def test_verbosity_false(capsys):
'''verbosity false for ks'''
d1 = np.random.normal(size=1000)
d2 = d1
ks(d1, d2, verbose=False)
captured = capsys.readouterr()
assert captured.out == ""
def test_verbosity_true_(capsys):
d1 = np.random.normal(size=1000)
d2 = d1
ks(d1, d2, verbose=True)
captured = capsys.readouterr()
assert captured.out == "\nKS: pvalue = 1.0\n\nKS: Null hypothesis cannot be rejected. Distributions not statistically different.\n"
es(d1, d2, verbose=True)
captured = capsys.readouterr()
assert captured.out == "\nES: pvalue = 1.0\n\nES: Null hypothesis cannot be rejected. Distributions not statistically different.\n"
def test_ks_returns_small():
"""
Test.
"""
d1 = np.random.normal(size=1000)
d2 = np.random.weibull(1, size=1000) - 1
assert ks(d1, d2)[1] < 0.001
def test_ks_accepts_pd_series():
"""
Test.
"""
d1 = pd.Series(np.random.normal(size=1000))
d2 = d1
assert ks(d1, d2)[1] == 1.0
def test_ks_returns_one():
"""
Test.
"""
d1 = np.random.normal(size=1000)
d2 = d1
assert ks(d1, d2)[1] == 1.0
def test_distribution_statistics_attributes_ks():
d1 = np.histogram(np.random.normal(size=1000), 10)[0]
d2 = np.histogram(np.random.normal(size=1000), 10)[0]
myTest = DistributionStatistics('ks', binning_strategy=None)
_ = myTest.compute(d1, d2, verbose=False)
ks_value, p_value = ks(d1, d2)
assert myTest.statistic == ks_value
def test_ks_returns_small():
'''Kolmogorov-Smirnov test statistic returns small value (<0.001)'''
d1 = np.random.normal(size=1000)
d2 = np.random.weibull(1, size=1000) - 1
assert ks(d1, d2)[1] < 0.001
def test_ks_accepts_pd_series():
'''Kolmogorov-Smirnov test statistic accepts pd Series'''
d1 = pd.Series(np.random.normal(size=1000))
d2 = d1
assert ks(d1, d2)[1] == 1.0
def test_ks_returns_one():
'''Kolmogorov-Smirnov test statistic returns one'''
d1 = np.random.normal(size=1000)
d2 = d1
assert ks(d1, d2)[1] == 1.0
