我有一个大概的清单. 10000个项目.当前的情况是,每个项目都有相关的权重(优先级或重要性).现在最小的权重是-100(可以删除负值和零值),而最大的权重是1500.体重是由人们的直觉决定的(有人认为该物品对社区很重要).由于确定最重要的商品并不容易,我想使用一些随机因素,以使重量较低的商品选择的机会更少,并且将来会调整其重量(常识和随机性.)
I have a list of approx. 10000 items. The current situation is that every item has an associated weight (priority or importance). Now the smallest weight is -100 (negative and zero values can be removed) and the highest weight is 1500. Weight is determined by intuition by people (how somebody thinks the item is important to community). Because it's not easy to determine the most important item, I'd like to use some random factor, so that items with lower weight will have less chance to be chosen and their weight will be adjusted in the future (some mix of common sense and randomness).
您知道如何对函数getItem进行编码吗?
Do you know how to code a function getItem?
def getItem(dict): # this function should return random item from # the dictionary of item-weight pairs (or list of tuples) # Normally I would return only random item from the dictionary, # but now I'd like to have this: The item with weight 1500 should # have much more chance to be returned than the item with weight 10. # What's my idea is to sum up the weights of all items and then compute # some ratios. But maybe you have better idea. return randomItem谢谢
推荐答案看看这个,我认为您需要在不同方法之间进行一些很好的比较在Python中加权随机生成
Have a look at this, i think it's what you need with some nice comparision between different methods Weighted random generation in Python
建议的最简单方法是:
import random def weighted_choice(weights): totals = [] running_total = 0 for w in weights: running_total += w totals.append(running_total) rnd = random.random() * running_total for i, total in enumerate(totals): if rnd < total: return i您可以在上面的链接中找到更多详细信息和可能的改进以及一些不同的方法.
You can find more details and possible improvements as well as some different approaches in the link above.
更多推荐
选择重量随机的物品
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