old_contents: from __future__ import division
  from menpofit.result import (
      ParametricAlgorithmResult, MultiFitterResult, SerializableIterativeResult)
  
  
  # TODO: document me!
  # TODO: handle costs
  class AAMAlgorithmResult(ParametricAlgorithmResult):
      r"""
      """
      def __init__(self, image, fitter, shape_parameters,
                   appearance_parameters=None, gt_shape=None):
          super(AAMAlgorithmResult, self).__init__(
              image, fitter, shape_parameters, gt_shape=gt_shape)
          self.appearance_parameters = appearance_parameters
  
  
  # TODO: document me!
  class LinearAAMAlgorithmResult(AAMAlgorithmResult):
      r"""
      """
      def shapes(self, as_points=False):
          if as_points:
              return [self.fitter.transform.from_vector(p).sparse_target.points
                      for p in self.shape_parameters]
  
          else:
              return [self.fitter.transform.from_vector(p).sparse_target
                      for p in self.shape_parameters]
  
      @property
      def final_shape(self):
          return self.final_transform.sparse_target
  
      @property
      def initial_shape(self):
          return self.initial_transform.sparse_target
  
  
  # TODO: document me!
  # TODO: handle costs
  class AAMFitterResult(MultiFitterResult):
      r"""
      """
      pass
  
new_contents: from __future__ import division
  from menpofit.result import (
      ParametricAlgorithmResult, MultiFitterResult, SerializableIterativeResult)
  
  
  # TODO: document me!
  # TODO: handle costs
  class AAMAlgorithmResult(ParametricAlgorithmResult):
      r"""
      """
      def __init__(self, image, fitter, shape_parameters,
                   appearance_parameters=None, gt_shape=None):
          super(AAMAlgorithmResult, self).__init__(
              image, fitter, shape_parameters, gt_shape=gt_shape)
          self.appearance_parameters = appearance_parameters
  
  
  # TODO: document me!
  class LinearAAMAlgorithmResult(AAMAlgorithmResult):
      r"""
      """
      @property
      def shapes(self, as_points=False):
          return [self.fitter.transform.from_vector(p).sparse_target
                  for p in self.shape_parameters]
  
      @property
      def final_shape(self):
          return self.final_transform.sparse_target
  
      @property
      def initial_shape(self):
          return self.initial_transform.sparse_target
  
  
  # TODO: document me!
  # TODO: handle costs
  class AAMFitterResult(MultiFitterResult):
      r"""
      """
      pass
  
subject: Make shape a property for LinearAAMAlgorithmResult