Merge pull request #497 from MAIF/hotfix/interactions_values

fix interaction_values values and list_ind

shapash/explainer/smart_plotter.py

@@ -1896,12 +1896,12 @@ def _select_indices_interactions_plot(self, selection, max_points):
                 list_ind = random.sample(self.explainer.x_init.index.tolist(), max_points)
                 addnote = "Length of random Subset : "
         elif isinstance(selection, list):
-            if hasattr(self, 'interaction_selection'):
-                if set(self.interaction_selection).issubset(set(selection)):
-                    list_ind = self.interaction_selection
-            elif len(selection) <= max_points:
+            if len(selection) <= max_points:
                 list_ind = selection
                 addnote = "Length of user-defined Subset : "
+            elif hasattr(self, 'interaction_selection'):
+                if set(selection).issubset(set(self.interaction_selection)):
+                    list_ind = self.interaction_selection
             else:
                 list_ind = random.sample(selection, max_points)
                 addnote = "Length of random Subset : "
@@ -1985,6 +1985,8 @@ def interactions_plot(self,
             feature_values2 = self.explainer.x_init.loc[list_ind, col_name2].to_frame()
 
         interaction_values = self.explainer.get_interaction_values(selection=list_ind)[:, col_id1, col_id2]
+        if col_id1 != col_id2:
+            interaction_values = interaction_values * 2
 
         # selecting the best plot : Scatter, Violin?
         if col_value_count1 > violin_maxf:

tests/unit_tests/explainer/test_smart_plotter.py

@@ -1798,7 +1798,7 @@ def test_interactions_plot_1(self):
                                      color=self.x_init[col1])
 
         assert np.array_equal(output.data[0].x, expected_output.data[0].x)
-        assert np.array_equal(output.data[1].y, expected_output.data[1].y)
+        assert np.array_equal(output.data[1].y, expected_output.data[1].y * 2)
         assert output.data[0].showlegend is True
         assert len(output.data) == 2
 
@@ -1819,8 +1819,8 @@ def test_interactions_plot_2(self):
         smart_explainer.x_encoded['X2'] = smart_explainer.x_encoded['X2'].astype(float)
 
         interaction_values = np.array([
-            [[0.1, -0.7], [-0.6, 0.3]],
-            [[0.2, -0.1], [-0.2, 0.1]]
+            [[0.1, -0.7], [-0.7, 0.3]],
+            [[0.2, -0.1], [-0.1, 0.1]]
         ])
 
         smart_explainer.interaction_values = interaction_values
@@ -1829,7 +1829,7 @@ def test_interactions_plot_2(self):
         output = smart_explainer.plot.interactions_plot(col1, col2, violin_maxf=0)
 
         assert np.array_equal(output.data[0].x, ['PhD', 'Master'])
-        assert np.array_equal(output.data[0].y, [-0.7, -0.1])
+        assert np.array_equal(output.data[0].y, [-1.4, -0.2])
         assert np.array_equal(output.data[0].marker.color, [34., 27.])
         assert len(output.data) == 1
 
@@ -1852,8 +1852,8 @@ def test_interactions_plot_3(self):
         smart_explainer.x_encoded['X2'] = smart_explainer.x_encoded['X2'].astype(float)
 
         interaction_values = np.array([
-            [[0.1, -0.7], [-0.6, 0.3]],
-            [[0.2, -0.1], [-0.2, 0.1]]
+            [[0.1, -0.7], [-0.7, 0.3]],
+            [[0.2, -0.1], [-0.1, 0.1]]
         ])
 
         smart_explainer.interaction_values = interaction_values
@@ -1862,7 +1862,7 @@ def test_interactions_plot_3(self):
         output = smart_explainer.plot.interactions_plot(col2, col1, violin_maxf=0)
 
         assert np.array_equal(output.data[0].x, [34.])
-        assert np.array_equal(output.data[0].y, [-0.6])
+        assert np.array_equal(output.data[0].y, [-1.4])
         assert output.data[0].name == 'PhD'
 
         assert np.array_equal(output.data[1].x, [27.])
@@ -1892,8 +1892,8 @@ def test_interactions_plot_4(self):
         smart_explainer.x_encoded['X2'] = smart_explainer.x_encoded['X2'].astype(float)
 
         interaction_values = np.array([
-            [[0.1, -0.7], [-0.6, 0.3]],
-            [[0.2, -0.1], [-0.2, 0.1]]
+            [[0.1, -0.7], [-0.7, 0.3]],
+            [[0.2, -0.1], [-0.1, 0.1]]
         ])
 
         smart_explainer.interaction_values = interaction_values
@@ -1902,7 +1902,7 @@ def test_interactions_plot_4(self):
         output = smart_explainer.plot.interactions_plot(col1, col2, violin_maxf=0)
 
         assert np.array_equal(output.data[0].x, [520, 12800])
-        assert np.array_equal(output.data[0].y, [-0.7, -0.1])
+        assert np.array_equal(output.data[0].y, [-1.4, -0.2])
         assert np.array_equal(output.data[0].marker.color, [34., 27.])
 
         assert len(output.data) == 1
@@ -1926,8 +1926,8 @@ def test_interactions_plot_5(self):
         smart_explainer.x_encoded['X2'] = smart_explainer.x_encoded['X2'].astype(float)
 
         interaction_values = np.array([
-            [[0.1, -0.7], [-0.6, 0.3]],
-            [[0.2, -0.1], [-0.2, 0.1]]
+            [[0.1, -0.7], [-0.7, 0.3]],
+            [[0.2, -0.1], [-0.1, 0.1]]
         ])
 
         smart_explainer.interaction_values = interaction_values
@@ -1942,7 +1942,7 @@ def test_interactions_plot_5(self):
         assert output.data[2].type == 'scatter'
 
         assert np.array_equal(output.data[2].x, ['PhD', 'Master'])
-        assert np.array_equal(output.data[2].y, [-0.7, -0.1])
+        assert np.array_equal(output.data[2].y, [-1.4, -0.2])
         assert np.array_equal(output.data[2].marker.color, [34., 27.])
 
         self.setUp()