我正在尝试使用matrix()
和diag()
函数创建以下模式,但使用100 x 100矩阵而不是5 x 5。
5 x 5矩阵:
| 0 1 0 0 0 |
| 1 0 1 0 0 |
| 0 1 0 1 0 |
| 0 0 1 0 1 |
| 0 0 0 1 0 |
换句话说,我想有两个对角线,其值为1,一个在主对角线的左侧,一个在主对角线的右侧。
答案 0 :(得分:2)
对于主对角线,行索引和列索引相同。对于其他对角线,行索引和列索引之间存在1
之间的差异。直接生成这些索引并在这些索引中分配值。
sz = 5
m = matrix(0, sz, sz)
inds1 = cbind(r = 1:(sz-1), c = 2:sz)
inds2 = cbind(r = 2:sz, c = 1:(sz-1))
m[inds1] = 1
m[inds2] = 1
m
# OR, to make it concise
m = matrix(0, sz, sz)
inds = rbind(cbind(1:(sz-1), 2:sz), cbind(2:sz, 1:(sz-1)))
replace(m, inds, 1)
# [,1] [,2] [,3] [,4] [,5]
#[1,] 0 1 0 0 0
#[2,] 1 0 1 0 0
#[3,] 0 1 0 1 0
#[4,] 0 0 1 0 1
#[5,] 0 0 0 1 0
答案 1 :(得分:2)
diag()
函数(实际上是diag<-
函数)可用于分配:
mat <- matrix( 0, 100,100)
diag(mat) <- 1
mat[1:10,1:10]
#-----------
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 0 0 0 0 0 0 0 0 0
[2,] 0 1 0 0 0 0 0 0 0 0
[3,] 0 0 1 0 0 0 0 0 0 0
[4,] 0 0 0 1 0 0 0 0 0 0
[5,] 0 0 0 0 1 0 0 0 0 0
[6,] 0 0 0 0 0 1 0 0 0 0
[7,] 0 0 0 0 0 0 1 0 0 0
[8,] 0 0 0 0 0 0 0 1 0 0
[9,] 0 0 0 0 0 0 0 0 1 0
[10,] 0 0 0 0 0 0 0 0 0 1
但是,您希望为子对角线和超对角线分配值,因此请对col
和row
使用逻辑表达式:
mat <- matrix( 0, 100,100)
mat[row(mat)==col(mat)-1] <- 1
mat[row(mat)==col(mat)+1] <- 1
mat[1:10,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 1 0 0 0 0 0 0 0 0
[2,] 1 0 1 0 0 0 0 0 0 0
[3,] 0 1 0 1 0 0 0 0 0 0
[4,] 0 0 1 0 1 0 0 0 0 0
[5,] 0 0 0 1 0 1 0 0 0 0
[6,] 0 0 0 0 1 0 1 0 0 0
[7,] 0 0 0 0 0 1 0 1 0 0
[8,] 0 0 0 0 0 0 1 0 1 0
[9,] 0 0 0 0 0 0 0 1 0 1
[10,] 0 0 0 0 0 0 0 0 1 0
(此方法不依赖于具有正方形矩阵。我记忆模糊,有一种更快的方法不需要使用row
和col
。对于非常大的对象,每个对象函数返回的矩阵尺寸与其参数相同。)
答案 2 :(得分:1)
我们可以使用数学技巧创建一个适用于所有方阵的函数。
get_off_diagonal_1s <- function(n) {
#Create a matrix with all 0's
mat <- matrix(0, ncol = n, nrow = n)
#Subtract row indices by column indices
inds = row(mat) - col(mat)
#Replace values where inds is 1 or -1
mat[inds == 1 | inds == -1] = 1
mat
}
get_off_diagonal_1s(5)
# [,1] [,2] [,3] [,4] [,5]
#[1,] 0 1 0 0 0
#[2,] 1 0 1 0 0
#[3,] 0 1 0 1 0
#[4,] 0 0 1 0 1
#[5,] 0 0 0 1 0
get_off_diagonal_1s(8)
# [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
#[1,] 0 1 0 0 0 0 0 0
#[2,] 1 0 1 0 0 0 0 0
#[3,] 0 1 0 1 0 0 0 0
#[4,] 0 0 1 0 1 0 0 0
#[5,] 0 0 0 1 0 1 0 0
#[6,] 0 0 0 0 1 0 1 0
#[7,] 0 0 0 0 0 1 0 1
#[8,] 0 0 0 0 0 0 1 0