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LSST Data Management Base Package
Classes | Functions
lsst.meas.algorithms.pcaPsfDeterminer Namespace Reference

Classes

class  PcaPsfDeterminerConfig
 
class  PcaPsfDeterminerTask
 

Functions

def numCandidatesToReject (numBadCandidates, numIter, totalIter)
 
def candidatesIter (psfCellSet, ignoreBad=True)
 

Function Documentation

◆ candidatesIter()

def lsst.meas.algorithms.pcaPsfDeterminer.candidatesIter (   psfCellSet,
  ignoreBad = True 
)
Generator for Psf candidates.

This allows two 'for' loops to be reduced to one.

Parameters
----------
psfCellSet : `lsst.afw.math.SpatialCellSet`
   SpatialCellSet of PSF candidates.
ignoreBad : `bool`, optional
   Ignore candidates flagged as BAD?

Yields
-------
cell : `lsst.afw.math.SpatialCell`
   A SpatialCell.
cand : `lsst.meas.algorithms.PsfCandidate`
  A PsfCandidate.

Definition at line 652 of file pcaPsfDeterminer.py.

652def candidatesIter(psfCellSet, ignoreBad=True):
653 """Generator for Psf candidates.
654
655 This allows two 'for' loops to be reduced to one.
656
657 Parameters
658 ----------
659 psfCellSet : `lsst.afw.math.SpatialCellSet`
660 SpatialCellSet of PSF candidates.
661 ignoreBad : `bool`, optional
662 Ignore candidates flagged as BAD?
663
664 Yields
665 -------
667 A SpatialCell.
669 A PsfCandidate.
670 """
671 for cell in psfCellSet.getCellList():
672 for cand in cell.begin(ignoreBad):
673 yield (cell, cand)
674
675
676psfDeterminerRegistry.register("pca", PcaPsfDeterminerTask)
Class to ensure constraints for spatial modeling.
Definition: SpatialCell.h:223
A collection of SpatialCells covering an entire image.
Definition: SpatialCell.h:383
Class stored in SpatialCells for spatial Psf fitting.
Definition: PsfCandidate.h:55
def candidatesIter(psfCellSet, ignoreBad=True)

◆ numCandidatesToReject()

def lsst.meas.algorithms.pcaPsfDeterminer.numCandidatesToReject (   numBadCandidates,
  numIter,
  totalIter 
)
Return the number of PSF candidates to be rejected.

The number of candidates being rejected on each iteration gradually
increases, so that on the Nth of M iterations we reject N/M of the bad
candidates.

Parameters
----------
numBadCandidates : `int`
    Number of bad candidates under consideration.

numIter : `int`
    The number of the current PSF iteration.

totalIter : `int`
    The total number of PSF iterations.

Returns
-------
return : `int`
    Number of candidates to reject.

Definition at line 44 of file pcaPsfDeterminer.py.

44def numCandidatesToReject(numBadCandidates, numIter, totalIter):
45 """Return the number of PSF candidates to be rejected.
46
47 The number of candidates being rejected on each iteration gradually
48 increases, so that on the Nth of M iterations we reject N/M of the bad
49 candidates.
50
51 Parameters
52 ----------
53 numBadCandidates : `int`
54 Number of bad candidates under consideration.
55
56 numIter : `int`
57 The number of the current PSF iteration.
58
59 totalIter : `int`
60 The total number of PSF iterations.
61
62 Returns
63 -------
64 return : `int`
65 Number of candidates to reject.
66 """
67 return int(numBadCandidates*(numIter + 1)//totalIter + 0.5)
68
69
def numCandidatesToReject(numBadCandidates, numIter, totalIter)