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).

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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: Streamline the preparation of survival targets and time-to-event data

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:

Resources

• Documentation: Full Documentation
• Source Code: GitHub Repository
• Issues & Support: Issue Tracker

Citation

If you use TanaT in your research, please cite:

@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 Inria Team.

The development has been supported by:

• 2024-2025: AIRacles Chair (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

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