cmaes.py 文件源码

def is_behavior_learning_done(self):
        """Check if the optimization is finished.

        Returns
        -------
        finished : bool
            Is the learning of a behavior finished?
        """
        if self.it <= self.n_samples_per_update:
            return False

        if not np.all(np.isfinite(self.fitness)):
            return True

        # Check for invalid values
        if not (np.all(np.isfinite(self.invsqrtC)) and
                np.all(np.isfinite(self.cov)) and
                np.all(np.isfinite(self.mean)) and
                np.isfinite(self.var)):
            self.logger.info("Stopping: infs or nans" % self.var)
            return True

        if (self.min_variance is not None and
                np.max(np.diag(self.cov)) * self.var <= self.min_variance):
            self.logger.info("Stopping: %g < min_variance" % self.var)
            return True

        max_dist = np.max(pdist(self.fitness[:, np.newaxis]))
        if max_dist < self.min_fitness_dist:
            self.logger.info("Stopping: %g < min_fitness_dist" % max_dist)
            return True

        cov_diag = np.diag(self.cov)
        if (self.max_condition is not None and
                np.max(cov_diag) > self.max_condition * np.min(cov_diag)):
            self.logger.info("Stopping: %g / %g > max_condition"
                             % (np.max(self.cov), np.min(self.cov)))
            return True

        return False