colSums2: Calculates the sum for each row (column) of a matrix-like...
In DelayedMatrixStats: Functions that Apply to Rows and Columns of 'DelayedMatrix' Objects

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

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

## S4 method for signature 'DelayedMatrix'
colSums2(
  x,
  rows = NULL,
  cols = NULL,
  na.rm = FALSE,
  force_block_processing = FALSE,
  ...
)

## S4 method for signature 'Matrix'
colSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, ...)

## S4 method for signature 'SolidRleArraySeed'
colSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, ...)

## S4 method for signature 'DelayedMatrix'
rowSums2(
  x,
  rows = NULL,
  cols = NULL,
  na.rm = FALSE,
  force_block_processing = FALSE,
  ...
)

## S4 method for signature 'Matrix'
rowSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, ...)

`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`, `NA`s 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.

The S4 methods for x of type matrix, array, or numeric call matrixStats::rowSums2 / matrixStats::colSums2.

Returns a numeric vector of length N (K).

Peter Hickey

matrixStats::rowSums2() and matrixStats::colSums2() which are used when the input is a matrix or numeric vector.
For mean estimates, see rowMeans2() and rowMeans().
base::sum().

# 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 'Matrix' seed
dm_Matrix <- DelayedArray(Matrix::Matrix(c(rep(1L, 5),
                                           as.integer((0:4) ^ 2),
                                           seq(-5L, -1L, 1L)),
                                         ncol = 3))

colSums2(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
rowSums2(dm_Matrix)
# Alternatively, can use the block-processing strategy
rowSums2(dm_Matrix, force_block_processing = TRUE)
options(DelayedMatrixStats.verbose = FALSE)

Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: ‘MatrixGenerics’

The following objects are masked from ‘package:matrixStats’:

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: DelayedArray
Loading required package: stats4
Loading required package: Matrix
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from ‘package:stats’:

    IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

    anyDuplicated, append, as.data.frame, basename, cbind, colnames,
    dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: ‘S4Vectors’

The following object is masked from ‘package:Matrix’:

    expand

The following object is masked from ‘package:base’:

    expand.grid

Loading required package: IRanges

Attaching package: ‘DelayedArray’

The following objects are masked from ‘package:base’:

    aperm, apply, rowsum


Attaching package: ‘DelayedMatrixStats’

The following objects are masked from ‘package:matrixStats’:

    colAnyMissings, rowAnyMissings

[1]   5  30 -15
dgeMatrix
[1] -4 -2  2  8 16
[1] -4 -2  2  8 16