As of September 7th 2022, further development will happen in the repo found at:
WIP refactor of lbhb/NEMS and lbhb/nems_db
- Download source code.
clone <nems-lite> # using url, ssh, or however you normally clone
2a. (pip)
pip install -r nems-lite/requirements.txt
pip install -e nems-lite
2b. (conda)
conda env create -f nems-lite/environment.yml
pip install -e nems-lite
Note: mkl library for numpy does not play well with tensorflow.
If using conda to install dependencies manually, use conda-forge
for numpy (which uses openblas instead of mkl):
conda install -c conda-forge numpy
(conda-forge/numpy-feedstock#84)
Coming soon, roughly in order of priority:
- Add more Layers from nems0.
- Add core pre-processing and scoring from nems0.
- Set up readthedocs.
- Convert scripts and dev_notebooks to tutorials where appropriate.
- Try Numba for Layer.evaluate and cost functions.
- Other core features (like jackknifed fits, cross-validation, etc.).
- Migrate to LBHB/NEMS.
- Enable Travis build (.travis.yml is already there, but not yet tested).
- Publish through conda install and pip install (and update readme accordingly).
- Backwards-compatibility tools for loading nems0 models.
- Implement Jax back-end. ... (other things on the massive issues list)