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1# See COPYRIGHT file at the top of the source tree. 

2# 

3# This file is part of fgcmcal. 

4# 

5# Developed for the LSST Data Management System. 

6# This product includes software developed by the LSST Project 

7# (https://www.lsst.org). 

8# See the COPYRIGHT file at the top-level directory of this distribution 

9# for details of code ownership. 

10# 

11# This program is free software: you can redistribute it and/or modify 

12# it under the terms of the GNU General Public License as published by 

13# the Free Software Foundation, either version 3 of the License, or 

14# (at your option) any later version. 

15# 

16# This program is distributed in the hope that it will be useful, 

17# but WITHOUT ANY WARRANTY; without even the implied warranty of 

18# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

19# GNU General Public License for more details. 

20# 

21# You should have received a copy of the GNU General Public License 

22# along with this program. If not, see <https://www.gnu.org/licenses/>. 

23"""Class for running fgcmcal on a single tract using sourceTable_visit tables. 

24""" 

25import numpy as np 

26 

27import lsst.pipe.base as pipeBase 

28from lsst.pipe.base import connectionTypes 

29from lsst.meas.algorithms import ReferenceObjectLoader 

30import lsst.afw.table as afwTable 

31 

32from .dataIds import TractCheckDataIdContainer 

33from .fgcmBuildStarsTable import FgcmBuildStarsTableTask 

34from .fgcmCalibrateTractBase import (FgcmCalibrateTractConfigBase, FgcmCalibrateTractRunner, 

35 FgcmCalibrateTractBaseTask) 

36from .utilities import lookupStaticCalibrations 

37 

38__all__ = ['FgcmCalibrateTractTableConfig', 'FgcmCalibrateTractTableTask'] 

39 

40 

41class FgcmCalibrateTractTableConnections(pipeBase.PipelineTaskConnections, 

42 dimensions=("instrument", 

43 "tract",)): 

44 camera = connectionTypes.PrerequisiteInput( 

45 doc="Camera instrument", 

46 name="camera", 

47 storageClass="Camera", 

48 dimensions=("instrument",), 

49 lookupFunction=lookupStaticCalibrations, 

50 isCalibration=True, 

51 ) 

52 

53 fgcmLookUpTable = connectionTypes.PrerequisiteInput( 

54 doc=("Atmosphere + instrument look-up-table for FGCM throughput and " 

55 "chromatic corrections."), 

56 name="fgcmLookUpTable", 

57 storageClass="Catalog", 

58 dimensions=("instrument",), 

59 deferLoad=True, 

60 ) 

61 

62 sourceSchema = connectionTypes.PrerequisiteInput( 

63 doc="Schema for source catalogs", 

64 name="src_schema", 

65 storageClass="SourceCatalog", 

66 deferLoad=True, 

67 ) 

68 

69 refCat = connectionTypes.PrerequisiteInput( 

70 doc="Reference catalog to use for photometric calibration", 

71 name="cal_ref_cat", 

72 storageClass="SimpleCatalog", 

73 dimensions=("skypix",), 

74 deferLoad=True, 

75 multiple=True, 

76 ) 

77 

78 source_catalogs = connectionTypes.Input( 

79 doc="Source table in parquet format, per visit", 

80 name="sourceTable_visit", 

81 storageClass="DataFrame", 

82 dimensions=("instrument", "visit"), 

83 deferLoad=True, 

84 multiple=True, 

85 ) 

86 

87 calexp = connectionTypes.Input( 

88 doc="Calibrated exposures used for psf and metadata", 

89 name="calexp", 

90 storageClass="ExposureF", 

91 dimensions=("instrument", "visit", "detector"), 

92 deferLoad=True, 

93 multiple=True, 

94 ) 

95 

96 background = connectionTypes.Input( 

97 doc="Calexp background model", 

98 name="calexpBackground", 

99 storageClass="Background", 

100 dimensions=("instrument", "visit", "detector"), 

101 deferLoad=True, 

102 multiple=True, 

103 ) 

104 

105 fgcmPhotoCalib = connectionTypes.Output( 

106 doc="Per-tract, per-visit photoCalib exposure catalogs produced from fgcm calibration", 

107 name="fgcmPhotoCalibTractCatalog", 

108 storageClass="ExposureCatalog", 

109 dimensions=("instrument", "tract", "visit",), 

110 multiple=True, 

111 ) 

112 

113 fgcmTransmissionAtmosphere = connectionTypes.Output( 

114 doc="Per-visit atmosphere transmission files produced from fgcm calibration", 

115 name="transmission_atmosphere_fgcm_tract", 

116 storageClass="TransmissionCurve", 

117 dimensions=("instrument", "tract", "visit",), 

118 multiple=True, 

119 ) 

120 

121 fgcmRepeatability = connectionTypes.Output( 

122 doc="Per-band raw repeatability numbers in the fgcm tract calibration", 

123 name="fgcmRawRepeatability", 

124 storageClass="Catalog", 

125 dimensions=("instrument", "tract",), 

126 multiple=False, 

127 ) 

128 

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

130 super().__init__(config=config) 

131 

132 # The ref_dataset_name will be deprecated with Gen2 

133 loaderName = config.fgcmBuildStars.fgcmLoadReferenceCatalog.refObjLoader.ref_dataset_name 

134 if config.connections.refCat != loaderName: 

135 raise ValueError("connections.refCat must be the same as " 

136 "config.fgcmBuildStars.fgcmLoadReferenceCatalog.refObjLoader.ref_dataset_name") 

137 if config.fgcmOutputProducts.doReferenceCalibration: 

138 loaderName = config.fgcmOutputProducts.refObjLoader.ref_dataset_name 

139 if config.connections.refCat != loaderName: 

140 raise ValueError("connections.refCat must be the same as " 

141 "config.fgcmOutputProducts.refObjLoader.ref_dataset_name") 

142 

143 if not config.fgcmBuildStars.doModelErrorsWithBackground: 

144 self.inputs.remove("background") 

145 

146 if config.fgcmOutputProducts.doRefcatOutput: 

147 raise ValueError("FgcmCalibrateTractTableTask (Gen3) does not support doRefcatOutput") 

148 if not config.fgcmOutputProducts.doAtmosphereOutput: 

149 self.prerequisiteInputs.remove("fgcmAtmosphereParameters") 

150 if not config.fgcmOutputProducts.doZeropointOutput: 

151 self.prerequisiteInputs.remove("fgcmZeropoints") 

152 

153 

154class FgcmCalibrateTractTableConfig(FgcmCalibrateTractConfigBase, pipeBase.PipelineTaskConfig, 

155 pipelineConnections=FgcmCalibrateTractTableConnections): 

156 """Config for FgcmCalibrateTractTable task""" 

157 def setDefaults(self): 

158 super().setDefaults() 

159 

160 # For the Table version of CalibrateTract, use the associated 

161 # Table version of the BuildStars task. 

162 self.fgcmBuildStars.retarget(FgcmBuildStarsTableTask) 

163 # For tract mode, we set a very high effective density cut. 

164 self.fgcmBuildStars.densityCutMaxPerPixel = 10000 

165 

166 

167class FgcmCalibrateTractTableTask(FgcmCalibrateTractBaseTask): 

168 """ 

169 Calibrate a single tract using fgcmcal, using sourceTable_visit (parquet) 

170 input catalogs. 

171 """ 

172 ConfigClass = FgcmCalibrateTractTableConfig 

173 RunnerClass = FgcmCalibrateTractRunner 

174 _DefaultName = "fgcmCalibrateTractTable" 

175 

176 canMultiprocess = False 

177 

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

179 dataRefDict = butlerQC.get(inputRefs) 

180 

181 self.log.info("Running with %d sourceTable_visit dataRefs", (len(dataRefDict['source_catalogs']))) 

182 

183 # Run the build stars tasks 

184 tract = butlerQC.quantum.dataId['tract'] 

185 

186 calexpRefs = dataRefDict['calexp'] 

187 calexpRefDict = {(calexpRef.dataId.byName()['visit'], 

188 calexpRef.dataId.byName()['detector']): 

189 calexpRef for calexpRef in calexpRefs} 

190 dataRefDict['calexps'] = calexpRefDict 

191 

192 # And the outputs 

193 if self.config.fgcmOutputProducts.doZeropointOutput: 

194 photoCalibRefDict = {photoCalibRef.dataId.byName()['visit']: 

195 photoCalibRef for photoCalibRef in outputRefs.fgcmPhotoCalib} 

196 dataRefDict['fgcmPhotoCalibs'] = photoCalibRefDict 

197 

198 if self.config.fgcmOutputProducts.doAtmosphereOutput: 

199 atmRefDict = {atmRef.dataId.byName()['visit']: atmRef for 

200 atmRef in outputRefs.fgcmTransmissionAtmosphere} 

201 dataRefDict['fgcmTransmissionAtmospheres'] = atmRefDict 

202 

203 if self.config.fgcmBuildStars.doReferenceMatches: 

204 refConfig = self.config.fgcmBuildStars.fgcmLoadReferenceCatalog.refObjLoader 

205 loader = ReferenceObjectLoader(dataIds=[ref.datasetRef.dataId 

206 for ref in inputRefs.refCat], 

207 refCats=butlerQC.get(inputRefs.refCat), 

208 config=refConfig, 

209 log=self.log) 

210 buildStarsRefObjLoader = loader 

211 else: 

212 buildStarsRefObjLoader = None 

213 

214 if self.config.fgcmOutputProducts.doReferenceCalibration: 

215 refConfig = self.config.fgcmOutputProducts.refObjLoader 

216 loader = ReferenceObjectLoader(dataIds=[ref.datasetRef.dataId 

217 for ref in inputRefs.refCat], 

218 refCats=butlerQC.get(inputRefs.refCat), 

219 config=refConfig, 

220 log=self.log) 

221 self.fgcmOutputProducts.refObjLoader = loader 

222 

223 struct = self.run(dataRefDict, tract, 

224 buildStarsRefObjLoader=buildStarsRefObjLoader, butler=butlerQC) 

225 

226 if struct.photoCalibCatalogs is not None: 

227 self.log.info("Outputting photoCalib catalogs.") 

228 for visit, expCatalog in struct.photoCalibCatalogs: 

229 butlerQC.put(expCatalog, photoCalibRefDict[visit]) 

230 self.log.info("Done outputting photoCalib catalogs.") 

231 

232 if struct.atmospheres is not None: 

233 self.log.info("Outputting atmosphere transmission files.") 

234 for visit, atm in struct.atmospheres: 

235 butlerQC.put(atm, atmRefDict[visit]) 

236 self.log.info("Done outputting atmosphere files.") 

237 

238 # Turn raw repeatability into simple catalog for persistence 

239 schema = afwTable.Schema() 

240 schema.addField('rawRepeatability', type=np.float64, 

241 doc="Per-band raw repeatability in FGCM calibration.") 

242 repeatabilityCat = afwTable.BaseCatalog(schema) 

243 repeatabilityCat.resize(len(struct.repeatability)) 

244 repeatabilityCat['rawRepeatability'][:] = struct.repeatability 

245 

246 butlerQC.put(repeatabilityCat, outputRefs.fgcmRepeatability) 

247 

248 return 

249 

250 @classmethod 

251 def _makeArgumentParser(cls): 

252 parser = pipeBase.ArgumentParser(name=cls._DefaultName) 

253 parser.add_id_argument("--id", "sourceTable_visit", 

254 help="Data ID, e.g. --id visit=6789 tract=9617", 

255 ContainerClass=TractCheckDataIdContainer) 

256 

257 return parser