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Enregistrement W7084386191 · doi:10.5281/zenodo.17247618

napari: a multi-dimensional image viewer for Python

2025· other· en· W7084386191 sur OpenAlexaff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2025
Typeother
Langueen
DomaineEngineering
ThématiqueTransportation and Mobility Innovations
Établissements canadiensInnovation Cluster (Canada)
Organismes subventionnairesnon disponible
Mots-clésPython (programming language)Scripting languageBridging (networking)ByteSoftware versioningDevelopment environmentSource code

Résumé

récupéré en direct d'OpenAlex

napari 0.6.5 Wed, Oct 1, 2025 We're happy to announce the release of napari 0.6.5! napari is a fast, interactive, multi-dimensional image viewer for Python. It's designed for browsing, annotating, and analyzing large multi-dimensional images. It's built on top of Qt (for the GUI), vispy (for performant GPU-based rendering), and the scientific Python stack (numpy, scipy). For more information, examples, and documentation, please visit our website, https://napari.org. napari follows EffVer (Intended Effort Versioning); this is a Meso release containing awesome new features, but some effort may be needed when updating previous projects to use this version. Highlights This a sizeable release containing a few new exciting features and a lot of bugfixes. EffVer and no more alpha It is our first release officially following the EffVer versioning scheme. We also took this occasion to (finally!) remove the Alpha qualifier from the project (#8288), to better reflect the reality of the extensive use of napari in production. Note that these changes are just formally bringing up to date the state of the project: our development continues as before! Define a startup script for custom launch behaviour Do you have a code snippet that you always find yourself running after you launch napari? No more! You can now put this code in a script and set its path in the new startup script setting (#8188), and it will be executed every time napari opens. It's just a python script, so sky's the limit :) We found it particularly useful for adding custom colormaps, setting up the scale bar just right, or automatically launching our favourite plugin on startup. Automatically tiled overlays and ColorBar overlay Canvas overlays such as scale_bar, text_overlay, and colorbar overlay are now automatically tiling (#7836), preventing annoying overlap and making them easier to use without having to manage positioning. Wait, colorbar overlay you said? You heard it right! This is a new overlay (#7832) that shows a color bar legend, and it works with any layer which uses a colormap. All of this works seamlessly with multiple overlays and even grid mode: import napari viewer = napari.Viewer() # enable grid with stride 2 to get layers split two-by-two viewer.grid.enabled = True viewer.grid.stride = 2 # set the scale bar to gridded mode so it appears in each grid box viewer.scale_bar.visible = True viewer.scale_bar.gridded = True layers = viewer.open_sample('napari', 'lily') # enable color bars for layer in layers: layer.colorbar.visible = True Alternatively, you may also activate the colorbar (and other layer-related overlays such as bounding_box) from the graphical interface by right clicking on selected layers in the layerlist and toggling the relative entries in the Visualization submenu (#8319). Task manager will now try to prevent losing unfinished work We added a new task manager (#8211) which automatically registers any running thread_worker, showing a confirmation dialog if you attempt to close napari while a task is running. New remove and pop methods for Points and Shapes Points and Shapes can now be easily removed, not just added :P (#8031 and #8072). A few shiny new updates to our website and documentation napari.org can now be visited in dark mode (docs#840)! You could try out this new relaxing colorscheme while exploring the new overhauled Preferences documentation section 😉 (docs#834). There's also new sections on viewer overlays and layer overlays, to better explain how to use these old and new tools. Our release notes page also received a glow-up (docs#838), displaying past release highlights in collapsible boxes in the timeline. This should make it easier to quickly catch up when updating across multiple releases! Extra dependencies for development moved to dependency groups A note for our contributors and plugin developers: we transferred our dev-related extra dependencies to the new python dependency groups (#8227). The installation is therefore slightly different, for example: pip install napari --group testing instead of pip install napari[testing]. The previous method will continue to work, but we will likely remove the old optional-dependences approach in a future release. New Features Add color bar overlay (#7832) Tiling canvas overlays (#7836) Add pop() for Points and Shapes (#8072) add option to define startup script in settings (#8188) use Selection class in shapes layer (#8297) Improvements Add remove() in Shapes and Points (#8031) Example from SciPy 2025 tutorial; image warping (#8111) Add a tasks manager status for plugins actions and napari processes (#8211) Use single settings path for all uv tool run (#8250) Add "Hide completed" checkbox to Tracks layer for improved visualization (#8253) Handle affine layer metadata when splitting RGB images (#8256) Update the Shapes select_all_shapes action to allow selection in all modes and add notification of number (#8292) Implement toggling colorbar and bounding box in layerlist context menu (#8319) Add warning for big stride when toggling grid mode (#8320) Bug Fixes Layer controls widgets refactor (#7355) Fix effect of scaling when converting shapes to labels (#8098) Fix disappearing points (#8223) Fix shape position by using a stable algorithm for sorting z_position (#8232) Remove console print action shortcut to prevent collision with command palette shortcut (#8233) Do not update thumbnail on Labels empty slice (#8251) Handle affine layer metadata when splitting RGB images (#8256) fix slice_from_axis to wrap zarr in dask to keep lazy behavior (#8260) Add menu-xdg to XPRA containers (#8263) Check for zarr in images_to_stack and use da.stack instead of np.stack (#8267) Better handling of remote zarr (#8268) Use custom logger formatting to most of argument to string (#8305) Documentation Use EffVer (#8243) Use shared workflows for build docs (#8308) Bump napari-sphinx-theme in deps and constraints (#8315) Update release notes 0.6.5 for full release (docs#855) Add funding information to the home page (docs#818) Update version switcher for 0.6.4 (docs#826) Fix version switcher URL to prevent problems with unversioned pages (docs#827) Update documentation for dependencies groups (docs#829) Update and restructure the preferences guide (docs#834) Fix @jaimergp's last name (docs#835) Auto generate release index with highlights and timeline (docs#838) Add EffVer to release guide and link to checklist template (docs#839) Enable dark mode for website (docs#840) Add draft of 0.6.5 release notes (docs#845) Add documentation for startup script. (docs#846) Add some info about running python scripts via cli (docs#847) Add note about workers registration as tasks and close confirmation dialog when closing napari GUI via close button (docs#851) Release notes v0.6.5 (docs#853) Re-add palette shortcut to viewer guide (docs#854) Add overlays to docs (docs#857) Other Pull Requests Move the test that requires make_napari_viewer from test_qt_viewer (#8176) Change headless setup for Windows and Linux to pyvista/setup-headless-display-action (#8216) Update coverage, hypothesis, pint, pyopengl, virtualenv, xarray (#8221) [pre-commit.ci] pre-commit autoupdate (#8222) Use global register for units in ScaleBar (#8226) Wait until viewer show in the test in make_napari_viewer (#8228) Update Qt backends used in tests to test more on Qt6 than Qt5 (#8229) Change properties for features usage in the Vectors layer controls (#8231) Add cache for pooch on CI for Linux jobs (#8235) Temporary increase timeout of macOS jobs (#8237) Update coverage, hypothesis, ipython, matplotlib, pyside6, pytest-rerunfailures, tifffile (#8239) ci(dependabot): bump the actions group with 6 updates (#8240) Make connect_setattr handle value conversion for widgets like checkboxes (#8244) Update fsspec, hypothesis, pytest, pytest-rerunfailures, xarray (#8249) [pre-commit.ci] pre-commit autoupdate (#8252) Add typing to points mouse bindings (#8255) Use proper name for ruff pre-commit hook and reorder hooks (#8259) [maint] Revert back to windows-2022 for windows runners (#8265) Update dask, hypothesis, pydantic, qtconsole, scipy, tifffile (#8270) Add napari to trove classifiers to populate builtins on napari hub (#8277) Add release checklist template (#8295) Update coverage, dask, hypothesis, lxml, numpy, psutil, tensorstore, tifffile (#8296) Move Jaime Rodríguez-Guerra to core-team section of CITATION.cff (#8298) Do not use verbose mode for headless test (#8300) Migrate macos-13 to macos-15-intel runner (#8301) Update remove_ready_to_merge so it only sweeps on pushed and crons (#8302) [maint] Revert docs constraints changes from #8270 (#8307) Fix constraints generation (#8309) CI: Fix github.rest.issues.removeLabel call (#8311) Fix little typos (#8316) Add pooch cache for build docs (docs#830) ci(dependabot): bump the github-actions group with 3 updates (docs#831) add docs/release/index.md to gitignore (docs#843) Add Jaime Rodríguez-Guerra to core-team (docs#844) Bump python to 3.12 for build docs workflows (docs#848) Use shared workflow for build docs (docs#850) 14 authors added to this release (alphabetical) (+) denotes first-time contributors 🥳 Constantin Aronssohn - @cnstt Daniel Althviz Moré (docs) - @dalthviz Grzegorz Bokota (docs) - @Czaki Jaime Rodríguez-Guerra (docs) - @jaimergp Johannes Soltwedel - @jo-mueller Juan Nunez-Iglesias - @jni Jules Vanaret - @jules-vanaret Kanai Potts - @8bitbiscuit Lorenzo Gaifas (docs) - @brisvag Melissa Weber Mendonça - @melissawm Peter Sobolewski (docs) - @psobolewskiPhD Rahul Kumar - @rahul713rk rwkozar - @rwkozar Tim Monko (docs) - @TimMonko 16 reviewers added to this release (alphabetical) (+) denotes first-time contributors 🥳 Andrew Sweet - @andy-sweet Carol Willing - @willingc Daniel Althviz Moré (docs) - @dalthviz Davis Be

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,094
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0260,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,025
Tête enseignante GPT0,250
Écart entre enseignants0,225 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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