如何恢复工会后的属性？ [英] How to restore attribute after union n igraphs?

问题描述

假设我有 n igraphs对象 g1 ， g2 ，..， gn 。他们是无向和加权图，即新权重的属性应该被添加。我想将 n 图合并到加权图 g 中。
$ b 如果 n从文档中已知（参见？graph.union ） 图具有权重属性，通过添加 _1 和（和 _3 等）后缀，即 weight_1 ， weight_2 ，...， weight_n 。



我已经看过回答并为 n = 3 图表编写代码（见下文）。

编辑：

  library ）
 
 rm（list = ls（all = TRUE））＃删除所有对象
 
 g1 < -  graph_from_literal（A1-B1-C1）
 g2 （A2-B2-C2）
 g3 <-graph_from_literal（A3-B3-C3）
 
 E（g1）$ weight <-c（1,2） （5,6）
 
 
（b）
 E（g2）$重量c <  -  union（g1，g2，g3）
 
 new_attr < -  as.list（list.edge.attributes（g））
k < -  length（new_attr）＃number新属性
 
 value_new_attr<  -  lapply（list.edge.attributes（g），
 function（x）get.edge.attribute（g，x））
 
 df < -  data.frame（）
 for（i in 1：k）{df < -  rbind（df，value_new_attr [[i]]）} 
 E（g）$ weight <  -  colSums（df，na.rm = TRUE）
 
g < -  delete_edge_attr（g，weight_1）＃1 
g < -  delete_edge_attr（g，weight_2）＃ 2 
g<  -  delete_edge_attr（g，weight_3）＃3 
  

问题如何用 lapply（）函数重写最后一个树命令？

我的尝试不起作用：

  g < -  lapply（value_new_attr，function（x）{g < -  delete_edge_attr（g，x）}）
  

解决方案

我已经找到解决方案 for循环

 ＃删除带有后缀
的边缘属性（i in 1：k）{g < -  delete_edge_attr（g，new_attr [i]）} 
  

let's say I have n igraphs objects g1, g2,.., gn. They are undirected and weighted graphs, i.e. new weight's attribute should be added. I'd like to union n graphs into the weighted graph g.

It is known from the documentation (see ?graph.union) if the n graphs have the weight attribute, it is renamed by adding a _1 and _2 (and _3, etc.) suffix, i.e. weight_1, weight_2,..., weight_n.

I have seen the answer and wrote the code for n=3 graphs (see below).

Edited:

library(igraph)

rm(list=ls(all=TRUE)) # delete all objects

g1 <- graph_from_literal(A1-B1-C1)
g2 <- graph_from_literal(A2-B2-C2)
g3 <- graph_from_literal(A3-B3-C3)

E(g1)$weight <- c(1, 2)
E(g2)$weight <- c(3, 4)
E(g3)$weight <- c(5, 6)


g        <- union(g1, g2, g3)

new_attr <- as.list(list.edge.attributes(g))
k        <- length(new_attr) # number of new attributes

value_new_attr <- lapply(list.edge.attributes(g), 
                         function(x) get.edge.attribute(g,x))

df <- data.frame()
for (i in 1:k) {df <- rbind(df, value_new_attr[[i]])}
E(g)$weight <- colSums(df, na.rm=TRUE)

g <- delete_edge_attr(g, "weight_1") # 1
g <- delete_edge_attr(g, "weight_2") # 2
g <- delete_edge_attr(g, "weight_3") # 3

Question. How to rewrite the last tree commands with the lapply() function?

My attempt does not work:

g <- lapply(value_new_attr, function(x) {g <- delete_edge_attr(g, x)})

解决方案

I have found the solution with for-loop

# delete edge attributes with suffix
for (i in 1:k) {g <- delete_edge_attr(g, new_attr[i])}

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