| """ |
| 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 |
| |
