blockApply: blockApply() and family

In DelayedArray: A unified framework for working transparently with on-disk and in-memory array-like datasets

Description

A family of convenience functions to walk on the blocks of an array-like object and process them.

Usage

## Main looping functions:

blockApply(x, FUN, ..., grid=NULL, as.sparse=FALSE,
           BPPARAM=getAutoBPPARAM(), verbose=NA)

blockReduce(FUN, x, init, ..., BREAKIF=NULL, grid=NULL, as.sparse=FALSE,
            verbose=NA)

## Lower-level looping functions:
viewportApply(grid, FUN, ..., BPPARAM=getAutoBPPARAM(), verbose=NA)
viewportReduce(FUN, grid, init, ..., BREAKIF=NULL, verbose=NA)

## Retrieve grid context for the current block/viewport:
effectiveGrid(envir=parent.frame(2))
currentBlockId(envir=parent.frame(2))
currentViewport(envir=parent.frame(2))

## Get/set automatic parallel back-end:
getAutoBPPARAM()
setAutoBPPARAM(BPPARAM=NULL)

## For testing/debugging callback functions:
set_grid_context(effective_grid, current_block_id, envir=parent.frame(1))

Arguments

x	An array-like object, typically a DelayedArray object or derivative.
FUN	For blockApply and blockReduce, FUN is the callback function to apply to each block of x. It must be able to accept as input any of the blocks of x. IMPORTANT: If as.sparse is set to FALSE, all blocks will be passed to FUN as ordinary arrays. If it's set to TRUE, they will be passed as SparseArraySeed objects. If it's set to NA, then is_sparse(x) determines how they will be passed to FUN. For viewportApply() and viewportReduce(), FUN is the callback function to apply to each **viewport** in grid. It must be able to accept as input any of the viewports in grid. For blockReduce(), init <- FUN(block, init) will be performed on each block so FUN must take at least two arguments (typically block and init but the names can differ) and should normally return a value of the same type as its 2nd argument (init). The same applies for viewportReduce(), except that init <- FUN(viewport, init) will be performed on each **viewport**.
...	Optional arguments to FUN.
grid	An ArrayGrid object that defines the blocks (or viewports) to walk on. For blockApply() and blockReduce() the supplied grid must be compatible with the geometry of x. If not specified, an automatic grid is used. By default defaultAutoGrid(x) is called to generate an automatic grid. The automatic grid maker can be changed with setAutoGridMaker(). See ?setAutoGridMaker for more information.
as.sparse	Passed to the internal calls to read_block. See ?read_block for more information.
BPPARAM	A NULL, in which case blocks are processed sequentially, or a BiocParallelParam instance (from the BiocParallel package), in which case they are processed in parallel. The specific BiocParallelParam instance determines the parallel back-end to use. See ?BiocParallelParam in the BiocParallel package for more information about parallel back-ends.
verbose	Whether block processing progress should be displayed or not. If set to NA (the default), verbosity is controlled by DelayedArray:::get_verbose_block_processing(). Setting verbose to TRUE or FALSE overrides this.
init	The value to pass to the first call to FUN(block, init) (or FUN(viewport, init)) when blockReduce() (or viewportReduce()) starts the walk. Note that blockReduce() and viewportReduce() always operate sequentially.
BREAKIF	An optional callback function that detects a break condition. Must return TRUE or FALSE. At each iteration blockReduce() (and viewportReduce()) will call it on the result of init <- FUN(block, init) (on the result of init <- FUN(viewport, init) for viewportReduce()) and exit the walk if BREAKIF(init) returned TRUE.
envir	Do not use (unless you know what you are doing).
effective_grid, current_block_id	See Details below.

Details

effectiveGrid(), currentBlockId(), and currentViewport() return the "grid context" for the block/viewport being currently processed. By "grid context" we mean:

• The effective grid, that is, the user-supplied grid or defaultAutoGrid(x) if the user didn't supply any grid.

• The current block id (a.k.a. block rank).

• The current viewport, that is, the ArrayViewport object describing the position of the current block w.r.t. the effective grid.

Note that effectiveGrid(), currentBlockId(), and currentViewport() can only be called (with no arguments) from **within** the callback functions FUN and/or BREAKIF passed to blockApply() and family.

If you need to be able to test/debug your callback function as a standalone function, set an arbitrary effective grid and current block id by calling

    set_grid_context(effective_grid, current_block_id)

**right before** calling the callback function.

Value

For blockApply() and viewportApply(), a list with one list element per block/viewport visited.

For blockReduce() and viewportReduce(), the result of the last call to FUN.

For effectiveGrid(), the grid (ArrayGrid object) being effectively used.

For currentBlockId(), the id (a.k.a. rank) of the current block.

For currentViewport(), the viewport (ArrayViewport object) of the current block.

See Also

• defaultAutoGrid and family to generate automatic grids to use for block processing of array-like objects.

• ArrayGrid for the formal representation of grids and viewports.

• read_block and write_block.

• MulticoreParam, SnowParam, and bpparam, from the BiocParallel package.

• DelayedArray objects.

Examples

m <- matrix(1:60, nrow=10)
m_grid <- defaultAutoGrid(m, block.length=16, block.shape="hypercube")

## ---------------------------------------------------------------------
## blockApply()
## ---------------------------------------------------------------------
blockApply(m, identity, grid=m_grid)
blockApply(m, sum, grid=m_grid)

blockApply(m, function(block) {block + currentBlockId()*1e3}, grid=m_grid)
blockApply(m, function(block) currentViewport(), grid=m_grid)
blockApply(m, dim, grid=m_grid)

## The grid does not need to be regularly spaced:
a <- array(runif(8000), dim=c(25, 40, 8))
a_tickmarks <- list(c(7L, 15L, 25L), c(14L, 22L, 40L), c(2L, 8L))
a_grid <- ArbitraryArrayGrid(a_tickmarks)
a_grid
blockApply(a, function(block) sum(log(block + 0.5)), grid=a_grid)

## See block processing in action:
blockApply(m, function(block) sum(log(block + 0.5)), grid=m_grid,
           verbose=TRUE)

## Use parallel evaluation:
library(BiocParallel)
if (.Platform$OS.type != "windows") {
    BPPARAM <- MulticoreParam(workers=4)
} else {
    ## MulticoreParam() is not supported on Windows so we use
    ## SnowParam() on this platform.
    BPPARAM <- SnowParam(4)
}
blockApply(m, function(block) sum(log(block + 0.5)), grid=m_grid,
           BPPARAM=BPPARAM, verbose=TRUE)
## Note that blocks can be visited in any order!

## ---------------------------------------------------------------------
## blockReduce()
## ---------------------------------------------------------------------
FUN <- function(block, init) anyNA(block) || init
blockReduce(FUN, m, init=FALSE, grid=m_grid, verbose=TRUE)

m[10, 1] <- NA
blockReduce(FUN, m, init=FALSE, grid=m_grid, verbose=TRUE)

## With early bailout:
blockReduce(FUN, m, init=FALSE, BREAKIF=identity, grid=m_grid,
            verbose=TRUE)

## Note that this is how the anyNA() method for DelayedArray objects is
## implemented.

## ---------------------------------------------------------------------
## viewportReduce()
## ---------------------------------------------------------------------
## The man page for write_block() contains several examples of how to
## use viewportReduce() to write array blocks to a "realization sink".
## See '?write_block'

DelayedArray documentation built on March 25, 2021, 6:01 p.m.