Probability distribution in Python

Question

I have a bunch of keys that each have an unlikeliness variable. I want to randomly choose one of these keys, yet I want it to be more unlikely for unlikely (key, values) to

Answer 1

Here's a better answer for a special probability distribution, the one Rex Logan's answer seems to be geared at. The distribution is like this: each object has an integer weight between 0 and 100, and its probability is in proportion to its weight. Since that's the currently accepted answer, I guess this is worth thinking about.

So keep an array of 101 bins. Each bin holds a list of all of the objects with its particular weight. Each bin also knows the total weight of all its objects.

To sample: pick a bin at random in proportion to its total weight. (Use one of the standard recipes for this -- linear or binary search.) Then pick an object from the bin uniformly at random.

To transfer an object: remove it from its bin, put it in its bin in the target, and update both bins' weights. (If you're using binary search for sampling, you must also update the running sums that uses. This is still reasonably fast since there aren't many bins.)