napari: a multi-dimensional image viewer for Python
Notice bibliographique
Résumé
napari 0.5.4 Monday, Sep 30, 2024 We're happy to announce the release of napari 0.5.4! 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 Another release with a lot of bug fixes, but also some (more!) improvements to Shapes layer performance (#7144, #7256), and a few nice usability/quality of life features! you can now follow the value under the cursor around in images in 3D view as well as 2D (#7126) Use standard keyboard shortcuts to zoom in and out ({kbd}Command/Ctrl+=, {kbd}Command/Ctrl+-) and to zoom-to-fit ({kbd}Command/Ctrl+0) (#7200) you can now save tiff files larger than 4GB (#7242) Finally, we're starting some work on tweaking the UI to make it more self-consistent, with the ultimate goal of adding functionality such as showing common controls when multiple layers are selected, so that, for example, you can select multiple layers and adjust all their opacity settings together. As the first step for this, the layer blending controls have been moved directly under the opacity control, so that all per-layer controls are next to each other in the UI (#7202) Read on for all the changes in this version! New Features enable get_value_3d for image layers (#7126) Preserve area of dock widgets between sessions (#7247) Improvements Speed up get_status for Shapes layer by using bounding boxes (#7144) Enh: Add zoom options and keybindings to View menu (#7200) [ux/ui] Put blending controls under opacity slider in layer controls (#7202) Enable conflicts detection with layer keybindings when changing viewer ones and add group info to conflicts popup (#7231) Speedup _is_convex by avoid calling np.roll (#7256) Sort plugin manifests in alphabetical order for registration (#7266) Performance Speed up get_status for Shapes layer by using bounding boxes (#7144) Speedup _is_convex by avoid calling np.roll (#7256) Bug Fixes start/stop status thread on show/hide main window (#7240) Added support for saving tiff files > 4GB :) (#7242) Accept any Mapping as output of a plugin widget (#7250) Eliminate nearly all Qt widget leaks by using qtbot (#7251) Enforce minimum side length when guessing if image is RGB (#7273) Remove skip conditions for PySide2/6 over plugins menu tests and bump napari-plugin-manager minimum version (>=0.1.3) (#7293) Fix color shuffling for bool labels (#7294) Fix cursor dimensionality race condition (#7295) Fix overflow error in shuffle colormap for signed integer labels (#7296) When calculating view directions, check ndim, not just ndisplay (#7301) Documentation Add beanli161514 to citation file (#7272) Doc/metadata: add jni's ORCID to the CITATION.cff file (#7275) Style fix: use recommended capitalization for "GitHub" in README (#7284) Add psygnal and pydantic to napari --info (#7285) Move images to _static folder (docs#483) Update version switcher to add 0.5.3 (docs#488) Move release notes to be under Usage (docs#489) Update release guide (docs#491) Use get_qapp or get_app_model instead of get_app (docs#495) Add 0.5.4 release notes (docs#496) Add note about questions in landing page (docs#498) Add further fixes to release notes ([docs#499](Add further fixes to release notes)) Other Pull Requests Update script for vendored modules (#5779) Update certifi, dask, hypothesis, ipython, numpy, qtconsole, rich, scipy, tifffile (#7212) Block zarr 3.0.0a1 and 3.0.0a2 in pre-release tests (#7217) Add autouse fixture that clears cached property Action.injected (#7224) Update tifffile (#7235) CI benchmark run comment will now include results table (#7237) [pre-commit.ci] pre-commit autoupdate (#7239) Fix coverage and debug artifacts upload (#7241) Replaced broken link to the "Translations" page :) (#7243) Alow to call benchmark that do not have params (#7252) Block zarr=3.0.0a3 to fix pre-release tests (#7254) Change type of layer Metadata from dict to Mapping (#7257) Update fsspec, hypothesis, pydantic, tensorstore, virtualenv, zarr (#7258) Deprecate usage of get_app functions to get QApplication or NapariApplication instances (#7269) Block zarr==3.0.0a4 (#7271) Update dask, hypothesis, napari-plugin-manager, pandas, pydantic, pytest, rich, tifffile, virtualenv, xarray (#7274) [pre-commit.ci] pre-commit autoupdate (#7276) Fix test_windows_grouping_overwrite skip condition and asserts (#7281) Update menu sorting tests still using mock_app and get_app instead of mock_app_model and get_app_model (#7283) Remove obsolete self from layout argument (#7291) 11 authors added to this release (alphabetical) (+) denotes first-time contributors 🥳 BeanLi - @beanli161514 Daniel Althviz Moré (docs) - @dalthviz Draga Doncila Pop - @DragaDoncila Grzegorz Bokota - @Czaki Ikko Eltociear Ashimine - @eltociear + Juan Nunez-Iglesias (docs) - @jni Lorenzo Gaifas - @brisvag Lucy Liu - @lucyleeow Melissa Weber Mendonça - @melissawm Peter Sobolewski - @psobolewskiPhD Sammy Hansali - @sammyhansali + 13 reviewers added to this release (alphabetical) (+) denotes first-time contributors 🥳 andrew sweet - @andy-sweet Ashley Anderson - @aganders3 Daniel Althviz Moré (docs) - @dalthviz Draga Doncila Pop - @DragaDoncila Grzegorz Bokota - @Czaki jaime rodriguez-guerra - @jaimergp Juan Nunez-Iglesias (docs) - @jni kyle i. s. harrington - @kephale Lorenzo Gaifas - @brisvag Lucy Liu - @lucyleeow Melissa Weber Mendonça - @melissawm Peter Sobolewski - @psobolewskiPhD Wouter-Michiel Vierdag - @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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,173 | 0,664 |
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 ».