DelayedMatrix row/col summarization

Only a small number of row/col summarization methods are provided by the DelayedArray package.

See the DelayedMatrixStats package for an extensive set of row/col summarization methods.

Usage

## N.B.: Showing ONLY the col*() methods (usage of row*() methods is
## the same):

# S4 method for class 'DelayedMatrix'
colSums(x, na.rm=FALSE, dims=1)

# S4 method for class 'DelayedMatrix'
colMeans(x, na.rm=FALSE, dims=1)

# S4 method for class 'DelayedMatrix'
colMins(x, rows=NULL, cols=NULL, na.rm=FALSE, useNames=TRUE)

# S4 method for class 'DelayedMatrix'
colMaxs(x, rows=NULL, cols=NULL, na.rm=FALSE, useNames=TRUE)

# S4 method for class 'DelayedMatrix'
colRanges(x, rows=NULL, cols=NULL, na.rm=FALSE, useNames=TRUE)

# S4 method for class 'DelayedMatrix'
colVars(x, rows=NULL, cols=NULL, na.rm=FALSE, center=NULL, useNames=TRUE)

Arguments

x

A DelayedMatrix object.

na.rm, useNames, center

See man pages for the corresponding generics in the MatrixGenerics package (e.g. ?MatrixGenerics::rowVars) for a description of these arguments.

dims, rows, cols

These arguments are not supported. Don't use them.

Details

All these operations are block-processed.

See also

• The DelayedMatrixStats package for more row/col summarization methods for DelayedMatrix objects.

• The man pages for the various generic functions defined in the MatrixGenerics package e.g. MatrixGenerics::colVars etc...

• DelayedMatrix-rowsum for rowsum() and colsum() methods for DelayedMatrix objects.

• DelayedMatrix-mult for DelayedMatrix multiplication and cross-product.

• DelayedArray objects.

Examples

library(HDF5Array)
toy_h5 <- system.file("extdata", "toy.h5", package="HDF5Array")
h5ls(toy_h5)
#>   group name       otype dclass         dim
#> 0     /   M1 H5I_DATASET  FLOAT 10000 x 150
#> 1     /   M2 H5I_DATASET  FLOAT   150 x 200

M1 <- HDF5Array(toy_h5, "M1")
M2 <- HDF5Array(toy_h5, "M2")

M12 <- rbind(M1, t(M2))  # delayed

## All these operations are block-processed.

rsums <- rowSums(M12)
csums <- colSums(M12)

rmeans <- rowMeans(M12)
cmeans <- colMeans(M12)

rmins <- rowMins(M12)
cmins <- colMins(M12)

rmaxs <- rowMaxs(M12)
cmaxs <- colMaxs(M12)

rranges <- rowRanges(M12)
cranges <- colRanges(M12)

rvars <- rowVars(M12, center=rmeans)
cvars <- colVars(M12, center=cmeans)

## Sanity checks:
m12 <- rbind(as.matrix(M1), t(as.matrix(M2)))
stopifnot(
  identical(rsums, rowSums(m12)),
  identical(csums, colSums(m12)),
  identical(rmeans, rowMeans(m12)),
  identical(cmeans, colMeans(m12)),
  identical(rmins, rowMins(m12)),
  identical(cmins, colMins(m12)),
  identical(rmaxs, rowMaxs(m12)),
  identical(cmaxs, colMaxs(m12)),
  identical(rranges, cbind(rmins, rmaxs, deparse.level=0)),
  identical(cranges, cbind(cmins, cmaxs, deparse.level=0)),
  all.equal(rvars, rowVars(m12)),
  all.equal(cvars, colVars(m12))
)