This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

Source code for networkx.readwrite.leda

Read graphs in LEDA format.

LEDA is a C++ class library for efficient data types and algorithms.

See http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html

# Original author: D. Eppstein, UC Irvine, August 12, 2003.
# The original code at http://www.ics.uci.edu/~eppstein/PADS/ is public domain.
__author__ = """Aric Hagberg (hagberg@lanl.gov)"""
#    Copyright (C) 2004-2010 by 
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.

__all__ = ['read_leda', 'parse_leda']

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

[docs]def read_leda(path, encoding='UTF-8'): """Read graph in LEDA format from path. Parameters ---------- path : file or string File or filename to read. Filenames ending in .gz or .bz2 will be uncompressed. Returns ------- G : NetworkX graph Examples -------- G=nx.read_leda('file.leda') References ---------- .. [1] http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html """ lines=(line.decode(encoding) for line in path) G=parse_leda(lines) return G
[docs]def parse_leda(lines): """Read graph in LEDA format from string or iterable. Parameters ---------- lines : string or iterable Data in LEDA format. Returns ------- G : NetworkX graph Examples -------- G=nx.parse_leda(string) References ---------- .. [1] http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html """ if is_string_like(lines): lines=iter(lines.split('\n')) lines = iter([line.rstrip('\n') for line in lines \ if not (line.startswith('#') or line.startswith('\n') or line=='')]) for i in range(3): next(lines) # Graph du = int(next(lines)) # -1=directed, -2=undirected if du==-1: G = nx.DiGraph() else: G = nx.Graph() # Nodes n =int(next(lines)) # number of nodes node={} for i in range(1,n+1): # LEDA counts from 1 to n symbol=next(lines).rstrip().strip('|{}| ') if symbol=="": symbol=str(i) # use int if no label - could be trouble node[i]=symbol G.add_nodes_from([s for i,s in node.items()]) # Edges m = int(next(lines)) # number of edges for i in range(m): try: s,t,reversal,label=next(lines).split() except: raise NetworkXError('Too few fields in LEDA.GRAPH edge %d'%(i+1)) # BEWARE: no handling of reversal edges G.add_edge(node[int(s)],node[int(t)],label=label[2:-2]) return G