Metadata-Version: 2.1
Name: hmmkay
Version: 0.0a0
Summary: Discrete Hidden Markov Models with Numba
Home-page: https://github.com/NicolasHug/hmmkay/
Author: Nicolas Hug
Author-email: contact@nicolas-hug.com
License: MIT
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: numba

# Hmmkay

Discrete Hidden Markov Models with Numba

## Installation

    pip install hmmkay

## Documentation

TODO

## Status

Highly experimental, API subjet to change without deprecation.

## Development

The following packages are required for testing:

    pip install pytest hmmlearn

For benchmarks:

    pip install matplotlib hmmlearn

For docs:

    pip install sphinx sphinx_rtd_theme


For development, use [pre-commit
hooks](https://ljvmiranda921.github.io/notebook/2018/06/21/precommits-using-black-and-flake8/)
for black and flake8.

## Deploy

(In a clean env?)

    pip install twine
    python 

