semvec/pypi-packages huggingface dataset:
comliner 0.4.1
Command Line Interface Wrapper for Python Functions. Wrap your Python functions with a simple command line interface, so that they can be run directly from the command line, just like any shell command.  This is achieved by simply adding a decorator in front of the function and creating a small standardized executible script.
Requires Python: >=3.7

comliner - Command Line Interface Wrapper for Python Functions
==============================================================

Make programs out of your Python functions that can be run from the command
line by simply adding a decorator in front of the function. The programs will
have a commandline interface based on the optparse module, and load data from
and save data to files (HDF5 format).



Copyright notice
----------------

Copyright (C) 2013-2023 Daniel Jung.
Contact: proggy-contact@mailbox.org

This program is free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the Free
Software Foundation; either version 2 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 General Public License for
more details.

You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
ocpdet 0.0.6
A Python package for online changepoint detection, implementing state-of-the-art algorithms and a novel approach.
Requires Python: >=3.6

# [ocpdet](https://pypi.org/project/ocpdet/)
OCPDet is an open-source Python package for online changepoint detection, implementing state-of-the-art algorithms and a novel approach, using a `scikit-learn` style API.

[![PyPI](https://img.shields.io/pypi/v/ocpdet?color=g)](https://img.shields.io/pypi/v/ocpdet?color=g)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7632721.svg)](https://doi.org/10.5281/zenodo.7632721)

This package is the outcome of my Master Thesis at Imperial College London within the MSc in Statistics, Department of Mathematics.

Algorithms implemented in ocpdet are

- **CUSUM**: Cumulative Sum algorithm, proposed by Page (1954)
- **EWMA**: Exponentially Weighted Moving Average algorithm, proposed by Roberts (1959)
- **Two Sample tests**: Nonparametric hypothesis testing for changepoint detection, proposed by Ross et al. (2011)
- **Neural Networks**: Novel approach based on sequentially learning neural networks, proposed by Hushchyn et al. (2020) and extended to online context (Master Thesis) 

## Installation

```bash
pip install ocpdet
``` 

## Examples

- [CUSUM.ipynb](https://github.com/vkhamesi/ocpdet/blob/main/docs/CUSUM.ipynb)  
- [EWMA.ipynb](https://github.com/vkhamesi/ocpdet/blob/main/docs/EWMA.ipynb)  
- [TwoSample.ipynb](https://github.com/vkhamesi/ocpdet/blob/main/docs/TwoSample.ipynb)  
- [NeuralNetwork.ipynb](https://github.com/vkhamesi/ocpdet/blob/main/docs/NeuralNetwork.ipynb)  

## How to cite this work

Here is a suggestion to cite this GitHub repository:

> Victor Khamesi. (2022). ocpdet: A Python package for online changepoint detection in univariate and multivariate data. (Version v0.0.5). Zenodo. https://doi.org/10.5281/zenodo.7632721

And a possible BibTeX entry:

```tex
@software{victor_khamesi_2022,
  author       = {Victor Khamesi},
  title        = {ocpdet: A Python package for online changepoint detection in univariate and multivariate data.},
  month        = oct,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {v0.0.5},
  doi          = {10.5281/zenodo.7632721},
  url          = {https://doi.org/10.5281/zenodo.7632721}
}
```

## License

The non-software content of this project is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/), and the software code is licensed under the [BSD-2 Clause license](https://opensource.org/licenses/BSD-2-Clause).