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Implemented basic functionality for using different target fitness types

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This commit is contained in:
SimpleArt
2020-10-21 14:11:43 -04:00
parent 9101072f26
commit 8e2698fc0d
5 changed files with 45 additions and 17 deletions
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12
src/parent_selection/parent_selection_methods.py
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@ -66,20 +66,20 @@ class Parent_Selection:
return
# Error if not all chromosomes has positive fitness
if (ga.population.get_chromosome(0).get_fitness() == 0 or ga.population.get_chromosome(-1).get_fitness() < 0):
if (ga.get_chromosome_fitness(0) == 0 or ga.get_chromosome_fitness(-1) < 0):
print("Error using roulette selection, all fitnesses must be positive.")
print("Consider using stockastic roulette selection or tournament selection.")
return
# The sum of all the fitnessess in a population
fitness_sum = sum(chromosome.get_fitness() for chromosome in ga.population.get_all_chromosomes())
fitness_sum = sum(ga.get_chromosome_fitness(index) for index in range(ga.population.size()))
# A list of ranges that represent the probability of a chromosome getting chosen
probability = [ga.selection_probability]
# The chance of being selected increases incrementally
for chromosome in ga.population.chromosome_list:
probability.append(probability[-1]+chromosome.fitness/fitness_sum)
for index in range(ga.population.size()):
probability.append(probability[-1]+ga.get_chromosome_fitness(index)/fitness_sum)
probability = probability[1:]
@ -111,7 +111,7 @@ class Parent_Selection:
print("Selection probability must be between 0 and 1 to select parents.")
return
max_fitness = ga.population.get_chromosome(0).get_fitness()
max_fitness = ga.get_chromosome_fitness(0)
# Error if the highest fitness is not positive
if max_fitness <= 0:
@ -126,5 +126,5 @@ class Parent_Selection:
index = random.randint(0, ga.population.size()-1)
# Probability of becoming a parent is fitness/max_fitness
if random.uniform(ga.selection_probability, 1) < ga.population.get_chromosome(index).get_fitness()/max_fitness:
if random.uniform(ga.selection_probability, 1) < ga.get_chromosome_fitness(index)/max_fitness:
ga.population.set_parent(index)