bit64 (version 4.5.2)

sort.integer64: High-level intger64 methods for sorting and ordering

Description

Fast high-level methods for sorting and ordering. These are wrappers to ramsort.integer64 and friends and do not modify their arguments.

Usage

# S3 method for integer64
sort(x, decreasing = FALSE, has.na = TRUE, na.last = TRUE, stable = TRUE
, optimize = c("time", "memory"), VERBOSE = FALSE, ...)
# S3 method for integer64
order(..., na.last = TRUE, decreasing = FALSE, has.na = TRUE, stable = TRUE
, optimize = c("time", "memory"), VERBOSE = FALSE)

Value

sort returns the sorted vector and vector returns the order positions.

Arguments

x

a vector to be sorted by ramsort.integer64 and ramsortorder.integer64, i.e. the output of sort.integer64

has.na

boolean scalar defining whether the input vector might contain NAs. If we know we don't have NAs, this may speed-up. Note that you risk a crash if there are unexpected NAs with has.na=FALSE

na.last

boolean scalar telling ramsort whether to sort NAs last or first. Note that 'boolean' means that there is no third option NA as in sort

decreasing

boolean scalar telling ramsort whether to sort increasing or decreasing

stable

boolean scalar defining whether stable sorting is needed. Allowing non-stable may speed-up.

optimize

by default ramsort optimizes for 'time' which requires more RAM, set to 'memory' to minimize RAM requirements and sacrifice speed

VERBOSE

cat some info about chosen method

...

further arguments, passed from generics, ignored in methods

Author

Jens Oehlschlägel <[e-mail]>

Details

see sort and order

See Also

sort, sortcache

Examples

  x <- as.integer64(sample(c(rep(NA, 9), 1:9), 32, TRUE))
  x
  sort(x)
  message("the following has default optimize='time' which is faster but requires more RAM
, this calls 'ramorder'")
  order.integer64(x)
  message("slower with less RAM, this calls 'ramsortorder'")
  order.integer64(x, optimize="memory")