chainsaddiction 0.2.4

HMM with Poisson-distributed latent variables.

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.

Installation

Prerequisites

The installation of ChainsAddiction requires to following tools to be installed on your system:

• Python >= 3.9
• pip, setuptools
• C compiler

Install from PyPi

You can install chainsaddiction from PyPi with:

python3 -m pip install chainsaddiction

Please note that ChainsAddiction is a CPython extension module. You have to have set up a C compiler in order to install. Currently we provide wheels for macOS. So, if you are using this OS you do not need a compiler.

Install from source

First, clone the source code by typing the following command in your terminal app. Replace path/to/ca with the path to where ChainsAddiction should be cloned:

git clone https://github.com/teagum/chainsaddiction path/to/ca

Second, change to the root directory of your freshly cloned code repository:

cd path/to/ca

Third, instruct Python to build and install ChainsAddiction:

python3 -m pip install .

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Notes

Currently only Poisson-distributed HMM are implemented.