def setUp(self):
self.graphname = os.getenv('PYLIBBVG_TESTGRAPH')
if self.graphname is None:
self.graphname = '../data/harvard500'
smatfile = open(self.graphname + '.smat', 'rt')
header = smatfile.readline().split()
self.check_nnodes = int(header[0])
self.check_nedges = int(header[2])
self.assertEqual(self.check_nnodes,
int(header[1])) # make sure it's square
self.checkgraph = {}
for i in xrange(0, self.check_nnodes):
self.checkgraph[i] = set()
for line in smatfile:
parts = line.split()
src = int(parts[0])
dst = int(parts[1])
#if src not in self.checkgraph:
# self.checkgraph[src] = set()
assert (dst not in self.checkgraph[src]) # no duplicateedges
self.checkgraph[src].add(dst)
smatfile.close()
# load with random access, in-memory streaming, and disk-streaming
self.bvg = bvg.BVGraph(self.graphname, 1)
self.bvgstream = bvg.BVGraph(self.graphname, 0)
self.bvgdisk = bvg.BVGraph(self.graphname, -1)
def load_twitter_graph():
print "Loading graph ..."
start_time = time.time()
twitter_graph = bvg.BVGraph('../dataset/twitter-2010-symm', 1)
print " ... done! %.1f seconds" % (time.time() - start_time)
time.sleep(0.75)
print "\n"
print "Twitter graph has"
print "nodes: %i" % (twitter_graph.nverts)
print "edges: %i" % (twitter_graph.nedges)
time.sleep(0.75)
print "\nt = 15"
print "eps = 10^-4\n"
time.sleep(0.75)
return twitter_graph
#!/usr/bin/env python
import bvg as bvg
import networkx as nx
G = bvg.BVGraph('../data/harvard500', 1)
Gcc = bvg.BVGraph('../data/harvard500-cc', 1)
nx.degree(G, 1)
nx.strongly_connected_components(G)
#g = nx.Graph()
# centrality
nx.degree_centrality(G)
nx.out_degree_centrality(G)
nx.betweenness_centrality(G)
nx.closeness_centrality(G)
nx.eigenvector_centrality(G)
# clique
#list(nx.find_cliques(G))
#list(nx.make_max_clique_graph(G))
#list(nx.make_clique_bipartite(G))
#nx.graph_clique_number(G)
#nx.graph_number_of_cliques(G)
# components
nx.is_strongly_connected(G)
nx.number_strongly_connected_components(G)
scc = nx.strongly_connected_components(G)
nx.strongly_connected_components_recursive(G)
nx.condensation(G, scc)
#!/usr/bin/python
import bvg
import sys
data = sys.argv[1]
G = bvg.BVGraph(data, 0) # load with offset step = 0 (iteration)
print('#nodes = ' + str(G.nverts) + ', #edges = ' + str(G.nedges))
edges_and_degrees = G.edges_and_degrees()
const = 10000000001
count = 0
for (src, dst, degree) in edges_and_degrees:
count += 1
if degree == 1 and dst + src != const:
print('error: reading 64bit bvgraph, src = ' + str(src) + ', dst = ' +
str(dst))
break
elif count == 1000:
print('Python: testing 64-bit bvgraph sequential read ... passed!')
break
import collections
import time
import random
def compute_psis(N, t):
psis = {}
psis[N] = 1.
for i in xrange(N - 1, 0, -1):
psis[i] = psis[i + 1] * t / (float(i + 1.)) + 1.
return psis
start = time.time()
print "Loading graph ..."
G = bvg.BVGraph('twitter-2010-symm', 1)
print " ... done! %.1f seconds" % (time.time() - start)
time.sleep(0.75)
print "\n"
print "Twitter graph has"
print "nodes: %i" % (G.nverts)
print "edges: %i" % (G.nedges)
time.sleep(0.75)
print "\nt = 15"
print "eps = 10^-4\n"
time.sleep(0.75)
Gvol = G.nedges
## Setup parameters that can be computed automatically
N = 47 # see paper for how to set this automatically
#!/usr/bin/python
import bvg
import sys
## new an object without loading graph
#G = bvg.Graph()
## new an object with graph loaded
data = sys.argv[1]
G1 = bvg.BVGraph(data, 0) # load with offset step = 0 (iteration)
G2 = bvg.BVGraph(data, 1) # load with offset step = 1 (random access)
node = int(sys.argv[2]) # node is given
## test successors and degree
a = G2.successors(node)
for v in a:
print v
print 'Degree = ' + str(G2.out_degree(node))
## test direct access to number of nodes and edges
print G1.nverts
print G1.nedges
## test iteration in G
for v in G1:
print v
# src = v.curr
# deg = v.degree
# print 'src = ' + str(src) + ', degree = ' + str(deg)
# for neigh in v: