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)
print("The greedy algorithm completed in " + str(runTime) + " seconds")
#saveResults(g2, runTime, density)
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)
print("The greedy algorithm completed in " + str(runTime) + " seconds")
#saveResults(g2, runTime, density)
prev_t = dense0.solution.get_values(0)
prev_xijm = dense0.solution.get_values(range(1,len(xijm)+1))
prev_val = dense0.solution.get_objective_value()
printResults.save(dense0)
print "time taken: " + str(iter0_time)
sys.exit()
print "Iteration 0 ("+str(iter0_time)+" sec.): " + str(prev_val)
# initial value of all lamdas are -1.
lamda = [-1]*len(Graphs)
times = []
times.append(iter0_time)
usedNodes = preprocessGreedy.simplePreprocessing(Graphs)
(nodes, LB) = DCSGreedy.getDCS_Greedy(Graphs,usedNodes)
scalar = 1.0
dense = cplex.Cplex("dense.lp")
j = 0
while(j<5):
#remove all output from cplex:
dense.set_results_stream(None)
oldlamda = lamda[:]
#calculate (sub)gradients:
grads = []
start = 1
for i in range(0,len(lamda)):
# split up prev_xijm
end = start+len(allEdges[i])
prev_xijm_sum = sum(prev_xijm[start:end])