def test_matrix_iter(self):
"""Test PauliSumOp 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)
coeff = 10
op = PauliSumOp(SparsePauliOp(table, coeffs), coeff)
for idx, i in enumerate(op.matrix_iter()):
self.assertTrue(np.array_equal(i, coeff * coeffs[idx] * Pauli(labels[idx]).to_matrix()))
def test_matrix_iter_sparse(self):
"""Test PauliSumOp sparse matrix_iter method."""
labels = ['III', 'IXI', 'IYY', 'YIZ', 'XYZ', 'III']
coeffs = np.array([1, 2, 3, 4, 5, 6])
coeff = 10
table = PauliTable.from_labels(labels)
op = PauliSumOp(SparsePauliOp(table, coeffs), coeff)
for idx, i in enumerate(op.matrix_iter(sparse=True)):
self.assertTrue(
np.array_equal(i.toarray(), coeff * coeffs[idx] *
Pauli(labels[idx]).to_matrix()))
def test_coder_operators(self):
"""Test runtime encoder and decoder for operators."""
x = Parameter("x")
y = x + 1
qc = QuantumCircuit(1)
qc.h(0)
coeffs = np.array([1, 2, 3, 4, 5, 6])
table = PauliTable.from_labels(
["III", "IXI", "IYY", "YIZ", "XYZ", "III"])
op = (2.0 * I ^ I)
z2_symmetries = Z2Symmetries(
[Pauli("IIZI"), Pauli("ZIII")],
[Pauli("IIXI"), Pauli("XIII")], [1, 3], [-1, 1])
isqrt2 = 1 / np.sqrt(2)
sparse = scipy.sparse.csr_matrix([[0, isqrt2, 0, isqrt2]])
subtests = (
PauliSumOp(SparsePauliOp(Pauli("XYZX"), coeffs=[2]), coeff=3),
PauliSumOp(SparsePauliOp(Pauli("XYZX"), coeffs=[1]), coeff=y),
PauliSumOp(SparsePauliOp(Pauli("XYZX"), coeffs=[1 + 2j]),
coeff=3 - 2j),
PauliSumOp.from_list([("II", -1.052373245772859),
("IZ", 0.39793742484318045)]),
PauliSumOp(SparsePauliOp(table, coeffs), coeff=10),
MatrixOp(primitive=np.array([[0, -1j], [1j, 0]]), coeff=x),
PauliOp(primitive=Pauli("Y"), coeff=x),
CircuitOp(qc, coeff=x),
EvolvedOp(op, coeff=x),
TaperedPauliSumOp(SparsePauliOp(Pauli("XYZX"), coeffs=[2]),
z2_symmetries),
StateFn(qc, coeff=x),
CircuitStateFn(qc, is_measurement=True),
DictStateFn("1" * 3, is_measurement=True),
VectorStateFn(np.ones(2**3, dtype=complex)),
OperatorStateFn(CircuitOp(QuantumCircuit(1))),
SparseVectorStateFn(sparse),
Statevector([1, 0]),
CVaRMeasurement(Z, 0.2),
ComposedOp([(X ^ Y ^ Z), (Z ^ X ^ Y ^ Z).to_matrix_op()]),
SummedOp([X ^ X * 2, Y ^ Y], 2),
TensoredOp([(X ^ Y), (Z ^ I)]),
(Z ^ Z) ^ (I ^ 2),
)
for op in subtests:
with self.subTest(op=op):
encoded = json.dumps(op, cls=RuntimeEncoder)
self.assertIsInstance(encoded, str)
decoded = json.loads(encoded, cls=RuntimeDecoder)
self.assertEqual(op, decoded)