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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 

29 

30class CpVerifyExpMergeConnections(pipeBase.PipelineTaskConnections, 

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

32 defaultTemplates={}): 

33 inputStats = cT.Input( 

34 name="detectorStats", 

35 doc="Input statistics to merge.", 

36 storageClass="StructuredDataDict", 

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

38 multiple=True, 

39 ) 

40 camera = cT.PrerequisiteInput( 

41 name="camera", 

42 storageClass="Camera", 

43 doc="Input camera.", 

44 dimensions=["instrument", ], 

45 isCalibration=True, 

46 ) 

47 

48 outputStats = cT.Output( 

49 name="exposureStats", 

50 doc="Output statistics.", 

51 storageClass="StructuredDataDict", 

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

53 ) 

54 

55 

56class CpVerifyExpMergeConfig(pipeBase.PipelineTaskConfig, 

57 pipelineConnections=CpVerifyExpMergeConnections): 

58 """Configuration parameters for exposure stats merging. 

59 """ 

60 exposureStatKeywords = pexConfig.DictField( 

61 keytype=str, 

62 itemtype=str, 

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

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

65 default={}, 

66 ) 

67 

68 

69class CpVerifyExpMergeTask(pipeBase.PipelineTask, pipeBase.CmdLineTask): 

70 """Merge statistics from detectors together. 

71 """ 

72 ConfigClass = CpVerifyExpMergeConfig 

73 _DefaultName = 'cpVerifyExpMerge' 

74 

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

76 inputs = butlerQC.get(inputRefs) 

77 

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

79 inputs['inputDims'] = dimensions 

80 

81 outputs = self.run(**inputs) 

82 butlerQC.put(outputs, outputRefs) 

83 

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

85 """Merge statistics. 

86 

87 Parameters 

88 ---------- 

89 inputStats : `list` [`dict`] 

90 Measured statistics for a detector (from 

91 CpVerifyStatsTask). 

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

93 The camera geometry for this exposure. 

94 inputDims : `list` [`dict`] 

95 List of dictionaries of input data dimensions/values. 

96 Each list entry should contain: 

97 

98 ``"exposure"`` 

99 exposure id value (`int`) 

100 ``"detector"`` 

101 detector id value (`int`) 

102 

103 Returns 

104 ------- 

105 outputStats : `dict` 

106 Merged full exposure statistics. 

107 

108 See Also 

109 -------- 

110 lsst.cp.verify.CpVerifyStatsTask 

111 

112 Notes 

113 ----- 

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

115 

116 DET: 

117 DetName1: 

118 FAILURES: 

119 - TEST_NAME 

120 STAT: value 

121 STAT2: value2 

122 DetName2: 

123 VERIFY: 

124 TEST: boolean 

125 TEST2: boolean 

126 SUCCESS: boolean 

127 """ 

128 outputStats = {} 

129 success = True 

130 

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

132 detId = dimensions['detector'] 

133 detName = camera[detId].getName() 

134 calcStats = {} 

135 

136 if detStats['SUCCESS'] is True: 

137 calcStats['SUCCESS'] = True 

138 else: 

139 calcStats['SUCCESS'] = False 

140 calcStats['FAILURES'] = list() 

141 success = False 

142 # See if the detector failed 

143 if 'DET' in detStats['VERIFY']: 

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

145 if testResult is False: 

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

147 # See if the catalog failed 

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

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

150 if testResult is False: 

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

152 # See if an amplifier failed 

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

154 ampSuccess = ampStats.pop('SUCCESS') 

155 if not ampSuccess: 

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

157 if testResult is False: 

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

159 

160 outputStats[detName] = calcStats 

161 

162 exposureSuccess = True 

163 if len(self.config.exposureStatKeywords): 

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

165 

166 outputStats['SUCCESS'] = success & exposureSuccess 

167 

168 return pipeBase.Struct( 

169 outputStats=outputStats, 

170 ) 

171 

172 def verify(self, statisticsDictionary): 

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

174 

175 Parameters 

176 ---------- 

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

178 Dictionary of measured statistics. The inner dictionary 

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

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

181 the mostly likely types). 

182 

183 Returns 

184 ------- 

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

186 A dictionary indexed by the amplifier name, containing 

187 dictionaries of the verification criteria. 

188 success : `bool` 

189 A boolean indicating if all tests have passed. 

190 

191 Raises 

192 ------ 

193 NotImplementedError : 

194 This method must be implemented by the calibration-type 

195 subclass. 

196 """ 

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

198 

199 

200class CpVerifyRunMergeConnections(pipeBase.PipelineTaskConnections, 

201 dimensions={"instrument"}, 

202 defaultTemplates={}): 

203 inputStats = cT.Input( 

204 name="exposureStats", 

205 doc="Input statistics to merge.", 

206 storageClass="StructuredDataDict", 

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

208 multiple=True, 

209 ) 

210 

211 outputStats = cT.Output( 

212 name="runStats", 

213 doc="Output statistics.", 

214 storageClass="StructuredDataDict", 

215 dimensions=["instrument"], 

216 ) 

217 

218 

219class CpVerifyRunMergeConfig(pipeBase.PipelineTaskConfig, 

220 pipelineConnections=CpVerifyRunMergeConnections): 

221 """Configuration paramters for exposure stats merging. 

222 """ 

223 runStatKeywords = pexConfig.DictField( 

224 keytype=str, 

225 itemtype=str, 

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

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

228 default={}, 

229 ) 

230 

231 

232class CpVerifyRunMergeTask(pipeBase.PipelineTask, pipeBase.CmdLineTask): 

233 """Merge statistics from detectors together. 

234 """ 

235 ConfigClass = CpVerifyRunMergeConfig 

236 _DefaultName = 'cpVerifyRunMerge' 

237 

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

239 inputs = butlerQC.get(inputRefs) 

240 

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

242 inputs['inputDims'] = dimensions 

243 

244 outputs = self.run(**inputs) 

245 butlerQC.put(outputs, outputRefs) 

246 

247 def run(self, inputStats, inputDims): 

248 """Merge statistics. 

249 

250 Parameters 

251 ---------- 

252 inputStats : `list` [`dict`] 

253 Measured statistics for a detector. 

254 inputDims : `list` [`dict`] 

255 List of dictionaries of input data dimensions/values. 

256 Each list entry should contain: 

257 

258 ``"exposure"`` 

259 exposure id value (`int`) 

260 

261 Returns 

262 ------- 

263 outputStats : `dict` 

264 Merged full exposure statistics. 

265 

266 Notes 

267 ----- 

268 The outputStats should have a yaml representation as follows. 

269 

270 VERIFY: 

271 ExposureId1: 

272 VERIFY_MEAN: boolean 

273 VERIFY_SIGMA: boolean 

274 ExposureId2: 

275 [...] 

276 MEAN_UNIMODAL: boolean 

277 SIGMA_UNIMODAL: boolean 

278 """ 

279 outputStats = {} 

280 success = True 

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

282 expId = dimensions['exposure'] 

283 calcStats = {} 

284 

285 expSuccess = expStats.pop('SUCCESS') 

286 if expSuccess: 

287 calcStats['SUCCESS'] = True 

288 else: 

289 calcStats['FAILURES'] = list() 

290 success = False 

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

292 detSuccess = detStats.pop('SUCCESS') 

293 if not detSuccess: 

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

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

296 

297 outputStats[expId] = calcStats 

298 

299 runSuccess = True 

300 if len(self.config.runStatKeywords): 

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

302 

303 outputStats['SUCCESS'] = success & runSuccess 

304 

305 return pipeBase.Struct( 

306 outputStats=outputStats, 

307 ) 

308 

309 def verify(self, statisticsDictionary): 

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

311 

312 Parameters 

313 ---------- 

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

315 Dictionary of measured statistics. The inner dictionary 

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

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

318 the mostly likely types). 

319 

320 Returns 

321 ------- 

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

323 A dictionary indexed by the amplifier name, containing 

324 dictionaries of the verification criteria. 

325 success : `bool` 

326 A boolean indicating if all tests have passed. 

327 

328 Raises 

329 ------ 

330 NotImplementedError : 

331 This method must be implemented by the calibration-type 

332 subclass. 

333 

334 """ 

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