Coverage for python/lsst/obs/base/gen2to3/convertRepo.py : 30%

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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/>.
21from __future__ import annotations
23__all__ = ["ConvertRepoConfig", "ConvertRepoTask", "ConvertRepoSkyMapConfig", "Rerun"]
25import os
26import fnmatch
27from dataclasses import dataclass
28from typing import Iterable, Optional, List, Dict
30from lsst.daf.butler import (
31 Butler as Butler3,
32 CollectionType,
33 SkyPixDimension
34)
35from lsst.pex.config import Config, ConfigurableField, ConfigDictField, DictField, ListField, Field
36from lsst.pipe.base import Task
37from lsst.skymap import skyMapRegistry, BaseSkyMap
39from ..ingest import RawIngestTask
40from ..defineVisits import DefineVisitsTask
41from .repoConverter import ConversionSubset
42from .rootRepoConverter import RootRepoConverter
43from .calibRepoConverter import CalibRepoConverter
44from .standardRepoConverter import StandardRepoConverter
45from .._instrument import Instrument
48@dataclass
49class ConfiguredSkyMap:
50 """Struct containing information about a skymap that may appear in a Gen2
51 repository.
52 """
54 name: str
55 """Name of the skymap used in Gen3 data IDs.
56 """
58 sha1: bytes
59 """Hash computed by `BaseSkyMap.getSha1`.
60 """
62 instance: BaseSkyMap
63 """Name of the skymap used in Gen3 data IDs.
64 """
66 used: bool = False
67 """Whether this skymap has been found in at least one repository being
68 converted.
69 """
72@dataclass
73class Rerun:
74 """Specification for a Gen2 processing-output repository to convert.
75 """
77 path: str
78 """Absolute or relative (to the root repository) path to the Gen2
79 repository (`str`).
80 """
82 runName: str
83 """Name of the `~lsst.daf.butler.CollectionType.RUN` collection datasets
84 will be inserted into (`str`).
85 """
87 chainName: Optional[str]
88 """Name of a `~lsst.daf.butler.CollectionType.CHAINED` collection that will
89 combine this repository's datasets with those of its parent repositories
90 (`str`, optional).
91 """
93 parents: List[str]
94 """Collection names associated with parent repositories, used to define the
95 chained collection (`list` [ `str` ]).
97 Ignored if `chainName` is `None`. Runs used in the root repo are
98 automatically included.
99 """
102class ConvertRepoSkyMapConfig(Config):
103 """Sub-config used to hold the parameters of a SkyMap.
105 Notes
106 -----
107 This config only needs to exist because we can't put a
108 `~lsst.pex.config.RegistryField` directly inside a
109 `~lsst.pex.config.ConfigDictField`.
111 It needs to have its only field named "skyMap" for compatibility with the
112 configuration of `lsst.pipe.tasks.MakeSkyMapTask`, which we want so we can
113 use one config file in an obs package to configure both.
115 This name leads to unfortunate repetition with the field named
116 "skymap" that holds it - "skyMap[name].skyMap" - but that seems
117 unavoidable.
118 """
119 skyMap = skyMapRegistry.makeField(
120 doc="Type and parameters for the SkyMap itself.",
121 default="dodeca",
122 )
125class ConvertRepoConfig(Config):
126 raws = ConfigurableField(
127 "Configuration for subtask responsible for ingesting raws and adding "
128 "exposure dimension entries.",
129 target=RawIngestTask,
130 )
131 defineVisits = ConfigurableField(
132 "Configuration for the subtask responsible for defining visits from "
133 "exposures.",
134 target=DefineVisitsTask,
135 )
136 skyMaps = ConfigDictField(
137 "Mapping from Gen3 skymap name to the parameters used to construct a "
138 "BaseSkyMap instance. This will be used to associate names with "
139 "existing skymaps found in the Gen2 repo.",
140 keytype=str,
141 itemtype=ConvertRepoSkyMapConfig,
142 default={}
143 )
144 rootSkyMapName = Field(
145 "Name of a Gen3 skymap (an entry in ``self.skyMaps``) to assume for "
146 "datasets in the root repository when no SkyMap is found there. ",
147 dtype=str,
148 optional=True,
149 default=None,
150 )
151 runs = DictField(
152 "A mapping from dataset type name to the RUN collection they should "
153 "be inserted into. This must include all datasets that can be found "
154 "in the root repository; other repositories will use per-repository "
155 "runs.",
156 keytype=str,
157 itemtype=str,
158 default={
159 "deepCoadd_skyMap": "skymaps",
160 "brightObjectMask": "masks",
161 }
162 )
163 storageClasses = DictField(
164 "Mapping from dataset type name or Gen2 policy entry (e.g. 'python' "
165 "or 'persistable') to the Gen3 StorageClass name.",
166 keytype=str,
167 itemtype=str,
168 default={
169 "bias": "ExposureF",
170 "dark": "ExposureF",
171 "flat": "ExposureF",
172 "defects": "Defects",
173 "crosstalk": "CrosstalkCalib",
174 "BaseSkyMap": "SkyMap",
175 "BaseCatalog": "Catalog",
176 "BackgroundList": "Background",
177 "raw": "Exposure",
178 "MultilevelParquetTable": "DataFrame",
179 "ParquetTable": "DataFrame",
180 "SkyWcs": "Wcs",
181 }
182 )
183 formatterClasses = DictField(
184 "Mapping from dataset type name to formatter class. "
185 "By default these are derived from the formatters listed in the"
186 " Gen3 datastore configuration.",
187 keytype=str,
188 itemtype=str,
189 default={}
190 )
191 targetHandlerClasses = DictField(
192 "Mapping from dataset type name to target handler class.",
193 keytype=str,
194 itemtype=str,
195 default={}
196 )
197 doRegisterInstrument = Field(
198 "If True (default), add dimension records for the Instrument and its "
199 "filters and detectors to the registry instead of assuming they are "
200 "already present.",
201 dtype=bool,
202 default=True,
203 )
204 doWriteCuratedCalibrations = Field(
205 "If True (default), ingest human-curated calibrations directly via "
206 "the Instrument interface. Note that these calibrations are never "
207 "converted from Gen2 repositories.",
208 dtype=bool,
209 default=True,
210 )
211 refCats = ListField(
212 "The names of reference catalogs (subdirectories under ref_cats) to "
213 "be converted",
214 dtype=str,
215 default=[]
216 )
217 fileIgnorePatterns = ListField(
218 "Filename globs that should be ignored instead of being treated as "
219 "datasets.",
220 dtype=str,
221 default=["README.txt", "*~?", "butler.yaml", "gen3.sqlite3",
222 "registry.sqlite3", "calibRegistry.sqlite3", "_mapper",
223 "_parent", "repositoryCfg.yaml"]
224 )
225 rawDatasetType = Field(
226 "Gen2 dataset type to use for raw data.",
227 dtype=str,
228 default="raw",
229 )
230 datasetIncludePatterns = ListField(
231 "Glob-style patterns for dataset type names that should be converted.",
232 dtype=str,
233 default=["*"]
234 )
235 datasetIgnorePatterns = ListField(
236 "Glob-style patterns for dataset type names that should not be "
237 "converted despite matching a pattern in datasetIncludePatterns.",
238 dtype=str,
239 default=[]
240 )
241 ccdKey = Field(
242 "Key used for the Gen2 equivalent of 'detector' in data IDs.",
243 dtype=str,
244 default="ccd",
245 )
246 relatedOnly = Field(
247 "If True (default), only convert datasets that are related to the "
248 "ingested visits. Ignored unless a list of visits is passed to "
249 "run().",
250 dtype=bool,
251 default=False,
252 )
254 @property
255 def transfer(self):
256 return self.raws.transfer
258 @transfer.setter
259 def transfer(self, value):
260 self.raws.transfer = value
262 def setDefaults(self):
263 self.transfer = None
265 # TODO: check that there are no collection overrides for curated
266 # calibrations, since we don't have a good way to utilize them.
269class ConvertRepoTask(Task):
270 """A task that converts one or more related Gen2 data repositories to a
271 single Gen3 data repository (with multiple collections).
273 Parameters
274 ----------
275 config: `ConvertRepoConfig`
276 Configuration for this task.
277 butler3: `lsst.daf.butler.Butler`
278 A writeable Gen3 Butler instance that represents the data repository
279 that datasets will be ingested into. If the 'raw' dataset is
280 configured to be included in the conversion, ``butler3.run`` should be
281 set to the name of the collection raws should be ingested into, and
282 ``butler3.collections`` should include a calibration collection from
283 which the ``camera`` dataset can be loaded, unless a calibration repo
284 is converted and ``doWriteCuratedCalibrations`` is `True`.
285 **kwargs
286 Other keyword arguments are forwarded to the `Task` constructor.
288 Notes
289 -----
290 Most of the work of converting repositories is delegated to instances of
291 the `RepoConverter` hierarchy. The `ConvertRepoTask` instance itself holds
292 only state that is relevant for all Gen2 repositories being ingested, while
293 each `RepoConverter` instance holds only state relevant for the conversion
294 of a single Gen2 repository. Both the task and the `RepoConverter`
295 instances are single use; `ConvertRepoTask.run` and most `RepoConverter`
296 methods may only be called once on a particular instance.
297 """
299 ConfigClass = ConvertRepoConfig
301 _DefaultName = "convertRepo"
303 def __init__(self, config=None, *, butler3: Butler3, instrument: Instrument, **kwargs):
304 config.validate() # Not a CmdlineTask nor PipelineTask, so have to validate the config here.
305 super().__init__(config, **kwargs)
306 self.butler3 = butler3
307 self.registry = self.butler3.registry
308 self.universe = self.registry.dimensions
309 if self.isDatasetTypeIncluded("raw"):
310 self.makeSubtask("raws", butler=butler3)
311 self.makeSubtask("defineVisits", butler=butler3)
312 else:
313 self.raws = None
314 self.defineVisits = None
315 self.instrument = instrument
316 self._configuredSkyMapsBySha1 = {}
317 self._configuredSkyMapsByName = {}
318 for name, config in self.config.skyMaps.items():
319 instance = config.skyMap.apply()
320 self._populateSkyMapDicts(name, instance)
321 self._usedSkyPix = set()
322 self.translatorFactory = self.instrument.makeDataIdTranslatorFactory()
323 self.translatorFactory.log = self.log.getChild("translators")
325 def _populateSkyMapDicts(self, name, instance):
326 struct = ConfiguredSkyMap(name=name, sha1=instance.getSha1(), instance=instance)
327 self._configuredSkyMapsBySha1[struct.sha1] = struct
328 self._configuredSkyMapsByName[struct.name] = struct
330 def isDatasetTypeIncluded(self, datasetTypeName: str):
331 """Return `True` if configuration indicates that the given dataset type
332 should be converted.
334 This method is intended to be called primarily by the
335 `RepoConverter` instances used interally by the task.
337 Parameters
338 ----------
339 datasetTypeName: str
340 Name of the dataset type.
342 Returns
343 -------
344 included : `bool`
345 Whether the dataset should be included in the conversion.
346 """
347 return (
348 any(fnmatch.fnmatchcase(datasetTypeName, pattern)
349 for pattern in self.config.datasetIncludePatterns)
350 and not any(fnmatch.fnmatchcase(datasetTypeName, pattern)
351 for pattern in self.config.datasetIgnorePatterns)
352 )
354 def useSkyMap(self, skyMap: BaseSkyMap, skyMapName: str) -> str:
355 """Indicate that a repository uses the given SkyMap.
357 This method is intended to be called primarily by the
358 `RepoConverter` instances used interally by the task.
360 Parameters
361 ----------
362 skyMap : `lsst.skymap.BaseSkyMap`
363 SkyMap instance being used, typically retrieved from a Gen2
364 data repository.
365 skyMapName : `str`
366 The name of the gen2 skymap, for error reporting.
368 Returns
369 -------
370 name : `str`
371 The name of the skymap in Gen3 data IDs.
373 Raises
374 ------
375 LookupError
376 Raised if the specified skymap cannot be found.
377 """
378 sha1 = skyMap.getSha1()
379 if sha1 not in self._configuredSkyMapsBySha1:
380 self._populateSkyMapDicts(skyMapName, skyMap)
381 try:
382 struct = self._configuredSkyMapsBySha1[sha1]
383 except KeyError as err:
384 msg = f"SkyMap '{skyMapName}' with sha1={sha1} not included in configuration."
385 raise LookupError(msg) from err
386 struct.used = True
387 return struct.name
389 def registerUsedSkyMaps(self, subset: Optional[ConversionSubset]):
390 """Register all skymaps that have been marked as used.
392 This method is intended to be called primarily by the
393 `RepoConverter` instances used interally by the task.
395 Parameters
396 ----------
397 subset : `ConversionSubset`, optional
398 Object that will be used to filter converted datasets by data ID.
399 If given, it will be updated with the tracts of this skymap that
400 overlap the visits in the subset.
401 """
402 for struct in self._configuredSkyMapsBySha1.values():
403 if struct.used:
404 struct.instance.register(struct.name, self.registry)
405 if subset is not None and self.config.relatedOnly:
406 subset.addSkyMap(self.registry, struct.name)
408 def useSkyPix(self, dimension: SkyPixDimension):
409 """Indicate that a repository uses the given SkyPix dimension.
411 This method is intended to be called primarily by the
412 `RepoConverter` instances used interally by the task.
414 Parameters
415 ----------
416 dimension : `lsst.daf.butler.SkyPixDimension`
417 Dimension represening a pixelization of the sky.
418 """
419 self._usedSkyPix.add(dimension)
421 def registerUsedSkyPix(self, subset: Optional[ConversionSubset]):
422 """Register all skymaps that have been marked as used.
424 This method is intended to be called primarily by the
425 `RepoConverter` instances used interally by the task.
427 Parameters
428 ----------
429 subset : `ConversionSubset`, optional
430 Object that will be used to filter converted datasets by data ID.
431 If given, it will be updated with the pixelization IDs that
432 overlap the visits in the subset.
433 """
434 if subset is not None and self.config.relatedOnly:
435 for dimension in self._usedSkyPix:
436 subset.addSkyPix(self.registry, dimension)
438 def run(self, root: str, *,
439 calibs: Dict[str, str] = None,
440 reruns: List[Rerun],
441 visits: Optional[Iterable[int]] = None):
442 """Convert a group of related data repositories.
444 Parameters
445 ----------
446 root : `str`
447 Complete path to the root Gen2 data repository. This should be
448 a data repository that includes a Gen2 registry and any raw files
449 and/or reference catalogs.
450 calibs : `dict`
451 Dictionary mapping calibration repository path to the
452 `~lsst.daf.butler.CollectionType.RUN` collection that converted
453 datasets within it should be inserted into.
454 reruns : `list` of `Rerun`
455 Specifications for rerun (processing output) collections to
456 convert.
457 visits : iterable of `int`, optional
458 The integer IDs of visits to convert. If not provided, all visits
459 in the Gen2 root repository will be converted.
460 """
461 if calibs is None:
462 calibs = {}
463 if visits is not None:
464 subset = ConversionSubset(instrument=self.instrument.getName(), visits=frozenset(visits))
465 else:
466 if self.config.relatedOnly:
467 self.log.warn("config.relatedOnly is True but all visits are being ingested; "
468 "no filtering will be done.")
469 subset = None
471 # Make converters for all Gen2 repos.
472 converters = []
473 rootConverter = RootRepoConverter(task=self, root=root, subset=subset, instrument=self.instrument)
474 converters.append(rootConverter)
475 for calibRoot, run in calibs.items():
476 if not os.path.isabs(calibRoot):
477 calibRoot = os.path.join(rootConverter.root, calibRoot)
478 converter = CalibRepoConverter(task=self, root=calibRoot, run=run, instrument=self.instrument,
479 mapper=rootConverter.mapper,
480 subset=rootConverter.subset)
481 converters.append(converter)
482 for spec in reruns:
483 runRoot = spec.path
484 if not os.path.isabs(runRoot):
485 runRoot = os.path.join(rootConverter.root, runRoot)
486 converter = StandardRepoConverter(task=self, root=runRoot, run=spec.runName,
487 instrument=self.instrument, subset=rootConverter.subset)
488 converters.append(converter)
490 # Register the instrument if we're configured to do so.
491 if self.config.doRegisterInstrument:
492 # Allow registration to fail on the assumption that this means
493 # we are reusing a butler
494 try:
495 self.instrument.register(self.registry)
496 except Exception:
497 pass
499 # Run raw ingest (does nothing if we weren't configured to convert the
500 # 'raw' dataset type).
501 rootConverter.runRawIngest()
503 # Write curated calibrations to all calibration runs and
504 # also in the default collection.
505 # Add new collections to the list of collections the butler was
506 # initialized to pass to DefineVisitsTask, to deal with the (likely)
507 # case the only 'camera' dataset in the repo will be one we're adding
508 # here.
509 if self.config.doWriteCuratedCalibrations:
510 butler3 = Butler3(butler=self.butler3)
511 calibCollections = set()
512 for run in calibs.values():
513 self.instrument.writeCuratedCalibrations(butler3, run=run)
514 calibCollections.add(run)
515 # Ensure that we have the curated calibrations even if there
516 # is no calibration conversion. It's possible that the default
517 # calib collection will have been specified (in fact the
518 # butler convert script enforces that behavior for now) so
519 # we check for the default situation
520 # Assume we know the default rather than letting
521 # writeCuratedCalibrations default itself
522 defaultCalibCollection = self.instrument.makeCollectionName("calib")
523 if defaultCalibCollection not in calibCollections:
524 self.instrument.writeCuratedCalibrations(butler3, run=defaultCalibCollection)
526 # Define visits (also does nothing if we weren't configurd to convert
527 # the 'raw' dataset type).
528 rootConverter.runDefineVisits()
530 # Walk Gen2 repos to find datasets convert.
531 for converter in converters:
532 converter.prep()
534 # Insert dimensions needed by any converters. In practice this is just
535 # calibration_labels right now, because exposures and visits (and
536 # things related to them) are handled by RawIngestTask and
537 # DefineVisitsTask earlier and skymaps are handled later.
538 #
539 # Note that we do not try to filter dimensions down to just those
540 # related to the given visits, even if config.relatedOnly is True; we
541 # need them in the Gen3 repo in order to be able to know which datasets
542 # to convert, because Gen2 alone doesn't know enough about the
543 # relationships between data IDs.
544 for converter in converters:
545 converter.insertDimensionData()
547 # Insert dimensions that are potentially shared by all Gen2
548 # repositories (and are hence managed directly by the Task, rather
549 # than a converter instance).
550 # This also finishes setting up the (shared) converter.subsets object
551 # that is used to filter data IDs for config.relatedOnly.
552 self.registerUsedSkyMaps(rootConverter.subset)
553 self.registerUsedSkyPix(rootConverter.subset)
555 # Look for datasets, generally by scanning the filesystem.
556 # This requires dimensions to have already been inserted so we can use
557 # dimension information to identify related datasets.
558 for converter in converters:
559 converter.findDatasets()
561 # Expand data IDs.
562 for converter in converters:
563 converter.expandDataIds()
565 # Actually ingest datasets.
566 for converter in converters:
567 converter.ingest()
569 # Add chained collections for reruns.
570 for spec in reruns:
571 if spec.chainName is not None:
572 self.butler3.registry.registerCollection(spec.chainName, type=CollectionType.CHAINED)
573 chain = [spec.runName]
574 chain.extend(spec.parents)
575 chain.extend(rootConverter.getCollectionChain())
576 self.log.info("Defining %s from chain %s.", spec.chainName, chain)
577 self.butler3.registry.setCollectionChain(spec.chainName, chain)