Python PyHyperNEAT.getMaximumGenerations示例

示例#1

# Move to experiment directory.
print "Moving to experiment run directory '%s'..." % experiment_run_dir
os.chdir(experiment_run_dir)

# Initialize HyperNEAT.
print "Initializing HyperNEAT..."
neat.initializeHyperNEAT()

# Load experiment.
print "Running HyperNEAT experiment '%s'..." % experiment_name
experimentRun = neat.setupExperiment(
    "%s/%sExperiment.dat" % (experiment_data_dir, experiment_name),
    "%s.xml" % output_name)

maxgen = neat.getMaximumGenerations()

for x in range(maxgen):

    if (x > 0):
        experimentRun.produceNextGeneration()

    #population pre-process, in experiment running
    experimentRun.preprocessPopulation()

    #vector = neat.GeneticIndividualVector()

    #evaluation run subclass from experiment run
    geneticIndividuals = experimentRun.pythonEvaluationSet()

    for generation in xrange(geneticIndividuals.getIndividualCount()):

示例#2

文件： experiment.py 项目： anthonytw/neat-deform

# Experiment prefix.
prefix = datetime.now().strftime("%y%m%d_%H%M%S")

# Move to experiment directory.
print "Moving to experiment run directory '%s'..." % experiment_run_dir
os.chdir( experiment_run_dir )

# Initialize HyperNEAT.
print "Initializing HyperNEAT..."
neat.initializeHyperNEAT()

# Load experiment.
print "Running HyperNEAT experiment '%s'..." % experiment_name
experimentRun = neat.setupExperiment( "%s/%sExperiment.dat" % (experiment_data_dir, experiment_name), "%s.xml" % output_name )

maxgen = neat.getMaximumGenerations()

for x in range(maxgen):

    if(x > 0):
        experimentRun.produceNextGeneration()

    #population pre-process, in experiment running
    experimentRun.preprocessPopulation()

    #vector = neat.GeneticIndividualVector()

    #evaluation run subclass from experiment run
    geneticIndividuals = experimentRun.pythonEvaluationSet()

    for generation in xrange(geneticIndividuals.getIndividualCount()):