def test__extract_constant(self):
distribution = UniformUnivariate()
distribution._params = {'loc': 1, 'scale': 0}
constant = distribution._extract_constant()
assert 1 == constant
def test__fit(self):
distribution = UniformUnivariate()
data = uniform.rvs(size=1000, loc=0, scale=1)
distribution._fit(data)
expected = {
'loc': 0,
'scale': 1,
}
for key, value in distribution._params.items():
np.testing.assert_allclose(value, expected[key], atol=0.3)
def test__fit_constant(self):
distribution = UniformUnivariate()
distribution._fit_constant(np.array([1, 1, 1, 1]))
assert distribution._params == {'loc': 1, 'scale': 0}
def test__is_constant_false(self):
distribution = UniformUnivariate()
distribution.fit(np.array([1, 2, 3, 4]))
assert not distribution._is_constant()
def test__is_constant_true(self):
distribution = UniformUnivariate()
distribution.fit(np.array([1, 1, 1, 1]))
assert distribution._is_constant()