Collapsing functions for batch processing
These are used in aggregating the chunks resulting from batch processing. They are usually called via do.call
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)
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 |
depends on the CFUN used
xx TODO: extend this for weighted means, weighted median etc.,
google "Re: [R] Weighted median"
Currently - for command line convenience - we map the elements of a single list argument to ..., but this may change in the future.
Jens Oehlschlägel
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)
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