add test for old explanation dashboard and interpret dashboard

python/interpret_community/explanation/explanation.py

@@ -522,6 +522,9 @@ def _perf_dict(self, y, y_hat, i):
             di["residual"] = int(y[i] == y_hat[i])
         else:
             di["residual"] = y[i] - y_hat[i]
+        # TODO: for classification case these should be the probabilities
+        di["actual_score"] = y[i]
+        di["predicted_score"] = y_hat[i]
         return di
 
     def _convert_local_importances_to_dense_list(self):
@@ -619,9 +622,8 @@ def selector(self):
         :return: The selector as a pandas dataframe of records.
         :rtype: pandas.DataFrame
         """
-        predicted = self._eval_y_predicted
-        dataset_shape = np.empty((self.num_examples, 1))
-        return gen_local_selector(dataset_shape, None, predicted.flatten())
+        data = self.data(key=-1)[InterpretData.SPECIFIC]
+        return gen_local_selector(data)
 
     @classmethod
     def _does_quack(cls, explanation):

python/interpret_community/widget/explanation_dashboard.py

@@ -2,7 +2,7 @@
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # ---------------------------------------------------------
 
-"""Defines the Explanation dashboard class."""
+"""Defines the DEPRECATED Explanation dashboard class."""
 
 import warnings
 
@@ -52,8 +52,5 @@ def __init__(self, explanation, model=None, *, dataset=None,
                  true_y=None, classes=None, features=None, port=None,
                  datasetX=None, trueY=None, locale=None, public_ip=None,
                  with_credentials=False, use_cdn=None):
-        if use_cdn is not None:
-            warnings.warn("""use_cdn parameter is deprecated, cdn has been deleted.
-                          Constructor parameter will be removed in the future""")
-        warnings.warn("""ExplanationDashboard in interpret-community package is deprecated and removed.
-                      Please use the ExplanationDashboard from raiwidgets package instead.""")
+        warnings.warn("ExplanationDashboard in interpret-community package is deprecated and removed."
+                      "Please use the ExplanationDashboard from raiwidgets package instead.")

requirements-vis.txt

@@ -3,3 +3,6 @@ prompt-toolkit>=2.0.0
 greenlet==0.4.17
 gevent==20.9.0
 raiwidgets
+# used by interpret show method
+dash
+dash-cytoscape

test/test_explanation_dashboard.py

@@ -12,6 +12,8 @@
 from interpret_community.mimic.models.lightgbm_model import LGBMExplainableModel
 from interpret_community.common.constants import ModelTask
 from raiwidgets import ExplanationDashboard
+from interpret import show
+from interpret_community.widget import ExplanationDashboard as OldExplanationDashboard
 from common_utils import (create_lightgbm_classifier, create_sklearn_svm_classifier,
                           create_cancer_data, create_cancer_data_booleans)
 
@@ -79,3 +81,26 @@ def test_boolean_labels(self, mimic_explainer):
                                     features=feature_names, classes=target_names)
         explanation = explainer.explain_local(x_test)
         ExplanationDashboard(explanation, model, dataset=x_test, true_y=y_test)
+
+    def test_old_explanation_dashboard(self, mimic_explainer):
+        # Validate old explanation dashboard namespace works but only prints a warning
+        x_train, x_test, y_train, y_test, feature_names, target_names = create_cancer_data()
+        # Fit an SVM model
+        model = create_sklearn_svm_classifier(x_train, y_train)
+        explainer = mimic_explainer(model, x_train, LGBMExplainableModel,
+                                    features=feature_names, classes=target_names)
+        explanation = explainer.explain_local(x_test)
+        err = ("ExplanationDashboard in interpret-community package is deprecated and removed."
+               "Please use the ExplanationDashboard from raiwidgets package instead.")
+        with pytest.warns(UserWarning, match=err):
+            OldExplanationDashboard(explanation, model, dataset=x_test, true_y=y_test)
+
+    def test_interpret_dashboard(self, mimic_explainer):
+        # Validate our explanation works with the interpret dashboard
+        x_train, x_test, y_train, y_test, feature_names, target_names = create_cancer_data()
+        # Fit an SVM model
+        model = create_sklearn_svm_classifier(x_train, y_train)
+        explainer = mimic_explainer(model, x_train, LGBMExplainableModel,
+                                    features=feature_names, classes=target_names)
+        explanation = explainer.explain_global(x_test)
+        show(explanation)