See the read the docs page for a description of this project: https://osl-dynamics.readthedocs.io.

If you find this toolbox useful, please cite:

Chetan Gohil, Rukuang Huang, Evan Roberts, Mats WJ van Es, Andrew J Quinn, Diego Vidaurre, Mark W Woolrich (2024) osl-dynamics, a toolbox for modeling fast dynamic brain activity eLife 12:RP91949.

We recommend installing osl-dynamics within a virtual environment. You can do this with Anaconda (or miniconda).

Below we describe how to install osl-dynamics from source. We recommend using the conda environment files in /envs.

git clone https://github.com/OHBA-analysis/osl-dynamics.git
cd osl-dynamics
conda env create -f envs/linux.yml
conda activate osld
pip install -e .

For a Mac, the installation of TensorFlow is slightly different to a Linux computer. We recommend using the lines above replacing the Linux environment file envs/linux.yml with the Mac environment file envs/mac.yml.

If you are using a Windows computer, we recommend first installing Linux (Ubuntu) as a Windows Subsystem by following the instructions here. Then following the instructions above in the Ubuntu terminal.

If you have already installed OSL you can install osl-dynamics in the osl environment with:

conda activate osl
cd osl-dynamics
pip install tensorflow==2.11.0
pip install tensorflow-probability==0.19.0
pip install -e .

Note, if you're using a Mac computer you need to install TensorFlow with pip install tensorflow-macos==2.11.0 instead of tensorflow==2.11.0.

Simply delete the conda environment and repository:

conda env remove -n osld
rm -rf osl-dynamics

The read the docs page should be automatically updated whenever there's a new commit on the main branch.

The documentation is included as docstrings in the source code. Please write docstrings to any classes or functions you add following the numpy style. The API reference documentation will only be automatically generated if the docstrings are written correctly. The documentation directory /doc also contains .rst files that provide additional info regarding installation, development, the models, etc.

To compile the documentation locally you need to install the required packages (sphinx, etc.) in your conda environment:

cd osl-dynamics
pip install -r doc/requirements.txt

To compile the documentation locally use:

python setup.py build_sphinx

The local build of the documentation webpage can be found in build/sphinx/html/index.html.

A couple packages are needed to build and upload a project to PyPI, these can be installed in your conda environment with:

pip install build twine

The following steps can be used to release a new version:

1. Update the version on line 5 of setup.cfg by removing dev from the version number.
2. Commit the updated setup.cfg to the main branch of the GitHub repo.
3. Delete any old distributions that have been built (if there are any): rm -r dist.
4. Build a distribution in the osl-dynamics root directory with python -m build. This will create a new directory called dist.
5. Test the build by installing in a test conda environment with cd dist; pip install <build>.whl.
6. Upload the distribution to PyPI with twine upload dist/*. You will need to enter the username and password that you used to register with https://pypi.org.
7. Tag the commit uploaded to PyPI with the version number using the 'Create a new release' link on the right of the GitHub repo webpage.
8. Change the version to X.Y.devZ in setup.cfg and commit the new dev version to main.

The uploaded distribution will then be available to be installed with:

pip install osl-dynamics

See here for useful info regarding how to use the BMRC cluster and how to edit the source code.