def test_two_dimensional_tests_agrees(self):
np.random.seed(43)
me = GaussianQuadraticTest(self.grad_log_normal)
samples = np.random.randn(10,2)
U1,_ = me.get_statisitc_two_dim(10,samples,1)
U2,_ = me.get_statistic_multiple_dim(samples,1)
np.testing.assert_almost_equal(U1,U2)
def test_two_dimensional_tests_agrees(self):
np.random.seed(43)
me = GaussianQuadraticTest(self.grad_log_normal)
samples = np.random.randn(10, 2)
U1, _ = me.get_statisitc_two_dim(10, samples, 1)
U2, _ = me.get_statistic_multiple_dim(samples, 1)
np.testing.assert_almost_equal(U1, U2)
def test_two_dimensional_tests_alt(self):
np.random.seed(43)
me = GaussianQuadraticTest(self.grad_log_normal)
samples = np.random.randn(100,2)+1
U,_ = me.get_statisitc_two_dim(100,samples,1)
p = me.compute_pvalue(U)
assert p == 0
def test_two_dimensional_tests_alt(self):
np.random.seed(43)
me = GaussianQuadraticTest(self.grad_log_normal)
samples = np.random.randn(100, 2) + 1
U, _ = me.get_statisitc_two_dim(100, samples, 1)
p = me.compute_pvalue(U)
assert p == 0
