def covariance_sig(fn):
#print "k value", k_value
#print "In cov sig", fn
filename = fn.split('/')[-1]
#print 'filename =', filename
#model_name = filename.split('_')[0]
model_name = fn.split('/')[-2]
#print 'modelname =', model_name
#G = nx.read_edgelist(fn)
G = nx.read_leda(fn)
adj_matrix = nx.adjacency_matrix(G)
num_nodes = G.number_of_nodes()
#print "In cov sig", num_nodes
e1 = np.zeros((num_nodes, 1)) + 1
p_iter = adj_matrix * e1
power_iter_matrix = (G.number_of_nodes() *
(p_iter)) / np.linalg.norm(p_iter)
for i in range(2, k_value + 1):
p_iter = adj_matrix * p_iter
p_iter = (G.number_of_nodes() * (p_iter)) / np.linalg.norm(p_iter)
power_iter_matrix = np.column_stack([power_iter_matrix, p_iter])
#print "power matrix", power_iter_matrix
cov_matrix = [[0 for x in range(k_value)] for x in range(k_value)]
for i in range(num_nodes):
C_i = np.matrix.transpose(power_iter_matrix[i, 0:] -
1) * (power_iter_matrix[i, 0:] - 1)
cov_matrix += C_i
return (fn, cov_matrix / num_nodes, model_name)
def covariance_sig(fn):
#print "k value", k_value
#print "In cov sig", fn
filename = fn.split('/')[-1]
#print 'filename =', filename
#model_name = filename.split('_')[0]
model_name = fn.split('/')[-2]
#print 'modelname =', model_name
#G = nx.read_edgelist(fn)
G = nx.read_leda(fn)
adj_matrix = nx.adjacency_matrix(G)
num_nodes = G.number_of_nodes();
#print "In cov sig", num_nodes
e1 = np.zeros((num_nodes, 1))+1
p_iter = adj_matrix * e1
power_iter_matrix = (G.number_of_nodes() * (p_iter))/np.linalg.norm(p_iter)
for i in range(2,k_value+1):
p_iter = adj_matrix * p_iter
p_iter = (G.number_of_nodes() * (p_iter))/np.linalg.norm(p_iter)
power_iter_matrix = np.column_stack([power_iter_matrix, p_iter])
#print "power matrix", power_iter_matrix
cov_matrix = [[0 for x in range(k_value)] for x in range(k_value)]
for i in range(num_nodes):
C_i = np.matrix.transpose(power_iter_matrix[i,0:]-1) * (power_iter_matrix[i,0:]-1)
cov_matrix += C_i
return (fn, cov_matrix/num_nodes, model_name)
def test_read_LEDA(self):
fh = io.BytesIO()
data="""#header section \nLEDA.GRAPH \nstring\nint\n-1\n#nodes section\n5 \n|{v1}| \n|{v2}| \n|{v3}| \n|{v4}| \n|{v5}| \n\n#edges section\n7 \n1 2 0 |{4}| \n1 3 0 |{3}| \n2 3 0 |{2}| \n3 4 0 |{3}| \n3 5 0 |{7}| \n4 5 0 |{6}| \n5 1 0 |{foo}|"""
G=nx.parse_leda(data)
fh.write(data.encode('UTF-8'))
fh.seek(0)
Gin = nx.read_leda(fh)
assert_equal(sorted(G.nodes()),sorted(Gin.nodes()))
assert_equal(sorted(G.edges()),sorted(Gin.edges()))
def test_read_LEDA(self):
fh = io.BytesIO()
data = """#header section \nLEDA.GRAPH \nstring\nint\n-1\n#nodes section\n5 \n|{v1}| \n|{v2}| \n|{v3}| \n|{v4}| \n|{v5}| \n\n#edges section\n7 \n1 2 0 |{4}| \n1 3 0 |{3}| \n2 3 0 |{2}| \n3 4 0 |{3}| \n3 5 0 |{7}| \n4 5 0 |{6}| \n5 1 0 |{foo}|"""
G = nx.parse_leda(data)
fh.write(data.encode('UTF-8'))
fh.seek(0)
Gin = nx.read_leda(fh)
assert sorted(G.nodes()) == sorted(Gin.nodes())
assert sorted(G.edges()) == sorted(Gin.edges())
def test_read_LEDA(self):
data="""#header section \nLEDA.GRAPH \nstring\nint\n-1\n#nodes section\n5 \n|{v1}| \n|{v2}| \n|{v3}| \n|{v4}| \n|{v5}| \n\n#edges section\n7 \n1 2 0 |{4}| \n1 3 0 |{3}| \n2 3 0 |{2}| \n3 4 0 |{3}| \n3 5 0 |{7}| \n4 5 0 |{6}| \n5 1 0 |{foo}|"""
G=nx.parse_leda(data)
(fd,fname)=tempfile.mkstemp()
fh=open(fname,'w')
b=fh.write(data)
fh.close()
Gin=nx.read_leda(fname)
assert_equal(sorted(G.nodes()),sorted(Gin.nodes()))
assert_equal(sorted(G.edges()),sorted(Gin.edges()))
os.close(fd)
os.unlink(fname)
def readGraph(filename, type):
extension = filename.split(".")[-1]
print '"' + extension + '"'
if extension == "txt":
return nx.read_edgelist(filename, create_using=type)
elif extension == "gml":
return nx.read_gml(filename)
elif extension == "leda":
return nx.read_leda(filename, create_using=type)
elif extension == "gexf":
return nx.read_gexf(filename, create_using=type)
elif extension == "graphml":
return nx.read_graphml(filename, create_using=type)
elif extension == "json":
return nx.read_json(filename, create_using=type)
else:
raise Exception("File format .{0} not supported".format(extension))
def readGraph(filename, type):
extension = filename.split(".")[-1]
print '"' + extension + '"'
if extension == "txt":
return nx.read_edgelist(filename, create_using=type)
elif extension == "gml":
return nx.read_gml(filename)
elif extension == "leda":
return nx.read_leda(filename, create_using=type)
elif extension == "gexf":
return nx.read_gexf(filename, create_using=type)
elif extension == "graphml":
return nx.read_graphml(filename, create_using=type)
elif extension == "json":
return nx.read_json(filename, create_using=type)
else:
raise Exception("File format .{0} not supported".format(extension))
def open_file(self, path: str, file_type: str):
logger.debug(locals())
if "json" in file_type.lower():
if "node link graph" in file_type.lower():
self.graph = networkx.node_link_graph(
json.loads(pathlib.Path(path).read_text()))
elif "adjacency graph" in file_type.lower():
self.graph = networkx.adjacency_graph(
json.loads(pathlib.Path(path).read_text()))
else:
raise NotImplementedError()
elif "graphml" in file_type.lower():
self.graph = networkx.read_graphml(path)
elif "leda" in file_type.lower():
self.graph = networkx.read_leda(path)
elif "pajek" in file_type.lower():
self.graph = networkx.read_pajek(path)
else:
raise NotImplementedError()
except IOError:
print("Error while READING the file ")
elif(input_file_type=='graphML'):
while True:
try:
G = nx.read_graphml(file_path)
break
#if the file format isin ---GraphML---- read the graph and put that in G variablich is later used to write graph
except IOError:
print("Error while READING the file ")
elif(input_file_type=='LEDA'):
while True:
try:
G = nx.read_leda(file_path)
break
#if the file format isin ---LEDA---- read the graph and put that in G variable which is later used to write graph
except IOError:
print("Error while READING the file ")
elif(input_file_type=='YAML'):
while True:
try:
G = nx.read_yaml(file_path)
break
#if the file format isin ---YAML--- read the graph and put that in G variable which is later used to write graph
except IOError:
print("Error while READING the file ")
elif(input_file_type=='Pajek'):
default=None,
metavar='report',
help='File to output the report to in CSV format.')
parser.add_argument('--cbc',
action='store_true',
help='Use Coin-Or Branch (built-in) instead of Gurobi')
parsed_args = parser.parse_args()
input_ext = os.path.splitext(parsed_args.i)[1]
if input_ext == ".pkl":
topo = nx.read_gpickle(parsed_args.i)
elif input_ext == '.graphml':
topo = nx.read_graphml(parsed_args.i)
elif input_ext == '.leda':
topo = nx.read_leda(parsed_args.i)
elif input_ext == '.yaml':
topo = nx.read_yaml(parsed_args.i)
elif input_ext == '.pjk':
topo = nx.read_pajek(parsed_args.i)
elif input_ext == '.gis':
topo = nx.read_shp(parsed_args.i)
else:
raise RuntimeError("Unsupported format (Wrong extension?)")
b_par = parsed_args.alpha
if b_par < 0:
b_par = 0
if b_par > 1:
b_par = 1
