# Quellcode für qiskit.aqua.components.uncertainty_models.multivariate_uniform_distribution

# This code is part of Qiskit.
#
# (C) Copyright IBM 2018, 2021.
#
# obtain a copy of this license in the LICENSE.txt file in the root directory
#
# 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 Multivariate Uniform Distribution.
"""

from typing import Optional, List, Union
import numpy as np
from .multivariate_distribution import MultivariateDistribution

[Doku]class MultivariateUniformDistribution(MultivariateDistribution):
"""
The Multivariate Uniform Distribution.

Although this just results in a Hadamard gate on all involved qubits, the lower and upper
bounds and the assignment of the qubits to the different dimensions is important if used in
a particular application.
"""

[Doku]    def __init__(self,
num_qubits: Union[List[int], np.ndarray],
low: Optional[Union[List[float], np.ndarray]] = None,
high: Optional[Union[List[float], np.ndarray]] = None) -> None:
"""
Args:
num_qubits: List with the number of qubits per dimension
low: List with the lower bounds per dimension, set to 0 for each dimension if None
high: List with the upper bounds per dimension, set to 1 for each dimension if None
"""
if low is None:
low = np.zeros(num_qubits)  # type: ignore
if high is None:
high = np.ones(num_qubits)  # type: ignore

num_values = np.prod([2**n for n in num_qubits])
probabilities = np.ones(num_values)  # type: ignore
super().__init__(num_qubits, probabilities, low, high)  # type: ignore

@staticmethod
def _replacement():
return 'qiskit.circuit.library.UniformDistribution'

[Doku]    def build(self, qc, q, q_ancillas=None, params=None):
if params is None or params['i_state'] is None:
for i in range(sum(self.num_qubits)):
qc.h(q[i])
else:
for qubits in params['i_state']:
for i in qubits:
qc.h(q[i])