LSST Applications 24.1.6,g063fba187b+56b85ce14a,g0f08755f38+df8a265115,g12f32b3c4e+891a09f10d,g1524ad2192+7a5d7b3fbd,g1653933729+a8ce1bb630,g168dd56ebc+a8ce1bb630,g28da252d5a+07cb1400be,g2bbee38e9b+ae03bbfc84,g2bc492864f+ae03bbfc84,g3156d2b45e+6e55a43351,g347aa1857d+ae03bbfc84,g35bb328faa+a8ce1bb630,g3a166c0a6a+ae03bbfc84,g3e281a1b8c+c5dd892a6c,g414038480c+6b9177ef31,g41af890bb2+8f257c4c0b,g781aacb6e4+a8ce1bb630,g7af13505b9+7137b3b17d,g80478fca09+6df6903293,g82479be7b0+091ce1d07f,g858d7b2824+df8a265115,g89c8672015+f4add4ffd5,g9125e01d80+a8ce1bb630,g9726552aa6+414189b318,ga5288a1d22+4a2bca08d7,gacef1a1666+c9a8ff65f4,gb58c049af0+d64f4d3760,gbcfae0f0a0+de1d42d831,gc28159a63d+ae03bbfc84,gcf0d15dbbd+72117bf34e,gda6a2b7d83+72117bf34e,gdaeeff99f8+1711a396fd,ge500cccec5+c8c9c9af63,ge79ae78c31+ae03bbfc84,gf0baf85859+c1f95f4921,gfa517265be+df8a265115,gfa999e8aa5+17cd334064,gfb92a5be7c+df8a265115
LSST Data Management Base Package
|
Functions | |
createPsf (fwhm) | |
transposeMaskedImage (maskedImage) | |
interpolateDefectList (maskedImage, defectList, fwhm, fallbackValue=None, maskNameList=None, useLegacyInterp=True) | |
makeThresholdMask (maskedImage, threshold, growFootprints=1, maskName='SAT') | |
growMasks (mask, radius=0, maskNameList=['BAD'], maskValue="BAD") | |
interpolateFromMask (maskedImage, fwhm, growSaturatedFootprints=1, maskNameList=['SAT'], fallbackValue=None, useLegacyInterp=True) | |
saturationCorrection (maskedImage, saturation, fwhm, growFootprints=1, interpolate=True, maskName='SAT', fallbackValue=None, useLegacyInterp=True) | |
trimToMatchCalibBBox (rawMaskedImage, calibMaskedImage) | |
biasCorrection (maskedImage, biasMaskedImage, trimToFit=False) | |
darkCorrection (maskedImage, darkMaskedImage, expScale, darkScale, invert=False, trimToFit=False) | |
updateVariance (maskedImage, gain, readNoise) | |
flatCorrection (maskedImage, flatMaskedImage, scalingType, userScale=1.0, invert=False, trimToFit=False) | |
illuminationCorrection (maskedImage, illumMaskedImage, illumScale, trimToFit=True) | |
brighterFatterCorrection (exposure, kernel, maxIter, threshold, applyGain, gains=None) | |
transferFlux (cFunc, fStep, correctionMode=True) | |
fluxConservingBrighterFatterCorrection (exposure, kernel, maxIter, threshold, applyGain, gains=None, correctionMode=True) | |
gainContext (exp, image, apply, gains=None, invert=False, isTrimmed=True) | |
attachTransmissionCurve (exposure, opticsTransmission=None, filterTransmission=None, sensorTransmission=None, atmosphereTransmission=None) | |
applyGains (exposure, normalizeGains=False, ptcGains=None, isTrimmed=True) | |
widenSaturationTrails (mask) | |
setBadRegions (exposure, badStatistic="MEDIAN") | |
checkFilter (exposure, filterList, log) | |
getPhysicalFilter (filterLabel, log) | |
countMaskedPixels (maskedIm, maskPlane) | |
getExposureGains (exposure) | |
getExposureReadNoises (exposure) | |
isTrimmedExposure (exposure) | |
isTrimmedImage (image, detector) | |
lsst.ip.isr.isrFunctions.applyGains | ( | exposure, | |
normalizeGains = False, | |||
ptcGains = None, | |||
isTrimmed = True ) |
Scale an exposure by the amplifier gains. Parameters ---------- exposure : `lsst.afw.image.Exposure` Exposure to process. The image is modified. normalizeGains : `Bool`, optional If True, then amplifiers are scaled to force the median of each amplifier to equal the median of those medians. ptcGains : `dict`[`str`], optional Dictionary keyed by amp name containing the PTC gains. isTrimmed : `bool`, optional Is the input image trimmed?
Definition at line 998 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.attachTransmissionCurve | ( | exposure, | |
opticsTransmission = None, | |||
filterTransmission = None, | |||
sensorTransmission = None, | |||
atmosphereTransmission = None ) |
Attach a TransmissionCurve to an Exposure, given separate curves for different components. Parameters ---------- exposure : `lsst.afw.image.Exposure` Exposure object to modify by attaching the product of all given ``TransmissionCurves`` in post-assembly trimmed detector coordinates. Must have a valid ``Detector`` attached that matches the detector associated with sensorTransmission. opticsTransmission : `lsst.afw.image.TransmissionCurve` A ``TransmissionCurve`` that represents the throughput of the optics, to be evaluated in focal-plane coordinates. filterTransmission : `lsst.afw.image.TransmissionCurve` A ``TransmissionCurve`` that represents the throughput of the filter itself, to be evaluated in focal-plane coordinates. sensorTransmission : `lsst.afw.image.TransmissionCurve` A ``TransmissionCurve`` that represents the throughput of the sensor itself, to be evaluated in post-assembly trimmed detector coordinates. atmosphereTransmission : `lsst.afw.image.TransmissionCurve` A ``TransmissionCurve`` that represents the throughput of the atmosphere, assumed to be spatially constant. Returns ------- combined : `lsst.afw.image.TransmissionCurve` The TransmissionCurve attached to the exposure. Notes ----- All ``TransmissionCurve`` arguments are optional; if none are provided, the attached ``TransmissionCurve`` will have unit transmission everywhere.
Definition at line 946 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.biasCorrection | ( | maskedImage, | |
biasMaskedImage, | |||
trimToFit = False ) |
Apply bias correction in place. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. The image is modified by this method. biasMaskedImage : `lsst.afw.image.MaskedImage` Bias image of the same size as ``maskedImage`` trimToFit : `Bool`, optional If True, raw data is symmetrically trimmed to match calibration size. Raises ------ RuntimeError Raised if ``maskedImage`` and ``biasMaskedImage`` do not have the same size.
Definition at line 348 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.brighterFatterCorrection | ( | exposure, | |
kernel, | |||
maxIter, | |||
threshold, | |||
applyGain, | |||
gains = None ) |
Apply brighter fatter correction in place for the image. Parameters ---------- exposure : `lsst.afw.image.Exposure` Exposure to have brighter-fatter correction applied. Modified by this method. kernel : `numpy.ndarray` Brighter-fatter kernel to apply. maxIter : scalar Number of correction iterations to run. threshold : scalar Convergence threshold in terms of the sum of absolute deviations between an iteration and the previous one. applyGain : `Bool` If True, then the exposure values are scaled by the gain prior to correction. gains : `dict` [`str`, `float`] A dictionary, keyed by amplifier name, of the gains to use. If gains is None, the nominal gains in the amplifier object are used. Returns ------- diff : `float` Final difference between iterations achieved in correction. iteration : `int` Number of iterations used to calculate correction. Notes ----- This correction takes a kernel that has been derived from flat field images to redistribute the charge. The gradient of the kernel is the deflection field due to the accumulated charge. Given the original image I(x) and the kernel K(x) we can compute the corrected image Ic(x) using the following equation: Ic(x) = I(x) + 0.5*d/dx(I(x)*d/dx(int( dy*K(x-y)*I(y)))) To evaluate the derivative term we expand it as follows: 0.5 * ( d/dx(I(x))*d/dx(int(dy*K(x-y)*I(y))) + I(x)*d^2/dx^2(int(dy* K(x-y)*I(y))) ) Because we use the measured counts instead of the incident counts we apply the correction iteratively to reconstruct the original counts and the correction. We stop iterating when the summed difference between the current corrected image and the one from the previous iteration is below the threshold. We do not require convergence because the number of iterations is too large a computational cost. How we define the threshold still needs to be evaluated, the current default was shown to work reasonably well on a small set of images. For more information on the method see DocuShare Document-19407. The edges as defined by the kernel are not corrected because they have spurious values due to the convolution.
Definition at line 525 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.checkFilter | ( | exposure, | |
filterList, | |||
log ) |
Check to see if an exposure is in a filter specified by a list. The goal of this is to provide a unified filter checking interface for all filter dependent stages. Parameters ---------- exposure : `lsst.afw.image.Exposure` Exposure to examine. filterList : `list` [`str`] List of physical_filter names to check. log : `logging.Logger` Logger to handle messages. Returns ------- result : `bool` True if the exposure's filter is contained in the list.
Definition at line 1136 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.countMaskedPixels | ( | maskedIm, | |
maskPlane ) |
Count the number of pixels in a given mask plane. Parameters ---------- maskedIm : `~lsst.afw.image.MaskedImage` Masked image to examine. maskPlane : `str` Name of the mask plane to examine. Returns ------- nPix : `int` Number of pixels in the requested mask plane.
Definition at line 1208 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.createPsf | ( | fwhm | ) |
Make a double Gaussian PSF. Parameters ---------- fwhm : scalar FWHM of double Gaussian smoothing kernel. Returns ------- psf : `lsst.meas.algorithms.DoubleGaussianPsf` The created smoothing kernel.
Definition at line 69 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.darkCorrection | ( | maskedImage, | |
darkMaskedImage, | |||
expScale, | |||
darkScale, | |||
invert = False, | |||
trimToFit = False ) |
Apply dark correction in place. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. The image is modified by this method. darkMaskedImage : `lsst.afw.image.MaskedImage` Dark image of the same size as ``maskedImage``. expScale : scalar Dark exposure time for ``maskedImage``. darkScale : scalar Dark exposure time for ``darkMaskedImage``. invert : `Bool`, optional If True, re-add the dark to an already corrected image. trimToFit : `Bool`, optional If True, raw data is symmetrically trimmed to match calibration size. Raises ------ RuntimeError Raised if ``maskedImage`` and ``darkMaskedImage`` do not have the same size. Notes ----- The dark correction is applied by calculating: maskedImage -= dark * expScaling / darkScaling
Definition at line 377 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.flatCorrection | ( | maskedImage, | |
flatMaskedImage, | |||
scalingType, | |||
userScale = 1.0, | |||
invert = False, | |||
trimToFit = False ) |
Apply flat correction in place. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. The image is modified. flatMaskedImage : `lsst.afw.image.MaskedImage` Flat image of the same size as ``maskedImage`` scalingType : str Flat scale computation method. Allowed values are 'MEAN', 'MEDIAN', or 'USER'. userScale : scalar, optional Scale to use if ``scalingType='USER'``. invert : `Bool`, optional If True, unflatten an already flattened image. trimToFit : `Bool`, optional If True, raw data is symmetrically trimmed to match calibration size. Raises ------ RuntimeError Raised if ``maskedImage`` and ``flatMaskedImage`` do not have the same size or if ``scalingType`` is not an allowed value.
Definition at line 443 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.fluxConservingBrighterFatterCorrection | ( | exposure, | |
kernel, | |||
maxIter, | |||
threshold, | |||
applyGain, | |||
gains = None, | |||
correctionMode = True ) |
Apply brighter fatter correction in place for the image. This version presents a modified version of the algorithm found in ``lsst.ip.isr.isrFunctions.brighterFatterCorrection`` which conserves the image flux, resulting in improved correction of the cores of stars. The convolution has also been modified to mitigate edge effects. Parameters ---------- exposure : `lsst.afw.image.Exposure` Exposure to have brighter-fatter correction applied. Modified by this method. kernel : `numpy.ndarray` Brighter-fatter kernel to apply. maxIter : scalar Number of correction iterations to run. threshold : scalar Convergence threshold in terms of the sum of absolute deviations between an iteration and the previous one. applyGain : `Bool` If True, then the exposure values are scaled by the gain prior to correction. gains : `dict` [`str`, `float`] A dictionary, keyed by amplifier name, of the gains to use. If gains is None, the nominal gains in the amplifier object are used. correctionMode : `Bool` If True (default) the function applies correction for BFE. If False, the code can instead be used to generate a simulation of BFE (sign change in the direction of the effect) Returns ------- diff : `float` Final difference between iterations achieved in correction. iteration : `int` Number of iterations used to calculate correction. Notes ----- Modified version of ``lsst.ip.isr.isrFunctions.brighterFatterCorrection``. This correction takes a kernel that has been derived from flat field images to redistribute the charge. The gradient of the kernel is the deflection field due to the accumulated charge. Given the original image I(x) and the kernel K(x) we can compute the corrected image Ic(x) using the following equation: Ic(x) = I(x) + 0.5*d/dx(I(x)*d/dx(int( dy*K(x-y)*I(y)))) Improved algorithm at this step applies the divergence theorem to obtain a pixelised correction. Because we use the measured counts instead of the incident counts we apply the correction iteratively to reconstruct the original counts and the correction. We stop iterating when the summed difference between the current corrected image and the one from the previous iteration is below the threshold. We do not require convergence because the number of iterations is too large a computational cost. How we define the threshold still needs to be evaluated, the current default was shown to work reasonably well on a small set of images. Edges are handled in the convolution by padding. This is still not a physical model for the edge, but avoids discontinuity in the correction. Author of modified version: Lance.Miller@physics.ox.ac.uk (see DM-38555).
Definition at line 734 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.gainContext | ( | exp, | |
image, | |||
apply, | |||
gains = None, | |||
invert = False, | |||
isTrimmed = True ) |
Context manager that applies and removes gain. Parameters ---------- exp : `lsst.afw.image.Exposure` Exposure to apply/remove gain. image : `lsst.afw.image.Image` Image to apply/remove gain. apply : `bool` If True, apply and remove the amplifier gain. gains : `dict` [`str`, `float`], optional A dictionary, keyed by amplifier name, of the gains to use. If gains is None, the nominal gains in the amplifier object are used. invert : `bool`, optional Invert the gains (e.g. convert electrons to adu temporarily)? isTrimmed : `bool`, optional Is this a trimmed exposure? Yields ------ exp : `lsst.afw.image.Exposure` Exposure with the gain applied.
Definition at line 884 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.getExposureGains | ( | exposure | ) |
Get the per-amplifier gains used for this exposure. Parameters ---------- exposure : `lsst.afw.image.Exposure` The exposure to find gains for. Returns ------- gains : `dict` [`str` `float`] Dictionary of gain values, keyed by amplifier name. Returns empty dict when detector is None.
Definition at line 1228 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.getExposureReadNoises | ( | exposure | ) |
Get the per-amplifier read noise used for this exposure. Parameters ---------- exposure : `lsst.afw.image.Exposure` The exposure to find read noise for. Returns ------- readnoises : `dict` [`str` `float`] Dictionary of read noise values, keyed by amplifier name. Returns empty dict when detector is None.
Definition at line 1260 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.getPhysicalFilter | ( | filterLabel, | |
log ) |
Get the physical filter label associated with the given filterLabel. If ``filterLabel`` is `None` or there is no physicalLabel attribute associated with the given ``filterLabel``, the returned label will be "Unknown". Parameters ---------- filterLabel : `lsst.afw.image.FilterLabel` The `lsst.afw.image.FilterLabel` object from which to derive the physical filter label. log : `logging.Logger` Logger to handle messages. Returns ------- physicalFilter : `str` The value returned by the physicalLabel attribute of ``filterLabel`` if it exists, otherwise set to \"Unknown\".
Definition at line 1175 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.growMasks | ( | mask, | |
radius = 0, | |||
maskNameList = ['BAD'], | |||
maskValue = "BAD" ) |
Grow a mask by an amount and add to the requested plane. Parameters ---------- mask : `lsst.afw.image.Mask` Mask image to process. radius : scalar Amount to grow the mask. maskNameList : `str` or `list` [`str`] Mask names that should be grown. maskValue : `str` Mask plane to assign the newly masked pixels to.
Definition at line 198 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.illuminationCorrection | ( | maskedImage, | |
illumMaskedImage, | |||
illumScale, | |||
trimToFit = True ) |
Apply illumination correction in place. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. The image is modified. illumMaskedImage : `lsst.afw.image.MaskedImage` Illumination correction image of the same size as ``maskedImage``. illumScale : scalar Scale factor for the illumination correction. trimToFit : `Bool`, optional If True, raw data is symmetrically trimmed to match calibration size. Raises ------ RuntimeError Raised if ``maskedImage`` and ``illumMaskedImage`` do not have the same size.
Definition at line 494 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.interpolateDefectList | ( | maskedImage, | |
defectList, | |||
fwhm, | |||
fallbackValue = None, | |||
maskNameList = None, | |||
useLegacyInterp = True ) |
Interpolate over defects specified in a defect list. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. defectList : `lsst.meas.algorithms.Defects` List of defects to interpolate over. fwhm : `float` FWHM of double Gaussian smoothing kernel. fallbackValue : scalar, optional Fallback value if an interpolated value cannot be determined. If None, then the clipped mean of the image is used. maskNameList : `list [string]` List of the defects to interpolate over (used for GP interpolator). useLegacyInterp : `bool` Use the legacy interpolation (polynomial interpolation) if True. Use Gaussian Process interpolation if False. Notes ----- The ``fwhm`` parameter is used to create a PSF, but the underlying interpolation code (`lsst.meas.algorithms.interpolateOverDefects`) does not currently make use of this information in legacy Interpolation, but use if for the Gaussian Process as an estimation of the correlation lenght.
Definition at line 106 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.interpolateFromMask | ( | maskedImage, | |
fwhm, | |||
growSaturatedFootprints = 1, | |||
maskNameList = ['SAT'], | |||
fallbackValue = None, | |||
useLegacyInterp = True ) |
Interpolate over defects identified by a particular set of mask planes. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. fwhm : `float` FWHM of double Gaussian smoothing kernel. growSaturatedFootprints : scalar, optional Number of pixels to grow footprints for saturated pixels. maskNameList : `List` of `str`, optional Mask plane name. fallbackValue : scalar, optional Value of last resort for interpolation. Notes ----- The ``fwhm`` parameter is used to create a PSF, but the underlying interpolation code (`lsst.meas.algorithms.interpolateOverDefects`) does not currently make use of this information.
Definition at line 219 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.isTrimmedExposure | ( | exposure | ) |
Check if the unused pixels (pre-/over-scan pixels) have been trimmed from an exposure. Parameters ---------- exposure : `lsst.afw.image.Exposure` The exposure to check. Returns ------- result : `bool` True if the image is trimmed, else False.
Definition at line 1292 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.isTrimmedImage | ( | image, | |
detector ) |
Check if the unused pixels (pre-/over-scan pixels) have been trimmed from an image Parameters ---------- image : `lsst.afw.image.Image` The image to check. detector : `lsst.afw.cameraGeom.Detector` The detector associated with the image. Returns ------- result : `bool` True if the image is trimmed, else False.
Definition at line 1309 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.makeThresholdMask | ( | maskedImage, | |
threshold, | |||
growFootprints = 1, | |||
maskName = 'SAT' ) |
Mask pixels based on threshold detection. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. Only the mask plane is updated. threshold : scalar Detection threshold. growFootprints : scalar, optional Number of pixels to grow footprints of detected regions. maskName : str, optional Mask plane name, or list of names to convert Returns ------- defectList : `lsst.meas.algorithms.Defects` Defect list constructed from pixels above the threshold.
Definition at line 163 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.saturationCorrection | ( | maskedImage, | |
saturation, | |||
fwhm, | |||
growFootprints = 1, | |||
interpolate = True, | |||
maskName = 'SAT', | |||
fallbackValue = None, | |||
useLegacyInterp = True ) |
Mark saturated pixels and optionally interpolate over them Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. saturation : scalar Saturation level used as the detection threshold. fwhm : `float` FWHM of double Gaussian smoothing kernel. growFootprints : scalar, optional Number of pixels to grow footprints of detected regions. interpolate : Bool, optional If True, saturated pixels are interpolated over. maskName : str, optional Mask plane name. fallbackValue : scalar, optional Value of last resort for interpolation. Notes ----- The ``fwhm`` parameter is used to create a PSF, but the underlying interpolation code (`lsst.meas.algorithms.interpolateOverDefects`) does not currently make use of this information.
Definition at line 260 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.setBadRegions | ( | exposure, | |
badStatistic = "MEDIAN" ) |
Set all BAD areas of the chip to the average of the rest of the exposure Parameters ---------- exposure : `lsst.afw.image.Exposure` Exposure to mask. The exposure mask is modified. badStatistic : `str`, optional Statistic to use to generate the replacement value from the image data. Allowed values are 'MEDIAN' or 'MEANCLIP'. Returns ------- badPixelCount : scalar Number of bad pixels masked. badPixelValue : scalar Value substituted for bad pixels. Raises ------ RuntimeError Raised if `badStatistic` is not an allowed value.
Definition at line 1089 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.transferFlux | ( | cFunc, | |
fStep, | |||
correctionMode = True ) |
Take the input convolved deflection potential and the flux array to compute and apply the flux transfer into the correction array. Parameters ---------- cFunc: `numpy.array` Deflection potential, being the convolution of the flux F with the kernel K. fStep: `numpy.array` The array of flux values which act as the source of the flux transfer. correctionMode: `bool` Defines if applying correction (True) or generating sims (False). Returns ------- corr: BFE correction array
Definition at line 650 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.transposeMaskedImage | ( | maskedImage | ) |
Make a transposed copy of a masked image. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. Returns ------- transposed : `lsst.afw.image.MaskedImage` The transposed copy of the input image.
Definition at line 86 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.trimToMatchCalibBBox | ( | rawMaskedImage, | |
calibMaskedImage ) |
Compute number of edge trim pixels to match the calibration data. Use the dimension difference between the raw exposure and the calibration exposure to compute the edge trim pixels. This trim is applied symmetrically, with the same number of pixels masked on each side. Parameters ---------- rawMaskedImage : `lsst.afw.image.MaskedImage` Image to trim. calibMaskedImage : `lsst.afw.image.MaskedImage` Calibration image to draw new bounding box from. Returns ------- replacementMaskedImage : `lsst.afw.image.MaskedImage` ``rawMaskedImage`` trimmed to the appropriate size. Raises ------ RuntimeError Raised if ``rawMaskedImage`` cannot be symmetrically trimmed to match ``calibMaskedImage``.
Definition at line 300 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.updateVariance | ( | maskedImage, | |
gain, | |||
readNoise ) |
Set the variance plane based on the image plane. The maskedImage must have units of `adu` (if gain != 1.0) or electron (if gain == 1.0). This routine will always produce a variance plane in the same units as the image. Parameters ---------- maskedImage : `lsst.afw.image.MaskedImage` Image to process. The variance plane is modified. gain : scalar The amplifier gain in electron/adu. readNoise : scalar The amplifier read noise in electron/pixel.
Definition at line 421 of file isrFunctions.py.
lsst.ip.isr.isrFunctions.widenSaturationTrails | ( | mask | ) |
Grow the saturation trails by an amount dependent on the width of the trail. Parameters ---------- mask : `lsst.afw.image.Mask` Mask which will have the saturated areas grown.
Definition at line 1041 of file isrFunctions.py.