def test_sample(self):
mcgsm = MCGSM(1, 1, 1, 1, 1)
mcgsm.scales = [[0.]]
mcgsm.predictors = [[0.]]
samples = mcgsm.sample(zeros([1, 10000])).flatten()
p = kstest(samples, lambda x: norm.cdf(x, scale=1.))[1]
# make sure Gaussian random number generation works
self.assertTrue(p > 0.0001)
def test_sample(self):
mcgsm = MCGSM(1, 1, 1, 1, 1)
mcgsm.scales = [[0.0]]
mcgsm.predictors = [[0.0]]
samples = mcgsm.sample(zeros([1, 10000])).flatten()
p = kstest(samples, lambda x: norm.cdf(x, scale=1.0))[1]
# make sure Gaussian random number generation works
self.assertTrue(p > 0.0001)
