scripts/sixdegrees/boostgraph.py

#!/usr/bin/env python

# $Id: boostgraph.py,v 1.3 2008/02/21 04:46:47 joko Exp $

# (c) 2008 Andreas Motl <andreas.motl@ilo.de>
# (c) 2008 Sebastian Utz <su@rotamente.com>

# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# 
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.
# 
# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.


# Uses BGL-Python (depth_first_search)
#
# BGL-Python Homepage: http://osl.iu.edu/~dgregor/bgl-python/
#
# Documentation (Boost):
#  - http://www.boost.org/libs/graph/doc/graph_theory_review.html
#  - http://www.boost.org/libs/graph/doc/depth_first_search.html
#  - http://www.boost.org/boost/graph/depth_first_search.hpp
#  - http://www.boost.org/libs/graph/doc/DFSVisitor.html
#  - http://www.boost.org/libs/graph/example/dfs-example.cpp
#
# Documentation (BGL-Python):
#  - http://osl.iu.edu/~dgregor/bgl-python/reference/boost.graph.html
#
# Subversion-Repository: https://svn.osl.iu.edu/svn/projects_viz/bgl-python/


RANDOM_MAX_NODES = 10
RANDOM_MAX_CHILDREN_PER_NODE = 500
MAX_SEARCH_DEPTH = 50


ENABLE_PROFILING = False

if ENABLE_PROFILING:
  import profile
  from profile import Profile


import sys, os
import random

sys.path.append('bgl_python')
os.environ['PATH'] += ';' + './bgl_python'

import boost.graph as bgl


# from http://www.boost.org/libs/graph/doc/DFSVisitor.html
class tree_edges_dfs_visitor(bgl.dfs_visitor):
#class tree_edges_bfs_visitor(bgl.bfs_visitor):
  
  def __init__(self, startVertex, endVertex, maxdepth, color_map):
    
    #print dir(self)
    
    #bgl.dfs_visitor.__init__(self)
    #self.name_map = name_map
    
    self.startVertex = startVertex
    self.endVertex = endVertex
    
    # for recognizing path switches
    self.state = True
    
    # for tracking paths
    self.paths = []
    self.current_path = []
    
    # for limiting search depth
    """
    self.color_map = color_map
    self.maxdepth = maxdepth
    self.depth = 0
    """
    
    self.level = 0
    

  #def back_edge(self, e, g):
  #  self.tree_edge(e, g, 'back_edge')

  #def forward_or_cross_edge(self, e, g):
  #  self.tree_edge(e, g, 'forward_or_cross_edge')

  #def tree_edge(self, e, g):
  #  self.tree_edge(e, g, 'examine_edge')

  def examine_edge(self, e, g):
    self._touch_edge(e, g, 'examine_edge')

  def _touch_edge(self, e, g, label=''):
    
    (u, v) = (g.source(e), g.target(e))
    
    # increase current search depth (level)
    """
    self.depth += 1
    
    # check if maximum depth reached
    if self.depth == self.maxdepth:
      # color all succeeding vertices to black (mark as "already visited")
      # BUG!!! marks too many nodes
      for child_edge in g.out_edges(v):
        end_vertex = g.target(child_edge)
        #self.color_map[end_vertex] = bgl.Color(bgl.Color.gray)
    """
    
    name_map = g.vertex_properties['node_id']
    
    if label:
      print "%s:" % label,
    print "edge ",
    print name_map[u],
    print " -> ",
    print name_map[v]
    
    #self.state = True
    
    if u == self.startVertex:
      print "starting"
      self.current_path = []

    # skip circular references
    if v != self.startVertex:
      self.current_path.append(e)

    if v == self.endVertex and self.current_path:
      print "found:"
      print self.current_path
      self.paths.append(self.current_path)
      self.current_path = []
    

  """
  def start_vertex(self, v, g):
    self._seperator('start_vertex')
    #pass
    #print 'sssss'

  def discover_vertex(self, v, g):
    #print '>>>'
    self._seperator('discover_vertex')
    #pass

  def initialize_vertex(self, v, g):
    #print '>>>'
    self._seperator('initialize_vertex')

  def examine_vertex(self, v, g):
    self._seperator('examine_vertex')

  def finish_vertex(self, v, g):
    #print '<<<'
    if self.current_path:
      self.paths.append(self.current_path)
    self.current_path = []
    self.depth = 0
    self._seperator('finish_vertex')
  """

  def _seperator(self, label = 'unknown'):
    if 1 or self.state:
      print '-' * 21, label
      self.state = False


def build_fixed_graph():
  
  graph = bgl.Graph()
  index = {}

  # doesn't this work? see http://www.nabble.com/-Graph--Getting-PageRank-to-work-in-BGL-Python-td14207115.html
  #graph.add_vertex_property_map(name='my_name', type='float')

  # 'write_graphviz' requires property 'node_id' on vertices
  # see http://lists.boost.org/boost-users/2006/06/19877.php
  vmap = graph.vertex_property_map('string')
  graph.vertex_properties['node_id'] = vmap


  v1 = graph.add_vertex()
  vmap[v1] = '1'
  index['1'] = v1

  v2 = graph.add_vertex()
  vmap[v2] = '2'
  index['2'] = v2

  v3 = graph.add_vertex()
  vmap[v3] = '3'
  index['3'] = v3

  v4 = graph.add_vertex()
  vmap[v4] = '4'
  index['4'] = v4

  e1 = graph.add_edge(v1, v2)
  e2 = graph.add_edge(v1, v3)
  e3 = graph.add_edge(v3, v4)
  
  e4 = graph.add_edge(v1, v4)
  #e5 = graph.add_edge(v3, v2)
  #e6 = graph.add_edge(v2, v4)

  """
  for vertex in graph.vertices:
    #print vertex.id, vertex
    print vmap[vertex], vertex
    #print vertex.__getattribute__('id')
    #print vertex['id']
    #print vertex.get('id')
    #print 
  """

  graph.write_graphviz('friends.dot')
  
  return (graph, index)


def build_random_graph():

  graph = bgl.Graph()
  index = {}

  vmap = graph.vertex_property_map('string')
  graph.vertex_properties['node_id'] = vmap

  count = 0
  for parent_id in range(1, RANDOM_MAX_NODES + 1):
    count += 1
    if count % 100 == 0:
      sys.stderr.write('.')
      
    parent_id_str = str(parent_id)
    v1New = False
    if not index.has_key(parent_id_str):
      #print "adding v1:", parent_id_str
      myVertex1 = graph.add_vertex()
      vmap[myVertex1] = parent_id_str
      index[parent_id_str] = myVertex1
      v1New = True

  
  count = 0
  #for j in range(1, random.randint(1, RANDOM_MAX_CHILDREN_PER_NODE)):
  for j in range(1, RANDOM_MAX_CHILDREN_PER_NODE):

    count += 1
    if count % 100 == 0:
      sys.stderr.write('.')

    parent_id_str = random.choice(index.keys())
    
    child_id_str = parent_id_str
    while child_id_str == parent_id_str:
      child_id_str = random.choice(index.keys())
      #print child_id_str
      
      myVertex1 = index[parent_id_str]
      myVertex2 = index[child_id_str]
      
      graph.add_edge(myVertex1, myVertex2)
        
  sys.stderr.write("\n")

  return (graph, index)


def dump_track(graph, track):
  track_ids = []
  for node in track:
    node_id = graph.vertex_properties['node_id'][node]
    track_ids.append(node_id)
  
  print ' -> '.join(track_ids)

def dump_edges(g, edges):
  name_map = g.vertex_properties['node_id']
  for e in edges:
    (u, v) = (g.source(e), g.target(e))
    print "edge ",
    print name_map[u],
    print " -> ",
    print name_map[v]

def find_path_solutions(source, target, graph, paths):
  
  print
  print "=" * 42
  print "find_path_solutions"
  print "=" * 42

  #print visitor.paths
  #(u, v) = (g.source(e), g.target(e))
  for path in paths:
    startVertex = graph.source(path[0])
    
    track = []
    track.append(startVertex)
    
    for edge in path:
      endVertex = graph.target(edge)
      track.append(endVertex)
      if source == startVertex and target == endVertex:
        #print "found:", track
        dump_track(graph, track)

def dump_graph(graph):
  for edge in graph.edges:
    (u, v) = (graph.source(edge), graph.target(edge))
    startIndex = graph.vertex_properties['node_id'][u]
    endIndex = graph.vertex_properties['node_id'][v]
    print "%s -> %s" % (startIndex, endIndex)
    

def main():
  
  # Load a graph from the GraphViz file 'mst.dot'
  #graph = bgl.Graph.read_graphviz('mst.dot')
  (graph, index) = build_fixed_graph()
  #(graph, index) = build_random_graph()

  #dump_graph(graph)

  # Compute all paths rooted from each vertex
  #mst_edges = bgl.kruskal_minimum_spanning_tree(graph, weight)
  #bgl.depth_first_search(graph, root_vertex = None, visitor = None, color_map = None)
  
  """
  for root in graph.vertices:
    print
    print '=' * 42
    print 'Paths originating from node %s' % graph.vertex_properties['node_id'][root]
    #cmap = graph.vertex_property_map('color')
    cmap = None
    visitor = tree_edges_dfs_visitor(3, graph.vertex_properties['node_id'], cmap)
    #visitor = tree_edges_bfs_visitor(3, graph.vertex_properties['node_id'], cmap)
    bgl.depth_first_search(graph, root_vertex = root, visitor = visitor, color_map = None)
    #bgl.breadth_first_search(graph, root_vertex = root, visitor = visitor, color_map = None)
    #find_path_solutions(index['1'], index['4'], graph, visitor.paths)
  #sys.exit(0)
  """

  startIndex = random.choice(index.keys())
  endIndex = random.choice(index.keys())
  startIndex = '1'
  endIndex = '4'

  print "Trying to find solution for: %s -> %s" % (startIndex, endIndex)

  startVertex = index[startIndex]
  endVertex = index[endIndex]

  def doCompute():
    cmap = graph.vertex_property_map('color')
    visitor = tree_edges_dfs_visitor(startVertex, endVertex, MAX_SEARCH_DEPTH, cmap)
    bgl.depth_first_search(graph, root_vertex = startVertex, visitor = visitor, color_map = None)
    #bgl.depth_first_visit(graph, root_vertex = startVertex, visitor = visitor, color_map = cmap)
    #find_path_solutions(startVertex, endVertex, graph, visitor.paths)
    for path in visitor.paths:
      print '-' * 21
      dump_edges(graph, path)

  if ENABLE_PROFILING:
    global paths
    paths = []
    p = Profile()
    p.runcall(doCompute)
    p.print_stats()
  else:
    paths = doCompute()

  
  # STOP HERE
  sys.exit(0)


  # Compute the weight of the minimum spanning tree 
  #print 'MST weight =',sum([weight[e] for e in mst_edges])

  # Put the weights into the label. Make MST edges solid while all other
  # edges remain dashed.
  label = graph.edge_property_map('string')
  style = graph.edge_property_map('string')
  for e in graph.edges:
      label[e] = str(weight[e])
      if e in mst_edges:
          style[e] = 'solid'
      else:
          style[e] = 'dashed'

  # Associate the label and style property maps with the graph for output
  graph.edge_properties['label'] = label
  graph.edge_properties['style'] = style

  # Write out the graph in GraphViz DOT format
  graph.write_graphviz('friends_path_2to3.dot')


if __name__ == '__main__':
  main()
1	joko	1.1	#!/usr/bin/env python
2
3	joko	1.4	# $Id: boostgraph.py,v 1.3 2008/02/21 04:46:47 joko Exp $
4	joko	1.1
5			# (c) 2008 Andreas Motl <andreas.motl@ilo.de>
6	joko	1.3	# (c) 2008 Sebastian Utz <su@rotamente.com>
7	joko	1.1
8			# This program is free software: you can redistribute it and/or modify
9			# it under the terms of the GNU Affero General Public License as published by
10			# the Free Software Foundation, either version 3 of the License, or
11			# (at your option) any later version.
12			#
13			# This program is distributed in the hope that it will be useful,
14			# but WITHOUT ANY WARRANTY; without even the implied warranty of
15			# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16			# GNU Affero General Public License for more details.
17			#
18			# You should have received a copy of the GNU Affero General Public License
19			# along with this program. If not, see <http://www.gnu.org/licenses/>.
20
21
22
23			# Uses BGL-Python (depth_first_search)
24			#
25			# BGL-Python Homepage: http://osl.iu.edu/~dgregor/bgl-python/
26			#
27	joko	1.2	# Documentation (Boost):
28			# - http://www.boost.org/libs/graph/doc/graph_theory_review.html
29			# - http://www.boost.org/libs/graph/doc/depth_first_search.html
30			# - http://www.boost.org/boost/graph/depth_first_search.hpp
31			# - http://www.boost.org/libs/graph/doc/DFSVisitor.html
32			# - http://www.boost.org/libs/graph/example/dfs-example.cpp
33			#
34			# Documentation (BGL-Python):
35	joko	1.1	# - http://osl.iu.edu/~dgregor/bgl-python/reference/boost.graph.html
36			#
37			# Subversion-Repository: https://svn.osl.iu.edu/svn/projects_viz/bgl-python/
38
39
40	joko	1.3	RANDOM_MAX_NODES = 10
41			RANDOM_MAX_CHILDREN_PER_NODE = 500
42			MAX_SEARCH_DEPTH = 50
43
44
45			ENABLE_PROFILING = False
46
47			if ENABLE_PROFILING:
48			import profile
49			from profile import Profile
50
51
52	joko	1.1	import sys, os
53	joko	1.3	import random
54	joko	1.1
55			sys.path.append('bgl_python')
56			os.environ['PATH'] += ';' + './bgl_python'
57
58			import boost.graph as bgl
59
60
61
62			# from http://www.boost.org/libs/graph/doc/DFSVisitor.html
63			class tree_edges_dfs_visitor(bgl.dfs_visitor):
64	joko	1.3	#class tree_edges_bfs_visitor(bgl.bfs_visitor):
65	joko	1.1
66	joko	1.4	def __init__(self, startVertex, endVertex, maxdepth, color_map):
67	joko	1.3
68	joko	1.4	#print dir(self)
69	joko	1.3
70	joko	1.1	#bgl.dfs_visitor.__init__(self)
71	joko	1.4	#self.name_map = name_map
72
73			self.startVertex = startVertex
74			self.endVertex = endVertex
75	joko	1.2
76			# for recognizing path switches
77	joko	1.1	self.state = True
78	joko	1.2
79			# for tracking paths
80			self.paths = []
81			self.current_path = []
82	joko	1.3
83			# for limiting search depth
84			"""
85			self.color_map = color_map
86			self.maxdepth = maxdepth
87			self.depth = 0
88			"""
89
90			self.level = 0
91
92
93	joko	1.4	#def back_edge(self, e, g):
94			# self.tree_edge(e, g, 'back_edge')
95
96			#def forward_or_cross_edge(self, e, g):
97			# self.tree_edge(e, g, 'forward_or_cross_edge')
98
99			#def tree_edge(self, e, g):
100			# self.tree_edge(e, g, 'examine_edge')
101
102	joko	1.3	def examine_edge(self, e, g):
103	joko	1.4	self._touch_edge(e, g, 'examine_edge')
104	joko	1.1
105	joko	1.4	def _touch_edge(self, e, g, label=''):
106	joko	1.3
107	joko	1.1	(u, v) = (g.source(e), g.target(e))
108	joko	1.3
109			# increase current search depth (level)
110			"""
111			self.depth += 1
112
113			# check if maximum depth reached
114			if self.depth == self.maxdepth:
115			# color all succeeding vertices to black (mark as "already visited")
116			# BUG!!! marks too many nodes
117			for child_edge in g.out_edges(v):
118			end_vertex = g.target(child_edge)
119			#self.color_map[end_vertex] = bgl.Color(bgl.Color.gray)
120			"""
121	joko	1.4
122			name_map = g.vertex_properties['node_id']
123	joko	1.3
124			if label:
125			print "%s:" % label,
126	joko	1.4	print "edge ",
127			print name_map[u],
128	joko	1.1	print " -> ",
129	joko	1.4	print name_map[v]
130
131			#self.state = True
132
133			if u == self.startVertex:
134			print "starting"
135			self.current_path = []
136
137			# skip circular references
138			if v != self.startVertex:
139			self.current_path.append(e)
140
141			if v == self.endVertex and self.current_path:
142			print "found:"
143			print self.current_path
144			self.paths.append(self.current_path)
145			self.current_path = []
146
147	joko	1.1
148	joko	1.4	"""
149	joko	1.1	def start_vertex(self, v, g):
150	joko	1.3	self._seperator('start_vertex')
151			#pass
152	joko	1.1	#print 'sssss'
153
154	joko	1.3	def discover_vertex(self, v, g):
155			#print '>>>'
156			self._seperator('discover_vertex')
157			#pass
158
159	joko	1.1	def initialize_vertex(self, v, g):
160			#print '>>>'
161	joko	1.2	self._seperator('initialize_vertex')
162	joko	1.1
163	joko	1.3	def examine_vertex(self, v, g):
164			self._seperator('examine_vertex')
165
166	joko	1.1	def finish_vertex(self, v, g):
167			#print '<<<'
168	joko	1.2	if self.current_path:
169			self.paths.append(self.current_path)
170			self.current_path = []
171	joko	1.3	self.depth = 0
172	joko	1.2	self._seperator('finish_vertex')
173	joko	1.4	"""
174	joko	1.1
175	joko	1.2	def _seperator(self, label = 'unknown'):
176	joko	1.3	if 1 or self.state:
177	joko	1.2	print '-' * 21, label
178	joko	1.1	self.state = False
179
180	joko	1.2
181	joko	1.1	def build_fixed_graph():
182	joko	1.2
183	joko	1.1	graph = bgl.Graph()
184	joko	1.2	index = {}
185	joko	1.1
186	joko	1.2	# doesn't this work? see http://www.nabble.com/-Graph--Getting-PageRank-to-work-in-BGL-Python-td14207115.html
187	joko	1.1	#graph.add_vertex_property_map(name='my_name', type='float')
188
189			# 'write_graphviz' requires property 'node_id' on vertices
190			# see http://lists.boost.org/boost-users/2006/06/19877.php
191			vmap = graph.vertex_property_map('string')
192			graph.vertex_properties['node_id'] = vmap
193
194
195			v1 = graph.add_vertex()
196			vmap[v1] = '1'
197	joko	1.2	index['1'] = v1
198	joko	1.1
199			v2 = graph.add_vertex()
200			vmap[v2] = '2'
201	joko	1.2	index['2'] = v2
202	joko	1.1
203			v3 = graph.add_vertex()
204			vmap[v3] = '3'
205	joko	1.2	index['3'] = v3
206	joko	1.1
207			v4 = graph.add_vertex()
208			vmap[v4] = '4'
209	joko	1.2	index['4'] = v4
210	joko	1.1
211			e1 = graph.add_edge(v1, v2)
212			e2 = graph.add_edge(v1, v3)
213			e3 = graph.add_edge(v3, v4)
214	joko	1.3
215			e4 = graph.add_edge(v1, v4)
216			#e5 = graph.add_edge(v3, v2)
217			#e6 = graph.add_edge(v2, v4)
218	joko	1.1
219			"""
220			for vertex in graph.vertices:
221			#print vertex.id, vertex
222			print vmap[vertex], vertex
223			#print vertex.__getattribute__('id')
224			#print vertex['id']
225			#print vertex.get('id')
226			#print
227			"""
228
229			graph.write_graphviz('friends.dot')
230
231	joko	1.2	return (graph, index)
232	joko	1.1
233
234	joko	1.3	def build_random_graph():
235
236			graph = bgl.Graph()
237			index = {}
238
239			vmap = graph.vertex_property_map('string')
240			graph.vertex_properties['node_id'] = vmap
241
242			count = 0
243			for parent_id in range(1, RANDOM_MAX_NODES + 1):
244			count += 1
245			if count % 100 == 0:
246			sys.stderr.write('.')
247
248			parent_id_str = str(parent_id)
249			v1New = False
250			if not index.has_key(parent_id_str):
251			#print "adding v1:", parent_id_str
252			myVertex1 = graph.add_vertex()
253			vmap[myVertex1] = parent_id_str
254			index[parent_id_str] = myVertex1
255			v1New = True
256
257
258			count = 0
259			#for j in range(1, random.randint(1, RANDOM_MAX_CHILDREN_PER_NODE)):
260			for j in range(1, RANDOM_MAX_CHILDREN_PER_NODE):
261
262			count += 1
263			if count % 100 == 0:
264			sys.stderr.write('.')
265
266			parent_id_str = random.choice(index.keys())
267
268			child_id_str = parent_id_str
269			while child_id_str == parent_id_str:
270			child_id_str = random.choice(index.keys())
271			#print child_id_str
272
273			myVertex1 = index[parent_id_str]
274			myVertex2 = index[child_id_str]
275
276			graph.add_edge(myVertex1, myVertex2)
277
278			sys.stderr.write("\n")
279
280			return (graph, index)
281
282
283			def dump_track(graph, track):
284			track_ids = []
285			for node in track:
286			node_id = graph.vertex_properties['node_id'][node]
287			track_ids.append(node_id)
288
289			print ' -> '.join(track_ids)
290	joko	1.1
291	joko	1.4	def dump_edges(g, edges):
292			name_map = g.vertex_properties['node_id']
293			for e in edges:
294			(u, v) = (g.source(e), g.target(e))
295			print "edge ",
296			print name_map[u],
297			print " -> ",
298			print name_map[v]
299
300	joko	1.2	def find_path_solutions(source, target, graph, paths):
301
302			print
303			print "=" * 42
304			print "find_path_solutions"
305			print "=" * 42
306
307			#print visitor.paths
308			#(u, v) = (g.source(e), g.target(e))
309			for path in paths:
310			startVertex = graph.source(path[0])
311	joko	1.3
312			track = []
313			track.append(startVertex)
314
315			for edge in path:
316			endVertex = graph.target(edge)
317			track.append(endVertex)
318			if source == startVertex and target == endVertex:
319			#print "found:", track
320			dump_track(graph, track)
321
322			def dump_graph(graph):
323			for edge in graph.edges:
324			(u, v) = (graph.source(edge), graph.target(edge))
325			startIndex = graph.vertex_properties['node_id'][u]
326			endIndex = graph.vertex_properties['node_id'][v]
327			print "%s -> %s" % (startIndex, endIndex)
328
329	joko	1.2
330	joko	1.1	def main():
331
332			# Load a graph from the GraphViz file 'mst.dot'
333			#graph = bgl.Graph.read_graphviz('mst.dot')
334	joko	1.2	(graph, index) = build_fixed_graph()
335	joko	1.3	#(graph, index) = build_random_graph()
336
337			#dump_graph(graph)
338	joko	1.1
339			# Compute all paths rooted from each vertex
340			#mst_edges = bgl.kruskal_minimum_spanning_tree(graph, weight)
341			#bgl.depth_first_search(graph, root_vertex = None, visitor = None, color_map = None)
342	joko	1.3
343	joko	1.4	"""
344	joko	1.1	for root in graph.vertices:
345			print
346			print '=' * 42
347			print 'Paths originating from node %s' % graph.vertex_properties['node_id'][root]
348	joko	1.3	#cmap = graph.vertex_property_map('color')
349			cmap = None
350			visitor = tree_edges_dfs_visitor(3, graph.vertex_properties['node_id'], cmap)
351			#visitor = tree_edges_bfs_visitor(3, graph.vertex_properties['node_id'], cmap)
352	joko	1.1	bgl.depth_first_search(graph, root_vertex = root, visitor = visitor, color_map = None)
353	joko	1.3	#bgl.breadth_first_search(graph, root_vertex = root, visitor = visitor, color_map = None)
354			#find_path_solutions(index['1'], index['4'], graph, visitor.paths)
355			#sys.exit(0)
356	joko	1.4	"""
357	joko	1.3
358			startIndex = random.choice(index.keys())
359			endIndex = random.choice(index.keys())
360			startIndex = '1'
361			endIndex = '4'
362
363			print "Trying to find solution for: %s -> %s" % (startIndex, endIndex)
364
365			startVertex = index[startIndex]
366			endVertex = index[endIndex]
367
368			def doCompute():
369			cmap = graph.vertex_property_map('color')
370	joko	1.4	visitor = tree_edges_dfs_visitor(startVertex, endVertex, MAX_SEARCH_DEPTH, cmap)
371	joko	1.3	bgl.depth_first_search(graph, root_vertex = startVertex, visitor = visitor, color_map = None)
372			#bgl.depth_first_visit(graph, root_vertex = startVertex, visitor = visitor, color_map = cmap)
373	joko	1.4	#find_path_solutions(startVertex, endVertex, graph, visitor.paths)
374			for path in visitor.paths:
375			print '-' * 21
376			dump_edges(graph, path)
377	joko	1.3
378			if ENABLE_PROFILING:
379			global paths
380			paths = []
381			p = Profile()
382			p.runcall(doCompute)
383			p.print_stats()
384			else:
385			paths = doCompute()
386
387	joko	1.1
388			# STOP HERE
389			sys.exit(0)
390
391
392
393
394
395			# Compute the weight of the minimum spanning tree
396			#print 'MST weight =',sum([weight[e] for e in mst_edges])
397
398			# Put the weights into the label. Make MST edges solid while all other
399			# edges remain dashed.
400			label = graph.edge_property_map('string')
401			style = graph.edge_property_map('string')
402			for e in graph.edges:
403			label[e] = str(weight[e])
404			if e in mst_edges:
405			style[e] = 'solid'
406			else:
407			style[e] = 'dashed'
408
409			# Associate the label and style property maps with the graph for output
410			graph.edge_properties['label'] = label
411			graph.edge_properties['style'] = style
412
413			# Write out the graph in GraphViz DOT format
414			graph.write_graphviz('friends_path_2to3.dot')
415
416
417			if __name__ == '__main__':
418			main()
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