| | import copy |
| | import pytest |
| |
|
| |
|
| | @pytest.mark.parametrize('model', [('kmeans_pca_topic_model'), |
| | ('base_topic_model'), |
| | ('custom_topic_model'), |
| | ('merged_topic_model'), |
| | ('reduced_topic_model'), |
| | ('online_topic_model')]) |
| | def test_topics(model, request): |
| | topic_model = copy.deepcopy(request.getfixturevalue(model)) |
| | fig = topic_model.visualize_topics() |
| | for slider in fig.to_dict()["layout"]["sliders"]: |
| | for step in slider["steps"]: |
| | assert int(step["label"].split(" ")[-1]) != -1 |
| |
|
| | fig = topic_model.visualize_topics(top_n_topics=5) |
| | for slider in fig.to_dict()["layout"]["sliders"]: |
| | for step in slider["steps"]: |
| | assert int(step["label"].split(" ")[-1]) != -1 |
| |
|
| | @pytest.mark.parametrize('model', [('kmeans_pca_topic_model'), |
| | ('base_topic_model'), |
| | ('custom_topic_model'), |
| | ('merged_topic_model'), |
| | ('reduced_topic_model'), |
| | ('online_topic_model')]) |
| | def test_topics_outlier(model, request): |
| | topic_model = copy.deepcopy(request.getfixturevalue(model)) |
| | topic_model.topic_sizes_[-1] = 4 |
| | fig = topic_model.visualize_topics() |
| |
|
| | for slider in fig.to_dict()["layout"]["sliders"]: |
| | for step in slider["steps"]: |
| | assert int(step["label"].split(" ")[-1]) != -1 |
| |
|
| | fig = topic_model.visualize_topics(top_n_topics=5) |
| | for slider in fig.to_dict()["layout"]["sliders"]: |
| | for step in slider["steps"]: |
| | assert int(step["label"].split(" ")[-1]) != -1 |
| |
|