scripts/sixdegrees/boostgraph.py

#!/usr/bin/env python

# $Id: boostgraph.py,v 1.1 2008/02/08 09:05:02 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, maxdepth, name_map, color_map):
    
    print dir(self)
    
    #bgl.dfs_visitor.__init__(self)
    self.name_map = name_map
    
    # 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 examine_edge(self, e, g):
    self.tree_edge2(e, g, 'examine_edge')

  def tree_edge2(self, e, g, label='tree_edge'):
    
    (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)
    """
      
    
    if label:
      print "%s:" % label,
    print "Tree edge ",
    print self.name_map[u],
    print " -> ",
    print self.name_map[v]
    sys.stdout.flush()
    self.state = True
    self.current_path.append(e)
    #return False

  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 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(MAX_SEARCH_DEPTH, graph.vertex_properties['node_id'], 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)

  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	#!/usr/bin/env python
2
3	# $Id: boostgraph.py,v 1.1 2008/02/08 09:05:02 joko Exp $
4
5	# (c) 2008 Andreas Motl <andreas.motl@ilo.de>
6	# (c) 2008 Sebastian Utz <su@rotamente.com>
7
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	# 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	# - 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	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	import sys, os
53	import random
54
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	#class tree_edges_bfs_visitor(bgl.bfs_visitor):
65
66	def __init__(self, maxdepth, name_map, color_map):
67
68	print dir(self)
69
70	#bgl.dfs_visitor.__init__(self)
71	self.name_map = name_map
72
73	# for recognizing path switches
74	self.state = True
75
76	# for tracking paths
77	self.paths = []
78	self.current_path = []
79
80	# for limiting search depth
81	"""
82	self.color_map = color_map
83	self.maxdepth = maxdepth
84	self.depth = 0
85	"""
86
87	self.level = 0
88
89
90	def examine_edge(self, e, g):
91	self.tree_edge2(e, g, 'examine_edge')
92
93	def tree_edge2(self, e, g, label='tree_edge'):
94
95	(u, v) = (g.source(e), g.target(e))
96
97	# increase current search depth (level)
98	"""
99	self.depth += 1
100
101	# check if maximum depth reached
102	if self.depth == self.maxdepth:
103	# color all succeeding vertices to black (mark as "already visited")
104	# BUG!!! marks too many nodes
105	for child_edge in g.out_edges(v):
106	end_vertex = g.target(child_edge)
107	#self.color_map[end_vertex] = bgl.Color(bgl.Color.gray)
108	"""
109
110
111	if label:
112	print "%s:" % label,
113	print "Tree edge ",
114	print self.name_map[u],
115	print " -> ",
116	print self.name_map[v]
117	sys.stdout.flush()
118	self.state = True
119	self.current_path.append(e)
120	#return False
121
122	def start_vertex(self, v, g):
123	self._seperator('start_vertex')
124	#pass
125	#print 'sssss'
126
127
128	def discover_vertex(self, v, g):
129	#print '>>>'
130	self._seperator('discover_vertex')
131	#pass
132
133	def initialize_vertex(self, v, g):
134	#print '>>>'
135	self._seperator('initialize_vertex')
136
137	def examine_vertex(self, v, g):
138	self._seperator('examine_vertex')
139
140	def finish_vertex(self, v, g):
141	#print '<<<'
142	if self.current_path:
143	self.paths.append(self.current_path)
144	self.current_path = []
145	self.depth = 0
146	self._seperator('finish_vertex')
147
148	def _seperator(self, label = 'unknown'):
149	if 1 or self.state:
150	print '-' * 21, label
151	self.state = False
152
153
154	def build_fixed_graph():
155
156	graph = bgl.Graph()
157	index = {}
158
159	# doesn't this work? see http://www.nabble.com/-Graph--Getting-PageRank-to-work-in-BGL-Python-td14207115.html
160	#graph.add_vertex_property_map(name='my_name', type='float')
161
162	# 'write_graphviz' requires property 'node_id' on vertices
163	# see http://lists.boost.org/boost-users/2006/06/19877.php
164	vmap = graph.vertex_property_map('string')
165	graph.vertex_properties['node_id'] = vmap
166
167
168	v1 = graph.add_vertex()
169	vmap[v1] = '1'
170	index['1'] = v1
171
172	v2 = graph.add_vertex()
173	vmap[v2] = '2'
174	index['2'] = v2
175
176	v3 = graph.add_vertex()
177	vmap[v3] = '3'
178	index['3'] = v3
179
180	v4 = graph.add_vertex()
181	vmap[v4] = '4'
182	index['4'] = v4
183
184	e1 = graph.add_edge(v1, v2)
185	e2 = graph.add_edge(v1, v3)
186	e3 = graph.add_edge(v3, v4)
187
188	e4 = graph.add_edge(v1, v4)
189	#e5 = graph.add_edge(v3, v2)
190	#e6 = graph.add_edge(v2, v4)
191
192	"""
193	for vertex in graph.vertices:
194	#print vertex.id, vertex
195	print vmap[vertex], vertex
196	#print vertex.__getattribute__('id')
197	#print vertex['id']
198	#print vertex.get('id')
199	#print
200	"""
201
202	graph.write_graphviz('friends.dot')
203
204	return (graph, index)
205
206
207	def build_random_graph():
208
209	graph = bgl.Graph()
210	index = {}
211
212	vmap = graph.vertex_property_map('string')
213	graph.vertex_properties['node_id'] = vmap
214
215	count = 0
216	for parent_id in range(1, RANDOM_MAX_NODES + 1):
217	count += 1
218	if count % 100 == 0:
219	sys.stderr.write('.')
220
221	parent_id_str = str(parent_id)
222	v1New = False
223	if not index.has_key(parent_id_str):
224	#print "adding v1:", parent_id_str
225	myVertex1 = graph.add_vertex()
226	vmap[myVertex1] = parent_id_str
227	index[parent_id_str] = myVertex1
228	v1New = True
229
230
231	count = 0
232	#for j in range(1, random.randint(1, RANDOM_MAX_CHILDREN_PER_NODE)):
233	for j in range(1, RANDOM_MAX_CHILDREN_PER_NODE):
234
235	count += 1
236	if count % 100 == 0:
237	sys.stderr.write('.')
238
239	parent_id_str = random.choice(index.keys())
240
241	child_id_str = parent_id_str
242	while child_id_str == parent_id_str:
243	child_id_str = random.choice(index.keys())
244	#print child_id_str
245
246	myVertex1 = index[parent_id_str]
247	myVertex2 = index[child_id_str]
248
249	graph.add_edge(myVertex1, myVertex2)
250
251	sys.stderr.write("\n")
252
253	return (graph, index)
254
255
256	def dump_track(graph, track):
257	track_ids = []
258	for node in track:
259	node_id = graph.vertex_properties['node_id'][node]
260	track_ids.append(node_id)
261
262	print ' -> '.join(track_ids)
263
264	def find_path_solutions(source, target, graph, paths):
265
266	print
267	print "=" * 42
268	print "find_path_solutions"
269	print "=" * 42
270
271	#print visitor.paths
272	#(u, v) = (g.source(e), g.target(e))
273	for path in paths:
274	startVertex = graph.source(path[0])
275
276	track = []
277	track.append(startVertex)
278
279	for edge in path:
280	endVertex = graph.target(edge)
281	track.append(endVertex)
282	if source == startVertex and target == endVertex:
283	#print "found:", track
284	dump_track(graph, track)
285
286	def dump_graph(graph):
287	for edge in graph.edges:
288	(u, v) = (graph.source(edge), graph.target(edge))
289	startIndex = graph.vertex_properties['node_id'][u]
290	endIndex = graph.vertex_properties['node_id'][v]
291	print "%s -> %s" % (startIndex, endIndex)
292
293
294	def main():
295
296	# Load a graph from the GraphViz file 'mst.dot'
297	#graph = bgl.Graph.read_graphviz('mst.dot')
298	(graph, index) = build_fixed_graph()
299	#(graph, index) = build_random_graph()
300
301	#dump_graph(graph)
302
303	# Compute all paths rooted from each vertex
304	#mst_edges = bgl.kruskal_minimum_spanning_tree(graph, weight)
305	#bgl.depth_first_search(graph, root_vertex = None, visitor = None, color_map = None)
306
307	for root in graph.vertices:
308	print
309	print '=' * 42
310	print 'Paths originating from node %s' % graph.vertex_properties['node_id'][root]
311	#cmap = graph.vertex_property_map('color')
312	cmap = None
313	visitor = tree_edges_dfs_visitor(3, graph.vertex_properties['node_id'], cmap)
314	#visitor = tree_edges_bfs_visitor(3, graph.vertex_properties['node_id'], cmap)
315	bgl.depth_first_search(graph, root_vertex = root, visitor = visitor, color_map = None)
316	#bgl.breadth_first_search(graph, root_vertex = root, visitor = visitor, color_map = None)
317	#find_path_solutions(index['1'], index['4'], graph, visitor.paths)
318	#sys.exit(0)
319
320	startIndex = random.choice(index.keys())
321	endIndex = random.choice(index.keys())
322	startIndex = '1'
323	endIndex = '4'
324
325	print "Trying to find solution for: %s -> %s" % (startIndex, endIndex)
326
327	startVertex = index[startIndex]
328	endVertex = index[endIndex]
329
330	def doCompute():
331	cmap = graph.vertex_property_map('color')
332	visitor = tree_edges_dfs_visitor(MAX_SEARCH_DEPTH, graph.vertex_properties['node_id'], cmap)
333	bgl.depth_first_search(graph, root_vertex = startVertex, visitor = visitor, color_map = None)
334	#bgl.depth_first_visit(graph, root_vertex = startVertex, visitor = visitor, color_map = cmap)
335	find_path_solutions(startVertex, endVertex, graph, visitor.paths)
336
337	if ENABLE_PROFILING:
338	global paths
339	paths = []
340	p = Profile()
341	p.runcall(doCompute)
342	p.print_stats()
343	else:
344	paths = doCompute()
345
346
347	# STOP HERE
348	sys.exit(0)
349
350
351
352
353
354	# Compute the weight of the minimum spanning tree
355	#print 'MST weight =',sum([weight[e] for e in mst_edges])
356
357	# Put the weights into the label. Make MST edges solid while all other
358	# edges remain dashed.
359	label = graph.edge_property_map('string')
360	style = graph.edge_property_map('string')
361	for e in graph.edges:
362	label[e] = str(weight[e])
363	if e in mst_edges:
364	style[e] = 'solid'
365	else:
366	style[e] = 'dashed'
367
368	# Associate the label and style property maps with the graph for output
369	graph.edge_properties['label'] = label
370	graph.edge_properties['style'] = style
371
372	# Write out the graph in GraphViz DOT format
373	graph.write_graphviz('friends_path_2to3.dot')
374
375
376	if __name__ == '__main__':
377	main()
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