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

Shortcuts on this page

r m x p   toggle line displays

j k   next/prev highlighted chunk

0   (zero) top of page

1   (one) first highlighted chunk

343 statements  

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 

24 

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 

40 

41__all__ = ["MakeCoaddTempExpTask", "MakeWarpTask", "MakeWarpConfig"] 

42 

43log = logging.getLogger(__name__.partition(".")[2]) 

44 

45 

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 

52 

53 

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 ) 

85 

86 doWriteEmptyWarps = pexConfig.Field( 

87 dtype=bool, 

88 default=False, 

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

90 ) 

91 

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?") 

98 

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 

108 

109 def setDefaults(self): 

110 CoaddBaseTask.ConfigClass.setDefaults(self) 

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

112 

113## \addtogroup LSST_task_documentation 

114## \{ 

115## \page MakeCoaddTempExpTask 

116## \ref MakeCoaddTempExpTask_ "MakeCoaddTempExpTask" 

117## \copybrief MakeCoaddTempExpTask 

118## \} 

119 

120 

121class MakeCoaddTempExpTask(CoaddBaseTask): 

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

123 

124 @anchor MakeCoaddTempExpTask_ 

125 

126 @section pipe_tasks_makeCoaddTempExp_Contents Contents 

127 

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 

134 

135 @section pipe_tasks_makeCoaddTempExp_Purpose Description 

136 

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 

143 

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

145 

146 @section pipe_tasks_makeCoaddTempExp_Initialize Task Initialization 

147 

148 @copydoc \_\_init\_\_ 

149 

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. 

153 

154 @section pipe_tasks_makeCoaddTempExp_IO Invoking the Task 

155 

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

157 

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

159 to process. 

160 

161 @copydoc run 

162 

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. 

167 

168 @section pipe_tasks_makeCoaddTempExp_Config Configuration parameters 

169 

170 See @ref MakeCoaddTempExpConfig and parameters inherited from 

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

172 

173 @subsection pipe_tasks_MakeCoaddTempExp_psfMatching Guide to PSF-Matching Configs 

174 

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. 

181 

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* 

192 

193 *Troublshooting PSF-Matching Configuration:* 

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

195 For example:_ 

196 

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

198 

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,_ 

203 

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

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

206 

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

208 

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

210 

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: 

217 

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

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

220 

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:_ 

224 

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

226 

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

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

229 

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

231 # from default [0.7, 1.5, 3.0] 

232 

233 

234 @section pipe_tasks_makeCoaddTempExp_Debug Debug variables 

235 

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

237 

238 @section pipe_tasks_makeCoaddTempExp_Example A complete example of using MakeCoaddTempExpTask 

239 

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: 

243 

244 setup ci_hsc 

245 cd $CI_HSC_DIR 

246 # if not built already: 

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

248 

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, 

252 

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 

259 

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. 

264 

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: 

268 

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 

272 

273 

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

275 """ 

276 ConfigClass = MakeCoaddTempExpConfig 

277 _DefaultName = "makeCoaddTempExp" 

278 

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" 

287 

288 @timeMethod 

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

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

291 

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. 

297 

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

299 

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) 

305 

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") 

311 

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

313 

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) 

320 

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) 

324 

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) 

334 

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 

342 

343 calExpList = [] 

344 ccdIdList = [] 

345 dataIdList = [] 

346 

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 

365 

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) 

368 

369 calExpList.append(calExp) 

370 ccdIdList.append(ccdId) 

371 dataIdList.append(calExpRef.dataId) 

372 

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

374 

375 if any(exps.values()): 

376 dataRefList.append(tempExpRef) 

377 else: 

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

379 

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)) 

385 

386 return dataRefList 

387 

388 @timeMethod 

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

390 """Create a Warp from inputs 

391 

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. 

395 

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. 

399 

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() 

412 

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} 

418 

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 

422 

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) 

426 

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 

461 

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

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

464 

465 except Exception as e: 

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

467 continue 

468 

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()) 

472 

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. 

486 

487 result = pipeBase.Struct(exposures=coaddTempExps) 

488 return result 

489 

490 def getCalibratedExposure(self, dataRef, bgSubtracted): 

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

492 

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 

497 

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

499 

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 

513 

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 

519 

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() 

527 

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) 

533 

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 

540 

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 

548 

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 

558 

559 def applySkyCorr(self, dataRef, calexp): 

560 """Apply correction to the sky background level 

561 

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. 

566 

567 The calexp is updated in-place. 

568 

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() 

581 

582 

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 ) 

690 

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") 

723 

724 

725class MakeWarpConfig(pipeBase.PipelineTaskConfig, MakeCoaddTempExpConfig, 

726 pipelineConnections=MakeWarpConnections): 

727 

728 def validate(self): 

729 super().validate() 

730 

731 

732class MakeWarpTask(MakeCoaddTempExpTask): 

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

734 """ 

735 ConfigClass = MakeWarpConfig 

736 _DefaultName = "makeWarp" 

737 

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 

744 

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

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

747 """ 

748 

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') 

752 

753 # Read in all inputs. 

754 inputs = butlerQC.get(inputRefs) 

755 

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']) 

761 

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] 

766 

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) 

773 

774 # Read from disk only the selected calexps 

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

776 

777 # Extract integer visitId requested by `run` 

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

779 visitId = visits[0] 

780 

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 

788 

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 

796 

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) 

802 

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) 

811 

812 def filterInputs(self, indices, inputs): 

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

814 

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 

825 

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 

830 

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. 

847 

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 

855 

856 includeCalibVar = self.config.includeCalibVar 

857 

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() 

865 

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

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

868 

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 

888 

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 

908 

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)) 

915 

916 # Apply skycorr 

917 if self.config.doApplySkyCorr: 

918 mi -= skyCorr.getImage() 

919 

920 indices.append(index) 

921 

922 return indices 

923 

924 

925def reorderRefs(inputRefs, outputSortKeyOrder, dataIdKey): 

926 """Reorder inputRefs per outputSortKeyOrder 

927 

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. 

936 

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. 

945 

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