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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/>. 

21 

22from __future__ import annotations 

23 

24__all__ = [ 

25 "DefineVisitsConfig", 

26 "DefineVisitsTask", 

27 "GroupExposuresConfig", 

28 "GroupExposuresTask", 

29 "VisitDefinitionData", 

30] 

31 

32from abc import ABCMeta, abstractmethod 

33from collections import defaultdict 

34import itertools 

35import dataclasses 

36from typing import Any, Dict, Iterable, List, Optional, Tuple 

37from multiprocessing import Pool 

38 

39from lsst.daf.butler import ( 

40 Butler, 

41 DataCoordinate, 

42 DataId, 

43 DimensionGraph, 

44 DimensionRecord, 

45 Timespan, 

46) 

47 

48import lsst.geom 

49from lsst.geom import Box2D 

50from lsst.pex.config import Config, Field, makeRegistry, registerConfigurable 

51from lsst.afw.cameraGeom import FOCAL_PLANE, PIXELS 

52from lsst.pipe.base import Task 

53from lsst.sphgeom import ConvexPolygon, Region, UnitVector3d 

54from ._instrument import loadCamera, Instrument 

55 

56 

57@dataclasses.dataclass 

58class VisitDefinitionData: 

59 """Struct representing a group of exposures that will be used to define a 

60 visit. 

61 """ 

62 

63 instrument: str 

64 """Name of the instrument this visit will be associated with. 

65 """ 

66 

67 id: int 

68 """Integer ID of the visit. 

69 

70 This must be unique across all visit systems for the instrument. 

71 """ 

72 

73 name: str 

74 """String name for the visit. 

75 

76 This must be unique across all visit systems for the instrument. 

77 """ 

78 

79 exposures: List[DimensionRecord] = dataclasses.field(default_factory=list) 

80 """Dimension records for the exposures that are part of this visit. 

81 """ 

82 

83 

84@dataclasses.dataclass 

85class _VisitRecords: 

86 """Struct containing the dimension records associated with a visit. 

87 """ 

88 

89 visit: DimensionRecord 

90 """Record for the 'visit' dimension itself. 

91 """ 

92 

93 visit_definition: List[DimensionRecord] 

94 """Records for 'visit_definition', which relates 'visit' to 'exposure'. 

95 """ 

96 

97 visit_detector_region: List[DimensionRecord] 

98 """Records for 'visit_detector_region', which associates the combination 

99 of a 'visit' and a 'detector' with a region on the sky. 

100 """ 

101 

102 

103class GroupExposuresConfig(Config): 

104 pass 

105 

106 

107class GroupExposuresTask(Task, metaclass=ABCMeta): 

108 """Abstract base class for the subtask of `DefineVisitsTask` that is 

109 responsible for grouping exposures into visits. 

110 

111 Subclasses should be registered with `GroupExposuresTask.registry` to 

112 enable use by `DefineVisitsTask`, and should generally correspond to a 

113 particular 'visit_system' dimension value. They are also responsible for 

114 defining visit IDs and names that are unique across all visit systems in 

115 use by an instrument. 

116 

117 Parameters 

118 ---------- 

119 config : `GroupExposuresConfig` 

120 Configuration information. 

121 **kwargs 

122 Additional keyword arguments forwarded to the `Task` constructor. 

123 """ 

124 def __init__(self, config: GroupExposuresConfig, **kwargs: Any): 

125 Task.__init__(self, config=config, **kwargs) 

126 

127 ConfigClass = GroupExposuresConfig 

128 

129 _DefaultName = "groupExposures" 

130 

131 registry = makeRegistry( 

132 doc="Registry of algorithms for grouping exposures into visits.", 

133 configBaseType=GroupExposuresConfig, 

134 ) 

135 

136 @abstractmethod 

137 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]: 

138 """Group the given exposures into visits. 

139 

140 Parameters 

141 ---------- 

142 exposures : `list` [ `DimensionRecord` ] 

143 DimensionRecords (for the 'exposure' dimension) describing the 

144 exposures to group. 

145 

146 Returns 

147 ------- 

148 visits : `Iterable` [ `VisitDefinitionData` ] 

149 Structs identifying the visits and the exposures associated with 

150 them. This may be an iterator or a container. 

151 """ 

152 raise NotImplementedError() 

153 

154 @abstractmethod 

155 def getVisitSystem(self) -> Tuple[int, str]: 

156 """Return identifiers for the 'visit_system' dimension this 

157 algorithm implements. 

158 

159 Returns 

160 ------- 

161 id : `int` 

162 Integer ID for the visit system (given an instrument). 

163 name : `str` 

164 Unique string identifier for the visit system (given an 

165 instrument). 

166 """ 

167 raise NotImplementedError() 

168 

169 

170class ComputeVisitRegionsConfig(Config): 

171 padding = Field( 

172 dtype=int, 

173 default=0, 

174 doc=("Pad raw image bounding boxes with specified number of pixels " 

175 "when calculating their (conservatively large) region on the " 

176 "sky."), 

177 ) 

178 

179 

180class ComputeVisitRegionsTask(Task, metaclass=ABCMeta): 

181 """Abstract base class for the subtask of `DefineVisitsTask` that is 

182 responsible for extracting spatial regions for visits and visit+detector 

183 combinations. 

184 

185 Subclasses should be registered with `ComputeVisitRegionsTask.registry` to 

186 enable use by `DefineVisitsTask`. 

187 

188 Parameters 

189 ---------- 

190 config : `ComputeVisitRegionsConfig` 

191 Configuration information. 

192 butler : `lsst.daf.butler.Butler` 

193 The butler to use. 

194 **kwargs 

195 Additional keyword arguments forwarded to the `Task` constructor. 

196 """ 

197 def __init__(self, config: ComputeVisitRegionsConfig, *, butler: Butler, **kwargs: Any): 

198 Task.__init__(self, config=config, **kwargs) 

199 self.butler = butler 

200 self.instrumentMap = {} 

201 

202 ConfigClass = ComputeVisitRegionsConfig 

203 

204 _DefaultName = "computeVisitRegions" 

205 

206 registry = makeRegistry( 

207 doc=("Registry of algorithms for computing on-sky regions for visits " 

208 "and visit+detector combinations."), 

209 configBaseType=ComputeVisitRegionsConfig, 

210 ) 

211 

212 def getInstrument(self, instrumentName) -> Instrument: 

213 """Retrieve an `~lsst.obs.base.Instrument` associated with this 

214 instrument name. 

215 

216 Parameters 

217 ---------- 

218 instrumentName : `str` 

219 The name of the instrument. 

220 

221 Returns 

222 ------- 

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

224 The associated instrument object. 

225 

226 Notes 

227 ----- 

228 The result is cached. 

229 """ 

230 instrument = self.instrumentMap.get(instrumentName) 

231 if instrument is None: 

232 instrument = Instrument.fromName(instrumentName, self.butler.registry) 

233 self.instrumentMap[instrumentName] = instrument 

234 return instrument 

235 

236 @abstractmethod 

237 def compute(self, visit: VisitDefinitionData, *, collections: Any = None 

238 ) -> Tuple[Region, Dict[int, Region]]: 

239 """Compute regions for the given visit and all detectors in that visit. 

240 

241 Parameters 

242 ---------- 

243 visit : `VisitDefinitionData` 

244 Struct describing the visit and the exposures associated with it. 

245 collections : Any, optional 

246 Collections to be searched for raws and camera geometry, overriding 

247 ``self.butler.collections``. 

248 Can be any of the types supported by the ``collections`` argument 

249 to butler construction. 

250 

251 Returns 

252 ------- 

253 visitRegion : `lsst.sphgeom.Region` 

254 Region for the full visit. 

255 visitDetectorRegions : `dict` [ `int`, `lsst.sphgeom.Region` ] 

256 Dictionary mapping detector ID to the region for that detector. 

257 Should include all detectors in the visit. 

258 """ 

259 raise NotImplementedError() 

260 

261 

262class DefineVisitsConfig(Config): 

263 groupExposures = GroupExposuresTask.registry.makeField( 

264 doc="Algorithm for grouping exposures into visits.", 

265 default="one-to-one", 

266 ) 

267 computeVisitRegions = ComputeVisitRegionsTask.registry.makeField( 

268 doc="Algorithm from computing visit and visit+detector regions.", 

269 default="single-raw-wcs", 

270 ) 

271 ignoreNonScienceExposures = Field( 

272 doc=("If True, silently ignore input exposures that do not have " 

273 "observation_type=SCIENCE. If False, raise an exception if one " 

274 "encountered."), 

275 dtype=bool, 

276 optional=False, 

277 default=True, 

278 ) 

279 

280 

281class DefineVisitsTask(Task): 

282 """Driver Task for defining visits (and their spatial regions) in Gen3 

283 Butler repositories. 

284 

285 Parameters 

286 ---------- 

287 config : `DefineVisitsConfig` 

288 Configuration for the task. 

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

290 Writeable butler instance. Will be used to read `raw.wcs` and `camera` 

291 datasets and insert/sync dimension data. 

292 **kwargs 

293 Additional keyword arguments are forwarded to the `lsst.pipe.base.Task` 

294 constructor. 

295 

296 Notes 

297 ----- 

298 Each instance of `DefineVisitsTask` reads from / writes to the same Butler. 

299 Each invocation of `DefineVisitsTask.run` processes an independent group of 

300 exposures into one or more new vists, all belonging to the same visit 

301 system and instrument. 

302 

303 The actual work of grouping exposures and computing regions is delegated 

304 to pluggable subtasks (`GroupExposuresTask` and `ComputeVisitRegionsTask`), 

305 respectively. The defaults are to create one visit for every exposure, 

306 and to use exactly one (arbitrary) detector-level raw dataset's WCS along 

307 with camera geometry to compute regions for all detectors. Other 

308 implementations can be created and configured for instruments for which 

309 these choices are unsuitable (e.g. because visits and exposures are not 

310 one-to-one, or because ``raw.wcs`` datasets for different detectors may not 

311 be consistent with camera geomery). 

312 

313 It is not necessary in general to ingest all raws for an exposure before 

314 defining a visit that includes the exposure; this depends entirely on the 

315 `ComputeVisitRegionTask` subclass used. For the default configuration, 

316 a single raw for each exposure is sufficient. 

317 

318 Defining the same visit the same way multiple times (e.g. via multiple 

319 invocations of this task on the same exposures, with the same 

320 configuration) is safe, but it may be inefficient, as most of the work must 

321 be done before new visits can be compared to existing visits. 

322 """ 

323 def __init__(self, config: Optional[DefineVisitsConfig] = None, *, butler: Butler, **kwargs: Any): 

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

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

326 self.butler = butler 

327 self.universe = self.butler.registry.dimensions 

328 self.makeSubtask("groupExposures") 

329 self.makeSubtask("computeVisitRegions", butler=self.butler) 

330 

331 def _reduce_kwargs(self): 

332 # Add extra parameters to pickle 

333 return dict(**super()._reduce_kwargs(), butler=self.butler) 

334 

335 ConfigClass = DefineVisitsConfig 

336 

337 _DefaultName = "defineVisits" 

338 

339 def _buildVisitRecords(self, definition: VisitDefinitionData, *, 

340 collections: Any = None) -> _VisitRecords: 

341 """Build the DimensionRecords associated with a visit. 

342 

343 Parameters 

344 ---------- 

345 definition : `VisitDefinition` 

346 Struct with identifiers for the visit and records for its 

347 constituent exposures. 

348 collections : Any, optional 

349 Collections to be searched for raws and camera geometry, overriding 

350 ``self.butler.collections``. 

351 Can be any of the types supported by the ``collections`` argument 

352 to butler construction. 

353 

354 Results 

355 ------- 

356 records : `_VisitRecords` 

357 Struct containing DimensionRecords for the visit, including 

358 associated dimension elements. 

359 """ 

360 # Compute all regions. 

361 visitRegion, visitDetectorRegions = self.computeVisitRegions.compute(definition, 

362 collections=collections) 

363 # Aggregate other exposure quantities. 

364 timespan = Timespan( 

365 begin=_reduceOrNone(min, (e.timespan.begin for e in definition.exposures)), 

366 end=_reduceOrNone(max, (e.timespan.end for e in definition.exposures)), 

367 ) 

368 exposure_time = _reduceOrNone(sum, (e.exposure_time for e in definition.exposures)) 

369 physical_filter = _reduceOrNone(lambda a, b: a if a == b else None, 

370 (e.physical_filter for e in definition.exposures)) 

371 target_name = _reduceOrNone(lambda a, b: a if a == b else None, 

372 (e.target_name for e in definition.exposures)) 

373 science_program = _reduceOrNone(lambda a, b: a if a == b else None, 

374 (e.science_program for e in definition.exposures)) 

375 observation_reason = _reduceOrNone(lambda a, b: a if a == b else None, 

376 (e.observation_reason for e in definition.exposures)) 

377 if observation_reason is None: 

378 # Be explicit about there being multiple reasons 

379 observation_reason = "various" 

380 

381 # Use the mean zenith angle as an approximation 

382 zenith_angle = _reduceOrNone(sum, (e.zenith_angle for e in definition.exposures)) 

383 if zenith_angle is not None: 

384 zenith_angle /= len(definition.exposures) 

385 

386 # Construct the actual DimensionRecords. 

387 return _VisitRecords( 

388 visit=self.universe["visit"].RecordClass( 

389 instrument=definition.instrument, 

390 id=definition.id, 

391 name=definition.name, 

392 physical_filter=physical_filter, 

393 target_name=target_name, 

394 science_program=science_program, 

395 observation_reason=observation_reason, 

396 zenith_angle=zenith_angle, 

397 visit_system=self.groupExposures.getVisitSystem()[0], 

398 exposure_time=exposure_time, 

399 timespan=timespan, 

400 region=visitRegion, 

401 # TODO: no seeing value in exposure dimension records, so we 

402 # can't set that here. But there are many other columns that 

403 # both dimensions should probably have as well. 

404 ), 

405 visit_definition=[ 

406 self.universe["visit_definition"].RecordClass( 

407 instrument=definition.instrument, 

408 visit=definition.id, 

409 exposure=exposure.id, 

410 visit_system=self.groupExposures.getVisitSystem()[0], 

411 ) 

412 for exposure in definition.exposures 

413 ], 

414 visit_detector_region=[ 

415 self.universe["visit_detector_region"].RecordClass( 

416 instrument=definition.instrument, 

417 visit=definition.id, 

418 detector=detectorId, 

419 region=detectorRegion, 

420 ) 

421 for detectorId, detectorRegion in visitDetectorRegions.items() 

422 ] 

423 ) 

424 

425 def _expandExposureId(self, dataId: DataId) -> DataCoordinate: 

426 """Return the expanded version of an exposure ID. 

427 

428 A private method to allow ID expansion in a pool without resorting 

429 to local callables. 

430 

431 Parameters 

432 ---------- 

433 dataId : `dict` or `DataCoordinate` 

434 Exposure-level data ID. 

435 

436 Returns 

437 ------- 

438 expanded : `DataCoordinate` 

439 A data ID that includes full metadata for all exposure dimensions. 

440 """ 

441 dimensions = DimensionGraph(self.universe, names=["exposure"]) 

442 return self.butler.registry.expandDataId(dataId, graph=dimensions) 

443 

444 def _buildVisitRecordsSingle(self, args) -> _VisitRecords: 

445 """Build the DimensionRecords associated with a visit and collection. 

446 

447 A wrapper for `_buildVisitRecords` to allow it to be run as part of 

448 a pool without resorting to local callables. 

449 

450 Parameters 

451 ---------- 

452 args : `tuple` [`VisitDefinition`, any] 

453 A tuple consisting of the ``definition`` and ``collections`` 

454 arguments to `_buildVisitRecords`, in that order. 

455 

456 Results 

457 ------- 

458 records : `_VisitRecords` 

459 Struct containing DimensionRecords for the visit, including 

460 associated dimension elements. 

461 """ 

462 return self._buildVisitRecords(args[0], collections=args[1]) 

463 

464 def run(self, dataIds: Iterable[DataId], *, 

465 pool: Optional[Pool] = None, 

466 processes: int = 1, 

467 collections: Optional[str] = None): 

468 """Add visit definitions to the registry for the given exposures. 

469 

470 Parameters 

471 ---------- 

472 dataIds : `Iterable` [ `dict` or `DataCoordinate` ] 

473 Exposure-level data IDs. These must all correspond to the same 

474 instrument, and are expected to be on-sky science exposures. 

475 pool : `multiprocessing.Pool`, optional 

476 If not `None`, a process pool with which to parallelize some 

477 operations. 

478 processes : `int`, optional 

479 The number of processes to use. Ignored if ``pool`` is not `None`. 

480 collections : Any, optional 

481 Collections to be searched for raws and camera geometry, overriding 

482 ``self.butler.collections``. 

483 Can be any of the types supported by the ``collections`` argument 

484 to butler construction. 

485 

486 Raises 

487 ------ 

488 lsst.daf.butler.registry.ConflictingDefinitionError 

489 Raised if a visit ID conflict is detected and the existing visit 

490 differs from the new one. 

491 """ 

492 # Set up multiprocessing, if desired. 

493 if pool is None and processes > 1: 

494 pool = Pool(processes) 

495 mapFunc = map if pool is None else pool.imap_unordered 

496 # Normalize, expand, and deduplicate data IDs. 

497 self.log.info("Preprocessing data IDs.") 

498 dataIds = set(mapFunc(self._expandExposureId, dataIds)) 

499 if not dataIds: 

500 raise RuntimeError("No exposures given.") 

501 # Extract exposure DimensionRecords, check that there's only one 

502 # instrument in play, and check for non-science exposures. 

503 exposures = [] 

504 instruments = set() 

505 for dataId in dataIds: 

506 record = dataId.records["exposure"] 

507 if record.observation_type != "science": 

508 if self.config.ignoreNonScienceExposures: 

509 continue 

510 else: 

511 raise RuntimeError(f"Input exposure {dataId} has observation_type " 

512 f"{record.observation_type}, not 'science'.") 

513 instruments.add(dataId["instrument"]) 

514 exposures.append(record) 

515 if not exposures: 

516 self.log.info("No science exposures found after filtering.") 

517 return 

518 if len(instruments) > 1: 

519 raise RuntimeError( 

520 f"All data IDs passed to DefineVisitsTask.run must be " 

521 f"from the same instrument; got {instruments}." 

522 ) 

523 instrument, = instruments 

524 # Ensure the visit_system our grouping algorithm uses is in the 

525 # registry, if it wasn't already. 

526 visitSystemId, visitSystemName = self.groupExposures.getVisitSystem() 

527 self.log.info("Registering visit_system %d: %s.", visitSystemId, visitSystemName) 

528 self.butler.registry.syncDimensionData( 

529 "visit_system", 

530 {"instrument": instrument, "id": visitSystemId, "name": visitSystemName} 

531 ) 

532 # Group exposures into visits, delegating to subtask. 

533 self.log.info("Grouping %d exposure(s) into visits.", len(exposures)) 

534 definitions = list(self.groupExposures.group(exposures)) 

535 # Compute regions and build DimensionRecords for each visit. 

536 # This is the only parallel step, but it _should_ be the most expensive 

537 # one (unless DB operations are slow). 

538 self.log.info("Computing regions and other metadata for %d visit(s).", len(definitions)) 

539 allRecords = mapFunc(self._buildVisitRecordsSingle, 

540 zip(definitions, itertools.repeat(collections))) 

541 # Iterate over visits and insert dimension data, one transaction per 

542 # visit. If a visit already exists, we skip all other inserts. 

543 for visitRecords in allRecords: 

544 with self.butler.registry.transaction(): 

545 if self.butler.registry.syncDimensionData("visit", visitRecords.visit): 

546 self.butler.registry.insertDimensionData("visit_definition", 

547 *visitRecords.visit_definition) 

548 self.butler.registry.insertDimensionData("visit_detector_region", 

549 *visitRecords.visit_detector_region) 

550 

551 

552def _reduceOrNone(func, iterable): 

553 """Apply a binary function to pairs of elements in an iterable until a 

554 single value is returned, but return `None` if any element is `None` or 

555 there are no elements. 

556 """ 

557 r = None 

558 for v in iterable: 

559 if v is None: 

560 return None 

561 if r is None: 

562 r = v 

563 else: 

564 r = func(r, v) 

565 return r 

566 

567 

568class _GroupExposuresOneToOneConfig(GroupExposuresConfig): 

569 visitSystemId = Field( 

570 doc=("Integer ID of the visit_system implemented by this grouping " 

571 "algorithm."), 

572 dtype=int, 

573 default=0, 

574 ) 

575 visitSystemName = Field( 

576 doc=("String name of the visit_system implemented by this grouping " 

577 "algorithm."), 

578 dtype=str, 

579 default="one-to-one", 

580 ) 

581 

582 

583@registerConfigurable("one-to-one", GroupExposuresTask.registry) 

584class _GroupExposuresOneToOneTask(GroupExposuresTask, metaclass=ABCMeta): 

585 """An exposure grouping algorithm that simply defines one visit for each 

586 exposure, reusing the exposures identifiers for the visit. 

587 """ 

588 

589 ConfigClass = _GroupExposuresOneToOneConfig 

590 

591 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]: 

592 # Docstring inherited from GroupExposuresTask. 

593 for exposure in exposures: 

594 yield VisitDefinitionData( 

595 instrument=exposure.instrument, 

596 id=exposure.id, 

597 name=exposure.name, 

598 exposures=[exposure], 

599 ) 

600 

601 def getVisitSystem(self) -> Tuple[int, str]: 

602 # Docstring inherited from GroupExposuresTask. 

603 return (self.config.visitSystemId, self.config.visitSystemName) 

604 

605 

606class _GroupExposuresByGroupMetadataConfig(GroupExposuresConfig): 

607 visitSystemId = Field( 

608 doc=("Integer ID of the visit_system implemented by this grouping " 

609 "algorithm."), 

610 dtype=int, 

611 default=1, 

612 ) 

613 visitSystemName = Field( 

614 doc=("String name of the visit_system implemented by this grouping " 

615 "algorithm."), 

616 dtype=str, 

617 default="by-group-metadata", 

618 ) 

619 

620 

621@registerConfigurable("by-group-metadata", GroupExposuresTask.registry) 

622class _GroupExposuresByGroupMetadataTask(GroupExposuresTask, metaclass=ABCMeta): 

623 """An exposure grouping algorithm that uses exposure.group_name and 

624 exposure.group_id. 

625 

626 This algorithm _assumes_ exposure.group_id (generally populated from 

627 `astro_metadata_translator.ObservationInfo.visit_id`) is not just unique, 

628 but disjoint from all `ObservationInfo.exposure_id` values - if it isn't, 

629 it will be impossible to ever use both this grouping algorithm and the 

630 one-to-one algorithm for a particular camera in the same data repository. 

631 """ 

632 

633 ConfigClass = _GroupExposuresByGroupMetadataConfig 

634 

635 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]: 

636 # Docstring inherited from GroupExposuresTask. 

637 groups = defaultdict(list) 

638 for exposure in exposures: 

639 groups[exposure.group_name].append(exposure) 

640 for visitName, exposuresInGroup in groups.items(): 

641 instrument = exposuresInGroup[0].instrument 

642 visitId = exposuresInGroup[0].group_id 

643 assert all(e.group_id == visitId for e in exposuresInGroup), \ 

644 "Grouping by exposure.group_name does not yield consistent group IDs" 

645 yield VisitDefinitionData(instrument=instrument, id=visitId, name=visitName, 

646 exposures=exposuresInGroup) 

647 

648 def getVisitSystem(self) -> Tuple[int, str]: 

649 # Docstring inherited from GroupExposuresTask. 

650 return (self.config.visitSystemId, self.config.visitSystemName) 

651 

652 

653class _ComputeVisitRegionsFromSingleRawWcsConfig(ComputeVisitRegionsConfig): 

654 mergeExposures = Field( 

655 doc=("If True, merge per-detector regions over all exposures in a " 

656 "visit (via convex hull) instead of using the first exposure and " 

657 "assuming its regions are valid for all others."), 

658 dtype=bool, 

659 default=False, 

660 ) 

661 detectorId = Field( 

662 doc=("Load the WCS for the detector with this ID. If None, use an " 

663 "arbitrary detector (the first found in a query of the data " 

664 "repository for each exposure (or all exposures, if " 

665 "mergeExposures is True)."), 

666 dtype=int, 

667 optional=True, 

668 default=None 

669 ) 

670 requireVersionedCamera = Field( 

671 doc=("If True, raise LookupError if version camera geometry cannot be " 

672 "loaded for an exposure. If False, use the nominal camera from " 

673 "the Instrument class instead."), 

674 dtype=bool, 

675 optional=False, 

676 default=False, 

677 ) 

678 

679 

680@registerConfigurable("single-raw-wcs", ComputeVisitRegionsTask.registry) 

681class _ComputeVisitRegionsFromSingleRawWcsTask(ComputeVisitRegionsTask): 

682 """A visit region calculator that uses a single raw WCS and a camera to 

683 project the bounding boxes of all detectors onto the sky, relating 

684 different detectors by their positions in focal plane coordinates. 

685 

686 Notes 

687 ----- 

688 Most instruments should have their raw WCSs determined from a combination 

689 of boresight angle, rotator angle, and camera geometry, and hence this 

690 algorithm should produce stable results regardless of which detector the 

691 raw corresponds to. If this is not the case (e.g. because a per-file FITS 

692 WCS is used instead), either the ID of the detector should be fixed (see 

693 the ``detectorId`` config parameter) or a different algorithm used. 

694 """ 

695 

696 ConfigClass = _ComputeVisitRegionsFromSingleRawWcsConfig 

697 

698 def computeExposureBounds(self, exposure: DimensionRecord, *, collections: Any = None 

699 ) -> Dict[int, List[UnitVector3d]]: 

700 """Compute the lists of unit vectors on the sphere that correspond to 

701 the sky positions of detector corners. 

702 

703 Parameters 

704 ---------- 

705 exposure : `DimensionRecord` 

706 Dimension record for the exposure. 

707 collections : Any, optional 

708 Collections to be searched for raws and camera geometry, overriding 

709 ``self.butler.collections``. 

710 Can be any of the types supported by the ``collections`` argument 

711 to butler construction. 

712 

713 Returns 

714 ------- 

715 bounds : `dict` 

716 Dictionary mapping detector ID to a list of unit vectors on the 

717 sphere representing that detector's corners projected onto the sky. 

718 """ 

719 if collections is None: 

720 collections = self.butler.collections 

721 camera, versioned = loadCamera(self.butler, exposure.dataId, collections=collections) 

722 if not versioned and self.config.requireVersionedCamera: 

723 raise LookupError(f"No versioned camera found for exposure {exposure.dataId}.") 

724 

725 # Derive WCS from boresight information -- if available in registry 

726 use_registry = True 

727 try: 

728 orientation = lsst.geom.Angle(exposure.sky_angle, lsst.geom.degrees) 

729 radec = lsst.geom.SpherePoint(lsst.geom.Angle(exposure.tracking_ra, lsst.geom.degrees), 

730 lsst.geom.Angle(exposure.tracking_dec, lsst.geom.degrees)) 

731 except AttributeError: 

732 use_registry = False 

733 

734 if use_registry: 

735 if self.config.detectorId is None: 

736 detectorId = next(camera.getIdIter()) 

737 else: 

738 detectorId = self.config.detectorId 

739 wcsDetector = camera[detectorId] 

740 

741 # Ask the raw formatter to create the relevant WCS 

742 # This allows flips to be taken into account 

743 instrument = self.getInstrument(exposure.instrument) 

744 rawFormatter = instrument.getRawFormatter({"detector": detectorId}) 

745 wcs = rawFormatter.makeRawSkyWcsFromBoresight(radec, orientation, wcsDetector) 

746 

747 else: 

748 if self.config.detectorId is None: 

749 wcsRefsIter = self.butler.registry.queryDatasets("raw.wcs", dataId=exposure.dataId, 

750 collections=collections) 

751 if not wcsRefsIter: 

752 raise LookupError(f"No raw.wcs datasets found for data ID {exposure.dataId} " 

753 f"in collections {collections}.") 

754 wcsRef = next(iter(wcsRefsIter)) 

755 wcsDetector = camera[wcsRef.dataId["detector"]] 

756 wcs = self.butler.getDirect(wcsRef) 

757 else: 

758 wcsDetector = camera[self.config.detectorId] 

759 wcs = self.butler.get("raw.wcs", dataId=exposure.dataId, detector=self.config.detectorId, 

760 collections=collections) 

761 fpToSky = wcsDetector.getTransform(FOCAL_PLANE, PIXELS).then(wcs.getTransform()) 

762 bounds = {} 

763 for detector in camera: 

764 pixelsToSky = detector.getTransform(PIXELS, FOCAL_PLANE).then(fpToSky) 

765 pixCorners = Box2D(detector.getBBox().dilatedBy(self.config.padding)).getCorners() 

766 bounds[detector.getId()] = [ 

767 skyCorner.getVector() for skyCorner in pixelsToSky.applyForward(pixCorners) 

768 ] 

769 return bounds 

770 

771 def compute(self, visit: VisitDefinitionData, *, collections: Any = None 

772 ) -> Tuple[Region, Dict[int, Region]]: 

773 # Docstring inherited from ComputeVisitRegionsTask. 

774 if self.config.mergeExposures: 

775 detectorBounds = defaultdict(list) 

776 for exposure in visit.exposures: 

777 exposureDetectorBounds = self.computeExposureBounds(exposure, collections=collections) 

778 for detectorId, bounds in exposureDetectorBounds.items(): 

779 detectorBounds[detectorId].extend(bounds) 

780 else: 

781 detectorBounds = self.computeExposureBounds(visit.exposures[0], collections=collections) 

782 visitBounds = [] 

783 detectorRegions = {} 

784 for detectorId, bounds in detectorBounds.items(): 

785 detectorRegions[detectorId] = ConvexPolygon.convexHull(bounds) 

786 visitBounds.extend(bounds) 

787 return ConvexPolygon.convexHull(visitBounds), detectorRegions