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`stmeasures` — Measure similarity between trajectories
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`GitHub <https://github.com/TT2024-B106/stmeasures>`_
| `PyPI <https://pypi.org/project/stmeasures/>`_
| `Documentation <http://stmeasures.readthedocs.io/>`_

`stmeasures` is a Python library designed to help researchers, data scientists, and GIS professionals analyze and compare trajectories efficiently. It provides a variety of algorithms for measuring trajectory similarity, supporting applications in clustering, pattern discovery, and outlier detection.

Key Features
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- **Comprehensive Algorithms:** Includes Hausdorff, Frechet, DTW, LCSS, Euclidean, and SPAD distance measures.  
- **Flexible and Extensible:** Allows integration with larger workflows and customization for specific trajectory data.  
- **Research-Driven Design:** Developed to support GIS and movement analysis in academic and practical contexts.

Applications
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- Group trajectories with similar movement patterns.
- Identify anomalies or outliers in trajectory datasets.
- Match and compare paths for logistics, navigation, or ecological research.

Contents
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Below find the documented contents where you will find how to use this package and how to also extend it if needed.

.. toctree::

   api
   classes
   modules
