def testInv(self):
import scipy.linalg
np.random.seed(1)
data = np.random.randint(1, 10, (20, 20))
A = tensor(data)
inv_A = inv(A)
res = self.executor.execute_tensor(inv_A, concat=True)[0]
self.assertTrue(np.allclose(res, scipy.linalg.inv(data)))
res = self.executor.execute_tensor(A.dot(inv_A), concat=True)[0]
self.assertTrue(np.allclose(res, np.eye(data.shape[0], dtype=float)))
A = tensor(data, chunk_size=5)
inv_A = inv(A)
res = self.executor.execute_tensor(inv_A, concat=True)[0]
self.assertTrue(np.allclose(res, scipy.linalg.inv(data)))
res = self.executor.execute_tensor(A.dot(inv_A), concat=True)[0]
self.assertTrue(np.allclose(res, np.eye(data.shape[0], dtype=float)))
B = A.T.dot(A)
inv_B = inv(B)
res = self.executor.execute_tensor(inv_B, concat=True)[0]
self.assertTrue(np.allclose(res, scipy.linalg.inv(data.T.dot(data))))
res = self.executor.execute_tensor(B.dot(inv_B), concat=True)[0]
self.assertTrue(np.allclose(res, np.eye(data.shape[0], dtype=float)))
# test for not all chunks are square in matrix A
A = tensor(data, chunk_size=8)
inv_A = inv(A)
res = self.executor.execute_tensor(inv_A, concat=True)[0]
self.assertTrue(np.allclose(res, scipy.linalg.inv(data)))
res = self.executor.execute_tensor(A.dot(inv_A), concat=True)[0]
self.assertTrue(np.allclose(res, np.eye(data.shape[0], dtype=float)))
# test sparse
data = np.random.randint(1, 10, (20, 20))
sp_data = sps.csr_matrix(data)
A = tensor(sp_data, chunk_size=5)
inv_A = inv(A)
res = self.executor.execute_tensor(inv_A, concat=True)[0]
self.assertIsInstance(res, SparseNDArray)
self.assertTrue(np.allclose(res, scipy.linalg.inv(data)))
res = self.executor.execute_tensor(A.dot(inv_A), concat=True)[0]
self.assertTrue(np.allclose(res, np.eye(data.shape[0], dtype=float)))
# test for not all chunks are square in matrix A
A = tensor(sp_data, chunk_size=8)
inv_A = inv(A)
res = self.executor.execute_tensor(inv_A, concat=True)[0]
self.assertIsInstance(res, SparseNDArray)
self.assertTrue(np.allclose(res, scipy.linalg.inv(data)))
res = self.executor.execute_tensor(A.dot(inv_A), concat=True)[0]
self.assertTrue(np.allclose(res, np.eye(data.shape[0], dtype=float)))
def testInv(self):
import scipy.linalg
np.random.seed(1)
data = np.random.randint(1, 10, (20, 20))
A = tensor(data, chunk_size=5)
inv_A = inv(A)
res = self.executor.execute_tensor(inv_A, concat=True)[0]
self.assertTrue(np.allclose(res, scipy.linalg.inv(data)))
res = self.executor.execute_tensor(A.dot(inv_A), concat=True)[0]
self.assertTrue(np.allclose(res, np.eye(data.shape[0], dtype=float)))
