Earlier today, Ian Fwllows has announced the release of Deducer 0.4-2 and DeducerExtras 1.2 to CRAN (I copy his announcement here): Deducer 0.4-2 contains a few bug fixes, and an interface to the iplots package. With the new iplots interface it is now possible to do interactive plots with Deducer. An introductory example screen cast (by Ian) is available on the tube:
DeducerExtras 1.2 contains a few new dialogs including ‘load data from package’, and ‘t-test power’.
Additionally, a new Windows R/JGR/Deducer installer is available which installs R-2.12.0, JGR with it’s launcher, Deducer, DeducerExtras, and DeducerPlugInScaling. It is available on the Deducer website:
Today I was informed of (what I believe is) a better the best WordPress plugin for R syntax highlighting called WP-CodeBox. This plugin doesn’t require any hacks to make it work (as opposed to the WP-Syntax plugin, which I wrote about in the past). WP-CodeBox can be downloaded and installed on a WordPress by searching for it in the “Add New” section in the plugins menu.
WP-CodeBox provides some nice features (some AJAX based) to the display of the code in the post:
The code box in the post can now be folded (top right of the code box) so the code can be hidden so to not clutter the post (if the code is too long)
The code box is added with another button (top left of the code box) which allows the reader to see the code in a new window – so to easily enable a copy paste of the code.
The options of the plugin allows automatic row numbering of the code, control over “tab” length and some other features.
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.
Here are the new features of ff, as Jens wrote in his announcement:
Dear R community,
The next release of package ff is available on CRAN. With kind help of Brian Ripley it now supports the Win64 and Sun versions of R. It has three major functional enhancements:
a) new fast in-memory sorting and ordering functions (single-threaded)
b) ff now supports on-disk sorting and ordering of ff vectors and ffdf dataframes
c) ff integer vectors now can be used as subscripts of ff vectors and ffdf dataframes
a) is achieved by careful implementation of NA-handling and exploiting context information
b) although permanently stored, sorting and ordering of ff objects can be faster than the standard routines in R
c) applying an order to ff vectors and ffdf dataframes is substantially slower than in pure R because it involves disk-access AND sorting index positions (to avoid random access).
There is still room for improvement, however, the current status should already be useful. I run some comparisons with SAS (see end of mail):
– both could sort German census size (81e6 rows) on a 3GB notebook
– ff sorts and orders faster on single columns
– sorting big multicolumn-tables is faster in SAS