def test_pdf(self):
model = StudentTUnivariate()
model.fit(self.data)
sampled_data = model.sample(50)
# Test PDF
pdf = model.probability_density(sampled_data)
assert (0 < pdf).all()
def test_cdf(self):
model = StudentTUnivariate()
model.fit(self.data)
sampled_data = model.sample(50)
# Test CDF
cdf = model.cumulative_distribution(sampled_data)
assert (0 <= cdf).all() and (cdf <= 1).all()
# Test CDF increasing function
sorted_data = sorted(sampled_data)
cdf = model.cumulative_distribution(sorted_data)
assert (np.diff(cdf) >= 0).all()
def test_fit_sample_constant(self):
model = StudentTUnivariate()
model.fit(self.constant)
sampled_data = model.sample(50)
assert isinstance(sampled_data, np.ndarray)
assert sampled_data.shape == (50, )
assert model._constant_value == 5
np.testing.assert_allclose(np.full(50, 5), model.sample(50), atol=0.2)
