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comparison planemo/lib/python3.7/site-packages/networkx/algorithms/vitality.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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0:d30785e31577 1:56ad4e20f292
1 # Copyright (C) 2010 by
2 # Aric Hagberg (hagberg@lanl.gov)
3 # Renato Fabbri
4 # Copyright (C) 2012 by
5 # Aric Hagberg <hagberg@lanl.gov>
6 # Dan Schult <dschult@colgate.edu>
7 # Pieter Swart <swart@lanl.gov>
8 # Copyright (C) 2016-2019 by NetworkX developers.
9 #
10 # All rights reserved.
11 # BSD license.
12 """
13 Vitality measures.
14 """
15 from functools import partial
16
17 import networkx as nx
18
19 __all__ = ['closeness_vitality']
20
21
22 def closeness_vitality(G, node=None, weight=None, wiener_index=None):
23 """Returns the closeness vitality for nodes in the graph.
24
25 The *closeness vitality* of a node, defined in Section 3.6.2 of [1],
26 is the change in the sum of distances between all node pairs when
27 excluding that node.
28
29 Parameters
30 ----------
31 G : NetworkX graph
32 A strongly-connected graph.
33
34 weight : string
35 The name of the edge attribute used as weight. This is passed
36 directly to the :func:`~networkx.wiener_index` function.
37
38 node : object
39 If specified, only the closeness vitality for this node will be
40 returned. Otherwise, a dictionary mapping each node to its
41 closeness vitality will be returned.
42
43 Other parameters
44 ----------------
45 wiener_index : number
46 If you have already computed the Wiener index of the graph
47 `G`, you can provide that value here. Otherwise, it will be
48 computed for you.
49
50 Returns
51 -------
52 dictionary or float
53 If `node` is None, this function returns a dictionary
54 with nodes as keys and closeness vitality as the
55 value. Otherwise, it returns only the closeness vitality for the
56 specified `node`.
57
58 The closeness vitality of a node may be negative infinity if
59 removing that node would disconnect the graph.
60
61 Examples
62 --------
63 >>> G = nx.cycle_graph(3)
64 >>> nx.closeness_vitality(G)
65 {0: 2.0, 1: 2.0, 2: 2.0}
66
67 See Also
68 --------
69 closeness_centrality
70
71 References
72 ----------
73 .. [1] Ulrik Brandes, Thomas Erlebach (eds.).
74 *Network Analysis: Methodological Foundations*.
75 Springer, 2005.
76 <http://books.google.com/books?id=TTNhSm7HYrIC>
77
78 """
79 if wiener_index is None:
80 wiener_index = nx.wiener_index(G, weight=weight)
81 if node is not None:
82 after = nx.wiener_index(G.subgraph(set(G) - {node}), weight=weight)
83 return wiener_index - after
84 vitality = partial(closeness_vitality, G, weight=weight,
85 wiener_index=wiener_index)
86 # TODO This can be trivially parallelized.
87 return {v: vitality(node=v) for v in G}