def subPartitionNx(self, graph): max_cover_clique_ls = cliques.find_cliques(graph) max_clique_index = numpy.argmax(map(len,max_cover_clique_ls)) max_clique = max_cover_clique_ls[max_clique_index] self.clique_ls.append(max_clique) graph.delete_nodes_from(max_clique) if graph.number_of_nodes()==0: #graph.size() is different, = number_of_edges() return else: self.subPartitionNx(graph)
def subPartitionNx(self, graph):
max_cover_clique_ls = cliques.find_cliques(graph)
max_clique_index = numpy.argmax(map(len, max_cover_clique_ls))
max_clique = max_cover_clique_ls[max_clique_index]
self.clique_ls.append(max_clique)
graph.delete_nodes_from(max_clique)
if graph.number_of_nodes() == 0: # graph.size() is different, = number_of_edges()
return
else:
self.subPartitionNx(graph)
def _processAgpat(self,sub,G):
"""
Workhorse function for packing agpats.
"""
# original 'agpat' edges
oldEdges = [edge
for node in sub
for edge in G.out_edges(node) if edge[2]=='agpat']
# find all possible agpat child pairs
I = NX.Graph()
# all nodes have to be present (some can be lone ones)
for x in oldEdges:
I.add_node(x[1])
for (c,d) in Packer._makePairs([x[1] for x in oldEdges]):
I.add_edge(c,d)
# find all cliques
# (sorted by size)
cliques = C.find_cliques(I)
newLen = reduce(lambda x,y:x+len(y), cliques, 0)
# proceed if new grouping use less edges that the original
# (rearrange edges)
unchanged = True
if newLen<len(oldEdges):
# pick an edge for each child in each clique..
edge_map = {}
for clique in cliques:
for node in clique:
if not edge_map.has_key(node):
edge_map[node] = []
current = [e for e in oldEdges if e[1]==node][0]
edge_map[node].append(current)
oldEdges.remove(current)
# and remove unneeded edges
for (a,b,c) in oldEdges:
self.mapping.append( ('edge-delete',
(a.node,b.node,c),
'_packAgpat') )
G.delete_edge(a,b,c)
# pack each group..
while cliques:
children = cliques.pop(0)
parent = sub.pop(0)
# connect children to the parent
for node in children:
(p1,p2,e) = edge_map[node].pop(0)
self.mapping.append( ('edge-move',
(p1.node,p2.node,e),
(parent.node,node.node,e),
'_packAgpat') )
G.delete_edge(p1,p2,e)
G.add_edge(parent,node,e)
# and remove unneeded parents
for node in sub:
self.mapping.append( ('node-delete',node.node,
'_packAgpat') )
G.delete_node(node)
unchanged = False
return(unchanged)
pdb.set_trace() self.init() node_ls = self.order_nodes(graph) self.sub_max_clique(graph, node_ls, 0) if __name__ == '__main__': import networkx as nx G=nx.Graph() G.add_edge(1,2) G.add_edge(2,3) G.add_edge(2,4) G.add_edge(2,5) G.add_edge(2,6) G.add_edge(4,6) #G.add_edge(7,8) #G.add_edge(3,4) #G.add_edge(3,6) clique_instance = clique(debug=1) clique_instance.max_clique(G) print 'max_clique_size:', clique_instance.max_clique_size print 'max_clique_ls:', clique_instance.max_clique_ls print 'nodes:', G.nodes() print 'degree:', G.degree() nx.draw(G) import pylab print 'the graph looks like this:' pylab.show() from networkx import cliques G_max_clique = cliques.find_cliques(G) print 'cliques found by networkx:', G_max_clique
self.init()
node_ls = self.order_nodes(graph)
self.sub_max_clique(graph, node_ls, 0)
if __name__ == '__main__':
import networkx as nx
G = nx.Graph()
G.add_edge(1, 2)
G.add_edge(2, 3)
G.add_edge(2, 4)
G.add_edge(2, 5)
G.add_edge(2, 6)
G.add_edge(4, 6)
#G.add_edge(7,8)
#G.add_edge(3,4)
#G.add_edge(3,6)
clique_instance = clique(debug=1)
clique_instance.max_clique(G)
print 'max_clique_size:', clique_instance.max_clique_size
print 'max_clique_ls:', clique_instance.max_clique_ls
print 'nodes:', G.nodes()
print 'degree:', G.degree()
nx.draw(G)
import pylab
print 'the graph looks like this:'
pylab.show()
from networkx import cliques
G_max_clique = cliques.find_cliques(G)
print 'cliques found by networkx:', G_max_clique
