optimizer.py 文件源码

def assign_fitnesses(self, targets):
        self._params['evals'] = len(targets)
        px_parameters = zip([self._params['specification']] * len(targets),
                            [self._params['sequence']] * len(targets),
                            [self.parse_individual(x) for x in targets])
        if (self._params['processors'] == 1) or (sys.platform == 'win32'):
            fitnesses = map(self.evaluation_function, px_parameters)
        else:
            with futures.ProcessPoolExecutor(
                    max_workers=self._params['processors']) as executor:
                fitnesses = executor.map(
                    self.evaluation_function, px_parameters)
        tars_fits = list(zip(targets, fitnesses))
        if 'log_params' in self._params:
            if self._params['log_params']:
                self.parameter_log.append(
                    [(self.parse_individual(x[0]), x[1]) for x in tars_fits])
        for ind, fit in tars_fits:
            ind.fitness.values = (fit,)