예제 #1
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class LDATests(unittest.TestCase, BaseTests):
    def setUp(self):
        self.corpus = Corpus.from_file('deerwester')
        self.model = LdaWrapper(num_topics=5)

    def test_too_large_id(self):
        self.model.fit(self.corpus)
        with self.assertRaises(ValueError):
            self.model.get_topics_table_by_id(6)

    def test_fit_transform(self):
        corpus = super().test_fit_transform()
        self.assertEqual(len(corpus.domain.attributes), 5)
        self.assertEqual(corpus.X.shape, (len(self.corpus), 5))
예제 #2
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class LDATests(unittest.TestCase, BaseTests):
    def setUp(self):
        self.corpus = Corpus.from_file('deerwester')
        self.model = LdaWrapper(num_topics=5)

    def test_too_large_id(self):
        self.model.fit(self.corpus)
        with self.assertRaises(ValueError):
            self.model.get_topics_table_by_id(6)

    def test_fit_transform(self):
        corpus = super().test_fit_transform()
        self.assertEqual(len(corpus.domain.attributes), 5)
        self.assertEqual(corpus.X.shape, (len(self.corpus), 5))
예제 #3
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 def setUp(self):
     self.corpus = Corpus.from_file('deerwester')
     self.model = LdaWrapper(num_topics=5)
예제 #4
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 def setUp(self):
     self.corpus = Corpus.from_file('deerwester')
     self.model = LdaWrapper(num_topics=5)
예제 #5
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        self.on_params_change()

    def set_visual_settings(self, key: KeyType, value: ValueType):
        self.graph.parameter_setter.set_parameter(key, value)
        self.visual_settings[key] = value

    def clear(self):
        self.Error.clear()
        self.graph.clear_all()
        self.data = None
        self.topic_list = []
        self.term_topic_matrix = None
        self.term_frequency = None
        self.num_tokens = None

    def send_report(self):
        self.report_items((
            ("Relevance", self.relevance),
            ("Shown topic", self.topic_list[self.selected_topic]),
        ))
        self.report_plot()


if __name__ == "__main__":
    corpus = Corpus.from_file("deerwester")
    lda = LdaWrapper(num_topics=5)
    lda.fit_transform(corpus)
    topics = lda.get_all_topics_table()

    WidgetPreview(OWLDAvis).run(topics)