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使用python3表示实体之间的关系

networkx graph matplotlib python-3.x python

giorgioW · 技术社区 · 7 年前

我想使用 networkx Python3的库,但我不知道如何解决这个问题。

基本上我有 relation 两人之间 entities 它位于一个名为 nations.csv . 看起来是这样的:

China, Economicaid, Egypt
China, Economicaid, Indonesia
USSR, Economicaid, Cuba 
USSR, Economicaid, India
USSR, Economicaid, Poland
UK, Economicaid, India 
UK, Economicaid, Jordan
USA, Economicaid, Brazil

理解第一行是与第二行之间的第三行(实体2)相关的实体之一:

我分析了csv文件,以便将每一行存储在字典中,如下所示:

d = {}
d['entity1'] = []
d['relation'] = []
d['entity2'] = []

dictReader = csv.DictReader(open('nations.csv', 'rt'), fieldnames = 
['entity1', 'relation', 'entity2'], delimiter = ',', quotechar = '"')

for row in dictReader:
    for key in row:
        d[key].append(row[key])

我所做的是使用函数绘制节点 add_node() 如以下示例所示:

import csv
import networkx as nx
import matplotlib.pyplot as plt


d = {}
d['entity1'] = []
d['relation'] = []
d['entity2'] = []

dictReader = csv.DictReader(open('nations.csv', 'rt'), fieldnames = ['entity1', 'relation', 'entity2'], delimiter = ',', quotechar = '"')

for row in dictReader:
    for key in row:
        d[key].append(row[key])

print()

for i in range (1, len(d['entity1'])):
    r.append(d['entity1'][i])

for k in range (1, len(d['entity2'])):
    o.append(d['entity2'][k])


G=nx.Graph()

for j in range(len(r)):
    G.add_node(r[j])
    G.add_node(o[j])

nx.draw_networkx(G, with_labels = True, node_size = 500)

plt.show()

但是,当我想表示节点之间的边时,问题就来了,因为它不仅是边本身,它还有自己的含义标签。

1 回复 | 直到 7 年前

Paul Brodersen 7 年前

基本上,国旗 with_labels 真的应该打电话 with_node_labels 因为它仅触发节点标签的打印。因此,需要手动添加边标签( networkx.draw_networkx_edge_labels )绘制完图形(networkx.draw`)后,需要1)在同一个轴上打印,2)对两个打印使用相同的图形布局。

import numpy as np
import matplotlib.pyplot as plt
import networkx as nx
import csv

# load data
dictReader = csv.DictReader(open('nations.csv', 'rt'), fieldnames = ['entity1', 'relation', 'entity2'], delimiter = ',', quotechar = '"')

# create a more amenable data structure
edge_to_label = {(d['entity1'], d['entity2']) : d['relation'] for d in dictReader}

# create graph
G = nx.from_edgelist(edge_to_label.keys())

# precompute layout (default layout used here)
layout = nx.layout.fruchterman_reingold_layout(G)

# create figure so we plot the graph and labels on the same plot
fig, ax = plt.subplots(1,1)

# draw graph
nx.draw(G, pos=layout, ax=ax, with_labels=True)

# draw labels using the same, pre-computed graph layout
nx.draw_networkx_edge_labels(G, pos=layout, edge_labels=edge_to_label, ax=ax)

plt.show()