def test_to_tuple():
a_list = [1, 2, [1, 3]]
actual = to_tuple(a_list)
expected = (1, 2, (1, 3))
assert actual == expected
a_tuple = (1, 2)
actual = to_tuple(a_tuple)
expected = a_tuple
assert actual == expected
a_mix = (1, 2, [1, 3])
actual = to_tuple(a_mix)
expected = (1, 2, (1, 3))
assert actual == expected
def node_link_graph(data, directed=False, multigraph=True, attrs=None):
"""Returns 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 five keys 'source', 'target', 'name',
'key' and 'link'. The corresponding values provide the attribute
names for storing NetworkX-internal graph data. Default value:
dict(source='source', target='target', name='id',
key='key', link='links')
Returns
-------
G : NetworkX graph
A NetworkX graph object
Examples
--------
>>> from networkx import json_graph
>>> G = nx.Graph([('A', 'B')])
>>> data = json_graph.node_link_data(G)
>>> H = json_graph.node_link_graph(data)
Notes
-----
Attribute 'key' is only used for multigraphs.
See Also
--------
node_link_data, adjacency_data, tree_data
"""
# Allow 'attrs' to keep default values.
if attrs is None:
attrs = _attrs
else:
attrs.update({k: v for k, v in _attrs.items() if k not in attrs})
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()
name = attrs['name']
source = attrs['source']
target = attrs['target']
links = attrs['link']
# Allow 'key' to be omitted from attrs if the graph is not a multigraph.
key = None if not multigraph else attrs['key']
graph.graph = data.get('graph', {})
c = count()
for d in data['nodes']:
node = to_tuple(d.get(name, next(c)))
nodedata = dict((make_str(k), v) for k, v in d.items() if k != name)
graph.add_node(node, **nodedata)
for d in data[links]:
src = tuple(d[source]) if isinstance(d[source], list) else d[source]
tgt = tuple(d[target]) if isinstance(d[target], list) else 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(src, 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(src, tgt, ky, **edgedata)
return graph
def node_link_graph(data, directed=False, multigraph=True, attrs=None):
"""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 five keys 'source', 'target', 'name',
'key' and 'link'. The corresponding values provide the attribute
names for storing NetworkX-internal graph data. Default value:
dict(source='source', target='target', name='id',
key='key', link='links')
Returns
-------
G : NetworkX graph
A NetworkX graph object
Examples
--------
>>> from networkx.readwrite import json_graph
>>> G = nx.Graph([('A', 'B')])
>>> data = json_graph.node_link_data(G)
>>> H = json_graph.node_link_graph(data)
Notes
-----
Attribute 'key' is only used for multigraphs.
See Also
--------
node_link_data, adjacency_data, tree_data
"""
# Allow 'attrs' to keep default values.
if attrs is None:
attrs = _attrs
else:
attrs.update({k: v for k, v in _attrs.items() if k not in attrs})
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()
name = attrs['name']
source = attrs['source']
target = attrs['target']
links = attrs['link']
# Allow 'key' to be omitted from attrs if the graph is not a multigraph.
key = None if not multigraph else attrs['key']
graph.graph = data.get('graph', {})
c = count()
for d in data['nodes']:
node = to_tuple(d.get(name, next(c)))
nodedata = dict((make_str(k), v) for k, v in d.items() if k != name)
graph.add_node(node, **nodedata)
for d in data[links]:
src = tuple(d[source]) if isinstance(d[source], list) else d[source]
tgt = tuple(d[target]) if isinstance(d[target], list) else 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(src, 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(src, tgt, ky, **edgedata)
return graph
