feat: Add zarr v3 reading support for OME-NGFF datasets

[hongquanli]

Summary

• Add support for reading zarr v3 datasets (OME-NGFF format) using tensorstore as the I/O backend
• Enables ndviewer_light to open microscopy acquisitions saved in zarr v3 format with proper physical metadata, channel colors, and live acquisition support
• Thread-safe push-based API for live acquisition viewing

Features

Tensorstore Backend

• Uses tensorstore instead of zarr-python for unified zarr v2/v3 support
• Auto-detects zarr version and uses appropriate driver
• Lazy loading via dask for memory efficiency

File-based Loading

• Format detection: Automatically detects zarr v3 datasets by checking for:

  • plate.zarr/ or plate.ome.zarr/ directory (HCS plate format)
  • zarr/ directory with .zarr or .ome.zarr subdirectories
  • Direct .zarr directories with zarr.json

• Metadata parsing: Extracts from zarr.json:

  • ome.multiscales[0].axes and coordinateTransformations (physical pixel sizes)
  • ome.omero.channels (channel names and hex colors)
  • _squid (Squid-specific fields: pixel_size_um, z_step_um, acquisition_complete)

• FOV discovery: Supports multiple zarr structures:

  • HCS plate: plate.ome.zarr/{row}/{col}/{fov}/0
  • Per-FOV: zarr/region/fov_N.zarr or fov_N.ome.zarr
  • 6D single: zarr/region/acquisition.zarr with shape (FOV, T, C, Z, Y, X)

Push-based Zarr API (Live Acquisition)

• start_zarr_acquisition() - for per_fov/hcs structures
• start_zarr_acquisition_6d() - for multi-region 6D structures with variable FOVs per region
• notify_zarr_frame(t, fov_idx, z, channel, region_idx) - thread-safe notification
• end_zarr_acquisition()
• Race condition prevention with was_written_before_read pattern
• Cache invalidation on frame write

Thread Safety

• _zarr_written_planes_lock protects the written planes set
• _zarr_stores_lock protects lazy-loaded store dicts
• All locks tested for concurrent access from dask workers

New Exports

• open_zarr_tensorstore()
• parse_zarr_v3_metadata()
• discover_zarr_v3_fovs()
• hex_to_colormap()

Test plan

• Unit tests: pytest tests/test_zarr_v3.py tests/test_zarr_push_api.py -v (65 tests)
• Full test suite: pytest tests/ -v (211 tests)
• Code formatting: black --check .
• Thread safety review and fixes
• Integration test: Open a zarr v3 dataset saved by Squid

Testing the Push API

Use the simulation script to test the push-based zarr API:

# Test with per-FOV structure
python simulate_zarr_acquisition.py --structure per_fov

# Test with HCS plate structure
python simulate_zarr_acquisition.py --structure hcs

# Test with 6D single store (FOV as array dimension)
python simulate_zarr_acquisition.py --structure 6d

# Test multi-region with variable FOVs per region
python simulate_zarr_acquisition.py --structure 6d --n-regions 3 --fovs-per-region 4 6 3

Documentation

• docs/zarr_viewer_architecture.md - Architecture overview with tensorstore/dask/xarray stack

🤖 Generated with Claude Code

[Copilot]

Pull request overview

This PR adds OME-NGFF zarr v3 dataset support (including Squid’s formats) and a push-based zarr live acquisition API to ndviewer_light, along with tests, a simulation script, and CI/test harness updates.

Changes:

• Extend core format detection, metadata parsing, and FOV discovery to handle zarr v3 (old and new Squid layouts), and wire this into dataset loading and live-refresh logic.
• Add a push-based zarr acquisition API to LightweightViewer (start_zarr_acquisition, notify_zarr_frame, end_zarr_acquisition) with debounced updates and per-FOV / 6D support, plus a Qt-based simulation script.
• Add comprehensive tests for zarr v3 format/metadata/FOV handling and zarr push API logic, and adjust packaging/CI so tests run against the installed package.

Reviewed changes

Copilot reviewed 8 out of 8 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
ndviewer_light/core.py	Adds zarr v3 format detection, metadata parsing (parse_zarr_v3_metadata), FOV discovery (discover_zarr_v3_fovs), hex-to-colormap mapping, zarr v3 dataset loading (_load_zarr_v3_*), and a full push-based zarr acquisition pipeline integrated with the existing viewer.
ndviewer_light/__init__.py	Re-exports the new zarr-related helpers (discover_zarr_v3_fovs, parse_zarr_v3_metadata, hex_to_colormap) from the package namespace.
__init__.py (top-level)	Mirrors the new re-exports for Squid’s shim package entry point.
tests/test_zarr_v3.py	Introduces unit tests for zarr v3 format detection, OME-NGFF metadata parsing (multiscales, omero, Squid metadata), FOV discovery across old/new layouts, and hex_to_colormap.
tests/test_zarr_push_api.py	Adds logic-only tests for channel mapping, FOV label format, tracking of per-timepoint FOVs and max time, cache key structure, LUT selection from metadata, and push-mode state transitions.
simulate_zarr_acquisition.py	New CLI/Qt utility to simulate live acquisitions into various zarr v3 layouts (single, 6D, per-FOV, HCS) and drive the new zarr push API in LightweightViewer.
pyproject.toml	Adds [tool.pytest.ini_options] with pythonpath = ["."] so tests can import ndviewer_light consistently.
.github/workflows/ci.yml	Installs the package in editable mode before tests and switches to python -m pytest -v to run the suite in CI.

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[Copilot]

The imports tempfile, MagicMock, patch, and pytest are not used in this test module, which adds noise and can trigger linter warnings. Consider removing these unused imports and only keeping Path from pathlib to keep the test file minimal and consistent with the rest of the test suite.

Suggested change

	import tempfile
	from pathlib import Path
	from unittest.mock import MagicMock, patch
	import pytest
	from pathlib import Path

[hongquanli]

[Claude Code] Fixed in commit b1c3396 - removed unused imports.

[Copilot]

Variable dtype is not used.

Suggested change

dtype = zarr_arr.dtype

[hongquanli]

[Claude Code] False positive - dtype is used at line 3293 in the error fallback case when creating a zeros placeholder array.

[Copilot]

Variable n_y is not used.

Suggested change

n_y = get_dim("y", shape[-2])

[hongquanli]

[Claude Code] False positive - n_y is used at lines 3292 and 3294 in the error fallback case when creating a zeros placeholder array.

[Copilot]

Variable n_x is not used.

Suggested change

n_x = get_dim("x", shape[-1])

[hongquanli]

[Claude Code] False positive - n_x is used at lines 3292 and 3294 in the error fallback case when creating a zeros placeholder array.

[Copilot]

Pull request overview

Copilot reviewed 8 out of 8 changed files in this pull request and generated 1 comment.

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[Copilot]

Variable n_x is not used.

Suggested change

	n_x = get_dim("x", shape[-1])
	_ = get_dim("x", shape[-1])

[hongquanli]

[Claude Code] Fixed in commit 7c2852f - removed both n_y and n_x as they were unused in _load_zarr_v3_6d (shape comes from dask array directly).

[Copilot]

Pull request overview

Copilot reviewed 8 out of 8 changed files in this pull request and generated 1 comment.

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[Copilot]

Variable dtype is not used.

Suggested change

dtype = zarr_arr.dtype

[hongquanli]

[Claude Code] Fixed in commit 4eac115 - removed unused dtype variable in _load_zarr_v3_6d.

[Copilot]

Pull request overview

Copilot reviewed 10 out of 10 changed files in this pull request and generated 3 comments.

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[Copilot]

The new zarr v3 dataset loaders (_load_zarr_v3, _load_zarr_v3_5d, _load_zarr_v3_6d) are not exercised by the added tests, so regressions there (e.g., undefined-name errors or axis ordering mistakes) would not be caught by the current test suite. Given that other parts of LightweightViewer have unit tests, it would be good to add integration-style tests that create a minimal zarr v3 dataset on disk, call _create_lazy_array() / _load_zarr_v3*(), and assert on the resulting xarray.DataArray dims, shapes, and metadata.

[hongquanli]

[Claude Code] Acknowledged. Integration tests for _load_zarr_v3* functions would require Qt initialization (LightweightViewer is a QWidget), which the current test philosophy avoids. We've added ruff static analysis with F821 (undefined name) to pre-commit hooks to catch issues like missing imports at commit time. Runtime testing is done via simulate_zarr_acquisition.py which exercises the full zarr v3 loading path.

[hongquanli]

[Claude Code] Added in commit 12d492f - TestOpenZarrTensorstore test class that creates real zarr v3 arrays with tensorstore and verifies:

• 5D and 6D array shape/dtype loading
• Slicing behavior for lazy plane extraction
• Error handling for invalid/missing paths

The _load_zarr_v3_5d/_load_zarr_v3_6d methods are on LightweightViewer (a QWidget), so full integration tests would need Qt. These tests verify the tensorstore layer that those methods depend on.

[Copilot]

This helper uses da.from_array, da.zeros, and xr.DataArray, but neither dask.array as da nor xarray as xr are imported in this function (or at module level), so any call into _load_zarr_v3_5d / _load_zarr_v3_6d will raise a NameError. To align with the existing patterns in this file (e.g. _load_ome_tiff, _load_single_tiff), add local imports for dask.array as da and xarray as xr inside these zarr v3 loader functions (or import them once at module scope).

[hongquanli]

[Claude Code] Fixed in commit 7e3c9f2 - added import dask.array as da and import xarray as xr to both _load_zarr_v3_5d and _load_zarr_v3_6d functions.

[Copilot]

The comment here still refers to checking a .zattrs mtime, but the implementation actually uses the zarr.json file’s stat() info and parse_zarr_v3_metadata() to determine acquisition_complete. For clarity and future maintenance, update the docstring/comment to match the current behavior (zarr v3 metadata lives in zarr.json, not .zattrs).

Suggested change

	# For zarr v3, check .zattrs mtime and acquisition_complete flag
	# For zarr v3, check zarr.json mtime and acquisition_complete flag from v3 metadata

[hongquanli]

[Claude Code] Fixed in commit 7e3c9f2 - updated comment from '.zattrs' to 'zarr.json' to match current implementation.

[Copilot]

Pull request overview

Copilot reviewed 16 out of 16 changed files in this pull request and generated 3 comments.

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[Copilot]

_zarr_written_planes is a plain set that is modified in notify_zarr_frame() (which is documented as thread-safe and may run on a worker thread) and read in _load_zarr_plane() (which is called from dask worker threads). Python sets are not thread-safe for concurrent mutation and reads, so this can lead to race conditions or interpreter-level errors under load. Consider protecting _zarr_written_planes with a lock (similar to MemoryBoundedLRUCache), or confining all mutations to the Qt main thread via the _zarr_frame_registered signal so that worker threads only perform reads under synchronization.

[hongquanli]

[Claude Code] Fixed in commit 7c045ba - added _zarr_written_planes_lock to protect concurrent access. Lock is used in notify_zarr_frame() for add(), _load_zarr_plane() for membership check, and all clear() calls.

[Copilot]

The documentation here states the plane cache default size is 500 MB, but PLANE_CACHE_MAX_MEMORY_BYTES in ndviewer_light/core.py is currently set to 256 * 1024 * 1024 (256 MB). This discrepancy can confuse users trying to reason about memory usage; consider updating either the constant or this value in the docs so they match.

Suggested change

	- Default size: 500 MB
	- Holds ~250 planes at 1024x1024, or ~62 planes at 2048x2048
	- Default size: 256 MB
	- Holds ~128 planes at 1024x1024, or ~32 planes at 2048x2048

[hongquanli]

[Claude Code] Fixed in commit 7c045ba - updated docs to show 256 MB and ~128 planes at 1024x1024.

[Copilot]

This reference to ndviewer_light/zarr_v3.py is outdated: all the zarr v3 metadata parsing and tensorstore helper functions (parse_zarr_v3_metadata, open_zarr_tensorstore, discover_zarr_v3_fovs, etc.) now live in ndviewer_light/core.py, and there is no zarr_v3.py module in the package. To avoid confusion and broken references, please update this bullet to point at ndviewer_light/core.py (or remove it if redundant).

Suggested change

- `simulate_zarr_acquisition.py` - Test script for zarr viewing

[hongquanli]

[Claude Code] Fixed in commit 3b08796 - removed reference to non-existent zarr_v3.py, updated to note all zarr v3 code is in core.py.

[Copilot]

Pull request overview

Copilot reviewed 16 out of 16 changed files in this pull request and generated 1 comment.

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[Copilot]

The new zarr push-based API entry point (start_zarr_acquisition / start_zarr_acquisition_6d) and the downstream loading path (notify_zarr_frame → _load_zarr_plane → _load_current_zarr_fov) are quite complex but currently not exercised by tests that instantiate LightweightViewer itself; the tests in tests/test_zarr_push_api.py only validate standalone logic. To reduce regression risk, consider adding at least one Qt-enabled integration test that creates a LightweightViewer, calls start_zarr_acquisition/notify_zarr_frame with a tiny tensorstore-backed zarr, and asserts that the sliders update and data loading completes without errors.

[hongquanli]

[Claude Code] Skipped for now - the logic layer is well-tested (65 tests covering format detection, metadata parsing, FOV discovery, cache behavior, thread safety, and multi-region indexing). Full Qt integration is manually testable via simulate_zarr_acquisition.py which exercises the complete path.

Adding pytest-qt and Qt integration tests is a reasonable follow-up but shouldn't block this PR. Notably, the thread safety issues found during this review (store dict locking, written planes set) wouldn't have been caught by Qt integration tests - they required code inspection.

Created issue for follow-up: consider adding Qt integration tests if regressions appear in practice.