Python networkx.write_gml方法代码示例

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def write_graph(self, G=None, subgraph_file=None):
        if G is None:
            G = self.context_graph
        if subgraph_file is None:
            subgraph_file = self.context_graph_file
        logging.info("Writing graph.")
        # write the graph out
        file_format = subgraph_file.split(".")[-1]
        if file_format == "graphml":
            nx.write_graphml(G, subgraph_file)
        elif file_format == "gml":
            nx.write_gml(G, subgraph_file)
        elif file_format == "gexf":
            nx.write_gexf(G, subgraph_file)
        elif file_format == "net":
            nx.write_pajek(G, subgraph_file)
        elif file_format == "yaml":
            nx.write_yaml(G, subgraph_file)
        elif file_format == "gpickle":
            nx.write_gpickle(G, subgraph_file)
        else:
            print "File format not found, writing graphml."
            nx.write_graphml(G, subgraph_file) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def create_report_graph(self):
        for (fallacy_type, localized) in get_fallacy_types():
            node = unidecode(self.normalize(localized))

            graph.add_node(node, type="fallacy", Weight=10)

            for premise in Premise.objects.filter(
                    reports__fallacy_type=fallacy_type):

                #graph.add_node(premise.argument.pk, type="argument")

                #graph.add_edge(premise.argument.pk, node, type="reported")

                if premise.argument.channel:
                    channel_node = unidecode(premise.argument.channel.title)

                    graph.add_node(channel_node, type="channel",
                                   Weight=premise.argument.channel.contentions.count() * 30)
                    graph.add_edge(channel_node, node, type="reported")


        nx.write_gml(graph, 'reports.gml') 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def WriteAdjList(adjList, graphName, colorLabels=None):
    g = nx.Graph()

    for i in range(0,len(adjList)):
        if (colorLabels is not None):
            g.add_node(i, color=colorLabels[i], id=str(i))
        else:
            g.add_node(i)

    idx = 0
    for i in range(0,len(adjList)):
        for j in range(0,len(adjList[i])):
            g.add_edge(i, adjList[i][j][0], capacity=adjList[i][j][1])

    if (graphName.find("gml") >= 0):
        nx.write_gml(g, graphName)
    elif (graphName.find("gexf") >= 0):
        nx.write_gexf(g, graphName)
    elif (graphName.find("graphml") >= 0):
        nx.write_graphml(g, graphName) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def test_quotes(self):
        # https://github.com/networkx/networkx/issues/1061
        # Encoding quotes as HTML entities.
        G = nx.path_graph(1)
        attr = 'This is "quoted" and this is a copyright: ' + unichr(169)
        G.node[0]['demo'] = attr
        fobj = tempfile.NamedTemporaryFile()
        nx.write_gml(G, fobj)
        fobj.seek(0)
        # Should be bytes in 2.x and 3.x
        data = fobj.read().strip().decode('ascii')
        answer = """graph [
  name "path_graph(1)"
  node [
    id 0
    label 0
    demo "This is "quoted" and this is a copyright: ©"
  ]
]"""
        assert_equal(data, answer) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def test_quotes(self):
        # https://github.com/networkx/networkx/issues/1061
        # Encoding quotes as HTML entities.
        G = nx.path_graph(1)
        G.name = "path_graph(1)"
        attr = 'This is "quoted" and this is a copyright: ' + unichr(169)
        G.nodes[0]['demo'] = attr
        fobj = tempfile.NamedTemporaryFile()
        nx.write_gml(G, fobj)
        fobj.seek(0)
        # Should be bytes in 2.x and 3.x
        data = fobj.read().strip().decode('ascii')
        answer = """graph [
  name "path_graph(1)"
  node [
    id 0
    label "0"
    demo "This is "quoted" and this is a copyright: ©"
  ]
]"""
        assert_equal(data, answer) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def test_unicode_node(self):
        node = 'node' + unichr(169)
        G = nx.Graph()
        G.add_node(node)
        fobj = tempfile.NamedTemporaryFile()
        nx.write_gml(G, fobj)
        fobj.seek(0)
        # Should be bytes in 2.x and 3.x
        data = fobj.read().strip().decode('ascii')
        answer = """graph [
  node [
    id 0
    label "node©"
  ]
]"""
        assert_equal(data, answer) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def test_float_label(self):
        node = 1.0
        G = nx.Graph()
        G.add_node(node)
        fobj = tempfile.NamedTemporaryFile()
        nx.write_gml(G, fobj)
        fobj.seek(0)
        # Should be bytes in 2.x and 3.x
        data = fobj.read().strip().decode('ascii')
        answer = """graph [
  node [
    id 0
    label "1.0"
  ]
]"""
        assert_equal(data, answer) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def _write_gml(G, path):
    """
    Wrapper around nx.write_gml
    """
    import networkx as nx
    return nx.write_gml(G, path, stringizer=str) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def to_gml(graph, outfilename, logfile=sys.stderr):
    """Write the given read graph to a GML file."""
    if not outfilename.endswith('.gml'):
        print('[kevlar] WARNING: GML files usually need extension .gml',
              file=logfile)
    networkx.write_gml(graph, outfilename, stringizer=str)
    message = '[kevlar] graph written to {}'.format(outfilename)
    print(message, file=logfile) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def dag(recipe_folder, config, packages="*", format='gml', hide_singletons=False):
    """
    Export the DAG of packages to a graph format file for visualization
    """
    dag, name2recipes = graph.build(utils.get_recipes(recipe_folder, "*"), config)
    if packages != "*":
        dag = graph.filter(dag, packages)
    if hide_singletons:
        for node in nx.nodes(dag):
            if dag.degree(node) == 0:
                dag.remove_node(node)
    if format == 'gml':
        nx.write_gml(dag, sys.stdout.buffer)
    elif format == 'dot':
        write_dot(dag, sys.stdout)
    elif format == 'txt':
        subdags = sorted(map(sorted, nx.connected_components(dag.to_undirected())))
        subdags = sorted(subdags, key=len, reverse=True)
        singletons = []
        for i, s in enumerate(subdags):
            if len(s) == 1:
                singletons += s
                continue
            print("# subdag {0}".format(i))
            subdag = dag.subgraph(s)
            recipes = [
                recipe for package in nx.topological_sort(subdag)
                for recipe in name2recipes[package]]
            print('\n'.join(recipes) + '\n')
        if not hide_singletons:
            print('# singletons')
            recipes = [recipe for package in singletons for recipe in
                       name2recipes[package]]
            print('\n'.join(recipes) + '\n') 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def create_conjunction_graph(self):
        fallacy_map = {
            unidecode(key): value
            for (key, value) in
            get_fallacy_types()
        }
        for contention in Contention.objects.all():
            for premise in contention.premises.all():
                fallacies = filter(None, premise.reports.values_list(
                    'fallacy_type', flat=True))
                fallacies = [
                    fallacy_map[unidecode(_f)]
                    for _f in fallacies
                ]
                fallacies_set = set(fallacies)
                for fallacy in fallacies_set:
                    graph.add_edges_from(
                        [
                            (unidecode(self.normalize(fallacy)),
                             unidecode(self.normalize(_f)))
                            for _f in fallacies_set
                            if _f != fallacy
                        ]
                    )


        nx.write_gml(graph, 'conjunction.gml') 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def reformat_network(single_gml, output_dir, isolateName):
    """Reformats the output of generate_network() for linear graphs to allow input into merge_graphs()"""
    for adj in single_gml._adj:
        for x in single_gml._adj[adj]:
            y = single_gml._adj[adj][x]

            y.pop('members')
            zero = {'members': 0}
            y.update(zero)

            genomes = {'genomeIDs': '0'}
            y.update(genomes)

    for node in single_gml._node:
        y = single_gml._node[node]
        y.pop('members')

        zero = {
            'members': 0
        }  #members are assigned intbitset[0]. needs to be 0
        y.update(zero)

        to_replace = {"[": "", "]": "", "'": ""}
        y['centroid'] = replace_all(str(y['centroid']), to_replace)
        y['dna'] = replace_all(str(y['dna']), to_replace)
        y['protein'] = replace_all(str(y['protein']), to_replace)

        y['hasEnd'] = int(y['hasEnd'])
        y['mergedDNA'] = int(y['mergedDNA'])
        y['paralog'] = int(y['paralog'])

        y['longCentroidID'] = list(y['longCentroidID'])
        y['seqIDs'] = list(y['seqIDs'])

    single_gml.graph.update({'isolateNames':
                             'x'})  # isolateName from gff filename
    nx.write_gml(single_gml, output_dir + "final_graph.gml")

    return single_gml 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def write_gml(self, path):

        """
        Write a GML file.

        Args:
            path (str): The file path.
        """

        nx.write_gml(self.graph, path) 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def construct_graph(frame, ligands=None, prefix="frame", threshold=6.7, save_graph=True):
    atom_filter = "(name CB and protein) or (name CA and resname GLY)"
    if ligands:
        ligands = ligands.split(",")

        for ligand in ligands:
            arr = ligand.split(":")
            atom_filter += " or (name %s and resname %s)" % (arr[1], arr[0])

    atoms = frame.topology.select(atom_filter)

    nodes_range = len(atoms)

    nodes = range(0, len(atoms))
    edges = []

    for i in range(nodes_range - 1):
        for j in range(i + 1, nodes_range):
            dist = calc_distance(frame, atoms[i], atoms[j]) * 10
            if dist < threshold:
                edges.append((i, j))

    protein_graph = nx.Graph()
    protein_graph.add_nodes_from(nodes)
    protein_graph.add_edges_from(edges)

    if save_graph:
        nx.write_gml(protein_graph, "%s_graph.gml" % prefix)
        nx.write_graphml(protein_graph, "%s_graph.graphml" % prefix)

    return protein_graph 

# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import write_gml [as 别名]
def WriteGraph(g, graphName, colorLabels=None):

    if (graphName.find("gml") >= 0):
        nx.write_gml(g, graphName)
    elif (graphName.find("gexf") >= 0):
        nx.write_gexf(g, graphName)
    elif (graphName.find("graphml") >= 0):
        nx.write_graphml(g, graphName)