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
23import logging
25import lsst.pex.config as pexConfig
26import lsst.daf.persistence as dafPersist
27import lsst.afw.image as afwImage
28import lsst.coadd.utils as coaddUtils
29import lsst.pipe.base as pipeBase
30import lsst.pipe.base.connectionTypes as connectionTypes
31import lsst.utils as utils
32import lsst.geom
33from lsst.meas.algorithms import CoaddPsf, CoaddPsfConfig
34from lsst.skymap import BaseSkyMap
35from lsst.utils.timer import timeMethod
36from .coaddBase import CoaddBaseTask, makeSkyInfo, reorderAndPadList
37from .warpAndPsfMatch import WarpAndPsfMatchTask
38from .coaddHelpers import groupPatchExposures, getGroupDataRef
39from collections.abc import Iterable
41__all__ = ["MakeCoaddTempExpTask", "MakeWarpTask", "MakeWarpConfig"]
43log = logging.getLogger(__name__)
46class MissingExposureError(Exception):
47 """Raised when data cannot be retrieved for an exposure.
48 When processing patches, sometimes one exposure is missing; this lets us
49 distinguish bewteen that case, and other errors.
50 """
51 pass
54class MakeCoaddTempExpConfig(CoaddBaseTask.ConfigClass):
55 """Config for MakeCoaddTempExpTask
56 """
57 warpAndPsfMatch = pexConfig.ConfigurableField(
58 target=WarpAndPsfMatchTask,
59 doc="Task to warp and PSF-match calexp",
60 )
61 doWrite = pexConfig.Field(
62 doc="persist <coaddName>Coadd_<warpType>Warp",
63 dtype=bool,
64 default=True,
65 )
66 bgSubtracted = pexConfig.Field(
67 doc="Work with a background subtracted calexp?",
68 dtype=bool,
69 default=True,
70 )
71 coaddPsf = pexConfig.ConfigField(
72 doc="Configuration for CoaddPsf",
73 dtype=CoaddPsfConfig,
74 )
75 makeDirect = pexConfig.Field(
76 doc="Make direct Warp/Coadds",
77 dtype=bool,
78 default=True,
79 )
80 makePsfMatched = pexConfig.Field(
81 doc="Make Psf-Matched Warp/Coadd?",
82 dtype=bool,
83 default=False,
84 )
86 doWriteEmptyWarps = pexConfig.Field(
87 dtype=bool,
88 default=False,
89 doc="Write out warps even if they are empty"
90 )
92 hasFakes = pexConfig.Field(
93 doc="Should be set to True if fake sources have been inserted into the input data.",
94 dtype=bool,
95 default=False,
96 )
97 doApplySkyCorr = pexConfig.Field(dtype=bool, default=False, doc="Apply sky correction?")
99 def validate(self):
100 CoaddBaseTask.ConfigClass.validate(self)
101 if not self.makePsfMatched and not self.makeDirect:
102 raise RuntimeError("At least one of config.makePsfMatched and config.makeDirect must be True")
103 if self.doPsfMatch:
104 # Backwards compatibility.
105 log.warning("Config doPsfMatch deprecated. Setting makePsfMatched=True and makeDirect=False")
106 self.makePsfMatched = True
107 self.makeDirect = False
109 def setDefaults(self):
110 CoaddBaseTask.ConfigClass.setDefaults(self)
111 self.warpAndPsfMatch.psfMatch.kernel.active.kernelSize = self.matchingKernelSize
113## \addtogroup LSST_task_documentation
114## \{
115## \page MakeCoaddTempExpTask
116## \ref MakeCoaddTempExpTask_ "MakeCoaddTempExpTask"
117## \copybrief MakeCoaddTempExpTask
118## \}
121class MakeCoaddTempExpTask(CoaddBaseTask):
122 r"""!Warp and optionally PSF-Match calexps onto an a common projection.
124 @anchor MakeCoaddTempExpTask_
126 @section pipe_tasks_makeCoaddTempExp_Contents Contents
128 - @ref pipe_tasks_makeCoaddTempExp_Purpose
129 - @ref pipe_tasks_makeCoaddTempExp_Initialize
130 - @ref pipe_tasks_makeCoaddTempExp_IO
131 - @ref pipe_tasks_makeCoaddTempExp_Config
132 - @ref pipe_tasks_makeCoaddTempExp_Debug
133 - @ref pipe_tasks_makeCoaddTempExp_Example
135 @section pipe_tasks_makeCoaddTempExp_Purpose Description
137 Warp and optionally PSF-Match calexps onto a common projection, by
138 performing the following operations:
139 - Group calexps by visit/run
140 - For each visit, generate a Warp by calling method @ref makeTempExp.
141 makeTempExp loops over the visit's calexps calling @ref WarpAndPsfMatch
142 on each visit
144 The result is a `directWarp` (and/or optionally a `psfMatchedWarp`).
146 @section pipe_tasks_makeCoaddTempExp_Initialize Task Initialization
148 @copydoc \_\_init\_\_
150 This task has one special keyword argument: passing reuse=True will cause
151 the task to skip the creation of warps that are already present in the
152 output repositories.
154 @section pipe_tasks_makeCoaddTempExp_IO Invoking the Task
156 This task is primarily designed to be run from the command line.
158 The main method is `runDataRef`, which takes a single butler data reference for the patch(es)
159 to process.
161 @copydoc run
163 WarpType identifies the types of convolutions applied to Warps (previously CoaddTempExps).
164 Only two types are available: direct (for regular Warps/Coadds) and psfMatched
165 (for Warps/Coadds with homogenized PSFs). We expect to add a third type, likelihood,
166 for generating likelihood Coadds with Warps that have been correlated with their own PSF.
168 @section pipe_tasks_makeCoaddTempExp_Config Configuration parameters
170 See @ref MakeCoaddTempExpConfig and parameters inherited from
171 @link lsst.pipe.tasks.coaddBase.CoaddBaseConfig CoaddBaseConfig @endlink
173 @subsection pipe_tasks_MakeCoaddTempExp_psfMatching Guide to PSF-Matching Configs
175 To make `psfMatchedWarps`, select `config.makePsfMatched=True`. The subtask
176 @link lsst.ip.diffim.modelPsfMatch.ModelPsfMatchTask ModelPsfMatchTask @endlink
177 is responsible for the PSF-Matching, and its config is accessed via `config.warpAndPsfMatch.psfMatch`.
178 The optimal configuration depends on aspects of dataset: the pixel scale, average PSF FWHM and
179 dimensions of the PSF kernel. These configs include the requested model PSF, the matching kernel size,
180 padding of the science PSF thumbnail and spatial sampling frequency of the PSF.
182 *Config Guidelines*: The user must specify the size of the model PSF to which to match by setting
183 `config.modelPsf.defaultFwhm` in units of pixels. The appropriate values depends on science case.
184 In general, for a set of input images, this config should equal the FWHM of the visit
185 with the worst seeing. The smallest it should be set to is the median FWHM. The defaults
186 of the other config options offer a reasonable starting point.
187 The following list presents the most common problems that arise from a misconfigured
188 @link lsst.ip.diffim.modelPsfMatch.ModelPsfMatchTask ModelPsfMatchTask @endlink
189 and corresponding solutions. All assume the default Alard-Lupton kernel, with configs accessed via
190 ```config.warpAndPsfMatch.psfMatch.kernel['AL']```. Each item in the list is formatted as:
191 Problem: Explanation. *Solution*
193 *Troublshooting PSF-Matching Configuration:*
194 - Matched PSFs look boxy: The matching kernel is too small. _Increase the matching kernel size.
195 For example:_
197 config.warpAndPsfMatch.psfMatch.kernel['AL'].kernelSize=27 # default 21
199 Note that increasing the kernel size also increases runtime.
200 - Matched PSFs look ugly (dipoles, quadropoles, donuts): unable to find good solution
201 for matching kernel. _Provide the matcher with more data by either increasing
202 the spatial sampling by decreasing the spatial cell size,_
204 config.warpAndPsfMatch.psfMatch.kernel['AL'].sizeCellX = 64 # default 128
205 config.warpAndPsfMatch.psfMatch.kernel['AL'].sizeCellY = 64 # default 128
207 _or increasing the padding around the Science PSF, for example:_
209 config.warpAndPsfMatch.psfMatch.autoPadPsfTo=1.6 # default 1.4
211 Increasing `autoPadPsfTo` increases the minimum ratio of input PSF dimensions to the
212 matching kernel dimensions, thus increasing the number of pixels available to fit
213 after convolving the PSF with the matching kernel.
214 Optionally, for debugging the effects of padding, the level of padding may be manually
215 controlled by setting turning off the automatic padding and setting the number
216 of pixels by which to pad the PSF:
218 config.warpAndPsfMatch.psfMatch.doAutoPadPsf = False # default True
219 config.warpAndPsfMatch.psfMatch.padPsfBy = 6 # pixels. default 0
221 - Deconvolution: Matching a large PSF to a smaller PSF produces
222 a telltale noise pattern which looks like ripples or a brain.
223 _Increase the size of the requested model PSF. For example:_
225 config.modelPsf.defaultFwhm = 11 # Gaussian sigma in units of pixels.
227 - High frequency (sometimes checkered) noise: The matching basis functions are too small.
228 _Increase the width of the Gaussian basis functions. For example:_
230 config.warpAndPsfMatch.psfMatch.kernel['AL'].alardSigGauss=[1.5, 3.0, 6.0]
231 # from default [0.7, 1.5, 3.0]
234 @section pipe_tasks_makeCoaddTempExp_Debug Debug variables
236 MakeCoaddTempExpTask has no debug output, but its subtasks do.
238 @section pipe_tasks_makeCoaddTempExp_Example A complete example of using MakeCoaddTempExpTask
240 This example uses the package ci_hsc to show how MakeCoaddTempExp fits
241 into the larger Data Release Processing.
242 Set up by running:
244 setup ci_hsc
245 cd $CI_HSC_DIR
246 # if not built already:
247 python $(which scons) # this will take a while
249 The following assumes that `processCcd.py` and `makeSkyMap.py` have previously been run
250 (e.g. by building `ci_hsc` above) to generate a repository of calexps and an
251 output respository with the desired SkyMap. The command,
253 makeCoaddTempExp.py $CI_HSC_DIR/DATA --rerun ci_hsc \
254 --id patch=5,4 tract=0 filter=HSC-I \
255 --selectId visit=903988 ccd=16 --selectId visit=903988 ccd=17 \
256 --selectId visit=903988 ccd=23 --selectId visit=903988 ccd=24 \
257 --config doApplyExternalPhotoCalib=False doApplyExternalSkyWcs=False \
258 makePsfMatched=True modelPsf.defaultFwhm=11
260 writes a direct and PSF-Matched Warp to
261 - `$CI_HSC_DIR/DATA/rerun/ci_hsc/deepCoadd/HSC-I/0/5,4/warp-HSC-I-0-5,4-903988.fits` and
262 - `$CI_HSC_DIR/DATA/rerun/ci_hsc/deepCoadd/HSC-I/0/5,4/psfMatchedWarp-HSC-I-0-5,4-903988.fits`
263 respectively.
265 @note PSF-Matching in this particular dataset would benefit from adding
266 `--configfile ./matchingConfig.py` to
267 the command line arguments where `matchingConfig.py` is defined by:
269 echo "
270 config.warpAndPsfMatch.psfMatch.kernel['AL'].kernelSize=27
271 config.warpAndPsfMatch.psfMatch.kernel['AL'].alardSigGauss=[1.5, 3.0, 6.0]" > matchingConfig.py
274 Add the option `--help` to see more options.
275 """
276 ConfigClass = MakeCoaddTempExpConfig
277 _DefaultName = "makeCoaddTempExp"
279 def __init__(self, reuse=False, **kwargs):
280 CoaddBaseTask.__init__(self, **kwargs)
281 self.reuse = reuse
282 self.makeSubtask("warpAndPsfMatch")
283 if self.config.hasFakes: 283 ↛ 284line 283 didn't jump to line 284, because the condition on line 283 was never true
284 self.calexpType = "fakes_calexp"
285 else:
286 self.calexpType = "calexp"
288 @timeMethod
289 def runDataRef(self, patchRef, selectDataList=[]):
290 """!Produce <coaddName>Coadd_<warpType>Warp images by warping and optionally PSF-matching.
292 @param[in] patchRef: data reference for sky map patch. Must include keys "tract", "patch",
293 plus the camera-specific filter key (e.g. "filter" or "band")
294 @return: dataRefList: a list of data references for the new <coaddName>Coadd_directWarps
295 if direct or both warp types are requested and <coaddName>Coadd_psfMatchedWarps if only psfMatched
296 warps are requested.
298 @warning: this task assumes that all exposures in a warp (coaddTempExp) have the same filter.
300 @warning: this task sets the PhotoCalib of the coaddTempExp to the PhotoCalib of the first calexp
301 with any good pixels in the patch. For a mosaic camera the resulting PhotoCalib should be ignored
302 (assembleCoadd should determine zeropoint scaling without referring to it).
303 """
304 skyInfo = self.getSkyInfo(patchRef)
306 # DataRefs to return are of type *_directWarp unless only *_psfMatchedWarp requested
307 if self.config.makePsfMatched and not self.config.makeDirect: 307 ↛ 308line 307 didn't jump to line 308, because the condition on line 307 was never true
308 primaryWarpDataset = self.getTempExpDatasetName("psfMatched")
309 else:
310 primaryWarpDataset = self.getTempExpDatasetName("direct")
312 calExpRefList = self.selectExposures(patchRef, skyInfo, selectDataList=selectDataList)
314 if len(calExpRefList) == 0: 314 ↛ 315line 314 didn't jump to line 315, because the condition on line 314 was never true
315 self.log.warning("No exposures to coadd for patch %s", patchRef.dataId)
316 return None
317 self.log.info("Selected %d calexps for patch %s", len(calExpRefList), patchRef.dataId)
318 calExpRefList = [calExpRef for calExpRef in calExpRefList if calExpRef.datasetExists(self.calexpType)]
319 self.log.info("Processing %d existing calexps for patch %s", len(calExpRefList), patchRef.dataId)
321 groupData = groupPatchExposures(patchRef, calExpRefList, self.getCoaddDatasetName(),
322 primaryWarpDataset)
323 self.log.info("Processing %d warp exposures for patch %s", len(groupData.groups), patchRef.dataId)
325 dataRefList = []
326 for i, (tempExpTuple, calexpRefList) in enumerate(groupData.groups.items()):
327 tempExpRef = getGroupDataRef(patchRef.getButler(), primaryWarpDataset,
328 tempExpTuple, groupData.keys)
329 if self.reuse and tempExpRef.datasetExists(datasetType=primaryWarpDataset, write=True): 329 ↛ 330line 329 didn't jump to line 330, because the condition on line 329 was never true
330 self.log.info("Skipping makeCoaddTempExp for %s; output already exists.", tempExpRef.dataId)
331 dataRefList.append(tempExpRef)
332 continue
333 self.log.info("Processing Warp %d/%d: id=%s", i, len(groupData.groups), tempExpRef.dataId)
335 # TODO: mappers should define a way to go from the "grouping keys" to a numeric ID (#2776).
336 # For now, we try to get a long integer "visit" key, and if we can't, we just use the index
337 # of the visit in the list.
338 try:
339 visitId = int(tempExpRef.dataId["visit"])
340 except (KeyError, ValueError):
341 visitId = i
343 calExpList = []
344 ccdIdList = []
345 dataIdList = []
347 for calExpInd, calExpRef in enumerate(calexpRefList):
348 self.log.info("Reading calexp %s of %s for Warp id=%s", calExpInd+1, len(calexpRefList),
349 calExpRef.dataId)
350 try:
351 ccdId = calExpRef.get("ccdExposureId", immediate=True)
352 except Exception:
353 ccdId = calExpInd
354 try:
355 # We augment the dataRef here with the tract, which is harmless for loading things
356 # like calexps that don't need the tract, and necessary for meas_mosaic outputs,
357 # which do.
358 calExpRef = calExpRef.butlerSubset.butler.dataRef(self.calexpType,
359 dataId=calExpRef.dataId,
360 tract=skyInfo.tractInfo.getId())
361 calExp = self.getCalibratedExposure(calExpRef, bgSubtracted=self.config.bgSubtracted)
362 except Exception as e:
363 self.log.warning("Calexp %s not found; skipping it: %s", calExpRef.dataId, e)
364 continue
366 if self.config.doApplySkyCorr: 366 ↛ 367line 366 didn't jump to line 367, because the condition on line 366 was never true
367 self.applySkyCorr(calExpRef, calExp)
369 calExpList.append(calExp)
370 ccdIdList.append(ccdId)
371 dataIdList.append(calExpRef.dataId)
373 exps = self.run(calExpList, ccdIdList, skyInfo, visitId, dataIdList).exposures
375 if any(exps.values()):
376 dataRefList.append(tempExpRef)
377 else:
378 self.log.warning("Warp %s could not be created", tempExpRef.dataId)
380 if self.config.doWrite: 380 ↛ 326line 380 didn't jump to line 326, because the condition on line 380 was never false
381 for (warpType, exposure) in exps.items(): # compatible w/ Py3
382 if exposure is not None:
383 self.log.info("Persisting %s", self.getTempExpDatasetName(warpType))
384 tempExpRef.put(exposure, self.getTempExpDatasetName(warpType))
386 return dataRefList
388 @timeMethod
389 def run(self, calExpList, ccdIdList, skyInfo, visitId=0, dataIdList=None, **kwargs):
390 """Create a Warp from inputs
392 We iterate over the multiple calexps in a single exposure to construct
393 the warp (previously called a coaddTempExp) of that exposure to the
394 supplied tract/patch.
396 Pixels that receive no pixels are set to NAN; this is not correct
397 (violates LSST algorithms group policy), but will be fixed up by
398 interpolating after the coaddition.
400 @param calexpRefList: List of data references for calexps that (may)
401 overlap the patch of interest
402 @param skyInfo: Struct from CoaddBaseTask.getSkyInfo() with geometric
403 information about the patch
404 @param visitId: integer identifier for visit, for the table that will
405 produce the CoaddPsf
406 @return a pipeBase Struct containing:
407 - exposures: a dictionary containing the warps requested:
408 "direct": direct warp if config.makeDirect
409 "psfMatched": PSF-matched warp if config.makePsfMatched
410 """
411 warpTypeList = self.getWarpTypeList()
413 totGoodPix = {warpType: 0 for warpType in warpTypeList}
414 didSetMetadata = {warpType: False for warpType in warpTypeList}
415 coaddTempExps = {warpType: self._prepareEmptyExposure(skyInfo) for warpType in warpTypeList}
416 inputRecorder = {warpType: self.inputRecorder.makeCoaddTempExpRecorder(visitId, len(calExpList))
417 for warpType in warpTypeList}
419 modelPsf = self.config.modelPsf.apply() if self.config.makePsfMatched else None
420 if dataIdList is None: 420 ↛ 421line 420 didn't jump to line 421, because the condition on line 420 was never true
421 dataIdList = ccdIdList
423 for calExpInd, (calExp, ccdId, dataId) in enumerate(zip(calExpList, ccdIdList, dataIdList)):
424 self.log.info("Processing calexp %d of %d for this Warp: id=%s",
425 calExpInd+1, len(calExpList), dataId)
427 try:
428 warpedAndMatched = self.warpAndPsfMatch.run(calExp, modelPsf=modelPsf,
429 wcs=skyInfo.wcs, maxBBox=skyInfo.bbox,
430 makeDirect=self.config.makeDirect,
431 makePsfMatched=self.config.makePsfMatched)
432 except Exception as e:
433 self.log.warning("WarpAndPsfMatch failed for calexp %s; skipping it: %s", dataId, e)
434 continue
435 try:
436 numGoodPix = {warpType: 0 for warpType in warpTypeList}
437 for warpType in warpTypeList:
438 exposure = warpedAndMatched.getDict()[warpType]
439 if exposure is None:
440 continue
441 coaddTempExp = coaddTempExps[warpType]
442 if didSetMetadata[warpType]:
443 mimg = exposure.getMaskedImage()
444 mimg *= (coaddTempExp.getPhotoCalib().getInstFluxAtZeroMagnitude()
445 / exposure.getPhotoCalib().getInstFluxAtZeroMagnitude())
446 del mimg
447 numGoodPix[warpType] = coaddUtils.copyGoodPixels(
448 coaddTempExp.getMaskedImage(), exposure.getMaskedImage(), self.getBadPixelMask())
449 totGoodPix[warpType] += numGoodPix[warpType]
450 self.log.debug("Calexp %s has %d good pixels in this patch (%.1f%%) for %s",
451 dataId, numGoodPix[warpType],
452 100.0*numGoodPix[warpType]/skyInfo.bbox.getArea(), warpType)
453 if numGoodPix[warpType] > 0 and not didSetMetadata[warpType]:
454 coaddTempExp.info.id = exposure.info.id
455 coaddTempExp.setPhotoCalib(exposure.getPhotoCalib())
456 coaddTempExp.setFilterLabel(exposure.getFilterLabel())
457 coaddTempExp.getInfo().setVisitInfo(exposure.getInfo().getVisitInfo())
458 # PSF replaced with CoaddPsf after loop if and only if creating direct warp
459 coaddTempExp.setPsf(exposure.getPsf())
460 didSetMetadata[warpType] = True
462 # Need inputRecorder for CoaddApCorrMap for both direct and PSF-matched
463 inputRecorder[warpType].addCalExp(calExp, ccdId, numGoodPix[warpType])
465 except Exception as e:
466 self.log.warning("Error processing calexp %s; skipping it: %s", dataId, e)
467 continue
469 for warpType in warpTypeList:
470 self.log.info("%sWarp has %d good pixels (%.1f%%)",
471 warpType, totGoodPix[warpType], 100.0*totGoodPix[warpType]/skyInfo.bbox.getArea())
473 if totGoodPix[warpType] > 0 and didSetMetadata[warpType]:
474 inputRecorder[warpType].finish(coaddTempExps[warpType], totGoodPix[warpType])
475 if warpType == "direct":
476 coaddTempExps[warpType].setPsf(
477 CoaddPsf(inputRecorder[warpType].coaddInputs.ccds, skyInfo.wcs,
478 self.config.coaddPsf.makeControl()))
479 else:
480 if not self.config.doWriteEmptyWarps: 480 ↛ 469line 480 didn't jump to line 469, because the condition on line 480 was never false
481 # No good pixels. Exposure still empty
482 coaddTempExps[warpType] = None
483 # NoWorkFound is unnecessary as the downstream tasks will
484 # adjust the quantum accordingly, and it prevents gen2
485 # MakeCoaddTempExp from continuing to loop over visits.
487 result = pipeBase.Struct(exposures=coaddTempExps)
488 return result
490 def getCalibratedExposure(self, dataRef, bgSubtracted):
491 """Return one calibrated Exposure, possibly with an updated SkyWcs.
493 @param[in] dataRef a sensor-level data reference
494 @param[in] bgSubtracted return calexp with background subtracted? If False get the
495 calexp's background background model and add it to the calexp.
496 @return calibrated exposure
498 @raises MissingExposureError If data for the exposure is not available.
500 If config.doApplyExternalPhotoCalib is `True`, the photometric calibration
501 (`photoCalib`) is taken from `config.externalPhotoCalibName` via the
502 `name_photoCalib` dataset. Otherwise, the photometric calibration is
503 retrieved from the processed exposure. When
504 `config.doApplyExternalSkyWcs` is `True`, the astrometric calibration
505 is taken from `config.externalSkyWcsName` with the `name_wcs` dataset.
506 Otherwise, the astrometric calibration is taken from the processed
507 exposure.
508 """
509 try:
510 exposure = dataRef.get(self.calexpType, immediate=True)
511 except dafPersist.NoResults as e:
512 raise MissingExposureError('Exposure not found: %s ' % str(e)) from e
514 if not bgSubtracted: 514 ↛ 515line 514 didn't jump to line 515, because the condition on line 514 was never true
515 background = dataRef.get("calexpBackground", immediate=True)
516 mi = exposure.getMaskedImage()
517 mi += background.getImage()
518 del mi
520 if self.config.doApplyExternalPhotoCalib: 520 ↛ 521line 520 didn't jump to line 521, because the condition on line 520 was never true
521 source = f"{self.config.externalPhotoCalibName}_photoCalib"
522 self.log.debug("Applying external photoCalib to %s from %s", dataRef.dataId, source)
523 photoCalib = dataRef.get(source)
524 exposure.setPhotoCalib(photoCalib)
525 else:
526 photoCalib = exposure.getPhotoCalib()
528 if self.config.doApplyExternalSkyWcs: 528 ↛ 529line 528 didn't jump to line 529, because the condition on line 528 was never true
529 source = f"{self.config.externalSkyWcsName}_wcs"
530 self.log.debug("Applying external skyWcs to %s from %s", dataRef.dataId, source)
531 skyWcs = dataRef.get(source)
532 exposure.setWcs(skyWcs)
534 exposure.maskedImage = photoCalib.calibrateImage(exposure.maskedImage,
535 includeScaleUncertainty=self.config.includeCalibVar)
536 exposure.maskedImage /= photoCalib.getCalibrationMean()
537 # TODO: The images will have a calibration of 1.0 everywhere once RFC-545 is implemented.
538 # exposure.setCalib(afwImage.Calib(1.0))
539 return exposure
541 @staticmethod
542 def _prepareEmptyExposure(skyInfo):
543 """Produce an empty exposure for a given patch"""
544 exp = afwImage.ExposureF(skyInfo.bbox, skyInfo.wcs)
545 exp.getMaskedImage().set(numpy.nan, afwImage.Mask
546 .getPlaneBitMask("NO_DATA"), numpy.inf)
547 return exp
549 def getWarpTypeList(self):
550 """Return list of requested warp types per the config.
551 """
552 warpTypeList = []
553 if self.config.makeDirect: 553 ↛ 555line 553 didn't jump to line 555, because the condition on line 553 was never false
554 warpTypeList.append("direct")
555 if self.config.makePsfMatched: 555 ↛ 557line 555 didn't jump to line 557, because the condition on line 555 was never false
556 warpTypeList.append("psfMatched")
557 return warpTypeList
559 def applySkyCorr(self, dataRef, calexp):
560 """Apply correction to the sky background level
562 Sky corrections can be generated with the 'skyCorrection.py'
563 executable in pipe_drivers. Because the sky model used by that
564 code extends over the entire focal plane, this can produce
565 better sky subtraction.
567 The calexp is updated in-place.
569 Parameters
570 ----------
571 dataRef : `lsst.daf.persistence.ButlerDataRef`
572 Data reference for calexp.
573 calexp : `lsst.afw.image.Exposure` or `lsst.afw.image.MaskedImage`
574 Calibrated exposure.
575 """
576 bg = dataRef.get("skyCorr")
577 self.log.debug("Applying sky correction to %s", dataRef.dataId)
578 if isinstance(calexp, afwImage.Exposure):
579 calexp = calexp.getMaskedImage()
580 calexp -= bg.getImage()
583class MakeWarpConnections(pipeBase.PipelineTaskConnections,
584 dimensions=("tract", "patch", "skymap", "instrument", "visit"),
585 defaultTemplates={"coaddName": "deep",
586 "skyWcsName": "jointcal",
587 "photoCalibName": "fgcm",
588 "calexpType": ""}):
589 calExpList = connectionTypes.Input(
590 doc="Input exposures to be resampled and optionally PSF-matched onto a SkyMap projection/patch",
591 name="{calexpType}calexp",
592 storageClass="ExposureF",
593 dimensions=("instrument", "visit", "detector"),
594 multiple=True,
595 deferLoad=True,
596 )
597 backgroundList = connectionTypes.Input(
598 doc="Input backgrounds to be added back into the calexp if bgSubtracted=False",
599 name="calexpBackground",
600 storageClass="Background",
601 dimensions=("instrument", "visit", "detector"),
602 multiple=True,
603 )
604 skyCorrList = connectionTypes.Input(
605 doc="Input Sky Correction to be subtracted from the calexp if doApplySkyCorr=True",
606 name="skyCorr",
607 storageClass="Background",
608 dimensions=("instrument", "visit", "detector"),
609 multiple=True,
610 )
611 skyMap = connectionTypes.Input(
612 doc="Input definition of geometry/bbox and projection/wcs for warped exposures",
613 name=BaseSkyMap.SKYMAP_DATASET_TYPE_NAME,
614 storageClass="SkyMap",
615 dimensions=("skymap",),
616 )
617 externalSkyWcsTractCatalog = connectionTypes.Input(
618 doc=("Per-tract, per-visit wcs calibrations. These catalogs use the detector "
619 "id for the catalog id, sorted on id for fast lookup."),
620 name="{skyWcsName}SkyWcsCatalog",
621 storageClass="ExposureCatalog",
622 dimensions=("instrument", "visit", "tract"),
623 )
624 externalSkyWcsGlobalCatalog = connectionTypes.Input(
625 doc=("Per-visit wcs calibrations computed globally (with no tract information). "
626 "These catalogs use the detector id for the catalog id, sorted on id for "
627 "fast lookup."),
628 name="{skyWcsName}SkyWcsCatalog",
629 storageClass="ExposureCatalog",
630 dimensions=("instrument", "visit"),
631 )
632 externalPhotoCalibTractCatalog = connectionTypes.Input(
633 doc=("Per-tract, per-visit photometric calibrations. These catalogs use the "
634 "detector id for the catalog id, sorted on id for fast lookup."),
635 name="{photoCalibName}PhotoCalibCatalog",
636 storageClass="ExposureCatalog",
637 dimensions=("instrument", "visit", "tract"),
638 )
639 externalPhotoCalibGlobalCatalog = connectionTypes.Input(
640 doc=("Per-visit photometric calibrations computed globally (with no tract "
641 "information). These catalogs use the detector id for the catalog id, "
642 "sorted on id for fast lookup."),
643 name="{photoCalibName}PhotoCalibCatalog",
644 storageClass="ExposureCatalog",
645 dimensions=("instrument", "visit"),
646 )
647 direct = connectionTypes.Output(
648 doc=("Output direct warped exposure (previously called CoaddTempExp), produced by resampling ",
649 "calexps onto the skyMap patch geometry."),
650 name="{coaddName}Coadd_directWarp",
651 storageClass="ExposureF",
652 dimensions=("tract", "patch", "skymap", "visit", "instrument"),
653 )
654 psfMatched = connectionTypes.Output(
655 doc=("Output PSF-Matched warped exposure (previously called CoaddTempExp), produced by resampling ",
656 "calexps onto the skyMap patch geometry and PSF-matching to a model PSF."),
657 name="{coaddName}Coadd_psfMatchedWarp",
658 storageClass="ExposureF",
659 dimensions=("tract", "patch", "skymap", "visit", "instrument"),
660 )
661 # TODO DM-28769, have selectImages subtask indicate which connections they need:
662 wcsList = connectionTypes.Input(
663 doc="WCSs of calexps used by SelectImages subtask to determine if the calexp overlaps the patch",
664 name="{calexpType}calexp.wcs",
665 storageClass="Wcs",
666 dimensions=("instrument", "visit", "detector"),
667 multiple=True,
668 )
669 bboxList = connectionTypes.Input(
670 doc="BBoxes of calexps used by SelectImages subtask to determine if the calexp overlaps the patch",
671 name="{calexpType}calexp.bbox",
672 storageClass="Box2I",
673 dimensions=("instrument", "visit", "detector"),
674 multiple=True,
675 )
676 srcList = connectionTypes.Input(
677 doc="src catalogs used by PsfWcsSelectImages subtask to further select on PSF stability",
678 name="src",
679 storageClass="SourceCatalog",
680 dimensions=("instrument", "visit", "detector"),
681 multiple=True,
682 )
683 psfList = connectionTypes.Input(
684 doc="PSF models used by BestSeeingWcsSelectImages subtask to futher select on seeing",
685 name="{calexpType}calexp.psf",
686 storageClass="Psf",
687 dimensions=("instrument", "visit", "detector"),
688 multiple=True,
689 )
691 def __init__(self, *, config=None):
692 super().__init__(config=config)
693 if config.bgSubtracted:
694 self.inputs.remove("backgroundList")
695 if not config.doApplySkyCorr:
696 self.inputs.remove("skyCorrList")
697 if config.doApplyExternalSkyWcs:
698 if config.useGlobalExternalSkyWcs:
699 self.inputs.remove("externalSkyWcsTractCatalog")
700 else:
701 self.inputs.remove("externalSkyWcsGlobalCatalog")
702 else:
703 self.inputs.remove("externalSkyWcsTractCatalog")
704 self.inputs.remove("externalSkyWcsGlobalCatalog")
705 if config.doApplyExternalPhotoCalib:
706 if config.useGlobalExternalPhotoCalib:
707 self.inputs.remove("externalPhotoCalibTractCatalog")
708 else:
709 self.inputs.remove("externalPhotoCalibGlobalCatalog")
710 else:
711 self.inputs.remove("externalPhotoCalibTractCatalog")
712 self.inputs.remove("externalPhotoCalibGlobalCatalog")
713 if not config.makeDirect:
714 self.outputs.remove("direct")
715 if not config.makePsfMatched:
716 self.outputs.remove("psfMatched")
717 # TODO DM-28769: add connection per selectImages connections
718 # instead of removing if not PsfWcsSelectImagesTask here:
719 if config.select.target != lsst.pipe.tasks.selectImages.PsfWcsSelectImagesTask:
720 self.inputs.remove("srcList")
721 if config.select.target != lsst.pipe.tasks.selectImages.BestSeeingWcsSelectImagesTask:
722 self.inputs.remove("psfList")
725class MakeWarpConfig(pipeBase.PipelineTaskConfig, MakeCoaddTempExpConfig,
726 pipelineConnections=MakeWarpConnections):
728 def validate(self):
729 super().validate()
732class MakeWarpTask(MakeCoaddTempExpTask):
733 """Warp and optionally PSF-Match calexps onto an a common projection
734 """
735 ConfigClass = MakeWarpConfig
736 _DefaultName = "makeWarp"
738 @utils.inheritDoc(pipeBase.PipelineTask)
739 def runQuantum(self, butlerQC, inputRefs, outputRefs):
740 """
741 Notes
742 ----
743 Construct warps for requested warp type for single epoch
745 PipelineTask (Gen3) entry point to warp and optionally PSF-match
746 calexps. This method is analogous to `runDataRef`.
747 """
749 # Ensure all input lists are in same detector order as the calExpList
750 detectorOrder = [ref.datasetRef.dataId['detector'] for ref in inputRefs.calExpList]
751 inputRefs = reorderRefs(inputRefs, detectorOrder, dataIdKey='detector')
753 # Read in all inputs.
754 inputs = butlerQC.get(inputRefs)
756 # Construct skyInfo expected by `run`. We remove the SkyMap itself
757 # from the dictionary so we can pass it as kwargs later.
758 skyMap = inputs.pop("skyMap")
759 quantumDataId = butlerQC.quantum.dataId
760 skyInfo = makeSkyInfo(skyMap, tractId=quantumDataId['tract'], patchId=quantumDataId['patch'])
762 # Construct list of input DataIds expected by `run`
763 dataIdList = [ref.datasetRef.dataId for ref in inputRefs.calExpList]
764 # Construct list of packed integer IDs expected by `run`
765 ccdIdList = [dataId.pack("visit_detector") for dataId in dataIdList]
767 # Run the selector and filter out calexps that were not selected
768 # primarily because they do not overlap the patch
769 cornerPosList = lsst.geom.Box2D(skyInfo.bbox).getCorners()
770 coordList = [skyInfo.wcs.pixelToSky(pos) for pos in cornerPosList]
771 goodIndices = self.select.run(**inputs, coordList=coordList, dataIds=dataIdList)
772 inputs = self.filterInputs(indices=goodIndices, inputs=inputs)
774 # Read from disk only the selected calexps
775 inputs['calExpList'] = [ref.get() for ref in inputs['calExpList']]
777 # Extract integer visitId requested by `run`
778 visits = [dataId['visit'] for dataId in dataIdList]
779 visitId = visits[0]
781 if self.config.doApplyExternalSkyWcs:
782 if self.config.useGlobalExternalSkyWcs:
783 externalSkyWcsCatalog = inputs.pop("externalSkyWcsGlobalCatalog")
784 else:
785 externalSkyWcsCatalog = inputs.pop("externalSkyWcsTractCatalog")
786 else:
787 externalSkyWcsCatalog = None
789 if self.config.doApplyExternalPhotoCalib:
790 if self.config.useGlobalExternalPhotoCalib:
791 externalPhotoCalibCatalog = inputs.pop("externalPhotoCalibGlobalCatalog")
792 else:
793 externalPhotoCalibCatalog = inputs.pop("externalPhotoCalibTractCatalog")
794 else:
795 externalPhotoCalibCatalog = None
797 completeIndices = self.prepareCalibratedExposures(**inputs,
798 externalSkyWcsCatalog=externalSkyWcsCatalog,
799 externalPhotoCalibCatalog=externalPhotoCalibCatalog)
800 # Redo the input selection with inputs with complete wcs/photocalib info.
801 inputs = self.filterInputs(indices=completeIndices, inputs=inputs)
803 results = self.run(**inputs, visitId=visitId,
804 ccdIdList=[ccdIdList[i] for i in goodIndices],
805 dataIdList=[dataIdList[i] for i in goodIndices],
806 skyInfo=skyInfo)
807 if self.config.makeDirect and results.exposures["direct"] is not None:
808 butlerQC.put(results.exposures["direct"], outputRefs.direct)
809 if self.config.makePsfMatched and results.exposures["psfMatched"] is not None:
810 butlerQC.put(results.exposures["psfMatched"], outputRefs.psfMatched)
812 def filterInputs(self, indices, inputs):
813 """Return task inputs with their lists filtered by indices
815 Parameters
816 ----------
817 indices : `list` of integers
818 inputs : `dict` of `list` of input connections to be passed to run
819 """
820 for key in inputs.keys():
821 # Only down-select on list inputs
822 if isinstance(inputs[key], list):
823 inputs[key] = [inputs[key][ind] for ind in indices]
824 return inputs
826 def prepareCalibratedExposures(self, calExpList, backgroundList=None, skyCorrList=None,
827 externalSkyWcsCatalog=None, externalPhotoCalibCatalog=None,
828 **kwargs):
829 """Calibrate and add backgrounds to input calExpList in place
831 Parameters
832 ----------
833 calExpList : `list` of `lsst.afw.image.Exposure`
834 Sequence of calexps to be modified in place
835 backgroundList : `list` of `lsst.afw.math.backgroundList`, optional
836 Sequence of backgrounds to be added back in if bgSubtracted=False
837 skyCorrList : `list` of `lsst.afw.math.backgroundList`, optional
838 Sequence of background corrections to be subtracted if doApplySkyCorr=True
839 externalSkyWcsCatalog : `lsst.afw.table.ExposureCatalog`, optional
840 Exposure catalog with external skyWcs to be applied
841 if config.doApplyExternalSkyWcs=True. Catalog uses the detector id
842 for the catalog id, sorted on id for fast lookup.
843 externalPhotoCalibCatalog : `lsst.afw.table.ExposureCatalog`, optional
844 Exposure catalog with external photoCalib to be applied
845 if config.doApplyExternalPhotoCalib=True. Catalog uses the detector
846 id for the catalog id, sorted on id for fast lookup.
848 Returns
849 -------
850 indices : `list` [`int`]
851 Indices of calExpList and friends that have valid photoCalib/skyWcs
852 """
853 backgroundList = len(calExpList)*[None] if backgroundList is None else backgroundList
854 skyCorrList = len(calExpList)*[None] if skyCorrList is None else skyCorrList
856 includeCalibVar = self.config.includeCalibVar
858 indices = []
859 for index, (calexp, background, skyCorr) in enumerate(zip(calExpList,
860 backgroundList,
861 skyCorrList)):
862 mi = calexp.maskedImage
863 if not self.config.bgSubtracted:
864 mi += background.getImage()
866 if externalSkyWcsCatalog is not None or externalPhotoCalibCatalog is not None:
867 detectorId = calexp.getInfo().getDetector().getId()
869 # Find the external photoCalib
870 if externalPhotoCalibCatalog is not None:
871 row = externalPhotoCalibCatalog.find(detectorId)
872 if row is None:
873 self.log.warning("Detector id %s not found in externalPhotoCalibCatalog "
874 "and will not be used in the warp.", detectorId)
875 continue
876 photoCalib = row.getPhotoCalib()
877 if photoCalib is None:
878 self.log.warning("Detector id %s has None for photoCalib in externalPhotoCalibCatalog "
879 "and will not be used in the warp.", detectorId)
880 continue
881 calexp.setPhotoCalib(photoCalib)
882 else:
883 photoCalib = calexp.getPhotoCalib()
884 if photoCalib is None:
885 self.log.warning("Detector id %s has None for photoCalib in the calexp "
886 "and will not be used in the warp.", detectorId)
887 continue
889 # Find and apply external skyWcs
890 if externalSkyWcsCatalog is not None:
891 row = externalSkyWcsCatalog.find(detectorId)
892 if row is None:
893 self.log.warning("Detector id %s not found in externalSkyWcsCatalog "
894 "and will not be used in the warp.", detectorId)
895 continue
896 skyWcs = row.getWcs()
897 if skyWcs is None:
898 self.log.warning("Detector id %s has None for skyWcs in externalSkyWcsCatalog "
899 "and will not be used in the warp.", detectorId)
900 continue
901 calexp.setWcs(skyWcs)
902 else:
903 skyWcs = calexp.getWcs()
904 if skyWcs is None:
905 self.log.warning("Detector id %s has None for skyWcs in the calexp "
906 "and will not be used in the warp.", detectorId)
907 continue
909 # Calibrate the image
910 calexp.maskedImage = photoCalib.calibrateImage(calexp.maskedImage,
911 includeScaleUncertainty=includeCalibVar)
912 calexp.maskedImage /= photoCalib.getCalibrationMean()
913 # TODO: The images will have a calibration of 1.0 everywhere once RFC-545 is implemented.
914 # exposure.setCalib(afwImage.Calib(1.0))
916 # Apply skycorr
917 if self.config.doApplySkyCorr:
918 mi -= skyCorr.getImage()
920 indices.append(index)
922 return indices
925def reorderRefs(inputRefs, outputSortKeyOrder, dataIdKey):
926 """Reorder inputRefs per outputSortKeyOrder
928 Any inputRefs which are lists will be resorted per specified key e.g.,
929 'detector.' Only iterables will be reordered, and values can be of type
930 `lsst.pipe.base.connections.DeferredDatasetRef` or
931 `lsst.daf.butler.core.datasets.ref.DatasetRef`.
932 Returned lists of refs have the same length as the outputSortKeyOrder.
933 If an outputSortKey not in the inputRef, then it will be padded with None.
934 If an inputRef contains an inputSortKey that is not in the
935 outputSortKeyOrder it will be removed.
937 Parameters
938 ----------
939 inputRefs : `lsst.pipe.base.connections.QuantizedConnection`
940 Input references to be reordered and padded.
941 outputSortKeyOrder : iterable
942 Iterable of values to be compared with inputRef's dataId[dataIdKey]
943 dataIdKey : `str`
944 dataIdKey in the dataRefs to compare with the outputSortKeyOrder.
946 Returns:
947 --------
948 inputRefs: `lsst.pipe.base.connections.QuantizedConnection`
949 Quantized Connection with sorted DatasetRef values sorted if iterable.
950 """
951 for connectionName, refs in inputRefs:
952 if isinstance(refs, Iterable):
953 if hasattr(refs[0], "dataId"):
954 inputSortKeyOrder = [ref.dataId[dataIdKey] for ref in refs]
955 else:
956 inputSortKeyOrder = [ref.datasetRef.dataId[dataIdKey] for ref in refs]
957 if inputSortKeyOrder != outputSortKeyOrder:
958 setattr(inputRefs, connectionName,
959 reorderAndPadList(refs, inputSortKeyOrder, outputSortKeyOrder))
960 return inputRefs