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Added function decorators

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This commit is contained in:
SimpleArt
2020-11-19 21:28:16 -05:00
parent 0bd08b94a9
commit 652e4a4b5b
1 changed files with 33 additions and 36 deletions
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69
src/parent_selection/parent_selection_methods.py
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@ -2,8 +2,35 @@ import random
class Parent_Selection:
def __check_selection_probability(selection_method):
def helper(ga):
if 0 < ga.selection_probability < 1:
selection_method(ga)
else:
raise Exception("Selection probability must be greater than 0 to select parents.")
return helper
def __check_positive_fitness(selection_method):
def helper(ga):
if ga.get_chromosome_fitness(0) == 0 or ga.get_chromosome_fitness(-1) < 0:
raise Exception("Converted fitness values must be all positive. Consider using rank selection instead.")
else:
selection_method(ga)
return helper
def __ensure_sorted(selection_method):
def helper(ga):
ga.population.sort_by_best_fitness(ga)
selection_method(ga)
return helper
class Rank:
@Parent_Selection._Parent_Selection__check_selection_probability
@Parent_Selection._Parent_Selection__ensure_sorted
def tournament(ga):
"""
Will make tournaments of size tournament_size and choose the winner (best fitness)
@ -11,14 +38,6 @@ class Parent_Selection:
of parents selected is determined by parent_ratio, an attribute to the GA object.
"""
# Error if can't select parents
if ga.selection_probability <= 0:
print("Selection probability must be greater than 0 to select parents.")
return
# Make sure the population is sorted by fitness
ga.population.sort_by_best_fitness(ga)
# Choose the tournament size.
# Use no less than 5 chromosomes per tournament.
tournament_size = int(len(ga.population)*ga.tournament_size_ratio)
@ -49,6 +68,9 @@ class Parent_Selection:
class Fitness:
@Parent_Selection._Parent_Selection__check_selection_probability
@Parent_Selection._Parent_Selection__check_positive_fitness
@Parent_Selection._Parent_Selection__ensure_sorted
def roulette(ga):
"""Roulette selection works based off of how strong the fitness is of the
chromosomes in the population. The stronger the fitness the higher the probability
@ -58,20 +80,6 @@ class Parent_Selection:
the ball falls is a randomly generated number between 0 and 1.
"""
# Make sure the population is sorted by fitness
ga.population.sort_by_best_fitness(ga)
# Error if can't select parents
if ga.selection_probability <= 0:
print("Selection probability must be greater than 0 to select parents.")
return
# Error if not all chromosomes has positive fitness
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(ga.get_chromosome_fitness(index) for index in range(len(ga.population)))
@ -97,6 +105,9 @@ class Parent_Selection:
break
@Parent_Selection._Parent_Selection__check_selection_probability
@Parent_Selection._Parent_Selection__check_positive_fitness
@Parent_Selection._Parent_Selection__ensure_sorted
def stochastic(ga):
"""Stochastic roulette selection works based off of how strong the fitness is of the
chromosomes in the population. The stronger the fitness the higher the probability
@ -104,22 +115,8 @@ class Parent_Selection:
and incrementally increasing the chance something is selected, the stochastic method
just divides by the highest fitness and selects randomly."""
# Make sure the population is sorted by fitness
ga.population.sort_by_best_fitness(ga)
# Error if can't select parents
if ga.selection_probability <= 0 or ga.selection_probability >= 1:
print("Selection probability must be between 0 and 1 to select parents.")
return
max_fitness = ga.get_chromosome_fitness(0)
# Error if the highest fitness is not positive
if max_fitness <= 0:
print("Error using stochastic roulette selection, best fitness must be positive.")
print("Consider using tournament selection.")
return
# Loops until it reaches a desired mating pool size
while (len(ga.population.get_mating_pool()) < len(ga.population)*ga.parent_ratio):