CatalogExposurePsfs#

class lsst.meas.extensions.multiprofit.fit_coadd_multiband.CatalogExposurePsfs(*, dataId: ~lsst.daf.butler.dimensions._coordinate.DataCoordinate | dict = <factory>, catalog: ~lsst.afw.table.SourceCatalog | None = None, exposure: ~lsst.afw.image._exposure._exposureContinued.Exposure | None = None, id_tract_patch: int = 0, metadata: dict = <factory>, table_psf_fits: ~astropy.table.table.Table = <factory>, channel: ~lsst.gauss2d.fit._gauss2d_fit.Channel = <factory>, config_fit: ~lsst.meas.extensions.multiprofit.fit_coadd_multiband.MultiProFitSourceConfig = <factory>)#

Bases: CatalogExposureInputs, CatalogExposureSourcesABC

Input data from lsst pipelines, parsed for MultiProFit.

Attributes Summary

`catalog`
`channel`
`config_fit`
`dataId`
`exposure`
`id_tract_patch`
`metadata`
`table_psf_fits`

Methods Summary

`get_psf_model`(source)	Get the PSF model for a given source row.
`get_source_observation`(source, **kwargs)	Get the Observation for a given source row.

Attributes Documentation

catalog: afwTable.SourceCatalog | None = None#

channel: Channel = FieldInfo(annotation=NoneType, required=True, title="Channel for the image's band")#

config_fit: MultiProFitSourceConfig = FieldInfo(annotation=NoneType, required=True, title='Config for fitting options')#

dataId: dafButler.DataCoordinate | dict = FieldInfo(annotation=NoneType, required=True, title="A DataCoordinate or dict containing a 'band' item")#

exposure: afwImage.Exposure | None = None#

id_tract_patch: int = 0#

metadata: dict = FieldInfo(annotation=NoneType, required=False, default_factory=dict, title='Arbitrary metadata')#

table_psf_fits: astropy.table.Table = FieldInfo(annotation=NoneType, required=True, title='A table of PSF fit parameters for each source')#

Methods Documentation

get_psf_model(source)#

Get the PSF model for a given source row.

Parameters#

paramsMapping[str, Any]: A mapping with parameter values for the best-fit PSF model at the centroid of a single source.

Returns#

psf_modellsst.gauss2d.fit.PsfModel: A PsfModel object initialized with the best-fit parameters, or None if PSF rebuilding failed for an expected reason (i.e. the input PSF fit table has a flag set).

get_source_observation(source, **kwargs) → ObservationD#

Get the Observation for a given source row.

Parameters#

sourceMapping[str, Any]: A mapping with any values needed to retrieve an observation for a single source.
**kwargs: Additional keyword arguments not used during fitting.

Returns#

observationlsst.gauss2d.fit.Observation: An Observation object with suitable data for fitting parametric models of the source, or None if the observation cannot be fit.