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1# 

2# LSST Data Management System 

3# Copyright 2008-2015 AURA/LSST. 

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 <https://www.lsstcorp.org/LegalNotices/>. 

21# 

22import numpy as np 

23 

24from lsstDebug import getDebugFrame 

25import lsst.afw.table as afwTable 

26import lsst.pex.config as pexConfig 

27import lsst.pipe.base as pipeBase 

28import lsst.daf.base as dafBase 

29import lsst.pipe.base.connectionTypes as cT 

30from lsst.afw.math import BackgroundList 

31from lsst.afw.table import SourceTable, SourceCatalog 

32from lsst.meas.algorithms import SubtractBackgroundTask, SourceDetectionTask, MeasureApCorrTask 

33from lsst.meas.algorithms.installGaussianPsf import InstallGaussianPsfTask 

34from lsst.meas.astrom import RefMatchTask, displayAstrometry 

35from lsst.meas.algorithms import LoadIndexedReferenceObjectsTask 

36from lsst.obs.base import ExposureIdInfo 

37from lsst.meas.base import SingleFrameMeasurementTask, ApplyApCorrTask, CatalogCalculationTask 

38from lsst.meas.deblender import SourceDeblendTask 

39from .measurePsf import MeasurePsfTask 

40from .repair import RepairTask 

41from .computeExposureSummaryStats import ComputeExposureSummaryStatsTask 

42from lsst.pex.exceptions import LengthError 

43from lsst.utils.timer import timeMethod 

44 

45__all__ = ["CharacterizeImageConfig", "CharacterizeImageTask"] 

46 

47 

48class CharacterizeImageConnections(pipeBase.PipelineTaskConnections, 

49 dimensions=("instrument", "visit", "detector")): 

50 exposure = cT.Input( 

51 doc="Input exposure data", 

52 name="postISRCCD", 

53 storageClass="Exposure", 

54 dimensions=["instrument", "exposure", "detector"], 

55 ) 

56 characterized = cT.Output( 

57 doc="Output characterized data.", 

58 name="icExp", 

59 storageClass="ExposureF", 

60 dimensions=["instrument", "visit", "detector"], 

61 ) 

62 sourceCat = cT.Output( 

63 doc="Output source catalog.", 

64 name="icSrc", 

65 storageClass="SourceCatalog", 

66 dimensions=["instrument", "visit", "detector"], 

67 ) 

68 backgroundModel = cT.Output( 

69 doc="Output background model.", 

70 name="icExpBackground", 

71 storageClass="Background", 

72 dimensions=["instrument", "visit", "detector"], 

73 ) 

74 outputSchema = cT.InitOutput( 

75 doc="Schema of the catalog produced by CharacterizeImage", 

76 name="icSrc_schema", 

77 storageClass="SourceCatalog", 

78 ) 

79 

80 def adjustQuantum(self, inputs, outputs, label, dataId): 

81 # Docstring inherited from PipelineTaskConnections 

82 try: 

83 return super().adjustQuantum(inputs, outputs, label, dataId) 

84 except pipeBase.ScalarError as err: 

85 raise pipeBase.ScalarError( 

86 "CharacterizeImageTask can at present only be run on visits that are associated with " 

87 "exactly one exposure. Either this is not a valid exposure for this pipeline, or the " 

88 "snap-combination step you probably want hasn't been configured to run between ISR and " 

89 "this task (as of this writing, that would be because it hasn't been implemented yet)." 

90 ) from err 

91 

92 

93class CharacterizeImageConfig(pipeBase.PipelineTaskConfig, 

94 pipelineConnections=CharacterizeImageConnections): 

95 

96 """!Config for CharacterizeImageTask""" 

97 doMeasurePsf = pexConfig.Field( 

98 dtype=bool, 

99 default=True, 

100 doc="Measure PSF? If False then for all subsequent operations use either existing PSF " 

101 "model when present, or install simple PSF model when not (see installSimplePsf " 

102 "config options)" 

103 ) 

104 doWrite = pexConfig.Field( 

105 dtype=bool, 

106 default=True, 

107 doc="Persist results?", 

108 ) 

109 doWriteExposure = pexConfig.Field( 

110 dtype=bool, 

111 default=True, 

112 doc="Write icExp and icExpBackground in addition to icSrc? Ignored if doWrite False.", 

113 ) 

114 psfIterations = pexConfig.RangeField( 

115 dtype=int, 

116 default=2, 

117 min=1, 

118 doc="Number of iterations of detect sources, measure sources, " 

119 "estimate PSF. If useSimplePsf is True then 2 should be plenty; " 

120 "otherwise more may be wanted.", 

121 ) 

122 background = pexConfig.ConfigurableField( 

123 target=SubtractBackgroundTask, 

124 doc="Configuration for initial background estimation", 

125 ) 

126 detection = pexConfig.ConfigurableField( 

127 target=SourceDetectionTask, 

128 doc="Detect sources" 

129 ) 

130 doDeblend = pexConfig.Field( 

131 dtype=bool, 

132 default=True, 

133 doc="Run deblender input exposure" 

134 ) 

135 deblend = pexConfig.ConfigurableField( 

136 target=SourceDeblendTask, 

137 doc="Split blended source into their components" 

138 ) 

139 measurement = pexConfig.ConfigurableField( 

140 target=SingleFrameMeasurementTask, 

141 doc="Measure sources" 

142 ) 

143 doApCorr = pexConfig.Field( 

144 dtype=bool, 

145 default=True, 

146 doc="Run subtasks to measure and apply aperture corrections" 

147 ) 

148 measureApCorr = pexConfig.ConfigurableField( 

149 target=MeasureApCorrTask, 

150 doc="Subtask to measure aperture corrections" 

151 ) 

152 applyApCorr = pexConfig.ConfigurableField( 

153 target=ApplyApCorrTask, 

154 doc="Subtask to apply aperture corrections" 

155 ) 

156 # If doApCorr is False, and the exposure does not have apcorrections already applied, the 

157 # active plugins in catalogCalculation almost certainly should not contain the characterization plugin 

158 catalogCalculation = pexConfig.ConfigurableField( 

159 target=CatalogCalculationTask, 

160 doc="Subtask to run catalogCalculation plugins on catalog" 

161 ) 

162 doComputeSummaryStats = pexConfig.Field( 

163 dtype=bool, 

164 default=True, 

165 doc="Run subtask to measure exposure summary statistics", 

166 deprecated=("This subtask has been moved to CalibrateTask " 

167 "with DM-30701.") 

168 ) 

169 computeSummaryStats = pexConfig.ConfigurableField( 

170 target=ComputeExposureSummaryStatsTask, 

171 doc="Subtask to run computeSummaryStats on exposure", 

172 deprecated=("This subtask has been moved to CalibrateTask " 

173 "with DM-30701.") 

174 ) 

175 useSimplePsf = pexConfig.Field( 

176 dtype=bool, 

177 default=True, 

178 doc="Replace the existing PSF model with a simplified version that has the same sigma " 

179 "at the start of each PSF determination iteration? Doing so makes PSF determination " 

180 "converge more robustly and quickly.", 

181 ) 

182 installSimplePsf = pexConfig.ConfigurableField( 

183 target=InstallGaussianPsfTask, 

184 doc="Install a simple PSF model", 

185 ) 

186 refObjLoader = pexConfig.ConfigurableField( 

187 target=LoadIndexedReferenceObjectsTask, 

188 doc="reference object loader", 

189 ) 

190 ref_match = pexConfig.ConfigurableField( 

191 target=RefMatchTask, 

192 doc="Task to load and match reference objects. Only used if measurePsf can use matches. " 

193 "Warning: matching will only work well if the initial WCS is accurate enough " 

194 "to give good matches (roughly: good to 3 arcsec across the CCD).", 

195 ) 

196 measurePsf = pexConfig.ConfigurableField( 

197 target=MeasurePsfTask, 

198 doc="Measure PSF", 

199 ) 

200 repair = pexConfig.ConfigurableField( 

201 target=RepairTask, 

202 doc="Remove cosmic rays", 

203 ) 

204 requireCrForPsf = pexConfig.Field( 

205 dtype=bool, 

206 default=True, 

207 doc="Require cosmic ray detection and masking to run successfully before measuring the PSF." 

208 ) 

209 checkUnitsParseStrict = pexConfig.Field( 

210 doc="Strictness of Astropy unit compatibility check, can be 'raise', 'warn' or 'silent'", 

211 dtype=str, 

212 default="raise", 

213 ) 

214 

215 def setDefaults(self): 

216 super().setDefaults() 

217 # just detect bright stars; includeThresholdMultipler=10 seems large, 

218 # but these are the values we have been using 

219 self.detection.thresholdValue = 5.0 

220 self.detection.includeThresholdMultiplier = 10.0 

221 self.detection.doTempLocalBackground = False 

222 # do not deblend, as it makes a mess 

223 self.doDeblend = False 

224 # measure and apply aperture correction; note: measuring and applying aperture 

225 # correction are disabled until the final measurement, after PSF is measured 

226 self.doApCorr = True 

227 # minimal set of measurements needed to determine PSF 

228 self.measurement.plugins.names = [ 

229 "base_PixelFlags", 

230 "base_SdssCentroid", 

231 "base_SdssShape", 

232 "base_GaussianFlux", 

233 "base_PsfFlux", 

234 "base_CircularApertureFlux", 

235 ] 

236 

237 def validate(self): 

238 if self.doApCorr and not self.measurePsf: 

239 raise RuntimeError("Must measure PSF to measure aperture correction, " 

240 "because flags determined by PSF measurement are used to identify " 

241 "sources used to measure aperture correction") 

242 

243## \addtogroup LSST_task_documentation 

244## \{ 

245## \page CharacterizeImageTask 

246## \ref CharacterizeImageTask_ "CharacterizeImageTask" 

247## \copybrief CharacterizeImageTask 

248## \} 

249 

250 

251class CharacterizeImageTask(pipeBase.PipelineTask, pipeBase.CmdLineTask): 

252 r"""!Measure bright sources and use this to estimate background and PSF of an exposure 

253 

254 @anchor CharacterizeImageTask_ 

255 

256 @section pipe_tasks_characterizeImage_Contents Contents 

257 

258 - @ref pipe_tasks_characterizeImage_Purpose 

259 - @ref pipe_tasks_characterizeImage_Initialize 

260 - @ref pipe_tasks_characterizeImage_IO 

261 - @ref pipe_tasks_characterizeImage_Config 

262 - @ref pipe_tasks_characterizeImage_Debug 

263 

264 

265 @section pipe_tasks_characterizeImage_Purpose Description 

266 

267 Given an exposure with defects repaired (masked and interpolated over, e.g. as output by IsrTask): 

268 - detect and measure bright sources 

269 - repair cosmic rays 

270 - measure and subtract background 

271 - measure PSF 

272 

273 @section pipe_tasks_characterizeImage_Initialize Task initialisation 

274 

275 @copydoc \_\_init\_\_ 

276 

277 @section pipe_tasks_characterizeImage_IO Invoking the Task 

278 

279 If you want this task to unpersist inputs or persist outputs, then call 

280 the `runDataRef` method (a thin wrapper around the `run` method). 

281 

282 If you already have the inputs unpersisted and do not want to persist the output 

283 then it is more direct to call the `run` method: 

284 

285 @section pipe_tasks_characterizeImage_Config Configuration parameters 

286 

287 See @ref CharacterizeImageConfig 

288 

289 @section pipe_tasks_characterizeImage_Debug Debug variables 

290 

291 The @link lsst.pipe.base.cmdLineTask.CmdLineTask command line task@endlink interface supports a flag 

292 `--debug` to import `debug.py` from your `$PYTHONPATH`; see @ref baseDebug for more about `debug.py`. 

293 

294 CharacterizeImageTask has a debug dictionary with the following keys: 

295 <dl> 

296 <dt>frame 

297 <dd>int: if specified, the frame of first debug image displayed (defaults to 1) 

298 <dt>repair_iter 

299 <dd>bool; if True display image after each repair in the measure PSF loop 

300 <dt>background_iter 

301 <dd>bool; if True display image after each background subtraction in the measure PSF loop 

302 <dt>measure_iter 

303 <dd>bool; if True display image and sources at the end of each iteration of the measure PSF loop 

304 See @ref lsst.meas.astrom.displayAstrometry for the meaning of the various symbols. 

305 <dt>psf 

306 <dd>bool; if True display image and sources after PSF is measured; 

307 this will be identical to the final image displayed by measure_iter if measure_iter is true 

308 <dt>repair 

309 <dd>bool; if True display image and sources after final repair 

310 <dt>measure 

311 <dd>bool; if True display image and sources after final measurement 

312 </dl> 

313 

314 For example, put something like: 

315 @code{.py} 

316 import lsstDebug 

317 def DebugInfo(name): 

318 di = lsstDebug.getInfo(name) # N.b. lsstDebug.Info(name) would call us recursively 

319 if name == "lsst.pipe.tasks.characterizeImage": 

320 di.display = dict( 

321 repair = True, 

322 ) 

323 

324 return di 

325 

326 lsstDebug.Info = DebugInfo 

327 @endcode 

328 into your `debug.py` file and run `calibrateTask.py` with the `--debug` flag. 

329 

330 Some subtasks may have their own debug variables; see individual Task documentation. 

331 """ 

332 

333 # Example description used to live here, removed 2-20-2017 by MSSG 

334 

335 ConfigClass = CharacterizeImageConfig 

336 _DefaultName = "characterizeImage" 

337 RunnerClass = pipeBase.ButlerInitializedTaskRunner 

338 

339 def runQuantum(self, butlerQC, inputRefs, outputRefs): 

340 inputs = butlerQC.get(inputRefs) 

341 if 'exposureIdInfo' not in inputs.keys(): 

342 inputs['exposureIdInfo'] = ExposureIdInfo.fromDataId(butlerQC.quantum.dataId, "visit_detector") 

343 outputs = self.run(**inputs) 

344 butlerQC.put(outputs, outputRefs) 

345 

346 def __init__(self, butler=None, refObjLoader=None, schema=None, **kwargs): 

347 """!Construct a CharacterizeImageTask 

348 

349 @param[in] butler A butler object is passed to the refObjLoader constructor in case 

350 it is needed to load catalogs. May be None if a catalog-based star selector is 

351 not used, if the reference object loader constructor does not require a butler, 

352 or if a reference object loader is passed directly via the refObjLoader argument. 

353 @param[in] refObjLoader An instance of LoadReferenceObjectsTasks that supplies an 

354 external reference catalog to a catalog-based star selector. May be None if a 

355 catalog star selector is not used or the loader can be constructed from the 

356 butler argument. 

357 @param[in,out] schema initial schema (an lsst.afw.table.SourceTable), or None 

358 @param[in,out] kwargs other keyword arguments for lsst.pipe.base.CmdLineTask 

359 """ 

360 super().__init__(**kwargs) 

361 

362 if schema is None: 

363 schema = SourceTable.makeMinimalSchema() 

364 self.schema = schema 

365 self.makeSubtask("background") 

366 self.makeSubtask("installSimplePsf") 

367 self.makeSubtask("repair") 

368 self.makeSubtask("measurePsf", schema=self.schema) 

369 if self.config.doMeasurePsf and self.measurePsf.usesMatches: 

370 if not refObjLoader: 

371 self.makeSubtask('refObjLoader', butler=butler) 

372 refObjLoader = self.refObjLoader 

373 self.makeSubtask("ref_match", refObjLoader=refObjLoader) 

374 self.algMetadata = dafBase.PropertyList() 

375 self.makeSubtask('detection', schema=self.schema) 

376 if self.config.doDeblend: 

377 self.makeSubtask("deblend", schema=self.schema) 

378 self.makeSubtask('measurement', schema=self.schema, algMetadata=self.algMetadata) 

379 if self.config.doApCorr: 

380 self.makeSubtask('measureApCorr', schema=self.schema) 

381 self.makeSubtask('applyApCorr', schema=self.schema) 

382 self.makeSubtask('catalogCalculation', schema=self.schema) 

383 self._initialFrame = getDebugFrame(self._display, "frame") or 1 

384 self._frame = self._initialFrame 

385 self.schema.checkUnits(parse_strict=self.config.checkUnitsParseStrict) 

386 self.outputSchema = afwTable.SourceCatalog(self.schema) 

387 

388 def getInitOutputDatasets(self): 

389 outputCatSchema = afwTable.SourceCatalog(self.schema) 

390 outputCatSchema.getTable().setMetadata(self.algMetadata) 

391 return {'outputSchema': outputCatSchema} 

392 

393 @timeMethod 

394 def runDataRef(self, dataRef, exposure=None, background=None, doUnpersist=True): 

395 """!Characterize a science image and, if wanted, persist the results 

396 

397 This simply unpacks the exposure and passes it to the characterize method to do the work. 

398 

399 @param[in] dataRef: butler data reference for science exposure 

400 @param[in,out] exposure exposure to characterize (an lsst.afw.image.ExposureF or similar). 

401 If None then unpersist from "postISRCCD". 

402 The following changes are made, depending on the config: 

403 - set psf to the measured PSF 

404 - set apCorrMap to the measured aperture correction 

405 - subtract background 

406 - interpolate over cosmic rays 

407 - update detection and cosmic ray mask planes 

408 @param[in,out] background initial model of background already subtracted from exposure 

409 (an lsst.afw.math.BackgroundList). May be None if no background has been subtracted, 

410 which is typical for image characterization. 

411 A refined background model is output. 

412 @param[in] doUnpersist if True the exposure is read from the repository 

413 and the exposure and background arguments must be None; 

414 if False the exposure must be provided. 

415 True is intended for running as a command-line task, False for running as a subtask 

416 

417 @return same data as the characterize method 

418 """ 

419 self._frame = self._initialFrame # reset debug display frame 

420 self.log.info("Processing %s", dataRef.dataId) 

421 

422 if doUnpersist: 

423 if exposure is not None or background is not None: 

424 raise RuntimeError("doUnpersist true; exposure and background must be None") 

425 exposure = dataRef.get("postISRCCD", immediate=True) 

426 elif exposure is None: 

427 raise RuntimeError("doUnpersist false; exposure must be provided") 

428 

429 exposureIdInfo = dataRef.get("expIdInfo") 

430 

431 charRes = self.run( 

432 exposure=exposure, 

433 exposureIdInfo=exposureIdInfo, 

434 background=background, 

435 ) 

436 

437 if self.config.doWrite: 

438 dataRef.put(charRes.sourceCat, "icSrc") 

439 if self.config.doWriteExposure: 

440 dataRef.put(charRes.exposure, "icExp") 

441 dataRef.put(charRes.background, "icExpBackground") 

442 

443 return charRes 

444 

445 @timeMethod 

446 def run(self, exposure, exposureIdInfo=None, background=None): 

447 """!Characterize a science image 

448 

449 Peforms the following operations: 

450 - Iterate the following config.psfIterations times, or once if config.doMeasurePsf false: 

451 - detect and measure sources and estimate PSF (see detectMeasureAndEstimatePsf for details) 

452 - interpolate over cosmic rays 

453 - perform final measurement 

454 

455 @param[in,out] exposure exposure to characterize (an lsst.afw.image.ExposureF or similar). 

456 The following changes are made: 

457 - update or set psf 

458 - set apCorrMap 

459 - update detection and cosmic ray mask planes 

460 - subtract background and interpolate over cosmic rays 

461 @param[in] exposureIdInfo ID info for exposure (an lsst.obs.base.ExposureIdInfo). 

462 If not provided, returned SourceCatalog IDs will not be globally unique. 

463 @param[in,out] background initial model of background already subtracted from exposure 

464 (an lsst.afw.math.BackgroundList). May be None if no background has been subtracted, 

465 which is typical for image characterization. 

466 

467 @return pipe_base Struct containing these fields, all from the final iteration 

468 of detectMeasureAndEstimatePsf: 

469 - exposure: characterized exposure; image is repaired by interpolating over cosmic rays, 

470 mask is updated accordingly, and the PSF model is set 

471 - sourceCat: detected sources (an lsst.afw.table.SourceCatalog) 

472 - background: model of background subtracted from exposure (an lsst.afw.math.BackgroundList) 

473 - psfCellSet: spatial cells of PSF candidates (an lsst.afw.math.SpatialCellSet) 

474 """ 

475 self._frame = self._initialFrame # reset debug display frame 

476 

477 if not self.config.doMeasurePsf and not exposure.hasPsf(): 

478 self.log.info("CharacterizeImageTask initialized with 'simple' PSF.") 

479 self.installSimplePsf.run(exposure=exposure) 

480 

481 if exposureIdInfo is None: 

482 exposureIdInfo = ExposureIdInfo() 

483 

484 # subtract an initial estimate of background level 

485 background = self.background.run(exposure).background 

486 

487 psfIterations = self.config.psfIterations if self.config.doMeasurePsf else 1 

488 for i in range(psfIterations): 

489 dmeRes = self.detectMeasureAndEstimatePsf( 

490 exposure=exposure, 

491 exposureIdInfo=exposureIdInfo, 

492 background=background, 

493 ) 

494 

495 psf = dmeRes.exposure.getPsf() 

496 psfSigma = psf.computeShape().getDeterminantRadius() 

497 psfDimensions = psf.computeImage().getDimensions() 

498 medBackground = np.median(dmeRes.background.getImage().getArray()) 

499 self.log.info("iter %s; PSF sigma=%0.2f, dimensions=%s; median background=%0.2f", 

500 i + 1, psfSigma, psfDimensions, medBackground) 

501 

502 self.display("psf", exposure=dmeRes.exposure, sourceCat=dmeRes.sourceCat) 

503 

504 # perform final repair with final PSF 

505 self.repair.run(exposure=dmeRes.exposure) 

506 self.display("repair", exposure=dmeRes.exposure, sourceCat=dmeRes.sourceCat) 

507 

508 # perform final measurement with final PSF, including measuring and applying aperture correction, 

509 # if wanted 

510 self.measurement.run(measCat=dmeRes.sourceCat, exposure=dmeRes.exposure, 

511 exposureId=exposureIdInfo.expId) 

512 if self.config.doApCorr: 

513 apCorrMap = self.measureApCorr.run(exposure=dmeRes.exposure, catalog=dmeRes.sourceCat).apCorrMap 

514 dmeRes.exposure.getInfo().setApCorrMap(apCorrMap) 

515 self.applyApCorr.run(catalog=dmeRes.sourceCat, apCorrMap=exposure.getInfo().getApCorrMap()) 

516 self.catalogCalculation.run(dmeRes.sourceCat) 

517 

518 self.display("measure", exposure=dmeRes.exposure, sourceCat=dmeRes.sourceCat) 

519 

520 return pipeBase.Struct( 

521 exposure=dmeRes.exposure, 

522 sourceCat=dmeRes.sourceCat, 

523 background=dmeRes.background, 

524 psfCellSet=dmeRes.psfCellSet, 

525 

526 characterized=dmeRes.exposure, 

527 backgroundModel=dmeRes.background 

528 ) 

529 

530 @timeMethod 

531 def detectMeasureAndEstimatePsf(self, exposure, exposureIdInfo, background): 

532 """!Perform one iteration of detect, measure and estimate PSF 

533 

534 Performs the following operations: 

535 - if config.doMeasurePsf or not exposure.hasPsf(): 

536 - install a simple PSF model (replacing the existing one, if need be) 

537 - interpolate over cosmic rays with keepCRs=True 

538 - estimate background and subtract it from the exposure 

539 - detect, deblend and measure sources, and subtract a refined background model; 

540 - if config.doMeasurePsf: 

541 - measure PSF 

542 

543 @param[in,out] exposure exposure to characterize (an lsst.afw.image.ExposureF or similar) 

544 The following changes are made: 

545 - update or set psf 

546 - update detection and cosmic ray mask planes 

547 - subtract background 

548 @param[in] exposureIdInfo ID info for exposure (an lsst.obs_base.ExposureIdInfo) 

549 @param[in,out] background initial model of background already subtracted from exposure 

550 (an lsst.afw.math.BackgroundList). 

551 

552 @return pipe_base Struct containing these fields, all from the final iteration 

553 of detect sources, measure sources and estimate PSF: 

554 - exposure characterized exposure; image is repaired by interpolating over cosmic rays, 

555 mask is updated accordingly, and the PSF model is set 

556 - sourceCat detected sources (an lsst.afw.table.SourceCatalog) 

557 - background model of background subtracted from exposure (an lsst.afw.math.BackgroundList) 

558 - psfCellSet spatial cells of PSF candidates (an lsst.afw.math.SpatialCellSet) 

559 """ 

560 # install a simple PSF model, if needed or wanted 

561 if not exposure.hasPsf() or (self.config.doMeasurePsf and self.config.useSimplePsf): 

562 self.log.info("PSF estimation initialized with 'simple' PSF") 

563 self.installSimplePsf.run(exposure=exposure) 

564 

565 # run repair, but do not interpolate over cosmic rays (do that elsewhere, with the final PSF model) 

566 if self.config.requireCrForPsf: 

567 self.repair.run(exposure=exposure, keepCRs=True) 

568 else: 

569 try: 

570 self.repair.run(exposure=exposure, keepCRs=True) 

571 except LengthError: 

572 self.log.warning("Skipping cosmic ray detection: Too many CR pixels (max %0.f)", 

573 self.config.repair.cosmicray.nCrPixelMax) 

574 

575 self.display("repair_iter", exposure=exposure) 

576 

577 if background is None: 

578 background = BackgroundList() 

579 

580 sourceIdFactory = exposureIdInfo.makeSourceIdFactory() 

581 table = SourceTable.make(self.schema, sourceIdFactory) 

582 table.setMetadata(self.algMetadata) 

583 

584 detRes = self.detection.run(table=table, exposure=exposure, doSmooth=True) 

585 sourceCat = detRes.sources 

586 if detRes.fpSets.background: 

587 for bg in detRes.fpSets.background: 

588 background.append(bg) 

589 

590 if self.config.doDeblend: 

591 self.deblend.run(exposure=exposure, sources=sourceCat) 

592 

593 self.measurement.run(measCat=sourceCat, exposure=exposure, exposureId=exposureIdInfo.expId) 

594 

595 measPsfRes = pipeBase.Struct(cellSet=None) 

596 if self.config.doMeasurePsf: 

597 if self.measurePsf.usesMatches: 

598 matches = self.ref_match.loadAndMatch(exposure=exposure, sourceCat=sourceCat).matches 

599 else: 

600 matches = None 

601 measPsfRes = self.measurePsf.run(exposure=exposure, sources=sourceCat, matches=matches, 

602 expId=exposureIdInfo.expId) 

603 self.display("measure_iter", exposure=exposure, sourceCat=sourceCat) 

604 

605 return pipeBase.Struct( 

606 exposure=exposure, 

607 sourceCat=sourceCat, 

608 background=background, 

609 psfCellSet=measPsfRes.cellSet, 

610 ) 

611 

612 def getSchemaCatalogs(self): 

613 """Return a dict of empty catalogs for each catalog dataset produced by this task. 

614 """ 

615 sourceCat = SourceCatalog(self.schema) 

616 sourceCat.getTable().setMetadata(self.algMetadata) 

617 return {"icSrc": sourceCat} 

618 

619 def display(self, itemName, exposure, sourceCat=None): 

620 """Display exposure and sources on next frame, if display of itemName has been requested 

621 

622 @param[in] itemName name of item in debugInfo 

623 @param[in] exposure exposure to display 

624 @param[in] sourceCat source catalog to display 

625 """ 

626 val = getDebugFrame(self._display, itemName) 

627 if not val: 

628 return 

629 

630 displayAstrometry(exposure=exposure, sourceCat=sourceCat, frame=self._frame, pause=False) 

631 self._frame += 1