29 import lsst.pipe.base.connectionTypes
as connectionTypes
35 from .coaddBase
import CoaddBaseTask, makeSkyInfo, reorderAndPadList
36 from .warpAndPsfMatch
import WarpAndPsfMatchTask
37 from .coaddHelpers
import groupPatchExposures, getGroupDataRef
38 from collections.abc
import Iterable
40 __all__ = [
"MakeCoaddTempExpTask",
"MakeWarpTask",
"MakeWarpConfig"]
44 """Raised when data cannot be retrieved for an exposure.
45 When processing patches, sometimes one exposure is missing; this lets us
46 distinguish bewteen that case, and other errors.
52 """Config for MakeCoaddTempExpTask
54 warpAndPsfMatch = pexConfig.ConfigurableField(
55 target=WarpAndPsfMatchTask,
56 doc=
"Task to warp and PSF-match calexp",
58 doWrite = pexConfig.Field(
59 doc=
"persist <coaddName>Coadd_<warpType>Warp",
63 bgSubtracted = pexConfig.Field(
64 doc=
"Work with a background subtracted calexp?",
68 coaddPsf = pexConfig.ConfigField(
69 doc=
"Configuration for CoaddPsf",
72 makeDirect = pexConfig.Field(
73 doc=
"Make direct Warp/Coadds",
77 makePsfMatched = pexConfig.Field(
78 doc=
"Make Psf-Matched Warp/Coadd?",
83 doWriteEmptyWarps = pexConfig.Field(
86 doc=
"Write out warps even if they are empty"
89 hasFakes = pexConfig.Field(
90 doc=
"Should be set to True if fake sources have been inserted into the input data.",
94 doApplySkyCorr = pexConfig.Field(dtype=bool, default=
False, doc=
"Apply sky correction?")
97 CoaddBaseTask.ConfigClass.validate(self)
99 raise RuntimeError(
"At least one of config.makePsfMatched and config.makeDirect must be True")
102 log.warning(
"Config doPsfMatch deprecated. Setting makePsfMatched=True and makeDirect=False")
107 CoaddBaseTask.ConfigClass.setDefaults(self)
108 self.
warpAndPsfMatchwarpAndPsfMatch.psfMatch.kernel.active.kernelSize = self.matchingKernelSize
119 r"""!Warp and optionally PSF-Match calexps onto an a common projection.
121 @anchor MakeCoaddTempExpTask_
123 @section pipe_tasks_makeCoaddTempExp_Contents Contents
125 - @ref pipe_tasks_makeCoaddTempExp_Purpose
126 - @ref pipe_tasks_makeCoaddTempExp_Initialize
127 - @ref pipe_tasks_makeCoaddTempExp_IO
128 - @ref pipe_tasks_makeCoaddTempExp_Config
129 - @ref pipe_tasks_makeCoaddTempExp_Debug
130 - @ref pipe_tasks_makeCoaddTempExp_Example
132 @section pipe_tasks_makeCoaddTempExp_Purpose Description
134 Warp and optionally PSF-Match calexps onto a common projection, by
135 performing the following operations:
136 - Group calexps by visit/run
137 - For each visit, generate a Warp by calling method @ref makeTempExp.
138 makeTempExp loops over the visit's calexps calling @ref WarpAndPsfMatch
141 The result is a `directWarp` (and/or optionally a `psfMatchedWarp`).
143 @section pipe_tasks_makeCoaddTempExp_Initialize Task Initialization
145 @copydoc \_\_init\_\_
147 This task has one special keyword argument: passing reuse=True will cause
148 the task to skip the creation of warps that are already present in the
151 @section pipe_tasks_makeCoaddTempExp_IO Invoking the Task
153 This task is primarily designed to be run from the command line.
155 The main method is `runDataRef`, which takes a single butler data reference for the patch(es)
160 WarpType identifies the types of convolutions applied to Warps (previously CoaddTempExps).
161 Only two types are available: direct (for regular Warps/Coadds) and psfMatched
162 (for Warps/Coadds with homogenized PSFs). We expect to add a third type, likelihood,
163 for generating likelihood Coadds with Warps that have been correlated with their own PSF.
165 @section pipe_tasks_makeCoaddTempExp_Config Configuration parameters
167 See @ref MakeCoaddTempExpConfig and parameters inherited from
168 @link lsst.pipe.tasks.coaddBase.CoaddBaseConfig CoaddBaseConfig @endlink
170 @subsection pipe_tasks_MakeCoaddTempExp_psfMatching Guide to PSF-Matching Configs
172 To make `psfMatchedWarps`, select `config.makePsfMatched=True`. The subtask
173 @link lsst.ip.diffim.modelPsfMatch.ModelPsfMatchTask ModelPsfMatchTask @endlink
174 is responsible for the PSF-Matching, and its config is accessed via `config.warpAndPsfMatch.psfMatch`.
175 The optimal configuration depends on aspects of dataset: the pixel scale, average PSF FWHM and
176 dimensions of the PSF kernel. These configs include the requested model PSF, the matching kernel size,
177 padding of the science PSF thumbnail and spatial sampling frequency of the PSF.
179 *Config Guidelines*: The user must specify the size of the model PSF to which to match by setting
180 `config.modelPsf.defaultFwhm` in units of pixels. The appropriate values depends on science case.
181 In general, for a set of input images, this config should equal the FWHM of the visit
182 with the worst seeing. The smallest it should be set to is the median FWHM. The defaults
183 of the other config options offer a reasonable starting point.
184 The following list presents the most common problems that arise from a misconfigured
185 @link lsst.ip.diffim.modelPsfMatch.ModelPsfMatchTask ModelPsfMatchTask @endlink
186 and corresponding solutions. All assume the default Alard-Lupton kernel, with configs accessed via
187 ```config.warpAndPsfMatch.psfMatch.kernel['AL']```. Each item in the list is formatted as:
188 Problem: Explanation. *Solution*
190 *Troublshooting PSF-Matching Configuration:*
191 - Matched PSFs look boxy: The matching kernel is too small. _Increase the matching kernel size.
194 config.warpAndPsfMatch.psfMatch.kernel['AL'].kernelSize=27 # default 21
196 Note that increasing the kernel size also increases runtime.
197 - Matched PSFs look ugly (dipoles, quadropoles, donuts): unable to find good solution
198 for matching kernel. _Provide the matcher with more data by either increasing
199 the spatial sampling by decreasing the spatial cell size,_
201 config.warpAndPsfMatch.psfMatch.kernel['AL'].sizeCellX = 64 # default 128
202 config.warpAndPsfMatch.psfMatch.kernel['AL'].sizeCellY = 64 # default 128
204 _or increasing the padding around the Science PSF, for example:_
206 config.warpAndPsfMatch.psfMatch.autoPadPsfTo=1.6 # default 1.4
208 Increasing `autoPadPsfTo` increases the minimum ratio of input PSF dimensions to the
209 matching kernel dimensions, thus increasing the number of pixels available to fit
210 after convolving the PSF with the matching kernel.
211 Optionally, for debugging the effects of padding, the level of padding may be manually
212 controlled by setting turning off the automatic padding and setting the number
213 of pixels by which to pad the PSF:
215 config.warpAndPsfMatch.psfMatch.doAutoPadPsf = False # default True
216 config.warpAndPsfMatch.psfMatch.padPsfBy = 6 # pixels. default 0
218 - Deconvolution: Matching a large PSF to a smaller PSF produces
219 a telltale noise pattern which looks like ripples or a brain.
220 _Increase the size of the requested model PSF. For example:_
222 config.modelPsf.defaultFwhm = 11 # Gaussian sigma in units of pixels.
224 - High frequency (sometimes checkered) noise: The matching basis functions are too small.
225 _Increase the width of the Gaussian basis functions. For example:_
227 config.warpAndPsfMatch.psfMatch.kernel['AL'].alardSigGauss=[1.5, 3.0, 6.0]
228 # from default [0.7, 1.5, 3.0]
231 @section pipe_tasks_makeCoaddTempExp_Debug Debug variables
233 MakeCoaddTempExpTask has no debug output, but its subtasks do.
235 @section pipe_tasks_makeCoaddTempExp_Example A complete example of using MakeCoaddTempExpTask
237 This example uses the package ci_hsc to show how MakeCoaddTempExp fits
238 into the larger Data Release Processing.
243 # if not built already:
244 python $(which scons) # this will take a while
246 The following assumes that `processCcd.py` and `makeSkyMap.py` have previously been run
247 (e.g. by building `ci_hsc` above) to generate a repository of calexps and an
248 output respository with the desired SkyMap. The command,
250 makeCoaddTempExp.py $CI_HSC_DIR/DATA --rerun ci_hsc \
251 --id patch=5,4 tract=0 filter=HSC-I \
252 --selectId visit=903988 ccd=16 --selectId visit=903988 ccd=17 \
253 --selectId visit=903988 ccd=23 --selectId visit=903988 ccd=24 \
254 --config doApplyExternalPhotoCalib=False doApplyExternalSkyWcs=False \
255 makePsfMatched=True modelPsf.defaultFwhm=11
257 writes a direct and PSF-Matched Warp to
258 - `$CI_HSC_DIR/DATA/rerun/ci_hsc/deepCoadd/HSC-I/0/5,4/warp-HSC-I-0-5,4-903988.fits` and
259 - `$CI_HSC_DIR/DATA/rerun/ci_hsc/deepCoadd/HSC-I/0/5,4/psfMatchedWarp-HSC-I-0-5,4-903988.fits`
262 @note PSF-Matching in this particular dataset would benefit from adding
263 `--configfile ./matchingConfig.py` to
264 the command line arguments where `matchingConfig.py` is defined by:
267 config.warpAndPsfMatch.psfMatch.kernel['AL'].kernelSize=27
268 config.warpAndPsfMatch.psfMatch.kernel['AL'].alardSigGauss=[1.5, 3.0, 6.0]" > matchingConfig.py
271 Add the option `--help` to see more options.
273 ConfigClass = MakeCoaddTempExpConfig
274 _DefaultName =
"makeCoaddTempExp"
277 CoaddBaseTask.__init__(self, **kwargs)
279 self.makeSubtask(
"warpAndPsfMatch")
280 if self.config.hasFakes:
287 """!Produce <coaddName>Coadd_<warpType>Warp images by warping and optionally PSF-matching.
289 @param[in] patchRef: data reference for sky map patch. Must include keys "tract", "patch",
290 plus the camera-specific filter key (e.g. "filter" or "band")
291 @return: dataRefList: a list of data references for the new <coaddName>Coadd_directWarps
292 if direct or both warp types are requested and <coaddName>Coadd_psfMatchedWarps if only psfMatched
295 @warning: this task assumes that all exposures in a warp (coaddTempExp) have the same filter.
297 @warning: this task sets the PhotoCalib of the coaddTempExp to the PhotoCalib of the first calexp
298 with any good pixels in the patch. For a mosaic camera the resulting PhotoCalib should be ignored
299 (assembleCoadd should determine zeropoint scaling without referring to it).
304 if self.config.makePsfMatched
and not self.config.makeDirect:
309 calExpRefList = self.
selectExposuresselectExposures(patchRef, skyInfo, selectDataList=selectDataList)
311 if len(calExpRefList) == 0:
312 self.log.warning(
"No exposures to coadd for patch %s", patchRef.dataId)
314 self.log.info(
"Selected %d calexps for patch %s", len(calExpRefList), patchRef.dataId)
315 calExpRefList = [calExpRef
for calExpRef
in calExpRefList
if calExpRef.datasetExists(self.
calexpTypecalexpType)]
316 self.log.info(
"Processing %d existing calexps for patch %s", len(calExpRefList), patchRef.dataId)
320 self.log.info(
"Processing %d warp exposures for patch %s", len(groupData.groups), patchRef.dataId)
323 for i, (tempExpTuple, calexpRefList)
in enumerate(groupData.groups.items()):
325 tempExpTuple, groupData.keys)
326 if self.
reusereuse
and tempExpRef.datasetExists(datasetType=primaryWarpDataset, write=
True):
327 self.log.info(
"Skipping makeCoaddTempExp for %s; output already exists.", tempExpRef.dataId)
328 dataRefList.append(tempExpRef)
330 self.log.info(
"Processing Warp %d/%d: id=%s", i, len(groupData.groups), tempExpRef.dataId)
336 visitId = int(tempExpRef.dataId[
"visit"])
337 except (KeyError, ValueError):
344 for calExpInd, calExpRef
in enumerate(calexpRefList):
345 self.log.info(
"Reading calexp %s of %s for Warp id=%s", calExpInd+1, len(calexpRefList),
348 ccdId = calExpRef.get(
"ccdExposureId", immediate=
True)
355 calExpRef = calExpRef.butlerSubset.butler.dataRef(self.
calexpTypecalexpType,
356 dataId=calExpRef.dataId,
357 tract=skyInfo.tractInfo.getId())
358 calExp = self.
getCalibratedExposuregetCalibratedExposure(calExpRef, bgSubtracted=self.config.bgSubtracted)
359 except Exception
as e:
360 self.log.warning(
"Calexp %s not found; skipping it: %s", calExpRef.dataId, e)
363 if self.config.doApplySkyCorr:
366 calExpList.append(calExp)
367 ccdIdList.append(ccdId)
368 dataIdList.append(calExpRef.dataId)
370 exps = self.
runrun(calExpList, ccdIdList, skyInfo, visitId, dataIdList).exposures
372 if any(exps.values()):
373 dataRefList.append(tempExpRef)
375 self.log.warning(
"Warp %s could not be created", tempExpRef.dataId)
377 if self.config.doWrite:
378 for (warpType, exposure)
in exps.items():
379 if exposure
is not None:
386 def run(self, calExpList, ccdIdList, skyInfo, visitId=0, dataIdList=None, **kwargs):
387 """Create a Warp from inputs
389 We iterate over the multiple calexps in a single exposure to construct
390 the warp (previously called a coaddTempExp) of that exposure to the
391 supplied tract/patch.
393 Pixels that receive no pixels are set to NAN; this is not correct
394 (violates LSST algorithms group policy), but will be fixed up by
395 interpolating after the coaddition.
397 @param calexpRefList: List of data references for calexps that (may)
398 overlap the patch of interest
399 @param skyInfo: Struct from CoaddBaseTask.getSkyInfo() with geometric
400 information about the patch
401 @param visitId: integer identifier for visit, for the table that will
403 @return a pipeBase Struct containing:
404 - exposures: a dictionary containing the warps requested:
405 "direct": direct warp if config.makeDirect
406 "psfMatched": PSF-matched warp if config.makePsfMatched
410 totGoodPix = {warpType: 0
for warpType
in warpTypeList}
411 didSetMetadata = {warpType:
False for warpType
in warpTypeList}
412 coaddTempExps = {warpType: self.
_prepareEmptyExposure_prepareEmptyExposure(skyInfo)
for warpType
in warpTypeList}
413 inputRecorder = {warpType: self.inputRecorder.makeCoaddTempExpRecorder(visitId, len(calExpList))
414 for warpType
in warpTypeList}
416 modelPsf = self.config.modelPsf.apply()
if self.config.makePsfMatched
else None
417 if dataIdList
is None:
418 dataIdList = ccdIdList
420 for calExpInd, (calExp, ccdId, dataId)
in enumerate(zip(calExpList, ccdIdList, dataIdList)):
421 self.log.info(
"Processing calexp %d of %d for this Warp: id=%s",
422 calExpInd+1, len(calExpList), dataId)
425 warpedAndMatched = self.warpAndPsfMatch.
run(calExp, modelPsf=modelPsf,
426 wcs=skyInfo.wcs, maxBBox=skyInfo.bbox,
427 makeDirect=self.config.makeDirect,
428 makePsfMatched=self.config.makePsfMatched)
429 except Exception
as e:
430 self.log.warning(
"WarpAndPsfMatch failed for calexp %s; skipping it: %s", dataId, e)
433 numGoodPix = {warpType: 0
for warpType
in warpTypeList}
434 for warpType
in warpTypeList:
435 exposure = warpedAndMatched.getDict()[warpType]
438 coaddTempExp = coaddTempExps[warpType]
439 if didSetMetadata[warpType]:
440 mimg = exposure.getMaskedImage()
441 mimg *= (coaddTempExp.getPhotoCalib().getInstFluxAtZeroMagnitude()
442 / exposure.getPhotoCalib().getInstFluxAtZeroMagnitude())
444 numGoodPix[warpType] = coaddUtils.copyGoodPixels(
445 coaddTempExp.getMaskedImage(), exposure.getMaskedImage(), self.
getBadPixelMaskgetBadPixelMask())
446 totGoodPix[warpType] += numGoodPix[warpType]
447 self.log.debug(
"Calexp %s has %d good pixels in this patch (%.1f%%) for %s",
448 dataId, numGoodPix[warpType],
449 100.0*numGoodPix[warpType]/skyInfo.bbox.getArea(), warpType)
450 if numGoodPix[warpType] > 0
and not didSetMetadata[warpType]:
451 coaddTempExp.setPhotoCalib(exposure.getPhotoCalib())
452 coaddTempExp.setFilterLabel(exposure.getFilterLabel())
453 coaddTempExp.getInfo().setVisitInfo(exposure.getInfo().getVisitInfo())
455 coaddTempExp.setPsf(exposure.getPsf())
456 didSetMetadata[warpType] =
True
459 inputRecorder[warpType].addCalExp(calExp, ccdId, numGoodPix[warpType])
461 except Exception
as e:
462 self.log.warning(
"Error processing calexp %s; skipping it: %s", dataId, e)
465 for warpType
in warpTypeList:
466 self.log.info(
"%sWarp has %d good pixels (%.1f%%)",
467 warpType, totGoodPix[warpType], 100.0*totGoodPix[warpType]/skyInfo.bbox.getArea())
469 if totGoodPix[warpType] > 0
and didSetMetadata[warpType]:
470 inputRecorder[warpType].finish(coaddTempExps[warpType], totGoodPix[warpType])
471 if warpType ==
"direct":
472 coaddTempExps[warpType].setPsf(
473 CoaddPsf(inputRecorder[warpType].coaddInputs.ccds, skyInfo.wcs,
474 self.config.coaddPsf.makeControl()))
476 if not self.config.doWriteEmptyWarps:
478 coaddTempExps[warpType] =
None
480 result = pipeBase.Struct(exposures=coaddTempExps)
484 """Return one calibrated Exposure, possibly with an updated SkyWcs.
486 @param[in] dataRef a sensor-level data reference
487 @param[in] bgSubtracted return calexp with background subtracted? If False get the
488 calexp's background background model and add it to the calexp.
489 @return calibrated exposure
491 @raises MissingExposureError If data for the exposure is not available.
493 If config.doApplyExternalPhotoCalib is `True`, the photometric calibration
494 (`photoCalib`) is taken from `config.externalPhotoCalibName` via the
495 `name_photoCalib` dataset. Otherwise, the photometric calibration is
496 retrieved from the processed exposure. When
497 `config.doApplyExternalSkyWcs` is `True`, the astrometric calibration
498 is taken from `config.externalSkyWcsName` with the `name_wcs` dataset.
499 Otherwise, the astrometric calibration is taken from the processed
503 exposure = dataRef.get(self.
calexpTypecalexpType, immediate=
True)
504 except dafPersist.NoResults
as e:
508 background = dataRef.get(
"calexpBackground", immediate=
True)
509 mi = exposure.getMaskedImage()
510 mi += background.getImage()
513 if self.config.doApplyExternalPhotoCalib:
514 source = f
"{self.config.externalPhotoCalibName}_photoCalib"
515 self.log.debug(
"Applying external photoCalib to %s from %s", dataRef.dataId, source)
516 photoCalib = dataRef.get(source)
517 exposure.setPhotoCalib(photoCalib)
519 photoCalib = exposure.getPhotoCalib()
521 if self.config.doApplyExternalSkyWcs:
522 source = f
"{self.config.externalSkyWcsName}_wcs"
523 self.log.debug(
"Applying external skyWcs to %s from %s", dataRef.dataId, source)
524 skyWcs = dataRef.get(source)
525 exposure.setWcs(skyWcs)
527 exposure.maskedImage = photoCalib.calibrateImage(exposure.maskedImage,
528 includeScaleUncertainty=self.config.includeCalibVar)
529 exposure.maskedImage /= photoCalib.getCalibrationMean()
535 def _prepareEmptyExposure(skyInfo):
536 """Produce an empty exposure for a given patch"""
537 exp = afwImage.ExposureF(skyInfo.bbox, skyInfo.wcs)
538 exp.getMaskedImage().set(numpy.nan, afwImage.Mask
539 .getPlaneBitMask(
"NO_DATA"), numpy.inf)
543 """Return list of requested warp types per the config.
546 if self.config.makeDirect:
547 warpTypeList.append(
"direct")
548 if self.config.makePsfMatched:
549 warpTypeList.append(
"psfMatched")
553 """Apply correction to the sky background level
555 Sky corrections can be generated with the 'skyCorrection.py'
556 executable in pipe_drivers. Because the sky model used by that
557 code extends over the entire focal plane, this can produce
558 better sky subtraction.
560 The calexp is updated in-place.
564 dataRef : `lsst.daf.persistence.ButlerDataRef`
565 Data reference for calexp.
566 calexp : `lsst.afw.image.Exposure` or `lsst.afw.image.MaskedImage`
569 bg = dataRef.get(
"skyCorr")
570 self.log.debug(
"Applying sky correction to %s", dataRef.dataId)
571 if isinstance(calexp, afwImage.Exposure):
572 calexp = calexp.getMaskedImage()
573 calexp -= bg.getImage()
577 dimensions=(
"tract",
"patch",
"skymap",
"instrument",
"visit"),
578 defaultTemplates={
"coaddName":
"deep",
579 "skyWcsName":
"jointcal",
580 "photoCalibName":
"fgcm",
582 calExpList = connectionTypes.Input(
583 doc=
"Input exposures to be resampled and optionally PSF-matched onto a SkyMap projection/patch",
584 name=
"{calexpType}calexp",
585 storageClass=
"ExposureF",
586 dimensions=(
"instrument",
"visit",
"detector"),
590 backgroundList = connectionTypes.Input(
591 doc=
"Input backgrounds to be added back into the calexp if bgSubtracted=False",
592 name=
"calexpBackground",
593 storageClass=
"Background",
594 dimensions=(
"instrument",
"visit",
"detector"),
597 skyCorrList = connectionTypes.Input(
598 doc=
"Input Sky Correction to be subtracted from the calexp if doApplySkyCorr=True",
600 storageClass=
"Background",
601 dimensions=(
"instrument",
"visit",
"detector"),
604 skyMap = connectionTypes.Input(
605 doc=
"Input definition of geometry/bbox and projection/wcs for warped exposures",
606 name=BaseSkyMap.SKYMAP_DATASET_TYPE_NAME,
607 storageClass=
"SkyMap",
608 dimensions=(
"skymap",),
610 externalSkyWcsTractCatalog = connectionTypes.Input(
611 doc=(
"Per-tract, per-visit wcs calibrations. These catalogs use the detector "
612 "id for the catalog id, sorted on id for fast lookup."),
613 name=
"{skyWcsName}SkyWcsCatalog",
614 storageClass=
"ExposureCatalog",
615 dimensions=(
"instrument",
"visit",
"tract"),
617 externalSkyWcsGlobalCatalog = connectionTypes.Input(
618 doc=(
"Per-visit wcs calibrations computed globally (with no tract information). "
619 "These catalogs use the detector id for the catalog id, sorted on id for "
621 name=
"{skyWcsName}SkyWcsCatalog",
622 storageClass=
"ExposureCatalog",
623 dimensions=(
"instrument",
"visit"),
625 externalPhotoCalibTractCatalog = connectionTypes.Input(
626 doc=(
"Per-tract, per-visit photometric calibrations. These catalogs use the "
627 "detector id for the catalog id, sorted on id for fast lookup."),
628 name=
"{photoCalibName}PhotoCalibCatalog",
629 storageClass=
"ExposureCatalog",
630 dimensions=(
"instrument",
"visit",
"tract"),
632 externalPhotoCalibGlobalCatalog = connectionTypes.Input(
633 doc=(
"Per-visit photometric calibrations computed globally (with no tract "
634 "information). These catalogs use the detector id for the catalog id, "
635 "sorted on id for fast lookup."),
636 name=
"{photoCalibName}PhotoCalibCatalog",
637 storageClass=
"ExposureCatalog",
638 dimensions=(
"instrument",
"visit"),
640 direct = connectionTypes.Output(
641 doc=(
"Output direct warped exposure (previously called CoaddTempExp), produced by resampling ",
642 "calexps onto the skyMap patch geometry."),
643 name=
"{coaddName}Coadd_directWarp",
644 storageClass=
"ExposureF",
645 dimensions=(
"tract",
"patch",
"skymap",
"visit",
"instrument"),
647 psfMatched = connectionTypes.Output(
648 doc=(
"Output PSF-Matched warped exposure (previously called CoaddTempExp), produced by resampling ",
649 "calexps onto the skyMap patch geometry and PSF-matching to a model PSF."),
650 name=
"{coaddName}Coadd_psfMatchedWarp",
651 storageClass=
"ExposureF",
652 dimensions=(
"tract",
"patch",
"skymap",
"visit",
"instrument"),
655 wcsList = connectionTypes.Input(
656 doc=
"WCSs of calexps used by SelectImages subtask to determine if the calexp overlaps the patch",
657 name=
"{calexpType}calexp.wcs",
659 dimensions=(
"instrument",
"visit",
"detector"),
662 bboxList = connectionTypes.Input(
663 doc=
"BBoxes of calexps used by SelectImages subtask to determine if the calexp overlaps the patch",
664 name=
"{calexpType}calexp.bbox",
665 storageClass=
"Box2I",
666 dimensions=(
"instrument",
"visit",
"detector"),
669 srcList = connectionTypes.Input(
670 doc=
"src catalogs used by PsfWcsSelectImages subtask to further select on PSF stability",
672 storageClass=
"SourceCatalog",
673 dimensions=(
"instrument",
"visit",
"detector"),
676 psfList = connectionTypes.Input(
677 doc=
"PSF models used by BestSeeingWcsSelectImages subtask to futher select on seeing",
678 name=
"{calexpType}calexp.psf",
680 dimensions=(
"instrument",
"visit",
"detector"),
684 def __init__(self, *, config=None):
685 super().__init__(config=config)
686 if config.bgSubtracted:
687 self.inputs.remove(
"backgroundList")
688 if not config.doApplySkyCorr:
689 self.inputs.remove(
"skyCorrList")
690 if config.doApplyExternalSkyWcs:
691 if config.useGlobalExternalSkyWcs:
692 self.inputs.remove(
"externalSkyWcsTractCatalog")
694 self.inputs.remove(
"externalSkyWcsGlobalCatalog")
696 self.inputs.remove(
"externalSkyWcsTractCatalog")
697 self.inputs.remove(
"externalSkyWcsGlobalCatalog")
698 if config.doApplyExternalPhotoCalib:
699 if config.useGlobalExternalPhotoCalib:
700 self.inputs.remove(
"externalPhotoCalibTractCatalog")
702 self.inputs.remove(
"externalPhotoCalibGlobalCatalog")
704 self.inputs.remove(
"externalPhotoCalibTractCatalog")
705 self.inputs.remove(
"externalPhotoCalibGlobalCatalog")
706 if not config.makeDirect:
707 self.outputs.remove(
"direct")
708 if not config.makePsfMatched:
709 self.outputs.remove(
"psfMatched")
712 if config.select.target != lsst.pipe.tasks.selectImages.PsfWcsSelectImagesTask:
713 self.inputs.remove(
"srcList")
714 if config.select.target != lsst.pipe.tasks.selectImages.BestSeeingWcsSelectImagesTask:
715 self.inputs.remove(
"psfList")
719 pipelineConnections=MakeWarpConnections):
726 """Warp and optionally PSF-Match calexps onto an a common projection
728 ConfigClass = MakeWarpConfig
729 _DefaultName =
"makeWarp"
731 @utils.inheritDoc(pipeBase.PipelineTask)
732 def runQuantum(self, butlerQC, inputRefs, outputRefs):
736 Construct warps for requested warp type for single epoch
738 PipelineTask (Gen3) entry point to warp and optionally PSF-match
739 calexps. This method is analogous to `runDataRef`.
743 detectorOrder = [ref.datasetRef.dataId[
'detector']
for ref
in inputRefs.calExpList]
744 inputRefs = reorderRefs(inputRefs, detectorOrder, dataIdKey=
'detector')
747 inputs = butlerQC.get(inputRefs)
751 skyMap = inputs.pop(
"skyMap")
752 quantumDataId = butlerQC.quantum.dataId
753 skyInfo =
makeSkyInfo(skyMap, tractId=quantumDataId[
'tract'], patchId=quantumDataId[
'patch'])
756 dataIdList = [ref.datasetRef.dataId
for ref
in inputRefs.calExpList]
758 ccdIdList = [dataId.pack(
"visit_detector")
for dataId
in dataIdList]
763 coordList = [skyInfo.wcs.pixelToSky(pos)
for pos
in cornerPosList]
764 goodIndices = self.select.
run(**inputs, coordList=coordList, dataIds=dataIdList)
765 inputs = self.filterInputs(indices=goodIndices, inputs=inputs)
768 inputs[
'calExpList'] = [ref.get()
for ref
in inputs[
'calExpList']]
771 visits = [dataId[
'visit']
for dataId
in dataIdList]
774 if self.config.doApplyExternalSkyWcs:
775 if self.config.useGlobalExternalSkyWcs:
776 externalSkyWcsCatalog = inputs.pop(
"externalSkyWcsGlobalCatalog")
778 externalSkyWcsCatalog = inputs.pop(
"externalSkyWcsTractCatalog")
780 externalSkyWcsCatalog =
None
782 if self.config.doApplyExternalPhotoCalib:
783 if self.config.useGlobalExternalPhotoCalib:
784 externalPhotoCalibCatalog = inputs.pop(
"externalPhotoCalibGlobalCatalog")
786 externalPhotoCalibCatalog = inputs.pop(
"externalPhotoCalibTractCatalog")
788 externalPhotoCalibCatalog =
None
790 completeIndices = self.prepareCalibratedExposures(**inputs,
791 externalSkyWcsCatalog=externalSkyWcsCatalog,
792 externalPhotoCalibCatalog=externalPhotoCalibCatalog)
794 inputs = self.filterInputs(indices=completeIndices, inputs=inputs)
796 results = self.run(**inputs, visitId=visitId,
797 ccdIdList=[ccdIdList[i]
for i
in goodIndices],
798 dataIdList=[dataIdList[i]
for i
in goodIndices],
800 if self.config.makeDirect
and results.exposures[
"direct"]
is not None:
801 butlerQC.put(results.exposures[
"direct"], outputRefs.direct)
802 if self.config.makePsfMatched
and results.exposures[
"psfMatched"]
is not None:
803 butlerQC.put(results.exposures[
"psfMatched"], outputRefs.psfMatched)
805 def filterInputs(self, indices, inputs):
806 """Return task inputs with their lists filtered by indices
810 indices : `list` of integers
811 inputs : `dict` of `list` of input connections to be passed to run
813 for key
in inputs.keys():
815 if isinstance(inputs[key], list):
816 inputs[key] = [inputs[key][ind]
for ind
in indices]
819 def prepareCalibratedExposures(self, calExpList, backgroundList=None, skyCorrList=None,
820 externalSkyWcsCatalog=None, externalPhotoCalibCatalog=None,
822 """Calibrate and add backgrounds to input calExpList in place
826 calExpList : `list` of `lsst.afw.image.Exposure`
827 Sequence of calexps to be modified in place
828 backgroundList : `list` of `lsst.afw.math.backgroundList`, optional
829 Sequence of backgrounds to be added back in if bgSubtracted=False
830 skyCorrList : `list` of `lsst.afw.math.backgroundList`, optional
831 Sequence of background corrections to be subtracted if doApplySkyCorr=True
832 externalSkyWcsCatalog : `lsst.afw.table.ExposureCatalog`, optional
833 Exposure catalog with external skyWcs to be applied
834 if config.doApplyExternalSkyWcs=True. Catalog uses the detector id
835 for the catalog id, sorted on id for fast lookup.
836 externalPhotoCalibCatalog : `lsst.afw.table.ExposureCatalog`, optional
837 Exposure catalog with external photoCalib to be applied
838 if config.doApplyExternalPhotoCalib=True. Catalog uses the detector
839 id for the catalog id, sorted on id for fast lookup.
843 indices : `list` [`int`]
844 Indices of calExpList and friends that have valid photoCalib/skyWcs
846 backgroundList = len(calExpList)*[
None]
if backgroundList
is None else backgroundList
847 skyCorrList = len(calExpList)*[
None]
if skyCorrList
is None else skyCorrList
849 includeCalibVar = self.config.includeCalibVar
852 for index, (calexp, background, skyCorr)
in enumerate(zip(calExpList,
855 mi = calexp.maskedImage
856 if not self.config.bgSubtracted:
857 mi += background.getImage()
859 if externalSkyWcsCatalog
is not None or externalPhotoCalibCatalog
is not None:
860 detectorId = calexp.getInfo().getDetector().getId()
863 if externalPhotoCalibCatalog
is not None:
864 row = externalPhotoCalibCatalog.find(detectorId)
866 self.log.warning(
"Detector id %s not found in externalPhotoCalibCatalog "
867 "and will not be used in the warp.", detectorId)
869 photoCalib = row.getPhotoCalib()
870 if photoCalib
is None:
871 self.log.warning(
"Detector id %s has None for photoCalib in externalPhotoCalibCatalog "
872 "and will not be used in the warp.", detectorId)
874 calexp.setPhotoCalib(photoCalib)
876 photoCalib = calexp.getPhotoCalib()
877 if photoCalib
is None:
878 self.log.warning(
"Detector id %s has None for photoCalib in the calexp "
879 "and will not be used in the warp.", detectorId)
883 if externalSkyWcsCatalog
is not None:
884 row = externalSkyWcsCatalog.find(detectorId)
886 self.log.warning(
"Detector id %s not found in externalSkyWcsCatalog "
887 "and will not be used in the warp.", detectorId)
889 skyWcs = row.getWcs()
891 self.log.warning(
"Detector id %s has None for skyWcs in externalSkyWcsCatalog "
892 "and will not be used in the warp.", detectorId)
894 calexp.setWcs(skyWcs)
896 skyWcs = calexp.getWcs()
898 self.log.warning(
"Detector id %s has None for skyWcs in the calexp "
899 "and will not be used in the warp.", detectorId)
903 calexp.maskedImage = photoCalib.calibrateImage(calexp.maskedImage,
904 includeScaleUncertainty=includeCalibVar)
905 calexp.maskedImage /= photoCalib.getCalibrationMean()
910 if self.config.doApplySkyCorr:
911 mi -= skyCorr.getImage()
913 indices.append(index)
918 def reorderRefs(inputRefs, outputSortKeyOrder, dataIdKey):
919 """Reorder inputRefs per outputSortKeyOrder
921 Any inputRefs which are lists will be resorted per specified key e.g.,
922 'detector.' Only iterables will be reordered, and values can be of type
923 `lsst.pipe.base.connections.DeferredDatasetRef` or
924 `lsst.daf.butler.core.datasets.ref.DatasetRef`.
925 Returned lists of refs have the same length as the outputSortKeyOrder.
926 If an outputSortKey not in the inputRef, then it will be padded with None.
927 If an inputRef contains an inputSortKey that is not in the
928 outputSortKeyOrder it will be removed.
932 inputRefs : `lsst.pipe.base.connections.QuantizedConnection`
933 Input references to be reordered and padded.
934 outputSortKeyOrder : iterable
935 Iterable of values to be compared with inputRef's dataId[dataIdKey]
937 dataIdKey in the dataRefs to compare with the outputSortKeyOrder.
941 inputRefs: `lsst.pipe.base.connections.QuantizedConnection`
942 Quantized Connection with sorted DatasetRef values sorted if iterable.
944 for connectionName, refs
in inputRefs:
945 if isinstance(refs, Iterable):
946 if hasattr(refs[0],
"dataId"):
947 inputSortKeyOrder = [ref.dataId[dataIdKey]
for ref
in refs]
949 inputSortKeyOrder = [ref.datasetRef.dataId[dataIdKey]
for ref
in refs]
950 if inputSortKeyOrder != outputSortKeyOrder:
951 setattr(inputRefs, connectionName,
Base class for coaddition.
def getTempExpDatasetName(self, warpType="direct")
def selectExposures(self, patchRef, skyInfo=None, selectDataList=[])
Select exposures to coadd.
def getCoaddDatasetName(self, warpType="direct")
def getSkyInfo(self, patchRef)
Use getSkyinfo to return the skyMap, tract and patch information, wcs and the outer bbox of the patch...
def getBadPixelMask(self)
Convenience method to provide the bitmask from the mask plane names.
Warp and optionally PSF-Match calexps onto an a common projection.
def getCalibratedExposure(self, dataRef, bgSubtracted)
def run(self, calExpList, ccdIdList, skyInfo, visitId=0, dataIdList=None, **kwargs)
def __init__(self, reuse=False, **kwargs)
def _prepareEmptyExposure(skyInfo)
def runDataRef(self, patchRef, selectDataList=[])
Produce <coaddName>Coadd_<warpType>Warp images by warping and optionally PSF-matching.
def getWarpTypeList(self)
def applySkyCorr(self, dataRef, calexp)
def run(self, skyInfo, tempExpRefList, imageScalerList, weightList, altMaskList=None, mask=None, supplementaryData=None)
def reorderAndPadList(inputList, inputKeys, outputKeys, padWith=None)
def makeSkyInfo(skyMap, tractId, patchId)
def getGroupDataRef(butler, datasetType, groupTuple, keys)
def groupPatchExposures(patchDataRef, calexpDataRefList, coaddDatasetType="deepCoadd", tempExpDatasetType="deepCoadd_directWarp")