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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/>.
22from __future__ import annotations
24__all__ = [
25 "DefineVisitsConfig",
26 "DefineVisitsTask",
27 "GroupExposuresConfig",
28 "GroupExposuresTask",
29 "VisitDefinitionData",
30]
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
39from lsst.daf.butler import (
40 Butler,
41 DataCoordinate,
42 DataId,
43 DimensionGraph,
44 DimensionRecord,
45 Timespan,
46)
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
57@dataclasses.dataclass
58class VisitDefinitionData:
59 """Struct representing a group of exposures that will be used to define a
60 visit.
61 """
63 instrument: str
64 """Name of the instrument this visit will be associated with.
65 """
67 id: int
68 """Integer ID of the visit.
70 This must be unique across all visit systems for the instrument.
71 """
73 name: str
74 """String name for the visit.
76 This must be unique across all visit systems for the instrument.
77 """
79 exposures: List[DimensionRecord] = dataclasses.field(default_factory=list)
80 """Dimension records for the exposures that are part of this visit.
81 """
84@dataclasses.dataclass
85class _VisitRecords:
86 """Struct containing the dimension records associated with a visit.
87 """
89 visit: DimensionRecord
90 """Record for the 'visit' dimension itself.
91 """
93 visit_definition: List[DimensionRecord]
94 """Records for 'visit_definition', which relates 'visit' to 'exposure'.
95 """
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 """
103class GroupExposuresConfig(Config):
104 pass
107class GroupExposuresTask(Task, metaclass=ABCMeta):
108 """Abstract base class for the subtask of `DefineVisitsTask` that is
109 responsible for grouping exposures into visits.
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.
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)
127 ConfigClass = GroupExposuresConfig
129 _DefaultName = "groupExposures"
131 registry = makeRegistry(
132 doc="Registry of algorithms for grouping exposures into visits.",
133 configBaseType=GroupExposuresConfig,
134 )
136 @abstractmethod
137 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]:
138 """Group the given exposures into visits.
140 Parameters
141 ----------
142 exposures : `list` [ `DimensionRecord` ]
143 DimensionRecords (for the 'exposure' dimension) describing the
144 exposures to group.
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()
154 @abstractmethod
155 def getVisitSystem(self) -> Tuple[int, str]:
156 """Return identifiers for the 'visit_system' dimension this
157 algorithm implements.
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()
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 )
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.
185 Subclasses should be registered with `ComputeVisitRegionsTask.registry` to
186 enable use by `DefineVisitsTask`.
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 = {}
202 ConfigClass = ComputeVisitRegionsConfig
204 _DefaultName = "computeVisitRegions"
206 registry = makeRegistry(
207 doc=("Registry of algorithms for computing on-sky regions for visits "
208 "and visit+detector combinations."),
209 configBaseType=ComputeVisitRegionsConfig,
210 )
212 def getInstrument(self, instrumentName) -> Instrument:
213 """Retrieve an `~lsst.obs.base.Instrument` associated with this
214 instrument name.
216 Parameters
217 ----------
218 instrumentName : `str`
219 The name of the instrument.
221 Returns
222 -------
223 instrument : `~lsst.obs.base.Instrument`
224 The associated instrument object.
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
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.
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.
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()
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 )
281class DefineVisitsTask(Task):
282 """Driver Task for defining visits (and their spatial regions) in Gen3
283 Butler repositories.
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.
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.
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).
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.
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)
331 def _reduce_kwargs(self):
332 # Add extra parameters to pickle
333 return dict(**super()._reduce_kwargs(), butler=self.butler)
335 ConfigClass = DefineVisitsConfig
337 _DefaultName = "defineVisits"
339 def _buildVisitRecords(self, definition: VisitDefinitionData, *,
340 collections: Any = None) -> _VisitRecords:
341 """Build the DimensionRecords associated with a visit.
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.
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"
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)
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 )
425 def _expandExposureId(self, dataId: DataId) -> DataCoordinate:
426 """Return the expanded version of an exposure ID.
428 A private method to allow ID expansion in a pool without resorting
429 to local callables.
431 Parameters
432 ----------
433 dataId : `dict` or `DataCoordinate`
434 Exposure-level data ID.
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)
444 def _buildVisitRecordsSingle(self, args) -> _VisitRecords:
445 """Build the DimensionRecords associated with a visit and collection.
447 A wrapper for `_buildVisitRecords` to allow it to be run as part of
448 a pool without resorting to local callables.
450 Parameters
451 ----------
452 args : `tuple` [`VisitDefinition`, any]
453 A tuple consisting of the ``definition`` and ``collections``
454 arguments to `_buildVisitRecords`, in that order.
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])
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.
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.
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)
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
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 )
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 """
589 ConfigClass = _GroupExposuresOneToOneConfig
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 )
601 def getVisitSystem(self) -> Tuple[int, str]:
602 # Docstring inherited from GroupExposuresTask.
603 return (self.config.visitSystemId, self.config.visitSystemName)
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 )
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.
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 """
633 ConfigClass = _GroupExposuresByGroupMetadataConfig
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)
648 def getVisitSystem(self) -> Tuple[int, str]:
649 # Docstring inherited from GroupExposuresTask.
650 return (self.config.visitSystemId, self.config.visitSystemName)
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 )
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.
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 """
696 ConfigClass = _ComputeVisitRegionsFromSingleRawWcsConfig
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.
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.
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}.")
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
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]
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)
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
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