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