Metadata-Version: 2.4
Name: hidten
Version: 0.0.1
Summary: A framework for combining hidden Markovian models with modern deep learning.
Project-URL: Homepage, https://github.com/gaius-augustus/hidten
Project-URL: Issues, https://github.com/gaius-augustus/hidten/issues
Author-email: Felix Becker <beckerfelix94@gmail.com>, Richard Krieg <irkri@irkri.net>
License-Expression: MIT
License-File: LICENSE
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.10
Requires-Dist: numpy
Requires-Dist: pydantic
Provides-Extra: docs
Requires-Dist: myst-parser>=2.0; extra == 'docs'
Requires-Dist: sphinx-rtd-theme>=1.3; extra == 'docs'
Requires-Dist: sphinx>=7.0; extra == 'docs'
Provides-Extra: plots
Requires-Dist: logomaker; extra == 'plots'
Requires-Dist: matplotlib; extra == 'plots'
Requires-Dist: networkx; extra == 'plots'
Requires-Dist: pandas; extra == 'plots'
Requires-Dist: scipy; extra == 'plots'
Provides-Extra: tensorflow
Requires-Dist: tensorflow[and-cuda]<=2.21,>=2.17; extra == 'tensorflow'
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'
Requires-Dist: scipy; extra == 'test'
Description-Content-Type: text/markdown

# hidten
A framework that integrates hidden Markov and related models with modern deep learning—revealing hid(den) structure within your ten(sors).

Find the documentation [here](https://gaius-augustus.github.io/hidten-docs/) to get started.

- Provides intuitive classes to easily define latent state graphs and combine emission distributions for both discrete and continuous input tracks. 🧩
- Implements core Hidden Markov Model (HMM) algorithms for training and inference, including Forward–Backward and Viterbi. ⚡
- Enables gradient-based, highly parallel training as well as efficient parallel inference. 🔄
- Pythonic, clean, extensible, and thoroughly tested. ✅

## Installation


`python -m pip install hidten[tensorflow]`


## Installation for developers

`git clone https://github.com/Gaius-Augustus/hidten`
`pip install -e .[tensorflow,plots,test,doc]`

Build the docs:

`cd docs && make html`

## License

This project is licensed under the [MIT license](/LICENSE).

## Tools using hidten

- [Tiberius: End-to-End Deep Learning with an HMM for Gene
   Prediction](https://github.com/Gaius-Augustus/Tiberius)
- [learnMSA: deep protein multiple alignments with large language and hidden Markov models](https://github.com/Gaius-Augustus/learnMSA)
- [bricks2marble: Pre- and postprocessing tools for genome annotation](https://github.com/Gaius-Augustus/bricks2marble)
