R: Collapsing functions for batch processing

CFUN {ff} | R Documentation

## Collapsing functions for batch processing

### Description

These are used in aggregating the chunks resulting from batch processing. They are usually called via `do.call`

### Usage

    ccbind(...)
    crbind(...)
    cfun(..., FUN, FUNARGS = list())
    cquantile(..., probs = seq(0, 1, 0.25), na.rm = FALSE, names = TRUE, type = 7)
    csummary(..., na.rm = "ignored")
    cmedian(..., na.rm = FALSE)
    clength(..., na.rm = FALSE)
    csum(..., na.rm = FALSE)
    cmean(..., na.rm = FALSE)

### Arguments

`...` | `...`
`FUN` | a aggregating function
`FUNARGS` | further arguments to the aggregating function
`na.rm` | TRUE to remove NAs
`probs` | see `quantile`
`names` | see `quantile`
`type` | see `quantile`

### Details

CFUN | FUN | comment
`ccbind` | `cbind` | like `cbind` but respecting names
`crbind` | `rbind` | like `rbind` but respecting names
`cfun` |  | `crbind` the input chunks and then apply 'FUN' to each column
`cquantile` | `quantile` | `crbind` the input chunks and then apply 'quantile' to each column
`csummary` | `summary` | `crbind` the input chunks and then apply 'summary' to each column
`cmedian` | `median` | `crbind` the input chunks and then apply 'median' to each column
`clength` | `length` | `crbind` the input chunks and then determine the number of values in each column
`csum` | `sum` | `crbind` the input chunks and then determine the sum values in each column
`cmean` | `mean` | `crbind` the input chunks and then determine the (unweighted) mean in each column

In order to use CFUNs on the result of `lapply` or `ffapply` use `do.call`.

### Value

depends on the CFUN used

### ff options

xx TODO: extend this for weighted means, weighted median etc.,
see http://tolstoy.newcastle.edu.au/R/help/02a/1073.html and http://tolstoy.newcastle.edu.au/R/help/02a/1060.html or google "Re: [R] Weighted median"

### Note

Currently - for command line convenience - we map the elements of a single list argument to ..., but this may change in the future.

### Author(s)

Jens Oehlschlägel

### See Also

`ffapply`, `do.call`, `na.count`

### Examples

       X <- lapply(split(rnorm(1000), 1:10), summary)
       do.call("crbind", X)
       do.call("csummary", X)
       do.call("cmean", X)
       do.call("cfun", c(X, list(FUN=mean, FUNARGS=list(na.rm=TRUE))))
       rm(X)

[Package ff version 2.2-13 Index]