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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 

23 

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 

39 

40__all__ = ["MakeCoaddTempExpTask", "MakeWarpTask", "MakeWarpConfig"] 

41 

42 

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 

49 

50 

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 ) 

82 

83 doWriteEmptyWarps = pexConfig.Field( 

84 dtype=bool, 

85 default=False, 

86 doc="Write out warps even if they are empty" 

87 ) 

88 

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?") 

95 

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.warn("Config doPsfMatch deprecated. Setting makePsfMatched=True and makeDirect=False") 

103 self.makePsfMatched = True 

104 self.makeDirect = False 

105 

106 def setDefaults(self): 

107 CoaddBaseTask.ConfigClass.setDefaults(self) 

108 self.warpAndPsfMatch.psfMatch.kernel.active.kernelSize = self.matchingKernelSize 

109 

110## \addtogroup LSST_task_documentation 

111## \{ 

112## \page MakeCoaddTempExpTask 

113## \ref MakeCoaddTempExpTask_ "MakeCoaddTempExpTask" 

114## \copybrief MakeCoaddTempExpTask 

115## \} 

116 

117 

118class MakeCoaddTempExpTask(CoaddBaseTask): 

119 r"""!Warp and optionally PSF-Match calexps onto an a common projection. 

120 

121 @anchor MakeCoaddTempExpTask_ 

122 

123 @section pipe_tasks_makeCoaddTempExp_Contents Contents 

124 

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 

131 

132 @section pipe_tasks_makeCoaddTempExp_Purpose Description 

133 

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 

140 

141 The result is a `directWarp` (and/or optionally a `psfMatchedWarp`). 

142 

143 @section pipe_tasks_makeCoaddTempExp_Initialize Task Initialization 

144 

145 @copydoc \_\_init\_\_ 

146 

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. 

150 

151 @section pipe_tasks_makeCoaddTempExp_IO Invoking the Task 

152 

153 This task is primarily designed to be run from the command line. 

154 

155 The main method is `runDataRef`, which takes a single butler data reference for the patch(es) 

156 to process. 

157 

158 @copydoc run 

159 

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. 

164 

165 @section pipe_tasks_makeCoaddTempExp_Config Configuration parameters 

166 

167 See @ref MakeCoaddTempExpConfig and parameters inherited from 

168 @link lsst.pipe.tasks.coaddBase.CoaddBaseConfig CoaddBaseConfig @endlink 

169 

170 @subsection pipe_tasks_MakeCoaddTempExp_psfMatching Guide to PSF-Matching Configs 

171 

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. 

178 

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* 

189 

190 *Troublshooting PSF-Matching Configuration:* 

191 - Matched PSFs look boxy: The matching kernel is too small. _Increase the matching kernel size. 

192 For example:_ 

193 

194 config.warpAndPsfMatch.psfMatch.kernel['AL'].kernelSize=27 # default 21 

195 

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,_ 

200 

201 config.warpAndPsfMatch.psfMatch.kernel['AL'].sizeCellX = 64 # default 128 

202 config.warpAndPsfMatch.psfMatch.kernel['AL'].sizeCellY = 64 # default 128 

203 

204 _or increasing the padding around the Science PSF, for example:_ 

205 

206 config.warpAndPsfMatch.psfMatch.autoPadPsfTo=1.6 # default 1.4 

207 

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: 

214 

215 config.warpAndPsfMatch.psfMatch.doAutoPadPsf = False # default True 

216 config.warpAndPsfMatch.psfMatch.padPsfBy = 6 # pixels. default 0 

217 

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:_ 

221 

222 config.modelPsf.defaultFwhm = 11 # Gaussian sigma in units of pixels. 

223 

224 - High frequency (sometimes checkered) noise: The matching basis functions are too small. 

225 _Increase the width of the Gaussian basis functions. For example:_ 

226 

227 config.warpAndPsfMatch.psfMatch.kernel['AL'].alardSigGauss=[1.5, 3.0, 6.0] 

228 # from default [0.7, 1.5, 3.0] 

229 

230 

231 @section pipe_tasks_makeCoaddTempExp_Debug Debug variables 

232 

233 MakeCoaddTempExpTask has no debug output, but its subtasks do. 

234 

235 @section pipe_tasks_makeCoaddTempExp_Example A complete example of using MakeCoaddTempExpTask 

236 

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: 

240 

241 setup ci_hsc 

242 cd $CI_HSC_DIR 

243 # if not built already: 

244 python $(which scons) # this will take a while 

245 

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, 

249 

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 

256 

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. 

261 

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: 

265 

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 

269 

270 

271 Add the option `--help` to see more options. 

272 """ 

273 ConfigClass = MakeCoaddTempExpConfig 

274 _DefaultName = "makeCoaddTempExp" 

275 

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" 

284 

285 @pipeBase.timeMethod 

286 def runDataRef(self, patchRef, selectDataList=[]): 

287 """!Produce <coaddName>Coadd_<warpType>Warp images by warping and optionally PSF-matching. 

288 

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. 

294 

295 @warning: this task assumes that all exposures in a warp (coaddTempExp) have the same filter. 

296 

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) 

302 

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") 

308 

309 calExpRefList = self.selectExposures(patchRef, skyInfo, selectDataList=selectDataList) 

310 

311 if len(calExpRefList) == 0: 

312 self.log.warn("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) 

317 

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) 

321 

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) 

331 

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 

339 

340 calExpList = [] 

341 ccdIdList = [] 

342 dataIdList = [] 

343 

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.warn("Calexp %s not found; skipping it: %s", calExpRef.dataId, e) 

361 continue 

362 

363 if self.config.doApplySkyCorr: 

364 self.applySkyCorr(calExpRef, calExp) 

365 

366 calExpList.append(calExp) 

367 ccdIdList.append(ccdId) 

368 dataIdList.append(calExpRef.dataId) 

369 

370 exps = self.run(calExpList, ccdIdList, skyInfo, visitId, dataIdList).exposures 

371 

372 if any(exps.values()): 

373 dataRefList.append(tempExpRef) 

374 else: 

375 self.log.warn("Warp %s could not be created", tempExpRef.dataId) 

376 

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)) 

382 

383 return dataRefList 

384 

385 @pipeBase.timeMethod 

386 def run(self, calExpList, ccdIdList, skyInfo, visitId=0, dataIdList=None, **kwargs): 

387 """Create a Warp from inputs 

388 

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. 

392 

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. 

396 

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() 

409 

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} 

415 

416 modelPsf = self.config.modelPsf.apply() if self.config.makePsfMatched else None 

417 if dataIdList is None: 

418 dataIdList = ccdIdList 

419 

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) 

423 

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.warn("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 

457 

458 # Need inputRecorder for CoaddApCorrMap for both direct and PSF-matched 

459 inputRecorder[warpType].addCalExp(calExp, ccdId, numGoodPix[warpType]) 

460 

461 except Exception as e: 

462 self.log.warn("Error processing calexp %s; skipping it: %s", dataId, e) 

463 continue 

464 

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()) 

468 

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 

479 

480 result = pipeBase.Struct(exposures=coaddTempExps) 

481 return result 

482 

483 def getCalibratedExposure(self, dataRef, bgSubtracted): 

484 """Return one calibrated Exposure, possibly with an updated SkyWcs. 

485 

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 

490 

491 @raises MissingExposureError If data for the exposure is not available. 

492 

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 

506 

507 if not bgSubtracted: 

508 background = dataRef.get("calexpBackground", immediate=True) 

509 mi = exposure.getMaskedImage() 

510 mi += background.getImage() 

511 del mi 

512 

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() 

520 

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) 

526 

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 

533 

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 

541 

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 

551 

552 def applySkyCorr(self, dataRef, calexp): 

553 """Apply correction to the sky background level 

554 

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. 

559 

560 The calexp is updated in-place. 

561 

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() 

574 

575 

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 ) 

683 

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") 

716 

717 

718class MakeWarpConfig(pipeBase.PipelineTaskConfig, MakeCoaddTempExpConfig, 

719 pipelineConnections=MakeWarpConnections): 

720 

721 def validate(self): 

722 super().validate() 

723 

724 

725class MakeWarpTask(MakeCoaddTempExpTask): 

726 """Warp and optionally PSF-Match calexps onto an a common projection 

727 """ 

728 ConfigClass = MakeWarpConfig 

729 _DefaultName = "makeWarp" 

730 

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 

737 

738 PipelineTask (Gen3) entry point to warp and optionally PSF-match 

739 calexps. This method is analogous to `runDataRef`. 

740 """ 

741 

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') 

745 

746 # Read in all inputs. 

747 inputs = butlerQC.get(inputRefs) 

748 

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']) 

754 

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] 

759 

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) 

766 

767 # Read from disk only the selected calexps 

768 inputs['calExpList'] = [ref.get() for ref in inputs['calExpList']] 

769 

770 # Extract integer visitId requested by `run` 

771 visits = [dataId['visit'] for dataId in dataIdList] 

772 visitId = visits[0] 

773 

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 

781 

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 

789 

790 self.prepareCalibratedExposures(**inputs, externalSkyWcsCatalog=externalSkyWcsCatalog, 

791 externalPhotoCalibCatalog=externalPhotoCalibCatalog) 

792 

793 results = self.run(**inputs, visitId=visitId, 

794 ccdIdList=[ccdIdList[i] for i in goodIndices], 

795 dataIdList=[dataIdList[i] for i in goodIndices], 

796 skyInfo=skyInfo) 

797 if self.config.makeDirect: 

798 butlerQC.put(results.exposures["direct"], outputRefs.direct) 

799 if self.config.makePsfMatched: 

800 butlerQC.put(results.exposures["psfMatched"], outputRefs.psfMatched) 

801 

802 def filterInputs(self, indices, inputs): 

803 """Return task inputs with their lists filtered by indices 

804 

805 Parameters 

806 ---------- 

807 indices : `list` of integers 

808 inputs : `dict` of `list` of input connections to be passed to run 

809 """ 

810 for key in inputs.keys(): 

811 # Only down-select on list inputs 

812 if isinstance(inputs[key], list): 

813 inputs[key] = [inputs[key][ind] for ind in indices] 

814 return inputs 

815 

816 def prepareCalibratedExposures(self, calExpList, backgroundList=None, skyCorrList=None, 

817 externalSkyWcsCatalog=None, externalPhotoCalibCatalog=None, 

818 **kwargs): 

819 """Calibrate and add backgrounds to input calExpList in place 

820 

821 Parameters 

822 ---------- 

823 calExpList : `list` of `lsst.afw.image.Exposure` 

824 Sequence of calexps to be modified in place 

825 backgroundList : `list` of `lsst.afw.math.backgroundList`, optional 

826 Sequence of backgrounds to be added back in if bgSubtracted=False 

827 skyCorrList : `list` of `lsst.afw.math.backgroundList`, optional 

828 Sequence of background corrections to be subtracted if doApplySkyCorr=True 

829 externalSkyWcsCatalog : `lsst.afw.table.ExposureCatalog`, optional 

830 Exposure catalog with external skyWcs to be applied 

831 if config.doApplyExternalSkyWcs=True. Catalog uses the detector id 

832 for the catalog id, sorted on id for fast lookup. 

833 externalPhotoCalibCatalog : `lsst.afw.table.ExposureCatalog`, optional 

834 Exposure catalog with external photoCalib to be applied 

835 if config.doApplyExternalPhotoCalib=True. Catalog uses the detector 

836 id for the catalog id, sorted on id for fast lookup. 

837 """ 

838 backgroundList = len(calExpList)*[None] if backgroundList is None else backgroundList 

839 skyCorrList = len(calExpList)*[None] if skyCorrList is None else skyCorrList 

840 

841 includeCalibVar = self.config.includeCalibVar 

842 

843 for calexp, background, skyCorr in zip(calExpList, backgroundList, skyCorrList): 

844 mi = calexp.maskedImage 

845 if not self.config.bgSubtracted: 

846 mi += background.getImage() 

847 

848 if externalSkyWcsCatalog is not None or externalPhotoCalibCatalog is not None: 

849 detectorId = calexp.getInfo().getDetector().getId() 

850 

851 # Find the external photoCalib 

852 if externalPhotoCalibCatalog is not None: 

853 row = externalPhotoCalibCatalog.find(detectorId) 

854 if row is None: 

855 raise RuntimeError(f"Detector id {detectorId} not found in " 

856 f"externalPhotoCalibCatalog.") 

857 photoCalib = row.getPhotoCalib() 

858 if photoCalib is None: 

859 raise RuntimeError(f"Detector id {detectorId} has None for photoCalib " 

860 f"in externalPhotoCalibCatalog.") 

861 calexp.setPhotoCalib(photoCalib) 

862 else: 

863 photoCalib = calexp.getPhotoCalib() 

864 

865 # Find and apply external skyWcs 

866 if externalSkyWcsCatalog is not None: 

867 row = externalSkyWcsCatalog.find(detectorId) 

868 if row is None: 

869 raise RuntimeError(f"Detector id {detectorId} not found in externalSkyWcsCatalog.") 

870 skyWcs = row.getWcs() 

871 if skyWcs is None: 

872 raise RuntimeError(f"Detector id {detectorId} has None for WCS " 

873 f" in externalSkyWcsCatalog.") 

874 calexp.setWcs(skyWcs) 

875 

876 # Calibrate the image 

877 calexp.maskedImage = photoCalib.calibrateImage(calexp.maskedImage, 

878 includeScaleUncertainty=includeCalibVar) 

879 calexp.maskedImage /= photoCalib.getCalibrationMean() 

880 # TODO: The images will have a calibration of 1.0 everywhere once RFC-545 is implemented. 

881 # exposure.setCalib(afwImage.Calib(1.0)) 

882 

883 # Apply skycorr 

884 if self.config.doApplySkyCorr: 

885 mi -= skyCorr.getImage() 

886 

887 

888def reorderRefs(inputRefs, outputSortKeyOrder, dataIdKey): 

889 """Reorder inputRefs per outputSortKeyOrder 

890 

891 Any inputRefs which are lists will be resorted per specified key e.g., 

892 'detector.' Only iterables will be reordered, and values can be of type 

893 `lsst.pipe.base.connections.DeferredDatasetRef` or 

894 `lsst.daf.butler.core.datasets.ref.DatasetRef`. 

895 Returned lists of refs have the same length as the outputSortKeyOrder. 

896 If an outputSortKey not in the inputRef, then it will be padded with None. 

897 If an inputRef contains an inputSortKey that is not in the 

898 outputSortKeyOrder it will be removed. 

899 

900 Parameters 

901 ---------- 

902 inputRefs : `lsst.pipe.base.connections.QuantizedConnection` 

903 Input references to be reordered and padded. 

904 outputSortKeyOrder : iterable 

905 Iterable of values to be compared with inputRef's dataId[dataIdKey] 

906 dataIdKey : `str` 

907 dataIdKey in the dataRefs to compare with the outputSortKeyOrder. 

908 

909 Returns: 

910 -------- 

911 inputRefs: `lsst.pipe.base.connections.QuantizedConnection` 

912 Quantized Connection with sorted DatasetRef values sorted if iterable. 

913 """ 

914 for connectionName, refs in inputRefs: 

915 if isinstance(refs, Iterable): 

916 if hasattr(refs[0], "dataId"): 

917 inputSortKeyOrder = [ref.dataId[dataIdKey] for ref in refs] 

918 else: 

919 inputSortKeyOrder = [ref.datasetRef.dataId[dataIdKey] for ref in refs] 

920 if inputSortKeyOrder != outputSortKeyOrder: 

921 setattr(inputRefs, connectionName, 

922 reorderAndPadList(refs, inputSortKeyOrder, outputSortKeyOrder)) 

923 return inputRefs