R Development Page
Contributed R Packages
Below is a list of all packages provided by project Large objects for R.
Important note for package
binaries: R-Forge provides these binaries only for
the most recent version of R, but not for older
versions. In order to successfully install the
packages provided on R-Forge, you have to switch
to the most recent version of R or, alternatively,
install from the package sources (.tar.gz).
|
R.ff | R functions for large ff data
|
| |
So far only an experimental stub with ffchunk() supporting convenient chunked looping |
| |
Version: 0.02 |
Last change: 2012-11-05 22:25:03+01 |
Rev.: 120 |
| |
Download:
 (.tar.gz) |
 (.zip) |
Build status: Current |
| |
R install command:
install.packages("R.ff", repos="http://R-Forge.R-project.org") |
| |
|
|
bit | A Class for Vectors of 1-Bit Booleans
|
| |
True boolean datatype (no NAs),
coercion from and to logicals, integers and integer subscripts;
fast boolean operators and fast summary statistics.
With bit vectors you can store true binary booleans {FALSE,TRUE} at the
expense of 1 bit only, on a 32 bit architecture this means factor 32 less
RAM and ~ factor 32 more speed on boolean operations. Due to overhead of
R calls, actual speed gain depends on the size of the vector: expect gains
for vectors of size > 10000 elements. Even for one-time boolean operations
it can pay-off to convert to bit, the pay-off is obvious, when such
components are used more than once.
Reading from and writing to bit is approximately as fast as accessing
standard logicals - mostly due to Rs time for memory allocation. The package
allows to work with pre-allocated memory for return values by calling .Call()
directly: when evaluating the speed of C-access with pre-allocated vector
memory, coping from bit to logical requires only 70% of the time for copying
from logical to logical; and copying from logical to bit comes at a
performance penalty of 150%. the package now contains further classes for
representing logical selections: bitwhich for very skewed selections and
ri for selecting ranges of values for chunked processing. All three index
classes can be used for subsetting ff objects (ff-2.1-0 and higher). |
| |
Version: 1.1-14 |
Last change: 2018-08-17 19:45:18+02 |
Rev.: 177 |
| |
Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get bit 4.0.5 from CRAN |
| |
R install command:
install.packages("bit", repos="http://R-Forge.R-project.org") |
| |
|
|
bit64 | A S3 Class for Vectors of 64bit Integers
|
| |
Package bit64 provides serializable S3 atomic 64bit (signed) integers.
These are useful for handling database keys and exact counting in +-2^63.
WARNING: do not use them as replacement for 32bit integers, integer64 are not
supported for subscripting by R-core and they have different semantics when
combined with double, e.g. integer64 + double => integer64.
Class integer64 can be used in vectors, matrices, arrays and data.frames.
Methods are available for coercion from and to logicals, integers, doubles,
characters and factors as well as many elementwise and summary functions.
Many fast algorithmic operations such as match and order support inter-
active data exploration and manipulation and optionally leverage caching. |
| |
Version: 0.9-8 |
Last change: 2018-08-17 19:45:18+02 |
Rev.: 177 |
| |
Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get bit64 4.0.5 from CRAN |
| |
R install command:
install.packages("bit64", repos="http://R-Forge.R-project.org") |
| |
|
|
ff | Memory-Efficient Storage of Large Data on Disk and Fast Access Functions
|
| |
The ff package provides data structures that are stored on
disk but behave (almost) as if they were in RAM by transparently
mapping only a section (pagesize) in main memory - the effective
virtual memory consumption per ff object. ff supports Rs standard
atomic data types double, logical, raw and integer and
non-standard atomic types boolean (1 bit), quad (2 bit unsigned),
nibble (4 bit unsigned), byte (1 byte signed with NAs), ubyte (1 byte
unsigned), short (2 byte signed with NAs), ushort (2 byte unsigned),
single (4 byte float with NAs). For example quad allows efficient
storage of genomic data as an A,T,G,C factor. The unsigned
types support circular arithmetic. There is also support for
close-to-atomic types factor, ordered, POSIXct, Date and
custom close-to-atomic types.
ff not only has native C-support for vectors, matrices and arrays
with flexible dimorder (major column-order, major row-order and
generalizations for arrays). There is also a ffdf class not unlike
data.frames and import/export filters for csv files.
ff objects store raw data in binary flat files in native encoding,
and complement this with metadata stored in R as physical and virtual
attributes. ff objects have well-defined hybrid copying semantics,
which gives rise to certain performance improvements through
virtualization. ff objects can be stored and reopened across R
sessions. ff files can be shared by multiple ff R objects
(using different data en/de-coding schemes) in the same process
or from multiple R processes to exploit parallelism. A wide choice of
finalizer options allows to work with permanent files as well as
creating/removing temporary ff files completely transparent to the
user. On certain OS/Filesystem combinations, creating the ff files
works without notable delay thanks to using sparse file allocation.
Several access optimization techniques such as Hybrid Index
Preprocessing and Virtualization are implemented to achieve good
performance even with large datasets, for example virtual matrix
transpose without touching a single byte on disk. Further, to reduce
disk I/O, logicals and non-standard data types get stored native and
compact on binary flat files i.e. logicals take up exactly 2 bits to
represent TRUE, FALSE and NA.
Beyond basic access functions, the ff package also provides
compatibility functions that facilitate writing code for ff and ram
objects and support for batch processing on ff objects (e.g. as.ram,
as.ff, ffapply). ff interfaces closely with functionality from package
bit: chunked looping, fast bit operations and coercions between
different objects that can store subscript information (bit,
bitwhich, ff boolean, ri range index, hi hybrid index). This allows
to work interactively with selections of large datasets and quickly
modify selection criteria.
Further high-performance enhancements can be made available upon request. |
| |
Version: 2.2-14 |
Last change: 2018-04-15 17:29:52+02 |
Rev.: 175 |
| |
Download:
(.tar.gz) |
(.zip) |
Build status: Failed to build | Stable Release: Get ff 4.0.9 from CRAN |
| |
R install command:
install.packages("ff", repos="http://R-Forge.R-project.org") |
| |
|
|
ref | References for R
|
| |
small package with functions for creating references,
reading from and writing to references and a memory efficient
refdata type that transparently encapsulates matrices and
data.frames |
| |
Version: 0.99 |
Last change: 2018-08-17 19:45:18+02 |
Rev.: 177 |
| |
Download:
(.tar.gz) |
(.zip) |
Build status: Current |
| |
R install command:
install.packages("ref", repos="http://R-Forge.R-project.org") |
| |
|
Build status codes
0 - Current: the package is available for download. The corresponding package passed checks on the Linux and Windows platform without ERRORs.
1 - Scheduled for build: the package has been recognized by the build system and provided in the staging area.
2 - Building: the package has been sent to the build machines. It will be built and checked using the latest patched version of R. Note that it is included in a batch of several packages. Thus, this process will take some time to finish.
3 - Failed to build: the package failed to build or did not pass the checks on the Linux and/or Windows platform. It is not made available since it does not meet the policies.
4 - Conflicts: two or more packages of the same name exist. None of them will be built. Maintainers are asked to negotiate further actions.
5 - Offline: the package is not available. The build system may be offline or the package maintainer did not trigger a rebuild (done e.g., via committing to the package repository).
If your package is not shown on this page or not building, then check the build system status report.
