Coverage for python / lsst / obs / base / _instrument.py: 22%
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« prev ^ index » next coverage.py v7.13.5, created at 2026-04-23 08:28 +0000
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__ = ("Instrument", "loadCamera", "makeExposureRecordFromObsInfo")
26import logging
27import re
28from abc import abstractmethod
29from collections import defaultdict
30from collections.abc import Sequence, Set
31from functools import lru_cache
32from typing import TYPE_CHECKING, Any, cast
34import astropy.time
36from lsst.afw.cameraGeom import Camera
37from lsst.daf.butler import (
38 Butler,
39 CollectionType,
40 DataCoordinate,
41 DataId,
42 DatasetType,
43 DimensionRecord,
44 DimensionUniverse,
45 Timespan,
46)
47from lsst.daf.butler.registry import DataIdError
48from lsst.pipe.base import Instrument as InstrumentBase
49from lsst.resources import ResourcePath
50from lsst.utils import doImport, getPackageDir
52from ._read_curated_calibs import CuratedCalibration, read_all
54if TYPE_CHECKING:
55 from astro_metadata_translator import MetadataTranslator, ObservationInfo
57 from lsst.daf.butler import Registry
59 from .filters import FilterDefinitionCollection
61_LOG = logging.getLogger(__name__)
63# To be a standard text curated calibration means that we use a
64# standard definition for the corresponding DatasetType.
65StandardCuratedCalibrationDatasetTypes = {
66 "defects": {"dimensions": ("instrument", "detector"), "storageClass": "Defects"},
67 "manual_defects": {"dimensions": ("instrument", "detector"), "storageClass": "Defects"},
68 "qe_curve": {"dimensions": ("instrument", "detector"), "storageClass": "QECurve"},
69 "crosstalk": {"dimensions": ("instrument", "detector"), "storageClass": "CrosstalkCalib"},
70 "linearizer": {"dimensions": ("instrument", "detector"), "storageClass": "Linearizer"},
71 "bfk": {"dimensions": ("instrument", "detector"), "storageClass": "BrighterFatterKernel"},
72 "transmission_optics": {"dimensions": ("instrument",), "storageClass": "TransmissionCurve"},
73 "transmission_filter": {
74 "dimensions": ("instrument", "physical_filter"),
75 "storageClass": "TransmissionCurve",
76 },
77 "transmission_filter_detector": {
78 "dimensions": ("instrument", "detector", "physical_filter"),
79 "storageClass": "TransmissionCurve",
80 },
81 "transmission_sensor": {"dimensions": ("instrument", "detector"), "storageClass": "TransmissionCurve"},
82 "transmission_atmosphere": {"dimensions": ("instrument",), "storageClass": "TransmissionCurve"},
83 "transmission_system": {
84 "dimensions": ("instrument", "detector", "physical_filter"),
85 "storageClass": "TransmissionCurve",
86 },
87}
90class Instrument(InstrumentBase):
91 """Rubin-specified base for instrument-specific logic for the Gen3 Butler.
93 Parameters
94 ----------
95 collection_prefix : `str`, optional
96 Prefix for collection names to use instead of the instrument's own
97 name. This is primarily for use in simulated-data repositories, where
98 the instrument name may not be necessary and/or sufficient to
99 distinguish between collections.
101 Notes
102 -----
103 Concrete instrument subclasses must have the same construction signature as
104 the base class.
105 """
107 policyName: str | None = None
108 """Instrument specific name to use when locating a policy or configuration
109 file in the file system."""
111 obsDataPackage: str | None = None
112 """Name of the package containing the text curated calibration files.
113 Usually a obs _data package. If `None` no curated calibration files
114 will be read. (`str`)"""
116 standardCuratedDatasetTypes: Set[str] = frozenset(StandardCuratedCalibrationDatasetTypes)
117 """The dataset types expected to be obtained from the obsDataPackage.
119 These dataset types are all required to have standard definitions and
120 must be known to the base class. Clearing this list will prevent
121 any of these calibrations from being stored. If a dataset type is not
122 known to a specific instrument it can still be included in this list
123 since the data package is the source of truth. (`set` of `str`)
124 """
126 additionalCuratedDatasetTypes: Set[str] = frozenset()
127 """Curated dataset types specific to this particular instrument that do
128 not follow the standard organization found in obs data packages.
130 These are the instrument-specific dataset types written by
131 `writeAdditionalCuratedCalibrations` in addition to the calibrations
132 found in obs data packages that follow the standard scheme.
133 (`set` of `str`)"""
135 translatorClass: MetadataTranslator | None = None
136 """Class to use when extracting information from metadata. If `None`
137 the metadata extraction system will determine the translator class itself.
138 This class can also be used to calculate the observing day offset in some
139 scenarios.
140 """
142 @property
143 @abstractmethod
144 def filterDefinitions(self) -> FilterDefinitionCollection:
145 """`~lsst.obs.base.FilterDefinitionCollection`, defining the filters
146 for this instrument.
147 """
148 raise NotImplementedError()
150 def __init__(self, collection_prefix: str | None = None):
151 super().__init__(collection_prefix=collection_prefix)
153 @classmethod
154 @lru_cache
155 def getCuratedCalibrationNames(cls) -> frozenset[str]:
156 """Return the names of all the curated calibration dataset types.
158 Returns
159 -------
160 names : `frozenset` of `str`
161 The dataset type names of all curated calibrations. This will
162 include the standard curated calibrations even if the particular
163 instrument does not support them.
165 Notes
166 -----
167 The returned list does not indicate whether a particular dataset
168 is present in the Butler repository, simply that these are the
169 dataset types that are handled by `writeCuratedCalibrations`.
170 """
171 # Camera is a special dataset type that is also handled as a
172 # curated calibration.
173 curated = {"camera"}
175 # Make a cursory attempt to filter out curated dataset types
176 # that are not present for this instrument
177 for datasetTypeName in cls.standardCuratedDatasetTypes:
178 calibPath = cls._getSpecificCuratedCalibrationPath(datasetTypeName)
179 if calibPath is not None:
180 curated.add(datasetTypeName)
182 curated.update(cls.additionalCuratedDatasetTypes)
183 return frozenset(curated)
185 @abstractmethod
186 def getCamera(self) -> Camera:
187 """Retrieve the cameraGeom representation of this instrument.
189 This is a temporary API that should go away once ``obs`` packages have
190 a standardized approach to writing versioned cameras to a Gen3 repo.
191 """
192 raise NotImplementedError()
194 @classmethod
195 @lru_cache
196 def getObsDataPackageDir(cls) -> str | None:
197 """Return the root of the obs data package that provides
198 specializations for this instrument.
200 Returns
201 -------
202 dir : `str` or `None`
203 The root of the relevant obs data package, or `None` if this
204 instrument does not have one.
206 Notes
207 -----
208 This is a less portable version of ``getObsDataPackageRoot``. Please
209 use that method in new code.
210 """
211 if cls.obsDataPackage is None:
212 return None
213 return getPackageDir(cls.obsDataPackage)
215 @classmethod
216 @lru_cache
217 def getObsDataPackageRoot(cls) -> ResourcePath | None:
218 """Return the root of the obs data package that provides
219 specializations for this instrument.
221 Returns
222 -------
223 dir : `lsst.resources.ResourcePath` or `None`
224 The root URI of the file resources of the relevant obs data
225 package, or `None` if this instrument does not have one.
226 """
227 if cls.obsDataPackage is None:
228 return None
229 return ResourcePath(f"eups://{cls.obsDataPackage}/", forceDirectory=True)
231 def _registerFilters(self, registry: Registry, update: bool = False) -> None:
232 """Register the physical and abstract filter Dimension relationships.
233 This should be called in the `register` implementation, within
234 a transaction context manager block.
236 Parameters
237 ----------
238 registry : `lsst.daf.butler.Registry`
239 The registry to add dimensions to.
240 update : `bool`, optional
241 If `True` (`False` is default), update existing records if they
242 differ from the new ones.
243 """
244 for filter in self.filterDefinitions:
245 # fix for undefined abstract filters causing trouble in the
246 # registry:
247 if filter.band is None:
248 band = filter.physical_filter
249 else:
250 band = filter.band
252 registry.syncDimensionData(
253 "physical_filter",
254 {"instrument": self.getName(), "name": filter.physical_filter, "band": band},
255 update=update,
256 )
258 def writeCuratedCalibrations(
259 self, butler: Butler, collection: str | None = None, labels: Sequence[str] = ()
260 ) -> None:
261 """Write human-curated calibration Datasets to the given Butler with
262 the appropriate validity ranges.
264 Parameters
265 ----------
266 butler : `lsst.daf.butler.Butler`
267 Butler to use to store these calibrations.
268 collection : `str`, optional
269 Name to use for the calibration collection that associates all
270 datasets with a validity range. If this collection already exists,
271 it must be a `~lsst.daf.butler.CollectionType.CALIBRATION`
272 collection, and it must not have any datasets that would conflict
273 with those inserted by this method. If `None`, a collection name
274 is worked out automatically from the instrument name and other
275 metadata by calling
276 `~lsst.obs.base.Instrument.makeCalibrationCollectionName`, but this
277 default name may not work well for long-lived repositories unless
278 ``labels`` is also provided (and changed every time curated
279 calibrations are ingested).
280 labels : `collections.abc.Sequence` [ `str` ], optional
281 Extra strings to include in collection names, after concatenating
282 them with the standard collection name delimiter. If provided,
283 these are inserted into the names of the
284 `~lsst.daf.butler.CollectionType.RUN` collections that datasets are
285 inserted directly into, as well the
286 `~lsst.daf.butler.CollectionType.CALIBRATION` collection if it is
287 generated automatically (i.e., if ``collection is None``).
288 Usually this is just the name of the ticket on which the
289 calibration collection is being created.
291 Notes
292 -----
293 Expected to be called from subclasses. The base method calls
294 ``writeCameraGeom``, ``writeStandardTextCuratedCalibrations``,
295 and ``writeAdditionalCuratedCalibrations``.
296 """
297 # Delegate registration of collections (and creating names for them)
298 # to other methods so they can be called independently with the same
299 # preconditions. Collection registration is idempotent, so this is
300 # safe, and while it adds a bit of overhead, as long as it's one
301 # registration attempt per method (not per dataset or dataset type),
302 # that's negligible.
303 self.writeCameraGeom(butler, collection, labels=labels)
304 self.writeStandardTextCuratedCalibrations(butler, collection, labels=labels)
305 self.writeAdditionalCuratedCalibrations(butler, collection, labels=labels)
307 def writeAdditionalCuratedCalibrations(
308 self, butler: Butler, collection: str | None = None, labels: Sequence[str] = ()
309 ) -> None:
310 """Write additional curated calibrations that might be instrument
311 specific and are not part of the standard set.
313 Default implementation does nothing.
315 Parameters
316 ----------
317 butler : `lsst.daf.butler.Butler`
318 Butler to use to store these calibrations.
319 collection : `str`, optional
320 Name to use for the calibration collection that associates all
321 datasets with a validity range. If this collection already exists,
322 it must be a `~lsst.daf.butler.CollectionType.CALIBRATION`
323 collection, and it must not have any datasets that would conflict
324 with those inserted by this method. If `None`, a collection name
325 is worked out automatically from the instrument name and other
326 metadata by calling
327 `~lsst.obs.base.Instrument.makeCalibrationCollectionName`, but this
328 default name may not work well for long-lived repositories unless
329 ``labels`` is also provided (and changed every time curated
330 calibrations are ingested).
331 labels : `collections.abc.Sequence` [ `str` ], optional
332 Extra strings to include in collection names, after concatenating
333 them with the standard collection name delimiter. If provided,
334 these are inserted into the names of the
335 `~lsst.daf.butler.CollectionType.RUN` collections that datasets are
336 inserted directly into, as well the
337 `~lsst.daf.butler.CollectionType.CALIBRATION` collection if it is
338 generated automatically (i.e. if ``collection is None``). Usually
339 this is just the name of the ticket on which the calibration
340 collection is being created.
341 """
342 return
344 def writeCameraGeom(
345 self, butler: Butler, collection: str | None = None, labels: Sequence[str] = ()
346 ) -> None:
347 """Write the default camera geometry to the butler repository and
348 associate it with the appropriate validity range in a calibration
349 collection.
351 Parameters
352 ----------
353 butler : `lsst.daf.butler.Butler`
354 Butler to use to store these calibrations.
355 collection : `str`, optional
356 Name to use for the calibration collection that associates all
357 datasets with a validity range. If this collection already exists,
358 it must be a `~lsst.daf.butler.CollectionType.CALIBRATION`
359 collection, and it must not have any datasets that would conflict
360 with those inserted by this method. If `None`, a collection name
361 is worked out automatically from the instrument name and other
362 metadata by calling
363 `~lsst.obs.base.Instrument.makeCalibrationCollectionName`, but this
364 default name may not work well for long-lived repositories unless
365 ``labels`` is also provided (and changed every time curated
366 calibrations are ingested).
367 labels : `collections.abc.Sequence` [ `str` ], optional
368 Extra strings to include in collection names, after concatenating
369 them with the standard collection name delimiter. If provided,
370 these are inserted into the names of the
371 `~lsst.daf.butler.CollectionType.RUN` collections that datasets are
372 inserted directly into, as well the
373 `~lsst.daf.butler.CollectionType.CALIBRATION` collection if it is
374 generated automatically (i.e. if ``collection is None``). Usually
375 this is just the name of the ticket on which the calibration
376 collection is being created.
377 """
378 if collection is None:
379 collection = self.makeCalibrationCollectionName(*labels)
380 butler.registry.registerCollection(collection, type=CollectionType.CALIBRATION)
381 run = self.makeUnboundedCalibrationRunName(*labels)
382 butler.registry.registerRun(run)
383 datasetType = DatasetType(
384 "camera", ("instrument",), "Camera", isCalibration=True, universe=butler.dimensions
385 )
386 butler.registry.registerDatasetType(datasetType)
387 camera = self.getCamera()
388 ref = butler.put(camera, datasetType, {"instrument": self.getName()}, run=run)
389 butler.registry.certify(collection, [ref], Timespan(begin=None, end=None))
391 def writeStandardTextCuratedCalibrations(
392 self, butler: Butler, collection: str | None = None, labels: Sequence[str] = ()
393 ) -> None:
394 """Write the set of standardized curated text calibrations to
395 the repository.
397 Parameters
398 ----------
399 butler : `lsst.daf.butler.Butler`
400 Butler to receive these calibration datasets.
401 collection : `str`, optional
402 Name to use for the calibration collection that associates all
403 datasets with a validity range. If this collection already exists,
404 it must be a `~lsst.daf.butler.CollectionType.CALIBRATION`
405 collection, and it must not have any datasets that would conflict
406 with those inserted by this method. If `None`, a collection name
407 is worked out automatically from the instrument name and other
408 metadata by calling
409 `~lsst.obs.base.Instrument.makeCalibrationCollectionName`, but this
410 default name may not work well for long-lived repositories unless
411 ``labels`` is also provided (and changed every time curated
412 calibrations are ingested).
413 labels : `collections.abc.Sequence` [ `str` ], optional
414 Extra strings to include in collection names, after concatenating
415 them with the standard collection name delimiter. If provided,
416 these are inserted into the names of the
417 `~lsst.daf.butler.CollectionType.RUN` collections that datasets are
418 inserted directly into, as well the
419 `~lsst.daf.butler.CollectionType.CALIBRATION` collection if it is
420 generated automatically (i.e., if ``collection is None``). Usually
421 this is just the name of the ticket on which the calibration
422 collection is being created.
423 """
424 if collection is None:
425 collection = self.makeCalibrationCollectionName(*labels)
426 butler.registry.registerCollection(collection, type=CollectionType.CALIBRATION)
427 runs: set[str] = set()
428 for datasetTypeName in self.standardCuratedDatasetTypes:
429 # We need to define the dataset types.
430 if datasetTypeName not in StandardCuratedCalibrationDatasetTypes:
431 raise ValueError(
432 f"DatasetType {datasetTypeName} not in understood list"
433 f" [{'.'.join(StandardCuratedCalibrationDatasetTypes)}]"
434 )
435 definition = StandardCuratedCalibrationDatasetTypes[datasetTypeName]
436 datasetType = DatasetType(
437 datasetTypeName,
438 universe=butler.dimensions,
439 isCalibration=True,
440 # MyPy should be able to figure out that the kwargs here have
441 # the right types, but it can't.
442 **definition, # type: ignore
443 )
444 self._writeSpecificCuratedCalibrationDatasets(
445 butler, datasetType, collection, runs=runs, labels=labels
446 )
448 @classmethod
449 def _getSpecificCuratedCalibrationPath(cls, datasetTypeName: str) -> ResourcePath | None:
450 """Return the path of the curated calibration directory.
452 Parameters
453 ----------
454 datasetTypeName : `str`
455 The name of the standard dataset type to find.
457 Returns
458 -------
459 path : `str` or `None`
460 The path to the standard curated data directory. `None` if the
461 dataset type is not found or the obs data package is not
462 available.
463 """
464 data_package_dir = cls.getObsDataPackageRoot()
465 if data_package_dir is None:
466 # if there is no data package then there can't be datasets
467 return None
469 if cls.policyName is None:
470 raise TypeError(f"Instrument {cls.getName()} has an obs data package but no policy name.")
472 calibPath = data_package_dir.join(cls.policyName).join(datasetTypeName, forceDirectory=True)
474 if calibPath.exists():
475 return calibPath
477 return None
479 def _writeSpecificCuratedCalibrationDatasets(
480 self, butler: Butler, datasetType: DatasetType, collection: str, runs: set[str], labels: Sequence[str]
481 ) -> None:
482 """Write standardized curated calibration datasets for this specific
483 dataset type from an obs data package.
485 Parameters
486 ----------
487 butler : `lsst.daf.butler.Butler`
488 Gen3 butler in which to put the calibrations.
489 datasetType : `lsst.daf.butler.DatasetType`
490 Dataset type to be put.
491 collection : `str`
492 Name of the `~lsst.daf.butler.CollectionType.CALIBRATION`
493 collection that associates all datasets with validity ranges.
494 Must have been registered prior to this call.
495 runs : `set` [ `str` ]
496 Names of runs that have already been registered by previous calls
497 and need not be registered again. Should be updated by this
498 method as new runs are registered.
499 labels : `collections.abc.Sequence` [ `str` ]
500 Extra strings to include in run names when creating them from
501 ``CALIBDATE`` metadata, via calls to `makeCuratedCalibrationName`.
502 Usually this is the name of the ticket on which the calibration
503 collection is being created.
505 Notes
506 -----
507 This method scans the location defined in the ``obsDataPackageDir``
508 class attribute for curated calibrations corresponding to the
509 supplied dataset type. The directory name in the data package must
510 match the name of the dataset type. They are assumed to use the
511 standard layout and can be read by
512 `~lsst.obs.base._read_curated_calibs.read_all` and provide standard
513 metadata.
514 """
515 calibPath = self._getSpecificCuratedCalibrationPath(datasetType.name)
516 if calibPath is None:
517 return
519 # Register the dataset type
520 butler.registry.registerDatasetType(datasetType)
521 _LOG.info("Processing %r curated calibration", datasetType.name)
523 # The class to use to read these calibrations comes from the storage
524 # class.
525 calib_class: Any
526 calib_class = datasetType.storageClass.pytype
527 if not hasattr(calib_class, "readText"):
528 # Let's try the default calib class. All curated
529 # calibrations should be subclasses of that, and the
530 # parent can identify the correct one to use.
531 calib_class = doImport("lsst.ip.isr.IsrCalib")
533 calib_class = cast(type[CuratedCalibration], calib_class)
535 # Read calibs, registering a new run for each CALIBDATE as needed.
536 # We try to avoid registering runs multiple times as an optimization
537 # by putting them in the ``runs`` set that was passed in.
538 camera = self.getCamera()
539 filters = set(self.filterDefinitions.physical_to_band.keys())
540 calib_dimensions: list[str]
541 if datasetType.name in StandardCuratedCalibrationDatasetTypes:
542 calib_dimensions = list(StandardCuratedCalibrationDatasetTypes[datasetType.name]["dimensions"])
543 else:
544 # This should never trigger with real data, but will
545 # trigger on the unit tests.
546 _LOG.warning(
547 "Unknown curated calibration type %s. Attempting to use supplied definition.",
548 datasetType.name,
549 )
550 calib_dimensions = list(datasetType.dimensions.names)
552 calibsDict, calib_type = read_all(calibPath, camera, calib_class, calib_dimensions, filters)
554 datasetRecords = []
555 for path in calibsDict:
556 times = sorted(calibsDict[path])
557 calibs = [calibsDict[path][time] for time in times]
558 atimes: list[astropy.time.Time | None] = [
559 astropy.time.Time(t, format="datetime", scale="utc") for t in times
560 ]
561 atimes += [None]
562 for calib, beginTime, endTime in zip(calibs, atimes[:-1], atimes[1:], strict=True):
563 md = calib.getMetadata()
564 run = self.makeCuratedCalibrationRunName(md["CALIBDATE"], *labels)
565 if run not in runs:
566 butler.registry.registerRun(run)
567 runs.add(run)
569 # DETECTOR and FILTER keywords in the calibration
570 # metadata must exist if the calibration depends on
571 # those dimensions.
572 dimension_arguments = {}
573 if "DETECTOR" in md:
574 dimension_arguments["detector"] = md["DETECTOR"]
575 if "FILTER" in md:
576 dimension_arguments["physical_filter"] = md["FILTER"]
578 dataId = DataCoordinate.standardize(
579 universe=butler.dimensions,
580 instrument=self.getName(),
581 **dimension_arguments,
582 )
583 datasetRecords.append((calib, dataId, run, Timespan(beginTime, endTime)))
585 # Second loop actually does the inserts and filesystem writes. We
586 # first do a butler.put on each dataset, inserting it into the run for
587 # its calibDate. We remember those refs and group them by timespan, so
588 # we can vectorize the certify calls as much as possible.
589 refsByTimespan = defaultdict(list)
590 with butler.transaction():
591 for calib, dataId, run, timespan in datasetRecords:
592 refsByTimespan[timespan].append(butler.put(calib, datasetType, dataId, run=run))
593 for timespan, refs in refsByTimespan.items():
594 butler.registry.certify(collection, refs, timespan)
596 @classmethod
597 def group_name_to_group_id(cls, group_name: str) -> int:
598 """Translate the exposure group name to an integer.
600 Parameters
601 ----------
602 group_name : `str`
603 The name of the exposure group.
605 Returns
606 -------
607 id : `int`
608 The exposure group name in integer form. This integer might be
609 used as an ID to uniquely identify the group in contexts where
610 a string can not be used.
612 Notes
613 -----
614 The default implementation removes all non numeric characters and casts
615 to an integer.
616 """
617 cleaned = re.sub(r"\D", "", group_name)
618 return int(cleaned)
620 def get_curated_calibration_labels(self) -> list[str]:
621 """Return appropriate labels (pieces of a collection name) for a
622 collection populated by `writeCuratedCalibrations`.
624 If this returns an empty list (as the default implementation does),
625 the user will be required to provide a label.
626 """
627 return []
630def makeExposureRecordFromObsInfo(
631 obsInfo: ObservationInfo, universe: DimensionUniverse, **kwargs: Any
632) -> DimensionRecord:
633 """Construct an exposure DimensionRecord from
634 `astro_metadata_translator.ObservationInfo`.
636 Parameters
637 ----------
638 obsInfo : `astro_metadata_translator.ObservationInfo`
639 A `~astro_metadata_translator.ObservationInfo` object corresponding to
640 the exposure.
641 universe : `~lsst.daf.butler.DimensionUniverse`
642 Set of all known dimensions.
643 **kwargs
644 Additional field values for this record.
646 Returns
647 -------
648 record : `~lsst.daf.butler.DimensionRecord`
649 A record containing exposure metadata, suitable for insertion into
650 a `~lsst.daf.butler.Registry`.
651 """
652 dimension = universe["exposure"]
654 # Some registries support additional items.
655 supported = {meta.name for meta in dimension.metadata}
657 ra, dec, sky_angle, azimuth, zenith_angle = (None, None, None, None, None)
658 if obsInfo.tracking_radec is not None:
659 icrs = obsInfo.tracking_radec.icrs
660 ra = float(icrs.ra.degree)
661 dec = float(icrs.dec.degree)
662 if obsInfo.boresight_rotation_coord == "sky":
663 assert obsInfo.boresight_rotation_angle is not None
664 sky_angle = float(obsInfo.boresight_rotation_angle.degree)
665 if obsInfo.altaz_begin is not None:
666 zenith_angle = float(obsInfo.altaz_begin.zen.degree)
667 azimuth = float(obsInfo.altaz_begin.az.degree)
669 extras: dict[str, Any] = {}
670 for meta_key, info_key in (
671 ("has_simulated", "has_simulated_content"),
672 ("seq_start", "group_counter_start"),
673 ("seq_end", "group_counter_end"),
674 ("can_see_sky", "can_see_sky"),
675 ):
676 if meta_key in supported:
677 extras[meta_key] = getattr(obsInfo, info_key)
679 if (k := "azimuth") in supported:
680 extras[k] = float(azimuth) if azimuth is not None else None
682 if "group" in dimension.implied:
683 extras["group"] = obsInfo.exposure_group
684 elif "group_name" in supported:
685 extras["group_name"] = obsInfo.exposure_group
686 extras["group_id"] = obsInfo.visit_id
687 else:
688 raise RuntimeError(f"Unable to determine where to put group metadata in exposure record: {supported}")
690 # In some bad observations, the end time is before the begin time. We
691 # can not let that be ingested as-is because it becomes an unbounded
692 # timespan that will not work correctly with calibration lookups. Instead
693 # force the end time to be the begin time.
694 datetime_end = obsInfo.datetime_end
695 assert obsInfo.datetime_begin is not None
696 if datetime_end < obsInfo.datetime_begin:
697 datetime_end = obsInfo.datetime_begin
698 _LOG.warning(
699 "Exposure %s:%s has end time before begin time. Forcing it to use the begin time.",
700 obsInfo.instrument,
701 obsInfo.observation_id,
702 )
704 assert obsInfo.exposure_time_requested is not None
705 return dimension.RecordClass(
706 instrument=obsInfo.instrument,
707 id=obsInfo.exposure_id,
708 obs_id=obsInfo.observation_id,
709 datetime_begin=obsInfo.datetime_begin,
710 datetime_end=datetime_end,
711 exposure_time=float(obsInfo.exposure_time_requested.to_value("s")),
712 # we are not mandating that dark_time be calculable
713 dark_time=float(obsInfo.dark_time.to_value("s")) if obsInfo.dark_time is not None else None,
714 observation_type=obsInfo.observation_type,
715 observation_reason=obsInfo.observation_reason,
716 day_obs=obsInfo.observing_day,
717 seq_num=obsInfo.observation_counter,
718 physical_filter=obsInfo.physical_filter,
719 science_program=obsInfo.science_program,
720 target_name=obsInfo.object,
721 tracking_ra=ra,
722 tracking_dec=dec,
723 sky_angle=sky_angle,
724 zenith_angle=zenith_angle,
725 **extras,
726 **kwargs,
727 )
730def loadCamera(butler: Butler, dataId: DataId, *, collections: Any = None) -> tuple[Camera, bool]:
731 """Attempt to load versioned camera geometry from a butler, but fall back
732 to obtaining a nominal camera from the `Instrument` class if that fails.
734 Parameters
735 ----------
736 butler : `lsst.daf.butler.Butler`
737 Butler instance to attempt to query for and load a ``camera`` dataset
738 from.
739 dataId : `dict` or `~lsst.daf.butler.DataCoordinate`
740 Data ID that identifies at least the ``instrument`` and ``exposure``
741 dimensions.
742 collections : `typing.Any`, optional
743 Collections to be searched, overriding
744 ``self.butler.collections.defaults``. Can be any of the types
745 supported by the ``collections`` argument to butler construction.
747 Returns
748 -------
749 camera : `lsst.afw.cameraGeom.Camera`
750 Camera object.
751 versioned : `bool`
752 If `True`, the camera was obtained from the butler and should represent
753 a versioned camera from a calibration repository. If `False`, no
754 camera datasets were found, and the returned camera was produced by
755 instantiating the appropriate `Instrument` class and calling
756 `Instrument.getCamera`.
758 Raises
759 ------
760 LookupError
761 Raised when ``dataId`` does not specify a valid data ID.
762 """
763 if collections is None:
764 collections = list(butler.collections.defaults)
765 # Registry would do data ID expansion internally if we didn't do it first,
766 # but we might want an expanded data ID ourselves later, so we do it here
767 # to ensure it only happens once.
768 # This will also catch problems with the data ID not having keys we need.
769 try:
770 dataId = butler.registry.expandDataId(dataId, dimensions=butler.dimensions["exposure"].minimal_group)
771 except DataIdError as exc:
772 raise LookupError(str(exc)) from exc
773 try:
774 cameraRef = butler.get("camera", dataId=dataId, collections=collections)
775 return cameraRef, True
776 except LookupError:
777 pass
778 # We know an instrument data ID is a value, but MyPy doesn't.
779 instrument = Instrument.fromName(dataId["instrument"], butler.registry) # type: ignore
780 assert isinstance(instrument, Instrument) # for mypy
781 return instrument.getCamera(), False