假设我有u, v, w维度矩阵3 x nwhere n > 3。所以u, v, w是这样的形式：
> u
u11 u12 ... u1n
u21 u22 ... u2n
u31 u22 ... u3n
> v
v11 v12 ... v1n
v21 v22 ... v2n
v31 v22 ... v3n
> w
w11 w12 ... w1n
w21 w22 ... w2n
w31 w22 ... w3n
是否可以创建一个在 R 中3 x 3绑定u, v和w列明智的矩阵列表？我的意思是我想获得表格列表：
[[1]]
u11 v11 w11
u21 v21 w21
u31 v31 w31
[[2]]
u12 v12 w12
u22 v22 w22
u32 v32 w32
.
.
.
[[n]]
u1n v1n w1n
u2n v2n w2n
u3n v3n w32n
我试过了
> do.call(cbind, list=(u,v,w))
但这不起作用。
数据示例
set.seed(1)
u = matrix(rnorm(15), nrow = 3)
v = matrix(rnorm(15), nrow = 3)
w = matrix(rnorm(15), nrow = 3)
> u
[,1] [,2] [,3] [,4] [,5]
[1,] -0.6264538 1.5952808 0.4874291 -0.3053884 -0.6212406
[2,] 0.1836433 0.3295078 0.7383247 1.5117812 -2.2146999
[3,] -0.8356286 -0.8204684 0.5757814 0.3898432 1.1249309
> v
[,1] [,2] [,3] [,4] [,5]
[1,] -0.04493361 0.8212212 0.78213630 0.61982575 -1.4707524
[2,] -0.01619026 0.5939013 0.07456498 -0.05612874 -0.4781501
[3,] 0.94383621 0.9189774 -1.98935170 -0.15579551 0.4179416
> w
[,1] [,2] [,3] [,4] [,5]
[1,] 1.3586796 -0.05380504 -0.3942900 0.7631757 0.6969634
[2,] -0.1027877 -1.37705956 -0.0593134 -0.1645236 0.5566632
[3,] 0.3876716 -0.41499456 1.1000254 -0.2533617 -0.6887557
期望输出：
[[1]]
-0.6264538 -0.04493361 1.3586796
0.1836433 -0.01619026 -0.1027877
-0.8356286 0.94383621 0.3876716
[[2]]
1.5952808 0.8212212 -0.05380504
0.3295078 0.5939013 -1.37705956
-0.8204684 0.9189774 -0.41499456
.
.
.
[[5]]
-0.6212406 -1.4707524 0.6969634
-2.2146999 -0.4781501 0.5566632
1.1249309 0.4179416 -0.6887557
您可以通过组合数据并使用array来设置维度来做到这一点：
ar <- array(rbind(u, v, w), dim = c(3, 3, ncol(u)))
如果你想要它，list那么asplit可以使用，其中数组在第 3 维中拆分
ars <- asplit(ar, 3)
ars[c(1,2,5)]
# [[1]]
# [,1] [,2] [,3]
# [1,] -0.6264538 -0.04493361 1.3586796
# [2,] 0.1836433 -0.01619026 -0.1027877
# [3,] -0.8356286 0.94383621 0.3876716
#
# [[2]]
# [,1] [,2] [,3]
# [1,] 1.5952808 0.8212212 -0.05380504
# [2,] 0.3295078 0.5939013 -1.37705956
# [3,] -0.8204684 0.9189774 -0.41499456
#
# [[3]]
# [,1] [,2] [,3]
# [1,] -0.6212406 -1.4707524 0.6969634
# [2,] -2.2146999 -0.4781501 0.5566632
# [3,] 1.1249309 0.4179416 -0.6887557
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