如何从字典制作加权图?
How to make weighted graph from dictionary?
我正在尝试根据字典制作加权图。我认为我获取数据的方式使它变得困难。
我得到的数据如下:
graph = {}
graph["A"] = {}
graph["A"] ["B"] = 1
graph["A"] ["C"] = 3
graph["A"] ["D"] = 2
graph["B"] = {}
graph["B"] ["D"] = 7
graph["B"] ["F"] = 5
graph["C"] = {}
graph["C"] ["E"] = 5
graph["D"] = {}
graph["D"] ["B"] = 7
graph["D"] ["E"] = 1
graph["E"] = {}
graph["E"] ["F"] = 4
graph["F"] = {}
父节点是一个字典,它存储了具有边权重的邻居。
我可以使用 networkx 制作一个未加权的图:
for k, v in graph.items():
G.add_edges_from(([(k,t) for t in v]))
但是想不出给边加权重的方法
不幸的是,我无法编辑获取数据的方式,这是我能想到的让它工作的唯一选择。请帮助
假设 G 是您的图表:
graph = {}
graph["A"] = {}
graph["A"] ["B"] = 1
graph["A"] ["C"] = 3
graph["A"] ["D"] = 2
graph["B"] = {}
graph["B"] ["D"] = 7
graph["B"] ["F"] = 5
graph["C"] = {}
graph["C"] ["E"] = 5
graph["D"] = {}
graph["D"] ["B"] = 7
graph["D"] ["E"] = 1
graph["E"] = {}
graph["E"] ["F"] = 4
graph["F"] = {}
for k,v in graph.items():
for l, w in v.items():
print(k, l, w)
G.add_edge(k,l, weight=w)
使用你的例子graph
。将 graph
中的键与其值中的每个项目组合起来。使用 .add_weighted_edges_from 添加边。
import networkx as nx
G = nx.Graph()
for k, v in graph.items():
edges = [(k,b,w) for b,w in v.items()]
print(edges)
#G.add_weighted_edges_from(edges)
G.add_weighted_edges_from((k,b,w) for b,w in v.items())
>>>
[('A', 'B', 1), ('A', 'C', 3), ('A', 'D', 2)]
[('B', 'D', 7), ('B', 'F', 5)]
[('C', 'E', 5)]
[('D', 'B', 7), ('D', 'E', 1)]
[('E', 'F', 4)]
[]
---
>>> for edge in G.edges.data():
... print(edge)
('A', 'B', {'weight': 1})
('A', 'C', {'weight': 3})
('A', 'D', {'weight': 2})
('B', 'D', {'weight': 7})
('B', 'F', {'weight': 5})
('C', 'E', {'weight': 5})
('D', 'E', {'weight': 1})
('F', 'E', {'weight': 4})
我正在尝试根据字典制作加权图。我认为我获取数据的方式使它变得困难。 我得到的数据如下:
graph = {}
graph["A"] = {}
graph["A"] ["B"] = 1
graph["A"] ["C"] = 3
graph["A"] ["D"] = 2
graph["B"] = {}
graph["B"] ["D"] = 7
graph["B"] ["F"] = 5
graph["C"] = {}
graph["C"] ["E"] = 5
graph["D"] = {}
graph["D"] ["B"] = 7
graph["D"] ["E"] = 1
graph["E"] = {}
graph["E"] ["F"] = 4
graph["F"] = {}
父节点是一个字典,它存储了具有边权重的邻居。
我可以使用 networkx 制作一个未加权的图:
for k, v in graph.items():
G.add_edges_from(([(k,t) for t in v]))
但是想不出给边加权重的方法
不幸的是,我无法编辑获取数据的方式,这是我能想到的让它工作的唯一选择。请帮助
假设 G 是您的图表:
graph = {}
graph["A"] = {}
graph["A"] ["B"] = 1
graph["A"] ["C"] = 3
graph["A"] ["D"] = 2
graph["B"] = {}
graph["B"] ["D"] = 7
graph["B"] ["F"] = 5
graph["C"] = {}
graph["C"] ["E"] = 5
graph["D"] = {}
graph["D"] ["B"] = 7
graph["D"] ["E"] = 1
graph["E"] = {}
graph["E"] ["F"] = 4
graph["F"] = {}
for k,v in graph.items():
for l, w in v.items():
print(k, l, w)
G.add_edge(k,l, weight=w)
使用你的例子graph
。将 graph
中的键与其值中的每个项目组合起来。使用 .add_weighted_edges_from 添加边。
import networkx as nx
G = nx.Graph()
for k, v in graph.items():
edges = [(k,b,w) for b,w in v.items()]
print(edges)
#G.add_weighted_edges_from(edges)
G.add_weighted_edges_from((k,b,w) for b,w in v.items())
>>>
[('A', 'B', 1), ('A', 'C', 3), ('A', 'D', 2)]
[('B', 'D', 7), ('B', 'F', 5)]
[('C', 'E', 5)]
[('D', 'B', 7), ('D', 'E', 1)]
[('E', 'F', 4)]
[]
---
>>> for edge in G.edges.data():
... print(edge)
('A', 'B', {'weight': 1})
('A', 'C', {'weight': 3})
('A', 'D', {'weight': 2})
('B', 'D', {'weight': 7})
('B', 'F', {'weight': 5})
('C', 'E', {'weight': 5})
('D', 'E', {'weight': 1})
('F', 'E', {'weight': 4})