#' @title Prepare tensor generated from two matrices that share samples
 #'
 #' @param sample Character vector of sample names
 #' @param feature list of features from two matrices
 #' @param value array, contents of 
 #' @param featureRange Genomic Ranges to be associated with features
 #' @param sampleData List of conditional labeling associated with samples
 #'
 #' @return Tensor generated from two matrices that share samples
 #' @export
 #'
 #' @examples

 #' matrix1 <- matrix(runif(1000),200) #row features, column samples
 #' matrix2 <- matrix(runif(2000),400) #row features, column samples

 #' Z <- prepareTensorfromMatrix(t(matrix1),t(matrix2))

 #' Z <- prepareTensorRect(sample=as.character(seq_len(50)),

 #' feature=list(as.character(seq_len(200)),as.character(seq_len(400))),
 #' sampleData=list(rep(seq_len(2),each=25)),value=Z)

 prepareTensorRect <- function(

     sample, feature, value,
     featureRange = GRanges(NULL), sampleData = list(NULL)) {
   # Argument check
   stopifnot("`sample` must be a character." = is.character(sample))
   stopifnot("`feature` must be a list." = is.list(feature))
   stopifnot("`value` must be a array." = is.array(value))
   stopifnot("`featureRange` must be an GRanges." = is(featureRange, "GRanges"))
   stopifnot("`sampleData` must be a list." = is.list(sampleData))
   #

   new("TensorRect",

     sample = sample,
     feature = feature, value = value,
     featureRange = featureRange, sampleData = sampleData
   )
 }