Metadata-Version: 2.4
Name: bader-chainsaddiction
Version: 0.2.5
Summary: HMM with Poisson-distributed latent variables.
Author-email: Michael Blaß <mblass@posteo.net>
License: Copyright 2019 Michael Blaß michael.blass@uni-hamburg.de
        
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Project-URL: Repository, https://codeberg.org/rbader/chainsaddiction
Project-URL: Documentation, https://codeberg.org/rbader/chainsaddiction
Keywords: hmm,poisson,hidden-markov model
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Dynamic: license-file

# ChainsAddiction

ChainsAddiction is an easy to use tool for time series analysis using
discrete-time Hidden Markov Models. It is written in `C` as a `numpy`-based
Python extension module.

This is the fork maintained by **Rolf Bader** (canonical repository on
[Codeberg](https://codeberg.org/rbader/chainsaddiction)). It is part of the
apollon / chainsaddiction / comsar stack; see the
[comsar repository](https://codeberg.org/rbader/comsar) for the full manual.


## Installation
### Install from PyPI (recommended, no compiler needed)

Pre-compiled wheels are provided for **Windows, macOS and Linux**
(CPython 3.9–3.13):

    python3 -m pip install bader-chainsaddiction

The import name is unchanged — you still write `import chainsaddiction`.


### Install from source

Building from source requires

- Python >= 3.9
- pip, setuptools, NumPy
- a C compiler (MSVC Build Tools on Windows, Xcode Command Line Tools on macOS,
  gcc/clang on Linux)

Then:

    git clone https://codeberg.org/rbader/chainsaddiction path/to/ca
    cd path/to/ca
    python3 -m pip install .

---

## Notes
Currently only Poisson-distributed HMM are implemented.
