPJ8PScuXh01qx+z+zLuYa/pqRAR4U1GQAV1YQI5IH4cPznJ+sgl/b9NVRptPgi6bqAWRFTJ5VKEbvOYMPiiRSou9UCZUTGKjkhHwf+dZ6JyeRS7HphE9y8HIRJSkRUpReZa4VPNDhZ78QsjuPwg4hZ2D13br/nDt3Ix4uJidDQ4WrEABXVhAhoRYQ/1kYFMrGPL+TQ24tkXBasj+23YTGNNiyalBs5VXjnz8f6xX/4s7UIChvZODgyNFUpu99A6RfX7577gkPwq9jYfu8qHispxm8uXECPlvbBkD5UVBMisO2L2FFYORUNuFpaJ1A2RAycPJwQYrBhMZFmVpuM2qoW7P3tV+hRswXbvY8sQsySGQJlJS68Rg11eTITU/otHPDejdOm46WFiyCTsCXTmfIy/PLCeaipsCY3UVFNiMAWB/vAx4ndfk6zq8l4GW5YLM4uRmVhpUDZkJHqaOvGq7/5Em0tXUx86boIrN82T6CsxEddlQ5e083EFL4LBr1/hZ8f/rJkCZRSKRM/X1GBn507h26NZpAniTmhopoQgUkkHO5byK4qfpmSj05Vj0AZETEIjwuDnbMdE6PVauOm6dHijZeOoqqsiYlHzPPDzieX0ei8CaQqvcBcy93CILUa+oj3BZ5e+PuyZbA0OGXxcnUVfnruLLqosDZ7VFSLSFtbG3bv3g1/f39YWlpi4cKFSE5OHv5BIrh7F4QwPXvt3T04cqVAwIyIqRvohMXk47Rh0VjxPI9395xCTkY5E/cJcMbjv1oPmUw6yJNkLFQl7CbFwVo/DM11c8ery5bDyqCwTq2pwbNnvkNHDy2GmDMqqkXk0UcfxYkTJ7Bv3z5kZmZizZo1WLVqFSoqaEatsfNyssGyMF8m9jG1gJBxiqUTFk3G4Y+ScOEk+3fe3skKz7x0J6yslQJlJU48z/fbpKgYYJPiYKJcXfHaihWwlcuZeHpdHXaf+Q7tavrF1VxRUT1C7c3tU/rPaHV1deGzzz7Dn//8ZyxZsgRBQUF44YUXEBgYiLfeemsS/kTIRDPcsJhaWI3rVY0CZUPEwNnDCcHRwUyMWkCMz8XTufj8A3aWuEIpwzMv3glnN7tBniJjpWksgK6jlokp/Ue2Un1LuLMLXl+xEnYKBRPPqq/H09+dRisV1maJjmIaoV/f/Zspfb093706qvs1Gg20Wi0sLNjDACwtLXH+/PlBniLGZOUsf7jaWaKutW+D0v6LufjNPaP7Zk/I7RZujENuUq7+uii7GFVFVfAMpLFsxiAvswL/+ftJJsZxwE/+dx0CZrgLlJW4Gc6nlti4Q+Y4bdSfJ9jJCf+3YiWe/u40mlR9h3blNDbiyVOn8I/Vq/v1XxNxo5VqkbC1tUVcXBxeeuklVFZWQqvV4sMPP8Tly5dRVVUldHpkBORSKbYuYDcsfnY5D6oeGtdExi48Lhx2BtNlLn5Fq9XGoKqsCa+98BU0Bn/H7//xUsyJG32RR0ZmoPnUY90EGuToiP9buQrOBgta+c1N2J+XN+YciWmiolpE9u3bB57n4e3tDaVSiddeew33338/pFLa4GIqthtMAWls78aJzGJhkiGiIJVJEbueHRVGJywKr7W5E6/+5kt0tKuY+KrNUVh912xhkjITqhJ28sdINykOJtDeHm+uXAVXS0smnlBRPsgTRKyoqBaR6dOn4+zZs2hvb0dZWRmSkpLQ09ODwMDA4R8mRiHQzQELZngxMZpZTcbL8ITFrvYupJ/NEDAj86ZWa/Da746gtqqFic9eEIj7f7REoKzMg7azEZq6XCam9F807s/rZ2eHX8Wyv7zmNjaijXqrzQo1+4zQ7z9/SegURsza2hrW1tZoamrCsWPH8Oc//1nolMgobF8Yikv5fYd0JOSWoayhFb7OtGGJjI2zpzOC5wcjN7mvmEg8koiYtdECZmWedDoe//rrCdy4xrbl+Qe54ce/uAMSKa11TSZ1Gdv6wcktofCcPSGfO8rVFQqJBGqdDgCg43lcqa3BUh/fYZ4kYkFF9QjZONgIncKwjh07Bp7nERwcjBs3buC5555DcHAwvv/97wudGhmF9XOm4fkDCWjt6l3h4HngQGIu/mdjjMCZEVMWtzGOKaqLsopow6IADr13EUlnrzMxJ1cb7H5xEywsFYM8RSaK4XxqhXc0OKl8kLtHx0ImwyxXV6TW1OhjKdVUVJsT+pVYRFpaWvDEE08gJCQEDz74IBYvXozjx49DLp+YbxhkalgoZLg7ZiYTO3AxF9qbqx+EjEXEwv4bFmm83tQ6+00WjuxPYWIWVgo889JmODob/8KNGAy0SXEizXf3YK5Taqon9PMT40ZFtYhs27YNBQUFUKlUqKqqwhtvvAF7e3uh0yJjsH0hO7O6qrkDZ6+VCZQNEQOpTIrYdQOcsKiins+pkJVagvdfO83EJBIOT/xqPXwDXQTKyrzwGjXUFewvNaOdTz2caA92DGJxayvqOjsn9DWI8aKimhAjFO7rgkg/VyZGGxbJeC3YwG6k6mrvQgZtWJx05cX1+L/ffw2djmfiDz61HLPm+wuUlflRV6WB13QzMaXvgkHuHpsQRyfYGLw7fHs7CBE3KqoJMVKGJyyezCxBbQuteJCxu7Vh8XbUAjK5mhs68OpvDqOrk31HYP2987Bs/SyBsjJPhqP05G5hkFg6TuhrSCUSzHVjV6tTqKg2G1RUE2KkNs+fAUtF315ijU6Hzy7TYQJkfBZuZHtICzN7NyySiafq7sHeFw6jobaNic+PD8LWR8Y/xo2MjuFJihMxSm8g8z0Mi+pq8Dw/yN1ETKioJsRI2VoqsHHudCb2ycUc+uZMxiViUQRsHQ02LB69JFA24qXT6vD2H79F0fVaJj491AM/fG4tJJKxneBHxobn+UnfpHiL4WbFms5OlLe3DXI3ERMqqgkxYjsWhTHXRbUtuJxPq4pk7AbasJhCGxYn3Cf/TEBaYiETc/Www64XNkGhpGm2U03TeAO6jjomNt6TFAcTYGcHF4PTFZOrqQXEHExYUU2rZ0RoYvwanDfNHUEebM/fxxeuCZQNEYsFG9iiurOtE1fPXRUoG/E5+WUGjn+ezsSsbJR45qXNsHOwEiYpM6cqYVepJTYekDpOzmnDHMdhXr++ahqtZw7GXVTfmoHcSSNjiMBufQ2KaS43x3HYYbBh8ev0QjR3qgTKiIiBi5cLguezs9Av0obFCZF+qRD/ffssE5PKJHjq+Y3w8nMSKCvSr5/aLw4cN3ktOIZ91UnV1ejRaift9YhxGPd7UFKpFA4ODqit7e0bs7KymtQvVEIM8TyPzs5O1NbWwsHBAVKpVOiUJtSWmJn44xeX0KPtPfxF1aPFl8n5eGhphMCZEVMWtzEOeSl9J/sVXi1EdUkNPPzdh3iKDKU4vxZvvfIteIPReY/sXoXQKB+BsiLAQJsUJ6f145YFnl7MdUdPD67U1iLWk04wFbMJaezy8Ohtyr9VWBMiBAcHB/3Xopg421piTVQgjl4p0Mc+vnANDy4Jp19gyZhFLIyAjaMN2pva9bHEIxdx9xN3C5iV6WqobcOe5w9D1d3DxDc/EItFq0MHeYpMBW1nAzR1uUxM6Te501dcLC0R4eyMrIYGfexceTkV1SI3IUU1x3Hw9PSEm5sbenp6hn+AkAkml8tFt0J9ux2LQpmi+lp5A66W1iHK303ArIgpk8lliL0jBqc+7jvlL/lYCjY+thFyhXhaqKZCV4cKe54/jObGDiYetzIEdz0QO8hTZKoYTv3g5FZQeEZN+usu8fFliuqEinL8z/z5kNBiiGhN6BZkqVQq6sKGEKEsDvaBj5Mtyhv7xjJ9ciGHimoyLnEb4piiurOtExlnr2L+6nkCZmVatFod3nz5G5QV1TPx4FneeGT3Sno3yQioDVo/FD7R4KST/4tjvI833sxI11/XdXUht7ERYc7Ok/7aRBg0Uo8QEyCRcLhvYQgT+zIlH50qemeIjJ2LtwtmzmM3LNIJiyPH8zz2vfEdMlNKmLiHjwOeen4j5AoanWcMpmo+taEAO3v42doxsXPl5VPy2kQYVFQTYiLuXRDCvG3Y3t3DtIQQMhaGJywWXC1ATSnN1B2Jbw9ewZmvs5iYrb0lnn1pM2zsLATKityO16igqkhhYpM1n3ogS3y8meuECiqqxYyKakJMhJeTDZaF+TKxjy7kCJQNEYuIRRGwcbBhYhe/otXq4SQn5GP/v84zMZlciqd/uxFuXg7CJEX6UVemAZrbRpByHJS+C6bs9Zf4sFNfCltaUNbWOmWvT6YWFdWEmBDDExZTC6txvapRoGyIGMjkMsTcEcPEko8no0dNrUWDKcitxjt/PtYv/sPn1mBGuNcATxChGI7Sk7uGQWLpMGWvH+7sAicL9l2Lc+UVU/b6ZGpRUU2ICVkxyw+uduzxt/sv5g5yNyEjE7eRXbnrbKUTFgdTV92CPc8fRo+aPchj6yMLEbN05iBPEaGoSi4w10r/yR2lZ0jCcYj3phYQc0FFNSEmRC6VYusCdsPiZ5fzoOqhk7rI2Ll6u2Lm3BlMjE5Y7K+jrRt///WXaGvpYuJL7gjHhm3zBcqKDIbneajKLjGxqdqkeDvDFpCrdXVo7O6e8jzI5KOimhATs91gCkhjezeOXy0SKBsiFnGGGxYzClBTSgd63aLp0eKNl46iqqyJiYfP9cODTy2n0XlGSNOQD11HHROb7JMUBzLP3QNWsr5JMDyA8xXUAiJGVFQTYmIC3RwQN4Pt2/yENiyScZq1eFa/DYs0Xq8Xz/N4d+8p5GSwb9v7BDjjiV+vh0xG5zMYI8NRelJbT0gdAqY8D6VU2u8kRWoBEScqqgkxQdsXscceJ+SWo7SedpSTsZPJZYhZG83Eko/RhkUAOPxREi6cYH9xtXeywjMv3Qkra6VAWZHhGG5SVPjFCfaOwlKDFpCkqip00gnUokNFNSEmaN3sabCzVDCxTxNpwyIZH8MWkI7WDlxNyBQoG+Nw8XQuPv+A7ctVKGV45sU74exmN8hTxBioStiieirnUxuK8/KG9LaCXq3TIam6WrB8yOSgopoQE2ShkGFLDDtpYH9iLrQ6nUAZETFw9XHFjDnshkVzbgHJy6zAf/5+kolxHPDjX9yBgBnuAmVFRkLbUQ9NfR4TE7KotlMoMMfNjYnR6YriQ0U1ISbKsAWkurkDZ7LLBMqGiIXhavWN9BuoLTO/DYvV5U147XdHoDGYrLPjR0swd+F0gbIiI2XYT83JraDwjBIom16GU0DOV1ZAQwshokJFNSEmKszHBVH+7MrHJxdpwyIZn8jFs2Btb83EzG21uq2lC3//9ZfoaGPHnq3aHIU1d88RKCsyGv36qX1iwEnlAmXTK96bLarb1Gpk1NUNcjcxRVRUE2LCDFerT2YWo7alU6BsiBjIFP1PWEz6NhkatUagjKaWWq3B3he+Qm1VCxOPig3E/T9aIlBWZLTUBivVQsynNuRhbY1gR0cmRi0g4kJFNSEm7M55QbBU9M0/1ep4HLycN8QThAwvbgN7wmJHaweunhf/CYs6HY9//fUEblyrYuL+Qa74yf/eAYmUfmSaAl6jgqoylYkJMZ96IIYtIOcqysHzvEDZkIlG3yEIMWG2lgpsmhfExD65kEPfpMm4uPm6YcYc9uvKHFpADr2fiKSz15mYk4sNdr94JywMpu0Q46WuvAJoVH0BjoPSd8HgD0yhJQYtINUdHchvbhYmGTLhqKgmxMTtMGgBKa5rwaX8SoGyIWJhuGExP03cGxbPHcvGkU+SmZiFlQLPvHQnHJ1tBnmKGCPDfmq5WzgkFvYCZcOa7uAAL2t2z0ICtYCIBhXVhJi4uYHumOHJ9unRCYtkvCIXR8Lajv3hf+nopUHuNm3ZV0rx/t7TTEwi4fDEr9bDd5qrQFmRsVKVXGCuhRylZ4jjuH4tIGepqBYNKqoJMXEcx2HHQna1+uu0QjR3qgZ5gpDh9W5YZE9YvPxtkug2LFYUN+CNl45Cq2VHmz341HLMmu8vUFZkrHieh6qU/eXPWPqpb4k3KKrzm5tQ1d4uUDZkIlFRTYgIbImdCfltm6hUGi2+SLo+xBOEDG/BBoMTFls6cPW8eE5YbG7swN9/8yW6OtVMfN2987Bs/SyBsiLjoam/Dl1nPRMzppVqAIh0cYW9gj3ePqGiQqBsyESiopoQEXCyscTaqEAm9jFtWCTj5O7nhulR7EEnYtmwqOruwd7fHkZDbRsTnx8fhHsfWSRQVmS8DA99kdp6QepgXO84yCQSLPL2YmI0Wk8cqKgmRCR2LA5jrnMqGnC1hA4WIOOzcBO7ypeflo+6ctP+utJpdXj7j9+i6Dq78XJaiAd++NxaSCScQJmR8TLcpKj0iwPHGd//n4Z91el1tWhRUcueqaOimhCRWDTTG77OtkzsYzphkYxTZPysfhsWE018w+L+f51HWmIhE3P1sMPu322CQikb5CliCvqdpGhk/dS3xHp4QimV6q+1PI+LlTS1ydRRUU2ISEgkHO4z2LD4ZXI+Orp7BMqIiIFcIUf0WnbDYtK3SdD0mOaGxZOHM3DsUBoTs7JR4pmXNsPOwUqgrMhE0HbUQVPP7iUxtn7qWyxkMsR4eDAxagExfVRUEyIi9y4IhuS2tzo7VD04cuWGgBkRMYjbyB6c0d7cjkwT3LCYfrkI/33rLBOTyiR46vmN8PJzEigrMlEM+6k5uRUUHpECZTM8wxaQS1WV6NaY5i+rpBcV1YSIiKejDZaF+zExmllNxsvdzx3TI017w2LJjVq89fI34HXs5t3v716J0CifQZ4ipqRf64dvLDipXKBshrfIy5tZBOnWapFSUyNgRmS8qKgmRGTuNzhhMbWoBnmVjQJlQ8Ri4SZ2vN71K/moqzCNDYuNdW149fnDUBm0Qm3+XgwWrw4b5CliagxXqpV+cYPcaRwcLSwQ6eLCxKgFxLRRUU2IyCyP8IOrHdsbup82LJJxilwSCSuDrytTOGGxq1ONV39zGM0NHUw8bmUI7tq5YJCniKnhe7qhrkhlYsbaT307wxaQ8xXl0Op0g9xNjB0V1YSIjFwqxb0LgpnYZ5evQ9WjFSgjIgZyhRzRawY4YdGINyxqtTq8+YevUVbEHgYSPMsbj+xeaZSj1sjYqCuvANrbDvHhOCh9Y4VLaITivdmiukmlQlZDg0DZkPGiopoQEdpuMAWkqaMbxzKKBMqGiEXcRvbt9PamdmRdyBIom6HxPI8P/+8MMlNKmLiHjwOeen4j5AoanScmhv3UcrcISCzsBcpm5HxsbTHNns2TWkBMFxXVhIhQgJs9Fs5kT+z6hFpAyDh5+LtjWuQ0JnbRSDcsfvtZGr47yk4osbW3xLMvbYaNnYVAWZHJ0u/QFyOdTz0QwxaQc+VldBquiaKimhCR2m6wYfF8bjlK61sFyoaIxUKD1errqddRX1E/yN3CSE7Ix4F/JTAxmVyKp3+7EW5eDsIkRSYNz/Mmt0nxdksMWkDK29tR3Erfq00RFdVGRKvV4syZM/j4449x5swZaLXUA0vG7o7Z02BvpWRiBxJzBcqGiEXU0ihY2bIbFhO/Np4NiwW51Xjnz8dguND3w+fWYEa418APEZOmqc+DrpPtQ1b6LxIom9ELcXKCq6UlEztLLSAmiYpqI3Ho0CEEBARg+fLluP/++7F8+XIEBATg0KFDQqdGTJSFXIa7Y2Yysf0Xc6HR0s5yMna9JyzOZ2KXv7lsFBsW66pbsPe3h9GjZhcktj6yEDFLZw7yFDF1hqvUUjtvSO39Brnb+HAc168F5EIFFdWmiIpqI3Do0CFs3boV5Qa/mVZUVGDr1q1UWJMx22GwYbGmpQNnrpUKlA0Ri7gNA2xYvCjshsWOtm68+pvDaG3uYuJL7gjHhm3zB3mKiEG/fmq/OJOb7GI4BSS7oQEtKpVA2ZCxoqJaYFqtFrt27RpwU8Kt2O7du6kVhIxJqI8zZge4MTE6YZGMl0eAB6bNCmRiQp6wqOnR4o2XjqKylD3kKHyuHx58arnJFVhkdFQlhkW16WxSvGW2mxuUUqn+mgdwuapKuITImFBRLbCEhIR+K9S343keZWVlSEhIGPQeQoZiOF7vVFYJalo6BrmbkJExHK+Xl3Id9ZVTv2GR53m8t/cUcjLY76Pe/s544tfrIZNJB3mSiIG2ow6ahnwmZopFtVIqxTx3dyZ2iYpqk0NFtcCqRviXZqT3EWLozvlBsFL2zeTV6ngcvJQnYEZEDAbasHjp6OUpz+Orj5Nx/gT77ou9kxWeeelOWFkrB3mKiIXhKjWnsIbcI1KgbMZngacnc32pqgo6Gq1nUqioFpinwV+i8d5HiCEbCwU2zQ1iYp9czIFOR9+sydgplArMX9N/w6JWM3Wtaomnc3HofbbtRKGUYffv7oSLu92U5UGEY7hJUeETA05qmgf7xHmy02maVN243tQkUDZkLKioFlh8fDx8fHwG7fnjOA6+vr6Ij4+f4syImBjOrC6pa8Wl/EqBsiFiEbdhAXPd1tQ2ZScs5mVW4N9/P8nEOA748S/uQOBM90GeImLTf5Oi6bV+3OJjawsfGxsmdqmKvk+bEiqqBSaVSrF3714AGKSw5rFnzx5IpdQXSMZubqA7Zno6MjE6YZGMl2egJwIj2A2LU3HCYnV5E1773RFoethV8e0/XIK5C6dP+usT48D3dENdeYWJmdJJigOJ82JXqxMrqfXTlFBRbQS2bNmCgwcPwtvbm4nbuljgh7/fgi1btgiUGRELjuP6rVZ/k1aI5o5ugTIiYtF/w2IeGqoaBrl7/NpauvDqb75ERxv7tbvyziisuXv2pL0uMT6qylRAq+4LcBIofWKFS2gCGLaAZDXUo1WtHuRuYmyoqDYSW7ZsQXFxMf6x/+9Y/2wktr0UjUffXgqbsE40dtQInR4RgS0xM6GQ9f2VV2m0OJR0XcCMiBjMXhYFSxv2NLhLRyfnhEW1WoPXfvcVaipbmHhUbCC+9+MlNDrPzKgNNinK3SMgsTDtXvo5bm5QSPq+T+t4HsnV1QJmREaDimojIpVK8f17HsfcFTPhG+EMibT3B0Ry6XGBMyNi4GRjibVR05jYxxdyBpyRTshIKZQKRE/BhkWdjse//3YC+dns2+H+Qa74yf/eAYmUfpyZGzH1U99iIZNhjhu7JyCxkvqqTQV9FzIycqkSc3yWM7Hk0hPQ8XT4Cxm/HQYtIHmVjcgoqRUoGyIWhi0grY1tyLqYPaGvcej9RFw+w76z4uRig90v3gkLS8WEvhYxfrxO12/yh9IvbpC7TYvhaL3L1VW0+GEiqKg2QjH+a5jr5q465NelC5MMEZWFM73h62zLxD6mExbJOHkGeiIwPICJTeQJi+eOZePIJ8lMzMJSjmdeuhOOzjaDPEXETFOfB10Xe4KmqW9SvMVws2J9VxduNDcLkwwZFSqqjZCPQxC87Nm36ZNKqAWEjJ9EwvU7YfFwyg10dPcIlBERi8nasJh9pRTv7z3NxCQSDo//aj18p7mO+/MT02S4Si2184HU3k+gbCaWn60tvKytmVgijdYzCVRUG6kY/7XMdVbVRXSoWwXKhojJvXHBkNy2oatD1YOvUm8ImBERg9nLZsPC2kJ/zfM8Ln09vhMWK4ob8MZLR6HV6pj4zieXIzI6YFyfm5i2/v3UcaLZqMpxHBYYTAGhI8tNAxXVRmquz3LIJHL9tVanwZWy7wTMiIiFh4MNloezKzo0s5qMl8JCgeg10UxsPBsWmxs78Pfnv0RXJztObN2987B8w6wx50nEoV9RLZLWj1sWeLF91Vfr6tDRQ+8oGjsqqo2UlcIWEZ7sN4mkkmO0WYFMiB2L2RaQK0U1yKucvNnCxDzEbWRPWGxtaEV24ug3LKq6e7D3t1+hoaaNic9fHIR7H1k0rhyJ6dO210LTwL67JobJH7eb5+YO+W2j9bQ0Ws8kUFFtxAxbQKpai1DRQm/Tk/FbEe4PN3srJvbJxVyBsiFi4TXNCwEGGxZHe8KiTqvDP/50DEXX2fn800I88MOfrYVEIo63+MnYGfZTcwpryN3F9e6FlVyOKFd2zwAdWW78qKg2YkGuUXC0dGNil0uOCZQNEROZVIJ7FwQzsc8u56G7RyNQRkQs+m1YTM5DQ3XjIHf3t/9f53HlYgETc3G3w+7fbYJCKZuQHIlpM2z9UPjEgpOK72vD8HTFxCoarWfsqKg2YhJOgmiD8XppZWfQo1UJkxARlfvi2BaQ5g4VjmcUCZQNEYs5A2xYvPz1yE5YPPVVBo4dSmNiVjZKPPv7zbBzsBrkKWJuxN5PfYthX3VtZyeKWlsGuZsYAyqqjdx8v1Xg0Pd2Z7emA5mVFwTMiIhFgJs9Fs5kV0JoZjUZr94Ni+wJi5e+vgytdugNi+mXi/Dhm2eZmFQmwVO/2QAvP6cJz5OYJl1PF9SVV5iY2Pqpbwm0s4e7FfvLZGIlTQExZlRUGzknK3fMcJ3NxC7TzGoyQXYsCmOuL+RVoKSeRjeS8el3wmJDK7ITrw16f0lBHd56+RvwOvat7e/vXonQ2b6TkiMxTeqKVEB72xQMTgKlb6xwCU2igUbr0bxq40ZFtQkw3LBYUJ+Bhg76bZWM39rZgbC3UjKxAzRej4yT1zQv+If5M7HBTlhsrGvDq7/5EiqDA4juvD8Gi1eHDfgMMV+GrR9y91mQKG0Hudv0GR5ZnlFXh04arWe0qKg2AeGecbCUs0fxJpecECgbIiYWchm2xMxkYgcS86AxOGyDkNFaaLBanZuUi0aDDYtdnWq8+vxhNDd0MPG4FcG4+0F2PB8hgPn0U98S7eEB6W2H2mh0OqTW1AzxBBESFdUmQC5VYJ7vCiaWXHYCOn5shyoQcrsdi9gNizUtHfguu1SgbIhYDHfColarw1svf42ywnrmuZkRXnjkmVWiOR2PTBxep4O6lN30qvSLG+RucbAeYLQetYAYLyqqTYRhC0hLVz2u16YNcjchIxfi7Yw5AezoRjphkYyX0lKJ+avmMbHL3/RuWOR5Hv998wyuJpcwH3f3dsDTv90IuUJ849HI+Gnqc6HrYt/tEOsmxdsNdGQ5jdYzTlRUmwgv+2nwtg9iYkk0s5pMkO0Gq9Wns0pQ3dwxyN2EjMztGxZ1vA7Z+Vn420t/w59f/CdOfpXB3Gtrb4lnX9oMGzvLqU6TmAjDQ1+k9r6QOfgJlM3UiTPoq67q6EBJG20oN0ZUVJsQw9Xq7KpLaFc1C5MMEZVN84JgddvBGlodj4OX6IRFMj7eQd7wD/XHjbobePfSf/BZxmf4+e9+jl+88CN8du5FlNT0FtYyuRRP/3Yj3L0dhE2YGLV+/dQib/24ZbqDA1ws2V82L9FoPaNERbUJmeuzDDKJQn+t5TW4UvadgBkRsbCxUODOeew7IZ9czIVOR28xkvFROXbjaPYRtKvamXinqhlnMt5FSU0GHvvpGswI9xrkMxDSS1XCrlSbQ+sHcGu0HrtaTUeWGycqqk2IpcIGs7zYbyJJpcept4pMCMMWkNL6ViTmVwiUDREDrVaLN95/Y8h7ssq/xvz46VOUETFV2vYaaBpvMDFzWakG+h9ZnlZbi26NRqBsyGCoqDYxhi0g1a3FKGu+LlA2REzmBLgj2Is9ue4TOmGRjMOnX3+JioqhfzGrb6jBm4cOoV2tnqKsiCky7KfmFDaQu88SKJupZzhaT63T4UotjdYzNlRUm5jpLpFwsvJgYkl0wiKZABzHYftCdrX6m/RCNLV3C5QRMUVNXW34z5XjuOODX+ORD/80omdeO3cWaw99hh8cP4Y309ORVFVFq3CEoSox6Kf2jQUnNZ8pMbYKBSJcXJgYHVlufMznK1IkJJwE0X6rcSx3nz6WXn4Gd0Y8BoXMYognCRnelpiZeOWLRKg1vYe/qDU6HEq6jh+siBQ4M2LMujVqHLtxBQeyzuH4jSvo0fXO0JfYjux7ktzBATqex7WGBlxraMC+nGuQSSSIcHbGPHd3zHP3QLizMxRS6WT+ZxAjZrhJUWFGrR+3LPD0QkZdnf6a5lUbHyqqTVC032ocz/0QPHp7qbs1nbhaeR7z/VYJnBkxdY42Frhj9jQcTunrXfzkYg4eWT6LDuMgDB2vQ2JZLg5kncMXuZfQ0t1/BKM0wBWcnSX41q5BP4/C2Ql2ISH94hqdDul1dUivq8O/s7KglEoR6eKKOW5umOvuhlAnKrLNha6nC+oq9lwGC/9FAmUjnDhPT/zjat8oyor2dpS1tcHXVrzHtJsaKqpNkIOVK2a6zUNebYo+llRynIpqMiG2Lwxliuq8ykakF9diTqC7gFkRY5FXX44DWedwIPs8ylrqhryXk3Bw3bIAte/1n1LEcRx4AMuffBKdMhl6dLohP5dKq0VyTTWSa6qBTEAplSLCxQVz3dwwx82dVrJFTF2RAmh7+gKcBAqfGOESEsgMR0c4WVigsbuvJe9SVSV8bYMFzIrcjopqExXjv4YpqgsbMlHfXgkXGxpLRcZn4Uxv+LnYobS+73CBjy/mUFFtxmrbm3Hw2gUcyDqH9OrCYe9XSuVYP3M+tkUsQbjCHw+l/RxJuZ+j87a5+j4+PtizZw+2bNmCbo0GmfX1uFJbg5SaGuQ0NEA7zFQjlVaL1JoapNbUAMiEQipFhLMz5rq5Y46bG8JdXKCkIlsUDPup5R6RkCjNb3VWcnO03tdFRfrYpaoq3DuTimpjQUW1iQr3iIWVwg6d6r7CJ6n0ONaHPSxcUkQUJBIO2xeG4M+Hk/Sxwyn5eP6ehbCxUAzxJBGTDnU3jl5PxoGsc/iu6Cq0/NAryQCw2C8c981agjuDY2FvYQ0AOH3kKvzdo+DrNgu1TQXg5Cr87A/3Y8mSJZDeLHotZDJEe3gg2sMDPwLQ0dODjLpapNTU4EpNDa43NWG4waFqrRZXamtxpbYWAKCQSBDu4tLbLnJzJdtCRj/yTJHh5A9zmU89EMOiOrWmBiqtln6BNBL0HcZEyaQKzPNdgYSCL/SxlNKTWBuyE1IJ/eUi47N1QQj++lUydDdXCztVGnyVegM7FoUJnBmZTFqdFmeLs7A/6xyO5F1GR49q2GdCXHxwX8QSbA1fDF97134fz0kvB9C7ydrDaQbiVgRj+fLlQ35Oa7kcC728sdDLGwDQolIhrbb25j81uNHcPHyRrdPpn/kPsiCXSBDu7IzZN4vsWS4uVGSbAF6ng7rMsKg2v02Kt8R4eELCcfrvzSqtFmm1NVjgSe9SGwP6jmLCYvzWMEV1a3cD8mpTEeZhfr1mZGJ5OFhjRYQfTmaW6GOfXMiholqEeJ5HZm0x9meew2fXLqC6vWnYZ9ytHbA1fDHum7UEs9wCBt3EqtPxyL1azsRCZ/uOOkd7pRLLfH2xzLf32RaVChl1dUirrcGV2lrkj2Alu+e2jY/vZWdDJpEgzMkZc93dMMfVDbNcXWFJRbbR6anLga6L/ZpU+pvvSrW9UokwJydkNTToY5eqqqioNhL0HcSEedoHwtdhJnP4S1LJMSqqyYTYsSiMKarTimuRW9GAEG9nAbMiE6W8tR6fZiXgQFYCcurLhr3fWq7ExuBYbJ+1BEv8I0b0jlhFSQPaWtjJH6FRPmPO+RZ7pRJLfHywxKf3c7Wq1cioq0VaTS3S6mpxvalJv5I3GI1Oh6v1dbhaX4f3kA0pxyHU2fnmxkc3RLq4wkouH3euZHzUBq0fUntfyOxH/4uZmCzw8mKK6sTKKuyeK2BCRI+KahMX47+WKaqvVV9Gm6oZtkoH4ZIiorA83A9u9laobenUxz65mIMX7l0sYFZkPFq6O3A47zL2Z57DhdJr+rGcg5FwHFYERmFbxBJsmBkNa8XoZuHnZrCr1C7udnD1sB913sOxUygQ7+2DeO/eIrtdrUZGXR2u3GwXyRtBka3leWTV1yOrvh4fXLsGKcchxMlJv/Ex0tUV1lRkTznD+dTm3E99S5ynF/6Vmam/Lm1rRWV7O7xsbATMigBUVJu82T5LcTjrHfRoe3sfdbwWqaWnsGzGPQJnRkydTCrBtgUheOPYFX3sUNJ1/OKuBbCQ07cOU6HW9uBUYQb2Z57DN/kpUN0+mmwQsz2mYVvEEtwTthDuNo5jfu1r6ewKeOjs8a9Sj4SNQoFF3t5Y5N3bk93R04OrdXW4crNdJK+xcdjpIlqeR3ZDA7JvHkYj5TgEOzlhjmvvnOwoVzcqsqdAv02KZtz6cUuIkxMclEo0q/r2PFyqqsKWGTMEzIoAVFSbPEu5NSK9FiO17JQ+llR6DEuDttBhHWTcti1ki+rmDhWOpRdhczR98zZmPM8jpTIfB7LO4bNrF9HY1TbsMz52LrgvIh7bIpYg2GX8xa9Oq+vfTx0lzNv21nI54ry8EOfV23d6q8i+tfExZ4RF9q0TH/+bmwMJxyHY0VG/8THK1RW2CpqOM5G07TXQNBYwMXPepHiLhOMQ6+GJYyXF+lhiVSUV1UaAimoRiPFfwxTVtW1lKG3Khb9TqIBZETEIcLXHwmBvXMyr0Mc+vphDRbWRKmyswoHs8ziQdQ6FTdXD3m+ntMLdoXHYFrEEcb4hkHCSCcultLAOXR1qJjYR/dQTwbDI7uzp0c/JTqutxbURzMnW8TxyGhuR09iIj3NzIeE4zHBw0LeLRLm5wY6K7HExnE/NKW0hd58lUDbGJc6LLapTa2qg1mrpACSBUVEtAtOcZ8HZ2hMNHVX6WFLJcSqqyYS4f1EoU1RfzKtAcV0LAlwnvjeWjF5DZys+z0nE/qyzSK7IH/Z+uUSKNUFzsS1iCdYGzYWFbHIKv2vp7Cq1h48DHF2Ms+fTSi5HrKcnYj09AQBdNw+jSbtZZGc3NEAzzImPOp5HXlMT8pqa8HFeLjgAQQ6OmOvet5Jtr1ROwX+NePRr/fCJBUcjYwH0jtbjAP2uiC6NBhl1dYj28BAyLbNHRbUIcByHGL81+CbnfX0sveIs7pz1Iyhlo9tYRIihNVGBcLBWormjr39v/8Uc/HzzAgGzMm/dGjW+zU/F/qxzOFGQBo1OO+wzsT7BuC9iCe4KiYOT1eSfRpebYdBPLVDrx1hYymSI8fBAzM0CpVtfZPe2i2Q3NAx7rDoPIL+5CfnNTdifl3ezyHbAnJvHqs9xc6Miexiq0gvMNbV+9HG0sECIkxNyGhv1scSqSiqqBUZFtUjM91uFb3P2gUfvN3qVpgtXKxIQ7b9a4MyIqbOQy7AlZib+813fbvMDiXn4n40xkEknrl2ADE3H63ChNAcHss7hy9xEtKq6hn1mupMn7otYgm3h8QhwnLpj5jUaLfIyK5nYWOZTG4vbT3wEeovs7IYG/Zzs7Pp6qEdUZDcjv7kZB673Tmyabu/QOyfbzQ2zXd3gaEGLILfo1J1QV6YxMdqkyIrz8mKK6stVVcAcARMiVFSLhb2lC4Ld5yG3JlkfSyo9RkU1mRDbF4YyRXVdaydOZ5dgTWSggFmZh5y6MhzIOodPsxNQ3tow7P3Olra4J3wx7ouIx1zPIEE2LBfl1UDVzU4ZCYn0nvI8JouFTIZ57u6Y5977i4pKq0V2Q33vnOzaWmQ21EOtHf7dg4KWZhS0NOPTm0X2NHt7ZiXbyYyLbHVFCqDT9AUkUih86AyG2y3w9MR/srL014UtLajp6IC7tbWAWZk3KqpFJNZ/LVNUFzVko669HK42xrE5iJiuEG9nzAlwQ1pxrT72yYUcKqonSXV7Ew5mn8eBrARcrSka9n4LmRwbZsZgW0Q8VgRGQS4V9lt7jsF8ap9AZ9g5WAmUzeRTSqWY6+aOuW69RbZaq8W1hgb9xsfM+nqoRlBkF7a0oLClBZ/l9/bGB9jZ9W58dHfDXFc3OFlaTup/hzExnE8t94iERDn5bUumJMzJGbYKBdrUfRuCE6uqcFdQkIBZmTcqqkUk1CMG1gp7dKhb9LGkkuPYEP6IgFkRsdixKIwpqk9nlaK6uR0eDsa5+czUtKu7cCQvCQeyEnCm+Oqwh5Vw4BDvH477Zi3BpuBY2CmNp2jNMeF+6omgkEox280Ns93cAPQW2TmNDUirrcWVmlpk1tehewRFdnFrK4pbW3HoRm+R7W9nhzlubjdPfXSHi4iL7H6bFOnQl36kEgliPTxwsrRUH7tUVUlFtYCoqBYRmUSOeb4rca7gkD6WUnoSd4Q+NKIjhQkZyqZ5QfjdwQvoUPW+ra/jeXyamIen1s0TODPTpdFpcbY4E/szz+HI9SR09qiGfSbM1Q/bZy3BPWGL4W1nfEfGq9Ua3LhWxcSMZZSeUBRSKaJcew+MeTgc6NFqkdPYqN/4mFE3siK7pLUVJa2t+OLGDQCAn62tvlVkjpsb3KyM5xer8eB1ugGKatqkOJAFnl5MUZ1cXY0erRZyGq0nCCqqRSbGfw1TVLepmpBbk4xwT5rUQMbH2kKOTfOD8MmFHH3sk4s5eGLtXEgkdNDQSPE8j4yaIuzPPIfPrp1HbUfLsM942jji3psHs0S4+U9BlmNXkFONHnVfgchJOARHmndRbUgulSLS1RWRrq54KDwcGp0OuY2N+naRq3V16NRohv08pW1tKG1rw5cFvUW2j40N5rq73zz10d1ki+yeuhzw3c1MjFaqB7bg5hjIWzpvTqqZ6z51G5NJHyqqRcbDzh9+jsEobcrTx5JKjlNRTSbEjoWhTFFd1tCGi9crsDiEiqbhlLbU4dOsBBzIOoe8hoph77dRWGBTcCy2RyzFYv8wk3m3KcfgaHL/6a6wtqHRcUORSSSIcHFBhIsLHgzrLbLzbq5kX7m5kj2SIru8vR3l7e04XNB7CqG3jc3NdpHe1WwPE9nAZthPLbX3g8yevscMxNnSEjMdHXG9qUkfu1RVRUW1QKioFqEY/7VMUZ1Tcxmt3Y2ws3ASMCsiBrMD3BDi5YTcyr4xTp9czKGiehDN3R04nHsJn2SexcWynGHvl3ISrJwWhfsilmLdzPmwkpteMZprsEnRlEfpCUUmkSDcxQXhLi54ICwMGp0O15uamCK7o6dn2M9T0d6OivZ2HCksBAB4WVvr20XmurnB08Y490MYnqRIrR9Di/P0YorqxKpKPD57tnAJmTEqqkVotvcSfJn5D/Roe/szdbwOqWWnsXzGVoEzI6aO4zhsXxSKFz7tO5Th2/RCNLZ3wclGvJumRkOt7cGJgnTszzyLYzeuQKUdvviZ6zkd90UsxZawhXC1Nt2TKlXdPSjIZY9HN/d+6okgk0gQ5uyMMGdnfC80FFqdDvnNzbhSU4O0ulqk19aifQRFdmVHByqLCnG0qLfI9rC2vrnpsXc129PaWpARjIbUhv3U/osEysQ0xHl54v1r2frrG83NqOvshKuJtv+YMiqqRchCbo0or3iklJ3Ux5JKjmFZ0D1G8Q2TmLYtMTPxyueXoNL09s2qNTocSrqOR1dECZyZcHieR1LFdezPPIvPcxPR1NU+7DN+9q7YFrEE90XEY4azOGY4X8+qhFbbdwiKVCrBzAgvATMSJ6lEghAnJ4Q4OeH+m0X2jeZmXLm58TG9thZtIyiyqzs68HVREb4u6h3b6G5lpZ+TPdfNDd42NlP+M0PbVg1NUyETo5XqoYU7u8BGLmd+sbpUVYVN06cLmJV5oqJapGL81zJFdV17OYobryHQOVzArIgYOFhb4I7Zgfgy5YY+9smFHPxgeaTZ/dJW0FiF/VnncCArAcXNNcPe72BhjbtDF2JbRDwW+ISI7s/LcJReYLA7LCwVAmVjPqQSCYKdnBDs5IQdISHQ6nQoaGnRn/iYXluL1ttmGQ+mprMT3xYX49viYgCAm5XVzU2PvavZPja2k/41a9hPzSntIHePmNTXNHUyiQTRHh74rqzv719iVSUV1QKgolqkAp3D4WLtjfqOvg1RySXHqagmE2L7olCmqL5e1YS04hrMDfQQMKupUd/RgkM5F3EgKwEplfnD3q+QyrA2aB62RcRjzfS5UMrkU5ClMHLSDfqpqfVDEFKJBDMdHTHT0RH3BYdAx/MobG5GWl3vnOy02lq0qIcf31jb2YljJcU4VlIMAHCxtNS3isx1c4Ov7cQX2f1G6fnGgjORTbpCWuDpxRTVydXV0Oh0kEkkAmZlfqioFimO4xDjvwZfX3tXH0uvOIc7Z/0IFnLqsyLjEzfDG/6udiipa9XHPrmQI9qiuqtHhW/yU7A/KwGnCtOh0Q0/UzjONxT3RcTjrpA4OFga54awidTZoULxjVomRpsUjYOE4xDk6IggR0fcOzMYOp5HUUuLfoRfWm0tmlXDF9n1XV04UVKCEyUlAABnCwvMdXPHbLfe1Wx/W7txF9mqkgvMNbV+jIzhaL32nh5kN9QjytVNoIzMExXVIjbfbxW+zXkfOr63x1Gt7UZGRQJiA9YKnBkxdRIJh/viQvHnw5f1scOpN/D81kWwsRDH2/06XoeEkmwcyErA4dxLaFN3DfvMDCcv3DdrCbaGL0aAg3mNtMrLrACv6zsFUiaXIijUc4gniFAkHIfpDg6Y7uCAe2cGg+d5FLe24kptjX4lu0nVPeznaejuxonSEpwo7S2ynSws9AfRzHVzR4Dd6IpsnboT6qp0JkbzqUfGzcoKQQ4OuNHcrI8lVlZRUT3FqKgWMTsLJ4S4R+NadV/hk1x6nIpqMiG2LgjG344kQXuzkOpUaXA45QbuXxwmcGbjk11bggNZCTiYfR4VbQ3D3u9qZY97whfhvoglmO0xTXR90iNlOJ86KNQTCiX9iDEFHMch0N4egfb2uGfGTPA8j5LWVv3Gx7TaWjR0D19kN3Z341RpKU7dPOHPUansXcW+OcYv0N4ekiH+fnSVXkJioRq17YCbDRATIIPCJ2bC/jvFboGnJ1NUX6qqxI+jzHcDuRDoO57IxfitYYrq4sZrqGkrhbutn4BZETHwcLDGigh/nLharI99cjHHJIvqqrZGHMw+j/1Z55BVWzLs/ZYyBTYGx2BbxBIsD4yEjHo+kdNvPjX1U5sqjuMQYG+PAHt7bJkxAzzPo7StjWkXqe8a/p2bJpUK35WV6Xt9LWUy+NjYwMfWFr62tvCztdP/7++OHsXTP3kElXV9rVWeDlK8Mec4tmzZMmn/rRNFx/Po0enQo9VCrdVCrdOhR6eFWqtDj04HtVbL/lunRY/29nsG+LdON/g9N1/r9s9pOFYxr6kJDV1dcLakcadThYpqkQv1iIGt0hFtqr7B8Eklx7Ep4lEBsyJisX1hKFNUpxfXIqe8AaE+zsIlNUJtqi58lXcZB7LO4WxxFnjwQ94v4TgsDZiFbRFLsHFmDGyV9IPqlraWLpQV1jMx2qQoHhzHwd/ODv52drg7qLfILm9v07eKXKmtQd0IiuwujQb5zc3Iv201FQAak5Jxfc+efvdXNatxz9at+Mu//40tW+6GnUIJe4UCMokEWp4ftFDt+3f/wrP/PbcVtzeL2ME/Zvjvvo9pdLp++RuDtLparPLzFzoNs0FFtchJJTLM812JMzcO6mOpZaewPuxhSCX0fz8Zn+XhfnC3t0ZNS4c+9vHFHLy4bbGAWQ1Oo9Piu6Kr2J95FkevJ6NLM/yYsQg3f9w3aym2hi2Cpy2dSjqQ3KvsKrVCKcO0YHFuWiW9RbavrR18be2wOSgIPM+jor1d3y5ypbYWtZ2dI/pcvE6H4g8+GOIGHr967qc4qJCDuznJQsJx0PFD/xJMiBCoqjIDMf5rmKK6XdWMnOokRHjRBhAyPjKpBNvigvH6t1f0sUOX8/DLuxbAQmEc3154nkd6dSE+yTyLQ9cuoq6zZdhnvG2dcW/EYtwbHo9wN1rlGY5h68fMCG/I5NQSYy44joOPrS18bG1x5/Tp4HkelR0dvQV2TW+hXT1Ikd2amwt1Y+OQn1/d0IjW3FzYh/W2llFBPTLz3d2x1JveMZpKxvFTj0wqN1tfBDiFobjxmj52ueQYFdVkQmxbGMoU1a1danybUYi7omcKmBXQ1NWGA1nn8UHGKWSPoE/aVmGJO0MW4L6IJVjsHwYJR/NdR8pwkyK1fpg3juPgbWMDbxsbbJzWewBJbWcnSltbUdbehrK2NpS39f47rWX4X3IBoMegZcSUyCQSKCQSyCVSyKU3/7dUyv5b/zHDfw/1MSnkEgkU0t5/931OCRyUFvC2Ef8oT2NDRbWZiPFfwxTVuTUpaOlqgL2l8fe+EuPm72KHRcHeuJDXd9DQJxdyBCmqb43B25d+Cl/lJUGlHfqoZplEipXTZmN7xBLcMWMeLOXKKcpUPJobOlBV1sTEaJMiMeRmZQU3KyvMB9sWdMrSCqtef2PY5+UODiN6HQnH9RaaBoXr7cWnYXE69MekUNz6t0HhOuC9A7zuUBNPiLhQUW0mIr3i8cXVt6HW9o5F4qFDatkprJi5TeDMiBjsWBTGFNUXr1eiuLYFAW72U/L6lW0N+OjqGezLOI2S5tph75/vNQP3RSzB3aFxcLGemhzFyvBocktrBfyDaDYuGZllS5fCx8cHFeXlA24V5jgOPj4+SHv+t+jQatGqUkGj0w1aMNMJgkRIVFSbCQu5FWZ7L0FS6XF9LKnkOJbPuNds5+qSibM2KhAO1ko0d/SdyvbJxRz84q4Fk/aaPVoNjt24gn0Zp3Gi4MqwfZZ+9q7YPmsp7otYgulOdCjJRDHspw6e5Q2plAobMjJSqRR/e+FZbH/0WXAAU1jf+tm0Z88eKOVyKOVyOFlYCJInISNBRbUZifZfwxTV9R0VKGrIxjSXCAGzImKglEtxT2ww/n36qj726aU8/M+maMilE7th7UZDJT68ehofXT2D2o6h+zEVUhk2BcfiwaiViA8Ipz7pSdBvPnUUHU1ORmdduAJvbZXid8e0qGrri/v4+GDPnj0mMaeaEICKarMS4BQGVxsf1LX3/RBMKjlGRTWZENsXhjBFdV1rJ77LKsWaqMBxf+7OHhUO517CB+mncLEsZ9j7w1x9sTNqJe6LWAInK9txvz4ZWH1NK+qq2F9saJMiGa3uorNYFyLBmpkckkp5tLjEY+bm3yI+Ph7SCf6lnJDJREW1GeE4DjH+a3E0+9/6WEZlAu6K/DEs5NYCZkbEINjLGXMD3XGlqEYf+/hCzriK6vTqQuxLP4VPsxPQqhr6cAkbhQXuCVuEB2evxFzPIGprmgKGq9Q2dhbwCXQRKBtiinidDqri8wAAqYRDXAAHpy3fh82cZYLmRchYUFFtZub5rsA3196Fju89/alHq0J6xTksCFgncGZEDHYsCmWK6u+yS1Hd3A4Ph5GPdmruasen2b2j8DJrioe9P9YnGDujVuKu0AWwUdAph1PJcJReSJQPJBL6ZYaMXE/dNeg62dM4LQKWCJQNIeNDRbWZsbNwQqh7LLKrE/WxpJJjVFSTCbFxbhBe+PQCOlS9o+x0PI/PLl/HE2vnDvkcz/M4X3oN+zJO4XDuJXRrhh6F52xpix2Ry7AzagWCXajdQAg8zw/QT03/X5DRURWdY66lDgGQOQYIkwwh40RFtRmK8V/DFNWlTXmobi2Bhx2dHEfGx9pCjk3zpuOTi7n62IHEXDy+Zs6A7RjV7U34+OYovMKm6iE/NwcOK6ZF4sGolVg3cz4UUvmE509GrqayGU317UyMNimS0eouOstcWwTGC5QJIeNHRbUZCnGPhq3SEW2qvgMbkkqO485ZjwmYFRGLbXGh+qKa1+mQk5aM3+9pRvycMMTHx4PngBMFafgg/RSO37gC7c1WpMH42LnggagV+F7kMvjau07FfwIZgZx0dpXa3skKnr6OAmVDTBHP81AVJzAxZcBSgbIhZPyoqDZDUokU8/1W4bv8T/Wx1LKTWB/+MGQSWv0j4zNvmjumuzsgM/E7NJ//FNqOZjx/uPdjdq5OsNk0Fx3THYb8HHKJFBtmxmDn7BVYFjALUglNADA2A43So82hZDR6agfopw6kfmpiuqioNlMx/muYorpD3Yqc6iTM8lokYFZEDDiOwwxtBc4c+2e/j7XWNaL1PydhdX8c5OHe/T4e4uKDB6JWYHvEEjrp0IjxPN9vkyIdTU5GS1Vs2E/tT/3UxKRRUW2mXG18EOgcjqKGbH3scskxKqrJuGm1Wnzxz78OeU/X0XTIQr3ASThYy5W4O2whHoxaiWjvmbTaaQIqShrQ1sKOOKR+ajJa/fqpA6ifmpg2KqrNWIzfWqaozqtJRUtXPewtac4sGb3m7g58ln0er+1/F3XVNUPey7d0IahdiV3bH8HdoQthq6RReKbEsPXD2d0Wrh52AmVDTNGA/dSB1E9NTBsV1WYs0jseX2S+BZWmd8WJhw4ppSexMni7wJkRU8HzPC6UXsO+jNP4MjcR3ZoeqEtKR/TsT6M2YsfslZOcIZkMhpsUQyN96B0GMiqauhzoOuqYGPVTE1NHRbUZU8osMNt7KS6XfKuPJZUex/KZ2yDhJAJmRozdrVF4H179DgWNVczHJLYWI/ocnp6ek5EamWQ6rQ55Vw2K6tnU+kFGp9twPrW9H6QOAcIkQ8gEoaLazMX4r2GK6oaOKhTWZyHINVLArIgx0ui0OH7jCvZlnB5yFJ40wBWcnSX41oGPFec4Dj4+PoiPp/5JU1RaWI+OdhUTo0NfyGipDPqplQHx9G4HMXlUVJs5P8cQuNv6oaat7y375NLjVFQTvcLGKuzLOI2PM8+iur1pyHtlEinWB89H4CsL8NKTPwPQ2yJyOx7Anj17IJXSmDxTZDj1w93bAU6utgJlQ0wRz/PoNuintqB+aiICVFSbOY7jEO23Bkey/6WPXa08j7sifwJLubWAmREhdfWocDjvMj5IP4ULpdeGvX+mszd2zl6J7RFL4HpzFF6UxzTs2rUL5eV9rQJSG0es2vkktmzZMmm5k8mVY9j6QavUZJQ0dbnQddQyMeqnJmJARTXBPL+V+Prau9DxWgBAj1aFtPIzWBi4QeDMyFRLry7Eh+mncSA7Aa2qziHvtZIrsSVsIXZGrUTMAKPwtmzZgs2bN+NXr7+Pfx49D6mVPZSeQbghk6G5oxsO1iPrvSbGQ6PR4npmBRMLo35qMkrdhvOp7X0hdQwUKBtCJg4V1QS2SgeEeyxAZtUFfSy55DgV1Waiuasdn2afx76M07haUzTs/fO9ZuDB2StHNApPKpXiF4/dj4OFPVBrenuw1RodvkjOx8PLZk1I/mTqFOfXorurh4mF0Eo1GSXqpyZiRUU1AQBE+69hiuqy5uuoaimCpz2tHogRz/M4X3oN+9JP4XDeJXRreoa838nSFvdFLMHOqBUIc/Mb1Ws5WFtgTWQgjlwp0McOJOZSUW2CDPupfQKcYedgJVA2xBRRPzURMyqqCQAg2G0e7Cyc0drdoI8llRzD5sgfC5gVmWhVbY34OPMs9mWcQlHT0Ae0cOCwPDASO6NWYP3MaChl8jG/7ra4EKaoziqrx7XyeoT50EFDpsRwPjWtUpPR0tTnQdfOfu9RUj81EQkqqgkAQCqRItpvFU5d36+PpZZ/hw3hj0AmVQiYGRmvHq0GxwvSsC/jFE7cSBt0FN4tPnbO+F7kCnwvajn87F0nJIf4UB94OFijurlDHzuQmIsX7l08IZ+fTL4etQb51yqZGM2nJqPVbz61nQ9kjtMEyoaQiUVFNdGL9lvDFNWd6lZkV19GlDfNEzZFBY1V2JdxCh9fPYuajuYh75VLpFg/MxoPzl6JZQGzIJVM7Lg7qUSCrbHBeOPYFX3si+R8/PLuOChkNFrPFBTkVqNHrdVfcxwQMstbwIyIKaJ+aiJmVFQTPRcbL0xznoXChkx9LKnkGBXVJqSzR4Uvcy9hX/opXCzLGfb+EBcfPBC1AtsjlsDl5ii8ybItLoQpqhvbu3EqswTr5tAqlSkw7Kf2m+4G6xGenkkIQP3URPyoqCaMGP81TFF9vfYKmjvr4GA1MW0AZOLxPI+M6kJ8kH4KB6+dR6tq4JMMb7GWK7ElbBF2Rq1A9ACj8CZLgJs9YoI8kXSj71jz/Ym5VFSbiJwMw6PJqZ+ajI6m/jp07dVMjPqpiZhQUU0YkV6L8cXVt9Ct6Z1RzINHcukJrA65X+DMiKHmrnYcyE7AB+mnkFVbMuz90d4zsDNqZKPwJsu2uBCmqD6TXYqalg6429NBQ8ZM1d2Dgly2GKJDX8ho9ZtPbecNmdN0gbIhZOJRUU0YCpkFZvssw6Xir/WxpNLjWBm8HRJOImBmBAB0vA4JJdn4MOM0Dudehko79Cg8Z0tb3DdrCXZGrUSoq/CbyjbMmY7nDySgU6UBAOh4HocuX8dP1swRODMylPzsSmg1fRtcJRIOMyOon5qMDvVTE7Gjopr0E+O/himqmzprUFB/FTNcZwuXlJmrbGvAR1fP4MOM71DcPPwovBXTIvFg1EqsmzkfCunYR+FNNGsLOTbODcKBxFx97EBiLn68ejb9cDVihq0f04I9YGlFU4HIyPE8DxX1UxORo6Ka9OPrMBMedgGobi3Wx5JKjlFRPcV6tBocu3GldxReQRp0PD/k/T52LnggagW+F7kMvhM0Cm8ybIsLYYrqgppmXCmqwbxpHgJmRYZiuEmR5lOT0dI05EPbVsXEqJ+aiA0V1aQfjuMQ47cGh7Pe0ccyKy+gU90GK4WtgJmZhxsNldiXcRofZ55BbUfLkPfKJVJsmBmDB2evxNKAiAkfhTcZoqd7INDNHkW1ff9t+xNzqag2Up0dKhTl1zKxMNqkSEZJZTif2tYTMqcggbIhZHJQUU0GNM93BY5m/wdavrf3VaPrQVr5WSyatlHgzMSpQ93dOwov4zQSRzAKL9TFFztnr8R9EfFwtrKbggwnDsdxuHdBMP58OEkfO5J6Ay9sXQQrpfG0qpBe1zMrwOv63iWRyaUICvMSMCNiirr79VMvoZYvIjpUVJMBWSvtEe65AFcrz+tjSSXHqKieQDzPI/3mKLzPRjAKz0ZhgS1hi/Bg1ErM8woy6R9I98QG469fJetbWtq7e/BNeiHuiQ0WODNiyLCfenqoBxRK+tFBRo76qYm5oO+MZFAx/muZorqi5QYqmgvg7UAjkMajqasN+7MSsC/jNLJHMAov1icYD0StwN2hcbBRCDMKb6J5OtpgSagPzlzr69U9cDGXimojZFhUh0UJP0WGmBZN4w1o29gj7qmfmogRFdVkUDPd5sDe0gUtXfX6WHLpcXg7/ETArEyTjtchoTgbH2ScwpG8pBGNwtsRuQwPRC5HiBGMwpsM2xaGMkV1Yn4lSupb4e9iWu0sYtbe2oXSgjomRpsUyWgZ9lNLbDwgc54hUDaETB4qqsmgJJwU0b6rcfL6x/pYatlpbAj/AeRSGqc1EhWtN0fhXT2NkubaIe/lwGHltCjsnL0S62bMM6pReJNh9awAOFgr0dyh0scOJubifzbFCJgVuV3u1QrmWqGUYXoIbSglo2PYT20RSP3URJyoqCZDivZni+qunnZkVyVitg/1ww2mR6vBN/mp+DDjFE4Wpg87Cs/X3hUPRC7H/UY+Cm+iKeVS3DV/Bt47m6WPHbych2c2REMioR+4xsBwlN7MCC/I5MY/YYYYj4H6qZXUT01EiopqMiRna09Md4lCQX2GPpZUcoyK6gFcr6/AvoxT+CTzHOo6hx6Fp5DKsHFmDHbOXoGlAbPM9rTKbQtDmKK6orEdF65XID6EWgyMgWE/NbV+kNHSNBZA28q+42ERQP3URJyoqCbDivVfwxTV+XXpaOysgZOVu4BZGYcOdTe+yE3EvvRTuFSeN+z9Ya6+2Bm1EvdFLIGTFc38jvB1RZiPM66VN+hjBy7mUFFtBJobO1BZ2sjEaJMiGa3+/dTukLnMFCgbQiYXFdVkWLO8FsEi4010azoAADx4pJSexJqQ7wmcmTB4nseVqhvYl34an127gDb18KPw7glbhAdnr8RcT9MehTcZtsWF4IVPL+ivv00vQnOnCg5WSgGzIrkGq9QWVgr4z3ATKBtiqvr1U9N8aiJiVFSTYcmlSszxXYbEoqP6WHLJcawK3mFWbQuNnW3Yn3UO+zJO41pd6bD3L/AJxgNRK3FX6ALRjMKbDHdFz8AfDiWiR6sDAKg0WnyVko+dSyIEzsy8GbZ+BM/yhlRqPn/fyfhRPzUxN1RUkxGJ9V/LFNVNXbW4UZeOmW5zBcxq8ul4Hc4VZ+GD9FM4cj0Jaq1myPtdrOywY9ZS7IxaiZku3lOUpWlzsrHEqsgAfJNWqI8dSMyjolpghpsU6WhyMlqapkJoWw3e8aD51ETEqKgmI+JtHwQvu2mobO0rfJJKjou2qC5vre8dhZdxGqUtdUPeK+E4rJo2Gw9ErcQdM+aKfhTeZLgvLoQpqjNKapFX2YBgL2cBszJfDbWtqK1iN9uGUD81GaWB+6npgCciXlRUkxHhOA7R/mvwZebb+lhW1UV0qttgpRDHhju1tgff5KdiX/opnCrMAI+hR+H52btiZ9RK3B+5DN52VPyNx5JQX7jZW6G2pVMfO5CYh9/cs1DArMyXYeuHte3/t3ff8XXX1f/AX587s/e6yc1OOtKR7h26mEIpxIIyVUSGIoWvCgr4U3GAqNDiAhRRZCjUMooyO2i6B206Mpo9b/Zed35+f6S97efepMltxueO1/Px8PHwnvvJzUlpktP3PZ9z/JCYGiVTNuSpnPupc9hPTV6NRTWN2rzE1fjg9F9htQ22QFhsZnxRswMr0tfLnNnYFLfU4p/5O/Cvk5+jpa/rotdqlCqsm7oYd2avRU7KDJ/qKZ9IKqUCGxZPxZ8+OWaPvXPoDH54w2KolZyLPNkKjzuM0pudwNnh5BL2U5MvYlFNoxaoCcEs3TIcrzv/lt6h6k88sqjuMfXjncL9eC1/Bw6OahReEu6csxY3z8jhKLwJcvPSaZKiuqW7HztPVePK7FQZs/I9oiiiMF/aTz19Dls/yDXW9gpYO6V/jzifmrwdi2pyycLkKyVFdX1nOWo7SqEPy5Axq9ERRRFH60vxav52bC3Yix7TwEWvD9b4Y8OMFbgjew3m6tL5tuUES4sNw4L0OBwpa7DH/r2/iEX1JGuq70Rbc48klsWimlw04NhPHRgDVfQ0mbIhmhwsqsklmdFzEeYfg47+JnvsUNXHbl1Ut/Z14d+n8vDP49tR2FIz4vVL9dNwx5y1WD9tCQI1fpOQIZ1z85JpkqJ6x6kqNHX2ISY0QMasfIvjKXVoRAB0ieEyZUOeiv3U5ItYVJNLFIICC5OuwKfFr9tjx2p3Yd3Mu6FWus+yDptow66Kk/hn/nb898zhEUfhRQeE4pbZK3H77DUchSej6+an4ydv70G/afC/l9Um4p1DZ3DvFXPkTcyHON6kOH22nsUQuYT91OSrWFSTyxYmXYHPit+wT8foN/fgZP0+zEtcLXNmQE1nM14/sQuvn9iJmlGMwrsifS5uz16DqzPmQ63kt4Pcgvw0uHZeOrYcON/n/taBItxzeTYLu0kw2E/tUFSz9YNcZO2ohLVTuiCL86nJF7CKIJdFBMYiI3oOSprP31R2qOpj2Ypqk9WMD88cwav527Gj/MSIo/CSw2JwR/Ya3Dp7FeKDOQrP3dy8ZJqkqC4xtCO/qglzUmJlzMo31Fe3oau9TxKbns2lL+Qa537qaKiip8uUDdHkYVFNl2RR8pWSorq0JR+tvQ2IDIybtByKmmvso/Ba+7sveq1Wqca6qYtwx5y1yEnmKDx3tjhTh+ToEFQ1nx9v+O99RSyqJ4HjKL3ImGBE60JlyoY8lbFSWlRr2U9NPoJFNV2Smbpl8FcHod98fkrA4epPcPX0Oyf08/aY+rG1YB/+mb8dh+tKRrx+Zkwy7shei5tnrkC4P0fheQJBEHDTkmn47bZD9tj7R0rx/zYsg7+G2yonkuNNitOy2U9NrnM8qfZjPzX5CBbVdEnUSg3m6Vdjb8U2e+xw9ae4ctptUAjju6xDFEUcrjuDf+bvwNaCveg1Gy96fYjWHxuyVuDOOWuRHZfGosADbVg8Fb/74BDEs5083QMmfHS8AjcumiJvYl7MZhNR5NBPncXV5OQiS3slrB1VkpiW86nJR7Copku2KPlKSVHd2d+CkqbjmBo7f1xev6W3E/86tRuv5e9AUUvtiNcvS5xuH4UXoHafSSTkuviIIORMS8TuwvMnp2/tL2JRPYFqypvR2yP9B+s09lOTi5z6qQOioI7JkikbosnFopouWUJYBhJC01HXWWaPHaz6eExFtdVmxa7Kk3j1+Hb878xhmG3Wi14fExiKW2atwu3Zq5EZyVF43uTmpVMlRfW+M3Woae1CYmSIjFl5L8epH7HxoYiMYcsUuYb91OTLWFTTmCxKvgrvnPiT/fFpw370GjsRqHXt5qbqzma8nr8Tr5/Ygdqu1oteOzgKbx7unLMWV6bP5Sg8L3VldipC/DXo6jcBAEQR2HKgGA9fu1DmzLxT4XGuJqexYz81+TJWIzQmc/WrsO3UX2CxmQEAVtGCL2p3Iif9hhE/1mgx439nDuOf+Tuws2LkUXip4bG4ffYa3DJ7JUfh+QA/tQo3LMzEq7tP22NbDhRj4zULoFDw5Gs8Wa02FJ+ql8TY+kGuGuynrpTEtCk58iRDJAMW1TQmAZpgzIpfjmO1u+yxQ1UfY0Xa+mHf8itoqsY/83fg36d2o20Uo/DWT1uC27PXYEVyFkfh+Ziblk6TFNU1rd3YX1KH5VNZ8I2nypImDPSZJDHOpyZXDVQ69lNHQh0zQ6ZsiCYfi2oas0XJV9qLaptVxKF9R/HH8ucwM2MecnJyoFQq0W3sxzuF+/Dq8e04Uj/yKLxZsSm4M3stbpqxAmH+QRP8FZC7mp0UjWnxESiqb7PH3tpfzKJ6nDm2fiQkRyI0PFCmbMhTOa0mT8mBoOBBCPkOFtU0ZulR2QgPiMWh7fnY8XIhelqNeAuHAQAxujjM+8Y6nAjrG8UovADcNGMF7pizFnPi0iYjdXJzgiDg5qXT8OR/9tljHx4rx8+/sgIh/pzwMl4cb1Jk6wddCvZTk6/jPyFpzBSCAsaiMLz/zHH0tEoL5yZDAz761V/Qcbx82I9fnpSFF9Y9gKIHX8Lvrv4WC2qSuHHRFKguOO0aMFuw7WjZRT6CXGE2WVByWtpPnTWHRTW5xtJRBWt7hSTGfmryNTyppjGzWq14+Zm3LnpN/3+PQzU9HsLZG8xiA8Nw6+xVuD17DdIjdJORJnmoyGB/XD4rGR/ln/+F/fb+Ity2grNvx0N5cSNMRov9sSAAU2exqCbXOM2n9o+AOmamTNkQyYNFNY3JmZY6/PLVP6G+znDR68TOfohVrbjmyqtwZ/ZaXJkxDyrF+G5eJO9109JpkqL6i4pGlBjakakLlzEr7+C4mjwpPRpBIX4yZUOeiv3URCyq6RJ0GfvwTsE+vH5iJw7VnYEpv3pUH/f00lvx7Zu+NcHZkTdaPSMJ0SEBaO7qs8fe2l+Ex3OXypiVdyg8Lu2nns7V5HQJjOynJmJRTaNjE23YU1WA10/sxPtFB9BvOT9+SxE8ulOtrLTMiUqPvJxKqUDuoil48bPj9thb+4vw4DXzEeyvkS8xD2cyWVBW1CCJ8SZFcpWloxqWdul9M+ynJl/EopouqrqzGW+e2IU3Tu5CVUfTkNcoU6IhhPhD7Oof8nlBEKDX65GTwx+ydOluXjpNUlS39w7gpc+O43vrFsmXlIerKG6ExWy1PxYUAqbMjJcxI/JEjqvJFf7hUMfOkikbIvmw4Ymc9JuNePt0Hm5440lk//E7eCrvrWELagCICQpD7sN3QxCEYRe+bNq0CUole6jp0mXqwnFVdqok9tL2fDR19g3zETSS4pN1ksdJadEICOSoQnLNAPupiQDwpJrOEkURXxhK8Xr+Tmwp2Isu48ULFaWgwFWZ83Hb7NW4Mn0u1EoVts5ehY0bN6K29nyPZnCUH+7/0Z3Izc2d6C+BfMAj1y/GpycqYRMHV9r3myx4/sMj+MVXL5M5M8/kWFRPncVTanKdYz+1lv3U5KNYVPu4pp4O/Pt0Ht7I34nClpoRr58Wpcdt2WvwlRk5iAkKkzyXm5uL9evX43evPYHPT/wPQeFaJEyPgJ9/J6w2C5QK/nWjscnUhePmpVPxr31F9tgbewpx95pspMSEypiZ57FabSgtkE7tmTIzQaZsyFNZOmtgaZPOjfdjPzX5KFY5PshsteCTsmN4/cROfFL6BSw260WvD9EGYEPWctyWvRrzdBnDtngAgFKpxDe+/ACaQo/bY72mThQ3fYGsOPa+0tg9fO1CvHO4BMazvcAWmw2/2XYIf/zmFTJn5lmqSptgHDBLYuynJlc5nlIP9lPPlikbInmxqPYhhc01eP3ETvz75G4093Ve9FoBAlamzMRt2atx3ZRF8FePvs8yOigByeHTUNV+/jTxaM12FtU0LnThQfjGqll44dPj9ti2o6W494o5mJ0ULV9iHqb4pHSLYnxSBELCAmTKhjyVUz918gr2U5PPYlHt5ToGerG1YC9eP7ETR+tLR7w+OSwGt85ahVtmr0JS6KUXKPMS10qK6tOG/eg398JfHXjJr0l0zrevmoc39hSgq//8aMen3z2ANx5cJ2NWnuWMQz81T6npUrCfmug8FtVeyCbakFd5Gq+d2IFtxQcxYDFf9Hp/lQbXT1uC22avxorkLCiEsZ8yzNFfhvdPvgirOLj+2GIz40TdHixOuWrMr00UFqDFt6+ah6ffPWCP7SmqRV5RLXKmcc7ySGw2EWdOORTVs9hPTa6xdNbC0iY9rGE/NfkyFtVepLKjEW+c2IU3T36Oms7mEa9flDAFt81ejRumL0Wo3/ieIAdqQjA9biFOGfbbY0drPmNRTePmG6tm4pWdJ9HY2WuPPf3uASx/5MtQKIbv+yegrqoVvT1GSWwqb1IkFznOpxb8wqCOYz81+S4W1R6uz2zEtuKDeC1/B/KqTo94fWxgGL46ayVunb0KU6Mm9kRvfuJaSVFd3noKbb2NiAiMndDPS77BX6PG/123AI++/rk9drK6GR98UYbrF2TImJn7czyljooNQWRMsEzZkKdy7Kf2S1kBQcF9BOS7WFR7IFEUcaS+BK/l78A7hfvQZRx6k+E5KoUS12QuwG2zV+Py9DlQTdIPvemxC+GvDkK/ucce+6J2By6fesukfH7yfjctmYa/fJaP0sYOe+y32w7hmrmpUHPZ0LAcb1KcytYPugTGis8lj9lPTb6ORbUHaehpx79P7sbrJ3biTGvdiNdnRSfh9uw1uHnGCkQFTv4MX5VSgzkJl2F/5f/ssaM127F2ylcvOpaPaLRUSgV+cP1i3PuXj+2xyuZO/GtvIe64bKaMmbkvURSdb1Lk0hdykaWrDpZWx35qLmEi38ai2s2ZrGZ8XPoFXsvfic/KjsEq2i56fahfIG6esQK3zV6N7Lg02YvX+YlrJUV1c08dajrOICl8qoxZkTe5ek4q5qbE4FhlEwBAtNnw8xdeg6ViBlKTE5GTkwMlT63tmuo70dHWK4mxn5pc5Tj1Q/ALZT81+TwW1W7qdFMVXsvfibdO7UZrf/dFrxUgYE3abNw2ezW+NGUh/FSaScpyZMkR0xEZqENr7/nNbUert7OopnEjCAJ+dMNS3LzpPfSVH0PHnrdh7e3AXW8OPq/X67F582bk5ubKm6ibKHbopw4JD0BsQpg8yZDHMjr2Uyezn5qIRbUb6ejvwdun9+D1EztxvKF8xOtTw2Nx2+zV+OqsldCHRE1Chq4TBAHz9GvwafHr9tixus+xbta3oFKoZcyMvMmSKfFIM9fi84//4vRcXV0dNmzYgC1btrCwhvN86qkzE2R/R4s8zwD7qYmcsKiWmdVmxeeVp/Ba/g7898xhGK0XnykdoNZi/bQluD17DZYlTveIX4bzk6RFdZ+pC8WNRzFDt0TGrMibWK1WFP3370M+J4oiBEHAQw89hPXr1/t8K0jxKd6kSGNj6aqHpbVEEmM/NRGLatmUtxnsM6XrultHvH6Jfipuy16DG6YtRbDWfxIyHD9RgfFIichCZVuBPXa0ZjuLaho3eXl5aDTUD/u8KIqoqanB55/vxpo1qycxM/fS1tyNZkOnJDaVNymSi5zmU2tDoNZly5QNkftgUT2Jekz9eK/oAF7P34l9NYUjXq8LCscts1fh1lmrkBHp2b/45iWukRTVpxsOoM/UjQANZ+PS2BkMhpEvAvDdP2/FT/x1WL8gE1q1751Yn3E4pQ4I0iIhxT1bx8h9OfZTazmfmggAi+oJJ4oiDtYW47UTO/Bu4X70mAYuer1aocSXpizE7dlrsDp19qTNlJ5ocxIuw3snX4DVNri23Gqz4ER9HpakfEnmzMgbKNsv3jZ1TrNJhe//cyeeef8gvrFqFm7PmYHQAO0EZ+c+ih36qTNnxHP7JLnMsZ/aj/3URABYVE+Y+u5W/OvkbrxxYidK20Y+RZsVm4LbZ6/BTTNWICLA+05vAzTByIpdjJOGvfbY0ZodLKppzJqLatD2rxMIUweh44JFQ46UQeHQ6gY3LTZ19uHX7x3EHz76Arcsn45vrpmNhAjv+75z5HhSzX5qcpW12wBLyxlJTMt+aiIALKrHldFixkclR/DaiZ3YXn4cNlG86PXh/kG4eUYObstejdmxqZOUpXzmJ66RFNUVrafR2mtAZKBOxqzIk3XWtmDbxhdh7TdjQ9Jl+GvZ/4a4SgAgImz5BggKheSZXqMZf91xAn/fdQrr5qfj3ivmIEvvne0Q3Z39qKuS3r/BoppcNeA4n1obAk0c+6mJABbV4+JEYwVey9+Jt0/nob1/+JMyAFAIAtamzcHts1fj6swF0Kp8Z6zctLiFCFAHo898fu720ZoduHLabTJmRZ6qv70H2za+gP62wb9Pc8IzcHf6l/Bu0360dLfbr0tM1OPZZ59D+NQFePGz4zhQ4nxDo8VmwzuHS/DO4RLkTNPj3ivmIGea3iOm64zWmdPSr1ujVSE5I1qmbMhTOfVTJ6+AoGQpQQSwqL5kbX3deOt0Hl4/sRMnGytHvD49QofbZ6/GV2ZdhvjgyIlP0A2pFGrM0a/EvooP7LEvanbgiqm3elXxQhPP3G/EBw+/hM7qZkn82iuuwR+f3Yp9B/fDYDBAp9NJNiqunZWM/MomvPDZcXx4rHzId5PyimqRV1SLLH0k7r18Dq6bnw61F4zhc5xPnTFdB5XK878umlzO/dQ5MmVC5H5YVLvAarNiR8UJvJa/Ax+WHIHJarno9UEaP9wwfSlun70Gi/VTWThisAXkwqK6pbce1e1FSI6YLmNW5EmsFis+fuzvaDpdJYlHZsbjmt98Exp/LVatWjXsx2enxODPd1+JqpYuvLw9H//aV4QBs/P3ckFtKzb+fTt+/d5BfHPNbNyyfDqC/NxnW6mrHG9SZOsHucra3QBLS7Ekpk3hTYpE57CoHoXS1nq8fmIn/nXycxh62ke8flnidNyevQbXT1uMII1nzZSeaEnh0xAVmICW3vO/4I/UbGdRTaMiiiI+f+rfqNpTIIkHxYVj3eb7oA0a/fdbclQInvxKDh6+diFe3X0Kf991Eq09ztN56tt78PP/7MPvPjiEBWk6LMrQYXGGDtkpMfBTe8aP0P4+E6rKpKf6U1hUk4sGnOZTB0OjmyNPMkRuyDN+I8ig29iPdwr34Y0TO3GgtnjE6xOCI3HL7FW4bfYqpIbHTUKGnkkQBMxPXIOPi/5pj+XX7sb6WfdybTmN6NAL/0Ph+wclMW1oANY9fx8Co0Mv6TXDg/yw8UsLcO/lc7DlYDH+sj0fFU2dTtf1GS3YXViD3YU1AACNSoHZyTFYnDFYaM9Pi0OIv3uO5ystMEC0nW91UaoUSJ/Gn1PkGvZTE10cvxsuIIoi9tUU4rX8HXiv6AD6zMaLXq9VqnHt2ZnSK1NmQuklM6Un2jyHorrP3I2ihsOYGb9MxqzI3Z36zx4c+dsnkphSq8a1v7sHEaljLxD9NCrcnjMDty7PwqcnKvHCZ8dxtLxh2OtNFhuOlDXgSFkD/vjxMSgEAdMTIrHobJG9KEOH6JCAMec1HhxbP1KnxEKj5Y9/co1TP3UK+6mJLsSfqgBqu1rw5onP8cbJnahobxzx+jlxabg9ew02ZC1HmH/QJGToXSID45AaOQMVraftsSM121lU07DKd53A7me2SGKCQsBVv/wadNnjO45SoRBw1ZxUXDUnFUfKGvDiZ8fxyYkKjDAhEzZRxOnaFpyubcEru04CAFJjQrE4Q4eFGTosyohHUmSwLPdWON6kyH5qcpW1pxGW5iJJTMulL0QSPltUD1hM+G/xYbx+Yid2VpyAiIv/xoz0D8ZXZl2G22avxoyY5EnK0nvNT1wrKaoLGw5xbTkNyZBfjk+eeFXSvgAAKx+9GakrZ03o516QHocF6VejpbsPh0oN9v8V1LaOOIceACqaOlHR1Il/7RssRmJDA7E4U4dF6YMn2VN0ERO+0dBksqD8jPSwgEU1ucppPrUmCBrdXJmyIXJPPlVUi6KI/IbywZnSBXvQOdB70euVggKXp8/F7dmrcVXGPGiU7PkdL9nxOXj3xJ9hsQ2ul7aKFhyv241lqdfKnBm5k7byBvz3//4Cq1G6hnzB3VdhRu7kvbMRFRyAL81Nx5fmpgMAuvtNOFregEOlBhwsrUd+VRNMFtuIr9PY2Yv3j5Ti/SOlAIDQAC0WpsfZ20VmJUWP+/i+iuJGWMxW+2NBISAjiwuXyDXspyYamU98R7T0duLfp/Pwev5OFDRXj3j9lMgE3HZ2pnRcUPgkZOh7/DVByIpbjBP1e+yxozXbWVSTXU9TB7Y9+GcYu/ok8az1S7HonmtkympQsL8Gq2YkYdWMJADAgNmC/KomHCox4FCZAUfLG9AzYB7hVYDOPiM+O1mFz04Ojgf016gwNzUWi9J1WJypw7zUWPhrxvaPecd+6qS0aAQEuucNleS+jOynJhqR1xbVFpsVn5Udx2v5O/BR6VFYbNaLXh+s8Udu1jLcnr0GC+IzOVN6EsxPXCspqqvaCtHSU4+ooHgZsyJ3YOzuwwcbX0BPY4cknrJiBlb+8Ca3+/70U6uwOCMeizMG/+5arDYU1rXiYGk9Dp9tGRlqXJ+jfpMF+4rrsK94sBBWKRSYlRR19iQ7HgvT4xAW6OdSbo5F9ZSZ/P4i11h7mmBuLpTE2E9N5MzriuozLXX2mdKNvR0jXp+TPAO3zV6N66ctQYCapzeTaVrsAgRqQtBr6rLHjtbswFXTb5cxK5Kb1WTBhz94Ga2lBkk8dmYyrvzV16DwgC2AKqUCs5KiMSspGnevyYYoiihv6sDBksEC+3CZATWt3SO+jsVmw7HKJhyrbMKLn+UDAKbGR9hPshdl6BAXNvzN0kajCbt3f47O7jYEaEMQE57OfmpymdFxPrUmCJp49lMTOfKKorq2qwXvFO7H1oK9OGYoG/F6fUgUbp29CrfOXoWUsNhJyJCGolSoMCdhJfZWbLPHvqjZjiun3eZ2J5E0OUSbDZ/95DXUHS2VxMOSYnDtc/dA7aZzoEciCALSY8ORHhuOW1dkAQDq23pwqKzefvPjGcPIi6UAoLi+DcX1bfhn3uCNvomRwZIxfmkxYRAEAVu3bsV3vvMAGhrO/+MkQBuGKyvisGBFxvh/keS1Bpz6qZdD4D1GRE4EURzFLewyslqtyMvLg8FggE6nQ05ODpRKJZp6OvBe0QFsLdiL/bVFI76On0qNdVMX47bZq3FZykwoBMUkZE8jqW4vxvOfPySJfSfnt0iNnCFPQiQbURSx59l3cOJf0t7NgMgQfPnlhxCSEClTZpOjvWcAh8vOThgpM+BkdTOsNtd/PEcF+yOqqwyfvvBLYIipRoIgYMuWLcjNzR2HrMkXGH4/B+am81tMQ6/4BUIve0TGjIjck1sX1Vu3bsXGjRtRW1trj4XHRiH9lrUoi7GNaqTV/PgM3DZ7NXKzliPML3Ai06VLIIointl+D5p7zv83XpLyJWyY810ZsyI5fPHP7dj//PuSmDpQixtffBDRU/UyZSWf3gEzvqhsxKGzfdlHKxphNF/83hBg8LTf8NoTsA7T/iYIAvR6PSoqKqAc50kj5H2svc2oe1raMhR7Tx60iYtlyojIfbltUb1161Zs2LABw6UXcOtSqGcM3RsYHRBqnyk9PTpxItOkcfBZ8Zv4qPBV+2N/dRB+cvXrUCk1MmZFk6n4f4fx2U9ek8QUKiWu23QvEhdPlSkr92KyWHGyutneLnK4zICufpPTdQN1Z9D8/qYRX++bT/4BX73hWixI1yEswDPbamji9Z3eipZ/fdX+WNAEQv9YE9s/iIbglj3VVqsVGzduHLagBoD+/x6Hano8hLOLE0K0AVg3dTG+nLUcl6XMhIorwz3GPP0aSVHdb+5BQcMhzE5YIWNWNFlqDhZhx5NvOMXX/uRWFtQX0KiUmJ8Wh/lpcbj/yrmw2UQU17fh0NmWkYOl9Wjq7IO1r3NUr/fO7qP4xDDYBnfu5seFGXFYlB6P+AhuiqVBjktftEnspyYajlsW1Xl5eZKWj6GInf1Q13bixmuuQ27WcqxJzYZWxW90TxQRGIu0yFkobz1pjx2t2cGi2gc0F9Xgw0f+BptVujhl2YPrMeXqBTJl5RkUCgHT9ZGYro/E11bOhCiKqGrpwt/fCsTPPntlxI9XBoTa/7/jzY8JEUFYlK7DgrObHzPjwid88yO5J8f51FrOpyYallsW1QaDYeSLAPx2+R34+vo7JzgbmgzzE9dKiuqixsPoNXYiUBt6kY8iT9ZZ24JtG1+Euc8oiWffshJzbl8tU1aeSxAEpESH4sf33YaXn378ogcTyqBwaHXDTwCpa+vBO20leOdwCQAgLFCLBWlxWJh+fvOjxgNGG9LYWHtbYG46LYn5cT410bDcsqjW6Ua3QjclMWmCM6HJMjthBd458SdYbIM9oufWli9PWydzZjQR+tt7sG3jC+hvk85qzrhiLpY/dANHKo6BUqnE5s2b8eUvf9npOUEQIAK49YFHMBCjx7HK0d382NEr3fyoVSsxNyUWizJ0WJgeh3mpcQj25z0Q3sZxNbmgDoAmYb5M2RC5P7csqnNycqDX61FXVzdkX/W5u9dzcvg2lLfwVwdipm4Jjted7987WrOdRbUXMvcb8cHDL6GzulkST1iQict/ejsEBcddjtWqnCuwKvsbOFT0DvqMHfa4Xq/Hpk2b7OP0jGYrTtU02298PFzWgE6Hdw6GYjRbcaCkHgdK6gEACkFAlj4SC9N1WJihw6J0HWJCAybka6PJM+Cw9IXzqYkuzi2L6nMnLRs2bBg8WbmgsD53grVp0yaOg/Iy8xLXSorq6vZiNPfUIjrI98apeSubxYqPH/s7mk5XSeKRmfG45jffhFLjlj+SPE7JaQOSY7ORGDMLTe1lsAr9+NHTt2PlysskPze16gtufsTgzY8lDW04VNpwtsg2oK6tZ8TPZxNFnKppwamaFryya7CNKzk6ZPDmx7MtI6kxoXwHwsOwn5rINW77Gyw3NxdbtmxxmlPteNJC3mNqzDwEakLRazo/veBo9Q5cncW+eW8giiJ2PfVvVO0pkMSD4sKxbvN90Ab5y5SZ9zlz+twJsgJxEZnIXpSCNWtG7lNXKARMjY/E1PhI3HHZ4AKmurZu+1Kaw2UNKK5vG1UOVc1dqGruwtsHigEMLqVZmB5nP82eoY+CSsl3JdyVtbcF5sZTkhj7qYkuzm2LamCwsF6/fv2QGxXJ+ygVKszTr0Je+Xv22NHaHbhy+u3cgOkFDr34IQrfPyiJaUMCsO75+xAYzRtSx1PJ2aL6nMyZ8Zf8WgkRwUiICMYNC6cAADp6B3CkvMFeZJ+oaoLZYXrLUFq6+/Hh8Qp8eLwCABCgVWFeahwWpsdhUYYOc1NiEaBla4G7MFbtkTwW1AHQxLOfmuhi3LqoBgZbQVatWiV3GjRJ5ietlRTV7X2NqGwtQFrUTBmzorE6tXUvjrz8sSSm1Kpx7bP3ICI1TqasvFNfrxE1FS2SWGbWpRfVjsIC/XD5rBRcPisFADBgsiC/qsnel32kvAE9A+aR8zRasKeoFnuKBt+JVCkUmJkUZW8ZWZgRhwi+eyEb5/nUyyCoeDMq0cW4fVFNviUhNAMxwYlo6q6xx47WbGdR7cHKd53A7l+/LYkJCgFX/vJr0GWnypSV9yorbIBoO38fikqtROrU2An7fH4aFRZnxmNx5mDhbrXZUFTXZi+yD5UZ0NTZN+LrWGw2HK9swvHKJry0PR8AkBEbhoUZ5/uyEyOD2Zc9SdhPTeQ6FtXkVgRBwPzEtfiw4O/2WH5dHm6YfT/UXFvucQz55fjkiVclRR4AXPboTUhbOUumrLzbGYfWj9QpMdBM4g2gSoUCMxKjMCMxCt9YPcu+lOZwmQGHz7aMlDV2jOq1Shs7UNrYgTf3FgIAYkMD7WP8FmXoMDU+AkpOixl31r5WmBtPSmLspyYaGYtqcjvz9KvxUcE/IGKwEBuw9KKg4SCyE3hS4knaKhrw3//7C6xGaSvAgm9ehZm5y2XKyvuVnHLop54xfq0fl+LcUpqU6FDctGQaAKCluw9Hys73ZZ+qaYbV5jw+1VFjZy+2HS3FtqOlAIAQfw3mpw32ZS/M0CE7OQZ+av5aGytjpWM/tT80CdxwSjQS/vQhtxMeEIO0qNkoa8m3x47WbGdR7UF6mzux7cEXYOySvu0/ff0SLLr3Gpmy8n4WsxXlxQ2S2BSZi+qhRAUH4Oo5abh6ThoAoHfAjGOVjfaWkS8qGtFvsoz4Ol39Juw8XY2dp6sBABqVArOTYwbbRdJ1mJ8eh7AA7YR+Ld7I6DCfWpO4lP3URKPAoprc0vzENZKiuqjxCHqMHQjShsmXFI2Ksacf2za+gJ6Gdkk8eUUWVv3wZvbETqDK0iaYjNJiNGMcb1KcKIF+aqyYpseKaYMz6c1WKwpqWnHI3jJiQGvPwIivY7LYcKSsAUfKGvBnHIMgAFN1EWdbRgb7snXhQRP95Xi8AYd+ar/Uy2TKhMizsKgmtzQ7fjneOfEnmK2D291sohXHaz/HivT1MmdGF2M1WfDh9/+K1hJpC0LMjGRc9auvQ6HiOMyJ5Nj6kZAciaAQP5myuXRqpRLZKTHITonBt9ZmQxRFlDd12NtFDpUaUN3SNeLriCJQVN+Govo2vLr7NABAHxF89ubHwb7sjNhwKBT8h9451r42p35qLfupiUaFRTW5JT91IGbqluJY7S577GjNDhbVbky02fDZT15D3dl+13NCk6Jx3XP3QO3Pt+EnmuNNilPGMJ/anQiCgPTYcKTHhuOW5VkAgIaOXvtq9cOlBhTUtUAcuS0btW3dqD3UjXcOnQEAhAVqB0f4nS2yZyZGQ+PD//gzVu3BhX+QgtofWvZTE40Ki2pyW/MS10iK6pqOM2jqrkFMcKJ8SdGQRFHE3k3vovSzY5K4f0Qwrn/+fvjzLfcJJ4riuC59cXdxYYFYNz8D6+ZnAAC6+o34orzRvv3xeGUTjBbriK/T0WvEpycq8emJSgCAn1qFuSkxWJgx2Jc9Ly0WQX6+009srHDsp14CQcV/EBONBotqcltTouchWBuObuP53tyjNdtxTdbX5UuKhnT8tZ3If1Pah6kO0GLd8/chJCFSpqx8i6GmHT1d0r5jd7xJcaKE+GuxakYSVs1IAgAYzVacrG62F9lHyhvQ2Wcc8XUGzBbsL6nH/pJzq94FZOkj7T3ZC9N1iAkNmNCvRU5O/dQp7KcmGi0W1eS2lAol5upXYXfZO/bY0ZqduGr6nVxb7kaKPzyCfc+/J4kplApc88xdiJ6qlykr3+N4Sh0RFYTImGCZspGfVq3EgvQ4LEiPw/1XzoXNJqKkoU3Sl13f3jPi69hEEadqWnCqpgWv7BrsNU6JDrW3iyxM1yE1JtQrbsC19bfD3HhCEmM/NdHosagmtzY/cY2kqO7ob0J5yylkRM+WMSs6p+ZgEXY8+YZTfM1PbkPi4mkyZOS7HPupM2fGe0WhN14UCgFT4yMxNT4Sd1w2uKG1rq37/ObHUgPOGNpHeJVBlc2dqGzuxNsHigEAUcH+9lnZC9N1mKGPgkrpef/wH6h06KdW+UGrXyhjRkSehUU1ubX40HTEBiejsbvKHvuiZjuLajfQXFSDDx/5G2wOfatLH7weU6/hjU2Tzd2WvniChIhg3LgoGDcumgIA6OgdGLzx8ewovxPVzTBbbSO+Tkt3Pz48XoEPj1cAAAK0KsxLjbNvf5yXGgt/jXpCv5bx4Dyfmv3URK5gUU1uTRAELEhai/+e/ps9dqJ+D27M/jbUSv6wl0tnbQu2bXwRZoce1dlfXYm5t6+RKSvf1dHaiyZDpyTmS/3U4yUs0A9XzE7BFbNTAAADJguOVzYNnmSXGXC0vAE9A+aLvwiAPqMFe4pqsaeoFgCgUigwKynK3pe9ID0OEUH+E/mlXBLOpyYaGxbV5Pbm6lfhf6dfuWBteR9OGw5gjp69fnLob+/Bto0voL+tWxLPuHwuVjx8A1sOZFBSID2l9g/QQJ/CG0THyk+jwpIp8VgyZfAfKFabDYV1rThc2oBDZ1tGmh22hg7FYrPhWGUTjlU24aXtg0utMuLCJX3ZiZHBsn7v2PrbYW7Il8TYT03kGhbV5PbC/KOREZ2Nkubj9tiRmu0sqmVg7jfig4dfQmd1sySeMD8Dl//sdggKz+sj9QZnHFo/MrJ0UHhgT6+7UyoUmJkYjZmJ0fjG6lkQRRFVLV32dpFDpQaUN3WO/EIAShvaUdrQjjf3FgIYHBF4fsJIHKbGR0A5id9PA1V7nfupE9hPTeQKFtXkEeYnrpUU1WeajqJ7oB3BfuHyJeVjbBYrPn7s72g6XSWJR2bG45rf3g2lhj9O5OI0n5qtH5NCEASkRIciJToUNy0ZvDG3pbsPh0sb7Dc/nq5tgdU28laaho5ebDtaim1nlyeF+GswPy1ucDFNRhyyk2Pgp5647zHn+dSLIag9bxsnkZz4W5A8wqz45fhP/h8uWFtuw/G6z5GTfoO8ifkIURSx66l/o2pPgSQeFBeOdZvvg9YN+0N9RX+fCVVl0ncOvGWToieKCg7ANXPTcM3cNABA74AZX1Q2Dp5klxlwrKIR/SbLiK/T1W/CztPV2Hm6GgCgUSkwOzkGi9IH20UWpMchNGD87isZqOR8aqKxYlFNHkGr8scs3TJ8UbvTHjtSvZ1F9SQ59OKHKHz/oCSmDQnAuufvQ2B0qExZEQCUFzVAvOAkVKlSIHVKrIwZ0YUC/dTImaZHzrTBme1mqxWna1rss7IPlxnQ1jMwwqsAJosNR8oacKSsAcAxCAIwLT5S0petu8TNpbb+DpgNxyUx9lMTuY5FNXmM+UlrJUV1XWcpqtoKkRwxXcasvN+prXtx5OWPJTGlVo1rn70HEalxMmVF55w5VSd5nJIZA62f+49v81VqpRJzUmIxJyUW31qbDVEUUdbYYW8XOVzWgOqWrhFfRxSBwrpWFNa14tXdpwEAiZHBWHBBX3ZmXPiobn40Vkv7qaHSQqtfdMlfI5GvYlFNHiMzeg5C/CLQNdBmj71+5Bk8vOr38Ndc2gkNXVz5rhPY/eu3JTFBIeDKX34NuuxUmbKiCzktfWE/tUcRBAEZceHIiAvHLcuzAAANHT2D87LPFtkFdS2Smnc4Na3dqGntxjuHzgAAwgP9sCA9brBlJCMOMxOjoVEpnT6ut3QX9lfa0NQDxAQBOZctYj810SUQRHE036pE7uGz4jfxUeGrkthM3TJ8bdETHOU2zgz55XjvO3+C1Sidy7vyRzdjZu5ymbKiC1ksVnw79wWYjOd7dB/8yXWYtyxdxqxovHX1G/FFeaO9XeR4ZROMDkuXRsNPrcLclBgszNBhUboOc1Nj8emHH+CBb94CQ4fJfl18dAh+/8IryM3NHc8vg8jrsagmj2K1WfDnPY+isk16w9z1M+/BZRk3ypSV92mraMDWuzfD6DCDd8E3r8Li+74kU1bkqLy4AU8++G9J7Pdv3YPgUN446s2MZitOVjfj0NlRfofLDOjqN438gQ4Gyo+j+eOXnOKD5xMCtmzZwsKayAUsqsnjdPQ149ldD6DPdL7vUCEo8Z2c3yI5YpqMmXmH3uZObLnrOfQ0tEvi09cvwerHv8p3BNzIx1u/wJsv5tkfxydF4Fd/uUPGjEgONpuIkoY2e0/2oVID6tt7Lvoxos0Gw2tPwNrbMeTzgiBAr9ejoqICSqVzywgROWNPNXmcsIBo3DL/+3h5//+zx2yiFf88/BT+b/UfEKAJljE7z2bs6ce2jS84FdTJK7Kw6oc3s6B2M45LX9hP7ZsUCgFT4yMxNT4Sd1w2EwBQ19aNQ6UGe8vIGYP0e9poKB22oAYGx2jW1NQgLy8Pq1atmsDsibwHi2rySNNjF2LNlK9gx5nzb3139DfhzaO/xTeW/AQKgdvkXGU1WfDh9/+K1hJpoRYzIxlX/errUAxxgxPJRxRFp6UvU1hU01kJEcG4cVEwblw0BQDQ0TswePPj2ZaRfWVHR/U6BoNhItMk8iosqsljXTXtDlS2nkZ56yl7rLDxED4v3YrVmRtkzMzziDYbPvvJa6g7u83tnNCkaFz33D1Q+4/fkgkaH431Hejq6JfEMrn0hYYRFuiHK2an4IrZKQCAT+aE4qpPXh7x43Q63QRnRuQ9eJxHHkupUOK2BT9EoEa6fOTDgldQ0Xpapqw8jyiK2LvpXZR+dkwS948IxvXP3w//S1woQROrxKH1IywiENFxITJlQ55m7ZpVSNDFYLiGLkEQkJiYiJycnEnNi8iTsagmjxbqH4nbFjwC4YJfDTbRhtcOP4VeY6eMmXmO46/tRP6b0hXF6gAt1j1/H0ISImXKikYy1Hxq9rzTaCmVSjz9nWsAwKmwPvf3aNOmTbxJkcgFLKrJ402JmYfLp94iiXUOtOKNo7+FTbTJlJVnKP7wCPY9/54kplAqcM0zdyF6ql6mrGg0nPqp2fpBLroqtQd/3qBEnMO93Xq9nuP0iC4Be6rJK1wx7VZUtJ5GaUu+PVZoOIznXvsp4lXTodPpkJOTw1OXC9QcLMaOJ99wiq/5yW1IXMzRhO6sq6MPDbUdkhgnf5ArRFGEsfoArpmmwJVTBByqFtGXdQ9Sl97Mn5VEl4hFNXkFhaDErQsewXM7H0C3sR0l+xuw4+VC9LR+bL9Gr9dj8+bNPH0B0Fxciw8feRk2h61sSx+8HlOvWSBTVjRajqfUfv5qJKZFyZQNeSJLWxlsvU0AAKVCwNIUAbp7vwd1BLdxEl0qtn+Q1wjxi8BtCx5Fyf4mvP/McfS0GiXP19XVYcOGDdi6datMGbqHrrpWbHvwBZj7pH8+s7+6EnNvXyNTVuQKx/nU6dN1UCr545xGz1i9X/JYERgDVXiaTNkQeQf+FCavkhoxE/terRzyuXPLQx966CFYrdYhr/F2/R09eP/BP6O/rVsSz7h8LlY8fANvdPMQjkU151OTq0wORbU2aSm//4nGiEU1eZW8vDy0NLQN+/yFW8J8jbnfiP8+/BI6q5sl8YT5Gbj8Z7dDUPDHgScwDphRVdokiXE+NbnK8aRam7RUpkyIvAd/i5JXGe32L1/bEmazWPHJY/9A46kqSTwyQ4drfns3lBreXuEpyooaYLOJ9scKhYD0aXEyZkSextbfAXNzgSSmTVomUzZE3oNFNXmV0W7/GtAMf5rtbURRxK6n30LlHulCnKC4cFy3+T5og/xlyowuhePSl+SMGGj91DJlQ57IWHsQEM//wwwqLTTxc+VLiMhLsKgmrzKtvx0xfpqLXhMc5YdT+ADbz/zb3mftzQ699CEK3zsgiWlDArDu+fsQFBMmT1J0yRyXvnA+NbnKWLVP8lgbPx+CSitTNkTeg0U1eY3OowdQ99ff4/uzMy563eq7pkFQAh8W/B1vHH0GZqvxotd7slNb9+LIXz+WxJRaNa599luISGXLgKexWm0oK5S2LrGoJlcZa6T/yNYkLZEpEyLvwqKavEJf2RmU//angM2KNfFReGZRltOJdWRsGK5/ZA4yl54vJo/V7sKf9jyKrgHvawcp//wkdv/6bUlMUAi48hd3QpfN0VmeqKa8BQP9ZkmMS1/IFaLVAlPtIUmM/dRE44NFNXk8Y5MBJb98FLaBfntsTXwUDr/4PHbu3Ik33ngDO3fuRENtMx6++3EIkI6NqmkvxuZdD6Km/cxkpz5hDPkV+OTxf0C0SdtbLntkA9JWzZYpKxorx6UvcfowhIQFyJQNeSJz40mIpl5JTJvIk2qi8cBb/smjWXq6UfrzR2Fpl540R6y8Aol33IMkh7mrqzI3ICY4Ea8f+TWMlvNFeOdAK/6Y9wN8dd7/YY5+5aTkPlHaKxvx3++9BKtReqK54K4rMfPLK2TKisaD43xqnlKTq4zV0n5qVWQGlEExMmVD5F14Uk0ey2Y2oezpJzBQKx0TFzxzLpK/8+iwiwyy4hbju5c9h8gAaU+xxWbCa0eexkeFr8Im2iYs74nU29yJ97/7Zxg7+yTx6dcvxqL7viRTVjQeRFF0Oqnm0hdyFedTE00cFtXkkUSbDZW/fxo9p49L4n6JqUj74c+hUF98xFhcSDIeXLkJ6VHOrRCfFb+Jfx76FYyWgfFMecIZe/qxbeML6Glol8STl2dh5Y++wm1pHq65oQsdbdK37bn0hVzlXFSzn5povLCoJo9U//pf0Z63XRJTh0ci88e/hioweFSvEagNxT3LfoklKc4nuCcNe/HH3d9DW1/juOQ70awmCz78wctoLZGeZMbMSMZVT30dSpVSpsxovDjOpw4J80dsfJg8yZBHsnTWwNpZI4lp2E9NNG5YVJPHaf7oPTRsfV0SU/j5I+OJp6GJjnXptZQKFb6c/QBunP1tKATpt0N9Vzme//whVLYWDPPR7kG02fDZT19D3ZESSTw0KRrXPXcP1P6cP+sNik/VSR5nzojnuw/kEsdTasEvDOro6TJlQ+R9WFSTR+k4vA/Vf9kkDSqUSHvkSQSkTbmk1xQEAcvT1uHupb+AvzpI8lyPsQN/3vsoDld9eokZT7y9m99D6afHJDH/iGCs23wf/MODhvko8jRO/dRs/SAXGasdlkAlLoGgYBlANF743UQeo7e0CBW/+xlgk95EmHz/9xA6d9GYX39KzFw8uHITooP0krjVZsG/jz2Lbaf+AptoHfPnGU/HXtuB/Dd2SWLqAC3Wbb4XofooeZKicdfV0QdDjbRXnpM/yFUmh8kfvEmRaHyxqCaPYGw0oPQXP4TNKL15UHfTnYi6/Npx+zzRQQl48LLnMDVmvtNzn5duxd8O/Az95t4hPnLynfnoCPZtfk8SUygVuOaZuxA9LVGmrGgilBZItyhqtCokpUfLlA15IpupF6aGfEmMRTXR+GJRTW7P0t2F0p8/Akun9KQuYtWV0N1y17h/Pn9NEO5a8jNcln6j03NFjYfx+90Po6WnfoiPnDw1B4ux/WdvOMXX/L9bkbh4mgwZ0UQ649D6kT49DirefEouMNUeBmwXvNOmUEKjXyhfQkReiEU1uTWbyYiypx/HQF21JB48ez6Sv/3IhN2opVQocf2se3Dz3IegFKQ7kpq6a/D85w+htDl/mI+eWM3FtfjwkZdhs0hbUZZ+93pM/RJ/SXojzqemsXK8SVETlw2FJlCmbIi8E4tqclv2WdQFJyRxv6RUpD/y5IizqMfDouSrcN+KpxCoCZHE+8zdeGnf49hX8cGE53ChrrpWbHvwBZj7jJL47K+uxNw71kxqLjQ5jANmVJY0SWLspyZXGWukNylqOJ+aaNyxqCa3VffaS2jfs0MSU0dEIfPHz0AZOHlTLVIjZ2LjyuehC0mRxG2iFVvz/4it+X+E1WaZ8Dz6O3rw/oN/Rn9btySecflcrHj4Bo5X81IVZxphtZy/OVehEJA+XSdjRuRpRJttiKUvnE9NNN5YVJNbavrwHTS+86YkpvAPQMYTv4YmKmbS84kIjMUDlz2LGXHON/bsq/gAf9n3BPpM3UN85Pgw9xvx34dfQmd1sySeMD8Dl//sdo7F8mJnHJa+JKVHwz9AI1M25IksLUUQBzokMW5SJBp//E1Mbqfj0F7U/PV5aVCpRPojTyIgNUOepABoVf742uInsHbKV5yeK23Jx+bPN6Kxu3qIjxwbm8WKTx77BxpPVUnikRk6XPPbu6HUqIb5SPIGjv3UbP0gVzmeUitDE6EK1Q9zNRFdKhbV5FZ6SwpRPuQs6u8jZI78N+EpBAWuyfo6bp3/CFQKaU93a68Bv//8YRQ2Hh63zyeKInY9/RYq95yWxIPiwnHd5vugDfIft89F7sdmtTmN0+PSF3KVc+sHR+kRTQQW1eQ2jA31KP3ljyCapDfh6b7ydUSt/ZJMWQ1tXuJqfDvnNwjxi5DEByx9+Nv+n+Lz0q0QRXHMn+fQSx+i8D2HLWghAVj3/H0Iigkb8+uTe6utbEV/n0kSy8xiUU2uMXLpC9GkYFFNbsHS1YmSIWZRR665GrqvfF2epEaQFD4VG1duhj4sUxIXYcO2U3/Bv489B4vVNMxHj+zU1r048tePJTGlVo1rn/0WIlLjLvl1yXM4zqeO0YUiLJJj0Gj0rL3NsLSWSmLspyaaGCyqSXY2kxGlTz0OY32NJB6cvQDJ9//AradahPpH4Ts5v8GchJVOzx2p/hQv7P0Ruo0dLr9uxecnsfvXb0tigkLAlb+4E7rstEtNlzyM402KmWz9IBc5tn4ImkCoY2fJlA2Rd2NRTbISbTZUbv4VeotOSuL+KelIf+RJCCr3vwlPrdTitgWP4urpdzo9V9lWgM27NqK+s3zUr2fIr8DHj/8Dok3aPnLZIxuQtmr2mPMlzyCKIs6cqpPEuPSFXOW09EW/CILS/X+uEnkiFtUkq7pXX0D7vl2SmDoyGhmPPw1lgOe8zS0IAi6fegu+tugJqJVayXMd/U34w+7v4WT93hFfp72yEf/93kuwGs2S+IK7rsTML68Y15zJvbU0dqOjtVcS4+QPcpXJ8SbFRM6nJpooLKpJNk3//Q8a3/u3JKYICETmj+WZRT0eZsUvxwM5v0OYvzR/k3UA/zj0C3xW/OawNzD2Nnfi/e/+GcbOPkl82rrFWHSfe92oSRPPcZReUIgfdInhMmVDnki0GGGsPyqJaZPZT000UVhUkyw6Du5Bzcu/lwbPzqL2T06XJ6lxkhCWjo2rNiMlIsvpuY8KX8XrR34Ns1U64cTY049tG19AT4P0Rs3k5VlY9dhX3LqvnCaGY+tH5ox4/j0gl5jqjwGWC37WCAK0+sXyJUTk5dhYRZOu90wByp99EnA4sU359iMIyV4gU1bjK1gbhvuWP4X/5P8Bh6s/lTx3vO5ztPTW484Fj+PEkULU1dSi4u3DCK23QSGc/3duzIxkXPXU16FUKSc7fXIDJacd5lOz9YNcZKyRtn6oo7Og8A+TJxkiH8CimiaV0VA39Czqr34DkWuulimriaFSanDz3IcRF5KCD069DBHnF9rs/DAPP7kpDV0t51s9wtRB2JB0GeaEZyA0KRrXPXcP1P7aoV6avFxP1wDqqlolMU7+IFcZqzifmmgysf2DJo2lq2NwFnVXhyQeufZL0N38NXmSmmCCIGBlRi7uWvpT+KkCAAAl+xvw/jPHJQU1AHSYe/DXsv+hwFyLdZvvg394kBwpkxsoLZD2U2u0KqRkeOZ9BiQPURRhrJEujtKwqCaaUCyqaVLYjGdnURtqJfGQOQuRfN/3vL5XdHrsQnx35XMI94vFjpcLL3rtu437EaTjDWm+zHHpS9rUOKjUbAOi0bO0l8PW0yiJ8aSaaGKxqKYJJ1qtqNj8S/QWnZLE/VMykPaDn3nELOrxEBuchHnKm9DTarzodfUNBuTl5U1SVuSOHCd/sPWDXOU4Sk8RGANVhGffBE7k7lhU04Sr/cef0bH/c0lMHRWDjB//2qNmUY+HjpauUV1nMBhGvoi8kslkQcWZJkmMNymSqxyXvmiTlnj9O4JEcmNRTROqcdsWNG2TrttWBAQi84lfQxMRJVNW8tHpdKO6LjwqdIIzIXdVeaYRFrPV/lhQCMiYHidjRuSJnItqzqcmmmgsqmnCtB/YjdpX/iCJCSoV0h/9BfyT02TKSl45OTnQ6/UXPTEKjvLDCbyHzv6WScyM3IVjP3ViahT8AzkFhkbP1t8Bc9NpSYz91EQTj0U1TYieolOoeO7nTrOok7/zCEJmz5MpK/kplUps3rwZAIYtrFffNQ1NvdX4/e7voam7ZjLTIzdw5pRDPzVbP8hFxtpD0p+9Sg008b77c5dosrCopnE3UF+L0l89BtFkksTjb70bkauukikr95Gbm4stW7YgISFBEg+JDsD1j8xB5tLBt/o7+pvwh7zvo6qtSI40SQY2m+h0kyL7qclVxmrpfGpNwnwIKr7bQTTRWFTTuDJ3dqD0F4/A2t0piUddfi3iNtwuU1buJzc3F5WVldi5cyfeeOMN7Ny5E6WlJVh2xXzJdX2mLryw94coajwiU6Y0meqqWtHfK/3HaOaM0fXhE51jrJbOp2brB9HkYFFN48ZmHEDZr34Eo6FOEg+ZuwhJ9/4f7zx3oFQqsWrVKtxyyy1YtWoVokPi8UDO75AYPlVyndlqxCsHfoYTdXtkypQmS4lD60dUbAgiooNlyoY8kWi1wFR7UBLTJrKoJpoMLKppXIhWKyqe+wV6zxRI4v5pmT41i3qsArWhuG/505gas0ASt4oW/PPwUzhc/alMmdFkcLxJkfOpyVXmxpMQTb2SGE+qiSYHi2oaF7V//xM6DkoXlmiiY5Hx+NNQ+gfIlJVn0qr8cNeSn2Cefo0kLsKGf3/xLPaWfyBTZjTR2E9NY+U4Sk8VkQFlEFfcE00GFtU0Zo3b3kbTB1skMWVAEDJ8dBb1eFAqVPjq/O9hacqXnJ5758QfsePMWzJkRROptakLrU3dkhiLanKV03zqZJ5SE00WFtU0Ju37P0ftK3+UxASVCuk/+gX8k1Jlyso7KAQFcrMfwKqMDU7P/a/gFXxY8A+IDiMLyXOVnJZu0QwM0kKXFCFTNuSpnIpq9lMTTRoW1XTJBmdR/8JpFnXKd3+I4JlzZcrKuwiCgGtn3IWrp9/p9Nz2M//CeydfhE20yZAZjTfHfuqMGfFQKHhzL42epbMW1s5qSUzDfmqiScOimi7JQF3N4Cxqs8Ms6tu/hYjLrpApK+8kCAIun3oLrp95j9Nze8rfw5Zjm2ETrUN8JHkSx8kfbP0gVzmeUgt+YVBHT5cpGyLfw6KaXGbuaEfJz4eYRX3lOsTl3iZTVt7vsowbcdOchyBAenp5qPoTvH7kGVhsZpkyo7Hq7TGitlK6ln4KJ3+Qi0w1DvOpE5dAUPDXPNFk4XcbucRmHEDpr34EU6P0VC1k/hIk3fMQZ1FPsMUpV+HWBY9AISgl8fy63fjHwV/AbDXKlBmNRVmhQdJFpVIrkZLJiQ3kGsdNitqkJTJlQuSbWFTTqIlWK8qf/Tn6Sgol8YC0KUj73k8gKDmLejLM1a/C1xY9AZVCLYkXNh7CX/f/BEZLv0yZ0aU649D6kTY1FmoNv59o9GymXpgMxyUxbdIyeZIh8lEsqmlURFFEzd9+j85D0q1+mug4ZDzBWdSTbYZuCb659GdQK7WSeFlLPl7a+xj6TN3DfCS5I86nprEy1R0BbBfcW6FQQqNfKF9CRD6IRTWNStP7b6H5f+9IYsrAIGT8+NdQh0fKlJVvy4yei3uX/Qp+qkBJvKq9CC/s/SG6jR3yJEYuMZssKCtqkMS4SZFc5XiToiYuGwpN4DBXE9FEYFFNI2rfuxO1f/+TJCao1Ej/0a/gn5giT1IEAEiJzML9K55GoCZEEq/vLMef8x5BR3+zTJnRaFWWNMFiPn/CKAhAxnSdjBmRJ3IqqjlKj2jSsaimi+opOIGKzb9yiqc8+EMEz8iWISNylBCWgW/n/AYhftJ3DJp6avDHvB+gtdcwzEeSO3Bs/UhIiURgsJ9M2ZAnEm0258kfLKqJJh2LahrWQF01Sp963GkWdcId9yIi53KZsqKhxAYn4Ts5v0FEQJwk3t7XiD/mfR8NXVUyZUYjcVz6wn5qcpWlpRi2/nZJjEU10eRjUU1DMne0Dc6i7umSxKOvXo/YG2+RKSu6mMhAHb6T8xvEBCVK4l0DbfjznkdQ21EqU2Y0HJtNdFpPnsmimlzk2PqhDE2EKjRxmKuJaKKwqCYn1oF+lP7yRzA1Sn/Zhy5YisS7H+QsajcW6h+F+3OeQXxomiTea+rCC3seRWVrgUyZ0VAMNW3o7R6QxLj0hVxlrJEW1dpEzqcmkgOLapIQrRZUPPsk+kqLJPGAjKlI5SxqjxCsDcP9y3+N5AjpeuIBSx9e3PcYzjQdkykzcuTYTx0RHYTImJBhriYamrHKYelLMudTE8mBRTXZiaKImr8+j87D0h/Qmpg4ZDz+NJR+/jJlRq7y1wThnmW/REaU9GZSs9WIlw/8P5w2HBjmI2kyOS59YT81ucra2wJLa4kkpk1kPzWRHFhUk13ju/9C80fvSWLKoGBk/vgZqMMiZMqKLpVW5Y9vLn0SWXGLJXGrzYJ/HPo5jtXukicxsnM8qeZ8anKVYz+1oA6AOm62TNkQ+TYW1QQAaNuzA3WvviCJDc6i/iX89MkyZUVjpVZq8LVFT2BOwmWSuE204Y0jz+Bg5UcyZUbtLT1obpDeCMyTanKVyaGfWqNfxDY9IpmwqCZ0n85H5VCzqDc+huAszqL2dEqFCrcueASLkq+SxEWIePv4ZuwufWeYj6SJ5HhK7R+oQUIyt5OSaxxPqrVJvEmRSC4sqn1cf00lyp56DKLFLIknfO1+RKxYI1NWNN4UghI3zdmInLT1Ts+9f+olfFL0OkRRlCEz3+U4nzpzRjwUSv5IptETLSYY645IYtok3qRIJBf+BPdh5vZWlP7iUVh7eyTx6GtuROz6r8iUFU0UQRBw/ax7cfkU5znjnxS9hg9Ov8zCehI5nlSz9YNcZTIcAyxGSUybuHiYq4loorGo9lHW/r7BWdRNDZJ46MLlSPzmdzmL2ksJgoCrs+7EtTPucnru89L/YGv+H2ATbTJk5lv6e42oLm+RxLj0hVzl2PqhjsmCwj9cpmyIiEW1DxKtFlT87kn0lRVL4gGZ05H2vf8HQamUKTOaLKszb0Ju9nec4vsr/4d/Hf0drDarDFn5jtLCBoi28+8KqNRKpE6NlTEj8kTGaofxp1xNTiQr3iLsY0RRRPVfNqPzqMMd47E6ZDz2FBRaP5kyo8m2LPU6aJX++NcXz0LE+dPpL2p3YMDUh+T+ZWhqaoFOp0NOTg6U/MfWuHHsp07JjIFGwx/HNHqiKMJYLZ03r2VRTSQr/hT3MY3vvImWj9+XxJRBIWdnUfNtQ18zP2ktNCo/vHb4aVhFCwCgZH8DXnz5KfS0nu/V1Ov12Lx5M3Jzc+VK1auUcOkLjZG1vQK2Hmn7HotqInmx/cOHtO3+FHX/fFESE9QaZDz2K/glJMmUFcltVvxy3LXkp1ArtSjZ34D3nzkuKagBoK6uDhs2bMDWrVtlytJ7WMxWlBdLiyEufSFXOfZTKwKjoYrIkCkbIgJYVPuM7lPHUfn7X0uDgoDUhx5H0PRZ8iRFbmNq7Hx8Y9FPsfPloiGfPzcV5KGHHoLVyn7rsagqa4bJaJHEMrN0MmVDnsppPnXiEt5gTiQzFtU+oL+mEmVPP+40i1r/tfsRvmyVPEmR26kv7EB368Cwz4uiiJqaGuTl5U1iVt7njEPrR3xSBIJC/GXKhjyVU1GdzPnURHJjUe3lzG2tKP35I86zqK/NRcz1N8uUFbkjg8EwrtfR0JzmU7P1g1xkG+iEuemUJKZNZD81kdxYVHsxa38fSn75KEzNjZJ42OIVSPzGA3yrkCRiIzSjuq7eXMAlMZdIFEWnoprzqclVxtpDwIXfg0oNNPHz5EuIiACwqPZaotWC8t/+FP3lJZJ44JQspD78Y86iJgmbqQNzhKcRHwlc7J9awVF+qAs8jDeP/gZmq2nS8vMWDbUd6O7sl8R4Uk2uMlY5zKeOnwdBzXGoRHJjUe2FRFFE9YvPoeuLg5K4Ni4B6ZxFTQ5Eaz96DtwE9JzCr+5SAxi+sF591zQolAK+qN2JF/Y8iu6B9slL1AucOV0neRwWGYio2BCZsiFPZapxnE/Nfmoid8Ci2gs1/Oc1tHz6gSSmDA5Fxo+fgTo0TJ6kyC2JNgt6Dn0NlpY9AIB1S5R45Qdq6KKkI+xjdJG4/pG5yFwaZ49VtRdh8+cbUd9ZPqk5e7Kh5lOzDYtcIVotMNY4HJgkLZEpGyK6EItqL9O66xPUv/5XSUzQnJ1FHa+XKStyR6Ioou/4gzAbtkni169MQEVZIXbu3Ik33ngDO3fuRH1NI556+AVoVdIpFR39zfjD7u/htEF6ckZDc75JMUGmTMhTmZtOQTRJbzzn0hci98CNil6k++QXqPrjULOon0DQtJnyJEVuq7/gZzBWviKJCaoQBC9/D6qQDKxaJV0kkRW3CA9c9iz+duCnaO87f/OryTqAvx98EldNvwNLU76EQG3opOTvaTraetFY3ymJcekLucpxlJ4qIh3KoFiZsiGiC7Go9hL9VeUoe/rHEC3SpRL6b3wH4UtXypQVuauBsj9hoNjhH2AKLYKWboEqbPawH6cLScGDKzfhHwd/jsq2AntchIiPCl/FR4WvIjpIj5SI6UiJmIHUyCxEB+nZ4gDnU2q/AA0SUyJlyoY8ldN8ap5SE7kNFtVewNTWgpJfPAprn/QtwZh1NyF23U0yZUXuyljzFvryv+8QVSBo0atQR+eM+PHB2jDct/wpvH38eRyt2e70fHNPLZp7anG4+lMAQIA6GMkR05EaOQPJEdORFD4FaqV2PL4Uj+K49CVjug4KJTvwyDWORbWGRTWR22BR7eGs/X0o/cWjMLc0SeJhSy6D/mv3y5QVuStz43b0HrkbgHTOdMDcP0ATf/2oX0el1OCr876HuJBk/O/0KxAx/NzqPnM3ChsPobDxEABAKaiQEJaOlIiswf9FZiHEL+KSvh5PwqUvNFaWrjpYO6okMZ5UE7kPFtUeTLRYUP6bn6C/olQSD5w6A6kPPcFZ1CRhaTuC7gNfAUTpunr/rJ/CL/UbLr+eIAhYnXkT9GEZ2HHmbVS2FcBsNY74cVbRgur2YlS3F2N32TsAgIiAOHuBnRKRhbiQJCgE7/n7299nQlVZsyTGpS/kKpPDKbXgFwp1dJZM2RCRIxbVHkq02VD14rPoOnZIEtfqEpDx2K+g0Pre2+s0PGv3GXTvuxGw9kri2vT74Tf1kTG9dmb0XGRGz4XVZkF9Zzkq2wpR2VaAytbT6BxoHdVrtPU1oK2vAV/U7gAA+KkCkBwx/WzbSBaSwqc5TR7xJOVFDRBt50/zlUoF0qby5jJyjbHaYT514hIICrYQEbkLFtUeaKCuGlV/+i16CvIlcVXI4CxqVUiYPImRW7L116N77zqIphZJXKO/CQGzfztuNxEqFSokhk9BYvgU5KSvhyiKaO9vQlVbISpaC1DZdhqGzkqIsI34WgOWPhQ3HUVx01EAgEJQQBeSNngDZGQWUiNmICwgelzyngxnHFo/kjNjoPVTy5QNeSpjtXSTojaR86mJ3AmLag8iWixoePdNGN56FaJZuiJa0GiQ/thT8NNxFjWdZzO1o3vv9bD1VUviqpi1CFzwVwjCxJ1yCYKAiIBYRATEYq5+FQBgwNyH6vbiwZPstgJUtRXCaOm/+AsBsIk21HWWoq6zFHsrBudqh/pHIfWCvmxdSBqUCvdsGRlq6QuRK2ymPpgMxyUxbTI3KRK5ExbVHqK3tAhVf/wN+itLnZ9UKJD68I8RNHXG5CdGbku09qNn/wZYu05L4sqweQhe/CYEhWbSc/JTB2BKzFxMiZkLALCJVjR0VZ1tFylARVuBZAb2xXT2t+B43W4cr9sNANAo/ZAUPtVeZCdHTIe/OnDCvpbRslisKCtqkMQ4n5pcZao7AtguGJmqUEKTsFC+hIjICYtqN2czDqD+zVfQuO0twOb8trkmJg7J33kUIbPnyZAduSvRZkHPwTtgaZW+XawIykTw8nchqINlykxKISgRH5qG+NA0LEu9DgDQ2d9qP8mubCtEXUcpbKJ1xNcyWQdQ2pKP0pbBtigBAmJDkpESkYXUiCwkR05HZIBu0mdm15S3wDggvTk0M0s3qTmQ53McpaeOmw2FNkimbIhoKCyq3VjXiS9Q/effwthQ5/ykQoGY6zYg/pa7oPTz3Bu4aPyJoojeYw/A3PBfSVzw0yF4+TYotO7dixzqH4nshBxkJwzOzDZZBlDTcWbwBsjWwWK739wzwqsMLqRp6KpEQ1clDlT+DwAQrA1HSkSW/QbIhLAMqBQT29vsOJ86Th+OkLCACf2c5H2clr4kcpQekbthUe2GzB1tqHv9r2j97L9DPu+fnIbkbz+CwCnTJzkz8gT9p/8fTFX/kMQEdRiCl78PZWCyTFldOo3KD+lRs5EeNbjp0Sba0NRdM3gD5Nm2kZbeIf7hOYRuYztOGvbipGEvAECl0CAxfMrZDZCDbSOBmpBxzZ/zqWmsRJsNphqHyR+cT03kdlhUTyKr1Yq8vDwYDAbodDrk5ORAeXaWtLmjHR0HdqN93y50nz4+ZKuHoFJDd/OdiL3hFijUnBxAzgZKf4+BM7+VBhV+g+vHQ2fKk9Q4UwgKxIUkIy4kGYtTrgYA9Bg7JCfZNR1nYL2w/3QYFpsJFa2nUNF6yh6LDtIP3gB5dmb2WNasi6LoNPmD86nJVZaWYtj62yQxFtVE7odF9STZunUrNm7ciNraWnssIT4eP7/rDiwXjMMW0ucETpuF5G9/H/6JKROfLHkkY/Wb6DvhMHNaUCJo0T+hjlouT1KTJEgbhpm6pZipGyw0LFYTajtK7b3ZFa0F6DV1juq1zq1ZP1T9CQAgQBNy/iQ7IguJ4ZmjXrPeWN+BrvY+SYyTP8hVRodTamWIHqqwJJmyIaLhsKieBFu3bsWGDRsgitJVznX19bjrF7/GM4uysCY+asiPVfj5I+GOexF99XoO+adhmRo+Qe/Re5zigXP/CE38dTJkJC+VUjN40hw5uG1OFEW09hpQ0Xbafprd2F09wqsM6jN1oaDhIAoaDgK4cM36DKSenTIy3Jr1ovwaNLSVoM/YhQBtCDLTZiEmPnR8vkjyGU7zqZM4n5rIHQmiY6VH48pqtSIlJUVyQu0o1l+L969cBOUFbzEr/PwRtiQHCbfeDU00N6/R8Cxth9CVdw1glZ6I+s94Ev5TfyBTVu6vz9SNqnPbH9sKUd1ePKo160OJDIhDSuSMs6fZ0xEbkox333kXd991L9o7zy/dCQuJwsuvvIjc3Nzx+jLIB9RvnglLyxn74/AvPYvgpQ/ImBERDYVF9QTbtWsXVq9ePeJ1LyyfjUWJOoQuWIrwZasQOm8xFFq/SciQPJm1uxhdn6+FaJKuA9dmPICAWc9M+vg4T2a1WVDXWXbBBsgCdI1yzbqjykMd+M9TB4Z4RoAgAFu2bGFhTaNi7W1B3dPSlqHY+/ZDmzBfpoyIaDhs/5hgBoNhVNcpr1iP7B8+xkKaRs3WV4vuPdc5FdSaxK8iYNavWVC7SKlQISl8KpLCpyIn/Qb7mvVz7SKVbQWjWrNus4r4+KVjwzw7eIaxceODWL9+vf1GZaLhOPZTC+oAaOJmy5QNEV0Mi+oJptONbslDxso1LKhp1GymtsH14/3StiJ1zBUInP/ihK4f9xUXrlmflzj4btOAuffsmvVCVLaeRlV7kdOa9brCNvS0Dt9GIopAbW0dvrv5y7jy8quRFjkTqVEzEawNm8gvhzyUyWE+tUa/EIKS05+I3BGL6gmWk5MDvV6Puro6pxsVgcFf3Hq9Hjk5OTJkR55ItPShZ9+XYe0ulMSV4QsQtOQNWdaP+wo/dSCmxMzDlJjBDabn1qwPtosM3gRZ2F4/wqsMqqqrwJ7y97Cn/D0AQExQItKiZiItcibSImchLMC9l/TQ5HBa+sJRekRui0X1BFMqldi8eTM2bNgAQRAkhfW5t+c3bdrEt4FpVESbGT2HboelTfqWsCJoCoKXvQNBxbXFk+nCNevL0wanrHyA9/C/Z28Y8WODwqVj+Zp6atDUU4MDlR8CAMIDYpEeOetsoT0LkYGTv2Kd5CVaTDDVHZHEWFQTuS/eqDhJhppTnZiYiE2bNvGGJRoVURTRe/QemKpfk8QFv3iErNoJZQDn1roDq9WK5ORk1NUNv+UxOMoPd7+wEgrl6IvkEL/IwVPss0V2THAiFGzz8WrGmkNofGmFJKZ/rBEK/3CZMiKii2FRPYkutlGRaCR9Jx/DQMlzkpigDkfwys+gCsmSKSsayvPP/gUbv+c8N/zcSfMfX3kWU5bEoaz1JCpbC2CyDrj8OQI0IUiLnIG0yFlIi5qF+NBUKAT+PPEmXfs2o+PD82Mx1dHToXswX8aMiOhi2P4xiZRKJVatWiV3GuSB+ks2ORXUUPojaNl/WFC7oVRdNlZlfwOHit5Bn7HDHtfr9ZJ3p9biq7DarKjrLEV5y+C69PLWU+g394z4OfpMXThl2I9ThsGeWz9VAFIis+xFtj4sAyoFb2jzZMYq6dIXTfIymTIhotHgSTWRmzNWvY7eo3dLg4ISQUvehkZ3jTxJ0UU9++P3cOJQJWyiDU3tZUifFY6b7lw7qnenbKINDV1VKG89aS+0u43tLuegVmqRHD4NaVGzkBY5C8kRU0e9Xp3kJ4oi6p5Jhq2nwR6LuPGvCJp3p4xZEdHFsKgmcmOmho/Qs38DIFol8cD5f4E2+XaZsqKLsdlEPHDTi+jrOT9W7/4fXYPFq6Zc0uuJoojmnjp7kV3eehId/c0uv45SUCExfMrZInsmUiKy4KcOuKScaOJZ2itQ/+xUSUz30GmoIzNlyoiIRsL2DyI3ZW49gJ6DtzoV1P4zf8mC2o3VV7dKCmoAyJwxunn1QxEEATHBesQE67EkZfCdiba+RpS3nER56ymUt5xCS+/wN0WeYxUt9iU2O/BvCFAgISz9bLvI4Ci/AE3wJedJ48txlJ4iMBqqiAyZsiGi0WBRTeSGrF2F6NmXC1ili0X8MjfCf8r/yZQVjcaZU9I51ZGxwYiIHt9iNSIgFhFJsViQdDkAoGug7WyBPVhoN3RVjvgaImyo7ShBbUcJdpdtBQDoQlKQekGRHeIXMa550+g5zadOXMKRikRujkU1kZux9tWge+86iGZpH60m6Vb4z/yVTFnRaJUUGCSPp8yIn/DPGeIXgTkJl2FOwmUAgF5TFypaT9uL7LqOshHXqwOAoasShq5K7KvYBgCIDkoYPMk+u/UxIiB2Qr8OOo9LX4g8D4tqIjdiM7aie+862Pqlb+erY69G4LwXuH7cA5Selp5UZ2ZNfFHtKFATgpm6pZipGyzEBsy9qGwrtJ9m17SfgVW0jPg6zT11aO6pw8GqjwAA4f4x9p7stKiZiApM4OnpBLANdMHceEoS0yZx8geRu2NRTeQmREsvuvfdCFt3sSSujFiEoMWvQeB4NLfX3tqD5oYuSWws/dTjxU8diGmxCzAtdgEAwGQZQHV7sb3IrmovgtlqHOFVgPb+Jhyt2Y6jNdsBAMHa8PNFduRMxIYkcyHNODDWHgLEC95ZUGqgiZ8nX0JENCosqoncgGgzo+fgbbC2H5bEFcHTELx0KwRVoEyZkStKTktbP/wDNUhIjpQpm+FpVH7IiM5GRnQ2AMBiM6O2vWSwyG49iYrW0zBa+kd4FaDb2I78ut3Ir9sNAAhQByPVvvVxJuJD06FUcCGNq4zVDvOp4+dBUPvJlA0RjRaLaiKZiaINvUfvhbnxY0lc4Z+A4OXvQ6F1v6KMhlbi0PqRMV0HhdL9T25VCjVSIrOQEpmFNbgZVpsVhq5y+wi/8pZT6DN3j/g6feZunG7Yj9MNg/3AWpU/UiJm2IvsxLBMqJSaif5yPJ6p+oDkMfupiTwDi2oiGYmiiP6TP4Kp5k1JXNBEIHj5B1AGJMqUGV0Kx6I6cxJuUpwISoUS+rBM6MMycVnGjbCJNjR2V59dRnMSZS0nR7WQxmjpR3HTERQ3HQEAqBQaJEdMs4/xSw6fBo2KJ7AXEm1WGGsPSmIsqok8A4tqIhkNlDyLgdLnpUFlAIKXbYUyZJo8SdElGeg3obpMupTFU4tqRwpBAV1ICnQhKViedh1EUURLb/35k+zWU2jvaxzxdSw2E8paTqCs5QRQPLiQRh+eefbGx1lIiciCv9q3W53MjacgGqXvCrCoJvIMLKqJZGKs+if6Tz0hDQoqBC1+A6qIxfIkRZesvKgBNtv5BbVKpQJpU71zBJ0gCIgOSkB0UAIWp1wFAGjva5LMym7uqR3xdayiBVVthahqK8TOkrchQIH40DSkRc1EeuQspEbOQKA2dKK/HLfiOEpPFZEOZZB3/j0i8jYsqolkYDL8F71f3O8UD5z/EjRxV8mQEY2V402KyRnR0Pr5zsSW8IAYzA9Yg/mJawAA3QPtTgtpRIgXfQ0RNtR1lqKusxR5Ze8CAGKDk+092WmRsxDq7933GDgW1ZrEJTJlQkSuYlFNNMnMrfvQc/B25/Xjs56GNukWmbKisTrjJf3U4yXYLxzZCTnITsgBAPSZugcX0pwttOs6S2ETR15I09hdhcbuKuyv+C8AICow3r6MJj1yNsIDYrxqVrbT0pdkzqcm8hQsqokmkaXzNHr2fRmwDUjiflP+D/6ZG2XKisbKZrWhrKhBEsvIkn8+tTsJ0ARjhm4JZugGT14HzH2oai+092VXtxfDaht5IU1Lbz1aeutxqPoTAECYf7R9GU1a5CxEB+k9tsi2dNXD2lEpiWl5Uk3kMVhUE00Sa1/V2fXjHZK4JukO+M/4hTxJ0bioqWzFQJ9JEvP1k+qR+KkDMDVmPqbGzAcAmK3GwYU0LadQ3noKlW0Fo1pI09HfjC9qd+KL2p0AgCBtmH0ZTVrULMSFpHjMQhqTwym1oA2BOmaGTNkQkatYVBNNApuxGd171kEckPbdquO+hMB5f/LYkzUaVHJK2voRowtFWIRvT7FwlVqpRXrUbKRHzQYwuJCmrqP0bLvIKVS0nsKApW/E1+kxduBE/R6cqN8DAPBXByE1coa9yE4ITYdS4Z6/+ow1DvOpE5dAUHjGPwiIiEU10YQTLT2D68d7SiRxVeRSBC36JwQ3/QVPo1dS4NBPPZOn1GOlUqiRHDEdyRHTsTrzJthEKwydFfYiu7z1JHpNXSO+Tr+5BwUNB1HQMDj7WaP0Q0pklv3Gx8TwKVC7yUIax02KHKVH5Fn425xoAok2E7oPfBXW9qOSuDIkC0FL/wNBFSBTZjSeHE+qM7NYVI83haBEQlgGEsIykJN+A0RRHFxI0zp4il3WchJdA60jvo7JOoAzTV/gTNMXAAaL96Twafae7OSI6dDKsJDGZu6Hqf6YJMaimsizsKgmmiCiaEPvkW/B0rRdElf4Jw6uH9eEy5QZjafWpi60tfRIYpkzeJPiRBMEAXEhyYgLScay1GshiiLa+hpQdnaEX0XLSbT2NYz4Ohab+ewCm5MA3oRCUEIfloG0qFlIi5yF1Igs+GuCJvzrMdUdAS68UVNQQKNfNOGfl4jGD4tqogkgiiL6TvwAptq3JHFBE4ngFdug8E+QKTMab47zqQOD/aBLjJApG98lCAIiA3WIDNRhUfKVAAZvYjx342N560k0ddeM+Do20Yrq9mJUtxdjV8kWCBCgC01FWuQspEcNLqQJ0oaNe/6Oo/TUcbOh0E58MU9E44dFNdEEGCj+DYxlf5IGlYEIXvYOlMFT5UmKJoTjfOqMLB0UCt546g7C/KMxL3E15iWuBgB0GztQ2Xr67Gn2SRg6K0axkEZEfWc56jvLsaf8PQBATHCivchOi5yJUP+oMefq3E/N+dREnoZFNdE4G6h4Bf0FP5EGBRWCl/wLqoiF8iRFE6bEoaiewlF6bitYG4ZZ8csxK345AKDf1IOKtoLB9o+Wk6jtKBnVQpqm7ho0ddfgQOX/AACRAXFIjZqF9MhZSIuaiYiAOJcm+oiiCFO1w+SPJM6nJvI0LKqJxpGp/n30HXvAKR644C9Qx14uQ0Y0kfp6jaitlN4cx35qz+GvCUJW3CJkxQ32Lhst/ahqKzpbZJ9CdXsRLDbziK/T2teA1uoGHKn+FAAQ6heJtKhZSI2cidSILMSGJEEhKIf9eGNjAfYWtqCpB4gJAhYlCTypJvJALKqJxom5ZQ96Dt0JQHrSFTD7N9AmflWepGhClRU2QLSdbx9QqZVImRIrY0Y0FlqVP6bEzMWUmLkAALPVhJr2M2dvZDyFytYCmKwDI7wK0DnQimO1u3Csdpf9dZPCpyI5fDqSIqYhOWIaAjUhAICtW7fiwfvvRl2T1f7xulAlfj/vML785aTx/yKJaMIIoihevKGMiEZk6TyJ7t1XQDR3SuJ+U36AgJlPypQVTbSt/9iP9984ZH+ckaXDE8/dLGNGNJGsNgvqOstQfm7CSOtp9Jt7Rv7AIUQFJqDxuBmbHn0Vjm3dAgAIArZs2YLc3Nwx501Ek4NFNdEYWXsr0bVrNUSjdHyXNvnrCOC2RK/260f+g8L8Wvvja26aj6/cvULGjGgy2UQrGrqq7EV2eesp9Bg7RvexVhF/uXcXelqHXsUuCAISEhJQWVkJpXL41hEib2a1WpGXlweDwQCdToecnBy3/n5g+wfRGNgGmtC95zqnglqtuw4Bc3/PgtqLWSxWlBVJ/7tnZrGf2pcoBCXiQ9MQH5qGFenrIYoimnvqUN56AmUtJ1HZVoj2vsYhP7ausG3YghoYvHmxtrYW9z13HZbnLIMuJBXxoamIC0lBZGDcRXu0ibzB1q1bsXHjRtTWnj+40Ov12Lx5s9u+g8OimugSiebuwfXjvWWSuCpyOYIWvcr1416uprwFJqNFEstgUe3TBEFATLAeMcF6LEn5EgCga6AN1W1FqGwvRHVbEWo6SmC2GtHTPnxBfaF6Qz1OGfbhlOH8yD21Uou4kBTEhwwW2bqQVOhCU+x92kSebuvWrdiwYQMcmynq6uqwYcMGt22N4m99oksgWo3oPvAVWDu+kMSVITMRtHQLBKW/TJnRZDnjsJo8Th+OkDCunSepEL8IzIxfhpnxg9M8rDYLDF0VeKfvbfwPJ0b8+KBwrVPMbDWipr0YNe3FknioXyTizhbY8SGpCPGLPDuHW8RgbSIOPhbP/T8REM9N6hbtBcz5+NnHF/7/s8/Z///Z5+2PRPGC18bQn//s46Fzc87H/uyFn2e0+do/xiEfx1wHX2hUOZ3/rCP/+V34eexfy4U5Ofz5DZvvBflIPs+wuQ6R7yj+/Bzzvdif3/n/PiP89xYv+KhR/PlZrVZsvnebU0F9Lh9BEPDQQw9h/fr1btcKwqKayEWiaEXvkW/C0rxTElcEJCN4+XtQaMLkSYwmVUmBw3zqmZxPTSNTKlTQh2Xi2195FM88+mfU1dbCuXQYFBzlh4Tpo9/O2TnQis6BVhQ3HRmfZIlkUHOqFV0t/cM+L4oiampqkJeXh1WrVk1eYqOgkDsBIk8iiiL68r8HU91/JHFBE4Xg5dug8Gdh5QtEUXRa+sJ+anKFUqnEc8/8CsDZaR8XEAQBgiDgd8/+Frcs+B4uS78RmdFzEKgJnfxEiSbZaFujDAbDBGfiOp5UE7lgoOhpGMtflAZVQQhe/i6UwZnyJEWTrrmhC51tfZJYJjcpkouunReBP29Q4mcfW2HoPh/X6/XYtGnTkD2j3QPtMHRVoL6zAoauCjR0VaKhuwpWm8XpWiJPNFTL01B0Ovc7yGBRTTRKA+V/RX+hw8xpQY3gJf+GKny+PEmRLBxPqYND/RGbECZPMuSxBirycM00Ba6cIuBQtYh2/2mYdusfLjo2LNgvHMF+4ZgSM88es9osaO6pg6GrAoauShg6K9DQXQWTZWDw1PuCs/DBiUSCfRb24P+TPnZ6bjAw+FjABfFzr3zB53B4/tyzEC74TBfkJMnH/jFnrx0yVzjndPZal/K9MDenxxhdvg5/fsM+N0Q+jp9nuHztzzj9WQ7/5yd97oKvapicpH+WF8l32D8/6X+fUedr//sm/bptS6zY/efr0GhoGrKvWhAE6PV65OTkOD0nNxbVRKNgqnsXfcc3OkQFBC58GeqYNbLkRPJxav2YEc/xieQyY+VuAIBSIWBpioCQVTch7BJ6RJUKFeJCkhEXkoy545wjkRz++Ps/YcOGDRAEQVJYn/s5u2nTJre7SRFgTzXRiMzNu9Fz+GtwWj+e/Tto9TfJkxTJquS0tJePrR/kKpuxGybDMUnML3WlTNkQuZfc3Fxs2bIFCQkJkrher3fbcXoAT6qJLsrSkY+e/TcBNpMk7jf1h/BLv1+mrEhOvd0DqKtqlcQyZ7hfbx+5N2P1PsBmPR9QaqBJXCxfQkRuJjc3F+vXr+dGRSJvYO0pR/fe9RAtXZK4NuWb8M/6fzJlRXIrKZCeUqs1SqRkxMiUDXkqY8Xnksda/UIo1JxvT3QhpVLpdmPzLobtH0RDsA00onvvOohG6Yphdfz1CJi7mf2zPqzUoZ86bWocVGr3PTkh9zRQmSd5rE1xv5uuiMg1LKqJHIjmLnTvvQG23nJJXBWVg6CF/4AgsIDyZWc4n5rGyGbqhanuqCSmTblMpmyIaLywqCa6gGgdQPeBm2HtPC6JK0NnI2jp2xCUfvIkRm7BYrai4oz03YtMblIkFxmr9wMXzpVWqKBNWipfQkQ0LlhUE50lilb0HP4GLM3SXkdFQAqCl70LhZrbzHxdZWkTzCarJJYxnSfV5Jpzo/TO0STMh0ITKFM2RDReWFQT4ez68eMPw1z/riQuaGMQvOIDKPxZOBFQckra+pGQHInAYL57Qa4xOvRT+7GfmsgrsKgmAtBf+EsYK/4iDaqCEbzsXSiD0uVJityO4+QPjtIjV9nM/TDWHpbEtJxPTeQVWFSTzxsofwkDRb+UBhUaBC95C6pw7iejQaIoDrlJkcgVppqDgPWCufcKJbRJy+RLiIjGDYtq8mmm2v+g7/hDDlEBQQtfgTpmlQwZkbtqrOtAd2e/JMaimlw14DCfWqObC4U2WKZsiGg8sagmn2Vu2oWeI3cBECXxgDmboElwzxWoJB/HU+qwiEBEx4XIlA15Ksd+ao7SI/IeLKrJJ1naj6H7wBDrx6c9Dr+0e2TKityZ43zqjBk6LgEil4jmARhrD0pifqm8SZHIW7CoJp9j7SlD974bAEuPJK5N/Rb8pz8uT1Lk9kpOS29SnMLWD3KRse4wYDGeDwgCtEnL5UuIiMYVi2ryKbZ+A7r3XAfR2CSJqxNuRMCc53jySEPq6uhDQ227JMZ+anKVsUI6n1odlw2Ff5g8yRDRuGNRTT7DZu5E974bYOurlMRV0SsRtOAVrh+nYZU6jNLTaFVITIuSKRvyVANO86nZT03kTVhUk08QrQPo2X8TrJ0nJHFl6BwEL3kLglIrU2bkCRznU6dPj4NKxX+E0eiJFhNMNfslMS2XvhB5FRbV5PUG149/DZYW6SmRIjANwcvfhaDmBAe6OMdNiplZbP0g15jqj0I0XzCSURBYVBN5GRbV5NVEUUTfsQdhrn9fEhe0sYPrx/1iZcqMPIXJZEFlqbQHf8pMFtXkmgHHfuqYmVAGRMiUDRFNBBbV5NX6C56EsfJvkpigCkHw8vegDEyVKSvyJJVnGmExW+2PBYWA9GlxMmZEnshYKS2qtanspybyNiyqyWsNlP0JA8VPS4MKLYKWvg1VWLY8SZHHcZxPrU+JhH8ge/Bp9ESrGcbqfZKYH1s/iLwOi2rySsaaf6Ev//sOUQWCFv4D6mieENHocT41jZWp/hhEU68kxn5qIu/Dopq8jqnuXfQeuRtO68fn/h6ahPXyJEUeyWYTUepwUs351OQqx9YPdfR0KAOjZcqGiCYKi2ryKqaGj9Bz6E5AtEri/lk/gV/qXTJlRZ7KZqWaVQAADVdJREFUUNOG3h6jJJY5QydTNuSpHOdTs5+ayDuxqCavYW7ahZ4DtwCiWRLXZjwAv6mPypQVeTLH1o+I6CBExnAEI42eaLPCWLVXEmPrB5F3YlFNXsHcug/d+zcAtgFJXJt6NwJmPcP143RJStj6QWNkNuRDNHZJYtykSOSdWFSTx7O0H0XP3hsBq/RGIE3SrQiYs5kFNV0yFtU0VgMO/dSqqClQBnMkI5E3YlFNHs3SeRLde9ZBtEhPgjQJuQic9yIEgX/F6dJ0tPWiydApibGoJlc53qTIU2oi78WKgzyWtbsY3Xuug2hul8TVcdcicOErEBQqmTIjb+B4Su0XoEFiSqRM2ZAnEm1WDFTukcTYT03kvVhUk0ey9pSjK+8aiEbp+mhVzFoELX4NgkIjU2bkLUoLpDcpZkyPg0LJH5k0eubGkxAHOiQxTv4g8l48yiOPYLVakZeXB4PBgJhwJeZYn4BglBY9qsjlCF7yFgSln0xZkjc5c8qhnzqLrR/kGsdReqqIdKhCEmTKhogmGotqcntbt27Fxo0bUVtba4/FRwK/ukuNdUuUAABl+AIEL9sKQRUgV5rkRYwDZlSXNUtimTNZVJNrjBXSfmq2fhB5N76XSW5t69at2LBhg6SgBgBDK/CN35ix7YAVytBsBC9/H4Ka84NpfJQXN8JqtdkfKxQC0qdxYgONnmizwVjFfmoiX8KimtyW1WrFxo0bIYqi03PnIo//HQhY+i4UmvBJzY28m+NNiknp0dD6qWXKhjyRubkAtr5WScyP/dREXo1FNbmtvLw8pxPqC4kA6prN2HuoaPKSIp/A+dQ0VkaHfmplWApUYckyZUNEk4FFNbktg8Ew8kUuXEc0GjarzWnyB4tqcpVjP7VfKls/iLwdi2pyWzqdblyvIxqNuqpW9PeZJLHMGfw7RqMniqLT5A8tl74QeT0W1eS2cnJyoNfrh10zLggCEhMTkZPDEyAaPyWnpafU0XEhCI8Mkikb8kSW5iLYeqUz9P14kyKR12NRTW5LqVRi8+bNAOBUWJ97vGnTJiiVyknPjbzXGYd+6gy2fpCLHE+plSF6KMNTZcqGiCYLi2pya7m5udiyZQsSEqQLE/R6PbZs2YLc3FyZMiNvVVIgLaqnsKgmFxkrnedTD/eOGxF5Dy5/IbeXm5uL9evX2zcq6nQ65OTk8ISaxl1bczdaG7slMfZTkytEUXSa/MFRekS+gUU1eQSlUolVq1bJnQZ5Ocd+6oAgLeKTImXKhjyRpa0U1m7p3yMufSHyDWz/ICI6y7H1IyNLB4WCb9vT6BkrpKfUiqA4qCIzZcqGiCYTi2oiorOclr5ksfWDXDNQ6Tif+jL2UxP5CBbVREQA+vtMqC5vkcSmzEwY5moiZ0P1U3M+NZHvYFFNRASgrNAA0SbaHytVCqROiZUxI/I01vYKWDtrJDHOpybyHSyqiYgAlDisJk/OiIFGy3u5afQc51MrAmOgip4mUzZENNlYVBMRASg9zfnUNDbO86lXsJ+ayIewqCYin2e12lBa2CCJcT41uWrAYfKHH/upiXwKi2oi8nk15S0wDpglsUyeVJMLLB3VsHZUSmKcT03kW1hUE5HPc5xPHZsQhpCwAJmyIU/k2Pqh8I+AOmaGTNkQkRxYVBORzys5xfnUNDaONylqU3IgKPgrlsiX8DueiHyaKIo447j0ZSZbP8g1jpsUtanspybyNSyqicintTR2o6O1VxLLzGJRTaNn6aqDpa1UEuN8aiLfw6KaiHyaYz91UIgfdInhMmVDnshYIe2nFvzCoI6dJVM2RCQXFtVE5NMc51NnZsVztjC5xHE1uV/ycggKpUzZEJFcWFQTkU9z6qfmfGpy0YDj0hf2UxP5JBbVROSzenuMqKtslcQ4n5pcYe1ugKXljCSm5dIXIp/EopqIfFZZoQGieP6xSq1ESmaMfAmRx3EcpSdog6GJy5YpGyKSE4tqIvJZJQ6tH6lTYqDWqGTKhjyRYz+1Nmk5BCX/DhH5IhbVROSzSk4bJI/Z+kGuctyk6Md+aiKfxaKaiHySxWJFeXGDJMaimlxh7W2GualAEmM/NZHvYlFNRD6purQZJqNFEuN6cnKFY+uHoAmEJn6uTNkQkdxYVBORT3Jc+hKfFIGgEH+ZsiFP5HiTojZpGQSlWqZsiEhuLKqJyCedOSUtqjN4Sk0uctykqOVqciKfxqKaiHyOKIooKZDepDhlJvupafSsfW0wN52SxPzYT03k01hUE5HPaarvRFd7nySWmcWimkbPWLUHFw45F9T+0CQskDEjIpIbi2oi8jmO/dQhYf6IiQ+VKRvyRI43KWoSl0BQaWTKhojcAYtqIvI5Q82nFgRBpmzIEw04zqdmPzWRz2NRTUQ+x3GTIudTkytsA50wG/IlMW3qSpmyISJ3waKaiHxKT1c/6qvbJLEpLKrJBcaqvYBoOx9QaaFNWChfQkTkFlhUE5FPcZz6odGqkJQRLVM25IkGHEfp6RdDUPvJlA0RuQsW1UTkUxxbP1KnxkKlUsqUDXkiYyXnUxORMxbVROQzrFYrPvnoM5QbjqKhrQQ20cbWD3KJzdgNk+GYJOaXyvnURASo5E6AiGgybN26FQ8+uBF1dbX2WIA2DHMufwrAMvkSI49irN4H2KznA0o1NPrF8iVERG6DJ9VE5PW2bt2KDRs2SApqAOgzduD7P/w2tm7dKlNm5GmcVpMnLIRCEyBTNkTkTlhUE5FXs1qt2LhxI8QLtt85euihh2C1Wod9nuicAYelL+ynJqJzWFQTkVfLy8tDbW3tsM+Looiamhrk5eUNew0RANhMvTDVHZHEOJ+aiM5hUU1EXs1gMIx8kQvXke8y1RwAbJbzAYUK2qSl8iVERG6FRTUReTWdTjeu15HvGqj4XPJYkzAfCk2gTNkQkbthUU1EXi0nJwd6vR6CIAz5vCAISExMRE4Oe2Pp4owO/dR+7KcmoguwqCYir6ZUKrF582YAcCqszz3etGkTlEougKHh2cz9MNYelsS0KZxPTUTnsagmIq+Xm5uLLVu2ICEhQRLX6/XYsmULcnNzZcqMPIWp5iBgNZ0PCApokzjfnIjO4/IXIvIJubm5WL9+PfLy8mAwGKDT6ZCTk8MTahqVAYfV5Jr4uVD4hciUDRG5IxbVROQzlEolVq1aJXca5IEc+6nZ+kFEjtj+QUREdBGixTjY/nEBLn0hIkcsqomIiC7CWHsYomXgfEAQ4Je8Qr6EiMgtsagmIiK6CKNDP7U6LhsK/zB5kiEit8WimoiI6CKc51Ozn5qInLGoJiIiGoZotcBYc0AS06aw9YOInLGoJiIiGoa58SREU68kxvnURDQUFtVERETDMFbvkzxWRWZAGRQjUzZE5M5YVBMREQ3DWCUtqnlKTUTDYVFNREQ0DKPjfOqkpTJlQkTujkU1ERHRECxd9bB2VktimsQlMmVDRO6ORTUREdEQTA5TPwRtCNTR02XKhojcHYtqIiKiIRir90sea/WLICj4a5OIhsafDkREREMwVu2VPNYm8yZFIhoei2oiIiIHNlMvTIbjkpg2ebk8yRCRR2BRTURE5MBUexiwWc4HFEpo9IvkS4iI3B6LaiIiIgeOrR8a3RwoNIEyZUNEnoBFNRERkQOnmxST2PpBRBfHopqIiOgCos0KY41jUc2lL0R0cSyqiYiILmBuPAnR2C2JcfIHEY1EJXcCRERE7qSvYi/2V9rQ1APEBAHL5mRAGayTOy0icnOCKIqi3EkQERG5g61bt+K737oD9W199lh8ZAB+/9I/kZubK2NmROTuWFQTERFhsKDesGEDHH8tCgAgCNiyZQsLayIaFotqIiLyeVarFSkpKaitrR3yeUEQoNfrUVFRAaVSOcnZEZEn4I2KRETk8/Ly8oYtqAFAFEXU1NQgLy9vErMiIk/CopqIiHyewWAY1+uIyPewqCYiIp+n041uusdoryMi38OeaiIi8nnneqrr6uqcblQE2FNNRCPjSTUREfk8pVKJzZs3AxgsoC907vGmTZtYUBPRsFhUExERAcjNzcWWLVuQkJAgiev1eo7TI6IRsf2DiIjoAlarFXl5eTAYDNDpdMjJyeEJNRGNiEU1EREREdEYsf2DiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGLGoJiIiIiIaIxbVRERERERjxKKaiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGLGoJiIiIiIaIxbVRERERERjxKKaiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGLGoJiIiIiIaIxbVRERERERjxKKaiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGLGoJiIiIiIaIxbVRERERERjxKKaiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGP1/AbVQnKZUA/cAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(1,1, figsize=(10,10))\n", "for stroke_id in stroke_gdf.stroke_id:\n", @@ -523,7 +197,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -544,588 +218,18 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
geometrymm_lennode_startnode_endmy_index
0LINESTRING (1603585.64 6464428.774, 1603413.20...264.103950010
1LINESTRING (1603268.502 6464060.781, 1603296.8...99.751190231
2LINESTRING (1603607.303 6464181.853, 1603592.8...199.746503142
3LINESTRING (1603363.558 6464031.885, 1603376.5...203.014090133
4LINESTRING (1603413.206 6464228.73, 1603274.45...198.482724154
\n", - "
" - ], - "text/plain": [ - " geometry mm_len node_start \\\n", - "0 LINESTRING (1603585.64 6464428.774, 1603413.20... 264.103950 0 \n", - "1 LINESTRING (1603268.502 6464060.781, 1603296.8... 99.751190 2 \n", - "2 LINESTRING (1603607.303 6464181.853, 1603592.8... 199.746503 1 \n", - "3 LINESTRING (1603363.558 6464031.885, 1603376.5... 203.014090 1 \n", - "4 LINESTRING (1603413.206 6464228.73, 1603274.45... 198.482724 1 \n", - "\n", - " node_end my_index \n", - "0 1 0 \n", - "1 3 1 \n", - "2 4 2 \n", - "3 3 3 \n", - "4 5 4 " - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "lines.head()" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Reds\", style_kwds={\"weight\":8})\n", "lines.explore(m=m, column = \"my_index\", name = \"lines\", cmap = \"Blues\", style_kwds={\"weight\":8})\n", @@ -1144,11 +248,11 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "def _angle_cos(a, b, c):\n", + "def get_interior_angle(a, b, c):\n", " \"\"\"\n", " Measure the angle between a-b, b-c (in degrees).\n", " \"\"\"\n", @@ -1159,6 +263,8 @@ " # np.linalg.norm(bc) # np.sqrt(bc[0]**2+bc[1]**2)\n", " theta_rad = math.acos(np.dot(ba,bc)/(np.linalg.norm(ba)*np.linalg.norm(bc)))\n", " theta_deg = np.degrees(theta_rad)\n", + " if theta_deg > 90:\n", + " theta_deg = 180 - theta_deg\n", " return theta_deg\n", "\n", "def get_segment(geom, n):\n", @@ -1191,20 +297,9 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "NodeDataView({0: {'edge_indeces': [0, 3, 15, 27], 'geometry': , 'geometry_stroke': , 'x': 1603374.6625343116, 'y': 6464077.898491419, 'connectivity': 0}, 1: {'edge_indeces': [1, 12, 14, 25], 'geometry': , 'geometry_stroke': , 'x': 1603237.0487682838, 'y': 6464133.622486805, 'connectivity': 0}, 2: {'edge_indeces': [2, 11, 28, 30], 'geometry': , 'geometry_stroke': , 'x': 1603707.1065106073, 'y': 6464238.853991265, 'connectivity': 0}, 3: {'edge_indeces': [4, 5, 6], 'geometry': , 'geometry_stroke': , 'x': 1603149.9288811635, 'y': 6464130.224503239, 'connectivity': 0}, 4: {'edge_indeces': [7, 8, 9, 13, 21, 22, 24], 'geometry': , 'geometry_stroke': , 'x': 1603264.6577362637, 'y': 6463848.97596353, 'connectivity': 0}, 5: {'edge_indeces': [10], 'geometry': , 'geometry_stroke': , 'x': 1603137.4077031056, 'y': 6463800.908382258, 'connectivity': 0}, 6: {'edge_indeces': [16, 17, 18, 23, 29], 'geometry': , 'geometry_stroke': , 'x': 1603592.2349246691, 'y': 6464121.336160048, 'connectivity': 0}, 7: {'edge_indeces': [19], 'geometry': , 'geometry_stroke': , 'x': 1603028.737187382, 'y': 6463900.594576759, 'connectivity': 0}, 8: {'edge_indeces': [20], 'geometry': , 'geometry_stroke': , 'x': 1603207.5969886228, 'y': 6463992.707728057, 'connectivity': 0}, 9: {'edge_indeces': [26], 'geometry': , 'geometry_stroke': , 'x': 1603342.3426854417, 'y': 6464406.368225728, 'connectivity': 0}})" - ] - }, - "execution_count": 73, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "stroke_graph = nx.Graph()\n", "stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", @@ -1238,611 +333,9 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node: 0\n", - "Adjacent strokes (list): [0, 2, 2]\n", - "Adjacent strokes (uniques): {0, 2}\n", - "Checking edge: (0, 2)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 2])\n", - "angles: [88.68317271320804]\n", - "(0, 2) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 1\n", - "Adjacent strokes (list): [0, 2, 0, 3, 9]\n", - "Adjacent strokes (uniques): {0, 9, 2, 3}\n", - "Checking edge: (0, 9)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [62.52031121665544]\n", - "(0, 9) added\n", - "Checking edge: (0, 2)\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh0AAAGTCAYAAACMMqDSAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABkfElEQVR4nO3dd1xV9f8H8NdlXUA2yBJUVALFwVIZLkQwUH82TMoCNRumpUZ9v6WVoyzHVxNHahaKI5UMV+XCAaIiiQJu0xwgww2Xve75/WFcvYLAZdzLeD0fj/N4dD/3c89534ud+76fKRIEQQARERFRI1NTdQBERETUOjDpICIiIqVg0kFERERKwaSDiIiIlIJJBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kHUhOXm5mLatGno0KEDdHR04OXlhVOnTqk6LCJqoubNm4fevXtDX18f5ubmeOmll3DlypUaXxcbGws3Nzdoa2ujU6dOWL16daU6UVFR6NatG8RiMbp164YdO3YoHB+TDqIm7J133kF0dDQ2btyIc+fOwd/fH0OGDEF6erqqQyOiJig2NhaTJ0/GyZMnER0djbKyMvj7+yM/P/+5r7lx4wYCAwPRv39/JCUlYcaMGZgyZQqioqJkdeLj4xEUFITg4GCkpKQgODgYo0ePRkJCgkLxibjhG1HTVFhYCH19fezatQvDhg2TlTs7O2P48OGYO3euCqMjoubg3r17MDc3R2xsLAYMGFBlnc8++wy7d+/GpUuXZGUTJ05ESkoK4uPjAQBBQUGQSCTYu3evrM6LL74IY2NjbNmypdbxaNTxfRC1KkVFRSgpKan3eQRBgEgkkisTi8UQi8WV6paVlaG8vBza2tpy5To6Ojh27Fi9YyGixtVQ9w1AsXvH03JycgAAJiYmz60THx8Pf39/ubKhQ4ciPDwcpaWl0NTURHx8PD7++ONKdcLCwhR4F0w6iGpUVFQEExMTFBYW1vtcenp6yMvLkyubNWsWZs+eXamuvr4+PD098c0336Br166wsLDAli1bkJCQAHt7+3rHQkSNpyHvG4Bi944KgiAgNDQU/fr1Q/fu3Z9bLysrCxYWFnJlFhYWKCsrw/3792FlZfXcOllZWQq9DyYdRDUoKSlBYWEhxowZAy0trXqdZ/PmzUhLS4OBgYGsvLpfKhs3bsTbb7+Ndu3aQV1dHa6urhgzZgzOnDlT5ziIqPE11H2j4lyK3jsA4MMPP8TZs2dr1TL6bCtKxciLp8urqvNsWU2YdBDVkpaWVr1vHgBgYGAgd+OoTufOnREbG4v8/HxIJBJYWVkhKCgIdnZ29Y6DiBpfQ903AMXuHR999BF2796No0ePwsbGptq6lpaWlVos7t69Cw0NDZiamlZb59nWj5pw9gpRM9CmTRtYWVnh0aNH2L9/P0aOHKnqkIioCRIEAR9++CG2b9+Ow4cP1+oHiqenJ6Kjo+XKDhw4AHd3d2hqalZbx8vLS6H42NJB1ITt378fgiDAwcEB165dw3/+8x84ODhg/Pjxqg6NiJqgyZMnY/Pmzdi1axf09fVlrROGhobQ0dEBAEyfPh3p6enYsGEDgMczVVasWIHQ0FC8++67iI+PR3h4uNyslKlTp2LAgAFYsGABRo4ciV27duHgwYMKD2pnSwdRE5aTk4PJkyfD0dERISEh6NevHw4cOCD79UFE9LRVq1YhJycHgwYNgpWVleyIjIyU1cnMzERqaqrssZ2dHfbs2YOYmBg4Ozvjm2++wbJly/Dqq6/K6nh5eWHr1q1Yt24devbsiYiICERGRqJv374Kxcd1OohqIJFIYGhoiHHjxtV7IGlERARycnJq3S9LRM1TQ903gJZ172BLBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kFERERKwaSDiIiIlIJJBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kFERERKwaSDiIiIlIJJBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kFERERKwaSDiIiIlIJJBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kHURJWVleHLL7+EnZ0ddHR00KlTJ3z99deQSqWqDo2IqE40VB0AEVVtwYIFWL16NdavXw8nJyckJiZi/PjxMDQ0xNSpU1UdHhGRwph0EDVR8fHxGDlyJIYNGwYA6NixI7Zs2YLExEQVR0ZEVDfsXiFSMolEIncUFxdXWa9fv344dOgQ/v77bwBASkoKjh07hsDAQGWGS0TUYNjSQaRktra2co9nzZqF2bNnV6r32WefIScnB46OjlBXV0d5eTm+/fZbvPHGG0qKlIioYbGlg0jJ0tLSkJOTIzumT59eZb3IyEhs2rQJmzdvxpkzZ7B+/XosWrQI69evV3LERNScHD16FCNGjIC1tTVEIhF27txZbf1x48ZBJBJVOpycnGR1IiIiqqxTVFSkUGxs6SBSMgMDAxgYGNRY7z//+Q8+//xzvP766wCAHj164NatW5g3bx7Gjh3b2GESUTOVn5+PXr16Yfz48Xj11VdrrL906VLMnz9f9risrAy9evXCa6+9JlfPwMAAV65ckSvT1tZWKDYmHURNVEFBAdTU5Bsj1dXVOWWWiKoVEBCAgICAWtc3NDSEoaGh7PHOnTvx6NEjjB8/Xq6eSCSCpaVlvWJj0kHURI0YMQLffvst2rdvDycnJyQlJeH777/H22+/rerQiEgFJBKJ3GOxWAyxWNzg1wkPD8eQIUPQoUMHufK8vDx06NAB5eXlcHZ2xjfffAMXFxeFzs2kg6iW+hlGQ1dc92FQBcVSRChQf/ny5fjqq68wadIk3L17F9bW1nj//fcxc+bMOsdARMpV3/sG8OTeUdtB6PWRmZmJvXv3YvPmzXLljo6OiIiIQI8ePSCRSLB06VJ4e3sjJSUF9vb2tT4/kw6iJkpfXx9hYWEICwtTdShE1ASkpaXJjQdrjFaOiIgIGBkZ4aWXXpIr9/DwgIeHh+yxt7c3XF1dsXz5cixbtqzW52fSQURE1AzUdhB6XQmCgLVr1yI4OBhaWlrV1lVTU0Pv3r1x9epVha7BKbNERESE2NhYXLt2DRMmTKixriAISE5OhpWVlULXaNCkY9myZRCJROjevftz64hEIrk+qJiYGIhEIsTExNT7+nv27Gnw/q0KFXOUm8sS1Js3b26SzfIN+feuEBYWhldeeQV2dnYQiUQYNGhQg52biKi5ycvLQ3JyMpKTkwEAN27cQHJyMlJTUwEA06dPR0hISKXXhYeHo2/fvlV+h8+ZMwf79+/H9evXkZycjAkTJiA5ORkTJ05UKLYGTTrWrl0LALhw4QISEhIa8tS1smfPHsyZM0fp122KmmrS0RhWr16NW7duYfDgwWjbtq2qwyEiUqnExES4uLjIZpaEhobCxcVFNgg9MzNTloBUyMnJQVRU1HNbObKzs/Hee++ha9eu8Pf3R3p6Oo4ePYo+ffooFFuDjelITExESkoKhg0bhj///FOWMTVVgiCgqKgIOjo6qg6F6unixYuy9Syqa2UjImoNBg0aBEEQnvt8REREpTJDQ0MUFBQ89zVLlizBkiVL6h1bg7V0hIeHAwDmz58PLy8vbN26tdo3oKiCggJ8+umnsLOzg7a2NkxMTODu7o4tW7YAeLyM6w8//AAAcku03rx5U1b24YcfYvXq1ejatSvEYrFsOeljx47B19cX+vr60NXVhZeXF/78888aY8rMzISbmxvs7e1lg2kkEoksTi0tLbRr1w7Tpk1Dfn6+3Gu3bduGvn37wtDQELq6uujUqVOt1l/44YcfMGDAAJibm6NNmzbo0aMHFi5ciNLSUlmdQYMG4c8//8StW7fkPovqdOzYEcOHD8e+ffvg6uoKHR0dODo6ylqvnnb+/HmMHDkSxsbG0NbWhrOzc5VLc1++fBkvvvgidHV1YWZmhokTJyI3N7fK6x88eBC+vr4wMDCArq4uvL29cejQoRo/DwCVFtAiIqKmqUFaOgoLC7Flyxb07t0b3bt3x9tvv4133nkH27Zta7DlmkNDQ7Fx40bMnTsXLi4uyM/Px/nz5/HgwQMAwFdffYX8/Hz89ttviI+Pl73u6UEuO3fuRFxcHGbOnAlLS0uYm5sjNjYWfn5+6NmzJ8LDwyEWi7Fy5UqMGDECW7ZsQVBQUJXxnD9/HoGBgbCxsUF8fDzMzMxQUFCAgQMH4vbt25gxYwZ69uyJCxcuYObMmTh37hwOHjwIkUiE+Ph4BAUFISgoCLNnz4a2tjZu3bqFw4cP1/g5/PPPPxgzZowsqUlJScG3336Ly5cvyxKElStX4r333sM///yDHTt21PozTklJwSeffILPP/8cFhYW+PnnnzFhwgR06dIFAwYMAABcuXIFXl5eMDc3x7Jly2BqaopNmzZh3LhxuHPnDv773/8CAO7cuYOBAwdCU1MTK1euhIWFBX755Rd8+OGHla67adMmhISEYOTIkVi/fj00NTXx448/YujQodi/fz98fX1r/R6IiKjpapCk47fffkNOTo6sLygoKAjTpk1DeHh4gyUdx48fh7+/Pz7++GNZ2bBhw2T/3blzZ1hYWACA3Fzip+Xl5eHcuXMwNjaWlXl6esLY2BgxMTHQ09MDAAwfPhzOzs749NNPMXr06EqtBAcPHsSrr74Kf39/bNy4Ubb2/LJly3D27FkkJCTA3d0dAODr64t27dph1KhR2LdvHwICAnDixAkIgoDVq1fLLT07bty4Gj+H77//XvbfUqkU/fv3h6mpKcaPH4/FixfD2NgY3bp1g5GREcRi8XM/i6rcv38fx48fR/v27QEAAwYMwKFDh7B582ZZ0jF79myUlJTgyJEjsoVqAgMDkZ2djTlz5uD999+HoaEhlixZgnv37iEpKQm9evUC8HhpXn9/f7m+xIKCAkydOhXDhw+XS5ACAwPh6uqKGTNmqGR8EBERNbwGaZcODw+Hjo6ObGMqPT09vPbaa4iLi1N4Du/z9OnTB3v37sXnn3+OmJgYFBYWKnyOwYMHyyUc+fn5SEhIwKhRo2QJB/B4f4vg4GDcvn270uY269evR2BgIN555x38+uuvcpvd/PHHH+jevTucnZ1RVlYmO4YOHSo3Y6N3794AgNGjR+PXX39Fenp6rd9DUlIS/u///g+mpqZQV1eHpqYmQkJCUF5ejr///lvhz+Rpzs7OsoQDeLyRzwsvvIBbt27Jyg4fPgxfX99KK+ONGzcOBQUFslamI0eOwMnJSZZwVBgzZozc4xMnTuDhw4cYO3as3GcmlUrx4osv4tSpU5W6poiIqHmqd9Jx7do1HD16FMOGDYMgCMjOzkZ2djZGjRoFAFWOCaiLZcuW4bPPPsPOnTvh4+MDExMTvPTSSwolNc/OJ3706BEEQahynrG1tTUAyLpvKmzduhU6Ojp45513KrWA3LlzB2fPnoWmpqbcoa+vD0EQcP/+fQCPWxB27tyJsrIyhISEwMbGBt27d5eNT3me1NRU9O/fH+np6Vi6dCni4uJw6tQp2ViWuiRiTzM1Na1UJhaL5c774MGDWn1eDx48qHJjoGfL7ty5AwAYNWpUpc9twYIFEAQBDx8+rPubIiKiJqPe3Str166FIAj47bff8Ntvv1V6fv369Zg7dy7U1dXrdZ02bdpgzpw5mDNnDu7cuSNr9RgxYgQuX75cq3M8myQYGxtDTU0NmZmZlepmZGQAAMzMzOTKf/nlF3z11VcYOHAgDhw4AGdnZ9lzZmZm0NHReW6i9fS5Ro4ciZEjR6K4uBgnT57EvHnzMGbMGHTs2BGenp5Vvn7nzp3Iz8/H9u3b5TbiqZiLrQympqa1+rxMTU2RlZVVqd6zZRX1ly9f/tyuoIpuMyIiat7qlXSUl5dj/fr16Ny5M37++edKz//xxx9YvHgx9u7di+HDh9fnUnIsLCwwbtw4pKSkICwsDAUFBdDV1ZWtQ19YWFirqbBt2rRB3759sX37dixatEj2GqlUik2bNsHGxgYvvPCC3GtMTExw8OBBDB8+HD4+Pti7d6/sy3L48OH47rvvYGpqCjs7u1q9F7FYjIEDB8LIyAj79+9HUlLSc5OOiqTp6fX2BUHATz/9VOV569vyURVfX1/s2LEDGRkZstYNANiwYQN0dXVln4WPjw8WLlyIlJQUuS6WZzcR8vb2hpGRES5evFjlIFMiImo56pV07N27FxkZGViwYEGVq0B2794dK1asQHh4eL2Tjr59+2L48OHo2bMnjI2NcenSJWzcuBGenp7Q1dUFAPTo0QMAsGDBAgQEBEBdXR09e/asdg35efPmwc/PDz4+Pvj000+hpaWFlStX4vz589iyZUuVU0319fWxb98+vPLKK/Dz88Pu3bvh4+ODadOmISoqCgMGDMDHH3+Mnj17QiqVIjU1FQcOHMAnn3yCvn37YubMmbh9+zZ8fX1hY2OD7OxsLF26FJqamhg4cOBzY/Xz84OWlhbeeOMN/Pe//0VRURFWrVqFR48eVarbo0cPbN++HatWrYKbmxvU1NRkg1vrY9asWfjjjz/g4+ODmTNnwsTEBL/88gv+/PNPLFy4UDYwdtq0aVi7di2GDRuGuXPnymavPNsqpaenh+XLl2Ps2LF4+PAhRo0aBXNzc9y7dw8pKSm4d+8eVq1aVW1MiYmJsqnREolE1vIGPB4/8+z2zEREpBr1SjrCw8OhpaWF8ePHV/m8mZkZXn75Zfz222+4c+dOvZrJBw8ejN27d2PJkiUoKChAu3btEBISgi+++EJWZ8yYMTh+/DhWrlyJr7/+GoIg4MaNG+jYseNzzztw4EAcPnwYs2bNwrhx4yCVStGrVy/s3r272kRJR0cHu3btwpgxYxAYGIioqCgEBgYiLi4O8+fPx5o1a3Djxg3o6Oigffv2GDJkiCyOvn37IjExEZ999hnu3bsHIyMjuLu74/Dhw3BycnruNR0dHREVFYUvv/wSr7zyCkxNTTFmzBiEhoYiICBAru7UqVNx4cIFzJgxAzk5ORAEodrFYmrLwcEBJ06cwIwZMzB58mQUFhaia9euWLdundzsG0tLS8TGxmLq1Kn44IMPoKuri5dffhkrVqzAyJEj5c751ltvoX379li4cCHef/995ObmwtzcHM7OzrWa0bNixYpK64S89tprAFApLiIiUh2R0BDfREQtmEQigaGhIX6e2g664rqPvS4oluKdpenIyclp1J0iiUj1Guq+AbSseweXciQiIiKlYNJBRERESsGkg4iIiJSCSQcR1VtCQgJefvlltG/fHmKxGBYWFvD09MQnn3wiV2/lypVV7nDZEMaNGye3srAqxcXFQSwWy63mCwBnzpzBkCFDoKenByMjI7zyyiu4fv16na+zfft2vPHGG+jSpQt0dHTQsWNHvPnmm5UWTSwtLUXnzp0RFhZW52s9z3fffYedO3c2+Hnra/bs2TVudKmI3Nxc/Pe//4W/vz/atm0LkUiE2bNnN9j5WwsmHURUL3/++Se8vLwgkUiwcOFCHDhwAEuXLoW3tzciIyPl6jZm0tFUCIKAadOm4d1335Wbrn358mUMGjQIJSUl+PXXX7F27Vr8/fff6N+/P+7du1enay1YsAAFBQX44osvsG/fPsydOxdJSUlwdXXFhQsXZPU0NTUxc+ZMfP3115VWWa6vppp0NLQHDx5gzZo1KC4uxksvvaTqcJqtBtnwjYhar4ULF8LOzg779++HhsaTW8rrr7+OhQsX1vm8paWlEIlEcudsDvbt24czZ85UWghv5syZEIvF+OOPP2QzENzc3GBvb49FixZhwYIFCl/r999/h7m5uVzZ4MGD0bFjRyxZskRu0cY33ngDoaGh+PHHHzFjxow6vLPWrUOHDnj06BFEIhHu379f5YKYVDO2dBBRvTx48ABmZmZVJgdqak9uMR07dsSFCxcQGxsLkUgEkUgkW7smJiYGIpEIGzduxCeffIJ27dpBLBbj2rVrAB5vt9CrVy9oa2vDxMQEL7/8Mi5dulRjbMePH4eZmRmGDx8u2zjw6tWrGDNmDMzNzSEWi9G1a1fZ/kUVpFIp5s6dCwcHB+jo6MDIyAg9e/bE0qVLa7zmqlWr0Lt3bzg4OMjKysrK8Mcff+DVV1+Vm/LYoUMH+Pj4yO2wrIhnEw7g8T5INjY2SEtLkyvX0tJCUFAQ1qxZU+OaPUVFRfjkk0/g7OwMQ0NDmJiYwNPTE7t27ZKrJxKJkJ+fj/Xr18v+plUtFFnh5s2bEIlEWLRoEb7//nvY2dlBT08Pnp6eOHnyZKX6u3fvli0Aqa+vDz8/P9mmkk/7888/4ezsDLFYDDs7OyxatKjK6wuCgJUrV8LZ2Rk6OjowNjbGqFGjatXFVfH+qH6YdBBRvXh6eiIhIQFTpkxBQkICSktLq6y3Y8cOdOrUCS4uLoiPj0d8fHylL9vp06cjNTUVq1evlv2KnzdvHiZMmAAnJyds374dS5cuxdmzZ+Hp6Vntho+//vorfH19MXr0aOzatQtt2rTBxYsX0bt3b5w/fx6LFy/GH3/8gWHDhmHKlCmYM2eO7LULFy7E7Nmz8cYbb+DPP/9EZGQkJkyYgOzs7Go/i5KSEhw8eBA+Pj5y5f/88w8KCwvRs2fPSq/p2bMnrl27hqKiomrPXVvXr1/HrVu3qlxocNCgQbh16xbOnz9f7TmKi4vx8OFDfPrpp9i5cye2bNmCfv364ZVXXsGGDRtk9eLj46Gjo4PAwEDZ33TlypU1xvjDDz8gOjoaYWFh+OWXX5Cfn4/AwEDk5OTI6mzevBkjR46EgYEBtmzZgvDwcDx69AiDBg3CsWPHZPUOHTqEkSNHQl9fH1u3bsX//vc//Prrr1i3bl2l677//vuYNm0ahgwZgp07d2LlypW4cOECvLy8ZJtPUuNqXu2WRNTkzJ8/H5cvX8by5cuxfPlyaGpqonfv3hgxYgQ+/PBD2eBOFxcX6OjowMDA4Lmb+3Xu3Bnbtm2TPc7OzsY333yDwMBAue6KQYMGwd7eHrNnz8Yvv/xS6TwLFizAF198ge+++w7//e9/ZeWhoaHQ19fHsWPHZC0Ofn5+KC4uxvz58zFlyhQYGxvj+PHj6NGjh9xAwaFDh9b4WSQnJ6OwsBCurq5y5RXjKExMTCq9xsTEBIIg4NGjR1Xu4KyIsrIyTJgwAXp6evj4448rPV8RV8X7ex5DQ0O5L+3y8nL4+vri0aNHCAsLQ0hICADAw8MDampqaNu27XP/plXR19fHH3/8IdsI1NraGn369MHevXvx+uuvQyqV4j//+Q969OiBvXv3ylrMAgMD0blzZ3z22Wc4fvw4AOCLL76AhYUFoqOjoa2tDeDx3+rZlahPnjyJn376CYsXL0ZoaKisvH///njhhRfw/fff16mLixTDlg4iqhdTU1PExcXh1KlTmD9/PkaOHIm///4b06dPR48ePXD//v1an+vVV1+VexwfH4/CwsJKS9nb2tpi8ODBOHTokFy5IAh4//33MWvWLGzevFku4SgqKsKhQ4fw8ssvQ1dXF2VlZbIjMDAQRUVFsib+Pn36ICUlBZMmTcL+/fshkUhqFX/FbstVdXsAlXe6ru1ztSEIAiZMmIC4uDhs2LABtra2lepUxJWenl7j+bZt2wZvb2/o6elBQ0MDmpqaCA8Pr1W3Vk2GDRsmt/N4RQtQxWyfK1euICMjA8HBwXJddHp6enj11Vdx8uRJFBQUID8/H6dOncIrr7wiSziAx0nNiBEj5K75xx9/QCQS4a233pL721taWqJXr16IiYmp9/uimjHpIKIG4e7ujs8++wzbtm1DRkYGPv74Y9y8eVOhwaTP/tKvaCGoqgXA2tq60kyMkpISREZGwsnJqdJ+RA8ePEBZWZmsNebpIzAwEABkCdL06dOxaNEinDx5EgEBATA1NYWvry8SExOrjb9iZ+envwCBx4nZ0+/naQ8fPoRIJIKRkVG1566OIAh45513sGnTJkRERFTa36hCRVw17UC9fft2jB49Gu3atcOmTZsQHx+PU6dO4e23326QbqCKz6PC0zuEAzX/3aVSKR49eoRHjx5BKpXC0tKyUr1ny+7cuQNBEGBhYVHp73/y5EmFkmOqO3avEFGD09TUxKxZs7BkyZIaxw887dlf+xVfTpmZmZXqZmRkwMzMTK5MLBbjyJEjGDp0KIYMGYJ9+/bB2NgYAGBsbAx1dXUEBwdj8uTJVV7fzs4OAKChoYHQ0FCEhoYiOzsbBw8exIwZMzB06FCkpaXJdrZ+VkU8Dx8+lCvv3LkzdHR0cO7cuUqvOXfuHLp06VIpUamtioRj3bp1CA8Px1tvvfXcuhVxPfu5PWvTpk2ws7NDZGSk3N+kuLi4TjEqqqa/u5qaGoyNjSEIAkQiEbKysirVe7bMzMwMIpFItobKs6oqo4bHlg4iqpeqvhgAyJrhra2tZWVisbjGX9lP8/T0hI6ODjZt2iRXfvv2bRw+fBi+vr6VXuPi4oLY2Fjcvn0bgwYNwt27dwEAurq68PHxQVJSEnr27Al3d/dKx7O/wAHAyMgIo0aNwuTJk/Hw4UPcvHnzufF27doVwOOBo0/T0NDAiBEjsH37duTm5srKU1NTceTIEbzyyiu1/kyeJggC3n33Xaxbtw4//vjjc3f8rlAxS6Nbt27V1hOJRNDS0pJLOLKysirNXgEU/5vWhoODA9q1a4fNmzfLzbTJz89HVFSUbEZLmzZt0KdPH2zfvl2uBSY3Nxe///673DmHDx8OQRCQnp5e5d++ujEu1HDY0kFE9TJ06FDY2NhgxIgRcHR0hFQqRXJyMhYvXgw9PT1MnTpVVrdHjx7YunUrIiMj0alTJ2hra1d7szcyMsJXX32FGTNmICQkBG+88QYePHiAOXPmQFtbG7NmzarydV27dkVcXByGDBmCAQMG4ODBg7CxscHSpUvRr18/9O/fHx988AE6duyI3NxcXLt2Db///jsOHz4MABgxYgS6d+8Od3d3tG3bFrdu3UJYWBg6dOgAe3v758ZrY2ODTp064eTJk5gyZYrcc3PmzEHv3r0xfPhwfP755ygqKsLMmTNhZmZWaeXWQYMGITY2tsaprVOmTEF4eDjefvtt9OjRQ27aqVgshouLi1z9kydPQl1dHQMGDKj2vMOHD8f27dsxadIkjBo1Cmlpafjmm29gZWVVacZQjx49EBMTg99//x1WVlbQ19eXmy5cF2pqali4cCHefPNNDB8+HO+//z6Ki4vxv//9D9nZ2Zg/f76s7jfffIMXX3wRfn5++OSTT1BeXo4FCxagTZs2ci1O3t7eeO+99zB+/HgkJiZiwIABaNOmDTIzM3Hs2DH06NEDH3zwQbVx7d27F/n5+bLE8eLFi/jtt98APB7k+rwWMHqCSQcR1cuXX36JXbt2YcmSJcjMzERxcTGsrKwwZMgQTJ8+XfbrH3j8xZuZmYl3330Xubm56NChQ7UtB8Dj8RXm5uZYtmwZIiMjoaOjg0GDBuG7776rNgHo1KmTLPHo378/Dh06hG7duuHMmTP45ptv8OWXX+Lu3bswMjKCvb29bFwHAPj4+CAqKgo///wzJBIJLC0t4efnh6+++gqamprVxvvmm29ixYoVKC4ulmuyd3R0RExMDD777DOMGjUKGhoaGDx4MBYtWoS2bdvKnSMvL6/KcQrPqvg1v3btWqxdu1buuao+2507dyIwMLDG8SPjx4/H3bt3sXr1aqxduxadOnXC559/jtu3b8tNLQaApUuXYvLkyXj99ddRUFCAgQMHNsigzDFjxqBNmzaYN28egoKCoK6uDg8PDxw5cgReXl6yen5+fti5cye+/PJLBAUFwdLSEpMmTUJhYWGlWH/88Ud4eHjgxx9/xMqVKyGVSmFtbQ1vb2/06dOnxpg++OADuaXtt23bJpttdePGjUozZqgykVBTKk3UykkkEhgaGuLnqe2gK657j2RBsRTvLE1HTk6O3AJRz9OxY8dKe3cAwKRJkyotZkVNR0ZGBuzs7LBhwwYEBQUp/Prc3FyYmJggLCzsuWNP6uKff/6Bvb099u/fDz8/vwY7L1Wtoe4bgOL3jqaMYzqImqhTp04hMzNTdkRHRwMAXnvtNRVHRtWxtrbGtGnT8O2330IqlSr8+qNHj6Jdu3Z49913GzSuuXPnwtfXlwkHqRS7V4iaqGeb3OfPn4/OnTtj4MCBKoqIauvLL7+Erq4u0tPTq1wvozrDhg3DsGHDGjSesrIydO7cGdOnT2/Q8xIpikkHkZI9u9CUWCyucbpeSUkJNm3ahNDQUO7/0Azo6+s/d5CrKmhoaODLL79UdRhE7F4hUjZbW1sYGhrKjnnz5tX4mp07dyI7O7vSypxERM0JWzqIlCwtLU1uMFhtFiUKDw9HQECA3JoXRETNDZMOIiUzMDBQaAT6rVu3cPDgQWzfvr0RoyIianzsXiFq4tatWwdzc/MGH1xIRKRsTDqImjCpVIp169Zh7Nix0NBgwyQRNW9MOoiasIMHDyI1NRVvv/22qkMhIqo3Jh1ETZi/vz8EQcALL7yg6lCIqJk4evQoRowYAWtra4hEIuzcubPa+jExMRCJRJWOy5cvy9WLiopCt27dIBaL0a1bN+zYsUPh2Jh0EBERtSD5+fno1asXVqxYodDrrly5IrcK8tN7G8XHxyMoKAjBwcFISUlBcHAwRo8ejYSEBIWuwU5iIiKiFiQgIAABAQEKv87c3Py5mwGGhYXBz89Ptqrt9OnTERsbi7CwMGzZsqXW12BLBxERUTMgkUjkjuLi4gY9v4uLC6ysrODr64sjR47IPRcfHw9/f3+5sqFDh+LEiRMKXYMtHUS11N81A/q6dV+CPLeAGzoTtTb1vW8AT+4dz+7jM2vWLMyePbte5wYAKysrrFmzBm5ubiguLsbGjRvh6+uLmJgYDBgwAACQlZUFCwsLuddZWFggKytLoWsx6aAW5/KjLDgaW6o6DCJqRjLzc6CtoQljsa6qQ3muuqxmXBsODg5wcHCQPfb09ERaWhoWLVokSzoAVNr3SRAEhfeCYvcKtSjrL8XDb+dS/HQhTtWhEFEzkVtShJDodXjpz1W4lftA1eE8V8VqxhVHQyUdVfHw8MDVq1dljy0tLSu1aty9e7dS60dNmHRQi3Eo7TK+StgNAQKKyspUHQ4RNQNl0nJ8ELMZlx5lQVJSCHURvxYBICkpCVZWVrLHnp6eiI6Olqtz4MABeHl5KXRedq9Qi3DhQQYmxWyGVBAQZO+OD3sOUnVIRNTECYKAr07uRkz639BW18Q637Gw0TNWdVj1lpeXh2vXrske37hxA8nJyTAxMUH79u0xffp0pKenY8OGDQAez0zp2LEjnJycUFJSgk2bNiEqKgpRUVGyc0ydOhUDBgzAggULMHLkSOzatQsHDx7EsWPHFIqNSQc1exn5OQg5GIH8shL0s+qC+V4vK9zPSEStz4/n47DxSgJEEOGHga/Dua1tzS9qBhITE+Hj4yN7HBoaCgAYO3YsIiIikJmZidTUVNnzJSUl+PTTT5Geng4dHR04OTnhzz//RGBgoKyOl5cXtm7dii+//BJfffUVOnfujMjISPTt21eh2ESCIHBIPTVbeaXFeGXPalx8mIkXjMyxI/ADGIp1GvQaEokEhoaGuLJeVO/ZKw5jBeTk5Ci0yywRNbw/b57D+0d+AQDM7jMc7zj1a9DzN9R9A2hZ9w52XlGzVSYtxwdHNuPiw0y01dHD+iHjGjzhIKKW58y9VEw5GgkAGOvoiQndvFUcUevBpIOaJUEQMDPhdxxJvyLri7XVN1F1WETUxKXmPsT4g+tRXF4GXxtHzOk7nN2xSsSkg5qlny4cw4bLJyGCCMsHBrWYvlgiajzZxQUIiV6HB0X56G5ijZWD3oCGmrqqw2pVmHRQs7P31nl8c2oPAOCr3oEI6NBdxRERUVNXUl6G9w5vwrWce7DUNcC6IWPRRrPx1rmgqjHpoGYl6V4aPoqNhAABYx098G4DD/4iopZHEAR8dmI7TmRdRxsNLWzwGwerNoaqDqtVYtJBzUbav32xReWlGGzjgDl9R7AvlohqtCzlMLZdOwN1kRpW+7yJbibWqg6p1WLSQc1CTnEhQqIjcL8oD04mVlg5aAz7YomoRjv+Scb/kh6vpDnX4//gY+NQwyuoMTHpoCavpLwM7x3ZhKs5d2Gpa4CIIeOgx75YIqpBQtYNfHJsGwDg/e4DEOzooeKIiEkHNWmCIGB6/A4cz/yHfbFEVGvXc+5hwuGNKJGWI7BDd3zh/qKqQyIw6aAmbvnZI4i8ehpqIhFWDhrDvlgiqtHDonyEREcgu7gAzma2WDpgNNS4kVuTwL8CNVk7rydj4ZkDAIC5HiPha+uo4oiIqKkrKivF24c24GbuA9jqGWPdkBDoaGipOiz6V4tNOkpKShAXF4eff/4Z3F6m+fnrzk2Exv3bF+vUHyHsiyWiGkgFKUKPbUPi3Vsw0NLGBr/xaKujr+qw6CktNukoLy/Hr7/+ilOnTuGff/5RdTikgOs59/H2oQ0okZbjxfZO+KJ3gKpDIqJm4H9norH7xlloiNTwk89bsDcyV3VI9IwWm3To6Oigd+/eAIC4uDgVR0O19bgvdp2sL3b5wCD2xRJRjbb+fQrLzx4BAPzP+1V4W3dRcURUlRZ9N+/fvz8A4PTp08jPz1dxNFSTorJSTPi3L9ZGz4h9sURUK3EZV/H5iR0AgKm9BuM1ezcVR0TP06KTjo4dO8LGxgalpaVISEhQdThUDakgxSfHf8Mp9sUSkQKuPLqD9w5vQpkgxUudnPGpi5+qQ6JqtOikQyQSyVo74uLiOKC0CVt0Jhq7rqdAQ6SGNT5v4QUjC1WHRERN3N2CXIREr0NuaTH6WnTE4n6juDVCE9eikw4A6Nu3LzQ1NZGRkYHr16+rOhyqQuTVRCz7ty92gfcr6Me+WCKqQWFZCcYfWo/0/GzYGZjh58HBEKtrqDosqkGLTzo4oLRpO5ZxDZ8d3w4AmNLTB0H27iqOiIiaunKpFB/GbkXK/dswFutig984GGu3UXVYVAstPukAngwoTUxM5IDSJuTv7Dt478jjvtiRnXrhP67+qg6JiJqBuYl7sD/1IsTqGljrGwI7AzNVh0S11CqSDjs7Ow4obWLuFT7ui5WUFKGPRUcs9mZfbFXS09Px1ltvwdTUFLq6unB2dsbp06dVHRaRykRcisdPF44BAL7v9xp6W3RUbUCkkFaRdIhEIvTr1w8AB5Q2BYVlJRh3cD1u52Wjo74pfh4cDG0NTVWH1eQ8evQI3t7e0NTUxN69e3Hx4kUsXrwYRkZGqg6NSCUOpV3GzITdAIDPXIdiZKdeKo6IFNVqRt307dsXUVFRsgGlnTt3VnVIrVK5VIqPYiOf6osdDxP2xVZpwYIFsLW1xbp162RlHTt2VF1ARCp0/kE6PojZDKkg4HV7d3zYc5CqQ6I6aBUtHQCgq6sLd/fHgxQ5oFR1vkvci32pF6Clpo5w3xB0Mmx9fbESiUTuKC4urrLe7t274e7ujtdeew3m5uZwcXHBTz/9pORoiVQvIz8HYw+uR0FZCfpZdcE8r5fZHdtMtZqkA5AfUFpQUKDiaFqfDZdP4scLjxO+7/u/hj6ttC/W1tYWhoaGsmPevHlV1rt+/TpWrVoFe3t77N+/HxMnTsSUKVOwYcMGJUdMpDp5pcUYdzACdwokeMHIHD/6vAlNNXVVh0V11Gq6VwCgU6dOsLa2RkZGBhISEuDj46PqkFqNQ2mX8eXJXQCA/7r646VOzqoNSIXS0tJgYGAgeywWi6usJ5VK4e7uju+++w4A4OLiggsXLmDVqlUICQlRSqxEqlQmLcfEI7/g4sNMtNXRwwa/8TAU66g6LKqHVtXSIRKJMGDAAAAcUKpMFx9mYNK/fbFB9m74qGfrTvYMDAzkjuclHVZWVujWrZtcWdeuXZGamqqMMIlUShAEfHVyN2LS/4a2uibW+Y6FjZ6xqsOiempVSQfwZIXS9PR03LhxQ9XhtHgZ+TkIiY5AflkJvK06Y54n+2Jry9vbG1euXJEr+/vvv9GhQwcVRUSkPGsuxGHjlQSIIMKKga/Dua2tqkOiBtDqkg4OKFWevNJijD8Ygax/+2LX+LwFLS5TXGsff/wxTp48ie+++w7Xrl3D5s2bsWbNGkyePFnVoRE1qj9vnsPcU3sBADP7BOLFDk4qjogaSqtLOoAnA0pPnTqFwsJCFUfTMpVJyzEpZjMuPMyEmbYe1g8Zx75YBfXu3Rs7duzAli1b0L17d3zzzTcICwvDm2++qerQiBrNmXupmHI0EgIEjHX0xDvd+qk6JGpArfJn59MDSk+ePMkBpQ1MEATMSvgdh29fedwXO2QsbPVNVB1WszR8+HAMHz5c1WEQKUVq7kO8fXADisvLMNjGAXP6Dmd3bAvTKls6uOV94/r54jGsv3wSIoiwfGAQXNgXS0Q1yC4uwNjoCNwvyoOTiRVWDRoDDU6NbXFaZdIByA8ovXnzpqrDaTH23jqPr//aAwD4sncAAjp0V3FERNTUlZSX4f0jv+Bqzl1Y6hogYsg4tNGselYXNW+tNulo06YN3NzcAHBAaUNJupeGj2If98WGOHrgPaf+qg6JiJo4QRDw+YkdOJ75D9poaGGD3zhYtTFUdVjUSFpt0gFwQGlDSst9iPEH16OovBQ+7Rzwdd8R7IslohotSzmMX6+dhrpIDat83kQ3E2tVh0SNqFUnHZ07d4aVlRVKSkrw119/qTqcZiunuBBjDz7ui+1mYoVVPuyLJaKa7fgnGf9LigYAzPX4Pwy2cVBxRNTYWnXS8fSA0qNHj3JAaR1U9MX+nX0XFv/2xeqxL5aIapCQdQOfHNsGAHi/+wAEO3qoOKKW4+jRoxgxYgSsra0hEomwc+fOautv374dfn5+aNu2LQwMDODp6Yn9+/fL1YmIiIBIJKp0FBUVKRRbq046AMDDwwOampq4ffs2B5QqSBAETI/fiWOZ16CroYUNQ8bBmn2xRFSD6zn3MOHwRpRIyxHQwQlfuL+o6pBalPz8fPTq1QsrVqyoVf2jR4/Cz88Pe/bswenTp+Hj44MRI0YgKSlJrp6BgQEyMzPlDm1tbYVia5XrdDytYkDpyZMnERcXBzs7O1WH1GysOBuDyKuJUBOJsGrQGDiZsi+WiKr3sCgfIdERyC4ugLOZLZYNCIKaqNX//m1QAQEBCAgIqHX9sLAwucffffcddu3ahd9//x0uLi6ycpFIBEtLy3rFxr80OKC0LnZeT8aCM4+b377p+3/wtXVUcURE1NQVlZViwqENuJn7ALZ6xlg3JAQ6GlqqDqvZkEgkckdxcXGjXEcqlSI3NxcmJvKLOubl5aFDhw6wsbHB8OHDK7WE1Earb+kAngwozczMxF9//YWBAweqOqQm7a87NxEa97gv9j2nfhjb1VPFESnHvNJ20Cqte55eUioFcLvhAiJqRqSCFJ8c+w2n7t6CgZY21vuNQ1sdfVWH1ejqe98Antw7bG3lF1qcNWsWZs+eXa9zV2Xx4sXIz8/H6NGjZWWOjo6IiIhAjx49IJFIsHTpUnh7eyMlJQX29va1PjeTDjxuMurXrx+2bduGuLg4DBgwgNM9n+OG5D4mHNqAEmk5XmzvhC/cA1UdEhE1A/87E41dN1KgIVLDTz5v4QUjC1WH1OykpaXBwMBA9lgsbvhB+1u2bMHs2bOxa9cumJuby8o9PDzg4fFksK+3tzdcXV2xfPlyLFu2rNbnZ/fKvzw9PaGhoYG0tDTcunVL1eE0SY/+7Yt9VFyAXmY2WD4wCOpq/CdERNXb+vcpLD97BACw0PsVeFt3UXFEzZOBgYHc0dBJR2RkJCZMmIBff/0VQ4YMqbaumpoaevfujatXryp0DX5j/IsrlFavuLwMEw5vxA3JfdjoGWGd71j2xRJRjeIyruLzEzsAAFN7DcZoe3cVR0RV2bJlC8aNG4fNmzdj2LBhNdYXBAHJycmwsrJS6DpMOp7CAaVVEwQBnxz7DX/dufm4L3bIeJjrtvy+WCKqnyuP7uC9w5tQJkjxUidnfOrip+qQWoW8vDwkJycjOTkZAHDjxg0kJycjNTUVADB9+nSEhITI6m/ZsgUhISFYvHgxPDw8kJWVhaysLOTk5MjqzJkzB/v378f169eRnJyMCRMmIDk5GRMnTlQoNiYdT+nSpQssLS1RXFyMU6dOqTqcJmNRUjR2Xk+GhkgNa3zegoMx+2KJqHp3C3Ix9uA65JYWo49FRyzuN4pj5ZQkMTERLi4usumuoaGhcHFxwcyZMwEAmZmZsgQEAH788UeUlZVh8uTJsLKykh1Tp06V1cnOzsZ7772Hrl27wt/fH+np6Th69Cj69OmjUGwcSPqUihVKnx5Q2tr9ejURS1MOAwDme72MfuyLJaIaFJaVYPyh9bidlw07AzOEDw6GWJ1fN8oyaNCgalfYjoiIkHscExNT4zmXLFmCJUuW1DMytnRU4uHhAQ0NDaSmprb6FUqPZ1zDf49vBwB81NMHr7/QW8UREVFTVy6V4sPYrUi5fxvGYl1s8BsHY+02qg6LmggmHc/Q09ODq6srgNY9oPTv7Dt498jjvtiRdr3wH1f2xRJRzb5N3IP9qRehpaaOtb4hsDMwU3VI1IQw6ajC0wNKFd3MpiW4V5iLsdERkJQUobd5ByzuN4rLFBNRjdZfiseaC8cAAEv6j0Zvi46qDYiaHH6TVMHe3h4WFhYoLi5udVveF5aVYPzBDUjLe4SO+qYI9w2BtoamqsMioibuUNplfJWwGwDwmetQjOzUS8URUVPEpKMKT29535q6WKSCFFOORiL5fhqMxLrY4DceJuyLJaIaXHiQgQ9iNkMqCAiyd8eHPQepOiRqoph0PEfFCqWpqamtZoXSbxP3Ye+tC9BSU0f44GB0MmRfLBFVLyM/ByEHI1BQVoJ+Vl0w3+tlTo2l52LS8Rx6enqyOc6tobVj4+WT+PH8UQDA4n6voa+lnYojIqKmLq+0GOMORuBOgQQvGJnjR583oammruqwqAlj0lGNinU6/vrrrxY9oPTw7Sv44uQuAMB/XPzwcmdn1QZERE1embQcHxzZjIsPM9FWRw/rh4yDoVhH1WFRE8ekoxpPDyhtqSuUXnyYgQ+O/AKpIGB0FzdM6TVY1SERURMnCAJmJvyOI+lXoK2uiXW+Y2Grb6LqsKgZYNJRjZY+oDQzPwch0RHILyuBt1Vn9sUSUa2suRCHDZdPQgQRVgx8Hc5tbVUdEjUTTDpqUDGg9NatW3Jr1Td3FX2xWQUS2BuaY43PW9DiMsVEVIM9N89j7qm9AICZfQLxYgcnFUdEzQmTjhq0xAGlZdJyTIrZjAsPM2GmrYf1fuyLJaKaJd1Lw5SjkRAgYKyjB97p1k/VIVEzw6SjFiq6WBISEpr9gFJBEDAr4Q8cvn0FYnUNrB0SgvbsiyWiGqTmPsT4g+tRVF6KwTYOmNN3BLtjSWFMOmrhhRdegLm5OYqLi5GYmKjqcOrl54vHsP5yPEQQYfmA1+Hatr2qQyKiJi6nuBBjoyNwvygPTiZWWDVoDDQ4NZbqgElHLbSUAaX7bl3A13/tAQB82TsAgR27qzgiqs7s2bMhEonkDktLS1WHRa1MSXkZ3juyCVdz7sJS1wARQ8ahjaZY1WFRM8Wko5Y8PT2hrq6OmzdvNssBpcn30vBh7FYIEBDs0BfvOfVXdUhUC05OTsjMzJQd586dU3VI1IoIgoDPT+zA8cx/0EZDCxv8xsGqjaGqw6JmjElHLenr68sGlB47dkzF0SgmLfchxh963Bfr084B33j8H/timwkNDQ1YWlrKjrZt26o6JGpFlp89gl+vnYaaSIRVPm+im4m1qkOiZo5JhwKa44DSnOJCjD0YgXuFeehqbIlVPuyLVTWJRCJ3FBcXP7fu1atXYW1tDTs7O7z++uu4fv26EiOl1mzn9WQsPHMAADDXYyQG2zioOCJqCZh0KMDBwQHm5uYoKipqFgNKS6XlmBjzC/7OvgsLXQOs9xsPPfbFqpytrS0MDQ1lx7x586qs17dvX2zYsAH79+/HTz/9hKysLHh5eeHBgwdKjpham4SsGwiN2wYAeN+pP0IcPVQcEbUUXA1KASKRCP369cP27dsRFxeHfv2a7hz1ir7YuIxr0NXQwvohY2HNvtgmIS0tDQYGBrLHYnHViWBAQIDsv3v06AFPT0907twZ69evR2hoaKPHSa3T9Zz7mHB4I0qk5Qjo4IQvegfU/CKiWmJLh4KeHlCalpam6nCe64dzMYi8mvi4L3bQGHQ3bafqkOhfBgYGcsfzko5ntWnTBj169MDVq1cbOUJqrR4W5SMkeh2yiwvgbGaLZQOCoCbi1wQ1HP5rUpCBgQGcnZ0BNN3ps7uup2D+6f0AgK/7/h98bR1VHBE1hOLiYly6dAlWVlaqDoVaoKKyUkw4tAE3cx/AVs8Y64aEQEdDS9VhUQvDpKMOnh5QWt0gQFU4decmQo897ot916kfxnX1VHFEVFeffvopYmNjcePGDSQkJGDUqFGQSCQYO3asqkOjFkYqSPHJsd9w6u4tGGhpY73fOLTV0Vd1WNQCMemog6Y6oPSG5D7ePrQBxeVlGNq+G750D1R1SFQPt2/fxhtvvAEHBwe88sor0NLSwsmTJ9GhQwdVh0YtzKIz0dh1IwUaIjWs8XkLLxhZqDokaqE4kLQO1NTU5AaUent7qzokPCrKR0h0BB4VF6CXmQ2WD3gd6mrMKZuzrVu3qjoEagW2/n0Ky84eAQAs9H4F/ay7qDgiasn4rVRHFQNKb9y4ofIBpcXlZXjn8EbckNyHjZ4R1vmOha4m+2KJqHrHMq7h8xM7AABTew3GaHt3FUdELR2Tjjp6ekCpKlcoFQQBnxz7DQl3bkJfU4z1Q8bDXJd9sURUvb+z7+C9I5tQJkgxslMvfOrip+qQqBVg0lEPFQNKT548iZKSEpXEsCgpGjuvJz/uix38FhyM2RdLRNW7W5CLkOh1kJQUoY9FR3zf7zVujUBKwaSjHhwcHGBmZoaioiKcOnVK6df/9WoilqYcBgDM93oZ/a3tlR4DETUvhWUlGH9oPW7nZcPOwAzhg4MhVufwPlIOJh31oKamprIt749nXMN/j28HAHzU0wevv9BbqdcnouanXCrFR7GRSLl/G8ZiXawfMg7G2m1UHRa1Ikw66snLywtqamq4ceMGbt++rZRrXs2+i3f/7Yv9P7ue+I8r+2KJqGbfJu7BvtQL0FJTR7hvCDoZmqk6JGplmHTUk7JXKL1X+KQvtrd5B3zf7zUuU0xENVp/KR5rLjwe9P59/9fQx6KjagOiVonfVg3g6RVKG3NAaWFZKd4+tAFpeY/QQd8U4b4h0NbQbLTrEVHLcCjtMr5K2A0A+K+rP17q5KzagKjVYtLRABwdHWFmZobCwsJGW6FUKkgx9Wgkku6lwUisi41+42DCvlgiqsGFBxmYFLMZUkFAkL07Purpo+qQqBVj0tEAlDGg9LvEfdhz6/zjvtjBwehk2LZRrkNELUdGfg5CDkYgv6wE/ay6YL7Xy5waSyrFpKOBeHp6Qk1NDdevX0d6enqDnnvT5QSsPn8UALC432voa2nXoOcnopYnr7QY4w5G4E6BBC8YmeNHnzehqaau6rBICY4ePYoRI0bA2toaIpEIO3furPE1sbGxcHNzg7a2Njp16oTVq1dXqhMVFYVu3bpBLBajW7du2LFjh8KxMeloIIaGho0yoPTI7Sv44uQuAMCnLn54ubNzg52biFqmMmk5PjiyGRcfZqKtjh7WDxkHQ7GOqsMiJcnPz0evXr2wYsWKWtW/ceMGAgMD0b9/fyQlJWHGjBmYMmUKoqKiZHXi4+MRFBSE4OBgpKSkIDg4GKNHj0ZCQoJCsXFFmAbUv39/nDlzBgkJCbJdQevj4sMMTDzyC8oFKV7r4oqpvQY3UKRE1FIJgoCZCb/jSPoVaKtrYq3vWNjqm6g6LFKigIAABAQE1Lr+6tWr0b59e4SFhQEAunbtisTERCxatAivvvoqACAsLAx+fn6YPn06AGD69OmIjY1FWFgYtmzZUutrsaWjATk6OsLU1BQFBQU4ffp0vc6VVSDB2Oj1yC8rgZdlJyzweoV9sURUo58uHMOGyychggjLBwbBpa2tqkOiBiKRSOSO4uLiBjlvfHw8/P395cqGDh2KxMRElJaWVlvnxIkTCl2LLR0NqGLL+127diEuLg6enp51Ok9+aTHGRUcgsyAHXQzbYs3gt6DFZYpVbsbC96Cvrl3n1+eWFyECMxswIiJ5e2+dxzen9gAAvuodiIAO3VUcEdX3vgE8uXfY2sonkLNmzcLs2bPrdW4AyMrKgoWF/L5dFhYWKCsrw/3792FlZfXcOllZWQpdi99kDczb2xu///47/vnnH6Snp6Ndu3YKvb5cKsWkmC04/zADptptsMFvPIzEuo0ULRG1FEn30vBRbCQECBjr6IF3nfqpOiRqYGlpaTAwMJA9FovFDXbuZ1vSBUGoVF5VHUVb4Nm90sAMDQ3Rq1cvAIpveS8IAmb99TsO3b4MsboG1g0Zi/bsiyWiGqTlPsT4g+tRVF6KwTYOmNN3BLtjWyADAwO5o6GSDktLy0otFnfv3oWGhgZMTU2rrfNs60dNmHQ0grpueR9+8TgiLsVDBBGWDQiCa9v2jRUiEbUQOcWFCImOwP2iPDiZWGHloDHQ4NRYUoCnpyeio6Plyg4cOAB3d3doampWW8fLy0uhazHpaARdu3aVDSg9c+ZMrV6z/9YFzPnrTwDAF+4BGNaxR2OGSEQtQEl5Gd47sglXc+7CUtcAEUPGQU+z4ZrcqXnKy8tDcnIykpOTATyeEpucnIzU1FQAj2eehISEyOpPnDgRt27dQmhoKC5duoS1a9ciPDwcn376qazO1KlTceDAASxYsACXL1/GggULcPDgQUybNk2h2Jh0NIKKAaXA40VaapJy/zY+PLoVAgS85dAX73fv39ghElEzJwgCpsfvwPHMf9BGQwvrh4yDVRtDVYdFTUBiYiJcXFzg4uICAAgNDYWLiwtmznw8kD0zM1OWgACAnZ0d9uzZg5iYGDg7O+Obb77BsmXLZNNlgcc7qm/duhXr1q1Dz549ERERgcjISPTt21eh2DiQtJF4eXnJBpRmZGTA2tq6ynq38x5h3MEIFJaVYlC7FzDX4//YF0tENVp+9ggir56GmkiElYPGwMm06nsMtT6DBg2SDQStSkRERKWygQMH1tgyP2rUKIwaNapesbGlo5EYGRmhZ8+eAJ6/QqmkpAhjoyNwrzAPXY0tsYp9sURUCzuvJ2PhmQMAgLkeI+Fr66jiiIhqh0lHI6puQGmptBzvH9mEK9l3YKFrgPVDxkFfq35zuYmo5fvrzk2Exm0DALzn1A8hjh4qjoio9ph0NKJu3bpVOaBUEARMP7EDcRnXoKuhhfVDxsJaz0h1gRJRs3A95z7ePrQBJdJyvNjeCV/2DlR1SEQKYdLRiNTU1ODt7Q1Avovlh3Ox2Ho18d++2DfQ3VSxBcSIqPV5VJSPkOh1yC4uQC8zGywfGAQ1EW/h1LzwX2wj8/b2hpqaGq5du4aMjAzsvp6C+af3AQDm9BmBIbZdVRwhETV1RWWlmHB4I27mPoCNnhEihoyFjkb9NpQkUgUmHY3s6QGlUQf24ONjj/ti3+nmjfHdFFtUhYhaH6kgxSfHf8Nfd27CQEsbG/zGo62OvqrDIqoTJh1KUDGgNOWvU9DLe4Sh7bvhq97DVBwVETUHi5MOIubsaWgKIqzxeQsvGCm27DRRU8J1OhpRXl4xUpIycPrUQ6iJ9KEtzsZPiVtglhaD++l/QberD3S7DoK6nqmqQyWiJuhW7gNcv58F52v5MChTw+ncP5Hn4ABHR0e0b98eamr83UjNC5OOBlZaUo4LF+4gKfE2rly+B6n08QItutoDkGx9E49K/oBR5mXkZF5GzuFVgEgEsW0v6HQdBN2uPtBxGAB1HYMarkJErUF06iX8nn4RFp314X4hBxcvXsTFixcBADo6OrC3t4fDv0mItbU1kxBq8ph0NACpVMD1fx7gTGI6zqVkori4TPacja0hTF7QweyMXWijrwXfDy6i6MpRFFw6goJLR1CSfgHFqckoTk1G9v4wQE0d2h3dYBa0ELoOXA6dnpg3bx5mzJiBqVOnIiwsTNXhkBKcyPwHADBhUCBGvmqPK1eu4PLly/j7779RWFiIs2fP4uzZswAAPT09dO/eHePGjeOqxtRkMemoh8wMCZJOpyPpdDpycopk5cbGOnBxbwcXt3awsNDH90kHUXSvFP5WXaGhZwI9t5eg5/YSAKAs5w4KLh1B4eUYFFw6gtI711B0/S+oaeup6F1RU3Tq1CmsWbNGNiiZWr4yaTnis64DALytu6CdWTu0a9cOgwcPhlQqRWpqKq5cuYIrV67g6tWryMvLQ3Z2NhMOatKYdCgoJ7sQyUkZOJOYjswMiaxcR0cTPZ2t4OrWDh3sTKCm9uR//BNZj3+teFl2rnQ+DUMLGHi8DgOP1wEApQ9SUXg5BmLbXo38Tqi5yMvLw5tvvomffvoJc+fOVXU4pCTnH2Qgt7QYBlra6G4iv6+KmpoaOnbsiI4dO2Lo0KEoKyvDzZs3VRMokQKYdNRCUVEZzp/NRNLpdFy7eh8V++ioq4vQtZsFXNzbwbGrOTQ1K++bUlhWgjN3H+/m52VVOel4lqZpe2h6h9RYj5oviUQi91gsFkMsfv525JMnT8awYcMwZMgQJh2tyIl/Wzk8LOygXsNYDQ0NDXTp0kUZYRHVC5OO5ygvl+LvK/eQdDodF85lobRUKnuuo50xXN1t0LOXFXTbVL9AT+LdWyiRlsNK1xB2BpylQoCtra3c41mzZmH27NlV1t26dSvOnDmDU6dOKSEyakqO/zueozY/VoiaCyYdTxEEAbfTcnAm8TZSkjKQl/dkkzaztm3g5m4DZ1drmJq1qfU5T2Q+/rXiZdWJfa0EAEhLS4OBwZMZSs9r5UhLS8PUqVNx4MABaGtzM8DWpKS8DKfu3ATApINaFiYdAB4+KEDS6XScOX0b9+7my8rb6GnB2cUaru42sLE1rFPSUPFrxZs3DvqXgYGBXNLxPKdPn8bdu3fh5uYmKysvL8fRo0exYsUKFBcXQ129cpceNX8p92+joKwEJuI2cDTmYmDUcrTapKOgoARnkzNxJjEdN288lJVraKrBqbslXN3b4QWHtlBXr/u897zSYqTcvw2Av1ZIcb6+vjh37pxc2fjx4+Ho6IjPPvuMCUcLVvFjxdOqEzd1oxalVSUdZWXluHTxLpIS03Hp4l2Ulz8epyESAZ27mMHVvR2697SEtrZmg1wvIesGygUpOuibwEbPuEHOSa2Hvr4+unfvLlfWpk0bmJqaViqnluUEW0iphWrxSYdUKuDWzUc4k3gbZ5MzUVhYKnvOylofLm42cHG1hqGRToNf+wQHghGRgorKSnH63uMZb0w6qKVpsUnH3Tt5OHP6NpJOp+PRw0JZuYGhGC6u7eDqbgMr68ZdbrxiyltV63MQ1UVMTIyqQ6BGdvpeKorLy2Cho49OBmaqDoeoQbWopCMvt/jfhbtu43ZajqxcS6yOnr2s4OJmg85dTOUW7mosj4oLcP5BBoDHM1eIiGrj6RZSznijlqbZJx0lJeW4cD4LZxJv4+qV+7IN1tTURHjBsS1c3dqhW3dLaGkpd9DdyazrECCgi2FbWOhyAzciqh2uz0EtWbNMOqRSAf9cvf94g7VzmSgpLpc9Z9veCK5u7dDLxRp6+s9f5bGxVazPwT5ZIqqt/NJiJN9LA8B7B7VMzSrpyEiX4Mzp20g+kw5JTrGs3MREV7bBmrl509gojYNIiUhRf925iTJBCls9Y7TXN1F1OEQNrsknHdnZhUg+nY4zp9ORlZkrK9fR1UQvZ+t/N1gzblJ9n/cKc3El+w4AwNOS4zmIqHaedK3wvkEtU5NMOoqKSnEu5fE4jev/PHhqgzU1dHMyh4u7DRy7toWGRtNcHCn+366VbiZWMNGu/ZLpRNS6VWxl72XFzduoZWoySUd5uRRXLv+7wdr5LJQ9tcGaXWcTuLq1Q49eVtDVrX6DtaaAS58TkaJyigtx7kE6AMCLLaTUQqk06RAEAWmp2TiTmI6UpAzk5z/ZYM3cXA+u7u3g7NYOJia6KoxScU/W5+CNg4hqJ+HODUgFAZ0MzGDVxlDV4RA1CpUkHQ/u5+PM6XQknU7H/XtPNljT09OCs2s7uLq3Qzubum2wpmoZ+Tm4IbkPNZEIfZl0EFEtsYWUWgOlJR35+SU4m5yBM4npuHXzkaxcU0sd3XtYwtWtHbq8YFavDdaagopZKz1M28FAi9uRE1HtcH0Oag0aNekoLS3HpQt3kHQ6HZcv3UV5+eMRoSIR0MXeDK7uNnDqYQlt7SYztKTeuFETESnqQVEeLj/KAsAZb9SyNfi3vVQq4Mb1h0g6/XiDtaKiMtlz1u0M4Opug14u1jA0bHmtAIIgsImUiBRWMePN0dgSZjpNY60hosbQYEnHnaxc2TiN7EdPNlgzMtKGi9vjhbssrVr2cuCpeQ+Rnp8NTTV19DbvqOpwiKiZ4OBzai0aJOkoKSnHsiXHUFryeDlybW0N9OhlBVf3drDrpJwN1pqCilYOl7a20NVs+lN7iahpYAsptRYNknRoaT3exbWgoBRu7u3QtZsFNJW8wVpTULHfCvtkiai2sgok+CfnHkQQoa+lnarDIWpUDTZVZPQbvTD+nd7o6WzdKhMOQRA4iJSIFPZkxps1jMTNa00iarpWrlwJOzs7aGtrw83NDXFxcc+tO27cOIhEokqHk5OTrE5ERESVdYqKihSKq8GSjua4pkZDupZzD3cLcyFW14Br2/aqDoeImglOlaWGFhkZiWnTpuGLL75AUlIS+vfvj4CAAKSmplZZf+nSpcjMzJQdaWlpMDExwWuvvSZXz8DAQK5eZmYmtLUVmxTSvBfFaEIqfq24m3eAtoamiqMhouaCO1JTQ/v+++8xYcIEvPPOO+jatSvCwsJga2uLVatWVVnf0NAQlpaWsiMxMRGPHj3C+PHj5eqJRCK5epaWlgrHxqSjgXAgGBEpKjX3IdLyHkFDpIY+Fh1VHQ41cRKJRO4oLi6uVKekpASnT5+Gv7+/XLm/vz9OnDhRq+uEh4djyJAh6NChg1x5Xl4eOnToABsbGwwfPhxJSUkKv4eWsyqXCkkF6ZPdIS2ZdLRUK3wdIK5Hn3txcQHwdwMGRM1eRStHLzMb6GmKVRwNNYb63jeAJ/cOW1tbufJZs2Zh9uzZcmX3799HeXk5LCws5MotLCyQlZVV47UyMzOxd+9ebN68Wa7c0dERERER6NGjByQSCZYuXQpvb2+kpKTA3t6+1u+FSUcDuPwoC4+KC6CroYVebW1UHQ4RNRMV63OwhZRqIy0tDQYGT9a7Eoufn6g+O85SEIRajb2MiIiAkZERXnrpJblyDw8PeHh4yB57e3vD1dUVy5cvx7Jly2r5Dph0NIiKrpW+FnbQVGt9M3eISHFcwZgUZWBgIJd0VMXMzAzq6uqVWjXu3r1bqfXjWYIgYO3atQgODoaWVvVrTampqaF37964evVq7YKveJ1CtalKFetzeFlxfQ4iqp3rkvu4UyCBlpo6XM071PwColrQ0tKCm5sboqOj5cqjo6Ph5eVV7WtjY2Nx7do1TJgwocbrCIKA5ORkWFlZKRQfWzrqqUxajpNsIiUiBVWM53Az7wAdznijBhQaGorg4GC4u7vD09MTa9asQWpqKiZOnAgAmD59OtLT07Fhwwa514WHh6Nv377o3r17pXPOmTMHHh4esLe3h0QiwbJly5CcnIwffvhBodiYdNTT+QcZyC0thqGWNpxMrFUdDhE1E+xaocYSFBSEBw8e4Ouvv0ZmZia6d++OPXv2yGajZGZmVlqzIycnB1FRUVi6dGmV58zOzsZ7772HrKwsGBoawsXFBUePHkWfPn0Uio1JRz1V3Dg8LDtBXY29VURUM6kgfapblkkHNbxJkyZh0qRJVT4XERFRqczQ0BAFBQXPPd+SJUuwZMmSesfFb8l64sI+RKSoK4/u4mFxPnQ0NOFsxhlv1How6aiHkvIy/HX3JgCuz0FEtXc88xoAoI95R2ips8GZWg8mHfWQfP82CstKYardBg7G5qoOh4iaCdligmwhpVaGSUc9yLpWLDtDTcSPkohqVi59soIxB5FSa8Nvynp4sjsk1+eghrdq1Sr07NlTtiCQp6cn9u7dq+qwqJ7OP8yApKQI+ppidDfljDdqXZh01FFhWSlO370FgL9WqHHY2Nhg/vz5SExMRGJiIgYPHoyRI0fiwoULqg6N6uHEUzPeNLiCMbUyHMFUR2fu3kKJtBwWugawMzBTdTjUAo0YMULu8bfffotVq1bh5MmTcHJyUlFUVF9sIaXWjElHHT29sE9tNtEhqiCRSOQei8XiajduAoDy8nJs27YN+fn58PT0bMzwqBGVSsvx152bANhCSq0Tu1fqiLtDUl3Z2trC0NBQdsybN++5dc+dOwc9PT2IxWJMnDgRO3bsQLdu3ZQYLTWklHu3UVBWAmOxLhyNLVUdDpHSsaWjDvJKi5F8Lw0A4GXJJlJSjCLbUzs4OCA5ORnZ2dmIiorC2LFjERsby8SjmapYn8PTshNnvFGrxKSjDv66cxNlghTt9Uxgq2+i6nComanN9tQVtLS00KVLFwCAu7s7Tp06haVLl+LHH39szBCpkbCFlFo7ptp1cIIDwUhFBEFAcXGxqsOgOigqK0UiZ7xRK8eWjjrgfiukDDNmzEBAQABsbW2Rm5uLrVu3IiYmBvv27VN1aFQHp++lori8DOY6+uhs2FbV4RCpBJMOBWUXF+D8wwwATDqocd25cwfBwcHIzMyEoaEhevbsiX379sHPz0/VoVEdPP1jhTPeqLVi0qGghKwbkAoCOhu2haVu7frlieoiPDxc1SFQA2K3LBHHdCjs6fU5iIhqo6C0BEn/znjjvYNaMyYdCjrB3SGJSEF/3X08481Gzwjt9TjjjVovJh0KeFCUh8uPsgBwfQ4iqr3jGU92pOZ4DmrNmHQoID7zcStHV2NLmGi3UXE0RNRcnMjijDcigEmHQo5zqiwRKUhSUoRzD9IB8N5BxKRDARxESkSKSsi6DqkgwM7ADNZtDFUdDpFKMemopcz8HFyX3IeaSIS+FnaqDoeImgn+WCF6gklHLVXMWulh2g6GYh0VR0NEzYWsW5aDz4mYdNTWiX93h/Sy5K8VIqqdh0X5uPTvjDdPLgpGxKSjtk78O3PF25pJBxHVTkULqYORBdrq6Ks4GiLVY9JRC6m5D5GW9wgaIjX0Nu+g6nCIqJng5pBE8ph01ELFjcOlrS3aaIpVHA0RNRcnOIiUSA6Tjlrg+hxEpKisAgmu5dyDCCJ4WHLGGxHApKNGgiCwiZSIFFaxgnF3U2sYiXVVHA1R08CkowbXJfdxpzAXYnUNuLVtr+pwiKiZOF4x440/VohkmHTUoKJrxa1te2hraKo4GiJqLipmvHF9DqInmHTUgAPBiEhRabkPkZr3EOoiNfTleA4iGSYd1ZAK0ie/Vph0EFEtVazP0cvMBnqc8UYkw6SjGpcf3cHD4nzoamihl5mNqsMhomaCLaREVWPSUY2KG0cfi47QUtdQcTRE1BwIgsBN3oieg0lHNThVlogUdUNyH1kFEmipqcONKxiTiqxcuRJ2dnbQ1taGm5sb4uLinls3JiYGIpGo0nH58mW5elFRUejWrRvEYjG6deuGHTt2KBwXk47nEAQBZ+6lAeCvFSKqvTP3UgEArubtocMZb6QCkZGRmDZtGr744gskJSWhf//+CAgIQGpqarWvu3LlCjIzM2WHvb297Ln4+HgEBQUhODgYKSkpCA4OxujRo5GQkKBQbCJBEIQ6vatWoLCsBIl3b8HLsjPU1ZiftVYSiQSGhoaY8kEkxPVY5Km4uADLVgUhJycHBgYGDRghNTWpuQ8hKSlEd9N2qg6FVKSh7huA4veOvn37wtXVFatWrZKVde3aFS+99BLmzZtXqX5MTAx8fHzw6NEjGBkZVXnOoKAgSCQS7N27V1b24osvwtjYGFu2bKn1e+E3aTV0NLTQ39qeCQcRKaS9vgkTDmpwEolE7iguLq5Up6SkBKdPn4a/v79cub+/P06cOFHt+V1cXGBlZQVfX18cOXJE7rn4+PhK5xw6dGiN53wWR0cS1dLY7NehpyWq8+vzSgQsa8B4iKjpq+99A3hy77C1tZUrnzVrFmbPni1Xdv/+fZSXl8PCwkKu3MLCAllZWVWe38rKCmvWrIGbmxuKi4uxceNG+Pr6IiYmBgMGDAAAZGVlKXTO52HSQURE1AykpaXJda+Ixc9fA0Ykkk90BEGoVFbBwcEBDg4Osseenp5IS0vDokWLZEmHoud8HvYbEBERNQMGBgZyR1VJh5mZGdTV1Su1QNy9e7dSS0V1PDw8cPXqVdljS0vLep8TYNJBRETUYmhpacHNzQ3R0dFy5dHR0fDy8qr1eZKSkmBlZSV77OnpWemcBw4cUOicALtXiIiIWpTQ0FAEBwfD3d0dnp6eWLNmDVJTUzFx4kQAwPTp05Geno4NGzYAAMLCwtCxY0c4OTmhpKQEmzZtQlRUFKKiomTnnDp1KgYMGIAFCxZg5MiR2LVrFw4ePIhjx44pFBuTDiIiohYkKCgIDx48wNdff43MzEx0794de/bsQYcOjxery8zMlFuzo6SkBJ9++inS09Oho6MDJycn/PnnnwgMDJTV8fLywtatW/Hll1/iq6++QufOnREZGYm+ffsqFBvX6SCqQcV8+9NviOo9e8Vti1Drufbz5s3D9u3bcfnyZejo6MDLywsLFiyQG/BFRE1TQ903AMXvHU0Zx3QQNVGxsbGYPHkyTp48iejoaJSVlcHf3x/5+fmqDo2IqE7YvULURO3bt0/u8bp162Bubo7Tp0/LTWMjImoumHQQKZlEIpF7LBaLq51vXyEnJwcAYGJi0ihxERE1NnavECmZra0tDA0NZUdVeyE8SxAEhIaGol+/fujevbsSoiQianhs6SBSMkVWFazw4Ycf4uzZswpPTyMiakqYdBApWcVqgrX10UcfYffu3Th69ChsbGwaMTIiosbFpIOoiRIEAR999BF27NiBmJgY2NnZqTokIqJ6YdJB1ERNnjwZmzdvxq5du6Cvry/b98DQ0BA6Ojoqjo6ISHEcSErURK1atQo5OTkYNGgQrKysZEdkZKSqQyMiqhO2dBA1UVwsmIhaGrZ0EBERkVIw6SAiIiKlYNJBRERESsGkg4iIiJSCSQcREREpBZMOIiIiUgomHURERKQUTDqIiIhIKZh0EBERkVIw6SAiIiKlYNJBRERESsGkg4iIiJSCSQcREREpBZMOIiIiUgomHURERKQUTDqIiIhIKZh0EBERkVIw6SAiIiKlYNJBRERESsGkg4iIiJSCSQcREREpBZMOIiIiUgomHURERKQUTDqIiIhIKZh0EBERkVIw6SAiImphVq5cCTs7O2hra8PNzQ1xcXHPrbt9+3b4+fmhbdu2MDAwgKenJ/bv3y9XJyIiAiKRqNJRVFSkUFxMOoiIiFqQyMhITJs2DV988QWSkpLQv39/BAQEIDU1tcr6R48ehZ+fH/bs2YPTp0/Dx8cHI0aMQFJSklw9AwMDZGZmyh3a2toKxaZR53dFRERETc7333+PCRMm4J133gEAhIWFYf/+/Vi1ahXmzZtXqX5YWJjc4++++w67du3C77//DhcXF1m5SCSCpaVlvWJjSwcREVEzIJFI5I7i4uJKdUpKSnD69Gn4+/vLlfv7++PEiRO1uo5UKkVubi5MTEzkyvPy8tChQwfY2Nhg+PDhlVpCaoMtHUS1NLzfVKjpiOv8emlhMbAlrOECIqImr773DeDJvcPW1laufNasWZg9e7Zc2f3791FeXg4LCwu5cgsLC2RlZdXqeosXL0Z+fj5Gjx4tK3N0dERERAR69OgBiUSCpUuXwtvbGykpKbC3t6/1e2HSQURE1AykpaXBwMBA9lgsfn4yIxKJ5B4LglCprCpbtmzB7NmzsWvXLpibm8vKPTw84OHhIXvs7e0NV1dXLF++HMuWLav1e2D3ClETdfToUYwYMQLW1tYQiUTYuXOnqkMiIhUyMDCQO6pKOszMzKCurl6pVePu3buVWj+eFRkZiQkTJuDXX3/FkCFDqq2rpqaG3r174+rVqwq9ByYdRE1Ufn4+evXqhRUrVqg6FCJqJrS0tODm5obo6Gi58ujoaHh5eT33dVu2bMG4ceOwefNmDBs2rMbrCIKA5ORkWFlZKRQfu1eIlEwikcg9FovFVf5iCQgIQEBAgLLCIqIWIjQ0FMHBwXB3d4enpyfWrFmD1NRUTJw4EQAwffp0pKenY8OGDQAeJxwhISFYunQpPDw8ZK0kOjo6MDQ0BADMmTMHHh4esLe3h0QiwbJly5CcnIwffvhBodjY0kGkZLa2tjA0NJQdVU1hIyKqq6CgIISFheHrr7+Gs7Mzjh49ij179qBDhw4AgMzMTLk1O3788UeUlZVh8uTJsLKykh1Tp06V1cnOzsZ7772Hrl27wt/fH+np6Th69Cj69OmjUGxs6SBSMkUGgxER1cWkSZMwadKkKp+LiIiQexwTE1Pj+ZYsWYIlS5bUOy4mHURKVjEIjIiotWH3ChERESkFkw4iIiJSCnavEDVReXl5uHbtmuzxjRs3kJycDBMTE7Rv316FkRER1Q2TDqImKjExET4+PrLHoaGhAICxY8dWGghGRNQcMOkgaqIGDRoEQRBUHQYRUYPhmA4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kFERERKwaSDiIiIlIJJBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kFERERKwaSDiIiIlIJJBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kFERERKwaSDiIiIlIJJBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kFERERKwaSDqIlbuXIl7OzsoK2tDTc3N8TFxak6JCJq4hS9b8TGxsLNzQ3a2tro1KkTVq9eXalOVFQUunXrBrFYjG7dumHHjh0Kx8Wkg6gJi4yMxLRp0/DFF18gKSkJ/fv3R0BAAFJTU1UdGhE1UYreN27cuIHAwED0798fSUlJmDFjBqZMmYKoqChZnfj4eAQFBSE4OBgpKSkIDg7G6NGjkZCQoFBsIkEQhHq9O6IWTiKRwNDQEFY/TIOajrjO55EWFiNzchhycnJgYGBQq9f07dsXrq6uWLVqlaysa9eueOmllzBv3rw6x0JEjauh7huA4vcORe8bn332GXbv3o1Lly7JyiZOnIiUlBTEx8cDAIKCgiCRSLB3715ZnRdffBHGxsbYsmVLrd+LRq1rErVyQmExpPV8PfD4ZvQ0sVgMsbjyTamkpASnT5/G559/Llfu7++PEydO1CMSIlKW+t43Ks4B1O7eUZf7Rnx8PPz9/eXKhg4divDwcJSWlkJTUxPx8fH4+OOPK9UJCwtT6L0w6SCqgZaWFiwtLZH16aqaK9dAT08Ptra2cmWzZs3C7NmzK9W9f/8+ysvLYWFhIVduYWGBrKysesdCRI2nIe8bQO3vHXW5b2RlZVVZv6ysDPfv34eVldVz6yh6L2LSQVQDbW1t3LhxAyUlJfU+lyAIEIlEcmVVtXI87dn6VZ2DiJqWhrxvAIrfOxS9b1RV/9nyhrgXMekgqgVtbW1oa2sr9ZpmZmZQV1ev9Evi7t27lX5xEFHT01zuG5aWllXW19DQgKmpabV1FL0XcfYKUROlpaUFNzc3REdHy5VHR0fDy8tLRVERUVNWl/uGp6dnpfoHDhyAu7s7NDU1q62j8L1IIKIma+vWrYKmpqYQHh4uXLx4UZg2bZrQpk0b4ebNm6oOjYiaqJruG59//rkQHBwsq3/9+nVBV1dX+Pjjj4WLFy8K4eHhgqampvDbb7/J6hw/flxQV1cX5s+fL1y6dEmYP3++oKGhIZw8eVKh2Jh0EDVxP/zwg9ChQwdBS0tLcHV1FWJjY1UdEhE1cdXdN8aOHSsMHDhQrn5MTIzg4uIiaGlpCR07dhRWrVpV6Zzbtm0THBwcBE1NTcHR0VGIiopSOC6u00FERERKwTEdREREpBRMOoiIiEgpmHQQERGRUjDpICIiIqVg0kFERERKwaSDiIiIlIJJBxERESkFkw4iIiJSCiYdREREpBRMOoiIiEgpmHQQERGRUvw/TpR9WXW2T0UAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [63.647466378271766]\n", - "(0, 2) already in graph, angles = [88.68317271320804]\n", - "(0, 2) already in graph, angles updated = [88.68317271320804, 63.647466378271766]\n", - "Checking edge: (0, 3)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [55.78135886136459]\n", - "(0, 3) added\n", - "Checking edge: (9, 2)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 2\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 1])\n", - "angles: [126.1677775949272]\n", - "(9, 2) added\n", - "Checking edge: (9, 3)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 2\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 1])\n", - "angles: [88.08366041995446]\n", - "(9, 3) added\n", - "Checking edge: (2, 3)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 2\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 1])\n", - "angles: [145.74856198511836]\n", - "(2, 3) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 2\n", - "Adjacent strokes (list): [1, 1, 8]\n", - "Adjacent strokes (uniques): {8, 1}\n", - "Checking edge: (8, 1)\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgcAAAGTCAYAAAC8vrHzAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABTGklEQVR4nO3dd3QUddvG8e+mbXpIAiH03hN6kRZAensQBEEsoCKgKCCgqI8KPhaahSJdRJQi0lWkCNKbdAhI71VaEkiDJPP+geR1pQWyZHaT63POnmMmszN3FufOld+Un8UwDAMRERGRv7mYXYCIiIg4FoUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAg4qCSkpJ47733KFSoEF5eXhQuXJj//e9/pKSkmF2aiDgoe/UNt0dUn4ik05AhQxg3bhxTpkyhTJkybNmyhRdeeIGAgAB69epldnki4oDs1TcUDkQc1IYNG2jVqhXNmzcHoGDBgsyYMYMtW7aYXJmIOCp79Q2FA5E0SEhI4Pr16+nejmEYWCwWm2VWqxWr1XrburVq1WLcuHEcOHCA4sWLs3PnTtauXcvw4cPTXYeIPHr26huQ9t5hr76hcCByHwkJCQQFBREfH5/ubfn6+nLt2jWbZQMGDGDgwIG3rdu/f3+io6MpWbIkrq6uJCcn88knn/D000+nuw4RebTs2Tcg7b3DXn1D4UDkPq5fv058fDwdO3bEw8MjXduZPn06J0+exN/fP3X5nUYNAGbOnMnUqVOZPn06ZcqUYceOHfTu3ZvcuXPTqVOnh65DRB49e/WNW9tKa++wV99QOBBJIw8Pj3Qf5AD+/v42B/jdvPnmm7z99tt06NABgPDwcI4fP86gQYMUDkSchL36BqStd9irb+hWRhEHFRcXh4uL7SHq6uqqWxlF5K7s1Tc0ciDioFq2bMknn3xC/vz5KVOmDNu3b+eLL77gxRdfNLs0EXFQ9uobCgciDmrUqFG8//77vPrqq/z111/kzp2bbt268cEHH5hdmog4KHv1DYUDEQfl5+fH8OHDdeuiiKSZvfqGrjkQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhpvZBYg4i1oBv+Ftffg8HZeYwrf2K0dEnEB6+waY0zs0ciAiIiI2FA5ERETEhsKBiIMqWLAgFovltlePHj3MLk1EHJg9eoeuORBxUJs3byY5OTn168jISBo2bEi7du1MrEpEHJ09eofCgYiDypEjh83XgwcPpkiRItSpU8ekikTEGdijdygciGSwmJgYm6+tVitWq/We77l+/TpTp06lT58+WCyWR1meiDiojOwduuZAJIPly5ePgICA1NegQYPu+5758+cTFRVF586dH32BIuKQMrJ3aORAJIOdPHkSf3//1K/vl/wBJk2aRNOmTcmdO/ejLE1EHFhG9g6FA5EM5u/vb3OA38/x48dZtmwZc+fOfYRViYijy8jeodMKIg5u8uTJhISE0Lx5c7NLEREnkp7eoXAg4sBSUlKYPHkynTp1ws1NA30ikjbp7R0KByIObNmyZZw4cYIXX3zR7FJExImkt3foTxERB9aoUSMMwzC7DBFxMuntHRo5EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERG3YNByNHjsRisRAWFnbXdSwWCwMHDkz9euXKlVgsFlauXJnu/f/6668227anb7/9FovFwpYtWx7J9u1t+vTpDB8+3OwybmPPf2+AAwcO0K9fPypVqkS2bNkICgqiZs2azJ492y7bFxHJiuwaDr755hsA9uzZw6ZNm+y56TT59ddf+fDDDzN8v47IUcOBvS1dupSFCxfy5JNPMmvWLKZNm0axYsVo164d//vf/8wuT0TEKdltboUtW7awc+dOmjdvzsKFC5k0aRLVqlWz1+btzjAMEhIS8PLyMrsUSYcOHTrQo0cPLBZL6rKmTZty8eJFhgwZQv/+/bFarSZWKCLifOw2cjBp0iQABg8eTI0aNfjhhx+Ii4uz1+aJi4ujX79+FCpUCE9PT4KCgqhcuTIzZswAoHPnzowePRq4eeri1uvYsWOpy1577TXGjRtHqVKlsFqtTJkyBYC1a9dSv359/Pz88Pb2pkaNGixcuPC+NZ09e5ZKlSpRrFgxDh48CEBMTExqnR4eHuTJk4fevXsTGxtr895Zs2ZRrVo1AgIC8Pb2pnDhwmmaPWv06NFEREQQEhKCj48P4eHhDB06lBs3bqSuU7duXRYuXMjx48dtPot7KViwIC1atGDx4sVUrFgRLy8vSpYsmToa9E+RkZG0atWKwMBAPD09KV++fOpn+U/79u2jSZMmeHt7kz17drp3787Vq1fvuP9ly5ZRv359/P398fb2pmbNmixfvvy+n0f27Nnv+LNVrVqVuLg4Ll++fN9tiIiILbuMHMTHxzNjxgyqVKlCWFgYL774Il26dGHWrFl06tTJHrugT58+fP/993z88cdUqFCB2NhYIiMjuXTpEgDvv/8+sbGxzJ49mw0bNqS+L1euXKn/PX/+fNasWcMHH3xAaGgoISEhrFq1ioYNG1K2bFkmTZqE1WplzJgxtGzZkhkzZtC+ffs71hMZGUmzZs3ImzcvGzZsIHv27MTFxVGnTh1OnTrFu+++S9myZdmzZw8ffPABu3fvZtmyZVgsFjZs2ED79u1p3749AwcOxNPTk+PHj/P777/f93M4fPgwHTt2TA0fO3fu5JNPPmHfvn2pv8jHjBlD165dOXz4MPPmzUvzZ7xz50769u3L22+/Tc6cOfn666956aWXKFq0KBEREQDs37+fGjVqEBISwsiRIwkODmbq1Kl07tyZ8+fP89ZbbwFw/vx56tSpg7u7O2PGjCFnzpxMmzaN11577bb9Tp06leeff55WrVoxZcoU3N3dGT9+PI0bN2bJkiXUr18/zT/DLStWrCBHjhyEhIQ88HtFRLI6u4SD2bNnEx0dzUsvvQRA+/bt6d27N5MmTbJbOFi3bh2NGjXijTfeSF3WvHnz1P8uUqQIOXPmBOCxxx674zauXbvG7t27CQwMTF1WvXp1AgMDWblyJb6+vgC0aNGC8uXL069fP5566qnb/jJdtmwZTz75JI0aNeL777/H09MTuHlB5q5du9i0aROVK1cGoH79+uTJk4e2bduyePFimjZtyvr16zEMg3HjxhEQEJC63c6dO9/3c/jiiy9S/zslJYXatWsTHBzMCy+8wOeff05gYCClS5cmW7ZsWK3Wu34Wd3Lx4kXWrVtH/vz5AYiIiGD58uVMnz49NRwMHDiQ69evs2LFCvLlywdAs2bNiIqK4sMPP6Rbt24EBATw5ZdfcuHCBbZv3065cuWAm8P9jRo14sSJE6n7jIuLo1evXrRo0cImyDRr1oyKFSvy7rvvPvD1K19//TUrV65kxIgRuLq6PtB7RUTETqcVJk2ahJeXFx06dADA19eXdu3asWbNmtTh9vSqWrUqixYt4u2332blypXEx8c/8DYef/xxm2AQGxvLpk2baNu2bWowAHB1deW5557j1KlT7N+/32YbU6ZMoVmzZnTp0oUff/wxNRgA/PLLL4SFhVG+fHmSkpJSX40bN7a5Qr9KlSoAPPXUU/z444+cPn06zT/D9u3b+c9//kNwcDCurq64u7vz/PPPk5yczIEDBx74M/mn8uXLpwYDAE9PT4oXL87x48dTl/3+++/Ur18/NRjc0rlzZ+Li4lJHbVasWEGZMmVSg8EtHTt2tPl6/fr1XL58mU6dOtl8ZikpKTRp0oTNmzffdkrmXhYtWkSPHj1o27Ytr7/+eprfJyIi/y/d4eDQoUOsXr2a5s2bYxgGUVFRREVF0bZtW4A7nrN+GCNHjqR///7Mnz+fevXqERQUxBNPPPFA4eOfpxgArly5gmEYty0HyJ07N0DqaYtbfvjhB7y8vOjSpcttIwrnz59n165duLu727z8/PwwDIOLFy8CN/8inz9/PklJSTz//PPkzZuXsLCw1Osn7ubEiRPUrl2b06dPM2LECNasWcPmzZtTr7V4mMD0T8HBwbcts1qtNtu9dOlSmj6vS5cuERoaett6/152/vx5ANq2bXvb5zZkyBAMw0jzdQNLliyhTZs2NGzYkGnTpt33OgsREbmzdJ9W+OabbzAMg9mzZ9/x3vIpU6bw8ccfp3t418fHhw8//JAPP/yQ8+fPp44itGzZkn379qVpG//+ZREYGIiLiwtnz569bd0zZ84ANy94+6dp06bx/vvvU6dOHZYuXUr58uVTv5c9e3a8vLzuGoj+ua1WrVrRqlUrEhMT2bhxI4MGDaJjx44ULFiQ6tWr3/H98+fPJzY2lrlz51KgQIHU5Tt27Ljnz21PwcHBafq8goODOXfu3G3r/XvZrfVHjRp111Mgt04X3cuSJUt44oknqFOnDnPmzMHDw+O+7xERkTtLVzhITk5mypQpFClShK+//vq27//yyy98/vnnLFq0iBYtWqRnVzZy5sxJ586d2blzJ8OHDycuLg5vb+/UW9bi4+PTdIuij48P1apVY+7cuXz22Wep70lJSWHq1KnkzZuX4sWL27wnKCiIZcuW0aJFC+rVq8eiRYtSf6m1aNGCTz/9lODgYAoVKpSmn8VqtVKnTh2yZcvGkiVL2L59+13Dwa1w889b8wzDYOLEiXfcbnpHEu6kfv36zJs3jzNnzqSOFgB89913eHt7p34W9erVY+jQoezcudPm1ML06dNttlezZk2yZcvG3r1773ixYlosXbqUJ554glq1ajF//nzduigikk7pCgeLFi3izJkzDBkyhLp16972/bCwML766ismTZqU7nBQrVo1WrRoQdmyZQkMDOTPP//k+++/p3r16nh7ewMQHh4OwJAhQ2jatCmurq6ULVv2nn9FDho0iIYNG1KvXj369euHh4cHY8aMITIykhkzZtxxaNrPz4/FixenDmH/9NNP1KtXj969ezNnzhwiIiJ44403KFu2LCkpKZw4cYKlS5fSt29fqlWrxgcffMCpU6eoX78+efPmJSoqihEjRuDu7k6dOnXuWmvDhg3x8PDg6aef5q233iIhIYGxY8dy5cqV29YNDw9n7ty5jB07lkqVKuHi4pJ6kWR6DBgwgF9++YV69erxwQcfEBQUxLRp01i4cCFDhw5NvcCyd+/efPPNNzRv3pyPP/449W6Ff4/y+Pr6MmrUKDp16sTly5dp27YtISEhXLhwgZ07d3LhwgXGjh1713rWrl3LE088QWhoKO++++5toyilS5fG398/3T+3iEhWkq5wMGnSJDw8PHjhhRfu+P3s2bPTunVrZs+ezfnz59M0PHw3jz/+OD/99BNffvklcXFx5MmTh+eff57//ve/qet07NiRdevWMWbMGP73v/9hGAZHjx6lYMGCd91unTp1+P333xkwYACdO3cmJSWFcuXK8dNPP90z0Hh5ebFgwQI6duxIs2bNmDNnDs2aNWPNmjUMHjyYCRMmcPToUby8vMifPz8NGjRIraNatWps2bKF/v37c+HCBbJly0blypX5/fffKVOmzF33WbJkSebMmcN7771HmzZtCA4OpmPHjvTp04emTZvarNurVy/27NnDu+++S3R0NIZhYBhG2j7seyhRogTr16/n3XffpUePHsTHx1OqVCkmT55sc7dFaGgoq1atolevXrzyyit4e3vTunVrvvrqK1q1amWzzWeffZb8+fMzdOhQunXrxtWrVwkJCaF8+fL3vYNj2bJlxMfHc+zYMR5//PHbvr9ixYo7BlcREbk7i2GP3xgimVhMTAwBAQF83SsP3taHv4Y3LjGFLiNOEx0drdEMkUzOXn0DzOkdmpVRREREbCgciIiIiA2FAxEREbGhcCAi6bZp0yZat25N/vz5sVqt5MyZk+rVq9O3b1+b9caMGcO33377SGro3LmzzZNOzbRmzRqsVqvN00Vv3XZcqVIl/P39CQ4Opk6dOmma5O1uTp06Re/evVNvh7ZYLHf8fG/cuEGRIkUeyTTun376KfPnz7f7dtNr4MCBdn0Q2u+//86LL75IyZIl8fHxIU+ePLRq1YqtW7fabR+OROFARNJl4cKF1KhRg5iYGIYOHcrSpUsZMWIENWvWZObMmTbrPspw4CgMw6B37968/PLLNg8rGzBgAF27dqVq1arMmTOHb7/9FqvVSosWLZg7d+5D7evQoUNMmzYNDw8PmjVrdtf13N3d+eCDD/jf//5321Nf08tRw4G9jR07lmPHjtGrVy9+/fVXRowYwV9//cVjjz2WpknznI1dJl4Skaxr6NChFCpUiCVLluDm9v8tpUOHDgwdOvSht3vjxg0sFovNNp3B4sWL2bZt220P/Prmm2+oVauWzXM7GjZsSGhoKFOmTKFNmzYPvK+IiAguXLgAwJYtW+75CPann36aPn36MH78eN59990H3ldWN3r06NtmeW3SpAlFixbl008/veOt1M5MIwciki6XLl0ie/bsd/wl7uLy/y2mYMGC7Nmzh1WrVmGxWLBYLKnP/li5ciUWi4Xvv/+evn37kidPHqxWK4cOHQJu/mItV64cnp6eBAUF0bp1a/7888/71rZu3TqyZ89OixYtUifwOnjwIB07diQkJASr1UqpUqVS5ye5JSUlhY8//pgSJUrg5eVFtmzZKFu2LCNGjLjvPseOHUuVKlUoUaKEzXJ3d3ebWVjh5uRmt14P45+f7/14eHjQvn17JkyYcN9nniQkJNC3b1/Kly9PQEAAQUFBVK9enQULFtisZ7FYiI2NZcqUKan/pvd6rsixY8ewWCx89tlnfPHFFxQqVAhfX1+qV6/Oxo0bb1v/p59+Sn3QnZ+fHw0bNkyd3O2fFi5cSPny5bFarRQqVIjPPvvsjvs3DIMxY8ZQvnx5vLy8CAwMpG3bthw5cuSenwdwx+nffX19KV26NCdPnrzv+52NwoGIpEv16tXZtGkTPXv2ZNOmTdy4ceOO682bN4/ChQtToUIFNmzYwIYNG2ym6QZ45513OHHiBOPGjePnn38mJCSEQYMG8dJLL1GmTBnmzp3LiBEj2LVrF9WrV7/nxGs//vgj9evX56mnnmLBggX4+Piwd+9eqlSpQmRkJJ9//jm//PILzZs3p2fPnnz44Yep7x06dCgDBw7k6aefZuHChcycOZOXXnqJqKioe34W169fZ9myZdSrV++27/Xq1YvFixczadIkrly5wtmzZ+nTpw/R0dH07Nnzntu1l7p163L8+HEiIyPvuV5iYiKXL1+mX79+zJ8/nxkzZlCrVi3atGnDd999l7rehg0b8PLyolmzZqn/pmPGjLlvHaNHj+a3335j+PDhTJs2jdjYWJo1a0Z0dHTqOtOnT6dVq1b4+/szY8aM1M+tbt26rF27NnW95cuX06pVK/z8/Pjhhx8YNmwYP/74I5MnT75tv926daN37940aNCA+fPnM2bMGPbs2UONGjVSJ4F7ENHR0Wzbtu2eD69zVs41XiciDmfw4MHs27ePUaNGMWrUKNzd3alSpQotW7bktddeS71IsEKFCnh5eeHv73/XSbaKFCnCrFmzUr+Oiorio48+olmzZjbD9HXr1qVYsWIMHDiQadOm3badIUOG8N///pdPP/2Ut956K3V5nz598PPzY+3atakPk2nYsCGJiYkMHjyYnj17EhgYyLp16wgPD2fgwIGp723cuPF9P4sdO3YQHx9PxYoVb/te79698fLyokePHnTp0gW4OVfLzz//TM2aNe+7bXu4Vdetn+9uAgICbH65JicnU79+fa5cucLw4cN5/vnnAXjsscdwcXEhR44cd/03vRM/Pz9++eWX1An5cufOTdWqVVm0aBEdOnQgJSWFN998k/DwcBYtWpQ6QtKsWTOKFClC//79WbduHQD//e9/yZkzJ7/99lvqCEzjxo1vezLuxo0bmThxIp9//jl9+vRJXV67dm2KFy/OF198wZAhQ9L8MwD06NGD2NhYmyf1ZhYaORCRdAkODk6dPnzw4MG0atWKAwcO8M477xAeHp46VXlaPPnkkzZfb9iwgfj4+Nseo50vXz4ef/xxli9fbrPcMAy6devGgAEDmD59uk0wSEhIYPny5bRu3Rpvb2+SkpJSX82aNSMhISF1aLtq1ars3LmTV199lSVLlhATE5Om+m/NTnqnIejJkyfTq1cvXnvtNZYtW8avv/5Ko0aNaNWqFUuWLEnT9tPrVl2nT5++77qzZs2iZs2a+Pr64ubmhru7O5MmTUrT6Zz7ad68uc1MvWXLlgVIvbtj//79nDlzhueee87m1Imvry9PPvkkGzduJC4ujtjYWDZv3kybNm1sTs34+fnRsmVLm33+8ssvWCwWnn32WZt/+9DQUMqVK8fKlSsf6Gd4//33mTZtGl9++SWVKlV60I/A4WnkQCSNalc8g5/3w98adTUucz+pvHLlyqmTe924cYP+/fvz5ZdfMnTo0DRfmJgrVy6br29dWf/v5XDzr83ffvvNZtn169eZOXMmZcqUuW2+kUuXLpGUlJQ6wnEnt4LMO++8g4+PD1OnTmXcuHG4uroSERHBkCFD7jmB2a2ZUP99DcGVK1dSRwz+eT68adOm1K1bl+7du3P06NG7btdebtV1vxlb586dy1NPPUW7du148803CQ0Nxc3NjbFjx951SvoHERwcbPP1P2fUhfv/u6ekpHDlyhUMwyAlJYXQ0NDb1vv3svPnz2MYxl3n+ClcuHCa6//www/5+OOP+eSTT+47m2x6+waY0zsUDkTE7tzd3RkwYABffvnlfc9v/9O/70u/9Uvk7Nmzt6175swZsmfPbrPMarWyYsUKGjduTIMGDVi8eDGBgYEABAYG4urqynPPPUePHj3uuP9bU627ubnRp08f+vTpQ1RUFMuWLePdd9+lcePGnDx5MnUm2H+7Vc/ly5dtlu/fv5/4+HiqVKly23sqV67MqlWruHbt2iN/TsOtuv79uf3b1KlTKVSoEDNnzrT5N0lMTHyk9d1yv393FxcXAgMDMQwDi8XCuXPnblvv38uyZ8+OxWJJfQbFv6V1qvcPP/yQgQMHMnDgwEx914dOK4hIutypgQOpw8+5c+dOXWa1Wu/7V+s/Va9eHS8vL6ZOnWqz/NSpU/z+++/Ur1//tvdUqFCBVatWcerUKerWrctff/0FgLe3N/Xq1WP79u2ULVs2daTjn69//0ULkC1bNtq2bUuPHj24fPkyx44du2u9pUqVAuDw4cM2y299Bv++It8wDDZu3EhgYCA+Pj73/0DS6dZV+aVLl77nehaLBQ8PD5tgcO7cudvuVoAH/zdNixIlSpAnTx6mT59uc2dFbGwsc+bMSb2DwcfHh6pVqzJ37lwSEhJS17t69So///yzzTZbtGiBYRicPn36jv/297oG45aPPvqIgQMH8t577zFgwAD7/cAOSCMHIpIujRs3Jm/evLRs2ZKSJUuSkpLCjh07+Pzzz/H19aVXr16p64aHh/PDDz8wc+ZMChcujKen5z2bcrZs2Xj//fd59913ef7553n66ae5dOkSH374IZ6enndt0KVKlWLNmjU0aNCAiIgIli1bRt68eRkxYgS1atWidu3avPLKKxQsWJCrV69y6NAhfv7559SH2bRs2ZKwsDAqV65Mjhw5OH78OMOHD6dAgQIUK1bsrvXmzZuXwoULs3HjRps7EPLnz0+bNm2YMGECVquVZs2akZiYyJQpU1i3bh0fffSRzS/iunXrsmrVqjRNsz579mzg/3/xb9myJXUEom3btjbrbty4MfUUyb3cejDTq6++Stu2bTl58iQfffQRuXLluu0OkfDwcFauXMnPP/9Mrly58PPzu+02zgfl4uLC0KFDeeaZZ2jRogXdunUjMTGRYcOGERUVxeDBg1PX/eijj2jSpAkNGzakb9++JCcnM2TIEHx8fGxGcGrWrEnXrl154YUX2LJlCxEREfj4+HD27FnWrl1LeHg4r7zyyl1r+vzzz/nggw9o0qQJzZs3vy3oPcgFmU7BEJF7io6ONgBj/xSLcWaWy0O/9k+xGIARHR1t9o9kVzNnzjQ6duxoFCtWzPD19TXc3d2N/PnzG88995yxd+9em3WPHTtmNGrUyPDz8zMAo0CBAoZhGMaKFSsMwJg1a9Yd9/H1118bZcuWNTw8PIyAgACjVatWxp49e2zW6dSpk+Hj42Oz7NSpU0bJkiWNggULGocPHzYMwzCOHj1qvPjii0aePHkMd3d3I0eOHEaNGjWMjz/+OPV9n3/+uVGjRg0je/bshoeHh5E/f37jpZdeMo4dO3bfz+P99983AgMDjYSEBJvl8fHxxrBhw4yyZcsafn5+RlBQkPHYY48ZU6dONVJSUmzWrVSpkhEaGnrffRmGYQB3ff1b7dq1jZYtW6Zpu4MHDzYKFixoWK1Wo1SpUsbEiRONAQMG3LbdHTt2GDVr1jS8vb0NwKhTp85dt3n06FEDMIYNG3bHn2PAgAE2y+bPn29Uq1bN8PT0NHx8fIz69esb69atu+29P/30U+r/H/nz5zcGDx58x1oNwzC++eYbo1q1aoaPj4/h5eVlFClSxHj++eeNLVu23PPzqFOnzgN91vbqG2b1DothpCGaimRht+Zl3z/Fku4LEkt0MjJ0TnbJeGfOnKFQoUJ89913tG/f/oHff/XqVYKCghg+fPhdr414GIcPH6ZYsWIsWbKEhg0b2m27cmf26htgTu/QNQciInaUO3duevfuzSeffEJKSsoDv3/16tXkyZOHl19+2a51ffzxx9SvX1/BQNJE4UBExM7ee+89nnzyyTQ9T+DfmjdvzrFjx/Dw8LBbPUlJSRQpUuS2x0SL3I0uSBQRsTM/Pz+Huprdzc2N9957z+wyxIlo5EBERERsKByIOLDTp0/z7LPPEhwcjLe3N+XLl2fr1q1mlyUiDswefUOnFUQc1JUrV6hZsyb16tVj0aJFhISEcPjwYbJly2Z2aSLioOzVNxQORBzUkCFDyJcvn83seP+eaU5E5J/s1Td0WkEkg8XExNi87va8+p9++onKlSvTrl07QkJCqFChAhMnTszgakXEUaSld9irbygciGSwfPnyERAQkPoaNGjQHdc7cuQIY8eOTX1wTffu3enZsyffffddBlcsIo4gLb3DXn1DpxVEMtjJkydtnnJ2t9ngUlJSqFy5Mp9++ilwc0KhPXv2MHbsWJ5//vkMqVVEHEdaeoe9+oZGDkQymL+/v83rbuEgV65ct82eV6pUKU6cOJERZYqIg0lL77BX31A4EHFQNWvWZP/+/TbLDhw4QIECBUyqSEQcnb36ht3CQXzSDWJv3PnCKhF5cG+88QYbN27k008/5dChQ0yfPp0JEybYdTIeR3A5IdbsEkQyDXv1DbuEg0XHI6k9Zxhf7Vppj82JCFClShXmzZvHjBkzCAsL46OPPmL48OE888wzZpdmF/FJ1+m5eiaPzRrC2dhos8sRyRTs1TfsckGiCxbOxcUwcc9aOpWqTqi3pqMVsYcWLVrQokULs8t4JDxd3Tl59TJxSdf5csdyhtZsY3ZJIpmCPfqGXUYOGuUvTeWQAiQk32D4juX22KSIZHIWi4V3KzcFYObBLRyOvmByRSJyi13CgcVi4Z1KTQCYcWAzR3SQi0gaVMlZkEb5SpFspDBk6xKzyxGRv9ntgsRqoYVokK/kzYN821J7bVZEMrn+lZrgYrHw6/FItl3QbZoijsCutzL2r9gECxYWHtvNjgsn7blpEcmkSgTmpG2RigAM2rIYwzBMrkhE7BoOSgWF0rZoBQA+3bJIB7mIpEnfCg2xurqx4dwRVp4+YHY5Ilme3R+C1LdCQzxcXFl/7girzhy09+ZFJBPK45uNziWrAzBo62JSjBSTKxLJ2uweDvL6BtKp1N8H+ZZFOshFJE1eK1sXP3crey+fZf6RnWaXI5KlPZLHJ79eth5+7lb2XD7LT0d3PYpdiEgmE+jpQ4+ydQEYtm0piclJ5hYkkoU9knAQ5OnDK+F1gJsH+XUd5CKSBi+VrklOLz9OXrvC1P2bzC5HJMt6ZBMvdSldixAvP45fvcy0/X88qt2ISCbi5ebBG+UbADBy5+9c03wtIqZ4ZOHA292DN8rXB2CEDnIRSaP2xStT2D87lxJiGR+52uxyRLKkRzplc4fiVSjkn52LCdeYELnmUe5KRDIJdxdX3qrUGIDxkWu4EH/V5IpEsp5HGg7cXVx5q2IjAMZHruZi/LVHuTsRySSaFwijXPa8xCVdZ8TO380uRyTLeaThAKB5wZsHeWzSdUbqIBeRNPjnpEzT9v/BsZhLJlckkrU88nDgYnFJnZTp+/2bOH5VB7mI3F/NXEWok6c4N1KSGbZd87WIZKRHHg4AauUuSkTuYtxISeazbb9lxC5FJBN45+9rDxYc2UnkpdMmVyOSdWRIOABSRw/mH9nJnktnMmq3IuLEwoLz8ETh8gAM0pTOIhkmw8JBePY8tCpUDgODQVsXZ9RuRcTJvVmxIe4urqw6fYB1Zw6ZXY5IlpBh4QCgX8WGuFlcWHn6AOvPHs7IXYuIkyrgF8wzJaoC8OlWTekskhEyNBwU8s/OMyWqAfCp5m0XkTTqXa4+Pm4e7Lx4ioXHI80uRyTTy9BwANC7/ON4u3mw4+JJftVBLiJpkN3Ll65htQEYsnUJN1KSTa5IJHPL8HCQw8uPl8vUAmDotqUk6SAXkTToFhZBsKcPR2MuMvPAFrPLEcnUMjwcAHQPiyDI6sPh6AvMPLjVjBJExMn4ulvpVe5xAL7csYy4G9dNrkgk8zIlHPh5eNKzXD0Avtj+G/FJOshF5P6eLVGN/L5BnI+/yqS968wuRyTTMiUcADxX8jHy+Qb+fZCvN6sMEXEiHq5u9KvYEIAxu1dyJSHW3IJEMinTwoHV1Y1+f0/KNGb3Sq4kxplViog4kScKl6N0UC6u3kjkq10rzS5HJFNyM3PnrQuXY9zuVfx55Ryjd63kvSrNzCxH5J4G3ciDx42Hz9PXb6QAp+xXUBZ1a76W536bzOQ/1/Ni6Zrk8c1mdlkid5TevgHm9A7TRg7g5kH+9t+PVZ7853rOXIsysxwRcRJ18xSnemhhrqck8/l2zdciYm+mhgOAx/OW4LHQQiQmJ/H5jmVmlyMiTuCfUzrPPryNfVfOmVyRSOZiejiwWCy8U+nmQT7r0FYORJ03uSIRcQYVcuSjWYEwUgyDIZqUScSuTA8HAJVC8tMkfxkd5CLyQPpXaoyrxYXfTv7JH+ePmV2OSKbhEOEA4O1KjXGxWFhyYi9bzh83uxwRcQJFAnLQoVhlAAZtWaT5WkTsxGHCQdFsIbS/dZBv1UEuImnzRoUGeLq6s/mv4/x28k+zyxHJFBwmHAD0Kd8Aq6sbm84fY/mpfWaXIyJOINTbn5dK1wRuTsqUnJJickUizs+hwkEun4DUg3zQlsU6yEUkTV4Nr0OAhxf7o84z5/A2s8sRcXoOFQ7g1kHuyf6o88w7st3sckTECQRYvXi97M35Wj7b/hsJSTdMrkjEuTlcOMhm9abH3wf5sG06yEUkbTqXqk4u7wDOxEYzZd8Gs8sRcWoOFw4AXihVg1Bvf07HRvH9/o1mlyMiTsDTzT11UqZRu1YSnRhvckUizsshw4GXmzt9K9w8yEfuXEHM9QSTKxIRZ9C2SEWKZwshKjGOsZGrzC5HxGk5ZDgAaFe0IkUDcnAlMY5xu3WQi8j9ubq40L9iYwC+3rOOc3ExJlck4pwcNhy4ubimTso0ce9azusgF5E0aJS/NJVDCpCQfIPhO5abXY6IU3LYcADQOH9pKuXIT3zSDUbs/N3sckQy1MCBA7FYLDav0NBQs8tyeP+clGnGgc0cjr5gckUiGcdefcOhw4HFYuGdyjdHD6bt/4Mj0RdNrkgkY5UpU4azZ8+mvnbv3m12SU6has6CNMhXkmQjhaHblppdjkiGskffcOhwAPBYaGHq5715kA/TQS5ZjJubG6GhoamvHDlymF2S03i7UhMsWFh4bDfbL5w0uxyRDGOPvuHw4QD+/yD/+dgudl48ZXY5IukSExNj80pMTLzrugcPHiR37twUKlSIDh06cOTIkQys1LmVDAylbdEKgCZlkswhrb3DHn3DKcJBqaBQ2hQpD9x8rLKIM8uXLx8BAQGpr0GDBt1xvWrVqvHdd9+xZMkSJk6cyLlz56hRowaXLl3K4IqdV98KDfFwcWX9uSOsOnPQ7HJE0iUtvcNefcPNXkU/av0qNOTno7tYe/YQq08fJCJPMbNLEnkoJ0+exN/fP/Vrq9V6x/WaNm2a+t/h4eFUr16dIkWKMGXKFPr06fPI68wM8voG0rlUdSbsWcugLYuIyF0UF4tT/E0kcpu09A579Q2nOUry+QXxfMnHABi0dTEphiZlEufk7+9v87pbOPg3Hx8fwsPDOXhQfwE/iNfL1sPP3cqey2dZcGSX2eWIPLSH6R0P2zecJhwA9Cz3OL7uVnZfOs3PR3XVtmQtiYmJ/Pnnn+TKlcvsUpxKoKcPr4TXAWDYtqVcT04yuSKRjPOwfcOpwkGQpw+vhEUAMFQHuWRy/fr1Y9WqVRw9epRNmzbRtm1bYmJi6NSpk9mlOZ0upWsR4uXHiWuXmbp/k9nliDwy9uobThUOAF4uU5scXr4cv3qJGQc2m12OyCNz6tQpnn76aUqUKEGbNm3w8PBg48aNFChQwOzSnI63uwdvlK8PwIidv3Ptxt3vEBFxZvbqG05zQeIt3u4e9C5Xn/9uXMCXO5bTtmhFfNzTds5WxJn88MMPZpeQqXQoXoUJe9ZyNOYiEyLX0KdCA7NLErE7e/UNpxs5AOhYoioF/YK5mHCNiXvWml2OiDgBdxdX+ldsBMD4yNVcjL9mckUijsspw4G7iytv/X2Qj4tczaUEHeQicn/NC4ZTLnteYpOua74WkXtwynAA0KJQOOHBebh2I5GRO1eYXY6IOAGLxcI7f8/2OnX/Jo5f1QOlRO7EacOBi8WFd/+elOn7fRs5efWyyRWJiDOolbsodXIX40ZKMsO2/WZ2OSIOyWnDAUDt3MWonbso11OS+Wy7DnIRSZtbs73OP7KDPZfOmFyNiONx6nAApA4Rzj28g72Xz5pcjYg4g7DgPLQqVA64+cRVEbHl9OGgbPa8/KdQWQwMBusgF5E0erNiI9wsLqw8fYB1Zw+bXY6IQ3H6cAD/f5D/fmo/G85pSlsRub+C/sE8U6IacHO2V03pLPL/MkU4KOSfnY4lqgLwqeZtF5E06l3+cbzdPNhx8SS/Ho80uxwRh5EpwgFA73L18XJzZ/uFkyw+scfsckTECeTw8qNrWG0AhmxdQlJKsskViTiGTBMOQrz96FpGB7mIPJhuZWoTZPXhSMxFfji4xexyRBxCpgkHAN3DIgi0enMo+gI/Htpqdjki4gT8PDzpWa4eAF9uX0Z80nWTKxIxX6YKB34envQq9zgAX2xfRnzSDZMrEhFn8FzJx8jnG8j5+KtM2rvO7HJETJepwgHcPMjz+mbjXFwMk/9cb3Y5IuIErK5u9Pt7vpYxu1dxJTHO5IpEzJXpwoHV1Y1+FRoCMHrXCqJ0kItIGrQuXI5SgaHEXE/gq10rzS5HxFSZLhwAtC5cgZKBoURfT2D0rlVmlyMiTsDF4sI7lZsC8O2f6zl9LcrcgkRMlCnDgauLS+pjlb/5cx1nYqNNrkhEnEG9PMV5LLQQiclJfLFD87VI1pUpwwHA43lLUC1nQRKTk/hyxzKzyxERJ3BzSuebowezDm1j/5XzJlckYo5MGw4sFgvv/j1EOPPgFg5G/WVyRSLiDCqF5KdpgTKkGAZDNF+LZFGZNhwAVAopQOP8pf8+yJeYXY6IOIn+FRvjYrGw9OSfbD5/zOxyRDKcxcjkExEcjPqL+vO/JMUwWND8VSqF5De7JHEyMTExBAQEcKD4//Bz9Xzo7VxNTqD4gQ+Ijo7G39/fjhXKo/DmujnMOLCZqjkLMqdpNywWi9kliROxV98Ac3pHph45ACiWLYSnilYCNCmTiKRdn/INsLq68cf5Yyw7+afZ5YhkqEwfDgD6VGiI1dWNTeeP8vup/WaXIyJOIJdPAC+VrgnA4K1LSE5JMbkikYyTJcJBbp8AXihVA4BBWxfrIBeRNHk1vA4BHp7sjzrP3MPbzS5HJMNkiXAA0KNsXQI8PNl35RzzjuwwuxwRcQLZrN68VvbmpEzDti8lQfO1SBaRZcJBoNWbV8PrAvDZ9qUkJieZW5CIOIXOpWqQyzuAM7HRfLdvo9nliGSILBMOAF4sXYOc3v6cuhbF9zrIRSQNvNzc6VOhAQAjd60g5nqCyRWJPHpZKhx4uXnQ99ZBvnMFV3WQi0gatCtakWIBIUQlxjF2t+ZrkcwvS4UDgKeKVqJoQA4uJ8YyLnK12eWIiBNwc3Glf6XGAEzcs5bzcTEmVyTyaGW5cODm4spbFf//IP8r7qrJFYmIM2icvzSVcuQnIfkGw3csN7sckUcqy4UDgKYFylAhRz7ikq4zYqcOchG5P4vFwjuVb872Ov3AZo5EXzC5IpFHJ0uGg39OyjRt/x8cjblockUi4gweCy1M/bwlSTZSGLptqdnliDwyWTIcAFQPLUy9PCVIMlL4bJvmbReRtHm7UhMsWPjl2G52XDhpdjkij0SWDQcA71RujAULC47uZNfFU2aXIyJOoFRQKE8WqQDcfOKq5muRzChLh4PSQblpXaQ8cPPZ6SIiadGvYkM8XFxZd/Ywq88cNLscEbvL0uEAoF+Fhri7uLL6zEHW6CAXkTTI6xvI8yUfA2DQlsWkGJqvRTKXLB8O8vsF6SAXkQfWs9zj+Lpbibx8hp+O7jK7HBG7yvLhAKBnuXr4ulvZdek0C49Fml2OiDiBIE8fXgmLAGDYtqVc13wtkokoHADBnr50C6sNwJCtS7iRkmxyRSLiDF4uU5scXr4cv3qZ6Qc2m12OiN0oHPyta5naZPf05djVS8zQQS4iaeDt7sEb5W/O1zJ8x3JibySaXJGIfSgc/M3H3Urv8vXBMPhi+zIuxl8zuyQRcQJPF69CQb9gLsZf5Ysdy8wuR8QuFA7+oU3+cOoeSCRfnIWIuZ8zbNtShQQRuSd3F1ee9y1KzcOJTI3cwJO/juO3E3t1cbM4NYWDvyUlJTH560n4XIknZNcZriXEMWLn71SbNZi318/Tc9TFdIMGDcJisdC7d2+zS5F/OHToEDt/Xka2i/HkPhPLpvPHeGH5dzw+70tmHNhMQtINs0uULOxh+4bCAWAYBt9//z179+7Fw8ODd3v1ZWz9Z6mQIx+JyUlM3b+JOnO/4KXl37Hl/HGzy5UsaPPmzUyYMIGyZcuaXYr8w5kzZxg9ejRJSUmUK1eO719/n1fC6uDnbuVQ9AXeXDeH6rOHMGrnCqIS48wuV7KY9PQNhQNg3rx5bNy4ERcXF7p160aRwoVpXjCcn5q/ypym3WiYrxQGBktO7OWJX8fyxMKxLD6+R8OGkiGuXbvGM888w8SJEwkMDDS7HPnblStXGDlyJHFxcRQuXJguXbqQ1z+I/1Zpyh9PvcP7VZqRyzuAC/HXGLJtCVV/HMyATT9z6toVs0uXLCC9fSPLh4Pff/+dJUtuPjr5ueeeIywsLPV7FouFaqGFmNygEyta96FDscp4uLiy5a/jdPn9e+rO/YKp+zdp2FAeSExMjM0rMfHeV7j36NGD5s2b06BBgwyqUO4nLi6OkSNHcuXKFXLmzEmPHj3w8PBI/b6fhyfdwiJY3+4thtd+ilKBocQlXWfS3nXUnD2MHqtmEHnptIk/gTijB+kd6e0bWTocbNmyhR9//BGAVq1aUaNGjbuuWyxbCJ/VasuGdv15rWxdAjw8ORJzkbfXz+OxWUMYvmM5VxJiM6p0cWL58uUjICAg9TVo0KC7rvvDDz+wbdu2e64jGevGjRuMHTuWM2fO4O/vT8+ePfH19b3juu4urrQtWpGlrXoxrdGL1M5dlGQjhQVHdtLkp1F0WPw1K07t1+RNkiZp7R326BtuD/1OJ7d//34mT56MYRjUqVOHpk2bpul9Ob39ebtSE14rW48fDmxm4p61nI6N4rPtvzF690raF6tM1zK1ye8X9Gh/AHFaJ0+exN/fP/Vrq9V61/V69erF0qVL8fT0zKjy5B5SUlL45ptvOHDgAJ6envTs2ZPs2bPf930Wi4U6eYpTJ09xIi+dZlzkGn4+uou1Zw+x9uwhSgaG0j2sNv8pVA4P1yzbluU+0tI77NU3LEYWjKynT59m2LBhxMfHU6FCBbp27YqLy8MNotxISWbhsd2M272ayMtnAHCxWGheIJzu4RGUy57XnqWLCWJiYggICOBA8f/h5/rwB9vV5ASKH/iA6OhomwP8bubPn0/r1q1xdXVNXZacnIzFYsHFxYXExESb78mjZRgGM2fOZMWKFbi6utKzZ09Kliz50Ns7de0KX+9Zy/QDm4lLug5AqLc/XUrXomOJqvh7KBA6M3v1DXiw3mGvvpHlwsHly5cZMmQIUVFRFC1alN69e+Pu7p7u7RqGwbqzhxkbuZpVpw+kLn8stBCvhNWhXt7iuFiy9Fkcp2VWOLh69SrHj9veHfPCCy9QsmRJ+vfvb3N9jDx6ixcvZt68eQB06dKFKlWq2GW7UYlxTN3/B9/sXcdf8VcB8HO30rFENV4qXZPcPgF22Y9kLLPCgb36RpYav4qNjWXkyJFERUWRO3duXn31VbsEA7g5bFgrd1Fq5S7K3stnmRC5hvlHdrDx3FE2njtK8WwhdAuL4InC5bFq2FDSwM/P77YD2cfHh+DgYAWDDLZx48bUYNCuXTu7BQOAbFZvXitbl5fL1GLe4e2Mj1zDwei/GB+5mkl71vJE4fJ0C4ugVFCo3fYpmZe9+kaW+VP2+vXrjB49mrNnz5ItWzZef/11fHx8Hsm+SgflYnjEU6xv159uYRH4uls5EPUXfdfOpsasIYzetZLoxPhHsm8Rsa89e/YwZcoUABo2bPjI7hqxurrRoXgVlrfuzbcNOlEtZyGSjBRmH95GwwXDeXbpN6w7c0gXL0qGyBKnFVJSUhg/fjw7duzA29ubfv36kSdPngzbf8z1BKbt38TXe9dxPi4GAB83D54pUZUupWuR2zdbhtUiD86s0wpivuPHj/P555+TmJhI1apVeeGFFx76+qSHsf3CScZFrmbR8UhS/m7V4cF56B4WQfOCYbi56JoTR2XWaQV7yfThwDAMZsyYwapVq3Bzc6NXr14UL17clFquJyex4MhOxkWuZn/UeQDcLC78p3A5uofVpnRQblPqkntTOMiaLly4wJAhQ7h69SolS5bk9ddfx83NnFOCx2IuMXHPWmYe3EJC8s3nquTzDaRLmVp0KFYZH/c73/Ei5lE4cHC//vorCxYswGKx0LVrVypWrGh2SRiGwcrTBxgXuZp1Zw+nLo/IXYzuYRHUzl0Ui8ViYoXyTwoHWU9MTAzDhg3jr7/+Il++fPTt2xcvLy+zy+JyQixT9m3g2z83cOnv56oEeHjxfMnHeKFUDUK8/UyuUG5x9nCQqa+MW7duHQsWLACgffv2DhEM4ObFi/XylqBe3hLsuniK8ZFr+PnYLlafOcjqMwcpE5SLbmERtCxUFncNG4pkqISEBEaPHs1ff/1FcHAwr7/+ukMEA4AgTx/eKN+A7mF1mH1oK+Mj13Ds6iVG7VrB+MjVPFm0It3K1KZothCzSxUnl2lHDnbv3s2YMWNISUmhSZMmtG7d2uyS7unk1ctM3LOWGQc3E//345hz+wTwcplaPF28Kr4aNjSNRg6yjuTkZMaMGUNkZCQ+Pj689dZbhIY67l0CySkpLDmxl3GRq9l24UTq8kb5StE9vA5VQgpoFNIkzj5ykCnDwdGjR/niiy+4fv061atXp1OnTk5zgFxJjOP7fRuZ/Od6LsRfA8Dfw5NnS1TjxdI1CfXWL5WMpnCQNRiGwZQpU9iwYQPu7u707duXQoUKmV1Wmm0+f4xxkatZeuJPDG629Yo58tMtrDZN8pfBNQMvpBTnDweZ7rTC+fPn+eqrr7h+/TplypThueeec5pgABBo9aZnucfpWqY2c4/cvOf5cPQFxuxexcQ9a2lT5OY9z8Wz5TS7VJFMZcGCBWzYsAEXFxe6du3qVMEAoErOglTJWZDD0RcYH7mGOYe3se3CCbqtmEZBv2C6htWmXdFKeLnZ59kukrllqpGD6Ohohg4dysWLFylQoAB9+vRx+mfSpxgpLDu5j3GRq/nj/LHU5fXzlqR7eASP5SzkVOHHGWnkIPNbuXIlM2bMAG7OzlqrVi2TK0q/C/FXmbx3PVP2bST6+s3nqgRZfehcqjqdS1UnyPPRPOdFbnL2kYNMEw4SEhL4/PPPOXHiBDly5OCtt97KdA14618nGBe5isXH96YOG5bLnpfuYRE0LVBG9zw/IgoHmdu2bduYMGEChmHQsmVLWrRoYXZJdhV7I5GZB7cwcc9aTl67AoCnqztPFavEy2VqUcj//hNHyYNTOHAASUlJfPXVV/z555/4+fnRv39/cuTIYXZZj8yR6It8vffmPc+JyUkA5PcN4uUytWhfrDLe7h732YI8CIWDzOvgwYMMHz6cpKQkateuzTPPPJNpR+KSUpL59Vgk4yJXs+vSaQAsWGhaoAzdwyOomCO/yRVmLgoHJktJSWHy5Mn88ccfWK1W+vTpQ8GCBc0uK0NcSrjGt3/evOf5SmIccPM57Z3+vuc5u9ed55iXB6NwkDmdOXOGYcOGERcXR7ly5ejWrVuWmOXSMAzWnzvCuN2rWXF6f+ryajkL0j0sgvr5SmqSODtw9nDg9Bckzps3jz/++CP1IqKsEgwAgj196VuhIa+G1+HHg1uZsGcNx69eZsTO3xkXuZp2RSvRtUxtCgdo2FDkn65cucLIkSOJi4ujcOHCdOnSJUsEA7j5nJWauYpQM1cR9l05x/jI1cw/spNN54+x6fwxigbkoFtYBG2KVNAkcVmYU48cLF++nB9//BGAzp07U716dZMrMldySgqLTuxh3O7V7Lh4Erg5bNg4f2leCY+gUkgBkyt0Tho5yFzi4uIYNmwYZ86cITQ0lDfffBNf36w9ynY2Nppv9q5n6v6NXL2RCECIlx8vlq7BsyWqkc3qbXKFzsfZRw6cNhxs2bKFr7/+GsMwaN26NU2aNDG7JIdhGAabzh9lfOQafjv5Z+ryyiEF6B4WQaP8pTRs+AAUDjKPGzduMGLECA4ePEi2bNl46623CA4ONrssh3H1egLTD/zB13vWcTYuGgBvNw+eLl6Fl8vUIq9voMkVOg+FAxPs37+fkSNHkpSURN26denQoUOmvYgovQ5G3ZwXfu7h7VxPSQagsH92uobVpm2Rinjqnuf7unWQ93xlJtZ0/AWVmBjHyLHtFQ5MkpKSwsSJE9m2bRuenp68+eab5M2b1+yyHNKNlOTUSeL2XTkHgKvFhRaFwnklLIKw4Iyb1dZZ2atvgDm9w+n+fDx16hRjxowhKSmJihUr0r59ewWDeyiWLYTParVlQ7v+vFa2LgEenhyJucjb6+fx2KwhjNixnCt/T+AiklkZhsHMmTPZtm0bbm5uvPrqqwoG9+Du4krbohX5rVUvpjZ6kdq5i5JspLDgyE6a/DSKDou/ZuXpAzjh35aSRk51tcnly5cZNWoUCQkJFCtWjBdffDFD51Z3Zjm9/Xm7UhNeK1uPHw5sZuKetZyOjWLY9t/4avdKOhS7OWyY3y/I7FJF7G7JkiWsXLkSuHl9UokSJcwtyElYLBbq5ilO3TzFibx0mnGRa/j56C7Wnj3E2rOHKBkYSvew2vynUDk8dPFipuI0v1ljY2MZOXIkUVFR5M6dm1deeQV3dw2JPyhfdytdytRibds3+apOB8KCchOfdIPJf66n1pxhvLJiOjsvnjK7TBG72bBhA/PmzQOgXbt2VKlSxeSKnFNYcB6+qtOBdW3fpEvpmni7ebDvyjl6r5lFjdlDGbd7NVevJ5hdptiJU4SD69evM3r0aM6ePUtgYCA9e/bEx0eP/kwPdxdXnihcnkX/eZ0fGnehTp7ipBgGPx/bRfOfv6LdogksP7mPFCPF7FJFHlpkZCTfffcdAA0bNqRBgwYmV+T88voGMrBaS/546m3ertSYEC8/zsXF8PGWX6n64yA+3vwrZ2OjzS5T0snhx4GSk5P5+uuvOXz4MN7e3vTs2ZPAQF0xay8Wi4VauYtSK3dR9l4+y/jI1Sw4spMN546w4dwRimcLoVtYBE8ULq97nsWpHDt2jAkTJpCSkkLVqlVp06aN2SVlKtms3rxWth4vl6nNvMM3J4k7GP0X4yJX8/WetTxR+OYkcaWCHHfKa7k7hx45MAyDH374gZ07d+Lm5kaPHj3InTu32WVlWqWDcjEioj3r275FtzK18XW3ciDqL/qunU2N2UMZvWsl0YnxZpcpcl8XLlzgq6++IjExkVKlStGpUyddn/SIWF3d6FC8Cstb9+bbBp2olrMQSUYKsw9vo+GC4Ty79BvWnTmkixedjEP/Kfjrr7+yevVqLBYLL730EkWLFjW7pCwht2823q/anF7l6zNt/ya+3ruO83ExDNq6mFG7VtCxeBW6lK5Fbt9sZpcqcpuYmBhGjBjB1atXyZcvH927d8fNzaFbXabgYnGhQb5SNMhXiu0XTjIucjWLjkey8vQBVp4+QHhwHrqHRdC8YJgmiXMCDhul165dy08//QRAhw4dqFixoskVZT3+Hp68El6HDW3f4sta7SiRLSfXbiQyYc9aasweSs/VM9l7+YzZZYqkSkhI4KuvvuLChQtkz56d119/3emnbXdGFXLkY3y9Z1jdph+dSj6Gp6s7uy+dpseqGdSe8xmT9q4j9u8nMYpjcshwsHv3bqZNmwZA06ZNqVu3rrkFZXEerm60K1aJZU/05ruGL1AjtDBJRgpzD2+n0YKRdFwyidWnD2rYUEyVnJzMhAkTOH78OL6+vvTs2ZOAgACzy8rSCvoH80n1J/jjqbfpW6EBQVYfTl67woBNP1P1x8EM2bqEv+Kuml2m3IHDjbUdPXqU8ePHk5KSQvXq1WnVqpXZJcnfLBYLj+ctweN5S7Dr4inGR67h52O7WH3mIKvPHKRMUC66hUXQslBZ3DVsKBnIMAy+//579uzZg4eHB6+99ho5c+Y0uyz5W5CnD2+Ub0D3sDrMPrSV8ZFrOHb1EqN2rWDCnjW0KVKBbmVqUzRbiNmlyt8cauTg/PnzjBo1ihs3bhAWFsZzzz2npx86qLLZ8zK67tOse/JNXixVAy83d/ZcPkvP1TOpNXsYE/es4ZqGDSWDLFiwgA0bNqTOzlqoUCGzS5I78HJz57mSj7GqTV8m1HuWijnyk5icxIwDm6k77wteXDaFP84f0yikA3CYcBAdHc2IESOIjY2lYMGCvPzyy1lmClVnls8viP899h/+eOod3qrYiOyevpyOjeLDPxZS9cdBDNqymPNxMWaXKZnYihUrWLRoEQDPPvss4eHhJlck9+Pq4kKzgmEsaP4Kc5t1p1G+UgAsPfknbX4dR6uFY/n1WCTJKXrOilkc4rRCfHw8o0aN4tKlS4SEhPDaa6/pIiInE2j1pme5x+lapjZzDm9nwp41HI6+wOjdK5m4Zw2ti1SgW1htimfTUK/Yz7Zt25g5cyYA//nPf6hZs6bJFcmDsFgsVM1ZkKo5C3I4+gLjI9cw5/A2tl04QdcVUynoF0y3sNq0LVoJL00Sl6FMHzlISkpi3LhxnDx5Ej8/P3r27Imfn5/ZZclD8nRz55kSVVnR+g2+qf88VXMW5HpKMjMPbuHxeV/S6bdv2XDuiIYNJd0OHjzIpEmTMAyDiIgImjVrZnZJkg5FAnIwtGYbNrbrT8+y9Qjw8OLY1Uu8s2E+1X4czBfbl3FZk8RlGFNHDlJSUpgyZQr79u3DarXy+uuvkyNHDjNLEjtxsbjQKH9pGuUvzda/TjAuchWLj+9l+al9LD+1j3LZ8/JKWARNCpTRPc/ywM6cOZM6O2v58uV5+umndX1SJpHDy4+3KjWmR9m6/HBwC1/vWcvJa1f4YscyxuxeRftilXi5TG0K+gebXWqmZurIwdy5c/njjz9wcXGhe/fuFChQwMxy5BGpFJKfiY8/x6o2fXmuRDWsrm7svHiK7iunEzHnc779cwPxSdfNLlOcxOXLlxk5ciRxcXEUKVKEl156SU8/zIR83K28VLoma57sx+g6TxMenIeE5BtM2beR2nM+o9uKaWy/cNLsMjMt046oZcuW8dtvvwHQqVMnSpcubVYpkkEKB2RnUI3WbGr3Nr3L1yfQ6s2Ja5d5b+MCqv44mGHblnIx/prZZYoDi42NZdSoUVy5coVcuXLRo0cPPDw8zC5LHiE3F1daFS7Hry1fY2aTl6mXpwQGBguP7ablL6N58tfx/HZiryaJszNTTits3ryZWbNmAdC6dWsee+wxM8oQk2T38qVfhYb0CK/Djwe3MmHPGo5fvcyInb8zLnI17YpWomuZ2hQOyG52qeJAbty4wdixYzlz5gzZsmXT7KxZjMVioWauItTMVYR9V84xPnI184/sZNP5o2w6f5RiASF0DatNmyIVNEmcHWT4yMH+/fv59ttvAahXrx6NGzfO6BLEQXi5edCpVHVWt+nHuHrPUD57PhKTk5i6fxN15n5Ol+Xfs/Wv42aXKQ4gJSWFb775hoMHD+Lp6UnPnj0JCgoyuywxScnAUL6s/RTr275F97AI/NytHIz+izfXzaH6rCF8tWsFUYlxZpfp1DI8HOzcuZOkpCQqVarEU089pYuIBFcXF1oUDOfnFq8yu2lXGuQriYHB4hN7aLVwLE8sHMvi43s0bJiFRUVFceTIEdzc3Hj11VfJkyeP2SWJA8jlE8B7VZrxx1Pv8H6VZuTyDuCv+KsM3rqEqj8OZsCmnzl17YrZZToli5HB95QZhsH69eupWrUq7u66b1Xu7EDUeSZErmHu4e1cT0kGoLB/drqG1aZtkYp4ZuA9zzExMQQEBNDzlZlYrd4PvZ3ExDhGjm1PdHQ0/v7+dqwwa7h8+TKnT5/WQ47krq4nJ/HT0V2Mi1zNvivnAHC1uNCiUDivhEUQFpxxodJefQPM6R0ZHg5EHsT5uBgm/7me7/dtJPp6AgDZPX15oVR1ni/5GIGej/6cs8KBiHMxDINVZw4yPnI1a84cSl1eK1dRuodHUCd3sUc+au3s4UBXbYhDy+ntz9uVmvBa2Xr8cGAzE/es5XRsFMO2/8ZXu1fSoVgVXi5Ti/x+Ov8sIjdZLBbq5ilO3TzFibx0mnGRa/j56C7Wnj3E2rOHKBkYSvew2vynUDk8dPHiHenmYHEKvu5WupSpxdq2bzIqogNlgnIRn3SDyX+up9acYbyyYjo7L54yu0wRcTBhwXn4qk4H1rV9ky6la+Lt5sG+K+fovWYWNWYPZdzu1Vz9e1RS/p/CgTgVdxdXWhcpz+L/9OSHxl2ok6c4KYbBz8d20fznr2i3aALLT+7T45lFxEZe30AGVmvJH0+9zduVGhPi5ce5uBg+3vIrVX8cxMebf+VsbLTZZToMhQNxShaLhVq5izKt0YssbdWLJ4tUwM3iwoZzR+i07Fum7t9kdoki4oCyWb15rWw9NrTrz7CaT1I0IAdXbyQyLnI1DReMIDE5yewSHYJOtojTKx2UixER7elfsTGT9q5j/tGd/KdQObPLEhEHZnV14+niVWhfrBLLT+5jXOQaymbPowco/U2fgmQauX2z8X7V5rxduQnumsxJRNLAxeJCw/ylaZi/NDf+vm1adFpBMqHMEgzGjh1L2bJl8ff3x9/fn+rVq7No0SKzyxLJtDJD77BX31A4EHFQefPmZfDgwWzZsoUtW7bw+OOP06pVK/bs2WN2aSLioOzVN3RaQcRBtWzZ0ubrTz75hLFjx7Jx40bKlCljUlUi4sjs1TcUDkQyWExMjM3XVqsVq9V6z/ckJycza9YsYmNjqV69+qMsT0Qc1IP2jvT0DZ1WEMlg+fLlIyAgIPU1aNCgu667e/dufH19sVqtdO/enXnz5lG6dOkMrFZEHEVae4c9+oZGDkQy2MmTJ22ej36v5F+iRAl27NhBVFQUc+bMoVOnTqxatUoBQSQLSmvvsEffUDgQyWC3riJOCw8PD4oWLQpA5cqV2bx5MyNGjGD8+PGPskQRcUBp7R326Bs6rSDiRAzDIDEx0ewyRMSJPEzf0MiBiIN69913adq0Kfny5ePq1av88MMPrFy5ksWLF5tdmog4KHv1DYUDEQd1/vx5nnvuOc6ePUtAQABly5Zl8eLFNGzY0OzSRMRB2atvKByIOKhJkyaZXYKIOBl79Q1dcyAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERs6FZGkTTqFNUBXw/LQ7//2nWDkXasR0QcX3r7BpjTOzRyICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBBxUIMGDaJKlSr4+fkREhLCE088wf79+80uS0QcmL36hsKBiINatWoVPXr0YOPGjfz2228kJSXRqFEjYmNjzS5NRByUvfqG2yOqT0TSafHixTZfT548mZCQELZu3UpERIRJVYmII7NX31A4EMlgMTExNl9brVasVut93xcdHQ1AUFDQI6lLRBzbw/SOh+0bOq0gksHy5ctHQEBA6mvQoEH3fY9hGPTp04datWoRFhaWAVWKiKN50N6Rnr6hkQORDHby5En8/f1Tv07LqMFrr73Grl27WLt27aMsTUQc2IP2jvT0DYUDkQzm7+9vc4Dfz+uvv85PP/3E6tWryZs37yOsTEQc2YP0jvT2DYUDEQdlGAavv/468+bNY+XKlRQqVMjskkTEwdmrbygciDioHj16MH36dBYsWICfnx/nzp0DICAgAC8vL5OrExFHZK++oQsSRRzU2LFjiY6Opm7duuTKlSv1NXPmTLNLExEHZa++oZEDkTRqUasXLl73v3jwblLiE2HG8DSvbxjGQ+9LRBxDevsGPFjvsFff0MiBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciDmr16tW0bNmS3LlzY7FYmD9/vtkliYgTsEfvUDgQcVCxsbGUK1eOr776yuxSRMSJ2KN3uNmxHhGxo6ZNm9K0aVOzyxARJ2OP3qFwIJJGRnwiKel8P0BMTIzNcqvVitVqTceWRcRRpbdv3NoGZGzvUDgQuQ8PDw9CQ0M5129surfl6+tLvnz5bJYNGDCAgQMHpnvbIuI47Nk3ION7h8KByH14enpy9OhRrl+/nu5tGYaBxWKxWaZRA5HMx559AzK+dygciKSBp6cnnp6eZpchIk7EmfuG7lYQERERGxo5EHFQ165d49ChQ6lfHz16lB07dhAUFET+/PlNrExEHJk9eofFMAzjURUoIg9v5cqV1KtX77blnTp14ttvv834gkTEKdijdygciIiIiA1dcyAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjY+D+CWfAsU69c4gAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [107.29030340175414]\n", - "(8, 1) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 3\n", - "Adjacent strokes (list): [1, 0, 1, 0]\n", - "Adjacent strokes (uniques): {0, 1}\n", - "Checking edge: (0, 1)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [[90.12528714780073, 89.74560192447649], [90.24732195021957, 89.88178897750322]]\n", - "(0, 1) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 4\n", - "Adjacent strokes (list): [2, 6, 2, 6]\n", - "Adjacent strokes (uniques): {2, 6}\n", - "Checking edge: (2, 6)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [[94.78903631548253, 84.23886881283048], [81.14186114900058, 99.83023372268642]]\n", - "(2, 6) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 5\n", - "Adjacent strokes (list): [3, 3, 1, 1]\n", - "Adjacent strokes (uniques): {1, 3}\n", - "Checking edge: (1, 3)\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh0AAAGTCAYAAACMMqDSAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABJg0lEQVR4nO3deVQUV94+8KdRaEBpEJRN3IMLi4Kyd4sat4g4msRI4gxqxuwYt+QdR0eDTjJxSTIR9+QNEZeIxqDiHjVRSLe4A0bjmhhBBFegAQUE6veHL/WzBFmbosXnc06fM325VX0LJ1+eqq5bVyEIggAiIiKiBmbS2AMgIiKiZwNDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDyEitXLkSPXv2hEqlgkqlQmBgIPbs2VPlNgkJCejTpw/Mzc3RuXNnrFq1qkKfuLg4uLm5QalUws3NDVu3bm2oQyAimRl73WDoIDJSLi4uWLBgAU6cOIETJ07g+eefx8iRI3H27NlK+1+5cgUhISHo27cvkpOTMWvWLEyePBlxcXFin6SkJISFhSE8PBypqakIDw/HmDFjcPToUbkOi4gakLHXDQUXfCN6etja2uKzzz7DxIkTK/xsxowZ2L59O86dOye2vfPOO0hNTUVSUhIAICwsDHq9XnLm88ILL6BVq1aIjY1t+AMgItkZU91oXsdjIHqmFBYWori4uN77EQQBCoVC0qZUKqFUKqvcrrS0FJs3b0ZBQQECAwMr7ZOUlIQhQ4ZI2oYOHYro6Gg8ePAApqamSEpKwrRp0yr0Wbx4ce0PhoiqZKi6AdStdhhj3WDoIKpGYWEhbG1tcf/+/Xrvq2XLlsjPz5e0RUZGYu7cuZX2//XXXxEYGIjCwkK0bNkSW7duhZubW6V9s7Ky4ODgIGlzcHBASUkJbt++DScnpyf2ycrKqvtBEVEFhqwbQO1qhzHXDYYOomoUFxfj/v37GDt2LMzMzOq1nw0bNiA9PR0qlUpsr+pMpVu3bkhJSUFOTg7i4uIwfvx4JCQkPLGAPH4mVP7t6aPtlfV5vI2I6sdQdaN8X7WpHcZcNxg6iGrIzMys3sUDgHhXeU0/87nnngMA+Pj44Pjx44iKisJXX31Voa+jo2OFM4+bN2+iefPmsLOzq7LP42cxRGQYhqobQM1rhzHXDc5eIXqKCIKAoqKiSn8WGBiI/fv3S9r27dsHHx8fmJqaVtknKCioYQZMRI3OmOoGr3QQGalZs2Zh2LBhaNeuHfLy8rBx40YcOnQIe/fuBQDMnDkTGRkZWLt2LYCHd5wvW7YM06dPx5tvvomkpCRER0dL7i6fMmUKgoODsXDhQowcORLx8fE4cOAAtFptoxwjERmWsdcNhg4iI3Xjxg2Eh4cjMzMT1tbW6NmzJ/bu3YvBgwcDADIzM5GWlib279SpE3bv3o1p06Zh+fLlcHZ2xpIlS/Dyyy+LfYKCgrBx40bMnj0bc+bMQZcuXbBp0yb4+/vLfnxEZHjGXjf4nA6iauj1elhbW2PChAn1vpE0JiYGubm5Nb6ng4ieToaqG0DTqh28p4OIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQGan58+fD19cXVlZWsLe3x6hRo3DhwoUqt5kwYQIUCkWFl7u7u9gnJiam0j6FhYUNfUhE1MCMvW4wdBAZqYSEBERERODIkSPYv38/SkpKMGTIEBQUFDxxm6ioKGRmZoqv9PR02Nra4pVXXpH0U6lUkn6ZmZkwNzdv6EMiogZm7HWjeZ2Oioga3N69eyXvV69eDXt7e5w8eRLBwcGVbmNtbQ1ra2vx/bZt25CdnY3XX39d0k+hUMDR0dHwgyaiRmXsdYNXOohkptfrJa+ioqIabZebmwsAsLW1rfFnRUdHY9CgQejQoYOkPT8/Hx06dICLiwtCQ0ORnJxc8wMgokZRl9phbHWDVzqIakhjvR+Wyrrn9HtFZYgB0K5dO0l7ZGQk5s6dW+W2giBg+vTp0Gg08PDwqNHnZWZmYs+ePdiwYYOkvXv37oiJiYGnpyf0ej2ioqKgVquRmpoKV1fXWhwREVWnvnUDqHvtMMa6wdBBJLP09HSoVCrxvVKprHabSZMm4fTp09BqtTX+nJiYGNjY2GDUqFGS9oCAAAQEBIjv1Wo1evfujaVLl2LJkiU13j8Ryau2tcMY6wZDB5HMVCqVpHBU5/3338f27duRmJgIFxeXGm0jCAK+/fZbhIeHw8zMrMq+JiYm8PX1xaVLl2o8JiKSX21qh7HWDd7TQWSkBEHApEmTsGXLFvz888/o1KlTjbdNSEjA5cuXMXHixBp9TkpKCpycnOozXCIyAsZeN3ilg8hIRUREYMOGDYiPj4eVlRWysrIAPLzT3MLCAgAwc+ZMZGRkYO3atZJto6Oj4e/vX+n3uPPmzUNAQABcXV2h1+uxZMkSpKSkYPny5Q1/UETUoIy9bjB0EBmplStXAgD69+8vaV+9ejUmTJgA4OFNX2lpaZKf5+bmIi4uDlFRUZXuNycnB2+99RaysrJgbW0Nb29vJCYmws/Pz+DHQETyMva6oRAEQajVFkTPGL1eD2tra3wzpW29Z6+8EZWB3NzcWt3TQURPH0PVDaBp1Q7e00FERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIjNT8+fPh6+sLKysr2NvbY9SoUbhw4UKV2xw6dAgKhaLC6/z585J+cXFxcHNzg1KphJubG7Zu3dqQh0JEMjH2usHQQWSkEhISEBERgSNHjmD//v0oKSnBkCFDUFBQUO22Fy5cQGZmpvhydXUVf5aUlISwsDCEh4cjNTUV4eHhGDNmDI4ePdqQh0NEMjD2uqEQBEGo9VERPUP0ej2sra3xzZS2sFTWPaffKyrDG1EZyM3NhUqlqvX2t27dgr29PRISEhAcHFxpn0OHDmHAgAHIzs6GjY1NpX3CwsKg1+uxZ88ese2FF15Aq1atEBsbW+txEVFFhqobQP1qh7HVDV7pIJKZXq+XvIqKimq0XW5uLgDA1ta22r7e3t5wcnLCwIEDcfDgQcnPkpKSMGTIEEnb0KFDcfjw4RoeARE1hrrUDmOrG81r1ZvoGda393VYWSrqvH3evYcXFdu1aydpj4yMxNy5c6vcVhAETJ8+HRqNBh4eHk/s5+TkhK+//hp9+vRBUVER1q1bh4EDB+LQoUPiWU5WVhYcHBwk2zk4OCArK6sOR0VEValv3QDqXjuMsW4wdBDJLD09XXKJVKlUVrvNpEmTcPr0aWi12ir7devWDd26dRPfBwYGIj09HZ9//rnk0qpCIS2CgiBUaCMi41Lb2mGMdYNfrxDJTKVSSV7VFY73338f27dvx8GDB+Hi4lLrzwsICMClS5fE946OjhXOTm7evFnhLIaIjEttaoex1g2GDiIjJQgCJk2ahC1btuDnn39Gp06d6rSf5ORkODk5ie8DAwOxf/9+SZ99+/YhKCioXuMlosZn7HWDX68QGamIiAhs2LAB8fHxsLKyEs8yrK2tYWFhAQCYOXMmMjIysHbtWgDA4sWL0bFjR7i7u6O4uBjr169HXFwc4uLixP1OmTIFwcHBWLhwIUaOHIn4+HgcOHCg2kuwRGT8jL1uMHQQGamVK1cCAPr37y9pX716NSZMmAAAyMzMRFpamviz4uJifPjhh8jIyICFhQXc3d2xa9cuhISEiH2CgoKwceNGzJ49G3PmzEGXLl2wadMm+Pv7N/gxEVHDMva6wed0EFWjfL79hTWKes9e6TZeqPNzOojo6WGougE0rdrBezqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwMGjqWLFkChUIBDw+PJ/ZRKBSYO3eu+P7QoUNQKBQ4dOhQvT9/9+7dkn0bUkxMDBQKBU6cONEg+ze0DRs2YPHixY09jAoM+e9dTqFQVPpasGCBwT6DiIjqz6Ch49tvvwUAnD17FkePHjXkrmtk9+7dmDdvnuyfa4yMNXQ0lNGjRyMpKUnyGjduXGMPi4iIHtHcUDs6ceIEUlNTMXz4cOzatQvR0dHw9/c31O4NThAEFBYWwsLCorGHQgbg4OCAgICAxh4GERFVwWBXOqKjowEACxYsQFBQEDZu3Ih79+4Zave4d+8ePvzwQ3Tq1Anm5uawtbWFj48PYmNjAQATJkzA8uXLAUgvt//5559i26RJk7Bq1Sr06NEDSqUSa9asAQBotVoMHDgQVlZWsLS0RFBQEHbt2lXtmDIzM9GnTx+4urri0qVLAAC9Xi+O08zMDG3btsXUqVNRUFAg2Xbz5s3w9/eHtbU1LC0t0blzZ/z973+v9jOXL1+O4OBg2Nvbo0WLFvD09MSiRYvw4MEDsU///v2xa9cuXL16VfK7qErHjh0RGhqKvXv3onfv3rCwsED37t3Fq1ePOnPmDEaOHIlWrVrB3NwcXl5e4u/yUefPn8cLL7wAS0tLtG7dGu+88w7y8vIq/fwDBw5g4MCBUKlUsLS0hFqtxk8//VTt74OIiJ4eBgkd9+/fR2xsLHx9feHh4YG///3vyMvLw+bNmw2xewDA9OnTsXLlSkyePBl79+7FunXr8Morr+DOnTsAgDlz5mD06NEAILnE7uTkJO5j27ZtWLlyJT766CP8+OOP6Nu3LxISEvD8888jNzcX0dHRiI2NhZWVFUaMGIFNmzY9cTxnzpyBv78/lEolkpKS4Orqinv37qFfv35Ys2YNJk+ejD179mDGjBmIiYnBX/7yFwiCII4vLCwMnTt3xsaNG7Fr1y589NFHKCkpqfb38Pvvv2Ps2LFYt24ddu7ciYkTJ+Kzzz7D22+/LfZZsWIF1Go1HB0dJb+L6qSmpuKDDz7AtGnTEB8fj549e2LixIlITEwU+1y4cAFBQUE4e/YslixZgi1btsDNzQ0TJkzAokWLxH43btxAv379cObMGaxYsQLr1q1Dfn4+Jk2aVOFz169fjyFDhkClUmHNmjX4/vvvYWtri6FDh9Y4eGzYsAEWFhZQKpXo06cPVq9eXaPtiIhIRoIBrF27VgAgrFq1ShAEQcjLyxNatmwp9O3bt0JfAEJkZKT4/uDBgwIA4eDBg1V+hoeHhzBq1Kgq+0RERAhPOiQAgrW1tXD37l1Je0BAgGBvby/k5eWJbSUlJYKHh4fg4uIilJWVCYIgCKtXrxYACMePHxf2798vqFQqYfTo0cL9+/fF7ebPny+YmJgIx48fl3zGDz/8IAAQdu/eLQiCIHz++ecCACEnJ6fK46lOaWmp8ODBA2Ht2rVCs2bNJMc2fPhwoUOHDjXeV4cOHQRzc3Ph6tWrYtv9+/cFW1tb4e233xbbXn31VUGpVAppaWmS7YcNGyZYWlqKxzRjxgxBoVAIKSkpkn6DBw+W/HsXFBQItra2wogRIyocW69evQQ/P79qxz527Fjhu+++ExITE4UffvhBGDZsmABAmD17do2Pvyq5ubkCAOHCGoVwfbNJnV8X1igEAEJubq5BxkVExstQdaOp1Q6DXOmIjo6GhYUFXn31VQBAy5Yt8corr+CXX34Rv3aoLz8/P+zZswf//Oc/cejQIdy/f7/W+3j++efRqlUr8X1BQQGOHj2K0aNHo2XLlmJ7s2bNEB4ejmvXruHChQuSfaxZswYhISF444038P3338Pc3Fz82c6dO+Hh4QEvLy+UlJSIr6FDh0pmbPj6+gIAxowZg++//x4ZGRk1Pobk5GT85S9/gZ2dHZo1awZTU1OMGzcOpaWluHjxYq1/J4/y8vJC+/btxffm5ubo2rUrrl69Krb9/PPPGDhwINq1ayfZdsKECbh37554ReXgwYNwd3dHr169JP3Gjh0reX/48GHcvXsX48ePl/zOysrK8MILL+D48eMVvpp63HfffYexY8eib9++ePnll7F7926EhoZiwYIFuHXrVp1+F0REZHj1Dh2XL19GYmIihg8fDkEQkJOTg5ycHPGrjsruCaiLJUuWYMaMGdi2bRsGDBgAW1tbjBo1qlah5tGvWgAgOzsbgiBUaAcAZ2dnABC/vim3ceNGWFhY4I033qhwn8SNGzdw+vRpmJqaSl5WVlYQBAG3b98GAAQHB2Pbtm0oKSnBuHHj4OLiAg8PD/H+lCdJS0tD3759kZGRgaioKPzyyy84fvy4eC9LXYLYo+zs7Cq0KZVKyX7v3LlTo9/XnTt34OjoWKHf4203btwA8HD2yeO/t4ULF0IQBNy9e7fWx/K3v/0NJSUlT80UZyKiZ0G9Z698++23EAQBP/zwA3744YcKP1+zZg0++eQTNGvWrF6f06JFC8ybNw/z5s3DjRs3xKseI0aMwPnz52u0j8dDQqtWrWBiYoLMzMwKfa9fvw4AaN26taT9u+++w5w5c9CvXz/s27cPXl5e4s9at24NCwuLJwatR/c1cuRIjBw5EkVFRThy5Ajmz5+PsWPHomPHjggMDKx0+23btqGgoABbtmxBhw4dxPaUlJQqj9uQ7OzsavT7srOzQ1ZWVoV+j7eV91+6dOkTZ584ODjUepzC/90/Y2LC598RERmLeoWO0tJSrFmzBl26dME333xT4ec7d+7EF198gT179iA0NLQ+HyXh4OCACRMmIDU1FYsXL8a9e/dgaWkJpVIJ4OEZf02mwrZo0QL+/v7YsmULPv/8c3GbsrIyrF+/Hi4uLujatatkG1tbWxw4cAChoaEYMGAA9uzZI/6xDA0Nxaeffgo7Ozt06tSpRseiVCrRr18/2NjY4Mcff0RycvITQ0d5aCo/TuDhH9f//d//rXS/9b3yUZmBAwdi69atuH79unh1AwDWrl0LS0tL8XcxYMAALFq0CKmpqZKvWDZs2CDZn1qtho2NDX777bdKbzKtq3Xr1sHU1BR9+vQx2D6JiKh+6hU69uzZg+vXr2PhwoXo379/hZ97eHhg2bJliI6Ornfo8Pf3R2hoKHr27IlWrVrh3LlzWLduHQIDA2FpaQkA8PT0BAAsXLgQw4YNQ7NmzdCzZ0+YmZk9cb/z58/H4MGDMWDAAHz44YcwMzPDihUrcObMGcTGxlY61dTKygp79+7FSy+9hMGDB2P79u0YMGAApk6diri4OAQHB2PatGno2bMnysrKkJaWhn379uGDDz6Av78/PvroI1y7dg0DBw6Ei4sLcnJyEBUVBVNTU/Tr1++JYx08eDDMzMzw2muv4R//+AcKCwuxcuVKZGdnV+jr6emJLVu2YOXKlejTpw9MTEzg4+NT2197BZGRkdi5cycGDBiAjz76CLa2tvjuu++wa9cuLFq0CNbW1gCAqVOn4ttvv8Xw4cPxySefwMHBAd99912Fq1ItW7bE0qVLMX78eNy9exejR4+Gvb09bt26hdTUVNy6dQsrV6584ng+++wz/Pbbb+Lv8ubNm4iOjsa+ffswd+7cCleqiIio8dQrdERHR8PMzAyvv/56pT9v3bo1XnzxRfzwww+4ceNGnS6Tl3v++eexfft2fPnll7h37x7atm2LcePG4V//+pfYZ+zYsdDpdFixYgX+/e9/QxAEXLlyBR07dnzifvv164eff/4ZkZGRmDBhAsrKytCrVy9s3769yqBkYWGB+Ph4jB07FiEhIYiLi0NISAh++eUXLFiwAF9//TWuXLkCCwsLtG/fHoMGDRLH4e/vjxMnTmDGjBm4desWbGxs4OPjg59//hnu7u5P/Mzu3bsjLi4Os2fPxksvvQQ7OzuMHTsW06dPx7BhwyR9p0yZgrNnz2LWrFnIzc2FIAjiVw710a1bNxw+fBizZs1CREQE7t+/jx49emD16tWYMGGC2M/R0REJCQmYMmUK3n33XVhaWuLFF1/EsmXLMHLkSMk+//a3v6F9+/ZYtGgR3n77beTl5cHe3h5eXl6SfT7pd7J9+3bs2rUL2dnZsLCwgJeXF2JjY8Ubm4mIyDgoBEP8JSJqwvR6PaytrXFhjQJWllU/ZK0qefcEdBsvIDc3FyqVyoAjJCJjY6i6ATSt2sG77IiIiEgWDB1EREQkC4YOIqq3o0eP4sUXX0T79u2hVCrh4OCAwMBAfPDBB5J+K1asQExMTIOMYcKECZKH/DWmX375BUqlUvJgPa1WizfeeAN9+vSBUqmUrA1VVwcOHMDgwYPh7OwMpVIJe3t7PP/889i9e7ek34MHD9ClS5cGWXn6008/xbZt2wy+3/qaO3dutWtO1cahQ4cka1k9+jpy5IjBPqepY+ggonrZtWsXgoKCoNfrsWjRIuzbtw9RUVFQq9UV1i9qyNBhLARBwNSpU/Hmm29Knqfz008/4cCBA2jfvj2CgoIM8ll37tyBu7s7vvzyS+zbtw9fffUVTE1NMXz4cKxfv17sZ2pqio8++gj//ve/KzzwsL6MNXQ0lE8//VSyplVSUhI8PDwae1hPDYMtbU9Ez6ZFixahU6dO+PHHH9G8+f8vKa+++qpkEcDaevDgARQKhWSfT4O9e/fi1KlTFZ5JM2fOHERGRgIAPv/8c3FZhPoICwtDWFiYpC00NBSdOnXC119/jb/97W9i+2uvvYbp06fjq6++wqxZs+r92c8qV1fXJz7IkKrHKx1EVC937txB69atKw0Hjz4RtmPHjjh79iwSEhLEy9Ll08jLL12vW7cOH3zwAdq2bQulUonLly8DePjk4169esHc3By2trZ48cUXce7cuWrHptPp0Lp1a4SGhopr+Fy6dAljx46Fvb09lEolevToIS4lUK6srAyffPIJunXrBgsLC9jY2KBnz56Iioqq9jNXrlwJX19fdOvW7Ym/i4ZkamoKGxubCv8eZmZmCAsLw9dff13t9PnCwkJ88MEH8PLygrW1NWxtbREYGIj4+HhJP4VCgYKCAqxZs0b8N63smU3l/vzzTygUCnz++ef473//i06dOqFly5YIDAys9CuK7du3i89isrKywuDBgytdMXvXrl3w8vKCUqlEp06d8Pnnn1f6+YIgYMWKFfDy8oKFhQVatWqF0aNH448//qjy90GGw9BBRPUSGBiIo0ePYvLkyTh69CgePHhQab+tW7eic+fO8Pb2Fi9Lb926VdJn5syZSEtLw6pVq7Bjxw7Y29tj/vz5mDhxItzd3bFlyxZERUXh9OnTCAwMrHLtpe+//x4DBw7EmDFjEB8fjxYtWuC3336Dr68vzpw5gy+++AI7d+7E8OHDMXnyZMybN0/cdtGiRZg7dy5ee+017Nq1C5s2bcLEiRORk5NT5e+iuLgYBw4cwIABA2r+CzSAsrIylJSU4Pr164iMjMTFixcr3E8DAP3798fVq1dx5syZKvdXVFSEu3fv4sMPP8S2bdsQGxsLjUaDl156CWvXrhX7JSUlwcLCAiEhIeK/6YoVK6od7/Lly7F//34sXrwY3333HQoKChASEoLc3Fyxz4YNGzBy5EioVCrExsYiOjoa2dnZ6N+/P7Rardjvp59+wsiRI2FlZYWNGzfis88+w/fff4/Vq1dX+Ny3334bU6dOxaBBg7Bt2zasWLECZ8+eRVBQkLgOVHUiIiLQvHlzqFQqDB06VDIWqoFGWNmW6KnSWEvbf/rpp4KPj4/QsmVLoU2bNsLIkSOF8+fPV7lNXFycMGjQIKF169aClZWVEBAQIOzdu1fSZ/Xq1QKACq/79+/X6fdz+/ZtQaPRiPsxNTUVgoKChPnz5wt5eXmSvu7u7kK/fv0q7OPgwYMCACE4OFjSnp2dLVhYWAghISGS9rS0NEGpVApjx44V28aPHy+0aNFCEARBWLBggdCsWTNh4cKFku2GDh0quLi4VPg3mDRpkmBubi7cvXtXEARBCA0NFby8vGr3ixAE4ejRowIAYePGjVX2++yzzwQAwpUrV2r9GZUZOnSo+PtXqVTCli1bKu136dIlAYCwcuXKWu2/pKREePDggTBx4kTB29tb8rMWLVoI48ePr9F+rly5IgAQPD09hZKSErH92LFjAgAhNjZWEARBKC0tFZydnQVPT0+htLRU7JeXlyfY29sLQUFBYpu/v7/g7Ows+f+vXq8XbG1thUf/xCUlJQkAhC+++EIypvT0dMHCwkL4xz/+UeXYT506JUyZMkXYunWrkJiYKHz77bdCjx49hGbNmlX4b0wQGm9pe2OvG7zSQWSkEhISEBERgSNHjmD//v0oKSnBkCFDxK8JKpOYmIjBgwdj9+7dOHnyJAYMGIARI0YgOTlZ0k+lUiEzM1PyMjc3r9M47ezsxBWPFyxYgJEjR+LixYuYOXMmPD09xdWVa+Lll1+WvE9KSsL9+/crPJm2Xbt2eP755/HTTz9J2gVBwNtvv43IyEhs2LAB//jHP8SfFRYW4qeffsKLL74IS0tLlJSUiK+QkBAUFhaKl/j9/PyQmpqK9957Dz/++CP0en2Nxl++8KG9vX2Nj9kQli5dimPHjiE+Ph5Dhw5FWFhYpatWl48rIyOj2n1u3rwZarUaLVu2RPPmzWFqaoro6Ogafa1VneHDh0sWAe3ZsycAiLN9Lly4gOvXryM8PFzytVTLli3x8ssv48iRI7h37x4KCgpw/PhxvPTSS5L//1pZWWHEiBGSz9y5cycUCoW4AnX5y9HREb169ar2Hhtvb28sXrwYo0aNQt++ffH666/j8OHDcHJykvz/rLEZe914uu7QImoCHv8DplQqJYv4ldu7d6/k/erVq2Fvb4+TJ08iODi40n0/PiXy008/RXx8PHbs2AFvb2+xXaFQwNHRsY5HUDkfHx9xfZ8HDx5gxowZ+PLLL7Fo0aIa31Dq5OQkeV8+0+LxdgBwdnbG/v37JW3FxcXYtGkT3N3dKywNcOfOHZSUlGDp0qVYunRppZ9fHpBmzpyJFi1aYP369Vi1ahWaNWuG4OBgLFy4sMo1jMoXWaxrgKsrV1dX8X//5S9/wbBhwxAREYGwsDDJH+3ycVW3GOSWLVswZswYvPLKK/if//kfODo6onnz5li5cuUTV9GuDTs7O8n7RxfrBKr/dy8rK0N2djYEQUBZWVml/19+vO3GjRsQBOGJy3F07ty51sdhY2OD0NBQrFq1qsYLjdZHTWqHsdcNhg6iGpr/oC3MHtT94mDxgzIA19CuXTtJe2RkJObOnVvt9uXfd9va2tb4M8vKypCXl1dhm/z8fHTo0AGlpaXw8vLCxx9/LCku9WVqaorIyEh8+eWX1d4/8KjHn6tQ/scpMzOzQt/r169XWNBPqVTi4MGDGDp0KAYNGoS9e/eiVatWAIBWrVqhWbNmCA8PR0RERKWfX746dPPmzTF9+nRMnz4dOTk5OHDgAGbNmoWhQ4ciPT1dXGTyceXjuXv3bo2PuSH4+flh7969uHXrluSPbPm4qlsIcf369ejUqRM2bdok+TcpKipqmAE/prp/dxMTE7Rq1QqCIEChUCArK6tCv8fbWrduDYVCIT5D5XGVtdWE8H835T7pmSD1rRtA/WqHsdUNhg4imaWnp0vWT6hJsRMEAdOnT4dGo6nVMwG++OILFBQUYMyYMWJb9+7dERMTA09PT+j1evGZGqmpqZIz5prKzMys9Iy0/DK8s7Oz2KZUKqs9y35UYGAgLCwssH79erzyyiti+7Vr1/Dzzz9j9OjRFbbx9vZGQkICBg0ahP79+2P//v2wt7eHpaUlBgwYgOTk5GpXn36UjY0NRo8ejYyMDEydOhV//vkn3NzcKu3bo0cPAMDvv/9e42M0NEEQkJCQABsbmwpXFMpnaTxp/OUUCgXMzMwkf0izsrIqzF4Bav9vWhPdunVD27ZtsWHDBnz44YfiOAoKChAXFydZXdzPzw9btmzBZ599Jl7JycvLw44dOyT7DA0NxYIFC5CRkSH576E+srOzsXPnTnh5eclydau2tcMY6wZDB5HMVCpVrRdtmjRpEk6fPl2rO+VjY2Mxd+5cxMfHS+4xCAgIkDxnQK1Wo3fv3li6dCmWLFlSq3EBwNChQ+Hi4oIRI0age/fuKCsrQ0pKCr744gu0bNkSU6ZMEft6enpi48aN2LRpEzp37gxzc3N4eno+cd82NjaYM2cOZs2ahXHjxuG1117DnTt3MG/ePJibm4vPvXhcjx498Msvv2DQoEEIDg7GgQMH4OLigqioKGg0GvTt2xfvvvsuOnbsiLy8PFy+fBk7duzAzz//DAAYMWIEPDw84OPjgzZt2uDq1atYvHgxOnToUGWBdXFxQefOnXHkyBFMnjxZ8rNbt24hISEBAPDrr78CAPbs2YM2bdqgTZs26Nevn9i3f//+SEhIqHZq68iRI9GrVy94eXnBzs4O169fR0xMDBISErB8+fIK02aPHDkiflVUldDQUGzZsgXvvfceRo8ejfT0dHz88cdwcnKqMGPI09MThw4dwo4dO+Dk5AQrK6sK04Vry8TEBIsWLcJf//pXhIaG4u2330ZRURE+++wz5OTkYMGCBWLfjz/+GC+88AIGDx6MDz74AKWlpVi4cCFatGghueKkVqvx1ltv4fXXX8eJEycQHByMFi1aIDMzE1qtFp6ennj33XefOKaxY8eiffv28PHxQevWrXHp0iV88cUXuHHjhmwPvKtt7TDGusHQQWTk3n//fWzfvh2JiYlwcXGp0TblUzw3b96MQYMGVdnXxMQEvr6+VU4/rcrs2bMRHx+PL7/8EpmZmSgqKoKTkxMGDRqEmTNnimf/ADBv3jxkZmbizTffRF5eHjp06FDto8BnzpwJe3t7LFmyBJs2bYKFhQX69++PTz/9tMoA0LlzZzF49O3bFz/99BPc3Nxw6tQpfPzxx5g9ezZu3rwJGxsbuLq6IiQkRNx2wIABiIuLwzfffAO9Xg9HR0cMHjwYc+bMgampaZXj/etf/4ply5ahqKhIciZ69uxZydUaAHjvvfcAAP369ZPcyJifn1+j787VajV++OEHLFu2DHq9HjY2NvDx8RGnAj9u27ZtCAkJgY2NTZX7ff3113Hz5k2sWrUK3377LTp37ox//vOfuHbtmmRqMQBERUUhIiICr776Ku7du1fhWOpq7NixaNGiBebPn4+wsDA0a9YMAQEBOHjwoOSJroMHD8a2bdswe/ZshIWFwdHREe+99x7u379fYaxfffUVAgIC8NVXX2HFihUoKyuDs7Mz1Go1/Pz8qhxPz549sWnTJqxatQr5+fmwtbWFRqPBunXr4OvrW+/jNTRjrRtc2p6oGuVLVE/4xgVmlvW4p+NeGWLeuFbj5akFQcD777+PrVu34tChQzW+hBkbG4u///3viI2NxahRo2r0OX5+fvD09DTITYLPuuvXr6NTp05Yu3ZthaeF1kT5d+mLFy9+4r0ndfH777/D1dUVP/74IwYPHmyw/VLlDFU3gNrVDmOvG7zSQWSkIiIisGHDBsTHx8PKykq8Mc7a2lq8S37mzJnIyMgQH9gUGxuLcePGISoqCgEBAeI2FhYWsLa2BvDwakNAQABcXV2h1+uxZMkSpKSkVHgqJ9WNs7Mzpk6div/85z945ZVXav0k0sTERLRt2xZvvvmmQcf1ySefYODAgQwcTZyx1w0+p4PISK1cuRK5ubno378/nJycxNeji6hlZmYiLS1NfP/VV1+hpKQEERERkm0eva8iJycHb731Fnr06IEhQ4YgIyMDiYmJ1V5eppqbPXs2Xn755Ro9D+Nxw4cPx59//lnjG11roqSkBF26dGGwfAYYe93g1ytE1Wisr1eI6OnVWF+vGDte6SAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHNTkPHjxo7CEQ0VNGEATWDhnw4WDUJJSVleHixYvQ6XT49ddf8Z///ActWrRo7GERkZHLz8/H0aNHodVq4erqirFjxzb2kJo0hg56quXk5ODw4cPQ6XS4ffu22H769GkEBgY24siIyFiVlZXhwoUL0Gq1SElJQUlJCYCHAaR8nRdqGAwd9NQpLS3Fr7/+Cq1WizNnzogrcZqbm8PPzw8ajQbt27dv5FESkbHJzs4WT1Lu3Lkjtrdr1w4ajQZ+fn4MHA2MoYOeGjdu3MDhw4dx+PBh6PV6sf25556DRqNB7969Jat6EhGVlpaKy7ufPXtWPEmxsLDgSUojYOggo1ZcXIxTp05Bp9Ph4sWLYruVlRUCAwOhVqtrtAQ4ET1bsrKyoNPpkJSUhLy8PLG9a9euUKvV6N27t0HXt6GaYeggo5SWlgatVotjx47h/v37AACFQgF3d3doNBr07NmTl0GJSKKoqAinTp2CVqvF5cuXxXaVSiWepDg4ODTiCImhgwwiPe8uikpL8JyNfZ33ce/ePRw7dgxarRbp6eliu52dHdRqNYKCgtCqVStDDJeIjEBJWSmSsv6Axuk5KBSKOu1DEARcvXoVOp0Ox44dQ2FhIYCHJykeHh7QaDTw9PTkSYqRYOigeltzLgn/OhKPYR3c8b/Ph9dqW0EQcOnSJeh0Opw8eVKcJ9+8eXN4eXlBo9GgW7duMDHhI2WImpLSsjIM2PolruhvI374u+hj36FW2xcUFIgnKdeuXRPbW7duDbVajcDAQJ6kGCGGDqo3f8dOAID9aedwpzAfduYtq90mNzcXSUlJ0Ol0uHnzptju7OwMjUYDf39/tGxZ/X6I6OnUzMQEPvbtcUV/GxsvnahR6CgrK8OlS5eg1Wpx6tQpcapr8+bN0bt3b6jVanTt2pUnKUaMoYPqrXsrR/Rq7YLU29ew5fdkvOnet9J+paWlOHv2LLRaLX799VeUlZUBAJRKJXx9faHRaNCxY8c6X2YloqdLmKsPNl8+hR1XTmOe3whYmlZ+Y+eTnsfj4uICtVoNf39/PgzwKcHQQQYR5uqD1NvXsOnSSbzhppEEh1u3bol3kefk5IjtXbp0gVqtRp8+fWBubt4IoyaixuTv0AkdrOxwNe8Odl/9FaOf6yP+rPx5POVPGX78eTxqtRodOnTgScpThqGDDGJkp16Yd2wnzmdn4fSdDLhZOyA5ORlarRYXLlwQ+7Vs2RIBAQFQq9VwdnZuxBETUWNTKBQIc+2DRaf2YdOlkxj9XB8+j6eJY+ggg7BWWuCFDu6I/yMVn+yOhUvyddy7dw/Aw8LSo0cPaDQa9OrVC82b8/92RPTQ6C698dmp/UjK+gNzvlyEm+d/F39mZWWFgIAAaDQaPo+niWD1p3q7f/8+jh07hrLjl6C0AS5lZ8L6/j20sbVFUFAQ1Go1bG1tG3uYRGRkyp/HY68vQamlGY7kXEOX/3sej1qtRs+ePXmS0sTwX5PqRBAEXL58GVqtVpzqWgbAxMsat1uZwWvs83hPE8K7yIlIorLn8TjbmiK5azOUdrbBhsmT0caudSOPkhoKQwfVSm5uLo4cOQKdTocbN26I7U5OTlCr1ehoVYSV57Q4fP8GJjFwEBEenqRcvHgROp0Op06dqvA8Ht/AAIxNjUN2cSF+K7yLfmDoaKoYOqha5VNddTodTp8+LZnq6uPjA41Gg06dOkGhUKBr3h2sPKfFL9cvIyM/B21b2jTu4Imo0eTk5CApKQmHDx+u9nk8L+b9jjXnj+D7SyfRr23XxhoyNTCGDnqiJ0117dy5M9RqNXx8fCpMde1gZYdAx85IyvoDP1w+iSleA2UeNRE1ptLSUpw5cwZarRZnzpwRT1LMzc3h6+v78IpoJc/jCXP1wZrzR7A37Sxyiu7BRmnZGMOnBsbQQRLFxcVITk6GTqer81TXMNc+SMr6A99fPon3ew2AiYJfsxA1dTdu3BBPUh6d6tqlSxdoNBr06dOnyqmunnZt0b2VI85nZyH+j1SM7xEox7BJZgwdBABIT08XV3Wt71TXkA6emH1kO67m3cXRG38i0LFzQw6diBpJcXGxuKrrpUuXxPa6THUtf2bHvGO78P3lkwwdTRRDxzPs3r17OH78OLRaLdLS0sR223pOdbU0NcOITj0Re/E4vr90gqGDqIkpn+p69OhRyaqu9Z3q+lIXb/zn+B6k3r6G89lZ6N6Kz+Zoahg6njFPWtW1WbNm4qqu3bt3r/dU11ddfRB78Th2/vkrPg4YiZamfIIg0dOsfFVXnU4nTnUFADs7O6jVagQFBdV7VVc785YY1K4H9qadxfeXTuAjv9D6DpuMDEPHM6KqVV3VajUCAgIMuqpr7zbt0cW6DX7PvYUdV07jta6+Bts3EcmjqlVdvb29oVar0a1bN4M+jyfMtQ/2pp1F3O/JmOkzDKYmzQy2b2p8DB1NWPld5OULJsm5qqtCoUB4N3+cuHkVXW3sDb5/Imo42dnZ4knKo6u6tm3bVpzq2lCrug5w6QYf+w7o19YVxaUlDB1NDENHE3Tz5k3xLvLc3FyxXe5VXd9w1+ANd02Dfw4R1V/5qq7lU10ba1XX5ibNsG34uw36GdR4GDqaiPK7yHU6HS5evCi2l99Frlar4eTk1IgjJCJjdOPGDWi1Whw5coSrulKDY+h4ypXfRX7s2DHcv38fgGHuIieipqu4uBgnT56EVqvF5cuXxXYrKysEBgZCrVZzVVdqEPxr9BSqbMEk4P/fRR4YGMhVXYlIQhAEXL16FTqdDseOHZNMdfXw8IBGo4GnpyeaNeM9FNRwGDqeEuULJmm1WiQnJ1dYMEmtVhtkqisRNS0FBQU4evQodDodrl27Jra3bt1aPEmp71RXopriXygjl5OTgz179mDOnDn473//i2PHjuHBgwdwdnbGmDFjsHDhQrz55ptwc3Nj4Ghi5s+fD19fX1hZWcHe3h6jRo2SPJr+SRISEsSbhTt37oxVq1ZV6BMXFwc3NzcolUq4ublh69atDXEI1EjKyspw7tw5fPPNN/jHP/6BTZs24dq1a2jevDn8/Pwwbdo0fPzxxwgJCWHgaGKMvW7wSocRKr+LXKfT1WrBJGpaEhISEBERAV9fX5SUlOBf//oXhgwZgt9+++2J0xWvXLmCkJAQvPnmm1i/fj10Oh3ee+89tGnTBi+//DIAICkpCWFhYfj444/x4osvYuvWrRgzZgy0Wi38/f3lPEQysOzsbBw+fBiHDx+WTHV1cXGBRqOBn59fg011JeNg7HVDIZTPi6JGV98Fk6hh6PV6WFtbY8I3LjCzrPvVpOJ7ZYh54xpyc3OhUqlqvf2tW7dgb2+PhIQEBAcHV9pnxowZ2L59O86dOye2vfPOO0hNTUVSUhIAICwsDHq9Hnv27BH7vPDCC2jVqhViY2NrPS5qXKWlpTh9+jS0Wi3Onj1bYaqrRqNB+/bteZIiM0PVDaB+tcPY6gavdDQyQy6YRE+HRwMl8PBhbTUJk+XPXKnqJuGkpCQMGTJE0jZ06FBER0fjwYMHMDU1RVJSEqZNm1ahz+LFi2t4BGQMsrKyxJOUvLw8sd3V1VV8Ho+ZmVkjjpAMrS61w9jqBkNHIxAEAWlpadDpdAZfMIkazqxFb8GqWd0fqpZXWogYfIR27dpJ2iMjIzF37twqtxUEAdOnT4dGo4GHh8cT+2VlZcHBwUHS5uDggJKSEty+fRtOTk5P7JOVlVW7AyLZFRUV4eTJk9DpdJKpriqVSpzq+vi/LTWu+tYNoO61wxjrBv+qyUiOBZPI+KWnp0sukdbkKsekSZPES+jVefwyevnl9kfbK+vDy+/GSRAE/Pnnn9DpdDh+/LjkJMXT0xNqtZpTXZ8Rta0dxlg3GDoaWGMsmETGTaVS1ep72ffffx/bt29HYmIiXFxcquzr6OhY4czj5s2baN68Oezs7KrswzNk45Kfny8+jycjI0Nsb9OmjTjV1cbGpvEGSLKrTe0w1rrB0NFAqlswyc/Pz6CrulLTIwgC3n//fWzduhWHDh1Cp06dqt0mMDAQO3bskLTt27cPPj4+MDU1Ffvs379f8v3svn37EBQUZNgDoForKyvDhQsXoNPpkJycLDlJ6d27NzQaDVxdXXmSQk9k7HWDocOAjGXBJGoaIiIisGHDBsTHx8PKyko8y7C2toaFhQUAYObMmcjIyMDatWsBPLzjfNmyZZg+fTrefPNNJCUlITo6WnJ3+ZQpUxAcHIyFCxdi5MiRiI+Px4EDB2p0CZYaxt27d8WTlDt37ojt7dq1g1qt5lRXqjFjrxsMHQbABZOoIaxcuRIA0L9/f0n76tWrMWHCBABAZmYm0tLSxJ916tQJu3fvxrRp07B8+XI4OztjyZIl4lx7AAgKCsLGjRsxe/ZszJkzB126dMGmTZv4jA6ZlZSU4PTp09DpdJKprhYWFpKprkS1Yex1g8/pqKOioiJxqisXTGrayufbX+z673rPXul68aM6P6eDmobMzEzodDocOXJEMtW1a9euUKvV6N27N6e6NgGGqhtA06odvNJRC9UtmFQ+1ZV3kRPRowoLC8Wprr///rvYrlKpEBQUhKCgIN7IS88Eho4a4IJJRFRb5VNdtVotjh8/jqKiIgCAiYmJONXVw8ODJyn0TGHoeILq7iJXq9Xo2rUr7yInIon8/HwcOXIEOp0O169fF9vt7e3FkxRra+tGHCFR42HoeAwXTCKi2iorK8P58+eh1WqRmpoqnqSYmppKprpy5ho96xg68HCqa2pqaoW7yLlgEhFV5e7du+L6J49OdW3fvr041dXS0rIRR0hkXJ7p0MEFk4iotkpKSpCamgqtVotz585Jprr6+/tDrVZzqivREzxzoYMLJhFRXVy/fl2c6pqfny+2d+3aFRqNBt7e3jxJIarGMxE6qlowycPDAxqNhgsmEVEFhYWFOHHiBHQ6Hf744w+x3draWjxJsbe3b8QREj1dmnToyM/PF6e6Pr5gUlBQEKe6ElEFgiDgypUr0Gq1OHHiBKe6EhlQkwsd5VNdtVotUlJSuGASEdVI+VRXrVaLzMxMsZ1TXYkMp8mEDi6YRES1VVZWhnPnzolTXUtLSwE8nOrap08fqNVqTnUlMqCnOnRwwSQiqos7d+7g8OHD0Ol0yM7OFtvbt28vPo+nfEVOIjKcpzJ0cMEkIqqtBw8e4PTp0xWmulpaWoonKe3atWvkURI1bU9N6OCCSURUFxkZGeJJSkFBgdjerVs3aDQaeHl58SSFSCZGHTq4YBIR1UX5VFetVosrV66I7TY2NuJU1zZt2jTiCImeTUYZOp60YFKbNm2g0Wh4FzkRVSAIAv744w/odLoKU1179uwJjUYDNzc3nqQQNSKjCR1cMImI6iIvL088SXl0qquDgwPUajUCAgJ4kkJkJBo9dHDBJCKqrbKyMvz222/Q6XQVprr6+PhArVbjueee40kKkZFplNDBBZOIqC5u376Nw4cP4/Dhw5Kprh06dIBGo4Gvry+nuhIZMVlDBxdMIqLaevDgAVJSUqDT6XD+/HnJVNfykxROdSV6OjR46HjSXeRcMImIqpKRkQGtVoujR49Kprp2794darUa3t7eMDU1bcQRElFtNUjo4IJJRFQX9+/fF09S/vzzT7HdxsZGfB4Pp7oSPb0MGjq4YBIR1ZYgCPj999/Fqa7FxcUAHp6k9OrVC2q1Gu7u7lykkagJMEjoKCwsxNq1a5GSksIFk4ioxlJTU7FlyxZkZWWJbQ4ODtBoNAgICIBKpWrE0RGRoRkkdCiVSly/fh2lpaXigkm+vr6c6kpEVTIxMUFWVhbMzMzQp08faDQadOnShScpRE2UQUKHQqHAq6++ihYtWvAuciKqMXd3d4wbNw69e/fmVFeiZ4DB7uno3r27oXZFRM8IExMTqNXqxh4GEcmEd2YRERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBmpxMREjBgxAs7OzlAoFNi2bVuV/SdMmACFQlHh5e7uLvaJiYmptE9hYWEDHw0RycWYawdDB5GRKigoQK9evbBs2bIa9Y+KikJmZqb4Sk9Ph62tLV555RVJP5VKJemXmZkJc3PzhjgEImoExlw7DLq0PREZzrBhwzBs2LAa97e2toa1tbX4ftu2bcjOzsbrr78u6adQKODo6GiwcRKRcTHm2sErHUQy0+v1kldRUVGDfE50dDQGDRqEDh06SNrz8/PRoUMHuLi4IDQ0FMnJyQ3y+URkWE2hdvBKB1ENLRvYDUqlZZ23Lyq6B1xEhZWYIyMjMXfu3HqOTiozMxN79uzBhg0bJO3du3dHTEwMPD09odfrERUVBbVajdTUVLi6uhp0DERU/7oBNK3awdBBJLP09HSoVCrxvVKpNPhnxMTEwMbGBqNGjZK0BwQEICAgQHyvVqvRu3dvLF26FEuWLDH4OIjIcJpC7WDoIJKZSqWSFA5DEwQB3377LcLDw2FmZlZlXxMTE/j6+uLSpUsNNh4iMoymUDt4TwdRE5OQkIDLly9j4sSJ1fYVBAEpKSlwcnKSYWREZMzkqB280kFkpPLz83H58mXx/ZUrV5CSkgJbW1u0b98eM2fOREZGBtauXSvZLjo6Gv7+/vDw8Kiwz3nz5iEgIACurq7Q6/VYsmQJUlJSsHz58gY/HiKShzHXDoYOIiN14sQJDBgwQHw/ffp0AMD48eMRExODzMxMpKWlSbbJzc1FXFwcoqKiKt1nTk4O3nrrLWRlZcHa2hre3t5ITEyEn59fwx0IEcnKmGuHQhAEoZbHQ/RM0ev1sLa2xuR3N9V79sqSlWHIzc1t0O9liajxGapuAE2rdvCeDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFkpBITEzFixAg4OztDoVBg27ZtVfY/dOgQFApFhdf58+cl/eLi4uDm5galUgk3Nzds3bq1AY+CiORmzLWDoYPISBUUFKBXr15YtmxZrba7cOECMjMzxZerq6v4s6SkJISFhSE8PBypqakIDw/HmDFjcPToUUMPn4gaiTHXjua16k1Eshk2bBiGDRtW6+3s7e1hY2NT6c8WL16MwYMHY+bMmQCAmTNnIiEhAYsXL0ZsbGx9hktERsKYawevdBDJTK/XS15FRUUG3b+3tzecnJwwcOBAHDx4UPKzpKQkDBkyRNI2dOhQHD582KBjICLDawq1g1c6iGpofM6raGmmqPP2+cUClgBo166dpD0yMhJz586t3+AAODk54euvv0afPn1QVFSEdevWYeDAgTh06BCCg4MBAFlZWXBwcJBs5+DggKysrHp/PhFVVN+6ATSt2sHQQSSz9PR0qFQq8b1SqTTIfrt164Zu3bqJ7wMDA5Geno7PP/9cLBwAoFBIC6AgCBXaiMj4NIXawa9XiGSmUqkkL0MVjsoEBATg0qVL4ntHR8cKZyY3b96scAZDRManKdQOhg6iJiw5ORlOTk7i+8DAQOzfv1/SZ9++fQgKCpJ7aERkxBqqdvDrFSIjlZ+fj8uXL4vvr1y5gpSUFNja2qJ9+/aYOXMmMjIysHbtWgAP7y7v2LEj3N3dUVxcjPXr1yMuLg5xcXHiPqZMmYLg4GAsXLgQI0eORHx8PA4cOACtViv78RFRwzDm2sHQQWSkTpw4gQEDBojvp0+fDgAYP348YmJikJmZibS0NPHnxcXF+PDDD5GRkQELCwu4u7tj165dCAkJEfsEBQVh48aNmD17NubMmYMuXbpg06ZN8Pf3l+/AiKhBGXPtUAiCINTz+IiaNL1eD2tra5x8TVHv2St9YgXk5uZKbgYjoqbHUHUDaFq1g/d0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIjlZiYiBEjRsDZ2RkKhQLbtm2rsv+WLVswePBgtGnTBiqVCoGBgfjxxx8lfWJiYqBQKCq8CgsLG/BIiEhOxlw7GDqIjFRBQQF69eqFZcuW1ah/YmIiBg8ejN27d+PkyZMYMGAARowYgeTkZEk/lUqFzMxMycvc3LwhDoGIGoEx147mtepNRLIZNmwYhg0bVuP+ixcvlrz/9NNPER8fjx07dsDb21tsVygUcHR0NNQwicjIGHPt4JUOIpnp9XrJq6ioqEE+p6ysDHl5ebC1tZW05+fno0OHDnBxcUFoaGiFsxkiMk5NoXbwSgdRDYVqpsDEQlnn7cvuFwGxi9GuXTtJe2RkJObOnVvP0VX0xRdfoKCgAGPGjBHbunfvjpiYGHh6ekKv1yMqKgpqtRqpqalwdXU1+BiInnX1rRtA06odDB1EMktPT4dKpRLfK5X1K0iViY2Nxdy5cxEfHw97e3uxPSAgAAEBAeJ7tVqN3r17Y+nSpViyZInBx0FEhtMUagdDB5HMVCqVpHAY2qZNmzBx4kRs3rwZgwYNqrKviYkJfH19cenSpQYbDxEZRlOoHbyng6gJiY2NxYQJE7BhwwYMHz682v6CICAlJQVOTk4yjI6IjJVctYNXOoiMVH5+Pi5fviy+v3LlClJSUmBra4v27dtj5syZyMjIwNq1awE8LBrjxo1DVFQUAgICkJWVBQCwsLCAtbU1AGDevHkICAiAq6sr9Ho9lixZgpSUFCxfvlz+AySiBmHMtYNXOoiM1IkTJ+Dt7S1OWZs+fTq8vb3x0UcfAQAyMzORlpYm9v/qq69QUlKCiIgIODk5ia8pU6aIfXJycvDWW2+hR48eGDJkCDIyMpCYmAg/Pz95D46IGowx1w6FIAiCAY6RqMnS6/WwtraG0/Kp9Z69khmxGLm5uQ36vSwRNT5D1Q2gadUOXukgIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIjlZiYiBEjRsDZ2RkKhQLbtm2rdpuEhAT06dMH5ubm6Ny5M1atWlWhT1xcHNzc3KBUKuHm5oatW7c2wOiJqLEYc+1g6CAyUgUFBejVqxeWLVtWo/5XrlxBSEgI+vbti+TkZMyaNQuTJ09GXFyc2CcpKQlhYWEIDw9HamoqwsPDMWbMGBw9erShDoOIZGbMtUMhCIJQqy2InjF6vR7W1tZwWj4VJhbKOu+n7H4RMiMWIz09HSqVSmxXKpVQKqver0KhwNatWzFq1Kgn9pkxYwa2b9+Oc+fOiW3vvPMOUlNTkZSUBAAICwuDXq/Hnj17xD4vvPACWrVqhdjY2DoeGRE9zlB1A2hataN5jXsSPeOO/eUDyX/wtaXX69EuYjHatWsnaY+MjMTcuXPrObqHZyJDhgyRtA0dOhTR0dF48OABTE1NkZSUhGnTplXos3jx4np/PhFVVN+6ATSt2sHQQVQNMzMzODo6VvgPvi4cHR2RmpoKc3Nzsa26M5WaysrKgoODg6TNwcEBJSUluH37NpycnJ7YJysryyBjIKKHDFk3gKZTOxg6iKphbm6OK1euoLi4uN77MjMzkxQNQ1MoFJL35d+ePtpeWZ/H24iofgxZN4CmUzsYOohqwNzcvEH/gzcER0fHCmcdN2/eRPPmzWFnZ1dln8fPYIio/p6GugHIWzs4e4WoiQgMDMT+/fslbfv27YOPjw9MTU2r7BMUFCTbOInIuMhaOwQiMkp5eXlCcnKykJycLAAQ/vvf/wrJycnC1atXBUEQhH/+859CeHi42P+PP/4QLC0thWnTpgm//fabEB0dLZiamgo//PCD2Een0wnNmjUTFixYIJw7d05YsGCB0Lx5c+HIkSOyHx8RNQxjrh0MHURG6uDBgwKACq/x48cLgiAI48ePF/r16yfZ5tChQ4K3t7dgZmYmdOzYUVi5cmWF/W7evFno1q2bYGpqKnTv3l2Ii4uT4WiISC7GXDv4nA4iIiKSBe/pICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBb/D3nOTJ7cgR3YAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [[90.46915502723192, 89.57504791798526], [89.58581817377714, 90.36997888100568]]\n", - "(1, 3) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 6\n", - "Adjacent strokes (list): [3, 3, 4, 4]\n", - "Adjacent strokes (uniques): {3, 4}\n", - "Checking edge: (3, 4)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [[89.83847705650136, 91.21166198882482], [89.75197989966416, 89.19788105500966]]\n", - "(3, 4) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 7\n", - "Adjacent strokes (list): [3]\n", - "Adjacent strokes (uniques): {3}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 8\n", - "Adjacent strokes (list): [4]\n", - "Adjacent strokes (uniques): {4}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 9\n", - "Adjacent strokes (list): [4, 7, 4]\n", - "Adjacent strokes (uniques): {4, 7}\n", - "Checking edge: (4, 7)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [91.62276842306488]\n", - "(4, 7) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 10\n", - "Adjacent strokes (list): [4, 0, 4, 0]\n", - "Adjacent strokes (uniques): {0, 4}\n", - "Checking edge: (0, 4)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [[90.29328808503493, 90.43376966492825], [89.84379058832397, 89.42915166171285]]\n", - "(0, 4) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 11\n", - "Adjacent strokes (list): [4, 5, 4]\n", - "Adjacent strokes (uniques): {4, 5}\n", - "Checking edge: (4, 5)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [91.18142429639235]\n", - "(4, 5) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 12\n", - "Adjacent strokes (list): [5]\n", - "Adjacent strokes (uniques): {5}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 13\n", - "Adjacent strokes (list): [2, 6, 2, 6]\n", - "Adjacent strokes (uniques): {2, 6}\n", - "Checking edge: (2, 6)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [[132.83556629096833, 48.92275878691167], [59.79419820769666, 118.44747671442332]]\n", - "(2, 6) already in graph, angles = [[94.78903631548253, 84.23886881283048], [81.14186114900058, 99.83023372268642]]\n", - "(2, 6) already in graph, angles updated = [[94.78903631548253, 84.23886881283048], [81.14186114900058, 99.83023372268642], [132.83556629096833, 48.92275878691167], [59.79419820769666, 118.44747671442332]]\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 14\n", - "Adjacent strokes (list): [4, 6, 6, 4]\n", - "Adjacent strokes (uniques): {4, 6}\n", - "Checking edge: (4, 6)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [[87.26341801197296, 93.7165388156464], [90.3973936094473, 88.62264956293333]]\n", - "(4, 6) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 15\n", - "Adjacent strokes (list): [4]\n", - "Adjacent strokes (uniques): {4}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 16\n", - "Adjacent strokes (list): [1, 6, 6]\n", - "Adjacent strokes (uniques): {1, 6}\n", - "Checking edge: (1, 6)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 2])\n", - "angles: [90.39785291117907]\n", - "(1, 6) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 17\n", - "Adjacent strokes (list): [7]\n", - "Adjacent strokes (uniques): {7}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 18\n", - "Adjacent strokes (list): [8, 4, 4]\n", - "Adjacent strokes (uniques): {8, 4}\n", - "Checking edge: (8, 4)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 2])\n", - "angles: [90.34989164828197]\n", - "(8, 4) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 19\n", - "Adjacent strokes (list): [6]\n", - "Adjacent strokes (uniques): {6}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 20\n", - "Adjacent strokes (list): [1]\n", - "Adjacent strokes (uniques): {1}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 21\n", - "Adjacent strokes (list): [9]\n", - "Adjacent strokes (uniques): {9}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 22\n", - "Adjacent strokes (list): [0]\n", - "Adjacent strokes (uniques): {0}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 23\n", - "Adjacent strokes (list): [2]\n", - "Adjacent strokes (uniques): {2}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 24\n", - "Adjacent strokes (list): [6]\n", - "Adjacent strokes (uniques): {6}\n", - "**************************************************************\n", - " \n", - " \n", - "\n" - ] - } - ], + "outputs": [], "source": [ "for n in graph.nodes:\n", "\n", @@ -1896,6 +389,7 @@ " if len(angles_gdf)==2:\n", "\n", " print(\"angles_gdf len 2\")\n", + "\n", " # connectivity equals 1 here\n", " connectivity = 1\n", "\n", @@ -1904,7 +398,7 @@ " row_a = angles_gdf.loc[0]\n", " row_b = angles_gdf.loc[1]\n", " angles = [\n", - " _angle_cos(\n", + " get_interior_angle(\n", " row_a.segment[1],\n", " row_a.segment[0],\n", " row_b.segment[1]\n", @@ -1935,13 +429,13 @@ " assert row_a.segment[0] == row_b.segment[0]\n", " # compute angle between stroke a and stroke b segments\n", " # and add to list of current angles\n", - " angles_stroke.append(_angle_cos(\n", + " angles_stroke.append(get_interior_angle(\n", " row_a.segment[1],\n", " row_a.segment[0],\n", " row_b.segment[1])\n", " )\n", - " # keep the smaller of the 2 angles to add to list of angles for the stroke pair\n", - " angles.append(min(angles_stroke))\n", + " # keep the smaller of the 2 angles to add to list of angles for the stroke pair\n", + " angles.append(min(angles_stroke))\n", "\n", " elif len(angles_gdf)==4:\n", " print(\"angles_gdf len 4\")\n", @@ -1956,23 +450,25 @@ " angles = []\n", " # iterate through stroke a segments\n", " for i, row_a in angles_stroke_a.iterrows():\n", - " angles_stroke = []\n", " # iterate through stroke b segments\n", + " angles_partial = []\n", " for j, row_b in angles_stroke_b.iterrows():\n", " assert row_a.segment[0] == row_b.segment[0]\n", " # compute angle between stroke a and stroke b segments\n", " # and add to list of current angles\n", - " angles_stroke.append(_angle_cos(\n", + " angle = get_interior_angle(\n", " row_a.segment[1],\n", " row_a.segment[0],\n", " row_b.segment[1])\n", - " )\n", - " # keep BOTH ANGLES to add to list of angles for this stroke pair\n", - " angles.append(angles_stroke)\n", - " \n", + " # if angle > 90:\n", + " # angle = 180 - angle\n", + " angles_partial.append(angle)\n", + " print(f\"Interior angles found: {angles_partial}\")\n", + " angles.append(min(angles_partial)) # @csebastiao we're keeping the minimal here?\n", + " print(f\"Final angles found: {angles}\")\n", "\n", " else:\n", - " ValueError(f\"Length of angles_gdf expected to be in [2,3,4], but is {len(angle_gdf)}\")\n", + " ValueError(f\"Length of angles_gdf expected to be in [2,3,4], but is {len(angles_gdf)}\")\n", "\n", " #### now that we have connectivity and angles, \n", " print(f\"connectivity: {connectivity}\")\n", @@ -2010,57 +506,102 @@ " " ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**We want as final output:**\n", + "\n", + "A networkx `Graph()` object (undirected, simple)\n", + "\n", + "* nodes represent strokes,\n", + "* edges represent stroke connections (intersecting, ie crossing or touching)\n", + "\n", + "* edges: attributes: \n", + " * angles \n", + " * number of connections\n", + "* nodes: attributes:\n", + " *should be inheriting from all primal edge attrs, at least:*\n", + " * geometry\n", + " * length\n", + "\n", + "***\n", + "\n", + "next step: functions to add attrs on the nodes (strokes):\n", + "* degree, closeness, betweenness (by def nx) \n", + "* connectivity == number of angles (total nr of connections, min=degree)\n", + "* access (abs diff connectivity-degree)\n", + "* spacing = length / connectivity\n", + "* orthogonality = average angle (sum of angles / connectivity)" + ] + }, { "cell_type": "code", - "execution_count": 70, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "# OUTDATED VERSION: CONTINUITY ADDED TO EDGES (I THINK THIS IS WRONG? anvy)\n", - "# for n in graph.nodes:\n", - " \n", - "# print(\"Node:\", graph.nodes[n][\"nodeID\"])\n", - " \n", - "# es = list(graph.edges(n, keys=True))\n", - "# stroke_list = [graph.edges[e][\"stroke_id\"] for e in es]\n", - "# stroke_set = set(stroke_list)\n", - " \n", - "# print(\"Adjacent strokes (list):\", stroke_list)\n", - "# print(\"Adjacent strokes (uniques):\", stroke_set)\n", + "# add graph metrics\n", + "\n", + "# betweenness centrality dict for all nodes\n", + "bc = nx.betweenness_centrality(stroke_graph)\n", + "\n", + "# closeness centrality dict for all nodes\n", + "cc = nx.closeness_centrality(stroke_graph)\n", + "\n", + "for n in stroke_graph.nodes:\n", " \n", - "# # for all size2 combinations from stroke_set\n", - "# for c in combinations(stroke_set, 2):\n", - "# print(\"Checking edge:\", c)\n", - "# continuities = {}\n", - "# for s in c: # s is the stroke ID\n", - "# continuities[s] = stroke_list.count(s)\n", - "# print(\"continuities\", continuities)\n", - "# angle = None # TODO\n", - "# if c not in stroke_graph.edges:\n", - "# edge_geom = LineString(\n", - "# [\n", - "# stroke_graph.nodes[c[0]][\"geometry\"],\n", - "# stroke_graph.nodes[c[1]][\"geometry\"]\n", - "# ]\n", - "# )\n", - "# stroke_graph.add_edge(\n", - "# c[0],\n", - "# c[1],\n", - "# continuities=continuities,\n", - "# geometry=edge_geom,\n", - "# angles=[angle]\n", - "# )\n", - "# print(f\"{c} added, continuities={continuities}\")\n", - "# else:\n", - "# for s in c:\n", - "# stroke_graph.edges[c][\"continuities\"][s] += continuities[s]\n", - "# stroke_graph.edges[c][\"angles\"].append(angle)\n", - "# print(f\"{c} already in graph, continuities=\", stroke_graph.edges[c][\"continuities\"])\n", - "# print(\"\\n\")\n", - "# # we want to add edges for all stroke IDs that co-occur on edges that share the same node in the primal graph\n", - "# # [0, 1, 1] means: stroke0 has an endpoint here; stroke1 has a throughpoint here; we add the edge [0,1] in the strokes_graph, with the attribute \n", - "# # stroke = {0: \"end\", 1: \"through\"}\n", - " " + " stroke_graph.nodes[n][\"degree\"] = nx.degree(stroke_graph, n)\n", + " stroke_graph.nodes[n][\"betweenness_centrality\"] = bc[n]\n", + " stroke_graph.nodes[n][\"closeness_centrality\"] = cc[n]\n", + "\n", + " # just for sanity check # TODO can be removed later\n", + " stroke_graph.nodes[n][\"connectivity_computed\"] = sum(\n", + " [len(stroke_graph.edges[edge][\"angles\"]) for edge in stroke_graph.edges(n)]\n", + " ) \n", + " assert stroke_graph.nodes[n][\"connectivity\"] == stroke_graph.nodes[n][\"connectivity_computed\"]\n", + "\n", + " # access = abs(connectivity - degree)\n", + " stroke_graph.nodes[n][\"access\"] = abs(stroke_graph.nodes[n][\"connectivity\"] - stroke_graph.nodes[n][\"degree\"])\n", + "\n", + " # spacing = length / connectivity\n", + " stroke_graph.nodes[n][\"length\"] = stroke_graph.nodes[n][\"geometry_stroke\"].length # compute length first\n", + " stroke_graph.nodes[n][\"spacing\"] = stroke_graph.nodes[n][\"length\"] / stroke_graph.nodes[n][\"connectivity\"]\n", + "\n", + " # orthogonality = sum(angles) / connectivity\n", + " # compute sum of angles of edges of that node first\n", + " node_angles = [stroke_graph.edges[edge][\"angles\"] for edge in stroke_graph.edges(n)]\n", + " node_angles = [item for sublist in node_angles for item in sublist] # un-nest list\n", + " stroke_graph.nodes[n][\"orthogonality\"] = sum(node_angles)/stroke_graph.nodes[n][\"connectivity\"]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Save as pickle" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# after iteration finished, save results:\n", + "with open('stroke_graph_anvy.pickle', 'wb') as handle:\n", + " pickle.dump(stroke_graph, handle, protocol=pickle.HIGHEST_PROTOCOL)\n", + "\n", + "# # to read back in:\n", + "# with open('stroke_graph.pickle', 'rb') as handle:\n", + "# G = pickle.load(handle)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Plot final results**" ] }, { @@ -2077,6 +618,24 @@ "points_strokes_primal=points_strokes_primal.set_crs(points_strokes.crs)" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "stroke_metrics = [\n", + " 'connectivity',\n", + " 'degree',\n", + " 'betweenness_centrality',\n", + " 'closeness_centrality',\n", + " 'access',\n", + " 'length', \n", + " 'spacing',\n", + " 'orthogonality'\n", + "]" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -2086,533 +645,9 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 102, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "m = points_strokes_primal.explore(\n", " tiles=\"cartodb.positron\",\n", @@ -2620,69 +655,34 @@ " name = \"strokes (original geoms)\",\n", " cmap = \"tab20c\", \n", " style_kwds={\"weight\":8},\n", - " opacity=0.5\n", + " opacity=0.9\n", ")\n", "points_strokes[[\"geometry\", \"connectivity\"]].explore(\n", " m=m,\n", " marker_kwds={\"radius\":10}, \n", " name =\"stroke nodes\",\n", " column = \"connectivity\", \n", - " cmap = \"Blues\"\n", + " cmap = \"Purples\",\n", " #opacity=0.2\n", " )\n", "\n", + "for metric in stroke_metrics:\n", + " points_strokes_primal.explore(\n", + " m=m,\n", + " column=metric,\n", + " cmap=\"Reds\",\n", + " name=f\"{metric}\")\n", + "\n", "lines_strokes[[\"geometry\", \"angles\"]].explore(m=m, \n", " name = \"Stroke graph edges\",\n", " color = \"black\",\n", - " style_kwds={\"weight\":4},\n", + " style_kwds={\"weight\":1},\n", + " dash_array=2\n", "\n", ")\n", "folium.LayerControl().add_to(m)\n", "m" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**We want as final output:**\n", - "\n", - "A networkx `Graph()` object (undirected, simple)\n", - "\n", - "* nodes represent strokes,\n", - "* edges represent stroke connections (intersecting, ie crossing or touching)\n", - "\n", - "* edges: attributes: \n", - " * angles \n", - " * number of connections\n", - "* nodes: attributes:\n", - " *should be inheriting from all primal edge attrs, at least:*\n", - " * geometry\n", - " * length\n", - "\n", - "***\n", - "\n", - "next step: functions to add attrs on the nodes (strokes):\n", - "* degree, closeness, betweenness (by def nx) \n", - "* connectivity == number of angles (total nr of connections, min=degree)\n", - "* access (abs diff connectivity-degree)\n", - "* spacing = length / connectivity\n", - "* orthogonality = average angle (sum of angles / connectivity)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From e21302c9ec91a07eea818daa499cedc13a1ca6dc Mon Sep 17 00:00:00 2001 From: anvy Date: Wed, 14 May 2025 13:41:53 +0200 Subject: [PATCH 10/27] rename nb --- momepy/{strokegraph.ipynb => strokegraph_anvy.ipynb} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename momepy/{strokegraph.ipynb => strokegraph_anvy.ipynb} (100%) diff --git a/momepy/strokegraph.ipynb b/momepy/strokegraph_anvy.ipynb similarity index 100% rename from momepy/strokegraph.ipynb rename to momepy/strokegraph_anvy.ipynb From e84702ad57dbebc6e5841184d9cf7903c8c4fdce Mon Sep 17 00:00:00 2001 From: anvy Date: Wed, 14 May 2025 13:42:14 +0200 Subject: [PATCH 11/27] add pickle-saving to clse nb --- momepy/strokegraph_clse.ipynb | 30 ++++++++++++++++++++++++++++-- 1 file changed, 28 insertions(+), 2 deletions(-) diff --git a/momepy/strokegraph_clse.ipynb b/momepy/strokegraph_clse.ipynb index 7c16aa8f..4862ec67 100644 --- a/momepy/strokegraph_clse.ipynb +++ b/momepy/strokegraph_clse.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -20,7 +20,8 @@ "import folium\n", "from itertools import combinations, product\n", "import shapely\n", - "import numpy as np" + "import numpy as np\n", + "import pickle" ] }, { @@ -187,6 +188,31 @@ " G_stroke.nodes[n][\"stroke_spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Save as pickle" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# after iteration finished, save results:\n", + "with open('stroke_graph_clse.pickle', 'wb') as handle:\n", + " pickle.dump(G_stroke, handle, protocol=pickle.HIGHEST_PROTOCOL)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Visualize final results**" + ] + }, { "cell_type": "code", "execution_count": 68, From e516188b39de2bfa421fed4752c204488fca9342 Mon Sep 17 00:00:00 2001 From: anvy Date: Wed, 14 May 2025 13:43:05 +0200 Subject: [PATCH 12/27] run anvy nb --- momepy/stroke_graph_anvy.pickle | Bin 0 -> 5777 bytes momepy/strokegraph_anvy.ipynb | 3380 ++++++++++++++++++++++++++++++- 2 files changed, 3350 insertions(+), 30 deletions(-) create mode 100644 momepy/stroke_graph_anvy.pickle diff --git a/momepy/stroke_graph_anvy.pickle b/momepy/stroke_graph_anvy.pickle new file mode 100644 index 0000000000000000000000000000000000000000..7457414f895b1863b8ae6ccfd37c3e52bcc8d072 GIT binary patch literal 5777 zcma)=30M?I7RMc6h5_+H(cl@8AVk3xaf5;jgD9&lXh6^)Iu1i;nh}_B4h|LLfq>YH zpslDehzE+|mFRk)d{L86jYcC1ct@g(VhHOI&&BBetLI=C(WF0){#94Ms`uW%j;;m5 zRoUI!@fX`Yh1R91G_%rue+} zouSsKls*9R%dxhjBcnKDeb!b>iX6sFiV7P!%zyYNoHm{n%hY&7CWm#AT9cS8OXBpb zP@1Ajph*){J7V04PEgR&#FPYDPHVa8q?od$I#Io7R;-{^$+S+B!Lg27My95dGJFzM z94r1@qe_;h&5B3sqg@07cqX~}<#wMmf62hx3o=%gO_gvNKiZG{?A( zUMsLceFyxmiw(ScKGk0`_QyKP8}In|Iv%+Mc3gI0p)YvM9B%ew@Q$1Q>!QF}3l^V# z3SNEwjqen&Z}~m@{%G^Zyc=VefcuEf=MMnq?kstc1Abxay6|t{f}4%9Rp7bXs{EqC z-tI@&bN<;f3>yvbeGL1%toQkw^S&~eHB(g%j3jQbP zGSoCFvH9GeTbi4LEPA3{K_C|q5i$M^F8&YIPRGTM7B@!^X3h@zG?>dqJv}9Wo|tY# zLITQ(>PWfLOm}45pb&Alc}}IsUj4;d#YR)KnLdnb$T$dy7ezOSg87elfe_VtEGe&k zhH9lAb&ETIAG@zy`8&9|(Pvl>@G9T#TONQvZrr=j7c4G6nsyr;k(WC!2)rn?_Sg+@ zJNwjO;ou{gi@v)GzFju{n@QlC>H3_@;D^eH*OS3}#>SkkCiNqf+-Kk=p#|5fz(rwG zMiqf0Z_J#t1AO?@$4}RRH?MVbECUx7cM2~7kM~K=-U4>=aw^ zbN4|m+LUn{bH;6`_Ec}GuVu#5!a{q^#rSGIv+ckUbJs}5y-XQ*M#GDSmkq6g2T!&P z$!WiRs-$w0>)v{B$t+>eYrGbzo>h4t9JH_Qt7foWMck&}z<>1otVcZ#AhFL zMYEYF{~LS{&x=IWcSe9aKYkg03#_~!p$#D%qV^yPxu%z1oCMY`4?cMXEali|?2*MSLP;Q3O`d?NprV5EjOogLU{ z2u4Z%jF1`x!yds95_uaZT@noA{EA@Mo8-N)@a2fOb4y7uCU?ur+vn$Kl6S?DdsBP| zN1B3RXAXuvC8ivx4wMVko%+BsC^HnYvSVdYxz?NSW>`ElI(V_@qbteCL(v<+;Id{zC5jPWM-fyzQYCm*6j}|-XISj{8TbO5Op?3SHOq zMxlEknMPEli=&HMIe4FUup_zhc5}U#c1z3)Wm7y6-XAdMdS^>Z}(h zYa#g!&vRb`A#rmqBznQ#wv^6|tHJkI)O7O%i|WOZ^|)n)t{dJcUPxWxM~n z@D!@b;rHy05kF10M&XUjnjcqLVD?jN^0S+zpIw8h*W_SuY*13(^WWj8^~99tmhVI+ zrh-S_9n^Ryzu%Rp3b1Z>dMr!)wAviC_?eosraGvr!O!{LlyU?7w7~$gA^BVt&0i#+ zb%-u5I!>tw*ky=AeNmxJDdJ#@I1pVMTsKTKbp}8j zY)x@UYq0-g@U&+n4$?Zut@S_sZqoIY)Y$>GJHw5-*0Xj}S%T91MM&|RIC%R8OJ<4p6|E_tz#kRk0VA0di$*k#aj}EG0 zEF%%qF~4q*+E|20@SBbIx6<}zqotL@r#<_QN@&%}AYrb5+B9=3hL1FgAL6asvL4^> z^vK}Q1FqrK#zn?YKSaG9bF{6H7= zrOma`oZm4s%Wh7JG+LDD^}OQYK}lO`v{ql6(r3)JOA@k2Xa73hterO0Xl>!0F)>7X z%j`#ehkPh8TWrJsw=BNPe`Ay#e^8c;>tx(%7+TpRnW??$IN4I5lcSovoK}Td7L`v> zk1MM;&Kxu%N8Cf?_Wza0{fVCg8UwzL6`Hex3H>>CP1oBR7uJ^kY+M95jqR`VZKbNF zhZ9_OOfaj;F#IT6r7J#7DSoAIEivmR+Ftg}GHA7=^26g4B_!+3`>nRUYc*SKwL^r} zHl$$P&$hRTuxOORtG=?4?kieJ;ehgAnO6szL-SWA3+q-53z)gz-o8ivzV)%O5i;Nq z3d&CDjaX}WCy?wnC>TzHFJSKKNd~|l@fFBqh0;qX2u6Wn&4B23;;jcrSr<~MXPu=| z)7h$2jzdpcD#e7n`HRYR+BQkI%Xr{S?U0@Y%0kHati1eO)?2c=q$ zamG=qkerfgIprj@#frxOEbDrrvf;Rvv1P?%HBCsA>o}%ZAJ5v7wUzDpR_o+A&e(Pb zNrF;_LqmCnrBT?F>2O92Gun8@-O#jSD1YQ=S\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
geometrymm_lennode_startnode_endmy_index
0LINESTRING (1603585.64 6464428.774, 1603413.20...264.103950010
1LINESTRING (1603268.502 6464060.781, 1603296.8...99.751190231
2LINESTRING (1603607.303 6464181.853, 1603592.8...199.746503142
3LINESTRING (1603363.558 6464031.885, 1603376.5...203.014090133
4LINESTRING (1603413.206 6464228.73, 1603274.45...198.482724154
\n", + "" + ], + "text/plain": [ + " geometry mm_len node_start \\\n", + "0 LINESTRING (1603585.64 6464428.774, 1603413.20... 264.103950 0 \n", + "1 LINESTRING (1603268.502 6464060.781, 1603296.8... 99.751190 2 \n", + "2 LINESTRING (1603607.303 6464181.853, 1603592.8... 199.746503 1 \n", + "3 LINESTRING (1603363.558 6464031.885, 1603376.5... 203.014090 1 \n", + "4 LINESTRING (1603413.206 6464228.73, 1603274.45... 198.482724 1 \n", + "\n", + " node_end my_index \n", + "0 1 0 \n", + "1 3 1 \n", + "2 4 2 \n", + "3 3 3 \n", + "4 5 4 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# remove false nodes\n", "streets = momepy.remove_false_nodes(streets)\n", @@ -134,9 +228,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(1,1, figsize=(8,8))\n", "lines.plot(ax=ax, column=\"my_index\", cmap=\"tab20\", lw=3, legend=True, zorder=0)\n", @@ -148,9 +253,106 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
n_segmentsgeometryrep_pointstroke_id
stroke_group
08LINESTRING (1603278.899 6463669.186, 1603283.7...POINT (1603374.663 6464077.898)0
119LINESTRING (1603077.5 6464475.323, 1603085.515...POINT (1603237.049 6464133.622)1
217LINESTRING (1603537.194 6464558.112, 1603557.6...POINT (1603707.107 6464238.854)2
35LINESTRING (1603413.206 6464228.73, 1603274.45...POINT (1603149.929 6464130.225)3
414LINESTRING (1602970.377 6464268.058, 1602974.0...POINT (1603264.658 6463848.976)4
\n", + "
" + ], + "text/plain": [ + " n_segments geometry \\\n", + "stroke_group \n", + "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", + "1 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", + "2 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", + "3 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", + "4 14 LINESTRING (1602970.377 6464268.058, 1602974.0... \n", + "\n", + " rep_point stroke_id \n", + "stroke_group \n", + "0 POINT (1603374.663 6464077.898) 0 \n", + "1 POINT (1603237.049 6464133.622) 1 \n", + "2 POINT (1603707.107 6464238.854) 2 \n", + "3 POINT (1603149.929 6464130.225) 3 \n", + "4 POINT (1603264.658 6463848.976) 4 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# make coins\n", "coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", @@ -168,9 +370,121 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
n_segmentsgeometryrep_pointstroke_idedge_indeces
stroke_group
08LINESTRING (1603278.899 6463669.186, 1603283.7...POINT (1603374.663 6464077.898)0[0, 3, 15, 27]
119LINESTRING (1603077.5 6464475.323, 1603085.515...POINT (1603237.049 6464133.622)1[1, 12, 14, 25]
217LINESTRING (1603537.194 6464558.112, 1603557.6...POINT (1603707.107 6464238.854)2[2, 11, 28, 30]
35LINESTRING (1603413.206 6464228.73, 1603274.45...POINT (1603149.929 6464130.225)3[4, 5, 6]
414LINESTRING (1602970.377 6464268.058, 1602974.0...POINT (1603264.658 6463848.976)4[7, 8, 9, 13, 21, 22, 24]
\n", + "
" + ], + "text/plain": [ + " n_segments geometry \\\n", + "stroke_group \n", + "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", + "1 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", + "2 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", + "3 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", + "4 14 LINESTRING (1602970.377 6464268.058, 1602974.0... \n", + "\n", + " rep_point stroke_id \\\n", + "stroke_group \n", + "0 POINT (1603374.663 6464077.898) 0 \n", + "1 POINT (1603237.049 6464133.622) 1 \n", + "2 POINT (1603707.107 6464238.854) 2 \n", + "3 POINT (1603149.929 6464130.225) 3 \n", + "4 POINT (1603264.658 6463848.976) 4 \n", + "\n", + " edge_indeces \n", + "stroke_group \n", + "0 [0, 3, 15, 27] \n", + "1 [1, 12, 14, 25] \n", + "2 [2, 11, 28, 30] \n", + "3 [4, 5, 6] \n", + "4 [7, 8, 9, 13, 21, 22, 24] " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# add edge_ids column (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", "stroke_gdf[\"edge_indeces\"] = stroke_gdf.stroke_id.apply(\n", @@ -182,9 +496,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(1,1, figsize=(10,10))\n", "for stroke_id in stroke_gdf.stroke_id:\n", @@ -197,7 +522,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -218,18 +543,588 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
geometrymm_lennode_startnode_endmy_index
0LINESTRING (1603585.64 6464428.774, 1603413.20...264.103950010
1LINESTRING (1603268.502 6464060.781, 1603296.8...99.751190231
2LINESTRING (1603607.303 6464181.853, 1603592.8...199.746503142
3LINESTRING (1603363.558 6464031.885, 1603376.5...203.014090133
4LINESTRING (1603413.206 6464228.73, 1603274.45...198.482724154
\n", + "
" + ], + "text/plain": [ + " geometry mm_len node_start \\\n", + "0 LINESTRING (1603585.64 6464428.774, 1603413.20... 264.103950 0 \n", + "1 LINESTRING (1603268.502 6464060.781, 1603296.8... 99.751190 2 \n", + "2 LINESTRING (1603607.303 6464181.853, 1603592.8... 199.746503 1 \n", + "3 LINESTRING (1603363.558 6464031.885, 1603376.5... 203.014090 1 \n", + "4 LINESTRING (1603413.206 6464228.73, 1603274.45... 198.482724 1 \n", + "\n", + " node_end my_index \n", + "0 1 0 \n", + "1 3 1 \n", + "2 4 2 \n", + "3 3 3 \n", + "4 5 4 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "lines.head()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Reds\", style_kwds={\"weight\":8})\n", "lines.explore(m=m, column = \"my_index\", name = \"lines\", cmap = \"Blues\", style_kwds={\"weight\":8})\n", @@ -248,7 +1143,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -297,9 +1192,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "NodeDataView({0: {'edge_indeces': [0, 3, 15, 27], 'geometry': , 'geometry_stroke': , 'x': 1603374.6625343116, 'y': 6464077.898491419, 'connectivity': 0}, 1: {'edge_indeces': [1, 12, 14, 25], 'geometry': , 'geometry_stroke': , 'x': 1603237.0487682838, 'y': 6464133.622486805, 'connectivity': 0}, 2: {'edge_indeces': [2, 11, 28, 30], 'geometry': , 'geometry_stroke': , 'x': 1603707.1065106073, 'y': 6464238.853991265, 'connectivity': 0}, 3: {'edge_indeces': [4, 5, 6], 'geometry': , 'geometry_stroke': , 'x': 1603149.9288811635, 'y': 6464130.224503239, 'connectivity': 0}, 4: {'edge_indeces': [7, 8, 9, 13, 21, 22, 24], 'geometry': , 'geometry_stroke': , 'x': 1603264.6577362637, 'y': 6463848.97596353, 'connectivity': 0}, 5: {'edge_indeces': [10], 'geometry': , 'geometry_stroke': , 'x': 1603137.4077031056, 'y': 6463800.908382258, 'connectivity': 0}, 6: {'edge_indeces': [16, 17, 18, 23, 29], 'geometry': , 'geometry_stroke': , 'x': 1603592.2349246691, 'y': 6464121.336160048, 'connectivity': 0}, 7: {'edge_indeces': [19], 'geometry': , 'geometry_stroke': , 'x': 1603028.737187382, 'y': 6463900.594576759, 'connectivity': 0}, 8: {'edge_indeces': [20], 'geometry': , 'geometry_stroke': , 'x': 1603207.5969886228, 'y': 6463992.707728057, 'connectivity': 0}, 9: {'edge_indeces': [26], 'geometry': , 'geometry_stroke': , 'x': 1603342.3426854417, 'y': 6464406.368225728, 'connectivity': 0}})" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "stroke_graph = nx.Graph()\n", "stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", @@ -333,9 +1239,632 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Node: 0\n", + "Adjacent strokes (list): [0, 2, 2]\n", + "Adjacent strokes (uniques): {0, 2}\n", + "Checking edge: (0, 2)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 2])\n", + "angles: [62.302182356951434]\n", + "(0, 2) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 1\n", + "Adjacent strokes (list): [0, 2, 0, 3, 9]\n", + "Adjacent strokes (uniques): {0, 9, 2, 3}\n", + "Checking edge: (0, 9)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [36.134980718680936]\n", + "(0, 9) added\n", + "Checking edge: (0, 2)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [63.647466378271766]\n", + "(0, 2) already in graph, angles = [62.302182356951434]\n", + "(0, 2) already in graph, angles updated = [62.302182356951434, 63.647466378271766]\n", + "Checking edge: (0, 3)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [29.396028363390087]\n", + "(0, 3) added\n", + "Checking edge: (9, 2)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 2\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 1])\n", + "angles: [53.8322224050728]\n", + "(9, 2) added\n", + "Checking edge: (9, 3)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 2\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 1])\n", + "angles: [88.08366041995446]\n", + "(9, 3) added\n", + "Checking edge: (2, 3)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 2\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 1])\n", + "angles: [34.25143801488164]\n", + "(2, 3) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 2\n", + "Adjacent strokes (list): [1, 1, 8]\n", + "Adjacent strokes (uniques): {8, 1}\n", + "Checking edge: (8, 1)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [70.04113695824684]\n", + "(8, 1) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 3\n", + "Adjacent strokes (list): [1, 0, 1, 0]\n", + "Adjacent strokes (uniques): {0, 1}\n", + "Checking edge: (0, 1)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "Interior angles found: [89.87471285219927, 89.74560192447649]\n", + "Interior angles found: [89.75267804978043, 89.88178897750322]\n", + "Final angles found: [89.74560192447649, 89.75267804978043]\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [89.74560192447649, 89.75267804978043]\n", + "(0, 1) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 4\n", + "Adjacent strokes (list): [2, 6, 2, 6]\n", + "Adjacent strokes (uniques): {2, 6}\n", + "Checking edge: (2, 6)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "Interior angles found: [85.21096368451747, 84.23886881283048]\n", + "Interior angles found: [81.14186114900058, 80.16976627731358]\n", + "Final angles found: [84.23886881283048, 80.16976627731358]\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [84.23886881283048, 80.16976627731358]\n", + "(2, 6) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 5\n", + "Adjacent strokes (list): [3, 3, 1, 1]\n", + "Adjacent strokes (uniques): {1, 3}\n", + "Checking edge: (1, 3)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "Interior angles found: [89.53084497276808, 89.57504791798526]\n", + "Interior angles found: [89.58581817377714, 89.63002111899432]\n", + "Final angles found: [89.53084497276808, 89.58581817377714]\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [89.53084497276808, 89.58581817377714]\n", + "(1, 3) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 6\n", + "Adjacent strokes (list): [3, 3, 4, 4]\n", + "Adjacent strokes (uniques): {3, 4}\n", + "Checking edge: (3, 4)\n" + ] + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGTCAYAAABwJ4sYAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABQUElEQVR4nO3dd1hUV/4G8HdoQ++CSBGkKSqggDQ7logaNtHYElvMrmaTXzR9dRM1iVmNKRtTNNmN2Zii2I3GaGLsQUAGBAELxQICooIUUVDg/v4gTBgBKXfgzsj7eR6eJxzu3PnOYA7vnXPOPTJBEAQQERERiaAjdQFERESk/RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiItsXLlSshkMixatOiBxx09ehQBAQEwNDREr1698MUXX3ROgUSkcTqz32CgINICCQkJ+M9//gNfX98HHnfx4kVERkZiyJAhOHXqFJYsWYIXXngB27dv76RKiUhTdHa/wUBBpOFu3bqFJ598Ev/9739hZWX1wGO/+OILuLi44OOPP0afPn3wzDPP4Omnn8YHH3zQSdUSkSaQot/QE1MwUVdRWVmJu3fvij6PIAiQyWQqbXK5HHK5vNnHPPfccxg/fjxGjRqFFStWPPD8sbGxGDNmjErb2LFjsX79ety7dw/6+vrtL56I2kRd/QbQ9r5Din6DgYKoBZWVlbC2tsadO3dEn8vU1BS3bt1SaVu2bBmWL1/e5PHR0dFISkpCQkJCq85/9epV2Nvbq7TZ29ujuroaN27cgIODQ7vqJqK2UWe/AbSt75Cq32CgIGrB3bt3cefOHcyYMQMGBgaizrNx40bk5ubC3Nxc2d7cFUZubi4WLlyIX3/9FYaGhq1+nvuvYgRBaLKdiDqOuvqN+nO1tu+Qst9goCBqJQMDA9EdAwCYm5urdArNSUxMxLVr1xAQEKBsq6mpwbFjx/DZZ5+hqqoKurq6Ko/p3r07rl69qtJ27do16OnpwcbGRnTtRNQ26uo3gNb1HVL2GwwURBoqIiICqampKm1z585F79698frrrzfqFAAgNDQUe/bsUWn79ddfERgYyPkTRF2AlP0GAwWRhjIzM0O/fv1U2kxMTGBjY6NsX7x4MfLy8vDtt98CABYsWIDPPvsML730Ev76178iNjYW69evx6ZNmzq9fiLqfFL2G1w2SqTFCgoKkJOTo/zezc0NP//8M44cOQJ/f3+88847+OSTTzBp0iQJqyQiTdJR/YZMqJ95QURNKisrg4WFBebMmSN6UuY333yD0tLSVs2hICLtpa5+A9CevoOfUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERiaYndQFE2mKwxQEYy9ufwW9X1eIb9ZVDRFpAbL8BaE/fwU8oiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6Ag0lDr1q2Dr68vzM3NYW5ujtDQUOzbt++Bj/nhhx/g5+cHY2NjODg4YO7cuSgqKuqkiolIalL2GwwURBrKyckJq1atgkKhgEKhwMiRIxEVFYX09PQmj//9998xa9YszJs3D+np6di6dSsSEhLwzDPPdHLlRCQVKfsNPbHFE1HHmDhxosr37777LtatW4e4uDj07du30fFxcXFwdXXFCy+8AABwc3PD/PnzsXr16k6pl4ikJ2W/wU8oiDpZWVmZyldVVVWLj6mpqUF0dDQqKioQGhra5DFhYWG4cuUKfv75ZwiCgMLCQmzbtg3jx49X90sgIgm0te/o7H6DgYKokzk7O8PCwkL5tXLlymaPTU1NhampKeRyORYsWICdO3fCx8enyWPDwsLwww8/YOrUqTAwMED37t1haWmJTz/9tKNeChF1otb2HVL1GwwURJ0sNzcXpaWlyq/Fixc3e6y3tzeSk5MRFxeHZ599FrNnz8aZM2eaPPbMmTN44YUXsHTpUiQmJmL//v24ePEiFixY0FEvhYg6UWv7Dqn6DbUGik8++QQymQz9+vVr9hiZTIbly5crvz9y5AhkMhmOHDki+vl//vlnlXOr0zfffAOZTAaFQtEh51e3jRs34uOPP5a6jEbU+ftu6PLly3j66afRo0cPyOVyODo64rHHHlPrc6hL/ezr+i+5XN7ssQYGBvDw8EBgYCBWrlwJPz8/rFmzpsljV65cifDwcLz66qvw9fXF2LFjsXbtWnz99dcoKCjoqJdDRJ2ktX2HVP2GWgPF119/DQBIT09HfHy8Ok/dKj///DPeeuutTn9eTaSpgaIjpKWlISAgAGlpafjggw9w4MABfPTRR7CyspK6NLUTBKHZcdPbt29DR0f1f2ldXV3l44ioa+qsfkNtqzwUCgVSUlIwfvx47N27F+vXr0dwcLC6Tq92giCgsrISRkZGUpdCIgiCgJkzZ8LZ2RnHjx9XSexTp06VsDLxlixZgnHjxsHZ2Rnl5eWIjo7GkSNHsH//fgDA4sWLkZeXh2+//RZA3ezuv/71r1i3bh3Gjh2LgoICLFq0CIMGDUKPHj2kfClE1Emk7DfU9gnF+vXrAQCrVq1CWFgYoqOjcfv2bXWdHrdv38Yrr7wCNzc3GBoawtraGoGBgdi0aRMAYM6cOfj8888B1A2r1H9dunRJ2fb888/jiy++QJ8+fSCXy7FhwwYAdetwIyIiYGZmBmNjY4SFhWHv3r0t1lRQUICAgAB4enoiMzMTQN0s3Po6DQwM4OjoiEWLFqGiokLlsVu3bkVwcDAsLCxgbGyMXr164emnn27xOT///HMMHToUdnZ2MDExQf/+/bF69Wrcu3dPeczw4cOxd+9eXL58WeW9eBBXV1dMmDAB+/fvx8CBA2FkZITevXsrP3VqKC0tDVFRUbCysoKhoSH8/f2V72VD586dwyOPPAJjY2PY2tpiwYIFKC8vb/L5f/vtN0RERMDc3BzGxsYIDw/HwYMHW3w/jh07huTkZCxatOiBQwfaqLCwEDNnzoS3tzciIiIQHx+P/fv3Y/To0QDq/v3l5OQoj58zZw4++ugjfPbZZ+jXrx+eeOIJeHt7Y8eOHVK9BCLqZFL2G2r5hOLOnTvYtGkTgoKC0K9fPzz99NN45plnsHXrVsyePVsdT4GXXnoJ3333HVasWIEBAwagoqICaWlpyrt5vfnmm6ioqMC2bdsQGxurfJyDg4Pyv3ft2oXjx49j6dKl6N69O+zs7HD06FGMHj0avr6+WL9+PeRyOdauXYuJEydi06ZNzV7lpqWlITIyEk5OToiNjYWtrS1u376NYcOG4cqVK1iyZAl8fX2Rnp6OpUuXIjU1Fb/99htkMhliY2MxdepUTJ06FcuXL4ehoSEuX76MQ4cOtfg+ZGdnY8aMGcrAkpKSgnfffRfnzp1T/vFfu3Yt/va3vyE7Oxs7d+5s9XuckpKCl19+Gf/4xz9gb2+Pr776CvPmzYOHhweGDh0KADh//jzCwsJgZ2eHTz75BDY2Nvj+++8xZ84cFBYW4rXXXgNQ94962LBh0NfXx9q1a2Fvb48ffvgBzz//fKPn/f777zFr1ixERUVhw4YN0NfXx5dffomxY8fil19+QURERLM1Hzt2DABgZmaGyMhIHDp0CHp6ehg+fDg++OAD9O7du9WvX9PUh/TmfPPNN43a/u///g//93//10EVEZGmk7LfUEug2LZtG0pLSzFv3jwAdR81L1q0COvXr1dboIiJicGYMWPw4osvKtsarpN1d3eHvb09ACAkJKTJc9y6dQupqakqY+uhoaGwsrLCkSNHYGpqCgCYMGEC/P398corr2DKlCmNru5/++03TJo0CWPGjMF3330HQ0NDAHWTUk+fPo34+HgEBgYCACIiIuDo6IjJkydj//79GDduHE6cOAFBEPDFF1/AwsJCed45c+a0+D589NFHyv+ura3FkCFDYGNjg7lz5+LDDz+ElZUVfHx8YGlpCblc3ux70ZQbN24gJiYGLi4uAIChQ4fi4MGD2LhxozJQLF++HHfv3sXhw4fh7OwMAIiMjERJSQneeustzJ8/HxYWFvj3v/+N69ev49SpU/Dz8wMAjBs3DmPGjFFJx7dv38bChQsxYcIElfATGRmJgQMHYsmSJQ+cj5OXlwcAmDt3Lp544gns3bsXBQUFeOONNzBkyBCcPn1aJVQSEVHHUMuQx/r162FkZIRp06YBAExNTfHEE0/g+PHjyqEAsQYNGoR9+/bhH//4B44cOYI7d+60+RwjR45UCRMVFRWIj4/H5MmTlWECqJuQMnPmTFy5cgXnz59XOceGDRsQGRmJZ555Blu2bFGGCQD46aef0K9fP/j7+6O6ulr5NXbsWJWVDUFBQQCAKVOmYMuWLco/iq1x6tQpPProo7CxsYGuri709fUxa9Ys1NTUICMjo83vSUP+/v7KMAEAhoaG8PLywuXLl5Vthw4dQkREhDJM1JszZw5u376t/HTo8OHD6Nu3rzJM1JsxY4bK9ydOnEBxcTFmz56t8p7V1tbikUceQUJCQqPhooZqa2sB1AXDr776ChEREXjqqaewa9cu3LhxQzkMRkREHUt0oMjKysKxY8cwfvx4CIKAkpISlJSUYPLkyQDQ5Bh8e3zyySd4/fXXsWvXLowYMQLW1tb4y1/+0qbAcv+V6s2bNyEIQpNXsPWTUe7fICU6OhpGRkZ45plnGn1yUVhYiNOnT0NfX1/ly8zMDIIg4MaNGwDqrvx37dqF6upqzJo1C05OTujXr59yPkhzcnJyMGTIEOTl5WHNmjU4fvw4EhISlH802xOyGrKxsWnUJpfLVc5bVFTUqverqKgI3bt3b3Tc/W2FhYUAgMmTJzd639577z0IgoDi4uIWax47dqxKu7+/PxwcHJCUlNTsY4mISH1ED3l8/fXXEAQB27Ztw7Zt2xr9fMOGDVixYoVyGUp7mZiY4K233sJbb72FwsJC5acVEydOxLlz51p1jvsDgJWVFXR0dJpca5ufnw8AsLW1VWn/4Ycf8Oabb2LYsGH49ddf4e/vr/yZra0tjIyMmg1RDc8VFRWFqKgoVFVVIS4uDitXrsSMGTPg6ura7C1Sd+3ahYqKCuzYsQM9e/ZUticnJz/wdauTjY1Nq94vGxsbXL16tdFx97fVH//pp582OzxTP5TVFF9f32Z/JghCo+VQRETUMUT1tjU1NdiwYQPc3d1x+PDhRl8vv/wyCgoKWtw6ta3s7e0xZ84cTJ8+HefPn1euJqmf5d/aK3UTExMEBwdjx44dKo+pra3F999/DycnJ3h5eak8xtraGr/99hv69OmDESNGIC4uTvmzCRMmIDs7GzY2NggMDGz05erq2qgGuVyOYcOG4b333gNQN6TRnPpA1HA1gyAI+O9//9vkecV+YtGUiIgIHDp0SBkg6n377bcwNjZWhoIRI0YgPT0dKSkpKsdt3LhR5fvw8HBYWlrizJkzTb5ngYGBMDAwaLaecePGwdjYuNG/saSkJFy9erVNc0iIiKj9RH1CsW/fPuTn5+O9997D8OHDG/28X79++Oyzz7B+/XpMmDBBzFMhODgYEyZMgK+vL6ysrHD27Fl89913CA0NhbGxMQCgf//+AID33nsP48aNg66uLnx9fR/4B2nlypUYPXo0RowYgVdeeQUGBgZYu3Yt0tLSsGnTpiaXW5qZmWH//v14/PHHMXr0aOzevRsjRozAokWLsH37dgwdOhQvvvgifH19UVtbi5ycHPz66694+eWXERwcjKVLl+LKlSuIiIiAk5MTSkpKsGbNGujr62PYsGHN1jp69GgYGBhg+vTpeO2111BZWYl169bh5s2bjY7t378/duzYgXXr1iEgIAA6OjrKiaJiLFu2DD/99BNGjBiBpUuXwtraGj/88AP27t2L1atXKyeZLlq0CF9//TXGjx+PFStWKFd53P9pkqmpKT799FPMnj0bxcXFmDx5Muzs7HD9+nWkpKTg+vXrWLduXbP1WFpa4u2338Yrr7yiDJlXr17Fm2++CRcXF/z9738X/ZqJiKhlogLF+vXrYWBggLlz5zb5c1tbWzz22GPYtm0bCgsLH/jRdUtGjhyJ3bt349///jdu374NR0dHzJo1C//85z+Vx8yYMQMxMTFYu3Yt3n77bQiCgIsXLzb5yUC9YcOG4dChQ1i2bBnmzJmD2tpa+Pn5Yffu3Q8MQUZGRvjxxx8xY8YMREZGYvv27YiMjMTx48exatUq/Oc//8HFixdhZGQEFxcXjBo1SllHcHAwFAoFXn/9dVy/fh2WlpYIDAzEoUOHmtxetl7v3r2xfft2vPHGG3j88cdhY2ODGTNm4KWXXsK4ceNUjl24cCHS09OxZMkSlJaWQhAEtdwt0dvbGydOnMCSJUvw3HPP4c6dO+jTpw/+97//qaxS6d69O44ePYqFCxfi2WefhbGxMR577DF89tlniIqKUjnnU089BRcXF6xevRrz589HeXk57Ozs4O/v36qVLy+//DIsLCywZs0abNq0CWZmZnjkkUewatUqWFtbi37NRETUMpnAe/ISPVBZWRksLCzw1UJHGMvbP0p4u6oWz6zJQ2lpKczNzdVYIRFpGnX1G4D29B2csUZERESiMVAQERGRaAwURCRafHw8HnvsMbi4uEAul8Pe3h6hoaF4+eWXVY5bu3Ztk7f+VYc5c+ao3KBOSvUb1TW8Kdwnn3yCkJAQ2NraQi6Xw8XFBdOmTUN6erranveNN96ATCZDv379VNrv3bsHd3f3DtmB+F//+hd27dql9vOKtXz58hb3MGqP33//HZGRkbCysoKRkRE8PT3xzjvvqP15tJHadhsletgNGZgPM+P2d1Dltx/O6Up79+7Fo48+iuHDh2P16tVwcHBAQUEBFAoFoqOj8eGHHyqPXbt2LWxtbVs12VZbCYKARYsW4a9//avK/WKKioowbtw4+Pn5wcrKChcuXMCqVasQHByMxMREeHt7i3re5ORkfPDBB01OftfX18fSpUvx4osvYubMmU3exK69/vWvf2Hy5Mn4y1/+orZzaqqNGzdi5syZmDJlCr799luYmpoiOzu70TL6hsT2G4D29B0MFEQkyurVq+Hm5oZffvkFenp/dinTpk3D6tWr233ee/fuQSaTqZxTG+zfvx9JSUmN7rny1ltvqXw/bNgwhISEwMfHBz/88APefvvtdj9ndXU15s6di/nz5yMlJUV5V96Gpk+fjpdeeglffvkllixZ0u7n6qry8vLwt7/9DfPnz8fatWuV7SNGjJCwKs3CIQ8iEqWoqAi2trZN/uFveKdSV1dXpKen4+jRo5DJZJDJZMql1EeOHIFMJsN3332Hl19+GY6OjpDL5cjKygJQd0dePz8/GBoawtraGo899hjOnj3bYm0xMTGwtbXFhAkTlHvCZGZmYsaMGbCzs4NcLkefPn0a7flSW1uLFStWwNvbG0ZGRrC0tISvry/WrFnT4nOuW7cOQUFBrfrEoVu3bgAgOjStWrUKxcXFePfdd5s9xsDAAFOnTsV//vOfFpeQV1ZW4uWXX4a/vz8sLCxgbW2N0NBQ/PjjjyrHyWQyVFRUYMOGDcrfaVP3JKp36dIlyGQyfPDBB/joo4/g5uYGU1NThIaGqtwksN7u3buV9xoyMzPD6NGjVXaTrrd37174+/tDLpfDzc0NH3zwQZPPLwgC1q5dC39/fxgZGcHKygqTJ0/GhQsXHvh+AMBXX32FiooKvP766y0e21UxUBCRKKGhoYiPj8cLL7yA+Ph43Lt3r8njdu7ciV69emHAgAGIjY1FbGysyg6zALB48WLk5OTgiy++wJ49e2BnZ4eVK1di3rx56Nu3L3bs2IE1a9bg9OnTCA0NfeBePlu2bEFERASmTJmCH3/8ESYmJjhz5gyCgoKQlpaGDz/8ED/99BPGjx+PF154QeUThNWrV2P58uWYPn069u7di82bN2PevHkoKSl54Htx9+5d/Pbbbw+8aq2pqUFVVRXOnTuHZ555BnZ2ds3ey6c1zpw5gxUrVmDdunUtziEZPnw4Ll++jLS0tAceV1VVheLiYrzyyivYtWsXNm3ahMGDB+Pxxx/Ht99+qzwuNjYWRkZGiIyMVP5OG169N+fzzz/HgQMH8PHHH+OHH35ARUUFIiMjUVpaqjxm48aNiIqKgrm5OTZt2oT169fj5s2bGD58OH7//XflcQcPHkRUVBTMzMwQHR2N999/H1u2bMH//ve/Rs87f/58LFq0CKNGjcKuXbuwdu1apKenIywsTLmvUHOOHTsGa2trnDt3Dv7+/tDT04OdnR0WLFiAsrKyFl9zlyAQ0QOVlpYKAITzG2RC/laddn+d3yATAAilpaVSvyS1unHjhjB48GABgABA0NfXF8LCwoSVK1cK5eXlKsf27dtXGDZsWKNzHD58WAAgDB06VKX95s2bgpGRkRAZGanSnpOTI8jlcmHGjBnKttmzZwsmJiaCIAjCqlWrBF1dXeG9995TedzYsWMFJyenRr+D559/XjA0NBSKi4sFQRCECRMmCP7+/m17IwRBiI+PFwAI0dHRzR4jl8uV75WXl5dw5syZNj9PvZqaGiE4OFiYPn26sm3YsGFC3759mzw+MzNTACCsW7euTc9TXV0t3Lt3T5g3b54wYMAAlZ+ZmJgIs2fPbtV5Ll68KAAQ+vfvL1RXVyvbT548KQAQNm3apHxdPXr0EPr37y/U1NQojysvLxfs7OyEsLAwZVtwcLDQo0cP4c6dO8q2srIywdraWmj4Jy42NlYAIHz44YcqNeXm5gpGRkbCa6+99sDavb29BUNDQ8HMzEz417/+JRw+fFhYvXq1YGRkJISHhwu1tbUqx6ur39CmvoOfUBCRKDY2Nsqdb1etWoWoqChkZGRg8eLF6N+/f5Pj+c2ZNGmSyvexsbG4c+dOo0mczs7OGDlyJA4ePKjSLggC5s+fj2XLlmHjxo147bXXlD+rrKzEwYMH8dhjj8HY2BjV1dXKr8jISFRWVio/dh80aBBSUlLw97//Hb/88kurr0DrJ+fZ2dk1e8yJEycQGxuL77//HmZmZsp9b9rjo48+QmZmZqtXb9TXlZeX1+KxW7duRXh4OExNTaGnpwd9fX2sX7++VUNNLRk/frzKhpH1m/zVr4o5f/488vPzMXPmTJVhM1NTU0yaNAlxcXG4ffs2KioqkJCQgMcffxyGhobK48zMzDBx4kSV5/zpp58gk8nw1FNPqfzuu3fvDj8/Pxw5cuSBNdfW1qKyshJLlizB4sWLMXz4cLz66qtYuXIlYmJiGv1b7IoYKIhILQIDA/H6669j69atyM/Px4svvohLly61aWKmg4ODyvdFRUVNtgNAjx49lD+vd/fuXWzevBl9+/ZtdDv6oqIiVFdX49NPP4W+vr7KV2RkJAAow8/ixYvxwQcfIC4uDuPGjYONjQ0iIiKgUCgeWH/9hnwN/7jdb+DAgQgJCcGTTz6Jw4cPQxCEdk2SzMnJwdKlS7Fs2TIYGBigpKQEJSUlqK6uRm1tLUpKShptEFhfV0sbB+7YsQNTpkyBo6Mjvv/+e8TGxiIhIQFPP/00Kisr21zr/e5fZXL/xo4t/d5ra2tx8+ZN3Lx5E7W1tejevXuj4+5vKywshCAIsLe3b/T7j4uLazH41tc8duxYlfb6f2dJSUkPfHxXoF3Tp4lIK+jr62PZsmX497//3eJ4fUP33zegvhMvKChodGx+fj5sbW1V2uRyOQ4fPoyxY8di1KhR2L9/P6ysrAAAVlZW0NXVxcyZM/Hcc881+fxubm4A6iZJvvTSS3jppZdQUlKC3377DUuWLMHYsWORm5ur3JDwfvX1FBcXt+r1mpmZoXfv3sjIyGjV8Q1duHABd+7cwcKFC7Fw4cJGP7eyssLChQtVPr2or+v+9+1+33//Pdzc3LB582aV30lVVVWb62yPln7vOjo6sLKygiAIkMlkuHr1aqPj7m+ztbWFTCZT3iPkfk21NeTr69vkxFHhjwmuDT9J6ar4DhCRKE11+gCUH4336NFD2SaXy1u8Om4oNDQURkZG+P7771Xar1y5gkOHDiEiIqLRYwYMGICjR4/iypUrGD58OK5duwYAMDY2xogRI3Dq1Cn4+voiMDCw0VdT92ewtLTE5MmT8dxzz6G4uBiXLl1qtt4+ffoAALKzs1v1+m7cuIHU1FR4eHi06viG/P39cfjw4UZffn5+cHV1xeHDh/H888+rPKZ+NYOPj88Dzy2TyWBgYKASJq5evdpolQfQ9t9pa3h7e8PR0REbN25UWZFSUVGB7du3K1d+mJiYYNCgQdixY4fKJyfl5eXYs2ePyjknTJgAQRCQl5fX5O++frfq5tQPx+3bt0+l/eeffwYAhISEiHrNDwN+QkFEoowdOxZOTk6YOHEievfujdraWiQnJ+PDDz+EqampytVz//79ER0djc2bN6NXr14wNDR8YEduaWmJN998E0uWLMGsWbMwffp0FBUV4a233oKhoSGWLVvW5OP69OmD48ePY9SoURg6dCh+++03ODk5Yc2aNRg8eDCGDBmCZ599Fq6urigvL0dWVhb27NmDQ4cOAQAmTpyIfv36ITAwEN26dcPly5fx8ccfo2fPnvD09Gy2XicnJ/Tq1QtxcXF44YUXlO2lpaUYPXo0ZsyYAU9PTxgZGSEjIwNr1qxBVVVVo9cxfPhwHD169IHLOy0tLZtcomlpaYnq6uomfxYXFwddXV0MHTq02fMCdX98d+zYgb///e+YPHkycnNz8c4778DBwaHRypr+/fvjyJEj2LNnDxwcHGBmZib6Jl06OjpYvXo1nnzySUyYMAHz589HVVUV3n//fZSUlGDVqlXKY9955x088sgjGD16NF5++WXU1NTgvffeg4mJiconReHh4fjb3/6GuXPnQqFQYOjQoTAxMUFBQQF+//139O/fH88++2yzNY0ZMwYTJ07E22+/jdraWoSEhEChUOCtt97ChAkTMHjwYFGv+aEg3XxQIu3AVR4PtnnzZmHGjBmCp6enYGpqKujr6wsuLi7CzJkzG61guHTpkjBmzBjBzMxMACD07NlTEIQ/V3ls3bq1yef46quvBF9fX8HAwECwsLAQoqKihPT0dJVjGq7yqHflyhWhd+/egqurq5CdnS0IQt1Kg6efflpwdHQU9PX1hW7duglhYWHCihUrlI/78MMPhbCwMMHW1lYwMDAQXFxchHnz5gmXLl1q8f148803BSsrK6GyslLZVllZKTzzzDNCnz59BFNTU0FPT09wcnISnnrqqUavQxAEISAgQOjevXuLz9WUB63yGDJkiDBx4sRWnWfVqlWCq6urIJfLhT59+gj//e9/hWXLlgn3/9lITk4WwsPDBWNjYwFAk6t46tWv8nj//fcb/QyAsGzZMpW2Xbt2CcHBwYKhoaFgYmIiRERECDExMY0eu3v3buW/DxcXF2HVqlVN1ioIgvD1118LwcHBgomJiWBkZCS4u7sLs2bNEhQKRYvvye3bt4XXX39dcHZ2FvT09AQXFxdh8eLFKr/rel1xlQe3LydqQf02xOc3yETfett7tqDxWxCTOPn5+XBzc8O3336LqVOntvnx5eXlsLa2xscff9zsXI/2yM7OhqenJ3755ReMHj1abeelpqmr3wC0p+/gHAoiIjXq0aMHFi1ahHfffRe1tbVtfvyxY8fg6OiIv/71r2qta8WKFYiIiGCYoA7DQEFEpGZvvPEGJk2a1Kr7Pdxv/PjxuHTpEgwMDNRWT3V1Ndzd3RvdYpxInTgpk4hIzczMzJqdMCoFPT09vPHGG1KXQQ85fkJBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgPZaDIz8/HN998gy1btkhdChFpkWPHjuFf//oXCgsLpS6FSOs8lIGivLwcsbGxiImJQVVVldTlEJGWSElJweXLlxETEyN1KURa56EMFJ6enrC1tUVlZSWSkpKkLoeItER4eDgAIDY2FjU1NRJXQ6RdHspAoaOjo+wYeKVBRK3l6+sLMzMzlJWVIS0tTepyiLTKQxkoACA0NBQymQyZmZkcDyWiVtHT00NwcDAAXowQtdVDGyisrKzQt29fAMCJEyckroaItEX9p5upqakoLS2VuBoi7fHQBgqA46FE1HY9evSAm5sbamtrERcXJ3U5RFrjoQ4Uvr6+MDU1RWlpKdLT06Uuh4i0RMM5WIIgSFwNkXZ4qAMFx0OJqD0CAwNhYGCAwsJCZGdnS10OkVZ4qAMF8OeVxunTp1FWViZxNUSkDYyMjBAQEACAc7CIWuuhDxSOjo5wdXXleCgRtUn9xYhCoUBlZaXE1RBpvoc+UAAcDyWitvPw8IC9vT2qqqqgUCikLodI43WJQBEUFAR9fX1cvXoVFy5ckLocItICMpkMYWFhADjsQdQaXSJQNBwP5eRMImqt0NBQ6OjoIDs7GwUFBVKXQ6TRukSgADgeSkRtZ2FhgX79+gHgxQhRS7pMoPD09ISdnR2qqqqQmJgodTlEpCXqL0bi4uJ4gzyiB+gygaLheCivNIiotfr37w9zc3OUl5cjNTVV6nKINFaXCRTAnxuGZWdn4+rVq1KXQ0RaQFdXFyEhIQCA33//XeJqiDRXlwoUlpaWHA8lojarH/ZIS0tDSUmJtMUQaaguFSgAjocSUdt1794d7u7uEASBN8gjakaXCxS+vr4wMzNDWVkZ0tLSpC6HiLQEb5BH9GBdLlA0HA/lsAcRtVZAQADkcjmuXbuGrKwsqcsh0jh6UhcghfDwcBw4cACpqakoLS2FhYWF1CWRFlh5zxEG99qfwe/eqwVwRX0FUacyNDREYGAgYmJiEBMTA09PT6lLIi0gtt8AtKfv6HKfUACAg4MDevXqxQ3DiKhN6oc9EhMTcefOHYmrIdIsXTJQABwPJaK269WrF7p37467d+9ywzCi+3TZQBEYGAi5XI7CwkJkZ2dLXQ4RaQHeII+oeV02UBgaGnLDMCJqs/oNwy5evIj8/HypyyHSGF02UACq46HcMIw0zbp16+Dr6wtzc3OYm5sjNDQU+/bte+Bjqqqq8M9//hM9e/aEXC6Hu7s7vv76606quGswNzeHr68vAF6MkOaRst/okqs86rm7u8Pe3h6FhYVQKBQYPHiw1CURKTk5OWHVqlXw8PAAAGzYsAFRUVE4deoU+vbt2+RjpkyZgsLCQqxfvx4eHh64du0aqqurO7PsLiEsLAzJycmIi4vDY489Bj29Lt2VkgaRst/o0v8XyGQyhIeHY8eOHYiJiWGgII0yceJEle/fffddrFu3DnFxcU12DPv378fRo0dx4cIFWFtbAwBcXV07o9Qup1+/frCwsEBpaSlOnz6NgQMHSl0SEQBp+40uPeQBACEhIdDR0cGFCxdQUFAgdTnUBZSVlal8VVVVtfiYmpoaREdHo6KiAqGhoU0es3v3bgQGBmL16tVwdHSEl5cXXnnlFS5v7AC6urrK3wOHPaiztLXv6Ox+o8sHCgsLC/Tv3x8AOwbqHM7OzrCwsFB+rVy5stljU1NTYWpqCrlcjgULFmDnzp3w8fFp8tgLFy7g999/R1paGnbu3ImPP/4Y27Ztw3PPPddRL6VLq1/tkZ6ejps3b0pcDXUFre07pOo3uvSQR73w8HCkpKQox0N1dXWlLokeYrm5uTA3N1d+L5fLmz3W29sbycnJKCkpwfbt2zF79mwcPXq0yc6htrYWMpkMP/zwg/Lurx999BEmT56Mzz//HEZGRup/MV2Yvb09PDw8kJWVhdjYWERGRkpdEj3kWtt3SNVvdPlPKIC68VBzc3OUl5fj9OnTUpdDD7n62df1Xw8KFAYGBvDw8EBgYCBWrlwJPz8/rFmzpsljHRwc4OjoqHIr+T59+kAQBFy5ovm37dVG9SvFTpw4gdraWomroYdda/sOqfoNBgpwwzDSHoIgNDtuGh4ejvz8fNy6dUvZlpGRAR0dHTg5OXVWiV1KQEAADA0Ncf36dWRmZkpdDlGTOqvfYKD4Q/2VRlpaGkpKSqQthgjAkiVLcPz4cVy6dAmpqan45z//iSNHjuDJJ58EACxevBizZs1SHj9jxgzY2Nhg7ty5OHPmDI4dO4ZXX30VTz/9NIc7OohcLkdgYCCAuk8piKQmZb/BQPGH7t27w93dHYIgIDY2VupyiFBYWIiZM2fC29sbERERiI+Px/79+zF69GgAQEFBAXJycpTHm5qa4sCBAygpKUFgYCCefPJJTJw4EZ988olUL6FL4IZhpEmk7Dc4KbOB8PBwZGdn48SJE3jkkUcgk8mkLom6sPXr1z/w5998802jtt69e+PAgQMdVBE1xc3NDQ4ODigoKMDJkycxbNgwqUuiLkzKfoOfUDQQEBAAuVyOa9eucTyUiFql/gZ5AIc9qGtjoGjA0NBQOR7KyZlE1FrBwcHQ0dHBpUuXkJeXJ3U5RJJgoLgPx0OJqK3Mzc3h5+cHAPj9998lroZIGgwU9+nVqxccHBxw7949JCQkSF0OEWmJ+ouR+Ph43Lt3T+JqiDofA8V9ZDKZ8pa6HPYgotby8fGBpaUlKioqeIM86pIYKJpQv2EYx0OJqLW4YRh1dQwUTTA3N4evry8AdgxE1Hr1n26eOXMGxcXFEldD1LkYKJrRcDy0urpa4mqISBvY2dnBy8uLN8ijLomBohl9+/aFhYUFbt26xfFQImo1bhhGXRUDRTM4HkpE7TFw4EAYGhrixo0byMjIkLocok7DQPEA9eOh6enpuHnzpsTVEJE2MDAwwKBBgwDwYoS6FgaKB7C3t4enpyfHQ7XEzcoKfJX+Oyb9/CUqq3kfAJJO/bBHUlISKioqJK6GHkQQBCReu4xXft+GdalHpS5Hq3FzsBaEh4cjMzMTMTExeOSRR6CjwwymSWqFWsQUZGNTRgL2X07H3doaAMAvOWcQ1ctP4uqoq+rZsyccHR2Rl5eHhIQEDB8+XOqS6D5FlbewPesUojMTkFFyDQDgaGKJv/UdAl328+3CQNGCgQMHIjo6Gjdu3EBmZia8vb2lLokA5N8qwZasRGzOVCD31p/DUf2se2C6VxCGOXpKWB11dfU3yNu6dStiYmIYKDRETW0tjhdkYVNGAn7NOYN7f1yAGOrqY4Jrf0z3CoIOd5luNwaKFsjlcgQFBeH48eOIiYlhoJDQ3ZpqHMg9i+gMBY7mZ6BWEAAA5gaGeKyXP6Z5BqG/raPEVRLVCQkJwY4dO5CTk4Pc3Fw4OztLXVKXdeXWTWzOVGBzpgL5FaXKdj9bJ0zzDERUL3+YGxhKWOHDgYGiFcLDw3H8+HEkJSVh2rRpMDY2lrqkLiWz5BqiMxKwLTsJRZV/jkeHdu+FaV5BiOzZD0Z6+hJWSNSYqakp/P39kZiYiJiYGEybNk3qkrqUqppq/JpzBtEZCTiWnwUBdRcgFgZGeNx9AKZ7BcLHuofEVT5cGChawdXVFT169EB+fj4SEhIwbNgwqUt66FXcq8Kei6cRnamA4tplZbu9kRme8AzAVM9AuJnbSlghUcvCwsKQmJiI+Ph4TJo0Cfr6DL4d7dzNq4jOSMD27FO4WXVb2R7u4I7pXkF4xKUvDHkB0iEYKFpBJpMhPDxcOR7KQNExBEHAqRu5iM5Q4McLyaiovgsA0JXpIMLJG9O9gjDCyRt6OroSV0rUOj4+PrCyssLNmzeRnJyMoKAgqUt6KN26V4XdF1OwKSMBp67nKtu7G5tjqmcgpngGoKeZjYQVdg0MFK0UHByMHTt24PLly7hy5QqcnJykLumhUVxZgR3Zp7ApIwHnSwqV7a5mNpjmFYQnPAbC3thcwgqJ2kdHRwdhYWHYu3cvYmJiGCjUqG65Zw42ZSZgz8XTuP3HBYieTAejnPtgulcQhjt6ccVGJ2KgaCUzMzP4+fkhKSkJMTExmDp1qtQlabVaoRbH87MQnaHALzl/LveU6+phgmt/TPMKQoi9G2SccU1aLjQ0FHv37sW5c+dQVFQEGxteKYtx484tbM9OQnSGApml15TtvcxtMd0rCJM9BqKbkZmEFXZdDBRtEB4ejqSkJMTHx+Pxxx/neGg75N0qweZMBbZkKXDlVomy3dfGEdO8ghDl5gcLuZF0BRKpWbdu3eDt7Y3z58/jxIkTmDhxotQlaZ2a2loczc9E9B/LPauFuj1SjPT0MdHVF9O8ghBk15MXIBJjoGgDHx8fWFpaoqSkBCkpKQgMDJS6JK1wt6Yav+aexaaMBBzLy2ww29oQf+lVN9u6nw2Xe9LDa/DgwTh//jxiY2Mxfvx43iCvlXLLi7E5KxGbMxQouK263HP6HxcgZlzuqTEYKNpAR0cHoaGh2LdvH2JiYhgoWpBRUli33DPrFIqr/lzuGfbHcs9xXO5JXYS/vz+MjIxQVFSEc+fOwcfHR+qSNFZVTTV+uZyO6EwFjjdY7mkpN8bjvfwxzSsIPtYOEldJTWGgaKPw8HDs27cPZ8+eRXFxMaytraUuSaNU3KvC7ounEZ2RgMTrOcp2e2NzTPGoW+7pas4xZOpa6jcMO3r0KE6cOMFA0YSzxVcRnVm33LOkwXLPIT08MM0zCGNdfLjcU8MxULTR/eOhEyZMkLokyQmCgKTrudiUcRJ7Lp5WWe45yrm3crY1l3tSVzZ48GAcPXoUp06dQkVFBUxMTKQuSXLldyvx48UURGcokHyj8XLPqZ6BcDHjRZu2YKBoh7CwMGWgiIyM7LLjocWVFdienYRNGX9urgMAbvWzrd0Hws6Ys62JAMDZ2RlOTk64cuUK4uPjMXLkSKlLkoQgCFBcu4xNGQnYc+k07vyxM7CeTAejXfpgutcgDOvhyeWeWoiBoh3qNwwrKirC+fPn0adPH6lL6jT1m+tEZyTglyY215nmFYhgLvckaqT+BnmbN2/GiRMnulyguHHnFrZlJSE6MwFZpdeV7R4W3TDNs265p62RqYQVklgMFO1gYGCAoKAgHDt2DDExMV0iUNRvrrMlMxF5FSXKdm6uQ9R6gwYNwvbt25Gbm4ucnBy4uLhIXVKHqqmtxZG8DERnJuBAzlmV5Z6PuvliuucgBNi58ALkIcFA0U7h4eE4duzYQz0eWlVTjQM5Z+qWe3JzHSLR6jcMUygUiImJeWgDRU55sfICpOFyT39bZ0z3CsKjbr5c7vkQYqBop549eyrHQ0+ePIkRI0ZIXZLanL9ZiOjMBGzLSuLmOkRqFh4eDoVCgZMnT2LSpEkwMDCQuiS1qKy+h1/+uAD5vSBL2W4pN8Yk9wGY5hmEPtbdJayQOhoDRTvJZDKEhYVhy5YtiImJ0fpAUb+5TnSGAkn3Lfec6hGAqV6BXX5znSWr/wYz3fZfVZXXVOIbLFVjRaSNevfuDWtraxQXFyM5ORmDBg2SuiRRzhQXKHf3LL17BwAggwxDenhgulcQxrj4QK7bdf/UiO03AO3pO7rub1kN6jcM09bx0LrlnjnYmNH85jrDHD253JNIjeo3DPvpp58QExOjlYGi/G4lfryQgk2ZCUi5cUXZ3sPEAlM8AzHVIwDOXO7Z5TBQiGBqago/Pz8kJiZq1XhoUeUfs625uQ6RJOp3ID137hxu3LgBW1tbqUtqkSAIOFl4CdGZCfjpUqpyuae+ji7GuPhgmmcghnK5Z5fGQCFSeHg4EhMTcfLkSUyePFljNwyrqa3FsfxMRGcq8Ot9yz0nuvXHdK9B3FyHqJPY2Nigd+/eOHv2LE6cOIFHH31U6pKadf1OObZl1d1v5kLZDWW7p4UdpnsFYZLHANgYcrknMVCI1qdPH1hZWeHmzZtITk5GUFCQ1CWpqN9cZ0umAvkV922u4xmER3v5cbknkQTCw8OVgWLChAkadYO86toaHM3LxKaMBPyW++dyT2M9A0x088UMryAM7MblnqSKgUKk+vHQvXv3IiYmRiMCRXOb61gYGNXNtubmOkSS8/f3h7GxMW7evImzZ8+ib9++UpeEy+VF2JyhwOasRBTeLlO2D+zmgmlegXjUzQ+m+nIJKyRNxkChBvWB4uzZs5KOh9ZvrrMj+5TKck9urkOkefT19TFo0CAcOXIEMTExkgWKyup72Hc5HdGZCYgpyFa2W8mNMdljIKZ5BsHbyl6S2ki7MFCoga2tLXr37o1z584hNjYWEydO7LTnvnWvqm62dUYCN9ch0jKDBw/GkSNHkJycjFu3bsHUtPPmIpwpzsfGjATszE5WWe459I/lnqO7+HJPajv+a1GT8PBwnDt3DidOnMD48eM7dDy0fnOd6MwE7L7YeHOdaZ51u3tytjWRZnN2doaLiwtycnIQHx+PiIiIDn2+sruV+PFCMjZlJOB0UZ6y3dHEElM8AzDVMxBOplYdWgM9vBgo1KR+PLS4uBjnzp2Dj4+P2p+jpc11JnkM4HJPIi0TFhaGnJwcxMTEYOTIkWqf6CgIAuILLyI6Q4GfLqWisubP5Z5jXXww3SsIgx08eAFCojFQqImBgYHKeKi6AkVNbS2O5mdiU8bJJjfXmeYZhEAu9yTSWoMGDcK2bduQl5eHy5cvw9XVVS3nvXa7HFuzErE5U6Gy3NPLsm655+PuXO5J6sVAoUbh4eFqGw/l5jpEXYOJiQkGDhyIkydPIiYmRlSgqK6twZG8jD+We55DTYPlno+6+WK61yAM7ObMCxDqEAwUauTi4gJnZ2fk5ubi5MmTGDlyZJseX7+5TnRmAo7nc3Mdoq4iLCwMJ0+exMmTJ/HEE0+0ecOwS2VFdRcg9y33DOjmguleQZjo5gsTLvekDsZAoWbh4eGIjo5WbhjWmiuB+s11dlxIRkmD5Z5De3himmcgxvbsy9nWRA8xb29v2Nra4saNG0hKSkJISEiLj7lTfQ/7LqchOiMBJ65eULZby00w2aPufjNellzuSZ2Hf6XUrH489MqVK8jJyUHPnj2bPK65zXUcjC0w1Yub6xB1JfU3yNu9ezdiYmIeGCjSivKwKUOBXRdOofRuJYC65Z7DHD0xzSsIY5z7wIAXICQB/qtTMxMTEwwYMAAJCQmIiYlRCRSCICDh2mVEZyRgz6XTKpvrjP5jd09urkPUNYWGhmLPnj3IyMjA9evX0a1bN+XPSqvu4MeLdfebSW2w3NPJ1BJTPQMxxSMQjqaWElRN9CcGig4QHh6OhIQE5YZhpTVVfyz3VCC7wXJPTws7TPMKxCT3gbA14mxroq7M2toaffr0wZkzZxATE4OoqCjEFV5EdEbd7p5VNdUAAAMdXYx16Vu33LOHO3RkvAAhzcBA0QG8vb1hbW2N4uJiPPf9pzigU9Roc53pnkEIsOPmOkT0p8GDB+PMmTM4cOwIPqzOxMXyIuXPvC3tlcs9rQ1NJKySqGkMFGqWXXodmzMVSDWvgX2lAfIuXkJ1LxNurkNEzbpbU40DuWex5XoKoA/U6NWiLLcAJramiOrlj2legRhgy+WepNkYKNSg/G4l9lw6jS2ZiVBcuwwAMLQU4HjpLnreBt55+nkEuXlLXCURaZozxfnYnJmosqGfj7UcboVViHJwwuvTFnK5J2kNBop2qhVqEXf1IrZkJmLv5VTlBEsdmQwjHL0x1TMQ6RX7kZWZiaLzFwEGCiICcLPqNnZlJ2NLVqLKBEt7IzNM8hiIoUHd8d2nX6A4Owe6NQLADYJJSzBQtFHerRJszUrE1qxEXC4vVra7W3TDVM9ATHIfAHtjcwCAeUgJsjIzERcXh7Fjx/LjSqIuqqa2FsfyM7ElMxG/5KTjbm0NgD9XeE31DMQwR0/o6ehCEAT8am+PwsJCJCUlISwsTOLqiVqHgaIV7lTfwy856diSmYjj+VkQIAAATPXlmOjmi2megRjYrfEEy4CAAERHR6OgoOCB96QgoofTxbIb2JKZiG1ZSSq30PexdsAUj4AmJ1jKZDKEhITgxx9/RFxcHAMFaQ0GimYIgoCUG1ewJSsRP15IVt5ABgBCu/fCVM9ARPbsB2P95m+Ra2RkBD8/PygUCsTFxTFQEHUBFfeq8NOlVGzJVCC+8JKy3cLACI+5+2OaZyD62Tg+8BzBwcH48ccfkZGRgeLiYlhb8yZ3pPkYKO5z484t7Mg+hc2ZCpwvKVS2O5pYYrLHQEzxDEBPM5tWny8kJAQKhQIJCQmYPHkydHV1O6JsIpKQIAg4WXgJW7IU2HMxFber7wKom1NVfwv90S4+rb6Fvo2NDby8vJCRkYGTJ0/ikUce6cjyidSCgQLAvdoaHL5yHpszFTiYe055zwi5rh4e6dkX0zwDEe7QvhvI+Pj4wMzMDOXl5Thz5gz69++v7vKJSCL5FaXYnpWELVmJuNhgi3BXM5u6OVUeA9HDxKJd5w4ODkZGRgbnYJHW6NKBIqOk8I8lW0m4fueWst3P1gnTPOvuGWEhNxL1HLq6uggKCsKhQ4cQFxfHQEGk5apqqvFrzhlszlTgWH4maoW6OVV1N63rj6meQQiy6yk6AHAOFmmbLhcoyu5WYveFFGzOUuDU9Vxlu42hCSa5D8AUz0D0tlLvFuEhISE4dOgQUlJScOfOHRgZiQspRNT50oryEJ2pwK4LKSq7Agfbu2KqZyDGu/ZX6z0jOAeLtE2XCBS1Qi1OFFzA5kwFfr6cprwnvq5MBxFOdfeMGOncG/o6HTO/wcXFBQ4ODigoKEBSUhLCw8M75HmISL2KKyuwI/sUtmQl4kxxgbK9u7E5nvAIwBMeAehlYdthz885WKRNHupAkVtejC1/3DPiyq0SZbuXpR2megbicfcB6GZk1uF1yGQyBAcHY9euXYiLi2OgINJg1bU1OJqXic2ZChzIPYt7f9wzon5TrqlegRji4NEpuwJzDhZpk4cuUNypvoufL6djS6YCMQXZynYzfTmievljqmcg/G2dOn2CU8NlYEVFRbCxaf1KESLqePX78GzPSkLhnXJle38bR0z1DERULz9YyY07tSbOwSJt8lAECkEQkHQ9F1syFdh9MQXl96qUPxvs4IEpngEY17MvjPSav2dER7O2toaXlxfOnz+P+Ph4REZGSlYLEdVpah8eALCSG+Nx9wGY6hkAH+seElb45xys5ORkzsEijabVgeLa7XJsz07ClsxEZJZeU7Y7m1r9Mb45EM5mmnNDmODgYJw/fx5xcXEYN24cl4ERSaA1+/CMcu4Ng1beM6KjNZyDlZiYiMGDB0tdElGTOn4QUM3u1lRj3+U0zP1tA4K2rMS7in3ILL0GQ119PO4+AJvHPoOYya/ipQGjNCpMAMDAgQOhr6+PwsJCXL58ueUHUJe2bt06+Pr6wtzcHObm5ggNDcW+ffta9diYmBjo6enB39+/Y4vUInm3SvBx8kEM2f4Bpuz/L7ZlJ+FO9T24W3TDksBxSJiyGBtGz0Gkaz+NCRPAn7fiBoD4+HiJqyFNJ2W/oTn/17TgbPFVbMlSYEf2KRRVVijbB3ZzwRTPADzq5gdzA0MJK2yZkZER/P39kZCQgLi4OLi6ukpdEmkwJycnrFq1Ch4eHgCADRs2ICoqCqdOnULfvn2bfVxpaSlmzZqFiIgIFBYWNntcV9DefXg0zaBBg7Br1y5kZGTgxo0bsLXtuJUlpN2k7Dc0OlCUVN3GjxdSsCUrESk3rijbuxmZYpL7QEz1DISnpZ2EFbZdSEgIEhISkJCQgCeeeILLwKhZEydOVPn+3Xffxbp16xAXF/fAjmH+/PmYMWMGdHV1sWvXrg6uUvOoYx8eTdNwDtbJkyc5B4uaJWW/oXGBoqa2Fr8XZGFLZiL256Qr7xmhJ9PBKOc+mOoZgOFO3h12z4iO1qdPH5ibm6OsrAxpaWnw8/OTuiTqZGVlZSrfy+VyyOUPviFSTU0Ntm7dioqKCoSGhjZ73P/+9z9kZ2fj+++/x4oVK9RSr7ZQ9z48miYkJIRzsLq4tvYdnd1vaEyguFRWhK1/3DMiv+LPbX57W3XHVM8APNZrAGyNTCWsUD3ql4EdPHgQ8fHxDBRdkLOzs8r3y5Ytw/Lly5s8NjU1FaGhoaisrISpqSl27twJHx+fJo/NzMzEP/7xDxw/fhx6ehrzv3aH6sh9eDTNwIEDsXHjRuUcLA6Zdj2t7Tuk6jck7XVu37uLvZdSsTlLgbirF5XtFgaG+Esvf0zxDISvjeNDl8RDQkJw8OBBpKSk4Pbt2zA27ty17SSt3NxcmJubK79/0BWGt7c3kpOTUVJSgu3bt2P27Nk4evRoo86hpqYGM2bMwFtvvQUvL68Oq11TdMY+PJrG0NBQOQcrNjaWgaILam3fIVW/IROEP3a26SSCIEBx7TI2Zyqw5+JpVPyxza8MMgzt4YEpnoEY6+IDQz39ziyrUwmCgLfffhv5+fl46qmnMGTIEKlLogcoKyuDhYUFMrzehplu+yf+ltdUwitjKUpLS1U6hbYYNWoU3N3d8eWXX6q0l5SUwMrKSmVOTm1tLQRBgK6uLn799VeMHDmy3bVrAin24dE0aWlp+PTTT2FqaorVq1dzDpYGU1e/AYjvOzqr3+i0Tyiu3i7DtqwkbMlU4EKDbX57mlljikcAJnsEwNHUsrPKkVT9MrAdO3YgLi6OgYJaTRAEVFVVNWo3NzdHamqqStvatWtx6NAhbNu2DW5ubp1VolpJvQ+PpuEcLGqPzuo3OjRQVNVU40DuWWzJVOBIXoZym18jPX1McO2PKZ6BCLZ3fSjGN9tq0KBB2LlzJ7KysrgMjJq0ZMkSjBs3Ds7OzigvL0d0dDSOHDmC/fv3AwAWL16MvLw8fPvtt9DR0UG/fv1UHm9nZwdDQ8NG7dpAU/bh0TQN52DFxcUxUFAjUvYbHRIo0ovysTlTgZ0XknGzwTa/QXY9McUzEBPdfGGqxm1+tZGVlRW8vb1x7tw5xMfHY/z48VKXRBqmsLAQM2fOREFBASwsLODr64v9+/dj9OjRAICCggLk5ORIXKX6aOo+PJomNDQUBw8exOnTpzkHixqRst9Q2xyKm5UV2HkhGVsyE5FWnK9stzc2x2T3uiVb7hbd1PFUD43Y2Fh88803sLOzw9tvv93lO0pNpUlzKB42Le3DM9UzEI/07Aujh3hOVVtxDpZ20KQ5FJ1FLZ9QVNyrQvDW93D7jwmW+jq6GOPigykeARjm6Am9LjK+2VYDBgzAxo0bce3aNVy6dElrx7mJ2us/6cfxTsLPyu+dTa0wxTMAT3gEwMnUSsLKNBfnYJGmUkugMNGXY0gPD1y5dRNTPAPxWC9/WBuaqOPUD7X6ZWAnT55EXFwcAwV1OaOdffDBqQMY17MfpnoGIrS7W5ecU9VWnINFmkhtcyg+HTpNq25lqylCQkJw8uRJ5a24u8oNibTRZxHekMvbP15dVXUbyFBjQQ+BXha2SJn2JvuONrKyskLv3r1x9uxZzsHScGL7DUB7+g61XQqwQ2if3r17w8LCAhUVFUhLS5O6HKJOx76jfYKDgwEAcXFx6OTbCRE1iZ8tSkxXVxeDBg0CwK2Jiaj1BgwYAAMDA1y7dg0XL15s+QFEHYyBQgPUX2mcPn0aFRUVLRxNRFQ3B2vAgAEA6j6lIJIaA4UGcHZ2hpOTE6qrq5GYmCh1OUSkJUJCQgAACoUC1dXVEldDXR0DhYZoOB5KRNQanINFmoSBQkMMGjQIMpkM2dnZuH79utTlEJEW0NHRUc7B4sUISY2BQkNYWlqid+/eANgxEFHr1Q97cA4WSY2BQoPUdwzx8fFcBkZEreLk5AQnJyfU1NRAoVBIXQ51YQwUGmTAgAGQy+W4fv06Lly4IHU5RKQlGl6MEEmFgUKDyOVyLgMjojZrOAfr2rVrUpdDXRQDhYZpuAzs3r17EldDRNrAwsICffr0AcBPKUg6DBQaxtvbG5aWlrh9+zaXgRFRq3EOFkmNgULDcBkYEbWHv78/52CRpBgoNFD9lUZqaipu3bolcTVEpA04B4ukxkChgRwdHeHs7IyamhreipuIWo1zsEhKDBQaqv5W3LGxsRJXQkTaouEcrNTUVKnLoS6GgUJD1S8Du3jxIgoLC6Uuh4i0AOdgkZQYKDSUhYUFfHx8AHAZGBG1Xv2wR1paGudgUadioNBgXAZGRG3VcA4Wb8VNnYmBQoPVLwOrqqpCUVGR1OUQkZaovxjJz8+XuBLqSvSkLoCaZ2BggFdffRU9evSArq6u1OUQkZYIDQ2Fn58funXrJnUp1IUwUGg4Z2dnqUsgIi1jYmICExMTqcugLoZDHkRERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREoulJXQCRtphdMg2mBrJ2P/7WXQGfqLEeItJ8YvsNQHv6Dn5CQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREGmrdunXw9fWFubk5zM3NERoain379jV7/I4dOzB69Gh069ZNefwvv/zSiRUTkdSk7DcYKIg0lJOTE1atWgWFQgGFQoGRI0ciKioK6enpTR5/7NgxjB49Gj///DMSExMxYsQITJw4EadOnerkyolIKlL2GzJBEASxL4DoYVZWVgYLCwskTpfB1EDW7vPcuisgYJOA0tJSmJubt+sc1tbWeP/99zFv3rxWHd+3b19MnToVS5cubdfzEVH7qKvfAMT3HZ3Vb+i1uTIiEqWsrEzle7lcDrlc/sDH1NTUYOvWraioqEBoaGirnqe2thbl5eWwtrZud61EpDna2nd0dr/BIQ+iTubs7AwLCwvl18qVK5s9NjU1FaamppDL5ViwYAF27twJHx+fVj3Phx9+iIqKCkyZMkVdpRORhFrbd0jVb/ATCqJOlpubq/Kx5YOuMLy9vZGcnIySkhJs374ds2fPxtGjR1vsHDZt2oTly5fjxx9/hJ2dndpqJyLptLbvkKrf4BwKohZo0hyKUaNGwd3dHV9++WWzx2zevBlz587F1q1bMX78+PaWS0QiaNIcis7qNzjkQaRFBEFAVVVVsz/ftGkT5syZg40bNzJMEBGAzus3OORBpKGWLFmCcePGwdnZGeXl5YiOjsaRI0ewf/9+AMDixYuRl5eHb7/9FkBdpzBr1iysWbMGISEhuHr1KgDAyMgIFhYWkr0OIuo8UvYb/ISCSEMVFhZi5syZ8Pb2RkREBOLj47F//36MHj0aAFBQUICcnBzl8V9++SWqq6vx3HPPwcHBQfm1cOFCqV4CEXUyKfsNzqEgaoEmzaEgIu2gSXMoOgs/oSAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiERjoCAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiERjoCAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiERjoCAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiERjoCAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiETTk7oAIm0xYfBC6BjJ2/342jtVwKaP1VcQEWk8sf0GoD19Bz+hICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiDbVu3Tr4+vrC3Nwc5ubmCA0Nxb59+x74mKNHjyIgIACGhobo1asXvvjii06qlog0gZT9BgMFkYZycnLCqlWroFAooFAoMHLkSERFRSE9Pb3J4y9evIjIyEgMGTIEp06dwpIlS/DCCy9g+/btnVw5EUlFyn5DJgiCIPYFED3MysrKYGFhge4fPAuZkbzd5xHuVOHqK+tQWloKc3Pzdp3D2toa77//PubNm9foZ6+//jp2796Ns2fPKtsWLFiAlJQUxMbGtrtuImo7dfUbgPi+o7P6Db02V0bUxRgYGKB79+64+so60efq3r07KisrVdrkcjnk8gd3ODU1Ndi6dSsqKioQGhra5DGxsbEYM2aMStvYsWOxfv163Lt3D/r6+uKKJ6JWU2e/AbSv7+jsfoOBgqgFhoaGuHjxIu7evSv6XKtXr4a9vb1K27Jly7B8+fImj09NTUVoaCgqKythamqKnTt3wsfHp8ljr1692ujc9vb2qK6uxo0bN+Dg4CC6fiJqHXX2G0Db+g6p+g0GCqJWMDQ0hKGhoejzvPnmm3jttddU2h50heHt7Y3k5GSUlJRg+/btmD17No4ePdps5yCTyVS+rx/RvL+diDqeuvoNoG19h1T9BgMFUSdqzfBGQwYGBvDw8AAABAYGIiEhAWvWrMGXX37Z6Nju3bvj6tWrKm3Xrl2Dnp4ebGxsxBVORJJqS98hVb/BVR5EWkQQBFRVVTX5s9DQUBw4cECl7ddff0VgYCDnTxB1YZ3VbzBQEGmoJUuW4Pjx47h06RJSU1Pxz3/+E0eOHMGTTz4JAFi8eDFmzZqlPH7BggW4fPkyXnrpJZw9exZff/011q9fj1deeUWql0BEnUzKfoNDHkQaqrCwEDNnzkRBQQEsLCzg6+uL/fv3Y/To0QCAgoIC5OTkKI93c3PDzz//jBdffBGff/45evTogU8++QSTJk2S6iUQUSeTst/gfSiIiIhINA55EBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJ9v+sUWrnDwVq0wAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "Interior angles found: [89.83847705650136, 88.78833801117518]\n", + "Interior angles found: [89.75197989966416, 89.19788105500966]\n", + "Final angles found: [88.78833801117518, 89.19788105500966]\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [88.78833801117518, 89.19788105500966]\n", + "(3, 4) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 7\n", + "Adjacent strokes (list): [3]\n", + "Adjacent strokes (uniques): {3}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 8\n", + "Adjacent strokes (list): [4]\n", + "Adjacent strokes (uniques): {4}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 9\n", + "Adjacent strokes (list): [4, 7, 4]\n", + "Adjacent strokes (uniques): {4, 7}\n", + "Checking edge: (4, 7)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [78.26155769686821]\n", + "(4, 7) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 10\n", + "Adjacent strokes (list): [4, 0, 4, 0]\n", + "Adjacent strokes (uniques): {0, 4}\n", + "Checking edge: (0, 4)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "Interior angles found: [89.70671191496507, 89.56623033507175]\n", + "Interior angles found: [89.84379058832397, 89.42915166171285]\n", + "Final angles found: [89.56623033507175, 89.42915166171285]\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [89.56623033507175, 89.42915166171285]\n", + "(0, 4) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 11\n", + "Adjacent strokes (list): [4, 5, 4]\n", + "Adjacent strokes (uniques): {4, 5}\n", + "Checking edge: (4, 5)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([2, 1])\n", + "angles: [87.60977577529626]\n", + "(4, 5) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 12\n", + "Adjacent strokes (list): [5]\n", + "Adjacent strokes (uniques): {5}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 13\n", + "Adjacent strokes (list): [2, 6, 2, 6]\n", + "Adjacent strokes (uniques): {2, 6}\n", + "Checking edge: (2, 6)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "Interior angles found: [47.16443370903167, 48.92275878691167]\n", + "Interior angles found: [59.79419820769666, 61.55252328557668]\n", + "Final angles found: [47.16443370903167, 59.79419820769666]\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [47.16443370903167, 59.79419820769666]\n", + "(2, 6) already in graph, angles = [84.23886881283048, 80.16976627731358]\n", + "(2, 6) already in graph, angles updated = [84.23886881283048, 80.16976627731358, 47.16443370903167, 59.79419820769666]\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 14\n", + "Adjacent strokes (list): [4, 6, 6, 4]\n", + "Adjacent strokes (uniques): {4, 6}\n", + "Checking edge: (4, 6)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 4\n", + "Interior angles found: [87.26341801197296, 86.2834611843536]\n", + "Interior angles found: [89.6026063905527, 88.62264956293333]\n", + "Final angles found: [86.2834611843536, 88.62264956293333]\n", + "connectivity: 2\n", + "Counter values: dict_values([2, 2])\n", + "angles: [86.2834611843536, 88.62264956293333]\n", + "(4, 6) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 15\n", + "Adjacent strokes (list): [4]\n", + "Adjacent strokes (uniques): {4}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 16\n", + "Adjacent strokes (list): [1, 6, 6]\n", + "Adjacent strokes (uniques): {1, 6}\n", + "Checking edge: (1, 6)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 2])\n", + "angles: [89.2861856598184]\n", + "(1, 6) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 17\n", + "Adjacent strokes (list): [7]\n", + "Adjacent strokes (uniques): {7}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 18\n", + "Adjacent strokes (list): [8, 4, 4]\n", + "Adjacent strokes (uniques): {8, 4}\n", + "Checking edge: (8, 4)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "angles_gdf len 3\n", + "connectivity: 1\n", + "Counter values: dict_values([1, 2])\n", + "angles: [87.79139488488063]\n", + "(8, 4) added\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 19\n", + "Adjacent strokes (list): [6]\n", + "Adjacent strokes (uniques): {6}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 20\n", + "Adjacent strokes (list): [1]\n", + "Adjacent strokes (uniques): {1}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 21\n", + "Adjacent strokes (list): [9]\n", + "Adjacent strokes (uniques): {9}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 22\n", + "Adjacent strokes (list): [0]\n", + "Adjacent strokes (uniques): {0}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 23\n", + "Adjacent strokes (list): [2]\n", + "Adjacent strokes (uniques): {2}\n", + "**************************************************************\n", + " \n", + " \n", + "\n", + "Node: 24\n", + "Adjacent strokes (list): [6]\n", + "Adjacent strokes (uniques): {6}\n", + "**************************************************************\n", + " \n", + " \n", + "\n" + ] + } + ], "source": [ "for n in graph.nodes:\n", "\n", @@ -537,7 +2066,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -584,7 +2113,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -606,7 +2135,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -620,7 +2149,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -645,9 +2174,1800 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "m = points_strokes_primal.explore(\n", " tiles=\"cartodb.positron\",\n", From f87e14c813f4c9883cd3728a1653743555ddd3e6 Mon Sep 17 00:00:00 2001 From: anvy Date: Wed, 14 May 2025 13:43:36 +0200 Subject: [PATCH 13/27] run clse nb --- momepy/stroke_graph_clse.pickle | Bin 0 -> 6996 bytes momepy/strokegraph_clse.ipynb | 331 ++++++++++++++------------------ 2 files changed, 143 insertions(+), 188 deletions(-) create mode 100644 momepy/stroke_graph_clse.pickle diff --git a/momepy/stroke_graph_clse.pickle b/momepy/stroke_graph_clse.pickle new file mode 100644 index 0000000000000000000000000000000000000000..cf7f1b22cbf23aa4cfa9eac63b3805fa2216aac9 GIT binary patch literal 6996 zcma)B30M=?7S2LKSfq$j7ql)#iW@#bo}jesrV>F4iW?e37&D2G#4G|Tu57}52z3y( zF1S#!xIJxa)%sO!KWi6J5m2dC)Q3VTuWDT%t-f<7Gm{|%p7V(}|J*z0-us{b+qf(KkFo0!3L^Xjj)s&^j&>ev~h+JQg zPbPp#A;AwJcDSFv^Qo(Vor^B7 z@dq5ej9l^<@MpJzwk873S-tMUQ^1>QUi;4i>|g!BaacxB_|Jtmr{n@2EUqbj7jVIW ziWm8SUkC@R`3K;VTWyLmz{~etnJ^RZSnO-R6MzYy<~{t(pl}D5{PAso$y_uS36`qD z2kV_K$NYX@g z#E?ef-jSYsJ~R)%@yUKa7~y+&S7&WxN5szr_t2i}E2n(4*QH`A1BQ_@5z&WftphtslX|Jz zlts!UY)gewiOhrM`qC|R1{1DR>9mS8)D-u``xAmi9C6}<>`C*&^PR!giU%d$tUBt^!=T0^Cylqn9TLQPHu#z5uXoXt{h^EJmT#d&R}c zDAZod1pBT7j@1~WvH|nI{V@AJ;J}dG#ub36(87K3(bjN5dPkS5rQo^I*!v*(4 z(!|HJF(T=^!nG2H+FaY9+Qpg<3AHEknSiG6(!anHZlc6W}qRlh{Z}k(cOr!tXOI;=&W8Ve*QnO;d(=nq>lx zntC&HK&vCArjd-AJfLcAVAc35z|NDsG@xp)G(jCnrn^60oyLjcGQCQ40O3z3f>^Pe1|T(Q%i<4%4<1v-SOkTFHb>N z7Smj{FfF>Og?)xq%M|y};+#WBE&Dzn(eAW79I2)0A-W#XYLS3i92m8@M+;^Iq{mv- zGRtDYEE96nB4Xyis3lTOEj(hlZ%d7+V2t@kQ2*sC{+}Iy`Pc@2>?-ovZ8NwkO?Mjw z`j|29A0+{vdU56j6v%_TzMLinyi#shi2|2Hb$@yo4s^*33k?HZh+<(b*(D&`-utN? zt!4EQ3yLdPlU$0K7F{W3pJ6CoQ~EME`Qmy+F}=$mis?-SC>B9LI&uTDwqQnWQe(W8 z;u(Dl3y)23Hp?716f=tpySzufq$oyvv})V7g41HUvVWQh`18#{ zl^VchZH)`p0^XIQ@>mFX$nU;krGSsLh@K?_woP-Y47VSPAzFqvru!yAeaZV>RHFwfC4gBnEJPMfJU_5CRj>GEy5WTb*5;b=z^3sj1#Gccvo!Ytfc?}Zif2m?+2#kMEVzH<<%qL}N#~)#UZC%Krl%dd>rV3HSw?k3y z$#Og#OwRga_@p?y6frHjQp7&PP=pVgc7Oe&2B3)Um4_(0`7^pM0!4hFhz}I;7>dgM zUzUg;%(PNOTQJMS9EuqCTPbR#C_>Sc@UcO;3{)i#_Av~EJ*;N4;A|G)!5*t{PryfW zUda`J1;=ug|AqNEc`tdf0It%kKqH7r0zVFO=+FboOXv>o*|@R+py)=4Tpa zH<@LQ9G5eP7pu#sQZ7fE!s*e`cQ!y&4EEpBj?Q0>p>vbB1Acxiy4M`QCr?THR09^B z+Zizrugzf%d8nwDkIF7(OpC6RvClA+sdT3UA2^(O^C+2= zvoiT~31=apEtqAJH>AvVFDM*d?27h+l1F2E>0v&_L#`*D1Z+B#IhR0`+2rMRC_~2) zbal6|^a-uooDU{q{6mos zN|x)te`kvm1nPWGmv35NelH>>w7UX+9-zy<4|wO2rS$5Vnxs*`ags=R zlk=y|m;N-H2?x0%Rl~mfu^d6rNogb%vuKB74*$$SpUHOF+?IOhfnIc^UPz&R8s3fpXu}(LfvY8zGrMxEqx24-Q4pS7_wMu&=@r6 zge2o@MnN$jo%P|cRWUNjRoXkk(w%}%ntQg*q?&AE*`4iA;sdkPPbagssh0sg+h)#{ z>?zV}TR@MS=BeN9*KR|Dlej!3xfM5!*3-9uCn`Jbxj!aHVl$#{``hYs{E})-RQE{QAKKAWZrKvtorPbW^1bl(mMNP%XFtDqpydvw(Stq#dh}uIdoR`-VwK4 zR{3;N_JL{osa4I)`b7CCF|mE5Ynha*|4ywipcYLTsGanN)V}fb2RBL^XDe7A$^@Eh z)CFIoK!u&Kv$g!@VYfg%$GwbTHalwOzI8S8?!WxVGIKOd)S*nM*@-%*60Ob(vh9pX zXV~P$8uOjK+$lGqqAwP8L7i}V?t(d2u&0Rby6ALBfG+F^$#(cm0?VeWR@*j_?Lo|& z<~54RttjrEH-=sskz|c*D#_|R7u&_kwts4Kw-<2#+#Xvs@ezICL6Hqa$s9DtfHNaC zG0;gaB@oRiRPZ%vP*AxsG^?hXq47Y)980tFR6SZ0K*j#(o" ], "text/plain": [ - "" + "" ] }, - "execution_count": 68, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -947,7 +902,7 @@ ], "metadata": { "kernelspec": { - "display_name": "momepy_dev", + "display_name": "simplification", "language": "python", "name": "python3" }, @@ -961,7 +916,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.10" + "version": "3.11.9" } }, "nbformat": 4, From be863d3c182bfd5a4edc9b567286593ed3f7958c Mon Sep 17 00:00:00 2001 From: anvy Date: Wed, 14 May 2025 14:08:35 +0200 Subject: [PATCH 14/27] add comparison notebook --- momepy/strokegraph_compare.ipynb | 455 +++++++++++++++++++++++++++++++ 1 file changed, 455 insertions(+) create mode 100644 momepy/strokegraph_compare.ipynb diff --git a/momepy/strokegraph_compare.ipynb b/momepy/strokegraph_compare.ipynb new file mode 100644 index 00000000..33eeb55a --- /dev/null +++ b/momepy/strokegraph_compare.ipynb @@ -0,0 +1,455 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "66901d81", + "metadata": {}, + "source": [ + "# Checking whether we're getting the same results" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "b411a245", + "metadata": {}, + "outputs": [], + "source": [ + "import pickle\n", + "import networkx as nx" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "b57b27f8", + "metadata": {}, + "outputs": [], + "source": [ + "with open('stroke_graph_anvy.pickle', 'rb') as handle:\n", + " G_anvy = pickle.load(handle)\n", + "with open('stroke_graph_clse.pickle', 'rb') as handle:\n", + " G_clse = pickle.load(handle)" + ] + }, + { + "cell_type": "markdown", + "id": "a17bf072", + "metadata": {}, + "source": [ + "Manually checking: edge attributes?" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cf78ba7a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'geometry': ,\n", + " 'angles': [36.134980718680936]}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G_anvy.edges[(0,9)]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "915e4cab", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'geometry': ,\n", + " 'number_connections': 1,\n", + " 'angles': [36.134980718680936]}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G_clse.edges[(0,9)]" + ] + }, + { + "cell_type": "markdown", + "id": "c712de5e", + "metadata": {}, + "source": [ + "@csebastiao is the `number_connections` used for any of the metrics, or just a nice-to-have metric in itself?" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "af4d762b", + "metadata": {}, + "outputs": [], + "source": [ + "# make sure we have the same edges\n", + "assert list(G_anvy.edges) == list(G_clse.edges), \"Edges differ\"" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "afbcc5f1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Edge (0, 2)\n", + "Angles equal\n", + "\n", + "\n", + "Edge (0, 9)\n", + "Angles equal\n", + "\n", + "\n", + "Edge (0, 3)\n", + "Angles differ:\n", + "[29.3960283634]\n", + "[27.9586406474]\n", + "\n", + "\n", + "Edge (0, 1)\n", + "Angles differ:\n", + "[89.7456019245, 89.7526780498]\n", + "[88.8925817012, 89.7526780498]\n", + "\n", + "\n", + "Edge (0, 4)\n", + "Angles differ:\n", + "[89.4291516617, 89.5662303351]\n", + "[63.1494214841, 63.2766055722]\n", + "\n", + "\n", + "Edge (1, 8)\n", + "Angles differ:\n", + "[70.0411369582]\n", + "[61.6127991329]\n", + "\n", + "\n", + "Edge (1, 3)\n", + "Angles differ:\n", + "[89.5308449728, 89.5858181738]\n", + "[83.0252283916, 89.5858181738]\n", + "\n", + "\n", + "Edge (1, 6)\n", + "Angles equal\n", + "\n", + "\n", + "Edge (2, 9)\n", + "Angles equal\n", + "\n", + "\n", + "Edge (2, 3)\n", + "Angles differ:\n", + "[34.2514380149]\n", + "[35.6888257308]\n", + "\n", + "\n", + "Edge (2, 6)\n", + "Angles differ:\n", + "[47.164433709, 59.7941982077, 80.1697662773, 84.2388688128]\n", + "[47.164433709, 59.7941982077, 59.7941982077, 88.6015042934]\n", + "\n", + "\n", + "Edge (3, 9)\n", + "Angles differ:\n", + "[88.08366042]\n", + "[89.5210481359]\n", + "\n", + "\n", + "Edge (3, 4)\n", + "Angles differ:\n", + "[88.7883380112, 89.197881055]\n", + "[71.9046849747, 74.1965981362]\n", + "\n", + "\n", + "Edge (4, 7)\n", + "Angles equal\n", + "\n", + "\n", + "Edge (4, 5)\n", + "Angles equal\n", + "\n", + "\n", + "Edge (4, 6)\n", + "Angles differ:\n", + "[86.2834611844, 88.6226495629]\n", + "[76.6579161543, 89.3460577129]\n", + "\n", + "\n", + "Edge (4, 8)\n", + "Angles differ:\n", + "[87.7913948849]\n", + "[87.7690220602]\n", + "\n", + "\n" + ] + } + ], + "source": [ + "for edge in G_anvy.edges:\n", + " assert G_anvy.edges[edge][\"geometry\"] == G_clse.edges[edge][\"geometry\"], \"Geoms differ\"\n", + " print(f\"Edge {edge}\")\n", + " angles_anvy = [round(angle, 10) for angle in sorted(G_anvy.edges[edge][\"angles\"])]\n", + " angles_clse = [round(angle, 10) for angle in sorted(G_clse.edges[edge][\"angles\"])]\n", + " if angles_anvy == angles_clse:\n", + " print(\"Angles equal\")\n", + " else:\n", + " print(\"Angles differ:\")\n", + " print(angles_anvy)\n", + " print(angles_clse)\n", + " print(\"\\n\")\n", + " #assert sortedG_anvy.edges[edge][\"angles\"] == G_clse.edges[edge][\"angles\"], \"Angles differ\"" + ] + }, + { + "cell_type": "markdown", + "id": "2b8ec8cc", + "metadata": {}, + "source": [ + "@csebastiao re the above. WHY :D " + ] + }, + { + "cell_type": "markdown", + "id": "4d35c3bc", + "metadata": {}, + "source": [ + "Checking nodes" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "029e919b", + "metadata": {}, + "outputs": [], + "source": [ + "assert list(G_anvy.nodes) == list(G_clse.nodes), \"Nodes differ\"" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "e7a7bf17", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'edge_indeces': [0, 3, 15, 27],\n", + " 'geometry': ,\n", + " 'geometry_stroke': ,\n", + " 'x': 1603374.6625343116,\n", + " 'y': 6464077.898491419,\n", + " 'connectivity': 8,\n", + " 'degree': 5,\n", + " 'betweenness_centrality': 0.13657407407407404,\n", + " 'closeness_centrality': 0.6923076923076923,\n", + " 'connectivity_computed': 8,\n", + " 'access': 3,\n", + " 'length': 839.5666838320316,\n", + " 'spacing': 104.94583547900395,\n", + " 'orthogonality': 68.74678997354196}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G_anvy.nodes[0]" + ] + }, + { + "cell_type": "markdown", + "id": "008c3f19", + "metadata": {}, + "source": [ + "@csebastiao: `connectivity_computed` can be ignored (we can later drop it entirely, was just a sanity check)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "829d8185", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'n_segments': 8,\n", + " 'geometry_stroke': ,\n", + " 'edge_ids': array([ 0, 3, 15, 27]),\n", + " 'geometry': ,\n", + " 'x': array('d', [1603374.6625343116]),\n", + " 'y': array('d', [6464077.898491419]),\n", + " 'length': 839.5666838320316,\n", + " 'stroke_betweenness': 0.13657407407407404,\n", + " 'stroke_closeness': 0.6923076923076923,\n", + " 'stroke_degree': 5,\n", + " 'stroke_connectivity': 8,\n", + " 'stroke_access': 3,\n", + " 'stroke_orthogonality': 61.889319613560986,\n", + " 'stroke_spacing': 104.94583547900395}" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G_clse.nodes[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "66b889d6", + "metadata": {}, + "outputs": [], + "source": [ + "# k:v is anvy:clse naming of node attrs\n", + "metrics_map = {\n", + " \"degree\": \"stroke_degree\",\n", + " \"betweenness_centrality\": \"stroke_betweenness\",\n", + " \"closeness_centrality\": \"stroke_closeness\",\n", + " \"connectivity\": \"stroke_connectivity\",\n", + " \"access\": \"stroke_access\",\n", + " \"spacing\": \"stroke_spacing\",\n", + " #\"orthogonality\": \"stroke_orthogonality\"\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "7f661ee2", + "metadata": {}, + "outputs": [], + "source": [ + "for n in G_anvy.nodes:\n", + " assert G_anvy.nodes[n][\"x\"] == G_clse.nodes[n][\"x\"][0], \"x coords differ\"\n", + " assert G_anvy.nodes[n][\"y\"] == G_clse.nodes[n][\"y\"][0], \"y coords differ\"\n", + " assert G_anvy.nodes[n][\"geometry\"] == G_clse.nodes[n][\"geometry\"], \"geometries differ\"\n", + " assert G_anvy.nodes[n][\"geometry_stroke\"] == G_clse.nodes[n][\"geometry_stroke\"], \"geometry_stroke differ\"\n", + " assert G_anvy.nodes[n][\"edge_indeces\"] == list(G_clse.nodes[n][\"edge_ids\"]), \"Edge IDs differ\"\n", + " assert G_anvy.nodes[n][\"length\"] == G_clse.nodes[n][\"length\"]\n", + " for k, v in metrics_map.items():\n", + " assert round(G_anvy.nodes[n][k], 10) == round(G_clse.nodes[n][v], 10), f\"{k} differ\"\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "d834bb01", + "metadata": {}, + "source": [ + "@csebastiao we get the same metrics everywhere but orthogonality (which i guess makes sense cause the angles are off?)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "d922e80c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0: orthos differ\n", + "68.7467899735\n", + "61.8893196136\n", + "1: orthos differ\n", + "86.3237109565\n", + "83.6925485182\n", + "2: orthos differ\n", + "60.6750720203\n", + "58.8531289111\n", + "3: orthos differ\n", + "72.6905727159\n", + "67.4115491701\n", + "4: orthos differ\n", + "87.2833822408\n", + "76.9079599519\n", + "5: same ortho\n", + "6: orthos differ\n", + "76.5085090591\n", + "72.9492134207\n", + "7: same ortho\n", + "8: orthos differ\n", + "78.9162659216\n", + "74.6909105965\n", + "9: orthos differ\n", + "59.3502878479\n", + "59.8294170866\n" + ] + } + ], + "source": [ + "for n in G_anvy.nodes:\n", + " ortho_anvy = round(G_anvy.nodes[n][\"orthogonality\"], 10)\n", + " ortho_clse = round(G_clse.nodes[n][\"stroke_orthogonality\"], 10)\n", + " if ortho_anvy == ortho_clse:\n", + " print(f\"{n}: same ortho\")\n", + " else:\n", + " print(f\"{n}: orthos differ\")\n", + " print(ortho_anvy)\n", + " print(ortho_clse) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fe17ccd0", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "simplification", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From d22ffe87b84314b61673fdc332b67719a1825c14 Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Tue, 27 May 2025 13:34:45 +0200 Subject: [PATCH 15/27] solve angle issue in clse --- momepy/stroke_graph_anvy.pickle | Bin 5777 -> 5778 bytes momepy/stroke_graph_clse.pickle | Bin 6996 -> 6998 bytes momepy/strokegraph_anvy.ipynb | 1225 ++++++++++++++++-------------- momepy/strokegraph_clse.ipynb | 362 +++++---- momepy/strokegraph_compare.ipynb | 542 ++++++++++--- 5 files changed, 1352 insertions(+), 777 deletions(-) diff --git a/momepy/stroke_graph_anvy.pickle b/momepy/stroke_graph_anvy.pickle index 7457414f895b1863b8ae6ccfd37c3e52bcc8d072..f7ee96c82bc7e1f735a6e1b03ce03a09d4bf42d3 100644 GIT binary patch delta 27 icmbQJJ4u(Nfpu#8MwV(O4zaw_+=5EI_|0uh+#&#dUI>!_ delta 26 hcmbQFJ5iUVfpu!zMwV(OcG0}j+=5EI&FxIwA^>zH2r>Ww diff --git a/momepy/stroke_graph_clse.pickle b/momepy/stroke_graph_clse.pickle index cf7f1b22cbf23aa4cfa9eac63b3805fa2216aac9..e81dfeae6462499bf4304de72e988f5ed9920fb5 100644 GIT binary patch delta 348 zcmca&cFl~Xfpx0)M3#vhVtJ*x1(ka78|PRsatK2?n{P9&XJr2!s*`bAKXCIz<}fDq z+S?lIwoeJ&{Ek(fiT&S>o9!*>02-T3=hUIYB6Zk-dp0RW>QrcJg-N zFt(OhrH|Y5Cku;YN$otLA!nNs<}jsgO3;)H(F|W_4sF&Bi}L8O$OE z;N+hovFtWMhOs{r!#2l?>N2t|EBq*@uP}LnShy6|$*cvQ{GrH3EOJaJzRMLdnNhrh zP5HI;#wgaw{o<)o);w;CB}OQgz5U=Ly2>YPGoOSKqvRjCL@Sj^C?;*o>aD%0KG{<; Sj7`^Qx7o5!o0m$iX9NHQSb`=1 delta 351 zcmca+cEyaPfpx0qM3#x{qIspc1(kXm=UOnb3qjbM?=r4uWIyqJzU9@Aew!yVhcU5t zOS5hddK0qw1FJd{yMQZGh;gp(W;u=+M)pe`A(z5#1#E8Qu43O7G9 z`@v01U+%XF+PsP{o{2p`Rpg=hnxM@BfRXj|uKr!d)n@=TFv_A60ajSJ5C zP5vzs%id?v9X|J9$mV!aT}Jkq{+xx{HykJ5k&v0ZUd&2riRxYMdbKcQbJqA2c&>Qr zJDFL$gH869`>lw?$rHs>rQ$Lp1*Y}{A*@69_W;WM%h55(L%O%${0stnbgv9^= diff --git a/momepy/strokegraph_anvy.ipynb b/momepy/strokegraph_anvy.ipynb index eab508ec..869f2139 100644 --- a/momepy/strokegraph_anvy.ipynb +++ b/momepy/strokegraph_anvy.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -29,7 +29,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ @@ -59,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -89,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -100,7 +100,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -192,7 +192,7 @@ "4 5 4 " ] }, - "execution_count": 5, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -228,12 +228,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -253,7 +253,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 27, "metadata": {}, "outputs": [ { @@ -348,7 +348,7 @@ "4 POINT (1603264.658 6463848.976) 4 " ] }, - "execution_count": 7, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -370,7 +370,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -480,7 +480,7 @@ "4 [7, 8, 9, 13, 21, 22, 24] " ] }, - "execution_count": 8, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -496,12 +496,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 29, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtUAAAMWCAYAAAA+uHrFAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3xUZdYH8N+dmt57DwRSSWhJCBB6kSaKiOCKuq5usYG+6+6+W1xXd3W7oL7qusWCq4KIiqBSBQIEUkhCEpIQ0nvvZSYzc98/AhOeSa935s75fj5+3Htyb+bIhuTkmfOch+N5ngchhBBCCCFkzCRCJ0AIIYQQQoipo6KaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGSTeQn02q16OnpmchPSciIyOVySKVSodMghBBCiJmakKKa53lUV1ejubl5Ij4dIWPi4OAADw8PcBwndCqEEEIIMTMTUlTfKqjd3NxgZWVFRQ2ZUjzPo7OzE7W1tQAAT09PgTMihBBCiLkZd1Gt1Wr1BbWzs/NE5ETIqFlaWgIAamtr4ebmRq0ghBBCCJlS496oeKuH2srKatzJEDIet74Gqa+fEEIIIVNtwqZ/UMsHERp9DRJCCCFEKDRSjxBCCCGEkHGioloAAQEB2LNnj9BpDOi9996Dg4OD0GkQQgghhJiUSS+qq6ursWvXLgQFBcHCwgLu7u5YvHgx3n77bXR2dk72y08YYy6EjTk3AFi2bBl2797NXHMcB47joFQq4e3tjU2bNuHQoUPCJUkIIYQQMg6TWlQXFhZizpw5OH78OF5++WWkpaXh5MmTeOaZZ/DVV1/h5MmTk/nyw+J5HhqNRtAcpopWq4VOpxM6Db3HHnsMVVVVuHHjBj777DOEhYVh+/bt+OEPfyh0aoQQQgghozapRfXjjz8OmUyGlJQUbNu2DaGhoZg1axbuueceHD16FJs2bdLf29LSgh/+8Idwc3ODnZ0dVqxYgYyMDP3HX3jhBcyePRv79u1DQEAA7O3tsX37drS1tenv4Xkef/7znzFt2jRYWloiKioKBw8e1H/8zJkz4DgOx44dw/z586FUKpGQkICCggJs3rwZ7u7usLGxQXR0NFPwL1u2DCUlJXjmmWf0K6y3XLx4EUuWLIGlpSV8fX3x9NNPo6OjQ//x2tpabNq0CZaWlggMDMR///vfMf1ZvvDCC/Dz84NSqYSXlxeefvrpIXO71cZx5MgRhIWFQalUoqSkBE1NTXjwwQfh6OgIKysrrFu3Dvn5+YO+bkNDA2JiYnDnnXeiu7t72D/jkbKysoKHhwd8fX2xYMEC/OlPf8I//vEP/POf/9T/2avVajz55JPw9PSEhYUFAgIC8Morr4zhT48QQgghZHJNWlHd0NCA48eP44knnoC1tfWA99wqAHmex4YNG1BdXY2vv/4aqampmDt3LlauXInGxkb9/QUFBfjiiy9w5MgRHDlyBGfPnsUf//hH/cd//etf491338Vbb72F7OxsPPPMM3jggQdw9uxZ5nV/9rOf4ZVXXkFOTg4iIyPR3t6O9evX4+TJk0hLS8PatWuxadMmlJaWAgAOHToEHx8fvPjii6iqqkJVVRUAIDMzE2vXrsWWLVtw9epV7N+/H+fPn8eTTz6pf62HH34YxcXFOH36NA4ePIg333xTf0jJ7fcsW7Zs0D/LgwcP4tVXX8U//vEP5Ofn44svvsCsWbOGzA0AOjs78corr+Bf//oXsrOz4ebmhocffhgpKSk4fPgwEhMTwfM81q9fP+AYuvLycsTHxyMkJASHDh2ChYXFiP+Mx+Khhx6Co6Ojvg3ktddew+HDh3HgwAHk5eXhww8/REBAwLhfhxBCCCFkwvHj1NXVxV+7do3v6upi4pcuXeIB8IcOHWLizs7OvLW1NW9tbc3/7Gc/43me50+dOsXb2dnx3d3dzL3Tp0/n//GPf/A8z/O//e1veSsrK761tVX/8eeee46PjY3leZ7n29vbeQsLC/7ixYvM5/jBD37A79ixg+d5nv/uu+94APwXX3wx7H9XWFgY//rrr+uv/f39+VdffZW5Z+fOnfwPf/hDJpaQkMBLJBK+q6uLz8vL4wHwly5d0n88JyeHB8B8rl/84hf8zp07B83lb3/7Gz9z5kxerVYP+PGBcnv33Xd5AHx6ero+dv36dR4Af+HCBX2svr6et7S05A8cOKB/zt7ens/Ly+P9/Pz4p556itfpdDzPj+zPeCBLly7ld+3aNej17WJjY/l169bxPM/zTz31FL9ixQr96w9nsK9FQgghhJDJNiHHlA/FcHZwUlISdDodvve970GlUgEAUlNT0d7e3u9Exq6uLhQUFOivAwICYGtrq7/29PTUr/peu3YN3d3dWL16NfM51Go15syZw8Tmz5/PXHd0dOB3v/sdjhw5gsrKSmg0GnR1delXqgeTmpqKGzduMC0dPM9Dp9OhqKgI169fh0wmY14vJCSk33SN4Voa7r33XuzZswfTpk3DHXfcgfXr12PTpk2QyYb+v0+hUCAyMlJ/nZOTA5lMhtjYWH3M2dkZwcHByMnJ0ce6urqwePFi7NixA3v37tXHR/NnPFY8z+u/Zh5++GGsXr0awcHBuOOOO7Bx40asWbNmQl6HEEIIIWQiTVpRHRQUBI7jkJuby8SnTZsGoO9YaQDQ6XTw9PTEmTNn+n2e2wtQuVzOfIzjOP3mu1v/Pnr0KLy9vZn7lEolc23YjvLcc8/h2LFj+Otf/4qgoCBYWlpi69atUKvVQ/436nQ6/OhHP9L3N9/Oz88PeXl5+jzHw9fXF3l5eThx4gROnjyJxx9/HH/5y19w9uzZfn8mt7O0tGRem+f5Ae+7vZAFev+8Vq1ahaNHj+K5556Dj48PgNH9GY+FVqtFfn4+oqOjAQBz585FUVERvvnmG5w8eRLbtm3DqlWrxtTDTQghhBAymSatqHZ2dsbq1avxxhtv4Kmnnhq0rxroLZ6qq6shk8nG3DN7azNeaWkpli5dOqpnExIS8PDDD+Puu+8GALS3t6O4uJi5R6FQQKvV9ss7OzsbQUFBA37e0NBQaDQapKSkICYmBgCQl5eH5ubmUeUH9BbId955J+6880488cQTCAkJQWZmJubOnTtgbgMJCwuDRqPB5cuXsXDhQgC9ve/Xr19HaGio/j6JRIJ9+/bh/vvvx4oVK3DmzBl4eXmN6894JN5//300NTXhnnvu0cfs7Oxw33334b777sPWrVtxxx13oLGxEU5OThP++oQQQgghYzWp7R9vvvkmFi1ahPnz5+OFF15AZGQkJBIJkpOTkZubi3nz5gEAVq1ahbi4ONx1113405/+hODgYFRWVuLrr7/GXXfd1a9dYyC2trb46U9/imeeeQY6nQ6LFy9Ga2srLl68CBsbGzz00EODPhsUFIRDhw5h06ZN4DgOv/nNb/qNnwsICMC5c+ewfft2KJVKuLi44Oc//zkWLFiAJ554Ao899hisra2Rk5ODEydO4PXXX9e3LTz22GN45513IJPJsHv3bmaVHgD+93//FxUVFfjggw8GzO+9996DVqtFbGwsrKyssG/fPlhaWsLf33/Q3AYyY8YMbN68GY899hj+8Y9/wNbWFr/4xS/g7e2NzZs3M/dKpVL897//xY4dO/SFtYeHx5j/jA11dnaiuroaGo0GFRUVOHToEF599VX85Cc/wfLlywEAr776Kjw9PTF79mxIJBJ8+umn8PDwoMNpCCGEEGJ8xtuUPdzmsMrKSv7JJ5/kAwMDeblcztvY2PAxMTH8X/7yF76jo0N/X2trK//UU0/xXl5evFwu5319ffnvfe97fGlpKc/zvRsVo6KimM/96quv8v7+/vprnU7H7927lw8ODublcjnv6urKr127lj979izP830bFZuampjPU1RUxC9fvpy3tLTkfX19+TfeeKPfZrrExEQ+MjKSVyqV/O1/bElJSfzq1at5Gxsb3tramo+MjOT/8Ic/6D9eVVXFb9iwgVcqlbyfnx//wQcf9NtY+NBDD/FLly4d9M/4888/52NjY3k7Ozve2tqaX7BgAX/y5Mkhc7u14dBQY2Mjv3PnTt7e3p63tLTk165dy1+/fl3/ccPnenp6+C1btvChoaF8TU3NsH/GAxlooyIAHgCvUCh4T09PfuPGjf02tb7zzjv87NmzeWtra97Ozo5fuXIlf+XKlUFfhzYqEkIIIUQoHM8P0mg7Qt3d3SgqKkJgYCAsLCwmoMwnZGzoa5EQQgghQpn0Y8oJIYQQQggROyqqCSGEEEIIGScqqgkhhBBCCBknKqoJIYQQQggZJyqqCSGEEEIIGadJP6acEEIIIYSMjVarRUJCAqqqquDp6Yn4+HhIpVKh0yIDoKKaEEIIIcQIHTp0CLt27UJ5ebk+5uPjg71792LLli0CZkYGQu0fhBBCCCFG5tChQ9i6dStTUANARUUFtm7dikOHDgmUGRkMFdWEEEIIIUZEq9Vi165dGOh8vlux3bt3Q6vVTnVqZAhUVIvMm2++qT9RcN68eUhISBA6JUIIIYSMQkJCQr8V6tvxPI+ysjL6GW9kqKgWkf3792P37t341a9+hbS0NMTHx2PdunUoLS0VOjVCCCGEjFBVVdWE3kemBhXVIvL3v/8dP/jBD/Doo48iNDQUe/bsga+vL9566y2hUyOEEELICHl6ek7ofWRq0PSPEWpt7pzS17NzsBrV/Wq1GqmpqfjFL37BxNesWYOLFy9OZGqEEEIImUTx8fHw8fFBRUU5BmirBsdx8PHxQXx8/NQnRwZFRfUIPX3fP6f09d47tmtU99fX10Or1cLd3Z2Ju7u7o7q6eiJTI4QQQsgkkkql2Lt3L7ZuvQccgNvrao7jAAB79uyhedVGhto/RObWX7ZbeJ7vFyOEEEKIcduyZQv2/fkpeNiycR8fHxw8eJDmVBshWqkWCRcXF0il0n6r0rW1tf1WrwkhhBBi/DYvjcTCp2RIKuVR2w54Tw/H5j9doRVqI0Ur1SKhUCgwb948nDhxgomfOHECCxcuFCgrQgghhIwVr+mGVMIhLkCCzRESLAr3oILaiNFK9Qi9tv8xoVMY1rPPPoudO3di/vz5iIuLwzvvvIPS0lL8+Mc/Fjo1QgghhIwS39PFXHMyC4EyISNBRfUIjXYahxDuu+8+NDQ04MUXX0RVVRUiIiLw9ddfw9/fX+jUCCGEEDJKvKabueZkSoEyISNBRbXIPP7443j88ceFToMQQggh49S/qKaVamNGPdWEEEIIIUaI16iYayqqjRsV1YQQQgghRohWqk0LFdWEEEIIIUaIimrTQkU1IYQQQogRoo2KpoWKakIIIYQQI6RpLGSuJRb2AmVCRoKKakIIIYQQI6NTd0Jdlc7EFN7zhEmGjAiN1COEmD2tVouEhARUVVXB09MT8fHxdGoZIURQ6spUQKfpC3ASKLyjhUuIDIuKakKIWTt06BB27dqF8vJyfczHxwd79+7Fli1bBMyMEGLOVKWJzLXcIxISpY1A2ZCRoPYPQojZOnToELZu3coU1ABQUVGBrVu34tChQwJlRggxd+qyS8y10neBQJmQkaKimhBilrRaLXbt2gWe5/t97FZs9+7d0Gq1U50aIcTM8TwPValBUe1HRbWxo6JaRM6dO4dNmzbBy8sLHMfhiy++EDolQoxWQkJCvxXq2/E8j7KyMiQkJExhVoQQAmgab0DXWc/ElH5xAmVDRoqKahHp6OhAVFQU3njjDaFTIcToVVVVTeh9hBAyUQz7qSU2HpA6BAiTDBkx2qgoIuvWrcO6deuEToMQk+Dp6Tmh9xFCyERRl11mrpW+seA4TqBsyEhRUT1CDW1dU/p6zraWU/p6hJib+Ph4+Pj4oKKiYsC+ao7j4OPjg/j4eAGyI4SYM8OVamr9MA1UVI/QnJ+/N6WvV/rmT6b09QgxN1KpFHv37sXWrVv7fYxD74rQnj17aF41IWRK6bpb0FObzcSoqDYN1FNNCDFbW7ZswcGDB2FrYcvEPdw9cPDgQZpTTQiZcqryJOD2d8+kCig85wiXEBkxWqkmhJi1LVu24PLKJBSU30CHugPWCmu88t4rmDF7htCpEULMkNpglJ7Caw44uYVA2ZDRoKKaEEJ0gI+jr/5SJpcLmAwhxJyp+h36Qq0fpoKK6hFK+9PDQqcwrPb2dty4cUN/XVRUhPT0dDg5OcHPz0/AzAgxbjqdjrmWSGiXPSFk6vE6LVSGkz/o0BeTQUX1CJnCNI6UlBQsX75cf/3ss88CAB566CG89957AmVFiPHTaQ2KailtNyGETL2e2mvgVa1MTEHHk5sMKqpFZNmyZQOOBiOEDK3/SjUV1YSQqWc4n1rq4A+ZnZdA2ZDRop8chBCzxvM8eB37yyitVBNChKAqM5hPTavUJoV+chBCzJrhKjVARTUhRBh06Itpo58chBCzxmv7t0xRUU0ImWrajjpoGm4wMSqqTQv95CCEmDWtVtsvRj3VhJCpZjj1g5NbQe4+S6BsyFjQTw5CiFkz7KcGaKWaEDL11AatHwqfaHBSmidhSugnByHErNFKNSHEGPQ/9IU2KZoa+hWIEGLWaKWaiIFWq0VCQgKqqqrg6emJ+Ph4SKVSodMiI8Rre6CuSGFi1E9teqioJoSYNVqpJqbu0KFD2LVrF8rLy/UxHx8f7N27F1u2bBEwMzJS6uqr4Hu6mJjCN1agbMhY0U8OQohZo5VqYsoOHTqErVu3MgU1AFRUVGDr1q04dOiQQJmR0TDsp5a5zITUylmgbMhY0U8OQohZ02ppTjUxTVqtFrt27RrwJN1bsd27dw/4bgwxLjSfWhzoJ4dIvPLKK4iOjoatrS3c3Nxw1113IS8vT+i0CDF6PBXVxEQlJCT0W6G+Hc/zKCsrQ0JCwhRmRcai/yZFKqpNEf3kEImzZ8/iiSeewKVLl3DixAloNBqsWbMGHR0dQqdGiFEbaKWaAydAJoSMTlVV1YTeR4ShaSmHtqWMiVE/tWmijYoj1NTdPaWv52hhMar7v/32W+b63XffhZubG1JTU7FkyZKJTI0QUbG06f937UbGDYREhwiQDSEj5+npOaH3EWGoDVapOQt7yF1DBcqGjAcV1SO0/vOp3eyRuOP+cT3f0tICAHBycpqIdAgRLTsnO/jM8EF5ft/b6MnHU6ioJkYvPj4ePj4+qKioGLCvmuM4+Pj4ID4+XoDsyEipSvvPp+ZoApFJov/XRIjneTz77LNYvHgxIiIihE6HEKMXvWY+c3014Sq6O6f23SlCRksqlWLv3r29F9zALUt79uyhedVGjg59EQ8qqkXoySefxNWrV/Hxxx8LnQohJmHuyrnM5sQeVQ8yzmYImBEhI7NlyxYcPHgQXl5eTFzh7ITde/bQnGojp+vpgroqjYkp/aioNlXU/iEyTz31FA4fPoxz587Bx8dH6HQIMQm2jrYIjQ1F9sVsfSz5eApi19FmIWL8tmzZgs2bN+ORt97Exbw8yB0cYBcSghpHR/A8D26QVWwiPHXlFUDb0xfgJFB4RwuXEBkXKqpH6Ou7jfu3fZ7n8dRTT+Hzzz/HmTNnEBgYKHRKhJiU6DXzmaL6RvoNNFY3wsmD9iUQ4yeVSvHU1ntx/bvT+lhhSwuuNTYg3NlFwMzIUAwPfZG7R0BiYSdQNmS8qKgeodFO45hqTzzxBD766CN8+eWXsLW1RXV1NQDA3t4elpaWAmdHiPGLiIuApY0lutr7jgpOOZGCNTvXCJgVISM3190dXtbWqLxtlOqRwkIqqo1Yv35qOvTFpFFPtUi89dZbaGlpwbJly+Dp6an/Z//+/UKnRohJkClkmLNiDhNLPp4y4FQFQoyRhOOwYdo0JnaipATdGo1AGZGh8Dw/wOQPajkzZVRUiwTP8wP+8/DDDwudGiEmI3oN28tYV16HkpwSgbIhZPQ2BE5jji7q6OnB6bJSwfIhg9M0FULXUcvEFLRSbdKoqCaEkJsCwvzh6uPKxJKOJQuUDSGj525tjViDw16OFBYKlA0ZimE/tcTaDTLHaYPcTUwBFdWEEHITx3H9ZlannU6DRk1vnxPTsXHadOY6rbYWZW1tAmVDBqMqu8xcK31jaVKLiaOimhBCbjNvNVtUd7V3ITsxe5C7CTE+8d7esFcomdiRwgKBsiGDURmsVNMmRdNHRTUhhNzG2cMJQbODmFjScWoBIaZDIZXijsAAJvZ1URE0Op0wCZF+dN2t6KnJYmLUT236qKgmhBADhi0gOZdz0NZEb58T07HJoAWkvqsLl6uqBMqGGFJXJAP8bb/kSOVQeM0VLiEyIaioJoQQA1FLoiBXyvXXOq0OV06nDfEEIcZluoMDwpydmdhX1AJiNAxH6Sk8Z0MipzMlTB0V1YQQYsDC2gKR8ZFMLJmmgBATs9FgZvX5igo0dnUNcjeZSv0OffGl1g8xoKKaEEIGYNgCUp5fjqoievucmI7Vfv5QSqX6ay3P45viYuESIgAAXqcb4CTFBQJlQyYSFdWEEDKAmXNnwt7FnonRajUxJTYKBVb4+jGxI4UFdEqowHrqcsB3tzAxhS8V1WJARTUhhAxAIpVg3qp5TCzlZCp0WpqgQEzHpunshsXi1lZkNdQLlA0BALXBfGqpvS9k9j4CZUMmEhXVIvHWW28hMjISdnZ2sLOzQ1xcHL755huh0yLEpBm2gLQ2tOL6lesCZUPI6M12dYWPjQ0T+6qATlgUkqrMYD41rVKLBhXVIuHj44M//vGPSElJQUpKClasWIHNmzcjO5sOrSBkrDwDPeEzg11BohYQYko4jut3wuKp0hJ09vQIlBGhQ1/ESyZ0AqaivqNl+JsmkIu1/fA33WbTpk3M9R/+8Ae89dZbuHTpEsLDwycyNULMSvTaaJTnl+uvr57PRHdHNyysLQTMipCRWx8YiHcyr0J3s5e6U6PB6bLSfsU2mXzazgZo6tl3u+jQF/GgonqEgvY+OqWv1/zLT8f8rFarxaeffoqOjg7ExdFfVkLGY+6KOfjyrS/1vdQ9qh5knMtA7LpYgTMjZGRcrawQ5+mJC5WV+thXBYVUVAvAsJ+ak1tC4RE5yN3E1FD7h4hkZmbCxsYGSqUSP/7xj/H5558jLCxM6LQIMWm2jrYIjQ1lYknUAkJMjGEBfbW+DsWtU/sOLOnf+qHwng9OKh/kbmJqqKgWkeDgYKSnp+PSpUv4yU9+goceegjXrl0TOi1CTF7MmmjmuiCjAA3VjQJlQ8joLfb2hqOSbVk6QhsWp1z/Q19ok6KYUFEtIgqFAkFBQZg/fz5eeeUVREVFYe/evUKnRYjJC48Lh6UNe4Rw6okUgbIhZPRkEgnWBQYysW+Ki6DR0YjIqcJrNVCXs+9yUT+1uFBP9Qjd2PUvoVMYNZ7noVKphE6DEJMnU8gwZ8UcXDx8UR9LPp6C1Q+sBsdxAmZGyMhtmjYNH+Xm6K8bu7txsbISS3xoRvJU6KnJBN/TycSUvrQ3Q0yoqB6h0U7jmGq//OUvsW7dOvj6+qKtrQ2ffPIJzpw5g2+//Vbo1AgRhZi10UxRXVdeh+JrJQgMDxAuKUJGIcDeHhEuLsiq7zv85avCAiqqp4hhP7XMOQhSa1eBsiGTgdo/RKKmpgY7d+5EcHAwVq5cicuXL+Pbb7/F6tWrhU6NEFHwD/WHqw/7AzD5OG1YJKZlk8GGxcTKStR3dQmUjXmh+dTiR0W1SPz73/9GcXExVCoVamtrcfLkSSqoCZlAHMchei27YTHtdBp61HSIBjEdK/38YCnre5Nay/P4pqhIwIzMR/9NilRUiw0V1YQQMkLzV81jrrvau5CdSKeWEtNhLZdjpZ8fEztSWAD+5sEwZHJoWiuhbS5hYgrqpxYdKqoJIWSEnDycEDQ7iIklH6cpIMS0GM6sLm1rQ0ZdnUDZmAe1wSo1p7SD3I3OkRAbKqoJIWQUDFtAci7noK2pTaBsCBm9SBcX+NnaMbGvCgsEysY8qEoNWz9iwUmkAmVDJgsV1YQQMgpRSyIhV/adgKbT6nDl1BUBMyJkdDiOw6bp05jY6dJSdPTQ/oDJoioz2KRIh76IEhXVhBAyChZWFoiMj2Ri1AJCTM36gEBIb5ux3q3V4mRJyRBPkLHie7qhrkxjYgo/KqrFiIpqQggZpRiDFpDy/HJUFVUJlA0ho+dkaYlFXt5MjFpAJoe6Kg3QqvsCHAelT4xwCZFJQ0U1IYSM0ow5M2Dvwh4IlXyMZlYT07LRoAUku6EBhS3NwiQjYobzqeVu4ZBYGPeBcmRsqKgmhJBRkkglmGcwXi/lZCp0Wp1AGREyenGeXnC2sGBiRwoKBcpGvPrNp6ZDX0SLimpCCBmD6DXzmevWhlbkpV4XKBtCRk8mkWB9ILta/U1xEXq0WoEyEh+e5/tN/qD51OJFRTUhhIyBZ6AnfGf6MLEUOracmJiN09iiulmlwvnKCoGyER9tczF07dVMjFaqxYuKapF65ZVXwHEcdu/eLXQqhIjW/DXshsWr5zPR3dEtUDaEjJ6fnR1mu7oysSOF1AIyUQz7qSVWLpA5BQ1yNzF1VFSLUHJyMt555x1ERkYOfzMhZMzmrZwLibTv22iPqgfpZzMEzIiQ0TM8YfFSVRVqOzsFykZcVGWXmWul3wJwt40yJOJCRfUItauap/SfMefZ3o7vfe97+Oc//wlHR8eJ+wMghPRj42CDsFj2qOFkagEhJmaFnx+sZDL9tY7n8XURrVZPBMOVagUd+iJqsuFvIQDwwjc7pvT1/nrXN2N67oknnsCGDRuwatUq/P73v5/grAghhqLXzEfWxSz9dUFGARqqGuDs6SxgVoSMnKVMhlX+/jhc0Den+lhxMR4OjxAwK9OnU7Wjp/oqE6N+anGjlWoR+eSTT3DlyhW88sorQqdCiNkIjwuHla0VE0s5kSpQNoSMjeEUkOLWVjR10/6A8VBXJAP8bWM2JTIovOYN/gAxeVRUi0RZWRl27dqFDz/8EBYGc0cJIZNHppBhzvI5TCz5eDJ4nhcoI0JGL9zZGRZSKRPLrK8XKBtx6DdKz3M2JAqrQe4mYkBFtUikpqaitrYW8+bNg0wmg0wmw9mzZ/Haa69BJpNBS3NHCZk00WvZmdX1FfUozi4WJhlCxkAmkSDcxYWJZdTVCZSNOBge+kL91OJHPdUj9MK6j4VOYUgrV65EZmYmE/v+97+PkJAQ/PznP4fUYAWCEDJx/EP94errirqyviIk+XgyAiMCBcyKkNGJdHFFak2N/vpqPRXVY8XzPNTl7KZlJR36InpUVI+QjdJB6BSGZGtri4gIdlOJtbU1nJ2d+8UJIROL4zhEr4nG1//+Wh9L+y4ddz95N+QKuYCZETJyka7sSnVeYyNUWi2UtCgzatrWcug62fYZpU/0IHcTsaD2D0IImQDzV7EbkLrau5B9MVugbAgZvVkurpDcNkO5R6dDbmODgBmZLnVlGnPNWdhD6kjvXIkdFdUidubMGezZs0foNAgxC04eTpgxhz0pjWZWE1NiLZdjur09E6O+6rExLKoVnnPo0BczQEU1IYRMEMNjy3Mu56KtqU2gbAgZvVkGR5ZfpaJ6TNRVhkX1bGESIVOKimpiknieR1tbGxoaGtDW1kbjy4hRiFoSCYWFQn+t0+mQeuqKgBkRMjpRLmxRnVZbiy6NRqBsTFdPZTpzrfCaLUgeZGpRUU1MTlNTEzIzM5GXl4eioiLk5eUhMzMTLS0tQqdGzJyFlQUi42cxsRRqASEmZK67O9NX3anR4FRpiYAZmR5tew20bZVMTOE5Z5C7iZhQUU1MSlNTEwoKCqBWq5m4Wq1GWVkZOjs7BcqMkF7RBi0g5fkVqCysHORuQoyLi6UlFnh6MrEvbzu+nAxPXZXOXHNyK8hcZgqTDJlSVFQTk8HzPMrKyoa8p7GxkQ66IYKaMWcG7F3YzV7Jx1MEyoaQ0btz+nTmOqu+HoUtzcIkY4LUFWzLl9wzCpyExhKaAyqqiclob2/vt0JtSKvVIjU1dYoyIqQ/iVSC+avZ8XqpJ1Lolz1iMhZ5ecPZwoKJfXmDVqtHSlVynrmm1g/zQUU1MRnDFdS31NbWTnImhAxt/mr22PLWxjZcT80XKBtCRkcmkWDDtGlM7NviIqjoF8Nh8Ro1VCUXmJhFQLxA2ZCpRkU1MRkKhWL4mwC4ublNciaEDM0z0BO+M32YWPIx2rBITMemaWwLSKtajTPDtN8RQF2RAr6H3dujDFwqUDZkqlFRTUyGjY3NsIW1VCrFvHnzhryHkKkQvZbdsJh5PhPdHd0CZUPI6PjY2mK+uzsTO1xwQ6BsTEd30RnmWu4+C1Jrl4FvJqJDRTUxGRzHwdfXd8h7LKxtIZXShhAivLkr5kIi7fsW26PuQfrZDAEzImR0Nk9nTwi9UluL0tZWgbIxDd2FZ5hri2nLBMmDCIOKapF44YUXwHEc84+Hh4fQaU04R0dHTJ8+vf+KtUQKqbUjVLwExbU0r5oIz8bBBmGxYUyMWkCIKVni4wN7hZKJHabxeoPie7qhKktkYtT6YV6oqBaR8PBwVFVV6f/JzMwUOqVJ4ejoiFmzZiE4OBg+fv6QO7hD4ewNicICPA/s/TqFTlgkRsGwBaTgagEaqhoEyoaQ0VFIpVgfGMjEvi4qRA9tWByQqvwyoFH1BTgJLAKWCJcQmXIyoRMwFTpV3ZS+nkTpOvxNBmQymShXpwfCcRxsbW1ha2sLXt6Outa+jSHpJbU4lHQd98QGC5ghIUD4gjBY2Vqhs63v6zPlRCrWPrhGwKwIGbk7g6bj47xc/XWTSoWEigqs8PMTMCvjZNj6ofCcDYmlgyC5EGFQUT1CzUen9huI05auUT+Tn58PLy8vKJVKxMbG4uWXX8Y0g7FIYuRmb4XmThXUmh597PefXcTKCH84WFsM8SQhk0umkGHuijk4/2XfiK3k48lYs3M1uNuOgibEWAXY2WO2qyvS6/oWlg4X3KCiegCqorPMtTJwmSB5EOFQ+4dIxMbG4oMPPsCxY8fwz3/+E9XV1Vi4cCEaGsT/VrNUIoG3ow0Ta2jvxh+/vCxQRoT0mW9wbHl9RT2Ks4uFSYaQMbjTYMNiUnU1qtrbBcrGOOlU7b3tH7exmEb91OaGimqRWLduHe655x7MmjULq1atwtGjRwEA77//vsCZTQ07KyVsLNnNix+dv4YrRdUCZURIL/9QP7j6su1cycdpwyIxHct9fWErl+uveQCHC2nD4u1UJecBbd+7pZDIoPSnQ1/MDRXVImVtbY1Zs2YhP998TnFztbOCxOAd9V9+fA4arU6YhAhBb/9/jMFqddp36ehR9wzyBCHGxUImw9oAdsPikcJCaHT0vfWW7sLvmGulbywkSptB7iZiRT3VI+SwoVToFEZFpVIhJycH8fHm85uyQiaFrSU7/ulaeQPeO5OJR1dGCZQVIb3Hlh/999f66672LmRfzMbsZbOFS4qQUdg8fToO5l/XX9d3dSGxqhLx3j5DPGU+ugtOMdfKacsFyoQIiYrqERrLNI6p9NOf/hSbNm2Cn58famtr8fvf/x6tra146KGHhE5tStlYyDHNzR4VLX0n1/3tSDI2zJ0OT0daNSDCcHR3xIw5QchP6zuRLvl4MhXVxGQEOToizNkZ127bp3O4oICKagDajjr0VF9lYhbTVgiUDREStX+IRHl5OXbs2IHg4GBs2bIFCoUCly5dgr+/v9CpTSmO47B7w3wm1qHqwQsHLwzyBCFTI9qgBSTnci7aGtsEyoaQ0ds8fTpzfbGyErWdnYPcbT4MWz84hTWUPjECZUOEREW1SHzyySeorKyEWq1GRUUFPvvsM4SFhQ3/oAjN8nPD9kWhTOybtEKczioRKCNCgMglkVBY9G2m1el0SD19RcCMCBmdVX7+sJL1vcGt43kcLSwUMCPj0K+fOmAJOJlikLuJmFFRTUTpfzcvgJMNO6P6N/sT0EWbw4hALKwsEBk/i4nRseXElFjJ5Vht8O7n4cIC6Mz8BNvugtPMtQX1U5stKqqJKDnaWOBXd8cxsbKGNrz+Da0MEuEYHltecaMClQWVAmVDyOgZzqyu7uhAUnWVQNkIT9NUBG1TEROzmE791OaKimoiWlsXBCMmyJOJ/eNkOvKrmgTKiJi7GbNnwN7Fnokln0gRKBtCRi/UyQkzHByY2OEC851Z3V3Atn5IrF0hd4sQKBsiNCqqiWhxHIc/bF8CmaTvy7xHq8OvPzkH3szfriTCkEglmL96HhNLPZECrVYrUEaEjA7Hcf1Wq8+Vl6Oxq0ugjIRlOErPYtpycBIqrcwV/T9PRC3YywmPrWJnVCfmV+JQ0vVBniBkchlOAWltbMP1VPp6JKZjbUAAlFKp/lrL8/i6qGiIJ8SJ1+nQXXSGidEoPfNGRTURvV3r5sHHyZaJ/eVwElQ9tDpIpp5HgAd8g32ZWPIxagEhpsNWocAKXz8mdriwwOzeAeypyYSuo46JUT+1eaOimoielVKO321bzMQqm9rx0flrAmVEzF30GnaWeub5THS1m+fb58Q0bQ5iZ1aXtbUhrbZWoGyEYThKT+Y4DTLHAGGSIUaBimpiFlbN8keswabFN46lolNFI/bI1Ju7ci4k0tt6/dU9yDibIWBGhIxOpIsrAuzsmNiXBTcGuVuc+o3So1Vqs0dFNTELHMfhuTtjmVhdaxfeP5slUEbEnNnY2yBsAXs4U/JxagEhpqN3wyK7Wn2mrAwtKpVAGU0tXqOGqiSBiSlpPrXZo6KamI2YIE8sC2N7Wd86kYbWLvP4IUCMi+GGxYKrBWioahAoG0JGb11gIOS3TbpQ63T4ttg8NiyqypPAqzuYGB36QqioFpGKigo88MADcHZ2hpWVFWbPno3U1FSh0zIq/7Mphrlu7lDhX6euCpQNMWfhC8JgZWfFxGi1mpgSB6UFlvr4MLHDBeaxYbG7kG39kHtEQWrtIlA2xFhQUS0STU1NWLRoEeRyOb755htcu3YNf/vb3+BgMKTf3EX5u+GOqEAm9q/TGWhq7xYoI2KuZAoZ5i6fw8RSjqeYRUFCxMNwZnVhSwsy6+sFymbqqPr1U68UKBNiTGRCJ2AqtAZjcyab1Np1VPf/6U9/gq+vL9599119LCAgYIKzEof/2RSNY1eLcKt2ae/uwVsn0vBLg2PNCZls89dE4/yXF/TX9ZX1KMoqwrRZ0wTMipCRm+fuDm8bG1S0t+tjhwsKEOk6up9hpkSnaoOqPImJWUyn1g9CRfWIVfzRe0pfz+8l9ajuP3z4MNauXYt7770XZ8+ehbe3Nx5//HE89thjk5Sh6Qr2csbm+TPwRXK+PvbemSw8uiIKbvZWQzxJyMTyD/WDm68basv6RpElH0+hopqYDAnHYdO06Xj7au/0Gl6nw8FvvoZ3fj4CfX0RHx8P6W0HxYiBqjgB0Gn6AlI5lP6LB3+AmA1q/xCJwsJCvPXWW5gxYwaOHTuGH//4x3j66afxwQcfCJ2aUXp2QzSkEk5/3d2jwRvHrgiYETFHHMf1m1md9l0aetQ06pGYjg3TpkHKcWhMSkba07uQ8eJLeOTBB7F8+XIEBATg0KFDQqc4oQznUyt9F0CisBYoG2JMqKgWCZ1Oh7lz5+Lll1/GnDlz8KMf/QiPPfYY3nrrLaFTM0oBbva4Ny6EiX10PhsVjW0CZUTM1fzV88Fxt/2C19GNrAs06pGYDhdLS7jeKMD1PXugbmxkPlZRUYGtW7eKqrDuLjjFXNPR5OQWKqpFwtPTE2Fh7Nzb0NBQlJaWCpSR8du1bh4UstvGQWl02PsNTUshU8vR3RFBs9nNXjQFhJgSrVaLi2++OeDHbm283b17N7Ra7VSmNSm07TXoqWF/6aVDX8gt1FM9Qt6/qBA6hSEtWrQIeXl5TOz69evw9/cXKCPj5+1ki/sXh+O9M5n62KeJufjJ6tkIdHMQLjFidqLXzEd+Wl+Pf25SLtoa22DrZCtgVoSMTEJCAmqrqgb9OM/zKCsrQ0JCApYtWzZ1iU0Cw9YPTmkLhff8Qe4m5oZWqkdIau06pf+M1jPPPINLly7h5Zdfxo0bN/DRRx/hnXfewRNPPDEJfxri8eTaubCQ9/1uqdXxePUorRKSqRW5JBIKC4X+WqfTIfUUvWtCTEPVEAX1WO4zZv36qQPiwUnlAmVDjA0V1SIRHR2Nzz//HB9//DEiIiLw0ksvYc+ePfje974ndGpGzc3eCg8vi2BiX6bkI6+STrYjU8fCygKR8ZFMjFpAiKlQSG1GdJ+np+ckZzK5eJ5HN82nJkOgolpENm7ciMzMTHR3dyMnJ4fG6Y3QT1bPge1tq4Q8D/ztq2QBMyLmKHot+xZyxY0KVBZUCpQNISPT2tyJi0fqYKV0GPI+pbMzrGfOnJqkJommqRDa5hImRkeTk9tRUU3MnqONBR5dya4SfptRhIyS2kGeIGTizZg9A/Yu9kws+Tj9ckeMl1qlwWsvHEFDTRtiQu4e8l7/nTvxPwnncNqEN88brlJLbNwhdwsXKBtijKioJgTAoyui4GCtZGJ/+yppkLsJmXgSqQTzDWZWp55MFcXEBCI+Oh2Pf/7lOG7k9PZJ+7tHYVnU92Fn7cTcp3B2wszdu+EUE40enQ6/vnAeB69fFyLlcet3NPm05cw4TEKoqCYEgK2lAj9ZPYeJnblWhqQbpr+xhpiO6NVsUd3a2IbrqaZZgBBx++y9i0hOyGdicyIWobCwCN999x0++ugjHDt5ErsPfganmGj9PTyAv6Wm4B9XM/Tj9kwBr9Ohu+gME6N+amKIimpCbnp4WQRc7SyZ2F8OXzapb/zEtHkEeMA32JeJJR2jFhBiXM58nYWj+9mNtBZWCjzz0mY4u9lh2bJl2LFjB9asXImXlyzB3UFB/T7He9nZ+GNyEjQ63VSlPS491RnQdbIb2KmfmhiiopqQmywVcjy5dh4Tu3yjCgm55QJlRMxRzNpo5jrrfBa62rsEyoYQVlZqCT543aC3WMLhyV+vh2+gS7/7pRIJnpsfjUdnzer3scMFBfjl+QR0azSTlu9E6S5k/5tlTkGQOfgJlA0xVlRUE3Kb+xeHwduJHQ/1l8NJtFpNpsycFXMglUn11z3qHqSfzRAwI0J6lRfX443ffw2djv1++OBTKxAxb/CDxjiOww8iZuHn0TGQGPQgJ1RU4OnvTqNFpZqUnCdKdwE7n5pOUSQDoaKakNso5VLsWsf2tWaU1OLE1WJhEiJmx8beBmELwpgYTQEhQmtu6MDff/0lujvVTHz9tnlYtj5ikKdYdwUF4eXFi6GQSpl4Zn09fnLyJGo6OiYs34nEa1RQlSQwMWr9IAOhopoQA/csmIkAV3a02V+/Suq3OkPIZIk2mAJSeLUQ9ZX1AmVDzJ2quwd7fnsYjXXtTDxmyQxs/f6iUX2upT6+eG35ctjK2VMIi1pb8IPjx5BVb3xf56qyy+B7bmvB4jgopy0TLB9ivKioJsSAXCrFsxvZoia3shFHrtwQKCNibsJiw2BlZ8XEUk7QCYtk6um0Orz9yrcozmfn9geFeuLRn66BRDL6kXJRrm54a9VquFqyG8Mburvx+KmTOFpYOK6cJ1p3wSnmWu45G1IrZ4GyIcaMimpCBnDnvBkI9mLnrf79SDI0WtPYqU5Mm0whw9wVc5lY8vEU6u0nU+7jdxKQdoktcl097fH0CxuhUMrG/HmnOzjgndVr4G9nx8R7dDr8/vIlvHblitFMBukuNOinnkb91GRgVFSLSEBAADiO6/fPE088IXRqJkci4fDTjTFMrLC2BYeSaGYwmRqGLSANlQ24kVEgUDbEHJ34Mh0nvkhnYtY2Sjz70mbYOVgN/NAoeFhb453VaxDj4dHvYx/n5eKnZ8+iTa0e4Mmpo+tuhbqC3dNAmxTJYKioFpHk5GRUVVXp/zlx4gQA4N577xU4M9O0JioAkX6uTGzP0RSoeuiEOzL5/EL84O7vzsQuHUkUKBtibtIuFeKjt88xMalMgqd+uxGevo4T9jp2CgX+tnQZ7gsO7vexy9VVePT4MZS0tk7Y641Wd/E5QHfb93ypAkq/0fWRE/NBRfUI9bQ0T+k/Y+Hq6goPDw/9P0eOHMH06dOxdOnSif3DMBMcx+G5O9nV6vLGNuy/mCNQRsSccByHBesXMLGMc1fR0WqcExKIeBTn1+Ktl78Bb7A5+wfPrkZIpM+Ev55MIsHuufPwy5hYyCRsWVLa1oZHjx9DYmXlhL/uSKgMWj+UfnGQKMa/Sk/EaewNUWbm6sObp/T15n1+dlzPq9VqfPjhh3j22WfBcaPfSEJ6LQn1RUyQJ3Nc+WvfpuLeuGBYKuRDPEnI+EWvnY8j/zoC7c13RzQ9GqQcT8HSrfSLMpkcDbVt2PP8YahV7IEsd+2MxcKVIZP62pumT4e/nR3+93wCGru79fH2nh789NxZPBE1GztCQqb0Z5rhJkXqpyZDoZVqkfriiy/Q3NyMhx9+WOhUTBrHcXhuE7taXdvSiQ/OZguUETEnNvY2iFwcycQufX2ZNiySSdHVocKrz3+J5kb23ZCFK0Ow+XuxU5JDpKsr/rNmLYId2RYTHc/j9fQ0vHgpESrt1LTgaduq0VN7jYlRPzUZChXVIvXvf/8b69atg5eXl9CpmLzYGV5YEurLxN48nob2bmE30BDzELeBbQGpKqpCSU6JQNkQsdJotPi/P3yD8qIGJh4c6Y3v7145pavD7tbWeHvVaqzy638M+LfFxXj81EnUdXZOeh6GR5NzSjsovOZN+usS00VFtQiVlJTg5MmTePTRR4VORTQMV6ubOrrx79NXBcqGmJOgOUFw9mJn4iYeuSRQNkSMeJ7Hh/93Blmp7C9rHj6OePr5jZArpr5T1EImw4sLF+FHkVH9PnatoQGPHD+Gaw0NAzw5cfqN0gtcAk5KXbNkcPTVMUKR730pdAoj9u6778LNzQ0bNmwQOhXRiApww5rIABy/7bjyd05m4KGlEXCwthAuMSJ6EokEC9YvwNF/HdXH0r5Lw91P3AUL+tojE+Cbg1dw5ussJmZrb4lnf78Z1rbCfY1xHIeHw8Mx3d4eLyReRKemr8+7vqsLPzl5Av8bE4s7AgMn/LV5nkd3AbtSbTF95YS/DhEXWqkeIbm9w5T+M1Y6nQ7vvvsuHnroIchk9DvTRPrpphjc/g5oW7ca/ziZLlg+xHzE3BENyW1TEdTdaqSeuiJgRkQskhPyceBf55mYTC7Frhc2wc3TXqCsWPE+PvjnmjXwtrFh4mqdDr+7lIj/S0+DdoIPitE03oC2pYyJWUxbPqGvQcSHimqROXnyJEpLS/HII48InYrohHg74855QUzsP99loq518nv7iHmzd7ZH+MJwJpZIM6vJON3IqcI7fz7WL/7Dn61FUJinABkNbpq9A/69Zi3mubn3+9iHOTn4WcI5tE/gQTGGq9RSW0/IXEMn7PMTcaKiWmTWrFkDnucxc+ZMoVMRpWc2REMq6Vuu7lJr8H/HaMWQTL64jXHMdXl+Ocryyga5m5Ch1Va1YO9vv0KPmp2kse0HixCzZIZAWQ3NXqnEnuXLsXVG/59vFysr8eiJ4yhrm5iDYgyLauW05TSelgyLimpCRmGauwO2xrInf32YkI3iuhaBMiLmImR+MBzd2TFjF2m1moxBR1s3Xv3Nl2hr6WLiS9dFYN29xj3dQiaR4H/mz8cvomP6HRRT0tqKHxw7hstVVYM8PTK8TgtV0RkmRqP0yEhQUU3IKO1aPx9y6W39rRodXvmcihsyuSRSSb8TFq+cuoLuzu5BniCkP02PFq+/eBRVZU1MPGKeH3Y+ucxkVmM3BwXh9eUr4KBUMvG2nh48e/YMPsnNHfM8956qDOi62D8fOvSFjAQV1YSMko+zLR5eNouJfZNehEvXhTlGl5iP2HUxzIZFVZcKV2jDIhkhnufx7p5TyL1azsR9Ap3xxK/WQyaTCpTZ2Mx2c8N/1t6BGQ4OTFzH89ibdgV/uHwZ6jEcFGN4iqLMZSZk9hN/PDsRHyqqCRmDp9fNg6PBOLMXP7sw4TvQCbmdg6sDwuLCmBhtWCQjdfi/SbhwMoeJ2TtZ4ZkX74SltXKQp4ybp7U1/rF6DZb7+vb72NGiQjxx+hQauroGeHJw/eZT0yo1GSEqqgkZA3srJf5nYzQTyyqrx2eXrwuUETEXCw02LJZdpw2LZHgXT+Xi833soUEKpQzPvHgnnN3sBMpqYljKZPj9osV4dNasfh/Lqq/HI8ePIbexcUSfi+/phqqEHTFI/dRkpKioJmSM7l8chhme7MaxP315GR3dPQJlRMxBSHQIHNwcmFjiUVqtJoPLy6zAv/9+golxHPCTX65DwIz+I+pMkYTj8IOIWXhlcTwsDc5oqO3sxI9OnsCJkuJhP4+q7BJ4zW37FDgJLAKXTnC2RKyoqCZkjGRSCZ6/ZyETq2vtxFsn0gTKiJiDgTYspp68AlWXSqCMiDGrKmvCay98Ba2GbU27/8dLMWfBNIGymjzLfH3xzqrV8LC2ZuJqrRbPX7yItzMyoBtiA6NhP7XCay4klo6D3E0Ii4pqQsZhaZgflof7MbF/nExHRWObQBkRc7BgfSy42+alq7pUuHKafpkjrNbmTvz9N1+io539hWv1XbOx+q7ZwiQ1BYIcHfGfNWsx29Wt38fev5aNnyecQ0fPwO8o9u+nplMUychRUU3IOP16y0LmQBhVjxZ//OLSEE8QMj4Org4IX8CesHjxq4sCZUOMkVqtwWsvHEFdFTtDf/aCQOz4YbxAWU0dRwsLvLZ8Oe4OCur3sfMVFfjxyRP9TmDUdTVDXZHCxCymr5zUPIm4UFFNyDjN8HTEzni2wPky5QZSC6sFyoiYg7iNbAtIWV4Zyq7ThkUC6HQ8/vWX47iRwx6C4h/khh//4g5IpObxo18uleJn0TF4bn40pAbzt280N2PPFXYcZXfxOYC/rU1GpoTCj90YTMhQzONvlhnQaDT49a9/jcDAQFhaWmLatGl48cUXoaMRb1PimQ3RsLNUMLEXD16ATje2wwcIGU5oTCgcXB2YWOJReoeEAJ+9dxFJ5/KZmJOrDZ558U5YGHyfMgdbZszAa8tXwF7Bjg08WlSIhIq+md39jib3WwSJ3HJKciTiQEW1SPzpT3/C22+/jTfeeAM5OTn485//jL/85S94/fXXhU7NLDjaWGD3+vlMLK24FodT8wd5gpDxkUglWLAhlomlnkylDYtm7uw3WTi636CFwUqBZ17aDAdn60GeEr+57u7455o1sJbLmfgfk5LQour9O9NdyBbV1E9NRks2/C0EALqa2qf09SwdbUZ1f2JiIjZv3owNGzYAAAICAvDxxx8jJSVlmCfJRHlwaQT2JWSjqLavh/GVzy9hbVQgLBXyIZ4kZGxi18Xi2AfHwd98R0TVqULa6TQs2LBgmCeJGGWlluD919jCUCLh8OSv18M30EWgrIyHr60tds2Zi5eTLutjjd3d+GtKMn47KxCaulzmfuqnJqNFRfUI/WfNr6b09Z5I3juq+xcvXoy3334b169fx8yZM5GRkYHz589jz549k5Mg6Uchk+JXW+Lw6Nvf6mNVzR1452QGdhmsYhMyERzdHBEWG4rsxGv62MUjiVRUm6Hy4nr83++/7tdy9uBTKxAxz1+grIzPxmnTcKa8DBcrK/Wxk6Wl2NidCs/b7uMsHKDwmjP1CRKTRu0fIvHzn/8cO3bsQEhICORyOebMmYPdu3djx44dQqdmVlbPCsCiYG8m9ubxNFQ3dwiUERG7hZvYWemluaUozy8f5G4iRs0NHXj1N4fR1clOs1i/bR6WrY8QKCvjxHEc/jcmFraKvt5yXqfD0c/ex5dZOiQW66DV8bAIXApOIhUwU2KKqKgWif379+PDDz/ERx99hCtXruD999/HX//6V7z//vtCp2ZWOI7D8/csguS2neZdag1e/jwR/BAHDhAyViExIf03LB6hDYvmQtXdgz2/PYyGWnY2fnT8DGz9/iKBsjJuLpaW+Om83ncPG5OSkfb0Lrz0Vhqe/kKL7R9qseh1DY6X0oEvZPSoqBaJ5557Dr/4xS+wfft2zJo1Czt37sQzzzyDV155RejUzE6ojzPuWxjCxL5IzsfPPjyDHq1WoKyIWEmlUsSuZzcsppxMoQ2LZkCn1eHtV75FcX4tEw8K9cRjz62BRMIN8iRZ7e8Pr8JCXN+zB+rGRuZj1W3Azl/+C4cOHRIoO2KqqKd6hB45/gehUxhSZ2cnJBL2dySpVEoj9QTy000x+Cr1Btq7+07t2p+Yi8qmdrz92FrYmuFYKzJ5FqyLxfF9BhsWv0vHAoNim4jLJ/9MQNqlQibm6mmPp1/YCIWSfrwPRafT4dJbbw/4MR4AB2D37t3YvHkzpFJqAyEjQ3/rRmi00zim2qZNm/CHP/wBfn5+CA8PR1paGv7+97/jkUceETo1s+RqZ4U/bF+C3e+fwu1dHwm55dj69y/w3uPr4WnkX1PEdDi6OyI0JhTXLt22YfGri1RUi9jJLzNw/PN0JmZto8QzL94JOwcrYZIyIQkJCaisqBj04zzPo6ysDAkJCVi2bNnUJUZMGrV/iMTrr7+OrVu34vHHH0doaCh++tOf4kc/+hFeeukloVMzW3fHzMQ7j90BCzn7u2tORQM2/+UQrpXXC5QZEaOFm9iT30pzS1F+Y/CigZiu9EuF+O/bZ5mYVCbBU7/dCC8/J4GyMi1VVVXD3zSK+wgBqKgWDVtbW+zZswclJSXo6upCQUEBfv/730OhoDYDIa2dHYj9u++Es40FE69u7sDWv3+Bs9dKBcqMiE1obCjsXeyZ2KUjiQJlQyZLcX4t3nz5G32rzy2PPLMKIZE+AmVlejw9PYe/CUCdjN7QJyNHRTUhk2xOoDu++Nk9mO7uwMTbu3vw8Jtf45MLOcIkRkRFKpX2a/dIoRMWRaWhtg17nj8MtUrDxDc/EItFq0IFyso0xcfHw8fHB9wQezkVzk7Y36PGseKiqUuMmDQqqgmZAv4udvj8p3cjeroHE9fqePzsv2fwl8OXaeQeGbcF6xeAu61K6O7oRvqZdOESIhOmq0OFV5//Es2N7Mz7hStDcNcD1Ds/WlKpFHv37gX43k2JAwnY+SB0HIffJSbiUH7+lOZHTBMV1YRMEQdrC/z36U3YNC+o38de//YKdr93CqoeGrlHxq53wyI7zvHiV9QCYuq0Wh3+7w/foLyogYkHR3rj+7tXMr9IkZHbsmUL/vmIPzxs2bi9uxtm7t4Np5hoAL3TQP6SkowPrmVPfZLEpFBRTcgUspDL8Pr3V+Ena/off/t5cj7+fPiyAFkRMYnbyG5YLMkpQQVtWDRZPM9j3xvfISu1hIl7+Djiqd9shFxBPb9jpe1sxGqvSlx4SoZPHpDitbukOLb/TdSXV+DxnQ/0u/+tjAy8mZ5O7yqSQVFRTcgUk0g4/O9dC/DyjiXMyYsA8MHZLDR3Ug8sGbuwuLB+GxYTj9IJi6bqm4NXcObrLCZma2+JZ1+6EzZ2FoM8RUZCXdb790Iq4RAXIMFds62wessPIJPJ8PScuXh01qx+z+zLuYa/pqRAR4U1GQAV1YQI5IH4cPznJ+sgl/b9NVRptPgi6bqAWRFTJ5VKEbvOYMPiiRSou9UCZUTGKjkhHwf+dZ6JyeRS7HphE9y8HIRJSkRUpReZa4VPNDhZ78QsjuPwg4hZ2D13br/nDt3Ix4uJidDQ4WrEABXVhAhoRYQ/1kYFMrGPL+TQ24tkXBasj+23YTGNNiyalBs5VXjnz8f6xX/4s7UIChvZODgyNFUpu99A6RfX7577gkPwq9jYfu8qHispxm8uXECPlvbBkD5UVBMisO2L2FFYORUNuFpaJ1A2RAycPJwQYrBhMZFmVpuM2qoW7P3tV+hRswXbvY8sQsySGQJlJS68Rg11eTITU/otHPDejdOm46WFiyCTsCXTmfIy/PLCeaipsCY3UVFNiMAWB/vAx4ndfk6zq8l4GW5YLM4uRmVhpUDZkJHqaOvGq7/5Em0tXUx86boIrN82T6CsxEddlQ5e083EFL4LBr1/hZ8f/rJkCZRSKRM/X1GBn507h26NZpAniTmhopoQgUkkHO5byK4qfpmSj05Vj0AZETEIjwuDnbMdE6PVauOm6dHijZeOoqqsiYlHzPPDzieX0ei8CaQqvcBcy93CILUa+oj3BZ5e+PuyZbA0OGXxcnUVfnruLLqosDZ7VFSLSFtbG3bv3g1/f39YWlpi4cKFSE5OHv5BIrh7F4QwPXvt3T04cqVAwIyIqRvohMXk47Rh0VjxPI9395xCTkY5E/cJcMbjv1oPmUw6yJNkLFQl7CbFwVo/DM11c8ery5bDyqCwTq2pwbNnvkNHDy2GmDMqqkXk0UcfxYkTJ7Bv3z5kZmZizZo1WLVqFSoqaEatsfNyssGyMF8m9jG1gJBxiqUTFk3G4Y+ScOEk+3fe3skKz7x0J6yslQJlJU48z/fbpKgYYJPiYKJcXfHaihWwlcuZeHpdHXaf+Q7tavrF1VxRUT1C7c3tU/rPaHV1deGzzz7Dn//8ZyxZsgRBQUF44YUXEBgYiLfeemsS/kTIRDPcsJhaWI3rVY0CZUPEwNnDCcHRwUyMWkCMz8XTufj8A3aWuEIpwzMv3glnN7tBniJjpWksgK6jlokp/Ue2Un1LuLMLXl+xEnYKBRPPqq/H09+dRisV1maJjmIaoV/f/Zspfb093706qvs1Gg20Wi0sLNjDACwtLXH+/PlBniLGZOUsf7jaWaKutW+D0v6LufjNPaP7Zk/I7RZujENuUq7+uii7GFVFVfAMpLFsxiAvswL/+ftJJsZxwE/+dx0CZrgLlJW4Gc6nlti4Q+Y4bdSfJ9jJCf+3YiWe/u40mlR9h3blNDbiyVOn8I/Vq/v1XxNxo5VqkbC1tUVcXBxeeuklVFZWQqvV4sMPP8Tly5dRVVUldHpkBORSKbYuYDcsfnY5D6oeGtdExi48Lhx2BtNlLn5Fq9XGoKqsCa+98BU0Bn/H7//xUsyJG32RR0ZmoPnUY90EGuToiP9buQrOBgta+c1N2J+XN+YciWmiolpE9u3bB57n4e3tDaVSiddeew33338/pFLa4GIqthtMAWls78aJzGJhkiGiIJVJEbueHRVGJywKr7W5E6/+5kt0tKuY+KrNUVh912xhkjITqhJ28sdINykOJtDeHm+uXAVXS0smnlBRPsgTRKyoqBaR6dOn4+zZs2hvb0dZWRmSkpLQ09ODwMDA4R8mRiHQzQELZngxMZpZTcbL8ITFrvYupJ/NEDAj86ZWa/Da746gtqqFic9eEIj7f7REoKzMg7azEZq6XCam9F807s/rZ2eHX8Wyv7zmNjaijXqrzQo1+4zQ7z9/SegURsza2hrW1tZoamrCsWPH8Oc//1nolMgobF8Yikv5fYd0JOSWoayhFb7OtGGJjI2zpzOC5wcjN7mvmEg8koiYtdECZmWedDoe//rrCdy4xrbl+Qe54ce/uAMSKa11TSZ1Gdv6wcktofCcPSGfO8rVFQqJBGqdDgCg43lcqa3BUh/fYZ4kYkFF9QjZONgIncKwjh07Bp7nERwcjBs3buC5555DcHAwvv/97wudGhmF9XOm4fkDCWjt6l3h4HngQGIu/mdjjMCZEVMWtzGOKaqLsopow6IADr13EUlnrzMxJ1cb7H5xEywsFYM8RSaK4XxqhXc0OKl8kLtHx0ImwyxXV6TW1OhjKdVUVJsT+pVYRFpaWvDEE08gJCQEDz74IBYvXozjx49DLp+YbxhkalgoZLg7ZiYTO3AxF9qbqx+EjEXEwv4bFmm83tQ6+00WjuxPYWIWVgo889JmODob/8KNGAy0SXEizXf3YK5Taqon9PMT40ZFtYhs27YNBQUFUKlUqKqqwhtvvAF7e3uh0yJjsH0hO7O6qrkDZ6+VCZQNEQOpTIrYdQOcsKiins+pkJVagvdfO83EJBIOT/xqPXwDXQTKyrzwGjXUFewvNaOdTz2caA92DGJxayvqOjsn9DWI8aKimhAjFO7rgkg/VyZGGxbJeC3YwG6k6mrvQgZtWJx05cX1+L/ffw2djmfiDz61HLPm+wuUlflRV6WB13QzMaXvgkHuHpsQRyfYGLw7fHs7CBE3KqoJMVKGJyyezCxBbQuteJCxu7Vh8XbUAjK5mhs68OpvDqOrk31HYP2987Bs/SyBsjJPhqP05G5hkFg6TuhrSCUSzHVjV6tTqKg2G1RUE2KkNs+fAUtF315ijU6Hzy7TYQJkfBZuZHtICzN7NyySiafq7sHeFw6jobaNic+PD8LWR8Y/xo2MjuFJihMxSm8g8z0Mi+pq8Dw/yN1ETKioJsRI2VoqsHHudCb2ycUc+uZMxiViUQRsHQ02LB69JFA24qXT6vD2H79F0fVaJj491AM/fG4tJJKxneBHxobn+UnfpHiL4WbFms5OlLe3DXI3ERMqqgkxYjsWhTHXRbUtuJxPq4pk7AbasJhCGxYn3Cf/TEBaYiETc/Www64XNkGhpGm2U03TeAO6jjomNt6TFAcTYGcHF4PTFZOrqQXEHExYUU2rZ0RoYvwanDfNHUEebM/fxxeuCZQNEYsFG9iiurOtE1fPXRUoG/E5+WUGjn+ezsSsbJR45qXNsHOwEiYpM6cqYVepJTYekDpOzmnDHMdhXr++ahqtZw7GXVTfmoHcSSNjiMBufQ2KaS43x3HYYbBh8ev0QjR3qgTKiIiBi5cLguezs9Av0obFCZF+qRD/ffssE5PKJHjq+Y3w8nMSKCvSr5/aLw4cN3ktOIZ91UnV1ejRaift9YhxGPd7UFKpFA4ODqit7e0bs7KymtQvVEIM8TyPzs5O1NbWwsHBAVKpVOiUJtSWmJn44xeX0KPtPfxF1aPFl8n5eGhphMCZEVMWtzEOeSl9J/sVXi1EdUkNPPzdh3iKDKU4vxZvvfIteIPReY/sXoXQKB+BsiLAQJsUJ6f145YFnl7MdUdPD67U1iLWk04wFbMJaezy8Ohtyr9VWBMiBAcHB/3Xopg421piTVQgjl4p0Mc+vnANDy4Jp19gyZhFLIyAjaMN2pva9bHEIxdx9xN3C5iV6WqobcOe5w9D1d3DxDc/EItFq0MHeYpMBW1nAzR1uUxM6Te501dcLC0R4eyMrIYGfexceTkV1SI3IUU1x3Hw9PSEm5sbenp6hn+AkAkml8tFt0J9ux2LQpmi+lp5A66W1iHK303ArIgpk8lliL0jBqc+7jvlL/lYCjY+thFyhXhaqKZCV4cKe54/jObGDiYetzIEdz0QO8hTZKoYTv3g5FZQeEZN+usu8fFliuqEinL8z/z5kNBiiGhN6BZkqVQq6sKGEKEsDvaBj5Mtyhv7xjJ9ciGHimoyLnEb4piiurOtExlnr2L+6nkCZmVatFod3nz5G5QV1TPx4FneeGT3Sno3yQioDVo/FD7R4KST/4tjvI833sxI11/XdXUht7ERYc7Ok/7aRBg0Uo8QEyCRcLhvYQgT+zIlH50qemeIjJ2LtwtmzmM3LNIJiyPH8zz2vfEdMlNKmLiHjwOeen4j5AoanWcMpmo+taEAO3v42doxsXPl5VPy2kQYVFQTYiLuXRDCvG3Y3t3DtIQQMhaGJywWXC1ATSnN1B2Jbw9ewZmvs5iYrb0lnn1pM2zsLATKityO16igqkhhYpM1n3ogS3y8meuECiqqxYyKakJMhJeTDZaF+TKxjy7kCJQNEYuIRRGwcbBhYhe/otXq4SQn5GP/v84zMZlciqd/uxFuXg7CJEX6UVemAZrbRpByHJS+C6bs9Zf4sFNfCltaUNbWOmWvT6YWFdWEmBDDExZTC6txvapRoGyIGMjkMsTcEcPEko8no0dNrUWDKcitxjt/PtYv/sPn1mBGuNcATxChGI7Sk7uGQWLpMGWvH+7sAicL9l2Lc+UVU/b6ZGpRUU2ICVkxyw+uduzxt/sv5g5yNyEjE7eRXbnrbKUTFgdTV92CPc8fRo+aPchj6yMLEbN05iBPEaGoSi4w10r/yR2lZ0jCcYj3phYQc0FFNSEmRC6VYusCdsPiZ5fzoOqhk7rI2Ll6u2Lm3BlMjE5Y7K+jrRt///WXaGvpYuJL7gjHhm3zBcqKDIbneajKLjGxqdqkeDvDFpCrdXVo7O6e8jzI5KOimhATs91gCkhjezeOXy0SKBsiFnGGGxYzClBTSgd63aLp0eKNl46iqqyJiYfP9cODTy2n0XlGSNOQD11HHROb7JMUBzLP3QNWsr5JMDyA8xXUAiJGVFQTYmIC3RwQN4Pt2/yENiyScZq1eFa/DYs0Xq8Xz/N4d+8p5GSwb9v7BDjjiV+vh0xG5zMYI8NRelJbT0gdAqY8D6VU2u8kRWoBEScqqgkxQdsXscceJ+SWo7SedpSTsZPJZYhZG83Eko/RhkUAOPxREi6cYH9xtXeywjMv3Qkra6VAWZHhGG5SVPjFCfaOwlKDFpCkqip00gnUokNFNSEmaN3sabCzVDCxTxNpwyIZH8MWkI7WDlxNyBQoG+Nw8XQuPv+A7ctVKGV45sU74exmN8hTxBioStiieirnUxuK8/KG9LaCXq3TIam6WrB8yOSgopoQE2ShkGFLDDtpYH9iLrQ6nUAZETFw9XHFjDnshkVzbgHJy6zAf/5+kolxHPDjX9yBgBnuAmVFRkLbUQ9NfR4TE7KotlMoMMfNjYnR6YriQ0U1ISbKsAWkurkDZ7LLBMqGiIXhavWN9BuoLTO/DYvV5U147XdHoDGYrLPjR0swd+F0gbIiI2XYT83JraDwjBIom16GU0DOV1ZAQwshokJFNSEmKszHBVH+7MrHJxdpwyIZn8jFs2Btb83EzG21uq2lC3//9ZfoaGPHnq3aHIU1d88RKCsyGv36qX1iwEnlAmXTK96bLarb1Gpk1NUNcjcxRVRUE2LCDFerT2YWo7alU6BsiBjIFP1PWEz6NhkatUagjKaWWq3B3he+Qm1VCxOPig3E/T9aIlBWZLTUBivVQsynNuRhbY1gR0cmRi0g4kJFNSEm7M55QbBU9M0/1ep4HLycN8QThAwvbgN7wmJHaweunhf/CYs6HY9//fUEblyrYuL+Qa74yf/eAYmUfmSaAl6jgqoylYkJMZ96IIYtIOcqysHzvEDZkIlG3yEIMWG2lgpsmhfExD65kEPfpMm4uPm6YcYc9uvKHFpADr2fiKSz15mYk4sNdr94JywMpu0Q46WuvAJoVH0BjoPSd8HgD0yhJQYtINUdHchvbhYmGTLhqKgmxMTtMGgBKa5rwaX8SoGyIWJhuGExP03cGxbPHcvGkU+SmZiFlQLPvHQnHJ1tBnmKGCPDfmq5WzgkFvYCZcOa7uAAL2t2z0ICtYCIBhXVhJi4uYHumOHJ9unRCYtkvCIXR8Lajv3hf+nopUHuNm3ZV0rx/t7TTEwi4fDEr9bDd5qrQFmRsVKVXGCuhRylZ4jjuH4tIGepqBYNKqoJMXEcx2HHQna1+uu0QjR3qgZ5gpDh9W5YZE9YvPxtkug2LFYUN+CNl45Cq2VHmz341HLMmu8vUFZkrHieh6qU/eXPWPqpb4k3KKrzm5tQ1d4uUDZkIlFRTYgIbImdCfltm6hUGi2+SLo+xBOEDG/BBoMTFls6cPW8eE5YbG7swN9/8yW6OtVMfN2987Bs/SyBsiLjoam/Dl1nPRMzppVqAIh0cYW9gj3ePqGiQqBsyESiopoQEXCyscTaqEAm9jFtWCTj5O7nhulR7EEnYtmwqOruwd7fHkZDbRsTnx8fhHsfWSRQVmS8DA99kdp6QepgXO84yCQSLPL2YmI0Wk8cqKgmRCR2LA5jrnMqGnC1hA4WIOOzcBO7ypeflo+6ctP+utJpdXj7j9+i6Dq78XJaiAd++NxaSCScQJmR8TLcpKj0iwPHGd//n4Z91el1tWhRUcueqaOimhCRWDTTG77OtkzsYzphkYxTZPysfhsWE018w+L+f51HWmIhE3P1sMPu322CQikb5CliCvqdpGhk/dS3xHp4QimV6q+1PI+LlTS1ydRRUU2ISEgkHO4z2LD4ZXI+Orp7BMqIiIFcIUf0WnbDYtK3SdD0mOaGxZOHM3DsUBoTs7JR4pmXNsPOwUqgrMhE0HbUQVPP7iUxtn7qWyxkMsR4eDAxagExfVRUEyIi9y4IhuS2tzo7VD04cuWGgBkRMYjbyB6c0d7cjkwT3LCYfrkI/33rLBOTyiR46vmN8PJzEigrMlEM+6k5uRUUHpECZTM8wxaQS1WV6NaY5i+rpBcV1YSIiKejDZaF+zExmllNxsvdzx3TI017w2LJjVq89fI34HXs5t3v716J0CifQZ4ipqRf64dvLDipXKBshrfIy5tZBOnWapFSUyNgRmS8qKgmRGTuNzhhMbWoBnmVjQJlQ8Ri4SZ2vN71K/moqzCNDYuNdW149fnDUBm0Qm3+XgwWrw4b5CliagxXqpV+cYPcaRwcLSwQ6eLCxKgFxLRRUU2IyCyP8IOrHdsbup82LJJxilwSCSuDrytTOGGxq1ONV39zGM0NHUw8bmUI7tq5YJCniKnhe7qhrkhlYsbaT307wxaQ8xXl0Op0g9xNjB0V1YSIjFwqxb0LgpnYZ5evQ9WjFSgjIgZyhRzRawY4YdGINyxqtTq8+YevUVbEHgYSPMsbj+xeaZSj1sjYqCuvANrbDvHhOCh9Y4VLaITivdmiukmlQlZDg0DZkPGiopoQEdpuMAWkqaMbxzKKBMqGiEXcRvbt9PamdmRdyBIom6HxPI8P/+8MMlNKmLiHjwOeen4j5AoanScmhv3UcrcISCzsBcpm5HxsbTHNns2TWkBMFxXVhIhQgJs9Fs5kT+z6hFpAyDh5+LtjWuQ0JnbRSDcsfvtZGr47yk4osbW3xLMvbYaNnYVAWZHJ0u/QFyOdTz0QwxaQc+VldBquiaKimhCR2m6wYfF8bjlK61sFyoaIxUKD1errqddRX1E/yN3CSE7Ix4F/JTAxmVyKp3+7EW5eDsIkRSYNz/Mmt0nxdksMWkDK29tR3Erfq00RFdVGRKvV4syZM/j4449x5swZaLXUA0vG7o7Z02BvpWRiBxJzBcqGiEXU0ihY2bIbFhO/Np4NiwW51Xjnz8dguND3w+fWYEa418APEZOmqc+DrpPtQ1b6LxIom9ELcXKCq6UlEztLLSAmiYpqI3Ho0CEEBARg+fLluP/++7F8+XIEBATg0KFDQqdGTJSFXIa7Y2Yysf0Xc6HR0s5yMna9JyzOZ2KXv7lsFBsW66pbsPe3h9GjZhcktj6yEDFLZw7yFDF1hqvUUjtvSO39Brnb+HAc168F5EIFFdWmiIpqI3Do0CFs3boV5Qa/mVZUVGDr1q1UWJMx22GwYbGmpQNnrpUKlA0Ri7gNA2xYvCjshsWOtm68+pvDaG3uYuJL7gjHhm3zB3mKiEG/fmq/OJOb7GI4BSS7oQEtKpVA2ZCxoqJaYFqtFrt27RpwU8Kt2O7du6kVhIxJqI8zZge4MTE6YZGMl0eAB6bNCmRiQp6wqOnR4o2XjqKylD3kKHyuHx58arnJFVhkdFQlhkW16WxSvGW2mxuUUqn+mgdwuapKuITImFBRLbCEhIR+K9S343keZWVlSEhIGPQeQoZiOF7vVFYJalo6BrmbkJExHK+Xl3Id9ZVTv2GR53m8t/cUcjLY76Pe/s544tfrIZNJB3mSiIG2ow6ahnwmZopFtVIqxTx3dyZ2iYpqk0NFtcCqRviXZqT3EWLozvlBsFL2zeTV6ngcvJQnYEZEDAbasHjp6OUpz+Orj5Nx/gT77ou9kxWeeelOWFkrB3mKiIXhKjWnsIbcI1KgbMZngacnc32pqgo6Gq1nUqioFpinwV+i8d5HiCEbCwU2zQ1iYp9czIFOR9+sydgplArMX9N/w6JWM3Wtaomnc3HofbbtRKGUYffv7oSLu92U5UGEY7hJUeETA05qmgf7xHmy02maVN243tQkUDZkLKioFlh8fDx8fHwG7fnjOA6+vr6Ij4+f4syImBjOrC6pa8Wl/EqBsiFiEbdhAXPd1tQ2ZScs5mVW4N9/P8nEOA748S/uQOBM90GeImLTf5Oi6bV+3OJjawsfGxsmdqmKvk+bEiqqBSaVSrF3714AGKSw5rFnzx5IpdQXSMZubqA7Zno6MjE6YZGMl2egJwIj2A2LU3HCYnV5E1773RFoethV8e0/XIK5C6dP+usT48D3dENdeYWJmdJJigOJ82JXqxMrqfXTlFBRbQS2bNmCgwcPwtvbm4nbuljgh7/fgi1btgiUGRELjuP6rVZ/k1aI5o5ugTIiYtF/w2IeGqoaBrl7/NpauvDqb75ERxv7tbvyziisuXv2pL0uMT6qylRAq+4LcBIofWKFS2gCGLaAZDXUo1WtHuRuYmyoqDYSW7ZsQXFxMf6x/+9Y/2wktr0UjUffXgqbsE40dtQInR4RgS0xM6GQ9f2VV2m0OJR0XcCMiBjMXhYFSxv2NLhLRyfnhEW1WoPXfvcVaipbmHhUbCC+9+MlNDrPzKgNNinK3SMgsTDtXvo5bm5QSPq+T+t4HsnV1QJmREaDimojIpVK8f17HsfcFTPhG+EMibT3B0Ry6XGBMyNi4GRjibVR05jYxxdyBpyRTshIKZQKRE/BhkWdjse//3YC+dns2+H+Qa74yf/eAYmUfpyZGzH1U99iIZNhjhu7JyCxkvqqTQV9FzIycqkSc3yWM7Hk0hPQ8XT4Cxm/HQYtIHmVjcgoqRUoGyIWhi0grY1tyLqYPaGvcej9RFw+w76z4uRig90v3gkLS8WEvhYxfrxO12/yh9IvbpC7TYvhaL3L1VW0+GEiqKg2QjH+a5jr5q465NelC5MMEZWFM73h62zLxD6mExbJOHkGeiIwPICJTeQJi+eOZePIJ8lMzMJSjmdeuhOOzjaDPEXETFOfB10Xe4KmqW9SvMVws2J9VxduNDcLkwwZFSqqjZCPQxC87Nm36ZNKqAWEjJ9EwvU7YfFwyg10dPcIlBERi8nasJh9pRTv7z3NxCQSDo//aj18p7mO+/MT02S4Si2184HU3k+gbCaWn60tvKytmVgijdYzCVRUG6kY/7XMdVbVRXSoWwXKhojJvXHBkNy2oatD1YOvUm8ImBERg9nLZsPC2kJ/zfM8Ln09vhMWK4ob8MZLR6HV6pj4zieXIzI6YFyfm5i2/v3UcaLZqMpxHBYYTAGhI8tNAxXVRmquz3LIJHL9tVanwZWy7wTMiIiFh4MNloezKzo0s5qMl8JCgeg10UxsPBsWmxs78Pfnv0RXJztObN2987B8w6wx50nEoV9RLZLWj1sWeLF91Vfr6tDRQ+8oGjsqqo2UlcIWEZ7sN4mkkmO0WYFMiB2L2RaQK0U1yKucvNnCxDzEbWRPWGxtaEV24ug3LKq6e7D3t1+hoaaNic9fHIR7H1k0rhyJ6dO210LTwL67JobJH7eb5+YO+W2j9bQ0Ws8kUFFtxAxbQKpai1DRQm/Tk/FbEe4PN3srJvbJxVyBsiFi4TXNCwEGGxZHe8KiTqvDP/50DEXX2fn800I88MOfrYVEIo63+MnYGfZTcwpryN3F9e6FlVyOKFd2zwAdWW78qKg2YkGuUXC0dGNil0uOCZQNEROZVIJ7FwQzsc8u56G7RyNQRkQs+m1YTM5DQ3XjIHf3t/9f53HlYgETc3G3w+7fbYJCKZuQHIlpM2z9UPjEgpOK72vD8HTFxCoarWfsqKg2YhJOgmiD8XppZWfQo1UJkxARlfvi2BaQ5g4VjmcUCZQNEYs5A2xYvPz1yE5YPPVVBo4dSmNiVjZKPPv7zbBzsBrkKWJuxN5PfYthX3VtZyeKWlsGuZsYAyqqjdx8v1Xg0Pd2Z7emA5mVFwTMiIhFgJs9Fs5kV0JoZjUZr94Ni+wJi5e+vgytdugNi+mXi/Dhm2eZmFQmwVO/2QAvP6cJz5OYJl1PF9SVV5iY2Pqpbwm0s4e7FfvLZGIlTQExZlRUGzknK3fMcJ3NxC7TzGoyQXYsCmOuL+RVoKSeRjeS8el3wmJDK7ITrw16f0lBHd56+RvwOvat7e/vXonQ2b6TkiMxTeqKVEB72xQMTgKlb6xwCU2igUbr0bxq40ZFtQkw3LBYUJ+Bhg76bZWM39rZgbC3UjKxAzRej4yT1zQv+If5M7HBTlhsrGvDq7/5EiqDA4juvD8Gi1eHDfgMMV+GrR9y91mQKG0Hudv0GR5ZnlFXh04arWe0qKg2AeGecbCUs0fxJpecECgbIiYWchm2xMxkYgcS86AxOGyDkNFaaLBanZuUi0aDDYtdnWq8+vxhNDd0MPG4FcG4+0F2PB8hgPn0U98S7eEB6W2H2mh0OqTW1AzxBBESFdUmQC5VYJ7vCiaWXHYCOn5shyoQcrsdi9gNizUtHfguu1SgbIhYDHfColarw1svf42ywnrmuZkRXnjkmVWiOR2PTBxep4O6lN30qvSLG+RucbAeYLQetYAYLyqqTYRhC0hLVz2u16YNcjchIxfi7Yw5AezoRjphkYyX0lKJ+avmMbHL3/RuWOR5Hv998wyuJpcwH3f3dsDTv90IuUJ849HI+Gnqc6HrYt/tEOsmxdsNdGQ5jdYzTlRUmwgv+2nwtg9iYkk0s5pMkO0Gq9Wns0pQ3dwxyN2EjMztGxZ1vA7Z+Vn420t/w59f/CdOfpXB3Gtrb4lnX9oMGzvLqU6TmAjDQ1+k9r6QOfgJlM3UiTPoq67q6EBJG20oN0ZUVJsQw9Xq7KpLaFc1C5MMEZVN84JgddvBGlodj4OX6IRFMj7eQd7wD/XHjbobePfSf/BZxmf4+e9+jl+88CN8du5FlNT0FtYyuRRP/3Yj3L0dhE2YGLV+/dQib/24ZbqDA1ws2V82L9FoPaNERbUJmeuzDDKJQn+t5TW4UvadgBkRsbCxUODOeew7IZ9czIVOR28xkvFROXbjaPYRtKvamXinqhlnMt5FSU0GHvvpGswI9xrkMxDSS1XCrlSbQ+sHcGu0HrtaTUeWGycqqk2IpcIGs7zYbyJJpcept4pMCMMWkNL6ViTmVwiUDREDrVaLN95/Y8h7ssq/xvz46VOUETFV2vYaaBpvMDFzWakG+h9ZnlZbi26NRqBsyGCoqDYxhi0g1a3FKGu+LlA2REzmBLgj2Is9ue4TOmGRjMOnX3+JioqhfzGrb6jBm4cOoV2tnqKsiCky7KfmFDaQu88SKJupZzhaT63T4UotjdYzNlRUm5jpLpFwsvJgYkl0wiKZABzHYftCdrX6m/RCNLV3C5QRMUVNXW34z5XjuOODX+ORD/80omdeO3cWaw99hh8cP4Y309ORVFVFq3CEoSox6Kf2jQUnNZ8pMbYKBSJcXJgYHVlufMznK1IkJJwE0X6rcSx3nz6WXn4Gd0Y8BoXMYognCRnelpiZeOWLRKg1vYe/qDU6HEq6jh+siBQ4M2LMujVqHLtxBQeyzuH4jSvo0fXO0JfYjux7ktzBATqex7WGBlxraMC+nGuQSSSIcHbGPHd3zHP3QLizMxRS6WT+ZxAjZrhJUWFGrR+3LPD0QkZdnf6a5lUbHyqqTVC032ocz/0QPHp7qbs1nbhaeR7z/VYJnBkxdY42Frhj9jQcTunrXfzkYg4eWT6LDuMgDB2vQ2JZLg5kncMXuZfQ0t1/BKM0wBWcnSX41q5BP4/C2Ql2ISH94hqdDul1dUivq8O/s7KglEoR6eKKOW5umOvuhlAnKrLNha6nC+oq9lwGC/9FAmUjnDhPT/zjat8oyor2dpS1tcHXVrzHtJsaKqpNkIOVK2a6zUNebYo+llRynIpqMiG2Lwxliuq8ykakF9diTqC7gFkRY5FXX44DWedwIPs8ylrqhryXk3Bw3bIAte/1n1LEcRx4AMuffBKdMhl6dLohP5dKq0VyTTWSa6qBTEAplSLCxQVz3dwwx82dVrJFTF2RAmh7+gKcBAqfGOESEsgMR0c4WVigsbuvJe9SVSV8bYMFzIrcjopqExXjv4YpqgsbMlHfXgkXGxpLRcZn4Uxv+LnYobS+73CBjy/mUFFtxmrbm3Hw2gUcyDqH9OrCYe9XSuVYP3M+tkUsQbjCHw+l/RxJuZ+j87a5+j4+PtizZw+2bNmCbo0GmfX1uFJbg5SaGuQ0NEA7zFQjlVaL1JoapNbUAMiEQipFhLMz5rq5Y46bG8JdXKCkIlsUDPup5R6RkCjNb3VWcnO03tdFRfrYpaoq3DuTimpjQUW1iQr3iIWVwg6d6r7CJ6n0ONaHPSxcUkQUJBIO2xeG4M+Hk/Sxwyn5eP6ehbCxUAzxJBGTDnU3jl5PxoGsc/iu6Cq0/NAryQCw2C8c981agjuDY2FvYQ0AOH3kKvzdo+DrNgu1TQXg5Cr87A/3Y8mSJZDeLHotZDJEe3gg2sMDPwLQ0dODjLpapNTU4EpNDa43NWG4waFqrRZXamtxpbYWAKCQSBDu4tLbLnJzJdtCRj/yTJHh5A9zmU89EMOiOrWmBiqtln6BNBL0HcZEyaQKzPNdgYSCL/SxlNKTWBuyE1IJ/eUi47N1QQj++lUydDdXCztVGnyVegM7FoUJnBmZTFqdFmeLs7A/6xyO5F1GR49q2GdCXHxwX8QSbA1fDF97134fz0kvB9C7ydrDaQbiVgRj+fLlQ35Oa7kcC728sdDLGwDQolIhrbb25j81uNHcPHyRrdPpn/kPsiCXSBDu7IzZN4vsWS4uVGSbAF6ng7rMsKg2v02Kt8R4eELCcfrvzSqtFmm1NVjgSe9SGwP6jmLCYvzWMEV1a3cD8mpTEeZhfr1mZGJ5OFhjRYQfTmaW6GOfXMiholqEeJ5HZm0x9meew2fXLqC6vWnYZ9ytHbA1fDHum7UEs9wCBt3EqtPxyL1azsRCZ/uOOkd7pRLLfH2xzLf32RaVChl1dUirrcGV2lrkj2Alu+e2jY/vZWdDJpEgzMkZc93dMMfVDbNcXWFJRbbR6anLga6L/ZpU+pvvSrW9UokwJydkNTToY5eqqqioNhL0HcSEedoHwtdhJnP4S1LJMSqqyYTYsSiMKarTimuRW9GAEG9nAbMiE6W8tR6fZiXgQFYCcurLhr3fWq7ExuBYbJ+1BEv8I0b0jlhFSQPaWtjJH6FRPmPO+RZ7pRJLfHywxKf3c7Wq1cioq0VaTS3S6mpxvalJv5I3GI1Oh6v1dbhaX4f3kA0pxyHU2fnmxkc3RLq4wkouH3euZHzUBq0fUntfyOxH/4uZmCzw8mKK6sTKKuyeK2BCRI+KahMX47+WKaqvVV9Gm6oZtkoH4ZIiorA83A9u9laobenUxz65mIMX7l0sYFZkPFq6O3A47zL2Z57DhdJr+rGcg5FwHFYERmFbxBJsmBkNa8XoZuHnZrCr1C7udnD1sB913sOxUygQ7+2DeO/eIrtdrUZGXR2u3GwXyRtBka3leWTV1yOrvh4fXLsGKcchxMlJv/Ex0tUV1lRkTznD+dTm3E99S5ynF/6Vmam/Lm1rRWV7O7xsbATMigBUVJu82T5LcTjrHfRoe3sfdbwWqaWnsGzGPQJnRkydTCrBtgUheOPYFX3sUNJ1/OKuBbCQ07cOU6HW9uBUYQb2Z57DN/kpUN0+mmwQsz2mYVvEEtwTthDuNo5jfu1r6ewKeOjs8a9Sj4SNQoFF3t5Y5N3bk93R04OrdXW4crNdJK+xcdjpIlqeR3ZDA7JvHkYj5TgEOzlhjmvvnOwoVzcqsqdAv02KZtz6cUuIkxMclEo0q/r2PFyqqsKWGTMEzIoAVFSbPEu5NSK9FiO17JQ+llR6DEuDttBhHWTcti1ki+rmDhWOpRdhczR98zZmPM8jpTIfB7LO4bNrF9HY1TbsMz52LrgvIh7bIpYg2GX8xa9Oq+vfTx0lzNv21nI54ry8EOfV23d6q8i+tfExZ4RF9q0TH/+bmwMJxyHY0VG/8THK1RW2CpqOM5G07TXQNBYwMXPepHiLhOMQ6+GJYyXF+lhiVSUV1UaAimoRiPFfwxTVtW1lKG3Khb9TqIBZETEIcLXHwmBvXMyr0Mc+vphDRbWRKmyswoHs8ziQdQ6FTdXD3m+ntMLdoXHYFrEEcb4hkHCSCcultLAOXR1qJjYR/dQTwbDI7uzp0c/JTqutxbURzMnW8TxyGhuR09iIj3NzIeE4zHBw0LeLRLm5wY6K7HExnE/NKW0hd58lUDbGJc6LLapTa2qg1mrpACSBUVEtAtOcZ8HZ2hMNHVX6WFLJcSqqyYS4f1EoU1RfzKtAcV0LAlwnvjeWjF5DZys+z0nE/qyzSK7IH/Z+uUSKNUFzsS1iCdYGzYWFbHIKv2vp7Cq1h48DHF2Ms+fTSi5HrKcnYj09AQBdNw+jSbtZZGc3NEAzzImPOp5HXlMT8pqa8HFeLjgAQQ6OmOvet5Jtr1ROwX+NePRr/fCJBUcjYwH0jtbjAP2uiC6NBhl1dYj28BAyLbNHRbUIcByHGL81+CbnfX0sveIs7pz1Iyhlo9tYRIihNVGBcLBWormjr39v/8Uc/HzzAgGzMm/dGjW+zU/F/qxzOFGQBo1OO+wzsT7BuC9iCe4KiYOT1eSfRpebYdBPLVDrx1hYymSI8fBAzM0CpVtfZPe2i2Q3NAx7rDoPIL+5CfnNTdifl3ezyHbAnJvHqs9xc6Miexiq0gvMNbV+9HG0sECIkxNyGhv1scSqSiqqBUZFtUjM91uFb3P2gUfvN3qVpgtXKxIQ7b9a4MyIqbOQy7AlZib+813fbvMDiXn4n40xkEknrl2ADE3H63ChNAcHss7hy9xEtKq6hn1mupMn7otYgm3h8QhwnLpj5jUaLfIyK5nYWOZTG4vbT3wEeovs7IYG/Zzs7Pp6qEdUZDcjv7kZB673Tmyabu/QOyfbzQ2zXd3gaEGLILfo1J1QV6YxMdqkyIrz8mKK6stVVcAcARMiVFSLhb2lC4Ld5yG3JlkfSyo9RkU1mRDbF4YyRXVdaydOZ5dgTWSggFmZh5y6MhzIOodPsxNQ3tow7P3Olra4J3wx7ouIx1zPIEE2LBfl1UDVzU4ZCYn0nvI8JouFTIZ57u6Y5977i4pKq0V2Q33vnOzaWmQ21EOtHf7dg4KWZhS0NOPTm0X2NHt7ZiXbyYyLbHVFCqDT9AUkUih86AyG2y3w9MR/srL014UtLajp6IC7tbWAWZk3KqpFJNZ/LVNUFzVko669HK42xrE5iJiuEG9nzAlwQ1pxrT72yYUcKqonSXV7Ew5mn8eBrARcrSka9n4LmRwbZsZgW0Q8VgRGQS4V9lt7jsF8ap9AZ9g5WAmUzeRTSqWY6+aOuW69RbZaq8W1hgb9xsfM+nqoRlBkF7a0oLClBZ/l9/bGB9jZ9W58dHfDXFc3OFlaTup/hzExnE8t94iERDn5bUumJMzJGbYKBdrUfRuCE6uqcFdQkIBZmTcqqkUk1CMG1gp7dKhb9LGkkuPYEP6IgFkRsdixKIwpqk9nlaK6uR0eDsa5+czUtKu7cCQvCQeyEnCm+Oqwh5Vw4BDvH477Zi3BpuBY2CmNp2jNMeF+6omgkEox280Ns93cAPQW2TmNDUirrcWVmlpk1tehewRFdnFrK4pbW3HoRm+R7W9nhzlubjdPfXSHi4iL7H6bFOnQl36kEgliPTxwsrRUH7tUVUlFtYCoqBYRmUSOeb4rca7gkD6WUnoSd4Q+NKIjhQkZyqZ5QfjdwQvoUPW+ra/jeXyamIen1s0TODPTpdFpcbY4E/szz+HI9SR09qiGfSbM1Q/bZy3BPWGL4W1nfEfGq9Ua3LhWxcSMZZSeUBRSKaJcew+MeTgc6NFqkdPYqN/4mFE3siK7pLUVJa2t+OLGDQCAn62tvlVkjpsb3KyM5xer8eB1ugGKatqkOJAFnl5MUZ1cXY0erRZyGq0nCCqqRSbGfw1TVLepmpBbk4xwT5rUQMbH2kKOTfOD8MmFHH3sk4s5eGLtXEgkdNDQSPE8j4yaIuzPPIfPrp1HbUfLsM942jji3psHs0S4+U9BlmNXkFONHnVfgchJOARHmndRbUgulSLS1RWRrq54KDwcGp0OuY2N+naRq3V16NRohv08pW1tKG1rw5cFvUW2j40N5rq73zz10d1ki+yeuhzw3c1MjFaqB7bg5hjIWzpvTqqZ6z51G5NJHyqqRcbDzh9+jsEobcrTx5JKjlNRTSbEjoWhTFFd1tCGi9crsDiEiqbhlLbU4dOsBBzIOoe8hoph77dRWGBTcCy2RyzFYv8wk3m3KcfgaHL/6a6wtqHRcUORSSSIcHFBhIsLHgzrLbLzbq5kX7m5kj2SIru8vR3l7e04XNB7CqG3jc3NdpHe1WwPE9nAZthPLbX3g8yevscMxNnSEjMdHXG9qUkfu1RVRUW1QKioFqEY/7VMUZ1Tcxmt3Y2ws3ASMCsiBrMD3BDi5YTcyr4xTp9czKGiehDN3R04nHsJn2SexcWynGHvl3ISrJwWhfsilmLdzPmwkpteMZprsEnRlEfpCUUmkSDcxQXhLi54ICwMGp0O15uamCK7o6dn2M9T0d6OivZ2HCksBAB4WVvr20XmurnB08Y490MYnqRIrR9Di/P0YorqxKpKPD57tnAJmTEqqkVotvcSfJn5D/Roe/szdbwOqWWnsXzGVoEzI6aO4zhsXxSKFz7tO5Th2/RCNLZ3wclGvJumRkOt7cGJgnTszzyLYzeuQKUdvviZ6zkd90UsxZawhXC1Nt2TKlXdPSjIZY9HN/d+6okgk0gQ5uyMMGdnfC80FFqdDvnNzbhSU4O0ulqk19aifQRFdmVHByqLCnG0qLfI9rC2vrnpsXc129PaWpARjIbUhv3U/osEysQ0xHl54v1r2frrG83NqOvshKuJtv+YMiqqRchCbo0or3iklJ3Ux5JKjmFZ0D1G8Q2TmLYtMTPxyueXoNL09s2qNTocSrqOR1dECZyZcHieR1LFdezPPIvPcxPR1NU+7DN+9q7YFrEE90XEY4azOGY4X8+qhFbbdwiKVCrBzAgvATMSJ6lEghAnJ4Q4OeH+m0X2jeZmXLm58TG9thZtIyiyqzs68HVREb4u6h3b6G5lpZ+TPdfNDd42NlP+M0PbVg1NUyETo5XqoYU7u8BGLmd+sbpUVYVN06cLmJV5oqJapGL81zJFdV17OYobryHQOVzArIgYOFhb4I7Zgfgy5YY+9smFHPxgeaTZ/dJW0FiF/VnncCArAcXNNcPe72BhjbtDF2JbRDwW+ISI7s/LcJReYLA7LCwVAmVjPqQSCYKdnBDs5IQdISHQ6nQoaGnRn/iYXluL1ttmGQ+mprMT3xYX49viYgCAm5XVzU2PvavZPja2k/41a9hPzSntIHePmNTXNHUyiQTRHh74rqzv719iVSUV1QKgolqkAp3D4WLtjfqOvg1RySXHqagmE2L7olCmqL5e1YS04hrMDfQQMKupUd/RgkM5F3EgKwEplfnD3q+QyrA2aB62RcRjzfS5UMrkU5ClMHLSDfqpqfVDEFKJBDMdHTHT0RH3BYdAx/MobG5GWl3vnOy02lq0qIcf31jb2YljJcU4VlIMAHCxtNS3isx1c4Ov7cQX2f1G6fnGgjORTbpCWuDpxRTVydXV0Oh0kEkkAmZlfqioFimO4xDjvwZfX3tXH0uvOIc7Z/0IFnLqsyLjEzfDG/6udiipa9XHPrmQI9qiuqtHhW/yU7A/KwGnCtOh0Q0/UzjONxT3RcTjrpA4OFga54awidTZoULxjVomRpsUjYOE4xDk6IggR0fcOzMYOp5HUUuLfoRfWm0tmlXDF9n1XV04UVKCEyUlAABnCwvMdXPHbLfe1Wx/W7txF9mqkgvMNbV+jIzhaL32nh5kN9QjytVNoIzMExXVIjbfbxW+zXkfOr63x1Gt7UZGRQJiA9YKnBkxdRIJh/viQvHnw5f1scOpN/D81kWwsRDH2/06XoeEkmwcyErA4dxLaFN3DfvMDCcv3DdrCbaGL0aAg3mNtMrLrACv6zsFUiaXIijUc4gniFAkHIfpDg6Y7uCAe2cGg+d5FLe24kptjX4lu0nVPeznaejuxonSEpwo7S2ynSws9AfRzHVzR4Dd6IpsnboT6qp0JkbzqUfGzcoKQQ4OuNHcrI8lVlZRUT3FqKgWMTsLJ4S4R+NadV/hk1x6nIpqMiG2LgjG344kQXuzkOpUaXA45QbuXxwmcGbjk11bggNZCTiYfR4VbQ3D3u9qZY97whfhvoglmO0xTXR90iNlOJ86KNQTCiX9iDEFHMch0N4egfb2uGfGTPA8j5LWVv3Gx7TaWjR0D19kN3Z341RpKU7dPOHPUansXcW+OcYv0N4ekiH+fnSVXkJioRq17YCbDRATIIPCJ2bC/jvFboGnJ1NUX6qqxI+jzHcDuRDoO57IxfitYYrq4sZrqGkrhbutn4BZETHwcLDGigh/nLharI99cjHHJIvqqrZGHMw+j/1Z55BVWzLs/ZYyBTYGx2BbxBIsD4yEjHo+kdNvPjX1U5sqjuMQYG+PAHt7bJkxAzzPo7StjWkXqe8a/p2bJpUK35WV6Xt9LWUy+NjYwMfWFr62tvCztdP/7++OHsXTP3kElXV9rVWeDlK8Mec4tmzZMmn/rRNFx/Po0enQo9VCrdVCrdOhR6eFWqtDj04HtVbL/lunRY/29nsG+LdON/g9N1/r9s9pOFYxr6kJDV1dcLakcadThYpqkQv1iIGt0hFtqr7B8Eklx7Ep4lEBsyJisX1hKFNUpxfXIqe8AaE+zsIlNUJtqi58lXcZB7LO4WxxFnjwQ94v4TgsDZiFbRFLsHFmDGyV9IPqlraWLpQV1jMx2qQoHhzHwd/ODv52drg7qLfILm9v07eKXKmtQd0IiuwujQb5zc3Iv201FQAak5Jxfc+efvdXNatxz9at+Mu//40tW+6GnUIJe4UCMokEWp4ftFDt+3f/wrP/PbcVtzeL2ME/Zvjvvo9pdLp++RuDtLparPLzFzoNs0FFtchJJTLM812JMzcO6mOpZaewPuxhSCX0fz8Zn+XhfnC3t0ZNS4c+9vHFHLy4bbGAWQ1Oo9Piu6Kr2J95FkevJ6NLM/yYsQg3f9w3aym2hi2Cpy2dSjqQ3KvsKrVCKcO0YHFuWiW9RbavrR18be2wOSgIPM+jor1d3y5ypbYWtZ2dI/pcvE6H4g8+GOIGHr967qc4qJCDuznJQsJx0PFD/xJMiBCoqjIDMf5rmKK6XdWMnOokRHjRBhAyPjKpBNvigvH6t1f0sUOX8/DLuxbAQmEc3154nkd6dSE+yTyLQ9cuoq6zZdhnvG2dcW/EYtwbHo9wN1rlGY5h68fMCG/I5NQSYy44joOPrS18bG1x5/Tp4HkelR0dvQV2TW+hXT1Ikd2amwt1Y+OQn1/d0IjW3FzYh/W2llFBPTLz3d2x1JveMZpKxvFTj0wqN1tfBDiFobjxmj52ueQYFdVkQmxbGMoU1a1danybUYi7omcKmBXQ1NWGA1nn8UHGKWSPoE/aVmGJO0MW4L6IJVjsHwYJR/NdR8pwkyK1fpg3juPgbWMDbxsbbJzWewBJbWcnSltbUdbehrK2NpS39f47rWX4X3IBoMegZcSUyCQSKCQSyCVSyKU3/7dUyv5b/zHDfw/1MSnkEgkU0t5/931OCRyUFvC2Ef8oT2NDRbWZiPFfwxTVuTUpaOlqgL2l8fe+EuPm72KHRcHeuJDXd9DQJxdyBCmqb43B25d+Cl/lJUGlHfqoZplEipXTZmN7xBLcMWMeLOXKKcpUPJobOlBV1sTEaJMiMeRmZQU3KyvMB9sWdMrSCqtef2PY5+UODiN6HQnH9RaaBoXr7cWnYXE69MekUNz6t0HhOuC9A7zuUBNPiLhQUW0mIr3i8cXVt6HW9o5F4qFDatkprJi5TeDMiBjsWBTGFNUXr1eiuLYFAW72U/L6lW0N+OjqGezLOI2S5tph75/vNQP3RSzB3aFxcLGemhzFyvBocktrBfyDaDYuGZllS5fCx8cHFeXlA24V5jgOPj4+SHv+t+jQatGqUkGj0w1aMNMJgkRIVFSbCQu5FWZ7L0FS6XF9LKnkOJbPuNds5+qSibM2KhAO1ko0d/SdyvbJxRz84q4Fk/aaPVoNjt24gn0Zp3Gi4MqwfZZ+9q7YPmsp7otYgulOdCjJRDHspw6e5Q2plAobMjJSqRR/e+FZbH/0WXAAU1jf+tm0Z88eKOVyKOVyOFlYCJInISNBRbUZifZfwxTV9R0VKGrIxjSXCAGzImKglEtxT2ww/n36qj726aU8/M+maMilE7th7UZDJT68ehofXT2D2o6h+zEVUhk2BcfiwaiViA8Ipz7pSdBvPnUUHU1ORmdduAJvbZXid8e0qGrri/v4+GDPnj0mMaeaEICKarMS4BQGVxsf1LX3/RBMKjlGRTWZENsXhjBFdV1rJ77LKsWaqMBxf+7OHhUO517CB+mncLEsZ9j7w1x9sTNqJe6LWAInK9txvz4ZWH1NK+qq2F9saJMiGa3uorNYFyLBmpkckkp5tLjEY+bm3yI+Ph7SCf6lnJDJREW1GeE4DjH+a3E0+9/6WEZlAu6K/DEs5NYCZkbEINjLGXMD3XGlqEYf+/hCzriK6vTqQuxLP4VPsxPQqhr6cAkbhQXuCVuEB2evxFzPIGprmgKGq9Q2dhbwCXQRKBtiinidDqri8wAAqYRDXAAHpy3fh82cZYLmRchYUFFtZub5rsA3196Fju89/alHq0J6xTksCFgncGZEDHYsCmWK6u+yS1Hd3A4Ph5GPdmruasen2b2j8DJrioe9P9YnGDujVuKu0AWwUdAph1PJcJReSJQPJBL6ZYaMXE/dNeg62dM4LQKWCJQNIeNDRbWZsbNwQqh7LLKrE/WxpJJjVFSTCbFxbhBe+PQCOlS9o+x0PI/PLl/HE2vnDvkcz/M4X3oN+zJO4XDuJXRrhh6F52xpix2Ry7AzagWCXajdQAg8zw/QT03/X5DRURWdY66lDgGQOQYIkwwh40RFtRmK8V/DFNWlTXmobi2Bhx2dHEfGx9pCjk3zpuOTi7n62IHEXDy+Zs6A7RjV7U34+OYovMKm6iE/NwcOK6ZF4sGolVg3cz4UUvmE509GrqayGU317UyMNimS0eouOstcWwTGC5QJIeNHRbUZCnGPhq3SEW2qvgMbkkqO485ZjwmYFRGLbXGh+qKa1+mQk5aM3+9pRvycMMTHx4PngBMFafgg/RSO37gC7c1WpMH42LnggagV+F7kMvjau07FfwIZgZx0dpXa3skKnr6OAmVDTBHP81AVJzAxZcBSgbIhZPyoqDZDUokU8/1W4bv8T/Wx1LKTWB/+MGQSWv0j4zNvmjumuzsgM/E7NJ//FNqOZjx/uPdjdq5OsNk0Fx3THYb8HHKJFBtmxmDn7BVYFjALUglNADA2A43So82hZDR6agfopw6kfmpiuqioNlMx/muYorpD3Yqc6iTM8lokYFZEDDiOwwxtBc4c+2e/j7XWNaL1PydhdX8c5OHe/T4e4uKDB6JWYHvEEjrp0IjxPN9vkyIdTU5GS1Vs2E/tT/3UxKRRUW2mXG18EOgcjqKGbH3scskxKqrJuGm1Wnzxz78OeU/X0XTIQr3ASThYy5W4O2whHoxaiWjvmbTaaQIqShrQ1sKOOKR+ajJa/fqpA6ifmpg2KqrNWIzfWqaozqtJRUtXPewtac4sGb3m7g58ln0er+1/F3XVNUPey7d0IahdiV3bH8HdoQthq6RReKbEsPXD2d0Wrh52AmVDTNGA/dSB1E9NTBsV1WYs0jseX2S+BZWmd8WJhw4ppSexMni7wJkRU8HzPC6UXsO+jNP4MjcR3ZoeqEtKR/TsT6M2YsfslZOcIZkMhpsUQyN96B0GMiqauhzoOuqYGPVTE1NHRbUZU8osMNt7KS6XfKuPJZUex/KZ2yDhJAJmRozdrVF4H179DgWNVczHJLYWI/ocnp6ek5EamWQ6rQ55Vw2K6tnU+kFGp9twPrW9H6QOAcIkQ8gEoaLazMX4r2GK6oaOKhTWZyHINVLArIgx0ui0OH7jCvZlnB5yFJ40wBWcnSX41oGPFec4Dj4+PoiPp/5JU1RaWI+OdhUTo0NfyGipDPqplQHx9G4HMXlUVJs5P8cQuNv6oaat7y375NLjVFQTvcLGKuzLOI2PM8+iur1pyHtlEinWB89H4CsL8NKTPwPQ2yJyOx7Anj17IJXSmDxTZDj1w93bAU6utgJlQ0wRz/PoNuintqB+aiICVFSbOY7jEO23Bkey/6WPXa08j7sifwJLubWAmREhdfWocDjvMj5IP4ULpdeGvX+mszd2zl6J7RFL4HpzFF6UxzTs2rUL5eV9rQJSG0es2vkktmzZMmm5k8mVY9j6QavUZJQ0dbnQddQyMeqnJmJARTXBPL+V+Prau9DxWgBAj1aFtPIzWBi4QeDMyFRLry7Eh+mncSA7Aa2qziHvtZIrsSVsIXZGrUTMAKPwtmzZgs2bN+NXr7+Pfx49D6mVPZSeQbghk6G5oxsO1iPrvSbGQ6PR4npmBRMLo35qMkrdhvOp7X0hdQwUKBtCJg4V1QS2SgeEeyxAZtUFfSy55DgV1Waiuasdn2afx76M07haUzTs/fO9ZuDB2StHNApPKpXiF4/dj4OFPVBrenuw1RodvkjOx8PLZk1I/mTqFOfXorurh4mF0Eo1GSXqpyZiRUU1AQBE+69hiuqy5uuoaimCpz2tHogRz/M4X3oN+9JP4XDeJXRreoa838nSFvdFLMHOqBUIc/Mb1Ws5WFtgTWQgjlwp0McOJOZSUW2CDPupfQKcYedgJVA2xBRRPzURMyqqCQAg2G0e7Cyc0drdoI8llRzD5sgfC5gVmWhVbY34OPMs9mWcQlHT0Ae0cOCwPDASO6NWYP3MaChl8jG/7ra4EKaoziqrx7XyeoT50EFDpsRwPjWtUpPR0tTnQdfOfu9RUj81EQkqqgkAQCqRItpvFU5d36+PpZZ/hw3hj0AmVQiYGRmvHq0GxwvSsC/jFE7cSBt0FN4tPnbO+F7kCnwvajn87F0nJIf4UB94OFijurlDHzuQmIsX7l08IZ+fTL4etQb51yqZGM2nJqPVbz61nQ9kjtMEyoaQiUVFNdGL9lvDFNWd6lZkV19GlDfNEzZFBY1V2JdxCh9fPYuajuYh75VLpFg/MxoPzl6JZQGzIJVM7Lg7qUSCrbHBeOPYFX3si+R8/PLuOChkNFrPFBTkVqNHrdVfcxwQMstbwIyIKaJ+aiJmVFQTPRcbL0xznoXChkx9LKnkGBXVJqSzR4Uvcy9hX/opXCzLGfb+EBcfPBC1AtsjlsDl5ii8ybItLoQpqhvbu3EqswTr5tAqlSkw7Kf2m+4G6xGenkkIQP3URPyoqCaMGP81TFF9vfYKmjvr4GA1MW0AZOLxPI+M6kJ8kH4KB6+dR6tq4JMMb7GWK7ElbBF2Rq1A9ACj8CZLgJs9YoI8kXSj71jz/Ym5VFSbiJwMw6PJqZ+ajI6m/jp07dVMjPqpiZhQUU0YkV6L8cXVt9Ct6Z1RzINHcukJrA65X+DMiKHmrnYcyE7AB+mnkFVbMuz90d4zsDNqZKPwJsu2uBCmqD6TXYqalg6429NBQ8ZM1d2Dgly2GKJDX8ho9ZtPbecNmdN0gbIhZOJRUU0YCpkFZvssw6Xir/WxpNLjWBm8HRJOImBmBAB0vA4JJdn4MOM0Dudehko79Cg8Z0tb3DdrCXZGrUSoq/CbyjbMmY7nDySgU6UBAOh4HocuX8dP1swRODMylPzsSmg1fRtcJRIOMyOon5qMDvVTE7Gjopr0E+O/himqmzprUFB/FTNcZwuXlJmrbGvAR1fP4MOM71DcPPwovBXTIvFg1EqsmzkfCunYR+FNNGsLOTbODcKBxFx97EBiLn68ejb9cDVihq0f04I9YGlFU4HIyPE8DxX1UxORo6Ka9OPrMBMedgGobi3Wx5JKjlFRPcV6tBocu3GldxReQRp0PD/k/T52LnggagW+F7kMvhM0Cm8ybIsLYYrqgppmXCmqwbxpHgJmRYZiuEmR5lOT0dI05EPbVsXEqJ+aiA0V1aQfjuMQ47cGh7Pe0ccyKy+gU90GK4WtgJmZhxsNldiXcRofZ55BbUfLkPfKJVJsmBmDB2evxNKAiAkfhTcZoqd7INDNHkW1ff9t+xNzqag2Up0dKhTl1zKxMNqkSEZJZTif2tYTMqcggbIhZHJQUU0GNM93BY5m/wdavrf3VaPrQVr5WSyatlHgzMSpQ93dOwov4zQSRzAKL9TFFztnr8R9EfFwtrKbggwnDsdxuHdBMP58OEkfO5J6Ay9sXQQrpfG0qpBe1zMrwOv63iWRyaUICvMSMCNiirr79VMvoZYvIjpUVJMBWSvtEe65AFcrz+tjSSXHqKieQDzPI/3mKLzPRjAKz0ZhgS1hi/Bg1ErM8woy6R9I98QG469fJetbWtq7e/BNeiHuiQ0WODNiyLCfenqoBxRK+tFBRo76qYm5oO+MZFAx/muZorqi5QYqmgvg7UAjkMajqasN+7MSsC/jNLJHMAov1icYD0StwN2hcbBRCDMKb6J5OtpgSagPzlzr69U9cDGXimojZFhUh0UJP0WGmBZN4w1o29gj7qmfmogRFdVkUDPd5sDe0gUtXfX6WHLpcXg7/ETArEyTjtchoTgbH2ScwpG8pBGNwtsRuQwPRC5HiBGMwpsM2xaGMkV1Yn4lSupb4e9iWu0sYtbe2oXSgjomRpsUyWgZ9lNLbDwgc54hUDaETB4qqsmgJJwU0b6rcfL6x/pYatlpbAj/AeRSGqc1EhWtN0fhXT2NkubaIe/lwGHltCjsnL0S62bMM6pReJNh9awAOFgr0dyh0scOJubifzbFCJgVuV3u1QrmWqGUYXoIbSglo2PYT20RSP3URJyoqCZDivZni+qunnZkVyVitg/1ww2mR6vBN/mp+DDjFE4Wpg87Cs/X3hUPRC7H/UY+Cm+iKeVS3DV/Bt47m6WPHbych2c2REMioR+4xsBwlN7MCC/I5MY/YYYYj4H6qZXUT01EiopqMiRna09Md4lCQX2GPpZUcoyK6gFcr6/AvoxT+CTzHOo6hx6Fp5DKsHFmDHbOXoGlAbPM9rTKbQtDmKK6orEdF65XID6EWgyMgWE/NbV+kNHSNBZA28q+42ERQP3URJyoqCbDivVfwxTV+XXpaOysgZOVu4BZGYcOdTe+yE3EvvRTuFSeN+z9Ya6+2Bm1EvdFLIGTFc38jvB1RZiPM66VN+hjBy7mUFFtBJobO1BZ2sjEaJMiGa3+/dTukLnMFCgbQiYXFdVkWLO8FsEi4010azoAADx4pJSexJqQ7wmcmTB4nseVqhvYl34an127gDb18KPw7glbhAdnr8RcT9MehTcZtsWF4IVPL+ivv00vQnOnCg5WSgGzIrkGq9QWVgr4z3ATKBtiqvr1U9N8aiJiVFSTYcmlSszxXYbEoqP6WHLJcawK3mFWbQuNnW3Yn3UO+zJO41pd6bD3L/AJxgNRK3FX6ALRjMKbDHdFz8AfDiWiR6sDAKg0WnyVko+dSyIEzsy8GbZ+BM/yhlRqPn/fyfhRPzUxN1RUkxGJ9V/LFNVNXbW4UZeOmW5zBcxq8ul4Hc4VZ+GD9FM4cj0Jaq1myPtdrOywY9ZS7IxaiZku3lOUpWlzsrHEqsgAfJNWqI8dSMyjolpghpsU6WhyMlqapkJoWw3e8aD51ETEqKgmI+JtHwQvu2mobO0rfJJKjou2qC5vre8dhZdxGqUtdUPeK+E4rJo2Gw9ErcQdM+aKfhTeZLgvLoQpqjNKapFX2YBgL2cBszJfDbWtqK1iN9uGUD81GaWB+6npgCciXlRUkxHhOA7R/mvwZebb+lhW1UV0qttgpRDHhju1tgff5KdiX/opnCrMAI+hR+H52btiZ9RK3B+5DN52VPyNx5JQX7jZW6G2pVMfO5CYh9/cs1DArMyXYeuHte3/t3ff8XXX1f/AX587s/e6yc1OOtKR7h26mEIpxIIyVUSGIoWvCgr4U3GAqNDiAhRRZCjUMooyO2i6B206Mpo9b/Zed35+f6S97efepMltxueO1/Px8PHwnvvJzUlpktP3PZ9z/JCYGiVTNuSpnPupc9hPTV6NRTWN2rzE1fjg9F9htQ22QFhsZnxRswMr0tfLnNnYFLfU4p/5O/Cvk5+jpa/rotdqlCqsm7oYd2avRU7KDJ/qKZ9IKqUCGxZPxZ8+OWaPvXPoDH54w2KolZyLPNkKjzuM0pudwNnh5BL2U5MvYlFNoxaoCcEs3TIcrzv/lt6h6k88sqjuMfXjncL9eC1/Bw6OahReEu6csxY3z8jhKLwJcvPSaZKiuqW7HztPVePK7FQZs/I9oiiiMF/aTz19Dls/yDXW9gpYO6V/jzifmrwdi2pyycLkKyVFdX1nOWo7SqEPy5Axq9ERRRFH60vxav52bC3Yix7TwEWvD9b4Y8OMFbgjew3m6tL5tuUES4sNw4L0OBwpa7DH/r2/iEX1JGuq70Rbc48klsWimlw04NhPHRgDVfQ0mbIhmhwsqsklmdFzEeYfg47+JnvsUNXHbl1Ut/Z14d+n8vDP49tR2FIz4vVL9dNwx5y1WD9tCQI1fpOQIZ1z85JpkqJ6x6kqNHX2ISY0QMasfIvjKXVoRAB0ieEyZUOeiv3U5ItYVJNLFIICC5OuwKfFr9tjx2p3Yd3Mu6FWus+yDptow66Kk/hn/nb898zhEUfhRQeE4pbZK3H77DUchSej6+an4ydv70G/afC/l9Um4p1DZ3DvFXPkTcyHON6kOH22nsUQuYT91OSrWFSTyxYmXYHPit+wT8foN/fgZP0+zEtcLXNmQE1nM14/sQuvn9iJmlGMwrsifS5uz16DqzPmQ63kt4Pcgvw0uHZeOrYcON/n/taBItxzeTYLu0kw2E/tUFSz9YNcZO2ohLVTuiCL86nJF7CKIJdFBMYiI3oOSprP31R2qOpj2Ypqk9WMD88cwav527Gj/MSIo/CSw2JwR/Ya3Dp7FeKDOQrP3dy8ZJqkqC4xtCO/qglzUmJlzMo31Fe3oau9TxKbns2lL+Qa537qaKiip8uUDdHkYVFNl2RR8pWSorq0JR+tvQ2IDIybtByKmmvso/Ba+7sveq1Wqca6qYtwx5y1yEnmKDx3tjhTh+ToEFQ1nx9v+O99RSyqJ4HjKL3ImGBE60JlyoY8lbFSWlRr2U9NPoJFNV2Smbpl8FcHod98fkrA4epPcPX0Oyf08/aY+rG1YB/+mb8dh+tKRrx+Zkwy7shei5tnrkC4P0fheQJBEHDTkmn47bZD9tj7R0rx/zYsg7+G2yonkuNNitOy2U9NrnM8qfZjPzX5CBbVdEnUSg3m6Vdjb8U2e+xw9ae4ctptUAjju6xDFEUcrjuDf+bvwNaCveg1Gy96fYjWHxuyVuDOOWuRHZfGosADbVg8Fb/74BDEs5083QMmfHS8AjcumiJvYl7MZhNR5NBPncXV5OQiS3slrB1VkpiW86nJR7Copku2KPlKSVHd2d+CkqbjmBo7f1xev6W3E/86tRuv5e9AUUvtiNcvS5xuH4UXoHafSSTkuviIIORMS8TuwvMnp2/tL2JRPYFqypvR2yP9B+s09lOTi5z6qQOioI7JkikbosnFopouWUJYBhJC01HXWWaPHaz6eExFtdVmxa7Kk3j1+Hb878xhmG3Wi14fExiKW2atwu3Zq5EZyVF43uTmpVMlRfW+M3Woae1CYmSIjFl5L8epH7HxoYiMYcsUuYb91OTLWFTTmCxKvgrvnPiT/fFpw370GjsRqHXt5qbqzma8nr8Tr5/Ygdqu1oteOzgKbx7unLMWV6bP5Sg8L3VldipC/DXo6jcBAEQR2HKgGA9fu1DmzLxT4XGuJqexYz81+TJWIzQmc/WrsO3UX2CxmQEAVtGCL2p3Iif9hhE/1mgx439nDuOf+Tuws2LkUXip4bG4ffYa3DJ7JUfh+QA/tQo3LMzEq7tP22NbDhRj4zULoFDw5Gs8Wa02FJ+ql8TY+kGuGuynrpTEtCk58iRDJAMW1TQmAZpgzIpfjmO1u+yxQ1UfY0Xa+mHf8itoqsY/83fg36d2o20Uo/DWT1uC27PXYEVyFkfh+Ziblk6TFNU1rd3YX1KH5VNZ8I2nypImDPSZJDHOpyZXDVQ69lNHQh0zQ6ZsiCYfi2oas0XJV9qLaptVxKF9R/HH8ucwM2MecnJyoFQq0W3sxzuF+/Dq8e04Uj/yKLxZsSm4M3stbpqxAmH+QRP8FZC7mp0UjWnxESiqb7PH3tpfzKJ6nDm2fiQkRyI0PFCmbMhTOa0mT8mBoOBBCPkOFtU0ZulR2QgPiMWh7fnY8XIhelqNeAuHAQAxujjM+8Y6nAjrG8UovADcNGMF7pizFnPi0iYjdXJzgiDg5qXT8OR/9tljHx4rx8+/sgIh/pzwMl4cb1Jk6wddCvZTk6/jPyFpzBSCAsaiMLz/zHH0tEoL5yZDAz761V/Qcbx82I9fnpSFF9Y9gKIHX8Lvrv4WC2qSuHHRFKguOO0aMFuw7WjZRT6CXGE2WVByWtpPnTWHRTW5xtJRBWt7hSTGfmryNTyppjGzWq14+Zm3LnpN/3+PQzU9HsLZG8xiA8Nw6+xVuD17DdIjdJORJnmoyGB/XD4rGR/ln/+F/fb+Ity2grNvx0N5cSNMRov9sSAAU2exqCbXOM2n9o+AOmamTNkQyYNFNY3JmZY6/PLVP6G+znDR68TOfohVrbjmyqtwZ/ZaXJkxDyrF+G5eJO9109JpkqL6i4pGlBjakakLlzEr7+C4mjwpPRpBIX4yZUOeiv3URCyq6RJ0GfvwTsE+vH5iJw7VnYEpv3pUH/f00lvx7Zu+NcHZkTdaPSMJ0SEBaO7qs8fe2l+Ex3OXypiVdyg8Lu2nns7V5HQJjOynJmJRTaNjE23YU1WA10/sxPtFB9BvOT9+SxE8ulOtrLTMiUqPvJxKqUDuoil48bPj9thb+4vw4DXzEeyvkS8xD2cyWVBW1CCJ8SZFcpWloxqWdul9M+ynJl/EopouqrqzGW+e2IU3Tu5CVUfTkNcoU6IhhPhD7Oof8nlBEKDX65GTwx+ydOluXjpNUlS39w7gpc+O43vrFsmXlIerKG6ExWy1PxYUAqbMjJcxI/JEjqvJFf7hUMfOkikbIvmw4Ymc9JuNePt0Hm5440lk//E7eCrvrWELagCICQpD7sN3QxCEYRe+bNq0CUole6jp0mXqwnFVdqok9tL2fDR19g3zETSS4pN1ksdJadEICOSoQnLNAPupiQDwpJrOEkURXxhK8Xr+Tmwp2Isu48ULFaWgwFWZ83Hb7NW4Mn0u1EoVts5ehY0bN6K29nyPZnCUH+7/0Z3Izc2d6C+BfMAj1y/GpycqYRMHV9r3myx4/sMj+MVXL5M5M8/kWFRPncVTanKdYz+1lv3U5KNYVPu4pp4O/Pt0Ht7I34nClpoRr58Wpcdt2WvwlRk5iAkKkzyXm5uL9evX43evPYHPT/wPQeFaJEyPgJ9/J6w2C5QK/nWjscnUhePmpVPxr31F9tgbewpx95pspMSEypiZ57FabSgtkE7tmTIzQaZsyFNZOmtgaZPOjfdjPzX5KFY5PshsteCTsmN4/cROfFL6BSw260WvD9EGYEPWctyWvRrzdBnDtngAgFKpxDe+/ACaQo/bY72mThQ3fYGsOPa+0tg9fO1CvHO4BMazvcAWmw2/2XYIf/zmFTJn5lmqSptgHDBLYuynJlc5nlIP9lPPlikbInmxqPYhhc01eP3ETvz75G4093Ve9FoBAlamzMRt2atx3ZRF8FePvs8yOigByeHTUNV+/jTxaM12FtU0LnThQfjGqll44dPj9ti2o6W494o5mJ0ULV9iHqb4pHSLYnxSBELCAmTKhjyVUz918gr2U5PPYlHt5ToGerG1YC9eP7ETR+tLR7w+OSwGt85ahVtmr0JS6KUXKPMS10qK6tOG/eg398JfHXjJr0l0zrevmoc39hSgq//8aMen3z2ANx5cJ2NWnuWMQz81T6npUrCfmug8FtVeyCbakFd5Gq+d2IFtxQcxYDFf9Hp/lQbXT1uC22avxorkLCiEsZ8yzNFfhvdPvgirOLj+2GIz40TdHixOuWrMr00UFqDFt6+ah6ffPWCP7SmqRV5RLXKmcc7ySGw2EWdOORTVs9hPTa6xdNbC0iY9rGE/NfkyFtVepLKjEW+c2IU3T36Oms7mEa9flDAFt81ejRumL0Wo3/ieIAdqQjA9biFOGfbbY0drPmNRTePmG6tm4pWdJ9HY2WuPPf3uASx/5MtQKIbv+yegrqoVvT1GSWwqb1IkFznOpxb8wqCOYz81+S4W1R6uz2zEtuKDeC1/B/KqTo94fWxgGL46ayVunb0KU6Mm9kRvfuJaSVFd3noKbb2NiAiMndDPS77BX6PG/123AI++/rk9drK6GR98UYbrF2TImJn7czyljooNQWRMsEzZkKdy7Kf2S1kBQcF9BOS7WFR7IFEUcaS+BK/l78A7hfvQZRx6k+E5KoUS12QuwG2zV+Py9DlQTdIPvemxC+GvDkK/ucce+6J2By6fesukfH7yfjctmYa/fJaP0sYOe+y32w7hmrmpUHPZ0LAcb1KcytYPugTGis8lj9lPTb6ORbUHaehpx79P7sbrJ3biTGvdiNdnRSfh9uw1uHnGCkQFTv4MX5VSgzkJl2F/5f/ssaM127F2ylcvOpaPaLRUSgV+cP1i3PuXj+2xyuZO/GtvIe64bKaMmbkvURSdb1Lk0hdykaWrDpZWx35qLmEi38ai2s2ZrGZ8XPoFXsvfic/KjsEq2i56fahfIG6esQK3zV6N7Lg02YvX+YlrJUV1c08dajrOICl8qoxZkTe5ek4q5qbE4FhlEwBAtNnw8xdeg6ViBlKTE5GTkwMlT63tmuo70dHWK4mxn5pc5Tj1Q/ALZT81+TwW1W7qdFMVXsvfibdO7UZrf/dFrxUgYE3abNw2ezW+NGUh/FSaScpyZMkR0xEZqENr7/nNbUert7OopnEjCAJ+dMNS3LzpPfSVH0PHnrdh7e3AXW8OPq/X67F582bk5ubKm6ibKHbopw4JD0BsQpg8yZDHMjr2Uyezn5qIRbUb6ejvwdun9+D1EztxvKF8xOtTw2Nx2+zV+OqsldCHRE1Chq4TBAHz9GvwafHr9tixus+xbta3oFKoZcyMvMmSKfFIM9fi84//4vRcXV0dNmzYgC1btrCwhvN86qkzE2R/R4s8zwD7qYmcsKiWmdVmxeeVp/Ba/g7898xhGK0XnykdoNZi/bQluD17DZYlTveIX4bzk6RFdZ+pC8WNRzFDt0TGrMibWK1WFP3370M+J4oiBEHAQw89hPXr1/t8K0jxKd6kSGNj6aqHpbVEEmM/NRGLatmUtxnsM6XrultHvH6Jfipuy16DG6YtRbDWfxIyHD9RgfFIichCZVuBPXa0ZjuLaho3eXl5aDTUD/u8KIqoqanB55/vxpo1qycxM/fS1tyNZkOnJDaVNymSi5zmU2tDoNZly5QNkftgUT2Jekz9eK/oAF7P34l9NYUjXq8LCscts1fh1lmrkBHp2b/45iWukRTVpxsOoM/UjQANZ+PS2BkMhpEvAvDdP2/FT/x1WL8gE1q1751Yn3E4pQ4I0iIhxT1bx8h9OfZTazmfmggAi+oJJ4oiDtYW47UTO/Bu4X70mAYuer1aocSXpizE7dlrsDp19qTNlJ5ocxIuw3snX4DVNri23Gqz4ER9HpakfEnmzMgbKNsv3jZ1TrNJhe//cyeeef8gvrFqFm7PmYHQAO0EZ+c+ih36qTNnxHP7JLnMsZ/aj/3URABYVE+Y+u5W/OvkbrxxYidK20Y+RZsVm4LbZ6/BTTNWICLA+05vAzTByIpdjJOGvfbY0ZodLKppzJqLatD2rxMIUweh44JFQ46UQeHQ6gY3LTZ19uHX7x3EHz76Arcsn45vrpmNhAjv+75z5HhSzX5qcpW12wBLyxlJTMt+aiIALKrHldFixkclR/DaiZ3YXn4cNlG86PXh/kG4eUYObstejdmxqZOUpXzmJ66RFNUVrafR2mtAZKBOxqzIk3XWtmDbxhdh7TdjQ9Jl+GvZ/4a4SgAgImz5BggKheSZXqMZf91xAn/fdQrr5qfj3ivmIEvvne0Q3Z39qKuS3r/BoppcNeA4n1obAk0c+6mJABbV4+JEYwVey9+Jt0/nob1/+JMyAFAIAtamzcHts1fj6swF0Kp8Z6zctLiFCFAHo898fu720ZoduHLabTJmRZ6qv70H2za+gP62wb9Pc8IzcHf6l/Bu0360dLfbr0tM1OPZZ59D+NQFePGz4zhQ4nxDo8VmwzuHS/DO4RLkTNPj3ivmIGea3iOm64zWmdPSr1ujVSE5I1qmbMhTOfVTJ6+AoGQpQQSwqL5kbX3deOt0Hl4/sRMnGytHvD49QofbZ6/GV2ZdhvjgyIlP0A2pFGrM0a/EvooP7LEvanbgiqm3elXxQhPP3G/EBw+/hM7qZkn82iuuwR+f3Yp9B/fDYDBAp9NJNiqunZWM/MomvPDZcXx4rHzId5PyimqRV1SLLH0k7r18Dq6bnw61F4zhc5xPnTFdB5XK878umlzO/dQ5MmVC5H5YVLvAarNiR8UJvJa/Ax+WHIHJarno9UEaP9wwfSlun70Gi/VTWThisAXkwqK6pbce1e1FSI6YLmNW5EmsFis+fuzvaDpdJYlHZsbjmt98Exp/LVatWjXsx2enxODPd1+JqpYuvLw9H//aV4QBs/P3ckFtKzb+fTt+/d5BfHPNbNyyfDqC/NxnW6mrHG9SZOsHucra3QBLS7Ekpk3hTYpE57CoHoXS1nq8fmIn/nXycxh62ke8flnidNyevQbXT1uMII1nzZSeaEnh0xAVmICW3vO/4I/UbGdRTaMiiiI+f+rfqNpTIIkHxYVj3eb7oA0a/fdbclQInvxKDh6+diFe3X0Kf991Eq09ztN56tt78PP/7MPvPjiEBWk6LMrQYXGGDtkpMfBTe8aP0P4+E6rKpKf6U1hUk4sGnOZTB0OjmyNPMkRuyDN+I8ig29iPdwr34Y0TO3GgtnjE6xOCI3HL7FW4bfYqpIbHTUKGnkkQBMxPXIOPi/5pj+XX7sb6WfdybTmN6NAL/0Ph+wclMW1oANY9fx8Co0Mv6TXDg/yw8UsLcO/lc7DlYDH+sj0fFU2dTtf1GS3YXViD3YU1AACNSoHZyTFYnDFYaM9Pi0OIv3uO5ystMEC0nW91UaoUSJ/Gn1PkGvZTE10cvxsuIIoi9tUU4rX8HXiv6AD6zMaLXq9VqnHt2ZnSK1NmQuklM6Un2jyHorrP3I2ihsOYGb9MxqzI3Z36zx4c+dsnkphSq8a1v7sHEaljLxD9NCrcnjMDty7PwqcnKvHCZ8dxtLxh2OtNFhuOlDXgSFkD/vjxMSgEAdMTIrHobJG9KEOH6JCAMec1HhxbP1KnxEKj5Y9/co1TP3UK+6mJLsSfqgBqu1rw5onP8cbJnahobxzx+jlxabg9ew02ZC1HmH/QJGToXSID45AaOQMVraftsSM121lU07DKd53A7me2SGKCQsBVv/wadNnjO45SoRBw1ZxUXDUnFUfKGvDiZ8fxyYkKjDAhEzZRxOnaFpyubcEru04CAFJjQrE4Q4eFGTosyohHUmSwLPdWON6kyH5qcpW1pxGW5iJJTMulL0QSPltUD1hM+G/xYbx+Yid2VpyAiIv/xoz0D8ZXZl2G22avxoyY5EnK0nvNT1wrKaoLGw5xbTkNyZBfjk+eeFXSvgAAKx+9GakrZ03o516QHocF6VejpbsPh0oN9v8V1LaOOIceACqaOlHR1Il/7RssRmJDA7E4U4dF6YMn2VN0ERO+0dBksqD8jPSwgEU1ucppPrUmCBrdXJmyIXJPPlVUi6KI/IbywZnSBXvQOdB70euVggKXp8/F7dmrcVXGPGiU7PkdL9nxOXj3xJ9hsQ2ul7aKFhyv241lqdfKnBm5k7byBvz3//4Cq1G6hnzB3VdhRu7kvbMRFRyAL81Nx5fmpgMAuvtNOFregEOlBhwsrUd+VRNMFtuIr9PY2Yv3j5Ti/SOlAIDQAC0WpsfZ20VmJUWP+/i+iuJGWMxW+2NBISAjiwuXyDXspyYamU98R7T0duLfp/Pwev5OFDRXj3j9lMgE3HZ2pnRcUPgkZOh7/DVByIpbjBP1e+yxozXbWVSTXU9TB7Y9+GcYu/ok8az1S7HonmtkympQsL8Gq2YkYdWMJADAgNmC/KomHCox4FCZAUfLG9AzYB7hVYDOPiM+O1mFz04Ojgf016gwNzUWi9J1WJypw7zUWPhrxvaPecd+6qS0aAQEuucNleS+jOynJhqR1xbVFpsVn5Udx2v5O/BR6VFYbNaLXh+s8Udu1jLcnr0GC+IzOVN6EsxPXCspqqvaCtHSU4+ooHgZsyJ3YOzuwwcbX0BPY4cknrJiBlb+8Ca3+/70U6uwOCMeizMG/+5arDYU1rXiYGk9Dp9tGRlqXJ+jfpMF+4rrsK94sBBWKRSYlRR19iQ7HgvT4xAW6OdSbo5F9ZSZ/P4i11h7mmBuLpTE2E9N5MzriuozLXX2mdKNvR0jXp+TPAO3zV6N66ctQYCapzeTaVrsAgRqQtBr6rLHjtbswFXTb5cxK5Kb1WTBhz94Ga2lBkk8dmYyrvzV16DwgC2AKqUCs5KiMSspGnevyYYoiihv6sDBksEC+3CZATWt3SO+jsVmw7HKJhyrbMKLn+UDAKbGR9hPshdl6BAXNvzN0kajCbt3f47O7jYEaEMQE57OfmpymdFxPrUmCJp49lMTOfKKorq2qwXvFO7H1oK9OGYoG/F6fUgUbp29CrfOXoWUsNhJyJCGolSoMCdhJfZWbLPHvqjZjiun3eZ2J5E0OUSbDZ/95DXUHS2VxMOSYnDtc/dA7aZzoEciCALSY8ORHhuOW1dkAQDq23pwqKzefvPjGcPIi6UAoLi+DcX1bfhn3uCNvomRwZIxfmkxYRAEAVu3bsV3vvMAGhrO/+MkQBuGKyvisGBFxvh/keS1Bpz6qZdD4D1GRE4EURzFLewyslqtyMvLg8FggE6nQ05ODpRKJZp6OvBe0QFsLdiL/bVFI76On0qNdVMX47bZq3FZykwoBMUkZE8jqW4vxvOfPySJfSfnt0iNnCFPQiQbURSx59l3cOJf0t7NgMgQfPnlhxCSEClTZpOjvWcAh8vOThgpM+BkdTOsNtd/PEcF+yOqqwyfvvBLYIipRoIgYMuWLcjNzR2HrMkXGH4/B+am81tMQ6/4BUIve0TGjIjck1sX1Vu3bsXGjRtRW1trj4XHRiH9lrUoi7GNaqTV/PgM3DZ7NXKzliPML3Ai06VLIIointl+D5p7zv83XpLyJWyY810ZsyI5fPHP7dj//PuSmDpQixtffBDRU/UyZSWf3gEzvqhsxKGzfdlHKxphNF/83hBg8LTf8NoTsA7T/iYIAvR6PSoqKqAc50kj5H2svc2oe1raMhR7Tx60iYtlyojIfbltUb1161Zs2LABw6UXcOtSqGcM3RsYHRBqnyk9PTpxItOkcfBZ8Zv4qPBV+2N/dRB+cvXrUCk1MmZFk6n4f4fx2U9ek8QUKiWu23QvEhdPlSkr92KyWHGyutneLnK4zICufpPTdQN1Z9D8/qYRX++bT/4BX73hWixI1yEswDPbamji9Z3eipZ/fdX+WNAEQv9YE9s/iIbglj3VVqsVGzduHLagBoD+/x6Hano8hLOLE0K0AVg3dTG+nLUcl6XMhIorwz3GPP0aSVHdb+5BQcMhzE5YIWNWNFlqDhZhx5NvOMXX/uRWFtQX0KiUmJ8Wh/lpcbj/yrmw2UQU17fh0NmWkYOl9Wjq7IO1r3NUr/fO7qP4xDDYBnfu5seFGXFYlB6P+AhuiqVBjktftEnspyYajlsW1Xl5eZKWj6GInf1Q13bixmuuQ27WcqxJzYZWxW90TxQRGIu0yFkobz1pjx2t2cGi2gc0F9Xgw0f+BptVujhl2YPrMeXqBTJl5RkUCgHT9ZGYro/E11bOhCiKqGrpwt/fCsTPPntlxI9XBoTa/7/jzY8JEUFYlK7DgrObHzPjwid88yO5J8f51FrOpyYallsW1QaDYeSLAPx2+R34+vo7JzgbmgzzE9dKiuqixsPoNXYiUBt6kY8iT9ZZ24JtG1+Euc8oiWffshJzbl8tU1aeSxAEpESH4sf33YaXn378ogcTyqBwaHXDTwCpa+vBO20leOdwCQAgLFCLBWlxWJh+fvOjxgNGG9LYWHtbYG46LYn5cT410bDcsqjW6Ua3QjclMWmCM6HJMjthBd458SdYbIM9oufWli9PWydzZjQR+tt7sG3jC+hvk85qzrhiLpY/dANHKo6BUqnE5s2b8eUvf9npOUEQIAK49YFHMBCjx7HK0d382NEr3fyoVSsxNyUWizJ0WJgeh3mpcQj25z0Q3sZxNbmgDoAmYb5M2RC5P7csqnNycqDX61FXVzdkX/W5u9dzcvg2lLfwVwdipm4Jjted7987WrOdRbUXMvcb8cHDL6GzulkST1iQict/ejsEBcddjtWqnCuwKvsbOFT0DvqMHfa4Xq/Hpk2b7OP0jGYrTtU02298PFzWgE6Hdw6GYjRbcaCkHgdK6gEACkFAlj4SC9N1WJihw6J0HWJCAybka6PJM+Cw9IXzqYkuzi2L6nMnLRs2bBg8WbmgsD53grVp0yaOg/Iy8xLXSorq6vZiNPfUIjrI98apeSubxYqPH/s7mk5XSeKRmfG45jffhFLjlj+SPE7JaQOSY7ORGDMLTe1lsAr9+NHTt2PlysskPze16gtufsTgzY8lDW04VNpwtsg2oK6tZ8TPZxNFnKppwamaFryya7CNKzk6ZPDmx7MtI6kxoXwHwsOwn5rINW77Gyw3NxdbtmxxmlPteNJC3mNqzDwEakLRazo/veBo9Q5cncW+eW8giiJ2PfVvVO0pkMSD4sKxbvN90Ab5y5SZ9zlz+twJsgJxEZnIXpSCNWtG7lNXKARMjY/E1PhI3HHZ4AKmurZu+1Kaw2UNKK5vG1UOVc1dqGruwtsHigEMLqVZmB5nP82eoY+CSsl3JdyVtbcF5sZTkhj7qYkuzm2LamCwsF6/fv2QGxXJ+ygVKszTr0Je+Xv22NHaHbhy+u3cgOkFDr34IQrfPyiJaUMCsO75+xAYzRtSx1PJ2aL6nMyZ8Zf8WgkRwUiICMYNC6cAADp6B3CkvMFeZJ+oaoLZYXrLUFq6+/Hh8Qp8eLwCABCgVWFeahwWpsdhUYYOc1NiEaBla4G7MFbtkTwW1AHQxLOfmuhi3LqoBgZbQVatWiV3GjRJ5ietlRTV7X2NqGwtQFrUTBmzorE6tXUvjrz8sSSm1Kpx7bP3ICI1TqasvFNfrxE1FS2SWGbWpRfVjsIC/XD5rBRcPisFADBgsiC/qsnel32kvAE9A+aR8zRasKeoFnuKBt+JVCkUmJkUZW8ZWZgRhwi+eyEb5/nUyyCoeDMq0cW4fVFNviUhNAMxwYlo6q6xx47WbGdR7cHKd53A7l+/LYkJCgFX/vJr0GWnypSV9yorbIBoO38fikqtROrU2An7fH4aFRZnxmNx5mDhbrXZUFTXZi+yD5UZ0NTZN+LrWGw2HK9swvHKJry0PR8AkBEbhoUZ5/uyEyOD2Zc9SdhPTeQ6FtXkVgRBwPzEtfiw4O/2WH5dHm6YfT/UXFvucQz55fjkiVclRR4AXPboTUhbOUumrLzbGYfWj9QpMdBM4g2gSoUCMxKjMCMxCt9YPcu+lOZwmQGHz7aMlDV2jOq1Shs7UNrYgTf3FgIAYkMD7WP8FmXoMDU+AkpOixl31r5WmBtPSmLspyYaGYtqcjvz9KvxUcE/IGKwEBuw9KKg4SCyE3hS4knaKhrw3//7C6xGaSvAgm9ehZm5y2XKyvuVnHLop54xfq0fl+LcUpqU6FDctGQaAKCluw9Hys73ZZ+qaYbV5jw+1VFjZy+2HS3FtqOlAIAQfw3mpw32ZS/M0CE7OQZ+av5aGytjpWM/tT80CdxwSjQS/vQhtxMeEIO0qNkoa8m3x47WbGdR7UF6mzux7cEXYOySvu0/ff0SLLr3Gpmy8n4WsxXlxQ2S2BSZi+qhRAUH4Oo5abh6ThoAoHfAjGOVjfaWkS8qGtFvsoz4Ol39Juw8XY2dp6sBABqVArOTYwbbRdJ1mJ8eh7AA7YR+Ld7I6DCfWpO4lP3URKPAoprc0vzENZKiuqjxCHqMHQjShsmXFI2Ksacf2za+gJ6Gdkk8eUUWVv3wZvbETqDK0iaYjNJiNGMcb1KcKIF+aqyYpseKaYMz6c1WKwpqWnHI3jJiQGvPwIivY7LYcKSsAUfKGvBnHIMgAFN1EWdbRgb7snXhQRP95Xi8AYd+ar/Uy2TKhMizsKgmtzQ7fjneOfEnmK2D291sohXHaz/HivT1MmdGF2M1WfDh9/+K1hJpC0LMjGRc9auvQ6HiOMyJ5Nj6kZAciaAQP5myuXRqpRLZKTHITonBt9ZmQxRFlDd12NtFDpUaUN3SNeLriCJQVN+Govo2vLr7NABAHxF89ubHwb7sjNhwKBT8h9451r42p35qLfupiUaFRTW5JT91IGbqluJY7S577GjNDhbVbky02fDZT15D3dl+13NCk6Jx3XP3QO3Pt+EnmuNNilPGMJ/anQiCgPTYcKTHhuOW5VkAgIaOXvtq9cOlBhTUtUAcuS0btW3dqD3UjXcOnQEAhAVqB0f4nS2yZyZGQ+PD//gzVu3BhX+QgtofWvZTE40Ki2pyW/MS10iK6pqOM2jqrkFMcKJ8SdGQRFHE3k3vovSzY5K4f0Qwrn/+fvjzLfcJJ4riuC59cXdxYYFYNz8D6+ZnAAC6+o34orzRvv3xeGUTjBbriK/T0WvEpycq8emJSgCAn1qFuSkxWJgx2Jc9Ly0WQX6+009srHDsp14CQcV/EBONBotqcltTouchWBuObuP53tyjNdtxTdbX5UuKhnT8tZ3If1Pah6kO0GLd8/chJCFSpqx8i6GmHT1d0r5jd7xJcaKE+GuxakYSVs1IAgAYzVacrG62F9lHyhvQ2Wcc8XUGzBbsL6nH/pJzq94FZOkj7T3ZC9N1iAkNmNCvRU5O/dQp7KcmGi0W1eS2lAol5upXYXfZO/bY0ZqduGr6nVxb7kaKPzyCfc+/J4kplApc88xdiJ6qlykr3+N4Sh0RFYTImGCZspGfVq3EgvQ4LEiPw/1XzoXNJqKkoU3Sl13f3jPi69hEEadqWnCqpgWv7BrsNU6JDrW3iyxM1yE1JtQrbsC19bfD3HhCEmM/NdHosagmtzY/cY2kqO7ob0J5yylkRM+WMSs6p+ZgEXY8+YZTfM1PbkPi4mkyZOS7HPupM2fGe0WhN14UCgFT4yMxNT4Sd1w2uKG1rq37/ObHUgPOGNpHeJVBlc2dqGzuxNsHigEAUcH+9lnZC9N1mKGPgkrpef/wH6h06KdW+UGrXyhjRkSehUU1ubX40HTEBiejsbvKHvuiZjuLajfQXFSDDx/5G2wOfatLH7weU6/hjU2Tzd2WvniChIhg3LgoGDcumgIA6OgdGLzx8ewovxPVzTBbbSO+Tkt3Pz48XoEPj1cAAAK0KsxLjbNvf5yXGgt/jXpCv5bx4Dyfmv3URK5gUU1uTRAELEhai/+e/ps9dqJ+D27M/jbUSv6wl0tnbQu2bXwRZoce1dlfXYm5t6+RKSvf1dHaiyZDpyTmS/3U4yUs0A9XzE7BFbNTAAADJguOVzYNnmSXGXC0vAE9A+aLvwiAPqMFe4pqsaeoFgCgUigwKynK3pe9ID0OEUH+E/mlXBLOpyYaGxbV5Pbm6lfhf6dfuWBteR9OGw5gjp69fnLob+/Bto0voL+tWxLPuHwuVjx8A1sOZFBSID2l9g/QQJ/CG0THyk+jwpIp8VgyZfAfKFabDYV1rThc2oBDZ1tGmh22hg7FYrPhWGUTjlU24aXtg0utMuLCJX3ZiZHBsn7v2PrbYW7Il8TYT03kGhbV5PbC/KOREZ2Nkubj9tiRmu0sqmVg7jfig4dfQmd1sySeMD8Dl//sdggKz+sj9QZnHFo/MrJ0UHhgT6+7UyoUmJkYjZmJ0fjG6lkQRRFVLV32dpFDpQaUN3WO/EIAShvaUdrQjjf3FgIYHBF4fsJIHKbGR0A5id9PA1V7nfupE9hPTeQKFtXkEeYnrpUU1WeajqJ7oB3BfuHyJeVjbBYrPn7s72g6XSWJR2bG45rf3g2lhj9O5OI0n5qtH5NCEASkRIciJToUNy0ZvDG3pbsPh0sb7Dc/nq5tgdU28laaho5ebDtaim1nlyeF+GswPy1ucDFNRhyyk2Pgp5647zHn+dSLIag9bxsnkZz4W5A8wqz45fhP/h8uWFtuw/G6z5GTfoO8ifkIURSx66l/o2pPgSQeFBeOdZvvg9YN+0N9RX+fCVVl0ncOvGWToieKCg7ANXPTcM3cNABA74AZX1Q2Dp5klxlwrKIR/SbLiK/T1W/CztPV2Hm6GgCgUSkwOzkGi9IH20UWpMchNGD87isZqOR8aqKxYlFNHkGr8scs3TJ8UbvTHjtSvZ1F9SQ59OKHKHz/oCSmDQnAuufvQ2B0qExZEQCUFzVAvOAkVKlSIHVKrIwZ0YUC/dTImaZHzrTBme1mqxWna1rss7IPlxnQ1jMwwqsAJosNR8oacKSsAcAxCAIwLT5S0petu8TNpbb+DpgNxyUx9lMTuY5FNXmM+UlrJUV1XWcpqtoKkRwxXcasvN+prXtx5OWPJTGlVo1rn70HEalxMmVF55w5VSd5nJIZA62f+49v81VqpRJzUmIxJyUW31qbDVEUUdbYYW8XOVzWgOqWrhFfRxSBwrpWFNa14tXdpwEAiZHBWHBBX3ZmXPiobn40Vkv7qaHSQqtfdMlfI5GvYlFNHiMzeg5C/CLQNdBmj71+5Bk8vOr38Ndc2gkNXVz5rhPY/eu3JTFBIeDKX34NuuxUmbKiCzktfWE/tUcRBAEZceHIiAvHLcuzAAANHT2D87LPFtkFdS2Smnc4Na3dqGntxjuHzgAAwgP9sCA9brBlJCMOMxOjoVEpnT6ut3QX9lfa0NQDxAQBOZctYj810SUQRHE036pE7uGz4jfxUeGrkthM3TJ8bdETHOU2zgz55XjvO3+C1Sidy7vyRzdjZu5ymbKiC1ksVnw79wWYjOd7dB/8yXWYtyxdxqxovHX1G/FFeaO9XeR4ZROMDkuXRsNPrcLclBgszNBhUboOc1Nj8emHH+CBb94CQ4fJfl18dAh+/8IryM3NHc8vg8jrsagmj2K1WfDnPY+isk16w9z1M+/BZRk3ypSV92mraMDWuzfD6DCDd8E3r8Li+74kU1bkqLy4AU8++G9J7Pdv3YPgUN446s2MZitOVjfj0NlRfofLDOjqN438gQ4Gyo+j+eOXnOKD5xMCtmzZwsKayAUsqsnjdPQ149ldD6DPdL7vUCEo8Z2c3yI5YpqMmXmH3uZObLnrOfQ0tEvi09cvwerHv8p3BNzIx1u/wJsv5tkfxydF4Fd/uUPGjEgONpuIkoY2e0/2oVID6tt7Lvoxos0Gw2tPwNrbMeTzgiBAr9ejoqICSqVzywgROWNPNXmcsIBo3DL/+3h5//+zx2yiFf88/BT+b/UfEKAJljE7z2bs6ce2jS84FdTJK7Kw6oc3s6B2M45LX9hP7ZsUCgFT4yMxNT4Sd1w2EwBQ19aNQ6UGe8vIGYP0e9poKB22oAYGx2jW1NQgLy8Pq1atmsDsibwHi2rySNNjF2LNlK9gx5nzb3139DfhzaO/xTeW/AQKgdvkXGU1WfDh9/+K1hJpoRYzIxlX/errUAxxgxPJRxRFp6UvU1hU01kJEcG4cVEwblw0BQDQ0TswePPj2ZaRfWVHR/U6BoNhItMk8iosqsljXTXtDlS2nkZ56yl7rLDxED4v3YrVmRtkzMzziDYbPvvJa6g7u83tnNCkaFz33D1Q+4/fkgkaH431Hejq6JfEMrn0hYYRFuiHK2an4IrZKQCAT+aE4qpPXh7x43Q63QRnRuQ9eJxHHkupUOK2BT9EoEa6fOTDgldQ0Xpapqw8jyiK2LvpXZR+dkwS948IxvXP3w//S1woQROrxKH1IywiENFxITJlQ55m7ZpVSNDFYLiGLkEQkJiYiJycnEnNi8iTsagmjxbqH4nbFjwC4YJfDTbRhtcOP4VeY6eMmXmO46/tRP6b0hXF6gAt1j1/H0ISImXKikYy1Hxq9rzTaCmVSjz9nWsAwKmwPvf3aNOmTbxJkcgFLKrJ402JmYfLp94iiXUOtOKNo7+FTbTJlJVnKP7wCPY9/54kplAqcM0zdyF6ql6mrGg0nPqp2fpBLroqtQd/3qBEnMO93Xq9nuP0iC4Be6rJK1wx7VZUtJ5GaUu+PVZoOIznXvsp4lXTodPpkJOTw1OXC9QcLMaOJ99wiq/5yW1IXMzRhO6sq6MPDbUdkhgnf5ArRFGEsfoArpmmwJVTBByqFtGXdQ9Sl97Mn5VEl4hFNXkFhaDErQsewXM7H0C3sR0l+xuw4+VC9LR+bL9Gr9dj8+bNPH0B0Fxciw8feRk2h61sSx+8HlOvWSBTVjRajqfUfv5qJKZFyZQNeSJLWxlsvU0AAKVCwNIUAbp7vwd1BLdxEl0qtn+Q1wjxi8BtCx5Fyf4mvP/McfS0GiXP19XVYcOGDdi6datMGbqHrrpWbHvwBZj7pH8+s7+6EnNvXyNTVuQKx/nU6dN1UCr545xGz1i9X/JYERgDVXiaTNkQeQf+FCavkhoxE/terRzyuXPLQx966CFYrdYhr/F2/R09eP/BP6O/rVsSz7h8LlY8fANvdPMQjkU151OTq0wORbU2aSm//4nGiEU1eZW8vDy0NLQN+/yFW8J8jbnfiP8+/BI6q5sl8YT5Gbj8Z7dDUPDHgScwDphRVdokiXE+NbnK8aRam7RUpkyIvAd/i5JXGe32L1/bEmazWPHJY/9A46kqSTwyQ4drfns3lBreXuEpyooaYLOJ9scKhYD0aXEyZkSextbfAXNzgSSmTVomUzZE3oNFNXmV0W7/GtAMf5rtbURRxK6n30LlHulCnKC4cFy3+T5og/xlyowuhePSl+SMGGj91DJlQ57IWHsQEM//wwwqLTTxc+VLiMhLsKgmrzKtvx0xfpqLXhMc5YdT+ADbz/zb3mftzQ699CEK3zsgiWlDArDu+fsQFBMmT1J0yRyXvnA+NbnKWLVP8lgbPx+CSitTNkTeg0U1eY3OowdQ99ff4/uzMy563eq7pkFQAh8W/B1vHH0GZqvxotd7slNb9+LIXz+WxJRaNa599luISGXLgKexWm0oK5S2LrGoJlcZa6T/yNYkLZEpEyLvwqKavEJf2RmU//angM2KNfFReGZRltOJdWRsGK5/ZA4yl54vJo/V7sKf9jyKrgHvawcp//wkdv/6bUlMUAi48hd3QpfN0VmeqKa8BQP9ZkmMS1/IFaLVAlPtIUmM/dRE44NFNXk8Y5MBJb98FLaBfntsTXwUDr/4PHbu3Ik33ngDO3fuRENtMx6++3EIkI6NqmkvxuZdD6Km/cxkpz5hDPkV+OTxf0C0SdtbLntkA9JWzZYpKxorx6UvcfowhIQFyJQNeSJz40mIpl5JTJvIk2qi8cBb/smjWXq6UfrzR2Fpl540R6y8Aol33IMkh7mrqzI3ICY4Ea8f+TWMlvNFeOdAK/6Y9wN8dd7/YY5+5aTkPlHaKxvx3++9BKtReqK54K4rMfPLK2TKisaD43xqnlKTq4zV0n5qVWQGlEExMmVD5F14Uk0ey2Y2oezpJzBQKx0TFzxzLpK/8+iwiwyy4hbju5c9h8gAaU+xxWbCa0eexkeFr8Im2iYs74nU29yJ97/7Zxg7+yTx6dcvxqL7viRTVjQeRFF0Oqnm0hdyFedTE00cFtXkkUSbDZW/fxo9p49L4n6JqUj74c+hUF98xFhcSDIeXLkJ6VHOrRCfFb+Jfx76FYyWgfFMecIZe/qxbeML6Glol8STl2dh5Y++wm1pHq65oQsdbdK37bn0hVzlXFSzn5povLCoJo9U//pf0Z63XRJTh0ci88e/hioweFSvEagNxT3LfoklKc4nuCcNe/HH3d9DW1/juOQ70awmCz78wctoLZGeZMbMSMZVT30dSpVSpsxovDjOpw4J80dsfJg8yZBHsnTWwNpZI4lp2E9NNG5YVJPHaf7oPTRsfV0SU/j5I+OJp6GJjnXptZQKFb6c/QBunP1tKATpt0N9Vzme//whVLYWDPPR7kG02fDZT19D3ZESSTw0KRrXPXcP1P6cP+sNik/VSR5nzojnuw/kEsdTasEvDOro6TJlQ+R9WFSTR+k4vA/Vf9kkDSqUSHvkSQSkTbmk1xQEAcvT1uHupb+AvzpI8lyPsQN/3vsoDld9eokZT7y9m99D6afHJDH/iGCs23wf/MODhvko8jRO/dRs/SAXGasdlkAlLoGgYBlANF743UQeo7e0CBW/+xlgk95EmHz/9xA6d9GYX39KzFw8uHITooP0krjVZsG/jz2Lbaf+AptoHfPnGU/HXtuB/Dd2SWLqAC3Wbb4XofooeZKicdfV0QdDjbRXnpM/yFUmh8kfvEmRaHyxqCaPYGw0oPQXP4TNKL15UHfTnYi6/Npx+zzRQQl48LLnMDVmvtNzn5duxd8O/Az95t4hPnLynfnoCPZtfk8SUygVuOaZuxA9LVGmrGgilBZItyhqtCokpUfLlA15IpupF6aGfEmMRTXR+GJRTW7P0t2F0p8/Akun9KQuYtWV0N1y17h/Pn9NEO5a8jNcln6j03NFjYfx+90Po6WnfoiPnDw1B4ux/WdvOMXX/L9bkbh4mgwZ0UQ649D6kT49DirefEouMNUeBmwXvNOmUEKjXyhfQkReiEU1uTWbyYiypx/HQF21JB48ez6Sv/3IhN2opVQocf2se3Dz3IegFKQ7kpq6a/D85w+htDl/mI+eWM3FtfjwkZdhs0hbUZZ+93pM/RJ/SXojzqemsXK8SVETlw2FJlCmbIi8E4tqclv2WdQFJyRxv6RUpD/y5IizqMfDouSrcN+KpxCoCZHE+8zdeGnf49hX8cGE53ChrrpWbHvwBZj7jJL47K+uxNw71kxqLjQ5jANmVJY0SWLspyZXGWukNylqOJ+aaNyxqCa3VffaS2jfs0MSU0dEIfPHz0AZOHlTLVIjZ2LjyuehC0mRxG2iFVvz/4it+X+E1WaZ8Dz6O3rw/oN/Rn9btySecflcrHj4Bo5X81IVZxphtZy/OVehEJA+XSdjRuRpRJttiKUvnE9NNN5YVJNbavrwHTS+86YkpvAPQMYTv4YmKmbS84kIjMUDlz2LGXHON/bsq/gAf9n3BPpM3UN85Pgw9xvx34dfQmd1sySeMD8Dl//sdo7F8mJnHJa+JKVHwz9AI1M25IksLUUQBzokMW5SJBp//E1Mbqfj0F7U/PV5aVCpRPojTyIgNUOepABoVf742uInsHbKV5yeK23Jx+bPN6Kxu3qIjxwbm8WKTx77BxpPVUnikRk6XPPbu6HUqIb5SPIGjv3UbP0gVzmeUitDE6EK1Q9zNRFdKhbV5FZ6SwpRPuQs6u8jZI78N+EpBAWuyfo6bp3/CFQKaU93a68Bv//8YRQ2Hh63zyeKInY9/RYq95yWxIPiwnHd5vugDfIft89F7sdmtTmN0+PSF3KVc+sHR+kRTQQW1eQ2jA31KP3ljyCapDfh6b7ydUSt/ZJMWQ1tXuJqfDvnNwjxi5DEByx9+Nv+n+Lz0q0QRXHMn+fQSx+i8D2HLWghAVj3/H0Iigkb8+uTe6utbEV/n0kSy8xiUU2uMXLpC9GkYFFNbsHS1YmSIWZRR665GrqvfF2epEaQFD4VG1duhj4sUxIXYcO2U3/Bv489B4vVNMxHj+zU1r048tePJTGlVo1rn/0WIlLjLvl1yXM4zqeO0YUiLJJj0Gj0rL3NsLSWSmLspyaaGCyqSXY2kxGlTz0OY32NJB6cvQDJ9//AradahPpH4Ts5v8GchJVOzx2p/hQv7P0Ruo0dLr9uxecnsfvXb0tigkLAlb+4E7rstEtNlzyM402KmWz9IBc5tn4ImkCoY2fJlA2Rd2NRTbISbTZUbv4VeotOSuL+KelIf+RJCCr3vwlPrdTitgWP4urpdzo9V9lWgM27NqK+s3zUr2fIr8DHj/8Dok3aPnLZIxuQtmr2mPMlzyCKIs6cqpPEuPSFXOW09EW/CILS/X+uEnkiFtUkq7pXX0D7vl2SmDoyGhmPPw1lgOe8zS0IAi6fegu+tugJqJVayXMd/U34w+7v4WT93hFfp72yEf/93kuwGs2S+IK7rsTML68Y15zJvbU0dqOjtVcS4+QPcpXJ8SbFRM6nJpooLKpJNk3//Q8a3/u3JKYICETmj+WZRT0eZsUvxwM5v0OYvzR/k3UA/zj0C3xW/OawNzD2Nnfi/e/+GcbOPkl82rrFWHSfe92oSRPPcZReUIgfdInhMmVDnki0GGGsPyqJaZPZT000UVhUkyw6Du5Bzcu/lwbPzqL2T06XJ6lxkhCWjo2rNiMlIsvpuY8KX8XrR34Ns1U64cTY049tG19AT4P0Rs3k5VlY9dhX3LqvnCaGY+tH5ox4/j0gl5jqjwGWC37WCAK0+sXyJUTk5dhYRZOu90wByp99EnA4sU359iMIyV4gU1bjK1gbhvuWP4X/5P8Bh6s/lTx3vO5ztPTW484Fj+PEkULU1dSi4u3DCK23QSGc/3duzIxkXPXU16FUKSc7fXIDJacd5lOz9YNcZKyRtn6oo7Og8A+TJxkiH8CimiaV0VA39Czqr34DkWuulimriaFSanDz3IcRF5KCD069DBHnF9rs/DAPP7kpDV0t51s9wtRB2JB0GeaEZyA0KRrXPXcP1P7aoV6avFxP1wDqqlolMU7+IFcZqzifmmgysf2DJo2lq2NwFnVXhyQeufZL0N38NXmSmmCCIGBlRi7uWvpT+KkCAAAl+xvw/jPHJQU1AHSYe/DXsv+hwFyLdZvvg394kBwpkxsoLZD2U2u0KqRkeOZ9BiQPURRhrJEujtKwqCaaUCyqaVLYjGdnURtqJfGQOQuRfN/3vL5XdHrsQnx35XMI94vFjpcLL3rtu437EaTjDWm+zHHpS9rUOKjUbAOi0bO0l8PW0yiJ8aSaaGKxqKYJJ1qtqNj8S/QWnZLE/VMykPaDn3nELOrxEBuchHnKm9DTarzodfUNBuTl5U1SVuSOHCd/sPWDXOU4Sk8RGANVhGffBE7k7lhU04Sr/cef0bH/c0lMHRWDjB//2qNmUY+HjpauUV1nMBhGvoi8kslkQcWZJkmMNymSqxyXvmiTlnj9O4JEcmNRTROqcdsWNG2TrttWBAQi84lfQxMRJVNW8tHpdKO6LjwqdIIzIXdVeaYRFrPV/lhQCMiYHidjRuSJnItqzqcmmmgsqmnCtB/YjdpX/iCJCSoV0h/9BfyT02TKSl45OTnQ6/UXPTEKjvLDCbyHzv6WScyM3IVjP3ViahT8AzkFhkbP1t8Bc9NpSYz91EQTj0U1TYieolOoeO7nTrOok7/zCEJmz5MpK/kplUps3rwZAIYtrFffNQ1NvdX4/e7voam7ZjLTIzdw5pRDPzVbP8hFxtpD0p+9Sg008b77c5dosrCopnE3UF+L0l89BtFkksTjb70bkauukikr95Gbm4stW7YgISFBEg+JDsD1j8xB5tLBt/o7+pvwh7zvo6qtSI40SQY2m+h0kyL7qclVxmrpfGpNwnwIKr7bQTTRWFTTuDJ3dqD0F4/A2t0piUddfi3iNtwuU1buJzc3F5WVldi5cyfeeOMN7Ny5E6WlJVh2xXzJdX2mLryw94coajwiU6Y0meqqWtHfK/3HaOaM0fXhE51jrJbOp2brB9HkYFFN48ZmHEDZr34Eo6FOEg+ZuwhJ9/4f7zx3oFQqsWrVKtxyyy1YtWoVokPi8UDO75AYPlVyndlqxCsHfoYTdXtkypQmS4lD60dUbAgiooNlyoY8kWi1wFR7UBLTJrKoJpoMLKppXIhWKyqe+wV6zxRI4v5pmT41i3qsArWhuG/505gas0ASt4oW/PPwUzhc/alMmdFkcLxJkfOpyVXmxpMQTb2SGE+qiSYHi2oaF7V//xM6DkoXlmiiY5Hx+NNQ+gfIlJVn0qr8cNeSn2Cefo0kLsKGf3/xLPaWfyBTZjTR2E9NY+U4Sk8VkQFlEFfcE00GFtU0Zo3b3kbTB1skMWVAEDJ8dBb1eFAqVPjq/O9hacqXnJ5758QfsePMWzJkRROptakLrU3dkhiLanKV03zqZJ5SE00WFtU0Ju37P0ftK3+UxASVCuk/+gX8k1Jlyso7KAQFcrMfwKqMDU7P/a/gFXxY8A+IDiMLyXOVnJZu0QwM0kKXFCFTNuSpnIpq9lMTTRoW1XTJBmdR/8JpFnXKd3+I4JlzZcrKuwiCgGtn3IWrp9/p9Nz2M//CeydfhE20yZAZjTfHfuqMGfFQKHhzL42epbMW1s5qSUzDfmqiScOimi7JQF3N4Cxqs8Ms6tu/hYjLrpApK+8kCAIun3oLrp95j9Nze8rfw5Zjm2ETrUN8JHkSx8kfbP0gVzmeUgt+YVBHT5cpGyLfw6KaXGbuaEfJz4eYRX3lOsTl3iZTVt7vsowbcdOchyBAenp5qPoTvH7kGVhsZpkyo7Hq7TGitlK6ln4KJ3+Qi0w1DvOpE5dAUPDXPNFk4XcbucRmHEDpr34EU6P0VC1k/hIk3fMQZ1FPsMUpV+HWBY9AISgl8fy63fjHwV/AbDXKlBmNRVmhQdJFpVIrkZLJiQ3kGsdNitqkJTJlQuSbWFTTqIlWK8qf/Tn6Sgol8YC0KUj73k8gKDmLejLM1a/C1xY9AZVCLYkXNh7CX/f/BEZLv0yZ0aU649D6kTY1FmoNv59o9GymXpgMxyUxbdIyeZIh8lEsqmlURFFEzd9+j85D0q1+mug4ZDzBWdSTbYZuCb659GdQK7WSeFlLPl7a+xj6TN3DfCS5I86nprEy1R0BbBfcW6FQQqNfKF9CRD6IRTWNStP7b6H5f+9IYsrAIGT8+NdQh0fKlJVvy4yei3uX/Qp+qkBJvKq9CC/s/SG6jR3yJEYuMZssKCtqkMS4SZFc5XiToiYuGwpN4DBXE9FEYFFNI2rfuxO1f/+TJCao1Ej/0a/gn5giT1IEAEiJzML9K55GoCZEEq/vLMef8x5BR3+zTJnRaFWWNMFiPn/CKAhAxnSdjBmRJ3IqqjlKj2jSsaimi+opOIGKzb9yiqc8+EMEz8iWISNylBCWgW/n/AYhftJ3DJp6avDHvB+gtdcwzEeSO3Bs/UhIiURgsJ9M2ZAnEm0258kfLKqJJh2LahrWQF01Sp963GkWdcId9yIi53KZsqKhxAYn4Ts5v0FEQJwk3t7XiD/mfR8NXVUyZUYjcVz6wn5qcpWlpRi2/nZJjEU10eRjUU1DMne0Dc6i7umSxKOvXo/YG2+RKSu6mMhAHb6T8xvEBCVK4l0DbfjznkdQ21EqU2Y0HJtNdFpPnsmimlzk2PqhDE2EKjRxmKuJaKKwqCYn1oF+lP7yRzA1Sn/Zhy5YisS7H+QsajcW6h+F+3OeQXxomiTea+rCC3seRWVrgUyZ0VAMNW3o7R6QxLj0hVxlrJEW1dpEzqcmkgOLapIQrRZUPPsk+kqLJPGAjKlI5SxqjxCsDcP9y3+N5AjpeuIBSx9e3PcYzjQdkykzcuTYTx0RHYTImJBhriYamrHKYelLMudTE8mBRTXZiaKImr8+j87D0h/Qmpg4ZDz+NJR+/jJlRq7y1wThnmW/REaU9GZSs9WIlw/8P5w2HBjmI2kyOS59YT81ucra2wJLa4kkpk1kPzWRHFhUk13ju/9C80fvSWLKoGBk/vgZqMMiZMqKLpVW5Y9vLn0SWXGLJXGrzYJ/HPo5jtXukicxsnM8qeZ8anKVYz+1oA6AOm62TNkQ+TYW1QQAaNuzA3WvviCJDc6i/iX89MkyZUVjpVZq8LVFT2BOwmWSuE204Y0jz+Bg5UcyZUbtLT1obpDeCMyTanKVyaGfWqNfxDY9IpmwqCZ0n85H5VCzqDc+huAszqL2dEqFCrcueASLkq+SxEWIePv4ZuwufWeYj6SJ5HhK7R+oQUIyt5OSaxxPqrVJvEmRSC4sqn1cf00lyp56DKLFLIknfO1+RKxYI1NWNN4UghI3zdmInLT1Ts+9f+olfFL0OkRRlCEz3+U4nzpzRjwUSv5IptETLSYY645IYtok3qRIJBf+BPdh5vZWlP7iUVh7eyTx6GtuROz6r8iUFU0UQRBw/ax7cfkU5znjnxS9hg9Ov8zCehI5nlSz9YNcZTIcAyxGSUybuHiYq4loorGo9lHW/r7BWdRNDZJ46MLlSPzmdzmL2ksJgoCrs+7EtTPucnru89L/YGv+H2ATbTJk5lv6e42oLm+RxLj0hVzl2PqhjsmCwj9cpmyIiEW1DxKtFlT87kn0lRVL4gGZ05H2vf8HQamUKTOaLKszb0Ju9nec4vsr/4d/Hf0drDarDFn5jtLCBoi28+8KqNRKpE6NlTEj8kTGaofxp1xNTiQr3iLsY0RRRPVfNqPzqMMd47E6ZDz2FBRaP5kyo8m2LPU6aJX++NcXz0LE+dPpL2p3YMDUh+T+ZWhqaoFOp0NOTg6U/MfWuHHsp07JjIFGwx/HNHqiKMJYLZ03r2VRTSQr/hT3MY3vvImWj9+XxJRBIWdnUfNtQ18zP2ktNCo/vHb4aVhFCwCgZH8DXnz5KfS0nu/V1Ov12Lx5M3Jzc+VK1auUcOkLjZG1vQK2Hmn7HotqInmx/cOHtO3+FHX/fFESE9QaZDz2K/glJMmUFcltVvxy3LXkp1ArtSjZ34D3nzkuKagBoK6uDhs2bMDWrVtlytJ7WMxWlBdLiyEufSFXOfZTKwKjoYrIkCkbIgJYVPuM7lPHUfn7X0uDgoDUhx5H0PRZ8iRFbmNq7Hx8Y9FPsfPloiGfPzcV5KGHHoLVyn7rsagqa4bJaJHEMrN0MmVDnsppPnXiEt5gTiQzFtU+oL+mEmVPP+40i1r/tfsRvmyVPEmR26kv7EB368Cwz4uiiJqaGuTl5U1iVt7njEPrR3xSBIJC/GXKhjyVU1GdzPnURHJjUe3lzG2tKP35I86zqK/NRcz1N8uUFbkjg8EwrtfR0JzmU7P1g1xkG+iEuemUJKZNZD81kdxYVHsxa38fSn75KEzNjZJ42OIVSPzGA3yrkCRiIzSjuq7eXMAlMZdIFEWnoprzqclVxtpDwIXfg0oNNPHz5EuIiACwqPZaotWC8t/+FP3lJZJ44JQspD78Y86iJgmbqQNzhKcRHwlc7J9awVF+qAs8jDeP/gZmq2nS8vMWDbUd6O7sl8R4Uk2uMlY5zKeOnwdBzXGoRHJjUe2FRFFE9YvPoeuLg5K4Ni4B6ZxFTQ5Eaz96DtwE9JzCr+5SAxi+sF591zQolAK+qN2JF/Y8iu6B9slL1AucOV0neRwWGYio2BCZsiFPZapxnE/Nfmoid8Ci2gs1/Oc1tHz6gSSmDA5Fxo+fgTo0TJ6kyC2JNgt6Dn0NlpY9AIB1S5R45Qdq6KKkI+xjdJG4/pG5yFwaZ49VtRdh8+cbUd9ZPqk5e7Kh5lOzDYtcIVotMNY4HJgkLZEpGyK6EItqL9O66xPUv/5XSUzQnJ1FHa+XKStyR6Ioou/4gzAbtkni169MQEVZIXbu3Ik33ngDO3fuRH1NI556+AVoVdIpFR39zfjD7u/htEF6ckZDc75JMUGmTMhTmZtOQTRJbzzn0hci98CNil6k++QXqPrjULOon0DQtJnyJEVuq7/gZzBWviKJCaoQBC9/D6qQDKxaJV0kkRW3CA9c9iz+duCnaO87f/OryTqAvx98EldNvwNLU76EQG3opOTvaTraetFY3ymJcekLucpxlJ4qIh3KoFiZsiGiC7Go9hL9VeUoe/rHEC3SpRL6b3wH4UtXypQVuauBsj9hoNjhH2AKLYKWboEqbPawH6cLScGDKzfhHwd/jsq2AntchIiPCl/FR4WvIjpIj5SI6UiJmIHUyCxEB+nZ4gDnU2q/AA0SUyJlyoY8ldN8ap5SE7kNFtVewNTWgpJfPAprn/QtwZh1NyF23U0yZUXuyljzFvryv+8QVSBo0atQR+eM+PHB2jDct/wpvH38eRyt2e70fHNPLZp7anG4+lMAQIA6GMkR05EaOQPJEdORFD4FaqV2PL4Uj+K49CVjug4KJTvwyDWORbWGRTWR22BR7eGs/X0o/cWjMLc0SeJhSy6D/mv3y5QVuStz43b0HrkbgHTOdMDcP0ATf/2oX0el1OCr876HuJBk/O/0KxAx/NzqPnM3ChsPobDxEABAKaiQEJaOlIiswf9FZiHEL+KSvh5PwqUvNFaWrjpYO6okMZ5UE7kPFtUeTLRYUP6bn6C/olQSD5w6A6kPPcFZ1CRhaTuC7gNfAUTpunr/rJ/CL/UbLr+eIAhYnXkT9GEZ2HHmbVS2FcBsNY74cVbRgur2YlS3F2N32TsAgIiAOHuBnRKRhbiQJCgE7/n7299nQlVZsyTGpS/kKpPDKbXgFwp1dJZM2RCRIxbVHkq02VD14rPoOnZIEtfqEpDx2K+g0Pre2+s0PGv3GXTvuxGw9kri2vT74Tf1kTG9dmb0XGRGz4XVZkF9Zzkq2wpR2VaAytbT6BxoHdVrtPU1oK2vAV/U7gAA+KkCkBwx/WzbSBaSwqc5TR7xJOVFDRBt50/zlUoF0qby5jJyjbHaYT514hIICrYQEbkLFtUeaKCuGlV/+i16CvIlcVXI4CxqVUiYPImRW7L116N77zqIphZJXKO/CQGzfztuNxEqFSokhk9BYvgU5KSvhyiKaO9vQlVbISpaC1DZdhqGzkqIsI34WgOWPhQ3HUVx01EAgEJQQBeSNngDZGQWUiNmICwgelzyngxnHFo/kjNjoPVTy5QNeSpjtXSTojaR86mJ3AmLag8iWixoePdNGN56FaJZuiJa0GiQ/thT8NNxFjWdZzO1o3vv9bD1VUviqpi1CFzwVwjCxJ1yCYKAiIBYRATEYq5+FQBgwNyH6vbiwZPstgJUtRXCaOm/+AsBsIk21HWWoq6zFHsrBudqh/pHIfWCvmxdSBqUCvdsGRlq6QuRK2ymPpgMxyUxbTI3KRK5ExbVHqK3tAhVf/wN+itLnZ9UKJD68I8RNHXG5CdGbku09qNn/wZYu05L4sqweQhe/CYEhWbSc/JTB2BKzFxMiZkLALCJVjR0VZ1tFylARVuBZAb2xXT2t+B43W4cr9sNANAo/ZAUPtVeZCdHTIe/OnDCvpbRslisKCtqkMQ4n5pcZao7AtguGJmqUEKTsFC+hIjICYtqN2czDqD+zVfQuO0twOb8trkmJg7J33kUIbPnyZAduSvRZkHPwTtgaZW+XawIykTw8nchqINlykxKISgRH5qG+NA0LEu9DgDQ2d9qP8mubCtEXUcpbKJ1xNcyWQdQ2pKP0pbBtigBAmJDkpESkYXUiCwkR05HZIBu0mdm15S3wDggvTk0M0s3qTmQ53McpaeOmw2FNkimbIhoKCyq3VjXiS9Q/effwthQ5/ykQoGY6zYg/pa7oPTz3Bu4aPyJoojeYw/A3PBfSVzw0yF4+TYotO7dixzqH4nshBxkJwzOzDZZBlDTcWbwBsjWwWK739wzwqsMLqRp6KpEQ1clDlT+DwAQrA1HSkSW/QbIhLAMqBQT29vsOJ86Th+OkLCACf2c5H2clr4kcpQekbthUe2GzB1tqHv9r2j97L9DPu+fnIbkbz+CwCnTJzkz8gT9p/8fTFX/kMQEdRiCl78PZWCyTFldOo3KD+lRs5EeNbjp0Sba0NRdM3gD5Nm2kZbeIf7hOYRuYztOGvbipGEvAECl0CAxfMrZDZCDbSOBmpBxzZ/zqWmsRJsNphqHyR+cT03kdlhUTyKr1Yq8vDwYDAbodDrk5ORAeXaWtLmjHR0HdqN93y50nz4+ZKuHoFJDd/OdiL3hFijUnBxAzgZKf4+BM7+VBhV+g+vHQ2fKk9Q4UwgKxIUkIy4kGYtTrgYA9Bg7JCfZNR1nYL2w/3QYFpsJFa2nUNF6yh6LDtIP3gB5dmb2WNasi6LoNPmD86nJVZaWYtj62yQxFtVE7odF9STZunUrNm7ciNraWnssIT4eP7/rDiwXjMMW0ucETpuF5G9/H/6JKROfLHkkY/Wb6DvhMHNaUCJo0T+hjlouT1KTJEgbhpm6pZipGyw0LFYTajtK7b3ZFa0F6DV1juq1zq1ZP1T9CQAgQBNy/iQ7IguJ4ZmjXrPeWN+BrvY+SYyTP8hVRodTamWIHqqwJJmyIaLhsKieBFu3bsWGDRsgitJVznX19bjrF7/GM4uysCY+asiPVfj5I+GOexF99XoO+adhmRo+Qe/Re5zigXP/CE38dTJkJC+VUjN40hw5uG1OFEW09hpQ0Xbafprd2F09wqsM6jN1oaDhIAoaDgK4cM36DKSenTIy3Jr1ovwaNLSVoM/YhQBtCDLTZiEmPnR8vkjyGU7zqZM4n5rIHQmiY6VH48pqtSIlJUVyQu0o1l+L969cBOUFbzEr/PwRtiQHCbfeDU00N6/R8Cxth9CVdw1glZ6I+s94Ev5TfyBTVu6vz9SNqnPbH9sKUd1ePKo160OJDIhDSuSMs6fZ0xEbkox333kXd991L9o7zy/dCQuJwsuvvIjc3Nzx+jLIB9RvnglLyxn74/AvPYvgpQ/ImBERDYVF9QTbtWsXVq9ePeJ1LyyfjUWJOoQuWIrwZasQOm8xFFq/SciQPJm1uxhdn6+FaJKuA9dmPICAWc9M+vg4T2a1WVDXWXbBBsgCdI1yzbqjykMd+M9TB4Z4RoAgAFu2bGFhTaNi7W1B3dPSlqHY+/ZDmzBfpoyIaDhs/5hgBoNhVNcpr1iP7B8+xkKaRs3WV4vuPdc5FdSaxK8iYNavWVC7SKlQISl8KpLCpyIn/Qb7mvVz7SKVbQWjWrNus4r4+KVjwzw7eIaxceODWL9+vf1GZaLhOPZTC+oAaOJmy5QNEV0Mi+oJptONbslDxso1LKhp1GymtsH14/3StiJ1zBUInP/ihK4f9xUXrlmflzj4btOAuffsmvVCVLaeRlV7kdOa9brCNvS0Dt9GIopAbW0dvrv5y7jy8quRFjkTqVEzEawNm8gvhzyUyWE+tUa/EIKS05+I3BGL6gmWk5MDvV6Puro6pxsVgcFf3Hq9Hjk5OTJkR55ItPShZ9+XYe0ulMSV4QsQtOQNWdaP+wo/dSCmxMzDlJjBDabn1qwPtosM3gRZ2F4/wqsMqqqrwJ7y97Cn/D0AQExQItKiZiItcibSImchLMC9l/TQ5HBa+sJRekRui0X1BFMqldi8eTM2bNgAQRAkhfW5t+c3bdrEt4FpVESbGT2HboelTfqWsCJoCoKXvQNBxbXFk+nCNevL0wanrHyA9/C/Z28Y8WODwqVj+Zp6atDUU4MDlR8CAMIDYpEeOetsoT0LkYGTv2Kd5CVaTDDVHZHEWFQTuS/eqDhJhppTnZiYiE2bNvGGJRoVURTRe/QemKpfk8QFv3iErNoJZQDn1roDq9WK5ORk1NUNv+UxOMoPd7+wEgrl6IvkEL/IwVPss0V2THAiFGzz8WrGmkNofGmFJKZ/rBEK/3CZMiKii2FRPYkutlGRaCR9Jx/DQMlzkpigDkfwys+gCsmSKSsayvPP/gUbv+c8N/zcSfMfX3kWU5bEoaz1JCpbC2CyDrj8OQI0IUiLnIG0yFlIi5qF+NBUKAT+PPEmXfs2o+PD82Mx1dHToXswX8aMiOhi2P4xiZRKJVatWiV3GuSB+ks2ORXUUPojaNl/WFC7oVRdNlZlfwOHit5Bn7HDHtfr9ZJ3p9biq7DarKjrLEV5y+C69PLWU+g394z4OfpMXThl2I9ThsGeWz9VAFIis+xFtj4sAyoFb2jzZMYq6dIXTfIymTIhotHgSTWRmzNWvY7eo3dLg4ISQUvehkZ3jTxJ0UU9++P3cOJQJWyiDU3tZUifFY6b7lw7qnenbKINDV1VKG89aS+0u43tLuegVmqRHD4NaVGzkBY5C8kRU0e9Xp3kJ4oi6p5Jhq2nwR6LuPGvCJp3p4xZEdHFsKgmcmOmho/Qs38DIFol8cD5f4E2+XaZsqKLsdlEPHDTi+jrOT9W7/4fXYPFq6Zc0uuJoojmnjp7kV3eehId/c0uv45SUCExfMrZInsmUiKy4KcOuKScaOJZ2itQ/+xUSUz30GmoIzNlyoiIRsL2DyI3ZW49gJ6DtzoV1P4zf8mC2o3VV7dKCmoAyJwxunn1QxEEATHBesQE67EkZfCdiba+RpS3nER56ymUt5xCS+/wN0WeYxUt9iU2O/BvCFAgISz9bLvI4Ci/AE3wJedJ48txlJ4iMBqqiAyZsiGi0WBRTeSGrF2F6NmXC1ili0X8MjfCf8r/yZQVjcaZU9I51ZGxwYiIHt9iNSIgFhFJsViQdDkAoGug7WyBPVhoN3RVjvgaImyo7ShBbUcJdpdtBQDoQlKQekGRHeIXMa550+g5zadOXMKRikRujkU1kZux9tWge+86iGZpH60m6Vb4z/yVTFnRaJUUGCSPp8yIn/DPGeIXgTkJl2FOwmUAgF5TFypaT9uL7LqOshHXqwOAoasShq5K7KvYBgCIDkoYPMk+u/UxIiB2Qr8OOo9LX4g8D4tqIjdiM7aie+862Pqlb+erY69G4LwXuH7cA5Selp5UZ2ZNfFHtKFATgpm6pZipGyzEBsy9qGwrtJ9m17SfgVW0jPg6zT11aO6pw8GqjwAA4f4x9p7stKiZiApM4OnpBLANdMHceEoS0yZx8geRu2NRTeQmREsvuvfdCFt3sSSujFiEoMWvQeB4NLfX3tqD5oYuSWws/dTjxU8diGmxCzAtdgEAwGQZQHV7sb3IrmovgtlqHOFVgPb+Jhyt2Y6jNdsBAMHa8PNFduRMxIYkcyHNODDWHgLEC95ZUGqgiZ8nX0JENCosqoncgGgzo+fgbbC2H5bEFcHTELx0KwRVoEyZkStKTktbP/wDNUhIjpQpm+FpVH7IiM5GRnQ2AMBiM6O2vWSwyG49iYrW0zBa+kd4FaDb2I78ut3Ir9sNAAhQByPVvvVxJuJD06FUcCGNq4zVDvOp4+dBUPvJlA0RjRaLaiKZiaINvUfvhbnxY0lc4Z+A4OXvQ6F1v6KMhlbi0PqRMV0HhdL9T25VCjVSIrOQEpmFNbgZVpsVhq5y+wi/8pZT6DN3j/g6feZunG7Yj9MNg/3AWpU/UiJm2IvsxLBMqJSaif5yPJ6p+oDkMfupiTwDi2oiGYmiiP6TP4Kp5k1JXNBEIHj5B1AGJMqUGV0Kx6I6cxJuUpwISoUS+rBM6MMycVnGjbCJNjR2V59dRnMSZS0nR7WQxmjpR3HTERQ3HQEAqBQaJEdMs4/xSw6fBo2KJ7AXEm1WGGsPSmIsqok8A4tqIhkNlDyLgdLnpUFlAIKXbYUyZJo8SdElGeg3obpMupTFU4tqRwpBAV1ICnQhKViedh1EUURLb/35k+zWU2jvaxzxdSw2E8paTqCs5QRQPLiQRh+eefbGx1lIiciCv9q3W53MjacgGqXvCrCoJvIMLKqJZGKs+if6Tz0hDQoqBC1+A6qIxfIkRZesvKgBNtv5BbVKpQJpU71zBJ0gCIgOSkB0UAIWp1wFAGjva5LMym7uqR3xdayiBVVthahqK8TOkrchQIH40DSkRc1EeuQspEbOQKA2dKK/HLfiOEpPFZEOZZB3/j0i8jYsqolkYDL8F71f3O8UD5z/EjRxV8mQEY2V402KyRnR0Pr5zsSW8IAYzA9Yg/mJawAA3QPtTgtpRIgXfQ0RNtR1lqKusxR5Ze8CAGKDk+092WmRsxDq7933GDgW1ZrEJTJlQkSuYlFNNMnMrfvQc/B25/Xjs56GNukWmbKisTrjJf3U4yXYLxzZCTnITsgBAPSZugcX0pwttOs6S2ETR15I09hdhcbuKuyv+C8AICow3r6MJj1yNsIDYrxqVrbT0pdkzqcm8hQsqokmkaXzNHr2fRmwDUjiflP+D/6ZG2XKisbKZrWhrKhBEsvIkn8+tTsJ0ARjhm4JZugGT14HzH2oai+092VXtxfDaht5IU1Lbz1aeutxqPoTAECYf7R9GU1a5CxEB+k9tsi2dNXD2lEpiWl5Uk3kMVhUE00Sa1/V2fXjHZK4JukO+M/4hTxJ0bioqWzFQJ9JEvP1k+qR+KkDMDVmPqbGzAcAmK3GwYU0LadQ3noKlW0Fo1pI09HfjC9qd+KL2p0AgCBtmH0ZTVrULMSFpHjMQhqTwym1oA2BOmaGTNkQkatYVBNNApuxGd171kEckPbdquO+hMB5f/LYkzUaVHJK2voRowtFWIRvT7FwlVqpRXrUbKRHzQYwuJCmrqP0bLvIKVS0nsKApW/E1+kxduBE/R6cqN8DAPBXByE1coa9yE4ITYdS4Z6/+ow1DvOpE5dAUHjGPwiIiEU10YQTLT2D68d7SiRxVeRSBC36JwQ3/QVPo1dS4NBPPZOn1GOlUqiRHDEdyRHTsTrzJthEKwydFfYiu7z1JHpNXSO+Tr+5BwUNB1HQMDj7WaP0Q0pklv3Gx8TwKVC7yUIax02KHKVH5Fn425xoAok2E7oPfBXW9qOSuDIkC0FL/wNBFSBTZjSeHE+qM7NYVI83haBEQlgGEsIykJN+A0RRHFxI0zp4il3WchJdA60jvo7JOoAzTV/gTNMXAAaL96Twafae7OSI6dDKsJDGZu6Hqf6YJMaimsizsKgmmiCiaEPvkW/B0rRdElf4Jw6uH9eEy5QZjafWpi60tfRIYpkzeJPiRBMEAXEhyYgLScay1GshiiLa+hpQdnaEX0XLSbT2NYz4Ohab+ewCm5MA3oRCUEIfloG0qFlIi5yF1Igs+GuCJvzrMdUdAS68UVNQQKNfNOGfl4jGD4tqogkgiiL6TvwAptq3JHFBE4ngFdug8E+QKTMab47zqQOD/aBLjJApG98lCAIiA3WIDNRhUfKVAAZvYjx342N560k0ddeM+Do20Yrq9mJUtxdjV8kWCBCgC01FWuQspEcNLqQJ0oaNe/6Oo/TUcbOh0E58MU9E44dFNdEEGCj+DYxlf5IGlYEIXvYOlMFT5UmKJoTjfOqMLB0UCt546g7C/KMxL3E15iWuBgB0GztQ2Xr67Gn2SRg6K0axkEZEfWc56jvLsaf8PQBATHCivchOi5yJUP+oMefq3E/N+dREnoZFNdE4G6h4Bf0FP5EGBRWCl/wLqoiF8iRFE6bEoaiewlF6bitYG4ZZ8csxK345AKDf1IOKtoLB9o+Wk6jtKBnVQpqm7ho0ddfgQOX/AACRAXFIjZqF9MhZSIuaiYiAOJcm+oiiCFO1w+SPJM6nJvI0LKqJxpGp/n30HXvAKR644C9Qx14uQ0Y0kfp6jaitlN4cx35qz+GvCUJW3CJkxQ32Lhst/ahqKzpbZJ9CdXsRLDbziK/T2teA1uoGHKn+FAAQ6heJtKhZSI2cidSILMSGJEEhKIf9eGNjAfYWtqCpB4gJAhYlCTypJvJALKqJxom5ZQ96Dt0JQHrSFTD7N9AmflWepGhClRU2QLSdbx9QqZVImRIrY0Y0FlqVP6bEzMWUmLkAALPVhJr2M2dvZDyFytYCmKwDI7wK0DnQimO1u3Csdpf9dZPCpyI5fDqSIqYhOWIaAjUhAICtW7fiwfvvRl2T1f7xulAlfj/vML785aTx/yKJaMIIoihevKGMiEZk6TyJ7t1XQDR3SuJ+U36AgJlPypQVTbSt/9iP9984ZH+ckaXDE8/dLGNGNJGsNgvqOstQfm7CSOtp9Jt7Rv7AIUQFJqDxuBmbHn0Vjm3dAgAIArZs2YLc3Nwx501Ek4NFNdEYWXsr0bVrNUSjdHyXNvnrCOC2RK/260f+g8L8Wvvja26aj6/cvULGjGgy2UQrGrqq7EV2eesp9Bg7RvexVhF/uXcXelqHXsUuCAISEhJQWVkJpXL41hEib2a1WpGXlweDwQCdToecnBy3/n5g+wfRGNgGmtC95zqnglqtuw4Bc3/PgtqLWSxWlBVJ/7tnZrGf2pcoBCXiQ9MQH5qGFenrIYoimnvqUN56AmUtJ1HZVoj2vsYhP7ausG3YghoYvHmxtrYW9z13HZbnLIMuJBXxoamIC0lBZGDcRXu0ibzB1q1bsXHjRtTWnj+40Ov12Lx5s9u+g8OimugSiebuwfXjvWWSuCpyOYIWvcr1416uprwFJqNFEstgUe3TBEFATLAeMcF6LEn5EgCga6AN1W1FqGwvRHVbEWo6SmC2GtHTPnxBfaF6Qz1OGfbhlOH8yD21Uou4kBTEhwwW2bqQVOhCU+x92kSebuvWrdiwYQMcmynq6uqwYcMGt22N4m99oksgWo3oPvAVWDu+kMSVITMRtHQLBKW/TJnRZDnjsJo8Th+OkDCunSepEL8IzIxfhpnxg9M8rDYLDF0VeKfvbfwPJ0b8+KBwrVPMbDWipr0YNe3FknioXyTizhbY8SGpCPGLPDuHW8RgbSIOPhbP/T8REM9N6hbtBcz5+NnHF/7/s8/Z///Z5+2PRPGC18bQn//s46Fzc87H/uyFn2e0+do/xiEfx1wHX2hUOZ3/rCP/+V34eexfy4U5Ofz5DZvvBflIPs+wuQ6R7yj+/Bzzvdif3/n/PiP89xYv+KhR/PlZrVZsvnebU0F9Lh9BEPDQQw9h/fr1btcKwqKayEWiaEXvkW/C0rxTElcEJCN4+XtQaMLkSYwmVUmBw3zqmZxPTSNTKlTQh2Xi2195FM88+mfU1dbCuXQYFBzlh4Tpo9/O2TnQis6BVhQ3HRmfZIlkUHOqFV0t/cM+L4oiampqkJeXh1WrVk1eYqOgkDsBIk8iiiL68r8HU91/JHFBE4Xg5dug8Gdh5QtEUXRa+sJ+anKFUqnEc8/8CsDZaR8XEAQBgiDgd8/+Frcs+B4uS78RmdFzEKgJnfxEiSbZaFujDAbDBGfiOp5UE7lgoOhpGMtflAZVQQhe/i6UwZnyJEWTrrmhC51tfZJYJjcpkouunReBP29Q4mcfW2HoPh/X6/XYtGnTkD2j3QPtMHRVoL6zAoauCjR0VaKhuwpWm8XpWiJPNFTL01B0Ovc7yGBRTTRKA+V/RX+hw8xpQY3gJf+GKny+PEmRLBxPqYND/RGbECZPMuSxBirycM00Ba6cIuBQtYh2/2mYdusfLjo2LNgvHMF+4ZgSM88es9osaO6pg6GrAoauShg6K9DQXQWTZWDw1PuCs/DBiUSCfRb24P+TPnZ6bjAw+FjABfFzr3zB53B4/tyzEC74TBfkJMnH/jFnrx0yVzjndPZal/K9MDenxxhdvg5/fsM+N0Q+jp9nuHztzzj9WQ7/5yd97oKvapicpH+WF8l32D8/6X+fUedr//sm/bptS6zY/efr0GhoGrKvWhAE6PV65OTkOD0nNxbVRKNgqnsXfcc3OkQFBC58GeqYNbLkRPJxav2YEc/xieQyY+VuAIBSIWBpioCQVTch7BJ6RJUKFeJCkhEXkoy545wjkRz++Ps/YcOGDRAEQVJYn/s5u2nTJre7SRFgTzXRiMzNu9Fz+GtwWj+e/Tto9TfJkxTJquS0tJePrR/kKpuxGybDMUnML3WlTNkQuZfc3Fxs2bIFCQkJkrher3fbcXoAT6qJLsrSkY+e/TcBNpMk7jf1h/BLv1+mrEhOvd0DqKtqlcQyZ7hfbx+5N2P1PsBmPR9QaqBJXCxfQkRuJjc3F+vXr+dGRSJvYO0pR/fe9RAtXZK4NuWb8M/6fzJlRXIrKZCeUqs1SqRkxMiUDXkqY8Xnksda/UIo1JxvT3QhpVLpdmPzLobtH0RDsA00onvvOohG6Yphdfz1CJi7mf2zPqzUoZ86bWocVGr3PTkh9zRQmSd5rE1xv5uuiMg1LKqJHIjmLnTvvQG23nJJXBWVg6CF/4AgsIDyZWc4n5rGyGbqhanuqCSmTblMpmyIaLywqCa6gGgdQPeBm2HtPC6JK0NnI2jp2xCUfvIkRm7BYrai4oz03YtMblIkFxmr9wMXzpVWqKBNWipfQkQ0LlhUE50lilb0HP4GLM3SXkdFQAqCl70LhZrbzHxdZWkTzCarJJYxnSfV5Jpzo/TO0STMh0ITKFM2RDReWFQT4ez68eMPw1z/riQuaGMQvOIDKPxZOBFQckra+pGQHInAYL57Qa4xOvRT+7GfmsgrsKgmAtBf+EsYK/4iDaqCEbzsXSiD0uVJityO4+QPjtIjV9nM/TDWHpbEtJxPTeQVWFSTzxsofwkDRb+UBhUaBC95C6pw7iejQaIoDrlJkcgVppqDgPWCufcKJbRJy+RLiIjGDYtq8mmm2v+g7/hDDlEBQQtfgTpmlQwZkbtqrOtAd2e/JMaimlw14DCfWqObC4U2WKZsiGg8sagmn2Vu2oWeI3cBECXxgDmboElwzxWoJB/HU+qwiEBEx4XIlA15Ksd+ao7SI/IeLKrJJ1naj6H7wBDrx6c9Dr+0e2TKityZ43zqjBk6LgEil4jmARhrD0pifqm8SZHIW7CoJp9j7SlD974bAEuPJK5N/Rb8pz8uT1Lk9kpOS29SnMLWD3KRse4wYDGeDwgCtEnL5UuIiMYVi2ryKbZ+A7r3XAfR2CSJqxNuRMCc53jySEPq6uhDQ227JMZ+anKVsUI6n1odlw2Ff5g8yRDRuGNRTT7DZu5E974bYOurlMRV0SsRtOAVrh+nYZU6jNLTaFVITIuSKRvyVANO86nZT03kTVhUk08QrQPo2X8TrJ0nJHFl6BwEL3kLglIrU2bkCRznU6dPj4NKxX+E0eiJFhNMNfslMS2XvhB5FRbV5PUG149/DZYW6SmRIjANwcvfhaDmBAe6OMdNiplZbP0g15jqj0I0XzCSURBYVBN5GRbV5NVEUUTfsQdhrn9fEhe0sYPrx/1iZcqMPIXJZEFlqbQHf8pMFtXkmgHHfuqYmVAGRMiUDRFNBBbV5NX6C56EsfJvkpigCkHw8vegDEyVKSvyJJVnGmExW+2PBYWA9GlxMmZEnshYKS2qtanspybyNiyqyWsNlP0JA8VPS4MKLYKWvg1VWLY8SZHHcZxPrU+JhH8ge/Bp9ESrGcbqfZKYH1s/iLwOi2rySsaaf6Ev//sOUQWCFv4D6mieENHocT41jZWp/hhEU68kxn5qIu/Dopq8jqnuXfQeuRtO68fn/h6ahPXyJEUeyWYTUepwUs351OQqx9YPdfR0KAOjZcqGiCYKi2ryKqaGj9Bz6E5AtEri/lk/gV/qXTJlRZ7KZqWaVQAADVdJREFUUNOG3h6jJJY5QydTNuSpHOdTs5+ayDuxqCavYW7ahZ4DtwCiWRLXZjwAv6mPypQVeTLH1o+I6CBExnAEI42eaLPCWLVXEmPrB5F3YlFNXsHcug/d+zcAtgFJXJt6NwJmPcP143RJStj6QWNkNuRDNHZJYtykSOSdWFSTx7O0H0XP3hsBq/RGIE3SrQiYs5kFNV0yFtU0VgMO/dSqqClQBnMkI5E3YlFNHs3SeRLde9ZBtEhPgjQJuQic9yIEgX/F6dJ0tPWiydApibGoJlc53qTIU2oi78WKgzyWtbsY3Xuug2hul8TVcdcicOErEBQqmTIjb+B4Su0XoEFiSqRM2ZAnEm1WDFTukcTYT03kvVhUk0ey9pSjK+8aiEbp+mhVzFoELX4NgkIjU2bkLUoLpDcpZkyPg0LJH5k0eubGkxAHOiQxTv4g8l48yiOPYLVakZeXB4PBgJhwJeZYn4BglBY9qsjlCF7yFgSln0xZkjc5c8qhnzqLrR/kGsdReqqIdKhCEmTKhogmGotqcntbt27Fxo0bUVtba4/FRwK/ukuNdUuUAABl+AIEL9sKQRUgV5rkRYwDZlSXNUtimTNZVJNrjBXSfmq2fhB5N76XSW5t69at2LBhg6SgBgBDK/CN35ix7YAVytBsBC9/H4Ka84NpfJQXN8JqtdkfKxQC0qdxYgONnmizwVjFfmoiX8KimtyW1WrFxo0bIYqi03PnIo//HQhY+i4UmvBJzY28m+NNiknp0dD6qWXKhjyRubkAtr5WScyP/dREXo1FNbmtvLw8pxPqC4kA6prN2HuoaPKSIp/A+dQ0VkaHfmplWApUYckyZUNEk4FFNbktg8Ew8kUuXEc0GjarzWnyB4tqcpVjP7VfKls/iLwdi2pyWzqdblyvIxqNuqpW9PeZJLHMGfw7RqMniqLT5A8tl74QeT0W1eS2cnJyoNfrh10zLggCEhMTkZPDEyAaPyWnpafU0XEhCI8Mkikb8kSW5iLYeqUz9P14kyKR12NRTW5LqVRi8+bNAOBUWJ97vGnTJiiVyknPjbzXGYd+6gy2fpCLHE+plSF6KMNTZcqGiCYLi2pya7m5udiyZQsSEqQLE/R6PbZs2YLc3FyZMiNvVVIgLaqnsKgmFxkrnedTD/eOGxF5Dy5/IbeXm5uL9evX2zcq6nQ65OTk8ISaxl1bczdaG7slMfZTkytEUXSa/MFRekS+gUU1eQSlUolVq1bJnQZ5Ocd+6oAgLeKTImXKhjyRpa0U1m7p3yMufSHyDWz/ICI6y7H1IyNLB4WCb9vT6BkrpKfUiqA4qCIzZcqGiCYTi2oiorOclr5ksfWDXDNQ6Tif+jL2UxP5CBbVREQA+vtMqC5vkcSmzEwY5moiZ0P1U3M+NZHvYFFNRASgrNAA0SbaHytVCqROiZUxI/I01vYKWDtrJDHOpybyHSyqiYgAlDisJk/OiIFGy3u5afQc51MrAmOgip4mUzZENNlYVBMRASg9zfnUNDbO86lXsJ+ayIewqCYin2e12lBa2CCJcT41uWrAYfKHH/upiXwKi2oi8nk15S0wDpglsUyeVJMLLB3VsHZUSmKcT03kW1hUE5HPc5xPHZsQhpCwAJmyIU/k2Pqh8I+AOmaGTNkQkRxYVBORzys5xfnUNDaONylqU3IgKPgrlsiX8DueiHyaKIo447j0ZSZbP8g1jpsUtanspybyNSyqicintTR2o6O1VxLLzGJRTaNn6aqDpa1UEuN8aiLfw6KaiHyaYz91UIgfdInhMmVDnshYIe2nFvzCoI6dJVM2RCQXFtVE5NMc51NnZsVztjC5xHE1uV/ycggKpUzZEJFcWFQTkU9z6qfmfGpy0YDj0hf2UxP5JBbVROSzenuMqKtslcQ4n5pcYe1ugKXljCSm5dIXIp/EopqIfFZZoQGieP6xSq1ESmaMfAmRx3EcpSdog6GJy5YpGyKSE4tqIvJZJQ6tH6lTYqDWqGTKhjyRYz+1Nmk5BCX/DhH5IhbVROSzSk4bJI/Z+kGuctyk6Md+aiKfxaKaiHySxWJFeXGDJMaimlxh7W2GualAEmM/NZHvYlFNRD6purQZJqNFEuN6cnKFY+uHoAmEJn6uTNkQkdxYVBORT3Jc+hKfFIGgEH+ZsiFP5HiTojZpGQSlWqZsiEhuLKqJyCedOSUtqjN4Sk0uctykqOVqciKfxqKaiHyOKIooKZDepDhlJvupafSsfW0wN52SxPzYT03k01hUE5HPaarvRFd7nySWmcWimkbPWLUHFw45F9T+0CQskDEjIpIbi2oi8jmO/dQhYf6IiQ+VKRvyRI43KWoSl0BQaWTKhojcAYtqIvI5Q82nFgRBpmzIEw04zqdmPzWRz2NRTUQ+x3GTIudTkytsA50wG/IlMW3qSpmyISJ3waKaiHxKT1c/6qvbJLEpLKrJBcaqvYBoOx9QaaFNWChfQkTkFlhUE5FPcZz6odGqkJQRLVM25IkGHEfp6RdDUPvJlA0RuQsW1UTkUxxbP1KnxkKlUsqUDXkiYyXnUxORMxbVROQzrFYrPvnoM5QbjqKhrQQ20cbWD3KJzdgNk+GYJOaXyvnURASo5E6AiGgybN26FQ8+uBF1dbX2WIA2DHMufwrAMvkSI49irN4H2KznA0o1NPrF8iVERG6DJ9VE5PW2bt2KDRs2SApqAOgzduD7P/w2tm7dKlNm5GmcVpMnLIRCEyBTNkTkTlhUE5FXs1qt2LhxI8QLtt85euihh2C1Wod9nuicAYelL+ynJqJzWFQTkVfLy8tDbW3tsM+Looiamhrk5eUNew0RANhMvTDVHZHEOJ+aiM5hUU1EXs1gMIx8kQvXke8y1RwAbJbzAYUK2qSl8iVERG6FRTUReTWdTjeu15HvGqj4XPJYkzAfCk2gTNkQkbthUU1EXi0nJwd6vR6CIAz5vCAISExMRE4Oe2Pp4owO/dR+7KcmoguwqCYir6ZUKrF582YAcCqszz3etGkTlEougKHh2cz9MNYelsS0KZxPTUTnsagmIq+Xm5uLLVu2ICEhQRLX6/XYsmULcnNzZcqMPIWp5iBgNZ0PCApokzjfnIjO4/IXIvIJubm5WL9+PfLy8mAwGKDT6ZCTk8MTahqVAYfV5Jr4uVD4hciUDRG5IxbVROQzlEolVq1aJXca5IEc+6nZ+kFEjtj+QUREdBGixTjY/nEBLn0hIkcsqomIiC7CWHsYomXgfEAQ4Je8Qr6EiMgtsagmIiK6CKNDP7U6LhsK/zB5kiEit8WimoiI6CKc51Ozn5qInLGoJiIiGoZotcBYc0AS06aw9YOInLGoJiIiGoa58SREU68kxvnURDQUFtVERETDMFbvkzxWRWZAGRQjUzZE5M5YVBMREQ3DWCUtqnlKTUTDYVFNREQ0DKPjfOqkpTJlQkTujkU1ERHRECxd9bB2VktimsQlMmVDRO6ORTUREdEQTA5TPwRtCNTR02XKhojcHYtqIiKiIRir90sea/WLICj4a5OIhsafDkREREMwVu2VPNYm8yZFIhoei2oiIiIHNlMvTIbjkpg2ebk8yRCRR2BRTURE5MBUexiwWc4HFEpo9IvkS4iI3B6LaiIiIgeOrR8a3RwoNIEyZUNEnoBFNRERkQOnmxST2PpBRBfHopqIiOgCos0KY41jUc2lL0R0cSyqiYiILmBuPAnR2C2JcfIHEY1EJXcCRERE7qSvYi/2V9rQ1APEBAHL5mRAGayTOy0icnOCKIqi3EkQERG5g61bt+K737oD9W199lh8ZAB+/9I/kZubK2NmROTuWFQTERFhsKDesGEDHH8tCgAgCNiyZQsLayIaFotqIiLyeVarFSkpKaitrR3yeUEQoNfrUVFRAaVSOcnZEZEn4I2KRETk8/Ly8oYtqAFAFEXU1NQgLy9vErMiIk/CopqIiHyewWAY1+uIyPewqCYiIp+n041uusdoryMi38OeaiIi8nnneqrr6uqcblQE2FNNRCPjSTUREfk8pVKJzZs3AxgsoC907vGmTZtYUBPRsFhUExERAcjNzcWWLVuQkJAgiev1eo7TI6IRsf2DiIjoAlarFXl5eTAYDNDpdMjJyeEJNRGNiEU1EREREdEYsf2DiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGLGoJiIiIiIaIxbVRERERERjxKKaiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGLGoJiIiIiIaIxbVRERERERjxKKaiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGLGoJiIiIiIaIxbVRERERERjxKKaiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGLGoJiIiIiIaIxbVRERERERjxKKaiIiIiGiMWFQTEREREY0Ri2oiIiIiojFiUU1ERERENEYsqomIiIiIxohFNRERERHRGP1/AbVQnKZUA/cAAAAASUVORK5CYII=", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtUAAAMWCAYAAAA+uHrFAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3Xd8VGXWB/DfnZreew8EUkloSQgQepEmiojgirqubrGBvuvuvltcV3d1u6C+6rrFgquCiIqgUgUCBFJIQhKSENJ772UmM3PfPwITnkmvd+bO+X4+ftx7cm/myIbk5JnznIfjeZ4HIYQQQgghZMwkQidACCGEEEKIqaOimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxoqKaEEIIIYSQcaKimhBCCCGEkHGiopoQQgghhJBxkk3kJ9Nqtejp6ZnIT0nIiMjlckilUqHTIIQQQoiZmpCimud5VFdXo7m5eSI+HSFj4uDgAA8PD3AcJ3QqhBBCCDEzE1JU3yqo3dzcYGVlRUUNmVI8z6OzsxO1tbUAAE9PT4EzIoQQQoi5GXdRrdVq9QW1s7PzROREyKhZWloCAGpra+Hm5katIIQQQgiZUuPeqHirh9rKymrcyRAyHre+BqmvnxBCCCFTbcKmf1DLBxEafQ0SQgghRCg0Uo8QQgghhJBxoqJaAAEBAdizZ4/QaQzovffeg4ODg9BpEEIIIYSYlEkvqqurq7Fr1y4EBQXBwsIC7u7uWLx4Md5++210dnZO9stPGGMuhI05NwBYtmwZdu/ezVxzHAeO46BUKuHt7Y1Nmzbh0KFDwiVJCCGEEDIOk1pUFxYWYs6cOTh+/DhefvllpKWl4eTJk3jmmWfw1Vdf4eTJk5P58sPieR4ajUbQHKaKVquFTqcTOg29xx57DFVVVbhx4wY+++wzhIWFYfv27fjhD38odGqEEEIIIaM2qUX1448/DplMhpSUFGzbtg2hoaGYNWsW7rnnHhw9ehSbNm3S39vS0oIf/vCHcHNzg52dHVasWIGMjAz9x1944QXMnj0b+/btQ0BAAOzt7bF9+3a0tbXp7+F5Hn/+858xbdo0WFpaIioqCgcPHtR//MyZM+A4DseOHcP8+fOhVCqRkJCAgoICbN68Ge7u7rCxsUF0dDRT8C9btgwlJSV45pln9Cust1y8eBFLliyBpaUlfH198fTTT6Ojo0P/8draWmzatAmWlpYIDAzEf//73zH9Wb7wwgvw8/ODUqmEl5cXnn766SFzu9XGceTIEYSFhUGpVKKkpARNTU148MEH4ejoCCsrK6xbtw75+fmDvm5DQwNiYmJw5513oru7e9g/45GysrKCh4cHfH19sWDBAvzpT3/CP/7xD/zzn//U/9mr1Wo8+eST8PT0hIWFBQICAvDKK6+M4U+PEEIIIWRyTVpR3dDQgOPHj+OJJ56AtbX1gPfcKgB5nseGDRtQXV2Nr7/+GqmpqZg7dy5WrlyJxsZG/f0FBQX44osvcOTIERw5cgRnz57FH//4R/3Hf/3rX+Pdd9/FW2+9hezsbDzzzDN44IEHcPbsWeZ1f/azn+GVV15BTk4OIiMj0d7ejvXr1+PkyZNIS0vD2rVrsWnTJpSWlgIADh06BB8fH7z44ouoqqpCVVUVACAzMxNr167Fli1bcPXqVezfvx/nz5/Hk08+qX+thx9+GMXFxTh9+jQOHjyIN998U39Iye33LFu2bNA/y4MHD+LVV1/FP/7xD+Tn5+OLL77ArFmzhswNADo7O/HKK6/gX//6F7Kzs+Hm5oaHH34YKSkpOHz4MBITE8HzPNavXz/gGLry8nLEx8cjJCQEhw4dgoWFxYj/jMfioYcegqOjo74N5LXXXsPhw4dx4MAB5OXl4cMPP0RAQMC4X4cQQgghZMLx49TV1cVfu3aN7+rqYuKXLl3iAfCHDh1i4s7Ozry1tTVvbW3N/+xnP+N5nudPnTrF29nZ8d3d3cy906dP5//xj3/wPM/zv/3tb3krKyu+tbVV//HnnnuOj42N5Xme59vb23kLCwv+4sWLzOf4wQ9+wO/YsYPneZ7/7rvveAD8F198Mex/V1hYGP/666/rr/39/flXX32VuWfnzp38D3/4QyaWkJDASyQSvquri8/Ly+MB8JcuXdJ/PCcnhwfAfK5f/OIX/M6dOwfN5W9/+xs/c+ZMXq1WD/jxgXJ79913eQB8enq6Pnb9+nUeAH/hwgV9rL6+nre0tOQPHDigf87e3p7Py8vj/fz8+KeeeorX6XQ8z4/sz3ggS5cu5Xft2jXo9e1iY2P5devW8TzP80899RS/YsUK/esPZ7CvRUIIIYSQyTYhx5QPxXB2cFJSEnQ6Hb73ve9BpVIBAFJTU9He3t7vRMauri4UFBTorwMCAmBra6u/9vT01K/6Xrt2Dd3d3Vi9ejXzOdRqNebMmcPE5s+fz1x3dHTgd7/7HY4cOYLKykpoNBp0dXXpV6oHk5qaihs3bjAtHTzPQ6fToaioCNevX4dMJmNeLyQkpN90jeFaGu69917s2bMH06ZNwx133IH169dj06ZNkMmG/r9PoVAgMjJSf52TkwOZTIbY2Fh9zNnZGcHBwcjJydHHurq6sHjxYuzYsQN79+7Vx0fzZzxWPM/rv2YefvhhrF69GsHBwbjjjjuwceNGrFmzZkJehxBCCCFkIk1aUR0UFASO45Cbm8vEp02bBqDvWGkA0Ol08PT0xJkzZ/p9ntsLULlcznyM4zj95rtb/z569Ci8vb2Z+5RKJXNt2I7y3HPP4dixY/jrX/+KoKAgWFpaYuvWrVCr1UP+N+p0OvzoRz/S9zffzs/PD3l5efo8x8PX1xd5eXk4ceIETp48iccffxx/+ctfcPbs2X5/JreztLRkXpvn+QHvu72QBXr/vFatWoWjR4/iueeeg4+PD4DR/RmPhVarRX5+PqKjowEAc+fORVFREb755hucPHkS27Ztw6pVq8bUw00IIYQQMpkmrah2dnbG6tWr8cYbb+Cpp54atK8a6C2eqqurIZPJxtwze2szXmlpKZYuXTqqZxMSEvDwww/j7rvvBgC0t7ejuLiYuUehUECr1fbLOzs7G0FBQQN+3tDQUGg0GqSkpCAmJgYAkJeXh+bm5lHlB/QWyHfeeSfuvPNOPPHEEwgJCUFmZibmzp07YG4DCQsLg0ajweXLl7Fw4UIAvb3v169fR2hoqP4+iUSCffv24f7778eKFStw5swZeHl5jevPeCTef/99NDU14Z577tHH7OzscN999+G+++7D1q1bcccdd6CxsRFOTk4T/vqEEEIIIWM1qe0fb775JhYtWoT58+fjhRdeQGRkJCQSCZKTk5Gbm4t58+YBAFatWoW4uDjcdddd+NOf/oTg4GBUVlbi66+/xl133dWvXWMgtra2+OlPf4pnnnkGOp0OixcvRmtrKy5evAgbGxs89NBDgz4bFBSEQ4cOYdOmTeA4Dr/5zW/6jZ8LCAjAuXPnsH37diiVSri4uODnP/85FixYgCeeeAKPPfYYrK2tkZOTgxMnTuD111/Xty089thjeOeddyCTybB7925mlR4A/vd//xcVFRX44IMPBszvvffeg1arRWxsLKysrLBv3z5YWlrC399/0NwGMmPGDGzevBmPPfYY/vGPf8DW1ha/+MUv4O3tjc2bNzP3SqVS/Pe//8WOHTv0hbWHh8eY/4wNdXZ2orq6GhqNBhUVFTh06BBeffVV/OQnP8Hy5csBAK+++io8PT0xe/ZsSCQSfPrpp/Dw8KDDaQghhBBifMbblD3c5rDKykr+ySef5AMDA3m5XM7b2NjwMTEx/F/+8he+o6NDf19rayv/1FNP8V5eXrxcLud9fX35733ve3xpaSnP870bFaOiopjP/eqrr/L+/v76a51Ox+/du5cPDg7m5XI57+rqyq9du5Y/e/Ysz/N9GxWbmpqYz1NUVMQvX76ct7S05H19ffk33nij32a6xMREPjIyklcqlfztf2xJSUn86tWreRsbG97a2pqPjIzk//CHP+g/XlVVxW/YsIFXKpW8n58f/8EHH/TbWPjQQw/xS5cuHfTP+PPPP+djY2N5Ozs73traml+wYAF/8uTJIXO7teHQUGNjI79z507e3t6et7S05NeuXctfv35d/3HD53p6evgtW7bwoaGhfE1NzbB/xgMZaKMiAB4Ar1AoeE9PT37jxo39NrW+8847/OzZs3lra2vezs6OX7lyJX/lypVBX4c2KhJCCCFEKBzPD9JoO0Ld3d0oKipCYGAgLCwsJqDMJ2Rs6GuREEIIIUKZ9GPKCSGEEEIIETsqqgkhhBBCCBknKqoJIYQQQggZJyqqCSGEEEIIGScqqgkhhBBCCBmnST+mnBBCCCGEjI1Wq0VCQgKqqqrg6emJ+Ph4SKVSodMiA6CimhBCCCHECB06dAi7du1CeXm5Pubj44O9e/diy5YtAmZGBkLtH4QQQgghRubQoUPYunUrU1ADQEVFBbZu3YpDhw4JlBkZDBXVhBBCCCFGRKvVYteuXRjofL5bsd27d0Or1U51amQIVFSLzJtvvqk/UXDevHlISEgQOiVCCCGEjEJCQkK/Ferb8TyPsrIy+hlvZKioFpH9+/dj9+7d+NWvfoW0tDTEx8dj3bp1KC0tFTo1QgghhIxQVVXVhN5HpgYV1SLy97//HT/4wQ/w6KOPIjQ0FHv27IGvry/eeustoVMjhBBCyAh5enpO6H1katD0jxFqbe6c0tezc7Aa1f1qtRqpqan4xS9+wcTXrFmDixcvTmRqhBBCCJlE8fHx8PHxQUVFOQZoqwbHcfDx8UF8fPzUJ0cGRUX1CD193z+n9PXeO7ZrVPfX19dDq9XC3d2dibu7u6O6unoiUyOEEELIJJJKpdi7dy+2br0HHIDb62qO4wAAe/bsoXnVRobaP0Tm1l+2W3ie7xcjhBBCiHHbsmUL9v35KXjYsnEfHx8cPHiQ5lQbIVqpFgkXFxdIpdJ+q9K1tbX9Vq8JIYQQYvw2L43EwqdkSCrlUdsOeE8Px+Y/XaEVaiNFK9UioVAoMG/ePJw4cYKJnzhxAgsXLhQoK0IIIYSMFa/phlTCIS5Ags0REiwK96CC2ojRSvUIvbb/MaFTGNazzz6LnTt3Yv78+YiLi8M777yD0tJS/PjHPxY6NUIIIYSMEt/TxVxzMguBMiEjQUX1CI12GocQ7rvvPjQ0NODFF19EVVUVIiIi8PXXX8Pf31/o1AghhBAySrymm7nmZEqBMiEjQUW1yDz++ON4/PHHhU6DEEIIIePUv6imlWpjRj3VhBBCCCFGiNeomGsqqo0bFdWEEEIIIUaIVqpNCxXVhBBCCCFGiIpq00JFNSGEEEKIEaKNiqaFimpCCCGEECOkaSxkriUW9gJlQkaCimpCCCGEECOjU3dCXZXOxBTe84RJhowIjdQjhJg9rVaLhIQEVFVVwdPTE/Hx8XRqGSFEUOrKVECn6QtwEii8o4VLiAyLimpCiFk7dOgQdu3ahfLycn3Mx8cHe/fuxZYtWwTMjBBizlSlicy13CMSEqWNQNmQkaD2D0KI2Tp06BC2bt3KFNQAUFFRga1bt+LQoUMCZUYIMXfqskvMtdJ3gUCZkJGiopoQYpa0Wi127doFnuf7fexWbPfu3dBqtVOdGiHEzPE8D1WpQVHtR0W1saOiWkTOnTuHTZs2wcvLCxzH4YsvvhA6JUKMVkJCQr8V6tvxPI+ysjIkJCRMYVaEEAJoGm9A11nPxJR+cQJlQ0aKimoR6ejoQFRUFN544w2hUyHE6FVVVU3ofYQQMlEM+6klNh6QOgQIkwwZMdqoKCLr1q3DunXrhE6DEJPg6ek5ofcRQshEUZddZq6VvrHgOE6gbMhIUVE9Qg1tXVP6es62llP6eoSYm/j4ePj4+KCiomLAvmqO4+Dj44P4+HgBsiOEmDPDlWpq/TANVFSP0Jyfvzelr1f65k+m9PUIMTdSqRR79+7F1q1b+32MQ++K0J49e2heNSFkSum6W9BTm83EqKg2DdRTTQgxW1u2bMHBgwdha2HLxD3cPXDw4EGaU00ImXKq8iTg9nfPpAooPOcIlxAZMVqpJoSYtS1btuDyyiQUlN9Ah7oD1gprvPLeK5gxe4bQqRFCzJDaYJSewmsOOLmFQNmQ0aCimhBCdICPo6/+UiaXC5gMIcScqfod+kKtH6aCiuoRSvvTw0KnMKz29nbcuHFDf11UVIT09HQ4OTnBz89PwMwIMW46nY65lkholz0hZOrxOi1UhpM/6NAXk0FF9QiZwjSOlJQULF++XH/97LPPAgAeeughvPfeewJlRYjx02kNimopbTchhEy9ntpr4FWtTExBx5ObDCqqRWTZsmUDjgYjhAyt/0o1FdWEkKlnOJ9a6uAPmZ2XQNmQ0aKfHIQQs8bzPHgd+8sorVQTQoSgKjOYT02r1CaFfnIQQsya4So1QEU1IUQYdOiLaaOfHIQQs8Zr+7dMUVFNCJlq2o46aBpuMDEqqk0L/eQghJg1rVbbL0Y91YSQqWY49YOTW0HuPkugbMhY0E8OQohZM+ynBmilmhAy9dQGrR8Kn2hwUponYUroJwchxKzRSjUhxBj0P/SFNimaGvoViBBi1milmoiBVqtFQkICqqqq4Onpifj4eEilUqHTIiPEa3ugrkhhYtRPbXqoqCaEmDVaqSam7tChQ9i1axfKy8v1MR8fH+zduxdbtmwRMDMyUurqq+B7upiYwjdWoGzIWNFPDkKIWaOVamLKDh06hK1btzIFNQBUVFRg69atOHTokECZkdEw7KeWucyE1MpZoGzIWNFPDkKIWdNqaU41MU1arRa7du0a8CTdW7Hdu3cP+G4MMS40n1oc6CeHSLzyyiuIjo6Gra0t3NzccNdddyEvL0/otAgxejwV1cREJSQk9Fuhvh3P8ygrK0NCQsIUZkXGov8mRSqqTRH95BCJs2fP4oknnsClS5dw4sQJaDQarFmzBh0dHUKnRohRG2ilmgMnQCaEjE5VVdWE3keEoWkph7aljIlRP7Vpoo2KI9TU3T2lr+doYTGq+7/99lvm+t1334WbmxtSU1OxZMmSiUyNEFGxtOn/d+1Gxg2ERIcIkA0hI+fp6Tmh9xFhqA1WqTkLe8hdQwXKhowHFdUjtP7zqd3skbjj/nE939LSAgBwcnKaiHQIES07Jzv4zPBBeX7f2+jJx1OoqCZGLz4+Hj4+PqioqBiwr5rjOPj4+CA+Pl6A7MhIqUr7z6fmaAKRSaL/10SI53k8++yzWLx4MSIiIoROhxCjF71mPnN9NeEqujun9t0pQkZLKpVi7969vRfcwC1Le/bsoXnVRo4OfREPKqpF6Mknn8TVq1fx8ccfC50KISZh7sq5zObEHlUPMs5mCJgRISOzZcsWHDx4EF5eXkxc4eyE3Xv20JxqI6fr6YK6Ko2JKf2oqDZV1P4hMk899RQOHz6Mc+fOwcfHR+h0CDEJto62CI0NRfbFbH0s+XgKYtfRZiFi/LZs2YLNmzfjkbfexMW8PMgdHGAXEoIaR0fwPA9ukFVsIjx15RVA29MX4CRQeEcLlxAZFyqqR+jru437t32e5/HUU0/h888/x5kzZxAYGCh0SoSYlOg185mi+kb6DTRWN8LJg/YlEOMnlUrx1NZ7cf270/pYYUsLrjU2INzZRcDMyFAMD32Ru0dAYmEnUDZkvKioHqHRTuOYak888QQ++ugjfPnll7C1tUV1dTUAwN7eHpaWlgJnR4jxi4iLgKWNJbra+44KTjmRgjU71wiYFSEjN9fdHV7W1qi8bZTqkcJCKqqNWL9+ajr0xaRRT7VIvPXWW2hpacGyZcvg6emp/2f//v1Cp0aISZApZJizYg4TSz6eMuBUBUKMkYTjsGHaNCZ2oqQE3RqNQBmRofA8P8DkD2o5M2VUVIsEz/MD/vPwww8LnRohJiN6DdvLWFdeh5KcEoGyIWT0NgROY44u6ujpwemyUsHyIYPTNBVC11HLxBS0Um3SqKgmhJCbAsL84erjysSSjiULlA0ho+dubY1Yg8NejhQWCpQNGYphP7XE2g0yx2mD3E1MARXVhBByE8dx/WZWp51Og0ZNb58T07Fx2nTmOq22FmVtbQJlQwajKrvMXCt9Y2lSi4mjopoQQm4zbzVbVHe1dyE7MXuQuwkxPvHe3rBXKJnYkcICgbIhg1EZrFTTJkXTR0U1IYTcxtnDCUGzg5hY0nFqASGmQyGV4o7AACb2dVERNDqdMAmRfnTdreipyWJi1E9t+qioJoQQA4YtIDmXc9DWRG+fE9OxyaAFpL6rC5erqgTKhhhSVyQD/G2/5EjlUHjNFS4hMiGoqCaEEANRS6IgV8r11zqtDldOpw3xBCHGZbqDA8KcnZnYV9QCYjQMR+kpPGdDIqczJUwdFdWEEGLAwtoCkfGRTCyZpoAQE7PRYGb1+YoKNHZ1DXI3mUr9Dn3xpdYPMaCimhBCBmDYAlKeX46qInr7nJiO1X7+UEql+mstz+Ob4mLhEiIAAF6nG+AkxQUCZUMmEhXVhBAygJlzZ8LexZ6J0Wo1MSU2CgVW+PoxsSOFBXRKqMB66nLAd7cwMYUvFdViQEU1IYQMQCKVYN6qeUws5WQqdFqaoEBMx6bp7IbF4tZWZDXUC5QNAQC1wXxqqb0vZPY+AmVDJhIV1SLx1ltvITIyEnZ2drCzs0NcXBy++eYbodMixKQZtoC0NrTi+pXrAmVDyOjNdnWFj40NE/uqgE5YFJKqzGA+Na1SiwYV1SLh4+ODP/7xj0hJSUFKSgpWrFiBzZs3IzubDq0gZKw8Az3hM4NdQaIWEGJKOI7rd8LiqdISdPb0CJQRoUNfxEsmdAKmor6jZfibJpCLtf3wN91m06ZNzPUf/vAHvPXWW7h06RLCw8MnMjVCzEr02miU55frr6+ez0R3RzcsrC0EzIqQkVsfGIh3Mq9Cd7OXulOjwemy0n7FNpl82s4GaOrZd7vo0BfxoKJ6hIL2Pjqlr9f8y0/H/KxWq8Wnn36Kjo4OxMXRX1ZCxmPuijn48q0v9b3UPaoeZJzLQOy6WIEzI2RkXK2sEOfpiQuVlfrYVwWFVFQLwLCfmpNbQuEROcjdxNRQ+4eIZGZmwsbGBkqlEj/+8Y/x+eefIywsTOi0CDFpto62CI0NZWJJ1AJCTIxhAX21vg7FrVP7Dizp3/qh8J4PTiof5G5iaqioFpHg4GCkp6fj0qVL+MlPfoKHHnoI165dEzotQkxezJpo5rogowAN1Y0CZUPI6C329oajkm1ZOkIbFqdc/0NfaJOimFBRLSIKhQJBQUGYP38+XnnlFURFRWHv3r1Cp0WIyQuPC4elDXuEcOqJFIGyIWT0ZBIJ1gUGMrFvioug0dGIyKnCazVQl7PvclE/tbhQT/UI3dj1L6FTGDWe56FSqYROgxCTJ1PIMGfFHFw8fFEfSz6egtUPrAbHcQJmRsjIbZo2DR/l5uivG7u7cbGyEkt8aEbyVOipyQTf08nElL60N0NMqKgeodFO45hqv/zlL7Fu3Tr4+vqira0Nn3zyCc6cOYNvv/1W6NQIEYWYtdFMUV1XXofiayUIDA8QLilCRiHA3h4RLi7Iqu87/OWrwgIqqqeIYT+1zDkIUmtXgbIhk4HaP0SipqYGO3fuRHBwMFauXInLly/j22+/xerVq4VOjRBR8A/1h6sP+wMw+ThtWCSmZZPBhsXEykrUd3UJlI15ofnU4kdFtUj8+9//RnFxMVQqFWpra3Hy5EkqqAmZQBzHIXotu2Ex7XQaetR0iAYxHSv9/GAp63uTWsvz+KaoSMCMzEf/TYpUVIsNFdWEEDJC81fNY6672ruQnUinlhLTYS2XY6WfHxM7UlgA/ubBMGRyaForoW0uYWIK6qcWHSqqCSFkhJw8nBA0O4iJJR+nKSDEtBjOrC5ta0NGXZ1A2ZgHtcEqNae0g9yNzpEQGyqqCSFkFAxbQHIu56CtqU2gbAgZvUgXF/jZ2jGxrwoLBMrGPKhKDVs/YsFJpAJlQyYLFdWEEDIKUUsiIVf2nYCm0+pw5dQVATMiZHQ4jsOm6dOY2OnSUnT00P6AyaIqM9ikSIe+iBIV1YQQMgoWVhaIjI9kYtQCQkzN+oBASG+bsd6t1eJkSckQT5Cx4nu6oa5MY2IKPyqqxYiKakIIGaUYgxaQ8vxyVBVVCZQNIaPnZGmJRV7eTIxaQCaHuioN0Kr7AhwHpU+McAmRSUNFNSGEjNKMOTNg78IeCJV8jGZWE9Oy0aAFJLuhAYUtzcIkI2KG86nlbuGQWBj3gXJkbKioJoSQUZJIJZhnMF4v5WQqdFqdQBkRMnpxnl5wtrBgYkcKCgXKRrz6zaemQ19Ei4pqQggZg+g185nr1oZW5KVeFygbQkZPJpFgfSC7Wv1NcRF6tFqBMhIfnuf7Tf6g+dTiRUU1IYSMgWegJ3xn+jCxFDq2nJiYjdPYorpZpcL5ygqBshEfbXMxdO3VTIxWqsWLimqReuWVV8BxHHbv3i10KoSI1vw17IbFq+cz0d3RLVA2hIyen50dZru6MrEjhdQCMlEM+6klVi6QOQUNcjcxdVRUi1BycjLeeecdREZGDn8zIWTM5q2cC4m079toj6oH6WczBMyIkNEzPGHxUlUVajs7BcpGXFRll5lrpd8CcLeNMiTiQkX1CLWrmqf0nzHn2d6O733ve/jnP/8JR0fHifsDIIT0Y+Ngg7BY9qjhZGoBISZmhZ8frGQy/bWO5/F1Ea1WTwTDlWoFHfoiarLhbyEA8MI3O6b09f561zdjeu6JJ57Ahg0bsGrVKvz+97+f4KwIIYai18xH1sUs/XVBRgEaqhrg7OksYFaEjJylTIZV/v44XNA3p/pYcTEeDo8QMCvTp1O1o6f6KhOjfmpxo5VqEfnkk09w5coVvPLKK0KnQojZCI8Lh5WtFRNLOZEqUDaEjI3hFJDi1lY0ddP+gPFQVyQD/G1jNiUyKLzmDf4AMXlUVItEWVkZdu3ahQ8//BAWBnNHCSGTR6aQYc7yOUws+XgyeJ4XKCNCRi/c2RkWUikTy6yvFygbceg3Ss9zNiQKq0HuJmJARbVIpKamora2FvPmzYNMJoNMJsPZs2fx2muvQSaTQUtzRwmZNNFr2ZnV9RX1KM4uFiYZQsZAJpEg3MWFiWXU1QmUjTgYHvpC/dTiRz3VI/TCuo+FTmFIK1euRGZmJhP7/ve/j5CQEPz85z+H1GAFghAycfxD/eHq64q6sr4iJPl4MgIjAgXMipDRiXRxRWpNjf76aj0V1WPF8zzU5eymZSUd+iJ6VFSPkI3SQegUhmRra4uICHZTibW1NZydnfvFCSETi+M4RK+Jxtf//lofS/suHXc/eTfkCrmAmREycpGu7Ep1XmMjVFotlLQoM2ra1nLoOtn2GaVP9CB3E7Gg9g9CCJkA81exG5C62ruQfTFboGwIGb1ZLq6Q3DZDuUenQ25jg4AZmS51ZRpzzVnYQ+pI71yJHRXVInbmzBns2bNH6DQIMQtOHk6YMYc9KY1mVhNTYi2XY7q9PROjvuqxMSyqFZ5z6NAXM0BFNSGETBDDY8tzLueiralNoGwIGb1ZBkeWX6WiekzUVYZF9WxhEiFTiopqYpJ4nkdbWxsaGhrQ1tZG48uIUYhaEgmFhUJ/rdPpkHrqioAZETI6US5sUZ1WW4sujUagbExXT2U6c63wmi1IHmRqUVFNTE5TUxMyMzORl5eHoqIi5OXlITMzEy0tLUKnRsychZUFIuNnMbEUagEhJmSuuzvTV92p0eBUaYmAGZkebXsNtG2VTEzhOWeQu4mYUFFNTEpTUxMKCgqgVquZuFqtRllZGTo7OwXKjJBe0QYtIOX5FagsrBzkbkKMi4ulJRZ4ejKxL287vpwMT12VzlxzcivIXGYKkwyZUlRUE5PB8zzKysqGvKexsZEOuiGCmjFnBuxd2M1eycdTBMqGkNG7c/p05jqrvh6FLc3CJGOC1BVsy5fcMwqchMYSmgMqqonJaG9v77dCbUir1SI1NXWKMiKkP4lUgvmr2fF6qSdS6Jc9YjIWeXnD2cKCiX15g1arR0pVcp65ptYP80FFNTEZwxXUt9TW1k5yJoQMbf5q9tjy1sY2XE/NFygbQkZHJpFgw7RpTOzb4iKo6BfDYfEaNVQlF5iYRUC8QNmQqUZFNTEZCoVi+JsAuLm5TXImhAzNM9ATvjN9mFjyMdqwSEzHpmlsC0irWo0zw7TfEUBdkQK+h93bowxcKlA2ZKpRUU1Mho2NzbCFtVQqxbx584a8h5CpEL2W3bCYeT4T3R3dAmVDyOj42Npivrs7EztccEOgbExHd9EZ5lruPgtSa5eBbyaiQ0U1MRkcx8HX13fIeyysbSGV0oYQIry5K+ZCIu37Ftuj7kH62QwBMyJkdDZPZ08IvVJbi9LWVoGyMQ3dhWeYa4tpywTJgwiDimqReOGFF8BxHPOPh4eH0GlNOEdHR0yfPr3/irVECqm1I1S8BMW1NK+aCM/GwQZhsWFMjFpAiClZ4uMDe4WSiR2m8XqD4nu6oSpLZGLU+mFeqKgWkfDwcFRVVen/yczMFDqlSeHo6IhZs2YhODgYPn7+kDu4Q+HsDYnCAjwP7P06hU5YJEbBsAWk4GoBGqoaBMqGkNFRSKVYHxjIxL4uKkQPbVgckKr8MqBR9QU4CSwClgiXEJlyMqETMBU6Vd2Uvp5E6Tr8TQZkMpkoV6cHwnEcbG1tYWtrC17ejrrWvo0h6SW1OJR0HffEBguYISFA+IIwWNlaobOt7+sz5UQq1j64RsCsCBm5O4Om4+O8XP11k0qFhIoKrPDzEzAr42TY+qHwnA2JpYMguRBhUFE9Qs1Hp/YbiNOWrlE/k5+fDy8vLyiVSsTGxuLll1/GNIOxSGLkZm+F5k4V1Joefez3n13Eygh/OFhbDPEkIZNLppBh7oo5OP9l34it5OPJWLNzNbjbjoImxFgF2Nljtqsr0uv6FpYOF9ygonoAqqKzzLUycJkgeRDhUPuHSMTGxuKDDz7AsWPH8M9//hPV1dVYuHAhGhrE/1azVCKBt6MNE2to78Yfv7wsUEaE9JlvcGx5fUU9irOLhUmGkDG402DDYlJ1Nara2wXKxjjpVO297R+3sZhG/dTmhopqkVi3bh3uuecezJo1C6tWrcLRo0cBAO+//77AmU0NOyslbCzZzYsfnb+GK0XVAmVESC//UD+4+rLtXMnHacMiMR3LfX1hK5frr3kAhwtpw+LtVCXnAW3fu6WQyKD0p0NfzA0V1SJlbW2NWbNmIT/ffE5xc7WzgsTgHfVffnwOGq1OmIQIQW//f4zBanXad+noUfcM8gQhxsVCJsPaAHbD4pHCQmh09L31lu7C75hrpW8sJEqbQe4mYkU91SPksKFU6BRGRaVSIScnB/Hx5vObskImha0lO/7pWnkD3juTiUdXRgmUFSG9x5Yf/ffX+uuu9i5kX8zG7GWzhUuKkFHYPH06DuZf11/Xd3UhsaoS8d4+QzxlProLTjHXymnLBcqECImK6hEayzSOqfTTn/4UmzZtgp+fH2pra/H73/8era2teOihh4RObUrZWMgxzc0eFS19J9f97UgyNsydDk9HWjUgwnB0d8SMOUHIT+s7kS75eDIV1cRkBDk6IszZGddu26dzuKCAimoA2o469FRfZWIW01YIlA0RErV/iER5eTl27NiB4OBgbNmyBQqFApcuXYK/v7/QqU0pjuOwe8N8Jtah6sELBy8M8gQhUyPaoAUk53Iu2hrbBMqGkNHbPH06c32xshK1nZ2D3G0+DFs/OIU1lD4xAmVDhERFtUh88sknqKyshFqtRkVFBT777DOEhYUN/6AIzfJzw/ZFoUzsm7RCnM4qESgjQoDIJZFQWPRtptXpdEg9fUXAjAgZnVV+/rCS9b3BreN5HC0sFDAj49CvnzpgCTiZYpC7iZhRUU1E6X83L4CTDTuj+jf7E9BFm8OIQCysLBAZP4uJ0bHlxJRYyeVYbfDu5+HCAujM/ATb7oLTzLUF9VObLSqqiSg52ljgV3fHMbGyhja8/g2tDBLhGB5bXnGjApUFlQJlQ8joGc6sru7oQFJ1lUDZCE/TVARtUxETs5hO/dTmiopqIlpbFwQjJsiTif3jZDryq5oEyoiYuxmzZ8DexZ6JJZ9IESgbQkYv1MkJMxwcmNjhAvOdWd1dwLZ+SKxdIXeLECgbIjQqqolocRyHP2xfApmk78u8R6vDrz85B97M364kwpBIJZi/eh4TSz2RAq1WK1BGhIwOx3H9VqvPlZejsatLoIyEZThKz2LacnASKq3MFf0/T0Qt2MsJj61iZ1Qn5lfiUNL1QZ4gZHIZTgFpbWzD9VT6eiSmY21AAJRSqf5ay/P4uqhoiCfEidfp0F10honRKD3zRkU1Eb1d6+bBx8mWif3lcBJUPbQ6SKaeR4AHfIN9mVjyMWoBIabDVqHACl8/Jna4sMDs3gHsqcmErqOOiVE/tXmjopqInpVSjt9tW8zEKpva8dH5awJlRMxd9Bp2lnrm+Ux0tZvn2+fENG0OYmdWl7W1Ia22VqBshGE4Sk/mOA0yxwBhkiFGgYpqYhZWzfJHrMGmxTeOpaJTRSP2yNSbu3IuJNLbev3VPcg4myFgRoSMTqSLKwLs7JjYlwU3BrlbnPqN0qNVarNHRTUxCxzH4bk7Y5lYXWsX3j+bJVBGxJzZ2NsgbAF7OFPycWoBIaajd8Miu1p9pqwMLSqVQBlNLV6jhqokgYkpaT612aOimpiNmCBPLAtje1nfOpGG1i7z+CFAjIvhhsWCqwVoqGoQKBtCRm9dYCDkt026UOt0+LbYPDYsqsqTwKs7mBgd+kKoqBaRiooKPPDAA3B2doaVlRVmz56N1NRUodMyKv+zKYa5bu5Q4V+nrgqUDTFn4QvCYGVnxcRotZqYEgelBZb6+DCxwwXmsWGxu5Bt/ZB7REFq7SJQNsRYUFEtEk1NTVi0aBHkcjm++eYbXLt2DX/729/gYDCk39xF+bvhjqhAJvav0xloau8WKCNirmQKGeYun8PEUo6nmEVBQsTDcGZ1YUsLMuvrBcpm6qj69VOvFCgTYkxkQidgKrQGY3Mmm9TadVT3/+lPf4Kvry/effddfSwgIGCCsxKH/9kUjWNXi3Crdmnv7sFbJ9LwS4NjzQmZbPPXROP8lxf01/WV9SjKKsK0WdMEzIqQkZvn7g5vGxtUtLfrY4cLChDpOrqfYaZEp2qDqjyJiVlMp9YPQkX1iFX80XtKX8/vJfWo7j98+DDWrl2Le++9F2fPnoW3tzcef/xxPPbYY5OUoekK9nLG5vkz8EVyvj723pksPLoiCm72VkM8ScjE8g/1g5uvG2rL+kaRJR9PoaKamAwJx2HTtOl4+2rv9Bpep8PBb76Gd34+An19ER8fD+ltB8WIgao4AdBp+gJSOZT+iwd/gJgNav8QicLCQrz11luYMWMGjh07hh//+Md4+umn8cEHHwidmlF6dkM0pBJOf93do8Ebx64ImBExRxzH9ZtZnfZdGnrUNOqRmI4N06ZBynFoTEpG2tO7kPHiS3jkwQexfPlyBAQE4NChQ0KnOKEM51MrfRdAorAWKBtiTKioFgmdToe5c+fi5Zdfxpw5c/CjH/0Ijz32GN566y2hUzNKAW72uDcuhIl9dD4bFY1tAmVEzNX81fPBcbf9gtfRjawLNOqRmA4XS0u43ijA9T17oG5sZD5WUVGBrVu3iqqw7i44xVzT0eTkFiqqRcLT0xNhYezc29DQUJSWlgqUkfHbtW4eFLLbxkFpdNj7DU1LIVPL0d0RQbPZzV40BYSYEq1Wi4tvvjngx25tvN29eze0Wu1UpjUptO016Klhf+mlQ1/ILdRTPULev6gQOoUhLVq0CHl5eUzs+vXr8Pf3Fygj4+ftZIv7F4fjvTOZ+tinibn4yerZCHRzEC4xYnai18xHflpfj39uUi7aGttg62QrYFaEjExCQgJqq6oG/TjP8ygrK0NCQgKWLVs2dYlNAsPWD05pC4X3/EHuJuaGVqpHSGrtOqX/jNYzzzyDS5cu4eWXX8aNGzfw0Ucf4Z133sETTzwxCX8a4vHk2rmwkPf9bqnV8Xj1KK0SkqkVuSQSCguF/lqn0yH1FL1rQkxD1RAF9VjuM2b9+qkD4sFJ5QJlQ4wNFdUiER0djc8//xwff/wxIiIi8NJLL2HPnj343ve+J3RqRs3N3goPL4tgYl+m5COvkk62I1PHwsoCkfGRTIxaQIipUEhtRnSfp6fnJGcyuXieRzfNpyZDoKJaRDZu3IjMzEx0d3cjJyeHxumN0E9Wz4HtbauEPA/87atkATMi5ih6LfsWcsWNClQWVAqUDSEj09rciYtH6mCldBjyPqWzM6xnzpyapCaJpqkQ2uYSJkZHk5PbUVFNzJ6jjQUeXcmuEn6bUYSMktpBniBk4s2YPQP2LvZMLPk4/XJHjJdapcFrLxxBQ00bYkLuHvJe/5078T8J53DahDfPG65SS2zcIXcLFygbYoyoqCYEwKMrouBgrWRif/sqaZC7CZl4EqkE8w1mVqeeTBXFxAQiPjodj3/+5Thu5PT2Sfu7R2FZ1PdhZ+3E3KdwdsLM3bvhFBONHp0Ov75wHgevXxci5XHrdzT5tOXMOExCqKgmBICtpQI/WT2HiZ25VoakG6a/sYaYjujVbFHd2tiG66mmWYAQcfvsvYtITshnYnMiFqGwsAjfffcdPvroIxw7eRK7D34Gp5ho/T08gL+lpuAfVzP04/ZMAa/TobvoDBOjfmpiiIpqQm56eFkEXO0smdhfDl82qW/8xLR5BHjAN9iXiSUdoxYQYlzOfJ2Fo/vZjbQWVgo889JmOLvZYdmyZdixYwfWrFyJl5cswd1BQf0+x3vZ2fhjchI0Ot1UpT0uPdUZ0HWyG9ipn5oYoqKakJssFXI8uXYeE7t8owoJueUCZUTMUczaaOY663wWutq7BMqGEFZWagk+eN2gt1jC4clfr4dvoEu/+6USCZ6bH41HZ83q97HDBQX45fkEdGs0k5bvROkuZP+bZU5BkDn4CZQNMVZUVBNym/sXh8HbiR0P9ZfDSbRaTabMnBVzIJVJ9dc96h6kn80QMCNCepUX1+ON338NnY79fvjgUysQMW/wg8Y4jsMPImbh59ExkBj0ICdUVODp706jRaWalJwnSncBO5+aTlEkA6GimpDbKOVS7FrH9rVmlNTixNViYRIiZsfG3gZhC8KYGE0BIUJrbujA33/9Jbo71Ux8/bZ5WLY+YpCnWHcFBeHlxYuhkEqZeGZ9PX5y8iRqOjomLN+JxGtUUJUkMDFq/SADoaKaEAP3LJiJAFd2tNlfv0rqtzpDyGSJNpgCUni1EPWV9QJlQ8ydqrsHe357GI117Uw8ZskMbP3+olF9rqU+vnht+XLYytlTCItaW/CD48eQVW98X+eqssvge25rweI4KKctEywfYryoqCbEgFwqxbMb2aImt7IRR67cECgjYm7CYsNgZWfFxFJO0AmLZOrptDq8/cq3KM5n5/YHhXri0Z+ugUQy+pFyUa5ueGvVarhashvDG7q78fipkzhaWDiunCdad8Ep5lruORtSK2eBsiHGjIpqQgZw57wZCPZi563+/UgyNFrT2KlOTJtMIcPcFXOZWPLxFOrtJ1Pu43cSkHaJLXJdPe3x9AsboVDKxvx5pzs44J3Va+BvZ8fEe3Q6/P7yJbx25YrRTAbpLjTop55G/dRkYFRUi0hAQAA4juv3zxNPPCF0aiZHIuHw040xTKywtgWHkmhmMJkahi0gDZUNuJFRIFA2xByd+DIdJ75IZ2LWNko8+9Jm2DlYDfzQKHhYW+Od1WsQ4+HR72Mf5+Xip2fPok2tHuDJqaPrboW6gt3TQJsUyWCoqBaR5ORkVFVV6f85ceIEAODee+8VODPTtCYqAJF+rkxsz9EUqHrohDsy+fxC/ODu787ELh1JFCgbYm7SLhXio7fPMTGpTIKnfrsRnr6OE/Y6dgoF/rZ0Ge4LDu73scvVVXj0+DGUtLZO2OuNVnfxOUB32/d8qQJKv9H1kRPzQUX1CPW0NE/pP2Ph6uoKDw8P/T9HjhzB9OnTsXTp0on9wzATHMfhuTvZ1eryxjbsv5gjUEbEnHAchwXrFzCxjHNX0dFqnBMSiHgU59firZe/AW+wOfsHz65GSKTPhL+eTCLB7rnz8MuYWMgkbFlS2taGR48fQ2Jl5YS/7kioDFo/lH5xkCjGv0pPxGnsDVFm5urDm6f09eZ9fnZcz6vVanz44Yd49tlnwXGj30hCei0J9UVMkCdzXPlr36bi3rhgWCrkQzxJyPhFr52PI/86Au3Nd0c0PRqkHE/B0q30izKZHA21bdjz/GGoVeyBLHftjMXClSGT+tqbpk+Hv50d/vd8Ahq7u/Xx9p4e/PTcWTwRNRs7QkKm9Gea4SZF6qcmQ6GVapH64osv0NzcjIcffljoVEwax3F4bhO7Wl3b0okPzmYLlBExJzb2NohcHMnELn19mTYskknR1aHCq89/ieZG9t2QhStDsPl7sVOSQ6SrK/6zZi2CHdkWEx3P4/X0NLx4KREq7dS04GnbqtFTe42JUT81GQoV1SL173//G+vWrYOXl5fQqZi82BleWBLqy8TePJ6G9m5hN9AQ8xC3gW0BqSqqQklOiUDZELHSaLT4vz98g/KiBiYeHOmN7+9eOaWrw+7W1nh71Wqs8ut/DPi3xcV4/NRJ1HV2TnoehkeTc0o7KLzmTfrrEtNFRbUIlZSU4OTJk3j00UeFTkU0DFermzq68e/TVwXKhpiToDlBcPZiZ+ImHrkkUDZEjHiex4f/dwZZqewvax4+jnj6+Y2QK6a+U9RCJsOLCxfhR5FR/T52raEBjxw/hmsNDQM8OXH6jdILXAJOSl2zZHD01TFCke99KXQKI/buu+/Czc0NGzZsEDoV0YgKcMOayAAcv+248ndOZuChpRFwsLYQLjEiehKJBAvWL8DRfx3Vx9K+S8PdT9wFC/raIxPgm4NXcObrLCZma2+JZ3+/Gda2wn2NcRyHh8PDMd3eHi8kXkSnpq/Pu76rCz85eQL/GxOLOwIDJ/y1eZ5HdwG7Um0xfeWEvw4RF1qpHiG5vcOU/jNWOp0O7777Lh566CHIZPQ700T66aYY3P4OaFu3Gv84mS5YPsR8xNwRDcltUxHU3WqknroiYEZELJIT8nHgX+eZmEwuxa4XNsHN016grFjxPj7455o18LaxYeJqnQ6/u5SI/0tPg3aCD4rRNN6AtqWMiVlMWz6hr0HEh4pqkTl58iRKS0vxyCOPCJ2K6IR4O+POeUFM7D/fZaKudfJ7+4h5s3e2R/jCcCaWSDOryTjdyKnCO38+1i/+w5+tRVCYpwAZDW6avQP+vWYt5rm59/vYhzk5+FnCObRP4EExhqvUUltPyFxDJ+zzE3Giolpk1qxZA57nMXPmTKFTEaVnNkRDKulbru5Sa/B/x2jFkEy+uI1xzHV5fjnK8soGuZuQodVWtWDvb79Cj5qdpLHtB4sQs2SGQFkNzV6pxJ7ly7F1Rv+fbxcrK/HoieMoa5uYg2IMi2rltOU0npYMi4pqQkZhmrsDtsayJ399mJCN4roWgTIi5iJkfjAc3dkxYxdptZqMQUdbN179zZdoa+li4kvXRWDdvcY93UImkeB/5s/HL6Jj+h0UU9Laih8cO4bLVVWDPD0yvE4LVdEZJkaj9MhIUFFNyCjtWj8fcult/a0aHV75nIobMrkkUkm/ExavnLqC7s7uQZ4gpD9Njxavv3gUVWVNTDxinh92PrnMZFZjNwcF4fXlK+CgVDLxtp4ePHv2DD7JzR3zPPeeqgzoutg/Hzr0hYwEFdWEjJKPsy0eXjaLiX2TXoRL14U5RpeYj9h1McyGRVWXCldowyIZIZ7n8e6eU8i9Ws7EfQKd8cSv1kMmkwqU2djMdnPDf9begRkODkxcx/PYm3YFf7h8GeoxHBRjeIqizGUmZPYTfzw7ER8qqgkZg6fXzYOjwTizFz+7MOE70Am5nYOrA8LiwpgYbVgkI3X4v0m4cDKHidk7WeGZF++EpbVykKeMm6e1Nf6xeg2W+/r2+9jRokI8cfoUGrq6BnhycP3mU9MqNRkhKqoJGQN7KyX+Z2M0E8sqq8dnl68LlBExFwsNNiyWXacNi2R4F0/l4vN97KFBCqUMz7x4J5zd7ATKamJYymT4/aLFeHTWrH4fy6qvxyPHjyG3sXFEn4vv6YaqhB0xSP3UZKSoqCZkjO5fHIYZnuzGsT99eRkd3T0CZUTMQUh0CBzcHJhY4lFarSaDy8uswL//foKJcRzwk1+uQ8CM/iPqTJGE4/CDiFl4ZXE8LA3OaKjt7MSPTp7AiZLiYT+PquwSeM1t+xQ4CSwCl05wtkSsqKgmZIxkUgmev2chE6tr7cRbJ9IEyoiYg4E2LKaevAJVl0qgjIgxqyprwmsvfAWthm1Nu//HSzFnwTSBspo8y3x98c6q1fCwtmbiaq0Wz1+8iLczMqAbYgOjYT+1wmsuJJaOg9xNCIuKakLGYWmYH5aH+zGxf5xMR0Vjm0AZEXOwYH0suNvmpau6VLhymn6ZI6zW5k78/TdfoqOd/YVr9V2zsfqu2cIkNQWCHB3xnzVrMdvVrd/H3r+WjZ8nnENHz8DvKPbvp6ZTFMnIUVFNyDj9estC5kAYVY8Wf/zi0hBPEDI+Dq4OCF/AnrB48auLAmVDjJFarcFrLxxBXRU7Q3/2gkDs+GG8QFlNHUcLC7y2fDnuDgrq97HzFRX48ckT/U5g1HU1Q12RwsQspq+c1DyJuFBRTcg4zfB0xM54tsD5MuUGUgurBcqImIO4jWwLSFleGcqu04ZFAuh0PP71l+O4kcMeguIf5IYf/+IOSKTm8aNfLpXiZ9ExeG5+NKQG87dvNDdjzxV2HGV38TmAv61NRqaEwo/dGEzIUMzjb5YZ0Gg0+PWvf43AwEBYWlpi2rRpePHFF6GjEW9T4pkN0bCzVDCxFw9egE43tsMHCBlOaEwoHFwdmFjiUXqHhACfvXcRSefymZiTqw2eefFOWBh8nzIHW2bMwGvLV8BewY4NPFpUiISKvpnd/Y4m91sEidxySnIk4kBFtUj86U9/wttvv4033ngDOTk5+POf/4y//OUveP3114VOzSw42lhg9/r5TCytuBaHU/MHeYKQ8ZFIJViwIZaJpZ5MpQ2LZu7sN1k4ut+ghcFKgWde2gwHZ+tBnhK/ue7u+OeaNbCWy5n4H5OS0KLq/TvTXcgW1dRPTUZLNvwtBAC6mtqn9PUsHW1GdX9iYiI2b96MDRs2AAACAgLw8ccfIyUlZZgnyUR5cGkE9iVko6i2r4fxlc8vYW1UICwV8iGeJGRsYtfF4tgHx8HffEdE1alC2uk0LNiwYJgniRhlpZbg/dfYwlAi4fDkr9fDN9BFoKyMh6+tLXbNmYuXky7rY43d3fhrSjJ+OysQmrpc5n7qpyajRUX1CP1nza+m9PWeSN47qvsXL16Mt99+G9evX8fMmTORkZGB8+fPY8+ePZOTIOlHIZPiV1vi8Ojb3+pjVc0deOdkBnYZrGITMhEc3RwRFhuK7MRr+tjFI4lUVJuh8uJ6/N/vv+7XcvbgUysQMc9foKyMz8Zp03CmvAwXKyv1sZOlpdjYnQrP2+7jLByg8Joz9QkSk0btHyLx85//HDt27EBISAjkcjnmzJmD3bt3Y8eOHUKnZlZWzwrAomBvJvbm8TRUN3cIlBERu4Wb2FnppbmlKM8vH+RuIkbNDR149TeH0dXJTrNYv20elq2PECgr48RxHP43Jha2ir7ecl6nw9HP3seXWTokFuug1fGwCFwKTiIVMFNiiqioFon9+/fjww8/xEcffYQrV67g/fffx1//+le8//77QqdmVjiOw/P3LILktp3mXWoNXv48EfwQBw4QMlYhMSH9NyweoQ2L5kLV3YM9vz2Mhlp2Nn50/Axs/f4igbIybi6WlvjpvN53DxuTkpH29C689FYanv5Ci+0farHodQ2Ol9KBL2T0qKgWieeeew6/+MUvsH37dsyaNQs7d+7EM888g1deeUXo1MxOqI8z7lsYwsS+SM7Hzz48gx6tVqCsiFhJpVLErmc3LKacTKENi2ZAp9Xh7Ve+RXF+LRMPCvXEY8+tgUTCDfIkWe3vD6/CQlzfswfqxkbmY9VtwM5f/guHDh0SKDtiqqineoQeOf4HoVMYUmdnJyQS9nckqVRKI/UE8tNNMfgq9Qbau/tO7dqfmIvKpna8/dha2JrhWCsyeRasi8XxfQYbFr9LxwKDYpuIyyf/TEDapUIm5uppj6df2AiFkn68D0Wn0+HSW28P+DEeAAdg9+7d2Lx5M6RSagMhI0N/60ZotNM4ptqmTZvwhz/8AX5+fggPD0daWhr+/ve/45FHHhE6NbPkameFP2xfgt3vn8LtXR8JueXY+vcv8N7j6+Fp5F9TxHQ4ujsiNCYU1y7dtmHxq4tUVIvYyS8zcPzzdCZmbaPEMy/eCTsHK2GSMiEJCQmorKgY9OM8z6OsrAwJCQlYtmzZ1CVGTBq1f4jE66+/jq1bt+Lxxx9HaGgofvrTn+JHP/oRXnrpJaFTM1t3x8zEO4/dAQs5+7trTkUDNv/lEK6V1wuUGRGjhZvYk99Kc0tRfmPwooGYrvRLhfjv22eZmFQmwVO/3QgvPyeBsjItVVVVw980ivsIAaioFg1bW1vs2bMHJSUl6OrqQkFBAX7/+99DoaA2AyGtnR2I/bvvhLONBROvbu7A1r9/gbPXSgXKjIhNaGwo7F3smdilI4kCZUMmS3F+Ld58+Rt9q88tjzyzCiGRPgJlZXo8PT2HvwlAnYze0CcjR0U1IZNsTqA7vvjZPZju7sDE27t78PCbX+OTCznCJEZERSqV9mv3SKETFkWlobYNe54/DLVKw8Q3PxCLRatCBcrKNMXHx8PHxwfcEHs5Fc5O2N+jxrHioqlLjJg0KqoJmQL+Lnb4/Kd3I3q6BxPX6nj87L9n8JfDl2nkHhm3BesXgLutSuju6Eb6mXThEiITpqtDhVef/xLNjezM+4UrQ3DXA9Q7P1pSqRR79+4F+N5NiQMJ2PkgdByH3yUm4lB+/pTmR0wTFdWETBEHawv89+lN2DQvqN/HXv/2Cna/dwqqHhq5R8aud8MiO87x4lfUAmLqtFod/u8P36C8qIGJB0d64/u7VzK/SJGR27JlC/75iD88bNm4vbsbZu7eDaeYaAC900D+kpKMD65lT32SxKRQUU3IFLKQy/D691fhJ2v6H3/7eXI+/nz4sgBZETGJ28huWCzJKUEFbVg0WTzPY98b3yErtYSJe/g44qnfbIRcQT2/Y6XtbMRqr0pceEqGTx6Q4rW7pDi2/03Ul1fg8Z0P9Lv/rYwMvJmeTu8qkkFRUU3IFJNIOPzvXQvw8o4lzMmLAPDB2Sw0d1IPLBm7sLiwfhsWE4/SCYum6puDV3Dm6ywmZmtviWdfuhM2dhaDPEVGQl3W+/dCKuEQFyDBXbOtsHrLDyCTyfD0nLl4dNasfs/sy7mGv6akQEeFNRkAFdWECOSB+HD85yfrIJf2/TVUabT4Ium6gFkRUyeVShG7zmDD4okUqLvVAmVExio5IR8H/nWeicnkUux6YRPcvByESUpEVKUXmWuFTzQ4We/ELI7j8IOIWdg9d26/5w7dyMeLiYnQ0OFqxAAV1YQIaEWEP9ZGBTKxjy/k0NuLZFwWrI/tt2ExjTYsmpQbOVV458/H+sV/+LO1CAob2Tg4MjRVKbvfQOkX1++e+4JD8KvY2H7vKh4rKcZvLlxAj5b2wZA+VFQTIrDti9hRWDkVDbhaWidQNkQMnDycEGKwYTGRZlabjNqqFuz97VfoUbMF272PLELMkhkCZSUuvEYNdXkyE1P6LRzw3o3TpuOlhYsgk7Al05nyMvzywnmoqbAmN1FRTYjAFgf7wMeJ3X5Os6vJeBluWCzOLkZlYaVA2ZCR6mjrxqu/+RJtLV1MfOm6CKzfNk+grMRHXZUOXtPNxBS+Cwa9f4WfH/6yZAmUUikTP19RgZ+dO4dujWaQJ4k5oaKaEIFJJBzuW8iuKn6Zko9OVY9AGRExCI8Lg52zHROj1WrjpunR4o2XjqKqrImJR8zzw84nl9HovAmkKr3AXMvdwiC1GvqI9wWeXvj7smWwNDhl8XJ1FX567iy6qLA2e1RUi0hbWxt2794Nf39/WFpaYuHChUhOTh7+QSK4exeEMD177d09OHKlQMCMiKkb6ITF5OO0YdFY8TyPd/ecQk5GORP3CXDG479aD5lMOsiTZCxUJewmxcFaPwzNdXPHq8uWw8qgsE6tqcGzZ75DRw8thpgzKqpF5NFHH8WJEyewb98+ZGZmYs2aNVi1ahUqKmhGrbHzcrLBsjBfJvYxtYCQcYqlExZNxuGPknDhJPt33t7JCs+8dCesrJUCZSVOPM/326SoGGCT4mCiXF3x2ooVsJXLmXh6XR12n/kO7Wr6xdVcUVE9Qu3N7VP6z2h1dXXhs88+w5///GcsWbIEQUFBeOGFFxAYGIi33nprEv5EyEQz3LCYWliN61WNAmVDxMDZwwnB0cFMjFpAjM/F07n4/AN2lrhCKcMzL94JZze7QZ4iY6VpLICuo5aJKf1HtlJ9S7izC15fsRJ2CgUTz6qvx9PfnUYrFdZmiY5iGqFf3/2bKX29Pd+9Oqr7NRoNtFotLCzYwwAsLS1x/vz5QZ4ixmTlLH+42lmirrVvg9L+i7n4zT2j+2ZPyO0WboxDblKu/roouxhVRVXwDKSxbMYgL7MC//n7SSbGccBP/ncdAma4C5SVuBnOp5bYuEPmOG3UnyfYyQn/t2Ilnv7uNJpUfYd25TQ24slTp/CP1av79V8TcaOVapGwtbVFXFwcXnrpJVRWVkKr1eLDDz/E5cuXUVVVJXR6ZATkUim2LmA3LH52OQ+qHhrXRMYuPC4cdgbTZS5+RavVxqCqrAmvvfAVNAZ/x+//8VLMiRt9kUdGZqD51GPdBBrk6Ij/W7kKzgYLWvnNTdiflzfmHIlpoqJaRPbt2wee5+Ht7Q2lUonXXnsN999/P6RS2uBiKrYbTAFpbO/GicxiYZIhoiCVSRG7nh0VRicsCq+1uROv/uZLdLSrmPiqzVFYfddsYZIyE6oSdvLHSDcpDibQ3h5vrlwFV0tLJp5QUT7IE0SsqKgWkenTp+Ps2bNob29HWVkZkpKS0NPTg8DAwOEfJkYh0M0BC2Z4MTGaWU3Gy/CExa72LqSfzRAwI/OmVmvw2u+OoLaqhYnPXhCI+3+0RKCszIO2sxGaulwmpvRfNO7P62dnh1/Fsr+85jY2oo16q80KNfuM0O8/f0noFEbM2toa1tbWaGpqwrFjx/DnP/9Z6JTIKGxfGIpL+X2HdCTklqGsoRW+zrRhiYyNs6czgucHIze5r5hIPJKImLXRAmZlnnQ6Hv/66wncuMa25fkHueHHv7gDEimtdU0mdRnb+sHJLaHwnD0hnzvK1RUKiQRqnQ4AoON5XKmtwVIf32GeJGJBRfUI2TjYCJ3CsI4dOwae5xEcHIwbN27gueeeQ3BwML7//e8LnRoZhfVzpuH5Awlo7epd4eB54EBiLv5nY4zAmRFTFrcxjimqi7KKaMOiAA69dxFJZ68zMSdXG+x+cRMsLBWDPEUmiuF8aoV3NDipfJC7R8dCJsMsV1ek1tToYynVVFSbE/qVWERaWlrwxBNPICQkBA8++CAWL16M48ePQy6fmG8YZGpYKGS4O2YmEztwMRfam6sfhIxFxML+GxZpvN7UOvtNFo7sT2FiFlYKPPPSZjg6G//CjRgMtElxIs1392CuU2qqJ/TzE+NGRbWIbNu2DQUFBVCpVKiqqsIbb7wBe3t7odMiY7B9ITuzuqq5A2evlQmUDREDqUyK2HUDnLCoop7PqZCVWoL3XzvNxCQSDk/8aj18A10Eysq88Bo11BXsLzWjnU89nGgPdgxicWsr6jo7J/Q1iPGiopoQIxTu64JIP1cmRhsWyXgt2MBupOpq70IGbVicdOXF9fi/338NnY5n4g8+tRyz5vsLlJX5UVelgdd0MzGl74JB7h6bEEcn2Bi8O3x7OwgRNyqqCTFShicsnswsQW0LrXiQsbu1YfF21AIyuZobOvDqbw6jq5N9R2D9vfOwbP0sgbIyT4aj9ORuYZBYOk7oa0glEsx1Y1erU6ioNhtUVBNipDbPnwFLRd9eYo1Oh88u02ECZHwWbmR7SAszezcskomn6u7B3hcOo6G2jYnPjw/C1kfGP8aNjI7hSYoTMUpvIPM9DIvqavA8P8jdREyoqCbESNlaKrBx7nQm9snFHPrmTMYlYlEEbB0NNiwevSRQNuKl0+rw9h+/RdH1WiY+PdQDP3xuLSSSsZ3gR8aG5/lJ36R4i+FmxZrOTpS3tw1yNxETKqoJMWI7FoUx10W1LbicT6uKZOwG2rCYQhsWJ9wn/0xAWmIhE3P1sMOuFzZBoaRptlNN03gDuo46JjbekxQHE2BnBxeD0xWTq6kFxBxMWFFNq2dEaGL8Gpw3zR1BHmzP38cXrgmUDRGLBRvYorqzrRNXz10VKBvxOfllBo5/ns7ErGyUeOalzbBzsBImKTOnKmFXqSU2HpA6Ts5pwxzHYV6/vmoarWcOxl1U35qB3EkjY4jAbn0NimkuN8dx2GGwYfHr9EI0d6oEyoiIgYuXC4Lns7PQL9KGxQmRfqkQ/337LBOTyiR46vmN8PJzEigr0q+f2i8OHDd5LTiGfdVJ1dXo0Won7fWIcRj3e1BSqRQODg6ore3tG7OysprUL1RCDPE8j87OTtTW1sLBwQFSqVTolCbUlpiZ+OMXl9Cj7T38RdWjxZfJ+XhoaYTAmRFTFrcxDnkpfSf7FV4tRHVJDTz83Yd4igylOL8Wb73yLXiD0XmP7F6F0CgfgbIiwECbFCen9eOWBZ5ezHVHTw+u1NYi1pNOMBWzCWns8vDobcq/VVgTIgQHBwf916KYONtaYk1UII5eKdDHPr5wDQ8uCadfYMmYRSyMgI2jDdqb2vWxxCMXcfcTdwuYlelqqG3DnucPQ9Xdw8Q3PxCLRatDB3mKTAVtZwM0dblMTOk3udNXXCwtEeHsjKyGBn3sXHk5FdUiNyFFNcdx8PT0hJubG3p6eoZ/gJAJJpfLRbdCfbsdi0KZovpaeQOultYhyt9NwKyIKZPJZYi9IwanPu475S/5WAo2PrYRcoV4WqimQleHCnueP4zmxg4mHrcyBHc9EDvIU2SqGE794ORWUHhGTfrrLvHxZYrqhIpy/M/8+ZDQYohoTegWZKlUKurChhChLA72gY+TLcob+8YyfXIhh4pqMi5xG+KYorqzrRMZZ69i/up5AmZlWrRaHd58+RuUFdUz8eBZ3nhk90p6N8kIqA1aPxQ+0eCkk/+LY7yPN97MSNdf13V1IbexEWHOzpP+2kQYNFKPEBMgkXC4b2EIE/syJR+dKnpniIydi7cLZs5jNyzSCYsjx/M89r3xHTJTSpi4h48Dnnp+I+QKGp1nDKZqPrWhADt7+NnaMbFz5eVT8tpEGFRUE2Ii7l0Qwrxt2N7dw7SEEDIWhicsFlwtQE0pzdQdiW8PXsGZr7OYmK29JZ59aTNs7CwEyorcjteooKpIYWKTNZ96IEt8vJnrhAoqqsWMimpCTISXkw2WhfkysY8u5AiUDRGLiEURsHGwYWIXv6LV6uEkJ+Rj/7/OMzGZXIqnf7sRbl4OwiRF+lFXpgGa20aQchyUvgum7PWX+LBTXwpbWlDW1jplr0+mFhXVhJgQwxMWUwurcb2qUaBsiBjI5DLE3BHDxJKPJ6NHTa1FgynIrcY7fz7WL/7D59ZgRrjXAE8QoRiO0pO7hkFi6TBlrx/u7AInC/Zdi3PlFVP2+mRqUVFNiAlZMcsPrnbs8bf7L+YOcjchIxO3kV2562ylExYHU1fdgj3PH0aPmj3IY+sjCxGzdOYgTxGhqEouMNdK/8kdpWdIwnGI96YWEHNBRTUhJkQulWLrAnbD4meX86DqoZO6yNi5erti5twZTIxOWOyvo60bf//1l2hr6WLiS+4Ix4Zt8wXKigyG53moyi4xsanapHg7wxaQq3V1aOzunvI8yOSjopoQE7PdYApIY3s3jl8tEigbIhZxhhsWMwpQU0oHet2i6dHijZeOoqqsiYmHz/XDg08tp9F5RkjTkA9dRx0Tm+yTFAcyz90DVrK+STA8gPMV1AIiRlRUE2JiAt0cEDeD7dv8hDYsknGatXhWvw2LNF6vF8/zeHfvKeRksG/b+wQ444lfr4dMRuczGCPDUXpSW09IHQKmPA+lVNrvJEVqAREnKqoJMUHbF7HHHifklqO0nnaUk7GTyWWIWRvNxJKP0YZFADj8URIunGB/cbV3ssIzL90JK2ulQFmR4RhuUlT4xQn2jsJSgxaQpKoqdNIJ1KJDRTUhJmjd7Gmws1QwsU8TacMiGR/DFpCO1g5cTcgUKBvjcPF0Lj7/gO3LVShleObFO+HsZjfIU8QYqErYonoq51MbivPyhvS2gl6t0yGpulqwfMjkoKKaEBNkoZBhSww7aWB/Yi60Op1AGRExcPVxxYw57IZFc24BycuswH/+fpKJcRzw41/cgYAZ7gJlRUZC21EPTX0eExOyqLZTKDDHzY2J0emK4kNFNSEmyrAFpLq5A2eyywTKhoiF4Wr1jfQbqC0zvw2L1eVNeO13R6AxmKyz40dLMHfhdIGyIiNl2E/Nya2g8IwSKJtehlNAzldWQEMLIaJCRTUhJirMxwVR/uzKxycXacMiGZ/IxbNgbW/NxMxttbqtpQt///WX6Ghjx56t2hyFNXfPESgrMhr9+ql9YsBJ5QJl0yvemy2q29RqZNTVDXI3MUVUVBNiwgxXq09mFqO2pVOgbIgYyBT9T1hM+jYZGrVGoIymllqtwd4XvkJtVQsTj4oNxP0/WiJQVmS01AYr1ULMpzbkYW2NYEdHJkYtIOJCRTUhJuzOeUGwVPTNP9XqeBy8nDfEE4QML24De8JiR2sHrp4X/wmLOh2Pf/31BG5cq2Li/kGu+Mn/3gGJlH5kmgJeo4KqMpWJCTGfeiCGLSDnKsrB87xA2ZCJRt8hCDFhtpYKbJoXxMQ+uZBD36TJuLj5umHGHPbryhxaQA69n4iks9eZmJOLDXa/eCcsDKbtEOOlrrwCaFR9AY6D0nfB4A9MoSUGLSDVHR3Ib24WJhky4aioJsTE7TBoASmua8Gl/EqBsiFiYbhhMT9N3BsWzx3LxpFPkpmYhZUCz7x0JxydbQZ5ihgjw35quVs4JBb2AmXDmu7gAC9rds9CArWAiAYV1YSYuLmB7pjhyfbp0QmLZLwiF0fC2o794X/p6KVB7jZt2VdK8f7e00xMIuHwxK/Ww3eaq0BZkbFSlVxgroUcpWeI47h+LSBnqagWDSqqCTFxHMdhx0J2tfrrtEI0d6oGeYKQ4fVuWGRPWLz8bZLoNixWFDfgjZeOQqtlR5s9+NRyzJrvL1BWZKx4noeqlP3lz1j6qW+JNyiq85ubUNXeLlA2ZCJRUU2ICGyJnQn5bZuoVBotvki6PsQThAxvwQaDExZbOnD1vHhOWGxu7MDff/MlujrVTHzdvfOwbP0sgbIi46Gpvw5dZz0TM6aVagCIdHGFvYI93j6hokKgbMhEoqKaEBFwsrHE2qhAJvYxbVgk4+Tu54bpUexBJ2LZsKjq7sHe3x5GQ20bE58fH4R7H1kkUFZkvAwPfZHaekHqYFzvOMgkEizy9mJiNFpPHKioJkQkdiwOY65zKhpwtYQOFiDjs3ATu8qXn5aPunLT/rrSaXV4+4/foug6u/FyWogHfvjcWkgknECZkfEy3KSo9IsDxxnf/5+GfdXpdbVoUVHLnqmjopoQkVg00xu+zrZM7GM6YZGMU2T8rH4bFhNNfMPi/n+dR1piIRNz9bDD7t9tgkIpG+QpYgr6naRoZP3Ut8R6eEIpleqvtTyPi5U0tcnUUVFNiEhIJBzuM9iw+GVyPjq6ewTKiIiBXCFH9Fp2w2LSt0nQ9JjmhsWThzNw7FAaE7OyUeKZlzbDzsFKoKzIRNB21EFTz+4lMbZ+6lssZDLEeHgwMWoBMX1UVBMiIvcuCIbktrc6O1Q9OHLlhoAZETGI28genNHe3I5ME9ywmH65CP996ywTk8okeOr5jfDycxIoKzJRDPupObkVFB6RAmUzPMMWkEtVlejWmOYvq6QXFdWEiIinow2WhfsxMZpZTcbL3c8d0yNNe8NiyY1avPXyN+B17Obd7+9eidAon0GeIqakX+uHbyw4qVygbIa3yMubWQTp1mqRUlMjYEZkvKioJkRk7jc4YTG1qAZ5lY0CZUPEYuEmdrze9Sv5qKswjQ2LjXVtePX5w1AZtEJt/l4MFq8OG+QpYmoMV6qVfnGD3GkcHC0sEOniwsSoBcS0UVFNiMgsj/CDqx3bG7qfNiyScYpcEgkrg68rUzhhsatTjVd/cxjNDR1MPG5lCO7auWCQp4ip4Xu6oa5IZWLG2k99O8MWkPMV5dDqdIPcTYwdFdWEiIxcKsW9C4KZ2GeXr0PVoxUoIyIGcoUc0WsGOGHRiDcsarU6vPmHr1FWxB4GEjzLG4/sXmmUo9bI2KgrrwDa2w7x4TgofWOFS2iE4r3ZorpJpUJWQ4NA2ZDxoqKaEBHabjAFpKmjG8cyigTKhohF3Eb27fT2pnZkXcgSKJuh8TyPD//vDDJTSpi4h48Dnnp+I+QKGp0nJob91HK3CEgs7AXKZuR8bG0xzZ7Nk1pATBcV1YSIUICbPRbOZE/s+oRaQMg4efi7Y1rkNCZ20Ug3LH77WRq+O8pOKLG1t8SzL22GjZ2FQFmRydLv0BcjnU89EMMWkHPlZXQaromiopoQkdpusGHxfG45SutbBcqGiMVCg9Xq66nXUV9RP8jdwkhOyMeBfyUwMZlciqd/uxFuXg7CJEUmDc/zJrdJ8XZLDFpAytvbUdxK36tNERXVRkSr1eLMmTP4+OOPcebMGWi11ANLxu6O2dNgb6VkYgcScwXKhohF1NIoWNmyGxYTvzaeDYsFudV458/HYLjQ98Pn1mBGuNfADxGTpqnPg66T7UNW+i8SKJvRC3FygqulJRM7Sy0gJomKaiNx6NAhBAQEYPny5bj//vuxfPlyBAQE4NChQ0KnRkyUhVyGu2NmMrH9F3Oh0dLOcjJ2vScszmdil7+5bBQbFuuqW7D3t4fRo2YXJLY+shAxS2cO8hQxdYar1FI7b0jt/Qa52/hwHNevBeRCBRXVpoiKaiNw6NAhbN26FeUGv5lWVFRg69atVFiTMdthsGGxpqUDZ66VCpQNEYu4DQNsWLwo7IbFjrZuvPqbw2ht7mLiS+4Ix4Zt8wd5iohBv35qvziTm+xiOAUku6EBLSqVQNmQsaKiWmBarRa7du0acFPCrdju3bupFYSMSaiPM2YHuDExOmGRjJdHgAemzQpkYkKesKjp0eKNl46ispQ95Ch8rh8efGq5yRVYZHRUJYZFtelsUrxltpsblFKp/poHcLmqSriEyJhQUS2whISEfivUt+N5HmVlZUhISBj0HkKGYjhe71RWCWpaOga5m5CRMRyvl5dyHfWVU79hked5vLf3FHIy2O+j3v7OeOLX6yGTSQd5koiBtqMOmoZ8JmaKRbVSKsU8d3cmdomKapNDRbXAqkb4l2ak9xFi6M75QbBS9s3k1ep4HLyUJ2BGRAwG2rB46ejlKc/jq4+Tcf4E++6LvZMVnnnpTlhZKwd5ioiF4So1p7CG3CNSoGzGZ4GnJ3N9qaoKOhqtZ1KoqBaYp8FfovHeR4ghGwsFNs0NYmKfXMyBTkffrMnYKZQKzF/Tf8OiVjN1rWqJp3Nx6H227UShlGH37+6Ei7vdlOVBhGO4SVHhEwNOapoH+8R5stNpmlTduN7UJFA2ZCyoqBZYfHw8fHx8Bu354zgOvr6+iI+Pn+LMiJgYzqwuqWvFpfxKgbIhYhG3YQFz3dbUNmUnLOZlVuDffz/JxDgO+PEv7kDgTPdBniJi03+Toum1ftziY2sLHxsbJnapir5PmxIqqgUmlUqxd+9eABiksOaxZ88eSKXUF0jGbm6gO2Z6OjIxOmGRjJdnoCcCI9gNi1NxwmJ1eRNe+90RaHrYVfHtP1yCuQunT/rrE+PA93RDXXmFiZnSSYoDifNiV6sTK6n105RQUW0EtmzZgoMHD8Lb25uJ27pY4Ie/34ItW7YIlBkRC47j+q1Wf5NWiOaOboEyImLRf8NiHhqqGga5e/zaWrrw6m++REcb+7W78s4orLl79qS9LjE+qspUQKvuC3ASKH1ihUtoAhi2gGQ11KNVrR7kbmJsqKg2Elu2bEFxcTH+sf/vWP9sJLa9FI1H314Km7BONHbUCJ0eEYEtMTOhkPX9lVdptDiUdF3AjIgYzF4WBUsb9jS4S0cn54RFtVqD1373FWoqW5h4VGwgvvfjJTQ6z8yoDTYpyt0jILEw7V76OW5uUEj6vk/reB7J1dUCZkRGg4pqIyKVSvH9ex7H3BUz4RvhDIm09wdEculxgTMjYuBkY4m1UdOY2McXcgackU7ISCmUCkRPwYZFnY7Hv/92AvnZ7Nvh/kGu+Mn/3gGJlH6cmRsx9VPfYiGTYY4buycgsZL6qk0FfRcyMnKpEnN8ljOx5NIT0PF0+AsZvx0GLSB5lY3IKKkVKBsiFoYtIK2Nbci6mD2hr3Ho/URcPsO+s+LkYoPdL94JC0vFhL4WMX68Ttdv8ofSL26Qu02L4Wi9y9VVtPhhIqioNkIx/muY6+auOuTXpQuTDBGVhTO94etsy8Q+phMWyTh5BnoiMDyAiU3kCYvnjmXjyCfJTMzCUo5nXroTjs42gzxFxExTnwddF3uCpqlvUrzFcLNifVcXbjQ3C5MMGRUqqo2Qj0MQvOzZt+mTSqgFhIyfRML1O2HxcMoNdHT3CJQREYvJ2rCYfaUU7+89zcQkEg6P/2o9fKe5jvvzE9NkuEottfOB1N5PoGwmlp+tLbysrZlYIo3WMwlUVBupGP+1zHVW1UV0qFsFyoaIyb1xwZDctqGrQ9WDr1JvCJgREYPZy2bDwtpCf83zPC59Pb4TFiuKG/DGS0eh1eqY+M4nlyMyOmBcn5uYtv791HGi2ajKcRwWGEwBoSPLTQMV1UZqrs9yyCRy/bVWp8GVsu8EzIiIhYeDDZaHsys6NLOajJfCQoHoNdFMbDwbFpsbO/D3579EVyc7TmzdvfOwfMOsMedJxKFfUS2S1o9bFnixfdVX6+rQ0UPvKBo7KqqNlJXCFhGe7DeJpJJjtFmBTIgdi9kWkCtFNcirnLzZwsQ8xG1kT1hsbWhFduLoNyyqunuw97dfoaGmjYnPXxyEex9ZNK4cienTttdC08C+uyaGyR+3m+fmDvlto/W0NFrPJFBRbcQMW0CqWotQ0UJv05PxWxHuDzd7Kyb2ycVcgbIhYuE1zQsBBhsWR3vCok6rwz/+dAxF19n5/NNCPPDDn62FRCKOt/jJ2Bn2U3MKa8jdxfXuhZVcjihXds8AHVlu/KioNmJBrlFwtHRjYpdLjgmUDRETmVSCexcEM7HPLuehu0cjUEZELPptWEzOQ0N14yB397f/X+dx5WIBE3Nxt8Pu322CQimbkByJaTNs/VD4xIKTiu9rw/B0xcQqGq1n7KioNmISToJog/F6aWVn0KNVCZMQEZX74tgWkOYOFY5nFAmUDRGLOQNsWLz89chOWDz1VQaOHUpjYlY2Sjz7+82wc7Aa5ClibsTeT32LYV91bWcnilpbBrmbGAMqqo3cfL9V4ND3dme3pgOZlRcEzIiIRYCbPRbOZFdCaGY1Ga/eDYvsCYuXvr4MrXboDYvpl4vw4ZtnmZhUJsFTv9kALz+nCc+TmCZdTxfUlVeYmNj6qW8JtLOHuxX7y2RiJU0BMWZUVBs5Jyt3zHCdzcQu08xqMkF2LApjri/kVaCknkY3kvHpd8JiQyuyE68Nen9JQR3eevkb8Dr2re3v716J0Nm+k5IjMU3qilRAe9sUDE4CpW+scAlNooFG69G8auNGRbUJMNywWFCfgYYO+m2VjN/a2YGwt1IysQM0Xo+Mk9c0L/iH+TOxwU5YbKxrw6u/+RIqgwOI7rw/BotXhw34DDFfhq0fcvdZkChtB7nb9BkeWZ5RV4dOGq1ntKioNgHhnnGwlLNH8SaXnBAoGyImFnIZtsTMZGIHEvOgMThsg5DRWmiwWp2blItGgw2LXZ1qvPr8YTQ3dDDxuBXBuPtBdjwfIYD59FPfEu3hAelth9podDqk1tQM8QQREhXVJkAuVWCe7womllx2Ajp+bIcqEHK7HYvYDYs1LR34LrtUoGyIWAx3wqJWq8NbL3+NssJ65rmZEV545JlVojkdj0wcXqeDupTd9Kr0ixvkbnGwHmC0HrWAGC8qqk2EYQtIS1c9rtemDXI3ISMX4u2MOQHs6EY6YZGMl9JSifmr5jGxy9/0bljkeR7/ffMMriaXMB9393bA07/dCLlCfOPRyPhp6nOh62Lf7RDrJsXbDXRkOY3WM05UVJsIL/tp8LYPYmJJNLOaTJDtBqvVp7NKUN3cMcjdhIzM7RsWdbwO2flZ+NtLf8OfX/wnTn6Vwdxra2+JZ1/aDBs7y6lOk5gIw0NfpPa+kDn4CZTN1Ikz6Kuu6uhASRttKDdGVFSbEMPV6uyqS2hXNQuTDBGVTfOCYHXbwRpaHY+Dl+iERTI+3kHe8A/1x426G3j30n/wWcZn+Pnvfo5fvPAjfHbuRZTU9BbWMrkUT/92I9y9HYRNmBi1fv3UIm/9uGW6gwNcLNlfNi/RaD2jREW1CZnrswwyiUJ/reU1uFL2nYAZEbGwsVDgznnsOyGfXMyFTkdvMZLxUTl242j2EbSr2pl4p6oZZzLeRUlNBh776RrMCPca5DMQ0ktVwq5Um0PrB3BrtB67Wk1HlhsnKqpNiKXCBrO82G8iSaXHqbeKTAjDFpDS+lYk5lcIlA0RA61Wizfef2PIe7LKv8b8+OlTlBExVdr2GmgabzAxc1mpBvofWZ5WW4tujUagbMhgqKg2MYYtINWtxShrvi5QNkRM5gS4I9iLPbnuEzphkYzDp19/iYqKoX8xq2+owZuHDqFdrZ6irIgpMuyn5hQ2kLvPEiibqWc4Wk+t0+FKLY3WMzZUVJuY6S6RcLLyYGJJdMIimQAcx2H7Qna1+pv0QjS1dwuUETFFTV1t+M+V47jjg1/jkQ//NKJnXjt3FmsPfYYfHD+GN9PTkVRVRatwhKEqMein9o0FJzWfKTG2CgUiXFyYGB1ZbnzM5ytSJCScBNF+q3Esd58+ll5+BndGPAaFzGKIJwkZ3paYmXjli0SoNb2Hv6g1OhxKuo4frIgUODNizLo1ahy7cQUHss7h+I0r6NH1ztCX2I7se5LcwQE6nse1hgZca2jAvpxrkEkkiHB2xjx3d8xz90C4szMUUulk/mcQI2a4SVFhRq0ftyzw9EJGXZ3+muZVGx8qqk1QtN9qHM/9EDx6e6m7NZ24Wnke8/1WCZwZMXWONha4Y/Y0HE7p61385GIOHlk+iw7jIAwdr0NiWS4OZJ3DF7mX0NLdfwSjNMAVnJ0l+NauQT+PwtkJdiEh/eIanQ7pdXVIr6vDv7OyoJRKEeniijlubpjr7oZQJyqyzYWupwvqKvZcBgv/RQJlI5w4T0/842rfKMqK9naUtbXB11a8x7SbGiqqTZCDlStmus1DXm2KPpZUcpyKajIhti8MZYrqvMpGpBfXYk6gu4BZEWORV1+OA1nncCD7PMpa6oa8l5NwcN2yALXv9Z9SxHEceADLn3wSnTIZenS6IT+XSqtFck01kmuqgUxAKZUiwsUFc93cMMfNnVayRUxdkQJoe/oCnAQKnxjhEhLIDEdHOFlYoLG7ryXvUlUlfG2DBcyK3I6KahMV47+GKaoLGzJR314JFxsaS0XGZ+FMb/i52KG0vu9wgY8v5lBRbcZq25tx8NoFHMg6h/TqwmHvV0rlWD9zPrZFLEG4wh8Ppf0cSbmfo/O2ufo+Pj7Ys2cPtmzZgm6NBpn19bhSW4OUmhrkNDRAO8xUI5VWi9SaGqTW1ADIhEIqRYSzM+a6uWOOmxvCXVygpCJbFAz7qeUekZAozW91VnJztN7XRUX62KWqKtw7k4pqY0FFtYkK94iFlcIOneq+wiep9DjWhz0sXFJEFCQSDtsXhuDPh5P0scMp+Xj+noWwsVAM8SQRkw51N45eT8aBrHP4rugqtPzQK8kAsNgvHPfNWoI7g2Nhb2ENADh95Cr83aPg6zYLtU0F4OQq/OwP92PJkiWQ3ix6LWQyRHt4INrDAz8C0NHTg4y6WqTU1OBKTQ2uNzVhuMGhaq0WV2prcaW2FgCgkEgQ7uLS2y5ycyXbQkY/8kyR4eQPc5lPPRDDojq1pgYqrZZ+gTQS9B3GRMmkCszzXYGEgi/0sZTSk1gbshNSCf3lIuOzdUEI/vpVMnQ3Vws7VRp8lXoDOxaFCZwZmUxanRZni7OwP+scjuRdRkePathnQlx8cF/EEmwNXwxfe9d+H89JLwfQu8naw2kG4lYEY/ny5UN+Tmu5HAu9vLHQyxsA0KJSIa229uY/NbjR3Dx8ka3T6Z/5D7Igl0gQ7uyM2TeL7FkuLlRkmwBep4O6zLCoNr9NirfEeHhCwnH6780qrRZptTVY4EnvUhsD+o5iwmL81jBFdWt3A/JqUxHmYX69ZmRieThYY0WEH05mluhjn1zIoaJahHieR2ZtMfZnnsNn1y6gur1p2GfcrR2wNXwx7pu1BLPcAgbdxKrT8ci9Ws7EQmf7jjpHe6USy3x9scy399kWlQoZdXVIq63Bldpa5I9gJbvnto2P72VnQyaRIMzJGXPd3TDH1Q2zXF1hSUW20empy4Gui/2aVPqb70q1vVKJMCcnZDU06GOXqqqoqDYS9B3EhHnaB8LXYSZz+EtSyTEqqsmE2LEojCmq04prkVvRgBBvZwGzIhOlvLUen2Yl4EBWAnLqy4a931quxMbgWGyftQRL/CNG9I5YRUkD2lrYyR+hUT5jzvkWe6USS3x8sMSn93O1qtXIqKtFWk0t0upqcb2pSb+SNxiNToer9XW4Wl+H95ANKcch1Nn55sZHN0S6uMJKLh93rmR81AatH1J7X8jsR/+LmZgs8PJiiurEyirsnitgQkSPimoTF+O/limqr1VfRpuqGbZKB+GSIqKwPNwPbvZWqG3p1Mc+uZiDF+5dLGBWZDxaujtwOO8y9meew4XSa/qxnIORcBxWBEZhW8QSbJgZDWvF6Gbh52awq9Qu7nZw9bAfdd7DsVMoEO/tg3jv3iK7Xa1GRl0drtxsF8kbQZGt5Xlk1dcjq74eH1y7BinHIcTJSb/xMdLVFdZUZE85w/nU5txPfUucpxf+lZmpvy5ta0Vlezu8bGwEzIoAVFSbvNk+S3E46x30aHt7H3W8Fqmlp7Bsxj0CZ0ZMnUwqwbYFIXjj2BV97FDSdfzirgWwkNO3DlOh1vbgVGEG9meewzf5KVDdPppsELM9pmFbxBLcE7YQ7jaOY37ta+nsCnjo7PGvUo+EjUKBRd7eWOTd25Pd0dODq3V1uHKzXSSvsXHY6SJankd2QwOybx5GI+U4BDs5YY5r75zsKFc3KrKnQL9Nimbc+nFLiJMTHJRKNKv69jxcqqrClhkzBMyKAFRUmzxLuTUivRYjteyUPpZUegxLg7bQYR1k3LYtZIvq5g4VjqUXYXM0ffM2ZjzPI6UyHweyzuGzaxfR2NU27DM+di64LyIe2yKWINhl/MWvTqvr308dJczb9tZyOeK8vBDn1dt3eqvIvrXxMWeERfatEx//m5sDCcch2NFRv/ExytUVtgqajjORtO010DQWMDFz3qR4i4TjEOvhiWMlxfpYYlUlFdVGgIpqEYjxX8MU1bVtZShtyoW/U6iAWRExCHC1x8Jgb1zMq9DHPr6YQ0W1kSpsrMKB7PM4kHUOhU3Vw95vp7TC3aFx2BaxBHG+IZBwkgnLpbSwDl0daiY2Ef3UE8GwyO7s6dHPyU6rrcW1EczJ1vE8chobkdPYiI9zcyHhOMxwcNC3i0S5ucGOiuxxMZxPzSltIXefJVA2xiXOiy2qU2tqoNZq6QAkgVFRLQLTnGfB2doTDR1V+lhSyXEqqsmEuH9RKFNUX8yrQHFdCwJcJ743loxeQ2crPs9JxP6ss0iuyB/2frlEijVBc7EtYgnWBs2FhWxyCr9r6ewqtYePAxxdjLPn00ouR6ynJ2I9PQEAXTcPo0m7WWRnNzRAM8yJjzqeR15TE/KamvBxXi44AEEOjpjr3reSba9UTsF/jXj0a/3wiQVHI2MB9I7W4wD9rogujQYZdXWI9vAQMi2zR0W1CHAchxi/Nfgm5319LL3iLO6c9SMoZaPbWESIoTVRgXCwVqK5o69/b//FHPx88wIBszJv3Ro1vs1Pxf6sczhRkAaNTjvsM7E+wbgvYgnuComDk9Xkn0aXm2HQTy1Q68dYWMpkiPHwQMzNAqVbX2T3totkNzQMe6w6DyC/uQn5zU3Yn5d3s8h2wJybx6rPcXOjInsYqtILzDW1fvRxtLBAiJMTchob9bHEqkoqqgVGRbVIzPdbhW9z9oFH7zd6laYLVysSEO2/WuDMiKmzkMuwJWYm/vNd327zA4l5+J+NMZBJJ65dgAxNx+twoTQHB7LO4cvcRLSquoZ9ZrqTJ+6LWIJt4fEIcJy6Y+Y1Gi3yMiuZ2FjmUxuL2098BHqL7OyGBv2c7Oz6eqhHVGQ3I7+5GQeu905smm7v0Dsn280Ns13d4GhBiyC36NSdUFemMTHapMiK8/JiiurLVVXAHAETIlRUi4W9pQuC3echtyZZH0sqPUZFNZkQ2xeGMkV1XWsnTmeXYE1koIBZmYecujIcyDqHT7MTUN7aMOz9zpa2uCd8Me6LiMdczyBBNiwX5dVA1c1OGQmJ9J7yPCaLhUyGee7umOfe+4uKSqtFdkN975zs2lpkNtRDrR3+3YOClmYUtDTj05tF9jR7e2Yl28mMi2x1RQqg0/QFJFIofOgMhtst8PTEf7Ky9NeFLS2o6eiAu7W1gFmZNyqqRSTWfy1TVBc1ZKOuvRyuNsaxOYiYrhBvZ8wJcENaca0+9smFHCqqJ0l1exMOZp/HgawEXK0pGvZ+C5kcG2bGYFtEPFYERkEuFfZbe47BfGqfQGfYOVgJlM3kU0qlmOvmjrluvUW2WqvFtYYG/cbHzPp6qEZQZBe2tKCwpQWf5ff2xgfY2fVufHR3w1xXNzhZWk7qf4cxMZxPLfeIhEQ5+W1LpiTMyRm2CgXa1H0bghOrqnBXUJCAWZk3KqpFJNQjBtYKe3SoW/SxpJLj2BD+iIBZEbHYsSiMKapPZ5WiurkdHg7GufnM1LSru3AkLwkHshJwpvjqsIeVcOAQ7x+O+2YtwabgWNgpjadozTHhfuqJoJBKMdvNDbPd3AD0Ftk5jQ1Iq63FlZpaZNbXoXsERXZxayuKW1tx6EZvke1vZ4c5bm43T310h4uIi+x+mxTp0Jd+pBIJYj08cLK0VB+7VFVJRbWAqKgWEZlEjnm+K3Gu4JA+llJ6EneEPjSiI4UJGcqmeUH43cEL6FD1vq2v43l8mpiHp9bNEzgz06XRaXG2OBP7M8/hyPUkdPaohn0mzNUP22ctwT1hi+FtZ3xHxqvVGty4VsXEjGWUnlAUUimiXHsPjHk4HOjRapHT2Kjf+JhRN7Iiu6S1FSWtrfjixg0AgJ+trb5VZI6bG9ysjOcXq/HgdboBimrapDiQBZ5eTFGdXF2NHq0WchqtJwgqqkUmxn8NU1S3qZqQW5OMcE+a1EDGx9pCjk3zg/DJhRx97JOLOXhi7VxIJHTQ0EjxPI+MmiLszzyHz66dR21Hy7DPeNo44t6bB7NEuPlPQZZjV5BTjR51X4HISTgER5p3UW1ILpUi0tUVka6ueCg8HBqdDrmNjfp2kat1dejUaIb9PKVtbShta8OXBb1Fto+NDea6u9889dHdZIvsnroc8N3NTIxWqge24OYYyFs6b06qmes+dRuTSR8qqkXGw84ffo7BKG3K08eSSo5TUU0mxI6FoUxRXdbQhovXK7A4hIqm4ZS21OHTrAQcyDqHvIaKYe+3UVhgU3AstkcsxWL/MJN5tynH4Ghy/+musLah0XFDkUkkiHBxQYSLCx4M6y2y826uZF+5uZI9kiK7vL0d5e3tOFzQewqht43NzXaR3tVsDxPZwGbYTy2194PMnr7HDMTZ0hIzHR1xvalJH7tUVUVFtUCoqBahGP+1TFGdU3MZrd2NsLNwEjArIgazA9wQ4uWE3Mq+MU6fXMyhonoQzd0dOJx7CZ9knsXFspxh75dyEqycFoX7IpZi3cz5sJKbXjGaa7BJ0ZRH6QlFJpEg3MUF4S4ueCAsDBqdDtebmpgiu6OnZ9jPU9Hejor2dhwpLAQAeFlb69tF5rq5wdPGOPdDGJ6kSK0fQ4vz9GKK6sSqSjw+e7ZwCZkxKqpFaLb3EnyZ+Q/0aHv7M3W8Dqllp7F8xlaBMyOmjuM4bF8Uihc+7TuU4dv0QjS2d8HJRrybpkZDre3BiYJ07M88i2M3rkClHb74mes5HfdFLMWWsIVwtTbdkypV3T0oyGWPRzf3fuqJIJNIEObsjDBnZ3wvNBRanQ75zc24UlODtLpapNfWon0ERXZlRwcqiwpxtKi3yPawtr656bF3NdvT2lqQEYyG1Ib91P6LBMrENMR5eeL9a9n66xvNzajr7ISribb/mDIqqkXIQm6NKK94pJSd1MeSSo5hWdA9RvENk5i2LTEz8crnl6DS9PbNqjU6HEq6jkdXRAmcmXB4nkdSxXXszzyLz3MT0dTVPuwzfvau2BaxBPdFxGOGszhmOF/PqoRW23cIilQqwcwILwEzEiepRIIQJyeEODnh/ptF9o3mZly5ufExvbYWbSMosqs7OvB1URG+Luod2+huZaWfkz3XzQ3eNjZT/jND21YNTVMhE6OV6qGFO7vARi5nfrG6VFWFTdOnC5iVeaKiWqRi/NcyRXVdezmKG68h0DlcwKyIGDhYW+CO2YH4MuWGPvbJhRz8YHmk2f3SVtBYhf1Z53AgKwHFzTXD3u9gYY27QxdiW0Q8FviEiO7Py3CUXmCwOywsFQJlYz6kEgmCnZwQ7OSEHSEh0Op0KGhp0Z/4mF5bi9bbZhkPpqazE98WF+Pb4mIAgJuV1c1Nj72r2T42tpP+NWvYT80p7SB3j5jU1zR1MokE0R4e+K6s7+9fYlUlFdUCoKJapAKdw+Fi7Y36jr4NUcklx6moJhNi+6JQpqi+XtWEtOIazA30EDCrqVHf0YJDORdxICsBKZX5w96vkMqwNmgetkXEY830uVDK5FOQpTBy0g36qan1QxBSiQQzHR0x09ER9wWHQMfzKGxuRlpd75zstNpatKiHH99Y29mJYyXFOFZSDABwsbTUt4rMdXODr+3EF9n9Run5xoIzkU26Qlrg6cUU1cnV1dDodJBJJAJmZX6oqBYpjuMQ478GX197Vx9LrziHO2f9CBZy6rMi4xM3wxv+rnYoqWvVxz65kCPaorqrR4Vv8lOwPysBpwrTodENP1M4zjcU90XE466QODhYGueGsInU2aFC8Y1aJkabFI2DhOMQ5OiIIEdH3DszGDqeR1FLi36EX1ptLZpVwxfZ9V1dOFFSghMlJQAAZwsLzHVzx2y33tVsf1u7cRfZqpILzDW1foyM4Wi99p4eZDfUI8rVTaCMzBMV1SI2328Vvs15Hzq+t8dRre1GRkUCYgPWCpwZMXUSCYf74kLx58OX9bHDqTfw/NZFsLEQx9v9Ol6HhJJsHMhKwOHcS2hTdw37zAwnL9w3awm2hi9GgIN5jbTKy6wAr+s7BVImlyIo1HOIJ4hQJByH6Q4OmO7ggHtnBoPneRS3tuJKbY1+JbtJ1T3s52no7saJ0hKcKO0tsp0sLPQH0cx1c0eA3eiKbJ26E+qqdCZG86lHxs3KCkEODrjR3KyPJVZWUVE9xaioFjE7CyeEuEfjWnVf4ZNcepyKajIhti4Ixt+OJEF7s5DqVGlwOOUG7l8cJnBm45NdW4IDWQk4mH0eFW0Nw97vamWPe8IX4b6IJZjtMU10fdIjZTifOijUEwol/YgxBRzHIdDeHoH29rhnxkzwPI+S1lb9xse02lo0dA9fZDd2d+NUaSlO3Tzhz1Gp7F3FvjnGL9DeHpIh/n50lV5CYqEate2Amw0QEyCDwidmwv47xW6BpydTVF+qqsSPo8x3A7kQ6DueyMX4rWGK6uLGa6hpK4W7rZ+AWREx8HCwxooIf5y4WqyPfXIxxySL6qq2RhzMPo/9WeeQVVsy7P2WMgU2BsdgW8QSLA+MhIx6PpHTbz419VObKo7jEGBvjwB7e2yZMQM8z6O0rY1pF6nvGv6dmyaVCt+Vlel7fS1lMvjY2MDH1ha+trbws7XT/+/vjh7F0z95BJV1fa1Vng5SvDHnOLZs2TJp/60TRcfz6NHp0KPVQq3VQq3ToUenhVqrQ49OB7VWy/5bp0WP9vZ7Bvi3Tjf4PTdf6/bPaThWMa+pCQ1dXXC2pHGnU4WKapEL9YiBrdIRbaq+wfBJJcexKeJRAbMiYrF9YShTVKcX1yKnvAGhPs7CJTVCbaoufJV3GQeyzuFscRZ48EPeL+E4LA2YhW0RS7BxZgxslfSD6pa2li6UFdYzMdqkKB4cx8Hfzg7+dna4O6i3yC5vb9O3ilyprUHdCIrsLo0G+c3NyL9tNRUAGpOScX3Pnn73VzWrcc/WrfjLv/+NLVvuhp1CCXuFAjKJBFqeH7RQ7ft3/8Kz/z23Fbc3i9jBP2b4776PaXS6fvkbg7S6Wqzy8xc6DbNBRbXISSUyzPNdiTM3DupjqWWnsD7sYUgl9H8/GZ/l4X5wt7dGTUuHPvbxxRy8uG2xgFkNTqPT4ruiq9ifeRZHryejSzP8mLEIN3/cN2sptoYtgqctnUo6kNyr7Cq1QinDtGBxblolvUW2r60dfG3tsDkoCDzPo6K9Xd8ucqW2FrWdnSP6XLxOh+IPPhjiBh6/eu6nOKiQg7s5yULCcdDxQ/8STIgQqKoyAzH+a5iiul3VjJzqJER40QYQMj4yqQTb4oLx+rdX9LFDl/Pwy7sWwEJhHN9eeJ5HenUhPsk8i0PXLqKus2XYZ7xtnXFvxGLcGx6PcDda5RmOYevHzAhvyOTUEmMuOI6Dj60tfGxtcef06eB5HpUdHb0Fdk1voV09SJHdmpsLdWPjkJ9f3dCI1txc2If1tpZRQT0y893dsdSb3jGaSsbxU49MKjdbXwQ4haG48Zo+drnkGBXVZEJsWxjKFNWtXWp8m1GIu6JnCpgV0NTVhgNZ5/FBxilkj6BP2lZhiTtDFuC+iCVY7B8GCUfzXUfKcJMitX6YN47j4G1jA28bG2yc1nsASW1nJ0pbW1HW3oaytjaUt/X+O61l+F9yAaDHoGXElMgkEigkEsglUsilN/+3VMr+W/8xw38P9TEp5BIJFNLef/d9TgkclBbwthH/KE9jQ0W1mYjxX8MU1bk1KWjpaoC9pfH3vhLj5u9ih0XB3riQ13fQ0CcXcgQpqm+NwduXfgpf5SVBpR36qGaZRIqV02Zje8QS3DFjHizlyinKVDyaGzpQVdbExGiTIjHkZmUFNysrzAfbFnTK0gqrXn9j2OflDg4jeh0Jx/UWmgaF6+3Fp2FxOvTHpFDc+rdB4TrgvQO87lATT4i4UFFtJiK94vHF1beh1vaOReKhQ2rZKayYuU3gzIgY7FgUxhTVF69Xori2BQFu9lPy+pVtDfjo6hnsyziNkubaYe+f7zUD90Uswd2hcXCxnpocxcrwaHJLawX8g2g2LhmZZUuXwsfHBxXl5QNuFeY4Dj4+Pkh7/rfo0GrRqlJBo9MNWjDTCYJESFRUmwkLuRVmey9BUulxfSyp5DiWz7jXbOfqkomzNioQDtZKNHf0ncr2ycUc/OKuBZP2mj1aDY7duIJ9GadxouDKsH2Wfvau2D5rKe6LWILpTnQoyUQx7KcOnuUNqZQKGzIyUqkUf3vhWWx/9FlwAFNY3/rZtGfPHijlcijlcjhZWAiSJyEjQUW1GYn2X8MU1fUdFShqyMY0lwgBsyJioJRLcU9sMP59+qo+9umlPPzPpmjIpRO7Ye1GQyU+vHoaH109g9qOofsxFVIZNgXH4sGolYgPCKc+6UnQbz51FB1NTkZnXbgCb22V4nfHtKhq64v7+Phgz549JjGnmhCAimqzEuAUBlcbH9S19/0QTCo5RkU1mRDbF4YwRXVdaye+yyrFmqjAcX/uzh4VDudewgfpp3CxLGfY+8NcfbEzaiXui1gCJyvbcb8+GVh9TSvqqthfbGiTIhmt7qKzWBciwZqZHJJKebS4xGPm5t8iPj4e0gn+pZyQyURFtRnhOA4x/mtxNPvf+lhGZQLuivwxLOTWAmZGxCDYyxlzA91xpahGH/v4Qs64iur06kLsSz+FT7MT0Koa+nAJG4UF7glbhAdnr8RczyBqa5oChqvUNnYW8Al0ESgbYop4nQ6q4vMAAKmEQ1wAB6ct34fNnGWC5kXIWFBRbWbm+a7AN9fehY7vPf2pR6tCesU5LAhYJ3BmRAx2LApliurvsktR3dwOD4eRj3Zq7mrHp9m9o/Aya4qHvT/WJxg7o1birtAFsFHQKYdTyXCUXkiUDyQS+mWGjFxP3TXoOtnTOC0ClgiUDSHjQ0W1mbGzcEKoeyyyqxP1saSSY1RUkwmxcW4QXvj0AjpUvaPsdDyPzy5fxxNr5w75HM/zOF96DfsyTuFw7iV0a4YehedsaYsdkcuwM2oFgl2o3UAIPM8P0E9N/1+Q0VEVnWOupQ4BkDkGCJMMIeNERbUZivFfwxTVpU15qG4tgYcdnRxHxsfaQo5N86bjk4u5+tiBxFw8vmbOgO0Y1e1N+PjmKLzCpuohPzcHDiumReLBqJVYN3M+FFL5hOdPRq6mshlN9e1MjDYpktHqLjrLXFsExguUCSHjR0W1GQpxj4at0hFtqr4DG5JKjuPOWY8JmBURi21xofqimtfpkJOWjN/vaUb8nDDEx8eD54ATBWn4IP0Ujt+4Au3NVqTB+Ni54IGoFfhe5DL42rtOxX8CGYGcdHaV2t7JCp6+jgJlQ0wRz/NQFScwMWXAUoGyIWT8qKg2Q1KJFPP9VuG7/E/1sdSyk1gf/jBkElr9I+Mzb5o7prs7IDPxOzSf/xTajmY8f7j3Y3auTrDZNBcd0x2G/BxyiRQbZsZg5+wVWBYwC1IJTQAwNgON0qPNoWQ0emoH6KcOpH5qYrqoqDZTMf5rmKK6Q92KnOokzPJaJGBWRAw4jsMMbQXOHPtnv4+11jWi9T8nYXV/HOTh3v0+HuLigweiVmB7xBI66dCI8Tzfb5MiHU1ORktVbNhP7U/91MSkUVFtplxtfBDoHI6ihmx97HLJMSqqybhptVp88c+/DnlP19F0yEK9wEk4WMuVuDtsIR6MWolo75m02mkCKkoa0NbCjjikfmoyWv36qQOon5qYNiqqzViM31qmqM6rSUVLVz3sLWnOLBm95u4OfJZ9Hq/tfxd11TVD3su3dCGoXYld2x/B3aELYaukUXimxLD1w9ndFq4edgJlQ0zRgP3UgdRPTUwbFdVmLNI7Hl9kvgWVpnfFiYcOKaUnsTJ4u8CZEVPB8zwulF7DvozT+DI3Ed2aHqhLSkf07E+jNmLH7JWTnCGZDIabFEMjfegdBjIqmroc6DrqmBj1UxNTR0W1GVPKLDDbeykul3yrjyWVHsfymdsg4SQCZkaM3a1ReB9e/Q4FjVXMxyS2FiP6HJ6enpORGplkOq0OeVcNiurZ1PpBRqfbcD61vR+kDgHCJEPIBKGi2szF+K9hiuqGjioU1mchyDVSwKyIMdLotDh+4wr2ZZwechSeNMAVnJ0l+NaBjxXnOA4+Pj6Ij6f+SVNUWliPjnYVE6NDX8hoqQz6qZUB8fRuBzF5VFSbOT/HELjb+qGmre8t++TS41RUE73CxirsyziNjzPPorq9ach7ZRIp1gfPR+ArC/DSkz8D0NsicjsewJ49eyCV0pg8U2Q49cPd2wFOrrYCZUNMEc/z6Dbop7agfmoiAlRUmzmO4xDttwZHsv+lj12tPI+7In8CS7m1gJkRIXX1qHA47zI+SD+FC6XXhr1/prM3ds5eie0RS+B6cxRelMc07Nq1C+Xlfa0CUhtHrNr5JLZs2TJpuZPJlWPY+kGr1GSUNHW50HXUMjHqpyZiQEU1wTy/lfj62rvQ8VoAQI9WhbTyM1gYuEHgzMhUS68uxIfpp3EgOwGtqs4h77WSK7ElbCF2Rq1EzACj8LZs2YLNmzfjV6+/j38ePQ+plT2UnkG4IZOhuaMbDtYj670mxkOj0eJ6ZgUTC6N+ajJK3Ybzqe19IXUMFCgbQiYOFdUEtkoHhHssQGbVBX0sueQ4FdVmormrHZ9mn8e+jNO4WlM07P3zvWbgwdkrRzQKTyqV4heP3Y+DhT1Qa3p7sNUaHb5IzsfDy2ZNSP5k6hTn16K7q4eJhdBKNRkl6qcmYkVFNQEARPuvYYrqsubrqGopgqc9rR6IEc/zOF96DfvST+Fw3iV0a3qGvN/J0hb3RSzBzqgVCHPzG9VrOVhbYE1kII5cKdDHDiTmUlFtggz7qX0CnGHnYCVQNsQUUT81ETMqqgkAINhtHuwsnNHa3aCPJZUcw+bIHwuYFZloVW2N+DjzLPZlnEJR09AHtHDgsDwwEjujVmD9zGgoZfIxv+62uBCmqM4qq8e18nqE+dBBQ6bEcD41rVKT0dLU50HXzn7vUVI/NREJKqoJAEAqkSLabxVOXd+vj6WWf4cN4Y9AJlUImBkZrx6tBscL0rAv4xRO3EgbdBTeLT52zvhe5Ap8L2o5/OxdJySH+FAfeDhYo7q5Qx87kJiLF+5dPCGfn0y+HrUG+dcqmRjNpyaj1W8+tZ0PZI7TBMqGkIlFRTXRi/ZbwxTVnepWZFdfRpQ3zRM2RQWNVdiXcQofXz2Lmo7mIe+VS6RYPzMaD85eiWUBsyCVTOy4O6lEgq2xwXjj2BV97IvkfPzy7jgoZDRazxQU5FajR63VX3McEDLLW8CMiCmifmoiZlRUEz0XGy9Mc56FwoZMfSyp5BgV1Saks0eFL3MvYV/6KVwsyxn2/hAXHzwQtQLbI5bA5eYovMmyLS6EKaob27txKrME6+bQKpUpMOyn9pvuBusRnp5JCED91ET8qKgmjBj/NUxRfb32Cpo76+BgNTFtAGTi8TyPjOpCfJB+CgevnUerauCTDG+xliuxJWwRdkatQPQAo/AmS4CbPWKCPJF0o+9Y8/2JuVRUm4icDMOjyamfmoyOpv46dO3VTIz6qYmYUFFNGJFei/HF1bfQremdUcyDR3LpCawOuV/gzIih5q52HMhOwAfpp5BVWzLs/dHeM7AzamSj8CbLtrgQpqg+k12KmpYOuNvTQUPGTNXdg4JcthiiQ1/IaPWbT23nDZnTdIGyIWTiUVFNGAqZBWb7LMOl4q/1saTS41gZvB0STiJgZgQAdLwOCSXZ+DDjNA7nXoZKO/QoPGdLW9w3awl2Rq1EqKvwm8o2zJmO5w8koFOlAQDoeB6HLl/HT9bMETgzMpT87EpoNX0bXCUSDjMjqJ+ajA71UxOxo6Ka9BPjv4Ypqps6a1BQfxUzXGcLl5SZq2xrwEdXz+DDjO9Q3Dz8KLwV0yLxYNRKrJs5Hwrp2EfhTTRrCzk2zg3CgcRcfexAYi5+vHo2/XA1YoatH9OCPWBpRVOByMjxPA8V9VMTkaOimvTj6zATHnYBqG4t1seSSo5RUT3FerQaHLtxpXcUXkEadDw/5P0+di54IGoFvhe5DL4TNApvMmyLC2GK6oKaZlwpqsG8aR4CZkWGYrhJkeZTk9HSNORD21bFxKifmogNFdWkH47jEOO3Boez3tHHMisvoFPdBiuFrYCZmYcbDZXYl3EaH2eeQW1Hy5D3yiVSbJgZgwdnr8TSgIgJH4U3GaKneyDQzR5FtX3/bfsTc6moNlKdHSoU5dcysTDapEhGSWU4n9rWEzKnIIGyIWRyUFFNBjTPdwWOZv8HWr6391Wj60Fa+VksmrZR4MzEqUPd3TsKL+M0EkcwCi/UxRc7Z6/EfRHxcLaym4IMJw7Hcbh3QTD+fDhJHzuSegMvbF0EK6XxtKqQXtczK8Dr+t4lkcmlCArzEjAjYoq6+/VTL6GWLyI6VFSTAVkr7RHuuQBXK8/rY0klx6ionkA8zyP95ii8z0YwCs9GYYEtYYvwYNRKzPMKMukfSPfEBuOvXyXrW1rau3vwTXoh7okNFjgzYsiwn3p6qAcUSvrRQUaO+qmJuaDvjGRQMf5rmaK6ouUGKpoL4O1AI5DGo6mrDfuzErAv4zSyRzAKL9YnGA9ErcDdoXGwUQgzCm+ieTraYEmoD85c6+vVPXAxl4pqI2RYVIdFCT9FhpgWTeMNaNvYI+6pn5qIERXVZFAz3ebA3tIFLV31+lhy6XF4O/xEwKxMk47XIaE4Gx9knMKRvKQRjcLbEbkMD0QuR4gRjMKbDNsWhjJFdWJ+JUrqW+HvYlrtLGLW3tqF0oI6JkabFMloGfZTS2w8IHOeIVA2hEweKqrJoCScFNG+q3Hy+sf6WGrZaWwI/wHkUhqnNRIVrTdH4V09jZLm2iHv5cBh5bQo7Jy9EutmzDOqUXiTYfWsADhYK9HcodLHDibm4n82xQiYFbld7tUK5lqhlGF6CG0oJaNj2E9tEUj91EScqKgmQ4r2Z4vqrp52ZFclYrYP9cMNpkerwTf5qfgw4xROFqYPOwrP194VD0Qux/1GPgpvoinlUtw1fwbeO5uljx28nIdnNkRDIqEfuMbAcJTezAgvyOTGP2GGGI+B+qmV1E9NRIqKajIkZ2tPTHeJQkF9hj6WVHKMiuoBXK+vwL6MU/gk8xzqOocehaeQyrBxZgx2zl6BpQGzzPa0ym0LQ5iiuqKxHReuVyA+hFoMjIFhPzW1fpDR0jQWQNvKvuNhEUD91EScqKgmw4r1X8MU1fl16WjsrIGTlbuAWRmHDnU3vshNxL70U7hUnjfs/WGuvtgZtRL3RSyBkxXN/I7wdUWYjzOulTfoYwcu5lBRbQSaGztQWdrIxGiTIhmt/v3U7pC5zBQoG0ImFxXVZFizvBbBIuNNdGs6AAA8eKSUnsSakO8JnJkweJ7Hlaob2Jd+Gp9du4A29fCj8O4JW4QHZ6/EXE/THoU3GbbFheCFTy/or79NL0JzpwoOVkoBsyK5BqvUFlYK+M9wEygbYqr69VPTfGoiYlRUk2HJpUrM8V2GxKKj+lhyyXGsCt5hVm0LjZ1t2J91DvsyTuNaXemw9y/wCcYDUStxV+gC0YzCmwx3Rc/AHw4lokerAwCoNFp8lZKPnUsiBM7MvBm2fgTP8oZUaj5/38n4UT81MTdUVJMRifVfyxTVTV21uFGXjplucwXMavLpeB3OFWfhg/RTOHI9CWqtZsj7XazssGPWUuyMWomZLt5TlKVpc7KxxKrIAHyTVqiPHUjMo6JaYIabFOlocjJamqZCaFsN3vGg+dRExKioJiPibR8EL7tpqGztK3ySSo6Ltqgub63vHYWXcRqlLXVD3ivhOKyaNhsPRK3EHTPmin4U3mS4Ly6EKaozSmqRV9mAYC9nAbMyXw21raitYjfbhlA/NRmlgfup6YAnIl5UVJMR4TgO0f5r8GXm2/pYVtVFdKrbYKUQx4Y7tbYH3+SnYl/6KZwqzACPoUfh+dm7YmfUStwfuQzedlT8jceSUF+42VuhtqVTHzuQmIff3LNQwKzMl2Hrh7Xt/7d33/F119X/wF+fO7P3usnNTjrSke4duphCKcSCMlVEhiKFrwoK+FNxgKjQ4gIUUWQo1DKKMjtougdtOjKaPW/2Xnd+fn+kve3n3qTJbcbnjtfz8fDx8J77yc1JaZLT9z2fc/yQmBolUzbkqZz7qXPYT01ejUU1jdq8xNX44PRfYbUNtkBYbGZ8UbMDK9LXy5zZ2BS31OKf+Tvwr5Ofo6Wv66LXapQqrJu6GHdmr0VOygyf6imfSCqlAhsWT8WfPjlmj71z6Ax+eMNiqJWcizzZCo87jNKbncDZ4eQS9lOTL2JRTaMWqAnBLN0yHK87/5beoepPPLKo7jH1453C/XgtfwcOjmoUXhLunLMWN8/I4Si8CXLz0mmSorqlux87T1XjyuxUGbPyPaIoojBf2k89fQ5bP8g11vYKWDulf484n5q8HYtqcsnC5CslRXV9ZzlqO0qhD8uQMavREUURR+tL8Wr+dmwt2Ise08BFrw/W+GPDjBW4I3sN5urS+bblBEuLDcOC9DgcKWuwx/69v4hF9SRrqu9EW3OPJJbFoppcNODYTx0YA1X0NJmyIZocLKrJJZnRcxHmH4OO/iZ77FDVx25dVLf2deHfp/Lwz+PbUdhSM+L1S/XTcMectVg/bQkCNX6TkCGdc/OSaZKiesepKjR19iEmNEDGrHyL4yl1aEQAdInhMmVDnor91OSLWFSTSxSCAguTrsCnxa/bY8dqd2HdzLuhVrrPsg6baMOuipP4Z/52/PfM4RFH4UUHhOKW2Stx++w1HIUno+vmp+Mnb+9Bv2nwv5fVJuKdQ2dw7xVz5E3MhzjepDh9tp7FELmE/dTkq1hUk8sWJl2Bz4rfsE/H6Df34GT9PsxLXC1zZkBNZzNeP7ELr5/YiZpRjMK7In0ubs9eg6sz5kOt5LeD3IL8NLh2Xjq2HDjf5/7WgSLcc3k2C7tJMNhP7VBUs/WDXGTtqIS1U7ogi/OpyRewiiCXRQTGIiN6Dkqaz99UdqjqY9mKapPVjA/PHMGr+duxo/zEiKPwksNicEf2Gtw6exXigzkKz93cvGSapKguMbQjv6oJc1JiZczKN9RXt6GrvU8Sm57NpS/kGud+6miooqfLlA3R5GFRTZdkUfKVkqK6tCUfrb0NiAyMm7Qcippr7KPwWvu7L3qtVqnGuqmLcMectchJ5ig8d7Y4U4fk6BBUNZ8fb/jvfUUsqieB4yi9yJhgROtCZcqGPJWxUlpUa9lPTT6CRTVdkpm6ZfBXB6HffH5KwOHqT3D19Dsn9PP2mPqxtWAf/pm/HYfrSka8fmZMMu7IXoubZ65AuD9H4XkCQRBw05Jp+O22Q/bY+0dK8f82LIO/htsqJ5LjTYrTstlPTa5zPKn2Yz81+QgW1XRJ1EoN5ulXY2/FNnvscPWnuHLabVAI47usQxRFHK47g3/m78DWgr3oNRsven2I1h8bslbgzjlrkR2XxqLAA21YPBW/++AQxLOdPN0DJnx0vAI3Lpoib2JezGYTUeTQT53F1eTkIkt7JawdVZKYlvOpyUewqKZLtij5SklR3dnfgpKm45gaO39cXr+ltxP/OrUbr+XvQFFL7YjXL0ucbh+FF6B2n0kk5Lr4iCDkTEvE7sLzJ6dv7S9iUT2Basqb0dsj/QfrNPZTk4uc+qkDoqCOyZIpG6LJxaKaLllCWAYSQtNR11lmjx2s+nhMRbXVZsWuypN49fh2/O/MYZht1oteHxMYiltmrcLt2auRGclReN7k5qVTJUX1vjN1qGntQmJkiIxZeS/HqR+x8aGIjGHLFLmG/dTky1hU05gsSr4K75z4k/3xacN+9Bo7Eah17eam6s5mvJ6/E6+f2IHartaLXjs4Cm8e7pyzFlemz+UoPC91ZXYqQvw16Oo3AQBEEdhyoBgPX7tQ5sy8U+FxriansWM/NfkyViM0JnP1q7Dt1F9gsZkBAFbRgi9qdyIn/YYRP9ZoMeN/Zw7jn/k7sLNi5FF4qeGxuH32GtwyeyVH4fkAP7UKNyzMxKu7T9tjWw4UY+M1C6BQ8ORrPFmtNhSfqpfE2PpBrhrsp66UxLQpOfIkQyQDFtU0JgGaYMyKX45jtbvssUNVH2NF2vph3/IraKrGP/N34N+ndqNtFKPw1k9bgtuz12BFchZH4fmYm5ZOkxTVNa3d2F9Sh+VTWfCNp8qSJgz0mSQxzqcmVw1UOvZTR0IdM0OmbIgmH4tqGrNFyVfai2qbVcShfUfxx/LnMDNjHnJycqBUKtFt7Mc7hfvw6vHtOFI/8ii8WbEpuDN7LW6asQJh/kET/BWQu5qdFI1p8REoqm+zx97aX8yiepw5tn4kJEciNDxQpmzIUzmtJk/JgaDgQQj5DhbVNGbpUdkID4jFoe352PFyIXpajXgLhwEAMbo4zPvGOpwI6xvFKLwA3DRjBe6YsxZz4tImI3Vyc4Ig4Oal0/Dkf/bZYx8eK8fPv7ICIf6c8DJeHG9SZOsHXQr2U5Ov4z8hacwUggLGojC8/8xx9LRKC+cmQwM++tVf0HG8fNiPX56UhRfWPYCiB1/C767+Fgtqkrhx0RSoLjjtGjBbsO1o2UU+glxhNllQclraT501h0U1ucbSUQVre4Ukxn5q8jU8qaYxs1qtePmZty56Tf9/j0M1PR7C2RvMYgPDcOvsVbg9ew3SI3STkSZ5qMhgf1w+Kxkf5Z//hf32/iLctoKzb8dDeXEjTEaL/bEgAFNnsagm1zjNp/aPgDpmpkzZEMmDRTWNyZmWOvzy1T+hvs5w0evEzn6IVa245sqrcGf2WlyZMQ8qxfhuXiTvddPSaZKi+ouKRpQY2pGpC5cxK+/guJo8KT0aQSF+MmVDnor91EQsqukSdBn78E7BPrx+YicO1Z2BKb96VB/39NJb8e2bvjXB2ZE3Wj0jCdEhAWju6rPH3tpfhMdzl8qYlXcoPC7tp57O1eR0CYzspyZiUU2jYxNt2FNVgNdP7MT7RQfQbzk/fksRPLpTray0zIlKj7ycSqlA7qIpePGz4/bYW/uL8OA18xHsr5EvMQ9nMllQVtQgifEmRXKVpaMalnbpfTPspyZfxKKaLqq6sxlvntiFN07uQlVH05DXKFOiIYT4Q+zqH/J5QRCg1+uRk8MfsnTpbl46TVJUt/cO4KXPjuN76xbJl5SHqyhuhMVstT8WFAKmzIyXMSPyRI6ryRX+4VDHzpIpGyL5sOGJnPSbjXj7dB5ueONJZP/xO3gq761hC2oAiAkKQ+7Dd0MQhGEXvmzatAlKJXuo6dJl6sJxVXaqJPbS9nw0dfYN8xE0kuKTdZLHSWnRCAjkqEJyzQD7qYkA8KSazhJFEV8YSvF6/k5sKdiLLuPFCxWloMBVmfNx2+zVuDJ9LtRKFbbOXoWNGzeitvZ8j2ZwlB/u/9GdyM3NnegvgXzAI9cvxqcnKmETB1fa95sseP7DI/jFVy+TOTPP5FhUT53FU2pynWM/tZb91OSjWFT7uKaeDvz7dB7eyN+JwpaaEa+fFqXHbdlr8JUZOYgJCpM8l5ubi/Xr1+N3rz2Bz0/8D0HhWiRMj4CffyesNguUCv51o7HJ1IXj5qVT8a99RfbYG3sKcfeabKTEhMqYmeexWm0oLZBO7ZkyM0GmbMhTWTprYGmTzo33Yz81+ShWOT7IbLXgk7JjeP3ETnxS+gUsNutFrw/RBmBD1nLclr0a83QZw7Z4AIBSqcQ3vvwAmkKP22O9pk4UN32BrDj2vtLYPXztQrxzuATGs73AFpsNv9l2CH/85hUyZ+ZZqkqbYBwwS2LspyZXOZ5SD/ZTz5YpGyJ5saj2IYXNNXj9xE78++RuNPd1XvRaAQJWpszEbdmrcd2URfBXj77PMjooAcnh01DVfv408WjNdhbVNC504UH4xqpZeOHT4/bYtqOluPeKOZidFC1fYh6m+KR0i2J8UgRCwgJkyoY8lVM/dfIK9lOTz2JR7eU6BnqxtWAvXj+xE0frS0e8PjksBrfOWoVbZq9CUuilFyjzEtdKiurThv3oN/fCXx14ya9JdM63r5qHN/YUoKv//GjHp989gDceXCdjVp7ljEM/NU+p6VKwn5roPBbVXsgm2pBXeRqvndiBbcUHMWAxX/R6f5UG109bgttmr8aK5CwohLGfMszRX4b3T74Iqzi4/thiM+NE3R4sTrlqzK9NFBagxbevmoen3z1gj+0pqkVeUS1ypnHO8khsNhFnTjkU1bPYT02usXTWwtImPaxhPzX5MhbVXqSyoxFvnNiFN09+jprO5hGvX5QwBbfNXo0bpi9FqN/4niAHakIwPW4hThn222NHaz5jUU3j5hurZuKVnSfR2Nlrjz397gEsf+TLUCiG7/snoK6qFb09RklsKm9SJBc5zqcW/MKgjmM/NfkuFtUers9sxLbig3gtfwfyqk6PeH1sYBi+Omslbp29ClOjJvZEb37iWklRXd56Cm29jYgIjJ3Qz0u+wV+jxv9dtwCPvv65PXayuhkffFGG6xdkyJiZ+3M8pY6KDUFkTLBM2ZCncuyn9ktZAUHBfQTku1hUeyBRFHGkvgSv5e/AO4X70GUcepPhOSqFEtdkLsBts1fj8vQ5UE3SD73psQvhrw5Cv7nHHvuidgcun3rLpHx+8n43LZmGv3yWj9LGDnvst9sO4Zq5qVBz2dCwHG9SnMrWD7oExorPJY/ZT02+jkW1B2noace/T+7G6yd24kxr3YjXZ0Un4fbsNbh5xgpEBU7+DF+VUoM5CZdhf+X/7LGjNduxdspXLzqWj2i0VEoFfnD9Ytz7l4/tscrmTvxrbyHuuGymjJm5L1EUnW9S5NIXcpGlqw6WVsd+ai5hIt/GotrNmaxmfFz6BV7L34nPyo7BKtouen2oXyBunrECt81ejey4NNmL1/mJayVFdXNPHWo6ziApfKqMWZE3uXpOKuamxOBYZRMAQLTZ8PMXXoOlYgZSkxORk5MDJU+t7ZrqO9HR1iuJsZ+aXOU49UPwC2U/Nfk8FtVu6nRTFV7L34m3Tu1Ga3/3Ra8VIGBN2mzcNns1vjRlIfxUmknKcmTJEdMRGahDa+/5zW1Hq7ezqKZxIwgCfnTDUty86T30lR9Dx563Ye3twF1vDj6v1+uxefNm5Obmypuomyh26KcOCQ9AbEKYPMmQxzI69lMns5+aiEW1G+no78Hbp/fg9RM7cbyhfMTrU8Njcdvs1fjqrJXQh0RNQoauEwQB8/Rr8Gnx6/bYsbrPsW7Wt6BSqGXMjLzJkinxSDPX4vOP/+L0XF1dHTZs2IAtW7awsIbzfOqpMxNkf0eLPM8A+6mJnLColpnVZsXnlafwWv4O/PfMYRitF58pHaDWYv20Jbg9ew2WJU73iF+G85OkRXWfqQvFjUcxQ7dExqzIm1itVhT99+9DPieKIgRBwEMPPYT169f7fCtI8SnepEhjY+mqh6W1RBJjPzURi2rZlLcZ7DOl67pbR7x+iX4qbstegxumLUWw1n8SMhw/UYHxSInIQmVbgT12tGY7i2oaN3l5eWg01A/7vCiKqKmpweef78aaNasnMTP30tbcjWZDpyQ2lTcpkouc5lNrQ6DWZcuUDZH7YFE9iXpM/Xiv6ABez9+JfTWFI16vCwrHLbNX4dZZq5AR6dm/+OYlrpEU1acbDqDP1I0ADWfj0tgZDIaRLwLw3T9vxU/8dVi/IBNate+dWJ9xOKUOCNIiIcU9W8fIfTn2U2s5n5oIAIvqCSeKIg7WFuO1EzvwbuF+9JgGLnq9WqHEl6YsxO3Za7A6dfakzZSeaHMSLsN7J1+A1Ta4ttxqs+BEfR6WpHxJ5szIGyjbL942dU6zSYXv/3Mnnnn/IL6xahZuz5mB0ADtBGfnPood+qkzZ8Rz+yS5zLGf2o/91EQAWFRPmPruVvzr5G68cWInSttGPkWbFZuC22evwU0zViAiwPtObwM0wciKXYyThr322NGaHSyqacyai2rQ9q8TCFMHoeOCRUOOlEHh0OoGNy02dfbh1+8dxB8++gK3LJ+Ob66ZjYQI7/u+c+R4Us1+anKVtdsAS8sZSUzLfmoiACyqx5XRYsZHJUfw2omd2F5+HDZRvOj14f5BuHlGDm7LXo3ZsamTlKV85ieukRTVFa2n0dprQGSgTsasyJN11rZg28YXYe03Y0PSZfhr2f+GuEoAICJs+QYICoXkmV6jGX/dcQJ/33UK6+an494r5iBL753tEN2d/airkt6/waKaXDXgOJ9aGwJNHPupiQAW1ePiRGMFXsvfibdP56G9f/iTMgBQCALWps3B7bNX4+rMBdCqfGes3LS4hQhQB6PPfH7u9tGaHbhy2m0yZkWeqr+9B9s2voD+tsG/T3PCM3B3+pfwbtN+tHS3269LTNTj2WefQ/jUBXjxs+M4UOJ8Q6PFZsM7h0vwzuES5EzT494r5iBnmt4jpuuM1pnT0q9bo1UhOSNapmzIUzn1UyevgKBkKUEEsKi+ZG193XjrdB5eP7ETJxsrR7w+PUKH22evxldmXYb44MiJT9ANqRRqzNGvxL6KD+yxL2p24Iqpt3pV8UITz9xvxAcPv4TO6mZJ/NorrsEfn92KfQf3w2AwQKfTSTYqrp2VjPzKJrzw2XF8eKx8yHeT8opqkVdUiyx9JO69fA6um58OtReM4XOcT50xXQeVyvO/Lppczv3UOTJlQuR+WFS7wGqzYkfFCbyWvwMflhyByWq56PVBGj/cMH0pbp+9Bov1U1k4YrAF5MKiuqW3HtXtRUiOmC5jVuRJrBYrPn7s72g6XSWJR2bG45rffBMafy1WrVo17Mdnp8Tgz3dfiaqWLry8PR//2leEAbPz93JBbSs2/n07fv3eQXxzzWzcsnw6gvzcZ1upqxxvUmTrB7nK2t0AS0uxJKZN4U2KROewqB6F0tZ6vH5iJ/518nMYetpHvH5Z4nTcnr0G109bjCCNZ82UnmhJ4dMQFZiAlt7zv+CP1GxnUU2jIooiPn/q36jaUyCJB8WFY93m+6ANGv33W3JUCJ78Sg4evnYhXt19Cn/fdRKtPc7Teerbe/Dz/+zD7z44hAVpOizK0GFxhg7ZKTHwU3vGj9D+PhOqyqSn+lNYVJOLBpzmUwdDo5sjTzJEbsgzfiPIoNvYj3cK9+GNEztxoLZ4xOsTgiNxy+xVuG32KqSGx01Chp5JEATMT1yDj4v+aY/l1+7G+ln3cm05jejQC/9D4fsHJTFtaADWPX8fAqNDL+k1w4P8sPFLC3Dv5XOw5WAx/rI9HxVNnU7X9Rkt2F1Yg92FNQAAjUqB2ckxWJwxWGjPT4tDiL97jucrLTBAtJ1vdVGqFEifxp9T5Br2UxNdHL8bLiCKIvbVFOK1/B14r+gA+szGi16vVapx7dmZ0itTZkLpJTOlJ9o8h6K6z9yNoobDmBm/TMasyN2d+s8eHPnbJ5KYUqvGtb+7BxGpYy8Q/TQq3J4zA7cuz8KnJyrxwmfHcbS8YdjrTRYbjpQ14EhZA/748TEoBAHTEyKx6GyRvShDh+iQgDHnNR4cWz9Sp8RCo+WPf3KNUz91CvupiS7En6oAarta8OaJz/HGyZ2oaG8c8fo5cWm4PXsNNmQtR5h/0CRk6F0iA+OQGjkDFa2n7bEjNdtZVNOwynedwO5ntkhigkLAVb/8GnTZ4zuOUqEQcNWcVFw1JxVHyhrw4mfH8cmJCowwIRM2UcTp2hacrm3BK7tOAgBSY0KxOEOHhRk6LMqIR1JksCz3VjjepMh+anKVtacRluYiSUzLpS9EEj5bVA9YTPhv8WG8fmIndlacgIiL/8aM9A/GV2Zdhttmr8aMmORJytJ7zU9cKymqCxsOcW05DcmQX45PnnhV0r4AACsfvRmpK2dN6OdekB6HBelXo6W7D4dKDfb/FdS2jjiHHgAqmjpR0dSJf+0bLEZiQwOxOFOHRemDJ9lTdBETvtHQZLKg/Iz0sIBFNbnKaT61Jgga3VyZsiFyTz5VVIuiiPyG8sGZ0gV70DnQe9HrlYICl6fPxe3Zq3FVxjxolOz5HS/Z8Tl498SfYbENrpe2ihYcr9uNZanXypwZuZO28gb89//+AqtRuoZ8wd1XYUbu5L2zERUcgC/NTceX5qYDALr7TTha3oBDpQYcLK1HflUTTBbbiK/T2NmL94+U4v0jpQCA0AAtFqbH2dtFZiVFj/v4voriRljMVvtjQSEgI4sLl8g17KcmGplPfEe09Hbi36fz8Hr+ThQ0V494/ZTIBNx2dqZ0XFD4JGToe/w1QciKW4wT9XvssaM121lUk11PUwe2PfhnGLv6JPGs9Uux6J5rZMpqULC/BqtmJGHVjCQAwIDZgvyqJhwqMeBQmQFHyxvQM2Ae4VWAzj4jPjtZhc9ODo4H9NeoMDc1FovSdVicqcO81Fj4a8b2j3nHfuqktGgEBLrnDZXkvozspyYakdcW1RabFZ+VHcdr+TvwUelRWGzWi14frPFHbtYy3J69BgviMzlTehLMT1wrKaqr2grR0lOPqKB4GbMid2Ds7sMHG19AT2OHJJ6yYgZW/vAmt/v+9FOrsDgjHoszBv/uWqw2FNa14mBpPQ6fbRkZalyfo36TBfuK67CveLAQVikUmJUUdfYkOx4L0+MQFujnUm6ORfWUmfz+ItdYe5pgbi6UxNhPTeTM64rqMy119pnSjb0dI16fkzwDt81ejeunLUGAmqc3k2la7AIEakLQa+qyx47W7MBV02+XMSuSm9VkwYc/eBmtpQZJPHZmMq781deg8IAtgCqlArOSojErKRp3r8mGKIoob+rAwZLBAvtwmQE1rd0jvo7FZsOxyiYcq2zCi5/lAwCmxkfYT7IXZegQFzb8zdJGowm7d3+Ozu42BGhDEBOezn5qcpnRcT61JgiaePZTEznyiqK6tqsF7xTux9aCvThmKBvxen1IFG6dvQq3zl6FlLDYSciQhqJUqDAnYSX2Vmyzx76o2Y4rp93mdieRNDlEmw2f/eQ11B0tlcTDkmJw7XP3QO2mc6BHIggC0mPDkR4bjltXZAEA6tt6cKis3n7z4xnDyIulAKC4vg3F9W34Z97gjb6JkcGSMX5pMWEQBAFbt27Fd77zABoazv/jJEAbhisr4rBgRcb4f5HktQac+qmXQ+A9RkROBFEcxS3sMrJarcjLy4PBYIBOp0NOTg6USiWaejrwXtEBbC3Yi/21RSO+jp9KjXVTF+O22atxWcpMKATFJGRPI6luL8bznz8kiX0n57dIjZwhT0IkG1EUsefZd3DiX9LezYDIEHz55YcQkhApU2aTo71nAIfLzk4YKTPgZHUzrDbXfzxHBfsjqqsMn77wS2CIqUaCIGDLli3Izc0dh6zJFxh+PwfmpvNbTEOv+AVCL3tExoyI3JNbF9Vbt27Fxo0bUVtba4+Fx0Yh/Za1KIuxjWqk1fz4DNw2ezVys5YjzC9wItOlSyCKIp7Zfg+ae87/N16S8iVsmPNdGbMiOXzxz+3Y//z7kpg6UIsbX3wQ0VP1MmUln94BM76obMShs33ZRysaYTRf/N4QYPC03/DaE7AO0/4mCAL0ej0qKiqgHOdJI+R9rL3NqHta2jIUe08etImLZcqIyH25bVG9detWbNiwAcOlF3DrUqhnDN0bGB0Qap8pPT06cSLTpHHwWfGb+KjwVftjf3UQfnL161ApNTJmRZOp+H+H8dlPXpPEFColrtt0LxIXT5UpK/dislhxsrrZ3i5yuMyArn6T03UDdWfQ/P6mEV/vm0/+AV+94VosSNchLMAz22po4vWd3oqWf33V/ljQBEL/WBPbP4iG4JY91VarFRs3bhy2oAaA/v8eh2p6PISzixNCtAFYN3Uxvpy1HJelzISKK8M9xjz9GklR3W/uQUHDIcxOWCFjVjRZag4WYceTbzjF1/7kVhbUF9ColJifFof5aXG4/8q5sNlEFNe34dDZlpGDpfVo6uyDta9zVK/3zu6j+MQw2AZ37ubHhRlxWJQej/gIboqlQY5LX7RJ7KcmGo5bFtV5eXmSlo+hiJ39UNd24sZrrkNu1nKsSc2GVsVvdE8UERiLtMhZKG89aY8drdnBotoHNBfV4MNH/gabVbo4ZdmD6zHl6gUyZeUZFAoB0/WRmK6PxNdWzoQoiqhq6cLf3wrEzz57ZcSPVwaE2v+/482PCRFBWJSuw4Kzmx8z48InfPMjuSfH+dRazqcmGpZbFtUGg2HkiwD8dvkd+Pr6Oyc4G5oM8xPXSorqosbD6DV2IlAbepGPIk/WWduCbRtfhLnPKIln37ISc25fLVNWnksQBKREh+LH992Gl59+/KIHE8qgcGh1w08AqWvrwTttJXjncAkAICxQiwVpcViYfn7zo8YDRhvS2Fh7W2BuOi2J+XE+NdGw3LKo1ulGt0I3JTFpgjOhyTI7YQXeOfEnWGyDPaLn1pYvT1snc2Y0Efrbe7Bt4wvob5POas64Yi6WP3QDRyqOgVKpxObNm/HlL3/Z6TlBECACuPWBRzAQo8exytHd/NjRK938qFUrMTclFosydFiYHod5qXEI9uc9EN7GcTW5oA6AJmG+TNkQuT+3LKpzcnKg1+tRV1c3ZF/1ubvXc3L4NpS38FcHYqZuCY7Xne/fO1qznUW1FzL3G/HBwy+hs7pZEk9YkInLf3o7BAXHXY7VqpwrsCr7GzhU9A76jB32uF6vx6ZNm+zj9IxmK07VNNtvfDxc1oBOh3cOhmI0W3GgpB4HSuoBAApBQJY+EgvTdViYocOidB1iQgMm5GujyTPgsPSF86mJLs4ti+pzJy0bNmwYPFm5oLA+d4K1adMmjoPyMvMS10qK6ur2YjT31CI6yPfGqXkrm8WKjx/7O5pOV0nikZnxuOY334RS45Y/kjxOyWkDkmOzkRgzC03tZbAK/fjR07dj5crLJD83teoLbn7E4M2PJQ1tOFTacLbINqCurWfEz2cTRZyqacGpmha8smuwjSs5OmTw5sezLSOpMaF8B8LDsJ+ayDVu+xssNzcXW7ZscZpT7XjSQt5jasw8BGpC0Ws6P73gaPUOXJ3FvnlvIIoidj31b1TtKZDEg+LCsW7zfdAG+cuUmfc5c/rcCbICcRGZyF6UgjVrRu5TVygETI2PxNT4SNxx2eACprq2bvtSmsNlDSiubxtVDlXNXahq7sLbB4oBDC6lWZgeZz/NnqGPgkrJdyXclbW3BebGU5IY+6mJLs5ti2pgsLBev379kBsVyfsoFSrM069CXvl79tjR2h24cvrt3IDpBQ69+CEK3z8oiWlDArDu+fsQGM0bUsdTydmi+pzMmfGX/FoJEcFIiAjGDQunAAA6egdwpLzBXmSfqGqC2WF6y1Bauvvx4fEKfHi8AgAQoFVhXmocFqbHYVGGDnNTYhGgZWuBuzBW7ZE8FtQB0MSzn5roYty6qAYGW0FWrVoldxo0SeYnrZUU1e19jahsLUBa1EwZs6KxOrV1L468/LEkptSqce2z9yAiNU6mrLxTX68RNRUtklhm1qUX1Y7CAv1w+awUXD4rBQAwYLIgv6rJ3pd9pLwBPQPmkfM0WrCnqBZ7igbfiVQpFJiZFGVvGVmYEYcIvnshG+f51MsgqHgzKtHFuH1RTb4lITQDMcGJaOqusceO1mxnUe3BynedwO5fvy2JCQoBV/7ya9Blp8qUlfcqK2yAaDt/H4pKrUTq1NgJ+3x+GhUWZ8ZjceZg4W612VBU12Yvsg+VGdDU2Tfi61hsNhyvbMLxyia8tD0fAJARG4aFGef7shMjg9mXPUnYT03kOhbV5FYEQcD8xLX4sODv9lh+XR5umH0/1Fxb7nEM+eX45IlXJUUeAFz26E1IWzlLpqy82xmH1o/UKTHQTOINoEqFAjMSozAjMQrfWD3LvpTmcJkBh8+2jJQ1dozqtUobO1Da2IE39xYCAGJDA+1j/BZl6DA1PgJKTosZd9a+VpgbT0pi7KcmGhmLanI78/Sr8VHBPyBisBAbsPSioOEgshN4UuJJ2ioa8N//+wusRmkrwIJvXoWZuctlysr7lZxy6KeeMX6tH5fi3FKalOhQ3LRkGgCgpbsPR8rO92WfqmmG1eY8PtVRY2cvth0txbajpQCAEH8N5qcN9mUvzNAhOzkGfmr+WhsrY6VjP7U/NAnccEo0Ev70IbcTHhCDtKjZKGvJt8eO1mxnUe1Beps7se3BF2Dskr7tP339Eiy69xqZsvJ+FrMV5cUNktgUmYvqoUQFB+DqOWm4ek4aAKB3wIxjlY32lpEvKhrRb7KM+Dpd/SbsPF2NnaerAQAalQKzk2MG20XSdZifHoewAO2Efi3eyOgwn1qTuJT91ESjwKKa3NL8xDWSorqo8Qh6jB0I0obJlxSNirGnH9s2voCehnZJPHlFFlb98Gb2xE6gytImmIzSYjRjHG9SnCiBfmqsmKbHimmDM+nNVisKalpxyN4yYkBrz8CIr2Oy2HCkrAFHyhrwZxyDIABTdRFnW0YG+7J14UET/eV4vAGHfmq/1MtkyoTIs7CoJrc0O3453jnxJ5itg9vdbKIVx2s/x4r09TJnRhdjNVnw4ff/itYSaQtCzIxkXPWrr0Oh4jjMieTY+pGQHImgED+Zsrl0aqUS2SkxyE6JwbfWZkMURZQ3ddjbRQ6VGlDd0jXi64giUFTfhqL6Nry6+zQAQB8RfPbmx8G+7IzYcCgU/IfeOda+Nqd+ai37qYlGhUU1uSU/dSBm6pbiWO0ue+xozQ4W1W5MtNnw2U9eQ93ZftdzQpOicd1z90Dtz7fhJ5rjTYpTxjCf2p0IgoD02HCkx4bjluVZAICGjl77avXDpQYU1LVAHLktG7Vt3ag91I13Dp0BAIQFagdH+J0tsmcmRkPjw//4M1btwYV/kILaH1r2UxONCotqclvzEtdIiuqajjNo6q5BTHCifEnRkERRxN5N76L0s2OSuH9EMK5//n748y33CSeK4rgufXF3cWGBWDc/A+vmZwAAuvqN+KK80b798XhlE4wW64iv09FrxKcnKvHpiUoAgJ9ahbkpMViYMdiXPS8tFkF+vtNPbKxw7KdeAkHFfxATjQaLanJbU6LnIVgbjm7j+d7cozXbcU3W1+VLioZ0/LWdyH9T2oepDtBi3fP3ISQhUqasfIuhph09XdK+Y3e8SXGihPhrsWpGElbNSAIAGM1WnKxuthfZR8ob0NlnHPF1BswW7C+px/6Sc6veBWTpI+092QvTdYgJDZjQr0VOTv3UKeynJhotFtXktpQKJebqV2F32Tv22NGanbhq+p1cW+5Gij88gn3PvyeJKZQKXPPMXYieqpcpK9/jeEodERWEyJhgmbKRn1atxIL0OCxIj8P9V86FzSaipKFN0pdd394z4uvYRBGnalpwqqYFr+wa7DVOiQ61t4ssTNchNSbUK27AtfW3w9x4QhJjPzXR6LGoJrc2P3GNpKju6G9CecspZETPljErOqfmYBF2PPmGU3zNT25D4uJpMmTkuxz7qTNnxntFoTdeFAoBU+MjMTU+EndcNrihta6t+/zmx1IDzhjaR3iVQZXNnahs7sTbB4oBAFHB/vZZ2QvTdZihj4JK6Xn/8B+odOinVvlBq18oY0ZEnoVFNbm1+NB0xAYno7G7yh77omY7i2o30FxUgw8f+RtsDn2rSx+8HlOv4Y1Nk83dlr54goSIYNy4KBg3LpoCAOjoHRi88fHsKL8T1c0wW20jvk5Ldz8+PF6BD49XAAACtCrMS42zb3+clxoLf416Qr+W8eA8n5r91ESuYFFNbk0QBCxIWov/nv6bPXaifg9uzP421Er+sJdLZ20Ltm18EWaHHtXZX12JubevkSkr39XR2osmQ6ck5kv91OMlLNAPV8xOwRWzUwAAAyYLjlc2DZ5klxlwtLwBPQPmi78IgD6jBXuKarGnqBYAoFIoMCspyt6XvSA9DhFB/hP5pVwSzqcmGhsW1eT25upX4X+nX7lgbXkfThsOYI6evX5y6G/vwbaNL6C/rVsSz7h8LlY8fANbDmRQUiA9pfYP0ECfwhtEx8pPo8KSKfFYMmXwHyhWmw2Fda04XNqAQ2dbRpodtoYOxWKz4VhlE45VNuGl7YNLrTLiwiV92YmRwbJ+79j622FuyJfE2E9N5BoW1eT2wvyjkRGdjZLm4/bYkZrtLKplYO434oOHX0JndbMknjA/A5f/7HYICs/rI/UGZxxaPzKydFB4YE+vu1MqFJiZGI2ZidH4xupZEEURVS1d9naRQ6UGlDd1jvxCAEob2lHa0I439xYCGBwReH7CSBymxkdAOYnfTwNVe537qRPYT03kChbV5BHmJ66VFNVnmo6ie6AdwX7h8iXlY2wWKz5+7O9oOl0liUdmxuOa394NpYY/TuTiNJ+arR+TQhAEpESHIiU6FDctGbwxt6W7D4dLG+w3P56ubYHVNvJWmoaOXmw7WoptZ5cnhfhrMD8tbnAxTUYcspNj4KeeuO8x5/nUiyGoPW8bJ5Gc+FuQPMKs+OX4T/4fLlhbbsPxus+Rk36DvIn5CFEUseupf6NqT4EkHhQXjnWb74PWDftDfUV/nwlVZdJ3Drxlk6InigoOwDVz03DN3DQAQO+AGV9UNg6eZJcZcKyiEf0my4iv09Vvws7T1dh5uhoAoFEpMDs5BovSB9tFFqTHITRg/O4rGajkfGqisWJRTR5Bq/LHLN0yfFG70x47Ur2dRfUkOfTihyh8/6Akpg0JwLrn70NgdKhMWREAlBc1QLzgJFSpUiB1SqyMGdGFAv3UyJmmR860wZntZqsVp2ta7LOyD5cZ0NYzMMKrACaLDUfKGnCkrAHAMQgCMC0+UtKXrbvEzaW2/g6YDcclMfZTE7mORTV5jPlJayVFdV1nKaraCpEcMV3GrLzfqa17ceTljyUxpVaNa5+9BxGpcTJlReecOVUneZySGQOtn/uPb/NVaqUSc1JiMSclFt9amw1RFFHW2GFvFzlc1oDqlq4RX0cUgcK6VhTWteLV3acBAImRwVhwQV92Zlz4qG5+NFZL+6mh0kKrX3TJXyORr2JRTR4jM3oOQvwi0DXQZo+9fuQZPLzq9/DXXNoJDV1c+a4T2P3rtyUxQSHgyl9+DbrsVJmyogs5LX1hP7VHEQQBGXHhyIgLxy3LswAADR09g/OyzxbZBXUtkpp3ODWt3ahp7cY7h84AAMID/bAgPW6wZSQjDjMTo6FRKZ0+rrd0F/ZX2tDUA8QEATmXLWI/NdElEERxNN+qRO7hs+I38VHhq5LYTN0yfG3RExzlNs4M+eV47zt/gtUoncu78kc3Y2bucpmyogtZLFZ8O/cFmIzne3Qf/Ml1mLcsXcasaLx19RvxRXmjvV3keGUTjA5Ll0bDT63C3JQYLMzQYVG6DnNTY/Hphx/ggW/eAkOHyX5dfHQIfv/CK8jNzR3PL4PI67GoJo9itVnw5z2PorJNesPc9TPvwWUZN8qUlfdpq2jA1rs3w+gwg3fBN6/C4vu+JFNW5Ki8uAFPPvhvSez3b92D4FDeOOrNjGYrTlY349DZUX6Hywzo6jeN/IEOBsqPo/njl5zig+cTArZs2cLCmsgFLKrJ43T0NePZXQ+gz3S+71AhKPGdnN8iOWKajJl5h97mTmy56zn0NLRL4tPXL8Hqx7/KdwTcyMdbv8CbL+bZH8cnReBXf7lDxoxIDjabiJKGNntP9qFSA+rbey76MaLNBsNrT8Da2zHk84IgQK/Xo6KiAkqlc8sIETljTzV5nLCAaNwy//t4ef//s8dsohX/PPwU/m/1HxCgCZYxO89m7OnHto0vOBXUySuysOqHN7OgdjOOS1/YT+2bFAoBU+MjMTU+EndcNhMAUNfWjUOlBnvLyBmD9HvaaCgdtqAGBsdo1tTUIC8vD6tWrZrA7Im8B4tq8kjTYxdizZSvYMeZ8299d/Q34c2jv8U3lvwECoHb5FxlNVnw4ff/itYSaaEWMyMZV/3q61AMcYMTyUcURaelL1NYVNNZCRHBuHFRMG5cNAUA0NE7MHjz49mWkX1lR0f1OgaDYSLTJPIqLKrJY1017Q5Utp5Geespe6yw8RA+L92K1ZkbZMzM84g2Gz77yWuoO7vN7ZzQpGhc99w9UPuP35IJGh+N9R3o6uiXxDK59IWGERbohytmp+CK2SkAgE/mhOKqT14e8eN0Ot0EZ0bkPXicRx5LqVDitgU/RKBGunzkw4JXUNF6WqasPI8oiti76V2UfnZMEvePCMb1z98P/0tcKEETq8Sh9SMsIhDRcSEyZUOeZu2aVUjQxWC4hi5BEJCYmIicnJxJzYvIk7GoJo8W6h+J2xY8AuGCXw020YbXDj+FXmOnjJl5juOv7UT+m9IVxeoALdY9fx9CEiJlyopGMtR8ava802gplUo8/Z1rAMCpsD7392jTpk28SZHIBSyqyeNNiZmHy6feIol1DrTijaO/hU20yZSVZyj+8Aj2Pf+eJKZQKnDNM3cheqpepqxoNJz6qdn6QS66KrUHf96gRJzDvd16vZ7j9IguAXuqyStcMe1WVLSeRmlLvj1WaDiM5177KeJV06HT6ZCTk8NTlwvUHCzGjiffcIqv+cltSFzM0YTurKujDw21HZIYJ3+QK0RRhLH6AK6ZpsCVUwQcqhbRl3UPUpfezJ+VRJeIRTV5BYWgxK0LHsFzOx9At7EdJfsbsOPlQvS0fmy/Rq/XY/PmzTx9AdBcXIsPH3kZNoetbEsfvB5Tr1kgU1Y0Wo6n1H7+aiSmRcmUDXkiS1sZbL1NAAClQsDSFAG6e78HdQS3cRJdKrZ/kNcI8YvAbQseRcn+Jrz/zHH0tBolz9fV1WHDhg3YunWrTBm6h666Vmx78AWY+6R/PrO/uhJzb18jU1bkCsf51OnTdVAq+eOcRs9YvV/yWBEYA1V4mkzZEHkH/hQmr5IaMRP7Xq0c8rlzy0MfeughWK3WIa/xdv0dPXj/wT+jv61bEs+4fC5WPHwDb3TzEI5FNedTk6tMDkW1Nmkpv/+JxohFNXmVvLw8tDS0Dfv8hVvCfI2534j/PvwSOqubJfGE+Rm4/Ge3Q1Dwx4EnMA6YUVXaJIlxPjW5yvGkWpu0VKZMiLwHf4uSVxnt9i9f2xJms1jxyWP/QOOpKkk8MkOHa357N5Qa3l7hKcqKGmCzifbHCoWA9GlxMmZEnsbW3wFzc4Ekpk1aJlM2RN6DRTV5ldFu/xrQDH+a7W1EUcSup99C5R7pQpyguHBct/k+aIP8ZcqMLoXj0pfkjBho/dQyZUOeyFh7EBDP/8MMKi008XPlS4jIS7CoJq8yrb8dMX6ai14THOWHU/gA28/8295n7c0OvfQhCt87IIlpQwKw7vn7EBQTJk9SdMkcl75wPjW5yli1T/JYGz8fgkorUzZE3oNFNXmNzqMHUPfX3+P7szMuet3qu6ZBUAIfFvwdbxx9Bmar8aLXe7JTW/fiyF8/lsSUWjWuffZbiEhly4CnsVptKCuUti6xqCZXGWuk/8jWJC2RKRMi78KimrxCX9kZlP/2p4DNijXxUXhmUZbTiXVkbBiuf2QOMpeeLyaP1e7Cn/Y8iq4B72sHKf/8JHb/+m1JTFAIuPIXd0KXzdFZnqimvAUD/WZJjEtfyBWi1QJT7SFJjP3UROODRTV5PGOTASW/fBS2gX57bE18FA6/+Dx27tyJN954Azt37kRDbTMevvtxCJCOjappL8bmXQ+ipv3MZKc+YQz5Ffjk8X9AtEnbWy57ZAPSVs2WKSsaK8elL3H6MISEBciUDXkic+NJiKZeSUybyJNqovHAW/7Jo1l6ulH680dhaZeeNEesvAKJd9yDJIe5q6syNyAmOBGvH/k1jJbzRXjnQCv+mPcDfHXe/2GOfuWk5D5R2isb8d/vvQSrUXqiueCuKzHzyytkyorGg+N8ap5Sk6uM1dJ+alVkBpRBMTJlQ+RdeFJNHstmNqHs6ScwUCsdExc8cy6Sv/PosIsMsuIW47uXPYfIAGlPscVmwmtHnsZHha/CJtomLO+J1Nvcife/+2cYO/sk8enXL8ai+74kU1Y0HkRRdDqp5tIXchXnUxNNHBbV5JFEmw2Vv38aPaePS+J+ialI++HPoVBffMRYXEgyHly5CelRzq0QnxW/iX8e+hWMloHxTHnCGXv6sW3jC+hpaJfEk5dnYeWPvsJtaR6uuaELHW3St+259IVc5VxUs5+aaLywqCaPVP/6X9Get10SU4dHIvPHv4YqMHhUrxGoDcU9y36JJSnOJ7gnDXvxx93fQ1tf47jkO9GsJgs+/MHLaC2RnmTGzEjGVU99HUqVUqbMaLw4zqcOCfNHbHyYPMmQR7J01sDaWSOJadhPTTRuWFSTx2n+6D00bH1dElP4+SPjiaehiY516bWUChW+nP0Abpz9bSgE6bdDfVc5nv/8IVS2Fgzz0e5BtNnw2U9fQ92REkk8NCka1z13D9T+nD/rDYpP1UkeZ86I57sP5BLHU2rBLwzq6OkyZUPkfVhUk0fpOLwP1X/ZJA0qlEh75EkEpE25pNcUBAHL09bh7qW/gL86SPJcj7EDf977KA5XfXqJGU+8vZvfQ+mnxyQx/4hgrNt8H/zDg4b5KPI0Tv3UbP0gFxmrHZZAJS6BoGAZQDRe+N1EHqO3tAgVv/sZYJPeRJh8//cQOnfRmF9/SsxcPLhyE6KD9JK41WbBv489i22n/gKbaB3z5xlPx17bgfw3dkli6gAt1m2+F6H6KHmSonHX1dEHQ420V56TP8hVJofJH7xJkWh8sagmj2BsNKD0Fz+EzSi9eVB3052Iuvzacfs80UEJePCy5zA1Zr7Tc5+XbsXfDvwM/ebeIT5y8p356Aj2bX5PElMoFbjmmbsQPS1RpqxoIpQWSLcoarQqJKVHy5QNeSKbqRemhnxJjEU10fhiUU1uz9LdhdKfPwJLp/SkLmLVldDdcte4fz5/TRDuWvIzXJZ+o9NzRY2H8fvdD6Olp36Ij5w8NQeLsf1nbzjF1/y/W5G4eJoMGdFEOuPQ+pE+PQ4q3nxKLjDVHgZsF7zTplBCo18oX0JEXohFNbk1m8mIsqcfx0BdtSQePHs+kr/9yITdqKVUKHH9rHtw89yHoBSkO5Kaumvw/OcPobQ5f5iPnljNxbX48JGXYbNIW1GWfvd6TP0Sf0l6I86nprFyvElRE5cNhSZQpmyIvBOLanJb9lnUBSckcb+kVKQ/8uSIs6jHw6Lkq3DfiqcQqAmRxPvM3Xhp3+PYV/HBhOdwoa66Vmx78AWY+4yS+OyvrsTcO9ZMai40OYwDZlSWNEli7KcmVxlrpDcpajifmmjcsagmt1X32kto37NDElNHRCHzx89AGTh5Uy1SI2di48rnoQtJkcRtohVb8/+Irfl/hNVmmfA8+jt68P6Df0Z/W7cknnH5XKx4+AaOV/NSFWcaYbWcvzlXoRCQPl0nY0bkaUSbbYilL5xPTTTeWFSTW2r68B00vvOmJKbwD0DGE7+GJipm0vOJCIzFA5c9ixlxzjf27Kv4AH/Z9wT6TN1DfOT4MPcb8d+HX0JndbMknjA/A5f/7HaOxfJiZxyWviSlR8M/QCNTNuSJLC1FEAc6JDFuUiQaf/xNTG6n49Be1Pz1eWlQqUT6I08iIDVDnqQAaFX++NriJ7B2ylecnittycfmzzeisbt6iI8cG5vFik8e+wcaT1VJ4pEZOlzz27uh1KiG+UjyBo791Gz9IFc5nlIrQxOhCtUPczURXSoW1eRWeksKUT7kLOrvI2SO/DfhKQQFrsn6Om6d/whUCmlPd2uvAb///GEUNh4et88niiJ2Pf0WKveclsSD4sJx3eb7oA3yH7fPRe7HZrU5jdPj0hdylXPrB0fpEU0EFtXkNowN9Sj95Y8gmqQ34em+8nVErf2STFkNbV7ianw75zcI8YuQxAcsffjb/p/i89KtEEVxzJ/n0EsfovA9hy1oIQFY9/x9CIoJG/Prk3urrWxFf59JEsvMYlFNrjFy6QvRpGBRTW7B0tWJkiFmUUeuuRq6r3xdnqRGkBQ+FRtXboY+LFMSF2HDtlN/wb+PPQeL1TTMR4/s1Na9OPLXjyUxpVaNa5/9FiJS4y75dclzOM6njtGFIiySY9Bo9Ky9zbC0lkpi7Kcmmhgsqkl2NpMRpU89DmN9jSQenL0Ayff/wK2nWoT6R+E7Ob/BnISVTs8dqf4UL+z9EbqNHS6/bsXnJ7H7129LYoJCwJW/uBO67LRLTZc8jONNipls/SAXObZ+CJpAqGNnyZQNkXdjUU2yEm02VG7+FXqLTkri/inpSH/kSQgq978JT63U4rYFj+Lq6Xc6PVfZVoDNuzaivrN81K9nyK/Ax4//A6JN2j5y2SMbkLZq9pjzJc8giiLOnKqTxLj0hVzltPRFvwiC0v1/rhJ5IhbVJKu6V19A+75dkpg6MhoZjz8NZYDnvM0tCAIun3oLvrboCaiVWslzHf1N+MPu7+Fk/d4RX6e9shH//d5LsBrNkviCu67EzC+vGNecyb21NHajo7VXEuPkD3KVyfEmxUTOpyaaKCyqSTZN//0PGt/7tySmCAhE5o/lmUU9HmbFL8cDOb9DmL80f5N1AP849At8VvzmsDcw9jZ34v3v/hnGzj5JfNq6xVh0n3vdqEkTz3GUXlCIH3SJ4TJlQ55ItBhhrD8qiWmT2U9NNFFYVJMsOg7uQc3Lv5cGz86i9k9OlyepcZIQlo6NqzYjJSLL6bmPCl/F60d+DbNVOuHE2NOPbRtfQE+D9EbN5OVZWPXYV9y6r5wmhmPrR+aMeP49IJeY6o8Blgt+1ggCtPrF8iVE5OXYWEWTrvdMAcqffRJwOLFN+fYjCMleIFNW4ytYG4b7lj+F/+T/AYerP5U8d7zuc7T01uPOBY/jxJFC1NXUouLtwwitt0EhnP93bsyMZFz11NehVCknO31yAyWnHeZTs/WDXGSskbZ+qKOzoPAPkycZIh/AopomldFQN/Qs6q9+A5FrrpYpq4mhUmpw89yHEReSgg9OvQwR5xfa7PwwDz+5KQ1dLedbPcLUQdiQdBnmhGcgNCka1z13D9T+2qFemrxcT9cA6qpaJTFO/iBXGas4n5poMrH9gyaNpatjcBZ1V4ckHrn2S9Dd/DV5kppggiBgZUYu7lr6U/ipAgAAJfsb8P4zxyUFNQB0mHvw17L/ocBci3Wb74N/eJAcKZMbKC2Q9lNrtCqkZHjmfQYkD1EUYayRLo7SsKgmmlAsqmlS2IxnZ1EbaiXxkDkLkXzf97y+V3R67EJ8d+VzCPeLxY6XCy967buN+xGk4w1pvsxx6Uva1Dio1GwDotGztJfD1tMoifGkmmhisaimCSdarajY/Ev0Fp2SxP1TMpD2g595xCzq8RAbnIR5ypvQ02q86HX1DQbk5eVNUlbkjhwnf7D1g1zlOEpPERgDVYRn3wRO5O5YVNOEq/3Hn9Gx/3NJTB0Vg4wf/9qjZlGPh46WrlFdZzAYRr6IvJLJZEHFmSZJjDcpkqscl75ok5Z4/TuCRHJjUU0TqnHbFjRtk67bVgQEIvOJX0MTESVTVvLR6XSjui48KnSCMyF3VXmmERaz1f5YUAjImB4nY0bkiZyLas6nJppoLKppwrQf2I3aV/4giQkqFdIf/QX8k9NkykpeOTk50Ov1Fz0xCo7ywwm8h87+lknMjNyFYz91YmoU/AM5BYZGz9bfAXPTaUmM/dREE49FNU2InqJTqHju506zqJO/8whCZs+TKSv5KZVKbN68GQCGLaxX3zUNTb3V+P3u76Gpu2Yy0yM3cOaUQz81Wz/IRcbaQ9KfvUoNNPG++3OXaLKwqKZxN1Bfi9JfPQbRZJLE42+9G5GrrpIpK/eRm5uLLVu2ICEhQRIPiQ7A9Y/MQebSwbf6O/qb8Ie876OqrUiONEkGNpvodJMi+6nJVcZq6XxqTcJ8CCq+20E00VhU07gyd3ag9BePwNrdKYlHXX4t4jbcLlNW7ic3NxeVlZXYuXMn3njjDezcuROlpSVYdsV8yXV9pi68sPeHKGo8IlOmNJnqqlrR3yv9x2jmjNH14ROdY6yWzqdm6wfR5GBRTePGZhxA2a9+BKOhThIPmbsISff+H+88d6BUKrFq1SrccsstWLVqFaJD4vFAzu+QGD5Vcp3ZasQrB36GE3V7ZMqUJkuJQ+tHVGwIIqKDZcqGPJFotcBUe1AS0yayqCaaDCyqaVyIVisqnvsFes8USOL+aZk+NYt6rAK1obhv+dOYGrNAEreKFvzz8FM4XP2pTJnRZHC8SZHzqclV5saTEE29khhPqokmB4tqGhe1f/8TOg5KF5ZoomOR8fjTUPoHyJSVZ9Kq/HDXkp9gnn6NJC7Chn9/8Sz2ln8gU2Y00dhPTWPlOEpPFZEBZRBX3BNNBhbVNGaN295G0wdbJDFlQBAyfHQW9XhQKlT46vzvYWnKl5yee+fEH7HjzFsyZEUTqbWpC61N3ZIYi2pyldN86mSeUhNNFhbVNCbt+z9H7St/lMQElQrpP/oF/JNSZcrKOygEBXKzH8CqjA1Oz/2v4BV8WPAPiA4jC8lzlZyWbtEMDNJClxQhUzbkqZyKavZTE00aFtV0yQZnUf/CaRZ1ynd/iOCZc2XKyrsIgoBrZ9yFq6ff6fTc9jP/wnsnX4RNtMmQGY03x37qjBnxUCh4cy+NnqWzFtbOaklMw35qoknDopouyUBdzeAsarPDLOrbv4WIy66QKSvvJAgCLp96C66feY/Tc3vK38OWY5thE61DfCR5EsfJH2z9IFc5nlILfmFQR0+XKRsi38Oimlxm7mhHyc+HmEV95TrE5d4mU1be77KMG3HTnIcgQHp6eaj6E7x+5BlYbGaZMqOx6u0xorZSupZ+Cid/kItMNQ7zqROXQFDw1zzRZOF3G7nEZhxA6a9+BFOj9FQtZP4SJN3zEGdRT7DFKVfh1gWPQCEoJfH8ut34x8FfwGw1ypQZjUVZoUHSRaVSK5GSyYkN5BrHTYrapCUyZULkm1hU06iJVivKn/05+koKJfGAtClI+95PICg5i3oyzNWvwtcWPQGVQi2JFzYewl/3/wRGS79MmdGlOuPQ+pE2NRZqDb+faPRspl6YDMclMW3SMnmSIfJRLKppVERRRM3ffo/OQ9KtfproOGQ8wVnUk22Gbgm+ufRnUCu1knhZSz5e2vsY+kzdw3wkuSPOp6axMtUdAWwX3FuhUEKjXyhfQkQ+iEU1jUrT+2+h+X/vSGLKwCBk/PjXUIdHypSVb8uMnot7l/0KfqpASbyqvQgv7P0huo0d8iRGLjGbLCgrapDEuEmRXOV4k6ImLhsKTeAwVxPRRGBRTSNq37sTtX//kyQmqNRI/9Gv4J+YIk9SBABIiczC/SueRqAmRBKv7yzHn/MeQUd/s0yZ0WhVljTBYj5/wigIQMZ0nYwZkSdyKqo5So9o0rGopovqKTiBis2/coqnPPhDBM/IliEjcpQQloFv5/wGIX7Sdwyaemrwx7wfoLXXMMxHkjtwbP1ISIlEYLCfTNmQJxJtNufJHyyqiSYdi2oa1kBdNUqfetxpFnXCHfciIudymbKiocQGJ+E7Ob9BRECcJN7e14g/5n0fDV1VMmVGI3Fc+sJ+anKVpaUYtv52SYxFNdHkY1FNQzJ3tA3Oou7pksSjr16P2BtvkSkrupjIQB2+k/MbxAQlSuJdA234855HUNtRKlNmNBybTXRaT57Joppc5Nj6oQxNhCo0cZiriWiisKgmJ9aBfpT+8kcwNUp/2YcuWIrEux/kLGo3FuofhftznkF8aJok3mvqwgt7HkVla4FMmdFQDDVt6O0ekMS49IVcZayRFtXaRM6nJpIDi2qSEK0WVDz7JPpKiyTxgIypSOUsao8QrA3D/ct/jeQI6XriAUsfXtz3GM40HZMpM3Lk2E8dER2EyJiQYa4mGpqxymHpSzLnUxPJgUU12YmiiJq/Po/Ow9If0JqYOGQ8/jSUfv4yZUau8tcE4Z5lv0RGlPRmUrPViJcP/D+cNhwY5iNpMjkufWE/NbnK2tsCS2uJJKZNZD81kRxYVJNd47v/QvNH70liyqBgZP74GajDImTKii6VVuWPby59EllxiyVxq82Cfxz6OY7V7pInMbJzPKnmfGpylWM/taAOgDputkzZEPk2FtUEAGjbswN1r74giQ3Oov4l/PTJMmVFY6VWavC1RU9gTsJlkrhNtOGNI8/gYOVHMmVG7S09aG6Q3gjMk2pylcmhn1qjX8Q2PSKZsKgmdJ/OR+VQs6g3PobgLM6i9nRKhQq3LngEi5KvksRFiHj7+GbsLn1nmI+kieR4Su0fqEFCMreTkmscT6q1SbxJkUguLKp9XH9NJcqeegyixSyJJ3ztfkSsWCNTVjTeFIISN83ZiJy09U7PvX/qJXxS9DpEUZQhM9/lOJ86c0Y8FEr+SKbREy0mGOuOSGLaJN6kSCQX/gT3Yeb2VpT+4lFYe3sk8ehrbkTs+q/IlBVNFEEQcP2se3H5FOc5458UvYYPTr/MwnoSOZ5Us/WDXGUyHAMsRklMm7h4mKuJaKKxqPZR1v6+wVnUTQ2SeOjC5Uj85nc5i9pLCYKAq7PuxLUz7nJ67vPS/2Br/h9gE20yZOZb+nuNqC5vkcS49IVc5dj6oY7JgsI/XKZsiIhFtQ8SrRZU/O5J9JUVS+IBmdOR9r3/B0GplCkzmiyrM29CbvZ3nOL7K/+Hfx39Haw2qwxZ+Y7SwgaItvPvCqjUSqROjZUxI/JExmqH8adcTU4kK94i7GNEUUT1Xzaj86jDHeOxOmQ89hQUWj+ZMqPJtiz1OmiV/vjXF89CxPnT6S9qd2DA1Ifk/mVoamqBTqdDTk4OlPzH1rhx7KdOyYyBRsMfxzR6oijCWC2dN69lUU0kK/4U9zGN77yJlo/fl8SUQSFnZ1HzbUNfMz9pLTQqP7x2+GlYRQsAoGR/A158+Sn0tJ7v1dTr9di8eTNyc3PlStWrlHDpC42Rtb0Cth5p+x6LaiJ5sf3Dh7Tt/hR1/3xREhPUGmQ89iv4JSTJlBXJbVb8cty15KdQK7Uo2d+A9585LimoAaCurg4bNmzA1q1bZcrSe1jMVpQXS4shLn0hVzn2UysCo6GKyJApGyICWFT7jO5Tx1H5+19Lg4KA1IceR9D0WfIkRW5jaux8fGPRT7Hz5aIhnz83FeShhx6C1cp+67GoKmuGyWiRxDKzdDJlQ57KaT514hLeYE4kMxbVPqC/phJlTz/uNIta/7X7Eb5slTxJkdupL+xAd+vAsM+Looiamhrk5eVNYlbe54xD60d8UgSCQvxlyoY8lVNRncz51ERyY1Ht5cxtrSj9+SPOs6ivzUXM9TfLlBW5I4PBMK7X0dCc5lOz9YNcZBvohLnplCSmTWQ/NZHcWFR7MWt/H0p++ShMzY2SeNjiFUj8xgN8q5AkYiM0o7qu3lzAJTGXSBRFp6Ka86nJVcbaQ8CF34NKDTTx8+RLiIgAsKj2WqLVgvLf/hT95SWSeOCULKQ+/GPOoiYJm6kDc4SnER8JXOyfWsFRfqgLPIw3j/4GZqtp0vLzFg21Heju7JfEeFJNrjJWOcynjp8HQc1xqERyY1HthURRRPWLz6Hri4OSuDYuAemcRU0ORGs/eg7cBPScwq/uUgMYvrBefdc0KJQCvqjdiRf2PIrugfbJS9QLnDldJ3kcFhmIqNgQmbIhT2WqcZxPzX5qInfAotoLNfznNbR8+oEkpgwORcaPn4E6NEyepMgtiTYLeg59DZaWPQCAdUuUeOUHauiipCPsY3SRuP6RuchcGmePVbUXYfPnG1HfWT6pOXuyoeZTsw2LXCFaLTDWOByYJC2RKRsiuhCLai/TuusT1L/+V0lM0JydRR2vlykrckeiKKLv+IMwG7ZJ4tevTEBFWSF27tyJN954Azt37kR9TSOeevgFaFXSKRUd/c34w+7v4bRBenJGQ3O+STFBpkzIU5mbTkE0SW8859IXIvfAjYpepPvkF6j641CzqJ9A0LSZ8iRFbqu/4GcwVr4iiQmqEAQvfw+qkAysWiVdJJEVtwgPXPYs/nbgp2jvO3/zq8k6gL8ffBJXTb8DS1O+hEBt6KTk72k62nrRWN8piXHpC7nKcZSeKiIdyqBYmbIhoguxqPYS/VXlKHv6xxAt0qUS+m98B+FLV8qUFbmrgbI/YaDY4R9gCi2Clm6BKmz2sB+nC0nBgys34R8Hf47KtgJ7XISIjwpfxUeFryI6SI+UiOlIiZiB1MgsRAfp2eIA51NqvwANElMiZcqGPJXTfGqeUhO5DRbVXsDU1oKSXzwKa5/0LcGYdTchdt1NMmVF7spY8xb68r/vEFUgaNGrUEfnjPjxwdow3Lf8Kbx9/Hkcrdnu9HxzTy2ae2pxuPpTAECAOhjJEdORGjkDyRHTkRQ+BWqldjy+FI/iuPQlY7oOCiU78Mg1jkW1hkU1kdtgUe3hrP19KP3FozC3NEniYUsug/5r98uUFbkrc+N29B65G4B0znTA3D9AE3/9qF9HpdTgq/O+h7iQZPzv9CsQMfzc6j5zNwobD6Gw8RAAQCmokBCWjpSIrMH/RWYhxC/ikr4eT8KlLzRWlq46WDuqJDGeVBO5DxbVHky0WFD+m5+gv6JUEg+cOgOpDz3BWdQkYWk7gu4DXwFE6bp6/6yfwi/1Gy6/niAIWJ15E/RhGdhx5m1UthXAbDWO+HFW0YLq9mJUtxdjd9k7AICIgDh7gZ0SkYW4kCQoBO/5+9vfZ0JVWbMkxqUv5CqTwym14BcKdXSWTNkQkSMW1R5KtNlQ9eKz6Dp2SBLX6hKQ8divoND63tvrNDxr9xl077sRsPZK4tr0++E39ZExvXZm9FxkRs+F1WZBfWc5KtsKUdlWgMrW0+gcaB3Va7T1NaCtrwFf1O4AAPipApAcMf1s20gWksKnOU0e8STlRQ0QbedP85VKBdKm8uYyco2x2mE+deISCAq2EBG5CxbVHmigrhpVf/otegryJXFVyOAsalVImDyJkVuy9deje+86iKYWSVyjvwkBs387bjcRKhUqJIZPQWL4FOSkr4coimjvb0JVWyEqWgtQ2XYahs5KiLCN+FoDlj4UNx1FcdNRAIBCUEAXkjZ4A2RkFlIjZiAsIHpc8p4MZxxaP5IzY6D1U8uUDXkqY7V0k6I2kfOpidwJi2oPIlosaHj3TRjeehWiWboiWtBokP7YU/DTcRY1nWcztaN77/Ww9VVL4qqYtQhc8FcIwsSdcgmCgIiAWEQExGKufhUAYMDch+r24sGT7LYCVLUVwmjpv/gLAbCJNtR1lqKusxR7Kwbnaof6RyH1gr5sXUgalAr3bBkZaukLkStspj6YDMclMW0yNykSuRMW1R6it7QIVX/8DforS52fVCiQ+vCPETR1xuQnRm5LtPajZ/8GWLtOS+LKsHkIXvwmBIVm0nPyUwdgSsxcTImZCwCwiVY0dFWdbRcpQEVbgWQG9sV09rfgeN1uHK/bDQDQKP2QFD7VXmQnR0yHvzpwwr6W0bJYrCgrapDEOJ+aXGWqOwLYLhiZqlBCk7BQvoSIyAmLajdnMw6g/s1X0LjtLcDm/La5JiYOyd95FCGz58mQHbkr0WZBz8E7YGmVvl2sCMpE8PJ3IaiDZcpMSiEoER+ahvjQNCxLvQ4A0Nnfaj/JrmwrRF1HKWyidcTXMlkHUNqSj9KWwbYoAQJiQ5KREpGF1IgsJEdOR2SAbtJnZteUt8A4IL05NDNLN6k5kOdzHKWnjpsNhTZIpmyIaCgsqt1Y14kvUP3n38LYUOf8pEKBmOs2IP6Wu6D089wbuGj8iaKI3mMPwNzwX0lc8NMhePk2KLTu3Ysc6h+J7IQcZCcMzsw2WQZQ03Fm8AbI1sFiu9/cM8KrDC6kaeiqRENXJQ5U/g8AEKwNR0pElv0GyISwDKgUE9vb7DifOk4fjpCwgAn9nOR9nJa+JHKUHpG7YVHthswdbah7/a9o/ey/Qz7vn5yG5G8/gsAp0yc5M/IE/af/H0xV/5DEBHUYgpe/D2VgskxZXTqNyg/pUbORHjW46dEm2tDUXTN4A+TZtpGW3iH+4TmEbmM7Thr24qRhLwBApdAgMXzK2Q2Qg20jgZqQcc2f86lprESbDaYah8kfnE9N5HZYVE8iq9WKvLw8GAwG6HQ65OTkQHl2lrS5ox0dB3ajfd8udJ8+PmSrh6BSQ3fznYi94RYo1JwcQM4GSn+PgTO/lQYVfoPrx0NnypPUOFMICsSFJCMuJBmLU64GAPQYOyQn2TUdZ2C9sP90GBabCRWtp1DResoeiw7SD94AeXZm9ljWrIui6DT5g/OpyVWWlmLY+tskMRbVRO6HRfUk2bp1KzZu3Ija2lp7LCE+Hj+/6w4sF4zDFtLnBE6bheRvfx/+iSkTnyx5JGP1m+g74TBzWlAiaNE/oY5aLk9SkyRIG4aZuqWYqRssNCxWE2o7Su292RWtBeg1dY7qtc6tWT9U/QkAIEATcv4kOyILieGZo16z3ljfga72PkmMkz/IVUaHU2pliB6qsCSZsiGi4bCongRbt27Fhg0bIIrSVc519fW46xe/xjOLsrAmPmrIj1X4+SPhjnsRffV6DvmnYZkaPkHv0Xuc4oFz/whN/HUyZCQvlVIzeNIcObhtThRFtPYaUNF22n6a3dhdPcKrDOozdaGg4SAKGg4CuHDN+gyknp0yMtya9aL8GjS0laDP2IUAbQgy02YhJj50fL5I8hlO86mTOJ+ayB0JomOlR+PKarUiJSVFckLtKNZfi/evXATlBW8xK/z8EbYkBwm33g1NNDev0fAsbYfQlXcNYJWeiPrPeBL+U38gU1bur8/Ujapz2x/bClHdXjyqNetDiQyIQ0rkjLOn2dMRG5KMd995F3ffdS/aO88v3QkLicLLr7yI3Nzc8foyyAfUb54JS8sZ++PwLz2L4KUPyJgREQ2FRfUE27VrF1avXj3idS8sn41FiTqELliK8GWrEDpvMRRav0nIkDyZtbsYXZ+vhWiSrgPXZjyAgFnPTPr4OE9mtVlQ11l2wQbIAnSNcs26o8pDHfjPUweGeEaAIABbtmxhYU2jYu1tQd3T0pah2Pv2Q5swX6aMiGg4bP+YYAaDYVTXKa9Yj+wfPsZCmkbN1leL7j3XORXUmsSvImDWr1lQu0ipUCEpfCqSwqciJ/0G+5r1c+0ilW0Fo1qzbrOK+PilY8M8O3iGsXHjg1i/fr39RmWi4Tj2UwvqAGjiZsuUDRFdDIvqCabTjW7JQ8bKNSyoadRsprbB9eP90rYidcwVCJz/4oSuH/cVF65Zn5c4+G7TgLn37Jr1QlS2nkZVe5HTmvW6wjb0tA7fRiKKQG1tHb67+cu48vKrkRY5E6lRMxGsDZvIL4c8lMlhPrVGvxCCktOfiNwRi+oJlpOTA71ej7q6OqcbFYHBX9x6vR45OTkyZEeeSLT0oWffl2HtLpTEleELELTkDVnWj/sKP3UgpsTMw5SYwQ2m59asD7aLDN4EWdheP8KrDKqqq8Ce8vewp/w9AEBMUCLSomYiLXIm0iJnISzAvZf00ORwWvrCUXpEbotF9QRTKpXYvHkzNmzYAEEQJIX1ubfnN23axLeBaVREmxk9h26HpU36lrAiaAqCl70DQcW1xZPpwjXry9MGp6x8gPfwv2dvGPFjg8KlY/maemrQ1FODA5UfAgDCA2KRHjnrbKE9C5GBk79ineQlWkww1R2RxFhUE7kv3qg4SYaaU52YmIhNmzbxhiUaFVEU0Xv0HpiqX5PEBb94hKzaCWUA59a6A6vViuTkZNTVDb/lMTjKD3e/sBIK5eiL5BC/yMFT7LNFdkxwIhRs8/FqxppDaHxphSSmf6wRCv9wmTIioothUT2JLrZRkWgkfScfw0DJc5KYoA5H8MrPoArJkikrGsrzz/4FG7/nPDf83EnzH195FlOWxKGs9SQqWwtgsg64/DkCNCFIi5yBtMhZSIuahfjQVCgE/jzxJl37NqPjw/NjMdXR06F7MF/GjIjoYtj+MYmUSiVWrVoldxrkgfpLNjkV1FD6I2jZf1hQu6FUXTZWZX8Dh4reQZ+xwx7X6/WSd6fW4quw2qyo6yxFecvguvTy1lPoN/eM+Dn6TF04ZdiPU4bBnls/VQBSIrPsRbY+LAMqBW9o82TGKunSF03yMpkyIaLR4Ek1kZszVr2O3qN3S4OCEkFL3oZGd408SdFFPfvj93DiUCVsog1N7WVInxWOm+5cO6p3p2yiDQ1dVShvPWkvtLuN7S7noFZqkRw+DWlRs5AWOQvJEVNHvV6d5CeKIuqeSYatp8Eei7jxrwiad6eMWRHRxbCoJnJjpoaP0LN/AyBaJfHA+X+BNvl2mbKii7HZRDxw04vo6zk/Vu/+H12DxaumXNLriaKI5p46e5Fd3noSHf3NLr+OUlAhMXzK2SJ7JlIisuCnDriknGjiWdorUP/sVElM99BpqCMzZcqIiEbC9g8iN2VuPYCeg7c6FdT+M3/JgtqN1Ve3SgpqAMicMbp59UMRBAExwXrEBOuxJGXwnYm2vkaUt5xEeesplLecQkvv8DdFnmMVLfYlNjvwbwhQICEs/Wy7yOAovwBN8CXnSePLcZSeIjAaqogMmbIhotFgUU3khqxdhejZlwtYpYtF/DI3wn/K/8mUFY3GmVPSOdWRscGIiB7fYjUiIBYRSbFYkHQ5AKBroO1sgT1YaDd0VY74GiJsqO0oQW1HCXaXbQUA6EJSkHpBkR3iFzGuedPoOc2nTlzCkYpEbo5FNZGbsfbVoHvvOohmaR+tJulW+M/8lUxZ0WiVFBgkj6fMiJ/wzxniF4E5CZdhTsJlAIBeUxcqWk/bi+y6jrIR16sDgKGrEoauSuyr2AYAiA5KGDzJPrv1MSIgdkK/DjqPS1+IPA+LaiI3YjO2onvvOtj6pW/nq2OvRuC8F7h+3AOUnpaeVGdmTXxR7ShQE4KZuqWYqRssxAbMvahsK7SfZte0n4FVtIz4Os09dWjuqcPBqo8AAOH+Mfae7LSomYgKTODp6QSwDXTB3HhKEtMmcfIHkbtjUU3kJkRLL7r33Qhbd7EkroxYhKDFr0HgeDS3197ag+aGLklsLP3U48VPHYhpsQswLXYBAMBkGUB1e7G9yK5qL4LZahzhVYD2/iYcrdmOozXbAQDB2vDzRXbkTMSGJHMhzTgw1h4CxAveWVBqoImfJ19CRDQqLKqJ3IBoM6Pn4G2wth+WxBXB0xC8dCsEVaBMmZErSk5LWz/8AzVISI6UKZvhaVR+yIjORkZ0NgDAYjOjtr1ksMhuPYmK1tMwWvpHeBWg29iO/LrdyK/bDQAIUAcj1b71cSbiQ9OhVHAhjauM1Q7zqePnQVD7yZQNEY0Wi2oimYmiDb1H74W58WNJXOGfgODl70Ohdb+ijIZW4tD6kTFdB4XS/U9uVQo1UiKzkBKZhTW4GVabFYaucvsIv/KWU+gzd4/4On3mbpxu2I/TDYP9wFqVP1IiZtiL7MSwTKiUmon+cjyeqfqA5DH7qYk8A4tqIhmJooj+kz+CqeZNSVzQRCB4+QdQBiTKlBldCseiOnMSblKcCEqFEvqwTOjDMnFZxo2wiTY0dlefXUZzEmUtJ0e1kMZo6Udx0xEUNx0BAKgUGiRHTLOP8UsOnwaNiiewFxJtVhhrD0piLKqJPAOLaiIZDZQ8i4HS56VBZQCCl22FMmSaPEnRJRnoN6G6TLqUxVOLakcKQQFdSAp0ISlYnnYdRFFES2/9+ZPs1lNo72sc8XUsNhPKWk6grOUEUDy4kEYfnnn2xsdZSInIgr/at1udzI2nIBql7wqwqCbyDCyqiWRirPon+k89IQ0KKgQtfgOqiMXyJEWXrLyoATbb+QW1SqUCaVO9cwSdIAiIDkpAdFACFqdcBQBo72uSzMpu7qkd8XWsogVVbYWoaivEzpK3IUCB+NA0pEXNRHrkLKRGzkCgNnSivxy34jhKTxWRDmWQd/49IvI2LKqJZGAy/Be9X9zvFA+c/xI0cVfJkBGNleNNiskZ0dD6+c7ElvCAGMwPWIP5iWsAAN0D7U4LaUSIF30NETbUdZairrMUeWXvAgBig5PtPdlpkbMQ6u/d9xg4FtWaxCUyZUJErmJRTTTJzK370HPwduf147OehjbpFpmyorE64yX91OMl2C8c2Qk5yE7IAQD0mboHF9KcLbTrOkthE0deSNPYXYXG7irsr/gvACAqMN6+jCY9cjbCA2K8ala209KXZM6nJvIULKqJJpGl8zR69n0ZsA1I4n5T/g/+mRtlyorGyma1oayoQRLLyJJ/PrU7CdAEY4ZuCWboBk9eB8x9qGovtPdlV7cXw2obeSFNS289Wnrrcaj6EwBAmH+0fRlNWuQsRAfpPbbItnTVw9pRKYlpeVJN5DFYVBNNEmtf1dn14x2SuCbpDvjP+IU8SdG4qKlsxUCfSRLz9ZPqkfipAzA1Zj6mxswHAJitxsGFNC2nUN56CpVtBaNaSNPR34wvanfii9qdAIAgbZh9GU1a1CzEhaR4zEIak8MptaANgTpmhkzZEJGrWFQTTQKbsRnde9ZBHJD23arjvoTAeX/y2JM1GlRyStr6EaMLRViEb0+xcJVaqUV61GykR80GMLiQpq6j9Gy7yClUtJ7CgKVvxNfpMXbgRP0enKjfAwDwVwchNXKGvchOCE2HUuGev/qMNQ7zqROXQFB4xj8IiIhFNdGEEy09g+vHe0okcVXkUgQt+icEN/0FT6NXUuDQTz2Tp9RjpVKokRwxHckR07E68ybYRCsMnRX2Iru89SR6TV0jvk6/uQcFDQdR0DA4+1mj9ENKZJb9xsfE8ClQu8lCGsdNihylR+RZ+NucaAKJNhO6D3wV1vajkrgyJAtBS/8DQRUgU2Y0nhxPqjOzWFSPN4WgREJYBhLCMpCTfgNEURxcSNM6eIpd1nISXQOtI76OyTqAM01f4EzTFwAGi/ek8Gn2nuzkiOnQyrCQxmbuh6n+mCTGoprIs7CoJpogomhD75FvwdK0XRJX+CcOrh/XhMuUGY2n1qYutLX0SGKZM3iT4kQTBAFxIcmIC0nGstRrIYoi2voaUHZ2hF9Fy0m09jWM+DoWm/nsApuTAN6EQlBCH5aBtKhZSIuchdSILPhrgib86zHVHQEuvFFTUECjXzThn5eIxg+LaqIJIIoi+k78AKbatyRxQROJ4BXboPBPkCkzGm+O86kDg/2gS4yQKRvfJQgCIgN1iAzUYVHylQAGb2I8d+NjeetJNHXXjPg6NtGK6vZiVLcXY1fJFggQoAtNRVrkLKRHDS6kCdKGjXv+jqP01HGzodBOfDFPROOHRTXRBBgo/g2MZX+SBpWBCF72DpTBU+VJiiaE43zqjCwdFAreeOoOwvyjMS9xNeYlrgYAdBs7UNl6+uxp9kkYOitGsZBGRH1nOeo7y7Gn/D0AQExwor3ITouciVD/qDHn6txPzfnURJ6GRTXROBuoeAX9BT+RBgUVgpf8C6qIhfIkRROmxKGonsJRem4rWBuGWfHLMSt+OQCg39SDiraCwfaPlpOo7SgZ1UKapu4aNHXX4EDl/wAAkQFxSI2ahfTIWUiLmomIgDiXJvqIoghTtcPkjyTOpybyNCyqicaRqf599B17wCkeuOAvUMdeLkNGNJH6eo2orZTeHMd+as/hrwlCVtwiZMUN9i4bLf2oais6W2SfQnV7ESw284iv09rXgNbqBhyp/hQAEOoXibSoWUiNnInUiCzEhiRBISiH/XhjYwH2FragqQeICQIWJQk8qSbyQCyqicaJuWUPeg7dCUB60hUw+zfQJn5VnqRoQpUVNkC0nW8fUKmVSJkSK2NGNBZalT+mxMzFlJi5AACz1YSa9jNnb2Q8hcrWApisAyO8CtA50IpjtbtwrHaX/XWTwqciOXw6kiKmITliGgI1IQCArVu34sH770Zdk9X+8bpQJX4/7zC+/OWk8f8iiWjCCKIoXryhjIhGZOk8ie7dV0A0d0riflN+gICZT8qUFU20rf/Yj/ffOGR/nJGlwxPP3SxjRjSRrDYL6jrLUH5uwkjrafSbe0b+wCFEBSag8bgZmx59FY5t3QIACAK2bNmC3NzcMedNRJODRTXRGFl7K9G1azVEo3R8lzb56wjgtkSv9utH/oPC/Fr742tumo+v3L1CxoxoMtlEKxq6quxFdnnrKfQYO0b3sVYRf7l3F3pah17FLggCEhISUFlZCaVy+NYRIm9mtVqRl5cHg8EAnU6HnJwct/5+YPsH0RjYBprQvec6p4JarbsOAXN/z4Lai1ksVpQVSf+7Z2axn9qXKAQl4kPTEB+ahhXp6yGKIpp76lDeegJlLSdR2VaI9r7GIT+2rrBt2IIaGLx5sba2Fvc9dx2W5yyDLiQV8aGpiAtJQWRg3EV7tIm8wdatW7Fx40bU1p4/uNDr9di8ebPbvoPDoproEonm7sH1471lkrgqcjmCFr3K9eNerqa8BSajRRLLYFHt0wRBQEywHjHBeixJ+RIAoGugDdVtRahsL0R1WxFqOkpgthrR0z58QX2hekM9Thn24ZTh/Mg9tVKLuJAUxIcMFtm6kFToQlPsfdpEnm7r1q3YsGEDHJsp6urqsGHDBrdtjeJvfaJLIFqN6D7wFVg7vpDElSEzEbR0CwSlv0yZ0WQ547CaPE4fjpAwrp0nqRC/CMyMX4aZ8YPTPKw2CwxdFXin7238DydG/PigcK1TzGw1oqa9GDXtxZJ4qF8k4s4W2PEhqQjxizw7h1vEYG0iDj4Wz/0/ERDPTeoW7QXM+fjZxxf+/7PP2f//2eftj0TxgtfG0J//7OOhc3POx/7shZ9ntPnaP8YhH8dcB19oVDmd/6wj//ld+HnsX8uFOTn8+Q2b7wX5SD7PsLkOke8o/vwc873Yn9/5/z4j/PcWL/ioUfz5Wa1WbL53m1NBfS4fQRDw0EMPYf369W7XCsKimshFomhF75FvwtK8UxJXBCQjePl7UGjC5EmMJlVJgcN86pmcT00jUypU0Idl4ttfeRTPPPpn1NXWwrl0GBQc5YeE6aPfztk50IrOgVYUNx0Zn2SJZFBzqhVdLf3DPi+KImpqapCXl4dVq1ZNXmKjoJA7ASJPIooi+vK/B1PdfyRxQROF4OXboPBnYeULRFF0WvrCfmpyhVKpxHPP/ArA2WkfFxAEAYIg4HfP/ha3LPgeLku/EZnRcxCoCZ38RIkm2WhbowwGwwRn4jqeVBO5YKDoaRjLX5QGVUEIXv4ulMGZ8iRFk665oQudbX2SWCY3KZKLrp0XgT9vUOJnH1th6D4f1+v12LRp05A9o90D7TB0VaC+swKGrgo0dFWiobsKVpvF6VoiTzRUy9NQdDr3O8hgUU00SgPlf0V/ocPMaUGN4CX/hip8vjxJkSwcT6mDQ/0RmxAmTzLksQYq8nDNNAWunCLgULWIdv9pmHbrHy46NizYLxzBfuGYEjPPHrPaLGjuqYOhqwKGrkoYOivQ0F0Fk2Vg8NT7grPwwYlEgn0W9uD/kz52em4wMPhYwAXxc698wedweP7csxAu+EwX5CTJx/4xZ68dMlc453T2WpfyvTA3p8cYXb4Of37DPjdEPo6fZ7h87c84/VkO/+cnfe6Cr2qYnKR/lhfJd9g/P+l/n1Hna//7Jv26bUus2P3n69BoaBqyr1oQBOj1euTk5Dg9JzcW1USjYKp7F33HNzpEBQQufBnqmDWy5ETycWr9mBHP8YnkMmPlbgCAUiFgaYqAkFU3IewSekSVChXiQpIRF5KMueOcI5Ec/vj7P2HDhg0QBEFSWJ/7Obtp0ya3u0kRYE810YjMzbvRc/hrcFo/nv07aPU3yZMUyarktLSXj60f5CqbsRsmwzFJzC91pUzZELmX3NxcbNmyBQkJCZK4Xq9323F6AE+qiS7K0pGPnv03ATaTJO439YfwS79fpqxITr3dA6irapXEMme4X28fuTdj9T7AZj0fUGqgSVwsX0JEbiY3Nxfr16/nRkUib2DtKUf33vUQLV2SuDblm/DP+n8yZUVyKymQnlKrNUqkZMTIlA15KmPF55LHWv1CKNScb090IaVS6XZj8y6G7R9EQ7ANNKJ77zqIRumKYXX89QiYu5n9sz6s1KGfOm1qHFRq9z05Ifc0UJkneaxNcb+brojINSyqiRyI5i50770Btt5ySVwVlYOghf+AILCA8mVnOJ+axshm6oWp7qgkpk25TKZsiGi8sKgmuoBoHUD3gZth7TwuiStDZyNo6dsQlH7yJEZuwWK2ouKM9N2LTG5SJBcZq/cDF86VVqigTVoqX0JENC5YVBOdJYpW9Bz+BizN0l5HRUAKgpe9C4Wa28x8XWVpE8wmqySWMZ0n1eSac6P0ztEkzIdCEyhTNkQ0XlhUE+Hs+vHjD8Nc/64kLmhjELziAyj8WTgRUHJK2vqRkByJwGC+e0GuMTr0U/uxn5rIK7CoJgLQX/hLGCv+Ig2qghG87F0og9LlSYrcjuPkD47SI1fZzP0w1h6WxLScT03kFVhUk88bKH8JA0W/lAYVGgQveQuqcO4no0GiKA65SZHIFaaag4D1grn3CiW0ScvkS4iIxg2LavJpptr/oO/4Qw5RAUELX4E6ZpUMGZG7aqzrQHdnvyTGoppcNeAwn1qjmwuFNlimbIhoPLGoJp9lbtqFniN3ARAl8YA5m6BJcM8VqCQfx1PqsIhARMeFyJQNeSrHfmqO0iPyHiyqySdZ2o+h+8AQ68enPQ6/tHtkyorcmeN86owZOi4BIpeI5gEYaw9KYn6pvEmRyFuwqCafY+0pQ/e+GwBLjySuTf0W/Kc/Lk9S5PZKTktvUpzC1g9ykbHuMGAxng8IArRJy+VLiIjGFYtq8im2fgO691wH0dgkiasTbkTAnOd48khD6uroQ0NtuyTGfmpylbFCOp9aHZcNhX+YPMkQ0bhjUU0+w2buRPe+G2Drq5TEVdErEbTgFa4fp2GVOozS02hVSEyLkikb8lQDTvOp2U9N5E1YVJNPEK0D6Nl/E6ydJyRxZegcBC95C4JSK1Nm5Akc51OnT4+DSsV/hNHoiRYTTDX7JTEtl74QeRUW1eT1BtePfw2WFukpkSIwDcHL34Wg5gQHujjHTYqZWWz9INeY6o9CNF8wklEQWFQTeRkW1eTVRFFE37EHYa5/XxIXtLGD68f9YmXKjDyFyWRBZam0B3/KTBbV5JoBx37qmJlQBkTIlA0RTQQW1eTV+guehLHyb5KYoApB8PL3oAxMlSkr8iSVZxphMVvtjwWFgPRpcTJmRJ7IWCktqrWp7Kcm8jYsqslrDZT9CQPFT0uDCi2Clr4NVVi2PEmRx3GcT61PiYR/IHvwafREqxnG6n2SmB9bP4i8Dotq8krGmn+hL//7DlEFghb+A+ponhDR6HE+NY2Vqf4YRFOvJMZ+aiLvw6KavI6p7l30HrkbTuvH5/4emoT18iRFHslmE1HqcFLN+dTkKsfWD3X0dCgDo2XKhogmCotq8iqmho/Qc+hOQLRK4v5ZP4Ff6l0yZUWeymalmlUAAA1XSURBVFDTht4eoySWOUMnUzbkqRznU7Ofmsg7sagmr2Fu2oWeA7cAolkS12Y8AL+pj8qUFXkyx9aPiOggRMZwBCONnmizwli1VxJj6weRd2JRTV7B3LoP3fs3ALYBSVybejcCZj3D9eN0SUrY+kFjZDbkQzR2SWLcpEjknVhUk8eztB9Fz94bAav0RiBN0q0ImLOZBTVdMhbVNFYDDv3UqqgpUAZzJCORN2JRTR7N0nkS3XvWQbRIT4I0CbkInPciBIF/xenSdLT1osnQKYmxqCZXOd6kyFNqIu/FioM8lrW7GN17roNobpfE1XHXInDhKxAUKpkyI2/geErtF6BBYkqkTNmQJxJtVgxU7pHE2E9N5L1YVJNHsvaUoyvvGohG6fpoVcxaBC1+DYJCI1Nm5C1KC6Q3KWZMj4NCyR+ZNHrmxpMQBzokMU7+IPJePMojj2C1WpGXlweDwYCYcCXmWJ+AYJQWParI5Qhe8hYEpZ9MWZI3OXPKoZ86i60f5BrHUXqqiHSoQhJkyoaIJhqLanJ7W7duxcaNG1FbW2uPxUcCv7pLjXVLlAAAZfgCBC/bCkEVIFea5EWMA2ZUlzVLYpkzWVSTa4wV0n5qtn4QeTe+l0lubevWrdiwYYOkoAYAQyvwjd+Yse2AFcrQbAQvfx+CmvODaXyUFzfCarXZHysUAtKncWIDjZ5os8FYxX5qIl/CoprcltVqxcaNGyGKotNz5yKP/x0IWPouFJrwSc2NvJvjTYpJ6dHQ+qllyoY8kbm5ALa+VknMj/3URF6NRTW5rby8PKcT6guJAOqazdh7qGjykiKfwPnUNFZGh35qZVgKVGHJMmVDRJOBRTW5LYPBMPJFLlxHNBo2q81p8geLanKVYz+1XypbP4i8HYtqcls6nW5cryMajbqqVvT3mSSxzBn8O0ajJ4qi0+QPLZe+EHk9FtXktnJycqDX64ddMy4IAhITE5GTwxMgGj8lp6Wn1NFxIQiPDJIpG/JEluYi2HqlM/T9eJMikddjUU1uS6lUYvPmzQDgVFife7xp0yYolcpJz4281xmHfuoMtn6QixxPqZUheijDU2XKhogmC4tqcmu5ubnYsmULEhKkCxP0ej22bNmC3NxcmTIjb1VSIC2qp7CoJhcZK53nUw/3jhsReQ8ufyG3l5ubi/Xr19s3Kup0OuTk5PCEmsZdW3M3Whu7JTH2U5MrRFF0mvzBUXpEvoFFNXkEpVKJVatWyZ0GeTnHfuqAIC3ikyJlyoY8kaWtFNZu6d8jLn0h8g1s/yAiOsux9SMjSweFgm/b0+gZK6Sn1IqgOKgiM2XKhogmE4tqIqKznJa+ZLH1g1wzUOk4n/oy9lMT+QgW1UREAPr7TKgub5HEpsxMGOZqImdD9VNzPjWR72BRTUQEoKzQANEm2h8rVQqkTomVMSPyNNb2Clg7ayQxzqcm8h0sqomIAJQ4rCZPzoiBRst7uWn0HOdTKwJjoIqeJlM2RDTZWFQTEQEoPc351DQ2zvOpV7CfmsiHsKgmIp9ntdpQWtggiXE+NblqwGHyhx/7qYl8CotqIvJ5NeUtMA6YJbFMnlSTCywd1bB2VEpinE9N5FtYVBORz3OcTx2bEIaQsACZsiFP5Nj6ofCPgDpmhkzZEJEcWFQTkc8rOcX51DQ2jjcpalNyICj4K5bIl/A7noh8miiKOOO49GUmWz/INY6bFLWp7Kcm8jUsqonIp7U0dqOjtVcSy8xiUU2jZ+mqg6WtVBLjfGoi38Oimoh8mmM/dVCIH3SJ4TJlQ57IWCHtpxb8wqCOnSVTNkQkFxbVROTTHOdTZ2bFc7YwucRxNblf8nIICqVM2RCRXFhUE5FPc+qn5nxqctGA49IX9lMT+SQW1UTks3p7jKirbJXEOJ+aXGHtboCl5YwkpuXSFyKfxKKaiHxWWaEBonj+sUqtREpmjHwJkcdxHKUnaIOhicuWKRsikhOLaiLyWSUOrR+pU2Kg1qhkyoY8kWM/tTZpOQQl/w4R+SIW1UTks0pOGySP2fpBrnLcpOjHfmoin8Wimoh8ksViRXlxgyTGoppcYe1thrmpQBJjPzWR72JRTUQ+qbq0GSajRRLjenJyhWPrh6AJhCZ+rkzZEJHcWFQTkU9yXPoSnxSBoBB/mbIhT+R4k6I2aRkEpVqmbIhIbiyqicgnnTklLaozeEpNLnLcpKjlanIin8aimoh8jiiKKCmQ3qQ4ZSb7qWn0rH1tMDedksT82E9N5NNYVBORz2mq70RXe58klpnFoppGz1i1BxcOORfU/tAkLJAxIyKSG4tqIvI5jv3UIWH+iIkPlSkb8kSONylqEpdAUGlkyoaI3AGLaiLyOUPNpxYEQaZsyBMNOM6nZj81kc9jUU1EPsdxkyLnU5MrbAOdMBvyJTFt6kqZsiEid8Gimoh8Sk9XP+qr2ySxKSyqyQXGqr2AaDsfUGmhTVgoX0JE5BZYVBORT3Gc+qHRqpCUES1TNuSJBhxH6ekXQ1D7yZQNEbkLFtVE5FMcWz9Sp8ZCpVLKlA15ImMl51MTkTMW1UTkM6xWKz756DOUG46ioa0ENtHG1g9yic3YDZPhmCTml8r51EQEqOROgIhoMmzduhUPPrgRdXW19liANgxzLn8KwDL5EiOPYqzeB9is5wNKNTT6xfIlRERugyfVROT1tm7dig0bNkgKagDoM3bg+z/8NrZu3SpTZuRpnFaTJyyEQhMgUzZE5E5YVBORV7Nardi4cSPEC7bfOXrooYdgtVqHfZ7onAGHpS/spyaic1hUE5FXy8vLQ21t7bDPi6KImpoa5OXlDXsNEQDYTL0w1R2RxDifmojOYVFNRF7NYDCMfJEL15HvMtUcAGyW8wGFCtqkpfIlRERuhUU1EXk1nU43rteR7xqo+FzyWJMwHwpNoEzZEJG7YVFNRF4tJycHer0egiAM+bwgCEhMTERODntj6eKMDv3UfuynJqILsKgmIq+mVCqxefNmAHAqrM893rRpE5RKLoCh4dnM/TDWHpbEtCmcT01E57GoJiKvl5ubiy1btiAhIUES1+v12LJlC3Jzc2XKjDyFqeYgYDWdDwgKaJM435yIzuPyFyLyCbm5uVi/fj3y8vJgMBig0+mQk5PDE2oalQGH1eSa+LlQ+IXIlA0RuSMW1UTkM5RKJVatWiV3GuSBHPup2fpBRI7Y/kFERHQRosU42P5xAS59ISJHLKqJiIguwlh7GKJl4HxAEOCXvEK+hIjILbGoJiIiugijQz+1Oi4bCv8weZIhIrfFopqIiOginOdTs5+aiJyxqCYiIhqGaLXAWHNAEtOmsPWDiJyxqCYiIhqGufEkRFOvJMb51EQ0FBbVREREwzBW75M8VkVmQBkUI1M2ROTOWFQTERENw1glLap5Sk1Ew2FRTURENAyj43zqpKUyZUJE7o5FNRER0RAsXfWwdlZLYprEJTJlQ0TujkU1ERHREEwOUz8EbQjU0dNlyoaI3B2LaiIioiEYq/dLHmv1iyAo+GuTiIbGnw5ERERDMFbtlTzWJvMmRSIaHotqIiIiBzZTL0yG45KYNnm5PMkQkUdgUU1EROTAVHsYsFnOBxRKaPSL5EuIiNwei2oiIiIHjq0fGt0cKDSBMmVDRJ6ARTUREZEDp5sUk9j6QUQXx6KaiIjoAqLNCmONY1HNpS9EdHEsqomIiC5gbjwJ0dgtiXHyBxGNRCV3AkRERO6kr2Iv9lfa0NQDxAQBy+ZkQBmskzstInJzgiiKotxJEBERuYOtW7fiu9+6A/VtffZYfGQAfv/SP5GbmytjZkTk7lhUExERYbCg3rBhAxx/LQoAIAjYsmULC2siGhaLaiIi8nlWqxUpKSmora0d8nlBEKDX61FRUQGlUjnJ2RGRJ+CNikRE5PPy8vKGLagBQBRF1NTUIC8vbxKzIiJPwqKaiIh8nsFgGNfriMj3sKgmIiKfp9ONbrrHaK8jIt/DnmoiIvJ553qq6+rqnG5UBNhTTUQj40k1ERH5PKVSic2bNwMYLKAvdO7xpk2bWFAT0bBYVBMREQHIzc3Fli1bkJCQIInr9XqO0yOiEbH9g4iI6AJWqxV5eXkwGAzQ6XTIycnhCTURjYhFNRERERHRGLH9g4iIiIhojFhUExERERGNEYtqIiIiIqIxYlFNRERERDRGLKqJiIiIiMaIRTURERER0RixqCYiIiIiGiMW1UREREREY8SimoiIiIhojFhUExERERGNEYtqIiIiIqIxYlFNRERERDRGLKqJiIiIiMaIRTURERER0RixqCYiIiIiGiMW1UREREREY8SimoiIiIhojFhUExERERGNEYtqIiIiIqIxYlFNRERERDRGLKqJiIiIiMaIRTURERER0RixqCYiIiIiGiMW1UREREREY8SimoiIiIhojFhUExERERGNEYtqIiIiIqIxYlFNRERERDRGLKqJiIiIiMaIRTURERER0RixqCYiIiIiGiMW1UREREREY8SimoiIiIhojFhUExERERGNEYtqIiIiIqIxYlFNRERERDRGLKqJiIiIiMaIRTURERER0Rj9fwG1UJymVAP3AAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -522,7 +522,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -543,7 +543,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 31, "metadata": {}, "outputs": [ { @@ -635,7 +635,7 @@ "4 5 4 " ] }, - "execution_count": 11, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -646,7 +646,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -679,7 +679,7 @@ " <meta name="viewport" content="width=device-width,\n", " initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />\n", " <style>\n", - " #map_2ec7d88abd2232a9ed05d3d1bdae62d9 {\n", + " #map_2fe6299aab429be5e64946fa852adcf1 {\n", " position: relative;\n", " width: 100.0%;\n", " height: 100.0%;\n", @@ -726,44 +726,58 @@ "<body>\n", " \n", " \n", - " <div class="folium-map" id="map_2ec7d88abd2232a9ed05d3d1bdae62d9" ></div>\n", + " <div class="folium-map" id="map_2fe6299aab429be5e64946fa852adcf1" ></div>\n", " \n", "</body>\n", "<script>\n", " \n", " \n", - " var map_2ec7d88abd2232a9ed05d3d1bdae62d9 = L.map(\n", - " "map_2ec7d88abd2232a9ed05d3d1bdae62d9",\n", + " var map_2fe6299aab429be5e64946fa852adcf1 = L.map(\n", + " "map_2fe6299aab429be5e64946fa852adcf1",\n", " {\n", " center: [50.102935750000015, 14.403062600000004],\n", " crs: L.CRS.EPSG3857,\n", - " zoom: 10,\n", - " zoomControl: true,\n", - " preferCanvas: false,\n", + " ...{\n", + " "zoom": 10,\n", + " "zoomControl": true,\n", + " "preferCanvas": false,\n", + "}\n", + "\n", " }\n", " );\n", - " L.control.scale().addTo(map_2ec7d88abd2232a9ed05d3d1bdae62d9);\n", + " L.control.scale().addTo(map_2fe6299aab429be5e64946fa852adcf1);\n", "\n", " \n", "\n", " \n", " \n", - " var tile_layer_89e4c5719cd7b695aa891255acc48f43 = L.tileLayer(\n", + " var tile_layer_8de714aba5d347398e64e486ed5940b8 = L.tileLayer(\n", " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",\n", - " {"attribution": "\\u0026copy; \\u003ca href=\\"https://www.openstreetmap.org/copyright\\"\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\"https://carto.com/attributions\\"\\u003eCARTO\\u003c/a\\u003e", "detectRetina": false, "maxZoom": 20, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}\n", + " {\n", + " "minZoom": 0,\n", + " "maxZoom": 20,\n", + " "maxNativeZoom": 20,\n", + " "noWrap": false,\n", + " "attribution": "\\u0026copy; \\u003ca href=\\"https://www.openstreetmap.org/copyright\\"\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\"https://carto.com/attributions\\"\\u003eCARTO\\u003c/a\\u003e",\n", + " "subdomains": "abc",\n", + " "detectRetina": false,\n", + " "tms": false,\n", + " "opacity": 1,\n", + "}\n", + "\n", " );\n", " \n", " \n", - " tile_layer_89e4c5719cd7b695aa891255acc48f43.addTo(map_2ec7d88abd2232a9ed05d3d1bdae62d9);\n", + " tile_layer_8de714aba5d347398e64e486ed5940b8.addTo(map_2fe6299aab429be5e64946fa852adcf1);\n", " \n", " \n", - " map_2ec7d88abd2232a9ed05d3d1bdae62d9.fitBounds(\n", + " map_2fe6299aab429be5e64946fa852adcf1.fitBounds(\n", " [[50.10007700000001, 14.398981599999999], [50.10579450000001, 14.407143600000008]],\n", " {}\n", " );\n", " \n", " \n", - " function geo_json_f69503db37bc7e131351577d6042c1b5_styler(feature) {\n", + " function geo_json_ba8489f3488749c7d1c6928d4b5df489_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#fff5f0", "fillColor": "#fff5f0", "fillOpacity": 0.5, "weight": 8};\n", @@ -787,52 +801,54 @@ " return {"color": "#67000d", "fillColor": "#67000d", "fillOpacity": 0.5, "weight": 8};\n", " }\n", " }\n", - " function geo_json_f69503db37bc7e131351577d6042c1b5_highlighter(feature) {\n", + " function geo_json_ba8489f3488749c7d1c6928d4b5df489_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_f69503db37bc7e131351577d6042c1b5_pointToLayer(feature, latlng) {\n", + " function geo_json_ba8489f3488749c7d1c6928d4b5df489_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_f69503db37bc7e131351577d6042c1b5_styler(feature)\n", + " let style = geo_json_ba8489f3488749c7d1c6928d4b5df489_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_f69503db37bc7e131351577d6042c1b5_onEachFeature(feature, layer) {\n", + " function geo_json_ba8489f3488749c7d1c6928d4b5df489_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_f69503db37bc7e131351577d6042c1b5.resetStyle(e.target);\n", + " geo_json_ba8489f3488749c7d1c6928d4b5df489.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_f69503db37bc7e131351577d6042c1b5_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_ba8489f3488749c7d1c6928d4b5df489_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_f69503db37bc7e131351577d6042c1b5 = L.geoJson(null, {\n", - " onEachFeature: geo_json_f69503db37bc7e131351577d6042c1b5_onEachFeature,\n", + " var geo_json_ba8489f3488749c7d1c6928d4b5df489 = L.geoJson(null, {\n", + " onEachFeature: geo_json_ba8489f3488749c7d1c6928d4b5df489_onEachFeature,\n", " \n", - " style: geo_json_f69503db37bc7e131351577d6042c1b5_styler,\n", - " pointToLayer: geo_json_f69503db37bc7e131351577d6042c1b5_pointToLayer,\n", + " style: geo_json_ba8489f3488749c7d1c6928d4b5df489_styler,\n", + " pointToLayer: geo_json_ba8489f3488749c7d1c6928d4b5df489_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_f69503db37bc7e131351577d6042c1b5_add (data) {\n", - " geo_json_f69503db37bc7e131351577d6042c1b5\n", + " function geo_json_ba8489f3488749c7d1c6928d4b5df489_add (data) {\n", + " geo_json_ba8489f3488749c7d1c6928d4b5df489\n", " .addData(data);\n", " }\n", - " geo_json_f69503db37bc7e131351577d6042c1b5_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fff5f0", "edge_indeces": "[0, 3, 15, 27]", "n_segments": 8, "stroke_group": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fee3d6", "edge_indeces": "[1, 12, 14, 25]", "n_segments": 19, "stroke_group": 1, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fcc4ad", "edge_indeces": "[2, 11, 28, 30]", "n_segments": 17, "stroke_group": 2, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fca082", "edge_indeces": "[4, 5, 6]", "n_segments": 5, "stroke_group": 3, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#fb7c5c", "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "n_segments": 14, "stroke_group": 4, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#f6553c", "edge_indeces": "[10]", "n_segments": 2, "stroke_group": 5, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e32f27", "edge_indeces": "[16, 17, 18, 23, 29]", "n_segments": 13, "stroke_group": 6, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#c2161b", "edge_indeces": "[19]", "n_segments": 3, "stroke_group": 7, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#9d0d14", "edge_indeces": "[20]", "n_segments": 3, "stroke_group": 8, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#67000d", "edge_indeces": "[26]", "n_segments": 5, "stroke_group": 9, "stroke_id": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_ba8489f3488749c7d1c6928d4b5df489_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fff5f0", "edge_indeces": "[0, 3, 15, 27]", "n_segments": 8, "stroke_group": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fee3d6", "edge_indeces": "[1, 12, 14, 25]", "n_segments": 19, "stroke_group": 1, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fcc4ad", "edge_indeces": "[2, 11, 28, 30]", "n_segments": 17, "stroke_group": 2, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fca082", "edge_indeces": "[4, 5, 6]", "n_segments": 5, "stroke_group": 3, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#fb7c5c", "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "n_segments": 14, "stroke_group": 4, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#f6553c", "edge_indeces": "[10]", "n_segments": 2, "stroke_group": 5, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e32f27", "edge_indeces": "[16, 17, 18, 23, 29]", "n_segments": 13, "stroke_group": 6, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#c2161b", "edge_indeces": "[19]", "n_segments": 3, "stroke_group": 7, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#9d0d14", "edge_indeces": "[20]", "n_segments": 3, "stroke_group": 8, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#67000d", "edge_indeces": "[26]", "n_segments": 5, "stroke_group": 9, "stroke_id": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_f69503db37bc7e131351577d6042c1b5.bindTooltip(\n", + " geo_json_ba8489f3488749c7d1c6928d4b5df489.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -853,48 +869,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_f69503db37bc7e131351577d6042c1b5.addTo(map_2ec7d88abd2232a9ed05d3d1bdae62d9);\n", + " geo_json_ba8489f3488749c7d1c6928d4b5df489.addTo(map_2fe6299aab429be5e64946fa852adcf1);\n", " \n", " \n", - " var color_map_4df795d703c51512148aa5b8c0075c1d = {};\n", + " var color_map_cd41b2020c8cf5087bb3041ff4524b9b = {};\n", "\n", " \n", - " color_map_4df795d703c51512148aa5b8c0075c1d.color = d3.scale.threshold()\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.color = d3.scale.threshold()\n", " .domain([0.0, 0.018036072144288578, 0.036072144288577156, 0.05410821643286573, 0.07214428857715431, 0.09018036072144289, 0.10821643286573146, 0.12625250501002003, 0.14428857715430862, 0.1623246492985972, 0.18036072144288579, 0.19839679358717435, 0.21643286573146292, 0.23446893787575152, 0.25250501002004005, 0.27054108216432865, 0.28857715430861725, 0.3066132264529058, 0.3246492985971944, 0.342685370741483, 0.36072144288577157, 0.3787575150300601, 0.3967935871743487, 0.4148296593186373, 0.43286573146292584, 0.45090180360721444, 0.46893787575150303, 0.48697394789579157, 0.5050100200400801, 0.5230460921843687, 0.5410821643286573, 0.5591182364729459, 0.5771543086172345, 0.5951903807615231, 0.6132264529058116, 0.6312625250501002, 0.6492985971943888, 0.6673346693386774, 0.685370741482966, 0.7034068136272545, 0.7214428857715431, 0.7394789579158316, 0.7575150300601202, 0.7755511022044088, 0.7935871743486974, 0.811623246492986, 0.8296593186372746, 0.8476953907815631, 0.8657314629258517, 0.8837675350701403, 0.9018036072144289, 0.9198396793587175, 0.9378757515030061, 0.9559118236472945, 0.9739478957915831, 0.9919839679358717, 1.0100200400801602, 1.028056112224449, 1.0460921843687374, 1.0641282565130261, 1.0821643286573146, 1.1002004008016033, 1.1182364729458918, 1.1362725450901803, 1.154308617234469, 1.1723446893787575, 1.1903807615230462, 1.2084168336673347, 1.2264529058116231, 1.2444889779559118, 1.2625250501002003, 1.280561122244489, 1.2985971943887775, 1.3166332665330662, 1.3346693386773547, 1.3527054108216432, 1.370741482965932, 1.3887775551102204, 1.406813627254509, 1.4248496993987976, 1.4428857715430863, 1.4609218436873748, 1.4789579158316633, 1.496993987975952, 1.5150300601202404, 1.5330661322645291, 1.5511022044088176, 1.5691382765531061, 1.5871743486973948, 1.6052104208416833, 1.623246492985972, 1.6412825651302605, 1.6593186372745492, 1.6773547094188377, 1.6953907815631262, 1.7134268537074149, 1.7314629258517034, 1.749498997995992, 1.7675350701402806, 1.785571142284569, 1.8036072144288577, 1.8216432865731462, 1.839679358717435, 1.8577154308617234, 1.8757515030060121, 1.8937875751503006, 1.911823647294589, 1.9298597194388778, 1.9478957915831663, 1.965931863727455, 1.9839679358717435, 2.002004008016032, 2.0200400801603204, 2.038076152304609, 2.056112224448898, 2.0741482965931866, 2.092184368737475, 2.1102204408817635, 2.1282565130260522, 2.1462925851703405, 2.164328657314629, 2.182364729458918, 2.2004008016032066, 2.218436873747495, 2.2364729458917836, 2.2545090180360723, 2.2725450901803605, 2.2905811623246493, 2.308617234468938, 2.3266533066132267, 2.344689378757515, 2.3627254509018036, 2.3807615230460923, 2.3987975951903806, 2.4168336673346693, 2.434869739478958, 2.4529058116232463, 2.470941883767535, 2.4889779559118237, 2.5070140280561124, 2.5250501002004007, 2.5430861723446894, 2.561122244488978, 2.5791583166332663, 2.597194388777555, 2.6152304609218437, 2.6332665330661325, 2.6513026052104207, 2.6693386773547094, 2.687374749498998, 2.7054108216432864, 2.723446893787575, 2.741482965931864, 2.7595190380761525, 2.7775551102204408, 2.7955911823647295, 2.813627254509018, 2.8316633266533064, 2.849699398797595, 2.867735470941884, 2.8857715430861726, 2.903807615230461, 2.9218436873747495, 2.9398797595190382, 2.9579158316633265, 2.975951903807615, 2.993987975951904, 3.012024048096192, 3.030060120240481, 3.0480961923847696, 3.0661322645290583, 3.0841683366733466, 3.1022044088176353, 3.120240480961924, 3.1382765531062122, 3.156312625250501, 3.1743486973947896, 3.1923847695390783, 3.2104208416833666, 3.2284569138276553, 3.246492985971944, 3.2645290581162323, 3.282565130260521, 3.3006012024048097, 3.3186372745490984, 3.3366733466933867, 3.3547094188376754, 3.372745490981964, 3.3907815631262523, 3.408817635270541, 3.4268537074148298, 3.444889779559118, 3.4629258517034067, 3.4809619238476954, 3.498997995991984, 3.5170340681362724, 3.535070140280561, 3.55310621242485, 3.571142284569138, 3.5891783567134268, 3.6072144288577155, 3.625250501002004, 3.6432865731462925, 3.661322645290581, 3.67935871743487, 3.697394789579158, 3.715430861723447, 3.7334669338677355, 3.7515030060120242, 3.7695390781563125, 3.787575150300601, 3.80561122244489, 3.823647294589178, 3.841683366733467, 3.8597194388777556, 3.8777555110220443, 3.8957915831663326, 3.9138276553106213, 3.93186372745491, 3.9498997995991982, 3.967935871743487, 3.9859719438877756, 4.004008016032064, 4.022044088176353, 4.040080160320641, 4.05811623246493, 4.076152304609218, 4.094188376753507, 4.112224448897796, 4.130260521042084, 4.148296593186373, 4.166332665330661, 4.18436873747495, 4.202404809619239, 4.220440881763527, 4.238476953907815, 4.2565130260521045, 4.274549098196393, 4.292585170340681, 4.31062124248497, 4.328657314629258, 4.346693386773547, 4.364729458917836, 4.382765531062124, 4.400801603206413, 4.4188376753507015, 4.43687374749499, 4.454909819639279, 4.472945891783567, 4.490981963927855, 4.509018036072145, 4.527054108216433, 4.545090180360721, 4.56312625250501, 4.5811623246492985, 4.599198396793587, 4.617234468937876, 4.635270541082164, 4.653306613226453, 4.671342685370742, 4.68937875751503, 4.707414829659319, 4.725450901803607, 4.7434869739478955, 4.761523046092185, 4.779559118236473, 4.797595190380761, 4.81563126252505, 4.833667334669339, 4.851703406813627, 4.869739478957916, 4.887775551102204, 4.905811623246493, 4.923847695390782, 4.94188376753507, 4.959919839679359, 4.977955911823647, 4.995991983967936, 5.014028056112225, 5.032064128256513, 5.050100200400801, 5.0681362725450905, 5.086172344689379, 5.104208416833667, 5.122244488977956, 5.140280561122244, 5.158316633266533, 5.176352705410822, 5.19438877755511, 5.212424849699399, 5.2304609218436875, 5.248496993987976, 5.266533066132265, 5.284569138276553, 5.302605210420841, 5.320641282565131, 5.338677354709419, 5.356713426853707, 5.374749498997996, 5.3927855711422845, 5.410821643286573, 5.428857715430862, 5.44689378757515, 5.4649298597194385, 5.482965931863728, 5.501002004008016, 5.519038076152305, 5.537074148296593, 5.5551102204408815, 5.573146292585171, 5.591182364729459, 5.609218436873747, 5.627254509018036, 5.645290581162325, 5.663326653306613, 5.681362725450902, 5.69939879759519, 5.717434869739479, 5.735470941883768, 5.753507014028056, 5.771543086172345, 5.789579158316633, 5.807615230460922, 5.825651302605211, 5.843687374749499, 5.861723446893787, 5.8797595190380765, 5.897795591182365, 5.915831663326653, 5.933867735470942, 5.95190380761523, 5.969939879759519, 5.987975951903808, 6.006012024048096, 6.024048096192384, 6.0420841683366735, 6.060120240480962, 6.078156312625251, 6.096192384769539, 6.114228456913827, 6.132264529058117, 6.150300601202405, 6.168336673346693, 6.186372745490982, 6.2044088176352705, 6.222444889779559, 6.240480961923848, 6.258517034068136, 6.2765531062124245, 6.294589178356714, 6.312625250501002, 6.330661322645291, 6.348697394789579, 6.3667334669338675, 6.384769539078157, 6.402805611222445, 6.420841683366733, 6.438877755511022, 6.456913827655311, 6.474949899799599, 6.492985971943888, 6.511022044088176, 6.529058116232465, 6.547094188376754, 6.565130260521042, 6.58316633266533, 6.601202404809619, 6.619238476953908, 6.637274549098197, 6.655310621242485, 6.673346693386773, 6.6913827655310625, 6.709418837675351, 6.727454909819639, 6.745490981963928, 6.763527054108216, 6.781563126252505, 6.799599198396794, 6.817635270541082, 6.83567134268537, 6.8537074148296595, 6.871743486973948, 6.889779559118236, 6.907815631262525, 6.925851703406813, 6.943887775551103, 6.961923847695391, 6.979959919839679, 6.997995991983968, 7.0160320641282565, 7.034068136272545, 7.052104208416834, 7.070140280561122, 7.0881763527054105, 7.1062124248497, 7.124248496993988, 7.142284569138276, 7.160320641282565, 7.1783567134268536, 7.196392785571143, 7.214428857715431, 7.232464929859719, 7.250501002004008, 7.268537074148297, 7.286573146292585, 7.304609218436874, 7.322645290581162, 7.340681362725451, 7.35871743486974, 7.376753507014028, 7.394789579158316, 7.412825651302605, 7.430861723446894, 7.448897795591182, 7.466933867735471, 7.484969939879759, 7.5030060120240485, 7.521042084168337, 7.539078156312625, 7.557114228456914, 7.575150300601202, 7.593186372745491, 7.61122244488978, 7.629258517034068, 7.647294589178356, 7.6653306613226455, 7.683366733466934, 7.701402805611222, 7.719438877755511, 7.7374749498997994, 7.755511022044089, 7.773547094188377, 7.791583166332665, 7.809619238476954, 7.8276553106212425, 7.845691382765531, 7.86372745490982, 7.881763527054108, 7.8997995991983965, 7.917835671342686, 7.935871743486974, 7.953907815631262, 7.971943887775551, 7.98997995991984, 8.008016032064129, 8.026052104208416, 8.044088176352705, 8.062124248496994, 8.080160320641282, 8.098196392785571, 8.11623246492986, 8.134268537074147, 8.152304609218437, 8.170340681362726, 8.188376753507015, 8.206412825651302, 8.224448897795591, 8.24248496993988, 8.260521042084168, 8.278557114228457, 8.296593186372746, 8.314629258517034, 8.332665330661323, 8.350701402805612, 8.3687374749499, 8.386773547094188, 8.404809619238478, 8.422845691382765, 8.440881763527054, 8.458917835671343, 8.47695390781563, 8.49498997995992, 8.513026052104209, 8.531062124248496, 8.549098196392785, 8.567134268537075, 8.585170340681362, 8.603206412825651, 8.62124248496994, 8.639278557114228, 8.657314629258517, 8.675350701402806, 8.693386773547093, 8.711422845691382, 8.729458917835672, 8.74749498997996, 8.765531062124248, 8.783567134268537, 8.801603206412826, 8.819639278557114, 8.837675350701403, 8.855711422845692, 8.87374749498998, 8.891783567134269, 8.909819639278558, 8.927855711422845, 8.945891783567134, 8.963927855711423, 8.98196392785571, 9.0])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.x = d3.scale.linear()\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.x = d3.scale.linear()\n", " .domain([0.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.legend = L.control({position: 'topright'});\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.legend.addTo(map_2ec7d88abd2232a9ed05d3d1bdae62d9);\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.legend = L.control({position: 'topright'});\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.legend.addTo(map_2fe6299aab429be5e64946fa852adcf1);\n", "\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.xAxis = d3.svg.axis()\n", - " .scale(color_map_4df795d703c51512148aa5b8c0075c1d.x)\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.xAxis = d3.svg.axis()\n", + " .scale(color_map_cd41b2020c8cf5087bb3041ff4524b9b.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.9176470588235294, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1.8352941176470587, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.7529411764705882, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.6705882352941175, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 4.588235294117647, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.5058823529411764, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 6.423529411764706, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 7.341176470588235, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 8.258823529411766, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.g = color_map_4df795d703c51512148aa5b8c0075c1d.svg.append("g")\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.g = color_map_cd41b2020c8cf5087bb3041ff4524b9b.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.g.selectAll("rect")\n", - " .data(color_map_4df795d703c51512148aa5b8c0075c1d.color.range().map(function(d, i) {\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.g.selectAll("rect")\n", + " .data(color_map_cd41b2020c8cf5087bb3041ff4524b9b.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_4df795d703c51512148aa5b8c0075c1d.x(color_map_4df795d703c51512148aa5b8c0075c1d.color.domain()[i - 1]) : color_map_4df795d703c51512148aa5b8c0075c1d.x.range()[0],\n", - " x1: i < color_map_4df795d703c51512148aa5b8c0075c1d.color.domain().length ? color_map_4df795d703c51512148aa5b8c0075c1d.x(color_map_4df795d703c51512148aa5b8c0075c1d.color.domain()[i]) : color_map_4df795d703c51512148aa5b8c0075c1d.x.range()[1],\n", + " x0: i ? color_map_cd41b2020c8cf5087bb3041ff4524b9b.x(color_map_cd41b2020c8cf5087bb3041ff4524b9b.color.domain()[i - 1]) : color_map_cd41b2020c8cf5087bb3041ff4524b9b.x.range()[0],\n", + " x1: i < color_map_cd41b2020c8cf5087bb3041ff4524b9b.color.domain().length ? color_map_cd41b2020c8cf5087bb3041ff4524b9b.x(color_map_cd41b2020c8cf5087bb3041ff4524b9b.color.domain()[i]) : color_map_cd41b2020c8cf5087bb3041ff4524b9b.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -904,12 +924,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_4df795d703c51512148aa5b8c0075c1d.g.call(color_map_4df795d703c51512148aa5b8c0075c1d.xAxis).append("text")\n", + " color_map_cd41b2020c8cf5087bb3041ff4524b9b.g.call(color_map_cd41b2020c8cf5087bb3041ff4524b9b.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("stroke_id");\n", " \n", - " function geo_json_b74bb6e4c718428b9e0aa4ecb476e382_styler(feature) {\n", + " function geo_json_dec813c8a622191caaa82e0fea238faf_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#f7fbff", "fillColor": "#f7fbff", "fillOpacity": 0.5, "weight": 8};\n", @@ -975,52 +996,54 @@ " return {"color": "#b7d4ea", "fillColor": "#b7d4ea", "fillOpacity": 0.5, "weight": 8};\n", " }\n", " }\n", - " function geo_json_b74bb6e4c718428b9e0aa4ecb476e382_highlighter(feature) {\n", + " function geo_json_dec813c8a622191caaa82e0fea238faf_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_b74bb6e4c718428b9e0aa4ecb476e382_pointToLayer(feature, latlng) {\n", + " function geo_json_dec813c8a622191caaa82e0fea238faf_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_b74bb6e4c718428b9e0aa4ecb476e382_styler(feature)\n", + " let style = geo_json_dec813c8a622191caaa82e0fea238faf_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_b74bb6e4c718428b9e0aa4ecb476e382_onEachFeature(feature, layer) {\n", + " function geo_json_dec813c8a622191caaa82e0fea238faf_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_b74bb6e4c718428b9e0aa4ecb476e382.resetStyle(e.target);\n", + " geo_json_dec813c8a622191caaa82e0fea238faf.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_b74bb6e4c718428b9e0aa4ecb476e382_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_dec813c8a622191caaa82e0fea238faf_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_b74bb6e4c718428b9e0aa4ecb476e382 = L.geoJson(null, {\n", - " onEachFeature: geo_json_b74bb6e4c718428b9e0aa4ecb476e382_onEachFeature,\n", + " var geo_json_dec813c8a622191caaa82e0fea238faf = L.geoJson(null, {\n", + " onEachFeature: geo_json_dec813c8a622191caaa82e0fea238faf_onEachFeature,\n", " \n", - " style: geo_json_b74bb6e4c718428b9e0aa4ecb476e382_styler,\n", - " pointToLayer: geo_json_b74bb6e4c718428b9e0aa4ecb476e382_pointToLayer,\n", + " style: geo_json_dec813c8a622191caaa82e0fea238faf_styler,\n", + " pointToLayer: geo_json_dec813c8a622191caaa82e0fea238faf_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_b74bb6e4c718428b9e0aa4ecb476e382_add (data) {\n", - " geo_json_b74bb6e4c718428b9e0aa4ecb476e382\n", + " function geo_json_dec813c8a622191caaa82e0fea238faf_add (data) {\n", + " geo_json_dec813c8a622191caaa82e0fea238faf\n", " .addData(data);\n", " }\n", - " geo_json_b74bb6e4c718428b9e0aa4ecb476e382_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#f7fbff", "mm_len": 264.1039496246775, "my_index": 0, "node_end": 1, "node_start": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#f1f7fd", "mm_len": 99.75118962647376, "my_index": 1, "node_end": 3, "node_start": 2}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#eaf2fb", "mm_len": 199.74650338337847, "my_index": 2, "node_end": 4, "node_start": 1}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#e3eef9", "mm_len": 203.01409000575802, "my_index": 3, "node_end": 3, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#dceaf6", "mm_len": 198.48272399064462, "my_index": 4, "node_end": 5, "node_start": 1}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#d6e6f4", "mm_len": 200.61768541143937, "my_index": 5, "node_end": 6, "node_start": 5}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#d0e1f2", "mm_len": 163.14628203947333, "my_index": 6, "node_end": 7, "node_start": 6}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#caddf0", "mm_len": 193.51137206831748, "my_index": 7, "node_end": 8, "node_start": 6}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#c1d9ed", "mm_len": 127.80086449751786, "my_index": 8, "node_end": 9, "node_start": 6}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#b7d4ea", "mm_len": 122.5319618088215, "my_index": 9, "node_end": 11, "node_start": 10}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "#abd0e6", "mm_len": 193.04063727323836, "my_index": 10, "node_end": 12, "node_start": 11}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "#a1cbe2", "mm_len": 88.92430548419476, "my_index": 11, "node_end": 13, "node_start": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "#94c4df", "mm_len": 107.88014814146449, "my_index": 12, "node_end": 5, "node_start": 2}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "#87bddc", "mm_len": 282.6905386499787, "my_index": 13, "node_end": 15, "node_start": 14}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "#79b5d9", "mm_len": 200.30351738673852, "my_index": 14, "node_end": 16, "node_start": 3}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "#6caed6", "mm_len": 200.3861708266132, "my_index": 15, "node_end": 10, "node_start": 3}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "#60a7d2", "mm_len": 191.66755798860544, "my_index": 16, "node_end": 13, "node_start": 4}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"__folium_color": "#549fcd", "mm_len": 202.03167967950094, "my_index": 17, "node_end": 16, "node_start": 4}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"__folium_color": "#4a98c9", "mm_len": 201.30697205908257, "my_index": 18, "node_end": 16, "node_start": 14}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"__folium_color": "#3f8fc5", "mm_len": 187.49184699173748, "my_index": 19, "node_end": 17, "node_start": 9}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"__folium_color": "#3787c0", "mm_len": 182.6849740039611, "my_index": 20, "node_end": 18, "node_start": 2}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"__folium_color": "#2e7ebc", "mm_len": 72.91516907666792, "my_index": 21, "node_end": 18, "node_start": 9}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"__folium_color": "#2575b7", "mm_len": 76.42465276315266, "my_index": 22, "node_end": 18, "node_start": 11}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"__folium_color": "#1d6cb1", "mm_len": 168.88041067114747, "my_index": 23, "node_end": 19, "node_start": 14}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"__folium_color": "#1764ab", "mm_len": 201.4861168351184, "my_index": 24, "node_end": 14, "node_start": 10}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"__folium_color": "#105ba4", "mm_len": 351.1551873514152, "my_index": 25, "node_end": 20, "node_start": 5}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"__folium_color": "#0a539e", "mm_len": 382.50195042922803, "my_index": 26, "node_end": 21, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"__folium_color": "#084a91", "mm_len": 172.0624733749828, "my_index": 27, "node_end": 22, "node_start": 10}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"__folium_color": "#084285", "mm_len": 138.23490844748363, "my_index": 28, "node_end": 23, "node_start": 0}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"__folium_color": "#083877", "mm_len": 255.8228880811063, "my_index": 29, "node_end": 24, "node_start": 13}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"__folium_color": "#08306b", "mm_len": 317.85221640975095, "my_index": 30, "node_end": 13, "node_start": 4}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_dec813c8a622191caaa82e0fea238faf_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#f7fbff", "mm_len": 264.1039496246775, "my_index": 0, "node_end": 1, "node_start": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#f1f7fd", "mm_len": 99.75118962647376, "my_index": 1, "node_end": 3, "node_start": 2}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#eaf2fb", "mm_len": 199.74650338337847, "my_index": 2, "node_end": 4, "node_start": 1}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#e3eef9", "mm_len": 203.01409000575802, "my_index": 3, "node_end": 3, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#dceaf6", "mm_len": 198.48272399064462, "my_index": 4, "node_end": 5, "node_start": 1}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#d6e6f4", "mm_len": 200.61768541143937, "my_index": 5, "node_end": 6, "node_start": 5}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#d0e1f2", "mm_len": 163.14628203947333, "my_index": 6, "node_end": 7, "node_start": 6}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#caddf0", "mm_len": 193.51137206831748, "my_index": 7, "node_end": 8, "node_start": 6}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#c1d9ed", "mm_len": 127.80086449751786, "my_index": 8, "node_end": 9, "node_start": 6}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#b7d4ea", "mm_len": 122.5319618088215, "my_index": 9, "node_end": 11, "node_start": 10}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "#abd0e6", "mm_len": 193.04063727323836, "my_index": 10, "node_end": 12, "node_start": 11}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "#a1cbe2", "mm_len": 88.92430548419476, "my_index": 11, "node_end": 13, "node_start": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "#94c4df", "mm_len": 107.88014814146449, "my_index": 12, "node_end": 5, "node_start": 2}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "#87bddc", "mm_len": 282.6905386499787, "my_index": 13, "node_end": 15, "node_start": 14}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "#79b5d9", "mm_len": 200.30351738673852, "my_index": 14, "node_end": 16, "node_start": 3}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "#6caed6", "mm_len": 200.3861708266132, "my_index": 15, "node_end": 10, "node_start": 3}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "#60a7d2", "mm_len": 191.66755798860544, "my_index": 16, "node_end": 13, "node_start": 4}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"__folium_color": "#549fcd", "mm_len": 202.03167967950094, "my_index": 17, "node_end": 16, "node_start": 4}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"__folium_color": "#4a98c9", "mm_len": 201.30697205908257, "my_index": 18, "node_end": 16, "node_start": 14}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"__folium_color": "#3f8fc5", "mm_len": 187.49184699173748, "my_index": 19, "node_end": 17, "node_start": 9}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"__folium_color": "#3787c0", "mm_len": 182.6849740039611, "my_index": 20, "node_end": 18, "node_start": 2}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"__folium_color": "#2e7ebc", "mm_len": 72.91516907666792, "my_index": 21, "node_end": 18, "node_start": 9}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"__folium_color": "#2575b7", "mm_len": 76.42465276315266, "my_index": 22, "node_end": 18, "node_start": 11}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"__folium_color": "#1d6cb1", "mm_len": 168.88041067114747, "my_index": 23, "node_end": 19, "node_start": 14}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"__folium_color": "#1764ab", "mm_len": 201.4861168351184, "my_index": 24, "node_end": 14, "node_start": 10}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"__folium_color": "#105ba4", "mm_len": 351.1551873514152, "my_index": 25, "node_end": 20, "node_start": 5}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"__folium_color": "#0a539e", "mm_len": 382.50195042922803, "my_index": 26, "node_end": 21, "node_start": 1}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"__folium_color": "#084a91", "mm_len": 172.0624733749828, "my_index": 27, "node_end": 22, "node_start": 10}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"__folium_color": "#084285", "mm_len": 138.23490844748363, "my_index": 28, "node_end": 23, "node_start": 0}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"__folium_color": "#083877", "mm_len": 255.8228880811063, "my_index": 29, "node_end": 24, "node_start": 13}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"__folium_color": "#08306b", "mm_len": 317.85221640975095, "my_index": 30, "node_end": 13, "node_start": 4}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_b74bb6e4c718428b9e0aa4ecb476e382.bindTooltip(\n", + " geo_json_dec813c8a622191caaa82e0fea238faf.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -1041,48 +1064,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_b74bb6e4c718428b9e0aa4ecb476e382.addTo(map_2ec7d88abd2232a9ed05d3d1bdae62d9);\n", + " geo_json_dec813c8a622191caaa82e0fea238faf.addTo(map_2fe6299aab429be5e64946fa852adcf1);\n", " \n", " \n", - " var color_map_9b247ac49c5f649f48504b13f26af503 = {};\n", + " var color_map_e795886b5389647b42c996f54fae0937 = {};\n", "\n", " \n", - " color_map_9b247ac49c5f649f48504b13f26af503.color = d3.scale.threshold()\n", + " color_map_e795886b5389647b42c996f54fae0937.color = d3.scale.threshold()\n", " .domain([0.0, 0.06012024048096192, 0.12024048096192384, 0.18036072144288579, 0.24048096192384769, 0.30060120240480964, 0.36072144288577157, 0.42084168336673344, 0.48096192384769537, 0.5410821643286573, 0.6012024048096193, 0.6613226452905812, 0.7214428857715431, 0.781563126252505, 0.8416833667334669, 0.9018036072144289, 0.9619238476953907, 1.0220440881763526, 1.0821643286573146, 1.1422845691382766, 1.2024048096192386, 1.2625250501002003, 1.3226452905811623, 1.3827655310621243, 1.4428857715430863, 1.503006012024048, 1.56312625250501, 1.623246492985972, 1.6833667334669338, 1.7434869739478958, 1.8036072144288577, 1.8637274549098197, 1.9238476953907815, 1.9839679358717435, 2.0440881763527052, 2.1042084168336674, 2.164328657314629, 2.224448897795591, 2.284569138276553, 2.344689378757515, 2.404809619238477, 2.464929859719439, 2.5250501002004007, 2.585170340681363, 2.6452905811623246, 2.7054108216432864, 2.7655310621242486, 2.8256513026052104, 2.8857715430861726, 2.9458917835671343, 3.006012024048096, 3.0661322645290583, 3.12625250501002, 3.186372745490982, 3.246492985971944, 3.306613226452906, 3.3667334669338675, 3.4268537074148298, 3.4869739478957915, 3.5470941883767537, 3.6072144288577155, 3.6673346693386772, 3.7274549098196395, 3.787575150300601, 3.847695390781563, 3.907815631262525, 3.967935871743487, 4.028056112224449, 4.0881763527054105, 4.148296593186373, 4.208416833667335, 4.268537074148297, 4.328657314629258, 4.38877755511022, 4.448897795591182, 4.509018036072145, 4.569138276553106, 4.629258517034068, 4.68937875751503, 4.749498997995992, 4.809619238476954, 4.869739478957916, 4.929859719438878, 4.98997995991984, 5.050100200400801, 5.110220440881764, 5.170340681362726, 5.2304609218436875, 5.290581162324649, 5.350701402805611, 5.410821643286573, 5.470941883767535, 5.531062124248497, 5.591182364729459, 5.651302605210421, 5.7114228456913825, 5.771543086172345, 5.831663326653307, 5.891783567134269, 5.95190380761523, 6.012024048096192, 6.072144288577154, 6.132264529058117, 6.192384769539078, 6.25250501002004, 6.312625250501002, 6.372745490981964, 6.432865731462926, 6.492985971943888, 6.55310621242485, 6.613226452905812, 6.673346693386773, 6.733466933867735, 6.793587174348698, 6.8537074148296595, 6.913827655310621, 6.973947895791583, 7.034068136272545, 7.094188376753507, 7.154308617234469, 7.214428857715431, 7.274549098196393, 7.3346693386773545, 7.394789579158316, 7.454909819639279, 7.515030060120241, 7.575150300601202, 7.635270541082164, 7.695390781563126, 7.755511022044089, 7.81563126252505, 7.875751503006012, 7.935871743486974, 7.995991983967936, 8.056112224448897, 8.11623246492986, 8.176352705410821, 8.236472945891784, 8.296593186372746, 8.356713426853707, 8.41683366733467, 8.47695390781563, 8.537074148296593, 8.597194388777556, 8.657314629258517, 8.71743486973948, 8.77755511022044, 8.837675350701403, 8.897795591182364, 8.957915831663327, 9.01803607214429, 9.07815631262525, 9.138276553106213, 9.198396793587174, 9.258517034068136, 9.318637274549099, 9.37875751503006, 9.438877755511022, 9.498997995991983, 9.559118236472946, 9.619238476953909, 9.67935871743487, 9.739478957915832, 9.799599198396793, 9.859719438877756, 9.919839679358718, 9.97995991983968, 10.040080160320642, 10.100200400801603, 10.160320641282565, 10.220440881763528, 10.280561122244489, 10.340681362725451, 10.400801603206412, 10.460921843687375, 10.521042084168336, 10.581162324649299, 10.641282565130261, 10.701402805611222, 10.761523046092185, 10.821643286573146, 10.881763527054108, 10.94188376753507, 11.002004008016032, 11.062124248496994, 11.122244488977955, 11.182364729458918, 11.24248496993988, 11.302605210420841, 11.362725450901804, 11.422845691382765, 11.482965931863728, 11.54308617234469, 11.603206412825651, 11.663326653306614, 11.723446893787575, 11.783567134268537, 11.843687374749498, 11.90380761523046, 11.963927855711423, 12.024048096192384, 12.084168336673347, 12.144288577154308, 12.20440881763527, 12.264529058116233, 12.324649298597194, 12.384769539078157, 12.444889779559118, 12.50501002004008, 12.565130260521043, 12.625250501002004, 12.685370741482966, 12.745490981963927, 12.80561122244489, 12.865731462925853, 12.925851703406813, 12.985971943887776, 13.046092184368737, 13.1062124248497, 13.16633266533066, 13.226452905811623, 13.286573146292586, 13.346693386773547, 13.40681362725451, 13.46693386773547, 13.527054108216433, 13.587174348697395, 13.647294589178356, 13.707414829659319, 13.76753507014028, 13.827655310621243, 13.887775551102205, 13.947895791583166, 14.008016032064129, 14.06813627254509, 14.128256513026052, 14.188376753507015, 14.248496993987976, 14.308617234468938, 14.3687374749499, 14.428857715430862, 14.488977955911823, 14.549098196392785, 14.609218436873748, 14.669338677354709, 14.729458917835672, 14.789579158316633, 14.849699398797595, 14.909819639278558, 14.969939879759519, 15.030060120240481, 15.090180360721442, 15.150300601202405, 15.210420841683367, 15.270541082164328, 15.330661322645291, 15.390781563126252, 15.450901803607215, 15.511022044088177, 15.571142284569138, 15.6312625250501, 15.691382765531062, 15.751503006012024, 15.811623246492985, 15.871743486973948, 15.93186372745491, 15.991983967935871, 16.052104208416832, 16.112224448897795, 16.172344689378757, 16.23246492985972, 16.292585170340683, 16.352705410821642, 16.412825651302605, 16.472945891783567, 16.53306613226453, 16.593186372745492, 16.65330661322645, 16.713426853707414, 16.773547094188377, 16.83366733466934, 16.893787575150302, 16.95390781563126, 17.014028056112224, 17.074148296593187, 17.13426853707415, 17.194388777555112, 17.25450901803607, 17.314629258517034, 17.374749498997996, 17.43486973947896, 17.49498997995992, 17.55511022044088, 17.615230460921843, 17.675350701402806, 17.73547094188377, 17.795591182364728, 17.85571142284569, 17.915831663326653, 17.975951903807616, 18.03607214428858, 18.096192384769537, 18.1563126252505, 18.216432865731463, 18.276553106212425, 18.336673346693388, 18.396793587174347, 18.45691382765531, 18.517034068136272, 18.577154308617235, 18.637274549098198, 18.697394789579157, 18.75751503006012, 18.817635270541082, 18.877755511022045, 18.937875751503007, 18.997995991983966, 19.05811623246493, 19.118236472945892, 19.178356713426854, 19.238476953907817, 19.298597194388776, 19.35871743486974, 19.4188376753507, 19.478957915831664, 19.539078156312627, 19.599198396793586, 19.65931863727455, 19.71943887775551, 19.779559118236474, 19.839679358717436, 19.899799599198396, 19.95991983967936, 20.02004008016032, 20.080160320641284, 20.140280561122246, 20.200400801603205, 20.260521042084168, 20.32064128256513, 20.380761523046093, 20.440881763527056, 20.501002004008015, 20.561122244488978, 20.62124248496994, 20.681362725450903, 20.741482965931862, 20.801603206412825, 20.861723446893787, 20.92184368737475, 20.981963927855713, 21.04208416833667, 21.102204408817634, 21.162324649298597, 21.22244488977956, 21.282565130260522, 21.34268537074148, 21.402805611222444, 21.462925851703407, 21.52304609218437, 21.583166332665332, 21.64328657314629, 21.703406813627254, 21.763527054108216, 21.82364729458918, 21.88376753507014, 21.9438877755511, 22.004008016032063, 22.064128256513026, 22.12424849699399, 22.18436873747495, 22.24448897795591, 22.304609218436873, 22.364729458917836, 22.4248496993988, 22.48496993987976, 22.54509018036072, 22.605210420841683, 22.665330661322646, 22.725450901803608, 22.78557114228457, 22.84569138276553, 22.905811623246493, 22.965931863727455, 23.026052104208418, 23.08617234468938, 23.14629258517034, 23.206412825651302, 23.266533066132265, 23.326653306613228, 23.386773547094187, 23.44689378757515, 23.507014028056112, 23.567134268537075, 23.627254509018037, 23.687374749498996, 23.74749498997996, 23.80761523046092, 23.867735470941884, 23.927855711422847, 23.987975951903806, 24.04809619238477, 24.10821643286573, 24.168336673346694, 24.228456913827657, 24.288577154308616, 24.34869739478958, 24.40881763527054, 24.468937875751504, 24.529058116232466, 24.589178356713425, 24.649298597194388, 24.70941883767535, 24.769539078156313, 24.829659318637276, 24.889779559118235, 24.949899799599198, 25.01002004008016, 25.070140280561123, 25.130260521042086, 25.190380761523045, 25.250501002004007, 25.31062124248497, 25.370741482965933, 25.430861723446895, 25.490981963927855, 25.551102204408817, 25.61122244488978, 25.671342685370742, 25.731462925851705, 25.791583166332664, 25.851703406813627, 25.91182364729459, 25.971943887775552, 26.03206412825651, 26.092184368737474, 26.152304609218437, 26.2124248496994, 26.272545090180362, 26.33266533066132, 26.392785571142284, 26.452905811623246, 26.51302605210421, 26.57314629258517, 26.63326653306613, 26.693386773547093, 26.753507014028056, 26.81362725450902, 26.87374749498998, 26.93386773547094, 26.993987975951903, 27.054108216432866, 27.11422845691383, 27.17434869739479, 27.23446893787575, 27.294589178356713, 27.354709418837675, 27.414829659318638, 27.4749498997996, 27.53507014028056, 27.595190380761522, 27.655310621242485, 27.715430861723448, 27.77555110220441, 27.83567134268537, 27.895791583166332, 27.955911823647295, 28.016032064128257, 28.07615230460922, 28.13627254509018, 28.196392785571142, 28.256513026052104, 28.316633266533067, 28.37675350701403, 28.43687374749499, 28.49699398797595, 28.557114228456914, 28.617234468937877, 28.677354709418836, 28.7374749498998, 28.79759519038076, 28.857715430861724, 28.917835671342687, 28.977955911823646, 29.03807615230461, 29.09819639278557, 29.158316633266534, 29.218436873747496, 29.278557114228455, 29.338677354709418, 29.39879759519038, 29.458917835671343, 29.519038076152306, 29.579158316633265, 29.639278557114228, 29.69939879759519, 29.759519038076153, 29.819639278557116, 29.879759519038075, 29.939879759519037, 30.0])\n", " .range(['#f7fbffff', '#f7fbffff', '#f6faffff', '#f6faffff', '#f5fafeff', '#f5fafeff', '#f5f9feff', '#f5f9feff', '#f4f9feff', '#f4f9feff', '#f3f8feff', '#f3f8feff', '#f2f8fdff', '#f2f8fdff', '#f2f7fdff', '#f2f7fdff', '#f1f7fdff', '#f1f7fdff', '#f0f6fdff', '#f0f6fdff', '#eff6fcff', '#eff6fcff', '#eef5fcff', '#eef5fcff', '#eef5fcff', '#eef5fcff', '#edf4fcff', '#edf4fcff', '#ecf4fbff', '#ecf4fbff', '#ebf3fbff', '#ebf3fbff', '#eaf3fbff', '#eaf3fbff', '#eaf2fbff', '#eaf2fbff', '#e9f2faff', '#e9f2faff', '#e8f1faff', '#e7f1faff', '#e7f1faff', '#e7f0faff', '#e7f0faff', '#e6f0faff', '#e6f0f9ff', '#e5eff9ff', '#e5eff9ff', '#e4eff9ff', '#e4eff9ff', '#e3eef9ff', '#e3eef9ff', '#e3eef8ff', '#e3eef8ff', '#e2edf8ff', '#e2edf8ff', '#e1edf8ff', '#e1edf8ff', '#e0ecf8ff', '#e0ecf8ff', '#dfecf7ff', '#dfecf7ff', '#dfebf7ff', '#dfebf7ff', '#deebf7ff', '#deebf7ff', '#ddeaf7ff', '#ddeaf7ff', '#dceaf6ff', '#dceaf6ff', '#dce9f6ff', '#dce9f6ff', '#dbe9f6ff', '#dbe9f6ff', '#dae8f6ff', '#dae8f6ff', '#d9e8f5ff', '#d9e8f5ff', '#d9e7f5ff', '#d8e7f5ff', '#d8e7f5ff', '#d7e7f5ff', '#d7e6f5ff', '#d6e6f5ff', '#d6e6f4ff', '#d6e5f4ff', '#d6e5f4ff', '#d5e5f4ff', '#d5e5f4ff', '#d4e4f4ff', '#d4e4f4ff', '#d3e4f3ff', '#d3e4f3ff', '#d3e3f3ff', '#d3e3f3ff', '#d2e3f3ff', '#d2e3f3ff', '#d1e2f3ff', '#d1e2f3ff', '#d0e2f2ff', '#d0e2f2ff', '#d0e1f2ff', '#d0e1f2ff', '#cfe1f2ff', '#cfe1f2ff', '#cee0f2ff', '#cee0f2ff', '#cde0f1ff', '#cde0f1ff', '#cddff1ff', '#cddff1ff', '#ccdff1ff', '#ccdff1ff', '#cbdef1ff', '#cbdef1ff', '#cadef0ff', '#cadef0ff', '#caddf0ff', '#c9ddf0ff', '#c9ddf0ff', '#c8ddf0ff', '#c8dcf0ff', '#c7dcf0ff', '#c7dcefff', '#c7dcefff', '#c7dbefff', '#c6dbefff', '#c5dbefff', '#c4daefff', '#c4daeeff', '#c3daeeff', '#c3daeeff', '#c2d9eeff', '#c2d9eeff', '#c1d9edff', '#c0d9edff', '#bfd8edff', '#bfd8edff', '#bed8ecff', '#bed8ecff', '#bdd7ecff', '#bdd7ecff', '#bcd7ebff', '#bbd7ebff', '#bad6ebff', '#bad6ebff', '#b9d6eaff', '#b9d6eaff', '#b8d5eaff', '#b8d5eaff', '#b7d4eaff', '#b6d4eaff', '#b5d4e9ff', '#b5d4e9ff', '#b4d3e9ff', '#b4d3e9ff', '#b3d3e8ff', '#b2d3e8ff', '#b2d2e8ff', '#b1d2e8ff', '#b0d2e7ff', '#afd2e7ff', '#afd1e7ff', '#aed1e7ff', '#aed1e7ff', '#add1e7ff', '#add0e6ff', '#acd0e6ff', '#abd0e6ff', '#aacfe6ff', '#aacfe5ff', '#a9cfe5ff', '#a9cfe5ff', '#a8cee4ff', '#a7cee4ff', '#a6cee4ff', '#a6cee4ff', '#a5cde3ff', '#a5cde3ff', '#a4cce3ff', '#a4cce3ff', '#a3cce3ff', '#a2cce3ff', '#a1cbe2ff', '#a1cbe2ff', '#a0cbe2ff', '#a0cbe2ff', '#9fcae1ff', '#9ecae1ff', '#9dcae1ff', '#9dcae1ff', '#9cc9e1ff', '#9bc9e1ff', '#9ac8e0ff', '#99c8e0ff', '#99c7e0ff', '#98c7e0ff', '#97c6dfff', '#96c6dfff', '#95c5dfff', '#94c5dfff', '#94c4dfff', '#93c4dfff', '#92c4deff', '#91c4deff', '#91c3deff', '#90c3deff', '#8fc2deff', '#8dc1deff', '#8dc1ddff', '#8cc0ddff', '#8bc0ddff', '#8abfddff', '#8abfddff', '#89beddff', '#88bedcff', '#87bddcff', '#86bddcff', '#85bcdcff', '#85bcdcff', '#84bcdbff', '#83bcdbff', '#82bbdbff', '#82bbdbff', '#81badbff', '#80badbff', '#7fb9daff', '#7eb9daff', '#7db8daff', '#7cb8daff', '#7cb7daff', '#7bb7daff', '#7ab6d9ff', '#79b6d9ff', '#79b5d9ff', '#78b5d9ff', '#77b5d9ff', '#76b5d9ff', '#75b4d8ff', '#74b4d8ff', '#74b3d8ff', '#73b3d8ff', '#72b2d8ff', '#71b2d8ff', '#71b1d7ff', '#70b1d7ff', '#6fb0d7ff', '#6eafd7ff', '#6dafd7ff', '#6caed7ff', '#6baed6ff', '#6aaed6ff', '#6aaed6ff', '#69add6ff', '#69add5ff', '#68acd5ff', '#67acd5ff', '#66abd5ff', '#66abd4ff', '#65aad4ff', '#65aad4ff', '#64a9d3ff', '#64a9d3ff', '#63a8d3ff', '#62a8d3ff', '#61a7d2ff', '#60a7d2ff', '#60a7d2ff', '#5fa7d2ff', '#5fa6d1ff', '#5ea6d1ff', '#5da5d1ff', '#5ca5d1ff', '#5ca4d0ff', '#5ba4d0ff', '#5ba3d0ff', '#5aa3d0ff', '#5aa2cfff', '#59a2cfff', '#58a1cfff', '#57a1cfff', '#57a0ceff', '#56a0ceff', '#56a0ceff', '#55a0ceff', '#549fcdff', '#539ecdff', '#539ecdff', '#529dcdff', '#529dccff', '#519cccff', '#509cccff', '#4f9bccff', '#4f9bcbff', '#4e9acbff', '#4e9acbff', '#4d99cbff', '#4c99caff', '#4b98caff', '#4b98caff', '#4a98c9ff', '#4998c9ff', '#4997c9ff', '#4897c9ff', '#4896c8ff', '#4796c8ff', '#4695c8ff', '#4595c8ff', '#4594c7ff', '#4494c7ff', '#4493c7ff', '#4393c7ff', '#4292c6ff', '#4192c6ff', '#4191c6ff', '#4091c6ff', '#4090c5ff', '#3f90c5ff', '#3f8fc5ff', '#3e8fc5ff', '#3e8ec4ff', '#3d8ec4ff', '#3d8dc4ff', '#3c8dc4ff', '#3c8cc3ff', '#3b8bc3ff', '#3b8bc2ff', '#3a8ac2ff', '#3a8ac2ff', '#3989c2ff', '#3989c1ff', '#3888c1ff', '#3888c1ff', '#3787c1ff', '#3787c0ff', '#3686c0ff', '#3686c0ff', '#3585c0ff', '#3485bfff', '#3484bfff', '#3384bfff', '#3383beff', '#3283beff', '#3282beff', '#3182beff', '#3181bdff', '#3081bdff', '#3080bdff', '#2f80bdff', '#2f7fbcff', '#2e7fbcff', '#2e7ebcff', '#2d7ebcff', '#2d7dbbff', '#2c7dbbff', '#2c7cbaff', '#2b7cbaff', '#2b7bbaff', '#2a7bbaff', '#2a7ab9ff', '#297ab9ff', '#2979b9ff', '#2878b9ff', '#2777b8ff', '#2676b8ff', '#2676b8ff', '#2575b8ff', '#2575b7ff', '#2474b7ff', '#2474b7ff', '#2373b7ff', '#2373b6ff', '#2272b6ff', '#2272b6ff', '#2171b6ff', '#2171b5ff', '#2070b5ff', '#2070b4ff', '#206fb4ff', '#1f6fb4ff', '#1f6eb4ff', '#1e6eb3ff', '#1e6db2ff', '#1d6db2ff', '#1d6cb1ff', '#1c6cb1ff', '#1c6bb0ff', '#1c6bb0ff', '#1c6ab0ff', '#1b6ab0ff', '#1b69afff', '#1a69afff', '#1a68aeff', '#1968aeff', '#1967adff', '#1967adff', '#1966adff', '#1866adff', '#1865acff', '#1765acff', '#1764abff', '#1663abff', '#1663aaff', '#1562aaff', '#1562a9ff', '#1561a9ff', '#1561a9ff', '#1460a9ff', '#1460a8ff', '#135fa8ff', '#135fa7ff', '#125ea7ff', '#125ea6ff', '#125da6ff', '#125da6ff', '#115ca6ff', '#105ca5ff', '#105ba5ff', '#0f5ba4ff', '#0f5aa4ff', '#0e5aa3ff', '#0e59a3ff', '#0e59a2ff', '#0e58a2ff', '#0d58a2ff', '#0d57a1ff', '#0c57a1ff', '#0c56a0ff', '#0b56a0ff', '#0b559fff', '#0a559fff', '#0a549eff', '#0a549eff', '#0a539eff', '#09539eff', '#09529dff', '#08529dff', '#08519cff', '#08509cff', '#08509bff', '#084f9aff', '#084f99ff', '#084e99ff', '#084e98ff', '#084d97ff', '#084d96ff', '#084c96ff', '#084c95ff', '#084b94ff', '#084b93ff', '#084a92ff', '#084a91ff', '#084991ff', '#084990ff', '#08488fff', '#08488eff', '#08478eff', '#08478dff', '#08468cff', '#08468bff', '#08458aff', '#08458aff', '#084489ff', '#084488ff', '#084387ff', '#084387ff', '#084286ff', '#084285ff', '#084184ff', '#084184ff', '#084083ff', '#083f82ff', '#083e81ff', '#083e81ff', '#083d80ff', '#083d7fff', '#083c7eff', '#083b7dff', '#083b7cff', '#083a7bff', '#083a7aff', '#08397aff', '#083979ff', '#083878ff', '#083877ff', '#083777ff', '#083776ff', '#083675ff', '#083674ff', '#083574ff', '#083573ff', '#083472ff', '#083471ff', '#083371ff', '#083370ff', '#08326fff', '#08326eff', '#08316dff', '#08316dff', '#08306cff', '#08306bff']);\n", " \n", "\n", - " color_map_9b247ac49c5f649f48504b13f26af503.x = d3.scale.linear()\n", + " color_map_e795886b5389647b42c996f54fae0937.x = d3.scale.linear()\n", " .domain([0.0, 30.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_9b247ac49c5f649f48504b13f26af503.legend = L.control({position: 'topright'});\n", - " color_map_9b247ac49c5f649f48504b13f26af503.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_9b247ac49c5f649f48504b13f26af503.legend.addTo(map_2ec7d88abd2232a9ed05d3d1bdae62d9);\n", + " color_map_e795886b5389647b42c996f54fae0937.legend = L.control({position: 'topright'});\n", + " color_map_e795886b5389647b42c996f54fae0937.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_e795886b5389647b42c996f54fae0937.legend.addTo(map_2fe6299aab429be5e64946fa852adcf1);\n", "\n", - " color_map_9b247ac49c5f649f48504b13f26af503.xAxis = d3.svg.axis()\n", - " .scale(color_map_9b247ac49c5f649f48504b13f26af503.x)\n", + " color_map_e795886b5389647b42c996f54fae0937.xAxis = d3.svg.axis()\n", + " .scale(color_map_e795886b5389647b42c996f54fae0937.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.0588235294117645, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 6.117647058823529, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 9.176470588235293, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 12.235294117647058, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 15.294117647058824, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 18.352941176470587, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 21.41176470588235, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 24.470588235294116, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 27.529411764705884, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_9b247ac49c5f649f48504b13f26af503.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_e795886b5389647b42c996f54fae0937.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_9b247ac49c5f649f48504b13f26af503.g = color_map_9b247ac49c5f649f48504b13f26af503.svg.append("g")\n", + " color_map_e795886b5389647b42c996f54fae0937.g = color_map_e795886b5389647b42c996f54fae0937.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_9b247ac49c5f649f48504b13f26af503.g.selectAll("rect")\n", - " .data(color_map_9b247ac49c5f649f48504b13f26af503.color.range().map(function(d, i) {\n", + " color_map_e795886b5389647b42c996f54fae0937.g.selectAll("rect")\n", + " .data(color_map_e795886b5389647b42c996f54fae0937.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_9b247ac49c5f649f48504b13f26af503.x(color_map_9b247ac49c5f649f48504b13f26af503.color.domain()[i - 1]) : color_map_9b247ac49c5f649f48504b13f26af503.x.range()[0],\n", - " x1: i < color_map_9b247ac49c5f649f48504b13f26af503.color.domain().length ? color_map_9b247ac49c5f649f48504b13f26af503.x(color_map_9b247ac49c5f649f48504b13f26af503.color.domain()[i]) : color_map_9b247ac49c5f649f48504b13f26af503.x.range()[1],\n", + " x0: i ? color_map_e795886b5389647b42c996f54fae0937.x(color_map_e795886b5389647b42c996f54fae0937.color.domain()[i - 1]) : color_map_e795886b5389647b42c996f54fae0937.x.range()[0],\n", + " x1: i < color_map_e795886b5389647b42c996f54fae0937.color.domain().length ? color_map_e795886b5389647b42c996f54fae0937.x(color_map_e795886b5389647b42c996f54fae0937.color.domain()[i]) : color_map_e795886b5389647b42c996f54fae0937.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -1092,35 +1119,40 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_9b247ac49c5f649f48504b13f26af503.g.call(color_map_9b247ac49c5f649f48504b13f26af503.xAxis).append("text")\n", + " color_map_e795886b5389647b42c996f54fae0937.g.call(color_map_e795886b5389647b42c996f54fae0937.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("my_index");\n", " \n", - " var layer_control_bec17d9d5a988995aa8759f035d98964_layers = {\n", + " var layer_control_2d8344a1de70f7cc81dbbe7dc289198c_layers = {\n", " base_layers : {\n", - " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_89e4c5719cd7b695aa891255acc48f43,\n", + " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_8de714aba5d347398e64e486ed5940b8,\n", " },\n", " overlays : {\n", - " "strokes" : geo_json_f69503db37bc7e131351577d6042c1b5,\n", - " "lines" : geo_json_b74bb6e4c718428b9e0aa4ecb476e382,\n", + " "strokes" : geo_json_ba8489f3488749c7d1c6928d4b5df489,\n", + " "lines" : geo_json_dec813c8a622191caaa82e0fea238faf,\n", " },\n", " };\n", - " let layer_control_bec17d9d5a988995aa8759f035d98964 = L.control.layers(\n", - " layer_control_bec17d9d5a988995aa8759f035d98964_layers.base_layers,\n", - " layer_control_bec17d9d5a988995aa8759f035d98964_layers.overlays,\n", - " {"autoZIndex": true, "collapsed": true, "position": "topright"}\n", - " ).addTo(map_2ec7d88abd2232a9ed05d3d1bdae62d9);\n", + " let layer_control_2d8344a1de70f7cc81dbbe7dc289198c = L.control.layers(\n", + " layer_control_2d8344a1de70f7cc81dbbe7dc289198c_layers.base_layers,\n", + " layer_control_2d8344a1de70f7cc81dbbe7dc289198c_layers.overlays,\n", + " {\n", + " "position": "topright",\n", + " "collapsed": true,\n", + " "autoZIndex": true,\n", + "}\n", + " ).addTo(map_2fe6299aab429be5e64946fa852adcf1);\n", "\n", " \n", "</script>\n", "</html>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen>" ], "text/plain": [ - "" + "" ] }, - "execution_count": 12, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -1143,7 +1175,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ @@ -1192,7 +1224,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 34, "metadata": {}, "outputs": [ { @@ -1201,7 +1233,7 @@ "NodeDataView({0: {'edge_indeces': [0, 3, 15, 27], 'geometry': , 'geometry_stroke': , 'x': 1603374.6625343116, 'y': 6464077.898491419, 'connectivity': 0}, 1: {'edge_indeces': [1, 12, 14, 25], 'geometry': , 'geometry_stroke': , 'x': 1603237.0487682838, 'y': 6464133.622486805, 'connectivity': 0}, 2: {'edge_indeces': [2, 11, 28, 30], 'geometry': , 'geometry_stroke': , 'x': 1603707.1065106073, 'y': 6464238.853991265, 'connectivity': 0}, 3: {'edge_indeces': [4, 5, 6], 'geometry': , 'geometry_stroke': , 'x': 1603149.9288811635, 'y': 6464130.224503239, 'connectivity': 0}, 4: {'edge_indeces': [7, 8, 9, 13, 21, 22, 24], 'geometry': , 'geometry_stroke': , 'x': 1603264.6577362637, 'y': 6463848.97596353, 'connectivity': 0}, 5: {'edge_indeces': [10], 'geometry': , 'geometry_stroke': , 'x': 1603137.4077031056, 'y': 6463800.908382258, 'connectivity': 0}, 6: {'edge_indeces': [16, 17, 18, 23, 29], 'geometry': , 'geometry_stroke': , 'x': 1603592.2349246691, 'y': 6464121.336160048, 'connectivity': 0}, 7: {'edge_indeces': [19], 'geometry': , 'geometry_stroke': , 'x': 1603028.737187382, 'y': 6463900.594576759, 'connectivity': 0}, 8: {'edge_indeces': [20], 'geometry': , 'geometry_stroke': , 'x': 1603207.5969886228, 'y': 6463992.707728057, 'connectivity': 0}, 9: {'edge_indeces': [26], 'geometry': , 'geometry_stroke': , 'x': 1603342.3426854417, 'y': 6464406.368225728, 'connectivity': 0}})" ] }, - "execution_count": 14, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } @@ -1239,7 +1271,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 35, "metadata": {}, "outputs": [ { @@ -1254,7 +1286,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1269,7 +1301,7 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([1, 2])\n", - "angles: [62.302182356951434]\n", + "angles: [np.float64(62.302182356951434)]\n", "(0, 2) added\n", "**************************************************************\n", " \n", @@ -1283,7 +1315,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1298,14 +1330,14 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([2, 1])\n", - "angles: [36.134980718680936]\n", + "angles: [np.float64(36.134980718680936)]\n", "(0, 9) added\n", "Checking edge: (0, 2)\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1320,15 +1352,15 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([2, 1])\n", - "angles: [63.647466378271766]\n", - "(0, 2) already in graph, angles = [62.302182356951434]\n", - "(0, 2) already in graph, angles updated = [62.302182356951434, 63.647466378271766]\n", + "angles: [np.float64(63.647466378271766)]\n", + "(0, 2) already in graph, angles = [np.float64(62.302182356951434)]\n", + "(0, 2) already in graph, angles updated = [np.float64(62.302182356951434), np.float64(63.647466378271766)]\n", "Checking edge: (0, 3)\n" ] }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGTCAYAAABwJ4sYAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABd50lEQVR4nO3deVhUVR8H8O+wDfsuOyouoaIIAgLuiGigvpZZlpVLtltm5FtppbZqvlZuqVnkmkvmWm7hAm6AILjvioJsirIvwzL3/YOYHEFgGOAO8P08zzxPc7lz74/B7nznnHPPkQiCIICIiIhIDVpiF0BERETNHwMFERERqY2BgoiIiNTGQEFERERqY6AgIiIitTFQEBERkdoYKIiIiEhtDBRERESkNgYKIiIiUhsDBREREamNgYJIg+Xl5WHatGlo164dDAwM0KdPH8TGxopdFhFpqOXLl8Pd3R2mpqYwNTWFv78/9u7dW+NrIiMj4eXlBX19fXTo0AErVqyo17kZKIg02Kuvvorw8HCsW7cO586dw9ChQzFkyBCkpKSIXRoRaSAnJyfMmzcPcXFxiIuLw+DBgzFq1ChcuHCh2v0TExMREhKC/v37IyEhATNnzsTUqVOxdetWlc8t4eJgRJqpqKgIJiYm2LlzJ4YPH67Y7uHhgREjRuCrr74SsToiai4sLS3xv//9D5MnT67ys48++gi7du3CpUuXFNvefPNNnDlzBlFRUSqdR0ftSolageLiYpSUlKh9HEEQIJFIlLZJpVJIpdIq+5aVlaG8vBz6+vpK2w0MDHDs2DG1ayGixtVQ1w1AtWtHpfLycmzZsgUFBQXw9/evdp+oqCgMHTpUaduwYcMQFhaG0tJS6Orq1rlGBgqiWhQXF8PS0hJFRUVqH8vY2Bj5+flK22bPno05c+ZU2dfExAT+/v748ssv0bVrV9ja2mLjxo2IiYlB586d1a6FiBpPQ143ANWuHefOnYO/vz+Ki4thbGyM7du3o1u3btUeNz09Hba2tkrbbG1tUVZWhszMTNjb29e5RgYKolqUlJSgqKgI48aNg56enlrH2bBhA5KTk2FqaqrYXtM3jHXr1uGVV16Bo6MjtLW10atXL4wbNw7x8fH1roOIGl9DXTcqj6XKtcPV1RWnT59GdnY2tm7digkTJiAyMvKxoeLRlo/KkRCPbq8NAwVRHenp6al9YQCgGH1dFx07dkRkZCQKCgqQm5sLe3t7jB07Fi4uLmrXQUSNr6GuG0Ddrx16enro1KkTAMDb2xuxsbFYtGgRfvrppyr72tnZIT09XWnb3bt3oaOjAysrK5Xq410eRM2AkZER7O3tkZWVhf3792PUqFFil0REzYQgCJDJZNX+zN/fH+Hh4Urb/v77b3h7e6s0fgJgCwWRRtu/fz8EQYCrqyuuX7+O//73v3B1dcWkSZPELo2INNDMmTMRHBwMZ2dn5OXlYdOmTYiIiMC+ffsAADNmzEBKSgrWrl0LoOKOjqVLlyI0NBSvvfYaoqKiEBYWho0bN6p8bgYKIg2Wk5ODGTNm4M6dO7C0tMQzzzyDr7/+WuVvDkTUOmRkZODll19GWloazMzM4O7ujn379iEoKAgAkJaWhqSkJMX+Li4u2LNnD95//338+OOPcHBwwOLFi/HMM8+ofG4GCiIN9txzz+G5554TuwwiaibCwsJq/Pnq1aurbBs4cGCDDPTmGAoiIiJSGwMFERERqY2BgoiIiNTGQEFERERqY6AgIiIitTFQEBERkdoYKIiIiEhtDBRERESkNgYKIiIiUhsDBREREamNgYKIiIjUxkBBREREamOgICIiIrUxUBAREZHaGCiIiIhIbQwUREREpDYGCiIiIlIbAwURERGpjYGCiIiI1MZAQURERGpjoCAiIiK1MVAQERGR2hgoiIiISG0MFERERKQ2BgoiIiJSGwMFERERqY2BgoiIiNTGQEFERERqY6AgIiIitTFQEBERkdoYKIg0VFlZGT799FO4uLjAwMAAHTp0wBdffAG5XC52aUREVeiIXQARVe/bb7/FihUrsGbNGri5uSEuLg6TJk2CmZkZ3nvvPbHLIyJSwkBBpKGioqIwatQoDB8+HADQvn17bNy4EXFxcSJXRkRUFbs8iJpYbm6u0kMmk1W7X79+/XDw4EFcvXoVAHDmzBkcO3YMISEhTVkuEVGdsIWCqIk5OzsrPZ89ezbmzJlTZb+PPvoIOTk56NKlC7S1tVFeXo6vv/4aL7zwQhNVSkRUdwwURE0sOTkZpqamiudSqbTa/TZv3oz169djw4YNcHNzw+nTpzFt2jQ4ODhgwoQJTVUuEVGdMFAQNTFTU1OlQPE4//3vf/Hxxx/j+eefBwD06NEDt2/fxty5cxkoiEjjcAwFkYYqLCyElpby/6La2tq8bZSINBJbKIg01MiRI/H111+jbdu2cHNzQ0JCAr7//nu88sorYpdGRFQFAwVRHfUzC4ehtP6NeoUyOVarsP+SJUvw2Wef4e2338bdu3fh4OCAN954A7Nmzap3DUTUtNS9bgCqXzvEwkBBpKFMTEywcOFCLFy4UOxSiIhqxTEUREREpDYGCiIiIlJbgwaKxYsXQyKRoHv37o/dRyKRKE3iExERAYlEgoiICLXPv2fPnmonCGoIq1evhkQiaTbTHm/YsEEjm8ob8u9daeHChRg9ejRcXFwgkUgwaNCgBjs2ERHVTYMGil9//RUAcOHCBcTExDTkoetkz549+Pzzz5v8vJpIUwNFY1ixYgVu376NwYMHo02bNmKXQ0TUKjVYoIiLi8OZM2cUCxmFhYU11KEbhSAIKCoqErsMagAXL17EqVOnEBYWBhsbG7HLISJqlRosUFQGiHnz5qFPnz7YtGkTCgsLG+rwKCwsxPTp0+Hi4gJ9fX1YWlrC29sbGzduBABMnDgRP/74I4CKbpXKx61btxTb3nnnHaxYsQJdu3aFVCrFmjVrAADHjh1DYGAgTExMYGhoiD59+mD37t211pSWlgYvLy907twZ165dA1Cx8FNlnXp6enB0dMS0adNQUFCg9NotW7bA19cXZmZmMDQ0RIcOHeo0v8CPP/6IAQMGwMbGBkZGRujRowfmz5+P0tJSxT6DBg3C7t27cfv2baX3oibt27fHiBEjsG/fPvTq1QsGBgbo0qWLotXpYefPn8eoUaNgYWEBfX19eHh4KN7Lh12+fBlPPvkkDA0NYW1tjTfffBN5eXnVnv/AgQMIDAyEqakpDA0N0bdvXxw8eLDW9wNAlcmfiIio6TXIbaNFRUXYuHEjfHx80L17d7zyyit49dVXsWXLlgabIjg0NBTr1q3DV199BU9PTxQUFOD8+fO4f/8+AOCzzz5DQUEB/vjjD0RFRSleZ29vr/jvHTt24OjRo5g1axbs7OxgY2ODyMhIBAUFwd3dHWFhYZBKpVi2bBlGjhyJjRs3YuzYsdXWc/78eYSEhMDJyQlRUVGwtrZGYWEhBg4ciDt37mDmzJlwd3fHhQsXMGvWLJw7dw4HDhyARCJBVFQUxo4di7Fjx2LOnDnQ19fH7du3cejQoVrfhxs3bmDcuHGKwHLmzBl8/fXXuHz5suLDf9myZXj99ddx48YNbN++vc7v8ZkzZ/DBBx/g448/hq2tLX755RdMnjwZnTp1woABAwAAV65cQZ8+fWBjY4PFixfDysoK69evx8SJE5GRkYEPP/wQAJCRkYGBAwdCV1cXy5Ytg62tLX777Te88847Vc67fv16jB8/HqNGjcKaNWugq6uLn376CcOGDcP+/fsRGBhY59+BiIjE0SCB4o8//kBOTg4mT54MABg7diymTZuGsLCwBgsUx48fx9ChQ/H+++8rtlV2rwBAx44dYWtrCwDw8/Or9hj5+fk4d+4cLCwsFNv8/f1hYWGBiIgIGBsbAwBGjBgBDw8PTJ8+Hc8991yVb/cHDhzAM888g6FDh2LdunXQ19cHUDEo9ezZs4iJiYG3tzcAIDAwEI6OjhgzZgz27duH4OBgnDhxAoIgYMWKFTAzM1Mcd+LEibW+D99//73iv+VyOfr37w8rKytMmjQJ3333HSwsLNCtWzeYm5tDKpU+9r2oTmZmJo4fP462bdsCAAYMGICDBw9iw4YNikAxZ84clJSU4PDhw4pVM0NCQpCdnY3PP/8cb7zxBszMzPDDDz/g3r17SEhIQM+ePQEAwcHBGDp0KJKSkhTnLCwsxHvvvYcRI0YohZ+QkBD06tULM2fOFGU8DhERqaZB2orDwsJgYGCgWMTI2NgYzz77LI4eParoClBX7969sXfvXnz88ceIiIio1/iHwYMHK4WJgoICxMTEYMyYMYowAVSsl/Dyyy/jzp07uHLlitIx1qxZg5CQELz66qv4/fffFWECAP766y90794dHh4eKCsrUzyGDRumdGeDj48PAOC5557D77//jpSUlDr/DgkJCfjPf/4DKysraGtrQ1dXF+PHj0d5eTmuXr2q8nvyMA8PD0WYAAB9fX088cQTuH37tmLboUOHEBgYWGUJ7okTJ6KwsFDROnT48GG4ubkpwkSlcePGKT0/ceIEHjx4gAkTJii9Z3K5HE8++SRiY2OrdBcREZHmUTtQXL9+HUeOHMHw4cMhCAKys7ORnZ2NMWPGAEC1ffD1sXjxYnz00UfYsWMHAgICYGlpiaeeekqlwPJw9wcAZGVlQRCEKtsBwMHBAQAUXSqVNm3aBAMDA7z66qtVWi4yMjJw9uxZ6OrqKj1MTEwgCAIyMzMBVHzz37FjB8rKyjB+/Hg4OTmhe/fuivEgj5OUlIT+/fsjJSUFixYtwtGjRxEbG6sYO6LuIFMrK6sq26RSqdJx79+/X6f36/79+7Czs6uy36PbMjIyAABjxoyp8r59++23EAQBDx48qP8vRURETULtQPHrr79CEAT88ccfsLCwUDwquyPWrFmD8vJytQs1MjLC559/jsuXLyM9PR3Lly9HdHQ0Ro4cWedjPBoALCwsoKWlhbS0tCr7pqamAgCsra2Vtv/222/o0qULBg4ciNOnTyv9zNraGj169EBsbGy1j88++0yx76hRo3Dw4EHk5OQgIiICTk5OGDdunNL4j0ft2LEDBQUF2LZtG1566SX069cP3t7e0NPTq/N7oC4rK6s6vV9WVlZIT0+vst+j2yr3X7JkyWPft8quLCIiqtncuXPh4+MDExMT2NjY4KmnnqrS0v6oyvmBHn1cvnxZpXOrNYaivLwca9asQceOHfHLL79U+flff/2F7777Dnv37sWIESPUOZUSW1tbTJw4EWfOnMHChQtRWFgIQ0NDSKVSABXf1A0MDGo9jpGREXx9fbFt2zYsWLBA8Rq5XI7169fDyckJTzzxhNJrLC0tceDAAYwYMQIBAQHYu3evYpzCiBEj8M0338DKygouLi51+l2kUikGDhwIc3Nz7N+/HwkJCfD3969238pAVPl7AhW3v/7888/VHrcxbosNDAzE9u3bkZqaqmiVAIC1a9fC0NBQ8V4EBARg/vz5OHPmjFK3x4YNG5SO17dvX5ibm+PixYvVDtgkIqK6i4yMxJQpU+Dj44OysjJ88sknGDp0KC5evAgjI6MaX3vlyhWYmpoqnqs6r49agWLv3r1ITU3Ft99+W+3shN27d8fSpUsRFhamdqDw9fXFiBEj4O7uDgsLC1y6dAnr1q2Dv78/DA0NAQA9evQAAHz77bcIDg6GtrY23N3da/wGP3fuXAQFBSEgIADTp0+Hnp4eli1bhvPnz2Pjxo3V3m5pYmKCffv2YfTo0QgKCsKuXbsQEBCAadOmYevWrRgwYADef/99uLu7Qy6XIykpCX///Tc++OAD+Pr6YtasWbhz5w4CAwPh5OSE7OxsLFq0CLq6uhg4cOBjaw0KCoKenh5eeOEFfPjhhyguLsby5cuRlZVVZd8ePXpg27ZtWL58Oby8vKClpaUYKKqO2bNn46+//kJAQABmzZoFS0tL/Pbbb9i9ezfmz5+vGGQ6bdo0/Prrrxg+fDi++uorxV0ejyZeY2NjLFmyBBMmTMCDBw8wZswY2NjY4N69ezhz5gzu3buH5cuX11hTXFyc4vbg3NxcRYsZUDFepV27dmr/3kREzcG+ffuUnq9atQo2NjY4deqUYnD949jY2MDc3Lze51YrUISFhUFPTw+TJk2q9ufW1tZ4+umn8ccffyAjI0OtpuvBgwdj165d+OGHH1BYWAhHR0eMHz8en3zyiWKfcePG4fjx41i2bBm++OILCIKAxMREtG/f/rHHHThwIA4dOoTZs2dj4sSJkMvl6NmzJ3bt2lVjCDIwMMDOnTsxbtw4hISEYOvWrQgJCcHRo0cxb948rFy5EomJiTAwMEDbtm0xZMgQRR2+vr6Ii4vDRx99hHv37sHc3Bze3t44dOgQ3NzcHnvOLl26YOvWrfj0008xevRoWFlZYdy4cQgNDUVwcLDSvu+99x4uXLiAmTNnIicnB4IgQBCEur3ZNXB1dcWJEycwc+ZMTJkyBUVFRejatStWrVqldJeKnZ0dIiMj8d577+Gtt96CoaEhnn76aSxduhSjRo1SOuZLL72Etm3bYv78+XjjjTeQl5cHGxsbeHh41OnOl6VLl1aZB+PZZ58FgCp1ERE1V7m5uUrPpVKpUot1dXJycgBUtK7XxtPTE8XFxejWrRs+/fRTBAQEqFSfRGiITxmiFiw3NxdmZmb45T1HGErrP+yoUCbHq4tSkJOTo9SsSEQtT0NdN4B/rx2Pmj17do3rVwmCgFGjRiErKwtHjx597H5XrlzBkSNH4OXlBZlMhnXr1mHFihWIiIiotVXjYQ0yDwURERE1ruTkZKUvI7W1Trzzzjs4e/Ysjh07VuN+rq6ucHV1VTz39/dHcnIyFixYoFKg4JzFREREzYCpqanSo6ZA8e6772LXrl04fPgwnJycVD6Xn5+fyvNIsYWCiIiohRAEAe+++y62b9+OiIiIOt9x+KiEhIRq5xyqCVsoiEhtMTExePrpp9G2bVtIpVLY2trC398fH3zwgdJ+y5Ytw+rVqxulhokTJyrNeCumo0ePQiqVKs0yCwDx8fEYMmQIjI2NYW5ujtGjR+PmzZv1Ps+BAwcQFBQEBwcHSKVS2NjYYPDgwdizZ4/SfqWlpejYsSMWLlxY73M9zjfffIMdO3Y0+HHVNWfOnFoXRVRFXl4ePvzwQwwdOhRt2rSBRCKpcfyCWKZMmYL169djw4YNMDExQXp6OtLT05WmEZgxYwbGjx+veL5w4ULs2LED165dw4ULFzBjxgxs3bpV5Vv5GSiISC27d+9Gnz59kJubi/nz5+Pvv//GokWL0LdvX2zevFlp38YMFJpCEARMmzYNr732mtIty5cvX8agQYNQUlKC33//Hb/++iuuXr2K/v374969e/U61/379+Hm5oYffvgBf//9N3766Sfo6upi+PDhWL9+vWI/XV1dzJo1C1988UWV2X/VpamBoqHdv38fK1euhEwmw1NPPSV2OY+1fPly5OTkYNCgQbC3t1c8Hv5/MS0tTWlNpZKSEkyfPh3u7u7o378/jh07ht27d2P06NEqnZtdHkSklvnz58PFxQX79++Hjs6/l5Tnn38e8+fPr/dxS0tLIZFIlI7ZHOzbtw/x8fFVJnGbNWsWpFIp/vrrL8XAOi8vL3Tu3BkLFizAt99+q/K5KlctftiIESPg4uKClStX4qWXXlJsf+GFFxAaGoqffvoJM2fOrMdv1rq1a9cOWVlZkEgkyMzMrHYyR01Qlxs3Hw31H374oWKlaHWwhYKI1HL//n1YW1tX+8GvpfXvJaZ9+/a4cOECIiMjFVP7Vs7NUjn177p16/DBBx/A0dERUqkU169fB1AxxX/Pnj2hr68PS0tLPP3007h06VKttR0/fhzW1tYYMWKEYpG5a9euYdy4cbCxsYFUKkXXrl0V6+FUksvl+Oqrr+Dq6goDAwOYm5vD3d0dixYtqvWcy5cvh4+Pj9Ko+bKyMvz111945plnlEbpt2vXDgEBAUor7apLV1cX5ubmVf4eenp6GDt2LFauXFnrh05xcTE++OADeHh4wMzMDJaWlvD398fOnTuV9pNIJCgoKMCaNWsUf9PqJjmsdOvWLUgkEixYsADff/89XFxcYGxsDH9/f0RHR1fZf9euXYrJC01MTBAUFFTt8gS7d++Gh4cHpFIpXFxcsGDBgmrPLwgCli1bBg8PDxgYGMDCwgJjxoypU7dT5e9Hj8dAQURq8ff3R0xMDKZOnYqYmBiUlpZWu9/27dvRoUMHeHp6IioqClFRUVU+SGfMmIGkpCSsWLECf/75J2xsbDB37lxMnjwZbm5u2LZtGxYtWoSzZ8/C39+/xlHov//+OwIDA/Hcc89h586dMDIywsWLF+Hj44Pz58/ju+++w19//YXhw4dj6tSp+PzzzxWvnT9/PubMmYMXXngBu3fvxubNmzF58mRkZ2fX+F6UlJTgwIEDVSYEunHjBoqKiuDu7l7lNe7u7rh+/TqKi4trPHZN5HI5ysrKkJqaitmzZ+Pq1atVxq8AwKBBg3D79m2cP3++xuPJZDI8ePAA06dPx44dO7Bx40b069cPo0ePxtq1axX7RUVFwcDAACEhIYq/6bJly2qt98cff0R4eDgWLlyI3377DQUFBQgJCVFMwgRUTNM/atQomJqaYuPGjQgLC0NWVhYGDRqkdBvkwYMHMWrUKJiYmGDTpk343//+h99//x2rVq2qct433ngD06ZNw5AhQ7Bjxw4sW7YMFy5cQJ8+fRQLFVL9Na+2RCLSOPPmzcPly5exZMkSLFmyBLq6uvDx8cHIkSPxzjvvKAZKenp6wsDAAKampoo1Xx7VsWNHbNmyRfE8OzsbX375JUJCQpS6EAYNGoTOnTtjzpw5+O2336oc59tvv8Unn3yCb775RqkpNzQ0FCYmJjh27JiipSAoKAgymQzz5s3D1KlTYWFhgePHj6NHjx5Kg+6GDRtW63tx+vRpFBUVoVevXkrbK8ctVDdboaWlJQRBQFZWlsqj6iuFhIRg//79ACpuLdy8ebNigcaHVdZV+fs9jpmZmdIHcnl5OQIDA5GVlYWFCxcqBvT5+flBS0sLbdq0eezftDomJib466+/oK2tDaBiteLevXtj7969eP755yGXy/Hf//4XPXr0wN69exUtXSEhIejYsSM++ugjHD9+HADwySefwNbWFuHh4dDX1wdQ8bd6dIbk6Oho/Pzzz/juu+8QGhqq2N6/f3888cQT+P777+vV7UT/YgsFEanFysoKR48eRWxsLObNm4dRo0bh6tWrmDFjBnr06IHMzMw6H+uZZ55Reh4VFYWioqIq06c7Oztj8ODBOHjwoNJ2QRDwxhtvYPbs2diwYYNSmCguLsbBgwfx9NNPw9DQEGVlZYpHSEgIiouLFc3uvXv3xpkzZ/D2229j//79VaY8fpzKVXdtbGyq/XlNTebqNKcvWbIEJ0+exM6dOzFs2DCMHTsWGzdurLJfZV0pKVVnXXzUli1b0LdvXxgbG0NHRwe6uroICwurU1dTbYYPH64IEwAULTeVd8VcuXIFqampePnll5W6zYyNjfHMM88gOjoahYWFKCgoQGxsLEaPHq0IE0BFYHl0Jeq//voLEokEL730ktLf3s7ODj179kRERITav1drx0BBRA3C29sbH330EbZs2YLU1FS8//77uHXrlkoDMx/9hl75zb66b+4ODg5V7lgoKSnB5s2b4ebmVmV9m/v376OsrEzRivLwIyQkBAAU4WfGjBlYsGABoqOjERwcDCsrKwQGBiIuLq7G+itvzXv4ww2oCF0P/z4Pe/DgASQSiVqLMnXu3Bk+Pj74z3/+o+jqmTJlCuRyudJ+lXXVthLxtm3b8Nxzz8HR0RHr169HVFQUYmNj8corr6jVNVOp8v2o9PBK0UDtf3e5XI6srCxkZWVBLpfDzs6uyn6PbsvIyIAgCLC1ta3y94+OjlYp+FL12OVBRA1OV1cXs2fPxg8//FBrf/3DHv2WXvnBk5aWVmXf1NRUWFtbK22TSqU4fPgwhg0bhiFDhmDfvn2wsLAAAFhYWEBbWxsvv/wypkyZUu35KycB0tHRQWhoKEJDQ5GdnY0DBw5g5syZGDZsGJKTkxUrHD+qsp4HDx4obe/YsSMMDAxw7ty5Kq85d+4cOnXqVCWEqKN3797Yt28f7t27p7QoY2Vdj75vj1q/fj1cXFywefNmpb+JTCZrsBprUtvfXUtLCxYWFhAEARKJBOnp6VX2e3SbtbU1JBKJYo6QR9U2jTXVji0URKSW6i76ABRN4w4ODoptUqm01m/HD/P394eBgYHSnAoAcOfOHRw6dAiBgYFVXuPp6YnIyEjcuXMHgwYNwt27dwEAhoaGCAgIQEJCAtzd3eHt7V3l8eg3ZwAwNzfHmDFjMGXKFDx48AC3bt16bL1du3YFUDEI82E6OjoYOXIktm3bhry8PMX2pKQkHD58WOX7/WsiCAIiIyNhbm5e5fepvJuhW7duNR5DIpFAT09PKUykp6dXucsDUP1vWheurq5wdHTEhg0blO5IKSgowNatWxV3fhgZGaF3797Ytm2bUstJXl4e/vzzT6VjjhgxAoIgICUlpdq/fU1jSqhu2EJBRGoZNmwYnJycMHLkSHTp0gVyuRynT5/Gd999B2NjY7z33nuKfXv06IFNmzZh8+bN6NChA/T19Wu8kJubm+Ozzz7DzJkzMX78eLzwwgu4f/8+Pv/8c+jr62P27NnVvq5r1644evQohgwZggEDBuDAgQNwcnLCokWL0K9fP/Tv3x9vvfUW2rdvj7y8PFy/fh1//vknDh06BAAYOXIkunfvDm9vb7Rp0wa3b9/GwoUL0a5dO3Tu3Pmx9To5OaFDhw6Ijo7G1KlTlX72+eefw8fHByNGjMDHH3+M4uJizJo1C9bW1lXuyBg0aBAiIyNrvb1z1KhR6NmzJzw8PGBlZYXU1FSsXr0akZGR+PHHH6vcOhodHQ1tbe1aF3waMWIEtm3bhrfffhtjxoxBcnIyvvzyS9jb21e5s6ZHjx6IiIjAn3/+CXt7e5iYmCjdMlsfWlpamD9/Pl588UWMGDECb7zxBmQyGf73v/8hOzsb8+bNU+z75Zdf4sknn0RQUBA++OADlJeX49tvv4WRkZFSS1Hfvn3x+uuvY9KkSYiLi8OAAQNgZGSEtLQ0HDt2DD169MBbb71VY1179+5FQUGBIhRevHgRf/zxB4CKAaOPa7lqLRgoiEgtn376KXbu3IkffvgBaWlpkMlksLe3x5AhQzBjxgzFt3ag4kM1LS0Nr732GvLy8tCuXbsav/EDFeMZbGxssHjxYmzevBkGBgYYNGgQvvnmmxo/3Dt06KAIFf3798fBgwfRrVs3xMfH48svv8Snn36Ku3fvwtzcHJ07d1aMowCAgIAAbN26Fb/88gtyc3NhZ2eHoKAgfPbZZ9DV1a2x3hdffBFLly6FTCZTakbv0qULIiIi8NFHH2HMmDHQ0dHB4MGDsWDBArRp00bpGPn5+dWOC3hU37598ccff2Dp0qXIzc2Fubk5vL29FbfDPmrHjh0ICQmpdbzGpEmTcPfuXaxYsQK//vorOnTogI8//hh37txRur0WABYtWoQpU6bg+eefR2FhIQYOHNggAxzHjRsHIyMjzJ07F2PHjoW2tjb8/Pxw+PBh9OnTR7FfUFAQduzYgU8//RRjx46FnZ0d3n77bRQVFVWp9aeffoKfnx9++uknLFu2DHK5HA4ODujbty969+5da01vvfWW0nTqW7ZsUdyVlJiYWOXOktZGItRlWi2iViw3NxdmZmb45T1HGErr30tYKJPj1UUpyMnJUZrc6HHat29fZS0IAHj77berTMREmiM1NRUuLi5Yu3ZtlVks6yIvLw+WlpZYuHDhY8d61MeNGzfQuXNn7N+/H0FBQQ12XKpeQ103ANWvHWLhGAoiDRUbG4u0tDTFIzw8HADw7LPPilwZ1cTBwQHTpk3D119/XeUui7o4cuQIHB0d8dprrzVoXV999RUCAwMZJqjRsMuDSEM92gw+b948dOzYEQMHDhSpIqqrTz/9FIaGhkhJSYGzs7NKrx0+fHi13RXqKCsrQ8eOHTFjxowGPS7RwxgoiJrYo5MkSaXSWm9ZKykpwfr16xEaGsr1BJoBExOTxw4YFYOOjg4+/fRTscugFo5dHkRNzNnZGWZmZorH3Llza33Njh07kJ2dXWXGSCIiTcEWCqImlpycrDSwqi4T6oSFhSE4OFhpTgciIk3CQEHUxExNTVUaqX379m0cOHAA27Zta8SqiIjUwy4PIg23atUq2NjYNPhAPSKihsRAQaTB5HI5Vq1ahQkTJlSZ9ZCISJMwUBBpsAMHDiApKQmvvPKK2KUQEdWIX3mINNjQoUNrXc+BiEgTsIWCiIiI1MZAQURERGpjoCAiIiK1cQwFUR3175UKE8P6T3udV8ixEEStjbrXDaD5XDvYQkEtzuWsdLFLIKJmJq0gB1myQrHLaNYYKKhFWXMpCkE7FuHnC0fFLoWImom8kmKMD1+Fp3Yvx+28+2KX02wxUFCLcTD5Mj6L2QUBAorLysQuh4iagTJ5Od6K2IBLWenILSmCtoQfi/XFd45ahAv3U/F2xAbIBQFjO3vjHfdBYpdERBpOEAR8Fr0LESlXoa+ti1WBE+BkbCF2Wc0WAwU1e6kFORh/YDUKykrQz74T5vV5GhKJeoOgiKjl++n8Uay7EgMJJPhx4PPwaOMsdknNGgMFNWv5pTJMPLAaGYW5eMLcBj8FvAhdLW2xyyIiDbf71jl8FbcHADC793AMa+cmckXNHwMFNVtl8nK8dXgDLj5IQxsDY6wZMhFmUgOxyyIiDRd/LwlTj2wGAEzo4o/J3fqKXFHLwEBBzZIgCJgV8ycOp1xR9H06m1iKXRYRabikvAeYdGANZOVlCHTqgs99R7CLtIEwUFCz9POFY1h7ORoSSLBk4Fj2fRJRrbJlhRgfvgr3iwvQ3dIBywa9AB12kTYYBgpqdvbePo8vYyv6Pj/zCUFwu+4iV0REmq6kvAyvH1qP6zn3YGdoilVDJsBIVyp2WS0KAwU1Kwn3kvFu5GYIEDChix9ec+sndklEpOEEQcBHJ7bhRPpNGOnoYW3QRNgbmYldVovDQEHNRvI/fZ/F5aUY7OSKz31Hsu+TiGq1+MwhbLkeD22JFlYEvIhulg5il9QiMVBQs5AjK8L48NXILM6Hm6U9lg0ax75PIqrV9hun8b+EcADAV37/QYCTq8gVtVwMFKTxSsrL8Prh9biWcxd2hqZYPWQijNn3SUS1iElPxAfHtgAA3ug+AC938RO5opaNgYI0miAImBG1HcfTbrDvk4jq7GbOPUw+tA4l8nKEtOuOT7yfFLukFo+BgjTakrOHsfnaKWhJJFg2aBz7PomoVg+KCzA+fDWyZYXwsHbGogHPQYuLfjU6vsOksXbcPI358X8DAL7yG4VA5y4iV0REmq64rBSvHFyLW3n34WxsgVVDxsNAR0/sslqFFhsoSkpKcPToUfzyyy8QBEHsckhFJzNuIfToP32fbv0xnn2fRFQLuSBH6LEtiLt7G6Z6+lgbNAltDEzELqvVaLGBory8HL///jtiY2Nx48YNscshFdzMycQrB9eiRF6OJ9u64ROfYLFLIqJm4H/x4diVeBY6Ei38HPASOpvbiF1Sq9JiA4WBgQF8fHwAAEePHhW5Gqqrir7PVYq+zyUDx7Lvk4hqtelqLJacPQwA+F/fZ9DXoZPIFbU+LfpK3b9/fwDAqVOnUFBQIHI1VJvislJM/qfv08nYnH2fRFQnR1Ov4eMT2wEA7/UcjGc7e4lcUevUogNF+/bt4eTkhNLSUsTExIhdDtVALsjxwfE/EMu+TyJSwZWsDLx+aD3KBDme6uCB6Z5BYpfUarXoQCGRSBStFEePHuXgTA22ID4cO2+egY5ECysDXsIT5rZil0REGu5uYR7Gh69CXqkMvrbt8V2/MZyOX0QtOlAAgK+vL3R1dZGamoqbN2+KXQ5VY/O1OCz+p+/z276j0Y99n0RUi6KyEkw6uAYpBdlwMbXGL4NfhlRbR+yyWrUWHyg4OFOzHUu9jo+ObwMATHUPwNjO3iJXRESarlwuxzuRm3Am8w4spIZYGzQRFvpGYpfV6rX4QAH8OzgzLi6OgzM1yNXsDLx+uKLvc1SHnvhvr6Fil0REzcBXcXuwP+kipNo6+DVwPFxMrcUuidBKAoWLiwsHZ2qYe0UVfZ+5JcXobdse3/Vl32d1UlJS8NJLL8HKygqGhobw8PDAqVOnxC6LSDSrL0Xh5wvHAADf93sWPrbtxS1Iw8ydOxc+Pj4wMTGBjY0NnnrqKVy5cqXW10VGRsLLywv6+vro0KEDVqxYofK5W0WgkEgk6NevHwAOztQERWUlmHhgDe7kZ6O9iRV+Gfwy9HV0xS5L42RlZaFv377Q1dXF3r17cfHiRXz33XcwNzcXuzQiURxMvoxZMbsAAB/1GoZRHXqKXJHmiYyMxJQpUxAdHY3w8HCUlZVh6NChNbbOJyYmIiQkBP3790dCQgJmzpyJqVOnYuvWrSqdu9WMYPH19cXWrVsVgzM7duwodkmtUrlcjncjNz/U9zkJluz7rNa3334LZ2dnrFq1SrGtffv24hVEJKLz91PwVsQGyAUBz3f2xjvug8QuSSPt27dP6fmqVatgY2ODU6dOYcCAAdW+ZsWKFWjbti0WLlwIAOjatSvi4uKwYMECPPPMM3U+d6tooQAAQ0NDeHtXDPjj4EzxfBO3F/uSLkBPSxthgePRwaz19X3m5uYqPWQyWbX77dq1C97e3nj22WdhY2MDT09P/Pzzz01cLZH4UgtyMOHAGhSWlaCffSfM7fN0q+wireu142E5OTkAAEtLy8fuExUVhaFDlcewDRs2DHFxcSgtLa1zfa0mUADKgzMLCwtFrqb1WXs5Gj9dqAhz3/d/Fr1bad+ns7MzzMzMFI+5c+dWu9/NmzexfPlydO7cGfv378ebb76JqVOnYu3atU1cMZF48ktlmHhgNTIKc/GEuQ1+CngRulraYpclirpeOyoJgoDQ0FD069cP3bt3f+x+6enpsLVVnvvH1tYWZWVlyMzMrHN9rabLAwA6dOgABwcHpKamIiYmBgEBAWKX1GocTL6MT6N3AgA+7DUUT3XwELcgESUnJ8PU1FTxXCqVVrufXC6Ht7c3vvnmGwCAp6cnLly4gOXLl2P8+PFNUiuRmMrk5Xjz8G+4+CANbQyMsTZoEsykBmKXJZq6XjsqvfPOOzh79iyOHTtW67EfbfGpHGuoSktQq2qhkEgkij4kDs5sOhcfpOLtf/o+x3b2wrvurTvImZqaKj0ed1Gwt7dHt27dlLZ17doVSUlJTVEmkagEQcBn0bsQkXIV+tq6WBU4AU7GFmKXJaq6XjsA4N1338WuXbtw+PBhODk51XhcOzs7pKenK227e/cudHR0YGVlVef6WlWgAP6dOTMlJQWJiYlil9PipRbkYHz4ahSUlaCvfUfM9W+dfZ/10bdv3yq3e129ehXt2rUTqSKiprPywlGsuxIDCSRYOvB5eLRxFrukZkEQBLzzzjvYtm0bDh06BBcXl1pf4+/vj/DwcKVtf//9N7y9vaGrW/c78FpdoODgzKaTXyrDpAOrkf5P3+fKgJegx6lx6+z9999HdHQ0vvnmG1y/fh0bNmzAypUrMWXKFLFLI2pUu2+dw1exewEAs3qH4Ml2biJX1HxMmTIF69evx4YNG2BiYoL09HSkp6ejqKhIsc+MGTOUuk3ffPNN3L59G6Ghobh06RJ+/fVXhIWFYfr06Sqdu9UFCuDfwZmxsbFKbzI1nDJ5Od6O2IALD9JgrW+MNUMmtuq+z/rw8fHB9u3bsXHjRnTv3h1ffvklFi5ciBdffFHs0ogaTfy9JEw9shkCBEzo4o9Xu/UTu6RmZfny5cjJycGgQYNgb2+veGzevFmxT1pamlLXqYuLC/bs2YOIiAh4eHjgyy+/xOLFi1W6ZRRoZYMyKz08ODM6OpqDMxuYIAiYHfMnDt25UtH3OWQCnE0ef8sSPd6IESMwYsQIscsgahJJeQ/wyoG1kJWXYbCTKz73HcEuUhXVZWzg6tWrq2wbOHAg4uPj1Tp3q2yh4LLmjeuXi8ew5nI0JJBgycCx8GTfJxHVIltWiAnhq5FZnA83S3ssHzQOOq309tDmqlUGCkB5cOatW7fELqfF2Hv7PL44uQcA8KlPMILbPf7eZyIiACgpL8Mbh3/DtZy7sDM0xeohE2GkW/MtkaR5Wm2gMDIygpeXFwAOzmwoCfeS8W5kRd/n+C5+eN2tv9glEZGGEwQBH5/YjuNpN2Cko4e1QRNhb2QmdllUD602UAAcnNmQkvMeYNKBNSguL0WAoyu+8B3Jvk8iqtXiM4fw+/VT0JZoYXnAi+hm6SB2SVRPrTpQdOzYEfb29igpKcHJkyfFLqfZypEVYcKBir7Pbpb2WB7Avk8iqt32G6fxv4SK+Q++8vsPBju5ilwRqaNVB4qHB2ceOXKEgzProbLv82r2Xdj+0/dpzL5PIqpFTHoiPji2BQDwRvcBeLmLn8gVkbpadaAAAD8/P+jq6uLOnTscnKkiQRAwI2oHjqVdh6GOHtYOmQgH9n0SUS1u5tzD5EPrUCIvR3A7N3zi/aTYJVEDaPWBgoMz62/p2QhsvhYHLYkEyweNg5sV+z6JqGYPigswPnw1smWF8LB2xuIBY6ElafUfRS0C/4rg4Mz62HHzNL6N3w8A+NL3Pwh07iJyRUSk6YrLSjH54FrcyrsPZ2MLrBoyHgY6emKXRQ2kVc6U+ajKwZlpaWk4efIkBg4cKHZJGu1kxi2EHq3o+3zdrR8mdPUXuaKmMbfUEXql9c/gJaVyAHcariCiZkQuyPHBsT8Qe/c2TPX0sSZoItoYmIhdVqNT97oBNJ9rB1soUDE4s1+/ivniOXNmzRJzMzH54FqUyMvxZFs3fOIdInZJRNQM/C8+HDsTz0BHooWfA17CE+a2YpdEDYyB4h/+/v7Q0dFBcnIybt++LXY5Ginrn77PLFkhelo7YcnAsdDW4j8hIqrZpquxWHL2MABgft/R6OvQSeSKqDHw0+AfHJxZM1l5GSYfWofE3Ew4GZtjVeAE9n0SUa2Opl7Dxye2AwDe6zkYz3X2FrkiaiwMFA/h4MzqCYKAD479gZMZtyr6PodMgo1hy+/7JCL1XMnKwOuH1qNMkOOpDh6Y7hkkdknUiBgoHtKpUyfY2dlBJpMhNjZW7HI0xoKEcOy4eRo6Ei2sDHgJrhbs+ySimt0tzMOEA6uQVypDb9v2+K7fGE7H38IxUDzk0WXNCfj9WhwWnTkEAJjX52n0Y98nEdWiqKwEkw6uwZ38bLiYWiNs8MuQavOmwpaOgeIRfn5+0NHRQVJSUqufOfN46nV8eHwbAOBd9wA8/4SPyBURkaYrl8vxTuQmnMm8AwupIdYGTYSFvpHYZVETYKB4hLGxMXr16gWgdbdSXM3OwGuHK/o+R7n0xH97se+TiGr3ddwe7E+6CD0tbfwaOB4uptZil0RNhIGiGg8PziwuLha5mqZ3rygPE8JXI7ekGD427fBdvzGcGpeIarXmUhRWXjgGAPih/3PwsW0vbkHUpPgpUY3OnTvD1tYWMpms1S1rXlRWgkkH1iI5PwvtTawQFjge+jq6YpdFRBruYPJlfBazCwDwUa9hGNWhp8gVUVNjoKhGax2cKRfkmHpkM05nJsNcaoi1QZNgyb5PIqrFhfupeCtiA+SCgLGdvfGO+yCxSyIRMFA8RuXMmUlJSa1m5syv4/Zh7+0L0NPSRtjgl9HBjH2fRFSz1IIcjD+wGoVlJehn3wnz+jzN20NbKQaKxzA2NoanpyeA1tFKse5yNH46fwQA8F2/Z+Fr5yJyRUSk6fJLZZh4YDUyCnPxhLkNfgp4Ebpa2mKXRSJhoKjBgAEDAAAnT55s0YMzD925gk+idwIA/usZhKc7eohbEBFpvDJ5Od46vAEXH6ShjYEx1gyZCDOpgdhlkYgYKGrw8ODMljpz5sUHqXjr8G+QCwKe6+SFqT0Hi10SEWk4QRAwK+ZPHE65An1tXawKnABnE0uxyyKRMVDUoKUPzkwryMH48NUoKCtBX/uO7PskojpZeeEo1l6OhgQSLB34PDzaOItdEmkABopaVA7OvH37NpKSksQup8FU9n2mF+ais5kNVga8BD1OjUtEtdhz6zy+it0LAJjVOwRPtnMTuSLSFAwUtWiJgzPL5OV4O2IDLjxIg7W+MdYEse+TiGqXcC8ZU49shgABE7r44dVu/cQuiTQIA0UdVHZ7xMTENPvBmYIgYHbMXzh05wqk2jr4dch4tGXfJxHVIinvASYdWIPi8lIMdnLF574j2UVKShgo6uCJJ56AjY0NZDIZ4uLixC5HLb9cPIY1l6MggQRLBjyPXm3ail0SEWm4HFkRJoSvRmZxPtws7bF80Djo8PZQegQDRR20lMGZ+25fwBcn9wAAPvUJRkj77iJXRDWZM2cOJBKJ0sPOzk7ssqiVKSkvw+uH1+Nazl3YGZpi9ZCJMNKVil0WaSAGijry9/eHtrY2bt261SwHZ56+l4x3IjdBgICXXX3xult/sUuiOnBzc0NaWprice7cObFLolZEEAR8fGI7jqfdgJGOHtYGTYS9kZnYZZGGYqCoIxMTE8XgzGPHjolcjWqS8x5g0sGKvs8AR1d86fcf9n02Ezo6OrCzs1M82rRpI3ZJ1IosOXsYv18/BS2JBMsDXkQ3SwexSyINxkChguY4ODNHVoQJB1bjXlE+ulrYYXkA+z7Flpubq/SQyWSP3ffatWtwcHCAi4sLnn/+edy8ebMJK6XWbMfN05gf/zcA4Cu/URjs5CpyRaTpGChU4OrqChsbGxQXFzeLwZml8nK8GfEbrmbfha2hKdYETYIx+z5F5+zsDDMzM8Vj7ty51e7n6+uLtWvXYv/+/fj555+Rnp6OPn364P79+01cMbU2MemJCD26BQDwhlt/jO/iJ3JF1BxwJiMVSCQS9OvXD9u2bcPRo0fRr5/m3oNd2fd5NPU6DHX0sGbIBDiw71MjJCcnw9TUVPFcKq0+5AUHByv+u0ePHvD390fHjh2xZs0ahIaGNnqd1DrdzMnE5EPrUCIvR3A7N3ziE1z7i4jAFgqVPTw4Mzk5WexyHuvHcxHYfC2uou9z0Dh0t3IUuyT6h6mpqdLjcYHiUUZGRujRoweuXbvWyBVSa/WguADjw1chW1YID2tnLB4wFloSfkxQ3fBfiopMTU3h4eEBQHNvId158wzmndoPAPjC9z8IdO4ickXUEGQyGS5dugR7e3uxS6EWqLisFJMPrsWtvPtwNrbAqiHjYaCjJ3ZZ1IwwUNTDw4MzaxpQJ4bYjFsIPVbR9/maWz9M7OovckVUX9OnT0dkZCQSExMRExODMWPGIDc3FxMmTBC7NGph5IIcHxz7A7F3b8NUTx9rgiaijYGJ2GVRM8NAUQ+aOjgzMTcTrxxcC1l5GYa17YZPvUPELonUcOfOHbzwwgtwdXXF6NGjoaenh+joaLRr107s0qiFWRAfjp2JZ6Aj0cLKgJfwhLmt2CVRM8RBmfWgpaWlNDizb9++YpeErOICjA9fjSxZIXpaO2HJgOehrcW82Jxt2rRJ7BKoFdh0NRaLzx4GAMzvOxr9HDqJXBE1V/zEqafKwZmJiYmiD86UlZfh1UPrkJibCSdjc6wKnABDXfZ9ElHNjqVex8cntgMA3us5GM919ha5ImrOGCjq6eHBmWLOnCkIAj449gdiMm7BRFeKNUMmwcaQfZ9EVLOr2Rl4/fB6lAlyjOrQE9M9g8QuiZo5Bgo1VA7OjI6ORklJiSg1LEgIx46bpyv6Pge/BFcL9n0SUc3uFuZhfPgq5JYUo7dte3zf71lOx09qY6BQg6urK6ytrVFcXIzY2NgmP//v1+Kw6MwhAMC8Pk+jv0PnJq+BiJqXorISTDq4Bnfys+Fiao2wwS9Dqs3hdKQ+Bgo1aGlpibas+fHU6/jw+DYAwLvuAXj+CZ8mPT8RNT/lcjnejdyMM5l3YCE1xJohE2GhbyR2WdRCMFCoqU+fPtDS0kJiYiLu3LnTJOe8ln0Xr/3T9/kfF3f8txf7Pomodl/H7cG+pAvQ09JGWOB4dDCzFrskakEYKNTU1DNn3iv6t+/Tx6Ydvu/3LKfGJaJarbkUhZUXKgaQf9//WfS2bS9uQdTi8JOoATw8c2ZjDs4sKivFKwfXIjk/C+1MrBAWOB76OrqNdj4iahkOJl/GZzG7AAAf9hqKpzp4iFsQtUgMFA2gS5cusLa2RlFRUaPNnCkX5HjvyGYk3EuGudQQ64ImwpJ9n0RUiwv3U/F2xAbIBQFjO3vjXfcAsUuiFoqBogE0xeDMb+L2Yc/t8xV9n4NfRgezNo1yHiJqOVILcjD+wGoUlJWgn30nzOvzNG8PpUbDQNFA/P39oaWlhZs3byIlJaVBj73+cgxWnD8CAPiu37PwtXNp0OMTUcuTXyrDxAOrkVGYiyfMbfBTwIvQ1dIWuyxqAkeOHMHIkSPh4OAAiUSCHTt21Lh/REQEJBJJlcfly5dVOi8DRQMxMzNrlMGZh+9cwSfROwEA0z2D8HRHjwY7NhG1TGXycrx1eAMuPkhDGwNjrBkyEWZSA7HLoiZSUFCAnj17YunSpSq97sqVK0hLS1M8OndWbW4jzmbSgPr374/4+HjExMQoVodUx8UHqXjz8G8oF+R4tlMvvNdzcANVSkQtlSAImBXzJw6nXIG+ti5+DZwAZxNLscuiJhQcHIzg4GCVX2djYwNzc/N6n5ctFA2oS5cusLKyQmFhIU6dOqXWsdILczEhfA0KykrQx64Dvu0zmn2fRFSrny8cw9rL0ZBAgiUDx8KzjbPYJVEDyc3NVXrIZLIGPb6npyfs7e0RGBiIw4cPq/x6tlA0oMplzXfu3ImjR4/C39+/XscpKJVhYvhqpBXmoJNZG6wc/BL0ODWu6GbOfx0m2vr1fn1eeTFWY1YDVkSkbO/t8/gydg8A4DOfEAS36y5yRaTudQP499rh7KwcDmfPno05c+aodWwAsLe3x8qVK+Hl5QWZTIZ169YhMDAQERERGDBgQJ2Pw0+pBta3b1/8+eefuHHjBlJSUuDo6KjS68vlcrwdsRHnH6TCSt8Ia4MmwVxq2EjVElFLkXAvGe9GboYAARO6+OE1t35il0QNLDk5GaampornUqm0QY7r6uoKV1dXxXN/f38kJydjwYIFKgUKdnk0MDMzM/Ts2ROA6suaC4KA2Sf/xME7lyHV1sGqIRPQln2fRFSL5LwHmHRgDYrLSzHYyRWf+45kF2kLZGpqqvRoqEBRHT8/P1y7dk2l1zBQNIL6LmsedvE4Vl+KggQSLB4wFr3atG2sEomohciRFWF8+GpkFufDzdIeywaNgw5vDyU1JSQkwN7eXqXXsMujEXTt2hVWVla4f/8+4uPj4efnV+tr9t++gM9P7gYAfOIdjOHtezR2mUTUzJWUl+H1w+txLecu7AxNsXrIRBjrNt63Vmoe8vPzcf36dcXzxMREnD59GpaWlmjbti1mzJiBlJQUrF27FgCwcOFCtG/fHm5ubigpKcH69euxdetWbN26VaXzsoWiEVQOzgQqJhipzZnMO3jnyCYIEPCSqy/e6N6/sUskomZOEATMiNqO42k3YKSjhzVDJsLeyEzsskgDxMXFwdPTE56engCA0NBQeHp6YtasikHhaWlpSEpKUuxfUlKC6dOnw93dHf3798exY8ewe/dujB49WqXzsoWikfTp00cxODM1NRUODg7V7ncnPwsTD6xGUVkpBjk+ga/8/sO+TyKq1ZKzh7H52iloSSRYNmgc3Kyqv8ZQ6zNo0CAIgvDYn69evVrp+YcffogPP/xQ7fOyhaKRmJubw93dHcDjZ87MLSnGhPDVuFeUj64WdljOvk8iqoMdN09jfvzfAICv/EYh0LmLyBURMVA0qpoGZ5bKy/HG4fW4kp0BW0NTrBkyESZ66t2rTEQt38mMWwg9ugUA8LpbP4zvUvsYLaKmwEDRiLp166aYOTM+Pl6xXRAEzDixHUdTr8NQRw9rhkyAg7G5eIUSUbNwMycTrxxcixJ5OZ5s64ZPfULELolIgYGiEWlpaaFv374AlLs9fjwXiU3X4v7p+3wB3a1Um/yKiFqfrOICjA9fhWxZIXpaO2HJwLHQkvASTpqD/xobWd++faGlpYXr168jNTUVu26ewbxT+wAAn/ceiSHOXUWukIg0XXFZKSYfWodbeffhZGyO1UMmwEBHvcUHiRoaA0Uje3hw5ta/9+D9YxV9n69264tJ3fqIWRoRNQNyQY4Pjv+Bkxm3YKqnj7VBk9DGwETssoiqYKBoApWDM8+cjIVxfhaGte2Gz3yGi1wVEWm6srIyzDuyEztvnoGORAsrA17CE+a2YpdFVC3OQ9GI8vNlOJOQilOxD6AlMYG+NBs/x22EdXIEMlNOwrBrAAy7DoK2sZXYpRKRhhAEATdv3kRMTAxOxp5Esb4OdFz18G3f0ejn0Ens8ogei4GigZWWlOPChQwkxN3Blcv3IJdXTC5iqD8Apx1uIavkL5inXUZO2mXkHFoOSCSQOveEQddBMOwaAAPXAdA2MK3lLETU0mRkZCAmJgYxMTHIzMxUbC8ulcDbvAfGdvYWsTqi2jFQNAC5XMDNG/cRH5eCc2fSIJOVKX7m5GwGyycMMCd1J4xM9BD41kUUXzmCwkuHUXjpMEpSLkCWdBqypNPI3r8Q0NKGfnsvWI+dD0NXTsFN/5o7dy5mzpyJ9957DwsXLhS7HGoAeXl5iIuLQ0xMDBITExXbpVIpPD09cUwvFwdlqZjZsbuIVRLVDQOFGtJSc5FwKgUJp1KQk1Os2G5hYQBPb0d4ejnC1tYE3yccQPG9Ugy17wodY0sYez0FY6+nAABlORkovHQYRZcjUHjpMEozrqP45klo6RuL9FuRJoqNjcXKlSsVA3yp+SopKcGZM2cQExODCxcuQC6XAwAkEgm6desGPz8/9OzZE9q6Opi/4QtAIkFf+44iV01UOwYKFeVkF+F0Qiri41KQlpqr2G5goAt3D3v08nJEOxdLaGn9ux7HifQbAIA+dlUvCjpmtjD1ex6mfs8DAErvJ6HocgSkzj0b+Teh5iI/Px8vvvgifv75Z3z11Vdil0P1IJfLcfXqVcTExCA+Ph7Fxf9+AWnbti38/Pzg7e0NM7N/F/c6fS8ZeaUymOrpo7sl1+kgzcdAUQfFxWU4fzYNCadScP1aJirXXNHWlqBrN1t4ejuiS1cb6OpWXYejqKwE8XcrVnXrU4dvGbpWbaHbd3yD1k+aJTc3V+m5VCqFVPr4JaenTJmC4cOHY8iQIQwUzUxKSgqio6MRGxuLrKwsxXYrKyv07t0bvr6+sLe3r/a1J9JvAgD8bF2grcUb8kjzMVA8Rnm5HFev3EPCqRRcOJeO0lK54mftXSzQy9sJ7j3tYWhU8+QycXdvo0ReDntDM7iY8m4OApydnZWez549G3PmzKl2302bNiE+Ph6xsbFNUBk1hOzsbJw8eRIxMTG4c+eOYruBgQG8vLzg5+eHjh07QquWkHA87Z+WTXZ3UDPBQPEQQRBwJzkH8XF3cCYhFfn5/y7oZd3GCF7eTvDo5QAra6M6H/NEWsW3jD72HbgsOQEAkpOTYWr67508j2udSE5OxnvvvYe///4b+vpcOE6TFRcXIyEhATExMbh8+bJi6WhtbW306NEDvr6+6NGjB3R1det0vJLyMsRm3ALAQEHNBwMFgAf3C5FwKgXxp+7g3t0CxXYjYz14eDqgl7cTnJzN6hUIKr9lcFAVVTI1NVUKFI9z6tQp3L17F15eXopt5eXlOHLkCJYuXQqZTAZtbS53L5by8nJcunQJ0dHROH36NEpLSxU/69ixI3x9feHt7Q0jo7p/Aal0JvMOCstKYCk1QhcLTmRFzUOrDRSFhSU4ezoN8XEpuJX4QLFdR1cLbt3t0MvbEU+4toG2dv37LvNLZTiTWdHkyW8ZpKrAwECcO3dOadukSZPQpUsXfPTRRwwTIhAEAbdv30ZMTAxiY2ORl5en+JmtrS18fX3Ru3dvtGnTRq3zVH4R8bfvwAXAqNloVYGirKwcly7eRUJcCi5dvIvy8srbtYCOnazRy9sR3d3toK9ft2bJ2sSkJ6JckKOdiSWcjC0a5JjUepiYmKB7d+X5B4yMjGBlZVVlOzWuzMxMnDx5EtHR0cjIyFBsNzExgbe3N3x9fdG+ffsG69Y8wZZNaoZafKCQywXcvpWF+Lg7OHs6DUVF/zZL2juYwNPLCZ69HGBmbtDg5z7BQVVEzVZBQQFOnTqFmJgYXL9+XbFdV1cXHh4e8PX1Rbdu3Rq8pai4rBSn7lXcGcZAQc1Jiw0UdzPyEX/qDhJOpSDrQZFiu6mZFJ69HNHL2wn2Do07xXXlbV/VzT9BVB8RERFil9CilZaW4vz584iJicG5c+dQVlYx661EIoGrqyt8fX3h6ekJA4OG/wJS6dS9JMjKy2BrYIIOptaNdh6ihtaiAkV+nuyfSafu4E5yjmK7nlQb7j3t4enlhI6drJQmnWosWbJCnL+fCqDiDg8i0kyCIODGjRuIiYlBXFwcCgsLFT9zdHRUjIuwsGiabsuHWzZ5Zxg1J80+UJSUlOPC+XTEx93BtSuZisW4tLQkeKJLG/TyckS37nbQ02vaAWzR6TchQEAnszawNeRiX0SaJj09XbEY1/379xXbzc3NFZNOOTk5NXldnH+CmqtmGSjkcgE3rmVWLMZ1Lg0lsnLFz5zbmqOXlyN6ejrA2OTxsw82tsr5J9gHSqQ5cnNzERcXh+joaNy+fVuxXSqVolevXvD19YWrq2utk041loJSGU7fSwbAawc1P80qUKSm5CL+1B2cjk9Bbo5Msd3S0lCxGJeNjWYsqsUBmUSaoaSkBKdPn0ZMTAwuXryoWIxLS0tLaTEuPb2aZ71tCiczbqFMkMPZ2AJtTSzFLodIJRofKLKzi3D6VAriT6UgPe3fe74NDHXR08Phn8W4LDSqr/FeUR6uZFfcWuZvx/ETRE1NLpfjypUrisW4ZLJ/v4C0b99eMelUXSYYa0r/dnfwukHNj0YGiuLiUpw7UzEu4uaN+w8txqWFbm428PR2QpeubaCjo5kT+0T9093RzdIelvqqz5JHRPWTnJysmHQqOztbsd3a2loxuNLOzk68AmsRVXlnmH0nkSshUp3GBIrycjmuXP5nMa7z6Sh7aDEul46W6OXliB497WFoKH6zZG043TZR08nKylIsxpWSkqLYbmhoqJh0qmNHzb9jIkdWhHP3K+rvw5ZNaoZEDRSCICA5KRvxcSk4k5CKgoJ/F+OysTFGL29HeHg5wtLSUMQqVffv/BO8KBA1hqKiIsTHxyMmJgZXr15VLMalo6ODHj16wM/PD25ubnVejEsTxGQkQi4I6GBqDXsjM7HLIVKZKIHifmYB4k+lIOFUCjLv/bsYl7GxHjx6OaKXtyMcneq3GJfYUgtykJibCS2JBL4MFEQNpry8HBcvXkR0dDTOnDmjtBhXp06d4OvrCy8vr3otxqUJ2LJJzV2TBYqCghKcPZ2K+LgU3L6Vpdiuq6eN7j3s0MvLEZ2esFZrMS5NUHl3Rw8rR5jqcclpInUIgoBbt24hOjoacXFxyM/PV/zM1tYWfn5+6N27N6ytm/+Mkpx/gpq7Rg0UpaXluHQhAwmnUnD50l2Ul1c0S0okQKfO1ujl7QS3HnbQ19eYoRxq46I+ROq7d++eYtKpu3fvKrabmJjAx8cHfn5+aNu2bbNsxazO/eJ8XM5KB8A7w6j5avBPcrlcQOLNB0g4VbEYV3FxmeJnDo6m6OXthJ6eDjAza3nf3gVBYLMlUT3l5+crFuO6ceOGYruuri48PT3h6+uLrl27tshl2yvvDOtiYQdrA82YS4dIVQ0WKDLS8xTjIrKz/l2My9xcH55eFZNO2dlr1j3fDS0p/wFSCrKhq6UNH5v2YpdDpPFKS0tx7tw5REdH4/z58ygvr5j1ViKRoEuXLorFuPT1W94XkIdxIDe1BA0SKEpKyrH4h2MoLam4GOjr66BHT3v08naES4emWYxLE1S2Tni2cYahrubf3koktoiICPzxxx+K587OzvD19YWPjw/Mzc3FK6yJsWWTWoIGCRR6ehWreRYWlsLL2xFdu9lCt4kX49IElet3sA+UqG68vb1x6NAh+Pj4wNfXF46OjmKX1OTSC3NxI+ceJJDA185F7HKI6q3Bujyee6FnixkgVR+CIHBAJpGKLCws8M0337Tqa8e/d4Y5wFzavObcIXpYg92j2ZovCABwPece7hblQaqtg15t2opdDlGz0dqvHbxdlFqK5j3pgwap/JbhbdMO+jrNZ3Y+IhIXVyamloKBooFwUBURqSop7wGS87OgI9FCb9v2YpdDpJaWM6OUiOSC/N9VAu0YKFqqpYGukKrRxy2TFQJXG7AgavYqWyd6WjvBWFcqcjXUGNS9bgDN59rBFooGcDkrHVmyQhjq6KFnGyexyyGiZqJy/gm2bFJLwEDRACq7O3xtXaCr1fpulyUi1XFmXWppGCgaQOX8E33sOf8EEdXNzdxMZBTmQk9LG71s2oldDpHaGCjUVCYvRzSbLYlIRZXjJ7xs2sGAd4ZRC8BAoabz91ORVyqDmZ4+3CwdxC6HiJoJdndQS8NAoabKi4KfXQdoa/HtJKLayQX5Q12lDBTUMvATUE2clIaIVHUl6y4eyApgoKMLD2veGUYtAwOFGkrKy3Dy7i0AnH+CiOrueNp1AEBvm/bQ0+Z0QNQyMFCo4XTmHRSVlcJK3wiuFjZil0NEzYRiIjy2bFILwkChBkV3h11HaEn4VhJR7crl/86sywGZ1JLwU1AN/64SyPknqOEtX74c7u7uMDU1hampKfz9/bF3716xyyI1nX+QitySYpjoStHdineGUcM7cuQIRo4cCQcHB0gkEuzYsaPW10RGRsLLywv6+vro0KEDVqxYofJ5GSjqqaisFKfu3gbAbxnUOJycnDBv3jzExcUhLi4OgwcPxqhRo3DhwgWxSyM1nHjozjAdzqxLjaCgoAA9e/bE0qVL67R/YmIiQkJC0L9/fyQkJGDmzJmYOnUqtm7dqtJ5ORqonuLv3kaJvBy2hqZwMbUWuxxqgUaOHKn0/Ouvv8by5csRHR0NNzc3kaoidbFlkxpbcHAwgoOD67z/ihUr0LZtWyxcuBAA0LVrV8TFxWHBggV45pln6nwcBop6enhSGolEInI11Jzk5uYqPZdKpZBKa15psry8HFu2bEFBQQH8/f0bszxqRKXycpzMuAWALZukuvpcO+oiKioKQ4cOVdo2bNgwhIWFobS0FLq6dZvJlV0e9cRVAqm+nJ2dYWZmpnjMnTv3sfueO3cOxsbGkEqlePPNN7F9+3Z069atCaulhnTm3h0UlpXAQmqILhZ2YpdDzYwq1w5VpKenw9bWVmmbra0tysrKkJmZWefjsIWiHvJLZTh9LxkA0MeOzZakmuTkZJiamiqe1/QNw9XVFadPn0Z2dja2bt2KCRMmIDIykqGimaqcf8LfrgPvDCOVqXLtUNWjLe2CIFS7vSYMFPVwMuMWygQ52hpbwtnEUuxyqJmpvGujLvT09NCpUycAgLe3N2JjY7Fo0SL89NNPjVkiNRK2bJI6VLl2qMLOzg7p6elK2+7evQsdHR1YWVnV+TiMyPVwgoOqSCSCIEAmk4ldBtVDcVkp4nhnGGkgf39/hIeHK237+++/4e3tXefxEwBbKOqF63dQU5g5cyaCg4Ph7OyMvLw8bNq0CREREdi3b5/YpVE9nLqXBFl5GWwMTNDRrI3Y5VALlp+fj+vXryueJyYm4vTp07C0tETbtm0xY8YMpKSkYO3atQCAN998E0uXLkVoaChee+01REVFISwsDBs3blTpvAwUKsqWFeL8g1QADBTUuDIyMvDyyy8jLS0NZmZmcHd3x759+xAUFCR2aVQPD38R4Z1h1Jji4uIQEBCgeB4aGgoAmDBhAlavXo20tDQkJSUpfu7i4oI9e/bg/fffx48//ggHBwcsXrxYpVtGAQYKlcWkJ0IuCOho1gZ2hg3fl0VUKSwsTOwSqAGxq5SayqBBgxSDKquzevXqKtsGDhyI+Ph4tc7LMRQqenj+CSKiuigsLUHCP3eG8dpBLRUDhYpOcJVAIlLRybsVd4Y5GZujrTHvDKOWiYFCBfeL83E5q+LWGs4/QUR1dTz135WJOX6CWioGChVEpVW0TnS1sIOlvpHI1RBRc3EinXeGUcvHQKGC47xdlIhUlFtSjHP3UwDw2kEtGwOFCjggk4hUFZN+E3JBgIupNRyMzMQuh6jRMFDUUVpBDm7mZkJLIoGvrYvY5RBRM8EvItRaMFDUUeXdHT2sHGEmNRC5GiJqLhRdpRzITS0cA0UdnfhnlcA+dvyWQUR186C4AJf+uTPMnxNaUQvHQFFHJ/65w6OvAwMFEdVNZcumq7kt2hiYiFwNUeNioKiDpLwHSM7Pgo5ECz427cQuh4iaCS4kSK0JA0UdVF4UPNs4w0hXKnI1RNRcnOCATGpFGCjqgPNPEJGq0gtzcT3nHiSQwM+Od4ZRy8dAUQtBENhsSUQqq5xZt7uVA8ylhiJXQ9T4GChqcTM3ExlFeZBq68CrTVuxyyGiZuJ45Z1h/CJCrQQDRS0quzu82rSFvo6uyNUQUXNReWcY55+g1oKBohYcVEVEqkrOe4Ck/AfQlmjBl+MnqJVgoKiBXJD/+y2DgYKI6qhy/ome1k4w5p1h1EowUNTgclYGHsgKYKijh57WTmKXQ0TNBFs2qTVioKhB5UWht2176GnriFwNETUHgiBwQTBqlRgoasDbRYlIVYm5mUgvzIWelja8OLMutSIMFI8hCALi7yUD4LcMIqq7+HtJAIBeNm1hwDvDqBVhO/5jSCQSRD37IeLu3kZ3SwexyyGiZmJMJy/0tnVBbkmR2KUQNSkGihoY6Oihv0NnscsgomamrYml2CUQNTkGCqI6mpD9PIz1JPV+fX6JgMUNWA8RaT51rxtA87l2cAwFERERqY2BgoiIiNTGQEFERERqY6AgIiIitTFQEBERkdoYKIg01Ny5c+Hj4wMTExPY2NjgqaeewpUrV8Qui4ioWgwURBoqMjISU6ZMQXR0NMLDw1FWVoahQ4eioKBA7NKIiKrgPBREGmrfvn1Kz1etWgUbGxucOnUKAwYMEKkqIqLqMVAQNbHc3Fyl51KpFFKptNbX5eTkAAAsLTkLIxFpHnZ5EDUxZ2dnmJmZKR5z586t9TWCICA0NBT9+vVD9+7dm6BKIiLVsIWCqIklJyfD1NRU8bwurRPvvPMOzp49i2PHjjVmaURE9cZAQdTETE1NlQJFbd59913s2rULR44cgZOTUyNWRkRUfwwURBpKEAS8++672L59OyIiIuDi4iJ2SUREj8VAQaShpkyZgg0bNmDnzp0wMTFBeno6AMDMzAwGBgYiV0dEpIyDMok01PLly5GTk4NBgwbB3t5e8di8ebPYpRERVcEWCiINJQiC2CUQEdUZWyiIiIhIbQwUREREpDYGCiIiIlIbAwURERGpjYGCiIiI1MZAQURERGpjoCAiIiK1MVAQERGR2hgoiIiISG0MFERERKQ2BgoiIqIWZtmyZXBxcYG+vj68vLxw9OjRx+4bEREBiURS5XH58mWVzslAQURE1IJs3rwZ06ZNwyeffIKEhAT0798fwcHBSEpKqvF1V65cQVpamuLRuXNnlc7LQEFERNSCfP/995g8eTJeffVVdO3aFQsXLoSzszOWL19e4+tsbGxgZ2eneGhra6t0XgYKIiKiZiA3N1fpIZPJquxTUlKCU6dOYejQoUrbhw4dihMnTtR4fE9PT9jb2yMwMBCHDx9WuT4GCiIiombA2dkZZmZmisfcuXOr7JOZmYny8nLY2toqbbe1tUV6enq1x7W3t8fKlSuxdetWbNu2Da6urggMDMSRI0dUqk9Hpb2JiIhIFMnJyTA1NVU8l0qlj91XIpEoPRcEocq2Sq6urnB1dVU89/f3R3JyMhYsWIABAwbUuT62UBARETUDpqamSo/qAoW1tTW0tbWrtEbcvXu3SqtFTfz8/HDt2jWV6mOgICIiaiH09PTg5eWF8PBwpe3h4eHo06dPnY+TkJAAe3t7lc7NLg8iIqIWJDQ0FC+//DK8vb3h7++PlStXIikpCW+++SYAYMaMGUhJScHatWsBAAsXLkT79u3h5uaGkpISrF+/Hlu3bsXWrVtVOi8DBRERUQsyduxY3L9/H1988QXS0tLQvXt37NmzB+3atQMApKWlKc1JUVJSgunTpyMlJQUGBgZwc3PD7t27ERISotJ5JYIgCA36mxC1MLm5uTAzM8OpFyQw1qt+UFNd5JcI8NooICcnR2lgFRG1PA113QCaz7WDYyiIiIhIbQwUREREpDYGCiIiIlIbAwURERGpjYGCiIiI1MZAQURERGpjoCAiIiK1MVAQERGR2jhTJlEdjej3HrQMHr+6X23kRTJg48KGK4iINJ661w2g+Vw72EJBREREamOgINJQR44cwciRI+Hg4ACJRIIdO3aIXRIR0WMxUBBpqIKCAvTs2RNLly4VuxQiolpxDAVRE8vNzVV6LpVKIZVW7WMNDg5GcHBwU5VFRKQWtlAQNTFnZ2eYmZkpHnPnzhW7JCIitbGFgqiJJScnKy1BXF3rBBFRc8NAQdTETE1NlQIFEVFLwC4PIiIiUhsDBREREamNXR5EGio/Px/Xr19XPE9MTMTp06dhaWmJtm3bilgZEVFVDBREGiouLg4BAQGK56GhoQCACRMmYPXq1SJVRURUPQYKIg01aNAgCIIgdhlERHXCMRRERESkNgYKIiIiUhsDBREREamNgYKIiIjUxkBBREREamOgICIiIrUxUBAREZHaGCiIiIhIbQwUREREpDYGCiIiIlIbAwURERGpjYGCiIiI1MZAQURERGpjoCAiIiK1MVAQERGR2hgoiIiISG0MFERERKQ2BgoiIiJSGwMFERERqY2BgoiIiNTGQEFERERqY6AgIiIitTFQEBERkdoYKIiIiEhtDBRERESkNgYKIiIiUhsDBREREamNgYKIiIjUxkBBREREamOgICIiIrUxUBBpuGXLlsHFxQX6+vrw8vLC0aNHxS6JiDScqteNyMhIeHl5QV9fHx06dMCKFStUPicDBZEG27x5M6ZNm4ZPPvkECQkJ6N+/P4KDg5GUlCR2aUSkoVS9biQmJiIkJAT9+/dHQkICZs6cialTp2Lr1q0qnZeBgkiDff/995g8eTJeffVVdO3aFQsXLoSzszOWL18udmlEpKFUvW6sWLECbdu2xcKFC9G1a1e8+uqreOWVV7BgwQKVzqvTEMUTtQZCkQxyNV8PALm5uUrbpVIppFJplf1LSkpw6tQpfPzxx0rbhw4dihMnTqhRCRE1FXWvG5XHAOp27ajPdSMqKgpDhw5V2jZs2DCEhYWhtLQUurq6daqTgYKoFnp6erCzs0P6dPVbBYyNjeHs7Ky0bfbs2ZgzZ06VfTMzM1FeXg5bW1ul7ba2tkhPT1e7FiJqPA153QDqfu2oz3UjPT292v3LysqQmZkJe3v7OtXIQEFUC319fSQmJqKkpETtYwmCAIlEorStutaJhz26f3XHICLN0pDXDUD1a4eq143q9q9ue00YKIjqQF9fH/r6+k16Tmtra2hra1f5VnH37t0q3yaISPM0l+uGnZ1dtfvr6OjAysqqzufmoEwiDaWnpwcvLy+Eh4crbQ8PD0efPn1EqoqINFl9rhv+/v5V9v/777/h7e1d5/ETAAMFkUYLDQ3FL7/8gl9//RWXLl3C+++/j6SkJLz55ptil0ZEGqq268aMGTMwfvx4xf5vvvkmbt++jdDQUFy6dAm//vorwsLCMH36dJXOyy4PIg02duxY3L9/H1988QXS0tLQvXt37NmzB+3atRO7NCLSULVdN9LS0pTmpHBxccGePXvw/vvv48cff4SDgwMWL16MZ555RqXzSoTKkRdERERE9cQuDyIiIlIbAwURERGpjYGCiIiI1MZAQURERGpjoCAiIiK1MVAQERGR2hgoiIiISG0MFERERKQ2BgoiIiJSGwMFERERqY2BgoiIiNT2f5Q5gETDCRd2AAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -1343,14 +1375,14 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([2, 1])\n", - "angles: [29.396028363390087]\n", + "angles: [np.float64(29.396028363390087)]\n", "(0, 3) added\n", "Checking edge: (9, 2)\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1365,14 +1397,14 @@ "angles_gdf len 2\n", "connectivity: 1\n", "Counter values: dict_values([1, 1])\n", - "angles: [53.8322224050728]\n", + "angles: [np.float64(53.8322224050728)]\n", "(9, 2) added\n", "Checking edge: (9, 3)\n" ] }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgcAAAGTCAYAAAC8vrHzAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABRKklEQVR4nO3dd1xV9f8H8NdlXea9LNmoSCrIVhyAG7FcmeYoK0fLykozG9rQykT9VV9N09LMkTkyZ87cGwUF9wRFppM9LuOe3x/ElROojAvnAq/n43Efj+7x3HPfQBxe93Pe5/ORCYIggIiIiOhfelIXQERERLqF4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiHRYVlYWJkyYgGbNmsHExATBwcGIjIyUuiwi0mHaOG8wHBDpsNdffx27d+/G77//jnPnzqF3797o1asXkpKSpC6NiHSUNs4bMi68RKSb8vLyYGFhgc2bN6Nfv36a7f7+/ujfvz+mT58uYXVEpIu0dd4wqK0CiRqS/Px8FBQU1Pg4giBAJpOJtsnlcsjl8nL7FhUVobi4GMbGxqLtJiYmOHLkSI1rIaLapa3zBlD5c4e2zhscOSB6gvz8fFhbWyMvL6/GxzI3N0d2drZo29SpUzFt2rQK9w8ODoaRkRFWrVoFe3t7rF69GiNHjkTLli1x5cqVGtdDRLVDm+cNoGrnDm2cNxgOiJ4gMzMTSqUSI0aMgJGRUbWPU1BQgFWrViEhIQEKhUKz/VEjBwAQGxuLV199FYcOHYK+vj7atm2LVq1a4fTp07h48WK1ayGi2qWt8wZQ9XOHNs4bvKxAVElGRkY1/iUHAIVCIfoFfxx3d3ccPHgQOTk5yMzMhKOjI4YPHw43N7ca10FEtU9b5w2g8ucObZw3eLcCUT1gZmYGR0dHpKWlYdeuXRg4cKDUJRGRjqvJeYMjB0Q6bNeuXRAEAa1bt8b169fx0UcfoXXr1hgzZozUpRGRjtLGeYMjB0Q6LCMjA+PGjYOHhwdGjhyJzp07459//oGhoaHUpRGRjtLGeYMjB0Q6bNiwYRg2bJjUZRBRPaKN8wZHDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoh0VFFRET7//HO4ubnBxMQELVq0wNdffw21Wi11aUTUwBlIXQARVWzWrFn4+eefsXz5cnh5eSEqKgpjxoyBUqnE+PHjpS6PiBowhgMiHXX8+HEMHDgQ/fr1AwA0b94cq1evRlRUlMSVEVFDx8sKRHUsMzNT9FCpVBXu17lzZ+zduxdXr14FAJw5cwZHjhxB375967JcImqEOHJAVMdcXV1Fz6dOnYpp06aV2++TTz5BRkYGPDw8oK+vj+LiYnz77bd48cUX66hSImqsGA6I6lhCQgIUCoXmuVwur3C/tWvXYuXKlVi1ahW8vLwQExODCRMmwMnJCaNGjaqrcomoEWI4IKpjCoVCFA4e5aOPPsKnn36KF154AQDg4+OD+Ph4hIeHMxwQUa1izwGRjsrNzYWenvhXVF9fn7cyElGt48gBkY4aMGAAvv32WzRt2hReXl6Ijo7GDz/8gFdffVXq0oiogWM4IKqkzsrdMJVXf7AtV6XGsirsP2/ePHzxxRd45513cOfOHTg5OWHs2LH48ssvq10DEdWtmp43gKqfO7SB4YBIR1lYWGDOnDmYM2eO1KUQUSPDngMiIiISYTggIiIiEa2Ggx9//BEymQze3t6P3Ecmk4kmfDlw4ABkMhkOHDhQ4/ffvn17hZPJaMOyZcsgk8nqzdS1q1at0snhaG3+vEvNmTMHgwcPhpubG2QyGbp37661YxMRNUZaDQe//fYbAODChQs4ceKENg9dKdu3b8dXX31V5++ri3Q1HNSGn3/+GfHx8ejZsyeaNGkidTlERPWe1sJBVFQUzpw5o1kkZsmSJdo6dK0QBAF5eXlSl0FacPHiRZw6dQpLliyBnZ2d1OUQEdV7WgsHpWFg5syZCA4Oxpo1a5Cbm6utwyM3NxeTJk2Cm5sbjI2NYW1tjcDAQKxevRoAMHr0aPz0008ASi5dlD5u3ryp2fbuu+/i559/hqenJ+RyOZYvXw4AOHLkCEJDQ2FhYQFTU1MEBwdj27ZtT6wpJSUF7dq1Q8uWLXHt2jUAJYvqlNZpZGQEZ2dnTJgwATk5OaLXrlu3Dh07doRSqYSpqSlatGhRqfvXf/rpJ3Tt2hV2dnYwMzODj48PZs+ejcLCQs0+3bt3x7Zt2xAfHy/6XjxO8+bN0b9/f+zcuRNt27aFiYkJPDw8NKNBZZ0/fx4DBw6ElZUVjI2N4e/vr/lelnX58mU888wzMDU1ha2tLd566y1kZWVV+P579uxBaGgoFAoFTE1NERISgr179z7x+wGg3ERBRERUM1q5lTEvLw+rV69G+/bt4e3tjVdffRWvv/461q1bp7VpXidOnIjff/8d06dPR0BAAHJycnD+/Hncv38fAPDFF18gJycHf/31F44fP655naOjo+a/N23ahMOHD+PLL7+Eg4MD7OzscPDgQYSFhcHX1xdLliyBXC7HggULMGDAAKxevRrDhw+vsJ7z58+jb9++cHFxwfHjx2Fra4vc3Fx069YNiYmJmDJlCnx9fXHhwgV8+eWXOHfuHPbs2QOZTIbjx49j+PDhGD58OKZNmwZjY2PEx8dj3759T/w+xMbGYsSIEZrwcebMGXz77be4fPmy5g/5ggUL8OabbyI2NhYbN26s9Pf4zJkz+PDDD/Hpp5/C3t4ev/76K1577TU89dRT6Nq1KwDgypUrCA4Ohp2dHX788UfY2Nhg5cqVGD16NG7fvo2PP/4YAHD79m1069YNhoaGWLBgAezt7fHHH3/g3XffLfe+K1euxMiRIzFw4EAsX74choaG+OWXX/D0009j165dCA0NrfTXQERENaeVcPDXX38hIyMDr732GgBg+PDhmDBhApYsWaK1cHD06FH07t0bH3zwgWZb6SUMAHB3d4e9vT0AoFOnThUeIzs7G+fOnYOVlZVmW1BQEKysrHDgwAGYm5sDAPr37w9/f39MmjQJw4YNK/epe8+ePXj++efRu3dv/P777zA2NgZQ0pB59uxZnDhxAoGBgQCA0NBQODs7Y8iQIdi5cyf69OmDY8eOQRAE/Pzzz1AqlZrjjh49+onfhx9++EHz32q1Gl26dIGNjQ3GjBmD77//HlZWVmjTpg0sLS0hl8sf+b2oyL1793D06FE0bdoUANC1a1fs3bsXq1at0oSDadOmoaCgAPv379esLti3b1+kp6fjq6++wtixY6FUKvG///0Pd+/eRXR0NPz8/AAAffr0Qe/evXHr1i3Ne+bm5mL8+PHo37+/KMj07dsXbdu2xZQpUyTpXyEiasy0Mh67ZMkSmJiYaBaIMTc3x9ChQ3H48GHNcHtNdejQATt27MCnn36KAwcOVKtfoGfPnqJgkJOTgxMnTmDIkCGaYACUzF//yiuvIDExEVeuXBEdY/ny5ejbty9ef/11/Pnnn5pgAABbt26Ft7c3/P39UVRUpHk8/fTTog799u3bAwCGDRuGP//8E0lJSZX+GqKjo/Hss8/CxsYG+vr6MDQ0xMiRI1FcXIyrV69W+XtSlr+/vyYYAICxsTFatWqF+Ph4zbZ9+/YhNDS03LLDo0ePRm5urmbUZv/+/fDy8tIEg1IjRowQPT927BgePHiAUaNGib5narUazzzzDCIjI8tdkiEiotpV43Bw/fp1HDp0CP369YMgCEhPT0d6ejqGDBkCABVes66OH3/8EZ988gk2bdqEHj16wNraGs8991yVwkfZSwwAkJaWBkEQym0HACcnJwDQXLYotWbNGpiYmOD1118vN6Jw+/ZtnD17FoaGhqKHhYUFBEHAvXv3AJR8It+0aROKioowcuRIuLi4wNvbW9M/8Si3bt1Cly5dkJSUhLlz5+Lw4cOIjIzU9FrUtMHSxsam3Da5XC467v379yv1/bp//z4cHBzK7fffbbdv3wYADBkypNz3bdasWRAEAQ8ePKj+F0VERFVW48sKv/32GwRBwF9//YW//vqr3L8vX74c06dPh76+fo3ex8zMDF999RW++uor3L59WzOKMGDAAFy+fLlSx/jvH3MrKyvo6ekhJSWl3L7JyckAAFtbW9H2P/74A1988QW6deuGf/75B/7+/pp/s7W1hYmJySMDUdljDRw4EAMHDoRKpUJERATCw8MxYsQING/eHEFBQRW+ftOmTcjJycGGDRvQrFkzzfaYmJjHft3aZGNjU6nvl42NDVJTU8vt999tpfvPmzfvkZdASi8XERHR4xUVFWHatGn4448/kJqaCkdHR4wePRqff/55lZq3axQOiouLsXz5cri7u+PXX38t9+9bt27F999/jx07dqB///41eSsRe3t7jB49GmfOnMGcOXOQm5sLU1NTyOVyACWfoE1MTJ54HDMzM3Ts2BEbNmzAd999p3mNWq3GypUr4eLiglatWoleY21tjT179qB///7o0aMHduzYofmj1r9/f8yYMQM2NjZwc3Or1Ncil8vRrVs3WFpaYteuXYiOjn5kOCgNN6VfJ1ByS+bixYsrPG5t3KoZGhqKjRs3Ijk5WTNaAAArVqyAqamp5nvRo0cPzJ49G2fOnBFdWli1apXoeCEhIbC0tMTFixcrbFYkIqLKmzVrFn7++WcsX74cXl5eiIqKwpgxY6BUKjF+/PhKH6dG4WDHjh1ITk7GrFmzKpyVztvbG/Pnz8eSJUtqHA46duyI/v37w9fXF1ZWVrh06RJ+//13BAUFwdTUFADg4+MDoOSb06dPH+jr68PX1xdGRkaPPG54eDjCwsLQo0cPTJo0CUZGRliwYAHOnz+P1atXV3gLoIWFBXbu3InBgwcjLCwMW7ZsQY8ePTBhwgSsX78eXbt2xQcffABfX1+o1WrcunUL//zzDz788EN07NgRX375JRITExEaGgoXFxekp6dj7ty5MDQ0RLdu3R5Za1hYGIyMjPDiiy/i448/Rn5+PhYuXIi0tLRy+/r4+GDDhg1YuHAh2rVrBz09PU2TZE1MnToVW7duRY8ePfDll1/C2toaf/zxB7Zt24bZs2drGiwnTJiA3377Df369cP06dM1dyv8d5TH3Nwc8+bNw6hRo/DgwQMMGTIEdnZ2uHv3Ls6cOYO7d+9i4cKFj60pKipKc8tqZmamZiQLKOnvKDvKQkRUX2VmZoqey+Vy0YdFADh+/DgGDhyoadhv3rw5Vq9eXeXZfWvUc7BkyRIYGRlhzJgxFf67ra0tBg0ahK1bt2quLVdXz549sWXLFowZMwa9e/fG7NmzMXLkSPz999+afUaMGIHXX38dCxYsQFBQENq3b68Z7n6Ubt26Yd++fTAzM8Po0aPxwgsvICMjA1u2bHnkbYwAYGJigs2bN+Ppp59G3759sX37dpiZmeHw4cMYPXo0Fi1ahH79+mHYsGH48ccf4eLigubNmwMoCTqpqan45JNP0Lt3b7z55pswMTHBvn374OXl9cj39PDwwPr165GWlobBgwfjvffeg7+/P3788cdy+44fPx5DhgzBlClT0KlTJ00TZE21bt0ax44dQ+vWrTFu3Dg899xzOH/+PJYuXYqPPvpIs5+DgwMOHjyINm3a4O2338bLL78MY2NjzJ8/v9wxX375Zezfvx/Z2dkYO3YsevXqhfHjx+P06dOVuo1x/vz5GDp0KIYOHYqEhARcvHhR83z//v1a+bqJiKTm6uoKpVKpeYSHh5fbp3Pnzti7d6+mQf3MmTM4cuQI+vbtW6X3kgmCIGilaqIGKjMzE0qlEr+Od67Ruuy5KjVen5uEjIwMKBQKLVZIRLpGW+cN4OG5IyEhQXTuqGjkQBAETJkyBbNmzYK+vj6Ki4vx7bffYvLkyVV6T63Mc0BERES1S6FQPPGDxdq1a7Fy5UqsWrUKXl5eiImJwYQJE+Dk5FSleYcYDoiIiBqIjz76CJ9++qlm3iEfHx/Ex8cjPDy8SuGAk9ITERE1ELm5ueVuWdTX14dara7ScRgOiKjGTpw4gUGDBqFp06aQy+Wwt7dHUFAQPvzwQ9F+CxYswLJly2qlhtGjR4tmOpXS4cOHIZfLRbOLCoKAH3/8ER4eHpDL5XB0dMTbb79d4d1GlbVnzx6EhYXByckJcrkcdnZ26NmzJ7Zv3y7ar7CwEO7u7rWyjPuMGTOwadMmrR+3pqZNm/bEBeeqIisrCx9//DF69+6NJk2aQCaTYdq0aVo7vrYMGDAA3377LbZt24abN29i48aN+OGHHzBo0KAqHYfhgIhqZNu2bQgODkZmZiZmz56Nf/75B3PnzkVISAjWrl0r2rc2w4GuEAQBEyZMwBtvvCG6jXbSpEn44IMPMHDgQGzduhWffvopVq1ahbCwMNGqqlVx//59eHl54X//+x/++ecf/PLLLzA0NES/fv2wcuVKzX6Ghob48ssv8fXXX5eb9bWmdDUcaNv9+/exaNEiqFQqPPfcc1KX80jz5s3DkCFD8M4778DT0xOTJk3C2LFj8c0331TpOOw5IKIamT17Ntzc3LBr1y4YGDw8pbzwwguYPXt2tY9bWFgImUwmOmZ9sHPnTpw+fVo04VfplOfjxo3DrFmzAJTMW2JnZ4cRI0Zg2bJleOONN6r8XqWru5bVv39/uLm5YdGiRXj55Zc121988UVMnDgRv/zyC6ZMmVLNr67xatasGdLS0iCTyXDv3r0KJ/7TBRYWFpgzZ06NR4k4ckBENXL//n3Y2tpW+Ee87LXP5s2b48KFCzh48CBkMhlkMplm7o8DBw5AJpPh999/x4cffghnZ2fI5XJcv34dQMk07X5+fjA2Noa1tTUGDRqES5cuPbG2o0ePwtbWFv3799cs4HXt2jWMGDECdnZ2kMvl8PT01KxPUkqtVmP69Olo3bo1TExMYGlpCV9fX8ydO/eJ77lw4UK0b98erVu31myLiIhAcXFxuXvNSyeHW79+/ROPW1mGhoawtLQs9/MwMjLC8OHDsWjRIjzpDvb8/Hx8+OGH8Pf3h1KphLW1NYKCgrB582bRfjKZDDk5OVi+fLnmZ1rRhHilbt68CZlMhu+++w4//PAD3NzcYG5ujqCgIERERJTbf8uWLZqJ7iwsLBAWFqZZ3K2sbdu2wd/fH3K5HG5ubvjuu+8qfH9BELBgwQL4+/vDxMQEVlZWGDJkCOLi4h77/Sj9WrV5mULXMRwQUY0EBQXhxIkTeP/993HixIlHDpFv3LgRLVq0QEBAAI4fP47jx4+LlukGgMmTJ+PWrVv4+eef8ffff8POzg7h4eF47bXX4OXlhQ0bNmDu3Lk4e/YsgoKCHrvw2p9//onQ0FAMGzYMmzdvhpmZGS5evIj27dvj/Pnz+P7777F161b069cP77//Pr766ivNa2fPno1p06bhxRdfxLZt27B27Vq89tprSE9Pf+z3oqCgAHv27EGPHj3KbQdQ7p50Q0NDyGQynD179rHHfRK1Wo2ioiIkJydj6tSpuHr1arl+DwDo3r074uPjcf78+cceT6VS4cGDB5g0aRI2bdqE1atXo3Pnzhg8eDBWrFih2e/48eMwMTFB3759NT/TBQsWPLHen376Cbt378acOXPwxx9/ICcnB3379kVGRoZmn1WrVmHgwIFQKBRYvXo1lixZgrS0NHTv3h1HjhzR7Ld3714MHDgQFhYWWLNmDf7v//4Pf/75J5YuXVrufceOHYsJEyagV69e2LRpExYsWIALFy4gODi4xhP1NTT1a7yOiHTOzJkzcfnyZcybNw/z5s2DoaEh2rdvjwEDBuDdd9/VNAkGBATAxMQECoXikYtsubu7Y926dZrn6enp+Oabb9C3b1/RMH337t3RsmVLzQIz/zVr1ix89tlnmDFjBj7++GPN9okTJ8LCwgJHjhzR3C8eFhYGlUqFmTNn4v3334eVlRWOHj0KHx8fUcPZ008//cTvRUxMDPLy8tC2bVvR9jZt2gAoGckoGxyOHTsGQRBq3AfQt29f7Nq1C0DJvfBr167VTJ9bVmldpV/foyiVStEf1+LiYoSGhiItLQ1z5szByJEjAQCdOnWCnp4emjRp8sifaUUsLCywdetWzYJ8Tk5O6NChA3bs2IEXXngBarUaH330EXx8fLBjxw7NCFTfvn3h7u6OTz75BEePHgUAfPbZZ7C3t8fu3bthbGwMoORnVToqVSoiIgKLFy/G999/j4kTJ2q2d+nSBa1atcIPP/ygueRDHDkgohqysbHRLB8+c+ZMDBw4EFevXsXkyZPh4+OjWaq8Mp5//nnR8+PHjyMvLw+jR48WbXd1dUXPnj2xd+9e0XZBEDB27FhMnToVq1atEgWD/Px87N27F4MGDYKpqSmKioo0j759+yI/P18ztN2hQwecOXMG77zzDnbt2lVuTvtHKZ2u3c7OTrTdz88PXbt2xf/93/9h3bp1SE9Px7Fjx/DWW29BX1+/SqvlVWTevHk4efKkZkr34cOHV7gEfGldSUlJTzzmunXrEBISAnNzcxgYGMDQ0BBLliyp1OWcJ+nXr59opV5fX18A0NzdceXKFSQnJ+OVV14RfW/Mzc3x/PPPIyIiArm5ucjJyUFkZCQGDx6sCQZASfgYMGCA6D23bt0KmUyGl19+WfSzd3BwgJ+fHw4cOFDjr6shYTggIq0IDAzEJ598gnXr1iE5ORkffPABbt68WaWmREdHR9Hz0k/U/90OlHza/O8n7oKCAqxduxZeXl7o06dPuWMVFRVpRjfKPkp7AUqDzOTJk/Hdd98hIiICffr0gY2NDUJDQ5+4eE3pSqhl/1CVKv1jO2zYMFhZWaFHjx4YPHgw/P394ezs/NjjPknLli3Rvn17PPvss5rLKePGjSt3b3tpXU9asXXDhg0YNmwYnJ2dsXLlShw/fhyRkZF49dVXkZ+fX6NagZJAWVbZFXWBJ//c1Wo10tLSkJaWBrVaDQcHh3L7/Xfb7du3IQgC7O3ty/38IyIiqhRiGwNeViAirTM0NMTUqVPxv//974nXt8v6b8NX6R+RlJSUcvsmJyfD1tZWtE0ul2P//v14+umn0atXL+zcuRNWVlYAACsrK+jr6+OVV17BuHHjKnz/0qXWDQwMMHHiREycOBHp6enYs2cPpkyZgqeffhoJCQmalWD/q7SeBw8elPs3Ozs7bN++HXfu3EFqaiqaNWsGExMTLFiwAEOGDHnct6XKOnTogJ07d+Lu3buwt7fXbC+t67/ft/9auXIl3NzcsHbtWtHPRKVSabXOR3nSz11PTw9WVlYQBAEymQypqanl9vvvNltbW8hkMs0cFP9V0bbGjCMHRFQjFZ3AAWiGn52cnDTb5HL5Ez+1lhUUFAQTExPRPfsAkJiYiH379lW4amdAQAAOHjyIxMREdO/eHXfu3AEAmJqaokePHoiOjoavry8CAwPLPf77iRYALC0tMWTIEIwbNw4PHjzQLA9eEU9PTwBAbGzsI/exs7ODr68vlEolfv75Z+Tk5ODdd9+tzLejUgRBwMGDB2FpaVnu6yntyi/tgXgUmUwGIyMjUTBITU0td7cCUPWfaWW0bt0azs7OWLVqlejOipycHKxfv15zB4OZmRk6dOiADRs2iEY0srKyRCv2AiV3hgiCgKSkpAp/9o/rwWiMOHJARDXy9NNPw8XFBQMGDICHhwfUajViYmLw/fffw9zcHOPHj9fs6+PjgzVr1mDt2rVo0aIFjI2NH3tStrS0xBdffIEpU6Zg5MiRePHFF3H//n189dVXMDY2xtSpUyt8naenJw4fPoxevXqha9eu2LNnD1xcXDB37lx07twZXbp0wdtvv43mzZsjKysL169fx99//419+/YBKJllztvbG4GBgWjSpAni4+MxZ84cNGvWDC1btnxkvS4uLmjRogUiIiLw/vvvi/5t8eLFAEqaLtPT07Fjxw4sWbIEM2bMKNfA2L17dxw8ePCJtxwOHDgQfn5+8Pf3h42NDZKTk7Fs2TIcPHgQP/30U7nbGSMiIqCvr4+uXbs+9rj9+/fHhg0b8M4772DIkCFISEjAN998A0dHx3J3iPj4+ODAgQP4+++/4ejoCAsLC9FtnNWhp6eH2bNn46WXXkL//v0xduxYqFQq/N///R/S09Mxc+ZMzb7ffPMNnnnmGYSFheHDDz9EcXExZs2aBTMzM9EITkhICN58802MGTMGUVFR6Nq1K8zMzJCSkoIjR47Ax8cHb7/99mPr2rFjB3JycpCVlQUAuHjxIv766y8AJc2SjxpRqo8YDoioRj7//HNs3rwZ//vf/5CSkgKVSgVHR0f06tULkydP1nyaBoCvvvoKKSkpeOONN5CVlYVmzZo99pM4UHL9387ODj/++CPWrl0LExMTdO/eHTNmzHjsH+oWLVpoAkKXLl2wd+9etGnTBqdPn8Y333yDzz//HHfu3IGlpSVatmwpmoOgR48eWL9+PX799VdkZmbCwcEBYWFh+OKLL2BoaPjYel966SXMnz8fKpVKNFQtCALmzJmD+Ph46OnpISAgABs3bsTAgQPLHSM7O7vC6+j/FRISgr/++gvz589HZmYmLC0tERgYqLlF8782bdqEvn37wtLS8rHHHTNmDO7cuYOff/4Zv/32G1q0aIFPP/0UiYmJols+AWgmd3rhhReQm5uLbt26aaW5b8SIETAzM0N4eDiGDx8OfX19dOrUCfv370dwcLBmv7CwMGzatAmff/45hg8fDgcHB7zzzjvIy8srV+svv/yCTp064ZdffsGCBQugVqvh5OSEkJAQdOjQ4Yk1vf3226IpsdetW6e5u+bGjRvl7pCoz2TCk6IpUSOnrXXZS9dkz8jIeOKyq0DJpEFlT0Sl3nnnnXKT9pDuSE5OhpubG1asWFFu9sLKyMrKgrW1NebMmfPI3ojqiI2NRcuWLbFr1y6EhYVp7bhUMW2dN4Cqnzu0gT0HRDoqMjISKSkpmsfu3bsBAEOHDpW4MnocJycnTJgwAd9++22VV8IDgEOHDsHZ2bla0yk/zvTp0xEaGspgQJXCywpEOqpJkyai5zNnzoS7uzu6desmUUVUWZ9//jlMTU2RlJQEV1fXKr22X79+FV4SqImioiK4u7tj8uTJWj0uNVwMB0R17L8T6sjl8ifeRlVQUICVK1di4sSJjWp+9/rKwsLikc2SUjAwMMDnn38udRlUj/CyAlEdc3V1hVKp1DzCw8Of+JpNmzYhPT293EyBRES1gSMHRHUsISFB1FRUmclXlixZgj59+ojmDCAiqi0MB0R1TKFQVKnjOD4+Hnv27MGGDRtqsSoiood4WYFIxy1duhR2dnZab1IjInoUhgMiHaZWq7F06VKMGjWq3Gx3RES1heGASIft2bMHt27dwquvvip1KUTUiPCjCJEO69279xPn1yci0jaOHBAREZEIwwERERGJMBwQERGRCHsOiCqpS9tkWJhWf+rirFz2DhA1NjU9bwDSnDs4ckANzuW0VKlLICKq1xgOqEFZfuk4wjbNxeILh6UuhYio3mI4oAZjb8JlfHFiCwQIyC8qkrocIqJ6i+GAGoQL95PxzoFVUAsChrcMxLu+3aUuiYio3mI4oHovOScDI/csQ05RATo7PoWZwYMgk9WsAYiIqDFjOKB6LbtQhdF7luF2biZaWdrhlx4vwVBPX+qyiIjqNYYDqreK1MV4e/8qXHyQgiYm5ljeazSUchOpyyIiqvcYDqheEgQBX574G/uTrsBY3xBLQ0fB1cJa6rKIiBoEhgOqlxZfOIIVlyMggwzzug2HfxNXqUsiImowGA6o3tkRfx7fRG4HAHzRvi/6NPOWuCIiooaF4YDqlei7CXjv4FoIEDDKoxPe8OosdUlERA0OwwHVGwlZDzBmz3LkFxeip0trfNVxAG9ZJCKqBQwHVC9kqPIwcvcy3MvPhpe1IxZ0HwED3rJIRFQrGA5I5xUUF+HN/StxLeMOHEwVWNZrNMwN5VKXRUTUYDEckE4TBAGTj2/E0ZRYmBkYYUXYaDiaKaUui4ioQWM4IJ027+x+rL12CnoyGRZ0H4E21k5Sl0RE1OAxHJDO2hQXg9mn/wEATO80EKGuHhJXRETUODTYcFBQUIDDhw/j119/hSAIUpdDVXTy9k1MPLwOADDWqwtGenSSuCJqLJKTk7F69WpERkZKXQqRZBpsOCguLsaff/6JyMhIxMbGSl0OVUFcxj28uncFCtTFeKapFz5r30fqkqgROXv2LA4cOIC9e/dKXQqRZBpsODAxMUH79u0BAIcPH5a4GqqsB/k5GLl7KdJVufC3dcW8bsOhJ2uw/5uSDgoKCoKenh5u3LiBxMREqcshkkSDPut26dIFAHDq1Cnk5ORIXA09SX5RIV7buwI3s+7DxdwSS3uNhImBkdRlUSOjVCrh7+8PgB8sqPFq0OGgefPmcHFxQWFhIU6cOCF1OfQYakGND4/+hcg78VAYGWNF2Bg0MbGQuixqpEo/WERERKCgoEDiaojqXoMOBzKZTPNLfvjwYTYm6rDvTu/G5rgzMJDpYVGPl9HK0l7qkqgR8/DwgK2tLfLz8xEVFSV1OUR1rkGHAwDo2LEjDA0NkZycjLi4OKnLoQqsvRaFH8/uBwDMChmMzk5PSVwRNXZ6enro3LlkUS9eWqDGqMGHAzYm6rYjydfxydENAID3fXtgeMtAiSsiKhEcHAw9PT3ExcUhKSlJ6nKI6lSDDwfAw+uHUVFRbEzUIVfTb+PN/StRJKgxsIUfPmrbW+qSiDSUSiX8/PwAAIcOHZK4GqK61SjCgZubGxsTdczdvCyM3L0UmQX56GDfHN+HDOHyyxVISkrCyy+/DBsbG5iamsLf3x+nTp2SuqxGo2vXrgCAEydOsDGR6o3mzZtDJpOVe4wbN67Sx2gU4UAmk4muH7IxUVp5RQUYvWc5ErPT0dzCBr/2fAXGBoZSl6Vz0tLSEBISAkNDQ+zYsQMXL17E999/D0tLS6lLazQ8PDxgY2ODvLw8hjKqNyIjI5GSkqJ57N69GwAwdOjQSh+jUYQDgI2JuqJYrcZ7B9fizL1EWMlNsSJsDKyNzaQuSyfNmjULrq6uWLp0KTp06IDmzZsjNDQU7u7uUpfWaLAxkeqjJk2awMHBQfPYunUr3N3d0a1bt0ofo9GEA1NTUwQGljS78ZdcOjOidmDnrQsw0tPHktCRaKG0lbqkOpeZmSl6qFSqCvfbsmULAgMDMXToUNjZ2SEgIACLFy+u42opJCQEenp6iI2NZWMiSaqy546yCgoKsHLlSrz66qtVunTbaMIBIG5MzM3NlbiaxmfF5Qj8cqEkmP3QZSg62DeXtiCJuLq6QqlUah7h4eEV7hcXF4eFCxeiZcuW2LVrF9566y28//77WLFiRR1X3LgplUr4+voCAI4cOSJxNdSYVfbcUdamTZuQnp6O0aNHV+m9DKpZY73UokULODk5ITk5GSdOnECPHj2kLqnR2JtwGZ9HbAYAfNy2N55r4S9tQRJKSEiAQqHQPJfL5RXup1arERgYiBkzZgAAAgICcOHCBSxcuBAjR46sk1qpRNeuXRETE4OIiAgMGjQIRkac1pvqXmXPHWUtWbIEffr0gZOTU5Xeq1GNHMhkMk33MRsT687FB8l458AqqAUBw1u2w3u+jTuUKRQK0eNRv+COjo5o06aNaJunpydu3bpVF2VSGZ6enrCxsUFubi4bE0kylT13lIqPj8eePXvw+uuvV/m9GlU4AB42JiYlJeHGjRtSl9PgJedkYOTuZcgpKkCIozvCgwbxlsVKCgkJwZUrV0Tbrl69imbNmklUUePFxkSqj5YuXQo7Ozv069evyq9tdOGAjYl1J7tQhTF7liE1NxOtLO2wqMfLMNJvVFeyauSDDz5AREQEZsyYgevXr2PVqlVYtGhRle5VJu0pnTExNjYWycnJUpdD9FhqtRpLly7FqFGjYGBQ9fNuowsHwMPGxMjISOTl5UlcTcNUpC7GOwdW4cKDFNgam2N5r9FQyk2kLqtead++PTZu3IjVq1fD29sb33zzDebMmYOXXnpJ6tIaJUtLS01jIj9YkK7bs2cPbt26hVdffbVar2+U4aC0MbGwsBARERFSl9PgCIKAqSf+xr7EKzDWN8TSXqPgamEtdVn1Uv/+/XHu3Dnk5+fj0qVLeOONN6QuqVHjUs5UX/Tu3RuCIKBVq1bVen2jDAdcyrl2/XrxCJZfjoAMMszrNhwBTVylLolIK9q0aaNpTDx9+rTU5RDVmkYZDgBxY+LNmzelLqfB2BF/Hl+f3A4A+Lx9H/Rp5i1xRUTao6enh5CQEAC8tEANW6MNB2ZmZmjXrh0A/pJrS/TdBLx3cC0ECBjp0QlvenWRuiQirSttTLx+/TobE6nBarThAGBjojYlZD3AmD3LkV9ciB7OrfF1xwG8ZZEaJCsrK/j4+ADgjInUcDXqcODu7g5HR0cUFBTg5MmTUpdTb2Wo8jBqzzLcy89GG2tHLOwxAgZ6+lKXRVRrSj9YHD9+HIWFhRJXQ6R9jToclG1MPHToEBsTq6GguAhj9/+Bq+l3YG+qwLJeo2Fu+OQpPYnqMy8vL1hbW3PGRGqwGnU4AIBOnTrB0NAQiYmJbEysIkEQMPn4JhxJuQ5TAyOs6DUaTmZKqcsiqnWcMZEaukYfDtiYWH3zzx7A2mtR0JPJsLD7CHjZVG1hD6L6LDg4GDKZDNevX0dKSorU5RBpFeeyRcn1w4iICERGRmLo0KEwMeFMfk+yKS4Gs07vAgB80/FZhLp6SFxR7QsvdIZRYfXzdEGhGkCi9goiSVlZWcHX1xdnzpzB4cOHMWzYMKlLIh1U0/MGIM25o9GPHABsTKyqk7dvYuLhdQCAN706Y5RnkMQVEUmj7IyJbEykhoThACWNiWWvH7Ix8dFuZN7Da3tXoEBdjGeaeuGzwL5Sl0QkGS8vL1hZWSEnJ4czJlKDwnDwr6CgIBgYGCAhIQHx8fFSl6OT0vJzMHL3MqSpcuFn64J53YZDX4//C1HjxcZEaqh4Zv8XGxMfT1VchNf2/Y4bmffgYm6JpaGjYGJgJHVZRJILCQmBTCbDtWvXkJqaKnU5RFrBcFAGZ0ysmCAI+PDIXzh5+yYURsZY3msM7EwtpC6LSCeUnTGRHyyooWA4KOOpp56Cg4MDVCoVIiMjpS5HZ3wXvRub4mJgINPDoh4vo7WVvdQlEekUzphIDQ3DQRn/XcqZgD+vRWHumX0AgJnBg9DZ6SmJKyLSPd7e3prGxOjoaKnLIaoxhoP/6NSpEwwMDHDr1q1GP2Pi0eTr+PjoBgDAe7498EKr9hJXRKSbuJQzNTQMB/9hbm6Otm3bAmjcv+RX02/jjf0rUSSoMdDNDx+1DZO6JCKdVtqYePXqVTYmUr3HcFCBso2J+fn5EldT9+7mZWHU7mXILMhHe7tm+L7zEOjJ+L8K0eNYW1vD29sbAJdypvqPZ/wKtGzZEvb29lCpVI1uxsS8ogKM2bMCCdlpaG5hgyWhI2FsYCh1WUT1QukHi2PHjrExkeo1hoMKNNbGRLWgxvuH1iLmXgIs5aZYETYG1sZmUpdFVG+UbUyMiYmRuhyiamM4eITSGRNv3brVaGZM/DZqJ3bEX4CRnj6W9HwFLZS2UpdEVK/o6+uzMZEaBIaDRzA3N0dAQACAxvFL/vvlCPxy/hAA4PvOQ9HRwU3iiojqp9LGxCtXruD27dtSl0NULQwHj9G1a1cAwMmTJxt0Y+K+xCv4LGIzAOCjgDAMcveXtiCieqxsY2Jj+GBBDRPDwWOUbUxsqDMmXnyQjLf3/wG1IGDYU+3wvl9PqUsiqvc4YyLVdwwHj9HQGxNTcjIwcvcy5BQVIMTRHTODB0Emk0ldFlG95+3tDUtLS2RnZ7MxkeolhoMnKG1MjI+Px61bt6QuR2uyC1UYvWcZUnMz0VJph0U9XoaRvoHUZRE1CGxMpPqO4eAJGmJjYpG6GO8cWIULD1Jga2yO5WGjoZSbSF0WUYPSuXNnNiZSvcVwUAmllxZOnDhR7xsTBUHA1BNbsS/xCuT6Bvit10g0tbCWuiyiBsfa2hpeXl4AOGMi1T8MB5XQqlUr2NnZQaVSISoqSupyauTXi0ew/PJxyCDDvK4voG2TplKXRNRgccZEqq8YDiqhoTQm7oy/gK9PbgcAfN6+D/o295a4InqcadOmQSaTiR4ODg5Sl0VV4OPjo2lMPHPmjNTlEFUaw0ElBQUFQV9fHzdv3qyXjYkxdxPw7sE1ECDgldYd8aZXF6lLokrw8vJCSkqK5nHu3DmpS6IqYGMi1VcMB5VkYWGhaUysb9cPE7IeYMze5cgvLkQP59b4ptOzvGWxnjAwMICDg4Pm0aRJE6lLoioqnTHx8uXLuHPnjtTlEFUKw0EV1MfGxAxVHkbtWYa7ednwtHLAwh4jYKCnL3VZjVpmZqbooVKpHrnvtWvX4OTkBDc3N7zwwguIi4urw0pJG2xsbDSNiRw9oPqC4aAKWrduDTs7O+Tn59eLxsRCdTHeOvAHrqbfgb2pAsvDxsDcUC51WY2eq6srlEql5hEeHl7hfh07dsSKFSuwa9cuLF68GKmpqQgODsb9+/fruGKqqbIzJhYVFUlcDdGTMRxUgUwmQ+fOnQHo/icAQRDw6bGNOJx8HaYGRljeaxSczJRSl0UAEhISkJGRoXlMnjy5wv369OmD559/Hj4+PujVqxe2bdsGAFi+fHldlkta4OPjA6VSiaysLDYmUr3AcFBFZRsTExISpC7nkX46dwBrr0VBTybDwu4j4G3jLHVJ9C+FQiF6yOWVG80xMzODj48Prl27VssVkraxMZHqG4aDKlIoFPD39wegu7/km+POYOapXQCArzs+i1BXD4krIm1QqVS4dOkSHB0dpS6FqqG0MfHSpUu4e/eu1OUQPRbDQTWUbUx8XDOZFCJv38TEI+sAAG94dcZozyCJK6LqmjRpEg4ePIgbN27gxIkTGDJkCDIzMzFq1CipS6NqsLW1RZs2bQDo7gcLolIMB9Wgq42JNzLv4dW9K6AqLsLTTdvg88C+UpdENZCYmIgXX3wRrVu3xuDBg2FkZISIiAg0a9ZM6tKomsrOmMjGRNJlDAfVoKenp3ONiWn5ORi5exnSVLnws3XBvK4vQF+PP976bM2aNUhOTkZBQQGSkpKwfv16zSdPqp98fX2hUCjYmEg6j389qqm0MfHGjRuSNyaqiovw+r7fcSPzHlzMLbE0dBRMDY0krYmIymNjItUXDAfVVLYxUcoZEwVBwIdH/sKJ2zdhYSjH8l5jYGdqIVk9RPR4pUs5szGRdBnDQQ2UXj+MiIhAQUGBJDV8F70bm+JiYCDTw6KeL6O1lb0kdRBR5dja2sLT0xNA/ZuKnRoPhoMaaN26NWxtbZGfn4/IyMg6f/8/r0Vh7pl9AICZwYPQxallnddARFVXtjGxuLhY4mqIymM4qAE9PT3JlnI+mnwdHx/dAAB4z7cHXmjVvk7fn4iqz8/PDwqFApmZmWxMJJ3EcFBDwcHB0NPTw40bN5CYmFgn73kt/Q7e2L8SRYIaz7r54qO2YXXyvkSkHWxMJF3HcFBDdT1j4t28LIzcvRSZBflob9cMP3QeCj0Zf4xE9U3p7dAXL17EvXv3JK6GSIx/VbSg7IyJtdmYmFdUiFf3rkBCdhqaWdhgSehIGBsY1tr7EVHtKTtjIhsTSdcwHGiBh4cHbG1tkZeXV2szJqoFNcYfWovouwmwlJvi97DRsDY2q5X3IqK6UfrB4ujRo2xMJJ3CcKAFddGYOCNqJ7bHn4eRnj6W9HwFLZRNauV9iKjusDGRdBXDgZYEBQVBT08PcXFxSEpK0uqxV14+gZ/PHwIAfN95KDo6uGn1+EQkDX19fQQHBwNgYyJpT1JSEl5++WXY2NjA1NQU/v7+OHXqVJWOwXCgJUqlslYaE/cnXsFnEZsBAJMCwjDI3V9rxyYi6ZU2Jl66dImNiVRjaWlpCAkJgaGhIXbs2IGLFy/i+++/h6WlZZWOw3CgRdpuTLz4IBlv7f8DxYIaQ59qi/F+PWt8TCLSLU2aNIGnpycEQWBjItXYrFmz4OrqiqVLl6JDhw5o3rw5QkND4e7uXqXjMBxokYeHB2xsbJCbm1vlIZz/Ss3NxKjdy5FTVIBghxaYFTwYMplMS5USkS7hjIlUGZmZmaKHSqUqt8+WLVsQGBiIoUOHws7ODgEBAVi8eHGV38tAGwVTidKlnDdv3ozDhw8jKCioWsfJKVRh9O5lSMnNwFPKJljU82UY6fNHJbUps9+Ehb5xtV+fVZyPZfhSixVRQ+Hn5wcLCwtkZGTg7NmzCAgIkLok0pKanjeAh+cOV1dX0fapU6di2rRpom1xcXFYuHAhJk6ciClTpuDkyZN4//33IZfLMXLkyEq/J0cOtCwkJAR6enqIjY2tVmNisVqNdw6sxvkHybAxNsOKsDGwlJvWQqVEpCsMDAzYmEhPlJCQgIyMDM1j8uTJ5fZRq9Vo27YtZsyYgYCAAIwdOxZvvPEGFi5cWKX3YjjQMqVSCT8/PwBVn9hEEARMPfk39iZehlzfAEt7jUJTC+vaKJOIdEzppQXOmEiPolAoRA+5XF5uH0dHR83kWqU8PT1x69atKr0Xw0EtqO5SzksuHsWyS8chgww/dh2Otk2a1laJRKRjyjYmHj16VOpyqJ4KCQnBlStXRNuuXr2KZs2aVek4DAe1wNPTU9OYePr06Uq9Zlf8BXx1chsA4LPAPujX3Kc2SyQiHcQZE6mmPvjgA0RERGDGjBm4fv06Vq1ahUWLFmHcuHFVOg7DQS0obUwEgEOHDj1x/zP3EvHuoTUQIODl1h0x1rtLbZdIRDqobGPiuXPnpC6H6qH27dtj48aNWL16Nby9vfHNN99gzpw5eOmll6p0HIaDWlK6lHNsbCySk5MfuV9idhpG71mGvKJCdHduhemdnuUti0SNlIGBgeYuJzYmUnX1798f586dQ35+Pi5duoQ33nijysdgOKgllpaW8PX1BfDoX/LMgnyM2r0Md/Oy4WnlgIXdR8BAT78uyyQiHVN6aeHChQu4f/++xNVQY8VwUIse15hYqC7G2P0rcSX9NuxNFVjeazQsjGp2LywR1X92dnbw8PBgYyJJiuGgFrVp06bCxkRBEDD52EYcTr4OUwMjLO81Ck7mltIVSkQ6hY2JJDWGg1qkp6eHkJAQAOJLCz+dO4g116KgJ5NhQfcX4W3jLFWJRKSD/P39YWFhgfT0dJw/f17qcqgRYjioZaUzJl6/fh3JycnYEncGM0/tBAB81WEAerl6SlwhEemaso2JlbnjiUjbGA5qWdnGxPX/bMcHR9YBAF5vE4IxbYKlLI2IdFjp7dAXLlzAgwcPJK6GGhuGgzpQev3wzMlImGen4emmbfBF+34SV0VEusze3h6tWrfiUs4kCS71V4uys1U4E52MU5EPoCezgLE8HYujVsM24QDuJZ2EqWcPmHp2h765jdSlEpGOEAQBp+7cwoa4aBzTuws3C2PY29tLXRY1MgwHWlZYUIwLF24jOioRVy7fhVotAABMjbsixukm0gq2wjLlMjJSLiNj30JAJoPc1Q8mnt1h6tkDJq27Qt9EIfFXQUR1LS7jHjbERWNjbDTis/69jKAQkNWuCVr5czp1qlsMB1qgVguIi72P01FJOHcmBSpVkebfXFyVsG5lgmnJm2FmYYTQty8i/8oh5F7aj9xL+1GQdAGqWzFQ3YpB+q45gJ4+jJu3g+3w2TBtzWmU6aHw8HBMmTIF48ePx5w5c6Quh7Tgfn42tsSdxYa4aETfTdBsNzUwQp9mXnjevS1CHN2hr8crwFS3GA5qICU5E9GnkhB9KgkZGfma7VZWJggIdEZAO2fY21vgh+g9yL9biN6OnjAwt4Z5u+dg3u45AEBRxm3kXtqPvMsHkHtpPwpvX0d+3EnoGZtL9FWRLoqMjMSiRYs0za1Uf+UVFWL3rYvYEBeNA4lXUSSoAQB6Mhm6OrXE8+5t8XTTNjA1NJK4UmrMGA6qKCM9DzHRyTgdlYSU5EzNdhMTQ/j6O6JtO2c0c7OGnt7D9RGOpcYCAIId3Msdz0BpD0WnF6Do9AIAoPD+LeRdPgC5q18tfyVUX2RnZ+Oll17C4sWLMX36dKnLoWpQC2ocT4nDhrhobLt5HtmFKs2/+do4Y7B7AJ5184OdqYWEVRI9xHBQCfn5RTh/NgXRp5Jw/do9CCVtBNDXl8GzjT0CAp3h4WkHQ8Py6yLkFRXg9J1bAIBgx/Lh4L8MbZrCMGSkVusn3ZKZmSl6LpfLIZfLH7n/uHHj0K9fP/Tq1YvhoJ65nJaK9dejsSkuBim5GZrtLuaWGNQiAIPdA9DS0k7CCokqxnDwCMXFaly9chfRp5Jw4VwqCgvVmn9r7maFtoEu8PVzhKnZ44f+ou7Eo0BdDEdTJdwUvCuBAFdXV9HzqVOnYtq0aRXuu2bNGpw+fRqRkZF1UBlpQ2puJjbFxmBDXDQuPkjRbFcYGaN/c1887x6A9vbNoCdjHwHpLoaDMgRBQGJCBk5HJeJMdDKysx8ulmTbxAztAl3g39YJNrZmlT7msZQ4AECwYwsuxUwAgISEBCgUD+9IedSoQUJCAsaPH49//vkHxsZclEuXZReqsDP+PNbHRuNIciwElAwvGurpo6dLawx2D0CoiweMDQwlrpSochgOADy4n4voU0k4fSoRd+/kaLabmRvBP8AJbQNd4OKqrNYf96MpJf0GIZW4pECNg0KhEIWDRzl16hTu3LmDdu3aabYVFxfj0KFDmD9/PlQqFfT1ucS3VIrUxTiUfB3rY09jV/xF5BcXav6tvV0zDHYPQH83X1jJTSWskqh6Gm04yM0twNmYFJyOSsLNGw+nJjUw1IOXtwPaBjqjVesm0Nev/tBfdqEKZ+4lAqhcvwFRWaGhoTh37pxo25gxY+Dh4YFPPvmEwUACgiDg7P0krL9+GltunMW9/GzNv7VQ2GKwewAGufujmQUvIVL91qjCQVFRMS5dvIPoqCRcungHxcUlfQQyGeD+lC3aBjrD29cBxsbaGfo7kXoDxYIazSys4WJupZVjUuNhYWEBb29v0TYzMzPY2NiU2061KyHrATbGxWB9bDRiM+5qttsYm+FZNz8Mdg+Av60LLx1Sg9Hgw4FaLSD+ZhpORyXibEwK8vIeDv05OlkgoJ0LAto6QWlpovX3PvbvJQWOGhDVP+mqXGy9eQ4bYqNx8vZNzXa5vgGeaeqFwe4B6OrcEoZ6HMGhhqfBhoM7t7Nx+lQiok8lIe1Bnma7QilHQFtntA10gaNT7U5TfCz132bECuY3IKqOAwcOSF1Cg6YqLsK+xMvYEBuNvQmXUaAuBgDIIEOIozsGu/ujTzNvWBixQZQatgYVDrKzVP9OUJSIxISH9xQbyfXh6+eIgHYucH/KRjRBUW1JU+Xi/P1kACV3KhCRbhIEAZF34rEhNhp/3ziLjIKHHyY8rBzwvHsABrbwh5OZUsIqiepWvQ8HBQXFuHA+FaejEnHtyj3NQkd6ejK08miCtu2c0cbbAUZGdTv0F5EaBwECnlI2gb0pF1Ii0jWxGXexITYaG2KjkZCdptlub6rAoBb+GOwegDbWjhJWSCSdehkO1GoBsdfulSx0dC4FBapizb+5NrVE23bO8AtwgrnFo2edq22l8xvwFkYi3XEvLxubb5zBhthozZ1EAGBmYIR+zX0w2D0AQQ4tuNARNXr1KhwkJ2Xi9KlExJxOQmbGw7nJra1NNQsd2dnpxoJFbEYk0g15RQXYdesiNsRG42DSNRT/u9CRvkwP3ZxLFjrq3dQTJgZc6IiolM6Hg/T0PMScSsLpU0lITcnSbDcxNYSfv9O/Cx1Z6dQtRHfzsnAl/TYAIMiB/QZEda1Yrcax1FhsiI3G9pvnkVP0cLZTP1sXPP/vQke2JrrxYYJI1+hkOMjPL8S5MyV9BHGx98ssdKSHNl52CAh0gYdnExgY6OYtRMf/vaTQxtoR1saVn2qZiGrm4oNkrI+Nwaa4GNzOfbjAVVNzawxyL+kjcFc2kbBCovpBZ8JBcbEaVy7/u9DR+VQUlVnoyM3dGm3bOcPHzxGmpro/9Mcpk4nqTnJOBjbFxWBDbDQup6VqtiuNTPCsmy8Guwcg0K6ZTo0uEuk6ScOBIAhIuJWO01FJOBOdjJych0N/dnbmaBvoDP92zrC2rl9zkz+c34CXFIhqQ1ZBPrbHn8eG2GgcS4nTLHRkpKePUFcPPO/eFj1cWkOurzOff4jqFUl+c+7fy8HpU0mIPpWEe3cfLnRkbm4E/7bOaBvoDGeX6i10JLXknAzcyLwHPZkMHRkOiLSmUF2MQ0nXShY6unURquIizb91tG+OQe4B6N/cB5Zc6IioxuosHOTkFOBsTDJORyUh/ubDe4oNjfTh7eOAtu2c8VQr2xotdKQLSu9S8LFxhoKzqBHViCAIiLmXiPWxp7El7iweqB5+mHBXNsHz7gEY1MIfrhbWElZJ1PDUajgoLCzGpQu3EX0qCZcv3UFxccnQn0wGPNXSFm0DXeDl4wBj44Yz9HeM/QZENRafdf/fCYpicCPznma7rbE5Brbww/PuAfCxca6Xo4tE9YHW/yqr1QJuxD1A9KmShY7y8x8O/Tk5K9A20AV+AU5QKhvep2pBENiMSFRNafk52HrzHNbHRiPqTrxmu7G+IZ5p5oXn3QPQxekpGHChI6Jap7VwcDs1S9NHkJ72cG5yS0tjBLQrmaDIwbFhTyN8K/sBknLSYainj/Z2zaUuh0jn5RcVYu+/Cx3tS7yCwn8XOtKTydDZ8SkMdvfHM828YW4o3WynRI2RVsJBQUExfvzfERQWlPxiGxsbwMfPEW0DneHWom4WOtIFpaMGAU1cYWqo+7dcEklt+eXj+CZyu+a5l7UjBv+70JED1yQhkoxWwoGRUcmqh7m5hWgX6AzPNvYwrOOFjnRB6XoKnBWRqHIGuPnht4vHMLCFHwa7B8DDykHqkogIWrysMOxFv0bdHCQIApsRiarIyUyJiKGfNOpzB5Eu0tp9g439l/t6xl3cycuCXN8AbZs0lboconqjsZ87iHRR/Z5UQIeUjhoE2jWDsYGhxNUQERFVH8OBlvAWRiIiaigazuxDElILahzXrKfAcNBQzQ9tDXkNpuZVqXKBq1osiIh0Xk3PG4A05w6OHGjB5bRUpKlyYWpgBL8mLlKXQ0REVCMMB1pQekmho70bDDl7GxER1XMMB1pQOr9BsCPnNyAiovqP4aCGitTFiPi334DNiERE1BAwHNTQ+fvJyCpUQWlkDC9rJ6nLISIiqjGGgxoq7Tfo5NAC+nr8dhIRUf3Hv2Y1VDr5UTAvKRARUQPBcFADBcVFOHnnJgDOb0BERA0Hw0ENxNxLRF5RIWyMzdDayk7qcoiIiLSC4aAGNJcUHNyhJ+O3koiIGgb+RauBo5p+A85vQNq3cOFC+Pr6QqFQQKFQICgoCDt27JC6LCLSYdOmTYNMJhM9HBwcqnwcrq1QTXlFhTh1Jx4A5zeg2uHi4oKZM2fiqaeeAgAsX74cAwcORHR0NLy8vCSujoh0lZeXF/bs2aN5rq9f9Zl7GQ6q6fSdeBSoi2FvqoCbwlbqcqgBGjBggOj5t99+i4ULFyIiIoLhgIgeycDAoFqjBaJjaKmWRqfsEs0ymUziaqg+yczMFD2Xy+WQy+WPfU1xcTHWrVuHnJwcBAUF1WZ5RKSjKnvuuHbtGpycnCCXy9GxY0fMmDEDLVpU7fI3ew6q6RinTKZqcnV1hVKp1DzCw8Mfue+5c+dgbm4OuVyOt956Cxs3bkSbNm3qsFoi0hWVOXd07NgRK1aswK5du7B48WKkpqYiODgY9+/fr9J7ceSgGrILVYi5mwAACHZgMyJVTUJCAhQKheb540YNWrdujZiYGKSnp2P9+vUYNWoUDh48yIBA1AhV5tzRp08fzX/7+PggKCgI7u7uWL58OSZOnFjp92I4qIaTt2+iSFCjqbk1XC2spS6H6pnSuw8qw8jISNOQGBgYiMjISMydOxe//PJLbZZIRDqoKueOUmZmZvDx8cG1a9eq9DpeVqiGY7yFkSQiCAJUKpXUZRBRPaFSqXDp0iU4OjpW6XUcOagGrqdAdWHKlCno06cPXF1dkZWVhTVr1uDAgQPYuXOn1KURkY6aNGkSBgwYgKZNm+LOnTuYPn06MjMzMWrUqCodh+GgitJVuTj/IBkAwwHVrtu3b+OVV15BSkoKlEolfH19sXPnToSFhUldGhHpqMTERLz44ou4d+8emjRpgk6dOiEiIgLNmjWr0nEYDqroROoNqAUB7somcDCt2rUfoqpYsmSJ1CUQUT2zZs0arRyHPQdVVHZ+AyIiooaI4aCKSuc34CUFIiJqqBgOquB+fjYup6UC4PwGRETUcDEcVMHxlJJRA08rB1gbm0lcDRERUe1gOKiCo7yFkYiIGgGGgypgMyIRETUGDAeVlJKTgbjMe9CTydDR3k3qcoiIiGoNw0Elld6l4GPjDKXcROJqiIiIag/DQSUdS7kOAAh24CUFIiJq2BgOKunYv3cqhDgxHBARUcPGcFAJt7IeICE7DQYyPbS3q9r81ERERPUNw0EllK7CGNDEFWaGcomrISIiql0MB5XA+Q2IiKgxYTh4AkEQNCMHDAdERNQYMBw8QVzmPdzOy4Jc3wDtmjSVuhwiIqJax3DwBKWXFNo1aQpjA0OJqyEiIqp9DAdPcIxTJhMRUSPDcPAYakGtmd+A/QZERNRYMBw8xuW023igyoGpgRH8bF2kLoeIiKhOMBw8RuklhQ72zWGkbyBxNURERHWD4eAxeAsjERE1RgwHjyAIAk7fTQDAZkQiImpcOFb+CDKZDMeHfoyoO/HwtnaSuhwiIqI6w3DwGCYGRuji1FLqMoiIiOoUwwFRJY1KfwHmRrJqvz67QMCPWqyHiHRfTc8bgDTnDvYcEBERkQjDAREREYkwHBAREZEIwwERERGJMBwQERGRCMMBkY4KDw9H+/btYWFhATs7Ozz33HO4cuWK1GURUSPAcECkow4ePIhx48YhIiICu3fvRlFREXr37o2cnBypSyOiBo7zHBDpqJ07d4qeL126FHZ2djh16hS6du0qUVVE1BgwHBDVsczMTNFzuVwOuVz+xNdlZGQAAKytrWulLiKiUrysQFTHXF1doVQqNY/w8PAnvkYQBEycOBGdO3eGt7d3HVRJRI0ZRw6I6lhCQgIUCoXmeWVGDd59912cPXsWR44cqc3SiIgAMBwQ1TmFQiEKB0/y3nvvYcuWLTh06BBcXFxqsTIiohIMB0Q6ShAEvPfee9i4cSMOHDgANzc3qUsiokaC4YBIR40bNw6rVq3C5s2bYWFhgdTUVACAUqmEiYmJxNURUUPGhkQiHbVw4UJkZGSge/fucHR01DzWrl0rdWlE1MBx5IBIRwmCIHUJRNRIceSAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiKiBCg8Ph0wmw4QJE6r0OoYDIiKiBigyMhKLFi2Cr69vlV/LcEBERNTAZGdn46WXXsLixYthZWVV5dczHBAREdUDmZmZoodKpXrkvuPGjUO/fv3Qq1evar0XwwEREVE94OrqCqVSqXmEh4dXuN+aNWtw+vTpR/57ZRhU+5VERERUZxISEqBQKDTP5XJ5hfuMHz8e//zzD4yNjav9XgwHRERE9YBCoRCFg4qcOnUKd+7cQbt27TTbiouLcejQIcyfPx8qlQr6+vpPfC+GAyIiogYiNDQU586dE20bM2YMPDw88Mknn1QqGAAMB0RERA2GhYUFvL29RdvMzMxgY2NTbvvjsCGRiIiIRDhyQERE1IAdOHCgyq/hyAERERGJMBwQERGRCMMBERERiTAcEBERkQjDAREREYkwHBAREZEIwwERERGJMBwQERGRCCdBIqqk/p3HQ8+k/CpolaXOUwGr52ivICLSeTU9bwDSnDs4ckBEREQiDAdEOurQoUMYMGAAnJycIJPJsGnTJqlLIqJGguGASEfl5OTAz88P8+fPl7oUImpk2HNAVMcyMzNFz+VyOeTy8tck+/Tpgz59+tRVWUREGhw5IKpjrq6uUCqVmkd4eLjUJRERiXDkgKiOJSQkQKFQaJ5XNGpARCQlhgOiOqZQKEThgIhI1/CyAhEREYkwHBAREZEILysQ6ajs7Gxcv35d8/zGjRuIiYmBtbU1mjZtKmFlRNTQMRwQ6aioqCj06NFD83zixIkAgFGjRmHZsmUSVUVEjQHDAZGO6t69OwRBkLoMImqE2HNAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBApOMWLFgANzc3GBsbo127djh8+LDUJRGRjlq4cCF8fX2hUCigUCgQFBSEHTt2VPk4DAdEOmzt2rWYMGECPvvsM0RHR6NLly7o06cPbt26JXVpRKSDXFxcMHPmTERFRSEqKgo9e/bEwIEDceHChSodh+GASIf98MMPeO211/D666/D09MTc+bMgaurKxYuXCh1aURUxzIzM0UPlUpVbp8BAwagb9++aNWqFVq1aoVvv/0W5ubmiIiIqNJ7GWiraKKGTshTQV3D1wMlv+BlyeVyyOXycvsXFBTg1KlT+PTTT0Xbe/fujWPHjtWgEiKqKyef/RAKhaJGx8jMzITruJIPBmVNnToV06ZNe+TriouLsW7dOuTk5CAoKKhK78lwQPQERkZGcHBwQOqkmn9aNzc3r/Qv+L1791BcXAx7e3vRdnt7e6Smpta4FiKqPaXnjf/+vleXg4MDzpw5A2NjY822ij5UAMC5c+cQFBSE/Px8mJubY+PGjWjTpk2V3o/hgOgJjI2NcePGDRQUFNT4WIIgQCaTibY96he81H/3r+gYRKRbtHneAErCRtlg8DitW7dGTEwM0tPTsX79eowaNQoHDx6sUkBgOCCqBGNj40r/YmqLra0t9PX1y40S3Llzp9xoAhHpHinOG0BJkHjqqacAAIGBgYiMjMTcuXPxyy+/VPoYbEgk0lFGRkZo164ddu/eLdq+e/duBAcHS1QVEdU3giBU2Lz4OBw5INJhEydOxCuvvILAwEAEBQVh0aJFuHXrFt566y2pSyMiHTRlyhT06dMHrq6uyMrKwpo1a3DgwAHs3LmzSsdhOCDSYcOHD8f9+/fx9ddfIyUlBd7e3ti+fTuaNWsmdWlEpINu376NV155BSkpKVAqlfD19cXOnTsRFhZWpePIBEEQaqlGIiIiqofYc0BEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCL/D9Eulv6nxTnyAAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -1387,14 +1419,14 @@ "angles_gdf len 2\n", "connectivity: 1\n", "Counter values: dict_values([1, 1])\n", - "angles: [88.08366041995446]\n", + "angles: [np.float64(88.08366041995446)]\n", "(9, 3) added\n", "Checking edge: (2, 3)\n" ] }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGTCAYAAABwJ4sYAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAAUtZJREFUeJzt3XdUFOffBfC7tKUuVToKomIBK4iADRWNLZrEkphEMeWniTWkaoqamKC+KZoYiSbEEmvspliwgCWCgNi7onQUpXfYef8wbFzpLDAL3M85e052dnbmy2KGu888RSIIggAiIiIiFWiIXQARERE1fQwUREREpDIGCiIiIlIZAwURERGpjIGCiIiIVMZAQURERCpjoCAiIiKVMVAQERGRyhgoiIiISGUMFERERKQyBgoiNZadnY25c+eiTZs20NPTg7e3NyIjI8Uui4jUVFBQELp27QqZTAaZTAYvLy/s37+/yveEhYWhV69e0NXVRdu2bfHTTz/V6dwMFERq7I033kBISAh+++03XLx4EUOHDsWQIUOQmJgodmlEpIbs7e2xZMkSREVFISoqCoMGDcKYMWNw+fLlCvePjY3FiBEj0K9fP8TExGD+/PmYPXs2du7cWetzS7g4GJF6ys/Ph5GREfbu3YuRI0cqtnfv3h2jRo3C4sWLRayOiJoKMzMz/N///R9ef/31cq99+OGH2LdvH65evarYNn36dJw/fx6nT5+u1Xm0VK6UqAUoKChAUVGRyscRBAESiURpm1QqhVQqLbdvSUkJSktLoaurq7RdT08PJ0+eVLkWImpY9XXdAGp37ShTWlqK7du3Izc3F15eXhXuc/r0aQwdOlRp27BhwxAcHIzi4mJoa2vXuEYGCqJqFBQUwMzMDPn5+Sofy9DQEDk5OUrbFixYgIULF5bb18jICF5eXvjiiy/QqVMnWFlZYcuWLYiIiED79u1VroWIGk59XjeA2l07Ll68CC8vLxQUFMDQ0BC7d+9G586dKzxuSkoKrKyslLZZWVmhpKQEaWlpsLGxqXGNDBRE1SgqKkJ+fj4mTZoEHR0dlY6zefNmxMfHQyaTKbZX9Q3jt99+w2uvvQY7OztoamqiZ8+emDRpEs6ePVvnOoio4dXXdaPsWLW5dri4uODcuXPIyMjAzp07MWXKFISFhVUaKp5u+SjrCfH09uowUBDVkI6OjsoXBgCK3tc14ezsjLCwMOTm5iIrKws2NjaYOHEinJycVK6DiBpefV03gJpfO3R0dNCuXTsAgLu7OyIjI7FixQqsXr263L7W1tZISUlR2nb//n1oaWnB3Ny8VvVxlAdRE2BgYAAbGxukp6fj4MGDGDNmjNglEVETIQgCCgsLK3zNy8sLISEhStsOHToEd3f3WvWfANhCQaTWDh48CEEQ4OLiglu3buH999+Hi4sLpk6dKnZpRKSG5s+fj+HDh8PBwQHZ2dnYunUrQkNDceDAAQDAvHnzkJiYiA0bNgB4PKJj5cqVCAgIwJtvvonTp08jODgYW7ZsqfW5GSiI1FhmZibmzZuHhIQEmJmZ4YUXXsCXX35Z628ORNQypKam4tVXX0VycjKMjY3RtWtXHDhwAH5+fgCA5ORkxMXFKfZ3cnLC33//jXfeeQc//vgjbG1t8f333+OFF16o9bkZKIjU2IQJEzBhwgSxyyCiJiI4OLjK19etW1du24ABA+qlozf7UBAREZHKGCiIiIhIZQwUREREpDIGCiIiIlIZAwURERGpjIGCiIiIVMZAQURERCpjoCAiIiKVMVAQERGRyhgoiIiISGUMFERERKQyBgoiIiJSGQMFERERqYyBgoiIiFTGQEFEREQqY6AgIiIilTFQEBERkcoYKIiIiEhlDBRERESkMgYKIiIiUhkDBREREamMgYKIiIhUxkBBREREKmOgICIiIpUxUBAREZHKGCiIiIhIZQwUREREpDIGCiIiIlIZAwURERGpjIGCiIiIVMZAQaSmSkpK8Mknn8DJyQl6enpo27YtPv/8c8jlcrFLIyIqR0vsAoioYkuXLsVPP/2E9evXo0uXLoiKisLUqVNhbGyMOXPmiF0eEZESBgoiNXX69GmMGTMGI0eOBAA4Ojpiy5YtiIqKErkyIqLyeMuDqJFlZWUpPQoLCyvcr2/fvjhy5Ahu3LgBADh//jxOnjyJESNGNGa5REQ1whYKokbm4OCg9HzBggVYuHBhuf0+/PBDZGZmomPHjtDU1ERpaSm+/PJLvPTSS41UKRFRzTFQEDWy+Ph4yGQyxXOpVFrhftu2bcPGjRuxefNmdOnSBefOncPcuXNha2uLKVOmNFa5REQ1wkBB1MhkMplSoKjM+++/j48++ggvvvgiAMDNzQ337t1DYGAgAwURqR32oSBSU3l5edDQUP5fVFNTk8NGiUgtsYWCSE2NHj0aX375JVq3bo0uXbogJiYG3377LV577TWxSyMiKoeBgqiG+hqHQF9a90a9vEI51tVi/x9++AGffvop3n77bdy/fx+2traYNm0aPvvsszrXQESNS9XrBlD7a4dYGCiI1JSRkRGWL1+O5cuXi10KEVG12IeCiIiIVMZAQURERCqr10Dx/fffQyKRwNXVtdJ9JBKJ0iQ+oaGhkEgkCA0NVfn8f//9d4UTBNWHdevWQSKRNJlpjzdv3qyWTeX1+fsus3z5cjz//PNwcnKCRCLBwIED6+3YRERUM/UaKH799VcAwOXLlxEREVGfh66Rv//+G4sWLWr086ojdQ0UDeGnn37CvXv3MGjQILRq1UrscoiIWqR6CxRRUVE4f/68YiGj4ODg+jp0gxAEAfn5+WKXQfXgypUriI6ORnBwMCwtLcUuh4ioRaq3QFEWIJYsWQJvb29s3boVeXl59XV45OXl4b333oOTkxN0dXVhZmYGd3d3bNmyBQDg7++PH3/8EcDj2yplj7t37yq2zZw5Ez/99BM6deoEqVSK9evXAwBOnjyJwYMHw8jICPr6+vD29sZff/1VbU3Jycno1asX2rdvj5s3bwJ4vPBTWZ06Ojqws7PD3LlzkZubq/Te7du3w9PTE8bGxtDX10fbtm1rNL/Ajz/+iP79+8PS0hIGBgZwc3PDsmXLUFxcrNhn4MCB+Ouvv3Dv3j2lz6Iqjo6OGDVqFA4cOICePXtCT08PHTt2VLQ6PenSpUsYM2YMTE1Noauri+7duys+yyddu3YNzzzzDPT19WFhYYHp06cjOzu7wvMfPnwYgwcPhkwmg76+Pnx8fHDkyJFqPw8A5SZ/IiKixlcvw0bz8/OxZcsWeHh4wNXVFa+99hreeOMNbN++vd6mCA4ICMBvv/2GxYsXo0ePHsjNzcWlS5fw8OFDAMCnn36K3Nxc7NixA6dPn1a8z8bGRvHfe/bswYkTJ/DZZ5/B2toalpaWCAsLg5+fH7p27Yrg4GBIpVKsWrUKo0ePxpYtWzBx4sQK67l06RJGjBgBe3t7nD59GhYWFsjLy8OAAQOQkJCA+fPno2vXrrh8+TI+++wzXLx4EYcPH4ZEIsHp06cxceJETJw4EQsXLoSuri7u3buHo0ePVvs53L59G5MmTVIElvPnz+PLL7/EtWvXFH/8V61ahf/973+4ffs2du/eXePP+Pz583j33Xfx0UcfwcrKCr/88gtef/11tGvXDv379wcAXL9+Hd7e3rC0tMT3338Pc3NzbNy4Ef7+/khNTcUHH3wAAEhNTcWAAQOgra2NVatWwcrKCps2bcLMmTPLnXfjxo2YPHkyxowZg/Xr10NbWxurV6/GsGHDcPDgQQwePLjGPwMREYmjXgLFjh07kJmZiddffx0AMHHiRMydOxfBwcH1FihOnTqFoUOH4p133lFsK7u9AgDOzs6wsrICAPTp06fCY+Tk5ODixYswNTVVbPPy8oKpqSlCQ0NhaGgIABg1ahS6d++O9957DxMmTCj37f7w4cN44YUXMHToUPz222/Q1dUF8LhT6oULFxAREQF3d3cAwODBg2FnZ4dx48bhwIEDGD58OP755x8IgoCffvoJxsbGiuP6+/tX+zl8++23iv+Wy+Xo168fzM3NMXXqVHzzzTcwNTVF586dYWJiAqlUWulnUZG0tDScOnUKrVu3BgD0798fR44cwebNmxWBYuHChSgqKsKxY8cUq2aOGDECGRkZWLRoEaZNmwZjY2N89913ePDgAWJiYtCtWzcAwPDhwzF06FDExcUpzpmXl4c5c+Zg1KhRSuFnxIgR6NmzJ+bPny9KfxwiIqqdemkrDg4Ohp6enmIRI0NDQ4wfPx4nTpxQ3ApQVe/evbF//3589NFHCA0NrVP/h0GDBimFidzcXERERGDcuHGKMAE8Xi/h1VdfRUJCAq5fv650jPXr12PEiBF444038PvvvyvCBAD8+eefcHV1Rffu3VFSUqJ4DBs2TGlkg4eHBwBgwoQJ+P3335GYmFjjnyEmJgbPPvsszM3NoampCW1tbUyePBmlpaW4ceNGrT+TJ3Xv3l0RJgBAV1cXHTp0wL179xTbjh49isGDB5dbgtvf3x95eXmK1qFjx46hS5cuijBRZtKkSUrP//nnHzx69AhTpkxR+szkcjmeeeYZREZGlrtdRERE6kflQHHr1i0cP34cI0eOhCAIyMjIQEZGBsaNGwcAFd6Dr4vvv/8eH374Ifbs2QNfX1+YmZlh7NixtQosT97+AID09HQIglBuOwDY2toCgOKWSpmtW7dCT08Pb7zxRrmWi9TUVFy4cAHa2tpKDyMjIwiCgLS0NACPv/nv2bMHJSUlmDx5Muzt7eHq6qroD1KZuLg49OvXD4mJiVixYgVOnDiByMhIRd8RVTuZmpubl9smlUqVjvvw4cMafV4PHz6EtbV1uf2e3paamgoAGDduXLnPbenSpRAEAY8ePar7D0VERI1C5Vsev/76KwRBwI4dO7Bjx45yr69fvx6LFy+GpqamSucxMDDAokWLsGjRIqSmpipaK0aPHo1r167V6BhPBwBTU1NoaGggOTm53L5JSUkAAAsLC6XtmzZtwqeffooBAwbg0KFD6N69u+I1CwsL6OnpVRqinjzWmDFjMGbMGBQWFiI8PByBgYGYNGkSHB0d4eXlVeH79+zZg9zcXOzatQtt2rRRbD937lyVP3d9Mjc3r9HnZW5ujpSUlHL7Pb2tbP8ffvih0tszZbeyiIhIfakUKEpLS7F+/Xo4Ozvjl19+Kff6n3/+iW+++Qb79+/HqFGjVDmVEisrK/j7++P8+fNYvnw58vLyoK+vD6lUCuDxN3U9Pb1qj2NgYABPT0/s2rULX3/9teI9crkcGzduhL29PTp06KD0HjMzMxw+fBijRo2Cr68v9u/fr/hDOGrUKHz11VcwNzeHk5NTjX4WqVSKAQMGwMTEBAcPHkRMTEylgaIsEJX9nMDj4a8///xzhcdtiGGxgwcPxu7du5GUlKRolQCADRs2QF9fX/FZ+Pr6YtmyZTh//rzSbY/NmzcrHc/HxwcmJia4cuVKhR02iYioaVApUOzfvx9JSUlYunRphbMTurq6YuXKlQgODlY5UHh6emLUqFHo2rUrTE1NcfXqVfz222/w8vKCvr4+AMDNzQ0AsHTpUgwfPhyampro2rUrdHR0Kj1uYGAg/Pz84Ovri/feew86OjpYtWoVLl26hC1btlQ43NLIyAgHDhzA888/Dz8/P+zbtw++vr6YO3cudu7cif79++Odd95B165dIZfLERcXh0OHDuHdd9+Fp6cnPvvsMyQkJGDw4MGwt7dHRkYGVqxYAW1tbQwYMKDSWv38/KCjo4OXXnoJH3zwAQoKChAUFIT09PRy+7q5uWHXrl0ICgpCr169oKGhoegoqooFCxbgzz//hK+vLz777DOYmZlh06ZN+Ouvv7Bs2TJFJ9O5c+fi119/xciRI7F48WLFKI+nW5MMDQ3xww8/YMqUKXj06BHGjRsHS0tLPHjwAOfPn8eDBw8QFBRUZU1RUVGK4cFZWVmKFjPgcX+VJ1tziIioYagUKIKDg6Gjo4OpU6dW+LqFhQWee+457NixA6mpqSo1XQ8aNAj79u3Dd999h7y8PNjZ2WHy5Mn4+OOPFftMmjQJp06dwqpVq/D5559DEATExsbC0dGx0uMOGDAAR48exYIFC+Dv7w+5XI5u3bph3759VYYgPT097N27F5MmTcKIESOwc+dOjBgxAidOnMCSJUuwZs0axMbGQk9PD61bt8aQIUMUdXh6eiIqKgoffvghHjx4ABMTE7i7u+Po0aPo0qVLpefs2LEjdu7ciU8++QTPP/88zM3NMWnSJAQEBGD48OFK+86ZMweXL1/G/PnzkZmZCUEQIAhCzT7sKri4uOCff/7B/PnzMWPGDOTn56NTp05Yu3at0igVa2trhIWFYc6cOXjrrbegr6+P5557DitXrsSYMWOUjvnKK6+gdevWWLZsGaZNm4bs7GxYWlqie/fuNRr5snLlynLzYIwfPx4AytVFREQNQyLUx18ZomYsKysLxsbG+GWOHfSlde/HnFcoxxsrEpGZmQmZTFaPFRKRuqmv6wbQdK4dnGKQiIiIVMZAQURERCpjoCAiIiKVMVAQkcoiIiLw3HPPoXXr1pBKpbCysoKXlxfeffddpf1WrVqFdevWNUgN/v7+SjPeiunEiROQSqWKWWZLS0vx7bff4plnnoG9vT309fXRqVMnfPTRR8jIyKjzeQ4fPgw/Pz/Y2tpCKpXC0tISgwYNwt9//620X3FxMZydnbF8+XIVfqqKffXVV9izZ0+9H1dVCxcurHZRxNrIzs7GBx98gKFDh6JVq1aQSCRYuHBhvR2/OWCgICKV/PXXX/D29kZWVhaWLVuGQ4cOYcWKFfDx8cG2bduU9m3IQKEuBEHA3Llz8eabbyqGLOfn52PhwoVo06YNli9fjr///htvvvkm1qxZAx8fnzrPGfPw4UN06dIF3333HQ4dOoTVq1dDW1sbI0eOxMaNGxX7aWtr47PPPsPnn39ebvZfValroKhvDx8+xJo1a1BYWIixY8eKXY5aqpfFwYio5Vq2bBmcnJxw8OBBaGn9d0l58cUXsWzZsjoft7i4GBKJROmYTcGBAwdw9uxZpUnc9PT0EBsbqzS9/cCBA9G6dWuMHz8eO3fuxCuvvFLrc5WtWvykUaNGwcnJCWvWrFE65ksvvYSAgACsXr0a8+fPr8NP1rK1adMG6enpkEgkSEtLq3Ayx5aOLRREpJKHDx/CwsKiwj/8Ghr/XWIcHR1x+fJlhIWFQSKRQCKRKOZmCQ0NhUQiwW+//YZ3330XdnZ2kEqluHXrFoDHU/x369YNurq6MDMzw3PPPYerV69WW9upU6dgYWGBUaNGKRaZu3nzJiZNmgRLS0tIpVJ06tRJsR5OGblcjsWLF8PFxQV6enowMTFB165dsWLFimrPGRQUBA8PD7i4uCi2aWpqVrhWTu/evQEA8fHx1R63prS1tWFiYlLu96Gjo4OJEydizZo11c5JU1BQgHfffRfdu3eHsbExzMzM4OXlhb179yrtJ5FIkJubi/Xr1yt+pxVNcljm7t27kEgk+Prrr/Htt9/CyckJhoaG8PLyQnh4eLn99+3bp5i80MjICH5+fooFCJ/0119/oXv37pBKpXBycsLXX39d4fkFQcCqVavQvXt36OnpwdTUFOPGjcOdO3eq/DzKftb6vIXSHDFQEJFKvLy8EBERgdmzZyMiIgLFxcUV7rd79260bdsWPXr0wOnTp3H69GmlJesBYN68eYiLi8NPP/2EP/74A5aWlggMDMTrr7+OLl26YNeuXVixYgUuXLgALy+vKhcH/P333zF48GBMmDABe/fuhYGBAa5cuQIPDw9cunQJ33zzDf7880+MHDkSs2fPxqJFixTvXbZsGRYuXIiXXnoJf/31F7Zt24bXX3+92v4ORUVFOHz4MHx9fWv02R09ehQAqpzQribkcjlKSkqQlJSEBQsW4MaNG+X6rwCPW0Xu3buHS5cuVXm8wsJCPHr0CO+99x727NmDLVu2oG/fvnj++eexYcMGxX6nT5+Gnp4eRowYofidrlq1qtp6f/zxR4SEhGD58uXYtGkTcnNzMWLECGRmZir22bx5M8aMGQOZTIYtW7YgODgY6enpGDhwIE6ePKnY78iRIxgzZgyMjIywdetW/N///R9+//13rF27ttx5p02bhrlz52LIkCHYs2cPVq1ahcuXL8Pb21uxUGFTFxgYCA8PDxgZGcHS0hJjx44tt2p2RTZt2oRu3bpBX18fNjY2mDp1aq1vj3FiK6JqcGKrqj18+BBjx45VXOS1tbXh4eGB0aNHY+bMmUodJV1dXWFhYYHQ0FClY4SGhsLX1xf9+/dHWFiYYntGRgZsbW3h6+uLv/76S7E9Pj4e7du3xwsvvIBNmzYBeNwpc8eOHcjJycHSpUvx8ccf46uvvsIHH3ygeN8zzzyDy5cv4/Lly0q/g1mzZuGXX35BUlISTE1NMXr0aCQkJCAmJqZWn8WZM2fg6emJrVu3lrsV8bTExET06tULDg4OiIiIUGrNqa1nnnkGBw8eBADIZDKsW7cOzz33XLn9bt26hfbt2yMoKAjTp0+v8fFLS0shCAKmT5+Os2fP4uzZs4rXDA0NMW7cuBr1jbl79y6cnJzg5uaGmJgYxaKRkZGR6N27N7Zs2YIXX3wRcrkcDg4OMDc3x7lz5xSfTU5ODpydndGuXTucOnUKANCnTx/Ex8fj9u3b0NXVBfC4A6WjoyMePXqkaI0JDw+Hl5cXvvnmGwQEBChqSkhIQIcOHTBr1iwsXbq0Rp9HWloaWrVqhQULFlTaMVOsia2eeeYZvPjii/Dw8EBJSQk+/vhjXLx4EVeuXIGBgUGF7zl58iQGDBiA7777DqNHj0ZiYiKmT5+O9u3blwv9VWELBRGpxNzcHCdOnEBkZCSWLFmCMWPG4MaNG5g3bx7c3NyQlpZW42O98MILSs9Pnz6N/Pz8ctOnOzg4YNCgQThy5IjSdkEQMG3aNCxYsACbN29WChMFBQU4cuQInnvuOejr66OkpETxGDFiBAoKChTN7r1798b58+fx9ttv4+DBg8jKyqpR/WWr7lpaWla536NHjzBixAgIgoBt27apFCaAx6v1njlzBnv37sWwYcMwceJEbNmypdx+ZXUlJiZWe8zt27fDx8cHhoaG0NLSgra2NoKDg2t0q6k6I0eOVFqBumvXrgCgGBVz/fp1JCUl4dVXX1X6bAwNDfHCCy8gPDwceXl5yM3NRWRkJJ5//nlFmAAer7c0evRopXP++eefkEgkeOWVV5R+99bW1ujWrVu5kNtUHThwAP7+/ujSpQu6deuGtWvXIi4uDtHR0ZW+Jzw8HI6Ojpg9ezacnJzQt29fTJs2DVFRUbU6NwMFEdULd3d3fPjhh9i+fTuSkpLwzjvv4O7du7XqmGljY6P0vKzJ9entAGBra1uuSbaoqAjbtm1Dly5dyq1v8/DhQ5SUlOCHH36Atra20mPEiBEAoAg/8+bNw9dff43w8HAMHz4c5ubmGDx4cLUX2LLRGk/+cXtaeno6/Pz8kJiYiJCQELRt27bKY9ZE+/bt4eHhgWeffVZxq2fGjBmQy+VK+5XVVd2okl27dmHChAmws7PDxo0bcfr0aURGRuK1115DQUGByvU+3Z/kyZWigep/73K5HOnp6UhPT4dcLoe1tXW5/Z7elpqaCkEQYGVlVe73Hx4eXqvgK5asrCylR2FhYbXvKbuNZGZmVuk+3t7eSEhIwN9//w1BEJCamoodO3Zg5MiRtaqvaXWfJqImQVtbGwsWLMB3331X7f36Jz3d6a3sD09ycnK5fZOSkmBhYaG0TSqV4tixYxg2bBiGDBmCAwcOwNTUFABgamoKTU1NvPrqq5gxY0aF53dycgIAaGlpISAgAAEBAcjIyMDhw4cxf/58DBs2DPHx8YoVjp9WVs+jR48qfD09PR1DhgxBbGwsjhw5ovhmXt969+6NAwcO4MGDB0qLMpbV9fTn9rSNGzfCyckJ27ZtU/qd1OQPWH2o7veuoaEBU1NTCIIAiUSClJSUcvs9vc3CwgISiUQxR8jTKtqmbhwcHJSeV3XLBXjcYhcQEIC+ffvC1dW10v28vb2xadMmTJw4EQUFBSgpKcGzzz6LH374oVb1sYWCiFRS0UUfgKJp3NbWVrFNKpXWas4FLy8v6OnpKc2pADy+73306FEMHjy43Ht69OiBsLAwJCQkYODAgbh//z4AQF9fH76+voiJiUHXrl3h7u5e7lHRSAwTExOMGzcOM2bMwKNHj3D37t1K6+3UqRMA4Pbt2+VeKwsTd+7cwaFDh9CjR48afw61IQgCwsLCYGJiUu7nKRvN0Llz5yqPIZFIoKOjoxQmUlJSyo3yAGr/O60JFxcX2NnZYfPmzUojUnJzc7Fz507FyA8DAwP07t0bu3btUmo5yc7Oxh9//KF0zFGjRkEQBCQmJlb4u3dzc6vXn6EhxMfHIzMzU/GYN29elfvPnDkTFy5cqPD215OuXLmC2bNn47PPPkN0dDQOHDiA2NjYWvWzAdhCQUQqGjZsGOzt7TF69Gh07NgRcrkc586dwzfffANDQ0PMmTNHsa+bmxu2bt2Kbdu2oW3bttDV1a3yQm5iYoJPP/0U8+fPx+TJk/HSSy/h4cOHWLRoEXR1dbFgwYIK39epUyecOHECQ4YMQf/+/XH48GHY29tjxYoV6Nu3L/r164e33noLjo6OyM7Oxq1bt/DHH38oRl2MHj0arq6ucHd3R6tWrXDv3j0sX74cbdq0Qfv27Sut197eHm3btkV4eDhmz56t2J6fn49hw4YhJiYGy5cvR0lJidIwyVatWsHZ2VnxfODAgQgLC6t2eOeYMWPQrVs3dO/eHebm5khKSsK6desQFhaGH3/8sdzQ0fDwcGhqaqJ///5VHnfUqFHYtWsX3n77bYwbNw7x8fH44osvYGNjU25kjZubG0JDQ/HHH3/AxsYGRkZGSkNm60JDQwPLli3Dyy+/jFGjRmHatGkoLCzE//3f/yEjIwNLlixR7PvFF1/gmWeegZ+fH959912UlpZi6dKlMDAwUGop8vHxwf/+9z9MnToVUVFR6N+/PwwMDJCcnIyTJ0/Czc0Nb731VpV17d+/H7m5ucjOzgbw+A/xjh07AAAjRoyotOWqvshkshp36J41axb27duH48ePw97evsp9AwMD4ePjg/fffx/A4z4tBgYG6NevHxYvXlzhraeKMFAQkUo++eQT7N27F9999x2Sk5NRWFgIGxsbDBkyBPPmzVN8aweARYsWITk5GW+++Says7PRpk2bKr/xA4/7M1haWuL777/Htm3boKenh4EDB+Krr76q8o9727ZtFaGiX79+OHLkCDp37oyzZ8/iiy++wCeffIL79+/DxMQE7du3V/SjAABfX1/s3LkTv/zyC7KysmBtbQ0/Pz98+umn0NbWrrLel19+GStXrkRhYaGiGT01NRWRkZEAoBSwykyZMkVplEROTk6F/QKe5uPjgx07dmDlypXIysqCiYkJ3N3dFcNhn7Znzx6MGDECJiYmVR536tSpuH//Pn766Sf8+uuvaNu2LT766CMkJCQoDa8FgBUrVmDGjBl48cUXkZeXhwEDBtRLB8dJkybBwMAAgYGBmDhxIjQ1NdGnTx8cO3YM3t7eiv38/PywZ88efPLJJ5g4cSKsra3x9ttvIz8/v1ytq1evRp8+fbB69WqsWrUKcrkctra28PHxUcwJUpW33npL0XEUeNxxdfv27QCA2NhYxbwqYhIEAbNmzcLu3bsRGhqquI1Xlby8vHLhs6zTbG0GgnLYKFE1xBo26ujoqHTxKvP222+Xm4iJ1EdSUhKcnJywYcOGaoeOViQ7OxtmZmZYvnx5pX096uL27dto3749Dh48CD8/v3o7LlVMrGGjb7/9NjZv3oy9e/cqtRQZGxtDT08PwOOQnpiYqJhTZN26dXjzzTfx/fffY9iwYUhOTsbcuXOhoaGBiIiIGtfJPhREaioyMhLJycmKR0hICABg/PjxIldGVbG1tcXcuXPx5ZdflhtlURPHjx+HnZ0d3nzzzXqta/HixRg8eDDDRDMXFBSEzMxMDBw4EDY2NorHk+vqJCcnIy4uTvHc398f3377LVauXAlXV1eMHz8eLi4u2LVrV63OzVseRGqqVatWSs+XLFkCZ2dnDBgwQKSKqKY++eQT6OvrIzExsVzP/OqMHDmy1sP1qlNSUgJnZ+dqO/FR01eTmw4VTUI2a9YszJo1S6VzM1AQNbKnJ0mSSqXVDlkrKirCxo0bERAQwPUEmgAjI6NKO4yKQUtLC5988onYZVAzx1seRI3MwcEBxsbGikdgYGC179mzZw8yMjLKzRhJRKQu2EJB1Mji4+OVOlbVZEKd4OBgDB8+XGlOByIidcJAQdTIajOWHHi8vsHhw4dr3UGKiKgx8ZYHkZpbu3YtLC0t672jHhFRfWKgIFJjcrkca9euxZQpU8pNPENEpE4YKIjU2OHDhxEXF4fXXntN7FKIiKrErzxEamzo0KG1mvqWiEgsbKEgIiIilTFQEBERkcoYKIiIiEhl7ENBVEP9eibBSL/u015n57EvBFFLo+p1A2g61w62UFCzcy09RewSiIhaHAYKalbWXz0Nvz0r8PPlE2KXQkTUojBQULNxJP4aPo3YBwECCkpKxC6HiKhFYaCgZuHywyS8HboZckHAxPbumNl1oNglERG1KAwU1OQl5WZi8uF1yC0pQl+bdlji/RwkEtU6QRERUe0wUFCTllNcCP/D65Cal4UOJpZY7fsytDU0xS6LiKjFYaCgJqtEXoq3jm3GlUfJaKVniPVD/GEs1RO7LCKiFomBgpokQRDwWcQfOJZ4Hbqa2lg7eAocjMzELouIqMVioKAm6efLJ7HhWjgkkOCHARPRvZWD2CUREbVoDBTU5Oy/dwlfRP4NAPjUYwSGt3EVuSIiImKgoCYl5kE8ZoVtgwABUzr2wZtd+opdEhERgYGCmpD47EeYeng9CkqLMcjeBYs8R3N4KBGRmmCgoCYhszAfk0PWIa0gB13MbLBq4CRocXgoEZHaYKAgtVdUWoL/HduIm5n3Ya0vw7oh/jDUlopdFhERPYGBgtSaIAiYd3o3TiXfhoGWDjb4+cPGwFjssoiI6CkMFKTWfrhwDNtuRkNDIsGqgZPQ2cxW7JKIiKgCDBSktvbcOYdlZw8BABb3GYPBDh1FroiIiCrTbANFUVERTpw4gV9++QWCIIhdDtXSmdS7CDixHQAwrUs/TO7YR+SKiIioKs02UJSWluL3339HZGQkbt++LXY5VAt3MtPw2pENKJKX4pnWXfCxx3CxSyIiomo020Chp6cHDw8PAMCJEydEroZq6lFBLiaHrEVGYR66WzjghwEToSFptv9MiYiajWZ9pe7Xrx8AIDo6Grm5uSJXQ9UpKCnG60c24G72Q9gbmmDtkMnQ09IRuywiIqqBZh0oHB0dYW9vj+LiYkRERIhdDlVBLsjx7qkdiLx/DzIdXWzwm4pWekZil0VERDXUrAOFRCJRtFKcOHGCnTPV2NdnQ7D3znloSTSwxvcVdDCxErskIiKqhWYdKADA09MT2traSEpKwp07d8Quhyqw7WYUvr9wDACw1Od59LVtJ3JFRERUW80+ULBzpno7mXQLH57aBQCY3dUXE9u7i1wRERHVRbMPFMB/nTOjoqLYOVON3MhIxf+ObUSJIMeYtt3wfs+hYpdERER11CIChZOTEztnqpkH+dmYHLIWWUUF6G3liG98xnEp8gokJibilVdegbm5OfT19dG9e3dER0eLXRYRUTktIlBIJBL07dsXADtnqoP8kiL4H16PhJwMOBqZ45dBr0JXS1vsstROeno6fHx8oK2tjf379+PKlSv45ptvYGJiInZpRETlaIldQGPx9PTEzp07FZ0znZ2dxS6pRSqVyzErbBvOpyXAVKqPDX5TYaZrIHZZamnp0qVwcHDA2rVrFdscHR3FK4iIqAotooUCAPT19eHu/rjDHztniuerqP04EHcZOhqaCB48GW2NLcQuqdFlZWUpPQoLCyvcb9++fXB3d8f48eNhaWmJHj164Oeff27kaomIaqbFBApAuXNmXl6eyNW0PBuuhWP15cdh7tt+49HbylHcgkTi4OAAY2NjxSMwMLDC/e7cuYOgoCC0b98eBw8exPTp0zF79mxs2LChkSsmIqpei7nlAQBt27aFra0tkpKSEBERAV9fX7FLajGOxF/DJ+F7AQAf9ByKsW27i1uQiOLj4yGTyRTPpVJphfvJ5XK4u7vjq6++AgD06NEDly9fRlBQECZPntwotRIR1VSLaqGQSCTo378/AHbObExXHiXh7dDNkAsCJrbvhVldW3aQk8lkSo/KAoWNjQ06d+6stK1Tp06Ii4trjDKJiGqlRQUK4L+ZMxMTExEbGyt2Oc1eUm4mJoesQ25JEXxsnBHo9RyHh9aQj48Prl+/rrTtxo0baNOmjUgVERFVrsUFCnbObDw5xYWYengdUvKy0MHEEmt8X4GOZou6y6aSd955B+Hh4fjqq69w69YtbN68GWvWrMGMGTPELo2IqJwWFyiA/zpnRkZGIj8/X+RqmqcSeSneDt2My4+SYaFriPVD/GEs1RO7rCbFw8MDu3fvxpYtW+Dq6oovvvgCy5cvx8svvyx2aURE5bTIr4tPds4MDw9n58x6JggCFkT8gaMJ16GrqY21Q6bAwchM7LKapFGjRmHUqFFil0FEVK0W2ULBZc0b1i9XTmL9tXBIIMEPAyaiRysHsUsiIqIG1iIDBaDcOfPu3btil9Ns7L93CZ+f+RsA8InHcAxv4ypyRURE1BhabKAwMDBAr169ALBzZn2JeRCPWWHbIEDA5I598L8u/cQuiYiIGkmLDRQAO2fWp/jsR5h6eD0KSovha+eCzz1Hc3goEVEL0qIDhbOzM2xsbFBUVIQzZ86IXU6TlVmYjymH1yGtIAedzWwQ5DsJWhqaYpdFRESNqEUHiic7Zx4/fpydM+ugqLQE045two2M+7DSl2HdEH8Yalc88yMRETVfLTpQAECfPn2gra2NhIQEds6sJUEQMO/0HpxMvgV9LR1sGOIPWwNjscsiIiIRtPhAwc6ZdbfyQii23YyChkSCoIGT0MXcVuySiIhIJC1yYqun9evXD+Hh4YiMjMT48eOhp8cZHauz5845LD17EADwheezGOzQUeSKGl5gsR10iuuewYuK5QAS6q8gIlJ7ql43gKZz7WjxLRQAO2fW1pnUuwg4sR0A8L8ufTGlk5fIFRERkdgYKPC4c2bfvn0BcObM6sRmpeH1IxtQJC/FM6274GP3EWKXREREaoCB4l9eXl7Q0tJCfHw87t27J3Y5aim9IBeTQ9YhvTAP3Szs8cOAidDU4D8hIiJioFBg58yqFZaW4PWjvyE2Kw32hiZYO3gK9LR0xC6LiIjUBAPFEzhzZsUEQcC7J3fgTOpdyHR0sX7IVFjqG4ldFhERqREGiie0a9cO1tbWKCwsRGRkpNjlqI2vY0Kw5845aEk0sMb3FbiYWoldEhERVSAwMBAeHh4wMjKCpaUlxo4di+vXr1f7vsLCQnz88cdo06YNpFIpnJ2d8euvv9bq3AwUT3h6WXMCfr8ZhRXnjwIAlng/h7627USuiIiIKhMWFoYZM2YgPDwcISEhKCkpwdChQ5Gbm1vl+yZMmIAjR44gODgY169fx5YtW9CxY+2mA+A8FE/p06cPdu/ejbi4ONy9exeOjo5ilySaU0m38MGpXQCAWV198WIHD5ErIiKiqhw4cEDp+dq1a2FpaYno6Gj079+/0veEhYXhzp07MDMzA4A6/e1jC8VTDA0N0bNnTwAtu5XiRkYq3jy2ESWCHGOcuuH9nn5il0RE1KJlZWUpPQoLC6t9T2ZmJgAogkJF9u3bB3d3dyxbtgx2dnbo0KED3nvvvVr3JWSgqMCTnTMLCgpErqbxPcjPxpSQdcgqKoCHZRt803ccNCT8p0JEJCYHBwcYGxsrHoGBgVXuLwgCAgIC0LdvX7i6ula63507d3Dy5ElcunQJu3fvxvLly7Fjxw7MmDGjVvXxlkcF2rdvDysrK6SmpuLMmTOVNhM1R/klRZh6eAPic9LhaGSO4MGToaulLXZZREQtXnx8PGQymeK5VFr1ys4zZ87EhQsXcPLkySr3k8vlkEgk2LRpE4yNHy/w+O2332LcuHH48ccfa7wcBb92VqClds6UC3LMPr4N59LiYSLVxwa/qTDTNRC7LCIiAiCTyZQeVQWKWbNmYd++fTh27Bjs7e2rPK6NjQ3s7OwUYQIAOnXqBEEQkJBQ8zVEGCgqUTZzZlxcXIuZOfPLqAPYf+8ydDQ0ETzoVbQ1thC7JCIiqgVBEDBz5kzs2rULR48ehZOTU7Xv8fHxQVJSEnJychTbbty4AQ0NjWrDyJMYKCphaGiIHj16AGgZrRS/XQvH6kvHAQDf9B0PT+vq/xESEZF6mTFjBjZu3IjNmzfDyMgIKSkpSElJUepgOW/ePEyePFnxfNKkSTA3N8fUqVNx5coVHD9+HO+//z5ee+21Wq2+zUBRhbK+E2fOnGnWnTOPJlzHx+F7AQDv9/DDc87dxS2IiIjqJCgoCJmZmRg4cCBsbGwUj23btin2SU5ORlxcnOK5oaEhQkJCkJGRAXd3d7z88ssYPXo0vv/++1qdm50yq/Bk58zIyEhFv4rm5MqjJLx1bBPkgoAJ7XphdrdBYpdERER1VJPVstetW1duW8eOHRESEqLSudlCUYXm3jkzOTcTk0PWIbekCD42zlji/RwkEonYZRERURPEQFGNss6Z9+7dU2oiaupyigvhf3gdUvKy0N7YEmt8X4GOJhusiIiobhgoqtEcO2eWyEvxduhmXH6UDAtdQ6z384extOYdb4iIiJ7GQFEDZbc9IiIimnznTEEQsCDiTxxNuA6pphZ+HTIZrY0qn5KViIioJhgoaqBDhw6wtLREYWEhoqKixC5HJb9cOYn1105DAgl+6P8ierZqLXZJRETUDDBQ1EBz6Zx54N5lfH7mbwDAJx7DMcKx8rndSXwLFy6ERCJRelhbW4tdFhFRhRgoasjLywuampq4e/duk+ycee5BPGaGbYUAAa+6eOJ/XZrfENjmqEuXLkhOTlY8Ll68KHZJREQVYqCoISMjI0XnzOoWWlE38dmPMPXIehSUFsPXzgVf9HmWw0ObCC0tLVhbWyserVq1ErskIqIKMVDUQlPsnJlZmI8ph9fhQX4OOplaI8h3ErQ0NMUuq0XLyspSehQWFla6782bN2FrawsnJye8+OKLuHPnTiNWSkRUcwwUteDi4gJLS0sUFBQ0ic6ZxfJSTA/dhBsZ92GlL8N6v6kw1K56uVtqeA4ODjA2NlY8AgMDK9zP09MTGzZswMGDB/Hzzz8jJSUF3t7eePjwYSNXTERUPc5kVAsSiQR9+/bFrl27cOLECfTt21fskiolCAI++mc3TiTdgr6WDtYPmQJbA+Pq30gNLj4+HjKZTPG8siWIhw8frvhvNzc3eHl5wdnZGevXr0dAQECD10lEVBtsoailJztnxsfHi11OpX68GIptN6OgIZEgaOAkuJrbiV0S/Usmkyk9KgsUTzMwMICbmxtu3rzZwBUSEdUeA0UtyWQydO/eHYD6DiHde+c8lkQfBAB87vksBjt0FLkiqg+FhYW4evUqbGxsxC6FiKgcBoo6eLJzZlUd6sQQmXoXASe3AwDe7NIX/p28RK6I6uq9995DWFgYYmNjERERgXHjxiErKwtTpkwRuzQionIYKOpAXTtnxmal4bUjG1BYWoJhrTvjE/cRYpdEKkhISMBLL70EFxcXPP/889DR0UF4eDjatGkjdmlEROWwU2YdaGhoKHXO9PHxEbskpBfkYnLIOqQX5qGbhT1+6P8iNDWYF5uyrVu3il0CEVGN8S9OHZV1zoyNjRW9c2ZhaQneOPobYrPSYG9ogrWDp0BfW0fUmoiIqGVhoKijJztnijlzpiAIePfkDkSk3oWRthTrh0yFpb6RaPUQEVHLxEChgrLOmeHh4SgqKhKlhq9jQrDnzjloSTSwZtArcDG1EqUOIiJq2RgoVODi4gILCwsUFBQgMjKy0c//+80orDh/FACwxPs59LNt3+g1EBERAQwUKtHQ0BBtWfNTSbfwwaldAIBZXX3xYgePRj0/ERHRkxgoVOTt7Q0NDQ3ExsYiISGhUc55M+M+3jy2ESWCHM86dcX7Pf0a5bxERESVYaBQUWPPnPkgPxuTQ9Yiq6gAHpZt8G3f8dCQ8NdIRETi4l+ievDkzJkN2Tkzv6QYrx3ZgPicdLQxMkfw4MnQ1dJusPMRERHVFANFPejYsSMsLCyQn5/fYDNnygU55hzfhpgH8TCR6uM3P3+Y6Ro0yLmIiIhqi4GiHjRG58yvog7g73uXoKOhieBBr6KtcasGOQ8REVFdMFDUEy8vL2hoaODOnTtITEys12NvvBaBny4dBwB803c8PK2d6vX4REREqmKgqCfGxsYN0jnzWMJ1fBy+FwDwXg8/POfcvd6OTUREVF8YKOpRfXfOvPIoCdOPbUKpIMf4dj0xp9sglY9JRETUEBgo6lHHjh1hbm6OvLw8REdHq3SslLwsTAlZj9ySInhbt8VS7+chkUjqqVIiIqL6xeXL61HZsuZ79+7FiRMn4OXlVafj5BYXwj9kHZLzMtHOuBXWDHoFOpr8VYlt/rL/wUhTt87vzy4twDp8Vo8VEZG6U/W6ATSdawdbKOqZj48PNDQ0cPv27Tp1ziyVy/F26BZcepQEc10DbPCbChOpfgNUSkREVH8YKOqZsbExunXrBqD2y5oLgoAFZ/7AkYRrkGpqYe2QKWhtZNYQZRIREdUrBooGUNdlzYOvnMK6q6chgQTf95+Inq1aN1SJRERE9YqBogF06tRJ0Tnz7NmzNXrPwXuXsejMXwCAj92HY6SjW0OWSEREVK8YKBpAWedMADh+/Hi1+59PS8DM41shQMArLp6Y5tqvoUskIiKqVwwUDaRsWfPbt28jKSmp0v0SctLhf3gd8kuKMdCuAxb3eZbDQ4mIqMlhoGggJiYm6Nq1K4DKZ87MKirAlJB1eJCfg06m1ggaOAlaGpqNWSYREVG9YKBoQFV1ziyWl2LasY24npEKK30Z1g/xh5GOamOViYiIxMJA0YA6d+5cYedMQRAw75/dOJF0C/paOlg/ZApsDU3EK5SIiEhFDBQNSENDAz4+PgCUb3v8eDEMW29GQUMiwaqBL8HV3E6sEomIiOoFA0UDK5s589atW0hKSsK+O+exJPoAAGBR79EY4tBJ5AqJiIhUx0DRwJ7snLnz0N945+R2AMAbnX0wtbO3mKURERHVGwaKRlDWOfP8mUgY5qRjWOvO+NRjpMhVEZG6KykpQVpaGmIexKOotETscoiqxCUsG1BOTiHOxyQhOvIRNCRG0JVm4OeoLbCID0Va4hnod/KFfqeB0DQ0F7tUIlITgiDgzp07iIiIQFRUFIzNzPCzXQ70tLTR28oJ3tZt4WPjDDdzO2hq8DshqQ8GinpWXFSKy5dTEROVgOvXHkAuFwAA+rr9cc72LtKL/oRJ8jVkJl9D5tEgQCKB1KEb9DoNhH4nX+i59Iemnkzkn4KIGltqaioiIiIQERGBtLQ0xXa5hgSWrWW4X5KPsMQbCEu8AQCQ6ejC08oJPjbO8LZxRkdTK2hIGDBIPAwU9UAuF3Dn9kOcjUrExfPJKCz8r2nS3sEYZh30sDBpLwyMdDD4rSsouH4ceVePIe/qMRQlXkZh3DkUxp1DxsHlgIYmdB17wWLiMui7cApu+k9gYCDmz5+POXPmYPny5WKXQ/UgOzsbUVFRiIiIQGxsrGK7VCpFjx494OnpiY4dO0IikeB6RipOJd/GP8m3cTrlDrKKChASfxUh8VcBAGZSA/jad8DyfhM42y6JgoFCBclJWYiJTkRMdCIyMwsU201N9dDD3Q49etnBysoI38YcRsGDYgy16QQtQzMY9hoLw15jAQAlmanIu3oM+ddCkXf1GIpTb6Hgzhlo6BqK9FOROoqMjMSaNWsUHXyp6SoqKsL58+cRERGBy5cvQy6XAwAkEgk6d+6MPn36oFu3bpBKpUrv62hqjY6m1ni9sw9K5XJcepSEf5Jv41TybUSkxuJRYS5S87IZJkg0DBS1lJmRj3MxSTgblYjkpCzFdj09bXTtboOevezQxskMGhr//U/9T8ptAIC3tXO542kZW0HW50XI+rwIACh+GIf8a6GQOnRr4J+EmoqcnBy8/PLL+Pnnn7F48WKxy6E6kMvluHHjBiIiInD27FkUFPz3BaR169bo06cP3N3dYWxsXKPjaWpooJuFPbpZ2OMttwEoKi3B+bQECA31AxDVAANFDRQUlODShWTERCfi1s00CP/+X6upKUGnzlbo4W6Hjp0soa1dfh2O/JIinL0fBwDwtikfKJ6mbd4a2j6T67V+Ui9ZWVlKz6VSablvo0+aMWMGRo4ciSFDhjBQNDGJiYkIDw9HZGQk0tPTFdvNzc3Ru3dveHp6wsbGRuXz6GhqwcPKUeXjEKmCgaISpaVy3Lj+ADHRibh8MQXFxXLFa45Opujpbo+u3Wygb6BT5XGi7t9DkbwUNvrGcJJxNAcBDg4OSs8XLFiAhQsXVrjv1q1bcfbsWURGRjZCZVQfMjIycObMGURERCAhIUGxXU9PD7169UKfPn3g7OwMDY7QoGaGgeIJgiAgIT4TZ6MScD4mCTk5/y3oZdHKAL3c7dG9py3MLQxqfMx/ku8AALxt2vLeJgEA4uPjIZP9N5KnstaJ+Ph4zJkzB4cOHYKuLheOU2cFBQWIiYlBREQErl27BuHfZkxNTU24ubnB09MTbm5u0NbWFrlSoobDQAHg0cM8xEQn4mx0Ah7cz1VsNzDUQfcetujpbg97B+M6BYJTyY/7T/jU4HYHtQwymUwpUFQmOjoa9+/fR69evRTbSktLcfz4caxcuRKFhYXQ1ORy92IpLS3F1atXER4ejnPnzqG4uFjxmrOzMzw9PeHu7g4Dg5p/ASFqylpsoMjLK8KFc8k4G5WIu7GPFNu1tDXQxdUaPd3t0MGlFTQ1694smVNciPNpj5s8a9J/guhJgwcPxsWLF5W2TZ06FR07dsSHH37IMCECQRBw7949REREIDIyEtnZ2YrXrKys4Onpid69e6NVq1YiVkkkjhYVKEpKSnH1yn3ERCXi6pX7KC0tG64FOLezQE93O7h2tYaubv00S0akxKJUkKONkRnsDU3r5ZjUchgZGcHV1VVpm4GBAczNzcttp4aVlpaGM2fOIDw8HKmpqYrtRkZGcHd3h6enJxwdHXlbk1q0Zh8o5HIB9+6m42xUAi6cS0Z+/n/Nkja2RujRyx49etrC2ESv3s/9z7+3O9g6QdT05ObmIjo6GhEREbh165Ziu7a2Nrp37w5PT0907tyZLUVE/2q2geJ+ag7ORicgJjoR6Y/yFdtlxlL06GmHnu72sLFt2Cmu/0n5t0NmBfNPENVFaGio2CU0a8XFxbh06RIiIiJw8eJFlJQ8nvVWIpHAxcUFnp6e6NGjB/T06v8LCFFT16wCRU524b+TTiUgIT5TsV1Hqomu3WzQo5c9nNuZK0061VDSC/Nw6WESgMcjPIhIPQmCgNu3bysW48rLy1O8Zmdnp+gXYWrK25ZEVWnygaKoqBSXL6XgbFQCbl5PUyzGpaEhQYeOrdCzlx06u1pDR6dxmyXDU+5AgIB2xq1gpc/FvojUTUpKimIxrocPHyq2m5iYKCadsre3F7FCoqalSQYKuVzA7ZtpjxfjupiMosJSxWsOrU3Qs5cduvWwhaFR5bMPNrSy+Sc4XJRIfWRlZSEqKgrh4eG4d++eYrtUKkXPnj3h6ekJFxcXTjpFVAdNKlAkJWbhbHQCzp1NRFZmoWK7mZm+YjEuS0v1WFSLHTKJ1ENRURHOnTuHiIgIXLlyRbEYl4aGhtJiXDo6Vc96S0RVU/tAkZGRj3PRiTgbnYiU5P/GfOvpa6Nbd9t/F+MyVavhWg/ys3E94/HQMi9r9p8gamxyuRzXr19XLMZVWPjfFxBHR0fFpFM1mWCMiGpGLQNFQUExLp5/3C/izu2HTyzGpYHOXSzRw90eHTu1gpaWeg7XOv3v7Y7OZjYw0+UseUSNJT4+XjHpVEZGhmK7hYWFonOltbW1eAUSNWNqEyhKS+W4fu3fxbgupaDkicW4nJzN0LOXHdy62UBfX/2bJTndNlHjSU9PVyzGlZiYqNiur6+vmHTK2dlZrVoxiRpKYGAgdu3ahWvXrkFPTw/e3t5YunQpXFxcavT+U6dOYcCAAXB1dcW5c+dqdW5RA4UgCIiPy8DZqEScj0lCbu5/i3FZWhqip7sduveyg5mZvohV1t5/80/wdgdRQ8jPz8fZs2cRERGBGzduKBbj0tLSgpubG/r06YMuXbpwMS5qccLCwjBjxgx4eHigpKQEH3/8MYYOHYorV65Uu65MZmYmJk+ejMGDByvNCFtTogSKh2m5OBudiJjoRKQ9+G8xLkNDHXTvaYee7naws6/bYlxiS8rNRGxWGjQkEngyUBDVm9LSUly5cgXh4eE4f/680mJc7dq1g6enJ3r16sXFuKhFO3DggNLztWvXwtLSEtHR0ejfv3+V7502bRomTZoETU1N7Nmzp9bnbrRAkZtbhAvnknA2KhH37qYrtmvraMLVzRo9e9mhXQcLlRbjUgdlozvczO0g0+GS00SqEAQBd+/eRXh4OKKiopCTk6N4zcrKCn369EHv3r1hYWEhYpVEjSMrK0vpuVQqhVRa9fQImZmPJ3k0MzOrcr+1a9fi9u3b2LhxIxYvXlyn+ho0UBQXl+Lq5VTERCfi2tX7KC193CwpkQDt2lugp7s9urhZQ1dXbbpyqOwf9p8gUtmDBw8Uk07dv39fsd3IyAgeHh7o06cPWrdu3SRbMYnqysHBQen5ggULsHDhwkr3FwQBAQEB6Nu3b5ULCt68eRMfffQRTpw4AS2tuv89rve/5HK5gNg7jxAT/XgxroKCEsVrtnYy9HS3R7cetjA2bn7f3gVBYIdMojrKyclRLMZ1+/ZtxXZtbW306NEDnp6e6NSpExfjohYrPj5eaahzda0TM2fOxIULF3Dy5MlK9yktLcWkSZOwaNEidOjQQaX66i1QpKZkK/pFZKT/txiXiYkuevR6POmUtU3zHvMdl/MIibkZ0NbQhIelo9jlEKm94uJiXLx4EeHh4bh06RJKSx/PeiuRSNCxY0fFYly6us3vCwhRbclkshrPnTJr1izs27cPx48fr3IK+ezsbERFRSEmJgYzZ84E8HgeF0EQoKWlhUOHDmHQoEE1Ome9BIqiolJ8/91JFBc9vhjo6mrBrZsNerrbwalt4yzGpQ7KWid6tHKAvrb6D28lEltoaCh27NiheO7g4ABPT094eHjAxMREvMKImihBEDBr1izs3r0boaGhcHJyqnJ/mUyGixcvKm1btWoVjh49ih07dlT7/ifVS6DQ0Xm8mmdeXjF6uduhU2craDfyYlzqoGz9Ds6OSVQz7u7uOHr0KDw8PODp6Qk7OzuxSyJq0mbMmIHNmzdj7969MDIyQkpKCgDA2NgYenp6AIB58+YhMTERGzZsgIaGRrn+FZaWltDV1a2y30VF6u2Wx4SXurXoDlKCILBDJlEtmZqa4quvvmrR1w6i+hQUFAQAGDhwoNL2tWvXwt/fHwCQnJyMuLi4ej93vQWKln5BuJX5APfzsyHV1ELPVq3FLoeoyWjp1w6i+lQ2yVtV1q1bV+XrCxcurHL0SGWa9qQPaqSsdcLdsg10tTg7HxERtSwMFPWEw0WJiKglaz4zSolILshxWrF+BwNFc7VysAuk0rqvK1NYmAfcqMeCiEjtqXrdAJrOtYMtFPXgWnoK0gvzoK+lg26tKh/vS0RE1FwxUNSDstsdnlZO0NZoecNliYiIGCjqQdn8E942nH+CiIhaJgYKFZXISxH+b/8JdsgkIqKWioFCRZceJiG7uBDGOrroYmYrdjlERESiYKBQUVn/iT7WbaGpwY+TiIhaJv4FVFHZhFbevN1BREQtGAOFCopKS3Dm/l0AnH+CiIhaNgYKFZxLS0B+STHMdQ3gYmopdjlERESiYaBQgeJ2h7UzNCT8KImIqOXiX0EVnFL0n+D8E1T/goKC0LVrV8hkMshkMnh5eWH//v1il0VEVCEGijrKLylG9P17ADj/BDUMe3t7LFmyBFFRUYiKisKgQYMwZswYXL58WezSiIjK4eJgdXT2/j0UyUthpS+Dk8xC7HKoGRo9erTS8y+//BJBQUEIDw9Hly5dRKqKiKhiDBR19ORy5RKJRORqqCnJyspSei6VSiGVSqt8T2lpKbZv347c3Fx4eXk1ZHlERHXCWx519A+n26Y6cnBwgLGxseIRGBhY6b4XL16EoaEhpFIppk+fjt27d6Nz586NWC0RUc2whaIOcooLce5BPADA25odMql24uPjIZPJFM+rap1wcXHBuXPnkJGRgZ07d2LKlCkICwtjqCAitcNAUQdnUu+iRJCjtaEZHIzMxC6HmpiyURs1oaOjg3bt2gEA3N3dERkZiRUrVmD16tUNWSIRUa3xlkcd/MPhoiQSQRBQWFgodhlEROWwhaIOuH4HNYb58+dj+PDhcHBwQHZ2NrZu3YrQ0FAcOHBA7NKIiMphoKiljMI8XHqUBICBghpWamoqXn31VSQnJ8PY2Bhdu3bFgQMH4OfnJ3ZpRETlMFDUUkRKLOSCAGfjVrDWr9l9cKK6CA4OFrsEIqIaYx+KWnpy/gkiIiJ6jIGilsrmn+DtDiIiov8wUNTCw4IcXEtPAcD5J4iIiJ7EQFELp5Mft050MrWGma6ByNUQERGpDwaKWjjF4aJEREQVYqCoBXbIJCIiqhgDRQ0l52biTlYaNCQSeFo5iV0OERGRWmGgqKGy0R1u5nYwluqJXA0REZF6YaCooX+SbwEAvK15u4OIiOhpDBQ19M+/Izx8bBkoiIiInsZAUQNx2Y8Qn5MOLYkGPCzbiF0OERGR2mGgqIGy1UV7tHKAgbZU5GqIiIjUDwNFDXD+CSIioqoxUFRDEARFCwUDBRERUcUYKKpxJysNqfnZkGpqoVer1mKXQ0REpJYYKKpRdrujV6vW0NXSFrkaIiIi9cRAUY1/ON02ERFRtRgoqiAX5Ir5J9h/goiIqHIMFFW4lp6KR4W50NfSQTcLe7HLISIiUlsMFFUou93R28oROppaIldDRESkvhgoqsDhokRERDXDQFEJQRBw9kE8AHbIJCIiqg7b8SshkUhwevwHiLp/D65mtmKXQ0REpNYYKKqgp6WDfrbtxS6DiIhI7TFQENXQlIwXYagjqfP7c4oEfF+P9RCR+lP1ugE0nWsH+1AQERGRyhgoiIiISGUMFERERKQyBgoiIiJSGQMFERERqYyBgkhNBQYGwsPDA0ZGRrC0tMTYsWNx/fp1scsiIqoQAwWRmgoLC8OMGTMQHh6OkJAQlJSUYOjQocjNzRW7NCKicjgPBZGaOnDggNLztWvXwtLSEtHR0ejfv79IVRERVYyBgqiRZWVlKT2XSqWQSqXVvi8zMxMAYGZm1iB1ERGpgrc8iBqZg4MDjI2NFY/AwMBq3yMIAgICAtC3b1+4uro2QpVERLXDFgqiRhYfHw+ZTKZ4XpPWiZkzZ+LChQs4efJkQ5ZGRFRnDBREjUwmkykFiurMmjUL+/btw/Hjx2Fvb9+AlRER1R0DBZGaEgQBs2bNwu7duxEaGgonJyexSyIiqhQDBZGamjFjBjZv3oy9e/fCyMgIKSkpAABjY2Po6emJXB0RkTJ2yiRSU0FBQcjMzMTAgQNhY2OjeGzbtk3s0ohITdVlQrxdu3bBz88PrVq1gkwmg5eXFw4ePFjrczNQEKkpQRAqfPj7+4tdGhGpqbpMiHf8+HH4+fnh77//RnR0NHx9fTF69GjExMTU6ty85UFERNRM1GVCvOXLlys9/+qrr7B371788ccf6NGjR43PzUBBRETUBNRlUry6TIgnl8uRnZ1d60n0eMuDiIioCajtpHh1nRDvm2++QW5uLiZMmFCr+thCQURE1ATUdlK8ukyIt2XLFixcuBB79+6FpaVlrepjoCAiImoCajMpXl0mxNu2bRtef/11bN++HUOGDKl1fQwUREREzURdJ8TbsmULXnvtNWzZsgUjR46s07kZKIiIiJqJmkyIN2/ePCQmJmLDhg0AHoeJyZMnY8WKFejTp4/iPXp6ejA2Nq7xudkpk4iIqJmoyYR4ycnJiIuLUzxfvXo1SkpKMGPGDKX3zJkzp1bnZgsFERFRMyEIQrX7rFu3Tul5aGhovZybLRRERESkMgYKIiIiUhkDBREREamMgYKIiIhUxkBBREREKmOgICIiIpUxUBAREZHKGCiIiIhIZQwUREREpDIGCiIiIlIZAwURERGpjIGCiIiIVMZAQURERCpjoCAiIiKVMVAQERGRyhgoiIiISGUMFERERKQyBgoiIiJSGQMFERERqYyBgoiIiFSmJXYBRE3FqL5zoKEnrfP75fmFwJbl9VcQEak9Va8bQNO5drCFgoiIiFTGQEGkpo4fP47Ro0fD1tYWEokEe/bsEbskIqJKMVAQqanc3Fx069YNK1euFLsUIqJqsQ8FUSPLyspSei6VSiGVlr/HOnz4cAwfPryxyiIiUglbKIgamYODA4yNjRWPwMBAsUsiIlIZWyiIGll8fDxkMpnieUWtE0RETQ0DBVEjk8lkSoGCiKg54C0PIiIiUhkDBREREamMtzyI1FROTg5u3bqleB4bG4tz587BzMwMrVu3FrEyIqLyGCiI1FRUVBR8fX0VzwMCAgAAU6ZMwbp160SqioioYgwURGpq4MCBEARB7DKIiGqEfSiIiIhIZQwUREREpDIGCiIiIlIZAwURERGpjIGCiIiIVMZAQURERCpjoCAiIiKVMVAQERGRyhgoiIiISGUMFERERKQyBgoiIiJSGQMFERERqYyBgoiIiFTGQEFEREQqY6AgIiIilTFQEBERkcoYKIiIiEhlDBRERESkMgYKIiIiUhkDBREREamMgYKIiIhUxkBBREREKmOgICIiIpUxUBAREZHKGCiIiIhIZQwUREREpDIGCiIiIlIZAwURERGpjIGCiIiIVMZAQURERCpjoCBSc6tWrYKTkxN0dXXRq1cvnDhxQuySiEhNBQYGwsPDA0ZGRrC0tMTYsWNx/fr1at8XFhaGXr16QVdXF23btsVPP/1U63MzUBCpsW3btmHu3Ln4+OOPERMTg379+mH48OGIi4sTuzQiUkNhYWGYMWMGwsPDERISgpKSEgwdOhS5ubmVvic2NhYjRoxAv379EBMTg/nz52P27NnYuXNnrc4tEQRBUPUHIGrOsrKyYGxsDOuv34JET1rn4wj5hUh5Lwjx8fGQyWSK7VKpFFJpxcf19PREz549ERQUpNjWqVMnjB07FoGBgXWuhYgaVn1dN4C6XTvKPHjwAJaWlggLC0P//v0r3OfDDz/Evn37cPXqVcW26dOn4/z58zh9+nSN69Sq8Z5ELZSOjg6sra2R8l5Q9TtXw9DQEA4ODkrbFixYgIULF5bbt6ioCNHR0fjoo4+Utg8dOhT//POPyrUQUcOpz+sGULtrx5MyMzMBAGZmZpXuc/r0aQwdOlRp27BhwxAcHIzi4mJoa2vXqEYGCqJq6OrqIjY2FkVFRSofSxAESCQSpW2VfcNIS0tDaWkprKyslLZbWVkhJSVF5VqIqOHU53UDqN2148n3BAQEoG/fvnB1da10v5SUlAqvMyUlJUhLS4ONjU2NamSgIKoBXV1d6OrqinLupy8iFV1YiEj9iHndAICZM2fiwoULOHnyZLX7VnSdqWh7VRgoiNSUhYUFNDU1y7VG3L9/v9y3CSKiJ82aNQv79u3D8ePHYW9vX+W+1tbWFV5ntLS0YG5uXuNzcpQHkZrS0dFBr169EBISorQ9JCQE3t7eIlVFROpMEATMnDkTu3btwtGjR+Hk5FTte7y8vMpdZw4dOgR3d/ca958AGCiI1FpAQAB++eUX/Prrr7h69SreeecdxMXFYfr06WKXRkRqaMaMGdi4cSM2b94MIyMjpKSkICUlBfn5+Yp95s2bh8mTJyueT58+Hffu3UNAQACuXr2KX3/9FcHBwXjvvfdqdW4OGyVSc6tWrcKyZcuQnJwMV1dXfPfdd5UO/yKilq2yPg9r166Fv78/AMDf3x93795FaGio4vWwsDC88847uHz5MmxtbfHhhx/W+osLAwURERGpjLc8iIiISGUMFERERKQyBgoiIiJSGQMFERERqYyBgoiIiFTGQEFEREQqY6AgIiIilTFQEBERkcoYKIiIiEhlDBRERESkMgYKIiIiUtn/A1WtNXsbR95QAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -1409,7 +1441,7 @@ "angles_gdf len 2\n", "connectivity: 1\n", "Counter values: dict_values([1, 1])\n", - "angles: [34.25143801488164]\n", + "angles: [np.float64(34.25143801488164)]\n", "(2, 3) added\n", "**************************************************************\n", " \n", @@ -1423,7 +1455,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1438,7 +1470,7 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([2, 1])\n", - "angles: [70.04113695824684]\n", + "angles: [np.float64(70.04113695824684)]\n", "(8, 1) added\n", "**************************************************************\n", " \n", @@ -1452,7 +1484,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1465,12 +1497,12 @@ "output_type": "stream", "text": [ "angles_gdf len 4\n", - "Interior angles found: [89.87471285219927, 89.74560192447649]\n", - "Interior angles found: [89.75267804978043, 89.88178897750322]\n", - "Final angles found: [89.74560192447649, 89.75267804978043]\n", + "Interior angles found: [np.float64(89.87471285219927), np.float64(89.74560192447649)]\n", + "Interior angles found: [np.float64(89.75267804978043), np.float64(89.88178897750322)]\n", + "Final angles found: [np.float64(89.74560192447649), np.float64(89.75267804978043)]\n", "connectivity: 2\n", "Counter values: dict_values([2, 2])\n", - "angles: [89.74560192447649, 89.75267804978043]\n", + "angles: [np.float64(89.74560192447649), np.float64(89.75267804978043)]\n", "(0, 1) added\n", "**************************************************************\n", " \n", @@ -1484,7 +1516,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1497,12 +1529,12 @@ "output_type": "stream", "text": [ "angles_gdf len 4\n", - "Interior angles found: [85.21096368451747, 84.23886881283048]\n", - "Interior angles found: [81.14186114900058, 80.16976627731358]\n", - "Final angles found: [84.23886881283048, 80.16976627731358]\n", + "Interior angles found: [np.float64(85.21096368451747), np.float64(84.23886881283048)]\n", + "Interior angles found: [np.float64(81.14186114900058), np.float64(80.16976627731358)]\n", + "Final angles found: [np.float64(84.23886881283048), np.float64(80.16976627731358)]\n", "connectivity: 2\n", "Counter values: dict_values([2, 2])\n", - "angles: [84.23886881283048, 80.16976627731358]\n", + "angles: [np.float64(84.23886881283048), np.float64(80.16976627731358)]\n", "(2, 6) added\n", "**************************************************************\n", " \n", @@ -1516,7 +1548,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh0AAAGTCAYAAACMMqDSAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAASYNJREFUeJzt3XlUFFfePvCnUWhAaRCUTdyDC4uCsneLGreIOJrESOIMasbsGLfkHUdHg04ycUkyEffkDRGXiMag4h41UUi3uANG45oYQQRXoAEFBOr3hy/1swRZm6LF53NOnzN9uVV9CydfnqquW1chCIIAIiIiogZm0tgDICIiomcDQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg8hIrVy5Ej179oRKpYJKpUJgYCD27NlT5TYJCQno06cPzM3N0blzZ6xatapCn7i4OLi5uUGpVMLNzQ1bt25tqEMgIpkZe91g6CAyUi4uLliwYAFOnDiBEydO4Pnnn8fIkSNx9uzZSvtfuXIFISEh6Nu3L5KTkzFr1ixMnjwZcXFxYp+kpCSEhYUhPDwcqampCA8Px5gxY3D06FG5DouIGpCx1w0FF3wjenrY2tris88+w8SJEyv8bMaMGdi+fTvOnTsntr3zzjtITU1FUlISACAsLAx6vV5y5vPCCy+gVatWiI2NbfgDICLZGVPdaF7HYyB6phQWFqK4uLje+xEEAQqFQtKmVCqhVCqr3K60tBSbN29GQUEBAgMDK+2TlJSEIUOGSNqGDh2K6OhoPHjwAKampkhKSsK0adMq9Fm8eHHtD4aIqmSougHUrXYYY91g6CCqRmFhIWxtbXH//v1676tly5bIz8+XtEVGRmLu3LmV9v/1118RGBiIwsJCtGzZElu3boWbm1ulfbOysuDg4CBpc3BwQElJCW7fvg0nJ6cn9snKyqr7QRFRBYasG0Dtaocx1w2GDqJqFBcX4/79+xg7dizMzMzqtZ8NGzYgPT0dKpVKbK/qTKVbt25ISUlBTk4O4uLiMH78eCQkJDyxgDx+JlT+7emj7ZX1ebyNiOrHUHWjfF+1qR3GXDcYOohqyMzMrN7FA4B4V3lNP/O5554DAPj4+OD48eOIiorCV199VaGvo6NjhTOPmzdvonnz5rCzs6uyz+NnMURkGIaqG0DNa4cx1w3OXiF6igiCgKKiokp/FhgYiP3790va9u3bBx8fH5iamlbZJygoqGEGTESNzpjqBq90EBmpWbNmYdiwYWjXrh3y8vKwceNGHDp0CHv37gUAzJw5ExkZGVi7di2Ah3ecL1u2DNOnT8ebb76JpKQkREdHS+4unzJlCoKDg7Fw4UKMHDkS8fHxOHDgALRabaMcIxEZlrHXDYYOIiN148YNhIeHIzMzE9bW1ujZsyf27t2LwYMHAwAyMzORlpYm9u/UqRN2796NadOmYfny5XB2dsaSJUvw8ssvi32CgoKwceNGzJ49G3PmzEGXLl2wadMm+Pv7y358RGR4xl43+JwOomro9XpYW1tjwoQJ9b6RNCYmBrm5uTW+p4OInk6GqhtA06odvKeDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBmp+fPnw9fXF1ZWVrC3t8eoUaNw4cKFKreZMGECFApFhZe7u7vYJyYmptI+hYWFDX1IRNTAjL1uMHQQGamEhARERETgyJEj2L9/P0pKSjBkyBAUFBQ8cZuoqChkZmaKr/T0dNja2uKVV16R9FOpVJJ+mZmZMDc3b+hDIqIGZux1o3mdjoqIGtzevXsl71evXg17e3ucPHkSwcHBlW5jbW0Na2tr8f22bduQnZ2N119/XdJPoVDA0dHR8IMmokZl7HWDVzqIZKbX6yWvoqKiGm2Xm5sLALC1ta3xZ0VHR2PQoEHo0KGDpD0/Px8dOnSAi4sLQkNDkZycXPMDIKJGUZfaYWx1g1c6iGpIY70flsq65/R7RWWIAdCuXTtJe2RkJObOnVvltoIgYPr06dBoNPDw8KjR52VmZmLPnj3YsGGDpL179+6IiYmBp6cn9Ho9oqKioFarkZqaCldX11ocERFVp751A6h77TDGusHQQSSz9PR0qFQq8b1Sqax2m0mTJuH06dPQarU1/pyYmBjY2Nhg1KhRkvaAgAAEBASI79VqNXr37o2lS5diyZIlNd4/EcmrtrXDGOsGQweRzFQqlaRwVOf999/H9u3bkZiYCBcXlxptIwgCvv32W4SHh8PMzKzKviYmJvD19cWlS5dqPCYikl9taoex1g3e00FkpARBwKRJk7Blyxb8/PPP6NSpU423TUhIwOXLlzFx4sQafU5KSgqcnJzqM1wiMgLGXjd4pYPISEVERGDDhg2Ij4+HlZUVsrKyADy809zCwgIAMHPmTGRkZGDt2rWSbaOjo+Hv71/p97jz5s1DQEAAXF1dodfrsWTJEqSkpGD58uUNf1BE1KCMvW4wdBAZqZUrVwIA+vfvL2lfvXo1JkyYAODhTV9paWmSn+fm5iIuLg5RUVGV7jcnJwdvvfUWsrKyYG1tDW9vbyQmJsLPz8/gx0BE8jL2uqEQBEGo1RZEzxi9Xg9ra2t8M6VtvWevvBGVgdzc3Frd00FETx9D1Q2gadUO3tNBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIzU/Pnz4evrCysrK9jb22PUqFG4cOFCldscOnQICoWiwuv8+fOSfnFxcXBzc4NSqYSbmxu2bt3akIdCRDIx9rrB0EFkpBISEhAREYEjR45g//79KCkpwZAhQ1BQUFDtthcuXEBmZqb4cnV1FX+WlJSEsLAwhIeHIzU1FeHh4RgzZgyOHj3akIdDRDIw9rqhEARBqPVRET1D9Ho9rK2t8c2UtrBU1j2n3ysqwxtRGcjNzYVKpar19rdu3YK9vT0SEhIQHBxcaZ9Dhw5hwIAByM7Oho2NTaV9wsLCoNfrsWfPHrHthRdeQKtWrRAbG1vrcRFRRYaqG0D9aoex1Q1e6SCSmV6vl7yKiopqtF1ubi4AwNbWttq+3t7ecHJywsCBA3Hw4EHJz5KSkjBkyBBJ29ChQ3H48OEaHgERNYa61A5jqxvNa9Wb6BnWt/d1WFkq6rx93r2HFxXbtWsnaY+MjMTcuXOr3FYQBEyfPh0ajQYeHh5P7Ofk5ISvv/4affr0QVFREdatW4eBAwfi0KFD4llOVlYWHBwcJNs5ODggKyurDkdFRFWpb90A6l47jLFuMHQQySw9PV1yiVSpVFa7zaRJk3D69Glotdoq+3Xr1g3dunUT3wcGBiI9PR2ff/655NKqQiEtgoIgVGgjIuNS29phjHWDX68QyUylUkle1RWO999/H9u3b8fBgwfh4uJS688LCAjApUuXxPeOjo4Vzk5u3rxZ4SyGiIxLbWqHsdYNhg4iIyUIAiZNmoQtW7bg559/RqdOneq0n+TkZDg5OYnvAwMDsX//fkmfffv2ISgoqF7jJaLGZ+x1g1+vEBmpiIgIbNiwAfHx8bCyshLPMqytrWFhYQEAmDlzJjIyMrB27VoAwOLFi9GxY0e4u7ujuLgY69evR1xcHOLi4sT9TpkyBcHBwVi4cCFGjhyJ+Ph4HDhwoNpLsERk/Iy9bjB0EBmplStXAgD69+8vaV+9ejUmTJgAAMjMzERaWpr4s+LiYnz44YfIyMiAhYUF3N3dsWvXLoSEhIh9goKCsHHjRsyePRtz5sxBly5dsGnTJvj7+zf4MRFRwzL2usHndBBVo3y+/YU1inrPXuk2XqjzczqI6OlhqLoBNK3awXs6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsDBo6lixZAoVCAQ8Pjyf2USgUmDt3rvj+0KFDUCgUOHToUL0/f/fu3ZJ9G1JMTAwUCgVOnDjRIPs3tA0bNmDx4sWNPYwKDPnvXU6hUFT6WrBggcE+g4iI6s+goePbb78FAJw9exZHjx415K5rZPfu3Zg3b57sn2uMjDV0NJTRo0cjKSlJ8ho3blxjD4uIiB7R3FA7OnHiBFJTUzF8+HDs2rUL0dHR8Pf3N9TuDU4QBBQWFsLCwqKxh0IG4ODggICAgMYeBhERVcFgVzqio6MBAAsWLEBQUBA2btyIe/fuGWr3uHfvHj788EN06tQJ5ubmsLW1hY+PD2JjYwEAEyZMwPLlywFIL7f/+eefYtukSZOwatUq9OjRA0qlEmvWrAEAaLVaDBw4EFZWVrC0tERQUBB27dpV7ZgyMzPRp08fuLq64tKlSwAAvV4vjtPMzAxt27bF1KlTUVBQINl28+bN8Pf3h7W1NSwtLdG5c2f8/e9/r/Yzly9fjuDgYNjb26NFixbw9PTEokWL8ODBA7FP//79sWvXLly9elXyu6hKx44dERoair1796J3796wsLBA9+7dxatXjzpz5gxGjhyJVq1awdzcHF5eXuLv8lHnz5/HCy+8AEtLS7Ru3RrvvPMO8vLyKv38AwcOYODAgVCpVLC0tIRarcZPP/1U7e+DiIieHgYJHffv30dsbCx8fX3h4eGBv//978jLy8PmzZsNsXsAwPTp07Fy5UpMnjwZe/fuxbp16/DKK6/gzp07AIA5c+Zg9OjRACC5xO7k5CTuY9u2bVi5ciU++ugj/Pjjj+jbty8SEhLw/PPPIzc3F9HR0YiNjYWVlRVGjBiBTZs2PXE8Z86cgb+/P5RKJZKSkuDq6op79+6hX79+WLNmDSZPnow9e/ZgxowZiImJwV/+8hcIgiCOLywsDJ07d8bGjRuxa9cufPTRRygpKan29/D7779j7NixWLduHXbu3ImJEyfis88+w9tvvy32WbFiBdRqNRwdHSW/i+qkpqbigw8+wLRp0xAfH4+ePXti4sSJSExMFPtcuHABQUFBOHv2LJYsWYItW7bAzc0NEyZMwKJFi8R+N27cQL9+/XDmzBmsWLEC69atQ35+PiZNmlThc9evX48hQ4ZApVJhzZo1+P7772Fra4uhQ4fWOHhs2LABFhYWUCqV6NOnD1avXl2j7YiISEaCAaxdu1YAIKxatUoQBEHIy8sTWrZsKfTt27dCXwBCZGSk+P7gwYMCAOHgwYNVfoaHh4cwatSoKvtEREQITzokAIK1tbVw9+5dSXtAQIBgb28v5OXliW0lJSWCh4eH4OLiIpSVlQmCIAirV68WAAjHjx8X9u/fL6hUKmH06NHC/fv3xe3mz58vmJiYCMePH5d8xg8//CAAEHbv3i0IgiB8/vnnAgAhJyenyuOpTmlpqfDgwQNh7dq1QrNmzSTHNnz4cKFDhw413leHDh0Ec3Nz4erVq2Lb/fv3BVtbW+Htt98W21599VVBqVQKaWlpku2HDRsmWFpaisc0Y8YMQaFQCCkpKZJ+gwcPlvx7FxQUCLa2tsKIESMqHFuvXr0EPz+/asc+duxY4bvvvhMSExOFH374QRg2bJgAQJg9e3aNj78qubm5AgDhwhqFcH2zSZ1fF9YoBABCbm6uQcZFRMbLUHWjqdUOg1zpiI6OhoWFBV599VUAQMuWLfHKK6/gl19+Eb92qC8/Pz/s2bMH//znP3Ho0CHcv3+/1vt4/vnn0apVK/F9QUEBjh49itGjR6Nly5Zie7NmzRAeHo5r167hwoULkn2sWbMGISEheOONN/D999/D3Nxc/NnOnTvh4eEBLy8vlJSUiK+hQ4dKZmz4+voCAMaMGYPvv/8eGRkZNT6G5ORk/OUvf4GdnR2aNWsGU1NTjBs3DqWlpbh48WKtfyeP8vLyQvv27cX35ubm6Nq1K65evSq2/fzzzxg4cCDatWsn2XbChAm4d++eeEXl4MGDcHd3R69evST9xo4dK3l/+PBh3L17F+PHj5f8zsrKyvDCCy/g+PHjFb6aetx3332HsWPHom/fvnj55Zexe/duhIaGYsGCBbh161adfhdERGR49Q4dly9fRmJiIoYPHw5BEJCTk4OcnBzxq47K7gmoiyVLlmDGjBnYtm0bBgwYAFtbW4waNapWoebRr1oAIDs7G4IgVGgHAGdnZwAQv74pt3HjRlhYWOCNN96ocJ/EjRs3cPr0aZiamkpeVlZWEAQBt2/fBgAEBwdj27ZtKCkpwbhx4+Di4gIPDw/x/pQnSUtLQ9++fZGRkYGoqCj88ssvOH78uHgvS12C2KPs7OwqtCmVSsl+79y5U6Pf1507d+Do6Fih3+NtN27cAPBw9snjv7eFCxdCEATcvXu31sfyt7/9DSUlJU/NFGciomdBvWevfPvttxAEAT/88AN++OGHCj9fs2YNPvnkEzRr1qxen9OiRQvMmzcP8+bNw40bN8SrHiNGjMD58+drtI/HQ0KrVq1gYmKCzMzMCn2vX78OAGjdurWk/bvvvsOcOXPQr18/7Nu3D15eXuLPWrduDQsLiycGrUf3NXLkSIwcORJFRUU4cuQI5s+fj7Fjx6Jjx44IDAysdPtt27ahoKAAW7ZsQYcOHcT2lJSUKo/bkOzs7Gr0+7Kzs0NWVlaFfo+3lfdfunTpE2efODg41Hqcwv/dP2NiwuffEREZi3qFjtLSUqxZswZdunTBN998U+HnO3fuxBdffIE9e/YgNDS0Ph8l4eDggAkTJiA1NRWLFy/GvXv3YGlpCaVSCeDhGX9NpsK2aNEC/v7+2LJlCz7//HNxm7KyMqxfvx4uLi7o2rWrZBtbW1scOHAAoaGhGDBgAPbs2SP+sQwNDcWnn34KOzs7dOrUqUbHolQq0a9fP9jY2ODHH39EcnLyE0NHeWgqP07g4R/X//3f/610v/W98lGZgQMHYuvWrbh+/bp4dQMA1q5dC0tLS/F3MWDAACxatAipqamSr1g2bNgg2Z9arYaNjQ1+++23Sm8yrat169bB1NQUffr0Mdg+iYiofuoVOvbs2YPr169j4cKF6N+/f4Wfe3h4YNmyZYiOjq536PD390doaCh69uyJVq1a4dy5c1i3bh0CAwNhaWkJAPD09AQALFy4EMOGDUOzZs3Qs2dPmJmZPXG/8+fPx+DBgzFgwAB8+OGHMDMzw4oVK3DmzBnExsZWOtXUysoKe/fuxUsvvYTBgwdj+/btGDBgAKZOnYq4uDgEBwdj2rRp6NmzJ8rKypCWloZ9+/bhgw8+gL+/Pz766CNcu3YNAwcOhIuLC3JychAVFQVTU1P069fviWMdPHgwzMzM8Nprr+Ef//gHCgsLsXLlSmRnZ1fo6+npiS1btmDlypXo06cPTExM4OPjU9tfewWRkZHYuXMnBgwYgI8++gi2trb47rvvsGvXLixatAjW1tYAgKlTp+Lbb7/F8OHD8cknn8DBwQHfffddhatSLVu2xNKlSzF+/HjcvXsXo0ePhr29PW7duoXU1FTcunULK1eufOJ4PvvsM/z222/i7/LmzZuIjo7Gvn37MHfu3ApXqoiIqPHUK3RER0fDzMwMr7/+eqU/b926NV588UX88MMPuHHjRp0uk5d7/vnnsX37dnz55Ze4d+8e2rZti3HjxuFf//qX2Gfs2LHQ6XRYsWIF/v3vf0MQBFy5cgUdO3Z84n779euHn3/+GZGRkZgwYQLKysrQq1cvbN++vcqgZGFhgfj4eIwdOxYhISGIi4tDSEgIfvnlFyxYsABff/01rly5AgsLC7Rv3x6DBg0Sx+Hv748TJ05gxowZuHXrFmxsbODj44Off/4Z7u7uT/zM7t27Iy4uDrNnz8ZLL70EOzs7jB07FtOnT8ewYcMkfadMmYKzZ89i1qxZyM3NhSAI4lcO9dGtWzccPnwYs2bNQkREBO7fv48ePXpg9erVmDBhgtjP0dERCQkJmDJlCt59911YWlrixRdfxLJlyzBy5EjJPv/2t7+hffv2WLRoEd5++23k5eXB3t4eXl5ekn0+6Xeyfft27Nq1C9nZ2bCwsICXlxdiY2PFG5uJiMg4KARD/CUiasL0ej2sra1xYY0CVpZVP2StKnn3BHQbLyA3NxcqlcqAIyQiY2OougE0rdrBu+yIiIhIFgwdREREJAuGDiKqt6NHj+LFF19E+/btoVQq4eDggMDAQHzwwQeSfitWrEBMTEyDjGHChAmSh/w1pl9++QVKpVLyYD2tVos33ngDffr0gVKplKwNVVcHDhzA4MGD4ezsDKVSCXt7ezz//PPYvXu3pN+DBw/QpUuXBll5+tNPP8W2bdsMvt/6mjt3brVrTtXGoUOHJGtZPfo6cuSIwT6nqWPoIKJ62bVrF4KCgqDX67Fo0SLs27cPUVFRUKvVFdYvasjQYSwEQcDUqVPx5ptvSp6n89NPP+HAgQNo3749goKCDPJZd+7cgbu7O7788kvs27cPX331FUxNTTF8+HCsX79e7GdqaoqPPvoI//73vys88LC+jDV0NJRPP/1UsqZVUlISPDw8GntYTw2DLW1PRM+mRYsWoVOnTvjxxx/RvPn/LymvvvqqZBHA2nrw4AEUCoVkn0+DvXv34tSpUxWeSTNnzhxERkYCAD7//HNxWYT6CAsLQ1hYmKQtNDQUnTp1wtdff42//e1vYvtrr72G6dOn46uvvsKsWbPq/dnPKldX1yc+yJCqxysdRFQvd+7cQevWrSsNB48+EbZjx444e/YsEhISxMvS5dPIyy9dr1u3Dh988AHatm0LpVKJy5cvA3j45ONevXrB3Nwctra2ePHFF3Hu3Llqx6bT6dC6dWuEhoaKa/hcunQJY8eOhb29PZRKJXr06CEuJVCurKwMn3zyCbp16wYLCwvY2NigZ8+eiIqKqvYzV65cCV9fX3Tr1u2Jv4uGZGpqChsbmwr/HmZmZggLC8PXX39d7fT5wsJCfPDBB/Dy8oK1tTVsbW0RGBiI+Ph4ST+FQoGCggKsWbNG/Det7JlN5f78808oFAp8/vnn+O9//4tOnTqhZcuWCAwMrPQriu3bt4vPYrKyssLgwYMrXTF7165d8PLyglKpRKdOnfD5559X+vmCIGDFihXw8vKChYUFWrVqhdGjR+OPP/6o8vdBhsPQQUT1EhgYiKNHj2Ly5Mk4evQoHjx4UGm/rVu3onPnzvD29hYvS2/dulXSZ+bMmUhLS8OqVauwY8cO2NvbY/78+Zg4cSLc3d2xZcsWREVF4fTp0wgMDKxy7aXvv/8eAwcOxJgxYxAfH48WLVrgt99+g6+vL86cOYMvvvgCO3fuxPDhwzF58mTMmzdP3HbRokWYO3cuXnvtNezatQubNm3CxIkTkZOTU+Xvori4GAcOHMCAAQNq/gs0gLKyMpSUlOD69euIjIzExYsXK9xPAwD9+/fH1atXcebMmSr3V1RUhLt37+LDDz/Etm3bEBsbC41Gg5deeglr164V+yUlJcHCwgIhISHiv+mKFSuqHe/y5cuxf/9+LF68GN999x0KCgoQEhKC3Nxcsc+GDRswcuRIqFQqxMbGIjo6GtnZ2ejfvz+0Wq3Y76effsLIkSNhZWWFjRs34rPPPsP333+P1atXV/jct99+G1OnTsWgQYOwbds2rFixAmfPnkVQUJC4DlR1IiIi0Lx5c6hUKgwdOlQyFqqBRljZluip0lhL23/66aeCj4+P0LJlS6FNmzbCyJEjhfPnz1e5TVxcnDBo0CChdevWgpWVlRAQECDs3btX0mf16tUCgAqv+/fv1+n3c/v2bUGj0Yj7MTU1FYKCgoT58+cLeXl5kr7u7u5Cv379Kuzj4MGDAgAhODhY0p6dnS1YWFgIISEhkva0tDRBqVQKY8eOFdvGjx8vtGjRQhAEQViwYIHQrFkzYeHChZLthg4dKri4uFT4N5g0aZJgbm4u3L17VxAEQQgNDRW8vLxq94sQBOHo0aMCAGHjxo1V9vvss88EAMKVK1dq/RmVGTp0qPj7V6lUwpYtWyrtd+nSJQGAsHLlylrtv6SkRHjw4IEwceJEwdvbW/KzFi1aCOPHj6/Rfq5cuSIAEDw9PYWSkhKx/dixYwIAITY2VhAEQSgtLRWcnZ0FT09PobS0VOyXl5cn2NvbC0FBQWKbv7+/4OzsLPn/r16vF2xtbYVH/8QlJSUJAIQvvvhCMqb09HTBwsJC+Mc//lHl2E+dOiVMmTJF2Lp1q5CYmCh8++23Qo8ePYRmzZpV+G9MEBpvaXtjrxu80kFkpBISEhAREYEjR45g//79KCkpwZAhQ8SvCSqTmJiIwYMHY/fu3Th58iQGDBiAESNGIDk5WdJPpVIhMzNT8jI3N6/TOO3s7MQVjxcsWICRI0fi4sWLmDlzJjw9PcXVlWvi5ZdflrxPSkrC/fv3KzyZtl27dnj++efx008/SdoFQcDbb7+NyMhIbNiwAf/4xz/EnxUWFuKnn37Ciy++CEtLS5SUlIivkJAQFBYWipf4/fz8kJqaivfeew8//vgj9Hp9jcZfvvChvb19jY/ZEJYuXYpjx44hPj4eQ4cORVhYWKWrVpePKyMjo9p9bt68GWq1Gi1btkTz5s1hamqK6OjoGn2tVZ3hw4dLFgHt2bMnAIizfS5cuIDr168jPDxc8rVUy5Yt8fLLL+PIkSO4d+8eCgoKcPz4cbz00kuS//9aWVlhxIgRks/cuXMnFAqFuAJ1+cvR0RG9evWq9h4bb29vLF68GKNGjULfvn3x+uuv4/Dhw3BycpL8/6yxGXvdeLru0CJqAh7/A6ZUKiWL+JXbu3ev5P3q1athb2+PkydPIjg4uNJ9Pz4l8tNPP0V8fDx27NgBb29vsV2hUMDR0bGOR1A5Hx8fcX2fBw8eYMaMGfjyyy+xaNGiGt9Q6uTkJHlfPtPi8XYAcHZ2xv79+yVtxcXF2LRpE9zd3SssDXDnzh2UlJRg6dKlWLp0aaWfXx6QZs6ciRYtWmD9+vVYtWoVmjVrhuDgYCxcuLDKNYzKF1msa4CrK1dXV/F//+Uvf8GwYcMQERGBsLAwyR/t8nFVtxjkli1bMGbMGLzyyiv4n//5Hzg6OqJ58+ZYuXLlE1fRrg07OzvJ+0cX6wSq/3cvKytDdnY2BEFAWVlZpf9ffrztxo0bEAThictxdO7cudbHYWNjg9DQUKxatarGC43WR01qh7HXDYYOohqa/6AtzB7U/eJg8YMyANfQrl07SXtkZCTmzp1b7fbl33fb2trW+DPLysqQl5dXYZv8/Hx06NABpaWl8PLywscffywpLvVlamqKyMhIfPnll9XeP/Cox5+rUP7HKTMzs0Lf69evV1jQT6lU4uDBgxg6dCgGDRqEvXv3olWrVgCAVq1aoVmzZggPD0dERESln1++OnTz5s0xffp0TJ8+HTk5OThw4ABmzZqFoUOHIj09XVxk8nHl47l7926Nj7kh+Pn5Ye/evbh165bkj2z5uKpbCHH9+vXo1KkTNm3aJPk3KSoqapgBP6a6f3cTExO0atUKgiBAoVAgKyurQr/H21q3bg2FQiE+Q+VxlbXVhPB/N+U+6Zkg9a0bQP1qh7HVDYYOIpmlp6dL1k+oSbETBAHTp0+HRqOp1TMBvvjiCxQUFGDMmDFiW/fu3RETEwNPT0/o9XrxmRqpqamSM+aayszMrPSMtPwyvLOzs9imVCqrPct+VGBgICwsLLB+/Xq88sorYvu1a9fw888/Y/To0RW28fb2RkJCAgYNGoT+/ftj//79sLe3h6WlJQYMGIDk5ORqV59+lI2NDUaPHo2MjAxMnToVf/75J9zc3Crt26NHDwDA77//XuNjNDRBEJCQkAAbG5sKVxTKZ2k8afzlFAoFzMzMJH9Is7KyKsxeAWr/b1oT3bp1Q9u2bbFhwwZ8+OGH4jgKCgoQFxcnWV3cz88PW7ZswWeffSZeycnLy8OOHTsk+wwNDcWCBQuQkZEh+e+hPrKzs7Fz5054eXnJcnWrtrXDGOsGQweRzFQqVa0XbZo0aRJOnz5dqzvlY2NjMXfuXMTHx0vuMQgICJA8Z0CtVqN3795YunQplixZUqtxAcDQoUPh4uKCESNGoHv37igrK0NKSgq++OILtGzZElOmTBH7enp6YuPGjdi0aRM6d+4Mc3NzeHp6PnHfNjY2mDNnDmbNmoVx48bhtddew507dzBv3jyYm5uLz714XI8ePfDLL79g0KBBCA4OxoEDB+Di4oKoqChoNBr07dsX7777Ljp27Ii8vDxcvnwZO3bswM8//wwAGDFiBDw8PODj44M2bdrg6tWrWLx4MTp06FBlgXVxcUHnzp1x5MgRTJ48WfKzW7duISEhAQDw66+/AgD27NmDNm3aoE2bNujXr5/Yt3///khISKh2auvIkSPRq1cveHl5wc7ODtevX0dMTAwSEhKwfPnyCtNmjxw5In5VVJXQ0FBs2bIF7733HkaPHo309HR8/PHHcHJyqjBjyNPTE4cOHcKOHTvg5OQEKyurCtOFa8vExASLFi3CX//6V4SGhuLtt99GUVERPvvsM+Tk5GDBggVi348//hgvvPACBg8ejA8++AClpaVYuHAhWrRoIbnipFar8dZbb+H111/HiRMnEBwcjBYtWiAzMxNarRaenp549913nzimsWPHon379vDx8UHr1q1x6dIlfPHFF7hx44ZsD7yrbe0wxrrB0EFk5N5//31s374diYmJcHFxqdE25VM8N2/ejEGDBlXZ18TEBL6+vlVOP63K7NmzER8fjy+//BKZmZkoKiqCk5MTBg0ahJkzZ4pn/wAwb948ZGZm4s0330ReXh46dOhQ7aPAZ86cCXt7eyxZsgSbNm2ChYUF+vfvj08//bTKANC5c2cxePTt2xc//fQT3NzccOrUKXz88ceYPXs2bt68CRsbG7i6uiIkJETcdsCAAYiLi8M333wDvV4PR0dHDB48GHPmzIGpqWmV4/3rX/+KZcuWoaioSHImevbsWcnVGgB47733AAD9+vWT3MiYn59fo+/O1Wo1fvjhByxbtgx6vR42Njbw8fERpwI/btu2bQgJCYGNjU2V+3399ddx8+ZNrFq1Ct9++y06d+6Mf/7zn7h27ZpkajEAREVFISIiAq+++iru3btX4VjqauzYsWjRogXmz5+PsLAwNGvWDAEBATh48KDkia6DBw/Gtm3bMHv2bISFhcHR0RHvvfce7t+/X2GsX331FQICAvDVV19hxYoVKCsrg7OzM9RqNfz8/KocT8+ePbFp0yasWrUK+fn5sLW1hUajwbp16+Dr61vv4zU0Y60bXNqeqBrlS1RP+MYFZpb1uKfjXhli3rhW4+WpBUHA+++/j61bt+LQoUM1voQZGxuLv//974iNjcWoUaNq9Dl+fn7w9PQ0yE2Cz7rr16+jU6dOWLt2bYWnhdZE+XfpixcvfuK9J3Xx+++/w9XVFT/++CMGDx5ssP1S5QxVN4Da1Q5jrxu80kFkpCIiIrBhwwbEx8fDyspKvDHO2tpavEt+5syZyMjIEB/YFBsbi3HjxiEqKgoBAQHiNhYWFrC2tgbw8GpDQEAAXF1dodfrsWTJEqSkpFR4KifVjbOzM6ZOnYr//Oc/eOWVV2r9JNLExES0bdsWb775pkHH9cknn2DgwIEMHE2csdcNPqeDyEitXLkSubm56N+/P5ycnMTXo4uoZWZmIi0tTXz/1VdfoaSkBBEREZJtHr2vIicnB2+99RZ69OiBIUOGICMjA4mJidVeXqaamz17Nl5++eUaPQ/jccOHD8eff/5Z4xtda6KkpARdunRhsHwGGHvd4NcrRNVorK9XiOjp1Vhfrxg7XukgIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBzU5Dx48aOwhENFTRhAE1g4Z8OFg1CSUlZXh4sWL0Ol0+PXXX/Gf//wHLVq0aOxhEZGRy8/Px9GjR6HVauHq6oqxY8c29pCaNIYOeqrl5OTg8OHD0Ol0uH37tth++vRpBAYGNuLIiMhYlZWV4cKFC9BqtUhJSUFJSQmAhwGkfJ0XahgMHfTUKS0txa+//gqtVoszZ86IK3Gam5vDz88PGo0G7du3b+RREpGxyc7OFk9S7ty5I7a3a9cOGo0Gfn5+DBwNjKGDnho3btzA4cOHcfjwYej1erH9ueeeg0ajQe/evSWrehIRlZaWisu7nz17VjxJsbCw4ElKI2DoIKNWXFyMU6dOQafT4eLFi2K7lZUVAgMDoVara7QEOBE9W7KysqDT6ZCUlIS8vDyxvWvXrlCr1ejdu7dB17ehmmHoIKOUlpYGrVaLY8eO4f79+wAAhUIBd3d3aDQa9OzZk5dBiUiiqKgIp06dglarxeXLl8V2lUolnqQ4ODg04giJoYMMIj3vLopKS/CcjX2d93Hv3j0cO3YMWq0W6enpYrudnR3UajWCgoLQqlUrQwyXiIxASVkpkrL+gMbpOSgUijrtQxAEXL16FTqdDseOHUNhYSGAhycpHh4e0Gg08PT05EmKkWDooHpbcy4J/zoSj2Ed3PG/z4fXaltBEHDp0iXodDqcPHlSnCffvHlzeHl5QaPRoFu3bjAx4SNliJqS0rIyDNj6Ja7obyN++LvoY9+hVtsXFBSIJynXrl0T21u3bg21Wo3AwECepBghhg6qN3/HTgCA/WnncKcwH3bmLavdJjc3F0lJSdDpdLh586bY7uzsDI1GA39/f7RsWf1+iOjp1MzEBD727XFFfxsbL52oUegoKyvDpUuXoNVqcerUKXGqa/PmzdG7d2+o1Wp07dqVJylGjKGD6q17K0f0au2C1NvXsOX3ZLzp3rfSfqWlpTh79iy0Wi1+/fVXlJWVAQCUSiV8fX2h0WjQsWPHOl9mJaKnS5irDzZfPoUdV05jnt8IWJpWfmPnk57H4+LiArVaDX9/fz4M8CnB0EEGEebqg9Tb17Dp0km84aaRBIdbt26Jd5Hn5OSI7V26dIFarUafPn1gbm7eCKMmosbk79AJHazscDXvDnZf/RWjn+sj/qz8eTzlTxl+/Hk8arUaHTp04EnKU4ahgwxiZKdemHdsJ85nZ+H0nQy4WTsgOTkZWq0WFy5cEPu1bNkSAQEBUKvVcHZ2bsQRE1FjUygUCHPtg0Wn9mHTpZMY/VwfPo+niWPoIIOwVlrghQ7uiP8jFZ/sjoVL8nXcu3cPwMPC0qNHD2g0GvTq1QvNm/P/dkT00OguvfHZqf1IyvoDc75chJvnfxd/ZmVlhYCAAGg0Gj6Pp4lg9ad6u3//Po4dO4ay45egtAEuZWfC+v49tLG1RVBQENRqNWxtbRt7mERkZMqfx2OvL0GppRmO5FxDl/97Ho9arUbPnj15ktLE8F+T6kQQBFy+fBlarVac6loGwMTLGrdbmcFr7PN4TxPCu8iJSKKy5/E425oiuWszlHa2wYbJk9HGrnUjj5IaCkMH1Upubi6OHDkCnU6HGzduiO1OTk5Qq9XoaFWElee0OHz/BiYxcBARHp6kXLx4ETqdDqdOnarwPB7fwACMTY1DdnEhfiu8i35g6GiqGDqoWuVTXXU6HU6fPi2Z6urj4wONRoNOnTpBoVCga94drDynxS/XLyMjPwdtW9o07uCJqNHk5OQgKSkJhw8frvZ5PC/m/Y4154/g+0sn0a9t18YaMjUwhg56oidNde3cuTPUajV8fHwqTHXtYGWHQMfOSMr6Az9cPokpXgNlHjURNabS0lKcOXMGWq0WZ86cEU9SzM3N4evr+/CKaCXP4wlz9cGa80ewN+0scoruwUZp2RjDpwbG0EESxcXFSE5Ohk6nq/NU1zDXPkjK+gPfXz6J93sNgImCX7MQNXU3btwQT1IenerapUsXaDQa9OnTp8qprp52bdG9lSPOZ2ch/o9UjO8RKMewSWYMHQQASE9PF1d1re9U15AOnph9ZDuu5t3F0Rt/ItCxc0MOnYgaSXFxsbiq66VLl8T2ukx1LX9mx7xju/D95ZMMHU0UQ8cz7N69ezh+/Di0Wi3S0tLEdtt6TnW1NDXDiE49EXvxOL6/dIKhg6iJKZ/qevToUcmqrvWd6vpSF2/85/gepN6+hvPZWejeis/maGoYOp4xT1rVtVmzZuKqrt27d6/3VNdXXX0Qe/E4dv75Kz4OGImWpnyCINHTrHxVV51OJ051BQA7Ozuo1WoEBQXVe1VXO/OWGNSuB/amncX3l07gI7/Q+g6bjAxDxzOiqlVd1Wo1AgICDLqqa+827dHFug1+z72FHVdO47WuvgbbNxHJo6pVXb29vaFWq9GtWzeDPo8nzLUP9qadRdzvyZjpMwymJs0Mtm9qfAwdTVj5XeTlCybJuaqrQqFAeDd/nLh5FV1t7A2+fyJqONnZ2eJJyqOrurZt21ac6tpQq7oOcOkGH/sO6NfWFcWlJQwdTQxDRxN08+ZN8S7y3NxcsV3uVV3fcNfgDXdNg38OEdVf+aqu5VNdG2tV1+YmzbBt+LsN+hnUeBg6mojyu8h1Oh0uXrwotpffRa5Wq+Hk5NSIIyQiY3Tjxg1otVocOXKEq7pSg2PoeMqV30V+7Ngx3L9/H4Bh7iInoqaruLgYJ0+ehFarxeXLl8V2KysrBAYGQq1Wc1VXahD8a/QUqmzBJOD/30UeGBjIVV2JSEIQBFy9ehU6nQ7Hjh2TTHX18PCARqOBp6cnmjXjPRTUcBg6nhLlCyZptVokJydXWDBJrVYbZKorETUtBQUFOHr0KHQ6Ha5duya2t27dWjxJqe9UV6Ka4l8oI5eTk4M9e/Zgzpw5+O9//4tjx47hwYMHcHZ2xpgxY7Bw4UK8+eabcHNzY+BoYubPnw9fX19YWVnB3t4eo0aNkjya/kkSEhLEm4U7d+6MVatWVegTFxcHNzc3KJVKuLm5YevWrQ1xCNRIysrKcO7cOXzzzTf4xz/+gU2bNuHatWto3rw5/Pz8MG3aNHz88ccICQlh4GhijL1u8EqHESq/i1yn09VqwSRqWhISEhAREQFfX1+UlJTgX//6F4YMGYLffvvtidMVr1y5gpCQELz55ptYv349dDod3nvvPbRp0wYvv/wyACApKQlhYWH4+OOP8eKLL2Lr1q0YM2YMtFot/P395TxEMrDs7GwcPnwYhw8flkx1dXFxgUajgZ+fX4NNdSXjYOx1QyGUz4uiRlffBZOoYej1elhbW2PCNy4ws6z71aTie2WIeeMacnNzoVKpar39rVu3YG9vj4SEBAQHB1faZ8aMGdi+fTvOnTsntr3zzjtITU1FUlISACAsLAx6vR579uwR+7zwwgto1aoVYmNjaz0ualylpaU4ffo0tFotzp49W2Gqq0ajQfv27XmSIjND1Q2gfrXD2OoGr3Q0MkMumERPh0cDJfDwYW01CZPlz1yp6ibhpKQkDBkyRNI2dOhQREdH48GDBzA1NUVSUhKmTZtWoc/ixYtreARkDLKyssSTlLy8PLHd1dVVfB6PmZlZI46QDK0utcPY6gZDRyMQBAFpaWnQ6XQGXzCJGs6sRW/BqlndH6qWV1qIGHyEdu3aSdojIyMxd+7cKrcVBAHTp0+HRqOBh4fHE/tlZWXBwcFB0ubg4ICSkhLcvn0bTk5OT+yTlZVVuwMi2RUVFeHkyZPQ6XSSqa4qlUqc6vr4vy01rvrWDaDutcMY6wb/qslIjgWTyPilp6dLLpHW5CrHpEmTxEvo1Xn8Mnr55fZH2yvrw8vvxkkQBPz555/Q6XQ4fvy45CTF09MTarWaU12fEbWtHcZYNxg6GlhjLJhExk2lUtXqe9n3338f27dvR2JiIlxcXKrs6+joWOHM4+bNm2jevDns7Oyq7MMzZOOSn58vPo8nIyNDbG/Tpo041dXGxqbxBkiyq03tMNa6wdDRQKpbMMnPz8+gq7pS0yMIAt5//31s3boVhw4dQqdOnardJjAwEDt27JC07du3Dz4+PjA1NRX77N+/X/L97L59+xAUFGTYA6BaKysrw4ULF6DT6ZCcnCw5Senduzc0Gg1cXV15kkJPZOx1g6HDgIxlwSRqGiIiIrBhwwbEx8fDyspKPMuwtraGhYUFAGDmzJnIyMjA2rVrATy843zZsmWYPn063nzzTSQlJSE6Olpyd/mUKVMQHByMhQsXYuTIkYiPj8eBAwdqdAmWGsbdu3fFk5Q7d+6I7e3atYNareZUV6oxY68bDB0GwAWTqCGsXLkSANC/f39J++rVqzFhwgQAQGZmJtLS0sSfderUCbt378a0adOwfPlyODs7Y8mSJeJcewAICgrCxo0bMXv2bMyZMwddunTBpk2b+IwOmZWUlOD06dPQ6XSSqa4WFhaSqa5EtWHsdYPP6aijoqIicaorF0xq2srn21/s+u96z17pevGjOj+ng5qGzMxM6HQ6HDlyRDLVtWvXrlCr1ejduzenujYBhqobQNOqHbzSUQvVLZhUPtWVd5ET0aMKCwvFqa6///672K5SqRAUFISgoCDeyEvPBIaOGuCCSURUW+VTXbVaLY4fP46ioiIAgImJiTjV1cPDgycp9Exh6HiC6u4iV6vV6Nq1K+8iJyKJ/Px8HDlyBDqdDtevXxfb7e3txZMUa2vrRhwhUeNh6HgMF0wiotoqKyvD+fPnodVqkZqaKp6kmJqaSqa6cuYaPesYOvBwqmtqamqFu8i5YBIRVeXu3bvi+iePTnVt3769ONXV0tKyEUdIZFye6dDBBZOIqLZKSkqQmpoKrVaLc+fOSaa6+vv7Q61Wc6or0RM8c6GDCyYRUV1cv35dnOqan58vtnft2hUajQbe3t48SSGqxjMROqpaMMnDwwMajYYLJhFRBYWFhThx4gR0Oh3++OMPsd3a2lo8SbG3t2/EERI9XZp06MjPzxenuj6+YFJQUBCnuhJRBYIg4MqVK9BqtThx4gSnuhIZUJMLHeVTXbVaLVJSUrhgEhHVSPlUV61Wi8zMTLGdU12JDKfJhA4umEREtVVWVoZz586JU11LS0sBPJzq2qdPH6jVak51JTKgpzp0cMEkIqqLO3fu4PDhw9DpdMjOzhbb27dvLz6Pp3xFTiIynKcydHDBJCKqrQcPHuD06dMVprpaWlqKJynt2rVr5FESNW1PTejggklEVBcZGRniSUpBQYHY3q1bN2g0Gnh5efEkhUgmRh06uGASEdVF+VRXrVaLK1euiO02NjbiVNc2bdo04giJnk1GGTqetGBSmzZtoNFoeBc5EVUgCAL++OMP6HS6ClNde/bsCY1GAzc3N56kEDUiowkdXDCJiOoiLy9PPEl5dKqrg4MD1Go1AgICeJJCZCQaPXRwwSQiqq2ysjL89ttv0Ol0Faa6+vj4QK1W47nnnuNJCpGRaZTQwQWTiKgubt++jcOHD+Pw4cOSqa4dOnSARqOBr68vp7oSGTFZQwcXTCKi2nrw4AFSUlKg0+lw/vx5yVTX8pMUTnUlejo0eOh40l3kXDCJiKqSkZEBrVaLo0ePSqa6du/eHWq1Gt7e3jA1NW3EERJRbTVI6OCCSURUF/fv3xdPUv7880+x3cbGRnweD6e6Ej29DBo6uGASEdWWIAj4/fffxamuxcXFAB6epPTq1QtqtRru7u5cpJGoCTBI6CgsLMTatWuRkpLCBZOIqMZSU1OxZcsWZGVliW0ODg7QaDQICAiASqVqxNERkaEZJHQolUpcv34dpaWl4oJJvr6+nOpKRFUyMTFBVlYWzMzM0KdPH2g0GnTp0oUnKURNlEFCh0KhwKuvvooWLVrwLnIiqjF3d3eMGzcOvXv35lRXomeAwe7p6N69u6F2RUTPCBMTE6jV6sYeBhHJhHdmERERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAZqcTERIwYMQLOzs5QKBTYtm1blf0nTJgAhUJR4eXu7i72iYmJqbRPYWFhAx8NEcnFmGsHQweRkSooKECvXr2wbNmyGvWPiopCZmam+EpPT4etrS1eeeUVST+VSiXpl5mZCXNz84Y4BCJqBMZcOwy6tD0RGc6wYcMwbNiwGve3traGtbW1+H7btm3Izs7G66+/LumnUCjg6OhosHESkXEx5trBKx1EMtPr9ZJXUVFRg3xOdHQ0Bg0ahA4dOkja8/Pz0aFDB7i4uCA0NBTJyckN8vlEZFhNoXbwSgdRDS0b2A1KpWWdty8qugdcRIWVmCMjIzF37tx6jk4qMzMTe/bswYYNGyTt3bt3R0xMDDw9PaHX6xEVFQW1Wo3U1FS4uroadAxEVP+6ATSt2sHQQSSz9PR0qFQq8b1SqTT4Z8TExMDGxgajRo2StAcEBCAgIEB8r1ar0bt3byxduhRLliwx+DiIyHCaQu1g6CCSmUqlkhQOQxMEAd9++y3Cw8NhZmZWZV8TExP4+vri0qVLDTYeIjKMplA7eE8HUROTkJCAy5cvY+LEidX2FQQBKSkpcHJykmFkRGTM5KgdvNJBZKTy8/Nx+fJl8f2VK1eQkpICW1tbtG/fHjNnzkRGRgbWrl0r2S46Ohr+/v7w8PCosM958+YhICAArq6u0Ov1WLJkCVJSUrB8+fIGPx4ikocx1w6GDiIjdeLECQwYMEB8P336dADA+PHjERMTg8zMTKSlpUm2yc3NRVxcHKKioirdZ05ODt566y1kZWXB2toa3t7eSExMhJ+fX8MdCBHJyphrh0IQBKGWx0P0TNHr9bC2tsbkdzfVe/bKkpVhyM3NbdDvZYmo8RmqbgBNq3bwng4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBZKQSExMxYsQIODs7Q6FQYNu2bVX2P3ToEBQKRYXX+fPnJf3i4uLg5uYGpVIJNzc3bN26tQGPgojkZsy1g6GDyEgVFBSgV69eWLZsWa22u3DhAjIzM8WXq6ur+LOkpCSEhYUhPDwcqampCA8Px5gxY3D06FFDD5+IGokx147mtepNRLIZNmwYhg0bVuvt7O3tYWNjU+nPFi9ejMGDB2PmzJkAgJkzZyIhIQGLFy9GbGxsfYZLREbCmGsHr3QQyUyv10teRUVFBt2/t7c3nJycMHDgQBw8eFDys6SkJAwZMkTSNnToUBw+fNigYyAiw2sKtYNXOohqaHzOq2hppqjz9vnFApYAaNeunaQ9MjISc+fOrd/gADg5OeHrr79Gnz59UFRUhHXr1mHgwIE4dOgQgoODAQBZWVlwcHCQbOfg4ICsrKx6fz4RVVTfugE0rdrB0EEks/T0dKhUKvG9Uqk0yH67deuGbt26ie8DAwORnp6Ozz//XCwcAKBQSAugIAgV2ojI+DSF2sGvV4hkplKpJC9DFY7KBAQE4NKlS+J7R0fHCmcmN2/erHAGQ0TGpynUDoYOoiYsOTkZTk5O4vvAwEDs379f0mffvn0ICgqSe2hEZMQaqnbw6xUiI5Wfn4/Lly+L769cuYKUlBTY2tqiffv2mDlzJjIyMrB27VoAD+8u79ixI9zd3VFcXIz169cjLi4OcXFx4j6mTJmC4OBgLFy4ECNHjkR8fDwOHDgArVYr+/ERUcMw5trB0EFkpE6cOIEBAwaI76dPnw4AGD9+PGJiYpCZmYm0tDTx58XFxfjwww+RkZEBCwsLuLu7Y9euXQgJCRH7BAUFYePGjZg9ezbmzJmDLl26YNOmTfD395fvwIioQRlz7VAIgiDU8/iImjS9Xg9ra2ucfE1R79krfWIF5ObmSm4GI6Kmx1B1A2hatYP3dBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iI5WYmIgRI0bA2dkZCoUC27Ztq7L/li1bMHjwYLRp0wYqlQqBgYH48ccfJX1iYmKgUCgqvAoLCxvwSIhITsZcOxg6iIxUQUEBevXqhWXLltWof2JiIgYPHozdu3fj5MmTGDBgAEaMGIHk5GRJP5VKhczMTMnL3Ny8IQ6BiBqBMdeO5rXqTUSyGTZsGIYNG1bj/osXL5a8//TTTxEfH48dO3bA29tbbFcoFHB0dDTUMInIyBhz7eCVDiKZ6fV6yauoqKhBPqesrAx5eXmwtbWVtOfn56NDhw5wcXFBaGhohbMZIjJOTaF28EoHUQ2FaqbAxEJZ5+3L7hcBsYvRrl07SXtkZCTmzp1bz9FV9MUXX6CgoABjxowR27p3746YmBh4enpCr9cjKioKarUaqampcHV1NfgYiJ519a0bQNOqHQwdRDJLT0+HSqUS3yuV9StIlYmNjcXcuXMRHx8Pe3t7sT0gIAABAQHie7Vajd69e2Pp0qVYsmSJwcdBRIbTFGoHQweRzFQqlaRwGNqmTZswceJEbN68GYMGDaqyr4mJCXx9fXHp0qUGGw8RGUZTqB28p4OoCYmNjcWECROwYcMGDB8+vNr+giAgJSUFTk5OMoyOiIyVXLWDVzqIjFR+fj4uX74svr9y5QpSUlJga2uL9u3bY+bMmcjIyMDatWsBPCwa48aNQ1RUFAICApCVlQUAsLCwgLW1NQBg3rx5CAgIgKurK/R6PZYsWYKUlBQsX75c/gMkogZhzLWDVzqIjNSJEyfg7e0tTlmbPn06vL298dFHHwEAMjMzkZaWJvb/6quvUFJSgoiICDg5OYmvKVOmiH1ycnLw1ltvoUePHhgyZAgyMjKQmJgIPz8/eQ+OiBqMMdcOhSAIggGOkajJ0uv1sLa2htPyqfWevZIZsRi5ubkN+r0sETU+Q9UNoGnVDl7pICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgWDB1EREQkC4YOIiIikgVDBxEREcmCoYOIiIhkwdBBREREsmDoICIiIlkwdBAREZEsGDqIiIhIFgwdREREJAuGDiIiIpIFQwcRERHJgqGDiIiIZMHQQURERLJg6CAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iI5WYmIgRI0bA2dkZCoUC27Ztq3abhIQE9OnTB+bm5ujcuTNWrVpVoU9cXBzc3NygVCrh5uaGrVu3NsDoiaixGHPtYOggMlIFBQXo1asXli1bVqP+V65cQUhICPr27Yvk5GTMmjULkydPRlxcnNgnKSkJYWFhCA8PR2pqKsLDwzFmzBgcPXq0oQ6DiGRmzLVDIQiCUKstiJ4xer0e1tbWcFo+FSYWyjrvp+x+ETIjFiM9PR0qlUpsVyqVUCqr3q9CocDWrVsxatSoJ/aZMWMGtm/fjnPnzolt77zzDlJTU5GUlAQACAsLg16vx549e8Q+L7zwAlq1aoXY2Ng6HhkRPc5QdQNoWrWjeY17Ej3jjv3lA8l/8LWl1+vRLmIx2rVrJ2mPjIzE3Llz6zm6h2ciQ4YMkbQNHToU0dHRePDgAUxNTZGUlIRp06ZV6LN48eJ6fz4RVVTfugE0rdrB0EFUDTMzMzg6Olb4D74uHB0dkZqaCnNzc7GtujOVmsrKyoKDg4OkzcHBASUlJbh9+zacnJye2CcrK8sgYyCihwxZN4CmUzsYOoiqYW5ujitXrqC4uLje+zIzM5MUDUNTKBSS9+Xfnj7aXlmfx9uIqH4MWTeAplM7GDqIasDc3LxB/4M3BEdHxwpnHTdv3kTz5s1hZ2dXZZ/Hz2CIqP6ehroByFs7OHuFqIkIDAzE/v37JW379u2Dj48PTE1Nq+wTFBQk2ziJyLjIWjsEIjJKeXl5QnJyspCcnCwAEP773/8KycnJwtWrVwVBEIR//vOfQnh4uNj/jz/+ECwtLYVp06YJv/32mxAdHS2YmpoKP/zwg9hHp9MJzZo1ExYsWCCcO3dOWLBggdC8eXPhyJEjsh8fETUMY64dDB1ERurgwYMCgAqv8ePHC4IgCOPHjxf69esn2ebQoUOCt7e3YGZmJnTs2FFYuXJlhf1u3rxZ6Natm2Bqaip0795diIuLk+FoiEguxlw7+JwOIiIikgXv6SAiIiJZMHQQERGRLBg6iIiISBYMHURERCQLhg4iIiKSBUMHERERyYKhg4iIiGTB0EFERESyYOggIiIiWTB0EBERkSwYOoiIiEgW/w95zkye3IEd2AAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -1529,12 +1561,12 @@ "output_type": "stream", "text": [ "angles_gdf len 4\n", - "Interior angles found: [89.53084497276808, 89.57504791798526]\n", - "Interior angles found: [89.58581817377714, 89.63002111899432]\n", - "Final angles found: [89.53084497276808, 89.58581817377714]\n", + "Interior angles found: [np.float64(89.53084497276808), np.float64(89.57504791798526)]\n", + "Interior angles found: [np.float64(89.58581817377714), np.float64(89.63002111899432)]\n", + "Final angles found: [np.float64(89.53084497276808), np.float64(89.58581817377714)]\n", "connectivity: 2\n", "Counter values: dict_values([2, 2])\n", - "angles: [89.53084497276808, 89.58581817377714]\n", + "angles: [np.float64(89.53084497276808), np.float64(89.58581817377714)]\n", "(1, 3) added\n", "**************************************************************\n", " \n", @@ -1548,7 +1580,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGTCAYAAABwJ4sYAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAABQUElEQVR4nO3dd1hUV/4G8HdoQ++CSBGkKSqggDQ7logaNtHYElvMrmaTXzR9dRM1iVmNKRtTNNmN2Zii2I3GaGLsQUAGBAELxQICooIUUVDg/v4gTBgBKXfgzsj7eR6eJxzu3PnOYA7vnXPOPTJBEAQQERERiaAjdQFERESk/RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiItsXLlSshkMixatOiBxx09ehQBAQEwNDREr1698MUXX3ROgUSkcTqz32CgINICCQkJ+M9//gNfX98HHnfx4kVERkZiyJAhOHXqFJYsWYIXXngB27dv76RKiUhTdHa/wUBBpOFu3bqFJ598Ev/9739hZWX1wGO/+OILuLi44OOPP0afPn3wzDPP4Omnn8YHH3zQSdUSkSaQot/QE1MwUVdRWVmJu3fvij6PIAiQyWQqbXK5HHK5vNnHPPfccxg/fjxGjRqFFStWPPD8sbGxGDNmjErb2LFjsX79ety7dw/6+vrtL56I2kRd/QbQ9r5Din6DgYKoBZWVlbC2tsadO3dEn8vU1BS3bt1SaVu2bBmWL1/e5PHR0dFISkpCQkJCq85/9epV2Nvbq7TZ29ujuroaN27cgIODQ7vqJqK2UWe/AbSt75Cq32CgIGrB3bt3cefOHcyYMQMGBgaizrNx40bk5ubC3Nxc2d7cFUZubi4WLlyIX3/9FYaGhq1+nvuvYgRBaLKdiDqOuvqN+nO1tu+Qst9goCBqJQMDA9EdAwCYm5urdArNSUxMxLVr1xAQEKBsq6mpwbFjx/DZZ5+hqqoKurq6Ko/p3r07rl69qtJ27do16OnpwcbGRnTtRNQ26uo3gNb1HVL2GwwURBoqIiICqampKm1z585F79698frrrzfqFAAgNDQUe/bsUWn79ddfERgYyPkTRF2AlP0GAwWRhjIzM0O/fv1U2kxMTGBjY6NsX7x4MfLy8vDtt98CABYsWIDPPvsML730Ev76178iNjYW69evx6ZNmzq9fiLqfFL2G1w2SqTFCgoKkJOTo/zezc0NP//8M44cOQJ/f3+88847+OSTTzBp0iQJqyQiTdJR/YZMqJ95QURNKisrg4WFBebMmSN6UuY333yD0tLSVs2hICLtpa5+A9CevoOfUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERiaYndQFE2mKwxQEYy9ufwW9X1eIb9ZVDRFpAbL8BaE/fwU8oiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6AgIiIi0RgoiIiISDQGCiIiIhKNgYKIiIhEY6Ag0lDr1q2Dr68vzM3NYW5ujtDQUOzbt++Bj/nhhx/g5+cHY2NjODg4YO7cuSgqKuqkiolIalL2GwwURBrKyckJq1atgkKhgEKhwMiRIxEVFYX09PQmj//9998xa9YszJs3D+np6di6dSsSEhLwzDPPdHLlRCQVKfsNPbHFE1HHmDhxosr37777LtatW4e4uDj07du30fFxcXFwdXXFCy+8AABwc3PD/PnzsXr16k6pl4ikJ2W/wU8oiDpZWVmZyldVVVWLj6mpqUF0dDQqKioQGhra5DFhYWG4cuUKfv75ZwiCgMLCQmzbtg3jx49X90sgIgm0te/o7H6DgYKokzk7O8PCwkL5tXLlymaPTU1NhampKeRyORYsWICdO3fCx8enyWPDwsLwww8/YOrUqTAwMED37t1haWmJTz/9tKNeChF1otb2HVL1GwwURJ0sNzcXpaWlyq/Fixc3e6y3tzeSk5MRFxeHZ599FrNnz8aZM2eaPPbMmTN44YUXsHTpUiQmJmL//v24ePEiFixY0FEvhYg6UWv7Dqn6DbUGik8++QQymQz9+vVr9hiZTIbly5crvz9y5AhkMhmOHDki+vl//vlnlXOr0zfffAOZTAaFQtEh51e3jRs34uOPP5a6jEbU+ftu6PLly3j66afRo0cPyOVyODo64rHHHlPrc6hL/ezr+i+5XN7ssQYGBvDw8EBgYCBWrlwJPz8/rFmzpsljV65cifDwcLz66qvw9fXF2LFjsXbtWnz99dcoKCjoqJdDRJ2ktX2HVP2GWgPF119/DQBIT09HfHy8Ok/dKj///DPeeuutTn9eTaSpgaIjpKWlISAgAGlpafjggw9w4MABfPTRR7CyspK6NLUTBKHZcdPbt29DR0f1f2ldXV3l44ioa+qsfkNtqzwUCgVSUlIwfvx47N27F+vXr0dwcLC6Tq92giCgsrISRkZGUpdCIgiCgJkzZ8LZ2RnHjx9XSexTp06VsDLxlixZgnHjxsHZ2Rnl5eWIjo7GkSNHsH//fgDA4sWLkZeXh2+//RZA3ezuv/71r1i3bh3Gjh2LgoICLFq0CIMGDUKPHj2kfClE1Emk7DfU9gnF+vXrAQCrVq1CWFgYoqOjcfv2bXWdHrdv38Yrr7wCNzc3GBoawtraGoGBgdi0aRMAYM6cOfj8888B1A2r1H9dunRJ2fb888/jiy++QJ8+fSCXy7FhwwYAdetwIyIiYGZmBmNjY4SFhWHv3r0t1lRQUICAgAB4enoiMzMTQN0s3Po6DQwM4OjoiEWLFqGiokLlsVu3bkVwcDAsLCxgbGyMXr164emnn27xOT///HMMHToUdnZ2MDExQf/+/bF69Wrcu3dPeczw4cOxd+9eXL58WeW9eBBXV1dMmDAB+/fvx8CBA2FkZITevXsrP3VqKC0tDVFRUbCysoKhoSH8/f2V72VD586dwyOPPAJjY2PY2tpiwYIFKC8vb/L5f/vtN0RERMDc3BzGxsYIDw/HwYMHW3w/jh07huTkZCxatOiBQwfaqLCwEDNnzoS3tzciIiIQHx+P/fv3Y/To0QDq/v3l5OQoj58zZw4++ugjfPbZZ+jXrx+eeOIJeHt7Y8eOHVK9BCLqZFL2G2r5hOLOnTvYtGkTgoKC0K9fPzz99NN45plnsHXrVsyePVsdT4GXXnoJ3333HVasWIEBAwagoqICaWlpyrt5vfnmm6ioqMC2bdsQGxurfJyDg4Pyv3ft2oXjx49j6dKl6N69O+zs7HD06FGMHj0avr6+WL9+PeRyOdauXYuJEydi06ZNzV7lpqWlITIyEk5OToiNjYWtrS1u376NYcOG4cqVK1iyZAl8fX2Rnp6OpUuXIjU1Fb/99htkMhliY2MxdepUTJ06FcuXL4ehoSEuX76MQ4cOtfg+ZGdnY8aMGcrAkpKSgnfffRfnzp1T/vFfu3Yt/va3vyE7Oxs7d+5s9XuckpKCl19+Gf/4xz9gb2+Pr776CvPmzYOHhweGDh0KADh//jzCwsJgZ2eHTz75BDY2Nvj+++8xZ84cFBYW4rXXXgNQ94962LBh0NfXx9q1a2Fvb48ffvgBzz//fKPn/f777zFr1ixERUVhw4YN0NfXx5dffomxY8fil19+QURERLM1Hzt2DABgZmaGyMhIHDp0CHp6ehg+fDg++OAD9O7du9WvX9PUh/TmfPPNN43a/u///g//93//10EVEZGmk7LfUEug2LZtG0pLSzFv3jwAdR81L1q0COvXr1dboIiJicGYMWPw4osvKtsarpN1d3eHvb09ACAkJKTJc9y6dQupqakqY+uhoaGwsrLCkSNHYGpqCgCYMGEC/P398corr2DKlCmNru5/++03TJo0CWPGjMF3330HQ0NDAHWTUk+fPo34+HgEBgYCACIiIuDo6IjJkydj//79GDduHE6cOAFBEPDFF1/AwsJCed45c+a0+D589NFHyv+ura3FkCFDYGNjg7lz5+LDDz+ElZUVfHx8YGlpCblc3ux70ZQbN24gJiYGLi4uAIChQ4fi4MGD2LhxozJQLF++HHfv3sXhw4fh7OwMAIiMjERJSQneeustzJ8/HxYWFvj3v/+N69ev49SpU/Dz8wMAjBs3DmPGjFFJx7dv38bChQsxYcIElfATGRmJgQMHYsmSJQ+cj5OXlwcAmDt3Lp544gns3bsXBQUFeOONNzBkyBCcPn1aJVQSEVHHUMuQx/r162FkZIRp06YBAExNTfHEE0/g+PHjyqEAsQYNGoR9+/bhH//4B44cOYI7d+60+RwjR45UCRMVFRWIj4/H5MmTlWECqJuQMnPmTFy5cgXnz59XOceGDRsQGRmJZ555Blu2bFGGCQD46aef0K9fP/j7+6O6ulr5NXbsWJWVDUFBQQCAKVOmYMuWLco/iq1x6tQpPProo7CxsYGuri709fUxa9Ys1NTUICMjo83vSUP+/v7KMAEAhoaG8PLywuXLl5Vthw4dQkREhDJM1JszZw5u376t/HTo8OHD6Nu3rzJM1JsxY4bK9ydOnEBxcTFmz56t8p7V1tbikUceQUJCQqPhooZqa2sB1AXDr776ChEREXjqqaewa9cu3LhxQzkMRkREHUt0oMjKysKxY8cwfvx4CIKAkpISlJSUYPLkyQDQ5Bh8e3zyySd4/fXXsWvXLowYMQLW1tb4y1/+0qbAcv+V6s2bNyEIQpNXsPWTUe7fICU6OhpGRkZ45plnGn1yUVhYiNOnT0NfX1/ly8zMDIIg4MaNGwDqrvx37dqF6upqzJo1C05OTujXr59yPkhzcnJyMGTIEOTl5WHNmjU4fvw4EhISlH802xOyGrKxsWnUJpfLVc5bVFTUqverqKgI3bt3b3Tc/W2FhYUAgMmTJzd639577z0IgoDi4uIWax47dqxKu7+/PxwcHJCUlNTsY4mISH1ED3l8/fXXEAQB27Ztw7Zt2xr9fMOGDVixYoVyGUp7mZiY4K233sJbb72FwsJC5acVEydOxLlz51p1jvsDgJWVFXR0dJpca5ufnw8AsLW1VWn/4Ycf8Oabb2LYsGH49ddf4e/vr/yZra0tjIyMmg1RDc8VFRWFqKgoVFVVIS4uDitXrsSMGTPg6ura7C1Sd+3ahYqKCuzYsQM9e/ZUticnJz/wdauTjY1Nq94vGxsbXL16tdFx97fVH//pp582OzxTP5TVFF9f32Z/JghCo+VQRETUMUT1tjU1NdiwYQPc3d1x+PDhRl8vv/wyCgoKWtw6ta3s7e0xZ84cTJ8+HefPn1euJqmf5d/aK3UTExMEBwdjx44dKo+pra3F999/DycnJ3h5eak8xtraGr/99hv69OmDESNGIC4uTvmzCRMmIDs7GzY2NggMDGz05erq2qgGuVyOYcOG4b333gNQN6TRnPpA1HA1gyAI+O9//9vkecV+YtGUiIgIHDp0SBkg6n377bcwNjZWhoIRI0YgPT0dKSkpKsdt3LhR5fvw8HBYWlrizJkzTb5ngYGBMDAwaLaecePGwdjYuNG/saSkJFy9erVNc0iIiKj9RH1CsW/fPuTn5+O9997D8OHDG/28X79++Oyzz7B+/XpMmDBBzFMhODgYEyZMgK+vL6ysrHD27Fl89913CA0NhbGxMQCgf//+AID33nsP48aNg66uLnx9fR/4B2nlypUYPXo0RowYgVdeeQUGBgZYu3Yt0tLSsGnTpiaXW5qZmWH//v14/PHHMXr0aOzevRsjRozAokWLsH37dgwdOhQvvvgifH19UVtbi5ycHPz66694+eWXERwcjKVLl+LKlSuIiIiAk5MTSkpKsGbNGujr62PYsGHN1jp69GgYGBhg+vTpeO2111BZWYl169bh5s2bjY7t378/duzYgXXr1iEgIAA6OjrKiaJiLFu2DD/99BNGjBiBpUuXwtraGj/88AP27t2L1atXKyeZLlq0CF9//TXGjx+PFStWKFd53P9pkqmpKT799FPMnj0bxcXFmDx5Muzs7HD9+nWkpKTg+vXrWLduXbP1WFpa4u2338Yrr7yiDJlXr17Fm2++CRcXF/z9738X/ZqJiKhlogLF+vXrYWBggLlz5zb5c1tbWzz22GPYtm0bCgsLH/jRdUtGjhyJ3bt349///jdu374NR0dHzJo1C//85z+Vx8yYMQMxMTFYu3Yt3n77bQiCgIsXLzb5yUC9YcOG4dChQ1i2bBnmzJmD2tpa+Pn5Yffu3Q8MQUZGRvjxxx8xY8YMREZGYvv27YiMjMTx48exatUq/Oc//8HFixdhZGQEFxcXjBo1SllHcHAwFAoFXn/9dVy/fh2WlpYIDAzEoUOHmtxetl7v3r2xfft2vPHGG3j88cdhY2ODGTNm4KWXXsK4ceNUjl24cCHS09OxZMkSlJaWQhAEtdwt0dvbGydOnMCSJUvw3HPP4c6dO+jTpw/+97//qaxS6d69O44ePYqFCxfi2WefhbGxMR577DF89tlniIqKUjnnU089BRcXF6xevRrz589HeXk57Ozs4O/v36qVLy+//DIsLCywZs0abNq0CWZmZnjkkUewatUqWFtbi37NRETUMpnAe/ISPVBZWRksLCzw1UJHGMvbP0p4u6oWz6zJQ2lpKczNzdVYIRFpGnX1G4D29B2csUZERESiMVAQERGRaAwURCRafHw8HnvsMbi4uEAul8Pe3h6hoaF4+eWXVY5bu3Ztk7f+VYc5c+ao3KBOSvUb1TW8Kdwnn3yCkJAQ2NraQi6Xw8XFBdOmTUN6erranveNN96ATCZDv379VNrv3bsHd3f3DtmB+F//+hd27dql9vOKtXz58hb3MGqP33//HZGRkbCysoKRkRE8PT3xzjvvqP15tJHadhsletgNGZgPM+P2d1Dltx/O6Up79+7Fo48+iuHDh2P16tVwcHBAQUEBFAoFoqOj8eGHHyqPXbt2LWxtbVs12VZbCYKARYsW4a9//avK/WKKioowbtw4+Pn5wcrKChcuXMCqVasQHByMxMREeHt7i3re5ORkfPDBB01OftfX18fSpUvx4osvYubMmU3exK69/vWvf2Hy5Mn4y1/+orZzaqqNGzdi5syZmDJlCr799luYmpoiOzu70TL6hsT2G4D29B0MFEQkyurVq+Hm5oZffvkFenp/dinTpk3D6tWr233ee/fuQSaTqZxTG+zfvx9JSUmN7rny1ltvqXw/bNgwhISEwMfHBz/88APefvvtdj9ndXU15s6di/nz5yMlJUV5V96Gpk+fjpdeeglffvkllixZ0u7n6qry8vLwt7/9DfPnz8fatWuV7SNGjJCwKs3CIQ8iEqWoqAi2trZN/uFveKdSV1dXpKen4+jRo5DJZJDJZMql1EeOHIFMJsN3332Hl19+GY6OjpDL5cjKygJQd0dePz8/GBoawtraGo899hjOnj3bYm0xMTGwtbXFhAkTlHvCZGZmYsaMGbCzs4NcLkefPn0a7flSW1uLFStWwNvbG0ZGRrC0tISvry/WrFnT4nOuW7cOQUFBrfrEoVu3bgAgOjStWrUKxcXFePfdd5s9xsDAAFOnTsV//vOfFpeQV1ZW4uWXX4a/vz8sLCxgbW2N0NBQ/PjjjyrHyWQyVFRUYMOGDcrfaVP3JKp36dIlyGQyfPDBB/joo4/g5uYGU1NThIaGqtwksN7u3buV9xoyMzPD6NGjVXaTrrd37174+/tDLpfDzc0NH3zwQZPPLwgC1q5dC39/fxgZGcHKygqTJ0/GhQsXHvh+AMBXX32FiooKvP766y0e21UxUBCRKKGhoYiPj8cLL7yA+Ph43Lt3r8njdu7ciV69emHAgAGIjY1FbGysyg6zALB48WLk5OTgiy++wJ49e2BnZ4eVK1di3rx56Nu3L3bs2IE1a9bg9OnTCA0NfeBePlu2bEFERASmTJmCH3/8ESYmJjhz5gyCgoKQlpaGDz/8ED/99BPGjx+PF154QeUThNWrV2P58uWYPn069u7di82bN2PevHkoKSl54Htx9+5d/Pbbbw+8aq2pqUFVVRXOnTuHZ555BnZ2ds3ey6c1zpw5gxUrVmDdunUtziEZPnw4Ll++jLS0tAceV1VVheLiYrzyyivYtWsXNm3ahMGDB+Pxxx/Ht99+qzwuNjYWRkZGiIyMVP5OG169N+fzzz/HgQMH8PHHH+OHH35ARUUFIiMjUVpaqjxm48aNiIqKgrm5OTZt2oT169fj5s2bGD58OH7//XflcQcPHkRUVBTMzMwQHR2N999/H1u2bMH//ve/Rs87f/58LFq0CKNGjcKuXbuwdu1apKenIywsTLmvUHOOHTsGa2trnDt3Dv7+/tDT04OdnR0WLFiAsrKyFl9zlyAQ0QOVlpYKAITzG2RC/laddn+d3yATAAilpaVSvyS1unHjhjB48GABgABA0NfXF8LCwoSVK1cK5eXlKsf27dtXGDZsWKNzHD58WAAgDB06VKX95s2bgpGRkRAZGanSnpOTI8jlcmHGjBnKttmzZwsmJiaCIAjCqlWrBF1dXeG9995TedzYsWMFJyenRr+D559/XjA0NBSKi4sFQRCECRMmCP7+/m17IwRBiI+PFwAI0dHRzR4jl8uV75WXl5dw5syZNj9PvZqaGiE4OFiYPn26sm3YsGFC3759mzw+MzNTACCsW7euTc9TXV0t3Lt3T5g3b54wYMAAlZ+ZmJgIs2fPbtV5Ll68KAAQ+vfvL1RXVyvbT548KQAQNm3apHxdPXr0EPr37y/U1NQojysvLxfs7OyEsLAwZVtwcLDQo0cP4c6dO8q2srIywdraWmj4Jy42NlYAIHz44YcqNeXm5gpGRkbCa6+99sDavb29BUNDQ8HMzEz417/+JRw+fFhYvXq1YGRkJISHhwu1tbUqx6ur39CmvoOfUBCRKDY2Nsqdb1etWoWoqChkZGRg8eLF6N+/f5Pj+c2ZNGmSyvexsbG4c+dOo0mczs7OGDlyJA4ePKjSLggC5s+fj2XLlmHjxo147bXXlD+rrKzEwYMH8dhjj8HY2BjV1dXKr8jISFRWVio/dh80aBBSUlLw97//Hb/88kurr0DrJ+fZ2dk1e8yJEycQGxuL77//HmZmZsp9b9rjo48+QmZmZqtXb9TXlZeX1+KxW7duRXh4OExNTaGnpwd9fX2sX7++VUNNLRk/frzKhpH1m/zVr4o5f/488vPzMXPmTJVhM1NTU0yaNAlxcXG4ffs2KioqkJCQgMcffxyGhobK48zMzDBx4kSV5/zpp58gk8nw1FNPqfzuu3fvDj8/Pxw5cuSBNdfW1qKyshJLlizB4sWLMXz4cLz66qtYuXIlYmJiGv1b7IoYKIhILQIDA/H6669j69atyM/Px4svvohLly61aWKmg4ODyvdFRUVNtgNAjx49lD+vd/fuXWzevBl9+/ZtdDv6oqIiVFdX49NPP4W+vr7KV2RkJAAow8/ixYvxwQcfIC4uDuPGjYONjQ0iIiKgUCgeWH/9hnwN/7jdb+DAgQgJCcGTTz6Jw4cPQxCEdk2SzMnJwdKlS7Fs2TIYGBigpKQEJSUlqK6uRm1tLUpKShptEFhfV0sbB+7YsQNTpkyBo6Mjvv/+e8TGxiIhIQFPP/00Kisr21zr/e5fZXL/xo4t/d5ra2tx8+ZN3Lx5E7W1tejevXuj4+5vKywshCAIsLe3b/T7j4uLazH41tc8duxYlfb6f2dJSUkPfHxXoF3Tp4lIK+jr62PZsmX497//3eJ4fUP33zegvhMvKChodGx+fj5sbW1V2uRyOQ4fPoyxY8di1KhR2L9/P6ysrAAAVlZW0NXVxcyZM/Hcc881+fxubm4A6iZJvvTSS3jppZdQUlKC3377DUuWLMHYsWORm5ur3JDwfvX1FBcXt+r1mpmZoXfv3sjIyGjV8Q1duHABd+7cwcKFC7Fw4cJGP7eyssLChQtVPr2or+v+9+1+33//Pdzc3LB582aV30lVVVWb62yPln7vOjo6sLKygiAIkMlkuHr1aqPj7m+ztbWFTCZT3iPkfk21NeTr69vkxFHhjwmuDT9J6ar4DhCRKE11+gCUH4336NFD2SaXy1u8Om4oNDQURkZG+P7771Xar1y5gkOHDiEiIqLRYwYMGICjR4/iypUrGD58OK5duwYAMDY2xogRI3Dq1Cn4+voiMDCw0VdT92ewtLTE5MmT8dxzz6G4uBiXLl1qtt4+ffoAALKzs1v1+m7cuIHU1FR4eHi06viG/P39cfjw4UZffn5+cHV1xeHDh/H888+rPKZ+NYOPj88Dzy2TyWBgYKASJq5evdpolQfQ9t9pa3h7e8PR0REbN25UWZFSUVGB7du3K1d+mJiYYNCgQdixY4fKJyfl5eXYs2ePyjknTJgAQRCQl5fX5O++frfq5tQPx+3bt0+l/eeffwYAhISEiHrNDwN+QkFEoowdOxZOTk6YOHEievfujdraWiQnJ+PDDz+EqampytVz//79ER0djc2bN6NXr14wNDR8YEduaWmJN998E0uWLMGsWbMwffp0FBUV4a233oKhoSGWLVvW5OP69OmD48ePY9SoURg6dCh+++03ODk5Yc2aNRg8eDCGDBmCZ599Fq6urigvL0dWVhb27NmDQ4cOAQAmTpyIfv36ITAwEN26dcPly5fx8ccfo2fPnvD09Gy2XicnJ/Tq1QtxcXF44YUXlO2lpaUYPXo0ZsyYAU9PTxgZGSEjIwNr1qxBVVVVo9cxfPhwHD169IHLOy0tLZtcomlpaYnq6uomfxYXFwddXV0MHTq02fMCdX98d+zYgb///e+YPHkycnNz8c4778DBwaHRypr+/fvjyJEj2LNnDxwcHGBmZib6Jl06OjpYvXo1nnzySUyYMAHz589HVVUV3n//fZSUlGDVqlXKY9955x088sgjGD16NF5++WXU1NTgvffeg4mJiconReHh4fjb3/6GuXPnQqFQYOjQoTAxMUFBQQF+//139O/fH88++2yzNY0ZMwYTJ07E22+/jdraWoSEhEChUOCtt97ChAkTMHjwYFGv+aEg3XxQIu3AVR4PtnnzZmHGjBmCp6enYGpqKujr6wsuLi7CzJkzG61guHTpkjBmzBjBzMxMACD07NlTEIQ/V3ls3bq1yef46quvBF9fX8HAwECwsLAQoqKihPT0dJVjGq7yqHflyhWhd+/egqurq5CdnS0IQt1Kg6efflpwdHQU9PX1hW7duglhYWHCihUrlI/78MMPhbCwMMHW1lYwMDAQXFxchHnz5gmXLl1q8f148803BSsrK6GyslLZVllZKTzzzDNCnz59BFNTU0FPT09wcnISnnrqqUavQxAEISAgQOjevXuLz9WUB63yGDJkiDBx4sRWnWfVqlWCq6urIJfLhT59+gj//e9/hWXLlgn3/9lITk4WwsPDBWNjYwFAk6t46tWv8nj//fcb/QyAsGzZMpW2Xbt2CcHBwYKhoaFgYmIiRERECDExMY0eu3v3buW/DxcXF2HVqlVN1ioIgvD1118LwcHBgomJiWBkZCS4u7sLs2bNEhQKRYvvye3bt4XXX39dcHZ2FvT09AQXFxdh8eLFKr/rel1xlQe3LydqQf02xOc3yETfett7tqDxWxCTOPn5+XBzc8O3336LqVOntvnx5eXlsLa2xscff9zsXI/2yM7OhqenJ3755ReMHj1abeelpqmr3wC0p+/gHAoiIjXq0aMHFi1ahHfffRe1tbVtfvyxY8fg6OiIv/71r2qta8WKFYiIiGCYoA7DQEFEpGZvvPEGJk2a1Kr7Pdxv/PjxuHTpEgwMDNRWT3V1Ndzd3RvdYpxInTgpk4hIzczMzJqdMCoFPT09vPHGG1KXQQ85fkJBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgPZaDIz8/HN998gy1btkhdChFpkWPHjuFf//oXCgsLpS6FSOs8lIGivLwcsbGxiImJQVVVldTlEJGWSElJweXLlxETEyN1KURa56EMFJ6enrC1tUVlZSWSkpKkLoeItER4eDgAIDY2FjU1NRJXQ6RdHspAoaOjo+wYeKVBRK3l6+sLMzMzlJWVIS0tTepyiLTKQxkoACA0NBQymQyZmZkcDyWiVtHT00NwcDAAXowQtdVDGyisrKzQt29fAMCJEyckroaItEX9p5upqakoLS2VuBoi7fHQBgqA46FE1HY9evSAm5sbamtrERcXJ3U5RFrjoQ4Uvr6+MDU1RWlpKdLT06Uuh4i0RMM5WIIgSFwNkXZ4qAMFx0OJqD0CAwNhYGCAwsJCZGdnS10OkVZ4qAMF8OeVxunTp1FWViZxNUSkDYyMjBAQEACAc7CIWuuhDxSOjo5wdXXleCgRtUn9xYhCoUBlZaXE1RBpvoc+UAAcDyWitvPw8IC9vT2qqqqgUCikLodI43WJQBEUFAR9fX1cvXoVFy5ckLocItICMpkMYWFhADjsQdQaXSJQNBwP5eRMImqt0NBQ6OjoIDs7GwUFBVKXQ6TRukSgADgeSkRtZ2FhgX79+gHgxQhRS7pMoPD09ISdnR2qqqqQmJgodTlEpCXqL0bi4uJ4gzyiB+gygaLheCivNIiotfr37w9zc3OUl5cjNTVV6nKINFaXCRTAnxuGZWdn4+rVq1KXQ0RaQFdXFyEhIQCA33//XeJqiDRXlwoUlpaWHA8lojarH/ZIS0tDSUmJtMUQaaguFSgAjocSUdt1794d7u7uEASBN8gjakaXCxS+vr4wMzNDWVkZ0tLSpC6HiLQEb5BH9GBdLlA0HA/lsAcRtVZAQADkcjmuXbuGrKwsqcsh0jh6UhcghfDwcBw4cACpqakoLS2FhYWF1CWRFlh5zxEG99qfwe/eqwVwRX0FUacyNDREYGAgYmJiEBMTA09PT6lLIi0gtt8AtKfv6HKfUACAg4MDevXqxQ3DiKhN6oc9EhMTcefOHYmrIdIsXTJQABwPJaK269WrF7p37467d+9ywzCi+3TZQBEYGAi5XI7CwkJkZ2dLXQ4RaQHeII+oeV02UBgaGnLDMCJqs/oNwy5evIj8/HypyyHSGF02UACq46HcMIw0zbp16+Dr6wtzc3OYm5sjNDQU+/bte+Bjqqqq8M9//hM9e/aEXC6Hu7s7vv76606quGswNzeHr68vAF6MkOaRst/okqs86rm7u8Pe3h6FhYVQKBQYPHiw1CURKTk5OWHVqlXw8PAAAGzYsAFRUVE4deoU+vbt2+RjpkyZgsLCQqxfvx4eHh64du0aqqurO7PsLiEsLAzJycmIi4vDY489Bj29Lt2VkgaRst/o0v8XyGQyhIeHY8eOHYiJiWGgII0yceJEle/fffddrFu3DnFxcU12DPv378fRo0dx4cIFWFtbAwBcXV07o9Qup1+/frCwsEBpaSlOnz6NgQMHSl0SEQBp+40uPeQBACEhIdDR0cGFCxdQUFAgdTnUBZSVlal8VVVVtfiYmpoaREdHo6KiAqGhoU0es3v3bgQGBmL16tVwdHSEl5cXXnnlFS5v7AC6urrK3wOHPaiztLXv6Ox+o8sHCgsLC/Tv3x8AOwbqHM7OzrCwsFB+rVy5stljU1NTYWpqCrlcjgULFmDnzp3w8fFp8tgLFy7g999/R1paGnbu3ImPP/4Y27Ztw3PPPddRL6VLq1/tkZ6ejps3b0pcDXUFre07pOo3uvSQR73w8HCkpKQox0N1dXWlLokeYrm5uTA3N1d+L5fLmz3W29sbycnJKCkpwfbt2zF79mwcPXq0yc6htrYWMpkMP/zwg/Lurx999BEmT56Mzz//HEZGRup/MV2Yvb09PDw8kJWVhdjYWERGRkpdEj3kWtt3SNVvdPlPKIC68VBzc3OUl5fj9OnTUpdDD7n62df1Xw8KFAYGBvDw8EBgYCBWrlwJPz8/rFmzpsljHRwc4OjoqHIr+T59+kAQBFy5ovm37dVG9SvFTpw4gdraWomroYdda/sOqfoNBgpwwzDSHoIgNDtuGh4ejvz8fNy6dUvZlpGRAR0dHTg5OXVWiV1KQEAADA0Ncf36dWRmZkpdDlGTOqvfYKD4Q/2VRlpaGkpKSqQthgjAkiVLcPz4cVy6dAmpqan45z//iSNHjuDJJ58EACxevBizZs1SHj9jxgzY2Nhg7ty5OHPmDI4dO4ZXX30VTz/9NIc7OohcLkdgYCCAuk8piKQmZb/BQPGH7t27w93dHYIgIDY2VupyiFBYWIiZM2fC29sbERERiI+Px/79+zF69GgAQEFBAXJycpTHm5qa4sCBAygpKUFgYCCefPJJTJw4EZ988olUL6FL4IZhpEmk7Dc4KbOB8PBwZGdn48SJE3jkkUcgk8mkLom6sPXr1z/w5998802jtt69e+PAgQMdVBE1xc3NDQ4ODigoKMDJkycxbNgwqUuiLkzKfoOfUDQQEBAAuVyOa9eucTyUiFql/gZ5AIc9qGtjoGjA0NBQOR7KyZlE1FrBwcHQ0dHBpUuXkJeXJ3U5RJJgoLgPx0OJqK3Mzc3h5+cHAPj9998lroZIGgwU9+nVqxccHBxw7949JCQkSF0OEWmJ+ouR+Ph43Lt3T+JqiDofA8V9ZDKZ8pa6HPYgotby8fGBpaUlKioqeIM86pIYKJpQv2EYx0OJqLW4YRh1dQwUTTA3N4evry8AdgxE1Hr1n26eOXMGxcXFEldD1LkYKJrRcDy0urpa4mqISBvY2dnBy8uLN8ijLomBohl9+/aFhYUFbt26xfFQImo1bhhGXRUDRTM4HkpE7TFw4EAYGhrixo0byMjIkLocok7DQPEA9eOh6enpuHnzpsTVEJE2MDAwwKBBgwDwYoS6FgaKB7C3t4enpyfHQ7XEzcoKfJX+Oyb9/CUqq3kfAJJO/bBHUlISKioqJK6GHkQQBCReu4xXft+GdalHpS5Hq3FzsBaEh4cjMzMTMTExeOSRR6CjwwymSWqFWsQUZGNTRgL2X07H3doaAMAvOWcQ1ctP4uqoq+rZsyccHR2Rl5eHhIQEDB8+XOqS6D5FlbewPesUojMTkFFyDQDgaGKJv/UdAl328+3CQNGCgQMHIjo6Gjdu3EBmZia8vb2lLokA5N8qwZasRGzOVCD31p/DUf2se2C6VxCGOXpKWB11dfU3yNu6dStiYmIYKDRETW0tjhdkYVNGAn7NOYN7f1yAGOrqY4Jrf0z3CoIOd5luNwaKFsjlcgQFBeH48eOIiYlhoJDQ3ZpqHMg9i+gMBY7mZ6BWEAAA5gaGeKyXP6Z5BqG/raPEVRLVCQkJwY4dO5CTk4Pc3Fw4OztLXVKXdeXWTWzOVGBzpgL5FaXKdj9bJ0zzDERUL3+YGxhKWOHDgYGiFcLDw3H8+HEkJSVh2rRpMDY2lrqkLiWz5BqiMxKwLTsJRZV/jkeHdu+FaV5BiOzZD0Z6+hJWSNSYqakp/P39kZiYiJiYGEybNk3qkrqUqppq/JpzBtEZCTiWnwUBdRcgFgZGeNx9AKZ7BcLHuofEVT5cGChawdXVFT169EB+fj4SEhIwbNgwqUt66FXcq8Kei6cRnamA4tplZbu9kRme8AzAVM9AuJnbSlghUcvCwsKQmJiI+Ph4TJo0Cfr6DL4d7dzNq4jOSMD27FO4WXVb2R7u4I7pXkF4xKUvDHkB0iEYKFpBJpMhPDxcOR7KQNExBEHAqRu5iM5Q4McLyaiovgsA0JXpIMLJG9O9gjDCyRt6OroSV0rUOj4+PrCyssLNmzeRnJyMoKAgqUt6KN26V4XdF1OwKSMBp67nKtu7G5tjqmcgpngGoKeZjYQVdg0MFK0UHByMHTt24PLly7hy5QqcnJykLumhUVxZgR3Zp7ApIwHnSwqV7a5mNpjmFYQnPAbC3thcwgqJ2kdHRwdhYWHYu3cvYmJiGCjUqG65Zw42ZSZgz8XTuP3HBYieTAejnPtgulcQhjt6ccVGJ2KgaCUzMzP4+fkhKSkJMTExmDp1qtQlabVaoRbH87MQnaHALzl/LveU6+phgmt/TPMKQoi9G2SccU1aLjQ0FHv37sW5c+dQVFQEGxteKYtx484tbM9OQnSGApml15TtvcxtMd0rCJM9BqKbkZmEFXZdDBRtEB4ejqSkJMTHx+Pxxx/neGg75N0qweZMBbZkKXDlVomy3dfGEdO8ghDl5gcLuZF0BRKpWbdu3eDt7Y3z58/jxIkTmDhxotQlaZ2a2loczc9E9B/LPauFuj1SjPT0MdHVF9O8ghBk15MXIBJjoGgDHx8fWFpaoqSkBCkpKQgMDJS6JK1wt6Yav+aexaaMBBzLy2ww29oQf+lVN9u6nw2Xe9LDa/DgwTh//jxiY2Mxfvx43iCvlXLLi7E5KxGbMxQouK263HP6HxcgZlzuqTEYKNpAR0cHoaGh2LdvH2JiYhgoWpBRUli33DPrFIqr/lzuGfbHcs9xXO5JXYS/vz+MjIxQVFSEc+fOwcfHR+qSNFZVTTV+uZyO6EwFjjdY7mkpN8bjvfwxzSsIPtYOEldJTWGgaKPw8HDs27cPZ8+eRXFxMaytraUuSaNU3KvC7ounEZ2RgMTrOcp2e2NzTPGoW+7pas4xZOpa6jcMO3r0KE6cOMFA0YSzxVcRnVm33LOkwXLPIT08MM0zCGNdfLjcU8MxULTR/eOhEyZMkLokyQmCgKTrudiUcRJ7Lp5WWe45yrm3crY1l3tSVzZ48GAcPXoUp06dQkVFBUxMTKQuSXLldyvx48UURGcokHyj8XLPqZ6BcDHjRZu2YKBoh7CwMGWgiIyM7LLjocWVFdienYRNGX9urgMAbvWzrd0Hws6Ys62JAMDZ2RlOTk64cuUK4uPjMXLkSKlLkoQgCFBcu4xNGQnYc+k07vyxM7CeTAejXfpgutcgDOvhyeWeWoiBoh3qNwwrKirC+fPn0adPH6lL6jT1m+tEZyTglyY215nmFYhgLvckaqT+BnmbN2/GiRMnulyguHHnFrZlJSE6MwFZpdeV7R4W3TDNs265p62RqYQVklgMFO1gYGCAoKAgHDt2DDExMV0iUNRvrrMlMxF5FSXKdm6uQ9R6gwYNwvbt25Gbm4ucnBy4uLhIXVKHqqmtxZG8DERnJuBAzlmV5Z6PuvliuucgBNi58ALkIcFA0U7h4eE4duzYQz0eWlVTjQM5Z+qWe3JzHSLR6jcMUygUiImJeWgDRU55sfICpOFyT39bZ0z3CsKjbr5c7vkQYqBop549eyrHQ0+ePIkRI0ZIXZLanL9ZiOjMBGzLSuLmOkRqFh4eDoVCgZMnT2LSpEkwMDCQuiS1qKy+h1/+uAD5vSBL2W4pN8Yk9wGY5hmEPtbdJayQOhoDRTvJZDKEhYVhy5YtiImJ0fpAUb+5TnSGAkn3Lfec6hGAqV6BXX5znSWr/wYz3fZfVZXXVOIbLFVjRaSNevfuDWtraxQXFyM5ORmDBg2SuiRRzhQXKHf3LL17BwAggwxDenhgulcQxrj4QK7bdf/UiO03AO3pO7rub1kN6jcM09bx0LrlnjnYmNH85jrDHD253JNIjeo3DPvpp58QExOjlYGi/G4lfryQgk2ZCUi5cUXZ3sPEAlM8AzHVIwDOXO7Z5TBQiGBqago/Pz8kJiZq1XhoUeUfs625uQ6RJOp3ID137hxu3LgBW1tbqUtqkSAIOFl4CdGZCfjpUqpyuae+ji7GuPhgmmcghnK5Z5fGQCFSeHg4EhMTcfLkSUyePFljNwyrqa3FsfxMRGcq8Ot9yz0nuvXHdK9B3FyHqJPY2Nigd+/eOHv2LE6cOIFHH31U6pKadf1OObZl1d1v5kLZDWW7p4UdpnsFYZLHANgYcrknMVCI1qdPH1hZWeHmzZtITk5GUFCQ1CWpqN9cZ0umAvkV922u4xmER3v5cbknkQTCw8OVgWLChAkadYO86toaHM3LxKaMBPyW++dyT2M9A0x088UMryAM7MblnqSKgUKk+vHQvXv3IiYmRiMCRXOb61gYGNXNtubmOkSS8/f3h7GxMW7evImzZ8+ib9++UpeEy+VF2JyhwOasRBTeLlO2D+zmgmlegXjUzQ+m+nIJKyRNxkChBvWB4uzZs5KOh9ZvrrMj+5TKck9urkOkefT19TFo0CAcOXIEMTExkgWKyup72Hc5HdGZCYgpyFa2W8mNMdljIKZ5BsHbyl6S2ki7MFCoga2tLXr37o1z584hNjYWEydO7LTnvnWvqm62dUYCN9ch0jKDBw/GkSNHkJycjFu3bsHUtPPmIpwpzsfGjATszE5WWe459I/lnqO7+HJPajv+a1GT8PBwnDt3DidOnMD48eM7dDy0fnOd6MwE7L7YeHOdaZ51u3tytjWRZnN2doaLiwtycnIQHx+PiIiIDn2+sruV+PFCMjZlJOB0UZ6y3dHEElM8AzDVMxBOplYdWgM9vBgo1KR+PLS4uBjnzp2Dj4+P2p+jpc11JnkM4HJPIi0TFhaGnJwcxMTEYOTIkWqf6CgIAuILLyI6Q4GfLqWisubP5Z5jXXww3SsIgx08eAFCojFQqImBgYHKeKi6AkVNbS2O5mdiU8bJJjfXmeYZhEAu9yTSWoMGDcK2bduQl5eHy5cvw9XVVS3nvXa7HFuzErE5U6Gy3NPLsm655+PuXO5J6sVAoUbh4eFqGw/l5jpEXYOJiQkGDhyIkydPIiYmRlSgqK6twZG8jD+We55DTYPlno+6+WK61yAM7ObMCxDqEAwUauTi4gJnZ2fk5ubi5MmTGDlyZJseX7+5TnRmAo7nc3Mdoq4iLCwMJ0+exMmTJ/HEE0+0ecOwS2VFdRcg9y33DOjmguleQZjo5gsTLvekDsZAoWbh4eGIjo5WbhjWmiuB+s11dlxIRkmD5Z5De3himmcgxvbsy9nWRA8xb29v2Nra4saNG0hKSkJISEiLj7lTfQ/7LqchOiMBJ65eULZby00w2aPufjNellzuSZ2Hf6XUrH489MqVK8jJyUHPnj2bPK65zXUcjC0w1Yub6xB1JfU3yNu9ezdiYmIeGCjSivKwKUOBXRdOofRuJYC65Z7DHD0xzSsIY5z7wIAXICQB/qtTMxMTEwwYMAAJCQmIiYlRCRSCICDh2mVEZyRgz6XTKpvrjP5jd09urkPUNYWGhmLPnj3IyMjA9evX0a1bN+XPSqvu4MeLdfebSW2w3NPJ1BJTPQMxxSMQjqaWElRN9CcGig4QHh6OhIQE5YZhpTVVfyz3VCC7wXJPTws7TPMKxCT3gbA14mxroq7M2toaffr0wZkzZxATE4OoqCjEFV5EdEbd7p5VNdUAAAMdXYx16Vu33LOHO3RkvAAhzcBA0QG8vb1hbW2N4uJiPPf9pzigU9Roc53pnkEIsOPmOkT0p8GDB+PMmTM4cOwIPqzOxMXyIuXPvC3tlcs9rQ1NJKySqGkMFGqWXXodmzMVSDWvgX2lAfIuXkJ1LxNurkNEzbpbU40DuWex5XoKoA/U6NWiLLcAJramiOrlj2legRhgy+WepNkYKNSg/G4l9lw6jS2ZiVBcuwwAMLQU4HjpLnreBt55+nkEuXlLXCURaZozxfnYnJmosqGfj7UcboVViHJwwuvTFnK5J2kNBop2qhVqEXf1IrZkJmLv5VTlBEsdmQwjHL0x1TMQ6RX7kZWZiaLzFwEGCiICcLPqNnZlJ2NLVqLKBEt7IzNM8hiIoUHd8d2nX6A4Owe6NQLADYJJSzBQtFHerRJszUrE1qxEXC4vVra7W3TDVM9ATHIfAHtjcwCAeUgJsjIzERcXh7Fjx/LjSqIuqqa2FsfyM7ElMxG/5KTjbm0NgD9XeE31DMQwR0/o6ehCEAT8am+PwsJCJCUlISwsTOLqiVqHgaIV7lTfwy856diSmYjj+VkQIAAATPXlmOjmi2megRjYrfEEy4CAAERHR6OgoOCB96QgoofTxbIb2JKZiG1ZSSq30PexdsAUj4AmJ1jKZDKEhITgxx9/RFxcHAMFaQ0GimYIgoCUG1ewJSsRP15IVt5ABgBCu/fCVM9ARPbsB2P95m+Ra2RkBD8/PygUCsTFxTFQEHUBFfeq8NOlVGzJVCC+8JKy3cLACI+5+2OaZyD62Tg+8BzBwcH48ccfkZGRgeLiYlhb8yZ3pPkYKO5z484t7Mg+hc2ZCpwvKVS2O5pYYrLHQEzxDEBPM5tWny8kJAQKhQIJCQmYPHkydHV1O6JsIpKQIAg4WXgJW7IU2HMxFber7wKom1NVfwv90S4+rb6Fvo2NDby8vJCRkYGTJ0/ikUce6cjyidSCgQLAvdoaHL5yHpszFTiYe055zwi5rh4e6dkX0zwDEe7QvhvI+Pj4wMzMDOXl5Thz5gz69++v7vKJSCL5FaXYnpWELVmJuNhgi3BXM5u6OVUeA9HDxKJd5w4ODkZGRgbnYJHW6NKBIqOk8I8lW0m4fueWst3P1gnTPOvuGWEhNxL1HLq6uggKCsKhQ4cQFxfHQEGk5apqqvFrzhlszlTgWH4maoW6OVV1N63rj6meQQiy6yk6AHAOFmmbLhcoyu5WYveFFGzOUuDU9Vxlu42hCSa5D8AUz0D0tlLvFuEhISE4dOgQUlJScOfOHRgZiQspRNT50oryEJ2pwK4LKSq7Agfbu2KqZyDGu/ZX6z0jOAeLtE2XCBS1Qi1OFFzA5kwFfr6cprwnvq5MBxFOdfeMGOncG/o6HTO/wcXFBQ4ODigoKEBSUhLCw8M75HmISL2KKyuwI/sUtmQl4kxxgbK9u7E5nvAIwBMeAehlYdthz885WKRNHupAkVtejC1/3DPiyq0SZbuXpR2megbicfcB6GZk1uF1yGQyBAcHY9euXYiLi2OgINJg1bU1OJqXic2ZChzIPYt7f9wzon5TrqlegRji4NEpuwJzDhZpk4cuUNypvoufL6djS6YCMQXZynYzfTmievljqmcg/G2dOn2CU8NlYEVFRbCxaf1KESLqePX78GzPSkLhnXJle38bR0z1DERULz9YyY07tSbOwSJt8lAECkEQkHQ9F1syFdh9MQXl96qUPxvs4IEpngEY17MvjPSav2dER7O2toaXlxfOnz+P+Ph4REZGSlYLEdVpah8eALCSG+Nx9wGY6hkAH+seElb45xys5ORkzsEijabVgeLa7XJsz07ClsxEZJZeU7Y7m1r9Mb45EM5mmnNDmODgYJw/fx5xcXEYN24cl4ERSaA1+/CMcu4Ng1beM6KjNZyDlZiYiMGDB0tdElGTOn4QUM3u1lRj3+U0zP1tA4K2rMS7in3ILL0GQ119PO4+AJvHPoOYya/ipQGjNCpMAMDAgQOhr6+PwsJCXL58ueUHUJe2bt06+Pr6wtzcHObm5ggNDcW+ffta9diYmBjo6enB39+/Y4vUInm3SvBx8kEM2f4Bpuz/L7ZlJ+FO9T24W3TDksBxSJiyGBtGz0Gkaz+NCRPAn7fiBoD4+HiJqyFNJ2W/oTn/17TgbPFVbMlSYEf2KRRVVijbB3ZzwRTPADzq5gdzA0MJK2yZkZER/P39kZCQgLi4OLi6ukpdEmkwJycnrFq1Ch4eHgCADRs2ICoqCqdOnULfvn2bfVxpaSlmzZqFiIgIFBYWNntcV9DefXg0zaBBg7Br1y5kZGTgxo0bsLXtuJUlpN2k7Dc0OlCUVN3GjxdSsCUrESk3rijbuxmZYpL7QEz1DISnpZ2EFbZdSEgIEhISkJCQgCeeeILLwKhZEydOVPn+3Xffxbp16xAXF/fAjmH+/PmYMWMGdHV1sWvXrg6uUvOoYx8eTdNwDtbJkyc5B4uaJWW/oXGBoqa2Fr8XZGFLZiL256Qr7xmhJ9PBKOc+mOoZgOFO3h12z4iO1qdPH5ibm6OsrAxpaWnw8/OTuiTqZGVlZSrfy+VyyOUPviFSTU0Ntm7dioqKCoSGhjZ73P/+9z9kZ2fj+++/x4oVK9RSr7ZQ9z48miYkJIRzsLq4tvYdnd1vaEyguFRWhK1/3DMiv+LPbX57W3XHVM8APNZrAGyNTCWsUD3ql4EdPHgQ8fHxDBRdkLOzs8r3y5Ytw/Lly5s8NjU1FaGhoaisrISpqSl27twJHx+fJo/NzMzEP/7xDxw/fhx6ehrzv3aH6sh9eDTNwIEDsXHjRuUcLA6Zdj2t7Tuk6jck7XVu37uLvZdSsTlLgbirF5XtFgaG+Esvf0zxDISvjeNDl8RDQkJw8OBBpKSk4Pbt2zA27ty17SSt3NxcmJubK79/0BWGt7c3kpOTUVJSgu3bt2P27Nk4evRoo86hpqYGM2bMwFtvvQUvL68Oq11TdMY+PJrG0NBQOQcrNjaWgaILam3fIVW/IROEP3a26SSCIEBx7TI2Zyqw5+JpVPyxza8MMgzt4YEpnoEY6+IDQz39ziyrUwmCgLfffhv5+fl46qmnMGTIEKlLogcoKyuDhYUFMrzehplu+yf+ltdUwitjKUpLS1U6hbYYNWoU3N3d8eWXX6q0l5SUwMrKSmVOTm1tLQRBgK6uLn799VeMHDmy3bVrAin24dE0aWlp+PTTT2FqaorVq1dzDpYGU1e/AYjvOzqr3+i0Tyiu3i7DtqwkbMlU4EKDbX57mlljikcAJnsEwNHUsrPKkVT9MrAdO3YgLi6OgYJaTRAEVFVVNWo3NzdHamqqStvatWtx6NAhbNu2DW5ubp1VolpJvQ+PpuEcLGqPzuo3OjRQVNVU40DuWWzJVOBIXoZym18jPX1McO2PKZ6BCLZ3fSjGN9tq0KBB2LlzJ7KysrgMjJq0ZMkSjBs3Ds7OzigvL0d0dDSOHDmC/fv3AwAWL16MvLw8fPvtt9DR0UG/fv1UHm9nZwdDQ8NG7dpAU/bh0TQN52DFxcUxUFAjUvYbHRIo0ovysTlTgZ0XknGzwTa/QXY9McUzEBPdfGGqxm1+tZGVlRW8vb1x7tw5xMfHY/z48VKXRBqmsLAQM2fOREFBASwsLODr64v9+/dj9OjRAICCggLk5ORIXKX6aOo+PJomNDQUBw8exOnTpzkHixqRst9Q2xyKm5UV2HkhGVsyE5FWnK9stzc2x2T3uiVb7hbd1PFUD43Y2Fh88803sLOzw9tvv93lO0pNpUlzKB42Le3DM9UzEI/07Aujh3hOVVtxDpZ20KQ5FJ1FLZ9QVNyrQvDW93D7jwmW+jq6GOPigykeARjm6Am9LjK+2VYDBgzAxo0bce3aNVy6dElrx7mJ2us/6cfxTsLPyu+dTa0wxTMAT3gEwMnUSsLKNBfnYJGmUkugMNGXY0gPD1y5dRNTPAPxWC9/WBuaqOPUD7X6ZWAnT55EXFwcAwV1OaOdffDBqQMY17MfpnoGIrS7W5ecU9VWnINFmkhtcyg+HTpNq25lqylCQkJw8uRJ5a24u8oNibTRZxHekMvbP15dVXUbyFBjQQ+BXha2SJn2JvuONrKyskLv3r1x9uxZzsHScGL7DUB7+g61XQqwQ2if3r17w8LCAhUVFUhLS5O6HKJOx76jfYKDgwEAcXFx6OTbCRE1iZ8tSkxXVxeDBg0CwK2Jiaj1BgwYAAMDA1y7dg0XL15s+QFEHYyBQgPUX2mcPn0aFRUVLRxNRFQ3B2vAgAEA6j6lIJIaA4UGcHZ2hpOTE6qrq5GYmCh1OUSkJUJCQgAACoUC1dXVEldDXR0DhYZoOB5KRNQanINFmoSBQkMMGjQIMpkM2dnZuH79utTlEJEW0NHRUc7B4sUISY2BQkNYWlqid+/eANgxEFHr1Q97cA4WSY2BQoPUdwzx8fFcBkZEreLk5AQnJyfU1NRAoVBIXQ51YQwUGmTAgAGQy+W4fv06Lly4IHU5RKQlGl6MEEmFgUKDyOVyLgMjojZrOAfr2rVrUpdDXRQDhYZpuAzs3r17EldDRNrAwsICffr0AcBPKUg6DBQaxtvbG5aWlrh9+zaXgRFRq3EOFkmNgULDcBkYEbWHv78/52CRpBgoNFD9lUZqaipu3bolcTVEpA04B4ukxkChgRwdHeHs7IyamhreipuIWo1zsEhKDBQaqv5W3LGxsRJXQkTaouEcrNTUVKnLoS6GgUJD1S8Du3jxIgoLC6Uuh4i0AOdgkZQYKDSUhYUFfHx8AHAZGBG1Xv2wR1paGudgUadioNBgXAZGRG3VcA4Wb8VNnYmBQoPVLwOrqqpCUVGR1OUQkZaovxjJz8+XuBLqSvSkLoCaZ2BggFdffRU9evSArq6u1OUQkZYIDQ2Fn58funXrJnUp1IUwUGg4Z2dnqUsgIi1jYmICExMTqcugLoZDHkRERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREoulJXQCRtphdMg2mBrJ2P/7WXQGfqLEeItJ8YvsNQHv6Dn5CQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREREQkGgMFERERicZAQURERKIxUBAREZFoDBREGmrdunXw9fWFubk5zM3NERoain379jV7/I4dOzB69Gh069ZNefwvv/zSiRUTkdSk7DcYKIg0lJOTE1atWgWFQgGFQoGRI0ciKioK6enpTR5/7NgxjB49Gj///DMSExMxYsQITJw4EadOnerkyolIKlL2GzJBEASxL4DoYVZWVgYLCwskTpfB1EDW7vPcuisgYJOA0tJSmJubt+sc1tbWeP/99zFv3rxWHd+3b19MnToVS5cubdfzEVH7qKvfAMT3HZ3Vb+i1uTIiEqWsrEzle7lcDrlc/sDH1NTUYOvWraioqEBoaGirnqe2thbl5eWwtrZud61EpDna2nd0dr/BIQ+iTubs7AwLCwvl18qVK5s9NjU1FaamppDL5ViwYAF27twJHx+fVj3Phx9+iIqKCkyZMkVdpRORhFrbd0jVb/ATCqJOlpubq/Kx5YOuMLy9vZGcnIySkhJs374ds2fPxtGjR1vsHDZt2oTly5fjxx9/hJ2dndpqJyLptLbvkKrf4BwKohZo0hyKUaNGwd3dHV9++WWzx2zevBlz587F1q1bMX78+PaWS0QiaNIcis7qNzjkQaRFBEFAVVVVsz/ftGkT5syZg40bNzJMEBGAzus3OORBpKGWLFmCcePGwdnZGeXl5YiOjsaRI0ewf/9+AMDixYuRl5eHb7/9FkBdpzBr1iysWbMGISEhuHr1KgDAyMgIFhYWkr0OIuo8UvYb/ISCSEMVFhZi5syZ8Pb2RkREBOLj47F//36MHj0aAFBQUICcnBzl8V9++SWqq6vx3HPPwcHBQfm1cOFCqV4CEXUyKfsNzqEgaoEmzaEgIu2gSXMoOgs/oSAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiERjoCAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiERjoCAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiERjoCAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiERjoCAiIiLRGCiIiIhINAYKIiIiEo2BgoiIiETTk7oAIm0xYfBC6BjJ2/342jtVwKaP1VcQEWk8sf0GoD19Bz+hICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiIiISjYGCiIiIRGOgICIiItEYKIiIiEg0BgoiDbVu3Tr4+vrC3Nwc5ubmCA0Nxb59+x74mKNHjyIgIACGhobo1asXvvjii06qlog0gZT9BgMFkYZycnLCqlWroFAooFAoMHLkSERFRSE9Pb3J4y9evIjIyEgMGTIEp06dwpIlS/DCCy9g+/btnVw5EUlFyn5DJgiCIPYFED3MysrKYGFhge4fPAuZkbzd5xHuVOHqK+tQWloKc3Pzdp3D2toa77//PubNm9foZ6+//jp2796Ns2fPKtsWLFiAlJQUxMbGtrtuImo7dfUbgPi+o7P6Db02V0bUxRgYGKB79+64+so60efq3r07KisrVdrkcjnk8gd3ODU1Ndi6dSsqKioQGhra5DGxsbEYM2aMStvYsWOxfv163Lt3D/r6+uKKJ6JWU2e/AbSv7+jsfoOBgqgFhoaGuHjxIu7evSv6XKtXr4a9vb1K27Jly7B8+fImj09NTUVoaCgqKythamqKnTt3wsfHp8ljr1692ujc9vb2qK6uxo0bN+Dg4CC6fiJqHXX2G0Db+g6p+g0GCqJWMDQ0hKGhoejzvPnmm3jttddU2h50heHt7Y3k5GSUlJRg+/btmD17No4ePdps5yCTyVS+rx/RvL+diDqeuvoNoG19h1T9BgMFUSdqzfBGQwYGBvDw8AAABAYGIiEhAWvWrMGXX37Z6Nju3bvj6tWrKm3Xrl2Dnp4ebGxsxBVORJJqS98hVb/BVR5EWkQQBFRVVTX5s9DQUBw4cECl7ddff0VgYCDnTxB1YZ3VbzBQEGmoJUuW4Pjx47h06RJSU1Pxz3/+E0eOHMGTTz4JAFi8eDFmzZqlPH7BggW4fPkyXnrpJZw9exZff/011q9fj1deeUWql0BEnUzKfoNDHkQaqrCwEDNnzkRBQQEsLCzg6+uL/fv3Y/To0QCAgoIC5OTkKI93c3PDzz//jBdffBGff/45evTogU8++QSTJk2S6iUQUSeTst/gfSiIiIhINA55EBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJxkBBREREojFQEBERkWgMFERERCQaAwURERGJ9v+sUWrnDwVq0wAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -1561,12 +1593,12 @@ "output_type": "stream", "text": [ "angles_gdf len 4\n", - "Interior angles found: [89.83847705650136, 88.78833801117518]\n", - "Interior angles found: [89.75197989966416, 89.19788105500966]\n", - "Final angles found: [88.78833801117518, 89.19788105500966]\n", + "Interior angles found: [np.float64(89.83847705650136), np.float64(88.78833801117518)]\n", + "Interior angles found: [np.float64(89.75197989966416), np.float64(89.19788105500966)]\n", + "Final angles found: [np.float64(88.78833801117518), np.float64(89.19788105500966)]\n", "connectivity: 2\n", "Counter values: dict_values([2, 2])\n", - "angles: [88.78833801117518, 89.19788105500966]\n", + "angles: [np.float64(88.78833801117518), np.float64(89.19788105500966)]\n", "(3, 4) added\n", "**************************************************************\n", " \n", @@ -1594,7 +1626,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1609,7 +1641,7 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([2, 1])\n", - "angles: [78.26155769686821]\n", + "angles: [np.float64(78.26155769686821)]\n", "(4, 7) added\n", "**************************************************************\n", " \n", @@ -1623,7 +1655,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1636,12 +1668,12 @@ "output_type": "stream", "text": [ "angles_gdf len 4\n", - "Interior angles found: [89.70671191496507, 89.56623033507175]\n", - "Interior angles found: [89.84379058832397, 89.42915166171285]\n", - "Final angles found: [89.56623033507175, 89.42915166171285]\n", + "Interior angles found: [np.float64(89.70671191496507), np.float64(89.56623033507175)]\n", + "Interior angles found: [np.float64(89.84379058832397), np.float64(89.42915166171285)]\n", + "Final angles found: [np.float64(89.56623033507175), np.float64(89.42915166171285)]\n", "connectivity: 2\n", "Counter values: dict_values([2, 2])\n", - "angles: [89.56623033507175, 89.42915166171285]\n", + "angles: [np.float64(89.56623033507175), np.float64(89.42915166171285)]\n", "(0, 4) added\n", "**************************************************************\n", " \n", @@ -1655,7 +1687,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1670,7 +1702,7 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([2, 1])\n", - "angles: [87.60977577529626]\n", + "angles: [np.float64(87.60977577529626)]\n", "(4, 5) added\n", "**************************************************************\n", " \n", @@ -1691,7 +1723,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1704,14 +1736,14 @@ "output_type": "stream", "text": [ "angles_gdf len 4\n", - "Interior angles found: [47.16443370903167, 48.92275878691167]\n", - "Interior angles found: [59.79419820769666, 61.55252328557668]\n", - "Final angles found: [47.16443370903167, 59.79419820769666]\n", + "Interior angles found: [np.float64(47.16443370903167), np.float64(48.92275878691167)]\n", + "Interior angles found: [np.float64(59.79419820769666), np.float64(61.55252328557668)]\n", + "Final angles found: [np.float64(47.16443370903167), np.float64(59.79419820769666)]\n", "connectivity: 2\n", "Counter values: dict_values([2, 2])\n", - "angles: [47.16443370903167, 59.79419820769666]\n", - "(2, 6) already in graph, angles = [84.23886881283048, 80.16976627731358]\n", - "(2, 6) already in graph, angles updated = [84.23886881283048, 80.16976627731358, 47.16443370903167, 59.79419820769666]\n", + "angles: [np.float64(47.16443370903167), np.float64(59.79419820769666)]\n", + "(2, 6) already in graph, angles = [np.float64(84.23886881283048), np.float64(80.16976627731358)]\n", + "(2, 6) already in graph, angles updated = [np.float64(84.23886881283048), np.float64(80.16976627731358), np.float64(47.16443370903167), np.float64(59.79419820769666)]\n", "**************************************************************\n", " \n", " \n", @@ -1724,7 +1756,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1737,12 +1769,12 @@ "output_type": "stream", "text": [ "angles_gdf len 4\n", - "Interior angles found: [87.26341801197296, 86.2834611843536]\n", - "Interior angles found: [89.6026063905527, 88.62264956293333]\n", - "Final angles found: [86.2834611843536, 88.62264956293333]\n", + "Interior angles found: [np.float64(87.26341801197296), np.float64(86.2834611843536)]\n", + "Interior angles found: [np.float64(89.6026063905527), np.float64(88.62264956293333)]\n", + "Final angles found: [np.float64(86.2834611843536), np.float64(88.62264956293333)]\n", "connectivity: 2\n", "Counter values: dict_values([2, 2])\n", - "angles: [86.2834611843536, 88.62264956293333]\n", + "angles: [np.float64(86.2834611843536), np.float64(88.62264956293333)]\n", "(4, 6) added\n", "**************************************************************\n", " \n", @@ -1763,7 +1795,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAAGxCAYAAACz7cW9AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAAQClJREFUeJzt3Xl4VNX9P/D3ZJvJvu97wi4BKiACiiICIvDFJbaiVbTar61oq+LPra1gtQWXWlArVosKKIILRZFFRRaxggUtiqhAIDskkAUSskyW+fz+oDPfGbLNne3emXm/nifPY4abmU8mznmfe8895+hEREBERESqClC7ACIiImIgExERaQIDmYiISAMYyERERBrAQCYiItIABjIREZEGMJCJiIg0gIFMRESkAQxkIiIiDXA4kJ977jnodDoMHTq0x2N0Oh0WLFhg+X779u3Q6XTYvn27oy9rsXHjRpvndqXXX38dOp0Oe/fudcvzu9qqVauwePFitcvowpV/b7PFixfjmmuuQW5uLnQ6HS699NJej3///fdxySWXICoqCuHh4TjvvPPw8ssvu6weIiJXcTiQX331VQDAgQMH8OWXX7qsIHtt3LgRjz32mMdfV4u0Gsju8NJLL6G0tBSXXXYZEhMTez120aJFuOaaazB06FC8/fbb+OCDD3DnnXeira3NQ9USEdkvyJEf2rt3L7755htMnz4dGzZswLJlyzBmzBhX1+YyIoLW1laEhoaqXQo56fvvv0dAwNl+ZG9XZ7766iv87ne/w8KFC/HAAw9YHp80aZLbayQicoRDZ8jLli0DcPYMZNy4cVi9ejWam5tdVlRzczPuv/9+5ObmwmAwIC4uDqNGjcJbb70FALjlllvwt7/9DcDZy+Lmr5KSEstjd911F1566SUMHjwYer0ey5cvBwB8/vnnmDRpEiIjIxEWFoZx48Zhw4YNfdZ0/PhxjBw5Ev3798fhw4cBAA0NDZY6Q0JCkJ6ejnvuuQdNTU02P/vOO+9gzJgxiI6ORlhYGPLy8vCLX/yiz9f829/+hgkTJiApKQnh4eEoKCjAU089hfb2dssxl156KTZs2IDS0lKb96I3OTk5mDFjBjZv3ozzzz8foaGhGDRokOWqh7XvvvsOs2bNQmxsLAwGA0aMGGF5L639+OOPuOKKKxAWFoaEhAT86le/QmNjY7evv2XLFkyaNAlRUVEICwvD+PHj8emnn/b5fgCwhHFfXnjhBej1etx99912HU9EpDpRqLm5WaKjo2X06NEiIvKPf/xDAMjrr7/e5VgAMn/+fMv327ZtEwCybdu2Xl/jjjvukLCwMHn22Wdl27Zt8uGHH8qiRYvk+eefFxGRoqIiKSwsFACya9cuy1dra6vlddPT02XYsGGyatUq2bp1q3z33Xeyfft2CQ4OlpEjR8qaNWtk3bp1MmXKFNHpdLJ69WrL67/22msCQPbs2SMiIvv375fMzEwZO3asnDx5UkREmpqaZMSIEZKQkCDPPvusbNmyRZYsWSLR0dFy2WWXiclkEhGRL774QnQ6nVx//fWyceNG2bp1q7z22mty00039fle33vvvbJ06VLZvHmzbN26Vf76179KQkKC3HrrrZZjDhw4IOPHj5eUlBSb96I32dnZkpGRIUOGDJEVK1bIRx99JNddd50AkB07dliO+/HHHyUyMlLy8/NlxYoVsmHDBpk9e7YAkCeffNJyXFVVlSQlJUl6erq89tprsnHjRrnxxhslKyury9975cqVotPp5KqrrpK1a9fK+vXrZcaMGRIYGChbtmzp8z2xdt5558kll1zS7b/l5eXJ+eefLytXrpQBAwZIQECApKeny4MPPihGo1HR6xAReYLiQF6xYoUAkJdeeklERBobGyUiIkIuvvjirk/uYCAPHTpUrrrqql6PmTt3rvTUnwAg0dHRUldXZ/P4hRdeKElJSdLY2Gh5rKOjQ4YOHSoZGRmWELUO5E8++USioqKksLBQWlpaLD+3cOFCCQgIsIS22bvvvisAZOPGjSIi8swzzwgAOXXqVK+/T186Ozulvb1dVqxYIYGBgTa/2/Tp0yU7O9vu58rOzhaDwSClpaWWx1paWiQuLk7uuOMOy2PXX3+96PV6KSsrs/n5adOmSVhYmOV3evDBB0Wn08m+fftsjps8ebLN37upqUni4uJk5syZXX634cOHywUXXGD37yDSeyDr9XqJjIyU2NhYeeGFF2Tr1q3yu9/9TgIDA+WGG25Q9DpERJ6g+JL1smXLEBoaiuuvvx4AEBERgeuuuw47d+60XMp11gUXXIBNmzbhoYcewvbt29HS0qL4OS677DLExsZavm9qasKXX36JwsJCREREWB4PDAzETTfdhIqKChw8eNDmOZYvX44rr7wSt99+O95++20YDAbLv3344YcYOnQoRowYgY6ODsvX1KlTbe4sHj16NADgpz/9Kd5++21UVlba/Tv85z//wf/8z/8gPj4egYGBCA4Oxs0334zOzk4cOnRI8XtibcSIEcjKyrJ8bzAYMGDAAJSWlloe27p1KyZNmoTMzEybn73lllvQ3NyMXbt2AQC2bduG8847D8OHD7c57oYbbrD5/osvvkBdXR3mzJlj856ZTCZcccUV2LNnT5fL/Y4ymUxobGzEiy++iLlz52LixIl44okncPfdd2PVqlUoKipyyesQEbmKokAuKirCZ599hunTp0NEcOrUKZw6dQqFhYUA0O0YpCOee+45PPjgg1i3bh0mTpyIuLg4XHXVVYoCPzU11eb7+vp6iEiXxwEgLS0NAFBbW2vz+OrVqxEaGorbb7+9y7hsdXU1vv32WwQHB9t8RUZGQkRQU1MDAJgwYQLWrVuHjo4O3HzzzcjIyMDQoUMt4+E9KSsrw8UXX4zKykosWbIEO3fuxJ49eyxj5450UqzFx8d3eUyv19s8b21trV3vV21tLVJSUrocd+5j1dXVAIDCwsIu79uTTz4JEUFdXZ3jv5QV8+83depUm8enTZsGAPj6669d8jpERK6i6C7rV199FSKCd999F++++26Xf1++fDmeeOIJBAYGOlVUeHg4HnvsMTz22GOorq62nC3PnDkTP/74o13PcW6AxsbGIiAgAMePH+9y7LFjxwAACQkJNo+/+eab+MMf/oBLLrkEH3/8MUaMGGH5t4SEBISGhvbYCbF+rlmzZmHWrFkwGo3YvXs3Fi5ciBtuuAE5OTkYO3Zstz+/bt06NDU1Ye3atcjOzrY8vm/fvl5/b1eKj4+36/2Kj49HVVVVl+POfcx8/PPPP48LL7yw29dMTk52qmazYcOGdVuTiACw/+YwIiJPsbtV6uzsxPLly5Gfn49t27Z1+Zo3bx6OHz+OTZs2ubTA5ORk3HLLLZg9ezYOHjxouZtbr9cDsP9MMTw8HGPGjMHatWttfsZkMuGNN95ARkYGBgwYYPMzcXFx2LJlCwYPHoyJEydi9+7dln+bMWMGjhw5gvj4eIwaNarLV05OTpca9Ho9LrnkEjz55JMAzl6S7om5Q2H+PYGzYfLKK690+7zOnjF3Z9KkSdi6daslgM1WrFiBsLAwS6hOnDgRBw4cwDfffGNz3KpVq2y+Hz9+PGJiYvD99993+56NGjUKISEhLqn92muvBYAu/z9u3LgRAQEBlqEEIiKtsPsMedOmTTh27BiefPLJbldHGjp0KF544QUsW7YMM2bMcKqoMWPGYMaMGRg2bBhiY2Pxww8/YOXKlRg7dizCwsIAAAUFBQCAJ598EtOmTUNgYCCGDRvWa4O+cOFCTJ48GRMnTsT999+PkJAQvPjii/juu+/w1ltvdTtdKDIyEps3b8Y111yDyZMn44MPPsDEiRNxzz334L333sOECRNw7733YtiwYTCZTCgrK8PHH3+MefPmYcyYMXj00UdRUVGBSZMmISMjA6dOncKSJUsQHByMSy65pMdaJ0+ejJCQEMyePRsPPPAAWltbsXTpUtTX13c5tqCgAGvXrsXSpUsxcuRIBAQEYNSoUUrf9i7mz5+PDz/8EBMnTsSjjz6KuLg4vPnmm9iwYQOeeuopREdHAwDuuecevPrqq5g+fTqeeOIJJCcn48033+xyNSMiIgLPP/885syZg7q6OhQWFiIpKQknT57EN998g5MnT2Lp0qW91rR3717L9LaGhgbLFRvg7Hi9+WrCrbfeir///e+48847UVNTgyFDhmDLli3429/+hjvvvNPmqgMRkSbYe/fXVVddJSEhIXLixIkej7n++uslKChIqqqqRMTxu6wfeughGTVqlMTGxoper5e8vDy59957paamxnKM0WiU22+/XRITE0Wn0wkAKS4utrzu3Llzu33unTt3ymWXXSbh4eESGhoqF154oaxfv97mmHOnPZlf79prrxWDwSAbNmwQEZEzZ87I73//exk4cKCEhIRIdHS0FBQUyL333mt5Dz788EOZNm2apKenS0hIiCQlJcmVV14pO3fu7PU9EBFZv369DB8+XAwGg6Snp8v/+3//TzZt2tTlPayrq5PCwkKJiYmxvBe9yc7OlunTp3d5/JJLLuly1/L+/ftl5syZEh0dLSEhITJ8+HB57bXXuvzs999/L5MnTxaDwSBxcXFy2223yfvvv9/t33vHjh0yffp0iYuLk+DgYElPT5fp06fLO++80+d7MmfOHAHQ7de5ddXW1sodd9whycnJEhwcLAMGDJCnn35aOjs7+3wdIiJP04n8d1CNiIiIVMM7W4iIiDSAgUxERKQBDGQiIiINYCATkWJffvklrr76amRlZUGv1yM5ORljx47FvHnzbI578cUX8frrr7ulhltuucVm1T017dy5E3q93malu88//xy33347Ro4cCb1eb7MBjrP62ue7vb0d+fn5btmW9c9//jPWrVvn8ud11oIFC/rcWEeJxsZGPPDAA5gyZQoSExOh0+mwYMGCHo9vb2/Hs88+i4KCAoSGhiImJgbjxo3DF198YfdrMpCJSJENGzZg3LhxaGhowFNPPYWPP/4YS5Yswfjx47FmzRqbY90ZyFohIrjnnnvwy1/+0mY63aeffootW7YgKysL48aNc9nr2bPPd3BwMB599FH88Y9/7LICobO0GsiuVltbi5dffhlGoxFXXXVVr8d2dnbi6quvxh//+EfMnj0bmzZtwptvvokrrrhC2XLAKt/lTUReZsKECZKfny/t7e1d/u3cKWW9bQByrra2tm6fsydz5syR8PBwu493l40bNwoA+fHHH20et34vnn76aZupmY7au3evBAQE2Oy21hOj0ShxcXHypz/9yanXPFd4eLjMmTPHpc/pCvPnz+9zyqcSJpPJsuHQyZMnu0zjtfbXv/5VAgIC+txpry88QyYiRWpra5GQkICgoK7rClkvSZqTk4MDBw5gx44dln26zSvYbd++HTqdDitXrsS8efOQnp4OvV5v2fTj1VdfxfDhwy37oV999dX44Ycf+qztX//6FxISEjBjxgzLmcnhw4dxww03ICkpCXq9HoMHD7asCW9mMpnwxBNPYODAgZbLjcOGDcOSJUv6fM2lS5di9OjRGDhwYI/vhaso2ec7JCQEP/vZz/Dyyy9bloztSWtrK+bNm4cRI0YgOjoacXFxGDt2LN5//32b43Q6HZqamrB8+XLL37S7haLMSkpKoNPp8Mwzz+DZZ59Fbm4uIiIiMHbsWJuVD80++OADywJQkZGRmDx5smUTG2sbNmzAiBEjoNfrkZubi2eeeabb1xcRvPjiixgxYgRCQ0MRGxuLwsJCHD16tNf3w/y72nsJfMmSJZgwYUKPSwLbzak4JyK/c/vttwsAufvuu2X37t3S1tbW7XFff/215OXlyU9+8hPLPt1ff/21iPzfIkHp6elSWFgoH3zwgXz44YdSW1srf/7znwWAzJ49WzZs2CArVqyQvLw8iY6OlkOHDlme/9wz5DVr1oher5df//rX0tHRISJn9ws3L9izYsUK+fjjj2XevHkSEBAgCxYssPzswoULJTAwUObPny+ffvqpbN68WRYvXmxzTHeMRqOEhobKAw880OtxrjpDVrrP95o1awSAfPvtt70+76lTp+SWW26RlStXytatW2Xz5s1y//33S0BAgCxfvtxy3K5duyQ0NFSuvPJKy9/0wIEDPT5vcXGxAJCcnBy54oorZN26dbJu3TopKCiQ2NhYm21p33zzTQEgU6ZMkXXr1smaNWtk5MiREhISYrOQ0pYtWyQwMFAuuugiWbt2rbzzzjsyevRoy/7r1n75y19KcHCwzJs3TzZv3iyrVq2SQYMGSXJysmXxJnv0doZcVlZm+Tw8/PDDkpSUJIGBgTJkyBB5/fXX7X4NEQf2QyYi/1ZTUyMXXXSRZYW04OBgGTdunCxcuNBmr3GRni9ZmwN5woQJNo/X19dbGnxrZWVlotfrbfaytg7kRYsWSWBgYJdLuVOnTpWMjAw5ffq0zeN33XWXGAwGy77iM2bMkBEjRih7I0Tkyy+/FACyevXqXo9zVSAr3ef78OHDAkCWLl2q6HU6Ojqkvb1dbrvtNvnJT35i829KLlmbA7mgoMDSSRIR+fe//y0A5K233hKRs5f309LSpKCgwOZSf2NjoyQlJcm4ceMsj40ZM0bS0tJs9qdvaGiQuLg4m0DetWuXAJC//OUvNjWVl5fb1Ymy1lsgm18nKipKhgwZIm+//bZ89NFHUlhYKADk5Zdftvt1eMmaiBSJj4+3bAe6aNEizJo1C4cOHcLDDz+MgoICy9aj9jBvAmK2a9cutLS04JZbbrF5PDMzE5dddhk+/fRTm8dFBHfccQfmz5+PVatW4YEHHrD8W2trKz799FNcffXVCAsLs9mD+8orr0Rra6vlsukFF1yAb775BnfeeSc++ugjNDQ02FW/eeOVpKQku39nZyjd59tclz37sL/zzjsYP348IiIiEBQUhODgYCxbtsyuoYK+TJ8+3WYXwGHDhgGA5a70gwcP4tixY7jppptsLvVHRETg2muvxe7du9Hc3Iympibs2bMH11xzjc3+9JGRkZg5c6bNa3744YfQ6XT4+c9/bvO3T0lJwfDhwy171jvLZDIBOPv/28aNG3HddddhypQpePvtt3H++efjj3/8o93PxUAmIoeMGjUKDz74IN555x0cO3YM9957L0pKSvDUU0/Z/Rzn7rdtviO4p324z71juK2tDWvWrMF5551n2eva+rk6Ojrw/PPPd9l/+8orrwQAS+fh4YcfxjPPPIPdu3dj2rRpiI+Px6RJk7B3795e6zfvsmYdDu6kdJ9vc1197Qa3du1a/PSnP0V6ejreeOMN7Nq1C3v27MEvfvELtLa2uqxus3N36+vr724ymVBfX4/6+nqYTCa7918XESQnJ3f5++/evVtRx9Ge323QoEE2d9nrdDpMnToVFRUVOHHihF3PpWg/ZCKi7gQHB2P+/Pn461//iu+++87unzv3phlz49bTPtzn7lmu1+uxbds2TJ06FZdffjk2b96M2NhYAGf3QA8MDMRNN92EuXPndvv6ubm5AICgoCDcd999uO+++3Dq1Cls2bIFjzzyCKZOnYry8nLLLnPnMtdTV1dn9+/sDKX7fJvrOvd9O9cbb7yB3NxcrFmzxuZvYjQanS3ZLn393QMCAhAbGwsRgU6ns3v/dZ1OZ5kjfq7uHnNEfn5+j/9/9PR36QnPkIlIke4aTQCWS5tpaWmWx5Tu1T127FiEhobijTfesHm8oqICW7duxaRJk7r8zE9+8hPs2LEDFRUVuPTSSy1nI2FhYZg4cSL+85//YNiwYd3uv33umRsAxMTEoLCwEHPnzkVdXV2vi3kMHjwYAHDkyBG7f0dnKN3n23w38ZAhQ3p9Xp1Oh5CQEJswrqqq6nKXNeCe/dcHDhyI9PR0rFq1yuaO8KamJrz33nuWO6/Dw8NxwQUXYO3atTZn7o2NjVi/fr3Nc86YMQMigsrKym7/9uYtfJ0VFBSEWbNm4YcffrD5f0VEsHnzZuTn5/fZIbI8l0sqIiK/MXXqVGRkZGDmzJkYNGgQTCYT9u3bh7/85S+IiIjAb3/7W8uxBQUFWL16NdasWYO8vDwYDIZeG8KYmBj84Q9/wCOPPIKbb74Zs2fPRm1tLR577DEYDAbMnz+/258bPHgwdu7cicsvvxwTJkzAli1bkJGRgSVLluCiiy7CxRdfjF//+tfIyclBY2MjioqKsH79emzduhUAMHPmTAwdOhSjRo1CYmIiSktLsXjxYmRnZ6N///491puRkYG8vDzs3r0bv/nNb2z+7eTJk9ixYwcAYP/+/QDOBmliYiISExNt9kO/9NJLsWPHjj6nJynd53v37t0IDAzEhAkTen3eGTNmYO3atbjzzjtRWFiI8vJyPP7440hNTcXhw4dtji0oKMD27duxfv16pKamIjIyssuUL6UCAgLw1FNP4cYbb8SMGTNwxx13wGg04umnn8apU6ewaNEiy7GPP/44rrjiCkyePBnz5s1DZ2cnnnzySYSHh9tcqRg/fjz+93//F7feeiv27t2LCRMmIDw8HMePH8fnn3+OgoIC/PrXv+61rk2bNqGpqQmNjY0AgO+//96y//qVV15pOTN+/PHHsWnTJlxxxRVYsGABoqKi8I9//APffPMN3n77bfvfCLtv/yIikrNTaW644Qbp37+/RERESHBwsGRlZclNN90k33//vc2xJSUlMmXKFImMjBQAkp2dLSL/d5d1T3tg/+Mf/5Bhw4ZZ9hmfNWtWl+k13S0MUlFRIYMGDZKcnBw5cuSIiJy90/cXv/iFpKenS3BwsCQmJsq4cePkiSeesPzcX/7yFxk3bpwkJCRISEiIZGVlyW233SYlJSV9vh9/+MMfJDY2VlpbW20eN/+O3X2de+f5yJEjJSUlpc/XElG2z/fFF18sM2fOtOt5Fy1aJDk5OaLX62Xw4MHyyiuvdLvYxr59+2T8+PESFhbW7e9izXyX9dNPP93l39DNXcvr1q2TMWPGiMFgkPDwcJk0aZL861//6vKzH3zwgeX/j6ysLFm0aFGPC4O8+uqrMmbMGAkPD5fQ0FDJz8+Xm2++Wfbu3dvne5Kdnd3j3/DcO+b3798v06dPl8jISDEYDHLhhRfK+vXr+3wNa9wPmYjICceOHUNubi5WrFiBn/3sZ4p/vrGxEXFxcVi8eHGPY92OOHLkCPr374+PPvoIkydPdtnzkvswkImInPTggw9i06ZN2Ldvn+IVujZs2IC5c+fi0KFDCAkJcVlNt956KyoqKvDJJ5+47DnJvXhTFxGRk37/+9/j2muvtWu+77mmT5+OkpISl4ZxR0cH8vPzuywRStrGQCa/UFlZiZ///OeIj49HWFgYRowYga+++krtsshHREZGYv78+cjMzFS7FABn7/z9/e9/jwEDBqhditfzZNvBu6zJ59XX12P8+PGYOHEiNm3ahKSkJBw5cgQxMTFql0ZEGubptoNjyOTzHnroIfzrX//Czp071S6FiLyIp9sOBjJ5VGtrq81G6s6Q/67aY02v13dZgWfIkCGWJex27NiB9PR03HnnnfjlL3/pkjqIyP1c1XbY224AKrQdiiZJETmhpaVFQkNDe5zXp/QrIiKiy2Pd7cai1+tFr9fLww8/LF9//bW89NJLYjAYbLaVIyLtcmXbYW+7IeL5toNnyOQxDQ0NiI6Oxg033OD0HaVtbW1YtWoVysvLERUVZXm8u55uSEgIRo0ahS+++MLy2G9+8xvs2bOn283PiUhbXNV2KGk3AM+3HbypizwuJCTEZVM8oqKibD5Y3UlNTe2ylu/gwYPx3nvvuaQGIvIMV7Ud9rQbgOfbDk57Ip83fvx4HDx40OaxQ4cOdVn3l4jImqfbDgYy+bx7770Xu3fvxp///GcUFRVh1apVePnll126TCER+R5Ptx0MZPJ5o0ePxj//+U+89dZbGDp0KB5//HEsXrwYN954o9qlEZGGebrt4Bgy+YUZM2ZgxowZapdBRF7Gk20Hz5CJiIg0gIFMRESkAQxkIiIiDWAgExERaQADmYiISAMYyERERBrAQCYiItIABjIREZEGMJCJiIg0gIFMdqutrcXnn3+OkydPql0KEXmRr776CgcOHIDRaFS7FE1jIJPdvv32W6xcuRJvvvmm2qUQkRd577338Nxzz6GoqEjtUjSNgUx2O3z4MABgwIABKldCRN6ipqYGtbW1CAgIQH5+vtrlaBoDmewiIjh06BAABjIR2c/ckc/OzobBYFC5Gm1jIJNdjh8/jsbGRgQHByMnJ0ftcojISxw8eBAAO/L2YCCTXcxnx/n5+QgK4q6dRGQfXlmzHwOZ7MIPFREpVVtbaxk/7tevn9rlaB4DmfpkPX48cOBAlashIm9hbjc4fmwfBjL1qaqqyjJ+nJ2drXY5ROQlzIHcv39/lSvxDgxk6pP5Q5WXl4fg4GCVqyEib8Era8owkKlP/FARkVJ1dXWoqanh/GMFGMjUK84/JiJHmNuNrKwshIaGqlyNd2AgU6+qq6vR0NDA+cdEpAg78soxkKlX5kn9HD8mIiW4IIhyDGTqFdevJiKlzOPHOp2O848VYCBTj0SEvVwiUsx6/jHHj+3HQKYemcePg4KCkJubq3Y5ROQlOP/YMQxk6hHnHxORI8xDXZwqqQwDmXrEuySJSKn6+nqcOHGC48cOYCBTt7h+NRE5gvOPHcdApm6dOHECp0+f5vgxESnCK2uOYyBTtzh+TESOYCA7joFM3eKHioiU4vixcxjI1AXXryYiR5jvrs7MzERYWJjK1XgfBjJ1ceLECZw6dYrjx0SkCBcScg4Dmbow93Jzc3MREhKicjVE5C241K5zGMjUBXu5RKTUqVOnUF1dDZ1OxxW6HMRAJhucf0xEjjC3Gxw/dhwDmWycPHmS48dEpBjXr3YeA5lsmD9UOTk5HD8mIrvxyprzgtQugLTFEx+qi6I/QZjeub5gs9GE111TDhE56fTp05bxY3fOP3a27dB6u8EzZLLg/GMicoS53cjIyEB4eLjK1XgvBjJZ1NTUoL6+HoGBgcjLy1O7HCLyEuzIuwYDmSzMHyrOPyYiJRjIrsFAJgt+qIhIqdOnT6Oqqorzj12AgUwAzo4fc0EQIlLK3JFPT0/n+LGTGMgEgOPHROQYXllzHQYyAbCdf6zX61Wuhoi8hXn9as4/dh4DmQCwl0tEyjU0NOD48eMcP3YRBjJx/jEROYTjx67FQCbU1tairq4OAQEByM/PV7scIvIS7Mi7FgOZbOYfc/yYiOzFQHYtBjLxQ0VEipnHjwHu8OQqDGRiIBORYua7q9PT0xEREaFyNb6BgeznampqUFtbi4CAAM4/JiK7cSEh12Mg+zlzLzcnJwcGg0HlaojIW5jbDgay6zCQ/Rx7uUSkVENDA44dOwaAbYcrMZD9HMePiUgp89lxWloax49diIHsx2pray3jx5x/TET2YkfePRjIfsz8ocrOzub4MRHZzdx2cP1q12Ig+zF+qIhIqcbGRsv4MecfuxYD2Y+ZA5kfKiKyl/X4cWRkpMrV+BYGsp+qq6tDTU0NAgIC0K9fP7XLISIvwfFj92Eg+ymOHxORIxjI7sNA9lP+9KFasGABdDqdzVdKSoraZRF5nTNnzqCyshKAfwx1ebrtCHLbM5Om+duCIOeddx62bNli+T4wMFDFaoi8k7kjn5qaiqioKJWr8QxPth0MZD9kPX7sL/OPg4KCeFZM5CR/XC7Tk20HL1n7IXMvNysrC6GhoSpX45yGhgabL6PR2O1xhw8fRlpaGnJzc3H99dfj6NGjHq6UyPv5ylRJe9sNwLNtBwPZD/nS+HFmZiaio6MtXwsXLuxyzJgxY7BixQp89NFHeOWVV1BVVYVx48ahtrZWhYqJvNOZM2dQUVEBwPvHj+1pNwDPtx28ZO2HfCmQy8vLbcay9Hp9l2OmTZtm+e+CggKMHTsW+fn5WL58Oe677z6P1Enk7cyXq31h/NiedgPwfNvBQPYz9fX1OHnyJHQ6nU/MP46KilLcOISHh6OgoMDSwBBR33ypI+9IuwG4v+3gJWs/Yz3/2NvHjx1lNBrxww8/IDU1Ve1SiLyGLwWyo9zddjCQ/Yw/fqjuv/9+7NixA8XFxfjyyy9RWFiIhoYGzJkzR+3SiLxCU1OTZf4x2w73tR28ZO1n/DGQKyoqMHv2bNTU1CAxMREXXnghdu/ejezsbLVLI/IKhw8fhoggJSXF68ePlfB028FA9iP19fU4ceKEz4wf22v16tVql0Dk1fyxIw94vu3gJWs/Yr4RwRfmHxOR5/hrIHsaA9mP+NtymUTkvKamJsv8Y7Yd7sVA9iPs5RKRUubx4+TkZERHR6tdjk9jIPuJU6dO+eX4MRE5x1eWy/QGDGQ/Yf5QZWZmIiwsTOVqiMhb8Mqa5zCQ/QQ/VESkFMePPYuB7CcYyESkVFFREcePPYiB7AdOnz6N6upq6HQ6r9+lhYg8hx15z2Ig+wGOHxORIxjInsVA9gPmDxXPjonIXs3NzSgvLwfAQPYUBrIfMC8IwmkLRGQv8/zjpKQkxMTEqF2OX+Ba1j7OevxYK/OPLz7/GCLDdE49R2OzuKgaIuqOealdLZ0dO9t2aL3d4BmyjzNfrs7IyEB4eLjK1RCRt+CVNc9jIPs43pRBREpZjx/z3hPPYSD7OAYyESllnn+clJSE2NhYtcvxGwxkH9bQ0ICqqirOPyYiRdiRVwcD2Ydx/JiIHMFAVgcD2Ydx/jERKdXS0oKysjIADGRPYyD7MG6bRkRKmcePExMTOX7sYQxkH9XQ0IDjx49z/JiIFOHlavUwkH2UeVJ/eno6x4+JyG4MZPUwkH2UeVI/P1REZK+WlhaUlpYCYNuhBgayj9LisndEpG1HjhyBiCAhIQFxcXFql+N3GMg+qKGhAceOHQPAO6yJyH5cLlNdDGQfZD47zsjIQEREhMrVEJG34PixuhjIPojzj4lIqdbWVs4/VhkD2Qexl0tEShUVFcFkMnH8WEUMZB/T2NhoGT9mIBORvdiRVx8D2cdYzz/m+DER2YuBrD4Gso8x3yXJ8WMisldrayvnH2sAA9nHmM+QOW2BiOx15MgRmEwmxMfHIz4+Xu1y/BYD2YecOXMGlZWVAHiGTET24+VqbWAg+xDzhyotLQ2RkZEqV0NE3oILgmgDA9mHsJdLREpZjx/zypq6GMg+hOtXE5FSR48etYwfJyQkqF2OX2Mg+4gzZ86goqICAHu5RGQ/7gynHQxkH2E+O05NTUVUVJTK1RCRt+BSu9rBQPYRHD8mIqWMRiNKSkoA8IYuLWAg+whzIPNDRUT2Ms8/jouL4/xjDWAg+4CmpibOPyYixayvrOl0OpWrIQayDzh8+DBEhOPHRKQIh7q0hYHsA3iXJBEpZTQaUVxcDIBth1YwkH0A5x8TkVLm+cexsbGcf6wRDGQv19TUZJl/zEAmIntZL5fJ8WNtYCB7OfP4cUpKCsePichunH+sPQxkL8ebMohIqba2Ns4/1iAGspdjIBORUkeOHEFnZyfHjzWGgezFOH5MRI7g/GNtYiB7saKiIogIkpOTER0drXY5ROQleGVNmxjIXoybihORUm1tbZx/rFEMZC/G+cdEpNTRo0fR2dmJmJgYJCYmql0OWWEge6nm5maUl5cDYCATkf04fqxdDGQvZZ5/zPFjIlKCS+1qFwPZS/FyNREpZT3/mG2H9jCQvRR7uUSkVHFxMTo6OhATE4OkpCS1y6FzMJC9EMePicgR1h15jh9rDwPZC5nnHyclJSEmJkbtcojIS3D9am1jIHshTuonIqXa29st84+5doE2BaldAClnDmRv/VAtbE9HSLtzfcG2dhOACtcUROQHjh49io6ODkRHR3vt+LGzbYfW2w2eIXuZlpYWlJWVAeBlJyKyH+cfax8D2ctYjx/HxsaqXQ4ReQkOdWkfA9nL8ENFREq1t7fj6NGjANh2aBkD2cswkIlIKfP846ioKCQnJ6tdDvWAgexFWlpaUFpaCoCB7IyFCxdCp9PhnnvuUbsUIo+w3hmO48eOc3fbwUD2Iubx48TERI4fO2jPnj14+eWXMWzYMLVLIfIYzj92nifaDgayF+HlauecOXMGN954I1555RV2aMhvcP6x8zzVdjCQvQgDuauGhgabL6PR2OOxc+fOxfTp03H55Zd7sEIidRUXF6O9vZ3jx1aUtBuA59oOBrKXsJ5/zED+P5mZmYiOjrZ8LVy4sNvjVq9eja+//rrHfyfyVdaXqzl+fJa97Qbg2baDK3V5iSNHjsBkMiEhIQFxcXFql6MZ5eXliIqKsnyv1+u7Pea3v/0tPv74YxgMBk+WR6Q6b1/Zzx3saTfMx3my7WAgewl+qLoXFRVl88HqzldffYUTJ05g5MiRlsc6Ozvx2Wef4YUXXoDRaERgYKC7SyXyOM4/7p497Qbg+baDgewlOH7suEmTJmH//v02j916660YNGgQHnzwQYYx+aySkhK0t7cjMjISKSkpapfjdTzddjCQvUBrayvnHzshMjISQ4cOtXksPDwc8fHxXR4n8iVcv9o5nm47eFOXFygqKuL4MREpZl4QhB1578AzZC9w+PBhAPxQudL27dvVLoHIrTh+7B7ubDt4huwF2MslIqVKS0st48epqalql0N2YCBrHMePicgR5o485x97DwayxpnnH8fHxyM+Pl7tcojIS3BmhvdhIGscP1REpFRHRweOHDkCgGsXeBMGssZxQRAiUso8/zgiIoLjx16Egaxhra2tKCkpAcBt04jIfpx/7J0YyBp29OhRy/hxQkKC2uUQkZfgUJd3YiBrGD9URKSU9fgx2w7vwkDWMAYyESlVWlqKtrY2jh97IQayRhmNRhQXFwNgIBOR/aznHwcEsIn3JvxraZR5/DguLo7zj4nIblxq13sxkDXKerlM3iVJRPbo7OxEUVERAE6V9EYMZI3i+DERKVVSUoK2tjaEh4dz/NgLMZA1qK2tzTL/mIFMRPYyd+Q5fuyd+BfToCNHjqCzsxOxsbGcf0xEduPKft6NgaxB1h8qjh8TkT06Ozs5/9jLMZA1iOPHRKRUaWkpjEYjwsPDkZaWpnY55AAGssa0tbVx/jERKcbxY+/Hv5rGHD16lOPHRKQYr6x5PwayxnCXFiJSynr+MQPZezGQNcZ6QRAiInuUlZXBaDQiLCwM6enpapdDDmIgawjnHxORI7h+tW/gX05DiouL0dHRgZiYGCQmJqpdDhF5Ca5f7RsYyBrC9auJSKnOzk5LIHNBEO/GQNYQrrJDREpx/Nh3MJDdqLb1DDpNJruOtZ5/3L9/f3eWRUQa1mkyoa61ye7jOf/YdwSpXYAvu2vHanxTU4GRidm4IDkHFyTnYHhCBgxBwV2OtR4/TkpKUqFaItKCg6eqMOX959AvOhGjk3MwJjkHo5NzkBUR1+1QFucf+w4GspuYxIRD9dVoaGvFtsqD2FZ5dnw4JCAQwxIyLAE9Mikbsfowzj8mIgDA93VVAICi0ydRdPok3jq0BwCQHBaFC5JyMDr5bAd/cGwqIML5xz6EgewmAboAfPnTh/BDXRX+faIE/64uwZ7qEpxoacTeE6XYe6IUL+7fAQAYGJOMQf+pBsDL1UT+rrDf+ZiUMRB7T5Tiy/+2G9/WVqK6uQHrS77F+pJvAQARwXqMDopHWGsrQkNDkZGRoXLl5CwGshsFBQSiICEdBQnpuG3IeIgIShvrsKe6BF9WF2PPiVIcOX0Sh+uqEN1yBsMz0hnIRIRYQzgmZw3B5KwhAICWjnbsqynHnuqznfuvTpSisd2IooqjGJEUg+F5gzh+7AMYyB6k0+mQExWPnKh4XNd/JACgpuUMNn+9Czv//S4apQEpKSkqV+l+jzz1v4gMNDj1HI2drXgdj7qoIiJtCw0KxtiUPIxNyQNw9savH+ursHLZa6g/UYa0i/xjdydn2w6ttxvsUqksITQCiWfO3omdn5/P8WMi6lNgQACGxKWi40Q9gLNtB3k/BrIGHD16FAA/VERkv5qaGjQ2NiIoKAjZ2dlql0MuwEBWmYjgyJEjABjIRGQ/893VWVlZCA7uOpWSvA8DWWUnT5609HKzsrLULoeIvASvrPkeBrLKzGfH2dnZ7OUSkd3MZ8gMZN/BQFYZL1cTkVLNzc04fvw4ALYdvoSBrDIGMhEpdfToUYgIEhMTERUVpXY55CIMZBU1Nzfj2LFjAIC8vDyVqyEib8HxY9/EQFaR+UOVlJTEXi4R2Y3jx76JgawiXq4mIqU6OztRUlICgG2Hr2Egq8gcyLxcTUT2qqyshNFoRGhoKFJTU9Uuh1yIgaySzs5OFBcXA2Avl4jsZ92R54YSvoV/TZVUVFSgra2NvVwiUoRDXb6LgawS9nKJyBEMZN/FJFAJP1REpFR9fT3q6uoQEBCAnJwctcshF2Mgq4SBTERKmduNjIwMGAzO7SlO2sNAVkFdXR3q6+vZyyUiRTgzw7cxkFXAXi4ROcLcdvTr10/lSsgdGMgq4OVqIlLKaDSivLwcANsOX8VAVgEDmYiUKikpgclkQkxMDGJjY9Uuh9yAgexhra2tqKioAMBAJiL7WXfkdTqdytWQOzCQPay0tBQmkwmxsbGIi4tTuxwi8hK8sub7GMgexl1aiEgpk8nELRf9AAPZw/ihIiKlqqqq0NzcjJCQEGRmZqpdDrkJA9mD2MslIkeYL1fn5OQgMDBQ5WrIXRjIHmTdy83IyFC7HCLyEhw/9g8MZA8yf6hyc3PZyyUiuzGQ/QMD2YO47B0RKdXY2IgTJ04AYNvh6xjIHsRl74hIKXO7kZqaivDwcJWrIXdiIHtIQ0ODpZebm5urcjVE5C14udp/MJA9xHx3dVpaGnu5RGQ3BrL/YCB7CMePiUip9vZ2lJaWAmAg+wMGsodw/Fg9S5cuxbBhwxAVFYWoqCiMHTsWmzZtUrssoj6VlZWho6MDERERSEpKUrscv+PptoOB7AHWvVyeIXteRkYGFi1ahL1792Lv3r247LLLMGvWLBw4cEDt0oh6Zb2QEDeU8DxPtx1BbnlWsmHu5UZGRrKXq4KZM2fafP+nP/0JS5cuxe7du3HeeeepVBVR37j2vbo83XYwkD3AevyYvVzXamhosPler9dDr9f3eHxnZyfeeecdNDU1YezYse4uj8hhIsKldt1EabsBeKbt4CVrD+Bdku6TmZmJ6Ohoy9fChQu7PW7//v2IiIiAXq/Hr371K/zzn//EkCFDPFwtkf1qamrQ0NCAwMBAZGdnq12OT7G33QA823bwDNnNRISB7Ebl5eWIioqyfN9TL3fgwIHYt28fTp06hffeew9z5szBjh07GMqkWeZ2IysrC8HBwSpX41vsbTcAz7YdDGQ3q6mpQWNjI4KCgtjLdQPz3Y99CQkJsdzhPmrUKOzZswdLlizB3//+d3eXSOQQzsxwH3vbDcCzbQcvWbuZ+aYM9nK1RURgNBrVLoOoR1y7QJvc2XbwDNnNeFOG+h555BFMmzYNmZmZaGxsxOrVq7F9+3Zs3rxZ7dKIutXc3Ixjx44BYNuhJk+3HQxkN+O0BfVVV1fjpptuwvHjxxEdHY1hw4Zh8+bNmDx5stqlEXWruLgYIoKEhARER0erXY7f8nTbwUB2o+bmZhw/fhwAA1lNy5YtU7sEIkU4fqwNnm47OIbsRkePHoWIIDEx0e4bCIiIOH7snxjIbsTxYyJSqrOzE8XFxQB4huxveMnajTh+3L0XJg2EXh/m1HMYjc3AIRcVRKQhlZWVMBqNMBgMSE1NVbscTXG27dB6u8EzZDfp7OxESUkJAAYyEdnP+nJ1QACbaH/Cv7absJdLRI7gyn7+i4HsJuzlEpEjeO+J/2JSuAmnLRCRUvX19aitrYVOp0Nubq7a5ZCHMZDdhNMWiEgp89lxRkYGDAaDytWQpzGQ3aC+vh51dXXs5RKRIpyZ4d8YyG5gPjtmL5eIlOD4sX9jILsB75IkIqXa2tpQVlYGgG2Hv2IguwEDmYiUKikpgclkQkxMDOLi4tQuh1TAQHYxo9GI8vJyALzDmojsZz1+rNPpVK6G1MBAdjHrXm5sbKza5RCRl+D4MTGQXcz6cjV7uURkD5PJxKEuYiC7Gj9URKRUdXU1mpubERwcjMzMTLXLIZUwkF3IZDLxshMRKWbuyOfm5iIwMFDlakgtDGQXqqqqQnNzM0JCQtjLJSK78coaAQxklzKfHefk5LCXS0R2YyATwEB2KS57R0RKnTlzBtXV1QC49r2/YyC7EMePiUgp89lxamoqwsPDVa6G1MRAdpHGxkb2colIMV6uJjMGsouYz47ZyyUiJbhVK5kxkF2E48dEpFRHRwdKSkoAcKldYiC7DMePiUipsrIydHR0ICIiAklJSWqXQypjILtAe3u7pZfLQCYie3GpXbLGQHaB8vJy9nKJSDGOH5M1BrILsJdLREqJiKXt4PgxAQxkl+C0BSJSqqamBg0NDQgMDERWVpba5ZAGMJCdZN3LZSATkb3M7UZWVhZCQkJUroa0gIHsJOtebnZ2ttrlEJGXYEeezsVAdpJ1Lzc4OFjlaojIW3CqJJ2Lgewk3pRBREq1tLSgsrISAAOZ/g8D2UmctkBEShUXF0NEkJCQgOjoaLXLIY1gIDuhpaUFx44dA8BeLhHZj0vtUncYyE44evQoe7lEpBjHj6k7DGQncPyYiJTq7OxkIFO3GMhO4PgxESl17NgxGI1GGAwGpKWlqV0OaQgD2UGdnZ0oLi4GwDNkIrKfefw4Ly8PAQFsgun/8P8GB1VWVlp6uampqWqXQ0RegperqScMZAdZX65mL5eI7MUVuqgnTBIH8UNFRErV19ejtrYWOp0Oubm5apdDGsNAdhAvOxGRUuZ2IyMjAwaDQeVqSGsYyA5gL5eIHMGZGdQbBrID2MslIkdw7QLqDQPZAVz2joiUamtrQ1lZGQCeIVP3GMgO4PgxESlVUlICk8mEmJgYxMfHq10OaRADWSHrXi4DmYjsZT1+rNPpVK6GtChI7QK8jXUvNy4uTu1yvNKcU9cjIsS5BulMm+A5F9VD5AmcKuk8Z9sOrbcbPENWyHr8mL1cIrKHyWTiUBf1iYGskPlDxZsyiMhe1dXVaGpqQnBwMLKystQuhzSKgayAyWTitAUiUszcbuTk5CAwMFDlakirGMgKVFdXo7m5GcHBwcjMzFS7HCLyEhw/JnswkBUwf6hyc3PZyyUiuzGQyR4MZAW47B0RKXXmzBlUV1cDYNtBvWMgK8DxYyJSytxupKSkICIiQuVqSMsYyHZiL5eIHMHL1WQvBrKdzB+q1NRUhIeHq1wNEXkLBjLZi4FsJ44fE5FSHR0dKC0tBcBApr4xkO3EXi4RKVVeXo729naEh4cjOTlZ7XJI4xjIdmAvl4gcwaV2SQkGsh3YyyUiR3D9alKCgWwH9nKJSCkRsWk7iPrCQLYDe7nebeHChRg9ejQiIyORlJSEq666CgcPHlS7LPJxtbW1aGhoQGBgILKzs9Uuhxzg6baDgdwH9nK9344dOzB37lzs3r0bn3zyCTo6OjBlyhQ0NTWpXRr5MHO7kZWVhZCQEJWrIUd4uu0Icsuz+hD2cr3f5s2bbb5/7bXXkJSUhK+++goTJkxQqSryddyq1ft5uu1gIPeBvVxta2hosPler9dDr9f3+jOnT58GAMTFxbmtLiIutatdjrQbgPvbDl6y7gPHj7UtMzMT0dHRlq+FCxf2eryI4L777sNFF12EoUOHeqhK8jctLS2orKwEwLZDi5S2G4Bn2g6eIfeBC4JoW3l5OaKioizf99XLveuuu/Dtt9/i888/d3dp5MeKi4shIkhISEB0dLTa5dA5lLYbgGfaDgZyL9jL1b6oqCibD1Zv7r77bnzwwQf47LPPkJGR4ebKyJ9xqV1tU9JuAJ5rOxjIvWAv1zeICO6++27885//xPbt25Gbm6t2SeTjOH7sGzzddjCQe8HL1b5h7ty5WLVqFd5//31ERkaiqqoKABAdHY3Q0FCVqyNfYzKZUFxcDIBnyN7O020Hb+rqBQPZNyxduhSnT5/GpZdeitTUVMvXmjVr1C6NfFBlZSVaW1thMBiQnp6udjnkBE+3HTxD7oHJZOId1j5CRNQugfyIuSOfm5uLgACe83gzT7cd/L+lB5WVlTAajTAYDEhLS1O7HCLyEryyRo5iIPfA+i5J9nKJyF4MZHIUk6YHnLZAREqdOnUKtbW10Ol0vJufFGMg94DTFohIKXO7kZ6ezjv4STEGcjese7k5OTlql0NEXoKXq8kZDORusJdLRI5gIJMzGMjd4IeKiJRqa2tDWVkZALYd5BgGcjcYyESkVElJCUwmE6KjoxEfH692OeSFGMjnYC+XiBxhvZCQTqdTuRryRgzkc7CXS0SOKCoqAsCOPDmOgXwO68vV7OUSkT1EhEvtktMYyOfg+DERKVVdXY2mpiYEBwcjMzNT7XLISzGQrXBDCSJyhLkjn5OTg6Ag7tlDjmEgWzlx4gR7uUSkGK+skSswkK2Yb8pgL5eIlGAgkyswkK3wcjURKXXmzBlUVVUB4GY05BwGshVOWyAipcwd+ZSUFERERKhcDXkzBvJ/nTlzBtXV1QDYyyUi+/FyNbkKA/m/2MslIkcwkMlVGMj/xQ8VESnV0dGBkpISAGw7yHm8lfi/GMieM+Oi3yIgVO/Uc5hajMBbi11TEJGDysvL0d7ejvDwcCQnJ6tdjs9ztu3QervBM2Swl0tEjjF35PPy8rjULjmNgQz2conIMeZA7tevn8qVkC9gIIO9XCJSTkRs2g4iZzGQwV4uESlXW1uL06dPIyAgADk5OWqXQz7A7wOZvVwicoS53cjKykJISIjK1ZAv8PtAZi+XiBzBmRnkan4fyOzlEpEjGMjkagxkfqiISKGWlhZUVlYCYNtBrsNAZiATkULFxcUQEcTHxyMmJkbtcshH+HUgs5dLRI5gR57cwa8Dmb1cInIEA5ncwa8DmR8qIlLKZDKhuLgYANsOci0GMvihIiL7VVZWorW1FQaDAenp6WqXQz7EbwOZvVwicoR57/Tc3FwEBPhtE0pu4Lf/N7GXS0SOKCoqAsCOPLme3wYye7lE5Ahz28FAJlfz2yRiL5eIlDp9+jRqamqg0+mQm5urdjnkY/w2kNnLJSKlzDeCpqenIzQ0VOVqyNf4ZSCzl0tEjuCVNXInvwxk9nKJyBHmK2vcqpXcwS8Dmb1cIlKqra0NZWVlAIB+/fqpXA35Ir8MZPZyiUip0tJSdHZ2IioqCvHx8WqXQz7I7wKZvVwicoR5qKtfv37Q6XQqV0O+yO8Cmb1cInKEOZB5ZY3cxe8Cmb1cIlJKRGzaDiJ38NtAZi+XiOxVXV2NpqYmBAcHIzMzU+1yyEf5VSCzl0tEjjC3G9nZ2QgKClK5GvJVfhXI7OUSkSO4VSt5gl919UwmE84//3wAYC+XiOyWlpaGvLw8DBgwQO1SyIf5VSqlpaXhjjvuULsMIvIyl19+OS6//HK1yyAf51eXrImIiLSKgUxERKQBDGQiIiINYCATERFpAAOZiIhIAxjIREREGsBAJiIi0gAGMhERkQYwkImIiDSAgUxERKQBDGQiIiINYCATERFpAAOZ/MJnn32GmTNnIi0tDTqdDuvWrVO7JCLSOE+3Gwxk8gtNTU0YPnw4XnjhBbVLISIv4el2w6+2XyT/NW3aNEybNk3tMojIi3i63WAgk8dJixEmFzwHADQ0NNg8rtfrodfrnXx2ItIiZ9sOrbcbDGTymJCQEKSkpKDq/qUueb6IiAhkZmbaPDZ//nwsWLDAJc9PRNrgyrZDy+0GA5k8xmAwoLi4GG1tbS55PhGBTqezeUwLvVwici1Xth1abjcYyORRBoMBBoNB7TKIyMv4Q9vBu6yJiIg0gGfI5BfOnDmDoqIiy/fFxcXYt28f4uLikJWVpWJlRKRVnm43dCIiLn9WIo3Zvn07Jk6c2OXxOXPm4PXXX/d8QUSkeZ5uNxjIREREGsAxZCIiIg1gIBMREWkAA5mIiEgDGMhEREQawEAmIiLSAAYyERGRBjCQiYiINICBTEREpAEMZCIiIg1gIBMREWkAA5mIiEgD/j+vKEri3+bkRAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -1778,7 +1810,7 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([1, 2])\n", - "angles: [89.2861856598184]\n", + "angles: [np.float64(89.2861856598184)]\n", "(1, 6) added\n", "**************************************************************\n", " \n", @@ -1799,7 +1831,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1814,7 +1846,7 @@ "angles_gdf len 3\n", "connectivity: 1\n", "Counter values: dict_values([1, 2])\n", - "angles: [87.79139488488063]\n", + "angles: [np.float64(87.79139488488063)]\n", "(8, 4) added\n", "**************************************************************\n", " \n", @@ -2066,7 +2098,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -2113,7 +2145,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -2135,7 +2167,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 38, "metadata": {}, "outputs": [], "source": [ @@ -2149,7 +2181,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 39, "metadata": {}, "outputs": [], "source": [ @@ -2174,7 +2206,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 40, "metadata": {}, "outputs": [ { @@ -2207,7 +2239,7 @@ " <meta name="viewport" content="width=device-width,\n", " initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />\n", " <style>\n", - " #map_8ca6d4b422ea6a8d8211d16b437c30ec {\n", + " #map_d5ae5f635c60ec2e2d6972df2e6bd9fb {\n", " position: relative;\n", " width: 100.0%;\n", " height: 100.0%;\n", @@ -2398,44 +2430,58 @@ "<body>\n", " \n", " \n", - " <div class="folium-map" id="map_8ca6d4b422ea6a8d8211d16b437c30ec" ></div>\n", + " <div class="folium-map" id="map_d5ae5f635c60ec2e2d6972df2e6bd9fb" ></div>\n", " \n", "</body>\n", "<script>\n", " \n", " \n", - " var map_8ca6d4b422ea6a8d8211d16b437c30ec = L.map(\n", - " "map_8ca6d4b422ea6a8d8211d16b437c30ec",\n", + " var map_d5ae5f635c60ec2e2d6972df2e6bd9fb = L.map(\n", + " "map_d5ae5f635c60ec2e2d6972df2e6bd9fb",\n", " {\n", " center: [50.102935750000015, 14.403062600000004],\n", " crs: L.CRS.EPSG3857,\n", - " zoom: 10,\n", - " zoomControl: true,\n", - " preferCanvas: false,\n", + " ...{\n", + " "zoom": 10,\n", + " "zoomControl": true,\n", + " "preferCanvas": false,\n", + "}\n", + "\n", " }\n", " );\n", - " L.control.scale().addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " L.control.scale().addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", " \n", "\n", " \n", " \n", - " var tile_layer_144e5103a0ffbba538577158de1c8ceb = L.tileLayer(\n", + " var tile_layer_e5c95f5cd33967de5fa8b0d6b6c0bafd = L.tileLayer(\n", " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",\n", - " {"attribution": "\\u0026copy; \\u003ca href=\\"https://www.openstreetmap.org/copyright\\"\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\"https://carto.com/attributions\\"\\u003eCARTO\\u003c/a\\u003e", "detectRetina": false, "maxZoom": 20, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}\n", + " {\n", + " "minZoom": 0,\n", + " "maxZoom": 20,\n", + " "maxNativeZoom": 20,\n", + " "noWrap": false,\n", + " "attribution": "\\u0026copy; \\u003ca href=\\"https://www.openstreetmap.org/copyright\\"\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\"https://carto.com/attributions\\"\\u003eCARTO\\u003c/a\\u003e",\n", + " "subdomains": "abc",\n", + " "detectRetina": false,\n", + " "tms": false,\n", + " "opacity": 1,\n", + "}\n", + "\n", " );\n", " \n", " \n", - " tile_layer_144e5103a0ffbba538577158de1c8ceb.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " tile_layer_e5c95f5cd33967de5fa8b0d6b6c0bafd.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " map_8ca6d4b422ea6a8d8211d16b437c30ec.fitBounds(\n", + " map_d5ae5f635c60ec2e2d6972df2e6bd9fb.fitBounds(\n", " [[50.10007700000001, 14.398981599999999], [50.10579450000001, 14.407143600000008]],\n", " {}\n", " );\n", " \n", " \n", - " function geo_json_2720fdbab9706987238be22d2fe5c965_styler(feature) {\n", + " function geo_json_5482c750e99258c086f171fa50bafc6f_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#3182bd", "fillColor": "#3182bd", "fillOpacity": 0.5, "weight": 8};\n", @@ -2459,53 +2505,55 @@ " return {"color": "#d9d9d9", "fillColor": "#d9d9d9", "fillOpacity": 0.5, "weight": 8};\n", " }\n", " }\n", - " function geo_json_2720fdbab9706987238be22d2fe5c965_highlighter(feature) {\n", + " function geo_json_5482c750e99258c086f171fa50bafc6f_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_2720fdbab9706987238be22d2fe5c965_pointToLayer(feature, latlng) {\n", + " function geo_json_5482c750e99258c086f171fa50bafc6f_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_2720fdbab9706987238be22d2fe5c965_styler(feature)\n", + " let style = geo_json_5482c750e99258c086f171fa50bafc6f_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_2720fdbab9706987238be22d2fe5c965_onEachFeature(feature, layer) {\n", + " function geo_json_5482c750e99258c086f171fa50bafc6f_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_2720fdbab9706987238be22d2fe5c965.resetStyle(e.target);\n", + " geo_json_5482c750e99258c086f171fa50bafc6f.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_2720fdbab9706987238be22d2fe5c965_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_5482c750e99258c086f171fa50bafc6f_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_2720fdbab9706987238be22d2fe5c965 = L.geoJson(null, {\n", - " onEachFeature: geo_json_2720fdbab9706987238be22d2fe5c965_onEachFeature,\n", + " var geo_json_5482c750e99258c086f171fa50bafc6f = L.geoJson(null, {\n", + " onEachFeature: geo_json_5482c750e99258c086f171fa50bafc6f_onEachFeature,\n", " \n", - " style: geo_json_2720fdbab9706987238be22d2fe5c965_styler,\n", - " pointToLayer: geo_json_2720fdbab9706987238be22d2fe5c965_pointToLayer,\n", - " opacity: 0.9,\n", + " style: geo_json_5482c750e99258c086f171fa50bafc6f_styler,\n", + " pointToLayer: geo_json_5482c750e99258c086f171fa50bafc6f_pointToLayer,\n", + " ...{\n", + " "opacity": 0.9,\n", + "}\n", " });\n", "\n", - " function geo_json_2720fdbab9706987238be22d2fe5c965_add (data) {\n", - " geo_json_2720fdbab9706987238be22d2fe5c965\n", + " function geo_json_5482c750e99258c086f171fa50bafc6f_add (data) {\n", + " geo_json_5482c750e99258c086f171fa50bafc6f\n", " .addData(data);\n", " }\n", - " geo_json_2720fdbab9706987238be22d2fe5c965_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#3182bd", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#9ecae1", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#e6550d", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fdae6b", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#31a354", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#c7e9c0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#9e9ac8", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#dadaeb", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#969696", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#d9d9d9", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_5482c750e99258c086f171fa50bafc6f_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#3182bd", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#9ecae1", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#e6550d", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fdae6b", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#31a354", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#c7e9c0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#9e9ac8", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#dadaeb", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#969696", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#d9d9d9", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_2720fdbab9706987238be22d2fe5c965.bindTooltip(\n", + " geo_json_5482c750e99258c086f171fa50bafc6f.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -2526,48 +2574,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_2720fdbab9706987238be22d2fe5c965.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_5482c750e99258c086f171fa50bafc6f.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_2bea82eadf75fa47941635a49528891e = {};\n", + " var color_map_4c96054fe3880dfb353c40a0788c4c36 = {};\n", "\n", " \n", - " color_map_2bea82eadf75fa47941635a49528891e.color = d3.scale.threshold()\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.color = d3.scale.threshold()\n", " .domain([0.0, 0.018036072144288578, 0.036072144288577156, 0.05410821643286573, 0.07214428857715431, 0.09018036072144289, 0.10821643286573146, 0.12625250501002003, 0.14428857715430862, 0.1623246492985972, 0.18036072144288579, 0.19839679358717435, 0.21643286573146292, 0.23446893787575152, 0.25250501002004005, 0.27054108216432865, 0.28857715430861725, 0.3066132264529058, 0.3246492985971944, 0.342685370741483, 0.36072144288577157, 0.3787575150300601, 0.3967935871743487, 0.4148296593186373, 0.43286573146292584, 0.45090180360721444, 0.46893787575150303, 0.48697394789579157, 0.5050100200400801, 0.5230460921843687, 0.5410821643286573, 0.5591182364729459, 0.5771543086172345, 0.5951903807615231, 0.6132264529058116, 0.6312625250501002, 0.6492985971943888, 0.6673346693386774, 0.685370741482966, 0.7034068136272545, 0.7214428857715431, 0.7394789579158316, 0.7575150300601202, 0.7755511022044088, 0.7935871743486974, 0.811623246492986, 0.8296593186372746, 0.8476953907815631, 0.8657314629258517, 0.8837675350701403, 0.9018036072144289, 0.9198396793587175, 0.9378757515030061, 0.9559118236472945, 0.9739478957915831, 0.9919839679358717, 1.0100200400801602, 1.028056112224449, 1.0460921843687374, 1.0641282565130261, 1.0821643286573146, 1.1002004008016033, 1.1182364729458918, 1.1362725450901803, 1.154308617234469, 1.1723446893787575, 1.1903807615230462, 1.2084168336673347, 1.2264529058116231, 1.2444889779559118, 1.2625250501002003, 1.280561122244489, 1.2985971943887775, 1.3166332665330662, 1.3346693386773547, 1.3527054108216432, 1.370741482965932, 1.3887775551102204, 1.406813627254509, 1.4248496993987976, 1.4428857715430863, 1.4609218436873748, 1.4789579158316633, 1.496993987975952, 1.5150300601202404, 1.5330661322645291, 1.5511022044088176, 1.5691382765531061, 1.5871743486973948, 1.6052104208416833, 1.623246492985972, 1.6412825651302605, 1.6593186372745492, 1.6773547094188377, 1.6953907815631262, 1.7134268537074149, 1.7314629258517034, 1.749498997995992, 1.7675350701402806, 1.785571142284569, 1.8036072144288577, 1.8216432865731462, 1.839679358717435, 1.8577154308617234, 1.8757515030060121, 1.8937875751503006, 1.911823647294589, 1.9298597194388778, 1.9478957915831663, 1.965931863727455, 1.9839679358717435, 2.002004008016032, 2.0200400801603204, 2.038076152304609, 2.056112224448898, 2.0741482965931866, 2.092184368737475, 2.1102204408817635, 2.1282565130260522, 2.1462925851703405, 2.164328657314629, 2.182364729458918, 2.2004008016032066, 2.218436873747495, 2.2364729458917836, 2.2545090180360723, 2.2725450901803605, 2.2905811623246493, 2.308617234468938, 2.3266533066132267, 2.344689378757515, 2.3627254509018036, 2.3807615230460923, 2.3987975951903806, 2.4168336673346693, 2.434869739478958, 2.4529058116232463, 2.470941883767535, 2.4889779559118237, 2.5070140280561124, 2.5250501002004007, 2.5430861723446894, 2.561122244488978, 2.5791583166332663, 2.597194388777555, 2.6152304609218437, 2.6332665330661325, 2.6513026052104207, 2.6693386773547094, 2.687374749498998, 2.7054108216432864, 2.723446893787575, 2.741482965931864, 2.7595190380761525, 2.7775551102204408, 2.7955911823647295, 2.813627254509018, 2.8316633266533064, 2.849699398797595, 2.867735470941884, 2.8857715430861726, 2.903807615230461, 2.9218436873747495, 2.9398797595190382, 2.9579158316633265, 2.975951903807615, 2.993987975951904, 3.012024048096192, 3.030060120240481, 3.0480961923847696, 3.0661322645290583, 3.0841683366733466, 3.1022044088176353, 3.120240480961924, 3.1382765531062122, 3.156312625250501, 3.1743486973947896, 3.1923847695390783, 3.2104208416833666, 3.2284569138276553, 3.246492985971944, 3.2645290581162323, 3.282565130260521, 3.3006012024048097, 3.3186372745490984, 3.3366733466933867, 3.3547094188376754, 3.372745490981964, 3.3907815631262523, 3.408817635270541, 3.4268537074148298, 3.444889779559118, 3.4629258517034067, 3.4809619238476954, 3.498997995991984, 3.5170340681362724, 3.535070140280561, 3.55310621242485, 3.571142284569138, 3.5891783567134268, 3.6072144288577155, 3.625250501002004, 3.6432865731462925, 3.661322645290581, 3.67935871743487, 3.697394789579158, 3.715430861723447, 3.7334669338677355, 3.7515030060120242, 3.7695390781563125, 3.787575150300601, 3.80561122244489, 3.823647294589178, 3.841683366733467, 3.8597194388777556, 3.8777555110220443, 3.8957915831663326, 3.9138276553106213, 3.93186372745491, 3.9498997995991982, 3.967935871743487, 3.9859719438877756, 4.004008016032064, 4.022044088176353, 4.040080160320641, 4.05811623246493, 4.076152304609218, 4.094188376753507, 4.112224448897796, 4.130260521042084, 4.148296593186373, 4.166332665330661, 4.18436873747495, 4.202404809619239, 4.220440881763527, 4.238476953907815, 4.2565130260521045, 4.274549098196393, 4.292585170340681, 4.31062124248497, 4.328657314629258, 4.346693386773547, 4.364729458917836, 4.382765531062124, 4.400801603206413, 4.4188376753507015, 4.43687374749499, 4.454909819639279, 4.472945891783567, 4.490981963927855, 4.509018036072145, 4.527054108216433, 4.545090180360721, 4.56312625250501, 4.5811623246492985, 4.599198396793587, 4.617234468937876, 4.635270541082164, 4.653306613226453, 4.671342685370742, 4.68937875751503, 4.707414829659319, 4.725450901803607, 4.7434869739478955, 4.761523046092185, 4.779559118236473, 4.797595190380761, 4.81563126252505, 4.833667334669339, 4.851703406813627, 4.869739478957916, 4.887775551102204, 4.905811623246493, 4.923847695390782, 4.94188376753507, 4.959919839679359, 4.977955911823647, 4.995991983967936, 5.014028056112225, 5.032064128256513, 5.050100200400801, 5.0681362725450905, 5.086172344689379, 5.104208416833667, 5.122244488977956, 5.140280561122244, 5.158316633266533, 5.176352705410822, 5.19438877755511, 5.212424849699399, 5.2304609218436875, 5.248496993987976, 5.266533066132265, 5.284569138276553, 5.302605210420841, 5.320641282565131, 5.338677354709419, 5.356713426853707, 5.374749498997996, 5.3927855711422845, 5.410821643286573, 5.428857715430862, 5.44689378757515, 5.4649298597194385, 5.482965931863728, 5.501002004008016, 5.519038076152305, 5.537074148296593, 5.5551102204408815, 5.573146292585171, 5.591182364729459, 5.609218436873747, 5.627254509018036, 5.645290581162325, 5.663326653306613, 5.681362725450902, 5.69939879759519, 5.717434869739479, 5.735470941883768, 5.753507014028056, 5.771543086172345, 5.789579158316633, 5.807615230460922, 5.825651302605211, 5.843687374749499, 5.861723446893787, 5.8797595190380765, 5.897795591182365, 5.915831663326653, 5.933867735470942, 5.95190380761523, 5.969939879759519, 5.987975951903808, 6.006012024048096, 6.024048096192384, 6.0420841683366735, 6.060120240480962, 6.078156312625251, 6.096192384769539, 6.114228456913827, 6.132264529058117, 6.150300601202405, 6.168336673346693, 6.186372745490982, 6.2044088176352705, 6.222444889779559, 6.240480961923848, 6.258517034068136, 6.2765531062124245, 6.294589178356714, 6.312625250501002, 6.330661322645291, 6.348697394789579, 6.3667334669338675, 6.384769539078157, 6.402805611222445, 6.420841683366733, 6.438877755511022, 6.456913827655311, 6.474949899799599, 6.492985971943888, 6.511022044088176, 6.529058116232465, 6.547094188376754, 6.565130260521042, 6.58316633266533, 6.601202404809619, 6.619238476953908, 6.637274549098197, 6.655310621242485, 6.673346693386773, 6.6913827655310625, 6.709418837675351, 6.727454909819639, 6.745490981963928, 6.763527054108216, 6.781563126252505, 6.799599198396794, 6.817635270541082, 6.83567134268537, 6.8537074148296595, 6.871743486973948, 6.889779559118236, 6.907815631262525, 6.925851703406813, 6.943887775551103, 6.961923847695391, 6.979959919839679, 6.997995991983968, 7.0160320641282565, 7.034068136272545, 7.052104208416834, 7.070140280561122, 7.0881763527054105, 7.1062124248497, 7.124248496993988, 7.142284569138276, 7.160320641282565, 7.1783567134268536, 7.196392785571143, 7.214428857715431, 7.232464929859719, 7.250501002004008, 7.268537074148297, 7.286573146292585, 7.304609218436874, 7.322645290581162, 7.340681362725451, 7.35871743486974, 7.376753507014028, 7.394789579158316, 7.412825651302605, 7.430861723446894, 7.448897795591182, 7.466933867735471, 7.484969939879759, 7.5030060120240485, 7.521042084168337, 7.539078156312625, 7.557114228456914, 7.575150300601202, 7.593186372745491, 7.61122244488978, 7.629258517034068, 7.647294589178356, 7.6653306613226455, 7.683366733466934, 7.701402805611222, 7.719438877755511, 7.7374749498997994, 7.755511022044089, 7.773547094188377, 7.791583166332665, 7.809619238476954, 7.8276553106212425, 7.845691382765531, 7.86372745490982, 7.881763527054108, 7.8997995991983965, 7.917835671342686, 7.935871743486974, 7.953907815631262, 7.971943887775551, 7.98997995991984, 8.008016032064129, 8.026052104208416, 8.044088176352705, 8.062124248496994, 8.080160320641282, 8.098196392785571, 8.11623246492986, 8.134268537074147, 8.152304609218437, 8.170340681362726, 8.188376753507015, 8.206412825651302, 8.224448897795591, 8.24248496993988, 8.260521042084168, 8.278557114228457, 8.296593186372746, 8.314629258517034, 8.332665330661323, 8.350701402805612, 8.3687374749499, 8.386773547094188, 8.404809619238478, 8.422845691382765, 8.440881763527054, 8.458917835671343, 8.47695390781563, 8.49498997995992, 8.513026052104209, 8.531062124248496, 8.549098196392785, 8.567134268537075, 8.585170340681362, 8.603206412825651, 8.62124248496994, 8.639278557114228, 8.657314629258517, 8.675350701402806, 8.693386773547093, 8.711422845691382, 8.729458917835672, 8.74749498997996, 8.765531062124248, 8.783567134268537, 8.801603206412826, 8.819639278557114, 8.837675350701403, 8.855711422845692, 8.87374749498998, 8.891783567134269, 8.909819639278558, 8.927855711422845, 8.945891783567134, 8.963927855711423, 8.98196392785571, 9.0])\n", " .range(['#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#3182bdff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#6baed6ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#9ecae1ff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#c6dbefff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#e6550dff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fd8d3cff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdae6bff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#fdd0a2ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#31a354ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#74c476ff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#a1d99bff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#c7e9c0ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#756bb1ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#9e9ac8ff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#bcbddcff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#dadaebff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#636363ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#969696ff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#bdbdbdff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff', '#d9d9d9ff']);\n", " \n", "\n", - " color_map_2bea82eadf75fa47941635a49528891e.x = d3.scale.linear()\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.x = d3.scale.linear()\n", " .domain([0.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_2bea82eadf75fa47941635a49528891e.legend = L.control({position: 'topright'});\n", - " color_map_2bea82eadf75fa47941635a49528891e.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_2bea82eadf75fa47941635a49528891e.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.legend = L.control({position: 'topright'});\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_2bea82eadf75fa47941635a49528891e.xAxis = d3.svg.axis()\n", - " .scale(color_map_2bea82eadf75fa47941635a49528891e.x)\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.xAxis = d3.svg.axis()\n", + " .scale(color_map_4c96054fe3880dfb353c40a0788c4c36.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', '', 1.35, '', '', 2.7, '', '', 4.05, '', '', 5.4, '', '', 6.75, '', '', 8.1, '', '']);\n", "\n", - " color_map_2bea82eadf75fa47941635a49528891e.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_2bea82eadf75fa47941635a49528891e.g = color_map_2bea82eadf75fa47941635a49528891e.svg.append("g")\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.g = color_map_4c96054fe3880dfb353c40a0788c4c36.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_2bea82eadf75fa47941635a49528891e.g.selectAll("rect")\n", - " .data(color_map_2bea82eadf75fa47941635a49528891e.color.range().map(function(d, i) {\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.g.selectAll("rect")\n", + " .data(color_map_4c96054fe3880dfb353c40a0788c4c36.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_2bea82eadf75fa47941635a49528891e.x(color_map_2bea82eadf75fa47941635a49528891e.color.domain()[i - 1]) : color_map_2bea82eadf75fa47941635a49528891e.x.range()[0],\n", - " x1: i < color_map_2bea82eadf75fa47941635a49528891e.color.domain().length ? color_map_2bea82eadf75fa47941635a49528891e.x(color_map_2bea82eadf75fa47941635a49528891e.color.domain()[i]) : color_map_2bea82eadf75fa47941635a49528891e.x.range()[1],\n", + " x0: i ? color_map_4c96054fe3880dfb353c40a0788c4c36.x(color_map_4c96054fe3880dfb353c40a0788c4c36.color.domain()[i - 1]) : color_map_4c96054fe3880dfb353c40a0788c4c36.x.range()[0],\n", + " x1: i < color_map_4c96054fe3880dfb353c40a0788c4c36.color.domain().length ? color_map_4c96054fe3880dfb353c40a0788c4c36.x(color_map_4c96054fe3880dfb353c40a0788c4c36.color.domain()[i]) : color_map_4c96054fe3880dfb353c40a0788c4c36.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -2577,12 +2629,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_2bea82eadf75fa47941635a49528891e.g.call(color_map_2bea82eadf75fa47941635a49528891e.xAxis).append("text")\n", + " color_map_4c96054fe3880dfb353c40a0788c4c36.g.call(color_map_4c96054fe3880dfb353c40a0788c4c36.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("nodeID");\n", " \n", - " function geo_json_96ba73f68b6eca55841fc8af743be14f_styler(feature) {\n", + " function geo_json_9d2a29810a8d4b480c6c12e18c313252_styler(feature) {\n", " switch(feature.id) {\n", " case "0": case "2": \n", " return {"color": "#54278f", "fillColor": "#54278f", "fillOpacity": 0.5, "weight": 2};\n", @@ -2600,52 +2653,54 @@ " return {"color": "#dadaeb", "fillColor": "#dadaeb", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_96ba73f68b6eca55841fc8af743be14f_highlighter(feature) {\n", + " function geo_json_9d2a29810a8d4b480c6c12e18c313252_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_96ba73f68b6eca55841fc8af743be14f_pointToLayer(feature, latlng) {\n", + " function geo_json_9d2a29810a8d4b480c6c12e18c313252_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 10, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_96ba73f68b6eca55841fc8af743be14f_styler(feature)\n", + " let style = geo_json_9d2a29810a8d4b480c6c12e18c313252_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_96ba73f68b6eca55841fc8af743be14f_onEachFeature(feature, layer) {\n", + " function geo_json_9d2a29810a8d4b480c6c12e18c313252_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_96ba73f68b6eca55841fc8af743be14f.resetStyle(e.target);\n", + " geo_json_9d2a29810a8d4b480c6c12e18c313252.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_96ba73f68b6eca55841fc8af743be14f_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_9d2a29810a8d4b480c6c12e18c313252_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_96ba73f68b6eca55841fc8af743be14f = L.geoJson(null, {\n", - " onEachFeature: geo_json_96ba73f68b6eca55841fc8af743be14f_onEachFeature,\n", + " var geo_json_9d2a29810a8d4b480c6c12e18c313252 = L.geoJson(null, {\n", + " onEachFeature: geo_json_9d2a29810a8d4b480c6c12e18c313252_onEachFeature,\n", " \n", - " style: geo_json_96ba73f68b6eca55841fc8af743be14f_styler,\n", - " pointToLayer: geo_json_96ba73f68b6eca55841fc8af743be14f_pointToLayer,\n", + " style: geo_json_9d2a29810a8d4b480c6c12e18c313252_styler,\n", + " pointToLayer: geo_json_9d2a29810a8d4b480c6c12e18c313252_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_96ba73f68b6eca55841fc8af743be14f_add (data) {\n", - " geo_json_96ba73f68b6eca55841fc8af743be14f\n", + " function geo_json_9d2a29810a8d4b480c6c12e18c313252_add (data) {\n", + " geo_json_9d2a29810a8d4b480c6c12e18c313252\n", " .addData(data);\n", " }\n", - " geo_json_96ba73f68b6eca55841fc8af743be14f_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "#54278f", "connectivity": 8}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "#807dba", "connectivity": 6}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "#54278f", "connectivity": 8}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "#6a51a3", "connectivity": 7}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "#3f007d", "connectivity": 9}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "#fcfbfd", "connectivity": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "#6a51a3", "connectivity": 7}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "#fcfbfd", "connectivity": 1}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "#efedf5", "connectivity": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "#dadaeb", "connectivity": 3}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_9d2a29810a8d4b480c6c12e18c313252_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "#54278f", "connectivity": 8}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "#807dba", "connectivity": 6}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "#54278f", "connectivity": 8}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "#6a51a3", "connectivity": 7}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "#3f007d", "connectivity": 9}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "#fcfbfd", "connectivity": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "#6a51a3", "connectivity": 7}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "#fcfbfd", "connectivity": 1}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "#efedf5", "connectivity": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "#dadaeb", "connectivity": 3}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_96ba73f68b6eca55841fc8af743be14f.bindTooltip(\n", + " geo_json_9d2a29810a8d4b480c6c12e18c313252.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -2666,48 +2721,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_96ba73f68b6eca55841fc8af743be14f.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_9d2a29810a8d4b480c6c12e18c313252.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_9a5b75c725f98020d784d6709b6fb44a = {};\n", + " var color_map_ac801250ad179acf17bcef26de589fb3 = {};\n", "\n", " \n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.color = d3.scale.threshold()\n", + " color_map_ac801250ad179acf17bcef26de589fb3.color = d3.scale.threshold()\n", " .domain([1.0, 1.0160320641282565, 1.032064128256513, 1.0480961923847696, 1.0641282565130261, 1.0801603206412826, 1.0961923847695392, 1.1122244488977957, 1.128256513026052, 1.1442885771543085, 1.160320641282565, 1.1763527054108216, 1.1923847695390781, 1.2084168336673347, 1.2244488977955912, 1.2404809619238477, 1.2565130260521042, 1.2725450901803608, 1.2885771543086173, 1.3046092184368738, 1.3206412825651301, 1.3366733466933867, 1.3527054108216432, 1.3687374749498997, 1.3847695390781563, 1.4008016032064128, 1.4168336673346693, 1.4328657314629258, 1.4488977955911824, 1.464929859719439, 1.4809619238476954, 1.496993987975952, 1.5130260521042085, 1.529058116232465, 1.5450901803607215, 1.561122244488978, 1.5771543086172346, 1.5931863727454911, 1.6092184368737477, 1.625250501002004, 1.6412825651302605, 1.657314629258517, 1.6733466933867736, 1.68937875751503, 1.7054108216432866, 1.7214428857715431, 1.7374749498997994, 1.753507014028056, 1.7695390781563125, 1.785571142284569, 1.8016032064128256, 1.817635270541082, 1.8336673346693386, 1.8496993987975952, 1.8657314629258517, 1.8817635270541082, 1.8977955911823647, 1.9138276553106213, 1.9298597194388778, 1.9458917835671343, 1.9619238476953909, 1.9779559118236474, 1.993987975951904, 2.0100200400801604, 2.026052104208417, 2.0420841683366735, 2.05811623246493, 2.0741482965931866, 2.090180360721443, 2.1062124248496996, 2.122244488977956, 2.1382765531062127, 2.154308617234469, 2.1703406813627257, 2.1863727454909823, 2.202404809619239, 2.2184368737474953, 2.2344689378757514, 2.250501002004008, 2.2665330661322645, 2.282565130260521, 2.2985971943887775, 2.314629258517034, 2.3306613226452906, 2.346693386773547, 2.3627254509018036, 2.37875751503006, 2.3947895791583167, 2.4108216432865732, 2.4268537074148298, 2.4428857715430863, 2.4589178356713424, 2.474949899799599, 2.4909819639278554, 2.507014028056112, 2.5230460921843685, 2.539078156312625, 2.5551102204408815, 2.571142284569138, 2.5871743486973946, 2.603206412825651, 2.6192384769539077, 2.635270541082164, 2.6513026052104207, 2.6673346693386772, 2.6833667334669338, 2.6993987975951903, 2.715430861723447, 2.7314629258517034, 2.74749498997996, 2.7635270541082164, 2.779559118236473, 2.7955911823647295, 2.811623246492986, 2.8276553106212425, 2.843687374749499, 2.8597194388777556, 2.875751503006012, 2.8917835671342687, 2.907815631262525, 2.9238476953907817, 2.9398797595190382, 2.9559118236472948, 2.9719438877755513, 2.987975951903808, 3.004008016032064, 3.0200400801603204, 3.036072144288577, 3.0521042084168335, 3.06813627254509, 3.0841683366733466, 3.100200400801603, 3.1162324649298596, 3.132264529058116, 3.1482965931863727, 3.164328657314629, 3.1803607214428857, 3.1963927855711423, 3.212424849699399, 3.2284569138276553, 3.244488977955912, 3.2605210420841684, 3.276553106212425, 3.2925851703406814, 3.308617234468938, 3.3246492985971945, 3.340681362725451, 3.3567134268537075, 3.372745490981964, 3.3887775551102206, 3.404809619238477, 3.4208416833667337, 3.43687374749499, 3.4529058116232463, 3.468937875751503, 3.4849699398797593, 3.501002004008016, 3.5170340681362724, 3.533066132264529, 3.5490981963927855, 3.565130260521042, 3.5811623246492985, 3.597194388777555, 3.6132264529058116, 3.629258517034068, 3.6452905811623246, 3.661322645290581, 3.6773547094188377, 3.693386773547094, 3.7094188376753507, 3.7254509018036073, 3.741482965931864, 3.7575150300601203, 3.773547094188377, 3.7895791583166334, 3.80561122244489, 3.8216432865731464, 3.837675350701403, 3.8537074148296595, 3.869739478957916, 3.8857715430861726, 3.9018036072144286, 3.917835671342685, 3.9338677354709417, 3.9498997995991982, 3.9659318637274548, 3.9819639278557113, 3.997995991983968, 4.014028056112224, 4.030060120240481, 4.046092184368737, 4.062124248496994, 4.07815631262525, 4.094188376753507, 4.110220440881763, 4.1262525050100205, 4.142284569138276, 4.158316633266534, 4.174348697394789, 4.190380761523047, 4.206412825651302, 4.22244488977956, 4.238476953907815, 4.254509018036073, 4.270541082164328, 4.286573146292586, 4.302605210420841, 4.318637274549099, 4.3346693386773545, 4.350701402805611, 4.3667334669338675, 4.382765531062124, 4.398797595190381, 4.414829659318637, 4.430861723446894, 4.44689378757515, 4.462925851703407, 4.478957915831663, 4.49498997995992, 4.511022044088176, 4.527054108216433, 4.543086172344689, 4.559118236472946, 4.575150300601202, 4.591182364729459, 4.6072144288577155, 4.623246492985972, 4.6392785571142285, 4.655310621242485, 4.671342685370742, 4.687374749498998, 4.703406813627255, 4.719438877755511, 4.735470941883768, 4.751503006012024, 4.767535070140281, 4.783567134268537, 4.799599198396793, 4.81563126252505, 4.831663326653306, 4.847695390781563, 4.863727454909819, 4.8797595190380765, 4.895791583166332, 4.9118236472945895, 4.927855711422845, 4.943887775551103, 4.959919839679358, 4.975951903807616, 4.991983967935871, 5.008016032064128, 5.024048096192384, 5.040080160320641, 5.056112224448897, 5.072144288577154, 5.0881763527054105, 5.104208416833667, 5.1202404809619235, 5.13627254509018, 5.152304609218437, 5.168336673346693, 5.18436873747495, 5.200400801603206, 5.216432865731463, 5.232464929859719, 5.248496993987976, 5.264529058116232, 5.280561122244489, 5.296593186372745, 5.312625250501002, 5.328657314629258, 5.344689378757515, 5.3607214428857715, 5.376753507014028, 5.3927855711422845, 5.408817635270541, 5.424849699398798, 5.440881763527054, 5.456913827655311, 5.472945891783567, 5.488977955911824, 5.50501002004008, 5.521042084168337, 5.537074148296593, 5.55310621242485, 5.569138276553106, 5.585170340681363, 5.601202404809619, 5.617234468937876, 5.6332665330661325, 5.649298597194389, 5.6653306613226455, 5.681362725450902, 5.697394789579159, 5.713426853707415, 5.729458917835672, 5.745490981963928, 5.761523046092185, 5.777555110220441, 5.793587174348698, 5.809619238476954, 5.825651302605211, 5.841683366733467, 5.857715430861724, 5.87374749498998, 5.889779559118236, 5.905811623246493, 5.921843687374749, 5.937875751503006, 5.953907815631262, 5.969939879759519, 5.985971943887775, 6.002004008016032, 6.018036072144288, 6.034068136272545, 6.050100200400801, 6.066132264529058, 6.082164328657314, 6.098196392785571, 6.114228456913827, 6.130260521042084, 6.1462925851703405, 6.162324649298597, 6.1783567134268536, 6.19438877755511, 6.210420841683367, 6.226452905811623, 6.24248496993988, 6.258517034068136, 6.274549098196393, 6.290581162324649, 6.306613226452906, 6.322645290581162, 6.338677354709419, 6.354709418837675, 6.370741482965932, 6.386773547094188, 6.402805611222445, 6.4188376753507015, 6.434869739478958, 6.4509018036072145, 6.466933867735471, 6.482965931863728, 6.498997995991984, 6.515030060120241, 6.531062124248497, 6.547094188376754, 6.56312625250501, 6.579158316633267, 6.595190380761523, 6.61122244488978, 6.627254509018036, 6.643286573146293, 6.659318637274549, 6.675350701402806, 6.6913827655310625, 6.707414829659319, 6.7234468937875755, 6.739478957915832, 6.755511022044089, 6.771543086172345, 6.787575150300601, 6.803607214428857, 6.819639278557114, 6.83567134268537, 6.851703406813627, 6.867735470941883, 6.88376753507014, 6.8997995991983965, 6.915831663326653, 6.9318637274549095, 6.947895791583166, 6.963927855711423, 6.979959919839679, 6.995991983967936, 7.012024048096192, 7.028056112224449, 7.044088176352705, 7.060120240480962, 7.076152304609218, 7.092184368737475, 7.108216432865731, 7.124248496993988, 7.140280561122244, 7.156312625250501, 7.1723446893787575, 7.188376753507014, 7.2044088176352705, 7.220440881763527, 7.236472945891784, 7.25250501002004, 7.268537074148297, 7.284569138276553, 7.30060120240481, 7.316633266533066, 7.332665330661323, 7.348697394789579, 7.364729458917836, 7.380761523046092, 7.396793587174349, 7.412825651302605, 7.428857715430862, 7.4448897795591185, 7.460921843687375, 7.4769539078156315, 7.492985971943888, 7.509018036072145, 7.525050100200401, 7.541082164328658, 7.557114228456914, 7.573146292585171, 7.589178356713427, 7.605210420841684, 7.62124248496994, 7.637274549098197, 7.653306613226453, 7.669338677354709, 7.6853707414829655, 7.701402805611222, 7.717434869739479, 7.733466933867735, 7.749498997995992, 7.765531062124248, 7.781563126252505, 7.797595190380761, 7.813627254509018, 7.829659318637274, 7.845691382765531, 7.861723446893787, 7.877755511022044, 7.8937875751503, 7.909819639278557, 7.925851703406813, 7.94188376753507, 7.9579158316633265, 7.973947895791583, 7.98997995991984, 8.006012024048097, 8.022044088176353, 8.038076152304608, 8.054108216432866, 8.070140280561123, 8.086172344689379, 8.102204408817634, 8.118236472945892, 8.13426853707415, 8.150300601202405, 8.16633266533066, 8.182364729458918, 8.198396793587175, 8.214428857715431, 8.230460921843687, 8.246492985971944, 8.262525050100201, 8.278557114228457, 8.294589178356713, 8.31062124248497, 8.326653306613228, 8.342685370741483, 8.358717434869739, 8.374749498997996, 8.390781563126254, 8.40681362725451, 8.422845691382765, 8.438877755511022, 8.45490981963928, 8.470941883767535, 8.486973947895791, 8.503006012024048, 8.519038076152306, 8.535070140280562, 8.551102204408817, 8.567134268537075, 8.58316633266533, 8.599198396793586, 8.615230460921843, 8.6312625250501, 8.647294589178356, 8.663326653306612, 8.67935871743487, 8.695390781563127, 8.711422845691382, 8.727454909819638, 8.743486973947896, 8.759519038076153, 8.775551102204409, 8.791583166332664, 8.807615230460922, 8.823647294589179, 8.839679358717435, 8.85571142284569, 8.871743486973948, 8.887775551102205, 8.90380761523046, 8.919839679358716, 8.935871743486974, 8.951903807615231, 8.967935871743487, 8.983967935871743, 9.0])\n", " .range(['#fcfbfdff', '#fcfbfdff', '#fcfbfdff', '#fcfbfdff', '#fbfafcff', '#fbfafcff', '#fbfafcff', '#fbfafcff', '#faf9fcff', '#faf9fcff', '#faf9fcff', '#faf9fcff', '#faf8fbff', '#faf8fbff', '#f9f8fbff', '#f9f8fbff', '#f9f7fbff', '#f9f7fbff', '#f8f7fbff', '#f8f7fbff', '#f8f7faff', '#f8f7faff', '#f8f6faff', '#f8f6faff', '#f7f6faff', '#f7f6faff', '#f7f5faff', '#f7f5faff', '#f6f5f9ff', '#f6f5f9ff', '#f6f4f9ff', '#f6f4f9ff', '#f5f4f9ff', '#f5f4f9ff', '#f5f4f9ff', '#f5f4f9ff', '#f5f3f8ff', '#f5f3f8ff', '#f4f3f8ff', '#f4f3f8ff', '#f4f2f8ff', '#f4f2f8ff', '#f3f2f8ff', '#f3f1f7ff', '#f3f1f7ff', '#f3f1f7ff', '#f3f1f7ff', '#f2f0f7ff', '#f2f0f7ff', '#f2f0f7ff', '#f2f0f7ff', '#f1f0f6ff', '#f1f0f6ff', '#f1eff6ff', '#f1eff6ff', '#f1eff6ff', '#f1eff6ff', '#f0eef6ff', '#f0eef6ff', '#f0eef5ff', '#f0eef5ff', '#efedf5ff', '#efedf5ff', '#efedf5ff', '#efedf5ff', '#eeecf5ff', '#eeecf5ff', '#eeecf4ff', '#eeecf4ff', '#edebf4ff', '#edebf4ff', '#ecebf4ff', '#ecebf4ff', '#eceaf3ff', '#eceaf3ff', '#ebe9f3ff', '#ebe9f3ff', '#eae9f3ff', '#eae9f3ff', '#eae8f2ff', '#eae8f2ff', '#e9e8f2ff', '#e9e8f2ff', '#e8e7f2ff', '#e8e6f2ff', '#e8e6f2ff', '#e7e6f1ff', '#e7e6f1ff', '#e6e5f1ff', '#e6e5f1ff', '#e6e5f1ff', '#e6e5f1ff', '#e5e4f0ff', '#e5e4f0ff', '#e4e3f0ff', '#e4e3f0ff', '#e4e3f0ff', '#e4e3f0ff', '#e3e2efff', '#e3e2efff', '#e2e2efff', '#e2e2efff', '#e2e1efff', '#e2e1efff', '#e1e0eeff', '#e1e0eeff', '#e0e0eeff', '#e0e0eeff', '#e0dfeeff', '#e0dfeeff', '#dfdfedff', '#dfdfedff', '#dedeedff', '#dedeedff', '#deddedff', '#deddedff', '#ddddecff', '#ddddecff', '#dcdcecff', '#dcdcecff', '#dcdcecff', '#dcdcecff', '#dbdbecff', '#dadaecff', '#dadaebff', '#dadaebff', '#dadaebff', '#d9d9ebff', '#d9d9eaff', '#d8d8eaff', '#d8d8eaff', '#d7d7e9ff', '#d7d7e9ff', '#d6d6e9ff', '#d6d6e9ff', '#d5d5e9ff', '#d5d5e9ff', '#d4d4e8ff', '#d4d4e8ff', '#d3d3e8ff', '#d3d3e8ff', '#d2d2e7ff', '#d2d2e7ff', '#d1d2e7ff', '#d1d2e7ff', '#d0d1e6ff', '#d0d1e6ff', '#cfd0e6ff', '#cfd0e6ff', '#cecfe5ff', '#cecfe5ff', '#cecee5ff', '#cecee5ff', '#cdcde4ff', '#cdcde4ff', '#cccce4ff', '#cccce4ff', '#cbcbe3ff', '#cbcbe3ff', '#cacae3ff', '#cacae3ff', '#c9c9e2ff', '#c8c8e2ff', '#c8c8e2ff', '#c7c8e2ff', '#c7c8e1ff', '#c6c7e1ff', '#c6c7e1ff', '#c5c6e1ff', '#c5c6e1ff', '#c4c5e1ff', '#c4c5e0ff', '#c3c4e0ff', '#c3c4e0ff', '#c2c3dfff', '#c2c3dfff', '#c1c2dfff', '#c1c2dfff', '#c0c1deff', '#c0c1deff', '#bfc0deff', '#bfc0deff', '#bebfddff', '#bebfddff', '#bebeddff', '#bebeddff', '#bdbedcff', '#bdbedcff', '#bcbddcff', '#bcbcdcff', '#bbbbdbff', '#bbbbdbff', '#babadbff', '#babadbff', '#b9b9daff', '#b9b9daff', '#b8b8d9ff', '#b8b8d9ff', '#b7b7d9ff', '#b7b7d9ff', '#b6b6d8ff', '#b5b5d8ff', '#b5b5d7ff', '#b4b4d7ff', '#b4b4d7ff', '#b3b3d7ff', '#b3b3d6ff', '#b2b2d6ff', '#b2b2d5ff', '#b1b1d5ff', '#b1b1d5ff', '#b0b0d5ff', '#b0afd4ff', '#afaed4ff', '#afaed4ff', '#aeadd3ff', '#aeadd3ff', '#aeacd2ff', '#aeacd2ff', '#adabd2ff', '#adabd2ff', '#acaad1ff', '#acaad1ff', '#aba9d0ff', '#aba9d0ff', '#aaa8d0ff', '#aaa8d0ff', '#a9a7cfff', '#a9a7cfff', '#a8a6cfff', '#a8a5cfff', '#a7a4ceff', '#a7a4ceff', '#a6a3cdff', '#a6a3cdff', '#a5a2cdff', '#a5a2cdff', '#a4a1ccff', '#a4a1ccff', '#a3a0cbff', '#a29fcbff', '#a29fcbff', '#a19ecbff', '#a19ecaff', '#a09dcaff', '#a09dcaff', '#9f9ccaff', '#9f9cc9ff', '#9e9bc9ff', '#9e9bc8ff', '#9e9ac8ff', '#9e9ac8ff', '#9d99c8ff', '#9d99c7ff', '#9c98c7ff', '#9c98c7ff', '#9b97c6ff', '#9b97c6ff', '#9a96c6ff', '#9a96c6ff', '#9995c6ff', '#9995c6ff', '#9894c5ff', '#9894c5ff', '#9793c5ff', '#9793c5ff', '#9692c4ff', '#9692c4ff', '#9591c4ff', '#9591c4ff', '#9490c3ff', '#9490c3ff', '#9390c3ff', '#9390c3ff', '#928fc3ff', '#928fc3ff', '#918ec2ff', '#918ec2ff', '#908dc2ff', '#8f8cc2ff', '#8f8cc1ff', '#8e8bc1ff', '#8e8bc1ff', '#8e8ac1ff', '#8e8ac0ff', '#8d89c0ff', '#8d89c0ff', '#8c88c0ff', '#8c88bfff', '#8b87bfff', '#8b87bfff', '#8a86bfff', '#8a86bfff', '#8986bfff', '#8986beff', '#8885beff', '#8885beff', '#8784bdff', '#8784bdff', '#8683bdff', '#8683bdff', '#8582bcff', '#8582bcff', '#8481bcff', '#8481bcff', '#8380bbff', '#8380bbff', '#827fbbff', '#827fbbff', '#817ebbff', '#817ebbff', '#807dbaff', '#807dbaff', '#807cbaff', '#807cbaff', '#7f7bb9ff', '#7f7ab9ff', '#7e79b8ff', '#7d78b8ff', '#7d78b7ff', '#7d77b7ff', '#7d77b7ff', '#7c76b7ff', '#7c75b6ff', '#7b74b6ff', '#7b74b5ff', '#7b73b5ff', '#7b72b4ff', '#7a71b4ff', '#7a71b4ff', '#7970b4ff', '#7970b3ff', '#796fb3ff', '#796eb2ff', '#786db2ff', '#786db2ff', '#776cb1ff', '#776bb1ff', '#776ab0ff', '#776ab0ff', '#7669afff', '#7668afff', '#7567afff', '#7567afff', '#7566aeff', '#7566aeff', '#7465adff', '#7464adff', '#7363adff', '#7363adff', '#7262acff', '#7262acff', '#7261abff', '#7260abff', '#715faaff', '#715eaaff', '#705eaaff', '#705daaff', '#705ca9ff', '#6f5ba9ff', '#6f5ba8ff', '#6e5aa8ff', '#6e5aa8ff', '#6e59a8ff', '#6e58a7ff', '#6d57a7ff', '#6d57a6ff', '#6c56a6ff', '#6c55a5ff', '#6c54a5ff', '#6c54a5ff', '#6b53a5ff', '#6b53a4ff', '#6a52a4ff', '#6a51a3ff', '#6950a3ff', '#6950a3ff', '#694fa2ff', '#694ea2ff', '#684da1ff', '#684da1ff', '#674ca1ff', '#674ca1ff', '#674ba0ff', '#674aa0ff', '#66499fff', '#66499fff', '#65489fff', '#65489fff', '#65479eff', '#65469eff', '#64459eff', '#64449eff', '#63449dff', '#63439dff', '#63439cff', '#63429cff', '#62429cff', '#61419cff', '#61409bff', '#613f9bff', '#613f9aff', '#603e9aff', '#603e9aff', '#5f3d9aff', '#5f3c99ff', '#5e3b99ff', '#5e3b98ff', '#5e3a98ff', '#5e3a98ff', '#5d3998ff', '#5d3897ff', '#5c3797ff', '#5c3797ff', '#5c3697ff', '#5c3696ff', '#5b3596ff', '#5b3495ff', '#5a3395ff', '#5a3395ff', '#5a3294ff', '#5a3194ff', '#593093ff', '#593093ff', '#582f93ff', '#582e93ff', '#582e92ff', '#582d92ff', '#572c92ff', '#572b92ff', '#562b91ff', '#562a91ff', '#552a90ff', '#552990ff', '#552890ff', '#552790ff', '#54278fff', '#54268fff', '#53268fff', '#53258fff', '#53258eff', '#52248eff', '#52238dff', '#51228dff', '#51228dff', '#51218dff', '#51218cff', '#50208cff', '#50208cff', '#4f1f8cff', '#4f1f8bff', '#4f1e8bff', '#4f1d8bff', '#4e1c8bff', '#4e1c8aff', '#4d1b8aff', '#4d1b89ff', '#4d1a89ff', '#4d1a89ff', '#4c1888ff', '#4c1888ff', '#4c1788ff', '#4c1688ff', '#4b1687ff', '#4b1587ff', '#4a1587ff', '#4a1487ff', '#4a1486ff', '#4a1386ff', '#491285ff', '#491185ff', '#481185ff', '#481085ff', '#481084ff', '#480f84ff', '#470f84ff', '#470e84ff', '#460d83ff', '#460c83ff', '#460c83ff', '#450b83ff', '#450b82ff', '#440a82ff', '#440a82ff', '#440982ff', '#440981ff', '#430881ff', '#430780ff', '#420680ff', '#420680ff', '#420580ff', '#42057fff', '#41047fff', '#41047fff', '#40037fff', '#40027eff', '#40017eff', '#40017eff', '#3f007eff', '#3f007dff']);\n", " \n", "\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.x = d3.scale.linear()\n", + " color_map_ac801250ad179acf17bcef26de589fb3.x = d3.scale.linear()\n", " .domain([1.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.legend = L.control({position: 'topright'});\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_ac801250ad179acf17bcef26de589fb3.legend = L.control({position: 'topright'});\n", + " color_map_ac801250ad179acf17bcef26de589fb3.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_ac801250ad179acf17bcef26de589fb3.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.xAxis = d3.svg.axis()\n", - " .scale(color_map_9a5b75c725f98020d784d6709b6fb44a.x)\n", + " color_map_ac801250ad179acf17bcef26de589fb3.xAxis = d3.svg.axis()\n", + " .scale(color_map_ac801250ad179acf17bcef26de589fb3.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([1.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1.815686274509804, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.631372549019608, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.447058823529412, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 4.262745098039216, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.078431372549019, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.894117647058824, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 6.709803921568628, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 7.525490196078431, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 8.341176470588234, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_ac801250ad179acf17bcef26de589fb3.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.g = color_map_9a5b75c725f98020d784d6709b6fb44a.svg.append("g")\n", + " color_map_ac801250ad179acf17bcef26de589fb3.g = color_map_ac801250ad179acf17bcef26de589fb3.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.g.selectAll("rect")\n", - " .data(color_map_9a5b75c725f98020d784d6709b6fb44a.color.range().map(function(d, i) {\n", + " color_map_ac801250ad179acf17bcef26de589fb3.g.selectAll("rect")\n", + " .data(color_map_ac801250ad179acf17bcef26de589fb3.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_9a5b75c725f98020d784d6709b6fb44a.x(color_map_9a5b75c725f98020d784d6709b6fb44a.color.domain()[i - 1]) : color_map_9a5b75c725f98020d784d6709b6fb44a.x.range()[0],\n", - " x1: i < color_map_9a5b75c725f98020d784d6709b6fb44a.color.domain().length ? color_map_9a5b75c725f98020d784d6709b6fb44a.x(color_map_9a5b75c725f98020d784d6709b6fb44a.color.domain()[i]) : color_map_9a5b75c725f98020d784d6709b6fb44a.x.range()[1],\n", + " x0: i ? color_map_ac801250ad179acf17bcef26de589fb3.x(color_map_ac801250ad179acf17bcef26de589fb3.color.domain()[i - 1]) : color_map_ac801250ad179acf17bcef26de589fb3.x.range()[0],\n", + " x1: i < color_map_ac801250ad179acf17bcef26de589fb3.color.domain().length ? color_map_ac801250ad179acf17bcef26de589fb3.x(color_map_ac801250ad179acf17bcef26de589fb3.color.domain()[i]) : color_map_ac801250ad179acf17bcef26de589fb3.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -2717,12 +2776,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_9a5b75c725f98020d784d6709b6fb44a.g.call(color_map_9a5b75c725f98020d784d6709b6fb44a.xAxis).append("text")\n", + " color_map_ac801250ad179acf17bcef26de589fb3.g.call(color_map_ac801250ad179acf17bcef26de589fb3.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("connectivity");\n", " \n", - " function geo_json_314a8206345634f725139c172aa569b7_styler(feature) {\n", + " function geo_json_481737a213be0aa700f931fc8dd15604_styler(feature) {\n", " switch(feature.id) {\n", " case "0": case "2": \n", " return {"color": "#a50f15", "fillColor": "#a50f15", "fillOpacity": 0.5, "weight": 2};\n", @@ -2740,52 +2800,54 @@ " return {"color": "#fcbca2", "fillColor": "#fcbca2", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_314a8206345634f725139c172aa569b7_highlighter(feature) {\n", + " function geo_json_481737a213be0aa700f931fc8dd15604_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_314a8206345634f725139c172aa569b7_pointToLayer(feature, latlng) {\n", + " function geo_json_481737a213be0aa700f931fc8dd15604_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_314a8206345634f725139c172aa569b7_styler(feature)\n", + " let style = geo_json_481737a213be0aa700f931fc8dd15604_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_314a8206345634f725139c172aa569b7_onEachFeature(feature, layer) {\n", + " function geo_json_481737a213be0aa700f931fc8dd15604_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_314a8206345634f725139c172aa569b7.resetStyle(e.target);\n", + " geo_json_481737a213be0aa700f931fc8dd15604.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_314a8206345634f725139c172aa569b7_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_481737a213be0aa700f931fc8dd15604_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_314a8206345634f725139c172aa569b7 = L.geoJson(null, {\n", - " onEachFeature: geo_json_314a8206345634f725139c172aa569b7_onEachFeature,\n", + " var geo_json_481737a213be0aa700f931fc8dd15604 = L.geoJson(null, {\n", + " onEachFeature: geo_json_481737a213be0aa700f931fc8dd15604_onEachFeature,\n", " \n", - " style: geo_json_314a8206345634f725139c172aa569b7_styler,\n", - " pointToLayer: geo_json_314a8206345634f725139c172aa569b7_pointToLayer,\n", + " style: geo_json_481737a213be0aa700f931fc8dd15604_styler,\n", + " pointToLayer: geo_json_481737a213be0aa700f931fc8dd15604_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_314a8206345634f725139c172aa569b7_add (data) {\n", - " geo_json_314a8206345634f725139c172aa569b7\n", + " function geo_json_481737a213be0aa700f931fc8dd15604_add (data) {\n", + " geo_json_481737a213be0aa700f931fc8dd15604\n", " .addData(data);\n", " }\n", - " geo_json_314a8206345634f725139c172aa569b7_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#a50f15", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ef3c2c", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#a50f15", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#cb181d", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#cb181d", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fee1d3", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fcbca2", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_481737a213be0aa700f931fc8dd15604_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#a50f15", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ef3c2c", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#a50f15", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#cb181d", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#cb181d", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fee1d3", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fcbca2", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_314a8206345634f725139c172aa569b7.bindTooltip(\n", + " geo_json_481737a213be0aa700f931fc8dd15604.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -2806,48 +2868,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_314a8206345634f725139c172aa569b7.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_481737a213be0aa700f931fc8dd15604.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_42ac98b1079831af98c2a01fc6323b93 = {};\n", + " var color_map_23aee2135710b1c8f89848bdc46525e4 = {};\n", "\n", " \n", - " color_map_42ac98b1079831af98c2a01fc6323b93.color = d3.scale.threshold()\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.color = d3.scale.threshold()\n", " .domain([1.0, 1.0160320641282565, 1.032064128256513, 1.0480961923847696, 1.0641282565130261, 1.0801603206412826, 1.0961923847695392, 1.1122244488977957, 1.128256513026052, 1.1442885771543085, 1.160320641282565, 1.1763527054108216, 1.1923847695390781, 1.2084168336673347, 1.2244488977955912, 1.2404809619238477, 1.2565130260521042, 1.2725450901803608, 1.2885771543086173, 1.3046092184368738, 1.3206412825651301, 1.3366733466933867, 1.3527054108216432, 1.3687374749498997, 1.3847695390781563, 1.4008016032064128, 1.4168336673346693, 1.4328657314629258, 1.4488977955911824, 1.464929859719439, 1.4809619238476954, 1.496993987975952, 1.5130260521042085, 1.529058116232465, 1.5450901803607215, 1.561122244488978, 1.5771543086172346, 1.5931863727454911, 1.6092184368737477, 1.625250501002004, 1.6412825651302605, 1.657314629258517, 1.6733466933867736, 1.68937875751503, 1.7054108216432866, 1.7214428857715431, 1.7374749498997994, 1.753507014028056, 1.7695390781563125, 1.785571142284569, 1.8016032064128256, 1.817635270541082, 1.8336673346693386, 1.8496993987975952, 1.8657314629258517, 1.8817635270541082, 1.8977955911823647, 1.9138276553106213, 1.9298597194388778, 1.9458917835671343, 1.9619238476953909, 1.9779559118236474, 1.993987975951904, 2.0100200400801604, 2.026052104208417, 2.0420841683366735, 2.05811623246493, 2.0741482965931866, 2.090180360721443, 2.1062124248496996, 2.122244488977956, 2.1382765531062127, 2.154308617234469, 2.1703406813627257, 2.1863727454909823, 2.202404809619239, 2.2184368737474953, 2.2344689378757514, 2.250501002004008, 2.2665330661322645, 2.282565130260521, 2.2985971943887775, 2.314629258517034, 2.3306613226452906, 2.346693386773547, 2.3627254509018036, 2.37875751503006, 2.3947895791583167, 2.4108216432865732, 2.4268537074148298, 2.4428857715430863, 2.4589178356713424, 2.474949899799599, 2.4909819639278554, 2.507014028056112, 2.5230460921843685, 2.539078156312625, 2.5551102204408815, 2.571142284569138, 2.5871743486973946, 2.603206412825651, 2.6192384769539077, 2.635270541082164, 2.6513026052104207, 2.6673346693386772, 2.6833667334669338, 2.6993987975951903, 2.715430861723447, 2.7314629258517034, 2.74749498997996, 2.7635270541082164, 2.779559118236473, 2.7955911823647295, 2.811623246492986, 2.8276553106212425, 2.843687374749499, 2.8597194388777556, 2.875751503006012, 2.8917835671342687, 2.907815631262525, 2.9238476953907817, 2.9398797595190382, 2.9559118236472948, 2.9719438877755513, 2.987975951903808, 3.004008016032064, 3.0200400801603204, 3.036072144288577, 3.0521042084168335, 3.06813627254509, 3.0841683366733466, 3.100200400801603, 3.1162324649298596, 3.132264529058116, 3.1482965931863727, 3.164328657314629, 3.1803607214428857, 3.1963927855711423, 3.212424849699399, 3.2284569138276553, 3.244488977955912, 3.2605210420841684, 3.276553106212425, 3.2925851703406814, 3.308617234468938, 3.3246492985971945, 3.340681362725451, 3.3567134268537075, 3.372745490981964, 3.3887775551102206, 3.404809619238477, 3.4208416833667337, 3.43687374749499, 3.4529058116232463, 3.468937875751503, 3.4849699398797593, 3.501002004008016, 3.5170340681362724, 3.533066132264529, 3.5490981963927855, 3.565130260521042, 3.5811623246492985, 3.597194388777555, 3.6132264529058116, 3.629258517034068, 3.6452905811623246, 3.661322645290581, 3.6773547094188377, 3.693386773547094, 3.7094188376753507, 3.7254509018036073, 3.741482965931864, 3.7575150300601203, 3.773547094188377, 3.7895791583166334, 3.80561122244489, 3.8216432865731464, 3.837675350701403, 3.8537074148296595, 3.869739478957916, 3.8857715430861726, 3.9018036072144286, 3.917835671342685, 3.9338677354709417, 3.9498997995991982, 3.9659318637274548, 3.9819639278557113, 3.997995991983968, 4.014028056112224, 4.030060120240481, 4.046092184368737, 4.062124248496994, 4.07815631262525, 4.094188376753507, 4.110220440881763, 4.1262525050100205, 4.142284569138276, 4.158316633266534, 4.174348697394789, 4.190380761523047, 4.206412825651302, 4.22244488977956, 4.238476953907815, 4.254509018036073, 4.270541082164328, 4.286573146292586, 4.302605210420841, 4.318637274549099, 4.3346693386773545, 4.350701402805611, 4.3667334669338675, 4.382765531062124, 4.398797595190381, 4.414829659318637, 4.430861723446894, 4.44689378757515, 4.462925851703407, 4.478957915831663, 4.49498997995992, 4.511022044088176, 4.527054108216433, 4.543086172344689, 4.559118236472946, 4.575150300601202, 4.591182364729459, 4.6072144288577155, 4.623246492985972, 4.6392785571142285, 4.655310621242485, 4.671342685370742, 4.687374749498998, 4.703406813627255, 4.719438877755511, 4.735470941883768, 4.751503006012024, 4.767535070140281, 4.783567134268537, 4.799599198396793, 4.81563126252505, 4.831663326653306, 4.847695390781563, 4.863727454909819, 4.8797595190380765, 4.895791583166332, 4.9118236472945895, 4.927855711422845, 4.943887775551103, 4.959919839679358, 4.975951903807616, 4.991983967935871, 5.008016032064128, 5.024048096192384, 5.040080160320641, 5.056112224448897, 5.072144288577154, 5.0881763527054105, 5.104208416833667, 5.1202404809619235, 5.13627254509018, 5.152304609218437, 5.168336673346693, 5.18436873747495, 5.200400801603206, 5.216432865731463, 5.232464929859719, 5.248496993987976, 5.264529058116232, 5.280561122244489, 5.296593186372745, 5.312625250501002, 5.328657314629258, 5.344689378757515, 5.3607214428857715, 5.376753507014028, 5.3927855711422845, 5.408817635270541, 5.424849699398798, 5.440881763527054, 5.456913827655311, 5.472945891783567, 5.488977955911824, 5.50501002004008, 5.521042084168337, 5.537074148296593, 5.55310621242485, 5.569138276553106, 5.585170340681363, 5.601202404809619, 5.617234468937876, 5.6332665330661325, 5.649298597194389, 5.6653306613226455, 5.681362725450902, 5.697394789579159, 5.713426853707415, 5.729458917835672, 5.745490981963928, 5.761523046092185, 5.777555110220441, 5.793587174348698, 5.809619238476954, 5.825651302605211, 5.841683366733467, 5.857715430861724, 5.87374749498998, 5.889779559118236, 5.905811623246493, 5.921843687374749, 5.937875751503006, 5.953907815631262, 5.969939879759519, 5.985971943887775, 6.002004008016032, 6.018036072144288, 6.034068136272545, 6.050100200400801, 6.066132264529058, 6.082164328657314, 6.098196392785571, 6.114228456913827, 6.130260521042084, 6.1462925851703405, 6.162324649298597, 6.1783567134268536, 6.19438877755511, 6.210420841683367, 6.226452905811623, 6.24248496993988, 6.258517034068136, 6.274549098196393, 6.290581162324649, 6.306613226452906, 6.322645290581162, 6.338677354709419, 6.354709418837675, 6.370741482965932, 6.386773547094188, 6.402805611222445, 6.4188376753507015, 6.434869739478958, 6.4509018036072145, 6.466933867735471, 6.482965931863728, 6.498997995991984, 6.515030060120241, 6.531062124248497, 6.547094188376754, 6.56312625250501, 6.579158316633267, 6.595190380761523, 6.61122244488978, 6.627254509018036, 6.643286573146293, 6.659318637274549, 6.675350701402806, 6.6913827655310625, 6.707414829659319, 6.7234468937875755, 6.739478957915832, 6.755511022044089, 6.771543086172345, 6.787575150300601, 6.803607214428857, 6.819639278557114, 6.83567134268537, 6.851703406813627, 6.867735470941883, 6.88376753507014, 6.8997995991983965, 6.915831663326653, 6.9318637274549095, 6.947895791583166, 6.963927855711423, 6.979959919839679, 6.995991983967936, 7.012024048096192, 7.028056112224449, 7.044088176352705, 7.060120240480962, 7.076152304609218, 7.092184368737475, 7.108216432865731, 7.124248496993988, 7.140280561122244, 7.156312625250501, 7.1723446893787575, 7.188376753507014, 7.2044088176352705, 7.220440881763527, 7.236472945891784, 7.25250501002004, 7.268537074148297, 7.284569138276553, 7.30060120240481, 7.316633266533066, 7.332665330661323, 7.348697394789579, 7.364729458917836, 7.380761523046092, 7.396793587174349, 7.412825651302605, 7.428857715430862, 7.4448897795591185, 7.460921843687375, 7.4769539078156315, 7.492985971943888, 7.509018036072145, 7.525050100200401, 7.541082164328658, 7.557114228456914, 7.573146292585171, 7.589178356713427, 7.605210420841684, 7.62124248496994, 7.637274549098197, 7.653306613226453, 7.669338677354709, 7.6853707414829655, 7.701402805611222, 7.717434869739479, 7.733466933867735, 7.749498997995992, 7.765531062124248, 7.781563126252505, 7.797595190380761, 7.813627254509018, 7.829659318637274, 7.845691382765531, 7.861723446893787, 7.877755511022044, 7.8937875751503, 7.909819639278557, 7.925851703406813, 7.94188376753507, 7.9579158316633265, 7.973947895791583, 7.98997995991984, 8.006012024048097, 8.022044088176353, 8.038076152304608, 8.054108216432866, 8.070140280561123, 8.086172344689379, 8.102204408817634, 8.118236472945892, 8.13426853707415, 8.150300601202405, 8.16633266533066, 8.182364729458918, 8.198396793587175, 8.214428857715431, 8.230460921843687, 8.246492985971944, 8.262525050100201, 8.278557114228457, 8.294589178356713, 8.31062124248497, 8.326653306613228, 8.342685370741483, 8.358717434869739, 8.374749498997996, 8.390781563126254, 8.40681362725451, 8.422845691382765, 8.438877755511022, 8.45490981963928, 8.470941883767535, 8.486973947895791, 8.503006012024048, 8.519038076152306, 8.535070140280562, 8.551102204408817, 8.567134268537075, 8.58316633266533, 8.599198396793586, 8.615230460921843, 8.6312625250501, 8.647294589178356, 8.663326653306612, 8.67935871743487, 8.695390781563127, 8.711422845691382, 8.727454909819638, 8.743486973947896, 8.759519038076153, 8.775551102204409, 8.791583166332664, 8.807615230460922, 8.823647294589179, 8.839679358717435, 8.85571142284569, 8.871743486973948, 8.887775551102205, 8.90380761523046, 8.919839679358716, 8.935871743486974, 8.951903807615231, 8.967935871743487, 8.983967935871743, 9.0])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.x = d3.scale.linear()\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.x = d3.scale.linear()\n", " .domain([1.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.legend = L.control({position: 'topright'});\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.legend = L.control({position: 'topright'});\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.xAxis = d3.svg.axis()\n", - " .scale(color_map_42ac98b1079831af98c2a01fc6323b93.x)\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.xAxis = d3.svg.axis()\n", + " .scale(color_map_23aee2135710b1c8f89848bdc46525e4.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([1.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1.815686274509804, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.631372549019608, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.447058823529412, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 4.262745098039216, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.078431372549019, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.894117647058824, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 6.709803921568628, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 7.525490196078431, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 8.341176470588234, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.g = color_map_42ac98b1079831af98c2a01fc6323b93.svg.append("g")\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.g = color_map_23aee2135710b1c8f89848bdc46525e4.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.g.selectAll("rect")\n", - " .data(color_map_42ac98b1079831af98c2a01fc6323b93.color.range().map(function(d, i) {\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.g.selectAll("rect")\n", + " .data(color_map_23aee2135710b1c8f89848bdc46525e4.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_42ac98b1079831af98c2a01fc6323b93.x(color_map_42ac98b1079831af98c2a01fc6323b93.color.domain()[i - 1]) : color_map_42ac98b1079831af98c2a01fc6323b93.x.range()[0],\n", - " x1: i < color_map_42ac98b1079831af98c2a01fc6323b93.color.domain().length ? color_map_42ac98b1079831af98c2a01fc6323b93.x(color_map_42ac98b1079831af98c2a01fc6323b93.color.domain()[i]) : color_map_42ac98b1079831af98c2a01fc6323b93.x.range()[1],\n", + " x0: i ? color_map_23aee2135710b1c8f89848bdc46525e4.x(color_map_23aee2135710b1c8f89848bdc46525e4.color.domain()[i - 1]) : color_map_23aee2135710b1c8f89848bdc46525e4.x.range()[0],\n", + " x1: i < color_map_23aee2135710b1c8f89848bdc46525e4.color.domain().length ? color_map_23aee2135710b1c8f89848bdc46525e4.x(color_map_23aee2135710b1c8f89848bdc46525e4.color.domain()[i]) : color_map_23aee2135710b1c8f89848bdc46525e4.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -2857,12 +2923,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_42ac98b1079831af98c2a01fc6323b93.g.call(color_map_42ac98b1079831af98c2a01fc6323b93.xAxis).append("text")\n", + " color_map_23aee2135710b1c8f89848bdc46525e4.g.call(color_map_23aee2135710b1c8f89848bdc46525e4.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("connectivity");\n", " \n", - " function geo_json_47fdf3d5e9a95b87f34b8727f476dd52_styler(feature) {\n", + " function geo_json_9c78f93b691003eecb71f5126e78fb84_styler(feature) {\n", " switch(feature.id) {\n", " case "0": case "3": \n", " return {"color": "#bc141a", "fillColor": "#bc141a", "fillOpacity": 0.5, "weight": 2};\n", @@ -2878,52 +2945,54 @@ " return {"color": "#fdcab5", "fillColor": "#fdcab5", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_47fdf3d5e9a95b87f34b8727f476dd52_highlighter(feature) {\n", + " function geo_json_9c78f93b691003eecb71f5126e78fb84_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_47fdf3d5e9a95b87f34b8727f476dd52_pointToLayer(feature, latlng) {\n", + " function geo_json_9c78f93b691003eecb71f5126e78fb84_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_47fdf3d5e9a95b87f34b8727f476dd52_styler(feature)\n", + " let style = geo_json_9c78f93b691003eecb71f5126e78fb84_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_47fdf3d5e9a95b87f34b8727f476dd52_onEachFeature(feature, layer) {\n", + " function geo_json_9c78f93b691003eecb71f5126e78fb84_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_47fdf3d5e9a95b87f34b8727f476dd52.resetStyle(e.target);\n", + " geo_json_9c78f93b691003eecb71f5126e78fb84.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_47fdf3d5e9a95b87f34b8727f476dd52_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_9c78f93b691003eecb71f5126e78fb84_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_47fdf3d5e9a95b87f34b8727f476dd52 = L.geoJson(null, {\n", - " onEachFeature: geo_json_47fdf3d5e9a95b87f34b8727f476dd52_onEachFeature,\n", + " var geo_json_9c78f93b691003eecb71f5126e78fb84 = L.geoJson(null, {\n", + " onEachFeature: geo_json_9c78f93b691003eecb71f5126e78fb84_onEachFeature,\n", " \n", - " style: geo_json_47fdf3d5e9a95b87f34b8727f476dd52_styler,\n", - " pointToLayer: geo_json_47fdf3d5e9a95b87f34b8727f476dd52_pointToLayer,\n", + " style: geo_json_9c78f93b691003eecb71f5126e78fb84_styler,\n", + " pointToLayer: geo_json_9c78f93b691003eecb71f5126e78fb84_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_47fdf3d5e9a95b87f34b8727f476dd52_add (data) {\n", - " geo_json_47fdf3d5e9a95b87f34b8727f476dd52\n", + " function geo_json_9c78f93b691003eecb71f5126e78fb84_add (data) {\n", + " geo_json_9c78f93b691003eecb71f5126e78fb84\n", " .addData(data);\n", " }\n", - " geo_json_47fdf3d5e9a95b87f34b8727f476dd52_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#bc141a", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#f14432", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#f14432", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#bc141a", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#fc8a6a", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fdcab5", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fc8a6a", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_9c78f93b691003eecb71f5126e78fb84_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#bc141a", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#f14432", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#f14432", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#bc141a", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#fc8a6a", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fdcab5", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fc8a6a", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_47fdf3d5e9a95b87f34b8727f476dd52.bindTooltip(\n", + " geo_json_9c78f93b691003eecb71f5126e78fb84.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -2944,48 +3013,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_47fdf3d5e9a95b87f34b8727f476dd52.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_9c78f93b691003eecb71f5126e78fb84.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_672b8b97bafd45dd67ea2d1cbf7ca59b = {};\n", + " var color_map_343bb295e5466c8b0defe9dad35869ac = {};\n", "\n", " \n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.color = d3.scale.threshold()\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.color = d3.scale.threshold()\n", " .domain([1.0, 1.0100200400801602, 1.0200400801603207, 1.0300601202404809, 1.0400801603206413, 1.0501002004008015, 1.060120240480962, 1.0701402805611222, 1.0801603206412826, 1.0901803607214429, 1.1002004008016033, 1.1102204408817635, 1.1202404809619237, 1.1302605210420842, 1.1402805611222444, 1.1503006012024048, 1.160320641282565, 1.1703406813627255, 1.1803607214428857, 1.1903807615230462, 1.2004008016032064, 1.2104208416833666, 1.220440881763527, 1.2304609218436875, 1.2404809619238477, 1.250501002004008, 1.2605210420841684, 1.2705410821643286, 1.280561122244489, 1.2905811623246493, 1.3006012024048097, 1.31062124248497, 1.3206412825651301, 1.3306613226452906, 1.340681362725451, 1.3507014028056112, 1.3607214428857715, 1.370741482965932, 1.3807615230460921, 1.3907815631262526, 1.4008016032064128, 1.4108216432865732, 1.4208416833667334, 1.4308617234468937, 1.440881763527054, 1.4509018036072145, 1.4609218436873748, 1.470941883767535, 1.4809619238476954, 1.4909819639278556, 1.5010020040080159, 1.5110220440881763, 1.5210420841683367, 1.531062124248497, 1.5410821643286572, 1.5511022044088176, 1.561122244488978, 1.5711422845691383, 1.5811623246492985, 1.591182364729459, 1.6012024048096194, 1.6112224448897794, 1.6212424849699398, 1.6312625250501003, 1.6412825651302605, 1.6513026052104207, 1.6613226452905812, 1.6713426853707416, 1.6813627254509018, 1.691382765531062, 1.7014028056112225, 1.711422845691383, 1.7214428857715431, 1.7314629258517034, 1.7414829659318638, 1.751503006012024, 1.7615230460921842, 1.7715430861723447, 1.7815631262525051, 1.7915831663326653, 1.8016032064128256, 1.811623246492986, 1.8216432865731464, 1.8316633266533067, 1.8416833667334669, 1.8517034068136273, 1.8617234468937875, 1.8717434869739478, 1.8817635270541082, 1.8917835671342687, 1.9018036072144289, 1.911823647294589, 1.9218436873747495, 1.93186372745491, 1.9418837675350702, 1.9519038076152304, 1.9619238476953909, 1.971943887775551, 1.9819639278557113, 1.9919839679358717, 2.0020040080160317, 2.012024048096192, 2.0220440881763526, 2.032064128256513, 2.0420841683366735, 2.052104208416834, 2.062124248496994, 2.0721442885771544, 2.0821643286573144, 2.092184368737475, 2.1022044088176353, 2.1122244488977957, 2.122244488977956, 2.132264529058116, 2.1422845691382766, 2.1523046092184366, 2.162324649298597, 2.1723446893787575, 2.182364729458918, 2.1923847695390783, 2.202404809619239, 2.212424849699399, 2.222444889779559, 2.2324649298597192, 2.2424849699398797, 2.25250501002004, 2.2625250501002006, 2.272545090180361, 2.282565130260521, 2.2925851703406814, 2.3026052104208414, 2.312625250501002, 2.3226452905811623, 2.3326653306613228, 2.342685370741483, 2.352705410821643, 2.3627254509018036, 2.3727454909819636, 2.382765531062124, 2.3927855711422845, 2.402805611222445, 2.4128256513026054, 2.422845691382766, 2.432865731462926, 2.4428857715430863, 2.4529058116232463, 2.4629258517034067, 2.472945891783567, 2.4829659318637276, 2.492985971943888, 2.503006012024048, 2.5130260521042085, 2.5230460921843685, 2.533066132264529, 2.5430861723446894, 2.55310621242485, 2.5631262525050102, 2.5731462925851702, 2.5831663326653307, 2.5931863727454907, 2.603206412825651, 2.6132264529058116, 2.623246492985972, 2.6332665330661325, 2.643286573146293, 2.653306613226453, 2.6633266533066133, 2.6733466933867733, 2.6833667334669338, 2.693386773547094, 2.7034068136272547, 2.713426853707415, 2.723446893787575, 2.7334669338677355, 2.7434869739478955, 2.753507014028056, 2.7635270541082164, 2.773547094188377, 2.7835671342685373, 2.7935871743486973, 2.8036072144288577, 2.8136272545090177, 2.823647294589178, 2.8336673346693386, 2.843687374749499, 2.8537074148296595, 2.86372745490982, 2.87374749498998, 2.8837675350701404, 2.8937875751503004, 2.903807615230461, 2.9138276553106213, 2.9238476953907817, 2.933867735470942, 2.943887775551102, 2.9539078156312626, 2.9639278557114226, 2.973947895791583, 2.9839679358717435, 2.993987975951904, 3.004008016032064, 3.0140280561122244, 3.024048096192385, 3.0340681362725452, 3.0440881763527052, 3.0541082164328657, 3.064128256513026, 3.0741482965931866, 3.0841683366733466, 3.094188376753507, 3.1042084168336674, 3.1142284569138274, 3.124248496993988, 3.1342685370741483, 3.1442885771543088, 3.1543086172344688, 3.164328657314629, 3.1743486973947896, 3.18436873747495, 3.19438877755511, 3.2044088176352705, 3.214428857715431, 3.224448897795591, 3.2344689378757514, 3.244488977955912, 3.2545090180360723, 3.2645290581162323, 3.2745490981963927, 3.284569138276553, 3.2945891783567136, 3.3046092184368736, 3.314629258517034, 3.3246492985971945, 3.3346693386773545, 3.344689378757515, 3.3547094188376754, 3.364729458917836, 3.374749498997996, 3.3847695390781563, 3.3947895791583167, 3.404809619238477, 3.414829659318637, 3.4248496993987976, 3.434869739478958, 3.444889779559118, 3.4549098196392785, 3.464929859719439, 3.4749498997995993, 3.4849699398797593, 3.49498997995992, 3.50501002004008, 3.5150300601202407, 3.5250501002004007, 3.535070140280561, 3.5450901803607215, 3.555110220440882, 3.565130260521042, 3.5751503006012024, 3.585170340681363, 3.595190380761523, 3.6052104208416833, 3.6152304609218437, 3.625250501002004, 3.635270541082164, 3.6452905811623246, 3.655310621242485, 3.6653306613226455, 3.6753507014028055, 3.685370741482966, 3.6953907815631264, 3.7054108216432864, 3.715430861723447, 3.7254509018036073, 3.7354709418837677, 3.7454909819639277, 3.755511022044088, 3.7655310621242486, 3.775551102204409, 3.785571142284569, 3.7955911823647295, 3.80561122244489, 3.81563126252505, 3.8256513026052104, 3.835671342685371, 3.8456913827655312, 3.8557114228456912, 3.8657314629258517, 3.875751503006012, 3.8857715430861726, 3.8957915831663326, 3.905811623246493, 3.9158316633266534, 3.9258517034068134, 3.935871743486974, 3.9458917835671343, 3.9559118236472948, 3.9659318637274548, 3.975951903807615, 3.9859719438877756, 3.995991983967936, 4.006012024048096, 4.0160320641282565, 4.026052104208417, 4.0360721442885765, 4.046092184368737, 4.056112224448897, 4.066132264529058, 4.076152304609218, 4.086172344689379, 4.096192384769539, 4.1062124248497, 4.11623246492986, 4.1262525050100205, 4.136272545090181, 4.1462925851703405, 4.156312625250501, 4.166332665330661, 4.176352705410822, 4.186372745490981, 4.196392785571142, 4.206412825651302, 4.216432865731463, 4.226452905811623, 4.236472945891784, 4.246492985971944, 4.2565130260521045, 4.266533066132265, 4.276553106212425, 4.286573146292586, 4.296593186372745, 4.306613226452906, 4.316633266533066, 4.326653306613227, 4.336673346693386, 4.346693386773547, 4.356713426853707, 4.3667334669338675, 4.376753507014028, 4.386773547094188, 4.396793587174349, 4.406813627254509, 4.41683366733467, 4.42685370741483, 4.436873747494991, 4.44689378757515, 4.456913827655311, 4.466933867735471, 4.476953907815631, 4.486973947895791, 4.4969939879759515, 4.507014028056112, 4.517034068136272, 4.527054108216433, 4.537074148296593, 4.547094188376754, 4.557114228456914, 4.567134268537075, 4.577154308617235, 4.587174348697395, 4.597194388777555, 4.6072144288577155, 4.617234468937876, 4.6272545090180355, 4.637274549098196, 4.647294589178356, 4.657314629258517, 4.667334669338677, 4.677354709418838, 4.687374749498998, 4.697394789579159, 4.707414829659319, 4.7174348697394795, 4.72745490981964, 4.7374749498997994, 4.74749498997996, 4.75751503006012, 4.767535070140281, 4.77755511022044, 4.787575150300601, 4.797595190380761, 4.807615230460922, 4.817635270541082, 4.8276553106212425, 4.837675350701403, 4.847695390781563, 4.857715430861724, 4.867735470941884, 4.877755511022045, 4.887775551102204, 4.897795591182365, 4.907815631262525, 4.917835671342685, 4.927855711422845, 4.937875751503006, 4.947895791583166, 4.9579158316633265, 4.967935871743487, 4.977955911823647, 4.987975951903808, 4.997995991983968, 5.008016032064128, 5.018036072144288, 5.028056112224449, 5.038076152304609, 5.04809619238477, 5.05811623246493, 5.0681362725450905, 5.078156312625251, 5.0881763527054105, 5.098196392785571, 5.108216432865731, 5.118236472945892, 5.128256513026052, 5.138276553106213, 5.148296593186373, 5.158316633266533, 5.168336673346693, 5.1783567134268536, 5.188376753507014, 5.198396793587174, 5.208416833667335, 5.218436873747495, 5.228456913827655, 5.238476953907815, 5.248496993987976, 5.258517034068136, 5.268537074148297, 5.278557114228457, 5.2885771543086175, 5.298597194388778, 5.3086172344689375, 5.318637274549098, 5.328657314629258, 5.338677354709419, 5.348697394789579, 5.35871743486974, 5.3687374749499, 5.37875751503006, 5.38877755511022, 5.398797595190381, 5.408817635270541, 5.4188376753507015, 5.428857715430862, 5.438877755511022, 5.448897795591182, 5.458917835671342, 5.468937875751503, 5.478957915831663, 5.488977955911824, 5.498997995991984, 5.509018036072145, 5.519038076152305, 5.529058116232465, 5.539078156312625, 5.5490981963927855, 5.559118236472946, 5.569138276553106, 5.579158316633267, 5.589178356713427, 5.599198396793587, 5.609218436873747, 5.619238476953908, 5.629258517034068, 5.6392785571142285, 5.649298597194389, 5.659318637274549, 5.669338677354709, 5.679358717434869, 5.68937875751503, 5.69939879759519, 5.709418837675351, 5.719438877755511, 5.729458917835672, 5.739478957915832, 5.749498997995992, 5.759519038076152, 5.7695390781563125, 5.779559118236473, 5.789579158316633, 5.799599198396794, 5.809619238476954, 5.819639278557114, 5.829659318637274, 5.839679358717435, 5.849699398797595, 5.859719438877756, 5.869739478957916, 5.8797595190380765, 5.889779559118236, 5.8997995991983965, 5.909819639278557, 5.919839679358717, 5.929859719438878, 5.939879759519038, 5.949899799599199, 5.959919839679359, 5.969939879759519, 5.979959919839679, 5.98997995991984, 6.0])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.x = d3.scale.linear()\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.x = d3.scale.linear()\n", " .domain([1.0, 6.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.legend = L.control({position: 'topright'});\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.legend = L.control({position: 'topright'});\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.xAxis = d3.svg.axis()\n", - " .scale(color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.x)\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.xAxis = d3.svg.axis()\n", + " .scale(color_map_343bb295e5466c8b0defe9dad35869ac.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([1.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1.5098039215686274, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.019607843137255, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.5294117647058822, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.0392156862745097, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.549019607843137, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 4.0588235294117645, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 4.568627450980392, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.078431372549019, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 5.588235294117647, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.g = color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.svg.append("g")\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.g = color_map_343bb295e5466c8b0defe9dad35869ac.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.g.selectAll("rect")\n", - " .data(color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.color.range().map(function(d, i) {\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.g.selectAll("rect")\n", + " .data(color_map_343bb295e5466c8b0defe9dad35869ac.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.x(color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.color.domain()[i - 1]) : color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.x.range()[0],\n", - " x1: i < color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.color.domain().length ? color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.x(color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.color.domain()[i]) : color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.x.range()[1],\n", + " x0: i ? color_map_343bb295e5466c8b0defe9dad35869ac.x(color_map_343bb295e5466c8b0defe9dad35869ac.color.domain()[i - 1]) : color_map_343bb295e5466c8b0defe9dad35869ac.x.range()[0],\n", + " x1: i < color_map_343bb295e5466c8b0defe9dad35869ac.color.domain().length ? color_map_343bb295e5466c8b0defe9dad35869ac.x(color_map_343bb295e5466c8b0defe9dad35869ac.color.domain()[i]) : color_map_343bb295e5466c8b0defe9dad35869ac.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -2995,12 +3068,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.g.call(color_map_672b8b97bafd45dd67ea2d1cbf7ca59b.xAxis).append("text")\n", + " color_map_343bb295e5466c8b0defe9dad35869ac.g.call(color_map_343bb295e5466c8b0defe9dad35869ac.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("degree");\n", " \n", - " function geo_json_a28d71e4798ccee310a0cf9b8847de6b_styler(feature) {\n", + " function geo_json_ca2557cc267ed2f39f50c77e77076e42_styler(feature) {\n", " switch(feature.id) {\n", " case "0": case "3": \n", " return {"color": "#fcb499", "fillColor": "#fcb499", "fillOpacity": 0.5, "weight": 2};\n", @@ -3018,52 +3092,54 @@ " return {"color": "#ffeee7", "fillColor": "#ffeee7", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_a28d71e4798ccee310a0cf9b8847de6b_highlighter(feature) {\n", + " function geo_json_ca2557cc267ed2f39f50c77e77076e42_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_a28d71e4798ccee310a0cf9b8847de6b_pointToLayer(feature, latlng) {\n", + " function geo_json_ca2557cc267ed2f39f50c77e77076e42_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_a28d71e4798ccee310a0cf9b8847de6b_styler(feature)\n", + " let style = geo_json_ca2557cc267ed2f39f50c77e77076e42_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_a28d71e4798ccee310a0cf9b8847de6b_onEachFeature(feature, layer) {\n", + " function geo_json_ca2557cc267ed2f39f50c77e77076e42_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_a28d71e4798ccee310a0cf9b8847de6b.resetStyle(e.target);\n", + " geo_json_ca2557cc267ed2f39f50c77e77076e42.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_a28d71e4798ccee310a0cf9b8847de6b_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_ca2557cc267ed2f39f50c77e77076e42_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_a28d71e4798ccee310a0cf9b8847de6b = L.geoJson(null, {\n", - " onEachFeature: geo_json_a28d71e4798ccee310a0cf9b8847de6b_onEachFeature,\n", + " var geo_json_ca2557cc267ed2f39f50c77e77076e42 = L.geoJson(null, {\n", + " onEachFeature: geo_json_ca2557cc267ed2f39f50c77e77076e42_onEachFeature,\n", " \n", - " style: geo_json_a28d71e4798ccee310a0cf9b8847de6b_styler,\n", - " pointToLayer: geo_json_a28d71e4798ccee310a0cf9b8847de6b_pointToLayer,\n", + " style: geo_json_ca2557cc267ed2f39f50c77e77076e42_styler,\n", + " pointToLayer: geo_json_ca2557cc267ed2f39f50c77e77076e42_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_a28d71e4798ccee310a0cf9b8847de6b_add (data) {\n", - " geo_json_a28d71e4798ccee310a0cf9b8847de6b\n", + " function geo_json_ca2557cc267ed2f39f50c77e77076e42_add (data) {\n", + " geo_json_ca2557cc267ed2f39f50c77e77076e42\n", " .addData(data);\n", " }\n", - " geo_json_a28d71e4798ccee310a0cf9b8847de6b_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fcb499", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fdd2bf", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fee6da", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fcb499", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#fedecf", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#ffeee7", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_ca2557cc267ed2f39f50c77e77076e42_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fcb499", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fdd2bf", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fee6da", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fcb499", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#fedecf", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#ffeee7", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_a28d71e4798ccee310a0cf9b8847de6b.bindTooltip(\n", + " geo_json_ca2557cc267ed2f39f50c77e77076e42.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -3084,48 +3160,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_a28d71e4798ccee310a0cf9b8847de6b.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_ca2557cc267ed2f39f50c77e77076e42.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_111a03ba5ecf7f3e6b7868ced0f6c4af = {};\n", + " var color_map_ce6b62b362f1c28b4349afe4361f4ea7 = {};\n", "\n", " \n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.color = d3.scale.threshold()\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.color = d3.scale.threshold()\n", " .domain([0.0, 0.0010112818229050693, 0.0020225636458101387, 0.003033845468715208, 0.004045127291620277, 0.005056409114525347, 0.006067690937430416, 0.007078972760335486, 0.008090254583240555, 0.009101536406145624, 0.010112818229050694, 0.011124100051955764, 0.012135381874860832, 0.013146663697765902, 0.014157945520670972, 0.015169227343576041, 0.01618050916648111, 0.01719179098938618, 0.01820307281229125, 0.01921435463519632, 0.02022563645810139, 0.021236918281006458, 0.022248200103911528, 0.023259481926816598, 0.024270763749721664, 0.025282045572626734, 0.026293327395531804, 0.027304609218436873, 0.028315891041341943, 0.029327172864247013, 0.030338454687152083, 0.03134973651005715, 0.03236101833296222, 0.03337230015586729, 0.03438358197877236, 0.03539486380167743, 0.0364061456245825, 0.03741742744748757, 0.03842870927039264, 0.03943999109329771, 0.04045127291620278, 0.04146255473910785, 0.042473836562012916, 0.04348511838491799, 0.044496400207823056, 0.04550768203072813, 0.046518963853633195, 0.04753024567653827, 0.04854152749944333, 0.0495528093223484, 0.05056409114525347, 0.05157537296815854, 0.05258665479106361, 0.05359793661396868, 0.05460921843687375, 0.05562050025977882, 0.056631782082683886, 0.05764306390558896, 0.058654345728494026, 0.0596656275513991, 0.060676909374304165, 0.06168819119720924, 0.0626994730201143, 0.06371075484301937, 0.06472203666592444, 0.0657333184888295, 0.06674460031173458, 0.06775588213463965, 0.06876716395754472, 0.06977844578044978, 0.07078972760335486, 0.07180100942625993, 0.072812291249165, 0.07382357307207006, 0.07483485489497514, 0.07584613671788021, 0.07685741854078527, 0.07786870036369034, 0.07887998218659542, 0.07989126400950049, 0.08090254583240555, 0.08191382765531062, 0.0829251094782157, 0.08393639130112077, 0.08494767312402583, 0.0859589549469309, 0.08697023676983598, 0.08798151859274105, 0.08899280041564611, 0.09000408223855118, 0.09101536406145626, 0.09202664588436132, 0.09303792770726639, 0.09404920953017146, 0.09506049135307654, 0.09607177317598159, 0.09708305499888666, 0.09809433682179174, 0.0991056186446968, 0.10011690046760187, 0.10112818229050693, 0.10213946411341202, 0.10315074593631708, 0.10416202775922215, 0.10517330958212721, 0.1061845914050323, 0.10719587322793736, 0.10820715505084243, 0.1092184368737475, 0.11022971869665257, 0.11124100051955764, 0.1122522823424627, 0.11326356416536777, 0.11427484598827285, 0.11528612781117792, 0.11629740963408298, 0.11730869145698805, 0.11831997327989313, 0.1193312551027982, 0.12034253692570326, 0.12135381874860833, 0.12236510057151341, 0.12337638239441848, 0.12438766421732354, 0.1253989460402286, 0.1264102278631337, 0.12742150968603874, 0.12843279150894382, 0.12944407333184887, 0.13045535515475395, 0.131466636977659, 0.1324779188005641, 0.13348920062346917, 0.13450048244637425, 0.1355117642692793, 0.13652304609218438, 0.13753432791508943, 0.1385456097379945, 0.13955689156089957, 0.14056817338380465, 0.14157945520670973, 0.1425907370296148, 0.14360201885251986, 0.14461330067542494, 0.14562458249833, 0.14663586432123507, 0.14764714614414012, 0.1486584279670452, 0.14966970978995028, 0.15068099161285536, 0.15169227343576042, 0.1527035552586655, 0.15371483708157055, 0.15472611890447563, 0.15573740072738068, 0.15674868255028576, 0.15775996437319084, 0.15877124619609592, 0.15978252801900097, 0.16079380984190603, 0.1618050916648111, 0.16281637348771616, 0.16382765531062124, 0.16483893713352632, 0.1658502189564314, 0.16686150077933645, 0.16787278260224153, 0.16888406442514659, 0.16989534624805167, 0.17090662807095672, 0.1719179098938618, 0.17292919171676688, 0.17394047353967196, 0.174951755362577, 0.1759630371854821, 0.17697431900838714, 0.17798560083129222, 0.17899688265419728, 0.18000816447710236, 0.18101944630000744, 0.18203072812291252, 0.18304200994581757, 0.18405329176872265, 0.1850645735916277, 0.18607585541453278, 0.18708713723743783, 0.18809841906034291, 0.189109700883248, 0.19012098270615307, 0.19113226452905813, 0.19214354635196318, 0.19315482817486826, 0.1941661099977733, 0.1951773918206784, 0.19618867364358347, 0.19719995546648855, 0.1982112372893936, 0.19922251911229868, 0.20023380093520374, 0.20124508275810882, 0.20225636458101387, 0.20326764640391895, 0.20427892822682403, 0.2052902100497291, 0.20630149187263416, 0.20731277369553924, 0.2083240555184443, 0.20933533734134938, 0.21034661916425443, 0.2113579009871595, 0.2123691828100646, 0.21338046463296967, 0.21439174645587472, 0.2154030282787798, 0.21641431010168485, 0.21742559192458993, 0.218436873747495, 0.21944815557040007, 0.22045943739330515, 0.22147071921621023, 0.22248200103911528, 0.22349328286202033, 0.2245045646849254, 0.2255158465078305, 0.22652712833073554, 0.22753841015364062, 0.2285496919765457, 0.22956097379945076, 0.23057225562235584, 0.2315835374452609, 0.23259481926816597, 0.23360610109107102, 0.2346173829139761, 0.23562866473688118, 0.23663994655978626, 0.23765122838269132, 0.2386625102055964, 0.23967379202850145, 0.24068507385140653, 0.24169635567431158, 0.24270763749721666, 0.24371891932012174, 0.24473020114302682, 0.24574148296593187, 0.24675276478883695, 0.247764046611742, 0.24877532843464709, 0.24978661025755214, 0.2507978920804572, 0.25180917390336227, 0.2528204557262674, 0.25383173754917243, 0.2548430193720775, 0.2558543011949826, 0.25686558301788764, 0.25787686484079275, 0.25888814666369775, 0.2598994284866028, 0.2609107103095079, 0.26192199213241296, 0.262933273955318, 0.2639445557782231, 0.2649558376011282, 0.2659671194240333, 0.26697840124693833, 0.2679896830698434, 0.2690009648927485, 0.27001224671565355, 0.2710235285385586, 0.2720348103614637, 0.27304609218436876, 0.27405737400727387, 0.27506865583017887, 0.2760799376530839, 0.277091219475989, 0.2781025012988941, 0.27911378312179913, 0.28012506494470424, 0.2811363467676093, 0.2821476285905144, 0.28315891041341945, 0.2841701922363245, 0.2851814740592296, 0.28619275588213466, 0.2872040377050397, 0.2882153195279448, 0.2892266013508499, 0.290237883173755, 0.29124916499666, 0.29226044681956503, 0.29327172864247014, 0.2942830104653752, 0.29529429228828025, 0.29630557411118535, 0.2973168559340904, 0.29832813775699546, 0.29933941957990057, 0.3003507014028056, 0.30136198322571073, 0.3023732650486158, 0.30338454687152083, 0.30439582869442594, 0.305407110517331, 0.306418392340236, 0.3074296741631411, 0.30844095598604615, 0.30945223780895126, 0.3104635196318563, 0.31147480145476136, 0.31248608327766647, 0.3134973651005715, 0.3145086469234766, 0.3155199287463817, 0.31653121056928674, 0.31754249239219184, 0.3185537742150969, 0.31956505603800195, 0.32057633786090706, 0.32158761968381205, 0.3225989015067171, 0.3236101833296222, 0.32462146515252727, 0.3256327469754323, 0.3266440287983374, 0.3276553106212425, 0.3286665924441476, 0.32967787426705264, 0.3306891560899577, 0.3317004379128628, 0.33271171973576785, 0.3337230015586729, 0.334734283381578, 0.33574556520448307, 0.3367568470273882, 0.33776812885029317, 0.3387794106731982, 0.33979069249610333, 0.3408019743190084, 0.34181325614191344, 0.34282453796481854, 0.3438358197877236, 0.3448471016106287, 0.34585838343353376, 0.3468696652564388, 0.3478809470793439, 0.34889222890224897, 0.349903510725154, 0.35091479254805913, 0.3519260743709642, 0.3529373561938693, 0.3539486380167743, 0.35495991983967934, 0.35597120166258445, 0.3569824834854895, 0.35799376530839455, 0.35900504713129966, 0.3600163289542047, 0.36102761077710976, 0.36203889260001487, 0.3630501744229199, 0.36406145624582503, 0.3650727380687301, 0.36608401989163514, 0.36709530171454025, 0.3681065835374453, 0.3691178653603503, 0.3701291471832554, 0.37114042900616045, 0.37215171082906556, 0.3731629926519706, 0.37417427447487567, 0.3751855562977808, 0.37619683812068583, 0.3772081199435909, 0.378219401766496, 0.37923068358940104, 0.38024196541230615, 0.3812532472352112, 0.38226452905811625, 0.38327581088102136, 0.38428709270392636, 0.3852983745268314, 0.3863096563497365, 0.38732093817264157, 0.3883322199955466, 0.38934350181845173, 0.3903547836413568, 0.3913660654642619, 0.39237734728716694, 0.393388629110072, 0.3943999109329771, 0.39541119275588216, 0.3964224745787872, 0.3974337564016923, 0.39844503822459737, 0.3994563200475025, 0.4004676018704075, 0.4014788836933125, 0.40249016551621764, 0.4035014473391227, 0.40451272916202774, 0.40552401098493285, 0.4065352928078379, 0.407546574630743, 0.40855785645364806, 0.4095691382765531, 0.4105804200994582, 0.4115917019223633, 0.4126029837452683, 0.41361426556817343, 0.4146255473910785, 0.4156368292139836, 0.4166481110368886, 0.41765939285979364, 0.41867067468269875, 0.4196819565056038, 0.42069323832850886, 0.42170452015141396, 0.422715801974319, 0.42372708379722407, 0.4247383656201292, 0.42574964744303423, 0.42676092926593934, 0.4277722110888444, 0.42878349291174944, 0.42979477473465455, 0.4308060565575596, 0.4318173383804646, 0.4328286202033697, 0.43383990202627476, 0.43485118384917987, 0.4358624656720849, 0.43687374749499, 0.4378850293178951, 0.43889631114080013, 0.4399075929637052, 0.4409188747866103, 0.44193015660951535, 0.44294143843242045, 0.4439527202553255, 0.44496400207823056, 0.44597528390113567, 0.44698656572404066, 0.4479978475469457, 0.4490091293698508, 0.4500204111927559, 0.451031693015661, 0.45204297483856604, 0.4530542566614711, 0.4540655384843762, 0.45507682030728125, 0.4560881021301863, 0.4570993839530914, 0.45811066577599646, 0.4591219475989015, 0.4601332294218066, 0.4611445112447117, 0.4621557930676168, 0.4631670748905218, 0.46417835671342683, 0.46518963853633194, 0.466200920359237, 0.46721220218214204, 0.46822348400504715, 0.4692347658279522, 0.4702460476508573, 0.47125732947376237, 0.4722686112966674, 0.4732798931195725, 0.4742911749424776, 0.47530245676538263, 0.47631373858828774, 0.4773250204111928, 0.4783363022340979, 0.4793475840570029, 0.48035886587990795, 0.48137014770281306, 0.4823814295257181, 0.48339271134862316, 0.48440399317152827, 0.4854152749944333, 0.4864265568173384, 0.4874378386402435, 0.48844912046314853, 0.48946040228605364, 0.4904716841089587, 0.49148296593186375, 0.49249424775476885, 0.4935055295776739, 0.4945168114005789, 0.495528093223484, 0.49653937504638906, 0.49755065686929417, 0.4985619386921992, 0.4995732205151043, 0.5005845023380094, 0.5015957841609144, 0.5026070659838194, 0.5036183478067245, 0.5046296296296297])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.x = d3.scale.linear()\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.x = d3.scale.linear()\n", " .domain([0.0, 0.5046296296296297])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.legend = L.control({position: 'topright'});\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.legend = L.control({position: 'topright'});\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.xAxis = d3.svg.axis()\n", - " .scale(color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.x)\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.xAxis = d3.svg.axis()\n", + " .scale(color_map_ce6b62b362f1c28b4349afe4361f4ea7.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.051452432824981846, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.10290486564996369, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.15435729847494556, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.20580973129992738, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.2572621641249092, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.3087145969498911, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.3601670297748729, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.41161946259985477, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.4630718954248366, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.g = color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.svg.append("g")\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.g = color_map_ce6b62b362f1c28b4349afe4361f4ea7.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.g.selectAll("rect")\n", - " .data(color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.color.range().map(function(d, i) {\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.g.selectAll("rect")\n", + " .data(color_map_ce6b62b362f1c28b4349afe4361f4ea7.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.x(color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.color.domain()[i - 1]) : color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.x.range()[0],\n", - " x1: i < color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.color.domain().length ? color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.x(color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.color.domain()[i]) : color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.x.range()[1],\n", + " x0: i ? color_map_ce6b62b362f1c28b4349afe4361f4ea7.x(color_map_ce6b62b362f1c28b4349afe4361f4ea7.color.domain()[i - 1]) : color_map_ce6b62b362f1c28b4349afe4361f4ea7.x.range()[0],\n", + " x1: i < color_map_ce6b62b362f1c28b4349afe4361f4ea7.color.domain().length ? color_map_ce6b62b362f1c28b4349afe4361f4ea7.x(color_map_ce6b62b362f1c28b4349afe4361f4ea7.color.domain()[i]) : color_map_ce6b62b362f1c28b4349afe4361f4ea7.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -3135,12 +3215,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.g.call(color_map_111a03ba5ecf7f3e6b7868ced0f6c4af.xAxis).append("text")\n", + " color_map_ce6b62b362f1c28b4349afe4361f4ea7.g.call(color_map_ce6b62b362f1c28b4349afe4361f4ea7.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("betweenness_centrality");\n", " \n", - " function geo_json_a39eb37451599e55cfacd6652675c360_styler(feature) {\n", + " function geo_json_0ad2bf043f957b751909041ebe7b5911_styler(feature) {\n", " switch(feature.id) {\n", " case "0": case "3": \n", " return {"color": "#b91419", "fillColor": "#b91419", "fillOpacity": 0.5, "weight": 2};\n", @@ -3158,52 +3239,54 @@ " return {"color": "#fdd4c2", "fillColor": "#fdd4c2", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_a39eb37451599e55cfacd6652675c360_highlighter(feature) {\n", + " function geo_json_0ad2bf043f957b751909041ebe7b5911_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_a39eb37451599e55cfacd6652675c360_pointToLayer(feature, latlng) {\n", + " function geo_json_0ad2bf043f957b751909041ebe7b5911_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_a39eb37451599e55cfacd6652675c360_styler(feature)\n", + " let style = geo_json_0ad2bf043f957b751909041ebe7b5911_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_a39eb37451599e55cfacd6652675c360_onEachFeature(feature, layer) {\n", + " function geo_json_0ad2bf043f957b751909041ebe7b5911_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_a39eb37451599e55cfacd6652675c360.resetStyle(e.target);\n", + " geo_json_0ad2bf043f957b751909041ebe7b5911.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_a39eb37451599e55cfacd6652675c360_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_0ad2bf043f957b751909041ebe7b5911_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_a39eb37451599e55cfacd6652675c360 = L.geoJson(null, {\n", - " onEachFeature: geo_json_a39eb37451599e55cfacd6652675c360_onEachFeature,\n", + " var geo_json_0ad2bf043f957b751909041ebe7b5911 = L.geoJson(null, {\n", + " onEachFeature: geo_json_0ad2bf043f957b751909041ebe7b5911_onEachFeature,\n", " \n", - " style: geo_json_a39eb37451599e55cfacd6652675c360_styler,\n", - " pointToLayer: geo_json_a39eb37451599e55cfacd6652675c360_pointToLayer,\n", + " style: geo_json_0ad2bf043f957b751909041ebe7b5911_styler,\n", + " pointToLayer: geo_json_0ad2bf043f957b751909041ebe7b5911_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_a39eb37451599e55cfacd6652675c360_add (data) {\n", - " geo_json_a39eb37451599e55cfacd6652675c360\n", + " function geo_json_0ad2bf043f957b751909041ebe7b5911_add (data) {\n", + " geo_json_0ad2bf043f957b751909041ebe7b5911\n", " .addData(data);\n", " }\n", - " geo_json_a39eb37451599e55cfacd6652675c360_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#b91419", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fc9373", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fcb79c", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#b91419", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#fb6b4b", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fdd4c2", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fdd4c2", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_0ad2bf043f957b751909041ebe7b5911_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#b91419", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fc9373", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fcb79c", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#b91419", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#fb6b4b", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fdd4c2", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fdd4c2", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_a39eb37451599e55cfacd6652675c360.bindTooltip(\n", + " geo_json_0ad2bf043f957b751909041ebe7b5911.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -3224,48 +3307,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_a39eb37451599e55cfacd6652675c360.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_0ad2bf043f957b751909041ebe7b5911.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_5f77472e0e35cab8a6fb23688955a0ca = {};\n", + " var color_map_b81b485a210c63483e348af089919a16 = {};\n", "\n", " \n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.color = d3.scale.threshold()\n", + " color_map_b81b485a210c63483e348af089919a16.color = d3.scale.threshold()\n", " .domain([0.45, 0.4506012024048096, 0.45120240480961926, 0.45180360721442886, 0.4524048096192385, 0.4530060120240481, 0.4536072144288577, 0.45420841683366736, 0.45480961923847696, 0.4554108216432866, 0.4560120240480962, 0.4566132264529058, 0.45721442885771546, 0.45781563126252506, 0.45841683366733466, 0.4590180360721443, 0.4596192384769539, 0.46022044088176356, 0.46082164328657316, 0.46142284569138275, 0.4620240480961924, 0.462625250501002, 0.46322645290581166, 0.46382765531062126, 0.46442885771543085, 0.4650300601202405, 0.4656312625250501, 0.4662324649298597, 0.46683366733466936, 0.46743486973947895, 0.4680360721442886, 0.4686372745490982, 0.4692384769539078, 0.46983967935871745, 0.47044088176352705, 0.4710420841683367, 0.4716432865731463, 0.4722444889779559, 0.47284569138276555, 0.47344689378757515, 0.4740480961923848, 0.4746492985971944, 0.475250501002004, 0.47585170340681365, 0.47645290581162325, 0.4770541082164329, 0.4776553106212425, 0.4782565130260521, 0.47885771543086175, 0.47945891783567135, 0.48006012024048095, 0.4806613226452906, 0.4812625250501002, 0.48186372745490985, 0.48246492985971945, 0.48306613226452905, 0.4836673346693387, 0.4842685370741483, 0.48486973947895795, 0.48547094188376755, 0.48607214428857715, 0.4866733466933868, 0.4872745490981964, 0.487875751503006, 0.48847695390781565, 0.48907815631262525, 0.4896793587174349, 0.4902805611222445, 0.4908817635270541, 0.49148296593186375, 0.49208416833667334, 0.492685370741483, 0.4932865731462926, 0.4938877755511022, 0.49448897795591185, 0.49509018036072144, 0.4956913827655311, 0.4962925851703407, 0.4968937875751503, 0.49749498997995995, 0.49809619238476954, 0.4986973947895792, 0.4992985971943888, 0.4998997995991984, 0.500501002004008, 0.5011022044088177, 0.5017034068136272, 0.5023046092184369, 0.5029058116232465, 0.5035070140280561, 0.5041082164328657, 0.5047094188376754, 0.5053106212424849, 0.5059118236472946, 0.5065130260521042, 0.5071142284569139, 0.5077154308617234, 0.5083166332665331, 0.5089178356713427, 0.5095190380761523, 0.5101202404809619, 0.5107214428857716, 0.5113226452905811, 0.5119238476953908, 0.5125250501002004, 0.51312625250501, 0.5137274549098196, 0.5143286573146293, 0.5149298597194389, 0.5155310621242485, 0.5161322645290581, 0.5167334669338677, 0.5173346693386773, 0.517935871743487, 0.5185370741482966, 0.5191382765531062, 0.5197394789579158, 0.5203406813627255, 0.520941883767535, 0.5215430861723447, 0.5221442885771543, 0.522745490981964, 0.5233466933867735, 0.5239478957915832, 0.5245490981963927, 0.5251503006012024, 0.525751503006012, 0.5263527054108217, 0.5269539078156312, 0.5275551102204409, 0.5281563126252505, 0.5287575150300601, 0.5293587174348697, 0.5299599198396794, 0.530561122244489, 0.5311623246492986, 0.5317635270541082, 0.5323647294589179, 0.5329659318637274, 0.5335671342685371, 0.5341683366733467, 0.5347695390781563, 0.5353707414829659, 0.5359719438877756, 0.5365731462925851, 0.5371743486973948, 0.5377755511022044, 0.5383767535070141, 0.5389779559118236, 0.5395791583166333, 0.5401803607214429, 0.5407815631262525, 0.5413827655310621, 0.5419839679358718, 0.5425851703406813, 0.543186372745491, 0.5437875751503006, 0.5443887775551103, 0.5449899799599198, 0.5455911823647295, 0.5461923847695391, 0.5467935871743487, 0.5473947895791583, 0.547995991983968, 0.5485971943887775, 0.5491983967935872, 0.5497995991983968, 0.5504008016032065, 0.551002004008016, 0.5516032064128257, 0.5522044088176353, 0.5528056112224449, 0.5534068136272545, 0.5540080160320642, 0.5546092184368737, 0.5552104208416834, 0.555811623246493, 0.5564128256513026, 0.5570140280561122, 0.5576152304609219, 0.5582164328657315, 0.5588176352705411, 0.5594188376753507, 0.5600200400801604, 0.5606212424849699, 0.5612224448897796, 0.5618236472945892, 0.5624248496993988, 0.5630260521042084, 0.5636272545090181, 0.5642284569138276, 0.5648296593186373, 0.5654308617234469, 0.5660320641282566, 0.5666332665330661, 0.5672344689378758, 0.5678356713426854, 0.568436873747495, 0.5690380761523046, 0.5696392785571143, 0.5702404809619238, 0.5708416833667335, 0.5714428857715431, 0.5720440881763527, 0.5726452905811623, 0.573246492985972, 0.5738476953907816, 0.5744488977955912, 0.5750501002004008, 0.5756513026052104, 0.57625250501002, 0.5768537074148297, 0.5774549098196393, 0.578056112224449, 0.5786573146292585, 0.5792585170340682, 0.5798597194388777, 0.5804609218436874, 0.581062124248497, 0.5816633266533067, 0.5822645290581162, 0.5828657314629259, 0.5834669338677354, 0.5840681362725451, 0.5846693386773547, 0.5852705410821644, 0.585871743486974, 0.5864729458917836, 0.5870741482965932, 0.5876753507014028, 0.5882765531062124, 0.5888777555110221, 0.5894789579158317, 0.5900801603206413, 0.5906813627254509, 0.5912825651302606, 0.5918837675350701, 0.5924849699398798, 0.5930861723446894, 0.5936873747494991, 0.5942885771543086, 0.5948897795591183, 0.5954909819639278, 0.5960921843687375, 0.5966933867735471, 0.5972945891783568, 0.5978957915831663, 0.598496993987976, 0.5990981963927855, 0.5996993987975952, 0.6003006012024048, 0.6009018036072145, 0.6015030060120241, 0.6021042084168337, 0.6027054108216433, 0.6033066132264528, 0.6039078156312625, 0.6045090180360722, 0.6051102204408818, 0.6057114228456915, 0.606312625250501, 0.6069138276553107, 0.6075150300601202, 0.6081162324649299, 0.6087174348697395, 0.6093186372745492, 0.6099198396793587, 0.6105210420841684, 0.6111222444889779, 0.6117234468937875, 0.6123246492985972, 0.6129258517034069, 0.6135270541082164, 0.614128256513026, 0.6147294589178357, 0.6153306613226452, 0.6159318637274549, 0.6165330661322646, 0.6171342685370742, 0.6177354709418837, 0.6183366733466934, 0.618937875751503, 0.6195390781563126, 0.6201402805611222, 0.6207414829659319, 0.6213426853707416, 0.6219438877755511, 0.6225450901803607, 0.6231462925851703, 0.62374749498998, 0.6243486973947896, 0.6249498997995993, 0.6255511022044088, 0.6261523046092184, 0.6267535070140281, 0.6273547094188376, 0.6279559118236473, 0.628557114228457, 0.6291583166332665, 0.6297595190380761, 0.6303607214428858, 0.6309619238476953, 0.631563126252505, 0.6321643286573146, 0.6327655310621243, 0.6333667334669338, 0.6339679358717435, 0.6345691382765531, 0.6351703406813627, 0.6357715430861723, 0.636372745490982, 0.6369739478957916, 0.6375751503006012, 0.6381763527054108, 0.6387775551102205, 0.63937875751503, 0.6399799599198397, 0.6405811623246493, 0.6411823647294589, 0.6417835671342685, 0.6423847695390782, 0.6429859719438877, 0.6435871743486974, 0.644188376753507, 0.6447895791583167, 0.6453907815631262, 0.6459919839679359, 0.6465931863727454, 0.6471943887775551, 0.6477955911823647, 0.6483967935871744, 0.6489979959919839, 0.6495991983967936, 0.6502004008016032, 0.6508016032064128, 0.6514028056112224, 0.6520040080160321, 0.6526052104208417, 0.6532064128256513, 0.6538076152304609, 0.6544088176352706, 0.6550100200400801, 0.6556112224448898, 0.6562124248496994, 0.6568136272545091, 0.6574148296593186, 0.6580160320641283, 0.6586172344689378, 0.6592184368737475, 0.6598196392785571, 0.6604208416833668, 0.6610220440881763, 0.661623246492986, 0.6622244488977955, 0.6628256513026052, 0.6634268537074148, 0.6640280561122245, 0.664629258517034, 0.6652304609218437, 0.6658316633266533, 0.6664328657314629, 0.6670340681362725, 0.6676352705410822, 0.6682364729458918, 0.6688376753507015, 0.669438877755511, 0.6700400801603207, 0.6706412825651302, 0.6712424849699399, 0.6718436873747495, 0.6724448897795592, 0.6730460921843687, 0.6736472945891784, 0.6742484969939879, 0.6748496993987976, 0.6754509018036072, 0.6760521042084169, 0.6766533066132264, 0.6772545090180361, 0.6778557114228457, 0.6784569138276553, 0.6790581162324649, 0.6796593186372746, 0.6802605210420841, 0.6808617234468938, 0.6814629258517034, 0.682064128256513, 0.6826653306613226, 0.6832665330661323, 0.6838677354709419, 0.6844689378757516, 0.6850701402805611, 0.6856713426853708, 0.6862725450901803, 0.68687374749499, 0.6874749498997996, 0.6880761523046093, 0.6886773547094188, 0.6892785571142285, 0.689879759519038, 0.6904809619238477, 0.6910821643286573, 0.691683366733467, 0.6922845691382765, 0.6928857715430862, 0.6934869739478958, 0.6940881763527054, 0.694689378757515, 0.6952905811623247, 0.6958917835671343, 0.6964929859719439, 0.6970941883767535, 0.6976953907815631, 0.6982965931863727, 0.6988977955911824, 0.699498997995992, 0.7001002004008017, 0.7007014028056112, 0.7013026052104208, 0.7019038076152304, 0.7025050100200401, 0.7031062124248497, 0.7037074148296594, 0.7043086172344689, 0.7049098196392786, 0.7055110220440881, 0.7061122244488978, 0.7067134268537074, 0.7073146292585171, 0.7079158316633267, 0.7085170340681363, 0.7091182364729458, 0.7097194388777555, 0.7103206412825651, 0.7109218436873748, 0.7115230460921844, 0.712124248496994, 0.7127254509018036, 0.7133266533066133, 0.7139278557114228, 0.7145290581162325, 0.7151302605210421, 0.7157314629258518, 0.7163326653306614, 0.7169338677354709, 0.7175350701402805, 0.7181362725450902, 0.7187374749498998, 0.7193386773547095, 0.719939879759519, 0.7205410821643287, 0.7211422845691382, 0.7217434869739479, 0.7223446893787575, 0.7229458917835672, 0.7235470941883768, 0.7241482965931864, 0.724749498997996, 0.7253507014028056, 0.7259519038076152, 0.7265531062124249, 0.7271543086172345, 0.7277555110220442, 0.7283567134268537, 0.7289579158316633, 0.7295591182364729, 0.7301603206412826, 0.7307615230460922, 0.7313627254509019, 0.7319639278557114, 0.7325651302605211, 0.7331663326653306, 0.7337675350701403, 0.7343687374749499, 0.7349699398797596, 0.7355711422845692, 0.7361723446893788, 0.7367735470941883, 0.737374749498998, 0.7379759519038076, 0.7385771543086173, 0.7391783567134269, 0.7397795591182365, 0.7403807615230461, 0.7409819639278556, 0.7415831663326653, 0.742184368737475, 0.7427855711422846, 0.7433867735470943, 0.7439879759519038, 0.7445891783567135, 0.745190380761523, 0.7457915831663327, 0.7463927855711423, 0.746993987975952, 0.7475951903807616, 0.748196392785571, 0.7487975951903807, 0.7493987975951903, 0.75])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.x = d3.scale.linear()\n", + " color_map_b81b485a210c63483e348af089919a16.x = d3.scale.linear()\n", " .domain([0.45, 0.75])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.legend = L.control({position: 'topright'});\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_b81b485a210c63483e348af089919a16.legend = L.control({position: 'topright'});\n", + " color_map_b81b485a210c63483e348af089919a16.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_b81b485a210c63483e348af089919a16.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.xAxis = d3.svg.axis()\n", - " .scale(color_map_5f77472e0e35cab8a6fb23688955a0ca.x)\n", + " color_map_b81b485a210c63483e348af089919a16.xAxis = d3.svg.axis()\n", + " .scale(color_map_b81b485a210c63483e348af089919a16.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.45, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.48058823529411765, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.5111764705882353, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.5417647058823529, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.5723529411764706, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.6029411764705883, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.6335294117647059, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.6641176470588235, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.6947058823529412, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.7252941176470589, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_b81b485a210c63483e348af089919a16.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.g = color_map_5f77472e0e35cab8a6fb23688955a0ca.svg.append("g")\n", + " color_map_b81b485a210c63483e348af089919a16.g = color_map_b81b485a210c63483e348af089919a16.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.g.selectAll("rect")\n", - " .data(color_map_5f77472e0e35cab8a6fb23688955a0ca.color.range().map(function(d, i) {\n", + " color_map_b81b485a210c63483e348af089919a16.g.selectAll("rect")\n", + " .data(color_map_b81b485a210c63483e348af089919a16.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_5f77472e0e35cab8a6fb23688955a0ca.x(color_map_5f77472e0e35cab8a6fb23688955a0ca.color.domain()[i - 1]) : color_map_5f77472e0e35cab8a6fb23688955a0ca.x.range()[0],\n", - " x1: i < color_map_5f77472e0e35cab8a6fb23688955a0ca.color.domain().length ? color_map_5f77472e0e35cab8a6fb23688955a0ca.x(color_map_5f77472e0e35cab8a6fb23688955a0ca.color.domain()[i]) : color_map_5f77472e0e35cab8a6fb23688955a0ca.x.range()[1],\n", + " x0: i ? color_map_b81b485a210c63483e348af089919a16.x(color_map_b81b485a210c63483e348af089919a16.color.domain()[i - 1]) : color_map_b81b485a210c63483e348af089919a16.x.range()[0],\n", + " x1: i < color_map_b81b485a210c63483e348af089919a16.color.domain().length ? color_map_b81b485a210c63483e348af089919a16.x(color_map_b81b485a210c63483e348af089919a16.color.domain()[i]) : color_map_b81b485a210c63483e348af089919a16.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -3275,12 +3362,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_5f77472e0e35cab8a6fb23688955a0ca.g.call(color_map_5f77472e0e35cab8a6fb23688955a0ca.xAxis).append("text")\n", + " color_map_b81b485a210c63483e348af089919a16.g.call(color_map_b81b485a210c63483e348af089919a16.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("closeness_centrality");\n", " \n", - " function geo_json_64b3815c09e2dbe740214783b790d60a_styler(feature) {\n", + " function geo_json_4af52d7389933299665d2f2960fc41fc_styler(feature) {\n", " switch(feature.id) {\n", " case "0": case "4": \n", " return {"color": "#cb181d", "fillColor": "#cb181d", "fillOpacity": 0.5, "weight": 2};\n", @@ -3292,52 +3380,54 @@ " return {"color": "#fff5f0", "fillColor": "#fff5f0", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_64b3815c09e2dbe740214783b790d60a_highlighter(feature) {\n", + " function geo_json_4af52d7389933299665d2f2960fc41fc_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_64b3815c09e2dbe740214783b790d60a_pointToLayer(feature, latlng) {\n", + " function geo_json_4af52d7389933299665d2f2960fc41fc_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_64b3815c09e2dbe740214783b790d60a_styler(feature)\n", + " let style = geo_json_4af52d7389933299665d2f2960fc41fc_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_64b3815c09e2dbe740214783b790d60a_onEachFeature(feature, layer) {\n", + " function geo_json_4af52d7389933299665d2f2960fc41fc_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_64b3815c09e2dbe740214783b790d60a.resetStyle(e.target);\n", + " geo_json_4af52d7389933299665d2f2960fc41fc.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_64b3815c09e2dbe740214783b790d60a_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_4af52d7389933299665d2f2960fc41fc_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_64b3815c09e2dbe740214783b790d60a = L.geoJson(null, {\n", - " onEachFeature: geo_json_64b3815c09e2dbe740214783b790d60a_onEachFeature,\n", + " var geo_json_4af52d7389933299665d2f2960fc41fc = L.geoJson(null, {\n", + " onEachFeature: geo_json_4af52d7389933299665d2f2960fc41fc_onEachFeature,\n", " \n", - " style: geo_json_64b3815c09e2dbe740214783b790d60a_styler,\n", - " pointToLayer: geo_json_64b3815c09e2dbe740214783b790d60a_pointToLayer,\n", + " style: geo_json_4af52d7389933299665d2f2960fc41fc_styler,\n", + " pointToLayer: geo_json_4af52d7389933299665d2f2960fc41fc_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_64b3815c09e2dbe740214783b790d60a_add (data) {\n", - " geo_json_64b3815c09e2dbe740214783b790d60a\n", + " function geo_json_4af52d7389933299665d2f2960fc41fc_add (data) {\n", + " geo_json_4af52d7389933299665d2f2960fc41fc\n", " .addData(data);\n", " }\n", - " geo_json_64b3815c09e2dbe740214783b790d60a_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#cb181d", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fb6b4b", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#67000d", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fb6b4b", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#cb181d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#67000d", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_4af52d7389933299665d2f2960fc41fc_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#cb181d", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fb6b4b", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#67000d", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fb6b4b", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#cb181d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#67000d", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_64b3815c09e2dbe740214783b790d60a.bindTooltip(\n", + " geo_json_4af52d7389933299665d2f2960fc41fc.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -3358,48 +3448,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_64b3815c09e2dbe740214783b790d60a.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_4af52d7389933299665d2f2960fc41fc.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_f7b486e4e6d130fb51e6d75ac9640624 = {};\n", + " var color_map_a36df43730e0342fc3e0479737776571 = {};\n", "\n", " \n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.color = d3.scale.threshold()\n", + " color_map_a36df43730e0342fc3e0479737776571.color = d3.scale.threshold()\n", " .domain([0.0, 0.008016032064128256, 0.01603206412825651, 0.02404809619238477, 0.03206412825651302, 0.04008016032064128, 0.04809619238476954, 0.056112224448897796, 0.06412825651302605, 0.07214428857715431, 0.08016032064128256, 0.08817635270541083, 0.09619238476953908, 0.10420841683366733, 0.11222444889779559, 0.12024048096192384, 0.1282565130260521, 0.13627254509018036, 0.14428857715430862, 0.1523046092184369, 0.16032064128256512, 0.1683366733466934, 0.17635270541082165, 0.1843687374749499, 0.19238476953907815, 0.20040080160320642, 0.20841683366733466, 0.21643286573146292, 0.22444889779559118, 0.23246492985971945, 0.24048096192384769, 0.24849699398797595, 0.2565130260521042, 0.26452905811623245, 0.2725450901803607, 0.280561122244489, 0.28857715430861725, 0.2965931863727455, 0.3046092184368738, 0.312625250501002, 0.32064128256513025, 0.3286573146292585, 0.3366733466933868, 0.34468937875751504, 0.3527054108216433, 0.36072144288577157, 0.3687374749498998, 0.37675350701402804, 0.3847695390781563, 0.3927855711422846, 0.40080160320641284, 0.4088176352705411, 0.4168336673346693, 0.4248496993987976, 0.43286573146292584, 0.4408817635270541, 0.44889779559118237, 0.45691382765531063, 0.4649298597194389, 0.4729458917835671, 0.48096192384769537, 0.48897795591182364, 0.4969939879759519, 0.5050100200400801, 0.5130260521042084, 0.5210420841683366, 0.5290581162324649, 0.5370741482965932, 0.5450901803607214, 0.5531062124248497, 0.561122244488978, 0.5691382765531062, 0.5771543086172345, 0.5851703406813628, 0.593186372745491, 0.6012024048096193, 0.6092184368737475, 0.6172344689378757, 0.625250501002004, 0.6332665330661322, 0.6412825651302605, 0.6492985971943888, 0.657314629258517, 0.6653306613226453, 0.6733466933867736, 0.6813627254509018, 0.6893787575150301, 0.6973947895791583, 0.7054108216432866, 0.7134268537074149, 0.7214428857715431, 0.7294589178356713, 0.7374749498997996, 0.7454909819639278, 0.7535070140280561, 0.7615230460921844, 0.7695390781563126, 0.7775551102204409, 0.7855711422845691, 0.7935871743486974, 0.8016032064128257, 0.8096192384769539, 0.8176352705410822, 0.8256513026052105, 0.8336673346693386, 0.8416833667334669, 0.8496993987975952, 0.8577154308617234, 0.8657314629258517, 0.87374749498998, 0.8817635270541082, 0.8897795591182365, 0.8977955911823647, 0.905811623246493, 0.9138276553106213, 0.9218436873747495, 0.9298597194388778, 0.9378757515030061, 0.9458917835671342, 0.9539078156312625, 0.9619238476953907, 0.969939879759519, 0.9779559118236473, 0.9859719438877755, 0.9939879759519038, 1.002004008016032, 1.0100200400801602, 1.0180360721442885, 1.0260521042084167, 1.034068136272545, 1.0420841683366733, 1.0501002004008015, 1.0581162324649298, 1.066132264529058, 1.0741482965931863, 1.0821643286573146, 1.0901803607214429, 1.0981963927855711, 1.1062124248496994, 1.1142284569138277, 1.122244488977956, 1.1302605210420842, 1.1382765531062125, 1.1462925851703407, 1.154308617234469, 1.1623246492985972, 1.1703406813627255, 1.1783567134268538, 1.186372745490982, 1.1943887775551103, 1.2024048096192386, 1.2104208416833668, 1.218436873747495, 1.2264529058116231, 1.2344689378757514, 1.2424849699398797, 1.250501002004008, 1.2585170340681362, 1.2665330661322645, 1.2745490981963927, 1.282565130260521, 1.2905811623246493, 1.2985971943887775, 1.3066132264529058, 1.314629258517034, 1.3226452905811623, 1.3306613226452906, 1.3386773547094188, 1.346693386773547, 1.3547094188376754, 1.3627254509018036, 1.370741482965932, 1.3787575150300602, 1.3867735470941884, 1.3947895791583167, 1.402805611222445, 1.4108216432865732, 1.4188376753507015, 1.4268537074148298, 1.434869739478958, 1.4428857715430863, 1.4509018036072143, 1.4589178356713426, 1.4669338677354709, 1.4749498997995991, 1.4829659318637274, 1.4909819639278556, 1.498997995991984, 1.5070140280561122, 1.5150300601202404, 1.5230460921843687, 1.531062124248497, 1.5390781563126252, 1.5470941883767535, 1.5551102204408818, 1.56312625250501, 1.5711422845691383, 1.5791583166332666, 1.5871743486973948, 1.595190380761523, 1.6032064128256514, 1.6112224448897796, 1.6192384769539079, 1.6272545090180361, 1.6352705410821644, 1.6432865731462927, 1.651302605210421, 1.6593186372745492, 1.6673346693386772, 1.6753507014028055, 1.6833667334669338, 1.691382765531062, 1.6993987975951903, 1.7074148296593186, 1.7154308617234468, 1.723446893787575, 1.7314629258517034, 1.7394789579158316, 1.74749498997996, 1.7555110220440882, 1.7635270541082164, 1.7715430861723447, 1.779559118236473, 1.7875751503006012, 1.7955911823647295, 1.8036072144288577, 1.811623246492986, 1.8196392785571143, 1.8276553106212425, 1.8356713426853708, 1.843687374749499, 1.8517034068136273, 1.8597194388777556, 1.8677354709418839, 1.8757515030060121, 1.8837675350701404, 1.8917835671342684, 1.8997995991983967, 1.907815631262525, 1.9158316633266532, 1.9238476953907815, 1.9318637274549098, 1.939879759519038, 1.9478957915831663, 1.9559118236472945, 1.9639278557114228, 1.971943887775551, 1.9799599198396793, 1.9879759519038076, 1.9959919839679359, 2.004008016032064, 2.012024048096192, 2.0200400801603204, 2.0280561122244487, 2.036072144288577, 2.0440881763527052, 2.0521042084168335, 2.0601202404809618, 2.06813627254509, 2.0761523046092183, 2.0841683366733466, 2.092184368737475, 2.100200400801603, 2.1082164328657313, 2.1162324649298596, 2.124248496993988, 2.132264529058116, 2.1402805611222444, 2.1482965931863727, 2.156312625250501, 2.164328657314629, 2.1723446893787575, 2.1803607214428857, 2.188376753507014, 2.1963927855711423, 2.2044088176352705, 2.212424849699399, 2.220440881763527, 2.2284569138276553, 2.2364729458917836, 2.244488977955912, 2.25250501002004, 2.2605210420841684, 2.2685370741482966, 2.276553106212425, 2.284569138276553, 2.2925851703406814, 2.3006012024048097, 2.308617234468938, 2.3166332665330662, 2.3246492985971945, 2.3326653306613228, 2.340681362725451, 2.3486973947895793, 2.3567134268537075, 2.364729458917836, 2.372745490981964, 2.3807615230460923, 2.3887775551102206, 2.396793587174349, 2.404809619238477, 2.4128256513026054, 2.4208416833667337, 2.428857715430862, 2.43687374749499, 2.444889779559118, 2.4529058116232463, 2.4609218436873745, 2.468937875751503, 2.476953907815631, 2.4849699398797593, 2.4929859719438876, 2.501002004008016, 2.509018036072144, 2.5170340681362724, 2.5250501002004007, 2.533066132264529, 2.541082164328657, 2.5490981963927855, 2.5571142284569137, 2.565130260521042, 2.5731462925851702, 2.5811623246492985, 2.5891783567134268, 2.597194388777555, 2.6052104208416833, 2.6132264529058116, 2.62124248496994, 2.629258517034068, 2.6372745490981964, 2.6452905811623246, 2.653306613226453, 2.661322645290581, 2.6693386773547094, 2.6773547094188377, 2.685370741482966, 2.693386773547094, 2.7014028056112225, 2.7094188376753507, 2.717434869739479, 2.7254509018036073, 2.7334669338677355, 2.741482965931864, 2.749498997995992, 2.7575150300601203, 2.7655310621242486, 2.773547094188377, 2.781563126252505, 2.7895791583166334, 2.7975951903807617, 2.80561122244489, 2.813627254509018, 2.8216432865731464, 2.8296593186372747, 2.837675350701403, 2.8456913827655312, 2.8537074148296595, 2.8617234468937878, 2.869739478957916, 2.8777555110220443, 2.8857715430861726, 2.8937875751503004, 2.9018036072144286, 2.909819639278557, 2.917835671342685, 2.9258517034068134, 2.9338677354709417, 2.94188376753507, 2.9498997995991982, 2.9579158316633265, 2.9659318637274548, 2.973947895791583, 2.9819639278557113, 2.9899799599198396, 2.997995991983968, 3.006012024048096, 3.0140280561122244, 3.0220440881763526, 3.030060120240481, 3.038076152304609, 3.0460921843687374, 3.0541082164328657, 3.062124248496994, 3.070140280561122, 3.0781563126252505, 3.0861723446893787, 3.094188376753507, 3.1022044088176353, 3.1102204408817635, 3.118236472945892, 3.12625250501002, 3.1342685370741483, 3.1422845691382766, 3.150300601202405, 3.158316633266533, 3.1663326653306614, 3.1743486973947896, 3.182364729458918, 3.190380761523046, 3.1983967935871744, 3.2064128256513027, 3.214428857715431, 3.2224448897795592, 3.2304609218436875, 3.2384769539078158, 3.246492985971944, 3.2545090180360723, 3.2625250501002006, 3.270541082164329, 3.278557114228457, 3.2865731462925853, 3.2945891783567136, 3.302605210420842, 3.31062124248497, 3.3186372745490984, 3.3266533066132267, 3.3346693386773545, 3.3426853707414828, 3.350701402805611, 3.3587174348697393, 3.3667334669338675, 3.374749498997996, 3.382765531062124, 3.3907815631262523, 3.3987975951903806, 3.406813627254509, 3.414829659318637, 3.4228456913827654, 3.4308617234468937, 3.438877755511022, 3.44689378757515, 3.4549098196392785, 3.4629258517034067, 3.470941883767535, 3.4789579158316633, 3.4869739478957915, 3.49498997995992, 3.503006012024048, 3.5110220440881763, 3.5190380761523046, 3.527054108216433, 3.535070140280561, 3.5430861723446894, 3.5511022044088176, 3.559118236472946, 3.567134268537074, 3.5751503006012024, 3.5831663326653307, 3.591182364729459, 3.599198396793587, 3.6072144288577155, 3.6152304609218437, 3.623246492985972, 3.6312625250501003, 3.6392785571142285, 3.647294589178357, 3.655310621242485, 3.6633266533066133, 3.6713426853707416, 3.67935871743487, 3.687374749498998, 3.6953907815631264, 3.7034068136272547, 3.711422845691383, 3.719438877755511, 3.7274549098196395, 3.7354709418837677, 3.743486973947896, 3.7515030060120242, 3.7595190380761525, 3.7675350701402808, 3.775551102204409, 3.783567134268537, 3.791583166332665, 3.7995991983967934, 3.8076152304609217, 3.81563126252505, 3.823647294589178, 3.8316633266533064, 3.8396793587174347, 3.847695390781563, 3.8557114228456912, 3.8637274549098195, 3.8717434869739478, 3.879759519038076, 3.8877755511022043, 3.8957915831663326, 3.903807615230461, 3.911823647294589, 3.9198396793587174, 3.9278557114228456, 3.935871743486974, 3.943887775551102, 3.9519038076152304, 3.9599198396793587, 3.967935871743487, 3.975951903807615, 3.9839679358717435, 3.9919839679358717, 4.0])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.x = d3.scale.linear()\n", + " color_map_a36df43730e0342fc3e0479737776571.x = d3.scale.linear()\n", " .domain([0.0, 4.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.legend = L.control({position: 'topright'});\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_a36df43730e0342fc3e0479737776571.legend = L.control({position: 'topright'});\n", + " color_map_a36df43730e0342fc3e0479737776571.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_a36df43730e0342fc3e0479737776571.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.xAxis = d3.svg.axis()\n", - " .scale(color_map_f7b486e4e6d130fb51e6d75ac9640624.x)\n", + " color_map_a36df43730e0342fc3e0479737776571.xAxis = d3.svg.axis()\n", + " .scale(color_map_a36df43730e0342fc3e0479737776571.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.40784313725490196, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 0.8156862745098039, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1.223529411764706, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1.6313725490196078, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.0392156862745097, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.447058823529412, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 2.854901960784314, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.2627450980392156, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 3.6705882352941175, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_a36df43730e0342fc3e0479737776571.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.g = color_map_f7b486e4e6d130fb51e6d75ac9640624.svg.append("g")\n", + " color_map_a36df43730e0342fc3e0479737776571.g = color_map_a36df43730e0342fc3e0479737776571.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.g.selectAll("rect")\n", - " .data(color_map_f7b486e4e6d130fb51e6d75ac9640624.color.range().map(function(d, i) {\n", + " color_map_a36df43730e0342fc3e0479737776571.g.selectAll("rect")\n", + " .data(color_map_a36df43730e0342fc3e0479737776571.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_f7b486e4e6d130fb51e6d75ac9640624.x(color_map_f7b486e4e6d130fb51e6d75ac9640624.color.domain()[i - 1]) : color_map_f7b486e4e6d130fb51e6d75ac9640624.x.range()[0],\n", - " x1: i < color_map_f7b486e4e6d130fb51e6d75ac9640624.color.domain().length ? color_map_f7b486e4e6d130fb51e6d75ac9640624.x(color_map_f7b486e4e6d130fb51e6d75ac9640624.color.domain()[i]) : color_map_f7b486e4e6d130fb51e6d75ac9640624.x.range()[1],\n", + " x0: i ? color_map_a36df43730e0342fc3e0479737776571.x(color_map_a36df43730e0342fc3e0479737776571.color.domain()[i - 1]) : color_map_a36df43730e0342fc3e0479737776571.x.range()[0],\n", + " x1: i < color_map_a36df43730e0342fc3e0479737776571.color.domain().length ? color_map_a36df43730e0342fc3e0479737776571.x(color_map_a36df43730e0342fc3e0479737776571.color.domain()[i]) : color_map_a36df43730e0342fc3e0479737776571.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -3409,12 +3503,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_f7b486e4e6d130fb51e6d75ac9640624.g.call(color_map_f7b486e4e6d130fb51e6d75ac9640624.xAxis).append("text")\n", + " color_map_a36df43730e0342fc3e0479737776571.g.call(color_map_a36df43730e0342fc3e0479737776571.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("access");\n", " \n", - " function geo_json_b3234c99aa829a72a054d90be27a0857_styler(feature) {\n", + " function geo_json_c41967b3da0880b89a03ffd072dc60d5_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#d01d1f", "fillColor": "#d01d1f", "fillOpacity": 0.5, "weight": 2};\n", @@ -3438,52 +3533,54 @@ " return {"color": "#fcc3ab", "fillColor": "#fcc3ab", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_b3234c99aa829a72a054d90be27a0857_highlighter(feature) {\n", + " function geo_json_c41967b3da0880b89a03ffd072dc60d5_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_b3234c99aa829a72a054d90be27a0857_pointToLayer(feature, latlng) {\n", + " function geo_json_c41967b3da0880b89a03ffd072dc60d5_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_b3234c99aa829a72a054d90be27a0857_styler(feature)\n", + " let style = geo_json_c41967b3da0880b89a03ffd072dc60d5_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_b3234c99aa829a72a054d90be27a0857_onEachFeature(feature, layer) {\n", + " function geo_json_c41967b3da0880b89a03ffd072dc60d5_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_b3234c99aa829a72a054d90be27a0857.resetStyle(e.target);\n", + " geo_json_c41967b3da0880b89a03ffd072dc60d5.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_b3234c99aa829a72a054d90be27a0857_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_c41967b3da0880b89a03ffd072dc60d5_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_b3234c99aa829a72a054d90be27a0857 = L.geoJson(null, {\n", - " onEachFeature: geo_json_b3234c99aa829a72a054d90be27a0857_onEachFeature,\n", + " var geo_json_c41967b3da0880b89a03ffd072dc60d5 = L.geoJson(null, {\n", + " onEachFeature: geo_json_c41967b3da0880b89a03ffd072dc60d5_onEachFeature,\n", " \n", - " style: geo_json_b3234c99aa829a72a054d90be27a0857_styler,\n", - " pointToLayer: geo_json_b3234c99aa829a72a054d90be27a0857_pointToLayer,\n", + " style: geo_json_c41967b3da0880b89a03ffd072dc60d5_styler,\n", + " pointToLayer: geo_json_c41967b3da0880b89a03ffd072dc60d5_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_b3234c99aa829a72a054d90be27a0857_add (data) {\n", - " geo_json_b3234c99aa829a72a054d90be27a0857\n", + " function geo_json_c41967b3da0880b89a03ffd072dc60d5_add (data) {\n", + " geo_json_c41967b3da0880b89a03ffd072dc60d5\n", " .addData(data);\n", " }\n", - " geo_json_b3234c99aa829a72a054d90be27a0857_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#d01d1f", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ea362a", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#ee3a2c", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fc8262", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff4ee", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#860811", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff4ef", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fcc3ab", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_c41967b3da0880b89a03ffd072dc60d5_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#d01d1f", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ea362a", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#ee3a2c", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fc8262", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#67000d", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#fff4ee", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#860811", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#fff4ef", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fcc3ab", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_b3234c99aa829a72a054d90be27a0857.bindTooltip(\n", + " geo_json_c41967b3da0880b89a03ffd072dc60d5.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -3504,48 +3601,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_b3234c99aa829a72a054d90be27a0857.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_c41967b3da0880b89a03ffd072dc60d5.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_966bb8e78b0e4f398a242d65cb175192 = {};\n", + " var color_map_59bef59e45e067863e4dc25bc43ec69f = {};\n", "\n", " \n", - " color_map_966bb8e78b0e4f398a242d65cb175192.color = d3.scale.threshold()\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.color = d3.scale.threshold()\n", " .domain([182.6849740039611, 184.4779112819082, 186.27084855985532, 188.06378583780244, 189.85672311574956, 191.6496603936967, 193.44259767164382, 195.23553494959094, 197.02847222753806, 198.82140950548518, 200.6143467834323, 202.4072840613794, 204.20022133932653, 205.99315861727365, 207.7860958952208, 209.57903317316791, 211.37197045111503, 213.16490772906215, 214.95784500700927, 216.7507822849564, 218.5437195629035, 220.33665684085065, 222.12959411879774, 223.9225313967449, 225.715468674692, 227.50840595263912, 229.30134323058624, 231.09428050853336, 232.88721778648048, 234.6801550644276, 236.4730923423747, 238.26602962032183, 240.05896689826898, 241.8519041762161, 243.6448414541632, 245.43777873211033, 247.23071601005745, 249.0236532880046, 250.81659056595169, 252.60952784389883, 254.40246512184592, 256.19540239979307, 257.9883396777402, 259.7812769556873, 261.5742142336344, 263.36715151158154, 265.1600887895287, 266.9530260674758, 268.7459633454229, 270.53890062337, 272.33183790131716, 274.12477517926425, 275.9177124572114, 277.71064973515854, 279.50358701310563, 281.2965242910528, 283.08946156899987, 284.882398846947, 286.6753361248941, 288.46827340284125, 290.26121068078834, 292.0541479587355, 293.8470852366826, 295.6400225146297, 297.43295979257687, 299.22589707052396, 301.0188343484711, 302.8117716264182, 304.60470890436534, 306.3976461823124, 308.1905834602596, 309.9835207382067, 311.7764580161538, 313.5693952941009, 315.3623325720481, 317.1552698499952, 318.9482071279423, 320.7411444058894, 322.5340816838366, 324.32701896178366, 326.11995623973075, 327.9128935176779, 329.70583079562505, 331.49876807357214, 333.2917053515193, 335.08464262946643, 336.8775799074135, 338.6705171853606, 340.46345446330776, 342.2563917412549, 344.049329019202, 345.8422662971491, 347.6352035750962, 349.4281408530434, 351.22107813099046, 353.0140154089376, 354.80695268688476, 356.59988996483185, 358.39282724277894, 360.18576452072614, 361.9787017986732, 363.7716390766203, 365.56457635456746, 367.35751363251455, 369.1504509104617, 370.9433881884088, 372.73632546635594, 374.5292627443031, 376.3222000222502, 378.11513730019726, 379.90807457814446, 381.70101185609155, 383.49394913403864, 385.2868864119858, 387.07982368993294, 388.87276096788, 390.6656982458272, 392.45863552377426, 394.2515728017214, 396.0445100796685, 397.8374473576156, 399.6303846355628, 401.4233219135099, 403.21625919145697, 405.0091964694041, 406.80213374735126, 408.59507102529835, 410.3880083032455, 412.18094558119265, 413.97388285913974, 415.7668201370868, 417.55975741503397, 419.3526946929811, 421.1456319709282, 422.9385692488753, 424.73150652682244, 426.5244438047696, 428.3173810827167, 430.1103183606638, 431.903255638611, 433.69619291655806, 435.48913019450515, 437.28206747245235, 439.07500475039944, 440.86794202834653, 442.6608793062937, 444.45381658424077, 446.2467538621879, 448.03969114013506, 449.83262841808215, 451.6255656960293, 453.4185029739764, 455.2114402519235, 457.0043775298706, 458.7973148078177, 460.5902520857649, 462.383189363712, 464.17612664165915, 465.96906391960624, 467.7620011975534, 469.5549384755005, 471.3478757534476, 473.1408130313947, 474.93375030934186, 476.72668758728895, 478.51962486523604, 480.31256214318324, 482.10549942113033, 483.8984366990775, 485.69137397702457, 487.4843112549717, 489.2772485329188, 491.07018581086595, 492.86312308881304, 494.6560603667602, 496.4489976447073, 498.2419349226544, 500.03487220060157, 501.82780947854866, 503.6207467564958, 505.4136840344429, 507.20662131239004, 508.99955859033713, 510.7924958682843, 512.5854331462314, 514.3783704241785, 516.1713077021257, 517.9642449800729, 519.7571822580198, 521.550119535967, 523.3430568139141, 525.1359940918612, 526.9289313698084, 528.7218686477554, 530.5148059257026, 532.3077432036497, 534.1006804815968, 535.893617759544, 537.6865550374912, 539.4794923154382, 541.2724295933854, 543.0653668713325, 544.8583041492795, 546.6512414272268, 548.4441787051738, 550.2371159831209, 552.030053261068, 553.8229905390151, 555.6159278169623, 557.4088650949095, 559.2018023728565, 560.9947396508037, 562.7876769287508, 564.5806142066979, 566.3735514846451, 568.1664887625922, 569.9594260405393, 571.7523633184865, 573.5453005964334, 575.3382378743806, 577.1311751523278, 578.9241124302748, 580.717049708222, 582.5099869861691, 584.3029242641162, 586.0958615420634, 587.8887988200105, 589.6817360979576, 591.4746733759048, 593.2676106538518, 595.060547931799, 596.8534852097462, 598.6464224876933, 600.4393597656403, 602.2322970435874, 604.0252343215345, 605.8181715994817, 607.6111088774288, 609.4040461553759, 611.1969834333231, 612.9899207112701, 614.7828579892173, 616.5757952671645, 618.3687325451116, 620.1616698230587, 621.9546071010059, 623.7475443789529, 625.5404816569, 627.3334189348471, 629.1263562127942, 630.9192934907414, 632.7122307686885, 634.5051680466356, 636.2981053245828, 638.0910426025299, 639.883979880477, 641.6769171584242, 643.4698544363712, 645.2627917143184, 647.0557289922655, 648.8486662702126, 650.6416035481598, 652.4345408261069, 654.227478104054, 656.0204153820011, 657.8133526599482, 659.6062899378953, 661.3992272158425, 663.1921644937895, 664.9851017717367, 666.7780390496838, 668.5709763276309, 670.3639136055781, 672.1568508835253, 673.9497881614723, 675.7427254394195, 677.5356627173666, 679.3285999953137, 681.1215372732609, 682.9144745512078, 684.707411829155, 686.5003491071021, 688.2932863850492, 690.0862236629964, 691.8791609409436, 693.6720982188906, 695.4650354968378, 697.2579727747849, 699.050910052732, 700.8438473306791, 702.6367846086263, 704.4297218865734, 706.2226591645205, 708.0155964424675, 709.8085337204147, 711.6014709983618, 713.394408276309, 715.1873455542561, 716.9802828322032, 718.7732201101503, 720.5661573880975, 722.3590946660446, 724.1520319439917, 725.9449692219388, 727.7379064998859, 729.5308437778331, 731.3237810557802, 733.1167183337272, 734.9096556116743, 736.7025928896215, 738.4955301675687, 740.2884674455158, 742.0814047234629, 743.8743420014101, 745.6672792793572, 747.4602165573043, 749.2531538352514, 751.0460911131985, 752.8390283911457, 754.6319656690928, 756.4249029470399, 758.217840224987, 760.0107775029342, 761.8037147808813, 763.5966520588283, 765.3895893367754, 767.1825266147226, 768.9754638926697, 770.7684011706168, 772.5613384485639, 774.354275726511, 776.1472130044583, 777.9401502824054, 779.7330875603525, 781.5260248382996, 783.3189621162468, 785.1118993941939, 786.904836672141, 788.697773950088, 790.4907112280353, 792.2836485059823, 794.0765857839294, 795.8695230618765, 797.6624603398236, 799.4553976177708, 801.2483348957179, 803.041272173665, 804.8342094516121, 806.6271467295593, 808.4200840075064, 810.2130212854535, 812.0059585634006, 813.7988958413478, 815.591833119295, 817.384770397242, 819.1777076751891, 820.9706449531362, 822.7635822310834, 824.5565195090305, 826.3494567869776, 828.1423940649247, 829.9353313428719, 831.728268620819, 833.5212058987661, 835.3141431767132, 837.1070804546604, 838.9000177326075, 840.6929550105546, 842.4858922885016, 844.2788295664487, 846.0717668443959, 847.864704122343, 849.6576414002901, 851.4505786782372, 853.2435159561845, 855.0364532341316, 856.8293905120787, 858.6223277900258, 860.415265067973, 862.2082023459201, 864.0011396238672, 865.7940769018143, 867.5870141797615, 869.3799514577086, 871.1728887356556, 872.9658260136027, 874.7587632915498, 876.551700569497, 878.3446378474441, 880.1375751253912, 881.9305124033383, 883.7234496812855, 885.5163869592326, 887.3093242371797, 889.1022615151268, 890.8951987930741, 892.6881360710212, 894.4810733489683, 896.2740106269154, 898.0669479048624, 899.8598851828096, 901.6528224607567, 903.4457597387038, 905.2386970166509, 907.0316342945981, 908.8245715725452, 910.6175088504923, 912.4104461284394, 914.2033834063866, 915.9963206843337, 917.7892579622808, 919.5821952402279, 921.375132518175, 923.1680697961222, 924.9610070740692, 926.7539443520163, 928.5468816299635, 930.3398189079107, 932.1327561858578, 933.9256934638049, 935.718630741752, 937.5115680196992, 939.3045052976463, 941.0974425755934, 942.8903798535405, 944.6833171314876, 946.4762544094348, 948.2691916873819, 950.062128965329, 951.855066243276, 953.6480035212232, 955.4409407991703, 957.2338780771174, 959.0268153550645, 960.8197526330117, 962.6126899109588, 964.4056271889059, 966.198564466853, 967.9915017448002, 969.7844390227474, 971.5773763006945, 973.3703135786416, 975.1632508565887, 976.9561881345359, 978.749125412483, 980.54206269043, 982.3349999683771, 984.1279372463243, 985.9208745242714, 987.7138118022185, 989.5067490801656, 991.2996863581127, 993.0926236360599, 994.885560914007, 996.6784981919541, 998.4714354699012, 1000.2643727478484, 1002.0573100257955, 1003.8502473037425, 1005.6431845816898, 1007.436121859637, 1009.229059137584, 1011.0219964155311, 1012.8149336934782, 1014.6078709714254, 1016.4008082493725, 1018.1937455273196, 1019.9866828052667, 1021.7796200832138, 1023.572557361161, 1025.365494639108, 1027.1584319170552, 1028.9513691950024, 1030.7443064729496, 1032.5372437508966, 1034.3301810288435, 1036.1231183067907, 1037.916055584738, 1039.7089928626851, 1041.501930140632, 1043.294867418579, 1045.0878046965263, 1046.8807419744735, 1048.6736792524207, 1050.466616530368, 1052.2595538083149, 1054.052491086262, 1055.845428364209, 1057.6383656421563, 1059.4313029201035, 1061.2242401980507, 1063.0171774759976, 1064.8101147539446, 1066.6030520318918, 1068.395989309839, 1070.1889265877862, 1071.9818638657332, 1073.7748011436802, 1075.5677384216274, 1077.3606756995746])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.x = d3.scale.linear()\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.x = d3.scale.linear()\n", " .domain([182.6849740039611, 1077.3606756995746])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.legend = L.control({position: 'topright'});\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.legend = L.control({position: 'topright'});\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.xAxis = d3.svg.axis()\n", - " .scale(color_map_966bb8e78b0e4f398a242d65cb175192.x)\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.xAxis = d3.svg.axis()\n", + " .scale(color_map_59bef59e45e067863e4dc25bc43ec69f.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([182.6849740039611, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 273.9068102552785, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 365.128646506596, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 456.3504827579135, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 547.5723190092309, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 638.7941552605483, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 730.0159915118659, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 821.2378277631833, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 912.4596640145007, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 1003.6815002658182, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.g = color_map_966bb8e78b0e4f398a242d65cb175192.svg.append("g")\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.g = color_map_59bef59e45e067863e4dc25bc43ec69f.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.g.selectAll("rect")\n", - " .data(color_map_966bb8e78b0e4f398a242d65cb175192.color.range().map(function(d, i) {\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.g.selectAll("rect")\n", + " .data(color_map_59bef59e45e067863e4dc25bc43ec69f.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_966bb8e78b0e4f398a242d65cb175192.x(color_map_966bb8e78b0e4f398a242d65cb175192.color.domain()[i - 1]) : color_map_966bb8e78b0e4f398a242d65cb175192.x.range()[0],\n", - " x1: i < color_map_966bb8e78b0e4f398a242d65cb175192.color.domain().length ? color_map_966bb8e78b0e4f398a242d65cb175192.x(color_map_966bb8e78b0e4f398a242d65cb175192.color.domain()[i]) : color_map_966bb8e78b0e4f398a242d65cb175192.x.range()[1],\n", + " x0: i ? color_map_59bef59e45e067863e4dc25bc43ec69f.x(color_map_59bef59e45e067863e4dc25bc43ec69f.color.domain()[i - 1]) : color_map_59bef59e45e067863e4dc25bc43ec69f.x.range()[0],\n", + " x1: i < color_map_59bef59e45e067863e4dc25bc43ec69f.color.domain().length ? color_map_59bef59e45e067863e4dc25bc43ec69f.x(color_map_59bef59e45e067863e4dc25bc43ec69f.color.domain()[i]) : color_map_59bef59e45e067863e4dc25bc43ec69f.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -3555,12 +3656,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_966bb8e78b0e4f398a242d65cb175192.g.call(color_map_966bb8e78b0e4f398a242d65cb175192.xAxis).append("text")\n", + " color_map_59bef59e45e067863e4dc25bc43ec69f.g.call(color_map_59bef59e45e067863e4dc25bc43ec69f.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("length");\n", " \n", - " function geo_json_1c9e043f9bc1179ca5f274defa59f1f8_styler(feature) {\n", + " function geo_json_714504b95353607487f4ed6bbeddf108_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#fdc5ae", "fillColor": "#fdc5ae", "fillOpacity": 0.5, "weight": 2};\n", @@ -3584,52 +3686,54 @@ " return {"color": "#fc8464", "fillColor": "#fc8464", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_1c9e043f9bc1179ca5f274defa59f1f8_highlighter(feature) {\n", + " function geo_json_714504b95353607487f4ed6bbeddf108_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_1c9e043f9bc1179ca5f274defa59f1f8_pointToLayer(feature, latlng) {\n", + " function geo_json_714504b95353607487f4ed6bbeddf108_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_1c9e043f9bc1179ca5f274defa59f1f8_styler(feature)\n", + " let style = geo_json_714504b95353607487f4ed6bbeddf108_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_1c9e043f9bc1179ca5f274defa59f1f8_onEachFeature(feature, layer) {\n", + " function geo_json_714504b95353607487f4ed6bbeddf108_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_1c9e043f9bc1179ca5f274defa59f1f8.resetStyle(e.target);\n", + " geo_json_714504b95353607487f4ed6bbeddf108.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_1c9e043f9bc1179ca5f274defa59f1f8_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_714504b95353607487f4ed6bbeddf108_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_1c9e043f9bc1179ca5f274defa59f1f8 = L.geoJson(null, {\n", - " onEachFeature: geo_json_1c9e043f9bc1179ca5f274defa59f1f8_onEachFeature,\n", + " var geo_json_714504b95353607487f4ed6bbeddf108 = L.geoJson(null, {\n", + " onEachFeature: geo_json_714504b95353607487f4ed6bbeddf108_onEachFeature,\n", " \n", - " style: geo_json_1c9e043f9bc1179ca5f274defa59f1f8_styler,\n", - " pointToLayer: geo_json_1c9e043f9bc1179ca5f274defa59f1f8_pointToLayer,\n", + " style: geo_json_714504b95353607487f4ed6bbeddf108_styler,\n", + " pointToLayer: geo_json_714504b95353607487f4ed6bbeddf108_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_1c9e043f9bc1179ca5f274defa59f1f8_add (data) {\n", - " geo_json_1c9e043f9bc1179ca5f274defa59f1f8\n", + " function geo_json_714504b95353607487f4ed6bbeddf108_add (data) {\n", + " geo_json_714504b95353607487f4ed6bbeddf108\n", " .addData(data);\n", " }\n", - " geo_json_1c9e043f9bc1179ca5f274defa59f1f8_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fdc5ae", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fc8767", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fee2d5", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fff5f0", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#fc9b7c", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#67000d", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#f34c37", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#7e0610", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fee5d8", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fc8464", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_714504b95353607487f4ed6bbeddf108_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fdc5ae", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#fc8767", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#fee2d5", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fff5f0", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#fc9b7c", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#67000d", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#f34c37", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#7e0610", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#fee5d8", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fc8464", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_1c9e043f9bc1179ca5f274defa59f1f8.bindTooltip(\n", + " geo_json_714504b95353607487f4ed6bbeddf108.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -3650,48 +3754,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_1c9e043f9bc1179ca5f274defa59f1f8.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_714504b95353607487f4ed6bbeddf108.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_a919b16c102e00244b4f66af7870fc21 = {};\n", + " var color_map_6b025ba90bc2511f78754e179ab90787 = {};\n", "\n", " \n", - " color_map_a919b16c102e00244b4f66af7870fc21.color = d3.scale.threshold()\n", + " color_map_6b025ba90bc2511f78754e179ab90787.color = d3.scale.threshold()\n", " .domain([80.32095592022247, 80.5468470652185, 80.77273821021453, 80.99862935521054, 81.22452050020657, 81.45041164520259, 81.67630279019862, 81.90219393519465, 82.12808508019066, 82.35397622518668, 82.57986737018271, 82.80575851517874, 83.03164966017476, 83.25754080517078, 83.4834319501668, 83.70932309516283, 83.93521424015886, 84.16110538515488, 84.3869965301509, 84.61288767514692, 84.83877882014295, 85.06466996513898, 85.290561110135, 85.51645225513101, 85.74234340012704, 85.96823454512307, 86.1941256901191, 86.42001683511512, 86.64590798011115, 86.87179912510716, 87.09769027010319, 87.32358141509921, 87.54947256009524, 87.77536370509127, 88.00125485008728, 88.2271459950833, 88.45303714007933, 88.67892828507536, 88.90481943007138, 89.13071057506741, 89.35660172006342, 89.58249286505945, 89.80838401005548, 90.0342751550515, 90.26016630004752, 90.48605744504354, 90.71194859003957, 90.9378397350356, 91.16373088003162, 91.38962202502765, 91.61551317002366, 91.84140431501969, 92.06729546001571, 92.29318660501174, 92.51907775000777, 92.74496889500378, 92.9708600399998, 93.19675118499583, 93.42264232999186, 93.64853347498789, 93.8744246199839, 94.10031576497992, 94.32620690997595, 94.55209805497198, 94.777989199968, 95.00388034496402, 95.22977148996004, 95.45566263495607, 95.6815537799521, 95.90744492494812, 96.13333606994414, 96.35922721494016, 96.58511835993619, 96.81100950493222, 97.03690064992824, 97.26279179492425, 97.48868293992028, 97.71457408491631, 97.94046522991233, 98.16635637490836, 98.39224751990437, 98.61813866490041, 98.84402980989643, 99.06992095489245, 99.29581209988848, 99.52170324488449, 99.74759438988052, 99.97348553487654, 100.19937667987257, 100.4252678248686, 100.65115896986461, 100.87705011486064, 101.10294125985666, 101.32883240485269, 101.55472354984872, 101.78061469484473, 102.00650583984077, 102.23239698483678, 102.45828812983281, 102.68417927482884, 102.91007041982486, 103.13596156482089, 103.3618527098169, 103.58774385481293, 103.81363499980895, 104.03952614480497, 104.265417289801, 104.49130843479702, 104.71719957979305, 104.94309072478907, 105.16898186978509, 105.39487301478111, 105.62076415977714, 105.84665530477317, 106.07254644976919, 106.29843759476522, 106.52432873976124, 106.75021988475726, 106.97611102975328, 107.20200217474931, 107.42789331974534, 107.65378446474136, 107.87967560973738, 108.1055667547334, 108.33145789972943, 108.55734904472546, 108.78324018972148, 109.0091313347175, 109.23502247971352, 109.46091362470955, 109.68680476970557, 109.9126959147016, 110.13858705969761, 110.36447820469364, 110.59036934968967, 110.8162604946857, 111.04215163968172, 111.26804278467773, 111.49393392967376, 111.71982507466979, 111.94571621966581, 112.17160736466184, 112.39749850965785, 112.62338965465388, 112.8492807996499, 113.07517194464593, 113.30106308964196, 113.52695423463797, 113.75284537963401, 113.97873652463002, 114.20462766962605, 114.43051881462208, 114.65640995961809, 114.88230110461413, 115.10819224961014, 115.33408339460617, 115.5599745396022, 115.7858656845982, 116.01175682959425, 116.23764797459026, 116.46353911958629, 116.68943026458231, 116.91532140957834, 117.14121255457435, 117.36710369957038, 117.59299484456639, 117.81888598956243, 118.04477713455844, 118.27066827955447, 118.4965594245505, 118.72245056954652, 118.94834171454255, 119.17423285953856, 119.40012400453459, 119.62601514953062, 119.85190629452664, 120.07779743952267, 120.30368858451868, 120.52957972951472, 120.75547087451073, 120.98136201950676, 121.20725316450279, 121.4331443094988, 121.65903545449484, 121.88492659949085, 122.11081774448688, 122.3367088894829, 122.56260003447892, 122.78849117947496, 123.01438232447097, 123.240273469467, 123.46616461446303, 123.69205575945905, 123.91794690445508, 124.14383804945109, 124.36972919444712, 124.59562033944314, 124.82151148443917, 125.0474026294352, 125.27329377443121, 125.49918491942725, 125.72507606442326, 125.95096720941929, 126.17685835441532, 126.40274949941133, 126.62864064440737, 126.85453178940338, 127.08042293439941, 127.30631407939543, 127.53220522439145, 127.75809636938747, 127.9839875143835, 128.2098786593795, 128.43576980437555, 128.66166094937157, 128.8875520943676, 129.11344323936362, 129.33933438435963, 129.56522552935567, 129.79111667435168, 130.01700781934773, 130.24289896434374, 130.46879010933975, 130.6946812543358, 130.9205723993318, 131.14646354432784, 131.37235468932386, 131.59824583431987, 131.8241369793159, 132.05002812431192, 132.27591926930796, 132.50181041430397, 132.7277015593, 132.95359270429603, 133.17948384929204, 133.40537499428808, 133.6312661392841, 133.8571572842801, 134.08304842927615, 134.30893957427216, 134.5348307192682, 134.7607218642642, 134.98661300926022, 135.21250415425627, 135.43839529925228, 135.66428644424832, 135.89017758924433, 136.11606873424034, 136.34195987923638, 136.56785102423243, 136.79374216922844, 137.01963331422445, 137.24552445922046, 137.4714156042165, 137.69730674921254, 137.92319789420856, 138.14908903920457, 138.37498018420058, 138.60087132919662, 138.82676247419263, 139.05265361918867, 139.2785447641847, 139.5044359091807, 139.73032705417674, 139.95621819917275, 140.1821093441688, 140.4080004891648, 140.63389163416082, 140.85978277915686, 141.08567392415287, 141.3115650691489, 141.53745621414492, 141.76334735914094, 141.98923850413698, 142.215129649133, 142.44102079412903, 142.66691193912504, 142.89280308412106, 143.1186942291171, 143.34458537411314, 143.57047651910915, 143.79636766410516, 144.02225880910117, 144.24814995409722, 144.47404109909326, 144.69993224408927, 144.92582338908528, 145.1517145340813, 145.37760567907733, 145.60349682407337, 145.8293879690694, 146.0552791140654, 146.2811702590614, 146.50706140405745, 146.7329525490535, 146.9588436940495, 147.18473483904552, 147.41062598404153, 147.63651712903757, 147.8624082740336, 148.08829941902962, 148.31419056402564, 148.54008170902168, 148.7659728540177, 148.99186399901373, 149.21775514400974, 149.44364628900576, 149.6695374340018, 149.8954285789978, 150.12131972399385, 150.34721086898986, 150.57310201398587, 150.79899315898192, 151.02488430397796, 151.25077544897397, 151.47666659396998, 151.702557738966, 151.92844888396203, 152.15434002895807, 152.3802311739541, 152.6061223189501, 152.8320134639461, 153.05790460894215, 153.2837957539382, 153.5096868989342, 153.73557804393022, 153.96146918892623, 154.18736033392224, 154.41325147891828, 154.63914262391432, 154.86503376891034, 155.09092491390635, 155.31681605890236, 155.5427072038984, 155.76859834889444, 155.99448949389046, 156.22038063888647, 156.44627178388248, 156.67216292887852, 156.89805407387456, 157.12394521887057, 157.3498363638666, 157.5757275088626, 157.80161865385864, 158.02750979885468, 158.2534009438507, 158.4792920888467, 158.70518323384272, 158.93107437883876, 159.1569655238348, 159.3828566688308, 159.60874781382682, 159.83463895882284, 160.06053010381888, 160.28642124881492, 160.51231239381093, 160.73820353880694, 160.96409468380295, 161.189985828799, 161.41587697379504, 161.64176811879105, 161.86765926378706, 162.0935504087831, 162.31944155377911, 162.54533269877516, 162.77122384377117, 162.99711498876718, 163.22300613376322, 163.44889727875923, 163.67478842375527, 163.9006795687513, 164.1265707137473, 164.35246185874334, 164.57835300373938, 164.8042441487354, 165.0301352937314, 165.25602643872742, 165.48191758372346, 165.7078087287195, 165.9336998737155, 166.15959101871152, 166.38548216370754, 166.61137330870358, 166.83726445369962, 167.06315559869563, 167.28904674369164, 167.51493788868765, 167.7408290336837, 167.96672017867974, 168.19261132367575, 168.41850246867176, 168.64439361366777, 168.87028475866381, 169.09617590365986, 169.32206704865587, 169.54795819365188, 169.7738493386479, 169.99974048364393, 170.22563162863997, 170.451522773636, 170.677413918632, 170.903305063628, 171.12919620862405, 171.3550873536201, 171.5809784986161, 171.80686964361212, 172.03276078860813, 172.25865193360417, 172.4845430786002, 172.71043422359622, 172.93632536859224, 173.16221651358828, 173.3881076585843, 173.61399880358033, 173.83988994857634, 174.06578109357235, 174.2916722385684, 174.51756338356438, 174.74345452856042, 174.96934567355646, 175.19523681855247, 175.42112796354849, 175.64701910854453, 175.87291025354054, 176.09880139853658, 176.3246925435326, 176.5505836885286, 176.77647483352465, 177.00236597852066, 177.2282571235167, 177.4541482685127, 177.68003941350872, 177.90593055850476, 178.1318217035008, 178.35771284849682, 178.58360399349283, 178.80949513848884, 179.03538628348488, 179.26127742848092, 179.48716857347694, 179.71305971847295, 179.93895086346896, 180.164842008465, 180.39073315346104, 180.61662429845705, 180.84251544345307, 181.06840658844908, 181.29429773344512, 181.52018887844116, 181.74608002343717, 181.97197116843319, 182.1978623134292, 182.42375345842524, 182.64964460342128, 182.8755357484173, 183.1014268934133, 183.32731803840932, 183.55320918340536, 183.7791003284014, 184.0049914733974, 184.23088261839342, 184.45677376338944, 184.68266490838548, 184.90855605338152, 185.13444719837753, 185.36033834337354, 185.58622948836955, 185.8121206333656, 186.03801177836164, 186.26390292335765, 186.48979406835366, 186.7156852133497, 186.9415763583457, 187.16746750334175, 187.39335864833777, 187.61924979333378, 187.84514093832982, 188.07103208332583, 188.29692322832187, 188.52281437331789, 188.7487055183139, 188.97459666330994, 189.20048780830598, 189.426378953302, 189.652270098298, 189.87816124329402, 190.10405238829006, 190.3299435332861, 190.5558346782821, 190.78172582327812, 191.00761696827414, 191.23350811327018, 191.45939925826622, 191.68529040326223, 191.91118154825824, 192.13707269325425, 192.3629638382503, 192.58885498324634, 192.81474612824235, 193.04063727323836])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_a919b16c102e00244b4f66af7870fc21.x = d3.scale.linear()\n", + " color_map_6b025ba90bc2511f78754e179ab90787.x = d3.scale.linear()\n", " .domain([80.32095592022247, 193.04063727323836])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_a919b16c102e00244b4f66af7870fc21.legend = L.control({position: 'topright'});\n", - " color_map_a919b16c102e00244b4f66af7870fc21.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_a919b16c102e00244b4f66af7870fc21.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_6b025ba90bc2511f78754e179ab90787.legend = L.control({position: 'topright'});\n", + " color_map_6b025ba90bc2511f78754e179ab90787.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_6b025ba90bc2511f78754e179ab90787.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_a919b16c102e00244b4f66af7870fc21.xAxis = d3.svg.axis()\n", - " .scale(color_map_a919b16c102e00244b4f66af7870fc21.x)\n", + " color_map_6b025ba90bc2511f78754e179ab90787.xAxis = d3.svg.axis()\n", + " .scale(color_map_6b025ba90bc2511f78754e179ab90787.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([80.32095592022247, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 91.81394303856919, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 103.30693015691591, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 114.79991727526263, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 126.29290439360935, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 137.78589151195607, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 149.27887863030278, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 160.77186574864947, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 172.26485286699622, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 183.7578399853429, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_a919b16c102e00244b4f66af7870fc21.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_6b025ba90bc2511f78754e179ab90787.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_a919b16c102e00244b4f66af7870fc21.g = color_map_a919b16c102e00244b4f66af7870fc21.svg.append("g")\n", + " color_map_6b025ba90bc2511f78754e179ab90787.g = color_map_6b025ba90bc2511f78754e179ab90787.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_a919b16c102e00244b4f66af7870fc21.g.selectAll("rect")\n", - " .data(color_map_a919b16c102e00244b4f66af7870fc21.color.range().map(function(d, i) {\n", + " color_map_6b025ba90bc2511f78754e179ab90787.g.selectAll("rect")\n", + " .data(color_map_6b025ba90bc2511f78754e179ab90787.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_a919b16c102e00244b4f66af7870fc21.x(color_map_a919b16c102e00244b4f66af7870fc21.color.domain()[i - 1]) : color_map_a919b16c102e00244b4f66af7870fc21.x.range()[0],\n", - " x1: i < color_map_a919b16c102e00244b4f66af7870fc21.color.domain().length ? color_map_a919b16c102e00244b4f66af7870fc21.x(color_map_a919b16c102e00244b4f66af7870fc21.color.domain()[i]) : color_map_a919b16c102e00244b4f66af7870fc21.x.range()[1],\n", + " x0: i ? color_map_6b025ba90bc2511f78754e179ab90787.x(color_map_6b025ba90bc2511f78754e179ab90787.color.domain()[i - 1]) : color_map_6b025ba90bc2511f78754e179ab90787.x.range()[0],\n", + " x1: i < color_map_6b025ba90bc2511f78754e179ab90787.color.domain().length ? color_map_6b025ba90bc2511f78754e179ab90787.x(color_map_6b025ba90bc2511f78754e179ab90787.color.domain()[i]) : color_map_6b025ba90bc2511f78754e179ab90787.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -3701,12 +3809,13 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_a919b16c102e00244b4f66af7870fc21.g.call(color_map_a919b16c102e00244b4f66af7870fc21.xAxis).append("text")\n", + " color_map_6b025ba90bc2511f78754e179ab90787.g.call(color_map_6b025ba90bc2511f78754e179ab90787.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("spacing");\n", " \n", - " function geo_json_b2d82c616ee323d67d892158207fd010_styler(feature) {\n", + " function geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#fca082", "fillColor": "#fca082", "fillOpacity": 0.5, "weight": 2};\n", @@ -3730,52 +3839,54 @@ " return {"color": "#fff5f0", "fillColor": "#fff5f0", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_b2d82c616ee323d67d892158207fd010_highlighter(feature) {\n", + " function geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_b2d82c616ee323d67d892158207fd010_pointToLayer(feature, latlng) {\n", + " function geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_b2d82c616ee323d67d892158207fd010_styler(feature)\n", + " let style = geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_b2d82c616ee323d67d892158207fd010_onEachFeature(feature, layer) {\n", + " function geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_b2d82c616ee323d67d892158207fd010.resetStyle(e.target);\n", + " geo_json_8358d0f07ce27fc26a87ccc9b0e669c2.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_b2d82c616ee323d67d892158207fd010_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_b2d82c616ee323d67d892158207fd010 = L.geoJson(null, {\n", - " onEachFeature: geo_json_b2d82c616ee323d67d892158207fd010_onEachFeature,\n", + " var geo_json_8358d0f07ce27fc26a87ccc9b0e669c2 = L.geoJson(null, {\n", + " onEachFeature: geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_onEachFeature,\n", " \n", - " style: geo_json_b2d82c616ee323d67d892158207fd010_styler,\n", - " pointToLayer: geo_json_b2d82c616ee323d67d892158207fd010_pointToLayer,\n", + " style: geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_styler,\n", + " pointToLayer: geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_b2d82c616ee323d67d892158207fd010_add (data) {\n", - " geo_json_b2d82c616ee323d67d892158207fd010\n", + " function geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_add (data) {\n", + " geo_json_8358d0f07ce27fc26a87ccc9b0e669c2\n", " .addData(data);\n", " }\n", - " geo_json_b2d82c616ee323d67d892158207fd010_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fca082", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#7c0510", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#ffede5", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fb7353", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#6b010e", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#67000d", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#f14130", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#e22e27", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#db2824", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_8358d0f07ce27fc26a87ccc9b0e669c2_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#fca082", "access": 3, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 8, "connectivity_computed": 8, "degree": 5, "edge_indeces": "[0, 3, 15, 27]", "length": 839.5666838320316, "nodeID": 0, "orthogonality": 68.74678997354196, "spacing": 104.94583547900395, "x": 1603374.6625343116, "y": 6464077.898491419}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#7c0510", "access": 2, "betweenness_centrality": 0.08796296296296295, "closeness_centrality": 0.5625, "connectivity": 6, "connectivity_computed": 6, "degree": 4, "edge_indeces": "[1, 12, 14, 25]", "length": 759.0900425060918, "nodeID": 1, "orthogonality": 86.32371095647791, "spacing": 126.51500708434862, "x": 1603237.0487682838, "y": 6464133.622486805}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#ffede5", "access": 4, "betweenness_centrality": 0.04629629629629629, "closeness_centrality": 0.5294117647058824, "connectivity": 8, "connectivity_computed": 8, "degree": 4, "edge_indeces": "[2, 11, 28, 30]", "length": 744.7579337248078, "nodeID": 2, "orthogonality": 60.675072020256245, "spacing": 93.09474171560097, "x": 1603707.1065106073, "y": 6464238.853991265}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#fb7353", "access": 2, "betweenness_centrality": 0.13657407407407404, "closeness_centrality": 0.6923076923076923, "connectivity": 7, "connectivity_computed": 7, "degree": 5, "edge_indeces": "[4, 5, 6]", "length": 562.2466914415573, "nodeID": 3, "orthogonality": 72.69057271585089, "spacing": 80.32095592022247, "x": 1603149.9288811635, "y": 6464130.224503239}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#6b010e", "access": 3, "betweenness_centrality": 0.5046296296296297, "closeness_centrality": 0.75, "connectivity": 9, "connectivity_computed": 9, "degree": 6, "edge_indeces": "[7, 8, 9, 13, 21, 22, 24]", "length": 1077.3606756995746, "nodeID": 4, "orthogonality": 87.28338224081126, "spacing": 119.70674174439718, "x": 1603264.6577362637, "y": 6463848.97596353}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#67000d", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[10]", "length": 193.04063727323836, "nodeID": 5, "orthogonality": 87.60977577529626, "spacing": 193.04063727323836, "x": 1603137.4077031056, "y": 6463800.908382258}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#f14130", "access": 4, "betweenness_centrality": 0.06712962962962961, "closeness_centrality": 0.6, "connectivity": 7, "connectivity_computed": 7, "degree": 3, "edge_indeces": "[16, 17, 18, 23, 29]", "length": 1019.7095084794428, "nodeID": 6, "orthogonality": 76.50850905913968, "spacing": 145.67278692563468, "x": 1603592.2349246691, "y": 6464121.336160048}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#e22e27", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.45, "connectivity": 1, "connectivity_computed": 1, "degree": 1, "edge_indeces": "[19]", "length": 187.49184699173748, "nodeID": 7, "orthogonality": 78.26155769686821, "spacing": 187.49184699173748, "x": 1603028.737187382, "y": 6463900.594576759}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#db2824", "access": 0, "betweenness_centrality": 0.020833333333333332, "closeness_centrality": 0.5, "connectivity": 2, "connectivity_computed": 2, "degree": 2, "edge_indeces": "[20]", "length": 182.6849740039611, "nodeID": 8, "orthogonality": 78.91626592156373, "spacing": 91.34248700198054, "x": 1603207.5969886228, "y": 6463992.707728057}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#fff5f0", "access": 0, "betweenness_centrality": 0.0, "closeness_centrality": 0.5, "connectivity": 3, "connectivity_computed": 3, "degree": 3, "edge_indeces": "[26]", "length": 382.50195042922803, "nodeID": 9, "orthogonality": 59.350287847902734, "spacing": 127.50065014307602, "x": 1603342.3426854417, "y": 6464406.368225728}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_b2d82c616ee323d67d892158207fd010.bindTooltip(\n", + " geo_json_8358d0f07ce27fc26a87ccc9b0e669c2.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -3796,48 +3907,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_b2d82c616ee323d67d892158207fd010.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_8358d0f07ce27fc26a87ccc9b0e669c2.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var color_map_9c9a3b841729163a37ee00e93c1e1e5e = {};\n", + " var color_map_1be8097c11a92d55585a09e66b89f55e = {};\n", "\n", " \n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.color = d3.scale.threshold()\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.color = d3.scale.threshold()\n", " .domain([59.350287847902734, 59.406920088238195, 59.46355232857365, 59.52018456890911, 59.57681680924457, 59.63344904958002, 59.69008128991548, 59.74671353025094, 59.8033457705864, 59.85997801092186, 59.91661025125732, 59.97324249159277, 60.02987473192823, 60.086506972263685, 60.143139212599145, 60.199771452934606, 60.25640369327006, 60.31303593360552, 60.36966817394098, 60.42630041427643, 60.48293265461189, 60.539564894947354, 60.59619713528281, 60.65282937561827, 60.70946161595373, 60.76609385628918, 60.82272609662464, 60.8793583369601, 60.935990577295556, 60.992622817631016, 61.04925505796648, 61.10588729830193, 61.16251953863739, 61.219151778972844, 61.275784019308304, 61.332416259643765, 61.38904849997922, 61.44568074031468, 61.50231298065014, 61.55894522098559, 61.61557746132105, 61.67220970165651, 61.728841941991966, 61.78547418232743, 61.84210642266289, 61.89873866299834, 61.9553709033338, 62.01200314366926, 62.068635384004715, 62.125267624340175, 62.181899864675636, 62.23853210501109, 62.29516434534655, 62.35179658568201, 62.40842882601746, 62.46506106635292, 62.52169330668838, 62.57832554702384, 62.6349577873593, 62.69159002769475, 62.74822226803021, 62.80485450836567, 62.861486748701125, 62.918118989036586, 62.974751229372046, 63.0313834697075, 63.08801571004296, 63.14464795037842, 63.201280190713874, 63.257912431049334, 63.314544671384795, 63.37117691172025, 63.42780915205571, 63.48444139239116, 63.54107363272662, 63.59770587306208, 63.65433811339754, 63.710970353732996, 63.76760259406846, 63.82423483440391, 63.88086707473937, 63.93749931507483, 63.994131555410284, 64.05076379574575, 64.1073960360812, 64.16402827641666, 64.22066051675212, 64.27729275708758, 64.33392499742304, 64.39055723775849, 64.44718947809395, 64.5038217184294, 64.56045395876487, 64.61708619910033, 64.67371843943579, 64.73035067977123, 64.7869829201067, 64.84361516044216, 64.90024740077762, 64.95687964111308, 65.01351188144854, 65.07014412178398, 65.12677636211944, 65.1834086024549, 65.24004084279036, 65.29667308312582, 65.35330532346129, 65.40993756379673, 65.46656980413219, 65.52320204446765, 65.57983428480311, 65.63646652513857, 65.69309876547402, 65.74973100580948, 65.80636324614494, 65.8629954864804, 65.91962772681586, 65.97625996715132, 66.03289220748677, 66.08952444782223, 66.14615668815769, 66.20278892849315, 66.25942116882861, 66.31605340916407, 66.37268564949952, 66.42931788983498, 66.48595013017044, 66.5425823705059, 66.59921461084136, 66.65584685117682, 66.71247909151226, 66.76911133184772, 66.82574357218319, 66.88237581251865, 66.9390080528541, 66.99564029318955, 67.05227253352501, 67.10890477386047, 67.16553701419593, 67.2221692545314, 67.27880149486685, 67.3354337352023, 67.39206597553776, 67.44869821587322, 67.50533045620868, 67.56196269654414, 67.61859493687959, 67.67522717721505, 67.73185941755051, 67.78849165788597, 67.84512389822143, 67.90175613855689, 67.95838837889235, 68.0150206192278, 68.07165285956326, 68.12828509989872, 68.18491734023418, 68.24154958056964, 68.29818182090509, 68.35481406124055, 68.411446301576, 68.46807854191147, 68.52471078224693, 68.58134302258239, 68.63797526291783, 68.6946075032533, 68.75123974358876, 68.80787198392422, 68.86450422425968, 68.92113646459514, 68.97776870493058, 69.03440094526604, 69.0910331856015, 69.14766542593696, 69.20429766627242, 69.26092990660788, 69.31756214694333, 69.37419438727879, 69.43082662761425, 69.48745886794971, 69.54409110828517, 69.60072334862062, 69.65735558895608, 69.71398782929154, 69.770620069627, 69.82725230996246, 69.88388455029792, 69.94051679063338, 69.99714903096883, 70.05378127130429, 70.11041351163975, 70.16704575197521, 70.22367799231066, 70.28031023264612, 70.33694247298158, 70.39357471331704, 70.4502069536525, 70.50683919398796, 70.56347143432342, 70.62010367465886, 70.67673591499432, 70.73336815532979, 70.79000039566525, 70.84663263600069, 70.90326487633615, 70.95989711667161, 71.01652935700707, 71.07316159734253, 71.129793837678, 71.18642607801345, 71.2430583183489, 71.29969055868436, 71.35632279901982, 71.41295503935528, 71.46958727969074, 71.52621952002619, 71.58285176036165, 71.63948400069711, 71.69611624103257, 71.75274848136803, 71.80938072170349, 71.86601296203894, 71.9226452023744, 71.97927744270986, 72.03590968304532, 72.09254192338078, 72.14917416371624, 72.20580640405169, 72.26243864438715, 72.3190708847226, 72.37570312505807, 72.43233536539353, 72.48896760572899, 72.54559984606443, 72.6022320863999, 72.65886432673535, 72.71549656707082, 72.77212880740628, 72.82876104774172, 72.88539328807718, 72.94202552841264, 72.9986577687481, 73.05529000908356, 73.11192224941902, 73.16855448975448, 73.22518673008993, 73.28181897042539, 73.33845121076085, 73.39508345109631, 73.45171569143176, 73.50834793176722, 73.56498017210268, 73.62161241243814, 73.6782446527736, 73.73487689310906, 73.79150913344452, 73.84814137377997, 73.90477361411543, 73.96140585445089, 74.01803809478635, 74.07467033512181, 74.13130257545725, 74.18793481579272, 74.24456705612818, 74.30119929646364, 74.3578315367991, 74.41446377713456, 74.47109601747, 74.52772825780546, 74.58436049814092, 74.64099273847638, 74.69762497881185, 74.7542572191473, 74.81088945948275, 74.86752169981821, 74.92415394015367, 74.98078618048913, 75.0374184208246, 75.09405066116005, 75.1506829014955, 75.20731514183096, 75.26394738216642, 75.32057962250188, 75.37721186283734, 75.43384410317279, 75.49047634350825, 75.54710858384371, 75.60374082417917, 75.66037306451463, 75.71700530485009, 75.77363754518554, 75.830269785521, 75.88690202585646, 75.94353426619192, 76.00016650652738, 76.05679874686282, 76.11343098719829, 76.17006322753375, 76.2266954678692, 76.28332770820467, 76.33995994854013, 76.39659218887559, 76.45322442921103, 76.5098566695465, 76.56648890988195, 76.62312115021741, 76.67975339055288, 76.73638563088832, 76.79301787122378, 76.84965011155924, 76.9062823518947, 76.96291459223016, 77.01954683256562, 77.07617907290108, 77.13281131323653, 77.18944355357199, 77.24607579390745, 77.3027080342429, 77.35934027457836, 77.41597251491382, 77.47260475524928, 77.52923699558474, 77.5858692359202, 77.64250147625566, 77.69913371659112, 77.75576595692657, 77.81239819726203, 77.86903043759749, 77.92566267793295, 77.98229491826841, 78.03892715860385, 78.09555939893932, 78.15219163927478, 78.20882387961024, 78.2654561199457, 78.32208836028116, 78.37872060061662, 78.43535284095206, 78.49198508128752, 78.54861732162298, 78.60524956195844, 78.6618818022939, 78.71851404262935, 78.77514628296481, 78.83177852330027, 78.88841076363573, 78.9450430039712, 79.00167524430665, 79.0583074846421, 79.11493972497756, 79.17157196531302, 79.22820420564848, 79.28483644598393, 79.34146868631939, 79.39810092665485, 79.45473316699031, 79.51136540732577, 79.56799764766123, 79.62462988799669, 79.68126212833215, 79.7378943686676, 79.79452660900306, 79.85115884933852, 79.90779108967398, 79.96442333000942, 80.02105557034488, 80.07768781068035, 80.1343200510158, 80.19095229135127, 80.24758453168673, 80.30421677202219, 80.36084901235765, 80.4174812526931, 80.47411349302855, 80.53074573336401, 80.58737797369947, 80.64401021403492, 80.70064245437038, 80.75727469470584, 80.8139069350413, 80.87053917537676, 80.92717141571222, 80.98380365604767, 81.04043589638313, 81.09706813671859, 81.15370037705405, 81.21033261738951, 81.26696485772496, 81.32359709806042, 81.38022933839588, 81.43686157873134, 81.4934938190668, 81.55012605940226, 81.60675829973772, 81.66339054007317, 81.72002278040863, 81.77665502074409, 81.83328726107955, 81.88991950141501, 81.94655174175045, 82.00318398208591, 82.05981622242138, 82.11644846275684, 82.1730807030923, 82.22971294342776, 82.2863451837632, 82.34297742409866, 82.39960966443412, 82.45624190476958, 82.51287414510503, 82.56950638544049, 82.62613862577595, 82.68277086611141, 82.73940310644687, 82.79603534678233, 82.85266758711779, 82.90929982745325, 82.9659320677887, 83.02256430812416, 83.07919654845962, 83.13582878879508, 83.19246102913053, 83.24909326946599, 83.30572550980145, 83.36235775013691, 83.41898999047237, 83.47562223080783, 83.53225447114329, 83.58888671147875, 83.6455189518142, 83.70215119214966, 83.75878343248512, 83.81541567282058, 83.87204791315602, 83.92868015349148, 83.98531239382694, 84.0419446341624, 84.09857687449787, 84.15520911483333, 84.21184135516877, 84.26847359550423, 84.3251058358397, 84.38173807617515, 84.43837031651061, 84.49500255684606, 84.55163479718152, 84.60826703751698, 84.66489927785244, 84.7215315181879, 84.77816375852336, 84.83479599885882, 84.89142823919428, 84.94806047952973, 85.00469271986519, 85.06132496020065, 85.11795720053611, 85.17458944087156, 85.23122168120702, 85.28785392154248, 85.34448616187794, 85.4011184022134, 85.45775064254886, 85.51438288288432, 85.57101512321978, 85.62764736355523, 85.68427960389069, 85.74091184422615, 85.7975440845616, 85.85417632489705, 85.91080856523251, 85.96744080556797, 86.02407304590344, 86.0807052862389, 86.13733752657436, 86.1939697669098, 86.25060200724526, 86.30723424758072, 86.36386648791618, 86.42049872825164, 86.47713096858709, 86.53376320892255, 86.59039544925801, 86.64702768959347, 86.70365992992893, 86.76029217026439, 86.81692441059985, 86.8735566509353, 86.93018889127076, 86.98682113160622, 87.04345337194168, 87.10008561227714, 87.15671785261259, 87.21335009294805, 87.26998233328351, 87.32661457361897, 87.38324681395443, 87.43987905428989, 87.49651129462534, 87.5531435349608, 87.60977577529626])\n", " .range(['#fff5f0ff', '#fff5f0ff', '#fff4efff', '#fff4efff', '#fff4eeff', '#fff4eeff', '#fff3edff', '#fff3edff', '#fff2ecff', '#fff2ecff', '#fff2ebff', '#fff2ebff', '#fff1eaff', '#fff1eaff', '#fff0e9ff', '#fff0e9ff', '#fff0e8ff', '#fff0e8ff', '#ffefe8ff', '#ffefe8ff', '#ffeee7ff', '#ffeee7ff', '#ffeee6ff', '#ffeee6ff', '#ffede5ff', '#ffede5ff', '#ffece4ff', '#ffece4ff', '#ffece3ff', '#ffece3ff', '#ffebe2ff', '#ffebe2ff', '#feeae1ff', '#feeae1ff', '#feeae0ff', '#feeadfff', '#fee9dfff', '#fee9deff', '#fee8deff', '#fee8ddff', '#fee8ddff', '#fee7dcff', '#fee7dcff', '#fee7dbff', '#fee7dbff', '#fee6daff', '#fee6daff', '#fee5d9ff', '#fee5d9ff', '#fee5d8ff', '#fee5d8ff', '#fee4d8ff', '#fee4d8ff', '#fee3d7ff', '#fee3d7ff', '#fee3d6ff', '#fee3d6ff', '#fee2d5ff', '#fee2d5ff', '#fee1d4ff', '#fee1d4ff', '#fee1d3ff', '#fee1d3ff', '#fee0d2ff', '#fee0d1ff', '#fedfd0ff', '#fedfd0ff', '#fedecfff', '#feddceff', '#fedccdff', '#fedccdff', '#fedbccff', '#fedbcbff', '#fedacaff', '#fedac9ff', '#fed9c9ff', '#fed9c8ff', '#fed8c7ff', '#fed7c6ff', '#fdd7c6ff', '#fdd6c5ff', '#fdd5c3ff', '#fdd4c2ff', '#fdd4c2ff', '#fdd3c1ff', '#fdd3c0ff', '#fdd2bfff', '#fdd2bfff', '#fdd1beff', '#fdd1bdff', '#fdd0bcff', '#fdcfbcff', '#fdcebbff', '#fdcebaff', '#fdcdb9ff', '#fdcdb9ff', '#fdccb8ff', '#fdccb7ff', '#fdcbb6ff', '#fdcbb6ff', '#fdcab5ff', '#fdcab4ff', '#fdc9b3ff', '#fdc8b3ff', '#fdc7b2ff', '#fdc7b1ff', '#fdc6b0ff', '#fdc6afff', '#fdc5aeff', '#fdc5adff', '#fcc4adff', '#fcc4acff', '#fcc3abff', '#fcc3aaff', '#fcc2aaff', '#fcc1a9ff', '#fcc1a8ff', '#fcc0a7ff', '#fcbfa7ff', '#fcbea6ff', '#fcbea5ff', '#fcbda4ff', '#fcbda3ff', '#fcbca2ff', '#fcbca2ff', '#fcbba1ff', '#fcbaa0ff', '#fcb99fff', '#fcb99fff', '#fcb89eff', '#fcb89dff', '#fcb79cff', '#fcb79cff', '#fcb69bff', '#fcb59aff', '#fcb499ff', '#fcb499ff', '#fcb398ff', '#fcb397ff', '#fcb296ff', '#fcb196ff', '#fcb095ff', '#fcb094ff', '#fcaf93ff', '#fcaf92ff', '#fcae92ff', '#fcae91ff', '#fcad90ff', '#fcac8fff', '#fcab8fff', '#fcab8eff', '#fcaa8dff', '#fca98cff', '#fca98cff', '#fca88bff', '#fca78bff', '#fca68aff', '#fca689ff', '#fca588ff', '#fca588ff', '#fca487ff', '#fca486ff', '#fca385ff', '#fca284ff', '#fca183ff', '#fca183ff', '#fca082ff', '#fc9f81ff', '#fc9e80ff', '#fc9e80ff', '#fc9d7fff', '#fc9d7eff', '#fc9c7dff', '#fc9c7dff', '#fc9b7cff', '#fc9a7bff', '#fc997aff', '#fc997aff', '#fc9879ff', '#fc9878ff', '#fc9777ff', '#fc9676ff', '#fc9576ff', '#fc9575ff', '#fc9474ff', '#fc9473ff', '#fc9373ff', '#fc9372ff', '#fc9272ff', '#fc9171ff', '#fc9070ff', '#fc8f6fff', '#fc8f6fff', '#fc8e6eff', '#fc8e6eff', '#fc8d6dff', '#fc8d6dff', '#fc8c6cff', '#fc8b6bff', '#fc8a6aff', '#fc8a6aff', '#fc8969ff', '#fc8968ff', '#fc8867ff', '#fc8767ff', '#fc8666ff', '#fc8666ff', '#fc8565ff', '#fc8565ff', '#fc8464ff', '#fc8363ff', '#fc8262ff', '#fc8262ff', '#fc8161ff', '#fc8161ff', '#fc8060ff', '#fc805fff', '#fc7f5fff', '#fc7e5eff', '#fc7d5dff', '#fb7d5cff', '#fb7c5cff', '#fb7c5bff', '#fb7b5bff', '#fb7b5aff', '#fb7a5aff', '#fb7959ff', '#fb7858ff', '#fb7757ff', '#fb7757ff', '#fb7656ff', '#fb7656ff', '#fb7555ff', '#fb7555ff', '#fb7454ff', '#fb7353ff', '#fb7252ff', '#fb7252ff', '#fb7151ff', '#fb7151ff', '#fb7050ff', '#fb704fff', '#fb6f4eff', '#fb6e4eff', '#fb6d4dff', '#fb6d4dff', '#fb6c4cff', '#fb6c4cff', '#fb6b4bff', '#fb6a4bff', '#fb694aff', '#fb694aff', '#fb6849ff', '#fa6748ff', '#fa6648ff', '#fa6647ff', '#fa6547ff', '#fa6446ff', '#fa6346ff', '#f96345ff', '#f96245ff', '#f96144ff', '#f96044ff', '#f95f43ff', '#f95f43ff', '#f85e42ff', '#f85d42ff', '#f85c41ff', '#f85c41ff', '#f75b40ff', '#f75b40ff', '#f75a3fff', '#f7593fff', '#f7583eff', '#f6583eff', '#f6573dff', '#f6563dff', '#f6553cff', '#f6553cff', '#f6543bff', '#f5533bff', '#f5523aff', '#f5523aff', '#f5513aff', '#f4503aff', '#f44f39ff', '#f44f39ff', '#f44d38ff', '#f44d38ff', '#f44c37ff', '#f34b37ff', '#f34a36ff', '#f34a35ff', '#f34935ff', '#f34834ff', '#f34734ff', '#f24733ff', '#f24633ff', '#f24532ff', '#f24432ff', '#f14331ff', '#f14331ff', '#f14230ff', '#f14130ff', '#f1402fff', '#f1402fff', '#f03f2eff', '#f03f2eff', '#f03e2dff', '#f03d2dff', '#f03c2cff', '#f03c2cff', '#ef3b2cff', '#ee3a2cff', '#ee392bff', '#ed392bff', '#ed382bff', '#ec382bff', '#ec372aff', '#eb372aff', '#eb362aff', '#ea362aff', '#ea3529ff', '#e93529ff', '#e93429ff', '#e83429ff', '#e73328ff', '#e63328ff', '#e63228ff', '#e53128ff', '#e53027ff', '#e43027ff', '#e42f27ff', '#e32f27ff', '#e32e27ff', '#e22d26ff', '#e22d26ff', '#e12c26ff', '#e12c26ff', '#e02b25ff', '#df2b25ff', '#de2a25ff', '#de2a25ff', '#dd2924ff', '#dd2924ff', '#dc2824ff', '#dc2824ff', '#db2723ff', '#db2723ff', '#da2623ff', '#d92523ff', '#d92422ff', '#d82422ff', '#d82322ff', '#d72322ff', '#d72221ff', '#d52221ff', '#d52121ff', '#d42121ff', '#d42020ff', '#d32020ff', '#d31f20ff', '#d21f20ff', '#d21e1fff', '#d11e1fff', '#d11d1fff', '#d01d1fff', '#d01c1fff', '#cf1b1fff', '#cf1a1eff', '#ce1a1eff', '#cd191eff', '#cc181eff', '#cc181dff', '#cb181dff', '#cb181dff', '#ca181dff', '#ca181dff', '#c9171cff', '#c9171cff', '#c8171cff', '#c8171cff', '#c7171cff', '#c6171cff', '#c5161cff', '#c5161cff', '#c4161bff', '#c4161bff', '#c3161bff', '#c2161bff', '#c2161bff', '#c1161bff', '#c1151bff', '#c0151bff', '#bf151aff', '#be151aff', '#be151aff', '#bd151aff', '#bd141aff', '#bc141aff', '#bc141aff', '#bb141aff', '#ba1419ff', '#b91419ff', '#b91419ff', '#b81419ff', '#b81319ff', '#b71319ff', '#b71319ff', '#b61319ff', '#b61318ff', '#b51318ff', '#b41218ff', '#b31218ff', '#b31218ff', '#b21218ff', '#b21218ff', '#b11217ff', '#b11217ff', '#b01117ff', '#b01117ff', '#af1117ff', '#ae1117ff', '#ad1117ff', '#ad1117ff', '#ac1016ff', '#ab1016ff', '#ab1016ff', '#aa1016ff', '#aa1016ff', '#a91016ff', '#a91016ff', '#a81016ff', '#a80f15ff', '#a70f15ff', '#a60f15ff', '#a50f15ff', '#a50f15ff', '#a30f15ff', '#a20e15ff', '#a10e15ff', '#a00e14ff', '#9f0e14ff', '#9e0d14ff', '#9d0d14ff', '#9d0d14ff', '#9c0d14ff', '#9b0c14ff', '#9a0c14ff', '#990c13ff', '#980c13ff', '#970b13ff', '#960b13ff', '#950b13ff', '#940b13ff', '#930a13ff', '#920a13ff', '#910a12ff', '#900912ff', '#8f0912ff', '#8e0912ff', '#8d0912ff', '#8c0812ff', '#8b0812ff', '#8a0811ff', '#890811ff', '#880811ff', '#870811ff', '#860711ff', '#850711ff', '#840711ff', '#830711ff', '#820610ff', '#810610ff', '#800610ff', '#7f0610ff', '#7d0510ff', '#7c0510ff', '#7b0510ff', '#7a0510ff', '#7a040fff', '#79040fff', '#78040fff', '#77040fff', '#76030fff', '#75030fff', '#74030fff', '#73030fff', '#72020eff', '#71020eff', '#70020eff', '#6f020eff', '#6e010eff', '#6d010eff', '#6c010eff', '#6b010eff', '#6a000dff', '#69000dff', '#68000dff', '#67000dff']);\n", " \n", "\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.x = d3.scale.linear()\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.x = d3.scale.linear()\n", " .domain([59.350287847902734, 87.60977577529626])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.legend = L.control({position: 'topright'});\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.legend.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.legend = L.control({position: 'topright'});\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.legend.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.xAxis = d3.svg.axis()\n", - " .scale(color_map_9c9a3b841729163a37ee00e93c1e1e5e.x)\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.xAxis = d3.svg.axis()\n", + " .scale(color_map_1be8097c11a92d55585a09e66b89f55e.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([59.350287847902734, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 62.231647401284036, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 65.11300695466534, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 67.99436650804664, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 70.87572606142794, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 73.75708561480924, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 76.63844516819054, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 79.51980472157183, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 82.40116427495315, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 85.28252382833443, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '']);\n", "\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.g = color_map_9c9a3b841729163a37ee00e93c1e1e5e.svg.append("g")\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.g = color_map_1be8097c11a92d55585a09e66b89f55e.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.g.selectAll("rect")\n", - " .data(color_map_9c9a3b841729163a37ee00e93c1e1e5e.color.range().map(function(d, i) {\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.g.selectAll("rect")\n", + " .data(color_map_1be8097c11a92d55585a09e66b89f55e.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_9c9a3b841729163a37ee00e93c1e1e5e.x(color_map_9c9a3b841729163a37ee00e93c1e1e5e.color.domain()[i - 1]) : color_map_9c9a3b841729163a37ee00e93c1e1e5e.x.range()[0],\n", - " x1: i < color_map_9c9a3b841729163a37ee00e93c1e1e5e.color.domain().length ? color_map_9c9a3b841729163a37ee00e93c1e1e5e.x(color_map_9c9a3b841729163a37ee00e93c1e1e5e.color.domain()[i]) : color_map_9c9a3b841729163a37ee00e93c1e1e5e.x.range()[1],\n", + " x0: i ? color_map_1be8097c11a92d55585a09e66b89f55e.x(color_map_1be8097c11a92d55585a09e66b89f55e.color.domain()[i - 1]) : color_map_1be8097c11a92d55585a09e66b89f55e.x.range()[0],\n", + " x1: i < color_map_1be8097c11a92d55585a09e66b89f55e.color.domain().length ? color_map_1be8097c11a92d55585a09e66b89f55e.x(color_map_1be8097c11a92d55585a09e66b89f55e.color.domain()[i]) : color_map_1be8097c11a92d55585a09e66b89f55e.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -3847,64 +3962,67 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_9c9a3b841729163a37ee00e93c1e1e5e.g.call(color_map_9c9a3b841729163a37ee00e93c1e1e5e.xAxis).append("text")\n", + " color_map_1be8097c11a92d55585a09e66b89f55e.g.call(color_map_1be8097c11a92d55585a09e66b89f55e.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("orthogonality");\n", " \n", - " function geo_json_deb953d739b64b76bb825be27a3a6ce3_styler(feature) {\n", + " function geo_json_3bae834d70b206d6895733d867917003_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"color": "black", "fillColor": "black", "fillOpacity": 0.5, "weight": 1};\n", " }\n", " }\n", - " function geo_json_deb953d739b64b76bb825be27a3a6ce3_highlighter(feature) {\n", + " function geo_json_3bae834d70b206d6895733d867917003_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_deb953d739b64b76bb825be27a3a6ce3_pointToLayer(feature, latlng) {\n", + " function geo_json_3bae834d70b206d6895733d867917003_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_deb953d739b64b76bb825be27a3a6ce3_styler(feature)\n", + " let style = geo_json_3bae834d70b206d6895733d867917003_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_deb953d739b64b76bb825be27a3a6ce3_onEachFeature(feature, layer) {\n", + " function geo_json_3bae834d70b206d6895733d867917003_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_deb953d739b64b76bb825be27a3a6ce3.resetStyle(e.target);\n", + " geo_json_3bae834d70b206d6895733d867917003.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_deb953d739b64b76bb825be27a3a6ce3_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_3bae834d70b206d6895733d867917003_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_deb953d739b64b76bb825be27a3a6ce3 = L.geoJson(null, {\n", - " onEachFeature: geo_json_deb953d739b64b76bb825be27a3a6ce3_onEachFeature,\n", + " var geo_json_3bae834d70b206d6895733d867917003 = L.geoJson(null, {\n", + " onEachFeature: geo_json_3bae834d70b206d6895733d867917003_onEachFeature,\n", " \n", - " style: geo_json_deb953d739b64b76bb825be27a3a6ce3_styler,\n", - " pointToLayer: geo_json_deb953d739b64b76bb825be27a3a6ce3_pointToLayer,\n", - " dashArray: 2,\n", + " style: geo_json_3bae834d70b206d6895733d867917003_styler,\n", + " pointToLayer: geo_json_3bae834d70b206d6895733d867917003_pointToLayer,\n", + " ...{\n", + " "dashArray": 2,\n", + "}\n", " });\n", "\n", - " function geo_json_deb953d739b64b76bb825be27a3a6ce3_add (data) {\n", - " geo_json_deb953d739b64b76bb825be27a3a6ce3\n", + " function geo_json_3bae834d70b206d6895733d867917003_add (data) {\n", + " geo_json_3bae834d70b206d6895733d867917003\n", " .addData(data);\n", " }\n", - " geo_json_deb953d739b64b76bb825be27a3a6ce3_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "black", "angles": "[62.302182356951434, 63.647466378271766]"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "black", "angles": "[36.134980718680936]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "black", "angles": "[29.396028363390087]"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "black", "angles": "[89.74560192447649, 89.75267804978043]"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "black", "angles": "[89.56623033507175, 89.42915166171285]"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "black", "angles": "[70.04113695824684]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "black", "angles": "[89.53084497276808, 89.58581817377714]"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "black", "angles": "[89.2861856598184]"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "black", "angles": "[53.8322224050728]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "black", "angles": "[34.25143801488164]"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "black", "angles": "[84.23886881283048, 80.16976627731358, 47.16443370903167, 59.79419820769666]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "black", "angles": "[88.08366041995446]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "black", "angles": "[88.78833801117518, 89.19788105500966]"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "black", "angles": "[78.26155769686821]"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "black", "angles": "[87.60977577529626]"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "black", "angles": "[86.2834611843536, 88.62264956293333]"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "black", "angles": "[87.79139488488063]"}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_3bae834d70b206d6895733d867917003_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "black", "angles": "[np.float64(62.302182356951434), np.float64(63.647466378271766)]"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "black", "angles": "[np.float64(36.134980718680936)]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "black", "angles": "[np.float64(29.396028363390087)]"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "black", "angles": "[np.float64(89.74560192447649), np.float64(89.75267804978043)]"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "black", "angles": "[np.float64(89.56623033507175), np.float64(89.42915166171285)]"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "black", "angles": "[np.float64(70.04113695824684)]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "black", "angles": "[np.float64(89.53084497276808), np.float64(89.58581817377714)]"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "black", "angles": "[np.float64(89.2861856598184)]"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "black", "angles": "[np.float64(53.8322224050728)]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "black", "angles": "[np.float64(34.25143801488164)]"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "black", "angles": "[np.float64(84.23886881283048), np.float64(80.16976627731358), np.float64(47.16443370903167), np.float64(59.79419820769666)]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "black", "angles": "[np.float64(88.08366041995446)]"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "black", "angles": "[np.float64(88.78833801117518), np.float64(89.19788105500966)]"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "black", "angles": "[np.float64(78.26155769686821)]"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "black", "angles": "[np.float64(87.60977577529626)]"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "black", "angles": "[np.float64(86.2834611843536), np.float64(88.62264956293333)]"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "black", "angles": "[np.float64(87.79139488488063)]"}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_deb953d739b64b76bb825be27a3a6ce3.bindTooltip(\n", + " geo_json_3bae834d70b206d6895733d867917003.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -3925,45 +4043,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_deb953d739b64b76bb825be27a3a6ce3.addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " geo_json_3bae834d70b206d6895733d867917003.addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", " \n", " \n", - " var layer_control_81f8dcf895027c0e8fafe34e17f7ae37_layers = {\n", + " var layer_control_10e0ab329f07016f75f12f283eced67e_layers = {\n", " base_layers : {\n", - " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_144e5103a0ffbba538577158de1c8ceb,\n", + " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_e5c95f5cd33967de5fa8b0d6b6c0bafd,\n", " },\n", " overlays : {\n", - " "strokes (original geoms)" : geo_json_2720fdbab9706987238be22d2fe5c965,\n", - " "stroke nodes" : geo_json_96ba73f68b6eca55841fc8af743be14f,\n", - " "connectivity" : geo_json_314a8206345634f725139c172aa569b7,\n", - " "degree" : geo_json_47fdf3d5e9a95b87f34b8727f476dd52,\n", - " "betweenness_centrality" : geo_json_a28d71e4798ccee310a0cf9b8847de6b,\n", - " "closeness_centrality" : geo_json_a39eb37451599e55cfacd6652675c360,\n", - " "access" : geo_json_64b3815c09e2dbe740214783b790d60a,\n", - " "length" : geo_json_b3234c99aa829a72a054d90be27a0857,\n", - " "spacing" : geo_json_1c9e043f9bc1179ca5f274defa59f1f8,\n", - " "orthogonality" : geo_json_b2d82c616ee323d67d892158207fd010,\n", - " "Stroke graph edges" : geo_json_deb953d739b64b76bb825be27a3a6ce3,\n", + " "strokes (original geoms)" : geo_json_5482c750e99258c086f171fa50bafc6f,\n", + " "stroke nodes" : geo_json_9d2a29810a8d4b480c6c12e18c313252,\n", + " "connectivity" : geo_json_481737a213be0aa700f931fc8dd15604,\n", + " "degree" : geo_json_9c78f93b691003eecb71f5126e78fb84,\n", + " "betweenness_centrality" : geo_json_ca2557cc267ed2f39f50c77e77076e42,\n", + " "closeness_centrality" : geo_json_0ad2bf043f957b751909041ebe7b5911,\n", + " "access" : geo_json_4af52d7389933299665d2f2960fc41fc,\n", + " "length" : geo_json_c41967b3da0880b89a03ffd072dc60d5,\n", + " "spacing" : geo_json_714504b95353607487f4ed6bbeddf108,\n", + " "orthogonality" : geo_json_8358d0f07ce27fc26a87ccc9b0e669c2,\n", + " "Stroke graph edges" : geo_json_3bae834d70b206d6895733d867917003,\n", " },\n", " };\n", - " let layer_control_81f8dcf895027c0e8fafe34e17f7ae37 = L.control.layers(\n", - " layer_control_81f8dcf895027c0e8fafe34e17f7ae37_layers.base_layers,\n", - " layer_control_81f8dcf895027c0e8fafe34e17f7ae37_layers.overlays,\n", - " {"autoZIndex": true, "collapsed": true, "position": "topright"}\n", - " ).addTo(map_8ca6d4b422ea6a8d8211d16b437c30ec);\n", + " let layer_control_10e0ab329f07016f75f12f283eced67e = L.control.layers(\n", + " layer_control_10e0ab329f07016f75f12f283eced67e_layers.base_layers,\n", + " layer_control_10e0ab329f07016f75f12f283eced67e_layers.overlays,\n", + " {\n", + " "position": "topright",\n", + " "collapsed": true,\n", + " "autoZIndex": true,\n", + "}\n", + " ).addTo(map_d5ae5f635c60ec2e2d6972df2e6bd9fb);\n", "\n", " \n", "</script>\n", "</html>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen>" ], "text/plain": [ - "" + "" ] }, - "execution_count": 20, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -4007,7 +4132,7 @@ ], "metadata": { "kernelspec": { - "display_name": "simplification", + "display_name": "momepy_dev", "language": "python", "name": "python3" }, @@ -4021,7 +4146,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.12.10" } }, "nbformat": 4, diff --git a/momepy/strokegraph_clse.ipynb b/momepy/strokegraph_clse.ipynb index 28553eb1..8136c362 100644 --- a/momepy/strokegraph_clse.ipynb +++ b/momepy/strokegraph_clse.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 110, "metadata": {}, "outputs": [], "source": [ @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 111, "metadata": {}, "outputs": [], "source": [ @@ -35,7 +35,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 112, "metadata": {}, "outputs": [], "source": [ @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 113, "metadata": {}, "outputs": [], "source": [ @@ -74,11 +74,44 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 114, "metadata": {}, "outputs": [ { "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "object", + "type": "string" + }, + { + "name": "0", + "rawType": "object", + "type": "unknown" + } + ], + "ref": "c36ef621-3a0c-42bc-9e3e-27d59609b574", + "rows": [ + [ + "n_segments", + "8" + ], + [ + "geometry", + "LINESTRING (1603278.8993584276 6463669.185595578, 1603283.7306243288 6463690.028353462, 1603314.4436718386 6463822.409720818, 1603317.7832565615 6463836.796863219, 1603361.0308787343 6464021.107210826, 1603363.557831175 6464031.88480676, 1603376.5042879563 6464085.530021086, 1603413.2063240695 6464228.730248732, 1603585.6402153103 6464428.773867372)" + ], + [ + "edge_ids", + "[ 0 3 15 27]" + ] + ], + "shape": { + "columns": 1, + "rows": 3 + } + }, "text/plain": [ "n_segments 8\n", "geometry LINESTRING (1603278.8993584276 6463669.1855955...\n", @@ -86,7 +119,7 @@ "Name: 0, dtype: object" ] }, - "execution_count": 5, + "execution_count": 114, "metadata": {}, "output_type": "execute_result" } @@ -97,12 +130,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 115, "metadata": {}, "outputs": [], "source": [ "def find_geom(linestring, point):\n", - " if point == linestring.coords[0]:\n", + " if point == list(linestring.coords[0]):\n", " geom = [np.array(val) for val in linestring.coords[:2]]\n", " else:\n", " geom = [np.array(val) for val in linestring.coords[-2:]]\n", @@ -111,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 116, "metadata": {}, "outputs": [], "source": [ @@ -124,7 +157,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 117, "metadata": {}, "outputs": [], "source": [ @@ -173,7 +206,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 118, "metadata": {}, "outputs": [], "source": [ @@ -197,7 +230,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 119, "metadata": {}, "outputs": [], "source": [ @@ -215,14 +248,14 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 120, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/66/3jkth_7d5gggg6pyr8yywwt40000gn/T/ipykernel_90883/2550495861.py:5: UserWarning: Approach is not set. Defaulting to 'primal'.\n", + "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_53570/2550495861.py:5: UserWarning: Approach is not set. Defaulting to 'primal'.\n", " points_stroke, lines_stroke = momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n" ] }, @@ -256,7 +289,7 @@ " <meta name="viewport" content="width=device-width,\n", " initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />\n", " <style>\n", - " #map_13bf1525072211457537cdb8347a311f {\n", + " #map_f485c7cefc845a343e7d2e56682f6348 {\n", " position: relative;\n", " width: 100.0%;\n", " height: 100.0%;\n", @@ -351,44 +384,58 @@ "<body>\n", " \n", " \n", - " <div class="folium-map" id="map_13bf1525072211457537cdb8347a311f" ></div>\n", + " <div class="folium-map" id="map_f485c7cefc845a343e7d2e56682f6348" ></div>\n", " \n", "</body>\n", "<script>\n", " \n", " \n", - " var map_13bf1525072211457537cdb8347a311f = L.map(\n", - " "map_13bf1525072211457537cdb8347a311f",\n", + " var map_f485c7cefc845a343e7d2e56682f6348 = L.map(\n", + " "map_f485c7cefc845a343e7d2e56682f6348",\n", " {\n", " center: [50.102935750000015, 14.403062600000004],\n", " crs: L.CRS.EPSG3857,\n", - " zoom: 10,\n", - " zoomControl: true,\n", - " preferCanvas: false,\n", + " ...{\n", + " "zoom": 10,\n", + " "zoomControl": true,\n", + " "preferCanvas": false,\n", + "}\n", + "\n", " }\n", " );\n", - " L.control.scale().addTo(map_13bf1525072211457537cdb8347a311f);\n", + " L.control.scale().addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", "\n", " \n", "\n", " \n", " \n", - " var tile_layer_9ba2d90e4c000d6f2acabb17da236daf = L.tileLayer(\n", + " var tile_layer_75a780ad99b6f7bd559c3dfd418bd85f = L.tileLayer(\n", " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",\n", - " {"attribution": "\\u0026copy; \\u003ca href=\\"https://www.openstreetmap.org/copyright\\"\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\"https://carto.com/attributions\\"\\u003eCARTO\\u003c/a\\u003e", "detectRetina": false, "maxZoom": 20, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}\n", + " {\n", + " "minZoom": 0,\n", + " "maxZoom": 20,\n", + " "maxNativeZoom": 20,\n", + " "noWrap": false,\n", + " "attribution": "\\u0026copy; \\u003ca href=\\"https://www.openstreetmap.org/copyright\\"\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\"https://carto.com/attributions\\"\\u003eCARTO\\u003c/a\\u003e",\n", + " "subdomains": "abc",\n", + " "detectRetina": false,\n", + " "tms": false,\n", + " "opacity": 1,\n", + "}\n", + "\n", " );\n", " \n", " \n", - " tile_layer_9ba2d90e4c000d6f2acabb17da236daf.addTo(map_13bf1525072211457537cdb8347a311f);\n", + " tile_layer_75a780ad99b6f7bd559c3dfd418bd85f.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", " \n", " \n", - " map_13bf1525072211457537cdb8347a311f.fitBounds(\n", + " map_f485c7cefc845a343e7d2e56682f6348.fitBounds(\n", " [[50.10007700000001, 14.398981599999999], [50.10579450000001, 14.407143600000008]],\n", " {}\n", " );\n", " \n", " \n", - " function geo_json_0e649b76f5226724814454416d8e5c0b_styler(feature) {\n", + " function geo_json_a75521f1f7e4c097815fc719c81c67c1_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#1f77b4", "fillColor": "#1f77b4", "fillOpacity": 0.5, "weight": 2};\n", @@ -412,52 +459,54 @@ " return {"color": "#17becf", "fillColor": "#17becf", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_0e649b76f5226724814454416d8e5c0b_highlighter(feature) {\n", + " function geo_json_a75521f1f7e4c097815fc719c81c67c1_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_0e649b76f5226724814454416d8e5c0b_pointToLayer(feature, latlng) {\n", + " function geo_json_a75521f1f7e4c097815fc719c81c67c1_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_0e649b76f5226724814454416d8e5c0b_styler(feature)\n", + " let style = geo_json_a75521f1f7e4c097815fc719c81c67c1_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_0e649b76f5226724814454416d8e5c0b_onEachFeature(feature, layer) {\n", + " function geo_json_a75521f1f7e4c097815fc719c81c67c1_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_0e649b76f5226724814454416d8e5c0b.resetStyle(e.target);\n", + " geo_json_a75521f1f7e4c097815fc719c81c67c1.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_0e649b76f5226724814454416d8e5c0b_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_a75521f1f7e4c097815fc719c81c67c1_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_0e649b76f5226724814454416d8e5c0b = L.geoJson(null, {\n", - " onEachFeature: geo_json_0e649b76f5226724814454416d8e5c0b_onEachFeature,\n", + " var geo_json_a75521f1f7e4c097815fc719c81c67c1 = L.geoJson(null, {\n", + " onEachFeature: geo_json_a75521f1f7e4c097815fc719c81c67c1_onEachFeature,\n", " \n", - " style: geo_json_0e649b76f5226724814454416d8e5c0b_styler,\n", - " pointToLayer: geo_json_0e649b76f5226724814454416d8e5c0b_pointToLayer,\n", + " style: geo_json_a75521f1f7e4c097815fc719c81c67c1_styler,\n", + " pointToLayer: geo_json_a75521f1f7e4c097815fc719c81c67c1_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_0e649b76f5226724814454416d8e5c0b_add (data) {\n", - " geo_json_0e649b76f5226724814454416d8e5c0b\n", + " function geo_json_a75521f1f7e4c097815fc719c81c67c1_add (data) {\n", + " geo_json_a75521f1f7e4c097815fc719c81c67c1\n", " .addData(data);\n", " }\n", - " geo_json_0e649b76f5226724814454416d8e5c0b_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#1f77b4", "edge_ids": "[ 0 3 15 27]", "id": 0, "n_segments": 8, "stroke_group": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ff7f0e", "edge_ids": "[ 1 12 14 25]", "id": 1, "n_segments": 19, "stroke_group": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#2ca02c", "edge_ids": "[ 2 11 28 30]", "id": 2, "n_segments": 17, "stroke_group": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#d62728", "edge_ids": "[4 5 6]", "id": 3, "n_segments": 5, "stroke_group": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#9467bd", "edge_ids": "[ 7 8 9 13 21 22 24]", "id": 4, "n_segments": 14, "stroke_group": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#8c564b", "edge_ids": "[10]", "id": 5, "n_segments": 2, "stroke_group": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e377c2", "edge_ids": "[16 17 18 23 29]", "id": 6, "n_segments": 13, "stroke_group": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#7f7f7f", "edge_ids": "[19]", "id": 7, "n_segments": 3, "stroke_group": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#bcbd22", "edge_ids": "[20]", "id": 8, "n_segments": 3, "stroke_group": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#17becf", "edge_ids": "[26]", "id": 9, "n_segments": 5, "stroke_group": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_a75521f1f7e4c097815fc719c81c67c1_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#1f77b4", "edge_ids": "[ 0 3 15 27]", "id": 0, "n_segments": 8, "stroke_group": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ff7f0e", "edge_ids": "[ 1 12 14 25]", "id": 1, "n_segments": 19, "stroke_group": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#2ca02c", "edge_ids": "[ 2 11 28 30]", "id": 2, "n_segments": 17, "stroke_group": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#d62728", "edge_ids": "[4 5 6]", "id": 3, "n_segments": 5, "stroke_group": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#9467bd", "edge_ids": "[ 7 8 9 13 21 22 24]", "id": 4, "n_segments": 14, "stroke_group": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#8c564b", "edge_ids": "[10]", "id": 5, "n_segments": 2, "stroke_group": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e377c2", "edge_ids": "[16 17 18 23 29]", "id": 6, "n_segments": 13, "stroke_group": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#7f7f7f", "edge_ids": "[19]", "id": 7, "n_segments": 3, "stroke_group": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#bcbd22", "edge_ids": "[20]", "id": 8, "n_segments": 3, "stroke_group": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#17becf", "edge_ids": "[26]", "id": 9, "n_segments": 5, "stroke_group": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_0e649b76f5226724814454416d8e5c0b.bindTooltip(\n", + " geo_json_a75521f1f7e4c097815fc719c81c67c1.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -478,48 +527,52 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_0e649b76f5226724814454416d8e5c0b.addTo(map_13bf1525072211457537cdb8347a311f);\n", + " geo_json_a75521f1f7e4c097815fc719c81c67c1.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", " \n", " \n", - " var color_map_11e795464feb0c44ca46c6681c4b269e = {};\n", + " var color_map_bfea797b9645266490881d1e7e916cb4 = {};\n", "\n", " \n", - " color_map_11e795464feb0c44ca46c6681c4b269e.color = d3.scale.threshold()\n", + " color_map_bfea797b9645266490881d1e7e916cb4.color = d3.scale.threshold()\n", " .domain([0.0, 0.018036072144288578, 0.036072144288577156, 0.05410821643286573, 0.07214428857715431, 0.09018036072144289, 0.10821643286573146, 0.12625250501002003, 0.14428857715430862, 0.1623246492985972, 0.18036072144288579, 0.19839679358717435, 0.21643286573146292, 0.23446893787575152, 0.25250501002004005, 0.27054108216432865, 0.28857715430861725, 0.3066132264529058, 0.3246492985971944, 0.342685370741483, 0.36072144288577157, 0.3787575150300601, 0.3967935871743487, 0.4148296593186373, 0.43286573146292584, 0.45090180360721444, 0.46893787575150303, 0.48697394789579157, 0.5050100200400801, 0.5230460921843687, 0.5410821643286573, 0.5591182364729459, 0.5771543086172345, 0.5951903807615231, 0.6132264529058116, 0.6312625250501002, 0.6492985971943888, 0.6673346693386774, 0.685370741482966, 0.7034068136272545, 0.7214428857715431, 0.7394789579158316, 0.7575150300601202, 0.7755511022044088, 0.7935871743486974, 0.811623246492986, 0.8296593186372746, 0.8476953907815631, 0.8657314629258517, 0.8837675350701403, 0.9018036072144289, 0.9198396793587175, 0.9378757515030061, 0.9559118236472945, 0.9739478957915831, 0.9919839679358717, 1.0100200400801602, 1.028056112224449, 1.0460921843687374, 1.0641282565130261, 1.0821643286573146, 1.1002004008016033, 1.1182364729458918, 1.1362725450901803, 1.154308617234469, 1.1723446893787575, 1.1903807615230462, 1.2084168336673347, 1.2264529058116231, 1.2444889779559118, 1.2625250501002003, 1.280561122244489, 1.2985971943887775, 1.3166332665330662, 1.3346693386773547, 1.3527054108216432, 1.370741482965932, 1.3887775551102204, 1.406813627254509, 1.4248496993987976, 1.4428857715430863, 1.4609218436873748, 1.4789579158316633, 1.496993987975952, 1.5150300601202404, 1.5330661322645291, 1.5511022044088176, 1.5691382765531061, 1.5871743486973948, 1.6052104208416833, 1.623246492985972, 1.6412825651302605, 1.6593186372745492, 1.6773547094188377, 1.6953907815631262, 1.7134268537074149, 1.7314629258517034, 1.749498997995992, 1.7675350701402806, 1.785571142284569, 1.8036072144288577, 1.8216432865731462, 1.839679358717435, 1.8577154308617234, 1.8757515030060121, 1.8937875751503006, 1.911823647294589, 1.9298597194388778, 1.9478957915831663, 1.965931863727455, 1.9839679358717435, 2.002004008016032, 2.0200400801603204, 2.038076152304609, 2.056112224448898, 2.0741482965931866, 2.092184368737475, 2.1102204408817635, 2.1282565130260522, 2.1462925851703405, 2.164328657314629, 2.182364729458918, 2.2004008016032066, 2.218436873747495, 2.2364729458917836, 2.2545090180360723, 2.2725450901803605, 2.2905811623246493, 2.308617234468938, 2.3266533066132267, 2.344689378757515, 2.3627254509018036, 2.3807615230460923, 2.3987975951903806, 2.4168336673346693, 2.434869739478958, 2.4529058116232463, 2.470941883767535, 2.4889779559118237, 2.5070140280561124, 2.5250501002004007, 2.5430861723446894, 2.561122244488978, 2.5791583166332663, 2.597194388777555, 2.6152304609218437, 2.6332665330661325, 2.6513026052104207, 2.6693386773547094, 2.687374749498998, 2.7054108216432864, 2.723446893787575, 2.741482965931864, 2.7595190380761525, 2.7775551102204408, 2.7955911823647295, 2.813627254509018, 2.8316633266533064, 2.849699398797595, 2.867735470941884, 2.8857715430861726, 2.903807615230461, 2.9218436873747495, 2.9398797595190382, 2.9579158316633265, 2.975951903807615, 2.993987975951904, 3.012024048096192, 3.030060120240481, 3.0480961923847696, 3.0661322645290583, 3.0841683366733466, 3.1022044088176353, 3.120240480961924, 3.1382765531062122, 3.156312625250501, 3.1743486973947896, 3.1923847695390783, 3.2104208416833666, 3.2284569138276553, 3.246492985971944, 3.2645290581162323, 3.282565130260521, 3.3006012024048097, 3.3186372745490984, 3.3366733466933867, 3.3547094188376754, 3.372745490981964, 3.3907815631262523, 3.408817635270541, 3.4268537074148298, 3.444889779559118, 3.4629258517034067, 3.4809619238476954, 3.498997995991984, 3.5170340681362724, 3.535070140280561, 3.55310621242485, 3.571142284569138, 3.5891783567134268, 3.6072144288577155, 3.625250501002004, 3.6432865731462925, 3.661322645290581, 3.67935871743487, 3.697394789579158, 3.715430861723447, 3.7334669338677355, 3.7515030060120242, 3.7695390781563125, 3.787575150300601, 3.80561122244489, 3.823647294589178, 3.841683366733467, 3.8597194388777556, 3.8777555110220443, 3.8957915831663326, 3.9138276553106213, 3.93186372745491, 3.9498997995991982, 3.967935871743487, 3.9859719438877756, 4.004008016032064, 4.022044088176353, 4.040080160320641, 4.05811623246493, 4.076152304609218, 4.094188376753507, 4.112224448897796, 4.130260521042084, 4.148296593186373, 4.166332665330661, 4.18436873747495, 4.202404809619239, 4.220440881763527, 4.238476953907815, 4.2565130260521045, 4.274549098196393, 4.292585170340681, 4.31062124248497, 4.328657314629258, 4.346693386773547, 4.364729458917836, 4.382765531062124, 4.400801603206413, 4.4188376753507015, 4.43687374749499, 4.454909819639279, 4.472945891783567, 4.490981963927855, 4.509018036072145, 4.527054108216433, 4.545090180360721, 4.56312625250501, 4.5811623246492985, 4.599198396793587, 4.617234468937876, 4.635270541082164, 4.653306613226453, 4.671342685370742, 4.68937875751503, 4.707414829659319, 4.725450901803607, 4.7434869739478955, 4.761523046092185, 4.779559118236473, 4.797595190380761, 4.81563126252505, 4.833667334669339, 4.851703406813627, 4.869739478957916, 4.887775551102204, 4.905811623246493, 4.923847695390782, 4.94188376753507, 4.959919839679359, 4.977955911823647, 4.995991983967936, 5.014028056112225, 5.032064128256513, 5.050100200400801, 5.0681362725450905, 5.086172344689379, 5.104208416833667, 5.122244488977956, 5.140280561122244, 5.158316633266533, 5.176352705410822, 5.19438877755511, 5.212424849699399, 5.2304609218436875, 5.248496993987976, 5.266533066132265, 5.284569138276553, 5.302605210420841, 5.320641282565131, 5.338677354709419, 5.356713426853707, 5.374749498997996, 5.3927855711422845, 5.410821643286573, 5.428857715430862, 5.44689378757515, 5.4649298597194385, 5.482965931863728, 5.501002004008016, 5.519038076152305, 5.537074148296593, 5.5551102204408815, 5.573146292585171, 5.591182364729459, 5.609218436873747, 5.627254509018036, 5.645290581162325, 5.663326653306613, 5.681362725450902, 5.69939879759519, 5.717434869739479, 5.735470941883768, 5.753507014028056, 5.771543086172345, 5.789579158316633, 5.807615230460922, 5.825651302605211, 5.843687374749499, 5.861723446893787, 5.8797595190380765, 5.897795591182365, 5.915831663326653, 5.933867735470942, 5.95190380761523, 5.969939879759519, 5.987975951903808, 6.006012024048096, 6.024048096192384, 6.0420841683366735, 6.060120240480962, 6.078156312625251, 6.096192384769539, 6.114228456913827, 6.132264529058117, 6.150300601202405, 6.168336673346693, 6.186372745490982, 6.2044088176352705, 6.222444889779559, 6.240480961923848, 6.258517034068136, 6.2765531062124245, 6.294589178356714, 6.312625250501002, 6.330661322645291, 6.348697394789579, 6.3667334669338675, 6.384769539078157, 6.402805611222445, 6.420841683366733, 6.438877755511022, 6.456913827655311, 6.474949899799599, 6.492985971943888, 6.511022044088176, 6.529058116232465, 6.547094188376754, 6.565130260521042, 6.58316633266533, 6.601202404809619, 6.619238476953908, 6.637274549098197, 6.655310621242485, 6.673346693386773, 6.6913827655310625, 6.709418837675351, 6.727454909819639, 6.745490981963928, 6.763527054108216, 6.781563126252505, 6.799599198396794, 6.817635270541082, 6.83567134268537, 6.8537074148296595, 6.871743486973948, 6.889779559118236, 6.907815631262525, 6.925851703406813, 6.943887775551103, 6.961923847695391, 6.979959919839679, 6.997995991983968, 7.0160320641282565, 7.034068136272545, 7.052104208416834, 7.070140280561122, 7.0881763527054105, 7.1062124248497, 7.124248496993988, 7.142284569138276, 7.160320641282565, 7.1783567134268536, 7.196392785571143, 7.214428857715431, 7.232464929859719, 7.250501002004008, 7.268537074148297, 7.286573146292585, 7.304609218436874, 7.322645290581162, 7.340681362725451, 7.35871743486974, 7.376753507014028, 7.394789579158316, 7.412825651302605, 7.430861723446894, 7.448897795591182, 7.466933867735471, 7.484969939879759, 7.5030060120240485, 7.521042084168337, 7.539078156312625, 7.557114228456914, 7.575150300601202, 7.593186372745491, 7.61122244488978, 7.629258517034068, 7.647294589178356, 7.6653306613226455, 7.683366733466934, 7.701402805611222, 7.719438877755511, 7.7374749498997994, 7.755511022044089, 7.773547094188377, 7.791583166332665, 7.809619238476954, 7.8276553106212425, 7.845691382765531, 7.86372745490982, 7.881763527054108, 7.8997995991983965, 7.917835671342686, 7.935871743486974, 7.953907815631262, 7.971943887775551, 7.98997995991984, 8.008016032064129, 8.026052104208416, 8.044088176352705, 8.062124248496994, 8.080160320641282, 8.098196392785571, 8.11623246492986, 8.134268537074147, 8.152304609218437, 8.170340681362726, 8.188376753507015, 8.206412825651302, 8.224448897795591, 8.24248496993988, 8.260521042084168, 8.278557114228457, 8.296593186372746, 8.314629258517034, 8.332665330661323, 8.350701402805612, 8.3687374749499, 8.386773547094188, 8.404809619238478, 8.422845691382765, 8.440881763527054, 8.458917835671343, 8.47695390781563, 8.49498997995992, 8.513026052104209, 8.531062124248496, 8.549098196392785, 8.567134268537075, 8.585170340681362, 8.603206412825651, 8.62124248496994, 8.639278557114228, 8.657314629258517, 8.675350701402806, 8.693386773547093, 8.711422845691382, 8.729458917835672, 8.74749498997996, 8.765531062124248, 8.783567134268537, 8.801603206412826, 8.819639278557114, 8.837675350701403, 8.855711422845692, 8.87374749498998, 8.891783567134269, 8.909819639278558, 8.927855711422845, 8.945891783567134, 8.963927855711423, 8.98196392785571, 9.0])\n", " .range(['#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff']);\n", " \n", "\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.x = d3.scale.linear()\n", + " color_map_bfea797b9645266490881d1e7e916cb4.x = d3.scale.linear()\n", " .domain([0.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.legend = L.control({position: 'topright'});\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.legend.addTo(map_13bf1525072211457537cdb8347a311f);\n", + " color_map_bfea797b9645266490881d1e7e916cb4.legend = L.control({position: 'topright'});\n", + " color_map_bfea797b9645266490881d1e7e916cb4.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_bfea797b9645266490881d1e7e916cb4.legend.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", "\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.xAxis = d3.svg.axis()\n", - " .scale(color_map_11e795464feb0c44ca46c6681c4b269e.x)\n", + " color_map_bfea797b9645266490881d1e7e916cb4.xAxis = d3.svg.axis()\n", + " .scale(color_map_bfea797b9645266490881d1e7e916cb4.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', 1.8, '', 3.6, '', 5.4, '', 7.2, '', 9.0, '']);\n", "\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_bfea797b9645266490881d1e7e916cb4.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.g = color_map_11e795464feb0c44ca46c6681c4b269e.svg.append("g")\n", + " color_map_bfea797b9645266490881d1e7e916cb4.g = color_map_bfea797b9645266490881d1e7e916cb4.svg.append("g")\n", " .attr("class", "key")\n", + " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.g.selectAll("rect")\n", - " .data(color_map_11e795464feb0c44ca46c6681c4b269e.color.range().map(function(d, i) {\n", + " color_map_bfea797b9645266490881d1e7e916cb4.g.selectAll("rect")\n", + " .data(color_map_bfea797b9645266490881d1e7e916cb4.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_11e795464feb0c44ca46c6681c4b269e.x(color_map_11e795464feb0c44ca46c6681c4b269e.color.domain()[i - 1]) : color_map_11e795464feb0c44ca46c6681c4b269e.x.range()[0],\n", - " x1: i < color_map_11e795464feb0c44ca46c6681c4b269e.color.domain().length ? color_map_11e795464feb0c44ca46c6681c4b269e.x(color_map_11e795464feb0c44ca46c6681c4b269e.color.domain()[i]) : color_map_11e795464feb0c44ca46c6681c4b269e.x.range()[1],\n", + " x0: i ? color_map_bfea797b9645266490881d1e7e916cb4.x(color_map_bfea797b9645266490881d1e7e916cb4.color.domain()[i - 1]) : color_map_bfea797b9645266490881d1e7e916cb4.x.range()[0],\n", + " x1: i < color_map_bfea797b9645266490881d1e7e916cb4.color.domain().length ? color_map_bfea797b9645266490881d1e7e916cb4.x(color_map_bfea797b9645266490881d1e7e916cb4.color.domain()[i]) : color_map_bfea797b9645266490881d1e7e916cb4.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -529,63 +582,66 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_11e795464feb0c44ca46c6681c4b269e.g.call(color_map_11e795464feb0c44ca46c6681c4b269e.xAxis).append("text")\n", + " color_map_bfea797b9645266490881d1e7e916cb4.g.call(color_map_bfea797b9645266490881d1e7e916cb4.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", + " .attr("fill", "black")\n", " .text("id");\n", " \n", - " function geo_json_cccc1bf1afbaa9c092bad04f46deb323_styler(feature) {\n", + " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_cccc1bf1afbaa9c092bad04f46deb323_highlighter(feature) {\n", + " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_cccc1bf1afbaa9c092bad04f46deb323_pointToLayer(feature, latlng) {\n", + " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_cccc1bf1afbaa9c092bad04f46deb323_styler(feature)\n", + " let style = geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_cccc1bf1afbaa9c092bad04f46deb323_onEachFeature(feature, layer) {\n", + " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_cccc1bf1afbaa9c092bad04f46deb323.resetStyle(e.target);\n", + " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_cccc1bf1afbaa9c092bad04f46deb323_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_cccc1bf1afbaa9c092bad04f46deb323 = L.geoJson(null, {\n", - " onEachFeature: geo_json_cccc1bf1afbaa9c092bad04f46deb323_onEachFeature,\n", + " var geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf = L.geoJson(null, {\n", + " onEachFeature: geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_onEachFeature,\n", " \n", - " style: geo_json_cccc1bf1afbaa9c092bad04f46deb323_styler,\n", - " pointToLayer: geo_json_cccc1bf1afbaa9c092bad04f46deb323_pointToLayer,\n", + " style: geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_styler,\n", + " pointToLayer: geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_cccc1bf1afbaa9c092bad04f46deb323_add (data) {\n", - " geo_json_cccc1bf1afbaa9c092bad04f46deb323\n", + " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_add (data) {\n", + " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf\n", " .addData(data);\n", " }\n", - " geo_json_cccc1bf1afbaa9c092bad04f46deb323_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.40525490000001, 50.1047055, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [14.40525490000001, 50.1047055], "type": "Point"}, "id": "0", "properties": {"nodeID": 0, "x": 1603585.6402153103, "y": 6464428.773867372}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.1035529, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [14.403705899999995, 50.1035529], "type": "Point"}, "id": "1", "properties": {"nodeID": 1, "x": 1603413.2063240695, "y": 6464228.730248732}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10258519999999, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [14.402405999999988, 50.10258519999999], "type": "Point"}, "id": "2", "properties": {"nodeID": 2, "x": 1603268.502117987, "y": 6464060.781328565}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [14.403259899999986, 50.10241870000001], "type": "Point"}, "id": "3", "properties": {"nodeID": 3, "x": 1603363.557831175, "y": 6464031.88480676}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [14.405449500000003, 50.10328279999999], "type": "Point"}, "id": "4", "properties": {"nodeID": 4, "x": 1603607.3029882177, "y": 6464181.852772597}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [14.402032799999994, 50.10315780000001], "type": "Point"}, "id": "5", "properties": {"nodeID": 5, "x": 1603226.9576840235, "y": 6464160.158361825}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [14.400352999999992, 50.102739099999994], "type": "Point"}, "id": "6", "properties": {"nodeID": 6, "x": 1603039.9632033885, "y": 6464087.491175889}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.398981599999999, 50.1024077], "geometry": {"coordinates": [14.398981599999999, 50.1024077], "type": "Point"}, "id": "7", "properties": {"nodeID": 7, "x": 1602887.2996537155, "y": 6464029.975730775}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.103779500000016, 14.39972789999999, 50.103779500000016], "geometry": {"coordinates": [14.39972789999999, 50.103779500000016], "type": "Point"}, "id": "8", "properties": {"nodeID": 8, "x": 1602970.3773896934, "y": 6464268.058242684}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.102068500000016, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [14.400807100000003, 50.102068500000016], "type": "Point"}, "id": "9", "properties": {"nodeID": 9, "x": 1603090.513384159, "y": 6463971.106984773}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [14.402848699999991, 50.101294599999996], "type": "Point"}, "id": "10", "properties": {"nodeID": 10, "x": 1603317.7832565615, "y": 6463836.796863219}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.10149909999998, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [14.401812000000007, 50.10149909999998], "type": "Point"}, "id": "11", "properties": {"nodeID": 11, "x": 1603202.3783404578, "y": 6463872.287568242}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.400640399999995, 50.100679099999994], "geometry": {"coordinates": [14.400640399999995, 50.100679099999994], "type": "Point"}, "id": "12", "properties": {"nodeID": 12, "x": 1603071.956425043, "y": 6463729.978565}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [14.405837099999994, 50.10435879999999], "type": "Point"}, "id": "13", "properties": {"nodeID": 13, "x": 1603650.450422848, "y": 6464368.600601688}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [14.404608199999993, 50.10102239999999], "type": "Point"}, "id": "14", "properties": {"nodeID": 14, "x": 1603513.6499006122, "y": 6463789.557147608}, "type": "Feature"}, {"bbox": [14.407143600000008, 50.10099869999999, 14.407143600000008, 50.10099869999999], "geometry": {"coordinates": [14.407143600000008, 50.10099869999999], "type": "Point"}, "id": "15", "properties": {"nodeID": 15, "x": 1603795.889337571, "y": 6463785.444077063}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [14.405011000000012, 50.1021532], "type": "Point"}, "id": "16", "properties": {"nodeID": 16, "x": 1603558.489391506, "y": 6463985.80677705}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.399633600000007, 50.10131139999999], "geometry": {"coordinates": [14.399633600000007, 50.10131139999999], "type": "Point"}, "id": "17", "properties": {"nodeID": 17, "x": 1602959.8799617135, "y": 6463839.712475327}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.401311799999997, 50.101800699999984], "geometry": {"coordinates": [14.401311799999997, 50.101800699999984], "type": "Point"}, "id": "18", "properties": {"nodeID": 18, "x": 1603146.6963311615, "y": 6463924.630126579}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404248800000007, 50.10007700000001], "geometry": {"coordinates": [14.404248800000007, 50.10007700000001], "type": "Point"}, "id": "19", "properties": {"nodeID": 19, "x": 1603473.6416756227, "y": 6463625.487127112}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1049737, 14.400690199999993, 50.1049737], "geometry": {"coordinates": [14.400690199999993, 50.1049737], "type": "Point"}, "id": "20", "properties": {"nodeID": 20, "x": 1603077.5001356844, "y": 6464475.322968743}, "type": "Feature"}, {"bbox": [14.402574900000001, 50.105621199999995, 14.402574900000001, 50.105621199999995], "geometry": {"coordinates": [14.402574900000001, 50.105621199999995], "type": "Point"}, "id": "21", "properties": {"nodeID": 21, "x": 1603287.303979983, "y": 6464587.704889874}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402499399999995, 50.100328799999986], "geometry": {"coordinates": [14.402499399999995, 50.100328799999986], "type": "Point"}, "id": "22", "properties": {"nodeID": 22, "x": 1603278.8993584276, "y": 6463669.185595578}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1054507, 14.404819700000001, 50.1054507], "geometry": {"coordinates": [14.404819700000001, 50.1054507], "type": "Point"}, "id": "23", "properties": {"nodeID": 23, "x": 1603537.1939729159, "y": 6464558.11228298}, "type": "Feature"}, {"bbox": [14.406339600000006, 50.10579450000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [14.406339600000006, 50.10579450000001], "type": "Point"}, "id": "24", "properties": {"nodeID": 24, "x": 1603706.3884669733, "y": 6464617.783583014}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.40525490000001, 50.1047055, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [14.40525490000001, 50.1047055], "type": "Point"}, "id": "0", "properties": {"nodeID": 0, "x": 1603585.6402153103, "y": 6464428.773867372}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.1035529, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [14.403705899999995, 50.1035529], "type": "Point"}, "id": "1", "properties": {"nodeID": 1, "x": 1603413.2063240695, "y": 6464228.730248732}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10258519999999, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [14.402405999999988, 50.10258519999999], "type": "Point"}, "id": "2", "properties": {"nodeID": 2, "x": 1603268.502117987, "y": 6464060.781328565}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [14.403259899999986, 50.10241870000001], "type": "Point"}, "id": "3", "properties": {"nodeID": 3, "x": 1603363.557831175, "y": 6464031.88480676}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [14.405449500000003, 50.10328279999999], "type": "Point"}, "id": "4", "properties": {"nodeID": 4, "x": 1603607.3029882177, "y": 6464181.852772597}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [14.402032799999994, 50.10315780000001], "type": "Point"}, "id": "5", "properties": {"nodeID": 5, "x": 1603226.9576840235, "y": 6464160.158361825}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [14.400352999999992, 50.102739099999994], "type": "Point"}, "id": "6", "properties": {"nodeID": 6, "x": 1603039.9632033885, "y": 6464087.491175889}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.398981599999999, 50.1024077], "geometry": {"coordinates": [14.398981599999999, 50.1024077], "type": "Point"}, "id": "7", "properties": {"nodeID": 7, "x": 1602887.2996537155, "y": 6464029.975730775}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.103779500000016, 14.39972789999999, 50.103779500000016], "geometry": {"coordinates": [14.39972789999999, 50.103779500000016], "type": "Point"}, "id": "8", "properties": {"nodeID": 8, "x": 1602970.3773896934, "y": 6464268.058242684}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.102068500000016, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [14.400807100000003, 50.102068500000016], "type": "Point"}, "id": "9", "properties": {"nodeID": 9, "x": 1603090.513384159, "y": 6463971.106984773}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [14.402848699999991, 50.101294599999996], "type": "Point"}, "id": "10", "properties": {"nodeID": 10, "x": 1603317.7832565615, "y": 6463836.796863219}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.10149909999998, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [14.401812000000007, 50.10149909999998], "type": "Point"}, "id": "11", "properties": {"nodeID": 11, "x": 1603202.3783404578, "y": 6463872.287568242}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.400640399999995, 50.100679099999994], "geometry": {"coordinates": [14.400640399999995, 50.100679099999994], "type": "Point"}, "id": "12", "properties": {"nodeID": 12, "x": 1603071.956425043, "y": 6463729.978565}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [14.405837099999994, 50.10435879999999], "type": "Point"}, "id": "13", "properties": {"nodeID": 13, "x": 1603650.450422848, "y": 6464368.600601688}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [14.404608199999993, 50.10102239999999], "type": "Point"}, "id": "14", "properties": {"nodeID": 14, "x": 1603513.6499006122, "y": 6463789.557147608}, "type": "Feature"}, {"bbox": [14.407143600000008, 50.10099869999999, 14.407143600000008, 50.10099869999999], "geometry": {"coordinates": [14.407143600000008, 50.10099869999999], "type": "Point"}, "id": "15", "properties": {"nodeID": 15, "x": 1603795.889337571, "y": 6463785.444077063}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [14.405011000000012, 50.1021532], "type": "Point"}, "id": "16", "properties": {"nodeID": 16, "x": 1603558.489391506, "y": 6463985.80677705}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.399633600000007, 50.10131139999999], "geometry": {"coordinates": [14.399633600000007, 50.10131139999999], "type": "Point"}, "id": "17", "properties": {"nodeID": 17, "x": 1602959.8799617135, "y": 6463839.712475327}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.401311799999997, 50.101800699999984], "geometry": {"coordinates": [14.401311799999997, 50.101800699999984], "type": "Point"}, "id": "18", "properties": {"nodeID": 18, "x": 1603146.6963311615, "y": 6463924.630126579}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404248800000007, 50.10007700000001], "geometry": {"coordinates": [14.404248800000007, 50.10007700000001], "type": "Point"}, "id": "19", "properties": {"nodeID": 19, "x": 1603473.6416756227, "y": 6463625.487127112}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1049737, 14.400690199999993, 50.1049737], "geometry": {"coordinates": [14.400690199999993, 50.1049737], "type": "Point"}, "id": "20", "properties": {"nodeID": 20, "x": 1603077.5001356844, "y": 6464475.322968743}, "type": "Feature"}, {"bbox": [14.402574900000001, 50.105621199999995, 14.402574900000001, 50.105621199999995], "geometry": {"coordinates": [14.402574900000001, 50.105621199999995], "type": "Point"}, "id": "21", "properties": {"nodeID": 21, "x": 1603287.303979983, "y": 6464587.704889874}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402499399999995, 50.100328799999986], "geometry": {"coordinates": [14.402499399999995, 50.100328799999986], "type": "Point"}, "id": "22", "properties": {"nodeID": 22, "x": 1603278.8993584276, "y": 6463669.185595578}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1054507, 14.404819700000001, 50.1054507], "geometry": {"coordinates": [14.404819700000001, 50.1054507], "type": "Point"}, "id": "23", "properties": {"nodeID": 23, "x": 1603537.1939729159, "y": 6464558.11228298}, "type": "Feature"}, {"bbox": [14.406339600000006, 50.10579450000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [14.406339600000006, 50.10579450000001], "type": "Point"}, "id": "24", "properties": {"nodeID": 24, "x": 1603706.3884669733, "y": 6464617.783583014}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_cccc1bf1afbaa9c092bad04f46deb323.bindTooltip(\n", + " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -606,64 +662,69 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_cccc1bf1afbaa9c092bad04f46deb323.addTo(map_13bf1525072211457537cdb8347a311f);\n", + " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", " \n", " \n", - " function geo_json_daf28d15d40ea7ca2d7f48de380385ca_styler(feature) {\n", + " function geo_json_838def6cdf8f4f50b5af320d0954887d_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_daf28d15d40ea7ca2d7f48de380385ca_highlighter(feature) {\n", + " function geo_json_838def6cdf8f4f50b5af320d0954887d_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_daf28d15d40ea7ca2d7f48de380385ca_pointToLayer(feature, latlng) {\n", + " function geo_json_838def6cdf8f4f50b5af320d0954887d_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_daf28d15d40ea7ca2d7f48de380385ca_styler(feature)\n", + " let style = geo_json_838def6cdf8f4f50b5af320d0954887d_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_daf28d15d40ea7ca2d7f48de380385ca_onEachFeature(feature, layer) {\n", + " function geo_json_838def6cdf8f4f50b5af320d0954887d_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_daf28d15d40ea7ca2d7f48de380385ca.resetStyle(e.target);\n", + " geo_json_838def6cdf8f4f50b5af320d0954887d.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_daf28d15d40ea7ca2d7f48de380385ca_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_838def6cdf8f4f50b5af320d0954887d_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_daf28d15d40ea7ca2d7f48de380385ca = L.geoJson(null, {\n", - " onEachFeature: geo_json_daf28d15d40ea7ca2d7f48de380385ca_onEachFeature,\n", + " var geo_json_838def6cdf8f4f50b5af320d0954887d = L.geoJson(null, {\n", + " onEachFeature: geo_json_838def6cdf8f4f50b5af320d0954887d_onEachFeature,\n", " \n", - " style: geo_json_daf28d15d40ea7ca2d7f48de380385ca_styler,\n", - " pointToLayer: geo_json_daf28d15d40ea7ca2d7f48de380385ca_pointToLayer,\n", + " style: geo_json_838def6cdf8f4f50b5af320d0954887d_styler,\n", + " pointToLayer: geo_json_838def6cdf8f4f50b5af320d0954887d_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_daf28d15d40ea7ca2d7f48de380385ca_add (data) {\n", - " geo_json_daf28d15d40ea7ca2d7f48de380385ca\n", + " function geo_json_838def6cdf8f4f50b5af320d0954887d_add (data) {\n", + " geo_json_838def6cdf8f4f50b5af320d0954887d\n", " .addData(data);\n", " }\n", - " geo_json_daf28d15d40ea7ca2d7f48de380385ca_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"edge_id": 0, "mm_len": 264.1039496246775, "node_end": 1, "node_start": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"edge_id": 1, "mm_len": 99.75118962647376, "node_end": 3, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"edge_id": 2, "mm_len": 199.74650338337847, "node_end": 4, "node_start": 1, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"edge_id": 3, "mm_len": 203.01409000575802, "node_end": 3, "node_start": 1, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"edge_id": 4, "mm_len": 198.48272399064462, "node_end": 5, "node_start": 1, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"edge_id": 5, "mm_len": 200.61768541143937, "node_end": 6, "node_start": 5, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"edge_id": 6, "mm_len": 163.14628203947333, "node_end": 7, "node_start": 6, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"edge_id": 7, "mm_len": 193.51137206831748, "node_end": 8, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"edge_id": 8, "mm_len": 127.80086449751786, "node_end": 9, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"edge_id": 9, "mm_len": 122.5319618088215, "node_end": 11, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"edge_id": 10, "mm_len": 193.04063727323836, "node_end": 12, "node_start": 11, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"edge_id": 11, "mm_len": 88.92430548419476, "node_end": 13, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"edge_id": 12, "mm_len": 107.88014814146449, "node_end": 5, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"edge_id": 13, "mm_len": 282.6905386499787, "node_end": 15, "node_start": 14, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"edge_id": 14, "mm_len": 200.30351738673852, "node_end": 16, "node_start": 3, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"edge_id": 15, "mm_len": 200.3861708266132, "node_end": 10, "node_start": 3, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"edge_id": 16, "mm_len": 191.66755798860544, "node_end": 13, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"edge_id": 17, "mm_len": 202.03167967950094, "node_end": 16, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"edge_id": 18, "mm_len": 201.30697205908257, "node_end": 16, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"edge_id": 19, "mm_len": 187.49184699173748, "node_end": 17, "node_start": 9, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"edge_id": 20, "mm_len": 182.6849740039611, "node_end": 18, "node_start": 2, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"edge_id": 21, "mm_len": 72.91516907666792, "node_end": 18, "node_start": 9, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"edge_id": 22, "mm_len": 76.42465276315266, "node_end": 18, "node_start": 11, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"edge_id": 23, "mm_len": 168.88041067114747, "node_end": 19, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"edge_id": 24, "mm_len": 201.4861168351184, "node_end": 14, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"edge_id": 25, "mm_len": 351.1551873514152, "node_end": 20, "node_start": 5, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"edge_id": 26, "mm_len": 382.50195042922803, "node_end": 21, "node_start": 1, "stroke_id": 9}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"edge_id": 27, "mm_len": 172.0624733749828, "node_end": 22, "node_start": 10, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"edge_id": 28, "mm_len": 138.23490844748363, "node_end": 23, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"edge_id": 29, "mm_len": 255.8228880811063, "node_end": 24, "node_start": 13, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"edge_id": 30, "mm_len": 317.85221640975095, "node_end": 13, "node_start": 4, "stroke_id": 2}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_838def6cdf8f4f50b5af320d0954887d_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"edge_id": 0, "mm_len": 264.1039496246775, "node_end": 1, "node_start": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"edge_id": 1, "mm_len": 99.75118962647376, "node_end": 3, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"edge_id": 2, "mm_len": 199.74650338337847, "node_end": 4, "node_start": 1, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"edge_id": 3, "mm_len": 203.01409000575802, "node_end": 3, "node_start": 1, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"edge_id": 4, "mm_len": 198.48272399064462, "node_end": 5, "node_start": 1, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"edge_id": 5, "mm_len": 200.61768541143937, "node_end": 6, "node_start": 5, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"edge_id": 6, "mm_len": 163.14628203947333, "node_end": 7, "node_start": 6, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"edge_id": 7, "mm_len": 193.51137206831748, "node_end": 8, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"edge_id": 8, "mm_len": 127.80086449751786, "node_end": 9, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"edge_id": 9, "mm_len": 122.5319618088215, "node_end": 11, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"edge_id": 10, "mm_len": 193.04063727323836, "node_end": 12, "node_start": 11, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"edge_id": 11, "mm_len": 88.92430548419476, "node_end": 13, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"edge_id": 12, "mm_len": 107.88014814146449, "node_end": 5, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"edge_id": 13, "mm_len": 282.6905386499787, "node_end": 15, "node_start": 14, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"edge_id": 14, "mm_len": 200.30351738673852, "node_end": 16, "node_start": 3, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"edge_id": 15, "mm_len": 200.3861708266132, "node_end": 10, "node_start": 3, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"edge_id": 16, "mm_len": 191.66755798860544, "node_end": 13, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"edge_id": 17, "mm_len": 202.03167967950094, "node_end": 16, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"edge_id": 18, "mm_len": 201.30697205908257, "node_end": 16, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"edge_id": 19, "mm_len": 187.49184699173748, "node_end": 17, "node_start": 9, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"edge_id": 20, "mm_len": 182.6849740039611, "node_end": 18, "node_start": 2, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"edge_id": 21, "mm_len": 72.91516907666792, "node_end": 18, "node_start": 9, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"edge_id": 22, "mm_len": 76.42465276315266, "node_end": 18, "node_start": 11, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"edge_id": 23, "mm_len": 168.88041067114747, "node_end": 19, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"edge_id": 24, "mm_len": 201.4861168351184, "node_end": 14, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"edge_id": 25, "mm_len": 351.1551873514152, "node_end": 20, "node_start": 5, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"edge_id": 26, "mm_len": 382.50195042922803, "node_end": 21, "node_start": 1, "stroke_id": 9}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"edge_id": 27, "mm_len": 172.0624733749828, "node_end": 22, "node_start": 10, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"edge_id": 28, "mm_len": 138.23490844748363, "node_end": 23, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"edge_id": 29, "mm_len": 255.8228880811063, "node_end": 24, "node_start": 13, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"edge_id": 30, "mm_len": 317.85221640975095, "node_end": 13, "node_start": 4, "stroke_id": 2}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_daf28d15d40ea7ca2d7f48de380385ca.bindTooltip(\n", + " geo_json_838def6cdf8f4f50b5af320d0954887d.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -684,64 +745,69 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_daf28d15d40ea7ca2d7f48de380385ca.addTo(map_13bf1525072211457537cdb8347a311f);\n", + " geo_json_838def6cdf8f4f50b5af320d0954887d.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", " \n", " \n", - " function geo_json_5f66724972d35afba4328bb53432ff17_styler(feature) {\n", + " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"color": "black", "fillColor": "black", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_5f66724972d35afba4328bb53432ff17_highlighter(feature) {\n", + " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_5f66724972d35afba4328bb53432ff17_pointToLayer(feature, latlng) {\n", + " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 10, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_5f66724972d35afba4328bb53432ff17_styler(feature)\n", + " let style = geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_5f66724972d35afba4328bb53432ff17_onEachFeature(feature, layer) {\n", + " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_5f66724972d35afba4328bb53432ff17.resetStyle(e.target);\n", + " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_5f66724972d35afba4328bb53432ff17_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_5f66724972d35afba4328bb53432ff17 = L.geoJson(null, {\n", - " onEachFeature: geo_json_5f66724972d35afba4328bb53432ff17_onEachFeature,\n", + " var geo_json_724ab5ab1a419daf695c69a0ba3e0ac1 = L.geoJson(null, {\n", + " onEachFeature: geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_onEachFeature,\n", " \n", - " style: geo_json_5f66724972d35afba4328bb53432ff17_styler,\n", - " pointToLayer: geo_json_5f66724972d35afba4328bb53432ff17_pointToLayer,\n", + " style: geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_styler,\n", + " pointToLayer: geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_5f66724972d35afba4328bb53432ff17_add (data) {\n", - " geo_json_5f66724972d35afba4328bb53432ff17\n", + " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_add (data) {\n", + " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1\n", " .addData(data);\n", " }\n", - " geo_json_5f66724972d35afba4328bb53432ff17_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "black", "edge_ids": "[ 0 3 15 27]", "geometry_stroke": "LINESTRING (1603278.8993584276 6463669.185595578, 1603283.7306243288 6463690.028353462, 1603314.4436718386 6463822.409720818, 1603317.7832565615 6463836.796863219, 1603361.0308787343 6464021.107210826, 1603363.557831175 6464031.88480676, 1603376.5042879563 6464085.530021086, 1603413.2063240695 6464228.730248732, 1603585.6402153103 6464428.773867372)", "length": 839.5666838320316, "n_segments": 8, "nodeID": 0, "stroke_access": 3, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 8, "stroke_degree": 5, "stroke_orthogonality": 61.889319613560986, "stroke_spacing": 104.94583547900395, "x": "array(\\u0027d\\u0027, [1603374.6625343116])", "y": "array(\\u0027d\\u0027, [6464077.898491419])"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "black", "edge_ids": "[ 1 12 14 25]", "geometry_stroke": "LINESTRING (1603077.5001356844 6464475.322968743, 1603085.5151390221 6464462.305855976, 1603095.1999347198 6464446.563854833, 1603122.5066058137 6464393.870890386, 1603135.486458439 6464371.013077857, 1603149.2010197043 6464359.054839547, 1603152.6964517166 6464350.116544929, 1603156.9933840595 6464339.130265876, 1603161.5797470808 6464327.415055399, 1603223.2396130317 6464169.912161903, 1603226.9576840235 6464160.158361825, 1603232.3010195831 6464146.100413868, 1603255.644716802 6464084.749030368, 1603268.502117987 6464060.781328565, 1603296.8217964454 6464047.851641227, 1603349.1085612718 6464035.338499875, 1603363.557831175 6464031.88480676, 1603376.025614145 6464028.934416787, 1603544.6523787973 6463989.069544387, 1603558.489391506 6463985.80677705)", "length": 759.0900425060918, "n_segments": 19, "nodeID": 1, "stroke_access": 2, "stroke_betweenness": 0.08796296296296295, "stroke_closeness": 0.5625, "stroke_connectivity": 6, "stroke_degree": 4, "stroke_orthogonality": 83.69254851816929, "stroke_spacing": 126.51500708434862, "x": "array(\\u0027d\\u0027, [1603237.0487682838])", "y": "array(\\u0027d\\u0027, [6464133.622486805])"}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "black", "edge_ids": "[ 2 11 28 30]", "geometry_stroke": "LINESTRING (1603537.1939729159 6464558.11228298, 1603557.6878911697 6464504.984705836, 1603561.7399206352 6464494.466839611, 1603564.634227396 6464481.987738368, 1603585.6402153103 6464428.773867372, 1603603.0951114655 6464413.0145736905, 1603641.889954006 6464381.218380466, 1603650.450422848 6464368.600601688, 1603664.8217691095 6464355.097690451, 1603676.1429613235 6464344.076693036, 1603680.7181923958 6464326.616686098, 1603697.6387549953 6464272.223619222, 1603722.7079043242 6464183.866016789, 1603618.7800277183 6464181.019706178, 1603607.3029882177 6464181.852772597, 1603592.8871141581 6464183.935439011, 1603433.8783535103 6464223.419421798, 1603413.2063240695 6464228.730248732)", "length": 744.7579337248078, "n_segments": 17, "nodeID": 2, "stroke_access": 4, "stroke_betweenness": 0.04629629629629629, "stroke_closeness": 0.5294117647058824, "stroke_connectivity": 8, "stroke_degree": 4, "stroke_orthogonality": 58.853128911121644, "stroke_spacing": 93.09474171560097, "x": "array(\\u0027d\\u0027, [1603707.1065106073])", "y": "array(\\u0027d\\u0027, [6464238.853991265])"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "black", "edge_ids": "[4 5 6]", "geometry_stroke": "LINESTRING (1603413.2063240695 6464228.730248732, 1603274.457710744 6464178.659351781, 1603226.9576840235 6464160.158361825, 1603039.9632033885 6464087.491175889, 1602902.3166530235 6464035.130236932, 1602887.2996537155 6464029.975730775)", "length": 562.2466914415573, "n_segments": 5, "nodeID": 3, "stroke_access": 2, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 7, "stroke_degree": 5, "stroke_orthogonality": 67.41154917006796, "stroke_spacing": 80.32095592022247, "x": "array(\\u0027d\\u0027, [1603149.9288811635])", "y": "array(\\u0027d\\u0027, [6464130.224503239])"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "black", "edge_ids": "[ 7 8 9 13 21 22 24]", "geometry_stroke": "LINESTRING (1602970.3773896934 6464268.058242684, 1602974.0843287394 6464258.443173138, 1603039.9632033885 6464087.491175889, 1603074.7839401108 6463991.950499589, 1603090.513384159 6463971.106984773, 1603146.6963311615 6463924.630126579, 1603157.794884393 6463914.581579376, 1603202.3783404578 6463872.287568242, 1603217.2506244255 6463859.844110653, 1603317.7832565615 6463836.796863219, 1603334.948722044 6463832.631704839, 1603497.3304632641 6463793.166932718, 1603513.6499006122 6463789.557147608, 1603542.0029749167 6463784.4895673115, 1603795.889337571 6463785.444077063)", "length": 1077.3606756995746, "n_segments": 14, "nodeID": 4, "stroke_access": 3, "stroke_betweenness": 0.5046296296296297, "stroke_closeness": 0.75, "stroke_connectivity": 9, "stroke_degree": 6, "stroke_orthogonality": 76.90795995185228, "stroke_spacing": 119.70674174439718, "x": "array(\\u0027d\\u0027, [1603264.6577362637])", "y": "array(\\u0027d\\u0027, [6463848.97596353])"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "black", "edge_ids": "[10]", "geometry_stroke": "LINESTRING (1603071.956425043 6463729.978565, 1603089.0217029832 6463747.749702545, 1603202.3783404578 6463872.287568242)", "length": 193.04063727323836, "n_segments": 2, "nodeID": 5, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 87.60977577529626, "stroke_spacing": 193.04063727323836, "x": "array(\\u0027d\\u0027, [1603137.4077031056])", "y": "array(\\u0027d\\u0027, [6463800.908382258])"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "black", "edge_ids": "[16 17 18 23 29]", "geometry_stroke": "LINESTRING (1603706.3884669733 6464617.783583014, 1603705.7539458754 6464597.632755783, 1603681.3749773917 6464489.555035355, 1603678.970476391 6464477.214790825, 1603675.6865514126 6464464.336524226, 1603674.2282660832 6464458.799917089, 1603650.450422848 6464368.600601688, 1603607.3029882177 6464181.852772597, 1603558.489391506 6463985.80677705, 1603513.6499006122 6463789.557147608, 1603480.142733884 6463653.653349537, 1603478.918219486 6463648.325535514, 1603477.8829482212 6463643.67454756, 1603473.6416756227 6463625.487127112)", "length": 1019.7095084794428, "n_segments": 13, "nodeID": 6, "stroke_access": 4, "stroke_betweenness": 0.06712962962962961, "stroke_closeness": 0.6, "stroke_connectivity": 7, "stroke_degree": 3, "stroke_orthogonality": 72.94921342069121, "stroke_spacing": 145.67278692563468, "x": "array(\\u0027d\\u0027, [1603592.2349246691])", "y": "array(\\u0027d\\u0027, [6464121.336160048])"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "black", "edge_ids": "[19]", "geometry_stroke": "LINESTRING (1602959.8799617135 6463839.712475327, 1602973.3607520477 6463844.207379333, 1602987.0753133134 6463853.041000848, 1603090.513384159 6463971.106984773)", "length": 187.49184699173748, "n_segments": 3, "nodeID": 7, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 78.26155769686821, "stroke_spacing": 187.49184699173748, "x": "array(\\u0027d\\u0027, [1603028.737187382])", "y": "array(\\u0027d\\u0027, [6463900.594576759])"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "black", "edge_ids": "[20]", "geometry_stroke": "LINESTRING (1603146.6963311615 6463924.630126579, 1603157.0490438067 6463936.205929175, 1603258.3275165292 6464049.413615812, 1603268.502117987 6464060.781328565)", "length": 182.6849740039611, "n_segments": 3, "nodeID": 8, "stroke_access": 0, "stroke_betweenness": 0.020833333333333332, "stroke_closeness": 0.5, "stroke_connectivity": 2, "stroke_degree": 2, "stroke_orthogonality": 74.69091059653624, "stroke_spacing": 91.34248700198054, "x": "array(\\u0027d\\u0027, [1603207.5969886228])", "y": "array(\\u0027d\\u0027, [6463992.707728057])"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "black", "edge_ids": "[26]", "geometry_stroke": "LINESTRING (1603287.303979983 6464587.704889874, 1603286.8809659188 6464556.602281818, 1603337.5981259246 6464418.98505148, 1603340.9265786987 6464409.959912292, 1603345.6687890065 6464397.932193951, 1603413.2063240695 6464228.730248732)", "length": 382.50195042922803, "n_segments": 5, "nodeID": 9, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.5, "stroke_connectivity": 3, "stroke_degree": 3, "stroke_orthogonality": 59.82941708655712, "stroke_spacing": 127.50065014307602, "x": "array(\\u0027d\\u0027, [1603342.3426854417])", "y": "array(\\u0027d\\u0027, [6464406.368225728])"}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "black", "edge_ids": "[ 0 3 15 27]", "geometry_stroke": "LINESTRING (1603278.8993584276 6463669.185595578, 1603283.7306243288 6463690.028353462, 1603314.4436718386 6463822.409720818, 1603317.7832565615 6463836.796863219, 1603361.0308787343 6464021.107210826, 1603363.557831175 6464031.88480676, 1603376.5042879563 6464085.530021086, 1603413.2063240695 6464228.730248732, 1603585.6402153103 6464428.773867372)", "length": 839.5666838320316, "n_segments": 8, "nodeID": 0, "stroke_access": 3, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 8, "stroke_degree": 5, "stroke_orthogonality": 68.74678997354196, "stroke_spacing": 104.94583547900395, "x": "array(\\u0027d\\u0027, [1603374.6625343116])", "y": "array(\\u0027d\\u0027, [6464077.898491419])"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "black", "edge_ids": "[ 1 12 14 25]", "geometry_stroke": "LINESTRING (1603077.5001356844 6464475.322968743, 1603085.5151390221 6464462.305855976, 1603095.1999347198 6464446.563854833, 1603122.5066058137 6464393.870890386, 1603135.486458439 6464371.013077857, 1603149.2010197043 6464359.054839547, 1603152.6964517166 6464350.116544929, 1603156.9933840595 6464339.130265876, 1603161.5797470808 6464327.415055399, 1603223.2396130317 6464169.912161903, 1603226.9576840235 6464160.158361825, 1603232.3010195831 6464146.100413868, 1603255.644716802 6464084.749030368, 1603268.502117987 6464060.781328565, 1603296.8217964454 6464047.851641227, 1603349.1085612718 6464035.338499875, 1603363.557831175 6464031.88480676, 1603376.025614145 6464028.934416787, 1603544.6523787973 6463989.069544387, 1603558.489391506 6463985.80677705)", "length": 759.0900425060918, "n_segments": 19, "nodeID": 1, "stroke_access": 2, "stroke_betweenness": 0.08796296296296295, "stroke_closeness": 0.5625, "stroke_connectivity": 6, "stroke_degree": 4, "stroke_orthogonality": 86.32371095647791, "stroke_spacing": 126.51500708434862, "x": "array(\\u0027d\\u0027, [1603237.0487682838])", "y": "array(\\u0027d\\u0027, [6464133.622486805])"}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "black", "edge_ids": "[ 2 11 28 30]", "geometry_stroke": "LINESTRING (1603537.1939729159 6464558.11228298, 1603557.6878911697 6464504.984705836, 1603561.7399206352 6464494.466839611, 1603564.634227396 6464481.987738368, 1603585.6402153103 6464428.773867372, 1603603.0951114655 6464413.0145736905, 1603641.889954006 6464381.218380466, 1603650.450422848 6464368.600601688, 1603664.8217691095 6464355.097690451, 1603676.1429613235 6464344.076693036, 1603680.7181923958 6464326.616686098, 1603697.6387549953 6464272.223619222, 1603722.7079043242 6464183.866016789, 1603618.7800277183 6464181.019706178, 1603607.3029882177 6464181.852772597, 1603592.8871141581 6464183.935439011, 1603433.8783535103 6464223.419421798, 1603413.2063240695 6464228.730248732)", "length": 744.7579337248078, "n_segments": 17, "nodeID": 2, "stroke_access": 4, "stroke_betweenness": 0.04629629629629629, "stroke_closeness": 0.5294117647058824, "stroke_connectivity": 8, "stroke_degree": 4, "stroke_orthogonality": 60.67507202025625, "stroke_spacing": 93.09474171560097, "x": "array(\\u0027d\\u0027, [1603707.1065106073])", "y": "array(\\u0027d\\u0027, [6464238.853991265])"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "black", "edge_ids": "[4 5 6]", "geometry_stroke": "LINESTRING (1603413.2063240695 6464228.730248732, 1603274.457710744 6464178.659351781, 1603226.9576840235 6464160.158361825, 1603039.9632033885 6464087.491175889, 1602902.3166530235 6464035.130236932, 1602887.2996537155 6464029.975730775)", "length": 562.2466914415573, "n_segments": 5, "nodeID": 3, "stroke_access": 2, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 7, "stroke_degree": 5, "stroke_orthogonality": 72.69057271585089, "stroke_spacing": 80.32095592022247, "x": "array(\\u0027d\\u0027, [1603149.9288811635])", "y": "array(\\u0027d\\u0027, [6464130.224503239])"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "black", "edge_ids": "[ 7 8 9 13 21 22 24]", "geometry_stroke": "LINESTRING (1602970.3773896934 6464268.058242684, 1602974.0843287394 6464258.443173138, 1603039.9632033885 6464087.491175889, 1603074.7839401108 6463991.950499589, 1603090.513384159 6463971.106984773, 1603146.6963311615 6463924.630126579, 1603157.794884393 6463914.581579376, 1603202.3783404578 6463872.287568242, 1603217.2506244255 6463859.844110653, 1603317.7832565615 6463836.796863219, 1603334.948722044 6463832.631704839, 1603497.3304632641 6463793.166932718, 1603513.6499006122 6463789.557147608, 1603542.0029749167 6463784.4895673115, 1603795.889337571 6463785.444077063)", "length": 1077.3606756995746, "n_segments": 14, "nodeID": 4, "stroke_access": 3, "stroke_betweenness": 0.5046296296296297, "stroke_closeness": 0.75, "stroke_connectivity": 9, "stroke_degree": 6, "stroke_orthogonality": 87.28338224081126, "stroke_spacing": 119.70674174439718, "x": "array(\\u0027d\\u0027, [1603264.6577362637])", "y": "array(\\u0027d\\u0027, [6463848.97596353])"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "black", "edge_ids": "[10]", "geometry_stroke": "LINESTRING (1603071.956425043 6463729.978565, 1603089.0217029832 6463747.749702545, 1603202.3783404578 6463872.287568242)", "length": 193.04063727323836, "n_segments": 2, "nodeID": 5, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 87.60977577529626, "stroke_spacing": 193.04063727323836, "x": "array(\\u0027d\\u0027, [1603137.4077031056])", "y": "array(\\u0027d\\u0027, [6463800.908382258])"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "black", "edge_ids": "[16 17 18 23 29]", "geometry_stroke": "LINESTRING (1603706.3884669733 6464617.783583014, 1603705.7539458754 6464597.632755783, 1603681.3749773917 6464489.555035355, 1603678.970476391 6464477.214790825, 1603675.6865514126 6464464.336524226, 1603674.2282660832 6464458.799917089, 1603650.450422848 6464368.600601688, 1603607.3029882177 6464181.852772597, 1603558.489391506 6463985.80677705, 1603513.6499006122 6463789.557147608, 1603480.142733884 6463653.653349537, 1603478.918219486 6463648.325535514, 1603477.8829482212 6463643.67454756, 1603473.6416756227 6463625.487127112)", "length": 1019.7095084794428, "n_segments": 13, "nodeID": 6, "stroke_access": 4, "stroke_betweenness": 0.06712962962962961, "stroke_closeness": 0.6, "stroke_connectivity": 7, "stroke_degree": 3, "stroke_orthogonality": 76.50850905913968, "stroke_spacing": 145.67278692563468, "x": "array(\\u0027d\\u0027, [1603592.2349246691])", "y": "array(\\u0027d\\u0027, [6464121.336160048])"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "black", "edge_ids": "[19]", "geometry_stroke": "LINESTRING (1602959.8799617135 6463839.712475327, 1602973.3607520477 6463844.207379333, 1602987.0753133134 6463853.041000848, 1603090.513384159 6463971.106984773)", "length": 187.49184699173748, "n_segments": 3, "nodeID": 7, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 78.26155769686821, "stroke_spacing": 187.49184699173748, "x": "array(\\u0027d\\u0027, [1603028.737187382])", "y": "array(\\u0027d\\u0027, [6463900.594576759])"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "black", "edge_ids": "[20]", "geometry_stroke": "LINESTRING (1603146.6963311615 6463924.630126579, 1603157.0490438067 6463936.205929175, 1603258.3275165292 6464049.413615812, 1603268.502117987 6464060.781328565)", "length": 182.6849740039611, "n_segments": 3, "nodeID": 8, "stroke_access": 0, "stroke_betweenness": 0.020833333333333332, "stroke_closeness": 0.5, "stroke_connectivity": 2, "stroke_degree": 2, "stroke_orthogonality": 78.91626592156373, "stroke_spacing": 91.34248700198054, "x": "array(\\u0027d\\u0027, [1603207.5969886228])", "y": "array(\\u0027d\\u0027, [6463992.707728057])"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "black", "edge_ids": "[26]", "geometry_stroke": "LINESTRING (1603287.303979983 6464587.704889874, 1603286.8809659188 6464556.602281818, 1603337.5981259246 6464418.98505148, 1603340.9265786987 6464409.959912292, 1603345.6687890065 6464397.932193951, 1603413.2063240695 6464228.730248732)", "length": 382.50195042922803, "n_segments": 5, "nodeID": 9, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.5, "stroke_connectivity": 3, "stroke_degree": 3, "stroke_orthogonality": 59.350287847902734, "stroke_spacing": 127.50065014307602, "x": "array(\\u0027d\\u0027, [1603342.3426854417])", "y": "array(\\u0027d\\u0027, [6464406.368225728])"}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_5f66724972d35afba4328bb53432ff17.bindTooltip(\n", + " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -762,64 +828,69 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_5f66724972d35afba4328bb53432ff17.addTo(map_13bf1525072211457537cdb8347a311f);\n", + " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", " \n", " \n", - " function geo_json_41e27f8d20a3fc51d321041139203280_styler(feature) {\n", + " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"color": "blue", "fillColor": "blue", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_41e27f8d20a3fc51d321041139203280_highlighter(feature) {\n", + " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_41e27f8d20a3fc51d321041139203280_pointToLayer(feature, latlng) {\n", + " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_41e27f8d20a3fc51d321041139203280_styler(feature)\n", + " let style = geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_41e27f8d20a3fc51d321041139203280_onEachFeature(feature, layer) {\n", + " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_41e27f8d20a3fc51d321041139203280.resetStyle(e.target);\n", + " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_41e27f8d20a3fc51d321041139203280_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_41e27f8d20a3fc51d321041139203280 = L.geoJson(null, {\n", - " onEachFeature: geo_json_41e27f8d20a3fc51d321041139203280_onEachFeature,\n", + " var geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2 = L.geoJson(null, {\n", + " onEachFeature: geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_onEachFeature,\n", " \n", - " style: geo_json_41e27f8d20a3fc51d321041139203280_styler,\n", - " pointToLayer: geo_json_41e27f8d20a3fc51d321041139203280_pointToLayer,\n", + " style: geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_styler,\n", + " pointToLayer: geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_pointToLayer,\n", + " ...{\n", + "}\n", " });\n", "\n", - " function geo_json_41e27f8d20a3fc51d321041139203280_add (data) {\n", - " geo_json_41e27f8d20a3fc51d321041139203280\n", + " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_add (data) {\n", + " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2\n", " .addData(data);\n", " }\n", - " geo_json_41e27f8d20a3fc51d321041139203280_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "blue", "angles": "[62.30218235695145, 63.647466378271766]", "node_end": 2, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "blue", "angles": "[36.134980718680936]", "node_end": 9, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "blue", "angles": "[27.958640647426915]", "node_end": 3, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "blue", "angles": "[88.89258170115896, 89.75267804978043]", "node_end": 1, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "blue", "angles": "[63.27660557215604, 63.14942148406139]", "node_end": 4, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "blue", "angles": "[61.612799132873675]", "node_end": 8, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "blue", "angles": "[83.02522839160721, 89.58581817377714]", "node_end": 3, "node_start": 1, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "blue", "angles": "[89.2861856598184]", "node_end": 6, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "blue", "angles": "[53.8322224050728]", "node_end": 9, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "blue", "angles": "[35.68882573084483]", "node_end": 3, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "blue", "angles": "[88.60150429340734, 59.79419820769667, 47.16443370903166, 59.79419820769667]", "node_end": 6, "node_start": 2, "number_connections": 4}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "blue", "angles": "[89.52104813591764]", "node_end": 9, "node_start": 3, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "blue", "angles": "[74.19659813624955, 71.90468497465247]", "node_end": 4, "node_start": 3, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "blue", "angles": "[78.26155769686821]", "node_end": 7, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "blue", "angles": "[87.60977577529626]", "node_end": 5, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "blue", "angles": "[76.65791615429069, 89.34605771289704]", "node_end": 6, "node_start": 4, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "blue", "angles": "[87.76902206019881]", "node_end": 8, "node_start": 4, "number_connections": 1}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "blue", "angles": "[np.float64(62.30218235695145), np.float64(63.647466378271766)]", "node_end": 2, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "blue", "angles": "[np.float64(36.134980718680936)]", "node_end": 9, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "blue", "angles": "[np.float64(29.396028363390094)]", "node_end": 3, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.74560192447649), np.float64(89.75267804978043)]", "node_end": 1, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.56623033507175), np.float64(89.42915166171285)]", "node_end": 4, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "blue", "angles": "[np.float64(70.04113695824684)]", "node_end": 8, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.53084497276808), np.float64(89.58581817377714)]", "node_end": 3, "node_start": 1, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.2861856598184)]", "node_end": 6, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "blue", "angles": "[np.float64(53.8322224050728)]", "node_end": 9, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "blue", "angles": "[np.float64(34.25143801488166)]", "node_end": 3, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "blue", "angles": "[np.float64(84.23886881283048), np.float64(80.16976627731358), np.float64(47.16443370903166), np.float64(59.79419820769667)]", "node_end": 6, "node_start": 2, "number_connections": 4}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "blue", "angles": "[np.float64(88.08366041995446)]", "node_end": 9, "node_start": 3, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "blue", "angles": "[np.float64(88.78833801117518), np.float64(89.19788105500966)]", "node_end": 4, "node_start": 3, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "blue", "angles": "[np.float64(78.26155769686821)]", "node_end": 7, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "blue", "angles": "[np.float64(87.60977577529626)]", "node_end": 5, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "blue", "angles": "[np.float64(86.2834611843536), np.float64(88.62264956293333)]", "node_end": 6, "node_start": 4, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "blue", "angles": "[np.float64(87.79139488488063)]", "node_end": 8, "node_start": 4, "number_connections": 1}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_41e27f8d20a3fc51d321041139203280.bindTooltip(\n", + " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -840,39 +911,46 @@ " \n", " return div\n", " }\n", - " ,{"className": "foliumtooltip", "sticky": true});\n", + " ,{\n", + " "sticky": true,\n", + " "className": "foliumtooltip",\n", + "});\n", " \n", " \n", - " geo_json_41e27f8d20a3fc51d321041139203280.addTo(map_13bf1525072211457537cdb8347a311f);\n", + " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", " \n", " \n", - " var layer_control_ba8a218fd3c07b79ef7ceb62f299284a_layers = {\n", + " var layer_control_7351cd324649a2def3af29bb0439822d_layers = {\n", " base_layers : {\n", - " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_9ba2d90e4c000d6f2acabb17da236daf,\n", + " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_75a780ad99b6f7bd559c3dfd418bd85f,\n", " },\n", " overlays : {\n", - " "strokes" : geo_json_0e649b76f5226724814454416d8e5c0b,\n", - " "points_primal" : geo_json_cccc1bf1afbaa9c092bad04f46deb323,\n", - " "lines_primal" : geo_json_daf28d15d40ea7ca2d7f48de380385ca,\n", - " "points_stroke" : geo_json_5f66724972d35afba4328bb53432ff17,\n", - " "lines_stroke" : geo_json_41e27f8d20a3fc51d321041139203280,\n", + " "strokes" : geo_json_a75521f1f7e4c097815fc719c81c67c1,\n", + " "points_primal" : geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf,\n", + " "lines_primal" : geo_json_838def6cdf8f4f50b5af320d0954887d,\n", + " "points_stroke" : geo_json_724ab5ab1a419daf695c69a0ba3e0ac1,\n", + " "lines_stroke" : geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2,\n", " },\n", " };\n", - " let layer_control_ba8a218fd3c07b79ef7ceb62f299284a = L.control.layers(\n", - " layer_control_ba8a218fd3c07b79ef7ceb62f299284a_layers.base_layers,\n", - " layer_control_ba8a218fd3c07b79ef7ceb62f299284a_layers.overlays,\n", - " {"autoZIndex": true, "collapsed": true, "position": "topright"}\n", - " ).addTo(map_13bf1525072211457537cdb8347a311f);\n", + " let layer_control_7351cd324649a2def3af29bb0439822d = L.control.layers(\n", + " layer_control_7351cd324649a2def3af29bb0439822d_layers.base_layers,\n", + " layer_control_7351cd324649a2def3af29bb0439822d_layers.overlays,\n", + " {\n", + " "position": "topright",\n", + " "collapsed": true,\n", + " "autoZIndex": true,\n", + "}\n", + " ).addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", "\n", " \n", "</script>\n", "</html>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen>" ], "text/plain": [ - "" + "" ] }, - "execution_count": 11, + "execution_count": 120, "metadata": {}, "output_type": "execute_result" } @@ -902,7 +980,7 @@ ], "metadata": { "kernelspec": { - "display_name": "simplification", + "display_name": "momepy_dev", "language": "python", "name": "python3" }, @@ -916,7 +994,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.12.10" } }, "nbformat": 4, diff --git a/momepy/strokegraph_compare.ipynb b/momepy/strokegraph_compare.ipynb index 33eeb55a..99f0eb4f 100644 --- a/momepy/strokegraph_compare.ipynb +++ b/momepy/strokegraph_compare.ipynb @@ -10,18 +10,23 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 160, "id": "b411a245", "metadata": {}, "outputs": [], "source": [ + "import math\n", "import pickle\n", - "import networkx as nx" + "\n", + "import geopandas as gpd\n", + "import numpy as np\n", + "\n", + "import momepy\n" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 161, "id": "b57b27f8", "metadata": {}, "outputs": [], @@ -42,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 162, "id": "cf78ba7a", "metadata": {}, "outputs": [ @@ -50,10 +55,10 @@ "data": { "text/plain": [ "{'geometry': ,\n", - " 'angles': [36.134980718680936]}" + " 'angles': [np.float64(36.134980718680936)]}" ] }, - "execution_count": 3, + "execution_count": 162, "metadata": {}, "output_type": "execute_result" } @@ -64,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 163, "id": "915e4cab", "metadata": {}, "outputs": [ @@ -73,10 +78,10 @@ "text/plain": [ "{'geometry': ,\n", " 'number_connections': 1,\n", - " 'angles': [36.134980718680936]}" + " 'angles': [np.float64(36.134980718680936)]}" ] }, - "execution_count": 4, + "execution_count": 163, "metadata": {}, "output_type": "execute_result" } @@ -95,7 +100,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 164, "id": "af4d762b", "metadata": {}, "outputs": [], @@ -106,7 +111,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 165, "id": "afbcc5f1", "metadata": {}, "outputs": [ @@ -123,33 +128,23 @@ "\n", "\n", "Edge (0, 3)\n", - "Angles differ:\n", - "[29.3960283634]\n", - "[27.9586406474]\n", + "Angles equal\n", "\n", "\n", "Edge (0, 1)\n", - "Angles differ:\n", - "[89.7456019245, 89.7526780498]\n", - "[88.8925817012, 89.7526780498]\n", + "Angles equal\n", "\n", "\n", "Edge (0, 4)\n", - "Angles differ:\n", - "[89.4291516617, 89.5662303351]\n", - "[63.1494214841, 63.2766055722]\n", + "Angles equal\n", "\n", "\n", "Edge (1, 8)\n", - "Angles differ:\n", - "[70.0411369582]\n", - "[61.6127991329]\n", + "Angles equal\n", "\n", "\n", "Edge (1, 3)\n", - "Angles differ:\n", - "[89.5308449728, 89.5858181738]\n", - "[83.0252283916, 89.5858181738]\n", + "Angles equal\n", "\n", "\n", "Edge (1, 6)\n", @@ -161,27 +156,19 @@ "\n", "\n", "Edge (2, 3)\n", - "Angles differ:\n", - "[34.2514380149]\n", - "[35.6888257308]\n", + "Angles equal\n", "\n", "\n", "Edge (2, 6)\n", - "Angles differ:\n", - "[47.164433709, 59.7941982077, 80.1697662773, 84.2388688128]\n", - "[47.164433709, 59.7941982077, 59.7941982077, 88.6015042934]\n", + "Angles equal\n", "\n", "\n", "Edge (3, 9)\n", - "Angles differ:\n", - "[88.08366042]\n", - "[89.5210481359]\n", + "Angles equal\n", "\n", "\n", "Edge (3, 4)\n", - "Angles differ:\n", - "[88.7883380112, 89.197881055]\n", - "[71.9046849747, 74.1965981362]\n", + "Angles equal\n", "\n", "\n", "Edge (4, 7)\n", @@ -193,15 +180,11 @@ "\n", "\n", "Edge (4, 6)\n", - "Angles differ:\n", - "[86.2834611844, 88.6226495629]\n", - "[76.6579161543, 89.3460577129]\n", + "Angles equal\n", "\n", "\n", "Edge (4, 8)\n", - "Angles differ:\n", - "[87.7913948849]\n", - "[87.7690220602]\n", + "Angles equal\n", "\n", "\n" ] @@ -241,7 +224,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 166, "id": "029e919b", "metadata": {}, "outputs": [], @@ -251,7 +234,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 167, "id": "e7a7bf17", "metadata": {}, "outputs": [ @@ -271,10 +254,10 @@ " 'access': 3,\n", " 'length': 839.5666838320316,\n", " 'spacing': 104.94583547900395,\n", - " 'orthogonality': 68.74678997354196}" + " 'orthogonality': np.float64(68.74678997354196)}" ] }, - "execution_count": 8, + "execution_count": 167, "metadata": {}, "output_type": "execute_result" } @@ -293,14 +276,14 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 168, "id": "829d8185", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'n_segments': 8,\n", + "{'n_segments': np.int64(8),\n", " 'geometry_stroke': ,\n", " 'edge_ids': array([ 0, 3, 15, 27]),\n", " 'geometry': ,\n", @@ -312,11 +295,11 @@ " 'stroke_degree': 5,\n", " 'stroke_connectivity': 8,\n", " 'stroke_access': 3,\n", - " 'stroke_orthogonality': 61.889319613560986,\n", + " 'stroke_orthogonality': np.float64(68.74678997354196),\n", " 'stroke_spacing': 104.94583547900395}" ] }, - "execution_count": 9, + "execution_count": 168, "metadata": {}, "output_type": "execute_result" } @@ -327,7 +310,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 169, "id": "66b889d6", "metadata": {}, "outputs": [], @@ -346,7 +329,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 170, "id": "7f661ee2", "metadata": {}, "outputs": [], @@ -359,8 +342,7 @@ " assert G_anvy.nodes[n][\"edge_indeces\"] == list(G_clse.nodes[n][\"edge_ids\"]), \"Edge IDs differ\"\n", " assert G_anvy.nodes[n][\"length\"] == G_clse.nodes[n][\"length\"]\n", " for k, v in metrics_map.items():\n", - " assert round(G_anvy.nodes[n][k], 10) == round(G_clse.nodes[n][v], 10), f\"{k} differ\"\n", - " " + " assert round(G_anvy.nodes[n][k], 10) == round(G_clse.nodes[n][v], 10), f\"{k} differ\"" ] }, { @@ -373,7 +355,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 171, "id": "d922e80c", "metadata": {}, "outputs": [ @@ -381,32 +363,16 @@ "name": "stdout", "output_type": "stream", "text": [ - "0: orthos differ\n", - "68.7467899735\n", - "61.8893196136\n", - "1: orthos differ\n", - "86.3237109565\n", - "83.6925485182\n", - "2: orthos differ\n", - "60.6750720203\n", - "58.8531289111\n", - "3: orthos differ\n", - "72.6905727159\n", - "67.4115491701\n", - "4: orthos differ\n", - "87.2833822408\n", - "76.9079599519\n", + "0: same ortho\n", + "1: same ortho\n", + "2: same ortho\n", + "3: same ortho\n", + "4: same ortho\n", "5: same ortho\n", - "6: orthos differ\n", - "76.5085090591\n", - "72.9492134207\n", + "6: same ortho\n", "7: same ortho\n", - "8: orthos differ\n", - "78.9162659216\n", - "74.6909105965\n", - "9: orthos differ\n", - "59.3502878479\n", - "59.8294170866\n" + "8: same ortho\n", + "9: same ortho\n" ] } ], @@ -419,21 +385,427 @@ " else:\n", " print(f\"{n}: orthos differ\")\n", " print(ortho_anvy)\n", - " print(ortho_clse) " + " print(ortho_clse)" + ] + }, + { + "cell_type": "markdown", + "id": "d8dd1c1f", + "metadata": {}, + "source": [ + "## Testing the angles function" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 172, "id": "fe17ccd0", "metadata": {}, "outputs": [], + "source": [ + "import math\n", + "\n", + "import numpy as np\n", + "\n", + "\n", + "# Anastassia angle def\n", + "def get_interior_angle(a, b, c):\n", + " \"\"\"\n", + " Measure the angle between a-b, b-c (in degrees).\n", + " \"\"\"\n", + " ba = [a[0]-b[0],a[1]-b[1]]\n", + " bc = [c[0]-b[0],c[1]-b[1]]\n", + " # np.dot(ba, bc) # ba[0]*bc[0] + ba[1]*bc[1]\n", + " # np.linalg.norm(ba) # np.sqrt(ba[0]**2+ba[1]**2)\n", + " # np.linalg.norm(bc) # np.sqrt(bc[0]**2+bc[1]**2)\n", + " theta_rad = math.acos(np.dot(ba,bc)/(np.linalg.norm(ba)*np.linalg.norm(bc)))\n", + " theta_deg = np.degrees(theta_rad)\n", + " if theta_deg > 90:\n", + " theta_deg = 180 - theta_deg\n", + " return theta_deg\n", + "\n", + "# Clément angle def\n", + "def angle(a, b):\n", + " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", + " if angle > 90:\n", + " angle = 180 - angle\n", + " return angle" + ] + }, + { + "cell_type": "code", + "execution_count": 173, + "id": "a11251c9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0.])" + ] + }, + "execution_count": 173, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vectors = [[np.cos(np.radians(deg)), np.sin(np.radians(deg))] for deg in range(360)]\n", + "angles_clse = np.array([round(angle(vectors[0], vectors[i]), 8) for i in range(1, 360)])\n", + "angles_anvy = np.array([round(get_interior_angle(vectors[0], [0,0], vectors[i]), 5) for i in range(1, 360)])\n", + "angles_clse - angles_anvy" + ] + }, + { + "cell_type": "markdown", + "id": "b034b463", + "metadata": {}, + "source": [ + "Both angle function work well and similarly if receiving the same inputs (with different formalism but still), so issue before !" + ] + }, + { + "cell_type": "code", + "execution_count": 174, + "id": "b7eabac6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0.])" + ] + }, + "execution_count": 174, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vectors = np.array([[np.cos(np.radians(deg)), np.sin(np.radians(deg))] for deg in range(360)]) + 183049\n", + "angles_clse = np.array([round(angle(vectors[0], vectors[i]), 5) for i in range(1, 360)])\n", + "angles_anvy = np.array([round(get_interior_angle(vectors[0], [0,0], vectors[i]), 5) for i in range(1, 360)])\n", + "angles_clse - angles_anvy" + ] + }, + { + "cell_type": "code", + "execution_count": 175, + "id": "95b0e4cc", + "metadata": {}, + "outputs": [], + "source": [ + "for edge in G_anvy.edges:\n", + " assert G_anvy.edges[edge][\"geometry\"] == G_clse.edges[edge][\"geometry\"], \"Geoms differ\"\n", + " angles_anvy = [round(angle, 10) for angle in sorted(G_anvy.edges[edge][\"angles\"])]\n", + " angles_clse = [round(angle, 10) for angle in sorted(G_clse.edges[edge][\"angles\"])]\n", + " if angles_anvy != angles_clse:\n", + " print(\"Angles differ:\")\n", + " print(angles_anvy)\n", + " print(angles_clse)\n", + " print(G_anvy.nodes[edge[0]])\n", + " print(G_anvy.nodes[edge[1]])\n", + " print(G_clse.nodes[edge[0]])\n", + " print(G_clse.nodes[edge[1]])\n", + " print(\"\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 176, + "id": "f84c0968", + "metadata": {}, + "outputs": [], + "source": [ + "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", + "# Clean data\n", + "streets = momepy.remove_false_nodes(streets)\n", + "streets[\"edge_id\"] = streets.index\n", + "# Transform into primal graph\n", + "G_primal = momepy.gdf_to_nx(streets, approach=\"primal\", preserve_index=True)\n", + "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 177, + "id": "59443a81", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "e1s2 ((1603413.2063240695, 6464228.730248732), (1603585.6402153103, 6464428.773867372), 0)\n", + "e2s2 ((1603413.2063240695, 6464228.730248732), (1603363.557831175, 6464031.88480676), 0)\n", + "e1s1 ((1603413.2063240695, 6464228.730248732), (1603226.9576840235, 6464160.158361825), 0)\n", + "[(1603413.2063240695, 6464228.730248732), (1603274.457710744, 6464178.659351781), (1603226.9576840235, 6464160.158361825)] [(1603585.6402153103, 6464428.773867372), (1603413.2063240695, 6464228.730248732)] [(1603363.557831175, 6464031.88480676), (1603376.5042879563, 6464085.530021086), (1603413.2063240695, 6464228.730248732)]\n" + ] + } + ], + "source": [ + "for e in G_primal.edges((1603413.2063240695, 6464228.730248732), keys=True):\n", + " if G_primal.edges[e][\"edge_id\"] == 4:\n", + " print(\"e1s1\", e)\n", + " e1s1 = G_primal.edges[e][\"geometry\"]\n", + " elif G_primal.edges[e][\"edge_id\"] == 0:\n", + " print(\"e1s2\", e)\n", + " e1s2 = G_primal.edges[e][\"geometry\"]\n", + " elif G_primal.edges[e][\"edge_id\"] == 3:\n", + " print(\"e2s2\", e)\n", + " e2s2 = G_primal.edges[e][\"geometry\"]\n", + "print(e1s1.coords[:], e1s2.coords[:], e2s2.coords[:])" + ] + }, + { + "cell_type": "code", + "execution_count": 178, + "id": "7b9e8d0e", + "metadata": {}, + "outputs": [], + "source": [ + "e1s1_geom = e1s1.coords[:2]\n", + "e1s2_geom = e1s2.coords[:2]\n", + "e2s2_geom = e2s2.coords[-2:]" + ] + }, + { + "cell_type": "code", + "execution_count": 179, + "id": "0da0e679", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(29.396028363390087)" + ] + }, + "execution_count": 179, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_interior_angle(e1s1_geom[1], e1s1_geom[0], e1s2_geom[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "id": "c1ab91cd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(29.396028363390094)" + ] + }, + "execution_count": 180, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "angle(np.array(e1s1_geom[1]) - np.array(e1s1_geom[0]), np.array(e1s2_geom[1]) - np.array(e1s2_geom[0]))" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "id": "9ccbe4d5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(29.396028363390087)" + ] + }, + "execution_count": 181, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "angle(np.array(e1s1_geom[0]) - np.array(e1s1_geom[1]), np.array(e1s2_geom[1]) - np.array(e1s2_geom[0]))" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "id": "5843905b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(29.396028363390094)" + ] + }, + "execution_count": 182, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "angle(np.array(e1s1_geom[0]) - np.array(e1s1_geom[1]), np.array(e1s2_geom[0]) - np.array(e1s2_geom[1]))" + ] + }, + { + "cell_type": "code", + "execution_count": 183, + "id": "6d0ae741", + "metadata": {}, + "outputs": [], + "source": [ + "def find_geom(linestring, point):\n", + " if point == linestring.coords[0]:\n", + " geom = [np.array(val) for val in linestring.coords[:2]]\n", + " else:\n", + " geom = [np.array(val) for val in linestring.coords[-2:]]\n", + " return np.array(geom[0] - geom[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "id": "d489cd28", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([138.74861333, 50.07089695])" + ] + }, + "execution_count": 184, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "find_geom(e1s1, (1603413.2063240695, 6464228.730248732))" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "id": "0e7e6b53", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([138.74861333, 50.07089695])" + ] + }, + "execution_count": 185, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.array(e1s1_geom[0]) - np.array(e1s1_geom[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 186, + "id": "8dfaabd1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([172.43389124, 200.04361864])" + ] + }, + "execution_count": 186, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.array(e1s2_geom[0]) - np.array(e1s2_geom[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 187, + "id": "d9880de6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([172.43389124, 200.04361864])" + ] + }, + "execution_count": 187, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "find_geom(e1s2, (1603413.2063240695, 6464228.730248732))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6c829f65", + "metadata": {}, + "outputs": [], "source": [] } ], "metadata": { "kernelspec": { - "display_name": "simplification", + "display_name": "momepy_dev", "language": "python", "name": "python3" }, @@ -447,7 +819,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.12.10" } }, "nbformat": 4, From d8a7b09dd0339a467d7e3654f1786dec03246c20 Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Tue, 27 May 2025 16:09:36 +0200 Subject: [PATCH 16/27] Add comparison function on osmnx graph --- momepy/strokegraph_clse.ipynb | 486 +++---- momepy/strokegraph_function_compare.ipynb | 1474 +++++++++++++++++++++ 2 files changed, 1677 insertions(+), 283 deletions(-) create mode 100644 momepy/strokegraph_function_compare.ipynb diff --git a/momepy/strokegraph_clse.ipynb b/momepy/strokegraph_clse.ipynb index 8136c362..6e334fa9 100644 --- a/momepy/strokegraph_clse.ipynb +++ b/momepy/strokegraph_clse.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 110, + "execution_count": 133, "metadata": {}, "outputs": [], "source": [ @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 111, + "execution_count": 134, "metadata": {}, "outputs": [], "source": [ @@ -35,105 +35,88 @@ }, { "cell_type": "code", - "execution_count": 112, - "metadata": {}, - "outputs": [], - "source": [ - "# Clean data\n", - "streets = momepy.remove_false_nodes(streets)\n", - "# Transform into primal graph\n", - "G_primal = momepy.gdf_to_nx(streets, approach=\"primal\", preserve_index=True)\n", - "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)\n", - "# Use COINS on primal graph edges\n", - "coins = momepy.COINS(lines_primal)\n", - "# List the stroke for each edge\n", - "stroke_attribute = coins.stroke_attribute()\n", - "# List each edge for each stroke\n", - "stroke_gdf = coins.stroke_gdf()\n", - "stroke_gdf[\"edge_ids\"] = [stroke_attribute[stroke_attribute == stroke_id].index.values for stroke_id in stroke_gdf.index.values]\n", - "# Add stroke ID to each edge\n", - "nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[G_primal.edges[e][\"index_position\"]]) for e in G_primal.edges}, \"stroke_id\")\n", - "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 113, - "metadata": {}, - "outputs": [], - "source": [ - "# stroke_gdf_viz = stroke_gdf.copy()\n", - "# stroke_gdf_viz[\"id\"] = stroke_gdf_viz.index\n", - "# lines_primal_viz = lines_primal.copy()\n", - "# lines_primal_viz[\"edge_id\"] = lines_primal.index\n", - "# m = stroke_gdf_viz.explore(tiles=\"cartodb-positron\", column=\"id\", cmap=\"Set2\", name=\"strokes\")\n", - "# lines_primal_viz.explore(m=m, column=\"stroke_id\", name = \"lines\", cmap=\"Set2\")\n", - "# folium.LayerControl().add_to(m)\n", - "# m" - ] - }, - { - "cell_type": "code", - "execution_count": 114, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.microsoft.datawrangler.viewer.v0+json": { - "columns": [ - { - "name": "index", - "rawType": "object", - "type": "string" - }, - { - "name": "0", - "rawType": "object", - "type": "unknown" - } - ], - "ref": "c36ef621-3a0c-42bc-9e3e-27d59609b574", - "rows": [ - [ - "n_segments", - "8" - ], - [ - "geometry", - "LINESTRING (1603278.8993584276 6463669.185595578, 1603283.7306243288 6463690.028353462, 1603314.4436718386 6463822.409720818, 1603317.7832565615 6463836.796863219, 1603361.0308787343 6464021.107210826, 1603363.557831175 6464031.88480676, 1603376.5042879563 6464085.530021086, 1603413.2063240695 6464228.730248732, 1603585.6402153103 6464428.773867372)" - ], - [ - "edge_ids", - "[ 0 3 15 27]" - ] - ], - "shape": { - "columns": 1, - "rows": 3 - } - }, - "text/plain": [ - "n_segments 8\n", - "geometry LINESTRING (1603278.8993584276 6463669.1855955...\n", - "edge_ids [0, 3, 15, 27]\n", - "Name: 0, dtype: object" - ] - }, - "execution_count": 114, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "stroke_gdf.loc[stroke_gdf.index.values[0]]" - ] - }, - { - "cell_type": "code", - "execution_count": 115, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ + "def make_stroke_graph(gdf, compute_metric=True, output=\"dataframe\"):\n", + " if output not in [\"dataframe\", \"graph\"]:\n", + " raise ValueError(\"output need to be either dataframe or graph\")\n", + " # Clean data\n", + " gdf = momepy.remove_false_nodes(gdf)\n", + " # Transform into primal graph\n", + " G_primal = momepy.gdf_to_nx(gdf, approach=\"primal\", preserve_index=True)\n", + " lines_primal = momepy.nx_to_gdf(G_primal, points=False, lines=True)\n", + " # Use COINS on primal graph edges\n", + " coins = momepy.COINS(lines_primal)\n", + " # List the stroke for each edge\n", + " stroke_attribute = coins.stroke_attribute()\n", + " # List each edge for each stroke\n", + " stroke_gdf = coins.stroke_gdf()\n", + " stroke_gdf[\"edge_ids\"] = [stroke_attribute[stroke_attribute == stroke_id].index.values for stroke_id in stroke_gdf.index.values]\n", + " # Add stroke ID to each edge\n", + " nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[G_primal.edges[e][\"index_position\"]]) for e in G_primal.edges}, \"stroke_id\")\n", + " # Create stroke graph\n", + " G_stroke = nx.Graph()\n", + " G_stroke.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", + " # Create a node for each stroke with the right features\n", + " G_stroke.add_nodes_from([[int(idx), {(attr if attr != \"geometry\" else \"geometry_stroke\"):stroke_gdf.loc[idx][attr] for attr in list(stroke_gdf)}] for idx in stroke_gdf.index.values])\n", + " # For all node, put its geometry at the center of the LineString\n", + " for n in G_stroke.nodes:\n", + " G_stroke.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", + " G_stroke.nodes[n][\"x\"] = G_stroke.nodes[n][\"geometry\"].xy[0]\n", + " G_stroke.nodes[n][\"y\"] = G_stroke.nodes[n][\"geometry\"].xy[1]\n", + " G_stroke.nodes[n][\"length\"] = G_stroke.nodes[n][\"geometry_stroke\"].length\n", + " # Find strokes intersecting\n", + " for n in G_primal.nodes:\n", + " strokes_present = [G_primal.edges[e][\"stroke_id\"] for e in G_primal.edges(n, keys=True)]\n", + " # If strokes intersecting, add the edge if not already present\n", + " if len(set(strokes_present)) > 1:\n", + " for u, v in combinations(set(strokes_present), 2):\n", + " # Find all edges touching the node for both strokes checked\n", + " edges_u = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == u]\n", + " edges_v = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == v]\n", + " angle_list = []\n", + " angle_dict = {}\n", + " # Choose the smallest list as number of angles kept\n", + " chosen, other = sorted([edges_u, edges_v], key=len)\n", + " # Find the angles\n", + " for ce, oe in list(product(chosen, other)):\n", + " point = [G_primal.nodes[n][\"x\"], G_primal.nodes[n][\"y\"]]\n", + " gc = find_geom(G_primal.edges[ce][\"geometry\"], point)\n", + " go = find_geom(G_primal.edges[oe][\"geometry\"], point)\n", + " if ce in angle_dict:\n", + " angle_dict[ce].append(angle(gc, go))\n", + " else:\n", + " angle_dict[ce]= [angle(gc, go)]\n", + " # Keep the smallest angles\n", + " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", + " if G_stroke.has_edge(u, v):\n", + " G_stroke.edges[u, v][\"angles\"] += angle_list\n", + " G_stroke.edges[u, v][\"number_connections\"] = len(G_stroke.edges[u, v][\"angles\"])\n", + " else:\n", + " G_stroke.add_edge(u, v, geometry = shapely.LineString([G_stroke.nodes[u][\"geometry\"], G_stroke.nodes[v][\"geometry\"]]), number_connections=len(angle_list), angles=angle_list)\n", + " if compute_metric:\n", + " nx.set_node_attributes(G_stroke, nx.betweenness_centrality(G_stroke), \"stroke_betweenness\")\n", + " nx.set_node_attributes(G_stroke, nx.closeness_centrality(G_stroke), \"stroke_closeness\")\n", + " nx.set_node_attributes(G_stroke, dict(nx.degree(G_stroke)), \"stroke_degree\")\n", + " for n in G_stroke.nodes:\n", + " G_stroke.nodes[n][\"stroke_connectivity\"] = sum([G_stroke.edges[e][\"number_connections\"] for e in G_stroke.edges(n)])\n", + " G_stroke.nodes[n][\"stroke_access\"] = G_stroke.nodes[n][\"stroke_connectivity\"] - G_stroke.nodes[n][\"stroke_degree\"]\n", + " angles = [val for e in G_stroke.edges(n) if G_stroke.edges[e][\"angles\"] for val in G_stroke.edges[e][\"angles\"]]\n", + " G_stroke.nodes[n][\"stroke_orthogonality\"] = sum(angles) / G_stroke.nodes[n][\"stroke_connectivity\"]\n", + " G_stroke.nodes[n][\"stroke_spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]\n", + " if output == \"dataframe\":\n", + " return momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n", + " elif output == \"graph\":\n", + " return G_stroke\n", + "\n", + "def angle(a, b):\n", + " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", + " if angle > 90:\n", + " angle = 180 - angle\n", + " return angle\n", + "\n", "def find_geom(linestring, point):\n", " if point == list(linestring.coords[0]):\n", " geom = [np.array(val) for val in linestring.coords[:2]]\n", @@ -144,82 +127,19 @@ }, { "cell_type": "code", - "execution_count": 116, - "metadata": {}, - "outputs": [], - "source": [ - "def angle(a, b):\n", - " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", - " if angle > 90:\n", - " angle = 180 - angle\n", - " return angle" - ] - }, - { - "cell_type": "code", - "execution_count": 117, + "execution_count": 136, "metadata": {}, "outputs": [], "source": [ - "# Create stroke graph\n", - "G_stroke = nx.Graph()\n", - "G_stroke.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", - "# Create a node for each stroke with the right features\n", - "G_stroke.add_nodes_from([[int(idx), {(attr if attr != \"geometry\" else \"geometry_stroke\"):stroke_gdf.loc[idx][attr] for attr in list(stroke_gdf)}] for idx in stroke_gdf.index.values])\n", - "# For all node, put its geometry at the center of the LineString\n", - "for n in G_stroke.nodes:\n", - " G_stroke.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", - " G_stroke.nodes[n][\"x\"] = G_stroke.nodes[n][\"geometry\"].xy[0]\n", - " G_stroke.nodes[n][\"y\"] = G_stroke.nodes[n][\"geometry\"].xy[1]\n", - " G_stroke.nodes[n][\"length\"] = G_stroke.nodes[n][\"geometry_stroke\"].length\n", - "# Find strokes intersecting\n", - "for n in G_primal.nodes:\n", - " strokes_present = [G_primal.edges[e][\"stroke_id\"] for e in G_primal.edges(n, keys=True)]\n", - " # If strokes intersecting, add the edge if not already present\n", - " if len(set(strokes_present)) > 1:\n", - " for u, v in combinations(set(strokes_present), 2):\n", - " # Find all edges touching the node for both strokes checked\n", - " edges_u = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == u]\n", - " edges_v = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == v]\n", - " angle_list = []\n", - " angle_dict = {}\n", - " # Choose the smallest list as number of angles kept\n", - " chosen, other = sorted([edges_u, edges_v], key=len)\n", - " # Find the angles\n", - " for ce, oe in list(product(chosen, other)):\n", - " point = [G_primal.nodes[n][\"x\"], G_primal.nodes[n][\"y\"]]\n", - " gc = find_geom(G_primal.edges[ce][\"geometry\"], point)\n", - " go = find_geom(G_primal.edges[oe][\"geometry\"], point)\n", - " if ce in angle_dict:\n", - " angle_dict[ce].append(angle(gc, go))\n", - " else:\n", - " angle_dict[ce]= [angle(gc, go)]\n", - " # Keep the smallest angles\n", - " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", - " # TODO solve angles\n", - " if G_stroke.has_edge(u, v):\n", - " G_stroke.edges[u, v][\"angles\"] += angle_list\n", - " G_stroke.edges[u, v][\"number_connections\"] = len(G_stroke.edges[u, v][\"angles\"])\n", - " else:\n", - " G_stroke.add_edge(u, v, geometry = shapely.LineString([G_stroke.nodes[u][\"geometry\"], G_stroke.nodes[v][\"geometry\"]]), number_connections=len(angle_list), angles=angle_list)" + "G_stroke = make_stroke_graph(streets, compute_metric=True, output=\"graph\")" ] }, { "cell_type": "code", - "execution_count": 118, + "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "nx.set_node_attributes(G_stroke, nx.betweenness_centrality(G_stroke), \"stroke_betweenness\")\n", - "nx.set_node_attributes(G_stroke, nx.closeness_centrality(G_stroke), \"stroke_closeness\")\n", - "nx.set_node_attributes(G_stroke, dict(nx.degree(G_stroke)), \"stroke_degree\")\n", - "for n in G_stroke.nodes:\n", - " G_stroke.nodes[n][\"stroke_connectivity\"] = sum([G_stroke.edges[e][\"number_connections\"] for e in G_stroke.edges(n)])\n", - " G_stroke.nodes[n][\"stroke_access\"] = G_stroke.nodes[n][\"stroke_connectivity\"] - G_stroke.nodes[n][\"stroke_degree\"]\n", - " angles = [val for e in G_stroke.edges(n) if G_stroke.edges[e][\"angles\"] for val in G_stroke.edges[e][\"angles\"]]\n", - " G_stroke.nodes[n][\"stroke_orthogonality\"] = sum(angles) / G_stroke.nodes[n][\"stroke_connectivity\"]\n", - " G_stroke.nodes[n][\"stroke_spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]" - ] + "source": [] }, { "cell_type": "markdown", @@ -230,7 +150,7 @@ }, { "cell_type": "code", - "execution_count": 119, + "execution_count": 137, "metadata": {}, "outputs": [], "source": [ @@ -248,7 +168,7 @@ }, { "cell_type": "code", - "execution_count": 120, + "execution_count": 138, "metadata": {}, "outputs": [ { @@ -289,7 +209,7 @@ " <meta name="viewport" content="width=device-width,\n", " initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />\n", " <style>\n", - " #map_f485c7cefc845a343e7d2e56682f6348 {\n", + " #map_0e2c896b366477a676b80af2d1218430 {\n", " position: relative;\n", " width: 100.0%;\n", " height: 100.0%;\n", @@ -384,14 +304,14 @@ "<body>\n", " \n", " \n", - " <div class="folium-map" id="map_f485c7cefc845a343e7d2e56682f6348" ></div>\n", + " <div class="folium-map" id="map_0e2c896b366477a676b80af2d1218430" ></div>\n", " \n", "</body>\n", "<script>\n", " \n", " \n", - " var map_f485c7cefc845a343e7d2e56682f6348 = L.map(\n", - " "map_f485c7cefc845a343e7d2e56682f6348",\n", + " var map_0e2c896b366477a676b80af2d1218430 = L.map(\n", + " "map_0e2c896b366477a676b80af2d1218430",\n", " {\n", " center: [50.102935750000015, 14.403062600000004],\n", " crs: L.CRS.EPSG3857,\n", @@ -403,13 +323,13 @@ "\n", " }\n", " );\n", - " L.control.scale().addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " L.control.scale().addTo(map_0e2c896b366477a676b80af2d1218430);\n", "\n", " \n", "\n", " \n", " \n", - " var tile_layer_75a780ad99b6f7bd559c3dfd418bd85f = L.tileLayer(\n", + " var tile_layer_764af7bd73b97e22bfeaab9072744982 = L.tileLayer(\n", " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",\n", " {\n", " "minZoom": 0,\n", @@ -426,16 +346,16 @@ " );\n", " \n", " \n", - " tile_layer_75a780ad99b6f7bd559c3dfd418bd85f.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " tile_layer_764af7bd73b97e22bfeaab9072744982.addTo(map_0e2c896b366477a676b80af2d1218430);\n", " \n", " \n", - " map_f485c7cefc845a343e7d2e56682f6348.fitBounds(\n", + " map_0e2c896b366477a676b80af2d1218430.fitBounds(\n", " [[50.10007700000001, 14.398981599999999], [50.10579450000001, 14.407143600000008]],\n", " {}\n", " );\n", " \n", " \n", - " function geo_json_a75521f1f7e4c097815fc719c81c67c1_styler(feature) {\n", + " function geo_json_f4d755600a90a349640574af8bd3bbbf_styler(feature) {\n", " switch(feature.id) {\n", " case "0": \n", " return {"color": "#1f77b4", "fillColor": "#1f77b4", "fillOpacity": 0.5, "weight": 2};\n", @@ -459,54 +379,54 @@ " return {"color": "#17becf", "fillColor": "#17becf", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_a75521f1f7e4c097815fc719c81c67c1_highlighter(feature) {\n", + " function geo_json_f4d755600a90a349640574af8bd3bbbf_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_a75521f1f7e4c097815fc719c81c67c1_pointToLayer(feature, latlng) {\n", + " function geo_json_f4d755600a90a349640574af8bd3bbbf_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_a75521f1f7e4c097815fc719c81c67c1_styler(feature)\n", + " let style = geo_json_f4d755600a90a349640574af8bd3bbbf_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_a75521f1f7e4c097815fc719c81c67c1_onEachFeature(feature, layer) {\n", + " function geo_json_f4d755600a90a349640574af8bd3bbbf_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_a75521f1f7e4c097815fc719c81c67c1.resetStyle(e.target);\n", + " geo_json_f4d755600a90a349640574af8bd3bbbf.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_a75521f1f7e4c097815fc719c81c67c1_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_f4d755600a90a349640574af8bd3bbbf_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_a75521f1f7e4c097815fc719c81c67c1 = L.geoJson(null, {\n", - " onEachFeature: geo_json_a75521f1f7e4c097815fc719c81c67c1_onEachFeature,\n", + " var geo_json_f4d755600a90a349640574af8bd3bbbf = L.geoJson(null, {\n", + " onEachFeature: geo_json_f4d755600a90a349640574af8bd3bbbf_onEachFeature,\n", " \n", - " style: geo_json_a75521f1f7e4c097815fc719c81c67c1_styler,\n", - " pointToLayer: geo_json_a75521f1f7e4c097815fc719c81c67c1_pointToLayer,\n", + " style: geo_json_f4d755600a90a349640574af8bd3bbbf_styler,\n", + " pointToLayer: geo_json_f4d755600a90a349640574af8bd3bbbf_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_a75521f1f7e4c097815fc719c81c67c1_add (data) {\n", - " geo_json_a75521f1f7e4c097815fc719c81c67c1\n", + " function geo_json_f4d755600a90a349640574af8bd3bbbf_add (data) {\n", + " geo_json_f4d755600a90a349640574af8bd3bbbf\n", " .addData(data);\n", " }\n", - " geo_json_a75521f1f7e4c097815fc719c81c67c1_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#1f77b4", "edge_ids": "[ 0 3 15 27]", "id": 0, "n_segments": 8, "stroke_group": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ff7f0e", "edge_ids": "[ 1 12 14 25]", "id": 1, "n_segments": 19, "stroke_group": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#2ca02c", "edge_ids": "[ 2 11 28 30]", "id": 2, "n_segments": 17, "stroke_group": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#d62728", "edge_ids": "[4 5 6]", "id": 3, "n_segments": 5, "stroke_group": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#9467bd", "edge_ids": "[ 7 8 9 13 21 22 24]", "id": 4, "n_segments": 14, "stroke_group": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#8c564b", "edge_ids": "[10]", "id": 5, "n_segments": 2, "stroke_group": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e377c2", "edge_ids": "[16 17 18 23 29]", "id": 6, "n_segments": 13, "stroke_group": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#7f7f7f", "edge_ids": "[19]", "id": 7, "n_segments": 3, "stroke_group": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#bcbd22", "edge_ids": "[20]", "id": 8, "n_segments": 3, "stroke_group": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#17becf", "edge_ids": "[26]", "id": 9, "n_segments": 5, "stroke_group": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_f4d755600a90a349640574af8bd3bbbf_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.402499399999995, 50.100328799999986, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "#1f77b4", "edge_ids": "[ 0 3 15 27]", "id": 0, "n_segments": 8, "stroke_group": 0}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1021532, 14.405011000000012, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "#ff7f0e", "edge_ids": "[ 1 12 14 25]", "id": 1, "n_segments": 19, "stroke_group": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10327799999998, 14.40648620000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999], [14.405966199999993, 50.10428099999998], [14.406067899999996, 50.10421749999998], [14.406109, 50.1041169], [14.406260999999994, 50.103803500000005], [14.40648620000001, 50.103294399999996], [14.405552600000002, 50.10327799999998], [14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "#2ca02c", "edge_ids": "[ 2 11 28 30]", "id": 2, "n_segments": 17, "stroke_group": 2}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "#d62728", "edge_ids": "[4 5 6]", "id": 3, "n_segments": 5, "stroke_group": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.10099319999999, 14.407143600000008, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998], [14.401945599999989, 50.1014274], [14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "#9467bd", "edge_ids": "[ 7 8 9 13 21 22 24]", "id": 4, "n_segments": 14, "stroke_group": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "#8c564b", "edge_ids": "[10]", "id": 5, "n_segments": 2, "stroke_group": 5}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "#e377c2", "edge_ids": "[16 17 18 23 29]", "id": 6, "n_segments": 13, "stroke_group": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "#7f7f7f", "edge_ids": "[19]", "id": 7, "n_segments": 3, "stroke_group": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "#bcbd22", "edge_ids": "[20]", "id": 8, "n_segments": 3, "stroke_group": 8}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "#17becf", "edge_ids": "[26]", "id": 9, "n_segments": 5, "stroke_group": 9}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_a75521f1f7e4c097815fc719c81c67c1.bindTooltip(\n", + " geo_json_f4d755600a90a349640574af8bd3bbbf.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -533,46 +453,46 @@ "});\n", " \n", " \n", - " geo_json_a75521f1f7e4c097815fc719c81c67c1.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " geo_json_f4d755600a90a349640574af8bd3bbbf.addTo(map_0e2c896b366477a676b80af2d1218430);\n", " \n", " \n", - " var color_map_bfea797b9645266490881d1e7e916cb4 = {};\n", + " var color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0 = {};\n", "\n", " \n", - " color_map_bfea797b9645266490881d1e7e916cb4.color = d3.scale.threshold()\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.color = d3.scale.threshold()\n", " .domain([0.0, 0.018036072144288578, 0.036072144288577156, 0.05410821643286573, 0.07214428857715431, 0.09018036072144289, 0.10821643286573146, 0.12625250501002003, 0.14428857715430862, 0.1623246492985972, 0.18036072144288579, 0.19839679358717435, 0.21643286573146292, 0.23446893787575152, 0.25250501002004005, 0.27054108216432865, 0.28857715430861725, 0.3066132264529058, 0.3246492985971944, 0.342685370741483, 0.36072144288577157, 0.3787575150300601, 0.3967935871743487, 0.4148296593186373, 0.43286573146292584, 0.45090180360721444, 0.46893787575150303, 0.48697394789579157, 0.5050100200400801, 0.5230460921843687, 0.5410821643286573, 0.5591182364729459, 0.5771543086172345, 0.5951903807615231, 0.6132264529058116, 0.6312625250501002, 0.6492985971943888, 0.6673346693386774, 0.685370741482966, 0.7034068136272545, 0.7214428857715431, 0.7394789579158316, 0.7575150300601202, 0.7755511022044088, 0.7935871743486974, 0.811623246492986, 0.8296593186372746, 0.8476953907815631, 0.8657314629258517, 0.8837675350701403, 0.9018036072144289, 0.9198396793587175, 0.9378757515030061, 0.9559118236472945, 0.9739478957915831, 0.9919839679358717, 1.0100200400801602, 1.028056112224449, 1.0460921843687374, 1.0641282565130261, 1.0821643286573146, 1.1002004008016033, 1.1182364729458918, 1.1362725450901803, 1.154308617234469, 1.1723446893787575, 1.1903807615230462, 1.2084168336673347, 1.2264529058116231, 1.2444889779559118, 1.2625250501002003, 1.280561122244489, 1.2985971943887775, 1.3166332665330662, 1.3346693386773547, 1.3527054108216432, 1.370741482965932, 1.3887775551102204, 1.406813627254509, 1.4248496993987976, 1.4428857715430863, 1.4609218436873748, 1.4789579158316633, 1.496993987975952, 1.5150300601202404, 1.5330661322645291, 1.5511022044088176, 1.5691382765531061, 1.5871743486973948, 1.6052104208416833, 1.623246492985972, 1.6412825651302605, 1.6593186372745492, 1.6773547094188377, 1.6953907815631262, 1.7134268537074149, 1.7314629258517034, 1.749498997995992, 1.7675350701402806, 1.785571142284569, 1.8036072144288577, 1.8216432865731462, 1.839679358717435, 1.8577154308617234, 1.8757515030060121, 1.8937875751503006, 1.911823647294589, 1.9298597194388778, 1.9478957915831663, 1.965931863727455, 1.9839679358717435, 2.002004008016032, 2.0200400801603204, 2.038076152304609, 2.056112224448898, 2.0741482965931866, 2.092184368737475, 2.1102204408817635, 2.1282565130260522, 2.1462925851703405, 2.164328657314629, 2.182364729458918, 2.2004008016032066, 2.218436873747495, 2.2364729458917836, 2.2545090180360723, 2.2725450901803605, 2.2905811623246493, 2.308617234468938, 2.3266533066132267, 2.344689378757515, 2.3627254509018036, 2.3807615230460923, 2.3987975951903806, 2.4168336673346693, 2.434869739478958, 2.4529058116232463, 2.470941883767535, 2.4889779559118237, 2.5070140280561124, 2.5250501002004007, 2.5430861723446894, 2.561122244488978, 2.5791583166332663, 2.597194388777555, 2.6152304609218437, 2.6332665330661325, 2.6513026052104207, 2.6693386773547094, 2.687374749498998, 2.7054108216432864, 2.723446893787575, 2.741482965931864, 2.7595190380761525, 2.7775551102204408, 2.7955911823647295, 2.813627254509018, 2.8316633266533064, 2.849699398797595, 2.867735470941884, 2.8857715430861726, 2.903807615230461, 2.9218436873747495, 2.9398797595190382, 2.9579158316633265, 2.975951903807615, 2.993987975951904, 3.012024048096192, 3.030060120240481, 3.0480961923847696, 3.0661322645290583, 3.0841683366733466, 3.1022044088176353, 3.120240480961924, 3.1382765531062122, 3.156312625250501, 3.1743486973947896, 3.1923847695390783, 3.2104208416833666, 3.2284569138276553, 3.246492985971944, 3.2645290581162323, 3.282565130260521, 3.3006012024048097, 3.3186372745490984, 3.3366733466933867, 3.3547094188376754, 3.372745490981964, 3.3907815631262523, 3.408817635270541, 3.4268537074148298, 3.444889779559118, 3.4629258517034067, 3.4809619238476954, 3.498997995991984, 3.5170340681362724, 3.535070140280561, 3.55310621242485, 3.571142284569138, 3.5891783567134268, 3.6072144288577155, 3.625250501002004, 3.6432865731462925, 3.661322645290581, 3.67935871743487, 3.697394789579158, 3.715430861723447, 3.7334669338677355, 3.7515030060120242, 3.7695390781563125, 3.787575150300601, 3.80561122244489, 3.823647294589178, 3.841683366733467, 3.8597194388777556, 3.8777555110220443, 3.8957915831663326, 3.9138276553106213, 3.93186372745491, 3.9498997995991982, 3.967935871743487, 3.9859719438877756, 4.004008016032064, 4.022044088176353, 4.040080160320641, 4.05811623246493, 4.076152304609218, 4.094188376753507, 4.112224448897796, 4.130260521042084, 4.148296593186373, 4.166332665330661, 4.18436873747495, 4.202404809619239, 4.220440881763527, 4.238476953907815, 4.2565130260521045, 4.274549098196393, 4.292585170340681, 4.31062124248497, 4.328657314629258, 4.346693386773547, 4.364729458917836, 4.382765531062124, 4.400801603206413, 4.4188376753507015, 4.43687374749499, 4.454909819639279, 4.472945891783567, 4.490981963927855, 4.509018036072145, 4.527054108216433, 4.545090180360721, 4.56312625250501, 4.5811623246492985, 4.599198396793587, 4.617234468937876, 4.635270541082164, 4.653306613226453, 4.671342685370742, 4.68937875751503, 4.707414829659319, 4.725450901803607, 4.7434869739478955, 4.761523046092185, 4.779559118236473, 4.797595190380761, 4.81563126252505, 4.833667334669339, 4.851703406813627, 4.869739478957916, 4.887775551102204, 4.905811623246493, 4.923847695390782, 4.94188376753507, 4.959919839679359, 4.977955911823647, 4.995991983967936, 5.014028056112225, 5.032064128256513, 5.050100200400801, 5.0681362725450905, 5.086172344689379, 5.104208416833667, 5.122244488977956, 5.140280561122244, 5.158316633266533, 5.176352705410822, 5.19438877755511, 5.212424849699399, 5.2304609218436875, 5.248496993987976, 5.266533066132265, 5.284569138276553, 5.302605210420841, 5.320641282565131, 5.338677354709419, 5.356713426853707, 5.374749498997996, 5.3927855711422845, 5.410821643286573, 5.428857715430862, 5.44689378757515, 5.4649298597194385, 5.482965931863728, 5.501002004008016, 5.519038076152305, 5.537074148296593, 5.5551102204408815, 5.573146292585171, 5.591182364729459, 5.609218436873747, 5.627254509018036, 5.645290581162325, 5.663326653306613, 5.681362725450902, 5.69939879759519, 5.717434869739479, 5.735470941883768, 5.753507014028056, 5.771543086172345, 5.789579158316633, 5.807615230460922, 5.825651302605211, 5.843687374749499, 5.861723446893787, 5.8797595190380765, 5.897795591182365, 5.915831663326653, 5.933867735470942, 5.95190380761523, 5.969939879759519, 5.987975951903808, 6.006012024048096, 6.024048096192384, 6.0420841683366735, 6.060120240480962, 6.078156312625251, 6.096192384769539, 6.114228456913827, 6.132264529058117, 6.150300601202405, 6.168336673346693, 6.186372745490982, 6.2044088176352705, 6.222444889779559, 6.240480961923848, 6.258517034068136, 6.2765531062124245, 6.294589178356714, 6.312625250501002, 6.330661322645291, 6.348697394789579, 6.3667334669338675, 6.384769539078157, 6.402805611222445, 6.420841683366733, 6.438877755511022, 6.456913827655311, 6.474949899799599, 6.492985971943888, 6.511022044088176, 6.529058116232465, 6.547094188376754, 6.565130260521042, 6.58316633266533, 6.601202404809619, 6.619238476953908, 6.637274549098197, 6.655310621242485, 6.673346693386773, 6.6913827655310625, 6.709418837675351, 6.727454909819639, 6.745490981963928, 6.763527054108216, 6.781563126252505, 6.799599198396794, 6.817635270541082, 6.83567134268537, 6.8537074148296595, 6.871743486973948, 6.889779559118236, 6.907815631262525, 6.925851703406813, 6.943887775551103, 6.961923847695391, 6.979959919839679, 6.997995991983968, 7.0160320641282565, 7.034068136272545, 7.052104208416834, 7.070140280561122, 7.0881763527054105, 7.1062124248497, 7.124248496993988, 7.142284569138276, 7.160320641282565, 7.1783567134268536, 7.196392785571143, 7.214428857715431, 7.232464929859719, 7.250501002004008, 7.268537074148297, 7.286573146292585, 7.304609218436874, 7.322645290581162, 7.340681362725451, 7.35871743486974, 7.376753507014028, 7.394789579158316, 7.412825651302605, 7.430861723446894, 7.448897795591182, 7.466933867735471, 7.484969939879759, 7.5030060120240485, 7.521042084168337, 7.539078156312625, 7.557114228456914, 7.575150300601202, 7.593186372745491, 7.61122244488978, 7.629258517034068, 7.647294589178356, 7.6653306613226455, 7.683366733466934, 7.701402805611222, 7.719438877755511, 7.7374749498997994, 7.755511022044089, 7.773547094188377, 7.791583166332665, 7.809619238476954, 7.8276553106212425, 7.845691382765531, 7.86372745490982, 7.881763527054108, 7.8997995991983965, 7.917835671342686, 7.935871743486974, 7.953907815631262, 7.971943887775551, 7.98997995991984, 8.008016032064129, 8.026052104208416, 8.044088176352705, 8.062124248496994, 8.080160320641282, 8.098196392785571, 8.11623246492986, 8.134268537074147, 8.152304609218437, 8.170340681362726, 8.188376753507015, 8.206412825651302, 8.224448897795591, 8.24248496993988, 8.260521042084168, 8.278557114228457, 8.296593186372746, 8.314629258517034, 8.332665330661323, 8.350701402805612, 8.3687374749499, 8.386773547094188, 8.404809619238478, 8.422845691382765, 8.440881763527054, 8.458917835671343, 8.47695390781563, 8.49498997995992, 8.513026052104209, 8.531062124248496, 8.549098196392785, 8.567134268537075, 8.585170340681362, 8.603206412825651, 8.62124248496994, 8.639278557114228, 8.657314629258517, 8.675350701402806, 8.693386773547093, 8.711422845691382, 8.729458917835672, 8.74749498997996, 8.765531062124248, 8.783567134268537, 8.801603206412826, 8.819639278557114, 8.837675350701403, 8.855711422845692, 8.87374749498998, 8.891783567134269, 8.909819639278558, 8.927855711422845, 8.945891783567134, 8.963927855711423, 8.98196392785571, 9.0])\n", " .range(['#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#1f77b4ff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#ff7f0eff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#2ca02cff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#d62728ff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#9467bdff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#8c564bff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#e377c2ff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#7f7f7fff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#bcbd22ff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff', '#17becfff']);\n", " \n", "\n", - " color_map_bfea797b9645266490881d1e7e916cb4.x = d3.scale.linear()\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.x = d3.scale.linear()\n", " .domain([0.0, 9.0])\n", " .range([0, 450 - 50]);\n", "\n", - " color_map_bfea797b9645266490881d1e7e916cb4.legend = L.control({position: 'topright'});\n", - " color_map_bfea797b9645266490881d1e7e916cb4.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", - " color_map_bfea797b9645266490881d1e7e916cb4.legend.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.legend = L.control({position: 'topright'});\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return div};\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.legend.addTo(map_0e2c896b366477a676b80af2d1218430);\n", "\n", - " color_map_bfea797b9645266490881d1e7e916cb4.xAxis = d3.svg.axis()\n", - " .scale(color_map_bfea797b9645266490881d1e7e916cb4.x)\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.xAxis = d3.svg.axis()\n", + " .scale(color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.x)\n", " .orient("top")\n", " .tickSize(1)\n", " .tickValues([0.0, '', 1.8, '', 3.6, '', 5.4, '', 7.2, '', 9.0, '']);\n", "\n", - " color_map_bfea797b9645266490881d1e7e916cb4.svg = d3.select(".legend.leaflet-control").append("svg")\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.svg = d3.select(".legend.leaflet-control").append("svg")\n", " .attr("id", 'legend')\n", " .attr("width", 450)\n", " .attr("height", 40);\n", "\n", - " color_map_bfea797b9645266490881d1e7e916cb4.g = color_map_bfea797b9645266490881d1e7e916cb4.svg.append("g")\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.g = color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.svg.append("g")\n", " .attr("class", "key")\n", " .attr("fill", "black")\n", " .attr("transform", "translate(25,16)");\n", "\n", - " color_map_bfea797b9645266490881d1e7e916cb4.g.selectAll("rect")\n", - " .data(color_map_bfea797b9645266490881d1e7e916cb4.color.range().map(function(d, i) {\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.g.selectAll("rect")\n", + " .data(color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.color.range().map(function(d, i) {\n", " return {\n", - " x0: i ? color_map_bfea797b9645266490881d1e7e916cb4.x(color_map_bfea797b9645266490881d1e7e916cb4.color.domain()[i - 1]) : color_map_bfea797b9645266490881d1e7e916cb4.x.range()[0],\n", - " x1: i < color_map_bfea797b9645266490881d1e7e916cb4.color.domain().length ? color_map_bfea797b9645266490881d1e7e916cb4.x(color_map_bfea797b9645266490881d1e7e916cb4.color.domain()[i]) : color_map_bfea797b9645266490881d1e7e916cb4.x.range()[1],\n", + " x0: i ? color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.x(color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.color.domain()[i - 1]) : color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.x.range()[0],\n", + " x1: i < color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.color.domain().length ? color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.x(color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.color.domain()[i]) : color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.x.range()[1],\n", " z: d\n", " };\n", " }))\n", @@ -582,66 +502,66 @@ " .attr("width", function(d) { return d.x1 - d.x0; })\n", " .style("fill", function(d) { return d.z; });\n", "\n", - " color_map_bfea797b9645266490881d1e7e916cb4.g.call(color_map_bfea797b9645266490881d1e7e916cb4.xAxis).append("text")\n", + " color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.g.call(color_map_bfcb04b330852a1b8c5f0ec5e5fd90e0.xAxis).append("text")\n", " .attr("class", "caption")\n", " .attr("y", 21)\n", " .attr("fill", "black")\n", " .text("id");\n", " \n", - " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_styler(feature) {\n", + " function geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_highlighter(feature) {\n", + " function geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_pointToLayer(feature, latlng) {\n", + " function geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_styler(feature)\n", + " let style = geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_onEachFeature(feature, layer) {\n", + " function geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf.resetStyle(e.target);\n", + " geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf = L.geoJson(null, {\n", - " onEachFeature: geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_onEachFeature,\n", + " var geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2 = L.geoJson(null, {\n", + " onEachFeature: geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_onEachFeature,\n", " \n", - " style: geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_styler,\n", - " pointToLayer: geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_pointToLayer,\n", + " style: geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_styler,\n", + " pointToLayer: geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_add (data) {\n", - " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf\n", + " function geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_add (data) {\n", + " geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2\n", " .addData(data);\n", " }\n", - " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.40525490000001, 50.1047055, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [14.40525490000001, 50.1047055], "type": "Point"}, "id": "0", "properties": {"nodeID": 0, "x": 1603585.6402153103, "y": 6464428.773867372}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.1035529, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [14.403705899999995, 50.1035529], "type": "Point"}, "id": "1", "properties": {"nodeID": 1, "x": 1603413.2063240695, "y": 6464228.730248732}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10258519999999, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [14.402405999999988, 50.10258519999999], "type": "Point"}, "id": "2", "properties": {"nodeID": 2, "x": 1603268.502117987, "y": 6464060.781328565}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [14.403259899999986, 50.10241870000001], "type": "Point"}, "id": "3", "properties": {"nodeID": 3, "x": 1603363.557831175, "y": 6464031.88480676}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [14.405449500000003, 50.10328279999999], "type": "Point"}, "id": "4", "properties": {"nodeID": 4, "x": 1603607.3029882177, "y": 6464181.852772597}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [14.402032799999994, 50.10315780000001], "type": "Point"}, "id": "5", "properties": {"nodeID": 5, "x": 1603226.9576840235, "y": 6464160.158361825}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [14.400352999999992, 50.102739099999994], "type": "Point"}, "id": "6", "properties": {"nodeID": 6, "x": 1603039.9632033885, "y": 6464087.491175889}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.398981599999999, 50.1024077], "geometry": {"coordinates": [14.398981599999999, 50.1024077], "type": "Point"}, "id": "7", "properties": {"nodeID": 7, "x": 1602887.2996537155, "y": 6464029.975730775}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.103779500000016, 14.39972789999999, 50.103779500000016], "geometry": {"coordinates": [14.39972789999999, 50.103779500000016], "type": "Point"}, "id": "8", "properties": {"nodeID": 8, "x": 1602970.3773896934, "y": 6464268.058242684}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.102068500000016, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [14.400807100000003, 50.102068500000016], "type": "Point"}, "id": "9", "properties": {"nodeID": 9, "x": 1603090.513384159, "y": 6463971.106984773}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [14.402848699999991, 50.101294599999996], "type": "Point"}, "id": "10", "properties": {"nodeID": 10, "x": 1603317.7832565615, "y": 6463836.796863219}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.10149909999998, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [14.401812000000007, 50.10149909999998], "type": "Point"}, "id": "11", "properties": {"nodeID": 11, "x": 1603202.3783404578, "y": 6463872.287568242}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.400640399999995, 50.100679099999994], "geometry": {"coordinates": [14.400640399999995, 50.100679099999994], "type": "Point"}, "id": "12", "properties": {"nodeID": 12, "x": 1603071.956425043, "y": 6463729.978565}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [14.405837099999994, 50.10435879999999], "type": "Point"}, "id": "13", "properties": {"nodeID": 13, "x": 1603650.450422848, "y": 6464368.600601688}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [14.404608199999993, 50.10102239999999], "type": "Point"}, "id": "14", "properties": {"nodeID": 14, "x": 1603513.6499006122, "y": 6463789.557147608}, "type": "Feature"}, {"bbox": [14.407143600000008, 50.10099869999999, 14.407143600000008, 50.10099869999999], "geometry": {"coordinates": [14.407143600000008, 50.10099869999999], "type": "Point"}, "id": "15", "properties": {"nodeID": 15, "x": 1603795.889337571, "y": 6463785.444077063}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [14.405011000000012, 50.1021532], "type": "Point"}, "id": "16", "properties": {"nodeID": 16, "x": 1603558.489391506, "y": 6463985.80677705}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.399633600000007, 50.10131139999999], "geometry": {"coordinates": [14.399633600000007, 50.10131139999999], "type": "Point"}, "id": "17", "properties": {"nodeID": 17, "x": 1602959.8799617135, "y": 6463839.712475327}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.401311799999997, 50.101800699999984], "geometry": {"coordinates": [14.401311799999997, 50.101800699999984], "type": "Point"}, "id": "18", "properties": {"nodeID": 18, "x": 1603146.6963311615, "y": 6463924.630126579}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404248800000007, 50.10007700000001], "geometry": {"coordinates": [14.404248800000007, 50.10007700000001], "type": "Point"}, "id": "19", "properties": {"nodeID": 19, "x": 1603473.6416756227, "y": 6463625.487127112}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1049737, 14.400690199999993, 50.1049737], "geometry": {"coordinates": [14.400690199999993, 50.1049737], "type": "Point"}, "id": "20", "properties": {"nodeID": 20, "x": 1603077.5001356844, "y": 6464475.322968743}, "type": "Feature"}, {"bbox": [14.402574900000001, 50.105621199999995, 14.402574900000001, 50.105621199999995], "geometry": {"coordinates": [14.402574900000001, 50.105621199999995], "type": "Point"}, "id": "21", "properties": {"nodeID": 21, "x": 1603287.303979983, "y": 6464587.704889874}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402499399999995, 50.100328799999986], "geometry": {"coordinates": [14.402499399999995, 50.100328799999986], "type": "Point"}, "id": "22", "properties": {"nodeID": 22, "x": 1603278.8993584276, "y": 6463669.185595578}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1054507, 14.404819700000001, 50.1054507], "geometry": {"coordinates": [14.404819700000001, 50.1054507], "type": "Point"}, "id": "23", "properties": {"nodeID": 23, "x": 1603537.1939729159, "y": 6464558.11228298}, "type": "Feature"}, {"bbox": [14.406339600000006, 50.10579450000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [14.406339600000006, 50.10579450000001], "type": "Point"}, "id": "24", "properties": {"nodeID": 24, "x": 1603706.3884669733, "y": 6464617.783583014}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.40525490000001, 50.1047055, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [14.40525490000001, 50.1047055], "type": "Point"}, "id": "0", "properties": {"nodeID": 0, "x": 1603585.6402153103, "y": 6464428.773867372}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.1035529, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [14.403705899999995, 50.1035529], "type": "Point"}, "id": "1", "properties": {"nodeID": 1, "x": 1603413.2063240695, "y": 6464228.730248732}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10258519999999, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [14.402405999999988, 50.10258519999999], "type": "Point"}, "id": "2", "properties": {"nodeID": 2, "x": 1603268.502117987, "y": 6464060.781328565}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [14.403259899999986, 50.10241870000001], "type": "Point"}, "id": "3", "properties": {"nodeID": 3, "x": 1603363.557831175, "y": 6464031.88480676}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [14.405449500000003, 50.10328279999999], "type": "Point"}, "id": "4", "properties": {"nodeID": 4, "x": 1603607.3029882177, "y": 6464181.852772597}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [14.402032799999994, 50.10315780000001], "type": "Point"}, "id": "5", "properties": {"nodeID": 5, "x": 1603226.9576840235, "y": 6464160.158361825}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [14.400352999999992, 50.102739099999994], "type": "Point"}, "id": "6", "properties": {"nodeID": 6, "x": 1603039.9632033885, "y": 6464087.491175889}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.398981599999999, 50.1024077], "geometry": {"coordinates": [14.398981599999999, 50.1024077], "type": "Point"}, "id": "7", "properties": {"nodeID": 7, "x": 1602887.2996537155, "y": 6464029.975730775}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.103779500000016, 14.39972789999999, 50.103779500000016], "geometry": {"coordinates": [14.39972789999999, 50.103779500000016], "type": "Point"}, "id": "8", "properties": {"nodeID": 8, "x": 1602970.3773896934, "y": 6464268.058242684}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.102068500000016, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [14.400807100000003, 50.102068500000016], "type": "Point"}, "id": "9", "properties": {"nodeID": 9, "x": 1603090.513384159, "y": 6463971.106984773}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [14.402848699999991, 50.101294599999996], "type": "Point"}, "id": "10", "properties": {"nodeID": 10, "x": 1603317.7832565615, "y": 6463836.796863219}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.10149909999998, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [14.401812000000007, 50.10149909999998], "type": "Point"}, "id": "11", "properties": {"nodeID": 11, "x": 1603202.3783404578, "y": 6463872.287568242}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.400640399999995, 50.100679099999994], "geometry": {"coordinates": [14.400640399999995, 50.100679099999994], "type": "Point"}, "id": "12", "properties": {"nodeID": 12, "x": 1603071.956425043, "y": 6463729.978565}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [14.405837099999994, 50.10435879999999], "type": "Point"}, "id": "13", "properties": {"nodeID": 13, "x": 1603650.450422848, "y": 6464368.600601688}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [14.404608199999993, 50.10102239999999], "type": "Point"}, "id": "14", "properties": {"nodeID": 14, "x": 1603513.6499006122, "y": 6463789.557147608}, "type": "Feature"}, {"bbox": [14.407143600000008, 50.10099869999999, 14.407143600000008, 50.10099869999999], "geometry": {"coordinates": [14.407143600000008, 50.10099869999999], "type": "Point"}, "id": "15", "properties": {"nodeID": 15, "x": 1603795.889337571, "y": 6463785.444077063}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [14.405011000000012, 50.1021532], "type": "Point"}, "id": "16", "properties": {"nodeID": 16, "x": 1603558.489391506, "y": 6463985.80677705}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.399633600000007, 50.10131139999999], "geometry": {"coordinates": [14.399633600000007, 50.10131139999999], "type": "Point"}, "id": "17", "properties": {"nodeID": 17, "x": 1602959.8799617135, "y": 6463839.712475327}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.401311799999997, 50.101800699999984], "geometry": {"coordinates": [14.401311799999997, 50.101800699999984], "type": "Point"}, "id": "18", "properties": {"nodeID": 18, "x": 1603146.6963311615, "y": 6463924.630126579}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404248800000007, 50.10007700000001], "geometry": {"coordinates": [14.404248800000007, 50.10007700000001], "type": "Point"}, "id": "19", "properties": {"nodeID": 19, "x": 1603473.6416756227, "y": 6463625.487127112}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.1049737, 14.400690199999993, 50.1049737], "geometry": {"coordinates": [14.400690199999993, 50.1049737], "type": "Point"}, "id": "20", "properties": {"nodeID": 20, "x": 1603077.5001356844, "y": 6464475.322968743}, "type": "Feature"}, {"bbox": [14.402574900000001, 50.105621199999995, 14.402574900000001, 50.105621199999995], "geometry": {"coordinates": [14.402574900000001, 50.105621199999995], "type": "Point"}, "id": "21", "properties": {"nodeID": 21, "x": 1603287.303979983, "y": 6464587.704889874}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402499399999995, 50.100328799999986], "geometry": {"coordinates": [14.402499399999995, 50.100328799999986], "type": "Point"}, "id": "22", "properties": {"nodeID": 22, "x": 1603278.8993584276, "y": 6463669.185595578}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1054507, 14.404819700000001, 50.1054507], "geometry": {"coordinates": [14.404819700000001, 50.1054507], "type": "Point"}, "id": "23", "properties": {"nodeID": 23, "x": 1603537.1939729159, "y": 6464558.11228298}, "type": "Feature"}, {"bbox": [14.406339600000006, 50.10579450000001, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [14.406339600000006, 50.10579450000001], "type": "Point"}, "id": "24", "properties": {"nodeID": 24, "x": 1603706.3884669733, "y": 6464617.783583014}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf.bindTooltip(\n", + " geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -668,63 +588,63 @@ "});\n", " \n", " \n", - " geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2.addTo(map_0e2c896b366477a676b80af2d1218430);\n", " \n", " \n", - " function geo_json_838def6cdf8f4f50b5af320d0954887d_styler(feature) {\n", + " function geo_json_36a89c55260edb5b9ab90f4bad27029b_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_838def6cdf8f4f50b5af320d0954887d_highlighter(feature) {\n", + " function geo_json_36a89c55260edb5b9ab90f4bad27029b_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_838def6cdf8f4f50b5af320d0954887d_pointToLayer(feature, latlng) {\n", + " function geo_json_36a89c55260edb5b9ab90f4bad27029b_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_838def6cdf8f4f50b5af320d0954887d_styler(feature)\n", + " let style = geo_json_36a89c55260edb5b9ab90f4bad27029b_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_838def6cdf8f4f50b5af320d0954887d_onEachFeature(feature, layer) {\n", + " function geo_json_36a89c55260edb5b9ab90f4bad27029b_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_838def6cdf8f4f50b5af320d0954887d.resetStyle(e.target);\n", + " geo_json_36a89c55260edb5b9ab90f4bad27029b.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_838def6cdf8f4f50b5af320d0954887d_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_36a89c55260edb5b9ab90f4bad27029b_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_838def6cdf8f4f50b5af320d0954887d = L.geoJson(null, {\n", - " onEachFeature: geo_json_838def6cdf8f4f50b5af320d0954887d_onEachFeature,\n", + " var geo_json_36a89c55260edb5b9ab90f4bad27029b = L.geoJson(null, {\n", + " onEachFeature: geo_json_36a89c55260edb5b9ab90f4bad27029b_onEachFeature,\n", " \n", - " style: geo_json_838def6cdf8f4f50b5af320d0954887d_styler,\n", - " pointToLayer: geo_json_838def6cdf8f4f50b5af320d0954887d_pointToLayer,\n", + " style: geo_json_36a89c55260edb5b9ab90f4bad27029b_styler,\n", + " pointToLayer: geo_json_36a89c55260edb5b9ab90f4bad27029b_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_838def6cdf8f4f50b5af320d0954887d_add (data) {\n", - " geo_json_838def6cdf8f4f50b5af320d0954887d\n", + " function geo_json_36a89c55260edb5b9ab90f4bad27029b_add (data) {\n", + " geo_json_36a89c55260edb5b9ab90f4bad27029b\n", " .addData(data);\n", " }\n", - " geo_json_838def6cdf8f4f50b5af320d0954887d_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"edge_id": 0, "mm_len": 264.1039496246775, "node_end": 1, "node_start": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"edge_id": 1, "mm_len": 99.75118962647376, "node_end": 3, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"edge_id": 2, "mm_len": 199.74650338337847, "node_end": 4, "node_start": 1, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"edge_id": 3, "mm_len": 203.01409000575802, "node_end": 3, "node_start": 1, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"edge_id": 4, "mm_len": 198.48272399064462, "node_end": 5, "node_start": 1, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"edge_id": 5, "mm_len": 200.61768541143937, "node_end": 6, "node_start": 5, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"edge_id": 6, "mm_len": 163.14628203947333, "node_end": 7, "node_start": 6, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"edge_id": 7, "mm_len": 193.51137206831748, "node_end": 8, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"edge_id": 8, "mm_len": 127.80086449751786, "node_end": 9, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"edge_id": 9, "mm_len": 122.5319618088215, "node_end": 11, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"edge_id": 10, "mm_len": 193.04063727323836, "node_end": 12, "node_start": 11, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"edge_id": 11, "mm_len": 88.92430548419476, "node_end": 13, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"edge_id": 12, "mm_len": 107.88014814146449, "node_end": 5, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"edge_id": 13, "mm_len": 282.6905386499787, "node_end": 15, "node_start": 14, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"edge_id": 14, "mm_len": 200.30351738673852, "node_end": 16, "node_start": 3, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"edge_id": 15, "mm_len": 200.3861708266132, "node_end": 10, "node_start": 3, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"edge_id": 16, "mm_len": 191.66755798860544, "node_end": 13, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"edge_id": 17, "mm_len": 202.03167967950094, "node_end": 16, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"edge_id": 18, "mm_len": 201.30697205908257, "node_end": 16, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"edge_id": 19, "mm_len": 187.49184699173748, "node_end": 17, "node_start": 9, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"edge_id": 20, "mm_len": 182.6849740039611, "node_end": 18, "node_start": 2, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"edge_id": 21, "mm_len": 72.91516907666792, "node_end": 18, "node_start": 9, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"edge_id": 22, "mm_len": 76.42465276315266, "node_end": 18, "node_start": 11, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"edge_id": 23, "mm_len": 168.88041067114747, "node_end": 19, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"edge_id": 24, "mm_len": 201.4861168351184, "node_end": 14, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"edge_id": 25, "mm_len": 351.1551873514152, "node_end": 20, "node_start": 5, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"edge_id": 26, "mm_len": 382.50195042922803, "node_end": 21, "node_start": 1, "stroke_id": 9}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"edge_id": 27, "mm_len": 172.0624733749828, "node_end": 22, "node_start": 10, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"edge_id": 28, "mm_len": 138.23490844748363, "node_end": 23, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"edge_id": 29, "mm_len": 255.8228880811063, "node_end": 24, "node_start": 13, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"edge_id": 30, "mm_len": 317.85221640975095, "node_end": 13, "node_start": 4, "stroke_id": 2}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_36a89c55260edb5b9ab90f4bad27029b_add({"bbox": [14.398981599999999, 50.10007700000001, 14.407143600000008, 50.10579450000001], "features": [{"bbox": [14.403705899999995, 50.1035529, 14.40525490000001, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "0", "properties": {"edge_id": 0, "mm_len": 264.1039496246775, "node_end": 1, "node_start": 0, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402405999999988, 50.10241870000001, 14.403259899999986, 50.10258519999999], "geometry": {"coordinates": [[14.402405999999988, 50.10258519999999], [14.402660399999995, 50.102510699999996], [14.403130100000002, 50.102438600000006], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "1", "properties": {"edge_id": 1, "mm_len": 99.75118962647376, "node_end": 3, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.403705899999995, 50.10328279999999, 14.405449500000003, 50.1035529], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405319999999984, 50.10329479999999], [14.403891599999998, 50.10352230000001], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "2", "properties": {"edge_id": 2, "mm_len": 199.74650338337847, "node_end": 4, "node_start": 1, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.10241870000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403376200000004, 50.10272779999999], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "3", "properties": {"edge_id": 3, "mm_len": 203.01409000575802, "node_end": 3, "node_start": 1, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10315780000001, 14.403705899999995, 50.1035529], "geometry": {"coordinates": [[14.403705899999995, 50.1035529], [14.402459499999987, 50.10326440000001], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "4", "properties": {"edge_id": 4, "mm_len": 198.48272399064462, "node_end": 5, "node_start": 1, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102739099999994, 14.402032799999994, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "5", "properties": {"edge_id": 5, "mm_len": 200.61768541143937, "node_end": 6, "node_start": 5, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.398981599999999, 50.1024077, 14.400352999999992, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.399116499999996, 50.1024374], [14.398981599999999, 50.1024077]], "type": "LineString"}, "id": "6", "properties": {"edge_id": 6, "mm_len": 163.14628203947333, "node_end": 7, "node_start": 6, "stroke_id": 3}, "type": "Feature"}, {"bbox": [14.39972789999999, 50.102739099999994, 14.400352999999992, 50.103779500000016], "geometry": {"coordinates": [[14.39972789999999, 50.103779500000016], [14.399761200000013, 50.103724099999994], [14.400352999999992, 50.102739099999994]], "type": "LineString"}, "id": "7", "properties": {"edge_id": 7, "mm_len": 193.51137206831748, "node_end": 8, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400352999999992, 50.102068500000016, 14.400807100000003, 50.102739099999994], "geometry": {"coordinates": [[14.400352999999992, 50.102739099999994], [14.400665800000011, 50.1021886], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "8", "properties": {"edge_id": 8, "mm_len": 127.80086449751786, "node_end": 9, "node_start": 6, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401812000000007, 50.101294599999996, 14.402848699999991, 50.10149909999998], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.401945599999989, 50.1014274], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "9", "properties": {"edge_id": 9, "mm_len": 122.5319618088215, "node_end": 11, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400640399999995, 50.100679099999994, 14.401812000000007, 50.10149909999998], "geometry": {"coordinates": [[14.400640399999995, 50.100679099999994], [14.400793700000012, 50.10078149999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "10", "properties": {"edge_id": 10, "mm_len": 193.04063727323836, "node_end": 12, "node_start": 11, "stroke_id": 5}, "type": "Feature"}, {"bbox": [14.40525490000001, 50.10435879999999, 14.405837099999994, 50.1047055], "geometry": {"coordinates": [[14.40525490000001, 50.1047055], [14.405411700000002, 50.10461469999999], [14.405760199999992, 50.104431499999976], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "11", "properties": {"edge_id": 11, "mm_len": 88.92430548419476, "node_end": 13, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.402032799999994, 50.10258519999999, 14.402405999999988, 50.10315780000001], "geometry": {"coordinates": [[14.402032799999994, 50.10315780000001], [14.40208080000001, 50.1030768], [14.402290500000007, 50.10272330000001], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "12", "properties": {"edge_id": 12, "mm_len": 107.88014814146449, "node_end": 5, "node_start": 2, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10099319999999, 14.407143600000008, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404862899999985, 50.10099319999999], [14.407143600000008, 50.10099869999999]], "type": "LineString"}, "id": "13", "properties": {"edge_id": 13, "mm_len": 282.6905386499787, "node_end": 15, "node_start": 14, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.403259899999986, 50.1021532, 14.405011000000012, 50.10241870000001], "geometry": {"coordinates": [[14.403259899999986, 50.10241870000001], [14.403371899999996, 50.10240169999999], [14.404886699999983, 50.102172], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "14", "properties": {"edge_id": 14, "mm_len": 200.30351738673852, "node_end": 16, "node_start": 3, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.101294599999996, 14.403259899999986, 50.10241870000001], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403237199999987, 50.1023566], [14.403259899999986, 50.10241870000001]], "type": "LineString"}, "id": "15", "properties": {"edge_id": 15, "mm_len": 200.3861708266132, "node_end": 10, "node_start": 3, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10328279999999, 14.405837099999994, 50.10435879999999], "geometry": {"coordinates": [[14.405837099999994, 50.10435879999999], [14.405449500000003, 50.10328279999999]], "type": "LineString"}, "id": "16", "properties": {"edge_id": 16, "mm_len": 191.66755798860544, "node_end": 13, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405011000000012, 50.1021532, 14.405449500000003, 50.10328279999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405011000000012, 50.1021532]], "type": "LineString"}, "id": "17", "properties": {"edge_id": 17, "mm_len": 202.03167967950094, "node_end": 16, "node_start": 4, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.404608199999993, 50.10102239999999, 14.405011000000012, 50.1021532], "geometry": {"coordinates": [[14.405011000000012, 50.1021532], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "18", "properties": {"edge_id": 18, "mm_len": 201.30697205908257, "node_end": 16, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.399633600000007, 50.10131139999999, 14.400807100000003, 50.102068500000016], "geometry": {"coordinates": [[14.399633600000007, 50.10131139999999], [14.399754699999999, 50.1013373], [14.399877899999998, 50.10138819999998], [14.400807100000003, 50.102068500000016]], "type": "LineString"}, "id": "19", "properties": {"edge_id": 19, "mm_len": 187.49184699173748, "node_end": 17, "node_start": 9, "stroke_id": 7}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.101800699999984, 14.402405999999988, 50.10258519999999], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401404800000007, 50.1018674], [14.402314599999997, 50.1025197], [14.402405999999988, 50.10258519999999]], "type": "LineString"}, "id": "20", "properties": {"edge_id": 20, "mm_len": 182.6849740039611, "node_end": 18, "node_start": 2, "stroke_id": 8}, "type": "Feature"}, {"bbox": [14.400807100000003, 50.101800699999984, 14.401311799999997, 50.102068500000016], "geometry": {"coordinates": [[14.400807100000003, 50.102068500000016], [14.401311799999997, 50.101800699999984]], "type": "LineString"}, "id": "21", "properties": {"edge_id": 21, "mm_len": 72.91516907666792, "node_end": 18, "node_start": 9, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.401311799999997, 50.10149909999998, 14.401812000000007, 50.101800699999984], "geometry": {"coordinates": [[14.401311799999997, 50.101800699999984], [14.401411499999988, 50.10174279999999], [14.401812000000007, 50.10149909999998]], "type": "LineString"}, "id": "22", "properties": {"edge_id": 22, "mm_len": 76.42465276315266, "node_end": 18, "node_start": 11, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.404248800000007, 50.10007700000001, 14.404608199999993, 50.10102239999999], "geometry": {"coordinates": [[14.404608199999993, 50.10102239999999], [14.404307199999998, 50.100239299999984], [14.404296200000006, 50.1002086], [14.404286899999999, 50.1001818], [14.404248800000007, 50.10007700000001]], "type": "LineString"}, "id": "23", "properties": {"edge_id": 23, "mm_len": 168.88041067114747, "node_end": 19, "node_start": 14, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.402848699999991, 50.10102239999999, 14.404608199999993, 50.101294599999996], "geometry": {"coordinates": [[14.402848699999991, 50.101294599999996], [14.403002900000013, 50.101270600000014], [14.404461600000014, 50.10104320000001], [14.404608199999993, 50.10102239999999]], "type": "LineString"}, "id": "24", "properties": {"edge_id": 24, "mm_len": 201.4861168351184, "node_end": 14, "node_start": 10, "stroke_id": 4}, "type": "Feature"}, {"bbox": [14.400690199999993, 50.10315780000001, 14.402032799999994, 50.1049737], "geometry": {"coordinates": [[14.400690199999993, 50.1049737], [14.4007622, 50.10489869999999], [14.400849199999989, 50.104808], [14.40109450000001, 50.104504399999996], [14.401211099999998, 50.1043727], [14.401334299999993, 50.10430380000001], [14.401365700000005, 50.1042523], [14.40140429999999, 50.104188999999984], [14.401445499999998, 50.10412150000001], [14.401999400000003, 50.103214], [14.402032799999994, 50.10315780000001]], "type": "LineString"}, "id": "25", "properties": {"edge_id": 25, "mm_len": 351.1551873514152, "node_end": 20, "node_start": 5, "stroke_id": 1}, "type": "Feature"}, {"bbox": [14.402571100000007, 50.1035529, 14.403705899999995, 50.105621199999995], "geometry": {"coordinates": [[14.402574900000001, 50.105621199999995], [14.402571100000007, 50.105442000000004], [14.40302670000001, 50.104649099999975], [14.403056600000005, 50.104597099999985], [14.403099200000005, 50.1045278], [14.403705899999995, 50.1035529]], "type": "LineString"}, "id": "26", "properties": {"edge_id": 26, "mm_len": 382.50195042922803, "node_end": 21, "node_start": 1, "stroke_id": 9}, "type": "Feature"}, {"bbox": [14.402499399999995, 50.100328799999986, 14.402848699999991, 50.101294599999996], "geometry": {"coordinates": [[14.402499399999995, 50.100328799999986], [14.4025428, 50.10044890000002], [14.4028187, 50.1012117], [14.402848699999991, 50.101294599999996]], "type": "LineString"}, "id": "27", "properties": {"edge_id": 27, "mm_len": 172.0624733749828, "node_end": 22, "node_start": 10, "stroke_id": 0}, "type": "Feature"}, {"bbox": [14.404819700000001, 50.1047055, 14.40525490000001, 50.1054507], "geometry": {"coordinates": [[14.404819700000001, 50.1054507], [14.405003799999989, 50.105144599999996], [14.405040199999995, 50.10508399999999], [14.405066199999997, 50.1050121], [14.40525490000001, 50.1047055]], "type": "LineString"}, "id": "28", "properties": {"edge_id": 28, "mm_len": 138.23490844748363, "node_end": 23, "node_start": 0, "stroke_id": 2}, "type": "Feature"}, {"bbox": [14.405837099999994, 50.10435879999999, 14.406339600000006, 50.10579450000001], "geometry": {"coordinates": [[14.406339600000006, 50.10579450000001], [14.406333900000003, 50.10567839999998], [14.406114900000004, 50.10505569999998], [14.406093300000007, 50.10498459999999], [14.406063800000007, 50.1049104], [14.406050700000007, 50.1048785], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "29", "properties": {"edge_id": 29, "mm_len": 255.8228880811063, "node_end": 24, "node_start": 13, "stroke_id": 6}, "type": "Feature"}, {"bbox": [14.405449500000003, 50.10327799999998, 14.40648620000001, 50.10435879999999], "geometry": {"coordinates": [[14.405449500000003, 50.10328279999999], [14.405552600000002, 50.10327799999998], [14.40648620000001, 50.103294399999996], [14.406260999999994, 50.103803500000005], [14.406109, 50.1041169], [14.406067899999996, 50.10421749999998], [14.405966199999993, 50.10428099999998], [14.405837099999994, 50.10435879999999]], "type": "LineString"}, "id": "30", "properties": {"edge_id": 30, "mm_len": 317.85221640975095, "node_end": 13, "node_start": 4, "stroke_id": 2}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_838def6cdf8f4f50b5af320d0954887d.bindTooltip(\n", + " geo_json_36a89c55260edb5b9ab90f4bad27029b.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -751,63 +671,63 @@ "});\n", " \n", " \n", - " geo_json_838def6cdf8f4f50b5af320d0954887d.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " geo_json_36a89c55260edb5b9ab90f4bad27029b.addTo(map_0e2c896b366477a676b80af2d1218430);\n", " \n", " \n", - " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_styler(feature) {\n", + " function geo_json_55272696570db606458acfba7e68f342_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"color": "black", "fillColor": "black", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_highlighter(feature) {\n", + " function geo_json_55272696570db606458acfba7e68f342_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_pointToLayer(feature, latlng) {\n", + " function geo_json_55272696570db606458acfba7e68f342_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 10, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_styler(feature)\n", + " let style = geo_json_55272696570db606458acfba7e68f342_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_onEachFeature(feature, layer) {\n", + " function geo_json_55272696570db606458acfba7e68f342_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1.resetStyle(e.target);\n", + " geo_json_55272696570db606458acfba7e68f342.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_55272696570db606458acfba7e68f342_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_724ab5ab1a419daf695c69a0ba3e0ac1 = L.geoJson(null, {\n", - " onEachFeature: geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_onEachFeature,\n", + " var geo_json_55272696570db606458acfba7e68f342 = L.geoJson(null, {\n", + " onEachFeature: geo_json_55272696570db606458acfba7e68f342_onEachFeature,\n", " \n", - " style: geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_styler,\n", - " pointToLayer: geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_pointToLayer,\n", + " style: geo_json_55272696570db606458acfba7e68f342_styler,\n", + " pointToLayer: geo_json_55272696570db606458acfba7e68f342_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_add (data) {\n", - " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1\n", + " function geo_json_55272696570db606458acfba7e68f342_add (data) {\n", + " geo_json_55272696570db606458acfba7e68f342\n", " .addData(data);\n", " }\n", - " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "black", "edge_ids": "[ 0 3 15 27]", "geometry_stroke": "LINESTRING (1603278.8993584276 6463669.185595578, 1603283.7306243288 6463690.028353462, 1603314.4436718386 6463822.409720818, 1603317.7832565615 6463836.796863219, 1603361.0308787343 6464021.107210826, 1603363.557831175 6464031.88480676, 1603376.5042879563 6464085.530021086, 1603413.2063240695 6464228.730248732, 1603585.6402153103 6464428.773867372)", "length": 839.5666838320316, "n_segments": 8, "nodeID": 0, "stroke_access": 3, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 8, "stroke_degree": 5, "stroke_orthogonality": 68.74678997354196, "stroke_spacing": 104.94583547900395, "x": "array(\\u0027d\\u0027, [1603374.6625343116])", "y": "array(\\u0027d\\u0027, [6464077.898491419])"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "black", "edge_ids": "[ 1 12 14 25]", "geometry_stroke": "LINESTRING (1603077.5001356844 6464475.322968743, 1603085.5151390221 6464462.305855976, 1603095.1999347198 6464446.563854833, 1603122.5066058137 6464393.870890386, 1603135.486458439 6464371.013077857, 1603149.2010197043 6464359.054839547, 1603152.6964517166 6464350.116544929, 1603156.9933840595 6464339.130265876, 1603161.5797470808 6464327.415055399, 1603223.2396130317 6464169.912161903, 1603226.9576840235 6464160.158361825, 1603232.3010195831 6464146.100413868, 1603255.644716802 6464084.749030368, 1603268.502117987 6464060.781328565, 1603296.8217964454 6464047.851641227, 1603349.1085612718 6464035.338499875, 1603363.557831175 6464031.88480676, 1603376.025614145 6464028.934416787, 1603544.6523787973 6463989.069544387, 1603558.489391506 6463985.80677705)", "length": 759.0900425060918, "n_segments": 19, "nodeID": 1, "stroke_access": 2, "stroke_betweenness": 0.08796296296296295, "stroke_closeness": 0.5625, "stroke_connectivity": 6, "stroke_degree": 4, "stroke_orthogonality": 86.32371095647791, "stroke_spacing": 126.51500708434862, "x": "array(\\u0027d\\u0027, [1603237.0487682838])", "y": "array(\\u0027d\\u0027, [6464133.622486805])"}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "black", "edge_ids": "[ 2 11 28 30]", "geometry_stroke": "LINESTRING (1603537.1939729159 6464558.11228298, 1603557.6878911697 6464504.984705836, 1603561.7399206352 6464494.466839611, 1603564.634227396 6464481.987738368, 1603585.6402153103 6464428.773867372, 1603603.0951114655 6464413.0145736905, 1603641.889954006 6464381.218380466, 1603650.450422848 6464368.600601688, 1603664.8217691095 6464355.097690451, 1603676.1429613235 6464344.076693036, 1603680.7181923958 6464326.616686098, 1603697.6387549953 6464272.223619222, 1603722.7079043242 6464183.866016789, 1603618.7800277183 6464181.019706178, 1603607.3029882177 6464181.852772597, 1603592.8871141581 6464183.935439011, 1603433.8783535103 6464223.419421798, 1603413.2063240695 6464228.730248732)", "length": 744.7579337248078, "n_segments": 17, "nodeID": 2, "stroke_access": 4, "stroke_betweenness": 0.04629629629629629, "stroke_closeness": 0.5294117647058824, "stroke_connectivity": 8, "stroke_degree": 4, "stroke_orthogonality": 60.67507202025625, "stroke_spacing": 93.09474171560097, "x": "array(\\u0027d\\u0027, [1603707.1065106073])", "y": "array(\\u0027d\\u0027, [6464238.853991265])"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "black", "edge_ids": "[4 5 6]", "geometry_stroke": "LINESTRING (1603413.2063240695 6464228.730248732, 1603274.457710744 6464178.659351781, 1603226.9576840235 6464160.158361825, 1603039.9632033885 6464087.491175889, 1602902.3166530235 6464035.130236932, 1602887.2996537155 6464029.975730775)", "length": 562.2466914415573, "n_segments": 5, "nodeID": 3, "stroke_access": 2, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 7, "stroke_degree": 5, "stroke_orthogonality": 72.69057271585089, "stroke_spacing": 80.32095592022247, "x": "array(\\u0027d\\u0027, [1603149.9288811635])", "y": "array(\\u0027d\\u0027, [6464130.224503239])"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "black", "edge_ids": "[ 7 8 9 13 21 22 24]", "geometry_stroke": "LINESTRING (1602970.3773896934 6464268.058242684, 1602974.0843287394 6464258.443173138, 1603039.9632033885 6464087.491175889, 1603074.7839401108 6463991.950499589, 1603090.513384159 6463971.106984773, 1603146.6963311615 6463924.630126579, 1603157.794884393 6463914.581579376, 1603202.3783404578 6463872.287568242, 1603217.2506244255 6463859.844110653, 1603317.7832565615 6463836.796863219, 1603334.948722044 6463832.631704839, 1603497.3304632641 6463793.166932718, 1603513.6499006122 6463789.557147608, 1603542.0029749167 6463784.4895673115, 1603795.889337571 6463785.444077063)", "length": 1077.3606756995746, "n_segments": 14, "nodeID": 4, "stroke_access": 3, "stroke_betweenness": 0.5046296296296297, "stroke_closeness": 0.75, "stroke_connectivity": 9, "stroke_degree": 6, "stroke_orthogonality": 87.28338224081126, "stroke_spacing": 119.70674174439718, "x": "array(\\u0027d\\u0027, [1603264.6577362637])", "y": "array(\\u0027d\\u0027, [6463848.97596353])"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "black", "edge_ids": "[10]", "geometry_stroke": "LINESTRING (1603071.956425043 6463729.978565, 1603089.0217029832 6463747.749702545, 1603202.3783404578 6463872.287568242)", "length": 193.04063727323836, "n_segments": 2, "nodeID": 5, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 87.60977577529626, "stroke_spacing": 193.04063727323836, "x": "array(\\u0027d\\u0027, [1603137.4077031056])", "y": "array(\\u0027d\\u0027, [6463800.908382258])"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "black", "edge_ids": "[16 17 18 23 29]", "geometry_stroke": "LINESTRING (1603706.3884669733 6464617.783583014, 1603705.7539458754 6464597.632755783, 1603681.3749773917 6464489.555035355, 1603678.970476391 6464477.214790825, 1603675.6865514126 6464464.336524226, 1603674.2282660832 6464458.799917089, 1603650.450422848 6464368.600601688, 1603607.3029882177 6464181.852772597, 1603558.489391506 6463985.80677705, 1603513.6499006122 6463789.557147608, 1603480.142733884 6463653.653349537, 1603478.918219486 6463648.325535514, 1603477.8829482212 6463643.67454756, 1603473.6416756227 6463625.487127112)", "length": 1019.7095084794428, "n_segments": 13, "nodeID": 6, "stroke_access": 4, "stroke_betweenness": 0.06712962962962961, "stroke_closeness": 0.6, "stroke_connectivity": 7, "stroke_degree": 3, "stroke_orthogonality": 76.50850905913968, "stroke_spacing": 145.67278692563468, "x": "array(\\u0027d\\u0027, [1603592.2349246691])", "y": "array(\\u0027d\\u0027, [6464121.336160048])"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "black", "edge_ids": "[19]", "geometry_stroke": "LINESTRING (1602959.8799617135 6463839.712475327, 1602973.3607520477 6463844.207379333, 1602987.0753133134 6463853.041000848, 1603090.513384159 6463971.106984773)", "length": 187.49184699173748, "n_segments": 3, "nodeID": 7, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 78.26155769686821, "stroke_spacing": 187.49184699173748, "x": "array(\\u0027d\\u0027, [1603028.737187382])", "y": "array(\\u0027d\\u0027, [6463900.594576759])"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "black", "edge_ids": "[20]", "geometry_stroke": "LINESTRING (1603146.6963311615 6463924.630126579, 1603157.0490438067 6463936.205929175, 1603258.3275165292 6464049.413615812, 1603268.502117987 6464060.781328565)", "length": 182.6849740039611, "n_segments": 3, "nodeID": 8, "stroke_access": 0, "stroke_betweenness": 0.020833333333333332, "stroke_closeness": 0.5, "stroke_connectivity": 2, "stroke_degree": 2, "stroke_orthogonality": 78.91626592156373, "stroke_spacing": 91.34248700198054, "x": "array(\\u0027d\\u0027, [1603207.5969886228])", "y": "array(\\u0027d\\u0027, [6463992.707728057])"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "black", "edge_ids": "[26]", "geometry_stroke": "LINESTRING (1603287.303979983 6464587.704889874, 1603286.8809659188 6464556.602281818, 1603337.5981259246 6464418.98505148, 1603340.9265786987 6464409.959912292, 1603345.6687890065 6464397.932193951, 1603413.2063240695 6464228.730248732)", "length": 382.50195042922803, "n_segments": 5, "nodeID": 9, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.5, "stroke_connectivity": 3, "stroke_degree": 3, "stroke_orthogonality": 59.350287847902734, "stroke_spacing": 127.50065014307602, "x": "array(\\u0027d\\u0027, [1603342.3426854417])", "y": "array(\\u0027d\\u0027, [6464406.368225728])"}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_55272696570db606458acfba7e68f342_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [14.40335965524552, 50.10268382777764], "type": "Point"}, "id": "0", "properties": {"__folium_color": "black", "edge_ids": "[ 0 3 15 27]", "geometry_stroke": "LINESTRING (1603278.8993584276 6463669.185595578, 1603283.7306243288 6463690.028353462, 1603314.4436718386 6463822.409720818, 1603317.7832565615 6463836.796863219, 1603361.0308787343 6464021.107210826, 1603363.557831175 6464031.88480676, 1603376.5042879563 6464085.530021086, 1603413.2063240695 6464228.730248732, 1603585.6402153103 6464428.773867372)", "length": 839.5666838320316, "n_segments": 8, "nodeID": 0, "stroke_access": 3, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 8, "stroke_degree": 5, "stroke_orthogonality": 68.74678997354196, "stroke_spacing": 104.94583547900395, "x": "array(\\u0027d\\u0027, [1603374.6625343116])", "y": "array(\\u0027d\\u0027, [6464077.898491419])"}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10300490375251, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [14.40212344975224, 50.10300490375251], "type": "Point"}, "id": "1", "properties": {"__folium_color": "black", "edge_ids": "[ 1 12 14 25]", "geometry_stroke": "LINESTRING (1603077.5001356844 6464475.322968743, 1603085.5151390221 6464462.305855976, 1603095.1999347198 6464446.563854833, 1603122.5066058137 6464393.870890386, 1603135.486458439 6464371.013077857, 1603149.2010197043 6464359.054839547, 1603152.6964517166 6464350.116544929, 1603156.9933840595 6464339.130265876, 1603161.5797470808 6464327.415055399, 1603223.2396130317 6464169.912161903, 1603226.9576840235 6464160.158361825, 1603232.3010195831 6464146.100413868, 1603255.644716802 6464084.749030368, 1603268.502117987 6464060.781328565, 1603296.8217964454 6464047.851641227, 1603349.1085612718 6464035.338499875, 1603363.557831175 6464031.88480676, 1603376.025614145 6464028.934416787, 1603544.6523787973 6463989.069544387, 1603558.489391506 6463985.80677705)", "length": 759.0900425060918, "n_segments": 19, "nodeID": 1, "stroke_access": 2, "stroke_betweenness": 0.08796296296296295, "stroke_closeness": 0.5625, "stroke_connectivity": 6, "stroke_degree": 4, "stroke_orthogonality": 86.32371095647791, "stroke_spacing": 126.51500708434862, "x": "array(\\u0027d\\u0027, [1603237.0487682838])", "y": "array(\\u0027d\\u0027, [6464133.622486805])"}, "type": "Feature"}, {"bbox": [14.406346050295715, 50.10361123107303, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [14.406346050295715, 50.10361123107303], "type": "Point"}, "id": "2", "properties": {"__folium_color": "black", "edge_ids": "[ 2 11 28 30]", "geometry_stroke": "LINESTRING (1603537.1939729159 6464558.11228298, 1603557.6878911697 6464504.984705836, 1603561.7399206352 6464494.466839611, 1603564.634227396 6464481.987738368, 1603585.6402153103 6464428.773867372, 1603603.0951114655 6464413.0145736905, 1603641.889954006 6464381.218380466, 1603650.450422848 6464368.600601688, 1603664.8217691095 6464355.097690451, 1603676.1429613235 6464344.076693036, 1603680.7181923958 6464326.616686098, 1603697.6387549953 6464272.223619222, 1603722.7079043242 6464183.866016789, 1603618.7800277183 6464181.019706178, 1603607.3029882177 6464181.852772597, 1603592.8871141581 6464183.935439011, 1603433.8783535103 6464223.419421798, 1603413.2063240695 6464228.730248732)", "length": 744.7579337248078, "n_segments": 17, "nodeID": 2, "stroke_access": 4, "stroke_betweenness": 0.04629629629629629, "stroke_closeness": 0.5294117647058824, "stroke_connectivity": 8, "stroke_degree": 4, "stroke_orthogonality": 60.67507202025625, "stroke_spacing": 93.09474171560097, "x": "array(\\u0027d\\u0027, [1603707.1065106073])", "y": "array(\\u0027d\\u0027, [6464238.853991265])"}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.401340838490729, 50.10298532497958], "geometry": {"coordinates": [14.401340838490729, 50.10298532497958], "type": "Point"}, "id": "3", "properties": {"__folium_color": "black", "edge_ids": "[4 5 6]", "geometry_stroke": "LINESTRING (1603413.2063240695 6464228.730248732, 1603274.457710744 6464178.659351781, 1603226.9576840235 6464160.158361825, 1603039.9632033885 6464087.491175889, 1602902.3166530235 6464035.130236932, 1602887.2996537155 6464029.975730775)", "length": 562.2466914415573, "n_segments": 5, "nodeID": 3, "stroke_access": 2, "stroke_betweenness": 0.13657407407407404, "stroke_closeness": 0.6923076923076923, "stroke_connectivity": 7, "stroke_degree": 5, "stroke_orthogonality": 72.69057271585089, "stroke_spacing": 80.32095592022247, "x": "array(\\u0027d\\u0027, [1603149.9288811635])", "y": "array(\\u0027d\\u0027, [6464130.224503239])"}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [14.40237146533139, 50.10136477695206], "type": "Point"}, "id": "4", "properties": {"__folium_color": "black", "edge_ids": "[ 7 8 9 13 21 22 24]", "geometry_stroke": "LINESTRING (1602970.3773896934 6464268.058242684, 1602974.0843287394 6464258.443173138, 1603039.9632033885 6464087.491175889, 1603074.7839401108 6463991.950499589, 1603090.513384159 6463971.106984773, 1603146.6963311615 6463924.630126579, 1603157.794884393 6463914.581579376, 1603202.3783404578 6463872.287568242, 1603217.2506244255 6463859.844110653, 1603317.7832565615 6463836.796863219, 1603334.948722044 6463832.631704839, 1603497.3304632641 6463793.166932718, 1603513.6499006122 6463789.557147608, 1603542.0029749167 6463784.4895673115, 1603795.889337571 6463785.444077063)", "length": 1077.3606756995746, "n_segments": 14, "nodeID": 4, "stroke_access": 3, "stroke_betweenness": 0.5046296296296297, "stroke_closeness": 0.75, "stroke_connectivity": 9, "stroke_degree": 6, "stroke_orthogonality": 87.28338224081126, "stroke_spacing": 119.70674174439718, "x": "array(\\u0027d\\u0027, [1603264.6577362637])", "y": "array(\\u0027d\\u0027, [6463848.97596353])"}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.401228358834482, 50.10108780709868], "geometry": {"coordinates": [14.401228358834482, 50.10108780709868], "type": "Point"}, "id": "5", "properties": {"__folium_color": "black", "edge_ids": "[10]", "geometry_stroke": "LINESTRING (1603071.956425043 6463729.978565, 1603089.0217029832 6463747.749702545, 1603202.3783404578 6463872.287568242)", "length": 193.04063727323836, "n_segments": 2, "nodeID": 5, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 87.60977577529626, "stroke_spacing": 193.04063727323836, "x": "array(\\u0027d\\u0027, [1603137.4077031056])", "y": "array(\\u0027d\\u0027, [6463800.908382258])"}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [14.405314141282124, 50.102934111376484], "type": "Point"}, "id": "6", "properties": {"__folium_color": "black", "edge_ids": "[16 17 18 23 29]", "geometry_stroke": "LINESTRING (1603706.3884669733 6464617.783583014, 1603705.7539458754 6464597.632755783, 1603681.3749773917 6464489.555035355, 1603678.970476391 6464477.214790825, 1603675.6865514126 6464464.336524226, 1603674.2282660832 6464458.799917089, 1603650.450422848 6464368.600601688, 1603607.3029882177 6464181.852772597, 1603558.489391506 6463985.80677705, 1603513.6499006122 6463789.557147608, 1603480.142733884 6463653.653349537, 1603478.918219486 6463648.325535514, 1603477.8829482212 6463643.67454756, 1603473.6416756227 6463625.487127112)", "length": 1019.7095084794428, "n_segments": 13, "nodeID": 6, "stroke_access": 4, "stroke_betweenness": 0.06712962962962961, "stroke_closeness": 0.6, "stroke_connectivity": 7, "stroke_degree": 3, "stroke_orthogonality": 76.50850905913968, "stroke_spacing": 145.67278692563468, "x": "array(\\u0027d\\u0027, [1603592.2349246691])", "y": "array(\\u0027d\\u0027, [6464121.336160048])"}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.101662206397165, 14.400252154982407, 50.101662206397165], "geometry": {"coordinates": [14.400252154982407, 50.101662206397165], "type": "Point"}, "id": "7", "properties": {"__folium_color": "black", "edge_ids": "[19]", "geometry_stroke": "LINESTRING (1602959.8799617135 6463839.712475327, 1602973.3607520477 6463844.207379333, 1602987.0753133134 6463853.041000848, 1603090.513384159 6463971.106984773)", "length": 187.49184699173748, "n_segments": 3, "nodeID": 7, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.45, "stroke_connectivity": 1, "stroke_degree": 1, "stroke_orthogonality": 78.26155769686821, "stroke_spacing": 187.49184699173748, "x": "array(\\u0027d\\u0027, [1603028.737187382])", "y": "array(\\u0027d\\u0027, [6463900.594576759])"}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.401858879914098, 50.102192963132694], "geometry": {"coordinates": [14.401858879914098, 50.102192963132694], "type": "Point"}, "id": "8", "properties": {"__folium_color": "black", "edge_ids": "[20]", "geometry_stroke": "LINESTRING (1603146.6963311615 6463924.630126579, 1603157.0490438067 6463936.205929175, 1603258.3275165292 6464049.413615812, 1603268.502117987 6464060.781328565)", "length": 182.6849740039611, "n_segments": 3, "nodeID": 8, "stroke_access": 0, "stroke_betweenness": 0.020833333333333332, "stroke_closeness": 0.5, "stroke_connectivity": 2, "stroke_degree": 2, "stroke_orthogonality": 78.91626592156373, "stroke_spacing": 91.34248700198054, "x": "array(\\u0027d\\u0027, [1603207.5969886228])", "y": "array(\\u0027d\\u0027, [6463992.707728057])"}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.1045764058213, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [14.403069321103317, 50.1045764058213], "type": "Point"}, "id": "9", "properties": {"__folium_color": "black", "edge_ids": "[26]", "geometry_stroke": "LINESTRING (1603287.303979983 6464587.704889874, 1603286.8809659188 6464556.602281818, 1603337.5981259246 6464418.98505148, 1603340.9265786987 6464409.959912292, 1603345.6687890065 6464397.932193951, 1603413.2063240695 6464228.730248732)", "length": 382.50195042922803, "n_segments": 5, "nodeID": 9, "stroke_access": 0, "stroke_betweenness": 0.0, "stroke_closeness": 0.5, "stroke_connectivity": 3, "stroke_degree": 3, "stroke_orthogonality": 59.350287847902734, "stroke_spacing": 127.50065014307602, "x": "array(\\u0027d\\u0027, [1603342.3426854417])", "y": "array(\\u0027d\\u0027, [6464406.368225728])"}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1.bindTooltip(\n", + " geo_json_55272696570db606458acfba7e68f342.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -834,63 +754,63 @@ "});\n", " \n", " \n", - " geo_json_724ab5ab1a419daf695c69a0ba3e0ac1.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " geo_json_55272696570db606458acfba7e68f342.addTo(map_0e2c896b366477a676b80af2d1218430);\n", " \n", " \n", - " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_styler(feature) {\n", + " function geo_json_2042153cc677b3cbdeacf282db632a9d_styler(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"color": "blue", "fillColor": "blue", "fillOpacity": 0.5, "weight": 2};\n", " }\n", " }\n", - " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_highlighter(feature) {\n", + " function geo_json_2042153cc677b3cbdeacf282db632a9d_highlighter(feature) {\n", " switch(feature.id) {\n", " default:\n", " return {"fillOpacity": 0.75};\n", " }\n", " }\n", - " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_pointToLayer(feature, latlng) {\n", + " function geo_json_2042153cc677b3cbdeacf282db632a9d_pointToLayer(feature, latlng) {\n", " var opts = {"bubblingMouseEvents": true, "color": "#3388ff", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3388ff", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 2, "stroke": true, "weight": 3};\n", " \n", - " let style = geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_styler(feature)\n", + " let style = geo_json_2042153cc677b3cbdeacf282db632a9d_styler(feature)\n", " Object.assign(opts, style)\n", " \n", " return new L.CircleMarker(latlng, opts)\n", " }\n", "\n", - " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_onEachFeature(feature, layer) {\n", + " function geo_json_2042153cc677b3cbdeacf282db632a9d_onEachFeature(feature, layer) {\n", " layer.on({\n", " mouseout: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2.resetStyle(e.target);\n", + " geo_json_2042153cc677b3cbdeacf282db632a9d.resetStyle(e.target);\n", " }\n", " },\n", " mouseover: function(e) {\n", " if(typeof e.target.setStyle === "function"){\n", - " const highlightStyle = geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_highlighter(e.target.feature)\n", + " const highlightStyle = geo_json_2042153cc677b3cbdeacf282db632a9d_highlighter(e.target.feature)\n", " e.target.setStyle(highlightStyle);\n", " }\n", " },\n", " });\n", " };\n", - " var geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2 = L.geoJson(null, {\n", - " onEachFeature: geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_onEachFeature,\n", + " var geo_json_2042153cc677b3cbdeacf282db632a9d = L.geoJson(null, {\n", + " onEachFeature: geo_json_2042153cc677b3cbdeacf282db632a9d_onEachFeature,\n", " \n", - " style: geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_styler,\n", - " pointToLayer: geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_pointToLayer,\n", + " style: geo_json_2042153cc677b3cbdeacf282db632a9d_styler,\n", + " pointToLayer: geo_json_2042153cc677b3cbdeacf282db632a9d_pointToLayer,\n", " ...{\n", "}\n", " });\n", "\n", - " function geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_add (data) {\n", - " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2\n", + " function geo_json_2042153cc677b3cbdeacf282db632a9d_add (data) {\n", + " geo_json_2042153cc677b3cbdeacf282db632a9d\n", " .addData(data);\n", " }\n", - " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "blue", "angles": "[np.float64(62.30218235695145), np.float64(63.647466378271766)]", "node_end": 2, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "blue", "angles": "[np.float64(36.134980718680936)]", "node_end": 9, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "blue", "angles": "[np.float64(29.396028363390094)]", "node_end": 3, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.74560192447649), np.float64(89.75267804978043)]", "node_end": 1, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.56623033507175), np.float64(89.42915166171285)]", "node_end": 4, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "blue", "angles": "[np.float64(70.04113695824684)]", "node_end": 8, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.53084497276808), np.float64(89.58581817377714)]", "node_end": 3, "node_start": 1, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.2861856598184)]", "node_end": 6, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "blue", "angles": "[np.float64(53.8322224050728)]", "node_end": 9, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "blue", "angles": "[np.float64(34.25143801488166)]", "node_end": 3, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "blue", "angles": "[np.float64(84.23886881283048), np.float64(80.16976627731358), np.float64(47.16443370903166), np.float64(59.79419820769667)]", "node_end": 6, "node_start": 2, "number_connections": 4}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "blue", "angles": "[np.float64(88.08366041995446)]", "node_end": 9, "node_start": 3, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "blue", "angles": "[np.float64(88.78833801117518), np.float64(89.19788105500966)]", "node_end": 4, "node_start": 3, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "blue", "angles": "[np.float64(78.26155769686821)]", "node_end": 7, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "blue", "angles": "[np.float64(87.60977577529626)]", "node_end": 5, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "blue", "angles": "[np.float64(86.2834611843536), np.float64(88.62264956293333)]", "node_end": 6, "node_start": 4, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "blue", "angles": "[np.float64(87.79139488488063)]", "node_end": 8, "node_start": 4, "number_connections": 1}, "type": "Feature"}], "type": "FeatureCollection"});\n", + " geo_json_2042153cc677b3cbdeacf282db632a9d_add({"bbox": [14.400252154982407, 50.10108780709868, 14.406346050295715, 50.1045764058213], "features": [{"bbox": [14.40335965524552, 50.10268382777764, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "0", "properties": {"__folium_color": "blue", "angles": "[np.float64(62.30218235695145), np.float64(63.647466378271766)]", "node_end": 2, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10268382777764, 14.40335965524552, 50.1045764058213], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.403069321103317, 50.1045764058213]], "type": "LineString"}, "id": "1", "properties": {"__folium_color": "blue", "angles": "[np.float64(36.134980718680936)]", "node_end": 9, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10268382777764, 14.40335965524552, 50.10298532497958], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "2", "properties": {"__folium_color": "blue", "angles": "[np.float64(29.396028363390094)]", "node_end": 3, "node_start": 0, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.10268382777764, 14.40335965524552, 50.10300490375251], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "3", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.74560192447649), np.float64(89.75267804978043)]", "node_end": 1, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.40335965524552, 50.10268382777764], "geometry": {"coordinates": [[14.40335965524552, 50.10268382777764], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "4", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.56623033507175), np.float64(89.42915166171285)]", "node_end": 4, "node_start": 0, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.102192963132694, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40212344975224, 50.10300490375251]], "type": "LineString"}, "id": "5", "properties": {"__folium_color": "blue", "angles": "[np.float64(70.04113695824684)]", "node_end": 8, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.40212344975224, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "6", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.53084497276808), np.float64(89.58581817377714)]", "node_end": 3, "node_start": 1, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.40212344975224, 50.102934111376484, 14.405314141282124, 50.10300490375251], "geometry": {"coordinates": [[14.40212344975224, 50.10300490375251], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "7", "properties": {"__folium_color": "blue", "angles": "[np.float64(89.2861856598184)]", "node_end": 6, "node_start": 1, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.403069321103317, 50.10361123107303, 14.406346050295715, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.406346050295715, 50.10361123107303]], "type": "LineString"}, "id": "8", "properties": {"__folium_color": "blue", "angles": "[np.float64(53.8322224050728)]", "node_end": 9, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "9", "properties": {"__folium_color": "blue", "angles": "[np.float64(34.25143801488166)]", "node_end": 3, "node_start": 2, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.405314141282124, 50.102934111376484, 14.406346050295715, 50.10361123107303], "geometry": {"coordinates": [[14.406346050295715, 50.10361123107303], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "10", "properties": {"__folium_color": "blue", "angles": "[np.float64(84.23886881283048), np.float64(80.16976627731358), np.float64(47.16443370903166), np.float64(59.79419820769667)]", "node_end": 6, "node_start": 2, "number_connections": 4}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10298532497958, 14.403069321103317, 50.1045764058213], "geometry": {"coordinates": [[14.403069321103317, 50.1045764058213], [14.401340838490729, 50.10298532497958]], "type": "LineString"}, "id": "11", "properties": {"__folium_color": "blue", "angles": "[np.float64(88.08366041995446)]", "node_end": 9, "node_start": 3, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401340838490729, 50.10136477695206, 14.40237146533139, 50.10298532497958], "geometry": {"coordinates": [[14.401340838490729, 50.10298532497958], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "12", "properties": {"__folium_color": "blue", "angles": "[np.float64(88.78833801117518), np.float64(89.19788105500966)]", "node_end": 4, "node_start": 3, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.400252154982407, 50.10136477695206, 14.40237146533139, 50.101662206397165], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.400252154982407, 50.101662206397165]], "type": "LineString"}, "id": "13", "properties": {"__folium_color": "blue", "angles": "[np.float64(78.26155769686821)]", "node_end": 7, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.401228358834482, 50.10108780709868, 14.40237146533139, 50.10136477695206], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.401228358834482, 50.10108780709868]], "type": "LineString"}, "id": "14", "properties": {"__folium_color": "blue", "angles": "[np.float64(87.60977577529626)]", "node_end": 5, "node_start": 4, "number_connections": 1}, "type": "Feature"}, {"bbox": [14.40237146533139, 50.10136477695206, 14.405314141282124, 50.102934111376484], "geometry": {"coordinates": [[14.40237146533139, 50.10136477695206], [14.405314141282124, 50.102934111376484]], "type": "LineString"}, "id": "15", "properties": {"__folium_color": "blue", "angles": "[np.float64(86.2834611843536), np.float64(88.62264956293333)]", "node_end": 6, "node_start": 4, "number_connections": 2}, "type": "Feature"}, {"bbox": [14.401858879914098, 50.10136477695206, 14.40237146533139, 50.102192963132694], "geometry": {"coordinates": [[14.401858879914098, 50.102192963132694], [14.40237146533139, 50.10136477695206]], "type": "LineString"}, "id": "16", "properties": {"__folium_color": "blue", "angles": "[np.float64(87.79139488488063)]", "node_end": 8, "node_start": 4, "number_connections": 1}, "type": "Feature"}], "type": "FeatureCollection"});\n", "\n", " \n", " \n", - " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2.bindTooltip(\n", + " geo_json_2042153cc677b3cbdeacf282db632a9d.bindTooltip(\n", " function(layer){\n", " let div = L.DomUtil.create('div');\n", " \n", @@ -917,40 +837,40 @@ "});\n", " \n", " \n", - " geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2.addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " geo_json_2042153cc677b3cbdeacf282db632a9d.addTo(map_0e2c896b366477a676b80af2d1218430);\n", " \n", " \n", - " var layer_control_7351cd324649a2def3af29bb0439822d_layers = {\n", + " var layer_control_04154b5179cddfeacf029de7c0bc3b84_layers = {\n", " base_layers : {\n", - " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_75a780ad99b6f7bd559c3dfd418bd85f,\n", + " "https://a.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png" : tile_layer_764af7bd73b97e22bfeaab9072744982,\n", " },\n", " overlays : {\n", - " "strokes" : geo_json_a75521f1f7e4c097815fc719c81c67c1,\n", - " "points_primal" : geo_json_ee641df7eb7cd19f1e10dabfa62ecdcf,\n", - " "lines_primal" : geo_json_838def6cdf8f4f50b5af320d0954887d,\n", - " "points_stroke" : geo_json_724ab5ab1a419daf695c69a0ba3e0ac1,\n", - " "lines_stroke" : geo_json_b0d3b76d7748d11b7b89ed84c1b96fa2,\n", + " "strokes" : geo_json_f4d755600a90a349640574af8bd3bbbf,\n", + " "points_primal" : geo_json_da9f3ba6358d6538f4138a8c8ddc5bd2,\n", + " "lines_primal" : geo_json_36a89c55260edb5b9ab90f4bad27029b,\n", + " "points_stroke" : geo_json_55272696570db606458acfba7e68f342,\n", + " "lines_stroke" : geo_json_2042153cc677b3cbdeacf282db632a9d,\n", " },\n", " };\n", - " let layer_control_7351cd324649a2def3af29bb0439822d = L.control.layers(\n", - " layer_control_7351cd324649a2def3af29bb0439822d_layers.base_layers,\n", - " layer_control_7351cd324649a2def3af29bb0439822d_layers.overlays,\n", + " let layer_control_04154b5179cddfeacf029de7c0bc3b84 = L.control.layers(\n", + " layer_control_04154b5179cddfeacf029de7c0bc3b84_layers.base_layers,\n", + " layer_control_04154b5179cddfeacf029de7c0bc3b84_layers.overlays,\n", " {\n", " "position": "topright",\n", " "collapsed": true,\n", " "autoZIndex": true,\n", "}\n", - " ).addTo(map_f485c7cefc845a343e7d2e56682f6348);\n", + " ).addTo(map_0e2c896b366477a676b80af2d1218430);\n", "\n", " \n", "</script>\n", "</html>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen>" ], "text/plain": [ - "" + "" ] }, - "execution_count": 120, + "execution_count": 138, "metadata": {}, "output_type": "execute_result" } diff --git a/momepy/strokegraph_function_compare.ipynb b/momepy/strokegraph_function_compare.ipynb new file mode 100644 index 00000000..2a972bb1 --- /dev/null +++ b/momepy/strokegraph_function_compare.ipynb @@ -0,0 +1,1474 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "738651d2", + "metadata": {}, + "outputs": [], + "source": [ + "import geopandas as gpd\n", + "import momepy\n", + "import networkx as nx\n", + "from itertools import combinations, product\n", + "import shapely\n", + "import numpy as np\n", + "import pickle\n", + "\n", + "from shapely import LineString\n", + "import math\n", + "from collections import Counter\n", + "\n", + "import osmnx as ox\n", + "import time" + ] + }, + { + "cell_type": "markdown", + "id": "01166e83", + "metadata": {}, + "source": [ + "## CLSE functions" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "1d99fa24", + "metadata": {}, + "outputs": [], + "source": [ + "def make_stroke_graph_clse(gdf, compute_metric=True, output=\"dataframe\"):\n", + " if output not in [\"dataframe\", \"graph\"]:\n", + " raise ValueError(\"output need to be either dataframe or graph\")\n", + " # Transform into primal graph\n", + " G_primal = momepy.gdf_to_nx(gdf, approach=\"primal\", preserve_index=True)\n", + " lines_primal = momepy.nx_to_gdf(G_primal, points=False, lines=True)\n", + " # Use COINS on primal graph edges\n", + " coins = momepy.COINS(lines_primal)\n", + " # List the stroke for each edge\n", + " stroke_attribute = coins.stroke_attribute()\n", + " # List each edge for each stroke\n", + " stroke_gdf = coins.stroke_gdf()\n", + " stroke_gdf[\"edge_ids\"] = [stroke_attribute[stroke_attribute == stroke_id].index.values for stroke_id in stroke_gdf.index.values]\n", + " # Add stroke ID to each edge\n", + " nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[G_primal.edges[e][\"index_position\"]]) for e in G_primal.edges}, \"stroke_id\")\n", + " # Create stroke graph\n", + " G_stroke = nx.Graph()\n", + " G_stroke.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", + " # Create a node for each stroke with the right features\n", + " G_stroke.add_nodes_from([[int(idx), {(attr if attr != \"geometry\" else \"geometry_stroke\"):stroke_gdf.loc[idx][attr] for attr in list(stroke_gdf)}] for idx in stroke_gdf.index.values])\n", + " # For all node, put its geometry at the center of the LineString\n", + " for n in G_stroke.nodes:\n", + " G_stroke.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", + " G_stroke.nodes[n][\"x\"] = G_stroke.nodes[n][\"geometry\"].xy[0]\n", + " G_stroke.nodes[n][\"y\"] = G_stroke.nodes[n][\"geometry\"].xy[1]\n", + " G_stroke.nodes[n][\"length\"] = G_stroke.nodes[n][\"geometry_stroke\"].length\n", + " # Find strokes intersecting\n", + " for n in G_primal.nodes:\n", + " strokes_present = [G_primal.edges[e][\"stroke_id\"] for e in G_primal.edges(n, keys=True)]\n", + " # If strokes intersecting, add the edge if not already present\n", + " if len(set(strokes_present)) > 1:\n", + " for u, v in combinations(set(strokes_present), 2):\n", + " # Find all edges touching the node for both strokes checked\n", + " edges_u = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == u]\n", + " edges_v = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == v]\n", + " angle_list = []\n", + " angle_dict = {}\n", + " # Choose the smallest list as number of angles kept\n", + " chosen, other = sorted([edges_u, edges_v], key=len)\n", + " # Find the angles\n", + " for ce, oe in list(product(chosen, other)):\n", + " point = [G_primal.nodes[n][\"x\"], G_primal.nodes[n][\"y\"]]\n", + " gc = find_geom(G_primal.edges[ce][\"geometry\"], point)\n", + " go = find_geom(G_primal.edges[oe][\"geometry\"], point)\n", + " if ce in angle_dict:\n", + " angle_dict[ce].append(angle(gc, go))\n", + " else:\n", + " angle_dict[ce]= [angle(gc, go)]\n", + " # Keep the smallest angles\n", + " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", + " if G_stroke.has_edge(u, v):\n", + " G_stroke.edges[u, v][\"angles\"] += angle_list\n", + " G_stroke.edges[u, v][\"number_connections\"] = len(G_stroke.edges[u, v][\"angles\"])\n", + " else:\n", + " G_stroke.add_edge(u, v, geometry = shapely.LineString([G_stroke.nodes[u][\"geometry\"], G_stroke.nodes[v][\"geometry\"]]), number_connections=len(angle_list), angles=angle_list)\n", + " if compute_metric:\n", + " nx.set_node_attributes(G_stroke, nx.betweenness_centrality(G_stroke), \"stroke_betweenness\")\n", + " nx.set_node_attributes(G_stroke, nx.closeness_centrality(G_stroke), \"stroke_closeness\")\n", + " nx.set_node_attributes(G_stroke, dict(nx.degree(G_stroke)), \"stroke_degree\")\n", + " for n in G_stroke.nodes:\n", + " G_stroke.nodes[n][\"stroke_connectivity\"] = sum([G_stroke.edges[e][\"number_connections\"] for e in G_stroke.edges(n)])\n", + " G_stroke.nodes[n][\"stroke_access\"] = G_stroke.nodes[n][\"stroke_connectivity\"] - G_stroke.nodes[n][\"stroke_degree\"]\n", + " angles = [val for e in G_stroke.edges(n) if G_stroke.edges[e][\"angles\"] for val in G_stroke.edges[e][\"angles\"]]\n", + " G_stroke.nodes[n][\"stroke_orthogonality\"] = sum(angles) / G_stroke.nodes[n][\"stroke_connectivity\"]\n", + " G_stroke.nodes[n][\"stroke_spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]\n", + " if output == \"dataframe\":\n", + " return momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n", + " elif output == \"graph\":\n", + " return G_stroke\n", + "\n", + "def angle(a, b):\n", + " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", + " if angle > 90:\n", + " angle = 180 - angle\n", + " return angle\n", + "\n", + "def find_geom(linestring, point):\n", + " if point == list(linestring.coords[0]):\n", + " geom = [np.array(val) for val in linestring.coords[:2]]\n", + " else:\n", + " geom = [np.array(val) for val in linestring.coords[-2:]]\n", + " return np.array(geom[0] - geom[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "7a369a85", + "metadata": {}, + "outputs": [], + "source": [ + "# define variable defaults (will be arguments passed to future function)\n", + "angle_threshold=0\n", + "flow_mode=False\n", + "# remove false nodes\n", + "\n", + "def make_stroke_graph_anvy(gdf, compute_metric=True, output=\"dataframe\"):\n", + " # make primal graph\n", + " graph = momepy.gdf_to_nx(\n", + " gdf, \n", + " preserve_index=True, # index of lines gdf should be referring to EXACTLY THE SAME ELEMENT as index of streets gdf\n", + " approach=\"primal\"\n", + " )\n", + " # get gdfs of points and lines\n", + " points, lines = momepy.nx_to_gdf(graph, points=True, lines=True)\n", + " lines[\"my_index\"] = lines.index # just for plotting TODO remove later\n", + " # make coins\n", + " coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", + " # get gdfs from COINS class\n", + " stroke_attribute = coins.stroke_attribute()\n", + " stroke_gdf = coins.stroke_gdf()\n", + " stroke_gdf[\"rep_point\"] = stroke_gdf.geometry.apply(lambda x: x.interpolate(0.5, normalized=True))\n", + " # add stroke_id column\n", + " stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", + " # add edge_ids column (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", + " stroke_gdf[\"edge_indeces\"] = stroke_gdf.stroke_id.apply(\n", + " lambda x: list(stroke_attribute[stroke_attribute==x].index)\n", + " )\n", + " # make dictionary for primal graph: d={edge_index:edge_name}\n", + " # where edge_name (in momepy language) is the corresponding node tuple\n", + " d_name2index = nx.get_edge_attributes(graph, \"index_position\")\n", + " d_index2name = {v:k for k,v in d_name2index.items()}\n", + " # for each edge, add \"stroke_id\" as attribute to graph\n", + " for _, row in stroke_gdf.iterrows():\n", + " for edge_index in row.edge_indeces: \n", + " graph.edges[d_index2name[edge_index]][\"stroke_id\"] = row.stroke_id\n", + " # getting dicts of edge name : stroke ID, and edge index : stroke id # TODO: one of them might be obsolete?\n", + " d_name2stroke = nx.get_edge_attributes(graph, \"stroke_id\")\n", + " d_index2stroke = {d_name2index[k]:v for k,v in d_name2stroke.items()} \n", + " stroke_graph = nx.Graph()\n", + " stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", + " stroke_graph.graph[\"approach\"] = graph.graph[\"approach\"]\n", + " stroke_graph.add_nodes_from(\n", + " [\n", + " (\n", + " row.stroke_id, \n", + " {\n", + " \"edge_indeces\": row.edge_indeces,\n", + " \"geometry\": row.rep_point,\n", + " \"geometry_stroke\": row.geometry,\n", + " \"x\": row.rep_point.xy[0][0],\n", + " \"y\": row.rep_point.xy[1][0],\n", + " \"connectivity\": 0\n", + " }\n", + " ) for _, row in stroke_gdf.iterrows()\n", + " ]\n", + " )\n", + " # node names are the stroke IDs.\n", + " # each node has the attribute \"edge_indeces\".\n", + " stroke_graph.nodes(data=True)\n", + " for n in graph.nodes:\n", + " es = list(graph.edges(n, keys=True))\n", + " stroke_list = [graph.edges[e][\"stroke_id\"] for e in es]\n", + " stroke_set = set(stroke_list)\n", + " # for all size2 combinations from stroke_set\n", + " for c in combinations(stroke_set, 2):\n", + " # get angles at that primal node for this 2-stroke combination c\n", + " es = list(graph.edges(n, keys=True))\n", + " stroke_ids = [graph.edges[e][\"stroke_id\"] for e in es]\n", + " geoms = [graph.edges[e][\"geometry\"] for e in es]\n", + " segments = [get_segment(geom, n) for geom in geoms] # extracting only edge segments that touch this node\n", + " angles_gdf = gpd.GeoDataFrame(\n", + " {\n", + " \"stroke_id\": stroke_ids,\n", + " \"segment\": segments,\n", + " \"geometry\": [LineString(x) for x in segments]\n", + " }\n", + " )\n", + " # filter out only those linestring that belong to current 2-stroke edge\n", + " angles_gdf = angles_gdf[angles_gdf.stroke_id.isin(c)].reset_index(drop=True)\n", + " if len(angles_gdf)==2:\n", + " # connectivity equals 1 here\n", + " connectivity = 1\n", + " # angle between 2 strokes is just angle between \n", + " # the 2 linestrings in the gdf:\n", + " row_a = angles_gdf.loc[0]\n", + " row_b = angles_gdf.loc[1]\n", + " angles = [\n", + " get_interior_angle(\n", + " row_a.segment[1],\n", + " row_a.segment[0],\n", + " row_b.segment[1]\n", + " )\n", + " ]\n", + " elif len(angles_gdf)==3:\n", + " # connectivity equals 1 here\n", + " connectivity = 1\n", + " # the iteration has to go through the stroke that appears TWICE\n", + " stroke_count = dict(Counter(angles_gdf.stroke_id))\n", + " stroke_count = {v:k for k,v in stroke_count.items()}\n", + " # separate angles_gdf into 2 separate gdf (one for each stroke)\n", + " angles_stroke_a = angles_gdf[angles_gdf[\"stroke_id\"]==stroke_count[1]].copy()\n", + " angles_stroke_b = angles_gdf[angles_gdf[\"stroke_id\"]==stroke_count[2]].copy()\n", + " angles = []\n", + " # there is only ONE row_a stroke segment\n", + " for i, row_a in angles_stroke_a.iterrows():\n", + " angles_stroke = []\n", + " # iterate through BOTH stroke b segments\n", + " for j, row_b in angles_stroke_b.iterrows():\n", + " assert row_a.segment[0] == row_b.segment[0]\n", + " # compute angle between stroke a and stroke b segments\n", + " # and add to list of current angles\n", + " angles_stroke.append(get_interior_angle(\n", + " row_a.segment[1],\n", + " row_a.segment[0],\n", + " row_b.segment[1])\n", + " )\n", + " # keep the smaller of the 2 angles to add to list of angles for the stroke pair\n", + " angles.append(min(angles_stroke))\n", + " elif len(angles_gdf)==4:\n", + " # connectivity equals 2 here\n", + " connectivity = 2\n", + " # separate angles_gdf into 2 separate gdf (one for each stroke)\n", + " angles_stroke_a = angles_gdf[angles_gdf[\"stroke_id\"]==c[0]].copy()\n", + " angles_stroke_b = angles_gdf[angles_gdf[\"stroke_id\"]==c[1]].copy()\n", + " angles = []\n", + " # iterate through stroke a segments\n", + " for i, row_a in angles_stroke_a.iterrows():\n", + " # iterate through stroke b segments\n", + " angles_partial = []\n", + " for j, row_b in angles_stroke_b.iterrows():\n", + " assert row_a.segment[0] == row_b.segment[0]\n", + " # compute angle between stroke a and stroke b segments\n", + " # and add to list of current angles\n", + " angle = get_interior_angle(\n", + " row_a.segment[1],\n", + " row_a.segment[0],\n", + " row_b.segment[1])\n", + " # if angle > 90:\n", + " # angle = 180 - angle\n", + " angles_partial.append(angle)\n", + " angles.append(min(angles_partial)) # @csebastiao we're keeping the minimal here?\n", + " else:\n", + " ValueError(f\"Length of angles_gdf expected to be in [2,3,4], but is {len(angles_gdf)}\")\n", + " # connectivity is added at stroke node level:\n", + " for s in c:\n", + " stroke_graph.nodes[s][\"connectivity\"] += connectivity\n", + " # and edge (or update edge info) at stroke edge level:\n", + " if c not in stroke_graph.edges:\n", + " edge_geom = LineString(\n", + " [\n", + " stroke_graph.nodes[c[0]][\"geometry\"],\n", + " stroke_graph.nodes[c[1]][\"geometry\"]\n", + " ]\n", + " )\n", + " stroke_graph.add_edge(\n", + " c[0],\n", + " c[1],\n", + " geometry=edge_geom,\n", + " angles=angles\n", + " )\n", + " else:\n", + " stroke_graph.edges[c][\"angles\"] += angles\n", + " # we want to add edges for all stroke IDs that co-occur on edges that share the same node in the primal graph\n", + " # [0, 1, 1] means: stroke0 has an endpoint here; stroke1 has a throughpoint here; we add the edge [0,1] in the strokes_graph, with the attribute \n", + " # stroke = {0: \"end\", 1: \"through\"}\n", + " # add graph metrics\n", + " # betweenness centrality dict for all nodes\n", + " if compute_metric:\n", + " bc = nx.betweenness_centrality(stroke_graph)\n", + " # closeness centrality dict for all nodes\n", + " cc = nx.closeness_centrality(stroke_graph)\n", + " for n in stroke_graph.nodes:\n", + " stroke_graph.nodes[n][\"degree\"] = nx.degree(stroke_graph, n)\n", + " stroke_graph.nodes[n][\"betweenness_centrality\"] = bc[n]\n", + " stroke_graph.nodes[n][\"closeness_centrality\"] = cc[n]\n", + " # just for sanity check # TODO can be removed later\n", + " stroke_graph.nodes[n][\"connectivity_computed\"] = sum(\n", + " [len(stroke_graph.edges[edge][\"angles\"]) for edge in stroke_graph.edges(n)]\n", + " ) \n", + " assert stroke_graph.nodes[n][\"connectivity\"] == stroke_graph.nodes[n][\"connectivity_computed\"]\n", + " # access = abs(connectivity - degree)\n", + " stroke_graph.nodes[n][\"access\"] = abs(stroke_graph.nodes[n][\"connectivity\"] - stroke_graph.nodes[n][\"degree\"])\n", + " # spacing = length / connectivity\n", + " stroke_graph.nodes[n][\"length\"] = stroke_graph.nodes[n][\"geometry_stroke\"].length # compute length first\n", + " stroke_graph.nodes[n][\"spacing\"] = stroke_graph.nodes[n][\"length\"] / stroke_graph.nodes[n][\"connectivity\"]\n", + " # orthogonality = sum(angles) / connectivity\n", + " # compute sum of angles of edges of that node first\n", + " node_angles = [stroke_graph.edges[edge][\"angles\"] for edge in stroke_graph.edges(n)]\n", + " node_angles = [item for sublist in node_angles for item in sublist] # un-nest list\n", + " stroke_graph.nodes[n][\"orthogonality\"] = sum(node_angles)/stroke_graph.nodes[n][\"connectivity\"]\n", + " if output == \"dataframe\":\n", + " return momepy.nx_to_gdf(stroke_graph, points=True, lines=True)\n", + " elif output == \"graph\":\n", + " return stroke_graph\n", + "\n", + "def get_interior_angle(a, b, c):\n", + " \"\"\"\n", + " Measure the angle between a-b, b-c (in degrees).\n", + " \"\"\"\n", + " ba = [a[0]-b[0],a[1]-b[1]]\n", + " bc = [c[0]-b[0],c[1]-b[1]]\n", + " # np.dot(ba, bc) # ba[0]*bc[0] + ba[1]*bc[1]\n", + " # np.linalg.norm(ba) # np.sqrt(ba[0]**2+ba[1]**2)\n", + " # np.linalg.norm(bc) # np.sqrt(bc[0]**2+bc[1]**2)\n", + " theta_rad = math.acos(np.dot(ba,bc)/(np.linalg.norm(ba)*np.linalg.norm(bc)))\n", + " theta_deg = np.degrees(theta_rad)\n", + " if theta_deg > 90:\n", + " theta_deg = 180 - theta_deg\n", + " return theta_deg\n", + "\n", + "def get_segment(geom, n):\n", + " '''\n", + " geom... linestring.\n", + " n.... coordinate of start-or-end node on linestring.\n", + " returns: coordinate tuple (n, adjacent-to-n), in THAT ORDER\n", + " (ie. if n is start node, returns coords in position 0 and 1;\n", + " if n is end node, reutnrs coords in position n, n-1\n", + " )\n", + " '''\n", + " coords = [c for c in geom.coords]\n", + " index_n = coords.index(n)\n", + " if index_n == 0:\n", + " return coords[0:2]\n", + " elif index_n == len(coords)-1:\n", + " return [coords[index_n], coords[index_n-1]]\n", + " else:\n", + " raise ValueError(\"Node not on end of edge?\")\n", + "\n", + "# use angles_gdf length to add to connectivity of strokes (nodes)\n", + "def get_connectivity(angles_gdf):\n", + " if len(angles_gdf)==4:\n", + " return 2\n", + " elif len(angles_gdf) in [2,3]:\n", + " return 1\n", + " else:\n", + " raise ValueError(\"Unexpected number of edge segments in angles_gdf\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "eec125ad", + "metadata": {}, + "outputs": [], + "source": [ + "gdf = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", + "gdf = momepy.remove_false_nodes(gdf)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "2d193aa8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(0.03989638328552246)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr = []\n", + "for _ in range(100):\n", + " beg = time.time()\n", + " G_stroke_clse = make_stroke_graph_clse(gdf, compute_metric=True, output=\"graph\")\n", + " end = time.time()\n", + " arr.append(end - beg)\n", + "np.mean(arr)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "b72b7c07", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(0.09599937915802002)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "arr = []\n", + "for _ in range(100):\n", + " beg = time.time()\n", + " G_stroke_anvy = make_stroke_graph_anvy(gdf, compute_metric=True, output=\"graph\")\n", + " end = time.time()\n", + " arr.append(end - beg)\n", + "np.mean(arr)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "92c9d466", + "metadata": {}, + "outputs": [], + "source": [ + "G = ox.graph_from_place(\"Aix-en-Provence, France\")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "3a02b257", + "metadata": {}, + "outputs": [], + "source": [ + "G = ox.convert.to_undirected(G)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "7200ae13", + "metadata": {}, + "outputs": [], + "source": [ + "gdf = ox.graph_to_gdfs(\n", + " G,\n", + " nodes=False,\n", + " edges=True,\n", + " node_geometry=False,\n", + " fill_edge_geometry=True,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "bfa58f48", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
osmidhighwaylanesmaxspeednameonewayrefreversedlengthgeometryfromtobridgejunctionaccessservicewidthtunnel
uvkey
553604594607072300[355742063, 147498237, 90283751]trunk2[90, 70]Avenue de la 1e Division FrançaiseTrueN 296False1038.297695LINESTRING (5.44934 43.55847, 5.44908 43.55836...55360459460707230NaNNaNNaNNaNNaNNaN
2770354880[90283752, 90283753, 25419836]trunk_link1110NaNTrueNaNFalse224.338024LINESTRING (5.45133 43.55971, 5.45138 43.55962...2770354885536045yesNaNNaNNaNNaNNaN
10470014030[685260154, 90283748, 90283751]trunk290Avenue de la 1e Division FrançaiseTrueN 296False364.686411LINESTRING (5.45305 43.56034, 5.45259 43.56007...10470014035536045yesNaNNaNNaNNaNNaN
55360522654890260[90731432, 31557546, 179308707]trunk250Avenue de la 1e Division FrançaiseTrueN 296False198.965351LINESTRING (5.43573 43.55346, 5.43543 43.55318...5536052265489026yesNaNNaNNaNNaNNaN
85184530060[90283320, 90283321, 179308930]trunk_linkNaN50NaNTrueNaNFalse147.744228LINESTRING (5.43573 43.55346, 5.43558 43.55335...55360528518453006yesNaNNaNNaNNaNNaN
...............................................................
12819726786128197267930[1384658856, 1384658857]trackNaNNaNNaNFalseNaNFalse117.859117LINESTRING (5.42804 43.59214, 5.42799 43.59202...1281972679312819726786NaNNaNNaNNaNNaNNaN
128407239071284072391801387085145footwayNaNNaNNaNFalseNaNTrue8.950842LINESTRING (5.34713 43.4941, 5.34714 43.49413,...1284072391812840723907NaNNaNNaNNaNNaNNaN
128407239081284072391301387085143serviceNaNNaNNaNFalseNaNTrue33.678924LINESTRING (5.34654 43.4942, 5.34653 43.49421,...1284072391312840723908NaNNaNNaNparking_aisleNaNNaN
128407239111284072391301387085143serviceNaNNaNNaNFalseNaNFalse28.646349LINESTRING (5.34654 43.4942, 5.34656 43.49414,...1284072391312840723911NaNNaNNaNparking_aisleNaNNaN
128407239131284072391501387085144footwayNaNNaNNaNFalseNaNTrue42.460380LINESTRING (5.34696 43.49408, 5.34698 43.49414...1284072391512840723913NaNNaNNaNNaNNaNNaN
\n", + "

28913 rows × 18 columns

\n", + "
" + ], + "text/plain": [ + " osmid highway \\\n", + "u v key \n", + "5536045 9460707230 0 [355742063, 147498237, 90283751] trunk \n", + " 277035488 0 [90283752, 90283753, 25419836] trunk_link \n", + " 1047001403 0 [685260154, 90283748, 90283751] trunk \n", + "5536052 265489026 0 [90731432, 31557546, 179308707] trunk \n", + " 8518453006 0 [90283320, 90283321, 179308930] trunk_link \n", + "... ... ... \n", + "12819726786 12819726793 0 [1384658856, 1384658857] track \n", + "12840723907 12840723918 0 1387085145 footway \n", + "12840723908 12840723913 0 1387085143 service \n", + "12840723911 12840723913 0 1387085143 service \n", + "12840723913 12840723915 0 1387085144 footway \n", + "\n", + " lanes maxspeed \\\n", + "u v key \n", + "5536045 9460707230 0 2 [90, 70] \n", + " 277035488 0 1 110 \n", + " 1047001403 0 2 90 \n", + "5536052 265489026 0 2 50 \n", + " 8518453006 0 NaN 50 \n", + "... ... ... \n", + "12819726786 12819726793 0 NaN NaN \n", + "12840723907 12840723918 0 NaN NaN \n", + "12840723908 12840723913 0 NaN NaN \n", + "12840723911 12840723913 0 NaN NaN \n", + "12840723913 12840723915 0 NaN NaN \n", + "\n", + " name oneway \\\n", + "u v key \n", + "5536045 9460707230 0 Avenue de la 1e Division Française True \n", + " 277035488 0 NaN True \n", + " 1047001403 0 Avenue de la 1e Division Française True \n", + "5536052 265489026 0 Avenue de la 1e Division Française True \n", + " 8518453006 0 NaN True \n", + "... ... ... \n", + "12819726786 12819726793 0 NaN False \n", + "12840723907 12840723918 0 NaN False \n", + "12840723908 12840723913 0 NaN False \n", + "12840723911 12840723913 0 NaN False \n", + "12840723913 12840723915 0 NaN False \n", + "\n", + " ref reversed length \\\n", + "u v key \n", + "5536045 9460707230 0 N 296 False 1038.297695 \n", + " 277035488 0 NaN False 224.338024 \n", + " 1047001403 0 N 296 False 364.686411 \n", + "5536052 265489026 0 N 296 False 198.965351 \n", + " 8518453006 0 NaN False 147.744228 \n", + "... ... ... ... \n", + "12819726786 12819726793 0 NaN False 117.859117 \n", + "12840723907 12840723918 0 NaN True 8.950842 \n", + "12840723908 12840723913 0 NaN True 33.678924 \n", + "12840723911 12840723913 0 NaN False 28.646349 \n", + "12840723913 12840723915 0 NaN True 42.460380 \n", + "\n", + " geometry \\\n", + "u v key \n", + "5536045 9460707230 0 LINESTRING (5.44934 43.55847, 5.44908 43.55836... \n", + " 277035488 0 LINESTRING (5.45133 43.55971, 5.45138 43.55962... \n", + " 1047001403 0 LINESTRING (5.45305 43.56034, 5.45259 43.56007... \n", + "5536052 265489026 0 LINESTRING (5.43573 43.55346, 5.43543 43.55318... \n", + " 8518453006 0 LINESTRING (5.43573 43.55346, 5.43558 43.55335... \n", + "... ... \n", + "12819726786 12819726793 0 LINESTRING (5.42804 43.59214, 5.42799 43.59202... \n", + "12840723907 12840723918 0 LINESTRING (5.34713 43.4941, 5.34714 43.49413,... \n", + "12840723908 12840723913 0 LINESTRING (5.34654 43.4942, 5.34653 43.49421,... \n", + "12840723911 12840723913 0 LINESTRING (5.34654 43.4942, 5.34656 43.49414,... \n", + "12840723913 12840723915 0 LINESTRING (5.34696 43.49408, 5.34698 43.49414... \n", + "\n", + " from to bridge junction access \\\n", + "u v key \n", + "5536045 9460707230 0 5536045 9460707230 NaN NaN NaN \n", + " 277035488 0 277035488 5536045 yes NaN NaN \n", + " 1047001403 0 1047001403 5536045 yes NaN NaN \n", + "5536052 265489026 0 5536052 265489026 yes NaN NaN \n", + " 8518453006 0 5536052 8518453006 yes NaN NaN \n", + "... ... ... ... ... ... \n", + "12819726786 12819726793 0 12819726793 12819726786 NaN NaN NaN \n", + "12840723907 12840723918 0 12840723918 12840723907 NaN NaN NaN \n", + "12840723908 12840723913 0 12840723913 12840723908 NaN NaN NaN \n", + "12840723911 12840723913 0 12840723913 12840723911 NaN NaN NaN \n", + "12840723913 12840723915 0 12840723915 12840723913 NaN NaN NaN \n", + "\n", + " service width tunnel \n", + "u v key \n", + "5536045 9460707230 0 NaN NaN NaN \n", + " 277035488 0 NaN NaN NaN \n", + " 1047001403 0 NaN NaN NaN \n", + "5536052 265489026 0 NaN NaN NaN \n", + " 8518453006 0 NaN NaN NaN \n", + "... ... ... ... \n", + "12819726786 12819726793 0 NaN NaN NaN \n", + "12840723907 12840723918 0 NaN NaN NaN \n", + "12840723908 12840723913 0 parking_aisle NaN NaN \n", + "12840723911 12840723913 0 parking_aisle NaN NaN \n", + "12840723913 12840723915 0 NaN NaN NaN \n", + "\n", + "[28913 rows x 18 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "gdf" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "f2b1a6a7", + "metadata": {}, + "outputs": [], + "source": [ + "gdf = gdf.to_crs(epsg=3857)\n", + "gdf = gdf[~gdf.geometry.duplicated()]" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c40e84c7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
osmidhighwaylanesmaxspeednameonewayrefreversedlengthgeometryfromtobridgejunctionaccessservicewidthtunnel
uvkey
553604594607072300[355742063, 147498237, 90283751]trunk2[90, 70]Avenue de la 1e Division FrançaiseTrueN 296False1038.297695LINESTRING (606617.776 5397366.114, 606588.822...55360459460707230NaNNaNNaNNaNNaNNaN
2770354880[90283752, 90283753, 25419836]trunk_link1110NaNTrueNaNFalse224.338024LINESTRING (606839.625 5397557.657, 606845.102...2770354885536045yesNaNNaNNaNNaNNaN
10470014030[685260154, 90283748, 90283751]trunk290Avenue de la 1e Division FrançaiseTrueN 296False364.686411LINESTRING (607030.872 5397653.622, 606980.066...10470014035536045yesNaNNaNNaNNaNNaN
55360522654890260[90731432, 31557546, 179308707]trunk250Avenue de la 1e Division FrançaiseTrueN 296False198.965351LINESTRING (605102.985 5396597.832, 605069.767...5536052265489026yesNaNNaNNaNNaNNaN
85184530060[90283320, 90283321, 179308930]trunk_linkNaN50NaNTrueNaNFalse147.744228LINESTRING (605102.985 5396597.832, 605085.53 ...55360528518453006yesNaNNaNNaNNaNNaN
...............................................................
12819726786128197267930[1384658856, 1384658857]trackNaNNaNNaNFalseNaNFalse117.859117LINESTRING (604246.326 5402539.811, 604240.827...1281972679312819726786NaNNaNNaNNaNNaNNaN
128407239071284072391801387085145footwayNaNNaNNaNFalseNaNTrue8.950842LINESTRING (595239.934 5387483.659, 595240.379...1284072391812840723907NaNNaNNaNNaNNaNNaN
128407239081284072391301387085143serviceNaNNaNNaNFalseNaNTrue33.678924LINESTRING (595173.765 5387499.526, 595173.164...1284072391312840723908NaNNaNNaNparking_aisleNaNNaN
128407239111284072391301387085143serviceNaNNaNNaNFalseNaNFalse28.646349LINESTRING (595173.765 5387499.526, 595176.704...1284072391312840723911NaNNaNNaNparking_aisleNaNNaN
128407239131284072391501387085144footwayNaNNaNNaNFalseNaNTrue42.460380LINESTRING (595221.143 5387481.005, 595222.534...1284072391512840723913NaNNaNNaNNaNNaNNaN
\n", + "

28913 rows × 18 columns

\n", + "
" + ], + "text/plain": [ + " osmid highway \\\n", + "u v key \n", + "5536045 9460707230 0 [355742063, 147498237, 90283751] trunk \n", + " 277035488 0 [90283752, 90283753, 25419836] trunk_link \n", + " 1047001403 0 [685260154, 90283748, 90283751] trunk \n", + "5536052 265489026 0 [90731432, 31557546, 179308707] trunk \n", + " 8518453006 0 [90283320, 90283321, 179308930] trunk_link \n", + "... ... ... \n", + "12819726786 12819726793 0 [1384658856, 1384658857] track \n", + "12840723907 12840723918 0 1387085145 footway \n", + "12840723908 12840723913 0 1387085143 service \n", + "12840723911 12840723913 0 1387085143 service \n", + "12840723913 12840723915 0 1387085144 footway \n", + "\n", + " lanes maxspeed \\\n", + "u v key \n", + "5536045 9460707230 0 2 [90, 70] \n", + " 277035488 0 1 110 \n", + " 1047001403 0 2 90 \n", + "5536052 265489026 0 2 50 \n", + " 8518453006 0 NaN 50 \n", + "... ... ... \n", + "12819726786 12819726793 0 NaN NaN \n", + "12840723907 12840723918 0 NaN NaN \n", + "12840723908 12840723913 0 NaN NaN \n", + "12840723911 12840723913 0 NaN NaN \n", + "12840723913 12840723915 0 NaN NaN \n", + "\n", + " name oneway \\\n", + "u v key \n", + "5536045 9460707230 0 Avenue de la 1e Division Française True \n", + " 277035488 0 NaN True \n", + " 1047001403 0 Avenue de la 1e Division Française True \n", + "5536052 265489026 0 Avenue de la 1e Division Française True \n", + " 8518453006 0 NaN True \n", + "... ... ... \n", + "12819726786 12819726793 0 NaN False \n", + "12840723907 12840723918 0 NaN False \n", + "12840723908 12840723913 0 NaN False \n", + "12840723911 12840723913 0 NaN False \n", + "12840723913 12840723915 0 NaN False \n", + "\n", + " ref reversed length \\\n", + "u v key \n", + "5536045 9460707230 0 N 296 False 1038.297695 \n", + " 277035488 0 NaN False 224.338024 \n", + " 1047001403 0 N 296 False 364.686411 \n", + "5536052 265489026 0 N 296 False 198.965351 \n", + " 8518453006 0 NaN False 147.744228 \n", + "... ... ... ... \n", + "12819726786 12819726793 0 NaN False 117.859117 \n", + "12840723907 12840723918 0 NaN True 8.950842 \n", + "12840723908 12840723913 0 NaN True 33.678924 \n", + "12840723911 12840723913 0 NaN False 28.646349 \n", + "12840723913 12840723915 0 NaN True 42.460380 \n", + "\n", + " geometry \\\n", + "u v key \n", + "5536045 9460707230 0 LINESTRING (606617.776 5397366.114, 606588.822... \n", + " 277035488 0 LINESTRING (606839.625 5397557.657, 606845.102... \n", + " 1047001403 0 LINESTRING (607030.872 5397653.622, 606980.066... \n", + "5536052 265489026 0 LINESTRING (605102.985 5396597.832, 605069.767... \n", + " 8518453006 0 LINESTRING (605102.985 5396597.832, 605085.53 ... \n", + "... ... \n", + "12819726786 12819726793 0 LINESTRING (604246.326 5402539.811, 604240.827... \n", + "12840723907 12840723918 0 LINESTRING (595239.934 5387483.659, 595240.379... \n", + "12840723908 12840723913 0 LINESTRING (595173.765 5387499.526, 595173.164... \n", + "12840723911 12840723913 0 LINESTRING (595173.765 5387499.526, 595176.704... \n", + "12840723913 12840723915 0 LINESTRING (595221.143 5387481.005, 595222.534... \n", + "\n", + " from to bridge junction access \\\n", + "u v key \n", + "5536045 9460707230 0 5536045 9460707230 NaN NaN NaN \n", + " 277035488 0 277035488 5536045 yes NaN NaN \n", + " 1047001403 0 1047001403 5536045 yes NaN NaN \n", + "5536052 265489026 0 5536052 265489026 yes NaN NaN \n", + " 8518453006 0 5536052 8518453006 yes NaN NaN \n", + "... ... ... ... ... ... \n", + "12819726786 12819726793 0 12819726793 12819726786 NaN NaN NaN \n", + "12840723907 12840723918 0 12840723918 12840723907 NaN NaN NaN \n", + "12840723908 12840723913 0 12840723913 12840723908 NaN NaN NaN \n", + "12840723911 12840723913 0 12840723913 12840723911 NaN NaN NaN \n", + "12840723913 12840723915 0 12840723915 12840723913 NaN NaN NaN \n", + "\n", + " service width tunnel \n", + "u v key \n", + "5536045 9460707230 0 NaN NaN NaN \n", + " 277035488 0 NaN NaN NaN \n", + " 1047001403 0 NaN NaN NaN \n", + "5536052 265489026 0 NaN NaN NaN \n", + " 8518453006 0 NaN NaN NaN \n", + "... ... ... ... \n", + "12819726786 12819726793 0 NaN NaN NaN \n", + "12840723907 12840723918 0 NaN NaN NaN \n", + "12840723908 12840723913 0 parking_aisle NaN NaN \n", + "12840723911 12840723913 0 parking_aisle NaN NaN \n", + "12840723913 12840723915 0 NaN NaN NaN \n", + "\n", + "[28913 rows x 18 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "gdf" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "f6630cf5", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_14835/721137014.py:15: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[G_primal.edges[e][\"index_position\"]]) for e in G_primal.edges}, \"stroke_id\")\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "498.3172490596771\n" + ] + } + ], + "source": [ + "beg = time.time()\n", + "G_stroke_clse = make_stroke_graph_clse(gdf, compute_metric=True, output=\"graph\")\n", + "print(time.time() - beg)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "30ef878f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "gdf.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "ccab49f2", + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "(5536045, 9460707230, 0)", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mKeyError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[15]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m beg = time.time()\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m G_stroke_anvy = \u001b[43mmake_stroke_graph_anvy\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcompute_metric\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moutput\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mgraph\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 3\u001b[39m \u001b[38;5;28mprint\u001b[39m(time.time() - beg)\n", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 35\u001b[39m, in \u001b[36mmake_stroke_graph_anvy\u001b[39m\u001b[34m(gdf, compute_metric, output)\u001b[39m\n\u001b[32m 33\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m _, row \u001b[38;5;129;01min\u001b[39;00m stroke_gdf.iterrows():\n\u001b[32m 34\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m edge_index \u001b[38;5;129;01min\u001b[39;00m row.edge_indeces: \n\u001b[32m---> \u001b[39m\u001b[32m35\u001b[39m graph.edges[\u001b[43md_index2name\u001b[49m\u001b[43m[\u001b[49m\u001b[43medge_index\u001b[49m\u001b[43m]\u001b[49m][\u001b[33m\"\u001b[39m\u001b[33mstroke_id\u001b[39m\u001b[33m\"\u001b[39m] = row.stroke_id\n\u001b[32m 36\u001b[39m \u001b[38;5;66;03m# getting dicts of edge name : stroke ID, and edge index : stroke id # TODO: one of them might be obsolete?\u001b[39;00m\n\u001b[32m 37\u001b[39m d_name2stroke = nx.get_edge_attributes(graph, \u001b[33m\"\u001b[39m\u001b[33mstroke_id\u001b[39m\u001b[33m\"\u001b[39m)\n", + "\u001b[31mKeyError\u001b[39m: (5536045, 9460707230, 0)" + ] + } + ], + "source": [ + "beg = time.time()\n", + "G_stroke_anvy = make_stroke_graph_anvy(gdf, compute_metric=True, output=\"graph\")\n", + "print(time.time() - beg)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a6ef3cbb", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "momepy_dev", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 078ba9666d2e0934c0caa753b7f75cdde9c5b5c0 Mon Sep 17 00:00:00 2001 From: anvy Date: Sun, 8 Jun 2025 18:42:23 +0200 Subject: [PATCH 17/27] add combination notebook --- momepy/stroke_graph_x2.ipynb | 442 +++++++++++++++++++++++++++++++++++ 1 file changed, 442 insertions(+) create mode 100644 momepy/stroke_graph_x2.ipynb diff --git a/momepy/stroke_graph_x2.ipynb b/momepy/stroke_graph_x2.ipynb new file mode 100644 index 00000000..38f1c7bf --- /dev/null +++ b/momepy/stroke_graph_x2.ipynb @@ -0,0 +1,442 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3867e2cf", + "metadata": {}, + "source": [ + "# Stroke graph generated twice...\n", + "\n", + "and then merging methods.\n", + "\n", + "(Also preparing for tests.)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "2345ab9a", + "metadata": {}, + "outputs": [], + "source": [ + "# import libraries\n", + "import geopandas as gpd\n", + "import momepy\n", + "import networkx as nx\n", + "from itertools import combinations, product\n", + "from shapely import LineString\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "id": "4d08f78b", + "metadata": {}, + "source": [ + "* read in gdf of linestrings\n", + "* explode\n", + "* mm remove false nodes\n", + "* mm gdf to nx, primal, preserving index\n", + "* mm nx to gdf only of lines\n", + "* run coins (pass angle_threshold and flow_mode, defaults!)\n", + "* from coins get .stroke_attribute() and .stroke_gdf()\n", + "* add \"rep_point\" to .stroke_gdf()\n", + "* add \"edge_indeces\" column to stroke gdf (anvy version)\n", + "* for each edge, add \"stroke_id\" as attribute to graph (clse version)\n", + "* create stroke graph (anvy version)\n", + "* add nodes to stroke graph (anvy version)\n", + "* adding edges to stroke graph (clse version)\n", + "* compute metrics\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "bb8c7e3f", + "metadata": {}, + "outputs": [], + "source": [ + "def _get_interior_angle(a, b):\n", + " '''\n", + " Helper function for ``make_stroke_graph()``.\n", + " Computes interior angle between two LineString segments\n", + " (interpreted as 2-dimensional vectors)\n", + "\n", + " Parameters\n", + " ----------\n", + " a, b: numpy.ndarray\n", + " '''\n", + " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", + " if angle > 90:\n", + " print(\"over 90\")\n", + " angle = 180 - angle\n", + " else:\n", + " print(\"under 90\")\n", + " return angle\n", + "\n", + "def _get_end_segment(linestring, point):\n", + " '''\n", + " Helper function for ``make_stroke_graph()``.\n", + " Returns the first or last two-Point segment of a LineString.\n", + "\n", + " Parameters\n", + " ----------\n", + " linestring: shapely.LineString\n", + " point: list\n", + " A list of length 2 containing the coordinates of either\n", + " the first or the last point on the linestring.\n", + " '''\n", + " point = tuple(point)\n", + " coords = list(linestring.coords)\n", + " assert point in coords, \"point not on linestring!\"\n", + " if point == coords[0]:\n", + " geom = [np.array(val) for val in linestring.coords[:2]]\n", + " elif point == coords[-1]:\n", + " geom = [np.array(val) for val in linestring.coords[-2:]]\n", + " else:\n", + " raise ValueError(\"point is not an endpoint of linestring!\")\n", + " return np.array(geom[0] - geom[1])\n", + "\n", + "def make_stroke_graph(gdf, compute_metrics=True, angle_threshold=0, flow_mode=False):\n", + " '''\n", + " Creates the stroke graph of a street network. The stroke graph is similar to, but not identical with,\n", + " the dual graph. In the stroke graph, each stroke (see ``momepy.COINS``) is a node; and each intersection\n", + " between two strokes is an edge.\n", + "\n", + " Parameters\n", + " ----------\n", + " gdf: GeoDataFrame\n", + " A GeoDataFrame containing edge geometry of a street network.\n", + " compute_metrics: bool (default True)\n", + " if True, computes stroke graph metrics and adds them as node attributes.\n", + " The following metrics are computed: betweenness centrality, closeness centrality, \n", + " degree, connectivity, access, orthogonality, spacing. # TODO add references here\n", + " angle_threshold: int, float (default 0), units: degrees\n", + " Passed on to ``momepy.COINS()``\n", + " flow_mode : bool, default False\n", + " Passed on to ``momepy.COINS()``\n", + " ''' \n", + "\n", + " # remove false nodes (interstitital nodes of degree 2)\n", + " gdf = momepy.remove_false_nodes(gdf)\n", + "\n", + " # make primal graph\n", + " graph = momepy.gdf_to_nx(\n", + " gdf, \n", + " preserve_index=True, # !! preserving index needed for unambiguous mapping to coins!\n", + " approach=\"primal\"\n", + " )\n", + "\n", + " # get momempy lines of graph\n", + " lines = momepy.nx_to_gdf(\n", + " graph,\n", + " points=False,\n", + " lines=True\n", + " )\n", + "\n", + " # get COINS of graph lines\n", + " coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", + "\n", + " # get strokes attributes from coins\n", + " stroke_attribute = coins.stroke_attribute()\n", + "\n", + " # get strokes gdf fro coins\n", + " stroke_gdf = coins.stroke_gdf()\n", + "\n", + " # add representative point to stroke_gdf (for later visualization)\n", + " stroke_gdf[\"rep_point\"] = stroke_gdf.geometry.apply(lambda x: x.interpolate(0.5, normalized=True))\n", + "\n", + " # add stroke_id column\n", + " stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", + "\n", + " # add column containing indeces of edges comprising each stroke \n", + " # (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", + " stroke_gdf[\"edge_indeces\"] = stroke_gdf.stroke_id.apply(\n", + " lambda x: list(stroke_attribute[stroke_attribute==x].index)\n", + " )\n", + "\n", + " # Add stroke ID to each edge on (primal) graph\n", + " nx.set_edge_attributes(\n", + " G=graph, \n", + " values={e: int(stroke_attribute[graph.edges[e][\"index_position\"]]) for e in graph.edges},\n", + " name=\"stroke_id\"\n", + " )\n", + "\n", + " # make stroke graph\n", + " stroke_graph = nx.Graph()\n", + "\n", + " # copy crs and approach attributes from \"original\" primal graph\n", + " stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", + " stroke_graph.graph[\"approach\"] = graph.graph[\"approach\"]\n", + "\n", + " # add nodes to stroke graph\n", + " stroke_graph.add_nodes_from(\n", + " [\n", + " (\n", + " row.stroke_id, \n", + " {\n", + " \"edge_indeces\": row.edge_indeces,\n", + " \"geometry\": row.rep_point, # \"geometry\" is the representative point (for viz later)\n", + " \"stroke_geometry\": row.geometry,\n", + " \"stroke_length\": row.geometry.length,\n", + " \"x\": row.rep_point.xy[0][0],\n", + " \"y\": row.rep_point.xy[1][0],\n", + " \"connectivity\": 0\n", + " }\n", + " ) for _, row in stroke_gdf.iterrows()\n", + " ]\n", + " )\n", + "\n", + " # add edges to stroke graph\n", + " for n in graph.nodes:\n", + " strokes_present = [graph.edges[e][\"stroke_id\"] for e in graph.edges(n, keys=True)]\n", + " # If strokes intersecting, add the edge if not already present\n", + " if len(set(strokes_present)) > 1:\n", + " for u, v in combinations(set(strokes_present), 2):\n", + " # Find all edges touching the node for both strokes checked\n", + " edges_u = [e for e in graph.edges(n, keys=True) if graph.edges[e][\"stroke_id\"] == u]\n", + " edges_v = [e for e in graph.edges(n, keys=True) if graph.edges[e][\"stroke_id\"] == v]\n", + " angle_list = []\n", + " angle_dict = {}\n", + " # Choose the smallest list as number of angles kept\n", + " chosen, other = sorted([edges_u, edges_v], key=len)\n", + " # Find the angles\n", + " for ce, oe in list(product(chosen, other)):\n", + " point = [graph.nodes[n][\"x\"], graph.nodes[n][\"y\"]]\n", + " gc = _get_end_segment(graph.edges[ce][\"geometry\"], point)\n", + " go = _get_end_segment(graph.edges[oe][\"geometry\"], point)\n", + " if ce in angle_dict:\n", + " print(gc, go)\n", + " angle_dict[ce].append(_get_interior_angle(gc, go))\n", + " else:\n", + " angle_dict[ce]= [_get_interior_angle(gc, go)]\n", + " # Keep the smallest angles\n", + " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", + " if stroke_graph.has_edge(u, v):\n", + " stroke_graph.edges[u, v][\"angles\"] += angle_list\n", + " stroke_graph.edges[u, v][\"number_connections\"] = len(stroke_graph.edges[u, v][\"angles\"])\n", + " else:\n", + " edge_geometry = LineString(\n", + " [\n", + " stroke_graph.nodes[u][\"geometry\"],\n", + " stroke_graph.nodes[v][\"geometry\"]\n", + " ]\n", + " )\n", + " stroke_graph.add_edge(\n", + " u,\n", + " v,\n", + " geometry=edge_geometry,\n", + " angles=angle_list,\n", + " number_connections=len(angle_list),\n", + " )\n", + "\n", + " # once stroke graph is created, compute metrics\n", + " if compute_metrics:\n", + " \n", + " # add stroke betweenness\n", + " nx.set_node_attributes(\n", + " stroke_graph,\n", + " nx.betweenness_centrality(stroke_graph),\n", + " \"stroke_betweenness\"\n", + " )\n", + "\n", + " # add stroke closeness\n", + " nx.set_node_attributes(\n", + " stroke_graph,\n", + " nx.closeness_centrality(stroke_graph),\n", + " \"stroke_closeness\"\n", + " )\n", + "\n", + " # add stroke degree\n", + " nx.set_node_attributes(\n", + " stroke_graph,\n", + " dict(nx.degree(stroke_graph)),\n", + " \"stroke_degree\"\n", + " )\n", + "\n", + " # add derived metrics\n", + " for n in stroke_graph.nodes:\n", + " stroke_graph.nodes[n][\"stroke_connectivity\"] = sum([stroke_graph.edges[e][\"number_connections\"] for e in stroke_graph.edges(n)])\n", + " stroke_graph.nodes[n][\"stroke_access\"] = stroke_graph.nodes[n][\"stroke_connectivity\"] - stroke_graph.nodes[n][\"stroke_degree\"]\n", + " angles = [val for e in stroke_graph.edges(n) if stroke_graph.edges[e][\"angles\"] for val in stroke_graph.edges[e][\"angles\"]]\n", + " stroke_graph.nodes[n][\"stroke_orthogonality\"] = sum(angles) / stroke_graph.nodes[n][\"stroke_connectivity\"]\n", + " stroke_graph.nodes[n][\"stroke_spacing\"] = stroke_graph.nodes[n][\"stroke_length\"] / stroke_graph.nodes[n][\"stroke_connectivity\"]\n", + "\n", + " return stroke_graph" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "cf48897f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[172.43389124 200.04361864] [-21.00598791 53.213871 ]\n", + "[-67.53753506 169.20194522] [ -36.70203611 -143.20022765]\n", + "[20.67202944 -5.31082693] [ -36.70203611 -143.20022765]\n", + "[138.74861333 50.07089695] [ -36.70203611 -143.20022765]\n", + "[-10.17460146 -11.36771275] [-12.85740118 23.9677018 ]\n", + "[-12.94645678 -53.64521433] [-12.46778297 2.95038997]\n", + "[ -2.52695244 -10.77759593] [-12.46778297 2.95038997]\n", + "[14.41587406 -2.08266641] [ 48.81359671 196.04599555]\n", + "[-11.4770395 0.83306642] [ 48.81359671 196.04599555]\n", + "[-5.34333556 14.05794796] [186.99448064 72.66718594]\n", + "[-3.71807099 9.75380008] [186.99448064 72.66718594]\n", + "[186.99448064 72.66718594] [-34.82073672 95.5406763 ]\n", + "[137.64655037 52.36093896] [-34.82073672 95.5406763 ]\n", + "[-103.43807085 -118.06598393] [-56.182947 46.47685819]\n", + "[ -43.24762217 -184.31034761] [-17.16546548 4.16515838]\n", + "[ -3.33958472 -14.3871424 ] [-17.16546548 4.16515838]\n", + "[-113.35663747 -124.5378657 ] [-44.58345606 42.29401113]\n", + "[-8.56046884 12.61777878] [23.77784324 90.1993154 ]\n", + "[ 14.37134626 -13.50291124] [23.77784324 90.1993154 ]\n", + "[-28.3530743 5.0675803] [ 33.50716673 135.90379807]\n", + "[-16.31943735 3.60978511] [ 33.50716673 135.90379807]\n", + "[-13.83701271 3.26276734] [ 44.83949089 196.24962944]\n", + "[-10.35271265 -11.5758026 ] [-11.09855323 10.0485472 ]\n" + ] + } + ], + "source": [ + "# read in toy graph (Bubenec)\n", + "gdf = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", + "\n", + "stroke_graph = make_stroke_graph(gdf)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "9ead622d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "under 90\n" + ] + }, + { + "data": { + "text/plain": [ + "np.float64(71.56505117707799)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "_get_interior_angle([0,1],[3,1])" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "4833829c", + "metadata": {}, + "outputs": [], + "source": [ + "linestring = LineString([[0,0],[0,1],[0,2],[0,3]])" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "2fe629ac", + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "linestring" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "3e752d4c", + "metadata": {}, + "outputs": [], + "source": [ + "linestring = LineString(\n", + " [\n", + " [0,0],\n", + " [0,1],\n", + " [0,2],\n", + " [0,3],\n", + " [1,3]\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "eae1c504", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1., 0.])" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "_get_end_segment(linestring, [1,3])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d242cf59", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "momepy_dev", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From afac2f884b1e76433eaedf18b817c456b9213ea6 Mon Sep 17 00:00:00 2001 From: anvy Date: Sun, 8 Jun 2025 18:42:41 +0200 Subject: [PATCH 18/27] add strokegraph.py functions --- momepy/strokegraph.py | 209 ++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 209 insertions(+) create mode 100644 momepy/strokegraph.py diff --git a/momepy/strokegraph.py b/momepy/strokegraph.py new file mode 100644 index 00000000..838ea58a --- /dev/null +++ b/momepy/strokegraph.py @@ -0,0 +1,209 @@ +import momepy +import networkx as nx +from itertools import combinations, product +from shapely import LineString +import numpy as np + +def _get_interior_angle(a, b): + ''' + Helper function for ``make_stroke_graph()``. + Computes interior angle between two LineString segments + (interpreted as 2-dimensional vectors) + + Parameters + ---------- + a, b: numpy.ndarray + ''' + angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b)))) + if angle > 90: + angle = 180 - angle + return angle + +def _get_end_segment(linestring, point): + ''' + Helper function for ``make_stroke_graph()``. + Returns the first or last two-Point segment of a LineString. + + Parameters + ---------- + linestring: shapely.LineString + point: list + A list of length 2 containing the coordinates of either + the first or the last point on the linestring. + ''' + point = tuple(point) + coords = list(linestring.coords) + assert point in coords, "point not on linestring!" + if point == coords[0]: + geom = [np.array(val) for val in linestring.coords[:2]] + elif point == coords[-1]: + geom = [np.array(val) for val in linestring.coords[-2:]] + else: + raise ValueError("point is not an endpoint of linestring!") + return np.array(geom[0] - geom[1]) + +def make_stroke_graph(gdf, compute_metrics=True, angle_threshold=0, flow_mode=False): + ''' + Creates the stroke graph of a street network. The stroke graph is similar to, but not identical with, + the dual graph. In the stroke graph, each stroke (see ``momepy.COINS``) is a node; and each intersection + between two strokes is an edge. + + Parameters + ---------- + gdf: GeoDataFrame + A GeoDataFrame containing edge geometry of a street network. + compute_metrics: bool (default True) + if True, computes stroke graph metrics and adds them as node attributes. + The following metrics are computed: betweenness centrality, closeness centrality, + degree, connectivity, access, orthogonality, spacing. # TODO add references here + angle_threshold: int, float (default 0), units: degrees + Passed on to ``momepy.COINS()`` + flow_mode : bool, default False + Passed on to ``momepy.COINS()`` + ''' + + # remove false nodes (interstitital nodes of degree 2) + gdf = momepy.remove_false_nodes(gdf) + + # make primal graph + graph = momepy.gdf_to_nx( + gdf, + preserve_index=True, # !! preserving index needed for unambiguous mapping to coins! + approach="primal" + ) + + # get momempy lines of graph + lines = momepy.nx_to_gdf( + graph, + points=False, + lines=True + ) + + # get COINS of graph lines + coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode) + + # get strokes attributes from coins + stroke_attribute = coins.stroke_attribute() + + # get strokes gdf fro coins + stroke_gdf = coins.stroke_gdf() + + # add representative point to stroke_gdf (for later visualization) + stroke_gdf["rep_point"] = stroke_gdf.geometry.apply(lambda x: x.interpolate(0.5, normalized=True)) + + # add stroke_id column + stroke_gdf["stroke_id"] = stroke_gdf.index + + # add column containing indeces of edges comprising each stroke + # (using COINS.stroke_attribute to map into ID defined in lines gdf) + stroke_gdf["edge_indeces"] = stroke_gdf.stroke_id.apply( + lambda x: list(stroke_attribute[stroke_attribute==x].index) + ) + + # Add stroke ID to each edge on (primal) graph + nx.set_edge_attributes( + G=graph, + values={e: int(stroke_attribute[graph.edges[e]["index_position"]]) for e in graph.edges}, + name="stroke_id" + ) + + # make stroke graph + stroke_graph = nx.Graph() + + # copy crs and approach attributes from "original" primal graph + stroke_graph.graph["crs"] = graph.graph["crs"] + stroke_graph.graph["approach"] = graph.graph["approach"] + + # add nodes to stroke graph + stroke_graph.add_nodes_from( + [ + ( + row.stroke_id, + { + "edge_indeces": row.edge_indeces, + "geometry": row.rep_point, # "geometry" is the representative point (for viz later) + "stroke_geometry": row.geometry, + "stroke_length": row.geometry.length, + "x": row.rep_point.xy[0][0], + "y": row.rep_point.xy[1][0], + "connectivity": 0 + } + ) for _, row in stroke_gdf.iterrows() + ] + ) + + # add edges to stroke graph + for n in graph.nodes: + strokes_present = [graph.edges[e]["stroke_id"] for e in graph.edges(n, keys=True)] + # If strokes intersecting, add the edge if not already present + if len(set(strokes_present)) > 1: + for u, v in combinations(set(strokes_present), 2): + # Find all edges touching the node for both strokes checked + edges_u = [e for e in graph.edges(n, keys=True) if graph.edges[e]["stroke_id"] == u] + edges_v = [e for e in graph.edges(n, keys=True) if graph.edges[e]["stroke_id"] == v] + angle_list = [] + angle_dict = {} + # Choose the smallest list as number of angles kept + chosen, other = sorted([edges_u, edges_v], key=len) + # Find the angles + for ce, oe in list(product(chosen, other)): + point = [graph.nodes[n]["x"], graph.nodes[n]["y"]] + gc = _get_end_segment(graph.edges[ce]["geometry"], point) + go = _get_end_segment(graph.edges[oe]["geometry"], point) + if ce in angle_dict: + angle_dict[ce].append(_get_interior_angle(gc, go)) + else: + angle_dict[ce]= [_get_interior_angle(gc, go)] + # Keep the smallest angles + angle_list = [min(angle_dict[ekey]) for ekey in angle_dict] + if stroke_graph.has_edge(u, v): + stroke_graph.edges[u, v]["angles"] += angle_list + stroke_graph.edges[u, v]["number_connections"] = len(stroke_graph.edges[u, v]["angles"]) + else: + edge_geometry = LineString( + [ + stroke_graph.nodes[u]["geometry"], + stroke_graph.nodes[v]["geometry"] + ] + ) + stroke_graph.add_edge( + u, + v, + geometry=edge_geometry, + angles=angle_list, + number_connections=len(angle_list), + ) + + # once stroke graph is created, compute metrics + if compute_metrics: + + # add stroke betweenness + nx.set_node_attributes( + stroke_graph, + nx.betweenness_centrality(stroke_graph), + "stroke_betweenness" + ) + + # add stroke closeness + nx.set_node_attributes( + stroke_graph, + nx.closeness_centrality(stroke_graph), + "stroke_closeness" + ) + + # add stroke degree + nx.set_node_attributes( + stroke_graph, + dict(nx.degree(stroke_graph)), + "stroke_degree" + ) + + # add derived metrics + for n in stroke_graph.nodes: + stroke_graph.nodes[n]["stroke_connectivity"] = sum([stroke_graph.edges[e]["number_connections"] for e in stroke_graph.edges(n)]) + stroke_graph.nodes[n]["stroke_access"] = stroke_graph.nodes[n]["stroke_connectivity"] - stroke_graph.nodes[n]["stroke_degree"] + angles = [val for e in stroke_graph.edges(n) if stroke_graph.edges[e]["angles"] for val in stroke_graph.edges[e]["angles"]] + stroke_graph.nodes[n]["stroke_orthogonality"] = sum(angles) / stroke_graph.nodes[n]["stroke_connectivity"] + stroke_graph.nodes[n]["stroke_spacing"] = stroke_graph.nodes[n]["stroke_length"] / stroke_graph.nodes[n]["stroke_connectivity"] + + return stroke_graph \ No newline at end of file From 54c000ab28daed7c7c547ff77beea41c5eec839d Mon Sep 17 00:00:00 2001 From: anvy Date: Sun, 8 Jun 2025 18:42:49 +0200 Subject: [PATCH 19/27] add draft for strokegraph tests --- momepy/tests/test_strokegraph.py | 49 ++++++++++++++++++++++++++++++++ 1 file changed, 49 insertions(+) create mode 100644 momepy/tests/test_strokegraph.py diff --git a/momepy/tests/test_strokegraph.py b/momepy/tests/test_strokegraph.py new file mode 100644 index 00000000..30941bbb --- /dev/null +++ b/momepy/tests/test_strokegraph.py @@ -0,0 +1,49 @@ +import geopandas as gpd +import pandas as pd +import pytest +from pandas.testing import assert_index_equal, assert_series_equal +from shapely.geometry import LineString +import numpy as np + +import momepy as mm + +class TestStrokeGraph: + def setup_method(self): + test_file_path = mm.datasets.get_path("bubenec") + self.gdf = gpd.read_file(test_file_path, layer="streets") + + def test_get_interior_angle(self): + + a = [172.43389124, 200.04361864] + b = [-21.00598791,53.213871] + result = mm.strokegraph._get_interior_angle(a, b) + assert result == 62.30218235137648 + + a = [1,0] + b = [-1,1] + result = mm.strokegraph._get_interior_angle(a, b) + assert result == 45 + + def test_get_end_segment(self): + + linestring = LineString( + [ + [0,0], + [0,1], + [0,2], + [0,3], + [1,3] + ] + ) + + first_segment = np.array([0,-1]) + last_segment = np.array([-1,0]) + + assert mm.strokegraph._get_end_segment(linestring, [0,0]) == first_segment + assert mm.strokegraph._get_end_segment(linestring, [1,3]) == last_segment + + with pytest.raises(ValueError, match="point is not an endpoint of linestring!"): + mm.strokegraph._get_end_segment(linestring, [0,2]) + + def test_make_stroke_graph(self): + pass \ No newline at end of file From 29c5ace99b1e2b65ad487d31c026de7b99744f7f Mon Sep 17 00:00:00 2001 From: anvy Date: Fri, 18 Jul 2025 14:44:14 +0200 Subject: [PATCH 20/27] add strokegraph to init --- momepy/__init__.py | 1 + 1 file changed, 1 insertion(+) diff --git a/momepy/__init__.py b/momepy/__init__.py index bf8e6168..f1cac59b 100644 --- a/momepy/__init__.py +++ b/momepy/__init__.py @@ -18,6 +18,7 @@ from .preprocessing import * from .shape import * from .streetscape import * +from .strokegraph import * from .utils import * from .weights import * From 10b85e34927e69da2be0106b4d2e1b509ae44d7f Mon Sep 17 00:00:00 2001 From: anvy Date: Fri, 18 Jul 2025 14:46:40 +0200 Subject: [PATCH 21/27] update tests for strokegraph --- momepy/tests/test_strokegraph.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/momepy/tests/test_strokegraph.py b/momepy/tests/test_strokegraph.py index 30941bbb..03771b60 100644 --- a/momepy/tests/test_strokegraph.py +++ b/momepy/tests/test_strokegraph.py @@ -15,7 +15,7 @@ def setup_method(self): def test_get_interior_angle(self): a = [172.43389124, 200.04361864] - b = [-21.00598791,53.213871] + b = [-21.00598791, 53.213871] result = mm.strokegraph._get_interior_angle(a, b) assert result == 62.30218235137648 @@ -39,11 +39,11 @@ def test_get_end_segment(self): first_segment = np.array([0,-1]) last_segment = np.array([-1,0]) - assert mm.strokegraph._get_end_segment(linestring, [0,0]) == first_segment - assert mm.strokegraph._get_end_segment(linestring, [1,3]) == last_segment + assert all(mm.strokegraph._get_end_segment(linestring, [0,0]) == first_segment) + assert all(mm.strokegraph._get_end_segment(linestring, [1,3]) == last_segment) with pytest.raises(ValueError, match="point is not an endpoint of linestring!"): mm.strokegraph._get_end_segment(linestring, [0,2]) - def test_make_stroke_graph(self): + def test_strokes_to_graph(self): pass \ No newline at end of file From 7068131688940aaf32f8475389f109e71d11c4d4 Mon Sep 17 00:00:00 2001 From: anvy Date: Fri, 18 Jul 2025 14:46:49 +0200 Subject: [PATCH 22/27] update strokegraph.py --- momepy/strokegraph.py | 60 +++++++++++++++++++++---------------------- 1 file changed, 30 insertions(+), 30 deletions(-) diff --git a/momepy/strokegraph.py b/momepy/strokegraph.py index 838ea58a..09e218c1 100644 --- a/momepy/strokegraph.py +++ b/momepy/strokegraph.py @@ -1,8 +1,13 @@ -import momepy import networkx as nx +import numpy as np from itertools import combinations, product from shapely import LineString -import numpy as np + +from .utils import gdf_to_nx + +__all__ = [ + "strokes_to_graph" +] def _get_interior_angle(a, b): ''' @@ -42,7 +47,7 @@ def _get_end_segment(linestring, point): raise ValueError("point is not an endpoint of linestring!") return np.array(geom[0] - geom[1]) -def make_stroke_graph(gdf, compute_metrics=True, angle_threshold=0, flow_mode=False): +def strokes_to_graph(coins, compute_metrics=True, return_primal=False): ''' Creates the stroke graph of a street network. The stroke graph is similar to, but not identical with, the dual graph. In the stroke graph, each stroke (see ``momepy.COINS``) is a node; and each intersection @@ -50,38 +55,13 @@ def make_stroke_graph(gdf, compute_metrics=True, angle_threshold=0, flow_mode=Fa Parameters ---------- - gdf: GeoDataFrame - A GeoDataFrame containing edge geometry of a street network. + coins: # TODO explain what this has to be compute_metrics: bool (default True) if True, computes stroke graph metrics and adds them as node attributes. The following metrics are computed: betweenness centrality, closeness centrality, degree, connectivity, access, orthogonality, spacing. # TODO add references here - angle_threshold: int, float (default 0), units: degrees - Passed on to ``momepy.COINS()`` - flow_mode : bool, default False - Passed on to ``momepy.COINS()`` ''' - # remove false nodes (interstitital nodes of degree 2) - gdf = momepy.remove_false_nodes(gdf) - - # make primal graph - graph = momepy.gdf_to_nx( - gdf, - preserve_index=True, # !! preserving index needed for unambiguous mapping to coins! - approach="primal" - ) - - # get momempy lines of graph - lines = momepy.nx_to_gdf( - graph, - points=False, - lines=True - ) - - # get COINS of graph lines - coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode) - # get strokes attributes from coins stroke_attribute = coins.stroke_attribute() @@ -100,6 +80,13 @@ def make_stroke_graph(gdf, compute_metrics=True, angle_threshold=0, flow_mode=Fa lambda x: list(stroke_attribute[stroke_attribute==x].index) ) + # recreate primal graph from coins.edge_gdf + graph = gdf_to_nx( + coins.edge_gdf, + preserve_index=True, + approach="primal" + ) + # Add stroke ID to each edge on (primal) graph nx.set_edge_attributes( G=graph, @@ -206,4 +193,17 @@ def make_stroke_graph(gdf, compute_metrics=True, angle_threshold=0, flow_mode=Fa stroke_graph.nodes[n]["stroke_orthogonality"] = sum(angles) / stroke_graph.nodes[n]["stroke_connectivity"] stroke_graph.nodes[n]["stroke_spacing"] = stroke_graph.nodes[n]["stroke_length"] / stroke_graph.nodes[n]["stroke_connectivity"] - return stroke_graph \ No newline at end of file + + if return_primal: + # TODO add metrics, mapping from each stroke:graph node to all its graph edges + return stroke_graph, graph + + if return_primal: + return stroke_graph, graph + + return stroke_graph + +# TODO: +def graph_to_strokes(stroke_graph): + # BLABLA + return coins \ No newline at end of file From 3d81d3a06dad3a7d641f2b0bc5e21d720a4df155 Mon Sep 17 00:00:00 2001 From: anvy Date: Fri, 18 Jul 2025 14:48:04 +0200 Subject: [PATCH 23/27] update compare nb: clse vs x2 --- momepy/strokegraph_compare.ipynb | 213 ++++++++++++++++--------------- 1 file changed, 111 insertions(+), 102 deletions(-) diff --git a/momepy/strokegraph_compare.ipynb b/momepy/strokegraph_compare.ipynb index 99f0eb4f..cb3db277 100644 --- a/momepy/strokegraph_compare.ipynb +++ b/momepy/strokegraph_compare.ipynb @@ -10,12 +10,11 @@ }, { "cell_type": "code", - "execution_count": 160, + "execution_count": 1, "id": "b411a245", "metadata": {}, "outputs": [], "source": [ - "import math\n", "import pickle\n", "\n", "import geopandas as gpd\n", @@ -26,12 +25,12 @@ }, { "cell_type": "code", - "execution_count": 161, + "execution_count": 2, "id": "b57b27f8", "metadata": {}, "outputs": [], "source": [ - "with open('stroke_graph_anvy.pickle', 'rb') as handle:\n", + "with open('stroke_graph_x2.pickle', 'rb') as handle:\n", " G_anvy = pickle.load(handle)\n", "with open('stroke_graph_clse.pickle', 'rb') as handle:\n", " G_clse = pickle.load(handle)" @@ -47,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 162, + "execution_count": 3, "id": "cf78ba7a", "metadata": {}, "outputs": [ @@ -55,10 +54,11 @@ "data": { "text/plain": [ "{'geometry': ,\n", - " 'angles': [np.float64(36.134980718680936)]}" + " 'angles': [np.float64(36.134980718680936)],\n", + " 'number_connections': 1}" ] }, - "execution_count": 162, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -69,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 163, + "execution_count": 4, "id": "915e4cab", "metadata": {}, "outputs": [ @@ -81,7 +81,7 @@ " 'angles': [np.float64(36.134980718680936)]}" ] }, - "execution_count": 163, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -100,7 +100,7 @@ }, { "cell_type": "code", - "execution_count": 164, + "execution_count": 5, "id": "af4d762b", "metadata": {}, "outputs": [], @@ -111,7 +111,7 @@ }, { "cell_type": "code", - "execution_count": 165, + "execution_count": 6, "id": "afbcc5f1", "metadata": {}, "outputs": [ @@ -119,72 +119,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Edge (0, 2)\n", - "Angles equal\n", "\n", "\n", - "Edge (0, 9)\n", - "Angles equal\n", "\n", "\n", - "Edge (0, 3)\n", - "Angles equal\n", "\n", "\n", - "Edge (0, 1)\n", - "Angles equal\n", "\n", "\n", - "Edge (0, 4)\n", - "Angles equal\n", "\n", "\n", - "Edge (1, 8)\n", - "Angles equal\n", "\n", "\n", - "Edge (1, 3)\n", - "Angles equal\n", "\n", "\n", - "Edge (1, 6)\n", - "Angles equal\n", "\n", "\n", - "Edge (2, 9)\n", - "Angles equal\n", "\n", "\n", - "Edge (2, 3)\n", - "Angles equal\n", "\n", "\n", - "Edge (2, 6)\n", - "Angles equal\n", "\n", "\n", - "Edge (3, 9)\n", - "Angles equal\n", "\n", "\n", - "Edge (3, 4)\n", - "Angles equal\n", "\n", "\n", - "Edge (4, 7)\n", - "Angles equal\n", "\n", "\n", - "Edge (4, 5)\n", - "Angles equal\n", "\n", "\n", - "Edge (4, 6)\n", - "Angles equal\n", "\n", "\n", - "Edge (4, 8)\n", - "Angles equal\n", "\n", "\n" ] @@ -193,11 +159,12 @@ "source": [ "for edge in G_anvy.edges:\n", " assert G_anvy.edges[edge][\"geometry\"] == G_clse.edges[edge][\"geometry\"], \"Geoms differ\"\n", - " print(f\"Edge {edge}\")\n", + " #print(f\"Edge {edge}\")\n", " angles_anvy = [round(angle, 10) for angle in sorted(G_anvy.edges[edge][\"angles\"])]\n", " angles_clse = [round(angle, 10) for angle in sorted(G_clse.edges[edge][\"angles\"])]\n", " if angles_anvy == angles_clse:\n", - " print(\"Angles equal\")\n", + " pass\n", + " #print(\"Angles equal\")\n", " else:\n", " print(\"Angles differ:\")\n", " print(angles_anvy)\n", @@ -224,7 +191,7 @@ }, { "cell_type": "code", - "execution_count": 166, + "execution_count": 7, "id": "029e919b", "metadata": {}, "outputs": [], @@ -234,7 +201,7 @@ }, { "cell_type": "code", - "execution_count": 167, + "execution_count": 8, "id": "e7a7bf17", "metadata": {}, "outputs": [ @@ -243,21 +210,21 @@ "text/plain": [ "{'edge_indeces': [0, 3, 15, 27],\n", " 'geometry': ,\n", - " 'geometry_stroke': ,\n", + " 'stroke_geometry': ,\n", + " 'stroke_length': 839.5666838320316,\n", " 'x': 1603374.6625343116,\n", " 'y': 6464077.898491419,\n", - " 'connectivity': 8,\n", - " 'degree': 5,\n", - " 'betweenness_centrality': 0.13657407407407404,\n", - " 'closeness_centrality': 0.6923076923076923,\n", - " 'connectivity_computed': 8,\n", - " 'access': 3,\n", - " 'length': 839.5666838320316,\n", - " 'spacing': 104.94583547900395,\n", - " 'orthogonality': np.float64(68.74678997354196)}" + " 'connectivity': 0,\n", + " 'stroke_betweenness': 0.13657407407407404,\n", + " 'stroke_closeness': 0.6923076923076923,\n", + " 'stroke_degree': 5,\n", + " 'stroke_connectivity': 8,\n", + " 'stroke_access': 3,\n", + " 'stroke_orthogonality': np.float64(68.74678997354196),\n", + " 'stroke_spacing': 104.94583547900395}" ] }, - "execution_count": 167, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -276,7 +243,7 @@ }, { "cell_type": "code", - "execution_count": 168, + "execution_count": 9, "id": "829d8185", "metadata": {}, "outputs": [ @@ -299,7 +266,7 @@ " 'stroke_spacing': 104.94583547900395}" ] }, - "execution_count": 168, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -310,26 +277,60 @@ }, { "cell_type": "code", - "execution_count": 169, + "execution_count": 10, "id": "66b889d6", "metadata": {}, "outputs": [], "source": [ "# k:v is anvy:clse naming of node attrs\n", "metrics_map = {\n", - " \"degree\": \"stroke_degree\",\n", - " \"betweenness_centrality\": \"stroke_betweenness\",\n", - " \"closeness_centrality\": \"stroke_closeness\",\n", - " \"connectivity\": \"stroke_connectivity\",\n", - " \"access\": \"stroke_access\",\n", - " \"spacing\": \"stroke_spacing\",\n", + " \"stroke_degree\": \"stroke_degree\",\n", + " \"stroke_betweenness\": \"stroke_betweenness\",\n", + " \"stroke_closeness\": \"stroke_closeness\",\n", + " \"stroke_connectivity\": \"stroke_connectivity\",\n", + " \"stroke_access\": \"stroke_access\",\n", + " \"stroke_spacing\": \"stroke_spacing\",\n", " #\"orthogonality\": \"stroke_orthogonality\"\n", "}" ] }, { "cell_type": "code", - "execution_count": 170, + "execution_count": 11, + "id": "5aa782b2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'edge_indeces': [0, 3, 15, 27],\n", + " 'geometry': ,\n", + " 'stroke_geometry': ,\n", + " 'stroke_length': 839.5666838320316,\n", + " 'x': 1603374.6625343116,\n", + " 'y': 6464077.898491419,\n", + " 'connectivity': 0,\n", + " 'stroke_betweenness': 0.13657407407407404,\n", + " 'stroke_closeness': 0.6923076923076923,\n", + " 'stroke_degree': 5,\n", + " 'stroke_connectivity': 8,\n", + " 'stroke_access': 3,\n", + " 'stroke_orthogonality': np.float64(68.74678997354196),\n", + " 'stroke_spacing': 104.94583547900395}" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G_anvy.nodes[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 12, "id": "7f661ee2", "metadata": {}, "outputs": [], @@ -338,9 +339,9 @@ " assert G_anvy.nodes[n][\"x\"] == G_clse.nodes[n][\"x\"][0], \"x coords differ\"\n", " assert G_anvy.nodes[n][\"y\"] == G_clse.nodes[n][\"y\"][0], \"y coords differ\"\n", " assert G_anvy.nodes[n][\"geometry\"] == G_clse.nodes[n][\"geometry\"], \"geometries differ\"\n", - " assert G_anvy.nodes[n][\"geometry_stroke\"] == G_clse.nodes[n][\"geometry_stroke\"], \"geometry_stroke differ\"\n", + " assert G_anvy.nodes[n][\"stroke_geometry\"] == G_clse.nodes[n][\"geometry_stroke\"], \"geometry_stroke differ\"\n", " assert G_anvy.nodes[n][\"edge_indeces\"] == list(G_clse.nodes[n][\"edge_ids\"]), \"Edge IDs differ\"\n", - " assert G_anvy.nodes[n][\"length\"] == G_clse.nodes[n][\"length\"]\n", + " assert G_anvy.nodes[n][\"stroke_length\"] == G_clse.nodes[n][\"length\"]\n", " for k, v in metrics_map.items():\n", " assert round(G_anvy.nodes[n][k], 10) == round(G_clse.nodes[n][v], 10), f\"{k} differ\"" ] @@ -355,7 +356,7 @@ }, { "cell_type": "code", - "execution_count": 171, + "execution_count": 13, "id": "d922e80c", "metadata": {}, "outputs": [ @@ -378,7 +379,7 @@ ], "source": [ "for n in G_anvy.nodes:\n", - " ortho_anvy = round(G_anvy.nodes[n][\"orthogonality\"], 10)\n", + " ortho_anvy = round(G_anvy.nodes[n][\"stroke_orthogonality\"], 10)\n", " ortho_clse = round(G_clse.nodes[n][\"stroke_orthogonality\"], 10)\n", " if ortho_anvy == ortho_clse:\n", " print(f\"{n}: same ortho\")\n", @@ -398,7 +399,7 @@ }, { "cell_type": "code", - "execution_count": 172, + "execution_count": 14, "id": "fe17ccd0", "metadata": {}, "outputs": [], @@ -434,7 +435,7 @@ }, { "cell_type": "code", - "execution_count": 173, + "execution_count": 15, "id": "a11251c9", "metadata": {}, "outputs": [ @@ -465,7 +466,7 @@ " 0., 0.])" ] }, - "execution_count": 173, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -487,7 +488,7 @@ }, { "cell_type": "code", - "execution_count": 174, + "execution_count": 16, "id": "b7eabac6", "metadata": {}, "outputs": [ @@ -518,7 +519,7 @@ " 0., 0.])" ] }, - "execution_count": 174, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -532,7 +533,7 @@ }, { "cell_type": "code", - "execution_count": 175, + "execution_count": 17, "id": "95b0e4cc", "metadata": {}, "outputs": [], @@ -554,7 +555,7 @@ }, { "cell_type": "code", - "execution_count": 176, + "execution_count": 18, "id": "f84c0968", "metadata": {}, "outputs": [], @@ -570,7 +571,7 @@ }, { "cell_type": "code", - "execution_count": 177, + "execution_count": 19, "id": "59443a81", "metadata": {}, "outputs": [ @@ -601,7 +602,7 @@ }, { "cell_type": "code", - "execution_count": 178, + "execution_count": 20, "id": "7b9e8d0e", "metadata": {}, "outputs": [], @@ -613,7 +614,7 @@ }, { "cell_type": "code", - "execution_count": 179, + "execution_count": 21, "id": "0da0e679", "metadata": {}, "outputs": [ @@ -623,7 +624,7 @@ "np.float64(29.396028363390087)" ] }, - "execution_count": 179, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -634,7 +635,7 @@ }, { "cell_type": "code", - "execution_count": 180, + "execution_count": 22, "id": "c1ab91cd", "metadata": {}, "outputs": [ @@ -644,7 +645,7 @@ "np.float64(29.396028363390094)" ] }, - "execution_count": 180, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -655,7 +656,7 @@ }, { "cell_type": "code", - "execution_count": 181, + "execution_count": 23, "id": "9ccbe4d5", "metadata": {}, "outputs": [ @@ -665,7 +666,7 @@ "np.float64(29.396028363390087)" ] }, - "execution_count": 181, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -676,7 +677,7 @@ }, { "cell_type": "code", - "execution_count": 182, + "execution_count": 24, "id": "5843905b", "metadata": {}, "outputs": [ @@ -686,7 +687,7 @@ "np.float64(29.396028363390094)" ] }, - "execution_count": 182, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -697,7 +698,7 @@ }, { "cell_type": "code", - "execution_count": 183, + "execution_count": 25, "id": "6d0ae741", "metadata": {}, "outputs": [], @@ -712,7 +713,7 @@ }, { "cell_type": "code", - "execution_count": 184, + "execution_count": 26, "id": "d489cd28", "metadata": {}, "outputs": [ @@ -722,7 +723,7 @@ "array([138.74861333, 50.07089695])" ] }, - "execution_count": 184, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -733,7 +734,7 @@ }, { "cell_type": "code", - "execution_count": 185, + "execution_count": 27, "id": "0e7e6b53", "metadata": {}, "outputs": [ @@ -743,7 +744,7 @@ "array([138.74861333, 50.07089695])" ] }, - "execution_count": 185, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -754,7 +755,7 @@ }, { "cell_type": "code", - "execution_count": 186, + "execution_count": 28, "id": "8dfaabd1", "metadata": {}, "outputs": [ @@ -764,7 +765,7 @@ "array([172.43389124, 200.04361864])" ] }, - "execution_count": 186, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -775,7 +776,7 @@ }, { "cell_type": "code", - "execution_count": 187, + "execution_count": 29, "id": "d9880de6", "metadata": {}, "outputs": [ @@ -785,7 +786,7 @@ "array([172.43389124, 200.04361864])" ] }, - "execution_count": 187, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -801,11 +802,19 @@ "metadata": {}, "outputs": [], "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ee8b6e50", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "momepy_dev", + "display_name": "test", "language": "python", "name": "python3" }, @@ -819,7 +828,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.10" + "version": "3.12.11" } }, "nbformat": 4, From a3fa4cb8e9f7269cfcfd48e37e32318808290ddb Mon Sep 17 00:00:00 2001 From: anvy Date: Fri, 18 Jul 2025 14:49:43 +0200 Subject: [PATCH 24/27] add x2 nb and pickle --- momepy/stroke_graph_x2.ipynb | 400 +++++----------------------------- momepy/stroke_graph_x2.pickle | Bin 0 -> 5900 bytes 2 files changed, 50 insertions(+), 350 deletions(-) create mode 100644 momepy/stroke_graph_x2.pickle diff --git a/momepy/stroke_graph_x2.ipynb b/momepy/stroke_graph_x2.ipynb index 38f1c7bf..55037e3e 100644 --- a/momepy/stroke_graph_x2.ipynb +++ b/momepy/stroke_graph_x2.ipynb @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "2345ab9a", "metadata": {}, "outputs": [], @@ -22,10 +22,18 @@ "# import libraries\n", "import geopandas as gpd\n", "import momepy\n", - "import networkx as nx\n", - "from itertools import combinations, product\n", - "from shapely import LineString\n", - "import numpy as np" + "\n", + "import pickle" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2fb98d56", + "metadata": {}, + "outputs": [], + "source": [ + "momepy.__version__" ] }, { @@ -51,376 +59,68 @@ }, { "cell_type": "code", - "execution_count": 7, - "id": "bb8c7e3f", + "execution_count": null, + "id": "af9a151d", "metadata": {}, "outputs": [], "source": [ - "def _get_interior_angle(a, b):\n", - " '''\n", - " Helper function for ``make_stroke_graph()``.\n", - " Computes interior angle between two LineString segments\n", - " (interpreted as 2-dimensional vectors)\n", - "\n", - " Parameters\n", - " ----------\n", - " a, b: numpy.ndarray\n", - " '''\n", - " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", - " if angle > 90:\n", - " print(\"over 90\")\n", - " angle = 180 - angle\n", - " else:\n", - " print(\"under 90\")\n", - " return angle\n", - "\n", - "def _get_end_segment(linestring, point):\n", - " '''\n", - " Helper function for ``make_stroke_graph()``.\n", - " Returns the first or last two-Point segment of a LineString.\n", - "\n", - " Parameters\n", - " ----------\n", - " linestring: shapely.LineString\n", - " point: list\n", - " A list of length 2 containing the coordinates of either\n", - " the first or the last point on the linestring.\n", - " '''\n", - " point = tuple(point)\n", - " coords = list(linestring.coords)\n", - " assert point in coords, \"point not on linestring!\"\n", - " if point == coords[0]:\n", - " geom = [np.array(val) for val in linestring.coords[:2]]\n", - " elif point == coords[-1]:\n", - " geom = [np.array(val) for val in linestring.coords[-2:]]\n", - " else:\n", - " raise ValueError(\"point is not an endpoint of linestring!\")\n", - " return np.array(geom[0] - geom[1])\n", - "\n", - "def make_stroke_graph(gdf, compute_metrics=True, angle_threshold=0, flow_mode=False):\n", - " '''\n", - " Creates the stroke graph of a street network. The stroke graph is similar to, but not identical with,\n", - " the dual graph. In the stroke graph, each stroke (see ``momepy.COINS``) is a node; and each intersection\n", - " between two strokes is an edge.\n", - "\n", - " Parameters\n", - " ----------\n", - " gdf: GeoDataFrame\n", - " A GeoDataFrame containing edge geometry of a street network.\n", - " compute_metrics: bool (default True)\n", - " if True, computes stroke graph metrics and adds them as node attributes.\n", - " The following metrics are computed: betweenness centrality, closeness centrality, \n", - " degree, connectivity, access, orthogonality, spacing. # TODO add references here\n", - " angle_threshold: int, float (default 0), units: degrees\n", - " Passed on to ``momepy.COINS()``\n", - " flow_mode : bool, default False\n", - " Passed on to ``momepy.COINS()``\n", - " ''' \n", - "\n", - " # remove false nodes (interstitital nodes of degree 2)\n", - " gdf = momepy.remove_false_nodes(gdf)\n", - "\n", - " # make primal graph\n", - " graph = momepy.gdf_to_nx(\n", - " gdf, \n", - " preserve_index=True, # !! preserving index needed for unambiguous mapping to coins!\n", - " approach=\"primal\"\n", - " )\n", - "\n", - " # get momempy lines of graph\n", - " lines = momepy.nx_to_gdf(\n", - " graph,\n", - " points=False,\n", - " lines=True\n", - " )\n", - "\n", - " # get COINS of graph lines\n", - " coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", - "\n", - " # get strokes attributes from coins\n", - " stroke_attribute = coins.stroke_attribute()\n", - "\n", - " # get strokes gdf fro coins\n", - " stroke_gdf = coins.stroke_gdf()\n", - "\n", - " # add representative point to stroke_gdf (for later visualization)\n", - " stroke_gdf[\"rep_point\"] = stroke_gdf.geometry.apply(lambda x: x.interpolate(0.5, normalized=True))\n", - "\n", - " # add stroke_id column\n", - " stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", - "\n", - " # add column containing indeces of edges comprising each stroke \n", - " # (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", - " stroke_gdf[\"edge_indeces\"] = stroke_gdf.stroke_id.apply(\n", - " lambda x: list(stroke_attribute[stroke_attribute==x].index)\n", - " )\n", - "\n", - " # Add stroke ID to each edge on (primal) graph\n", - " nx.set_edge_attributes(\n", - " G=graph, \n", - " values={e: int(stroke_attribute[graph.edges[e][\"index_position\"]]) for e in graph.edges},\n", - " name=\"stroke_id\"\n", - " )\n", - "\n", - " # make stroke graph\n", - " stroke_graph = nx.Graph()\n", - "\n", - " # copy crs and approach attributes from \"original\" primal graph\n", - " stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", - " stroke_graph.graph[\"approach\"] = graph.graph[\"approach\"]\n", - "\n", - " # add nodes to stroke graph\n", - " stroke_graph.add_nodes_from(\n", - " [\n", - " (\n", - " row.stroke_id, \n", - " {\n", - " \"edge_indeces\": row.edge_indeces,\n", - " \"geometry\": row.rep_point, # \"geometry\" is the representative point (for viz later)\n", - " \"stroke_geometry\": row.geometry,\n", - " \"stroke_length\": row.geometry.length,\n", - " \"x\": row.rep_point.xy[0][0],\n", - " \"y\": row.rep_point.xy[1][0],\n", - " \"connectivity\": 0\n", - " }\n", - " ) for _, row in stroke_gdf.iterrows()\n", - " ]\n", - " )\n", - "\n", - " # add edges to stroke graph\n", - " for n in graph.nodes:\n", - " strokes_present = [graph.edges[e][\"stroke_id\"] for e in graph.edges(n, keys=True)]\n", - " # If strokes intersecting, add the edge if not already present\n", - " if len(set(strokes_present)) > 1:\n", - " for u, v in combinations(set(strokes_present), 2):\n", - " # Find all edges touching the node for both strokes checked\n", - " edges_u = [e for e in graph.edges(n, keys=True) if graph.edges[e][\"stroke_id\"] == u]\n", - " edges_v = [e for e in graph.edges(n, keys=True) if graph.edges[e][\"stroke_id\"] == v]\n", - " angle_list = []\n", - " angle_dict = {}\n", - " # Choose the smallest list as number of angles kept\n", - " chosen, other = sorted([edges_u, edges_v], key=len)\n", - " # Find the angles\n", - " for ce, oe in list(product(chosen, other)):\n", - " point = [graph.nodes[n][\"x\"], graph.nodes[n][\"y\"]]\n", - " gc = _get_end_segment(graph.edges[ce][\"geometry\"], point)\n", - " go = _get_end_segment(graph.edges[oe][\"geometry\"], point)\n", - " if ce in angle_dict:\n", - " print(gc, go)\n", - " angle_dict[ce].append(_get_interior_angle(gc, go))\n", - " else:\n", - " angle_dict[ce]= [_get_interior_angle(gc, go)]\n", - " # Keep the smallest angles\n", - " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", - " if stroke_graph.has_edge(u, v):\n", - " stroke_graph.edges[u, v][\"angles\"] += angle_list\n", - " stroke_graph.edges[u, v][\"number_connections\"] = len(stroke_graph.edges[u, v][\"angles\"])\n", - " else:\n", - " edge_geometry = LineString(\n", - " [\n", - " stroke_graph.nodes[u][\"geometry\"],\n", - " stroke_graph.nodes[v][\"geometry\"]\n", - " ]\n", - " )\n", - " stroke_graph.add_edge(\n", - " u,\n", - " v,\n", - " geometry=edge_geometry,\n", - " angles=angle_list,\n", - " number_connections=len(angle_list),\n", - " )\n", - "\n", - " # once stroke graph is created, compute metrics\n", - " if compute_metrics:\n", - " \n", - " # add stroke betweenness\n", - " nx.set_node_attributes(\n", - " stroke_graph,\n", - " nx.betweenness_centrality(stroke_graph),\n", - " \"stroke_betweenness\"\n", - " )\n", - "\n", - " # add stroke closeness\n", - " nx.set_node_attributes(\n", - " stroke_graph,\n", - " nx.closeness_centrality(stroke_graph),\n", - " \"stroke_closeness\"\n", - " )\n", - "\n", - " # add stroke degree\n", - " nx.set_node_attributes(\n", - " stroke_graph,\n", - " dict(nx.degree(stroke_graph)),\n", - " \"stroke_degree\"\n", - " )\n", - "\n", - " # add derived metrics\n", - " for n in stroke_graph.nodes:\n", - " stroke_graph.nodes[n][\"stroke_connectivity\"] = sum([stroke_graph.edges[e][\"number_connections\"] for e in stroke_graph.edges(n)])\n", - " stroke_graph.nodes[n][\"stroke_access\"] = stroke_graph.nodes[n][\"stroke_connectivity\"] - stroke_graph.nodes[n][\"stroke_degree\"]\n", - " angles = [val for e in stroke_graph.edges(n) if stroke_graph.edges[e][\"angles\"] for val in stroke_graph.edges[e][\"angles\"]]\n", - " stroke_graph.nodes[n][\"stroke_orthogonality\"] = sum(angles) / stroke_graph.nodes[n][\"stroke_connectivity\"]\n", - " stroke_graph.nodes[n][\"stroke_spacing\"] = stroke_graph.nodes[n][\"stroke_length\"] / stroke_graph.nodes[n][\"stroke_connectivity\"]\n", + "### PREPROCESSING EXPECTED FROM USER!\n", "\n", - " return stroke_graph" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "cf48897f", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[172.43389124 200.04361864] [-21.00598791 53.213871 ]\n", - "[-67.53753506 169.20194522] [ -36.70203611 -143.20022765]\n", - "[20.67202944 -5.31082693] [ -36.70203611 -143.20022765]\n", - "[138.74861333 50.07089695] [ -36.70203611 -143.20022765]\n", - "[-10.17460146 -11.36771275] [-12.85740118 23.9677018 ]\n", - "[-12.94645678 -53.64521433] [-12.46778297 2.95038997]\n", - "[ -2.52695244 -10.77759593] [-12.46778297 2.95038997]\n", - "[14.41587406 -2.08266641] [ 48.81359671 196.04599555]\n", - "[-11.4770395 0.83306642] [ 48.81359671 196.04599555]\n", - "[-5.34333556 14.05794796] [186.99448064 72.66718594]\n", - "[-3.71807099 9.75380008] [186.99448064 72.66718594]\n", - "[186.99448064 72.66718594] [-34.82073672 95.5406763 ]\n", - "[137.64655037 52.36093896] [-34.82073672 95.5406763 ]\n", - "[-103.43807085 -118.06598393] [-56.182947 46.47685819]\n", - "[ -43.24762217 -184.31034761] [-17.16546548 4.16515838]\n", - "[ -3.33958472 -14.3871424 ] [-17.16546548 4.16515838]\n", - "[-113.35663747 -124.5378657 ] [-44.58345606 42.29401113]\n", - "[-8.56046884 12.61777878] [23.77784324 90.1993154 ]\n", - "[ 14.37134626 -13.50291124] [23.77784324 90.1993154 ]\n", - "[-28.3530743 5.0675803] [ 33.50716673 135.90379807]\n", - "[-16.31943735 3.60978511] [ 33.50716673 135.90379807]\n", - "[-13.83701271 3.26276734] [ 44.83949089 196.24962944]\n", - "[-10.35271265 -11.5758026 ] [-11.09855323 10.0485472 ]\n" - ] - } - ], - "source": [ "# read in toy graph (Bubenec)\n", "gdf = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", "\n", - "stroke_graph = make_stroke_graph(gdf)" + "# remove false nodes (interstitital nodes of degree 2)\n", + "gdf = momepy.remove_false_nodes(gdf)\n", + "\n", + "# make primal graph\n", + "graph = momepy.gdf_to_nx(\n", + " gdf, \n", + " preserve_index=True, # !! preserving index needed for unambiguous mapping to coins!\n", + " approach=\"primal\"\n", + ")\n", + "\n", + "# get momempy lines of graph\n", + "lines = momepy.nx_to_gdf(\n", + " graph,\n", + " points=False,\n", + " lines=True\n", + ")\n", + "\n", + "# get COINS of graph lines\n", + "coins = momepy.COINS(\n", + " lines,\n", + " angle_threshold=0,\n", + " flow_mode=False\n", + ") # this will be the input to strokes_to_graph" ] }, { "cell_type": "code", - "execution_count": 22, - "id": "9ead622d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "under 90\n" - ] - }, - { - "data": { - "text/plain": [ - "np.float64(71.56505117707799)" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "_get_interior_angle([0,1],[3,1])" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "4833829c", + "execution_count": null, + "id": "cf48897f", "metadata": {}, "outputs": [], "source": [ - "linestring = LineString([[0,0],[0,1],[0,2],[0,3]])" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "2fe629ac", - "metadata": {}, - "outputs": [ - { - "data": { - "image/svg+xml": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "linestring" + "### USING THE FUNCTION\n", + "strokes_graph = momepy.strokegraph.strokes_to_graph(coins)" ] }, { "cell_type": "code", - "execution_count": 29, - "id": "3e752d4c", + "execution_count": null, + "id": "7dc4874c", "metadata": {}, "outputs": [], "source": [ - "linestring = LineString(\n", - " [\n", - " [0,0],\n", - " [0,1],\n", - " [0,2],\n", - " [0,3],\n", - " [1,3]\n", - " ]\n", - ")" + "# after iteration finished, save results:\n", + "with open('stroke_graph_x2.pickle', 'wb') as handle:\n", + " pickle.dump(strokes_graph, handle, protocol=pickle.HIGHEST_PROTOCOL)" ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "eae1c504", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([-1., 0.])" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "_get_end_segment(linestring, [1,3])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d242cf59", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "momepy_dev", + "display_name": "test", "language": "python", "name": "python3" }, @@ -434,7 +134,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.10" + "version": "3.12.11" } }, "nbformat": 4, diff --git a/momepy/stroke_graph_x2.pickle b/momepy/stroke_graph_x2.pickle new file mode 100644 index 0000000000000000000000000000000000000000..98a2d3af098c19eddc1e965a92352ee87b7d8c40 GIT binary patch literal 5900 zcmb7|30Ms?hicket)D{I7f@oGo(1L(PG=?zE5P^go94b~30dW>V zM^S4P4-{`(TMv|{YWrBK)rti?s+H=ZSju|T1D96!Kba&ZS=8=4BK&5)dEf7S|L=Fq zw}`)**T+VG(Y-TBZMIT9Hzz=rCe>(2O@Lf2RZ$Gh7wdnoV*C~}d5ka3=kBwA+R4-! zhIUous?#2YuuSkk&}|tj1*EvYM5EZqg5;Ck`j|0 zs_%q#JX^GP#LxP~klW|8f<%+PZzlZlPC%g3u^+)s%P%Yr1W%mDWIhD%x*oJX7F@7s zN!?@cn)5FL6TpGH?>G#G&+kjFO76t$hY^c{vIBO0 zaz#Y*ase}{SLH6cIh1ymDKj!inKm^mRh!EYHnf|;Ml!S}Nj%eN7;)&y`QfuKR2-yx z7@o?~lp50T?Do*)Ec~O5-cv}qnj{&5Pxmsmw(ub|wUo-Bn}#9mXm>+PrCLiV<;o0c z8rvOIoGx9J8z7M>)nq`rE=`*%RjZ|VAkfI9X;L*rr1|TnFs6`I+tuJ-qms%}Gvr8JB9}TH!9%4{ z?rd@K2xr2T=u1+)Q43t{2;CPrS3%d7i%s&)Mja?ms&DvYl$O3++)*ynzl4kUXx3-x z?uI95R^`*Y#0C7&d)2Dn!JTaZqxyhX2ln1}5BzT1fyIGf;qK$vH^I>*#S22g`4LSg zu7PbFvPMOLkLBfmeFc28I`Z>r;OjZMqD$cWis{r26*>%m*sc{x>s%Qtq9ssu*{q!(@jJNr3T9R|C3-XFo1WBa+1 zMc;snCi4PUfOEs77n{MOBNsne4sP9jroRWuRoc0;u^4P!-rcsB3fS`Qx!_zdTkbCi z+Z~s|Q3_2&9+>y_Kk{ya$AoOrECB1vn;I+*D>`z78eK7s@@{09EB-}@hTfUO7k z`mrCr)eCO(PX9aX4xU#C8g7jR_jvd$>IPVGH(C?Ua=6Net&poa$;D}4&5E$om%%*G zb>2zf)@7~sP2fk`pAOFfchqI?U@M|Xy>x3P_{Hg|uHS%9zCZTM67c@|w5NN)1ugr( z^#Xr!JzT`{=`CeZeZU1juF7Kh%H6)Vgy1#7KX`-b9pIussj&dD?o)c2_!&d+?tvk;z9ei2oIt+@s@c~X3M43ClFxmh^)USnmWiP<(WPy-H{aeh7EJpBZ$J# z8oRI2W?uOkkB#7;A0}-$0k%%U$|(oxY+-ZU9}R!7W4zrveTf@*XVc}=IpFA1;h#r> zGoHu#rh|Q#=beoMf3Y^GN&#Noc6ClZcyoc=Z4P+QZ@yvW-~+AvCrM!ICAM09c6I?FXA2|j5`%TIAqu|WwY8e5(_~evL6WiV`Zcrq+sB-tMA5qbx zPt8qY*(6d~W9IaZoDxo?6V+1rY)+)azh{l8HHy^C7HqhL6{!`;!Ud585XliD*%>P~ zYDmOAuZw1L(5&`g(b1z)QA1bq;ay5El<|*%;%h2z*v1xMLQV!M2VNn2N6l(UWi^`VgMxh1bUS4q>Me zWz~|njTQmk)d%Pb-!UuIvUzAD8SA6&hpF}aTHBMkU{AM?DG%`H1u=P}GJ=Iw+PS%AqdQ6G; zS`-p9??S2{?Cr?t(Y6MBcV(lyFIdnbytx`&^xd#FA8_H-h;8NIz&`#GFR)3F71#H= z)%7ptrbc0iH{UQDY>Zn{r8E}WXISa3x;OAH0uZlW1;mjFSG|!j~s765$#*<;v+Zpi7m9rdL8VcL+!AMzpOwT&%kxX4o%9XWa?%1Eu$Ej;Leq`zcuJGhOF3b1* ze}y-$U|~{inOU3$+d4vMjMLpb&R(GnYl|>AHYo`Ig|CRydSWW^Ds^Tjrm_eAE-JiJ zI_Pq24OqJ`Cy{33wAvh*;{2$wEqeW^``iF4TH6rXi;HuiKcU!U)N^&5{$llPMv`$s zPh03|Yd*kAZ`JqRR$~@tJZD=+I2z;ZXCCL?;F<(i)L4~mc}0swoG(|orp@(Hmk`I? zUk9|iVI1Xm7XH!%cKU9)54(kF{C40vN7$I<(e0~N*yso!-R=y2I!c*$8@%b{nB6_W z^*wgZzXi5lHBEWQZgu!`_{=BzJY>5j)CBM4^3YOIZd=ub-p%?nuz6tX+Ri)=m$Nd1 zoAyM#tZPZL)Ap7he%I+}dx~Y<4lCo$ z6BX}T+B{5UxJ9D>$clbH@_J8Q??+yGI$GyDaD0k|r(yi!pzN6zp15y0ZYHqwXFUzP zGBPf(dra#eoAV9djs_KMs9J8DX=&No(kqoPi%2$R=6732T13Jvqi^uk z(gQkR=F6sFCVPpmE0_1Y2UgsyBsZ)$$n)@;e^6pBQ0u5zYVvvYHj6} z`Qb9ZJ@di95pRnutm?NEZ?O8RTo|(M^qrz|a(Cl?ML(psh~{XnJ54t)-q_f7Kj+nA z^ILnSs3upp80H_gp6zwqfJ7F*{3}^}L%c)Uf;87V>x5N9dHgX@I?j8gMR^=j{4?*$P>VGEm5IgLGq)z1`tKij?7i&| z4UUY1lAp&A_KE=HUZWrPgssAc6~bQe9{Y<&-O=yjz&`pm>`n)F8*oE}8{D#kdfbc3 zxepcH*qb`qO(HR#=SpNaXeA{Qtd=-V!x1ZvV+R-?nhtx_qzcD#S*c_;9t)$P9eD-I7R5sB+Z-qDw5DQ_~%PB jI++Y_;V+e%Ou=7@c=pjo+Ch>{rphTT6Rk_uB?tT$Q#8!n literal 0 HcmV?d00001 From f63d47df28b78b68eab08eb74dc1d0f027a147c5 Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Tue, 22 Jul 2025 13:48:47 +0200 Subject: [PATCH 25/27] Add g2s and add metrics to primal graph from strokes --- docs/_static/references.bib | 12 +++ momepy/stroke_graph_x2.ipynb | 25 +++-- momepy/strokegraph.py | 175 +++++++++++++++++++++++------------ 3 files changed, 147 insertions(+), 65 deletions(-) diff --git a/docs/_static/references.bib b/docs/_static/references.bib index 6165bf1a..5ee67781 100644 --- a/docs/_static/references.bib +++ b/docs/_static/references.bib @@ -240,3 +240,15 @@ @article{araldi2024multi abstract = {Multiple fabric assessment (MFA) is a computer-aided procedure designed for identifying and characterizing urban fabric types (morphotypes) from a street-based perspective. Nonetheless, the original MFA presents some limitations: it relies on surface-based descriptors, conceived as proxy variables for the pedestrian perspective in urban form analysis, rather than direct sight-based measurements. It also uses building footprint classes as proxies for building types. The spatial statistics on the street network concentrate on patterns of over- and under-represented values, which often results in a limited number of morphotypes. Furthermore, the morphotypes are typically valid only for a specific study area. This article presents the latest methodological advancements in MFA overcoming these four limitations. Its implementation over the eight largest French metropolitan areas successfully distinguishes approximately 20 distinct place-specific morphotypes, which are further aggregated into a comprehensive multi-level nested taxonomy. The new MFA procedure allows a nationwide comparative analysis of contemporary urban forms, laying the groundwork for a comprehensive understanding of morphologically regionalized metropolitan areas. Through detailed algorithmic improvements and nationwide implementation, integrating traditional urban morphology with streetscape analysis, MFA provides insights into the analogies and differences of the urban fabric in contemporary metropolitan areas, enabling interoperability with other domains of urban research.} } +@article{el2022urban, + title = {Urban morphogenesis analysis based on geohistorical road data}, + author = {El Gouj, Hanae and Rinc{\'o}n-Acosta, Christian and Lagesse, Claire}, + journal = {Applied Network Science}, + volume = {7}, + number = {1}, + pages = {6}, + year = {2022}, + publisher = {Springer}, + doi = {https://doi.org/10.1007/s41109-021-00440-0}, + url = {https://link.springer.com/article/10.1007/s41109-021-00440-0} +} diff --git a/momepy/stroke_graph_x2.ipynb b/momepy/stroke_graph_x2.ipynb index 55037e3e..ed1a9137 100644 --- a/momepy/stroke_graph_x2.ipynb +++ b/momepy/stroke_graph_x2.ipynb @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "2345ab9a", "metadata": {}, "outputs": [], @@ -22,16 +22,29 @@ "# import libraries\n", "import geopandas as gpd\n", "import momepy\n", + "import networkx as nx\n", + "import shapely\n", "\n", "import pickle" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "2fb98d56", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'0.5.4.dev228+ga3fa4cb.d20250722'" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "momepy.__version__" ] @@ -59,7 +72,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "af9a151d", "metadata": {}, "outputs": [], @@ -96,13 +109,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "cf48897f", "metadata": {}, "outputs": [], "source": [ "### USING THE FUNCTION\n", - "strokes_graph = momepy.strokegraph.strokes_to_graph(coins)" + "strokes_graph, graph = momepy.strokegraph.strokes_to_graph(coins, return_primal=True)" ] }, { diff --git a/momepy/strokegraph.py b/momepy/strokegraph.py index 09e218c1..decac502 100644 --- a/momepy/strokegraph.py +++ b/momepy/strokegraph.py @@ -1,16 +1,21 @@ +from itertools import combinations, product + import networkx as nx import numpy as np -from itertools import combinations, product -from shapely import LineString +from geopandas import GeoDataFrame +from shapely import LineString, unary_union +from .coins import COINS from .utils import gdf_to_nx __all__ = [ - "strokes_to_graph" + "strokes_to_graph", + "graph_to_strokes", ] + def _get_interior_angle(a, b): - ''' + """ Helper function for ``make_stroke_graph()``. Computes interior angle between two LineString segments (interpreted as 2-dimensional vectors) @@ -18,14 +23,17 @@ def _get_interior_angle(a, b): Parameters ---------- a, b: numpy.ndarray - ''' - angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b)))) + """ + angle = np.rad2deg( + np.arccos(np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))) + ) if angle > 90: angle = 180 - angle return angle + def _get_end_segment(linestring, point): - ''' + """ Helper function for ``make_stroke_graph()``. Returns the first or last two-Point segment of a LineString. @@ -35,7 +43,7 @@ def _get_end_segment(linestring, point): point: list A list of length 2 containing the coordinates of either the first or the last point on the linestring. - ''' + """ point = tuple(point) coords = list(linestring.coords) assert point in coords, "point not on linestring!" @@ -47,20 +55,23 @@ def _get_end_segment(linestring, point): raise ValueError("point is not an endpoint of linestring!") return np.array(geom[0] - geom[1]) + def strokes_to_graph(coins, compute_metrics=True, return_primal=False): - ''' - Creates the stroke graph of a street network. The stroke graph is similar to, but not identical with, - the dual graph. In the stroke graph, each stroke (see ``momepy.COINS``) is a node; and each intersection - between two strokes is an edge. + """ + Creates the stroke graph of a street network. The stroke graph is similar to, but + not identical with, the dual graph. In the stroke graph, each stroke (see + ``momepy.COINS``) is a node; and each intersection between two strokes is an edge. Parameters ---------- - coins: # TODO explain what this has to be + coins: momepy.COINS + Strokes computed from a street network. compute_metrics: bool (default True) if True, computes stroke graph metrics and adds them as node attributes. - The following metrics are computed: betweenness centrality, closeness centrality, - degree, connectivity, access, orthogonality, spacing. # TODO add references here - ''' + The following metrics are computed: betweenness centrality, closeness + centrality, degree, connectivity, access, orthogonality, spacing. + For details on all metrics computed, see :cite:`el2022urban`. + """ # get strokes attributes from coins stroke_attribute = coins.stroke_attribute() @@ -69,29 +80,30 @@ def strokes_to_graph(coins, compute_metrics=True, return_primal=False): stroke_gdf = coins.stroke_gdf() # add representative point to stroke_gdf (for later visualization) - stroke_gdf["rep_point"] = stroke_gdf.geometry.apply(lambda x: x.interpolate(0.5, normalized=True)) + stroke_gdf["rep_point"] = stroke_gdf.geometry.apply( + lambda x: x.interpolate(0.5, normalized=True) + ) # add stroke_id column stroke_gdf["stroke_id"] = stroke_gdf.index - # add column containing indeces of edges comprising each stroke + # add column containing indeces of edges comprising each stroke # (using COINS.stroke_attribute to map into ID defined in lines gdf) stroke_gdf["edge_indeces"] = stroke_gdf.stroke_id.apply( - lambda x: list(stroke_attribute[stroke_attribute==x].index) + lambda x: list(stroke_attribute[stroke_attribute == x].index) ) # recreate primal graph from coins.edge_gdf - graph = gdf_to_nx( - coins.edge_gdf, - preserve_index=True, - approach="primal" - ) + graph = gdf_to_nx(coins.edge_gdf, preserve_index=True, approach="primal") # Add stroke ID to each edge on (primal) graph nx.set_edge_attributes( - G=graph, - values={e: int(stroke_attribute[graph.edges[e]["index_position"]]) for e in graph.edges}, - name="stroke_id" + G=graph, + values={ + e: int(stroke_attribute[graph.edges[e]["index_position"]]) + for e in graph.edges + }, + name="stroke_id", ) # make stroke graph @@ -105,29 +117,40 @@ def strokes_to_graph(coins, compute_metrics=True, return_primal=False): stroke_graph.add_nodes_from( [ ( - row.stroke_id, + row.stroke_id, { "edge_indeces": row.edge_indeces, - "geometry": row.rep_point, # "geometry" is the representative point (for viz later) + "geometry": row.rep_point, # "geometry" is the representative point "stroke_geometry": row.geometry, "stroke_length": row.geometry.length, "x": row.rep_point.xy[0][0], "y": row.rep_point.xy[1][0], - "connectivity": 0 - } - ) for _, row in stroke_gdf.iterrows() + "connectivity": 0, + }, + ) + for _, row in stroke_gdf.iterrows() ] ) # add edges to stroke graph for n in graph.nodes: - strokes_present = [graph.edges[e]["stroke_id"] for e in graph.edges(n, keys=True)] + strokes_present = [ + graph.edges[e]["stroke_id"] for e in graph.edges(n, keys=True) + ] # If strokes intersecting, add the edge if not already present if len(set(strokes_present)) > 1: for u, v in combinations(set(strokes_present), 2): # Find all edges touching the node for both strokes checked - edges_u = [e for e in graph.edges(n, keys=True) if graph.edges[e]["stroke_id"] == u] - edges_v = [e for e in graph.edges(n, keys=True) if graph.edges[e]["stroke_id"] == v] + edges_u = [ + e + for e in graph.edges(n, keys=True) + if graph.edges[e]["stroke_id"] == u + ] + edges_v = [ + e + for e in graph.edges(n, keys=True) + if graph.edges[e]["stroke_id"] == v + ] angle_list = [] angle_dict = {} # Choose the smallest list as number of angles kept @@ -140,17 +163,19 @@ def strokes_to_graph(coins, compute_metrics=True, return_primal=False): if ce in angle_dict: angle_dict[ce].append(_get_interior_angle(gc, go)) else: - angle_dict[ce]= [_get_interior_angle(gc, go)] + angle_dict[ce] = [_get_interior_angle(gc, go)] # Keep the smallest angles angle_list = [min(angle_dict[ekey]) for ekey in angle_dict] if stroke_graph.has_edge(u, v): stroke_graph.edges[u, v]["angles"] += angle_list - stroke_graph.edges[u, v]["number_connections"] = len(stroke_graph.edges[u, v]["angles"]) + stroke_graph.edges[u, v]["number_connections"] = len( + stroke_graph.edges[u, v]["angles"] + ) else: edge_geometry = LineString( [ stroke_graph.nodes[u]["geometry"], - stroke_graph.nodes[v]["geometry"] + stroke_graph.nodes[v]["geometry"], ] ) stroke_graph.add_edge( @@ -163,39 +188,65 @@ def strokes_to_graph(coins, compute_metrics=True, return_primal=False): # once stroke graph is created, compute metrics if compute_metrics: - # add stroke betweenness nx.set_node_attributes( - stroke_graph, - nx.betweenness_centrality(stroke_graph), - "stroke_betweenness" + stroke_graph, nx.betweenness_centrality(stroke_graph), "stroke_betweenness" ) # add stroke closeness nx.set_node_attributes( - stroke_graph, - nx.closeness_centrality(stroke_graph), - "stroke_closeness" + stroke_graph, nx.closeness_centrality(stroke_graph), "stroke_closeness" ) # add stroke degree nx.set_node_attributes( - stroke_graph, - dict(nx.degree(stroke_graph)), - "stroke_degree" + stroke_graph, dict(nx.degree(stroke_graph)), "stroke_degree" ) # add derived metrics for n in stroke_graph.nodes: - stroke_graph.nodes[n]["stroke_connectivity"] = sum([stroke_graph.edges[e]["number_connections"] for e in stroke_graph.edges(n)]) - stroke_graph.nodes[n]["stroke_access"] = stroke_graph.nodes[n]["stroke_connectivity"] - stroke_graph.nodes[n]["stroke_degree"] - angles = [val for e in stroke_graph.edges(n) if stroke_graph.edges[e]["angles"] for val in stroke_graph.edges[e]["angles"]] - stroke_graph.nodes[n]["stroke_orthogonality"] = sum(angles) / stroke_graph.nodes[n]["stroke_connectivity"] - stroke_graph.nodes[n]["stroke_spacing"] = stroke_graph.nodes[n]["stroke_length"] / stroke_graph.nodes[n]["stroke_connectivity"] - + stroke_graph.nodes[n]["stroke_connectivity"] = sum( + [ + stroke_graph.edges[e]["number_connections"] + for e in stroke_graph.edges(n) + ] + ) + stroke_graph.nodes[n]["stroke_access"] = ( + stroke_graph.nodes[n]["stroke_connectivity"] + - stroke_graph.nodes[n]["stroke_degree"] + ) + angles = [ + val + for e in stroke_graph.edges(n) + if stroke_graph.edges[e]["angles"] + for val in stroke_graph.edges[e]["angles"] + ] + stroke_graph.nodes[n]["stroke_orthogonality"] = ( + sum(angles) / stroke_graph.nodes[n]["stroke_connectivity"] + ) + stroke_graph.nodes[n]["stroke_spacing"] = ( + stroke_graph.nodes[n]["stroke_length"] + / stroke_graph.nodes[n]["stroke_connectivity"] + ) if return_primal: - # TODO add metrics, mapping from each stroke:graph node to all its graph edges + edgelist = { + val: key + for key, val in nx.get_edge_attributes(graph, "index_position").items() + } + for n in stroke_graph.nodes: + for e in stroke_graph.nodes[n]["edge_indeces"]: + for attr in [ + "stroke_betweenness", + "stroke_closeness", + "stroke_degree", + "stroke_length", + "stroke_connectivity", + "stroke_orthogonality", + "stroke_access", + "stroke_spacing", + ]: + graph.edges[edgelist[e]][attr] = stroke_graph.nodes[n][attr] return stroke_graph, graph if return_primal: @@ -203,7 +254,13 @@ def strokes_to_graph(coins, compute_metrics=True, return_primal=False): return stroke_graph -# TODO: -def graph_to_strokes(stroke_graph): - # BLABLA - return coins \ No newline at end of file + +def graph_to_strokes(stroke_graph, *kwargs): + edge_gdf = GeoDataFrame( + geometry=[ + unary_union( + list(nx.get_node_attributes(stroke_graph, "stroke_geometry").values()) + ) + ] + ).explode() + return COINS(edge_gdf, *kwargs) From 4e65dfb66888fcb5ddb717ee070cc77007141393 Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Thu, 24 Jul 2025 10:40:11 +0200 Subject: [PATCH 26/27] Add doc g2s --- momepy/strokegraph.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/momepy/strokegraph.py b/momepy/strokegraph.py index decac502..38c71b16 100644 --- a/momepy/strokegraph.py +++ b/momepy/strokegraph.py @@ -256,6 +256,7 @@ def strokes_to_graph(coins, compute_metrics=True, return_primal=False): def graph_to_strokes(stroke_graph, *kwargs): + """Recreate COINS from the edges. TBD""" edge_gdf = GeoDataFrame( geometry=[ unary_union( @@ -263,4 +264,5 @@ def graph_to_strokes(stroke_graph, *kwargs): ) ] ).explode() + # Remove false nodes ? return COINS(edge_gdf, *kwargs) From 7b9c02c99155300e5f0f8c5256d579026e36e9b4 Mon Sep 17 00:00:00 2001 From: Clement Sebastiao Date: Thu, 24 Jul 2025 10:44:35 +0200 Subject: [PATCH 27/27] Add primal_graph doc, remove notebooks and pickles --- momepy/stroke_graph_anvy.pickle | Bin 5778 -> 0 bytes momepy/stroke_graph_clse.pickle | Bin 6998 -> 0 bytes momepy/stroke_graph_x2.ipynb | 155 - momepy/stroke_graph_x2.pickle | Bin 5900 -> 0 bytes momepy/strokegraph.py | 4 + momepy/strokegraph_anvy.ipynb | 4154 --------------------- momepy/strokegraph_clse.ipynb | 922 ----- momepy/strokegraph_compare.ipynb | 836 ----- momepy/strokegraph_function_compare.ipynb | 1474 -------- 9 files changed, 4 insertions(+), 7541 deletions(-) delete mode 100644 momepy/stroke_graph_anvy.pickle delete mode 100644 momepy/stroke_graph_clse.pickle delete mode 100644 momepy/stroke_graph_x2.ipynb delete mode 100644 momepy/stroke_graph_x2.pickle delete mode 100644 momepy/strokegraph_anvy.ipynb delete mode 100644 momepy/strokegraph_clse.ipynb delete mode 100644 momepy/strokegraph_compare.ipynb delete mode 100644 momepy/strokegraph_function_compare.ipynb diff --git a/momepy/stroke_graph_anvy.pickle b/momepy/stroke_graph_anvy.pickle deleted file mode 100644 index f7ee96c82bc7e1f735a6e1b03ce03a09d4bf42d3..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 5778 zcma)=30M?I7RTk7VL(tp(4e9b2|^TH5jH5e9HOkWpaB7c$2bg~X+~g%IXF~|2MS^@ zg0`Z@ARZ`+SEB397d83RXfz&xcO<$fhOi#-T#W9&dJcvWP5R^LUv>4Xdhh+~=$b27 zQP86kf3ZC>Xic_4H6zDYnkG@JX|=CRB~daQD~RO(FXz1Hae15Bz8mDCi z;tWL!O`4!O5##oBii{SgW~9(kTFp%*#grA*mFi8iA{nhnr!}fvjzk_J zSkdPyMY=e9MlxC-(M`AH3u1XLtA#*lx-Bd4Ay0Gr7#i;B7Yp*TjMI=Po$) z6uk1>8^1)bU-dnk{%G^Zq8notg58AYiU)uTw^zI<0Kc$uo%c6z$<1cT3h=Bg7yRSF zKJ*dagJ9OPaic{}V3>91f}zb|U7sy-xX7@;Y~QV4UJYX{asiX7mgmmBJ&?7RDl#%? zsU|fmRg=q6B376}%TzSYQ3AF{GSW)Zc&=89rF4cyB}pT-B14YN3ZHhqY!B-!O;f1p zx1Zk~n4EV%0jl*}SY7)J z)haz37C3+(dn{l6JGiykcUVvG3cntk9)Le?-aXF`EUG?|eH$E8R5&{XJU^oT=nZfu zo2+5c;KOC~U`Z03uGw{NQl4}>hWs!*^ z%fPWWrqA34K6vuur)$6)SG(I)flJG~MpuBNeA5?g0^57rSMCQpxjh_0RM&F0Xzusm zg0U8UOToFJl8X&s|EPJ-mVle8Pxp3#DkZI3>k7f#dt=B+(y(%;0NNV7iGzKM}`(0IKcRqO<+Eb3>8;AZ5Y$fg&D;7GXA4PdDp#m z?&snS8MicM+>+`{^`ZKjW;{DGqW3Heu-4OC_8m5Mjbz;0kZ~t8JU^gn=mmK2WYds> z&RZvi)ogIx-3YFjAqaVm*J713YVLzW_B4Fe3bsBpWy5daKYD%g#S5_cI9@aSvk$tX z*}N0~4ZVlwWy0D!!@=Dizl^>Gmfw$2hZ7E0dJ=_P(~2)n0IQdVp11Cf_ z$+{l=M00)rbnuH)*;|Mr3RDX>W`f_G7~kc4@Uc&Z|GNmh>q6S|9pL=NT_@eadvAt^ z5k9e@B)TU!|I+d-!dLIR-VuRU2L0Shxb(#JhE({o=-lON`@!b(R9i-KX7!GU%+_V} z@V+glTai(bA){ONe$-++D~x2c;UT#mA)_K>)SA!em~J7(`8!EQ6ZNI2iDOp{5fj>5s3AzA-OGIo#z@Nc5P z8L#8K(!pL!^3KGA_pS=8l!I3^Uz#-0D zbibDFm4N3ZBUew{3N97yiW&$0{kC}XL2zbFm6QTse0IE3J*n>$-!BSWP*Hv75)|!! ze8v>QCP_M4C6P_jB`N72Swm`&BwHj&NRre*1RE|UNoqora3M*yNRky%Y)M__#1}b5 zBuP_Sg2E0SylO~N^ni#5?iY=7kU*a#%1&ak+&Bh_nK1aA_`rQcjImE7FT?q~SfRPa zqpv)9gFJljQ^lNM)Y%wUEO5j-$se{p2nCzR(ZsJXMjYg*^DAbA`-4RIWdXk|;1}-+ zaRz?f_>o*^;g<#c>O}lv`j5N2_)$Ia%W$h7iDiB-ON94~ehH1@>qa?JPE=3I%~W{J z0*_!ajVLM?#Fw{o@ILQg7jz+ZnMyhnb;QFxRlP8^o?B&kEEnwN^abMr{wDvmSOT`( zvrzg!*s%4;d@&7d?fz}_bMU0PW4k7Uo7OINc>+$ZRE$Uht1b`S^B8PCm6}g==8KcL zko*IRJXS$S+|2W--mteNqg(Sz@cm_V&R$?)qv-YuaKR6Qnmxgbu0?Dr1^e~%5xaxi z5|Sed_7Lc2gYx(Vl?wfAU`2%XHCDQ7PEScf?hNBE{cONbjZ1Ita5~kykR&8Ipdd#z zslgyL$xbeH$%k=<*}%piwC<)tdo=#Qky?mo=Mo1`nXykqXk+<2SR)TLgGT?d6m{JE zR=1F?t4&DKl&`?g_l$P<41DNtWcO;Y;P|@m$zbyV-{z;b_Q-+pk95M5c{(iF`PYRf zQ`7|9vp!1vG~DWiHzI$|l$sKwpCW^w&Zd5L52;;MfWfg&PWjAvho9yXQ;~bIJ(-wF z9{D&Z@lJ8SD{+Uwnw>dGEb-H9bJXT%R>7*;knTD^=lD?ab@0;?1I&`-b45IVk$g5F zy10-}OTz&ByskNB&9H~W&jkIg-p}GY7hE?TGWuz2@UxexpF4sMC3bwWyjj1l3zionz7vcUb_TcBk z6nS^S>y8CfJAyBC+dAtG*nHJ&i$ivo#6v+lba7}bE48dd9IOxrqHCS&x{0Pi2Z)1} zAr9G1Hh&DB{EWmw++er4@u%Mny1tT?8C1VLTCZy@Yb}+b6u+q>8+UJBz~p<) z{QIuMtsN_rWXRHVUy-`qVn#&5{T-g;bq(o??myq?({NE=L~AKN3GZ*L{Sk!UG?2lIZ59q(j}7U$a2ZprjWqecF^=KU5s{>N_%}T`PkGg@M_VjjiZD(kOn2w{OdQe81Bp zokI_}rdR9d>p%Sv^-j!@jv{Yv<(-k&$0;~==+u{zb{>>x&hI>jHhMtu>tg%9ztu{I zYojs0qo-HhoDi$GDA8(p#lwS&j?`$bz7D0&7;RUiEE=`w*C?ZQI#8pzg?Gk87wJuz zkNOVzFwAJN1OMN$_%8qTQMUU*UNN?-ey5>pWkc9>^-a5prUIQ9*WzuzBGR;|dYp1> zRil39pb+@}syW69 zXQ={mOseMO6VMhb8VxY5>xIg?^IFD=6_M36B~_~7m~w40Yem*pw%1#&ljAsj+YVtV zatTfirMad?VN;^PAu-ITlNk?P({>U3nWJevFZpD23JnXyYOPd?>bO&?aCpd+%j3zT Ua@IziO{dBj4Hu(L)+YP@A18XDQUCw| diff --git a/momepy/stroke_graph_clse.pickle b/momepy/stroke_graph_clse.pickle deleted file mode 100644 index e81dfeae6462499bf4304de72e988f5ed9920fb5..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 6998 zcma)B30PBC7S2LKL{vm^Uy&kK#WBhh1&7^KBGiK5hQ=g3^AaHmSy;4KMK3aVU14qHOzk^zK-zMo4HVy(qW5}nOC zW{b%X2mt-T?WlxAl4(wet>{*Vm??>h@neF6J|L|cDl&Hou;;cX+lD^fil&WW5&=Okv^DQR$N3T zfK4$W3?<{^<73~#Mg6A~*ho#3Oh(UDKo&wfqKghQrDHZrj>>AYnC4?7;bFzqW-Kiy zP;Vj$**uFWU6nOo1LmXF2}SU12l!h*GxXm1%;1QLKh-HmR!xrxlzSZi1+d5R3rpmH zV-}DZPXO<}6}&zXaQ@<@XP*IHbN;P-8en<#efPmx!4W@|+?-edxWDv#=@7uhdn#WR z0e&g&z2q-|%WgHQR|8(Svu11(;E~u@fky!o{`Fgh*})NR9g9Xc0wxR4Tx3|P4pZq< zfxm8i{@^!e(Q8SfqY6z&W1lw>OYo#H zl~j5~$ylRwufiM>4-UXX@K998bwrIwnuZy5Hk?$1mxLCV7pFH9-n2ti8jv)G8I73L zN-DxmEsUIVq2eIn#nfukOjeAkyEjym3IB*rOkFCbvtSshln~w6)+Vr{wdphUwj5F^ z<65erSTJ(ZedC|2eZvqy$ zXO4*jd^|Vrn`?mYRK}1)cHg?JL<$xQif9UH2LR2^Jx?Bv{Ikr0PD3zkv>iWsK5EN@~ zm7<+j0mm7v(Yb(y-+Y*R4{%WE7V9T~so25;@Zl}tg7l6qPr49vX3E}7$%G3Yh@^>+ z=3+$F{S(jaFx2{swYtrm=^&n{*%p-G@o-)Z_Y7q-S`l7!42eK6a&ur>3s# z9MJMesc9IiCU2<93#uAj1MEEAHma!OuIUjcw)8$w54du^BFc|J&z-PhSFdUb)tfo6)NqtYo=o{vCcF>MNv|?v4ZO_2gCDZNP>H@zzL$ zBhCIueb?=(i&FqwSA?Ir3Ru{GonH#zhGh+IwSb@6ZXBKq_~qHGok(p(mV&JrfZv|^ zsPnggPkk`%pCy3z*QCAJ3pl@i|98HCzq}P0f$*6vWpOBgg&U0k^3J?a%jG1{Yb8#c^c50n&!9TR^8<6ls|#%CkoU!SCGI0@L9 z(v_1BoE5=*$G^Vx8m)Cre(6iS0q?54dL|oi{OQOqVgVc9BnG4d4p^T1V-nym*9LDl z0AAgAeQqA$&G|a-xqt`$5fEMu_&|f?c?w|XJg3TX`-v2y#rJx8Kr+;qO;|T|7vOT~ z{@BTY|GcBxaTIVye3e!S_~P@^f?CwxJ857n;G)XvyT3pPj6FR+1!11cgDJ-f1nx}9 zrgbPiLsuud5cn`<52j?Lf+XSYLK1Uy>Z+44r4yqv|2C8Bk}nCiMQcfL&#;mxyPPrg zWp)XYL>&scNEMPq13eUwgcKyv0VE-2qb_bp^h4i^yfu1uQ%JeII%fnGmXE((S5Z%r(fbcOk71~oqn2kh)Z9;GaW9t>58BB2Y4x`wFm z2rxPAq3`&3mlUxrT2sV5!%~C~o_ufF<65AI=~aLzy7?2j&H+V2phyT530R6MScu+pMk0IE`r^SAVYJ?#8i(WxB3{k=cMeE@%v|3;+- zEIL@A{SVBqgI~tWIe^`Kzm9tWc>3j2`)2`e*s#p!DPYZZ)A*TyEmuY#d;-{c&vM>V zoHGpPC>R@5;w<2lH?RGnT3+ui`4r_{qjMHEeoY4s3_Yqz0R(5 z=ee9cytKG{66JEVDV!J{^Vv0D(H&r{mWRFu#|PW1BnyzZhf6y$5*Hsi5kvfNQ*VExZfZIfHURX&-t%ZBn{7 ztyrSMErEH7Vlyc9olx8)!|98Z!=T0hYp%ewKm`~}|%#4uQJ#j68tE%(Z zQUCLwc01vwQl}cYw?Fg|1f7(IQ89~lIQH<*9`xC4m&2CU zq*6pk)ka+!W+i9CIhi{Bn4^;)?DhYM847jl!HcaU>n<|4FviX8kAWqNqXvz^fKEtC zq2YZfW}~w{9JVTlC3`BmM$+A>nWVXW+ia@IC6;a3&hy0jYp@BNZR%w}`?lG0C3lK! zu`Oc8&G3{z+xPKdQ!<~Yv2lmy1M+D;$pVPfy0iBSufV@J+Pb{So+ zI;u=9j4J#+mQ$Y#(wuFzLz<&sc4RyrFltZ)XPe6C9LL?tcH0EGIV#)Zdqd@~Ol%tFxmv-$wP&((ieW%4nley3{vD}(=jjh=4EcPfg!7?N zWXMHb2n}jfxClFE%kLg`A)XTl+vE=FYhXRn z9fWkq@b}znLpko=WwCPZpW57A1>8va@xShP!gPls8;DZ684dzxR%&9PlLAU0hU2IZ z8q%Pka${&#O*KPFA5_eso1LNR(V_qa{k~Fa(WELx@q@K=f%f0Q9AZ>Aq7$szI&AjM^N& zT`;S*!B;KX5)4Diyx*tC;So)}?dLxcVE7ICgi%OTR=ZY9KM25V!BS~pxB(5QkrD2y QEKIM%ZDhP%W7h=!5447(^8f$< diff --git a/momepy/stroke_graph_x2.ipynb b/momepy/stroke_graph_x2.ipynb deleted file mode 100644 index ed1a9137..00000000 --- a/momepy/stroke_graph_x2.ipynb +++ /dev/null @@ -1,155 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "3867e2cf", - "metadata": {}, - "source": [ - "# Stroke graph generated twice...\n", - "\n", - "and then merging methods.\n", - "\n", - "(Also preparing for tests.)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "2345ab9a", - "metadata": {}, - "outputs": [], - "source": [ - "# import libraries\n", - "import geopandas as gpd\n", - "import momepy\n", - "import networkx as nx\n", - "import shapely\n", - "\n", - "import pickle" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2fb98d56", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'0.5.4.dev228+ga3fa4cb.d20250722'" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "momepy.__version__" - ] - }, - { - "cell_type": "markdown", - "id": "4d08f78b", - "metadata": {}, - "source": [ - "* read in gdf of linestrings\n", - "* explode\n", - "* mm remove false nodes\n", - "* mm gdf to nx, primal, preserving index\n", - "* mm nx to gdf only of lines\n", - "* run coins (pass angle_threshold and flow_mode, defaults!)\n", - "* from coins get .stroke_attribute() and .stroke_gdf()\n", - "* add \"rep_point\" to .stroke_gdf()\n", - "* add \"edge_indeces\" column to stroke gdf (anvy version)\n", - "* for each edge, add \"stroke_id\" as attribute to graph (clse version)\n", - "* create stroke graph (anvy version)\n", - "* add nodes to stroke graph (anvy version)\n", - "* adding edges to stroke graph (clse version)\n", - "* compute metrics\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "af9a151d", - "metadata": {}, - "outputs": [], - "source": [ - "### PREPROCESSING EXPECTED FROM USER!\n", - "\n", - "# read in toy graph (Bubenec)\n", - "gdf = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", - "\n", - "# remove false nodes (interstitital nodes of degree 2)\n", - "gdf = momepy.remove_false_nodes(gdf)\n", - "\n", - "# make primal graph\n", - "graph = momepy.gdf_to_nx(\n", - " gdf, \n", - " preserve_index=True, # !! preserving index needed for unambiguous mapping to coins!\n", - " approach=\"primal\"\n", - ")\n", - "\n", - "# get momempy lines of graph\n", - "lines = momepy.nx_to_gdf(\n", - " graph,\n", - " points=False,\n", - " lines=True\n", - ")\n", - "\n", - "# get COINS of graph lines\n", - "coins = momepy.COINS(\n", - " lines,\n", - " angle_threshold=0,\n", - " flow_mode=False\n", - ") # this will be the input to strokes_to_graph" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "cf48897f", - "metadata": {}, - "outputs": [], - "source": [ - "### USING THE FUNCTION\n", - "strokes_graph, graph = momepy.strokegraph.strokes_to_graph(coins, return_primal=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7dc4874c", - "metadata": {}, - "outputs": [], - "source": [ - "# after iteration finished, save results:\n", - "with open('stroke_graph_x2.pickle', 'wb') as handle:\n", - " pickle.dump(strokes_graph, handle, protocol=pickle.HIGHEST_PROTOCOL)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "test", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/momepy/stroke_graph_x2.pickle b/momepy/stroke_graph_x2.pickle deleted file mode 100644 index 98a2d3af098c19eddc1e965a92352ee87b7d8c40..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 5900 zcmb7|30Ms?hicket)D{I7f@oGo(1L(PG=?zE5P^go94b~30dW>V zM^S4P4-{`(TMv|{YWrBK)rti?s+H=ZSju|T1D96!Kba&ZS=8=4BK&5)dEf7S|L=Fq zw}`)**T+VG(Y-TBZMIT9Hzz=rCe>(2O@Lf2RZ$Gh7wdnoV*C~}d5ka3=kBwA+R4-! zhIUous?#2YuuSkk&}|tj1*EvYM5EZqg5;Ck`j|0 zs_%q#JX^GP#LxP~klW|8f<%+PZzlZlPC%g3u^+)s%P%Yr1W%mDWIhD%x*oJX7F@7s zN!?@cn)5FL6TpGH?>G#G&+kjFO76t$hY^c{vIBO0 zaz#Y*ase}{SLH6cIh1ymDKj!inKm^mRh!EYHnf|;Ml!S}Nj%eN7;)&y`QfuKR2-yx z7@o?~lp50T?Do*)Ec~O5-cv}qnj{&5Pxmsmw(ub|wUo-Bn}#9mXm>+PrCLiV<;o0c z8rvOIoGx9J8z7M>)nq`rE=`*%RjZ|VAkfI9X;L*rr1|TnFs6`I+tuJ-qms%}Gvr8JB9}TH!9%4{ z?rd@K2xr2T=u1+)Q43t{2;CPrS3%d7i%s&)Mja?ms&DvYl$O3++)*ynzl4kUXx3-x z?uI95R^`*Y#0C7&d)2Dn!JTaZqxyhX2ln1}5BzT1fyIGf;qK$vH^I>*#S22g`4LSg zu7PbFvPMOLkLBfmeFc28I`Z>r;OjZMqD$cWis{r26*>%m*sc{x>s%Qtq9ssu*{q!(@jJNr3T9R|C3-XFo1WBa+1 zMc;snCi4PUfOEs77n{MOBNsne4sP9jroRWuRoc0;u^4P!-rcsB3fS`Qx!_zdTkbCi z+Z~s|Q3_2&9+>y_Kk{ya$AoOrECB1vn;I+*D>`z78eK7s@@{09EB-}@hTfUO7k z`mrCr)eCO(PX9aX4xU#C8g7jR_jvd$>IPVGH(C?Ua=6Net&poa$;D}4&5E$om%%*G zb>2zf)@7~sP2fk`pAOFfchqI?U@M|Xy>x3P_{Hg|uHS%9zCZTM67c@|w5NN)1ugr( z^#Xr!JzT`{=`CeZeZU1juF7Kh%H6)Vgy1#7KX`-b9pIussj&dD?o)c2_!&d+?tvk;z9ei2oIt+@s@c~X3M43ClFxmh^)USnmWiP<(WPy-H{aeh7EJpBZ$J# z8oRI2W?uOkkB#7;A0}-$0k%%U$|(oxY+-ZU9}R!7W4zrveTf@*XVc}=IpFA1;h#r> zGoHu#rh|Q#=beoMf3Y^GN&#Noc6ClZcyoc=Z4P+QZ@yvW-~+AvCrM!ICAM09c6I?FXA2|j5`%TIAqu|WwY8e5(_~evL6WiV`Zcrq+sB-tMA5qbx zPt8qY*(6d~W9IaZoDxo?6V+1rY)+)azh{l8HHy^C7HqhL6{!`;!Ud585XliD*%>P~ zYDmOAuZw1L(5&`g(b1z)QA1bq;ay5El<|*%;%h2z*v1xMLQV!M2VNn2N6l(UWi^`VgMxh1bUS4q>Me zWz~|njTQmk)d%Pb-!UuIvUzAD8SA6&hpF}aTHBMkU{AM?DG%`H1u=P}GJ=Iw+PS%AqdQ6G; zS`-p9??S2{?Cr?t(Y6MBcV(lyFIdnbytx`&^xd#FA8_H-h;8NIz&`#GFR)3F71#H= z)%7ptrbc0iH{UQDY>Zn{r8E}WXISa3x;OAH0uZlW1;mjFSG|!j~s765$#*<;v+Zpi7m9rdL8VcL+!AMzpOwT&%kxX4o%9XWa?%1Eu$Ej;Leq`zcuJGhOF3b1* ze}y-$U|~{inOU3$+d4vMjMLpb&R(GnYl|>AHYo`Ig|CRydSWW^Ds^Tjrm_eAE-JiJ zI_Pq24OqJ`Cy{33wAvh*;{2$wEqeW^``iF4TH6rXi;HuiKcU!U)N^&5{$llPMv`$s zPh03|Yd*kAZ`JqRR$~@tJZD=+I2z;ZXCCL?;F<(i)L4~mc}0swoG(|orp@(Hmk`I? zUk9|iVI1Xm7XH!%cKU9)54(kF{C40vN7$I<(e0~N*yso!-R=y2I!c*$8@%b{nB6_W z^*wgZzXi5lHBEWQZgu!`_{=BzJY>5j)CBM4^3YOIZd=ub-p%?nuz6tX+Ri)=m$Nd1 zoAyM#tZPZL)Ap7he%I+}dx~Y<4lCo$ z6BX}T+B{5UxJ9D>$clbH@_J8Q??+yGI$GyDaD0k|r(yi!pzN6zp15y0ZYHqwXFUzP zGBPf(dra#eoAV9djs_KMs9J8DX=&No(kqoPi%2$R=6732T13Jvqi^uk z(gQkR=F6sFCVPpmE0_1Y2UgsyBsZ)$$n)@;e^6pBQ0u5zYVvvYHj6} z`Qb9ZJ@di95pRnutm?NEZ?O8RTo|(M^qrz|a(Cl?ML(psh~{XnJ54t)-q_f7Kj+nA z^ILnSs3upp80H_gp6zwqfJ7F*{3}^}L%c)Uf;87V>x5N9dHgX@I?j8gMR^=j{4?*$P>VGEm5IgLGq)z1`tKij?7i&| z4UUY1lAp&A_KE=HUZWrPgssAc6~bQe9{Y<&-O=yjz&`pm>`n)F8*oE}8{D#kdfbc3 zxepcH*qb`qO(HR#=SpNaXeA{Qtd=-V!x1ZvV+R-?nhtx_qzcD#S*c_;9t)$P9eD-I7R5sB+Z-qDw5DQ_~%PB jI++Y_;V+e%Ou=7@c=pjo+Ch>{rphTT6Rk_uB?tT$Q#8!n diff --git a/momepy/strokegraph.py b/momepy/strokegraph.py index 38c71b16..45cce71d 100644 --- a/momepy/strokegraph.py +++ b/momepy/strokegraph.py @@ -71,6 +71,10 @@ def strokes_to_graph(coins, compute_metrics=True, return_primal=False): The following metrics are computed: betweenness centrality, closeness centrality, degree, connectivity, access, orthogonality, spacing. For details on all metrics computed, see :cite:`el2022urban`. + return_primal: bool (default False) + if True, return both the dual graph (where each node is a stroke and each + edge is if two strokes intersect) and the primal graph. Else return only + the dual graph. """ # get strokes attributes from coins diff --git a/momepy/strokegraph_anvy.ipynb b/momepy/strokegraph_anvy.ipynb deleted file mode 100644 index 869f2139..00000000 --- a/momepy/strokegraph_anvy.ipynb +++ /dev/null @@ -1,4154 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Playground for strokes graph" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "# import libraries\n", - "import geopandas as gpd\n", - "import matplotlib.pyplot as plt\n", - "import momepy\n", - "import networkx as nx\n", - "import folium\n", - "from itertools import combinations\n", - "from shapely import LineString\n", - "import numpy as np\n", - "import math\n", - "import pickle\n", - "from collections import Counter" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "# https://carto.com/carto-colors/ > Prism\n", - "colors_list = [\n", - " \"#5F4690\",\n", - " \"#1D6996\",\n", - " \"#38A6A5\",\n", - " \"#0F8554\",\n", - " \"#73AF48\",\n", - " \"#EDAD08\",\n", - " \"#E17C05\",\n", - " \"#CC503E\",\n", - " \"#94346E\",\n", - " \"#6F4070\",\n", - " \"#994E95\",\n", - " \"#666666\"\n", - "]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Import example data set" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [], - "source": [ - "# read in toy graph (Bubenec)\n", - "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Workflow (will be wrapped in function later)\n", - "\n", - "- [ ] input is a set of linestrings\n", - "- [ ] remove false nodes \n", - "- [ ] convert linestrings to primal graph\n", - "- [ ] get points and lines gdf from primal graph\n", - "- [ ] run COINS on lines gdf to find strokes\n", - "- [ ] add mapping of strokeID:edgeIDs to stroke gdf (use momepy's **edge ID**, not indexing)\n", - "- [ ] add stroke attribute to each edge on primal graph" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "# define variable defaults (will be arguments passed to future function)\n", - "angle_threshold=0\n", - "flow_mode=False" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
geometrymm_lennode_startnode_endmy_index
0LINESTRING (1603585.64 6464428.774, 1603413.20...264.103950010
1LINESTRING (1603268.502 6464060.781, 1603296.8...99.751190231
2LINESTRING (1603607.303 6464181.853, 1603592.8...199.746503142
3LINESTRING (1603363.558 6464031.885, 1603376.5...203.014090133
4LINESTRING (1603413.206 6464228.73, 1603274.45...198.482724154
\n", - "
" - ], - "text/plain": [ - " geometry mm_len node_start \\\n", - "0 LINESTRING (1603585.64 6464428.774, 1603413.20... 264.103950 0 \n", - "1 LINESTRING (1603268.502 6464060.781, 1603296.8... 99.751190 2 \n", - "2 LINESTRING (1603607.303 6464181.853, 1603592.8... 199.746503 1 \n", - "3 LINESTRING (1603363.558 6464031.885, 1603376.5... 203.014090 1 \n", - "4 LINESTRING (1603413.206 6464228.73, 1603274.45... 198.482724 1 \n", - "\n", - " node_end my_index \n", - "0 1 0 \n", - "1 3 1 \n", - "2 4 2 \n", - "3 3 3 \n", - "4 5 4 " - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# remove false nodes\n", - "streets = momepy.remove_false_nodes(streets)\n", - "\n", - "# add unique edge ID to streets, already HERE!\n", - "# streets[\"edge_id\"] = streets.index\n", - "\n", - "# make primal graph\n", - "graph = momepy.gdf_to_nx(\n", - " streets, \n", - " preserve_index=True, # index of lines gdf should be referring to EXACTLY THE SAME ELEMENT as index of streets gdf\n", - " approach=\"primal\"\n", - ")\n", - "\n", - "# get gdfs of points and lines\n", - "points, lines = momepy.nx_to_gdf(graph, points=True, lines=True)\n", - "\n", - "# # asserting that our edge indeces didn't get messed up\n", - "# assert(len(lines) == len(streets))\n", - "\n", - "# for i, row in lines.iterrows():\n", - "# assert(row[\"geometry\"] == streets.loc[i,\"geometry\"])\n", - "\n", - "lines[\"my_index\"] = lines.index # just for plotting TODO remove later\n", - "\n", - "# each row is an edge\n", - "lines.head()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(1,1, figsize=(8,8))\n", - "lines.plot(ax=ax, column=\"my_index\", cmap=\"tab20\", lw=3, legend=True, zorder=0)\n", - "points.plot(ax=ax, color = \"black\", zorder=1)\n", - "ax.set_axis_off()\n", - "plt.title(\"Input: edges\")\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
n_segmentsgeometryrep_pointstroke_id
stroke_group
08LINESTRING (1603278.899 6463669.186, 1603283.7...POINT (1603374.663 6464077.898)0
119LINESTRING (1603077.5 6464475.323, 1603085.515...POINT (1603237.049 6464133.622)1
217LINESTRING (1603537.194 6464558.112, 1603557.6...POINT (1603707.107 6464238.854)2
35LINESTRING (1603413.206 6464228.73, 1603274.45...POINT (1603149.929 6464130.225)3
414LINESTRING (1602970.377 6464268.058, 1602974.0...POINT (1603264.658 6463848.976)4
\n", - "
" - ], - "text/plain": [ - " n_segments geometry \\\n", - "stroke_group \n", - "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", - "1 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", - "2 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", - "3 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", - "4 14 LINESTRING (1602970.377 6464268.058, 1602974.0... \n", - "\n", - " rep_point stroke_id \n", - "stroke_group \n", - "0 POINT (1603374.663 6464077.898) 0 \n", - "1 POINT (1603237.049 6464133.622) 1 \n", - "2 POINT (1603707.107 6464238.854) 2 \n", - "3 POINT (1603149.929 6464130.225) 3 \n", - "4 POINT (1603264.658 6463848.976) 4 " - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# make coins\n", - "coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", - "\n", - "# get gdfs from COINS class\n", - "stroke_attribute = coins.stroke_attribute()\n", - "stroke_gdf = coins.stroke_gdf()\n", - "stroke_gdf[\"rep_point\"] = stroke_gdf.geometry.apply(lambda x: x.interpolate(0.5, normalized=True))\n", - "\n", - "# add stroke_id column\n", - "stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", - "\n", - "stroke_gdf.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
n_segmentsgeometryrep_pointstroke_idedge_indeces
stroke_group
08LINESTRING (1603278.899 6463669.186, 1603283.7...POINT (1603374.663 6464077.898)0[0, 3, 15, 27]
119LINESTRING (1603077.5 6464475.323, 1603085.515...POINT (1603237.049 6464133.622)1[1, 12, 14, 25]
217LINESTRING (1603537.194 6464558.112, 1603557.6...POINT (1603707.107 6464238.854)2[2, 11, 28, 30]
35LINESTRING (1603413.206 6464228.73, 1603274.45...POINT (1603149.929 6464130.225)3[4, 5, 6]
414LINESTRING (1602970.377 6464268.058, 1602974.0...POINT (1603264.658 6463848.976)4[7, 8, 9, 13, 21, 22, 24]
\n", - "
" - ], - "text/plain": [ - " n_segments geometry \\\n", - "stroke_group \n", - "0 8 LINESTRING (1603278.899 6463669.186, 1603283.7... \n", - "1 19 LINESTRING (1603077.5 6464475.323, 1603085.515... \n", - "2 17 LINESTRING (1603537.194 6464558.112, 1603557.6... \n", - "3 5 LINESTRING (1603413.206 6464228.73, 1603274.45... \n", - "4 14 LINESTRING (1602970.377 6464268.058, 1602974.0... \n", - "\n", - " rep_point stroke_id \\\n", - "stroke_group \n", - "0 POINT (1603374.663 6464077.898) 0 \n", - "1 POINT (1603237.049 6464133.622) 1 \n", - "2 POINT (1603707.107 6464238.854) 2 \n", - "3 POINT (1603149.929 6464130.225) 3 \n", - "4 POINT (1603264.658 6463848.976) 4 \n", - "\n", - " edge_indeces \n", - "stroke_group \n", - "0 [0, 3, 15, 27] \n", - "1 [1, 12, 14, 25] \n", - "2 [2, 11, 28, 30] \n", - "3 [4, 5, 6] \n", - "4 [7, 8, 9, 13, 21, 22, 24] " - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# add edge_ids column (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", - "stroke_gdf[\"edge_indeces\"] = stroke_gdf.stroke_id.apply(\n", - " lambda x: list(stroke_attribute[stroke_attribute==x].index)\n", - ")\n", - "\n", - "stroke_gdf.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(1,1, figsize=(10,10))\n", - "for stroke_id in stroke_gdf.stroke_id:\n", - " stroke_gdf[stroke_gdf.stroke_id==stroke_id].plot(ax=ax, lw=3, label=stroke_id, zorder=0, color=colors_list[stroke_id])\n", - "points.plot(ax=ax, color = \"black\", zorder=1)\n", - "ax.set_axis_off()\n", - "ax.legend(title=\"Generated: stroke IDs\")\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [], - "source": [ - "# make dictionary for primal graph: d={edge_index:edge_name}\n", - "# where edge_name (in momepy language) is the corresponding node tuple\n", - "d_name2index = nx.get_edge_attributes(graph, \"index_position\")\n", - "d_index2name = {v:k for k,v in d_name2index.items()}\n", - "\n", - "# for each edge, add \"stroke_id\" as attribute to graph\n", - "for _, row in stroke_gdf.iterrows():\n", - " for edge_index in row.edge_indeces: \n", - " graph.edges[d_index2name[edge_index]][\"stroke_id\"] = row.stroke_id\n", - "\n", - "# getting dicts of edge name : stroke ID, and edge index : stroke id # TODO: one of them might be obsolete?\n", - "d_name2stroke = nx.get_edge_attributes(graph, \"stroke_id\")\n", - "d_index2stroke = {d_name2index[k]:v for k,v in d_name2stroke.items()} " - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
geometrymm_lennode_startnode_endmy_index
0LINESTRING (1603585.64 6464428.774, 1603413.20...264.103950010
1LINESTRING (1603268.502 6464060.781, 1603296.8...99.751190231
2LINESTRING (1603607.303 6464181.853, 1603592.8...199.746503142
3LINESTRING (1603363.558 6464031.885, 1603376.5...203.014090133
4LINESTRING (1603413.206 6464228.73, 1603274.45...198.482724154
\n", - "
" - ], - "text/plain": [ - " geometry mm_len node_start \\\n", - "0 LINESTRING (1603585.64 6464428.774, 1603413.20... 264.103950 0 \n", - "1 LINESTRING (1603268.502 6464060.781, 1603296.8... 99.751190 2 \n", - "2 LINESTRING (1603607.303 6464181.853, 1603592.8... 199.746503 1 \n", - "3 LINESTRING (1603363.558 6464031.885, 1603376.5... 203.014090 1 \n", - "4 LINESTRING (1603413.206 6464228.73, 1603274.45... 198.482724 1 \n", - "\n", - " node_end my_index \n", - "0 1 0 \n", - "1 3 1 \n", - "2 4 2 \n", - "3 3 3 \n", - "4 5 4 " - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "lines.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = stroke_gdf.explore(tiles=\"cartodb.positron\", column = \"stroke_id\", name = \"strokes\", cmap = \"Reds\", style_kwds={\"weight\":8})\n", - "lines.explore(m=m, column = \"my_index\", name = \"lines\", cmap = \"Blues\", style_kwds={\"weight\":8})\n", - "folium.LayerControl().add_to(m)\n", - "m" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "* Now we have a primal graph `graph` where each edge has the attributes `edge_id` and `stroke_id`\n", - "* We have this information also in `stroke_gdf`\n", - "* Each stroke (each line in stroke_gdf) will be a node of the stroke graph" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "def get_interior_angle(a, b, c):\n", - " \"\"\"\n", - " Measure the angle between a-b, b-c (in degrees).\n", - " \"\"\"\n", - " ba = [a[0]-b[0],a[1]-b[1]]\n", - " bc = [c[0]-b[0],c[1]-b[1]]\n", - " # np.dot(ba, bc) # ba[0]*bc[0] + ba[1]*bc[1]\n", - " # np.linalg.norm(ba) # np.sqrt(ba[0]**2+ba[1]**2)\n", - " # np.linalg.norm(bc) # np.sqrt(bc[0]**2+bc[1]**2)\n", - " theta_rad = math.acos(np.dot(ba,bc)/(np.linalg.norm(ba)*np.linalg.norm(bc)))\n", - " theta_deg = np.degrees(theta_rad)\n", - " if theta_deg > 90:\n", - " theta_deg = 180 - theta_deg\n", - " return theta_deg\n", - "\n", - "def get_segment(geom, n):\n", - " '''\n", - " geom... linestring.\n", - " n.... coordinate of start-or-end node on linestring.\n", - " returns: coordinate tuple (n, adjacent-to-n), in THAT ORDER\n", - " (ie. if n is start node, returns coords in position 0 and 1;\n", - " if n is end node, reutnrs coords in position n, n-1\n", - " )\n", - " '''\n", - " coords = [c for c in geom.coords]\n", - " index_n = coords.index(n)\n", - " if index_n == 0:\n", - " return coords[0:2]\n", - " elif index_n == len(coords)-1:\n", - " return [coords[index_n], coords[index_n-1]]\n", - " else:\n", - " raise ValueError(\"Node not on end of edge?\")\n", - "\n", - "# use angles_gdf length to add to connectivity of strokes (nodes)\n", - "def get_connectivity(angles_gdf):\n", - " if len(angles_gdf)==4:\n", - " return 2\n", - " elif len(angles_gdf) in [2,3]:\n", - " return 1\n", - " else:\n", - " raise ValueError(\"Unexpected number of edge segments in angles_gdf\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "NodeDataView({0: {'edge_indeces': [0, 3, 15, 27], 'geometry': , 'geometry_stroke': , 'x': 1603374.6625343116, 'y': 6464077.898491419, 'connectivity': 0}, 1: {'edge_indeces': [1, 12, 14, 25], 'geometry': , 'geometry_stroke': , 'x': 1603237.0487682838, 'y': 6464133.622486805, 'connectivity': 0}, 2: {'edge_indeces': [2, 11, 28, 30], 'geometry': , 'geometry_stroke': , 'x': 1603707.1065106073, 'y': 6464238.853991265, 'connectivity': 0}, 3: {'edge_indeces': [4, 5, 6], 'geometry': , 'geometry_stroke': , 'x': 1603149.9288811635, 'y': 6464130.224503239, 'connectivity': 0}, 4: {'edge_indeces': [7, 8, 9, 13, 21, 22, 24], 'geometry': , 'geometry_stroke': , 'x': 1603264.6577362637, 'y': 6463848.97596353, 'connectivity': 0}, 5: {'edge_indeces': [10], 'geometry': , 'geometry_stroke': , 'x': 1603137.4077031056, 'y': 6463800.908382258, 'connectivity': 0}, 6: {'edge_indeces': [16, 17, 18, 23, 29], 'geometry': , 'geometry_stroke': , 'x': 1603592.2349246691, 'y': 6464121.336160048, 'connectivity': 0}, 7: {'edge_indeces': [19], 'geometry': , 'geometry_stroke': , 'x': 1603028.737187382, 'y': 6463900.594576759, 'connectivity': 0}, 8: {'edge_indeces': [20], 'geometry': , 'geometry_stroke': , 'x': 1603207.5969886228, 'y': 6463992.707728057, 'connectivity': 0}, 9: {'edge_indeces': [26], 'geometry': , 'geometry_stroke': , 'x': 1603342.3426854417, 'y': 6464406.368225728, 'connectivity': 0}})" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "stroke_graph = nx.Graph()\n", - "stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", - "stroke_graph.graph[\"approach\"] = graph.graph[\"approach\"]\n", - "stroke_graph.add_nodes_from(\n", - " [\n", - " (\n", - " row.stroke_id, \n", - " {\n", - " \"edge_indeces\": row.edge_indeces,\n", - " \"geometry\": row.rep_point,\n", - " \"geometry_stroke\": row.geometry,\n", - " \"x\": row.rep_point.xy[0][0],\n", - " \"y\": row.rep_point.xy[1][0],\n", - " \"connectivity\": 0\n", - " }\n", - " ) for _, row in stroke_gdf.iterrows()\n", - " ]\n", - ")\n", - "# node names are the stroke IDs.\n", - "# each node has the attribute \"edge_indeces\".\n", - "stroke_graph.nodes(data=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "to find the **edges** of the stroke graph, we look at the primal `graph`'s nodes and the stroke_ids of their adjacent edges" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node: 0\n", - "Adjacent strokes (list): [0, 2, 2]\n", - "Adjacent strokes (uniques): {0, 2}\n", - "Checking edge: (0, 2)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 2])\n", - "angles: [np.float64(62.302182356951434)]\n", - "(0, 2) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 1\n", - "Adjacent strokes (list): [0, 2, 0, 3, 9]\n", - "Adjacent strokes (uniques): {0, 9, 2, 3}\n", - "Checking edge: (0, 9)\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgcAAAGTCAYAAAC8vrHzAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAAVABJREFUeJzt3XdcVfX/B/DXZV32lo2KC5Sp4gBciGiun2mWZoXaLhtmw4Y5ynJ8G5qlZZli5sicWWou3CCIouKeTEHZMi7jnt8fyI0jKOvCuRdez8eDxyOO5977BuLD657P+3w+MkEQBBARERHdpyN1AURERKRZGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgEiD5eXlYerUqWjTpg2MjIwQGBiI6OhoqcsiIg2mjnGD4YBIg7344ovYs2cPfvvtN5w9exaDBw/GoEGDkJycLHVpRKSh1DFuyLjxEpFmKiwshJmZGbZt24bhw4erjvv5+WHEiBGYO3euhNURkSZS17ih11gFEjUnRUVFKC4ubvDzCIIAmUwmOiaXyyGXy6ucW1pairKyMhgaGoqOGxkZ4ciRIw2uhYgal7rGDaD2Y4e6xg1eOSCqQVFREaytrVFYWNjg5zI1NcW9e/dEx2bNmoXZs2dXe35gYCAMDAywdu1a2NvbY926dQgLC0PHjh1x6dKlBtdDRI1DneMGULexQx3jBsMBUQ1yc3NhYWGBCRMmwMDAoN7PU1xcjLVr1yIxMRHm5uaq4w+7cgAA165dw/PPP49Dhw5BV1cX3bp1Q6dOnRAbG4vz58/XuxYialzqGjeAuo8d6hg3OK1AVEsGBgYN/iUHAHNzc9Ev+KO0b98eBw8eRH5+PnJzc+Ho6Ihx48bBzc2twXUQUeNT17gB1H7sUMe4wbsViLSAiYkJHB0dkZWVhd27d2PUqFFSl0REGq4h4wavHBBpsN27d0MQBLi7u+Pq1at4//334e7ujsmTJ0tdGhFpKHWMG7xyQKTBcnJyMGXKFHh4eCAsLAx9+vTBv//+C319falLIyINpY5xg1cOiDTYU089haeeekrqMohIi6hj3OCVAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyIiIhJhOCAiIiIRhgMiIiISYTggIiIiEYYDIiIiEmE4ICIiIhGGAyINVVpaihkzZsDNzQ1GRkZo164dPvvsMyiVSqlLIyINpa5xQ6+R6iOiBlqwYAF+/PFHhIeHw9PTEzExMZg8eTIsLCzw9ttvS10eEWkgdY0bDAdEGur48eMYNWoUhg8fDgBo27Yt1q1bh5iYGIkrIyJNpa5xg9MKRE0sNzdX9KFQKKo9r0+fPti3bx8uX74MAIiLi8ORI0cwbNiwpiyXiDREbcYOdY0bvHJA1MRcXV1Fn8+aNQuzZ8+uct706dORk5MDDw8P6OrqoqysDF988QWefvrpJqqUiDRJbcYOdY0bDAdETSwxMRHm5uaqz+VyebXnbdiwAWvWrMHatWvh6emJ06dPY+rUqXBycsLEiRObqlwi0hC1GTvUNW4wHBA1MXNzc9Ev+MO8//77+PDDDzF+/HgAgLe3N27duoV58+YxHBC1QLUZO9Q1brDngEhDFRQUQEdH/Cuqq6vLWxmJ6KHUNW7wygGRhho5ciS++OILtG7dGp6enjh16hS++eYbPP/881KXRkQaSl3jBsMBUS31sdgDY3n9L7YVKJRYVYfzlyxZgk8//RSvv/460tPT4eTkhFdeeQUzZ86sdw1E1LQaOm4AdRs71DVuyARBEOpcKVELkpubCwsLC/zytnODw8GLi5ORk5NTq54DItJe6ho3AGnGDvYcEBERkQjDAREREYmoNRx89913kMlk8PLyeug5MplMtGhDREQEZDIZIiIiGvz6//zzT7WLyajDqlWrIJPJtGbp2rVr12LRokVSl1GFOn/eFRYtWoQxY8bAzc0NMpkMAwYMUNtzExG1RGoNB7/++isAID4+HlFRUep86lr5559/MGfOnCZ/XU2kqeGgMfz444+4desWBg4ciFatWkldDhGR1lNbOIiJiUFcXJxqs4cVK1ao66kbhSAIKCwslLoMUoPz58/j5MmTWLFiBezs7KQuh4hI66ktHFSEgfnz5yMwMBDr169HQUGBup4eBQUFeO+99+Dm5gZDQ0NYW1vD398f69atAwBMmjQJP/zwA4DyqYuKj5s3b6qOvfHGG/jxxx/RuXNnyOVyhIeHAwCOHDmCkJAQmJmZwdjYGIGBgfj7779rrCk1NRXdu3dHx44dceXKFQDlHaoVdRoYGMDZ2RlTp05Ffn6+6LEbN25Er169YGFhAWNjY7Rr165W96H+8MMP6NevH+zs7GBiYgJvb28sXLgQJSUlqnMGDBiAv//+G7du3RJ9Lx6lbdu2GDFiBHbt2oVu3brByMgIHh4eqqtBlZ07dw6jRo2ClZUVDA0N4efnp/peVnbx4kU89thjMDY2hq2tLV599VXk5eVV+/p79+5FSEgIzM3NYWxsjKCgIOzbt6/G7weAKgt+EBFRw6hlnYPCwkKsW7cOPXr0gJeXF55//nm8+OKL2Lhxo9qWeZ02bRp+++03zJ07F127dkV+fj7OnTuHjIwMAMCnn36K/Px8/Pnnnzh+/LjqcY6Ojqr/3rp1Kw4fPoyZM2fCwcEBdnZ2OHjwIEJDQ+Hj44MVK1ZALpdj6dKlGDlyJNatW4dx48ZVW8+5c+cwbNgwuLi44Pjx47C1tUVBQQH69++PpKQkfPzxx/Dx8UF8fDxmzpyJs2fPYu/evZDJZDh+/DjGjRuHcePGYfbs2TA0NMStW7ewf//+Gr8P165dw4QJE1ThIy4uDl988QUuXryo+kO+dOlSvPzyy7h27Rq2bNlS6+9xXFwc3n33XXz44Yewt7fHL7/8ghdeeAEdOnRAv379AACXLl1CYGAg7Ozs8N1338HGxgZr1qzBpEmTkJaWhg8++AAAkJaWhv79+0NfXx9Lly6Fvb09fv/9d7zxxhtVXnfNmjUICwvDqFGjEB4eDn19ffz0008YMmQIdu/ejZCQkFp/DURE1HBqCQd//vkncnJy8MILLwAAxo0bh6lTp2LFihVqCwdHjx7F4MGD8c4776iOVUxhAED79u1hb28PAOjdu3e1z3Hv3j2cPXsWVlZWqmMBAQGwsrJCREQETE1NAQAjRoyAn58f3nvvPTz11FNV3nXv3bsXTzzxBAYPHozffvsNhoaGAMobMs+cOYOoqCj4+/sDAEJCQuDs7IyxY8di165dGDp0KI4dOwZBEPDjjz/CwsJC9byTJk2q8fvwzTffqP5bqVSib9++sLGxweTJk/H111/DysoKXbp0gaWlJeRy+UO/F9W5e/cujh49itatWwMA+vXrh3379mHt2rWqcDB79mwUFxfjwIEDqh3Chg0bhuzsbMyZMwevvPIKLCws8O233+LOnTs4deoUfH19AQBDhw7F4MGDkZCQoHrNgoICvP322xgxYoQoyAwbNgzdunXDxx9/LEn/ChFRS6aW67ErVqyAkZGRaqMHU1NTPPnkkzh8+LDqcntD9ezZEzt37sSHH36IiIiIevULDBw4UBQM8vPzERUVhbFjx6qCAVC+DvVzzz2HpKQkXLp0SfQc4eHhGDZsGF588UX88ccfqmAAADt27ICXlxf8/PxQWlqq+hgyZIioQ79Hjx4AgKeeegp//PEHkpOTa/01nDp1Cv/3f/8HGxsb6OrqQl9fH2FhYSgrK1Pt311ffn5+qmAAAIaGhujUqRNu3bqlOrZ//36EhIRU2Tp00qRJKCgoUF21OXDgADw9PVXBoMKECRNEnx87dgyZmZmYOHGi6HumVCrx2GOPITo6usqUDBERNa4Gh4OrV6/i0KFDGD58OARBQHZ2NrKzszF27FgAqHbOuj6+++47TJ8+HVu3bkVwcDCsra3x+OOP1yl8VJ5iAICsrCwIglDlOAA4OTkBgGraosL69ethZGSEF198scoVhbS0NJw5cwb6+vqiDzMzMwiCgLt37wIof0e+detWlJaWIiwsDC4uLvDy8lL1TzxMQkIC+vbti+TkZCxevBiHDx9GdHS0qteioQ2WNjY2VY7J5XLR82ZkZNTq+5WRkQEHB4cq5z14LC0tDQAwduzYKt+3BQsWQBAEZGZm1v+LIiKiOmvwtMKvv/4KQRDw559/4s8//6zy7+Hh4Zg7dy50dXUb9DomJiaYM2cO5syZg7S0NNVVhJEjR+LixYu1eo4H/5hbWVlBR0cHqampVc5NSUkBANja2oqO//777/j000/Rv39//Pvvv/Dz81P9m62tLYyMjB4aiCo/16hRozBq1CgoFApERkZi3rx5mDBhAtq2bYuAgIBqH79161bk5+dj8+bNaNOmjer46dOnH/l1q5ONjU2tvl82Nja4fft2lfMePFZx/pIlSx46BVIxXURERE2jQeGgrKwM4eHhaN++PX755Zcq/75jxw58/fXX2LlzJ0aMGNGQlxKxt7fHpEmTEBcXh0WLFqGgoADGxsaQy+UAyt9BGxkZ1fg8JiYm6NWrFzZv3oyvvvpK9RilUok1a9bAxcUFnTp1Ej3G2toae/fuxYgRIxAcHIydO3eq/qiNGDECX375JWxsbODm5larr0Uul6N///6wtLTE7t27cerUqYeGg4pwU/F1AuW3ZP7888/VPm9j3KoZEhKCLVu2ICUlRXW1AABWr14NY2Nj1fciODgYCxcuRFxcnGhqYe3ataLnCwoKgqWlJc6fP19tsyIRETW9BoWDnTt3IiUlBQsWLKh2VTovLy98//33WLFiRYPDQa9evTBixAj4+PjAysoKFy5cwG+//YaAgAAYGxsDALy9vQEACxYswNChQ6GrqwsfHx8YGBg89HnnzZuH0NBQBAcH47333oOBgQGWLl2Kc+fOYd26ddXeAmhmZoZdu3ZhzJgxCA0Nxfbt2xEcHIypU6di06ZN6NevH9555x34+PhAqVQiISEB//77L95991306tULM2fORFJSEkJCQuDi4oLs7GwsXrwY+vr66N+//0NrDQ0NhYGBAZ5++ml88MEHKCoqwrJly5CVlVXlXG9vb2zevBnLli1D9+7doaOjo2qSbIhZs2Zhx44dCA4OxsyZM2FtbY3ff/8df//9NxYuXKhqsJw6dSp+/fVXDB8+HHPnzlXdrfDgVR5TU1MsWbIEEydORGZmJsaOHQs7OzvcuXMHcXFxuHPnDpYtW/bImmJiYlS3rObm5qquZAHl/R2Vr7IQEVHNGhQOVqxYAQMDA0yePLnaf7e1tcXo0aPx559/Ii0trUGXhwcOHIjt27fj22+/RUFBAZydnREWFoZPPvlEdc6ECRNw9OhRLF26FJ999hkEQcCNGzfQtm3bhz5v//79sX//fsyaNQuTJk2CUqmEr68vtm/f/shAY2RkhG3btmHChAkYNmwYNm3ahGHDhuHw4cOYP38+li9fjhs3bsDIyAitW7fGoEGDVHX06tULMTExmD59Ou7cuQNLS0v4+/tj//798PT0fOhrenh4YNOmTZgxYwbGjBkDGxsbTJgwAdOmTcPQoUNF57799tuIj4/Hxx9/jJycHAiCAHVswOnu7o5jx47h448/xpQpU1BYWIjOnTtj5cqVorstHBwccPDgQbz99tt47bXXYGxsjNGjR+P777/HqFGjRM/57LPPonXr1li4cCFeeeUV5OXlwc7ODn5+frW6g+P777+vss7Ck08+CQBV6iIioppxy2aiGnDLZiKqK27ZTERERM0KwwERERGJMBwQERGRCMMBETVYVFQURo8ejdatW0Mul8Pe3h4BAQF49913RectXboUq1atapQaJk2aJFrpVEqHDx+GXC4XrS4KALGxsRg0aBBMTU1haWmJMWPG4Pr16w16rd27dyMoKAhGRkawsLDAyJEjER8fLzqnpKQE7du3b5Rt3L/88kts3bpV7c/bULNnz65xw7m6yMvLwwcffIDBgwejVatWkMlkmD17ttqeX9MwHBBRg/z9998IDAxEbm4uFi5ciH///ReLFy9GUFAQNmzYIDq3McOBphAEAVOnTsVLL70kuo324sWLGDBgAIqLi/HHH3/g119/xeXLl9G3b1/cuXOnXq+1bds2DB06FHZ2dti0aRN+/PFHXLlyBX379sW1a9dU5+nr62PmzJn47LPPqqz62lCaGg7ULSMjA8uXL4dCocDjjz8udTmNTi0bLxFRy7Vw4UK4ublh9+7d0NP7b0gZP348Fi5cWO/nLSkpgUwmEz2nNti1axdiY2OrLPg1c+ZMyOVy7NixQ9VxXrHl+1dffYUFCxbU+bWmT5+uWtOk4l1yYGAgOnXqhJkzZ+L3339Xnfv0009j2rRp+Omnn/Dxxx834Ctsmdq0aYOsrCzIZDLcvXu32oX/mhNeOSCiBsnIyICtrW21f8R1dP4bYtq2bYv4+HgcPHgQMpkMMplMtfZHREQEZDIZfvvtN7z77rtwdnaGXC7H1atXAZQv0+7r6wtDQ0NYW1tj9OjRuHDhQo21HT16FLa2thgxYoRqA68rV65gwoQJsLOzg1wuR+fOnVX7k1RQKpWYO3cu3N3dYWRkBEtLS/j4+GDx4sU1vuayZcvQo0cPuLu7q46VlpZix44deOKJJ0S3orVp0wbBwcF12lq9QkZGBi5duoShQ4eKLp+3adMGXl5e2Lp1K8rKylTHDQwMMG7cOCxfvrzGNU+Kiorw7rvvws/PDxYWFrC2tkZAQAC2bdsmOk8mkyE/Px/h4eGqn2l1C+JVuHnzJmQyGb766it88803cHNzg6mpKQICAhAZGVnl/O3bt6sWujMzM0NoaKhqc7fK/v77b/j5+UEul8PNzQ1fffVVta8vCAKWLl0KPz8/GBkZwcrKCmPHjq3V1E7F19dSMBwQUYMEBAQgKioKb731FqKiolBSUlLteVu2bEG7du3QtWtXHD9+HMePH6/yR/Gjjz5CQkICfvzxR/z111+ws7PDvHnz8MILL8DT0xObN2/G4sWLcebMGQQEBDxy47U//vgDISEheOqpp7Bt2zaYmJjg/Pnz6NGjB86dO4evv/4aO3bswPDhw/HWW29hzpw5qscuXLgQs2fPxtNPP42///4bGzZswAsvvIDs7OxHfi+Ki4uxd+9eBAcHi45fu3YNhYWF8PHxqfIYHx8fXL16FUVFRY987upeCxAvp15BLpejoKBANLUAAAMGDMCtW7dw7ty5Rz63QqFAZmYm3nvvPWzduhXr1q1Dnz59MGbMGKxevVp13vHjx2FkZIRhw4apfqZLly6tsfYffvgBe/bswaJFi/D7778jPz8fw4YNQ05OjuqctWvXYtSoUTA3N8e6deuwYsUKZGVlYcCAAThy5IjqvH379mHUqFEwMzPD+vXr8b///Q9//PEHVq5cWeV1X3nlFUydOhWDBg3C1q1bsXTpUsTHxyMwMFC1CRyV067rdUSkcebPn4+LFy9iyZIlWLJkCfT19dGjRw+MHDkSb7zxhqpJsGvXrjAyMoK5uflDN9lq3749Nm7cqPo8Ozsbn3/+OYYNGya6TD9gwAB07NgRs2fPFl06r7BgwQJ88skn+PLLL/HBBx+ojk+bNg1mZmY4cuSI6h18aGgoFAoF5s+fj7feegtWVlY4evQovL29RQ1nQ4YMqfF7cfr0aRQWFqJbt26i4xXz/NbW1lUeY21tDUEQkJWVVe2Opw9jb28Pa2trHD16VHQ8Oztb9cf/wf6Ciroqvr6HsbCwEP1xLSsrQ0hICLKysrBo0SKEhYUBAHr37g0dHR20atXqoT/T6piZmWHHjh2qDfmcnJzQs2dP7Ny5E+PHj4dSqcT7778Pb29v7Ny5U3UFatiwYWjfvj2mT5+u+ro/+eQT2NvbY8+ePTA0NARQ/rN6cGXcyMhI/Pzzz/j6668xbdo01fG+ffuiU6dO+Oabb+o1tdNc8coBETWIjY2Navvw+fPnY9SoUbh8+TI++ugjeHt7q7Yqr40nnnhC9Pnx48dRWFhYZQlsV1dXDBw4EPv27RMdFwQBr7zyCmbNmoW1a9eKgkFRURH27duH0aNHw9jYGKWlpaqPYcOGoaioSHVpu2fPnoiLi8Prr7+O3bt3Izc3t1b1V+xOamdnV+2/P+qydF0vWevo6GDKlCnYt28fPv/8c6Snp+Pq1at49tlnUVBQoDqnsoq6kpOTa3z+jRs3IigoCKamptDT04O+vj5WrFhRq+mcmgwfPly0U2/FFZWKuzsuXbqElJQUPPfcc6KvwdTUFE888QQiIyNRUFCA/Px8REdHY8yYMapgAJSHj5EjR4pec8eOHZDJZHj22WdFP3sHBwf4+voiIiKiwV9Xc8JwQERq4e/vj+nTp2Pjxo1ISUnBO++8g5s3b9apKfHBd84V73yre0ft5ORU5Z1xcXExNmzYAE9Pzyr7jWRkZKC0tFR1daPyx7BhwwBAFWQ++ugjfPXVV4iMjMTQoUNhY2ODkJAQxMTEPLL+ip1QK/+hAsoDVOWvp7LMzEzIZDJYWlo+8rmrM3PmTLzzzjuqzc06duwIAKr9bpydnUXnV9RV046tmzdvxlNPPQVnZ2esWbMGx48fR3R0NJ5//vk6T39Up+L7UaHyjrpAzT93pVKJrKwsZGVlQalUwsHBocp5Dx5LS0uDIAiwt7ev8vOPjIysU4htCTitQERqp6+vj1mzZuHbb7+tcX67sgffPVf8EUlNTa1ybkpKCmxtbUXH5HI5Dhw4gCFDhmDQoEHYtWsXrKysAABWVlbQ1dXFc889hylTplT7+hVbrevp6WHatGmYNm0asrOzsXfvXnz88ccYMmQIEhMTVTvBPqiinszMTNHx9u3bw8jICGfPnq3ymLNnz6JDhw5VAkVt6Onp4ZtvvsFnn32GGzduwNbWFo6OjhgyZAjc3Nzg4uIiOr+irge/bw9as2YN3NzcsGHDBtHPRKFQ1LnG+qjp566jowMrKysIggCZTIbbt29XOe/BY7a2tpDJZKo1KB5U3bGWjFcOiKhBqhvAAaguPzs5OamOyeXyGt+1VhYQEAAjIyOsWbNGdDwpKQn79+9HSEhIlcd07doVBw8eRFJSEgYMGID09HQAgLGxMYKDg3Hq1Cn4+PjA39+/yseD72gBwNLSEmPHjsWUKVOQmZmp2h68Op07dwaAKo2Aenp6GDlyJDZv3oy8vDzV8YSEBBw4cABjxoyp9fekOqampvD29oajoyNiY2Oxb98+vP3221XOq+jK79KlyyOfTyaTwcDAQBQMbt++XeVuBaDuP9PacHd3h7OzM9auXSu6syI/Px+bNm1S3cFgYmKCnj17YvPmzaIrGnl5efjrr79EzzlixAgIgoDk5ORqf/aP6sFoiXjlgIgaZMiQIXBxccHIkSPh4eEBpVKJ06dP4+uvv4apqanoj5S3tzfWr1+PDRs2oF27djA0NHzkoGxpaYlPP/0UH3/8McLCwvD0008jIyMDc+bMgaGhIWbNmlXt4zp37ozDhw9j0KBB6NevH/bu3QsXFxcsXrwYffr0Qd++ffHaa6+hbdu2yMvLw9WrV/HXX39h//79AICRI0fCy8sL/v7+aNWqFW7duoVFixahTZs2qkv31XFxcUG7du0QGRmJt956S/Rvc+bMQY8ePTBixAh8+OGHKCoqwsyZM2Fra1tlJckBAwbg4MGDNd5yGBERgejoaPj4+EAQBJw4cQILFizAY489hjfeeKPK+ZGRkdDV1UW/fv0e+bwjRozA5s2b8frrr2Ps2LFITEzE559/DkdHxyp3iHh7eyMiIgJ//fUXHB0dYWZmJrqNsz50dHSwcOFCPPPMMxgxYgReeeUVKBQK/O9//0N2djbmz5+vOvfzzz/HY489htDQULz77rsoKyvDggULYGJiIrqCExQUhJdffhmTJ09GTEwM+vXrBxMTE6SmpuLIkSPw9vbGa6+99si6du7cifz8fFXAO3/+PP78808A5c2SD7uipI0YDoioQWbMmIFt27bh22+/RWpqKhQKBRwdHTFo0CB89NFHqnfTQPkfyNTUVLz00kvIy8tDmzZtHvlOHCif/7ezs8N3332HDRs2wMjICAMGDMCXX375yD/U7dq1UwWEvn37Yt++fejSpQtiY2Px+eefY8aMGUhPT4elpSU6duyo6jsAgODgYGzatAm//PILcnNz4eDggNDQUHz66afQ19d/ZL3PPPMMvv/+eygUCtGlag8PD0RERGD69OkYO3Ys9PT0MHDgQHz11Vdo1aqV6Dnu3btX7Tz6gwwMDLBp0ybMnTsXCoUCHTt2xGeffYa33npL1PBXYevWrRg2bFiN/Q2TJ09Geno6fvzxR/z6669o164dPvzwQyQlJYlu+QSAxYsXY8qUKRg/fjwKCgrQv39/tTT3TZgwASYmJpg3bx7GjRsHXV1d9O7dGwcOHEBgYKDqvNDQUGzduhUzZszAuHHj4ODggNdffx2FhYVVav3pp5/Qu3dv/PTTT1i6dCmUSiWcnJwQFBSEnj171ljTa6+9JloSe+PGjaq7a27cuFHlDgltJhNqiqZELZy69mWv657sbdu2rbI2PwC8/vrrVRbtIc2RkpICNzc3rF69GuPGjavz4/Py8mBtbY1FixY9tDeiPq5du4aOHTti9+7dCA0NVdvzUvXUNW4A0owd7Dkg0lDR0dFITU1VfezZswcA8OSTT0pcGT2Kk5MTpk6dii+++AJKpbLOjz906BCcnZ3x0ksvqbWuuXPnIiQkhMGgBVDH2MFpBSIN9eCl5vnz56N9+/bo37+/RBVRbc2YMQPGxsZITk6Gq6trnR47fPhwDB8+XK31lJaWon379vjoo4/U+rykmdQxdjAcEDWxBxfUkcvlNd5GVVxcjDVr1mDatGktan13bWVmZvbQZkkp6OnpYcaMGVKXQQ3UlGMHpxWImpirqyssLCxUH/PmzavxMVu3bkV2dnaVlQKJqOVoyrGDVw6ImlhiYqKoqag2i6+sWLECQ4cOFa0ZQEQtS1OOHQwHRE3M3Ny8Vh3HFW7duoW9e/di8+bNjVgVEWm6phw7OK1ApOFWrlwJOzs7tTepEVHz1pCxg+GASIMplUqsXLkSEydOhJ4eL/QRUe00dOxgOCDSYHv37kVCQgKef/55qUshIi3S0LGDb0WINNjgwYNrXF+fiOhBDR07eOWAiIiIRBgOiIiISIThgIiIiETYc0BUS327pcDMuP5LF+cVsHeAqKVp6LgBSDN28MoBNTsXs25LXQIRaZnU/BxkKQqkLkNjMBxQsxJ+4ThCty7Gz/GHpS6FiLREXnERwvasxON/L8OtvAypy9EIDAfUbOxLvIhPo7ZDgICi0lKpyyEiLVCqLMNrEWtxIes2cosLoSvjn0WA4YCaifiMFLwesRZKQcC4jv54w2eA1CURkYYTBAGfRm5HRPJlGOrqY2XIRLiYWkldlkZgOCCtl5Kfg7C9q5BfWow+jh0wP3B0nfYtJ6KW6adzh/HbpSjIIMMP/cfDr5Wr1CVpDIYD0mr3ShSYtHcV0gpy0cnSDj8FPwN9HV2pyyIiDff3zbOYG/MPAGBWz+EY0sZT4oo0C8MBaa1SZRleO7AW5zNT0crIFOGDJsFCbiR1WUSk4WLvJOCtQxsAABM9AvBClyCJK9I8DAeklQRBwMyov3Ag+ZJqrtDVzFrqsohIwyXkZWLy3nAoykoR4uKBOb1GcBqyGgwHpJV+jj+C1RcjIYMMS/qP41whEdUoW1GAsD0rkVGUDy9rJywd8DT0OA1ZLYYD0jo7b53D59Hlc4Wf9hiGoW28JK6IiDRdcVkpXt6/Bldz7sDB2BwrB02Eib5c6rI0FsMBaZVTdxLx5sENECBgokdvvOTZR+qSiEjDCYKA6cc249jt6zDRM8Dq0ElwNLGQuiyNxnBAWiPx/lxhUVkJBrq4Y06vkZwrJKIafRe3HxuvxkJXpoMfg59BF2snqUvSeAwHpBVyFIUI27MKd4vuwdPaEUsHTOBcIRHVaMu10/jfqT0AgLm9/w/BLu4SV6QdGA5I4xWXleLlA2twJScdDsbmWDVoEkw5V0hENYi6fQPvHtkIAHjFqx+e8+gtcUXag+GANJogCPjo+BYcTb3GuUIiqrXrOXfwwv7fUKwsw7A2XvjE/zGpS9IqDAek0ZacOYANV05CRybD0gETOFdIRDXKLMpH2J5VyFYUwM/WFYv7PQUdbqhUJ/xukcbaev00Fsb+CwCY23sUQlw9JK6IiDRdUWkJnt+3GjfzMuBqaoWVg8JgpGcgdVlap9mGg+LiYhw+fBi//PILBEGQuhyqoxNpNzHt8P25Qs++CONcITWRlJQUrFu3DtHR0VKXQnWkFJSYdmQjYtJvwdzAEKtDJ6OVkZnUZWmlZhsOysrK8McffyA6OhrXrl2Tuhyqg+s5d/H8vtUoVpbhsdae+KTHUKlLohbkzJkziIiIwL59+6Quherof7F7sP3GGejJdPBz8LPoaGkndUlaq9mGAyMjI/To0QMAcPjwYYmrodoqnytcqZorXNJ/HOcKqUkFBARAR0cHN27cQFJSktTlUC2tvxyNJWcOAAD+F/QEgpw6SFyRdmvWo27fvn0BACdPnkR+fr7E1VBNikpL8ML9uUIXU0vOFZIkLCws4OfnB4BvLLTF4ZQr+PDYFgDA274D8WTH7hJXpP2adTho27YtXFxcUFJSgqioKKnLoUdQCkq8e/RPRHOukDRAxRuLyMhIFBcXS1wNPcqlrDS8vH8NSgUlHm/nh/e6hkpdUrPQrMOBTCZT/ZIfPnyYjYka7KvYPdh2PQ56Mh0sD34WnSztpS6JWjAPDw/Y2tqiqKgIMTExUpdDD5FekIewPSuRV6JAL/u2+LrPWC6pribNOhwAQK9evaCvr4+UlBRcv35d6nKoGhuuxOC7+3OFC4LGoA/nCkliOjo66NOnfFMvTi1opsLSYkzeF47k/Gy4mdvil4HPQa6rJ3VZzUazDwdsTNRsR1KuYvrRzQCAt3yCMa6jv8QVEZULDAyEjo4Orl+/juTkZKnLoUrKlEq8cXA94u4mwUpujNWhk2BlaCJ1Wc1Ksw8HwH/zhzExMWxM1CCXs9Pw8oHyucJR7XzxfrfBUpdEpGJhYQFfX18AwKFDhySuhiqbG/MPdiech1xXD7+GhMHN3FbqkpqdFhEO3Nzc2JioYe4Uls8V5hYXoad9W3wdxLnC6iQnJ+PZZ5+FjY0NjI2N4efnh5MnT0pdVovRr18/AEBUVBQbEzXEqgvH8XP8EQDAN32eRA/7ttIWpIHUMW60iHAgk8lE84dsTJRWYWkxJu0NR9K9bLQ1s8EvA5+DoZ6+1GVpnKysLAQFBUFfXx87d+7E+fPn8fXXX8PS0lLq0loMDw8P2NjYoLCwkKFMA+xLvIiZUdsBANO7DcGodr4SV6R51DVutJjujV69emHTpk2qxsT27dtLXVKLVKZU4s2DGyrNFU6GNecKq7VgwQK4urpi5cqVqmNt27aVrqAWqKIxcdu2bTh8+DACAgKkLqnFOpeRjNci1kIpCBjf0R9v+AyQuiSNpK5xo0VcOQAAY2Nj+PuXN7uxMVE6X8bsxK6EeBjo6GJFSBjaWbS8ucLc3FzRh0KhqPa87du3w9/fH08++STs7OzQtWtX/Pzzz01cLQUFBUFHRwfXrl1jY6JEUvJzMHFvOApKi9HHsQPmBY5ukdOQtRk71DVutJhwAIgbEwsKCiSupuVZfTESP8WXB7Nv+j6Jni10rtDV1RUWFhaqj3nz5lV73vXr17Fs2TJ07NgRu3fvxquvvoq33noLq1evbuKKWzYLCwv4+PgAAI4cOSJxNS3PvRIFJu1dhbSCXHSytMNPwc9AX0dX6rIkUZuxQ13jRouZVgCAdu3awcnJCSkpKYiKikJwcLDUJbUY+xIvYkbkNgDAB90G4/F2ftIWJKHExESYm5urPpfL5dWep1Qq4e/vjy+//BIA0LVrV8THx2PZsmUICwtrklqpXL9+/XD69GlERkZi9OjRMDDgst5NoVRZhlcP/I7zmaloZWSK1aGTYSE3krosydRm7FDXuNGirhzIZDJV9zEbE5vO+cwUvH5/rnBcx+5406dlhzJzc3PRx8PCgaOjI7p06SI61rlzZyQkJDRFmVRJ586dYWNjg4KCAjYmNhFBEPBp5HZEJF+Goa4+VoZMhIupldRlSao2Y4e6xo0WFQ6A/1ZMTE5Oxo0bN6Qup9lLyc9B2J5VyC8tRpBje8wLaJlzhfURFBSES5cuiY5dvnwZbdq0kaiilosrJja95fGH8dulKMggw/f9x8OvlavUJWkFdY0bLS4csDGx6dwrUWDy3lW4fX+ucHnwszDg8qa19s477yAyMhJffvklrl69irVr12L58uWYMmWK1KW1SBUrJl67dg0pKSlSl9Os/X3zLOZG7wQAzOw5DI+18ZS4Iu2hrnGjxYUD4L/GxOjoaBQWFkpcTfNUqizD6xFrEZ+ZCltDU4QPmtSi5wrro0ePHtiyZQvWrVsHLy8vfP7551i0aBGeeeYZqUtrkSwtLVWNiXxj0Xhi7yTgrUMbIEDARI8AvNilj9QlaRV1jRst8m1c5cbEyMhINiaqmSAImBX1F/YnXSqfKxw0Ea5m1lKXpZVGjBiBESNGSF0G3de3b182JjaihLxMPL93NRRlpRjo4o45vUZwGrIe1DFutMgrB9zKuXH9cv4Iwi9GQgYZlvQfh66cK6RmokuXLqrGxNjYWKnLaVayFQWYuGcV7hbdg6e1I5YNmAC9FnrLoiZokeEAEDcm3rx5U+pymo2dt87hsxP/AABm9BiKoW28JK6ISH10dHQQFBQEgFML6lRcVopXDvyOKznpcDA2x6pBk2CiX/1dPNQ0Wmw4MDExQffu3QHwl1xdTt1JxJsHy+cKwzx642XPvlKXRKR2FY2JV69eZWOiGgiCgA+PbcHR1Gsw0TPA6tBJcDSxkLqsFq/FhgOAjYnqlJiXicl7w1FUVoJgZ3d81msk5wqpWbKysoK3tzcArpioDt/F7ccfV09CV6aDZcHPoIu1k9QlEVp4OGjfvj0cHR1RXFyMEydOSF2O1spRFGLi3vK5wi7WjlgWzLlCat4q3lgcP34cJSUlElejvbZcO43/ndoDAJjb+/8w0MVd4oqoQosOB5UbEw8dOsTGxHqomCu8nJ0O+/tzhaacK6RmztPTE9bW1lwxsQGibt/Au0c2AgBe8eqH5zx6S1wRVdaiwwEA9O7dG/r6+khKSmJjYh0JgoCPjm/FkdSrMNYzwOpBk+DEuUJqAbhiYsNcz7mDF/b/hmJlGYa28cQn/o9JXRI9oMWHAzYm1t/3ZyKw4UoMdGQyLBswAZ42nCukliMwMBAymQxXr15Famqq1OVojcyifITtWYVsRQH8bF3xXb9x0JG1+D9FGoc/EbAxsT62Xj+NBbG7AQCf9/o/hLh6SFwRUdOysrLiiol1VFRaghf2rcbNvAy4mlph5aAwGOlxISlN1CJXSHxQRWNiamoqTpw4gf79+0tdkkY7kXYT0w6XzxW+7NkHEzsHSFxR05hX4gyDkvrn6eISJYAk9RVEkuvbty/i4uJUKybq6+tLXZLGUgpKvHvkT0Sn34K5gSHCQyehlZGZ1GU1uoaOG4A0YwevHKC8MbHy/CEbEx/uRu5dvLBvNYqVZXistSc+8R8mdUlEkvH09ISVlRXy8/O5YmIN/he7B9tuxEFPpoOfg59FJ0t7qUuiR2A4uC8gIAB6enpITEzErVu3pC5HI2XdnyvMUhTA19YFS/qPg64O/xeilouNibWz/nI0lpw5AABYGDQGQU4dJK6IasKR/T42Jj6aoqwUL+z/DTdy78LF1BIrQyZyrpAIQFBQEGQyGa5cuYLbt29LXY7GOZxyBR8e2wIAeNt3IJ7q6C9xRVQbDAeVsDGxeoIg4N0jf+JE2s3yucJBk2Fn3PznColqo/KKiXxjIXYpKw0v71+DUkGJx9v54b2uoVKXRLXEcFBJhw4d4ODgAIVCgejoaKnL0RhfndqDrddPQ0+mg+XBz8LdinOFRJVxxcSq0gvyMHHvSuSVKNDTvi2+7jOWS6prEYaDSh7cypmAP67EYHHcfgDA/MDR6MO5QqIqvLy8VI2Jp06dkrocyRWWFmPyvnAk3cuGm7ktVgx8DnJd3hynTRgOHtC7d2/o6ekhISGhxa+YeDTlKj44uhkA8KZPMMZ36iFxRUSaiVs5/6dMqcQbB9cj7m4SrOTGWB06CVaGJlKXRXXEcPAAU1NTdOvWDUDL/iW/nJ2Glw6UzxWOcvPF+904V0j0KBWNiZcvX27RjYlfxPyD3QnnYaCji19DwuBmbit1SVQPDAfVqNyYWFRUJHE1Te9OYR4m7lmF3OIi9LBrg6/7jOXypkQ1sLa2hpeXF4CWu5Vz+IXjWB5f/rV/2/cp9LBvK21BVG8c8avRsWNH2NvbQ6FQtLitnAtLizF572ok3stCWzMbrAgJg6EeV30jqo2KNxbHjh1rcY2J+xIv4tOo7QCA6d2GYFQ7X4krooZgOKhGS21MVApKvHVoA07fTYSl3BirQyfDmnOFRLVWuTHx9OnTUpfTZOIzUvBaxFooBQHjOvrjDZ8BUpdEDcRw8BAVKyYmJCS0mBUTv4jZhZ234mGgo4sVA59DOwvOFRLVha6ubotrTEzJz0HY3lUoKC1GH8cOmB84mrcsNgMMBw9hamqKrl27AmgZv+S/XYzET+cOAQC+7vMkejm4SVwRkXaqaEy8dOkS0tLSpC6nUd0rUWDS3lVIK8hFJ0s7/BT8DPR1dKUui9SA4eAR+vXrBwA4ceJEs25M3J90CZ9EbgMAvN81FKPb+0lbEJEWq9yY2JzfWJQqy/DagbU4n5mKVkamCB80CRZyI6nLIjVhOHiEyo2JzXXFxPOZKXjtwO9QCgKe6tAdb/kOlLokIq3X3FdMFAQBM6P+woHkSzDU1cfKkIlwNbOWuixSI4aDR2jujYmp+TkI27MK+aXFCHJsz7lCIjXx8vKCpaUl7t271ywbE5fHH8bqi5GQQYbv+4+HXytXqUsiNWM4qEFFY+KtW7eQkJAgdTlqUzFXeLsgFx0t7LA8+FkYcHlTIrVozo2J/9w8h7nROwEAM3sOw2NtPCWuiBoDw0ENmmNjYqmyDK9HrEV8ZipsDU0RHsq5QiJ169OnT7NrTDx1JxFvHdoAAQImevTGi136SF0SNRKGg1qomFqIiorS+sZEQRAwK2oH9iddglxXD78OCkNrzhUSqZ21tTU8PcvfVTeHFRMT8jIxeW84ispKMNDFHXN6jeQ0ZDPGcFALnTp1gp2dHRQKBWJiYqQup0F+OX8E4RePQwYZlvQbj26tWktdElGz1VxWTMxRFGLinlW4W3QPntaOWDZgAvR4y2KzxnBQC82lMXHXrXh8duIfAMCMHkMxrK2XxBXRo8yePRsymUz04eDgIHVZVAfe3t6qxsS4uDipy6mX4rJSvHxgDa7kpMPB2ByrBk2Cib5c6rLoIdQ1bjAc1FJAQAB0dXVx8+ZNrWxMPH0nEW8cXA8BAp5z74WXPftKXRLVgqenJ1JTU1UfZ8+elbokqgNtb0wUBAEfHtuCo6nXYKJngNWhk+BoYiF1WVQDdYwbDAe1ZGZmpmpM1Lb5w8S8TEzeVz5XGOzsjs97/x/nCrWEnp4eHBwcVB+tWrWSuiSqo4oVEy9evIj09HSpy6mTJWcO4I+rJ6Ejk2FZ8DPoYu0kdUlUC+oYNxgO6kAbGxNzFIWYuHcV7hTeQ2crBywL5lyh1HJzc0UfCoXioedeuXIFTk5OcHNzw/jx43H9+vUmrJTUwcbGRtWYqE1XD7ZeP42Fsf8CAOb2HoWBLu4SV0S1HTvUMW4wHNSBu7s77OzsUFRUpBWNiSXKMrwa8TsuZ6fD3tgc4aGTYcq5Qsm5urrCwsJC9TFv3rxqz+vVqxdWr16N3bt34+eff8bt27cRGBiIjIyMJq6YGqryiomlpaUSV1OzqNs3MO3wRgDAK559EebRW+KKCKjd2KGucYOr3tSBTCZDnz59sHnzZhw+fBh9+mjuPb4Vc4WHU67CWM8A4YMmwolzhRohMTER5ubmqs/l8uoD29ChQ1X/7e3tjYCAALRv3x7h4eGYNm1ao9dJ6uPt7Q0LCwvk5OQgLi4O3bt3l7qkh7qecxcv7P8NxcoyDG3jiU96DK35QdQkajN2qGvc4JWDOqrcmJiYmCh1OQ/1w9kIbLgSUz5XOGACvGycpS6J7jM3Nxd9PCwcPMjExATe3t64cuVKI1dI6qYtjYmZRfkI27MS2YoC+Nm64rt+46Aj458JTVGfsaO+4wZ/6nVkbm4OPz8/AJr7S77tehzmn9wNAPis1/8hxNVD4opIHRQKBS5cuABHR0epS6F6qGhMvHDhAu7cuSN1OVUUlZbghX2rcTMvA66mVlg5KAxGegZSl0UNVN9xg+GgHio3Jj6qmUwK0Wk3Me1I+VzhS559MKlzgMQVUX299957OHjwIG7cuIGoqCiMHTsWubm5mDhxotSlUT3Y2tqiS5cuADTvjYVSUOLdI38iOv0WzA0MER46Ca2MzKQui+pBXeMGw0E9aGpj4o3cu3h+32ooykoxpHUXzPAfJnVJ1ABJSUl4+umn4e7ujjFjxsDAwACRkZFo06aN1KVRPVVeMVGTGhO/it2DbTfioCfTwfLgZ9HJ0l7qkqie1DVusCGxHnR0dESNiRVziVLKKspH2J5VyFIUwNfWBUv6jYeuDrOfNlu/fr3UJZCa+fj4wNzcHLm5uRrTmLj+cjS+O3MAALAwaAz6OHWQuCJqCHWNG/zrUU8VjYk3btyQvDFRUVaKF/f/hhu5d+FiaomVIRNhrM+5QiJNo2mNiUdSruLDY1sAAG/7DsRTHf0lrog0BcNBPVVuTJRyxURBEPDukT8RlXYTZvpyhA+aDDtjzhUSaaqKrZylbky8nJ2Glw+sQamgxKh2vniva6hktZDmYThogIr5w8jISBQXF0tSw1en9mDr9dPlc4UDn4W7FecKiTSZra0tOnfuDEC6NxbpBXkI27MSucVF6GnfFt/0eZJLqpMIw0EDuLu7w9bWFkVFRYiOjm7y1//jSgwWx+0HAMwPHI2+Th2bvAYiqrvKjYllZWVN+tqFpcWYvC8cSfey4WZuixUDn4Ncl+1nJMZw0AA6OjqSbeV8NOUqPji6GQDwpk8wxnfq0aSvT0T15+vrK2pMbCplSiXePLgBcXeTYCU3RvigSbAyNGmy1yftwXDQQIGBgdDR0cGNGzeQlJTUJK95JTsdL92fK/w/Nx+8341zhUTaRKrGxC9i/sGuhHgY6OhiRUgY2lnYNtlrk3ZhOGigpl4x8U7hf3OFPeza4Js+T3J5UyItVLE3y/nz53H37t1Gf73wC8exPL68x+Gbvk+ip33bRn9N0l78q6IGlVdMbMzGxMLSEjy/bzUS72WhjZkNVoSEwVBPv9Fej4gaT+UVExu7MXFf4kV8GrUdAPBBt8F4vJ1fo74eaT+GAzXw8PCAra0tCgsLG23FRKWgxNuHNuDUnURYyo3xW+gkWHOukEirVbyxOHr0aKM1JsZnpOD1iLVQCgLGdfTHmz7BjfI61LwwHKhBUzQmfhmzC//cOlc+VzjwObSzaNUor0NETaexGxNT8nMQtncV8kuL0cexA+YHjuYti1QrDAdqEhAQAB0dHVy/fh3Jyclqfe41F6Pw47lDAICv+zyJXg5uan1+IpKGrq4uAgMDAaj/jcW9EgUm7V2FtIJcdLK0w0/Bz0BfR1etr0HNF8OBmlhYWDRKY+KBpEv4JHIbAOC9rqEY3d5Pbc9NRNKraEy8cOGC2hoTS5VleO3AWpzPTEUrI1OED5oEC7mRWp6bWgaGAzVSd2Pi+cwUvHrgd5QJSjzZoRve9h3Y4OckIs3SqlUrdO7cGYIgqKUxURAEzIz6CweSL8FQVx+/hkyEq5m1GiqlloThQI08PDxgY2ODgoICnDx5skHPdbsgFxP3hCO/tBiBDu2wIHAM5wqJmil1rpj4c/wRrL4YCRlkWNJ/HLq2clVHidTCcM1MNarYynnbtm04fPgwAgIC6vU8+SUKTNqzCqkFOehg0QrLBz4LAy5vKrmPF74MM13Dej8+r6wIqzBTjRVRc+Hr6wszMzPk5OTgzJkz6Nq1a72eZ+etc/g8+h8AwKc9hmFoGy91lkn10NBxA5Bm7OCVAzULCgqCjo4Orl27Vq/GxDKlEq9HrMO5zBTYGJpgdehkWMqNG6FSItIUenp6DW5MPHUnEW8e3AABAiZ69MZLnn3UWSK1MAwHamZhYQFfX18AdV/YRBAEzDrxF/YlXYRcVw8rB01Ea84VErUIFVML9VkxMTEvE5P3hqOorAQDXdwxp9dITkNSgzAcNIL6buW84vxRrLpwHDLI8F2/cejWqnVjlUhEGqZyY+LRo0dr/bgcRSHC9qzC3aJ78LR2xNIBE6DHWxapgRgOGkHnzp1VjYmxsbG1eszuW/GYc+JvAMAn/kMxvK13Y5ZIRBqorismFpeV4uUDa3AlJx0OxuZYNWgSTPXljV0mtQAMB42gojERAA4dOlTj+XF3k/DGofUQIOBZ9154xatvY5dIRBqocmPi2bNnH3muIAj46PgWHE29BhM9A4QPmgRHE4smqpSaO4aDRlKxlfO1a9eQkpLy0POS7mVh0t5VKCwtwQDnTpjb+/84V0jUQunp6anucqqpMXHJmQPYcOUkdGQyLB0wAZ42Tk1RIrUQDAeNxNLSEj4+PgAe/kueW1yEiXtW4U7hPXS2csAyzhUStXgVUwvx8fHIyMio9pyt109jYey/AIC5vUchxNWjyeqjloHhoBE9qjGxRFmGVw6swaXsNNgbmyN80CSYGTTsXlgi0n52dnbw8PB4aGPiibSbmHZ4IwDgZc8+CPPo3dQlUgvAcNCIunTpUm1joiAI+OjYFhxOuQpjPQOED5oIJ1NL6QolIo3ysMbE6zl38fy+1ShWluGx1p6Y0WOYVCVSM8dw0Ih0dHQQFBQEQDy18MPZg1h/Jeb+XOHT8LJxlqpEItJAfn5+MDMzQ3Z2Ns6dOwcAyCrKR9ielchWFMDX1gVL+o+DjoxDODUO/p/VyCpWTLx69SpSUlKw/Xoc5p/cBQCY03MkBrl2lrhCItI0lRsTDx06hKLSEryw/zfczMuAi6klVg2aCCM9A4mrpOaM4aCRVW5M3PTvP3jnSPlc4YtdgjC5S6CUpRGRBqu4HTo+Ph7T/l2DE2k3YW5giNWhk9HKyEzi6qi5YzhoAhXzh3EnomF6LwtDWnfBpz2GS1wVEWkye3t7uLu7QxAEXIg5DT2ZDpYHP4tOlvZSl0YtALf6a0T37ikQdyoFJ6MzoSMzg6E8Gz/HrINtYgTuJp+AcedgGHceAF1TG6lLJSIN1LlHV1xOS0KRkQwLgsagj1MHqUuiFoLhQM1KissQH5+GUzFJuHTxDpRKAQBgbNgPp51uIqt4ByxTLyIn9SJy9i8DZDLIXX1h1HkAjDsHw8i9H3SNzCX+KohIEyRZ6WGHuz56ObTDuI7+UpdDLQinFdRAqRRw9cpd/LEuDp/N3IO1q2Nx4Xw6lEoBLq4W8AlxwLYu0bjrkoOQBefh9OYmWA56AwbOnoAgQJFwGtm7FyFl0Shcm2KLhM8CUHCpftu2UvM1b948yGQyTJ06VepSqIkcv30dkMm4yBHVW33HDV45aIDUlFycOpmMUyeTkZNTpDpuZWWErv7O6NrdGfb2Zvjm1F4U3SnBYMfO0DO1hmn3x2Ha/XEAQGlOGgouHEDhxQgUXDiAkrSrKLp+AjqGphJ9VaSJoqOjsXz5clVzKzV/pcqy8nAAIMixvcTVkDZqyLjBcFBHOdmFOH0qBbExyUhNyVUdNzLSh4+fI7p1d0YbN2vo6Py3P8Kx29cAAIEOVX/B9SzsYd57PMx7jwcAlGQkoPBiBOSuvo38lZC2uHfvHp555hn8/PPPmDt3rtTlUBM5l5GCvBIFzA0M4WXNfROobho6bjAc1EJRUSnOnUnFqZPJuHrlLoTyNgLo6srQuYs9uvo7w6OzHfT1q+6LUFhajNj0BABAYC3Sv75Na+gHham1ftIsubm5os/lcjnk8odvsztlyhQMHz4cgwYNYjhoQY7dv2rQ294NujqcAaa6jR0NHTcYDh6irEyJy5fu4NTJZMSfvY2SEqXq39q6WaGbvwt8fB1hbPLohUhi0m+hWFkGR2MLuJnzrgQCXF1dRZ/PmjULs2fPrvbc9evXIzY2FtHR0U1QGWmSo6n3rzhySoHuq+3YoY5xg+GgEkEQkJSYg9iYJMSdSsG9e/9tlmTbygTd/V3g180JNrYmtX7OY6nl6T/QsR23YiYAQGJiIszN/7sj5WHJPzExEW+//Tb+/fdfGBpyU66WpLisFNFpNwEwHNB/ajN2qGvcYDgAkJlRgFMnkxF7Mgl30vNVx01MDeDX1Qnd/F3g4mpRrz/uFemfDUVUwdzcXPQL/jAnT55Eeno6unfvrjpWVlaGQ4cO4fvvv4dCoYCuLrf4bo7i7iahoLQY1nITeFhx0SMqV5uxQ13jRosNBwUFxThzOhWxMcm4eSNTdVxPXweeXg7o5u+MTu6toKtb/7m+eyUKxN1NAsD0T3UXEhKCs2fPio5NnjwZHh4emD59OoNBM1bxpiLAsR03V6I6Ude40aLCQWlpGS6cT8epmGRcOJ+OsrLyPgKZDGjfwRbd/J3h5eMAQ0N9tbxe1O0bKBOUaGNmDRdTK7U8J7UcZmZm8PLyEh0zMTGBjY1NlePUvBzjFUeqJ3WNG80+HCiVAm7dzEJsTBLOnE5FYWGJ6t8cnczQtbsLunZzgoWlkdpf+xgbioiojopKS3DyTvkdTgwHJJVmGw7S0+4h9mQSTp1MRlZmoeq4uYUcXbs5o5u/CxydGneZ4opbkapb34CoPiIiIqQugRrZyTsJUJSVwt7IDO3MbaUuh5qB+owbzSoc3MtT3F+gKAlJiTmq4wZyXfj4OqJrdxe072AjWqCosWQpCnAuIwVA+Z0KRES1UfmKI+9wIqlofTgoLi5D/LnbiI1JwpVLd1UbHenoyNDJoxW6dXdGFy8HGBg0bfNW5O3rECCgg0Ur2BtzIyUiqh2ub0CaQCvDgVIp4NqVu4iNScbZs6koVpSp/s21tSW6dXeGb1cnmJo9fNW5xlaxvgHnDImotvJLFDh9JxEAxw6SllaFg5TkXMSeTMLp2GTk5ihUx62tjVUbHdnZacaGRWxGJKK6OpF2E6WCEq6mVmhtZi11OdSCaXw4yM4uxOmTyYg9mYzbqXmq40bG+vD1c7q/0ZGVRs3N3SnMw6XsNABAgAP7DYiodv6bUuC4QdLSyHBQVFSCs3HlfQTXr2VU2uhIB1087dDV3wUenVtBT08zF4E5fn9KoYu1I6wNa7/UMhG1bBVbNAc6dpC4EmrpNCYclJUpceni/Y2Ozt1GaaWNjtzaW6Nbd2d4+zrC2PjRGx1pAi6ZTER1laMoxNmMZABAIK84ksQkDQeCICAxIRuxMcmIO5WC/Pz/NjqyszNFN39n+HV3hrW1sYRV1t1/6xvwF5yIaicq7QaUgoB25rZwNLGQuhxq4SQJBxl38xF7MhmnTibj7p3/NjoyNTWAXzdndPN3hrNL/TY6klpKfg5u5N6FjkyGXgwHRFRLvOJImqTJwkF+fjHOnE5BbEwybt3MUh3XN9CFl7cDunV3RodOtg3a6EgTVNyl4G3jDHMDbrNLRLXD9Q1IkzRqOCgpKcOF+DScOpmMixfSUVZW3lkokwEdOtqim78LPL0dYGioMa0PDcYNU4iorjKK7uFi1m0AvMOJNIPa/yorlQJuXM/EqZPlGx0VFZWq/s3J2Rzd/F3g29UJFhbN7121IAi8NEhEdVZxh5OHlQNsjTRjrRZq2dQWDtJu56n6CLKz/tvoyNLSEF27ly9Q5ODYvJcRTriXieT8bOjr6KKHXVupyyEiLcEmZtI0agkHxcVl+O7bIygpLl/G2NBQD96+jujm7wy3dk2z0ZEmqLhq0LWVK4z1Nf+WSyLSDLziSJpGLeHAwKB818OCghJ093dG5y720G/ijY40QcV+CpwzJKLaul2Qi2s5dyCDDL0c3KQuhwiAGqcVnnraVytvPVQXQRDYjEhEdfbfHU5OsJRr15ou1Hyp7b7BlhwMAOBqzh2kF+ZBrquHbq1aS10OEWkJ3sJImki7FxXQIBXp39+uDQz19CWuhoi0BXdwJU3EcKAmbCgiorpKyMtE4r0s6Ml00NO+rdTlEKk0n9WHJKQUlP/tpubAcNBcfR/iDnkD5oQVigLgshoLIq1XcdXA19YFpvpyiauhxtDQcQOQZuzglQM1uJh1G1mKAhjrGcC3lYvU5RCRlqhY34BXHEnTMByoQcWUQi97N+jrtLxbOImo7riiKmkyhgM1qFjfINCR6xsQUe1cz72LtIJcGOjooptdG6nLIRJhOGigUmUZInlpkIjqqKLfoLtdGxjxDifSMAwHDXQuIwV5JQpYGBjC09pJ6nKISEtwSoE0GcNBA1X8gvd2aAddHX47iahmSkFZaTqS4YA0D/+aNRAXMCGiurqUlY5MRT6M9PThZ8s7nEjzMBw0QHFZKU6k3wTA9Q2IqPaOpl4FAPS0awsDXS43Q5qH4aABTt9NQmFpCWwMTeBuZSd1OUSkJVSLpvGKI2kohoMGUE0pOLSHjozfSiKqWZnyvxVV2YxImop/0Rrgv93UuL4Bqd+yZcvg4+MDc3NzmJubIyAgADt37pS6LGqgc5kpyC0ugpm+HF42vMOJ1Etd4wbDQT0VlpbgZPotAEz/1DhcXFwwf/58xMTEICYmBgMHDsSoUaMQHx8vdWnUAMcq3eGkxxVVSc3UNW6wE6aeYtNvoVhZBntjc7iZ20pdDjVDI0eOFH3+xRdfYNmyZYiMjISnp6dEVVFD8YojNSZ1jRsMB/VUeQETmUwmcTWkTXJzc0Wfy+VyyOWP3pGvrKwMGzduRH5+PgICAhqzPGpEJcoynEi7CYBXHKnu6jp2NGTc4LRCPXE3NaovV1dXWFhYqD7mzZv30HPPnj0LU1NTyOVyvPrqq9iyZQu6dOnShNWSOsXdSUJBaTGs5MbwsHKQuhzSMrUdO9QxbvDKQT3cK1Hg9J1EAECgAy8NUt0kJibC3Nxc9fmjkr+7uztOnz6N7OxsbNq0CRMnTsTBgwcZELRUxfoGAQ7teIcT1Vltxw51jBsMB/VwIu0mSgUlWptaw9XMWupySMtUdBHXhoGBATp06AAA8Pf3R3R0NBYvXoyffvqpMUukRsIrjtQQtR071DFuMLrWwzE2FJFEBEGAQqGQugyqh6LSEsTwDieSQH3GDV45qAfup0BN4eOPP8bQoUPh6uqKvLw8rF+/HhEREdi1a5fUpVE9nLyTAEVZKeyMzNDeopXU5VAzpa5xg+GgjrIVBTiXmQKA4YAaV1paGp577jmkpqbCwsICPj4+2LVrF0JDQ6Uujeqh8psK3uFEjUVd4wbDQR1F3b4BpSCgvUUrOBjXbt6YqD5WrFghdQmkRpyOpKagrnGDPQd1VHl9AyKi2igoKcap+3c4cewgbcBwUEfHuJsaEdXRifTyO5xcTC3R2pR3OJHmYziog4yie7iYdRsA1zcgoto7mvLfDq7sNyBtwHBQB8dTy68adLZygLWhicTVEJG2OHabdziRdmE4qIOjvIWRiOoot7gIZzOSAXDsIO3BcFAHbEYkorqKun0dSkGAm7ktnEwspC6HqFYYDmopNT8H13PvQkcmQy97N6nLISItwTcVpI0YDmqp4i4FbxtnWMiNJK6GiLSFajqSTcykRRgOaunY/d3UAh2Y/omodjKL8nHh/h1OAVz8iLQIw0EtHbt/p0KQE8MBEdVOxRVHd0t7tDIyk7gaotpjOKiFhLxMJN7Lgp5MBz3s2khdDhFpCW7SRtqK4aAWKn7Bu7ZyhYm+XOJqiEhbHGMzImkphoNa4PoGRFRXtwtycTXnDmSQobcD73Ai7cJwUANBEHhpkIjqrGJFVS8bJ1jKjSWuhqhuGA5qcD33LtIK8yDX1UP3Vq2lLoeItMTRijuc+KaCtBDDQQ0qphS6t2oNQz19iashIm1RcYcT1zcgbcRwUAM2FBFRXSXmZSLhXiZ0ZTroxX4D0kIMB4+gFJT/pX+GAyKqpYr1DXxtXWDKO5xICzEcPMLFrDRkKvJhrGcAX1sXqcshIi3BK46k7RgOHqHiF7ynfVsY6OpJXA0RaQNBELjZEmk9hoNH4C2MRFRXN3Lv4nZBLgx0dNGdK6qSlmI4eAhBEBB7JxEA0z8R1V7snQQAQDe71jDiHU6kpXit/CFkMhmOP/kBYtJvwcvaSepyiEhLjO3QHT3t3ZBbXCh1KUT1xnDwCEZ6Bujr1FHqMohIy7Q2s5a6BKIGYTggqqWJ2eNhaiCr9+PvFQv4To31EJHma+i4AUgzdrDngIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiDTUvHnz0KNHD5iZmcHOzg6PP/44Ll26JHVZRKTB1DVuMBwQaaiDBw9iypQpiIyMxJ49e1BaWorBgwcjPz9f6tKISEOpa9zgOgdEGmrXrl2iz1euXAk7OzucPHkS/fr1k6gqItJk6ho3GA6Imlhubq7oc7lcDrlcXuPjcnJyAADW1lx9j6glqs/YUd9xg9MKRE3M1dUVFhYWqo958+bV+BhBEDBt2jT06dMHXl5eTVAlEWmauo4dDRk3eOWAqIklJibC3Nxc9Xltrhq88cYbOHPmDI4cOdKYpRGRBqvr2NGQcYPhgKiJmZubi37Ba/Lmm29i+/btOHToEFxcXBqxMiLSZHUZOxo6bjAcEGkoQRDw5ptvYsuWLYiIiICbm5vUJRGRhlPXuMFwQKShpkyZgrVr12Lbtm0wMzPD7du3AQAWFhYwMjKSuDoi0kTqGjfYkEikoZYtW4acnBwMGDAAjo6Oqo8NGzZIXRoRaSh1jRu8ckCkoQRBkLoEItIy6ho3eOWAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhE9KQugEhbjOjzNnSM5PV+vLJQAaxbpL6CiEjjNXTcAKQZO3jlgIiIiEQYDog01KFDhzBy5Eg4OTlBJpNh69atUpdERFpAHWMHwwGRhsrPz4evry++//57qUshIi2ijrGDPQdETSw3N1f0uVwuh1xedU5y6NChGDp0aFOVRUQarinHDl45IGpirq6usLCwUH3MmzdP6pKISAs05djBKwdETSwxMRHm5uaqz6tL/kRED2rKsYPhgKiJmZubi37BiYhqoynHDk4rEBERkQjDAREREYlwWoFIQ927dw9Xr15VfX7jxg2cPn0a1tbWaN26tYSVEZEmU8fYwXBApKFiYmIQHBys+nzatGkAgIkTJ2LVqlUSVUVEmk4dYwfDAZGGGjBgAARBkLoMItIy6hg72HNAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBAREREIgwHREREJMJwQERERCIMB0RERCTCcEBEREQiDAdEREQkwnBApOGWLl0KNzc3GBoaonv37jh8+LDUJRGRhmvouMFwQKTBNmzYgKlTp+KTTz7BqVOn0LdvXwwdOhQJCQlSl0ZEGkod4wbDAZEG++abb/DCCy/gxRdfROfOnbFo0SK4urpi2bJlUpdGRBpKHeOGXiPWR9SsCIUKKBv4eADIzc0VHZfL5ZDL5VXOLy4uxsmTJ/Hhhx+Kjg8ePBjHjh1rQCVE1FQaOm5UPAdQu7FDXeMGwwFRDQwMDODg4IDb7zX83bqpqSlcXV1Fx2bNmoXZs2dXOffu3bsoKyuDvb296Li9vT1u377d4FqIqPGoc9wAaj92qGvcYDggqoGhoSFu3LiB4uLiBj+XIAiQyWSiY9VdNajswfOrew4i0izqHDeAuo8dDR03GA6IasHQ0BCGhoZN+pq2trbQ1dWtkvbT09OrvCsgIs2jzeMGGxKJNJSBgQG6d++OPXv2iI7v2bMHgYGBElVFRJpMXeMGrxwQabBp06bhueeeg7+/PwICArB8+XIkJCTg1Vdflbo0ItJQ6hg3GA6INNi4ceOQkZGBzz77DKmpqfDy8sI///yDNm3aSF0aEWkodYwbMkEQhEaskYiIiLQMew6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEiE4YCIiIhEGA6IiIhIhOGAiIiIRBgOiIiISIThgIiIiEQYDoiIiEjk/wGQVouY9JoyWwAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [np.float64(36.134980718680936)]\n", - "(0, 9) added\n", - "Checking edge: (0, 2)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [np.float64(63.647466378271766)]\n", - "(0, 2) already in graph, angles = [np.float64(62.302182356951434)]\n", - "(0, 2) already in graph, angles updated = [np.float64(62.302182356951434), np.float64(63.647466378271766)]\n", - "Checking edge: (0, 3)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [np.float64(29.396028363390087)]\n", - "(0, 3) added\n", - "Checking edge: (9, 2)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 2\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 1])\n", - "angles: [np.float64(53.8322224050728)]\n", - "(9, 2) added\n", - "Checking edge: (9, 3)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 2\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 1])\n", - "angles: [np.float64(88.08366041995446)]\n", - "(9, 3) added\n", - "Checking edge: (2, 3)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 2\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 1])\n", - "angles: [np.float64(34.25143801488164)]\n", - "(2, 3) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 2\n", - "Adjacent strokes (list): [1, 1, 8]\n", - "Adjacent strokes (uniques): {8, 1}\n", - "Checking edge: (8, 1)\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgcAAAGTCAYAAAC8vrHzAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAAUxpJREFUeJzt3Xd0FHXbxvHvpm16SAIh9N4TepEWQHp7EARBLKAioCggoKiPCj4WmoUiXUSUItJVpAjSm3QISO9VWhJIgyTz/oHkdaUFsmR2k+tzzp5jJrMzdxbnzpXflJ/FMAwDERERkb+5mF2AiIiIOBaFAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwIOKgkpKSeO+99yhUqBBeXl4ULlyY//3vf6SkpJhdmog4KHv1DbdHVJ+IpNOQIUMYN24cU6ZMoUyZMmzZsoUXXniBgIAAevXqZXZ5IuKA7NU3FA5EHNSGDRto1aoVzZs3B6BgwYLMmDGDLVu2mFyZiDgqe/UNhQORNEhISOD69evp3o5hGFgsFptlVqsVq9V627q1atVi3LhxHDhwgOLFi7Nz507Wrl3L8OHD012HiDx69uobkPbeYa++oXAgch8JCQkEBQURHx+f7m35+vpy7do1m2UDBgxg4MCBt63bv39/oqOjKVmyJK6uriQnJ/PJJ5/w9NNPp7sOEXm07Nk3IO29w159Q+FA5D6uX79OfHw8HTt2xMPDI13bmT59OidPnsTf3z91+Z1GDQBmzpzJ1KlTmT59OmXKlGHHjh307t2b3Llz06lTp4euQ0QePXv1jVvbSmvvsFffUDgQSSMPD490H+QA/v7+Ngf43bz55pu8/fbbdOjQAYDw8HCOHz/OoEGDFA5EnIS9+gakrXfYq2/oVkYRBxUXF4eLi+0h6urqqlsZReSu7NU3NHIg4qBatmzJJ598Qv78+SlTpgzbt2/niy++4MUXXzS7NBFxUPbqGwoHIg5q1KhRvP/++7z66qv89ddf5M6dm27duvHBBx+YXZqIOCh79Q2FAxEH5efnx/Dhw3Xrooikmb36hq45EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIab2QWIOItaAb/hbX34PB2XmMK39itHRJxAevsGmNM7NHIgIiIiNhQORERExIbCgYiDKliwIBaL5bZXjx49zC5NRByYPXqHrjkQcVCbN28mOTk59evIyEgaNmxIu3btTKxKRBydPXqHwoGIg8qRI4fN14MHD6ZIkSLUqVPHpIpExBnYo3coHIhksJiYGJuvrVYrVqv1nu+5fv06U6dOpU+fPlgslkdZnog4qIzsHbrmQCSD5cuXj4CAgNTXoEGD7vue+fPnExUVRefOnR99gSLikDKyd2jkQCSDnTx5En9//9Sv75f8ASZNmkTTpk3JnTv3oyxNRBxYRvYOhQORDObv729zgN/P8ePHWbZsGXPnzn2EVYmIo8vI3qHTCiIObvLkyYSEhNC8eXOzSxERJ5Ke3qFwIOLAUlJSmDx5Mp06dcLNTQN9IpI26e0dCgciDmzZsmWcOHGCF1980exSRMSJpLd36E8REQfWqFEjDMMwuwwRcTLp7R0aORAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERt2DQcjR47EYrEQFhZ213UsFgsDBw5M/XrlypVYLBZWrlyZ7v3/+uuvNtu2p2+//RaLxcKWLVseyfbtbfr06QwfPtzsMm5jz39vgAMHDtCvXz8qVapEtmzZCAoKombNmsyePdsu2xcRyYrsGg6++eYbAPbs2cOmTZvsuek0+fXXX/nwww8zfL+OyFHDgb0tXbqUhQsX8uSTTzJr1iymTZtGsWLFaNeuHf/73//MLk9ExCnZbW6FLVu2sHPnTpo3b87ChQuZNGkS1apVs9fm7c4wDBISEvDy8jK7FEmHDh060KNHDywWS+qypk2bcvHiRYYMGUL//v2xWq0mVigi4nzsNnIwadIkAAYPHkyNGjX44YcfiIuLs9fmiYuLo1+/fhQqVAhPT0+CgoKoXLkyM2bMAKBz586MHj0auHnq4tbr2LFjqctee+01xo0bR6lSpbBarUyZMgWAtWvXUr9+ffz8/PD29qZGjRosXLjwvjWdPXuWSpUqUaxYMQ4ePAhATExMap0eHh7kyZOH3r17Exsba/PeWbNmUa1aNQICAvD29qZw4cJpmj1r9OjRREREEBISgo+PD+Hh4QwdOpQbN26krlO3bl0WLlzI8ePHbT6LeylYsCAtWrRg8eLFVKxYES8vL0qWLJk6GvRPkZGRtGrVisDAQDw9PSlfvnzqZ/lP+/bto0mTJnh7e5M9e3a6d+/O1atX77j/ZcuWUb9+ffz9/fH29qZmzZosX778vp9H9uzZ7/izVa1albi4OC5fvnzfbYiIiC27jBzEx8czY8YMqlSpQlhYGC+++CJdunRh1qxZdOrUyR67oE+fPnz//fd8/PHHVKhQgdjYWCIjI7l06RIA77//PrGxscyePZsNGzakvi9Xrlyp/z1//nzWrFnDBx98QGhoKCEhIaxatYqGDRtStmxZJk2ahNVqZcyYMbRs2ZIZM2bQvn37O9YTGRlJs2bNyJs3Lxs2bCB79uzExcVRp04dTp06xbvvvkvZsmXZs2cPH3zwAbt372bZsmVYLBY2bNhA+/btad++PQMHDsTT05Pjx4/z+++/3/dzOHz4MB07dkwNHzt37uSTTz5h3759qb/Ix4wZQ9euXTl8+DDz5s1L82e8c+dO+vbty9tvv03OnDn5+uuveemllyhatCgREREA7N+/nxo1ahASEsLIkSMJDg5m6tSpdO7cmfPnz/PWW28BcP78eerUqYO7uztjxowhZ86cTJs2jddee+22/U6dOpXnn3+eVq1aMWXKFNzd3Rk/fjyNGzdmyZIl1K9fP80/wy0rVqwgR44chISEPPB7RUSyOruEg9mzZxMdHc1LL70EQPv27enduzeTJk2yWzhYt24djRo14o033khd1rx589T/LlKkCDlz5gTgscceu+M2rl27xu7duwkMDExdVr16dQIDA1m5ciW+vr4AtGjRgvLly9OvXz+eeuqp2/4yXbZsGU8++SSNGjXi+++/x9PTE7h5QeauXbvYtGkTlStXBqB+/frkyZOHtm3bsnjxYpo2bcr69esxDINx48YREBCQut3OnTvf93P44osvUv87JSWF2rVrExwczAsvvMDnn39OYGAgpUuXJlu2bFit1rt+Fndy8eJF1q1bR/78+QGIiIhg+fLlTJ8+PTUcDBw4kOvXr7NixQry5csHQLNmzYiKiuLDDz+kW7duBAQE8OWXX3LhwgW2b99OuXLlgJvD/Y0aNeLEiROp+4yLi6NXr160aNHCJsg0a9aMihUr8u677z7w9Stff/01K1euZMSIEbi6uj7Qe0VExE6nFSZNmoSXlxcdOnQAwNfXl3bt2rFmzZrU4fb0qlq1KosWLeLtt99m5cqVxMfHP/A2Hn/8cZtgEBsby6ZNm2jbtm1qMABwdXXlueee49SpU+zfv99mG1OmTKFZs2Z06dKFH3/8MTUYAPzyyy+EhYVRvnx5kpKSUl+NGze2uUK/SpUqADz11FP8+OOPnD59Os0/w/bt2/nPf/5DcHAwrq6uuLu78/zzz5OcnMyBAwce+DP5p/Lly6cGAwBPT0+KFy/O8ePHU5f9/vvv1K9fPzUY3NK5c2fi4uJSR21WrFhBmTJlUoPBLR07drT5ev369Vy+fJlOnTrZfGYpKSk0adKEzZs333ZK5l4WLVpEjx49aNu2La+//nqa3yciIv8v3eHg0KFDrF69mubNm2MYBlFRUURFRdG2bVuAO56zfhgjR46kf//+zJ8/n3r16hEUFMQTTzzxQOHjn6cYAK5cuYJhGLctB8idOzdA6mmLW3744Qe8vLzo0qXLbSMK58+fZ9euXbi7u9u8/Pz8MAyDixcvAjf/Ip8/fz5JSUk8//zz5M2bl7CwsNTrJ+7mxIkT1K5dm9OnTzNixAjWrFnD5s2bU6+1eJjA9E/BwcG3LbNarTbbvXTpUpo+r0uXLhEaGnrbev9edv78eQDatm172+c2ZMgQDMNI83UDS5YsoU2bNjRs2JBp06bd9zoLERG5s3SfVvjmm28wDIPZs2ff8d7yKVOm8PHHH6d7eNfHx4cPP/yQDz/8kPPnz6eOIrRs2ZJ9+/alaRv//mURGBiIi4sLZ8+evW3dM2fOADcvePunadOm8f7771OnTh2WLl1K+fLlU7+XPXt2vLy87hqI/rmtVq1a0apVKxITE9m4cSODBg2iY8eOFCxYkOrVq9/x/fPnzyc2Npa5c+dSoECB1OU7duy4589tT8HBwWn6vIKDgzl37txt6/172a31R40adddTILdOF93LkiVLeOKJJ6hTpw5z5szBw8Pjvu8REZE7S1c4SE5OZsqUKRQpUoSvv/76tu//8ssvfP755yxatIgWLVqkZ1c2cubMSefOndm5cyfDhw8nLi4Ob2/v1FvW4uPj03SLoo+PD9WqVWPu3Ll89tlnqe9JSUlh6tSp5M2bl+LFi9u8JygoiGXLltGiRQvq1avHokWLUn+ptWjRgk8//ZTg4GAKFSqUpp/FarVSp04dsmXLxpIlS9i+fftdw8GtcPPPW/MMw2DixIl33G56RxLupH79+sybN48zZ86kjhYAfPfdd3h7e6d+FvXq1WPo0KHs3LnT5tTC9OnTbbZXs2ZNsmXLxt69e+94sWJaLF26lCeeeIJatWoxf/583booIpJO6QoHixYt4syZMwwZMoS6deve9v2wsDC++uorJk2alO5wUK1aNVq0aEHZsmUJDAzkzz//5Pvvv6d69ep4e3sDEB4eDsCQIUNo2rQprq6ulC1b9p5/RQ4aNIiGDRtSr149+vXrh4eHB2PGjCEyMpIZM2bccWjaz8+PxYsXpw5h//TTT9SrV4/evXszZ84cIiIieOONNyhbtiwpKSmcOHGCpUuX0rdvX6pVq8YHH3zAqVOnqF+/Pnnz5iUqKooRI0bg7u5OnTp17lprw4YN8fDw4Omnn+att94iISGBsWPHcuXKldvWDQ8PZ+7cuYwdO5ZKlSrh4uKSepFkegwYMIBffvmFevXq8cEHHxAUFMS0adNYuHAhQ4cOTb3Asnfv3nzzzTc0b96cjz/+OPVuhX+P8vj6+jJq1Cg6derE5cuXadu2LSEhIVy4cIGdO3dy4cIFxo4de9d61q5dyxNPPEFoaCjvvvvubaMopUuXxt/fP90/t4hIVpKucDBp0iQ8PDx44YUX7vj97Nmz07p1a2bPns358+fTNDx8N48//jg//fQTX375JXFxceTJk4fnn3+e//73v6nrdOzYkXXr1jFmzBj+97//YRgGR48epWDBgnfdbp06dfj9998ZMGAAnTt3JiUlhXLlyvHTTz/dM9B4eXmxYMECOnbsSLNmzZgzZw7NmjVjzZo1DB48mAkTJnD06FG8vLzInz8/DRo0SK2jWrVqbNmyhf79+3PhwgWyZctG5cqV+f333ylTpsxd91myZEnmzJnDe++9R5s2bQgODqZjx4706dOHpk2b2qzbq1cv9uzZw7vvvkt0dDSGYWAYRto+7HsoUaIE69ev591336VHjx7Ex8dTqlQpJk+ebHO3RWhoKKtWraJXr1688soreHt707p1a7766itatWpls81nn32W/PnzM3ToULp168bVq1cJCQmhfPny972DY9myZcTHx3Ps2DEef/zx276/YsWKOwZXERG5O4thj98YIplYTEwMAQEBfN0rD97Wh7+GNy4xhS4jThMdHa3RDJFMzl59A8zpHZqVUURERGwoHIiIiIgNhQMRERGxoXAgIum2adMmWrduTf78+bFareTMmZPq1avTt29fm/XGjBnDt99++0hq6Ny5s82TTs20Zs0arFarzdNFb912XKlSJfz9/QkODqZOnTppmuTtbk6dOkXv3r1Tb4e2WCx3/Hxv3LhBkSJFHsk07p9++inz58+3+3bTa+DAgXZ9ENrvv//Oiy++SMmSJfHx8SFPnjy0atWKrVu32m0fjkThQETSZeHChdSoUYOYmBiGDh3K0qVLGTFiBDVr1mTmzJk26z7KcOAoDMOgd+/evPzyyzYPKxswYABdu3alatWqzJkzh2+//Rar1UqLFi2YO3fuQ+3r0KFDTJs2DQ8PD5o1a3bX9dzd3fnggw/43//+d9tTX9PLUcOBvY0dO5Zjx47Rq1cvfv31V0aMGMFff/3FY489lqZJ85yNXSZeEpGsa+jQoRQqVIglS5bg5vb/LaVDhw4MHTr0obd748YNLBaLzTadweLFi9m2bdttD/z65ptvqFWrls1zOxo2bEhoaChTpkyhTZs2D7yviIgILly4AMCWLVvu+Qj2p59+mj59+jB+/HjefffdB95XVjd69OjbZnlt0qQJRYsW5dNPP73jrdTOTCMHIpIuly5dInv27Hf8Je7i8v8tpmDBguzZs4dVq1ZhsViwWCypz/5YuXIlFouF77//nr59+5InTx6sViuHDh0Cbv5iLVeuHJ6engQFBdG6dWv+/PPP+9a2bt06smfPTosWLVIn8Dp48CAdO3YkJCQEq9VKqVKlUucnuSUlJYWPP/6YEiVK4OXlRbZs2ShbtiwjRoy47z7Hjh1LlSpVKFGihM1yd3d3m1lY4ebkZrdeD+Ofn+/9eHh40L59eyZMmHDfZ54kJCTQt29fypcvT0BAAEFBQVSvXp0FCxbYrGexWIiNjWXKlCmp/6b3eq7IsWPHsFgsfPbZZ3zxxRcUKlQIX19fqlevzsaNG29b/6effkp90J2fnx8NGzZMndztnxYuXEj58uWxWq0UKlSIzz777I77NwyDMWPGUL58eby8vAgMDKRt27YcOXLknp8HcMfp3319fSldujQnT5687/udjcKBiKRL9erV2bRpEz179mTTpk3cuHHjjuvNmzePwoULU6FCBTZs2MCGDRtspukGeOeddzhx4gTjxo3j559/JiQkhEGDBvHSSy9RpkwZ5s6dy4gRI9i1axfVq1e/58RrP/74I/Xr1+epp55iwYIF+Pj4sHfvXqpUqUJkZCSff/45v/zyC82bN6dnz558+OGHqe8dOnQoAwcO5Omnn2bhwoXMnDmTl156iaioqHt+FtevX2fZsmXUq1fvtu/16tWLxYsXM2nSJK5cucLZs2fp06cP0dHR9OzZ857btZe6dety/PhxIiMj77leYmIily9fpl+/fsyfP58ZM2ZQq1Yt2rRpw3fffZe63oYNG/Dy8qJZs2ap/6Zjxoy5bx2jR4/mt99+Y/jw4UybNo3Y2FiaNWtGdHR06jrTp0+nVatW+Pv7M2PGjNTPrW7duqxduzZ1veXLl9OqVSv8/Pz44YcfGDZsGD/++COTJ0++bb/dunWjd+/eNGjQgPnz5zNmzBj27NlDjRo1UieBexDR0dFs27btng+vc1bONV4nIg5n8ODB7Nu3j1GjRjFq1Cjc3d2pUqUKLVu25LXXXku9SLBChQp4eXnh7+9/10m2ihQpwqxZs1K/joqK4qOPPqJZs2Y2w/R169alWLFiDBw4kGnTpt22nSFDhvDf//6XTz/9lLfeeit1eZ8+ffDz82Pt2rWpD5Np2LAhiYmJDB48mJ49exIYGMi6desIDw9n4MCBqe9t3LjxfT+LHTt2EB8fT8WKFW/7Xu/evfHy8qJHjx506dIFuDlXy88//0zNmjXvu217uFXXrZ/vbgICAmx+uSYnJ1O/fn2uXLnC8OHDef755wF47LHHcHFxIUeOHHf9N70TPz8/fvnll9QJ+XLnzk3VqlVZtGgRHTp0ICUlhTfffJPw8HAWLVqUOkLSrFkzihQpQv/+/Vm3bh0A//3vf8mZMye//fZb6ghM48aNb3sy7saNG5k4cSKff/45ffr0SV1eu3ZtihcvzhdffMGQIUPS/DMA9OjRg9jYWJsn9WYWGjkQkXQJDg5OnT588ODBtGrVigMHDvDOO+8QHh6eOlV5Wjz55JM2X2/YsIH4+PjbHqOdL18+Hn/8cZYvX26z3DAMunXrxoABA5g+fbpNMEhISGD58uW0bt0ab29vkpKSUl/NmjUjISEhdWi7atWq7Ny5k1dffZUlS5YQExOTpvpvzU56pyHoyZMn06tXL1577TWWLVvGr7/+SqNGjWjVqhVLlixJ0/bT61Zdp0+fvu+6s2bNombNmvj6+uLm5oa7uzuTJk1K0+mc+2nevLnNTL1ly5YFSL27Y//+/Zw5c4bnnnvO5tSJr68vTz75JBs3biQuLo7Y2Fg2b95MmzZtbE7N+Pn50bJlS5t9/vLLL1gsFp599lmbf/vQ0FDKlSvHypUrH+hneP/995k2bRpffvkllSpVetCPwOFp5EAkjWpXPIOf98PfGnU1LnM/qbxy5cqpk3vduHGD/v378+WXXzJ06NA0X5iYK1cum69vXVn/7+Vw86/N3377zWbZ9evXmTlzJmXKlLltvpFLly6RlJSUOsJxJ7eCzDvvvIOPjw9Tp05l3LhxuLq6EhERwZAhQ+45gdmtmVD/fQ3BlStXUkcM/nk+vGnTptStW5fu3btz9OjRu27XXm7Vdb8ZW+fOnctTTz1Fu3btePPNNwkNDcXNzY2xY8fedUr6BxEcHGzz9T9n1IX7/7unpKRw5coVDMMgJSWF0NDQ29b797Lz589jGMZd5/gpXLhwmuv/8MMP+fjjj/nkk0/uO5tsevsGmNM7FA5ExO7c3d0ZMGAAX3755X3Pb//Tv+9Lv/VL5OzZs7ete+bMGbJnz26zzGq1smLFCho3bkyDBg1YvHgxgYGBAAQGBuLq6spzzz1Hjx497rj/W1Otu7m50adPH/r06UNUVBTLli3j3XffpXHjxpw8eTJ1Jth/u1XP5cuXbZbv37+f+Ph4qlSpctt7KleuzKpVq7h27dojf07Drbr+/bn929SpUylUqBAzZ860+TdJTEx8pPXdcr9/dxcXFwIDAzEMA4vFwrlz525b79/LsmfPjsViSX0Gxb+ldar3Dz/8kIEDBzJw4MBMfdeHTiuISLrcqYEDqcPPuXPnTl1mtVrv+1frP1WvXh0vLy+mTp1qs/zUqVP8/vvv1K9f/7b3VKhQgVWrVnHq1Cnq1q3LX3/9BYC3tzf16tVj+/btlC1bNnWk45+vf/9FC5AtWzbatm1Ljx49uHz5MseOHbtrvaVKlQLg8OHDNstvfQb/viLfMAw2btxIYGAgPj4+9/9A0unWVfmlS5e+53oWiwUPDw+bYHDu3Lnb7laAB/83TYsSJUqQJ08epk+fbnNnRWxsLHPmzEm9g8HHx4eqVasyd+5cEhISUte7evUqP//8s802W7RogWEYnD59+o7/9ve6BuOWjz76iIEDB/Lee+8xYMAA+/3ADkgjByKSLo0bNyZv3ry0bNmSkiVLkpKSwo4dO/j888/x9fWlV69eqeuGh4fzww8/MHPmTAoXLoynp+c9m3K2bNl4//33effdd3n++ed5+umnuXTpEh9++CGenp53bdClSpVizZo1NGjQgIiICJYtW0bevHkZMWIEtWrVonbt2rzyyisULFiQq1evcujQIX7++efUh9m0bNmSsLAwKleuTI4cOTh+/DjDhw+nQIECFCtW7K715s2bl8KFC7Nx40abOxDy589PmzZtmDBhAlarlWbNmpGYmMiUKVNYt24dH330kc0v4rp167Jq1ao0TbM+e/Zs4P9/8W/ZsiV1BKJt27Y2627cuDH1FMm93How06uvvkrbtm05efIkH330Ebly5brtDpHw8HBWrlzJzz//TK5cufDz87vtNs4H5eLiwtChQ3nmmWdo0aIF3bp1IzExkWHDhhEVFcXgwYNT1/3oo49o0qQJDRs2pG/fviQnJzNkyBB8fHxsRnBq1qxJ165deeGFF9iyZQsRERH4+Phw9uxZ1q5dS3h4OK+88spda/r888/54IMPaNKkCc2bN78t6D3IBZlOwRCRe4qOjjYAY/8Ui3FmlstDv/ZPsRiAER0dbfaPZFczZ840OnbsaBQrVszw9fU13N3djfz58xvPPfecsXfvXpt1jx07ZjRq1Mjw8/MzAKNAgQKGYRjGihUrDMCYNWvWHffx9ddfG2XLljU8PDyMgIAAo1WrVsaePXts1unUqZPh4+Njs+zUqVNGyZIljYIFCxqHDx82DMMwjh49arz44otGnjx5DHd3dyNHjhxGjRo1jI8//jj1fZ9//rlRo0YNI3v27IaHh4eRP39+46WXXjKOHTt238/j/fffNwIDA42EhASb5fHx8cawYcOMsmXLGn5+fkZQUJDx2GOPGVOnTjVSUlJs1q1UqZIRGhp6330ZhmEAd339W+3atY2WLVumabuDBw82ChYsaFitVqNUqVLGxIkTjQEDBty23R07dhg1a9Y0vL29DcCoU6fOXbd59OhRAzCGDRt2x59jwIABNsvmz59vVKtWzfD09DR8fHyM+vXrG+vWrbvtvT/99FPq/x/58+c3Bg8efMdaDcMwvvnmG6NatWqGj4+P4eXlZRQpUsR4/vnnjS1bttzz86hTp84Dfdb26htm9Q6LYaQhmopkYbfmZd8/xZLuCxJLdDIydE52yXhnzpyhUKFCfPfdd7Rv3/6B33/16lWCgoIYPnz4Xa+NeBiHDx+mWLFiLFmyhIYNG9ptu3Jn9uobYE7v0DUHIiJ2lDt3bnr37s0nn3xCSkrKA79/9erV5MmTh5dfftmudX388cfUr19fwUDSROFARMTO3nvvPZ588sk0PU/g35o3b86xY8fw8PCwWz1JSUkUKVLktsdEi9yNLkgUEbEzPz8/h7qa3c3Njffee8/sMsSJaORAREREbCgciDiw06dP8+yzzxIcHIy3tzfly5dn69atZpclIg7MHn1DpxVEHNSVK1eoWbMm9erVY9GiRYSEhHD48GGyZctmdmki4qDs1TcUDkQc1JAhQ8iXL5/N7Hj/nmlOROSf7NU3dFpBJIPFxMTYvO72vPqffvqJypUr065dO0JCQqhQoQITJ07M4GpFxFGkpXfYq28oHIhksHz58hEQEJD6GjRo0B3XO3LkCGPHjk19cE337t3p2bMn3333XQZXLCKOIC29w159Q6cVRDLYyZMnbZ5ydrfZ4FJSUqhcuTKffvopcHNCoT179jB27Fief/75DKlVRBxHWnqHvfqGRg5EMpi/v7/N627hIFeuXLfNnleqVClOnDiREWWKiINJS++wV99QOBBxUDVr1mT//v02yw4cOECBAgVMqkhEHJ29+obdwkF80g1ib9z5wioReXBvvPEGGzdu5NNPP+XQoUNMnz6dCRMm2HUyHkdwOSHW7BJEMg179Q27hINFxyOpPWcYX+1aaY/NiQhQpUoV5s2bx4wZMwgLC+Ojjz5i+PDhPPPMM2aXZhfxSdfpuXomj80awtnYaLPLEckU7NU37HJBogsWzsXFMHHPWjqVqk6ot6ajFbGHFi1a0KJFC7PLeCQ8Xd05efUycUnX+XLHcobWbGN2SSKZgj36hl1GDhrlL03lkAIkJN9g+I7l9tikiGRyFouFdys3BWDmwS0cjr5gckUicotdwoHFYuGdSk0AmHFgM0d0kItIGlTJWZBG+UqRbKQwZOsSs8sRkb/Z7YLEaqGFaJCv5M2DfNtSe21WRDK5/pWa4GKx8OvxSLZd0G2aIo7Arrcy9q/YBAsWFh7bzY4LJ+25aRHJpEoE5qRtkYoADNqyGMMwTK5IROwaDkoFhdK2aAUAPt2ySAe5iKRJ3woNsbq6seHcEVaePmB2OSJZnt0fgtS3QkM8XFxZf+4Iq84ctPfmRSQTyuObjc4lqwMwaOtiUowUkysSydrsHg7y+gbSqdTfB/mWRTrIRSRNXitbFz93K3svn2X+kZ1mlyOSpT2Sxye/XrYefu5W9lw+y09Hdz2KXYhIJhPo6UOPsnUBGLZtKYnJSeYWJJKFPZJwEOTpwyvhdYCbB/l1HeQikgYvla5JTi8/Tl67wtT9m8wuRyTLemQTL3UpXYsQLz+OX73MtP1/PKrdiEgm4uXmwRvlGwAwcufvXNN8LSKmeGThwNvdgzfK1wdghA5yEUmj9sUrU9g/O5cSYhkfudrsckSypEc6ZXOH4lUo5J+diwnXmBC55lHuSkQyCXcXV96q1BiA8ZFruBB/1eSKRLKeRxoO3F1ceatiIwDGR67mYvy1R7k7EckkmhcIo1z2vMQlXWfEzt/NLkcky3mk4QCgecGbB3ls0nVG6iAXkTT456RM0/b/wbGYSyZXJJK1PPJw4GJxSZ2U6fv9mzh+VQe5iNxfzVxFqJOnODdSkhm2XfO1iGSkRx4OAGrlLkpE7mLcSEnms22/ZcQuRSQTeOfvaw8WHNlJ5KXTJlcjknVkSDgAUkcP5h/ZyZ5LZzJqtyLixMKC8/BE4fIADNKUziIZJsPCQXj2PLQqVA4Dg0FbF2fUbkXEyb1ZsSHuLq6sOn2AdWcOmV2OSJaQYeEAoF/FhrhZXFh5+gDrzx7OyF2LiJMq4BfMMyWqAvDpVk3pLJIRMjQcFPLPzjMlqgHwqeZtF5E06l2uPj5uHuy8eIqFxyPNLkck08vQcADQu/zjeLt5sOPiSX7VQS4iaZDdy5euYbUBGLJ1CTdSkk2uSCRzy/BwkMPLj5fL1AJg6LalJOkgF5E06BYWQbCnD0djLjLzwBazyxHJ1DI8HAB0D4sgyOrD4egLzDy41YwSRMTJ+Lpb6VXucQC+3LGMuBvXTa5IJPMyJRz4eXjSs1w9AL7Y/hvxSTrIReT+ni1Rjfy+QZyPv8qkvevMLkck0zIlHAA8V/Ix8vkG/n2QrzerDBFxIh6ubvSr2BCAMbtXciUh1tyCRDIp08KB1dWNfn9PyjRm90quJMaZVYqIOJEnCpejdFAurt5I5KtdK80uRyRTcjNz560Ll2Pc7lX8eeUco3et5L0qzcwsR+SeBt3Ig8eNh8/T12+kAKfsV1AWdWu+lud+m8zkP9fzYuma5PHNZnZZIneU3r4B5vQO00YO4OZB/vbfj1We/Od6zlyLMrMcEXESdfMUp3poYa6nJPP5ds3XImJvpoYDgMfzluCx0EIkJifx+Y5lZpcjIk7gn1M6zz68jX1XzplckUjmYno4sFgsvFPp5kE+69BWDkSdN7kiEXEGFXLko1mBMFIMgyGalEnErkwPBwCVQvLTJH8ZHeQi8kD6V2qMq8WF307+yR/nj5ldjkim4RDhAODtSo1xsVhYcmIvW84fN7scEXECRQJy0KFYZQAGbVmk+VpE7MRhwkHRbCG0v3WQb9VBLiJp80aFBni6urP5r+P8dvJPs8sRyRQcJhwA9CnfAKurG5vOH2P5qX1mlyMiTiDU25+XStcEbk7KlJySYnJFIs7PocJBLp+A1IN80JbFOshFJE1eDa9DgIcX+6POM+fwNrPLEXF6DhUO4NZB7sn+qPPMO7Ld7HJExAkEWL14vezN+Vo+2/4bCUk3TK5IxLk5XDjIZvWmx98H+bBtOshFJG06l6pOLu8AzsRGM2XfBrPLEXFqDhcOAF4oVYNQb39Ox0bx/f6NZpcjIk7A0809dVKmUbtWEp0Yb3JFIs7LIcOBl5s7fSvcPMhH7lxBzPUEkysSEWfQtkhFimcLISoxjrGRq8wuR8RpOWQ4AGhXtCJFA3JwJTGOcbt1kIvI/bm6uNC/YmMAvt6zjnNxMSZXJOKcHDYcuLm4pk7KNHHvWs7rIBeRNGiUvzSVQwqQkHyD4TuWm12OiFNy2HAA0Dh/aSrlyE980g1G7Pzd7HJEMtTAgQOxWCw2r9DQULPLcnj/nJRpxoHNHI6+YHJFIhnHXn3DocOBxWLhnco3Rw+m7f+DI9EXTa5IJGOVKVOGs2fPpr52795tdklOoWrOgjTIV5JkI4Wh25aaXY5IhrJH33DocADwWGhh6ue9eZAP00EuWYybmxuhoaGprxw5cphdktN4u1ITLFhYeGw32y+cNLsckQxjj77h8OEA/v8g//nYLnZePGV2OSLpEhMTY/NKTEy867oHDx4kd+7cFCpUiA4dOnDkyJEMrNS5lQwMpW3RCoAmZZLMIa29wx59wynCQamgUNoUKQ/cfKyyiDPLly8fAQEBqa9Bgwbdcb1q1arx3XffsWTJEiZOnMi5c+eoUaMGly5dyuCKnVffCg3xcHFl/bkjrDpz0OxyRNIlLb3DXn3DzV5FP2r9KjTk56O7WHv2EKtPHyQiTzGzSxJ5KCdPnsTf3z/1a6vVesf1mjZtmvrf4eHhVK9enSJFijBlyhT69OnzyOvMDPL6BtK5VHUm7FnLoC2LiMhdFBeLU/xNJHKbtPQOe/UNpzlK8vkF8XzJxwAYtHUxKYYmZRLn5O/vb/O6Wzj4Nx8fH8LDwzl4UH8BP4jXy9bDz93KnstnWXBkl9nliDy0h+kdD9s3nCYcAPQs9zi+7lZ2XzrNz0d11bZkLYmJifz555/kypXL7FKcSqCnD6+E1wFg2LalXE9OMrkikYzzsH3DqcJBkKcPr4RFADBUB7lkcv369WPVqlUcPXqUTZs20bZtW2JiYujUqZPZpTmdLqVrEeLlx4lrl5m6f5PZ5Yg8MvbqG04VDgBeLlObHF6+HL96iRkHNptdjsgjc+rUKZ5++mlKlChBmzZt8PDwYOPGjRQoUMDs0pyOt7sHb5SvD8CInb9z7cbd7xARcWb26htOc0HiLd7uHvQuV5//blzAlzuW07ZoRXzc03bOVsSZ/PDDD2aXkKl0KF6FCXvWcjTmIhMi19CnQgOzSxKxO3v1DacbOQDoWKIqBf2CuZhwjYl71ppdjog4AXcXV/pXbATA+MjVXIy/ZnJFIo7LKcOBu4srb/19kI+LXM2lBB3kInJ/zQuGUy57XmKTrmu+FpF7cMpwANCiUDjhwXm4diORkTtXmF2OiDgBi8XCO3/P9jp1/yaOX9UDpUTuxGnDgYvFhXf/npTp+30bOXn1sskViYgzqJW7KHVyF+NGSjLDtv1mdjkiDslpwwFA7dzFqJ27KNdTkvlsuw5yEUmbW7O9zj+ygz2XzphcjYjjcepwAKQOEc49vIO9l8+aXI2IOIOw4Dy0KlQOuPnEVRGx5fThoGz2vPynUFkMDAbrIBeRNHqzYiPcLC6sPH2AdWcPm12OiENx+nAA/3+Q/35qPxvOaUpbEbm/gv7BPFOiGnBztldN6Szy/zJFOCjkn52OJaoC8KnmbReRNOpd/nG83TzYcfEkvx6PNLscEYeRKcIBQO9y9fFyc2f7hZMsPrHH7HJExAnk8PKja1htAIZsXUJSSrLJFYk4hkwTDkK8/ehaRge5iDyYbmVqE2T14UjMRX44uMXsckQcQqYJBwDdwyIItHpzKPoCPx7aanY5IuIE/Dw86VmuHgBfbl9GfNJ1kysSMV+mCgd+Hp70Kvc4AF9sX0Z80g2TKxIRZ/BcycfI5xvI+firTNq7zuxyREyXqcIB3DzI8/pm41xcDJP/XG92OSLiBKyubvT7e76WMbtXcSUxzuSKRMyV6cKB1dWNfhUaAjB61wqidJCLSBq0LlyOUoGhxFxP4KtdK80uR8RUmS4cALQuXIGSgaFEX09g9K5VZpcjIk7AxeLCO5WbAvDtn+s5fS3K3IJETJQpw4Gri0vqY5W/+XMdZ2KjTa5IRJxBvTzFeSy0EInJSXyxQ/O1SNaVKcMBwON5S1AtZ0ESk5P4cscys8sRESdwc0rnm6MHsw5tY/+V8yZXJGKOTBsOLBYL7/49RDjz4BYORv1lckUi4gwqheSnaYEypBgGQzRfi2RRmTYcAFQKKUDj/KX/PsiXmF2OiDiJ/hUb42KxsPTkn2w+f8zsckQynMXI5BMRHIz6i/rzvyTFMFjQ/FUqheQ3uyRxMjExMQQEBHCg+P/wc/V86O1cTU6g+IEPiI6Oxt/f344VyqPw5ro5zDiwmao5CzKnaTcsFovZJYkTsVffAHN6R6YeOQAoli2Ep4pWAjQpk4ikXZ/yDbC6uvHH+WMsO/mn2eWIZKhMHw4A+lRoiNXVjU3nj/L7qf1mlyMiTiCXTwAvla4JwOCtS0hOSTG5IpGMkyXCQW6fAF4oVQOAQVsX6yAXkTR5NbwOAR6e7I86z9zD280uRyTDZIlwANCjbF0CPDzZd+Uc847sMLscEXEC2azevFb25qRMw7YvJUHztUgWkWXCQaDVm1fD6wLw2falJCYnmVuQiDiFzqVqkMs7gDOx0Xy3b6PZ5YhkiCwTDgBeLF2DnN7+nLoWxfc6yEUkDbzc3OlToQEAI3etIOZ6gskViTx6WSoceLl50PfWQb5zBVd1kItIGrQrWpFiASFEJcYxdrfma5HML0uFA4CnilaiaEAOLifGMi5ytdnliIgTcHNxpX+lxgBM3LOW83ExJlck8mhluXDg5uLKWxX//yD/K+6qyRWJiDNonL80lXLkJyH5BsN3LDe7HJFHKsuFA4CmBcpQIUc+4pKuM2KnDnIRuT+LxcI7lW/O9jr9wGaORF8wuSKRRydLhoN/Tso0bf8fHI25aHJFIuIMHgstTP28JUk2Uhi6banZ5Yg8MlkyHABUDy1MvTwlSDJS+Gyb5m0XkbR5u1ITLFj45dhudlw4aXY5Io9Elg0HAO9UbowFCwuO7mTXxVNmlyMiTqBUUChPFqkA3HziquZrkcwoS4eD0kG5aV2kPHDz2ekiImnRr2JDPFxcWXf2MKvPHDS7HBG7y9LhAKBfhYa4u7iy+sxB1uggF5E0yOsbyPMlHwNg0JbFpBiar0UylywfDvL7BekgF5EH1rPc4/i6W4m8fIafju4yuxwRu8ry4QCgZ7l6+Lpb2XXpNAuPRZpdjog4gSBPH14JiwBg2LalXNd8LZKJKBwAwZ6+dAurDcCQrUu4kZJsckUi4gxeLlObHF6+HL96mekHNptdjojdKBz8rWuZ2mT39OXY1UvM0EEuImng7e7BG+VvztcyfMdyYm8kmlyRiH0oHPzNx91K7/L1wTD4YvsyLsZfM7skEXECTxevQkG/YC7GX+WLHcvMLkfELhQO/qFN/nDqHkgkX5yFiLmfM2zbUoUEEbkndxdXnvctSs3DiUyN3MCTv47jtxN7dXGzODWFg78lJSUx+etJ+FyJJ2TXGa4lxDFi5+9UmzWYt9fP03PUxXSDBg3CYrHQu3dvs0uRfzh06BA7f15Gtovx5D4Ty6bzx3hh+Xc8Pu9LZhzYTELSDbNLlCzsYfuGwgFgGAbff/89e/fuxcPDg3d79WVs/WepkCMficlJTN2/iTpzv+Cl5d+x5fxxs8uVLGjz5s1MmDCBsmXLml2K/MOZM2cYPXo0SUlJlCtXju9ff59Xwurg527lUPQF3lw3h+qzhzBq5wqiEuPMLleymPT0DYUDYN68eWzcuBEXFxe6detGkcKFaV4wnJ+av8qcpt1omK8UBgZLTuzliV/H8sTCsSw+vkfDhpIhrl27xjPPPMPEiRMJDAw0uxz525UrVxg5ciRxcXEULlyYLl26kNc/iP9WacofT73D+1Wakcs7gAvx1xiybQlVfxzMgE0/c+raFbNLlywgvX0jy4eD33//nSVLbj46+bnnniMsLCz1exaLhWqhhZjcoBMrWvehQ7HKeLi4suWv43T5/Xvqzv2Cqfs3adhQHkhMTIzNKzHx3le49+jRg+bNm9OgQYMMqlDuJy4ujpEjR3LlyhVy5sxJjx498PDwSP2+n4cn3cIiWN/uLYbXfopSgaHEJV1n0t511Jw9jB6rZhB56bSJP4E4owfpHentG1k6HGzZsoUff/wRgFatWlGjRo27rlssWwif1WrLhnb9ea1sXQI8PDkSc5G318/jsVlDGL5jOVcSYjOqdHFi+fLlIyAgIPU1aNCgu677ww8/sG3btnuuIxnrxo0bjB07ljNnzuDv70/Pnj3x9fW947ruLq60LVqRpa16Ma3Ri9TOXZRkI4UFR3bS5KdRdFj8NStO7dfkTZImae0d9ugbbg/9Tie3f/9+Jk+ejGEY1KlTh6ZNm6bpfTm9/Xm7UhNeK1uPHw5sZuKetZyOjeKz7b8xevdK2herTNcytcnvF/RofwBxWidPnsTf3z/1a6vVetf1evXqxdKlS/H09Myo8uQeUlJS+Oabbzhw4ACenp707NmT7Nmz3/d9FouFOnmKUydPcSIvnWZc5Bp+PrqLtWcPsfbsIUoGhtI9rDb/KVQOD9cs25blPtLSO+zVNyxGFoysp0+fZtiwYcTHx1OhQgW6du2Ki8vDDaLcSElm4bHdjNu9msjLZwBwsVhoXiCc7uERlMue156liwliYmIICAjgQPH/4ef68Afb1eQEih/4gOjoaJsD/G7mz59P69atcXV1TV2WnJyMxWLBxcWFxMREm+/Jo2UYBjNnzmTFihW4urrSs2dPSpYs+dDbO3XtCl/vWcv0A5uJS7oOQKi3P11K16Jjiar4eygQOjN79Q14sN5hr76R5cLB5cuXGTJkCFFRURQtWpTevXvj7u6e7u0ahsG6s4cZG7maVacPpC5/LLQQr4TVoV7e4rhYsvRZHKdlVji4evUqx4/b3h3zwgsvULJkSfr3729zfYw8eosXL2bevHkAdOnShSpVqthlu1GJcUzd/wff7F3HX/FXAfBzt9KxRDVeKl2T3D4BdtmPZCyzwoG9+kaWGr+KjY1l5MiRREVFkTt3bl599VW7BAO4OWxYK3dRauUuyt7LZ5kQuYb5R3aw8dxRNp47SvFsIXQLi+CJwuWxathQ0sDPz++2A9nHx4fg4GAFgwy2cePG1GDQrl07uwUDgGxWb14rW5eXy9Ri3uHtjI9cw8HovxgfuZpJe9byROHydAuLoFRQqN32KZmXvfpGlvlT9vr164wePZqzZ8+SLVs2Xn/9dXx8fB7JvkoH5WJ4xFOsb9efbmER+LpbORD1F33XzqbGrCGM3rWS6MT4R7JvEbGvPXv2MGXKFAAaNmz4yO4asbq60aF4FZa37s23DTpRLWchkowUZh/eRsMFw3l26TesO3NIFy9KhsgSpxVSUlIYP348O3bswNvbm379+pEnT54M23/M9QSm7d/E13vXcT4uBgAfNw+eKVGVLqVrkds3W4bVIg/OrNMKYr7jx4/z+eefk5iYSNWqVXnhhRce+vqkh7H9wknGRa5m0fFIUv5u1eHBeegeFkHzgmG4ueiaE0dl1mkFe8n04cAwDGbMmMGqVatwc3OjV69eFC9e3JRaricnseDITsZFrmZ/1HkA3Cwu/KdwObqH1aZ0UG5T6pJ7UzjImi5cuMCQIUO4evUqJUuW5PXXX8fNzZxTgsdiLjFxz1pmHtxCQvLN56rk8w2kS5ladChWGR/3O9/xIuZROHBwv/76KwsWLMBisdC1a1cqVqxodkkYhsHK0wcYF7madWcPpy6PyF2M7mER1M5dFIvFYmKF8k8KB1lPTEwMw4YN46+//iJfvnz07dsXLy8vs8vickIsU/Zt4Ns/N3Dp7+eqBHh48XzJx3ihVA1CvP1MrlBucfZwkKmvjFu3bh0LFiwAoH379g4RDODmxYv18pagXt4S7Lp4ivGRa/j52C5WnznI6jMHKROUi25hEbQsVBZ3DRuKZKiEhARGjx7NX3/9RXBwMK+//rpDBAOAIE8f3ijfgO5hdZh9aCvjI9dw7OolRu1awfjI1TxZtCLdytSmaLYQs0sVJ5dpRw52797NmDFjSElJoUmTJrRu3drsku7p5NXLTNyzlhkHNxP/9+OYc/sE8HKZWjxdvCq+GjY0jUYOso7k5GTGjBlDZGQkPj4+vPXWW4SGOu5dAskpKSw5sZdxkavZduFE6vJG+UrRPbwOVUIKaBTSJM4+cpApw8HRo0f54osvuH79OtWrV6dTp05Oc4BcSYzj+30bmfznei7EXwPA38OTZ0tU48XSNQn11i+VjKZwkDUYhsGUKVPYsGED7u7u9O3bl0KFCpldVpptPn+McZGrWXriTwxutvWKOfLTLaw2TfKXwTUDL6QU5w8Hme60wvnz5/nqq6+4fv06ZcqU4bnnnnOaYAAQaPWmZ7nH6VqmNnOP3Lzn+XD0BcbsXsXEPWtpU+TmPc/Fs+U0u1SRTGXBggVs2LABFxcXunbt6lTBAKBKzoJUyVmQw9EXGB+5hjmHt7Htwgm6rZhGQb9guobVpl3RSni52efZLpK5ZaqRg+joaIYOHcrFixcpUKAAffr0cfpn0qcYKSw7uY9xkav54/yx1OX185ake3gEj+Us5FThxxlp5CDzW7lyJTNmzABuzs5aq1YtkytKvwvxV5m8dz1T9m0k+vrN56oEWX3oXKo6nUtVJ8jz0TznRW5y9pGDTBMOEhIS+Pzzzzlx4gQ5cuTgrbfeynQNeOtfJxgXuYrFx/emDhuWy56X7mERNC1QRvc8PyIKB5nbtm3bmDBhAoZh0LJlS1q0aGF2SXYVeyORmQe3MHHPWk5euwKAp6s7TxWrxMtlalHI//4TR8mDUzhwAElJSXz11Vf8+eef+Pn50b9/f3LkyGF2WY/MkeiLfL335j3PiclJAOT3DeLlMrVoX6wy3u4e99mCPAiFg8zr4MGDDB8+nKSkJGrXrs0zzzyTaUfiklKS+fVYJOMiV7Pr0mkALFhoWqAM3cMjqJgjv8kVZi4KByZLSUlh8uTJ/PHHH1itVvr06UPBggXNLitDXEq4xrd/3rzn+UpiHHDzOe2d/r7nObvXneeYlwejcJA5nTlzhmHDhhEXF0e5cuXo1q1blpjl0jAM1p87wrjdq1lxen/q8mo5C9I9LIL6+Upqkjg7cPZw4PQXJM6bN48//vgj9SKirBIMAII9felboSGvhtfhx4NbmbBnDcevXmbEzt8ZF7madkUr0bVMbQoHaNhQ5J+uXLnCyJEjiYuLo3DhwnTp0iVLBAO4+ZyVmrmKUDNXEfZdOcf4yNXMP7KTTeePsen8MYoG5KBbWARtilTQJHFZmFOPHCxfvpwff/wRgM6dO1O9enWTKzJXckoKi07sYdzu1ey4eBK4OWzYOH9pXgmPoFJIAZMrdE4aOchc4uLiGDZsGGfOnCE0NJQ333wTX9+sPcp2Njaab/auZ+r+jVy9kQhAiJcfL5auwbMlqpHN6m1yhc7H2UcOnDYcbNmyha+//hrDMGjdujVNmjQxuySHYRgGm84fZXzkGn47+Wfq8sohBegeFkGj/KU0bPgAFA4yjxs3bjBixAgOHjxItmzZeOuttwgODja7LIdx9XoC0w/8wdd71nE2LhoAbzcPni5ehZfL1CKvb6DJFToPhQMT7N+/n5EjR5KUlETdunXp0KFDpr2IKL0ORt2cF37u4e1cT0kGoLB/drqG1aZtkYp46p7n+7p1kPd8ZSbWdPwFlZgYx8ix7RUOTJKSksLEiRPZtm0bnp6evPnmm+TNm9fsshzSjZTk1Eni9l05B4CrxYUWhcJ5JSyCsOCMm9XWWdmrb4A5vcPp/nw8deoUY8aMISkpiYoVK9K+fXsFg3soli2Ez2q1ZUO7/rxWti4BHp4cibnI2+vn8disIYzYsZwrf0/gIpJZGYbBzJkz2bZtG25ubrz66qsKBvfg7uJK26IV+a1VL6Y2epHauYuSbKSw4MhOmvw0ig6Lv2bl6QM44d+WkkZOdbXJ5cuXGTVqFAkJCRQrVowXX3wxQ+dWd2Y5vf15u1ITXitbjx8ObGbinrWcjo1i2Pbf+Gr3SjoUuzlsmN8vyOxSRexuyZIlrFy5Erh5fVKJEiXMLchJWCwW6uYpTt08xYm8dJpxkWv4+egu1p49xNqzhygZGEr3sNr8p1A5PHTxYqbiNL9ZY2NjGTlyJFFRUeTOnZtXXnkFd3cNiT8oX3crXcrUYm3bN/mqTgfCgnITn3SDyX+up9acYbyyYjo7L54yu0wRu9mwYQPz5s0DoF27dlSpUsXkipxTWHAevqrTgXVt36RL6Zp4u3mw78o5eq+ZRY3ZQxm3ezVXryeYXabYiVOEg+vXrzN69GjOnj1LYGAgPXv2xMdHj/5MD3cXV54oXJ5F/3mdHxp3oU6e4qQYBj8f20Xzn7+i3aIJLD+5jxQjxexSRR5aZGQk3333HQANGzakQYMGJlfk/PL6BjKwWkv+eOpt3q7UmBAvP87FxfDxll+p+uMgPt78K2djo80uU9LJ4ceBkpOT+frrrzl8+DDe3t707NmTwEBdMWsvFouFWrmLUit3UfZePsv4yNUsOLKTDeeOsOHcEYpnC6FbWARPFC6ve57FqRw7dowJEyaQkpJC1apVadOmjdklZSrZrN68VrYeL5epzbzDNyeJOxj9F+MiV/P1nrU8UfjmJHGlghx3ymu5O4ceOTAMgx9++IGdO3fi5uZGjx49yJ07t9llZVqlg3IxIqI969u+RbcytfF1t3Ig6i/6rp1NjdlDGb1rJdGJ8WaXKXJfFy5c4KuvviIxMZFSpUrRqVMnXZ/0iFhd3ehQvArLW/fm2wadqJazEElGCrMPb6PhguE8u/Qb1p05pIsXnYxD/yn466+/snr1aiwWCy+99BJFixY1u6QsIbdvNt6v2pxe5eszbf8mvt67jvNxMQzauphRu1bQsXgVupSuRW7fbGaXKnKbmJgYRowYwdWrV8mXLx/du3fHzc2hW12m4GJxoUG+UjTIV4rtF04yLnI1i45HsvL0AVaePkB4cB66h0XQvGCYJolzAg4bpdeuXctPP/0EQIcOHahYsaLJFWU9/h6evBJehw1t3+LLWu0okS0n124kMmHPWmrMHkrP1TPZe/mM2WWKpEpISOCrr77iwoULZM+enddff93pp213RhVy5GN8vWdY3aYfnUo+hqerO7svnabHqhnUnvMZk/auI/bvJzGKY3LIcLB7926mTZsGQNOmTalbt665BWVxHq5utCtWiWVP9Oa7hi9QI7QwSUYKcw9vp9GCkXRcMonVpw9q2FBMlZyczIQJEzh+/Di+vr707NmTgIAAs8vK0gr6B/NJ9Sf446m36VuhAUFWH05eu8KATT9T9cfBDNm6hL/irppdptyBw421HT16lPHjx5OSkkL16tVp1aqV2SXJ3ywWC4/nLcHjeUuw6+Ipxkeu4edju1h95iCrzxykTFAuuoVF0LJQWdw1bCgZyDAMvv/+e/bs2YOHhwevvfYaOXPmNLss+VuQpw9vlG9A97A6zD60lfGRazh29RKjdq1gwp41tClSgW5lalM0W4jZpcrfHGrk4Pz584waNYobN24QFhbGc889p6cfOqiy2fMyuu7TrHvyTV4sVQMvN3f2XD5Lz9UzqTV7GBP3rOGahg0lgyxYsIANGzakzs5aqFAhs0uSO/Byc+e5ko+xqk1fJtR7loo58pOYnMSMA5upO+8LXlw2hT/OH9MopANwmHAQHR3NiBEjiI2NpWDBgrz88stZZgpVZ5bPL4j/PfYf/njqHd6q2Ijsnr6cjo3iwz8WUvXHQQzaspjzcTFmlymZ2IoVK1i0aBEAzz77LOHh4SZXJPfj6uJCs4JhLGj+CnObdadRvlIALD35J21+HUerhWP59VgkySl6zopZHOK0Qnx8PKNGjeLSpUuEhITw2muv6SIiJxNo9aZnucfpWqY2cw5vZ8KeNRyOvsDo3SuZuGcNrYtUoFtYbYpn01Cv2M+2bduYOXMmAP/5z3+oWbOmyRXJg7BYLFTNWZCqOQtyOPoC4yPXMOfwNrZdOEHXFVMp6BdMt7DatC1aCS9NEpehTB85SEpKYty4cZw8eRI/Pz969uyJn5+f2WXJQ/J0c+eZElVZ0foNvqn/PFVzFuR6SjIzD27h8Xlf0um3b9lw7oiGDSXdDh48yKRJkzAMg4iICJo1a2Z2SZIORQJyMLRmGza260/PsvUI8PDi2NVLvLNhPtV+HMwX25dxWZPEZRhTRw5SUlKYMmUK+/btw2q18vrrr5MjRw4zSxI7cbG40Ch/aRrlL83Wv04wLnIVi4/vZfmpfSw/tY9y2fPySlgETQqU0T3P8sDOnDmTOjtr+fLlefrpp3V9UiaRw8uPtyo1pkfZuvxwcAtf71nLyWtX+GLHMsbsXkX7YpV4uUxtCvoHm11qpmbqyMHcuXP5448/cHFxoXv37hQoUMDMcuQRqRSSn4mPP8eqNn15rkQ1rK5u7Lx4iu4rpxMx53O+/XMD8UnXzS5TnMTly5cZOXIkcXFxFClShJdeeklPP8yEfNytvFS6Jmue7MfoOk8THpyHhOQbTNm3kdpzPqPbimlsv3DS7DIzLdOOqGXLlvHbb78B0KlTJ0qXLm1WKZJBCgdkZ1CN1mxq9za9y9cn0OrNiWuXeW/jAqr+OJhh25ZyMf6a2WWKA4uNjWXUqFFcuXKFXLly0aNHDzw8PMwuSx4hNxdXWhUux68tX2Nmk5epl6cEBgYLj+2m5S+jefLX8fx2Yq8mibMzU04rbN68mVmzZgHQunVrHnvsMTPKEJNk9/KlX4WG9Aivw48HtzJhzxqOX73MiJ2/My5yNe2KVqJrmdoUDshudqniQG7cuMHYsWM5c+YM2bJl0+ysWYzFYqFmriLUzFWEfVfOMT5yNfOP7GTT+aNsOn+UYgEhdA2rTZsiFTRJnB1k+MjB/v37+fbbbwGoV68ejRs3zugSxEF4uXnQqVR1Vrfpx7h6z1A+ez4Sk5OYun8TdeZ+Tpfl37P1r+NmlykOICUlhW+++YaDBw/i6elJz549CQoKMrssMUnJwFC+rP0U69u+RfewCPzcrRyM/os3182h+qwhfLVrBVGJcWaX6dQyPBzs3LmTpKQkKlWqxFNPPaWLiARXFxdaFAzn5xavMrtpVxrkK4mBweITe2i1cCxPLBzL4uN7NGyYhUVFRXHkyBHc3Nx49dVXyZMnj9kliQPI5RPAe1Wa8cdT7/B+lWbk8g7gr/irDN66hKo/DmbApp85de2K2WU6JYuRwfeUGYbB+vXrqVq1Ku7uum9V7uxA1HkmRK5h7uHtXE9JBqCwf3a6htWmbZGKeGbgPc8xMTEEBATQ85WZWK3eD72dxMQ4Ro5tT3R0NP7+/nasMGu4fPkyp0+f1kOO5K6uJyfx09FdjItczb4r5wBwtbjQolA4r4RFEBaccaHSXn0DzOkdGR4ORB7E+bgYJv+5nu/3bST6egIA2T19eaFUdZ4v+RiBno/+nLPCgYhzMQyDVWcOMj5yNWvOHEpdXitXUbqHR1And7FHPmrt7OFAV22IQ8vp7c/blZrwWtl6/HBgMxP3rOV0bBTDtv/GV7tX0qFYFV4uU4v8fjr/LCI3WSwW6uYpTt08xYm8dJpxkWv4+egu1p49xNqzhygZGEr3sNr8p1A5PHTx4h3p5mBxCr7uVrqUqcXatm8yKqIDZYJyEZ90g8l/rqfWnGG8smI6Oy+eMrtMEXEwYcF5+KpOB9a1fZMupWvi7ebBvivn6L1mFjVmD2Xc7tVc/XtUUv6fwoE4FXcXV1oXKc/i//Tkh8ZdqJOnOCmGwc/HdtH8569ot2gCy0/u0+OZRcRGXt9ABlZryR9Pvc3blRoT4uXHubgYPt7yK1V/HMTHm3/lbGy02WU6DIUDcUoWi4VauYsyrdGLLG3ViyeLVMDN4sKGc0fotOxbpu7fZHaJIuKAslm9ea1sPTa068+wmk9SNCAHV28kMi5yNQ0XjCAxOcnsEh2CTraI0ysdlIsREe3pX7Exk/auY/7RnfynUDmzyxIRB2Z1dePp4lVoX6wSy0/uY1zkGspmz6MHKP1Nn4JkGrl9s/F+1ea8XbkJ7prMSUTSwMXiQsP8pWmYvzQ3/r5tWnRaQTKhzBIMxo4dS9myZfH398ff35/q1auzaNEis8sSybQyQ++wV99QOBBxUHnz5mXw4MFs2bKFLVu28Pjjj9OqVSv27Nljdmki4qDs1Td0WkHEQbVs2dLm608++YSxY8eyceNGypQpY1JVIuLI7NU3FA5EMlhMTIzN11arFavVes/3JCcnM2vWLGJjY6levfqjLE9EHNSD9o709A2dVhDJYPny5SMgICD1NWjQoLuuu3v3bnx9fbFarXTv3p158+ZRunTpDKxWRBxFWnuHPfqGRg5EMtjJkydtno9+r+RfokQJduzYQVRUFHPmzKFTp06sWrVKAUEkC0pr77BH31A4EMlgt64iTgsPDw+KFi0KQOXKldm8eTMjRoxg/Pjxj7JEEXFAae0d9ugbOq0g4kQMwyAxMdHsMkTEiTxM39DIgYiDevfdd2natCn58uXj6tWr/PDDD6xcuZLFixebXZqIOCh79Q2FAxEHdf78eZ577jnOnj1LQEAAZcuWZfHixTRs2NDs0kTEQdmrbygciDioSZMmmV2CiDgZe/UNXXMgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbOhWRpE06hTVAV8Py0O//9p1g5F2rEdEHF96+waY0zs0ciAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQcVCDBg2iSpUq+Pn5ERISwhNPPMH+/fvNLktEHJi9+obCgYiDWrVqFT169GDjxo389ttvJCUl0ahRI2JjY80uTUQclL36htsjqk9E0mnx4sU2X0+ePJmQkBC2bt1KRESESVWJiCOzV99QOBDJYDExMTZfW61WrFbrfd8XHR0NQFBQ0COpS0Qc28P0joftGzqtIJLB8uXLR0BAQOpr0KBB932PYRj06dOHWrVqERYWlgFVioijedDekZ6+oZEDkQx28uRJ/P39U79Oy6jBa6+9xq5du1i7du2jLE1EHNiD9o709A2FA5EM5u/vb3OA38/rr7/OTz/9xOrVq8mbN+8jrExEHNmD9I709g2FAxEHZRgGr7/+OvPmzWPlypUUKlTI7JJExMHZq28oHIg4qB49ejB9+nQWLFiAn58f586dAyAgIAAvLy+TqxMRR2SvvqELEkUc1NixY4mOjqZu3brkypUr9TVz5kyzSxMRB2WvvqGRA5E0alGrFy5e97948G5S4hNhxvA0r28YxkPvS0QcQ3r7BjxY77BX39DIgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIiIiYkPhQERERGwoHIiIiIgNhQMRERGxoXAgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2FA4EBERERsKByIiImJD4UBERERsKByIiIiIDYUDERERsaFwICIiIjYUDkRERMSGwoGIiIjYUDgQERERGwoHIg5q9erVtGzZkty5c2OxWJg/f77ZJYmIE7BH71A4EHFQsbGxlCtXjq+++srsUkTEidijd7jZsR4RsaOmTZvStGlTs8sQESdjj96hcCCSRkZ8IinpfD9ATEyMzXKr1YrVak3HlkXEUaW3b9zaBmRs71A4ELkPDw8PQkNDOddvbLq35evrS758+WyWDRgwgIEDB6Z72yLiOOzZNyDje4fCgch9eHp6cvToUa5fv57ubRmGgcVisVmmUQORzMeefQMyvncoHIikgaenJ56enmaXISJOxJn7hu5WEBERERsaORBxUNeuXePQoUOpXx89epQdO3YQFBRE/vz5TaxMRByZPXqHxTAM41EVKCIPb+XKldSrV++25Z06deLbb7/N+IJExCnYo3coHIiIiIgNXXMgIiIiNhQORERExIbCgYiIiNhQOBAREREbCgciIiJiQ+FAREREbCgciIiIiA2FAxEREbGhcCAiIiI2FA5ERETEhsKBiIiI2Pg/glnwLFOvXOIAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [np.float64(70.04113695824684)]\n", - "(8, 1) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 3\n", - "Adjacent strokes (list): [1, 0, 1, 0]\n", - "Adjacent strokes (uniques): {0, 1}\n", - "Checking edge: (0, 1)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "Interior angles found: [np.float64(89.87471285219927), np.float64(89.74560192447649)]\n", - "Interior angles found: [np.float64(89.75267804978043), np.float64(89.88178897750322)]\n", - "Final angles found: [np.float64(89.74560192447649), np.float64(89.75267804978043)]\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [np.float64(89.74560192447649), np.float64(89.75267804978043)]\n", - "(0, 1) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 4\n", - "Adjacent strokes (list): [2, 6, 2, 6]\n", - "Adjacent strokes (uniques): {2, 6}\n", - "Checking edge: (2, 6)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "Interior angles found: [np.float64(85.21096368451747), np.float64(84.23886881283048)]\n", - "Interior angles found: [np.float64(81.14186114900058), np.float64(80.16976627731358)]\n", - "Final angles found: [np.float64(84.23886881283048), np.float64(80.16976627731358)]\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [np.float64(84.23886881283048), np.float64(80.16976627731358)]\n", - "(2, 6) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 5\n", - "Adjacent strokes (list): [3, 3, 1, 1]\n", - "Adjacent strokes (uniques): {1, 3}\n", - "Checking edge: (1, 3)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "Interior angles found: [np.float64(89.53084497276808), np.float64(89.57504791798526)]\n", - "Interior angles found: [np.float64(89.58581817377714), np.float64(89.63002111899432)]\n", - "Final angles found: [np.float64(89.53084497276808), np.float64(89.58581817377714)]\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [np.float64(89.53084497276808), np.float64(89.58581817377714)]\n", - "(1, 3) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 6\n", - "Adjacent strokes (list): [3, 3, 4, 4]\n", - "Adjacent strokes (uniques): {3, 4}\n", - "Checking edge: (3, 4)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "Interior angles found: [np.float64(89.83847705650136), np.float64(88.78833801117518)]\n", - "Interior angles found: [np.float64(89.75197989966416), np.float64(89.19788105500966)]\n", - "Final angles found: [np.float64(88.78833801117518), np.float64(89.19788105500966)]\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [np.float64(88.78833801117518), np.float64(89.19788105500966)]\n", - "(3, 4) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 7\n", - "Adjacent strokes (list): [3]\n", - "Adjacent strokes (uniques): {3}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 8\n", - "Adjacent strokes (list): [4]\n", - "Adjacent strokes (uniques): {4}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 9\n", - "Adjacent strokes (list): [4, 7, 4]\n", - "Adjacent strokes (uniques): {4, 7}\n", - "Checking edge: (4, 7)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [np.float64(78.26155769686821)]\n", - "(4, 7) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 10\n", - "Adjacent strokes (list): [4, 0, 4, 0]\n", - "Adjacent strokes (uniques): {0, 4}\n", - "Checking edge: (0, 4)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "Interior angles found: [np.float64(89.70671191496507), np.float64(89.56623033507175)]\n", - "Interior angles found: [np.float64(89.84379058832397), np.float64(89.42915166171285)]\n", - "Final angles found: [np.float64(89.56623033507175), np.float64(89.42915166171285)]\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [np.float64(89.56623033507175), np.float64(89.42915166171285)]\n", - "(0, 4) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 11\n", - "Adjacent strokes (list): [4, 5, 4]\n", - "Adjacent strokes (uniques): {4, 5}\n", - "Checking edge: (4, 5)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([2, 1])\n", - "angles: [np.float64(87.60977577529626)]\n", - "(4, 5) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 12\n", - "Adjacent strokes (list): [5]\n", - "Adjacent strokes (uniques): {5}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 13\n", - "Adjacent strokes (list): [2, 6, 2, 6]\n", - "Adjacent strokes (uniques): {2, 6}\n", - "Checking edge: (2, 6)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "Interior angles found: [np.float64(47.16443370903167), np.float64(48.92275878691167)]\n", - "Interior angles found: [np.float64(59.79419820769666), np.float64(61.55252328557668)]\n", - "Final angles found: [np.float64(47.16443370903167), np.float64(59.79419820769666)]\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [np.float64(47.16443370903167), np.float64(59.79419820769666)]\n", - "(2, 6) already in graph, angles = [np.float64(84.23886881283048), np.float64(80.16976627731358)]\n", - "(2, 6) already in graph, angles updated = [np.float64(84.23886881283048), np.float64(80.16976627731358), np.float64(47.16443370903167), np.float64(59.79419820769666)]\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 14\n", - "Adjacent strokes (list): [4, 6, 6, 4]\n", - "Adjacent strokes (uniques): {4, 6}\n", - "Checking edge: (4, 6)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 4\n", - "Interior angles found: [np.float64(87.26341801197296), np.float64(86.2834611843536)]\n", - "Interior angles found: [np.float64(89.6026063905527), np.float64(88.62264956293333)]\n", - "Final angles found: [np.float64(86.2834611843536), np.float64(88.62264956293333)]\n", - "connectivity: 2\n", - "Counter values: dict_values([2, 2])\n", - "angles: [np.float64(86.2834611843536), np.float64(88.62264956293333)]\n", - "(4, 6) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 15\n", - "Adjacent strokes (list): [4]\n", - "Adjacent strokes (uniques): {4}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 16\n", - "Adjacent strokes (list): [1, 6, 6]\n", - "Adjacent strokes (uniques): {1, 6}\n", - "Checking edge: (1, 6)\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAAGxCAYAAACz7cW9AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAAQClJREFUeJzt3Xl4VNX9P/D3ZJvJvu97wi4BKiACiiICIvDFJbaiVbTar61oq+LPra1gtQWXWlArVosKKIILRZFFRRaxggUtiqhAIDskkAUSskyW+fz+oDPfGbLNne3emXm/nifPY4abmU8mznmfe8895+hEREBERESqClC7ACIiImIgExERaQIDmYiISAMYyERERBrAQCYiItIABjIREZEGMJCJiIg0gIFMRESkAQxkIiIiDXA4kJ977jnodDoMHTq0x2N0Oh0WLFhg+X779u3Q6XTYvn27oy9rsXHjRpvndqXXX38dOp0Oe/fudcvzu9qqVauwePFitcvowpV/b7PFixfjmmuuQW5uLnQ6HS699NJej3///fdxySWXICoqCuHh4TjvvPPw8ssvu6weIiJXcTiQX331VQDAgQMH8OWXX7qsIHtt3LgRjz32mMdfV4u0Gsju8NJLL6G0tBSXXXYZEhMTez120aJFuOaaazB06FC8/fbb+OCDD3DnnXeira3NQ9USEdkvyJEf2rt3L7755htMnz4dGzZswLJlyzBmzBhX1+YyIoLW1laEhoaqXQo56fvvv0dAwNl+ZG9XZ7766iv87ne/w8KFC/HAAw9YHp80aZLbayQicoRDZ8jLli0DcPYMZNy4cVi9ejWam5tdVlRzczPuv/9+5ObmwmAwIC4uDqNGjcJbb70FALjlllvwt7/9DcDZy+Lmr5KSEstjd911F1566SUMHjwYer0ey5cvBwB8/vnnmDRpEiIjIxEWFoZx48Zhw4YNfdZ0/PhxjBw5Ev3798fhw4cBAA0NDZY6Q0JCkJ6ejnvuuQdNTU02P/vOO+9gzJgxiI6ORlhYGPLy8vCLX/yiz9f829/+hgkTJiApKQnh4eEoKCjAU089hfb2dssxl156KTZs2IDS0lKb96I3OTk5mDFjBjZv3ozzzz8foaGhGDRokOWqh7XvvvsOs2bNQmxsLAwGA0aMGGF5L639+OOPuOKKKxAWFoaEhAT86le/QmNjY7evv2XLFkyaNAlRUVEICwvD+PHj8emnn/b5fgCwhHFfXnjhBej1etx99912HU9EpDpRqLm5WaKjo2X06NEiIvKPf/xDAMjrr7/e5VgAMn/+fMv327ZtEwCybdu2Xl/jjjvukLCwMHn22Wdl27Zt8uGHH8qiRYvk+eefFxGRoqIiKSwsFACya9cuy1dra6vlddPT02XYsGGyatUq2bp1q3z33Xeyfft2CQ4OlpEjR8qaNWtk3bp1MmXKFNHpdLJ69WrL67/22msCQPbs2SMiIvv375fMzEwZO3asnDx5UkREmpqaZMSIEZKQkCDPPvusbNmyRZYsWSLR0dFy2WWXiclkEhGRL774QnQ6nVx//fWyceNG2bp1q7z22mty00039fle33vvvbJ06VLZvHmzbN26Vf76179KQkKC3HrrrZZjDhw4IOPHj5eUlBSb96I32dnZkpGRIUOGDJEVK1bIRx99JNddd50AkB07dliO+/HHHyUyMlLy8/NlxYoVsmHDBpk9e7YAkCeffNJyXFVVlSQlJUl6erq89tprsnHjRrnxxhslKyury9975cqVotPp5KqrrpK1a9fK+vXrZcaMGRIYGChbtmzp8z2xdt5558kll1zS7b/l5eXJ+eefLytXrpQBAwZIQECApKeny4MPPihGo1HR6xAReYLiQF6xYoUAkJdeeklERBobGyUiIkIuvvjirk/uYCAPHTpUrrrqql6PmTt3rvTUnwAg0dHRUldXZ/P4hRdeKElJSdLY2Gh5rKOjQ4YOHSoZGRmWELUO5E8++USioqKksLBQWlpaLD+3cOFCCQgIsIS22bvvvisAZOPGjSIi8swzzwgAOXXqVK+/T186Ozulvb1dVqxYIYGBgTa/2/Tp0yU7O9vu58rOzhaDwSClpaWWx1paWiQuLk7uuOMOy2PXX3+96PV6KSsrs/n5adOmSVhYmOV3evDBB0Wn08m+fftsjps8ebLN37upqUni4uJk5syZXX634cOHywUXXGD37yDSeyDr9XqJjIyU2NhYeeGFF2Tr1q3yu9/9TgIDA+WGG25Q9DpERJ6g+JL1smXLEBoaiuuvvx4AEBERgeuuuw47d+60XMp11gUXXIBNmzbhoYcewvbt29HS0qL4OS677DLExsZavm9qasKXX36JwsJCREREWB4PDAzETTfdhIqKChw8eNDmOZYvX44rr7wSt99+O95++20YDAbLv3344YcYOnQoRowYgY6ODsvX1KlTbe4sHj16NADgpz/9Kd5++21UVlba/Tv85z//wf/8z/8gPj4egYGBCA4Oxs0334zOzk4cOnRI8XtibcSIEcjKyrJ8bzAYMGDAAJSWlloe27p1KyZNmoTMzEybn73lllvQ3NyMXbt2AQC2bduG8847D8OHD7c57oYbbrD5/osvvkBdXR3mzJlj856ZTCZcccUV2LNnT5fL/Y4ymUxobGzEiy++iLlz52LixIl44okncPfdd2PVqlUoKipyyesQEbmKokAuKirCZ599hunTp0NEcOrUKZw6dQqFhYUA0O0YpCOee+45PPjgg1i3bh0mTpyIuLg4XHXVVYoCPzU11eb7+vp6iEiXxwEgLS0NAFBbW2vz+OrVqxEaGorbb7+9y7hsdXU1vv32WwQHB9t8RUZGQkRQU1MDAJgwYQLWrVuHjo4O3HzzzcjIyMDQoUMt4+E9KSsrw8UXX4zKykosWbIEO3fuxJ49eyxj5450UqzFx8d3eUyv19s8b21trV3vV21tLVJSUrocd+5j1dXVAIDCwsIu79uTTz4JEUFdXZ3jv5QV8+83depUm8enTZsGAPj6669d8jpERK6i6C7rV199FSKCd999F++++26Xf1++fDmeeOIJBAYGOlVUeHg4HnvsMTz22GOorq62nC3PnDkTP/74o13PcW6AxsbGIiAgAMePH+9y7LFjxwAACQkJNo+/+eab+MMf/oBLLrkEH3/8MUaMGGH5t4SEBISGhvbYCbF+rlmzZmHWrFkwGo3YvXs3Fi5ciBtuuAE5OTkYO3Zstz+/bt06NDU1Ye3atcjOzrY8vm/fvl5/b1eKj4+36/2Kj49HVVVVl+POfcx8/PPPP48LL7yw29dMTk52qmazYcOGdVuTiACw/+YwIiJPsbtV6uzsxPLly5Gfn49t27Z1+Zo3bx6OHz+OTZs2ubTA5ORk3HLLLZg9ezYOHjxouZtbr9cDsP9MMTw8HGPGjMHatWttfsZkMuGNN95ARkYGBgwYYPMzcXFx2LJlCwYPHoyJEydi9+7dln+bMWMGjhw5gvj4eIwaNarLV05OTpca9Ho9LrnkEjz55JMAzl6S7om5Q2H+PYGzYfLKK690+7zOnjF3Z9KkSdi6daslgM1WrFiBsLAwS6hOnDgRBw4cwDfffGNz3KpVq2y+Hz9+PGJiYvD99993+56NGjUKISEhLqn92muvBYAu/z9u3LgRAQEBlqEEIiKtsPsMedOmTTh27BiefPLJbldHGjp0KF544QUsW7YMM2bMcKqoMWPGYMaMGRg2bBhiY2Pxww8/YOXKlRg7dizCwsIAAAUFBQCAJ598EtOmTUNgYCCGDRvWa4O+cOFCTJ48GRMnTsT999+PkJAQvPjii/juu+/w1ltvdTtdKDIyEps3b8Y111yDyZMn44MPPsDEiRNxzz334L333sOECRNw7733YtiwYTCZTCgrK8PHH3+MefPmYcyYMXj00UdRUVGBSZMmISMjA6dOncKSJUsQHByMSy65pMdaJ0+ejJCQEMyePRsPPPAAWltbsXTpUtTX13c5tqCgAGvXrsXSpUsxcuRIBAQEYNSoUUrf9i7mz5+PDz/8EBMnTsSjjz6KuLg4vPnmm9iwYQOeeuopREdHAwDuuecevPrqq5g+fTqeeOIJJCcn48033+xyNSMiIgLPP/885syZg7q6OhQWFiIpKQknT57EN998g5MnT2Lp0qW91rR3717L9LaGhgbLFRvg7Hi9+WrCrbfeir///e+48847UVNTgyFDhmDLli3429/+hjvvvNPmqgMRkSbYe/fXVVddJSEhIXLixIkej7n++uslKChIqqqqRMTxu6wfeughGTVqlMTGxoper5e8vDy59957paamxnKM0WiU22+/XRITE0Wn0wkAKS4utrzu3Llzu33unTt3ymWXXSbh4eESGhoqF154oaxfv97mmHOnPZlf79prrxWDwSAbNmwQEZEzZ87I73//exk4cKCEhIRIdHS0FBQUyL333mt5Dz788EOZNm2apKenS0hIiCQlJcmVV14pO3fu7PU9EBFZv369DB8+XAwGg6Snp8v/+3//TzZt2tTlPayrq5PCwkKJiYmxvBe9yc7OlunTp3d5/JJLLuly1/L+/ftl5syZEh0dLSEhITJ8+HB57bXXuvzs999/L5MnTxaDwSBxcXFy2223yfvvv9/t33vHjh0yffp0iYuLk+DgYElPT5fp06fLO++80+d7MmfOHAHQ7de5ddXW1sodd9whycnJEhwcLAMGDJCnn35aOjs7+3wdIiJP04n8d1CNiIiIVMM7W4iIiDSAgUxERKQBDGQiIiINYCATkWJffvklrr76amRlZUGv1yM5ORljx47FvHnzbI578cUX8frrr7ulhltuucVm1T017dy5E3q93malu88//xy33347Ro4cCb1eb7MBjrP62ue7vb0d+fn5btmW9c9//jPWrVvn8ud11oIFC/rcWEeJxsZGPPDAA5gyZQoSExOh0+mwYMGCHo9vb2/Hs88+i4KCAoSGhiImJgbjxo3DF198YfdrMpCJSJENGzZg3LhxaGhowFNPPYWPP/4YS5Yswfjx47FmzRqbY90ZyFohIrjnnnvwy1/+0mY63aeffootW7YgKysL48aNc9nr2bPPd3BwMB599FH88Y9/7LICobO0GsiuVltbi5dffhlGoxFXXXVVr8d2dnbi6quvxh//+EfMnj0bmzZtwptvvokrrrhC2XLAKt/lTUReZsKECZKfny/t7e1d/u3cKWW9bQByrra2tm6fsydz5syR8PBwu493l40bNwoA+fHHH20et34vnn76aZupmY7au3evBAQE2Oy21hOj0ShxcXHypz/9yanXPFd4eLjMmTPHpc/pCvPnz+9zyqcSJpPJsuHQyZMnu0zjtfbXv/5VAgIC+txpry88QyYiRWpra5GQkICgoK7rClkvSZqTk4MDBw5gx44dln26zSvYbd++HTqdDitXrsS8efOQnp4OvV5v2fTj1VdfxfDhwy37oV999dX44Ycf+qztX//6FxISEjBjxgzLmcnhw4dxww03ICkpCXq9HoMHD7asCW9mMpnwxBNPYODAgZbLjcOGDcOSJUv6fM2lS5di9OjRGDhwYI/vhaso2ec7JCQEP/vZz/Dyyy9bloztSWtrK+bNm4cRI0YgOjoacXFxGDt2LN5//32b43Q6HZqamrB8+XLL37S7haLMSkpKoNPp8Mwzz+DZZ59Fbm4uIiIiMHbsWJuVD80++OADywJQkZGRmDx5smUTG2sbNmzAiBEjoNfrkZubi2eeeabb1xcRvPjiixgxYgRCQ0MRGxuLwsJCHD16tNf3w/y72nsJfMmSJZgwYUKPSwLbzak4JyK/c/vttwsAufvuu2X37t3S1tbW7XFff/215OXlyU9+8hPLPt1ff/21iPzfIkHp6elSWFgoH3zwgXz44YdSW1srf/7znwWAzJ49WzZs2CArVqyQvLw8iY6OlkOHDlme/9wz5DVr1oher5df//rX0tHRISJn9ws3L9izYsUK+fjjj2XevHkSEBAgCxYssPzswoULJTAwUObPny+ffvqpbN68WRYvXmxzTHeMRqOEhobKAw880OtxrjpDVrrP95o1awSAfPvtt70+76lTp+SWW26RlStXytatW2Xz5s1y//33S0BAgCxfvtxy3K5duyQ0NFSuvPJKy9/0wIEDPT5vcXGxAJCcnBy54oorZN26dbJu3TopKCiQ2NhYm21p33zzTQEgU6ZMkXXr1smaNWtk5MiREhISYrOQ0pYtWyQwMFAuuugiWbt2rbzzzjsyevRoy/7r1n75y19KcHCwzJs3TzZv3iyrVq2SQYMGSXJysmXxJnv0doZcVlZm+Tw8/PDDkpSUJIGBgTJkyBB5/fXX7X4NEQf2QyYi/1ZTUyMXXXSRZYW04OBgGTdunCxcuNBmr3GRni9ZmwN5woQJNo/X19dbGnxrZWVlotfrbfaytg7kRYsWSWBgYJdLuVOnTpWMjAw5ffq0zeN33XWXGAwGy77iM2bMkBEjRih7I0Tkyy+/FACyevXqXo9zVSAr3ef78OHDAkCWLl2q6HU6Ojqkvb1dbrvtNvnJT35i829KLlmbA7mgoMDSSRIR+fe//y0A5K233hKRs5f309LSpKCgwOZSf2NjoyQlJcm4ceMsj40ZM0bS0tJs9qdvaGiQuLg4m0DetWuXAJC//OUvNjWVl5fb1Ymy1lsgm18nKipKhgwZIm+//bZ89NFHUlhYKADk5Zdftvt1eMmaiBSJj4+3bAe6aNEizJo1C4cOHcLDDz+MgoICy9aj9jBvAmK2a9cutLS04JZbbrF5PDMzE5dddhk+/fRTm8dFBHfccQfmz5+PVatW4YEHHrD8W2trKz799FNcffXVCAsLs9mD+8orr0Rra6vlsukFF1yAb775BnfeeSc++ugjNDQ02FW/eeOVpKQku39nZyjd59tclz37sL/zzjsYP348IiIiEBQUhODgYCxbtsyuoYK+TJ8+3WYXwGHDhgGA5a70gwcP4tixY7jppptsLvVHRETg2muvxe7du9Hc3Iympibs2bMH11xzjc3+9JGRkZg5c6bNa3744YfQ6XT4+c9/bvO3T0lJwfDhwy171jvLZDIBOPv/28aNG3HddddhypQpePvtt3H++efjj3/8o93PxUAmIoeMGjUKDz74IN555x0cO3YM9957L0pKSvDUU0/Z/Rzn7rdtviO4p324z71juK2tDWvWrMF5551n2eva+rk6Ojrw/PPPd9l/+8orrwQAS+fh4YcfxjPPPIPdu3dj2rRpiI+Px6RJk7B3795e6zfvsmYdDu6kdJ9vc1197Qa3du1a/PSnP0V6ejreeOMN7Nq1C3v27MEvfvELtLa2uqxus3N36+vr724ymVBfX4/6+nqYTCa7918XESQnJ3f5++/evVtRx9Ge323QoEE2d9nrdDpMnToVFRUVOHHihF3PpWg/ZCKi7gQHB2P+/Pn461//iu+++87unzv3phlz49bTPtzn7lmu1+uxbds2TJ06FZdffjk2b96M2NhYAGf3QA8MDMRNN92EuXPndvv6ubm5AICgoCDcd999uO+++3Dq1Cls2bIFjzzyCKZOnYry8nLLLnPnMtdTV1dn9+/sDKX7fJvrOvd9O9cbb7yB3NxcrFmzxuZvYjQanS3ZLn393QMCAhAbGwsRgU6ns3v/dZ1OZ5kjfq7uHnNEfn5+j/9/9PR36QnPkIlIke4aTQCWS5tpaWmWx5Tu1T127FiEhobijTfesHm8oqICW7duxaRJk7r8zE9+8hPs2LEDFRUVuPTSSy1nI2FhYZg4cSL+85//YNiwYd3uv33umRsAxMTEoLCwEHPnzkVdXV2vi3kMHjwYAHDkyBG7f0dnKN3n23w38ZAhQ3p9Xp1Oh5CQEJswrqqq6nKXNeCe/dcHDhyI9PR0rFq1yuaO8KamJrz33nuWO6/Dw8NxwQUXYO3atTZn7o2NjVi/fr3Nc86YMQMigsrKym7/9uYtfJ0VFBSEWbNm4YcffrD5f0VEsHnzZuTn5/fZIbI8l0sqIiK/MXXqVGRkZGDmzJkYNGgQTCYT9u3bh7/85S+IiIjAb3/7W8uxBQUFWL16NdasWYO8vDwYDIZeG8KYmBj84Q9/wCOPPIKbb74Zs2fPRm1tLR577DEYDAbMnz+/258bPHgwdu7cicsvvxwTJkzAli1bkJGRgSVLluCiiy7CxRdfjF//+tfIyclBY2MjioqKsH79emzduhUAMHPmTAwdOhSjRo1CYmIiSktLsXjxYmRnZ6N///491puRkYG8vDzs3r0bv/nNb2z+7eTJk9ixYwcAYP/+/QDOBmliYiISExNt9kO/9NJLsWPHjj6nJynd53v37t0IDAzEhAkTen3eGTNmYO3atbjzzjtRWFiI8vJyPP7440hNTcXhw4dtji0oKMD27duxfv16pKamIjIyssuUL6UCAgLw1FNP4cYbb8SMGTNwxx13wGg04umnn8apU6ewaNEiy7GPP/44rrjiCkyePBnz5s1DZ2cnnnzySYSHh9tcqRg/fjz+93//F7feeiv27t2LCRMmIDw8HMePH8fnn3+OgoIC/PrXv+61rk2bNqGpqQmNjY0AgO+//96y//qVV15pOTN+/PHHsWnTJlxxxRVYsGABoqKi8I9//APffPMN3n77bfvfCLtv/yIikrNTaW644Qbp37+/RERESHBwsGRlZclNN90k33//vc2xJSUlMmXKFImMjBQAkp2dLSL/d5d1T3tg/+Mf/5Bhw4ZZ9hmfNWtWl+k13S0MUlFRIYMGDZKcnBw5cuSIiJy90/cXv/iFpKenS3BwsCQmJsq4cePkiSeesPzcX/7yFxk3bpwkJCRISEiIZGVlyW233SYlJSV9vh9/+MMfJDY2VlpbW20eN/+O3X2de+f5yJEjJSUlpc/XElG2z/fFF18sM2fOtOt5Fy1aJDk5OaLX62Xw4MHyyiuvdLvYxr59+2T8+PESFhbW7e9izXyX9dNPP93l39DNXcvr1q2TMWPGiMFgkPDwcJk0aZL861//6vKzH3zwgeX/j6ysLFm0aFGPC4O8+uqrMmbMGAkPD5fQ0FDJz8+Xm2++Wfbu3dvne5Kdnd3j3/DcO+b3798v06dPl8jISDEYDHLhhRfK+vXr+3wNa9wPmYjICceOHUNubi5WrFiBn/3sZ4p/vrGxEXFxcVi8eHGPY92OOHLkCPr374+PPvoIkydPdtnzkvswkImInPTggw9i06ZN2Ldvn+IVujZs2IC5c+fi0KFDCAkJcVlNt956KyoqKvDJJ5+47DnJvXhTFxGRk37/+9/j2muvtWu+77mmT5+OkpISl4ZxR0cH8vPzuywRStrGQCa/UFlZiZ///OeIj49HWFgYRowYga+++krtsshHREZGYv78+cjMzFS7FABn7/z9/e9/jwEDBqhditfzZNvBu6zJ59XX12P8+PGYOHEiNm3ahKSkJBw5cgQxMTFql0ZEGubptoNjyOTzHnroIfzrX//Czp071S6FiLyIp9sOBjJ5VGtrq81G6s6Q/67aY02v13dZgWfIkCGWJex27NiB9PR03HnnnfjlL3/pkjqIyP1c1XbY224AKrQdiiZJETmhpaVFQkNDe5zXp/QrIiKiy2Pd7cai1+tFr9fLww8/LF9//bW89NJLYjAYbLaVIyLtcmXbYW+7IeL5toNnyOQxDQ0NiI6Oxg033OD0HaVtbW1YtWoVysvLERUVZXm8u55uSEgIRo0ahS+++MLy2G9+8xvs2bOn283PiUhbXNV2KGk3AM+3HbypizwuJCTEZVM8oqKibD5Y3UlNTe2ylu/gwYPx3nvvuaQGIvIMV7Ud9rQbgOfbDk57Ip83fvx4HDx40OaxQ4cOdVn3l4jImqfbDgYy+bx7770Xu3fvxp///GcUFRVh1apVePnll126TCER+R5Ptx0MZPJ5o0ePxj//+U+89dZbGDp0KB5//HEsXrwYN954o9qlEZGGebrt4Bgy+YUZM2ZgxowZapdBRF7Gk20Hz5CJiIg0gIFMRESkAQxkIiIiDWAgExERaQADmYiISAMYyERERBrAQCYiItIABjIREZEGMJCJiIg0gIFMdqutrcXnn3+OkydPql0KEXmRr776CgcOHIDRaFS7FE1jIJPdvv32W6xcuRJvvvmm2qUQkRd577338Nxzz6GoqEjtUjSNgUx2O3z4MABgwIABKldCRN6ipqYGtbW1CAgIQH5+vtrlaBoDmewiIjh06BAABjIR2c/ckc/OzobBYFC5Gm1jIJNdjh8/jsbGRgQHByMnJ0ftcojISxw8eBAAO/L2YCCTXcxnx/n5+QgK4q6dRGQfXlmzHwOZ7MIPFREpVVtbaxk/7tevn9rlaB4DmfpkPX48cOBAlashIm9hbjc4fmwfBjL1qaqqyjJ+nJ2drXY5ROQlzIHcv39/lSvxDgxk6pP5Q5WXl4fg4GCVqyEib8Era8owkKlP/FARkVJ1dXWoqanh/GMFGMjUK84/JiJHmNuNrKwshIaGqlyNd2AgU6+qq6vR0NDA+cdEpAg78soxkKlX5kn9HD8mIiW4IIhyDGTqFdevJiKlzOPHOp2O848VYCBTj0SEvVwiUsx6/jHHj+3HQKYemcePg4KCkJubq3Y5ROQlOP/YMQxk6hHnHxORI8xDXZwqqQwDmXrEuySJSKn6+nqcOHGC48cOYCBTt7h+NRE5gvOPHcdApm6dOHECp0+f5vgxESnCK2uOYyBTtzh+TESOYCA7joFM3eKHioiU4vixcxjI1AXXryYiR5jvrs7MzERYWJjK1XgfBjJ1ceLECZw6dYrjx0SkCBcScg4Dmbow93Jzc3MREhKicjVE5C241K5zGMjUBXu5RKTUqVOnUF1dDZ1OxxW6HMRAJhucf0xEjjC3Gxw/dhwDmWycPHmS48dEpBjXr3YeA5lsmD9UOTk5HD8mIrvxyprzgtQugLTFEx+qi6I/QZjeub5gs9GE111TDhE56fTp05bxY3fOP3a27dB6u8EzZLLg/GMicoS53cjIyEB4eLjK1XgvBjJZ1NTUoL6+HoGBgcjLy1O7HCLyEuzIuwYDmSzMHyrOPyYiJRjIrsFAJgt+qIhIqdOnT6Oqqorzj12AgUwAzo4fc0EQIlLK3JFPT0/n+LGTGMgEgOPHROQYXllzHQYyAbCdf6zX61Wuhoi8hXn9as4/dh4DmQCwl0tEyjU0NOD48eMcP3YRBjJx/jEROYTjx67FQCbU1tairq4OAQEByM/PV7scIvIS7Mi7FgOZbOYfc/yYiOzFQHYtBjLxQ0VEipnHjwHu8OQqDGRiIBORYua7q9PT0xEREaFyNb6BgeznampqUFtbi4CAAM4/JiK7cSEh12Mg+zlzLzcnJwcGg0HlaojIW5jbDgay6zCQ/Rx7uUSkVENDA44dOwaAbYcrMZD9HMePiUgp89lxWloax49diIHsx2pray3jx5x/TET2YkfePRjIfsz8ocrOzub4MRHZzdx2cP1q12Ig+zF+qIhIqcbGRsv4MecfuxYD2Y+ZA5kfKiKyl/X4cWRkpMrV+BYGsp+qq6tDTU0NAgIC0K9fP7XLISIvwfFj92Eg+ymOHxORIxjI7sNA9lP+9KFasGABdDqdzVdKSoraZRF5nTNnzqCyshKAfwx1ebrtCHLbM5Om+duCIOeddx62bNli+T4wMFDFaoi8k7kjn5qaiqioKJWr8QxPth0MZD9kPX7sL/OPg4KCeFZM5CR/XC7Tk20HL1n7IXMvNysrC6GhoSpX45yGhgabL6PR2O1xhw8fRlpaGnJzc3H99dfj6NGjHq6UyPv5ylRJe9sNwLNtBwPZD/nS+HFmZiaio6MtXwsXLuxyzJgxY7BixQp89NFHeOWVV1BVVYVx48ahtrZWhYqJvNOZM2dQUVEBwPvHj+1pNwDPtx28ZO2HfCmQy8vLbcay9Hp9l2OmTZtm+e+CggKMHTsW+fn5WL58Oe677z6P1Enk7cyXq31h/NiedgPwfNvBQPYz9fX1OHnyJHQ6nU/MP46KilLcOISHh6OgoMDSwBBR33ypI+9IuwG4v+3gJWs/Yz3/2NvHjx1lNBrxww8/IDU1Ve1SiLyGLwWyo9zddjCQ/Yw/fqjuv/9+7NixA8XFxfjyyy9RWFiIhoYGzJkzR+3SiLxCU1OTZf4x2w73tR28ZO1n/DGQKyoqMHv2bNTU1CAxMREXXnghdu/ejezsbLVLI/IKhw8fhoggJSXF68ePlfB028FA9iP19fU4ceKEz4wf22v16tVql0Dk1fyxIw94vu3gJWs/Yr4RwRfmHxOR5/hrIHsaA9mP+NtymUTkvKamJsv8Y7Yd7sVA9iPs5RKRUubx4+TkZERHR6tdjk9jIPuJU6dO+eX4MRE5x1eWy/QGDGQ/Yf5QZWZmIiwsTOVqiMhb8Mqa5zCQ/QQ/VESkFMePPYuB7CcYyESkVFFREcePPYiB7AdOnz6N6upq6HQ6r9+lhYg8hx15z2Ig+wGOHxORIxjInsVA9gPmDxXPjonIXs3NzSgvLwfAQPYUBrIfMC8IwmkLRGQv8/zjpKQkxMTEqF2OX+Ba1j7OevxYK/OPLz7/GCLDdE49R2OzuKgaIuqOealdLZ0dO9t2aL3d4BmyjzNfrs7IyEB4eLjK1RCRt+CVNc9jIPs43pRBREpZjx/z3hPPYSD7OAYyESllnn+clJSE2NhYtcvxGwxkH9bQ0ICqqirOPyYiRdiRVwcD2Ydx/JiIHMFAVgcD2Ydx/jERKdXS0oKysjIADGRPYyD7MG6bRkRKmcePExMTOX7sYQxkH9XQ0IDjx49z/JiIFOHlavUwkH2UeVJ/eno6x4+JyG4MZPUwkH2UeVI/P1REZK+WlhaUlpYCYNuhBgayj9LisndEpG1HjhyBiCAhIQFxcXFql+N3GMg+qKGhAceOHQPAO6yJyH5cLlNdDGQfZD47zsjIQEREhMrVEJG34PixuhjIPojzj4lIqdbWVs4/VhkD2Qexl0tEShUVFcFkMnH8WEUMZB/T2NhoGT9mIBORvdiRVx8D2cdYzz/m+DER2YuBrD4Gso8x3yXJ8WMisldrayvnH2sAA9nHmM+QOW2BiOx15MgRmEwmxMfHIz4+Xu1y/BYD2YecOXMGlZWVAHiGTET24+VqbWAg+xDzhyotLQ2RkZEqV0NE3oILgmgDA9mHsJdLREpZjx/zypq6GMg+hOtXE5FSR48etYwfJyQkqF2OX2Mg+4gzZ86goqICAHu5RGQ/7gynHQxkH2E+O05NTUVUVJTK1RCRt+BSu9rBQPYRHD8mIqWMRiNKSkoA8IYuLWAg+whzIPNDRUT2Ms8/jouL4/xjDWAg+4CmpibOPyYixayvrOl0OpWrIQayDzh8+DBEhOPHRKQIh7q0hYHsA3iXJBEpZTQaUVxcDIBth1YwkH0A5x8TkVLm+cexsbGcf6wRDGQv19TUZJl/zEAmIntZL5fJ8WNtYCB7OfP4cUpKCsePichunH+sPQxkL8ebMohIqba2Ns4/1iAGspdjIBORUkeOHEFnZyfHjzWGgezFOH5MRI7g/GNtYiB7saKiIogIkpOTER0drXY5ROQleGVNmxjIXoybihORUm1tbZx/rFEMZC/G+cdEpNTRo0fR2dmJmJgYJCYmql0OWWEge6nm5maUl5cDYCATkf04fqxdDGQvZZ5/zPFjIlKCS+1qFwPZS/FyNREpZT3/mG2H9jCQvRR7uUSkVHFxMTo6OhATE4OkpCS1y6FzMJC9EMePicgR1h15jh9rDwPZC5nnHyclJSEmJkbtcojIS3D9am1jIHshTuonIqXa29st84+5doE2BaldAClnDmRv/VAtbE9HSLtzfcG2dhOACtcUROQHjh49io6ODkRHR3vt+LGzbYfW2w2eIXuZlpYWlJWVAeBlJyKyH+cfax8D2ctYjx/HxsaqXQ4ReQkOdWkfA9nL8ENFREq1t7fj6NGjANh2aBkD2cswkIlIKfP846ioKCQnJ6tdDvWAgexFWlpaUFpaCoCB7IyFCxdCp9PhnnvuUbsUIo+w3hmO48eOc3fbwUD2Iubx48TERI4fO2jPnj14+eWXMWzYMLVLIfIYzj92nifaDgayF+HlauecOXMGN954I1555RV2aMhvcP6x8zzVdjCQvQgDuauGhgabL6PR2OOxc+fOxfTp03H55Zd7sEIidRUXF6O9vZ3jx1aUtBuA59oOBrKXsJ5/zED+P5mZmYiOjrZ8LVy4sNvjVq9eja+//rrHfyfyVdaXqzl+fJa97Qbg2baDK3V5iSNHjsBkMiEhIQFxcXFql6MZ5eXliIqKsnyv1+u7Pea3v/0tPv74YxgMBk+WR6Q6b1/Zzx3saTfMx3my7WAgewl+qLoXFRVl88HqzldffYUTJ05g5MiRlsc6Ozvx2Wef4YUXXoDRaERgYKC7SyXyOM4/7p497Qbg+baDgewlOH7suEmTJmH//v02j916660YNGgQHnzwQYYx+aySkhK0t7cjMjISKSkpapfjdTzddjCQvUBrayvnHzshMjISQ4cOtXksPDwc8fHxXR4n8iVcv9o5nm47eFOXFygqKuL4MREpZl4QhB1578AzZC9w+PBhAPxQudL27dvVLoHIrTh+7B7ubDt4huwF2MslIqVKS0st48epqalql0N2YCBrHMePicgR5o485x97DwayxpnnH8fHxyM+Pl7tcojIS3BmhvdhIGscP1REpFRHRweOHDkCgGsXeBMGssZxQRAiUso8/zgiIoLjx16Egaxhra2tKCkpAcBt04jIfpx/7J0YyBp29OhRy/hxQkKC2uUQkZfgUJd3YiBrGD9URKSU9fgx2w7vwkDWMAYyESlVWlqKtrY2jh97IQayRhmNRhQXFwNgIBOR/aznHwcEsIn3JvxraZR5/DguLo7zj4nIblxq13sxkDXKerlM3iVJRPbo7OxEUVERAE6V9EYMZI3i+DERKVVSUoK2tjaEh4dz/NgLMZA1qK2tzTL/mIFMRPYyd+Q5fuyd+BfToCNHjqCzsxOxsbGcf0xEduPKft6NgaxB1h8qjh8TkT06Ozs5/9jLMZA1iOPHRKRUaWkpjEYjwsPDkZaWpnY55AAGssa0tbVx/jERKcbxY+/Hv5rGHD16lOPHRKQYr6x5PwayxnCXFiJSynr+MQPZezGQNcZ6QRAiInuUlZXBaDQiLCwM6enpapdDDmIgawjnHxORI7h+tW/gX05DiouL0dHRgZiYGCQmJqpdDhF5Ca5f7RsYyBrC9auJSKnOzk5LIHNBEO/GQNYQrrJDREpx/Nh3MJDdqLb1DDpNJruOtZ5/3L9/f3eWRUQa1mkyoa61ye7jOf/YdwSpXYAvu2vHanxTU4GRidm4IDkHFyTnYHhCBgxBwV2OtR4/TkpKUqFaItKCg6eqMOX959AvOhGjk3MwJjkHo5NzkBUR1+1QFucf+w4GspuYxIRD9dVoaGvFtsqD2FZ5dnw4JCAQwxIyLAE9Mikbsfowzj8mIgDA93VVAICi0ydRdPok3jq0BwCQHBaFC5JyMDr5bAd/cGwqIML5xz6EgewmAboAfPnTh/BDXRX+faIE/64uwZ7qEpxoacTeE6XYe6IUL+7fAQAYGJOMQf+pBsDL1UT+rrDf+ZiUMRB7T5Tiy/+2G9/WVqK6uQHrS77F+pJvAQARwXqMDopHWGsrQkNDkZGRoXLl5CwGshsFBQSiICEdBQnpuG3IeIgIShvrsKe6BF9WF2PPiVIcOX0Sh+uqEN1yBsMz0hnIRIRYQzgmZw3B5KwhAICWjnbsqynHnuqznfuvTpSisd2IooqjGJEUg+F5gzh+7AMYyB6k0+mQExWPnKh4XNd/JACgpuUMNn+9Czv//S4apQEpKSkqV+l+jzz1v4gMNDj1HI2drXgdj7qoIiJtCw0KxtiUPIxNyQNw9savH+ursHLZa6g/UYa0i/xjdydn2w6ttxvsUqksITQCiWfO3omdn5/P8WMi6lNgQACGxKWi40Q9gLNtB3k/BrIGHD16FAA/VERkv5qaGjQ2NiIoKAjZ2dlql0MuwEBWmYjgyJEjABjIRGQ/893VWVlZCA7uOpWSvA8DWWUnT5609HKzsrLULoeIvASvrPkeBrLKzGfH2dnZ7OUSkd3MZ8gMZN/BQFYZL1cTkVLNzc04fvw4ALYdvoSBrDIGMhEpdfToUYgIEhMTERUVpXY55CIMZBU1Nzfj2LFjAIC8vDyVqyEib8HxY9/EQFaR+UOVlJTEXi4R2Y3jx76JgawiXq4mIqU6OztRUlICgG2Hr2Egq8gcyLxcTUT2qqyshNFoRGhoKFJTU9Uuh1yIgaySzs5OFBcXA2Avl4jsZ92R54YSvoV/TZVUVFSgra2NvVwiUoRDXb6LgawS9nKJyBEMZN/FJFAJP1REpFR9fT3q6uoQEBCAnJwctcshF2Mgq4SBTERKmduNjIwMGAzO7SlO2sNAVkFdXR3q6+vZyyUiRTgzw7cxkFXAXi4ROcLcdvTr10/lSsgdGMgq4OVqIlLKaDSivLwcANsOX8VAVgEDmYiUKikpgclkQkxMDGJjY9Uuh9yAgexhra2tqKioAMBAJiL7WXfkdTqdytWQOzCQPay0tBQmkwmxsbGIi4tTuxwi8hK8sub7GMgexl1aiEgpk8nELRf9AAPZw/ihIiKlqqqq0NzcjJCQEGRmZqpdDrkJA9mD2MslIkeYL1fn5OQgMDBQ5WrIXRjIHmTdy83IyFC7HCLyEhw/9g8MZA8yf6hyc3PZyyUiuzGQ/QMD2YO47B0RKdXY2IgTJ04AYNvh6xjIHsRl74hIKXO7kZqaivDwcJWrIXdiIHtIQ0ODpZebm5urcjVE5C14udp/MJA9xHx3dVpaGnu5RGQ3BrL/YCB7CMePiUip9vZ2lJaWAmAg+wMGsodw/Fg9S5cuxbBhwxAVFYWoqCiMHTsWmzZtUrssoj6VlZWho6MDERERSEpKUrscv+PptoOB7AHWvVyeIXteRkYGFi1ahL1792Lv3r247LLLMGvWLBw4cEDt0oh6Zb2QEDeU8DxPtx1BbnlWsmHu5UZGRrKXq4KZM2fafP+nP/0JS5cuxe7du3HeeeepVBVR37j2vbo83XYwkD3AevyYvVzXamhosPler9dDr9f3eHxnZyfeeecdNDU1YezYse4uj8hhIsKldt1EabsBeKbt4CVrD+Bdku6TmZmJ6Ohoy9fChQu7PW7//v2IiIiAXq/Hr371K/zzn//EkCFDPFwtkf1qamrQ0NCAwMBAZGdnq12OT7G33QA823bwDNnNRISB7Ebl5eWIioqyfN9TL3fgwIHYt28fTp06hffeew9z5szBjh07GMqkWeZ2IysrC8HBwSpX41vsbTcAz7YdDGQ3q6mpQWNjI4KCgtjLdQPz3Y99CQkJsdzhPmrUKOzZswdLlizB3//+d3eXSOQQzsxwH3vbDcCzbQcvWbuZ+aYM9nK1RURgNBrVLoOoR1y7QJvc2XbwDNnNeFOG+h555BFMmzYNmZmZaGxsxOrVq7F9+3Zs3rxZ7dKIutXc3Ixjx44BYNuhJk+3HQxkN+O0BfVVV1fjpptuwvHjxxEdHY1hw4Zh8+bNmDx5stqlEXWruLgYIoKEhARER0erXY7f8nTbwUB2o+bmZhw/fhwAA1lNy5YtU7sEIkU4fqwNnm47OIbsRkePHoWIIDEx0e4bCIiIOH7snxjIbsTxYyJSqrOzE8XFxQB4huxveMnajTh+3L0XJg2EXh/m1HMYjc3AIRcVRKQhlZWVMBqNMBgMSE1NVbscTXG27dB6u8EzZDfp7OxESUkJAAYyEdnP+nJ1QACbaH/Cv7absJdLRI7gyn7+i4HsJuzlEpEjeO+J/2JSuAmnLRCRUvX19aitrYVOp0Nubq7a5ZCHMZDdhNMWiEgp89lxRkYGDAaDytWQpzGQ3aC+vh51dXXs5RKRIpyZ4d8YyG5gPjtmL5eIlOD4sX9jILsB75IkIqXa2tpQVlYGgG2Hv2IguwEDmYiUKikpgclkQkxMDOLi4tQuh1TAQHYxo9GI8vJyALzDmojsZz1+rNPpVK6G1MBAdjHrXm5sbKza5RCRl+D4MTGQXcz6cjV7uURkD5PJxKEuYiC7Gj9URKRUdXU1mpubERwcjMzMTLXLIZUwkF3IZDLxshMRKWbuyOfm5iIwMFDlakgtDGQXqqqqQnNzM0JCQtjLJSK78coaAQxklzKfHefk5LCXS0R2YyATwEB2KS57R0RKnTlzBtXV1QC49r2/YyC7EMePiUgp89lxamoqwsPDVa6G1MRAdpHGxkb2colIMV6uJjMGsouYz47ZyyUiJbhVK5kxkF2E48dEpFRHRwdKSkoAcKldYiC7DMePiUipsrIydHR0ICIiAklJSWqXQypjILtAe3u7pZfLQCYie3GpXbLGQHaB8vJy9nKJSDGOH5M1BrILsJdLREqJiKXt4PgxAQxkl+C0BSJSqqamBg0NDQgMDERWVpba5ZAGMJCdZN3LZSATkb3M7UZWVhZCQkJUroa0gIHsJOtebnZ2ttrlEJGXYEeezsVAdpJ1Lzc4OFjlaojIW3CqJJ2Lgewk3pRBREq1tLSgsrISAAOZ/g8D2UmctkBEShUXF0NEkJCQgOjoaLXLIY1gIDuhpaUFx44dA8BeLhHZj0vtUncYyE44evQoe7lEpBjHj6k7DGQncPyYiJTq7OxkIFO3GMhO4PgxESl17NgxGI1GGAwGpKWlqV0OaQgD2UGdnZ0oLi4GwDNkIrKfefw4Ly8PAQFsgun/8P8GB1VWVlp6uampqWqXQ0RegperqScMZAdZX65mL5eI7MUVuqgnTBIH8UNFRErV19ejtrYWOp0Oubm5apdDGsNAdhAvOxGRUuZ2IyMjAwaDQeVqSGsYyA5gL5eIHMGZGdQbBrID2MslIkdw7QLqDQPZAVz2joiUamtrQ1lZGQCeIVP3GMgO4PgxESlVUlICk8mEmJgYxMfHq10OaRADWSHrXi4DmYjsZT1+rNPpVK6GtChI7QK8jXUvNy4uTu1yvNKcU9cjIsS5BulMm+A5F9VD5AmcKuk8Z9sOrbcbPENWyHr8mL1cIrKHyWTiUBf1iYGskPlDxZsyiMhe1dXVaGpqQnBwMLKystQuhzSKgayAyWTitAUiUszcbuTk5CAwMFDlakirGMgKVFdXo7m5GcHBwcjMzFS7HCLyEhw/JnswkBUwf6hyc3PZyyUiuzGQyR4MZAW47B0RKXXmzBlUV1cDYNtBvWMgK8DxYyJSytxupKSkICIiQuVqSMsYyHZiL5eIHMHL1WQvBrKdzB+q1NRUhIeHq1wNEXkLBjLZi4FsJ44fE5FSHR0dKC0tBcBApr4xkO3EXi4RKVVeXo729naEh4cjOTlZ7XJI4xjIdmAvl4gcwaV2SQkGsh3YyyUiR3D9alKCgWwH9nKJSCkRsWk7iPrCQLYDe7nebeHChRg9ejQiIyORlJSEq666CgcPHlS7LPJxtbW1aGhoQGBgILKzs9Uuhxzg6baDgdwH9nK9344dOzB37lzs3r0bn3zyCTo6OjBlyhQ0NTWpXRr5MHO7kZWVhZCQEJWrIUd4uu0Icsuz+hD2cr3f5s2bbb5/7bXXkJSUhK+++goTJkxQqSryddyq1ft5uu1gIPeBvVxta2hosPler9dDr9f3+jOnT58GAMTFxbmtLiIutatdjrQbgPvbDl6y7gPHj7UtMzMT0dHRlq+FCxf2eryI4L777sNFF12EoUOHeqhK8jctLS2orKwEwLZDi5S2G4Bn2g6eIfeBC4JoW3l5OaKioizf99XLveuuu/Dtt9/i888/d3dp5MeKi4shIkhISEB0dLTa5dA5lLYbgGfaDgZyL9jL1b6oqCibD1Zv7r77bnzwwQf47LPPkJGR4ebKyJ9xqV1tU9JuAJ5rOxjIvWAv1zeICO6++27885//xPbt25Gbm6t2SeTjOH7sGzzddjCQe8HL1b5h7ty5WLVqFd5//31ERkaiqqoKABAdHY3Q0FCVqyNfYzKZUFxcDIBnyN7O020Hb+rqBQPZNyxduhSnT5/GpZdeitTUVMvXmjVr1C6NfFBlZSVaW1thMBiQnp6udjnkBE+3HTxD7oHJZOId1j5CRNQugfyIuSOfm5uLgACe83gzT7cd/L+lB5WVlTAajTAYDEhLS1O7HCLyEryyRo5iIPfA+i5J9nKJyF4MZHIUk6YHnLZAREqdOnUKtbW10Ol0vJufFGMg94DTFohIKXO7kZ6ezjv4STEGcjese7k5OTlql0NEXoKXq8kZDORusJdLRI5gIJMzGMjd4IeKiJRqa2tDWVkZALYd5BgGcjcYyESkVElJCUwmE6KjoxEfH692OeSFGMjnYC+XiBxhvZCQTqdTuRryRgzkc7CXS0SOKCoqAsCOPDmOgXwO68vV7OUSkT1EhEvtktMYyOfg+DERKVVdXY2mpiYEBwcjMzNT7XLISzGQrXBDCSJyhLkjn5OTg6Ag7tlDjmEgWzlx4gR7uUSkGK+skSswkK2Yb8pgL5eIlGAgkyswkK3wcjURKXXmzBlUVVUB4GY05BwGshVOWyAipcwd+ZSUFERERKhcDXkzBvJ/nTlzBtXV1QDYyyUi+/FyNbkKA/m/2MslIkcwkMlVGMj/xQ8VESnV0dGBkpISAGw7yHm8lfi/GMieM+Oi3yIgVO/Uc5hajMBbi11TEJGDysvL0d7ejvDwcCQnJ6tdjs9ztu3QervBM2Swl0tEjjF35PPy8rjULjmNgQz2conIMeZA7tevn8qVkC9gIIO9XCJSTkRs2g4iZzGQwV4uESlXW1uL06dPIyAgADk5OWqXQz7A7wOZvVwicoS53cjKykJISIjK1ZAv8PtAZi+XiBzBmRnkan4fyOzlEpEjGMjkagxkfqiISKGWlhZUVlYCYNtBrsNAZiATkULFxcUQEcTHxyMmJkbtcshH+HUgs5dLRI5gR57cwa8Dmb1cInIEA5ncwa8DmR8qIlLKZDKhuLgYANsOci0GMvihIiL7VVZWorW1FQaDAenp6WqXQz7EbwOZvVwicoR57/Tc3FwEBPhtE0pu4Lf/N7GXS0SOKCoqAsCOPLme3wYye7lE5Ahz28FAJlfz2yRiL5eIlDp9+jRqamqg0+mQm5urdjnkY/w2kNnLJSKlzDeCpqenIzQ0VOVqyNf4ZSCzl0tEjuCVNXInvwxk9nKJyBHmK2vcqpXcwS8Dmb1cIlKqra0NZWVlAIB+/fqpXA35Ir8MZPZyiUip0tJSdHZ2IioqCvHx8WqXQz7I7wKZvVwicoR5qKtfv37Q6XQqV0O+yO8Cmb1cInKEOZB5ZY3cxe8Cmb1cIlJKRGzaDiJ38NtAZi+XiOxVXV2NpqYmBAcHIzMzU+1yyEf5VSCzl0tEjjC3G9nZ2QgKClK5GvJVfhXI7OUSkSO4VSt5gl919UwmE84//3wAYC+XiOyWlpaGvLw8DBgwQO1SyIf5VSqlpaXhjjvuULsMIvIyl19+OS6//HK1yyAf51eXrImIiLSKgUxERKQBDGQiIiINYCATERFpAAOZiIhIAxjIREREGsBAJiIi0gAGMhERkQYwkImIiDSAgUxERKQBDGQiIiINYCATERFpAAOZ/MJnn32GmTNnIi0tDTqdDuvWrVO7JCLSOE+3Gwxk8gtNTU0YPnw4XnjhBbVLISIv4el2w6+2XyT/NW3aNEybNk3tMojIi3i63WAgk8dJixEmFzwHADQ0NNg8rtfrodfrnXx2ItIiZ9sOrbcbDGTymJCQEKSkpKDq/qUueb6IiAhkZmbaPDZ//nwsWLDAJc9PRNrgyrZDy+0GA5k8xmAwoLi4GG1tbS55PhGBTqezeUwLvVwici1Xth1abjcYyORRBoMBBoNB7TKIyMv4Q9vBu6yJiIg0gGfI5BfOnDmDoqIiy/fFxcXYt28f4uLikJWVpWJlRKRVnm43dCIiLn9WIo3Zvn07Jk6c2OXxOXPm4PXXX/d8QUSkeZ5uNxjIREREGsAxZCIiIg1gIBMREWkAA5mIiEgDGMhEREQawEAmIiLSAAYyERGRBjCQiYiINICBTEREpAEMZCIiIg1gIBMREWkAA5mIiEgD/j+vKEri3+bkRAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 2])\n", - "angles: [np.float64(89.2861856598184)]\n", - "(1, 6) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 17\n", - "Adjacent strokes (list): [7]\n", - "Adjacent strokes (uniques): {7}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 18\n", - "Adjacent strokes (list): [8, 4, 4]\n", - "Adjacent strokes (uniques): {8, 4}\n", - "Checking edge: (8, 4)\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "angles_gdf len 3\n", - "connectivity: 1\n", - "Counter values: dict_values([1, 2])\n", - "angles: [np.float64(87.79139488488063)]\n", - "(8, 4) added\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 19\n", - "Adjacent strokes (list): [6]\n", - "Adjacent strokes (uniques): {6}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 20\n", - "Adjacent strokes (list): [1]\n", - "Adjacent strokes (uniques): {1}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 21\n", - "Adjacent strokes (list): [9]\n", - "Adjacent strokes (uniques): {9}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 22\n", - "Adjacent strokes (list): [0]\n", - "Adjacent strokes (uniques): {0}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 23\n", - "Adjacent strokes (list): [2]\n", - "Adjacent strokes (uniques): {2}\n", - "**************************************************************\n", - " \n", - " \n", - "\n", - "Node: 24\n", - "Adjacent strokes (list): [6]\n", - "Adjacent strokes (uniques): {6}\n", - "**************************************************************\n", - " \n", - " \n", - "\n" - ] - } - ], - "source": [ - "for n in graph.nodes:\n", - "\n", - " node_id = graph.nodes[n][\"nodeID\"] # TODO Remove (only for plotting now)\n", - " print(f\"Node: {node_id}\")\n", - " \n", - " es = list(graph.edges(n, keys=True))\n", - " stroke_list = [graph.edges[e][\"stroke_id\"] for e in es]\n", - " stroke_set = set(stroke_list)\n", - " \n", - " print(\"Adjacent strokes (list):\", stroke_list)\n", - " print(\"Adjacent strokes (uniques):\", stroke_set)\n", - " \n", - " # for all size2 combinations from stroke_set\n", - " for c in combinations(stroke_set, 2):\n", - " \n", - " print(\"Checking edge:\", c)\n", - " \n", - " # get angles at that primal node for this 2-stroke combination c\n", - " es = list(graph.edges(n, keys=True))\n", - " stroke_ids = [graph.edges[e][\"stroke_id\"] for e in es]\n", - " geoms = [graph.edges[e][\"geometry\"] for e in es]\n", - " segments = [get_segment(geom, n) for geom in geoms] # extracting only edge segments that touch this node\n", - " angles_gdf = gpd.GeoDataFrame(\n", - " {\n", - " \"stroke_id\": stroke_ids,\n", - " \"segment\": segments,\n", - " \"geometry\": [LineString(x) for x in segments]\n", - " }\n", - " )\n", - "\n", - " # TODO plots can be removed later\n", - " fig, axs = plt.subplots(1,2, sharex=True, sharey=True)\n", - " ax = axs[0]\n", - " angles_gdf.plot(ax=ax, column=\"stroke_id\", legend=True, cmap = \"Dark2\")\n", - " ax.set_title(f\"All strokes at node {node_id}\")\n", - " ax.set_axis_off()\n", - "\n", - " # filter out only those linestring that belong to current 2-stroke edge\n", - " angles_gdf = angles_gdf[angles_gdf.stroke_id.isin(c)].reset_index(drop=True)\n", - " \n", - " # TODO plots can be removed later\n", - " ax = axs[1]\n", - " angles_gdf.plot(ax=ax, column=\"stroke_id\", legend=True, cmap = \"Dark2\")\n", - " ax.set_title(f\"Strokes {c} at node {node_id}\")\n", - " ax.set_axis_off()\n", - " \n", - " plt.show()\n", - " \n", - "\n", - " if len(angles_gdf)==2:\n", - "\n", - " print(\"angles_gdf len 2\")\n", - "\n", - " # connectivity equals 1 here\n", - " connectivity = 1\n", - "\n", - " # angle between 2 strokes is just angle between \n", - " # the 2 linestrings in the gdf:\n", - " row_a = angles_gdf.loc[0]\n", - " row_b = angles_gdf.loc[1]\n", - " angles = [\n", - " get_interior_angle(\n", - " row_a.segment[1],\n", - " row_a.segment[0],\n", - " row_b.segment[1]\n", - " )\n", - " ]\n", - "\n", - " elif len(angles_gdf)==3:\n", - "\n", - " print(\"angles_gdf len 3\")\n", - "\n", - " # connectivity equals 1 here\n", - " connectivity = 1\n", - "\n", - " # the iteration has to go through the stroke that appears TWICE\n", - " stroke_count = dict(Counter(angles_gdf.stroke_id))\n", - " stroke_count = {v:k for k,v in stroke_count.items()}\n", - " \n", - " # separate angles_gdf into 2 separate gdf (one for each stroke)\n", - " angles_stroke_a = angles_gdf[angles_gdf[\"stroke_id\"]==stroke_count[1]].copy()\n", - " angles_stroke_b = angles_gdf[angles_gdf[\"stroke_id\"]==stroke_count[2]].copy()\n", - "\n", - " angles = []\n", - " # there is only ONE row_a stroke segment\n", - " for i, row_a in angles_stroke_a.iterrows():\n", - " angles_stroke = []\n", - " # iterate through BOTH stroke b segments\n", - " for j, row_b in angles_stroke_b.iterrows():\n", - " assert row_a.segment[0] == row_b.segment[0]\n", - " # compute angle between stroke a and stroke b segments\n", - " # and add to list of current angles\n", - " angles_stroke.append(get_interior_angle(\n", - " row_a.segment[1],\n", - " row_a.segment[0],\n", - " row_b.segment[1])\n", - " )\n", - " # keep the smaller of the 2 angles to add to list of angles for the stroke pair\n", - " angles.append(min(angles_stroke))\n", - "\n", - " elif len(angles_gdf)==4:\n", - " print(\"angles_gdf len 4\")\n", - "\n", - " # connectivity equals 2 here\n", - " connectivity = 2\n", - "\n", - " # separate angles_gdf into 2 separate gdf (one for each stroke)\n", - " angles_stroke_a = angles_gdf[angles_gdf[\"stroke_id\"]==c[0]].copy()\n", - " angles_stroke_b = angles_gdf[angles_gdf[\"stroke_id\"]==c[1]].copy()\n", - "\n", - " angles = []\n", - " # iterate through stroke a segments\n", - " for i, row_a in angles_stroke_a.iterrows():\n", - " # iterate through stroke b segments\n", - " angles_partial = []\n", - " for j, row_b in angles_stroke_b.iterrows():\n", - " assert row_a.segment[0] == row_b.segment[0]\n", - " # compute angle between stroke a and stroke b segments\n", - " # and add to list of current angles\n", - " angle = get_interior_angle(\n", - " row_a.segment[1],\n", - " row_a.segment[0],\n", - " row_b.segment[1])\n", - " # if angle > 90:\n", - " # angle = 180 - angle\n", - " angles_partial.append(angle)\n", - " print(f\"Interior angles found: {angles_partial}\")\n", - " angles.append(min(angles_partial)) # @csebastiao we're keeping the minimal here?\n", - " print(f\"Final angles found: {angles}\")\n", - "\n", - " else:\n", - " ValueError(f\"Length of angles_gdf expected to be in [2,3,4], but is {len(angles_gdf)}\")\n", - "\n", - " #### now that we have connectivity and angles, \n", - " print(f\"connectivity: {connectivity}\")\n", - " print(\"Counter values:\", Counter(angles_gdf.stroke_id).values())\n", - " print(\"angles:\", angles)\n", - "\n", - " # connectivity is added at stroke node level:\n", - " for s in c:\n", - " stroke_graph.nodes[s][\"connectivity\"] += connectivity\n", - "\n", - " # and edge (or update edge info) at stroke edge level:\n", - " if c not in stroke_graph.edges:\n", - " edge_geom = LineString(\n", - " [\n", - " stroke_graph.nodes[c[0]][\"geometry\"],\n", - " stroke_graph.nodes[c[1]][\"geometry\"]\n", - " ]\n", - " )\n", - " stroke_graph.add_edge(\n", - " c[0],\n", - " c[1],\n", - " geometry=edge_geom,\n", - " angles=angles\n", - " )\n", - " print(f\"{c} added\")\n", - "\n", - " else:\n", - " print(f\"{c} already in graph, angles =\", stroke_graph.edges[c][\"angles\"])\n", - " stroke_graph.edges[c][\"angles\"] += angles\n", - " print(f\"{c} already in graph, angles updated =\", stroke_graph.edges[c][\"angles\"])\n", - " print(\"**************************************************************\\n \\n \\n\")\n", - "# we want to add edges for all stroke IDs that co-occur on edges that share the same node in the primal graph\n", - "# [0, 1, 1] means: stroke0 has an endpoint here; stroke1 has a throughpoint here; we add the edge [0,1] in the strokes_graph, with the attribute \n", - "# stroke = {0: \"end\", 1: \"through\"}\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**We want as final output:**\n", - "\n", - "A networkx `Graph()` object (undirected, simple)\n", - "\n", - "* nodes represent strokes,\n", - "* edges represent stroke connections (intersecting, ie crossing or touching)\n", - "\n", - "* edges: attributes: \n", - " * angles \n", - " * number of connections\n", - "* nodes: attributes:\n", - " *should be inheriting from all primal edge attrs, at least:*\n", - " * geometry\n", - " * length\n", - "\n", - "***\n", - "\n", - "next step: functions to add attrs on the nodes (strokes):\n", - "* degree, closeness, betweenness (by def nx) \n", - "* connectivity == number of angles (total nr of connections, min=degree)\n", - "* access (abs diff connectivity-degree)\n", - "* spacing = length / connectivity\n", - "* orthogonality = average angle (sum of angles / connectivity)" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "# add graph metrics\n", - "\n", - "# betweenness centrality dict for all nodes\n", - "bc = nx.betweenness_centrality(stroke_graph)\n", - "\n", - "# closeness centrality dict for all nodes\n", - "cc = nx.closeness_centrality(stroke_graph)\n", - "\n", - "for n in stroke_graph.nodes:\n", - " \n", - " stroke_graph.nodes[n][\"degree\"] = nx.degree(stroke_graph, n)\n", - " stroke_graph.nodes[n][\"betweenness_centrality\"] = bc[n]\n", - " stroke_graph.nodes[n][\"closeness_centrality\"] = cc[n]\n", - "\n", - " # just for sanity check # TODO can be removed later\n", - " stroke_graph.nodes[n][\"connectivity_computed\"] = sum(\n", - " [len(stroke_graph.edges[edge][\"angles\"]) for edge in stroke_graph.edges(n)]\n", - " ) \n", - " assert stroke_graph.nodes[n][\"connectivity\"] == stroke_graph.nodes[n][\"connectivity_computed\"]\n", - "\n", - " # access = abs(connectivity - degree)\n", - " stroke_graph.nodes[n][\"access\"] = abs(stroke_graph.nodes[n][\"connectivity\"] - stroke_graph.nodes[n][\"degree\"])\n", - "\n", - " # spacing = length / connectivity\n", - " stroke_graph.nodes[n][\"length\"] = stroke_graph.nodes[n][\"geometry_stroke\"].length # compute length first\n", - " stroke_graph.nodes[n][\"spacing\"] = stroke_graph.nodes[n][\"length\"] / stroke_graph.nodes[n][\"connectivity\"]\n", - "\n", - " # orthogonality = sum(angles) / connectivity\n", - " # compute sum of angles of edges of that node first\n", - " node_angles = [stroke_graph.edges[edge][\"angles\"] for edge in stroke_graph.edges(n)]\n", - " node_angles = [item for sublist in node_angles for item in sublist] # un-nest list\n", - " stroke_graph.nodes[n][\"orthogonality\"] = sum(node_angles)/stroke_graph.nodes[n][\"connectivity\"]\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Save as pickle" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [], - "source": [ - "# after iteration finished, save results:\n", - "with open('stroke_graph_anvy.pickle', 'wb') as handle:\n", - " pickle.dump(stroke_graph, handle, protocol=pickle.HIGHEST_PROTOCOL)\n", - "\n", - "# # to read back in:\n", - "# with open('stroke_graph.pickle', 'rb') as handle:\n", - "# G = pickle.load(handle)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Plot final results**" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [], - "source": [ - "# get gdfs of points and lines\n", - "points_strokes, lines_strokes = momepy.nx_to_gdf(stroke_graph, points=True, lines=True)\n", - "# and also one with the prinal stroke geoms\n", - "points_strokes_primal = points_strokes.copy()\n", - "points_strokes_primal=points_strokes_primal.set_geometry(\"geometry_stroke\")\n", - "points_strokes_primal=points_strokes_primal.set_crs(points_strokes.crs)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [], - "source": [ - "stroke_metrics = [\n", - " 'connectivity',\n", - " 'degree',\n", - " 'betweenness_centrality',\n", - " 'closeness_centrality',\n", - " 'access',\n", - " 'length', \n", - " 'spacing',\n", - " 'orthogonality'\n", - "]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Final result for now**" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 40, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m = points_strokes_primal.explore(\n", - " tiles=\"cartodb.positron\",\n", - " column = \"nodeID\",\n", - " name = \"strokes (original geoms)\",\n", - " cmap = \"tab20c\", \n", - " style_kwds={\"weight\":8},\n", - " opacity=0.9\n", - ")\n", - "points_strokes[[\"geometry\", \"connectivity\"]].explore(\n", - " m=m,\n", - " marker_kwds={\"radius\":10}, \n", - " name =\"stroke nodes\",\n", - " column = \"connectivity\", \n", - " cmap = \"Purples\",\n", - " #opacity=0.2\n", - " )\n", - "\n", - "for metric in stroke_metrics:\n", - " points_strokes_primal.explore(\n", - " m=m,\n", - " column=metric,\n", - " cmap=\"Reds\",\n", - " name=f\"{metric}\")\n", - "\n", - "lines_strokes[[\"geometry\", \"angles\"]].explore(m=m, \n", - " name = \"Stroke graph edges\",\n", - " color = \"black\",\n", - " style_kwds={\"weight\":1},\n", - " dash_array=2\n", - "\n", - ")\n", - "folium.LayerControl().add_to(m)\n", - "m" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "momepy_dev", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.10" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/momepy/strokegraph_clse.ipynb b/momepy/strokegraph_clse.ipynb deleted file mode 100644 index 6e334fa9..00000000 --- a/momepy/strokegraph_clse.ipynb +++ /dev/null @@ -1,922 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Playground for strokes graph" - ] - }, - { - "cell_type": "code", - "execution_count": 133, - "metadata": {}, - "outputs": [], - "source": [ - "import geopandas as gpd\n", - "import matplotlib.pyplot as plt\n", - "import momepy\n", - "import networkx as nx\n", - "import folium\n", - "from itertools import combinations, product\n", - "import shapely\n", - "import numpy as np\n", - "import pickle" - ] - }, - { - "cell_type": "code", - "execution_count": 134, - "metadata": {}, - "outputs": [], - "source": [ - "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def make_stroke_graph(gdf, compute_metric=True, output=\"dataframe\"):\n", - " if output not in [\"dataframe\", \"graph\"]:\n", - " raise ValueError(\"output need to be either dataframe or graph\")\n", - " # Clean data\n", - " gdf = momepy.remove_false_nodes(gdf)\n", - " # Transform into primal graph\n", - " G_primal = momepy.gdf_to_nx(gdf, approach=\"primal\", preserve_index=True)\n", - " lines_primal = momepy.nx_to_gdf(G_primal, points=False, lines=True)\n", - " # Use COINS on primal graph edges\n", - " coins = momepy.COINS(lines_primal)\n", - " # List the stroke for each edge\n", - " stroke_attribute = coins.stroke_attribute()\n", - " # List each edge for each stroke\n", - " stroke_gdf = coins.stroke_gdf()\n", - " stroke_gdf[\"edge_ids\"] = [stroke_attribute[stroke_attribute == stroke_id].index.values for stroke_id in stroke_gdf.index.values]\n", - " # Add stroke ID to each edge\n", - " nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[G_primal.edges[e][\"index_position\"]]) for e in G_primal.edges}, \"stroke_id\")\n", - " # Create stroke graph\n", - " G_stroke = nx.Graph()\n", - " G_stroke.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", - " # Create a node for each stroke with the right features\n", - " G_stroke.add_nodes_from([[int(idx), {(attr if attr != \"geometry\" else \"geometry_stroke\"):stroke_gdf.loc[idx][attr] for attr in list(stroke_gdf)}] for idx in stroke_gdf.index.values])\n", - " # For all node, put its geometry at the center of the LineString\n", - " for n in G_stroke.nodes:\n", - " G_stroke.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", - " G_stroke.nodes[n][\"x\"] = G_stroke.nodes[n][\"geometry\"].xy[0]\n", - " G_stroke.nodes[n][\"y\"] = G_stroke.nodes[n][\"geometry\"].xy[1]\n", - " G_stroke.nodes[n][\"length\"] = G_stroke.nodes[n][\"geometry_stroke\"].length\n", - " # Find strokes intersecting\n", - " for n in G_primal.nodes:\n", - " strokes_present = [G_primal.edges[e][\"stroke_id\"] for e in G_primal.edges(n, keys=True)]\n", - " # If strokes intersecting, add the edge if not already present\n", - " if len(set(strokes_present)) > 1:\n", - " for u, v in combinations(set(strokes_present), 2):\n", - " # Find all edges touching the node for both strokes checked\n", - " edges_u = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == u]\n", - " edges_v = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == v]\n", - " angle_list = []\n", - " angle_dict = {}\n", - " # Choose the smallest list as number of angles kept\n", - " chosen, other = sorted([edges_u, edges_v], key=len)\n", - " # Find the angles\n", - " for ce, oe in list(product(chosen, other)):\n", - " point = [G_primal.nodes[n][\"x\"], G_primal.nodes[n][\"y\"]]\n", - " gc = find_geom(G_primal.edges[ce][\"geometry\"], point)\n", - " go = find_geom(G_primal.edges[oe][\"geometry\"], point)\n", - " if ce in angle_dict:\n", - " angle_dict[ce].append(angle(gc, go))\n", - " else:\n", - " angle_dict[ce]= [angle(gc, go)]\n", - " # Keep the smallest angles\n", - " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", - " if G_stroke.has_edge(u, v):\n", - " G_stroke.edges[u, v][\"angles\"] += angle_list\n", - " G_stroke.edges[u, v][\"number_connections\"] = len(G_stroke.edges[u, v][\"angles\"])\n", - " else:\n", - " G_stroke.add_edge(u, v, geometry = shapely.LineString([G_stroke.nodes[u][\"geometry\"], G_stroke.nodes[v][\"geometry\"]]), number_connections=len(angle_list), angles=angle_list)\n", - " if compute_metric:\n", - " nx.set_node_attributes(G_stroke, nx.betweenness_centrality(G_stroke), \"stroke_betweenness\")\n", - " nx.set_node_attributes(G_stroke, nx.closeness_centrality(G_stroke), \"stroke_closeness\")\n", - " nx.set_node_attributes(G_stroke, dict(nx.degree(G_stroke)), \"stroke_degree\")\n", - " for n in G_stroke.nodes:\n", - " G_stroke.nodes[n][\"stroke_connectivity\"] = sum([G_stroke.edges[e][\"number_connections\"] for e in G_stroke.edges(n)])\n", - " G_stroke.nodes[n][\"stroke_access\"] = G_stroke.nodes[n][\"stroke_connectivity\"] - G_stroke.nodes[n][\"stroke_degree\"]\n", - " angles = [val for e in G_stroke.edges(n) if G_stroke.edges[e][\"angles\"] for val in G_stroke.edges[e][\"angles\"]]\n", - " G_stroke.nodes[n][\"stroke_orthogonality\"] = sum(angles) / G_stroke.nodes[n][\"stroke_connectivity\"]\n", - " G_stroke.nodes[n][\"stroke_spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]\n", - " if output == \"dataframe\":\n", - " return momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n", - " elif output == \"graph\":\n", - " return G_stroke\n", - "\n", - "def angle(a, b):\n", - " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", - " if angle > 90:\n", - " angle = 180 - angle\n", - " return angle\n", - "\n", - "def find_geom(linestring, point):\n", - " if point == list(linestring.coords[0]):\n", - " geom = [np.array(val) for val in linestring.coords[:2]]\n", - " else:\n", - " geom = [np.array(val) for val in linestring.coords[-2:]]\n", - " return np.array(geom[0] - geom[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 136, - "metadata": {}, - "outputs": [], - "source": [ - "G_stroke = make_stroke_graph(streets, compute_metric=True, output=\"graph\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Save as pickle" - ] - }, - { - "cell_type": "code", - "execution_count": 137, - "metadata": {}, - "outputs": [], - "source": [ - "# after iteration finished, save results:\n", - "with open('stroke_graph_clse.pickle', 'wb') as handle:\n", - " pickle.dump(G_stroke, handle, protocol=pickle.HIGHEST_PROTOCOL)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Visualize final results**" - ] - }, - { - "cell_type": "code", - "execution_count": 138, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_53570/2550495861.py:5: UserWarning: Approach is not set. Defaulting to 'primal'.\n", - " points_stroke, lines_stroke = momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n" - ] - }, - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 138, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "stroke_gdf_viz = stroke_gdf.copy()\n", - "stroke_gdf_viz[\"id\"] = stroke_gdf_viz.index\n", - "lines_primal_viz = lines_primal.copy()\n", - "lines_primal_viz[\"edge_id\"] = lines_primal.index\n", - "points_stroke, lines_stroke = momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n", - "m = stroke_gdf_viz.explore(tiles=\"cartodb-positron\", column=\"id\", cmap=\"tab10\", name=\"strokes\")\n", - "points_primal.explore(m=m, name=\"points_primal\")\n", - "lines_primal_viz.explore(m=m, name=\"lines_primal\")\n", - "points_stroke.explore(m=m, color=\"black\", marker_kwds={\"radius\":10}, name=\"points_stroke\")\n", - "lines_stroke.explore(m=m, color=\"blue\", name=\"lines_stroke\")\n", - "folium.LayerControl().add_to(m)\n", - "m" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "momepy_dev", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.10" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/momepy/strokegraph_compare.ipynb b/momepy/strokegraph_compare.ipynb deleted file mode 100644 index cb3db277..00000000 --- a/momepy/strokegraph_compare.ipynb +++ /dev/null @@ -1,836 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "66901d81", - "metadata": {}, - "source": [ - "# Checking whether we're getting the same results" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "b411a245", - "metadata": {}, - "outputs": [], - "source": [ - "import pickle\n", - "\n", - "import geopandas as gpd\n", - "import numpy as np\n", - "\n", - "import momepy\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "b57b27f8", - "metadata": {}, - "outputs": [], - "source": [ - "with open('stroke_graph_x2.pickle', 'rb') as handle:\n", - " G_anvy = pickle.load(handle)\n", - "with open('stroke_graph_clse.pickle', 'rb') as handle:\n", - " G_clse = pickle.load(handle)" - ] - }, - { - "cell_type": "markdown", - "id": "a17bf072", - "metadata": {}, - "source": [ - "Manually checking: edge attributes?" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "cf78ba7a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'geometry': ,\n", - " 'angles': [np.float64(36.134980718680936)],\n", - " 'number_connections': 1}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G_anvy.edges[(0,9)]" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "915e4cab", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'geometry': ,\n", - " 'number_connections': 1,\n", - " 'angles': [np.float64(36.134980718680936)]}" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G_clse.edges[(0,9)]" - ] - }, - { - "cell_type": "markdown", - "id": "c712de5e", - "metadata": {}, - "source": [ - "@csebastiao is the `number_connections` used for any of the metrics, or just a nice-to-have metric in itself?" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "af4d762b", - "metadata": {}, - "outputs": [], - "source": [ - "# make sure we have the same edges\n", - "assert list(G_anvy.edges) == list(G_clse.edges), \"Edges differ\"" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "afbcc5f1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n" - ] - } - ], - "source": [ - "for edge in G_anvy.edges:\n", - " assert G_anvy.edges[edge][\"geometry\"] == G_clse.edges[edge][\"geometry\"], \"Geoms differ\"\n", - " #print(f\"Edge {edge}\")\n", - " angles_anvy = [round(angle, 10) for angle in sorted(G_anvy.edges[edge][\"angles\"])]\n", - " angles_clse = [round(angle, 10) for angle in sorted(G_clse.edges[edge][\"angles\"])]\n", - " if angles_anvy == angles_clse:\n", - " pass\n", - " #print(\"Angles equal\")\n", - " else:\n", - " print(\"Angles differ:\")\n", - " print(angles_anvy)\n", - " print(angles_clse)\n", - " print(\"\\n\")\n", - " #assert sortedG_anvy.edges[edge][\"angles\"] == G_clse.edges[edge][\"angles\"], \"Angles differ\"" - ] - }, - { - "cell_type": "markdown", - "id": "2b8ec8cc", - "metadata": {}, - "source": [ - "@csebastiao re the above. WHY :D " - ] - }, - { - "cell_type": "markdown", - "id": "4d35c3bc", - "metadata": {}, - "source": [ - "Checking nodes" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "029e919b", - "metadata": {}, - "outputs": [], - "source": [ - "assert list(G_anvy.nodes) == list(G_clse.nodes), \"Nodes differ\"" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "e7a7bf17", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'edge_indeces': [0, 3, 15, 27],\n", - " 'geometry': ,\n", - " 'stroke_geometry': ,\n", - " 'stroke_length': 839.5666838320316,\n", - " 'x': 1603374.6625343116,\n", - " 'y': 6464077.898491419,\n", - " 'connectivity': 0,\n", - " 'stroke_betweenness': 0.13657407407407404,\n", - " 'stroke_closeness': 0.6923076923076923,\n", - " 'stroke_degree': 5,\n", - " 'stroke_connectivity': 8,\n", - " 'stroke_access': 3,\n", - " 'stroke_orthogonality': np.float64(68.74678997354196),\n", - " 'stroke_spacing': 104.94583547900395}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G_anvy.nodes[0]" - ] - }, - { - "cell_type": "markdown", - "id": "008c3f19", - "metadata": {}, - "source": [ - "@csebastiao: `connectivity_computed` can be ignored (we can later drop it entirely, was just a sanity check)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "829d8185", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'n_segments': np.int64(8),\n", - " 'geometry_stroke': ,\n", - " 'edge_ids': array([ 0, 3, 15, 27]),\n", - " 'geometry': ,\n", - " 'x': array('d', [1603374.6625343116]),\n", - " 'y': array('d', [6464077.898491419]),\n", - " 'length': 839.5666838320316,\n", - " 'stroke_betweenness': 0.13657407407407404,\n", - " 'stroke_closeness': 0.6923076923076923,\n", - " 'stroke_degree': 5,\n", - " 'stroke_connectivity': 8,\n", - " 'stroke_access': 3,\n", - " 'stroke_orthogonality': np.float64(68.74678997354196),\n", - " 'stroke_spacing': 104.94583547900395}" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G_clse.nodes[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "66b889d6", - "metadata": {}, - "outputs": [], - "source": [ - "# k:v is anvy:clse naming of node attrs\n", - "metrics_map = {\n", - " \"stroke_degree\": \"stroke_degree\",\n", - " \"stroke_betweenness\": \"stroke_betweenness\",\n", - " \"stroke_closeness\": \"stroke_closeness\",\n", - " \"stroke_connectivity\": \"stroke_connectivity\",\n", - " \"stroke_access\": \"stroke_access\",\n", - " \"stroke_spacing\": \"stroke_spacing\",\n", - " #\"orthogonality\": \"stroke_orthogonality\"\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "5aa782b2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'edge_indeces': [0, 3, 15, 27],\n", - " 'geometry': ,\n", - " 'stroke_geometry': ,\n", - " 'stroke_length': 839.5666838320316,\n", - " 'x': 1603374.6625343116,\n", - " 'y': 6464077.898491419,\n", - " 'connectivity': 0,\n", - " 'stroke_betweenness': 0.13657407407407404,\n", - " 'stroke_closeness': 0.6923076923076923,\n", - " 'stroke_degree': 5,\n", - " 'stroke_connectivity': 8,\n", - " 'stroke_access': 3,\n", - " 'stroke_orthogonality': np.float64(68.74678997354196),\n", - " 'stroke_spacing': 104.94583547900395}" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G_anvy.nodes[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "7f661ee2", - "metadata": {}, - "outputs": [], - "source": [ - "for n in G_anvy.nodes:\n", - " assert G_anvy.nodes[n][\"x\"] == G_clse.nodes[n][\"x\"][0], \"x coords differ\"\n", - " assert G_anvy.nodes[n][\"y\"] == G_clse.nodes[n][\"y\"][0], \"y coords differ\"\n", - " assert G_anvy.nodes[n][\"geometry\"] == G_clse.nodes[n][\"geometry\"], \"geometries differ\"\n", - " assert G_anvy.nodes[n][\"stroke_geometry\"] == G_clse.nodes[n][\"geometry_stroke\"], \"geometry_stroke differ\"\n", - " assert G_anvy.nodes[n][\"edge_indeces\"] == list(G_clse.nodes[n][\"edge_ids\"]), \"Edge IDs differ\"\n", - " assert G_anvy.nodes[n][\"stroke_length\"] == G_clse.nodes[n][\"length\"]\n", - " for k, v in metrics_map.items():\n", - " assert round(G_anvy.nodes[n][k], 10) == round(G_clse.nodes[n][v], 10), f\"{k} differ\"" - ] - }, - { - "cell_type": "markdown", - "id": "d834bb01", - "metadata": {}, - "source": [ - "@csebastiao we get the same metrics everywhere but orthogonality (which i guess makes sense cause the angles are off?)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "d922e80c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0: same ortho\n", - "1: same ortho\n", - "2: same ortho\n", - "3: same ortho\n", - "4: same ortho\n", - "5: same ortho\n", - "6: same ortho\n", - "7: same ortho\n", - "8: same ortho\n", - "9: same ortho\n" - ] - } - ], - "source": [ - "for n in G_anvy.nodes:\n", - " ortho_anvy = round(G_anvy.nodes[n][\"stroke_orthogonality\"], 10)\n", - " ortho_clse = round(G_clse.nodes[n][\"stroke_orthogonality\"], 10)\n", - " if ortho_anvy == ortho_clse:\n", - " print(f\"{n}: same ortho\")\n", - " else:\n", - " print(f\"{n}: orthos differ\")\n", - " print(ortho_anvy)\n", - " print(ortho_clse)" - ] - }, - { - "cell_type": "markdown", - "id": "d8dd1c1f", - "metadata": {}, - "source": [ - "## Testing the angles function" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "fe17ccd0", - "metadata": {}, - "outputs": [], - "source": [ - "import math\n", - "\n", - "import numpy as np\n", - "\n", - "\n", - "# Anastassia angle def\n", - "def get_interior_angle(a, b, c):\n", - " \"\"\"\n", - " Measure the angle between a-b, b-c (in degrees).\n", - " \"\"\"\n", - " ba = [a[0]-b[0],a[1]-b[1]]\n", - " bc = [c[0]-b[0],c[1]-b[1]]\n", - " # np.dot(ba, bc) # ba[0]*bc[0] + ba[1]*bc[1]\n", - " # np.linalg.norm(ba) # np.sqrt(ba[0]**2+ba[1]**2)\n", - " # np.linalg.norm(bc) # np.sqrt(bc[0]**2+bc[1]**2)\n", - " theta_rad = math.acos(np.dot(ba,bc)/(np.linalg.norm(ba)*np.linalg.norm(bc)))\n", - " theta_deg = np.degrees(theta_rad)\n", - " if theta_deg > 90:\n", - " theta_deg = 180 - theta_deg\n", - " return theta_deg\n", - "\n", - "# Clément angle def\n", - "def angle(a, b):\n", - " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", - " if angle > 90:\n", - " angle = 180 - angle\n", - " return angle" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "a11251c9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0.])" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "vectors = [[np.cos(np.radians(deg)), np.sin(np.radians(deg))] for deg in range(360)]\n", - "angles_clse = np.array([round(angle(vectors[0], vectors[i]), 8) for i in range(1, 360)])\n", - "angles_anvy = np.array([round(get_interior_angle(vectors[0], [0,0], vectors[i]), 5) for i in range(1, 360)])\n", - "angles_clse - angles_anvy" - ] - }, - { - "cell_type": "markdown", - "id": "b034b463", - "metadata": {}, - "source": [ - "Both angle function work well and similarly if receiving the same inputs (with different formalism but still), so issue before !" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "b7eabac6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0.])" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "vectors = np.array([[np.cos(np.radians(deg)), np.sin(np.radians(deg))] for deg in range(360)]) + 183049\n", - "angles_clse = np.array([round(angle(vectors[0], vectors[i]), 5) for i in range(1, 360)])\n", - "angles_anvy = np.array([round(get_interior_angle(vectors[0], [0,0], vectors[i]), 5) for i in range(1, 360)])\n", - "angles_clse - angles_anvy" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "95b0e4cc", - "metadata": {}, - "outputs": [], - "source": [ - "for edge in G_anvy.edges:\n", - " assert G_anvy.edges[edge][\"geometry\"] == G_clse.edges[edge][\"geometry\"], \"Geoms differ\"\n", - " angles_anvy = [round(angle, 10) for angle in sorted(G_anvy.edges[edge][\"angles\"])]\n", - " angles_clse = [round(angle, 10) for angle in sorted(G_clse.edges[edge][\"angles\"])]\n", - " if angles_anvy != angles_clse:\n", - " print(\"Angles differ:\")\n", - " print(angles_anvy)\n", - " print(angles_clse)\n", - " print(G_anvy.nodes[edge[0]])\n", - " print(G_anvy.nodes[edge[1]])\n", - " print(G_clse.nodes[edge[0]])\n", - " print(G_clse.nodes[edge[1]])\n", - " print(\"\\n\")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "f84c0968", - "metadata": {}, - "outputs": [], - "source": [ - "streets = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", - "# Clean data\n", - "streets = momepy.remove_false_nodes(streets)\n", - "streets[\"edge_id\"] = streets.index\n", - "# Transform into primal graph\n", - "G_primal = momepy.gdf_to_nx(streets, approach=\"primal\", preserve_index=True)\n", - "points_primal, lines_primal = momepy.nx_to_gdf(G_primal, points=True, lines=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "59443a81", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "e1s2 ((1603413.2063240695, 6464228.730248732), (1603585.6402153103, 6464428.773867372), 0)\n", - "e2s2 ((1603413.2063240695, 6464228.730248732), (1603363.557831175, 6464031.88480676), 0)\n", - "e1s1 ((1603413.2063240695, 6464228.730248732), (1603226.9576840235, 6464160.158361825), 0)\n", - "[(1603413.2063240695, 6464228.730248732), (1603274.457710744, 6464178.659351781), (1603226.9576840235, 6464160.158361825)] [(1603585.6402153103, 6464428.773867372), (1603413.2063240695, 6464228.730248732)] [(1603363.557831175, 6464031.88480676), (1603376.5042879563, 6464085.530021086), (1603413.2063240695, 6464228.730248732)]\n" - ] - } - ], - "source": [ - "for e in G_primal.edges((1603413.2063240695, 6464228.730248732), keys=True):\n", - " if G_primal.edges[e][\"edge_id\"] == 4:\n", - " print(\"e1s1\", e)\n", - " e1s1 = G_primal.edges[e][\"geometry\"]\n", - " elif G_primal.edges[e][\"edge_id\"] == 0:\n", - " print(\"e1s2\", e)\n", - " e1s2 = G_primal.edges[e][\"geometry\"]\n", - " elif G_primal.edges[e][\"edge_id\"] == 3:\n", - " print(\"e2s2\", e)\n", - " e2s2 = G_primal.edges[e][\"geometry\"]\n", - "print(e1s1.coords[:], e1s2.coords[:], e2s2.coords[:])" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "7b9e8d0e", - "metadata": {}, - "outputs": [], - "source": [ - "e1s1_geom = e1s1.coords[:2]\n", - "e1s2_geom = e1s2.coords[:2]\n", - "e2s2_geom = e2s2.coords[-2:]" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "0da0e679", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float64(29.396028363390087)" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "get_interior_angle(e1s1_geom[1], e1s1_geom[0], e1s2_geom[0])" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "c1ab91cd", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float64(29.396028363390094)" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "angle(np.array(e1s1_geom[1]) - np.array(e1s1_geom[0]), np.array(e1s2_geom[1]) - np.array(e1s2_geom[0]))" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "9ccbe4d5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float64(29.396028363390087)" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "angle(np.array(e1s1_geom[0]) - np.array(e1s1_geom[1]), np.array(e1s2_geom[1]) - np.array(e1s2_geom[0]))" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "5843905b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float64(29.396028363390094)" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "angle(np.array(e1s1_geom[0]) - np.array(e1s1_geom[1]), np.array(e1s2_geom[0]) - np.array(e1s2_geom[1]))" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "6d0ae741", - "metadata": {}, - "outputs": [], - "source": [ - "def find_geom(linestring, point):\n", - " if point == linestring.coords[0]:\n", - " geom = [np.array(val) for val in linestring.coords[:2]]\n", - " else:\n", - " geom = [np.array(val) for val in linestring.coords[-2:]]\n", - " return np.array(geom[0] - geom[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "d489cd28", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([138.74861333, 50.07089695])" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "find_geom(e1s1, (1603413.2063240695, 6464228.730248732))" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "0e7e6b53", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([138.74861333, 50.07089695])" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array(e1s1_geom[0]) - np.array(e1s1_geom[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "8dfaabd1", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([172.43389124, 200.04361864])" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array(e1s2_geom[0]) - np.array(e1s2_geom[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "d9880de6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([172.43389124, 200.04361864])" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "find_geom(e1s2, (1603413.2063240695, 6464228.730248732))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6c829f65", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ee8b6e50", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "test", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/momepy/strokegraph_function_compare.ipynb b/momepy/strokegraph_function_compare.ipynb deleted file mode 100644 index 2a972bb1..00000000 --- a/momepy/strokegraph_function_compare.ipynb +++ /dev/null @@ -1,1474 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "738651d2", - "metadata": {}, - "outputs": [], - "source": [ - "import geopandas as gpd\n", - "import momepy\n", - "import networkx as nx\n", - "from itertools import combinations, product\n", - "import shapely\n", - "import numpy as np\n", - "import pickle\n", - "\n", - "from shapely import LineString\n", - "import math\n", - "from collections import Counter\n", - "\n", - "import osmnx as ox\n", - "import time" - ] - }, - { - "cell_type": "markdown", - "id": "01166e83", - "metadata": {}, - "source": [ - "## CLSE functions" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "1d99fa24", - "metadata": {}, - "outputs": [], - "source": [ - "def make_stroke_graph_clse(gdf, compute_metric=True, output=\"dataframe\"):\n", - " if output not in [\"dataframe\", \"graph\"]:\n", - " raise ValueError(\"output need to be either dataframe or graph\")\n", - " # Transform into primal graph\n", - " G_primal = momepy.gdf_to_nx(gdf, approach=\"primal\", preserve_index=True)\n", - " lines_primal = momepy.nx_to_gdf(G_primal, points=False, lines=True)\n", - " # Use COINS on primal graph edges\n", - " coins = momepy.COINS(lines_primal)\n", - " # List the stroke for each edge\n", - " stroke_attribute = coins.stroke_attribute()\n", - " # List each edge for each stroke\n", - " stroke_gdf = coins.stroke_gdf()\n", - " stroke_gdf[\"edge_ids\"] = [stroke_attribute[stroke_attribute == stroke_id].index.values for stroke_id in stroke_gdf.index.values]\n", - " # Add stroke ID to each edge\n", - " nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[G_primal.edges[e][\"index_position\"]]) for e in G_primal.edges}, \"stroke_id\")\n", - " # Create stroke graph\n", - " G_stroke = nx.Graph()\n", - " G_stroke.graph[\"crs\"] = G_primal.graph[\"crs\"]\n", - " # Create a node for each stroke with the right features\n", - " G_stroke.add_nodes_from([[int(idx), {(attr if attr != \"geometry\" else \"geometry_stroke\"):stroke_gdf.loc[idx][attr] for attr in list(stroke_gdf)}] for idx in stroke_gdf.index.values])\n", - " # For all node, put its geometry at the center of the LineString\n", - " for n in G_stroke.nodes:\n", - " G_stroke.nodes[n][\"geometry\"] = stroke_gdf.iloc[n].geometry.interpolate(0.5, normalized=True)\n", - " G_stroke.nodes[n][\"x\"] = G_stroke.nodes[n][\"geometry\"].xy[0]\n", - " G_stroke.nodes[n][\"y\"] = G_stroke.nodes[n][\"geometry\"].xy[1]\n", - " G_stroke.nodes[n][\"length\"] = G_stroke.nodes[n][\"geometry_stroke\"].length\n", - " # Find strokes intersecting\n", - " for n in G_primal.nodes:\n", - " strokes_present = [G_primal.edges[e][\"stroke_id\"] for e in G_primal.edges(n, keys=True)]\n", - " # If strokes intersecting, add the edge if not already present\n", - " if len(set(strokes_present)) > 1:\n", - " for u, v in combinations(set(strokes_present), 2):\n", - " # Find all edges touching the node for both strokes checked\n", - " edges_u = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == u]\n", - " edges_v = [e for e in G_primal.edges(n, keys=True) if G_primal.edges[e][\"stroke_id\"] == v]\n", - " angle_list = []\n", - " angle_dict = {}\n", - " # Choose the smallest list as number of angles kept\n", - " chosen, other = sorted([edges_u, edges_v], key=len)\n", - " # Find the angles\n", - " for ce, oe in list(product(chosen, other)):\n", - " point = [G_primal.nodes[n][\"x\"], G_primal.nodes[n][\"y\"]]\n", - " gc = find_geom(G_primal.edges[ce][\"geometry\"], point)\n", - " go = find_geom(G_primal.edges[oe][\"geometry\"], point)\n", - " if ce in angle_dict:\n", - " angle_dict[ce].append(angle(gc, go))\n", - " else:\n", - " angle_dict[ce]= [angle(gc, go)]\n", - " # Keep the smallest angles\n", - " angle_list = [min(angle_dict[ekey]) for ekey in angle_dict]\n", - " if G_stroke.has_edge(u, v):\n", - " G_stroke.edges[u, v][\"angles\"] += angle_list\n", - " G_stroke.edges[u, v][\"number_connections\"] = len(G_stroke.edges[u, v][\"angles\"])\n", - " else:\n", - " G_stroke.add_edge(u, v, geometry = shapely.LineString([G_stroke.nodes[u][\"geometry\"], G_stroke.nodes[v][\"geometry\"]]), number_connections=len(angle_list), angles=angle_list)\n", - " if compute_metric:\n", - " nx.set_node_attributes(G_stroke, nx.betweenness_centrality(G_stroke), \"stroke_betweenness\")\n", - " nx.set_node_attributes(G_stroke, nx.closeness_centrality(G_stroke), \"stroke_closeness\")\n", - " nx.set_node_attributes(G_stroke, dict(nx.degree(G_stroke)), \"stroke_degree\")\n", - " for n in G_stroke.nodes:\n", - " G_stroke.nodes[n][\"stroke_connectivity\"] = sum([G_stroke.edges[e][\"number_connections\"] for e in G_stroke.edges(n)])\n", - " G_stroke.nodes[n][\"stroke_access\"] = G_stroke.nodes[n][\"stroke_connectivity\"] - G_stroke.nodes[n][\"stroke_degree\"]\n", - " angles = [val for e in G_stroke.edges(n) if G_stroke.edges[e][\"angles\"] for val in G_stroke.edges[e][\"angles\"]]\n", - " G_stroke.nodes[n][\"stroke_orthogonality\"] = sum(angles) / G_stroke.nodes[n][\"stroke_connectivity\"]\n", - " G_stroke.nodes[n][\"stroke_spacing\"] = G_stroke.nodes[n][\"length\"] / G_stroke.nodes[n][\"stroke_connectivity\"]\n", - " if output == \"dataframe\":\n", - " return momepy.nx_to_gdf(G_stroke, points=True, lines=True)\n", - " elif output == \"graph\":\n", - " return G_stroke\n", - "\n", - "def angle(a, b):\n", - " angle = np.rad2deg(np.arccos(np.dot(a, b)/(np.linalg.norm(a) * np.linalg.norm(b))))\n", - " if angle > 90:\n", - " angle = 180 - angle\n", - " return angle\n", - "\n", - "def find_geom(linestring, point):\n", - " if point == list(linestring.coords[0]):\n", - " geom = [np.array(val) for val in linestring.coords[:2]]\n", - " else:\n", - " geom = [np.array(val) for val in linestring.coords[-2:]]\n", - " return np.array(geom[0] - geom[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "7a369a85", - "metadata": {}, - "outputs": [], - "source": [ - "# define variable defaults (will be arguments passed to future function)\n", - "angle_threshold=0\n", - "flow_mode=False\n", - "# remove false nodes\n", - "\n", - "def make_stroke_graph_anvy(gdf, compute_metric=True, output=\"dataframe\"):\n", - " # make primal graph\n", - " graph = momepy.gdf_to_nx(\n", - " gdf, \n", - " preserve_index=True, # index of lines gdf should be referring to EXACTLY THE SAME ELEMENT as index of streets gdf\n", - " approach=\"primal\"\n", - " )\n", - " # get gdfs of points and lines\n", - " points, lines = momepy.nx_to_gdf(graph, points=True, lines=True)\n", - " lines[\"my_index\"] = lines.index # just for plotting TODO remove later\n", - " # make coins\n", - " coins = momepy.COINS(lines, angle_threshold=angle_threshold, flow_mode=flow_mode)\n", - " # get gdfs from COINS class\n", - " stroke_attribute = coins.stroke_attribute()\n", - " stroke_gdf = coins.stroke_gdf()\n", - " stroke_gdf[\"rep_point\"] = stroke_gdf.geometry.apply(lambda x: x.interpolate(0.5, normalized=True))\n", - " # add stroke_id column\n", - " stroke_gdf[\"stroke_id\"] = stroke_gdf.index\n", - " # add edge_ids column (using COINS.stroke_attribute to map into ID defined in lines gdf)\n", - " stroke_gdf[\"edge_indeces\"] = stroke_gdf.stroke_id.apply(\n", - " lambda x: list(stroke_attribute[stroke_attribute==x].index)\n", - " )\n", - " # make dictionary for primal graph: d={edge_index:edge_name}\n", - " # where edge_name (in momepy language) is the corresponding node tuple\n", - " d_name2index = nx.get_edge_attributes(graph, \"index_position\")\n", - " d_index2name = {v:k for k,v in d_name2index.items()}\n", - " # for each edge, add \"stroke_id\" as attribute to graph\n", - " for _, row in stroke_gdf.iterrows():\n", - " for edge_index in row.edge_indeces: \n", - " graph.edges[d_index2name[edge_index]][\"stroke_id\"] = row.stroke_id\n", - " # getting dicts of edge name : stroke ID, and edge index : stroke id # TODO: one of them might be obsolete?\n", - " d_name2stroke = nx.get_edge_attributes(graph, \"stroke_id\")\n", - " d_index2stroke = {d_name2index[k]:v for k,v in d_name2stroke.items()} \n", - " stroke_graph = nx.Graph()\n", - " stroke_graph.graph[\"crs\"] = graph.graph[\"crs\"]\n", - " stroke_graph.graph[\"approach\"] = graph.graph[\"approach\"]\n", - " stroke_graph.add_nodes_from(\n", - " [\n", - " (\n", - " row.stroke_id, \n", - " {\n", - " \"edge_indeces\": row.edge_indeces,\n", - " \"geometry\": row.rep_point,\n", - " \"geometry_stroke\": row.geometry,\n", - " \"x\": row.rep_point.xy[0][0],\n", - " \"y\": row.rep_point.xy[1][0],\n", - " \"connectivity\": 0\n", - " }\n", - " ) for _, row in stroke_gdf.iterrows()\n", - " ]\n", - " )\n", - " # node names are the stroke IDs.\n", - " # each node has the attribute \"edge_indeces\".\n", - " stroke_graph.nodes(data=True)\n", - " for n in graph.nodes:\n", - " es = list(graph.edges(n, keys=True))\n", - " stroke_list = [graph.edges[e][\"stroke_id\"] for e in es]\n", - " stroke_set = set(stroke_list)\n", - " # for all size2 combinations from stroke_set\n", - " for c in combinations(stroke_set, 2):\n", - " # get angles at that primal node for this 2-stroke combination c\n", - " es = list(graph.edges(n, keys=True))\n", - " stroke_ids = [graph.edges[e][\"stroke_id\"] for e in es]\n", - " geoms = [graph.edges[e][\"geometry\"] for e in es]\n", - " segments = [get_segment(geom, n) for geom in geoms] # extracting only edge segments that touch this node\n", - " angles_gdf = gpd.GeoDataFrame(\n", - " {\n", - " \"stroke_id\": stroke_ids,\n", - " \"segment\": segments,\n", - " \"geometry\": [LineString(x) for x in segments]\n", - " }\n", - " )\n", - " # filter out only those linestring that belong to current 2-stroke edge\n", - " angles_gdf = angles_gdf[angles_gdf.stroke_id.isin(c)].reset_index(drop=True)\n", - " if len(angles_gdf)==2:\n", - " # connectivity equals 1 here\n", - " connectivity = 1\n", - " # angle between 2 strokes is just angle between \n", - " # the 2 linestrings in the gdf:\n", - " row_a = angles_gdf.loc[0]\n", - " row_b = angles_gdf.loc[1]\n", - " angles = [\n", - " get_interior_angle(\n", - " row_a.segment[1],\n", - " row_a.segment[0],\n", - " row_b.segment[1]\n", - " )\n", - " ]\n", - " elif len(angles_gdf)==3:\n", - " # connectivity equals 1 here\n", - " connectivity = 1\n", - " # the iteration has to go through the stroke that appears TWICE\n", - " stroke_count = dict(Counter(angles_gdf.stroke_id))\n", - " stroke_count = {v:k for k,v in stroke_count.items()}\n", - " # separate angles_gdf into 2 separate gdf (one for each stroke)\n", - " angles_stroke_a = angles_gdf[angles_gdf[\"stroke_id\"]==stroke_count[1]].copy()\n", - " angles_stroke_b = angles_gdf[angles_gdf[\"stroke_id\"]==stroke_count[2]].copy()\n", - " angles = []\n", - " # there is only ONE row_a stroke segment\n", - " for i, row_a in angles_stroke_a.iterrows():\n", - " angles_stroke = []\n", - " # iterate through BOTH stroke b segments\n", - " for j, row_b in angles_stroke_b.iterrows():\n", - " assert row_a.segment[0] == row_b.segment[0]\n", - " # compute angle between stroke a and stroke b segments\n", - " # and add to list of current angles\n", - " angles_stroke.append(get_interior_angle(\n", - " row_a.segment[1],\n", - " row_a.segment[0],\n", - " row_b.segment[1])\n", - " )\n", - " # keep the smaller of the 2 angles to add to list of angles for the stroke pair\n", - " angles.append(min(angles_stroke))\n", - " elif len(angles_gdf)==4:\n", - " # connectivity equals 2 here\n", - " connectivity = 2\n", - " # separate angles_gdf into 2 separate gdf (one for each stroke)\n", - " angles_stroke_a = angles_gdf[angles_gdf[\"stroke_id\"]==c[0]].copy()\n", - " angles_stroke_b = angles_gdf[angles_gdf[\"stroke_id\"]==c[1]].copy()\n", - " angles = []\n", - " # iterate through stroke a segments\n", - " for i, row_a in angles_stroke_a.iterrows():\n", - " # iterate through stroke b segments\n", - " angles_partial = []\n", - " for j, row_b in angles_stroke_b.iterrows():\n", - " assert row_a.segment[0] == row_b.segment[0]\n", - " # compute angle between stroke a and stroke b segments\n", - " # and add to list of current angles\n", - " angle = get_interior_angle(\n", - " row_a.segment[1],\n", - " row_a.segment[0],\n", - " row_b.segment[1])\n", - " # if angle > 90:\n", - " # angle = 180 - angle\n", - " angles_partial.append(angle)\n", - " angles.append(min(angles_partial)) # @csebastiao we're keeping the minimal here?\n", - " else:\n", - " ValueError(f\"Length of angles_gdf expected to be in [2,3,4], but is {len(angles_gdf)}\")\n", - " # connectivity is added at stroke node level:\n", - " for s in c:\n", - " stroke_graph.nodes[s][\"connectivity\"] += connectivity\n", - " # and edge (or update edge info) at stroke edge level:\n", - " if c not in stroke_graph.edges:\n", - " edge_geom = LineString(\n", - " [\n", - " stroke_graph.nodes[c[0]][\"geometry\"],\n", - " stroke_graph.nodes[c[1]][\"geometry\"]\n", - " ]\n", - " )\n", - " stroke_graph.add_edge(\n", - " c[0],\n", - " c[1],\n", - " geometry=edge_geom,\n", - " angles=angles\n", - " )\n", - " else:\n", - " stroke_graph.edges[c][\"angles\"] += angles\n", - " # we want to add edges for all stroke IDs that co-occur on edges that share the same node in the primal graph\n", - " # [0, 1, 1] means: stroke0 has an endpoint here; stroke1 has a throughpoint here; we add the edge [0,1] in the strokes_graph, with the attribute \n", - " # stroke = {0: \"end\", 1: \"through\"}\n", - " # add graph metrics\n", - " # betweenness centrality dict for all nodes\n", - " if compute_metric:\n", - " bc = nx.betweenness_centrality(stroke_graph)\n", - " # closeness centrality dict for all nodes\n", - " cc = nx.closeness_centrality(stroke_graph)\n", - " for n in stroke_graph.nodes:\n", - " stroke_graph.nodes[n][\"degree\"] = nx.degree(stroke_graph, n)\n", - " stroke_graph.nodes[n][\"betweenness_centrality\"] = bc[n]\n", - " stroke_graph.nodes[n][\"closeness_centrality\"] = cc[n]\n", - " # just for sanity check # TODO can be removed later\n", - " stroke_graph.nodes[n][\"connectivity_computed\"] = sum(\n", - " [len(stroke_graph.edges[edge][\"angles\"]) for edge in stroke_graph.edges(n)]\n", - " ) \n", - " assert stroke_graph.nodes[n][\"connectivity\"] == stroke_graph.nodes[n][\"connectivity_computed\"]\n", - " # access = abs(connectivity - degree)\n", - " stroke_graph.nodes[n][\"access\"] = abs(stroke_graph.nodes[n][\"connectivity\"] - stroke_graph.nodes[n][\"degree\"])\n", - " # spacing = length / connectivity\n", - " stroke_graph.nodes[n][\"length\"] = stroke_graph.nodes[n][\"geometry_stroke\"].length # compute length first\n", - " stroke_graph.nodes[n][\"spacing\"] = stroke_graph.nodes[n][\"length\"] / stroke_graph.nodes[n][\"connectivity\"]\n", - " # orthogonality = sum(angles) / connectivity\n", - " # compute sum of angles of edges of that node first\n", - " node_angles = [stroke_graph.edges[edge][\"angles\"] for edge in stroke_graph.edges(n)]\n", - " node_angles = [item for sublist in node_angles for item in sublist] # un-nest list\n", - " stroke_graph.nodes[n][\"orthogonality\"] = sum(node_angles)/stroke_graph.nodes[n][\"connectivity\"]\n", - " if output == \"dataframe\":\n", - " return momepy.nx_to_gdf(stroke_graph, points=True, lines=True)\n", - " elif output == \"graph\":\n", - " return stroke_graph\n", - "\n", - "def get_interior_angle(a, b, c):\n", - " \"\"\"\n", - " Measure the angle between a-b, b-c (in degrees).\n", - " \"\"\"\n", - " ba = [a[0]-b[0],a[1]-b[1]]\n", - " bc = [c[0]-b[0],c[1]-b[1]]\n", - " # np.dot(ba, bc) # ba[0]*bc[0] + ba[1]*bc[1]\n", - " # np.linalg.norm(ba) # np.sqrt(ba[0]**2+ba[1]**2)\n", - " # np.linalg.norm(bc) # np.sqrt(bc[0]**2+bc[1]**2)\n", - " theta_rad = math.acos(np.dot(ba,bc)/(np.linalg.norm(ba)*np.linalg.norm(bc)))\n", - " theta_deg = np.degrees(theta_rad)\n", - " if theta_deg > 90:\n", - " theta_deg = 180 - theta_deg\n", - " return theta_deg\n", - "\n", - "def get_segment(geom, n):\n", - " '''\n", - " geom... linestring.\n", - " n.... coordinate of start-or-end node on linestring.\n", - " returns: coordinate tuple (n, adjacent-to-n), in THAT ORDER\n", - " (ie. if n is start node, returns coords in position 0 and 1;\n", - " if n is end node, reutnrs coords in position n, n-1\n", - " )\n", - " '''\n", - " coords = [c for c in geom.coords]\n", - " index_n = coords.index(n)\n", - " if index_n == 0:\n", - " return coords[0:2]\n", - " elif index_n == len(coords)-1:\n", - " return [coords[index_n], coords[index_n-1]]\n", - " else:\n", - " raise ValueError(\"Node not on end of edge?\")\n", - "\n", - "# use angles_gdf length to add to connectivity of strokes (nodes)\n", - "def get_connectivity(angles_gdf):\n", - " if len(angles_gdf)==4:\n", - " return 2\n", - " elif len(angles_gdf) in [2,3]:\n", - " return 1\n", - " else:\n", - " raise ValueError(\"Unexpected number of edge segments in angles_gdf\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "eec125ad", - "metadata": {}, - "outputs": [], - "source": [ - "gdf = gpd.read_file(momepy.datasets.get_path(\"bubenec\"), layer=\"streets\")\n", - "gdf = momepy.remove_false_nodes(gdf)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "2d193aa8", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float64(0.03989638328552246)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "arr = []\n", - "for _ in range(100):\n", - " beg = time.time()\n", - " G_stroke_clse = make_stroke_graph_clse(gdf, compute_metric=True, output=\"graph\")\n", - " end = time.time()\n", - " arr.append(end - beg)\n", - "np.mean(arr)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "b72b7c07", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float64(0.09599937915802002)" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "arr = []\n", - "for _ in range(100):\n", - " beg = time.time()\n", - " G_stroke_anvy = make_stroke_graph_anvy(gdf, compute_metric=True, output=\"graph\")\n", - " end = time.time()\n", - " arr.append(end - beg)\n", - "np.mean(arr)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "92c9d466", - "metadata": {}, - "outputs": [], - "source": [ - "G = ox.graph_from_place(\"Aix-en-Provence, France\")" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "3a02b257", - "metadata": {}, - "outputs": [], - "source": [ - "G = ox.convert.to_undirected(G)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "7200ae13", - "metadata": {}, - "outputs": [], - "source": [ - "gdf = ox.graph_to_gdfs(\n", - " G,\n", - " nodes=False,\n", - " edges=True,\n", - " node_geometry=False,\n", - " fill_edge_geometry=True,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "bfa58f48", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
osmidhighwaylanesmaxspeednameonewayrefreversedlengthgeometryfromtobridgejunctionaccessservicewidthtunnel
uvkey
553604594607072300[355742063, 147498237, 90283751]trunk2[90, 70]Avenue de la 1e Division FrançaiseTrueN 296False1038.297695LINESTRING (5.44934 43.55847, 5.44908 43.55836...55360459460707230NaNNaNNaNNaNNaNNaN
2770354880[90283752, 90283753, 25419836]trunk_link1110NaNTrueNaNFalse224.338024LINESTRING (5.45133 43.55971, 5.45138 43.55962...2770354885536045yesNaNNaNNaNNaNNaN
10470014030[685260154, 90283748, 90283751]trunk290Avenue de la 1e Division FrançaiseTrueN 296False364.686411LINESTRING (5.45305 43.56034, 5.45259 43.56007...10470014035536045yesNaNNaNNaNNaNNaN
55360522654890260[90731432, 31557546, 179308707]trunk250Avenue de la 1e Division FrançaiseTrueN 296False198.965351LINESTRING (5.43573 43.55346, 5.43543 43.55318...5536052265489026yesNaNNaNNaNNaNNaN
85184530060[90283320, 90283321, 179308930]trunk_linkNaN50NaNTrueNaNFalse147.744228LINESTRING (5.43573 43.55346, 5.43558 43.55335...55360528518453006yesNaNNaNNaNNaNNaN
...............................................................
12819726786128197267930[1384658856, 1384658857]trackNaNNaNNaNFalseNaNFalse117.859117LINESTRING (5.42804 43.59214, 5.42799 43.59202...1281972679312819726786NaNNaNNaNNaNNaNNaN
128407239071284072391801387085145footwayNaNNaNNaNFalseNaNTrue8.950842LINESTRING (5.34713 43.4941, 5.34714 43.49413,...1284072391812840723907NaNNaNNaNNaNNaNNaN
128407239081284072391301387085143serviceNaNNaNNaNFalseNaNTrue33.678924LINESTRING (5.34654 43.4942, 5.34653 43.49421,...1284072391312840723908NaNNaNNaNparking_aisleNaNNaN
128407239111284072391301387085143serviceNaNNaNNaNFalseNaNFalse28.646349LINESTRING (5.34654 43.4942, 5.34656 43.49414,...1284072391312840723911NaNNaNNaNparking_aisleNaNNaN
128407239131284072391501387085144footwayNaNNaNNaNFalseNaNTrue42.460380LINESTRING (5.34696 43.49408, 5.34698 43.49414...1284072391512840723913NaNNaNNaNNaNNaNNaN
\n", - "

28913 rows × 18 columns

\n", - "
" - ], - "text/plain": [ - " osmid highway \\\n", - "u v key \n", - "5536045 9460707230 0 [355742063, 147498237, 90283751] trunk \n", - " 277035488 0 [90283752, 90283753, 25419836] trunk_link \n", - " 1047001403 0 [685260154, 90283748, 90283751] trunk \n", - "5536052 265489026 0 [90731432, 31557546, 179308707] trunk \n", - " 8518453006 0 [90283320, 90283321, 179308930] trunk_link \n", - "... ... ... \n", - "12819726786 12819726793 0 [1384658856, 1384658857] track \n", - "12840723907 12840723918 0 1387085145 footway \n", - "12840723908 12840723913 0 1387085143 service \n", - "12840723911 12840723913 0 1387085143 service \n", - "12840723913 12840723915 0 1387085144 footway \n", - "\n", - " lanes maxspeed \\\n", - "u v key \n", - "5536045 9460707230 0 2 [90, 70] \n", - " 277035488 0 1 110 \n", - " 1047001403 0 2 90 \n", - "5536052 265489026 0 2 50 \n", - " 8518453006 0 NaN 50 \n", - "... ... ... \n", - "12819726786 12819726793 0 NaN NaN \n", - "12840723907 12840723918 0 NaN NaN \n", - "12840723908 12840723913 0 NaN NaN \n", - "12840723911 12840723913 0 NaN NaN \n", - "12840723913 12840723915 0 NaN NaN \n", - "\n", - " name oneway \\\n", - "u v key \n", - "5536045 9460707230 0 Avenue de la 1e Division Française True \n", - " 277035488 0 NaN True \n", - " 1047001403 0 Avenue de la 1e Division Française True \n", - "5536052 265489026 0 Avenue de la 1e Division Française True \n", - " 8518453006 0 NaN True \n", - "... ... ... \n", - "12819726786 12819726793 0 NaN False \n", - "12840723907 12840723918 0 NaN False \n", - "12840723908 12840723913 0 NaN False \n", - "12840723911 12840723913 0 NaN False \n", - "12840723913 12840723915 0 NaN False \n", - "\n", - " ref reversed length \\\n", - "u v key \n", - "5536045 9460707230 0 N 296 False 1038.297695 \n", - " 277035488 0 NaN False 224.338024 \n", - " 1047001403 0 N 296 False 364.686411 \n", - "5536052 265489026 0 N 296 False 198.965351 \n", - " 8518453006 0 NaN False 147.744228 \n", - "... ... ... ... \n", - "12819726786 12819726793 0 NaN False 117.859117 \n", - "12840723907 12840723918 0 NaN True 8.950842 \n", - "12840723908 12840723913 0 NaN True 33.678924 \n", - "12840723911 12840723913 0 NaN False 28.646349 \n", - "12840723913 12840723915 0 NaN True 42.460380 \n", - "\n", - " geometry \\\n", - "u v key \n", - "5536045 9460707230 0 LINESTRING (5.44934 43.55847, 5.44908 43.55836... \n", - " 277035488 0 LINESTRING (5.45133 43.55971, 5.45138 43.55962... \n", - " 1047001403 0 LINESTRING (5.45305 43.56034, 5.45259 43.56007... \n", - "5536052 265489026 0 LINESTRING (5.43573 43.55346, 5.43543 43.55318... \n", - " 8518453006 0 LINESTRING (5.43573 43.55346, 5.43558 43.55335... \n", - "... ... \n", - "12819726786 12819726793 0 LINESTRING (5.42804 43.59214, 5.42799 43.59202... \n", - "12840723907 12840723918 0 LINESTRING (5.34713 43.4941, 5.34714 43.49413,... \n", - "12840723908 12840723913 0 LINESTRING (5.34654 43.4942, 5.34653 43.49421,... \n", - "12840723911 12840723913 0 LINESTRING (5.34654 43.4942, 5.34656 43.49414,... \n", - "12840723913 12840723915 0 LINESTRING (5.34696 43.49408, 5.34698 43.49414... \n", - "\n", - " from to bridge junction access \\\n", - "u v key \n", - "5536045 9460707230 0 5536045 9460707230 NaN NaN NaN \n", - " 277035488 0 277035488 5536045 yes NaN NaN \n", - " 1047001403 0 1047001403 5536045 yes NaN NaN \n", - "5536052 265489026 0 5536052 265489026 yes NaN NaN \n", - " 8518453006 0 5536052 8518453006 yes NaN NaN \n", - "... ... ... ... ... ... \n", - "12819726786 12819726793 0 12819726793 12819726786 NaN NaN NaN \n", - "12840723907 12840723918 0 12840723918 12840723907 NaN NaN NaN \n", - "12840723908 12840723913 0 12840723913 12840723908 NaN NaN NaN \n", - "12840723911 12840723913 0 12840723913 12840723911 NaN NaN NaN \n", - "12840723913 12840723915 0 12840723915 12840723913 NaN NaN NaN \n", - "\n", - " service width tunnel \n", - "u v key \n", - "5536045 9460707230 0 NaN NaN NaN \n", - " 277035488 0 NaN NaN NaN \n", - " 1047001403 0 NaN NaN NaN \n", - "5536052 265489026 0 NaN NaN NaN \n", - " 8518453006 0 NaN NaN NaN \n", - "... ... ... ... \n", - "12819726786 12819726793 0 NaN NaN NaN \n", - "12840723907 12840723918 0 NaN NaN NaN \n", - "12840723908 12840723913 0 parking_aisle NaN NaN \n", - "12840723911 12840723913 0 parking_aisle NaN NaN \n", - "12840723913 12840723915 0 NaN NaN NaN \n", - "\n", - "[28913 rows x 18 columns]" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "gdf" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "f2b1a6a7", - "metadata": {}, - "outputs": [], - "source": [ - "gdf = gdf.to_crs(epsg=3857)\n", - "gdf = gdf[~gdf.geometry.duplicated()]" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "c40e84c7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
osmidhighwaylanesmaxspeednameonewayrefreversedlengthgeometryfromtobridgejunctionaccessservicewidthtunnel
uvkey
553604594607072300[355742063, 147498237, 90283751]trunk2[90, 70]Avenue de la 1e Division FrançaiseTrueN 296False1038.297695LINESTRING (606617.776 5397366.114, 606588.822...55360459460707230NaNNaNNaNNaNNaNNaN
2770354880[90283752, 90283753, 25419836]trunk_link1110NaNTrueNaNFalse224.338024LINESTRING (606839.625 5397557.657, 606845.102...2770354885536045yesNaNNaNNaNNaNNaN
10470014030[685260154, 90283748, 90283751]trunk290Avenue de la 1e Division FrançaiseTrueN 296False364.686411LINESTRING (607030.872 5397653.622, 606980.066...10470014035536045yesNaNNaNNaNNaNNaN
55360522654890260[90731432, 31557546, 179308707]trunk250Avenue de la 1e Division FrançaiseTrueN 296False198.965351LINESTRING (605102.985 5396597.832, 605069.767...5536052265489026yesNaNNaNNaNNaNNaN
85184530060[90283320, 90283321, 179308930]trunk_linkNaN50NaNTrueNaNFalse147.744228LINESTRING (605102.985 5396597.832, 605085.53 ...55360528518453006yesNaNNaNNaNNaNNaN
...............................................................
12819726786128197267930[1384658856, 1384658857]trackNaNNaNNaNFalseNaNFalse117.859117LINESTRING (604246.326 5402539.811, 604240.827...1281972679312819726786NaNNaNNaNNaNNaNNaN
128407239071284072391801387085145footwayNaNNaNNaNFalseNaNTrue8.950842LINESTRING (595239.934 5387483.659, 595240.379...1284072391812840723907NaNNaNNaNNaNNaNNaN
128407239081284072391301387085143serviceNaNNaNNaNFalseNaNTrue33.678924LINESTRING (595173.765 5387499.526, 595173.164...1284072391312840723908NaNNaNNaNparking_aisleNaNNaN
128407239111284072391301387085143serviceNaNNaNNaNFalseNaNFalse28.646349LINESTRING (595173.765 5387499.526, 595176.704...1284072391312840723911NaNNaNNaNparking_aisleNaNNaN
128407239131284072391501387085144footwayNaNNaNNaNFalseNaNTrue42.460380LINESTRING (595221.143 5387481.005, 595222.534...1284072391512840723913NaNNaNNaNNaNNaNNaN
\n", - "

28913 rows × 18 columns

\n", - "
" - ], - "text/plain": [ - " osmid highway \\\n", - "u v key \n", - "5536045 9460707230 0 [355742063, 147498237, 90283751] trunk \n", - " 277035488 0 [90283752, 90283753, 25419836] trunk_link \n", - " 1047001403 0 [685260154, 90283748, 90283751] trunk \n", - "5536052 265489026 0 [90731432, 31557546, 179308707] trunk \n", - " 8518453006 0 [90283320, 90283321, 179308930] trunk_link \n", - "... ... ... \n", - "12819726786 12819726793 0 [1384658856, 1384658857] track \n", - "12840723907 12840723918 0 1387085145 footway \n", - "12840723908 12840723913 0 1387085143 service \n", - "12840723911 12840723913 0 1387085143 service \n", - "12840723913 12840723915 0 1387085144 footway \n", - "\n", - " lanes maxspeed \\\n", - "u v key \n", - "5536045 9460707230 0 2 [90, 70] \n", - " 277035488 0 1 110 \n", - " 1047001403 0 2 90 \n", - "5536052 265489026 0 2 50 \n", - " 8518453006 0 NaN 50 \n", - "... ... ... \n", - "12819726786 12819726793 0 NaN NaN \n", - "12840723907 12840723918 0 NaN NaN \n", - "12840723908 12840723913 0 NaN NaN \n", - "12840723911 12840723913 0 NaN NaN \n", - "12840723913 12840723915 0 NaN NaN \n", - "\n", - " name oneway \\\n", - "u v key \n", - "5536045 9460707230 0 Avenue de la 1e Division Française True \n", - " 277035488 0 NaN True \n", - " 1047001403 0 Avenue de la 1e Division Française True \n", - "5536052 265489026 0 Avenue de la 1e Division Française True \n", - " 8518453006 0 NaN True \n", - "... ... ... \n", - "12819726786 12819726793 0 NaN False \n", - "12840723907 12840723918 0 NaN False \n", - "12840723908 12840723913 0 NaN False \n", - "12840723911 12840723913 0 NaN False \n", - "12840723913 12840723915 0 NaN False \n", - "\n", - " ref reversed length \\\n", - "u v key \n", - "5536045 9460707230 0 N 296 False 1038.297695 \n", - " 277035488 0 NaN False 224.338024 \n", - " 1047001403 0 N 296 False 364.686411 \n", - "5536052 265489026 0 N 296 False 198.965351 \n", - " 8518453006 0 NaN False 147.744228 \n", - "... ... ... ... \n", - "12819726786 12819726793 0 NaN False 117.859117 \n", - "12840723907 12840723918 0 NaN True 8.950842 \n", - "12840723908 12840723913 0 NaN True 33.678924 \n", - "12840723911 12840723913 0 NaN False 28.646349 \n", - "12840723913 12840723915 0 NaN True 42.460380 \n", - "\n", - " geometry \\\n", - "u v key \n", - "5536045 9460707230 0 LINESTRING (606617.776 5397366.114, 606588.822... \n", - " 277035488 0 LINESTRING (606839.625 5397557.657, 606845.102... \n", - " 1047001403 0 LINESTRING (607030.872 5397653.622, 606980.066... \n", - "5536052 265489026 0 LINESTRING (605102.985 5396597.832, 605069.767... \n", - " 8518453006 0 LINESTRING (605102.985 5396597.832, 605085.53 ... \n", - "... ... \n", - "12819726786 12819726793 0 LINESTRING (604246.326 5402539.811, 604240.827... \n", - "12840723907 12840723918 0 LINESTRING (595239.934 5387483.659, 595240.379... \n", - "12840723908 12840723913 0 LINESTRING (595173.765 5387499.526, 595173.164... \n", - "12840723911 12840723913 0 LINESTRING (595173.765 5387499.526, 595176.704... \n", - "12840723913 12840723915 0 LINESTRING (595221.143 5387481.005, 595222.534... \n", - "\n", - " from to bridge junction access \\\n", - "u v key \n", - "5536045 9460707230 0 5536045 9460707230 NaN NaN NaN \n", - " 277035488 0 277035488 5536045 yes NaN NaN \n", - " 1047001403 0 1047001403 5536045 yes NaN NaN \n", - "5536052 265489026 0 5536052 265489026 yes NaN NaN \n", - " 8518453006 0 5536052 8518453006 yes NaN NaN \n", - "... ... ... ... ... ... \n", - "12819726786 12819726793 0 12819726793 12819726786 NaN NaN NaN \n", - "12840723907 12840723918 0 12840723918 12840723907 NaN NaN NaN \n", - "12840723908 12840723913 0 12840723913 12840723908 NaN NaN NaN \n", - "12840723911 12840723913 0 12840723913 12840723911 NaN NaN NaN \n", - "12840723913 12840723915 0 12840723915 12840723913 NaN NaN NaN \n", - "\n", - " service width tunnel \n", - "u v key \n", - "5536045 9460707230 0 NaN NaN NaN \n", - " 277035488 0 NaN NaN NaN \n", - " 1047001403 0 NaN NaN NaN \n", - "5536052 265489026 0 NaN NaN NaN \n", - " 8518453006 0 NaN NaN NaN \n", - "... ... ... ... \n", - "12819726786 12819726793 0 NaN NaN NaN \n", - "12840723907 12840723918 0 NaN NaN NaN \n", - "12840723908 12840723913 0 parking_aisle NaN NaN \n", - "12840723911 12840723913 0 parking_aisle NaN NaN \n", - "12840723913 12840723915 0 NaN NaN NaN \n", - "\n", - "[28913 rows x 18 columns]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "gdf" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "f6630cf5", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/mb/_ysy1pzs13qgnh9b942_7lkh0000gn/T/ipykernel_14835/721137014.py:15: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " nx.set_edge_attributes(G_primal, {e: int(stroke_attribute[G_primal.edges[e][\"index_position\"]]) for e in G_primal.edges}, \"stroke_id\")\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "498.3172490596771\n" - ] - } - ], - "source": [ - "beg = time.time()\n", - "G_stroke_clse = make_stroke_graph_clse(gdf, compute_metric=True, output=\"graph\")\n", - "print(time.time() - beg)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "30ef878f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "gdf.plot()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "ccab49f2", - "metadata": {}, - "outputs": [ - { - "ename": "KeyError", - "evalue": "(5536045, 9460707230, 0)", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mKeyError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[15]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m beg = time.time()\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m G_stroke_anvy = \u001b[43mmake_stroke_graph_anvy\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcompute_metric\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moutput\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mgraph\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 3\u001b[39m \u001b[38;5;28mprint\u001b[39m(time.time() - beg)\n", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 35\u001b[39m, in \u001b[36mmake_stroke_graph_anvy\u001b[39m\u001b[34m(gdf, compute_metric, output)\u001b[39m\n\u001b[32m 33\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m _, row \u001b[38;5;129;01min\u001b[39;00m stroke_gdf.iterrows():\n\u001b[32m 34\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m edge_index \u001b[38;5;129;01min\u001b[39;00m row.edge_indeces: \n\u001b[32m---> \u001b[39m\u001b[32m35\u001b[39m graph.edges[\u001b[43md_index2name\u001b[49m\u001b[43m[\u001b[49m\u001b[43medge_index\u001b[49m\u001b[43m]\u001b[49m][\u001b[33m\"\u001b[39m\u001b[33mstroke_id\u001b[39m\u001b[33m\"\u001b[39m] = row.stroke_id\n\u001b[32m 36\u001b[39m \u001b[38;5;66;03m# getting dicts of edge name : stroke ID, and edge index : stroke id # TODO: one of them might be obsolete?\u001b[39;00m\n\u001b[32m 37\u001b[39m d_name2stroke = nx.get_edge_attributes(graph, \u001b[33m\"\u001b[39m\u001b[33mstroke_id\u001b[39m\u001b[33m\"\u001b[39m)\n", - "\u001b[31mKeyError\u001b[39m: (5536045, 9460707230, 0)" - ] - } - ], - "source": [ - "beg = time.time()\n", - "G_stroke_anvy = make_stroke_graph_anvy(gdf, compute_metric=True, output=\"graph\")\n", - "print(time.time() - beg)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a6ef3cbb", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "momepy_dev", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}