code: def derivative(x: Continuous, *, axis=0, params=None) -> Continuous:
      r"""Derivative operator for continuous fields.
  
      Args:
        x: Continuous field
        axis: Axis along which to take the derivative
  
      Returns:
        Continuous field
      """
      get_x = x.get_fun
  
      def grad_fun(p, coords):
          f_jac = jax.jacfwd(get_x, argnums=(1,))
          return jnp.expand_dims(f_jac(p, coords)[0][0][axis], -1)
  
      return Continuous(x.params, x.domain, grad_fun)
  
imports: from typing import Union
  import jax
  import numpy
  from jax import numpy
  from jaxdf.conv import fd_coefficients_fornberg, reflection_conv
  from jaxdf.core import operator
  from jaxdf.discretization import Continuous, FiniteDifferences, FourierSeries
label_desc: Use image node_id 2 for calling a global function with example usage: derivative(x) and returns: Continuous, jnp