def setUp(self):
super().setUp()
algorithm_globals.random_seed = 10598
self.optimizer = COBYLA(maxiter=25)
# pylint: disable=no-member
self.backend = qiskit.providers.aer.AerSimulator(method="statevector")
data_block = ZZFeatureMap(2)
trainable_block = ZZFeatureMap(2)
training_parameters = trainable_block.parameters
for i, _ in enumerate(training_parameters):
training_parameters[i]._name = f"θ[{i}]"
self.feature_map = data_block.compose(trainable_block).compose(
data_block)
self.training_parameters = training_parameters
self.sample_train = np.asarray([
[3.07876080, 1.75929189],
[6.03185789, 5.27787566],
[6.22035345, 2.70176968],
[0.18849556, 2.82743339],
])
self.label_train = np.asarray([0, 0, 1, 1])
self.sample_test = np.asarray([[2.199114860, 5.15221195],
[0.50265482, 0.06283185]])
self.label_test = np.asarray([1, 0])
self.quantum_kernel = QuantumKernel(
feature_map=self.feature_map,
training_parameters=self.training_parameters,
quantum_instance=self.backend,
)
def setUp(self):
super().setUp()
# Create an arbitrary 3-qubit feature map circuit
circ1 = ZZFeatureMap(3)
circ2 = ZZFeatureMap(3)
user_params = circ2.parameters
for i, _ in enumerate(user_params):
user_params[i]._name = f"θ[{i}]"
self.feature_map = circ1.compose(circ2).compose(circ1)
self.user_parameters = user_params
