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annotate planemo/lib/python3.7/site-packages/networkx/readwrite/leda.py @ 1:56ad4e20f292 draft

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"planemo upload commit 6eee67778febed82ddd413c3ca40b3183a3898f1"
author guerler
date Fri, 31 Jul 2020 00:32:28 -0400
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1 """
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2 Read graphs in LEDA format.
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3
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4 LEDA is a C++ class library for efficient data types and algorithms.
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5
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6 Format
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7 ------
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8 See http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html
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9
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10 """
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11 # Original author: D. Eppstein, UC Irvine, August 12, 2003.
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12 # The original code at http://www.ics.uci.edu/~eppstein/PADS/ is public domain.
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13 __author__ = """Aric Hagberg (hagberg@lanl.gov)"""
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14 # Copyright (C) 2004-2019 by
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15 # Aric Hagberg <hagberg@lanl.gov>
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16 # Dan Schult <dschult@colgate.edu>
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17 # Pieter Swart <swart@lanl.gov>
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18 # All rights reserved.
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19 # BSD license.
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20
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21 __all__ = ['read_leda', 'parse_leda']
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22
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23 import networkx as nx
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24 from networkx.exception import NetworkXError
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25 from networkx.utils import open_file, is_string_like
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26
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27
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28 @open_file(0, mode='rb')
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29 def read_leda(path, encoding='UTF-8'):
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30 """Read graph in LEDA format from path.
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31
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32 Parameters
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33 ----------
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34 path : file or string
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35 File or filename to read. Filenames ending in .gz or .bz2 will be
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36 uncompressed.
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37
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38 Returns
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39 -------
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40 G : NetworkX graph
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41
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42 Examples
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43 --------
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44 G=nx.read_leda('file.leda')
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45
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46 References
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47 ----------
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48 .. [1] http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html
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49 """
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50 lines = (line.decode(encoding) for line in path)
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51 G = parse_leda(lines)
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52 return G
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53
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54
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55 def parse_leda(lines):
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56 """Read graph in LEDA format from string or iterable.
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57
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58 Parameters
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59 ----------
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60 lines : string or iterable
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61 Data in LEDA format.
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62
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63 Returns
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64 -------
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65 G : NetworkX graph
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66
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67 Examples
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68 --------
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69 G=nx.parse_leda(string)
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70
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71 References
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72 ----------
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73 .. [1] http://www.algorithmic-solutions.info/leda_guide/graphs/leda_native_graph_fileformat.html
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74 """
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75 if is_string_like(lines):
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76 lines = iter(lines.split('\n'))
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77 lines = iter([line.rstrip('\n') for line in lines
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78 if not (line.startswith('#') or line.startswith('\n') or line == '')])
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79 for i in range(3):
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80 next(lines)
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81 # Graph
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82 du = int(next(lines)) # -1=directed, -2=undirected
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83 if du == -1:
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84 G = nx.DiGraph()
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85 else:
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86 G = nx.Graph()
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87
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88 # Nodes
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89 n = int(next(lines)) # number of nodes
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90 node = {}
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91 for i in range(1, n + 1): # LEDA counts from 1 to n
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92 symbol = next(lines).rstrip().strip('|{}| ')
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93 if symbol == "":
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94 symbol = str(i) # use int if no label - could be trouble
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95 node[i] = symbol
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96
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97 G.add_nodes_from([s for i, s in node.items()])
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98
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99 # Edges
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100 m = int(next(lines)) # number of edges
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101 for i in range(m):
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102 try:
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103 s, t, reversal, label = next(lines).split()
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104 except:
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105 raise NetworkXError('Too few fields in LEDA.GRAPH edge %d' % (i + 1))
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106 # BEWARE: no handling of reversal edges
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107 G.add_edge(node[int(s)], node[int(t)], label=label[2:-2])
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108 return G