old_contents: import numpy as np
  
  import _unwrap_2d
  import _unwrap_3d
  
  
  def unwrap(wrapped_array,
             wrap_around_axis_0 = False,
             wrap_around_axis_1 = False,
             wrap_around_axis_2 = False):
  
      wrapped_array = np.require(wrapped_array, np.float32, ['C'])
      if wrapped_array.ndim not in [2,3]:
          raise ValueError('input array needs to have 2 or 3 dimensions')
  
      wrapped_array_masked = np.ma.asarray(wrapped_array)
      unwrapped_array = np.empty_like(wrapped_array_masked.data)
      if wrapped_array.ndim == 2:
          _unwrap_2d._unwrap2D(wrapped_array_masked.data,
                             np.ma.getmaskarray(wrapped_array_masked).astype(np.uint8),
                             unwrapped_array,
                             bool(wrap_around_axis_0), bool(wrap_around_axis_1))
      elif wrapped_array.ndim == 3:
          _unwrap_3d._unwrap3D(wrapped_array_masked.data,
                             np.ma.getmaskarray(wrapped_array_masked).astype(np.uint8),
                             unwrapped_array,
                             bool(wrap_around_axis_0), bool(wrap_around_axis_1), bool(wrap_around_axis_2))
  
      if np.ma.isMaskedArray(wrapped_array):
          return np.ma.array(unwrapped_array, mask = wrapped_array_masked.mask)
      else:
          return unwrapped_array
  
      #TODO: set_fill to minimum value
      #TODO: check for empty mask, not a single contiguous pixel
  
  
new_contents: import numpy as np
  
  import _unwrap_2d
  import _unwrap_3d
  
  
  def unwrap(wrapped_array,
             wrap_around_axis_0=False,
             wrap_around_axis_1=False,
             wrap_around_axis_2=False):
      '''From ``image``, wrapped to lie in the interval [-pi, pi), recover the
      original, unwrapped image.
  
      Parameters
      ----------
      image : 2D or 3D ndarray, optionally a masked array
      wrap_around : bool or sequence of bool
  
      Returns
      -------
      image_unwrapped : array_like
      '''
      wrapped_array = np.require(wrapped_array, np.float32, ['C'])
      if wrapped_array.ndim not in [2,3]:
          raise ValueError('input array needs to have 2 or 3 dimensions')
  
      wrapped_array_masked = np.ma.asarray(wrapped_array)
      unwrapped_array = np.empty_like(wrapped_array_masked.data)
      if wrapped_array.ndim == 2:
          _unwrap_2d._unwrap2D(wrapped_array_masked.data,
                             np.ma.getmaskarray(wrapped_array_masked).astype(np.uint8),
                             unwrapped_array,
                             bool(wrap_around_axis_0), bool(wrap_around_axis_1))
      elif wrapped_array.ndim == 3:
          _unwrap_3d._unwrap3D(wrapped_array_masked.data,
                             np.ma.getmaskarray(wrapped_array_masked).astype(np.uint8),
                             unwrapped_array,
                             bool(wrap_around_axis_0), bool(wrap_around_axis_1), bool(wrap_around_axis_2))
  
      if np.ma.isMaskedArray(wrapped_array):
          return np.ma.array(unwrapped_array, mask = wrapped_array_masked.mask)
      else:
          return unwrapped_array
  
      #TODO: set_fill to minimum value
      #TODO: check for empty mask, not a single contiguous pixel
  
  
subject: Add unfinished docstrings.