/usr/lib/python3/dist-packages/networkx/readwrite/json_graph/node_link.py is in python3-networkx 1.11-2.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 | # Copyright (C) 2011-2013 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>
# All rights reserved.
# BSD license.
from itertools import chain, count
import json
import networkx as nx
from networkx.utils import make_str
__author__ = """Aric Hagberg <hagberg@lanl.gov>"""
__all__ = ['node_link_data', 'node_link_graph']
_attrs = dict(id='id', source='source', target='target', key='key')
def node_link_data(G, attrs=_attrs):
"""Return data in node-link format that is suitable for JSON serialization
and use in Javascript documents.
Parameters
----------
G : NetworkX graph
attrs : dict
A dictionary that contains four keys 'id', 'source', 'target' and
'key'. The corresponding values provide the attribute names for storing
NetworkX-internal graph data. The values should be unique. Default
value:
:samp:`dict(id='id', source='source', target='target', key='key')`.
If some user-defined graph data use these attribute names as data keys,
they may be silently dropped.
Returns
-------
data : dict
A dictionary with node-link formatted data.
Raises
------
NetworkXError
If values in attrs are not unique.
Examples
--------
>>> from networkx.readwrite import json_graph
>>> G = nx.Graph([(1,2)])
>>> data = json_graph.node_link_data(G)
To serialize with json
>>> import json
>>> s = json.dumps(data)
Notes
-----
Graph, node, and link attributes are stored in this format. Note that
attribute keys will be converted to strings in order to comply with
JSON.
The default value of attrs will be changed in a future release of NetworkX.
See Also
--------
node_link_graph, adjacency_data, tree_data
"""
multigraph = G.is_multigraph()
id_ = attrs['id']
source = attrs['source']
target = attrs['target']
# Allow 'key' to be omitted from attrs if the graph is not a multigraph.
key = None if not multigraph else attrs['key']
if len(set([source, target, key])) < 3:
raise nx.NetworkXError('Attribute names are not unique.')
mapping = dict(zip(G, count()))
data = {}
data['directed'] = G.is_directed()
data['multigraph'] = multigraph
data['graph'] = G.graph
data['nodes'] = [dict(chain(G.node[n].items(), [(id_, n)])) for n in G]
if multigraph:
data['links'] = [
dict(chain(d.items(),
[(source, mapping[u]), (target, mapping[v]), (key, k)]))
for u, v, k, d in G.edges_iter(keys=True, data=True)]
else:
data['links'] = [
dict(chain(d.items(),
[(source, mapping[u]), (target, mapping[v])]))
for u, v, d in G.edges_iter(data=True)]
return data
def node_link_graph(data, directed=False, multigraph=True, attrs=_attrs):
"""Return graph from node-link data format.
Parameters
----------
data : dict
node-link formatted graph data
directed : bool
If True, and direction not specified in data, return a directed graph.
multigraph : bool
If True, and multigraph not specified in data, return a multigraph.
attrs : dict
A dictionary that contains four keys 'id', 'source', 'target' and
'key'. The corresponding values provide the attribute names for storing
NetworkX-internal graph data. Default value:
:samp:`dict(id='id', source='source', target='target', key='key')`.
Returns
-------
G : NetworkX graph
A NetworkX graph object
Examples
--------
>>> from networkx.readwrite import json_graph
>>> G = nx.Graph([(1,2)])
>>> data = json_graph.node_link_data(G)
>>> H = json_graph.node_link_graph(data)
Notes
-----
The default value of attrs will be changed in a future release of NetworkX.
See Also
--------
node_link_data, adjacency_data, tree_data
"""
multigraph = data.get('multigraph', multigraph)
directed = data.get('directed', directed)
if multigraph:
graph = nx.MultiGraph()
else:
graph = nx.Graph()
if directed:
graph = graph.to_directed()
id_ = attrs['id']
source = attrs['source']
target = attrs['target']
# Allow 'key' to be omitted from attrs if the graph is not a multigraph.
key = None if not multigraph else attrs['key']
mapping = []
graph.graph = data.get('graph', {})
c = count()
for d in data['nodes']:
node = d.get(id_, next(c))
mapping.append(node)
nodedata = dict((make_str(k), v) for k, v in d.items() if k != id_)
graph.add_node(node, **nodedata)
for d in data['links']:
src = d[source]
tgt = d[target]
if not multigraph:
edgedata = dict((make_str(k), v) for k, v in d.items()
if k != source and k != target)
graph.add_edge(mapping[src], mapping[tgt], **edgedata)
else:
ky = d.get(key, None)
edgedata = dict((make_str(k), v) for k, v in d.items()
if k != source and k != target and k != key)
graph.add_edge(mapping[src], mapping[tgt], ky, **edgedata)
return graph
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