Spaces:
Running
Running
File size: 4,692 Bytes
b200bda |
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 |
import networkx as nx
__all__ = ["adjacency_data", "adjacency_graph"]
_attrs = {"id": "id", "key": "key"}
def adjacency_data(G, attrs=_attrs):
"""Returns data in adjacency format that is suitable for JSON serialization
and use in JavaScript documents.
Parameters
----------
G : NetworkX graph
attrs : dict
A dictionary that contains two keys 'id' 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', 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 adjacency 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.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.
The default value of attrs will be changed in a future release of NetworkX.
See Also
--------
adjacency_graph, node_link_data, tree_data
"""
multigraph = G.is_multigraph()
id_ = attrs["id"]
# Allow 'key' to be omitted from attrs if the graph is not a multigraph.
key = None if not multigraph else attrs["key"]
if id_ == key:
raise nx.NetworkXError("Attribute names are not unique.")
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():
data["nodes"].append({**G.nodes[n], id_: n})
adj = []
if multigraph:
for nbr, keys in nbrdict.items():
for k, d in keys.items():
adj.append({**d, id_: nbr, key: k})
else:
for nbr, d in nbrdict.items():
adj.append({**d, id_: nbr})
data["adjacency"].append(adj)
return data
@nx._dispatch(graphs=None)
def adjacency_graph(data, directed=False, multigraph=True, attrs=_attrs):
"""Returns graph from adjacency data format.
Parameters
----------
data : dict
Adjacency list 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 two keys 'id' 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', 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.adjacency_data(G)
>>> H = json_graph.adjacency_graph(data)
Notes
-----
The default value of attrs will be changed in a future release of NetworkX.
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()
id_ = attrs["id"]
# Allow 'key' to be omitted from attrs if the graph is not a multigraph.
key = None if not multigraph else attrs["key"]
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)
graph.nodes[node].update(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_)
if not multigraph:
graph.add_edge(source, target)
graph[source][target].update(target_data)
else:
ky = target_data.pop(key, None)
graph.add_edge(source, target, key=ky)
graph[source][target][ky].update(target_data)
return graph
|