def test_svds(dtype, R, R1, num_charges): np.random.seed(10) D = 30 charges = [ BaseCharge(np.random.randint(-5, 6, (D, num_charges)), charge_types=[U1Charge] * num_charges) for n in range(R) ] flows = [True] * R A = BlockSparseTensor.random( [Index(charges[n], flows[n]) for n in range(R)], dtype=dtype) u, s, v, _ = decompositions.svd(bs, A, R1) u_dense, s_dense, v_dense, _ = np_decompositions.svd(np, A.todense(), R1) res1 = bs.tensordot(bs.tensordot(u, bs.diag(s), 1), v, 1) res2 = np.tensordot(np.tensordot(u_dense, np.diag(s_dense), 1), v_dense, 1) np.testing.assert_almost_equal(res1.todense(), res2)
def test_outer_product(R1, R2, dtype, num_charges): np.random.seed(10) backend = symmetric_backend.SymmetricBackend() a = get_tensor(R1, num_charges, dtype) b = get_tensor(R2, num_charges, dtype) actual = backend.outer_product(a, b) expected = tensordot(a, b, 0) np.testing.assert_allclose(expected.data, actual.data) assert np.all([ charge_equal(expected._charges[n], actual._charges[n]) for n in range(len(actual._charges)) ])
def test_tensordot(R1, R2, cont, dtype, num_charges): np.random.seed(10) backend = symmetric_backend.SymmetricBackend() a, b, indsa, indsb = get_contractable_tensors(R1, R2, cont, dtype, num_charges) actual = backend.tensordot(a, b, (indsa, indsb)) expected = tensordot(a, b, (indsa, indsb)) np.testing.assert_allclose(expected.data, actual.data) assert np.all([ charge_equal(expected._charges[n], actual._charges[n]) for n in range(len(actual._charges)) ])
def test_qr_decomposition(dtype, R, R1): np.random.seed(10) D = 30 charges = [U1Charge.random(-5, 5, D) for n in range(R)] flows = [True] * R A = BlockSparseTensor.random( [Index(charges[n], flows[n]) for n in range(R)], dtype=dtype) q, r = decompositions.qr_decomposition(bs, A, R1) res = bs.tensordot(q, r, 1) q_dense, r_dense = np_decompositions.qr_decomposition(np, A.todense(), R1) res2 = np.tensordot(q_dense, r_dense, 1) np.testing.assert_almost_equal(res.todense(), res2)
def test_rq(dtype, R, R1, num_charges): np.random.seed(10) D = 30 charges = [ BaseCharge(np.random.randint(-5, 6, (D, num_charges)), charge_types=[U1Charge] * num_charges) for n in range(R) ] flows = [True] * R A = BlockSparseTensor.random( [Index(charges[n], flows[n]) for n in range(R)], dtype=dtype) r, q = decompositions.rq(bs, A, R1) res = bs.tensordot(r, q, 1) r_dense, q_dense = np_decompositions.rq(np, A.todense(), R1, False) res2 = np.tensordot(r_dense, q_dense, 1) np.testing.assert_almost_equal(res.todense(), res2)