def statistics(cls, function, group=None):
        """
        Compute statistics (average, max, median, minimun and sum) from _results
        into a dictionary of numpy array.
        """
        benchmark = cls.results(function, group)
        results = {}
        for name, stat in {'avg': numpy.average, 'max': numpy.amax, 'med': numpy.median, 'min': numpy.amin, 'sum': numpy.sum}.items():
            results[name] = stat(benchmark, axis=0)
        return results
def statistics ( cls , function , group = None ) : benchmark = cls . results ( function , group ) results = { } for name , stat in { 'avg' : numpy . average , 'max' : numpy . amax , 'med' : numpy . median , 'min' : numpy . amin , 'sum' : numpy . sum } . items ( ) : results [ name ] = stat ( benchmark , axis = 0 ) return results
Compute statistics (average, max, median, minimun and sum) from _results
        into a dictionary of numpy array.