如何从 2 个或更多矩阵的所有可能组合创建矩阵?
How to create a matrix from all possible combinations of 2 or more matrices?
假设有两个矩阵:
A <- B <- diag(3)
> A
[,1] [,2] [,3]
[1,] 1 0 0
[2,] 0 1 0
[3,] 0 0 1
我想创建一个新的矩阵AB,它由A行和B行的所有可能组合组成。预期结果:
> AB
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1 0 0 1 0 0
[2,] 1 0 0 0 1 0
[3,] 1 0 0 0 0 1
[4,] 0 1 0 1 0 0
[5,] 0 1 0 0 1 0
[6,] 0 1 0 0 0 1
[7,] 0 0 1 1 0 0
[8,] 0 0 1 0 1 0
[9,] 0 0 1 0 0 1
如何有效地做到这一点?是否可以扩展为两个以上的矩阵?
您可以使用 expand.grid()
并使用其输出来索引矩阵 A 和 B,
x <- expand.grid(1:3,1:3)
cbind(A[x[,1],], B[x[,2],])
给予,
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1 0 0 1 0 0
[2,] 0 1 0 0 1 0
[3,] 0 0 1 0 0 1
[4,] 1 0 0 1 0 0
[5,] 0 1 0 0 1 0
[6,] 0 0 1 0 0 1
[7,] 1 0 0 1 0 0
[8,] 0 1 0 0 1 0
[9,] 0 0 1 0 0 1
编辑:
对于两个以上的矩阵,可以使用如下函数,
myfun <- function(...) {
arguments <- list(...)
a <- expand.grid(lapply(arguments, function(x) 1:nrow(x)))
do.call(cbind,lapply(seq(a),function(x) { arguments[[x]][a[,x],] }))
}
out <- myfun(A,B,C)
head(out)
给予,
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 0 0 1 0 0 1 0 0 0
[2,] 0 1 0 1 0 0 1 0 0 0
[3,] 0 0 1 1 0 0 1 0 0 0
[4,] 1 0 0 0 1 0 1 0 0 0
[5,] 0 1 0 0 1 0 1 0 0 0
[6,] 0 0 1 0 1 0 1 0 0 0
数据:
A <- B <- diag(3)
C <- diag(4)
假设有两个矩阵:
A <- B <- diag(3)
> A
[,1] [,2] [,3]
[1,] 1 0 0
[2,] 0 1 0
[3,] 0 0 1
我想创建一个新的矩阵AB,它由A行和B行的所有可能组合组成。预期结果:
> AB
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1 0 0 1 0 0
[2,] 1 0 0 0 1 0
[3,] 1 0 0 0 0 1
[4,] 0 1 0 1 0 0
[5,] 0 1 0 0 1 0
[6,] 0 1 0 0 0 1
[7,] 0 0 1 1 0 0
[8,] 0 0 1 0 1 0
[9,] 0 0 1 0 0 1
如何有效地做到这一点?是否可以扩展为两个以上的矩阵?
您可以使用 expand.grid()
并使用其输出来索引矩阵 A 和 B,
x <- expand.grid(1:3,1:3)
cbind(A[x[,1],], B[x[,2],])
给予,
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1 0 0 1 0 0
[2,] 0 1 0 0 1 0
[3,] 0 0 1 0 0 1
[4,] 1 0 0 1 0 0
[5,] 0 1 0 0 1 0
[6,] 0 0 1 0 0 1
[7,] 1 0 0 1 0 0
[8,] 0 1 0 0 1 0
[9,] 0 0 1 0 0 1
编辑:
对于两个以上的矩阵,可以使用如下函数,
myfun <- function(...) {
arguments <- list(...)
a <- expand.grid(lapply(arguments, function(x) 1:nrow(x)))
do.call(cbind,lapply(seq(a),function(x) { arguments[[x]][a[,x],] }))
}
out <- myfun(A,B,C)
head(out)
给予,
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 0 0 1 0 0 1 0 0 0
[2,] 0 1 0 1 0 0 1 0 0 0
[3,] 0 0 1 1 0 0 1 0 0 0
[4,] 1 0 0 0 1 0 1 0 0 0
[5,] 0 1 0 0 1 0 1 0 0 0
[6,] 0 0 1 0 1 0 1 0 0 0
数据:
A <- B <- diag(3)
C <- diag(4)