How to create an image cube - arrays

Question

I am new to R and would like to use it for my data analysis and visualization.
I have a dataframe with about 38575 rows (pixels) and 600 columns. Each column contains the intensity of an analyte, resulting in a spectrum per pixel.
I also have x and y coordinates for each pixel to create a data cube(array), in the sense that if I say image_cube[1,1,] gives me the first spectrum and if I say image_cube[,,1], I get an image of all pixels showing the intensity for the first analyte.
Not all pixels have a spectrum and they are not in the dataframe, these should just be empty pixels (black).
EDIT
I tried to use the following code with ROI data being the big dataframe and sample_overview the variable containing x and y coordinates for each pixel:
ROI_cube <- array(rep(0, 311*381*603), dim=c(311, 381, 603))
for (i in 1:dim(ROI_data)[1]) {
ROI_cube[sample_overview[i,2], sample_overview[i,1],] = ROI_data[i,]
}
But I get the following error:
Error in ROI_cube[sample_overview[i, 1], sample_overview[i, 2], ] <- ROI_data[i, :
incorrect number of subscripts

Answer 1

If i get your question correctly you want to map a 2D Dataframe of Spectra through known x-y Coordinates to a 3D-Array.
If thats all you want, you don't need any packages, it's just a matter of mapping the data in the dataframe to an Array
#Simulate some gaussian spectra
set.seed(1234)
simSpec <- function()
{
x <- 1:400
y <- stats::dnorm(x,mean=runif(1,min=0,max=400),sd=runif(1,min=2,max=50))
return(y)
}
#build a dataframe
data <- data.frame(matrix(data=NA,nrow=400,ncol=20))
for(i in 1:20) data[,i] <- simSpec()
#assume data is ordered in ascending x/y pixels
#=> data[,1] -> x=1, y=1 ; data[,2] -> x=2, y=1; data[,length(x)] -> x=length(x), y=y;
#data[,m+(n-1)*length(x)] -> x=m, y=n
Array <- array(data=t(data),dim=c(5,4,400)) #Build Array of format [X,Y,NSpectralVariables]
#transpose dataframe because default order is to first increase Columnnumber
plot(Array[1,1,],type="l") # Plot Spectrum at x=1, y=1
contour(Array[,,1]) #Contour Intensity at first Analyte