chunk_apply {matter} | R Documentation

## Apply Functions Over Chunks of a List, Vector, or Matrix

### Description

Perform equivalents of `apply`, `lapply`, and `mapply`, but over parallelized chunks of the data. This is most useful if accessing the data is potentially time-consuming, such as for file-based `matter` objects. Operating on chunks reduces the number of I/O operations.

### Usage

    chunk_apply(X, FUN, MARGIN, ..., simplify = FALSE,
        chunks = NA, view = c("element", "chunk"),
        attr = list(), alist = list(), pattern = NULL,
        outfile = NULL, verbose = FALSE,
        BPREDO = list(), BPPARAM = bpparam())

    chunk_mapply(FUN, ..., MoreArgs = NULL, simplify = FALSE,
        chunks = NA, view = c("element", "chunk"),
        attr = list(), alist = list(), pattern = NULL,
        outfile = NULL, verbose = FALSE,
        BPREDO = list(), BPPARAM = bpparam())

### Arguments

`X` | A list, vector, or matrix for `chunk_apply()`. These may be any class that implements suitable methods for `[`, `[[`, `dim`, and `length()`. Only lists are supported for `chunk_mapply()`.
`FUN` | The function to be applied.
`MARGIN` | If the object is matrix-like, which dimension to iterate over. Must be 1 or 2, where 1 indicates rows and 2 indicates columns. The dimension names can also be used if `X` has `dimnames` set.
`MoreArgs` | A list of other arguments to `FUN`.
`...` | Additional arguments to be passed to `FUN`.
`simplify` | Should the result be simplified into a vector, matrix, or higher dimensional array?
`chunks` | The number of chunks to use. If `NA` (the default), this is inferred from `chunksize(X)` for `matter` objects, or from `getOption("matter.default.chunksize")` for non-`matter` classes. For IO-bound operations, using fewer chunks will often be faster, but use more memory.
`view` | What should be passed as the argment to `FUN`: "element" means the vector element, row, or column are passed (same as the behavior of `lapply` and `apply`), and "chunk" means to pass the entire chunk.
`attr` | A named list of attributes that will be attached to the argument passed to `FUN` as-is.
`alist` | A named list of vector-like attributes that will be attached to the argument passed to `FUN`, subsetted to the current elements. Typically, each attribute should be as long as `X`, unless `pattern` is specified, in which case each attribute should be as long as `pattern`.
`pattern` | A list of indices giving a pattern over which to apply `FUN` to `X`. Each element of `pattern` should give a vector of indices which can be used subscript `X`. For time and space efficiency, no attempt is made to verify these indices are valid.
`outfile` | If non-NULL, a file path where the results should be written as they are processed. If specified, `FUN` must return a 'raw', 'logical', 'integer', or 'numeric' vector. The result will be returned as a `matter` object.
`verbose` | Should user messages be printed with the current chunk being processed?
`BPREDO` | See documentation for `bplapply`.
`BPPARAM` | An optional instance of `BiocParallelParam`. See documentation for `bplapply`.

### Details

When `view = "element"`:

For vectors and lists, the vector is broken into some number of chunks according to `chunks`. The individual elements of the chunk are then passed to `FUN`.

For matrices, the matrix is chunked along rows or columns, based on the number of `chunks`. The individual rows or columns of the chunk are then passed to `FUN`.

In this way, the first argument of `FUN` is analogous to using the base `apply` and `lapply` functions.

However, when `view = "chunk"`:

In this situation, the entire chunk is passed to `FUN`, and `FUN` is responsible for knowing how to handle a sub-vector or sub-matrix of the original object. This may be useful if `FUN` is already a function that could be applied to the whole object such as `rowSums` or `colSums`.

When this is the case, it may be useful to provide a custom `simplify` function. Otherwise, the result will be returned as a list with length equal to the number of chunks, which must be post-processed to get into a desirable form.

For convenience to the programmer, several attributes are made available when `view = "chunk"`.

- "chunk_id":The index of the chunk currently being processed by `FUN`.

- "chunk_elt":The indices of the elements of the chunk, as rows/columns/elements in the original matrix/vector.

- "pattern_id" (optional):The indices of the patterns that compose the current chunk.

- "pattern_elt" (optional):The indices of the elements of the patterns, as rows/columns/elements in the original matrix/vector, that compose the current chunk.

The `pattern` argument can be used to iterate over dependent elements of a vector, or dependent rows/columns of a matrix. This can be useful if the calculation for a particular row/column/element depends on the values of others.

When `pattern` is provided, multiple rows/columns/elements will be passed to `FUN`, even when `view="element"`. Each element of the `pattern` list should be a vector giving the indices that should be passed to `FUN`.

This can be used to implement a rolling apply function.

### Value

Typically, a list if `simplify=FALSE`. Otherwise, the results may be coerced to a vector or array.

### Author(s)

Kylie A. Bemis

### See Also

`apply`, `lapply`, `mapply`,

### Examples

    register(SerialParam())

    set.seed(1)
    x <- matrix(rnorm(1000^2), nrow=1000, ncol=1000)

    out <- chunk_apply(x, mean, 1, chunks=20, verbose=TRUE)

[Package matter version 1.18.0 Index]