#' @include bicluster.R
NULL
#' Extract a list of bicluster objects from an akmbiclust biclustering object.
#'
#' @param bics A result object from akmbiclust.
#' @param transposed \code{True}, if the bicluster calculation was
#' performed on a tranposed matrix.
#' @param mat Original matrix, that was used for biclustering.
#' @param filterfun A function to filter biclusters.
#' Only if the function returns \code{True}, the bicluster is added to the
#' returned list. The function has to accept a the
#' bicluster (given as submatrix
#' of \code{mat}) \code{filterfun(bicluster_matrix, ...)}.
#' @param ... Other parameters forwarded to the \code{filterfun}.
#' @return A list of \code{\link{bicluster}} objects, which have to be
#' valid (See \code{\link{validate_bicluster}}.
#'
#' @examples
#' # Function called in
#' m <- matrix(seq(1:16), nrow=4)
#' # m <- matrix(rnorm(10000), nrow=100)
#' # Not run: run_akmbiclust(m, k=10)
#'
#' @export
getAkmbiclustClusters <- function(bics, mat,
transposed = FALSE,
filterfun = NULL, ...) {
numClus <- max(bics$row_labels)
tmp <- bicluster()
res <- list()
for (i in seq(1, numClus)) {
if (transposed) {
tmp <- bicluster(
column = (seq(1, ncol(mat)))[bics$row_labels == i],
row = (seq(1, nrow(mat)))[bics$col_labels == i],
algorithm = "akmbiclust"
)
} else {
tmp <- bicluster(
row = (seq(1, nrow(mat)))[bics$row_labels == i],
column = (seq(1, ncol(mat)))[bics$col_labels == i],
algorithm = "akmbiclust"
)
}
tmp <- set_bicluster_names(tmp, mat)
# Check if cluster fits the constraints
if (validate_bicluster(tmp)) {
if (is.null(filterfun)) {
res[[length(res) + 1]] <- tmp
} else {
if (filterfun(bicluster_to_matrix(mat, tmp), ...)) {
res[[length(res) + 1]] <- tmp
}
}
}
}
return(res)
}
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