def ProcessFile(filename):
print("Processing '%s'" % (filename))
file_title = os.path.splitext(os.path.basename(filename))[0]
matrix = np.loadtxt(filename, delimiter=",")
G = nx.Graph()
for i in range(0,matrix.shape[0]):
for j in range(i,matrix.shape[1]):
G.add_edge(i,j,weight=matrix[i][j])
#Once the network has been loaded, one needs to produce the filtration of the
#network. This can be done in different ways. The simplest is to rank the
#edges in descending order and use their rank as the indices for the sequence
#of simplicial complex. Holes contains a few options for different
#filtrations (ascending, descending, metrical..). Below we consider the one
#with descending weights described in
#[http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0066506]:
fil = ho.filtrations.dense_graph_weight_clique_rank_filtration(G,2)
#Once the filtration has been created, it needs to be saved and passed to
#jython, so that javaplex can receive the data and process it. This requires
#calling a subprocess and feeding it the right file.
clique_dictionary_file = './output/'+file_title+'_filtration.pck'
pk.dump(fil,open(clique_dictionary_file,'w'))
hom_dim = 2 # max homology group calculated
dataset_tag = 'test_IO2009'
output_dir = './output/';
gen_file = './output/gen/generators_test_'+file_title+'_.pck'
if not os.path.isfile(gen_file):
ho.persistent_homology_calculation(clique_dictionary_file, hom_dim, dataset_tag, output_dir, jython_call='C:\\jython2.5.4rc1\\jython.bat', m1=2048, m2=2048)
gen = pk.load(open(gen_file))
#The properties of each generator can be listed easily:
gen[1][0].summary()
#One can also simply produce the barcodes for the network then:
ho.barcode_creator(gen[0])
plt.title(r'Barcode for $H_0$, '+file_title)
plt.savefig('Barcode0_2006.png')
ho.barcode_creator(gen[1])
plt.title(r'Barcode for $H_1$, '+file_title)
plt.savefig('Barcode1_2006.png')
ho.barcode_creator(gen[2])
plt.title(r'Barcode for $H_2$, '+file_title)
plt.savefig('Barcode2_2006.png')
original_graph= #name of the edgelist file
dir= #output directory path
dataset_tag= #name tag
IR_weight_cutoff= #optional cutoff weight
else:
if len(sys.argv)>=3:
dir=str(sys.argv[1]); #insert final slash
dataset_tag=str(sys.argv[2]); #without underlines
else:
print('Input is required as:\n 1) name of output directory
\n 2) name tag for output files');
sys.exit();
if not os.path.exists(dir):
os.makedirs(dir)
sys.path.append('../')
import Holes as ho
import pickle as pk
generators_dict=pk.load(open(dir+'gen/generators_'+dataset_tag+'_.pck'))
for key in generators_dict:
if len(generators_dict[key])>0:
print key
ho.barcode_creator(generators_dict[key]);
plt.show()
ho.complete_persistence_diagram(generators_dict[key])
import networkx as nx
sys.path.append('../../../')
import Holes as ho
import pickle as pk
import numpy as np
import matplotlib.pyplot as plt
gen_file = './output/gen/generators_test_IO2007_.pck'
if not os.path.isfile(gen_file):
os.environ["JAVA_OPTS"]="-Xms2048m -Xmx2048m"
ho.persistent_homology_calculation(clique_dictionary_file, hom_dim, dataset_tag, output_dir, jython_call='C:\\jython2.5.4rc1\\jython.bat', m1=2048, m2=2048)
gen = pk.load(open(gen_file))
#The properties of each generator can be listed easily:
gen[1][0].summary()
#One can also simply produce the barcodes for the network then:
ho.barcode_creator(gen[0])
plt.title(r'Barcode for $H_0$, IO2007')
plt.savefig('Barcode0.png')
ho.barcode_creator(gen[1])
plt.title(r'Barcode for $H_1$, IO2007')
plt.savefig('Barcode1.png')
ho.barcode_creator(gen[2])
plt.title(r'Barcode for $H_2$, IO2007')
plt.savefig('Barcode2.png')
