Inheritance diagram for lsst.pipe.tasks.interpImage.InterpImageTask:

Public Member Functions
	run (self, image, planeName=None, fwhmPixels=None, defects=None)

	transposeContext (self, maskedImage, defects)

	interpolateImage (self, maskedImage, psf, defectList, fallbackValue)

Static Public Attributes
	ConfigClass = InterpImageConfig

Protected Member Functions
	_setFallbackValue (self, mi=None)

Static Protected Attributes
str	_DefaultName = "interpImage"

Detailed Description

Interpolate over bad image pixels

Definition at line 85 of file interpImage.py.

Member Function Documentation

◆ _setFallbackValue()

lsst.pipe.tasks.interpImage.InterpImageTask._setFallbackValue	(		self,
			mi = None )

protected

Set the edge fallbackValue for interpolation

Parameters
----------
mi : `lsst.afw.image.MaskedImage`, optional
    Input maskedImage on which to calculate the statistics
    Must be provided if fallbackValueType != "USER".

Returns
-------
fallbackValue : `float`
    The value set/computed based on the fallbackValueType
    and negativeFallbackAllowed config parameters.

Definition at line 91 of file interpImage.py.

    def _setFallbackValue(self, mi=None):
        """Set the edge fallbackValue for interpolation
 
        Parameters
        ----------
        mi : `lsst.afw.image.MaskedImage`, optional
            Input maskedImage on which to calculate the statistics
            Must be provided if fallbackValueType != "USER".
 
        Returns
        -------
        fallbackValue : `float`
            The value set/computed based on the fallbackValueType
            and negativeFallbackAllowed config parameters.
        """
        if self.config.fallbackValueType != 'USER':
            assert mi, "No maskedImage provided"
        if self.config.fallbackValueType == 'MEAN':
            fallbackValue = afwMath.makeStatistics(mi, afwMath.MEAN).getValue()
        elif self.config.fallbackValueType == 'MEDIAN':
            fallbackValue = afwMath.makeStatistics(mi, afwMath.MEDIAN).getValue()
        elif self.config.fallbackValueType == 'MEANCLIP':
            fallbackValue = afwMath.makeStatistics(mi, afwMath.MEANCLIP).getValue()
        elif self.config.fallbackValueType == 'USER':
            fallbackValue = self.config.fallbackUserValue
        else:
            raise NotImplementedError("%s : %s not implemented" %
                                      ("fallbackValueType", self.config.fallbackValueType))
 
        if not self.config.negativeFallbackAllowed and fallbackValue < 0.0:
            self.log.warning("Negative interpolation edge fallback value computed but "
                             "negativeFallbackAllowed is False: setting fallbackValue to 0.0")
            fallbackValue = max(fallbackValue, 0.0)
 
        self.log.info("fallbackValueType %s has been set to %.4f",
                      self.config.fallbackValueType, fallbackValue)
 
        return fallbackValue
 

◆ interpolateImage()

lsst.pipe.tasks.interpImage.InterpImageTask.interpolateImage	(	self,
		maskedImage,
		psf,
		defectList,
		fallbackValue )

Interpolate over defects in an image

Parameters
----------
maskedImage : `lsst.afw.image.MaskedImage`
    Image on which to perform interpolation.
psf : `lsst.afw.detection.Psf`
    Point-spread function; currently unused.
defectList : `lsst.meas.algorithms.Defects`
    List of defects to interpolate over.
fallbackValue : `float`
    Value to set when interpolation fails.

Definition at line 251 of file interpImage.py.

    def interpolateImage(self, maskedImage, psf, defectList, fallbackValue):
        """Interpolate over defects in an image
 
        Parameters
        ----------
        maskedImage : `lsst.afw.image.MaskedImage`
            Image on which to perform interpolation.
        psf : `lsst.afw.detection.Psf`
            Point-spread function; currently unused.
        defectList : `lsst.meas.algorithms.Defects`
            List of defects to interpolate over.
        fallbackValue : `float`
            Value to set when interpolation fails.
        """
        if not defectList:
            return
        with self.transposeContext(maskedImage, defectList) as (image, defects):
            measAlg.interpolateOverDefects(image, psf, defects, fallbackValue,
                                           self.config.useFallbackValueAtEdge)

◆ run()

lsst.pipe.tasks.interpImage.InterpImageTask.run	(	self,
		image,
		planeName = None,
		fwhmPixels = None,
		defects = None )

Interpolate in place over pixels in a maskedImage marked as bad

Pixels to be interpolated are set by either a mask planeName provided
by the caller OR a defects list of type `~lsst.meas.algorithms.Defects`
If both are provided an exception is raised.

Note that the interpolation code in meas_algorithms currently doesn't
use the input PSF (though it's a required argument), so it's not
important to set the input PSF parameters exactly.  This PSF is set
here as the psf attached to the "image" (i.e if the image passed in
is an Exposure).  Otherwise, a psf model is created using
measAlg.GaussianPsfFactory with the value of fwhmPixels (the value
passed in by the caller, or the default defaultFwhm set in
measAlg.GaussianPsfFactory if None).

Parameters
----------
image : `lsst.afw.image.MaskedImage` or `lsst.afw.image.exposure.Exposure`
    MaskedImage OR Exposure to be interpolated.
planeName : `str`, optional
    Name of mask plane over which to interpolate.
    If None, must provide a defects list.
fwhmPixels : `int`, optional
    FWHM of core star (pixels).
    If None the default is used, where the default
    is set to the exposure psf if available.
defects : `lsst.meas.algorithms.Defects`, optional
    List of defects of type ipIsr.Defects
    over which to interpolate.

Definition at line 131 of file interpImage.py.

    def run(self, image, planeName=None, fwhmPixels=None, defects=None):
        """Interpolate in place over pixels in a maskedImage marked as bad
 
        Pixels to be interpolated are set by either a mask planeName provided
        by the caller OR a defects list of type `~lsst.meas.algorithms.Defects`
        If both are provided an exception is raised.
 
        Note that the interpolation code in meas_algorithms currently doesn't
        use the input PSF (though it's a required argument), so it's not
        important to set the input PSF parameters exactly.  This PSF is set
        here as the psf attached to the "image" (i.e if the image passed in
        is an Exposure).  Otherwise, a psf model is created using
        measAlg.GaussianPsfFactory with the value of fwhmPixels (the value
        passed in by the caller, or the default defaultFwhm set in
        measAlg.GaussianPsfFactory if None).
 
        Parameters
        ----------
        image : `lsst.afw.image.MaskedImage` or `lsst.afw.image.exposure.Exposure`
            MaskedImage OR Exposure to be interpolated.
        planeName : `str`, optional
            Name of mask plane over which to interpolate.
            If None, must provide a defects list.
        fwhmPixels : `int`, optional
            FWHM of core star (pixels).
            If None the default is used, where the default
            is set to the exposure psf if available.
        defects : `lsst.meas.algorithms.Defects`, optional
            List of defects of type ipIsr.Defects
            over which to interpolate.
        """
        try:
            maskedImage = image.getMaskedImage()
        except AttributeError:
            maskedImage = image
 
        # set defectList from defects OR mask planeName provided
        if planeName is None:
            if defects is None:
                raise ValueError("No defects or plane name provided")
            else:
                if not isinstance(defects, ipIsr.Defects):
                    defectList = ipIsr.Defects(defects)
                else:
                    defectList = defects
                planeName = "defects"
        else:
            if defects is not None:
                raise ValueError("Provide EITHER a planeName OR a list of defects, not both")
            if planeName not in maskedImage.getMask().getMaskPlaneDict():
                raise ValueError("maskedImage does not contain mask plane %s" % planeName)
            defectList = ipIsr.Defects.fromMask(maskedImage, planeName)
 
        # set psf from exposure if provided OR using modelPsf with fwhmPixels provided
        try:
            psf = image.getPsf()
            self.log.info("Setting psf for interpolation from image")
        except AttributeError:
            self.log.info("Creating psf model for interpolation from fwhm(pixels) = %s",
                          str(fwhmPixels) if fwhmPixels is not None else
                          (str(self.config.modelPsf.defaultFwhm)) + " [default]")
            psf = self.config.modelPsf.apply(fwhm=fwhmPixels)
 
        fallbackValue = 0.0  # interpolateOverDefects needs this to be a float, regardless if it is used
        if self.config.useFallbackValueAtEdge:
            fallbackValue = self._setFallbackValue(maskedImage)
 
        self.interpolateImage(maskedImage, psf, defectList, fallbackValue)
 
        self.log.info("Interpolated over %d %s pixels.", len(defectList), planeName)
 

◆ transposeContext()

lsst.pipe.tasks.interpImage.InterpImageTask.transposeContext	(	self,
		maskedImage,
		defects )

Context manager to potentially transpose an image

This applies the ``transpose`` configuration setting.

Transposing the image allows us to interpolate along columns instead
of rows, which is useful when the saturation trails are typically
oriented along rows on the warped/coadded images, instead of along
columns as they typically are in raw CCD images.

Parameters
----------
maskedImage : `lsst.afw.image.MaskedImage`
    Image on which to perform interpolation.
defects : `lsst.meas.algorithms.Defects`
    List of defects to interpolate over.

Yields
------
useImage : `lsst.afw.image.MaskedImage`
    Image to use for interpolation; it may have been transposed.
useDefects : `lsst.meas.algorithms.Defects`
    List of defects to use for interpolation; they may have been
    transposed.

Definition at line 203 of file interpImage.py.

    def transposeContext(self, maskedImage, defects):
        """Context manager to potentially transpose an image
 
        This applies the ``transpose`` configuration setting.
 
        Transposing the image allows us to interpolate along columns instead
        of rows, which is useful when the saturation trails are typically
        oriented along rows on the warped/coadded images, instead of along
        columns as they typically are in raw CCD images.
 
        Parameters
        ----------
        maskedImage : `lsst.afw.image.MaskedImage`
            Image on which to perform interpolation.
        defects : `lsst.meas.algorithms.Defects`
            List of defects to interpolate over.
 
        Yields
        ------
        useImage : `lsst.afw.image.MaskedImage`
            Image to use for interpolation; it may have been transposed.
        useDefects : `lsst.meas.algorithms.Defects`
            List of defects to use for interpolation; they may have been
            transposed.
        """
        def transposeImage(image):
            """Transpose an image
 
            Parameters
            ----------
            image : `Unknown`
            """
            transposed = image.array.T.copy()  # Copy to force row-major; required for ndarray+pybind
            return image.Factory(transposed, False, lsst.geom.Point2I(*reversed(image.getXY0())))
 
        useImage = maskedImage
        useDefects = defects
        if self.config.transpose:
            useImage = afwImage.makeMaskedImage(transposeImage(maskedImage.image),
                                                transposeImage(maskedImage.mask),
                                                transposeImage(maskedImage.variance))
            useDefects = defects.transpose()
        yield useImage, useDefects
        if self.config.transpose:
            maskedImage.image.array = useImage.image.array.T
            maskedImage.mask.array = useImage.mask.array.T
            maskedImage.variance.array = useImage.variance.array.T
 

Member Data Documentation

◆ _DefaultName

str lsst.pipe.tasks.interpImage.InterpImageTask._DefaultName = "interpImage"

staticprotected

Definition at line 89 of file interpImage.py.

◆ ConfigClass

lsst.pipe.tasks.interpImage.InterpImageTask.ConfigClass = InterpImageConfig

static

Definition at line 88 of file interpImage.py.

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

/j/snowflake/release/lsstsw/stack/lsst-scipipe-8.0.0/Linux64/pipe_tasks/g2a9a014e59+6f9be1b9cd/python/lsst/pipe/tasks/interpImage.py

Public Member Functions

Static Public Attributes

Protected Member Functions

Static Protected Attributes