LSST Applications  21.0.0+04719a4bac,21.0.0-1-ga51b5d4+f5e6047307,21.0.0-11-g2b59f77+a9c1acf22d,21.0.0-11-ga42c5b2+86977b0b17,21.0.0-12-gf4ce030+76814010d2,21.0.0-13-g1721dae+760e7a6536,21.0.0-13-g3a573fe+768d78a30a,21.0.0-15-g5a7caf0+f21cbc5713,21.0.0-16-g0fb55c1+b60e2d390c,21.0.0-19-g4cded4ca+71a93a33c0,21.0.0-2-g103fe59+bb20972958,21.0.0-2-g45278ab+04719a4bac,21.0.0-2-g5242d73+3ad5d60fb1,21.0.0-2-g7f82c8f+8babb168e8,21.0.0-2-g8f08a60+06509c8b61,21.0.0-2-g8faa9b5+616205b9df,21.0.0-2-ga326454+8babb168e8,21.0.0-2-gde069b7+5e4aea9c2f,21.0.0-2-gecfae73+1d3a86e577,21.0.0-2-gfc62afb+3ad5d60fb1,21.0.0-25-g1d57be3cd+e73869a214,21.0.0-3-g357aad2+ed88757d29,21.0.0-3-g4a4ce7f+3ad5d60fb1,21.0.0-3-g4be5c26+3ad5d60fb1,21.0.0-3-g65f322c+e0b24896a3,21.0.0-3-g7d9da8d+616205b9df,21.0.0-3-ge02ed75+a9c1acf22d,21.0.0-4-g591bb35+a9c1acf22d,21.0.0-4-g65b4814+b60e2d390c,21.0.0-4-gccdca77+0de219a2bc,21.0.0-4-ge8a399c+6c55c39e83,21.0.0-5-gd00fb1e+05fce91b99,21.0.0-6-gc675373+3ad5d60fb1,21.0.0-64-g1122c245+4fb2b8f86e,21.0.0-7-g04766d7+cd19d05db2,21.0.0-7-gdf92d54+04719a4bac,21.0.0-8-g5674e7b+d1bd76f71f,master-gac4afde19b+a9c1acf22d,w.2021.13
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)