将 networkx 2D 图转换为 3D 交互式图

如何解决将 networkx 2D 图转换为 3D 交互式图

我在 networkx 中有以下图表：

import matplotlib.pyplot as plt
import networkx as nx

G = nx.Graph()
G.add_edge(1,2,weight = 1)
G.add_edge(2,3,weight = 3)
G.add_edge(4,5,weight = 2)
G.add_edge(6,weight = 4)
G.add_edge(6,4,weight = 6)


plt.figure(figsize=(12,12))
edges = G.edges()
pos = nx.spring_layout(G,k = 0.5) # k regulates the distance between nodes
weights = [G[u][v]['weight'] for u,v in edges]
nx.draw(G,with_labels=True,node_color='skyblue',font_weight='bold',width=weights,pos=pos)

有没有办法将这个 2D 图形转换为 3D 图形？坐标无所谓。我只对绘图的交互能力感兴趣（即我能够旋转图形）。我知道 plotly 有能力做这样的 plots，但我不确定如何以这种方式组合我的 2D networkx 图和 plotly

解决方法

免责声明：我无论如何都不是 networkx 方面的专家，因此 this article 在回答您的问题时非常有价值。我已经尽可能地适应了代码以适合您的示例。

我们首先要在调用 dim=3 时设置参数 nx.spring_layout 以确保您的坐标为 3D。然后我们提取所有节点和边的 x、y、z 坐标，并通过跟踪将它们传递给 Plotly 中的 go.Scatter3d 方法。

更新：要在悬停文本中添加权重，我们可以将它们锚定到边缘之间的中点，如here 所述。

# import matplotlib.pyplot as plt
import plotly.graph_objects as go
import networkx as nx

G = nx.Graph()
G.add_edge(1,2,weight = 1)
G.add_edge(2,3,weight = 3)
G.add_edge(4,5,weight = 2)
G.add_edge(6,weight = 4)
G.add_edge(6,4,weight = 6)

edge_weights =[1,6]

Num_nodes = len(G.nodes)

# plt.figure(figsize=(5,5))
edges = G.edges()

# ## update to 3d dimension
spring_3D = nx.spring_layout(G,dim = 3,k = 0.5) # k regulates the distance between nodes
# weights = [G[u][v]['weight'] for u,v in edges]
# nx.draw(G,with_labels=True,node_color='skyblue',font_weight='bold',width=weights,pos=pos)

# we need to seperate the X,Y,Z coordinates for Plotly
# NOTE: spring_3D is a dictionary where the keys are 1,...,6
x_nodes= [spring_3D[key][0] for key in spring_3D.keys()] # x-coordinates of nodes
y_nodes = [spring_3D[key][1] for key in spring_3D.keys()] # y-coordinates
z_nodes = [spring_3D[key][2] for key in spring_3D.keys()] # z-coordinates

#we need to create lists that contain the starting and ending coordinates of each edge.
x_edges=[]
y_edges=[]
z_edges=[]

#create lists holding midpoints that we will use to anchor text
xtp = []
ytp = []
ztp = []

#need to fill these with all of the coordinates
for edge in edges:
    #format: [beginning,ending,None]
    x_coords = [spring_3D[edge[0]][0],spring_3D[edge[1]][0],None]
    x_edges += x_coords
    xtp.append(0.5*(spring_3D[edge[0]][0]+ spring_3D[edge[1]][0]))

    y_coords = [spring_3D[edge[0]][1],spring_3D[edge[1]][1],None]
    y_edges += y_coords
    ytp.append(0.5*(spring_3D[edge[0]][1]+ spring_3D[edge[1]][1]))

    z_coords = [spring_3D[edge[0]][2],spring_3D[edge[1]][2],None]
    z_edges += z_coords
    ztp.append(0.5*(spring_3D[edge[0]][2]+ spring_3D[edge[1]][2])) 


etext = [f'weight={w}' for w in edge_weights]

trace_weights = go.Scatter3d(x=xtp,y=ytp,z=ztp,mode='markers',marker =dict(color='rgb(125,125,125)',size=1),#set the same color as for the edge lines
    text = etext,hoverinfo='text')

#create a trace for the edges
trace_edges = go.Scatter3d(
    x=x_edges,y=y_edges,z=z_edges,mode='lines',line=dict(color='black',width=2),hoverinfo='none')

#create a trace for the nodes
trace_nodes = go.Scatter3d(
    x=x_nodes,y=y_nodes,z=z_nodes,marker=dict(symbol='circle',size=10,color='skyblue')
    )

#Include the traces we want to plot and create a figure
data = [trace_edges,trace_nodes,trace_weights]
fig = go.Figure(data=data)

fig.show()