LSSTApplications  18.0.0+106,18.0.0+50,19.0.0,19.0.0+1,19.0.0+10,19.0.0+11,19.0.0+13,19.0.0+17,19.0.0+2,19.0.0-1-g20d9b18+6,19.0.0-1-g425ff20,19.0.0-1-g5549ca4,19.0.0-1-g580fafe+6,19.0.0-1-g6fe20d0+1,19.0.0-1-g7011481+9,19.0.0-1-g8c57eb9+6,19.0.0-1-gb5175dc+11,19.0.0-1-gdc0e4a7+9,19.0.0-1-ge272bc4+6,19.0.0-1-ge3aa853,19.0.0-10-g448f008b,19.0.0-12-g6990b2c,19.0.0-2-g0d9f9cd+11,19.0.0-2-g3d9e4fb2+11,19.0.0-2-g5037de4,19.0.0-2-gb96a1c4+3,19.0.0-2-gd955cfd+15,19.0.0-3-g2d13df8,19.0.0-3-g6f3c7dc,19.0.0-4-g725f80e+11,19.0.0-4-ga671dab3b+1,19.0.0-4-gad373c5+3,19.0.0-5-ga2acb9c+2,19.0.0-5-gfe96e6c+2,w.2020.01
LSSTDataManagementBasePackage
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)
676 
lsst::meas::algorithms.pcaPsfDeterminer.candidatesIter
def candidatesIter(psfCellSet, ignoreBad=True)
Definition: pcaPsfDeterminer.py:651

◆ 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 
lsst::meas::algorithms.pcaPsfDeterminer.numCandidatesToReject
def numCandidatesToReject(numBadCandidates, numIter, totalIter)
Definition: pcaPsfDeterminer.py:44
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