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Enabling Access To Multi-resolution Data

Award napari Plugin Accelerator

Project Summary

The napari platform provides an important link between modern scientific workflows such as Python notebooks and a familiar GUI-based visualization application. The initial focus of napari has been to efficiently handle large image stacks from bioimaging domains such as CT scans and cell imaging. This project will develop a new yt-napari plugin to load images from more complex data storage formats, leveraging the open source yt package to sample geometrically complex datasets stored in hierarchical data formats (including adaptive resolution, overlapping regions, and discretely sampled data requiring resampling). The yt platform is an open source Python package for analysis and visualization of multi-resolution volumetric data. The new yt-napari plugin will provide a new, interactive visualization environment for the yt community and also demonstrate a napari workflow capable of loading a subset of co-registered variables. yt is widely used in the astrophysics community and is gaining use among other scientific domains.

The proposed yt-napari plugin would help fill in the interactive visualization gap for yt users as well as provide instant access to the existing image analysis plugins that have already been developed for napari.


Principal Investigator
Matthew Turk, PhD
Matthew Turk, PhD
Co-Principal Investigator
Chris Havlin, PhD
Chris Havlin, PhD