如何从字典在 networkx 中创建有向图？

Question

我有大约 1 万篇出版物有入站 or/and 出站引用。

数据采用以下格式（以两个条目为例）：

# each 'number' is a 'paper_id'
citations = {
    '157553241': { 
        'inbound_citations': [],
        'outbound_citations': [
            '141919793',
            '158546657',
            '156580052',
            '159778536',
            '157021328',
            '158546657',
            '157021328',
            '141919793',
            '153005744',
            '159778536',
            '112335878',
            '156580052'
        ]
    },
    '54196724': {
        'inbound_citations': ['204753337', '55910675'],
        'outbound_citations': ['153776751', '141060228', '33718066', '158233543']
    },
}

如何将此格式转换为我可以提供给 networkx 的内容？

我想找到最多 'central' 篇论文并发现一些派系（首先）。

我试过了

G = nx.DiGraph(citations)

但我不认为它是那样工作的...

Answer 1

您需要像这样构建边列表：

import networkx as nx
import matplotlib.pyplot as plt

edges = []
for node in citations:
    for parent in citations[node]['inbound_citations']:
        edges.append((parent, node))
    for child in citations[node]['outbound_citations']:
        edges.append((node, child))

G = nx.DiGraph()
G.add_edges_from(edges)

nx.draw(G, with_labels=True)
plt.show()

如何从字典在 networkx 中创建有向图？

How do I create a directed graph in networkx from a dictionary?

python

networkx