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LSST Applications g04a91732dc+7fec47d7bc,g07dc498a13+5ab4d22ec3,g0fba68d861+565de8e5d5,g1409bbee79+5ab4d22ec3,g1a7e361dbc+5ab4d22ec3,g1fd858c14a+11200c7927,g20f46db602+25d63fd678,g35bb328faa+fcb1d3bbc8,g4d2262a081+61302e889d,g4d39ba7253+d05e267ece,g4e0f332c67+5d362be553,g53246c7159+fcb1d3bbc8,g60b5630c4e+d05e267ece,g78460c75b0+2f9a1b4bcd,g786e29fd12+cf7ec2a62a,g7b71ed6315+fcb1d3bbc8,g8048e755c2+a1301e4c20,g8852436030+163ceb82d8,g89139ef638+5ab4d22ec3,g89e1512fd8+fbb808ebce,g8d6b6b353c+d05e267ece,g9125e01d80+fcb1d3bbc8,g989de1cb63+5ab4d22ec3,g9f33ca652e+8abe617c77,ga9baa6287d+d05e267ece,gaaedd4e678+5ab4d22ec3,gabe3b4be73+1e0a283bba,gb1101e3267+fefe9ce5b1,gb58c049af0+f03b321e39,gb90eeb9370+824c420ec4,gc741bbaa4f+77ddc33078,gcf25f946ba+163ceb82d8,gd315a588df+0f88d5218e,gd6cbbdb0b4+c8606af20c,gd9a9a58781+fcb1d3bbc8,gde0f65d7ad+e6bd566e97,ge278dab8ac+932305ba37,ge82c20c137+76d20ab76d,w.2025.10
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lsst.meas.algorithms.pcaPsfDeterminer Namespace Reference

Classes

class  PcaPsfDeterminerConfig
 
class  PcaPsfDeterminerTask
 

Functions

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

Function Documentation

◆ candidatesIter()

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 631 of file pcaPsfDeterminer.py.

631def candidatesIter(psfCellSet, ignoreBad=True):
632 """Generator for Psf candidates.
633
634 This allows two 'for' loops to be reduced to one.
635
636 Parameters
637 ----------
638 psfCellSet : `lsst.afw.math.SpatialCellSet`
639 SpatialCellSet of PSF candidates.
640 ignoreBad : `bool`, optional
641 Ignore candidates flagged as BAD?
642
643 Yields
644 -------
645 cell : `lsst.afw.math.SpatialCell`
646 A SpatialCell.
647 cand : `lsst.meas.algorithms.PsfCandidate`
648 A PsfCandidate.
649 """
650 for cell in psfCellSet.getCellList():
651 for cand in cell.begin(ignoreBad):
652 yield (cell, cand)
653
654

◆ numCandidatesToReject()

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 43 of file pcaPsfDeterminer.py.

43def numCandidatesToReject(numBadCandidates, numIter, totalIter):
44 """Return the number of PSF candidates to be rejected.
45
46 The number of candidates being rejected on each iteration gradually
47 increases, so that on the Nth of M iterations we reject N/M of the bad
48 candidates.
49
50 Parameters
51 ----------
52 numBadCandidates : `int`
53 Number of bad candidates under consideration.
54
55 numIter : `int`
56 The number of the current PSF iteration.
57
58 totalIter : `int`
59 The total number of PSF iterations.
60
61 Returns
62 -------
63 return : `int`
64 Number of candidates to reject.
65 """
66 return int(numBadCandidates*(numIter + 1)//totalIter + 0.5)
67
68