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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 def _reduce_kwargs(self):
327 # Add extra parameters to pickle
328 return dict(**super()._reduce_kwargs(), butler=self.butler)
330 ConfigClass = DefineVisitsConfig
332 _DefaultName = "defineVisits"
334 def _buildVisitRecords(self, definition: VisitDefinitionData, *,
335 collections: Any = None) -> _VisitRecords:
336 """Build the DimensionRecords associated with a visit.
338 Parameters
339 ----------
340 definition : `VisitDefinition`
341 Struct with identifiers for the visit and records for its
342 constituent exposures.
343 collections : Any, optional
344 Collections to be searched for raws and camera geometry, overriding
345 ``self.butler.collections``.
346 Can be any of the types supported by the ``collections`` argument
347 to butler construction.
349 Results
350 -------
351 records : `_VisitRecords`
352 Struct containing DimensionRecords for the visit, including
353 associated dimension elements.
354 """
355 # Compute all regions.
356 visitRegion, visitDetectorRegions = self.computeVisitRegions.compute(definition,
357 collections=collections)
358 # Aggregate other exposure quantities.
359 timespan = Timespan(
360 begin=_reduceOrNone(min, (e.timespan.begin for e in definition.exposures)),
361 end=_reduceOrNone(max, (e.timespan.end for e in definition.exposures)),
362 )
363 exposure_time = _reduceOrNone(sum, (e.exposure_time for e in definition.exposures))
364 physical_filter = _reduceOrNone(lambda a, b: a if a == b else None,
365 (e.physical_filter for e in definition.exposures))
366 target_name = _reduceOrNone(lambda a, b: a if a == b else None,
367 (e.target_name for e in definition.exposures))
368 science_program = _reduceOrNone(lambda a, b: a if a == b else None,
369 (e.science_program for e in definition.exposures))
370 observation_reason = _reduceOrNone(lambda a, b: a if a == b else None,
371 (e.observation_reason for e in definition.exposures))
372 if observation_reason is None:
373 # Be explicit about there being multiple reasons
374 observation_reason = "various"
376 # Use the mean zenith angle as an approximation
377 zenith_angle = _reduceOrNone(sum, (e.zenith_angle for e in definition.exposures))
378 if zenith_angle is not None:
379 zenith_angle /= len(definition.exposures)
381 # Construct the actual DimensionRecords.
382 return _VisitRecords(
383 visit=self.universe["visit"].RecordClass(
384 instrument=definition.instrument,
385 id=definition.id,
386 name=definition.name,
387 physical_filter=physical_filter,
388 target_name=target_name,
389 science_program=science_program,
390 observation_reason=observation_reason,
391 zenith_angle=zenith_angle,
392 visit_system=self.groupExposures.getVisitSystem()[0],
393 exposure_time=exposure_time,
394 timespan=timespan,
395 region=visitRegion,
396 # TODO: no seeing value in exposure dimension records, so we
397 # can't set that here. But there are many other columns that
398 # both dimensions should probably have as well.
399 ),
400 visit_definition=[
401 self.universe["visit_definition"].RecordClass(
402 instrument=definition.instrument,
403 visit=definition.id,
404 exposure=exposure.id,
405 visit_system=self.groupExposures.getVisitSystem()[0],
406 )
407 for exposure in definition.exposures
408 ],
409 visit_detector_region=[
410 self.universe["visit_detector_region"].RecordClass(
411 instrument=definition.instrument,
412 visit=definition.id,
413 detector=detectorId,
414 region=detectorRegion,
415 )
416 for detectorId, detectorRegion in visitDetectorRegions.items()
417 ]
418 )
420 def _expandExposureId(self, dataId: DataId) -> DataCoordinate:
421 """Return the expanded version of an exposure ID.
423 A private method to allow ID expansion in a pool without resorting
424 to local callables.
426 Parameters
427 ----------
428 dataId : `dict` or `DataCoordinate`
429 Exposure-level data ID.
431 Returns
432 -------
433 expanded : `DataCoordinate`
434 A data ID that includes full metadata for all exposure dimensions.
435 """
436 dimensions = DimensionGraph(self.universe, names=["exposure"])
437 return self.butler.registry.expandDataId(dataId, graph=dimensions)
439 def _buildVisitRecordsSingle(self, args) -> _VisitRecords:
440 """Build the DimensionRecords associated with a visit and collection.
442 A wrapper for `_buildVisitRecords` to allow it to be run as part of
443 a pool without resorting to local callables.
445 Parameters
446 ----------
447 args : `tuple` [`VisitDefinition`, any]
448 A tuple consisting of the ``definition`` and ``collections``
449 arguments to `_buildVisitRecords`, in that order.
451 Results
452 -------
453 records : `_VisitRecords`
454 Struct containing DimensionRecords for the visit, including
455 associated dimension elements.
456 """
457 return self._buildVisitRecords(args[0], collections=args[1])
459 def run(self, dataIds: Iterable[DataId], *,
460 pool: Optional[Pool] = None,
461 processes: int = 1,
462 collections: Optional[str] = None):
463 """Add visit definitions to the registry for the given exposures.
465 Parameters
466 ----------
467 dataIds : `Iterable` [ `dict` or `DataCoordinate` ]
468 Exposure-level data IDs. These must all correspond to the same
469 instrument, and are expected to be on-sky science exposures.
470 pool : `multiprocessing.Pool`, optional
471 If not `None`, a process pool with which to parallelize some
472 operations.
473 processes : `int`, optional
474 The number of processes to use. Ignored if ``pool`` is not `None`.
475 collections : Any, optional
476 Collections to be searched for raws and camera geometry, overriding
477 ``self.butler.collections``.
478 Can be any of the types supported by the ``collections`` argument
479 to butler construction.
480 """
481 # Set up multiprocessing, if desired.
482 if pool is None and processes > 1:
483 pool = Pool(processes)
484 mapFunc = map if pool is None else pool.imap_unordered
485 # Normalize, expand, and deduplicate data IDs.
486 self.log.info("Preprocessing data IDs.")
487 dataIds = set(mapFunc(self._expandExposureId, dataIds))
488 if not dataIds:
489 raise RuntimeError("No exposures given.")
490 # Extract exposure DimensionRecords, check that there's only one
491 # instrument in play, and check for non-science exposures.
492 exposures = []
493 instruments = set()
494 for dataId in dataIds:
495 record = dataId.records["exposure"]
496 if record.observation_type != "science":
497 if self.config.ignoreNonScienceExposures:
498 continue
499 else:
500 raise RuntimeError(f"Input exposure {dataId} has observation_type "
501 f"{record.observation_type}, not 'science'.")
502 instruments.add(dataId["instrument"])
503 exposures.append(record)
504 if not exposures:
505 self.log.info("No science exposures found after filtering.")
506 return
507 if len(instruments) > 1:
508 raise RuntimeError(
509 f"All data IDs passed to DefineVisitsTask.run must be "
510 f"from the same instrument; got {instruments}."
511 )
512 instrument, = instruments
513 # Ensure the visit_system our grouping algorithm uses is in the
514 # registry, if it wasn't already.
515 visitSystemId, visitSystemName = self.groupExposures.getVisitSystem()
516 self.log.info("Registering visit_system %d: %s.", visitSystemId, visitSystemName)
517 self.butler.registry.syncDimensionData(
518 "visit_system",
519 {"instrument": instrument, "id": visitSystemId, "name": visitSystemName}
520 )
521 # Group exposures into visits, delegating to subtask.
522 self.log.info("Grouping %d exposure(s) into visits.", len(exposures))
523 definitions = list(self.groupExposures.group(exposures))
524 # Compute regions and build DimensionRecords for each visit.
525 # This is the only parallel step, but it _should_ be the most expensive
526 # one (unless DB operations are slow).
527 self.log.info("Computing regions and other metadata for %d visit(s).", len(definitions))
528 allRecords = mapFunc(self._buildVisitRecordsSingle,
529 zip(definitions, itertools.repeat(collections)))
530 # Iterate over visits and insert dimension data, one transaction per
531 # visit.
532 for visitRecords in allRecords:
533 with self.butler.registry.transaction():
534 self.butler.registry.insertDimensionData("visit", visitRecords.visit)
535 self.butler.registry.insertDimensionData("visit_definition",
536 *visitRecords.visit_definition)
537 self.butler.registry.insertDimensionData("visit_detector_region",
538 *visitRecords.visit_detector_region)
541def _reduceOrNone(func, iterable):
542 """Apply a binary function to pairs of elements in an iterable until a
543 single value is returned, but return `None` if any element is `None` or
544 there are no elements.
545 """
546 r = None
547 for v in iterable:
548 if v is None:
549 return None
550 if r is None:
551 r = v
552 else:
553 r = func(r, v)
554 return r
557class _GroupExposuresOneToOneConfig(GroupExposuresConfig):
558 visitSystemId = Field(
559 doc=("Integer ID of the visit_system implemented by this grouping "
560 "algorithm."),
561 dtype=int,
562 default=0,
563 )
564 visitSystemName = Field(
565 doc=("String name of the visit_system implemented by this grouping "
566 "algorithm."),
567 dtype=str,
568 default="one-to-one",
569 )
572@registerConfigurable("one-to-one", GroupExposuresTask.registry)
573class _GroupExposuresOneToOneTask(GroupExposuresTask, metaclass=ABCMeta):
574 """An exposure grouping algorithm that simply defines one visit for each
575 exposure, reusing the exposures identifiers for the visit.
576 """
578 ConfigClass = _GroupExposuresOneToOneConfig
580 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]:
581 # Docstring inherited from GroupExposuresTask.
582 for exposure in exposures:
583 yield VisitDefinitionData(
584 instrument=exposure.instrument,
585 id=exposure.id,
586 name=exposure.name,
587 exposures=[exposure],
588 )
590 def getVisitSystem(self) -> Tuple[int, str]:
591 # Docstring inherited from GroupExposuresTask.
592 return (self.config.visitSystemId, self.config.visitSystemName)
595class _GroupExposuresByGroupMetadataConfig(GroupExposuresConfig):
596 visitSystemId = Field(
597 doc=("Integer ID of the visit_system implemented by this grouping "
598 "algorithm."),
599 dtype=int,
600 default=1,
601 )
602 visitSystemName = Field(
603 doc=("String name of the visit_system implemented by this grouping "
604 "algorithm."),
605 dtype=str,
606 default="by-group-metadata",
607 )
610@registerConfigurable("by-group-metadata", GroupExposuresTask.registry)
611class _GroupExposuresByGroupMetadataTask(GroupExposuresTask, metaclass=ABCMeta):
612 """An exposure grouping algorithm that uses exposure.group_name and
613 exposure.group_id.
615 This algorithm _assumes_ exposure.group_id (generally populated from
616 `astro_metadata_translator.ObservationInfo.visit_id`) is not just unique,
617 but disjoint from all `ObservationInfo.exposure_id` values - if it isn't,
618 it will be impossible to ever use both this grouping algorithm and the
619 one-to-one algorithm for a particular camera in the same data repository.
620 """
622 ConfigClass = _GroupExposuresByGroupMetadataConfig
624 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]:
625 # Docstring inherited from GroupExposuresTask.
626 groups = defaultdict(list)
627 for exposure in exposures:
628 groups[exposure.group_name].append(exposure)
629 for visitName, exposuresInGroup in groups.items():
630 instrument = exposuresInGroup[0].instrument
631 visitId = exposuresInGroup[0].group_id
632 assert all(e.group_id == visitId for e in exposuresInGroup), \
633 "Grouping by exposure.group_name does not yield consistent group IDs"
634 yield VisitDefinitionData(instrument=instrument, id=visitId, name=visitName,
635 exposures=exposuresInGroup)
637 def getVisitSystem(self) -> Tuple[int, str]:
638 # Docstring inherited from GroupExposuresTask.
639 return (self.config.visitSystemId, self.config.visitSystemName)
642class _ComputeVisitRegionsFromSingleRawWcsConfig(ComputeVisitRegionsConfig):
643 mergeExposures = Field(
644 doc=("If True, merge per-detector regions over all exposures in a "
645 "visit (via convex hull) instead of using the first exposure and "
646 "assuming its regions are valid for all others."),
647 dtype=bool,
648 default=False,
649 )
650 detectorId = Field(
651 doc=("Load the WCS for the detector with this ID. If None, use an "
652 "arbitrary detector (the first found in a query of the data "
653 "repository for each exposure (or all exposures, if "
654 "mergeExposures is True)."),
655 dtype=int,
656 optional=True,
657 default=None
658 )
659 requireVersionedCamera = Field(
660 doc=("If True, raise LookupError if version camera geometry cannot be "
661 "loaded for an exposure. If False, use the nominal camera from "
662 "the Instrument class instead."),
663 dtype=bool,
664 optional=False,
665 default=False,
666 )
669@registerConfigurable("single-raw-wcs", ComputeVisitRegionsTask.registry)
670class _ComputeVisitRegionsFromSingleRawWcsTask(ComputeVisitRegionsTask):
671 """A visit region calculator that uses a single raw WCS and a camera to
672 project the bounding boxes of all detectors onto the sky, relating
673 different detectors by their positions in focal plane coordinates.
675 Notes
676 -----
677 Most instruments should have their raw WCSs determined from a combination
678 of boresight angle, rotator angle, and camera geometry, and hence this
679 algorithm should produce stable results regardless of which detector the
680 raw corresponds to. If this is not the case (e.g. because a per-file FITS
681 WCS is used instead), either the ID of the detector should be fixed (see
682 the ``detectorId`` config parameter) or a different algorithm used.
683 """
685 ConfigClass = _ComputeVisitRegionsFromSingleRawWcsConfig
687 def computeExposureBounds(self, exposure: DimensionRecord, *, collections: Any = None
688 ) -> Dict[int, List[UnitVector3d]]:
689 """Compute the lists of unit vectors on the sphere that correspond to
690 the sky positions of detector corners.
692 Parameters
693 ----------
694 exposure : `DimensionRecord`
695 Dimension record for the exposure.
696 collections : Any, optional
697 Collections to be searched for raws and camera geometry, overriding
698 ``self.butler.collections``.
699 Can be any of the types supported by the ``collections`` argument
700 to butler construction.
702 Returns
703 -------
704 bounds : `dict`
705 Dictionary mapping detector ID to a list of unit vectors on the
706 sphere representing that detector's corners projected onto the sky.
707 """
708 if collections is None:
709 collections = self.butler.collections
710 camera, versioned = loadCamera(self.butler, exposure.dataId, collections=collections)
711 if not versioned and self.config.requireVersionedCamera:
712 raise LookupError(f"No versioned camera found for exposure {exposure.dataId}.")
714 # Derive WCS from boresight information -- if available in registry
715 use_registry = True
716 try:
717 orientation = lsst.geom.Angle(exposure.sky_angle, lsst.geom.degrees)
718 radec = lsst.geom.SpherePoint(lsst.geom.Angle(exposure.tracking_ra, lsst.geom.degrees),
719 lsst.geom.Angle(exposure.tracking_dec, lsst.geom.degrees))
720 except AttributeError:
721 use_registry = False
723 if use_registry:
724 if self.config.detectorId is None:
725 detectorId = next(camera.getIdIter())
726 else:
727 detectorId = self.config.detectorId
728 wcsDetector = camera[detectorId]
730 # Ask the raw formatter to create the relevant WCS
731 # This allows flips to be taken into account
732 instrument = self.getInstrument(exposure.instrument)
733 rawFormatter = instrument.getRawFormatter({"detector": detectorId})
734 wcs = rawFormatter.makeRawSkyWcsFromBoresight(radec, orientation, wcsDetector)
736 else:
737 if self.config.detectorId is None:
738 wcsRefsIter = self.butler.registry.queryDatasets("raw.wcs", dataId=exposure.dataId,
739 collections=collections)
740 if not wcsRefsIter:
741 raise LookupError(f"No raw.wcs datasets found for data ID {exposure.dataId} "
742 f"in collections {collections}.")
743 wcsRef = next(iter(wcsRefsIter))
744 wcsDetector = camera[wcsRef.dataId["detector"]]
745 wcs = self.butler.getDirect(wcsRef)
746 else:
747 wcsDetector = camera[self.config.detectorId]
748 wcs = self.butler.get("raw.wcs", dataId=exposure.dataId, detector=self.config.detectorId,
749 collections=collections)
750 fpToSky = wcsDetector.getTransform(FOCAL_PLANE, PIXELS).then(wcs.getTransform())
751 bounds = {}
752 for detector in camera:
753 pixelsToSky = detector.getTransform(PIXELS, FOCAL_PLANE).then(fpToSky)
754 pixCorners = Box2D(detector.getBBox().dilatedBy(self.config.padding)).getCorners()
755 bounds[detector.getId()] = [
756 skyCorner.getVector() for skyCorner in pixelsToSky.applyForward(pixCorners)
757 ]
758 return bounds
760 def compute(self, visit: VisitDefinitionData, *, collections: Any = None
761 ) -> Tuple[Region, Dict[int, Region]]:
762 # Docstring inherited from ComputeVisitRegionsTask.
763 if self.config.mergeExposures:
764 detectorBounds = defaultdict(list)
765 for exposure in visit.exposures:
766 exposureDetectorBounds = self.computeExposureBounds(exposure, collections=collections)
767 for detectorId, bounds in exposureDetectorBounds.items():
768 detectorBounds[detectorId].extend(bounds)
769 else:
770 detectorBounds = self.computeExposureBounds(visit.exposures[0], collections=collections)
771 visitBounds = []
772 detectorRegions = {}
773 for detectorId, bounds in detectorBounds.items():
774 detectorRegions[detectorId] = ConvexPolygon.convexHull(bounds)
775 visitBounds.extend(bounds)
776 return ConvexPolygon.convexHull(visitBounds), detectorRegions