code: def _mask_cov_func(self, *args):
          
          # Have to do it in two cases to get the 1d unwrapped properly:
          if self.num_dim == 1:
              return self.cov_func(args[0], args[1], *self.params)
          else:
              return self.cov_func(args[:self.num_dim], args[self.num_dim:], *self.params)
docs: Masks the covariance function into a form usable by :py:func:`mpmath.diff`.
          
          Parameters
          ----------
          *args : `num_dim` * 2 floats
              The individual elements of Xi and Xj to be passed to :py:attr:`cov_func`.