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)))