Coverage for python/lsst/ip/isr/isrMockLSST.py: 16%

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 

22__all__ = ["IsrMockLSSTConfig", "IsrMockLSST", "RawMockLSST", 

23 "CalibratedRawMockLSST", "ReferenceMockLSST", 

24 "BiasMockLSST", "DarkMockLSST", "FlatMockLSST", "FringeMockLSST", 

25 "BfKernelMockLSST", "DefectMockLSST", "CrosstalkCoeffMockLSST", 

26 "TransmissionMockLSST"] 

27 

28import numpy as np 

29import galsim 

30 

31import lsst.geom as geom 

32import lsst.pex.config as pexConfig 

33import lsst.afw.detection as afwDetection 

34import lsst.afw.math as afwMath 

35from lsst.afw.cameraGeom import ReadoutCorner 

36from lsst.daf.base import PropertyList 

37from .crosstalk import CrosstalkCalib 

38from .isrMock import IsrMockConfig, IsrMock 

39from .defects import Defects 

40from .assembleCcdTask import AssembleCcdTask 

41from .linearize import Linearizer 

42from .brighterFatterKernel import BrighterFatterKernel 

43from .deferredCharge import ( 

44 SegmentSimulator, 

45 FloatingOutputAmplifier, 

46 DeferredChargeCalib 

47) 

48 

49 

50class IsrMockLSSTConfig(IsrMockConfig): 

51 """Configuration parameters for isrMockLSST. 

52 """ 

53 # Detector parameters and "Exposure" parameters, 

54 # mostly inherited from IsrMockConfig. 

55 isLsstLike = pexConfig.Field( 

56 dtype=bool, 

57 default=True, 

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

59 ) 

60 calibMode = pexConfig.Field( 

61 dtype=bool, 

62 default=False, 

63 doc="Set to true to produce mock calibration products, e.g. combined bias, dark, flat, etc.", 

64 ) 

65 doAdd2DBias = pexConfig.Field( 

66 dtype=bool, 

67 default=True, 

68 doc="Add 2D bias residual frame to data.", 

69 ) 

70 doAddBrightDefects = pexConfig.Field( 

71 dtype=bool, 

72 default=True, 

73 doc="Add bright defects (bad column) to data.", 

74 ) 

75 brightDefectLevel = pexConfig.Field( 

76 dtype=float, 

77 default=30000.0, 

78 doc="Bright defect level (electron).", 

79 ) 

80 doAddBadParallelOverscanColumn = pexConfig.Field( 

81 dtype=bool, 

82 default=True, 

83 doc="Add a bad column to the parallel overscan.", 

84 ) 

85 badParallelOverscanColumnLevel = pexConfig.Field( 

86 dtype=float, 

87 default=300000., 

88 doc="Bright parallel overscan column level (electron). Should be above saturation.", 

89 ) 

90 doAddBadParallelOverscanColumnNeighbors = pexConfig.Field( 

91 dtype=bool, 

92 default=True, 

93 doc="Add low-level bad columns next to parallel overscan bad column.", 

94 ) 

95 badParallelOverscanColumnNeighborsLevel = pexConfig.Field( 

96 dtype=float, 

97 default=50.0, 

98 doc="Bright parallel overscan column neighbors level (electron).", 

99 ) 

100 doAddBrighterFatter = pexConfig.Field( 

101 dtype=bool, 

102 default=False, 

103 doc="Add brighter fatter and/or diffusion effects to image.", 

104 ) 

105 doAddDeferredCharge = pexConfig.Field( 

106 dtype=bool, 

107 default=False, 

108 doc="Add serial CTI at the amp level?", 

109 ) 

110 bfStrength = pexConfig.Field( 

111 dtype=float, 

112 default=2.0, 

113 doc="The brighter fatter effect scaling parameter (cannot be zero)." 

114 "Nominally = 1, but = 2 is more realistic." 

115 ) 

116 nRecalc = pexConfig.Field( 

117 dtype=int, 

118 default=10000, 

119 doc="Number of electrons to accumulate before recalculating pixel shapes.", 

120 ) 

121 doAddClockInjectedOffset = pexConfig.Field( 

122 dtype=bool, 

123 default=True, 

124 doc="Add clock-injected offset to data (on-chip bias level).", 

125 ) 

126 clockInjectedOffsetLevel = pexConfig.Field( 

127 dtype=float, 

128 default=8500.0, 

129 doc="Clock-injected offset (on-chip bias level), in electron.", 

130 ) 

131 noise2DBias = pexConfig.Field( 

132 dtype=float, 

133 default=2.0, 

134 doc="Noise (in electron) to generate a 2D bias residual frame.", 

135 ) 

136 doAddDarkNoiseOnly = pexConfig.Field( 

137 dtype=bool, 

138 default=False, 

139 doc="Add only dark current noise, for testing consistency.", 

140 ) 

141 doAddParallelOverscanRamp = pexConfig.Field( 

142 dtype=bool, 

143 default=True, 

144 doc="Add overscan ramp to parallel overscan and data regions.", 

145 ) 

146 doAddSerialOverscanRamp = pexConfig.Field( 

147 dtype=bool, 

148 default=True, 

149 doc="Add overscan ramp to serial overscan and data regions.", 

150 ) 

151 doAddHighSignalNonlinearity = pexConfig.Field( 

152 dtype=bool, 

153 default=True, 

154 doc="Add high signal non-linearity to overscan and data regions?", 

155 ) 

156 doAddLowSignalNonlinearity = pexConfig.Field( 

157 dtype=bool, 

158 default=False, 

159 doc="Add low signal non-linearity to overscan and data regions? (Not supported yet.)", 

160 ) 

161 highSignalNonlinearityThreshold = pexConfig.Field( 

162 dtype=float, 

163 default=40_000., 

164 doc="Threshold (in adu) for the non-linearity to be considered ``high signal``.", 

165 ) 

166 doApplyGain = pexConfig.Field( 

167 dtype=bool, 

168 default=True, 

169 doc="Add gain to data.", 

170 ) 

171 doRoundAdu = pexConfig.Field( 

172 dtype=bool, 

173 default=True, 

174 doc="Round adu values to nearest integer.", 

175 ) 

176 gainDict = pexConfig.DictField( 

177 keytype=str, 

178 itemtype=float, 

179 doc="Dictionary of amp name to gain; any amps not listed will use " 

180 "config.gain as the value. Units are electron/adu.", 

181 default={ 

182 "C:0,0": 1.65, 

183 "C:0,1": 1.60, 

184 "C:0,2": 1.55, 

185 "C:0,3": 1.70, 

186 "C:1,0": 1.75, 

187 "C:1,1": 1.80, 

188 "C:1,2": 1.85, 

189 "C:1,3": 1.70, 

190 }, 

191 ) 

192 assembleCcd = pexConfig.ConfigurableField( 

193 target=AssembleCcdTask, 

194 doc="CCD assembly task; used for defect box conversions.", 

195 ) 

196 

197 def validate(self): 

198 super().validate() 

199 

200 if self.doAddLowSignalNonlinearity: 

201 raise NotImplementedError("Low signal non-linearity is not implemented.") 

202 

203 if self.doAddDeferredCharge and self.isTrimmed: 

204 raise NotImplementedError("Must be untrimmed for mock serial CTI to" 

205 "realistically add charge into overscan regions.") 

206 

207 def setDefaults(self): 

208 super().setDefaults() 

209 

210 self.gain = 1.7 # Default value. 

211 self.skyLevel = 1700.0 # electron 

212 self.sourceFlux = [50_000.0] # electron 

213 self.sourceX = [35.0] # pixel 

214 self.sourceY = [37.0] # pixel 

215 self.overscanScale = 170.0 # electron 

216 self.biasLevel = 20_000.0 # adu 

217 self.doAddCrosstalk = True 

218 

219 

220class IsrMockLSST(IsrMock): 

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

222 """ 

223 ConfigClass = IsrMockLSSTConfig 

224 _DefaultName = "isrMockLSST" 

225 

226 def __init__(self, **kwargs): 

227 super().__init__(**kwargs) 

228 

229 # Get kernel derived from imSim generated flats with BFE. The kernel 

230 # was used for Ops Rehearsal 3 for LSSTCam-type sensors 

231 # See https://rubinobs.atlassian.net/browse/DM-43059 for more details. 

232 self.bfKernel = np.array([[4.83499829e-01, 8.10171823e-01, 5.31096720e-01, 

233 3.54369868e-02, -8.44782871e-01, -1.64614462e+00, 

234 -3.83933101e+00, -5.60243416e+00, -6.51691578e+00, 

235 -5.60243416e+00, -3.83933101e+00, -1.64614462e+00, 

236 -8.44782871e-01, 3.54369868e-02, 5.31096720e-01, 

237 8.10171823e-01, 4.83499829e-01], 

238 [1.12382749e+00, 2.22609074e+00, 1.27877807e+00, 

239 4.55434098e-01, -1.76842385e+00, -1.90046460e+00, 

240 -8.10874526e+00, -1.20534899e+01, -1.48627948e+01, 

241 -1.20534899e+01, -8.10874526e+00, -1.90046460e+00, 

242 -1.76842385e+00, 4.55434098e-01, 1.27877807e+00, 

243 2.22609074e+00, 1.12382749e+00], 

244 [1.78571940e+00, 4.38918110e+00, 3.95098587e+00, 

245 3.70961649e-01, -3.48151981e+00, -9.61567736e+00, 

246 -1.78621172e+01, -2.32278872e+01, -2.31833727e+01, 

247 -2.32278872e+01, -1.78621172e+01, -9.61567736e+00, 

248 -3.48151981e+00, 3.70961649e-01, 3.95098587e+00, 

249 4.38918110e+00, 1.78571940e+00], 

250 [1.62986900e+00, 3.67851228e+00, 5.68645252e+00, 

251 2.15342566e-01, -8.89937202e+00, -1.44739813e+01, 

252 -2.98952660e+01, -4.37420817e+01, -4.83160958e+01, 

253 -4.37420817e+01, -2.98952660e+01, -1.44739813e+01, 

254 -8.89937202e+00, 2.15342566e-01, 5.68645252e+00, 

255 3.67851228e+00, 1.62986900e+00], 

256 [1.05524430e+00, 1.71917897e+00, 1.73105590e+00, 

257 -2.10088420e+00, -1.15118208e+01, -2.55007598e+01, 

258 -4.73056159e+01, -6.97257685e+01, -8.09264433e+01, 

259 -6.97257685e+01, -4.73056159e+01, -2.55007598e+01, 

260 -1.15118208e+01, -2.10088420e+00, 1.73105590e+00, 

261 1.71917897e+00, 1.05524430e+00], 

262 [8.71929228e-01, 5.41025574e-01, 9.47560771e-01, 

263 -5.75314708e-01, -7.46104027e+00, -4.42314481e+01, 

264 -9.54126971e+01, -1.61603201e+02, -2.07520692e+02, 

265 -1.61603201e+02, -9.54126971e+01, -4.42314481e+01, 

266 -7.46104027e+00, -5.75314708e-01, 9.47560771e-01, 

267 5.41025574e-01, 8.71929228e-01], 

268 [1.89144704e+00, 3.57543979e+00, -6.91419168e-02, 

269 -3.37950835e+00, -1.46695089e+01, -7.22850746e+01, 

270 -1.65563055e+02, -3.10820425e+02, -4.70026655e+02, 

271 -3.10820425e+02, -1.65563055e+02, -7.22850746e+01, 

272 -1.46695089e+01, -3.37950835e+00, -6.91419168e-02, 

273 3.57543979e+00, 1.89144704e+00], 

274 [3.11841913e+00, 7.84024994e+00, 1.88495248e+00, 

275 -7.69011009e+00, -2.71782400e+01, -1.04343326e+02, 

276 -2.47561370e+02, -5.32959841e+02, -1.16529012e+03, 

277 -5.32959841e+02, -2.47561370e+02, -1.04343326e+02, 

278 -2.71782400e+01, -7.69011009e+00, 1.88495248e+00, 

279 7.84024994e+00, 3.11841913e+00], 

280 [2.74197956e+00, 4.73107997e+00, -9.48352966e-01, 

281 -9.44822832e+00, -3.06477671e+01, -1.26788739e+02, 

282 -3.22828411e+02, -8.47943472e+02, -3.87702420e+03, 

283 -8.47943472e+02, -3.22828411e+02, -1.26788739e+02, 

284 -3.06477671e+01, -9.44822832e+00, -9.48352966e-01, 

285 4.73107997e+00, 2.74197956e+00], 

286 [3.11841913e+00, 7.84024994e+00, 1.88495248e+00, 

287 -7.69011009e+00, -2.71782400e+01, -1.04343326e+02, 

288 -2.47561370e+02, -5.32959841e+02, -1.16529012e+03, 

289 -5.32959841e+02, -2.47561370e+02, -1.04343326e+02, 

290 -2.71782400e+01, -7.69011009e+00, 1.88495248e+00, 

291 7.84024994e+00, 3.11841913e+00], 

292 [1.89144704e+00, 3.57543979e+00, -6.91419168e-02, 

293 -3.37950835e+00, -1.46695089e+01, -7.22850746e+01, 

294 -1.65563055e+02, -3.10820425e+02, -4.70026655e+02, 

295 -3.10820425e+02, -1.65563055e+02, -7.22850746e+01, 

296 -1.46695089e+01, -3.37950835e+00, -6.91419168e-02, 

297 3.57543979e+00, 1.89144704e+00], 

298 [8.71929228e-01, 5.41025574e-01, 9.47560771e-01, 

299 -5.75314708e-01, -7.46104027e+00, -4.42314481e+01, 

300 -9.54126971e+01, -1.61603201e+02, -2.07520692e+02, 

301 -1.61603201e+02, -9.54126971e+01, -4.42314481e+01, 

302 -7.46104027e+00, -5.75314708e-01, 9.47560771e-01, 

303 5.41025574e-01, 8.71929228e-01], 

304 [1.05524430e+00, 1.71917897e+00, 1.73105590e+00, 

305 -2.10088420e+00, -1.15118208e+01, -2.55007598e+01, 

306 -4.73056159e+01, -6.97257685e+01, -8.09264433e+01, 

307 -6.97257685e+01, -4.73056159e+01, -2.55007598e+01, 

308 -1.15118208e+01, -2.10088420e+00, 1.73105590e+00, 

309 1.71917897e+00, 1.05524430e+00], 

310 [1.62986900e+00, 3.67851228e+00, 5.68645252e+00, 

311 2.15342566e-01, -8.89937202e+00, -1.44739813e+01, 

312 -2.98952660e+01, -4.37420817e+01, -4.83160958e+01, 

313 -4.37420817e+01, -2.98952660e+01, -1.44739813e+01, 

314 -8.89937202e+00, 2.15342566e-01, 5.68645252e+00, 

315 3.67851228e+00, 1.62986900e+00], 

316 [1.78571940e+00, 4.38918110e+00, 3.95098587e+00, 

317 3.70961649e-01, -3.48151981e+00, -9.61567736e+00, 

318 -1.78621172e+01, -2.32278872e+01, -2.31833727e+01, 

319 -2.32278872e+01, -1.78621172e+01, -9.61567736e+00, 

320 -3.48151981e+00, 3.70961649e-01, 3.95098587e+00, 

321 4.38918110e+00, 1.78571940e+00], 

322 [1.12382749e+00, 2.22609074e+00, 1.27877807e+00, 

323 4.55434098e-01, -1.76842385e+00, -1.90046460e+00, 

324 -8.10874526e+00, -1.20534899e+01, -1.48627948e+01, 

325 -1.20534899e+01, -8.10874526e+00, -1.90046460e+00, 

326 -1.76842385e+00, 4.55434098e-01, 1.27877807e+00, 

327 2.22609074e+00, 1.12382749e+00], 

328 [4.83499829e-01, 8.10171823e-01, 5.31096720e-01, 

329 3.54369868e-02, -8.44782871e-01, -1.64614462+00, 

330 -3.83933101e+00, -5.60243416e+00, -6.51691578e+00, 

331 -5.60243416e+00, -3.83933101e+00, -1.64614462e+00, 

332 -8.44782871e-01, 3.54369868e-02, 5.31096720e-01, 

333 8.10171823e-01, 4.83499829e-01]]) * 1e-10 

334 

335 # Spline trap coefficients and the ctiCalibDict are all taken from a 

336 # cti calibration measured from LSSTCam sensor R03_S12 during Run 5 

337 # EO testing. These are the coefficients for the spline trap model 

338 # used in the deferred charge calibration. The collection can be 

339 # found in /repo/ir2: u/abrought/13144/cti (processed 3/4/2024). 

340 self.splineTrapCoeffs = np.array([0.0, 28.1, 47.4, 56.4, 66.6, 78.6, 92.4, 109.4, 

341 129.0, 151.9, 179.4, 211.9, 250.5, 296.2, 350.0, 

342 413.5, 488.0, 576.0, 680.4, 753.0, 888.2, 1040.5, 

343 1254.1, 1478.9, 1747.0, 2055.7, 2416.9, 2855.2, 

344 3361.9, 3969.4, 4665.9, 5405.3, 6380.0, 7516.7, 

345 8875.9, 10488.6, 12681.9, 14974.2, 17257.6, 20366.5, 

346 24026.7, 28372.1, 33451.7, 39550.4, 46624.8, 55042.9, 

347 64862.7, 76503.1, 90265.6, 106384.2, 0.0, 0.0, 0.0, 

348 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 

349 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 

350 0.1, 0.2, 0.6, 0.1, 0.0, 0.1, 0.0, 0.6, 0.3, 0.5, 0.8, 

351 0.8, 1.5, 2.0, 1.8, 2.4, 2.6, 3.7, 5.0, 6.4, 8.4, 10.9, 

352 14.5, 21.1, 28.9]) 

353 

354 self.ctiCalibDict = {'inputGain': {'C:0,0': 1.5, 

355 'C:0,1': 1.5, 

356 'C:0,2': 1.5, 

357 'C:0,3': 1.5, 

358 'C:1,0': 1.5, 

359 'C:1,1': 1.5, 

360 'C:1,2': 1.5, 

361 'C:1,3': 1.5}, 

362 'driftScale': {'C:0,0': 0.000127, 

363 'C:0,1': 0.000137, 

364 'C:0,2': 0.000138, 

365 'C:0,3': 0.000147, 

366 'C:1,0': 0.000147, 

367 'C:1,1': 0.000122, 

368 'C:1,2': 0.000123, 

369 'C:1,3': 0.000116}, 

370 'decayTime': {'C:0,0': 2.30, 

371 'C:0,1': 2.21, 

372 'C:0,2': 2.28, 

373 'C:0,3': 2.34, 

374 'C:1,0': 2.30, 

375 'C:1,1': 2.40, 

376 'C:1,2': 2.51, 

377 'C:1,3': 2.21}, 

378 'globalCti': {'C:0,0': 5.25e-07, 

379 'C:0,1': 5.38e-07, 

380 'C:0,2': 5.80e-07, 

381 'C:0,3': 5.91e-07, 

382 'C:1,0': 6.24e-07, 

383 'C:1,1': 5.72e-07, 

384 'C:1,2': 5.60e-07, 

385 'C:1,3': 4.40e-07}, 

386 'signals': {'C:0,0': np.linspace(1.0e2, 1.0e5, 10), 

387 'C:0,1': np.linspace(1.0e2, 1.0e5, 10), 

388 'C:0,2': np.linspace(1.0e2, 1.0e5, 10), 

389 'C:0,3': np.linspace(1.0e2, 1.0e5, 10), 

390 'C:1,0': np.linspace(1.0e2, 1.0e5, 10), 

391 'C:1,1': np.linspace(1.0e2, 1.0e5, 10), 

392 'C:1,2': np.linspace(1.0e2, 1.0e5, 10), 

393 'C:1,3': np.linspace(1.0e2, 1.0e5, 10)}, 

394 'serialEper': {'C:0,0': np.full(10, 5.25e-07), 

395 'C:0,1': np.full(10, 5.38e-07), 

396 'C:0,2': np.full(10, 5.80e-07), 

397 'C:0,3': np.full(10, 5.91e-07), 

398 'C:1,0': np.full(10, 6.24e-07), 

399 'C:1,1': np.full(10, 5.72e-07), 

400 'C:1,2': np.full(10, 5.60e-07), 

401 'C:1,3': np.full(10, 4.40e-07)}, 

402 'parallelEper': {'C:0,0': np.full(10, 5.25e-07), 

403 'C:0,1': np.full(10, 5.38e-07), 

404 'C:0,2': np.full(10, 5.80e-07), 

405 'C:0,3': np.full(10, 5.91e-07), 

406 'C:1,0': np.full(10, 6.24e-07), 

407 'C:1,1': np.full(10, 5.72e-07), 

408 'C:1,2': np.full(10, 5.60e-07), 

409 'C:1,3': np.full(10, 4.40e-07)}, 

410 'serialCtiTurnoff': {'C:0,0': 1.0e5, 

411 'C:0,1': 1.0e5, 

412 'C:0,2': 1.0e5, 

413 'C:0,3': 1.0e5, 

414 'C:1,0': 1.0e5, 

415 'C:1,1': 1.0e5, 

416 'C:1,2': 1.0e5, 

417 'C:1,3': 1.0e5}, 

418 'parallelCtiTurnoff': {'C:0,0': 1.0e5, 

419 'C:0,1': 1.0e5, 

420 'C:0,2': 1.0e5, 

421 'C:0,3': 1.0e5, 

422 'C:1,0': 1.0e5, 

423 'C:1,1': 1.0e5, 

424 'C:1,2': 1.0e5, 

425 'C:1,3': 1.0e5}, 

426 'serialCtiTurnoffSamplingErr': {'C:0,0': 1.0e3, 

427 'C:0,1': 1.0e3, 

428 'C:0,2': 1.0e3, 

429 'C:0,3': 1.0e3, 

430 'C:1,0': 1.0e3, 

431 'C:1,1': 1.0e3, 

432 'C:1,2': 1.0e3, 

433 'C:1,3': 1.0e3}, 

434 'parallelCtiTurnoffSamplingErr': {'C:0,0': 1.0e3, 

435 'C:0,1': 1.0e3, 

436 'C:0,2': 1.0e3, 

437 'C:0,3': 1.0e3, 

438 'C:1,0': 1.0e3, 

439 'C:1,1': 1.0e3, 

440 'C:1,2': 1.0e3, 

441 'C:1,3': 1.0e3}, 

442 'serialTraps': {'C:0,0': {'size': 20000.0, 

443 'emissionTime': 0.4, 

444 'pixel': 1, 

445 'trap_type': 'spline', 

446 'coeffs': self.splineTrapCoeffs}, 

447 'C:0,1': {'size': 20000.0, 

448 'emissionTime': 0.4, 

449 'pixel': 1, 

450 'trap_type': 'spline', 

451 'coeffs': self.splineTrapCoeffs}, 

452 'C:0,2': {'size': 20000.0, 

453 'emissionTime': 0.4, 

454 'pixel': 1, 

455 'trap_type': 'spline', 

456 'coeffs': self.splineTrapCoeffs}, 

457 'C:0,3': {'size': 20000.0, 

458 'emissionTime': 0.4, 

459 'pixel': 1, 

460 'trap_type': 'spline', 

461 'coeffs': self.splineTrapCoeffs}, 

462 'C:1,0': {'size': 20000.0, 

463 'emissionTime': 0.4, 

464 'pixel': 1, 

465 'trap_type': 'spline', 

466 'coeffs': self.splineTrapCoeffs}, 

467 'C:1,1': {'size': 20000.0, 

468 'emissionTime': 0.4, 

469 'pixel': 1, 

470 'trap_type': 'spline', 

471 'coeffs': self.splineTrapCoeffs}, 

472 'C:1,2': {'size': 20000.0, 

473 'emissionTime': 0.4, 

474 'pixel': 1, 

475 'trap_type': 'spline', 

476 'coeffs': self.splineTrapCoeffs}, 

477 'C:1,3': {'size': 20000.0, 

478 'emissionTime': 0.4, 

479 'pixel': 1, 

480 'trap_type': 'spline', 

481 'coeffs': self.splineTrapCoeffs}}} 

482 

483 self.deferredChargeCalib = self.makeDeferredChargeCalib() 

484 

485 # Cross-talk coeffs are defined in the parent class. 

486 

487 self.makeSubtask("assembleCcd") 

488 

489 def run(self): 

490 """Generate a mock ISR product following LSSTCam ISR, and return it. 

491 

492 Returns 

493 ------- 

494 image : `lsst.afw.image.Exposure` 

495 Simulated ISR image with signals added. 

496 dataProduct : 

497 Simulated ISR data products. 

498 None : 

499 Returned if no valid configuration was found. 

500 

501 Raises 

502 ------ 

503 RuntimeError 

504 Raised if both doGenerateImage and doGenerateData are specified. 

505 """ 

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

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

508 elif self.config.doGenerateImage: 

509 return self.makeImage() 

510 elif self.config.doGenerateData: 

511 return self.makeData() 

512 else: 

513 return None 

514 

515 def makeImage(self): 

516 """Generate a simulated ISR LSST image. 

517 

518 Returns 

519 ------- 

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

521 Simulated ISR image data. 

522 

523 Notes 

524 ----- 

525 This method constructs a "raw" data image. 

526 """ 

527 exposure = self.getExposure() 

528 

529 # Set up random number generators for consistency of components, 

530 # no matter the group that are configured. 

531 rngSky = np.random.RandomState(seed=self.config.rngSeed + 1) 

532 rngDark = np.random.RandomState(seed=self.config.rngSeed + 2) 

533 rng2DBias = np.random.RandomState(seed=self.config.rngSeed + 3) 

534 rngOverscan = np.random.RandomState(seed=self.config.rngSeed + 4) 

535 rngReadNoise = np.random.RandomState(seed=self.config.rngSeed + 5) 

536 rngBrighterFatter = galsim.BaseDeviate(self.config.rngSeed + 6) 

537 

538 # Create the linearizer if we will need it. 

539 if self.config.doAddHighSignalNonlinearity: 

540 linearizer = LinearizerMockLSST().run() 

541 

542 # We introduce effects as they happen from a source to the signal, 

543 # so the effects go from electron to adu. 

544 # The ISR steps will then correct these effects in the reverse order. 

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

546 # Get image bbox and data 

547 bbox = None 

548 if self.config.isTrimmed: 

549 bbox = amp.getBBox() 

550 bboxFull = bbox 

551 else: 

552 bbox = amp.getRawDataBBox() 

553 bboxFull = amp.getRawBBox() 

554 

555 # This is the image data (excluding pre/overscans). 

556 ampImageData = exposure.image[bbox] 

557 # This is the full data (including pre/overscans if untrimmed). 

558 ampFullData = exposure.image[bboxFull] 

559 

560 # Astrophysical signals are all in electron (e-). 

561 # These are only applied to the imaging portion of the 

562 # amplifier (ampImageData) 

563 

564 if self.config.doAddSky: 

565 # The sky effects are in electron. 

566 self.amplifierAddNoise( 

567 ampImageData, 

568 self.config.skyLevel, 

569 np.sqrt(self.config.skyLevel), 

570 rng=rngSky, 

571 ) 

572 

573 if self.config.doAddSource: 

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

575 self.config.sourceFlux, 

576 self.config.sourceX, 

577 self.config.sourceY): 

578 if idx == sourceAmp: 

579 # The source flux is in electron. 

580 self.amplifierAddSource(ampImageData, sourceFlux, sourceX, sourceY) 

581 

582 if self.config.doAddFringe: 

583 # Fringes are added in electron. 

584 self.amplifierAddFringe(amp, 

585 ampImageData, 

586 np.array(self.config.fringeScale), 

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

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

589 

590 if self.config.doAddFlat: 

591 if self.config.calibMode: 

592 # In case we are making a combined flat, 

593 # add a non-zero signal so the mock flat can be multiplied 

594 self.amplifierAddNoise(ampImageData, 1.0, 0.0) 

595 # Multiply each amplifier by a Gaussian centered on u0 and v0 

596 u0 = exposure.getDetector().getBBox().getDimensions().getX()/2. 

597 v0 = exposure.getDetector().getBBox().getDimensions().getY()/2. 

598 self.amplifierMultiplyFlat(amp, ampImageData, self.config.flatDrop, u0=u0, v0=v0) 

599 

600 # On-chip electronic effects. 

601 

602 # 1. Add bright defect(s). 

603 if self.config.doAddBrightDefects: 

604 defectList = self.makeDefectList(isTrimmed=self.config.isTrimmed) 

605 

606 for defect in defectList: 

607 exposure.image[defect.getBBox()] = self.config.brightDefectLevel 

608 

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

610 # Get image bbox and data 

611 bbox = None 

612 if self.config.isTrimmed: 

613 bbox = amp.getBBox() 

614 bboxFull = bbox 

615 else: 

616 bbox = amp.getRawDataBBox() 

617 bboxFull = amp.getRawBBox() 

618 

619 # This is the image data (excluding pre/overscans). 

620 ampImageData = exposure.image[bbox] 

621 # This is the full data (including pre/overscans if untrimmed). 

622 ampFullData = exposure.image[bboxFull] 

623 

624 # 2. Add dark current (electron) to imaging portion of the amp. 

625 if self.config.doAddDark or self.config.doAddDarkNoiseOnly: 

626 if self.config.doAddDarkNoiseOnly: 

627 darkLevel = 0.0 

628 else: 

629 darkLevel = self.config.darkRate * self.config.darkTime 

630 if self.config.calibMode: 

631 darkNoise = 0.0 

632 else: 

633 darkNoise = np.sqrt(self.config.darkRate * self.config.darkTime) 

634 

635 self.amplifierAddNoise(ampImageData, darkLevel, darkNoise, rng=rngDark) 

636 

637 # 3. Add BF effect (electron) to imaging portion of the amp. 

638 if self.config.doAddBrighterFatter is True: 

639 self.amplifierAddBrighterFatter( 

640 ampImageData, 

641 rngBrighterFatter, 

642 self.config.bfStrength, 

643 self.config.nRecalc, 

644 ) 

645 

646 # 4. Add serial CTI (electron) to amplifier (imaging + overscan). 

647 if self.config.doAddDeferredCharge: 

648 # Get the free charge area for the amplifier. 

649 self.amplifierAddDeferredCharge(exposure, amp) 

650 

651 # 5. Add 2D bias residual (electron) to imaging portion of the amp. 

652 if self.config.doAdd2DBias: 

653 # For now we use an unstructured noise field to add some 

654 # consistent 2D bias residual that can be subtracted. In 

655 # the future this can be made into a warm corner (for example). 

656 self.amplifierAddNoise( 

657 ampImageData, 

658 0.0, 

659 self.config.noise2DBias, 

660 rng=rng2DBias, 

661 ) 

662 

663 # 6. Add clock-injected offset (electron) to amplifer 

664 # (imaging + overscan). 

665 # This is just an offset that will be crosstalked and modified by 

666 # the gain, and does not have a noise associated with it. 

667 if self.config.doAddClockInjectedOffset: 

668 self.amplifierAddNoise( 

669 ampFullData, 

670 self.config.clockInjectedOffsetLevel, 

671 0.0, 

672 ) 

673 

674 # 7./8. Add serial and parallel overscan slopes (electron) 

675 # (imaging + overscan) 

676 if (self.config.doAddParallelOverscanRamp or self.config.doAddSerialOverscanRamp) and \ 

677 not self.config.isTrimmed: 

678 

679 if self.config.doAddParallelOverscanRamp: 

680 # Apply gradient along the X axis. 

681 self.amplifierAddXGradient(ampFullData, -1.0 * self.config.overscanScale, 

682 1.0 * self.config.overscanScale) 

683 

684 if self.config.doAddSerialOverscanRamp: 

685 # Apply the gradient along the Y axis. 

686 self.amplifierAddYGradient(ampFullData, -1.0 * self.config.overscanScale, 

687 1.0 * self.config.overscanScale) 

688 

689 # 9. Add non-linearity (electron) to amplifier 

690 # (imaging + overscan). 

691 if self.config.doAddHighSignalNonlinearity: 

692 # The linearizer coefficients come from makeLinearizer(). 

693 if linearizer.linearityType[amp.getName()] != "Spline": 

694 raise RuntimeError("IsrMockLSST only supports spline non-linearity.") 

695 

696 coeffs = linearizer.linearityCoeffs[amp.getName()] 

697 centers, values = np.split(coeffs, 2) 

698 

699 # This is an application of high signal non-linearity, so we 

700 # set the lower values to 0.0 (this cut is arbitrary). 

701 values[centers < self.config.highSignalNonlinearityThreshold] = 0.0 

702 

703 # The linearizer is units of adu, so convert to electron 

704 centers *= self.config.gainDict[amp.getName()] 

705 values *= self.config.gainDict[amp.getName()] 

706 

707 # Note that the linearity spline is in "overscan subtracted" 

708 # units so needs to be applied without the clock-injected 

709 # offset. 

710 self.amplifierAddNonlinearity( 

711 ampFullData, 

712 centers, 

713 values, 

714 self.config.clockInjectedOffsetLevel if self.config.doAddClockInjectedOffset else 0.0, 

715 ) 

716 

717 # 10. Add read noise (electron) to the amplifier 

718 # (imaging + overscan). 

719 # Unsure if this should be before or after crosstalk. 

720 # Probably some of both; hopefully doesn't matter. 

721 if not self.config.calibMode: 

722 # Add read noise to the imaging region. 

723 self.amplifierAddNoise( 

724 ampImageData, 

725 0.0, 

726 self.config.readNoise, 

727 rng=rngReadNoise, 

728 ) 

729 

730 # If not trimmed, add to the overscan regions. 

731 if not self.config.isTrimmed: 

732 parallelOverscanBBox = amp.getRawParallelOverscanBBox() 

733 parallelOverscanData = exposure.image[parallelOverscanBBox] 

734 

735 serialOverscanBBox = self.getFullSerialOverscanBBox(amp) 

736 serialOverscanData = exposure.image[serialOverscanBBox] 

737 

738 # Add read noise of mean 0 

739 # to the parallel and serial overscan regions. 

740 self.amplifierAddNoise( 

741 parallelOverscanData, 

742 0.0, 

743 self.config.readNoise, 

744 rng=rngOverscan, 

745 ) 

746 self.amplifierAddNoise( 

747 serialOverscanData, 

748 0.0, 

749 self.config.readNoise, 

750 rng=rngOverscan, 

751 ) 

752 

753 # 7b. Add bad column to the parallel overscan region. 

754 if self.config.doAddBadParallelOverscanColumn and not self.config.isTrimmed: 

755 # We want to place this right above the defect, to simulate 

756 # bleeding into the parallel overscan region. 

757 amp = exposure.getDetector()[2] 

758 parBBox = amp.getRawParallelOverscanBBox() 

759 bboxBad = geom.Box2I( 

760 corner=geom.Point2I(50, parBBox.getMinY()), 

761 dimensions=geom.Extent2I(1, parBBox.getHeight()), 

762 ) 

763 exposure[bboxBad].image.array[:, :] += self.config.badParallelOverscanColumnLevel 

764 

765 if self.config.doAddBadParallelOverscanColumnNeighbors: 

766 for neighbor in [49, 51]: 

767 bboxBad = geom.Box2I( 

768 corner=geom.Point2I(neighbor, parBBox.getMinY()), 

769 dimensions=geom.Extent2I(1, parBBox.getHeight()), 

770 ) 

771 exposure[bboxBad].image.array[:, :] += self.config.badParallelOverscanColumnNeighborsLevel 

772 

773 # 11. Add crosstalk (electron) to all the amplifiers 

774 # (imaging + overscan). 

775 if self.config.doAddCrosstalk: 

776 ctCalib = CrosstalkCalib() 

777 # We use the regular subtractCrosstalk code but with a negative 

778 # sign on the crosstalk coefficients so it adds instead of 

779 # subtracts. We only apply the signal plane (ignoreVariance, 

780 # subtrahendMasking) with a very large pixel to mask to ensure 

781 # no crosstalk mask bits are set. 

782 ctCalib.subtractCrosstalk( 

783 exposure, 

784 crosstalkCoeffs=-1*self.crosstalkCoeffs, 

785 doSubtrahendMasking=True, 

786 minPixelToMask=np.inf, 

787 ignoreVariance=True, 

788 fullAmplifier=True, 

789 ) 

790 

791 for amp in exposure.getDetector(): 

792 # Get image bbox and data (again). 

793 bbox = None 

794 if self.config.isTrimmed: