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I needed to write a weighted version of random.choice (each element in the list has a different probability for being selected). This is what I came up with:
def weightedChoice(choices): """Like random.choice, but each element can have a different chance of being selected. choices can be any iterable containing iterables with two items each. Technically, they can have more than two items, the rest will just be ignored. The first item is the thing being chosen, the second item is its weight. The weights can be any numeric values, what matters is the relative differences between them. """ space = {} current = 0 for choice, weight in choices: if weight > 0: space[current] = choice current += weight rand = random.uniform(0, current) for key in sorted(space.keys() + [current]): if rand < key: return choice choice = space[key] return None This function seems overly complex to me, and ugly. I'm hoping everyone here can offer some suggestions on improving it or alternate ways of doing this. Efficiency isn't as important to me as code cleanliness and readability.
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Weighted random choices mean selecting random elements from a list or an array by the probability of that element. We can assign a probability to each element and according to that element(s) will be selected. By this, we can select one or more than one element from the list, And it can be achieved in two ways.
1) calculate the sum of all the weights. 2) pick a random number that is 0 or greater and is less than the sum of the weights. 3) go through the items one at a time, subtracting their weight from your random number, until you get the item where the random number is less than that item's weight.
Python Random choice() Method The choice() method returns a randomly selected element from the specified sequence. The sequence can be a string, a range, a list, a tuple or any other kind of sequence.
Since version 1.7.0, NumPy has a choice function that supports probability distributions.
from numpy.random import choice draw = choice(list_of_candidates, number_of_items_to_pick, p=probability_distribution) Note that probability_distribution is a sequence in the same order of list_of_candidates. You can also use the keyword replace=False to change the behavior so that drawn items are not replaced.
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