def test_svd_execution(setup):
rs = np.random.RandomState()
data = rs.randn(18, 6) + 1j * rs.randn(18, 6)
a = tensor(data, chunk_size=(9, 6))
U, s, V = svd(a)
t = U.dot(diag(s).dot(V))
res = t.execute().fetch()
np.testing.assert_array_almost_equal(res, data)
a = tensor(data, chunk_size=(18, 6))
U, s, V = svd(a)
t = U.dot(diag(s).dot(V))
res = t.execute().fetch()
np.testing.assert_array_almost_equal(res, data)
a = tensor(data, chunk_size=(2, 6))
U, s, V = svd(a)
t = U.dot(diag(s).dot(V))
res = t.execute().fetch()
np.testing.assert_array_almost_equal(res, data)
data = rs.randn(6, 18) + 1j * rs.randn(6, 18)
a = tensor(data)
U, s, V = svd(a)
t = U.dot(diag(s).dot(V))
res = t.execute().fetch()
np.testing.assert_array_almost_equal(res, data)
# test for matrix of ones
data = np.ones((20, 10))
a = tensor(data, chunk_size=10)
s = svd(a)[1]
res = s.execute().fetch()
expected = np.linalg.svd(a)[1]
np.testing.assert_array_almost_equal(res, expected)
def testSVDExecution(self):
data = np.random.randn(18, 6) + 1j * np.random.randn(18, 6)
a = tensor(data, chunk_size=(9, 6))
U, s, V = svd(a)
t = U.dot(diag(s).dot(V))
res = self.executor.execute_tensor(t, concat=True)[0]
self.assertTrue(np.allclose(res, data))
a = tensor(data, chunk_size=(18, 6))
U, s, V = svd(a)
t = U.dot(diag(s).dot(V))
res = self.executor.execute_tensor(t, concat=True)[0]
self.assertTrue(np.allclose(res, data))
a = tensor(data, chunk_size=(2, 6))
U, s, V = svd(a)
t = U.dot(diag(s).dot(V))
res = self.executor.execute_tensor(t, concat=True)[0]
self.assertTrue(np.allclose(res, data))
data = np.random.randn(6, 18) + 1j * np.random.randn(6, 18)
a = tensor(data)
U, s, V = svd(a)
t = U.dot(diag(s).dot(V))
res = self.executor.execute_tensor(t, concat=True)[0]
self.assertTrue(np.allclose(res, data))
# test for matrix of ones
data = np.ones((20, 10))
a = tensor(data, chunk_size=10)
s = svd(a)[1]
res = self.executor.execute_tensor(s, concat=True)[0]
expected = np.linalg.svd(a)[1]
np.testing.assert_array_almost_equal(res, expected)
def testDiagExecution(self):
# 2-d 6 * 6
a = arange(36, chunk_size=2).reshape(6, 6)
d = diag(a)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(36).reshape(6, 6))
np.testing.assert_equal(res, expected)
d = diag(a, k=1)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(36).reshape(6, 6), k=1)
np.testing.assert_equal(res, expected)
d = diag(a, k=3)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(36).reshape(6, 6), k=3)
np.testing.assert_equal(res, expected)
d = diag(a, k=-2)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(36).reshape(6, 6), k=-2)
np.testing.assert_equal(res, expected)
d = diag(a, k=-5)
res = self.executor.execute_tensor(d)[0]
expected = np.diag(np.arange(36).reshape(6, 6), k=-5)
np.testing.assert_equal(res, expected)
# 2-d 6 * 6 sparse, no tensor
a = sps.rand(6, 6, density=.1)
d = diag(a)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(a.toarray())
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(a.toarray(), k=1)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=3)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(a.toarray(), k=3)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(a.toarray(), k=-2)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-5)
res = self.executor.execute_tensor(d)[0]
expected = np.diag(a.toarray(), k=-5)
np.testing.assert_equal(res.toarray(), expected)
# 2-d 6 * 6 sparse, from tensor
raw_a = sps.rand(6, 6, density=.1)
a = tensor(raw_a, chunk_size=2)
d = diag(a)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(raw_a.toarray())
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(raw_a.toarray(), k=1)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=3)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(raw_a.toarray(), k=3)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(raw_a.toarray(), k=-2)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-5)
res = self.executor.execute_tensor(d)[0]
expected = np.diag(raw_a.toarray(), k=-5)
np.testing.assert_equal(res.toarray(), expected)
# 2-d 4 * 9
a = arange(36, chunk_size=2).reshape(4, 9)
d = diag(a)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(36).reshape(4, 9))
np.testing.assert_equal(res, expected)
d = diag(a, k=1)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(36).reshape(4, 9), k=1)
np.testing.assert_equal(res, expected)
d = diag(a, k=3)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(36).reshape(4, 9), k=3)
np.testing.assert_equal(res, expected)
d = diag(a, k=-2)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(36).reshape(4, 9), k=-2)
np.testing.assert_equal(res, expected)
d = diag(a, k=-3)
res = self.executor.execute_tensor(d)[0]
expected = np.diag(np.arange(36).reshape(4, 9), k=-3)
np.testing.assert_equal(res, expected)
# 2-d 4 * 9 sparse, no tensor
a = sps.rand(4, 9, density=.1)
d = diag(a)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(a.toarray())
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(a.toarray(), k=1)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=3)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(a.toarray(), k=3)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(a.toarray(), k=-2)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-3)
res = self.executor.execute_tensor(d)[0]
expected = np.diag(a.toarray(), k=-3)
np.testing.assert_equal(res.toarray(), expected)
# 2-d 4 * 9 sparse, from tensor
raw_a = sps.rand(4, 9, density=.1)
a = tensor(raw_a, chunk_size=2)
d = diag(a)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(raw_a.toarray())
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(raw_a.toarray(), k=1)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=3)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(raw_a.toarray(), k=3)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(raw_a.toarray(), k=-2)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-3)
res = self.executor.execute_tensor(d)[0]
expected = np.diag(raw_a.toarray(), k=-3)
np.testing.assert_equal(res.toarray(), expected)
# 1-d
a = arange(5, chunk_size=2)
d = diag(a)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5))
np.testing.assert_equal(res, expected)
self.assertTrue(res.flags['C_CONTIGUOUS'])
self.assertFalse(res.flags['F_CONTIGUOUS'])
d = diag(a, k=1)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5), k=1)
np.testing.assert_equal(res, expected)
d = diag(a, k=3)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5), k=3)
np.testing.assert_equal(res, expected)
d = diag(a, k=-2)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5), k=-2)
np.testing.assert_equal(res, expected)
d = diag(a, k=-3)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5), k=-3)
np.testing.assert_equal(res, expected)
d = diag(a, sparse=True)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5))
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1, sparse=True)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5), k=1)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=2, sparse=True)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5), k=2)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2, sparse=True)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5), k=-2)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-3, sparse=True)
res = self.executor.execute_tensor(d, concat=True)[0]
expected = np.diag(np.arange(5), k=-3)
self.assertIsInstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
def test_diag_execution(setup):
# 2-d 6 * 6
a = arange(36, chunk_size=5).reshape(6, 6)
d = diag(a)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(6, 6))
np.testing.assert_equal(res, expected)
d = diag(a, k=1)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(6, 6), k=1)
np.testing.assert_equal(res, expected)
d = diag(a, k=3)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(6, 6), k=3)
np.testing.assert_equal(res, expected)
d = diag(a, k=-2)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(6, 6), k=-2)
np.testing.assert_equal(res, expected)
d = diag(a, k=-5)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(6, 6), k=-5)
np.testing.assert_equal(res, expected)
# 2-d 6 * 6 sparse, no tensor
a = sps.rand(6, 6, density=.1)
d = diag(a)
res = d.execute().fetch()
expected = np.diag(a.toarray())
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1)
res = d.execute().fetch()
expected = np.diag(a.toarray(), k=1)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=3)
res = d.execute().fetch()
expected = np.diag(a.toarray(), k=3)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2)
res = d.execute().fetch()
expected = np.diag(a.toarray(), k=-2)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-5)
res = d.execute().fetch()
expected = np.diag(a.toarray(), k=-5)
np.testing.assert_equal(res.toarray(), expected)
# 2-d 6 * 6 sparse, from tensor
raw_a = sps.rand(6, 6, density=.1)
a = tensor(raw_a, chunk_size=2)
d = diag(a)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray())
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray(), k=1)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=3)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray(), k=3)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray(), k=-2)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-5)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray(), k=-5)
np.testing.assert_equal(res.toarray(), expected)
# 2-d 4 * 9
a = arange(36, chunk_size=2).reshape(4, 9)
d = diag(a)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(4, 9))
np.testing.assert_equal(res, expected)
d = diag(a, k=1)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(4, 9), k=1)
np.testing.assert_equal(res, expected)
d = diag(a, k=3)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(4, 9), k=3)
np.testing.assert_equal(res, expected)
d = diag(a, k=-2)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(4, 9), k=-2)
np.testing.assert_equal(res, expected)
d = diag(a, k=-3)
res = d.execute().fetch()
expected = np.diag(np.arange(36).reshape(4, 9), k=-3)
np.testing.assert_equal(res, expected)
# 2-d 4 * 9 sparse, no tensor
a = sps.rand(4, 9, density=.1)
d = diag(a)
res = d.execute().fetch()
expected = np.diag(a.toarray())
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1)
res = d.execute().fetch()
expected = np.diag(a.toarray(), k=1)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=3)
res = d.execute().fetch()
expected = np.diag(a.toarray(), k=3)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2)
res = d.execute().fetch()
expected = np.diag(a.toarray(), k=-2)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-3)
res = d.execute().fetch()
expected = np.diag(a.toarray(), k=-3)
np.testing.assert_equal(res.toarray(), expected)
# 2-d 4 * 9 sparse, from tensor
raw_a = sps.rand(4, 9, density=.1)
a = tensor(raw_a, chunk_size=2)
d = diag(a)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray())
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray(), k=1)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=3)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray(), k=3)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray(), k=-2)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-3)
res = d.execute().fetch()
expected = np.diag(raw_a.toarray(), k=-3)
np.testing.assert_equal(res.toarray(), expected)
# 1-d
a = arange(5, chunk_size=2)
d = diag(a)
res = d.execute().fetch()
expected = np.diag(np.arange(5))
np.testing.assert_equal(res, expected)
assert res.flags['C_CONTIGUOUS'] is True
assert res.flags['F_CONTIGUOUS'] is False
d = diag(a, k=1)
res = d.execute().fetch()
expected = np.diag(np.arange(5), k=1)
np.testing.assert_equal(res, expected)
d = diag(a, k=3)
res = d.execute().fetch()
expected = np.diag(np.arange(5), k=3)
np.testing.assert_equal(res, expected)
d = diag(a, k=-2)
res = d.execute().fetch()
expected = np.diag(np.arange(5), k=-2)
np.testing.assert_equal(res, expected)
d = diag(a, k=-3)
res = d.execute().fetch()
expected = np.diag(np.arange(5), k=-3)
np.testing.assert_equal(res, expected)
d = diag(a, sparse=True)
res = d.execute().fetch()
expected = np.diag(np.arange(5))
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=1, sparse=True)
res = d.execute().fetch()
expected = np.diag(np.arange(5), k=1)
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=2, sparse=True)
res = d.execute().fetch()
expected = np.diag(np.arange(5), k=2)
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-2, sparse=True)
res = d.execute().fetch()
expected = np.diag(np.arange(5), k=-2)
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
d = diag(a, k=-3, sparse=True)
res = d.execute().fetch()
expected = np.diag(np.arange(5), k=-3)
assert isinstance(res, SparseNDArray)
np.testing.assert_equal(res.toarray(), expected)
