LSST Applications  21.0.0-147-g0e635eb1+1acddb5be5,22.0.0+052faf71bd,22.0.0+1ea9a8b2b2,22.0.0+6312710a6c,22.0.0+729191ecac,22.0.0+7589c3a021,22.0.0+9f079a9461,22.0.1-1-g7d6de66+b8044ec9de,22.0.1-1-g87000a6+536b1ee016,22.0.1-1-g8e32f31+6312710a6c,22.0.1-10-gd060f87+016f7cdc03,22.0.1-12-g9c3108e+df145f6f68,22.0.1-16-g314fa6d+c825727ab8,22.0.1-19-g93a5c75+d23f2fb6d8,22.0.1-19-gb93eaa13+aab3ef7709,22.0.1-2-g8ef0a89+b8044ec9de,22.0.1-2-g92698f7+9f079a9461,22.0.1-2-ga9b0f51+052faf71bd,22.0.1-2-gac51dbf+052faf71bd,22.0.1-2-gb66926d+6312710a6c,22.0.1-2-gcb770ba+09e3807989,22.0.1-20-g32debb5+b8044ec9de,22.0.1-23-gc2439a9a+fb0756638e,22.0.1-3-g496fd5d+09117f784f,22.0.1-3-g59f966b+1e6ba2c031,22.0.1-3-g849a1b8+f8b568069f,22.0.1-3-gaaec9c0+c5c846a8b1,22.0.1-32-g5ddfab5d3+60ce4897b0,22.0.1-4-g037fbe1+64e601228d,22.0.1-4-g8623105+b8044ec9de,22.0.1-5-g096abc9+d18c45d440,22.0.1-5-g15c806e+57f5c03693,22.0.1-7-gba73697+57f5c03693,master-g6e05de7fdc+c1283a92b8,master-g72cdda8301+729191ecac,w.2021.39
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 651 of file pcaPsfDeterminer.py.

651 def candidatesIter(psfCellSet, ignoreBad=True):
652  """Generator for Psf candidates.
653 
654  This allows two 'for' loops to be reduced to one.
655 
656  Parameters
657  ----------
658  psfCellSet : `lsst.afw.math.SpatialCellSet`
659  SpatialCellSet of PSF candidates.
660  ignoreBad : `bool`, optional
661  Ignore candidates flagged as BAD?
662 
663  Yields
664  -------
665  cell : `lsst.afw.math.SpatialCell`
666  A SpatialCell.
667  cand : `lsst.meas.algorithms.PsfCandidate`
668  A PsfCandidate.
669  """
670  for cell in psfCellSet.getCellList():
671  for cand in cell.begin(ignoreBad):
672  yield (cell, cand)
673 
674 
675 psfDeterminerRegistry.register("pca", PcaPsfDeterminerTask)
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.

44 def 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)