英文:
Contract a dataframe of an edge list by summing the contracted edge weights from/to two nodes
问题
Here's the translated code part:
我有一个包含两对节点之间边权重数据的数据框 `df`：df <- data.frame(c("A","A","B","B","C","C"),c("B","C","A","C","A","B"),c(2,3,6,4,9,1))colnames(df) <- c("node_from", "node_to", "weight")print(df)# 输出:node_from node_to weight1 A B 22 A C 33 B A 64 B C 45 C A 96 C B 1
你想要合并节点 A 和 B 并将它们与其他节点的所有边权重相加，这里只有节点 C。结果应该是一个边列表，A 和 B 之间的边已消失，AB 现在是一个节点：
# 一些代码来合并节点 A 和 Bprint(df_contracted)# 输出:node_from node_to weight1 AB C 73 C AB 10
你是否有方法可以在更大的数据框上高效执行此操作？
我可以将数据框转换为实际的图，使用 igraph 包中的 graph_from_data_frame 和 contract 函数，但考虑到我必须多次执行此操作，我宁愿不必每次都进行转换和重新转换。
英文:
I have a dataframe df that contains data on edge weights between two pairs of nodes:
df <- data.frame(c("A","A","B","B","C","C"),c("B","C","A","C","A","B"),c(2,3,6,4,9,1))colnames(df) <- c("node_from", "node_to", "weight")print(df)# Output:node_from node_to weight1 A B 22 A C 33 B A 64 B C 45 C A 96 C B 1
I would like to contract this dataframe by merging nodes A and B and summing all edge weights to and from these nodes with any other node, in this case C only. The result should be an edge list where the edges between A and B have disappeared and AB is now one node:
# some code to merge nodes A and Bprint(df_contracted)# Output:node_from node_to weight1 AB C 73 C AB 10
Is there a way to do this efficiently for larger dataframes?
I could convert the dataframe to an actual graph using graph_from_data_frame from the igraph package and then the contract function, but given that I have to do this operation multiple times I'd rather not have to convert it then reconvert it back every time.
答案1
得分: 4
base R 方法
使用基本的 R 语法，我们可以像下面这样使用 aggregate + subset：
aggregate(weight ~ .,subset(transform(df,node_from = gsub("A|B", "AB", node_from),node_to = gsub("A|B", "AB", node_to)),node_from != node_to),sum)
这将得到如下结果：
node_from node_to weight1 C AB 102 AB C 7
igraph 方法
这是使用 igraph 中的 contract 函数的方法：
df %>%graph_from_data_frame() %>%contract(c(1, 1, 2), function(v) paste0(v, collapse = "")) %>%simplify() %>%get.data.frame()
这将得到如下结果：
from to weight1 AB C 72 C AB 10
英文:
base R approach
With base R we can use aggregate + subset like below
aggregate(weight ~ .,subset(transform(df,node_from = gsub("A|B", "AB", node_from),node_to = gsub("A|B", "AB", node_to)),node_from != node_to),sum)
which gives
node_from node_to weight1 C AB 102 AB C 7
igraph approach
Here is an option using contract from igraph
df %>%graph_from_data_frame() %>%contract(c(1, 1, 2), function(v) paste0(v, collapse = "")) %>%simplify() %>%get.data.frame()
which gives
from to weight1 AB C 72 C AB 10
答案2
得分: 2
以下是翻译好的代码部分：
library(dplyr)to.merge <- c('A', 'B')merged.name <- paste(to.merge, collapse='')df %>%mutate(across(c(node_from, node_to),~ if_else(.x %in% to.merge, merged.name, .x))) %>%group_by(node_from, node_to) %>%summarise(weight = sum(weight), .groups = "drop") %>%filter(node_from != node_to)# # A tibble: 2 × 3# node_from node_to weight# <chr> <chr> <dbl># 1 AB C 7# 2 C AB 10
希望这对您有帮助。
英文:
Here's a dplyr solution:
library(dplyr)to.merge <- c('A', 'B')merged.name <- paste(to.merge, collapse='')df %>%mutate(across(c(node_from, node_to),~ if_else(.x %in% to.merge, merged.name, .x))) %>%group_by(node_from, node_to) %>%summarise(weight = sum(weight), .groups = "drop") %>%filter(node_from != node_to)# # A tibble: 2 × 3# node_from node_to weight# <chr> <chr> <dbl># 1 AB C 7# 2 C AB 10
It changes all from and to node names that are "A" or "B" to "AB", groups rows with the same combination of from_node and to_node, sums weights within these groups, and finally removes the AB<->AB self-loop.
答案3
得分: 2
You may subset the AB and BA rows away, next summarize by a grepl on 'C', and rbind.
subset(df, rowSums(sapply(df[1:2], grepl, pat='A|B')) != 2) |
{
(.) by(., grepl('C', .$node_from), (x) {
data.frame(t(sapply(x[1:2], (z) paste(unique(z), collapse=''))), weight=sum(x$weight))
})}() |
unname() |
do.call(what='rbind')
node_from node_to weight
1 AB C 7
2 C AB 10
Data:
df <- structure(list(node_from = c("A", "A", "B", "B", "C", "C"), node_to = c("B",
"C", "A", "C", "A", "B"), weight = c(2, 3, 6, 4, 9, 1)), class = "data.frame", row names = c(NA,
-6L))
英文:
You may subset the AB and BA rows away, next summarize by a grepl on 'C', and rbind.
subset(df, rowSums(sapply(df[1:2], grepl, pat='A|B')) != 2) |>{\(.) by(., grepl('C', .$node_from), \(x) {data.frame(t(sapply(x[1:2], \(z) paste(unique(z), collapse=''))), weight=sum(x$weight))})}() |> unname() |> do.call(what='rbind')# node_from node_to weight# 1 AB C 7# 2 C AB 10
Data:
df <- structure(list(node_from = c("A", "A", "B", "B", "C", "C"), node_to = c("B","C", "A", "C", "A", "B"), weight = c(2, 3, 6, 4, 9, 1)), class = "data.frame", row.names = c(NA,-6L))
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