Recommended: Install from source¶
NEMS is still under rapid development, so this is the best way to ensure you’re using the most up-to-date version.
1. Download source code
git clone https://github.com/lbhb/nems
2a. Create and activate a new virtual environment using your preferred
environment manager (example for venv below).
python -m venv ./nems-env
./nems-env/scripts/activate
2b. Install frozen dependencies. This will install the exact versions used during development.
pip install -r .\NEMS\requirements.txt
2c. Alternatively, use conda to replace both step 2a and step 2b.
conda env create -f NEMS/environment.yml
conda activate nems-env
3. Install NEMS in editable mode along with optional development tools.
pip install -e NEMS[dev]
4. Run tests to ensure proper installation. We recommend repeating this step after making changes to the source code.
pytest NEMS
Install with pip¶
Create a new environment using your preferred environment manager, then use
pip install.
conda create -n nems-env python=3.9 pip # note that python=3.9 is currently required
pip install PyNEMS # note the leading Py
Install with conda¶
Coming soon.
Note: the mkl library for numpy does not play well with
tensorflow. If using conda to install dependencies manually,
and you want to use the tensorflow backend, use conda-forge for
numpy (which uses openblas instead of mkl):
conda install -c conda-forge numpy
(See: <https://github.com/conda-forge/numpy-feedstock/issues/84>)