deblend

lsst.meas.deblender.baseline.deblend(footprint, maskedImage, psf, psffwhm, psfChisqCut1=1.5, psfChisqCut2=1.5, psfChisqCut2b=1.5, fitPsfs=True, medianSmoothTemplate=True, medianFilterHalfsize=2, monotonicTemplate=True, weightTemplates=False, log=None, verbose=False, sigma1=None, maxNumberOfPeaks=0, assignStrayFlux=True, strayFluxToPointSources='necessary', strayFluxAssignment='r-to-peak', rampFluxAtEdge=False, patchEdges=False, tinyFootprintSize=2, getTemplateSum=False, clipStrayFluxFraction=0.001, clipFootprintToNonzero=True, removeDegenerateTemplates=False, maxTempDotProd=0.5)

Deblend a parent Footprint in a MaskedImageF.

Deblending assumes that footprint has multiple peaks, as it will still create a PerFootprint object with a list of peaks even if there is only one peak in the list. It is recommended to first check that footprint has more than one peak, similar to the execution of lsst.meas.deblender.deblend.SourceDeblendTask.

Note

This is the API for the old deblender, however the function builds the plugins necessary to use the new deblender to perform identically to the old deblender. To test out newer functionality use newDeblend instead.

Deblending involves several mandatory and optional steps:

# Optional: If fitPsfs is True, find all peaks that are well-fit by a PSF + background model

  • Peaks that pass the cuts have their footprints modified to the PSF + background model and their deblendedAsPsf property set to True.
  • Relevant parameters: psfChisqCut1, psfChisqCut2, psfChisqCut2b, tinyFootprintSize.
  • See the parameter descriptions for more.

# Build a symmetric template for each peak not well-fit by the PSF model

  • Given maskedImageF, footprint, and a DeblendedPeak, creates a symmetric template (templateImage and templateFootprint) around the peak for all peaks not flagged as skip or deblendedAsPsf.
  • If patchEdges=True and if footprint touches pixels with the EDGE bit set, then footprint is grown to include spans whose symmetric mirror is outside of the image.
  • Relevant parameters: sigma1 and patchEdges.

# Optional: If rampFluxAtEdge is True, adjust flux on the edges of the template footprints

  • Using the PSF, a peak Footprint with pixels on the edge of of footprint is grown by the psffwhm*1.5 and filled in with zeros.
  • The result is a new symmetric footprint template for the peaks near the edge.
  • Relevant parameter: patchEdges.

# Optionally (medianSmoothTemplate=True) filter the template images

  • Apply a median smoothing filter to all of the template images.
  • Relevant parameters: medianFilterHalfSize

# Optional: If monotonicTemplate is True, make the templates monotonic.

  • The pixels in the templates are modified such that pixels further from the peak will have values smaller than those closer to the peak.

# Optional: If clipFootprintToNonzero is True, clip non-zero spans in the template footprints

  • Peak Footprints are clipped to the region in the image containing non-zero values by dropping spans that are completely zero and moving endpoints to non-zero pixels (but does not split spans that have internal zeros).

# Optional: If weightTemplates is True, weight the templates to best fit the observed image

  • Re-weight the templates so that their linear combination best represents the observed maskedImage

# Optional: If removeDegenerateTempaltes is True, reconstruct shredded galaxies

  • If galaxies have substructure, such as face-on spirals, the process of identifying peaks can “shred” the galaxy into many pieces. The templates of shredded galaxies are typically quite similar because they represent the same galaxy, so we try to identify these “degenerate” peaks by looking at the inner product (in pixel space) of pairs of templates.
  • If they are nearly parallel, we only keep one of the peaks and reject the other.
  • If only one of the peaks is a PSF template, the other template is used, otherwise the one with the maximum template value is kept.
  • Relevant parameters: maxTempDotProduct

# Apportion flux to all of the peak templates

  • Divide the maskedImage flux amongst all of the templates based on the fraction of flux assigned to each tempalteFootprint.
  • Leftover “stray flux” is assigned to peaks based on the other parameters.
  • Relevant parameters: clipStrayFluxFraction, strayFluxAssignment, strayFluxToPointSources, assignStrayFlux
Parameters:
footprint: `afw.detection.Footprint`

Parent footprint to deblend

maskedImage: `afw.image.MaskedImageF`

Masked image containing the footprint

psf: `afw.detection.Psf`

Psf of the maskedImage

psffwhm: `float`

FWHM of the maskedImage’s psf

psfChisqCut*: `float`, optional

If fitPsfs==True, all of the peaks are fit to the image PSF. psfChisqCut1 is the maximum chi-squared-per-degree-of-freedom allowed for a peak to be considered a PSF match without recentering. A fit is also made that includes terms to recenter the PSF. psfChisqCut2 is the same as psfChisqCut1 except it determines the restriction on the fit that includes recentering terms. If the peak is a match for a re-centered PSF, the PSF is repositioned at the new center and the peak footprint is fit again, this time to the new PSF. If the resulting chi-squared-per-degree-of-freedom is less than psfChisqCut2b then it passes the re-centering algorithm. If the peak passes both the re-centered and fixed position cuts, the better of the two is accepted, but parameters for all three psf fits are stored in the DeblendedPeak. The default for psfChisqCut1, psfChisqCut2, and psfChisqCut2b is 1.5.

fitPsfs: `bool`, optional

If True then all of the peaks will be compared to the image PSF to distinguish stars from galaxies.

medianSmoothTemplate: ``bool``, optional

If medianSmoothTemplate==True it a median smoothing filter is applied to the maskedImage. The default is True.

medianFilterHalfSize: `int`, optional

Half the box size of the median filter, ie a medianFilterHalfSize of 50 means that each output pixel will be the median of the pixels in a 101 x 101-pixel box in the input image. This parameter is only used when medianSmoothTemplate==True, otherwise it is ignored. The default value is 2.

monotonicTempalte: `bool`, optional

If True then make the template monotonic. The default is True.

weightTemplates: `bool`, optional

If True, re-weight the templates so that their linear combination best represents the observed maskedImage. The default is False.

log: `log.Log`, optional

LSST logger for logging purposes. The default is None (no logging).

verbose: `bool`, optional

Whether or not to show a more verbose output. The default is False.

sigma1: `float`, optional

Average noise level in maskedImage. The default is None, which estimates the noise from the median value of maskedImage.

maxNumberOfPeaks: `int`, optional

If nonzero, the maximum number of peaks to deblend. If the total number of peaks is greater than maxNumberOfPeaks, then only the first maxNumberOfPeaks sources are deblended. The default is 0, which deblends all of the peaks.

assignStrayFlux: `bool`, optional

If True then flux in the parent footprint that is not covered by any of the template footprints is assigned to templates based on their 1/(1+r^2) distance. How the flux is apportioned is determined by strayFluxAssignment. The default is True.

strayFluxToPointSources: `string`

Determines how stray flux is apportioned to point sources

  • never: never apportion stray flux to point sources
  • necessary (default): point sources are included only if there are no extended sources nearby
  • always: point sources are always included in the 1/(1+r^2) splitting
strayFluxAssignment: `string`, optional

Determines how stray flux is apportioned.

  • trim: Trim stray flux and do not include in any footprints
  • r-to-peak (default): Stray flux is assigned based on (1/(1+r^2) from the peaks
  • r-to-footprint: Stray flux is distributed to the footprints based on 1/(1+r^2) of the minimum distance from the stray flux to footprint
  • nearest-footprint: Stray flux is assigned to the footprint with lowest L-1 (Manhattan) distance to the stray flux
rampFluxAtEdge: `bool`, optional

If True then extend footprints with excessive flux on the edges as described above. The default is False.

patchEdges: `bool`, optional

If True and if the footprint touches pixels with the EDGE bit set, then grow the footprint to include all symmetric templates. The default is False.

tinyFootprintSize: `float`, optional

The PSF model is shrunk to the size that contains the original footprint. If the bbox of the clipped PSF model for a peak is smaller than max(tinyFootprintSize,2) then tinyFootprint for the peak is set to True and the peak is not fit. The default is 2.

getTemplateSum: `bool`, optional

As part of the flux calculation, the sum of the templates is calculated. If getTemplateSum==True then the sum of the templates is stored in the result (a PerFootprint). The default is False.

clipStrayFluxFraction: `float`, optional

Minimum stray-flux portion. Any stray-flux portion less than clipStrayFluxFraction is clipped to zero. The default is 0.001.

clipFootprintToNonzero: `bool`, optional

If True then clip non-zero spans in the template footprints. See above for more. The default is True.

removeDegenerateTemplates: `bool`, optional

If True then we try to identify “degenerate” peaks by looking at the inner product (in pixel space) of pairs of templates. The default is False.

maxTempDotProduct: `float`, optional

All dot products between templates greater than maxTempDotProduct will result in one of the templates removed. This parameter is only used when removeDegenerateTempaltes==True. The default is 0.5.
Returns:
res: PerFootprint

Deblender result that contains a list of DeblendedPeaks for each peak and (optionally) the template sum.