Installation

OSX and Linux

The recommended was to use pygauss is to download the Anaconda Scientific Python Distribution (64-bit). Once downloaded a new environment can be created in terminal and pygauss installed:

conda create -n pg_env python=2.7
conda install -c https://conda.binstar.org/cjs14 -n pg_env pygauss

Windows

There is currently no pygauss Conda distributable for Windows or for chemlab, which has C-extensions that need to be built using a compiler. Therefore chemlab will need to be cloned from GitHub, its extensions built, dependancies installed and finally install pygauss.

conda create -n pg_env python=2.7
conda install -n pg_env -c https://conda.binstar.org/cjs14 cclib
conda install -n pg_env -c https://conda.binstar.org/cjs14 chemview
conda install -n pg_env -c https://conda.binstar.org/cjs14 pyopengl
git clone --recursive https://github.com/chemlab/chemlab.git
cd chemlab
python setup.py build_ext --inplace
conda install -n pg_env <pil, pandas, matplotlib, scikit-learn, ...>
activate pg_env
pip install . # or add to PYTHONPATH
pip install pygauss

Troubleshooting

If you encounter difficulties it may be useful to look in working_conda_environments at conda environments known to work.

Testing

Pygauss utilises a unit test suite (nose/nose-parameterized) to ensure that computations run, and are correct. These tests are an automated condition of the conda build, but can also be run manually in the command line;

nosetests

or directly in python;

pygauss.run_nose(verbose=True)