I have a numerical matrix of size 17 (rows) x 6 (columns). It looks looks like this:
Now I want to transform this matrix to an array of size 2 (rows) x 3 (columns) x (17 dimensions) in a way that every row is transformed to one dimension in the new array, in a way that columns 1-3 go to the first row and columns 4-6 go to the second row.
I have used the numbers out of the example to give an example how dimension 1 looks in this new array (it includes the values of the first row):
How can I transform this matrix to the array I would like to have?
m <- matrix(c(1:12), ncol = 6)
# [,1] [,2] [,3] [,4] [,5] [,6]
#[1,] 1 3 5 7 9 11
#[2,] 2 4 6 8 10 12
a <- array(t(m), dim = c(3, 2, length(m)/6))
a <- aperm(a, c(2, 1, 3)) #switch first and second dimension
#, , 1
#
# [,1] [,2] [,3]
#[1,] 1 3 5
#[2,] 7 9 11
#
#, , 2
#
# [,1] [,2] [,3]
#[1,] 2 4 6
#[2,] 8 10 12
M = matrix(data = 1:9, nrow = 3, ncol = 3)
print (M)
## [,1] [,2] [,3]
## [1,] 1 4 7
## [2,] 1 4 8
## [3,] 3 6 9
I wanna check that elements in row [1,] are equal to elements at row[2,]. Or which elements at row[1,] are equal to elements at column[,3], for example.
I have
mat1 = matrix(c(2, 4, 3, 6, 7, 8), nrow=2, ncol=3)
mat2 = matrix(c(5, 6, 7, 1, 2, 3), nrow=2, ncol=3)
mat3 = matrix(c(8, 5, 8, 6, 7, 9), nrow=2, ncol=3)
which gives me 3 matrices:
[,1] [,2] [,3]
[1,] 2 3 7
[2,] 4 6 8
[,1] [,2] [,3]
[1,] 5 7 2
[2,] 6 1 3
[,1] [,2] [,3]
[1,] 8 8 7
[2,] 5 6 9
What I would like to do is compare the three matrices per row per first column, and select the row of the matrix that has the highest value on the first column.
For example: in row 1 column 1, matrix3 has the highest value (8) compared to matrix1 (2) and matrix2 (5). In row 2 column 1, matrix2 has the highest value (6). I would like to create a new matrix that copies the row of the matrix that has that highest value, resulting in:
[,1] [,2] [,3]
[1,] 8 8 7 <- From mat3
[2,] 6 1 3 <- From mat2
I know how to get a vector with the highest values from column 1, but I cannot get the whole row of the matrix copied into a new matrix. I have:
mat <- (mat1[1,])
which just copies the first row of the first matrix
[1] 2 3 7
I can select which number is the maximum number:
max(mat1[,1],mat2[,1],mat3[,1])
[1] 8
But I cannot seem to combine the two to return a matrix with the whole row.
Getting the code to loop for each row will be no problem, but I cannot seem to get it to work for the first row and as such, I am missing the essential code. Any help would be greatly appreciated. Thank you.
Are you working interactively? Do you manipulate multiple matrices spread in your workspace? A straightforward answer to your problem could be:
#which matrices have the largest element of column 1 in each row?
max.col(cbind(mat1[, 1], mat2[, 1], mat3[, 1]))
#[1] 3 2
rbind(mat3[1, ], mat2[2, ]) #use the above information to get your matrix
# [,1] [,2] [,3]
#[1,] 8 8 7
#[2,] 6 1 3
On a more ganeral use-case, a way could be:
mat_ls = list(mat1, mat2, mat3) #put your matrices in a "list"
which_col = 1 #compare column 1
which_mats = max.col(do.call(cbind, lapply(mat_ls, function(x) x[, which_col])))
do.call(rbind, lapply(seq_along(which_mats),
function(i) mat_ls[[which_mats[i]]][i, ]))
# [,1] [,2] [,3]
#[1,] 8 8 7
#[2,] 6 1 3
Probably not the prettiest solution
temp <- rbind(mat1, mat2, mat3)
rbind(temp[c(T,F),][which.max(temp[c(T,F),][, 1]),],
temp[c(F,T),][which.max(temp[c(F,T),][, 1]),])
## [,1] [,2] [,3]
## [1,] 8 8 7
## [2,] 6 1 3
You may also try:
a2 <- aperm(simplify2array( mget(ls(pattern="mat"))),c(3,2,1)) #gets all matrices with name `mat`
t(sapply(1:(dim(a2)[3]), function(i) {x1 <- a2[,,i]; x1[which.max(x1[,1]),]}))
# [,1] [,2] [,3]
#[1,] 8 8 7
#[2,] 6 1 3
I have two matrices A and B. Matrix B is a two-column matrix, each row containing one index of an element in matrix A. I want to change those elements in matrix A, which are indexed by each row in matrix B, to 0.
Is there a way to avoid using the loop shown below?
> A <- matrix(1:12, 3, 4)
> B <- matrix(c(1, 2, 2, 2, 3, 4), byrow = TRUE, ncol = 2)
> A
[,1] [,2] [,3] [,4]
[1,] 1 4 7 10
[2,] 2 5 8 11
[3,] 3 6 9 12
> B
[,1] [,2]
[1,] 1 2
[2,] 2 2
[3,] 3 4
> for (i in 1:nrow(B)) {
+ A[B[i, 1], B[i, 2]] <- 0
+ }
> A
[,1] [,2] [,3] [,4]
[1,] 1 0 7 10
[2,] 2 0 8 11
[3,] 3 6 9 0
It's done like this
A[B] <- 0;
If I have a matrix mat1
[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6
it is possible via a very simple command to square all individual values by
mat1 * mat1
[,1] [,2] [,3]
[1,] 1 9 25
[2,] 4 16 36
Now, what I want to do is to create a new matrix where all values are computed by e^(old_value), e.g., e^1, e^2, e^3 and so forth. How can I do this?
exp computes the exponential function
> mat1 <- matrix(1:6, nrow=2)
> exp(mat1)
[,1] [,2] [,3]
[1,] 2.718282 20.08554 148.4132
[2,] 7.389056 54.59815 403.4288