Fixed save path of the track origin plot, and some minor changes to c…

…omments

puma/hlplots/aux_results.py

@@ -419,7 +419,7 @@ def plot_track_origin_confmat(
             to allow better readability on darker cmap colors. If 1, all text is black;
             if 0, all text is white. by default 0.6
         colormap : plt.cm, optional
-            Colormap of the plot, by default plt.cm.Oranges
+            Colormap of the plot, by default `plt.cm.Oranges`
         atlas_offset : float, optional
             Space at the top of the plot reserved to the Atlasify text. by default 1.5
         """
@@ -455,4 +455,4 @@ def plot_track_origin_confmat(
                 atlas_second_tag=self.atlas_second_tag,
             )
 
-            plot_cm.savefig(tagger.name + "_trackorigin_cm.png")
+            plot_cm.savefig(self.get_filename(tagger.name + "_trackorigin_cm.png"))

puma/matshow.py

@@ -39,14 +39,14 @@ def __init__(
         show_entries : bool, optional
             If True, show matrix entries as numbers in the plot. by default True
         show_percentage : bool, optional
-            If True, if matrix entries are percentages (numbers in [0,1]), show them as such.
-            by default False
+            If True, if matrix entries are percentages (numbers in [0,1]), format them as
+            percentages. by default False
         text_color_threshold : float, optional
             percentage of the range of matrix's values after which the text color switches to white,
             to allow better readability on darker cmap colors. If 1, all text is black;
             if 0, all text is white. by default 0.6
         colormap : plt.cm, optional
-            Colormap for the plot, by default plt.cm.Oranges
+            Colormap for the plot, by default `plt.cm.Oranges`
         cbar_label : str | None, optional
             Label of the colorbar, by default None
         atlas_offset : float, optional

puma/utils/confusion_matrix.py

@@ -31,7 +31,7 @@ def confusion_matrix(
     -------
     np.ndarray : the confusion matrix.
 
-    Example:
+    Example
     --------
     >>> targets = np.array([2, 0, 2, 2, 0, 1])
     >>> predictions = np.array([0, 0, 2, 2, 0, 2])