如何在python中draw samples

如何在python中draw samples

https://stackoverflow.com/questions/10803135/weighted-choice-short-and-simple/15907274

[Youtube videos tutorial]https://www.youtube.com/watch?v=KzqSDvzOFNA&pbjreload=101&ab_channel=CoreySchafer

Since Python 3.6 there is a method choices from the random module.

import random
random.choices(population = [['a','b'], ['b','a'], ['c','b']],
               weights = [0.2, 0.2, 0.6],
               k = 10)
import random
random.choices(['one', 'two', 'three'], [0.2, 0.3, 0.5], k=10)

也可以用numpy模块

numpy.random.choice(items, trials, p = probs)

Since numpy version 1.7 you can use numpy.random.choice():

elements = ['one', 'two', 'three'] 
weights = [0.2, 0.3, 0.5]

from numpy.random import choice
print(choice(elements, p = weights))

通过这个语句可以按照一定的概率选取一个或几个元素,用来控制强化学习任务中的输钱和赢钱的

random.choices(population = ['H', 'T'], weights = [0.3, 0.7], k = 1)

Note that random.choices will sample with replacement, per the docs:

https://pynative.com/python-random-choice/

Use random.choice() to Randomly select an item from a list

import random
movie_list = ['The Godfather', 'The Wizard of Oz', 'Citizen Kane', 'The Shawshank Redemption', 'Pulp Fiction']

moview_item = random.choice(movie_list)
print ("Randomly selected item from list is - ", moview_item)

https://pynative.com/python-weighted-random-choices-with-probability/

random.choices()

Python 3.6 introduced a new function choices() in the random module. By using random.choices() we can make a weighted random choice with replacement. You can also call it a weighted random sample with replacement. Let’s have a look into the syntax of this function.

Yuan Bo 袁博
Yuan Bo 袁博
Associate Professor of Psychology (Social Psychology)

My research examines the nature and dynamics of social norms, namely how norms may emerge and become stable, why norms may suddenly change, how is it possible that inefficient or unpopular norms survive, and what motivates people to obey norms. I combines laboratory and simulation experiments to test theoretical predictions and build empirically-grounded models of social norms and their dynamics.

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