Coverage for python/lsst/pipe/tasks/makeCoaddTempExp.py : 46%

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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: 280 ↛ 281line 280 didn't jump to line 281, because the condition on line 280 was never true
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: 304 ↛ 305line 304 didn't jump to line 305, because the condition on line 304 was never true
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: 311 ↛ 312line 311 didn't jump to line 312, because the condition on line 311 was never true
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): 326 ↛ 327line 326 didn't jump to line 327, because the condition on line 326 was never 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: 363 ↛ 364line 363 didn't jump to line 364, because the condition on line 363 was never true
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: 377 ↛ 323line 377 didn't jump to line 323, because the condition on line 377 was never false
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: 417 ↛ 418line 417 didn't jump to line 418, because the condition on line 417 was never true
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: 476 ↛ 465line 476 didn't jump to line 465, because the condition on line 476 was never false
477 # No good pixels. Exposure still empty
478 coaddTempExps[warpType] = None
479 # NoWorkFound is unnecessary as the downstream tasks will
480 # adjust the quantum accordingly, and it prevents gen2
481 # MakeCoaddTempExp from continuing to loop over visits.
483 result = pipeBase.Struct(exposures=coaddTempExps)
484 return result
486 def getCalibratedExposure(self, dataRef, bgSubtracted):
487 """Return one calibrated Exposure, possibly with an updated SkyWcs.
489 @param[in] dataRef a sensor-level data reference
490 @param[in] bgSubtracted return calexp with background subtracted? If False get the
491 calexp's background background model and add it to the calexp.
492 @return calibrated exposure
494 @raises MissingExposureError If data for the exposure is not available.
496 If config.doApplyExternalPhotoCalib is `True`, the photometric calibration
497 (`photoCalib`) is taken from `config.externalPhotoCalibName` via the
498 `name_photoCalib` dataset. Otherwise, the photometric calibration is
499 retrieved from the processed exposure. When
500 `config.doApplyExternalSkyWcs` is `True`, the astrometric calibration
501 is taken from `config.externalSkyWcsName` with the `name_wcs` dataset.
502 Otherwise, the astrometric calibration is taken from the processed
503 exposure.
504 """
505 try:
506 exposure = dataRef.get(self.calexpType, immediate=True)
507 except dafPersist.NoResults as e:
508 raise MissingExposureError('Exposure not found: %s ' % str(e)) from e
510 if not bgSubtracted: 510 ↛ 511line 510 didn't jump to line 511, because the condition on line 510 was never true
511 background = dataRef.get("calexpBackground", immediate=True)
512 mi = exposure.getMaskedImage()
513 mi += background.getImage()
514 del mi
516 if self.config.doApplyExternalPhotoCalib: 516 ↛ 517line 516 didn't jump to line 517, because the condition on line 516 was never true
517 source = f"{self.config.externalPhotoCalibName}_photoCalib"
518 self.log.debug("Applying external photoCalib to %s from %s", dataRef.dataId, source)
519 photoCalib = dataRef.get(source)
520 exposure.setPhotoCalib(photoCalib)
521 else:
522 photoCalib = exposure.getPhotoCalib()
524 if self.config.doApplyExternalSkyWcs: 524 ↛ 525line 524 didn't jump to line 525, because the condition on line 524 was never true
525 source = f"{self.config.externalSkyWcsName}_wcs"
526 self.log.debug("Applying external skyWcs to %s from %s", dataRef.dataId, source)
527 skyWcs = dataRef.get(source)
528 exposure.setWcs(skyWcs)
530 exposure.maskedImage = photoCalib.calibrateImage(exposure.maskedImage,
531 includeScaleUncertainty=self.config.includeCalibVar)
532 exposure.maskedImage /= photoCalib.getCalibrationMean()
533 # TODO: The images will have a calibration of 1.0 everywhere once RFC-545 is implemented.
534 # exposure.setCalib(afwImage.Calib(1.0))
535 return exposure
537 @staticmethod
538 def _prepareEmptyExposure(skyInfo):
539 """Produce an empty exposure for a given patch"""
540 exp = afwImage.ExposureF(skyInfo.bbox, skyInfo.wcs)
541 exp.getMaskedImage().set(numpy.nan, afwImage.Mask
542 .getPlaneBitMask("NO_DATA"), numpy.inf)
543 return exp
545 def getWarpTypeList(self):
546 """Return list of requested warp types per the config.
547 """
548 warpTypeList = []
549 if self.config.makeDirect: 549 ↛ 551line 549 didn't jump to line 551, because the condition on line 549 was never false
550 warpTypeList.append("direct")
551 if self.config.makePsfMatched: 551 ↛ 553line 551 didn't jump to line 553, because the condition on line 551 was never false
552 warpTypeList.append("psfMatched")
553 return warpTypeList
555 def applySkyCorr(self, dataRef, calexp):
556 """Apply correction to the sky background level
558 Sky corrections can be generated with the 'skyCorrection.py'
559 executable in pipe_drivers. Because the sky model used by that
560 code extends over the entire focal plane, this can produce
561 better sky subtraction.
563 The calexp is updated in-place.
565 Parameters
566 ----------
567 dataRef : `lsst.daf.persistence.ButlerDataRef`
568 Data reference for calexp.
569 calexp : `lsst.afw.image.Exposure` or `lsst.afw.image.MaskedImage`
570 Calibrated exposure.
571 """
572 bg = dataRef.get("skyCorr")
573 self.log.debug("Applying sky correction to %s", dataRef.dataId)
574 if isinstance(calexp, afwImage.Exposure):
575 calexp = calexp.getMaskedImage()
576 calexp -= bg.getImage()
579class MakeWarpConnections(pipeBase.PipelineTaskConnections,
580 dimensions=("tract", "patch", "skymap", "instrument", "visit"),
581 defaultTemplates={"coaddName": "deep",
582 "skyWcsName": "jointcal",
583 "photoCalibName": "fgcm",
584 "calexpType": ""}):
585 calExpList = connectionTypes.Input(
586 doc="Input exposures to be resampled and optionally PSF-matched onto a SkyMap projection/patch",
587 name="{calexpType}calexp",
588 storageClass="ExposureF",
589 dimensions=("instrument", "visit", "detector"),
590 multiple=True,
591 deferLoad=True,
592 )
593 backgroundList = connectionTypes.Input(
594 doc="Input backgrounds to be added back into the calexp if bgSubtracted=False",
595 name="calexpBackground",
596 storageClass="Background",
597 dimensions=("instrument", "visit", "detector"),
598 multiple=True,
599 )
600 skyCorrList = connectionTypes.Input(
601 doc="Input Sky Correction to be subtracted from the calexp if doApplySkyCorr=True",
602 name="skyCorr",
603 storageClass="Background",
604 dimensions=("instrument", "visit", "detector"),
605 multiple=True,
606 )
607 skyMap = connectionTypes.Input(
608 doc="Input definition of geometry/bbox and projection/wcs for warped exposures",
609 name=BaseSkyMap.SKYMAP_DATASET_TYPE_NAME,
610 storageClass="SkyMap",
611 dimensions=("skymap",),
612 )
613 externalSkyWcsTractCatalog = connectionTypes.Input(
614 doc=("Per-tract, per-visit wcs calibrations. These catalogs use the detector "
615 "id for the catalog id, sorted on id for fast lookup."),
616 name="{skyWcsName}SkyWcsCatalog",
617 storageClass="ExposureCatalog",
618 dimensions=("instrument", "visit", "tract"),
619 )
620 externalSkyWcsGlobalCatalog = connectionTypes.Input(
621 doc=("Per-visit wcs calibrations computed globally (with no tract information). "
622 "These catalogs use the detector id for the catalog id, sorted on id for "
623 "fast lookup."),
624 name="{skyWcsName}SkyWcsCatalog",
625 storageClass="ExposureCatalog",
626 dimensions=("instrument", "visit"),
627 )
628 externalPhotoCalibTractCatalog = connectionTypes.Input(
629 doc=("Per-tract, per-visit photometric calibrations. These catalogs use the "
630 "detector id for the catalog id, sorted on id for fast lookup."),
631 name="{photoCalibName}PhotoCalibCatalog",
632 storageClass="ExposureCatalog",
633 dimensions=("instrument", "visit", "tract"),
634 )
635 externalPhotoCalibGlobalCatalog = connectionTypes.Input(
636 doc=("Per-visit photometric calibrations computed globally (with no tract "
637 "information). These catalogs use the detector id for the catalog id, "
638 "sorted on id for fast lookup."),
639 name="{photoCalibName}PhotoCalibCatalog",
640 storageClass="ExposureCatalog",
641 dimensions=("instrument", "visit"),
642 )
643 direct = connectionTypes.Output(
644 doc=("Output direct warped exposure (previously called CoaddTempExp), produced by resampling ",
645 "calexps onto the skyMap patch geometry."),
646 name="{coaddName}Coadd_directWarp",
647 storageClass="ExposureF",
648 dimensions=("tract", "patch", "skymap", "visit", "instrument"),
649 )
650 psfMatched = connectionTypes.Output(
651 doc=("Output PSF-Matched warped exposure (previously called CoaddTempExp), produced by resampling ",
652 "calexps onto the skyMap patch geometry and PSF-matching to a model PSF."),
653 name="{coaddName}Coadd_psfMatchedWarp",
654 storageClass="ExposureF",
655 dimensions=("tract", "patch", "skymap", "visit", "instrument"),
656 )
657 # TODO DM-28769, have selectImages subtask indicate which connections they need:
658 wcsList = connectionTypes.Input(
659 doc="WCSs of calexps used by SelectImages subtask to determine if the calexp overlaps the patch",
660 name="{calexpType}calexp.wcs",
661 storageClass="Wcs",
662 dimensions=("instrument", "visit", "detector"),
663 multiple=True,
664 )
665 bboxList = connectionTypes.Input(
666 doc="BBoxes of calexps used by SelectImages subtask to determine if the calexp overlaps the patch",
667 name="{calexpType}calexp.bbox",
668 storageClass="Box2I",
669 dimensions=("instrument", "visit", "detector"),
670 multiple=True,
671 )
672 srcList = connectionTypes.Input(
673 doc="src catalogs used by PsfWcsSelectImages subtask to further select on PSF stability",
674 name="src",
675 storageClass="SourceCatalog",
676 dimensions=("instrument", "visit", "detector"),
677 multiple=True,
678 )
679 psfList = connectionTypes.Input(
680 doc="PSF models used by BestSeeingWcsSelectImages subtask to futher select on seeing",
681 name="{calexpType}calexp.psf",
682 storageClass="Psf",
683 dimensions=("instrument", "visit", "detector"),
684 multiple=True,
685 )
687 def __init__(self, *, config=None):
688 super().__init__(config=config)
689 if config.bgSubtracted:
690 self.inputs.remove("backgroundList")
691 if not config.doApplySkyCorr:
692 self.inputs.remove("skyCorrList")
693 if config.doApplyExternalSkyWcs:
694 if config.useGlobalExternalSkyWcs:
695 self.inputs.remove("externalSkyWcsTractCatalog")
696 else:
697 self.inputs.remove("externalSkyWcsGlobalCatalog")
698 else:
699 self.inputs.remove("externalSkyWcsTractCatalog")
700 self.inputs.remove("externalSkyWcsGlobalCatalog")
701 if config.doApplyExternalPhotoCalib:
702 if config.useGlobalExternalPhotoCalib:
703 self.inputs.remove("externalPhotoCalibTractCatalog")
704 else:
705 self.inputs.remove("externalPhotoCalibGlobalCatalog")
706 else:
707 self.inputs.remove("externalPhotoCalibTractCatalog")
708 self.inputs.remove("externalPhotoCalibGlobalCatalog")
709 if not config.makeDirect:
710 self.outputs.remove("direct")
711 if not config.makePsfMatched:
712 self.outputs.remove("psfMatched")
713 # TODO DM-28769: add connection per selectImages connections
714 # instead of removing if not PsfWcsSelectImagesTask here:
715 if config.select.target != lsst.pipe.tasks.selectImages.PsfWcsSelectImagesTask:
716 self.inputs.remove("srcList")
717 if config.select.target != lsst.pipe.tasks.selectImages.BestSeeingWcsSelectImagesTask:
718 self.inputs.remove("psfList")
721class MakeWarpConfig(pipeBase.PipelineTaskConfig, MakeCoaddTempExpConfig,
722 pipelineConnections=MakeWarpConnections):
724 def validate(self):
725 super().validate()
728class MakeWarpTask(MakeCoaddTempExpTask):
729 """Warp and optionally PSF-Match calexps onto an a common projection
730 """
731 ConfigClass = MakeWarpConfig
732 _DefaultName = "makeWarp"
734 @utils.inheritDoc(pipeBase.PipelineTask)
735 def runQuantum(self, butlerQC, inputRefs, outputRefs):
736 """
737 Notes
738 ----
739 Construct warps for requested warp type for single epoch
741 PipelineTask (Gen3) entry point to warp and optionally PSF-match
742 calexps. This method is analogous to `runDataRef`.
743 """
745 # Ensure all input lists are in same detector order as the calExpList
746 detectorOrder = [ref.datasetRef.dataId['detector'] for ref in inputRefs.calExpList]
747 inputRefs = reorderRefs(inputRefs, detectorOrder, dataIdKey='detector')
749 # Read in all inputs.
750 inputs = butlerQC.get(inputRefs)
752 # Construct skyInfo expected by `run`. We remove the SkyMap itself
753 # from the dictionary so we can pass it as kwargs later.
754 skyMap = inputs.pop("skyMap")
755 quantumDataId = butlerQC.quantum.dataId
756 skyInfo = makeSkyInfo(skyMap, tractId=quantumDataId['tract'], patchId=quantumDataId['patch'])
758 # Construct list of input DataIds expected by `run`
759 dataIdList = [ref.datasetRef.dataId for ref in inputRefs.calExpList]
760 # Construct list of packed integer IDs expected by `run`
761 ccdIdList = [dataId.pack("visit_detector") for dataId in dataIdList]
763 # Run the selector and filter out calexps that were not selected
764 # primarily because they do not overlap the patch
765 cornerPosList = lsst.geom.Box2D(skyInfo.bbox).getCorners()
766 coordList = [skyInfo.wcs.pixelToSky(pos) for pos in cornerPosList]
767 goodIndices = self.select.run(**inputs, coordList=coordList, dataIds=dataIdList)
768 inputs = self.filterInputs(indices=goodIndices, inputs=inputs)
770 # Read from disk only the selected calexps
771 inputs['calExpList'] = [ref.get() for ref in inputs['calExpList']]
773 # Extract integer visitId requested by `run`
774 visits = [dataId['visit'] for dataId in dataIdList]
775 visitId = visits[0]
777 if self.config.doApplyExternalSkyWcs:
778 if self.config.useGlobalExternalSkyWcs:
779 externalSkyWcsCatalog = inputs.pop("externalSkyWcsGlobalCatalog")
780 else:
781 externalSkyWcsCatalog = inputs.pop("externalSkyWcsTractCatalog")
782 else:
783 externalSkyWcsCatalog = None
785 if self.config.doApplyExternalPhotoCalib:
786 if self.config.useGlobalExternalPhotoCalib:
787 externalPhotoCalibCatalog = inputs.pop("externalPhotoCalibGlobalCatalog")
788 else:
789 externalPhotoCalibCatalog = inputs.pop("externalPhotoCalibTractCatalog")
790 else:
791 externalPhotoCalibCatalog = None
793 completeIndices = self.prepareCalibratedExposures(**inputs,
794 externalSkyWcsCatalog=externalSkyWcsCatalog,
795 externalPhotoCalibCatalog=externalPhotoCalibCatalog)
796 # Redo the input selection with inputs with complete wcs/photocalib info.
797 inputs = self.filterInputs(indices=completeIndices, inputs=inputs)
799 results = self.run(**inputs, visitId=visitId,
800 ccdIdList=[ccdIdList[i] for i in goodIndices],
801 dataIdList=[dataIdList[i] for i in goodIndices],
802 skyInfo=skyInfo)
803 if self.config.makeDirect and results.exposures["direct"] is not None:
804 butlerQC.put(results.exposures["direct"], outputRefs.direct)
805 if self.config.makePsfMatched and results.exposures["psfMatched"] is not None:
806 butlerQC.put(results.exposures["psfMatched"], outputRefs.psfMatched)
808 def filterInputs(self, indices, inputs):
809 """Return task inputs with their lists filtered by indices
811 Parameters
812 ----------
813 indices : `list` of integers
814 inputs : `dict` of `list` of input connections to be passed to run
815 """
816 for key in inputs.keys():
817 # Only down-select on list inputs
818 if isinstance(inputs[key], list):
819 inputs[key] = [inputs[key][ind] for ind in indices]
820 return inputs
822 def prepareCalibratedExposures(self, calExpList, backgroundList=None, skyCorrList=None,
823 externalSkyWcsCatalog=None, externalPhotoCalibCatalog=None,
824 **kwargs):
825 """Calibrate and add backgrounds to input calExpList in place
827 Parameters
828 ----------
829 calExpList : `list` of `lsst.afw.image.Exposure`
830 Sequence of calexps to be modified in place
831 backgroundList : `list` of `lsst.afw.math.backgroundList`, optional
832 Sequence of backgrounds to be added back in if bgSubtracted=False
833 skyCorrList : `list` of `lsst.afw.math.backgroundList`, optional
834 Sequence of background corrections to be subtracted if doApplySkyCorr=True
835 externalSkyWcsCatalog : `lsst.afw.table.ExposureCatalog`, optional
836 Exposure catalog with external skyWcs to be applied
837 if config.doApplyExternalSkyWcs=True. Catalog uses the detector id
838 for the catalog id, sorted on id for fast lookup.
839 externalPhotoCalibCatalog : `lsst.afw.table.ExposureCatalog`, optional
840 Exposure catalog with external photoCalib to be applied
841 if config.doApplyExternalPhotoCalib=True. Catalog uses the detector
842 id for the catalog id, sorted on id for fast lookup.
844 Returns
845 -------
846 indices : `list` [`int`]
847 Indices of calExpList and friends that have valid photoCalib/skyWcs
848 """
849 backgroundList = len(calExpList)*[None] if backgroundList is None else backgroundList
850 skyCorrList = len(calExpList)*[None] if skyCorrList is None else skyCorrList
852 includeCalibVar = self.config.includeCalibVar
854 indices = []
855 for index, (calexp, background, skyCorr) in enumerate(zip(calExpList,
856 backgroundList,
857 skyCorrList)):
858 mi = calexp.maskedImage
859 if not self.config.bgSubtracted:
860 mi += background.getImage()
862 if externalSkyWcsCatalog is not None or externalPhotoCalibCatalog is not None:
863 detectorId = calexp.getInfo().getDetector().getId()
865 # Find the external photoCalib
866 if externalPhotoCalibCatalog is not None:
867 row = externalPhotoCalibCatalog.find(detectorId)
868 if row is None:
869 self.log.warning("Detector id %s not found in externalPhotoCalibCatalog "
870 "and will not be used in the warp.", detectorId)
871 continue
872 photoCalib = row.getPhotoCalib()
873 if photoCalib is None:
874 self.log.warning("Detector id %s has None for photoCalib in externalPhotoCalibCatalog "
875 "and will not be used in the warp.", detectorId)
876 continue
877 calexp.setPhotoCalib(photoCalib)
878 else:
879 photoCalib = calexp.getPhotoCalib()
880 if photoCalib is None:
881 self.log.warning("Detector id %s has None for photoCalib in the calexp "
882 "and will not be used in the warp.", detectorId)
883 continue
885 # Find and apply external skyWcs
886 if externalSkyWcsCatalog is not None:
887 row = externalSkyWcsCatalog.find(detectorId)
888 if row is None:
889 self.log.warning("Detector id %s not found in externalSkyWcsCatalog "
890 "and will not be used in the warp.", detectorId)
891 continue
892 skyWcs = row.getWcs()
893 if skyWcs is None:
894 self.log.warning("Detector id %s has None for skyWcs in externalSkyWcsCatalog "
895 "and will not be used in the warp.", detectorId)
896 continue
897 calexp.setWcs(skyWcs)
898 else:
899 skyWcs = calexp.getWcs()
900 if skyWcs is None:
901 self.log.warning("Detector id %s has None for skyWcs in the calexp "
902 "and will not be used in the warp.", detectorId)
903 continue
905 # Calibrate the image
906 calexp.maskedImage = photoCalib.calibrateImage(calexp.maskedImage,
907 includeScaleUncertainty=includeCalibVar)
908 calexp.maskedImage /= photoCalib.getCalibrationMean()
909 # TODO: The images will have a calibration of 1.0 everywhere once RFC-545 is implemented.
910 # exposure.setCalib(afwImage.Calib(1.0))
912 # Apply skycorr
913 if self.config.doApplySkyCorr:
914 mi -= skyCorr.getImage()
916 indices.append(index)
918 return indices
921def reorderRefs(inputRefs, outputSortKeyOrder, dataIdKey):
922 """Reorder inputRefs per outputSortKeyOrder
924 Any inputRefs which are lists will be resorted per specified key e.g.,
925 'detector.' Only iterables will be reordered, and values can be of type
926 `lsst.pipe.base.connections.DeferredDatasetRef` or
927 `lsst.daf.butler.core.datasets.ref.DatasetRef`.
928 Returned lists of refs have the same length as the outputSortKeyOrder.
929 If an outputSortKey not in the inputRef, then it will be padded with None.
930 If an inputRef contains an inputSortKey that is not in the
931 outputSortKeyOrder it will be removed.
933 Parameters
934 ----------
935 inputRefs : `lsst.pipe.base.connections.QuantizedConnection`
936 Input references to be reordered and padded.
937 outputSortKeyOrder : iterable
938 Iterable of values to be compared with inputRef's dataId[dataIdKey]
939 dataIdKey : `str`
940 dataIdKey in the dataRefs to compare with the outputSortKeyOrder.
942 Returns:
943 --------
944 inputRefs: `lsst.pipe.base.connections.QuantizedConnection`
945 Quantized Connection with sorted DatasetRef values sorted if iterable.
946 """
947 for connectionName, refs in inputRefs:
948 if isinstance(refs, Iterable):
949 if hasattr(refs[0], "dataId"):
950 inputSortKeyOrder = [ref.dataId[dataIdKey] for ref in refs]
951 else:
952 inputSortKeyOrder = [ref.datasetRef.dataId[dataIdKey] for ref in refs]
953 if inputSortKeyOrder != outputSortKeyOrder:
954 setattr(inputRefs, connectionName,
955 reorderAndPadList(refs, inputSortKeyOrder, outputSortKeyOrder))
956 return inputRefs