Metadata-Version: 2.4
Name: TanaT
Version: 0.9.0
Summary: A library for temporal analysis of trajectories.
Project-URL: Homepage, https://gitlab.inria.fr/tanat/core/tanat
Project-URL: Source, https://gitlab.inria.fr/tanat/core/tanat.git
Project-URL: Documentation, https://tanat.gitlabpages.inria.fr/tanat
Project-URL: Issues, https://gitlab.inria.fr/tanat/core/tanat/-/issues
Author-email: Arnaud Duvermy <arnaud.duvermy@inria.fr>, Thomas Guyet <thomas.guyet@inria.fr>
License: MIT License
        
        Copyright (c) 2022, Inria
        
        Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
License-File: LICENSE.txt
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Requires-Dist: matplotlib
Requires-Dist: numba
Requires-Dist: pandas
Requires-Dist: pypassist
Requires-Dist: pyyaml
Requires-Dist: scikit-learn
Requires-Dist: scikit-survival
Requires-Dist: sqlalchemy
Requires-Dist: tanat-cli-preset
Requires-Dist: tqdm
Requires-Dist: tseqmock
Provides-Extra: runner
Requires-Dist: dagster; extra == 'runner'
Requires-Dist: hydra-core; extra == 'runner'
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'
Requires-Dist: pytest-cov; extra == 'test'
Requires-Dist: syrupy; extra == 'test'
Description-Content-Type: text/markdown

# TanaT
**Temporal Analysis of Trajectories** 

*TanaT* is a powerful Python library designed for advanced temporal sequence analysis, with specialized focus on patient care pathways and complex temporal data structures (trajectories).

## Stay Updated

[Subscribe](https://sympa.inria.fr/sympa/subscribe/tanat-community) to our newsletter to get updates, release notes, and example notebooks straight to your inbox!


## What Makes TanaT Different

TanaT bridges the gap between traditional time series analysis and complex temporal sequence modeling by offering:

- **Expressive Data Representation**: Handle event sequences, interval sequences, and state sequences with unified APIs
- **Advanced Distance Metrics**: Specialized metrics for temporal data including DTW, edit distance, and custom metrics
- **Flexible Clustering**: State-of-the-art clustering algorithms adapted for temporal sequences and trajectories
- **Extensible Architecture**: Modular design allowing easy integration of new methods and metrics

## Core Capabilities

### Data Structures
- **Event Sequences**: Point-in-time events with rich feature descriptions
- **Interval Sequences**: Time-spanning events with overlapping support
- **State Sequences**: Continuous state representations with temporal transitions
- **Trajectories**: Multi-dimensional temporal data combining multiple sequence types

### Analysis Methods
- **Distance Computation**: Dynamic Time Warping, Edit Distance, Longest Common Subsequence, and more
- **Clustering**: Specialized algorithms for grouping similar temporal patterns
- **Filtering & Selection**: Advanced criteria-based data selection and manipulation
- **Visualization**: Comprehensive tools for temporal data exploration
- **Survival analysis**: Model and predict time until key events

## Scientific Foundation

TanaT draws inspiration from established frameworks:

- **TraMineR** (R): State sequence analysis methodologies
- **aeon** & **tslearn**: Time series analysis best practices

## Architecture Overview

TanaT provides a comprehensive suite of interconnected modules for end-to-end temporal sequence analysis:


| Feature | Description |
|---------|-------------|
| **Simulation** | Generate synthetic data for statistical power analysis and algorithm benchmarking |
| **Visualization** | Explore and interpret temporal sequences through rich visual representations |
| **Data Wrangling** | Manipulate, filter, and transform temporal data with flexible operations |
| **Survival Analysis** | Integrate time-to-event modeling and survival techniques |
| **Metrics & Clustering** | Apply specialized distance metrics and clustering algorithms for temporal data |
| **Workflow Orchestration** | Build reproducible, automated analysis pipelines |

## Resources

- **Documentation**: [Full Documentation](https://tanat.gitlabpages.inria.fr/core/tanat/)
- **Source Code**: [GitLab Repository](https://gitlab.inria.fr/tanat/core/tanat.git)
- **Issues & Support**: [Issue Tracker](https://gitlab.inria.fr/tanat/core/tanat/-/issues)

## Citation

If you use TanaT in your research, please cite:

```bibtex
@inproceedings{tanat2025,
title={Towards a Library for the Analysis of Temporal Sequences},
authors={Thomas Guyet and Arnaud Duvermy},
booktitle={Proceedings of AALTD, ECML Workshop on Advanced Analytics and Learning on Temporal Data},
year={2025},
pages={16}
}
```

## Affiliation & Support

TanaT is actively developed within the [AIstroSight](https://team.inria.fr/aistrosight/) Inria Team.

The development has been supported by:

* **2024-2025**: [AIRacles Chair](https://www.bernoulli-lab.fr/project/chaire-ai-racles/) (Inria/APHP/CS)
* **2025-present**: PEPR/SafePaw project (Government funding managed by the French National Research Agency under France 2030, reference number ANR-22-PESN-0005)

## Team

**Core Development Team**
- **Arnaud Duvermy** - Architecture & Core Development
- **Thomas Guyet** - Project Leadership & Research Methods

**Contact**: [TanaT](mailto:tanat@inria.fr)

This work benefits from the advice of Mike Rye.

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*TanaT is open source software designed to advance temporal sequence analysis in research and industry applications.*