Metadata-Version: 2.4
Name: HySOM
Version: 0.1.1
Summary: Fast, lightweight library for training Self-Organizing Maps on 2D time series, tailored for analyzing concentration-discharge hysteresis loops.
Author-email: Arlex Marin Ramirez <arlexmarinr@gmail.com>
Project-URL: Repository, https://github.com/ArlexMR/HySOM
Keywords: Self-Organizing Maps,SOM,unsupervised learning,clustering,Hydrology,Water Quality,Discharge-Concentration,Hysteresis,time series
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Hydrology
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.26
Requires-Dist: matplotlib>=3.9
Requires-Dist: tslearn>=0.6.3
Dynamic: license-file

# HySOM

**Fast, lightweight Python library for training Self-Organizing Maps on 2D time series, tailored for analyzing concentration-discharge hysteresis loops.**


## 🚀 Overview

**HySOM** is a Python library that simplifies the training and visualization of Self-Organizing Maps (SOMs) for 2D time series. It is specifically designed for the study of concentration–discharge (C–Q) hysteresis loops. With **HySOM**, you can access the **General T-Q SOM**—a standard framework for classifying sediment transport hysteresis loops (details on its development can be found [here](www.mypaper.com)). The library also includes several visualization tools to streamline the analysis of sediment transport hysteresis loops. Additionally, **HySOM** allows you to train your own SOM for C–Q analysis.

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## 🔍 Features

- Direct access to the **General T-Q SOM** for sediment transport hysteresis loop analysis
- Tools for analyzing and classifying C-Q **hysteresis loops**
- **Visualization** utilities for SOM grids and hysteresis loops
- Easy, yet flexible, training of rectangular **Self-Organizing Maps** for 2D sequences
- Supports the **Dynamic Time Warping** distance function 
- Lightweight and dependency-minimized

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# 🌊 The General T-Q SOM
Includes the General T–Q SOM, a standard framework for analyzing sediment transport hysteresis loops. Usage examples can be found in the [Documentation](www.documentation.com)

<p align="center">
  <img src="https://raw.githubusercontent.com/ArlexMR/HySOM/refs/heads/main/docs/images/generalTQsom.png" alt="General T-Q SOM" width="400">
</p>

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# 📖 [Documentation](www.documentation.com)
Comprehensive docuemnattion is provided, inclusing quickstart tutorials, How-to guides and an API reference. [Click Here!](www.documentation.com)

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## 📦 Dependencies
HySOM requires the following libraries for proper functioning:  
- numpy
- tslearn
- matplotlib

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### 🤝 Contributing
We welcome contributions! If you'd like to include your own standard SOM for C-Q hysteresis analysis, improve the code, report issues, or request features, please open a GitHub issue or pull request.


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