Classes
class	CrosstalkConfig

class	CrosstalkTask

class	NullCrosstalkTask

Functions
def	extractAmp (image, amp, corner, isTrimmed=False)

def	calculateBackground (mi, badPixels=["BAD"])

def	subtractCrosstalk (exposure, crosstalkCoeffs=None, badPixels=["BAD"], minPixelToMask=45000, crosstalkStr="CROSSTALK", isTrimmed=False, backgroundMethod="None")

def	writeCrosstalkCoeffs (outputFileName, coeff, det=None, crosstalkName="Unknown", indent=2)

Variables
dictionary	X_FLIP

dictionary	Y_FLIP

Function Documentation

◆ calculateBackground()

def lsst.ip.isr.crosstalk.calculateBackground	(	mi,
		badPixels = `["BAD"]`
	)

Calculate median background in image

Getting a great background model isn't important for crosstalk correction,
since the crosstalk is at a low level. The median should be sufficient.

Parameters
----------
mi : `lsst.afw.image.MaskedImage`
    MaskedImage for which to measure background.
badPixels : `list` of `str`
    Mask planes to ignore.

Returns
-------
bg : `float`
    Median background level.

Definition at line 228 of file crosstalk.py.

 def calculateBackground(mi, badPixels=["BAD"]):
     """Calculate median background in image
 
     Getting a great background model isn't important for crosstalk correction,
     since the crosstalk is at a low level. The median should be sufficient.
 
     Parameters
     ----------
     mi : `lsst.afw.image.MaskedImage`
         MaskedImage for which to measure background.
     badPixels : `list` of `str`
         Mask planes to ignore.
 
     Returns
     -------
     bg : `float`
         Median background level.
     """
     mask = mi.getMask()
     stats = lsst.afw.math.StatisticsControl()
     stats.setAndMask(mask.getPlaneBitMask(badPixels))
     return lsst.afw.math.makeStatistics(mi, lsst.afw.math.MEDIAN, stats).getValue()
 
 

◆ extractAmp()

def lsst.ip.isr.crosstalk.extractAmp	(	image,
		amp,
		corner,
		isTrimmed = `False`
	)

Return an image of the amp

The returned image will have the amp's readout corner in the
nominated `corner`.

Parameters
----------
image : `lsst.afw.image.Image` or `lsst.afw.image.MaskedImage`
    Image containing the amplifier of interest.
amp : `lsst.afw.table.AmpInfoRecord`
    Amplifier information.
corner : `lsst.afw.table.ReadoutCorner` or `None`
    Corner in which to put the amp's readout corner, or `None` for
    no flipping.
isTrimmed : `bool`
    The image is already trimmed.
    This should no longer be needed once DM-15409 is resolved.

Returns
-------
output : `lsst.afw.image.Image`
    Image of the amplifier in the standard configuration.

Definition at line 196 of file crosstalk.py.

 def extractAmp(image, amp, corner, isTrimmed=False):
     """Return an image of the amp
 
     The returned image will have the amp's readout corner in the
     nominated `corner`.
 
     Parameters
     ----------
     image : `lsst.afw.image.Image` or `lsst.afw.image.MaskedImage`
         Image containing the amplifier of interest.
     amp : `lsst.afw.table.AmpInfoRecord`
         Amplifier information.
     corner : `lsst.afw.table.ReadoutCorner` or `None`
         Corner in which to put the amp's readout corner, or `None` for
         no flipping.
     isTrimmed : `bool`
         The image is already trimmed.
         This should no longer be needed once DM-15409 is resolved.
 
     Returns
     -------
     output : `lsst.afw.image.Image`
         Image of the amplifier in the standard configuration.
     """
     output = image[amp.getBBox() if isTrimmed else amp.getRawDataBBox()]
     ampCorner = amp.getReadoutCorner()
     # Flipping is necessary only if the desired configuration doesn't match what we currently have
     xFlip = X_FLIP[corner] ^ X_FLIP[ampCorner]
     yFlip = Y_FLIP[corner] ^ Y_FLIP[ampCorner]
     return lsst.afw.math.flipImage(output, xFlip, yFlip)
 
 

◆ subtractCrosstalk()

def lsst.ip.isr.crosstalk.subtractCrosstalk	(	exposure,
		crosstalkCoeffs = `None`,
		badPixels = `["BAD"]`,
		minPixelToMask = `45000`,
		crosstalkStr = `"CROSSTALK"`,
		isTrimmed = `False`,
		backgroundMethod = `"None"`
	)

Subtract the intra-detector crosstalk from an exposure

We set the mask plane indicated by ``crosstalkStr`` in a target amplifier
for pixels in a source amplifier that exceed `minPixelToMask`. Note that
the correction is applied to all pixels in the amplifier, but only those
that have a substantial crosstalk are masked with ``crosstalkStr``.

The uncorrected image is used as a template for correction. This is good
enough if the crosstalk is small (e.g., coefficients < ~ 1e-3), but if it's
larger you may want to iterate.

This method needs unittests (DM-18876), but such testing requires
DM-18610 to allow the test detector to have the crosstalk
parameters set.

Parameters
----------
exposure : `lsst.afw.image.Exposure`
    Exposure for which to subtract crosstalk.
crosstalkCoeffs : `numpy.ndarray`
    Coefficients to use to correct crosstalk.
badPixels : `list` of `str`
    Mask planes to ignore.
minPixelToMask : `float`
    Minimum pixel value (relative to the background level) in
    source amplifier for which to set ``crosstalkStr`` mask plane
    in target amplifier.
crosstalkStr : `str`
    Mask plane name for pixels greatly modified by crosstalk.
isTrimmed : `bool`
    The image is already trimmed.
    This should no longer be needed once DM-15409 is resolved.
backgroundMethod : `str`
    Method used to subtract the background.  "AMP" uses
    amplifier-by-amplifier background levels, "DETECTOR" uses full
    exposure/maskedImage levels.  Any other value results in no
    background subtraction.

Definition at line 255 of file crosstalk.py.

                       backgroundMethod="None"):
     """Subtract the intra-detector crosstalk from an exposure
 
     We set the mask plane indicated by ``crosstalkStr`` in a target amplifier
     for pixels in a source amplifier that exceed `minPixelToMask`. Note that
     the correction is applied to all pixels in the amplifier, but only those
     that have a substantial crosstalk are masked with ``crosstalkStr``.
 
     The uncorrected image is used as a template for correction. This is good
     enough if the crosstalk is small (e.g., coefficients < ~ 1e-3), but if it's
     larger you may want to iterate.
 
     This method needs unittests (DM-18876), but such testing requires
     DM-18610 to allow the test detector to have the crosstalk
     parameters set.
 
     Parameters
     ----------
     exposure : `lsst.afw.image.Exposure`
         Exposure for which to subtract crosstalk.
     crosstalkCoeffs : `numpy.ndarray`
         Coefficients to use to correct crosstalk.
     badPixels : `list` of `str`
         Mask planes to ignore.
     minPixelToMask : `float`
         Minimum pixel value (relative to the background level) in
         source amplifier for which to set ``crosstalkStr`` mask plane
         in target amplifier.
     crosstalkStr : `str`
         Mask plane name for pixels greatly modified by crosstalk.
     isTrimmed : `bool`
         The image is already trimmed.
         This should no longer be needed once DM-15409 is resolved.
     backgroundMethod : `str`
         Method used to subtract the background.  "AMP" uses
         amplifier-by-amplifier background levels, "DETECTOR" uses full
         exposure/maskedImage levels.  Any other value results in no
         background subtraction.
     """
     mi = exposure.getMaskedImage()
     mask = mi.getMask()
 
     ccd = exposure.getDetector()
     numAmps = len(ccd)
     if crosstalkCoeffs is None:
         coeffs = ccd.getCrosstalk()
     else:
         coeffs = crosstalkCoeffs
     assert coeffs.shape == (numAmps, numAmps)
 
     # Set background level based on the requested method.  The
     # thresholdBackground holds the offset needed so that we only mask
     # pixels high relative to the background, not in an absolute
     # sense.
     thresholdBackground = calculateBackground(mi, badPixels)
 
     backgrounds = [0.0 for amp in ccd]
     if backgroundMethod is None:
         pass
     elif backgroundMethod == "AMP":
         backgrounds = [calculateBackground(mi[amp.getBBox()], badPixels) for amp in ccd]
     elif backgroundMethod == "DETECTOR":
         backgrounds = [calculateBackground(mi, badPixels) for amp in ccd]
 
     # Set the crosstalkStr bit for the bright pixels (those which will have significant crosstalk correction)
     crosstalkPlane = mask.addMaskPlane(crosstalkStr)
     footprints = lsst.afw.detection.FootprintSet(mi, lsst.afw.detection.Threshold(minPixelToMask +
                                                                                   thresholdBackground))
     footprints.setMask(mask, crosstalkStr)
     crosstalk = mask.getPlaneBitMask(crosstalkStr)
 
     # Do pixel level crosstalk correction.
     subtrahend = mi.Factory(mi.getBBox())
     subtrahend.set((0, 0, 0))
     for ii, iAmp in enumerate(ccd):
         iImage = subtrahend[iAmp.getBBox() if isTrimmed else iAmp.getRawDataBBox()]
         for jj, jAmp in enumerate(ccd):
             if ii == jj:
                 assert coeffs[ii, jj] == 0.0
             if coeffs[ii, jj] == 0.0:
                 continue
 
             jImage = extractAmp(mi, jAmp, iAmp.getReadoutCorner(), isTrimmed)
             jImage.getMask().getArray()[:] &= crosstalk  # Remove all other masks
             jImage -= backgrounds[jj]
 
             iImage.scaledPlus(coeffs[ii, jj], jImage)
 
     # Set crosstalkStr bit only for those pixels that have been significantly modified (i.e., those
     # masked as such in 'subtrahend'), not necessarily those that are bright originally.
     mask.clearMaskPlane(crosstalkPlane)
     mi -= subtrahend  # also sets crosstalkStr bit for bright pixels
 
 

◆ writeCrosstalkCoeffs()

def lsst.ip.isr.crosstalk.writeCrosstalkCoeffs	(	outputFileName,
		coeff,
		det = `None`,
		crosstalkName = `"Unknown"`,
		indent = `2`
	)

Write a yaml file containing the crosstalk coefficients

The coeff array is indexed by [i, j] where i and j are amplifiers
corresponding to the amplifiers in det

Parameters
----------
outputFileName : `str`
    Name of output yaml file
coeff : `numpy.array(namp, namp)`
    numpy array of coefficients
det : `lsst.afw.cameraGeom.Detector`
    Used to provide the list of amplifier names;
    if None use ['0', '1', ...]
ccdType : `str`
    Name of detector, used to index the yaml file
    If all detectors are identical could be the type (e.g. ITL)
indent : `int`
    Indent width to use when writing the yaml file

Definition at line 349 of file crosstalk.py.

 def writeCrosstalkCoeffs(outputFileName, coeff, det=None, crosstalkName="Unknown", indent=2):
     """Write a yaml file containing the crosstalk coefficients
 
     The coeff array is indexed by [i, j] where i and j are amplifiers
     corresponding to the amplifiers in det
 
     Parameters
     ----------
     outputFileName : `str`
         Name of output yaml file
     coeff : `numpy.array(namp, namp)`
         numpy array of coefficients
     det : `lsst.afw.cameraGeom.Detector`
         Used to provide the list of amplifier names;
         if None use ['0', '1', ...]
     ccdType : `str`
         Name of detector, used to index the yaml file
         If all detectors are identical could be the type (e.g. ITL)
     indent : `int`
         Indent width to use when writing the yaml file
     """
 
     if det is None:
         ampNames = [str(i) for i in range(coeff.shape[0])]
     else:
         ampNames = [a.getName() for a in det]
 
     assert coeff.shape == (len(ampNames), len(ampNames))
 
     dIndent = indent
     indent = 0
     with open(outputFileName, "w") as fd:
         print(indent*" " + "crosstalk :", file=fd)
         indent += dIndent
         print(indent*" " + "%s :" % crosstalkName, file=fd)
         indent += dIndent
 
         for i, ampNameI in enumerate(ampNames):
             print(indent*" " + "%s : {" % ampNameI, file=fd)
             indent += dIndent
             print(indent*" ", file=fd, end='')
 
             for j, ampNameJ in enumerate(ampNames):
                 print("%s : %11.4e, " % (ampNameJ, coeff[i, j]), file=fd,
                       end='\n' + indent*" " if j%4 == 3 else '')
             print("}", file=fd)
 
             indent -= dIndent

Variable Documentation

◆ X_FLIP

dictionary lsst.ip.isr.crosstalk.X_FLIP

Initial value:

1 = {lsst.afw.cameraGeom.ReadoutCorner.LL: False, lsst.afw.cameraGeom.ReadoutCorner.LR: True,

2 lsst.afw.cameraGeom.ReadoutCorner.UL: False, lsst.afw.cameraGeom.ReadoutCorner.UR: True}

Definition at line 185 of file crosstalk.py.

◆ Y_FLIP

dictionary lsst.ip.isr.crosstalk.Y_FLIP

Initial value:

1 = {lsst.afw.cameraGeom.ReadoutCorner.LL: False, lsst.afw.cameraGeom.ReadoutCorner.LR: False,

2 lsst.afw.cameraGeom.ReadoutCorner.UL: True, lsst.afw.cameraGeom.ReadoutCorner.UR: True}

Definition at line 187 of file crosstalk.py.

Classes

Functions

Variables