def test_attracting_component_subgraphs(self):
subgraphs = nx.attracting_component_subgraphs(self.G1)
for subgraph in subgraphs:
assert_equal(len(subgraph), 1)
subgraphs = nx.attracting_component_subgraphs(self.G2)
assert_equal(len(subgraphs), 1)
assert_true(1 in subgraphs[0])
assert_true(2 in subgraphs[0])
def test_attracting_component_subgraphs(self):
subgraphs = nx.attracting_component_subgraphs(self.G1)
for subgraph in subgraphs:
assert_equal(len(subgraph), 1)
subgraphs = nx.attracting_component_subgraphs(self.G2)
assert_equal(len(subgraphs), 1)
assert_true(1 in subgraphs[0])
assert_true(2 in subgraphs[0])
def test_attracting_component_subgraphs(self):
subgraphs = nx.attracting_component_subgraphs(self.G1)
for subgraph in subgraphs:
assert_equal(len(subgraph), 1)
self.G2.add_edge(1, 2, eattr='red') # test attrs copied to subgraphs
self.G2.node[2]['nattr'] = 'blue'
self.G2.graph['gattr'] = 'green'
subgraphs = nx.attracting_component_subgraphs(self.G2)
assert_equal(len(subgraphs), 1)
SG2 = subgraphs[0]
assert_true(1 in SG2)
assert_true(2 in SG2)
assert_equal(SG2[1][2]['eattr'], 'red')
assert_equal(SG2.node[2]['nattr'], 'blue')
assert_equal(SG2.graph['gattr'], 'green')
SG2.add_edge(1, 2, eattr='blue')
assert_equal(SG2[1][2]['eattr'], 'blue')
assert_equal(self.G2[1][2]['eattr'], 'red')
def test_attracting_component_subgraphs(self):
subgraphs = nx.attracting_component_subgraphs(self.G1)
for subgraph in subgraphs:
assert_equal(len(subgraph), 1)
self.G2.add_edge(1,2,eattr='red') # test attrs copied to subgraphs
self.G2.node[2]['nattr']='blue'
self.G2.graph['gattr']='green'
subgraphs = nx.attracting_component_subgraphs(self.G2)
assert_equal(len(subgraphs), 1)
SG2=subgraphs[0]
assert_true(1 in SG2)
assert_true(2 in SG2)
assert_equal(SG2[1][2]['eattr'],'red')
assert_equal(SG2.node[2]['nattr'],'blue')
assert_equal(SG2.graph['gattr'],'green')
SG2.add_edge(1,2,eattr='blue')
assert_equal(SG2[1][2]['eattr'],'blue')
assert_equal(self.G2[1][2]['eattr'],'red')
print 'The number of attracting components of G is:', nx.number_attracting_components(
G)
print str(" ")
print 'List of attracting components:'
print sorted(nx.attracting_components(G), key=len, reverse=True)
print str(" ")
lc = sorted(nx.strongly_connected_components(G), key=len, reverse=True)
print 'List of strongly connected components:'
print lc
print str(" ")
colors_list = ['c', 'b', 'g', 'y', 'k', 'm']
colors_to_select = list(colors_list)
graphs = sorted(nx.attracting_component_subgraphs(G), key=len, reverse=True)
attracting_component_subgraphs_edges = []
attracting_component_subgraphs_nodes = []
nodes_color_alpha = []
edges_color_alpha = []
colors_of_edges = []
edge_width_l = []
attracting_component_subgraphs_edges_one_mode = []
attracting_component_subgraphs_nodes_one_mode = []
nodes_color_alpha = []
edges_color_alpha = []
colors_of_edges = []
edge_width_l = []
graphs_labels = dict()
graphs_lists = dict()
for gr in range(len(graphs)):
print 'Does the graph G consist of a single attracting component?', nx.is_attracting_component(G)
print 'The number of attracting components of G is:', nx.number_attracting_components(G)
print str(" ")
print 'List of attracting components:'
print sorted(nx.attracting_components(G), key = len, reverse=True)
print str(" ")
lc=sorted(nx.strongly_connected_components(G), key = len, reverse=True)
print 'List of strongly connected components:'
print lc
print str(" ")
colors_list=['c','b','g','y','k','m']
colors_to_select=list(colors_list)
graphs =sorted(nx.attracting_component_subgraphs(G), key = len, reverse=True)
attracting_component_subgraphs_edges=[]
attracting_component_subgraphs_nodes=[]
nodes_color_alpha=[]
edges_color_alpha=[]
colors_of_edges=[]
edge_width_l=[]
attracting_component_subgraphs_edges_one_mode=[]
attracting_component_subgraphs_nodes_one_mode=[]
nodes_color_alpha=[]
edges_color_alpha=[]
colors_of_edges=[]
edge_width_l=[]
graphs_labels=dict()
graphs_lists=dict()
for gr in range(len(graphs)):
import networkx
import sys
graph = networkx.MultiGraph()
tags = []
tags_file = open(sys.argv[2])
n_tags = int(tags_file.readline().strip())
for tag in tags_file:
tag = tag.strip()
tags.append(unicode(tag, 'utf-8'))
graph.add_node(unicode(tag, 'utf-8'))
edges_file = open(sys.argv[1])
n_nodes = int(edges_file.readline().strip())
n_edges = int(edges_file.readline().strip())
for line in edges_file:
a, b = line.split()
graph.add_edge(tags[int(a)], tags[int(b)])
print(graph.number_of_nodes())
print(graph.number_of_edges())
sub_list=networkx.attracting_component_subgraphs(graph)
for cluster in sub_list:
for node in cluster.nodes():
print node
print
