fix: read Imaris .ims via direct HDF5 (multi-channel)#19
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Real .ims files broke conversion with an IndexError / broadcast error: the imaris-ims-file-reader array interface squeezes singleton dims and pads slices to chunk boundaries, which da.from_array can't handle, and its file handle closes on GC (stale h5py reads under threads). Read the underlying HDF5 Data datasets directly instead: open our own h5py handle (kept alive by the dataset refs in the dask graph), stack the per-(timepoint, channel) 3-D arrays, and crop the Imaris chunk padding to the true extent the reader reports. dask's default read lock makes the threaded h5py reads safe. Verified on a real 5-D (1,3,115,37716,27277) 3-channel file: opens as czyx with correct µm calibration and converts without error. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Real
.imsfiles failed to convert (IndexError/ broadcast error). Theimaris-ims-file-readerarray interface squeezes singleton dims, pads slices to chunk boundaries, and closes its file handle on GC — all of which breakda.from_array.Fix: read the underlying HDF5
Datadatasets directly — open our ownh5py.File(kept alive via the dataset refs in the dask graph), stack the per-(timepoint, channel) 3-D arrays, crop the Imaris chunk padding to the true extent. dask's default read lock makes the threaded h5py reads safe.Verified on a real 5-D (1, 3, 115, 37716, 27277) 3-channel file: opens as
czyxwith correct µm calibration (z=0.35, y=x=0.108) and converts a crop without error. Suite green (29 passed), ruff clean.🤖 Generated with Claude Code