I am working on a genetic algorithm, and I found a code that works, and now I am trying to understand, but I saw this return statement:
return sum(1 for expected, actual in zip(target, guess)
if expected == actual)
What does it do?
Here is the full code:
main.py:
from population import *
while True:
child = mutate(bestParent)
childFitness = get_fitness(child)
if bestFitness >= childFitness:
continue
print(child)
if childFitness >= len(bestParent):
break
bestFitness = childFitness
bestParent = child
population.py:
import random
geneSet = " abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!.,1234567890-_=+!@#$%^&*():'[]\""
target = input()
def generate_parent(length):
genes = []
while len(genes) < length:
sampleSize = min(length - len(genes), len(geneSet))
genes.extend(random.sample(geneSet, sampleSize))
parent = ""
for i in genes:
parent += i
return parent
def get_fitness(guess):
return sum(1 for expected, actual in zip(target, guess)
if expected == actual)
def mutate(parent):
index = random.randrange(0, len(parent))
childGenes = list(parent)
newGene, alternate = random.sample(geneSet, 2)
childGenes[index] = alternate \
if newGene == childGenes[index] \
else newGene
child = ""
for i in childGenes:
child += i
return child
def display(guess):
timeDiff = datetime.datetime.now() - startTime
fitness = get_fitness(guess)
print(str(guess) + "\t" + str(fitness) + "\t" + str(timeDiff))
random.seed()
bestParent = generate_parent(len(target))
bestFitness = get_fitness(bestParent)
print(bestParent)
This is the full code of an working genetic algorithm. I modified some parts to make it more readable for me.
The return statement is in the population.py file, in the get_fitness function.