PcaPsfDeterminerConfig#
- class lsst.meas.algorithms.PcaPsfDeterminerConfig(*args, **kw)#
Bases:
BasePsfDeterminerConfigAttributes Summary
Number of pixels to ignore around the edge of PSF candidate postage stamps (
int, default0)Should each PSF candidate be given the same weight, independent of magnitude? (
bool, defaultTrue)Mask blends in image? (
bool, defaultTrue)Reject candidates that are blended? (
bool, defaultFalse)Random seed to use to downsample candidates.
floor for variance is lam*data (
float, default0.05)Maximum number of candidates to consider.
number of eigen components for PSF kernel creation (
int, default4)number of iterations of PSF candidate star list (
int, default3)number of stars per psf cell for PSF kernel creation (
int, default3)number of stars per psf Cell for spatial fitting (
int, default5)Use non-linear fitter for spatial variation of Kernel (
bool, defaultFalse)Threshold (stdev) for rejecting extraneous pixels around candidate; applied if positive (
float, default0.0)for psf candidate evaluation (
float, default2.0)size of cell used to determine PSF (pixels, column direction) (
int, default256)size of cell used to determine PSF (pixels, row direction) (
int, default256)specify spatial order for PSF kernel creation (
int, default2)Rejection threshold (stdev) for candidates based on spatial fit (
float, default3.0)Size of the postage stamp (in native pixels) to render the PSF model.
tolerance of spatial fitting (
float, default0.01)Methods Summary
Subclass hook for computing defaults.
Attributes Documentation
- borderWidth#
Number of pixels to ignore around the edge of PSF candidate postage stamps (
int, default0)
- constantWeight#
Should each PSF candidate be given the same weight, independent of magnitude? (
bool, defaultTrue)
- doMaskBlends#
Mask blends in image? (
bool, defaultTrue)
- doRejectBlends#
Reject candidates that are blended? (
bool, defaultFalse)
- downsampleRandomSeed#
Random seed to use to downsample candidates. (
int, default98765)
- lam#
floor for variance is lam*data (
float, default0.05)
- maxCandidates#
Maximum number of candidates to consider. Will down-sample if given more. (
int, default300)
- nEigenComponents#
number of eigen components for PSF kernel creation (
int, default4)
- nIterForPsf#
number of iterations of PSF candidate star list (
int, default3)
- nStarPerCell#
number of stars per psf cell for PSF kernel creation (
int, default3)
- nStarPerCellSpatialFit#
number of stars per psf Cell for spatial fitting (
int, default5)
- nonLinearSpatialFit#
Use non-linear fitter for spatial variation of Kernel (
bool, defaultFalse)
- pixelThreshold#
Threshold (stdev) for rejecting extraneous pixels around candidate; applied if positive (
float, default0.0)
- reducedChi2ForPsfCandidates#
for psf candidate evaluation (
float, default2.0)
- sizeCellX#
size of cell used to determine PSF (pixels, column direction) (
int, default256)
- sizeCellY#
size of cell used to determine PSF (pixels, row direction) (
int, default256)
- spatialOrder#
specify spatial order for PSF kernel creation (
int, default2)
- spatialReject#
Rejection threshold (stdev) for candidates based on spatial fit (
float, default3.0)
- stampSize#
Size of the postage stamp (in native pixels) to render the PSF model. Should be odd. (
int, defaultNone)
- tolerance#
tolerance of spatial fitting (
float, default0.01)
Methods Documentation