class_docstr: Executes the complete pipeline of the graph cut algorithm, checking the results.
class_docstr_tok: ["Executes","the","complete","pipeline","of","the","graph","cut","algorithm",",","checking","the","results","."]
docstr: Returns the edges that should not be in the graph and have to be removed.
docstr_tok: ["Returns","the","edges","that","should","not","be","in","the","graph","and","have","to","be","removed","."]
code: def __get_bad_edges(self):
      "Returns the edges that should not be in the graph and have to be removed."
      return ((3, 6), (7, 10))
  
file_path: medpy/tests/graphcut_/cut.py
imports: import unittest
  from medpy.graphcut import graph_from_labels, GraphDouble, Graph, graph_from_voxels
  from medpy.graphcut.energy_voxel import boundary_difference_linear
  from medpy import filter
  import scipy
label_desc: Use image node_id 5 for calling the TestCut obj's underlying member method code with example usage: obj.__get_bad_edges() and returns: int,  int,  int,  int