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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 Progress,
46 Timespan,
47)
49import lsst.geom
50from lsst.geom import Box2D
51from lsst.pex.config import Config, Field, makeRegistry, registerConfigurable
52from lsst.afw.cameraGeom import FOCAL_PLANE, PIXELS
53from lsst.pipe.base import Task
54from lsst.sphgeom import ConvexPolygon, Region, UnitVector3d
55from ._instrument import loadCamera, Instrument
58@dataclasses.dataclass
59class VisitDefinitionData:
60 """Struct representing a group of exposures that will be used to define a
61 visit.
62 """
64 instrument: str
65 """Name of the instrument this visit will be associated with.
66 """
68 id: int
69 """Integer ID of the visit.
71 This must be unique across all visit systems for the instrument.
72 """
74 name: str
75 """String name for the visit.
77 This must be unique across all visit systems for the instrument.
78 """
80 exposures: List[DimensionRecord] = dataclasses.field(default_factory=list)
81 """Dimension records for the exposures that are part of this visit.
82 """
85@dataclasses.dataclass
86class _VisitRecords:
87 """Struct containing the dimension records associated with a visit.
88 """
90 visit: DimensionRecord
91 """Record for the 'visit' dimension itself.
92 """
94 visit_definition: List[DimensionRecord]
95 """Records for 'visit_definition', which relates 'visit' to 'exposure'.
96 """
98 visit_detector_region: List[DimensionRecord]
99 """Records for 'visit_detector_region', which associates the combination
100 of a 'visit' and a 'detector' with a region on the sky.
101 """
104class GroupExposuresConfig(Config):
105 pass
108class GroupExposuresTask(Task, metaclass=ABCMeta):
109 """Abstract base class for the subtask of `DefineVisitsTask` that is
110 responsible for grouping exposures into visits.
112 Subclasses should be registered with `GroupExposuresTask.registry` to
113 enable use by `DefineVisitsTask`, and should generally correspond to a
114 particular 'visit_system' dimension value. They are also responsible for
115 defining visit IDs and names that are unique across all visit systems in
116 use by an instrument.
118 Parameters
119 ----------
120 config : `GroupExposuresConfig`
121 Configuration information.
122 **kwargs
123 Additional keyword arguments forwarded to the `Task` constructor.
124 """
125 def __init__(self, config: GroupExposuresConfig, **kwargs: Any):
126 Task.__init__(self, config=config, **kwargs)
128 ConfigClass = GroupExposuresConfig
130 _DefaultName = "groupExposures"
132 registry = makeRegistry(
133 doc="Registry of algorithms for grouping exposures into visits.",
134 configBaseType=GroupExposuresConfig,
135 )
137 @abstractmethod
138 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]:
139 """Group the given exposures into visits.
141 Parameters
142 ----------
143 exposures : `list` [ `DimensionRecord` ]
144 DimensionRecords (for the 'exposure' dimension) describing the
145 exposures to group.
147 Returns
148 -------
149 visits : `Iterable` [ `VisitDefinitionData` ]
150 Structs identifying the visits and the exposures associated with
151 them. This may be an iterator or a container.
152 """
153 raise NotImplementedError()
155 @abstractmethod
156 def getVisitSystem(self) -> Tuple[int, str]:
157 """Return identifiers for the 'visit_system' dimension this
158 algorithm implements.
160 Returns
161 -------
162 id : `int`
163 Integer ID for the visit system (given an instrument).
164 name : `str`
165 Unique string identifier for the visit system (given an
166 instrument).
167 """
168 raise NotImplementedError()
171class ComputeVisitRegionsConfig(Config):
172 padding = Field(
173 dtype=int,
174 default=250,
175 doc=("Pad raw image bounding boxes with specified number of pixels "
176 "when calculating their (conservatively large) region on the "
177 "sky. Note that the config value for pixelMargin of the "
178 "reference object loaders in meas_algorithms should be <= "
179 "the value set here."),
180 )
183class ComputeVisitRegionsTask(Task, metaclass=ABCMeta):
184 """Abstract base class for the subtask of `DefineVisitsTask` that is
185 responsible for extracting spatial regions for visits and visit+detector
186 combinations.
188 Subclasses should be registered with `ComputeVisitRegionsTask.registry` to
189 enable use by `DefineVisitsTask`.
191 Parameters
192 ----------
193 config : `ComputeVisitRegionsConfig`
194 Configuration information.
195 butler : `lsst.daf.butler.Butler`
196 The butler to use.
197 **kwargs
198 Additional keyword arguments forwarded to the `Task` constructor.
199 """
200 def __init__(self, config: ComputeVisitRegionsConfig, *, butler: Butler, **kwargs: Any):
201 Task.__init__(self, config=config, **kwargs)
202 self.butler = butler
203 self.instrumentMap = {}
205 ConfigClass = ComputeVisitRegionsConfig
207 _DefaultName = "computeVisitRegions"
209 registry = makeRegistry(
210 doc=("Registry of algorithms for computing on-sky regions for visits "
211 "and visit+detector combinations."),
212 configBaseType=ComputeVisitRegionsConfig,
213 )
215 def getInstrument(self, instrumentName) -> Instrument:
216 """Retrieve an `~lsst.obs.base.Instrument` associated with this
217 instrument name.
219 Parameters
220 ----------
221 instrumentName : `str`
222 The name of the instrument.
224 Returns
225 -------
226 instrument : `~lsst.obs.base.Instrument`
227 The associated instrument object.
229 Notes
230 -----
231 The result is cached.
232 """
233 instrument = self.instrumentMap.get(instrumentName)
234 if instrument is None:
235 instrument = Instrument.fromName(instrumentName, self.butler.registry)
236 self.instrumentMap[instrumentName] = instrument
237 return instrument
239 @abstractmethod
240 def compute(self, visit: VisitDefinitionData, *, collections: Any = None
241 ) -> Tuple[Region, Dict[int, Region]]:
242 """Compute regions for the given visit and all detectors in that visit.
244 Parameters
245 ----------
246 visit : `VisitDefinitionData`
247 Struct describing the visit and the exposures associated with it.
248 collections : Any, optional
249 Collections to be searched for raws and camera geometry, overriding
250 ``self.butler.collections``.
251 Can be any of the types supported by the ``collections`` argument
252 to butler construction.
254 Returns
255 -------
256 visitRegion : `lsst.sphgeom.Region`
257 Region for the full visit.
258 visitDetectorRegions : `dict` [ `int`, `lsst.sphgeom.Region` ]
259 Dictionary mapping detector ID to the region for that detector.
260 Should include all detectors in the visit.
261 """
262 raise NotImplementedError()
265class DefineVisitsConfig(Config):
266 groupExposures = GroupExposuresTask.registry.makeField(
267 doc="Algorithm for grouping exposures into visits.",
268 default="one-to-one",
269 )
270 computeVisitRegions = ComputeVisitRegionsTask.registry.makeField(
271 doc="Algorithm from computing visit and visit+detector regions.",
272 default="single-raw-wcs",
273 )
274 ignoreNonScienceExposures = Field(
275 doc=("If True, silently ignore input exposures that do not have "
276 "observation_type=SCIENCE. If False, raise an exception if one "
277 "encountered."),
278 dtype=bool,
279 optional=False,
280 default=True,
281 )
284class DefineVisitsTask(Task):
285 """Driver Task for defining visits (and their spatial regions) in Gen3
286 Butler repositories.
288 Parameters
289 ----------
290 config : `DefineVisitsConfig`
291 Configuration for the task.
292 butler : `~lsst.daf.butler.Butler`
293 Writeable butler instance. Will be used to read `raw.wcs` and `camera`
294 datasets and insert/sync dimension data.
295 **kwargs
296 Additional keyword arguments are forwarded to the `lsst.pipe.base.Task`
297 constructor.
299 Notes
300 -----
301 Each instance of `DefineVisitsTask` reads from / writes to the same Butler.
302 Each invocation of `DefineVisitsTask.run` processes an independent group of
303 exposures into one or more new vists, all belonging to the same visit
304 system and instrument.
306 The actual work of grouping exposures and computing regions is delegated
307 to pluggable subtasks (`GroupExposuresTask` and `ComputeVisitRegionsTask`),
308 respectively. The defaults are to create one visit for every exposure,
309 and to use exactly one (arbitrary) detector-level raw dataset's WCS along
310 with camera geometry to compute regions for all detectors. Other
311 implementations can be created and configured for instruments for which
312 these choices are unsuitable (e.g. because visits and exposures are not
313 one-to-one, or because ``raw.wcs`` datasets for different detectors may not
314 be consistent with camera geomery).
316 It is not necessary in general to ingest all raws for an exposure before
317 defining a visit that includes the exposure; this depends entirely on the
318 `ComputeVisitRegionTask` subclass used. For the default configuration,
319 a single raw for each exposure is sufficient.
321 Defining the same visit the same way multiple times (e.g. via multiple
322 invocations of this task on the same exposures, with the same
323 configuration) is safe, but it may be inefficient, as most of the work must
324 be done before new visits can be compared to existing visits.
325 """
326 def __init__(self, config: Optional[DefineVisitsConfig] = None, *, butler: Butler, **kwargs: Any):
327 config.validate() # Not a CmdlineTask nor PipelineTask, so have to validate the config here.
328 super().__init__(config, **kwargs)
329 self.butler = butler
330 self.universe = self.butler.registry.dimensions
331 self.progress = Progress("obs.base.DefineVisitsTask")
332 self.makeSubtask("groupExposures")
333 self.makeSubtask("computeVisitRegions", butler=self.butler)
335 def _reduce_kwargs(self):
336 # Add extra parameters to pickle
337 return dict(**super()._reduce_kwargs(), butler=self.butler)
339 ConfigClass = DefineVisitsConfig
341 _DefaultName = "defineVisits"
343 def _buildVisitRecords(self, definition: VisitDefinitionData, *,
344 collections: Any = None) -> _VisitRecords:
345 """Build the DimensionRecords associated with a visit.
347 Parameters
348 ----------
349 definition : `VisitDefinition`
350 Struct with identifiers for the visit and records for its
351 constituent exposures.
352 collections : Any, optional
353 Collections to be searched for raws and camera geometry, overriding
354 ``self.butler.collections``.
355 Can be any of the types supported by the ``collections`` argument
356 to butler construction.
358 Results
359 -------
360 records : `_VisitRecords`
361 Struct containing DimensionRecords for the visit, including
362 associated dimension elements.
363 """
364 # Compute all regions.
365 visitRegion, visitDetectorRegions = self.computeVisitRegions.compute(definition,
366 collections=collections)
367 # Aggregate other exposure quantities.
368 timespan = Timespan(
369 begin=_reduceOrNone(min, (e.timespan.begin for e in definition.exposures)),
370 end=_reduceOrNone(max, (e.timespan.end for e in definition.exposures)),
371 )
372 exposure_time = _reduceOrNone(sum, (e.exposure_time for e in definition.exposures))
373 physical_filter = _reduceOrNone(lambda a, b: a if a == b else None,
374 (e.physical_filter for e in definition.exposures))
375 target_name = _reduceOrNone(lambda a, b: a if a == b else None,
376 (e.target_name for e in definition.exposures))
377 science_program = _reduceOrNone(lambda a, b: a if a == b else None,
378 (e.science_program for e in definition.exposures))
380 # observing day for a visit is defined by the earliest observation
381 # of the visit
382 observing_day = _reduceOrNone(min, (e.day_obs for e in definition.exposures))
383 observation_reason = _reduceOrNone(lambda a, b: a if a == b else None,
384 (e.observation_reason for e in definition.exposures))
385 if observation_reason is None:
386 # Be explicit about there being multiple reasons
387 observation_reason = "various"
389 # Use the mean zenith angle as an approximation
390 zenith_angle = _reduceOrNone(sum, (e.zenith_angle for e in definition.exposures))
391 if zenith_angle is not None:
392 zenith_angle /= len(definition.exposures)
394 # Construct the actual DimensionRecords.
395 return _VisitRecords(
396 visit=self.universe["visit"].RecordClass(
397 instrument=definition.instrument,
398 id=definition.id,
399 name=definition.name,
400 physical_filter=physical_filter,
401 target_name=target_name,
402 science_program=science_program,
403 observation_reason=observation_reason,
404 day_obs=observing_day,
405 zenith_angle=zenith_angle,
406 visit_system=self.groupExposures.getVisitSystem()[0],
407 exposure_time=exposure_time,
408 timespan=timespan,
409 region=visitRegion,
410 # TODO: no seeing value in exposure dimension records, so we
411 # can't set that here. But there are many other columns that
412 # both dimensions should probably have as well.
413 ),
414 visit_definition=[
415 self.universe["visit_definition"].RecordClass(
416 instrument=definition.instrument,
417 visit=definition.id,
418 exposure=exposure.id,
419 visit_system=self.groupExposures.getVisitSystem()[0],
420 )
421 for exposure in definition.exposures
422 ],
423 visit_detector_region=[
424 self.universe["visit_detector_region"].RecordClass(
425 instrument=definition.instrument,
426 visit=definition.id,
427 detector=detectorId,
428 region=detectorRegion,
429 )
430 for detectorId, detectorRegion in visitDetectorRegions.items()
431 ]
432 )
434 def _expandExposureId(self, dataId: DataId) -> DataCoordinate:
435 """Return the expanded version of an exposure ID.
437 A private method to allow ID expansion in a pool without resorting
438 to local callables.
440 Parameters
441 ----------
442 dataId : `dict` or `DataCoordinate`
443 Exposure-level data ID.
445 Returns
446 -------
447 expanded : `DataCoordinate`
448 A data ID that includes full metadata for all exposure dimensions.
449 """
450 dimensions = DimensionGraph(self.universe, names=["exposure"])
451 return self.butler.registry.expandDataId(dataId, graph=dimensions)
453 def _buildVisitRecordsSingle(self, args) -> _VisitRecords:
454 """Build the DimensionRecords associated with a visit and collection.
456 A wrapper for `_buildVisitRecords` to allow it to be run as part of
457 a pool without resorting to local callables.
459 Parameters
460 ----------
461 args : `tuple` [`VisitDefinition`, any]
462 A tuple consisting of the ``definition`` and ``collections``
463 arguments to `_buildVisitRecords`, in that order.
465 Results
466 -------
467 records : `_VisitRecords`
468 Struct containing DimensionRecords for the visit, including
469 associated dimension elements.
470 """
471 return self._buildVisitRecords(args[0], collections=args[1])
473 def run(self, dataIds: Iterable[DataId], *,
474 pool: Optional[Pool] = None,
475 processes: int = 1,
476 collections: Optional[str] = None,
477 update_records: bool = False):
478 """Add visit definitions to the registry for the given exposures.
480 Parameters
481 ----------
482 dataIds : `Iterable` [ `dict` or `DataCoordinate` ]
483 Exposure-level data IDs. These must all correspond to the same
484 instrument, and are expected to be on-sky science exposures.
485 pool : `multiprocessing.Pool`, optional
486 If not `None`, a process pool with which to parallelize some
487 operations.
488 processes : `int`, optional
489 The number of processes to use. Ignored if ``pool`` is not `None`.
490 collections : Any, optional
491 Collections to be searched for raws and camera geometry, overriding
492 ``self.butler.collections``.
493 Can be any of the types supported by the ``collections`` argument
494 to butler construction.
495 update_records : `bool`, optional
496 If `True` (`False` is default), update existing visit records that
497 conflict with the new ones instead of rejecting them (and when this
498 occurs, update visit_detector_region as well). THIS IS AN ADVANCED
499 OPTION THAT SHOULD ONLY BE USED TO FIX REGIONS AND/OR METADATA THAT
500 ARE KNOWN TO BE BAD, AND IT CANNOT BE USED TO REMOVE EXPOSURES OR
501 DETECTORS FROM A VISIT.
503 Raises
504 ------
505 lsst.daf.butler.registry.ConflictingDefinitionError
506 Raised if a visit ID conflict is detected and the existing visit
507 differs from the new one.
508 """
509 # Set up multiprocessing, if desired.
510 if pool is None and processes > 1:
511 pool = Pool(processes)
512 mapFunc = map if pool is None else pool.imap_unordered
513 # Normalize, expand, and deduplicate data IDs.
514 self.log.info("Preprocessing data IDs.")
515 dataIds = set(mapFunc(self._expandExposureId, dataIds))
516 if not dataIds:
517 raise RuntimeError("No exposures given.")
518 # Extract exposure DimensionRecords, check that there's only one
519 # instrument in play, and check for non-science exposures.
520 exposures = []
521 instruments = set()
522 for dataId in dataIds:
523 record = dataId.records["exposure"]
524 if record.observation_type != "science":
525 if self.config.ignoreNonScienceExposures:
526 continue
527 else:
528 raise RuntimeError(f"Input exposure {dataId} has observation_type "
529 f"{record.observation_type}, not 'science'.")
530 instruments.add(dataId["instrument"])
531 exposures.append(record)
532 if not exposures:
533 self.log.info("No science exposures found after filtering.")
534 return
535 if len(instruments) > 1:
536 raise RuntimeError(
537 f"All data IDs passed to DefineVisitsTask.run must be "
538 f"from the same instrument; got {instruments}."
539 )
540 instrument, = instruments
541 # Ensure the visit_system our grouping algorithm uses is in the
542 # registry, if it wasn't already.
543 visitSystemId, visitSystemName = self.groupExposures.getVisitSystem()
544 self.log.info("Registering visit_system %d: %s.", visitSystemId, visitSystemName)
545 self.butler.registry.syncDimensionData(
546 "visit_system",
547 {"instrument": instrument, "id": visitSystemId, "name": visitSystemName}
548 )
549 # Group exposures into visits, delegating to subtask.
550 self.log.info("Grouping %d exposure(s) into visits.", len(exposures))
551 definitions = list(self.groupExposures.group(exposures))
552 # Compute regions and build DimensionRecords for each visit.
553 # This is the only parallel step, but it _should_ be the most expensive
554 # one (unless DB operations are slow).
555 self.log.info("Computing regions and other metadata for %d visit(s).", len(definitions))
556 allRecords = mapFunc(self._buildVisitRecordsSingle,
557 zip(definitions, itertools.repeat(collections)))
558 # Iterate over visits and insert dimension data, one transaction per
559 # visit. If a visit already exists, we skip all other inserts.
560 for visitRecords in self.progress.wrap(allRecords, total=len(definitions),
561 desc="Computing regions and inserting visits"):
562 with self.butler.registry.transaction():
563 inserted_or_updated = self.butler.registry.syncDimensionData(
564 "visit",
565 visitRecords.visit,
566 update=update_records,
567 )
568 if inserted_or_updated:
569 if inserted_or_updated is True:
570 # This is a new visit, not an update to an existing
571 # one, so insert visit definition.
572 # We don't allow visit definitions to change even when
573 # asked to update, because we'd have to delete the old
574 # visit_definitions first and also worry about what
575 # this does to datasets that already use the visit.
576 self.butler.registry.insertDimensionData("visit_definition",
577 *visitRecords.visit_definition)
578 # [Re]Insert visit_detector_region records for both inserts
579 # and updates, because we do allow updating to affect the
580 # region calculations.
581 self.butler.registry.insertDimensionData("visit_detector_region",
582 *visitRecords.visit_detector_region,
583 replace=update_records)
586def _reduceOrNone(func, iterable):
587 """Apply a binary function to pairs of elements in an iterable until a
588 single value is returned, but return `None` if any element is `None` or
589 there are no elements.
590 """
591 r = None
592 for v in iterable:
593 if v is None:
594 return None
595 if r is None:
596 r = v
597 else:
598 r = func(r, v)
599 return r
602class _GroupExposuresOneToOneConfig(GroupExposuresConfig):
603 visitSystemId = Field(
604 doc=("Integer ID of the visit_system implemented by this grouping "
605 "algorithm."),
606 dtype=int,
607 default=0,
608 )
609 visitSystemName = Field(
610 doc=("String name of the visit_system implemented by this grouping "
611 "algorithm."),
612 dtype=str,
613 default="one-to-one",
614 )
617@registerConfigurable("one-to-one", GroupExposuresTask.registry)
618class _GroupExposuresOneToOneTask(GroupExposuresTask, metaclass=ABCMeta):
619 """An exposure grouping algorithm that simply defines one visit for each
620 exposure, reusing the exposures identifiers for the visit.
621 """
623 ConfigClass = _GroupExposuresOneToOneConfig
625 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]:
626 # Docstring inherited from GroupExposuresTask.
627 for exposure in exposures:
628 yield VisitDefinitionData(
629 instrument=exposure.instrument,
630 id=exposure.id,
631 name=exposure.obs_id,
632 exposures=[exposure],
633 )
635 def getVisitSystem(self) -> Tuple[int, str]:
636 # Docstring inherited from GroupExposuresTask.
637 return (self.config.visitSystemId, self.config.visitSystemName)
640class _GroupExposuresByGroupMetadataConfig(GroupExposuresConfig):
641 visitSystemId = Field(
642 doc=("Integer ID of the visit_system implemented by this grouping "
643 "algorithm."),
644 dtype=int,
645 default=1,
646 )
647 visitSystemName = Field(
648 doc=("String name of the visit_system implemented by this grouping "
649 "algorithm."),
650 dtype=str,
651 default="by-group-metadata",
652 )
655@registerConfigurable("by-group-metadata", GroupExposuresTask.registry)
656class _GroupExposuresByGroupMetadataTask(GroupExposuresTask, metaclass=ABCMeta):
657 """An exposure grouping algorithm that uses exposure.group_name and
658 exposure.group_id.
660 This algorithm _assumes_ exposure.group_id (generally populated from
661 `astro_metadata_translator.ObservationInfo.visit_id`) is not just unique,
662 but disjoint from all `ObservationInfo.exposure_id` values - if it isn't,
663 it will be impossible to ever use both this grouping algorithm and the
664 one-to-one algorithm for a particular camera in the same data repository.
665 """
667 ConfigClass = _GroupExposuresByGroupMetadataConfig
669 def group(self, exposures: List[DimensionRecord]) -> Iterable[VisitDefinitionData]:
670 # Docstring inherited from GroupExposuresTask.
671 groups = defaultdict(list)
672 for exposure in exposures:
673 groups[exposure.group_name].append(exposure)
674 for visitName, exposuresInGroup in groups.items():
675 instrument = exposuresInGroup[0].instrument
676 visitId = exposuresInGroup[0].group_id
677 assert all(e.group_id == visitId for e in exposuresInGroup), \
678 "Grouping by exposure.group_name does not yield consistent group IDs"
679 yield VisitDefinitionData(instrument=instrument, id=visitId, name=visitName,
680 exposures=exposuresInGroup)
682 def getVisitSystem(self) -> Tuple[int, str]:
683 # Docstring inherited from GroupExposuresTask.
684 return (self.config.visitSystemId, self.config.visitSystemName)
687class _ComputeVisitRegionsFromSingleRawWcsConfig(ComputeVisitRegionsConfig):
688 mergeExposures = Field(
689 doc=("If True, merge per-detector regions over all exposures in a "
690 "visit (via convex hull) instead of using the first exposure and "
691 "assuming its regions are valid for all others."),
692 dtype=bool,
693 default=False,
694 )
695 detectorId = Field(
696 doc=("Load the WCS for the detector with this ID. If None, use an "
697 "arbitrary detector (the first found in a query of the data "
698 "repository for each exposure (or all exposures, if "
699 "mergeExposures is True)."),
700 dtype=int,
701 optional=True,
702 default=None
703 )
704 requireVersionedCamera = Field(
705 doc=("If True, raise LookupError if version camera geometry cannot be "
706 "loaded for an exposure. If False, use the nominal camera from "
707 "the Instrument class instead."),
708 dtype=bool,
709 optional=False,
710 default=False,
711 )
714@registerConfigurable("single-raw-wcs", ComputeVisitRegionsTask.registry)
715class _ComputeVisitRegionsFromSingleRawWcsTask(ComputeVisitRegionsTask):
716 """A visit region calculator that uses a single raw WCS and a camera to
717 project the bounding boxes of all detectors onto the sky, relating
718 different detectors by their positions in focal plane coordinates.
720 Notes
721 -----
722 Most instruments should have their raw WCSs determined from a combination
723 of boresight angle, rotator angle, and camera geometry, and hence this
724 algorithm should produce stable results regardless of which detector the
725 raw corresponds to. If this is not the case (e.g. because a per-file FITS
726 WCS is used instead), either the ID of the detector should be fixed (see
727 the ``detectorId`` config parameter) or a different algorithm used.
728 """
730 ConfigClass = _ComputeVisitRegionsFromSingleRawWcsConfig
732 def computeExposureBounds(self, exposure: DimensionRecord, *, collections: Any = None
733 ) -> Dict[int, List[UnitVector3d]]:
734 """Compute the lists of unit vectors on the sphere that correspond to
735 the sky positions of detector corners.
737 Parameters
738 ----------
739 exposure : `DimensionRecord`
740 Dimension record for the exposure.
741 collections : Any, optional
742 Collections to be searched for raws and camera geometry, overriding
743 ``self.butler.collections``.
744 Can be any of the types supported by the ``collections`` argument
745 to butler construction.
747 Returns
748 -------
749 bounds : `dict`
750 Dictionary mapping detector ID to a list of unit vectors on the
751 sphere representing that detector's corners projected onto the sky.
752 """
753 if collections is None:
754 collections = self.butler.collections
755 camera, versioned = loadCamera(self.butler, exposure.dataId, collections=collections)
756 if not versioned and self.config.requireVersionedCamera:
757 raise LookupError(f"No versioned camera found for exposure {exposure.dataId}.")
759 # Derive WCS from boresight information -- if available in registry
760 use_registry = True
761 try:
762 orientation = lsst.geom.Angle(exposure.sky_angle, lsst.geom.degrees)
763 radec = lsst.geom.SpherePoint(lsst.geom.Angle(exposure.tracking_ra, lsst.geom.degrees),
764 lsst.geom.Angle(exposure.tracking_dec, lsst.geom.degrees))
765 except AttributeError:
766 use_registry = False
768 if use_registry:
769 if self.config.detectorId is None:
770 detectorId = next(camera.getIdIter())
771 else:
772 detectorId = self.config.detectorId
773 wcsDetector = camera[detectorId]
775 # Ask the raw formatter to create the relevant WCS
776 # This allows flips to be taken into account
777 instrument = self.getInstrument(exposure.instrument)
778 rawFormatter = instrument.getRawFormatter({"detector": detectorId})
779 wcs = rawFormatter.makeRawSkyWcsFromBoresight(radec, orientation, wcsDetector)
781 else:
782 if self.config.detectorId is None:
783 wcsRefsIter = self.butler.registry.queryDatasets("raw.wcs", dataId=exposure.dataId,
784 collections=collections)
785 if not wcsRefsIter:
786 raise LookupError(f"No raw.wcs datasets found for data ID {exposure.dataId} "
787 f"in collections {collections}.")
788 wcsRef = next(iter(wcsRefsIter))
789 wcsDetector = camera[wcsRef.dataId["detector"]]
790 wcs = self.butler.getDirect(wcsRef)
791 else:
792 wcsDetector = camera[self.config.detectorId]
793 wcs = self.butler.get("raw.wcs", dataId=exposure.dataId, detector=self.config.detectorId,
794 collections=collections)
795 fpToSky = wcsDetector.getTransform(FOCAL_PLANE, PIXELS).then(wcs.getTransform())
796 bounds = {}
797 for detector in camera:
798 pixelsToSky = detector.getTransform(PIXELS, FOCAL_PLANE).then(fpToSky)
799 pixCorners = Box2D(detector.getBBox().dilatedBy(self.config.padding)).getCorners()
800 bounds[detector.getId()] = [
801 skyCorner.getVector() for skyCorner in pixelsToSky.applyForward(pixCorners)
802 ]
803 return bounds
805 def compute(self, visit: VisitDefinitionData, *, collections: Any = None
806 ) -> Tuple[Region, Dict[int, Region]]:
807 # Docstring inherited from ComputeVisitRegionsTask.
808 if self.config.mergeExposures:
809 detectorBounds = defaultdict(list)
810 for exposure in visit.exposures:
811 exposureDetectorBounds = self.computeExposureBounds(exposure, collections=collections)
812 for detectorId, bounds in exposureDetectorBounds.items():
813 detectorBounds[detectorId].extend(bounds)
814 else:
815 detectorBounds = self.computeExposureBounds(visit.exposures[0], collections=collections)
816 visitBounds = []
817 detectorRegions = {}
818 for detectorId, bounds in detectorBounds.items():
819 detectorRegions[detectorId] = ConvexPolygon.convexHull(bounds)
820 visitBounds.extend(bounds)
821 return ConvexPolygon.convexHull(visitBounds), detectorRegions