def calc_fitness_candidates(candidates, args):
"""Requires the candidates to be in chromosome representation.
See chromgen for details.
"""
chromosomes = candidates
channels_list = []
for chromosome in chromosomes:
channels = chromgen.chromosome_to_channels(chromosome)
channels_list.append(channels)
return [x["fitness"] for x in evaluate_channels(channels_list, args)]
def start(pconf):
global logger
logger = pconf.get_logger("evolution")
# logger.info(Currents)
rand = Random()
rand.seed(int(time()))
t = strftime("%d.%m.%Y-%H:%M:%S")
EC = inspyred.ec.EvolutionaryComputation(rand)
# EC.analysis = inspyred.ec.analysis.generation_plot
mode = pconf.get("mode", "Simulation")
l_bound, u_bound = chromgen.get_bounds(mode)
# braucht statistics_file und individuals_file für analysis
EC.observer = inspyred.ec.observers.file_observer
statistics_file = open(pconf.local_path("inspyred-statistics-{0}.csv".format(strftime("%m%d-%H%M"))), "w")
individuals_file = open(pconf.local_path("inspyred-individuals-{0}.csv".format(strftime("%m%d-%H%M"))), "w")
filename = pconf.local_path("inspyred-inspyred-statistics-{0}.csv".format(strftime("%m%d-%H%M")))
parsed_kwargs = {
"statistics_file": statistics_file,
"individuals_file": individuals_file,
"filename": filename,
"proj_name": pconf.parse_project_data()["proj_name"],
"errorbars": False,
"logger": pconf.get_logger("EC.inspyred"),
"lower_bound": l_bound,
"upper_bound": u_bound,
"pconf": pconf,
"mode": mode,
}
# Parse general evolve parameters.
for item in pconf.cfg.items("EvolveParameters"):
parsed_kwargs[item[0]] = eval(item[1])
# Load selector, variators, replacer and terminators from the config file.
selector_section = pconf.get("selector", "Simulation")
logger.debug("Parsing selector: " + selector_section)
EC.selector, parsed_kwargs = parse_callable(pconf, logger, selector_section, parsed_kwargs)
variator_section_list = pconf.get_list("variators", "Simulation")
logger.debug("Parsing variators: " + repr(variator_section_list))
EC.variator, parsed_kwargs = parse_callable(pconf, logger, variator_section_list, parsed_kwargs)
replacer_section = pconf.get("replacer", "Simulation")
logger.debug("Parsing replacer: " + replacer_section)
EC.replacer, parsed_kwargs = parse_callable(pconf, logger, replacer_section, parsed_kwargs)
terminator_section_list = pconf.get_list("terminators", "Simulation")
logger.debug("Parsing terminators: " + repr(terminator_section_list))
EC.terminator, parsed_kwargs = parse_callable(pconf, logger, terminator_section_list, parsed_kwargs)
evaluator_section = pconf.get("evaluator", "Simulation")
logger.debug("Parsing evaluator: " + evaluator_section)
evaluator, parsed_kwargs = parse_callable(pconf, logger, evaluator_section, parsed_kwargs)
generator_section = pconf.get("generator", "Simulation")
logger.debug("Parsing generator: " + generator_section)
generator, parsed_kwargs = parse_callable(pconf, logger, generator_section, parsed_kwargs)
logger.debug("Arguments accumulated for evolve: " + repr(parsed_kwargs))
final_pop = EC.evolve(generator=generator, evaluator=evaluator, **parsed_kwargs)
final_pop.sort(reverse=True)
logger.info("=================================")
logger.info("The best candidate has a fitness value of " + repr(final_pop[0].fitness))
# schreibt Ergebnisse in Datei zur späteren Auswertung!
with open(pconf.get_local_path("resultDensityFile"), "a") as d:
for item in final_pop:
d.write("# fitness: " + repr(item.fitness) + "\n")
channels = chromgen.chromosome_to_channels(item.candidate)
for v in channels:
d.write(str(v) + "\n")
d.write("\n")
d.write("####\n\n")
logger.info(
"Die Eigenschaften der letzten Generation"
+ " kann in '"
+ pconf.get("resultDensityFile")
+ "' gefunden werden."
)
