Python generate Examples

Example #1

File: loop_several_noise.py Project: karthi2016/dynamic_dense_subgraph

best_intervals = []
nodesInCom = 5
truth = []
for i in xrange(number_of_communities):
    truth.append(set(range(i*nodesInCom,(i+1)*nodesInCom)))

noise = 0.5
while noise < 6.1:
    noise += 0.5
    avgBack = []
    precGr, precBi = [], []
    recallGr, recallBi = [], []
    #FmGr, FmBi = {},{}
    for ind in xrange(0,n):
        nodes, edges = [],[]
        edgesTS, avg_back, _ = generate.generate(k, B, number_of_communities, noise, nodesInCom-1, nodesInCom)
        avgBack.append(avg_back)
        edgesTSBi = copy.deepcopy(edgesTS)
        edgesTSGr = copy.deepcopy(edgesTS)
        nodesGr, nodesBi = [], []
        for ind in xrange(0, number_of_communities):        
           
            initIntervals = []    
            #initIntervals.append((st, end))
            initIntervals.append((0, len(edgesTS)))
            #try:
            
            if runMainAlgs == 'grbi': 

                #avg_greedy, _, num_nodes_gr = main.main(outpath, 'greedy', charikar_version, 'unweighted', pics, k, B, edgesTS, nodes, edges, initIntervals, False)
                #nodes_coveredGr, timeIntGr, usedBgr, S, edges_coveredGr = loop_and_short_function.gamble(edgesTSGr, k, B, n, 'gr', nodes, edges, [(0,len(edgesTSGr)-1)])

Example #2

File: loop_noise_inner.py Project: karthi2016/dynamic_dense_subgraph

truth = set(range(0, nodesInCom))
noise = 4.0

innernoise = 1.5

while innernoise < 6.9:

    innernoise += 0.5
    avgBack = []
    precGr, precBi = [], []
    recallGr, recallBi = [], []
    #FmGr, FmBi = {},{}
    for ind in xrange(0, n):

        nodes, edges = [], []
        edgesTS, _, inner_out = generate.generate(k, B, 1, noise, innernoise,
                                                  nodesInCom, 500, 1000)
        print len(edgesTS)
        break
        #i,j = i1[ind], i2[ind]
        #st, end = min(i,j), max(i,j)
        initIntervals = []
        #initIntervals.append((st, end))
        initIntervals.append((0, len(edgesTS)))
        #try:

        if runMainAlgs == 'grbi':
            tic = time.time()
            #avg_greedy, _, num_nodes_gr = main.main(outpath, 'greedy', charikar_version, 'unweighted', pics, k, B, edgesTS, nodes, edges, initIntervals, False)
            nodes_coveredGr, timeIntGr, usedBgr, S, edges_coveredGr = main.main(
                outpath, 'greedy', charikar_version, 'unweighted', pics, k, B,
                edgesTS, nodes, edges, initIntervals, False)

Example #3

nodesInCom = 5
truth = set(range(0, nodesInCom))

noise = 0.5
while noise < 5.9:

    noise += 0.5
    avgBack = []
    precGr, precBi = [], []
    recallGr, recallBi = [], []
    #FmGr, FmBi = {},{}
    for ind in xrange(0, n):

        nodes, edges = [], []
        edgesTS, avg_back, _ = generate.generate(k, B, 1, noise,
                                                 nodesInCom - 1, nodesInCom,
                                                 500, 1000)
        print len(edgesTS)
        #break
        #i,j = i1[ind], i2[ind]
        #st, end = min(i,j), max(i,j)
        initIntervals = []
        #initIntervals.append((st, end))
        initIntervals.append((0, len(edgesTS)))
        #try:

        if runMainAlgs == 'grbi':
            tic = time.time()
            #avg_greedy, _, num_nodes_gr = main.main(outpath, 'greedy', charikar_version, 'unweighted', pics, k, B, edgesTS, nodes, edges, initIntervals, False)
            nodes_coveredGr, timeIntGr, usedBgr, S, edges_coveredGr = main.main(
                outpath, 'greedy', charikar_version, 'unweighted', pics, k, B,

Example #4

    truth.append(set(range(i * nodesInCom, (i + 1) * nodesInCom)))

noise = 4.0

innernoise = 1.5

while innernoise < 7.1:
    innernoise += 0.5
    avgBack = []
    precGr, precBi = [], []
    recallGr, recallBi = [], []
    #FmGr, FmBi = {},{}
    for ind in xrange(0, n):
        nodes, edges = [], []
        edgesTS, _, inner_out = generate.generate(k, B, number_of_communities,
                                                  noise, innernoise,
                                                  nodesInCom)
        avgBack.append(inner_out)
        edgesTSBi = copy.deepcopy(edgesTS)
        edgesTSGr = copy.deepcopy(edgesTS)
        nodesGr, nodesBi = [], []
        for ind in xrange(0, number_of_communities):

            initIntervals = []
            #initIntervals.append((st, end))
            initIntervals.append((0, len(edgesTS)))
            #try:

            if runMainAlgs == 'grbi':

                #avg_greedy, _, num_nodes_gr = main.main(outpath, 'greedy', charikar_version, 'unweighted', pics, k, B, edgesTS, nodes, edges, initIntervals, False)

Example #5

while innernoise < 6.6:

    innernoise += 0.5
    
    #innernoise = 7.0
    avgBack = []
    avgBack = []
    precGr, precBi, precDy = [],[],[]
    recallGr, recallBi, recallDy = [],[],[]
    
    #FmGr, FmBi = {},{}
    for ind in xrange(0,n):
    
        nodes, edges = [],[]
        edgesTS, _, avg_back = generate.generate(k, B, 1, noise, innernoise, nodesInCom, 50, 100)
        print len(edgesTS)
        break
        #print len(edgesTS)
        #i,j = i1[ind], i2[ind]
        #st, end = min(i,j), max(i,j)    
        initIntervals = []    
        #initIntervals.append((st, end))
        initIntervals.append((0, len(edgesTS)))
        #try:
        
        #if runMainAlgs == 'grbi':
        tic = time.time()
        nodes_coveredGr, timeIntGr, usedBgr, S, edges_coveredGr = main.main(outpath, 'greedy', charikar_version, 'unweighted', pics, k, B, edgesTS, nodes, edges, initIntervals, False)
        #print nodes_coveredGr, timeIntGr, usedBgr, edges_coveredGr
        usedBgr = usedBgr.total_seconds()/(60*60*24.0)