a3fd728f8cbf7c4f278681c36f7f668def787376,tests/test_bow.py,,test_codoc_frequencies,#Any#Any#Any#,90

Before Change

    df = bow.bow_stats.codoc_frequencies(dtm, proportions=proportions)
    assert isinstance(df, dict)
    assert len(df) == math.factorial(n_vocab) / math.factorial(2) / math.factorial(n_vocab - 2)
    for w1, w2 in itertools.combinations(range(n_vocab), 2):
        n = df[(w1, w2)]
        if proportions:
            assert 0 <= n <= 1
        else:
            assert 0 <= n <= n_docs


def test_codoc_frequencies2():
    dtm = np.array([
        [0, 2, 3, 0, 0],
        [1, 2, 0, 5, 0],

After Change

    cooc = bow.bow_stats.codoc_frequencies(dtm, proportions=proportions)

    if matrix_type == 1:
        assert issparse(cooc)
    else:
        assert isinstance(cooc, np.ndarray)

    assert cooc.shape == (n_vocab, n_vocab)

    if matrix_type == 1:
        cooc = cooc.todense()

Instances