Aller au contenu principal
Accès ouvert déclaré 2026 software

neuroinformatics-unit/movement: v0.16.0

0Citations signalées, ce qui n’est pas une note de qualité
8Institutions déclarées
4Pays d’affiliation déclarés

Rattachement africain : gb, us, ru, it. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

To update movement to the latest version, see the update guide. What's Changed ⚡️ Highlight 1: draw, save, and load Regions of Interest in the GUI Widget for drawing Regions of Interest (ROIs) as napari Shapes by @niksirbi in https://github.com/neuroinformatics-unit/movement/pull/617 Add conversion between napari Shapes and movement RoIs by @niksirbi in https://github.com/neuroinformatics-unit/movement/pull/927 You can now define Regions of Interest (RoIs) interactively in the movement napari GUI, export them to a GeoJSON file, and load them back into Python for analysis — all without writing any coordinates by hand. https://github.com/user-attachments/assets/2231a49c-ec13-4d31-9310-d486de663185 The Define regions of interest menu lets you draw shapes directly on the video frames, name them, and save them via the Save layer button. The saved .geojson file can then be loaded with movement.roi.load_rois(): from movement.roi import load_rois rois = load_rois("my_regions.geojson") [roi.name for roi in rois] # ['arena', 'nest', 'corridor'] # use in analysis — e.g. check if the animal is inside a region is_in_nest = rois[1].contains_point(ds.position) You can also load a .geojson file back into napari via the Load layer button to review or edit your regions. See the Define regions of interest section of the GUI guide and the updated boundary_angles example for a full walkthrough. ⚡️ Highlight 2: automatic detection of source software in load_dataset Add source_software auto-detection for dataset loading by @M0hammed-Reda in https://github.com/neuroinformatics-unit/movement/pull/920 Thanks to a first contribution from @M0hammed-Reda, load_dataset() can now infer source_software automatically from the file format. When you know which software produced your file, we still recommend passing it explicitly, but automatic inference can be a convenient fallback. from movement.io import load_dataset # recommended: explicit is clearer and faster ds = load_dataset("path/to/file.h5", source_software="DeepLabCut", fps=30) # convenient fallback: automatic inference from file format ds = load_dataset("path/to/file.h5", fps=30) You can also call infer_source_software() directly to check what movement would infer for a given file. 🚀 Performance improvements Speed up and improve memory use when loading VIA tracks file by @sfmig in https://github.com/neuroinformatics-unit/movement/pull/769 @sfmig has substantially sped up loading of VIA-tracks bounding box files. Loading a 34 MB file now takes ~0.5 s (down from ~30 s), and a 100 MB file takes ~1.7 s (down from ~1-2 min). Memory use at peak is now comparable to the final in-memory size of the dataset. ⚠️ Breaking changes Make transforms.scale require an explicit factor by @Tushar7012 in https://github.com/neuroinformatics-unit/movement/pull/839 transforms.scale() no longer has a default value for the factor parameter. Previously, omitting factor silently multiplied the data by 1.0 (equivalent to no scaling). If you were omitting factor, add it explicitly: # Before (silently did nothing) ds_scaled = scale(ds) # After ds_scaled = scale(ds, factor=0.01) # e.g. convert pixels to centimetres 🛠️ Refactoring Convert CLI from argparse to typer by @roaldarbol in https://github.com/neuroinformatics-unit/movement/pull/962 @roaldarbol has been a long-time collaborator and a constant source of ideas for movement — and this is his first, but not last, PR! He migrated the CLI from argparse to Typer, giving the movement command automatic shell completion support and a cleaner foundation for future CLI additions. 📚 Documentation Update and add missing docstrings by @lochhh in https://github.com/neuroinformatics-unit/movement/pull/885 Added link to TheBehaviourForum virtual workshop talk by @niksirbi in https://github.com/neuroinformatics-unit/movement/pull/951 Add acknowledgements to examples by @niksirbi in https://github.com/neuroinformatics-unit/movement/pull/952 Replace fixed contributor table with responsive grid by @lochhh in https://github.com/neuroinformatics-unit/movement/pull/954 Update pandas URL in intersphinx config by @lochhh in https://github.com/neuroinformatics-unit/movement/pull/895 🧹 Housekeeping and dependencies Updated supported Python versions to 3.12 - 3.14 by @niksirbi in https://github.com/neuroinformatics-unit/movement/pull/810 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/neuroinformatics-unit/movement/pull/950 New Contributors @M0hammed-Reda made their first contribution in https://github.com/neuroinformatics-unit/movement/pull/920 @roaldarbol made their first contribution in https://github.com/neuroinformatics-unit/movement/pull/962 Full Changelog: https://github.com/neuroinformatics-unit/movement/compare/v0.15.0...v0.16.0

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

La source scientifique ouverte est momentanément indisponible.

Les institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.