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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.
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)
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.
332 Parameters
333 ----------
334 All parameters are as for `DefineVisitsTask`.
335 """
336 return cls(config=config, butler=butler, name=name, parentTask=parentTask)
338 # Overrides Task.__reduce__
339 def __reduce__(self):
340 return (self._makeTask, (self.config, self.butler, self._name, self._parentTask))
342 ConfigClass = DefineVisitsConfig
344 _DefaultName = "defineVisits"
346 def _buildVisitRecords(self, definition: VisitDefinitionData, *,
347 collections: Any = None) -> _VisitRecords:
348 """Build the DimensionRecords associated with a visit.
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.
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))
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)
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 )
426 def _expandExposureId(self, dataId: DataId) -> DataCoordinate:
427 """Return the expanded version of an exposure ID.
429 A private method to allow ID expansion in a pool without resorting
430 to local callables.
432 Parameters
433 ----------
434 dataId : `dict` or `DataCoordinate`
435 Exposure-level data ID.
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)
445 def _buildVisitRecordsSingle(self, args) -> _VisitRecords:
446 """Build the DimensionRecords associated with a visit and collection.
448 A wrapper for `_buildVisitRecords` to allow it to be run as part of
449 a pool without resorting to local callables.
451 Parameters
452 ----------
453 args : `tuple` [`VisitDefinition`, any]
454 A tuple consisting of the ``definition`` and ``collections``
455 arguments to `_buildVisitRecords`, in that order.
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])
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.
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)
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
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 )
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 """
584 ConfigClass = _GroupExposuresOneToOneConfig
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 )
596 def getVisitSystem(self) -> Tuple[int, str]:
597 # Docstring inherited from GroupExposuresTask.
598 return (self.config.visitSystemId, self.config.visitSystemName)
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 )
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.
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 """
628 ConfigClass = _GroupExposuresByGroupMetadataConfig
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)
643 def getVisitSystem(self) -> Tuple[int, str]:
644 # Docstring inherited from GroupExposuresTask.
645 return (self.config.visitSystemId, self.config.visitSystemName)
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 )
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.
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 """
691 ConfigClass = _ComputeVisitRegionsFromSingleRawWcsConfig
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.
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.
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}.")
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
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]
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)
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
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