class_docstr: Constrained delaunay triangulation
  
  Implementation based on [1]_.
  
  Parameters
  ----------
  pts : array
      Nx2 array of points.
  edges : array
      Nx2 array of edges (dtype=int).
  
  Notes
  -----
  * Delaunay legalization is not yet implemented. This produces a proper
    triangulation, but adding legalisation would produce fewer thin
    triangles.
  * The pts and edges arrays may be modified.
  
  References
  ----------
  .. [1] Domiter, V. and Žalik, B. Sweep‐line algorithm for constrained
     Delaunay triangulation
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docstr: Given a list of *edges*, return the first that is intersected by
  *cut_edge*.
docstr_tok: ["Given","a","list","of","*","edges","*",",","return","the","first","that","is","intersected","by","*","cut_edge","*","."]
code: def _intersected_edge(self, edges, cut_edge):
      """Given a list of *edges*, return the first that is intersected by
      *cut_edge*.
      """
      for edge in edges:
          if self._edges_intersect(edge, cut_edge):
              return edge
  
imports: from __future__ import division, print_function
  from itertools import permutations
  import numpy
  from collections import OrderedDict
label_desc: Use image node_id 15 for calling the Triangulation obj's underlying member method code with example usage: obj._intersected_edge(edges, cut_edge) and returns: edge