Inheritance diagram for lsst.meas.algorithms.psfDeterminer.BasePsfDeterminerTask:

Public Member Functions
	__init__ (self, config, schema=None, **kwds)

	downsampleCandidates (self, inputCandidateList)

	determinePsf (self, exposure, psfCandidateList, metadata=None, flagKey=None)

Static Public Attributes
bool	usesMatches = False

	ConfigClass = BasePsfDeterminerConfig

Static Protected Attributes
str	_DefaultName = "psfDeterminer"

Detailed Description

Base class for PSF determiners

Register all PSF determiners with the psfDeterminerRegistry using:
    psfDeterminerRegistry.register(name, class)

Parameters
----------
config : `lsst.pexConfig.Config`
    Input for configuring the algorithm
schema : `lsst.afw.table.Schema`
    Schema used for sources; passing a schema allows the
    determiner to reserve a flag field to mark stars used in
    PSF measurement, but some PSF determiners ignore this argument.

Definition at line 52 of file psfDeterminer.py.

Constructor & Destructor Documentation

◆ init()

lsst.meas.algorithms.psfDeterminer.BasePsfDeterminerTask.__init__	(		self,
			config,
			schema = None,
		**	kwds )

Definition at line 72 of file psfDeterminer.py.

    def __init__(self, config, schema=None, **kwds):
        pipeBase.Task.__init__(self, config=config, **kwds)
 

Member Function Documentation

◆ determinePsf()

lsst.meas.algorithms.psfDeterminer.BasePsfDeterminerTask.determinePsf	(	self,
		exposure,
		psfCandidateList,
		metadata = None,
		flagKey = None )

Determine a PSF model.

Parameters
----------
exposure : `lsst.afw.Exposure`
    Exposure containing the psf candidates.
psdCandidateList : `list` [`lsst.meas.algorithms.PsfCandidate`]
    A sequence of PSF candidates; typically obtained by
    detecting sources and then running them through a star
    selector.
metadata : `str`, optional
    A place to save interesting items.
flagKey: `lsst.afw.table.Key`, optional
    Schema key used to mark sources actually used in PSF determination.

Returns
-------
psf : `lsst.afw.detection.Psf`
    The fit PSF.
cellSet : `lsst.afw.math.SpatialCellSet`
    The spatial cell set used to determine the PSF

Reimplemented in lsst.meas.algorithms.pcaPsfDeterminer.PcaPsfDeterminerTask, and lsst.meas.extensions.piff.piffPsfDeterminer.PiffPsfDeterminerTask.

Definition at line 107 of file psfDeterminer.py.

    def determinePsf(self, exposure, psfCandidateList, metadata=None, flagKey=None):
        """Determine a PSF model.
 
        Parameters
        ----------
        exposure : `lsst.afw.Exposure`
            Exposure containing the psf candidates.
        psdCandidateList : `list` [`lsst.meas.algorithms.PsfCandidate`]
            A sequence of PSF candidates; typically obtained by
            detecting sources and then running them through a star
            selector.
        metadata : `str`, optional
            A place to save interesting items.
        flagKey: `lsst.afw.table.Key`, optional
            Schema key used to mark sources actually used in PSF determination.
 
        Returns
        -------
        psf : `lsst.afw.detection.Psf`
            The fit PSF.
        cellSet : `lsst.afw.math.SpatialCellSet`
            The spatial cell set used to determine the PSF
        """
        raise NotImplementedError("BasePsfDeterminerTask is abstract, subclasses must override this method")
 
 

◆ downsampleCandidates()

lsst.meas.algorithms.psfDeterminer.BasePsfDeterminerTask.downsampleCandidates	(		self,
			inputCandidateList )

Down-sample candidates from the input candidate list.

Parameters
----------
inputCandidateList : `list` [`lsst.meas.algorithms.PsfCandidate`]
    Input candidate list.

Returns
-------
outputCandidateList : `list` [`lsst.meas.algorithms.PsfCandidate`]
    Down-selected candidate list.

Definition at line 75 of file psfDeterminer.py.

    def downsampleCandidates(self, inputCandidateList):
        """Down-sample candidates from the input candidate list.
 
        Parameters
        ----------
        inputCandidateList : `list` [`lsst.meas.algorithms.PsfCandidate`]
            Input candidate list.
 
        Returns
        -------
        outputCandidateList : `list` [`lsst.meas.algorithms.PsfCandidate`]
            Down-selected candidate list.
        """
        if len(inputCandidateList) <= self.config.maxCandidates:
            return inputCandidateList
 
        rng = np.random.RandomState(seed=self.config.downsampleRandomSeed)
 
        self.log.info(
            "Down-sampling from %d to %d psf candidates.",
            len(inputCandidateList),
            self.config.maxCandidates,
        )
 
        selection = rng.choice(len(inputCandidateList), size=self.config.maxCandidates, replace=False)
        selection = np.sort(selection)
 
        outputCandidateList = [inputCandidateList[index] for index in selection]
 
        return outputCandidateList
 

Member Data Documentation

◆ _DefaultName

str lsst.meas.algorithms.psfDeterminer.BasePsfDeterminerTask._DefaultName = "psfDeterminer"

staticprotected

Definition at line 70 of file psfDeterminer.py.

◆ ConfigClass

lsst.meas.algorithms.psfDeterminer.BasePsfDeterminerTask.ConfigClass = BasePsfDeterminerConfig

static

Definition at line 69 of file psfDeterminer.py.

◆ usesMatches

bool lsst.meas.algorithms.psfDeterminer.BasePsfDeterminerTask.usesMatches = False

static

Definition at line 68 of file psfDeterminer.py.

The documentation for this class was generated from the following file:

/j/snowflake/release/lsstsw/stack/lsst-scipipe-10.0.0/Linux64/meas_algorithms/g9f7030ddb1+11b9b6f027/python/lsst/meas/algorithms/psfDeterminer.py

Public Member Functions

Static Public Attributes

Static Protected Attributes