Fix failing tests

Signed-off-by: Gaurav Gupta <gaugup@microsoft.com>

Author: gaugup

docs/source/notebooks/DiCE_multiclass_classification_and_regression.ipynb

@@ -162,7 +162,7 @@
    "outputs": [],
    "source": [
     "# Single input\n",
-    "query_instances_iris = x_train[2:3]\n",
+    "query_instances_iris = x_test[2:3]\n",
     "genetic_iris = exp_genetic_iris.generate_counterfactuals(query_instances_iris, total_CFs=7, desired_class=2)\n",
     "genetic_iris.visualize_as_dataframe()"
    ]
@@ -174,7 +174,7 @@
    "outputs": [],
    "source": [
     "# Multiple queries can be given as input at once\n",
-    "query_instances_iris = x_train[17:19]\n",
+    "query_instances_iris = x_test[17:19]\n",
     "genetic_iris = exp_genetic_iris.generate_counterfactuals(query_instances_iris, total_CFs=7, desired_class=2)\n",
     "genetic_iris.visualize_as_dataframe(show_only_changes=True)"
    ]
@@ -275,7 +275,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "exp_genetic_housing = Dice(d_housing, m_housing, method=\"random\")"
+    "exp_genetic_housing = Dice(d_housing, m_housing, method=\"genetic\")"
    ]
   },
   {
@@ -292,25 +292,12 @@
    "outputs": [],
    "source": [
     "# Multiple queries can be given as input at once\n",
-    "query_instances_housing = x_train[2:3]\n",
+    "query_instances_housing = x_test[2:4]\n",
     "genetic_housing = exp_genetic_housing.generate_counterfactuals(query_instances_housing,\n",
     "                                                               total_CFs=2,\n",
-    "                                                               features_to_vary=[\"AveRooms\"],\n",
     "                                                               desired_range=[3.0, 5.0])\n",
     "genetic_housing.visualize_as_dataframe(show_only_changes=True)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Multiple queries can be given as input at once\n",
-    "query_instances_housing = x_train[17:19]\n",
-    "genetic_housing = exp_genetic_housing.generate_counterfactuals(query_instances_housing, total_CFs=4, desired_range=[40, 50])\n",
-    "genetic_housing.visualize_as_dataframe(show_only_changes=True)"
-   ]
   }
  ],
  "metadata": {

tests/conftest.py

@@ -226,4 +226,4 @@ def create_housing_data():
         test_size=0.2, random_state=7)
     x_train = pd.DataFrame(data=x_train, columns=housing.feature_names)
     x_test = pd.DataFrame(data=x_test, columns=housing.feature_names)
-    return x_train, x_test, y_train, y_test, housing.feature_names.tolist()
+    return x_train, x_test, y_train, y_test, housing.feature_names

tests/test_dice_interface/test_explainer_base.py

@@ -398,7 +398,7 @@ def test_zero_totalcfs(self, desired_range, regression_exp_object, sample_custom
                     desired_range=desired_range)
 
     @pytest.mark.parametrize("desired_range, method",
-                             [([10, 100], 'random')])
+                             [([3, 5], 'random')])
     def test_numeric_categories(self, desired_range, method, create_housing_data):
         x_train, x_test, y_train, y_test, feature_names = \
             create_housing_data
@@ -409,7 +409,6 @@ def test_numeric_categories(self, desired_range, method, create_housing_data):
 
         dataset_train = x_train.copy()
         dataset_train['Outcome'] = y_train
-        feature_names.remove('CHAS')
 
         d = dice_ml.Data(dataframe=dataset_train, continuous_features=feature_names, outcome_name='Outcome')
         m = dice_ml.Model(model=model, backend='sklearn', model_type='regressor')