如何对每行具有不同列位置的矩阵进行子集化? [英] How to subset a matrix with different column positions for each row?

问题描述

我想对每一行使用不同(但只有一个)列的矩阵进行子集化.那么适当地申请可以完成这项工作吗?但也许智能子集也可以工作，但我还没有找到解决方案.计算时间是一个问题 - 我有一个带有 for 循环的解决方案，但是在 RAM 中多次加载矩阵太慢了.下面是一个例子:

I want to subset a matrix using different (but one) column for every row. So propably apply could do the job? But propably also smart subsetting could work, but i havent found a solution. Computation time is an issue - I have a solution with a for loop, but loading the matrix in the RAM several times is just too slow. Here is an example:

矩阵M和向量v给定，

M<-matrix(1:15,nrow=5,ncol=3)

     [,1] [,2] [,3]
[1,]    1    6   11
[2,]    2    7   12
[3,]    3    8   13
[4,]    4    9   14
[5,]    5   10   15

v<-c(3,1,1,2,1)

解决方案是:

(11,2,3,9,5)

推荐答案

我们可以试试行/列索引

We can try the row/column indexing

M[cbind(1:nrow(M), v)]
#[1] 11  2  3  9  5

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