# This code is part of Qiskit. # # (C) Copyright IBM 2018, 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 Log-Normal Distribution. """ from scipy.stats.distributions import lognorm import numpy as np from qiskit.aqua.utils.validation import validate_min from .univariate_distribution import UnivariateDistribution[ドキュメント]class LogNormalDistribution(UnivariateDistribution): """ The Univariate Log-Normal Distribution. Log-normal distribution, truncated to lower and upper bound and discretized on a grid defined by the number of qubits. """ def __init__(self, num_target_qubits: int, mu: float = 0, sigma: float = 1, low: float = 0, high: float = 1) -> None: r""" Args: num_target_qubits: Number of qubits it acts on, has a minimum value of 1. mu: Expected value of considered normal distribution sigma: Standard deviation of considered normal distribution low: Lower bound, i.e., the value corresponding to \|0...0> (assuming an equidistant grid) high: Upper bound, i.e., the value corresponding to \|1...1> (assuming an equidistant grid) """ validate_min('num_target_qubits', num_target_qubits, 1) probabilities, _ = UnivariateDistribution.\ pdf_to_probabilities( lambda x: lognorm.pdf(x, s=sigma, scale=np.exp(mu)), low, high, 2 ** num_target_qubits) super().__init__(num_target_qubits, probabilities, low, high) @staticmethod def _replacement(): return 'qiskit.circuit.library.LogNormalDistribution'