merge significance bar plot methods

mlair/plotting/postprocessing_plotting.py

@@ -1155,14 +1155,14 @@ class PlotSampleUncertaintyFromBootstrap(AbstractPlotClass):  # pragma: no cover
                     width=width, orient=orientation)
         if orientation == "v":
             if apply_u_test:
-                ax = self.set_sigificance_bars_vertical(asteriks, ax, data_table)
+                ax = self.set_significance_bars(asteriks, ax, data_table, orientation)
             ylims = list(ax.get_ylim())
             ax.set_ylim([ylims[0], ylims[1]*1.025])
             ax.set_ylabel(f"{self.error_measure} (in {self.error_unit})")
             ax.set_xticklabels(ax.get_xticklabels(), rotation=45)
         elif orientation == "h":
             if apply_u_test:
-                ax = self.set_sigificance_bars_horizontal(asteriks, ax, data_table)
+                ax = self.set_significance_bars(asteriks, ax, data_table, orientation)
             ax.set_xlabel(f"{self.error_measure} (in {self.error_unit})")
             xlims = list(ax.get_xlim())
             ax.set_xlim([xlims[0], xlims[1] * 1.015])
@@ -1180,35 +1180,25 @@ class PlotSampleUncertaintyFromBootstrap(AbstractPlotClass):  # pragma: no cover
         self._save()
         plt.close("all")
 
-    def set_sigificance_bars_vertical(self, asteriks, ax, data_table):
-        x1 = list(asteriks.index).index(self.model_name)
-        y_prev = 0.
-        for i, v in enumerate(asteriks):
+    def set_significance_bars(self, asteriks, ax, data_table, orientation):
+        p1 = list(asteriks.index).index(self.model_name)
+        q_prev = 0.
+        factor = 0.025
+        for i, ast in enumerate(asteriks):
             if not i == list(asteriks.index).index(self.model_name):
-                x2 = i
-                y = data_table[[self.model_name, data_table.columns[i]]].max().max()
-                y = max(y, y_prev) * 1.025
-                if abs(y-y_prev) < y * 0.025:
-                    y = y * 1.025
-                h = .01 * data_table.max().max()
-                ax.plot([x1, x1, x2, x2], [y, y + h, y + h, y], c="k")
-                ax.text((x1 + x2) * .5, y + h, v, ha="center", va="bottom", color="k")
-                y_prev = y
-        return ax
-
-    def set_sigificance_bars_horizontal(self, asteriks, ax, data_table):
-        y1 = list(asteriks.index).index(self.model_name)
-        x_prev = 0.
-        for i, v in enumerate(asteriks):
-            if not i == list(asteriks.index).index(self.model_name):
-                y2 = i
-                x = data_table[[self.model_name, data_table.columns[i]]].max().max()
-                x = max(x, x_prev) * 1.025
-                if abs(x-x_prev) < x * 0.025:
-                    x = x * 1.025
-                h = .01 * data_table.max().max()
-                ax.plot([x, x+h, x+h, x], [y1, y1, y2, y2], c="k")
-                ax.text(x + h, (y1 + y2) * .5, v, ha="left", va="center", color="k", rotation=-90)
+                p2 = i
+                q = data_table[[self.model_name, data_table.columns[i]]].max().max()
+                q = max(q, q_prev) * (1 + factor)
+                if abs(q - q_prev) < q * factor:
+                    q = q * (1 + factor)
+                h = 0.01 * data_table.max().max()
+                if orientation == "h":
+                    ax.plot([q, q + h, q + h, q], [p1, p1, p2, p2], c="k")
+                    ax.text(q + h, (p1 + p2) * 0.5, ast, ha="left", va="center", color="k", rotation=-90)
+                elif orientation == "v":
+                    ax.plot([p1, p1, p2, p2], [q, q + h, q + h, q], c="k")
+                    ax.text((p1 + p2) * 0.5, q + h, ast, ha="center", va="bottom", color="k")
+                q_prev = q
         return ax