class_docstr: Moves a sliding window over the array, where the first patch is places centered on
  the top-left voxel and outside-of-image values filled with `cval`. The returned
  patches are views if the array.
  
  All yielded patches will be of size ``psize``. Areas outside of the array are
  filled with ``cval``. Besides the patch, a patch mask is returned, that denoted
  the outside values.
  
  Central element for even patches:
  
      [[0, 0],
       [0, X]]
  
  Parameters
  ----------
  array : array_like
      A n-dimensional array.
  psize : int or sequence of ints
      The patch size. If a single integer interpreted as hyper-cube.
  cval : number
      Value to fill undefined positions.
docstr: Apply a slicer returned by the iterator to a new array of the same
  dimensionality as the one used to initialize the iterator.
  
  Notes
  -----
  If ``array`` has more dimensions than ``slicer`` and ``pmask``, the first ones
  are sliced.
  
  Parameters
  ----------
  array : array_like
      A n-dimensional array.
  slicer : list
      List if `slice()` instances as returned by `next()`.
  cval : number
      Value to fill undefined positions. If None, the ``cval`` of the object is used.
  
  Returns
  -------
  patch: ndarray
      A patch from the input ``array``.
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code: def applyslicer(self, array, slicer, cval=None):
      r"""
      Apply a slicer returned by the iterator to a new array of the same
      dimensionality as the one used to initialize the iterator.
  
      Notes
      -----
      If ``array`` has more dimensions than ``slicer`` and ``pmask``, the first ones
      are sliced.
  
      Parameters
      ----------
      array : array_like
          A n-dimensional array.
      slicer : list
          List if `slice()` instances as returned by `next()`.
      cval : number
          Value to fill undefined positions. If None, the ``cval`` of the object is used.
  
      Returns
      -------
      patch: ndarray
          A patch from the input ``array``.
      """
      if cval is None:
          cval = self.cval
      _padding = self.padding + [(0, 0)] * (
          array.ndim - len(self.padding)
      )
      array = numpy.pad(
          array, _padding, mode="constant", constant_values=cval
      )
      _psize = self.psize + list(array.shape[len(self.psize) :])
      return array[slicer].reshape(_psize)
  
imports: from itertools import product
  import numpy
  from operator import itemgetter
  from scipy.ndimage import find_objects
label_desc: Use image node_id 4 for calling the SlidingWindowIterator obj's underlying member method code with example usage: obj.applyslicer(array, slicer, cval) and returns: array