ExtendedPsfCandidateSerializationModel#
- class lsst.pipe.tasks.extended_psf.ExtendedPsfCandidateSerializationModel(*, schema_version: str = '1.0.0', min_read_version: int = 1, metadata: dict[str, MetadataValue] = <factory>, butler_info: ~lsst.images.serialization._common.ButlerInfo | None = None, indirect: list[~typing.Any] = <factory>, image: ~lsst.images._image.ImageSerializationModel[TypeVar], mask: ~lsst.images._mask.MaskSerializationModel[TypeVar], variance: ~lsst.images._image.ImageSerializationModel[TypeVar], projection: ~lsst.images._transforms._projection.ProjectionSerializationModel[TypeVar] | None = None, psf_kernel_image: ~lsst.images._image.ImageSerializationModel[TypeVar] | None = None, star_info: ~lsst.pipe.tasks.extended_psf.extended_psf_candidates.ExtendedPsfCandidateInfo)#
Bases:
MaskedImageSerializationModel[TypeVar],GenericA Pydantic model to represent a serialized
ExtendedPsfCandidate.Attributes Summary
Configuration for the model, should be a dictionary conforming to [
ConfigDict][pydantic.config.ConfigDict].Methods Summary
deserialize(archive, *[, bbox])Deserialize an image from an input archive.
Attributes Documentation
- MIN_READ_VERSION: ClassVar[int] = 1#
- SCHEMA_NAME: ClassVar[str] = 'extended_psf_candidate'#
- SCHEMA_VERSION: ClassVar[str] = '1.0.0'#
- model_config: ClassVar[ConfigDict] = {'json_schema_extra': {'$id': 'https://images.lsst.io/schemas/masked_image-1.0.0', 'title': 'masked_image'}, 'ser_json_bytes': 'base64', 'ser_json_inf_nan': 'constants', 'val_json_bytes': 'base64'}#
Configuration for the model, should be a dictionary conforming to [
ConfigDict][pydantic.config.ConfigDict].
Methods Documentation
- deserialize(archive: InputArchive[Any], *, bbox: Box | None = None) ExtendedPsfCandidate#
Deserialize an image from an input archive.
Parameters#
- archive
Archive to read from.
- bbox
Bounding box of a subimage to read instead.
- **kwargs
Unsupported keyword arguments are accepted only to provide better error messages (raising
serialization.InvalidParameterError).