32 from contextlib
import contextmanager
33 from lsstDebug
import getDebugFrame
43 from .
import isrFunctions
45 from .
import linearize
47 from .assembleCcdTask
import AssembleCcdTask
48 from .crosstalk
import CrosstalkTask
49 from .fringe
import FringeTask
50 from .isr
import maskNans
51 from .masking
import MaskingTask
52 from .straylight
import StrayLightTask
53 from .vignette
import VignetteTask
55 __all__ = [
"IsrTask",
"IsrTaskConfig",
"RunIsrTask",
"RunIsrConfig"]
59 """Configuration parameters for IsrTask. 61 Items are grouped in the order in which they are executed by the task. 66 isrName = pexConfig.Field(
73 ccdExposure = pipeBase.InputDatasetField(
74 doc=
"Input exposure to process",
77 storageClass=
"Exposure",
78 dimensions=[
"instrument",
"exposure",
"detector"],
80 camera = pipeBase.InputDatasetField(
81 doc=
"Input camera to construct complete exposures.",
84 storageClass=
"TablePersistableCamera",
85 dimensions=[
"instrument",
"calibration_label"],
87 bias = pipeBase.InputDatasetField(
88 doc=
"Input bias calibration.",
91 storageClass=
"ImageF",
92 dimensions=[
"instrument",
"calibration_label",
"detector"],
94 dark = pipeBase.InputDatasetField(
95 doc=
"Input dark calibration.",
98 storageClass=
"ImageF",
99 dimensions=[
"instrument",
"calibration_label",
"detector"],
101 flat = pipeBase.InputDatasetField(
102 doc=
"Input flat calibration.",
105 storageClass=
"MaskedImageF",
106 dimensions=[
"instrument",
"physical_filter",
"calibration_label",
"detector"],
108 bfKernel = pipeBase.InputDatasetField(
109 doc=
"Input brighter-fatter kernel.",
112 storageClass=
"NumpyArray",
113 dimensions=[
"instrument",
"calibration_label"],
115 defects = pipeBase.InputDatasetField(
116 doc=
"Input defect tables.",
119 storageClass=
"DefectsList",
120 dimensions=[
"instrument",
"calibration_label",
"detector"],
122 opticsTransmission = pipeBase.InputDatasetField(
123 doc=
"Transmission curve due to the optics.",
124 name=
"transmission_optics",
126 storageClass=
"TablePersistableTransmissionCurve",
127 dimensions=[
"instrument",
"calibration_label"],
129 filterTransmission = pipeBase.InputDatasetField(
130 doc=
"Transmission curve due to the filter.",
131 name=
"transmission_filter",
133 storageClass=
"TablePersistableTransmissionCurve",
134 dimensions=[
"instrument",
"physical_filter",
"calibration_label"],
136 sensorTransmission = pipeBase.InputDatasetField(
137 doc=
"Transmission curve due to the sensor.",
138 name=
"transmission_sensor",
140 storageClass=
"TablePersistableTransmissionCurve",
141 dimensions=[
"instrument",
"calibration_label",
"detector"],
143 atmosphereTransmission = pipeBase.InputDatasetField(
144 doc=
"Transmission curve due to the atmosphere.",
145 name=
"transmission_atmosphere",
147 storageClass=
"TablePersistableTransmissionCurve",
148 dimensions=[
"instrument"],
150 illumMaskedImage = pipeBase.InputDatasetField(
151 doc=
"Input illumination correction.",
154 storageClass=
"MaskedImageF",
155 dimensions=[
"instrument",
"physical_filter",
"calibration_label",
"detector"],
159 outputExposure = pipeBase.OutputDatasetField(
160 doc=
"Output ISR processed exposure.",
163 storageClass=
"ExposureF",
164 dimensions=[
"instrument",
"visit",
"detector"],
166 outputOssThumbnail = pipeBase.OutputDatasetField(
167 doc=
"Output Overscan-subtracted thumbnail image.",
170 storageClass=
"Thumbnail",
171 dimensions=[
"instrument",
"visit",
"detector"],
173 outputFlattenedThumbnail = pipeBase.OutputDatasetField(
174 doc=
"Output flat-corrected thumbnail image.",
175 name=
"FlattenedThumb",
177 storageClass=
"TextStorage",
178 dimensions=[
"instrument",
"visit",
"detector"],
181 quantum = pipeBase.QuantumConfig(
182 dimensions=[
"visit",
"detector",
"instrument"],
186 datasetType = pexConfig.Field(
188 doc=
"Dataset type for input data; users will typically leave this alone, " 189 "but camera-specific ISR tasks will override it",
193 fallbackFilterName = pexConfig.Field(
195 doc=
"Fallback default filter name for calibrations.",
198 expectWcs = pexConfig.Field(
201 doc=
"Expect input science images to have a WCS (set False for e.g. spectrographs)." 203 fwhm = pexConfig.Field(
205 doc=
"FWHM of PSF in arcseconds.",
208 qa = pexConfig.ConfigField(
210 doc=
"QA related configuration options.",
214 doConvertIntToFloat = pexConfig.Field(
216 doc=
"Convert integer raw images to floating point values?",
221 doSaturation = pexConfig.Field(
223 doc=
"Mask saturated pixels? NB: this is totally independent of the" 224 " interpolation option - this is ONLY setting the bits in the mask." 225 " To have them interpolated make sure doSaturationInterpolation=True",
228 saturatedMaskName = pexConfig.Field(
230 doc=
"Name of mask plane to use in saturation detection and interpolation",
233 saturation = pexConfig.Field(
235 doc=
"The saturation level to use if no Detector is present in the Exposure (ignored if NaN)",
236 default=float(
"NaN"),
238 growSaturationFootprintSize = pexConfig.Field(
240 doc=
"Number of pixels by which to grow the saturation footprints",
245 doSuspect = pexConfig.Field(
247 doc=
"Mask suspect pixels?",
250 suspectMaskName = pexConfig.Field(
252 doc=
"Name of mask plane to use for suspect pixels",
255 numEdgeSuspect = pexConfig.Field(
257 doc=
"Number of edge pixels to be flagged as untrustworthy.",
262 doSetBadRegions = pexConfig.Field(
264 doc=
"Should we set the level of all BAD patches of the chip to the chip's average value?",
267 badStatistic = pexConfig.ChoiceField(
269 doc=
"How to estimate the average value for BAD regions.",
272 "MEANCLIP":
"Correct using the (clipped) mean of good data",
273 "MEDIAN":
"Correct using the median of the good data",
278 doOverscan = pexConfig.Field(
280 doc=
"Do overscan subtraction?",
283 overscanFitType = pexConfig.ChoiceField(
285 doc=
"The method for fitting the overscan bias level.",
288 "POLY":
"Fit ordinary polynomial to the longest axis of the overscan region",
289 "CHEB":
"Fit Chebyshev polynomial to the longest axis of the overscan region",
290 "LEG":
"Fit Legendre polynomial to the longest axis of the overscan region",
291 "NATURAL_SPLINE":
"Fit natural spline to the longest axis of the overscan region",
292 "CUBIC_SPLINE":
"Fit cubic spline to the longest axis of the overscan region",
293 "AKIMA_SPLINE":
"Fit Akima spline to the longest axis of the overscan region",
294 "MEAN":
"Correct using the mean of the overscan region",
295 "MEANCLIP":
"Correct using a clipped mean of the overscan region",
296 "MEDIAN":
"Correct using the median of the overscan region",
299 overscanOrder = pexConfig.Field(
301 doc=(
"Order of polynomial or to fit if overscan fit type is a polynomial, " +
302 "or number of spline knots if overscan fit type is a spline."),
305 overscanNumSigmaClip = pexConfig.Field(
307 doc=
"Rejection threshold (sigma) for collapsing overscan before fit",
310 overscanIsInt = pexConfig.Field(
312 doc=
"Treat overscan as an integer image for purposes of overscan.FitType=MEDIAN",
315 overscanNumLeadingColumnsToSkip = pexConfig.Field(
317 doc=
"Number of columns to skip in overscan, i.e. those closest to amplifier",
320 overscanNumTrailingColumnsToSkip = pexConfig.Field(
322 doc=
"Number of columns to skip in overscan, i.e. those farthest from amplifier",
325 overscanMaxDev = pexConfig.Field(
327 doc=
"Maximum deviation from the median for overscan",
328 default=1000.0, check=
lambda x: x > 0
330 overscanBiasJump = pexConfig.Field(
332 doc=
"Fit the overscan in a piecewise-fashion to correct for bias jumps?",
335 overscanBiasJumpKeyword = pexConfig.Field(
337 doc=
"Header keyword containing information about devices.",
338 default=
"NO_SUCH_KEY",
340 overscanBiasJumpDevices = pexConfig.ListField(
342 doc=
"List of devices that need piecewise overscan correction.",
345 overscanBiasJumpLocation = pexConfig.Field(
347 doc=
"Location of bias jump along y-axis.",
352 doAssembleCcd = pexConfig.Field(
355 doc=
"Assemble amp-level exposures into a ccd-level exposure?" 357 assembleCcd = pexConfig.ConfigurableField(
358 target=AssembleCcdTask,
359 doc=
"CCD assembly task",
363 doAssembleIsrExposures = pexConfig.Field(
366 doc=
"Assemble amp-level calibration exposures into ccd-level exposure?" 368 doTrimToMatchCalib = pexConfig.Field(
371 doc=
"Trim raw data to match calibration bounding boxes?" 375 doBias = pexConfig.Field(
377 doc=
"Apply bias frame correction?",
380 biasDataProductName = pexConfig.Field(
382 doc=
"Name of the bias data product",
387 doVariance = pexConfig.Field(
389 doc=
"Calculate variance?",
392 gain = pexConfig.Field(
394 doc=
"The gain to use if no Detector is present in the Exposure (ignored if NaN)",
395 default=float(
"NaN"),
397 readNoise = pexConfig.Field(
399 doc=
"The read noise to use if no Detector is present in the Exposure",
402 doEmpiricalReadNoise = pexConfig.Field(
405 doc=
"Calculate empirical read noise instead of value from AmpInfo data?" 409 doLinearize = pexConfig.Field(
411 doc=
"Correct for nonlinearity of the detector's response?",
416 doCrosstalk = pexConfig.Field(
418 doc=
"Apply intra-CCD crosstalk correction?",
421 doCrosstalkBeforeAssemble = pexConfig.Field(
423 doc=
"Apply crosstalk correction before CCD assembly, and before trimming?",
426 crosstalk = pexConfig.ConfigurableField(
427 target=CrosstalkTask,
428 doc=
"Intra-CCD crosstalk correction",
432 doDefect = pexConfig.Field(
434 doc=
"Apply correction for CCD defects, e.g. hot pixels?",
437 numEdgeSuspect = pexConfig.Field(
439 doc=
"Number of edge pixels to be flagged as untrustworthy.",
442 doNanMasking = pexConfig.Field(
444 doc=
"Mask NAN pixels?",
447 doWidenSaturationTrails = pexConfig.Field(
449 doc=
"Widen bleed trails based on their width?",
454 doBrighterFatter = pexConfig.Field(
457 doc=
"Apply the brighter fatter correction" 459 brighterFatterLevel = pexConfig.ChoiceField(
462 doc=
"The level at which to correct for brighter-fatter.",
464 "AMP":
"Every amplifier treated separately.",
465 "DETECTOR":
"One kernel per detector",
468 brighterFatterKernelFile = pexConfig.Field(
471 doc=
"Kernel file used for the brighter fatter correction" 473 brighterFatterMaxIter = pexConfig.Field(
476 doc=
"Maximum number of iterations for the brighter fatter correction" 478 brighterFatterThreshold = pexConfig.Field(
481 doc=
"Threshold used to stop iterating the brighter fatter correction. It is the " 482 " absolute value of the difference between the current corrected image and the one" 483 " from the previous iteration summed over all the pixels." 485 brighterFatterApplyGain = pexConfig.Field(
488 doc=
"Should the gain be applied when applying the brighter fatter correction?" 492 doDark = pexConfig.Field(
494 doc=
"Apply dark frame correction?",
497 darkDataProductName = pexConfig.Field(
499 doc=
"Name of the dark data product",
504 doStrayLight = pexConfig.Field(
506 doc=
"Subtract stray light in the y-band (due to encoder LEDs)?",
509 strayLight = pexConfig.ConfigurableField(
510 target=StrayLightTask,
511 doc=
"y-band stray light correction" 515 doFlat = pexConfig.Field(
517 doc=
"Apply flat field correction?",
520 flatDataProductName = pexConfig.Field(
522 doc=
"Name of the flat data product",
525 flatScalingType = pexConfig.ChoiceField(
527 doc=
"The method for scaling the flat on the fly.",
530 "USER":
"Scale by flatUserScale",
531 "MEAN":
"Scale by the inverse of the mean",
532 "MEDIAN":
"Scale by the inverse of the median",
535 flatUserScale = pexConfig.Field(
537 doc=
"If flatScalingType is 'USER' then scale flat by this amount; ignored otherwise",
540 doTweakFlat = pexConfig.Field(
542 doc=
"Tweak flats to match observed amplifier ratios?",
547 doApplyGains = pexConfig.Field(
549 doc=
"Correct the amplifiers for their gains instead of applying flat correction",
552 normalizeGains = pexConfig.Field(
554 doc=
"Normalize all the amplifiers in each CCD to have the same median value.",
559 doFringe = pexConfig.Field(
561 doc=
"Apply fringe correction?",
564 fringe = pexConfig.ConfigurableField(
566 doc=
"Fringe subtraction task",
568 fringeAfterFlat = pexConfig.Field(
570 doc=
"Do fringe subtraction after flat-fielding?",
575 doAddDistortionModel = pexConfig.Field(
577 doc=
"Apply a distortion model based on camera geometry to the WCS?",
582 doMeasureBackground = pexConfig.Field(
584 doc=
"Measure the background level on the reduced image?",
589 doCameraSpecificMasking = pexConfig.Field(
591 doc=
"Mask camera-specific bad regions?",
594 masking = pexConfig.ConfigurableField(
601 doInterpolate = pexConfig.Field(
603 doc=
"Interpolate masked pixels?",
606 doSaturationInterpolation = pexConfig.Field(
608 doc=
"Perform interpolation over pixels masked as saturated?" 609 " NB: This is independent of doSaturation; if that is False this plane" 610 " will likely be blank, resulting in a no-op here.",
613 doNanInterpolation = pexConfig.Field(
615 doc=
"Perform interpolation over pixels masked as NaN?" 616 " NB: This is independent of doNanMasking; if that is False this plane" 617 " will likely be blank, resulting in a no-op here.",
620 doNanInterpAfterFlat = pexConfig.Field(
622 doc=(
"If True, ensure we interpolate NaNs after flat-fielding, even if we " 623 "also have to interpolate them before flat-fielding."),
626 maskListToInterpolate = pexConfig.ListField(
628 doc=
"List of mask planes that should be interpolated.",
629 default=[
'SAT',
'BAD',
'UNMASKEDNAN'],
631 doSaveInterpPixels = pexConfig.Field(
633 doc=
"Save a copy of the pre-interpolated pixel values?",
638 fluxMag0T1 = pexConfig.DictField(
641 doc=
"The approximate flux of a zero-magnitude object in a one-second exposure, per filter.",
642 default=dict((f, pow(10.0, 0.4*m))
for f, m
in ((
"Unknown", 28.0),
645 defaultFluxMag0T1 = pexConfig.Field(
647 doc=
"Default value for fluxMag0T1 (for an unrecognized filter).",
648 default=pow(10.0, 0.4*28.0)
652 doVignette = pexConfig.Field(
654 doc=
"Apply vignetting parameters?",
657 vignette = pexConfig.ConfigurableField(
659 doc=
"Vignetting task.",
663 doAttachTransmissionCurve = pexConfig.Field(
666 doc=
"Construct and attach a wavelength-dependent throughput curve for this CCD image?" 668 doUseOpticsTransmission = pexConfig.Field(
671 doc=
"Load and use transmission_optics (if doAttachTransmissionCurve is True)?" 673 doUseFilterTransmission = pexConfig.Field(
676 doc=
"Load and use transmission_filter (if doAttachTransmissionCurve is True)?" 678 doUseSensorTransmission = pexConfig.Field(
681 doc=
"Load and use transmission_sensor (if doAttachTransmissionCurve is True)?" 683 doUseAtmosphereTransmission = pexConfig.Field(
686 doc=
"Load and use transmission_atmosphere (if doAttachTransmissionCurve is True)?" 690 doIlluminationCorrection = pexConfig.Field(
693 doc=
"Perform illumination correction?" 695 illuminationCorrectionDataProductName = pexConfig.Field(
697 doc=
"Name of the illumination correction data product.",
700 illumScale = pexConfig.Field(
702 doc=
"Scale factor for the illumination correction.",
705 illumFilters = pexConfig.ListField(
708 doc=
"Only perform illumination correction for these filters." 712 doWrite = pexConfig.Field(
714 doc=
"Persist postISRCCD?",
721 raise ValueError(
"You may not specify both doFlat and doApplyGains")
723 self.config.maskListToInterpolate.append(
"SAT")
725 self.config.maskListToInterpolate.append(
"UNMASKEDNAN")
728 class IsrTask(pipeBase.PipelineTask, pipeBase.CmdLineTask):
729 """Apply common instrument signature correction algorithms to a raw frame. 731 The process for correcting imaging data is very similar from 732 camera to camera. This task provides a vanilla implementation of 733 doing these corrections, including the ability to turn certain 734 corrections off if they are not needed. The inputs to the primary 735 method, `run()`, are a raw exposure to be corrected and the 736 calibration data products. The raw input is a single chip sized 737 mosaic of all amps including overscans and other non-science 738 pixels. The method `runDataRef()` identifies and defines the 739 calibration data products, and is intended for use by a 740 `lsst.pipe.base.cmdLineTask.CmdLineTask` and takes as input only a 741 `daf.persistence.butlerSubset.ButlerDataRef`. This task may be 742 subclassed for different camera, although the most camera specific 743 methods have been split into subtasks that can be redirected 746 The __init__ method sets up the subtasks for ISR processing, using 747 the defaults from `lsst.ip.isr`. 752 Positional arguments passed to the Task constructor. None used at this time. 753 kwargs : `dict`, optional 754 Keyword arguments passed on to the Task constructor. None used at this time. 756 ConfigClass = IsrTaskConfig
761 self.makeSubtask(
"assembleCcd")
762 self.makeSubtask(
"crosstalk")
763 self.makeSubtask(
"strayLight")
764 self.makeSubtask(
"fringe")
765 self.makeSubtask(
"masking")
766 self.makeSubtask(
"vignette")
775 if config.doBias
is not True:
776 inputTypeDict.pop(
"bias",
None)
777 if config.doLinearize
is not True:
778 inputTypeDict.pop(
"linearizer",
None)
779 if config.doCrosstalk
is not True:
780 inputTypeDict.pop(
"crosstalkSources",
None)
781 if config.doBrighterFatter
is not True:
782 inputTypeDict.pop(
"bfKernel",
None)
783 if config.doDefect
is not True:
784 inputTypeDict.pop(
"defects",
None)
785 if config.doDark
is not True:
786 inputTypeDict.pop(
"dark",
None)
787 if config.doFlat
is not True:
788 inputTypeDict.pop(
"flat",
None)
789 if config.doAttachTransmissionCurve
is not True:
790 inputTypeDict.pop(
"opticsTransmission",
None)
791 inputTypeDict.pop(
"filterTransmission",
None)
792 inputTypeDict.pop(
"sensorTransmission",
None)
793 inputTypeDict.pop(
"atmosphereTransmission",
None)
794 if config.doUseOpticsTransmission
is not True:
795 inputTypeDict.pop(
"opticsTransmission",
None)
796 if config.doUseFilterTransmission
is not True:
797 inputTypeDict.pop(
"filterTransmission",
None)
798 if config.doUseSensorTransmission
is not True:
799 inputTypeDict.pop(
"sensorTransmission",
None)
800 if config.doUseAtmosphereTransmission
is not True:
801 inputTypeDict.pop(
"atmosphereTransmission",
None)
802 if config.doIlluminationCorrection
is not True:
803 inputTypeDict.pop(
"illumMaskedImage",
None)
811 if config.qa.doThumbnailOss
is not True:
812 outputTypeDict.pop(
"outputOssThumbnail",
None)
813 if config.qa.doThumbnailFlattened
is not True:
814 outputTypeDict.pop(
"outputFlattenedThumbnail",
None)
815 if config.doWrite
is not True:
816 outputTypeDict.pop(
"outputExposure",
None)
818 return outputTypeDict
827 names.remove(
"ccdExposure")
836 return frozenset([
"calibration_label"])
840 inputData[
'detectorNum'] = int(inputDataIds[
'ccdExposure'][
'detector'])
841 except Exception
as e:
842 raise ValueError(f
"Failure to find valid detectorNum value for Dataset {inputDataIds}: {e}")
844 inputData[
'isGen3'] =
True 846 if self.config.doLinearize
is True:
847 if 'linearizer' not in inputData.keys():
848 detector = inputData[
'camera'][inputData[
'detectorNum']]
849 linearityName = detector.getAmpInfoCatalog()[0].getLinearityType()
850 inputData[
'linearizer'] = linearize.getLinearityTypeByName(linearityName)()
852 if inputData[
'defects']
is not None:
855 if not isinstance(inputData[
"defects"], Defects):
856 inputData[
"defects"] = Defects.fromTable(inputData[
"defects"])
873 return super().
adaptArgsAndRun(inputData, inputDataIds, outputDataIds, butler)
879 """!Retrieve necessary frames for instrument signature removal. 881 Pre-fetching all required ISR data products limits the IO 882 required by the ISR. Any conflict between the calibration data 883 available and that needed for ISR is also detected prior to 884 doing processing, allowing it to fail quickly. 888 dataRef : `daf.persistence.butlerSubset.ButlerDataRef` 889 Butler reference of the detector data to be processed 890 rawExposure : `afw.image.Exposure` 891 The raw exposure that will later be corrected with the 892 retrieved calibration data; should not be modified in this 897 result : `lsst.pipe.base.Struct` 898 Result struct with components (which may be `None`): 899 - ``bias``: bias calibration frame (`afw.image.Exposure`) 900 - ``linearizer``: functor for linearization (`ip.isr.linearize.LinearizeBase`) 901 - ``crosstalkSources``: list of possible crosstalk sources (`list`) 902 - ``dark``: dark calibration frame (`afw.image.Exposure`) 903 - ``flat``: flat calibration frame (`afw.image.Exposure`) 904 - ``bfKernel``: Brighter-Fatter kernel (`numpy.ndarray`) 905 - ``defects``: list of defects (`lsst.meas.algorithms.Defects`) 906 - ``fringes``: `lsst.pipe.base.Struct` with components: 907 - ``fringes``: fringe calibration frame (`afw.image.Exposure`) 908 - ``seed``: random seed derived from the ccdExposureId for random 909 number generator (`uint32`). 910 - ``opticsTransmission``: `lsst.afw.image.TransmissionCurve` 911 A ``TransmissionCurve`` that represents the throughput of the optics, 912 to be evaluated in focal-plane coordinates. 913 - ``filterTransmission`` : `lsst.afw.image.TransmissionCurve` 914 A ``TransmissionCurve`` that represents the throughput of the filter 915 itself, to be evaluated in focal-plane coordinates. 916 - ``sensorTransmission`` : `lsst.afw.image.TransmissionCurve` 917 A ``TransmissionCurve`` that represents the throughput of the sensor 918 itself, to be evaluated in post-assembly trimmed detector coordinates. 919 - ``atmosphereTransmission`` : `lsst.afw.image.TransmissionCurve` 920 A ``TransmissionCurve`` that represents the throughput of the 921 atmosphere, assumed to be spatially constant. 922 - ``strayLightData`` : `object` 923 An opaque object containing calibration information for 924 stray-light correction. If `None`, no correction will be 926 - ``illumMaskedImage`` : illumination correction image (`lsst.afw.image.MaskedImage`) 930 NotImplementedError : 931 Raised if a per-amplifier brighter-fatter kernel is requested by the configuration. 933 ccd = rawExposure.getDetector()
934 filterName = afwImage.Filter(rawExposure.getFilter().getId()).getName()
935 rawExposure.mask.addMaskPlane(
"UNMASKEDNAN")
936 biasExposure = (self.
getIsrExposure(dataRef, self.config.biasDataProductName)
937 if self.config.doBias
else None)
939 linearizer = (dataRef.get(
"linearizer", immediate=
True)
941 crosstalkSources = (self.crosstalk.prepCrosstalk(dataRef)
942 if self.config.doCrosstalk
else None)
943 darkExposure = (self.
getIsrExposure(dataRef, self.config.darkDataProductName)
944 if self.config.doDark
else None)
945 flatExposure = (self.
getIsrExposure(dataRef, self.config.flatDataProductName)
946 if self.config.doFlat
else None)
948 brighterFatterKernel =
None 949 if self.config.doBrighterFatter
is True:
953 brighterFatterKernel = dataRef.get(
"brighterFatterKernel")
957 brighterFatterKernel = dataRef.get(
"bfKernel")
959 brighterFatterKernel =
None 960 if brighterFatterKernel
is not None and not isinstance(brighterFatterKernel, numpy.ndarray):
963 if self.config.brighterFatterLevel ==
'DETECTOR':
964 brighterFatterKernel = brighterFatterKernel.kernel[ccd.getId()]
967 raise NotImplementedError(
"Per-amplifier brighter-fatter correction not implemented")
969 defectList = (dataRef.get(
"defects")
970 if self.config.doDefect
else None)
971 fringeStruct = (self.fringe.readFringes(dataRef, assembler=self.assembleCcd
972 if self.config.doAssembleIsrExposures
else None)
973 if self.config.doFringe
and self.fringe.checkFilter(rawExposure)
974 else pipeBase.Struct(fringes=
None))
976 if self.config.doAttachTransmissionCurve:
977 opticsTransmission = (dataRef.get(
"transmission_optics")
978 if self.config.doUseOpticsTransmission
else None)
979 filterTransmission = (dataRef.get(
"transmission_filter")
980 if self.config.doUseFilterTransmission
else None)
981 sensorTransmission = (dataRef.get(
"transmission_sensor")
982 if self.config.doUseSensorTransmission
else None)
983 atmosphereTransmission = (dataRef.get(
"transmission_atmosphere")
984 if self.config.doUseAtmosphereTransmission
else None)
986 opticsTransmission =
None 987 filterTransmission =
None 988 sensorTransmission =
None 989 atmosphereTransmission =
None 991 if self.config.doStrayLight:
992 strayLightData = self.strayLight.
readIsrData(dataRef, rawExposure)
994 strayLightData =
None 997 self.config.illuminationCorrectionDataProductName).getMaskedImage()
998 if (self.config.doIlluminationCorrection
and 999 filterName
in self.config.illumFilters)
1003 return pipeBase.Struct(bias=biasExposure,
1004 linearizer=linearizer,
1005 crosstalkSources=crosstalkSources,
1008 bfKernel=brighterFatterKernel,
1010 fringes=fringeStruct,
1011 opticsTransmission=opticsTransmission,
1012 filterTransmission=filterTransmission,
1013 sensorTransmission=sensorTransmission,
1014 atmosphereTransmission=atmosphereTransmission,
1015 strayLightData=strayLightData,
1016 illumMaskedImage=illumMaskedImage
1019 @pipeBase.timeMethod
1020 def run(self, ccdExposure, camera=None, bias=None, linearizer=None, crosstalkSources=None,
1021 dark=None, flat=None, bfKernel=None, defects=None, fringes=pipeBase.Struct(fringes=
None),
1022 opticsTransmission=
None, filterTransmission=
None,
1023 sensorTransmission=
None, atmosphereTransmission=
None,
1024 detectorNum=
None, strayLightData=
None, illumMaskedImage=
None,
1027 """!Perform instrument signature removal on an exposure. 1029 Steps included in the ISR processing, in order performed, are: 1030 - saturation and suspect pixel masking 1031 - overscan subtraction 1032 - CCD assembly of individual amplifiers 1034 - variance image construction 1035 - linearization of non-linear response 1037 - brighter-fatter correction 1040 - stray light subtraction 1042 - masking of known defects and camera specific features 1043 - vignette calculation 1044 - appending transmission curve and distortion model 1048 ccdExposure : `lsst.afw.image.Exposure` 1049 The raw exposure that is to be run through ISR. The 1050 exposure is modified by this method. 1051 camera : `lsst.afw.cameraGeom.Camera`, optional 1052 The camera geometry for this exposure. Used to select the 1053 distortion model appropriate for this data. 1054 bias : `lsst.afw.image.Exposure`, optional 1055 Bias calibration frame. 1056 linearizer : `lsst.ip.isr.linearize.LinearizeBase`, optional 1057 Functor for linearization. 1058 crosstalkSources : `list`, optional 1059 List of possible crosstalk sources. 1060 dark : `lsst.afw.image.Exposure`, optional 1061 Dark calibration frame. 1062 flat : `lsst.afw.image.Exposure`, optional 1063 Flat calibration frame. 1064 bfKernel : `numpy.ndarray`, optional 1065 Brighter-fatter kernel. 1066 defects : `lsst.meas.algorithms.Defects`, optional 1068 fringes : `lsst.pipe.base.Struct`, optional 1069 Struct containing the fringe correction data, with 1071 - ``fringes``: fringe calibration frame (`afw.image.Exposure`) 1072 - ``seed``: random seed derived from the ccdExposureId for random 1073 number generator (`uint32`) 1074 opticsTransmission: `lsst.afw.image.TransmissionCurve`, optional 1075 A ``TransmissionCurve`` that represents the throughput of the optics, 1076 to be evaluated in focal-plane coordinates. 1077 filterTransmission : `lsst.afw.image.TransmissionCurve` 1078 A ``TransmissionCurve`` that represents the throughput of the filter 1079 itself, to be evaluated in focal-plane coordinates. 1080 sensorTransmission : `lsst.afw.image.TransmissionCurve` 1081 A ``TransmissionCurve`` that represents the throughput of the sensor 1082 itself, to be evaluated in post-assembly trimmed detector coordinates. 1083 atmosphereTransmission : `lsst.afw.image.TransmissionCurve` 1084 A ``TransmissionCurve`` that represents the throughput of the 1085 atmosphere, assumed to be spatially constant. 1086 detectorNum : `int`, optional 1087 The integer number for the detector to process. 1088 isGen3 : bool, optional 1089 Flag this call to run() as using the Gen3 butler environment. 1090 strayLightData : `object`, optional 1091 Opaque object containing calibration information for stray-light 1092 correction. If `None`, no correction will be performed. 1093 illumMaskedImage : `lsst.afw.image.MaskedImage`, optional 1094 Illumination correction image. 1098 result : `lsst.pipe.base.Struct` 1099 Result struct with component: 1100 - ``exposure`` : `afw.image.Exposure` 1101 The fully ISR corrected exposure. 1102 - ``outputExposure`` : `afw.image.Exposure` 1103 An alias for `exposure` 1104 - ``ossThumb`` : `numpy.ndarray` 1105 Thumbnail image of the exposure after overscan subtraction. 1106 - ``flattenedThumb`` : `numpy.ndarray` 1107 Thumbnail image of the exposure after flat-field correction. 1112 Raised if a configuration option is set to True, but the 1113 required calibration data has not been specified. 1117 The current processed exposure can be viewed by setting the 1118 appropriate lsstDebug entries in the `debug.display` 1119 dictionary. The names of these entries correspond to some of 1120 the IsrTaskConfig Boolean options, with the value denoting the 1121 frame to use. The exposure is shown inside the matching 1122 option check and after the processing of that step has 1123 finished. The steps with debug points are: 1134 In addition, setting the "postISRCCD" entry displays the 1135 exposure after all ISR processing has finished. 1143 self.config.doFringe =
False 1146 if detectorNum
is None:
1147 raise RuntimeError(
"Must supply the detectorNum if running as Gen3.")
1149 ccdExposure = self.
ensureExposure(ccdExposure, camera, detectorNum)
1154 if isinstance(ccdExposure, ButlerDataRef):
1157 ccd = ccdExposure.getDetector()
1158 filterName = afwImage.Filter(ccdExposure.getFilter().getId()).getName()
1161 assert not self.config.doAssembleCcd,
"You need a Detector to run assembleCcd." 1162 ccd = [
FakeAmp(ccdExposure, self.config)]
1165 if self.config.doBias
and bias
is None:
1166 raise RuntimeError(
"Must supply a bias exposure if config.doBias=True.")
1168 raise RuntimeError(
"Must supply a linearizer if config.doLinearize=True for this detector.")
1169 if self.config.doBrighterFatter
and bfKernel
is None:
1170 raise RuntimeError(
"Must supply a kernel if config.doBrighterFatter=True.")
1171 if self.config.doDark
and dark
is None:
1172 raise RuntimeError(
"Must supply a dark exposure if config.doDark=True.")
1173 if self.config.doFlat
and flat
is None:
1174 raise RuntimeError(
"Must supply a flat exposure if config.doFlat=True.")
1175 if self.config.doDefect
and defects
is None:
1176 raise RuntimeError(
"Must supply defects if config.doDefect=True.")
1177 if self.config.doAddDistortionModel
and camera
is None:
1178 raise RuntimeError(
"Must supply camera if config.doAddDistortionModel=True.")
1179 if (self.config.doFringe
and filterName
in self.fringe.config.filters
and 1180 fringes.fringes
is None):
1185 raise RuntimeError(
"Must supply fringe exposure as a pipeBase.Struct.")
1186 if (self.config.doIlluminationCorrection
and filterName
in self.config.illumFilters
and 1187 illumMaskedImage
is None):
1188 raise RuntimeError(
"Must supply an illumcor if config.doIlluminationCorrection=True.")
1191 if self.config.doConvertIntToFloat:
1192 self.log.info(
"Converting exposure to floating point values.")
1199 if ccdExposure.getBBox().contains(amp.getBBox()):
1203 if self.config.doOverscan
and not badAmp:
1206 self.log.debug(f
"Corrected overscan for amplifier {amp.getName()}.")
1207 if self.config.qa
is not None and self.config.qa.saveStats
is True:
1208 if isinstance(overscanResults.overscanFit, float):
1209 qaMedian = overscanResults.overscanFit
1210 qaStdev = float(
"NaN")
1212 qaStats = afwMath.makeStatistics(overscanResults.overscanFit,
1213 afwMath.MEDIAN | afwMath.STDEVCLIP)
1214 qaMedian = qaStats.getValue(afwMath.MEDIAN)
1215 qaStdev = qaStats.getValue(afwMath.STDEVCLIP)
1217 self.metadata.set(f
"ISR OSCAN {amp.getName()} MEDIAN", qaMedian)
1218 self.metadata.set(f
"ISR OSCAN {amp.getName()} STDEV", qaStdev)
1219 self.log.debug(
" Overscan stats for amplifer %s: %f +/- %f" %
1220 (amp.getName(), qaMedian, qaStdev))
1221 ccdExposure.getMetadata().set(
'OVERSCAN',
"Overscan corrected")
1224 self.log.warn(f
"Amplifier {amp.getName()} is bad.")
1225 overscanResults =
None 1227 overscans.append(overscanResults
if overscanResults
is not None else None)
1229 self.log.info(f
"Skipped OSCAN for {amp.getName()}.")
1231 if self.config.doCrosstalk
and self.config.doCrosstalkBeforeAssemble:
1232 self.log.info(
"Applying crosstalk correction.")
1233 self.crosstalk.
run(ccdExposure, crosstalkSources=crosstalkSources)
1234 self.
debugView(ccdExposure,
"doCrosstalk")
1236 if self.config.doAssembleCcd:
1237 self.log.info(
"Assembling CCD from amplifiers.")
1238 ccdExposure = self.assembleCcd.assembleCcd(ccdExposure)
1240 if self.config.expectWcs
and not ccdExposure.getWcs():
1241 self.log.warn(
"No WCS found in input exposure.")
1242 self.
debugView(ccdExposure,
"doAssembleCcd")
1245 if self.config.qa.doThumbnailOss:
1246 ossThumb = isrQa.makeThumbnail(ccdExposure, isrQaConfig=self.config.qa)
1248 if self.config.doBias:
1249 self.log.info(
"Applying bias correction.")
1250 isrFunctions.biasCorrection(ccdExposure.getMaskedImage(), bias.getMaskedImage(),
1251 trimToFit=self.config.doTrimToMatchCalib)
1254 if self.config.doVariance:
1255 for amp, overscanResults
in zip(ccd, overscans):
1256 if ccdExposure.getBBox().contains(amp.getBBox()):
1257 self.log.debug(f
"Constructing variance map for amplifer {amp.getName()}.")
1258 ampExposure = ccdExposure.Factory(ccdExposure, amp.getBBox())
1259 if overscanResults
is not None:
1261 overscanImage=overscanResults.overscanImage)
1265 if self.config.qa
is not None and self.config.qa.saveStats
is True:
1266 qaStats = afwMath.makeStatistics(ampExposure.getVariance(),
1267 afwMath.MEDIAN | afwMath.STDEVCLIP)
1268 self.metadata.set(f
"ISR VARIANCE {amp.getName()} MEDIAN",
1269 qaStats.getValue(afwMath.MEDIAN))
1270 self.metadata.set(f
"ISR VARIANCE {amp.getName()} STDEV",
1271 qaStats.getValue(afwMath.STDEVCLIP))
1272 self.log.debug(
" Variance stats for amplifer %s: %f +/- %f." %
1273 (amp.getName(), qaStats.getValue(afwMath.MEDIAN),
1274 qaStats.getValue(afwMath.STDEVCLIP)))
1277 self.log.info(
"Applying linearizer.")
1278 linearizer(image=ccdExposure.getMaskedImage().getImage(), detector=ccd, log=self.log)
1280 if self.config.doCrosstalk
and not self.config.doCrosstalkBeforeAssemble:
1281 self.log.info(
"Applying crosstalk correction.")
1282 self.crosstalk.
run(ccdExposure, crosstalkSources=crosstalkSources, isTrimmed=
True)
1283 self.
debugView(ccdExposure,
"doCrosstalk")
1287 if self.config.doDefect:
1288 self.log.info(
"Masking defects.")
1291 if self.config.doNanMasking:
1292 self.log.info(
"Masking NAN value pixels.")
1295 if self.config.doWidenSaturationTrails:
1296 self.log.info(
"Widening saturation trails.")
1297 isrFunctions.widenSaturationTrails(ccdExposure.getMaskedImage().getMask())
1299 if self.config.doCameraSpecificMasking:
1300 self.log.info(
"Masking regions for camera specific reasons.")
1301 self.masking.
run(ccdExposure)
1303 if self.config.doBrighterFatter:
1312 interpExp = ccdExposure.clone()
1314 isrFunctions.interpolateFromMask(
1315 maskedImage=ccdExposure.getMaskedImage(),
1316 fwhm=self.config.fwhm,
1317 growSaturatedFootprints=self.config.growSaturationFootprintSize,
1318 maskNameList=self.config.maskListToInterpolate
1320 bfExp = interpExp.clone()
1322 self.log.info(
"Applying brighter fatter correction.")
1323 bfResults = isrFunctions.brighterFatterCorrection(bfExp, bfKernel,
1324 self.config.brighterFatterMaxIter,
1325 self.config.brighterFatterThreshold,
1326 self.config.brighterFatterApplyGain
1328 if bfResults[1] == self.config.brighterFatterMaxIter:
1329 self.log.warn(
"Brighter fatter correction did not converge, final difference {bfResults[0]}.")
1331 self.log.info(
"Finished brighter fatter correction in {bfResults[1]} iterations.")
1332 image = ccdExposure.getMaskedImage().getImage()
1333 bfCorr = bfExp.getMaskedImage().getImage()
1334 bfCorr -= interpExp.getMaskedImage().getImage()
1337 self.
debugView(ccdExposure,
"doBrighterFatter")
1339 if self.config.doDark:
1340 self.log.info(
"Applying dark correction.")
1344 if self.config.doFringe
and not self.config.fringeAfterFlat:
1345 self.log.info(
"Applying fringe correction before flat.")
1346 self.fringe.
run(ccdExposure, **fringes.getDict())
1349 if self.config.doStrayLight:
1350 if strayLightData
is not None:
1351 self.log.info(
"Applying stray light correction.")
1352 self.strayLight.
run(ccdExposure, strayLightData)
1353 self.
debugView(ccdExposure,
"doStrayLight")
1355 self.log.debug(
"Skipping stray light correction: no data found for this image.")
1357 if self.config.doFlat:
1358 self.log.info(
"Applying flat correction.")
1362 if self.config.doApplyGains:
1363 self.log.info(
"Applying gain correction instead of flat.")
1364 isrFunctions.applyGains(ccdExposure, self.config.normalizeGains)
1366 if self.config.doFringe
and self.config.fringeAfterFlat:
1367 self.log.info(
"Applying fringe correction after flat.")
1368 self.fringe.
run(ccdExposure, **fringes.getDict())
1370 if self.config.doVignette:
1371 self.log.info(
"Constructing Vignette polygon.")
1374 if self.config.vignette.doWriteVignettePolygon:
1377 if self.config.doAttachTransmissionCurve:
1378 self.log.info(
"Adding transmission curves.")
1379 isrFunctions.attachTransmissionCurve(ccdExposure, opticsTransmission=opticsTransmission,
1380 filterTransmission=filterTransmission,
1381 sensorTransmission=sensorTransmission,
1382 atmosphereTransmission=atmosphereTransmission)
1384 if self.config.doAddDistortionModel:
1385 self.log.info(
"Adding a distortion model to the WCS.")
1386 isrFunctions.addDistortionModel(exposure=ccdExposure, camera=camera)
1388 flattenedThumb =
None 1389 if self.config.qa.doThumbnailFlattened:
1390 flattenedThumb = isrQa.makeThumbnail(ccdExposure, isrQaConfig=self.config.qa)
1392 if self.config.doIlluminationCorrection
and filterName
in self.config.illumFilters:
1393 self.log.info(
"Performing illumination correction.")
1394 isrFunctions.illuminationCorrection(ccdExposure.getMaskedImage(),
1395 illumMaskedImage, illumScale=self.config.illumScale,
1396 trimToFit=self.config.doTrimToMatchCalib)
1399 if self.config.doSaveInterpPixels:
1400 preInterpExp = ccdExposure.clone()
1402 if self.config.doInterpolate:
1403 self.log.info(
"Interpolating masked pixels.")
1404 isrFunctions.interpolateFromMask(
1405 maskedImage=ccdExposure.getMaskedImage(),
1406 fwhm=self.config.fwhm,
1407 growSaturatedFootprints=self.config.growSaturationFootprintSize,
1408 maskNameList=list(self.config.maskListToInterpolate)
1411 if self.config.doSetBadRegions:
1413 badPixelCount, badPixelValue = isrFunctions.setBadRegions(ccdExposure)
1414 if badPixelCount > 0:
1415 self.log.info(
"Set %d BAD pixels to %f." % (badPixelCount, badPixelValue))
1419 if self.config.doMeasureBackground:
1420 self.log.info(
"Measuring background level.")
1423 if self.config.qa
is not None and self.config.qa.saveStats
is True:
1425 ampExposure = ccdExposure.Factory(ccdExposure, amp.getBBox())
1426 qaStats = afwMath.makeStatistics(ampExposure.getImage(),
1427 afwMath.MEDIAN | afwMath.STDEVCLIP)
1428 self.metadata.set(
"ISR BACKGROUND {} MEDIAN".format(amp.getName()),
1429 qaStats.getValue(afwMath.MEDIAN))
1430 self.metadata.set(
"ISR BACKGROUND {} STDEV".format(amp.getName()),
1431 qaStats.getValue(afwMath.STDEVCLIP))
1432 self.log.debug(
" Background stats for amplifer %s: %f +/- %f" %
1433 (amp.getName(), qaStats.getValue(afwMath.MEDIAN),
1434 qaStats.getValue(afwMath.STDEVCLIP)))
1436 self.
debugView(ccdExposure,
"postISRCCD")
1438 return pipeBase.Struct(
1439 exposure=ccdExposure,
1441 flattenedThumb=flattenedThumb,
1443 preInterpolatedExposure=preInterpExp,
1444 outputExposure=ccdExposure,
1445 outputOssThumbnail=ossThumb,
1446 outputFlattenedThumbnail=flattenedThumb,
1449 @pipeBase.timeMethod
1451 """Perform instrument signature removal on a ButlerDataRef of a Sensor. 1453 This method contains the `CmdLineTask` interface to the ISR 1454 processing. All IO is handled here, freeing the `run()` method 1455 to manage only pixel-level calculations. The steps performed 1457 - Read in necessary detrending/isr/calibration data. 1458 - Process raw exposure in `run()`. 1459 - Persist the ISR-corrected exposure as "postISRCCD" if 1460 config.doWrite=True. 1464 sensorRef : `daf.persistence.butlerSubset.ButlerDataRef` 1465 DataRef of the detector data to be processed 1469 result : `lsst.pipe.base.Struct` 1470 Result struct with component: 1471 - ``exposure`` : `afw.image.Exposure` 1472 The fully ISR corrected exposure. 1477 Raised if a configuration option is set to True, but the 1478 required calibration data does not exist. 1481 self.log.info(
"Performing ISR on sensor %s." % (sensorRef.dataId))
1483 ccdExposure = sensorRef.get(self.config.datasetType)
1485 camera = sensorRef.get(
"camera")
1486 if camera
is None and self.config.doAddDistortionModel:
1487 raise RuntimeError(
"config.doAddDistortionModel is True " 1488 "but could not get a camera from the butler.")
1489 isrData = self.
readIsrData(sensorRef, ccdExposure)
1491 result = self.
run(ccdExposure, camera=camera, **isrData.getDict())
1493 if self.config.doWrite:
1494 sensorRef.put(result.exposure,
"postISRCCD")
1495 if result.preInterpolatedExposure
is not None:
1496 sensorRef.put(result.preInterpolatedExposure,
"postISRCCD_uninterpolated")
1497 if result.ossThumb
is not None:
1498 isrQa.writeThumbnail(sensorRef, result.ossThumb,
"ossThumb")
1499 if result.flattenedThumb
is not None:
1500 isrQa.writeThumbnail(sensorRef, result.flattenedThumb,
"flattenedThumb")
1505 """!Retrieve a calibration dataset for removing instrument signature. 1510 dataRef : `daf.persistence.butlerSubset.ButlerDataRef` 1511 DataRef of the detector data to find calibration datasets 1514 Type of dataset to retrieve (e.g. 'bias', 'flat', etc). 1516 If True, disable butler proxies to enable error handling 1517 within this routine. 1521 exposure : `lsst.afw.image.Exposure` 1522 Requested calibration frame. 1527 Raised if no matching calibration frame can be found. 1530 exp = dataRef.get(datasetType, immediate=immediate)
1531 except Exception
as exc1:
1532 if not self.config.fallbackFilterName:
1533 raise RuntimeError(
"Unable to retrieve %s for %s: %s." % (datasetType, dataRef.dataId, exc1))
1535 exp = dataRef.get(datasetType, filter=self.config.fallbackFilterName, immediate=immediate)
1536 except Exception
as exc2:
1537 raise RuntimeError(
"Unable to retrieve %s for %s, even with fallback filter %s: %s AND %s." %
1538 (datasetType, dataRef.dataId, self.config.fallbackFilterName, exc1, exc2))
1539 self.log.warn(
"Using fallback calibration from filter %s." % self.config.fallbackFilterName)
1541 if self.config.doAssembleIsrExposures:
1542 exp = self.assembleCcd.assembleCcd(exp)
1546 """Ensure that the data returned by Butler is a fully constructed exposure. 1548 ISR requires exposure-level image data for historical reasons, so if we did 1549 not recieve that from Butler, construct it from what we have, modifying the 1554 inputExp : `lsst.afw.image.Exposure`, `lsst.afw.image.DecoratedImageU`, or 1555 `lsst.afw.image.ImageF` 1556 The input data structure obtained from Butler. 1557 camera : `lsst.afw.cameraGeom.camera` 1558 The camera associated with the image. Used to find the appropriate 1561 The detector this exposure should match. 1565 inputExp : `lsst.afw.image.Exposure` 1566 The re-constructed exposure, with appropriate detector parameters. 1571 Raised if the input data cannot be used to construct an exposure. 1573 if isinstance(inputExp, afwImage.DecoratedImageU):
1574 inputExp = afwImage.makeExposure(afwImage.makeMaskedImage(inputExp))
1575 elif isinstance(inputExp, afwImage.ImageF):
1576 inputExp = afwImage.makeExposure(afwImage.makeMaskedImage(inputExp))
1577 elif isinstance(inputExp, afwImage.MaskedImageF):
1578 inputExp = afwImage.makeExposure(inputExp)
1579 elif isinstance(inputExp, afwImage.Exposure):
1581 elif inputExp
is None:
1585 raise TypeError(f
"Input Exposure is not known type in isrTask.ensureExposure: {type(inputExp)}.")
1587 if inputExp.getDetector()
is None:
1588 inputExp.setDetector(camera[detectorNum])
1593 """Convert exposure image from uint16 to float. 1595 If the exposure does not need to be converted, the input is 1596 immediately returned. For exposures that are converted to use 1597 floating point pixels, the variance is set to unity and the 1602 exposure : `lsst.afw.image.Exposure` 1603 The raw exposure to be converted. 1607 newexposure : `lsst.afw.image.Exposure` 1608 The input ``exposure``, converted to floating point pixels. 1613 Raised if the exposure type cannot be converted to float. 1616 if isinstance(exposure, afwImage.ExposureF):
1618 self.log.debug(
"Exposure already of type float.")
1620 if not hasattr(exposure,
"convertF"):
1621 raise RuntimeError(
"Unable to convert exposure (%s) to float." % type(exposure))
1623 newexposure = exposure.convertF()
1624 newexposure.variance[:] = 1
1625 newexposure.mask[:] = 0x0
1630 """Identify bad amplifiers, saturated and suspect pixels. 1634 ccdExposure : `lsst.afw.image.Exposure` 1635 Input exposure to be masked. 1636 amp : `lsst.afw.table.AmpInfoCatalog` 1637 Catalog of parameters defining the amplifier on this 1639 defects : `lsst.meas.algorithms.Defects` 1640 List of defects. Used to determine if the entire 1646 If this is true, the entire amplifier area is covered by 1647 defects and unusable. 1650 maskedImage = ccdExposure.getMaskedImage()
1656 if defects
is not None:
1657 badAmp = bool(sum([v.getBBox().contains(amp.getBBox())
for v
in defects]))
1662 dataView = afwImage.MaskedImageF(maskedImage, amp.getRawBBox(),
1664 maskView = dataView.getMask()
1665 maskView |= maskView.getPlaneBitMask(
"BAD")
1672 if self.config.doSaturation
and not badAmp:
1673 limits.update({self.config.saturatedMaskName: amp.getSaturation()})
1674 if self.config.doSuspect
and not badAmp:
1675 limits.update({self.config.suspectMaskName: amp.getSuspectLevel()})
1676 if math.isfinite(self.config.saturation):
1677 limits.update({self.config.saturatedMaskName: self.config.saturation})
1679 for maskName, maskThreshold
in limits.items():
1680 if not math.isnan(maskThreshold):
1681 dataView = maskedImage.Factory(maskedImage, amp.getRawBBox())
1682 isrFunctions.makeThresholdMask(
1683 maskedImage=dataView,
1684 threshold=maskThreshold,
1690 maskView = afwImage.Mask(maskedImage.getMask(), amp.getRawDataBBox(),
1692 maskVal = maskView.getPlaneBitMask([self.config.saturatedMaskName,
1693 self.config.suspectMaskName])
1694 if numpy.all(maskView.getArray() & maskVal > 0):
1700 """Apply overscan correction in place. 1702 This method does initial pixel rejection of the overscan 1703 region. The overscan can also be optionally segmented to 1704 allow for discontinuous overscan responses to be fit 1705 separately. The actual overscan subtraction is performed by 1706 the `lsst.ip.isr.isrFunctions.overscanCorrection` function, 1707 which is called here after the amplifier is preprocessed. 1711 ccdExposure : `lsst.afw.image.Exposure` 1712 Exposure to have overscan correction performed. 1713 amp : `lsst.afw.table.AmpInfoCatalog` 1714 The amplifier to consider while correcting the overscan. 1718 overscanResults : `lsst.pipe.base.Struct` 1719 Result struct with components: 1720 - ``imageFit`` : scalar or `lsst.afw.image.Image` 1721 Value or fit subtracted from the amplifier image data. 1722 - ``overscanFit`` : scalar or `lsst.afw.image.Image` 1723 Value or fit subtracted from the overscan image data. 1724 - ``overscanImage`` : `lsst.afw.image.Image` 1725 Image of the overscan region with the overscan 1726 correction applied. This quantity is used to estimate 1727 the amplifier read noise empirically. 1732 Raised if the ``amp`` does not contain raw pixel information. 1736 lsst.ip.isr.isrFunctions.overscanCorrection 1738 if not amp.getHasRawInfo():
1739 raise RuntimeError(
"This method must be executed on an amp with raw information.")
1741 if amp.getRawHorizontalOverscanBBox().isEmpty():
1742 self.log.info(
"ISR_OSCAN: No overscan region. Not performing overscan correction.")
1745 statControl = afwMath.StatisticsControl()
1746 statControl.setAndMask(ccdExposure.mask.getPlaneBitMask(
"SAT"))
1749 dataBBox = amp.getRawDataBBox()
1750 oscanBBox = amp.getRawHorizontalOverscanBBox()
1754 prescanBBox = amp.getRawPrescanBBox()
1755 if (oscanBBox.getBeginX() > prescanBBox.getBeginX()):
1756 dx0 += self.config.overscanNumLeadingColumnsToSkip
1757 dx1 -= self.config.overscanNumTrailingColumnsToSkip
1759 dx0 += self.config.overscanNumTrailingColumnsToSkip
1760 dx1 -= self.config.overscanNumLeadingColumnsToSkip
1766 if ((self.config.overscanBiasJump
and 1767 self.config.overscanBiasJumpLocation)
and 1768 (ccdExposure.getMetadata().exists(self.config.overscanBiasJumpKeyword)
and 1769 ccdExposure.getMetadata().getScalar(self.config.overscanBiasJumpKeyword)
in 1770 self.config.overscanBiasJumpDevices)):
1771 if amp.getReadoutCorner()
in (afwTable.LL, afwTable.LR):
1772 yLower = self.config.overscanBiasJumpLocation
1773 yUpper = dataBBox.getHeight() - yLower
1775 yUpper = self.config.overscanBiasJumpLocation
1776 yLower = dataBBox.getHeight() - yUpper
1795 oscanBBox.getHeight())))
1798 for imageBBox, overscanBBox
in zip(imageBBoxes, overscanBBoxes):
1799 ampImage = ccdExposure.maskedImage[imageBBox]
1800 overscanImage = ccdExposure.maskedImage[overscanBBox]
1802 overscanArray = overscanImage.image.array
1803 median = numpy.ma.median(numpy.ma.masked_where(overscanImage.mask.array, overscanArray))
1804 bad = numpy.where(numpy.abs(overscanArray - median) > self.config.overscanMaxDev)
1805 overscanImage.mask.array[bad] = overscanImage.mask.getPlaneBitMask(
"SAT")
1807 statControl = afwMath.StatisticsControl()
1808 statControl.setAndMask(ccdExposure.mask.getPlaneBitMask(
"SAT"))
1810 overscanResults = isrFunctions.overscanCorrection(ampMaskedImage=ampImage,
1811 overscanImage=overscanImage,
1812 fitType=self.config.overscanFitType,
1813 order=self.config.overscanOrder,
1814 collapseRej=self.config.overscanNumSigmaClip,
1815 statControl=statControl,
1816 overscanIsInt=self.config.overscanIsInt
1820 levelStat = afwMath.MEDIAN
1821 sigmaStat = afwMath.STDEVCLIP
1823 sctrl = afwMath.StatisticsControl(self.config.qa.flatness.clipSigma,
1824 self.config.qa.flatness.nIter)
1825 metadata = ccdExposure.getMetadata()
1826 ampNum = amp.getName()
1827 if self.config.overscanFitType
in (
"MEDIAN",
"MEAN",
"MEANCLIP"):
1828 metadata.set(
"ISR_OSCAN_LEVEL%s" % ampNum, overscanResults.overscanFit)
1829 metadata.set(
"ISR_OSCAN_SIGMA%s" % ampNum, 0.0)
1831 stats = afwMath.makeStatistics(overscanResults.overscanFit, levelStat | sigmaStat, sctrl)
1832 metadata.set(
"ISR_OSCAN_LEVEL%s" % ampNum, stats.getValue(levelStat))
1833 metadata.set(
"ISR_OSCAN_SIGMA%s" % ampNum, stats.getValue(sigmaStat))
1835 return overscanResults
1838 """Set the variance plane using the amplifier gain and read noise 1840 The read noise is calculated from the ``overscanImage`` if the 1841 ``doEmpiricalReadNoise`` option is set in the configuration; otherwise 1842 the value from the amplifier data is used. 1846 ampExposure : `lsst.afw.image.Exposure` 1847 Exposure to process. 1848 amp : `lsst.afw.table.AmpInfoRecord` or `FakeAmp` 1849 Amplifier detector data. 1850 overscanImage : `lsst.afw.image.MaskedImage`, optional. 1851 Image of overscan, required only for empirical read noise. 1855 lsst.ip.isr.isrFunctions.updateVariance 1857 maskPlanes = [self.config.saturatedMaskName, self.config.suspectMaskName]
1858 gain = amp.getGain()
1860 if math.isnan(gain):
1862 self.log.warn(
"Gain set to NAN! Updating to 1.0 to generate Poisson variance.")
1865 self.log.warn(
"Gain for amp %s == %g <= 0; setting to %f." %
1866 (amp.getName(), gain, patchedGain))
1869 if self.config.doEmpiricalReadNoise
and overscanImage
is None:
1870 self.log.info(
"Overscan is none for EmpiricalReadNoise.")
1872 if self.config.doEmpiricalReadNoise
and overscanImage
is not None:
1873 stats = afwMath.StatisticsControl()
1874 stats.setAndMask(overscanImage.mask.getPlaneBitMask(maskPlanes))
1875 readNoise = afwMath.makeStatistics(overscanImage, afwMath.STDEVCLIP, stats).getValue()
1876 self.log.info(
"Calculated empirical read noise for amp %s: %f.", amp.getName(), readNoise)
1878 readNoise = amp.getReadNoise()
1880 isrFunctions.updateVariance(
1881 maskedImage=ampExposure.getMaskedImage(),
1883 readNoise=readNoise,
1887 """!Apply dark correction in place. 1891 exposure : `lsst.afw.image.Exposure` 1892 Exposure to process. 1893 darkExposure : `lsst.afw.image.Exposure` 1894 Dark exposure of the same size as ``exposure``. 1895 invert : `Bool`, optional 1896 If True, re-add the dark to an already corrected image. 1901 Raised if either ``exposure`` or ``darkExposure`` do not 1902 have their dark time defined. 1906 lsst.ip.isr.isrFunctions.darkCorrection 1908 expScale = exposure.getInfo().getVisitInfo().getDarkTime()
1909 if math.isnan(expScale):
1910 raise RuntimeError(
"Exposure darktime is NAN.")
1911 if darkExposure.getInfo().getVisitInfo()
is not None:
1912 darkScale = darkExposure.getInfo().getVisitInfo().getDarkTime()
1916 self.log.warn(
"darkExposure.getInfo().getVisitInfo() does not exist. Using darkScale = 1.0.")
1919 if math.isnan(darkScale):
1920 raise RuntimeError(
"Dark calib darktime is NAN.")
1921 isrFunctions.darkCorrection(
1922 maskedImage=exposure.getMaskedImage(),
1923 darkMaskedImage=darkExposure.getMaskedImage(),
1925 darkScale=darkScale,
1927 trimToFit=self.config.doTrimToMatchCalib
1931 """!Check if linearization is needed for the detector cameraGeom. 1933 Checks config.doLinearize and the linearity type of the first 1938 detector : `lsst.afw.cameraGeom.Detector` 1939 Detector to get linearity type from. 1943 doLinearize : `Bool` 1944 If True, linearization should be performed. 1946 return self.config.doLinearize
and \
1947 detector.getAmpInfoCatalog()[0].getLinearityType() != NullLinearityType
1950 """!Apply flat correction in place. 1954 exposure : `lsst.afw.image.Exposure` 1955 Exposure to process. 1956 flatExposure : `lsst.afw.image.Exposure` 1957 Flat exposure of the same size as ``exposure``. 1958 invert : `Bool`, optional 1959 If True, unflatten an already flattened image. 1963 lsst.ip.isr.isrFunctions.flatCorrection 1965 isrFunctions.flatCorrection(
1966 maskedImage=exposure.getMaskedImage(),
1967 flatMaskedImage=flatExposure.getMaskedImage(),
1968 scalingType=self.config.flatScalingType,
1969 userScale=self.config.flatUserScale,
1971 trimToFit=self.config.doTrimToMatchCalib
1975 """!Detect saturated pixels and mask them using mask plane config.saturatedMaskName, in place. 1979 exposure : `lsst.afw.image.Exposure` 1980 Exposure to process. Only the amplifier DataSec is processed. 1981 amp : `lsst.afw.table.AmpInfoCatalog` 1982 Amplifier detector data. 1986 lsst.ip.isr.isrFunctions.makeThresholdMask 1988 if not math.isnan(amp.getSaturation()):
1989 maskedImage = exposure.getMaskedImage()
1990 dataView = maskedImage.Factory(maskedImage, amp.getRawBBox())
1991 isrFunctions.makeThresholdMask(
1992 maskedImage=dataView,
1993 threshold=amp.getSaturation(),
1995 maskName=self.config.saturatedMaskName,
1999 """!Interpolate over saturated pixels, in place. 2001 This method should be called after `saturationDetection`, to 2002 ensure that the saturated pixels have been identified in the 2003 SAT mask. It should also be called after `assembleCcd`, since 2004 saturated regions may cross amplifier boundaries. 2008 exposure : `lsst.afw.image.Exposure` 2009 Exposure to process. 2013 lsst.ip.isr.isrTask.saturationDetection 2014 lsst.ip.isr.isrFunctions.interpolateFromMask 2016 isrFunctions.interpolateFromMask(
2017 maskedImage=exposure.getMaskedImage(),
2018 fwhm=self.config.fwhm,
2019 growSaturatedFootprints=self.config.growSaturationFootprintSize,
2020 maskNameList=list(self.config.saturatedMaskName),
2024 """!Detect suspect pixels and mask them using mask plane config.suspectMaskName, in place. 2028 exposure : `lsst.afw.image.Exposure` 2029 Exposure to process. Only the amplifier DataSec is processed. 2030 amp : `lsst.afw.table.AmpInfoCatalog` 2031 Amplifier detector data. 2035 lsst.ip.isr.isrFunctions.makeThresholdMask 2039 Suspect pixels are pixels whose value is greater than amp.getSuspectLevel(). 2040 This is intended to indicate pixels that may be affected by unknown systematics; 2041 for example if non-linearity corrections above a certain level are unstable 2042 then that would be a useful value for suspectLevel. A value of `nan` indicates 2043 that no such level exists and no pixels are to be masked as suspicious. 2045 suspectLevel = amp.getSuspectLevel()
2046 if math.isnan(suspectLevel):
2049 maskedImage = exposure.getMaskedImage()
2050 dataView = maskedImage.Factory(maskedImage, amp.getRawBBox())
2051 isrFunctions.makeThresholdMask(
2052 maskedImage=dataView,
2053 threshold=suspectLevel,
2055 maskName=self.config.suspectMaskName,
2059 """!Mask defects using mask plane "BAD", in place. 2063 exposure : `lsst.afw.image.Exposure` 2064 Exposure to process. 2065 defectBaseList : `lsst.meas.algorithms.Defects` or `list` of 2066 `lsst.afw.image.DefectBase`. 2067 List of defects to mask and interpolate. 2071 Call this after CCD assembly, since defects may cross amplifier boundaries. 2073 maskedImage = exposure.getMaskedImage()
2074 if not isinstance(defectBaseList, Defects):
2076 defectList = Defects(defectBaseList)
2078 defectList = defectBaseList
2079 defectList.maskPixels(maskedImage, maskName=
"BAD")
2081 if self.config.numEdgeSuspect > 0:
2082 goodBBox = maskedImage.getBBox()
2084 goodBBox.grow(-self.config.numEdgeSuspect)
2086 SourceDetectionTask.setEdgeBits(
2089 maskedImage.getMask().getPlaneBitMask(
"SUSPECT")
2093 """Mask and interpolate defects using mask plane "BAD", in place. 2097 exposure : `lsst.afw.image.Exposure` 2098 Exposure to process. 2099 defectBaseList : `List` of `Defects` 2102 self.maskDefects(exposure, defectBaseList)
2103 isrFunctions.interpolateFromMask(
2104 maskedImage=exposure.getMaskedImage(),
2105 fwhm=self.config.fwhm,
2106 growSaturatedFootprints=0,
2107 maskNameList=[
"BAD"],
2111 """Mask NaNs using mask plane "UNMASKEDNAN", in place. 2115 exposure : `lsst.afw.image.Exposure` 2116 Exposure to process. 2120 We mask over all NaNs, including those that are masked with 2121 other bits (because those may or may not be interpolated over 2122 later, and we want to remove all NaNs). Despite this 2123 behaviour, the "UNMASKEDNAN" mask plane is used to preserve 2124 the historical name. 2126 maskedImage = exposure.getMaskedImage()
2129 maskedImage.getMask().addMaskPlane(
"UNMASKEDNAN")
2130 maskVal = maskedImage.getMask().getPlaneBitMask(
"UNMASKEDNAN")
2131 numNans =
maskNans(maskedImage, maskVal)
2132 self.metadata.set(
"NUMNANS", numNans)
2134 self.log.warn(f
"There were {numNans} unmasked NaNs.")
2137 """"Mask and interpolate NaNs using mask plane "UNMASKEDNAN", in place. 2141 exposure : `lsst.afw.image.Exposure` 2142 Exposure to process. 2146 lsst.ip.isr.isrTask.maskNan() 2149 isrFunctions.interpolateFromMask(
2150 maskedImage=exposure.getMaskedImage(),
2151 fwhm=self.config.fwhm,
2152 growSaturatedFootprints=0,
2153 maskNameList=[
"UNMASKEDNAN"],
2157 """Measure the image background in subgrids, for quality control purposes. 2161 exposure : `lsst.afw.image.Exposure` 2162 Exposure to process. 2163 IsrQaConfig : `lsst.ip.isr.isrQa.IsrQaConfig` 2164 Configuration object containing parameters on which background 2165 statistics and subgrids to use. 2167 if IsrQaConfig
is not None:
2168 statsControl = afwMath.StatisticsControl(IsrQaConfig.flatness.clipSigma,
2169 IsrQaConfig.flatness.nIter)
2170 maskVal = exposure.getMaskedImage().getMask().getPlaneBitMask([
"BAD",
"SAT",
"DETECTED"])
2171 statsControl.setAndMask(maskVal)
2172 maskedImage = exposure.getMaskedImage()
2173 stats = afwMath.makeStatistics(maskedImage, afwMath.MEDIAN | afwMath.STDEVCLIP, statsControl)
2174 skyLevel = stats.getValue(afwMath.MEDIAN)
2175 skySigma = stats.getValue(afwMath.STDEVCLIP)
2176 self.log.info(
"Flattened sky level: %f +/- %f." % (skyLevel, skySigma))
2177 metadata = exposure.getMetadata()
2178 metadata.set(
'SKYLEVEL', skyLevel)
2179 metadata.set(
'SKYSIGMA', skySigma)
2182 stat = afwMath.MEANCLIP
if IsrQaConfig.flatness.doClip
else afwMath.MEAN
2183 meshXHalf = int(IsrQaConfig.flatness.meshX/2.)
2184 meshYHalf = int(IsrQaConfig.flatness.meshY/2.)
2185 nX = int((exposure.getWidth() + meshXHalf) / IsrQaConfig.flatness.meshX)
2186 nY = int((exposure.getHeight() + meshYHalf) / IsrQaConfig.flatness.meshY)
2187 skyLevels = numpy.zeros((nX, nY))
2190 yc = meshYHalf + j * IsrQaConfig.flatness.meshY
2192 xc = meshXHalf + i * IsrQaConfig.flatness.meshX
2194 xLLC = xc - meshXHalf
2195 yLLC = yc - meshYHalf
2196 xURC = xc + meshXHalf - 1
2197 yURC = yc + meshYHalf - 1
2200 miMesh = maskedImage.Factory(exposure.getMaskedImage(), bbox, afwImage.LOCAL)
2202 skyLevels[i, j] = afwMath.makeStatistics(miMesh, stat, statsControl).getValue()
2204 good = numpy.where(numpy.isfinite(skyLevels))
2205 skyMedian = numpy.median(skyLevels[good])
2206 flatness = (skyLevels[good] - skyMedian) / skyMedian
2207 flatness_rms = numpy.std(flatness)
2208 flatness_pp = flatness.max() - flatness.min()
if len(flatness) > 0
else numpy.nan
2210 self.log.info(
"Measuring sky levels in %dx%d grids: %f." % (nX, nY, skyMedian))
2211 self.log.info(
"Sky flatness in %dx%d grids - pp: %f rms: %f." %
2212 (nX, nY, flatness_pp, flatness_rms))
2214 metadata.set(
'FLATNESS_PP', float(flatness_pp))
2215 metadata.set(
'FLATNESS_RMS', float(flatness_rms))
2216 metadata.set(
'FLATNESS_NGRIDS',
'%dx%d' % (nX, nY))
2217 metadata.set(
'FLATNESS_MESHX', IsrQaConfig.flatness.meshX)
2218 metadata.set(
'FLATNESS_MESHY', IsrQaConfig.flatness.meshY)
2221 """Set an approximate magnitude zero point for the exposure. 2225 exposure : `lsst.afw.image.Exposure` 2226 Exposure to process. 2228 filterName = afwImage.Filter(exposure.getFilter().getId()).getName()
2229 if filterName
in self.config.fluxMag0T1:
2230 fluxMag0 = self.config.fluxMag0T1[filterName]
2232 self.log.warn(
"No rough magnitude zero point set for filter %s." % filterName)
2233 fluxMag0 = self.config.defaultFluxMag0T1
2235 expTime = exposure.getInfo().getVisitInfo().getExposureTime()
2237 self.log.warn(
"Non-positive exposure time; skipping rough zero point.")
2240 self.log.info(
"Setting rough magnitude zero point: %f" % (2.5*math.log10(fluxMag0*expTime),))
2241 exposure.setPhotoCalib(afwImage.makePhotoCalibFromCalibZeroPoint(fluxMag0*expTime, 0.0))
2244 """!Set the valid polygon as the intersection of fpPolygon and the ccd corners. 2248 ccdExposure : `lsst.afw.image.Exposure` 2249 Exposure to process. 2250 fpPolygon : `lsst.afw.geom.Polygon` 2251 Polygon in focal plane coordinates. 2254 ccd = ccdExposure.getDetector()
2255 fpCorners = ccd.getCorners(FOCAL_PLANE)
2256 ccdPolygon = Polygon(fpCorners)
2259 intersect = ccdPolygon.intersectionSingle(fpPolygon)
2262 ccdPoints = ccd.transform(intersect, FOCAL_PLANE, PIXELS)
2263 validPolygon = Polygon(ccdPoints)
2264 ccdExposure.getInfo().setValidPolygon(validPolygon)
2268 """Context manager that applies and removes flats and darks, 2269 if the task is configured to apply them. 2273 exp : `lsst.afw.image.Exposure` 2274 Exposure to process. 2275 flat : `lsst.afw.image.Exposure` 2276 Flat exposure the same size as ``exp``. 2277 dark : `lsst.afw.image.Exposure`, optional 2278 Dark exposure the same size as ``exp``. 2282 exp : `lsst.afw.image.Exposure` 2283 The flat and dark corrected exposure. 2285 if self.config.doDark
and dark
is not None:
2287 if self.config.doFlat:
2292 if self.config.doFlat:
2294 if self.config.doDark
and dark
is not None:
2298 """Utility function to examine ISR exposure at different stages. 2302 exposure : `lsst.afw.image.Exposure` 2305 State of processing to view. 2307 frame = getDebugFrame(self._display, stepname)
2309 display = getDisplay(frame)
2310 display.scale(
'asinh',
'zscale')
2311 display.mtv(exposure)
2315 """A Detector-like object that supports returning gain and saturation level 2317 This is used when the input exposure does not have a detector. 2321 exposure : `lsst.afw.image.Exposure` 2322 Exposure to generate a fake amplifier for. 2323 config : `lsst.ip.isr.isrTaskConfig` 2324 Configuration to apply to the fake amplifier. 2328 self.
_bbox = exposure.getBBox(afwImage.LOCAL)
2330 self.
_gain = config.gain
2360 isr = pexConfig.ConfigurableField(target=IsrTask, doc=
"Instrument signature removal")
2364 """Task to wrap the default IsrTask to allow it to be retargeted. 2366 The standard IsrTask can be called directly from a command line 2367 program, but doing so removes the ability of the task to be 2368 retargeted. As most cameras override some set of the IsrTask 2369 methods, this would remove those data-specific methods in the 2370 output post-ISR images. This wrapping class fixes the issue, 2371 allowing identical post-ISR images to be generated by both the 2372 processCcd and isrTask code. 2374 ConfigClass = RunIsrConfig
2375 _DefaultName =
"runIsr" 2379 self.makeSubtask(
"isr")
2385 dataRef : `lsst.daf.persistence.ButlerDataRef` 2386 data reference of the detector data to be processed 2390 result : `pipeBase.Struct` 2391 Result struct with component: 2393 - exposure : `lsst.afw.image.Exposure` 2394 Post-ISR processed exposure. def getInputDatasetTypes(cls, config)
def runDataRef(self, sensorRef)
def measureBackground(self, exposure, IsrQaConfig=None)
def debugView(self, exposure, stepname)
def __init__(self, kwargs)
def ensureExposure(self, inputExp, camera, detectorNum)
def readIsrData(self, dataRef, rawExposure)
Retrieve necessary frames for instrument signature removal.
def adaptArgsAndRun(self, inputData, inputDataIds, outputDataIds, butler)
def runDataRef(self, dataRef)
def run(self, ccdExposure, camera=None, bias=None, linearizer=None, crosstalkSources=None, dark=None, flat=None, bfKernel=None, defects=None, fringes=pipeBase.Struct(fringes=None), opticsTransmission=None, filterTransmission=None, sensorTransmission=None, atmosphereTransmission=None, detectorNum=None, strayLightData=None, illumMaskedImage=None, isGen3=False)
Perform instrument signature removal on an exposure.
def __init__(self, args, kwargs)
def getPrerequisiteDatasetTypes(cls, config)
def roughZeroPoint(self, exposure)
def maskAndInterpolateDefects(self, exposure, defectBaseList)
def getRawHorizontalOverscanBBox(self)
def maskNan(self, exposure)
def getSuspectLevel(self)
def getOutputDatasetTypes(cls, config)
def maskDefect(self, exposure, defectBaseList)
Mask defects using mask plane "BAD", in place.
def overscanCorrection(self, ccdExposure, amp)
def convertIntToFloat(self, exposure)
def flatCorrection(self, exposure, flatExposure, invert=False)
Apply flat correction in place.
def makeDatasetType(self, dsConfig)
def getIsrExposure(self, dataRef, datasetType, immediate=True)
Retrieve a calibration dataset for removing instrument signature.
_RawHorizontalOverscanBBox
def darkCorrection(self, exposure, darkExposure, invert=False)
Apply dark correction in place.
def doLinearize(self, detector)
Check if linearization is needed for the detector cameraGeom.
def setValidPolygonIntersect(self, ccdExposure, fpPolygon)
Set the valid polygon as the intersection of fpPolygon and the ccd corners.
def maskAmplifier(self, ccdExposure, amp, defects)
def getPerDatasetTypeDimensions(cls, config)
def flatContext(self, exp, flat, dark=None)
size_t maskNans(afw::image::MaskedImage< PixelT > const &mi, afw::image::MaskPixel maskVal, afw::image::MaskPixel allow=0)
Mask NANs in an image.
def updateVariance(self, ampExposure, amp, overscanImage=None)
def maskAndInterpolateNan(self, exposure)
def suspectDetection(self, exposure, amp)
Detect suspect pixels and mask them using mask plane config.suspectMaskName, in place.
def saturationInterpolation(self, exposure)
Interpolate over saturated pixels, in place.
def saturationDetection(self, exposure, amp)
Detect saturated pixels and mask them using mask plane config.saturatedMaskName, in place...
doSaturationInterpolation
def __init__(self, exposure, config)