def testMeanExecution(self):
raw1 = np.random.random((20, 25))
raw2 = np.random.randint(10, size=(20, 25))
arr1 = tensor(raw1, chunk_size=3)
res1 = self.executor.execute_tensor(arr1.mean())
expected1 = raw1.mean()
self.assertTrue(np.allclose(res1[0], expected1))
res2 = self.executor.execute_tensor(arr1.mean(axis=0))
expected2 = raw1.mean(axis=0)
self.assertTrue(np.allclose(np.concatenate(res2), expected2))
res3 = self.executor.execute_tensor(arr1.mean(axis=1, keepdims=True))
expected3 = raw1.mean(axis=1, keepdims=True)
self.assertTrue(np.allclose(np.concatenate(res3), expected3))
arr2 = tensor(raw2, chunk_size=3)
res1 = self.executor.execute_tensor(arr2.mean())
expected1 = raw2.mean()
self.assertEqual(res1[0], expected1)
res2 = self.executor.execute_tensor(arr2.mean(axis=0))
expected2 = raw2.mean(axis=0)
self.assertTrue(np.allclose(np.concatenate(res2), expected2))
res3 = self.executor.execute_tensor(arr2.mean(axis=1, keepdims=True))
expected3 = raw2.mean(axis=1, keepdims=True)
self.assertTrue(np.allclose(np.concatenate(res3), expected3))
raw1 = sps.random(20, 25, density=.1)
arr1 = tensor(raw1, chunk_size=3)
res1 = self.executor.execute_tensor(arr1.mean())
expected1 = raw1.mean()
self.assertTrue(np.allclose(res1[0], expected1))
arr2 = tensor(raw1, chunk_size=30)
res1 = self.executor.execute_tensor(arr2.mean())
expected1 = raw1.mean()
self.assertTrue(np.allclose(res1[0], expected1))
arr = mean(1)
self.assertEqual(self.executor.execute_tensor(arr)[0], 1)
with self.assertRaises(TypeError):
self.executor.execute_tensor(tensor(list('abcdefghi'), dtype=object).mean())
def test_mean_execution(setup):
raw1 = np.random.random((20, 25))
raw2 = np.random.randint(10, size=(20, 25))
arr1 = tensor(raw1, chunk_size=6)
res1 = arr1.mean().execute().fetch()
expected1 = raw1.mean()
np.testing.assert_allclose(res1, expected1)
res2 = arr1.mean(axis=0).execute().fetch()
expected2 = raw1.mean(axis=0)
assert np.allclose(res2, expected2) is True
res3 = arr1.mean(axis=1, keepdims=True).execute().fetch()
expected3 = raw1.mean(axis=1, keepdims=True)
np.testing.assert_allclose(res3, expected3)
arr2 = tensor(raw2, chunk_size=6)
res1 = arr2.mean().execute().fetch()
expected1 = raw2.mean()
assert res1 == expected1
res2 = arr2.mean(axis=0).execute().fetch()
expected2 = raw2.mean(axis=0)
np.testing.assert_allclose(res2, expected2)
res3 = arr2.mean(axis=1, keepdims=True).execute().fetch()
expected3 = raw2.mean(axis=1, keepdims=True)
np.testing.assert_allclose(res3, expected3)
raw1 = sps.random(20, 25, density=.1)
arr1 = tensor(raw1, chunk_size=6)
res1 = arr1.mean().execute().fetch()
expected1 = raw1.mean()
np.testing.assert_allclose(res1, expected1)
arr2 = tensor(raw1, chunk_size=30)
res1 = arr2.mean().execute().fetch()
expected1 = raw1.mean()
np.testing.assert_allclose(res1, expected1)
arr = mean(1)
assert arr.execute().fetch() == 1
with pytest.raises(TypeError):
tensor(list('abcdefghi'), dtype=object).mean().execute()