Coverage for python/lsst/pipe/tasks/multiBand.py: 25%

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1# This file is part of pipe_tasks. 

2# 

3# Developed for the LSST Data Management System. 

4# This product includes software developed by the LSST Project 

5# (https://www.lsst.org). 

6# See the COPYRIGHT file at the top-level directory of this distribution 

7# for details of code ownership. 

8# 

9# This program is free software: you can redistribute it and/or modify 

10# it under the terms of the GNU General Public License as published by 

11# the Free Software Foundation, either version 3 of the License, or 

12# (at your option) any later version. 

13# 

14# This program is distributed in the hope that it will be useful, 

15# but WITHOUT ANY WARRANTY; without even the implied warranty of 

16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

17# GNU General Public License for more details. 

18# 

19# You should have received a copy of the GNU General Public License 

20# along with this program. If not, see <https://www.gnu.org/licenses/>. 

21 

22__all__ = ["DetectCoaddSourcesConfig", "DetectCoaddSourcesTask"] 

23 

24from lsst.pipe.base import (Struct, PipelineTask, PipelineTaskConfig, PipelineTaskConnections) 

25import lsst.pipe.base.connectionTypes as cT 

26from lsst.pex.config import Field, ConfigurableField, ChoiceField 

27from lsst.meas.algorithms import DynamicDetectionTask, ReferenceObjectLoader, ScaleVarianceTask 

28from lsst.meas.base import ( 

29 SingleFrameMeasurementTask, 

30 ApplyApCorrTask, 

31 CatalogCalculationTask, 

32 SkyMapIdGeneratorConfig, 

33) 

34from lsst.meas.extensions.scarlet.io import updateCatalogFootprints 

35from lsst.meas.astrom import DirectMatchTask, denormalizeMatches 

36from lsst.pipe.tasks.setPrimaryFlags import SetPrimaryFlagsTask 

37from lsst.pipe.tasks.propagateSourceFlags import PropagateSourceFlagsTask 

38import lsst.afw.table as afwTable 

39import lsst.afw.math as afwMath 

40from lsst.daf.base import PropertyList 

41from lsst.skymap import BaseSkyMap 

42 

43# NOTE: these imports are a convenience so multiband users only have to import this file. 

44from .mergeDetections import MergeDetectionsConfig, MergeDetectionsTask # noqa: F401 

45from .mergeMeasurements import MergeMeasurementsConfig, MergeMeasurementsTask # noqa: F401 

46from .multiBandUtils import CullPeaksConfig # noqa: F401 

47from .deblendCoaddSourcesPipeline import DeblendCoaddSourcesSingleConfig # noqa: F401 

48from .deblendCoaddSourcesPipeline import DeblendCoaddSourcesSingleTask # noqa: F401 

49from .deblendCoaddSourcesPipeline import DeblendCoaddSourcesMultiConfig # noqa: F401 

50from .deblendCoaddSourcesPipeline import DeblendCoaddSourcesMultiTask # noqa: F401 

51 

52 

53""" 

54New set types: 

55* deepCoadd_det: detections from what used to be processCoadd (tract, patch, filter) 

56* deepCoadd_mergeDet: merged detections (tract, patch) 

57* deepCoadd_meas: measurements of merged detections (tract, patch, filter) 

58* deepCoadd_ref: reference sources (tract, patch) 

59All of these have associated *_schema catalogs that require no data ID and hold no records. 

60 

61In addition, we have a schema-only dataset, which saves the schema for the PeakRecords in 

62the mergeDet, meas, and ref dataset Footprints: 

63* deepCoadd_peak_schema 

64""" 

65 

66 

67############################################################################################################## 

68class DetectCoaddSourcesConnections(PipelineTaskConnections, 

69 dimensions=("tract", "patch", "band", "skymap"), 

70 defaultTemplates={"inputCoaddName": "deep", "outputCoaddName": "deep"}): 

71 detectionSchema = cT.InitOutput( 

72 doc="Schema of the detection catalog", 

73 name="{outputCoaddName}Coadd_det_schema", 

74 storageClass="SourceCatalog", 

75 ) 

76 exposure = cT.Input( 

77 doc="Exposure on which detections are to be performed", 

78 name="{inputCoaddName}Coadd", 

79 storageClass="ExposureF", 

80 dimensions=("tract", "patch", "band", "skymap") 

81 ) 

82 outputBackgrounds = cT.Output( 

83 doc="Output Backgrounds used in detection", 

84 name="{outputCoaddName}Coadd_calexp_background", 

85 storageClass="Background", 

86 dimensions=("tract", "patch", "band", "skymap") 

87 ) 

88 outputSources = cT.Output( 

89 doc="Detected sources catalog", 

90 name="{outputCoaddName}Coadd_det", 

91 storageClass="SourceCatalog", 

92 dimensions=("tract", "patch", "band", "skymap") 

93 ) 

94 outputExposure = cT.Output( 

95 doc="Exposure post detection", 

96 name="{outputCoaddName}Coadd_calexp", 

97 storageClass="ExposureF", 

98 dimensions=("tract", "patch", "band", "skymap") 

99 ) 

100 

101 

102class DetectCoaddSourcesConfig(PipelineTaskConfig, pipelineConnections=DetectCoaddSourcesConnections): 

103 """Configuration parameters for the DetectCoaddSourcesTask 

104 """ 

105 

106 doScaleVariance = Field(dtype=bool, default=True, doc="Scale variance plane using empirical noise?") 

107 scaleVariance = ConfigurableField(target=ScaleVarianceTask, doc="Variance rescaling") 

108 detection = ConfigurableField(target=DynamicDetectionTask, doc="Source detection") 

109 coaddName = Field(dtype=str, default="deep", doc="Name of coadd") 

110 hasFakes = Field( 

111 dtype=bool, 

112 default=False, 

113 doc="Should be set to True if fake sources have been inserted into the input data.", 

114 ) 

115 idGenerator = SkyMapIdGeneratorConfig.make_field() 

116 

117 def setDefaults(self): 

118 super().setDefaults() 

119 self.detection.thresholdType = "pixel_stdev" 

120 self.detection.isotropicGrow = True 

121 # Coadds are made from background-subtracted CCDs, so any background subtraction should be very basic 

122 self.detection.reEstimateBackground = False 

123 self.detection.background.useApprox = False 

124 self.detection.background.binSize = 4096 

125 self.detection.background.undersampleStyle = 'REDUCE_INTERP_ORDER' 

126 self.detection.doTempWideBackground = True # Suppress large footprints that overwhelm the deblender 

127 # Include band in packed data IDs that go into object IDs (None -> "as 

128 # many bands as are defined", rather than the default of zero). 

129 self.idGenerator.packer.n_bands = None 

130 

131 

132class DetectCoaddSourcesTask(PipelineTask): 

133 """Detect sources on a single filter coadd. 

134 

135 Coadding individual visits requires each exposure to be warped. This 

136 introduces covariance in the noise properties across pixels. Before 

137 detection, we correct the coadd variance by scaling the variance plane in 

138 the coadd to match the observed variance. This is an approximate 

139 approach -- strictly, we should propagate the full covariance matrix -- 

140 but it is simple and works well in practice. 

141 

142 After scaling the variance plane, we detect sources and generate footprints 

143 by delegating to the @ref SourceDetectionTask_ "detection" subtask. 

144 

145 DetectCoaddSourcesTask is meant to be run after assembling a coadded image 

146 in a given band. The purpose of the task is to update the background, 

147 detect all sources in a single band and generate a set of parent 

148 footprints. Subsequent tasks in the multi-band processing procedure will 

149 merge sources across bands and, eventually, perform forced photometry. 

150 

151 Parameters 

152 ---------- 

153 schema : `lsst.afw.table.Schema`, optional 

154 Initial schema for the output catalog, modified-in place to include all 

155 fields set by this task. If None, the source minimal schema will be used. 

156 **kwargs 

157 Additional keyword arguments. 

158 """ 

159 

160 _DefaultName = "detectCoaddSources" 

161 ConfigClass = DetectCoaddSourcesConfig 

162 

163 def __init__(self, schema=None, **kwargs): 

164 # N.B. Super is used here to handle the multiple inheritance of PipelineTasks, the init tree 

165 # call structure has been reviewed carefully to be sure super will work as intended. 

166 super().__init__(**kwargs) 

167 if schema is None: 

168 schema = afwTable.SourceTable.makeMinimalSchema() 

169 self.schema = schema 

170 self.makeSubtask("detection", schema=self.schema) 

171 if self.config.doScaleVariance: 

172 self.makeSubtask("scaleVariance") 

173 

174 self.detectionSchema = afwTable.SourceCatalog(self.schema) 

175 

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

177 inputs = butlerQC.get(inputRefs) 

178 idGenerator = self.config.idGenerator.apply(butlerQC.quantum.dataId) 

179 inputs["idFactory"] = idGenerator.make_table_id_factory() 

180 inputs["expId"] = idGenerator.catalog_id 

181 outputs = self.run(**inputs) 

182 butlerQC.put(outputs, outputRefs) 

183 

184 def run(self, exposure, idFactory, expId): 

185 """Run detection on an exposure. 

186 

187 First scale the variance plane to match the observed variance 

188 using ``ScaleVarianceTask``. Then invoke the ``SourceDetectionTask_`` "detection" subtask to 

189 detect sources. 

190 

191 Parameters 

192 ---------- 

193 exposure : `lsst.afw.image.Exposure` 

194 Exposure on which to detect (may be backround-subtracted and scaled, 

195 depending on configuration). 

196 idFactory : `lsst.afw.table.IdFactory` 

197 IdFactory to set source identifiers. 

198 expId : `int` 

199 Exposure identifier (integer) for RNG seed. 

200 

201 Returns 

202 ------- 

203 result : `lsst.pipe.base.Struct` 

204 Results as a struct with attributes: 

205 

206 ``sources`` 

207 Catalog of detections (`lsst.afw.table.SourceCatalog`). 

208 ``backgrounds`` 

209 List of backgrounds (`list`). 

210 """ 

211 if self.config.doScaleVariance: 

212 varScale = self.scaleVariance.run(exposure.maskedImage) 

213 exposure.getMetadata().add("VARIANCE_SCALE", varScale) 

214 backgrounds = afwMath.BackgroundList() 

215 table = afwTable.SourceTable.make(self.schema, idFactory) 

216 detections = self.detection.run(table, exposure, expId=expId) 

217 sources = detections.sources 

218 if hasattr(detections, "background") and detections.background: 

219 for bg in detections.background: 

220 backgrounds.append(bg) 

221 return Struct(outputSources=sources, outputBackgrounds=backgrounds, outputExposure=exposure) 

222 

223 

224class MeasureMergedCoaddSourcesConnections(PipelineTaskConnections, 

225 dimensions=("tract", "patch", "band", "skymap"), 

226 defaultTemplates={"inputCoaddName": "deep", 

227 "outputCoaddName": "deep", 

228 "deblendedCatalog": "deblendedFlux"}): 

229 inputSchema = cT.InitInput( 

230 doc="Input schema for measure merged task produced by a deblender or detection task", 

231 name="{inputCoaddName}Coadd_deblendedFlux_schema", 

232 storageClass="SourceCatalog" 

233 ) 

234 outputSchema = cT.InitOutput( 

235 doc="Output schema after all new fields are added by task", 

236 name="{inputCoaddName}Coadd_meas_schema", 

237 storageClass="SourceCatalog" 

238 ) 

239 refCat = cT.PrerequisiteInput( 

240 doc="Reference catalog used to match measured sources against known sources", 

241 name="ref_cat", 

242 storageClass="SimpleCatalog", 

243 dimensions=("skypix",), 

244 deferLoad=True, 

245 multiple=True 

246 ) 

247 exposure = cT.Input( 

248 doc="Input coadd image", 

249 name="{inputCoaddName}Coadd_calexp", 

250 storageClass="ExposureF", 

251 dimensions=("tract", "patch", "band", "skymap") 

252 ) 

253 skyMap = cT.Input( 

254 doc="SkyMap to use in processing", 

255 name=BaseSkyMap.SKYMAP_DATASET_TYPE_NAME, 

256 storageClass="SkyMap", 

257 dimensions=("skymap",), 

258 ) 

259 visitCatalogs = cT.Input( 

260 doc="Source catalogs for visits which overlap input tract, patch, band. Will be " 

261 "further filtered in the task for the purpose of propagating flags from image calibration " 

262 "and characterization to coadd objects. Only used in legacy PropagateVisitFlagsTask.", 

263 name="src", 

264 dimensions=("instrument", "visit", "detector"), 

265 storageClass="SourceCatalog", 

266 multiple=True 

267 ) 

268 sourceTableHandles = cT.Input( 

269 doc=("Source tables that are derived from the ``CalibrateTask`` sources. " 

270 "These tables contain astrometry and photometry flags, and optionally " 

271 "PSF flags."), 

272 name="sourceTable_visit", 

273 storageClass="DataFrame", 

274 dimensions=("instrument", "visit"), 

275 multiple=True, 

276 deferLoad=True, 

277 ) 

278 finalizedSourceTableHandles = cT.Input( 

279 doc=("Finalized source tables from ``FinalizeCalibrationTask``. These " 

280 "tables contain PSF flags from the finalized PSF estimation."), 

281 name="finalized_src_table", 

282 storageClass="DataFrame", 

283 dimensions=("instrument", "visit"), 

284 multiple=True, 

285 deferLoad=True, 

286 ) 

287 inputCatalog = cT.Input( 

288 doc=("Name of the input catalog to use." 

289 "If the single band deblender was used this should be 'deblendedFlux." 

290 "If the multi-band deblender was used this should be 'deblendedModel, " 

291 "or deblendedFlux if the multiband deblender was configured to output " 

292 "deblended flux catalogs. If no deblending was performed this should " 

293 "be 'mergeDet'"), 

294 name="{inputCoaddName}Coadd_{deblendedCatalog}", 

295 storageClass="SourceCatalog", 

296 dimensions=("tract", "patch", "band", "skymap"), 

297 ) 

298 scarletCatalog = cT.Input( 

299 doc="Catalogs produced by multiband deblending", 

300 name="{inputCoaddName}Coadd_deblendedCatalog", 

301 storageClass="SourceCatalog", 

302 dimensions=("tract", "patch", "skymap"), 

303 ) 

304 scarletModels = cT.Input( 

305 doc="Multiband scarlet models produced by the deblender", 

306 name="{inputCoaddName}Coadd_scarletModelData", 

307 storageClass="ScarletModelData", 

308 dimensions=("tract", "patch", "skymap"), 

309 ) 

310 outputSources = cT.Output( 

311 doc="Source catalog containing all the measurement information generated in this task", 

312 name="{outputCoaddName}Coadd_meas", 

313 dimensions=("tract", "patch", "band", "skymap"), 

314 storageClass="SourceCatalog", 

315 ) 

316 matchResult = cT.Output( 

317 doc="Match catalog produced by configured matcher, optional on doMatchSources", 

318 name="{outputCoaddName}Coadd_measMatch", 

319 dimensions=("tract", "patch", "band", "skymap"), 

320 storageClass="Catalog", 

321 ) 

322 denormMatches = cT.Output( 

323 doc="Denormalized Match catalog produced by configured matcher, optional on " 

324 "doWriteMatchesDenormalized", 

325 name="{outputCoaddName}Coadd_measMatchFull", 

326 dimensions=("tract", "patch", "band", "skymap"), 

327 storageClass="Catalog", 

328 ) 

329 

330 def __init__(self, *, config=None): 

331 super().__init__(config=config) 

332 if config.doPropagateFlags is False: 

333 self.inputs -= set(("visitCatalogs",)) 

334 self.inputs -= set(("sourceTableHandles",)) 

335 self.inputs -= set(("finalizedSourceTableHandles",)) 

336 elif config.propagateFlags.target == PropagateSourceFlagsTask: 

337 # New PropagateSourceFlagsTask does not use visitCatalogs. 

338 self.inputs -= set(("visitCatalogs",)) 

339 # Check for types of flags required. 

340 if not config.propagateFlags.source_flags: 

341 self.inputs -= set(("sourceTableHandles",)) 

342 if not config.propagateFlags.finalized_source_flags: 

343 self.inputs -= set(("finalizedSourceTableHandles",)) 

344 else: 

345 # Deprecated PropagateVisitFlagsTask uses visitCatalogs. 

346 self.inputs -= set(("sourceTableHandles",)) 

347 self.inputs -= set(("finalizedSourceTableHandles",)) 

348 

349 if config.inputCatalog == "deblendedCatalog": 

350 self.inputs -= set(("inputCatalog",)) 

351 

352 if not config.doAddFootprints: 

353 self.inputs -= set(("scarletModels",)) 

354 else: 

355 self.inputs -= set(("deblendedCatalog")) 

356 self.inputs -= set(("scarletModels",)) 

357 

358 if config.doMatchSources is False: 

359 self.outputs -= set(("matchResult",)) 

360 

361 if config.doWriteMatchesDenormalized is False: 

362 self.outputs -= set(("denormMatches",)) 

363 

364 

365class MeasureMergedCoaddSourcesConfig(PipelineTaskConfig, 

366 pipelineConnections=MeasureMergedCoaddSourcesConnections): 

367 """Configuration parameters for the MeasureMergedCoaddSourcesTask 

368 """ 

369 inputCatalog = ChoiceField( 

370 dtype=str, 

371 default="deblendedCatalog", 

372 allowed={ 

373 "deblendedCatalog": "Output catalog from ScarletDeblendTask", 

374 "deblendedFlux": "Output catalog from SourceDeblendTask", 

375 "mergeDet": "The merged detections before deblending." 

376 }, 

377 doc="The name of the input catalog.", 

378 ) 

379 doAddFootprints = Field(dtype=bool, 

380 default=True, 

381 doc="Whether or not to add footprints to the input catalog from scarlet models. " 

382 "This should be true whenever using the multi-band deblender, " 

383 "otherwise this should be False.") 

384 doConserveFlux = Field(dtype=bool, default=True, 

385 doc="Whether to use the deblender models as templates to re-distribute the flux " 

386 "from the 'exposure' (True), or to perform measurements on the deblender " 

387 "model footprints.") 

388 doStripFootprints = Field(dtype=bool, default=True, 

389 doc="Whether to strip footprints from the output catalog before " 

390 "saving to disk. " 

391 "This is usually done when using scarlet models to save disk space.") 

392 measurement = ConfigurableField(target=SingleFrameMeasurementTask, doc="Source measurement") 

393 setPrimaryFlags = ConfigurableField(target=SetPrimaryFlagsTask, doc="Set flags for primary tract/patch") 

394 doPropagateFlags = Field( 

395 dtype=bool, default=True, 

396 doc="Whether to match sources to CCD catalogs to propagate flags (to e.g. identify PSF stars)" 

397 ) 

398 propagateFlags = ConfigurableField(target=PropagateSourceFlagsTask, doc="Propagate source flags to coadd") 

399 doMatchSources = Field(dtype=bool, default=True, doc="Match sources to reference catalog?") 

400 match = ConfigurableField(target=DirectMatchTask, doc="Matching to reference catalog") 

401 doWriteMatchesDenormalized = Field( 

402 dtype=bool, 

403 default=False, 

404 doc=("Write reference matches in denormalized format? " 

405 "This format uses more disk space, but is more convenient to read."), 

406 ) 

407 coaddName = Field(dtype=str, default="deep", doc="Name of coadd") 

408 psfCache = Field(dtype=int, default=100, doc="Size of psfCache") 

409 checkUnitsParseStrict = Field( 

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

411 dtype=str, 

412 default="raise", 

413 ) 

414 doApCorr = Field( 

415 dtype=bool, 

416 default=True, 

417 doc="Apply aperture corrections" 

418 ) 

419 applyApCorr = ConfigurableField( 

420 target=ApplyApCorrTask, 

421 doc="Subtask to apply aperture corrections" 

422 ) 

423 doRunCatalogCalculation = Field( 

424 dtype=bool, 

425 default=True, 

426 doc='Run catalogCalculation task' 

427 ) 

428 catalogCalculation = ConfigurableField( 

429 target=CatalogCalculationTask, 

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

431 ) 

432 

433 hasFakes = Field( 

434 dtype=bool, 

435 default=False, 

436 doc="Should be set to True if fake sources have been inserted into the input data." 

437 ) 

438 idGenerator = SkyMapIdGeneratorConfig.make_field() 

439 

440 @property 

441 def refObjLoader(self): 

442 return self.match.refObjLoader 

443 

444 def setDefaults(self): 

445 super().setDefaults() 

446 self.measurement.plugins.names |= ['base_InputCount', 

447 'base_Variance', 

448 'base_LocalPhotoCalib', 

449 'base_LocalWcs'] 

450 self.measurement.plugins['base_PixelFlags'].masksFpAnywhere = ['CLIPPED', 'SENSOR_EDGE', 

451 'INEXACT_PSF', 'STREAK'] 

452 self.measurement.plugins['base_PixelFlags'].masksFpCenter = ['CLIPPED', 'SENSOR_EDGE', 

453 'INEXACT_PSF', 'STREAK'] 

454 

455 def validate(self): 

456 super().validate() 

457 

458 if not self.doMatchSources and self.doWriteMatchesDenormalized: 

459 raise ValueError("Cannot set doWriteMatchesDenormalized if doMatchSources is False.") 

460 

461 

462class MeasureMergedCoaddSourcesTask(PipelineTask): 

463 """Deblend sources from main catalog in each coadd seperately and measure. 

464 

465 Use peaks and footprints from a master catalog to perform deblending and 

466 measurement in each coadd. 

467 

468 Given a master input catalog of sources (peaks and footprints) or deblender 

469 outputs(including a HeavyFootprint in each band), measure each source on 

470 the coadd. Repeating this procedure with the same master catalog across 

471 multiple coadds will generate a consistent set of child sources. 

472 

473 The deblender retains all peaks and deblends any missing peaks (dropouts in 

474 that band) as PSFs. Source properties are measured and the @c is-primary 

475 flag (indicating sources with no children) is set. Visit flags are 

476 propagated to the coadd sources. 

477 

478 Optionally, we can match the coadd sources to an external reference 

479 catalog. 

480 

481 After MeasureMergedCoaddSourcesTask has been run on multiple coadds, we 

482 have a set of per-band catalogs. The next stage in the multi-band 

483 processing procedure will merge these measurements into a suitable catalog 

484 for driving forced photometry. 

485 

486 Parameters 

487 ---------- 

488 schema : ``lsst.afw.table.Schema`, optional 

489 The schema of the merged detection catalog used as input to this one. 

490 peakSchema : ``lsst.afw.table.Schema`, optional 

491 The schema of the PeakRecords in the Footprints in the merged detection catalog. 

492 refObjLoader : `lsst.meas.algorithms.ReferenceObjectLoader`, optional 

493 An instance of ReferenceObjectLoader that supplies an external reference 

494 catalog. May be None if the loader can be constructed from the butler argument or all steps 

495 requiring a reference catalog are disabled. 

496 initInputs : `dict`, optional 

497 Dictionary that can contain a key ``inputSchema`` containing the 

498 input schema. If present will override the value of ``schema``. 

499 **kwargs 

500 Additional keyword arguments. 

501 """ 

502 

503 _DefaultName = "measureCoaddSources" 

504 ConfigClass = MeasureMergedCoaddSourcesConfig 

505 

506 def __init__(self, schema=None, peakSchema=None, refObjLoader=None, initInputs=None, 

507 **kwargs): 

508 super().__init__(**kwargs) 

509 self.deblended = self.config.inputCatalog.startswith("deblended") 

510 self.inputCatalog = "Coadd_" + self.config.inputCatalog 

511 if initInputs is not None: 

512 schema = initInputs['inputSchema'].schema 

513 if schema is None: 

514 raise ValueError("Schema must be defined.") 

515 self.schemaMapper = afwTable.SchemaMapper(schema) 

516 self.schemaMapper.addMinimalSchema(schema) 

517 self.schema = self.schemaMapper.getOutputSchema() 

518 afwTable.CoordKey.addErrorFields(self.schema) 

519 self.algMetadata = PropertyList() 

520 self.makeSubtask("measurement", schema=self.schema, algMetadata=self.algMetadata) 

521 self.makeSubtask("setPrimaryFlags", schema=self.schema) 

522 if self.config.doMatchSources: 

523 self.makeSubtask("match", refObjLoader=refObjLoader) 

524 if self.config.doPropagateFlags: 

525 self.makeSubtask("propagateFlags", schema=self.schema) 

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

527 if self.config.doApCorr: 

528 self.makeSubtask("applyApCorr", schema=self.schema) 

529 if self.config.doRunCatalogCalculation: 

530 self.makeSubtask("catalogCalculation", schema=self.schema) 

531 

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

533 

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

535 inputs = butlerQC.get(inputRefs) 

536 

537 if self.config.doMatchSources: 

538 refObjLoader = ReferenceObjectLoader([ref.datasetRef.dataId for ref in inputRefs.refCat], 

539 inputs.pop('refCat'), 

540 name=self.config.connections.refCat, 

541 config=self.config.refObjLoader, 

542 log=self.log) 

543 self.match.setRefObjLoader(refObjLoader) 

544 

545 # Set psfcache 

546 # move this to run after gen2 deprecation 

547 inputs['exposure'].getPsf().setCacheCapacity(self.config.psfCache) 

548 

549 # Get unique integer ID for IdFactory and RNG seeds; only the latter 

550 # should really be used as the IDs all come from the input catalog. 

551 idGenerator = self.config.idGenerator.apply(butlerQC.quantum.dataId) 

552 inputs['exposureId'] = idGenerator.catalog_id 

553 

554 # Transform inputCatalog 

555 table = afwTable.SourceTable.make(self.schema, idGenerator.make_table_id_factory()) 

556 sources = afwTable.SourceCatalog(table) 

557 # Load the correct input catalog 

558 if "scarletCatalog" in inputs: 

559 inputCatalog = inputs.pop("scarletCatalog") 

560 catalogRef = inputRefs.scarletCatalog 

561 else: 

562 inputCatalog = inputs.pop("inputCatalog") 

563 catalogRef = inputRefs.inputCatalog 

564 sources.extend(inputCatalog, self.schemaMapper) 

565 del inputCatalog 

566 # Add the HeavyFootprints to the deblended sources 

567 if self.config.doAddFootprints: 

568 modelData = inputs.pop('scarletModels') 

569 if self.config.doConserveFlux: 

570 imageForRedistribution = inputs['exposure'] 

571 else: 

572 imageForRedistribution = None 

573 updateCatalogFootprints( 

574 modelData=modelData, 

575 catalog=sources, 

576 band=inputRefs.exposure.dataId["band"], 

577 imageForRedistribution=imageForRedistribution, 

578 removeScarletData=True, 

579 updateFluxColumns=True, 

580 ) 

581 table = sources.getTable() 

582 table.setMetadata(self.algMetadata) # Capture algorithm metadata to write out to the source catalog. 

583 inputs['sources'] = sources 

584 

585 skyMap = inputs.pop('skyMap') 

586 tractNumber = catalogRef.dataId['tract'] 

587 tractInfo = skyMap[tractNumber] 

588 patchInfo = tractInfo.getPatchInfo(catalogRef.dataId['patch']) 

589 skyInfo = Struct( 

590 skyMap=skyMap, 

591 tractInfo=tractInfo, 

592 patchInfo=patchInfo, 

593 wcs=tractInfo.getWcs(), 

594 bbox=patchInfo.getOuterBBox() 

595 ) 

596 inputs['skyInfo'] = skyInfo 

597 

598 if self.config.doPropagateFlags: 

599 if self.config.propagateFlags.target == PropagateSourceFlagsTask: 

600 # New version 

601 ccdInputs = inputs["exposure"].getInfo().getCoaddInputs().ccds 

602 inputs["ccdInputs"] = ccdInputs 

603 

604 if "sourceTableHandles" in inputs: 

605 sourceTableHandles = inputs.pop("sourceTableHandles") 

606 sourceTableHandleDict = {handle.dataId["visit"]: handle 

607 for handle in sourceTableHandles} 

608 inputs["sourceTableHandleDict"] = sourceTableHandleDict 

609 if "finalizedSourceTableHandles" in inputs: 

610 finalizedSourceTableHandles = inputs.pop("finalizedSourceTableHandles") 

611 finalizedSourceTableHandleDict = {handle.dataId["visit"]: handle 

612 for handle in finalizedSourceTableHandles} 

613 inputs["finalizedSourceTableHandleDict"] = finalizedSourceTableHandleDict 

614 else: 

615 # Deprecated legacy version 

616 # Filter out any visit catalog that is not coadd inputs 

617 ccdInputs = inputs['exposure'].getInfo().getCoaddInputs().ccds 

618 visitKey = ccdInputs.schema.find("visit").key 

619 ccdKey = ccdInputs.schema.find("ccd").key 

620 inputVisitIds = set() 

621 ccdRecordsWcs = {} 

622 for ccdRecord in ccdInputs: 

623 visit = ccdRecord.get(visitKey) 

624 ccd = ccdRecord.get(ccdKey) 

625 inputVisitIds.add((visit, ccd)) 

626 ccdRecordsWcs[(visit, ccd)] = ccdRecord.getWcs() 

627 

628 inputCatalogsToKeep = [] 

629 inputCatalogWcsUpdate = [] 

630 for i, dataRef in enumerate(inputRefs.visitCatalogs): 

631 key = (dataRef.dataId['visit'], dataRef.dataId['detector']) 

632 if key in inputVisitIds: 

633 inputCatalogsToKeep.append(inputs['visitCatalogs'][i]) 

634 inputCatalogWcsUpdate.append(ccdRecordsWcs[key]) 

635 inputs['visitCatalogs'] = inputCatalogsToKeep 

636 inputs['wcsUpdates'] = inputCatalogWcsUpdate 

637 inputs['ccdInputs'] = ccdInputs 

638 

639 outputs = self.run(**inputs) 

640 # Strip HeavyFootprints to save space on disk 

641 sources = outputs.outputSources 

642 butlerQC.put(outputs, outputRefs) 

643 

644 def run(self, exposure, sources, skyInfo, exposureId, ccdInputs=None, visitCatalogs=None, wcsUpdates=None, 

645 sourceTableHandleDict=None, finalizedSourceTableHandleDict=None): 

646 """Run measurement algorithms on the input exposure, and optionally populate the 

647 resulting catalog with extra information. 

648 

649 Parameters 

650 ---------- 

651 exposure : `lsst.afw.exposure.Exposure` 

652 The input exposure on which measurements are to be performed. 

653 sources : `lsst.afw.table.SourceCatalog` 

654 A catalog built from the results of merged detections, or 

655 deblender outputs. 

656 skyInfo : `lsst.pipe.base.Struct` 

657 A struct containing information about the position of the input exposure within 

658 a `SkyMap`, the `SkyMap`, its `Wcs`, and its bounding box. 

659 exposureId : `int` or `bytes` 

660 Packed unique number or bytes unique to the input exposure. 

661 ccdInputs : `lsst.afw.table.ExposureCatalog`, optional 

662 Catalog containing information on the individual visits which went into making 

663 the coadd. 

664 visitCatalogs : `list` of `lsst.afw.table.SourceCatalogs`, optional 

665 A list of source catalogs corresponding to measurements made on the individual 

666 visits which went into the input exposure. If None and butler is `None` then 

667 the task cannot propagate visit flags to the output catalog. 

668 Deprecated, to be removed with PropagateVisitFlagsTask. 

669 wcsUpdates : `list` of `lsst.afw.geom.SkyWcs`, optional 

670 If visitCatalogs is not `None` this should be a list of wcs objects which correspond 

671 to the input visits. Used to put all coordinates to common system. If `None` and 

672 butler is `None` then the task cannot propagate visit flags to the output catalog. 

673 Deprecated, to be removed with PropagateVisitFlagsTask. 

674 sourceTableHandleDict : `dict` [`int`, `lsst.daf.butler.DeferredDatasetHandle`], optional 

675 Dict for sourceTable_visit handles (key is visit) for propagating flags. 

676 These tables are derived from the ``CalibrateTask`` sources, and contain 

677 astrometry and photometry flags, and optionally PSF flags. 

678 finalizedSourceTableHandleDict : `dict` [`int`, `lsst.daf.butler.DeferredDatasetHandle`], optional 

679 Dict for finalized_src_table handles (key is visit) for propagating flags. 

680 These tables are derived from ``FinalizeCalibrationTask`` and contain 

681 PSF flags from the finalized PSF estimation. 

682 

683 Returns 

684 ------- 

685 results : `lsst.pipe.base.Struct` 

686 Results of running measurement task. Will contain the catalog in the 

687 sources attribute. Optionally will have results of matching to a 

688 reference catalog in the matchResults attribute, and denormalized 

689 matches in the denormMatches attribute. 

690 """ 

691 self.measurement.run(sources, exposure, exposureId=exposureId) 

692 

693 if self.config.doApCorr: 

694 self.applyApCorr.run( 

695 catalog=sources, 

696 apCorrMap=exposure.getInfo().getApCorrMap() 

697 ) 

698 

699 # TODO DM-11568: this contiguous check-and-copy could go away if we 

700 # reserve enough space during SourceDetection and/or SourceDeblend. 

701 # NOTE: sourceSelectors require contiguous catalogs, so ensure 

702 # contiguity now, so views are preserved from here on. 

703 if not sources.isContiguous(): 

704 sources = sources.copy(deep=True) 

705 

706 if self.config.doRunCatalogCalculation: 

707 self.catalogCalculation.run(sources) 

708 

709 self.setPrimaryFlags.run(sources, skyMap=skyInfo.skyMap, tractInfo=skyInfo.tractInfo, 

710 patchInfo=skyInfo.patchInfo) 

711 if self.config.doPropagateFlags: 

712 if self.config.propagateFlags.target == PropagateSourceFlagsTask: 

713 # New version 

714 self.propagateFlags.run( 

715 sources, 

716 ccdInputs, 

717 sourceTableHandleDict, 

718 finalizedSourceTableHandleDict 

719 ) 

720 else: 

721 # Legacy deprecated version 

722 self.propagateFlags.run( 

723 sources, 

724 ccdInputs, 

725 exposure.getWcs(), 

726 visitCatalogs, 

727 wcsUpdates 

728 ) 

729 

730 results = Struct() 

731 

732 if self.config.doMatchSources: 

733 matchResult = self.match.run(sources, exposure.getInfo().getFilter().bandLabel) 

734 matches = afwTable.packMatches(matchResult.matches) 

735 matches.table.setMetadata(matchResult.matchMeta) 

736 results.matchResult = matches 

737 if self.config.doWriteMatchesDenormalized: 

738 if matchResult.matches: 

739 denormMatches = denormalizeMatches(matchResult.matches, matchResult.matchMeta) 

740 else: 

741 self.log.warning("No matches, so generating dummy denormalized matches file") 

742 denormMatches = afwTable.BaseCatalog(afwTable.Schema()) 

743 denormMatches.setMetadata(PropertyList()) 

744 denormMatches.getMetadata().add("COMMENT", 

745 "This catalog is empty because no matches were found.") 

746 results.denormMatches = denormMatches 

747 results.denormMatches = denormMatches 

748 

749 results.outputSources = sources 

750 return results