Experiment.py 文件源码

def get_arg_best(self):
        best_idx = -1
        best_value = sys.maxint
        for i, trial in enumerate(self.trials):
            tmp_res = np.NaN
            if np.isfinite(trial['result']):
                tmp_res = trial['result']
            elif np.isfinite(trial['instance_results']).any():
                tmp_res = wrapping_util.nan_mean(trial['instance_results'])
                # np.nanmean is not available in older numpy versions
                # tmp_res = scipy.nanmean(trial['instance_results'])
            else:
                continue
            if tmp_res < best_value:
                best_idx = i
                best_value = tmp_res
        if best_idx == -1:
            raise ValueError("No best value found.")
        return best_idx

    # Get the best value so far, for more documentation see get_arg_best