Coverage for python/lsst/pipe/tasks/makeCoaddTempExp.py : 14%

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1#
2# LSST Data Management System
3# Copyright 2008, 2009, 2010, 2011, 2012 LSST Corporation.
4#
5# This product includes software developed by the
6# LSST Project (http://www.lsst.org/).
7#
8# This program is free software: you can redistribute it and/or modify
9# it under the terms of the GNU General Public License as published by
10# the Free Software Foundation, either version 3 of the License, or
11# (at your option) any later version.
12#
13# This program is distributed in the hope that it will be useful,
14# but WITHOUT ANY WARRANTY; without even the implied warranty of
15# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16# GNU General Public License for more details.
17#
18# You should have received a copy of the LSST License Statement and
19# the GNU General Public License along with this program. If not,
20# see <http://www.lsstcorp.org/LegalNotices/>.
21#
22import numpy
24import lsst.pex.config as pexConfig
25import lsst.daf.persistence as dafPersist
26import lsst.afw.image as afwImage
27import lsst.coadd.utils as coaddUtils
28import lsst.pipe.base as pipeBase
29import lsst.pipe.base.connectionTypes as connectionTypes
30import lsst.log as log
31import lsst.utils as utils
32import lsst.geom
33from lsst.meas.algorithms import CoaddPsf, CoaddPsfConfig
34from lsst.skymap import BaseSkyMap
35from .coaddBase import CoaddBaseTask, makeSkyInfo, reorderAndPadList
36from .warpAndPsfMatch import WarpAndPsfMatchTask
37from .coaddHelpers import groupPatchExposures, getGroupDataRef
38from collections.abc import Iterable
40__all__ = ["MakeCoaddTempExpTask", "MakeWarpTask", "MakeWarpConfig"]
43class MissingExposureError(Exception):
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.
47 """
48 pass
51class MakeCoaddTempExpConfig(CoaddBaseTask.ConfigClass):
52 """Config for MakeCoaddTempExpTask
53 """
54 warpAndPsfMatch = pexConfig.ConfigurableField(
55 target=WarpAndPsfMatchTask,
56 doc="Task to warp and PSF-match calexp",
57 )
58 doWrite = pexConfig.Field(
59 doc="persist <coaddName>Coadd_<warpType>Warp",
60 dtype=bool,
61 default=True,
62 )
63 bgSubtracted = pexConfig.Field(
64 doc="Work with a background subtracted calexp?",
65 dtype=bool,
66 default=True,
67 )
68 coaddPsf = pexConfig.ConfigField(
69 doc="Configuration for CoaddPsf",
70 dtype=CoaddPsfConfig,
71 )
72 makeDirect = pexConfig.Field(
73 doc="Make direct Warp/Coadds",
74 dtype=bool,
75 default=True,
76 )
77 makePsfMatched = pexConfig.Field(
78 doc="Make Psf-Matched Warp/Coadd?",
79 dtype=bool,
80 default=False,
81 )
83 doWriteEmptyWarps = pexConfig.Field(
84 dtype=bool,
85 default=False,
86 doc="Write out warps even if they are empty"
87 )
89 hasFakes = pexConfig.Field(
90 doc="Should be set to True if fake sources have been inserted into the input data.",
91 dtype=bool,
92 default=False,
93 )
94 doApplySkyCorr = pexConfig.Field(dtype=bool, default=False, doc="Apply sky correction?")
96 def validate(self):
97 CoaddBaseTask.ConfigClass.validate(self)
98 if not self.makePsfMatched and not self.makeDirect:
99 raise RuntimeError("At least one of config.makePsfMatched and config.makeDirect must be True")
100 if self.doPsfMatch:
101 # Backwards compatibility.
102 log.warning("Config doPsfMatch deprecated. Setting makePsfMatched=True and makeDirect=False")
103 self.makePsfMatched = True
104 self.makeDirect = False
106 def setDefaults(self):
107 CoaddBaseTask.ConfigClass.setDefaults(self)
108 self.warpAndPsfMatch.psfMatch.kernel.active.kernelSize = self.matchingKernelSize
110## \addtogroup LSST_task_documentation
111## \{
112## \page MakeCoaddTempExpTask
113## \ref MakeCoaddTempExpTask_ "MakeCoaddTempExpTask"
114## \copybrief MakeCoaddTempExpTask
115## \}
118class MakeCoaddTempExpTask(CoaddBaseTask):
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
139 on each visit
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
149 output repositories.
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)
156 to process.
158 @copydoc run
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.
192 For example:_
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.
239 Set up by running:
241 setup ci_hsc
242 cd $CI_HSC_DIR
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`
260 respectively.
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:
266 echo "
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.
272 """
273 ConfigClass = MakeCoaddTempExpConfig
274 _DefaultName = "makeCoaddTempExp"
276 def __init__(self, reuse=False, **kwargs):
277 CoaddBaseTask.__init__(self, **kwargs)
278 self.reuse = reuse
279 self.makeSubtask("warpAndPsfMatch")
280 if self.config.hasFakes:
281 self.calexpType = "fakes_calexp"
282 else:
283 self.calexpType = "calexp"
285 @pipeBase.timeMethod
286 def runDataRef(self, patchRef, selectDataList=[]):
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
293 warps are requested.
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).
300 """
301 skyInfo = self.getSkyInfo(patchRef)
303 # DataRefs to return are of type *_directWarp unless only *_psfMatchedWarp requested
304 if self.config.makePsfMatched and not self.config.makeDirect:
305 primaryWarpDataset = self.getTempExpDatasetName("psfMatched")
306 else:
307 primaryWarpDataset = self.getTempExpDatasetName("direct")
309 calExpRefList = self.selectExposures(patchRef, skyInfo, selectDataList=selectDataList)
311 if len(calExpRefList) == 0:
312 self.log.warning("No exposures to coadd for patch %s", patchRef.dataId)
313 return None
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.calexpType)]
316 self.log.info("Processing %d existing calexps for patch %s", len(calExpRefList), patchRef.dataId)
318 groupData = groupPatchExposures(patchRef, calExpRefList, self.getCoaddDatasetName(),
319 primaryWarpDataset)
320 self.log.info("Processing %d warp exposures for patch %s", len(groupData.groups), patchRef.dataId)
322 dataRefList = []
323 for i, (tempExpTuple, calexpRefList) in enumerate(groupData.groups.items()):
324 tempExpRef = getGroupDataRef(patchRef.getButler(), primaryWarpDataset,
325 tempExpTuple, groupData.keys)
326 if self.reuse and tempExpRef.datasetExists(datasetType=primaryWarpDataset, write=True):
327 self.log.info("Skipping makeCoaddTempExp for %s; output already exists.", tempExpRef.dataId)
328 dataRefList.append(tempExpRef)
329 continue
330 self.log.info("Processing Warp %d/%d: id=%s", i, len(groupData.groups), tempExpRef.dataId)
332 # TODO: mappers should define a way to go from the "grouping keys" to a numeric ID (#2776).
333 # For now, we try to get a long integer "visit" key, and if we can't, we just use the index
334 # of the visit in the list.
335 try:
336 visitId = int(tempExpRef.dataId["visit"])
337 except (KeyError, ValueError):
338 visitId = i
340 calExpList = []
341 ccdIdList = []
342 dataIdList = []
344 for calExpInd, calExpRef in enumerate(calexpRefList):
345 self.log.info("Reading calexp %s of %s for Warp id=%s", calExpInd+1, len(calexpRefList),
346 calExpRef.dataId)
347 try:
348 ccdId = calExpRef.get("ccdExposureId", immediate=True)
349 except Exception:
350 ccdId = calExpInd
351 try:
352 # We augment the dataRef here with the tract, which is harmless for loading things
353 # like calexps that don't need the tract, and necessary for meas_mosaic outputs,
354 # which do.
355 calExpRef = calExpRef.butlerSubset.butler.dataRef(self.calexpType,
356 dataId=calExpRef.dataId,
357 tract=skyInfo.tractInfo.getId())
358 calExp = self.getCalibratedExposure(calExpRef, bgSubtracted=self.config.bgSubtracted)
359 except Exception as e:
360 self.log.warning("Calexp %s not found; skipping it: %s", calExpRef.dataId, e)
361 continue
363 if self.config.doApplySkyCorr:
364 self.applySkyCorr(calExpRef, calExp)
366 calExpList.append(calExp)
367 ccdIdList.append(ccdId)
368 dataIdList.append(calExpRef.dataId)
370 exps = self.run(calExpList, ccdIdList, skyInfo, visitId, dataIdList).exposures
372 if any(exps.values()):
373 dataRefList.append(tempExpRef)
374 else:
375 self.log.warning("Warp %s could not be created", tempExpRef.dataId)
377 if self.config.doWrite:
378 for (warpType, exposure) in exps.items(): # compatible w/ Py3
379 if exposure is not None:
380 self.log.info("Persisting %s", self.getTempExpDatasetName(warpType))
381 tempExpRef.put(exposure, self.getTempExpDatasetName(warpType))
383 return dataRefList
385 @pipeBase.timeMethod
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
402 produce the CoaddPsf
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
407 """
408 warpTypeList = self.getWarpTypeList()
410 totGoodPix = {warpType: 0 for warpType in warpTypeList}
411 didSetMetadata = {warpType: False for warpType in warpTypeList}
412 coaddTempExps = {warpType: self._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)
424 try:
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)
431 continue
432 try:
433 numGoodPix = {warpType: 0 for warpType in warpTypeList}
434 for warpType in warpTypeList:
435 exposure = warpedAndMatched.getDict()[warpType]
436 if exposure is None:
437 continue
438 coaddTempExp = coaddTempExps[warpType]
439 if didSetMetadata[warpType]:
440 mimg = exposure.getMaskedImage()
441 mimg *= (coaddTempExp.getPhotoCalib().getInstFluxAtZeroMagnitude()
442 / exposure.getPhotoCalib().getInstFluxAtZeroMagnitude())
443 del mimg
444 numGoodPix[warpType] = coaddUtils.copyGoodPixels(
445 coaddTempExp.getMaskedImage(), exposure.getMaskedImage(), self.getBadPixelMask())
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())
454 # PSF replaced with CoaddPsf after loop if and only if creating direct warp
455 coaddTempExp.setPsf(exposure.getPsf())
456 didSetMetadata[warpType] = True
458 # Need inputRecorder for CoaddApCorrMap for both direct and PSF-matched
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)
463 continue
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()))
475 else:
476 if not self.config.doWriteEmptyWarps:
477 # No good pixels. Exposure still empty
478 coaddTempExps[warpType] = None
480 result = pipeBase.Struct(exposures=coaddTempExps)
481 return result
483 def getCalibratedExposure(self, dataRef, bgSubtracted):
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
500 exposure.
501 """
502 try:
503 exposure = dataRef.get(self.calexpType, immediate=True)
504 except dafPersist.NoResults as e:
505 raise MissingExposureError('Exposure not found: %s ' % str(e)) from e
507 if not bgSubtracted:
508 background = dataRef.get("calexpBackground", immediate=True)
509 mi = exposure.getMaskedImage()
510 mi += background.getImage()
511 del mi
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)
518 else:
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()
530 # TODO: The images will have a calibration of 1.0 everywhere once RFC-545 is implemented.
531 # exposure.setCalib(afwImage.Calib(1.0))
532 return exposure
534 @staticmethod
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)
540 return exp
542 def getWarpTypeList(self):
543 """Return list of requested warp types per the config.
544 """
545 warpTypeList = []
546 if self.config.makeDirect:
547 warpTypeList.append("direct")
548 if self.config.makePsfMatched:
549 warpTypeList.append("psfMatched")
550 return warpTypeList
552 def applySkyCorr(self, dataRef, calexp):
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.
562 Parameters
563 ----------
564 dataRef : `lsst.daf.persistence.ButlerDataRef`
565 Data reference for calexp.
566 calexp : `lsst.afw.image.Exposure` or `lsst.afw.image.MaskedImage`
567 Calibrated exposure.
568 """
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()
576class MakeWarpConnections(pipeBase.PipelineTaskConnections,
577 dimensions=("tract", "patch", "skymap", "instrument", "visit"),
578 defaultTemplates={"coaddName": "deep",
579 "skyWcsName": "jointcal",
580 "photoCalibName": "fgcm",
581 "calexpType": ""}):
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"),
587 multiple=True,
588 deferLoad=True,
589 )
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"),
595 multiple=True,
596 )
597 skyCorrList = connectionTypes.Input(
598 doc="Input Sky Correction to be subtracted from the calexp if doApplySkyCorr=True",
599 name="skyCorr",
600 storageClass="Background",
601 dimensions=("instrument", "visit", "detector"),
602 multiple=True,
603 )
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",),
609 )
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"),
616 )
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 "
620 "fast lookup."),
621 name="{skyWcsName}SkyWcsCatalog",
622 storageClass="ExposureCatalog",
623 dimensions=("instrument", "visit"),
624 )
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"),
631 )
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"),
639 )
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"),
646 )
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"),
653 )
654 # TODO DM-28769, have selectImages subtask indicate which connections they need:
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",
658 storageClass="Wcs",
659 dimensions=("instrument", "visit", "detector"),
660 multiple=True,
661 )
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"),
667 multiple=True,
668 )
669 srcList = connectionTypes.Input(
670 doc="src catalogs used by PsfWcsSelectImages subtask to further select on PSF stability",
671 name="src",
672 storageClass="SourceCatalog",
673 dimensions=("instrument", "visit", "detector"),
674 multiple=True,
675 )
676 psfList = connectionTypes.Input(
677 doc="PSF models used by BestSeeingWcsSelectImages subtask to futher select on seeing",
678 name="{calexpType}calexp.psf",
679 storageClass="Psf",
680 dimensions=("instrument", "visit", "detector"),
681 multiple=True,
682 )
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")
693 else:
694 self.inputs.remove("externalSkyWcsGlobalCatalog")
695 else:
696 self.inputs.remove("externalSkyWcsTractCatalog")
697 self.inputs.remove("externalSkyWcsGlobalCatalog")
698 if config.doApplyExternalPhotoCalib:
699 if config.useGlobalExternalPhotoCalib:
700 self.inputs.remove("externalPhotoCalibTractCatalog")
701 else:
702 self.inputs.remove("externalPhotoCalibGlobalCatalog")
703 else:
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")
710 # TODO DM-28769: add connection per selectImages connections
711 # instead of removing if not PsfWcsSelectImagesTask here:
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")
718class MakeWarpConfig(pipeBase.PipelineTaskConfig, MakeCoaddTempExpConfig,
719 pipelineConnections=MakeWarpConnections):
721 def validate(self):
722 super().validate()
725class MakeWarpTask(MakeCoaddTempExpTask):
726 """Warp and optionally PSF-Match calexps onto an a common projection
727 """
728 ConfigClass = MakeWarpConfig
729 _DefaultName = "makeWarp"
731 @utils.inheritDoc(pipeBase.PipelineTask)
732 def runQuantum(self, butlerQC, inputRefs, outputRefs):
733 """
734 Notes
735 ----
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`.
740 """
742 # Ensure all input lists are in same detector order as the calExpList
743 detectorOrder = [ref.datasetRef.dataId['detector'] for ref in inputRefs.calExpList]
744 inputRefs = reorderRefs(inputRefs, detectorOrder, dataIdKey='detector')
746 # Read in all inputs.
747 inputs = butlerQC.get(inputRefs)
749 # Construct skyInfo expected by `run`. We remove the SkyMap itself
750 # from the dictionary so we can pass it as kwargs later.
751 skyMap = inputs.pop("skyMap")
752 quantumDataId = butlerQC.quantum.dataId
753 skyInfo = makeSkyInfo(skyMap, tractId=quantumDataId['tract'], patchId=quantumDataId['patch'])
755 # Construct list of input DataIds expected by `run`
756 dataIdList = [ref.datasetRef.dataId for ref in inputRefs.calExpList]
757 # Construct list of packed integer IDs expected by `run`
758 ccdIdList = [dataId.pack("visit_detector") for dataId in dataIdList]
760 # Run the selector and filter out calexps that were not selected
761 # primarily because they do not overlap the patch
762 cornerPosList = lsst.geom.Box2D(skyInfo.bbox).getCorners()
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)
767 # Read from disk only the selected calexps
768 inputs['calExpList'] = [ref.get() for ref in inputs['calExpList']]
770 # Extract integer visitId requested by `run`
771 visits = [dataId['visit'] for dataId in dataIdList]
772 visitId = visits[0]
774 if self.config.doApplyExternalSkyWcs:
775 if self.config.useGlobalExternalSkyWcs:
776 externalSkyWcsCatalog = inputs.pop("externalSkyWcsGlobalCatalog")
777 else:
778 externalSkyWcsCatalog = inputs.pop("externalSkyWcsTractCatalog")
779 else:
780 externalSkyWcsCatalog = None
782 if self.config.doApplyExternalPhotoCalib:
783 if self.config.useGlobalExternalPhotoCalib:
784 externalPhotoCalibCatalog = inputs.pop("externalPhotoCalibGlobalCatalog")
785 else:
786 externalPhotoCalibCatalog = inputs.pop("externalPhotoCalibTractCatalog")
787 else:
788 externalPhotoCalibCatalog = None
790 completeIndices = self.prepareCalibratedExposures(**inputs,
791 externalSkyWcsCatalog=externalSkyWcsCatalog,
792 externalPhotoCalibCatalog=externalPhotoCalibCatalog)
793 # Redo the input selection with inputs with complete wcs/photocalib info.
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],
799 skyInfo=skyInfo)
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
808 Parameters
809 ----------
810 indices : `list` of integers
811 inputs : `dict` of `list` of input connections to be passed to run
812 """
813 for key in inputs.keys():
814 # Only down-select on list inputs
815 if isinstance(inputs[key], list):
816 inputs[key] = [inputs[key][ind] for ind in indices]
817 return inputs
819 def prepareCalibratedExposures(self, calExpList, backgroundList=None, skyCorrList=None,
820 externalSkyWcsCatalog=None, externalPhotoCalibCatalog=None,
821 **kwargs):
822 """Calibrate and add backgrounds to input calExpList in place
824 Parameters
825 ----------
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.
841 Returns
842 -------
843 indices : `list` [`int`]
844 Indices of calExpList and friends that have valid photoCalib/skyWcs
845 """
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
851 indices = []
852 for index, (calexp, background, skyCorr) in enumerate(zip(calExpList,
853 backgroundList,
854 skyCorrList)):
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()
862 # Find the external photoCalib
863 if externalPhotoCalibCatalog is not None:
864 row = externalPhotoCalibCatalog.find(detectorId)
865 if row is None:
866 self.log.warning("Detector id %s not found in externalPhotoCalibCatalog "
867 "and will not be used in the warp.", detectorId)
868 continue
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)
873 continue
874 calexp.setPhotoCalib(photoCalib)
875 else:
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)
880 continue
882 # Find and apply external skyWcs
883 if externalSkyWcsCatalog is not None:
884 row = externalSkyWcsCatalog.find(detectorId)
885 if row is None:
886 self.log.warning("Detector id %s not found in externalSkyWcsCatalog "
887 "and will not be used in the warp.", detectorId)
888 continue
889 skyWcs = row.getWcs()
890 if skyWcs is None:
891 self.log.warning("Detector id %s has None for skyWcs in externalSkyWcsCatalog "
892 "and will not be used in the warp.", detectorId)
893 continue
894 calexp.setWcs(skyWcs)
895 else:
896 skyWcs = calexp.getWcs()
897 if skyWcs is None:
898 self.log.warning("Detector id %s has None for skyWcs in the calexp "
899 "and will not be used in the warp.", detectorId)
900 continue
902 # Calibrate the image
903 calexp.maskedImage = photoCalib.calibrateImage(calexp.maskedImage,
904 includeScaleUncertainty=includeCalibVar)
905 calexp.maskedImage /= photoCalib.getCalibrationMean()
906 # TODO: The images will have a calibration of 1.0 everywhere once RFC-545 is implemented.
907 # exposure.setCalib(afwImage.Calib(1.0))
909 # Apply skycorr
910 if self.config.doApplySkyCorr:
911 mi -= skyCorr.getImage()
913 indices.append(index)
915 return indices
918def 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.
930 Parameters
931 ----------
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]
936 dataIdKey : `str`
937 dataIdKey in the dataRefs to compare with the outputSortKeyOrder.
939 Returns:
940 --------
941 inputRefs: `lsst.pipe.base.connections.QuantizedConnection`
942 Quantized Connection with sorted DatasetRef values sorted if iterable.
943 """
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]
948 else:
949 inputSortKeyOrder = [ref.datasetRef.dataId[dataIdKey] for ref in refs]
950 if inputSortKeyOrder != outputSortKeyOrder:
951 setattr(inputRefs, connectionName,
952 reorderAndPadList(refs, inputSortKeyOrder, outputSortKeyOrder))
953 return inputRefs