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

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

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

321 self.butler = butler 

322 self.universe = self.butler.registry.dimensions 

323 self.makeSubtask("groupExposures") 

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

325 

326 @classmethod 

327 # WARNING: this method hardcodes the parameters to pipe.base.Task.__init__. 

328 # Nobody seems to know a way to delegate them to Task code. 

329 def _makeTask(cls, config: DefineVisitsConfig, butler: Butler, name: str, parentTask: Task): 

330 """Construct a DefineVisitsTask using only positional arguments. 

331 

332 Parameters 

333 ---------- 

334 All parameters are as for `DefineVisitsTask`. 

335 """ 

336 return cls(config=config, butler=butler, name=name, parentTask=parentTask) 

337 

338 # Overrides Task.__reduce__ 

339 def __reduce__(self): 

340 return (self._makeTask, (self.config, self.butler, self._name, self._parentTask)) 

341 

342 ConfigClass = DefineVisitsConfig 

343 

344 _DefaultName = "defineVisits" 

345 

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

347 collections: Any = None) -> _VisitRecords: 

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

349 

350 Parameters 

351 ---------- 

352 definition : `VisitDefinition` 

353 Struct with identifiers for the visit and records for its 

354 constituent exposures. 

355 collections : Any, optional 

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

357 ``self.butler.collections``. 

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

359 to butler construction. 

360 

361 Results 

362 ------- 

363 records : `_VisitRecords` 

364 Struct containing DimensionRecords for the visit, including 

365 associated dimension elements. 

366 """ 

367 # Compute all regions. 

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

369 collections=collections) 

370 # Aggregate other exposure quantities. 

371 timespan = Timespan( 

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

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

374 ) 

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

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

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

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

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

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

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

382 

383 # Use the mean zenith angle as an approximation 

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

385 if zenith_angle is not None: 

386 zenith_angle /= len(definition.exposures) 

387 

388 # Construct the actual DimensionRecords. 

389 return _VisitRecords( 

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

391 instrument=definition.instrument, 

392 id=definition.id, 

393 name=definition.name, 

394 physical_filter=physical_filter, 

395 target_name=target_name, 

396 science_program=science_program, 

397 zenith_angle=zenith_angle, 

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

399 exposure_time=exposure_time, 

400 timespan=timespan, 

401 region=visitRegion, 

402 # TODO: no seeing value in exposure dimension records, so we can't 

403 # set that here. But there are many other columns that both 

404 # dimensions should probably have as well. 

405 ), 

406 visit_definition=[ 

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

408 instrument=definition.instrument, 

409 visit=definition.id, 

410 exposure=exposure.id, 

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

412 ) 

413 for exposure in definition.exposures 

414 ], 

415 visit_detector_region=[ 

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

417 instrument=definition.instrument, 

418 visit=definition.id, 

419 detector=detectorId, 

420 region=detectorRegion, 

421 ) 

422 for detectorId, detectorRegion in visitDetectorRegions.items() 

423 ] 

424 ) 

425 

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

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

428 

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

430 to local callables. 

431 

432 Parameters 

433 ---------- 

434 dataId : `dict` or `DataCoordinate` 

435 Exposure-level data ID. 

436 

437 Returns 

438 ------- 

439 expanded : `DataCoordinate` 

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

441 """ 

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

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

444 

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

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

447 

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

449 a pool without resorting to local callables. 

450 

451 Parameters 

452 ---------- 

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

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

455 arguments to `_buildVisitRecords`, in that order. 

456 

457 Results 

458 ------- 

459 records : `_VisitRecords` 

460 Struct containing DimensionRecords for the visit, including 

461 associated dimension elements. 

462 """ 

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

464 

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

466 pool: Optional[Pool] = None, 

467 processes: int = 1, 

468 collections: Optional[str] = None): 

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

470 

471 Parameters 

472 ---------- 

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

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

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

476 pool : `multiprocessing.Pool`, optional 

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

478 operations. 

479 processes : `int`, optional 

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

481 collections : Any, optional 

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

483 ``self.butler.collections``. 

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

485 to butler construction. 

486 """ 

487 # Set up multiprocessing, if desired. 

488 if pool is None and processes > 1: 

489 pool = Pool(processes) 

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

491 # Normalize, expand, and deduplicate data IDs. 

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

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

494 if not dataIds: 

495 raise RuntimeError("No exposures given.") 

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

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

498 exposures = [] 

499 instruments = set() 

500 for dataId in dataIds: 

501 record = dataId.records["exposure"] 

502 if record.observation_type != "science": 

503 if self.config.ignoreNonScienceExposures: 

504 continue 

505 else: 

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

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

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

509 exposures.append(record) 

510 if not exposures: 

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

512 return 

513 if len(instruments) > 1: 

514 raise RuntimeError( 

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

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

517 ) 

518 instrument, = instruments 

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

520 # registry, if it wasn't already. 

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

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

523 self.butler.registry.syncDimensionData( 

524 "visit_system", 

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

526 ) 

527 # Group exposures into visits, delegating to subtask. 

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

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

530 # Compute regions and build DimensionRecords for each visit. 

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

532 # one (unless DB operations are slow). 

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

534 allRecords = mapFunc(self._buildVisitRecordsSingle, 

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

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

537 # visit. 

538 for visitRecords in allRecords: 

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

540 self.butler.registry.insertDimensionData("visit", visitRecords.visit) 

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

542 *visitRecords.visit_definition) 

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

544 *visitRecords.visit_detector_region) 

545 

546 

547def _reduceOrNone(func, iterable): 

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

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

550 there are no elements. 

551 """ 

552 r = None 

553 for v in iterable: 

554 if v is None: 

555 return None 

556 if r is None: 

557 r = v 

558 else: 

559 r = func(r, v) 

560 return r 

561 

562 

563class _GroupExposuresOneToOneConfig(GroupExposuresConfig): 

564 visitSystemId = Field( 

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

566 "algorithm."), 

567 dtype=int, 

568 default=0, 

569 ) 

570 visitSystemName = Field( 

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

572 "algorithm."), 

573 dtype=str, 

574 default="one-to-one", 

575 ) 

576 

577 

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

579class _GroupExposuresOneToOneTask(GroupExposuresTask, metaclass=ABCMeta): 

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

581 exposure, reusing the exposures identifiers for the visit. 

582 """ 

583 

584 ConfigClass = _GroupExposuresOneToOneConfig 

585 

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

587 # Docstring inherited from GroupExposuresTask. 

588 for exposure in exposures: 

589 yield VisitDefinitionData( 

590 instrument=exposure.instrument, 

591 id=exposure.id, 

592 name=exposure.name, 

593 exposures=[exposure], 

594 ) 

595 

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

597 # Docstring inherited from GroupExposuresTask. 

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

599 

600 

601class _GroupExposuresByGroupMetadataConfig(GroupExposuresConfig): 

602 visitSystemId = Field( 

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

604 "algorithm."), 

605 dtype=int, 

606 default=1, 

607 ) 

608 visitSystemName = Field( 

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

610 "algorithm."), 

611 dtype=str, 

612 default="by-group-metadata", 

613 ) 

614 

615 

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

617class _GroupExposuresByGroupMetadataTask(GroupExposuresTask, metaclass=ABCMeta): 

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

619 exposure.group_id. 

620 

621 This algorithm _assumes_ exposure.group_id (generally populated from 

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

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

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

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

626 """ 

627 

628 ConfigClass = _GroupExposuresByGroupMetadataConfig 

629 

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

631 # Docstring inherited from GroupExposuresTask. 

632 groups = defaultdict(list) 

633 for exposure in exposures: 

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

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

636 instrument = exposuresInGroup[0].instrument 

637 visitId = exposuresInGroup[0].group_id 

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

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

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

641 exposures=exposuresInGroup) 

642 

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

644 # Docstring inherited from GroupExposuresTask. 

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

646 

647 

648class _ComputeVisitRegionsFromSingleRawWcsConfig(ComputeVisitRegionsConfig): 

649 mergeExposures = Field( 

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

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

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

653 dtype=bool, 

654 default=False, 

655 ) 

656 detectorId = Field( 

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

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

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

660 "mergeExposures is True)."), 

661 dtype=int, 

662 optional=True, 

663 default=None 

664 ) 

665 requireVersionedCamera = Field( 

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

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

668 "the Instrument class instead."), 

669 dtype=bool, 

670 optional=False, 

671 default=False, 

672 ) 

673 

674 

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

676class _ComputeVisitRegionsFromSingleRawWcsTask(ComputeVisitRegionsTask): 

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

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

679 different detectors by their positions in focal plane coordinates. 

680 

681 Notes 

682 ----- 

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

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

685 algorithm should produce stable results regardless of which detector the 

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

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

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

689 """ 

690 

691 ConfigClass = _ComputeVisitRegionsFromSingleRawWcsConfig 

692 

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

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

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

696 the sky positions of detector corners. 

697 

698 Parameters 

699 ---------- 

700 exposure : `DimensionRecord` 

701 Dimension record for the exposure. 

702 collections : Any, optional 

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

704 ``self.butler.collections``. 

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

706 to butler construction. 

707 

708 Returns 

709 ------- 

710 bounds : `dict` 

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

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

713 """ 

714 if collections is None: 

715 collections = self.butler.collections 

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

717 if not versioned and self.config.requireVersionedCamera: 

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

719 

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

721 use_registry = True 

722 try: 

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

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

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

726 except AttributeError: 

727 use_registry = False 

728 

729 if use_registry: 

730 if self.config.detectorId is None: 

731 detectorId = next(camera.getIdIter()) 

732 else: 

733 detectorId = self.config.detectorId 

734 wcsDetector = camera[detectorId] 

735 

736 # Ask the raw formatter to create the relevant WCS 

737 # This allows flips to be taken into account 

738 instrument = self.getInstrument(exposure.instrument) 

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

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

741 

742 else: 

743 if self.config.detectorId is None: 

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

745 collections=collections) 

746 if not wcsRefsIter: 

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

748 f"in collections {collections}.") 

749 wcsRef = next(iter(wcsRefsIter)) 

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

751 wcs = self.butler.getDirect(wcsRef) 

752 else: 

753 wcsDetector = camera[self.config.detectorId] 

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

755 collections=collections) 

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

757 bounds = {} 

758 for detector in camera: 

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

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

761 bounds[detector.getId()] = [ 

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

763 ] 

764 return bounds 

765 

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

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

768 # Docstring inherited from ComputeVisitRegionsTask. 

769 if self.config.mergeExposures: 

770 detectorBounds = defaultdict(list) 

771 for exposure in visit.exposures: 

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

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

774 detectorBounds[detectorId].extend(bounds) 

775 else: 

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

777 visitBounds = [] 

778 detectorRegions = {} 

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

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

781 visitBounds.extend(bounds) 

782 return ConvexPolygon.convexHull(visitBounds), detectorRegions