def get_metadata(
self,
digest: Optional[Digest] = None,
ignore_errors: bool = True,
) -> BareAsset:
bids_metadata = BIDSAsset.get_metadata(self)
nwb_metadata = NWBAsset.get_metadata(self, digest, ignore_errors)
return BareAsset(
**{**bids_metadata.dict(), **nwb_metadata.dict(exclude_none=True)}
)
def get_metadata(
self,
digest: Optional[Digest] = None,
ignore_errors: bool = True,
) -> BareAsset:
metadata = self.bids_dataset_description.get_asset_metadata(self)
start_time = end_time = datetime.now().astimezone()
add_common_metadata(metadata, self.filepath, start_time, end_time, digest)
metadata["path"] = self.path
return BareAsset(**metadata)
def validate_dandi_nwb(filepath, schema_version=None, devel_debug=False):
"""Provide validation of .nwb file regarding requirements we impose"""
if schema_version is not None:
from dandischema.models import BareAsset, get_schema_version
from pydantic import ValidationError
from .metadata import nwb2asset
current_version = get_schema_version()
if schema_version != current_version:
raise ValueError(
f"Unsupported schema version: {schema_version}; expected {current_version}"
)
try:
asset = nwb2asset(filepath,
digest=32 * "d" + "-1",
digest_type="dandi_etag")
BareAsset(**asset.dict())
except ValidationError as e:
if devel_debug:
raise
lgr.warning("Validation error for %s: %s",
filepath,
e,
extra={"validating": True})
return [str(e)]
except Exception as e:
if devel_debug:
raise
lgr.warning(
"Unexpected validation error for %s: %s",
filepath,
e,
extra={"validating": True},
)
return [f"Failed to read metadata: {e}"]
return []
else:
# make sure that we have some basic metadata fields we require
try:
meta = get_metadata(filepath)
except Exception as e:
if devel_debug:
raise
lgr.warning(
"Failed to read metadata in %s: %s",
filepath,
e,
extra={"validating": True},
)
return [f"Failed to read metadata: {e}"]
return _check_required_fields(meta, _required_nwb_metadata_fields)
def process_ndtypes(asset: models.BareAsset,
nd_types: Iterable[str]) -> models.BareAsset:
approach = set()
technique = set()
variables = set()
for val in nd_types:
val = val.split()[0]
if val not in neurodata_typemap:
continue
if neurodata_typemap[val]["approach"]:
approach.add(neurodata_typemap[val]["approach"])
if neurodata_typemap[val]["technique"]:
technique.add(neurodata_typemap[val]["technique"])
variables.add(val)
asset.approach = [models.ApproachType(name=val) for val in approach]
asset.measurementTechnique = [
models.MeasurementTechniqueType(name=val) for val in technique
]
asset.variableMeasured = [
models.PropertyValue(value=val) for val in variables
]
return asset
def get_validation_errors(
self,
schema_version: Optional[str] = None,
devel_debug: bool = False,
) -> list[str]:
if schema_version is not None:
current_version = get_schema_version()
if schema_version != current_version:
raise ValueError(
f"Unsupported schema version: {schema_version}; expected {current_version}"
)
try:
asset = self.get_metadata(digest=DUMMY_DIGEST)
BareAsset(**asset.dict())
except ValidationError as e:
if devel_debug:
raise
lgr.warning(
"Validation error for %s: %s",
self.filepath,
e,
extra={"validating": True},
)
return [str(e)]
except Exception as e:
if devel_debug:
raise
lgr.warning(
"Unexpected validation error for %s: %s",
self.filepath,
e,
extra={"validating": True},
)
return [f"Failed to read metadata: {e}"]
return []
else:
# TODO: Do something else?
return []