This R for Mac OS X FAQ is rather incomplete at the moment and requires contributions from users. Anything specific to the R language can be found in the official R-FAQ (see http://cran.r-project.org/doc/FAQ/R-FAQ.html). Please send any requests/questions you would like answers on to the maintainers.
In this document R refers to the core, command line based R system while R.app refers to the GUI based Mac OS application that controls the underlying R.
This document contains information on how to build R from sources, how to install and run it. It also contains a user guide to the R.app version of R.
There is currently only one version of R for Mac OS X. However, R on Mac OS X can be used either on the command-line (see Command line version of R) like on other Unix systems, or via the R.app GUI (see R.app). The second approach is mostly preferred by Macintosh users.
R for Mac OS X requires Mac OS X version 10.2 (Jaguar) or higher to run. The R.app GUI requires Mac OS X 10.3 (Panther) or higher. The latest version of the system is always preferable, though. We do not support Mac OS X version 10.1 and earlier. The binaries provided on CRAN are universal and require Mac OS X 10.4.4 (Tiger) or higher.
R can be compiled from sources as a pure 64-bit application on PowerMac G5 machines, but currently the R.app GUI does not support such setup.
R for Mac OS X is available on CRAN in the form of a disk image containing a multi-package consisting of the R framework, the R.app GUI and optional libraries. The image is usually named R.dmg with optional version number.
The installation is done by double-clicking on the disk image, which opens a new Finder window with the installer package, followed by double-clicking on that package installer. The installer will guide you through the steps necessary to install R on Mac OS X. Note that the installer will require password or login of an administrator. The installation can be customized, but the default is suitable for most users.
If you experience problems with R, we highly recommend the use of the CRAN binary package to make sure R was built correctly. Nevertheless it is possible to build R from the sources which can be useful for special purposes. Note that the CRAN binary includes R shared library, so there is no need to re-compile R with --enable-R-shlib
.
The requirements for building R vary, depending whether the build machine is an Intel-based or PowerPC-based Mac and whether universal build is desired. The following description shows the minimum requirements for building R. The process of building a universal binary is more complex and described in section see How to build universal R.
If you have Mac OS X 10.3 (aka Panther) or higher you just need to install the software from the Xcode Tools CD or DVD. This is only true if you bought retial version of Mac OS X. If your computer came with pre-installed version of OS X, look into /Applications/Installers. Recent installations feature Xcode Tools folder containing the necessary installer. If neither of the above works for you, download Xcode from Apple Developer Connection site (see Apple Developer Connection): in the download section, look for Xcode Tools v 1.1 or above (the most recent version of Xcode tools available for Tiger is version 2.2.1). During the installation, don't forget to setect X11 SDK if you plan to use X11.
If you are using Mac OS X 10.2 (aka Jaguar) then you should download and install the Apple Developers Tools Dec 2002 including the latest updates which dates August 2003. Either it comes on a separate CD with your Mac or you can download these from the Apple Developer Connection site (see Apple Developer Connection) In either cases be sure you have gcc version 3.3 or later - you can check the version by typing the following in a Terminal window:
gcc --version
Users of Intel Macs have to use gcc version 4.0 or higher, because gcc 3.x is not supported on Intel Macs.
Unfortunately the Xcode Tools don't include a Fortran compiler. You need to install a version 3.3 or later of the Fortran compiler from gcc which is built for Mac OS X. R 2.3.0 CRAN binary comes with GNU Fortran F95 4.0.3 in the gcc optional package. If you plan to install packages from sources, select "custom install" during R installation and enable the GNU GCC from the list of packages. The CRAN binaries are configured to use gcc 4.0.3 and the supplied Fortran compiler.
Please note that it is important that the major version of the Fortran compiler matches the version of your C compiler! You can only use gcc 3.x with g77 3.x or gcc 4.0 with gfortran 4.x, other combinations don't work.
The readline library is optional and only necessary for OS X 10.3 (Panther) and earlier. Mac OS X 10.4 (Tiger) comes with libedit library which emulated readline. Nevertheless, GNU readline has some addiional functionality so it may be worth installing anyway.
Readline is necessary if you want to be able to retrieve history using use arrow keys or for <TAB> completion of filenames when you run R as a command line tool. The original source archive is located at GNU web page ftp://www.gnu.org.
Readline 5.0 and later compile out-of-the box, however it is recommended to use make CPPFLAGS=-DNEED_EXTERN_PC
, because the configure script fails to detect that flag. The use of readline 5.1 with recent patches is recommended due to bugs in earlier versions that can lead to crashes.
If using readline 4.3, you need to modify the original file shlib/Makefile.in in order to make it
work under Mac OS X 10.2.x and later (this is because libreadline needs to be linked against
-lncurses -lcc_dynamic
). If you can do better at configure time working on the original archive
let me know. I suggest you to download my patched version from http://www.economia.unimi.it/R.
Once you have done, please do the following (you'll be asked for a root password):
uncompress the archive, cd inside the folder and type the following
./configure make sudo make install
It installs everything in /usr/local.
X11 window system is necessary to use the X11 device in R and other devices that rely on X11. Mac OS X 10.3 (Panther) and later include X11 on the installation CD/DVD, however, it is not selected by default. If it is not installed, you can re-install it using the original installation CD/DVD. The corresponding package is either visible directly, or you can select the multi-package of bundled software, control-click on it, select Show Original - in the same directory that it will warp you to there is the X11 installer, labeled X11User.pkg.
In addition to the user part, you need to install the X11 SDK package from the Xcode Tools CD. Again, it is not selected by default, so make sure you select it during the installation of Xcode Tools.
Mac OS X 10.2 (Jaguar) does not include X11 installer. However, there are two options to obtain X11: Apple released X11 beta for Jaguar which is still around, although not officially supported. It features the Quartz window manager that integrates nicely into the system. If you are unable to find Apple's X11 beta, you will need to install both the X11 Window server and the X11 SDK package from the XFree86 web page. Other versions such as using fink are available, too.
If you plan to use tcltk package for R, you can either use Tcl/Tk headers and library supplied in the R CRAN binary or compile your own. The CRAN binary includes universal Tcl/Tk 8.4.12 for X11. This package is optional so you need to select "custom install" during R installation and enable it. This is the recommended procedure because it will allow you to use CRAN R package binaries as well.
Alternatively you need to download the sources of the Tcl and Tk 8.4.x packages to build yourself the sources. The original sources can be found on the official TclTk web page http://www.tcl.tk/software/tcltk/8.4.html. Please do the following respecting the sequence (you'll be asked for a root password). These are examples for version 8.4.4 of the Tcl and Tk sources, you'll probably find new version on the web page, thus only the name of the .tar.gz archives changes.
The following shell commands will download, compile and install universal Tcl/Tk. Modify the configure part to suit your needs, such as if you don't need all architectures:
cd /tmp/ curl -O http://internap.dl.sourceforge.net/sourceforge/tcl/tcl8.4.12-src.tar.gz curl -O http://internap.dl.sourceforge.net/sourceforge/tcl/tk8.4.12-src.tar.gz tar fxz tcl8.4.12-src.tar.gz cd tcl8.4.12/unix CFLAGS='-arch i386 -arch ppc -arch ppc64' ./configure --with-x \ --disable-corefoundation --enable-threads --disable-symbols --disable-aqua make sudo make install cd ../.. tar fxz tk8.4.12-src.tar.gz cd tk8.4.12/unix CFLAGS='-arch i386 -arch ppc -arch ppc64' ./configure --with-x \ --disable-corefoundation --enable-threads --disable-symbols --disable-aqua make sudo make install
Mac OS X 10.4 (Tiger) comes with Aqua TclTk libraries. If those are not detected automatically, use the following flags with configure
:
--with-tcl-config=/System/Library/Frameworks/Tcl.framework/tclConfig.sh --with-tk-config=/System/Library/Frameworks/Tk.framework/tkConfig.sh
For older versions of OS X you need to obtain Aqua TclTk separately. Once you have installed the AquaTclTk libraries and headers files, you can configure R using these additional arguments
--with-tcl-config=/Library/Frameworks/Tcl.framework/tclConfig.sh --with-tk-config=/Library/Frameworks/Tk.framework/tkConfig.sh TCLTK_LIBS='-framework Tcl -framework Tk' TCLTK_CPPFLAGS='-I/Library/Frameworks/Tcl.Framework/Headers -I/Library/Frameworks/Tk.Framework/Headers'
Note that currently R.app doesn't support Aqua Tcl/Tk, because of conflicting event loops.
There is a nice installer, called the i-Installer II, that allows you to install a complete teTeX distribution. You can find details on the i-Installer at http://www.rna.nl/ii.html. The teTeX is one of the i-Packages.
Note: You may also want to install TeXShop (http://www.uoregon.edu/~koch/texshop/texshop.html). Beside wonderful GUI for editing TeX files that page also provides many useful links for TeX on Mac OS X.
Download the latest sources of R from CRAN. Unpack the archive with tar -zxf name_of_R_sources_archive and cd inside the R sources directory. Then you need to configure R for your system and build R. Just type
./configure make
This will configure R to be built as a Framework to be installed inside your /Library/Frameworks directory with the name
R.framework. You can change the default location of the R.framework
installation at configure time by specifying the flag --enable-R-framework[=DIR]
, i.e.
with something like
./configure --enable-R-framework=FOO
and the final destination of the R.framework will be FOO/R.framework, which means that you don't have to specify the R.framework text in the path.
A standard installation of R requires you have built it as a Framework. At this point just type (a root password will be required):
sudo make install
and all will be installed in /Library/Frameworks. You can decide to change the R.framework destination by using the prefix option specifying the final destination.
sudo make prefix=/where/you/want/R.framework/to/go install
As in the above, you don't need to specify the name R.framework in the path.
The sources for the R.app GUI are currently not included in the global R source distribution. They are available in the form of a Xcode project on the R for Mac OS X pages as well as the SVN repository. Before compiling R.app make sure R is installed as /Library/Frameworks/R.framework and working.
Using Xcode load the R.xcodeproj project, select R target (which is the default), set Deployment configuration build. The same effect can be achieved on the command line in the Mac-GUI directory by typing:
xcodebuild -target R -configuration Deployment
The current development is done using Xcode 2.2.1. The default build is universal, therefore you will need universal R framework and Mac OS X 10.4u SDK. Make sure R is available inside the SDK by running the following in Terminal:
ln -sf /Library /Developer/SDKs/MacOSX10.4u.sdk/Library
For compatibility, the GUI offers an old-style project for Xcode 2.0 named R.xcode which will build PowerPC binary only. However, this project file is no longer actively maintained.
The build includes both R.app and this R for Mac OS X FAQ. However, it is recommended to use at least GNU texinfo 4.7, because a bug in previous versions leads to invalid html output. Mac OS X 10.4 (Tiger) and later include the correct version of makeinfo.
R.app does not need to be installed in any specific way. Building R.app results in the R.app bundle which appears as one R icon. This application bundle can be run anywhere and it is customary to place it in the Applications folder.
Starting with R 2.3.0 it is possible to build R that runs on multiple architectures. One special application of this feature is to build R that runs on both Intel and PowerPC based Macs on Mac OS X 10.4.4 or higher. Such R build is called universal.
In order to be able to build universal R, all necessary libraries must be available as i386 and ppc binaries. For system libraries this is the default for Mac OS X on Intel Macs. Other libraries such as readline must be compiled accordingly.
In addition, the compilers must support both architectures as well. For Intel Macs, such compilers are supplied with R 2.3.0 in the CRAN binary package (GNU gcc 4.0.3 with Apple drivers).
The next step is to build a binary for each architecture. This can be either done natively n two machines - one PowerPC and one Intel based Mac, or by cross-compiling the PowerPC part on an Intel Mac. In either case, the configuration is the same.
Configure, build and install the ppc binary (assuming R-2.3.0.tar.gz is in the current directory, replace R-2.3.0 with any other version or name as appropriate):
tar fxz R-2.3.0.tar.gz mkdir R-ppc cd R-ppc ../R-2.3.0/configure r_arch=ppc CC="gcc-4.0 -arch ppc" \ CXX="g++-4.0 -arch ppc" F77="gfortran-4.0 -arch ppc" \ FC="gfortran-4.0 -arch ppc" make make install cd ..
Depending on your permissions, you may need to run sudo make install. The next step is to build and install the Intel binary:
mkdir R-i386 cd R-i386 ../R-2.3.0/configure r_arch=i386 CC="gcc-4.0 -arch i386" \ CXX="g++-4.0 -arch i386" F77="gfortran-4.0 -arch i386" \ FC="gfortran-4.0 -arch i386" CPPFLAGS=-msse3 make make install cd ..
The installation scripts in R are intelligent enough to merge both builds together and create a universal R framework. One crucial requirement for this to work is to use i386 and ppc as the architecture names.
It is possible to use additional flags at configure time. To optimize the build for Intel Core Solo/Duo processors, add the following flags for the Intel build:
CFLAGS="-g -O2 -march=pentium-m -mtune=prescott" \ CXXFLAGS="-g -O2 -march=pentium-m -mtune=prescott" \ FFLAGS="-g -O2 -march=pentium-m -mtune=prescott" \ FCFLAGS="-g -O2 -march=pentium-m -mtune=prescott"
In addition, vecLib currently does not use both cores on Core Duo, so it advisable to use threaded BLAS library such as ATLAS instead. Assuming ATLAS is installed in a standard place, the corresponding configure flag is
--with-blas="-lptf77blas -lpthread -latlas"
Finally, the standard R shell script uses by default the last installed architecture. This is probably not what you want, because the native architecture is known at run time. Therefore the line
: ${R_ARCH=/i386}
can be replaced by
: ${R_ARCH=/`arch`}.
to default to the current native architecture. It addition, it may be a good idea to make sure that the PATH environment variable contains the path to your universal compiler, otherwise there may be problems with compilation of universal packages.
The command line version of R is identical to R as used on other unix operating systems. Therefore general documentation for R applies to this version as well. On each release (and patched-release) ready to use binaries are distributed through CRAN. These binaries come with a common installer used by R.app so please read the related notes (see How to get R.app). To use R you probably need to add a symbolic link on your system as the R binary is located inside the framework. Suppose you have the /usr/local/bin directory on your system (if you do not have one, you can use /usr/bin instead) you should just type in your Terminal (a root password is required)
sudo ln -s /Library/Frameworks/R.framework/Resources/R /usr/local/bin/R
Assuming that you have /usr/local/bin in your PATH environment variable, you will be able to launch R from any location on your system just by typing R. In this way, when you install a new version of the R.framework this link will point to the latest R binary.
R.app is the name for the new Cocoa-based GUI for Mac OS X that was introduced in R 2.0. It appears as an icon labeled R, but to avoid confusion with general R, we prefer to use the name as it appears when using Get Info on the GUI: R.app This stands for R application.
Internally R.app is a Cocoa program (hence written in Obj-C) that loads R dynamic library in order to use R facilities.
Historically there were two more GUI for Mac OS X: RAqua and Cocoa GUI bundle. The latter was never officially released and RAqua was retired in R version 2.1, because it used legacy toolkit from the times of Mac OS9.
R.app is part of the binary distribution of R for Mac OS X available from CRAN. That distribution consists of one disk image containing multiple packages including R framework and R.app.
Development versions of R.app are made available on daily basis in the form of a disk image containing the R.app itself. See the Mac OS X pages on CRAN for detail how to obtain such images.
R.app is installed the same way as the R framework, namely using binary package provided on CRAN. The bin/macosx directory of a CRAN site contains a standard Apple installer package inside a disk image named R.dmg (optinally containing the version number). Download and double-click the image. New window will appear with a package icon representing the installer. Double-click that icon and it will install the current non-developer release of R, including R.app.
In this section you'll find general information on the R.app. For specific R tasks that can be done via the R.app using menus you should read below (see The Menus).
The current design of the R Console is to have a single frame for input (user) and output (R).
Copy and paste works in R as in any other Macintosh application.
If you want high resolution graphic exports, you can save the PDF format using the File/Save as menu item (see Quartz device). Or you can use supported formats in R through pdf()
, jpeg()
etc. (type ?capabilities
to get more details).
If not otherwise specified in the Preferences (see Preferences), or if the specified path is no longer available, then the default working directory at startup is the user home.
The working directory can be changed using the setwd R command or using the Misc menu item Change working directory. Finally it is possible to use a specific directory for a single R session by dragging a folder onto the R.app icon. If R.app is not runnig, this will cause R.app to be started in the directory corresponding to the folder dragged. The same can be achieved on the command line - for example open -a R .
causes R.app to be started using the current directory as the startup working directory.
This feature is useful if you want different startup procedures defined by the .Rprofile; you can edit a .Rprofile (containing you personal initialization R commands) in a particular directory and use the Preferences (or any other method mentioned above) to change the startup directory. Next time you launch R.app the .Rprofile is read and executed by R at startup. This is the equivalent on Unix (or the command line) to launch R from different directories.
When the R Console Window is resized, the R option width is set appropriately so that any future output will fit the window size. This behavior can be inhibited using the Preferences settings (see Preferences). On closing the R application, the position and the size of the R Console window are saved in the Preferences and reused next time you launch R. You can inhibit R to do this using the appropriate Preferences settings.
Text windows and frames are divided in Read-Only and Read and Write ones. Text colors can be set separately for the two kinds of windows. This happens as well for their respective backgrounds. Use the Preferences window to set these colors (see Preferences).
R.app provides an integrated editor for editing of R code. It sports a number of features designed to help developing code inside R. The probably most often used function is the ability to execute code directly from the editor by pressing <Command>-<Return>. Other features include syntax highlighting, brace-matching, code completion and function indexing.
The editor supports undo/redo operations on an appropriate level of granularity (used to be all or nothing). The editor has an optional facility to show line numbers. These help with locating error messages. The editor also responds to the 'Go to Line' Edit menu function. The associated Preference Pane allows enabling/disabling of the line numbers, as well as setting line number gutter width and text margin width.
Completion of typed input (both file names and R code) in the editor is available through the Edit menu 'Complete' or by typing <Control>-<.> (same as is Xcode). It uses the same facilities as the console window (for compatibility the console responds to both <Tab> and <Control>-<.>).
The editor maintains a popup list of functions defined in the edited document. The list is available in the toolbar and is updated as you type. Selecting a function from that list causes the cursor to jump to the beginning of the function.
The editor supports syntax-highlighting for R code. It is possible to change the syntax highlighting colors using the Syntax Color Preference Pane (see below).
By default, the editor used is incorporated into R.app, the Mac OS X GUI for R. It is a
relatively simple multi-document editor that supports the features listed above. Additionally,
two powerful commands are available to source the file being edited in its entirety (Command-E)
or to source the current selection to R (Command-Return). Using R's edit()
function, allows
editing of R objects or files while R is kept waiting for the edit session to finish.
It is possible to 'redirect' all R requests to an external editor, which runs
outside R.app. In that case, it is not possible to keep R waiting if edit()
is used. Using
AppleScript it is easy to implement Command-E and Command-Return like functionality.
The editor contains a light-weight help system in form of a search filed placed inside the toolbar. It is possible to use either an exact or approximate search.
Drag and drop of a directory on the R icon while R is not running will start R and set the working directory. By default .RData and .Rhistory are fetched from this working directory. If a file is dropped on thr R icon while R is not running, R is started, the file is either restored (if it is a saved workspace), sourced into R or opened in the selected editor. Whether the file is opened or sourced is specified by a Preference setting in the StartUp Preference Pane. Note: At this point opening a file in the editor before R is finished loading will crash R. While R is running, d&d of a directory updates the working directory. D&d of a file sources or opens the file in the selected editor. Double clicking on files bound to ("Open With ...") R, if R is not running, R is started and the file is sourced or opened in editor. If R is running, the file is opened in the editor.
The Help screen allows a user to go back or forward to previous help pages. It is possible to print help pages. If a help topic is not found, a pop-up window allows to exit the help search or expand the search to a fuzzy/approximate search.
R.app uses history files that are (superset) compatible with history files created by R. Multiline support remains available from inside R.app. Multiline is particularly useful when using the <Command>-<Return> feature while editing an R script. Import and export allows storing and importing history from files visible in the Mac OS Finder. Multiline is preserved. This can be set through the StartUp Preference Panel. Default number of kept history entries is 250. A variety of history entry cleanup modes is possible. At a minimum I would suggest to select "Cleanup history entries". It's optional to select removal of duplicate entries and strip comments.
The official CRAN binaries come pre-packaged in such a way that administrator have sufficient privileges to update R and install packages system-wide. However, the default unix build requires root-authentication for package instllation and other administrative tasks. As it is not feasible to run the GUI as root, we provide the possibility to authenticate system commands issued from the GUI. The authentication requires an administrator login and causes all subsequent system commands to be executed as root. Use with care!
In order to allow non-administrators to maintain their own set of packages, R.app optionally adds ~/Library/R/library
to the .libPaths
(see start-up preferences). It is possible to use the Package Installer to install packages either globally (admin users only) or for the current user only. Note that user-local packages are only used when the corresponding preference option is enabled. The default for admin users is to use system-wide directorie, for non-admin users local packages will be used.
Several aditional preference panes have been implemented (see below).
The Drag & drop section defines drag & drop behaviour during R start-up. Options are to open file in an editor or to source file. Default is to source the file. The Default Library Paths section enables, on next start-up of R, to add a directory, e.g. ~/R/Library, to the library search/install path. The initial working directory section can be used to enforce the initial working directory. If no directory is specified, this directory is used as the default. The Change button allows to select a new directory. The Always apply selection will enforce the specified intial start-up directory. The history section controls reading of the history file on startup. If selected, R will read history file on start-up. The R history file field is used to read and store history from/to. This field can be edited to allow selecting files starting with a period (e.g. .Rhistory). If you want the same history file regardless of your selected working directory, specify a fixec path (e.g. ~/.Rhistory). The Default button will reset the history file name to its default value. The History handling area allows setting of the max number of entries to be kept in history, to remove duplicate entries, to cleanup history entries (this is very useful to remove blank lines when submitting multiple lines using Command-Return) and the strip comments before the entry is added to the history.
If Built-in editor is selected, allows enable/disable of syntax coloring, brace highlighting and the showing of line numbers. If External editor is selected, allows specifying which external editor. That editor will be used for all editing functions. It runs as a separate application. Using an external editor means that R will never wait while editing (e.g. edit(A) will return immediately and open A in the external editor. Command-E and Command-Return like functionality would need to be implemented by other means, i.e. AppleScript. The external editor can be any application (e.g. SubEthaEdit, TextWrangler, BBEdit, Smultron, etc) or can be activated through a shell script (e.g. see or smultron, both give better control on how to start the editor).
Enables to select the syntax colors.
Enables to select the input/output colors in R Console.
Use the Quartz preference pane to override R Quartz width/height parameters if override is enabled. You can set the default location for initial Quartz window. Subsequent windows are offset sligthly. The Font section is not implemented. Restore defaults resets to default values.
The Application menu is the first one after the main Apple Menu.
With this menu you can access three items: 1. the About box, which tells you which version of R is currently in use, 2. Check for updates, which search on CRAN if a new version of the binary distribution of R for Mac OS X is available (you need an internet connection), 3. you can access the Preferences (see Preferences).
This menu provides standard functionalities. The open command is associated to the action Source R code, which means that you can select a file, which is a script, and it will be executed in R. This is a interface to the R source command source.
Apart for standard functionalities, the only relevant item in this menu is the Edito Object which is an interface to the R edit function.
With this menu you can load and save the history of commands typed in the R Console or view what's currently inside. You can also change the current working directory, let R show you the current working directory or set it back to the startup directory. From release 1.9.0 of R the current working directory is also shown on the main window bar.
Here you find self explanatory menu items for manage your workspace in R. You can either load and save the workspace also by specifying file name. All of these are interfaces to the load and save R commands. The only relevant item, which is specific to this GUI, is the Browse workspace. This will open a window with a summary description of the objects in your workspace. Complex objects (like lists, data.frame etc) can be expanded (one level only though).
Using this menu you can have access to the list of packages and data-sets installed on your system and to the ones on CRAN or on the Bioconductor site.
With the first two menus you can load and detach packages and data-set from the workspace. Let's start with the Package Manager. This opens a window with several columns displayed. For each package on your system you can see a check box, the current status of the package (loaded/not loaded), its name and the package description text. You use the check box to select/de-select the packages you want. On window closure, the checked packaged will be loaded and the unchecked ones (if loaded) will the detached (not completely as on Mac OS X you cannot unload completely dynamic libraries).
The same applies to the Dataset Manager menu but for data-sets.
You can than get or update packages CRAN either in binary or source format. Daily build of CRAN packages are available for Mac OS X. If you don't know how to build R itself from source (see Building R from sources), you'll probably be unable to build packages from source on your own. In this case, you should always choose for the binary option. These binary packages work (for sure!) for the release version of R for Mac OS X you find on CRAN even though it is not excluded that they will work for other prebuilt versions of R.
When you attempt to install packages from CRAN, R first tries to get a connection to the Internet to download the list of available packages. Than a window will open similar to the one in the package manager with the only difference that for each package there is also the information concerning the version of the package installed on your system (if any) and the version of the prebuilt package available on CRAN. When you close the window, the select packages will be downloaded.
The same strategy applies to the Bioconductor menu item, with some more options typical of the Bioconductor way of managing packages.
For some reason it could happen that you have the package you want to install (either in binary or source form) on one of your local disks, or even a directory containing a package source. You can use the last menu to do the task of installing the package. Having a package in a directory form usually applies to people that are developing packages themselves.
For more information on this topic see also How to install packages.
Using this menu you can open the on-line manuals (R Help), read this FAQ and review the latest changes, bug fixes and new features of R for Mac OS X (What's new in this version). There are also interfaces to the R help and help.search functions as well as the example function.
You can set several aspects of the R GUI via preferences. You can access the Preferences window via the Application menu when the R Console is open. Preferences are organized in Tabs, more or less grouped for content.
You can change the font size, face and the tab size in all the windows including the Console. If you have help windows opened, the changed only apply to the Console window and to the window you'll open from now on. This is a misfeature more than a bug.
You can also change the foreground and background colors for the read-only windows (i.e. the R Console output and the Help windows) and for read-and-write windows (i.e. the R Console input and the Edit windows). At the moment you cannot change the color of the cursor which always stays black which ever background you choose. So, for the time being, it's a bad idea to set the background of the R Console to black.
You have also the possibility to check two options. The first is for adapting the R output when you resize the R Console to the maximum character displayable, the second one is to let R remember the position of the R Console on exit.
You can set all the parameters of the quartz device for this tab. Please note: your changes only take effect if you select the final checkbox, namely override the R quartz default settings.
This also apply to the Quartz window position option even if it is not a quartz parameter itself.
From this tab you can set the default repositories for the CRAN and Bioconductor urls. This will affect the corresponding R options.
For this tab you can decide to redirect the stderr and stdout of R and the tasks launched by R, to the R Console. This is useful, for example, during package installation. If you don't check these options, every output will be sent to the Console application which you can find on every Mac OS X installation inside the directory /Applications/Utilities.
You can also set the startup working directory. This is very useful for having different sessions in different directories (see The current and startup working directories and How can I have a per session .Rprofile?).
We have introduced R.app in R 2.0. Although it was a new apporach, tt that point it was mainly replicating features fount in the old Carbon GUI. With R 2.1 we have moved more towards look at feel of the OS X operating system and worked mainly on improving the editor and its integration. In the near future we want to continue to improve the interface, add new features and exploit the possibilities of Mac OS X 10.4 (Tiger).
The R.app is still very much a moving target. Although we release official versions with each R release, we continue to work on R.app and offer experimental builds that can be used with the last official release of R. See http://www.economia.unimi.it/R for the current links to the most recent R.app.
On Unix systems a bug report can be generated using the function
bug.report()
. This automatically includes the version
information and sends the bug to the correct address. Alternatively the
bug report can be emailed to R-bugs@R-project.org or submitted
to the Web page at http://bugs.R-project.org/.
Before you fill a bug report, please try to reproduce it using both R.app and the console version of R (if applicable). If the bug if R.app-specific, please report the bug to R-SIG-Mac@R-project.org instead.
In any circumstances, in case of a crash, please report the crash.log for the R.bin and/or R.app application. You can get this crash.log using the Console.app located inside /Applications/Utilities.
You have several options for installing new packages on your system. We discuss here only the interface to the standard R functions like install.package. For the R functions see the standard R documentation.
At the moment the GUI provide direct access/download/installation of packages located on CRAN, the Bioconductor repository or a custom repository. You can also install packages from local files, either binary of source packages, as explained below. Otherwise you can use the appropriate R commands to install packages from a specific location other than the above mentioned ones.
You can choose to install packages from source if they are located on CRAN, on the BioConductor repository and on your local disk. Further you can either install packages from sources or use pre-built binary packages. Only packages that pass all tests are provided in the binary form.
Usually it is much faster and easier to install binary packages, because they are immeditely ready to use. On the other hand only packages that pass all tests are available in binary form. If your desired package is not available in binary form, you will need to use its source form. Source packages have to be compiled first before they can be used. If you want to install a source package, you will need the same working setup for building R itself (see see Building R from sources), including Apple Xcode Tools and a working FORTRAN compiler (if the package requires it).
If you decide to install packages you should use the Packages & Data menu of the GUI, in particular the sub-item Package Installer. Select the repository, package tyep (bionary or source) and press Get List. This will connect to the repository through the Internet and a list all packages available for installation. This is list tells you if a package is already installed on your system, the version of the package available on CRAN and the version of the same package if already installed.
You can use the search field to narrow the list of package to those matching your search criteria. Additionally you can use the search list menu to list only packages that are already installed on your system which is useful for comparing versions of available and installed packages.
Select any package you want to install and press the Install button. You can follow the progress of the instllation in the R Console. Once the required packages are installed, the list is re-loaded to reflect the versions of newly installed packages.
If you want to update all packages to the latest version, select the repository to use for the packages and press Update All. R will automatically determine the list of packages that can be updated and present you with a selection of packages to update.
You can also download any other package from the Internet yourself and decide to install it from source. In such case select one of the local entries in the top left list and press the Install button (which is now enabled).
Note that currently the Package Installer assumes that custom repositories maintain proper hierarchy for both source and binary packages the same way CRAN does. If your custom repository is flat, you will need to use install.packages
manually or update the repository format.
Starting with R 2.3.0 the same binary package can be used for both PowerPC and Intel based Macs. Such a package is called universal, because it works on either platform. Building universal packages requires special handling. First, R itself must be compiled as universal binary to support universal packages at all. The CRAN binary is built this way, see see How to build universal R for details.
Further, universal binaries can be currently built on Intel Macs only. The main reason is that the default Mac OS X installation on PowerPC based Macs does not include system libraries for Intel Macs (and R building process is unaware of Xcode SDKs). If you happen to have a PowerPC machine with full system libraries it should work. Finally, a compiler supporting both platforms is necessary, see see How to build universal R.
Once all tools are in place it is considerably easy to build an universal binary. Assuming that you have a source package called foo_1.0.tar.gz
, it can be installed universally using the following two-step process:
R_ARCH=/i386 R CMD INSTALL foo_1.0.tar.gz R_ARCH=/ppc R CMD INSTALL --libs-only foo_1.0.tar.gz
In the first step a full package for the Intel platform is built and installed. In the scond step a package for PowerPC platofrm is built, but only the relevant binary libraries are installed. This way both platforms share the same set of files except for the package library.
R CMD INSTALL --build
does not support universal binaries, because it is not aware of the other platfrom, therefore it is necessary to create the resulting tar-ball manually. This is how the process could be automated (replace first line with the real package name and version):
pkg=foo_1.0 rm -rf /tmp/pkg mkdir /tmp/pkg R_ARCH=/i386 R CMD INSTALL -l /tmp/pkg $pkg.tar.gz R_ARCH=/ppc R CMD INSTALL -l /tmp/pkg --libs-only $pkg.tar.gz tar fvcz $pkg.tgz -C /tmp/pkg `echo $pkg|awk -F_ '{print $1}'` rm -rf /tmp/pkg
As a general rule the answer is yes if the package does not contain any C/C++/Fortran code in the sources, otherwise the answer is negative. Another caution should be taken, that is, the package and the installed version of R should be the same major release, i.e. you can install a package built for R 1.8.0 on R 1.8.1, but usually not the same package on R 1.9.0.
A Mac OS X specific requirements, is that a prebuilt package is assumed to be named (and accordingly archived and compressed) as package_name.tgz. On Windows, for example, packages come in a zipped format.
The main library of packages is the one located inside the R.framework. This library contains the packages (base and
recommended ones) distributed along with R. Only administrators are allowed to install packages in this system-wide directory.
Optionally users can install private packages in their ~/Library/R/library
directory.
The Package Installer performs installation to either place depending on teh installation target setting. The default fro admin users is to install packages system-wide, whereas the default for regular users is their private place.
If you happen to use install.packages
R function instead of the Package Installer, the regular unix behavior applies (see help pages for details). For default setup this means that the packages are installed according to the startup preference setting. You can check the current defaults by issuing
.libPaths()
When upgrading to a next major release of R, users should delete their ~/Library/R/library
directory, because packages are incompatible across major R versions.
R has partial support for Apple-Scripts. At the moment R can be invoked and asked to run commands from an AppleScript script. What follows is an example of script that interacts with R. It firstly invokes R and then sends commands to R with the cmd applescript command.
set CommandLine to "R.Version()" try tell application "R" activate with timeout of 90000 seconds cmd CommandLine cmd "Sys.getenv()" cmd "print(\"HelloWorld!\")" end timeout end tell end try
In the above, cmd is the (only) applescript command in the R dictionary that is used to tell R to execute an R command in the R Console. The syntax is
cmd <command string>
where command string have to be in quotes. Actually, the output of the command is not sent back to the application that is calling R but to the R Console directly.
There are some issues. The first is that if R is still not running, it will take a while (depending on how fast your machine is) to startup. In the meanwhile the script sends commands without waiting and it could happen that some commands are missed by R, i.e. they arrive before R is ready to receive applescript commands. The second issue, is that it could be that the applescript calls a bad version of R. This could happen if you have an old version of R (for example the old Carbon R) installed on your System.
As an example, we report here a small script that asks R to source a file using a file dialog.
set file_to_source to (choose file with prompt "Choose file to source") as alias try tell application "R" activate with timeout of 90000 seconds cmd "source(\"" & file_to_source & "\")" end timeout end tell end try
R accepts the Apple Event command open. This means than an external editor can communicate with R sending portions of R code to execute via files. This is the approach used by the R-Tcl Mode in Alpha X (see http://www.kelehers.org/alpha/).
Dragging a file on the R icon, causes R to source this file via the source R command or, if the file is an R image data file RDX1 or RDX2 (normally files with extension .rda or .Rdata), the data is loaded in the workspace and every object with the same name in the workspace is overwritten without notice. Loading a data file is equivalent to the R command load. At the moment there is no control over the file types, i.e. dragging wrong files (i.e. files that are not R scripts or image data) simply gives an error. It's up to the user to do the right thing.
If R is not yet running this action causes R to startup.
The quartz device is the native graphic device in R for Mac OS X. It's name derives from Apple's Quartz Technology which is essentially similar to PDF rendering. One of the most amazing features of Quartz is antialiasing which gives you very nice plots and images. Try to compare a quartz plot with the same plot generated on any other interactive device. For its PDF nature it is also resolution independent.
The quartz device allows for interaction. You can use both identify and locator functions. To break the sequence you should press the <ESC> key on your keyboard as Apple's mouse have ever had only one button. If you happen to have a multi-button mouse, you can use any of the additional buttons to break the loop, unless you re-defined the function of the buttons.
You can can the content of the quartz device window into a PDF file. This is a very simple way to export high quality graphics from R into other applications on Mac OS X graphics is PDF based (so are almost all applications available). If you want bitmap copies of you quartz device window just use copy, to copy the image into the clipboard and paste the result in a graphic application (see Copying the image into the clipboard).
You can copy the content of the quartz device window in the clipboard to make the resulting image available for pasting into other applications. The clipboard will contain a bitmap copy of the quartz device window. If you want to work with high resolution images, you should save the content of the quartz device as a PDF file (see Saving the image). Pay attention to the following fact: the bitmap image produced has exactly the same dimensions of the quartz device window. This means that if you resize the window, the resulting image you obtain in the clipboard will have the same dimensions and you cannot resize the image from the inside another applications (say MS-Word) without loosing quality.
When rendering text and/or mathematical symbols the style is ignored, i.e. only plain style is drawn. The printing function is not yet implemented.
Each binary distribution of R available through CRAN is built to use the X11 implementation of TclTk. Of course a X windows server has to be started first. If you are not using the R.app you need to also define the environment variable DISPLAY before attempting to use X11 from inside R. You can do this as follows
Sys.putenv("DISPLAY"=":0")
If you don't like the X11 GUI you would probably want to build R using the Aqua version of TclTk (see Aqua TclTk headers and libraries (optional)). After installing the R.framework you should do the following to have the quartz device working under Aqua TclTk. Open a Terminal window and move inside the Resources/bin directory of the R.framework (usually /Library/Frameworks/R.framework), then type the following
sudo /Developer/Tools/Rez -t APPL Carbon.r -o R.bin
In R 2.1 both R and the R.app GUI introduced support for internationalization. Among other things this means that both messages and GUI elements can be translated into various languages. R.app automatically detects user's settings in the International section of the System Preferences and uses that information to offer translated messages and GUI if available. Please note that both Language and Formats information is used so they should be set up consistently.
Another change from previous versions (R 2.0 and R.app 1.01) is the support for UTF-8 character encoding. By default R.app uses UTF-8 for newly created documents and for the console. When opening new documents R.app assumes UTF-8 and only if the document violates UTF-8 rules, it will try to fallback to legacy encoding, usually Mac Roman.
If you are interested in translating R.app GUI into other languages, please read the developer documentation http://developer.r-project.org/Translations.html for details.
Here are few references that can be of interest for Mac OS X and/or developers.
The Apple Developer Connection (can be reached at http://developer.apple.com) is the main source of information for Apple products (OS, hardware, software) for developers. You can subscribe for free to ADC and get the latest up-to-date tools from Apple (compilers for example).
There is a page dedicated to the latest R-devel version of R. This page is located at http://www.economia.unimi.it/R and is maintained by Stefano M. Iacus. This page is intended to give additional documentation for building the latest R-devel version of R. From time to time, snapshots of R-devel binaries are available for testing purposes.
Special thanks go to Simon Urbanek, Jan de Leeuw, Byron Ellis and Thomas Lumley in random order. Last but not least Apple for amazing OS and GUI.
You can by writing a .Rprofile file in your favorite session directory and change accordingly the startup working directory using the Preferences (see The current and startup working directories).
In this case R will try to source this file or load the image data file (see Finder actions). If R is not yet running it will be launched.
In R.app you can use the the Stop toolbar button or the <ESC> (escape) key in the console window to interrupt a running calculation or output.
For the command line version the same is achieved by pressing <Ctrl>-c. Both applications honor the INT
signal, i.e. you can type the following in a separate Terminal window to cancel all R computations:
killall -INT R
The output is not produced continuously during the package installation. Unlike previous GUIs R.app does its best to display the output as soon as possible, but for example the documentation script does not print anything until done.
Also note that the development build of R.app sends output to the error console instead of the screen. You may want to check the Console application in that case.