如何在networkx中从字典中创建有向图？

Question

我有大约10,000个出版物有入站或/和出站引用。

数据格式如下(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可以提供给networkx的格式

我想找到最“核心”的论文，并发现一些小团体(首先)。

我试过了

G = nx.DiGraph(citations)

但我不认为它是那样的.

Answer 1

您需要构建一个边列表，如下所示：

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()

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