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()
decreasing: boolean scalar telling ramsort whether to sort increasing or decreasing
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()
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

Details

see sort() and order()

Examples

Run this code

  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")