### =============================================================================
### rowMeans2
###
### ----------------------------------------------------------------------------
### Non-exported methods
###
.DelayedMatrix_block_rowMeans2 <- function(x, rows = NULL, cols = NULL,
na.rm = FALSE, ..., useNames = TRUE) {
# Check input
stopifnot(is(x, "DelayedMatrix"))
DelayedArray:::.get_ans_type(x, must.be.numeric = TRUE)
# Subset
x <- ..subset(x, rows, cols)
# Compute result
val <- rowblock_APPLY(x = x,
FUN = rowMeans2,
na.rm = na.rm,
...,
useNames = useNames)
if (length(val) == 0L) {
return(numeric(nrow(x)))
}
unlist(val, recursive = FALSE, use.names = useNames)
}
### ----------------------------------------------------------------------------
### Exported methods
###
# ------------------------------------------------------------------------------
# General method
#
#' @inherit MatrixGenerics::rowMeans2
#' @importMethodsFrom DelayedArray seed
#' @rdname colMeans2
#' @export
#' @examples
#'
#' # NOTE: Temporarily use verbose output to demonstrate which method is
#' # which method is being used
#' options(DelayedMatrixStats.verbose = TRUE)
#' # By default, this uses a seed-aware method for a DelayedMatrix with a
#' # 'SolidRleArraySeed' seed
#' rowMeans2(dm_Rle)
#' # Alternatively, can use the block-processing strategy
#' rowMeans2(dm_Rle, force_block_processing = TRUE)
#' options(DelayedMatrixStats.verbose = FALSE)
setMethod("rowMeans2", "DelayedMatrix",
function(x, rows = NULL, cols = NULL, na.rm = FALSE,
force_block_processing = FALSE, ..., useNames = TRUE) {
.smart_seed_dispatcher(x, generic = MatrixGenerics::rowMeans2,
blockfun = .DelayedMatrix_block_rowMeans2,
force_block_processing = force_block_processing,
rows = rows,
cols = cols,
na.rm = na.rm,
...,
useNames = useNames)
}
)
# ------------------------------------------------------------------------------
# Seed-aware methods
#
#' @importMethodsFrom Matrix rowMeans
#' @rdname colMeans2
#' @export
setMethod("rowMeans2", "Matrix",
function(x, rows = NULL, cols = NULL, na.rm = FALSE,
..., useNames = TRUE) {
message2(class(x), get_verbose())
x <- ..subset(x, rows, cols)
val <- rowMeans(x = x, na.rm = na.rm)
if (!useNames) {
val <- unname(val)
}
val
}
)
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