NetworkX

Source code for networkx.readwrite.gml

"""
Read graphs in GML format.

"GML, the G>raph Modelling Language, is our proposal for a portable
file format for graphs. GML's key features are portability, simple
syntax, extensibility and flexibility. A GML file consists of a
hierarchical key-value lists. Graphs can be annotated with arbitrary
data structures. The idea for a common file format was born at the
GD'95; this proposal is the outcome of many discussions. GML is the
standard file format in the Graphlet graph editor system. It has been
overtaken and adapted by several other systems for drawing graphs."

See http://www.infosun.fim.uni-passau.de/Graphlet/GML/gml-tr.html

Requires pyparsing: http://pyparsing.wikispaces.com/

Format
------
See http://www.infosun.fim.uni-passau.de/Graphlet/GML/gml-tr.html
for format specification.

Example graphs in GML format:
http://www-personal.umich.edu/~mejn/netdata/
"""
__author__ = """Aric Hagberg (hagberg@lanl.gov)"""
#    Copyright (C) 2008-2010 by 
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.

__all__ = ['read_gml', 'parse_gml', 'generate_gml', 'write_gml']

import networkx as nx
from networkx.exception import NetworkXError
from networkx.utils import is_string_like, open_file


@open_file(0,mode='rb')
[docs]def read_gml(path,encoding='UTF-8',relabel=False): """Read graph in GML format from path. Parameters ---------- path : filename or filehandle The filename or filehandle to read from. encoding : string, optional Text encoding. 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/ 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=(line.decode(encoding) for line in path) G=parse_gml(lines,relabel=relabel) return G
[docs]def parse_gml(lines, relabel=True): """Parse GML graph from a string or iterable. Parameters ---------- lines : string or iterable Data in GML format. 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, read_gml Notes ----- This stores nested GML attributes as dictionaries in the NetworkX graph, node, and edge attribute structures. Requires pyparsing: http://pyparsing.wikispaces.com/ References ---------- GML specification: http://www.infosun.fim.uni-passau.de/Graphlet/GML/gml-tr.html """ try: from pyparsing import ParseException except ImportError: try: from matplotlib.pyparsing import ParseException except: raise ImportError('Import Error: not able to import pyparsing:', 'http://pyparsing.wikispaces.com/') try: data = "".join(lines) gml = pyparse_gml() tokens =gml.parseString(data) except ParseException as err: print((err.line)) print((" "*(err.column-1) + "^")) print(err) raise # function to recursively make dicts of key/value pairs def wrap(tok): listtype=type(tok) result={} for k,v in tok: if type(v)==listtype: result[str(k)]=wrap(v) else: result[str(k)]=v return result # Set flag multigraph=False # but assume multigraphs to start if tokens.directed==1: G=nx.MultiDiGraph() else: G=nx.MultiGraph() for k,v in tokens.asList(): if k=="node": vdict=wrap(v) node=vdict['id'] G.add_node(node,attr_dict=vdict) elif k=="edge": vdict=wrap(v) source=vdict.pop('source') target=vdict.pop('target') if G.has_edge(source,target): multigraph=True G.add_edge(source,target,attr_dict=vdict) else: G.graph[k]=v # switch to Graph or DiGraph if no parallel edges were found. if not multigraph: if G.is_directed(): G=nx.DiGraph(G) else: G=nx.Graph(G) if relabel: # relabel, but check for duplicate labels first mapping=[(n,d['label']) for n,d in G.node.items()] x,y=zip(*mapping) if len(set(y))!=len(G): raise NetworkXError('Failed to relabel nodes: ' 'duplicate node labels found. ' 'Use relabel=False.') G=nx.relabel_nodes(G,dict(mapping)) 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
[docs]def generate_gml(G): """Generate a single entry of the graph G in GML format. Parameters ---------- G : NetworkX graph Returns ------- lines: string Lines in GML format. Notes ----- 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]" ] """ # recursively make dicts into gml brackets def listify(d,indent,indentlevel): result='[ \n' for k,v in d.items(): if type(v)==dict: v=listify(v,indent,indentlevel+1) result += (indentlevel+1)*indent + \ string_item(k,v,indentlevel*indent)+'\n' return result+indentlevel*indent+"]" def string_item(k,v,indent): # try to make a string of the data if type(v)==dict: v=listify(v,indent,2) elif is_string_like(v): v='"%s"'%v elif type(v)==bool: v=int(v) return "%s %s"%(k,v) # check for attributes or assign empty dict if hasattr(G,'graph_attr'): graph_attr=G.graph_attr else: graph_attr={} if hasattr(G,'node_attr'): node_attr=G.node_attr else: node_attr={} indent=2*' ' count=iter(range(len(G))) node_id={} yield "graph [" if G.is_directed(): yield indent+"directed 1" # write graph attributes for k,v in G.graph.items(): if k == 'directed': continue yield indent+string_item(k,v,indent) # write nodes for n in G: yield indent+"node [" # get id or assign number nid=G.node[n].get('id',next(count)) node_id[n]=nid yield 2*indent+"id %s"%nid label=G.node[n].get('label',n) if is_string_like(label): label='"%s"'%label yield 2*indent+'label %s'%label if n in G: for k,v in G.node[n].items(): if k=='id' or k == 'label': continue yield 2*indent+string_item(k,v,indent) yield indent+"]" # write edges for u,v,edgedata in G.edges_iter(data=True): yield indent+"edge [" yield 2*indent+"source %s"%node_id[u] yield 2*indent+"target %s"%node_id[v] for k,v in edgedata.items(): if k=='source': continue if k=='target': continue yield 2*indent+string_item(k,v,indent) yield indent+"]" yield "]"
@open_file(1,mode='wb')
[docs]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('latin-1')) # fixture for nose tests
def setup_module(module): from nose import SkipTest try: import pyparsing except: try: import matplotlib.pyparsing except: raise SkipTest("pyparsing not available") # fixture for nose tests def teardown_module(module): import os os.unlink('test.gml') os.unlink('test.gml.gz')