code: def inverse_jacobian(self, maps):
          r
          x = maps[self._outputvar]
          expx = numpy.exp(x)
          return expx * (self._b - self._a) / (1. + expx)**2.
docs: r"""Computes the Jacobian of :math:`y = \mathrm{logistic}(x; a,b)`.
  
          This is:
  
          .. math::
  
              \frac{\mathrm{d}y}{\mathrm{d}x} = \frac{e^x (b-a)}{(1+e^y)^2},
  
          where :math:`y \in (a, b)`.
  
          Parameters
          ----------
          maps : dict or FieldArray
              A dictionary or FieldArray which provides a map between the
              parameter name of the variable to transform and its value(s).
  
          Returns
          -------
          float
              The value of the jacobian at the given point(s).