Coverage for python/lsst/ip/diffim/subtractImages.py: 23%

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1# This file is part of ip_diffim. 

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 

22import numpy as np 

23 

24import lsst.afw.image 

25import lsst.afw.math 

26import lsst.geom 

27from lsst.ip.diffim.utils import getPsfFwhm 

28from lsst.meas.algorithms import ScaleVarianceTask 

29import lsst.pex.config 

30import lsst.pipe.base 

31from lsst.pipe.base import connectionTypes 

32from . import MakeKernelTask, DecorrelateALKernelTask 

33from lsst.utils.timer import timeMethod 

34 

35__all__ = ["AlardLuptonSubtractConfig", "AlardLuptonSubtractTask"] 

36 

37_dimensions = ("instrument", "visit", "detector") 

38_defaultTemplates = {"coaddName": "deep", "fakesType": ""} 

39 

40 

41class SubtractInputConnections(lsst.pipe.base.PipelineTaskConnections, 

42 dimensions=_dimensions, 

43 defaultTemplates=_defaultTemplates): 

44 template = connectionTypes.Input( 

45 doc="Input warped template to subtract.", 

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

47 storageClass="ExposureF", 

48 name="{fakesType}{coaddName}Diff_templateExp" 

49 ) 

50 science = connectionTypes.Input( 

51 doc="Input science exposure to subtract from.", 

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

53 storageClass="ExposureF", 

54 name="{fakesType}calexp" 

55 ) 

56 sources = connectionTypes.Input( 

57 doc="Sources measured on the science exposure; " 

58 "used to select sources for making the matching kernel.", 

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

60 storageClass="SourceCatalog", 

61 name="{fakesType}src" 

62 ) 

63 finalizedPsfApCorrCatalog = connectionTypes.Input( 

64 doc=("Per-visit finalized psf models and aperture correction maps. " 

65 "These catalogs use the detector id for the catalog id, " 

66 "sorted on id for fast lookup."), 

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

68 storageClass="ExposureCatalog", 

69 name="finalized_psf_ap_corr_catalog", 

70 ) 

71 

72 

73class SubtractImageOutputConnections(lsst.pipe.base.PipelineTaskConnections, 

74 dimensions=_dimensions, 

75 defaultTemplates=_defaultTemplates): 

76 difference = connectionTypes.Output( 

77 doc="Result of subtracting convolved template from science image.", 

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

79 storageClass="ExposureF", 

80 name="{fakesType}{coaddName}Diff_differenceTempExp", 

81 ) 

82 matchedTemplate = connectionTypes.Output( 

83 doc="Warped and PSF-matched template used to create `subtractedExposure`.", 

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

85 storageClass="ExposureF", 

86 name="{fakesType}{coaddName}Diff_matchedExp", 

87 ) 

88 

89 

90class AlardLuptonSubtractConnections(SubtractInputConnections, SubtractImageOutputConnections): 

91 

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

93 super().__init__(config=config) 

94 if not config.doApplyFinalizedPsf: 

95 self.inputs.remove("finalizedPsfApCorrCatalog") 

96 

97 

98class AlardLuptonSubtractConfig(lsst.pipe.base.PipelineTaskConfig, 

99 pipelineConnections=AlardLuptonSubtractConnections): 

100 mode = lsst.pex.config.ChoiceField( 

101 dtype=str, 

102 default="convolveTemplate", 

103 allowed={"auto": "Choose which image to convolve at runtime.", 

104 "convolveScience": "Only convolve the science image.", 

105 "convolveTemplate": "Only convolve the template image."}, 

106 doc="Choose which image to convolve at runtime, or require that a specific image is convolved." 

107 ) 

108 makeKernel = lsst.pex.config.ConfigurableField( 

109 target=MakeKernelTask, 

110 doc="Task to construct a matching kernel for convolution.", 

111 ) 

112 doDecorrelation = lsst.pex.config.Field( 

113 dtype=bool, 

114 default=True, 

115 doc="Perform diffim decorrelation to undo pixel correlation due to A&L " 

116 "kernel convolution? If True, also update the diffim PSF." 

117 ) 

118 decorrelate = lsst.pex.config.ConfigurableField( 

119 target=DecorrelateALKernelTask, 

120 doc="Task to decorrelate the image difference.", 

121 ) 

122 requiredTemplateFraction = lsst.pex.config.Field( 

123 dtype=float, 

124 default=0.1, 

125 doc="Abort task if template covers less than this fraction of pixels." 

126 " Setting to 0 will always attempt image subtraction." 

127 ) 

128 doScaleVariance = lsst.pex.config.Field( 

129 dtype=bool, 

130 default=True, 

131 doc="Scale variance of the image difference?" 

132 ) 

133 scaleVariance = lsst.pex.config.ConfigurableField( 

134 target=ScaleVarianceTask, 

135 doc="Subtask to rescale the variance of the template to the statistically expected level." 

136 ) 

137 doSubtractBackground = lsst.pex.config.Field( 

138 doc="Subtract the background fit when solving the kernel?", 

139 dtype=bool, 

140 default=True, 

141 ) 

142 doApplyFinalizedPsf = lsst.pex.config.Field( 

143 doc="Replace science Exposure's psf and aperture correction map" 

144 " with those in finalizedPsfApCorrCatalog.", 

145 dtype=bool, 

146 default=False, 

147 ) 

148 

149 forceCompatibility = lsst.pex.config.Field( 

150 dtype=bool, 

151 default=False, 

152 doc="Set up and run diffim using settings that ensure the results" 

153 "are compatible with the old version in pipe_tasks.", 

154 deprecated="This option is only for backwards compatibility purposes" 

155 " and will be removed after v24.", 

156 ) 

157 

158 def setDefaults(self): 

159 self.makeKernel.kernel.name = "AL" 

160 self.makeKernel.kernel.active.fitForBackground = self.doSubtractBackground 

161 self.makeKernel.kernel.active.spatialKernelOrder = 1 

162 self.makeKernel.kernel.active.spatialBgOrder = 2 

163 

164 def validate(self): 

165 if self.forceCompatibility and not (self.mode == "convolveTemplate"): 

166 msg = f"forceCompatibility=True requires mode='convolveTemplate', but mode was '{self.mode}'." 

167 raise lsst.pex.config.FieldValidationError(AlardLuptonSubtractConfig.forceCompatibility, 

168 self, msg) 

169 

170 

171class AlardLuptonSubtractTask(lsst.pipe.base.PipelineTask): 

172 """Compute the image difference of a science and template image using 

173 the Alard & Lupton (1998) algorithm. 

174 """ 

175 ConfigClass = AlardLuptonSubtractConfig 

176 _DefaultName = "alardLuptonSubtract" 

177 

178 def __init__(self, **kwargs): 

179 super().__init__(**kwargs) 

180 self.makeSubtask("decorrelate") 

181 self.makeSubtask("makeKernel") 

182 if self.config.doScaleVariance: 

183 self.makeSubtask("scaleVariance") 

184 

185 self.convolutionControl = lsst.afw.math.ConvolutionControl() 

186 # Normalization is an extra, unnecessary, calculation and will result 

187 # in mis-subtraction of the images if there are calibration errors. 

188 self.convolutionControl.setDoNormalize(False) 

189 self.convolutionControl.setDoCopyEdge(True) 

190 

191 def _applyExternalCalibrations(self, exposure, finalizedPsfApCorrCatalog): 

192 """Replace calibrations (psf, and ApCorrMap) on this exposure with external ones.". 

193 

194 Parameters 

195 ---------- 

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

197 Input exposure to adjust calibrations. 

198 finalizedPsfApCorrCatalog : `lsst.afw.table.ExposureCatalog` 

199 Exposure catalog with finalized psf models and aperture correction 

200 maps to be applied if config.doApplyFinalizedPsf=True. Catalog uses 

201 the detector id for the catalog id, sorted on id for fast lookup. 

202 

203 Returns 

204 ------- 

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

206 Exposure with adjusted calibrations. 

207 """ 

208 detectorId = exposure.info.getDetector().getId() 

209 

210 row = finalizedPsfApCorrCatalog.find(detectorId) 

211 if row is None: 

212 self.log.warning("Detector id %s not found in finalizedPsfApCorrCatalog; " 

213 "Using original psf.", detectorId) 

214 else: 

215 psf = row.getPsf() 

216 apCorrMap = row.getApCorrMap() 

217 if psf is None: 

218 self.log.warning("Detector id %s has None for psf in " 

219 "finalizedPsfApCorrCatalog; Using original psf and aperture correction.", 

220 detectorId) 

221 elif apCorrMap is None: 

222 self.log.warning("Detector id %s has None for apCorrMap in " 

223 "finalizedPsfApCorrCatalog; Using original psf and aperture correction.", 

224 detectorId) 

225 else: 

226 exposure.setPsf(psf) 

227 exposure.info.setApCorrMap(apCorrMap) 

228 

229 return exposure 

230 

231 @timeMethod 

232 def run(self, template, science, sources, finalizedPsfApCorrCatalog=None): 

233 """PSF match, subtract, and decorrelate two images. 

234 

235 Parameters 

236 ---------- 

237 template : `lsst.afw.image.ExposureF` 

238 Template exposure, warped to match the science exposure. 

239 science : `lsst.afw.image.ExposureF` 

240 Science exposure to subtract from the template. 

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

242 Identified sources on the science exposure. This catalog is used to 

243 select sources in order to perform the AL PSF matching on stamp 

244 images around them. 

245 finalizedPsfApCorrCatalog : `lsst.afw.table.ExposureCatalog`, optional 

246 Exposure catalog with finalized psf models and aperture correction 

247 maps to be applied if config.doApplyFinalizedPsf=True. Catalog uses 

248 the detector id for the catalog id, sorted on id for fast lookup. 

249 

250 Returns 

251 ------- 

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

253 ``difference`` : `lsst.afw.image.ExposureF` 

254 Result of subtracting template and science. 

255 ``matchedTemplate`` : `lsst.afw.image.ExposureF` 

256 Warped and PSF-matched template exposure. 

257 ``backgroundModel`` : `lsst.afw.math.Function2D` 

258 Background model that was fit while solving for the PSF-matching kernel 

259 ``psfMatchingKernel`` : `lsst.afw.math.Kernel` 

260 Kernel used to PSF-match the convolved image. 

261 

262 Raises 

263 ------ 

264 RuntimeError 

265 If an unsupported convolution mode is supplied. 

266 lsst.pipe.base.NoWorkFound 

267 Raised if fraction of good pixels, defined as not having NO_DATA 

268 set, is less then the configured requiredTemplateFraction 

269 """ 

270 self._validateExposures(template, science) 

271 if self.config.doApplyFinalizedPsf: 

272 self._applyExternalCalibrations(science, 

273 finalizedPsfApCorrCatalog=finalizedPsfApCorrCatalog) 

274 checkTemplateIsSufficient(template, self.log, 

275 requiredTemplateFraction=self.config.requiredTemplateFraction) 

276 if self.config.forceCompatibility: 

277 # Compatibility option to maintain old functionality 

278 # This should be removed in the future! 

279 self.log.warning("Running with `config.forceCompatibility=True`") 

280 sources = None 

281 sciencePsfSize = getPsfFwhm(science.psf) 

282 templatePsfSize = getPsfFwhm(template.psf) 

283 self.log.info("Science PSF size: %f", sciencePsfSize) 

284 self.log.info("Template PSF size: %f", templatePsfSize) 

285 if self.config.mode == "auto": 

286 if sciencePsfSize < templatePsfSize: 

287 self.log.info("Template PSF size is greater: convolving science image.") 

288 convolveTemplate = False 

289 else: 

290 self.log.info("Science PSF size is greater: convolving template image.") 

291 convolveTemplate = True 

292 elif self.config.mode == "convolveTemplate": 

293 self.log.info("`convolveTemplate` is set: convolving template image.") 

294 convolveTemplate = True 

295 elif self.config.mode == "convolveScience": 

296 self.log.info("`convolveScience` is set: convolving science image.") 

297 convolveTemplate = False 

298 else: 

299 raise RuntimeError("Cannot handle AlardLuptonSubtract mode: %s", self.config.mode) 

300 

301 if self.config.doScaleVariance and not self.config.forceCompatibility: 

302 # Scale the variance of the template and science images before 

303 # convolution, subtraction, or decorrelation so that they have the 

304 # correct ratio. 

305 templateVarFactor = self.scaleVariance.run(template.maskedImage) 

306 sciVarFactor = self.scaleVariance.run(science.maskedImage) 

307 self.log.info("Template variance scaling factor: %.2f", templateVarFactor) 

308 self.metadata.add("scaleTemplateVarianceFactor", templateVarFactor) 

309 self.log.info("Science variance scaling factor: %.2f", sciVarFactor) 

310 self.metadata.add("scaleScienceVarianceFactor", sciVarFactor) 

311 

312 kernelSources = self.makeKernel.selectKernelSources(template, science, 

313 candidateList=sources, 

314 preconvolved=False) 

315 if convolveTemplate: 

316 subtractResults = self.runConvolveTemplate(template, science, kernelSources) 

317 else: 

318 subtractResults = self.runConvolveScience(template, science, kernelSources) 

319 

320 if self.config.doScaleVariance and self.config.forceCompatibility: 

321 # The old behavior scaled the variance of the final image difference. 

322 diffimVarFactor = self.scaleVariance.run(subtractResults.difference.maskedImage) 

323 self.log.info("Diffim variance scaling factor: %.2f", diffimVarFactor) 

324 self.metadata.add("scaleDiffimVarianceFactor", diffimVarFactor) 

325 

326 return subtractResults 

327 

328 def runConvolveTemplate(self, template, science, sources): 

329 """Convolve the template image with a PSF-matching kernel and subtract 

330 from the science image. 

331 

332 Parameters 

333 ---------- 

334 template : `lsst.afw.image.ExposureF` 

335 Template exposure, warped to match the science exposure. 

336 science : `lsst.afw.image.ExposureF` 

337 Science exposure to subtract from the template. 

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

339 Identified sources on the science exposure. This catalog is used to 

340 select sources in order to perform the AL PSF matching on stamp 

341 images around them. 

342 

343 Returns 

344 ------- 

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

346 

347 ``difference`` : `lsst.afw.image.ExposureF` 

348 Result of subtracting template and science. 

349 ``matchedTemplate`` : `lsst.afw.image.ExposureF` 

350 Warped and PSF-matched template exposure. 

351 ``backgroundModel`` : `lsst.afw.math.Function2D` 

352 Background model that was fit while solving for the PSF-matching kernel 

353 ``psfMatchingKernel`` : `lsst.afw.math.Kernel` 

354 Kernel used to PSF-match the template to the science image. 

355 """ 

356 if self.config.forceCompatibility: 

357 # Compatibility option to maintain old behavior 

358 # This should be removed in the future! 

359 template = template[science.getBBox()] 

360 kernelResult = self.makeKernel.run(template, science, sources, preconvolved=False) 

361 

362 matchedTemplate = self._convolveExposure(template, kernelResult.psfMatchingKernel, 

363 self.convolutionControl, 

364 bbox=science.getBBox(), 

365 psf=science.psf, 

366 photoCalib=science.getPhotoCalib()) 

367 difference = _subtractImages(science, matchedTemplate, 

368 backgroundModel=(kernelResult.backgroundModel 

369 if self.config.doSubtractBackground else None)) 

370 correctedExposure = self.finalize(template, science, difference, kernelResult.psfMatchingKernel, 

371 templateMatched=True) 

372 

373 return lsst.pipe.base.Struct(difference=correctedExposure, 

374 matchedTemplate=matchedTemplate, 

375 matchedScience=science, 

376 backgroundModel=kernelResult.backgroundModel, 

377 psfMatchingKernel=kernelResult.psfMatchingKernel) 

378 

379 def runConvolveScience(self, template, science, sources): 

380 """Convolve the science image with a PSF-matching kernel and subtract the template image. 

381 

382 Parameters 

383 ---------- 

384 template : `lsst.afw.image.ExposureF` 

385 Template exposure, warped to match the science exposure. 

386 science : `lsst.afw.image.ExposureF` 

387 Science exposure to subtract from the template. 

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

389 Identified sources on the science exposure. This catalog is used to 

390 select sources in order to perform the AL PSF matching on stamp 

391 images around them. 

392 

393 Returns 

394 ------- 

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

396 

397 ``difference`` : `lsst.afw.image.ExposureF` 

398 Result of subtracting template and science. 

399 ``matchedTemplate`` : `lsst.afw.image.ExposureF` 

400 Warped template exposure. Note that in this case, the template 

401 is not PSF-matched to the science image. 

402 ``backgroundModel`` : `lsst.afw.math.Function2D` 

403 Background model that was fit while solving for the PSF-matching kernel 

404 ``psfMatchingKernel`` : `lsst.afw.math.Kernel` 

405 Kernel used to PSF-match the science image to the template. 

406 """ 

407 if self.config.forceCompatibility: 

408 # Compatibility option to maintain old behavior 

409 # This should be removed in the future! 

410 template = template[science.getBBox()] 

411 kernelResult = self.makeKernel.run(science, template, sources, preconvolved=False) 

412 modelParams = kernelResult.backgroundModel.getParameters() 

413 # We must invert the background model if the matching kernel is solved for the science image. 

414 kernelResult.backgroundModel.setParameters([-p for p in modelParams]) 

415 

416 kernelImage = lsst.afw.image.ImageD(kernelResult.psfMatchingKernel.getDimensions()) 

417 norm = kernelResult.psfMatchingKernel.computeImage(kernelImage, doNormalize=False) 

418 

419 matchedScience = self._convolveExposure(science, kernelResult.psfMatchingKernel, 

420 self.convolutionControl, 

421 psf=template.psf) 

422 

423 # Place back on native photometric scale 

424 matchedScience.maskedImage /= norm 

425 matchedTemplate = template.clone()[science.getBBox()] 

426 matchedTemplate.maskedImage /= norm 

427 matchedTemplate.setPhotoCalib(science.getPhotoCalib()) 

428 

429 difference = _subtractImages(matchedScience, matchedTemplate, 

430 backgroundModel=(kernelResult.backgroundModel 

431 if self.config.doSubtractBackground else None)) 

432 

433 correctedExposure = self.finalize(template, science, difference, kernelResult.psfMatchingKernel, 

434 templateMatched=False) 

435 

436 return lsst.pipe.base.Struct(difference=correctedExposure, 

437 matchedTemplate=matchedTemplate, 

438 matchedScience=matchedScience, 

439 backgroundModel=kernelResult.backgroundModel, 

440 psfMatchingKernel=kernelResult.psfMatchingKernel,) 

441 

442 def finalize(self, template, science, difference, kernel, 

443 templateMatched=True, 

444 preConvMode=False, 

445 preConvKernel=None, 

446 spatiallyVarying=False): 

447 """Decorrelate the difference image to undo the noise correlations 

448 caused by convolution. 

449 

450 Parameters 

451 ---------- 

452 template : `lsst.afw.image.ExposureF` 

453 Template exposure, warped to match the science exposure. 

454 science : `lsst.afw.image.ExposureF` 

455 Science exposure to subtract from the template. 

456 difference : `lsst.afw.image.ExposureF` 

457 Result of subtracting template and science. 

458 kernel : `lsst.afw.math.Kernel` 

459 An (optionally spatially-varying) PSF matching kernel 

460 templateMatched : `bool`, optional 

461 Was the template PSF-matched to the science image? 

462 preConvMode : `bool`, optional 

463 Was the science image preconvolved with its own PSF 

464 before PSF matching the template? 

465 preConvKernel : `lsst.afw.detection.Psf`, optional 

466 If not `None`, then the science image was pre-convolved with 

467 (the reflection of) this kernel. Must be normalized to sum to 1. 

468 spatiallyVarying : `bool`, optional 

469 Compute the decorrelation kernel spatially varying across the image? 

470 

471 Returns 

472 ------- 

473 correctedExposure : `lsst.afw.image.ExposureF` 

474 The decorrelated image difference. 

475 """ 

476 # Erase existing detection mask planes. 

477 # We don't want the detection mask from the science image 

478 mask = difference.mask 

479 mask &= ~(mask.getPlaneBitMask("DETECTED") | mask.getPlaneBitMask("DETECTED_NEGATIVE")) 

480 

481 if self.config.doDecorrelation: 

482 self.log.info("Decorrelating image difference.") 

483 correctedExposure = self.decorrelate.run(science, template[science.getBBox()], difference, kernel, 

484 templateMatched=templateMatched, 

485 preConvMode=preConvMode, 

486 preConvKernel=preConvKernel, 

487 spatiallyVarying=spatiallyVarying).correctedExposure 

488 else: 

489 self.log.info("NOT decorrelating image difference.") 

490 correctedExposure = difference 

491 return correctedExposure 

492 

493 @staticmethod 

494 def _validateExposures(template, science): 

495 """Check that the WCS of the two Exposures match, and the template bbox 

496 contains the science bbox. 

497 

498 Parameters 

499 ---------- 

500 template : `lsst.afw.image.ExposureF` 

501 Template exposure, warped to match the science exposure. 

502 science : `lsst.afw.image.ExposureF` 

503 Science exposure to subtract from the template. 

504 

505 Raises 

506 ------ 

507 AssertionError 

508 Raised if the WCS of the template is not equal to the science WCS, 

509 or if the science image is not fully contained in the template 

510 bounding box. 

511 """ 

512 assert template.wcs == science.wcs,\ 

513 "Template and science exposure WCS are not identical." 

514 templateBBox = template.getBBox() 

515 scienceBBox = science.getBBox() 

516 

517 assert templateBBox.contains(scienceBBox),\ 

518 "Template bbox does not contain all of the science image." 

519 

520 @staticmethod 

521 def _convolveExposure(exposure, kernel, convolutionControl, 

522 bbox=None, 

523 psf=None, 

524 photoCalib=None): 

525 """Convolve an exposure with the given kernel. 

526 

527 Parameters 

528 ---------- 

529 exposure : `lsst.afw.Exposure` 

530 exposure to convolve. 

531 kernel : `lsst.afw.math.LinearCombinationKernel` 

532 PSF matching kernel computed in the ``makeKernel`` subtask. 

533 convolutionControl : `lsst.afw.math.ConvolutionControl` 

534 Configuration for convolve algorithm. 

535 bbox : `lsst.geom.Box2I`, optional 

536 Bounding box to trim the convolved exposure to. 

537 psf : `lsst.afw.detection.Psf`, optional 

538 Point spread function (PSF) to set for the convolved exposure. 

539 photoCalib : `lsst.afw.image.PhotoCalib`, optional 

540 Photometric calibration of the convolved exposure. 

541 

542 Returns 

543 ------- 

544 convolvedExp : `lsst.afw.Exposure` 

545 The convolved image. 

546 """ 

547 convolvedExposure = exposure.clone() 

548 if psf is not None: 

549 convolvedExposure.setPsf(psf) 

550 if photoCalib is not None: 

551 convolvedExposure.setPhotoCalib(photoCalib) 

552 convolvedImage = lsst.afw.image.MaskedImageF(exposure.getBBox()) 

553 lsst.afw.math.convolve(convolvedImage, exposure.maskedImage, kernel, convolutionControl) 

554 convolvedExposure.setMaskedImage(convolvedImage) 

555 if bbox is None: 

556 return convolvedExposure 

557 else: 

558 return convolvedExposure[bbox] 

559 

560 

561def checkTemplateIsSufficient(templateExposure, logger, requiredTemplateFraction=0.): 

562 """Raise NoWorkFound if template coverage < requiredTemplateFraction 

563 

564 Parameters 

565 ---------- 

566 templateExposure : `lsst.afw.image.ExposureF` 

567 The template exposure to check 

568 logger : `lsst.log.Log` 

569 Logger for printing output. 

570 requiredTemplateFraction : `float`, optional 

571 Fraction of pixels of the science image required to have coverage 

572 in the template. 

573 

574 Raises 

575 ------ 

576 lsst.pipe.base.NoWorkFound 

577 Raised if fraction of good pixels, defined as not having NO_DATA 

578 set, is less then the configured requiredTemplateFraction 

579 """ 

580 # Count the number of pixels with the NO_DATA mask bit set 

581 # counting NaN pixels is insufficient because pixels without data are often intepolated over) 

582 pixNoData = np.count_nonzero(templateExposure.mask.array 

583 & templateExposure.mask.getPlaneBitMask('NO_DATA')) 

584 pixGood = templateExposure.getBBox().getArea() - pixNoData 

585 logger.info("template has %d good pixels (%.1f%%)", pixGood, 

586 100*pixGood/templateExposure.getBBox().getArea()) 

587 

588 if pixGood/templateExposure.getBBox().getArea() < requiredTemplateFraction: 

589 message = ("Insufficient Template Coverage. (%.1f%% < %.1f%%) Not attempting subtraction. " 

590 "To force subtraction, set config requiredTemplateFraction=0." % ( 

591 100*pixGood/templateExposure.getBBox().getArea(), 

592 100*requiredTemplateFraction)) 

593 raise lsst.pipe.base.NoWorkFound(message) 

594 

595 

596def _subtractImages(science, template, backgroundModel=None): 

597 """Subtract template from science, propagating relevant metadata. 

598 

599 Parameters 

600 ---------- 

601 science : `lsst.afw.Exposure` 

602 The input science image. 

603 template : `lsst.afw.Exposure` 

604 The template to subtract from the science image. 

605 backgroundModel : `lsst.afw.MaskedImage`, optional 

606 Differential background model 

607 

608 Returns 

609 ------- 

610 difference : `lsst.afw.Exposure` 

611 The subtracted image. 

612 """ 

613 difference = science.clone() 

614 if backgroundModel is not None: 

615 difference.maskedImage -= backgroundModel 

616 difference.maskedImage -= template.maskedImage 

617 return difference