示例#1
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def test_pvalues_type():
    poisson = np.random.poisson(2, size=100)
    normal = np.random.normal(loc=10, scale=2, size=50)
    cor = get_pvalues([poisson, normal])
    assert (type(cor) == np.ndarray)
示例#2
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def test_pvalues_similarity():
    # test p values for close distributions
    poisson = np.random.poisson(2, size=100)
    normal = np.random.normal(loc=10, scale=2, size=50)
    cor = get_pvalues([poisson, normal])
    assert (cor[0, 0] > 0.95 and cor[1, 1] > 0.95)
示例#3
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def test_pvalues_difference():
    # test p values for very different distributions
    poisson = np.random.poisson(2, size=100)
    normal = np.random.normal(loc=10, scale=2, size=50)
    cor = get_pvalues([poisson, normal])
    assert (cor[0, 1] < 0.05)
示例#4
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def test_pvalues_size():
    poisson = np.random.poisson(2, size=100)
    normal = np.random.normal(loc=10, scale=2, size=50)
    cor = get_pvalues([poisson, normal])
    assert (cor.size == 4)
示例#5
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def test_pvalues_type():
    poisson = np.random.poisson(2, size=100)
    normal = np.random.normal(loc=10, scale=2, size=50)
    cor = get_pvalues([poisson, normal])
    assert (type(cor) == np.ndarray)
示例#6
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def test_pvalues_difference():
    # test p values for very different distributions
    poisson = np.random.poisson(2, size=100)
    normal = np.random.normal(loc=10, scale=2, size=50)
    cor = get_pvalues([poisson, normal])
    assert (cor[0, 1] < 0.05)
示例#7
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def test_pvalues_similarity():
    # test p values for close distributions
    poisson = np.random.poisson(2, size=100)
    normal = np.random.normal(loc=10, scale=2, size=50)
    cor = get_pvalues([poisson, normal])
    assert (cor[0, 0] > 0.95 and cor[1, 1] > 0.95)
示例#8
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def test_pvalues_size():
    poisson = np.random.poisson(2, size=100)
    normal = np.random.normal(loc=10, scale=2, size=50)
    cor = get_pvalues([poisson, normal])
    assert (cor.size == 4)