def test_psi_returns_zero():
x = np.random.normal(size=1000)
myBucketer = binning.QuantileBucketer(bin_count=10)
myBucketer.fit(x)
d1 = myBucketer.counts_
d2 = d1
psi_test, p_value_test = psi(d1, d2, verbose=False)
assert psi_test == 0.0
def test_psi_returns_large():
"""
Test.
"""
d1 = np.histogram(np.random.normal(size=1000), 10)[0]
d2 = np.histogram(np.random.weibull(1, size=1000) - 1, 10)[0]
psi_test, p_value_test = psi(d1, d2, verbose=False)
assert psi_test > 1.0
def test_distribution_statistics_attributes_psi():
a = np.random.normal(size=1000)
b = np.random.normal(size=1000)
d1 = np.histogram(a, 10)[0]
d2 = np.histogram(b, 10)[0]
myTest = DistributionStatistics('psi', binning_strategy=None)
_ = myTest.compute(d1, d2, verbose=False)
psi_value_test, p_value_test = psi(d1, d2, verbose=False)
assert myTest.statistic == psi_value_test
def test_psi_returns_large():
'''Population Stability Index returns large value (>1.0)'''
d1 = np.histogram(np.random.normal(size=1000), 10)[0]
d2 = np.histogram(np.random.weibull(1, size=1000) - 1, 10)[0]
psi_test, p_value_test = psi(d1, d2, verbose=False)
assert psi_test > 1.0
