tensor_predictors/tensorPredictors/R/mcrossprod.R

#' Tensor Mode Crossproduct
#'
#'      C = A_(m) t(B_(m))
#'
#' For a matrices `A`, `B`, the first mode is `mcrossprod(A, B, 1)` equivalent
#' to `A %*% t(B)` (`tcrossprod`). On the other hand for mode two
#' `mcrossprod(A, 2)` the equivalence is `t(A) %*% B` (`crossprod`).
#'
#' @param A multi-dimensional array
#' @param B multi-dimensional array (allowed missing, defaults to `A`)
#' @param mode index (1-indexed)
#'
#' @returns matrix of dimensions \code{dim(A)[mode] by dim(B)[mode]}.
#'
#' @note equivalent to \code{tcrossprod(mat(A, mode), mat(B, mode))} with around
#'  the same performance but only allocates the result matrix.
#'
#' @examples
#' dimA <- c(2, 5, 7, 11)
#' A <- array(rnorm(prod(dimA)), dim = dimA)
#' stopifnot(exprs = {
#'     all.equal(mcrossprod(A, mode = 1),      tcrossprod(mat(A, 1)))
#'     all.equal(mcrossprod(A, , 2),           tcrossprod(mat(A, 2)))
#'     all.equal(mcrossprod(A, , mode = 3),    tcrossprod(mat(A, 3)))
#'     all.equal(mcrossprod(A, A, 4),          tcrossprod(mat(A, 4)))
#' })
#'
#' dimA <- c(2, 5, 7, 11)
#' dimB <- c(3, 5, 7, 11) # same as dimA except 1. entry
#' A <- array(rnorm(prod(dimA)), dim = dimA)
#' B <- array(rnorm(prod(dimB)), dim = dimB)
#' stopifnot(all.equal(
#'     mcrossprod(A, B, 1),
#'     tcrossprod(mat(A, 1), mat(B, 1))
#' ))
#'
#' dimA <- c(5, 2, 7, 11)
#' dimB <- c(5, 3, 7, 11) # same as dimA except 2. entry
#' A <- array(rnorm(prod(dimA)), dim = dimA)
#' B <- array(rnorm(prod(dimB)), dim = dimB)
#' stopifnot(all.equal(
#'     mcrossprod(A, B, mode = 2L),
#'     tcrossprod(mat(A, 2), mat(B, 2))
#' ))
#'
#' @export
mcrossprod <- function(A, B, mode) {
    storage.mode(A) <- "double"
    if (is.null(dim(A))) {
        dim(A) <- length(A)
    }
    if (missing(B)) {
        .Call("C_mcrossprod_sym", A, as.integer(mode))
    } else {
        storage.mode(B) <- "double"
        if (is.null(dim(B))) {
            dim(B) <- length(B)
        }
        .Call("C_mcrossprod", A, B, as.integer(mode))
    }
}