File size: 2,355 Bytes
b7d9967 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | # This code is part of a Qiskit project.
#
# (C) Copyright IBM 2022, 2023.
#
# 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.
"""Validate an initial point."""
from __future__ import annotations
import numpy as np
from qiskit.circuit import QuantumCircuit
from qiskit_algorithms.utils.algorithm_globals import algorithm_globals
def validate_initial_point(point: np.ndarray | None | None, circuit: QuantumCircuit) -> np.ndarray:
r"""
Validate a choice of initial point against a choice of circuit. If no point is provided, a
random point will be generated within certain parameter bounds. It will first look to the
circuit for these bounds. If the circuit does not specify bounds, bounds of :math:`-2\pi`,
:math:`2\pi` will be used.
Args:
point: An initial point.
circuit: A parameterized quantum circuit.
Returns:
A validated initial point.
Raises:
ValueError: If the dimension of the initial point does not match the number of circuit
parameters.
"""
expected_size = circuit.num_parameters
if point is None:
# get bounds if circuit has them set, otherwise use [-2pi, 2pi] for each parameter
bounds = getattr(circuit, "parameter_bounds", None)
if bounds is None:
bounds = [(-2 * np.pi, 2 * np.pi)] * expected_size
# replace all Nones by [-2pi, 2pi]
lower_bounds = []
upper_bounds = []
for lower, upper in bounds:
lower_bounds.append(lower if lower is not None else -2 * np.pi)
upper_bounds.append(upper if upper is not None else 2 * np.pi)
# sample from within bounds
point = algorithm_globals.random.uniform(lower_bounds, upper_bounds)
elif len(point) != expected_size:
raise ValueError(
f"The dimension of the initial point ({len(point)}) does not match the "
f"number of parameters in the circuit ({expected_size})."
)
return point
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