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 2.0.0 Index]