112 lines
2.8 KiB
Python
112 lines
2.8 KiB
Python
# Copyright (C) 2011-2019 by
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# Aric Hagberg <hagberg@lanl.gov>
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# Dan Schult <dschult@colgate.edu>
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# Pieter Swart <swart@lanl.gov>
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# All rights reserved.
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# BSD license.
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"""
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Read and write NetworkX graphs as JavaScript InfoVis Toolkit (JIT) format JSON.
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See the `JIT documentation`_ for more examples.
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Format
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------
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var json = [
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{
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"id": "aUniqueIdentifier",
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"name": "usually a nodes name",
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"data": {
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"some key": "some value",
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"some other key": "some other value"
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},
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"adjacencies": [
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{
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nodeTo:"aNodeId",
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data: {} //put whatever you want here
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},
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'other adjacencies go here...'
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},
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'other nodes go here...'
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];
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.. _JIT documentation: http://thejit.org
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"""
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import json
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import networkx as nx
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from networkx.utils.decorators import not_implemented_for
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__all__ = ['jit_graph', 'jit_data']
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def jit_graph(data, create_using=None):
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"""Read a graph from JIT JSON.
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Parameters
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----------
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data : JSON Graph Object
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create_using : Networkx Graph, optional (default: Graph())
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Return graph of this type. The provided instance will be cleared.
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Returns
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-------
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G : NetworkX Graph built from create_using if provided.
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"""
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if create_using is None:
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G = nx.Graph()
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else:
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G = create_using
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G.clear()
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if nx.utils.is_string_like(data):
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data = json.loads(data)
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for node in data:
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G.add_node(node['id'], **node['data'])
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if node.get('adjacencies') is not None:
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for adj in node['adjacencies']:
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G.add_edge(node['id'], adj['nodeTo'], **adj['data'])
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return G
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@not_implemented_for('multigraph')
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def jit_data(G, indent=None):
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"""Returns data in JIT JSON format.
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Parameters
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----------
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G : NetworkX Graph
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indent: optional, default=None
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If indent is a non-negative integer, then JSON array elements and
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object members will be pretty-printed with that indent level.
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An indent level of 0, or negative, will only insert newlines.
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None (the default) selects the most compact representation.
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Returns
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-------
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data: JIT JSON string
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"""
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json_graph = []
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for node in G.nodes():
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json_node = {
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"id": node,
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"name": node
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}
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# node data
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json_node["data"] = G.nodes[node]
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# adjacencies
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if G[node]:
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json_node["adjacencies"] = []
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for neighbour in G[node]:
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adjacency = {
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"nodeTo": neighbour,
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}
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# adjacency data
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adjacency["data"] = G.edges[node, neighbour]
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json_node["adjacencies"].append(adjacency)
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json_graph.append(json_node)
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return json.dumps(json_graph, indent=indent)
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