我试图使用matrix()
和diag()
函数来创建以下模式,但有一个100×100矩阵,而不是5×5。
的5×5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,我想有两个对角线为1,一个主对角线的左边,一个在主对角线的权值。
该diag()
功能(实际上是diag<-
功能),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
你却希望子对角线上斜线被分配值,因此使用具有col
和row
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方形矩阵。我有一个模糊的存储器存在,其不需要使用row
和col
更快的方法。对于非常大的对象中的每个的那些功能返回相同的维度的矩阵作为其参数。)
对于主对角线的行和列的索引是相同的。对于其他对角线,存在的行索引和列索引之间1
的差。直接生成这些指标和这些指标赋值。
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
我们可以创建使用数学技巧这将所有方阵工作的功能。
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