After version 0.3, Gala requires Python 3.5 to run. For a full list of dependencies, see the requirements.txt file.
- vigra/vigranumpy (1.9.0)
In its original incarnation, this project used Vigra for the random forest classifier. Installation is less simple than scikit-learn, which has emerged in the last few years as a truly excellent implementation and is now recommended. Tests in the test suite expect scikit-learn rather than Vigra. You can also use any of the scikit-learn classifiers, including their newly-excellent random forest.
Installing with distutils¶
Gala is a Python library with limited Cython extensions and can be installed in two ways:
- Use the command
python setup.py build_ext -iin the gala directory, then add the gala directory to your PYTHONPATH environment variable, or
- Install it into your preferred python environment with
python setup.py install.
Though you can install all the requirements yourself, as most are available in the Python Package Index (PyPI) and can be installed with simple commands, the easiest way to get up and running is to use [miniconda](http://conda.pydata.org/miniconda.html). Once you have the conda command, you can create a fully-functional gala environment with conda env create -f environment.yml (inside the gala directory).
Installing with Buildem¶
Alternatively, you can use Janelia’s own buildem system to automatically download, compile, test, and install requirements into a specified buildem prefix directory. (You will need CMake.)
$ cmake -D BUILDEM_DIR=/path/to/platform-specific/build/dir <gala directory> $ make
You might have to run the above steps twice if this is the first time you are using the buildem system.
On Mac, you might have to install compilers (such as gcc, g++, and gfortran).
The test coverage is rather tiny, but it is still a nice way to check you haven’t completely screwed up your installation. The tests do cover the fundamental functionality of agglomeration learning.
We use pytest for testing. Run the tests by building
gala in-place and running the
py.test command. (You need to have installed
pytest and pytest-cov for this to work. Both are readily available in PyPI.)
Alternatively, you can run individual test files independently:
$ cd tests $ python test_agglo.py $ python test_features.py $ python test_watershed.py $ python test_optimized.py $ python test_gala.py