code: def _njacobian(self):
          
          return [
              [sympy_to_py(
                      sympy.diff(expr, var), self.independent_vars + self.dependent_vars + self.params
                  ) for var in self.dependent_vars
              ] for _, expr in self.items()
          ]
docs: :return: The `numerical_jacobian` of the components of the ODEModel with
              regards to the dependent variables. This is not to be confused with
              the jacobian of the model as a whole, which is 2D and computed with
              regards to the dependent vars and the fit parameters, and the
              ODEModel still needs to integrated to compute that.
  
              Instead, this function is used by the ODE integrator, and is not
              meant for human consumption.