add imaris metadata strategy

[Arshya-Guru]

Added a fallback strategy for extracting metadata from Imaris native HDF5 attributes. The existing two strategies are unchanged and still tried first. The new fallback only runs if both fail. Also cleans up the exception handling (proper try/except with specific exception types instead of bare except:).

Tried on /nfs/trident3/lightsheet/prado/mouse_app_vaccine_batch/bids/sub-AS177M4/
using:

./run.py \
  --output-bids-dir /nfs/trident3/lightsheet/prado/mouse_app_vaccine_batch/bids \
  --work-dir /nfs/scratch/apooladi/sq2test \
  --stains Abeta CD31 YoPro \
  --subject AS177M4 \
  --acq imaris4x \
  --input-path "/cifs/trident2/lightsheet/prado/mouse_app_vaccine_batch1/raw/ims_4x_stitched/B_AS177M4/19-39-03_b-AS177 M4 Epoe4 Sham Abeta 647 CD31 561 YoPro1X1  _Blaze.ims" \
  -c 4 \
  --use-conda \
  --conda-prefix /nfs/khan/trainees/apooladi/conda_envs

[akhanf]

Nice, that is a useful fallback, as the other fallback (to search based on the filesystem and standard naming scheme) is really hacky.. If this works fine then I would suggest removing the other fallback..

Btw these imaris datasets with no OME metadata were from how Shaz was running the stitching, and hopefully shouldn't come up in the future, but good to have a patch for this..

[Copilot]

Pull request overview

Adds a third, fallback metadata-extraction strategy for Imaris .ims files by reading native HDF5 attributes when OME-XML (in-file) and associated .ome.tif metadata are unavailable.

Changes:

• Added h5_attr_to_str() and a new native-Imaris fallback build_bids_metadata_from_native_imaris() using ExtMin/ExtMax + X/Y/Z to compute voxel sizes.
• Refactored extraction flow into three explicit strategies (OME-in-file → tif fallback → native HDF5), replacing bare except: with more specific exception handling.

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[Copilot]

h5_attr_to_str assumes the attribute is an iterable of 1-byte values (each with .decode()), but h5py attributes are often returned as a scalar bytes/str, a NumPy scalar (e.g. np.bytes_), or a NumPy array of uint8. In those cases this will raise (e.g. iterating a bytes yields ints). Consider making this helper handle: str (return as-is), bytes/np.bytes_ (single decode), NumPy ndarray (decode bytes dtype or convert uint8 via .tobytes()), and strip any trailing \x00 padding if present.

[Copilot]

The for attr_name in [...] list is formatted in a way that likely won’t pass the repo’s Black formatting checks (the line is far beyond typical line length and Black will reflow it). Please reformat this list in Black-compliant style (e.g., one item per line) to avoid CI/lint failures.

Suggested change

	for attr_name in ["Name", "LSMExcitationWavelength", "LSMEmissionWavelength",
	"Color", "Description"]:
	for attr_name in [
	"Name",
	"LSMExcitationWavelength",
	"LSMEmissionWavelength",
	"Color",
	"Description",
	]:

[Copilot]

Strategy 2’s tif fallback only catches IndexError, KeyError, TypeError, ValueError, but opening/reading a found .ome.tif can also raise OSError/FileNotFoundError (e.g., corrupt file, permissions). In that case the script will crash instead of continuing to the native Imaris HDF5 fallback. Consider including OSError (and/or FileNotFoundError) in this except clause so Strategy 3 can still run when the tif path exists but can’t be read.

Suggested change

	except (IndexError, KeyError, TypeError, ValueError) as e:
	except (IndexError, KeyError, TypeError, ValueError, OSError) as e:

[Copilot]

Strategy 1 only catches KeyError, TypeError, ValueError, but reading the embedded OME dataset (hdf5_file[...][:]) can also raise OSError (e.g., dataset exists but can’t be read). If you want to continue on to strategies 2/3 in that case, consider adding OSError to this except list.