https://github.com/neuroinformatics-unit/movement

A Python toolbox for analysing animal body movements across space and time
https://github.com/neuroinformatics-unit/movement

animal behavior behaviour ethology kinematics motion-tracking neuroscience

Last synced: 3 months ago
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A Python toolbox for analysing animal body movements across space and time

• Host: GitHub
• URL: https://github.com/neuroinformatics-unit/movement
• Owner: neuroinformatics-unit
• License: bsd-3-clause
• Created: 2020-04-02T17:14:58.000Z (almost 6 years ago)
• Default Branch: main
• Last Pushed: 2025-12-12T19:13:33.000Z (3 months ago)
• Last Synced: 2025-12-12T23:56:23.868Z (3 months ago)
• Topics: animal, behavior, behaviour, ethology, kinematics, motion-tracking, neuroscience
• Language: Python
• Homepage: http://movement.neuroinformatics.dev
• Size: 34.9 MB
• Stars: 212
• Watchers: 7
• Forks: 76
• Open Issues: 139
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.CFF

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# movement

A Python toolbox for analysing animal body movements across space and time.

![](docs/source/_static/movement_overview.png)

## Quick install

Create and activate a conda environment with movement installed (including the GUI):

```bash

conda create -n movement-env -c conda-forge movement napari pyqt

conda activate movement-env

```

> [!Note]

> Read the [documentation](https://movement.neuroinformatics.dev/latest) for more information, including [full installation instructions](https://movement.neuroinformatics.dev/latest/user_guide/installation.html) and [examples](https://movement.neuroinformatics.dev/latest/examples/index.html).

## Overview

Deep learning methods for motion tracking have revolutionised a range of

scientific disciplines, from neuroscience and biomechanics, to conservation

and ethology. Tools such as

[DeepLabCut](https://www.mackenziemathislab.org/deeplabcut) and

[SLEAP](https://sleap.ai/) now allow researchers to track animal movements

in videos with remarkable accuracy, without requiring physical markers.

However, there is still a need for standardised, easy-to-use methods

to process the tracks generated by these tools.

`movement` aims to provide a consistent, modular interface for analysing

motion tracks, enabling steps such as data cleaning, visualisation,

and motion quantification. We aim to support all popular animal tracking

frameworks and file formats.

Find out more on our [mission and scope](https://movement.neuroinformatics.dev/latest/community/mission-scope.html) statement and our [roadmap](https://movement.neuroinformatics.dev/latest/community/roadmaps.html).

> [!Tip]

> If you prefer analysing your data in R, we recommend checking out the

> [animovement](https://animovement.dev/) toolbox, which is similar in scope.

> We are working together with its developer

> to gradually converge on common data standards and workflows.

## Join the movement

`movement` is made possible by the generous contributions of many [people](https://movement.neuroinformatics.dev/latest/community/people.html).

We welcome and encourage contributions in any form—whether it is fixing a bug, developing a new feature, or improving the documentation—as long as you follow our [code of conduct](CODE_OF_CONDUCT.md).

Go to our [community page](https://movement.neuroinformatics.dev/latest/community/index.html) to find out how to connect with us and get involved.

## Citation

If you use movement in your work, please cite the following Zenodo DOI:

> Nikoloz Sirmpilatze, Chang Huan Lo, Sofía Miñano, Brandon D. Peri, Dhruv Sharma, Laura Porta, Iván Varela & Adam L. Tyson (2024). neuroinformatics-unit/movement. Zenodo. https://zenodo.org/doi/10.5281/zenodo.12755724

## License

⚖️ [BSD 3-Clause](./LICENSE)

## Package template

This package layout and configuration (including pre-commit hooks and GitHub actions) have been copied from the [python-cookiecutter](https://github.com/neuroinformatics-unit/python-cookiecutter) template.