code: def scharr_v(image, mask=None):
      """Find the vertical edges of an image using the Scharr transform.
  
      Parameters
      ----------
      image : 2-D array
          Image to process
      mask : 2-D array, 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 : 2-D array
          The Scharr edge map.
  
      Notes
      -----
      We use the following kernel::
  
         3   0   -3
        10   0  -10
         3   0   -3
  
      References
      ----------
      .. [1] D. Kroon, 2009, Short Paper University Twente, Numerical
             Optimization of Kernel Based Image Derivatives.
      """
      check_nD(image, 2)
      return scharr(image, mask=mask, axis=1)
  
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 10 for calling a global function with example usage: scharr_v(image, mask) and returns: scharr