Docs: is_1d() and is_2d() are now under Methods and not Attributes. Improved some more docstrings.

Author: knutfrode

docs/source/api.rst

@@ -94,8 +94,6 @@ Attributes
     Dataset.traj.tlon
     Dataset.traj.tlat
     Dataset.traj.crs
-    Dataset.traj.is_1d
-    Dataset.traj.is_2d
 
 .. _dsmeth:
 
@@ -121,6 +119,8 @@ Methods
     Dataset.traj.get_area_convex_hull
     Dataset.traj.gridtime
     Dataset.traj.seltime
+    Dataset.traj.is_1d
+    Dataset.traj.is_2d
 
 .. currentmodule:: trajan
 

docs/source/conf.py

@@ -84,7 +84,6 @@
     "members": True,
     "undoc-members": True,
     "private-members": True,
-    "show-inheritance": True,
 }
 napoleon_use_param = True
 napoleon_use_rtype = True

trajan/__init__.py

@@ -33,17 +33,16 @@ def from_dataframe(df: pd.DataFrame,
     Construct a CF-compliant trajectory dataset from a `pd.DataFrame` of positions.
 
     Args:
-
-        `lon`: name of column containing longitudes.
-
-        `lat`: name of column containing latitudes.
-
-        `time`: name of column containing timestamps (parsable by pandas).
-
-        `name`: name of column to be used for drifter names.
+        `lon`: str
+            Name of column containing longitudes.
+        `lat`: str
+            Name of column containing latitudes.
+        `time`: str
+            Name of column containing timestamps (parsable by pandas).
+        `name`: str
+            Name of column to be used for drifter names.
 
     Returns:
-
         `ds`: a CF-compliant trajectory `xarray.Dataset`.
 
 
@@ -155,14 +154,16 @@ def trajectory_dict_to_dataset(trajectory_dict,
                                global_attributes=None):
     """Create a CF-compatible trajectory file from dictionary of drifter positions
 
-    Trajectory_dict shall have the following structure:
+    Trajectory_dict shall have the following structure::
+
         {'buoy1_name': {
             time0: {'lon': lon0, 'lat': lat0, 'variable1': var1_0, ... 'variableM': varM_0},
             time1: {'lon': lon1, 'lat': lat1, 'variable1': var1_1, ... 'variableM': varM_1},
                 ...
             timeN: {'lon': lonN, 'lat': latN, 'variable1': var1_N, ... 'variableM': varM_N}},
         {'buoy2_name': {
             ...
+
     """
 
     if variable_attributes is None:

trajan/plot/spectra.py

@@ -27,35 +27,29 @@ def plot_trajan_spectra(
     horizontal time basis.
 
     Args:
-
-        `xr_trajan_in`: input xarray following the trajan conventions
-
+        `xr_trajan_in`:
+            input xarray following the trajan conventions
         `tuple_date_start_end`: can be either:
-            - None to plot over the full datetime range available across
-            trajectories
-            - a tuple of datetimes (datetime_start, datetime_end) to set
-            the time axis limits explicitely
-
+            - None to plot over the full datetime range available across trajectories
+            - a tuple of datetimes (datetime_start, datetime_end) to set the time axis limits explicitely
         `tuple_vrange_pcolor`: can be either:
             - None to use the default log range [-3.0, 1.0]
             - a tuple of float to set the log range explicitely
-
-        `plt_show`: bool flag, wether to show the figure or not
-
+        `plt_show`: bool flag
+            Whether to show the figure or not
         `fignamesave`: can be either:
             - None to not save the figure
-            - a valid filename string or path ending in .png or .pdf to save
-            the figure to disk
-
-        `field`: string, the xr_trajan_in field to use as the 1D spectrum data;
-        by default, this is the "processed_elevation_energy_spectrum", but
-        one could also set "elevation_energy_spectrum" to plot also the bins
-        with low frequency noise.
-
-        `nseconds_gap`: float, number of seconds between 2 consecutive
-        spectra for one instrument above which we consider that there is a
-        data loss that should be filled with NaN. This is to avoid "stretching"
-        neighboring spectra over long times if an instrument gets offline.
+            - a valid filename string or path ending in .png or .pdf to save the figure to disk
+        `field`: string
+            the xr_trajan_in field to use as the 1D spectrum data;
+            by default, this is the "processed_elevation_energy_spectrum", but
+            one could also set "elevation_energy_spectrum" to plot also the bins
+            with low frequency noise.
+        `nseconds_gap`: float
+            Number of seconds between 2 consecutive
+            spectra for one instrument above which we consider that there is a
+            data loss that should be filled with NaN. This is to avoid "stretching"
+            neighboring spectra over long times if an instrument gets offline.
     """
 
     if tuple_date_start_end is not None:

trajan/traj.py

@@ -166,13 +166,10 @@ def transform(self, to_crs, x, y):
         Transform coordinates in this datasets coordinate system to `to_crs` coordinate system.
 
         Args:
-
             to_crs: `pyproj.CRS`.
-
             x, y: Coordinates in `self` CRS.
 
         Returns:
-
             xn, yn: Coordinates in `to_crs`.
         """
         t = pyproj.Transformer.from_crs(self.crs, to_crs, always_xy=True)
@@ -183,13 +180,10 @@ def itransform(self, from_crs, x, y):
         Transform coordinates in `from_crs` coordinate system to this datasets coordinate system.
 
         Args:
-
             from_crs: `pyproj.CRS`.
-
             x, y: Coordinates in `from_crs` CRS.
 
         Returns:
-
             xn, yn: Coordinates in this datasets CRS.
         """
         t = pyproj.Transformer.from_crs(from_crs, self.crs, always_xy=True)
@@ -269,12 +263,10 @@ def set_crs(self, crs):
     @abstractmethod
     def is_1d(self):
         """Returns True if dataset is 1D, i.e. time is a 1D coordinate variable."""
-        pass
 
     @abstractmethod
     def is_2d(self):
         """Returns True if dataset is 2D, i.e. time is a 2D variable and not a coordinate variable."""
-        pass
 
     def assign_cf_attrs(self,
                         creator_name=None,
@@ -495,15 +487,15 @@ def gridtime(self, times, timedim = None):
         """Interpolate dataset to a regular time interval or a different grid.
 
         Args:
+            `times`: array or str
+                Target time interval, can be either:
+                    - an array of times, or
+                    - a string "freq" specifying a Pandas daterange (e.g. 'h', '6h, 'D'...) suitable for `pd.date_range`.
 
-            `times`: Target time interval, can be either:
-                - an array of times, or
-                - a string "freq" specifying a Pandas daterange (e.g. 'h', '6h, 'D'...) suitable for `pd.date_range`.
-
-            `timedime`: Name of new time dimension. The default is to use the same name as previously.
+            `timedime`: str
+                Name of new time dimension. The default is to use the same name as previously.
 
         Returns:
-
             A new dataset interpolated to the target times. The dataset will be 1D (i.e. gridded) and the time dimension will be named `time`.
         """