def getDCS_Greedy(graphs,nodes):
global numberOfNodes
global numberOfEdges
numberOfNodes = len(nodes)
# Create a table of nodes by degree, to enable faster lookup.
utils.timer()
initLookupTable(graphs)
print("initilization took " + str(utils.timer()))
# Pass 1, to find the subgraph with the highest density.
highestDensity = 0
originalNumberOfNodes = numberOfNodes
while numberOfNodes > 1:
#printProgress("Searching for highest density: ",
# originalGraphs[0].GetNodes(), graphs[0].GetNodes())
currDensity = densityMultiple(graphs)
if (highestDensity < currDensity):
highestDensity = currDensity
optimalNumberOfNodes = numberOfNodes
node = takeSmallestDegree(graphs)
numberOfNodes -= 1
updateLists(graphs, node)
print("first pass took: " + str(utils.timer()))
print("Highest density found: " + str(highestDensity))
# Pass 2, look for the subgraph that has a density equal to highest seen.
numberOfNodes = originalNumberOfNodes
initLookupTable(graphs)
while numberOfNodes > optimalNumberOfNodes:
node = takeSmallestDegree(graphs)
numberOfNodes -=1
updateLists(graphs,node)
nodesInSubGraph = getNodesInSubGraph(nodes)
print("second pass took: " + str(utils.timer()))
print("we found a total number of nodes = " + str(optimalNumberOfNodes))
return (nodesInSubGraph,highestDensity)
def getDCS_Greedy(graphs, nodes):
global numberOfNodes
global numberOfEdges
numberOfNodes = len(nodes)
# Create a table of nodes by degree, to enable faster lookup.
utils.timer()
initLookupTable(graphs)
print("initilization took " + str(utils.timer()))
# Pass 1, to find the subgraph with the highest density.
highestDensity = 0
originalNumberOfNodes = numberOfNodes
while numberOfNodes > 1:
#printProgress("Searching for highest density: ",
# originalGraphs[0].GetNodes(), graphs[0].GetNodes())
currDensity = densityMultiple(graphs)
if (highestDensity < currDensity):
highestDensity = currDensity
optimalNumberOfNodes = numberOfNodes
node = takeSmallestDegree(graphs)
numberOfNodes -= 1
updateLists(graphs, node)
print("first pass took: " + str(utils.timer()))
print("Highest density found: " + str(highestDensity))
# Pass 2, look for the subgraph that has a density equal to highest seen.
numberOfNodes = originalNumberOfNodes
initLookupTable(graphs)
while numberOfNodes > optimalNumberOfNodes:
node = takeSmallestDegree(graphs)
numberOfNodes -= 1
updateLists(graphs, node)
nodesInSubGraph = getNodesInSubGraph(nodes)
print("second pass took: " + str(utils.timer()))
print("we found a total number of nodes = " + str(optimalNumberOfNodes))
return (nodesInSubGraph, highestDensity)
from lib import snap
import sys
import time
from greedy import DCSGreedy, utils, preprocessGreedy
if (len(sys.argv) < 2):
sys.exit("Usage: python " + sys.argv[0] + " <file1> <file2> ...")
utils.timer() # Start the timer.
if (sys.argv[1] == "-d"):
graphs = preprocessGreedy.loadDirGraphs()
else:
graphs = preprocessGreedy.loadGraphs()
print("Imported " + str(len(graphs)) + " graphs in " + utils.timer())
# Don't remove, this isn't the deep preprocessing that takes time.
numberOfNodes = preprocessGreedy.simplePreprocessing(graphs)
# If multiple graphs, do some preprocessing to make sure they are over the same
# set of nodes.
# Make sure all graphs have the same amount of nodes.
# There could be a deeper check here.
print("Preprocessing took " + utils.timer())
startTime = time.clock()
(nodes, density) = DCSGreedy.getDCS_Greedy(graphs, numberOfNodes)
runTime = time.clock() - startTime
utils.saveResults(nodes, str(runTime) + " seconds", density)
# printQuickStats(g2)
from lib import snap
import sys
import time
from greedy import DCSGreedy, utils, preprocessGreedy
if(len(sys.argv) < 2):
sys.exit("Usage: python " + sys.argv[0] + " <file1> <file2> ...")
utils.timer() # Start the timer.
if(sys.argv[1] == "-d"):
graphs = preprocessGreedy.loadDirGraphs()
else:
graphs = preprocessGreedy.loadGraphs()
print("Imported " + str(len(graphs)) + " graphs in " + utils.timer())
# Don't remove, this isn't the deep preprocessing that takes time.
numberOfNodes = preprocessGreedy.simplePreprocessing(graphs)
# If multiple graphs, do some preprocessing to make sure they are over the same
# set of nodes.
# Make sure all graphs have the same amount of nodes.
# There could be a deeper check here.
print("Preprocessing took " + utils.timer())
startTime = time.clock()
(nodes,density) = DCSGreedy.getDCS_Greedy(graphs,numberOfNodes)
runTime = time.clock()-startTime
utils.saveResults(nodes,str(runTime) + " seconds",density)
# printQuickStats(g2)