LSST Applications  21.0.0-172-gfb10e10a+18fedfabac,22.0.0+297cba6710,22.0.0+80564b0ff1,22.0.0+8d77f4f51a,22.0.0+a28f4c53b1,22.0.0+dcf3732eb2,22.0.1-1-g7d6de66+2a20fdde0d,22.0.1-1-g8e32f31+297cba6710,22.0.1-1-geca5380+7fa3b7d9b6,22.0.1-12-g44dc1dc+2a20fdde0d,22.0.1-15-g6a90155+515f58c32b,22.0.1-16-g9282f48+790f5f2caa,22.0.1-2-g92698f7+dcf3732eb2,22.0.1-2-ga9b0f51+7fa3b7d9b6,22.0.1-2-gd1925c9+bf4f0e694f,22.0.1-24-g1ad7a390+a9625a72a8,22.0.1-25-g5bf6245+3ad8ecd50b,22.0.1-25-gb120d7b+8b5510f75f,22.0.1-27-g97737f7+2a20fdde0d,22.0.1-32-gf62ce7b1+aa4237961e,22.0.1-4-g0b3f228+2a20fdde0d,22.0.1-4-g243d05b+871c1b8305,22.0.1-4-g3a563be+32dcf1063f,22.0.1-4-g44f2e3d+9e4ab0f4fa,22.0.1-42-gca6935d93+ba5e5ca3eb,22.0.1-5-g15c806e+85460ae5f3,22.0.1-5-g58711c4+611d128589,22.0.1-5-g75bb458+99c117b92f,22.0.1-6-g1c63a23+7fa3b7d9b6,22.0.1-6-g50866e6+84ff5a128b,22.0.1-6-g8d3140d+720564cf76,22.0.1-6-gd805d02+cc5644f571,22.0.1-8-ge5750ce+85460ae5f3,master-g6e05de7fdc+babf819c66,master-g99da0e417a+8d77f4f51a,w.2021.48
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)