Example #1
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def test_integration_nonperfect_linear():
    X, y = data_gen(nrows=100, Non_perfect=True)
    X_train, X_test, y_train, y_test = train_test_split(X, y)
    scores = cross_validation(lm(), X=X_train, y=y_train, shuffle=False)
    summary = summary_cv(scores)
    assert summary['mean'] < 1 and summary['median'] < 1 and summary[
        'sd'] > 0, 'Non-perfect linear relation test does not give correct summary'
Example #2
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def test_integration_nonperfect_linear():
    X, y = data_gen(nrows=100, Non_perfect=True)
    X_train, X_test, y_train, y_test = train_test_split(X, y)
    scores = cross_validation(lm(), X=X_train, y=y_train, shuffle=False)
    summary = summary_cv(scores)
    assert summary['mean'] < 1 and summary['median'] < 1 and summary[
        'sd'] > 0, 'Non-perfect linear relation test does not give correct summary'
Example #3
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def test_sd_is_float():
    assert isinstance(summary_cv(gen_summary())['sd'], float)
Example #4
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def test_output_length():
    assert len(summary_cv(gen_summary())) == 3
Example #5
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def test_input_contains_over_1():
    with pytest.raises(ValueError):
        summary_cv(scores=[0.96, 0.97, 1.98])
Example #6
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def test_zero_length_input():
    with pytest.raises(TypeError):
        summary_cv(scores=[])
Example #7
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def test_input_as_tuple():
    with pytest.raises(TypeError):
        summary_cv(scores=(0.96, 0.97, 0.98, 0.99))
Example #8
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def test_summary_cv_sd():
    assert summary_cv(gen_summary())['sd'] == 0.009
Example #9
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def test_sd_is_float():
    assert isinstance(summary_cv(gen_summary())['sd'], float)
Example #10
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def test_summary_cv():
    assert summary_cv(gen_summary())['mean'] == 0.9666667
    assert summary_cv(gen_summary())['sd'] == 0.01032796
    assert summary_cv(gen_summary())['mode'] == 0.97
    assert summary_cv(gen_summary())['median'] == 0.97
Example #11
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def test_is_float():
    assert isinstance(summary_cv(gen_summary())['mean'], float)
    assert isinstance(summary_cv(gen_summary())['sd'], float)
    assert isinstance(summary_cv(gen_summary())['mode'], float)
    assert isinstance(summary_cv(gen_summary())['median'], float)
Example #12
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def test_input_contains_over_1():
    with pytest.raises(ValueError('`scores` must be between 0 and 1.')):
        summary_cv(scores=[0.96, 0.97, 1.98])
Example #13
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def test_input_contains_negative():
    with pytest.raises(ValueError('`scores` must be a nonnegative number.')):
        summary_cv(scores=[0.96, 0.97, -0.98])
Example #14
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def test_zero_length_input():
    with pytest.raises(DimensionError('`scores` cannot be of length zero.')):
        summary_cv(scores=[])
Example #15
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def test_summary_cv_sd():
    assert summary_cv(gen_summary())['sd'] == 0.009
Example #16
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def test_input_contains_string():
    with pytest.raises(TypeError('Elements of `scores` must be numbers.')):
        summary_cv(scores=c(0.96, 0.97, "0.98"))
Example #17
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def test_input_as_dataframe():
    with pytest.raises(TypeError):
        summary_cv(scores=pd.DataFrame(
            data={'cv_scores': [0.97, 0.96, 0.98, 0.97, 0.95, 0.97]}))
Example #18
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def test_summary_cv_median():
    assert summary_cv(gen_summary())['median'] == 0.97
Example #19
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def test_input_as_tuple():
    with pytest.raises(TypeError):
        summary_cv(scores=(0.96, 0.97, 0.98, 0.99))
Example #20
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def test_input_as_dataframe():
    with pytest.raises(TypeError):
        summary_cv(scores=pd.DataFrame(data={'cv_scores': [0.97, 0.96, 0.98, 0.97, 0.95, 0.97]}))
Example #21
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def test_input_contains_string():
    with pytest.raises(TypeError):
        summary_cv(scores=[0.96, 0.97, "0.98"])
Example #22
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def test_input_contains_string():
    with pytest.raises(TypeError):
        summary_cv(scores=[0.96, 0.97, "0.98"])
Example #23
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def test_zero_length_input():
    with pytest.raises(TypeError):
        summary_cv(scores=[])
Example #24
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def test_input_contains_negative():
    with pytest.raises(ValueError):
        summary_cv(scores=[0.96, 0.97, -0.98])
Example #25
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def test_input_contains_negative():
    with pytest.raises(ValueError):
        summary_cv(scores=[0.96, 0.97, -0.98])
Example #26
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def test_is_dict():
    assert isinstance(summary_cv(gen_summary()), dict)
Example #27
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def test_input_contains_over_1():
    with pytest.raises(ValueError):
        summary_cv(scores=[0.96, 0.97, 1.98])
Example #28
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def test_median_is_float():
    assert isinstance(summary_cv(gen_summary())['median'], float)
Example #29
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def test_is_dict():
    assert isinstance(summary_cv(gen_summary()), dict)
Example #30
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def test_summary_cv_median():
    assert summary_cv(gen_summary())['median'] == 0.97
Example #31
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def test_output_length():
    assert len(summary_cv(gen_summary())) == 3
Example #32
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def test_median_is_float():
    assert isinstance(summary_cv(gen_summary())['median'], float)
Example #33
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def test_input_as_tuple():
    with pytest.raises(TypeError('`scores` must be a list.')):
        summary_cv(scores=(0.96, 0.97, 0.98, 0.99))