Tools for MEG/EEG analysis.
Documentation: https://osl-ephys.readthedocs.io/en/latest/.
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.
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 .
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 .
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 .
Simply removing the conda environment and delete the repository:
conda env remove -n osle
rm -rf osl-ephys
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.