Note
The current latest and greatest version of AFNI is: 16.0.11
The direct links for downloading precompiled AFNI binaries, as well as the compilable source code, are provided here. Each download includes all SUMA and FATCAT tools, as well.
As of Jan. 1, 2016, AFNI utilizes a version numbering system, which is useful for tracking changes, getting help on the Message Board, reporting in published work, etc. The version is reported using a trio of numbers, corresponding to “major.minor.micro” (or roughly, “yearly.quarterly.oftenly”) updates. You can discover the mystery number on your own system by simply typing:
afni -ver
This version number should always be provided when posting questions on the Message Board.
Note
The record of changes (new options, new programs, bug fixes, et al.) is maintained for all the see in the online AFNI History.
Some additional introductory reading is available here.
If you have already have a working set of AFNI binaries on your computer that you are wishing to update, this can be done most simply by using the following script from the terminal command line:
@update.afni.binaries -d
This will automatically detect which binary version to download and where to install it (based on location of the present binaries), and then it will unpackage the new binaries so you can just keep rollin’ along. (It will also make an automatic backup of your existing binaries in a subdirectory called auto_backup.BINARY_VERSION/, just in case you want it.)
If you don’t have AFNI on your computer already, or if you just want to download particular a set of binaries, then you can click on a link below to get the code for your desired system. For help installing the various prerequisite tools on which AFNI depends (and for seeing handy command line tools to check if things are OK), please see the The Authoritative HowTo for Installing AFNI. After that set-up, then these precompiled codes should be ready-to-run.
Note
Those with only Windows systems have entered a world of pain, with respect to using AFNI. The best options are likely to procure a computer with a Unix/Linux/Mac operating system or to make a dual boot computer (for example, with Linux) rather than to install a virtual machine. It’s worth it, for a league game.
Recommended binaries for (most) Linux/Unix:
OpenMP, 64 bit | Ubuntu, Fedora (< 21), Red Hat, etc. |
Fedora21, 64 bit | Fedora 21+ |
Recommended binaries for (most) Mac OS: 10.7+.
Mac OS X (10.7 Intel), 64 bit | Mac 10.7 (Lion) and higher |
For Mac OS 10.11 (El Capitan) users, some additional modifications to your computer settings are required for smooth sailing. These are currently documented here.
Binaries for other systems: the rest.
Another way to get AFNI working on your computer (requiring a bit more work) is to compile from the source itself:
AFNI Source Code Compilable source (can be built on most Linux/Unix/Mac)
There are several usable, example Makefiles included in the main afni_src/ directory, as well as a couple (mainly for Linux systems) in afni_src/other_builds/.
In all likelihood this option is pretty much only useful if you are writing or contributing code yourself, or if your system is particularly finicky. Otherwise, it is likely far easier to grab a set of recommended precompiled binaries of the Linux/Unix or Mac variety (again, sorrry, Windowers...).
The following is a browsable page that contains a tarball for each of the precompiled platform versions:
It also contains several standard reference brains and demo data sets. All files are downloadable by clicking on the links on the above page, and also by using command line functions such as curl or wget, such as:
curl -O https://afni.nimh.nih.gov/pub/dist/tgz/TTatlas+tlrc.*
wget https://afni.nimh.nih.gov/pub/dist/tgz/TTatlas+tlrc.*
NB: for most demo sets, there is an @Install_* command to procure and open the directory.