Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.9/dist-packages/networkx/readwrite/json_graph/adjacency.py: 11%

1import networkx as nx 

2 

3__all__ = ["adjacency_data", "adjacency_graph"] 

4 

5_attrs = {"id": "id", "key": "key"} 

6 

7 

8def adjacency_data(G, attrs=_attrs): 

9 """Returns data in adjacency format that is suitable for JSON serialization 

10 and use in JavaScript documents. 

11 

12 Parameters 

13 ---------- 

14 G : NetworkX graph 

15 

16 attrs : dict 

17 A dictionary that contains two keys 'id' and 'key'. The corresponding 

18 values provide the attribute names for storing NetworkX-internal graph 

19 data. The values should be unique. Default value: 

20 :samp:`dict(id='id', key='key')`. 

21 

22 If some user-defined graph data use these attribute names as data keys, 

23 they may be silently dropped. 

24 

25 Returns 

26 ------- 

27 data : dict 

28 A dictionary with adjacency formatted data. 

29 

30 Raises 

31 ------ 

32 NetworkXError 

33 If values in attrs are not unique. 

34 

35 Examples 

36 -------- 

37 >>> from networkx.readwrite import json_graph 

38 >>> G = nx.Graph([(1, 2)]) 

39 >>> data = json_graph.adjacency_data(G) 

40 

41 To serialize with json 

42 

43 >>> import json 

44 >>> s = json.dumps(data) 

45 

46 Notes 

47 ----- 

48 Graph, node, and link attributes will be written when using this format 

49 but attribute keys must be strings if you want to serialize the resulting 

50 data with JSON. 

51 

52 The default value of attrs will be changed in a future release of NetworkX. 

53 

54 See Also 

55 -------- 

56 adjacency_graph, node_link_data, tree_data 

57 """ 

58 multigraph = G.is_multigraph() 

59 id_ = attrs["id"] 

60 # Allow 'key' to be omitted from attrs if the graph is not a multigraph. 

61 key = None if not multigraph else attrs["key"] 

62 if id_ == key: 

63 raise nx.NetworkXError("Attribute names are not unique.") 

64 data = {} 

65 data["directed"] = G.is_directed() 

66 data["multigraph"] = multigraph 

67 data["graph"] = list(G.graph.items()) 

68 data["nodes"] = [] 

69 data["adjacency"] = [] 

70 for n, nbrdict in G.adjacency(): 

71 data["nodes"].append({**G.nodes[n], id_: n}) 

72 adj = [] 

73 if multigraph: 

74 for nbr, keys in nbrdict.items(): 

75 for k, d in keys.items(): 

76 adj.append({**d, id_: nbr, key: k}) 

77 else: 

78 for nbr, d in nbrdict.items(): 

79 adj.append({**d, id_: nbr}) 

80 data["adjacency"].append(adj) 

81 return data 

82 

83 

84@nx._dispatch(graphs=None) 

85def adjacency_graph(data, directed=False, multigraph=True, attrs=_attrs): 

86 """Returns graph from adjacency data format. 

87 

88 Parameters 

89 ---------- 

90 data : dict 

91 Adjacency list formatted graph data 

92 

93 directed : bool 

94 If True, and direction not specified in data, return a directed graph. 

95 

96 multigraph : bool 

97 If True, and multigraph not specified in data, return a multigraph. 

98 

99 attrs : dict 

100 A dictionary that contains two keys 'id' and 'key'. The corresponding 

101 values provide the attribute names for storing NetworkX-internal graph 

102 data. The values should be unique. Default value: 

103 :samp:`dict(id='id', key='key')`. 

104 

105 Returns 

106 ------- 

107 G : NetworkX graph 

108 A NetworkX graph object 

109 

110 Examples 

111 -------- 

112 >>> from networkx.readwrite import json_graph 

113 >>> G = nx.Graph([(1, 2)]) 

114 >>> data = json_graph.adjacency_data(G) 

115 >>> H = json_graph.adjacency_graph(data) 

116 

117 Notes 

118 ----- 

119 The default value of attrs will be changed in a future release of NetworkX. 

120 

121 See Also 

122 -------- 

123 adjacency_graph, node_link_data, tree_data 

124 """ 

125 multigraph = data.get("multigraph", multigraph) 

126 directed = data.get("directed", directed) 

127 if multigraph: 

128 graph = nx.MultiGraph() 

129 else: 

130 graph = nx.Graph() 

131 if directed: 

132 graph = graph.to_directed() 

133 id_ = attrs["id"] 

134 # Allow 'key' to be omitted from attrs if the graph is not a multigraph. 

135 key = None if not multigraph else attrs["key"] 

136 graph.graph = dict(data.get("graph", [])) 

137 mapping = [] 

138 for d in data["nodes"]: 

139 node_data = d.copy() 

140 node = node_data.pop(id_) 

141 mapping.append(node) 

142 graph.add_node(node) 

143 graph.nodes[node].update(node_data) 

144 for i, d in enumerate(data["adjacency"]): 

145 source = mapping[i] 

146 for tdata in d: 

147 target_data = tdata.copy() 

148 target = target_data.pop(id_) 

149 if not multigraph: 

150 graph.add_edge(source, target) 

151 graph[source][target].update(target_data) 

152 else: 

153 ky = target_data.pop(key, None) 

154 graph.add_edge(source, target, key=ky) 

155 graph[source][target][ky].update(target_data) 

156 return graph