code: def gradient(
      x: FiniteDifferences, *, stagger=[0], params=None
  ) -> FiniteDifferences:
      r"""Gradient operator for finite differences fields.
  
      Args:
        x: FiniteDifferences field
        stagger: Stagger of the derivative
  
      Returns:
        The gradient of the field
      """
      return diag_jacobian(x, stagger=stagger, params=params)
  
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 8 for calling a global function with example usage: gradient(x) and returns: diag_jacobian