Add BERTopic.

LLMTopicDetection_BERTopic/tests/test_vectorizers/test_online_cv.py

@@ -0,0 +1,38 @@
+import copy
+import pytest
+from bertopic.vectorizers import OnlineCountVectorizer
+
+
+@pytest.mark.parametrize(
+    "model",
+    [
+        ("kmeans_pca_topic_model"),
+        ("custom_topic_model"),
+        ("merged_topic_model"),
+        ("reduced_topic_model"),
+        ("online_topic_model"),
+    ],
+)
+def test_online_cv(model, documents, request):
+    topic_model = copy.deepcopy(request.getfixturevalue(model))
+    vectorizer_model = OnlineCountVectorizer(stop_words="english", ngram_range=(2, 2))
+
+    topics = [topic_model.get_topic(topic) for topic in set(topic_model.topics_)]
+    topic_model.update_topics(documents, vectorizer_model=vectorizer_model)
+    new_topics = [topic_model.get_topic(topic) for topic in set(topic_model.topics_)]
+
+    for old_topic, new_topic in zip(topics, new_topics):
+        if old_topic[0][0] != "":
+            assert old_topic != new_topic
+
+
+@pytest.mark.parametrize("model", [("online_topic_model")])
+def test_clean_bow(model, request):
+    topic_model = copy.deepcopy(request.getfixturevalue(model))
+
+    original_shape = topic_model.vectorizer_model.X_.shape
+    topic_model.vectorizer_model.delete_min_df = 2
+    topic_model.vectorizer_model._clean_bow()
+
+    assert original_shape[0] == topic_model.vectorizer_model.X_.shape[0]
+    assert original_shape[1] > topic_model.vectorizer_model.X_.shape[1]