March 2020
Intermediate to advanced
200 pages
3h 12m
Chinese
Content preview from 复杂性思考：复杂性科学和计算模型（原书第2 版）
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无标度网络
｜
53
>>> pmf_fb.Mean(), pmf_fb.Std()
(43.691, 52.414)
WS 模型也做了相同的工作：
>>> pmf_ws = Pmf(degrees(ws))
>>> pmf_ws.mean(), pmf_ws.std()
(44.000, 1.465)
可以使用 thinkplot 模块来绘制结果：
thinkplot.Pdf(pmf_fb, label='Facebook')
thinkplot.Pdf(pmf_ws, label='WS graph')
图 4-1 分别显示了 Facebook 网络数据集与 WS 图中节点的度的平均值和标
准差的分布。它们差别较大。
0.025
0.020
0.015
0.010
0.005
0.000
0.30
0.25
0.20
0.15
0.10
0.05
0.00
0 200 400 600 800 1000
38 40 42 44 45 48
DegreeDegree
Facebook
WS graph
PMF
图 4-1：在 Facebook 数据集和 WS 模型中的节点度的 PMF
在 WS 模型中，大多数用户大约有 44 位好友；最小值为 38，最大值为 50，
变化不大。在数据集中，有许多用户只有 1 位或 2 位好友，其中只有一位好
友的用户有 1000 多个！
这种分布称为
重尾分布
，其特征是有许多小的值和一些非常大的值。
4.4 重尾分布
在复杂性科学的很多领域中，重尾分布是一个常见特征，它们将是本书反复
54
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第
4
章
出现的一个主题。 ...
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