def testNanCumReduction(self):
raw = np.random.randint(5, size=(8, 8, 8))
raw[:2, 2:4, 4:6] = np.nan
arr = tensor(raw, chunk_size=3)
res1 = self.executor.execute_tensor(nancumsum(arr, axis=1),
concat=True)
res2 = self.executor.execute_tensor(nancumprod(arr, axis=1),
concat=True)
expected1 = np.nancumsum(raw, axis=1)
expected2 = np.nancumprod(raw, axis=1)
np.testing.assert_array_equal(res1[0], expected1)
np.testing.assert_array_equal(res2[0], expected2)
raw = sps.random(8, 8, density=.1, format='lil')
raw[:2, 2:4] = np.nan
arr = tensor(raw, chunk_size=3)
res1 = self.executor.execute_tensor(nancumsum(arr, axis=1),
concat=True)[0]
res2 = self.executor.execute_tensor(nancumprod(arr, axis=1),
concat=True)[0]
expected1 = np.nancumsum(raw.A, axis=1)
expected2 = np.nancumprod(raw.A, axis=1)
self.assertTrue(np.allclose(res1, expected1))
self.assertTrue(np.allclose(res2, expected2))
def test_nan_cum_reduction(setup):
raw = np.random.randint(5, size=(8, 8, 8)).astype(float)
raw[:2, 2:4, 4:6] = np.nan
arr = tensor(raw, chunk_size=6)
res1 = nancumsum(arr, axis=1).execute().fetch()
res2 = nancumprod(arr, axis=1).execute().fetch()
expected1 = np.nancumsum(raw, axis=1)
expected2 = np.nancumprod(raw, axis=1)
np.testing.assert_array_equal(res1, expected1)
np.testing.assert_array_equal(res2, expected2)
raw = sps.random(8, 8, density=.1, format='lil')
raw[:2, 2:4] = np.nan
arr = tensor(raw, chunk_size=6)
res1 = nancumsum(arr, axis=1).execute().fetch()
res2 = nancumprod(arr, axis=1).execute().fetch()
expected1 = np.nancumsum(raw.A, axis=1)
expected2 = np.nancumprod(raw.A, axis=1)
assert np.allclose(res1, expected1) is True
assert np.allclose(res2, expected2) is True