我有一个矩阵M,我想创建3个额外的矩阵,其中每个附加矩阵都有一定数量的3x3 M个列切片乘以向量中的值,然后我将生成的3个新矩阵存储在{{1}中}。
list
我想做的伪代码
##create the initial matrix
M <- matrix(1:20, nrow = 4)
[,1] [,2] [,3] [,4] [,5]
[1,] 1 5 9 13 17
[2,] 2 6 10 14 18
[3,] 3 7 11 15 19
[4,] 4 8 12 16 20
## coordinates in the matrix I want to alter
iy <- c(1, 2, 3)
ix <- c(1, 4, 5)
coords <- as.data.frame(cbind(ix, iy))
## multiplier values
multis <- c(0.1, 2, 100)
结果应该是什么样的
mapply (function(multis, cords) {multis * M[coords$iy, coords$ix]})
答案 0 :(得分:4)
首先,您需要将coords
强制转换为矩阵以进行索引,然后反转列顺序。然后它只是一个简单的lapply()
循环。
coords <- as.matrix(coords)[, 2:1]
lapply(multis, function(x) {
M[coords] <- M[coords] * x
M
})
导致
[[1]]
[,1] [,2] [,3] [,4] [,5]
[1,] 0.1 5 9 13.0 17.0
[2,] 2.0 6 10 1.4 18.0
[3,] 3.0 7 11 15.0 1.9
[4,] 4.0 8 12 16.0 20.0
[[2]]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 5 9 13 17
[2,] 2 6 10 28 18
[3,] 3 7 11 15 38
[4,] 4 8 12 16 20
[[3]]
[,1] [,2] [,3] [,4] [,5]
[1,] 100 5 9 13 17
[2,] 2 6 10 1400 18
[3,] 3 7 11 15 1900
[4,] 4 8 12 16 20
答案 1 :(得分:2)
另一种解决方案是使用已定义的函数,并为每个sapply
使用multis
:
##create the initial matrix
M <- matrix(1:20, nrow = 4)
## coordinates in the matrix I want to alter
Y <- c(1, 2, 3)
X <- c(1, 4, 5)
coords <- as.data.frame(cbind(X, Y))
## multiplier values
multis <- c(0.1, 2, 100)
## Modifying the specific coordinates.
modif.one.matrix <- function(one_multis, coords, M) {
M_out <- M
for(one_coord in 1:nrow(coords)) {
M_out[coords$Y[one_coord], coords$X[one_coord]] <- M[coords$Y[one_coord], coords$X[one_coord]] * one_multis
}
return(M_out)
}
## Modifying one matrix
modif.one.matrix(multis[1], coords, M)
# [,1] [,2] [,3] [,4] [,5]
#[1,] 0.1 5 9 13.0 17.0
#[2,] 2.0 6 10 1.4 18.0
#[3,] 3.0 7 11 15.0 1.9
#[4,] 4.0 8 12 16.0 20.0
## Modifying all the matrices
sapply(multis, modif.one.matrix, coords, M, simplify = FALSE)
#[[1]]
# [,1] [,2] [,3] [,4] [,5]
#[1,] 0.1 5 9 13.0 17.0
#[2,] 2.0 6 10 1.4 18.0
#[3,] 3.0 7 11 15.0 1.9
#[4,] 4.0 8 12 16.0 20.0
#
#[[2]]
# [,1] [,2] [,3] [,4] [,5]
#[1,] 2 5 9 13 17
#[2,] 2 6 10 28 18
#[3,] 3 7 11 15 38
#[4,] 4 8 12 16 20
#
#[[3]]
# [,1] [,2] [,3] [,4] [,5]
#[1,] 100 5 9 13 17
#[2,] 2 6 10 1400 18
#[3,] 3 7 11 15 1900
#[4,] 4 8 12 16 20