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1# This file is part of cp_pipe 

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 <http://www.gnu.org/licenses/>. 

21import itertools 

22import numpy as np 

23 

24from collections import defaultdict 

25 

26import lsst.pipe.base as pipeBase 

27import lsst.pipe.base.connectionTypes as cT 

28 

29from lsstDebug import getDebugFrame 

30from lsst.afw.detection import FootprintSet, Threshold 

31from lsst.afw.display import getDisplay 

32from lsst.pex.config import Config, Field, ListField, ConfigurableField 

33from lsst.ip.isr import CrosstalkCalib, IsrProvenance 

34from lsst.pipe.tasks.getRepositoryData import DataRefListRunner 

35from lsst.cp.pipe.utils import (ddict2dict, sigmaClipCorrection) 

36 

37from ._lookupStaticCalibration import lookupStaticCalibration 

38 

39__all__ = ["CrosstalkExtractConfig", "CrosstalkExtractTask", 

40 "CrosstalkSolveTask", "CrosstalkSolveConfig", 

41 "MeasureCrosstalkConfig", "MeasureCrosstalkTask"] 

42 

43 

44class CrosstalkExtractConnections(pipeBase.PipelineTaskConnections, 

45 dimensions=("instrument", "exposure", "detector")): 

46 inputExp = cT.Input( 

47 name="crosstalkInputs", 

48 doc="Input post-ISR processed exposure to measure crosstalk from.", 

49 storageClass="Exposure", 

50 dimensions=("instrument", "exposure", "detector"), 

51 multiple=False, 

52 ) 

53 # TODO: Depends on DM-21904. 

54 sourceExp = cT.Input( 

55 name="crosstalkSource", 

56 doc="Post-ISR exposure to measure for inter-chip crosstalk onto inputExp.", 

57 storageClass="Exposure", 

58 dimensions=("instrument", "exposure", "detector"), 

59 multiple=True, 

60 deferLoad=True, 

61 # lookupFunction=None, 

62 ) 

63 

64 outputRatios = cT.Output( 

65 name="crosstalkRatios", 

66 doc="Extracted crosstalk pixel ratios.", 

67 storageClass="StructuredDataDict", 

68 dimensions=("instrument", "exposure", "detector"), 

69 ) 

70 outputFluxes = cT.Output( 

71 name="crosstalkFluxes", 

72 doc="Source pixel fluxes used in ratios.", 

73 storageClass="StructuredDataDict", 

74 dimensions=("instrument", "exposure", "detector"), 

75 ) 

76 

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

78 super().__init__(config=config) 

79 # Discard sourceExp until DM-21904 allows full interchip 

80 # measurements. 

81 self.inputs.discard("sourceExp") 

82 

83 

84class CrosstalkExtractConfig(pipeBase.PipelineTaskConfig, 

85 pipelineConnections=CrosstalkExtractConnections): 

86 """Configuration for the measurement of pixel ratios. 

87 """ 

88 doMeasureInterchip = Field( 

89 dtype=bool, 

90 default=False, 

91 doc="Measure inter-chip crosstalk as well?", 

92 ) 

93 threshold = Field( 

94 dtype=float, 

95 default=30000, 

96 doc="Minimum level of source pixels for which to measure crosstalk." 

97 ) 

98 ignoreSaturatedPixels = Field( 

99 dtype=bool, 

100 default=True, 

101 doc="Should saturated pixels be ignored?" 

102 ) 

103 badMask = ListField( 

104 dtype=str, 

105 default=["BAD", "INTRP"], 

106 doc="Mask planes to ignore when identifying source pixels." 

107 ) 

108 isTrimmed = Field( 

109 dtype=bool, 

110 default=True, 

111 doc="Is the input exposure trimmed?" 

112 ) 

113 

114 def validate(self): 

115 super().validate() 

116 

117 # Ensure the handling of the SAT mask plane is consistent 

118 # with the ignoreSaturatedPixels value. 

119 if self.ignoreSaturatedPixels: 

120 if 'SAT' not in self.badMask: 

121 self.badMask.append('SAT') 

122 else: 

123 if 'SAT' in self.badMask: 

124 self.badMask = [mask for mask in self.badMask if mask != 'SAT'] 

125 

126 

127class CrosstalkExtractTask(pipeBase.PipelineTask, 

128 pipeBase.CmdLineTask): 

129 """Task to measure pixel ratios to find crosstalk. 

130 """ 

131 ConfigClass = CrosstalkExtractConfig 

132 _DefaultName = 'cpCrosstalkExtract' 

133 

134 def run(self, inputExp, sourceExps=[]): 

135 """Measure pixel ratios between amplifiers in inputExp. 

136 

137 Extract crosstalk ratios between different amplifiers. 

138 

139 For pixels above ``config.threshold``, we calculate the ratio 

140 between each background-subtracted target amp and the source 

141 amp. We return a list of ratios for each pixel for each 

142 target/source combination, as nested dictionary containing the 

143 ratio. 

144 

145 Parameters 

146 ---------- 

147 inputExp : `lsst.afw.image.Exposure` 

148 Input exposure to measure pixel ratios on. 

149 sourceExp : `list` [`lsst.afw.image.Exposure`], optional 

150 List of chips to use as sources to measure inter-chip 

151 crosstalk. 

152 

153 Returns 

154 ------- 

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

156 The results struct containing: 

157 

158 ``outputRatios`` : `dict` [`dict` [`dict` [`dict` [`list`]]]] 

159 A catalog of ratio lists. The dictionaries are 

160 indexed such that: 

161 outputRatios[targetChip][sourceChip][targetAmp][sourceAmp] 

162 contains the ratio list for that combination. 

163 ``outputFluxes`` : `dict` [`dict` [`list`]] 

164 A catalog of flux lists. The dictionaries are 

165 indexed such that: 

166 outputFluxes[sourceChip][sourceAmp] 

167 contains the flux list used in the outputRatios. 

168 

169 Notes 

170 ----- 

171 The lsstDebug.Info() method can be rewritten for __name__ = 

172 `lsst.cp.pipe.measureCrosstalk`, and supports the parameters: 

173 

174 debug.display['extract'] : `bool` 

175 Display the exposure under consideration, with the pixels used 

176 for crosstalk measurement indicated by the DETECTED mask plane. 

177 debug.display['pixels'] : `bool` 

178 Display a plot of the ratio calculated for each pixel used in this 

179 exposure, split by amplifier pairs. The median value is listed 

180 for reference. 

181 """ 

182 outputRatios = defaultdict(lambda: defaultdict(dict)) 

183 outputFluxes = defaultdict(lambda: defaultdict(dict)) 

184 

185 threshold = self.config.threshold 

186 badPixels = list(self.config.badMask) 

187 

188 targetDetector = inputExp.getDetector() 

189 targetChip = targetDetector.getName() 

190 

191 # Always look at the target chip first, then go to any other supplied exposures. 

192 sourceExtractExps = [inputExp] 

193 sourceExtractExps.extend(sourceExps) 

194 

195 self.log.info("Measuring full detector background for target: %s", targetChip) 

196 targetIm = inputExp.getMaskedImage() 

197 FootprintSet(targetIm, Threshold(threshold), "DETECTED") 

198 detected = targetIm.getMask().getPlaneBitMask("DETECTED") 

199 bg = CrosstalkCalib.calculateBackground(targetIm, badPixels + ["DETECTED"]) 

200 

201 self.debugView('extract', inputExp) 

202 

203 for sourceExp in sourceExtractExps: 

204 sourceDetector = sourceExp.getDetector() 

205 sourceChip = sourceDetector.getName() 

206 sourceIm = sourceExp.getMaskedImage() 

207 bad = sourceIm.getMask().getPlaneBitMask(badPixels) 

208 self.log.info("Measuring crosstalk from source: %s", sourceChip) 

209 

210 if sourceExp != inputExp: 

211 FootprintSet(sourceIm, Threshold(threshold), "DETECTED") 

212 detected = sourceIm.getMask().getPlaneBitMask("DETECTED") 

213 

214 # The dictionary of amp-to-amp ratios for this pair of source->target detectors. 

215 ratioDict = defaultdict(lambda: defaultdict(list)) 

216 extractedCount = 0 

217 

218 for sourceAmp in sourceDetector: 

219 sourceAmpName = sourceAmp.getName() 

220 sourceAmpBBox = sourceAmp.getBBox() if self.config.isTrimmed else sourceAmp.getRawDataBBox() 

221 sourceAmpImage = sourceIm[sourceAmpBBox] 

222 sourceMask = sourceAmpImage.mask.array 

223 select = ((sourceMask & detected > 0) 

224 & (sourceMask & bad == 0) 

225 & np.isfinite(sourceAmpImage.image.array)) 

226 count = np.sum(select) 

227 self.log.debug(" Source amplifier: %s", sourceAmpName) 

228 

229 outputFluxes[sourceChip][sourceAmpName] = sourceAmpImage.image.array[select].tolist() 

230 

231 for targetAmp in targetDetector: 

232 # iterate over targetExposure 

233 targetAmpName = targetAmp.getName() 

234 if sourceAmpName == targetAmpName and sourceChip == targetChip: 

235 ratioDict[sourceAmpName][targetAmpName] = [] 

236 continue 

237 self.log.debug(" Target amplifier: %s", targetAmpName) 

238 

239 targetAmpImage = CrosstalkCalib.extractAmp(targetIm.image, 

240 targetAmp, sourceAmp, 

241 isTrimmed=self.config.isTrimmed) 

242 ratios = (targetAmpImage.array[select] - bg)/sourceAmpImage.image.array[select] 

243 ratioDict[targetAmpName][sourceAmpName] = ratios.tolist() 

244 extractedCount += count 

245 

246 self.debugPixels('pixels', 

247 sourceAmpImage.image.array[select], 

248 targetAmpImage.array[select] - bg, 

249 sourceAmpName, targetAmpName) 

250 

251 self.log.info("Extracted %d pixels from %s -> %s (targetBG: %f)", 

252 extractedCount, sourceChip, targetChip, bg) 

253 outputRatios[targetChip][sourceChip] = ratioDict 

254 

255 return pipeBase.Struct( 

256 outputRatios=ddict2dict(outputRatios), 

257 outputFluxes=ddict2dict(outputFluxes) 

258 ) 

259 

260 def debugView(self, stepname, exposure): 

261 """Utility function to examine the image being processed. 

262 

263 Parameters 

264 ---------- 

265 stepname : `str` 

266 State of processing to view. 

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

268 Exposure to view. 

269 """ 

270 frame = getDebugFrame(self._display, stepname) 

271 if frame: 

272 display = getDisplay(frame) 

273 display.scale('asinh', 'zscale') 

274 display.mtv(exposure) 

275 

276 prompt = "Press Enter to continue: " 

277 while True: 

278 ans = input(prompt).lower() 

279 if ans in ("", "c",): 

280 break 

281 

282 def debugPixels(self, stepname, pixelsIn, pixelsOut, sourceName, targetName): 

283 """Utility function to examine the CT ratio pixel values. 

284 

285 Parameters 

286 ---------- 

287 stepname : `str` 

288 State of processing to view. 

289 pixelsIn : `np.ndarray` 

290 Pixel values from the potential crosstalk source. 

291 pixelsOut : `np.ndarray` 

292 Pixel values from the potential crosstalk target. 

293 sourceName : `str` 

294 Source amplifier name 

295 targetName : `str` 

296 Target amplifier name 

297 """ 

298 frame = getDebugFrame(self._display, stepname) 

299 if frame: 

300 import matplotlib.pyplot as plt 

301 figure = plt.figure(1) 

302 figure.clear() 

303 

304 axes = figure.add_axes((0.1, 0.1, 0.8, 0.8)) 

305 axes.plot(pixelsIn, pixelsOut / pixelsIn, 'k+') 

306 plt.xlabel("Source amplifier pixel value") 

307 plt.ylabel("Measured pixel ratio") 

308 plt.title(f"(Source {sourceName} -> Target {targetName}) median ratio: " 

309 f"{(np.median(pixelsOut / pixelsIn))}") 

310 figure.show() 

311 

312 prompt = "Press Enter to continue: " 

313 while True: 

314 ans = input(prompt).lower() 

315 if ans in ("", "c",): 

316 break 

317 plt.close() 

318 

319 

320class CrosstalkSolveConnections(pipeBase.PipelineTaskConnections, 

321 dimensions=("instrument", "detector")): 

322 inputRatios = cT.Input( 

323 name="crosstalkRatios", 

324 doc="Ratios measured for an input exposure.", 

325 storageClass="StructuredDataDict", 

326 dimensions=("instrument", "exposure", "detector"), 

327 multiple=True, 

328 ) 

329 inputFluxes = cT.Input( 

330 name="crosstalkFluxes", 

331 doc="Fluxes of CT source pixels, for nonlinear fits.", 

332 storageClass="StructuredDataDict", 

333 dimensions=("instrument", "exposure", "detector"), 

334 multiple=True, 

335 ) 

336 camera = cT.PrerequisiteInput( 

337 name="camera", 

338 doc="Camera the input data comes from.", 

339 storageClass="Camera", 

340 dimensions=("instrument",), 

341 isCalibration=True, 

342 lookupFunction=lookupStaticCalibration, 

343 ) 

344 

345 outputCrosstalk = cT.Output( 

346 name="crosstalk", 

347 doc="Output proposed crosstalk calibration.", 

348 storageClass="CrosstalkCalib", 

349 dimensions=("instrument", "detector"), 

350 multiple=False, 

351 isCalibration=True, 

352 ) 

353 

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

355 super().__init__(config=config) 

356 

357 if config.fluxOrder == 0: 

358 self.inputs.discard("inputFluxes") 

359 

360 

361class CrosstalkSolveConfig(pipeBase.PipelineTaskConfig, 

362 pipelineConnections=CrosstalkSolveConnections): 

363 """Configuration for the solving of crosstalk from pixel ratios. 

364 """ 

365 rejIter = Field( 

366 dtype=int, 

367 default=3, 

368 doc="Number of rejection iterations for final coefficient calculation.", 

369 ) 

370 rejSigma = Field( 

371 dtype=float, 

372 default=2.0, 

373 doc="Rejection threshold (sigma) for final coefficient calculation.", 

374 ) 

375 fluxOrder = Field( 

376 dtype=int, 

377 default=0, 

378 doc="Polynomial order in source flux to fit crosstalk.", 

379 ) 

380 doFiltering = Field( 

381 dtype=bool, 

382 default=False, 

383 doc="Filter generated crosstalk to remove marginal measurements.", 

384 ) 

385 

386 

387class CrosstalkSolveTask(pipeBase.PipelineTask, 

388 pipeBase.CmdLineTask): 

389 """Task to solve crosstalk from pixel ratios. 

390 """ 

391 ConfigClass = CrosstalkSolveConfig 

392 _DefaultName = 'cpCrosstalkSolve' 

393 

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

395 """Ensure that the input and output dimensions are passed along. 

396 

397 Parameters 

398 ---------- 

399 butlerQC : `lsst.daf.butler.butlerQuantumContext.ButlerQuantumContext` 

400 Butler to operate on. 

401 inputRefs : `lsst.pipe.base.connections.InputQuantizedConnection` 

402 Input data refs to load. 

403 ouptutRefs : `lsst.pipe.base.connections.OutputQuantizedConnection` 

404 Output data refs to persist. 

405 """ 

406 inputs = butlerQC.get(inputRefs) 

407 

408 # Use the dimensions to set calib/provenance information. 

409 inputs['inputDims'] = [exp.dataId.byName() for exp in inputRefs.inputRatios] 

410 inputs['outputDims'] = outputRefs.outputCrosstalk.dataId.byName() 

411 

412 outputs = self.run(**inputs) 

413 butlerQC.put(outputs, outputRefs) 

414 

415 def run(self, inputRatios, inputFluxes=None, camera=None, inputDims=None, outputDims=None): 

416 """Combine ratios to produce crosstalk coefficients. 

417 

418 Parameters 

419 ---------- 

420 inputRatios : `list` [`dict` [`dict` [`dict` [`dict` [`list`]]]]] 

421 A list of nested dictionaries of ratios indexed by target 

422 and source chip, then by target and source amplifier. 

423 inputFluxes : `list` [`dict` [`dict` [`list`]]] 

424 A list of nested dictionaries of source pixel fluxes, indexed 

425 by source chip and amplifier. 

426 camera : `lsst.afw.cameraGeom.Camera` 

427 Input camera. 

428 inputDims : `list` [`lsst.daf.butler.DataCoordinate`] 

429 DataIds to use to construct provenance. 

430 outputDims : `list` [`lsst.daf.butler.DataCoordinate`] 

431 DataIds to use to populate the output calibration. 

432 

433 Returns 

434 ------- 

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

436 The results struct containing: 

437 

438 ``outputCrosstalk`` : `lsst.ip.isr.CrosstalkCalib` 

439 Final crosstalk calibration. 

440 ``outputProvenance`` : `lsst.ip.isr.IsrProvenance` 

441 Provenance data for the new calibration. 

442 

443 Raises 

444 ------ 

445 RuntimeError 

446 Raised if the input data contains multiple target detectors. 

447 

448 Notes 

449 ----- 

450 The lsstDebug.Info() method can be rewritten for __name__ = 

451 `lsst.ip.isr.measureCrosstalk`, and supports the parameters: 

452 

453 debug.display['reduce'] : `bool` 

454 Display a histogram of the combined ratio measurements for 

455 a pair of source/target amplifiers from all input 

456 exposures/detectors. 

457 

458 """ 

459 if outputDims: 

460 calibChip = outputDims['detector'] 

461 instrument = outputDims['instrument'] 

462 else: 

463 # calibChip needs to be set manually in Gen2. 

464 calibChip = None 

465 instrument = None 

466 

467 self.log.info("Combining measurements from %d ratios and %d fluxes", 

468 len(inputRatios), len(inputFluxes) if inputFluxes else 0) 

469 

470 if inputFluxes is None: 

471 inputFluxes = [None for exp in inputRatios] 

472 

473 combinedRatios = defaultdict(lambda: defaultdict(list)) 

474 combinedFluxes = defaultdict(lambda: defaultdict(list)) 

475 for ratioDict, fluxDict in zip(inputRatios, inputFluxes): 

476 for targetChip in ratioDict: 

477 if calibChip and targetChip != calibChip: 

478 raise RuntimeError("Received multiple target chips!") 

479 

480 sourceChip = targetChip 

481 if sourceChip in ratioDict[targetChip]: 

482 ratios = ratioDict[targetChip][sourceChip] 

483 

484 for targetAmp in ratios: 

485 for sourceAmp in ratios[targetAmp]: 

486 combinedRatios[targetAmp][sourceAmp].extend(ratios[targetAmp][sourceAmp]) 

487 if fluxDict: 

488 combinedFluxes[targetAmp][sourceAmp].extend(fluxDict[sourceChip][sourceAmp]) 

489 # TODO: DM-21904 

490 # Iterating over all other entries in ratioDict[targetChip] will yield 

491 # inter-chip terms. 

492 

493 for targetAmp in combinedRatios: 

494 for sourceAmp in combinedRatios[targetAmp]: 

495 self.log.info("Read %d pixels for %s -> %s", 

496 len(combinedRatios[targetAmp][sourceAmp]), 

497 targetAmp, sourceAmp) 

498 if len(combinedRatios[targetAmp][sourceAmp]) > 1: 

499 self.debugRatios('reduce', combinedRatios, targetAmp, sourceAmp) 

500 

501 if self.config.fluxOrder == 0: 

502 self.log.info("Fitting crosstalk coefficients.") 

503 calib = self.measureCrosstalkCoefficients(combinedRatios, 

504 self.config.rejIter, self.config.rejSigma) 

505 else: 

506 raise NotImplementedError("Non-linear crosstalk terms are not yet supported.") 

507 

508 self.log.info("Number of valid coefficients: %d", np.sum(calib.coeffValid)) 

509 

510 if self.config.doFiltering: 

511 # This step will apply the calculated validity values to 

512 # censor poorly measured coefficients. 

513 self.log.info("Filtering measured crosstalk to remove invalid solutions.") 

514 calib = self.filterCrosstalkCalib(calib) 

515 

516 # Populate the remainder of the calibration information. 

517 calib.hasCrosstalk = True 

518 calib.interChip = {} 

519 

520 # calibChip is the detector dimension, which is the detector Id 

521 calib._detectorId = calibChip 

522 if camera: 

523 calib._detectorName = camera[calibChip].getName() 

524 calib._detectorSerial = camera[calibChip].getSerial() 

525 

526 calib._instrument = instrument 

527 calib.updateMetadata(setCalibId=True, setDate=True) 

528 

529 # Make an IsrProvenance(). 

530 provenance = IsrProvenance(calibType="CROSSTALK") 

531 provenance._detectorName = calibChip 

532 if inputDims: 

533 provenance.fromDataIds(inputDims) 

534 provenance._instrument = instrument 

535 provenance.updateMetadata() 

536 

537 return pipeBase.Struct( 

538 outputCrosstalk=calib, 

539 outputProvenance=provenance, 

540 ) 

541 

542 def measureCrosstalkCoefficients(self, ratios, rejIter, rejSigma): 

543 """Measure crosstalk coefficients from the ratios. 

544 

545 Given a list of ratios for each target/source amp combination, 

546 we measure a sigma clipped mean and error. 

547 

548 The coefficient errors returned are the standard deviation of 

549 the final set of clipped input ratios. 

550 

551 Parameters 

552 ---------- 

553 ratios : `dict` of `dict` of `numpy.ndarray` 

554 Catalog of arrays of ratios. 

555 rejIter : `int` 

556 Number of rejection iterations. 

557 rejSigma : `float` 

558 Rejection threshold (sigma). 

559 

560 Returns 

561 ------- 

562 calib : `lsst.ip.isr.CrosstalkCalib` 

563 The output crosstalk calibration. 

564 

565 Notes 

566 ----- 

567 The lsstDebug.Info() method can be rewritten for __name__ = 

568 `lsst.ip.isr.measureCrosstalk`, and supports the parameters: 

569 

570 debug.display['measure'] : `bool` 

571 Display the CDF of the combined ratio measurements for 

572 a pair of source/target amplifiers from the final set of 

573 clipped input ratios. 

574 """ 

575 calib = CrosstalkCalib(nAmp=len(ratios)) 

576 

577 # Calibration stores coefficients as a numpy ndarray. 

578 ordering = list(ratios.keys()) 

579 for ii, jj in itertools.product(range(calib.nAmp), range(calib.nAmp)): 

580 if ii == jj: 

581 values = [0.0] 

582 else: 

583 values = np.array(ratios[ordering[ii]][ordering[jj]]) 

584 values = values[np.abs(values) < 1.0] # Discard unreasonable values 

585 

586 calib.coeffNum[ii][jj] = len(values) 

587 

588 if len(values) == 0: 

589 self.log.warn("No values for matrix element %d,%d" % (ii, jj)) 

590 calib.coeffs[ii][jj] = np.nan 

591 calib.coeffErr[ii][jj] = np.nan 

592 calib.coeffValid[ii][jj] = False 

593 else: 

594 if ii != jj: 

595 for rej in range(rejIter): 

596 lo, med, hi = np.percentile(values, [25.0, 50.0, 75.0]) 

597 sigma = 0.741*(hi - lo) 

598 good = np.abs(values - med) < rejSigma*sigma 

599 if good.sum() == len(good): 

600 break 

601 values = values[good] 

602 

603 calib.coeffs[ii][jj] = np.mean(values) 

604 if calib.coeffNum[ii][jj] == 1: 

605 calib.coeffErr[ii][jj] = np.nan 

606 else: 

607 correctionFactor = sigmaClipCorrection(rejSigma) 

608 calib.coeffErr[ii][jj] = np.std(values) * correctionFactor 

609 calib.coeffValid[ii][jj] = (np.abs(calib.coeffs[ii][jj]) 

610 > calib.coeffErr[ii][jj] / np.sqrt(calib.coeffNum[ii][jj])) 

611 

612 if calib.coeffNum[ii][jj] > 1: 

613 self.debugRatios('measure', ratios, ordering[ii], ordering[jj], 

614 calib.coeffs[ii][jj], calib.coeffValid[ii][jj]) 

615 

616 return calib 

617 

618 @staticmethod 

619 def filterCrosstalkCalib(inCalib): 

620 """Apply valid constraints to the measured values. 

621 

622 Any measured coefficient that is determined to be invalid is 

623 set to zero, and has the error set to nan. The validation is 

624 determined by checking that the measured coefficient is larger 

625 than the calculated standard error of the mean. 

626 

627 Parameters 

628 ---------- 

629 inCalib : `lsst.ip.isr.CrosstalkCalib` 

630 Input calibration to filter. 

631 

632 Returns 

633 ------- 

634 outCalib : `lsst.ip.isr.CrosstalkCalib` 

635 Filtered calibration. 

636 """ 

637 outCalib = CrosstalkCalib() 

638 outCalib.numAmps = inCalib.numAmps 

639 

640 outCalib.coeffs = inCalib.coeffs 

641 outCalib.coeffs[~inCalib.coeffValid] = 0.0 

642 

643 outCalib.coeffErr = inCalib.coeffErr 

644 outCalib.coeffErr[~inCalib.coeffValid] = np.nan 

645 

646 outCalib.coeffNum = inCalib.coeffNum 

647 outCalib.coeffValid = inCalib.coeffValid 

648 

649 return outCalib 

650 

651 def debugRatios(self, stepname, ratios, i, j, coeff=0.0, valid=False): 

652 """Utility function to examine the final CT ratio set. 

653 

654 Parameters 

655 ---------- 

656 stepname : `str` 

657 State of processing to view. 

658 ratios : `dict` of `dict` of `np.ndarray` 

659 Array of measured CT ratios, indexed by source/victim 

660 amplifier. 

661 i : `str` 

662 Index of the source amplifier. 

663 j : `str` 

664 Index of the target amplifier. 

665 coeff : `float`, optional 

666 Coefficient calculated to plot along with the simple mean. 

667 valid : `bool`, optional 

668 Validity to be added to the plot title. 

669 """ 

670 frame = getDebugFrame(self._display, stepname) 

671 if frame: 

672 if i == j or ratios is None or len(ratios) < 1: 

673 pass 

674 

675 ratioList = ratios[i][j] 

676 if ratioList is None or len(ratioList) < 1: 

677 pass 

678 

679 mean = np.mean(ratioList) 

680 std = np.std(ratioList) 

681 import matplotlib.pyplot as plt 

682 figure = plt.figure(1) 

683 figure.clear() 

684 plt.hist(x=ratioList, bins=len(ratioList), 

685 cumulative=True, color='b', density=True, histtype='step') 

686 plt.xlabel("Measured pixel ratio") 

687 plt.ylabel(f"CDF: n={len(ratioList)}") 

688 plt.xlim(np.percentile(ratioList, [1.0, 99])) 

689 plt.axvline(x=mean, color="k") 

690 plt.axvline(x=coeff, color='g') 

691 plt.axvline(x=(std / np.sqrt(len(ratioList))), color='r') 

692 plt.axvline(x=-(std / np.sqrt(len(ratioList))), color='r') 

693 plt.title(f"(Source {i} -> Target {j}) mean: {mean:.2g} coeff: {coeff:.2g} valid: {valid}") 

694 figure.show() 

695 

696 prompt = "Press Enter to continue: " 

697 while True: 

698 ans = input(prompt).lower() 

699 if ans in ("", "c",): 

700 break 

701 elif ans in ("pdb", "p",): 

702 import pdb 

703 pdb.set_trace() 

704 plt.close() 

705 

706 

707class MeasureCrosstalkConfig(Config): 

708 extract = ConfigurableField( 

709 target=CrosstalkExtractTask, 

710 doc="Task to measure pixel ratios.", 

711 ) 

712 solver = ConfigurableField( 

713 target=CrosstalkSolveTask, 

714 doc="Task to convert ratio lists to crosstalk coefficients.", 

715 ) 

716 

717 

718class MeasureCrosstalkTask(pipeBase.CmdLineTask): 

719 """Measure intra-detector crosstalk. 

720 

721 See also 

722 -------- 

723 lsst.ip.isr.crosstalk.CrosstalkCalib 

724 lsst.cp.pipe.measureCrosstalk.CrosstalkExtractTask 

725 lsst.cp.pipe.measureCrosstalk.CrosstalkSolveTask 

726 

727 Notes 

728 ----- 

729 The crosstalk this method measures assumes that when a bright 

730 pixel is found in one detector amplifier, all other detector 

731 amplifiers may see a signal change in the same pixel location 

732 (relative to the readout amplifier) as these other pixels are read 

733 out at the same time. 

734 

735 After processing each input exposure through a limited set of ISR 

736 stages, bright unmasked pixels above the threshold are identified. 

737 The potential CT signal is found by taking the ratio of the 

738 appropriate background-subtracted pixel value on the other 

739 amplifiers to the input value on the source amplifier. If the 

740 source amplifier has a large number of bright pixels as well, the 

741 background level may be elevated, leading to poor ratio 

742 measurements. 

743 

744 The set of ratios found between each pair of amplifiers across all 

745 input exposures is then gathered to produce the final CT 

746 coefficients. The sigma-clipped mean and sigma are returned from 

747 these sets of ratios, with the coefficient to supply to the ISR 

748 CrosstalkTask() being the multiplicative inverse of these values. 

749 

750 This Task simply calls the pipetask versions of the measure 

751 crosstalk code. 

752 """ 

753 ConfigClass = MeasureCrosstalkConfig 

754 _DefaultName = "measureCrosstalk" 

755 

756 # Let's use this instead of messing with parseAndRun. 

757 RunnerClass = DataRefListRunner 

758 

759 def __init__(self, **kwargs): 

760 super().__init__(**kwargs) 

761 self.makeSubtask("extract") 

762 self.makeSubtask("solver") 

763 

764 def runDataRef(self, dataRefList): 

765 """Run extract task on each of inputs in the dataRef list, then pass 

766 that to the solver task. 

767 

768 Parameters 

769 ---------- 

770 dataRefList : `list` [`lsst.daf.peristence.ButlerDataRef`] 

771 Data references for exposures for detectors to process. 

772 

773 Returns 

774 ------- 

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

776 The results struct containing: 

777 

778 ``outputCrosstalk`` : `lsst.ip.isr.CrosstalkCalib` 

779 Final crosstalk calibration. 

780 ``outputProvenance`` : `lsst.ip.isr.IsrProvenance` 

781 Provenance data for the new calibration. 

782 

783 Raises 

784 ------ 

785 RuntimeError 

786 Raised if multiple target detectors are supplied. 

787 """ 

788 dataRef = dataRefList[0] 

789 camera = dataRef.get("camera") 

790 

791 ratios = [] 

792 activeChip = None 

793 for dataRef in dataRefList: 

794 exposure = dataRef.get("postISRCCD") 

795 if activeChip: 

796 if exposure.getDetector().getName() != activeChip: 

797 raise RuntimeError("Too many input detectors supplied!") 

798 else: 

799 activeChip = exposure.getDetector().getName() 

800 

801 self.extract.debugView("extract", exposure) 

802 result = self.extract.run(exposure) 

803 ratios.append(result.outputRatios) 

804 

805 for detIter, detector in enumerate(camera): 

806 if detector.getName() == activeChip: 

807 detectorId = detIter 

808 outputDims = {'instrument': camera.getName(), 

809 'detector': detectorId, 

810 } 

811 

812 finalResults = self.solver.run(ratios, camera=camera, outputDims=outputDims) 

813 dataRef.put(finalResults.outputCrosstalk, "crosstalk") 

814 

815 return finalResults