Refactor function to also show min and max values in boxplots

src/plotting/plotter.py

@@ -67,7 +67,11 @@ class Plotter:
         box_plot.xaxis.set_tick_params(rotation=45)
         box_plot.legend(loc='upper right', bbox_to_anchor=(1, 1))
 
-        self._add_median_labels(box_plot)
+        self._add_stat_labels(box_plot)
+        show_min_max = plot_specs.get("show_min_max", False)
+        if show_min_max:
+            self._add_stat_labels(box_plot, value_type="min")
+            self._add_stat_labels(box_plot, value_type="max")
 
     def _create_subplot_paths_group(self, plot_specs: Dict) -> List:
         subplot_path = [[f"{folder}{data}" for folder in plot_specs["folder"]] for data in
@@ -75,29 +79,41 @@ class Plotter:
 
         return subplot_path
 
-    def _add_median_labels(self, ax: plt.Axes, fmt: str = ".3f") -> None:
-        # https://stackoverflow.com/a/63295846
-        """Add text labels to the median lines of a seaborn boxplot.
+    def _add_stat_labels(self, ax: plt.Axes, fmt: str = ".3f", value_type: str = "median") -> None:
+        # Refactor from https://stackoverflow.com/a/63295846
+        """
+        Add text labels to the median, minimum, or maximum lines of a seaborn boxplot.
 
         Args:
-            ax: plt.Axes, e.g. the return value of sns.boxplot()
-            fmt: format string for the median value
+            ax: plt.Axes, e.g., the return value of sns.boxplot()
+            fmt: Format string for the value (e.g., min/max/median).
+            value_type: The type of value to label. Can be 'median', 'min', or 'max'.
         """
         lines = ax.get_lines()
-        boxes = [c for c in ax.get_children() if "Patch" in str(c)]
+        boxes = [c for c in ax.get_children() if "Patch" in str(c)]  # Get box patches
         start = 4
-        if not boxes:  # seaborn v0.13 => fill=False => no patches => +1 line
+        if not boxes:  # seaborn v0.13 or above (no patches => need to shift index)
             boxes = [c for c in ax.get_lines() if len(c.get_xdata()) == 5]
             start += 1
         lines_per_box = len(lines) // len(boxes)
-        for median in lines[start::lines_per_box]:
-            x, y = (data.mean() for data in median.get_data())
+
+        if value_type == "median":
+            line_idx = start
+        elif value_type == "min":
+            line_idx = start - 2  # min line comes 2 positions before the median
+        elif value_type == "max":
+            line_idx = start - 1  # max line comes 1 position before the median
+        else:
+            raise ValueError("Invalid value_type. Must be 'min', 'max', or 'median'.")
+
+        for value_line in lines[line_idx::lines_per_box]:
+            x, y = (data.mean() for data in value_line.get_data())
             # choose value depending on horizontal or vertical plot orientation
-            value = x if len(set(median.get_xdata())) == 1 else y
-            text = ax.text(x, y, f'{value/1000:{fmt}}', ha='center', va='center',
-                           fontweight='bold', color='white')
-            # create median-colored border around white text for contrast
+            value = x if len(set(value_line.get_xdata())) == 1 else y
+            text = ax.text(x, y, f'{value / 1000:{fmt}}', ha='center', va='center',
+                           fontweight='bold', color='white', size=10)
+            # create colored border around white text for contrast
             text.set_path_effects([
-                path_effects.Stroke(linewidth=3, foreground=median.get_color()),
+                path_effects.Stroke(linewidth=3, foreground=value_line.get_color()),
                 path_effects.Normal(),
             ])