def test_parameter_prefix(self):
"""Test the Parameter prefix"""
encoding_pauli = PauliFeatureMap(feature_dimension=2,
reps=2,
paulis=["ZY"],
parameter_prefix="p")
encoding_z = ZFeatureMap(feature_dimension=2,
reps=2,
parameter_prefix="q")
encoding_zz = ZZFeatureMap(feature_dimension=2,
reps=2,
parameter_prefix="r")
x = ParameterVector("x", 2)
y = Parameter("y")
self.assertEqual(
str(encoding_pauli.parameters),
"ParameterView([ParameterVectorElement(p[0]), ParameterVectorElement(p[1])])",
)
self.assertEqual(
str(encoding_z.parameters),
"ParameterView([ParameterVectorElement(q[0]), ParameterVectorElement(q[1])])",
)
self.assertEqual(
str(encoding_zz.parameters),
"ParameterView([ParameterVectorElement(r[0]), ParameterVectorElement(r[1])])",
)
encoding_pauli_param_x = encoding_pauli.assign_parameters(x)
encoding_z_param_x = encoding_z.assign_parameters(x)
encoding_zz_param_x = encoding_zz.assign_parameters(x)
self.assertEqual(
str(encoding_pauli_param_x.parameters),
"ParameterView([ParameterVectorElement(x[0]), ParameterVectorElement(x[1])])",
)
self.assertEqual(
str(encoding_z_param_x.parameters),
"ParameterView([ParameterVectorElement(x[0]), ParameterVectorElement(x[1])])",
)
self.assertEqual(
str(encoding_zz_param_x.parameters),
"ParameterView([ParameterVectorElement(x[0]), ParameterVectorElement(x[1])])",
)
encoding_pauli_param_y = encoding_pauli.assign_parameters({1, y})
encoding_z_param_y = encoding_z.assign_parameters({1, y})
encoding_zz_param_y = encoding_zz.assign_parameters({1, y})
self.assertEqual(str(encoding_pauli_param_y.parameters),
"ParameterView([Parameter(y)])")
self.assertEqual(str(encoding_z_param_y.parameters),
"ParameterView([Parameter(y)])")
self.assertEqual(str(encoding_zz_param_y.parameters),
"ParameterView([Parameter(y)])")
def test_partial_large_circuit(self, method):
np.random.seed(21)
featuremap = ZFeatureMap(2, reps=1)
featuremap.assign_parameters(np.random.random(
featuremap.num_parameters), inplace=True)
ansatz = RealAmplitudes(2, reps=1)
params = ansatz.ordered_parameters[:]
values = np.random.random(ansatz.num_parameters)
init = Statevector.from_int(1, dims=(2, 2))
circuit = featuremap.compose(ansatz)
grad = StateGradient(X ^ X, circuit, init, params)
grads = getattr(grad, method)(dict(zip(params, values)))
ref = [-0.7700884147948044, 0.011116605029003569, -0.6889501710944109,
-0.07972088641561373]
np.testing.assert_array_almost_equal(grads, ref)
def _build(self):
# wipe current state
self._data = []
self._parameter_table = ParameterTable()
# get UCCSD circuit
featmap = ZFeatureMap(self.num_qubits, reps=self.reps)
ansatz = RealAmplitudes(self.num_qubits,
reps=self.reps,
entanglement='circular')
# store the parameters in a list for assigning them
self._params = ansatz.ordered_parameters
# set the data circuit with some input data
featmap.assign_parameters(np.random.random(featmap.num_parameters),
inplace=True)
# combine the circuit
self.compose(featmap, inplace=True)
self.compose(ansatz, inplace=True)