Coverage for python/lsst/cp/verify/mergeResults.py: 38%

1# This file is part of cp_verify. 

2# 

3# Developed for the LSST Data Management System. 

4# This product includes software developed by the LSST Project 

5# (http://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 lsst.pipe.base as pipeBase 

22import lsst.pipe.base.connectionTypes as cT 

23import lsst.pex.config as pexConfig 

24 

25 

26__all__ = ['CpVerifyExpMergeConfig', 'CpVerifyExpMergeTask', 

27 'CpVerifyRunMergeConfig', 'CpVerifyRunMergeTask', 

28 'CpVerifyVisitExpMergeConfig', 'CpVerifyVisitExpMergeTask', 

29 'CpVerifyVisitRunMergeConfig', 'CpVerifyVisitRunMergeTask'] 

30 

31 

32class CpVerifyExpMergeConnections(pipeBase.PipelineTaskConnections, 

33 dimensions={"instrument", "exposure"}, 

34 defaultTemplates={}): 

35 inputStats = cT.Input( 

36 name="detectorStats", 

37 doc="Input statistics to merge.", 

38 storageClass="StructuredDataDict", 

39 dimensions=["instrument", "exposure", "detector"], 

40 multiple=True, 

41 ) 

42 camera = cT.PrerequisiteInput( 

43 name="camera", 

44 storageClass="Camera", 

45 doc="Input camera.", 

46 dimensions=["instrument", ], 

47 isCalibration=True, 

48 ) 

49 

50 outputStats = cT.Output( 

51 name="exposureStats", 

52 doc="Output statistics.", 

53 storageClass="StructuredDataDict", 

54 dimensions=["instrument", "exposure"], 

55 ) 

56 

57 

58class CpVerifyExpMergeConfig(pipeBase.PipelineTaskConfig, 

59 pipelineConnections=CpVerifyExpMergeConnections): 

60 """Configuration parameters for exposure stats merging. 

61 """ 

62 exposureStatKeywords = pexConfig.DictField( 

63 keytype=str, 

64 itemtype=str, 

65 doc="Dictionary of statistics to run on the set of detector values. The key should be the test " 

66 "name to record in the output, and the value should be the `lsst.afw.math` statistic name string.", 

67 default={}, 

68 ) 

69 

70 

71class CpVerifyExpMergeTask(pipeBase.PipelineTask, pipeBase.CmdLineTask): 

72 """Merge statistics from detectors together. 

73 """ 

74 ConfigClass = CpVerifyExpMergeConfig 

75 _DefaultName = 'cpVerifyExpMerge' 

76 

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

78 inputs = butlerQC.get(inputRefs) 

79 

80 dimensions = [exp.dataId.byName() for exp in inputRefs.inputStats] 

81 inputs['inputDims'] = dimensions 

82 

83 outputs = self.run(**inputs) 

84 butlerQC.put(outputs, outputRefs) 

85 

86 def run(self, inputStats, camera, inputDims): 

87 """Merge statistics. 

88 

89 Parameters 

90 ---------- 

91 inputStats : `list` [`dict`] 

92 Measured statistics for a detector (from 

93 CpVerifyStatsTask). 

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

95 The camera geometry for this exposure. 

96 inputDims : `list` [`dict`] 

97 List of dictionaries of input data dimensions/values. 

98 Each list entry should contain: 

99 

100 ``"exposure"`` 

101 exposure id value (`int`) 

102 ``"detector"`` 

103 detector id value (`int`) 

104 

105 Returns 

106 ------- 

107 outputStats : `dict` 

108 Merged full exposure statistics. 

109 

110 See Also 

111 -------- 

112 lsst.cp.verify.CpVerifyStatsTask 

113 

114 Notes 

115 ----- 

116 The outputStats should have a yaml representation of the form: 

117 

118 DET: 

119 DetName1: 

120 FAILURES: 

121 - TEST_NAME 

122 STAT: value 

123 STAT2: value2 

124 DetName2: 

125 VERIFY: 

126 TEST: boolean 

127 TEST2: boolean 

128 SUCCESS: boolean 

129 """ 

130 outputStats = {} 

131 success = True 

132 

133 mergedStats = {} 

134 for detStats, dimensions in zip(inputStats, inputDims): 

135 detId = dimensions['detector'] 

136 detName = camera[detId].getName() 

137 calcStats = {} 

138 

139 mergedStats[detName] = detStats 

140 

141 if detStats['SUCCESS'] is True: 

142 calcStats['SUCCESS'] = True 

143 else: 

144 calcStats['SUCCESS'] = False 

145 calcStats['FAILURES'] = list() 

146 success = False 

147 # See if the detector failed 

148 if 'DET' in detStats['VERIFY']: 

149 for testName, testResult in detStats['VERIFY']['DET'].items(): 

150 if testResult is False: 

151 calcStats['FAILURES'].append(testName) 

152 # See if the catalog failed 

153 if 'CATALOG' in detStats['VERIFY']: 

154 for testName, testResult in detStats['VERIFY']['CATALOG'].items(): 

155 if testResult is False: 

156 calcStats['FAILURES'].append(testName) 

157 # See if an amplifier failed 

158 for ampName, ampStats in detStats['VERIFY']['AMP'].items(): 

159 ampSuccess = ampStats.pop('SUCCESS') 

160 if not ampSuccess: 

161 for testName, testResult in ampStats.items(): 

162 if testResult is False: 

163 calcStats['FAILURES'].append(ampName + " " + testName) 

164 

165 outputStats[detName] = calcStats 

166 

167 exposureSuccess = True 

168 if len(self.config.exposureStatKeywords): 

169 outputStats['EXP'] = self.exposureStatistics(mergedStats) 

170 outputStats['VERIFY'], exposureSuccess = self.verify(mergedStats, outputStats) 

171 

172 outputStats['SUCCESS'] = success & exposureSuccess 

173 

174 return pipeBase.Struct( 

175 outputStats=outputStats, 

176 ) 

177 

178 def exposureStatistics(self, statisticsDict): 

179 """Calculate exposure level statistics based on the existing 

180 per-amplifier and per-detector measurements. 

181 

182 Parameters 

183 ---------- 

184 statisticsDictionary : `dict [`str`, `dict` [`str`, scalar]], 

185 Dictionary of measured statistics. The top level 

186 dictionary is keyed on the detector names, and contains 

187 the measured statistics from the per-detector 

188 measurements. 

189 

190 Returns 

191 ------- 

192 outputStatistics : `dict` [`str, scalar] 

193 A dictionary of the statistics measured and their values. 

194 """ 

195 raise NotImplementedError("Subclasses must implement verification criteria.") 

196 

197 def verify(self, detectorStatistics, statisticsDictionary): 

198 

199 """Verify if the measured statistics meet the verification criteria. 

200 

201 Parameters 

202 ---------- 

203 detectorStatistics : `dict` [`str`, `dict` [`str`, scalar]] 

204 Merged set of input detector level statistics. 

205 statisticsDictionary : `dict` [`str`, `dict` [`str`, scalar]] 

206 Dictionary of measured statistics. The inner dictionary 

207 should have keys that are statistic names (`str`) with 

208 values that are some sort of scalar (`int` or `float` are 

209 the mostly likely types). 

210 

211 Returns 

212 ------- 

213 outputStatistics : `dict` [`str`, `dict` [`str`, `bool`]] 

214 A dictionary indexed by the amplifier name, containing 

215 dictionaries of the verification criteria. 

216 success : `bool` 

217 A boolean indicating if all tests have passed. 

218 

219 Raises 

220 ------ 

221 NotImplementedError : 

222 This method must be implemented by the calibration-type 

223 subclass. 

224 """ 

225 raise NotImplementedError("Subclasses must implement verification criteria.") 

226 

227 

228class CpVerifyRunMergeConnections(pipeBase.PipelineTaskConnections, 

229 dimensions={"instrument"}, 

230 defaultTemplates={}): 

231 inputStats = cT.Input( 

232 name="exposureStats", 

233 doc="Input statistics to merge.", 

234 storageClass="StructuredDataDict", 

235 dimensions=["instrument", "exposure"], 

236 multiple=True, 

237 ) 

238 

239 outputStats = cT.Output( 

240 name="runStats", 

241 doc="Output statistics.", 

242 storageClass="StructuredDataDict", 

243 dimensions=["instrument"], 

244 ) 

245 

246 

247class CpVerifyRunMergeConfig(pipeBase.PipelineTaskConfig, 

248 pipelineConnections=CpVerifyRunMergeConnections): 

249 """Configuration paramters for exposure stats merging. 

250 """ 

251 runStatKeywords = pexConfig.DictField( 

252 keytype=str, 

253 itemtype=str, 

254 doc="Dictionary of statistics to run on the set of exposure values. The key should be the test " 

255 "name to record in the output, and the value should be the `lsst.afw.math` statistic name string.", 

256 default={}, 

257 ) 

258 

259 

260class CpVerifyRunMergeTask(pipeBase.PipelineTask, pipeBase.CmdLineTask): 

261 """Merge statistics from detectors together. 

262 """ 

263 ConfigClass = CpVerifyRunMergeConfig 

264 _DefaultName = 'cpVerifyRunMerge' 

265 

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

267 inputs = butlerQC.get(inputRefs) 

268 

269 dimensions = [exp.dataId.byName() for exp in inputRefs.inputStats] 

270 inputs['inputDims'] = dimensions 

271 

272 outputs = self.run(**inputs) 

273 butlerQC.put(outputs, outputRefs) 

274 

275 def run(self, inputStats, inputDims): 

276 """Merge statistics. 

277 

278 Parameters 

279 ---------- 

280 inputStats : `list` [`dict`] 

281 Measured statistics for a detector. 

282 inputDims : `list` [`dict`] 

283 List of dictionaries of input data dimensions/values. 

284 Each list entry should contain: 

285 

286 ``"exposure"`` 

287 exposure id value (`int`) 

288 

289 Returns 

290 ------- 

291 outputStats : `dict` 

292 Merged full exposure statistics. 

293 

294 Notes 

295 ----- 

296 The outputStats should have a yaml representation as follows. 

297 

298 VERIFY: 

299 ExposureId1: 

300 VERIFY_MEAN: boolean 

301 VERIFY_SIGMA: boolean 

302 ExposureId2: 

303 [...] 

304 MEAN_UNIMODAL: boolean 

305 SIGMA_UNIMODAL: boolean 

306 """ 

307 outputStats = {} 

308 success = True 

309 for expStats, dimensions in zip(inputStats, inputDims): 

310 expId = dimensions.get('exposure', dimensions.get('visit', None)) 

311 if expId is None: 

312 raise RuntimeError("Could not identify the exposure from %s", dimensions) 

313 

314 calcStats = {} 

315 

316 expSuccess = expStats.pop('SUCCESS') 

317 if expSuccess: 

318 calcStats['SUCCESS'] = True 

319 else: 

320 calcStats['FAILURES'] = list() 

321 success = False 

322 for detName, detStats in expStats.items(): 

323 detSuccess = detStats.pop('SUCCESS') 

324 if not detSuccess: 

325 for testName in expStats[detName]['FAILURES']: 

326 calcStats['FAILURES'].append(detName + " " + testName) 

327 

328 outputStats[expId] = calcStats 

329 

330 runSuccess = True 

331 if len(self.config.runStatKeywords): 

332 outputStats['VERIFY'], runSuccess = self.verify(outputStats) 

333 

334 outputStats['SUCCESS'] = success & runSuccess 

335 

336 return pipeBase.Struct( 

337 outputStats=outputStats, 

338 ) 

339 

340 def verify(self, statisticsDictionary): 

341 """Verify if the measured statistics meet the verification criteria. 

342 

343 Parameters 

344 ---------- 

345 statisticsDictionary : `dict` [`str`, `dict`], 

346 Dictionary of measured statistics. The inner dictionary 

347 should have keys that are statistic names (`str`) with 

348 values that are some sort of scalar (`int` or `float` are 

349 the mostly likely types). 

350 

351 Returns 

352 ------- 

353 outputStatistics : `dict` [`str`, `dict` [`str`, `bool`]] 

354 A dictionary indexed by the amplifier name, containing 

355 dictionaries of the verification criteria. 

356 success : `bool` 

357 A boolean indicating if all tests have passed. 

358 

359 Raises 

360 ------ 

361 NotImplementedError : 

362 This method must be implemented by the calibration-type 

363 subclass. 

364 

365 """ 

366 raise NotImplementedError("Subclasses must implement verification criteria.") 

367 

368 

369class CpVerifyVisitExpMergeConnections(pipeBase.PipelineTaskConnections, 

370 dimensions={"instrument", "visit"}, 

371 defaultTemplates={}): 

372 inputStats = cT.Input( 

373 name="detectorStats", 

374 doc="Input statistics to merge.", 

375 storageClass="StructuredDataDict", 

376 dimensions=["instrument", "visit", "detector"], 

377 multiple=True, 

378 ) 

379 camera = cT.PrerequisiteInput( 

380 name="camera", 

381 storageClass="Camera", 

382 doc="Input camera.", 

383 dimensions=["instrument", ], 

384 isCalibration=True, 

385 ) 

386 

387 outputStats = cT.Output( 

388 name="exposureStats", 

389 doc="Output statistics.", 

390 storageClass="StructuredDataDict", 

391 dimensions=["instrument", "visit"], 

392 ) 

393 

394 

395class CpVerifyVisitExpMergeConfig(CpVerifyExpMergeConfig, 

396 pipelineConnections=CpVerifyVisitExpMergeConnections): 

397 pass 

398 

399 

400class CpVerifyVisitExpMergeTask(CpVerifyExpMergeTask): 

401 """Merge visit based data.""" 

402 

403 ConfigClass = CpVerifyVisitExpMergeConfig 

404 _DefaultName = 'cpVerifyVisitExpMerge' 

405 

406 pass 

407 

408 

409class CpVerifyVisitRunMergeConnections(pipeBase.PipelineTaskConnections, 

410 dimensions={"instrument"}, 

411 defaultTemplates={}): 

412 inputStats = cT.Input( 

413 name="exposureStats", 

414 doc="Input statistics to merge.", 

415 storageClass="StructuredDataDict", 

416 dimensions=["instrument", "visit"], 

417 multiple=True, 

418 ) 

419 

420 outputStats = cT.Output( 

421 name="runStats", 

422 doc="Output statistics.", 

423 storageClass="StructuredDataDict", 

424 dimensions=["instrument"], 

425 ) 

426 

427 

428class CpVerifyVisitRunMergeConfig(CpVerifyRunMergeConfig, 

429 pipelineConnections=CpVerifyVisitRunMergeConnections): 

430 pass 

431 

432 

433class CpVerifyVisitRunMergeTask(CpVerifyRunMergeTask): 

434 """Merge visit based data.""" 

435 

436 ConfigClass = CpVerifyVisitRunMergeConfig 

437 _DefaultName = 'cpVerifyVisitRunMerge' 

438 

439 pass