code: def get_warped_stacked_image(image, nslices, b, m):
      r"""Creates a volume by stacking copies of a deformed image
  
      The image is deformed under an invertible field, and a 3D volume is
      generated as follows:
      the first and last `nslices`//3 slices are filled with zeros
      to simulate background. The remaining middle slices are filled with
      copies of the deformed `image` under the action of the invertible
      field.
  
      Parameters
      ----------
      image : 2d array shape(r, c)
          the image to be deformed
      nslices : int
          the number of slices in the final volume
      b, m : float
          parameters of the harmonic field (as in [1]).
  
      Returns
      -------
      vol : array shape(r, c) if `nslices`==1 else (r, c, `nslices`)
          the volumed generated using the undeformed image
      wvol : array shape(r, c) if `nslices`==1 else (r, c, `nslices`)
          the volumed generated using the warped image
  
      References
      ----------
      [1] Chen, M., Lu, W., Chen, Q., Ruchala, K. J., & Olivera, G. H. (2008).
          A simple fixed-point approach to invert a deformation field.
          Medical Physics, 35(1), 81. doi:10.1118/1.2816107
      """
      shape = image.shape
      # create a synthetic invertible map and warp the circle
      d, dinv = vfu.create_harmonic_fields_2d(shape[0], shape[1], b, m)
      d = np.asarray(d, dtype=floating)
      dinv = np.asarray(dinv, dtype=floating)
      mapping = DiffeomorphicMap(2, shape)
      mapping.forward, mapping.backward = d, dinv
      wimage = mapping.transform(image)
  
      if nslices == 1:
          return image, wimage
  
      # normalize and form the 3d by piling slices
      image = image.astype(floating)
      image = (image - image.min()) / (image.max() - image.min())
      zero_slices = nslices // 3
      vol = np.zeros(shape=image.shape + (nslices,))
      vol[..., zero_slices : (2 * zero_slices)] = image[..., None]
      wvol = np.zeros(shape=image.shape + (nslices,))
      wvol[..., zero_slices : (2 * zero_slices)] = wimage[..., None]
  
      return vol, wvol
  
imports: import numpy
  import nibabel.eulerangles
  from numpy.testing import assert_equal, assert_array_equal, assert_array_almost_equal, assert_raises
  from dipy.core.interpolation import interpolate_scalar_2d, interpolate_scalar_3d
  from dipy.data import get_fnames
  from dipy.align import floating
  from dipy.align import imwarp
  from dipy.align import metrics
  from dipy.align import vector_fields
  from dipy.align import VerbosityLevels
  from dipy.align.imwarp import DiffeomorphicMap
  from dipy.tracking.streamline import deform_streamlines
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 10 for calling a global function with example usage: get_warped_stacked_image(image, nslices, b, m) and returns: vol,  wvol, image,  wimage