How do I make an array of matrices in R, like the data from dataset

I want to make my own array of (N x N) matrices that matches the keras-compatible format that is loaded with dataset_mnist(). As

mnist <- dataset_mnist()
x_train <- mnist$train$x
str (x_train)

yields

int [1:60000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...

I want to make my own data in this format. Let's say I have 2000 different 100x100 matrices of integers: mat1, mat2, mat3, mat4... mat2000. How can I combine them to produce an object with the structure:

int [1:2000, 1:100, 1:100] ...

that I can then use as input data for keras models?

I've tried:

as.vector (c(mat1, mat2))
as.array (c(mat1, mat2))
rbind (mat1, mat2)

But it does not produce the correctly structured data. Thank you for your help!

CodePudding user response：

concatenate your matrices and make array. Also concatenate matrix dimension and third dimension, which is the number of matrices. Example:

m1 <- matrix(1, 2, 3)
m2 <- matrix(2, 2, 3)
m3 <- matrix(3, 2, 3)

array(c(m1, m2, m3), c(dim(m1), 3))
# , , 1
# 
#      [,1] [,2] [,3]
# [1,]    1    1    1
# [2,]    1    1    1
# 
# , , 2
# 
#      [,1] [,2] [,3]
# [1,]    2    2    2
# [2,]    2    2    2
# 
# , , 3
# 
#      [,1] [,2] [,3]
# [1,]    3    3    3
# [2,]    3    3    3

CodePudding user response：

You can also take a look the package listarrays.

m <- matrix(1:4, ncol = 2)
listarrays::bind_as_rows(m, m, m) |> str()
# int [1:3, 1:2, 1:2] 1 1 1 2 2 2 3 3 3 4 ...