我们从Python开源项目中，提取了以下15个代码示例，用于说明如何使用networkx.read_gml()。
def test_edges_to_graph_gml(self): graph = nx.read_gml(fixtures_path('graph.gml')) with open(fixtures_path('graph.json'), 'r') as json_graph: edges = json.load(json_graph) out = nx.parse_gml(utils.edges_to_graph(edges, fmt='gml')) assert nodeset(out) == nodeset(graph) assert edgeset(out) == edgeset(graph)
def test_command_graph(self): matches = [ ((0, 0), (3, 3)), ((1, 11), (4, 14)), ((8, 12), (11, 15)), ] regions = utils.serialize_json(matches) result = self.runner.invoke( cli.graph, [regions, self.image_grid] ) out = nx.parse_graphml(result.output.strip()) graph = nx.read_gml(fixtures_path('graph.gml')) assert nodeset(out) == nodeset(graph) assert edgeset(out) == edgeset(graph)
def main(): #extract_intra_function_cfg("C:\\Users\\Xu Zhengzi\\Desktop\\oh\\") cfg1 = nx.read_gml("C:\\Users\\Xu Zhengzi\\Desktop\\og\\dtls1_reassemble_fragment.gml") cfg2 = nx.read_gml("C:\\Users\\Xu Zhengzi\\Desktop\\oh\\dtls1_reassemble_fragment.gml") nodes1 = ['0x80c0b14', '0x80c0b9a', '0x80c0c3c', '0x80c0c57', '0x80c0c5d', '0x80c0c8c', '0x80c0ccc', '0x80c0d0a', '0x80c0d2c', '0x80c0e83', '0x80c0fb4', '0x80c0eb6', '0x80c0f53', '0x80c0b97', '0x80c0d88', '0x80c0de1', '0x80c0db5', '0x80c0fac', '0x80c0f73', '0x80c0dd9'] extract_trace(cfg1, 3, nodes1) print "Finish"
def main(): #wait until IDA finishing loading the project idaapi.autoWait() #extract_intra_function_cfg("C:\\Users\\Xu Zhengzi\\Desktop\\oh\\") cfg1 = nx.read_gml("C:\\Users\\Xu Zhengzi\\Desktop\\og\\dtls1_reassemble_fragment.gml") cfg2 = nx.read_gml("C:\\Users\\Xu Zhengzi\\Desktop\\oh\\dtls1_reassemble_fragment.gml") nodes1 = ['0x80c0b14', '0x80c0b9a', '0x80c0c3c', '0x80c0c57', '0x80c0c5d', '0x80c0c8c', '0x80c0ccc', '0x80c0d0a', '0x80c0d2c', '0x80c0e83', '0x80c0fb4', '0x80c0eb6', '0x80c0f53', '0x80c0b97', '0x80c0d88', '0x80c0de1', '0x80c0db5', '0x80c0fac', '0x80c0f73', '0x80c0dd9'] extract_trace(cfg1, 3, nodes1) print "Finish"
def load_3(gml1,gml2,name): g1 = nx.read_gml(gml1) g2 = nx.read_gml(gml2) q1 = qucik_hash(g1) q2 = qucik_hash(g2) if not q1: return 0 if not q2: return 0 v1 = q1[1] v2 = q2[1] s1 = q1[0] s2 = q2[0] if v1 == v2: #print "skip" return 0 #print s1 #print s2 to_write = [] to_write.append(name) with open("result_openssl.txt", "a") as myfile: for item in to_write: myfile.write(item) myfile.write("\n") return 1
def merge_node(path,new_path): g = nx.read_gml(path) nodes = [n for n,d in g.out_degree().items() if d==1] for node in nodes: if not node in g.nodes(): continue if g.in_degree(node) != 1: continue p = g.successors(node) #print p #dict = g.in_degree(p) #print dict[p] #print g.in_degree(p)[p[0]] if g.in_degree(p)[p[0]] == 1: text1 = g.node[node]["text"] text1 = remove_last_jump(text1) text2 = g.node[p[0]]["text"] #print text1 #print text2 new_text = text1 + ',' + text2 #print new_text nns = g.successors(p[0]) g.node[node]["text"] = new_text for n in nns: g.add_edge(node, n) g.remove_node(p[0]) nx.write_gml(g, new_path) return nx.number_of_nodes(g)
def celegans(path): """Load the neural network of the worm C. Elegans [@watts1998collective]. The neural network consists of around 300 neurons. Each connection between neurons is associated with a weight (positive integer) capturing the strength of the connection. Args: path: str. Path to directory which either stores file or otherwise file will be downloaded and extracted there. Filename is `celegansneural.gml`. Returns: Adjacency matrix as a np.darray `x_train` with 297 rows and 297 columns. """ import networkx as nx path = os.path.expanduser(path) filename = 'celegansneural.gml' if not os.path.exists(os.path.join(path, filename)): url = 'http://www-personal.umich.edu/~mejn/netdata/celegansneural.zip' maybe_download_and_extract(path, url) graph = nx.read_gml(os.path.join(path, filename)) x_train = np.zeros([graph.number_of_nodes(), graph.number_of_nodes()], dtype=np.int) for i, j in graph.edges(): x_train[i, j] = int(graph[i][j][0]['value']) return x_train
def karate(path): """Load Zachary's Karate Club [@zachary1977information]. It is a social network of friendships between 34 members of a karate club at a US university from 1970 to 1972. During the study a conflict between instructor 'Mr. Hi' and administrator 'Officer' led the club to split into two. Half of the members formed a new club around 'Mr. Hi'; other members found a new instructor or quit karate. Args: path: str. Path to directory which either stores file or otherwise file will be downloaded and extracted there. Filename is `karate.gml`. Returns: Tuple of adjacency matrix as a np.darray `x_train` with 34 rows and 34 columns and np.darray `y_train` of class memberships (0 for 'Mr.Hi' and 1 for 'Officer'). """ import networkx as nx path = os.path.expanduser(path) filename = 'karate.gml' if not os.path.exists(os.path.join(path, filename)): url = 'http://www-personal.umich.edu/~mejn/netdata/karate.zip' maybe_download_and_extract(path, url) x_train = nx.read_gml(os.path.join(path, filename)) x_train = nx.to_numpy_matrix(x_train).astype(int) labels = [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 16, 17, 19, 21] y_train = np.array([0 if i in labels else 1 for i in range(x_train.shape[0])], dtype=np.int) return x_train, y_train
def __loadGMLFiles__(self): """ Iterates through all of the files inside of support directory merges these graphs with the whole gapGraph creates a dictionary of {"readName":[gapName or nodeName,...] } """ self.readSupport = defaultdict(list) for i in glob.glob(os.path.join(self.protocol.outDir,"support","*.gml")): truncNxVer = float('.'.join(networkx.__version__.split('.')[:2])) if truncNxVer >= 1.7: try: inputGml = networkx.read_gml(i, relabel=True) except ValueError: logging.warning("GML file %s is empty" % i) continue elif truncNxVer == 1.1: inputGml = networkx.read_gml(i) else: logging.warning("It is unknown if networkx version %s will work." % networkx.__version__) logging.warning("If you get an error here, please report it!!!") inputGml = networkx.read_gml(i) for node in inputGml.nodes_iter(): for readName in inputGml.node[node]['extenders'].split(':'): if readName == '': continue trimInfo = self.__cleanReadName__(readName) self.gapGraph.add_extend(node, trimInfo.name) self.readSupport[trimInfo.name].append((node, trimInfo)) for source, target, evidence in inputGml.edges_iter(data=True): for readName in evidence['evidence'].split(':'): if readName == '': continue trimInfo = self.__cleanReadName__(readName) self.gapGraph.add_evidence(source, target, trimInfo.name) self.readSupport[trimInfo.name].append((source, target, trimInfo)) self.readSupport = dict(self.readSupport)
def read_zoo_topology_gml(zoo_file): g = nx.read_gml(zoo_file, label="id") log.info(g.nodes(data=True)) for n, items in g.nodes_iter(data=True): log.info("node {0}: {1}".format(str(n), str(items))) return Topology(nx.Graph(g.to_directed()))
def load(gml1,gml2,name): g1 = nx.read_gml(gml1) g2 = nx.read_gml(gml2) s1 = t(g1) s2 = t(g2) #print s1 #print s2 with open("result.txt", "a") as myfile: myfile.write(name) myfile.write("\n") m = lcs(s1,s2) index = find_index(m) match1 = [] match2 = [] for item in index: myfile.write(hex(s1[item[0]][0]) + " " + hex(s2[item[1]][0])) myfile.write("\n") #print hex(s1[item[0]][0]) + " " + hex(s2[item[1]][0]) match1.append(s1[item[0]][0]) match2.append(s2[item[1]][0]) myfile.write("o") myfile.write("\n") for item in s1: if item[0] not in match1: #print hex(item[0]) myfile.write(hex(item[0])) myfile.write("\n") myfile.write("p") myfile.write("\n") for item in s2: if item[0] not in match2: #print hex(item[0]) myfile.write(hex(item[0])) myfile.write("\n") #print return 0
def read_gml(path, relabel=False): """Read graph in GML format from path. Parameters ---------- path : filename or filehandle The filename or filehandle to read from. relabel : bool, optional If True use the GML node label attribute for node names otherwise use the node id. Returns ------- G : MultiGraph or MultiDiGraph Raises ------ ImportError If the pyparsing module is not available. See Also -------- write_gml, parse_gml Notes ----- Requires pyparsing: http://pyparsing.wikispaces.com/ The GML specification says that files should be ASCII encoded, with any extended ASCII characters (iso8859-1) appearing as HTML character entities. References ---------- GML specification: http://www.infosun.fim.uni-passau.de/Graphlet/GML/gml-tr.html Examples -------- >>> G=nx.path_graph(4) >>> nx.write_gml(G,'test.gml') >>> H=nx.read_gml('test.gml') """ lines = (unescape(line.decode('ascii')) for line in path) G = parse_gml(lines, relabel=relabel) return G
def pyparse_gml(): """A pyparsing tokenizer for GML graph format. This is not intended to be called directly. See Also -------- write_gml, read_gml, parse_gml """ try: from pyparsing import \ Literal, CaselessLiteral, Word, Forward,\ ZeroOrMore, Group, Dict, Optional, Combine,\ ParseException, restOfLine, White, alphas, alphanums, nums,\ OneOrMore,quotedString,removeQuotes,dblQuotedString, Regex except ImportError: try: from matplotlib.pyparsing import \ Literal, CaselessLiteral, Word, Forward,\ ZeroOrMore, Group, Dict, Optional, Combine,\ ParseException, restOfLine, White, alphas, alphanums, nums,\ OneOrMore,quotedString,removeQuotes,dblQuotedString, Regex except: raise ImportError('pyparsing not found', 'http://pyparsing.wikispaces.com/') lbrack = Literal("[").suppress() rbrack = Literal("]").suppress() pound = ("#") comment = pound + Optional( restOfLine ) integer = Word(nums+'-').setParseAction(lambda s,l,t:[ int(t[0])]) real = Regex(r"[+-]?\d+\.\d*([eE][+-]?\d+)?").setParseAction( lambda s,l,t:[ float(t[0]) ]) dblQuotedString.setParseAction( removeQuotes ) key = Word(alphas,alphanums+'_') value_atom = (real | integer | Word(alphanums) | dblQuotedString) value = Forward() # to be defined later with << operator keyvalue = Group(key+value) value << (value_atom | Group( lbrack + ZeroOrMore(keyvalue) + rbrack )) node = Group(Literal("node") + lbrack + Group(OneOrMore(keyvalue)) + rbrack) edge = Group(Literal("edge") + lbrack + Group(OneOrMore(keyvalue)) + rbrack) creator = Group(Literal("Creator")+ Optional( restOfLine )) version = Group(Literal("Version")+ Optional( restOfLine )) graphkey = Literal("graph").suppress() graph = Dict (Optional(creator)+Optional(version)+\ graphkey + lbrack + ZeroOrMore( (node|edge|keyvalue) ) + rbrack ) graph.ignore(comment) return graph
def write_gml(G, path): """ Write the graph G in GML format to the file or file handle path. Parameters ---------- path : filename or filehandle The filename or filehandle to write. Filenames ending in .gz or .gz2 will be compressed. See Also -------- read_gml, parse_gml Notes ----- GML specifications indicate that the file should only use 7bit ASCII text encoding.iso8859-1 (latin-1). This implementation does not support all Python data types as GML data. Nodes, node attributes, edge attributes, and graph attributes must be either dictionaries or single stings or numbers. If they are not an attempt is made to represent them as strings. For example, a list as edge data G[1][2]['somedata']=[1,2,3], will be represented in the GML file as:: edge [ source 1 target 2 somedata "[1, 2, 3]" ] Examples --------- >>> G=nx.path_graph(4) >>> nx.write_gml(G,"test.gml") Filenames ending in .gz or .bz2 will be compressed. >>> nx.write_gml(G,"test.gml.gz") """ for line in generate_gml(G): line += '\n' path.write(line.encode('ascii', 'xmlcharrefreplace')) # fixture for nose tests
