Add bar chart for feature importance per position to CPPPlot().feature_map

Author: breimanntools

aaanalysis/_utils/check_data.py

@@ -62,7 +62,7 @@ def check_array_like(name=None, val=None, dtype=None, ensure_2d=False, allow_nan
     check_type.check_str(name="dtype", val=dtype, accept_none=True)
     valid_dtypes = ["numeric", "int", "float", "bool", None]
     if dtype not in valid_dtypes:
-        str_error = add_str(str_error=f"'dtype' should be one of the following: {valid_dtypes}", str_add=str_add)
+        str_error = add_str(str_error=f"'dtype' should be one of: {valid_dtypes}", str_add=str_add)
         raise ValueError(str_error)
     dict_expected_dtype = {"numeric": "numeric", "int": "int64", "float": "float64", "bool": "bool"}
     expected_dtype = dict_expected_dtype[dtype] if dtype is not None else None

aaanalysis/_utils/check_type.py

@@ -77,7 +77,7 @@ def check_str_options(name=None, val=None, accept_none=False, list_str_options=N
     """Check if valid string option"""
     if accept_none and val is None:
         return None  # Skip test
-    str_add = add_str(str_error=f"'{name}' ({val}) should be one of following: {list_str_options}")
+    str_add = add_str(str_error=f"'{name}' ({val}) should be one of: {list_str_options}")
     check_str(name=name, val=val, accept_none=accept_none, str_add=str_add)
     if val not in list_str_options:
         raise ValueError(str_add)

aaanalysis/_utils/plotting.py

@@ -96,7 +96,7 @@ def _check_hatches(marker=None, hatch=None, list_cat=None):
         wrong_hatch = [x for x in hatch if x not in valid_hatches]
         if len(wrong_hatch) != 0:
             raise ValueError(
-                f"'hatch' contains wrong values ('{wrong_hatch}')! Should be one of following: {valid_hatches}")
+                f"'hatch' contains wrong values ('{wrong_hatch}')! Should be one of: {valid_hatches}")
         if len(hatch) != len(list_cat):
             raise ValueError(f"Length must match of 'hatch' ({hatch}) and categories ({list_cat}).")  # Check if hatch can be chosen
     # Warn for parameter conflicts
@@ -117,7 +117,7 @@ def _check_marker(marker=None, list_cat=None, lw=0):
     if isinstance(marker, list):
         wrong_markers = [x for x in marker if x not in valid_markers]
         if len(wrong_markers) != 0:
-            raise ValueError(f"'marker' contains wrong values  ('{wrong_markers}'). Should be one of following: {valid_markers}")
+            raise ValueError(f"'marker' contains wrong values  ('{wrong_markers}'). Should be one of: {valid_markers}")
         if len(marker) != len(list_cat):
             raise ValueError(f"Length must match of 'marker' ({marker}) and categories ({list_cat}).")
     # Warn for parameter conflicts
@@ -155,7 +155,7 @@ def _check_linestyle(linestyle=None, list_cat=None, marker=None):
         wrong_mls = [x for x in linestyle if x not in valid_mls]
         if len(wrong_mls) != 0:
             raise ValueError(
-                f"'marker_linestyle' contains wrong values ('{wrong_mls}')! Should be one of following: {valid_mls}")
+                f"'marker_linestyle' contains wrong values ('{wrong_mls}')! Should be one of: {valid_mls}")
         if len(linestyle) != len(list_cat):
             raise ValueError(f"Length must match of 'marker_linestyle' ({linestyle}) and categories ({list_cat}).")
     # Check if marker_linestyle is conflicting with other settings

aaanalysis/_utils/utils_plot_elements.py

@@ -3,9 +3,10 @@
 """
 import seaborn as sns
 import matplotlib.patches as mpatches
-import matplotlib.pyplot as plt
 import matplotlib.ticker as mticker
 import matplotlib as mpl
+import matplotlib.pyplot as plt
+import numpy as np
 
 
 # Helper functions
@@ -177,15 +178,53 @@ def adjust_spine_to_middle(ax=None):
     return ax
 
 
-def x_ticks_0(ax):
+def ticks_0(ax, show_zero=True, axis="x", precision=2):
     """Apply custom formatting for x-axis ticks."""
-    def custom_x_ticks(x, pos):
+    if axis not in ["x", "y"]:
+        raise ValueError("'axis' should be 'x' or 'y'")
+    def custom_ticks(x, pos):
         """Format x-axis ticks."""
-        if x % 1 == 0:  # Check if number is an integer
+        if x == 0 and not show_zero:
+            return ''
+        elif x % 1 == 0:  # Check if number is an integer
+            return f'{int(x)}'  # Format as integer
+        else:
+            # Format as float with two decimal places
+            return f'{x:.{precision}f}'
+    if axis == "x":
+        ax.xaxis.set_major_formatter(mticker.FuncFormatter(custom_ticks))
+    else:
+        ax.yaxis.set_major_formatter(mticker.FuncFormatter(custom_ticks))
+
+
+def ticks_0(ax, show_zero=True, show_only_max=False, axis="x", precision=2):
+    """Apply custom formatting for axis ticks and ensure max value is shown."""
+    if axis not in ["x", "y"]:
+        raise ValueError("'axis' should be 'x' or 'y'")
+    # Format tick labels
+    def custom_ticks(x, pos):
+        """Format axis ticks."""
+        if x == 0 and not show_zero:
+            return ''
+        elif x % 1 == 0:  # Check if number is an integer
             return f'{int(x)}'  # Format as integer
         else:
-            return f'{x:.2f}'  # Format as float with two decimal places
-    ax.xaxis.set_major_formatter(mticker.FuncFormatter(custom_x_ticks))
+            # Format as float with specified precision
+            return f'{x:.{precision}f}'
+
+    # Get the current axis object
+    axis_obj = ax.xaxis if axis == "x" else ax.yaxis
+    axis_obj.set_major_formatter(mticker.FuncFormatter(custom_ticks))
+
+    # Get the current limits
+    if show_only_max:
+        vmax = ax.get_xlim()[1] if axis == "x" else ax.get_ylim()[1]
+        max_val = int(np.ceil(vmax))
+        new_ticks = [max_val]
+        if axis == "x":
+            ax.set_xticks(new_ticks)
+        else:
+            ax.set_yticks(new_ticks)
 
 
 def adjust_tuple_elements(tuple_in=None, tuple_default=None):

aaanalysis/data_handling/_load_features.py

@@ -12,7 +12,7 @@
 def check_name(name=None):
     """Check provided names of dataset"""
     if name not in LIST_DATASETS_WITH_FEATURES:
-        raise ValueError(f"'name' should be one of the following: {LIST_DATASETS_WITH_FEATURES}")
+        raise ValueError(f"'name' should be one of: {LIST_DATASETS_WITH_FEATURES}")
 
 
 # II Main Functions

aaanalysis/feature_engineering/_aaclust_plot.py

@@ -68,7 +68,7 @@ def check_method(method=None):
     """Validate the method parameter against a list of valid hierarchical clustering methods"""
     valid_methods = ["single", "complete", "average", "weighted", "centroid", "median", "ward"]
     if method not in valid_methods:
-        raise ValueError(f"'method' ({method}) should be one of following: {valid_methods}")
+        raise ValueError(f"'method' ({method}) should be one of: {valid_methods}")
 
 
 def check_match_df_corr_clust_x(df_corr=None, cluster_x=None):

aaanalysis/feature_engineering/_backend/aaclust/aaclust_plot.py

@@ -71,7 +71,7 @@ def plot_eval(df_eval=None, dict_xlims=None, figsize=None, colors=None):
             ax.set_title("Quality measures", weight="bold")
         ax.tick_params(axis='y', which='both', left=False)
         if i != 0:
-            ut.x_ticks_0(ax=ax)
+            ut.ticks_0(ax=ax)
     # Set xlims
     if dict_xlims is not None:
         for i in dict_xlims: