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Solution: Random Pick with Weight

Explore how to select a weighted random index from an array by creating running sums of weights and applying a binary search to find the appropriate index quickly. This lesson helps you understand both a naive linear search approach and an optimized binary search for efficient weighted random selection.

Statement

You’re given an array of positive integers, weights, where weights[i] is the weight of the ithi^{th} index.

Write a function, Pick Index(), which performs weighted random selection to return an index from the weights array. The larger the value of weights[i], the heavier the weight is, and the higher the chances of its index being picked.

Suppose that the array consists of the weights [12,84,35][12, 84, 35]. In this case, the probabilities of picking the indexes will be as follows:

  • Index 0: 12/(12+84+35)=9.2%12/(12 + 84 + 35) = 9.2\%

  • Index 1: 84/(12 ...