/usr/lib/python2.7/dist-packages/networkx/readwrite/json_graph/adjacency.py is in python-networkx 1.8.1-0ubuntu3.
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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 | # 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 copy import deepcopy
from itertools import count,repeat
import json
import networkx as nx
__author__ = """Aric Hagberg <aric.hagberg@gmail.com>"""
__all__ = ['adjacency_data', 'adjacency_graph']
def adjacency_data(G):
"""Return data in adjacency format that is suitable for JSON serialization
and use in Javascript documents.
Parameters
----------
G : NetworkX graph
Returns
-------
data : dict
A dictionary with node-link formatted data.
Examples
--------
>>> from networkx.readwrite import json_graph
>>> G = nx.Graph([(1,2)])
>>> data = json_graph.adjacency_data(G)
To serialize with json
>>> import json
>>> s = json.dumps(data)
Notes
-----
Graph, node, and link attributes will be written when using this format
but attribute keys must be strings if you want to serialize the resulting
data with JSON.
See Also
--------
adjacency_graph, node_link_data, tree_data
"""
multigraph = G.is_multigraph()
data = {}
data['directed'] = G.is_directed()
data['multigraph'] = multigraph
data['graph'] = list(G.graph.items())
data['nodes'] = []
data['adjacency'] = []
for n,nbrdict in G.adjacency_iter():
data['nodes'].append(dict(id=n, **G.node[n]))
adj = []
if multigraph:
for nbr,key in nbrdict.items():
for k,d in key.items():
adj.append(dict(id=nbr, key=k, **d))
else:
for nbr,d in nbrdict.items():
adj.append(dict(id=nbr, **d))
data['adjacency'].append(adj)
return data
def adjacency_graph(data, directed=False, multigraph=True):
"""Return graph from adjacency data format.
Parameters
----------
data : dict
Adjacency list formatted graph data
Returns
-------
G : NetworkX graph
A NetworkX graph object
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.
Examples
--------
>>> from networkx.readwrite import json_graph
>>> G = nx.Graph([(1,2)])
>>> data = json_graph.adjacency_data(G)
>>> H = json_graph.adjacency_graph(data)
See Also
--------
adjacency_graph, node_link_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()
graph.graph = dict(data.get('graph',[]))
mapping=[]
for d in data['nodes']:
node_data = d.copy()
node = node_data.pop('id')
mapping.append(node)
graph.add_node(node, attr_dict=node_data)
for i,d in enumerate(data['adjacency']):
source = mapping[i]
for tdata in d:
target_data = tdata.copy()
target = target_data.pop('id')
key = target_data.pop('key', None)
if not multigraph or key is None:
graph.add_edge(source,target,attr_dict=tdata)
else:
graph.add_edge(source,target,key=key, attr_dict=tdata)
return graph
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