/usr/lib/python2.7/dist-packages/networkx/readwrite/leda.py is in python-networkx 1.8.1-0ubuntu3.
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Read graphs in LEDA format.
LEDA is a C++ class library for efficient data types and algorithms.
Format
------
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
@open_file(0,mode='rb')
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
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
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