def test_triu_execution(setup):
a = arange(24, chunk_size=2).reshape(2, 3, 4)
t = triu(a)
res = t.execute().fetch()
expected = np.triu(np.arange(24).reshape(2, 3, 4))
np.testing.assert_equal(res, expected)
t = triu(a, k=1)
res = t.execute().fetch()
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=1)
np.testing.assert_equal(res, expected)
t = triu(a, k=2)
res = t.execute().fetch()
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=2)
np.testing.assert_equal(res, expected)
t = triu(a, k=-1)
res = t.execute().fetch()
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=-1)
np.testing.assert_equal(res, expected)
t = triu(a, k=-2)
res = t.execute().fetch()
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=-2)
np.testing.assert_equal(res, expected)
# test sparse
a = arange(12, chunk_size=2).reshape(3, 4).tosparse()
t = triu(a)
res = t.execute().fetch()
expected = np.triu(np.arange(12).reshape(3, 4))
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=1)
res = t.execute().fetch()
expected = np.triu(np.arange(12).reshape(3, 4), k=1)
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=2)
res = t.execute().fetch()
expected = np.triu(np.arange(12).reshape(3, 4), k=2)
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=-1)
res = t.execute().fetch()
expected = np.triu(np.arange(12).reshape(3, 4), k=-1)
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=-2)
res = t.execute().fetch()
expected = np.triu(np.arange(12).reshape(3, 4), k=-2)
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
raw = np.asfortranarray(np.random.rand(10, 7))
a = tensor(raw, chunk_size=3)
t = triu(a, k=-2)
res = t.execute().fetch()
expected = np.triu(raw, k=-2)
np.testing.assert_array_equal(res, expected)
assert res.flags['C_CONTIGUOUS'] == expected.flags['C_CONTIGUOUS']
assert res.flags['F_CONTIGUOUS'] == expected.flags['F_CONTIGUOUS']
def testTriuExecution(self):
a = arange(24, chunk_size=2).reshape(2, 3, 4)
t = triu(a)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4))
np.testing.assert_equal(res, expected)
t = triu(a, k=1)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=1)
np.testing.assert_equal(res, expected)
t = triu(a, k=2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=2)
np.testing.assert_equal(res, expected)
t = triu(a, k=-1)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=-1)
np.testing.assert_equal(res, expected)
t = triu(a, k=-2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=-2)
np.testing.assert_equal(res, expected)
# test sparse
a = arange(12, chunk_size=2).reshape(3, 4).tosparse()
t = triu(a)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4))
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=1)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4), k=1)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4), k=2)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=-1)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4), k=-1)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=-2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4), k=-2)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
raw = np.asfortranarray(np.random.rand(10, 7))
a = tensor(raw, chunk_size=3)
t = triu(a, k=-2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(raw, k=-2)
np.testing.assert_array_equal(res, expected)
self.assertEqual(res.flags['C_CONTIGUOUS'],
expected.flags['C_CONTIGUOUS'])
self.assertEqual(res.flags['F_CONTIGUOUS'],
expected.flags['F_CONTIGUOUS'])
def testTriuExecution(self):
a = arange(24, chunk_size=2).reshape(2, 3, 4)
t = triu(a)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4))
np.testing.assert_equal(res, expected)
t = triu(a, k=1)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=1)
np.testing.assert_equal(res, expected)
t = triu(a, k=2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=2)
np.testing.assert_equal(res, expected)
t = triu(a, k=-1)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=-1)
np.testing.assert_equal(res, expected)
t = triu(a, k=-2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(24).reshape(2, 3, 4), k=-2)
np.testing.assert_equal(res, expected)
# test sparse
a = arange(12, chunk_size=2).reshape(3, 4).tosparse()
t = triu(a)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4))
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=1)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4), k=1)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4), k=2)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=-1)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4), k=-1)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)
t = triu(a, k=-2)
res = self.executor.execute_tensor(t, concat=True)[0]
expected = np.triu(np.arange(12).reshape(3, 4), k=-2)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res, expected)