如何在可视化分配期间防止 networkx_edge_labels 乱序

Question

我有密码。当我绘制图表时，标签在乱序并且显示不正确。我已经查阅了参考指南(https://networkx.org/documentation) and related post (i.e. )，但我无能为力。

我使用的数据是]。

当我打印

的值时

dict(zip(G.edges, df['value'].tolist()))

它给了我错误的标签分配。例如，在第 2 行中，('aquatic communities', 'biocoenosis') 应该是“Borader”。

如下图；

{('plankton', 'aquatic communities'): 'broader',
 ('plankton', 'zooplankton'): 'broader',
 ('plankton', 'phytoplankton'): 'narrower',
 ('plankton', 'cryoplankton'): 'narrower',
 ('plankton', 'nannoplankton'): 'narrower',
 ('plankton', 'picoplankton'): 'narrower',
 ('plankton', 'plankton surveys'): 'narrower',
 ('aquatic communities', 'biocoenosis'): 'related'}

绘图代码；

import pandas as pd
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
 
# Build a dataframe with your connections
# df = results_df_4a[results_df_4a["value"] == 'broader']
  df = results_df_4a
# And I need to transform my categorical column in a numerical value typeA->1, typeB->2...
df['value']=pd.Categorical(df['value'])
df['value'].cat.codes
 
# Build your graph
G = nx.from_pandas_edgelist(df, 'from', 'to', create_using=nx.DiGraph(directed=True) )
 
pos = nx.spring_layout(G, k=3)

from matplotlib.pyplot import figure

figure(figsize=(8, 6), dpi=120)

# Custom the nodes:
nx.draw_networkx(G, pos = pos, font_size = 10, with_labels=True, arrows=True, node_color= 'skyblue', node_size= 700, width= 3.5, arrowstyle= '-|>', arrowsize= 12, edge_color=df['value'].cat.codes)
nx.draw_networkx_edge_labels(G,pos = pos, edge_labels=dict(zip(G.edges, df['value'].tolist())))
plt.show()

Answer 1

如何使用您要使用的 edge_label 信息直接创建图表：

# Build your graph
G = nx.from_pandas_edgelist(
      df, 'from', 'to', create_using=nx.DiGraph(directed=True),
     edge_attr='value'    
)

基于此，您可以轻松地按照“常规程序”从边缘属性添加边缘标签，请参阅。

编辑 1

一个完整的最小工作示例：

import networkx as nx
import matplotlib.pylab as plt

g = nx.DiGraph()

g.add_weighted_edges_from([(0, 1, 1), (0, 2, 3)])

pos = nx.spring_layout(g)

nx.draw(g, pos, with_labels=True)

# in above case you need to use 'value' instead of 'weight' here
edge_labels = dict([((n1, n2), d['weight'])
                    for n1, n2, d in g.edges(data=True)])

nx.draw_networkx_edge_labels(g, pos, edge_labels=edge_labels,)

plt.show()

如何在可视化分配期间防止 networkx_edge_labels 乱序

How to prevent the networkx_edge_labels shuffling during assignment for a visualization

python

dictionary

graph

list

networkx

编辑 1