# -*- coding: utf-8 -*-
# This code is part of Qiskit.
#
# (C) Copyright IBM 2019, 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""The Univariate Variational Distribution."""
import warnings
from typing import Union, List
import numpy as np
from qiskit import ClassicalRegister, QuantumCircuit
from qiskit.aqua.components.variational_forms import VariationalForm
from qiskit.aqua.utils.validation import validate_min
from .univariate_distribution import UnivariateDistribution
[docs]class UnivariateVariationalDistribution(UnivariateDistribution):
"""The Univariate Variational Distribution."""
def __init__(self,
num_qubits: int,
var_form: Union[QuantumCircuit, VariationalForm],
params: Union[List[float], np.ndarray],
low: float = 0,
high: float = 1) -> None:
"""
Args:
num_qubits: Number of qubits
var_form: Variational form
params: Parameters for variational form
low: Lower bound
high: Upper bound
"""
validate_min('num_qubits', num_qubits, 1)
self._num_qubits = num_qubits
self._var_form = var_form
# fix the order of the parameters in the circuit
if isinstance(self._var_form, QuantumCircuit):
self._var_form_params = sorted(self._var_form.parameters, key=lambda p: p.name)
else:
warnings.warn('The VariationalForm type is deprecated as argument of the '
'UnivariateVariationalDistribution as of 0.7.0 and will be removed no '
'earlier than 3 months after the release. You should pass an object '
'of type QuantumCircuit instead (see qiskit.circuit.library for a '
'collection of suitable objects).',
DeprecationWarning, stacklevel=2)
self.params = params
if isinstance(num_qubits, int):
probabilities = np.zeros(2 ** num_qubits)
elif isinstance(num_qubits, float):
probabilities = np.zeros(2 ** int(num_qubits))
else:
probabilities = np.zeros(2 ** sum(num_qubits))
super().__init__(num_qubits, probabilities, low, high)
[docs] def build(self, qc, q, q_ancillas=None, params=None):
if isinstance(self._var_form, QuantumCircuit):
param_dict = dict(zip(self._var_form_params, self.params))
circuit_var_form = self._var_form.assign_parameters(param_dict)
else:
circuit_var_form = self._var_form.construct_circuit(self.params)
qc.append(circuit_var_form.to_instruction(), q)
[docs] def set_probabilities(self, quantum_instance):
"""Set Probabilities
Args:
quantum_instance (QuantumInstance): Quantum instance
"""
if isinstance(self._var_form, QuantumCircuit):
param_dict = dict(zip(self._var_form_params, self.params))
qc_ = self._var_form.assign_parameters(param_dict)
else:
qc_ = self._var_form.construct_circuit(self.params)
# q_ = QuantumRegister(self._num_qubits)
# qc_ = QuantumCircuit(q_)
# self.build(qc_, None)
if quantum_instance.is_statevector:
pass
else:
c__ = ClassicalRegister(self._num_qubits, name='c')
qc_.add_register(c__)
qc_.measure(qc_.qregs[0], c__)
result = quantum_instance.execute(qc_)
if quantum_instance.is_statevector:
result = result.get_statevector(qc_)
values = np.multiply(result, np.conj(result))
values = list(values.real)
else:
result = result.get_counts(qc_)
keys = list(result)
values = list(result.values())
values = [float(v) / np.sum(values) for v in values]
values = [x for _, x in sorted(zip(keys, values))]
probabilities = values
self._probabilities = np.array(probabilities)