Entropy of a Geometric Distribution

Problem

Compute the entropy in bits of a geometric distribution on {1, 2, 3, ...} with success probability p:

H = (-(1 - p) * log2(1 - p) - p * log2(p)) / p

Return 0.0 when p = 1.

Hint

For p = 1/2 the numerator is 1, so H = 1 / p = 2 bits.

case 1

in: [0.5]

expected: 2

case 2

in: [0.25]

expected: 3.2451124978365313

case 3

in: [0.1]

expected: 4.689955935892812

case 4

in: [1]

expected: 0

Starter codePython

import math
def geometric_entropy(p):
    # Your code here
    pass

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