paulin/EasyGA
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Cleaned up comments.

Browse Source
This commit is contained in:
SimpleArt
2020-11-27 20:03:43 -05:00
parent cbd0265cd8
commit 65a35e71dc
1 changed files with 14 additions and 11 deletions
Download Patch File Download Diff File Expand all files Collapse all files

25
src/EasyGA.py
View File

@ -98,6 +98,9 @@ class GA(Attributes):
def adapt(self): def adapt(self):
"""Modifies the parent ratio and mutation rates """Modifies the parent ratio and mutation rates
based on the adapt rate and percent converged. based on the adapt rate and percent converged.
Attempts to balance out so that 25% of the desired
percent converged (50%*25% = 12.5% default)
is the amount converged at all times.
""" """
# Don't adapt # Don't adapt
@ -125,30 +128,30 @@ class GA(Attributes):
threshhold_fitness = self.population[round(self.percent_converged*len(self.population)/8)].fitness threshhold_fitness = self.population[round(self.percent_converged*len(self.population)/8)].fitness
# Way too few converged # Way too few converged, adapt twice as fast
if abs(best_fitness - threshhold_fitness) > tol: if abs(best_fitness - threshhold_fitness) > tol:
multiplier **= 2 multiplier **= 2
limit = max_val / multiplier limit = max_val / multiplier
self.parent_ratio = min(max_val, self.parent_ratio*multiplier) self.parent_ratio = min(max_val, self.parent_ratio * multiplier)
self.selection_probability = min(max_val, self.selection_probability*multiplier) self.selection_probability = min(max_val, self.selection_probability * multiplier)
self.chromosome_mutation_rate = max(min_val, self.chromosome_mutation_rate/multiplier) self.chromosome_mutation_rate = max(min_val, self.chromosome_mutation_rate / multiplier)
self.gene_mutation_rate = max(min_val, self.gene_mutation_rate/multiplier) self.gene_mutation_rate = max(min_val, self.gene_mutation_rate / multiplier)
# Too many converged: cross less and mutate more # Too many converged: cross less and mutate more
else: else:
threshhold_fitness = self.population[round(self.percent_converged*len(self.population)/2)].fitness threshhold_fitness = self.population[round(self.percent_converged*len(self.population)*3/8)].fitness
# Way too many converged # Way too many converged, adapt twice as fast
if abs(best_fitness - threshhold_fitness) < tol: if abs(best_fitness - threshhold_fitness) < tol:
multiplier **= 2 multiplier **= 2
limit = max_val / multiplier limit = max_val / multiplier
self.parent_ratio = max(min_val, self.parent_ratio/multiplier) self.parent_ratio = max(min_val, self.parent_ratio / multiplier)
self.selection_probability = max(min_val, self.selection_probability/multiplier) self.selection_probability = max(min_val, self.selection_probability / multiplier)
self.chromosome_mutation_rate = min(max_val, self.chromosome_mutation_rate*multiplier) self.chromosome_mutation_rate = min(max_val, self.chromosome_mutation_rate * multiplier)
self.gene_mutation_rate = min(max_val, self.gene_mutation_rate*multiplier) self.gene_mutation_rate = min(max_val, self.gene_mutation_rate * multiplier)