def test_dijkstra():
import boost.graph as bgl
graph = bgl.Graph()
a = graph.add_vertex()
b = graph.add_vertex()
e = graph.add_edge(a, b)
distances = graph.add_vertex_property('float')
predecessors = graph.add_vertex_property('vertex')
bgl.dijkstra_shortest_paths(
graph,
a,
predecessor_map = predecessors,
distance_map = distances
)
def get_shortest_distances(g, vertices=None):
"The shortest distance between the given vertices and all others in the graph"
import boost.graph as bgl
if None == vertices: vertices = g.vertices
predecessor_map = g.add_vertex_property('predecessor', 'vertex')
distance_map = g.add_vertex_property('distance', 'float')
index_map = g.add_vertex_property('index', 'index')
result = dict((index_map[v], dict()) for v in g.vertices)
for v1 in vertices:
if v1 in result: continue # avoid duplicating work
bgl.dijkstra_shortest_paths(g, v1, predecessor_map, distance_map)
for v2 in g.vertices:
result[index_map[v1]][index_map[v2]] = distance_map[v2]
del g.vertex_properties['predecessor']
del g.vertex_properties['distance']
return result
def dijkstraBoost(boostGraph, start):
from boost.graph import dijkstra_shortest_paths
dijkstra_shortest_paths(boostGraph, start,
distance_map = boostGraph.vertex_properties['distance'],
predecessor_map = boostGraph.vertex_properties['predecessor'],
weight_map = boostGraph.edge_properties['weight'])
# dictionary of final distances
D = {}
# dictionary of predecessors
P = {}
for v in boostGraph.vertices:
D[v.partner] = v.distance
for edge in v.partner.inEdges:
if edge.source == v.predecessor.partner:
P[v.partner] = edge
break
return (D, P)
def dijkstraBoost(boostGraph, start):
from boost.graph import dijkstra_shortest_paths
dijkstra_shortest_paths(
boostGraph,
start,
distance_map=boostGraph.vertex_properties['distance'],
predecessor_map=boostGraph.vertex_properties['predecessor'],
weight_map=boostGraph.edge_properties['weight'])
# dictionary of final distances
D = {}
# dictionary of predecessors
P = {}
for v in boostGraph.vertices:
D[v.partner] = v.distance
for edge in v.partner.inEdges:
if edge.source == v.predecessor.partner:
P[v.partner] = edge
break
return (D, P)
def get_shortest_distances( g, vertices = None ):
"The shortest distance between the given vertices and all others in the graph"
import boost.graph as bgl
if None == vertices: vertices = g.vertices
predecessor_map = g.add_vertex_property( 'predecessor', 'vertex' )
distance_map = g.add_vertex_property( 'distance', 'float' )
index_map = g.add_vertex_property( 'index', 'index' )
result = dict( (index_map[ v ], dict()) for v in g.vertices )
for v1 in vertices:
if v1 in result: continue # avoid duplicating work
bgl.dijkstra_shortest_paths(
g,
v1,
predecessor_map,
distance_map
)
for v2 in g.vertices:
result[ index_map[ v1 ] ][ index_map[ v2 ] ] = distance_map[ v2 ]
del g.vertex_properties[ 'predecessor' ]
del g.vertex_properties[ 'distance' ]
return result
# Copyright (C) 2006 The Trustees of Indiana University.
# Use, modification and distribution is subject to the Boost Software
# License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
# http:#www.boost.org/LICENSE_1_0.txt)
# Authors: Douglas Gregor
# Andrew Lumsdaine
import boost.graph as bgl
# Load a graph from the GraphViz file 'mst.dot'
graph = bgl.Graph.read_graphviz('mst.dot')
# Compute the shortest paths from the first vertex ('A')
A = graph.vertices.next()
bgl.dijkstra_shortest_paths(
graph,
A,
distance_map=graph.add_vertex_property('distance'),
predecessor_map=graph.add_vertex_property('predecessor'),
weight_map=graph.edge_properties['weight'])
# Print out the shortest paths tree
for v in graph.vertices:
print v.node_id, 'distance from A = ', v.distance,
print ', predecessor = ', v.predecessor.node_id
# Copyright (C) 2006 The Trustees of Indiana University.
# Use, modification and distribution is subject to the Boost Software
# License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
# http:#www.boost.org/LICENSE_1_0.txt)
# Authors: Douglas Gregor
# Andrew Lumsdaine
import boost.graph as bgl
# Load a graph from the GraphViz file 'mst.dot'
graph = bgl.Graph.read_graphviz('mst.dot')
# Compute the shortest paths from the first vertex ('A')
A = graph.vertices.next()
bgl.dijkstra_shortest_paths(graph, A,
distance_map = graph.add_vertex_property('distance') ,
predecessor_map = graph.add_vertex_property('predecessor'),
weight_map = graph.edge_properties['weight'])
# Print out the shortest paths tree
for v in graph.vertices:
print v.node_id,'distance from A = ',v.distance,
print ', predecessor = ', v.predecessor.node_id
