R: Low-level intger64 methods for in-RAM sorting and ordering
ramsort.integer64
R Documentation
Low-level intger64 methods for in-RAM sorting and ordering
Description
Fast low-level methods for sorting and ordering.
The ..sortorder methods do sorting and ordering at once, which requires more RAM than ordering but is (almost) as fast as as sorting.
Usage
## S3 method for class 'integer64'
shellsort(x, has.na=TRUE, na.last=FALSE, decreasing=FALSE, ...)
## S3 method for class 'integer64'
shellsortorder(x, i, has.na=TRUE, na.last=FALSE, decreasing=FALSE, ...)
## S3 method for class 'integer64'
shellorder(x, i, has.na=TRUE, na.last=FALSE, decreasing=FALSE, ...)
## S3 method for class 'integer64'
mergesort(x, has.na=TRUE, na.last=FALSE, decreasing=FALSE, ...)
## S3 method for class 'integer64'
mergeorder(x, i, has.na=TRUE, na.last=FALSE, decreasing=FALSE, ...)
## S3 method for class 'integer64'
mergesortorder(x, i, has.na=TRUE, na.last=FALSE, decreasing=FALSE, ...)
## S3 method for class 'integer64'
quicksort(x, has.na=TRUE, na.last=FALSE, decreasing=FALSE
, restlevel=floor(1.5*log2(length(x))), ...)
## S3 method for class 'integer64'
quicksortorder(x, i, has.na=TRUE, na.last=FALSE, decreasing=FALSE
, restlevel=floor(1.5*log2(length(x))), ...)
## S3 method for class 'integer64'
quickorder(x, i, has.na=TRUE, na.last=FALSE, decreasing=FALSE
, restlevel=floor(1.5*log2(length(x))), ...)
## S3 method for class 'integer64'
radixsort(x, has.na=TRUE, na.last=FALSE, decreasing=FALSE, radixbits=8L, ...)
## S3 method for class 'integer64'
radixsortorder(x, i, has.na=TRUE, na.last=FALSE, decreasing=FALSE, radixbits=8L, ...)
## S3 method for class 'integer64'
radixorder(x, i, has.na=TRUE, na.last=FALSE, decreasing=FALSE, radixbits=8L, ...)
## S3 method for class 'integer64'
ramsort(x, has.na = TRUE, na.last=FALSE, decreasing = FALSE, stable = TRUE
, optimize = c("time", "memory"), VERBOSE = FALSE, ...)
## S3 method for class 'integer64'
ramsortorder(x, i, has.na = TRUE, na.last=FALSE, decreasing = FALSE, stable = TRUE
, optimize = c("time", "memory"), VERBOSE = FALSE, ...)
## S3 method for class 'integer64'
ramorder(x, i, has.na = TRUE, na.last=FALSE, decreasing = FALSE, stable = TRUE
, optimize = c("time", "memory"), VERBOSE = FALSE, ...)
Arguments
x
a vector to be sorted by ramsort and ramsortorder, i.e. the output of sort
i
integer positions to be modified by ramorder and ramsortorder, default is 1:n, in this case the output is similar to order
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
restlevel
number of remaining recursionlevels before quicksort switches from recursing to shellsort
radixbits
size of radix in bits
VERBOSE
cat some info about chosen method
...
further arguments, passed from generics, ignored in methods
Details
see ramsort
Value
These functions return the number of NAs found or assumed during sorting
Note
Note that these methods purposely violate the functional programming paradigm: they are called for the side-effect of changing some of their arguments.
The sort-methods change x, the order-methods change i, and the sortoder-methods change both x and i
ramsort for the generic, ramsort.default for the methods provided by package ff, sort.integer64 for the sort interface and sortcache for caching the work of sorting
Examples
x <- as.integer64(sample(c(rep(NA, 9), 1:9), 32, TRUE))
x
message("ramsort example")
s <- clone(x)
ramsort(s)
message("s has been changed in-place - whether or not ramsort uses an in-place algorithm")
s
message("ramorder example")
s <- clone(x)
o <- seq_along(s)
ramorder(s, o)
message("o has been changed in-place - s remains unchanged")
s
o
s[o]
message("ramsortorder example")
o <- seq_along(s)
ramsortorder(s, o)
message("s and o have both been changed in-place - this is much faster")
s
o