def synthetic():
b = open('synthetic.csv', 'w')
a = csv.writer(b)
data = [["Data", "k=1", "k=5", "k=25", "k=100"]]
for file_name in ("web-Stanford.txt", "ca-AstroPh.txt",
"soc-LiveJournal1.txt", "cit-Patents.txt"):
file = os.path.dirname(
os.path.abspath(__file__)) + '/graphs/' + file_name
G1 = BuildGraphFromFile(file)
neighbors_dic = InitNeighbors(G1)
times = []
times.append(file_name)
for i in (1, 5, 25, 100):
prunconnected.k = i
time = prunconnected.run(G1, 1000, neighbors_dic, "")[0]
times.append(time)
data.append(times)
G1 = BuildGraphFromFiles("./graphs/twitter")
neighbors_dic = InitNeighbors(G1)
times = []
times.append("twitter")
for i in (1, 5, 25, 100):
prun2.k = i
time = prun2.run(G1, 1000, neighbors_dic, "")
times.append(time)
data.append(times)
a.writerows(data)
b.close()
pretty_file.pretty_file("synthetic.csv",
header=True,
border=True,
delimiter=",",
new_filename="synthetic.txt")
def differentNumberOfResultsWithAllTypes():
b = open('diffrent_number_of_results_for_all_types.csv', 'w')
a = csv.writer(b)
data = [[
"Number of results", "EnumIncExcConnected", "EnumConnected",
"EnumIncExcUnConnected", "EnumUnConnected"
]]
print "Building a random graph with 1000000 nodes and 10000000 edges."
G1 = snap.GenRndGnm(snap.PUNGraph, 1000000, 10 * 1000000)
neighbors_dic = InitNeighbors(G1)
for i in (1, 10, 100, 1000, 10000):
times = []
num_of_nodes = 1000000
prunconnected.k = 5
time1 = prunconnected.run(G1, i, neighbors_dic, "")[0]
noprun.k = 5
time2 = noprun.run(G1, i, neighbors_dic)
prun2.k = 5
time3 = prun2.run(G1, i, neighbors_dic, "")
noprun.k = 5
time4 = noprun.run(G1, i, neighbors_dic)
data.append([i, time1, time2, time3, time4])
a.writerows(data)
b.close()
pretty_file.pretty_file(
"diffrent_number_of_results_for_all_types.csv",
header=True,
border=True,
delimiter=",",
new_filename="diffrent_number_of_results_for_all_types.txt")
def differentNumberOfNodesEnumIncExc():
b = open('diffrent_number_of_nodes.csv', 'w')
a = csv.writer(b)
data = [["Number of nodes", "EnumIncExc"]]
for i in (1, 10, 100, 1000):
times = []
num_of_nodes = i * 1000
times.append(num_of_nodes)
print "Building a random graph with %s nodes and %s edges." % (
num_of_nodes, 10 * num_of_nodes)
G1 = snap.GenRndGnm(snap.PUNGraph, num_of_nodes, 10 * num_of_nodes)
neighbors_dic = InitNeighbors(G1)
prunconnected.k = 5
time = prunconnected.run(G1, 1000, neighbors_dic, "")[0]
times.append(time)
data.append(times)
a.writerows(data)
b.close()
pretty_file.pretty_file("diffrent_number_of_nodes.csv",
header=True,
border=True,
delimiter=",",
new_filename="diffrent_number_of_nodes.txt")
print "Results can be found in: diffrent_number_of_nodes.csv"
def find_kplex(G1):
import prunning
neighbors_dic = InitNeighbors(G1)
print "Graph is ready"
if (args.type == "unconnected" or args.type == "all"):
prunning.k = args.k
prunning.run(G1, args.num_of_kplex, neighbors_dic,
args.output + "_unconnected")
if (args.type == "connected" or args.type == "all"):
prunconnected.k = args.k
result = prunconnected.run(G1, args.num_of_kplex, neighbors_dic,
args.output + "_connected")
def differentNumberOfEdgesEnumIncExc():
b = open('diffrent_number_of_edges.csv', 'w')
a = csv.writer(b)
data = [["Number of edges", "EnumIncExc"]]
for i in (1000, 10000, 100000):
times = []
num_of_edges = i * 1000
print "Building a random graph with 1000000 nodes and %s edges." % num_of_edges
G1 = snap.GenRndGnm(snap.PUNGraph, 1000000, num_of_edges)
neighbors_dic = InitNeighbors(G1)
print "Graph is ready"
prunconnected.k = 5
time1 = prunconnected.run(G1, 1000, neighbors_dic, "")[0]
data.append([num_of_edges, time1])
a.writerows(data)
b.close()
pretty_file.pretty_file("diffrent_number_of_edges.csv",
header=True,
border=True,
delimiter=",",
new_filename="diffrent_number_of_edges.txt")
def differentNumberOfKEnumIncExc():
import noprun
#import noprunun2
b = open('diffrent_number_of_k.csv', 'w')
a = csv.writer(b)
data = [["k", "EnumIncExc"]]
print "Building a random graph with 1000000 nodes and 10000000 edges."
G1 = snap.GenRndGnm(snap.PUNGraph, 1000000, 10 * 1000000)
neighbors_dic = InitNeighbors(G1)
for i in (1, 5, 25, 100):
times = []
num_of_nodes = 1000000
prunconnected.k = i
time1 = prunconnected.run(G1, 1000, neighbors_dic, "")[0]
data.append(["k = %s" % i, time1])
a.writerows(data)
b.close()
pretty_file.pretty_file("diffrent_number_of_k.csv",
header=True,
border=True,
delimiter=",",
new_filename="diffrent_number_of_k.txt")
