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1# This file is part of obs_base. 

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 <http://www.gnu.org/licenses/>. 

21from __future__ import annotations 

22 

23__all__ = ["ConvertRepoConfig", "ConvertRepoTask", "ConvertRepoSkyMapConfig", "Rerun"] 

24 

25import os 

26import fnmatch 

27from dataclasses import dataclass 

28from typing import Iterable, Optional, List, Dict 

29 

30from lsst.utils import doImport 

31from lsst.daf.butler import ( 

32 Butler as Butler3, 

33 CollectionType, 

34 SkyPixDimension 

35) 

36from lsst.pex.config import Config, ConfigurableField, ConfigDictField, DictField, ListField, Field 

37from lsst.pipe.base import Task 

38from lsst.skymap import skyMapRegistry, BaseSkyMap 

39 

40from ..ingest import RawIngestTask 

41from ..defineVisits import DefineVisitsTask 

42from .repoConverter import ConversionSubset 

43from .rootRepoConverter import RootRepoConverter 

44from .calibRepoConverter import CalibRepoConverter 

45from .standardRepoConverter import StandardRepoConverter 

46 

47 

48@dataclass 

49class ConfiguredSkyMap: 

50 """Struct containing information about a skymap that may appear in a Gen2 

51 repository. 

52 """ 

53 

54 name: str 

55 """Name of the skymap used in Gen3 data IDs. 

56 """ 

57 

58 sha1: bytes 

59 """Hash computed by `BaseSkyMap.getSha1`. 

60 """ 

61 

62 instance: BaseSkyMap 

63 """Name of the skymap used in Gen3 data IDs. 

64 """ 

65 

66 used: bool = False 

67 """Whether this skymap has been found in at least one repository being 

68 converted. 

69 """ 

70 

71 

72@dataclass 

73class Rerun: 

74 """Specification for a Gen2 processing-output repository to convert. 

75 """ 

76 

77 path: str 

78 """Absolute or relative (to the root repository) path to the Gen2 

79 repository (`str`). 

80 """ 

81 

82 runName: str 

83 """Name of the `~lsst.daf.butler.CollectionType.RUN` collection datasets 

84 will be inserted into (`str`). 

85 """ 

86 

87 chainName: Optional[str] 

88 """Name of a `~lsst.daf.butler.CollectionType.CHAINED` collection that will 

89 combine this repository's datasets with those of its parent repositories 

90 (`str`, optional). 

91 """ 

92 

93 parents: List[str] 

94 """Collection names associated with parent repositories, used to define the 

95 chained collection (`list` [ `str` ]). 

96 

97 Ignored if `chainName` is `None`. Runs used in the root repo are 

98 automatically included. 

99 """ 

100 

101 

102class ConvertRepoSkyMapConfig(Config): 

103 """Sub-config used to hold the parameters of a SkyMap. 

104 

105 Notes 

106 ----- 

107 This config only needs to exist because we can't put a 

108 `~lsst.pex.config.RegistryField` directly inside a 

109 `~lsst.pex.config.ConfigDictField`. 

110 

111 It needs to have its only field named "skyMap" for compatibility with the 

112 configuration of `lsst.pipe.tasks.MakeSkyMapTask`, which we want so we can 

113 use one config file in an obs package to configure both. 

114 

115 This name leads to unfortunate repetition with the field named 

116 "skymap" that holds it - "skyMap[name].skyMap" - but that seems 

117 unavoidable. 

118 """ 

119 skyMap = skyMapRegistry.makeField( 

120 doc="Type and parameters for the SkyMap itself.", 

121 default="dodeca", 

122 ) 

123 

124 

125class ConvertRepoConfig(Config): 

126 raws = ConfigurableField( 

127 "Configuration for subtask responsible for ingesting raws and adding " 

128 "exposure dimension entries.", 

129 target=RawIngestTask, 

130 ) 

131 defineVisits = ConfigurableField( 

132 "Configuration for the subtask responsible for defining visits from " 

133 "exposures.", 

134 target=DefineVisitsTask, 

135 ) 

136 skyMaps = ConfigDictField( 

137 "Mapping from Gen3 skymap name to the parameters used to construct a " 

138 "BaseSkyMap instance. This will be used to associate names with " 

139 "existing skymaps found in the Gen2 repo.", 

140 keytype=str, 

141 itemtype=ConvertRepoSkyMapConfig, 

142 default={} 

143 ) 

144 rootSkyMapName = Field( 

145 "Name of a Gen3 skymap (an entry in ``self.skyMaps``) to assume for " 

146 "datasets in the root repository when no SkyMap is found there. ", 

147 dtype=str, 

148 optional=True, 

149 default=None, 

150 ) 

151 runs = DictField( 

152 "A mapping from dataset type name to the RUN collection they should " 

153 "be inserted into. This must include all datasets that can be found " 

154 "in the root repository; other repositories will use per-repository " 

155 "runs.", 

156 keytype=str, 

157 itemtype=str, 

158 default={ 

159 "deepCoadd_skyMap": "skymaps", 

160 "brightObjectMask": "masks", 

161 } 

162 ) 

163 storageClasses = DictField( 

164 "Mapping from dataset type name or Gen2 policy entry (e.g. 'python' " 

165 "or 'persistable') to the Gen3 StorageClass name.", 

166 keytype=str, 

167 itemtype=str, 

168 default={ 

169 "bias": "ExposureF", 

170 "dark": "ExposureF", 

171 "flat": "ExposureF", 

172 "defects": "Defects", 

173 "BaseSkyMap": "SkyMap", 

174 "BaseCatalog": "Catalog", 

175 "BackgroundList": "Background", 

176 "raw": "Exposure", 

177 "MultilevelParquetTable": "DataFrame", 

178 "ParquetTable": "DataFrame", 

179 "SkyWcs": "Wcs", 

180 } 

181 ) 

182 formatterClasses = DictField( 

183 "Mapping from dataset type name to formatter class. " 

184 "By default these are derived from the formatters listed in the" 

185 " Gen3 datastore configuration.", 

186 keytype=str, 

187 itemtype=str, 

188 default={} 

189 ) 

190 targetHandlerClasses = DictField( 

191 "Mapping from dataset type name to target handler class.", 

192 keytype=str, 

193 itemtype=str, 

194 default={} 

195 ) 

196 doRegisterInstrument = Field( 

197 "If True (default), add dimension records for the Instrument and its " 

198 "filters and detectors to the registry instead of assuming they are " 

199 "already present.", 

200 dtype=bool, 

201 default=True, 

202 ) 

203 doWriteCuratedCalibrations = Field( 

204 "If True (default), ingest human-curated calibrations directly via " 

205 "the Instrument interface. Note that these calibrations are never " 

206 "converted from Gen2 repositories.", 

207 dtype=bool, 

208 default=True, 

209 ) 

210 refCats = ListField( 

211 "The names of reference catalogs (subdirectories under ref_cats) to " 

212 "be converted", 

213 dtype=str, 

214 default=[] 

215 ) 

216 fileIgnorePatterns = ListField( 

217 "Filename globs that should be ignored instead of being treated as " 

218 "datasets.", 

219 dtype=str, 

220 default=["README.txt", "*~?", "butler.yaml", "gen3.sqlite3", 

221 "registry.sqlite3", "calibRegistry.sqlite3", "_mapper", 

222 "_parent", "repositoryCfg.yaml"] 

223 ) 

224 rawDatasetType = Field( 

225 "Gen2 dataset type to use for raw data.", 

226 dtype=str, 

227 default="raw", 

228 ) 

229 datasetIncludePatterns = ListField( 

230 "Glob-style patterns for dataset type names that should be converted.", 

231 dtype=str, 

232 default=["*"] 

233 ) 

234 datasetIgnorePatterns = ListField( 

235 "Glob-style patterns for dataset type names that should not be " 

236 "converted despite matching a pattern in datasetIncludePatterns.", 

237 dtype=str, 

238 default=[] 

239 ) 

240 ccdKey = Field( 

241 "Key used for the Gen2 equivalent of 'detector' in data IDs.", 

242 dtype=str, 

243 default="ccd", 

244 ) 

245 relatedOnly = Field( 

246 "If True (default), only convert datasets that are related to the " 

247 "ingested visits. Ignored unless a list of visits is passed to " 

248 "run().", 

249 dtype=bool, 

250 default=False, 

251 ) 

252 curatedCalibrations = ListField( 

253 "Dataset types that are handled by `Instrument.writeCuratedCalibrations()` " 

254 "and thus should not be converted using the standard calibration " 

255 "conversion system.", 

256 dtype=str, 

257 default=["camera", 

258 "transmission_sensor", 

259 "transmission_filter", 

260 "transmission_optics", 

261 "transmission_atmosphere", 

262 "bfKernel"] 

263 ) 

264 instrument = Field( 

265 doc=("Fully-qualified Python name of the `Instrument` subclass for " 

266 "all converted datasets."), 

267 dtype=str, 

268 optional=False, 

269 default=None, 

270 ) 

271 

272 @property 

273 def transfer(self): 

274 return self.raws.transfer 

275 

276 @transfer.setter 

277 def transfer(self, value): 

278 self.raws.transfer = value 

279 

280 def setDefaults(self): 

281 self.transfer = None 

282 

283 # TODO: check that there are no collection overrides for curated 

284 # calibrations, since we don't have a good way to utilize them. 

285 

286 

287class ConvertRepoTask(Task): 

288 """A task that converts one or more related Gen2 data repositories to a 

289 single Gen3 data repository (with multiple collections). 

290 

291 Parameters 

292 ---------- 

293 config: `ConvertRepoConfig` 

294 Configuration for this task. 

295 butler3: `lsst.daf.butler.Butler` 

296 A writeable Gen3 Butler instance that represents the data repository 

297 that datasets will be ingested into. If the 'raw' dataset is 

298 configured to be included in the conversion, ``butler3.run`` should be 

299 set to the name of the collection raws should be ingested into, and 

300 ``butler3.collections`` should include a calibration collection from 

301 which the ``camera`` dataset can be loaded, unless a calibration repo 

302 is converted and ``doWriteCuratedCalibrations`` is `True`. 

303 **kwargs 

304 Other keyword arguments are forwarded to the `Task` constructor. 

305 

306 Notes 

307 ----- 

308 Most of the work of converting repositories is delegated to instances of 

309 the `RepoConverter` hierarchy. The `ConvertRepoTask` instance itself holds 

310 only state that is relevant for all Gen2 repositories being ingested, while 

311 each `RepoConverter` instance holds only state relevant for the conversion 

312 of a single Gen2 repository. Both the task and the `RepoConverter` 

313 instances are single use; `ConvertRepoTask.run` and most `RepoConverter` 

314 methods may only be called once on a particular instance. 

315 """ 

316 

317 ConfigClass = ConvertRepoConfig 

318 

319 _DefaultName = "convertRepo" 

320 

321 def __init__(self, config=None, *, butler3: Butler3, **kwargs): 

322 config.validate() # Not a CmdlineTask nor PipelineTask, so have to validate the config here. 

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

324 self.butler3 = butler3 

325 self.registry = self.butler3.registry 

326 self.universe = self.registry.dimensions 

327 if self.isDatasetTypeIncluded("raw"): 

328 self.makeSubtask("raws", butler=butler3) 

329 self.makeSubtask("defineVisits", butler=butler3) 

330 else: 

331 self.raws = None 

332 self.defineVisits = None 

333 self.instrument = doImport(self.config.instrument)() 

334 self._configuredSkyMapsBySha1 = {} 

335 self._configuredSkyMapsByName = {} 

336 for name, config in self.config.skyMaps.items(): 

337 instance = config.skyMap.apply() 

338 self._populateSkyMapDicts(name, instance) 

339 self._usedSkyPix = set() 

340 

341 def _populateSkyMapDicts(self, name, instance): 

342 struct = ConfiguredSkyMap(name=name, sha1=instance.getSha1(), instance=instance) 

343 self._configuredSkyMapsBySha1[struct.sha1] = struct 

344 self._configuredSkyMapsByName[struct.name] = struct 

345 

346 def isDatasetTypeIncluded(self, datasetTypeName: str): 

347 """Return `True` if configuration indicates that the given dataset type 

348 should be converted. 

349 

350 This method is intended to be called primarily by the 

351 `RepoConverter` instances used interally by the task. 

352 

353 Parameters 

354 ---------- 

355 datasetTypeName: str 

356 Name of the dataset type. 

357 

358 Returns 

359 ------- 

360 included : `bool` 

361 Whether the dataset should be included in the conversion. 

362 """ 

363 return ( 

364 any(fnmatch.fnmatchcase(datasetTypeName, pattern) 

365 for pattern in self.config.datasetIncludePatterns) 

366 and not any(fnmatch.fnmatchcase(datasetTypeName, pattern) 

367 for pattern in self.config.datasetIgnorePatterns) 

368 ) 

369 

370 def useSkyMap(self, skyMap: BaseSkyMap, skyMapName: str) -> str: 

371 """Indicate that a repository uses the given SkyMap. 

372 

373 This method is intended to be called primarily by the 

374 `RepoConverter` instances used interally by the task. 

375 

376 Parameters 

377 ---------- 

378 skyMap : `lsst.skymap.BaseSkyMap` 

379 SkyMap instance being used, typically retrieved from a Gen2 

380 data repository. 

381 skyMapName : `str` 

382 The name of the gen2 skymap, for error reporting. 

383 

384 Returns 

385 ------- 

386 name : `str` 

387 The name of the skymap in Gen3 data IDs. 

388 

389 Raises 

390 ------ 

391 LookupError 

392 Raised if the specified skymap cannot be found. 

393 """ 

394 sha1 = skyMap.getSha1() 

395 if sha1 not in self._configuredSkyMapsBySha1: 

396 self._populateSkyMapDicts(skyMapName, skyMap) 

397 try: 

398 struct = self._configuredSkyMapsBySha1[sha1] 

399 except KeyError as err: 

400 msg = f"SkyMap '{skyMapName}' with sha1={sha1} not included in configuration." 

401 raise LookupError(msg) from err 

402 struct.used = True 

403 return struct.name 

404 

405 def registerUsedSkyMaps(self, subset: Optional[ConversionSubset]): 

406 """Register all skymaps that have been marked as used. 

407 

408 This method is intended to be called primarily by the 

409 `RepoConverter` instances used interally by the task. 

410 

411 Parameters 

412 ---------- 

413 subset : `ConversionSubset`, optional 

414 Object that will be used to filter converted datasets by data ID. 

415 If given, it will be updated with the tracts of this skymap that 

416 overlap the visits in the subset. 

417 """ 

418 for struct in self._configuredSkyMapsBySha1.values(): 

419 if struct.used: 

420 struct.instance.register(struct.name, self.registry) 

421 if subset is not None and self.config.relatedOnly: 

422 subset.addSkyMap(self.registry, struct.name) 

423 

424 def useSkyPix(self, dimension: SkyPixDimension): 

425 """Indicate that a repository uses the given SkyPix dimension. 

426 

427 This method is intended to be called primarily by the 

428 `RepoConverter` instances used interally by the task. 

429 

430 Parameters 

431 ---------- 

432 dimension : `lsst.daf.butler.SkyPixDimension` 

433 Dimension represening a pixelization of the sky. 

434 """ 

435 self._usedSkyPix.add(dimension) 

436 

437 def registerUsedSkyPix(self, subset: Optional[ConversionSubset]): 

438 """Register all skymaps that have been marked as used. 

439 

440 This method is intended to be called primarily by the 

441 `RepoConverter` instances used interally by the task. 

442 

443 Parameters 

444 ---------- 

445 subset : `ConversionSubset`, optional 

446 Object that will be used to filter converted datasets by data ID. 

447 If given, it will be updated with the pixelization IDs that 

448 overlap the visits in the subset. 

449 """ 

450 if subset is not None and self.config.relatedOnly: 

451 for dimension in self._usedSkyPix: 

452 subset.addSkyPix(self.registry, dimension) 

453 

454 def run(self, root: str, *, 

455 calibs: Dict[str, str] = None, 

456 reruns: List[Rerun], 

457 visits: Optional[Iterable[int]] = None): 

458 """Convert a group of related data repositories. 

459 

460 Parameters 

461 ---------- 

462 root : `str` 

463 Complete path to the root Gen2 data repository. This should be 

464 a data repository that includes a Gen2 registry and any raw files 

465 and/or reference catalogs. 

466 calibs : `dict` 

467 Dictionary mapping calibration repository path to the 

468 `~lsst.daf.butler.CollectionType.RUN` collection that converted 

469 datasets within it should be inserted into. 

470 reruns : `list` of `Rerun` 

471 Specifications for rerun (processing output) collections to 

472 convert. 

473 visits : iterable of `int`, optional 

474 The integer IDs of visits to convert. If not provided, all visits 

475 in the Gen2 root repository will be converted. 

476 """ 

477 if calibs is None: 

478 calibs = {} 

479 if visits is not None: 

480 subset = ConversionSubset(instrument=self.instrument.getName(), visits=frozenset(visits)) 

481 else: 

482 if self.config.relatedOnly: 

483 self.log.warn("config.relatedOnly is True but all visits are being ingested; " 

484 "no filtering will be done.") 

485 subset = None 

486 

487 # Make converters for all Gen2 repos. 

488 converters = [] 

489 rootConverter = RootRepoConverter(task=self, root=root, subset=subset) 

490 converters.append(rootConverter) 

491 for calibRoot, run in calibs.items(): 

492 if not os.path.isabs(calibRoot): 

493 calibRoot = os.path.join(rootConverter.root, calibRoot) 

494 converter = CalibRepoConverter(task=self, root=calibRoot, run=run, 

495 mapper=rootConverter.mapper, 

496 subset=rootConverter.subset) 

497 converters.append(converter) 

498 for spec in reruns: 

499 runRoot = spec.path 

500 if not os.path.isabs(runRoot): 

501 runRoot = os.path.join(rootConverter.root, runRoot) 

502 converter = StandardRepoConverter(task=self, root=runRoot, run=spec.runName, 

503 subset=rootConverter.subset) 

504 converters.append(converter) 

505 

506 # Register the instrument if we're configured to do so. 

507 if self.config.doRegisterInstrument: 

508 # Allow registration to fail on the assumption that this means 

509 # we are reusing a butler 

510 try: 

511 self.instrument.register(self.registry) 

512 except Exception: 

513 pass 

514 

515 # Run raw ingest (does nothing if we weren't configured to convert the 

516 # 'raw' dataset type). 

517 rootConverter.runRawIngest() 

518 

519 # Write curated calibrations to all calibration repositories. 

520 # Add new collections to the list of collections the butler was 

521 # initialized to pass to DefineVisitsTask, to deal with the (likely) 

522 # case the only 'camera' dataset in the repo will be one we're adding 

523 # here. 

524 if self.config.doWriteCuratedCalibrations: 

525 for run in calibs.values(): 

526 butler3 = Butler3(butler=self.butler3, run=run) 

527 self.instrument.writeCuratedCalibrations(butler3) 

528 

529 # Define visits (also does nothing if we weren't configurd to convert 

530 # the 'raw' dataset type). 

531 rootConverter.runDefineVisits() 

532 

533 # Walk Gen2 repos to find datasets convert. 

534 for converter in converters: 

535 converter.prep() 

536 

537 # Insert dimensions needed by any converters. In practice this is just 

538 # calibration_labels right now, because exposures and visits (and 

539 # things related to them) are handled by RawIngestTask and 

540 # DefineVisitsTask earlier and skymaps are handled later. 

541 # 

542 # Note that we do not try to filter dimensions down to just those 

543 # related to the given visits, even if config.relatedOnly is True; we 

544 # need them in the Gen3 repo in order to be able to know which datasets 

545 # to convert, because Gen2 alone doesn't know enough about the 

546 # relationships between data IDs. 

547 for converter in converters: 

548 converter.insertDimensionData() 

549 

550 # Insert dimensions that are potentially shared by all Gen2 

551 # repositories (and are hence managed directly by the Task, rather 

552 # than a converter instance). 

553 # This also finishes setting up the (shared) converter.subsets object 

554 # that is used to filter data IDs for config.relatedOnly. 

555 self.registerUsedSkyMaps(rootConverter.subset) 

556 self.registerUsedSkyPix(rootConverter.subset) 

557 

558 # Look for datasets, generally by scanning the filesystem. 

559 # This requires dimensions to have already been inserted so we can use 

560 # dimension information to identify related datasets. 

561 for converter in converters: 

562 converter.findDatasets() 

563 

564 # Expand data IDs. 

565 for converter in converters: 

566 converter.expandDataIds() 

567 

568 # Actually ingest datasets. 

569 for converter in converters: 

570 converter.ingest() 

571 

572 # Add chained collections for reruns. 

573 for spec in reruns: 

574 if spec.chainName is not None: 

575 self.butler3.registry.registerCollection(spec.chainName, type=CollectionType.CHAINED) 

576 chain = [spec.runName] 

577 chain.extend(spec.parents) 

578 chain.extend(rootConverter.getCollectionChain()) 

579 self.log.info("Defining %s from chain %s.", spec.chainName, chain) 

580 self.butler3.registry.setCollectionChain(spec.chainName, chain)