用矢量值乘以矩阵的元素

时间:2018-02-08 03:52:17

标签: r matrix elementwise-operations

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]})

2 个答案:

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