def test_floquet_parse_result_bad_metric():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
request = FloquetPhasedFSimCalibrationRequest(
gate=gate,
pairs=((q_00, q_01), (q_02, q_03)),
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
result = cirq_google.CalibrationResult(
code=cirq_google.api.v2.calibration_pb2.SUCCESS,
error_message=None,
token=None,
valid_until=None,
metrics=cirq_google.Calibration(
cirq_google.api.v2.metrics_pb2.MetricsSnapshot(metrics=[
cirq_google.api.v2.metrics_pb2.Metric(
name='angles',
targets=[
'1000gerbils',
],
values=[
cirq_google.api.v2.metrics_pb2.Value(str_val='100_10'),
],
)
])),
)
with pytest.raises(ValueError, match='Unknown metric name 1000gerbils'):
_ = request.parse_result(result)
def test_floquet_parse_result_failure():
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
request = FloquetPhasedFSimCalibrationRequest(
gate=gate,
pairs=(),
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
result = cirq_google.CalibrationResult(
code=cirq_google.api.v2.calibration_pb2.ERROR_CALIBRATION_FAILED,
error_message="Test message",
token=None,
valid_until=None,
metrics=cirq_google.Calibration(),
)
with pytest.raises(PhasedFSimCalibrationError, match='Test message'):
request.parse_result(result)
def test_floquet_parse_result():
q_00, q_01, q_02, q_03 = [cirq.GridQubit(0, index) for index in range(4)]
gate = cirq.FSimGate(theta=np.pi / 4, phi=0.0)
request = FloquetPhasedFSimCalibrationRequest(
gate=gate,
pairs=((q_00, q_01), (q_02, q_03)),
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)
result = cirq_google.CalibrationResult(
code=cirq_google.api.v2.calibration_pb2.SUCCESS,
error_message=None,
token=None,
valid_until=None,
metrics=cirq_google.Calibration(
cirq_google.api.v2.metrics_pb2.MetricsSnapshot(metrics=[
cirq_google.api.v2.metrics_pb2.Metric(
name='angles',
targets=[
'0_qubit_a',
'0_qubit_b',
'0_theta_est',
'0_zeta_est',
'0_phi_est',
'1_qubit_a',
'1_qubit_b',
'1_theta_est',
'1_zeta_est',
'1_phi_est',
],
values=[
cirq_google.api.v2.metrics_pb2.Value(str_val='0_0'),
cirq_google.api.v2.metrics_pb2.Value(str_val='0_1'),
cirq_google.api.v2.metrics_pb2.Value(double_val=0.1),
cirq_google.api.v2.metrics_pb2.Value(double_val=0.2),
cirq_google.api.v2.metrics_pb2.Value(double_val=0.3),
cirq_google.api.v2.metrics_pb2.Value(str_val='0_2'),
cirq_google.api.v2.metrics_pb2.Value(str_val='0_3'),
cirq_google.api.v2.metrics_pb2.Value(double_val=0.4),
cirq_google.api.v2.metrics_pb2.Value(double_val=0.5),
cirq_google.api.v2.metrics_pb2.Value(double_val=0.6),
],
)
])),
)
assert request.parse_result(result) == PhasedFSimCalibrationResult(
parameters={
(q_00, q_01):
PhasedFSimCharacterization(theta=0.1,
zeta=0.2,
chi=None,
gamma=None,
phi=0.3),
(q_02, q_03):
PhasedFSimCharacterization(theta=0.4,
zeta=0.5,
chi=None,
gamma=None,
phi=0.6),
},
gate=gate,
options=FloquetPhasedFSimCalibrationOptions(
characterize_theta=True,
characterize_zeta=True,
characterize_chi=False,
characterize_gamma=False,
characterize_phi=True,
),
)