pyknos 0.13.0

Conditional density estimation.

Description

Python package for conditional density estimation. It either wraps or implements diverse conditional density estimators.

Density estimation with normalizing flows

This package provides pass-through access to all the functionalities of nflows.

Setup

Clone the repo and install all the dependencies using the environment.yml file to create a conda environment: conda env create -f environment.yml. If you already have a pyknos environment and want to refresh dependencies, just run conda env update -f environment.yml --prune.

Alternatively, you can install via setup.py using pip install -e ".[dev]" (the dev flag installs development and testing dependencies).

Examples

Examples are collected in notebooks in examples/.

Binary files and Jupyter notebooks

Using

We use git lfs to store large binary files. Those files are not downloaded by cloning the repository, but you have to pull them separately. To do so follow installation instructions here https://git-lfs.github.com/. In particular, in a freshly cloned repository on a new machine, you will need to run both git-lfs install and git-lfs pull.

Contributing

We use a filename filter to identify large binary files. Once you installed and pulled git lfs you can add a file to git lfs by appending _gitlfs to the basename, e.g., oldbase_gitlfs.npy. Then add the file to the index, commit, and it will be tracked by git lfs.

Additionally, to avoid large diffs due to Jupyter notebook outputs we are using nbstripout to remove output from notebooks before every commit. The nbstripout package is downloaded automatically during installation of pyknos. However, please make sure to set up the filter yourself, e.g., through nbstriout --install or with different options as described here.

Name

pyknós (πυκνός) is the transliterated Greek root for density (pyknótita) and also means sagacious.

Copyright notice

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see https://www.gnu.org/licenses/.

Acknowledgements

Thanks to Artur Bekasov, Conor Durkan and George Papamarkarios for their work on nflows.

The MDN implementation in this package is by Conor M. Durkan.