def test_sample_distribution(self):
n_samples = 1000
np.random.seed(805)
bounds = np.random.rand(2) + np.array([0, 1])
u = Uniform(*bounds)
samples = u.sample(n_samples)
p_val = kstest(samples, 'uniform', (bounds[0], np.diff(bounds)))[1]
self.assertTrue(p_val > 0.05)
def test_sample_shape(self):
n_samples = 7
bounds = np.random.rand(2) + np.array([0, 1])
u = Uniform(*bounds)
samples = u.sample(n_samples)
self.assertEqual(samples.shape, np.array(n_samples))
self.assertTrue(np.all(samples > bounds[0]))
self.assertTrue(np.all(samples < bounds[1]))
