Merge pull request #202 from seanzhangkx8/dependency-package-update

Dependency Packages Upgrade
CornellNLP · Nov 1, 2023 · c5b2bd7 · c5b2bd7
2 parents c63c970 + c219fc0
commit c5b2bd7
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Showing 3 changed files with 8 additions and 8 deletions.
diff --git a/convokit/bag_of_words/bow_transformer.py b/convokit/bag_of_words/bow_transformer.py
@@ -105,7 +105,7 @@ def transform(
 
         matrix = self.vectorizer.transform(docs)
         try:
-            column_names = self.vectorizer.get_feature_names()
+            column_names = self.vectorizer.get_feature_names_out()
         except AttributeError:
             column_names = np.arange(matrix.shape[1])
         corpus.set_vector_matrix(self.vector_name, matrix=matrix, ids=ids, columns=column_names)
@@ -134,4 +134,4 @@ def get_vocabulary(self):
         """
         Get the vocabulary of the vectorizer object
         """
-        return self.vectorizer.get_feature_names()
+        return self.vectorizer.get_feature_names_out()
diff --git a/convokit/expected_context_framework/col_normed_tfidf.py b/convokit/expected_context_framework/col_normed_tfidf.py
@@ -62,7 +62,7 @@ def transform(self, corpus, selector=lambda x: True):
             docs.append(self.text_func(ut))
             ut.add_vector(self.output_field)
         vects = self.tfidf_obj.transform(docs)
-        column_names = self.tfidf_obj.get_feature_names()
+        column_names = self.tfidf_obj.get_feature_names_out()
         corpus.set_vector_matrix(self.output_field, matrix=vects, ids=ids, columns=column_names)
         n_feats = np.array((vects > 0).sum(axis=1)).flatten()
         for id, n in zip(ids, n_feats):
@@ -93,7 +93,7 @@ def get_vocabulary(self):
         """
         :return: array of feature names
         """
-        return self.tfidf_obj.get_feature_names()
+        return self.tfidf_obj.get_feature_names_out()
 
     def load(self, dirname):
         """
@@ -140,8 +140,8 @@ def fit_transform(self, X, y=None):
         self.fit(X, y)
         return self.transform(X)
 
-    def get_feature_names(self):
-        return self.tfidf_model.get_feature_names()
+    def get_feature_names_out(self):
+        return self.tfidf_model.get_feature_names_out()
 
     def get_params(self, deep=True):
         return self.tfidf_model.get_params(deep=deep)

diff --git a/convokit/prompt_types/promptTypes.py b/convokit/prompt_types/promptTypes.py
@@ -709,12 +709,12 @@ def fit_prompt_type_model(model, n_types, random_state=None, max_dist=0.9, verbo
     reference_clusters[reference_dists.min(axis=1) >= max_dist] = -1
 
     prompt_df = pd.DataFrame(
-        index=model["prompt_tfidf_model"].get_feature_names(),
+        index=model["prompt_tfidf_model"].get_feature_names_out(),
         data=np.hstack([prompt_dists, prompt_clusters[:, np.newaxis]]),
         columns=list(range(n_types)) + ["type_id"],
     )
     reference_df = pd.DataFrame(
-        index=model["reference_tfidf_model"].get_feature_names(),
+        index=model["reference_tfidf_model"].get_feature_names_out(),
         data=np.hstack([reference_dists, reference_clusters[:, np.newaxis]]),
         columns=list(range(n_types)) + ["type_id"],
     )