在 python 3.5 中使用 random.choices() 的替代方法是什么
What is an alternative method of using random.choices() in python 3.5
因为 random.choices() 在 python 3.5 中不可用,是否有其他方法可以实现此功能?
按照 Mark Dickinson 的建议将代码从 python 3.6 复制到
from itertools import accumulate as _accumulate, repeat as _repeat
from bisect import bisect as _bisect
import random
def choices(population, weights=None, *, cum_weights=None, k=1):
"""Return a k sized list of population elements chosen with replacement.
If the relative weights or cumulative weights are not specified,
the selections are made with equal probability.
"""
n = len(population)
if cum_weights is None:
if weights is None:
_int = int
n += 0.0 # convert to float for a small speed improvement
return [population[_int(random.random() * n)] for i in _repeat(None, k)]
cum_weights = list(_accumulate(weights))
elif weights is not None:
raise TypeError('Cannot specify both weights and cumulative weights')
if len(cum_weights) != n:
raise ValueError('The number of weights does not match the population')
bisect = _bisect
total = cum_weights[-1] + 0.0 # convert to float
hi = n - 1
return [population[bisect(cum_weights, random.random() * total, 0, hi)]
for i in _repeat(None, k)]
现在可以安心使用choices
功能了!
因为 random.choices() 在 python 3.5 中不可用,是否有其他方法可以实现此功能?
按照 Mark Dickinson 的建议将代码从 python 3.6 复制到
from itertools import accumulate as _accumulate, repeat as _repeat
from bisect import bisect as _bisect
import random
def choices(population, weights=None, *, cum_weights=None, k=1):
"""Return a k sized list of population elements chosen with replacement.
If the relative weights or cumulative weights are not specified,
the selections are made with equal probability.
"""
n = len(population)
if cum_weights is None:
if weights is None:
_int = int
n += 0.0 # convert to float for a small speed improvement
return [population[_int(random.random() * n)] for i in _repeat(None, k)]
cum_weights = list(_accumulate(weights))
elif weights is not None:
raise TypeError('Cannot specify both weights and cumulative weights')
if len(cum_weights) != n:
raise ValueError('The number of weights does not match the population')
bisect = _bisect
total = cum_weights[-1] + 0.0 # convert to float
hi = n - 1
return [population[bisect(cum_weights, random.random() * total, 0, hi)]
for i in _repeat(None, k)]
现在可以安心使用choices
功能了!