feat(ngff zarr): add multi channel support

[PaulHax]

Somehow these hacks work for all the datasets I've loaded except for the 2 lowest resolution scales in oeway's astronaut where the chunks span components.

[thewtex]

const chunkSize = toDimensionArray(['c', 'x', 'y', 'z'], info.chunkSize)

Instead of ['c', 'x', 'y', 'z'], this should be info.dims now, correct?

[PaulHax]

Works on oeway's astronaut now. Some fishy stuff with the x chunk index to shift down x rows:

pixelArray[
                cc +
                  zz * pixelStrides.z +
                  (yy + x) * pixelStrides.y +
                  xx * pixelStrides.x
              ] =

[oeway]

Thanks for working on this! Looking forward it! FYI: I am currently making a browser file system that can handle large files backed by indexeddb. Would be nice to test using pyodide/jupyterlite + zarr-python to read in-browser large files, then pipe the data as a zarr store to itk-vtk-viewer!

[thewtex]

Looking good. Can we base and add tests for the new datasets?

[PaulHax]

Looking good. Can we base and add tests for the new datasets?

Added tests for a selection of the working images.

Some issues:

• All the first_instar_brains: .zattrs 'axes' metadata order does not match the array's .zattrs "_ARRAY_DIMENSIONS". I'll change code to use _ARRAY_DIMENSIONS.
• first_instar_brain_czyx.zarr/.zattrs file is empty {}
• Most of the idr datasets have their dtype endianness the way we don't support, >u2 and >f4. Not sure what to do there.

[thewtex]

For the first two, we should fix the data generator. Could you please create issues on the multi-scale-spatial-image repository, and assign it to me?

For the endianness issue, we should transform an chunk array from big to little before loading into the itk.Image. Could you please look for a JS library to do that and apply when required?

[PaulHax]

[ ] 2. For the conditions where we can use them in the inner-most loop, use .subarray and .set for getting and setting the contiguous region.

Implemented the above with guidance from the old code. Good speedup with first_instar_brain_zyxc.zarr highest resolution taking the worker ~11ms vs old way of ~26ms.

[oeway]

Hi @PaulHax @thewtex Awesome to see this PR get merged! Well done, can't wait to try it.

It looks like the master branch CI is failing and that it explains why I cannot already show the multi-channel zarr images.

[github-actions[bot]]

:tada: This PR is included in version 12.3.0 :tada:

The release is available on:

• npm package (@latest dist-tag)
• GitHub release

Your semantic-release bot :package::rocket:

[thewtex]

Hi @oeway CI was given some :heart: , v12.3.0 is now out with these improvements, please give it a whirl!