如何在R igraph中将边缘权重分配给某些边缘 [英] How to assign edge weights to certain edges in R igraph

问题描述

我想为最短路径中使用的某些边缘分配较小的非负边缘权重.这是一个示例图:

I'd like to assign a small, non-negative edge weights to certain edges used in a shortest path. Here is an example graph:

library(igraph)
data <- read.table(text="
1 2
1 4
1 5
2 3
2 4
3 4
5 7
5 8
3 6", header=FALSE)
gmatrix <- data.matrix(data, rownames.force = NA) #convert into a matrix to use in igraph
g <- graph_from_edgelist(gmatrix, directed = FALSE) 

如果我发现节点1和节点3之间的最短路径，则使用的边是1-2和1-3.

If I find the shortest path between node 1 and node 3, the edges used are 1-2 and 1-3.

get.shortest.paths(g, 1,3)
$vpath
$vpath[[1]]
+ 3/9 vertices, from 634c426:
[1] 1 2 3

我要做的是为这些边缘分配一个小的epsilon值.然后，我想调用 get.shortest.paths(g，1,3)来测试该函数是否会标识相同的路径.

What I want to do is to assign a small epsilon value to those edges. Then, I'd like to call get.shortest.paths(g, 1,3) to test whether the function will identify the same path or not.

推荐答案

好的，我可以帮助您:

使用 E()查询具有从 get.shortest.paths 中获取的ID的边缘，并将值分配给新的边缘属性名称(例如，"weight"")

Use E() to query the edges with the ids grabbed from get.shortest.paths and assign the values to a new edge attribute name (e.g., "weight" or whatever):

p <- get.shortest.paths(g, 1, 3)$vpath[[1]]

E(g, path = p)$weight <- 0.1

检查结果:

> E(g)
+ 9/9 edges from 605e8c7:
[1] 1--2 1--4 1--5 2--3 2--4 3--4 5--7 5--8 3--6
> E(g)$weight
[1] 0.1  NA  NA 0.1  NA  NA  NA  NA  NA

从1到2和2到3的路径现在具有加权边.

The path from 1 to 2 and 2 to 3 now has a weighted edge.

现在，将零分配给其他边，并且'get.shortest.paths`标识另一条路径:

Now, assign zero to the other edges and 'get.shortest.paths` identifies another path:

> E(g)$weight <- ifelse(is.na(E(g)$weight), 0, E(g)$weight)
> E(g)$weight
[1] 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0
> get.shortest.paths(g, 1, 3, weights = E(g)$weight)
$vpath
$vpath[[1]]
+ 3/8 vertices, from 605e8c7:
[1] 1 4 3


$epath
NULL

$predecessors
NULL

$inbound_edges
NULL

更加简洁:

g <- set_edge_attr(g, "weight", value = ifelse(E(g) %in% E(g, path = p), 0.1, 0))

E(g)$weight
[1] 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0

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