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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.18553832 |
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| _version_ | 1866901577562849280 |
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| author | ArlexMR |
| author_facet | ArlexMR |
| contents | <p><strong>See the most up-to-date version of this library in the <a href="https://github.com/ArlexMR/HySOM" target="_blank" rel="noopener">GitHub repository</a></strong></p> <p>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. 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.</p> <p> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18553832 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | HySOM: A Python library for Self-Organizing Map–based analysis of concentration–discharge hysteresis ArlexMR <p><strong>See the most up-to-date version of this library in the <a href="https://github.com/ArlexMR/HySOM" target="_blank" rel="noopener">GitHub repository</a></strong></p> <p>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. 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.</p> <p> </p> |
| title | HySOM: A Python library for Self-Organizing Map–based analysis of concentration–discharge hysteresis |
| url | https://doi.org/10.5281/zenodo.18553832 |