lsst.ip.diffim.snapPsfMatch.SnapPsfMatchTask Class Reference

Image-based Psf-matching of two subsequent snaps from the same visit. More...

Inheritance diagram for lsst.ip.diffim.snapPsfMatch.SnapPsfMatchTask:

Public Member Functions
def	subtractExposures

Static Public Attributes
	ConfigClass = SnapPsfMatchConfig

Detailed Description

Image-based Psf-matching of two subsequent snaps from the same visit.

Contents

• Description
• Task initialization
• Invoking the Task
• Configuration parameters
• Quantities set in Metadata
• Debug variables
• A complete example of using SnapPsfMatchTask

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Description

SnapPsfMatchTask

This Task differs from ImagePsfMatchTask in that it matches two Exposures assuming that the images have been acquired very closely in time. Under this assumption, the astrometric misalignments and/or relative distortions should be within a pixel, and the Psf-shapes should be very similar. As a consequence, the default configurations for this class assume a very simple solution.

. The spatial variation in the kernel (SnapPsfMatchConfig.spatialKernelOrder) is assumed to be zero

. With no spatial variation, we turn of the spatial clipping loops (SnapPsfMatchConfig.spatialKernelClipping)

. The differential background is not fit for (SnapPsfMatchConfig.fitForBackground)

. The kernel is expected to be appx. a delta function, and has a small size (SnapPsfMatchConfig.kernelSize)

The sub-configurations for the Alard-Lupton (SnapPsfMatchConfigAL) and delta-function (SnapPsfMatchConfigDF) bases also are designed to generate a small, simple kernel.

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Task initialization

Initialization is the same as base class ImagePsfMatch.__init__, with the difference being that the Task's ConfigClass is SnapPsfMatchConfig.

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Invoking the Task

The Task is only configured to have a subtractExposures method, which in turn calls ImagePsfMatchTask.subtractExposures.

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Configuration parameters

See SnapPsfMatchConfig, which uses either SnapPsfMatchConfigDF and SnapPsfMatchConfigAL as its active configuration.

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Quantities set in Metadata

See PsfMatchTask

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Debug variables

The command line task interface supports a flag -d/–debug to import debug.py from your PYTHONPATH. The relevant contents of debug.py for this Task include:

import sys
import lsstDebug
def DebugInfo(name):
    di = lsstDebug.getInfo(name)   
    if name == "lsst.ip.diffim.psfMatch":
        di.display = True                 # enable debug output
        di.maskTransparency = 80          # ds9 mask transparency
        di.displayCandidates = True       # show all the candidates and residuals
        di.displayKernelBasis = False     # show kernel basis functions
        di.displayKernelMosaic = True     # show kernel realized across the image
        di.plotKernelSpatialModel = False # show coefficients of spatial model
        di.showBadCandidates = True       # show the bad candidates (red) along with good (green)
    elif name == "lsst.ip.diffim.imagePsfMatch":
        di.display = True                 # enable debug output
        di.maskTransparency = 30          # ds9 mask transparency
        di.displayTemplate = True         # show full (remapped) template
        di.displaySciIm = True            # show science image to match to
        di.displaySpatialCells = True     # show spatial cells
        di.displayDiffIm = True           # show difference image
        di.showBadCandidates = True       # show the bad candidates (red) along with good (green) 
    elif name == "lsst.ip.diffim.diaCatalogSourceSelector":
        di.display = False                # enable debug output
        di.maskTransparency = 30          # ds9 mask transparency
        di.displayExposure = True         # show exposure with candidates indicated
        di.pauseAtEnd = False             # pause when done
    return di
lsstDebug.Info = DebugInfo
lsstDebug.frame = 1      

Note that if you want addional logging info, you may add to your scripts:

import lsst.pex.logging as pexLog
pexLog.Trace_setVerbosity('lsst.ip.diffim', 5)

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A complete example of using SnapPsfMatchTask

This code is snapPsfMatchTask.py in the examples directory, and can be run as e.g.

examples/snapPsfMatchTask.py
examples/snapPsfMatchTask.py --debug 
examples/snapPsfMatchTask.py --debug --template /path/to/templateExp.fits --science /path/to/scienceExp.fits

First, create a subclass of SnapPsfMatchTask that accepts two exposures. Ideally these exposures would have been taken back-to-back, such that the pointing/background/Psf does not vary substantially between the two:

class MySnapPsfMatchTask(SnapPsfMatchTask):
    """An override for SnapPsfMatchTask"""
    def __init__(self, *args, **kwargs):
        SnapPsfMatchTask.__init__(self, *args, **kwargs)

    def run(self, templateExp, scienceExp):
        return self.subtractExposures(templateExp, scienceExp)

And allow the user the freedom to either run the script in default mode, or point to their own images on disk. Note that these images must be readable as an lsst.afw.image.Exposure:

if __name__ == "__main__":
    import argparse
    parser = argparse.ArgumentParser(description="Demonstrate the use of ImagePsfMatchTask")

    parser.add_argument("--debug", "-d", action="store_true", help="Load debug.py?", default=False)
    parser.add_argument("--template", "-t", help="Template Exposure to use", default=None)
    parser.add_argument("--science", "-s", help="Science Exposure to use", default=None)

    args = parser.parse_args()

We have enabled some minor display debugging in this script via the –debug option. However, if you have an lsstDebug debug.py in your PYTHONPATH you will get additional debugging displays. The following block checks for this script:

    if args.debug:
        try:
            import debug
            # Since I am displaying 2 images here, set the starting frame number for the LSST debug LSST
            debug.lsstDebug.frame = 3
        except ImportError as e:
            print >> sys.stderr, e

Finally, we call a run method that we define below. First set up a Config and choose the basis set to use:

def run(args):
    #
    # Create the Config and use sum of gaussian basis
    #
    config = SnapPsfMatchTask.ConfigClass()
    config.doWarping = True
    config.kernel.name = "AL"

Make sure the images (if any) that were sent to the script exist on disk and are readable. If no images are sent, make some fake data up for the sake of this example script (have a look at the code if you want more details on generateFakeImages; as a detail of how the fake images were made, you do have to fit for a differential background):

    # Run the requested method of the Task
    if args.template is not None and args.science is not None:
        if not os.path.isfile(args.template):
                raise Exception, "Template image %s does not exist" % (args.template)
        if not os.path.isfile(args.science):
                raise Exception, "Science image %s does not exist" % (args.science)

        try:
                templateExp = afwImage.ExposureF(args.template)
        except pexExcept.LsstCppException, e:
                raise Exception, "Cannot read template image %s" % (args.template)
        try:
                scienceExp = afwImage.ExposureF(args.science)
        except pexExcept.LsstCppException, e:
                raise Exception, "Cannot read science image %s" % (args.science)
    else:
        templateExp, scienceExp = generateFakeImages()
        config.kernel.active.fitForBackground = True
        config.kernel.active.spatialBgOrder = 0
        config.kernel.active.sizeCellX = 128
        config.kernel.active.sizeCellY = 128

Display the two images if –debug:

    if args.debug:
        ds9.mtv(templateExp, frame=1, title="Example script: Input Template")
        ds9.mtv(scienceExp, frame=2, title="Example script: Input Science Image")

Create and run the Task:

    # Create the Task
    psfMatchTask = MySnapPsfMatchTask(config=config)

    # Run the Task
    result = psfMatchTask.run(templateExp, scienceExp)

And finally provide optional debugging display of the Psf-matched (via the Psf models) science image:

    if args.debug:
        # See if the LSST debug has incremented the frame number; if not start with frame 3
        try:
                frame = debug.lsstDebug.frame+1
        except Exception:
                frame = 3
        ds9.mtv(result.matchedExposure, frame=frame, title="Example script: Matched Template Image")
        if result.getDict().has_key("subtractedExposure"):
                ds9.mtv(result.subtractedExposure, frame=frame+1, title="Example script: Subtracted Image")

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Definition at line 87 of file snapPsfMatch.py.

Member Function Documentation

def lsst.ip.diffim.snapPsfMatch.SnapPsfMatchTask.subtractExposures	(		self,
			templateExposure,
			scienceExposure,
			templateFwhmPix = None,
			scienceFwhmPix = None,
			candidateList = None
	)

Definition at line 257 of file snapPsfMatch.py.

                          candidateList = None):
        return ImagePsfMatchTask.subtractExposures(self,
            templateExposure = templateExposure,
            scienceExposure = scienceExposure,
            templateFwhmPix = templateFwhmPix,
            scienceFwhmPix = scienceFwhmPix,
            candidateList = candidateList,
            doWarping = self.config.doWarping,
        )

Member Data Documentation

lsst.ip.diffim.snapPsfMatch.SnapPsfMatchTask.ConfigClass = SnapPsfMatchConfig

static

Definition at line 252 of file snapPsfMatch.py.

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The documentation for this class was generated from the following file:

• /home/lsstsw/stack/Linux64/ip_diffim/11.0+1/python/lsst/ip/diffim/snapPsfMatch.py