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