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 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