In [1]:

    

import os
from shutil import copyfile
import subprocess
from save_embedded_graph27 import main_binary as embed_main
from spearmint_ghsom import main as ghsom_main
import numpy as np
import pickle
from time import time

def save_obj(obj, name):
    with open(name + '.pkl', 'wb') as f:
        pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)

def load_obj(name):
    with open(name + '.pkl', 'rb') as f:
        return pickle.load(f)

#root dir
os.chdir("C:\Miniconda3\Jupyter\GHSOM_simplex_dsd")

#save directory
dir = os.path.abspath("parameter_tests_edges")

#number of times to repeat
num_repeats = 30

#number of nodes in the graph
N = 64


#make save directory
if not os.path.isdir(dir):
    os.mkdir(dir)

#change to dir
os.chdir(dir)    

#network file names -- output of network generator
network = "network.dat"
first_level = "community.dat"

#community labels
labels = 'firstlevelcommunity'

#mixing factors
mu = 0.1

num_edges_ls = [256, 512, 1024]
parameter_settings = [0.5, 0.6, 0.7, 0.8, 0.9, 1][::-1]

overall_nmi_scores = np.zeros((len(num_edges_ls), len(parameter_settings)))

for i in range(len(num_edges_ls)):
    
    #number of edges
    num_edges = num_edges_ls[i]
    
    #create directory
    dir_string = os.path.join(dir, str(num_edges))
    if not os.path.isdir(dir_string):
        os.mkdir(dir_string)
    
    #change working directory    
    os.chdir(dir_string)
    
    for j in range(len(parameter_settings)):
        
        #setting fo e_sg
        p = parameter_settings[j]
        
        #ghsom parameters
        params = {'w': 0.0001,
                 'eta': 0.0001,
                 'sigma': 1,
                  'e_sg': p,
                 'e_en': 0.8}
    
        #create directory
        dir_string_p = os.path.join(dir_string, str(p))
        if not os.path.isdir(dir_string_p):
            os.mkdir(dir_string_p)
    
        #change working directory    
        os.chdir(dir_string_p)
        
        if os.path.isfile('nmi_scores.csv'):
            print 'already completed {}/{}, loading scores and continuing'.format(k1, p)
            nmi_scores = np.genfromtxt('nmi_scores.csv', delimiter=',')
            overall_nmi_scores[i,j] = np.mean(nmi_scores, axis=0)
            continue
        
        #copy executable
        ex = "benchmark.exe"   
        if not os.path.isfile(ex):

            source = "C:\\Users\\davem\\Documents\\PhD\\Benchmark Graph Generators\\binary_networks\\benchmark.exe"
            copyfile(source, ex)

        #record NMI scores
        if not os.path.isfile('nmi_scores.pkl'):
            print 'creating new nmi scores array'
            nmi_scores = np.zeros(num_repeats)
        else:
            print 'loading nmi score progress'
            nmi_scores = load_obj('nmi_scores')

        #record running times
        if not os.path.isfile('running_times.pkl'):
            print 'creating new running time array'
            running_times = np.zeros(num_repeats)
        else:
            print 'loading running time progress'
            running_times = load_obj('running_times')
            
        print

        #generate networks
        for r in range(1, num_repeats+1):
            
            #number of communities
            num_communities = np.random.randint(1,5)

            #number of nodes in micro community
            minc = np.floor(float(N) / num_communities)
            maxc = np.ceil(float(N) / num_communities)

            #average number of edges
            k = float(num_edges) / N

            #max number of edges
            maxk = 2 * k
            
            #make benchmark parameter file
            filename = "benchmark_flags_{}_{}_{}.dat".format(num_edges,p,r)
            if not os.path.isfile(filename):
                print 'number of edges: {}'.format(num_edges)
                print 'number of communities: {}'.format(num_communities)
                print '-N {} -k {} -maxk {} -minc {} -maxc {} -mu {}'.format(N, k, maxk, minc, maxc, mu)
                with open(filename,"w") as f:
                    f.write("-N {} -k {} -maxk {} -minc {} -maxc {} -mu {}".format(N, k, maxk, minc, maxc, mu))
                print 'written flag file: {}'.format(filename)


            #cmd strings
            change_dir_cmd = "cd {}".format(dir_string_p)
            generate_network_cmd = "benchmark -f {}".format(filename)

            #output of cmd
            output_file = open("cmd_output.out", 'w')

            network_rename = "{}_{}".format(r,network)
            first_level_rename = "{}_{}".format(r,first_level)
            gml_filename = 'embedded_network_{}.gml'.format(r)

            if not os.path.isfile(network_rename):

                process = subprocess.Popen(change_dir_cmd + " && " + generate_network_cmd, 
                                        stdout=output_file, 
                                        stderr=output_file, 
                                        shell=True)
                process.wait()
                
                print 'generated graph {}'.format(r)

                os.rename(network, network_rename)
                os.rename(first_level, first_level_rename)
                
                print 'renamed graph {}'.format(r)

            if not os.path.isfile(gml_filename):

                ##embed graph
                embed_main(network_rename, first_level_rename)

                print 'embedded graph {} as {} in {}'.format(r, gml_filename, os.getcwd())

            ##score for this network
            if not np.all(nmi_scores[r-1]):

                start_time = time()

                print 'starting ghsom for: {}/{}/{}'.format(num_edges, p, gml_filename)
                nmi_score, communities_detected = ghsom_main(params, gml_filename, labels)
                nmi_scores[r-1] = nmi_score

                running_time = time() - start_time
                print 'running time of algorithm: {}'.format(running_time)
                running_times[r-1] = running_time

                #save
                save_obj(nmi_scores, 'nmi_scores')
                save_obj(running_times, 'running_times')

                print 'saved nmi score for network {}: {}'.format(gml_filename, nmi_score)
                print

        ##output nmi scores to csv file
        print 'writing nmi scores and running times to file'
        np.savetxt('nmi_scores.csv',nmi_scores,delimiter=',')
        np.savetxt('running_times.csv',running_times,delimiter=',')
        print
        
        #odd to overall list
        overall_nmi_scores[i,j] = np.mean(nmi_scores, axis=0)
    
print 'DONE'

print 'OVERALL NMI SCORES'
print overall_nmi_scores


    

    




creating new nmi scores array
creating new running time array

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_1.gml
running time of algorithm: 79.2119998932
saved nmi score for network embedded_network_1.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_1_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_2.gml
running time of algorithm: 49.7569999695
saved nmi score for network embedded_network_2.gml: [ -3.33066907e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_3.gml
running time of algorithm: 78.368999958
saved nmi score for network embedded_network_3.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_1_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_4.gml
running time of algorithm: 50.2279999256
saved nmi score for network embedded_network_4.gml: [ 1.]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_1_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_5.gml
running time of algorithm: 79.6129999161
saved nmi score for network embedded_network_5.gml: [ 0.51492773]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_6.gml
running time of algorithm: 78.3570001125
saved nmi score for network embedded_network_6.gml: [ 0.77167215]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_1_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_7.gml
running time of algorithm: 79.0110001564
saved nmi score for network embedded_network_7.gml: [ -1.66533454e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_1_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_8.gml
running time of algorithm: 73.1050000191
saved nmi score for network embedded_network_8.gml: [ 0.76228442]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_1_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_9.gml
running time of algorithm: 78.9559998512
saved nmi score for network embedded_network_9.gml: [ -6.66133815e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_1_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_10.gml
running time of algorithm: 79.4759998322
saved nmi score for network embedded_network_10.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_11.gml
running time of algorithm: 49.6809999943
saved nmi score for network embedded_network_11.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_12.gml
running time of algorithm: 49.6180000305
saved nmi score for network embedded_network_12.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_1_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_13.gml
running time of algorithm: 78.498000145
saved nmi score for network embedded_network_13.gml: [ 1.]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_1_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_14.gml
running time of algorithm: 78.1349999905
saved nmi score for network embedded_network_14.gml: [ -3.33066907e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_15.gml
running time of algorithm: 78.5209999084
saved nmi score for network embedded_network_15.gml: [ 0.62354]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_1_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_16.gml
running time of algorithm: 79.4379999638
saved nmi score for network embedded_network_16.gml: [ -6.66133815e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_1_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_17.gml
running time of algorithm: 61.5659999847
saved nmi score for network embedded_network_17.gml: [ 0.58785673]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_1_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_18.gml
running time of algorithm: 49.3389999866
saved nmi score for network embedded_network_18.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_1_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_19.gml
running time of algorithm: 78.2869999409
saved nmi score for network embedded_network_19.gml: [ 1.]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_1_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_20.gml
running time of algorithm: 78.0959999561
saved nmi score for network embedded_network_20.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_1_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_21.gml
running time of algorithm: 49.8180000782
saved nmi score for network embedded_network_21.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_22.gml
running time of algorithm: 49.6890001297
saved nmi score for network embedded_network_22.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_1_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_23.gml
running time of algorithm: 49.8280000687
saved nmi score for network embedded_network_23.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_1_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_24.gml
running time of algorithm: 49.6610000134
saved nmi score for network embedded_network_24.gml: [ -3.33066907e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_25.gml
running time of algorithm: 61.7380001545
saved nmi score for network embedded_network_25.gml: [ 0.79937768]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_26.gml
running time of algorithm: 70.1559998989
saved nmi score for network embedded_network_26.gml: [ 0.73059667]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_1_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_27.gml
running time of algorithm: 49.5610001087
saved nmi score for network embedded_network_27.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_1_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_28.gml
running time of algorithm: 61.8350000381
saved nmi score for network embedded_network_28.gml: [ 0.53096952]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_29.gml
running time of algorithm: 69.9379999638
saved nmi score for network embedded_network_29.gml: [ 0.89930114]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_1_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\1
starting ghsom for: 256/1/embedded_network_30.gml
running time of algorithm: 70.2269999981
saved nmi score for network embedded_network_30.gml: [ 0.73059667]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_1.gml
running time of algorithm: 72.2179999352
saved nmi score for network embedded_network_1.gml: [ 0.57954983]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_2.gml
running time of algorithm: 107.812000036
saved nmi score for network embedded_network_2.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_3.gml
running time of algorithm: 61.8090000153
saved nmi score for network embedded_network_3.gml: [ 0.58669068]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_4.gml
running time of algorithm: 61.7899999619
saved nmi score for network embedded_network_4.gml: [ 0.58669068]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_5.gml
running time of algorithm: 78.2029998302
saved nmi score for network embedded_network_5.gml: [ 0.6472116]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_6.gml
running time of algorithm: 71.628000021
saved nmi score for network embedded_network_6.gml: [ 0.76228442]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_7.gml
running time of algorithm: 71.9309999943
saved nmi score for network embedded_network_7.gml: [ 0.60822761]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_8.gml
running time of algorithm: 77.8650000095
saved nmi score for network embedded_network_8.gml: [ -7.21644966e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_9.gml
running time of algorithm: 113.204999924
saved nmi score for network embedded_network_9.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_10.gml
running time of algorithm: 71.0750000477
saved nmi score for network embedded_network_10.gml: [ 0.77167215]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_11.gml
running time of algorithm: 71.9380002022
saved nmi score for network embedded_network_11.gml: [ 0.36323764]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_12.gml
running time of algorithm: 118.588000059
saved nmi score for network embedded_network_12.gml: [ -2.22044605e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_13.gml
running time of algorithm: 113.784999847
saved nmi score for network embedded_network_13.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_14.gml
running time of algorithm: 69.8090000153
saved nmi score for network embedded_network_14.gml: [ 0.58785673]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_15.gml
running time of algorithm: 78.5429999828
saved nmi score for network embedded_network_15.gml: [ 0.57903808]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_16.gml
running time of algorithm: 70.8009998798
saved nmi score for network embedded_network_16.gml: [ 0.42982425]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_17.gml
running time of algorithm: 61.6319999695
saved nmi score for network embedded_network_17.gml: [ 0.58679478]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_18.gml
running time of algorithm: 83.135999918
saved nmi score for network embedded_network_18.gml: [ -1.66533454e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_19.gml
running time of algorithm: 71.6930000782
saved nmi score for network embedded_network_19.gml: [ 0.34204958]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_20.gml
running time of algorithm: 70.0989999771
saved nmi score for network embedded_network_20.gml: [ 0.89930114]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_21.gml
running time of algorithm: 67.6760001183
saved nmi score for network embedded_network_21.gml: [ 0.89350236]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_22.gml
running time of algorithm: 78.3429999352
saved nmi score for network embedded_network_22.gml: [ 0.89930114]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_23.gml
running time of algorithm: 69.2760000229
saved nmi score for network embedded_network_23.gml: [ 0.48761676]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_24.gml
running time of algorithm: 73.251999855
saved nmi score for network embedded_network_24.gml: [ 0.49612391]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_25.gml
running time of algorithm: 92.4990000725
saved nmi score for network embedded_network_25.gml: [ 0.37482432]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_26.gml
running time of algorithm: 72.251999855
saved nmi score for network embedded_network_26.gml: [ 0.50629011]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_27.gml
running time of algorithm: 70.1380000114
saved nmi score for network embedded_network_27.gml: [ 0.60643184]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_28.gml
running time of algorithm: 70.1380000114
saved nmi score for network embedded_network_28.gml: [ 0.89930114]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_29.gml
running time of algorithm: 71.4769999981
saved nmi score for network embedded_network_29.gml: [ 0.41898669]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.9_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.9
starting ghsom for: 256/0.9/embedded_network_30.gml
running time of algorithm: 118.916000128
saved nmi score for network embedded_network_30.gml: [ -2.77555756e-06]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_1.gml
running time of algorithm: 155.081999779
saved nmi score for network embedded_network_1.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_2.gml
running time of algorithm: 107.983999968
saved nmi score for network embedded_network_2.gml: [ -1.66533454e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_3.gml
running time of algorithm: 88.0230000019
saved nmi score for network embedded_network_3.gml: [ 0.66675594]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_4.gml
running time of algorithm: 222.638999939
saved nmi score for network embedded_network_4.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_5.gml
running time of algorithm: 102.044000149
saved nmi score for network embedded_network_5.gml: [ 0.63864421]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_6.gml
running time of algorithm: 101.53000021
saved nmi score for network embedded_network_6.gml: [ 0.77773659]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_7.gml
running time of algorithm: 93.8619999886
saved nmi score for network embedded_network_7.gml: [ 0.52585145]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_8.gml
running time of algorithm: 116.912999868
saved nmi score for network embedded_network_8.gml: [ 0.56700531]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_9.gml
running time of algorithm: 184.898999929
saved nmi score for network embedded_network_9.gml: [ -3.33066907e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_10.gml
running time of algorithm: 85.1589999199
saved nmi score for network embedded_network_10.gml: [ 0.6472116]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_11.gml
running time of algorithm: 104.974999905
saved nmi score for network embedded_network_11.gml: [ 0.55309039]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_12.gml
running time of algorithm: 101.976999998
saved nmi score for network embedded_network_12.gml: [ 0.6791461]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_13.gml
running time of algorithm: 84.2269999981
saved nmi score for network embedded_network_13.gml: [ 0.34566801]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_14.gml
running time of algorithm: 102.325999975
saved nmi score for network embedded_network_14.gml: [ 0.94210793]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_15.gml
running time of algorithm: 184.182999849
saved nmi score for network embedded_network_15.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_16.gml
running time of algorithm: 174.812000036
saved nmi score for network embedded_network_16.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_17.gml
running time of algorithm: 61.4500000477
saved nmi score for network embedded_network_17.gml: [ 0.58679478]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_18.gml
running time of algorithm: 61.6199998856
saved nmi score for network embedded_network_18.gml: [ 0.6472116]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_19.gml
running time of algorithm: 107.181999922
saved nmi score for network embedded_network_19.gml: [ 0.48893353]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_20.gml
running time of algorithm: 86.5250000954
saved nmi score for network embedded_network_20.gml: [ 0.54864714]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_21.gml
running time of algorithm: 107.580999851
saved nmi score for network embedded_network_21.gml: [ 0.56654029]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_22.gml
running time of algorithm: 121.11500001
saved nmi score for network embedded_network_22.gml: [ 0.63057221]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_23.gml
running time of algorithm: 155.467000008
saved nmi score for network embedded_network_23.gml: [ -2.22044605e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_24.gml
running time of algorithm: 109.504999876
saved nmi score for network embedded_network_24.gml: [ 0.70821192]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_25.gml
running time of algorithm: 90.9739999771
saved nmi score for network embedded_network_25.gml: [ 0.62186393]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_26.gml
running time of algorithm: 90.5119998455
saved nmi score for network embedded_network_26.gml: [ 0.64743951]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_27.gml
running time of algorithm: 168.828999996
saved nmi score for network embedded_network_27.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_28.gml
running time of algorithm: 62.3289999962
saved nmi score for network embedded_network_28.gml: [ 0.43666864]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_29.gml
running time of algorithm: 89.7479999065
saved nmi score for network embedded_network_29.gml: [ 0.49225339]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.8_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.8
starting ghsom for: 256/0.8/embedded_network_30.gml
running time of algorithm: 62.0889999866
saved nmi score for network embedded_network_30.gml: [ 0.46626624]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_1.gml
running time of algorithm: 101.545000076
saved nmi score for network embedded_network_1.gml: [ 0.64760226]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_2.gml
running time of algorithm: 221.09100008
saved nmi score for network embedded_network_2.gml: [ 0.56811972]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_3.gml
running time of algorithm: 299.17200017
saved nmi score for network embedded_network_3.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_4.gml
running time of algorithm: 385.718999863
saved nmi score for network embedded_network_4.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_5.gml
running time of algorithm: 102.105999947
saved nmi score for network embedded_network_5.gml: [ 0.46591616]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_6.gml
running time of algorithm: 219.740999937
saved nmi score for network embedded_network_6.gml: [ 0.52111144]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_7.gml
running time of algorithm: 395.384000063
saved nmi score for network embedded_network_7.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_8.gml
running time of algorithm: 154.917000055
saved nmi score for network embedded_network_8.gml: [ 0.58026067]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_9.gml
running time of algorithm: 102.213999987
saved nmi score for network embedded_network_9.gml: [ 0.94245004]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_10.gml
running time of algorithm: 387.532000065
saved nmi score for network embedded_network_10.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_11.gml
running time of algorithm: 101.796000004
saved nmi score for network embedded_network_11.gml: [ 0.90393421]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_12.gml
running time of algorithm: 220.380000114
saved nmi score for network embedded_network_12.gml: [ 0.5465292]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_13.gml
running time of algorithm: 102.51699996
saved nmi score for network embedded_network_13.gml: [ 0.8837941]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_14.gml
running time of algorithm: 101.888000011
saved nmi score for network embedded_network_14.gml: [ 0.72574161]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_15.gml
running time of algorithm: 235.631999969
saved nmi score for network embedded_network_15.gml: [ -4.99600361e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_16.gml
running time of algorithm: 220.906000137
saved nmi score for network embedded_network_16.gml: [ 0.3413619]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_17.gml
running time of algorithm: 102.421000004
saved nmi score for network embedded_network_17.gml: [ 0.77245209]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_18.gml
running time of algorithm: 220.350000143
saved nmi score for network embedded_network_18.gml: [ 0.46135522]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_19.gml
running time of algorithm: 219.696000099
saved nmi score for network embedded_network_19.gml: [ -5.55111512e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_20.gml
running time of algorithm: 307.968999863
saved nmi score for network embedded_network_20.gml: [ -4.99600361e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_21.gml
running time of algorithm: 219.685000181
saved nmi score for network embedded_network_21.gml: [ 0.42338969]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_22.gml
running time of algorithm: 101.934999943
saved nmi score for network embedded_network_22.gml: [ 0.56156415]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_23.gml
running time of algorithm: 220.390000105
saved nmi score for network embedded_network_23.gml: [ -4.44089210e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_24.gml
running time of algorithm: 297.496000051
saved nmi score for network embedded_network_24.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_25.gml
running time of algorithm: 102.163000107
saved nmi score for network embedded_network_25.gml: [ 0.82177502]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_26.gml
running time of algorithm: 122.392000198
saved nmi score for network embedded_network_26.gml: [ 0.70493618]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_27.gml
running time of algorithm: 102.385000229
saved nmi score for network embedded_network_27.gml: [ 0.65854106]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_28.gml
running time of algorithm: 155.325000048
saved nmi score for network embedded_network_28.gml: [ 0.54865915]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_29.gml
running time of algorithm: 321.710000038
saved nmi score for network embedded_network_29.gml: [ -5.55111512e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.7_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.7
starting ghsom for: 256/0.7/embedded_network_30.gml
running time of algorithm: 396.965999842
saved nmi score for network embedded_network_30.gml: [ -3.88578059e-06]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_1.gml
running time of algorithm: 390.364000082
saved nmi score for network embedded_network_1.gml: [ -4.99600361e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_2.gml
running time of algorithm: 154.664000034
saved nmi score for network embedded_network_2.gml: [ 0.80883855]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_3.gml
running time of algorithm: 388.119999886
saved nmi score for network embedded_network_3.gml: [ 0.40820077]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_4.gml
running time of algorithm: 102.110999823
saved nmi score for network embedded_network_4.gml: [ 0.67292368]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_5.gml
running time of algorithm: 220.277999878
saved nmi score for network embedded_network_5.gml: [ 0.88202512]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_6.gml
running time of algorithm: 739.871999979
saved nmi score for network embedded_network_6.gml: [ -2.22044605e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_7.gml
running time of algorithm: 388.113000154
saved nmi score for network embedded_network_7.gml: [ 0.43852791]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_8.gml
running time of algorithm: 154.96600008
saved nmi score for network embedded_network_8.gml: [ 0.88869251]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_9.gml
running time of algorithm: 387.48300004
saved nmi score for network embedded_network_9.gml: [ 0.34547741]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_10.gml
running time of algorithm: 738.245000124
saved nmi score for network embedded_network_10.gml: [ -2.22044605e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_11.gml
running time of algorithm: 491.687000036
saved nmi score for network embedded_network_11.gml: [ 0.44676591]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_12.gml
running time of algorithm: 607.01699996
saved nmi score for network embedded_network_12.gml: [ -2.22044605e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_13.gml
running time of algorithm: 390.400999784
saved nmi score for network embedded_network_13.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_14.gml
running time of algorithm: 508.383999825
saved nmi score for network embedded_network_14.gml: [ -3.88578059e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_15.gml
running time of algorithm: 389.153000116
saved nmi score for network embedded_network_15.gml: [ 0.37437887]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_16.gml
running time of algorithm: 490.857000113
saved nmi score for network embedded_network_16.gml: [ -3.33066907e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_17.gml
running time of algorithm: 154.527999878
saved nmi score for network embedded_network_17.gml: [ 0.68276727]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_18.gml
running time of algorithm: 493.026000023
saved nmi score for network embedded_network_18.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_19.gml
running time of algorithm: 155.264999866
saved nmi score for network embedded_network_19.gml: [ 0.91529524]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_20.gml
running time of algorithm: 388.86500001
saved nmi score for network embedded_network_20.gml: [ 0.4640391]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_21.gml
running time of algorithm: 391.652999878
saved nmi score for network embedded_network_21.gml: [ 0.54804541]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_22.gml
running time of algorithm: 619.06099987
saved nmi score for network embedded_network_22.gml: [ -3.33066907e-06]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_23.gml
running time of algorithm: 298.532999992
saved nmi score for network embedded_network_23.gml: [ 0.54437535]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_24.gml
running time of algorithm: 155.125
saved nmi score for network embedded_network_24.gml: [ 0.9152575]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_25.gml
running time of algorithm: 388.23300004
saved nmi score for network embedded_network_25.gml: [ 0.46496833]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_26.gml
running time of algorithm: 155.211000204
saved nmi score for network embedded_network_26.gml: [ 0.78836225]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_27.gml
running time of algorithm: 879.781000137
saved nmi score for network embedded_network_27.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_28.gml
running time of algorithm: 61.9370000362
saved nmi score for network embedded_network_28.gml: [ 0.49612391]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_29.gml
running time of algorithm: 155.238999844
saved nmi score for network embedded_network_29.gml: [ 0.9152575]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.6_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.6
starting ghsom for: 256/0.6/embedded_network_30.gml
running time of algorithm: 245.141000032
saved nmi score for network embedded_network_30.gml: [ 0.61294752]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_1.gml
running time of algorithm: 296.426000118
saved nmi score for network embedded_network_1.gml: [ 0.67830392]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_2.gml
running time of algorithm: 219.244000196
saved nmi score for network embedded_network_2.gml: [ 0.86500593]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_3.gml
running time of algorithm: 386.649999857
saved nmi score for network embedded_network_3.gml: [ 0.46640931]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_4.gml
running time of algorithm: 494.680000067
saved nmi score for network embedded_network_4.gml: [ 0.4739422]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_5.gml
running time of algorithm: 219.200999975
saved nmi score for network embedded_network_5.gml: [ 0.88557045]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_6.gml
running time of algorithm: 606.893000126
saved nmi score for network embedded_network_6.gml: [ 0.41678708]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_7.gml
running time of algorithm: 607.934999943
saved nmi score for network embedded_network_7.gml: [ 0.40205372]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_8.gml
running time of algorithm: 608.529000044
saved nmi score for network embedded_network_8.gml: [ 0.50668906]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_9.gml
running time of algorithm: 490.11500001
saved nmi score for network embedded_network_9.gml: [ 0.59591484]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_10.gml
running time of algorithm: 296.417000055
saved nmi score for network embedded_network_10.gml: [ 0.78190199]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_11.gml
running time of algorithm: 1402.13400006
saved nmi score for network embedded_network_11.gml: [ -2.22044605e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_12.gml
running time of algorithm: 882.627000093
saved nmi score for network embedded_network_12.gml: [ 0.44822599]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_13.gml
running time of algorithm: 390.993000031
saved nmi score for network embedded_network_13.gml: [ 0.61351901]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_14.gml
running time of algorithm: 297.929000139
saved nmi score for network embedded_network_14.gml: [ 0.87339981]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_15.gml
running time of algorithm: 881.273000002
saved nmi score for network embedded_network_15.gml: [ 0.40650606]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_16.gml
running time of algorithm: 1035.50999999
saved nmi score for network embedded_network_16.gml: [ -2.22044605e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_17.gml
running time of algorithm: 1220.21000004
saved nmi score for network embedded_network_17.gml: [ -1.66533454e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_18.gml
running time of algorithm: 154.927999973
saved nmi score for network embedded_network_18.gml: [ 0.84648561]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_19.gml
running time of algorithm: 742.859999895
saved nmi score for network embedded_network_19.gml: [ 0.38664245]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_20.gml
running time of algorithm: 493.344000101
saved nmi score for network embedded_network_20.gml: [ 0.68390847]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_21.gml
running time of algorithm: 740.003000021
saved nmi score for network embedded_network_21.gml: [ 0.48928963]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_22.gml
running time of algorithm: 387.548000097
saved nmi score for network embedded_network_22.gml: [ 0.81050885]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_23.gml
running time of algorithm: 609.382999897
saved nmi score for network embedded_network_23.gml: [ 0.47584635]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_24.gml
running time of algorithm: 891.565000057
saved nmi score for network embedded_network_24.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_25.gml
running time of algorithm: 1207.352
saved nmi score for network embedded_network_25.gml: [ -2.22044605e-06]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_26.gml
running time of algorithm: 155.710000038
saved nmi score for network embedded_network_26.gml: [ 0.87272182]

number of edges: 256
number of communities: 1
-N 64 -k 4.0 -maxk 8.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_27.gml
running time of algorithm: 1029.33300018
saved nmi score for network embedded_network_27.gml: [ -2.77555756e-06]

number of edges: 256
number of communities: 3
-N 64 -k 4.0 -maxk 8.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_28.gml
running time of algorithm: 220.353999853
saved nmi score for network embedded_network_28.gml: [ 0.81566461]

number of edges: 256
number of communities: 4
-N 64 -k 4.0 -maxk 8.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_29.gml
running time of algorithm: 220.988999844
saved nmi score for network embedded_network_29.gml: [ 0.87011568]

number of edges: 256
number of communities: 2
-N 64 -k 4.0 -maxk 8.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_256_0.5_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\256\0.5
starting ghsom for: 256/0.5/embedded_network_30.gml
running time of algorithm: 882.170000076
saved nmi score for network embedded_network_30.gml: [ 0.44459108]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_1_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_1.gml
running time of algorithm: 78.7749998569
saved nmi score for network embedded_network_1.gml: [ 0.46201863]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_2.gml
running time of algorithm: 50.5260000229
saved nmi score for network embedded_network_2.gml: [ 1.]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_1_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_3.gml
running time of algorithm: 78.888999939
saved nmi score for network embedded_network_3.gml: [ 0.6472116]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_4.gml
running time of algorithm: 78.3170001507
saved nmi score for network embedded_network_4.gml: [ -2.77555756e-06]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_1_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_5.gml
running time of algorithm: 70.888999939
saved nmi score for network embedded_network_5.gml: [ 0.55108821]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_1_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_6.gml
running time of algorithm: 50.2979998589
saved nmi score for network embedded_network_6.gml: [ -2.77555756e-06]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_7.gml
running time of algorithm: 50.4909999371
saved nmi score for network embedded_network_7.gml: [ 1.]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_8.gml
running time of algorithm: 49.8310000896
saved nmi score for network embedded_network_8.gml: [ -4.44089210e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_9.gml
running time of algorithm: 70.1319999695
saved nmi score for network embedded_network_9.gml: [ 0.89930114]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_10.gml
running time of algorithm: 70.4570000172
saved nmi score for network embedded_network_10.gml: [ 0.89930114]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_11.gml
running time of algorithm: 70.504999876
saved nmi score for network embedded_network_11.gml: [ 0.89930114]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_12.gml
running time of algorithm: 78.9320001602
saved nmi score for network embedded_network_12.gml: [ 0.00071308]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_1_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_13.gml
running time of algorithm: 70.4990000725
saved nmi score for network embedded_network_13.gml: [ 0.6472116]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_1_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_14.gml
running time of algorithm: 72.0210001469
saved nmi score for network embedded_network_14.gml: [ 0.49707919]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_1_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_15.gml
running time of algorithm: 73.3840000629
saved nmi score for network embedded_network_15.gml: [ 0.89208711]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_16.gml
running time of algorithm: 70.4880001545
saved nmi score for network embedded_network_16.gml: [ 0.89930114]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_1_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_17.gml
running time of algorithm: 49.9919998646
saved nmi score for network embedded_network_17.gml: [ -3.33066907e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_18.gml
running time of algorithm: 70.5969998837
saved nmi score for network embedded_network_18.gml: [ 0.89930114]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_19.gml
running time of algorithm: 50.2909998894
saved nmi score for network embedded_network_19.gml: [ 1.]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_20.gml
running time of algorithm: 50.256000042
saved nmi score for network embedded_network_20.gml: [ -4.44089210e-06]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_21.gml
running time of algorithm: 50.1870000362
saved nmi score for network embedded_network_21.gml: [ 1.]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_22.gml
running time of algorithm: 78.4470000267
saved nmi score for network embedded_network_22.gml: [ -6.66133815e-06]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_23.gml
running time of algorithm: 50.0889999866
saved nmi score for network embedded_network_23.gml: [ 1.]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_24.gml
running time of algorithm: 78.5369999409
saved nmi score for network embedded_network_24.gml: [ -2.77555756e-06]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_1_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_25.gml
running time of algorithm: 50.0260000229
saved nmi score for network embedded_network_25.gml: [ -4.44089210e-06]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_26.gml
running time of algorithm: 78.6100001335
saved nmi score for network embedded_network_26.gml: [ 1.]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_1_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_27.gml
running time of algorithm: 78.621999979
saved nmi score for network embedded_network_27.gml: [ -4.44089210e-06]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_1_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_28.gml
running time of algorithm: 69.3329999447
saved nmi score for network embedded_network_28.gml: [ 0.50982586]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_1_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_29.gml
running time of algorithm: 78.7369999886
saved nmi score for network embedded_network_29.gml: [ -3.88578059e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_1_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\1
starting ghsom for: 512/1/embedded_network_30.gml
running time of algorithm: 72.4140000343
saved nmi score for network embedded_network_30.gml: [ 0.58679478]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_1.gml
running time of algorithm: 79.1760001183
saved nmi score for network embedded_network_1.gml: [ 0.52791952]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_2.gml
running time of algorithm: 78.8339998722
saved nmi score for network embedded_network_2.gml: [ 0.46201863]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_3.gml
running time of algorithm: 127.430000067
saved nmi score for network embedded_network_3.gml: [ -5.55111512e-06]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_4.gml
running time of algorithm: 78.5720000267
saved nmi score for network embedded_network_4.gml: [ 0.31529665]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_5.gml
running time of algorithm: 72.7850000858
saved nmi score for network embedded_network_5.gml: [ 0.64743951]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_6.gml
running time of algorithm: 79.3039999008
saved nmi score for network embedded_network_6.gml: [ 0.42069022]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_7.gml
running time of algorithm: 72.9469997883
saved nmi score for network embedded_network_7.gml: [ 0.89350236]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_8.gml
running time of algorithm: 72.4309999943
saved nmi score for network embedded_network_8.gml: [ 0.89350236]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_9.gml
running time of algorithm: 78.6309998035
saved nmi score for network embedded_network_9.gml: [ 1.]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_10.gml
running time of algorithm: 128.234999895
saved nmi score for network embedded_network_10.gml: [ -4.99600361e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_11.gml
running time of algorithm: 72.9409999847
saved nmi score for network embedded_network_11.gml: [ 0.53525024]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_12.gml
running time of algorithm: 119.18900013
saved nmi score for network embedded_network_12.gml: [ -1.66533454e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_13.gml
running time of algorithm: 72.6739997864
saved nmi score for network embedded_network_13.gml: [ 0.46808409]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_14.gml
running time of algorithm: 78.8320000172
saved nmi score for network embedded_network_14.gml: [ 0.6472116]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_15.gml
running time of algorithm: 94.2260000706
saved nmi score for network embedded_network_15.gml: [ 0.36881743]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_16.gml
running time of algorithm: 70.628000021
saved nmi score for network embedded_network_16.gml: [ 1.]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_17.gml
running time of algorithm: 130.204999924
saved nmi score for network embedded_network_17.gml: [ -2.77555756e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_18.gml
running time of algorithm: 70.1929998398
saved nmi score for network embedded_network_18.gml: [ 0.89930114]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_19.gml
running time of algorithm: 74.0419998169
saved nmi score for network embedded_network_19.gml: [ 0.40366304]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_20.gml
running time of algorithm: 71.748000145
saved nmi score for network embedded_network_20.gml: [ 0.52995759]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_21.gml
running time of algorithm: 72.8329999447
saved nmi score for network embedded_network_21.gml: [ 0.89350236]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_22.gml
running time of algorithm: 78.5199999809
saved nmi score for network embedded_network_22.gml: [ 0.58785673]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_23.gml
running time of algorithm: 70.9319999218
saved nmi score for network embedded_network_23.gml: [ 0.89930114]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_24.gml
running time of algorithm: 71.2099997997
saved nmi score for network embedded_network_24.gml: [ 0.89930114]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_25.gml
running time of algorithm: 122.529999971
saved nmi score for network embedded_network_25.gml: [ -6.10622664e-06]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_26.gml
running time of algorithm: 79.0280001163
saved nmi score for network embedded_network_26.gml: [ 0.3541919]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_27.gml
running time of algorithm: 119.352999926
saved nmi score for network embedded_network_27.gml: [ -2.77555756e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_28.gml
running time of algorithm: 70.9560000896
saved nmi score for network embedded_network_28.gml: [ 0.89930114]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_29.gml
running time of algorithm: 168.200999975
saved nmi score for network embedded_network_29.gml: [ -4.99600361e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.9_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.9
starting ghsom for: 512/0.9/embedded_network_30.gml
running time of algorithm: 72.8630001545
saved nmi score for network embedded_network_30.gml: [ 0.50677453]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_1.gml
running time of algorithm: 235.482000113
saved nmi score for network embedded_network_1.gml: [ -2.77555756e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_2.gml
running time of algorithm: 102.779000044
saved nmi score for network embedded_network_2.gml: [ 0.69352199]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_3.gml
running time of algorithm: 103.08100009
saved nmi score for network embedded_network_3.gml: [ 0.8122362]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_4.gml
running time of algorithm: 62.7189998627
saved nmi score for network embedded_network_4.gml: [ 0.67591663]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_5.gml
running time of algorithm: 225.407999992
saved nmi score for network embedded_network_5.gml: [ -4.99600361e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_6.gml
running time of algorithm: 124.686000109
saved nmi score for network embedded_network_6.gml: [ 0.63287168]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_7.gml
running time of algorithm: 122.493000031
saved nmi score for network embedded_network_7.gml: [ 0.70084977]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_8.gml
running time of algorithm: 248.571000099
saved nmi score for network embedded_network_8.gml: [ -6.10622664e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_9.gml
running time of algorithm: 102.823999882
saved nmi score for network embedded_network_9.gml: [ 0.94210793]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_10.gml
running time of algorithm: 95.621999979
saved nmi score for network embedded_network_10.gml: [ 0.47579294]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_11.gml
running time of algorithm: 91.1900000572
saved nmi score for network embedded_network_11.gml: [ 0.64924119]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_12.gml
running time of algorithm: 92.75
saved nmi score for network embedded_network_12.gml: [ 0.89208711]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_13.gml
running time of algorithm: 241.848999977
saved nmi score for network embedded_network_13.gml: [ -3.88578059e-06]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_14.gml
running time of algorithm: 102.709000111
saved nmi score for network embedded_network_14.gml: [ 0.76865815]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_15.gml
running time of algorithm: 230.534999847
saved nmi score for network embedded_network_15.gml: [ -3.33066907e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_16.gml
running time of algorithm: 90.9809999466
saved nmi score for network embedded_network_16.gml: [ 0.89350236]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_17.gml
running time of algorithm: 103.349999905
saved nmi score for network embedded_network_17.gml: [ 0.75199851]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_18.gml
running time of algorithm: 103.046000004
saved nmi score for network embedded_network_18.gml: [ 0.76321086]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_19.gml
running time of algorithm: 125.241999865
saved nmi score for network embedded_network_19.gml: [ 0.82177502]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_20.gml
running time of algorithm: 127.111000061
saved nmi score for network embedded_network_20.gml: [ 0.8122362]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_21.gml
running time of algorithm: 305.822999954
saved nmi score for network embedded_network_21.gml: [ -2.22044605e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_22.gml
running time of algorithm: 103.937999964
saved nmi score for network embedded_network_22.gml: [ 0.94213065]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_23.gml
running time of algorithm: 229.318000078
saved nmi score for network embedded_network_23.gml: [ -3.33066907e-06]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_24.gml
running time of algorithm: 103.521999836
saved nmi score for network embedded_network_24.gml: [ 0.8122362]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_25.gml
running time of algorithm: 62.8830001354
saved nmi score for network embedded_network_25.gml: [ 0.89930114]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_26.gml
running time of algorithm: 158.171000004
saved nmi score for network embedded_network_26.gml: [ 0.56362708]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_27.gml
running time of algorithm: 124.523000002
saved nmi score for network embedded_network_27.gml: [ 0.72906552]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_28.gml
running time of algorithm: 230.51699996
saved nmi score for network embedded_network_28.gml: [ -3.88578059e-06]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_29.gml
running time of algorithm: 244.024000168
saved nmi score for network embedded_network_29.gml: [ -5.55111512e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.8_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.8
starting ghsom for: 512/0.8/embedded_network_30.gml
running time of algorithm: 108.274999857
saved nmi score for network embedded_network_30.gml: [ 0.74559154]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_1.gml
running time of algorithm: 125.700999975
saved nmi score for network embedded_network_1.gml: [ 0.74279578]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_2.gml
running time of algorithm: 626.06400013
saved nmi score for network embedded_network_2.gml: [ -2.77555756e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_3.gml
running time of algorithm: 172.799999952
saved nmi score for network embedded_network_3.gml: [ 0.67007531]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_4.gml
running time of algorithm: 103.958000183
saved nmi score for network embedded_network_4.gml: [ 0.73357562]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_5.gml
running time of algorithm: 124.941999912
saved nmi score for network embedded_network_5.gml: [ 0.73427923]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_6.gml
running time of algorithm: 628.690999985
saved nmi score for network embedded_network_6.gml: [ -3.33066907e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_7.dat
generated graph 7
renamed graph 7
embedded graph 7 as embedded_network_7.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_7.gml
running time of algorithm: 320.989000082
saved nmi score for network embedded_network_7.gml: [ 0.56279058]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_8.dat
generated graph 8
renamed graph 8
embedded graph 8 as embedded_network_8.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_8.gml
running time of algorithm: 127.174000025
saved nmi score for network embedded_network_8.gml: [ 0.75385946]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_9.dat
generated graph 9
renamed graph 9
embedded graph 9 as embedded_network_9.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_9.gml
running time of algorithm: 306.101999998
saved nmi score for network embedded_network_9.gml: [ 0.5813923]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_10.dat
generated graph 10
renamed graph 10
embedded graph 10 as embedded_network_10.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_10.gml
running time of algorithm: 175.904000044
saved nmi score for network embedded_network_10.gml: [ 0.89930114]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_11.dat
generated graph 11
renamed graph 11
embedded graph 11 as embedded_network_11.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_11.gml
running time of algorithm: 104.965000153
saved nmi score for network embedded_network_11.gml: [ 0.72574161]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_12.dat
generated graph 12
renamed graph 12
embedded graph 12 as embedded_network_12.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_12.gml
running time of algorithm: 198.328999996
saved nmi score for network embedded_network_12.gml: [ 0.63281545]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_13.dat
generated graph 13
renamed graph 13
embedded graph 13 as embedded_network_13.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_13.gml
running time of algorithm: 104.385999918
saved nmi score for network embedded_network_13.gml: [ 0.94213065]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_14.dat
generated graph 14
renamed graph 14
embedded graph 14 as embedded_network_14.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_14.gml
running time of algorithm: 126.129999876
saved nmi score for network embedded_network_14.gml: [ 0.77245209]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_15.dat
generated graph 15
renamed graph 15
embedded graph 15 as embedded_network_15.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_15.gml
running time of algorithm: 222.426000118
saved nmi score for network embedded_network_15.gml: [ 0.58814859]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_16.dat
generated graph 16
renamed graph 16
embedded graph 16 as embedded_network_16.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_16.gml
running time of algorithm: 159.350000143
saved nmi score for network embedded_network_16.gml: [ 0.68687998]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_17.dat
generated graph 17
renamed graph 17
embedded graph 17 as embedded_network_17.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_17.gml
running time of algorithm: 159.622999907
saved nmi score for network embedded_network_17.gml: [ 0.70244278]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_18.dat
generated graph 18
renamed graph 18
embedded graph 18 as embedded_network_18.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_18.gml
running time of algorithm: 401.565999985
saved nmi score for network embedded_network_18.gml: [ -4.44089210e-06]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_19.dat
generated graph 19
renamed graph 19
embedded graph 19 as embedded_network_19.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_19.gml
running time of algorithm: 224.960999966
saved nmi score for network embedded_network_19.gml: [ 0.61165156]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_20.dat
generated graph 20
renamed graph 20
embedded graph 20 as embedded_network_20.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_20.gml
running time of algorithm: 103.207000017
saved nmi score for network embedded_network_20.gml: [ 0.94210793]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_21.dat
generated graph 21
renamed graph 21
embedded graph 21 as embedded_network_21.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_21.gml
running time of algorithm: 223.19900012
saved nmi score for network embedded_network_21.gml: [ 0.54893626]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_22.dat
generated graph 22
renamed graph 22
embedded graph 22 as embedded_network_22.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_22.gml
running time of algorithm: 618.164999962
saved nmi score for network embedded_network_22.gml: [ -3.33066907e-06]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_23.dat
generated graph 23
renamed graph 23
embedded graph 23 as embedded_network_23.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_23.gml
running time of algorithm: 492.934000015
saved nmi score for network embedded_network_23.gml: [ -2.77555756e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_24.dat
generated graph 24
renamed graph 24
embedded graph 24 as embedded_network_24.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_24.gml
running time of algorithm: 103.595000029
saved nmi score for network embedded_network_24.gml: [ 0.94210793]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_25.dat
generated graph 25
renamed graph 25
embedded graph 25 as embedded_network_25.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_25.gml
running time of algorithm: 104.864000082
saved nmi score for network embedded_network_25.gml: [ 0.94210793]

number of edges: 512
number of communities: 1
-N 64 -k 8.0 -maxk 16.0 -minc 64.0 -maxc 64.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_26.dat
generated graph 26
renamed graph 26
embedded graph 26 as embedded_network_26.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_26.gml
running time of algorithm: 399.743999958
saved nmi score for network embedded_network_26.gml: [ -2.22044605e-06]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_27.dat
generated graph 27
renamed graph 27
embedded graph 27 as embedded_network_27.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_27.gml
running time of algorithm: 222.414999962
saved nmi score for network embedded_network_27.gml: [ 0.59519323]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_28.dat
generated graph 28
renamed graph 28
embedded graph 28 as embedded_network_28.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_28.gml
running time of algorithm: 103.072999954
saved nmi score for network embedded_network_28.gml: [ 0.94210793]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_29.dat
generated graph 29
renamed graph 29
embedded graph 29 as embedded_network_29.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_29.gml
running time of algorithm: 105.030999899
saved nmi score for network embedded_network_29.gml: [ 0.75124394]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.7_30.dat
generated graph 30
renamed graph 30
embedded graph 30 as embedded_network_30.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.7
starting ghsom for: 512/0.7/embedded_network_30.gml
running time of algorithm: 103.809000015
saved nmi score for network embedded_network_30.gml: [ 0.71307848]

writing nmi scores and running times to file

creating new nmi scores array
creating new running time array

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.6_1.dat
generated graph 1
renamed graph 1
embedded graph 1 as embedded_network_1.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.6
starting ghsom for: 512/0.6/embedded_network_1.gml
running time of algorithm: 156.526000023
saved nmi score for network embedded_network_1.gml: [ 0.95747136]

number of edges: 512
number of communities: 2
-N 64 -k 8.0 -maxk 16.0 -minc 32.0 -maxc 32.0 -mu 0.1
written flag file: benchmark_flags_512_0.6_2.dat
generated graph 2
renamed graph 2
embedded graph 2 as embedded_network_2.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.6
starting ghsom for: 512/0.6/embedded_network_2.gml
running time of algorithm: 611.092000008
saved nmi score for network embedded_network_2.gml: [ 0.55121243]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.6_3.dat
generated graph 3
renamed graph 3
embedded graph 3 as embedded_network_3.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.6
starting ghsom for: 512/0.6/embedded_network_3.gml
running time of algorithm: 308.78399992
saved nmi score for network embedded_network_3.gml: [ 0.59206284]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.6_4.dat
generated graph 4
renamed graph 4
embedded graph 4 as embedded_network_4.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.6
starting ghsom for: 512/0.6/embedded_network_4.gml
running time of algorithm: 156.177999973
saved nmi score for network embedded_network_4.gml: [ 0.95747136]

number of edges: 512
number of communities: 4
-N 64 -k 8.0 -maxk 16.0 -minc 16.0 -maxc 16.0 -mu 0.1
written flag file: benchmark_flags_512_0.6_5.dat
generated graph 5
renamed graph 5
embedded graph 5 as embedded_network_5.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.6
starting ghsom for: 512/0.6/embedded_network_5.gml
running time of algorithm: 155.833999872
saved nmi score for network embedded_network_5.gml: [ 0.95747136]

number of edges: 512
number of communities: 3
-N 64 -k 8.0 -maxk 16.0 -minc 21.0 -maxc 22.0 -mu 0.1
written flag file: benchmark_flags_512_0.6_6.dat
generated graph 6
renamed graph 6
embedded graph 6 as embedded_network_6.gml in C:\Miniconda3\Jupyter\GHSOM_simplex_dsd\parameter_tests_edges\512\0.6
starting ghsom for: 512/0.6/embedded_network_6.gml






    




---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
<ipython-input-1-d9b218c2c654> in <module>()
    181 
    182                 print 'starting ghsom for: {}/{}/{}'.format(num_edges, p, gml_filename)
--> 183                 nmi_score, communities_detected = ghsom_main(params, gml_filename, labels)
    184                 nmi_scores[r-1] = nmi_score
    185 

spearmint_ghsom.pyc in main(params, gml_filename, labels)

spearmint_ghsom.pyc in fitness(w, eta, sigma, e_sg, e_en, gml_filename, labels)

spearmint_ghsom.pyc in ghsom(G, lam, w, eta, sigma, e_0, e_sg, e_en, layer)

spearmint_ghsom.pyc in ghsom(G, lam, w, eta, sigma, e_0, e_sg, e_en, layer)

spearmint_ghsom.pyc in train_network(X, network, num_epochs, eta_0, sigma_0, N)

spearmint_ghsom.pyc in winning_neuron(x, network)

C:\Miniconda3\envs\py27\lib\site-packages\numpy\linalg\linalg.pyc in norm(x, ord, axis, keepdims)
   2127                 sqnorm = dot(x.real, x.real) + dot(x.imag, x.imag)
   2128             else:
-> 2129                 sqnorm = dot(x, x)
   2130             ret = sqrt(sqnorm)
   2131             if keepdims:

KeyboardInterrupt: 

In [3]:

    

for scores in overall_nmi_scores:
    
    print scores
    idx = np.argsort(scores)[::-1]
    
    print parameter_settings[idx[0]]


    

    




[ 0.35632148  0.33486922  0.35229303  0.22688871  0.11498475]
0.2
[ 0.66275255  0.60090522  0.50301436  0.49588778  0.09876066]
0.2
[ 0.75081969  0.73525978  0.71798402  0.51541049  0.36483149]
0.2
[ 0.74710549  0.73859407  0.62326257  0.46137132  0.27593319]
0.2
[ 0.78002338  0.70857     0.65989855  0.53043045  0.33119491]
0.2
[ 0.77031049  0.73689024  0.67103124  0.50923749  0.04067397]
0.2
[ 0.78066878  0.71794796  0.68473928  0.51168871  0.17288067]
0.2