colMeans2: Calculates the mean for each row (column) of a matrix-like...

Description Usage Arguments Details Value Author(s) See Also Examples

Description

Calculates the mean for each row (column) of a matrix-like object.

Usage

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## S4 method for signature 'DelayedMatrix'
colMeans2(
  x,
  rows = NULL,
  cols = NULL,
  na.rm = FALSE,
  force_block_processing = FALSE,
  ...
)

## S4 method for signature 'Matrix'
colMeans2(x, rows = NULL, cols = NULL, na.rm = FALSE, ...)

## S4 method for signature 'SolidRleArraySeed'
colMeans2(x, rows = NULL, cols = NULL, na.rm = FALSE, ...)

## S4 method for signature 'DelayedMatrix'
rowMeans2(
  x,
  rows = NULL,
  cols = NULL,
  na.rm = FALSE,
  force_block_processing = FALSE,
  ...
)

## S4 method for signature 'Matrix'
rowMeans2(x, rows = NULL, cols = NULL, na.rm = FALSE, ...)

Arguments

x

A NxK DelayedMatrix.

rows

A vector indicating the subset of rows (and/or columns) to operate over. If NULL, no subsetting is done.

cols

A vector indicating the subset of rows (and/or columns) to operate over. If NULL, no subsetting is done.

na.rm

If TRUE, NAs are excluded first, otherwise not.

force_block_processing

FALSE (the default) means that a seed-aware, optimised method is used (if available). This can be overridden to use the general block-processing strategy by setting this to TRUE (typically not advised). The block-processing strategy loads one or more (depending on \link[DelayedArray]{getAutoBlockSize}()) columns (colFoo()) or rows (rowFoo()) into memory as an ordinary base::array.

...

Additional arguments passed to specific methods.

Details

The S4 methods for x of type matrix, array, or numeric call matrixStats::rowMeans2 / matrixStats::colMeans2.

Value

Returns a numeric vector of length N (K).

Author(s)

Peter Hickey

See Also

Examples

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# A DelayedMatrix with a 'matrix' seed
dm_matrix <- DelayedArray(matrix(c(rep(1L, 5),
                                   as.integer((0:4) ^ 2),
                                   seq(-5L, -1L, 1L)),
                                 ncol = 3))
# A DelayedMatrix with a 'SolidRleArraySeed' seed
dm_Rle <- RleArray(Rle(c(rep(1L, 5),
                         as.integer((0:4) ^ 2),
                         seq(-5L, -1L, 1L))),
                   dim = c(5, 3))

colMeans2(dm_matrix)

# 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)

DelayedMatrixStats documentation built on Feb. 5, 2021, 2:04 a.m.