Coverage for python/lsst/ip/isr/isrMock.py: 26%

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1# This file is part of ip_isr. 

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 copy 

23import numpy as np 

24import tempfile 

25 

26import lsst.geom 

27import lsst.afw.geom as afwGeom 

28import lsst.afw.image as afwImage 

29 

30import lsst.afw.cameraGeom.utils as afwUtils 

31import lsst.afw.cameraGeom.testUtils as afwTestUtils 

32import lsst.pex.config as pexConfig 

33import lsst.pipe.base as pipeBase 

34from .crosstalk import CrosstalkCalib 

35from .defects import Defects 

36 

37__all__ = ["IsrMockConfig", "IsrMock", "RawMock", "TrimmedRawMock", "RawDictMock", 

38 "CalibratedRawMock", "MasterMock", 

39 "BiasMock", "DarkMock", "FlatMock", "FringeMock", "UntrimmedFringeMock", 

40 "BfKernelMock", "DefectMock", "CrosstalkCoeffMock", "TransmissionMock", 

41 "MockDataContainer", "MockFringeContainer"] 

42 

43 

44class IsrMockConfig(pexConfig.Config): 

45 """Configuration parameters for isrMock. 

46 

47 These parameters produce generic fixed position signals from 

48 various sources, and combine them in a way that matches how those 

49 signals are combined to create real data. The camera used is the 

50 test camera defined by the afwUtils code. 

51 """ 

52 # Detector parameters. "Exposure" parameters. 

53 isLsstLike = pexConfig.Field( 

54 dtype=bool, 

55 default=False, 

56 doc="If True, products have one raw image per amplifier, otherwise, one raw image per detector.", 

57 ) 

58 plateScale = pexConfig.Field( 

59 dtype=float, 

60 default=20.0, 

61 doc="Plate scale used in constructing mock camera.", 

62 ) 

63 radialDistortion = pexConfig.Field( 

64 dtype=float, 

65 default=0.925, 

66 doc="Radial distortion term used in constructing mock camera.", 

67 ) 

68 isTrimmed = pexConfig.Field( 

69 dtype=bool, 

70 default=True, 

71 doc="If True, amplifiers have been trimmed and mosaicked to remove regions outside the data BBox.", 

72 ) 

73 detectorIndex = pexConfig.Field( 

74 dtype=int, 

75 default=20, 

76 doc="Index for the detector to use. The default value uses a standard 2x4 array of amps.", 

77 ) 

78 rngSeed = pexConfig.Field( 

79 dtype=int, 

80 default=20000913, 

81 doc="Seed for random number generator used to add noise.", 

82 ) 

83 # TODO: DM-18345 Check that mocks scale correctly when gain != 1.0 

84 gain = pexConfig.Field( 

85 dtype=float, 

86 default=1.0, 

87 doc="Gain for simulated data in e^-/DN.", 

88 ) 

89 readNoise = pexConfig.Field( 

90 dtype=float, 

91 default=5.0, 

92 doc="Read noise of the detector in e-.", 

93 ) 

94 expTime = pexConfig.Field( 

95 dtype=float, 

96 default=5.0, 

97 doc="Exposure time for simulated data.", 

98 ) 

99 

100 # Signal parameters 

101 skyLevel = pexConfig.Field( 

102 dtype=float, 

103 default=1000.0, 

104 doc="Background contribution to be generated from 'the sky' in DN.", 

105 ) 

106 sourceFlux = pexConfig.ListField( 

107 dtype=float, 

108 default=[45000.0], 

109 doc="Peak flux level (in DN) of simulated 'astronomical sources'.", 

110 ) 

111 sourceAmp = pexConfig.ListField( 

112 dtype=int, 

113 default=[0], 

114 doc="Amplifier to place simulated 'astronomical sources'.", 

115 ) 

116 sourceX = pexConfig.ListField( 

117 dtype=float, 

118 default=[50.0], 

119 doc="Peak position (in amplifier coordinates) of simulated 'astronomical sources'.", 

120 ) 

121 sourceY = pexConfig.ListField( 

122 dtype=float, 

123 default=[25.0], 

124 doc="Peak position (in amplifier coordinates) of simulated 'astronomical sources'.", 

125 ) 

126 overscanScale = pexConfig.Field( 

127 dtype=float, 

128 default=100.0, 

129 doc="Amplitude (in DN) of the ramp function to add to overscan data.", 

130 ) 

131 biasLevel = pexConfig.Field( 

132 dtype=float, 

133 default=8000.0, 

134 doc="Background contribution to be generated from the bias offset in DN.", 

135 ) 

136 darkRate = pexConfig.Field( 

137 dtype=float, 

138 default=5.0, 

139 doc="Background level contribution (in e-/s) to be generated from dark current.", 

140 ) 

141 darkTime = pexConfig.Field( 

142 dtype=float, 

143 default=5.0, 

144 doc="Exposure time for the dark current contribution.", 

145 ) 

146 flatDrop = pexConfig.Field( 

147 dtype=float, 

148 default=0.1, 

149 doc="Fractional flux drop due to flat from center to edge of detector along x-axis.", 

150 ) 

151 fringeScale = pexConfig.ListField( 

152 dtype=float, 

153 default=[200.0], 

154 doc="Peak fluxes for the components of the fringe ripple in DN.", 

155 ) 

156 fringeX0 = pexConfig.ListField( 

157 dtype=float, 

158 default=[-100], 

159 doc="Center position for the fringe ripples.", 

160 ) 

161 fringeY0 = pexConfig.ListField( 

162 dtype=float, 

163 default=[-0], 

164 doc="Center position for the fringe ripples.", 

165 ) 

166 

167 # Inclusion parameters 

168 doAddSky = pexConfig.Field( 

169 dtype=bool, 

170 default=True, 

171 doc="Apply 'sky' signal to output image.", 

172 ) 

173 doAddSource = pexConfig.Field( 

174 dtype=bool, 

175 default=True, 

176 doc="Add simulated source to output image.", 

177 ) 

178 doAddCrosstalk = pexConfig.Field( 

179 dtype=bool, 

180 default=False, 

181 doc="Apply simulated crosstalk to output image. This cannot be corrected by ISR, " 

182 "as detector.hasCrosstalk()==False.", 

183 ) 

184 doAddOverscan = pexConfig.Field( 

185 dtype=bool, 

186 default=True, 

187 doc="If untrimmed, add overscan ramp to overscan and data regions.", 

188 ) 

189 doAddBias = pexConfig.Field( 

190 dtype=bool, 

191 default=True, 

192 doc="Add bias signal to data.", 

193 ) 

194 doAddDark = pexConfig.Field( 

195 dtype=bool, 

196 default=True, 

197 doc="Add dark signal to data.", 

198 ) 

199 doAddFlat = pexConfig.Field( 

200 dtype=bool, 

201 default=True, 

202 doc="Add flat signal to data.", 

203 ) 

204 doAddFringe = pexConfig.Field( 

205 dtype=bool, 

206 default=True, 

207 doc="Add fringe signal to data.", 

208 ) 

209 

210 # Datasets to create and return instead of generating an image. 

211 doTransmissionCurve = pexConfig.Field( 

212 dtype=bool, 

213 default=False, 

214 doc="Return a simulated transmission curve.", 

215 ) 

216 doDefects = pexConfig.Field( 

217 dtype=bool, 

218 default=False, 

219 doc="Return a simulated defect list.", 

220 ) 

221 doBrighterFatter = pexConfig.Field( 

222 dtype=bool, 

223 default=False, 

224 doc="Return a simulated brighter-fatter kernel.", 

225 ) 

226 doCrosstalkCoeffs = pexConfig.Field( 

227 dtype=bool, 

228 default=False, 

229 doc="Return the matrix of crosstalk coefficients.", 

230 ) 

231 doDataRef = pexConfig.Field( 

232 dtype=bool, 

233 default=False, 

234 doc="Return a simulated gen2 butler dataRef.", 

235 ) 

236 doGenerateImage = pexConfig.Field( 

237 dtype=bool, 

238 default=False, 

239 doc="Return the generated output image if True.", 

240 ) 

241 doGenerateData = pexConfig.Field( 

242 dtype=bool, 

243 default=False, 

244 doc="Return a non-image data structure if True.", 

245 ) 

246 doGenerateAmpDict = pexConfig.Field( 

247 dtype=bool, 

248 default=False, 

249 doc="Return a dict of exposure amplifiers instead of an afwImage.Exposure.", 

250 ) 

251 

252 

253class IsrMock(pipeBase.Task): 

254 """Class to generate consistent mock images for ISR testing. 

255 

256 ISR testing currently relies on one-off fake images that do not 

257 accurately mimic the full set of detector effects. This class 

258 uses the test camera/detector/amplifier structure defined in 

259 `lsst.afw.cameraGeom.testUtils` to avoid making the test data 

260 dependent on any of the actual obs package formats. 

261 """ 

262 ConfigClass = IsrMockConfig 

263 _DefaultName = "isrMock" 

264 

265 def __init__(self, **kwargs): 

266 super().__init__(**kwargs) 

267 self.rng = np.random.RandomState(self.config.rngSeed) 

268 self.crosstalkCoeffs = np.array([[0.0, 0.0, 0.0, 0.0, 0.0, -1e-3, 0.0, 0.0], 

269 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 

270 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 

271 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 

272 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 

273 [1e-2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 

274 [1e-2, 0.0, 0.0, 2.2e-2, 0.0, 0.0, 0.0, 0.0], 

275 [1e-2, 5e-3, 5e-4, 3e-3, 4e-2, 5e-3, 5e-3, 0.0]]) 

276 

277 self.bfKernel = np.array([[1., 4., 7., 4., 1.], 

278 [4., 16., 26., 16., 4.], 

279 [7., 26., 41., 26., 7.], 

280 [4., 16., 26., 16., 4.], 

281 [1., 4., 7., 4., 1.]]) / 273.0 

282 

283 def run(self): 

284 """Generate a mock ISR product, and return it. 

285 

286 Returns 

287 ------- 

288 image : `lsst.afw.image.Exposure` 

289 Simulated ISR image with signals added. 

290 dataProduct : 

291 Simulated ISR data products. 

292 None : 

293 Returned if no valid configuration was found. 

294 

295 Raises 

296 ------ 

297 RuntimeError 

298 Raised if both doGenerateImage and doGenerateData are specified. 

299 """ 

300 if self.config.doGenerateImage and self.config.doGenerateData: 

301 raise RuntimeError("Only one of doGenerateImage and doGenerateData may be specified.") 

302 elif self.config.doGenerateImage: 

303 return self.makeImage() 

304 elif self.config.doGenerateData: 

305 return self.makeData() 

306 else: 

307 return None 

308 

309 def makeData(self): 

310 """Generate simulated ISR data. 

311 

312 Currently, only the class defined crosstalk coefficient 

313 matrix, brighter-fatter kernel, a constant unity transmission 

314 curve, or a simple single-entry defect list can be generated. 

315 

316 Returns 

317 ------- 

318 dataProduct : 

319 Simulated ISR data product. 

320 """ 

321 if sum(map(bool, [self.config.doBrighterFatter, 

322 self.config.doDefects, 

323 self.config.doTransmissionCurve, 

324 self.config.doCrosstalkCoeffs])) != 1: 

325 raise RuntimeError("Only one data product can be generated at a time.") 

326 elif self.config.doBrighterFatter is True: 

327 return self.makeBfKernel() 

328 elif self.config.doDefects is True: 

329 return self.makeDefectList() 

330 elif self.config.doTransmissionCurve is True: 

331 return self.makeTransmissionCurve() 

332 elif self.config.doCrosstalkCoeffs is True: 

333 return self.crosstalkCoeffs 

334 else: 

335 return None 

336 

337 def makeBfKernel(self): 

338 """Generate a simple Gaussian brighter-fatter kernel. 

339 

340 Returns 

341 ------- 

342 kernel : `numpy.ndarray` 

343 Simulated brighter-fatter kernel. 

344 """ 

345 return self.bfKernel 

346 

347 def makeDefectList(self): 

348 """Generate a simple single-entry defect list. 

349 

350 Returns 

351 ------- 

352 defectList : `lsst.meas.algorithms.Defects` 

353 Simulated defect list 

354 """ 

355 return Defects([lsst.geom.Box2I(lsst.geom.Point2I(0, 0), 

356 lsst.geom.Extent2I(40, 50))]) 

357 

358 def makeCrosstalkCoeff(self): 

359 """Generate the simulated crosstalk coefficients. 

360 

361 Returns 

362 ------- 

363 coeffs : `numpy.ndarray` 

364 Simulated crosstalk coefficients. 

365 """ 

366 

367 return self.crosstalkCoeffs 

368 

369 def makeTransmissionCurve(self): 

370 """Generate a simulated flat transmission curve. 

371 

372 Returns 

373 ------- 

374 transmission : `lsst.afw.image.TransmissionCurve` 

375 Simulated transmission curve. 

376 """ 

377 

378 return afwImage.TransmissionCurve.makeIdentity() 

379 

380 def makeImage(self): 

381 """Generate a simulated ISR image. 

382 

383 Returns 

384 ------- 

385 exposure : `lsst.afw.image.Exposure` or `dict` 

386 Simulated ISR image data. 

387 

388 Notes 

389 ----- 

390 This method currently constructs a "raw" data image by: 

391 * Generating a simulated sky with noise 

392 * Adding a single Gaussian "star" 

393 * Adding the fringe signal 

394 * Multiplying the frame by the simulated flat 

395 * Adding dark current (and noise) 

396 * Adding a bias offset (and noise) 

397 * Adding an overscan gradient parallel to the pixel y-axis 

398 * Simulating crosstalk by adding a scaled version of each 

399 amplifier to each other amplifier. 

400 

401 The exposure with image data constructed this way is in one of 

402 three formats. 

403 * A single image, with overscan and prescan regions retained 

404 * A single image, with overscan and prescan regions trimmed 

405 * A `dict`, containing the amplifer data indexed by the 

406 amplifier name. 

407 

408 The nonlinearity, CTE, and brighter fatter are currently not 

409 implemented. 

410 

411 Note that this method generates an image in the reverse 

412 direction as the ISR processing, as the output image here has 

413 had a series of instrument effects added to an idealized 

414 exposure. 

415 """ 

416 exposure = self.getExposure() 

417 

418 for idx, amp in enumerate(exposure.getDetector()): 

419 bbox = None 

420 if self.config.isTrimmed is True: 

421 bbox = amp.getBBox() 

422 else: 

423 bbox = amp.getRawDataBBox() 

424 

425 ampData = exposure.image[bbox] 

426 

427 if self.config.doAddSky is True: 

428 self.amplifierAddNoise(ampData, self.config.skyLevel, np.sqrt(self.config.skyLevel)) 

429 

430 if self.config.doAddSource is True: 

431 for sourceAmp, sourceFlux, sourceX, sourceY in zip(self.config.sourceAmp, 

432 self.config.sourceFlux, 

433 self.config.sourceX, 

434 self.config.sourceY): 

435 if idx == sourceAmp: 

436 self.amplifierAddSource(ampData, sourceFlux, sourceX, sourceY) 

437 

438 if self.config.doAddFringe is True: 

439 self.amplifierAddFringe(amp, ampData, np.array(self.config.fringeScale), 

440 x0=np.array(self.config.fringeX0), 

441 y0=np.array(self.config.fringeY0)) 

442 

443 if self.config.doAddFlat is True: 

444 if ampData.getArray().sum() == 0.0: 

445 self.amplifierAddNoise(ampData, 1.0, 0.0) 

446 u0 = exposure.getDimensions().getX() 

447 v0 = exposure.getDimensions().getY() 

448 self.amplifierMultiplyFlat(amp, ampData, self.config.flatDrop, u0=u0, v0=v0) 

449 

450 if self.config.doAddDark is True: 

451 self.amplifierAddNoise(ampData, 

452 self.config.darkRate * self.config.darkTime / self.config.gain, 

453 np.sqrt(self.config.darkRate 

454 * self.config.darkTime / self.config.gain)) 

455 

456 if self.config.doAddCrosstalk is True: 

457 ctCalib = CrosstalkCalib() 

458 for idxS, ampS in enumerate(exposure.getDetector()): 

459 for idxT, ampT in enumerate(exposure.getDetector()): 

460 ampDataT = exposure.image[ampT.getBBox() 

461 if self.config.isTrimmed else ampT.getRawDataBBox()] 

462 outAmp = ctCalib.extractAmp(exposure.getImage(), ampS, ampT, 

463 isTrimmed=self.config.isTrimmed) 

464 self.amplifierAddCT(outAmp, ampDataT, self.crosstalkCoeffs[idxT][idxS]) 

465 

466 for amp in exposure.getDetector(): 

467 bbox = None 

468 if self.config.isTrimmed is True: 

469 bbox = amp.getBBox() 

470 else: 

471 bbox = amp.getRawDataBBox() 

472 

473 ampData = exposure.image[bbox] 

474 

475 if self.config.doAddBias is True: 

476 self.amplifierAddNoise(ampData, self.config.biasLevel, 

477 self.config.readNoise / self.config.gain) 

478 

479 if self.config.doAddOverscan is True: 

480 oscanBBox = amp.getRawHorizontalOverscanBBox() 

481 oscanData = exposure.image[oscanBBox] 

482 self.amplifierAddNoise(oscanData, self.config.biasLevel, 

483 self.config.readNoise / self.config.gain) 

484 

485 self.amplifierAddYGradient(ampData, -1.0 * self.config.overscanScale, 

486 1.0 * self.config.overscanScale) 

487 self.amplifierAddYGradient(oscanData, -1.0 * self.config.overscanScale, 

488 1.0 * self.config.overscanScale) 

489 

490 if self.config.doGenerateAmpDict is True: 

491 expDict = dict() 

492 for amp in exposure.getDetector(): 

493 expDict[amp.getName()] = exposure 

494 return expDict 

495 else: 

496 return exposure 

497 

498 # afw primatives to construct the image structure 

499 def getCamera(self): 

500 """Construct a test camera object. 

501 

502 Returns 

503 ------- 

504 camera : `lsst.afw.cameraGeom.camera` 

505 Test camera. 

506 """ 

507 cameraWrapper = afwTestUtils.CameraWrapper( 

508 plateScale=self.config.plateScale, 

509 radialDistortion=self.config.radialDistortion, 

510 isLsstLike=self.config.isLsstLike, 

511 ) 

512 camera = cameraWrapper.camera 

513 return camera 

514 

515 def getExposure(self): 

516 """Construct a test exposure. 

517 

518 The test exposure has a simple WCS set, as well as a list of 

519 unlikely header keywords that can be removed during ISR 

520 processing to exercise that code. 

521 

522 Returns 

523 ------- 

524 exposure : `lsst.afw.exposure.Exposure` 

525 Construct exposure containing masked image of the 

526 appropriate size. 

527 """ 

528 camera = self.getCamera() 

529 detector = camera[self.config.detectorIndex] 

530 image = afwUtils.makeImageFromCcd(detector, 

531 isTrimmed=self.config.isTrimmed, 

532 showAmpGain=False, 

533 rcMarkSize=0, 

534 binSize=1, 

535 imageFactory=afwImage.ImageF) 

536 

537 var = afwImage.ImageF(image.getDimensions()) 

538 mask = afwImage.Mask(image.getDimensions()) 

539 image.assign(0.0) 

540 

541 maskedImage = afwImage.makeMaskedImage(image, mask, var) 

542 exposure = afwImage.makeExposure(maskedImage) 

543 exposure.setDetector(detector) 

544 exposure.setWcs(self.getWcs()) 

545 

546 visitInfo = afwImage.VisitInfo(exposureTime=self.config.expTime, darkTime=self.config.darkTime) 

547 exposure.getInfo().setVisitInfo(visitInfo) 

548 

549 metadata = exposure.getMetadata() 

550 metadata.add("SHEEP", 7.3, "number of sheep on farm") 

551 metadata.add("MONKEYS", 155, "monkeys per tree") 

552 metadata.add("VAMPIRES", 4, "How scary are vampires.") 

553 

554 ccd = exposure.getDetector() 

555 newCcd = ccd.rebuild() 

556 newCcd.clear() 

557 for amp in ccd: 

558 newAmp = amp.rebuild() 

559 newAmp.setLinearityCoeffs((0., 1., 0., 0.)) 

560 newAmp.setLinearityType("Polynomial") 

561 newAmp.setGain(self.config.gain) 

562 newAmp.setSuspectLevel(25000.0) 

563 newAmp.setSaturation(32000.0) 

564 newCcd.append(newAmp) 

565 exposure.setDetector(newCcd.finish()) 

566 

567 exposure.image.array[:] = np.zeros(exposure.getImage().getDimensions()).transpose() 

568 exposure.mask.array[:] = np.zeros(exposure.getMask().getDimensions()).transpose() 

569 exposure.variance.array[:] = np.zeros(exposure.getVariance().getDimensions()).transpose() 

570 

571 return exposure 

572 

573 def getWcs(self): 

574 """Construct a dummy WCS object. 

575 

576 Taken from the deprecated ip_isr/examples/exampleUtils.py. 

577 

578 This is not guaranteed, given the distortion and pixel scale 

579 listed in the afwTestUtils camera definition. 

580 

581 Returns 

582 ------- 

583 wcs : `lsst.afw.geom.SkyWcs` 

584 Test WCS transform. 

585 """ 

586 return afwGeom.makeSkyWcs(crpix=lsst.geom.Point2D(0.0, 100.0), 

587 crval=lsst.geom.SpherePoint(45.0, 25.0, lsst.geom.degrees), 

588 cdMatrix=afwGeom.makeCdMatrix(scale=1.0*lsst.geom.degrees)) 

589 

590 def localCoordToExpCoord(self, ampData, x, y): 

591 """Convert between a local amplifier coordinate and the full 

592 exposure coordinate. 

593 

594 Parameters 

595 ---------- 

596 ampData : `lsst.afw.image.ImageF` 

597 Amplifier image to use for conversions. 

598 x : `int` 

599 X-coordinate of the point to transform. 

600 y : `int` 

601 Y-coordinate of the point to transform. 

602 

603 Returns 

604 ------- 

605 u : `int` 

606 Transformed x-coordinate. 

607 v : `int` 

608 Transformed y-coordinate. 

609 

610 Notes 

611 ----- 

612 The output is transposed intentionally here, to match the 

613 internal transpose between numpy and afw.image coordinates. 

614 """ 

615 u = x + ampData.getBBox().getBeginX() 

616 v = y + ampData.getBBox().getBeginY() 

617 

618 return (v, u) 

619 

620 # Simple data values. 

621 def amplifierAddNoise(self, ampData, mean, sigma): 

622 """Add Gaussian noise to an amplifier's image data. 

623 

624 This method operates in the amplifier coordinate frame. 

625 

626 Parameters 

627 ---------- 

628 ampData : `lsst.afw.image.ImageF` 

629 Amplifier image to operate on. 

630 mean : `float` 

631 Mean value of the Gaussian noise. 

632 sigma : `float` 

633 Sigma of the Gaussian noise. 

634 """ 

635 ampArr = ampData.array 

636 ampArr[:] = ampArr[:] + self.rng.normal(mean, sigma, 

637 size=ampData.getDimensions()).transpose() 

638 

639 def amplifierAddYGradient(self, ampData, start, end): 

640 """Add a y-axis linear gradient to an amplifier's image data. 

641 

642 This method operates in the amplifier coordinate frame. 

643 

644 Parameters 

645 ---------- 

646 ampData : `lsst.afw.image.ImageF` 

647 Amplifier image to operate on. 

648 start : `float` 

649 Start value of the gradient (at y=0). 

650 end : `float` 

651 End value of the gradient (at y=ymax). 

652 """ 

653 nPixY = ampData.getDimensions().getY() 

654 ampArr = ampData.array 

655 ampArr[:] = ampArr[:] + (np.interp(range(nPixY), (0, nPixY - 1), (start, end)).reshape(nPixY, 1) 

656 + np.zeros(ampData.getDimensions()).transpose()) 

657 

658 def amplifierAddSource(self, ampData, scale, x0, y0): 

659 """Add a single Gaussian source to an amplifier. 

660 

661 This method operates in the amplifier coordinate frame. 

662 

663 Parameters 

664 ---------- 

665 ampData : `lsst.afw.image.ImageF` 

666 Amplifier image to operate on. 

667 scale : `float` 

668 Peak flux of the source to add. 

669 x0 : `float` 

670 X-coordinate of the source peak. 

671 y0 : `float` 

672 Y-coordinate of the source peak. 

673 """ 

674 for x in range(0, ampData.getDimensions().getX()): 

675 for y in range(0, ampData.getDimensions().getY()): 

676 ampData.array[y][x] = (ampData.array[y][x] 

677 + scale * np.exp(-0.5 * ((x - x0)**2 + (y - y0)**2) / 3.0**2)) 

678 

679 def amplifierAddCT(self, ampDataSource, ampDataTarget, scale): 

680 """Add a scaled copy of an amplifier to another, simulating crosstalk. 

681 

682 This method operates in the amplifier coordinate frame. 

683 

684 Parameters 

685 ---------- 

686 ampDataSource : `lsst.afw.image.ImageF` 

687 Amplifier image to add scaled copy from. 

688 ampDataTarget : `lsst.afw.image.ImageF` 

689 Amplifier image to add scaled copy to. 

690 scale : `float` 

691 Flux scale of the copy to add to the target. 

692 

693 Notes 

694 ----- 

695 This simulates simple crosstalk between amplifiers. 

696 """ 

697 ampDataTarget.array[:] = (ampDataTarget.array[:] 

698 + scale * ampDataSource.array[:]) 

699 

700 # Functional form data values. 

701 def amplifierAddFringe(self, amp, ampData, scale, x0=100, y0=0): 

702 """Add a fringe-like ripple pattern to an amplifier's image data. 

703 

704 Parameters 

705 ---------- 

706 amp : `~lsst.afw.ampInfo.AmpInfoRecord` 

707 Amplifier to operate on. Needed for amp<->exp coordinate 

708 transforms. 

709 ampData : `lsst.afw.image.ImageF` 

710 Amplifier image to operate on. 

711 scale : `numpy.array` or `float` 

712 Peak intensity scaling for the ripple. 

713 x0 : `numpy.array` or `float`, optional 

714 Fringe center 

715 y0 : `numpy.array` or `float`, optional 

716 Fringe center 

717 

718 Notes 

719 ----- 

720 This uses an offset sinc function to generate a ripple 

721 pattern. True fringes have much finer structure, but this 

722 pattern should be visually identifiable. The (x, y) 

723 coordinates are in the frame of the amplifier, and (u, v) in 

724 the frame of the full trimmed image. 

725 """ 

726 for x in range(0, ampData.getDimensions().getX()): 

727 for y in range(0, ampData.getDimensions().getY()): 

728 (u, v) = self.localCoordToExpCoord(amp, x, y) 

729 ampData.getArray()[y][x] = np.sum((ampData.getArray()[y][x] 

730 + scale * np.sinc(((u - x0) / 50)**2 

731 + ((v - y0) / 50)**2))) 

732 

733 def amplifierMultiplyFlat(self, amp, ampData, fracDrop, u0=100.0, v0=100.0): 

734 """Multiply an amplifier's image data by a flat-like pattern. 

735 

736 Parameters 

737 ---------- 

738 amp : `lsst.afw.ampInfo.AmpInfoRecord` 

739 Amplifier to operate on. Needed for amp<->exp coordinate 

740 transforms. 

741 ampData : `lsst.afw.image.ImageF` 

742 Amplifier image to operate on. 

743 fracDrop : `float` 

744 Fractional drop from center to edge of detector along x-axis. 

745 u0 : `float` 

746 Peak location in detector coordinates. 

747 v0 : `float` 

748 Peak location in detector coordinates. 

749 

750 Notes 

751 ----- 

752 This uses a 2-d Gaussian to simulate an illumination pattern 

753 that falls off towards the edge of the detector. The (x, y) 

754 coordinates are in the frame of the amplifier, and (u, v) in 

755 the frame of the full trimmed image. 

756 """ 

757 if fracDrop >= 1.0: 

758 raise RuntimeError("Flat fractional drop cannot be greater than 1.0") 

759 

760 sigma = u0 / np.sqrt(-2.0 * np.log(fracDrop)) 

761 

762 for x in range(0, ampData.getDimensions().getX()): 

763 for y in range(0, ampData.getDimensions().getY()): 

764 (u, v) = self.localCoordToExpCoord(amp, x, y) 

765 f = np.exp(-0.5 * ((u - u0)**2 + (v - v0)**2) / sigma**2) 

766 ampData.array[y][x] = (ampData.array[y][x] * f) 

767 

768 

769class RawMock(IsrMock): 

770 """Generate a raw exposure suitable for ISR. 

771 """ 

772 def __init__(self, **kwargs): 

773 super().__init__(**kwargs) 

774 self.config.isTrimmed = False 

775 self.config.doGenerateImage = True 

776 self.config.doGenerateAmpDict = False 

777 self.config.doAddOverscan = True 

778 self.config.doAddSky = True 

779 self.config.doAddSource = True 

780 self.config.doAddCrosstalk = False 

781 self.config.doAddBias = True 

782 self.config.doAddDark = True 

783 

784 

785class TrimmedRawMock(RawMock): 

786 """Generate a trimmed raw exposure. 

787 """ 

788 def __init__(self, **kwargs): 

789 super().__init__(**kwargs) 

790 self.config.isTrimmed = True 

791 self.config.doAddOverscan = False 

792 

793 

794class CalibratedRawMock(RawMock): 

795 """Generate a trimmed raw exposure. 

796 """ 

797 def __init__(self, **kwargs): 

798 super().__init__(**kwargs) 

799 self.config.isTrimmed = True 

800 self.config.doGenerateImage = True 

801 self.config.doAddOverscan = False 

802 self.config.doAddSky = True 

803 self.config.doAddSource = True 

804 self.config.doAddCrosstalk = False 

805 

806 self.config.doAddBias = False 

807 self.config.doAddDark = False 

808 self.config.doAddFlat = False 

809 self.config.doAddFringe = True 

810 

811 self.config.biasLevel = 0.0 

812 self.config.readNoise = 10.0 

813 

814 

815class RawDictMock(RawMock): 

816 """Generate a raw exposure dict suitable for ISR. 

817 """ 

818 def __init__(self, **kwargs): 

819 super().__init__(**kwargs) 

820 self.config.doGenerateAmpDict = True 

821 

822 

823class MasterMock(IsrMock): 

824 """Parent class for those that make master calibrations. 

825 """ 

826 def __init__(self, **kwargs): 

827 super().__init__(**kwargs) 

828 self.config.isTrimmed = True 

829 self.config.doGenerateImage = True 

830 self.config.doAddOverscan = False 

831 self.config.doAddSky = False 

832 self.config.doAddSource = False 

833 self.config.doAddCrosstalk = False 

834 

835 self.config.doAddBias = False 

836 self.config.doAddDark = False 

837 self.config.doAddFlat = False 

838 self.config.doAddFringe = False 

839 

840 

841class BiasMock(MasterMock): 

842 """Simulated master bias calibration. 

843 """ 

844 def __init__(self, **kwargs): 

845 super().__init__(**kwargs) 

846 self.config.doAddBias = True 

847 self.config.readNoise = 10.0 

848 

849 

850class DarkMock(MasterMock): 

851 """Simulated master dark calibration. 

852 """ 

853 def __init__(self, **kwargs): 

854 super().__init__(**kwargs) 

855 self.config.doAddDark = True 

856 self.config.darkTime = 1.0 

857 

858 

859class FlatMock(MasterMock): 

860 """Simulated master flat calibration. 

861 """ 

862 def __init__(self, **kwargs): 

863 super().__init__(**kwargs) 

864 self.config.doAddFlat = True 

865 

866 

867class FringeMock(MasterMock): 

868 """Simulated master fringe calibration. 

869 """ 

870 def __init__(self, **kwargs): 

871 super().__init__(**kwargs) 

872 self.config.doAddFringe = True 

873 

874 

875class UntrimmedFringeMock(FringeMock): 

876 """Simulated untrimmed master fringe calibration. 

877 """ 

878 def __init__(self, **kwargs): 

879 super().__init__(**kwargs) 

880 self.config.isTrimmed = False 

881 

882 

883class BfKernelMock(IsrMock): 

884 """Simulated brighter-fatter kernel. 

885 """ 

886 def __init__(self, **kwargs): 

887 super().__init__(**kwargs) 

888 self.config.doGenerateImage = False 

889 self.config.doGenerateData = True 

890 self.config.doBrighterFatter = True 

891 self.config.doDefects = False 

892 self.config.doCrosstalkCoeffs = False 

893 self.config.doTransmissionCurve = False 

894 

895 

896class DefectMock(IsrMock): 

897 """Simulated defect list. 

898 """ 

899 def __init__(self, **kwargs): 

900 super().__init__(**kwargs) 

901 self.config.doGenerateImage = False 

902 self.config.doGenerateData = True 

903 self.config.doBrighterFatter = False 

904 self.config.doDefects = True 

905 self.config.doCrosstalkCoeffs = False 

906 self.config.doTransmissionCurve = False 

907 

908 

909class CrosstalkCoeffMock(IsrMock): 

910 """Simulated crosstalk coefficient matrix. 

911 """ 

912 def __init__(self, **kwargs): 

913 super().__init__(**kwargs) 

914 self.config.doGenerateImage = False 

915 self.config.doGenerateData = True 

916 self.config.doBrighterFatter = False 

917 self.config.doDefects = False 

918 self.config.doCrosstalkCoeffs = True 

919 self.config.doTransmissionCurve = False 

920 

921 

922class TransmissionMock(IsrMock): 

923 """Simulated transmission curve. 

924 """ 

925 def __init__(self, **kwargs): 

926 super().__init__(**kwargs) 

927 self.config.doGenerateImage = False 

928 self.config.doGenerateData = True 

929 self.config.doBrighterFatter = False 

930 self.config.doDefects = False 

931 self.config.doCrosstalkCoeffs = False 

932 self.config.doTransmissionCurve = True 

933 

934 

935class MockDataContainer(object): 

936 """Container for holding ISR mock objects. 

937 """ 

938 dataId = "isrMock Fake Data" 

939 darkval = 2. # e-/sec 

940 oscan = 250. # DN 

941 gradient = .10 

942 exptime = 15.0 # seconds 

943 darkexptime = 15.0 # seconds 

944 

945 def __init__(self, **kwargs): 

946 if 'config' in kwargs.keys(): 

947 self.config = kwargs['config'] 

948 else: 

949 self.config = None 

950 

951 def expectImage(self): 

952 if self.config is None: 

953 self.config = IsrMockConfig() 

954 self.config.doGenerateImage = True 

955 self.config.doGenerateData = False 

956 

957 def expectData(self): 

958 if self.config is None: 

959 self.config = IsrMockConfig() 

960 self.config.doGenerateImage = False 

961 self.config.doGenerateData = True 

962 

963 def get(self, dataType, **kwargs): 

964 """Return an appropriate data product. 

965 

966 Parameters 

967 ---------- 

968 dataType : `str` 

969 Type of data product to return. 

970 

971 Returns 

972 ------- 

973 mock : IsrMock.run() result 

974 The output product. 

975 """ 

976 if "_filename" in dataType: 

977 self.expectData() 

978 return tempfile.mktemp(), "mock" 

979 elif 'transmission_' in dataType: 

980 self.expectData() 

981 return TransmissionMock(config=self.config).run() 

982 elif dataType == 'ccdExposureId': 

983 self.expectData() 

984 return 20090913 

985 elif dataType == 'camera': 

986 self.expectData() 

987 return IsrMock(config=self.config).getCamera() 

988 elif dataType == 'raw': 

989 self.expectImage() 

990 return RawMock(config=self.config).run() 

991 elif dataType == 'bias': 

992 self.expectImage() 

993 return BiasMock(config=self.config).run() 

994 elif dataType == 'dark': 

995 self.expectImage() 

996 return DarkMock(config=self.config).run() 

997 elif dataType == 'flat': 

998 self.expectImage() 

999 return FlatMock(config=self.config).run() 

1000 elif dataType == 'fringe': 

1001 self.expectImage() 

1002 return FringeMock(config=self.config).run() 

1003 elif dataType == 'defects': 

1004 self.expectData() 

1005 return DefectMock(config=self.config).run() 

1006 elif dataType == 'bfKernel': 

1007 self.expectData() 

1008 return BfKernelMock(config=self.config).run() 

1009 elif dataType == 'linearizer': 

1010 return None 

1011 elif dataType == 'crosstalkSources': 

1012 return None 

1013 else: 

1014 raise RuntimeError("ISR DataRefMock cannot return %s.", dataType) 

1015 

1016 

1017class MockFringeContainer(object): 

1018 """Container for mock fringe data. 

1019 """ 

1020 dataId = "isrMock Fake Data" 

1021 darkval = 2. # e-/sec 

1022 oscan = 250. # DN 

1023 gradient = .10 

1024 exptime = 15 # seconds 

1025 darkexptime = 40. # seconds 

1026 

1027 def __init__(self, **kwargs): 

1028 if 'config' in kwargs.keys(): 

1029 self.config = kwargs['config'] 

1030 else: 

1031 self.config = IsrMockConfig() 

1032 self.config.isTrimmed = True 

1033 self.config.doAddFringe = True 

1034 self.config.readNoise = 10.0 

1035 

1036 def get(self, dataType, **kwargs): 

1037 """Return an appropriate data product. 

1038 

1039 Parameters 

1040 ---------- 

1041 dataType : `str` 

1042 Type of data product to return. 

1043 

1044 Returns 

1045 ------- 

1046 mock : IsrMock.run() result 

1047 The output product. 

1048 """ 

1049 if "_filename" in dataType: 

1050 return tempfile.mktemp(), "mock" 

1051 elif 'transmission_' in dataType: 

1052 return TransmissionMock(config=self.config).run() 

1053 elif dataType == 'ccdExposureId': 

1054 return 20090913 

1055 elif dataType == 'camera': 

1056 return IsrMock(config=self.config).getCamera() 

1057 elif dataType == 'raw': 

1058 return CalibratedRawMock(config=self.config).run() 

1059 elif dataType == 'bias': 

1060 return BiasMock(config=self.config).run() 

1061 elif dataType == 'dark': 

1062 return DarkMock(config=self.config).run() 

1063 elif dataType == 'flat': 

1064 return FlatMock(config=self.config).run() 

1065 elif dataType == 'fringe': 

1066 fringes = [] 

1067 configCopy = copy.deepcopy(self.config) 

1068 for scale, x, y in zip(self.config.fringeScale, self.config.fringeX0, self.config.fringeY0): 

1069 configCopy.fringeScale = [1.0] 

1070 configCopy.fringeX0 = [x] 

1071 configCopy.fringeY0 = [y] 

1072 fringes.append(FringeMock(config=configCopy).run()) 

1073 return fringes 

1074 elif dataType == 'defects': 

1075 return DefectMock(config=self.config).run() 

1076 elif dataType == 'bfKernel': 

1077 return BfKernelMock(config=self.config).run() 

1078 elif dataType == 'linearizer': 

1079 return None 

1080 elif dataType == 'crosstalkSources': 

1081 return None 

1082 else: 

1083 return None