napari: a multi-dimensional image viewer for Python
Notice bibliographique
Résumé
napari 0.5.6 Fri, Jan 17, 2025 🚧 These notes are under construction while in pre-release 🚧 We're happy to announce the release of napari 0.5.6! napari is a fast, interactive, multi-dimensional image viewer for Python. It's designed for exploring, annotating, and analyzing multi-dimensional images. It's built on Qt (for the GUI), VisPy (for performant GPU-based rendering), and the scientific Python stack (NumPy, SciPy, and friends). For more information, examples, and documentation, please visit our website: https://napari.org/ Highlights Faster shapes 🚀 For its whole history, napari has been a pure Python package. As we go deeper into its performance bottlenecks, though, we're finding that we need some compiled code. This is a big change to the napari installation story, though, so we are rolling it out slowly. But if you've been waiting forever to load your shapes data, this release has some enhancements for you (>2x speedup)! (#7346) To use this speedup, you'll need to: install napari core developer Grzegorz Bokota's collection of performant algorithms, PartSegCore-compiled-backend. (you can install it automatically by pip installing "napari[optional]".) and, in the napari advanced settings, tick the "Use C++ code to speed up creation and updates of Shapes layers" box. Please give it a try and let us know if you encounter any issues! This is the beginning of a new era of performance improvements in napari, to help it live up to its promise of a fast viewer for n-dimensional data in Python! New path drawing tool Drawing paths is easier and smoother with the open-line equilavent of the lasso tool. If you want to draw a curve through your data, whether with a mouse or a tablet+stylus, it is now much easier to freehand rather than clicking on individual points. Try it out! (#7099) Other improvements Often, the important information in a layer name is at the end of the name rather than the beginning. We've improved the eliding (…) of long names by placing the ellipsis in the middle of the name rather than the end (#7461). The default value of "flash" has been changed to False in viewer.screenshot, so that taking many screenshots in a script will not result in rapid flickering (#7476). This is part of a broader accessibility initiative by recent contributor Tim Monko to improve napari for light-sensitive users (#7433, and we are so grateful! 🙏 Read on for the full list of changes since 0.5.5. Add poly line drawing (#7099) New Features Add poly line drawing (#7099) Iterative ROI Screenshots (#7209) Elide layer name in the middle instead of the end (#7461) Improvements Perform triangulation using compiled backend (#7346) stop/start notification timer on window focus change (#7392) Extend reading with plugins to allow Layer objects (#7443) Add CtrlCmd-Backspace as a 2ndary delete_selected_layer keybind (#7449) Change default flash behavior for viewer screenshot-like methods (GUI functionality remains the same) (#7476) Update pyproject.toml remove upper bound on numpy on python 3.9 (#7500) [Enhancement] Modify attenuation slider aspect: attenuation value is displayed (#7523) Performance Perform triangulation using compiled backend (#7346) Use faster triangulation edge function form compiled backend (#7512) Bug Fixes [bugfix] Adjust scale bar position based on font_size when at top (#7018) [Bugfix] Don't exit Preferences widget when using Return/Enter to confirm a shortcut (#7420) Fix thread warning if not napari.run() is called (#7450) Fix highlighting artifacts when selecting multiple shapes (#7457) Fix selection of nD-sliced shapes (#7459) [bugfix] use mean instead of norm for fixed aspect scaling in transform mode (#7466) TracksFilter head_length property bug (#7474) Use faster triangulation edge function form compiled backend (#7512) Bugfix: Check if Layer._loaded before returning status (#7515) Breakout gray and gray_r from mpl_colormaps and ensure they work with ensure_colormap (#7517) Update camera depth when layer extents change (#7529) Documentation Add an image to the get_current_viewer example (#7462) Add initial UI sections docs pages and script for generation (docs#114) Update tutorials (docs#514) Add version warning banner for old versions of the docs (docs#531) Add troubleshooting page (docs#533) add info on how to cross-reference gallery examples (docs#534) Add reference to napari architecture guide in the contributing guide (docs#537) Fix broken link in installation tutorial (docs#539) Add docs on advanced contrast limits widget (docs#542) Update version_switcher.json for 0.5.5 (docs#543) Add resources page with logos (docs#544) Fix build-on-windows link in README.md (docs#546) add documentation for new path tool (docs#547) Add 0.5.6 release notes (docs#548) Other Pull Requests Bump tifffile version to 2022.7.28 (#7371) Update app-model, certifi, coverage, dask, hypothesis, imageio, ipython, matplotlib, napari-console, pydantic, pyqt6, pytest, scikit-image, superqt, tensorstore, tifffile, tqdm, virtualenv, xarray, zarr (#7406) [pre-commit.ci] pre-commit autoupdate (#7451) Update dask, fsspec, hypothesis, ipython, magicgui, napari-console, psutil, pydantic (#7464) [pre-commit.ci] pre-commit autoupdate (#7465) changes Shapes data to float32 and reduce randomization in tests shapes test (#7470) Fix typo observable in Preferences -> Appearance (#7472) Set pytest configuration file for test run using pip (#7473) Update coverage, hypothesis (#7475) [py313] Fix test_qt_plugin_sorter on Python >= 3.13 (#7479) [--pre] Update constraints to allow pyOpenGL 3.1.7, but block 3.1.9a1 (#7480) [py313] Update test_prereleases.yml to add py313 (#7481) [py313] Update plugins/test_utils.py to account for Windows py313 os.path.isabs change (#7482) Flip z axis on 3D camera to default to right-handed frame (#7488) [Maint] Update version_denylist.txt to block zarr rc1 in --pre tests (#7489) Update hypothesis, napari-plugin-manager, pillow, pydantic, pygments, scipy, superqt, virtualenv, xarray, zarr (#7491) [pre-commit.ci] pre-commit autoupdate (#7494) Specify dtype when using zarr.Group.create_array (#7497) remove xfail from test_add_many_zarr_1d_array_is_ignored (#7501) Remove numpy constraints from docs dependency (#7510) [maint] Update pyproject.toml to move plugin manager to optional and let triangle work on arm64 (#7511) Update hypothesis, scipy, tifffile, wrapt (#7514) Revert #7488 "Flip z axis on 3D camera to default to right-handed frame" (#7519) Add test suite without numba (#7520) [pre-commit.ci] pre-commit autoupdate (#7522) Revert PR #3243 ; commit 68157f3 ; (drop compatibility, just use QLabeled* sliders) (#7525) Fix formatting after ruff update in #7522 (#7530) 13 authors added to this release (alphabetical) (+) denotes first-time contributors 🥳 Carol Willing - @willingc Colin Watson - @cjwatson + Daniel Althviz Moré - @dalthviz Draga Doncila Pop - @DragaDoncila Etienne Doumazane - @edoumazane + Grzegorz Bokota - @Czaki Jordão Bragantini - @JoOkuma Juan Nunez-Iglesias - @jni Melissa Weber Mendonça - @melissawm Peter Sobolewski - @psobolewskiPhD Sesan - @Olusesan + Tim Monko (docs) - @TimMonko Wouter-Michiel Vierdag (docs) - @melonora 13 reviewers added to this release (alphabetical) (+) denotes first-time contributors 🥳 Daniel Althviz Moré - @dalthviz Draga Doncila Pop - @DragaDoncila Etienne Doumazane - @edoumazane + Genevieve Buckley - @GenevieveBuckley Grzegorz Bokota - @Czaki Juan Nunez-Iglesias - @jni kyle i. s. harrington - @kephale Lorenzo Gaifas - @brisvag Melissa Weber Mendonça - @melissawm Peter Sobolewski - @psobolewskiPhD Sesan - @Olusesan + Tim Monko (docs) - @TimMonko Wouter-Michiel Vierdag (docs) - @melonora
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,035 | 0,005 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».