SCM

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).

Packages

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: linux(.tar.gz) | windows(.zip) | Build status: Current
  R install command: install.packages("R.ff", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


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: 1.1-13 | Last change: 2015-06-26 19:46:09+02 | Rev.: 157
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get bit 1.1-12 from CRAN
  R install command: install.packages("bit", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


bit64

A S3 Class for Vectors of 64bit Integers

  Package bit64 provides serializable S3 atomic 64bit (signed) integers that 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 interactive data exploration and manipulation and optionally leverage caching.
  Version: 0.9-5 | Last change: 2016-03-25 14:22:03+01 | Rev.: 160
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get bit64 0.9-5 from CRAN
  R install command: install.packages("bit64", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


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: 2015-07-04 09:52:44+02 | Rev.: 159
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get ff 2.2-13 from CRAN
  R install command: install.packages("ff", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


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: 2013-12-02 20:13:58+01 | Rev.: 138
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get ref 0.99 from CRAN
  R install command: install.packages("ref", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)

 

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.

Thanks to:
Vienna University of Economics and Business University of Wisconsin - Madison Powered By FusionForge