Merge pull request #236 from interpretml/gaugup/RaiseExceptionWhenNoCfsFound

Raise user exception when no counterfactuals are computed for any query point

Author: gaugup

dice_ml/explainer_interfaces/explainer_base.py

@@ -87,6 +87,7 @@ def generate_counterfactuals(self, query_instances, total_CFs,
                 query_instances_list.append(query_instances[ix:(ix+1)])
         elif isinstance(query_instances, Iterable):
             query_instances_list = query_instances
+
         for query_instance in tqdm(query_instances_list):
             self.data_interface.set_continuous_feature_indexes(query_instance)
             res = self._generate_counterfactuals(
@@ -101,6 +102,9 @@ def generate_counterfactuals(self, query_instances, total_CFs,
                 verbose=verbose,
                 **kwargs)
             cf_examples_arr.append(res)
+
+        self._check_any_counterfactuals_computed(cf_examples_arr=cf_examples_arr)
+
         return CounterfactualExplanations(cf_examples_list=cf_examples_arr)
 
     @abstractmethod
@@ -695,3 +699,15 @@ def round_to_precision(self):
             self.final_cfs_df[feature] = self.final_cfs_df[feature].astype(float).round(precisions[ix])
             if self.final_cfs_df_sparse is not None:
                 self.final_cfs_df_sparse[feature] = self.final_cfs_df_sparse[feature].astype(float).round(precisions[ix])
+
+    def _check_any_counterfactuals_computed(self, cf_examples_arr):
+        """Check if any counterfactuals were generated for any query point."""
+        no_cf_generated = True
+        # Check if any counterfactuals were generated for any query point
+        for cf_examples in cf_examples_arr:
+            if cf_examples.final_cfs_df is not None and len(cf_examples.final_cfs_df) > 0:
+                no_cf_generated = False
+                break
+        if no_cf_generated:
+            raise UserConfigValidationException(
+                "No counterfactuals found for any of the query points! Kindly check your configuration.")

docs/source/notebooks/DiCE_getting_started.ipynb

@@ -285,7 +285,7 @@
     "e2 = exp.generate_counterfactuals(x_test[0:1],\n",
     "                                  total_CFs=2,\n",
     "                                  desired_class=\"opposite\",\n",
-    "                                  features_to_vary=[\"age\", \"education\", \"race\"]\n",
+    "                                  features_to_vary=[\"education\", \"occupation\"]\n",
     "                                  )\n",
     "e2.visualize_as_dataframe(show_only_changes=True)"
    ]

tests/test_dice_interface/test_explainer_base.py

@@ -4,6 +4,7 @@
 
 import dice_ml
 from dice_ml.utils.exception import UserConfigValidationException
+from dice_ml.diverse_counterfactuals import CounterfactualExamples
 from dice_ml.explainer_interfaces.explainer_base import ExplainerBase
 
 
@@ -15,6 +16,37 @@ def _verify_feature_importance(self, feature_importance):
             for key in feature_importance:
                 assert feature_importance[key] >= 0.0 and feature_importance[key] <= 1.0
 
+    def test_check_any_counterfactuals_computed(
+        self, method,
+        custom_public_data_interface,
+        sklearn_binary_classification_model_interface
+    ):
+        exp = dice_ml.Dice(
+            custom_public_data_interface,
+            sklearn_binary_classification_model_interface,
+            method=method)
+
+        sample_custom_query = custom_public_data_interface.data_df[0:1]
+        cf_example = CounterfactualExamples(
+            data_interface=custom_public_data_interface,
+            test_instance_df=sample_custom_query)
+        cf_examples_arr = [cf_example]
+
+        with pytest.raises(
+                UserConfigValidationException,
+                match="No counterfactuals found for any of the query points! Kindly check your configuration."):
+            exp._check_any_counterfactuals_computed(cf_examples_arr=cf_examples_arr)
+
+        cf_example_has_cf = CounterfactualExamples(
+            data_interface=custom_public_data_interface,
+            final_cfs_df=sample_custom_query,
+            test_instance_df=sample_custom_query)
+        cf_example_no_cf = CounterfactualExamples(
+            data_interface=custom_public_data_interface,
+            test_instance_df=sample_custom_query)
+        cf_examples_arr = [cf_example_has_cf, cf_example_no_cf]
+        exp._check_any_counterfactuals_computed(cf_examples_arr=cf_examples_arr)
+
     @pytest.mark.parametrize("desired_class", [1])
     def test_zero_totalcfs(
         self, desired_class, method, sample_custom_query_1,