def test_vs_nonmasked(self): np.random.seed(1234567) outcome = np.random.randn(20, 4) + [0, 0, 1, 2] # 1-D inputs res1 = stats.ttest_ind(outcome[:, 0], outcome[:, 1]) res2 = mstats.ttest_ind(outcome[:, 0], outcome[:, 1]) assert_allclose(res1, res2) # 2-D inputs res1 = stats.ttest_ind(outcome[:, 0], outcome[:, 1], axis=None) res2 = mstats.ttest_ind(outcome[:, 0], outcome[:, 1], axis=None) assert_allclose(res1, res2) res1 = stats.ttest_ind(outcome[:, :2], outcome[:, 2:], axis=0) res2 = mstats.ttest_ind(outcome[:, :2], outcome[:, 2:], axis=0) assert_allclose(res1, res2) # Check default is axis=0 res3 = mstats.ttest_ind(outcome[:, :2], outcome[:, 2:]) assert_allclose(res2, res3)
def test_empty(self): res1 = mstats.ttest_ind([], []) assert_(np.all(np.isnan(res1)))