def generate_scale_free_power_law_graph(num, exp, seed):
'''
this function generates a scale free with power law
graph and write it into a file with .net format
'''
sequence = create_degree_sequence(num, powerlaw_sequence, exponent=exp)
graph = nx.configuration_model(sequence, seed=seed)
loops = graph.selfloop_edges()
json_str = json_graph.dumps(graph)
dict_graph = json.loads(json_str)
output_file = open('scale_free_power_law.net', 'w')
# write nodes
total_node_num = len(dict_graph['nodes'])
output_file.write('*Vertices ' + str(total_node_num) + '\n')
count = 1
for item in dict_graph['nodes']:
# +1 coz id starts with 0, it should start from 1
output_file.write(' ' + str(count) + ' ' + str(item['id'] + 1) +
'\n')
count = count + 1
# write edges, links
output_file.write('*Edges' + '\n')
for item in dict_graph['links']:
# +1 coz source and target starts with 0, it should start from 1
output_file.write(
str(item['source'] + 1) + ' ' + str(item['target'] + 1) + ' 1' +
'\n')
output_file.close()
def pogiantc(n, c):
mean = 0
for i in range(0, 1):
z = utils.create_degree_sequence(100, powerlaw_sequence)
print(z)
G = nx.configuration_model(z)
components = nx.connected_components(G)
gene_components = sorted(components, key=len, reverse=True)
mean = mean + (1.0 * len(gene_components[0])) / n
i = i + 1
print(i)
return (mean)
def create_star(self,node): sequence = create_degree_sequence(node, powerlaw_sequence, exponent=2.5) graph = nx.configuration_model(sequence) loops = graph.selfloop_edges() graph = nx.Graph(graph) graph.remove_edges_from(loops) components = sorted(nx.connected_components(graph), key=len, reverse=True) lcc = graph.subgraph(components[0]) #pos = nx.spring_layout(lcc) #nx.draw_networkx(lcc, pos) graph = list(nx.generate_edgelist(lcc)) edges = lcc.edges() #print(edges) flat = list(sum(edges, ())) return edges, max(flat,key=flat.count)
def test_degree_sequences():
seq = create_degree_sequence(10, uniform_sequence)
assert_equal(len(seq), 10)
seq = create_degree_sequence(10, powerlaw_sequence)
assert_equal(len(seq), 10)
print components print "in: infect" for i in infect: print "link: infect infect@node%d" % i ports = [0 for i in range(0,len(nodes))] for edge in CM.edges(): origin = edge[0] target = edge[1] print "link: out%d@node%d in%d@node%d" % (ports[origin],origin,ports[target],target) print "link: out%d@node%d in%d@node%d" % (ports[target],target,ports[origin],origin) ports[origin] += 1 ports[target] += 1 if (len(sys.argv) < 2): print "arg[0] is population size, arg[1] is gamma alpha (default 10), arg[2] is beta (default 1) and arg[3] is infected size (default 1%)" sys.exit(0); n = int(sys.argv[1]) seq=create_degree_sequence(n,lambda x: [rnd.gammavariate(alpha=10.0 if len(sys.argv) < 3 else float(sys.argv[2]) ,beta=1.0 if len(sys.argv) < 4 else float(sys.argv[3])) for i in range(x)]) G=nx.configuration_model(seq) G.remove_edges_from(G.selfloop_edges()) G=nx.Graph(G) degree_sequence=sorted(nx.degree(G).values(),reverse=True) # degree sequence print "%Degree sequence is ", degree_sequence dmax=max(degree_sequence) print "%%Max degree is: %d"%dmax printma(G,infect=[rnd.randint(0,n-1) for i in range(n/100 if len(sys.argv) < 5 else int(sys.argv[4]))])
cp = 0.02
cdr = args.cell_death_rate #0.25
bcr = args.b_cell_rate #0.05
Variant.creact = True
T = args.T
fasta = SeqIO.parse(args.input, 'fasta')
initial = fasta.next()
print initial
# Generate network
# noinspection PyDeprecation
sequence = create_degree_sequence(num, powerlaw_sequence, exponent=exp)
graph = nx.configuration_model(sequence, seed=seed)
loops = graph.selfloop_edges()
# remove parallel edges and self-loops
graph = nx.Graph(graph)
graph.remove_edges_from(loops)
# get largest connected component
# unfortunately, the iterator over the components is not guaranteed to be sorted by size
component = max(nx.connected_components(graph), key=len)
lcc = graph.subgraph(component)
nd.write_dot(lcc, out_dir_f % "scale_free.dot")
print "Number of nodes in generated scale free graph: %i" % len(lcc)
transmission = nx.DiGraph()
def test_degree_sequences():
seq=create_degree_sequence(10,uniform_sequence)
assert_equal(len(seq), 10)
seq=create_degree_sequence(10,powerlaw_sequence)
assert_equal(len(seq), 10)