def test_noise_model(kraus_model_I_dict, kraus_model_RX90_dict): noise_model_dict = { "gates": [kraus_model_I_dict, kraus_model_RX90_dict], "assignment_probs": {"1": [[1.0, 0.0], [0.0, 1.0]], "0": [[1.0, 0.0], [0.0, 1.0]]}, } nm = NoiseModel.from_dict(noise_model_dict) km1 = KrausModel.from_dict(kraus_model_I_dict) km2 = KrausModel.from_dict(kraus_model_RX90_dict) assert nm == NoiseModel(gates=[km1, km2], assignment_probs={0: np.eye(2), 1: np.eye(2)}) assert nm.gates_by_name("I") == [km1] assert nm.gates_by_name("RX") == [km2] assert nm.to_dict() == noise_model_dict
def test_noise_model(kraus_model_I_dict, kraus_model_RX90_dict): noise_model_dict = {'gates': [kraus_model_I_dict, kraus_model_RX90_dict], 'assignment_probs': {'1': [[1.0, 0.0], [0.0, 1.0]], '0': [[1.0, 0.0], [0.0, 1.0]]}, } nm = NoiseModel.from_dict(noise_model_dict) km1 = KrausModel.from_dict(kraus_model_I_dict) km2 = KrausModel.from_dict(kraus_model_RX90_dict) assert nm == NoiseModel(gates=[km1, km2], assignment_probs={0: np.eye(2), 1: np.eye(2)}) assert nm.gates_by_name('I') == [km1] assert nm.gates_by_name('RX') == [km2] assert nm.to_dict() == noise_model_dict
def test_kraus_model(): km = KrausModel('I', (5., ), (0, 1), [np.array([[1 + 1j]])], 1.0) d = km.to_dict() assert d == OrderedDict([('gate', km.gate), ('params', km.params), ('targets', (0, 1)), ('kraus_ops', [[[[1.]], [[1.0]]]]), ('fidelity', 1.0)]) assert KrausModel.from_dict(d) == km
def test_kraus_model(): km = KrausModel("I", (5.0, ), (0, 1), [np.array([[1 + 1j]])], 1.0) d = km.to_dict() assert d == OrderedDict([ ("gate", km.gate), ("params", km.params), ("targets", (0, 1)), ("kraus_ops", [[[[1.0]], [[1.0]]]]), ("fidelity", 1.0), ]) assert KrausModel.from_dict(d) == km
def test_kraus_model(kraus_model_I_dict): km = KrausModel.from_dict(kraus_model_I_dict) assert km == KrausModel(gate=kraus_model_I_dict['gate'], params=kraus_model_I_dict['params'], targets=kraus_model_I_dict['targets'], kraus_ops=[ KrausModel.unpack_kraus_matrix(kraus_op) for kraus_op in kraus_model_I_dict['kraus_ops'] ], fidelity=kraus_model_I_dict['fidelity']) d = km.to_dict() assert d == OrderedDict([('gate', km.gate), ('params', km.params), ('targets', (0, 1)), ('kraus_ops', [[[[1.]], [[1.0]]]]), ('fidelity', 1.0)])
def test_kraus_model_2(kraus_model_I_dict): km = KrausModel.from_dict(kraus_model_I_dict) assert km == KrausModel( gate=kraus_model_I_dict["gate"], params=kraus_model_I_dict["params"], targets=kraus_model_I_dict["targets"], kraus_ops=[ KrausModel.unpack_kraus_matrix(kraus_op) for kraus_op in kraus_model_I_dict["kraus_ops"] ], fidelity=kraus_model_I_dict["fidelity"], ) d = km.to_dict() assert d == OrderedDict([ ("gate", km.gate), ("params", km.params), ("targets", (0, 1)), ("kraus_ops", [[[[1.0]], [[1.0]]]]), ("fidelity", 1.0), ])