code: def get_j_ty_callback(self):
          
          j_exprs = self.get_jac()
          if j_exprs is False:
              return None
          cb = self._callback_factory(j_exprs)
          if self.sparse:
              from scipy.sparse import csc_matrix
  
              def sparse_cb(x, y, p=()):
                  data = cb(x, y, p).flatten()
                  return csc_matrix((data, self._rowvals, self._colptrs))
  
              return sparse_cb
          else:
              return cb
docs: Generates a callback for evaluating the jacobian.