colRanks: Calculates the rank of the elements for each row (column) of...
In DelayedMatrixStats: Functions that Apply to Rows and Columns of 'DelayedMatrix' Objects

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

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

## S4 method for signature 'DelayedMatrix'
colRanks(
  x,
  rows = NULL,
  cols = NULL,
  ties.method = c("max", "average", "first", "last", "random", "max", "min", "dense"),
  preserveShape = FALSE,
  force_block_processing = FALSE,
  ...
)

## S4 method for signature 'DelayedMatrix'
rowRanks(
  x,
  rows = NULL,
  cols = NULL,
  ties.method = c("max", "average", "first", "last", "random", "max", "min", "dense"),
  force_block_processing = 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.
`ties.method`	A character string specifying how ties are treated. Note that the default specifies fewer options than the original matrixStats package.
`preserveShape`	If `TRUE` the output matrix has the same shape as the input x. Note, that this is not a generic argument and not all implementation of this function have to provide it.
`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::rowRanks / matrixStats::colRanks.

The matrixStats::rowRanks() function can handle a lot of different values for the ties.method argument. Users of the generic function should however only rely on max and average because the other ones are not guaranteed to be implemented:

max: for values with identical values the maximum rank is returned
average: for values with identical values the average of the ranks they cover is returned. Note, that in this case the return value is of type numeric.

a matrix of type integer is returned unless ties.method = "average". Ithas dimensions' NxJ (KxJ) matrix, where N (K) is the number of rows (columns) of the input x.

Peter Hickey

matrixStats::rowRanks() and matrixStats::colRanks() which are used when the input is a matrix or numeric vector.
base::rank

# 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))

colRanks(dm_Matrix)

rowRanks(dm_Matrix)

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] [,2] [,3] [,4] [,5]
[1,]    5    5    5    5    5
[2,]    1    2    3    4    5
[3,]    1    2    3    4    5
     [,1] [,2] [,3]
[1,]    3    2    1
[2,]    3    3    1
[3,]    2    3    1
[4,]    2    3    1
[5,]    2    3    1