Personalized PageRank Normalize

Problem

Normalize a Personalized PageRank vector so its entries sum to 1.

Divide every entry by the total sum. If the sum is 0, return a list of zeros of the same length. ranks is the raw rank list.

Hint

Dividing by the sum makes the vector a probability distribution again.

case 1

in: [[1,1,2]]

expected: [0.25,0.25,0.5]

case 2

in: [[0,0,0]]

expected: [0,0,0]

case 3

in: [[2.5,2.5]]

expected: [0.5,0.5]

case 4

in: [[3]]

expected: [1]

Starter codePython

def normalize_ppr(ranks):
    # Your code here
    pass

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