def random_rescaling_factor_to_mahalanobis_size(self, y):
        """``self.mean + self.random_rescaling_factor_to_mahalanobis_size(y)``
        is guarantied to appear like from the sample distribution.
        """
        if len(y) != self.N:
            raise ValueError('len(y)=%d != %d=dimension' % (len(y), self.N))
        if not any(y):
            _print_warning("input was all-zeros, which is probably a bug",
                           "random_rescaling_factor_to_mahalanobis_size",
                           iteration=self.countiter)
            return 1.0
        return sum(self.randn(len(y))**2)**0.5 / self.mahalanobis_norm(y)
``self.mean + self.random_rescaling_factor_to_mahalanobis_size(y)``
        is guarantied to appear like from the sample distribution.