Validating a fileset

validate() checks a fileset (an image, a plate, a well or a bioformats2raw collection) against the OME-Zarr 0.5 schemas and returns a FilesetReport. It never raises on malformed metadata; problems are collected in report.errors. To try it, first write a small image:

import numpy as np
from ome_zarr_io import Writer

Writer(
    path="example.ome.zarr",
    image=np.zeros((2, 64, 64), dtype=np.uint8),
    dims=["c", "y", "x"],
    axis_units={"y": "micrometer", "x": "micrometer"},
    channels=["DAPI", "GFP"],
    overwrite=True,
).write()

from ome_zarr_io import validate

report = validate("example.ome.zarr")  # local path or URL

if report:  # same as report.is_valid
    print(report.spec_version, [a["name"] for a in report.axes])
    print([c.label for c in report.channels], [lb.name for lb in report.labels])
else:
    for issue in report.errors:
        print(issue.location, issue.path, issue.message)

print(report)               # human-readable summary
report.to_dict()            # JSON-serializable
report.raise_if_invalid()   # raises jsonschema.exceptions.ValidationError

Use strict=True for the stricter schemas.

A plate is validated all the way down: its own metadata, every well it lists, and every field of view and label image in those wells. issue.location says where each problem is, for example plate, A/1 (a well), A/1/0 (a field) or A/1/0/labels/cells. Besides the schemas, it checks that each well’s path, rowIndex and columnIndex agree, that listed wells and fields exist, that field acquisitions are defined by the plate, and that the OME-Zarr version is the same throughout. Validating a well on its own checks its fields too.