code: def laplacian(x: Continuous, *, params=None) -> Continuous:
      r"""Laplacian operator for continuous fields.
  
      Args:
        x: Continuous field
  
      Returns:
        The Laplacian of the field
      """
      get_x = x.get_fun
  
      def grad_fun(p, coords):
          hessian = jax.hessian(get_x, argnums=(1,))(p, coords)[0][0][0]
          return jnp.diag(hessian)
  
      return x.update_fun_and_params(x.params, 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 15 for calling a global function with example usage: laplacian(x) and returns: x, jnp