ZogyTask

class lsst.ip.diffim.ZogyTask(templateExposure=None, scienceExposure=None, sig1=None, sig2=None, psf1=None, psf2=None, *args, **kwargs)

Bases: lsst.pipe.base.Task

Task to perform ZOGY proper image subtraction. See module-level documentation for additional details.

In all methods, im1 is R (reference, or template) and im2 is N (new, or science).

Methods Summary

computeDiffim([inImageSpace, padSize, …]) Wrapper method to compute ZOGY proper diffim
computeDiffimFourierSpace([debug, …]) Compute ZOGY diffim D as proscribed in ZOGY (2016) manuscript
computeDiffimImageSpace([padSize, debug]) Compute ZOGY diffim D using image-space convlutions
computeDiffimPsf([padSize, keepFourier, …]) Compute the ZOGY diffim PSF (ZOGY manuscript eq.
computePrereqs([psf1, psf2, padSize]) Compute standard ZOGY quantities used by (nearly) all methods.
computeScorr([xVarAst, yVarAst, …]) Wrapper method to compute ZOGY corrected likelihood image, optimal for source detection
computeScorrFourierSpace([xVarAst, yVarAst]) Compute corrected likelihood image, optimal for source detection
computeScorrImageSpace([xVarAst, yVarAst, …]) Compute corrected likelihood image, optimal for source detection
setup([templateExposure, scienceExposure, …]) Set up the ZOGY task.

Methods Documentation

computeDiffim(inImageSpace=None, padSize=None, returnMatchedTemplate=False, **kwargs)

Wrapper method to compute ZOGY proper diffim

This method should be used as the public interface for computing the ZOGY diffim.

Parameters:
inImageSpace : bool

Override config inImageSpace parameter

padSize : int

Override config padSize parameter

returnMatchedTemplate : bool

Include the PSF-matched template in the results Struct

**kwargs : dict

additional keyword arguments to be passed to computeDiffimFourierSpace or computeDiffimImageSpace.
Returns:
An lsst.pipe.base.Struct containing:
  • D : lsst.afw.Exposure

    the proper image difference, including correct variance, masks, and PSF

  • R : lsst.afw.Exposure

    If returnMatchedTemplate is True, the PSF-matched template exposure
computeDiffimFourierSpace(debug=False, returnMatchedTemplate=False, **kwargs)

Compute ZOGY diffim D as proscribed in ZOGY (2016) manuscript

Compute the ZOGY eqn. (13): $$ widehat{D} =
rac{Frwidehat{Pr}widehat{N} -
F_nwidehat{Pn}widehat{R}}{sqrt{sigma_n^2 Fr^2 |widehat{Pr}|^2 + sigma_r^2 F_n^2 |widehat{Pn}|^2}} $$ where $D$ is the optimal difference image, $R$ and $N$ are the reference and “new” image, respectively, $Pr$ and $P_n$ are their PSFs, $Fr$ and $Fn$ are their flux-based zero-points (which we will set to one here), $sigma_r^2$ and $sigma_n^2$ are their variance, and $widehat{D}$ denotes the FT of $D$.
Returns:
A `lsst.pipe.base.Struct` containing:
computeDiffimImageSpace(padSize=None, debug=False, **kwargs)

Compute ZOGY diffim D using image-space convlutions

This method is still being debugged as it results in artifacts when the PSFs are noisy (see module-level docstring). Thus there are several options still enabled by the debug flag, which are disabled by defult.

Parameters:
padSize : int, the amount to pad the PSFs by
debug : bool, flag to enable debugging tests and options
Returns:
D : lsst.afw.Exposure

the proper image difference, including correct variance, masks, and PSF
computeDiffimPsf(padSize=0, keepFourier=False, psf1=None, psf2=None)

Compute the ZOGY diffim PSF (ZOGY manuscript eq. 14)

Parameters:
padSize : int

Override config padSize parameter

keepFourier : bool

Return the FFT of the diffim PSF (do not inverse-FFT it)

psf1 : 2D numpy.array

(Optional) Input psf of template, override if already padded

psf2 : 2D numpy.array

(Optional) Input psf of science image, override if already padded
Returns:
Pd : 2D numpy.array, the diffim PSF (or FFT of PSF if keepFourier=True)
computePrereqs(psf1=None, psf2=None, padSize=0)

Compute standard ZOGY quantities used by (nearly) all methods.

Many of the ZOGY calculations require similar quantities, including FFTs of the PSFs, and the “denominator” term (e.g. in eq. 13 of ZOGY manuscript (2016). This function consolidates many of those operations.

Parameters:
psf1 : 2D numpy.array

(Optional) Input psf of template, override if already padded

psf2 : 2D numpy.array

(Optional) Input psf of science image, override if already padded
Returns:
A lsst.pipe.base.Struct containing:
- Pr : 2D numpy.array, the (possibly zero-padded) template PSF
- Pn : 2D numpy.array, the (possibly zero-padded) science PSF
- Pr_hat : 2D numpy.array, the FFT of Pr
- Pn_hat : 2D numpy.array, the FFT of Pn
- denom : 2D numpy.array, the denominator of equation (13) in ZOGY (2016) manuscript
- Fd : float, the relative flux scaling factor between science and template
computeScorr(xVarAst=0.0, yVarAst=0.0, inImageSpace=None, padSize=0, **kwargs)

Wrapper method to compute ZOGY corrected likelihood image, optimal for source detection

This method should be used as the public interface for computing the ZOGY S_corr.

Parameters:
xVarAst, yVarAst : float

estimated astrometric noise (variance of astrometric registration errors)

inImageSpace : bool

Override config inImageSpace parameter

padSize : int

Override config padSize parameter
Returns:
S : lsst.afw.image.Exposure, the likelihood exposure S (eq. 12 of ZOGY (2016)),

including corrected variance, masks, and PSF
computeScorrFourierSpace(xVarAst=0.0, yVarAst=0.0, **kwargs)

Compute corrected likelihood image, optimal for source detection

Compute ZOGY S_corr image. This image can be thresholded for detection without optimal filtering, and the variance image is corrected to account for astrometric noise (errors in astrometric registration whether systematic or due to effects such as DCR). The calculations here are all performed in Fourier space, as proscribed in ZOGY (2016).

Parameters:
xVarAst, yVarAst : float

estimated astrometric noise (variance of astrometric registration errors)
Returns:
A lsst.pipe.base.Struct containing:
- S : numpy.array, the likelihood image S (eq. 12 of ZOGY (2016))
- S_var : the corrected variance image (denominator of eq. 25 of ZOGY (2016))
- Dpsf : the PSF of the diffim D, likely never to be used.
computeScorrImageSpace(xVarAst=0.0, yVarAst=0.0, padSize=None, **kwargs)

Compute corrected likelihood image, optimal for source detection

Compute ZOGY S_corr image. This image can be thresholded for detection without optimal filtering, and the variance image is corrected to account for astrometric noise (errors in astrometric registration whether systematic or due to effects such as DCR). The calculations here are all performed in Real (image) space.

Parameters:
xVarAst, yVarAst : float

estimated astrometric noise (variance of astrometric registration errors)
Returns:
a tuple containing:
- S : lsst.afw.image.Exposure, the likelihood exposure S (eq. 12 of ZOGY (2016)),

including corrected variance, masks, and PSF

- D : lsst.afw.image.Exposure, the proper image difference, including correct

variance, masks, and PSF
setup(templateExposure=None, scienceExposure=None, sig1=None, sig2=None, psf1=None, psf2=None, correctBackground=False, *args, **kwargs)

Set up the ZOGY task.

Parameters:
templateExposure : lsst.afw.image.Exposure

Template exposure (“Reference image” in ZOGY (2016)).

scienceExposure : lsst.afw.image.Exposure

Science exposure (“New image” in ZOGY (2016)). Must have already been registered and photmetrically matched to template.

sig1 : float

(Optional) sqrt(variance) of templateExposure. If None, it is computed from the sqrt(mean) of the templateExposure variance image.

sig2 : float

(Optional) sqrt(variance) of scienceExposure. If None, it is computed from the sqrt(mean) of the scienceExposure variance image.

psf1 : 2D numpy.array

(Optional) 2D array containing the PSF image for the template. If None, it is extracted from the PSF taken at the center of templateExposure.

psf2 : 2D numpy.array

(Optional) 2D array containing the PSF image for the science img. If None, it is extracted from the PSF taken at the center of scienceExposure.

correctBackground : bool

(Optional) subtract sigma-clipped mean of exposures. Zogy doesn’t correct nonzero backgrounds (unlike AL) so subtract them here.

args :

additional arguments to be passed to lsst.pipe.base.task.Task.__init__

kwargs :

additional keyword arguments to be passed to lsst.pipe.base.task.Task.__init__