Coverage for python/lsst/obs/lsst/_ingestPhotodiode.py: 13%

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1# This file is part of obs_lsst. 

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/>. 

21__all__ = ('PhotodiodeIngestConfig', 'PhotodiodeIngestTask') 

22 

23 

24from lsst.daf.butler import ( 

25 CollectionType, 

26 DataCoordinate, 

27 DatasetIdGenEnum, 

28 DatasetRef, 

29 DatasetType, 

30 FileDataset, 

31 Progress, 

32) 

33from lsst.ip.isr import PhotodiodeCalib 

34from lsst.obs.base import makeTransferChoiceField 

35from lsst.obs.base.formatters.fitsGeneric import FitsGenericFormatter 

36from lsst.pex.config import Config 

37from lsst.pipe.base import Task 

38from lsst.resources import ResourcePath 

39 

40 

41class PhotodiodeIngestConfig(Config): 

42 """Configuration class for PhotodiodeIngestTask.""" 

43 

44 transfer = makeTransferChoiceField(default="copy") 

45 

46 def validate(self): 

47 super().validate() 

48 if self.transfer != "copy": 

49 raise ValueError(f"Transfer Must be 'copy' for photodiode data. {self.transfer}") 

50 

51 

52class PhotodiodeIngestTask(Task): 

53 """Task to ingest photodiode data into a butler repository. 

54 

55 Parameters 

56 ---------- 

57 config : `PhotodiodeIngestConfig` 

58 Configuration for the task. 

59 instrument : `~lsst.obs.base.Instrument` 

60 The instrument these photodiode datasets are from. 

61 butler : `~lsst.daf.butler.Butler` 

62 Writable butler instance, with ``butler.run`` set to the 

63 appropriate `~lsst.daf.butler.CollectionType.RUN` collection 

64 for these datasets. 

65 **kwargs 

66 Additional keyword arguments. 

67 """ 

68 

69 ConfigClass = PhotodiodeIngestConfig 

70 _DefaultName = "photodiodeIngest" 

71 

72 def getDatasetType(self): 

73 """Return the DatasetType of the photodiode datasets.""" 

74 return DatasetType( 

75 "photodiode", 

76 ("instrument", "exposure"), 

77 "IsrCalib", 

78 universe=self.universe, 

79 ) 

80 

81 def __init__(self, butler, instrument, config=None, **kwargs): 

82 config.validate() 

83 super().__init__(config, **kwargs) 

84 self.butler = butler 

85 self.universe = self.butler.dimensions 

86 self.datasetType = self.getDatasetType() 

87 self.progress = Progress(self.log.name) 

88 self.instrument = instrument 

89 self.camera = self.instrument.getCamera() 

90 

91 def run(self, locations, run=None, file_filter=r"Photodiode_Readings.*txt$|_photodiode.ecsv$", 

92 track_file_attrs=None): 

93 """Ingest photodiode data into a Butler data repository. 

94 

95 Parameters 

96 ---------- 

97 files : iterable over `lsst.resources.ResourcePath` 

98 URIs to the files to be ingested. 

99 run : `str`, optional 

100 Name of the RUN-type collection to write to, 

101 overriding the default derived from the instrument 

102 name. 

103 skip_existing_exposures : `bool`, optional 

104 If `True`, skip photodiodes that have already been 

105 ingested (i.e. raws for which we already have a 

106 dataset with the same data ID in the target 

107 collection). 

108 track_file_attrs : `bool`, optional 

109 Control whether file attributes such as the size or 

110 checksum should be tracked by the datastore. Whether 

111 this parameter is honored depends on the specific 

112 datastore implementation. 

113 

114 Returns 

115 ------- 

116 refs : `list` [`lsst.daf.butler.DatasetRef`] 

117 Dataset references for ingested raws. 

118 

119 Raises 

120 ------ 

121 RuntimeError 

122 Raised if the number of exposures found for a photodiode 

123 file is not one 

124 """ 

125 files = ResourcePath.findFileResources(locations, file_filter) 

126 

127 registry = self.butler.registry 

128 registry.registerDatasetType(self.datasetType) 

129 

130 # Find and register run that we will ingest to. 

131 if run is None: 

132 run = self.instrument.makeCollectionName("calib", "photodiode") 

133 registry.registerCollection(run, type=CollectionType.RUN) 

134 

135 # Use datasetIds that match the raw exposure data. 

136 if self.butler.registry.supportsIdGenerationMode(DatasetIdGenEnum.DATAID_TYPE_RUN): 

137 mode = DatasetIdGenEnum.DATAID_TYPE_RUN 

138 else: 

139 mode = DatasetIdGenEnum.UNIQUE 

140 

141 refs = [] 

142 numExisting = 0 

143 numFailed = 0 

144 for inputFile in files: 

145 # Convert the file into the right class. 

146 calibType = "Unknown" 

147 try: 

148 # Can this be read directly in standard form? 

149 with inputFile.as_local() as localFile: 

150 calib = PhotodiodeCalib.readText(localFile.ospath) 

151 calibType = "full" 

152 except Exception: 

153 # Try reading as a two-column file. 

154 with inputFile.as_local() as localFile: 

155 calib = PhotodiodeCalib.readTwoColumnPhotodiodeData(localFile.ospath) 

156 calibType = "two-column" 

157 

158 # Get exposure records 

159 if calibType == "full": 

160 instrumentName = calib.getMetadata().get('INSTRUME') 

161 if instrumentName is None: 

162 # The field is populated by the calib class, so we 

163 # can't use defaults. 

164 instrumentName = self.instrument.getName() 

165 

166 obsId = calib.getMetadata()['obsId'] 

167 whereClause = "exposure.obs_id=obsId" 

168 binding = {"obsId": obsId} 

169 logId = obsId 

170 

171 elif calibType == "two-column": 

172 dayObs = calib.getMetadata()['day_obs'] 

173 seqNum = calib.getMetadata()['seq_num'] 

174 

175 # Find the associated exposure information. 

176 whereClause = "exposure.day_obs=dayObs and exposure.seq_num=seqNum" 

177 instrumentName = self.instrument.getName() 

178 binding = {"dayObs": dayObs, "seqNum": seqNum} 

179 logId = (dayObs, seqNum) 

180 

181 else: 

182 self.log.warning("Skipping input file %s of unknown type.", 

183 inputFile) 

184 continue 

185 exposureRecords = [rec for rec in registry.queryDimensionRecords("exposure", 

186 instrument=instrumentName, 

187 where=whereClause, 

188 bind=binding)] 

189 

190 nRecords = len(exposureRecords) 

191 if nRecords == 1: 

192 exposureId = exposureRecords[0].id 

193 calib.updateMetadata(camera=self.camera, exposure=exposureId) 

194 elif nRecords == 0: 

195 numFailed += 1 

196 self.log.warning("Skipping instrument %s and identifiers %s: no exposures found.", 

197 instrumentName, logId) 

198 continue 

199 else: 

200 numFailed += 1 

201 self.log.warning("Multiple exposure entries found for instrument %s and " 

202 "identifiers %s.", instrumentName, logId) 

203 continue 

204 

205 # Generate the dataId for this file. 

206 dataId = DataCoordinate.standardize( 

207 instrument=self.instrument.getName(), 

208 exposure=exposureId, 

209 universe=self.universe, 

210 ) 

211 

212 # If this already exists, we should skip it and continue. 

213 existing = { 

214 ref.dataId 

215 for ref in self.butler.registry.queryDatasets(self.datasetType, collections=[run], 

216 dataId=dataId) 

217 } 

218 if existing: 

219 self.log.debug("Skipping instrument %s and identifiers %s: already exists in run %s.", 

220 instrumentName, logId, run) 

221 numExisting += 1 

222 continue 

223 

224 # Ingest must work from a file, but we can't use the 

225 # original, as we've added new metadata and reformatted 

226 # it. Write it to a temp file that we can use to ingest. 

227 # If we can have the files written appropriately, this 

228 # will be a direct ingest of those files. 

229 with ResourcePath.temporary_uri(suffix=".fits") as tempFile: 

230 calib.writeFits(tempFile.ospath) 

231 

232 ref = DatasetRef(self.datasetType, dataId, run=run, id_generation_mode=mode) 

233 dataset = FileDataset(path=tempFile, refs=ref, formatter=FitsGenericFormatter) 

234 

235 # No try, as if this fails, we should stop. 

236 self.butler.ingest(dataset, transfer=self.config.transfer, 

237 record_validation_info=track_file_attrs) 

238 self.log.info("Photodiode %s:%d (%s) ingested successfully", instrumentName, exposureId, 

239 logId) 

240 refs.append(dataset) 

241 

242 if numExisting != 0: 

243 self.log.warning("Skipped %d entries that already existed in run %s", numExisting, run) 

244 if numFailed != 0: 

245 raise RuntimeError(f"Failed to ingest {numFailed} entries due to missing exposure information.") 

246 return refs