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#' @title Compute Partial TAI or TDI Values
#' @description This function computes the partial \code{\link{TAI}} or \code{\link{TDI}}
#' values for each single gene in a PhyloExpressionSet or DivergenceExpressionSet object.
#'
#' In detail, each gene gets a \emph{TAI contribution profile} or \emph{TDI contribution profile}.
#'
#' \deqn{TAI_is = f_is * ps_i}
#'
#' or
#'
#' \deqn{TDI_is = f_is * ps_i}
#'
#' where TAI_is or TDI_is is the partial TAI or TDI value of gene i,
#' \eqn{f_is = e_is / \sum e_is} and \eqn{ps_i} is the phylostratum or divergence-stratum of gene i.
#' @param ExpressionSet a standard PhyloExpressionSet or DivergenceExpressionSet object.
#' @details The partial TAI or TDI matrix can be used to perform different cluster analyses
#' and also gives an overall impression of the contribution of each gene to the global \code{\link{TAI}} or \code{\link{TDI}} pattern.
#' @return a numeric matrix storing the partial TAI or TDI values for each gene in the
#' corresponding PhyloExpressionSet or DivergenceExpressionSet.
#' @references
#' Domazet-Loso T and Tautz D. 2010. "A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns". Nature (468): 815-818.
#' @author Hajk-Georg Drost
#' @examples
#'
#'
#' # read standard phylotranscriptomics data
#' data(PhyloExpressionSetExample)
#' data(DivergenceExpressionSetExample)
#'
#' # example PhyloExpressionSet
#' PTM_ps <- pMatrix(PhyloExpressionSetExample)
#'
#' # example DivergenceExpressionSet
#' PTM_ds <- pMatrix(DivergenceExpressionSetExample)
#'
#' # boxplot of the pMatrix
#' boxplot(pMatrix(PhyloExpressionSetExample),outline = FALSE)
#'
#' # boxplot of the pMatrix using log2 transformed expression levels
#' boxplot(pMatrix(tf(PhyloExpressionSetExample,log2)))
#'
#'
#' @export
pMatrix <- function(ExpressionSet)
{
is.ExpressionSet(ExpressionSet)
nCols <- dim(ExpressionSet)[2]
nRows <- dim(ExpressionSet)[1]
pTAIMatrix <- matrix(nrow = nRows,ncol = nCols - 2)
pTAIMatrix <- cpp_pMatrix(as.matrix(dplyr::select(ExpressionSet, 3:ncol(ExpressionSet))), as.vector(unlist(dplyr::select(ExpressionSet, 1))))
colnames(pTAIMatrix) <- names(ExpressionSet)[3:nCols]
rownames(pTAIMatrix) <- unlist(dplyr::select(ExpressionSet, 2))
return(pTAIMatrix)
}
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