# TanaT: A library for the analysis of temporal sequences

Thomas Guyet, Arnaud Duvermy

► To cite this version:

Thomas Guyet, Arnaud Duvermy. TanaT: A library for the analysis of temporal sequences. PEPR-SanteNum 2025 - Journées Annuelles du PEPR Santé Numérique, Oct 2025, Lille, France, Oct 2025, Lille, France. *hal-05351453*

HAL Id: hal-05351453

https://inria.hal.science/hal-05351453v1

Submitted on 6 Nov 2025

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Distributed under a Creative Commons Attribution 4.0 International License
# TANAT: A LIBRARY FOR THE ANALYSIS OF TEMPORAL SEQUENCES

## THOMAS GUYET AND ARNAUD DUVERMY, INRIA AISTROSIGHT

TanaT is an open-source Python framework for temporal sequence analysis. It handles data made of timestamped observations described by qualitative and quantitative features. Such longitudinal data arise in many fields (medicine, social sciences, education, activity traces, ...) and require dedicated methods. TanaT aims to empower data analysts with a coherent toolbox for handling temporal sequences at all stages of the analysis process: data loading, data pre-processing and transformation, data analysis and data visualization.

## DATA MODEL: ENTITIES, SEQUENCES AND TRAJECTORIES

TanaT provides a unified model to represent complex temporal data.

- **Entities**: the atomic objects (events, intervals, state).

- **Sequences**: collections of entities with shared features.

- **Trajectories**: groups of sequences with additional static attributes.

Flexible time representation (datetime or numeric)

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## CORE FRAMEWORK FUNCTIONALITIES

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Compose a trajectory metric by combining entity, sequence and trajectory metrics (including time-warping support).

Sksurv modules trainable in just a few lines.

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**TANAT**
TEMPORAL ANALYSIS OF TRAJECTORIES

https://gitlab.inria.fr/tanat/core/tanat

This work has been partly funded by Chaire AIRacles (Inria/APHP) this work also received government funding managed by the French National Research Agency under France 2030, reference number ANR-22-PESN-0005.

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