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
class_docstr_tok: ["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","\u017dalik",",","B.","Sweep\u2010line","algorithm","for","constrained","Delaunay","triangulation"]
code: def _remove_tri(self, a, b, c):
      for k in permutations((a, b, c)):
          if k in self.tris:
              break
      del self.tris[k]
      (a, b, c) = k
  
      if self._edges_lookup.get((a, b), -1) == c:
          del self._edges_lookup[(a, b)]
          del self._edges_lookup[(b, c)]
          del self._edges_lookup[(c, a)]
      elif self._edges_lookup.get((b, a), -1) == c:
          del self._edges_lookup[(b, a)]
          del self._edges_lookup[(a, c)]
          del self._edges_lookup[(c, b)]
      else:
          raise RuntimeError(
              "Lost edges_lookup for tri (%d, %d, %d)" % (a, b, c)
          )
  
      return k
  
imports: from __future__ import division, print_function
  from itertools import permutations
  import numpy
  from collections import OrderedDict
label_desc: Use image node_id 27 for calling the Triangulation obj's underlying member method code with example usage: obj._remove_tri(a, b, c) and returns: k