Update CPPPlot().feature_map

Author: breimanntools

aaanalysis/feature_engineering/_backend/cpp/cpp_plot_feature_map.py

@@ -160,7 +160,6 @@ def add_feat_importance_legend(ax=None,
 
 
 # II Main Functions
-# TODO in frontend: test (add_imp_bar_top, imp_bar_label_type)
 # TODO stacked bar charts for SHAP (later)
 def plot_feature_map(df_feat=None, df_cat=None,
                      col_cat="subcategory", col_val="mean_dif", col_imp="feat_importance",
@@ -313,7 +312,7 @@ def plot_feature_map(df_feat=None, df_cat=None,
                                fontsize_annotations=fs_annotations)
     if add_imp_bar_top:
         ax_empty.axis("off")
-    plt.sca(ax_hm)
     plt.subplots_adjust(wspace=0.0, hspace=0.0)
-    ax = [ax_hm, ax_br, ax_bt] if add_imp_bar_top else [ax_hm, ax_br]
+    plt.sca(ax_hm)
+    ax = ax_hm
     return fig, ax

tests/unit/cpp_plot_tests/test_cpp_plot_feature_map.py

@@ -318,8 +318,15 @@ def test_valid_imp_marker_sizes(self):
                                        imp_marker_sizes=valid_imp_marker_sizes)
         assert isinstance(fig, plt.Figure) and isinstance(ax, plt.Axes)
         plt.close()
-    
-    
+
+    def test_valid_add_imp_bar_top(self):
+        cpp_plot = aa.CPPPlot()
+        df_feat = get_df_feat()
+        for add_imp_bar_top in [True, False]:
+            fig, ax = cpp_plot.feature_map(df_feat=df_feat, add_imp_bar_top=add_imp_bar_top)
+            assert isinstance(fig, plt.Figure) and isinstance(ax, plt.Axes)
+            plt.close()
+
     def test_valid_imp_bar_th(self):
         cpp_plot = aa.CPPPlot()
         df_feat = get_df_feat()
@@ -328,6 +335,14 @@ def test_valid_imp_bar_th(self):
         assert isinstance(fig, plt.Figure) and isinstance(ax, plt.Axes)
         plt.close()
 
+    def test_valid_imp_bar_label_type(self):
+        cpp_plot = aa.CPPPlot()
+        df_feat = get_df_feat()
+        for imp_bar_label_type in ["short", "long", None]:
+            fig, ax = cpp_plot.feature_map(df_feat=df_feat, imp_bar_label_type=imp_bar_label_type)
+            assert isinstance(fig, plt.Figure) and isinstance(ax, plt.Axes)
+            plt.close()
+
     @settings(max_examples=3, deadline=5000)
     @given(xtick_size=st.floats(min_value=8.0, max_value=14.0), xtick_width=st.floats(min_value=0.5, max_value=2.0),
            xtick_length=st.floats(min_value=3.0, max_value=10.0))
@@ -656,6 +671,14 @@ def test_invalid_imp_marker_sizes(self):
             cpp_plot.feature_map(df_feat=df_feat, imp_marker_sizes=invalid_imp_marker_sizes)
         plt.close()
 
+    def test_invalid_add_imp_bar_top(self):
+        cpp_plot = aa.CPPPlot()
+        df_feat = get_df_feat()
+        for add_imp_bar_top in [None, "adsf", 123, pd.DataFrame, {}]:
+            with pytest.raises(ValueError):
+                cpp_plot.feature_map(df_feat=df_feat, add_imp_bar_top=add_imp_bar_top)
+            plt.close()
+
     def test_invalid_imp_bar_th(self):
         cpp_plot = aa.CPPPlot()
         df_feat = get_df_feat()
@@ -664,6 +687,14 @@ def test_invalid_imp_bar_th(self):
             cpp_plot.feature_map(df_feat=df_feat, imp_bar_th=invalid_imp_bar_th)
         plt.close()
 
+    def test_invalid_imp_bar_label_type(self):
+        cpp_plot = aa.CPPPlot()
+        df_feat = get_df_feat()
+        for imp_bar_label_type in ["adsf", 123, pd.DataFrame, {}]:
+            with pytest.raises(ValueError):
+                cpp_plot.feature_map(df_feat=df_feat, imp_bar_label_type=imp_bar_label_type)
+            plt.close()
+
     @settings(max_examples=3, deadline=5000)
     @given(xtick_size=st.just(-1), xtick_width=st.just(-1), xtick_length=st.just(-1))
     def test_invalid_tick_styling(self, xtick_size, xtick_width, xtick_length):
@@ -734,4 +765,4 @@ def test_complex_negative_positive(self):
                                  xtick_width=-1,  # Invalid xtick_width
                                  xtick_length=-1,  # Invalid xtick_length
                                  **args_seq)
-        plt.close()
+        plt.close()

tests/unit/cpp_plot_tests/test_cpp_plot_heatmap.py

@@ -43,7 +43,6 @@ def adjust_vmin_vmax(vmin=None, vmax=None):
     return vmin, vmax
 
 
-
 def get_args_seq(n=0):
     aa.options["verbose"] = False
     df_seq = aa.load_dataset(name="DOM_GSEC", n=N_SEQ)