本文整理汇总了Python中scipy.optimize.OptimizeResult.mean_nhev方法的典型用法代码示例。如果您正苦于以下问题：Python OptimizeResult.mean_nhev方法的具体用法？Python OptimizeResult.mean_nhev怎么用？Python OptimizeResult.mean_nhev使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类scipy.optimize.OptimizeResult的用法示例。
在下文中一共展示了OptimizeResult.mean_nhev方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: average_results
# 需要导入模块: from scipy.optimize import OptimizeResult [as 别名]
# 或者: from scipy.optimize.OptimizeResult import mean_nhev [as 别名]
def average_results(self):
"""
group the results by minimizer and average over the runs
"""
grouped_results = defaultdict(list)
for res in self.results:
grouped_results[res.name].append(res)
averaged_results = dict()
for name, result_list in grouped_results.items():
newres = OptimizeResult()
newres.name = name
newres.mean_nfev = np.mean([r.nfev for r in result_list])
newres.mean_njev = np.mean([r.njev for r in result_list])
newres.mean_nhev = np.mean([r.nhev for r in result_list])
newres.mean_time = np.mean([r.time for r in result_list])
newres.ntrials = len(result_list)
newres.nfail = len([r for r in result_list if not r.success])
try:
newres.ndim = len(result_list[0].x)
except TypeError:
newres.ndim = 1
averaged_results[name] = newres
return averaged_results.values()