code: def shift_operator(
      x: FiniteDifferences, *, dx=[0.0], params=None
  ) -> FiniteDifferences:
      r"""Shifts the field by `dx` using finite differences.
  
      Args:
        x: The field to shift
        dx: The shift to apply. It is ignored if the `params` argument is not `None`.
  
      Returns:
        A new field corresponding to the shifted input field.
      """
      # Apply convolution
      kernels = params
      array = x.on_grid
  
      # Apply the corresponding kernel to each dimension
      outs = [
          reflection_conv(kernels[i], array[..., i], i)
          for i in range(x.domain.ndim)
      ]
      new_params = jnp.stack(outs, axis=-1)
  
      return x.replace_params(new_params)
  
imports: from typing import List
  import numpy
  from jax import numpy
  from jaxdf.conv import reflection_conv
  from jaxdf.core import operator
  from jaxdf.discretization import Continuous, FiniteDifferences, FourierSeries, OnGrid
  from jaxdf.operators.differential import get_fd_coefficients
label_desc: Use image node_id 12 for calling a global function with example usage: shift_operator(x) and returns: x