This toolkit depends on a number of external tools which must be
installed before you install MAT. For the Mac version, they are:
To prepare MacOS for installation of this toolkit, first ensure
that you've installed the proper version of Java (if you want to
use jCarafe). Then you should unzip the distribution (you must
have already done that to read this). Assume <toolkit_dir>
is the root directory of the distribution. For Python 2:
% cd <toolkit_dir>
% ./install.sh
or, if you don't want to use the executable named python
in your path:
% cd <toolkit_dir>
% /<path>/<to>/python ./install.py
For Python 3:
% cd <toolkit_dir>
% ./install3.sh
or, if you don't want to use the executable named python3
in your path:
% cd <toolkit_dir>
% /<path>/<to>/python3 ./install.py
During the installation, you might be prompted for various paths
and locations which the toolkit requires.
When the installation is complete, your runtime environment will be
configured for you. If you want to do something fancy during your
installation (e.g., use your own settings file, or store the task
plugin record outside your installation), see install.py.
As of MAT 3.3, the core of MAT can also be distributed as a pip-compatible Python library. This library contains the core MAT APIs, but lacks the Web server, the jCarafe engine, the documentation, and the command-line tools. Its sole dependency, a library implementing the Kuhn-Munkres bipartite set alignment algorithm, is installed as a dependency when the pip module is installed (and is only needed for the pairer/scorer).
While it is possible to override MAT's runtime environment using
environment variables, it's not recommended. So you may have to do
something special if you want to change your installation in any
way.