Spaces:
Running
Running
| """ | |
| 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. | |
| __all__ = ["read_leda", "parse_leda"] | |
| import networkx as nx | |
| from networkx.exception import NetworkXError | |
| from networkx.utils import open_file | |
| 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 isinstance(lines, str): | |
| lines = iter(lines.split("\n")) | |
| lines = iter( | |
| [ | |
| line.rstrip("\n") | |
| for line in lines | |
| if not (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 BaseException as err: | |
| raise NetworkXError(f"Too few fields in LEDA.GRAPH edge {i+1}") from err | |
| # BEWARE: no handling of reversal edges | |
| G.add_edge(node[int(s)], node[int(t)], label=label[2:-2]) | |
| return G | |