29 import lsst.pipe.base
as pipeBase
30 import lsst.pipe.base.connectionTypes
as cT
32 from contextlib
import contextmanager
33 from lsstDebug
import getDebugFrame
43 from .
import isrFunctions
45 from .
import linearize
46 from .defects
import Defects
48 from .assembleCcdTask
import AssembleCcdTask
49 from .crosstalk
import CrosstalkTask, CrosstalkCalib
50 from .fringe
import FringeTask
51 from .isr
import maskNans
52 from .masking
import MaskingTask
53 from .overscan
import OverscanCorrectionTask
54 from .straylight
import StrayLightTask
55 from .vignette
import VignetteTask
56 from lsst.daf.butler
import DimensionGraph
59 __all__ = [
"IsrTask",
"IsrTaskConfig",
"RunIsrTask",
"RunIsrConfig"]
63 """Lookup function to identify crosstalkSource entries.
65 This should return an empty list under most circumstances. Only
66 when inter-chip crosstalk has been identified should this be
69 This will be unused until DM-25348 resolves the quantum graph
76 registry : `lsst.daf.butler.Registry`
77 Butler registry to query.
78 quantumDataId : `lsst.daf.butler.ExpandedDataCoordinate`
79 Data id to transform to identify crosstalkSources. The
80 ``detector`` entry will be stripped.
81 collections : `lsst.daf.butler.CollectionSearch`
82 Collections to search through.
86 results : `list` [`lsst.daf.butler.DatasetRef`]
87 List of datasets that match the query that will be used as
90 newDataId = quantumDataId.subset(DimensionGraph(registry.dimensions, names=[
"instrument",
"exposure"]))
91 results = list(registry.queryDatasets(datasetType,
92 collections=collections,
100 dimensions={
"instrument",
"exposure",
"detector"},
101 defaultTemplates={}):
102 ccdExposure = cT.Input(
104 doc=
"Input exposure to process.",
105 storageClass=
"Exposure",
106 dimensions=[
"instrument",
"exposure",
"detector"],
108 camera = cT.PrerequisiteInput(
110 storageClass=
"Camera",
111 doc=
"Input camera to construct complete exposures.",
112 dimensions=[
"instrument"],
116 crosstalk = cT.PrerequisiteInput(
118 doc=
"Input crosstalk object",
119 storageClass=
"CrosstalkCalib",
120 dimensions=[
"instrument",
"detector"],
125 crosstalkSources = cT.PrerequisiteInput(
126 name=
"isrOverscanCorrected",
127 doc=
"Overscan corrected input images.",
128 storageClass=
"Exposure",
129 dimensions=[
"instrument",
"exposure",
"detector"],
132 lookupFunction=crosstalkSourceLookup,
134 bias = cT.PrerequisiteInput(
136 doc=
"Input bias calibration.",
137 storageClass=
"ExposureF",
138 dimensions=[
"instrument",
"detector"],
141 dark = cT.PrerequisiteInput(
143 doc=
"Input dark calibration.",
144 storageClass=
"ExposureF",
145 dimensions=[
"instrument",
"detector"],
148 flat = cT.PrerequisiteInput(
150 doc=
"Input flat calibration.",
151 storageClass=
"ExposureF",
152 dimensions=[
"instrument",
"physical_filter",
"detector"],
155 ptc = cT.PrerequisiteInput(
157 doc=
"Input Photon Transfer Curve dataset",
158 storageClass=
"PhotonTransferCurveDataset",
159 dimensions=[
"instrument",
"detector"],
162 fringes = cT.PrerequisiteInput(
164 doc=
"Input fringe calibration.",
165 storageClass=
"ExposureF",
166 dimensions=[
"instrument",
"physical_filter",
"detector"],
169 strayLightData = cT.PrerequisiteInput(
171 doc=
"Input stray light calibration.",
172 storageClass=
"StrayLightData",
173 dimensions=[
"instrument",
"physical_filter",
"detector"],
176 bfKernel = cT.PrerequisiteInput(
178 doc=
"Input brighter-fatter kernel.",
179 storageClass=
"NumpyArray",
180 dimensions=[
"instrument"],
183 newBFKernel = cT.PrerequisiteInput(
184 name=
'brighterFatterKernel',
185 doc=
"Newer complete kernel + gain solutions.",
186 storageClass=
"BrighterFatterKernel",
187 dimensions=[
"instrument",
"detector"],
190 defects = cT.PrerequisiteInput(
192 doc=
"Input defect tables.",
193 storageClass=
"Defects",
194 dimensions=[
"instrument",
"detector"],
197 linearizer = cT.PrerequisiteInput(
199 storageClass=
"Linearizer",
200 doc=
"Linearity correction calibration.",
201 dimensions=[
"instrument",
"detector"],
204 opticsTransmission = cT.PrerequisiteInput(
205 name=
"transmission_optics",
206 storageClass=
"TransmissionCurve",
207 doc=
"Transmission curve due to the optics.",
208 dimensions=[
"instrument"],
211 filterTransmission = cT.PrerequisiteInput(
212 name=
"transmission_filter",
213 storageClass=
"TransmissionCurve",
214 doc=
"Transmission curve due to the filter.",
215 dimensions=[
"instrument",
"physical_filter"],
218 sensorTransmission = cT.PrerequisiteInput(
219 name=
"transmission_sensor",
220 storageClass=
"TransmissionCurve",
221 doc=
"Transmission curve due to the sensor.",
222 dimensions=[
"instrument",
"detector"],
225 atmosphereTransmission = cT.PrerequisiteInput(
226 name=
"transmission_atmosphere",
227 storageClass=
"TransmissionCurve",
228 doc=
"Transmission curve due to the atmosphere.",
229 dimensions=[
"instrument"],
232 illumMaskedImage = cT.PrerequisiteInput(
234 doc=
"Input illumination correction.",
235 storageClass=
"MaskedImageF",
236 dimensions=[
"instrument",
"physical_filter",
"detector"],
240 outputExposure = cT.Output(
242 doc=
"Output ISR processed exposure.",
243 storageClass=
"Exposure",
244 dimensions=[
"instrument",
"exposure",
"detector"],
246 preInterpExposure = cT.Output(
247 name=
'preInterpISRCCD',
248 doc=
"Output ISR processed exposure, with pixels left uninterpolated.",
249 storageClass=
"ExposureF",
250 dimensions=[
"instrument",
"exposure",
"detector"],
252 outputOssThumbnail = cT.Output(
254 doc=
"Output Overscan-subtracted thumbnail image.",
255 storageClass=
"Thumbnail",
256 dimensions=[
"instrument",
"exposure",
"detector"],
258 outputFlattenedThumbnail = cT.Output(
259 name=
"FlattenedThumb",
260 doc=
"Output flat-corrected thumbnail image.",
261 storageClass=
"Thumbnail",
262 dimensions=[
"instrument",
"exposure",
"detector"],
268 if config.doBias
is not True:
269 self.prerequisiteInputs.discard(
"bias")
270 if config.doLinearize
is not True:
271 self.prerequisiteInputs.discard(
"linearizer")
272 if config.doCrosstalk
is not True:
273 self.inputs.discard(
"crosstalkSources")
274 self.prerequisiteInputs.discard(
"crosstalk")
275 if config.doBrighterFatter
is not True:
276 self.prerequisiteInputs.discard(
"bfKernel")
277 self.prerequisiteInputs.discard(
"newBFKernel")
278 if config.doDefect
is not True:
279 self.prerequisiteInputs.discard(
"defects")
280 if config.doDark
is not True:
281 self.prerequisiteInputs.discard(
"dark")
282 if config.doFlat
is not True:
283 self.prerequisiteInputs.discard(
"flat")
284 if config.usePtcGains
is not True and config.usePtcReadNoise
is not True:
285 self.prerequisiteInputs.discard(
"ptc")
286 if config.doAttachTransmissionCurve
is not True:
287 self.prerequisiteInputs.discard(
"opticsTransmission")
288 self.prerequisiteInputs.discard(
"filterTransmission")
289 self.prerequisiteInputs.discard(
"sensorTransmission")
290 self.prerequisiteInputs.discard(
"atmosphereTransmission")
291 if config.doUseOpticsTransmission
is not True:
292 self.prerequisiteInputs.discard(
"opticsTransmission")
293 if config.doUseFilterTransmission
is not True:
294 self.prerequisiteInputs.discard(
"filterTransmission")
295 if config.doUseSensorTransmission
is not True:
296 self.prerequisiteInputs.discard(
"sensorTransmission")
297 if config.doUseAtmosphereTransmission
is not True:
298 self.prerequisiteInputs.discard(
"atmosphereTransmission")
299 if config.doIlluminationCorrection
is not True:
300 self.prerequisiteInputs.discard(
"illumMaskedImage")
302 if config.doWrite
is not True:
303 self.outputs.discard(
"outputExposure")
304 self.outputs.discard(
"preInterpExposure")
305 self.outputs.discard(
"outputFlattenedThumbnail")
306 self.outputs.discard(
"outputOssThumbnail")
307 if config.doSaveInterpPixels
is not True:
308 self.outputs.discard(
"preInterpExposure")
309 if config.qa.doThumbnailOss
is not True:
310 self.outputs.discard(
"outputOssThumbnail")
311 if config.qa.doThumbnailFlattened
is not True:
312 self.outputs.discard(
"outputFlattenedThumbnail")
316 pipelineConnections=IsrTaskConnections):
317 """Configuration parameters for IsrTask.
319 Items are grouped in the order in which they are executed by the task.
321 datasetType = pexConfig.Field(
323 doc=
"Dataset type for input data; users will typically leave this alone, "
324 "but camera-specific ISR tasks will override it",
328 fallbackFilterName = pexConfig.Field(
330 doc=
"Fallback default filter name for calibrations.",
333 useFallbackDate = pexConfig.Field(
335 doc=
"Pass observation date when using fallback filter.",
338 expectWcs = pexConfig.Field(
341 doc=
"Expect input science images to have a WCS (set False for e.g. spectrographs)."
343 fwhm = pexConfig.Field(
345 doc=
"FWHM of PSF in arcseconds.",
348 qa = pexConfig.ConfigField(
350 doc=
"QA related configuration options.",
354 doConvertIntToFloat = pexConfig.Field(
356 doc=
"Convert integer raw images to floating point values?",
361 doSaturation = pexConfig.Field(
363 doc=
"Mask saturated pixels? NB: this is totally independent of the"
364 " interpolation option - this is ONLY setting the bits in the mask."
365 " To have them interpolated make sure doSaturationInterpolation=True",
368 saturatedMaskName = pexConfig.Field(
370 doc=
"Name of mask plane to use in saturation detection and interpolation",
373 saturation = pexConfig.Field(
375 doc=
"The saturation level to use if no Detector is present in the Exposure (ignored if NaN)",
376 default=float(
"NaN"),
378 growSaturationFootprintSize = pexConfig.Field(
380 doc=
"Number of pixels by which to grow the saturation footprints",
385 doSuspect = pexConfig.Field(
387 doc=
"Mask suspect pixels?",
390 suspectMaskName = pexConfig.Field(
392 doc=
"Name of mask plane to use for suspect pixels",
395 numEdgeSuspect = pexConfig.Field(
397 doc=
"Number of edge pixels to be flagged as untrustworthy.",
400 edgeMaskLevel = pexConfig.ChoiceField(
402 doc=
"Mask edge pixels in which coordinate frame: DETECTOR or AMP?",
405 'DETECTOR':
'Mask only the edges of the full detector.',
406 'AMP':
'Mask edges of each amplifier.',
411 doSetBadRegions = pexConfig.Field(
413 doc=
"Should we set the level of all BAD patches of the chip to the chip's average value?",
416 badStatistic = pexConfig.ChoiceField(
418 doc=
"How to estimate the average value for BAD regions.",
421 "MEANCLIP":
"Correct using the (clipped) mean of good data",
422 "MEDIAN":
"Correct using the median of the good data",
427 doOverscan = pexConfig.Field(
429 doc=
"Do overscan subtraction?",
432 overscan = pexConfig.ConfigurableField(
433 target=OverscanCorrectionTask,
434 doc=
"Overscan subtraction task for image segments.",
437 overscanFitType = pexConfig.ChoiceField(
439 doc=
"The method for fitting the overscan bias level.",
442 "POLY":
"Fit ordinary polynomial to the longest axis of the overscan region",
443 "CHEB":
"Fit Chebyshev polynomial to the longest axis of the overscan region",
444 "LEG":
"Fit Legendre polynomial to the longest axis of the overscan region",
445 "NATURAL_SPLINE":
"Fit natural spline to the longest axis of the overscan region",
446 "CUBIC_SPLINE":
"Fit cubic spline to the longest axis of the overscan region",
447 "AKIMA_SPLINE":
"Fit Akima spline to the longest axis of the overscan region",
448 "MEAN":
"Correct using the mean of the overscan region",
449 "MEANCLIP":
"Correct using a clipped mean of the overscan region",
450 "MEDIAN":
"Correct using the median of the overscan region",
451 "MEDIAN_PER_ROW":
"Correct using the median per row of the overscan region",
453 deprecated=(
"Please configure overscan via the OverscanCorrectionConfig interface."
454 " This option will no longer be used, and will be removed after v20.")
456 overscanOrder = pexConfig.Field(
458 doc=(
"Order of polynomial or to fit if overscan fit type is a polynomial, "
459 "or number of spline knots if overscan fit type is a spline."),
461 deprecated=(
"Please configure overscan via the OverscanCorrectionConfig interface."
462 " This option will no longer be used, and will be removed after v20.")
464 overscanNumSigmaClip = pexConfig.Field(
466 doc=
"Rejection threshold (sigma) for collapsing overscan before fit",
468 deprecated=(
"Please configure overscan via the OverscanCorrectionConfig interface."
469 " This option will no longer be used, and will be removed after v20.")
471 overscanIsInt = pexConfig.Field(
473 doc=
"Treat overscan as an integer image for purposes of overscan.FitType=MEDIAN"
474 " and overscan.FitType=MEDIAN_PER_ROW.",
476 deprecated=(
"Please configure overscan via the OverscanCorrectionConfig interface."
477 " This option will no longer be used, and will be removed after v20.")
480 overscanNumLeadingColumnsToSkip = pexConfig.Field(
482 doc=
"Number of columns to skip in overscan, i.e. those closest to amplifier",
485 overscanNumTrailingColumnsToSkip = pexConfig.Field(
487 doc=
"Number of columns to skip in overscan, i.e. those farthest from amplifier",
490 overscanMaxDev = pexConfig.Field(
492 doc=
"Maximum deviation from the median for overscan",
493 default=1000.0, check=
lambda x: x > 0
495 overscanBiasJump = pexConfig.Field(
497 doc=
"Fit the overscan in a piecewise-fashion to correct for bias jumps?",
500 overscanBiasJumpKeyword = pexConfig.Field(
502 doc=
"Header keyword containing information about devices.",
503 default=
"NO_SUCH_KEY",
505 overscanBiasJumpDevices = pexConfig.ListField(
507 doc=
"List of devices that need piecewise overscan correction.",
510 overscanBiasJumpLocation = pexConfig.Field(
512 doc=
"Location of bias jump along y-axis.",
517 doAssembleCcd = pexConfig.Field(
520 doc=
"Assemble amp-level exposures into a ccd-level exposure?"
522 assembleCcd = pexConfig.ConfigurableField(
523 target=AssembleCcdTask,
524 doc=
"CCD assembly task",
528 doAssembleIsrExposures = pexConfig.Field(
531 doc=
"Assemble amp-level calibration exposures into ccd-level exposure?"
533 doTrimToMatchCalib = pexConfig.Field(
536 doc=
"Trim raw data to match calibration bounding boxes?"
540 doBias = pexConfig.Field(
542 doc=
"Apply bias frame correction?",
545 biasDataProductName = pexConfig.Field(
547 doc=
"Name of the bias data product",
550 doBiasBeforeOverscan = pexConfig.Field(
552 doc=
"Reverse order of overscan and bias correction.",
557 doVariance = pexConfig.Field(
559 doc=
"Calculate variance?",
562 gain = pexConfig.Field(
564 doc=
"The gain to use if no Detector is present in the Exposure (ignored if NaN)",
565 default=float(
"NaN"),
567 readNoise = pexConfig.Field(
569 doc=
"The read noise to use if no Detector is present in the Exposure",
572 doEmpiricalReadNoise = pexConfig.Field(
575 doc=
"Calculate empirical read noise instead of value from AmpInfo data?"
577 usePtcReadNoise = pexConfig.Field(
580 doc=
"Use readnoise values from the Photon Transfer Curve?"
583 doLinearize = pexConfig.Field(
585 doc=
"Correct for nonlinearity of the detector's response?",
590 doCrosstalk = pexConfig.Field(
592 doc=
"Apply intra-CCD crosstalk correction?",
595 doCrosstalkBeforeAssemble = pexConfig.Field(
597 doc=
"Apply crosstalk correction before CCD assembly, and before trimming?",
600 crosstalk = pexConfig.ConfigurableField(
601 target=CrosstalkTask,
602 doc=
"Intra-CCD crosstalk correction",
606 doDefect = pexConfig.Field(
608 doc=
"Apply correction for CCD defects, e.g. hot pixels?",
611 doNanMasking = pexConfig.Field(
613 doc=
"Mask non-finite (NAN, inf) pixels?",
616 doWidenSaturationTrails = pexConfig.Field(
618 doc=
"Widen bleed trails based on their width?",
623 doBrighterFatter = pexConfig.Field(
626 doc=
"Apply the brighter-fatter correction?"
628 brighterFatterLevel = pexConfig.ChoiceField(
631 doc=
"The level at which to correct for brighter-fatter.",
633 "AMP":
"Every amplifier treated separately.",
634 "DETECTOR":
"One kernel per detector",
637 brighterFatterMaxIter = pexConfig.Field(
640 doc=
"Maximum number of iterations for the brighter-fatter correction"
642 brighterFatterThreshold = pexConfig.Field(
645 doc=
"Threshold used to stop iterating the brighter-fatter correction. It is the "
646 "absolute value of the difference between the current corrected image and the one "
647 "from the previous iteration summed over all the pixels."
649 brighterFatterApplyGain = pexConfig.Field(
652 doc=
"Should the gain be applied when applying the brighter-fatter correction?"
654 brighterFatterMaskListToInterpolate = pexConfig.ListField(
656 doc=
"List of mask planes that should be interpolated over when applying the brighter-fatter "
658 default=[
"SAT",
"BAD",
"NO_DATA",
"UNMASKEDNAN"],
660 brighterFatterMaskGrowSize = pexConfig.Field(
663 doc=
"Number of pixels to grow the masks listed in config.brighterFatterMaskListToInterpolate "
664 "when brighter-fatter correction is applied."
668 doDark = pexConfig.Field(
670 doc=
"Apply dark frame correction?",
673 darkDataProductName = pexConfig.Field(
675 doc=
"Name of the dark data product",
680 doStrayLight = pexConfig.Field(
682 doc=
"Subtract stray light in the y-band (due to encoder LEDs)?",
685 strayLight = pexConfig.ConfigurableField(
686 target=StrayLightTask,
687 doc=
"y-band stray light correction"
691 doFlat = pexConfig.Field(
693 doc=
"Apply flat field correction?",
696 flatDataProductName = pexConfig.Field(
698 doc=
"Name of the flat data product",
701 flatScalingType = pexConfig.ChoiceField(
703 doc=
"The method for scaling the flat on the fly.",
706 "USER":
"Scale by flatUserScale",
707 "MEAN":
"Scale by the inverse of the mean",
708 "MEDIAN":
"Scale by the inverse of the median",
711 flatUserScale = pexConfig.Field(
713 doc=
"If flatScalingType is 'USER' then scale flat by this amount; ignored otherwise",
716 doTweakFlat = pexConfig.Field(
718 doc=
"Tweak flats to match observed amplifier ratios?",
723 doApplyGains = pexConfig.Field(
725 doc=
"Correct the amplifiers for their gains instead of applying flat correction",
728 usePtcGains = pexConfig.Field(
730 doc=
"Use the gain values from the Photon Transfer Curve?",
733 normalizeGains = pexConfig.Field(
735 doc=
"Normalize all the amplifiers in each CCD to have the same median value.",
740 doFringe = pexConfig.Field(
742 doc=
"Apply fringe correction?",
745 fringe = pexConfig.ConfigurableField(
747 doc=
"Fringe subtraction task",
749 fringeAfterFlat = pexConfig.Field(
751 doc=
"Do fringe subtraction after flat-fielding?",
756 doMeasureBackground = pexConfig.Field(
758 doc=
"Measure the background level on the reduced image?",
763 doCameraSpecificMasking = pexConfig.Field(
765 doc=
"Mask camera-specific bad regions?",
768 masking = pexConfig.ConfigurableField(
775 doInterpolate = pexConfig.Field(
777 doc=
"Interpolate masked pixels?",
780 doSaturationInterpolation = pexConfig.Field(
782 doc=
"Perform interpolation over pixels masked as saturated?"
783 " NB: This is independent of doSaturation; if that is False this plane"
784 " will likely be blank, resulting in a no-op here.",
787 doNanInterpolation = pexConfig.Field(
789 doc=
"Perform interpolation over pixels masked as NaN?"
790 " NB: This is independent of doNanMasking; if that is False this plane"
791 " will likely be blank, resulting in a no-op here.",
794 doNanInterpAfterFlat = pexConfig.Field(
796 doc=(
"If True, ensure we interpolate NaNs after flat-fielding, even if we "
797 "also have to interpolate them before flat-fielding."),
800 maskListToInterpolate = pexConfig.ListField(
802 doc=
"List of mask planes that should be interpolated.",
803 default=[
'SAT',
'BAD'],
805 doSaveInterpPixels = pexConfig.Field(
807 doc=
"Save a copy of the pre-interpolated pixel values?",
812 fluxMag0T1 = pexConfig.DictField(
815 doc=
"The approximate flux of a zero-magnitude object in a one-second exposure, per filter.",
816 default=dict((f, pow(10.0, 0.4*m))
for f, m
in ((
"Unknown", 28.0),
819 defaultFluxMag0T1 = pexConfig.Field(
821 doc=
"Default value for fluxMag0T1 (for an unrecognized filter).",
822 default=pow(10.0, 0.4*28.0)
826 doVignette = pexConfig.Field(
828 doc=
"Apply vignetting parameters?",
831 vignette = pexConfig.ConfigurableField(
833 doc=
"Vignetting task.",
837 doAttachTransmissionCurve = pexConfig.Field(
840 doc=
"Construct and attach a wavelength-dependent throughput curve for this CCD image?"
842 doUseOpticsTransmission = pexConfig.Field(
845 doc=
"Load and use transmission_optics (if doAttachTransmissionCurve is True)?"
847 doUseFilterTransmission = pexConfig.Field(
850 doc=
"Load and use transmission_filter (if doAttachTransmissionCurve is True)?"
852 doUseSensorTransmission = pexConfig.Field(
855 doc=
"Load and use transmission_sensor (if doAttachTransmissionCurve is True)?"
857 doUseAtmosphereTransmission = pexConfig.Field(
860 doc=
"Load and use transmission_atmosphere (if doAttachTransmissionCurve is True)?"
864 doIlluminationCorrection = pexConfig.Field(
867 doc=
"Perform illumination correction?"
869 illuminationCorrectionDataProductName = pexConfig.Field(
871 doc=
"Name of the illumination correction data product.",
874 illumScale = pexConfig.Field(
876 doc=
"Scale factor for the illumination correction.",
879 illumFilters = pexConfig.ListField(
882 doc=
"Only perform illumination correction for these filters."
886 doWrite = pexConfig.Field(
888 doc=
"Persist postISRCCD?",
895 raise ValueError(
"You may not specify both doFlat and doApplyGains")
897 raise ValueError(
"You may not specify both doBiasBeforeOverscan and doTrimToMatchCalib")
906 class IsrTask(pipeBase.PipelineTask, pipeBase.CmdLineTask):
907 """Apply common instrument signature correction algorithms to a raw frame.
909 The process for correcting imaging data is very similar from
910 camera to camera. This task provides a vanilla implementation of
911 doing these corrections, including the ability to turn certain
912 corrections off if they are not needed. The inputs to the primary
913 method, `run()`, are a raw exposure to be corrected and the
914 calibration data products. The raw input is a single chip sized
915 mosaic of all amps including overscans and other non-science
916 pixels. The method `runDataRef()` identifies and defines the
917 calibration data products, and is intended for use by a
918 `lsst.pipe.base.cmdLineTask.CmdLineTask` and takes as input only a
919 `daf.persistence.butlerSubset.ButlerDataRef`. This task may be
920 subclassed for different camera, although the most camera specific
921 methods have been split into subtasks that can be redirected
924 The __init__ method sets up the subtasks for ISR processing, using
925 the defaults from `lsst.ip.isr`.
930 Positional arguments passed to the Task constructor. None used at this time.
931 kwargs : `dict`, optional
932 Keyword arguments passed on to the Task constructor. None used at this time.
934 ConfigClass = IsrTaskConfig
939 self.makeSubtask(
"assembleCcd")
940 self.makeSubtask(
"crosstalk")
941 self.makeSubtask(
"strayLight")
942 self.makeSubtask(
"fringe")
943 self.makeSubtask(
"masking")
944 self.makeSubtask(
"overscan")
945 self.makeSubtask(
"vignette")
948 inputs = butlerQC.get(inputRefs)
951 inputs[
'detectorNum'] = inputRefs.ccdExposure.dataId[
'detector']
952 except Exception
as e:
953 raise ValueError(
"Failure to find valid detectorNum value for Dataset %s: %s." %
956 inputs[
'isGen3'] =
True
958 detector = inputs[
'ccdExposure'].getDetector()
960 if self.config.doCrosstalk
is True:
963 if 'crosstalk' in inputs
and inputs[
'crosstalk']
is not None:
964 if not isinstance(inputs[
'crosstalk'], CrosstalkCalib):
965 inputs[
'crosstalk'] = CrosstalkCalib.fromTable(inputs[
'crosstalk'])
967 coeffVector = (self.config.crosstalk.crosstalkValues
968 if self.config.crosstalk.useConfigCoefficients
else None)
969 crosstalkCalib =
CrosstalkCalib().fromDetector(detector, coeffVector=coeffVector)
970 inputs[
'crosstalk'] = crosstalkCalib
971 if inputs[
'crosstalk'].interChip
and len(inputs[
'crosstalk'].interChip) > 0:
972 if 'crosstalkSources' not in inputs:
973 self.log.warn(
"No crosstalkSources found for chip with interChip terms!")
976 if 'linearizer' in inputs:
977 if isinstance(inputs[
'linearizer'], dict):
979 linearizer.fromYaml(inputs[
'linearizer'])
980 self.log.warn(
"Dictionary linearizers will be deprecated in DM-28741.")
981 elif isinstance(inputs[
'linearizer'], numpy.ndarray):
985 self.log.warn(
"Bare lookup table linearizers will be deprecated in DM-28741.")
987 linearizer = inputs[
'linearizer']
988 linearizer.log = self.log
989 inputs[
'linearizer'] = linearizer
992 self.log.warn(
"Constructing linearizer from cameraGeom information.")
994 if self.config.doDefect
is True:
995 if "defects" in inputs
and inputs[
'defects']
is not None:
998 if not isinstance(inputs[
"defects"], Defects):
999 inputs[
"defects"] = Defects.fromTable(inputs[
"defects"])
1003 if self.config.doBrighterFatter:
1004 brighterFatterKernel = inputs.pop(
'newBFKernel',
None)
1005 if brighterFatterKernel
is None:
1006 brighterFatterKernel = inputs.get(
'bfKernel',
None)
1008 if brighterFatterKernel
is not None and not isinstance(brighterFatterKernel, numpy.ndarray):
1010 detName = detector.getName()
1011 level = brighterFatterKernel.level
1014 inputs[
'bfGains'] = brighterFatterKernel.gain
1015 if self.config.brighterFatterLevel ==
'DETECTOR':
1016 if level ==
'DETECTOR':
1017 if detName
in brighterFatterKernel.detKernels:
1018 inputs[
'bfKernel'] = brighterFatterKernel.detKernels[detName]
1020 raise RuntimeError(
"Failed to extract kernel from new-style BF kernel.")
1021 elif level ==
'AMP':
1022 self.log.warn(
"Making DETECTOR level kernel from AMP based brighter fatter kernels.")
1023 brighterFatterKernel.makeDetectorKernelFromAmpwiseKernels(detName)
1024 inputs[
'bfKernel'] = brighterFatterKernel.detKernels[detName]
1025 elif self.config.brighterFatterLevel ==
'AMP':
1026 raise NotImplementedError(
"Per-amplifier brighter-fatter correction not implemented")
1028 if self.config.doFringe
is True and self.fringe.
checkFilter(inputs[
'ccdExposure']):
1029 expId = inputs[
'ccdExposure'].getInfo().getVisitInfo().getExposureId()
1030 inputs[
'fringes'] = self.fringe.loadFringes(inputs[
'fringes'],
1032 assembler=self.assembleCcd
1033 if self.config.doAssembleIsrExposures
else None)
1035 inputs[
'fringes'] = pipeBase.Struct(fringes=
None)
1037 if self.config.doStrayLight
is True and self.strayLight.
checkFilter(inputs[
'ccdExposure']):
1038 if 'strayLightData' not in inputs:
1039 inputs[
'strayLightData'] =
None
1041 outputs = self.
runrun(**inputs)
1042 butlerQC.put(outputs, outputRefs)
1045 """Retrieve necessary frames for instrument signature removal.
1047 Pre-fetching all required ISR data products limits the IO
1048 required by the ISR. Any conflict between the calibration data
1049 available and that needed for ISR is also detected prior to
1050 doing processing, allowing it to fail quickly.
1054 dataRef : `daf.persistence.butlerSubset.ButlerDataRef`
1055 Butler reference of the detector data to be processed
1056 rawExposure : `afw.image.Exposure`
1057 The raw exposure that will later be corrected with the
1058 retrieved calibration data; should not be modified in this
1063 result : `lsst.pipe.base.Struct`
1064 Result struct with components (which may be `None`):
1065 - ``bias``: bias calibration frame (`afw.image.Exposure`)
1066 - ``linearizer``: functor for linearization (`ip.isr.linearize.LinearizeBase`)
1067 - ``crosstalkSources``: list of possible crosstalk sources (`list`)
1068 - ``dark``: dark calibration frame (`afw.image.Exposure`)
1069 - ``flat``: flat calibration frame (`afw.image.Exposure`)
1070 - ``bfKernel``: Brighter-Fatter kernel (`numpy.ndarray`)
1071 - ``defects``: list of defects (`lsst.ip.isr.Defects`)
1072 - ``fringes``: `lsst.pipe.base.Struct` with components:
1073 - ``fringes``: fringe calibration frame (`afw.image.Exposure`)
1074 - ``seed``: random seed derived from the ccdExposureId for random
1075 number generator (`uint32`).
1076 - ``opticsTransmission``: `lsst.afw.image.TransmissionCurve`
1077 A ``TransmissionCurve`` that represents the throughput of the optics,
1078 to be evaluated in focal-plane coordinates.
1079 - ``filterTransmission`` : `lsst.afw.image.TransmissionCurve`
1080 A ``TransmissionCurve`` that represents the throughput of the filter
1081 itself, to be evaluated in focal-plane coordinates.
1082 - ``sensorTransmission`` : `lsst.afw.image.TransmissionCurve`
1083 A ``TransmissionCurve`` that represents the throughput of the sensor
1084 itself, to be evaluated in post-assembly trimmed detector coordinates.
1085 - ``atmosphereTransmission`` : `lsst.afw.image.TransmissionCurve`
1086 A ``TransmissionCurve`` that represents the throughput of the
1087 atmosphere, assumed to be spatially constant.
1088 - ``strayLightData`` : `object`
1089 An opaque object containing calibration information for
1090 stray-light correction. If `None`, no correction will be
1092 - ``illumMaskedImage`` : illumination correction image (`lsst.afw.image.MaskedImage`)
1096 NotImplementedError :
1097 Raised if a per-amplifier brighter-fatter kernel is requested by the configuration.
1100 dateObs = rawExposure.getInfo().getVisitInfo().getDate()
1101 dateObs = dateObs.toPython().isoformat()
1102 except RuntimeError:
1103 self.log.warn(
"Unable to identify dateObs for rawExposure.")
1106 ccd = rawExposure.getDetector()
1107 filterLabel = rawExposure.getFilterLabel()
1108 rawExposure.mask.addMaskPlane(
"UNMASKEDNAN")
1109 biasExposure = (self.
getIsrExposuregetIsrExposure(dataRef, self.config.biasDataProductName)
1110 if self.config.doBias
else None)
1112 linearizer = (dataRef.get(
"linearizer", immediate=
True)
1114 if linearizer
is not None and not isinstance(linearizer, numpy.ndarray):
1115 linearizer.log = self.log
1116 if isinstance(linearizer, numpy.ndarray):
1119 crosstalkCalib =
None
1120 if self.config.doCrosstalk:
1122 crosstalkCalib = dataRef.get(
"crosstalk", immediate=
True)
1124 coeffVector = (self.config.crosstalk.crosstalkValues
1125 if self.config.crosstalk.useConfigCoefficients
else None)
1126 crosstalkCalib =
CrosstalkCalib().fromDetector(ccd, coeffVector=coeffVector)
1127 crosstalkSources = (self.crosstalk.prepCrosstalk(dataRef, crosstalkCalib)
1128 if self.config.doCrosstalk
else None)
1130 darkExposure = (self.
getIsrExposuregetIsrExposure(dataRef, self.config.darkDataProductName)
1131 if self.config.doDark
else None)
1132 flatExposure = (self.
getIsrExposuregetIsrExposure(dataRef, self.config.flatDataProductName,
1134 if self.config.doFlat
else None)
1136 brighterFatterKernel =
None
1137 brighterFatterGains =
None
1138 if self.config.doBrighterFatter
is True:
1143 brighterFatterKernel = dataRef.get(
"brighterFatterKernel")
1144 brighterFatterGains = brighterFatterKernel.gain
1145 self.log.info(
"New style brighter-fatter kernel (brighterFatterKernel) loaded")
1148 brighterFatterKernel = dataRef.get(
"bfKernel")
1149 self.log.info(
"Old style brighter-fatter kernel (np.array) loaded")
1151 brighterFatterKernel =
None
1152 if brighterFatterKernel
is not None and not isinstance(brighterFatterKernel, numpy.ndarray):
1155 if self.config.brighterFatterLevel ==
'DETECTOR':
1156 if brighterFatterKernel.detectorKernel:
1157 brighterFatterKernel = brighterFatterKernel.detectorKernel[ccd.getId()]
1159 raise RuntimeError(
"Failed to extract kernel from new-style BF kernel.")
1162 raise NotImplementedError(
"Per-amplifier brighter-fatter correction not implemented")
1164 defectList = (dataRef.get(
"defects")
1165 if self.config.doDefect
else None)
1166 expId = rawExposure.getInfo().getVisitInfo().getExposureId()
1167 fringeStruct = (self.fringe.readFringes(dataRef, expId=expId, assembler=self.assembleCcd
1168 if self.config.doAssembleIsrExposures
else None)
1169 if self.config.doFringe
and self.fringe.
checkFilter(rawExposure)
1170 else pipeBase.Struct(fringes=
None))
1172 if self.config.doAttachTransmissionCurve:
1173 opticsTransmission = (dataRef.get(
"transmission_optics")
1174 if self.config.doUseOpticsTransmission
else None)
1175 filterTransmission = (dataRef.get(
"transmission_filter")
1176 if self.config.doUseFilterTransmission
else None)
1177 sensorTransmission = (dataRef.get(
"transmission_sensor")
1178 if self.config.doUseSensorTransmission
else None)
1179 atmosphereTransmission = (dataRef.get(
"transmission_atmosphere")
1180 if self.config.doUseAtmosphereTransmission
else None)
1182 opticsTransmission =
None
1183 filterTransmission =
None
1184 sensorTransmission =
None
1185 atmosphereTransmission =
None
1187 if self.config.doStrayLight:
1188 strayLightData = self.strayLight.
readIsrData(dataRef, rawExposure)
1190 strayLightData =
None
1193 self.config.illuminationCorrectionDataProductName).getMaskedImage()
1194 if (self.config.doIlluminationCorrection
1195 and filterLabel
in self.config.illumFilters)
1199 return pipeBase.Struct(bias=biasExposure,
1200 linearizer=linearizer,
1201 crosstalk=crosstalkCalib,
1202 crosstalkSources=crosstalkSources,
1205 bfKernel=brighterFatterKernel,
1206 bfGains=brighterFatterGains,
1208 fringes=fringeStruct,
1209 opticsTransmission=opticsTransmission,
1210 filterTransmission=filterTransmission,
1211 sensorTransmission=sensorTransmission,
1212 atmosphereTransmission=atmosphereTransmission,
1213 strayLightData=strayLightData,
1214 illumMaskedImage=illumMaskedImage
1217 @pipeBase.timeMethod
1218 def run(self, ccdExposure, *, camera=None, bias=None, linearizer=None,
1219 crosstalk=None, crosstalkSources=None,
1220 dark=None, flat=None, ptc=None, bfKernel=None, bfGains=None, defects=None,
1221 fringes=pipeBase.Struct(fringes=
None), opticsTransmission=
None, filterTransmission=
None,
1222 sensorTransmission=
None, atmosphereTransmission=
None,
1223 detectorNum=
None, strayLightData=
None, illumMaskedImage=
None,
1226 """Perform instrument signature removal on an exposure.
1228 Steps included in the ISR processing, in order performed, are:
1229 - saturation and suspect pixel masking
1230 - overscan subtraction
1231 - CCD assembly of individual amplifiers
1233 - variance image construction
1234 - linearization of non-linear response
1236 - brighter-fatter correction
1239 - stray light subtraction
1241 - masking of known defects and camera specific features
1242 - vignette calculation
1243 - appending transmission curve and distortion model
1247 ccdExposure : `lsst.afw.image.Exposure`
1248 The raw exposure that is to be run through ISR. The
1249 exposure is modified by this method.
1250 camera : `lsst.afw.cameraGeom.Camera`, optional
1251 The camera geometry for this exposure. Required if ``isGen3`` is
1252 `True` and one or more of ``ccdExposure``, ``bias``, ``dark``, or
1253 ``flat`` does not have an associated detector.
1254 bias : `lsst.afw.image.Exposure`, optional
1255 Bias calibration frame.
1256 linearizer : `lsst.ip.isr.linearize.LinearizeBase`, optional
1257 Functor for linearization.
1258 crosstalk : `lsst.ip.isr.crosstalk.CrosstalkCalib`, optional
1259 Calibration for crosstalk.
1260 crosstalkSources : `list`, optional
1261 List of possible crosstalk sources.
1262 dark : `lsst.afw.image.Exposure`, optional
1263 Dark calibration frame.
1264 flat : `lsst.afw.image.Exposure`, optional
1265 Flat calibration frame.
1266 ptc : `lsst.ip.isr.PhotonTransferCurveDataset`, optional
1267 Photon transfer curve dataset, with, e.g., gains
1269 bfKernel : `numpy.ndarray`, optional
1270 Brighter-fatter kernel.
1271 bfGains : `dict` of `float`, optional
1272 Gains used to override the detector's nominal gains for the
1273 brighter-fatter correction. A dict keyed by amplifier name for
1274 the detector in question.
1275 defects : `lsst.ip.isr.Defects`, optional
1277 fringes : `lsst.pipe.base.Struct`, optional
1278 Struct containing the fringe correction data, with
1280 - ``fringes``: fringe calibration frame (`afw.image.Exposure`)
1281 - ``seed``: random seed derived from the ccdExposureId for random
1282 number generator (`uint32`)
1283 opticsTransmission: `lsst.afw.image.TransmissionCurve`, optional
1284 A ``TransmissionCurve`` that represents the throughput of the optics,
1285 to be evaluated in focal-plane coordinates.
1286 filterTransmission : `lsst.afw.image.TransmissionCurve`
1287 A ``TransmissionCurve`` that represents the throughput of the filter
1288 itself, to be evaluated in focal-plane coordinates.
1289 sensorTransmission : `lsst.afw.image.TransmissionCurve`
1290 A ``TransmissionCurve`` that represents the throughput of the sensor
1291 itself, to be evaluated in post-assembly trimmed detector coordinates.
1292 atmosphereTransmission : `lsst.afw.image.TransmissionCurve`
1293 A ``TransmissionCurve`` that represents the throughput of the
1294 atmosphere, assumed to be spatially constant.
1295 detectorNum : `int`, optional
1296 The integer number for the detector to process.
1297 isGen3 : bool, optional
1298 Flag this call to run() as using the Gen3 butler environment.
1299 strayLightData : `object`, optional
1300 Opaque object containing calibration information for stray-light
1301 correction. If `None`, no correction will be performed.
1302 illumMaskedImage : `lsst.afw.image.MaskedImage`, optional
1303 Illumination correction image.
1307 result : `lsst.pipe.base.Struct`
1308 Result struct with component:
1309 - ``exposure`` : `afw.image.Exposure`
1310 The fully ISR corrected exposure.
1311 - ``outputExposure`` : `afw.image.Exposure`
1312 An alias for `exposure`
1313 - ``ossThumb`` : `numpy.ndarray`
1314 Thumbnail image of the exposure after overscan subtraction.
1315 - ``flattenedThumb`` : `numpy.ndarray`
1316 Thumbnail image of the exposure after flat-field correction.
1321 Raised if a configuration option is set to True, but the
1322 required calibration data has not been specified.
1326 The current processed exposure can be viewed by setting the
1327 appropriate lsstDebug entries in the `debug.display`
1328 dictionary. The names of these entries correspond to some of
1329 the IsrTaskConfig Boolean options, with the value denoting the
1330 frame to use. The exposure is shown inside the matching
1331 option check and after the processing of that step has
1332 finished. The steps with debug points are:
1343 In addition, setting the "postISRCCD" entry displays the
1344 exposure after all ISR processing has finished.
1352 if detectorNum
is None:
1353 raise RuntimeError(
"Must supply the detectorNum if running as Gen3.")
1355 ccdExposure = self.
ensureExposureensureExposure(ccdExposure, camera, detectorNum)
1356 bias = self.
ensureExposureensureExposure(bias, camera, detectorNum)
1357 dark = self.
ensureExposureensureExposure(dark, camera, detectorNum)
1358 flat = self.
ensureExposureensureExposure(flat, camera, detectorNum)
1360 if isinstance(ccdExposure, ButlerDataRef):
1361 return self.
runDataRefrunDataRef(ccdExposure)
1363 ccd = ccdExposure.getDetector()
1364 filterLabel = ccdExposure.getFilterLabel()
1367 assert not self.config.doAssembleCcd,
"You need a Detector to run assembleCcd."
1368 ccd = [
FakeAmp(ccdExposure, self.config)]
1371 if self.config.doBias
and bias
is None:
1372 raise RuntimeError(
"Must supply a bias exposure if config.doBias=True.")
1373 if self.
doLinearizedoLinearize(ccd)
and linearizer
is None:
1374 raise RuntimeError(
"Must supply a linearizer if config.doLinearize=True for this detector.")
1375 if self.config.doBrighterFatter
and bfKernel
is None:
1376 raise RuntimeError(
"Must supply a kernel if config.doBrighterFatter=True.")
1377 if self.config.doDark
and dark
is None:
1378 raise RuntimeError(
"Must supply a dark exposure if config.doDark=True.")
1379 if self.config.doFlat
and flat
is None:
1380 raise RuntimeError(
"Must supply a flat exposure if config.doFlat=True.")
1381 if self.config.doDefect
and defects
is None:
1382 raise RuntimeError(
"Must supply defects if config.doDefect=True.")
1383 if (self.config.doFringe
and filterLabel
in self.fringe.config.filters
1384 and fringes.fringes
is None):
1389 raise RuntimeError(
"Must supply fringe exposure as a pipeBase.Struct.")
1390 if (self.config.doIlluminationCorrection
and filterLabel
in self.config.illumFilters
1391 and illumMaskedImage
is None):
1392 raise RuntimeError(
"Must supply an illumcor if config.doIlluminationCorrection=True.")
1395 if self.config.doConvertIntToFloat:
1396 self.log.info(
"Converting exposure to floating point values.")
1399 if self.config.doBias
and self.config.doBiasBeforeOverscan:
1400 self.log.info(
"Applying bias correction.")
1401 isrFunctions.biasCorrection(ccdExposure.getMaskedImage(), bias.getMaskedImage(),
1402 trimToFit=self.config.doTrimToMatchCalib)
1403 self.
debugViewdebugView(ccdExposure,
"doBias")
1409 if ccdExposure.getBBox().contains(amp.getBBox()):
1411 badAmp = self.
maskAmplifiermaskAmplifier(ccdExposure, amp, defects)
1413 if self.config.doOverscan
and not badAmp:
1416 self.log.debug(
"Corrected overscan for amplifier %s.", amp.getName())
1417 if overscanResults
is not None and \
1418 self.config.qa
is not None and self.config.qa.saveStats
is True:
1419 if isinstance(overscanResults.overscanFit, float):
1420 qaMedian = overscanResults.overscanFit
1421 qaStdev = float(
"NaN")
1423 qaStats = afwMath.makeStatistics(overscanResults.overscanFit,
1424 afwMath.MEDIAN | afwMath.STDEVCLIP)
1425 qaMedian = qaStats.getValue(afwMath.MEDIAN)
1426 qaStdev = qaStats.getValue(afwMath.STDEVCLIP)
1428 self.metadata.set(f
"FIT MEDIAN {amp.getName()}", qaMedian)
1429 self.metadata.set(f
"FIT STDEV {amp.getName()}", qaStdev)
1430 self.log.debug(
" Overscan stats for amplifer %s: %f +/- %f",
1431 amp.getName(), qaMedian, qaStdev)
1434 qaStatsAfter = afwMath.makeStatistics(overscanResults.overscanImage,
1435 afwMath.MEDIAN | afwMath.STDEVCLIP)
1436 qaMedianAfter = qaStatsAfter.getValue(afwMath.MEDIAN)
1437 qaStdevAfter = qaStatsAfter.getValue(afwMath.STDEVCLIP)
1439 self.metadata.set(f
"RESIDUAL MEDIAN {amp.getName()}", qaMedianAfter)
1440 self.metadata.set(f
"RESIDUAL STDEV {amp.getName()}", qaStdevAfter)
1441 self.log.debug(
" Overscan stats for amplifer %s after correction: %f +/- %f",
1442 amp.getName(), qaMedianAfter, qaStdevAfter)
1444 ccdExposure.getMetadata().set(
'OVERSCAN',
"Overscan corrected")
1447 self.log.warn(
"Amplifier %s is bad.", amp.getName())
1448 overscanResults =
None
1450 overscans.append(overscanResults
if overscanResults
is not None else None)
1452 self.log.info(
"Skipped OSCAN for %s.", amp.getName())
1454 if self.config.doCrosstalk
and self.config.doCrosstalkBeforeAssemble:
1455 self.log.info(
"Applying crosstalk correction.")
1456 self.crosstalk.
run(ccdExposure, crosstalk=crosstalk,
1457 crosstalkSources=crosstalkSources, camera=camera)
1458 self.
debugViewdebugView(ccdExposure,
"doCrosstalk")
1460 if self.config.doAssembleCcd:
1461 self.log.info(
"Assembling CCD from amplifiers.")
1462 ccdExposure = self.assembleCcd.assembleCcd(ccdExposure)
1464 if self.config.expectWcs
and not ccdExposure.getWcs():
1465 self.log.warn(
"No WCS found in input exposure.")
1466 self.
debugViewdebugView(ccdExposure,
"doAssembleCcd")
1469 if self.config.qa.doThumbnailOss:
1470 ossThumb = isrQa.makeThumbnail(ccdExposure, isrQaConfig=self.config.qa)
1472 if self.config.doBias
and not self.config.doBiasBeforeOverscan:
1473 self.log.info(
"Applying bias correction.")
1474 isrFunctions.biasCorrection(ccdExposure.getMaskedImage(), bias.getMaskedImage(),
1475 trimToFit=self.config.doTrimToMatchCalib)
1476 self.
debugViewdebugView(ccdExposure,
"doBias")
1478 if self.config.doVariance:
1479 for amp, overscanResults
in zip(ccd, overscans):
1480 if ccdExposure.getBBox().contains(amp.getBBox()):
1481 self.log.debug(
"Constructing variance map for amplifer %s.", amp.getName())
1482 ampExposure = ccdExposure.Factory(ccdExposure, amp.getBBox())
1483 if overscanResults
is not None:
1485 overscanImage=overscanResults.overscanImage,
1491 if self.config.qa
is not None and self.config.qa.saveStats
is True:
1492 qaStats = afwMath.makeStatistics(ampExposure.getVariance(),
1493 afwMath.MEDIAN | afwMath.STDEVCLIP)
1494 self.metadata.set(f
"ISR VARIANCE {amp.getName()} MEDIAN",
1495 qaStats.getValue(afwMath.MEDIAN))
1496 self.metadata.set(f
"ISR VARIANCE {amp.getName()} STDEV",
1497 qaStats.getValue(afwMath.STDEVCLIP))
1498 self.log.debug(
" Variance stats for amplifer %s: %f +/- %f.",
1499 amp.getName(), qaStats.getValue(afwMath.MEDIAN),
1500 qaStats.getValue(afwMath.STDEVCLIP))
1503 self.log.info(
"Applying linearizer.")
1504 linearizer.applyLinearity(image=ccdExposure.getMaskedImage().getImage(),
1505 detector=ccd, log=self.log)
1507 if self.config.doCrosstalk
and not self.config.doCrosstalkBeforeAssemble:
1508 self.log.info(
"Applying crosstalk correction.")
1509 self.crosstalk.
run(ccdExposure, crosstalk=crosstalk,
1510 crosstalkSources=crosstalkSources, isTrimmed=
True)
1511 self.
debugViewdebugView(ccdExposure,
"doCrosstalk")
1515 if self.config.doDefect:
1516 self.log.info(
"Masking defects.")
1517 self.
maskDefectmaskDefect(ccdExposure, defects)
1519 if self.config.numEdgeSuspect > 0:
1520 self.log.info(
"Masking edges as SUSPECT.")
1521 self.
maskEdgesmaskEdges(ccdExposure, numEdgePixels=self.config.numEdgeSuspect,
1522 maskPlane=
"SUSPECT", level=self.config.edgeMaskLevel)
1524 if self.config.doNanMasking:
1525 self.log.info(
"Masking non-finite (NAN, inf) value pixels.")
1526 self.
maskNanmaskNan(ccdExposure)
1528 if self.config.doWidenSaturationTrails:
1529 self.log.info(
"Widening saturation trails.")
1530 isrFunctions.widenSaturationTrails(ccdExposure.getMaskedImage().getMask())
1532 if self.config.doCameraSpecificMasking:
1533 self.log.info(
"Masking regions for camera specific reasons.")
1534 self.masking.
run(ccdExposure)
1536 if self.config.doBrighterFatter:
1545 interpExp = ccdExposure.clone()
1546 with self.
flatContextflatContext(interpExp, flat, dark):
1547 isrFunctions.interpolateFromMask(
1548 maskedImage=interpExp.getMaskedImage(),
1549 fwhm=self.config.fwhm,
1550 growSaturatedFootprints=self.config.growSaturationFootprintSize,
1551 maskNameList=list(self.config.brighterFatterMaskListToInterpolate)
1553 bfExp = interpExp.clone()
1555 self.log.info(
"Applying brighter-fatter correction using kernel type %s / gains %s.",
1556 type(bfKernel), type(bfGains))
1557 bfResults = isrFunctions.brighterFatterCorrection(bfExp, bfKernel,
1558 self.config.brighterFatterMaxIter,
1559 self.config.brighterFatterThreshold,
1560 self.config.brighterFatterApplyGain,
1562 if bfResults[1] == self.config.brighterFatterMaxIter:
1563 self.log.warn(
"Brighter-fatter correction did not converge, final difference %f.",
1566 self.log.info(
"Finished brighter-fatter correction in %d iterations.",
1568 image = ccdExposure.getMaskedImage().getImage()
1569 bfCorr = bfExp.getMaskedImage().getImage()
1570 bfCorr -= interpExp.getMaskedImage().getImage()
1579 self.log.info(
"Ensuring image edges are masked as EDGE to the brighter-fatter kernel size.")
1580 self.
maskEdgesmaskEdges(ccdExposure, numEdgePixels=numpy.max(bfKernel.shape) // 2,
1583 if self.config.brighterFatterMaskGrowSize > 0:
1584 self.log.info(
"Growing masks to account for brighter-fatter kernel convolution.")
1585 for maskPlane
in self.config.brighterFatterMaskListToInterpolate:
1586 isrFunctions.growMasks(ccdExposure.getMask(),
1587 radius=self.config.brighterFatterMaskGrowSize,
1588 maskNameList=maskPlane,
1589 maskValue=maskPlane)
1591 self.
debugViewdebugView(ccdExposure,
"doBrighterFatter")
1593 if self.config.doDark:
1594 self.log.info(
"Applying dark correction.")
1596 self.
debugViewdebugView(ccdExposure,
"doDark")
1598 if self.config.doFringe
and not self.config.fringeAfterFlat:
1599 self.log.info(
"Applying fringe correction before flat.")
1600 self.fringe.
run(ccdExposure, **fringes.getDict())
1601 self.
debugViewdebugView(ccdExposure,
"doFringe")
1603 if self.config.doStrayLight
and self.strayLight.check(ccdExposure):
1604 self.log.info(
"Checking strayLight correction.")
1605 self.strayLight.
run(ccdExposure, strayLightData)
1606 self.
debugViewdebugView(ccdExposure,
"doStrayLight")
1608 if self.config.doFlat:
1609 self.log.info(
"Applying flat correction.")
1611 self.
debugViewdebugView(ccdExposure,
"doFlat")
1613 if self.config.doApplyGains:
1614 self.log.info(
"Applying gain correction instead of flat.")
1615 if self.config.usePtcGains:
1616 self.log.info(
"Using gains from the Photon Transfer Curve.")
1617 isrFunctions.applyGains(ccdExposure, self.config.normalizeGains,
1620 isrFunctions.applyGains(ccdExposure, self.config.normalizeGains)
1622 if self.config.doFringe
and self.config.fringeAfterFlat:
1623 self.log.info(
"Applying fringe correction after flat.")
1624 self.fringe.
run(ccdExposure, **fringes.getDict())
1626 if self.config.doVignette:
1627 self.log.info(
"Constructing Vignette polygon.")
1630 if self.config.vignette.doWriteVignettePolygon:
1633 if self.config.doAttachTransmissionCurve:
1634 self.log.info(
"Adding transmission curves.")
1635 isrFunctions.attachTransmissionCurve(ccdExposure, opticsTransmission=opticsTransmission,
1636 filterTransmission=filterTransmission,
1637 sensorTransmission=sensorTransmission,
1638 atmosphereTransmission=atmosphereTransmission)
1640 flattenedThumb =
None
1641 if self.config.qa.doThumbnailFlattened:
1642 flattenedThumb = isrQa.makeThumbnail(ccdExposure, isrQaConfig=self.config.qa)
1644 if self.config.doIlluminationCorrection
and filterLabel
in self.config.illumFilters:
1645 self.log.info(
"Performing illumination correction.")
1646 isrFunctions.illuminationCorrection(ccdExposure.getMaskedImage(),
1647 illumMaskedImage, illumScale=self.config.illumScale,
1648 trimToFit=self.config.doTrimToMatchCalib)
1651 if self.config.doSaveInterpPixels:
1652 preInterpExp = ccdExposure.clone()
1667 if self.config.doSetBadRegions:
1668 badPixelCount, badPixelValue = isrFunctions.setBadRegions(ccdExposure)
1669 if badPixelCount > 0:
1670 self.log.info(
"Set %d BAD pixels to %f.", badPixelCount, badPixelValue)
1672 if self.config.doInterpolate:
1673 self.log.info(
"Interpolating masked pixels.")
1674 isrFunctions.interpolateFromMask(
1675 maskedImage=ccdExposure.getMaskedImage(),
1676 fwhm=self.config.fwhm,
1677 growSaturatedFootprints=self.config.growSaturationFootprintSize,
1678 maskNameList=list(self.config.maskListToInterpolate)
1683 if self.config.doMeasureBackground:
1684 self.log.info(
"Measuring background level.")
1687 if self.config.qa
is not None and self.config.qa.saveStats
is True:
1689 ampExposure = ccdExposure.Factory(ccdExposure, amp.getBBox())
1690 qaStats = afwMath.makeStatistics(ampExposure.getImage(),
1691 afwMath.MEDIAN | afwMath.STDEVCLIP)
1692 self.metadata.set(
"ISR BACKGROUND {} MEDIAN".format(amp.getName()),
1693 qaStats.getValue(afwMath.MEDIAN))
1694 self.metadata.set(
"ISR BACKGROUND {} STDEV".format(amp.getName()),
1695 qaStats.getValue(afwMath.STDEVCLIP))
1696 self.log.debug(
" Background stats for amplifer %s: %f +/- %f",
1697 amp.getName(), qaStats.getValue(afwMath.MEDIAN),
1698 qaStats.getValue(afwMath.STDEVCLIP))
1700 self.
debugViewdebugView(ccdExposure,
"postISRCCD")
1702 return pipeBase.Struct(
1703 exposure=ccdExposure,
1705 flattenedThumb=flattenedThumb,
1707 preInterpolatedExposure=preInterpExp,
1708 outputExposure=ccdExposure,
1709 outputOssThumbnail=ossThumb,
1710 outputFlattenedThumbnail=flattenedThumb,
1713 @pipeBase.timeMethod
1715 """Perform instrument signature removal on a ButlerDataRef of a Sensor.
1717 This method contains the `CmdLineTask` interface to the ISR
1718 processing. All IO is handled here, freeing the `run()` method
1719 to manage only pixel-level calculations. The steps performed
1721 - Read in necessary detrending/isr/calibration data.
1722 - Process raw exposure in `run()`.
1723 - Persist the ISR-corrected exposure as "postISRCCD" if
1724 config.doWrite=True.
1728 sensorRef : `daf.persistence.butlerSubset.ButlerDataRef`
1729 DataRef of the detector data to be processed
1733 result : `lsst.pipe.base.Struct`
1734 Result struct with component:
1735 - ``exposure`` : `afw.image.Exposure`
1736 The fully ISR corrected exposure.
1741 Raised if a configuration option is set to True, but the
1742 required calibration data does not exist.
1745 self.log.info(
"Performing ISR on sensor %s.", sensorRef.dataId)
1747 ccdExposure = sensorRef.get(self.config.datasetType)
1749 camera = sensorRef.get(
"camera")
1750 isrData = self.
readIsrDatareadIsrData(sensorRef, ccdExposure)
1752 result = self.
runrun(ccdExposure, camera=camera, **isrData.getDict())
1754 if self.config.doWrite:
1755 sensorRef.put(result.exposure,
"postISRCCD")
1756 if result.preInterpolatedExposure
is not None:
1757 sensorRef.put(result.preInterpolatedExposure,
"postISRCCD_uninterpolated")
1758 if result.ossThumb
is not None:
1759 isrQa.writeThumbnail(sensorRef, result.ossThumb,
"ossThumb")
1760 if result.flattenedThumb
is not None:
1761 isrQa.writeThumbnail(sensorRef, result.flattenedThumb,
"flattenedThumb")
1766 """Retrieve a calibration dataset for removing instrument signature.
1771 dataRef : `daf.persistence.butlerSubset.ButlerDataRef`
1772 DataRef of the detector data to find calibration datasets
1775 Type of dataset to retrieve (e.g. 'bias', 'flat', etc).
1776 dateObs : `str`, optional
1777 Date of the observation. Used to correct butler failures
1778 when using fallback filters.
1780 If True, disable butler proxies to enable error handling
1781 within this routine.
1785 exposure : `lsst.afw.image.Exposure`
1786 Requested calibration frame.
1791 Raised if no matching calibration frame can be found.
1794 exp = dataRef.get(datasetType, immediate=immediate)
1795 except Exception
as exc1:
1796 if not self.config.fallbackFilterName:
1797 raise RuntimeError(
"Unable to retrieve %s for %s: %s." % (datasetType, dataRef.dataId, exc1))
1799 if self.config.useFallbackDate
and dateObs:
1800 exp = dataRef.get(datasetType, filter=self.config.fallbackFilterName,
1801 dateObs=dateObs, immediate=immediate)
1803 exp = dataRef.get(datasetType, filter=self.config.fallbackFilterName, immediate=immediate)
1804 except Exception
as exc2:
1805 raise RuntimeError(
"Unable to retrieve %s for %s, even with fallback filter %s: %s AND %s." %
1806 (datasetType, dataRef.dataId, self.config.fallbackFilterName, exc1, exc2))
1807 self.log.warn(
"Using fallback calibration from filter %s.", self.config.fallbackFilterName)
1809 if self.config.doAssembleIsrExposures:
1810 exp = self.assembleCcd.assembleCcd(exp)
1814 """Ensure that the data returned by Butler is a fully constructed exposure.
1816 ISR requires exposure-level image data for historical reasons, so if we did
1817 not recieve that from Butler, construct it from what we have, modifying the
1822 inputExp : `lsst.afw.image.Exposure`, `lsst.afw.image.DecoratedImageU`, or
1823 `lsst.afw.image.ImageF`
1824 The input data structure obtained from Butler.
1825 camera : `lsst.afw.cameraGeom.camera`
1826 The camera associated with the image. Used to find the appropriate
1829 The detector this exposure should match.
1833 inputExp : `lsst.afw.image.Exposure`
1834 The re-constructed exposure, with appropriate detector parameters.
1839 Raised if the input data cannot be used to construct an exposure.
1841 if isinstance(inputExp, afwImage.DecoratedImageU):
1842 inputExp = afwImage.makeExposure(afwImage.makeMaskedImage(inputExp))
1843 elif isinstance(inputExp, afwImage.ImageF):
1844 inputExp = afwImage.makeExposure(afwImage.makeMaskedImage(inputExp))
1845 elif isinstance(inputExp, afwImage.MaskedImageF):
1846 inputExp = afwImage.makeExposure(inputExp)
1847 elif isinstance(inputExp, afwImage.Exposure):
1849 elif inputExp
is None:
1853 raise TypeError(
"Input Exposure is not known type in isrTask.ensureExposure: %s." %
1856 if inputExp.getDetector()
is None:
1857 inputExp.setDetector(camera[detectorNum])
1862 """Convert exposure image from uint16 to float.
1864 If the exposure does not need to be converted, the input is
1865 immediately returned. For exposures that are converted to use
1866 floating point pixels, the variance is set to unity and the
1871 exposure : `lsst.afw.image.Exposure`
1872 The raw exposure to be converted.
1876 newexposure : `lsst.afw.image.Exposure`
1877 The input ``exposure``, converted to floating point pixels.
1882 Raised if the exposure type cannot be converted to float.
1885 if isinstance(exposure, afwImage.ExposureF):
1887 self.log.debug(
"Exposure already of type float.")
1889 if not hasattr(exposure,
"convertF"):
1890 raise RuntimeError(
"Unable to convert exposure (%s) to float." % type(exposure))
1892 newexposure = exposure.convertF()
1893 newexposure.variance[:] = 1
1894 newexposure.mask[:] = 0x0
1899 """Identify bad amplifiers, saturated and suspect pixels.
1903 ccdExposure : `lsst.afw.image.Exposure`
1904 Input exposure to be masked.
1905 amp : `lsst.afw.table.AmpInfoCatalog`
1906 Catalog of parameters defining the amplifier on this
1908 defects : `lsst.ip.isr.Defects`
1909 List of defects. Used to determine if the entire
1915 If this is true, the entire amplifier area is covered by
1916 defects and unusable.
1919 maskedImage = ccdExposure.getMaskedImage()
1925 if defects
is not None:
1926 badAmp = bool(sum([v.getBBox().contains(amp.getBBox())
for v
in defects]))
1931 dataView = afwImage.MaskedImageF(maskedImage, amp.getRawBBox(),
1933 maskView = dataView.getMask()
1934 maskView |= maskView.getPlaneBitMask(
"BAD")
1941 if self.config.doSaturation
and not badAmp:
1942 limits.update({self.config.saturatedMaskName: amp.getSaturation()})
1943 if self.config.doSuspect
and not badAmp:
1944 limits.update({self.config.suspectMaskName: amp.getSuspectLevel()})
1945 if math.isfinite(self.config.saturation):
1946 limits.update({self.config.saturatedMaskName: self.config.saturation})
1948 for maskName, maskThreshold
in limits.items():
1949 if not math.isnan(maskThreshold):
1950 dataView = maskedImage.Factory(maskedImage, amp.getRawBBox())
1951 isrFunctions.makeThresholdMask(
1952 maskedImage=dataView,
1953 threshold=maskThreshold,
1959 maskView = afwImage.Mask(maskedImage.getMask(), amp.getRawDataBBox(),
1961 maskVal = maskView.getPlaneBitMask([self.config.saturatedMaskName,
1962 self.config.suspectMaskName])
1963 if numpy.all(maskView.getArray() & maskVal > 0):
1965 maskView |= maskView.getPlaneBitMask(
"BAD")
1970 """Apply overscan correction in place.
1972 This method does initial pixel rejection of the overscan
1973 region. The overscan can also be optionally segmented to
1974 allow for discontinuous overscan responses to be fit
1975 separately. The actual overscan subtraction is performed by
1976 the `lsst.ip.isr.isrFunctions.overscanCorrection` function,
1977 which is called here after the amplifier is preprocessed.
1981 ccdExposure : `lsst.afw.image.Exposure`
1982 Exposure to have overscan correction performed.
1983 amp : `lsst.afw.cameraGeom.Amplifer`
1984 The amplifier to consider while correcting the overscan.
1988 overscanResults : `lsst.pipe.base.Struct`
1989 Result struct with components:
1990 - ``imageFit`` : scalar or `lsst.afw.image.Image`
1991 Value or fit subtracted from the amplifier image data.
1992 - ``overscanFit`` : scalar or `lsst.afw.image.Image`
1993 Value or fit subtracted from the overscan image data.
1994 - ``overscanImage`` : `lsst.afw.image.Image`
1995 Image of the overscan region with the overscan
1996 correction applied. This quantity is used to estimate
1997 the amplifier read noise empirically.
2002 Raised if the ``amp`` does not contain raw pixel information.
2006 lsst.ip.isr.isrFunctions.overscanCorrection
2008 if amp.getRawHorizontalOverscanBBox().isEmpty():
2009 self.log.info(
"ISR_OSCAN: No overscan region. Not performing overscan correction.")
2012 statControl = afwMath.StatisticsControl()
2013 statControl.setAndMask(ccdExposure.mask.getPlaneBitMask(
"SAT"))
2016 dataBBox = amp.getRawDataBBox()
2017 oscanBBox = amp.getRawHorizontalOverscanBBox()
2021 prescanBBox = amp.getRawPrescanBBox()
2022 if (oscanBBox.getBeginX() > prescanBBox.getBeginX()):
2023 dx0 += self.config.overscanNumLeadingColumnsToSkip
2024 dx1 -= self.config.overscanNumTrailingColumnsToSkip
2026 dx0 += self.config.overscanNumTrailingColumnsToSkip
2027 dx1 -= self.config.overscanNumLeadingColumnsToSkip
2033 if ((self.config.overscanBiasJump
2034 and self.config.overscanBiasJumpLocation)
2035 and (ccdExposure.getMetadata().exists(self.config.overscanBiasJumpKeyword)
2036 and ccdExposure.getMetadata().getScalar(self.config.overscanBiasJumpKeyword)
in
2037 self.config.overscanBiasJumpDevices)):
2038 if amp.getReadoutCorner()
in (ReadoutCorner.LL, ReadoutCorner.LR):
2039 yLower = self.config.overscanBiasJumpLocation
2040 yUpper = dataBBox.getHeight() - yLower
2042 yUpper = self.config.overscanBiasJumpLocation
2043 yLower = dataBBox.getHeight() - yUpper
2061 oscanBBox.getHeight())))
2064 for imageBBox, overscanBBox
in zip(imageBBoxes, overscanBBoxes):
2065 ampImage = ccdExposure.maskedImage[imageBBox]
2066 overscanImage = ccdExposure.maskedImage[overscanBBox]
2068 overscanArray = overscanImage.image.array
2069 median = numpy.ma.median(numpy.ma.masked_where(overscanImage.mask.array, overscanArray))
2070 bad = numpy.where(numpy.abs(overscanArray - median) > self.config.overscanMaxDev)
2071 overscanImage.mask.array[bad] = overscanImage.mask.getPlaneBitMask(
"SAT")
2073 statControl = afwMath.StatisticsControl()
2074 statControl.setAndMask(ccdExposure.mask.getPlaneBitMask(
"SAT"))
2076 overscanResults = self.overscan.
run(ampImage.getImage(), overscanImage, amp)
2079 levelStat = afwMath.MEDIAN
2080 sigmaStat = afwMath.STDEVCLIP
2082 sctrl = afwMath.StatisticsControl(self.config.qa.flatness.clipSigma,
2083 self.config.qa.flatness.nIter)
2084 metadata = ccdExposure.getMetadata()
2085 ampNum = amp.getName()
2087 if isinstance(overscanResults.overscanFit, float):
2088 metadata.set(
"ISR_OSCAN_LEVEL%s" % ampNum, overscanResults.overscanFit)
2089 metadata.set(
"ISR_OSCAN_SIGMA%s" % ampNum, 0.0)
2091 stats = afwMath.makeStatistics(overscanResults.overscanFit, levelStat | sigmaStat, sctrl)
2092 metadata.set(
"ISR_OSCAN_LEVEL%s" % ampNum, stats.getValue(levelStat))
2093 metadata.set(
"ISR_OSCAN_SIGMA%s" % ampNum, stats.getValue(sigmaStat))
2095 return overscanResults
2098 """Set the variance plane using the gain and read noise
2100 The read noise is calculated from the ``overscanImage`` if the
2101 ``doEmpiricalReadNoise`` option is set in the configuration; otherwise
2102 the value from the amplifier data is used.
2106 ampExposure : `lsst.afw.image.Exposure`
2107 Exposure to process.
2108 amp : `lsst.afw.table.AmpInfoRecord` or `FakeAmp`
2109 Amplifier detector data.
2110 overscanImage : `lsst.afw.image.MaskedImage`, optional.
2111 Image of overscan, required only for empirical read noise.
2112 ptcDataset : `lsst.ip.isr.PhotonTransferCurveDataset`, optional
2113 PTC dataset containing the gains and read noise.
2119 Raised if either ``usePtcGains`` of ``usePtcReadNoise``
2120 are ``True``, but ptcDataset is not provided.
2122 Raised if ```doEmpiricalReadNoise`` is ``True`` but
2123 ``overscanImage`` is ``None``.
2127 lsst.ip.isr.isrFunctions.updateVariance
2129 maskPlanes = [self.config.saturatedMaskName, self.config.suspectMaskName]
2130 if self.config.usePtcGains:
2131 if ptcDataset
is None:
2132 raise RuntimeError(
"No ptcDataset provided to use PTC gains.")
2134 gain = ptcDataset.gain[amp.getName()]
2135 self.log.info(
"Using gain from Photon Transfer Curve.")
2137 gain = amp.getGain()
2139 if math.isnan(gain):
2141 self.log.warn(
"Gain set to NAN! Updating to 1.0 to generate Poisson variance.")
2144 self.log.warn(
"Gain for amp %s == %g <= 0; setting to %f.",
2145 amp.getName(), gain, patchedGain)
2148 if self.config.doEmpiricalReadNoise
and overscanImage
is None:
2149 raise RuntimeError(
"Overscan is none for EmpiricalReadNoise.")
2151 if self.config.doEmpiricalReadNoise
and overscanImage
is not None:
2152 stats = afwMath.StatisticsControl()
2153 stats.setAndMask(overscanImage.mask.getPlaneBitMask(maskPlanes))
2154 readNoise = afwMath.makeStatistics(overscanImage, afwMath.STDEVCLIP, stats).getValue()
2155 self.log.info(
"Calculated empirical read noise for amp %s: %f.",
2156 amp.getName(), readNoise)
2157 elif self.config.usePtcReadNoise:
2158 if ptcDataset
is None:
2159 raise RuntimeError(
"No ptcDataset provided to use PTC readnoise.")
2161 readNoise = ptcDataset.noise[amp.getName()]
2162 self.log.info(
"Using read noise from Photon Transfer Curve.")
2164 readNoise = amp.getReadNoise()
2166 isrFunctions.updateVariance(
2167 maskedImage=ampExposure.getMaskedImage(),
2169 readNoise=readNoise,
2173 """Apply dark correction in place.
2177 exposure : `lsst.afw.image.Exposure`
2178 Exposure to process.
2179 darkExposure : `lsst.afw.image.Exposure`
2180 Dark exposure of the same size as ``exposure``.
2181 invert : `Bool`, optional
2182 If True, re-add the dark to an already corrected image.
2187 Raised if either ``exposure`` or ``darkExposure`` do not
2188 have their dark time defined.
2192 lsst.ip.isr.isrFunctions.darkCorrection
2194 expScale = exposure.getInfo().getVisitInfo().getDarkTime()
2195 if math.isnan(expScale):
2196 raise RuntimeError(
"Exposure darktime is NAN.")
2197 if darkExposure.getInfo().getVisitInfo()
is not None \
2198 and not math.isnan(darkExposure.getInfo().getVisitInfo().getDarkTime()):
2199 darkScale = darkExposure.getInfo().getVisitInfo().getDarkTime()
2203 self.log.warn(
"darkExposure.getInfo().getVisitInfo() does not exist. Using darkScale = 1.0.")
2206 isrFunctions.darkCorrection(
2207 maskedImage=exposure.getMaskedImage(),
2208 darkMaskedImage=darkExposure.getMaskedImage(),
2210 darkScale=darkScale,
2212 trimToFit=self.config.doTrimToMatchCalib
2216 """Check if linearization is needed for the detector cameraGeom.
2218 Checks config.doLinearize and the linearity type of the first
2223 detector : `lsst.afw.cameraGeom.Detector`
2224 Detector to get linearity type from.
2228 doLinearize : `Bool`
2229 If True, linearization should be performed.
2231 return self.config.doLinearize
and \
2232 detector.getAmplifiers()[0].getLinearityType() != NullLinearityType
2235 """Apply flat correction in place.
2239 exposure : `lsst.afw.image.Exposure`
2240 Exposure to process.
2241 flatExposure : `lsst.afw.image.Exposure`
2242 Flat exposure of the same size as ``exposure``.
2243 invert : `Bool`, optional
2244 If True, unflatten an already flattened image.
2248 lsst.ip.isr.isrFunctions.flatCorrection
2250 isrFunctions.flatCorrection(
2251 maskedImage=exposure.getMaskedImage(),
2252 flatMaskedImage=flatExposure.getMaskedImage(),
2253 scalingType=self.config.flatScalingType,
2254 userScale=self.config.flatUserScale,
2256 trimToFit=self.config.doTrimToMatchCalib
2260 """Detect saturated pixels and mask them using mask plane config.saturatedMaskName, in place.
2264 exposure : `lsst.afw.image.Exposure`
2265 Exposure to process. Only the amplifier DataSec is processed.
2266 amp : `lsst.afw.table.AmpInfoCatalog`
2267 Amplifier detector data.
2271 lsst.ip.isr.isrFunctions.makeThresholdMask
2273 if not math.isnan(amp.getSaturation()):
2274 maskedImage = exposure.getMaskedImage()
2275 dataView = maskedImage.Factory(maskedImage, amp.getRawBBox())
2276 isrFunctions.makeThresholdMask(
2277 maskedImage=dataView,
2278 threshold=amp.getSaturation(),
2280 maskName=self.config.saturatedMaskName,
2284 """Interpolate over saturated pixels, in place.
2286 This method should be called after `saturationDetection`, to
2287 ensure that the saturated pixels have been identified in the
2288 SAT mask. It should also be called after `assembleCcd`, since
2289 saturated regions may cross amplifier boundaries.
2293 exposure : `lsst.afw.image.Exposure`
2294 Exposure to process.
2298 lsst.ip.isr.isrTask.saturationDetection
2299 lsst.ip.isr.isrFunctions.interpolateFromMask
2301 isrFunctions.interpolateFromMask(
2302 maskedImage=exposure.getMaskedImage(),
2303 fwhm=self.config.fwhm,
2304 growSaturatedFootprints=self.config.growSaturationFootprintSize,
2305 maskNameList=list(self.config.saturatedMaskName),
2309 """Detect suspect pixels and mask them using mask plane config.suspectMaskName, in place.
2313 exposure : `lsst.afw.image.Exposure`
2314 Exposure to process. Only the amplifier DataSec is processed.
2315 amp : `lsst.afw.table.AmpInfoCatalog`
2316 Amplifier detector data.
2320 lsst.ip.isr.isrFunctions.makeThresholdMask
2324 Suspect pixels are pixels whose value is greater than amp.getSuspectLevel().
2325 This is intended to indicate pixels that may be affected by unknown systematics;
2326 for example if non-linearity corrections above a certain level are unstable
2327 then that would be a useful value for suspectLevel. A value of `nan` indicates
2328 that no such level exists and no pixels are to be masked as suspicious.
2330 suspectLevel = amp.getSuspectLevel()
2331 if math.isnan(suspectLevel):
2334 maskedImage = exposure.getMaskedImage()
2335 dataView = maskedImage.Factory(maskedImage, amp.getRawBBox())
2336 isrFunctions.makeThresholdMask(
2337 maskedImage=dataView,
2338 threshold=suspectLevel,
2340 maskName=self.config.suspectMaskName,
2344 """Mask defects using mask plane "BAD", in place.
2348 exposure : `lsst.afw.image.Exposure`
2349 Exposure to process.
2350 defectBaseList : `lsst.ip.isr.Defects` or `list` of
2351 `lsst.afw.image.DefectBase`.
2352 List of defects to mask.
2356 Call this after CCD assembly, since defects may cross amplifier boundaries.
2358 maskedImage = exposure.getMaskedImage()
2359 if not isinstance(defectBaseList, Defects):
2361 defectList =
Defects(defectBaseList)
2363 defectList = defectBaseList
2364 defectList.maskPixels(maskedImage, maskName=
"BAD")
2366 def maskEdges(self, exposure, numEdgePixels=0, maskPlane="SUSPECT", level='DETECTOR'):
2367 """Mask edge pixels with applicable mask plane.
2371 exposure : `lsst.afw.image.Exposure`
2372 Exposure to process.
2373 numEdgePixels : `int`, optional
2374 Number of edge pixels to mask.
2375 maskPlane : `str`, optional
2376 Mask plane name to use.
2377 level : `str`, optional
2378 Level at which to mask edges.
2380 maskedImage = exposure.getMaskedImage()
2381 maskBitMask = maskedImage.getMask().getPlaneBitMask(maskPlane)
2383 if numEdgePixels > 0:
2384 if level ==
'DETECTOR':
2385 boxes = [maskedImage.getBBox()]
2386 elif level ==
'AMP':
2387 boxes = [amp.getBBox()
for amp
in exposure.getDetector()]
2391 subImage = maskedImage[box]
2392 box.grow(-numEdgePixels)
2394 SourceDetectionTask.setEdgeBits(
2400 """Mask and interpolate defects using mask plane "BAD", in place.
2404 exposure : `lsst.afw.image.Exposure`
2405 Exposure to process.
2406 defectBaseList : `lsst.ip.isr.Defects` or `list` of
2407 `lsst.afw.image.DefectBase`.
2408 List of defects to mask and interpolate.
2412 lsst.ip.isr.isrTask.maskDefect
2414 self.
maskDefectmaskDefect(exposure, defectBaseList)
2415 self.
maskEdgesmaskEdges(exposure, numEdgePixels=self.config.numEdgeSuspect,
2416 maskPlane=
"SUSPECT", level=self.config.edgeMaskLevel)
2417 isrFunctions.interpolateFromMask(
2418 maskedImage=exposure.getMaskedImage(),
2419 fwhm=self.config.fwhm,
2420 growSaturatedFootprints=0,
2421 maskNameList=[
"BAD"],
2425 """Mask NaNs using mask plane "UNMASKEDNAN", in place.
2429 exposure : `lsst.afw.image.Exposure`
2430 Exposure to process.
2434 We mask over all non-finite values (NaN, inf), including those
2435 that are masked with other bits (because those may or may not be
2436 interpolated over later, and we want to remove all NaN/infs).
2437 Despite this behaviour, the "UNMASKEDNAN" mask plane is used to
2438 preserve the historical name.
2440 maskedImage = exposure.getMaskedImage()
2443 maskedImage.getMask().addMaskPlane(
"UNMASKEDNAN")
2444 maskVal = maskedImage.getMask().getPlaneBitMask(
"UNMASKEDNAN")
2445 numNans =
maskNans(maskedImage, maskVal)
2446 self.metadata.set(
"NUMNANS", numNans)
2448 self.log.warn(
"There were %d unmasked NaNs.", numNans)
2451 """"Mask and interpolate NaN/infs using mask plane "UNMASKEDNAN",
2456 exposure : `lsst.afw.image.Exposure`
2457 Exposure to process.
2461 lsst.ip.isr.isrTask.maskNan
2464 isrFunctions.interpolateFromMask(
2465 maskedImage=exposure.getMaskedImage(),
2466 fwhm=self.config.fwhm,
2467 growSaturatedFootprints=0,
2468 maskNameList=[
"UNMASKEDNAN"],
2472 """Measure the image background in subgrids, for quality control purposes.
2476 exposure : `lsst.afw.image.Exposure`
2477 Exposure to process.
2478 IsrQaConfig : `lsst.ip.isr.isrQa.IsrQaConfig`
2479 Configuration object containing parameters on which background
2480 statistics and subgrids to use.
2482 if IsrQaConfig
is not None:
2483 statsControl = afwMath.StatisticsControl(IsrQaConfig.flatness.clipSigma,
2484 IsrQaConfig.flatness.nIter)
2485 maskVal = exposure.getMaskedImage().getMask().getPlaneBitMask([
"BAD",
"SAT",
"DETECTED"])
2486 statsControl.setAndMask(maskVal)
2487 maskedImage = exposure.getMaskedImage()
2488 stats = afwMath.makeStatistics(maskedImage, afwMath.MEDIAN | afwMath.STDEVCLIP, statsControl)
2489 skyLevel = stats.getValue(afwMath.MEDIAN)
2490 skySigma = stats.getValue(afwMath.STDEVCLIP)
2491 self.log.info(
"Flattened sky level: %f +/- %f.", skyLevel, skySigma)
2492 metadata = exposure.getMetadata()
2493 metadata.set(
'SKYLEVEL', skyLevel)
2494 metadata.set(
'SKYSIGMA', skySigma)
2497 stat = afwMath.MEANCLIP
if IsrQaConfig.flatness.doClip
else afwMath.MEAN
2498 meshXHalf = int(IsrQaConfig.flatness.meshX/2.)
2499 meshYHalf = int(IsrQaConfig.flatness.meshY/2.)
2500 nX = int((exposure.getWidth() + meshXHalf) / IsrQaConfig.flatness.meshX)
2501 nY = int((exposure.getHeight() + meshYHalf) / IsrQaConfig.flatness.meshY)
2502 skyLevels = numpy.zeros((nX, nY))
2505 yc = meshYHalf + j * IsrQaConfig.flatness.meshY
2507 xc = meshXHalf + i * IsrQaConfig.flatness.meshX
2509 xLLC = xc - meshXHalf
2510 yLLC = yc - meshYHalf
2511 xURC = xc + meshXHalf - 1
2512 yURC = yc + meshYHalf - 1
2515 miMesh = maskedImage.Factory(exposure.getMaskedImage(), bbox, afwImage.LOCAL)
2517 skyLevels[i, j] = afwMath.makeStatistics(miMesh, stat, statsControl).getValue()
2519 good = numpy.where(numpy.isfinite(skyLevels))
2520 skyMedian = numpy.median(skyLevels[good])
2521 flatness = (skyLevels[good] - skyMedian) / skyMedian
2522 flatness_rms = numpy.std(flatness)
2523 flatness_pp = flatness.max() - flatness.min()
if len(flatness) > 0
else numpy.nan
2525 self.log.info(
"Measuring sky levels in %dx%d grids: %f.", nX, nY, skyMedian)
2526 self.log.info(
"Sky flatness in %dx%d grids - pp: %f rms: %f.",
2527 nX, nY, flatness_pp, flatness_rms)
2529 metadata.set(
'FLATNESS_PP', float(flatness_pp))
2530 metadata.set(
'FLATNESS_RMS', float(flatness_rms))
2531 metadata.set(
'FLATNESS_NGRIDS',
'%dx%d' % (nX, nY))
2532 metadata.set(
'FLATNESS_MESHX', IsrQaConfig.flatness.meshX)
2533 metadata.set(
'FLATNESS_MESHY', IsrQaConfig.flatness.meshY)
2536 """Set an approximate magnitude zero point for the exposure.
2540 exposure : `lsst.afw.image.Exposure`
2541 Exposure to process.
2543 filterLabel = exposure.getFilterLabel()
2544 if filterLabel
in self.config.fluxMag0T1:
2545 fluxMag0 = self.config.fluxMag0T1[filterLabel]
2547 self.log.warn(
"No rough magnitude zero point set for filter %s.", filterLabel)
2548 fluxMag0 = self.config.defaultFluxMag0T1
2550 expTime = exposure.getInfo().getVisitInfo().getExposureTime()
2552 self.log.warn(
"Non-positive exposure time; skipping rough zero point.")
2555 self.log.info(
"Setting rough magnitude zero point: %f", 2.5*math.log10(fluxMag0*expTime))
2556 exposure.setPhotoCalib(afwImage.makePhotoCalibFromCalibZeroPoint(fluxMag0*expTime, 0.0))
2559 """Set the valid polygon as the intersection of fpPolygon and the ccd corners.
2563 ccdExposure : `lsst.afw.image.Exposure`
2564 Exposure to process.
2565 fpPolygon : `lsst.afw.geom.Polygon`
2566 Polygon in focal plane coordinates.
2569 ccd = ccdExposure.getDetector()
2570 fpCorners = ccd.getCorners(FOCAL_PLANE)
2571 ccdPolygon = Polygon(fpCorners)
2574 intersect = ccdPolygon.intersectionSingle(fpPolygon)
2577 ccdPoints = ccd.transform(intersect, FOCAL_PLANE, PIXELS)
2578 validPolygon = Polygon(ccdPoints)
2579 ccdExposure.getInfo().setValidPolygon(validPolygon)
2583 """Context manager that applies and removes flats and darks,
2584 if the task is configured to apply them.
2588 exp : `lsst.afw.image.Exposure`
2589 Exposure to process.
2590 flat : `lsst.afw.image.Exposure`
2591 Flat exposure the same size as ``exp``.
2592 dark : `lsst.afw.image.Exposure`, optional
2593 Dark exposure the same size as ``exp``.
2597 exp : `lsst.afw.image.Exposure`
2598 The flat and dark corrected exposure.
2600 if self.config.doDark
and dark
is not None:
2602 if self.config.doFlat:
2607 if self.config.doFlat:
2609 if self.config.doDark
and dark
is not None:
2613 """Utility function to examine ISR exposure at different stages.
2617 exposure : `lsst.afw.image.Exposure`
2620 State of processing to view.
2622 frame = getDebugFrame(self._display, stepname)
2624 display = getDisplay(frame)
2625 display.scale(
'asinh',
'zscale')
2626 display.mtv(exposure)
2627 prompt =
"Press Enter to continue [c]... "
2629 ans = input(prompt).lower()
2630 if ans
in (
"",
"c",):
2635 """A Detector-like object that supports returning gain and saturation level
2637 This is used when the input exposure does not have a detector.
2641 exposure : `lsst.afw.image.Exposure`
2642 Exposure to generate a fake amplifier for.
2643 config : `lsst.ip.isr.isrTaskConfig`
2644 Configuration to apply to the fake amplifier.
2648 self.
_bbox_bbox = exposure.getBBox(afwImage.LOCAL)
2650 self.
_gain_gain = config.gain
2655 return self.
_bbox_bbox
2658 return self.
_bbox_bbox
2664 return self.
_gain_gain
2677 isr = pexConfig.ConfigurableField(target=IsrTask, doc=
"Instrument signature removal")
2681 """Task to wrap the default IsrTask to allow it to be retargeted.
2683 The standard IsrTask can be called directly from a command line
2684 program, but doing so removes the ability of the task to be
2685 retargeted. As most cameras override some set of the IsrTask
2686 methods, this would remove those data-specific methods in the
2687 output post-ISR images. This wrapping class fixes the issue,
2688 allowing identical post-ISR images to be generated by both the
2689 processCcd and isrTask code.
2691 ConfigClass = RunIsrConfig
2692 _DefaultName =
"runIsr"
2696 self.makeSubtask(
"isr")
2702 dataRef : `lsst.daf.persistence.ButlerDataRef`
2703 data reference of the detector data to be processed
2707 result : `pipeBase.Struct`
2708 Result struct with component:
2710 - exposure : `lsst.afw.image.Exposure`
2711 Post-ISR processed exposure.
def getRawHorizontalOverscanBBox(self)
def getSuspectLevel(self)
_RawHorizontalOverscanBBox
def __init__(self, exposure, config)
doSaturationInterpolation
def __init__(self, *config=None)
def flatCorrection(self, exposure, flatExposure, invert=False)
def maskAndInterpolateNan(self, exposure)
def saturationInterpolation(self, exposure)
def runDataRef(self, sensorRef)
def maskNan(self, exposure)
def maskAmplifier(self, ccdExposure, amp, defects)
def debugView(self, exposure, stepname)
def getIsrExposure(self, dataRef, datasetType, dateObs=None, immediate=True)
def saturationDetection(self, exposure, amp)
def maskDefect(self, exposure, defectBaseList)
def __init__(self, **kwargs)
def runQuantum(self, butlerQC, inputRefs, outputRefs)
def maskEdges(self, exposure, numEdgePixels=0, maskPlane="SUSPECT", level='DETECTOR')
def overscanCorrection(self, ccdExposure, amp)
def measureBackground(self, exposure, IsrQaConfig=None)
def roughZeroPoint(self, exposure)
def maskAndInterpolateDefects(self, exposure, defectBaseList)
def setValidPolygonIntersect(self, ccdExposure, fpPolygon)
def readIsrData(self, dataRef, rawExposure)
def ensureExposure(self, inputExp, camera, detectorNum)
def run(self, ccdExposure, *camera=None, bias=None, linearizer=None, crosstalk=None, crosstalkSources=None, dark=None, flat=None, ptc=None, bfKernel=None, bfGains=None, defects=None, fringes=pipeBase.Struct(fringes=None), opticsTransmission=None, filterTransmission=None, sensorTransmission=None, atmosphereTransmission=None, detectorNum=None, strayLightData=None, illumMaskedImage=None, isGen3=False)
def doLinearize(self, detector)
def flatContext(self, exp, flat, dark=None)
def convertIntToFloat(self, exposure)
def suspectDetection(self, exposure, amp)
def updateVariance(self, ampExposure, amp, overscanImage=None, ptcDataset=None)
def darkCorrection(self, exposure, darkExposure, invert=False)
def __init__(self, *args, **kwargs)
def runDataRef(self, dataRef)
def checkFilter(exposure, filterList, log)
def crosstalkSourceLookup(datasetType, registry, quantumDataId, collections)
size_t maskNans(afw::image::MaskedImage< PixelT > const &mi, afw::image::MaskPixel maskVal, afw::image::MaskPixel allow=0)
Mask NANs in an image.