Moran Fixation Probability

Problem

In the Moran process with population size N, initial mutants and relative fitness r, the probability that the mutants take over is:

(1 - (1 / r)^initial) / (1 - (1 / r)^N)

for r different from 1, and initial / N for r = 1. Return 0.0 for invalid arguments.

Hint

Use the ratio 1 / r so beneficial mutants have r > 1.

case 1

in: [10,2,1]

expected: 0.5004887585532747

case 2

in: [10,1,1]

expected: 0.1

case 3

in: [10,2,5]

expected: 0.9696969696969697

case 4

in: [10,1,10]

expected: 1

case 5

in: [10,0.5,1]

expected: 0.0009775171065493646

Starter codePython

def moran_fixation_probability(population, fitness, initial):
    # Your code here
    pass

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