raising ValueError when y_missing

explainerdashboard/explainers.py

@@ -1717,8 +1717,11 @@ def get_prop_for_label(self, prop:str, label):
     def y_binary(self):
         """for multiclass problems returns one-vs-rest array of [1,0] pos_label"""
         if not hasattr(self, '_y_binaries'):
-            self._y_binaries = [np.where(self.y.values==i, 1, 0)
-                        for i in range(self.y.nunique())]
+            if not self.y_missing:
+                self._y_binaries = [np.where(self.y.values==i, 1, 0)
+                            for i in range(self.y.nunique())]
+            else:
+                self._y_binaries = [self.y.values for i in range(len(self.labels))]
         return default_list(self._y_binaries, self.pos_label)
 
     @property
@@ -1945,6 +1948,9 @@ def metrics(self, cutoff=0.5, pos_label=None):
           dict
 
         """
+        if self.y_missing:
+            raise ValueError("No y was passed to explainer, so cannot calculate metrics!")
+
         if pos_label is None: pos_label = self.pos_label
         metrics_dict = {
             'accuracy' : accuracy_score(self.y_binary(pos_label), np.where(self.pred_probas(pos_label) > cutoff, 1, 0)),
@@ -2090,6 +2096,8 @@ def precision_df(self, bin_size=None, quantiles=None, multiclass=False,
           pd.DataFrame: precision_df
 
         """
+        if self.y_missing:
+            raise ValueError("No y was passed to explainer, so cannot calculate precision_df!")
         assert self.pred_probas is not None
 
         if pos_label is None: pos_label = self.pos_label
@@ -2223,6 +2231,8 @@ def plot_confusion_matrix(self, cutoff=0.5, normalized=False, binary=False, pos_
           plotly fig
 
         """
+        if self.y_missing:
+            raise ValueError("No y was passed to explainer, so cannot plot confusion matrix!")
         if pos_label is None: pos_label = self.pos_label
         pos_label_str = self.labels[pos_label]
 
@@ -2288,6 +2298,8 @@ def plot_roc_auc(self, cutoff=0.5, pos_label=None):
         Returns:
 
         """
+        if self.y_missing:
+            raise ValueError("No y was passed to explainer, so cannot plot roc auc!")
         return plotly_roc_auc_curve(self.y_binary(pos_label), self.pred_probas(pos_label), cutoff=cutoff)
 
     def plot_pr_auc(self, cutoff=0.5, pos_label=None):
@@ -2302,6 +2314,8 @@ def plot_pr_auc(self, cutoff=0.5, pos_label=None):
         Returns:
 
         """
+        if self.y_missing:
+            raise ValueError("No y was passed to explainer, so cannot plot PR AUC!")
         return plotly_pr_auc_curve(self.y_binary(pos_label), self.pred_probas(pos_label), cutoff=cutoff)
 
     def calculate_properties(self, include_interactions=True):