def PerformExperiment(cls, poolNumber=None):
''' Perform single experiment and save all possible results (album, gene pool of last population and summary with
best and average fitnesses (other parameters are optional)
:param poolNumber: int
Set, if you want to start your experiment not from the random beginning, but from the saved progress.
'''
# Set up environment
SetUpManager.SetUp()
# Load population if experiment doesn't start from the random beginning.
if poolNumber is not None:
EvolutonaryAlgorithm.LoadPopulation("data/genePools/pool" +
str(poolNumber) + ".txt")
# Perform experiment
EvolutonaryAlgorithm.Execute()
# Create album
album = AlbumWriter.AlbumFromAlgorithm(EvolutonaryAlgorithm)
# Save results
cls.SaveAlbum(album)
cls.SaveGenePool()
cls.AddSummaryToRegistry()
# Increment counter (next experiment will have another number)
cls.numberOfExperiment += 1
def SaveGenePool(cls):
''' Save genes of all individuals from the last population.
'''
EvolutonaryAlgorithm.SavePopulation(PathsManager.mainPath +
"Scripts/Data/genePools/pool" +
str(cls.numberOfExperiment) +
".txt")
def PerformExperiment(cls, poolNumber=None):
# Set up environment
SetUpManager.SetUp()
# Load population if experiment doesn't start from the random beginning.
if poolNumber is not None:
EvolutonaryAlgorithm.LoadPopulation("data/genePools/pool" +
str(poolNumber) + ".txt")
# Perform experiment
EvolutonaryAlgorithm.Execute()
# Create album
album = AlbumWriter.AlbumFromAlgorithm(EvolutonaryAlgorithm)
# Save results
cls.SaveAlbum(album)
cls.SaveGenePool()
cls.AddSummaryToRegistry()
# Increment counter (next experiment will have another number)
cls.numberOfExperiment += 1
def SetUpEvolutonaryAlgorithm(cls):
cls.ExecuteIfHasNotBeenYet(SetUpManager.SetUpPattern)
creator.create("FitnessMax", base.Fitness, weights=(1.0, ))
EvolutonaryAlgorithm.lverbose = True
# INDIVIDUALS
EvolutonaryAlgorithm.geneRandomizingFunction = Pattern.RandomWage
EvolutonaryAlgorithm.lengthOfIndividual = Pattern.length
#LAWS
EvolutonaryAlgorithm.probabilityOfCrossing = SETTINGS.GENETICS.CROSSING.PROBABILITY
EvolutonaryAlgorithm.crossingMethod = SETTINGS.GENETICS.CROSSING.METHOD
EvolutonaryAlgorithm.crossingParameters = {}
EvolutonaryAlgorithm.probabilityOfMutation = SETTINGS.GENETICS.MUTATION.PROBABILITY
EvolutonaryAlgorithm.mutationMethod = SETTINGS.GENETICS.MUTATION.METHOD
EvolutonaryAlgorithm.mutationParameters = {}
EvolutonaryAlgorithm.mutationParameters[
'mu'] = SETTINGS.GENETICS.MUTATION.GAUSSIAN.MEAN_OF_THE_DISTRIBUTION
EvolutonaryAlgorithm.mutationParameters[
'sigma'] = SETTINGS.GENETICS.MUTATION.GAUSSIAN.STD_DEVIATION_OF_THE_DISTRIBUTION
EvolutonaryAlgorithm.mutationParameters[
'indpb'] = SETTINGS.GENETICS.MUTATION.PROBABILITY_OF_ATTRIBUTE_MUTATION
EvolutonaryAlgorithm.selectionMethod = SETTINGS.GENETICS.SELECTION.METHOD
EvolutonaryAlgorithm.selectionParameters = {}
EvolutonaryAlgorithm.selectionParameters[
'tournsize'] = SETTINGS.GENETICS.SELECTION.TOURNAMENT.SIZE
#MAKRO
EvolutonaryAlgorithm.paramMu = SETTINGS.GENETICS.SIZE_OF_POPULATION_AFTER_SELECTION
EvolutonaryAlgorithm.paramLambda = SETTINGS.GENETICS.SIZE_OF_POPULATION_BEFORE_SELECTION
EvolutonaryAlgorithm.numberOfGenerations = SETTINGS.GENETICS.NUMBER_OF_GENERATIONS
#STATISTICS
EvolutonaryAlgorithm.dictWithStatistics = {}
EvolutonaryAlgorithm.dictWithStatistics[
'min'] = SETTINGS.GENETICS.STATISTICS.MIN
EvolutonaryAlgorithm.dictWithStatistics[
'max'] = SETTINGS.GENETICS.STATISTICS.MAX
EvolutonaryAlgorithm.dictWithStatistics[
'avg'] = SETTINGS.GENETICS.STATISTICS.AVERAGE
#GENERAL
EvolutonaryAlgorithm.Prepare()
from Modules.AI.Genetics.genetics import AlbumWriter, EvolutonaryAlgorithm
from Modules.GUI.displayer import Displayer
from Modules.Simulation.map import Map
from Modules.General.general_tools import PathsManager
from Modules.Settings.set_up_manager import SetUpManager
from Modules.Settings.settings import SETTINGS
#SETUP
SetUpManager.SetUp()
EvolutonaryAlgorithm.Execute()
amap = Map()
amap.LoadFromFile(PathsManager.GetPath("map"))
adisplayer = Displayer
adisplayer.map = amap
albumWriter = AlbumWriter()
album = albumWriter.AlbumFromAlgorithm(EvolutonaryAlgorithm)
adisplayer.PlayAlbum(album)
def SaveGenePool(cls):
EvolutonaryAlgorithm.SavePopulation(PathsManager.mainPath +
"Scripts/Data/genePools/pool" +
str(cls.numberOfExperiment) +
".txt")
from Modules.AI.Genetics.genetics import EvolutonaryAlgorithm
from Modules.Settings.set_up_manager import SetUpManager
import unittest
def EvaluatePattern(gaPattern):
return sum(gaPattern),
# #SETUP
SetUpManager.SetUp()
EvolutonaryAlgorithm.Prepare()
EvolutonaryAlgorithm.toolbox.register("evaluate", EvaluatePattern)
EvolutonaryAlgorithm.Execute()
class TestPatternBreeder(unittest.TestCase):
def test_effect(self):
self.assertTrue(max(EvolutonaryAlgorithm.logbook.select("max")) > 15)
self.assertTrue(max(EvolutonaryAlgorithm.logbook.select("avg")) > 15)
if __name__ == '__main__':
unittest.main()