def average_results(self):
        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 = scipy.optimize.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])
            newres.nsuccess = len([r for r in result_list if r.success])
            try:
                newres.ndim = len(result_list[0].x)
            except TypeError:
                newres.ndim = 1
            averaged_results[name] = newres
        return averaged_results

    # for basinhopping
Argument of the Meijer G-function.
dataset/ETHPy150Open scipy/scipy/benchmarks/benchmarks/optimize.py/_BenchOptimizers.average_results--crossover with--dataset/ETHPy150Open sympy/sympy/sympy/functions/special/hyper.py/meijerg.argument