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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__ = ("Instrument", "makeExposureRecordFromObsInfo", "loadCamera")
26import os.path
27from abc import ABCMeta, abstractmethod
28from collections import defaultdict
29import datetime
30from typing import Any, Optional, Set, Sequence, Tuple, TYPE_CHECKING, Union
31from functools import lru_cache
33import astropy.time
35from lsst.afw.cameraGeom import Camera
36from lsst.daf.butler import (
37 Butler,
38 CollectionType,
39 DataCoordinate,
40 DataId,
41 DatasetType,
42 Timespan,
43)
44from lsst.utils import getPackageDir, doImport
46if TYPE_CHECKING: 46 ↛ 47line 46 didn't jump to line 47, because the condition on line 46 was never true
47 from .gen2to3 import TranslatorFactory
48 from lsst.daf.butler import Registry
50# To be a standard text curated calibration means that we use a
51# standard definition for the corresponding DatasetType.
52StandardCuratedCalibrationDatasetTypes = {
53 "defects": {"dimensions": ("instrument", "detector"), "storageClass": "Defects"},
54 "qe_curve": {"dimensions": ("instrument", "detector"), "storageClass": "QECurve"},
55 "crosstalk": {"dimensions": ("instrument", "detector"), "storageClass": "CrosstalkCalib"},
56 "linearizer": {"dimensions": ("instrument", "detector"), "storageClass": "Linearizer"},
57}
60class Instrument(metaclass=ABCMeta):
61 """Base class for instrument-specific logic for the Gen3 Butler.
63 Parameters
64 ----------
65 collection_prefix : `str`, optional
66 Prefix for collection names to use instead of the intrument's own name.
67 This is primarily for use in simulated-data repositories, where the
68 instrument name may not be necessary and/or sufficient to distinguish
69 between collections.
71 Notes
72 -----
73 Concrete instrument subclasses must have the same construction signature as
74 the base class.
75 """
77 configPaths: Sequence[str] = ()
78 """Paths to config files to read for specific Tasks.
80 The paths in this list should contain files of the form `task.py`, for
81 each of the Tasks that requires special configuration.
82 """
84 policyName: Optional[str] = None
85 """Instrument specific name to use when locating a policy or configuration
86 file in the file system."""
88 obsDataPackage: Optional[str] = None
89 """Name of the package containing the text curated calibration files.
90 Usually a obs _data package. If `None` no curated calibration files
91 will be read. (`str`)"""
93 standardCuratedDatasetTypes: Set[str] = frozenset(StandardCuratedCalibrationDatasetTypes)
94 """The dataset types expected to be obtained from the obsDataPackage.
96 These dataset types are all required to have standard definitions and
97 must be known to the base class. Clearing this list will prevent
98 any of these calibrations from being stored. If a dataset type is not
99 known to a specific instrument it can still be included in this list
100 since the data package is the source of truth. (`set` of `str`)
101 """
103 additionalCuratedDatasetTypes: Set[str] = frozenset()
104 """Curated dataset types specific to this particular instrument that do
105 not follow the standard organization found in obs data packages.
107 These are the instrument-specific dataset types written by
108 `writeAdditionalCuratedCalibrations` in addition to the calibrations
109 found in obs data packages that follow the standard scheme.
110 (`set` of `str`)"""
112 @property
113 @abstractmethod
114 def filterDefinitions(self):
115 """`~lsst.obs.base.FilterDefinitionCollection`, defining the filters
116 for this instrument.
117 """
118 return None
120 def __init__(self, collection_prefix: Optional[str] = None):
121 self.filterDefinitions.reset()
122 self.filterDefinitions.defineFilters()
123 if collection_prefix is None: 123 ↛ 125line 123 didn't jump to line 125, because the condition on line 123 was never false
124 collection_prefix = self.getName()
125 self.collection_prefix = collection_prefix
127 @classmethod
128 @abstractmethod
129 def getName(cls):
130 """Return the short (dimension) name for this instrument.
132 This is not (in general) the same as the class name - it's what is used
133 as the value of the "instrument" field in data IDs, and is usually an
134 abbreviation of the full name.
135 """
136 raise NotImplementedError()
138 @classmethod
139 @lru_cache()
140 def getCuratedCalibrationNames(cls) -> Set[str]:
141 """Return the names of all the curated calibration dataset types.
143 Returns
144 -------
145 names : `set` of `str`
146 The dataset type names of all curated calibrations. This will
147 include the standard curated calibrations even if the particular
148 instrument does not support them.
150 Notes
151 -----
152 The returned list does not indicate whether a particular dataset
153 is present in the Butler repository, simply that these are the
154 dataset types that are handled by ``writeCuratedCalibrations``.
155 """
157 # Camera is a special dataset type that is also handled as a
158 # curated calibration.
159 curated = {"camera"}
161 # Make a cursory attempt to filter out curated dataset types
162 # that are not present for this instrument
163 for datasetTypeName in cls.standardCuratedDatasetTypes:
164 calibPath = cls._getSpecificCuratedCalibrationPath(datasetTypeName)
165 if calibPath is not None:
166 curated.add(datasetTypeName)
168 curated.update(cls.additionalCuratedDatasetTypes)
169 return frozenset(curated)
171 @abstractmethod
172 def getCamera(self):
173 """Retrieve the cameraGeom representation of this instrument.
175 This is a temporary API that should go away once ``obs`` packages have
176 a standardized approach to writing versioned cameras to a Gen3 repo.
177 """
178 raise NotImplementedError()
180 @abstractmethod
181 def register(self, registry):
182 """Insert instrument, physical_filter, and detector entries into a
183 `Registry`.
185 Implementations should guarantee that registration is atomic (the
186 registry should not be modified if any error occurs) and idempotent at
187 the level of individual dimension entries; new detectors and filters
188 should be added, but changes to any existing record should not be.
189 This can generally be achieved via a block like::
191 with registry.transaction():
192 registry.syncDimensionData("instrument", ...)
193 registry.syncDimensionData("detector", ...)
194 self.registerFilters(registry)
196 Raises
197 ------
198 lsst.daf.butler.registry.ConflictingDefinitionError
199 Raised if any existing record has the same key but a different
200 definition as one being registered.
201 """
202 raise NotImplementedError()
204 @classmethod
205 @lru_cache()
206 def getObsDataPackageDir(cls):
207 """The root of the obs data package that provides specializations for
208 this instrument.
210 returns
211 -------
212 dir : `str`
213 The root of the relevat obs data package.
214 """
215 if cls.obsDataPackage is None:
216 return None
217 return getPackageDir(cls.obsDataPackage)
219 @staticmethod
220 def fromName(name: str, registry: Registry, collection_prefix: Optional[str] = None) -> Instrument:
221 """Given an instrument name and a butler, retrieve a corresponding
222 instantiated instrument object.
224 Parameters
225 ----------
226 name : `str`
227 Name of the instrument (must match the return value of `getName`).
228 registry : `lsst.daf.butler.Registry`
229 Butler registry to query to find the information.
230 collection_prefix : `str`, optional
231 Prefix for collection names to use instead of the intrument's own
232 name. This is primarily for use in simulated-data repositories,
233 where the instrument name may not be necessary and/or sufficient to
234 distinguish between collections.
236 Returns
237 -------
238 instrument : `Instrument`
239 An instance of the relevant `Instrument`.
241 Notes
242 -----
243 The instrument must be registered in the corresponding butler.
245 Raises
246 ------
247 LookupError
248 Raised if the instrument is not known to the supplied registry.
249 ModuleNotFoundError
250 Raised if the class could not be imported. This could mean
251 that the relevant obs package has not been setup.
252 TypeError
253 Raised if the class name retrieved is not a string.
254 """
255 records = list(registry.queryDimensionRecords("instrument", instrument=name))
256 if not records:
257 raise LookupError(f"No registered instrument with name '{name}'.")
258 cls = records[0].class_name
259 if not isinstance(cls, str):
260 raise TypeError(f"Unexpected class name retrieved from {name} instrument dimension (got {cls})")
261 instrument = doImport(cls)
262 return instrument(collection_prefix=collection_prefix)
264 @staticmethod
265 def importAll(registry: Registry) -> None:
266 """Import all the instruments known to this registry.
268 This will ensure that all metadata translators have been registered.
270 Parameters
271 ----------
272 registry : `lsst.daf.butler.Registry`
273 Butler registry to query to find the information.
275 Notes
276 -----
277 It is allowed for a particular instrument class to fail on import.
278 This might simply indicate that a particular obs package has
279 not been setup.
280 """
281 records = list(registry.queryDimensionRecords("instrument"))
282 for record in records:
283 cls = record.class_name
284 try:
285 doImport(cls)
286 except Exception:
287 pass
289 def _registerFilters(self, registry):
290 """Register the physical and abstract filter Dimension relationships.
291 This should be called in the `register` implementation, within
292 a transaction context manager block.
294 Parameters
295 ----------
296 registry : `lsst.daf.butler.core.Registry`
297 The registry to add dimensions to.
298 """
299 for filter in self.filterDefinitions:
300 # fix for undefined abstract filters causing trouble in the
301 # registry:
302 if filter.band is None:
303 band = filter.physical_filter
304 else:
305 band = filter.band
307 registry.syncDimensionData("physical_filter",
308 {"instrument": self.getName(),
309 "name": filter.physical_filter,
310 "band": band
311 })
313 @abstractmethod
314 def getRawFormatter(self, dataId):
315 """Return the Formatter class that should be used to read a particular
316 raw file.
318 Parameters
319 ----------
320 dataId : `DataCoordinate`
321 Dimension-based ID for the raw file or files being ingested.
323 Returns
324 -------
325 formatter : `Formatter` class
326 Class to be used that reads the file into an
327 `lsst.afw.image.Exposure` instance.
328 """
329 raise NotImplementedError()
331 def applyConfigOverrides(self, name, config):
332 """Apply instrument-specific overrides for a task config.
334 Parameters
335 ----------
336 name : `str`
337 Name of the object being configured; typically the _DefaultName
338 of a Task.
339 config : `lsst.pex.config.Config`
340 Config instance to which overrides should be applied.
341 """
342 for root in self.configPaths:
343 path = os.path.join(root, f"{name}.py")
344 if os.path.exists(path):
345 config.load(path)
347 def writeCuratedCalibrations(self, butler: Butler, collection: Optional[str] = None,
348 labels: Sequence[str] = ()) -> None:
349 """Write human-curated calibration Datasets to the given Butler with
350 the appropriate validity ranges.
352 Parameters
353 ----------
354 butler : `lsst.daf.butler.Butler`
355 Butler to use to store these calibrations.
356 collection : `str`, optional
357 Name to use for the calibration collection that associates all
358 datasets with a validity range. If this collection already exists,
359 it must be a `~CollectionType.CALIBRATION` collection, and it must
360 not have any datasets that would conflict with those inserted by
361 this method. If `None`, a collection name is worked out
362 automatically from the instrument name and other metadata by
363 calling ``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 : `Sequence` [ `str` ], optional
368 Extra strings to include in collection names, after concatenating
369 them with the standard collection name delimeter. If provided,
370 these are inserted into the names of the `~CollectionType.RUN`
371 collections that datasets are inserted directly into, as well the
372 `~CollectionType.CALIBRATION` collection if it is generated
373 automatically (i.e. if ``collection is None``). Usually this is
374 just the name of the ticket on which the calibration collection is
375 being created.
377 Notes
378 -----
379 Expected to be called from subclasses. The base method calls
380 ``writeCameraGeom``, ``writeStandardTextCuratedCalibrations``,
381 and ``writeAdditionalCuratdCalibrations``.
382 """
383 # Delegate registration of collections (and creating names for them)
384 # to other methods so they can be called independently with the same
385 # preconditions. Collection registration is idempotent, so this is
386 # safe, and while it adds a bit of overhead, as long as it's one
387 # registration attempt per method (not per dataset or dataset type),
388 # that's negligible.
389 self.writeCameraGeom(butler, collection, labels=labels)
390 self.writeStandardTextCuratedCalibrations(butler, collection, labels=labels)
391 self.writeAdditionalCuratedCalibrations(butler, collection, labels=labels)
393 def writeAdditionalCuratedCalibrations(self, butler: Butler, collection: Optional[str] = None,
394 labels: Sequence[str] = ()) -> None:
395 """Write additional curated calibrations that might be instrument
396 specific and are not part of the standard set.
398 Default implementation does nothing.
400 Parameters
401 ----------
402 butler : `lsst.daf.butler.Butler`
403 Butler to use to store these calibrations.
404 collection : `str`, optional
405 Name to use for the calibration collection that associates all
406 datasets with a validity range. If this collection already exists,
407 it must be a `~CollectionType.CALIBRATION` collection, and it must
408 not have any datasets that would conflict with those inserted by
409 this method. If `None`, a collection name is worked out
410 automatically from the instrument name and other metadata by
411 calling ``makeCalibrationCollectionName``, but this
412 default name may not work well for long-lived repositories unless
413 ``labels`` is also provided (and changed every time curated
414 calibrations are ingested).
415 labels : `Sequence` [ `str` ], optional
416 Extra strings to include in collection names, after concatenating
417 them with the standard collection name delimeter. If provided,
418 these are inserted into the names of the `~CollectionType.RUN`
419 collections that datasets are inserted directly into, as well the
420 `~CollectionType.CALIBRATION` collection if it is generated
421 automatically (i.e. if ``collection is None``). Usually this is
422 just the name of the ticket on which the calibration collection is
423 being created.
424 """
425 return
427 def writeCameraGeom(self, butler: Butler, collection: Optional[str] = None,
428 labels: Sequence[str] = ()) -> None:
429 """Write the default camera geometry to the butler repository and
430 associate it with the appropriate validity range in a calibration
431 collection.
433 Parameters
434 ----------
435 butler : `lsst.daf.butler.Butler`
436 Butler to use to store these calibrations.
437 collection : `str`, optional
438 Name to use for the calibration collection that associates all
439 datasets with a validity range. If this collection already exists,
440 it must be a `~CollectionType.CALIBRATION` collection, and it must
441 not have any datasets that would conflict with those inserted by
442 this method. If `None`, a collection name is worked out
443 automatically from the instrument name and other metadata by
444 calling ``makeCalibrationCollectionName``, but this
445 default name may not work well for long-lived repositories unless
446 ``labels`` is also provided (and changed every time curated
447 calibrations are ingested).
448 labels : `Sequence` [ `str` ], optional
449 Extra strings to include in collection names, after concatenating
450 them with the standard collection name delimeter. If provided,
451 these are inserted into the names of the `~CollectionType.RUN`
452 collections that datasets are inserted directly into, as well the
453 `~CollectionType.CALIBRATION` collection if it is generated
454 automatically (i.e. if ``collection is None``). Usually this is
455 just the name of the ticket on which the calibration collection is
456 being created.
457 """
458 if collection is None:
459 collection = self.makeCalibrationCollectionName(*labels)
460 butler.registry.registerCollection(collection, type=CollectionType.CALIBRATION)
461 run = self.makeUnboundedCalibrationRunName(*labels)
462 butler.registry.registerRun(run)
463 datasetType = DatasetType("camera", ("instrument",), "Camera", isCalibration=True,
464 universe=butler.registry.dimensions)
465 butler.registry.registerDatasetType(datasetType)
466 camera = self.getCamera()
467 ref = butler.put(camera, datasetType, {"instrument": self.getName()}, run=run)
468 butler.registry.certify(collection, [ref], Timespan(begin=None, end=None))
470 def writeStandardTextCuratedCalibrations(self, butler: Butler, collection: Optional[str] = None,
471 labels: Sequence[str] = ()) -> None:
472 """Write the set of standardized curated text calibrations to
473 the repository.
475 Parameters
476 ----------
477 butler : `lsst.daf.butler.Butler`
478 Butler to receive these calibration datasets.
479 collection : `str`, optional
480 Name to use for the calibration collection that associates all
481 datasets with a validity range. If this collection already exists,
482 it must be a `~CollectionType.CALIBRATION` collection, and it must
483 not have any datasets that would conflict with those inserted by
484 this method. If `None`, a collection name is worked out
485 automatically from the instrument name and other metadata by
486 calling ``makeCalibrationCollectionName``, but this
487 default name may not work well for long-lived repositories unless
488 ``labels`` is also provided (and changed every time curated
489 calibrations are ingested).
490 labels : `Sequence` [ `str` ], optional
491 Extra strings to include in collection names, after concatenating
492 them with the standard collection name delimeter. If provided,
493 these are inserted into the names of the `~CollectionType.RUN`
494 collections that datasets are inserted directly into, as well the
495 `~CollectionType.CALIBRATION` collection if it is generated
496 automatically (i.e. if ``collection is None``). Usually this is
497 just the name of the ticket on which the calibration collection is
498 being created.
499 """
500 if collection is None:
501 collection = self.makeCalibrationCollectionName(*labels)
502 butler.registry.registerCollection(collection, type=CollectionType.CALIBRATION)
503 runs = set()
504 for datasetTypeName in self.standardCuratedDatasetTypes:
505 # We need to define the dataset types.
506 if datasetTypeName not in StandardCuratedCalibrationDatasetTypes:
507 raise ValueError(f"DatasetType {datasetTypeName} not in understood list"
508 f" [{'.'.join(StandardCuratedCalibrationDatasetTypes)}]")
509 definition = StandardCuratedCalibrationDatasetTypes[datasetTypeName]
510 datasetType = DatasetType(datasetTypeName,
511 universe=butler.registry.dimensions,
512 isCalibration=True,
513 **definition)
514 self._writeSpecificCuratedCalibrationDatasets(butler, datasetType, collection, runs=runs,
515 labels=labels)
517 @classmethod
518 def _getSpecificCuratedCalibrationPath(cls, datasetTypeName):
519 """Return the path of the curated calibration directory.
521 Parameters
522 ----------
523 datasetTypeName : `str`
524 The name of the standard dataset type to find.
526 Returns
527 -------
528 path : `str`
529 The path to the standard curated data directory. `None` if the
530 dataset type is not found or the obs data package is not
531 available.
532 """
533 if cls.getObsDataPackageDir() is None:
534 # if there is no data package then there can't be datasets
535 return None
537 calibPath = os.path.join(cls.getObsDataPackageDir(), cls.policyName,
538 datasetTypeName)
540 if os.path.exists(calibPath):
541 return calibPath
543 return None
545 def _writeSpecificCuratedCalibrationDatasets(self, butler: Butler, datasetType: DatasetType,
546 collection: str, runs: Set[str], labels: Sequence[str]):
547 """Write standardized curated calibration datasets for this specific
548 dataset type from an obs data package.
550 Parameters
551 ----------
552 butler : `lsst.daf.butler.Butler`
553 Gen3 butler in which to put the calibrations.
554 datasetType : `lsst.daf.butler.DatasetType`
555 Dataset type to be put.
556 collection : `str`
557 Name of the `~CollectionType.CALIBRATION` collection that
558 associates all datasets with validity ranges. Must have been
559 registered prior to this call.
560 runs : `set` [ `str` ]
561 Names of runs that have already been registered by previous calls
562 and need not be registered again. Should be updated by this
563 method as new runs are registered.
564 labels : `Sequence` [ `str` ]
565 Extra strings to include in run names when creating them from
566 ``CALIBDATE`` metadata, via calls to `makeCuratedCalibrationName`.
567 Usually this is the name of the ticket on which the calibration
568 collection is being created.
570 Notes
571 -----
572 This method scans the location defined in the ``obsDataPackageDir``
573 class attribute for curated calibrations corresponding to the
574 supplied dataset type. The directory name in the data package must
575 match the name of the dataset type. They are assumed to use the
576 standard layout and can be read by
577 `~lsst.pipe.tasks.read_curated_calibs.read_all` and provide standard
578 metadata.
579 """
580 calibPath = self._getSpecificCuratedCalibrationPath(datasetType.name)
581 if calibPath is None:
582 return
584 # Register the dataset type
585 butler.registry.registerDatasetType(datasetType)
587 # obs_base can't depend on pipe_tasks but concrete obs packages
588 # can -- we therefore have to defer import
589 from lsst.pipe.tasks.read_curated_calibs import read_all
591 # Read calibs, registering a new run for each CALIBDATE as needed.
592 # We try to avoid registering runs multiple times as an optimization
593 # by putting them in the ``runs`` set that was passed in.
594 camera = self.getCamera()
595 calibsDict = read_all(calibPath, camera)[0] # second return is calib type
596 datasetRecords = []
597 for det in calibsDict:
598 times = sorted([k for k in calibsDict[det]])
599 calibs = [calibsDict[det][time] for time in times]
600 times = [astropy.time.Time(t, format="datetime", scale="utc") for t in times]
601 times += [None]
602 for calib, beginTime, endTime in zip(calibs, times[:-1], times[1:]):
603 md = calib.getMetadata()
604 run = self.makeCuratedCalibrationRunName(md['CALIBDATE'], *labels)
605 if run not in runs:
606 butler.registry.registerRun(run)
607 runs.add(run)
608 dataId = DataCoordinate.standardize(
609 universe=butler.registry.dimensions,
610 instrument=self.getName(),
611 detector=md["DETECTOR"],
612 )
613 datasetRecords.append((calib, dataId, run, Timespan(beginTime, endTime)))
615 # Second loop actually does the inserts and filesystem writes. We
616 # first do a butler.put on each dataset, inserting it into the run for
617 # its calibDate. We remember those refs and group them by timespan, so
618 # we can vectorize the certify calls as much as possible.
619 refsByTimespan = defaultdict(list)
620 with butler.transaction():
621 for calib, dataId, run, timespan in datasetRecords:
622 refsByTimespan[timespan].append(butler.put(calib, datasetType, dataId, run=run))
623 for timespan, refs in refsByTimespan.items():
624 butler.registry.certify(collection, refs, timespan)
626 @abstractmethod
627 def makeDataIdTranslatorFactory(self) -> TranslatorFactory:
628 """Return a factory for creating Gen2->Gen3 data ID translators,
629 specialized for this instrument.
631 Derived class implementations should generally call
632 `TranslatorFactory.addGenericInstrumentRules` with appropriate
633 arguments, but are not required to (and may not be able to if their
634 Gen2 raw data IDs are sufficiently different from the HSC/DECam/CFHT
635 norm).
637 Returns
638 -------
639 factory : `TranslatorFactory`.
640 Factory for `Translator` objects.
641 """
642 raise NotImplementedError("Must be implemented by derived classes.")
644 @staticmethod
645 def formatCollectionTimestamp(timestamp: Union[str, datetime.datetime]) -> str:
646 """Format a timestamp for use in a collection name.
648 Parameters
649 ----------
650 timestamp : `str` or `datetime.datetime`
651 Timestamp to format. May be a date or datetime string in extended
652 ISO format (assumed UTC), with or without a timezone specifier, a
653 datetime string in basic ISO format with a timezone specifier, a
654 naive `datetime.datetime` instance (assumed UTC) or a
655 timezone-aware `datetime.datetime` instance (converted to UTC).
656 This is intended to cover all forms that string ``CALIBDATE``
657 metadata values have taken in the past, as well as the format this
658 method itself writes out (to enable round-tripping).
660 Returns
661 -------
662 formatted : `str`
663 Standardized string form for the timestamp.
664 """
665 if isinstance(timestamp, str):
666 if "-" in timestamp:
667 # extended ISO format, with - and : delimiters
668 timestamp = datetime.datetime.fromisoformat(timestamp)
669 else:
670 # basic ISO format, with no delimiters (what this method
671 # returns)
672 timestamp = datetime.datetime.strptime(timestamp, "%Y%m%dT%H%M%S%z")
673 if not isinstance(timestamp, datetime.datetime):
674 raise TypeError(f"Unexpected date/time object: {timestamp!r}.")
675 if timestamp.tzinfo is not None:
676 timestamp = timestamp.astimezone(datetime.timezone.utc)
677 return f"{timestamp:%Y%m%dT%H%M%S}Z"
679 @staticmethod
680 def makeCollectionTimestamp() -> str:
681 """Create a timestamp string for use in a collection name from the
682 current time.
684 Returns
685 -------
686 formatted : `str`
687 Standardized string form of the current time.
688 """
689 return Instrument.formatCollectionTimestamp(datetime.datetime.now(tz=datetime.timezone.utc))
691 def makeDefaultRawIngestRunName(self) -> str:
692 """Make the default instrument-specific run collection string for raw
693 data ingest.
695 Returns
696 -------
697 coll : `str`
698 Run collection name to be used as the default for ingestion of
699 raws.
700 """
701 return self.makeCollectionName("raw", "all")
703 def makeUnboundedCalibrationRunName(self, *labels: str) -> str:
704 """Make a RUN collection name appropriate for inserting calibration
705 datasets whose validity ranges are unbounded.
707 Parameters
708 ----------
709 *labels : `str`
710 Extra strings to be included in the base name, using the default
711 delimiter for collection names. Usually this is the name of the
712 ticket on which the calibration collection is being created.
714 Returns
715 -------
716 name : `str`
717 Run collection name.
718 """
719 return self.makeCollectionName("calib", *labels, "unbounded")
721 def makeCuratedCalibrationRunName(self, calibDate: str, *labels: str) -> str:
722 """Make a RUN collection name appropriate for inserting curated
723 calibration datasets with the given ``CALIBDATE`` metadata value.
725 Parameters
726 ----------
727 calibDate : `str`
728 The ``CALIBDATE`` metadata value.
729 *labels : `str`
730 Strings to be included in the collection name (before
731 ``calibDate``, but after all other terms), using the default
732 delimiter for collection names. Usually this is the name of the
733 ticket on which the calibration collection is being created.
735 Returns
736 -------
737 name : `str`
738 Run collection name.
739 """
740 return self.makeCollectionName("calib", *labels, "curated", self.formatCollectionTimestamp(calibDate))
742 def makeCalibrationCollectionName(self, *labels: str) -> str:
743 """Make a CALIBRATION collection name appropriate for associating
744 calibration datasets with validity ranges.
746 Parameters
747 ----------
748 *labels : `str`
749 Strings to be appended to the base name, using the default
750 delimiter for collection names. Usually this is the name of the
751 ticket on which the calibration collection is being created.
753 Returns
754 -------
755 name : `str`
756 Calibration collection name.
757 """
758 return self.makeCollectionName("calib", *labels)
760 @staticmethod
761 def makeRefCatCollectionName(*labels: str) -> str:
762 """Return a global (not instrument-specific) name for a collection that
763 holds reference catalogs.
765 With no arguments, this returns the name of the collection that holds
766 all reference catalogs (usually a ``CHAINED`` collection, at least in
767 long-lived repos that may contain more than one reference catalog).
769 Parameters
770 ----------
771 *labels : `str`
772 Strings to be added to the global collection name, in order to
773 define a collection name for one or more reference catalogs being
774 ingested at the same time.
776 Returns
777 -------
778 name : `str`
779 Collection name.
781 Notes
782 -----
783 This is a ``staticmethod``, not a ``classmethod``, because it should
784 be the same for all instruments.
785 """
786 return "/".join(("refcats",) + labels)
788 def makeUmbrellaCollectionName(self) -> str:
789 """Return the name of the umbrella ``CHAINED`` collection for this
790 instrument that combines all standard recommended input collections.
792 This method should almost never be overridden by derived classes.
794 Returns
795 -------
796 name : `str`
797 Name for the umbrella collection.
798 """
799 return self.makeCollectionName("defaults")
801 def makeCollectionName(self, *labels: str) -> str:
802 """Get the instrument-specific collection string to use as derived
803 from the supplied labels.
805 Parameters
806 ----------
807 *labels : `str`
808 Strings to be combined with the instrument name to form a
809 collection name.
811 Returns
812 -------
813 name : `str`
814 Collection name to use that includes the instrument's recommended
815 prefix.
816 """
817 return "/".join((self.collection_prefix,) + labels)
820def makeExposureRecordFromObsInfo(obsInfo, universe):
821 """Construct an exposure DimensionRecord from
822 `astro_metadata_translator.ObservationInfo`.
824 Parameters
825 ----------
826 obsInfo : `astro_metadata_translator.ObservationInfo`
827 A `~astro_metadata_translator.ObservationInfo` object corresponding to
828 the exposure.
829 universe : `DimensionUniverse`
830 Set of all known dimensions.
832 Returns
833 -------
834 record : `DimensionRecord`
835 A record containing exposure metadata, suitable for insertion into
836 a `Registry`.
837 """
838 dimension = universe["exposure"]
840 ra, dec, sky_angle, zenith_angle = (None, None, None, None)
841 if obsInfo.tracking_radec is not None:
842 icrs = obsInfo.tracking_radec.icrs
843 ra = icrs.ra.degree
844 dec = icrs.dec.degree
845 if obsInfo.boresight_rotation_coord == "sky":
846 sky_angle = obsInfo.boresight_rotation_angle.degree
847 if obsInfo.altaz_begin is not None:
848 zenith_angle = obsInfo.altaz_begin.zen.degree
850 return dimension.RecordClass(
851 instrument=obsInfo.instrument,
852 id=obsInfo.exposure_id,
853 obs_id=obsInfo.observation_id,
854 group_name=obsInfo.exposure_group,
855 group_id=obsInfo.visit_id,
856 datetime_begin=obsInfo.datetime_begin,
857 datetime_end=obsInfo.datetime_end,
858 exposure_time=obsInfo.exposure_time.to_value("s"),
859 # we are not mandating that dark_time be calculable
860 dark_time=obsInfo.dark_time.to_value("s") if obsInfo.dark_time is not None else None,
861 observation_type=obsInfo.observation_type,
862 observation_reason=obsInfo.observation_reason,
863 day_obs=obsInfo.observing_day,
864 seq_num=obsInfo.observation_counter,
865 physical_filter=obsInfo.physical_filter,
866 science_program=obsInfo.science_program,
867 target_name=obsInfo.object,
868 tracking_ra=ra,
869 tracking_dec=dec,
870 sky_angle=sky_angle,
871 zenith_angle=zenith_angle,
872 )
875def loadCamera(butler: Butler, dataId: DataId, *, collections: Any = None) -> Tuple[Camera, bool]:
876 """Attempt to load versioned camera geometry from a butler, but fall back
877 to obtaining a nominal camera from the `Instrument` class if that fails.
879 Parameters
880 ----------
881 butler : `lsst.daf.butler.Butler`
882 Butler instance to attempt to query for and load a ``camera`` dataset
883 from.
884 dataId : `dict` or `DataCoordinate`
885 Data ID that identifies at least the ``instrument`` and ``exposure``
886 dimensions.
887 collections : Any, optional
888 Collections to be searched, overriding ``self.butler.collections``.
889 Can be any of the types supported by the ``collections`` argument
890 to butler construction.
892 Returns
893 -------
894 camera : `lsst.afw.cameraGeom.Camera`
895 Camera object.
896 versioned : `bool`
897 If `True`, the camera was obtained from the butler and should represent
898 a versioned camera from a calibration repository. If `False`, no
899 camera datasets were found, and the returned camera was produced by
900 instantiating the appropriate `Instrument` class and calling
901 `Instrument.getCamera`.
902 """
903 if collections is None:
904 collections = butler.collections
905 # Registry would do data ID expansion internally if we didn't do it first,
906 # but we might want an expanded data ID ourselves later, so we do it here
907 # to ensure it only happens once.
908 # This will also catch problems with the data ID not having keys we need.
909 dataId = butler.registry.expandDataId(dataId, graph=butler.registry.dimensions["exposure"].graph)
910 try:
911 cameraRef = butler.get("camera", dataId=dataId, collections=collections)
912 return cameraRef, True
913 except LookupError:
914 pass
915 instrument = Instrument.fromName(dataId["instrument"], butler.registry)
916 return instrument.getCamera(), False