def test_matrix_iter_sparse(self):
"""Test SparsePauliOp sparse matrix_iter method."""
labels = ["III", "IXI", "IYY", "YIZ", "XYZ", "III"]
coeffs = np.array([1, 2, 3, 4, 5, 6])
op = SparsePauliOp(labels, coeffs)
for idx, i in enumerate(op.matrix_iter(sparse=True)):
np.testing.assert_array_equal(i.toarray(), coeffs[idx] * pauli_mat(labels[idx]))
def test_matrix_iter_sparse(self):
"""Test PauliTable sparse matrix_iter method."""
labels = ['III', 'IXI', 'IYY', 'YIZ', 'XYZ', 'III']
coeffs = np.array([1, 2, 3, 4, 5, 6])
table = PauliTable.from_labels(labels)
op = SparsePauliOp(table, coeffs)
for idx, i in enumerate(op.matrix_iter(sparse=True)):
self.assertTrue(
np.array_equal(i.toarray(), coeffs[idx] * pauli_mat(labels[idx])))
def test_matrix_iter(self):
"""Test PauliTable dense matrix_iter method."""
labels = ["III", "IXI", "IYY", "YIZ", "XYZ", "III"]
coeffs = np.array([1, 2, 3, 4, 5, 6])
table = PauliTable.from_labels(labels)
op = SparsePauliOp(table, coeffs)
for idx, i in enumerate(op.matrix_iter()):
self.assertTrue(
np.array_equal(i, coeffs[idx] * pauli_mat(labels[idx])))
