Spaces:
Running
Running
| 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 | |
| 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 | |