The OHBA Software Library for the analysis of electrophysiological data (osl-ephys)

Tools for MEG/EEG analysis.

Documentation: https://osl-ephys.readthedocs.io/en/latest/.

Installation

See the official documentation for recommended installation instructions.

Alternatively, osl-ephys can be installed from source code within a Miniconda (or Anaconda) environment using the following.

Linux

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

Mac

git clone https://github.com/OHBA-analysis/osl-ephys.git
cd osl-ephys
conda env create -f envs/mac.yml
conda activate osle
pip install -e .

Oxford-specific computers

If you are installing on an OHBA workstation computer (HBAWS) use:

git clone https://github.com/OHBA-analysis/osl-ephys.git
cd osl-ephys
conda env create -f envs/hbaws.yml
conda activate osle
pip install -e .
pip install spyder==5.1.5

Or on the BMRC cluster:

git clone https://github.com/OHBA-analysis/osl-ephys.git
cd osl-ephys
conda env create -f envs/bmrc.yml
conda activate osle
pip install -e .

Removing OSL

Simply removing the conda environment and delete the repository:

conda env remove -n osle
rm -rf osl-ephys

For Developers

Run tests:

cd osl_ephys
pytest tests

or to run a specific test:

cd osl_ephys/tests
pytest test_file_handling.py

Build documentation (if build_sphinx is not recognised, first try pip install sphinx==5.3.0):

python setup.py build_sphinx

Compiled docs can be found in doc/build/html/index.html.