如何在R中使用igraph计算加权度分布? [英] How do I calculate weighted degree distributions with igraph in R?

问题描述

考虑一个数据帧df，其中前两列是节点对，连续列V1，V2，...，Vn表示节点之间的流(可能为0，这意味着该列的边缘没有边缘网络).我想使用流作为权重对学位，社区发现和其他网络度量进行分析.

Consider a dataframe df where the first two columns are node pairs and successive columns V1, V2, ..., Vn represent flows between the nodes (potentially 0, implying no edge for that column's network). I would like to conduct analysis on degree, community detection, and other network measures using the flows as weights.

然后根据我在V1中的权重来分析图形:

Then to analyze the graph with respect to the weights in V1 I do:

# create graph and explore unweighted degrees with respect to V1
g <- graph.data.frame( df[df$V1!=0,] )
qplot(degree(g))
x <- 0:max(degree(g))
qplot(x,degree.distribution(g))

# set weights and explore weighted degrees using V1
E(g)$weights <- E(g)$V1
qplot(degree(g))

第三个qplot的输出与第一个qplot的输出相同.我在做什么错了?

The output from the third qplot is no different than the first. What am I doing wrong?

更新:

所以 graph.strength 是我想要的，但是在我的情况下，graph.strength(g)提供标准学位输出，其后是:

So graph.strength is what I am looking for, but graph.strength(g) in my case gives standard degree output followed by:

Warning message:
In graph.strength(g) :
At structural_properties.c:4928 :No edge weights for strength calculation,
normal degree

我必须设置错误的权重，这样做E(g)$weights <- E(g)$V1是否还不够?为什么g$weights与E(g)$weights有区别?

I must be setting the weights incorrectly, is it not sufficient to do E(g)$weights <- E(g)$V1 and why can g$weights differ from E(g)$weights?

推荐答案

可以使用weights参数为函数graph.strength提供权重向量.我认为您的代码出了什么问题，您应该调用weights属性E(g)$weight而不是E(g)$weights.

The function graph.strength can be given a weights vector with the weights argument. I think what is going wrong in your code is that you should call the weights attribute E(g)$weight not E(g)$weights.

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