code: def laplace(image, ksize=3, mask=None):
      """Find the edges of an image using the Laplace operator.
  
      Parameters
      ----------
      image : ndarray
          Image to process.
      ksize : int, optional
          Define the size of the discrete Laplacian operator such that it
          will have a size of (ksize,) * image.ndim.
      mask : ndarray, optional
          An optional mask to limit the application to a certain area.
          Note that pixels surrounding masked regions are also masked to
          prevent masked regions from affecting the result.
  
      Returns
      -------
      output : ndarray
          The Laplace edge map.
  
      Notes
      -----
      The Laplacian operator is generated using the function
      skimage.restoration.uft.laplacian().
  
      """
      if image.dtype.kind == "f":
          float_dtype = _supported_float_type(image.dtype)
          image = image.astype(float_dtype, copy=False)
      else:
          image = img_as_float(image)
      # Create the discrete Laplacian operator - We keep only the real part of
      # the filter
      _, laplace_op = laplacian(image.ndim, (ksize,) * image.ndim)
      result = convolve(image, laplace_op)
      return _mask_filter_result(result, mask)
  
imports: import numpy
  from scipy import ndimage
  from scipy.ndimage import binary_erosion, convolve
  from .._shared.utils import _supported_float_type, check_nD
  from ..restoration.uft import laplacian
  from ..util.dtype import img_as_float
label_desc: Use image node_id 17 for calling a global function with example usage: laplace(image, ksize, mask) and returns: _mask_filter_result