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iohub's `create_empty_plate` does the same plate + channel create/append work. The only waveorder-specific behavior was writing a `plate_metadata` dict into the plate's zattrs; that's now done inline in apply_inverse_transfer_function.py after create_empty_plate returns. Tests: 347 passed, 1 skipped, 2 xfailed. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- apply_inverse_transfer_function.get_reconstruction_output_metadata: no longer pins "chunks": (1, 1, 1, Y, X). create_empty_plate picks chunks (and shards for v0.5) from its own defaults. - compute_transfer_function: drop the explicit chunks= passed to every create_image call. iohub's default is shape[-3:] padded with leading 1s (docstring: "ZYX stack size will be used if not specified"), which matches what we want for both 2D (Z=1 array axis, XY chunk) and 3D (full-ZYX chunk) reconstructions. _write_phase_tf and _write_fluorescence_tf no longer need zyx_shape. - Tests updated to match the new helper signatures. Tests: 347 passed, 1 skipped, 2 xfailed. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
iohub's feat/sharding_in_utils branch requires Python >=3.12, so drop 3.11 from the supported range, classifiers, and CI matrix. TODO left in pyproject.toml: revert to a released iohub once that branch is merged and published. Tests: 347 passed, 1 skipped, 2 xfailed. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
talonchandler
approved these changes
Apr 24, 2026
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Summary
Stack built on top of #554. Removes waveorder's hand-rolled chunk shapes and lets iohub pick them. Also pins iohub to the
feat/sharding_in_utilsbranch so the new sharding defaults are exercised end-to-end.apply_inverse_transfer_function.get_reconstruction_output_metadata: drop the hardcoded"chunks": (1, 1, 1, Y, X)from the returned dict.create_empty_plate(from Replace create_empty_hcs_zarr with iohub's create_empty_plate #554) now picks chunks via iohub's version-specific defaults (and shards for v0.5).compute_transfer_function: drop every explicitchunks=arg passed tocreate_image. iohub's default isshape[-min(3, len(shape)):]padded with leading 1s — docstring: "ZYX stack size will be used if not specified." For a standard TCZYX array that's(1, 1, Z, Y, X)— one full ZYX volume per chunk — which is what we want for both 2D reconstructions (array Z-axis is 1, so the chunk collapses to an XY plane) and 3D reconstructions (full-ZYX chunk)._write_phase_tf/_write_fluorescence_tf/_write_vector_birefringence_tflose theirzyx_shapeparameter since chunks no longer depend on the input's shape.Dependency / Python
iohubtogit+https://github.com/czbiohub-sf/iohub@feat/sharding_in_utils.requires-pythonto>=3.12(iohub's branch requires it), drop3.11from the classifiers and the CI matrix (["3.12", "3.13"]).TODO (follow-ups)
iohub>=...,<0.4) oncefeat/sharding_in_utilsis merged and published.Test plan
uv run pytest— 347 passed, 1 skipped, 2 xfailed.🤖 Generated with Claude Code