Inverse Transform Discrete Counts

Problem

Generate n samples from a discrete distribution by inverse transform with random.Random(seed). For each uniform u, return the first index whose cumulative probability exceeds u, and count the results. Return [] for an empty distribution or n <= 0.

Hint

Walk the cumulative distribution and pick the first crossing index.

Test cases

case 1

in: [[0.5,0.5],1000,42]

expected: [480,520]

case 2

in: [[0.3333333333333333,0.3333333333333333,0.3333333333333333],600,7]

expected: [218,190,192]

case 3

in: [[1],50,1]

expected: [50]

case 4

in: [[],5,0]

expected: []

Starter codePython

import random


def inverse_transform_discrete(probs, n, seed):
    # Your code here
    pass

4 test cases · run your code against them in the editor