Fast arbitrary distribution random sampling (inverse transform sampling)

Question

The random module (http://docs.python.org/2/library/random.html) has several fixed functions to randomly sample from. For example random.gauss

Answer 1

You need to use Inverse transform sampling method to get random values distributed according to a law you want. Using this method you can just apply inverted function to random numbers having standard uniform distribution in the interval [0,1].

After you find the inverted function, you get 1000 numbers distributed according to the needed distribution this obvious way:

[inverted_function(random.random()) for x in range(1000)]

More on Inverse Transform Sampling:

• http://en.wikipedia.org/wiki/Inverse_transform_sampling

Also, there is a good question on StackOverflow related to the topic:

• Pythonic way to select list elements with different probability