# SimQN: a discrete-event simulator for the quantum networks
# Copyright (C) 2021-2022 Lutong Chen, Jian Li, Kaiping Xue
# University of Science and Technology of China, USTC.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import random
from typing import Optional
import numpy as np
[docs]def set_seed(seed: Optional[int] = None):
"""
Set a seed for random generator
Args:
seed (int): the seed
"""
if seed is None:
return
random.seed(seed)
np.random.seed(seed)
[docs]def get_rand(low: float = 0, high: float = 1) -> float:
"""
Get a random number from [low, high)
Args:
low (int): the low bound
high (int): the high bound
"""
return low + np.random.random() * (high - low)
[docs]def get_randint(low: int, high: int) -> float:
"""
Get a random integer from [low, high]
Args:
low (int): the low bound
high (int): the high bound
"""
if low != int(low):
raise ValueError("input low")
if low > high:
raise ValueError("low should smaller than high")
return np.random.randint(low, high+1)
[docs]def get_choice(a):
"""
return an random element from a list
Args:
a: a iterable object
"""
return a[get_randint(0, len(a)-1)]
[docs]def get_normal(mean: float = 0, std: float = 1):
return np.random.normal(loc=mean, scale=std)