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1# This file is part of fgcmcal.
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 <https://www.gnu.org/licenses/>.
21"""Base class for BuildStars using src tables or sourceTable_visit tables.
22"""
24import os
25import sys
26import traceback
27import abc
29import numpy as np
31import lsst.daf.persistence as dafPersist
32import lsst.pex.config as pexConfig
33import lsst.pipe.base as pipeBase
34import lsst.afw.table as afwTable
35import lsst.geom as geom
36from lsst.daf.base import PropertyList
37from lsst.daf.base.dateTime import DateTime
38from lsst.meas.algorithms.sourceSelector import sourceSelectorRegistry
40from .utilities import computeApertureRadiusFromDataRef
41from .fgcmLoadReferenceCatalog import FgcmLoadReferenceCatalogTask
43import fgcm
45REFSTARS_FORMAT_VERSION = 1
47__all__ = ['FgcmBuildStarsConfigBase', 'FgcmBuildStarsRunner', 'FgcmBuildStarsBaseTask']
50class FgcmBuildStarsConfigBase(pexConfig.Config):
51 """Base config for FgcmBuildStars tasks"""
53 instFluxField = pexConfig.Field(
54 doc=("Faull name of the source instFlux field to use, including 'instFlux'. "
55 "The associated flag will be implicitly included in badFlags"),
56 dtype=str,
57 default='slot_CalibFlux_instFlux',
58 )
59 minPerBand = pexConfig.Field(
60 doc="Minimum observations per band",
61 dtype=int,
62 default=2,
63 )
64 matchRadius = pexConfig.Field(
65 doc="Match radius (arcseconds)",
66 dtype=float,
67 default=1.0,
68 )
69 isolationRadius = pexConfig.Field(
70 doc="Isolation radius (arcseconds)",
71 dtype=float,
72 default=2.0,
73 )
74 densityCutNside = pexConfig.Field(
75 doc="Density cut healpix nside",
76 dtype=int,
77 default=128,
78 )
79 densityCutMaxPerPixel = pexConfig.Field(
80 doc="Density cut number of stars per pixel",
81 dtype=int,
82 default=1000,
83 )
84 matchNside = pexConfig.Field(
85 doc="Healpix Nside for matching",
86 dtype=int,
87 default=4096,
88 )
89 coarseNside = pexConfig.Field(
90 doc="Healpix coarse Nside for partitioning matches",
91 dtype=int,
92 default=8,
93 )
94 filterMap = pexConfig.DictField(
95 doc="Mapping from 'filterName' to band.",
96 keytype=str,
97 itemtype=str,
98 default={},
99 deprecated=("This field is no longer used, and has been deprecated by "
100 "DM-28088. It will be removed after v22. Use "
101 "physicalFilterMap instead.")
102 )
103 # The following config will not be necessary after Gen2 retirement.
104 # In the meantime, obs packages should set to 'filterDefinitions.filter_to_band'
105 # which is easiest to access in the config file.
106 physicalFilterMap = pexConfig.DictField(
107 doc="Mapping from 'physicalFilter' to band.",
108 keytype=str,
109 itemtype=str,
110 default={},
111 )
112 requiredBands = pexConfig.ListField(
113 doc="Bands required for each star",
114 dtype=str,
115 default=(),
116 )
117 primaryBands = pexConfig.ListField(
118 doc=("Bands for 'primary' star matches. "
119 "A star must be observed in one of these bands to be considered "
120 "as a calibration star."),
121 dtype=str,
122 default=None
123 )
124 visitDataRefName = pexConfig.Field(
125 doc="dataRef name for the 'visit' field, usually 'visit'.",
126 dtype=str,
127 default="visit"
128 )
129 ccdDataRefName = pexConfig.Field(
130 doc="dataRef name for the 'ccd' field, usually 'ccd' or 'detector'.",
131 dtype=str,
132 default="ccd"
133 )
134 doApplyWcsJacobian = pexConfig.Field(
135 doc="Apply the jacobian of the WCS to the star observations prior to fit?",
136 dtype=bool,
137 default=True
138 )
139 doModelErrorsWithBackground = pexConfig.Field(
140 doc="Model flux errors with background term?",
141 dtype=bool,
142 default=True
143 )
144 psfCandidateName = pexConfig.Field(
145 doc="Name of field with psf candidate flag for propagation",
146 dtype=str,
147 default="calib_psf_candidate"
148 )
149 doSubtractLocalBackground = pexConfig.Field(
150 doc=("Subtract the local background before performing calibration? "
151 "This is only supported for circular aperture calibration fluxes."),
152 dtype=bool,
153 default=False
154 )
155 localBackgroundFluxField = pexConfig.Field(
156 doc="Full name of the local background instFlux field to use.",
157 dtype=str,
158 default='base_LocalBackground_instFlux'
159 )
160 sourceSelector = sourceSelectorRegistry.makeField(
161 doc="How to select sources",
162 default="science"
163 )
164 apertureInnerInstFluxField = pexConfig.Field(
165 doc=("Full name of instFlux field that contains inner aperture "
166 "flux for aperture correction proxy"),
167 dtype=str,
168 default='base_CircularApertureFlux_12_0_instFlux'
169 )
170 apertureOuterInstFluxField = pexConfig.Field(
171 doc=("Full name of instFlux field that contains outer aperture "
172 "flux for aperture correction proxy"),
173 dtype=str,
174 default='base_CircularApertureFlux_17_0_instFlux'
175 )
176 doReferenceMatches = pexConfig.Field(
177 doc="Match reference catalog as additional constraint on calibration",
178 dtype=bool,
179 default=True,
180 )
181 fgcmLoadReferenceCatalog = pexConfig.ConfigurableField(
182 target=FgcmLoadReferenceCatalogTask,
183 doc="FGCM reference object loader",
184 )
185 nVisitsPerCheckpoint = pexConfig.Field(
186 doc="Number of visits read between checkpoints",
187 dtype=int,
188 default=500,
189 )
191 def setDefaults(self):
192 sourceSelector = self.sourceSelector["science"]
193 sourceSelector.setDefaults()
195 sourceSelector.doFlags = True
196 sourceSelector.doUnresolved = True
197 sourceSelector.doSignalToNoise = True
198 sourceSelector.doIsolated = True
200 sourceSelector.signalToNoise.minimum = 10.0
201 sourceSelector.signalToNoise.maximum = 1000.0
203 # FGCM operates on unresolved sources, and this setting is
204 # appropriate for the current base_ClassificationExtendedness
205 sourceSelector.unresolved.maximum = 0.5
208class FgcmBuildStarsRunner(pipeBase.ButlerInitializedTaskRunner):
209 """Subclass of TaskRunner for FgcmBuildStars tasks
211 fgcmBuildStarsTask.run() and fgcmBuildStarsTableTask.run() take a number of
212 arguments, one of which is the butler (for persistence and mapper data),
213 and a list of dataRefs extracted from the command line. Note that FGCM
214 runs on a large set of dataRefs, and not on single dataRef/tract/patch.
215 This class transforms the process arguments generated by the ArgumentParser
216 into the arguments expected by FgcmBuildStarsTask.run(). This runner does
217 not use any parallelization.
218 """
219 @staticmethod
220 def getTargetList(parsedCmd):
221 """
222 Return a list with one element: a tuple with the butler and
223 list of dataRefs
224 """
225 # we want to combine the butler with any (or no!) dataRefs
226 return [(parsedCmd.butler, parsedCmd.id.refList)]
228 def __call__(self, args):
229 """
230 Parameters
231 ----------
232 args: `tuple` with (butler, dataRefList)
234 Returns
235 -------
236 exitStatus: `list` with `lsst.pipe.base.Struct`
237 exitStatus (0: success; 1: failure)
238 """
239 butler, dataRefList = args
241 task = self.TaskClass(config=self.config, log=self.log)
243 exitStatus = 0
244 if self.doRaise:
245 task.runDataRef(butler, dataRefList)
246 else:
247 try:
248 task.runDataRef(butler, dataRefList)
249 except Exception as e:
250 exitStatus = 1
251 task.log.fatal("Failed: %s" % e)
252 if not isinstance(e, pipeBase.TaskError):
253 traceback.print_exc(file=sys.stderr)
255 task.writeMetadata(butler)
257 # The task does not return any results:
258 return [pipeBase.Struct(exitStatus=exitStatus)]
260 def run(self, parsedCmd):
261 """
262 Run the task, with no multiprocessing
264 Parameters
265 ----------
266 parsedCmd: `lsst.pipe.base.ArgumentParser` parsed command line
267 """
269 resultList = []
271 if self.precall(parsedCmd):
272 targetList = self.getTargetList(parsedCmd)
273 resultList = self(targetList[0])
275 return resultList
278class FgcmBuildStarsBaseTask(pipeBase.PipelineTask, pipeBase.CmdLineTask, abc.ABC):
279 """
280 Base task to build stars for FGCM global calibration
282 Parameters
283 ----------
284 butler : `lsst.daf.persistence.Butler`
285 """
286 def __init__(self, butler=None, initInputs=None, **kwargs):
287 super().__init__(**kwargs)
289 self.makeSubtask("sourceSelector")
290 # Only log warning and fatal errors from the sourceSelector
291 self.sourceSelector.log.setLevel(self.sourceSelector.log.WARN)
293 # no saving of metadata for now
294 def _getMetadataName(self):
295 return None
297 @pipeBase.timeMethod
298 def runDataRef(self, butler, dataRefs):
299 """
300 Cross-match and make star list for FGCM Input
302 Parameters
303 ----------
304 butler: `lsst.daf.persistence.Butler`
305 dataRefs: `list` of `lsst.daf.persistence.ButlerDataRef`
306 Source data references for the input visits.
308 Raises
309 ------
310 RuntimeErrror: Raised if `config.doReferenceMatches` is set and
311 an fgcmLookUpTable is not available, or if computeFluxApertureRadius()
312 fails if the calibFlux is not a CircularAperture flux.
313 """
314 datasetType = dataRefs[0].butlerSubset.datasetType
315 self.log.info("Running with %d %s dataRefs", len(dataRefs), datasetType)
317 if self.config.doReferenceMatches:
318 self.makeSubtask("fgcmLoadReferenceCatalog", butler=butler)
319 # Ensure that we have a LUT
320 if not butler.datasetExists('fgcmLookUpTable'):
321 raise RuntimeError("Must have fgcmLookUpTable if using config.doReferenceMatches")
322 # Compute aperture radius if necessary. This is useful to do now before
323 # any heavy lifting has happened (fail early).
324 calibFluxApertureRadius = None
325 if self.config.doSubtractLocalBackground:
326 try:
327 calibFluxApertureRadius = computeApertureRadiusFromDataRef(dataRefs[0],
328 self.config.instFluxField)
329 except RuntimeError as e:
330 raise RuntimeError("Could not determine aperture radius from %s. "
331 "Cannot use doSubtractLocalBackground." %
332 (self.config.instFluxField)) from e
334 camera = butler.get('camera')
335 groupedDataRefs = self._findAndGroupDataRefs(camera, dataRefs, butler=butler)
337 # Make the visit catalog if necessary
338 # First check if the visit catalog is in the _current_ path
339 # We cannot use Gen2 datasetExists() because that checks all parent
340 # directories as well, which would make recovering from faults
341 # and fgcmcal reruns impossible.
342 visitCatDataRef = butler.dataRef('fgcmVisitCatalog')
343 filename = visitCatDataRef.get('fgcmVisitCatalog_filename')[0]
344 if os.path.exists(filename):
345 # This file exists and we should continue processing
346 inVisitCat = visitCatDataRef.get()
347 if len(inVisitCat) != len(groupedDataRefs):
348 raise RuntimeError("Existing visitCatalog found, but has an inconsistent "
349 "number of visits. Cannot continue.")
350 else:
351 inVisitCat = None
353 visitCat = self.fgcmMakeVisitCatalog(camera, groupedDataRefs,
354 visitCatDataRef=visitCatDataRef,
355 inVisitCat=inVisitCat)
357 # Persist the visitCat as a checkpoint file.
358 visitCatDataRef.put(visitCat)
360 starObsDataRef = butler.dataRef('fgcmStarObservations')
361 filename = starObsDataRef.get('fgcmStarObservations_filename')[0]
362 if os.path.exists(filename):
363 inStarObsCat = starObsDataRef.get()
364 else:
365 inStarObsCat = None
367 rad = calibFluxApertureRadius
368 sourceSchemaDataRef = butler.dataRef('src_schema')
369 fgcmStarObservationCat = self.fgcmMakeAllStarObservations(groupedDataRefs,
370 visitCat,
371 sourceSchemaDataRef,
372 camera,
373 calibFluxApertureRadius=rad,
374 starObsDataRef=starObsDataRef,
375 visitCatDataRef=visitCatDataRef,
376 inStarObsCat=inStarObsCat)
377 visitCatDataRef.put(visitCat)
378 starObsDataRef.put(fgcmStarObservationCat)
380 # Always do the matching.
381 if self.config.doReferenceMatches:
382 lutDataRef = butler.dataRef('fgcmLookUpTable')
383 else:
384 lutDataRef = None
385 fgcmStarIdCat, fgcmStarIndicesCat, fgcmRefCat = self.fgcmMatchStars(visitCat,
386 fgcmStarObservationCat,
387 lutDataRef=lutDataRef)
389 # Persist catalogs via the butler
390 butler.put(fgcmStarIdCat, 'fgcmStarIds')
391 butler.put(fgcmStarIndicesCat, 'fgcmStarIndices')
392 if fgcmRefCat is not None:
393 butler.put(fgcmRefCat, 'fgcmReferenceStars')
395 @abc.abstractmethod
396 def _findAndGroupDataRefs(self, camera, dataRefs, butler=None, calexpDataRefDict=None):
397 """
398 Find and group dataRefs (by visit). For Gen2 usage, set butler, and for
399 Gen3, use calexpDataRefDict
401 Parameters
402 ----------
403 camera : `lsst.afw.cameraGeom.Camera`
404 Camera from the butler.
405 dataRefs : `list` of `lsst.daf.persistence.ButlerDataRef` or
406 `lsst.daf.butler.DeferredDatasetHandle`
407 Data references for the input visits.
408 butler : `lsst.daf.persistence.Butler`, optional
409 Gen2 butler when used as CommandLineTask
410 calexpDataRefDict : `dict`, optional
411 Dictionary of Gen3 deferred data refs for calexps
413 Returns
414 -------
415 groupedDataRefs : `OrderedDict` [`int`, `list`]
416 Dictionary with sorted visit keys, and `list`s of
417 `lsst.daf.persistence.ButlerDataRef` or
418 `lsst.daf.butler.DeferredDatasetHandle`
420 Raises
421 ------
422 RuntimeError : Raised if neither or both of butler and dataRefDict are set.
423 """
424 raise NotImplementedError("_findAndGroupDataRefs not implemented.")
426 @abc.abstractmethod
427 def fgcmMakeAllStarObservations(self, groupedDataRefs, visitCat,
428 sourceSchemaDataRef,
429 camera,
430 calibFluxApertureRadius=None,
431 visitCatDataRef=None,
432 starObsDataRef=None,
433 inStarObsCat=None):
434 """
435 Compile all good star observations from visits in visitCat. Checkpoint files
436 will be stored if both visitCatDataRef and starObsDataRef are not None.
438 Parameters
439 ----------
440 groupedDataRefs: `dict` of `list`s
441 Lists of `~lsst.daf.persistence.ButlerDataRef` or
442 `~lsst.daf.butler.DeferredDatasetHandle`, grouped by visit.
443 visitCat: `~afw.table.BaseCatalog`
444 Catalog with visit data for FGCM
445 sourceSchemaDataRef: `~lsst.daf.persistence.ButlerDataRef` or
446 `~lsst.daf.butler.DeferredDatasetHandle`
447 DataRef for the schema of the src catalogs.
448 camera: `~lsst.afw.cameraGeom.Camera`
449 calibFluxApertureRadius: `float`, optional
450 Aperture radius for calibration flux.
451 visitCatDataRef: `~lsst.daf.persistence.ButlerDataRef`, optional
452 Dataref to write visitCat for checkpoints
453 starObsDataRef: `~lsst.daf.persistence.ButlerDataRef`, optional
454 Dataref to write the star observation catalog for checkpoints.
455 inStarObsCat: `~afw.table.BaseCatalog`
456 Input observation catalog. If this is incomplete, observations
457 will be appended from when it was cut off.
459 Returns
460 -------
461 fgcmStarObservations: `afw.table.BaseCatalog`
462 Full catalog of good observations.
464 Raises
465 ------
466 RuntimeError: Raised if doSubtractLocalBackground is True and
467 calibFluxApertureRadius is not set.
468 """
469 raise NotImplementedError("fgcmMakeAllStarObservations not implemented.")
471 def fgcmMakeVisitCatalog(self, camera, groupedDataRefs, bkgDataRefDict=None,
472 visitCatDataRef=None, inVisitCat=None):
473 """
474 Make a visit catalog with all the keys from each visit
476 Parameters
477 ----------
478 camera: `lsst.afw.cameraGeom.Camera`
479 Camera from the butler
480 groupedDataRefs: `dict`
481 Dictionary with visit keys, and `list`s of
482 `lsst.daf.persistence.ButlerDataRef`
483 bkgDataRefDict: `dict`, optional
484 Dictionary of gen3 dataRefHandles for background info.
485 visitCatDataRef: `lsst.daf.persistence.ButlerDataRef`, optional
486 Dataref to write visitCat for checkpoints
487 inVisitCat: `afw.table.BaseCatalog`, optional
488 Input (possibly incomplete) visit catalog
490 Returns
491 -------
492 visitCat: `afw.table.BaseCatalog`
493 """
495 self.log.info("Assembling visitCatalog from %d %ss" %
496 (len(groupedDataRefs), self.config.visitDataRefName))
498 nCcd = len(camera)
500 if inVisitCat is None:
501 schema = self._makeFgcmVisitSchema(nCcd)
503 visitCat = afwTable.BaseCatalog(schema)
504 visitCat.reserve(len(groupedDataRefs))
505 visitCat.resize(len(groupedDataRefs))
507 visitCat['visit'] = list(groupedDataRefs.keys())
508 visitCat['used'] = 0
509 visitCat['sources_read'] = False
510 else:
511 visitCat = inVisitCat
513 # No matter what, fill the catalog. This will check if it was
514 # already read.
515 self._fillVisitCatalog(visitCat, groupedDataRefs,
516 bkgDataRefDict=bkgDataRefDict,
517 visitCatDataRef=visitCatDataRef)
519 return visitCat
521 def _fillVisitCatalog(self, visitCat, groupedDataRefs, bkgDataRefDict=None,
522 visitCatDataRef=None):
523 """
524 Fill the visit catalog with visit metadata
526 Parameters
527 ----------
528 visitCat: `afw.table.BaseCatalog`
529 Catalog with schema from _makeFgcmVisitSchema()
530 groupedDataRefs: `dict`
531 Dictionary with visit keys, and `list`s of
532 `lsst.daf.persistence.ButlerDataRef`
533 visitCatDataRef: `lsst.daf.persistence.ButlerDataRef`, optional
534 Dataref to write visitCat for checkpoints
535 bkgDataRefDict: `dict`, optional
536 Dictionary of gen3 dataRefHandles for background info. FIXME
537 """
538 bbox = geom.BoxI(geom.PointI(0, 0), geom.PointI(1, 1))
540 for i, visit in enumerate(groupedDataRefs):
541 # We don't use the bypasses since we need the psf info which does
542 # not have a bypass
543 # TODO: When DM-15500 is implemented in the Gen3 Butler, this
544 # can be fixed
546 # Do not read those that have already been read
547 if visitCat['used'][i]:
548 continue
550 if (i % self.config.nVisitsPerCheckpoint) == 0:
551 self.log.info("Retrieving metadata for %s %d (%d/%d)" %
552 (self.config.visitDataRefName, visit, i, len(groupedDataRefs)))
553 # Save checkpoint if desired
554 if visitCatDataRef is not None:
555 visitCatDataRef.put(visitCat)
557 # Note that the reference ccd is first in the list (if available).
559 # The first dataRef in the group will be the reference ccd (if available)
560 dataRef = groupedDataRefs[visit][0]
561 if isinstance(dataRef, dafPersist.ButlerDataRef):
562 exp = dataRef.get(datasetType='calexp_sub', bbox=bbox)
563 visitInfo = exp.getInfo().getVisitInfo()
564 label = dataRef.get(datasetType='calexp_filterLabel')
565 physicalFilter = label.physicalLabel
566 psf = exp.getPsf()
567 else:
568 visitInfo = dataRef.get(component='visitInfo')
569 # TODO: When DM-28583 is fixed we can get the filterLabel
570 # via dataRef.get(component='filterLabel')
571 physicalFilter = dataRef.dataId['physical_filter']
572 psf = dataRef.get(component='psf')
574 rec = visitCat[i]
575 rec['visit'] = visit
576 rec['physicalFilter'] = physicalFilter
577 # TODO DM-26991: when gen2 is removed, gen3 workflow will make it
578 # much easier to get the wcs's necessary to recompute the pointing
579 # ra/dec at the center of the camera.
580 radec = visitInfo.getBoresightRaDec()
581 rec['telra'] = radec.getRa().asDegrees()
582 rec['teldec'] = radec.getDec().asDegrees()
583 rec['telha'] = visitInfo.getBoresightHourAngle().asDegrees()
584 rec['telrot'] = visitInfo.getBoresightRotAngle().asDegrees()
585 rec['mjd'] = visitInfo.getDate().get(system=DateTime.MJD)
586 rec['exptime'] = visitInfo.getExposureTime()
587 # convert from Pa to millibar
588 # Note that I don't know if this unit will need to be per-camera config
589 rec['pmb'] = visitInfo.getWeather().getAirPressure() / 100
590 # Flag to signify if this is a "deep" field. Not currently used
591 rec['deepFlag'] = 0
592 # Relative flat scaling (1.0 means no relative scaling)
593 rec['scaling'][:] = 1.0
594 # Median delta aperture, to be measured from stars
595 rec['deltaAper'] = 0.0
597 rec['psfSigma'] = psf.computeShape().getDeterminantRadius()
599 if self.config.doModelErrorsWithBackground:
600 foundBkg = False
601 if isinstance(dataRef, dafPersist.ButlerDataRef):
602 det = dataRef.dataId[self.config.ccdDataRefName]
603 if dataRef.datasetExists(datasetType='calexpBackground'):
604 bgList = dataRef.get(datasetType='calexpBackground')
605 foundBkg = True
606 else:
607 det = dataRef.dataId.byName()['detector']
608 try:
609 bkgRef = bkgDataRefDict[(visit, det)]
610 bgList = bkgRef.get()
611 foundBkg = True
612 except KeyError:
613 pass
615 if foundBkg:
616 bgStats = (bg[0].getStatsImage().getImage().array
617 for bg in bgList)
618 rec['skyBackground'] = sum(np.median(bg[np.isfinite(bg)]) for bg in bgStats)
619 else:
620 self.log.warn('Sky background not found for visit %d / ccd %d' %
621 (visit, det))
622 rec['skyBackground'] = -1.0
623 else:
624 rec['skyBackground'] = -1.0
626 rec['used'] = 1
628 def _makeSourceMapper(self, sourceSchema):
629 """
630 Make a schema mapper for fgcm sources
632 Parameters
633 ----------
634 sourceSchema: `afwTable.Schema`
635 Default source schema from the butler
637 Returns
638 -------
639 sourceMapper: `afwTable.schemaMapper`
640 Mapper to the FGCM source schema
641 """
643 # create a mapper to the preferred output
644 sourceMapper = afwTable.SchemaMapper(sourceSchema)
646 # map to ra/dec
647 sourceMapper.addMapping(sourceSchema['coord_ra'].asKey(), 'ra')
648 sourceMapper.addMapping(sourceSchema['coord_dec'].asKey(), 'dec')
649 sourceMapper.addMapping(sourceSchema['slot_Centroid_x'].asKey(), 'x')
650 sourceMapper.addMapping(sourceSchema['slot_Centroid_y'].asKey(), 'y')
651 # Add the mapping if the field exists in the input catalog.
652 # If the field does not exist, simply add it (set to False).
653 # This field is not required for calibration, but is useful
654 # to collate if available.
655 try:
656 sourceMapper.addMapping(sourceSchema[self.config.psfCandidateName].asKey(),
657 'psf_candidate')
658 except LookupError:
659 sourceMapper.editOutputSchema().addField(
660 "psf_candidate", type='Flag',
661 doc=("Flag set if the source was a candidate for PSF determination, "
662 "as determined by the star selector."))
664 # and add the fields we want
665 sourceMapper.editOutputSchema().addField(
666 "visit", type=np.int32, doc="Visit number")
667 sourceMapper.editOutputSchema().addField(
668 "ccd", type=np.int32, doc="CCD number")
669 sourceMapper.editOutputSchema().addField(
670 "instMag", type=np.float32, doc="Instrumental magnitude")
671 sourceMapper.editOutputSchema().addField(
672 "instMagErr", type=np.float32, doc="Instrumental magnitude error")
673 sourceMapper.editOutputSchema().addField(
674 "jacobian", type=np.float32, doc="Relative pixel scale from wcs jacobian")
675 sourceMapper.editOutputSchema().addField(
676 "deltaMagBkg", type=np.float32, doc="Change in magnitude due to local background offset")
678 return sourceMapper
680 def fgcmMatchStars(self, visitCat, obsCat, lutDataRef=None):
681 """
682 Use FGCM code to match observations into unique stars.
684 Parameters
685 ----------
686 visitCat: `afw.table.BaseCatalog`
687 Catalog with visit data for fgcm
688 obsCat: `afw.table.BaseCatalog`
689 Full catalog of star observations for fgcm
690 lutDataRef: `lsst.daf.persistence.ButlerDataRef` or
691 `lsst.daf.butler.DeferredDatasetHandle`, optional
692 Data reference to fgcm look-up table (used if matching reference stars).
694 Returns
695 -------
696 fgcmStarIdCat: `afw.table.BaseCatalog`
697 Catalog of unique star identifiers and index keys
698 fgcmStarIndicesCat: `afwTable.BaseCatalog`
699 Catalog of unique star indices
700 fgcmRefCat: `afw.table.BaseCatalog`
701 Catalog of matched reference stars.
702 Will be None if `config.doReferenceMatches` is False.
703 """
704 # get filter names into a numpy array...
705 # This is the type that is expected by the fgcm code
706 visitFilterNames = np.zeros(len(visitCat), dtype='a30')
707 for i in range(len(visitCat)):
708 visitFilterNames[i] = visitCat[i]['physicalFilter']
710 # match to put filterNames with observations
711 visitIndex = np.searchsorted(visitCat['visit'],
712 obsCat['visit'])
714 obsFilterNames = visitFilterNames[visitIndex]
716 if self.config.doReferenceMatches:
717 # Get the reference filter names, using the LUT
718 lutCat = lutDataRef.get()
720 stdFilterDict = {filterName: stdFilter for (filterName, stdFilter) in
721 zip(lutCat[0]['physicalFilters'].split(','),
722 lutCat[0]['stdPhysicalFilters'].split(','))}
723 stdLambdaDict = {stdFilter: stdLambda for (stdFilter, stdLambda) in
724 zip(lutCat[0]['stdPhysicalFilters'].split(','),
725 lutCat[0]['lambdaStdFilter'])}
727 del lutCat
729 referenceFilterNames = self._getReferenceFilterNames(visitCat,
730 stdFilterDict,
731 stdLambdaDict)
732 self.log.info("Using the following reference filters: %s" %
733 (', '.join(referenceFilterNames)))
735 else:
736 # This should be an empty list
737 referenceFilterNames = []
739 # make the fgcm starConfig dict
740 starConfig = {'logger': self.log,
741 'filterToBand': self.config.physicalFilterMap,
742 'requiredBands': self.config.requiredBands,
743 'minPerBand': self.config.minPerBand,
744 'matchRadius': self.config.matchRadius,
745 'isolationRadius': self.config.isolationRadius,
746 'matchNSide': self.config.matchNside,
747 'coarseNSide': self.config.coarseNside,
748 'densNSide': self.config.densityCutNside,
749 'densMaxPerPixel': self.config.densityCutMaxPerPixel,
750 'primaryBands': self.config.primaryBands,
751 'referenceFilterNames': referenceFilterNames}
753 # initialize the FgcmMakeStars object
754 fgcmMakeStars = fgcm.FgcmMakeStars(starConfig)
756 # make the primary stars
757 # note that the ra/dec native Angle format is radians
758 # We determine the conversion from the native units (typically
759 # radians) to degrees for the first observation. This allows us
760 # to treate ra/dec as numpy arrays rather than Angles, which would
761 # be approximately 600x slower.
762 conv = obsCat[0]['ra'].asDegrees() / float(obsCat[0]['ra'])
763 fgcmMakeStars.makePrimaryStars(obsCat['ra'] * conv,
764 obsCat['dec'] * conv,
765 filterNameArray=obsFilterNames,
766 bandSelected=False)
768 # and match all the stars
769 fgcmMakeStars.makeMatchedStars(obsCat['ra'] * conv,
770 obsCat['dec'] * conv,
771 obsFilterNames)
773 if self.config.doReferenceMatches:
774 fgcmMakeStars.makeReferenceMatches(self.fgcmLoadReferenceCatalog)
776 # now persist
778 objSchema = self._makeFgcmObjSchema()
780 # make catalog and records
781 fgcmStarIdCat = afwTable.BaseCatalog(objSchema)
782 fgcmStarIdCat.reserve(fgcmMakeStars.objIndexCat.size)
783 for i in range(fgcmMakeStars.objIndexCat.size):
784 fgcmStarIdCat.addNew()
786 # fill the catalog
787 fgcmStarIdCat['fgcm_id'][:] = fgcmMakeStars.objIndexCat['fgcm_id']
788 fgcmStarIdCat['ra'][:] = fgcmMakeStars.objIndexCat['ra']
789 fgcmStarIdCat['dec'][:] = fgcmMakeStars.objIndexCat['dec']
790 fgcmStarIdCat['obsArrIndex'][:] = fgcmMakeStars.objIndexCat['obsarrindex']
791 fgcmStarIdCat['nObs'][:] = fgcmMakeStars.objIndexCat['nobs']
793 obsSchema = self._makeFgcmObsSchema()
795 fgcmStarIndicesCat = afwTable.BaseCatalog(obsSchema)
796 fgcmStarIndicesCat.reserve(fgcmMakeStars.obsIndexCat.size)
797 for i in range(fgcmMakeStars.obsIndexCat.size):
798 fgcmStarIndicesCat.addNew()
800 fgcmStarIndicesCat['obsIndex'][:] = fgcmMakeStars.obsIndexCat['obsindex']
802 if self.config.doReferenceMatches:
803 refSchema = self._makeFgcmRefSchema(len(referenceFilterNames))
805 fgcmRefCat = afwTable.BaseCatalog(refSchema)
806 fgcmRefCat.reserve(fgcmMakeStars.referenceCat.size)
808 for i in range(fgcmMakeStars.referenceCat.size):
809 fgcmRefCat.addNew()
811 fgcmRefCat['fgcm_id'][:] = fgcmMakeStars.referenceCat['fgcm_id']
812 fgcmRefCat['refMag'][:, :] = fgcmMakeStars.referenceCat['refMag']
813 fgcmRefCat['refMagErr'][:, :] = fgcmMakeStars.referenceCat['refMagErr']
815 md = PropertyList()
816 md.set("REFSTARS_FORMAT_VERSION", REFSTARS_FORMAT_VERSION)
817 md.set("FILTERNAMES", referenceFilterNames)
818 fgcmRefCat.setMetadata(md)
820 else:
821 fgcmRefCat = None
823 return fgcmStarIdCat, fgcmStarIndicesCat, fgcmRefCat
825 def _makeFgcmVisitSchema(self, nCcd):
826 """
827 Make a schema for an fgcmVisitCatalog
829 Parameters
830 ----------
831 nCcd: `int`
832 Number of CCDs in the camera
834 Returns
835 -------
836 schema: `afwTable.Schema`
837 """
839 schema = afwTable.Schema()
840 schema.addField('visit', type=np.int32, doc="Visit number")
841 schema.addField('physicalFilter', type=str, size=30, doc="Physical filter")
842 schema.addField('telra', type=np.float64, doc="Pointing RA (deg)")
843 schema.addField('teldec', type=np.float64, doc="Pointing Dec (deg)")
844 schema.addField('telha', type=np.float64, doc="Pointing Hour Angle (deg)")
845 schema.addField('telrot', type=np.float64, doc="Camera rotation (deg)")
846 schema.addField('mjd', type=np.float64, doc="MJD of visit")
847 schema.addField('exptime', type=np.float32, doc="Exposure time")
848 schema.addField('pmb', type=np.float32, doc="Pressure (millibar)")
849 schema.addField('psfSigma', type=np.float32, doc="PSF sigma (reference CCD)")
850 schema.addField('deltaAper', type=np.float32, doc="Delta-aperture")
851 schema.addField('skyBackground', type=np.float32, doc="Sky background (ADU) (reference CCD)")
852 # the following field is not used yet
853 schema.addField('deepFlag', type=np.int32, doc="Deep observation")
854 schema.addField('scaling', type='ArrayD', doc="Scaling applied due to flat adjustment",
855 size=nCcd)
856 schema.addField('used', type=np.int32, doc="This visit has been ingested.")
857 schema.addField('sources_read', type='Flag', doc="This visit had sources read.")
859 return schema
861 def _makeFgcmObjSchema(self):
862 """
863 Make a schema for the objIndexCat from fgcmMakeStars
865 Returns
866 -------
867 schema: `afwTable.Schema`
868 """
870 objSchema = afwTable.Schema()
871 objSchema.addField('fgcm_id', type=np.int32, doc='FGCM Unique ID')
872 # Will investigate making these angles...
873 objSchema.addField('ra', type=np.float64, doc='Mean object RA (deg)')
874 objSchema.addField('dec', type=np.float64, doc='Mean object Dec (deg)')
875 objSchema.addField('obsArrIndex', type=np.int32,
876 doc='Index in obsIndexTable for first observation')
877 objSchema.addField('nObs', type=np.int32, doc='Total number of observations')
879 return objSchema
881 def _makeFgcmObsSchema(self):
882 """
883 Make a schema for the obsIndexCat from fgcmMakeStars
885 Returns
886 -------
887 schema: `afwTable.Schema`
888 """
890 obsSchema = afwTable.Schema()
891 obsSchema.addField('obsIndex', type=np.int32, doc='Index in observation table')
893 return obsSchema
895 def _makeFgcmRefSchema(self, nReferenceBands):
896 """
897 Make a schema for the referenceCat from fgcmMakeStars
899 Parameters
900 ----------
901 nReferenceBands: `int`
902 Number of reference bands
904 Returns
905 -------
906 schema: `afwTable.Schema`
907 """
909 refSchema = afwTable.Schema()
910 refSchema.addField('fgcm_id', type=np.int32, doc='FGCM Unique ID')
911 refSchema.addField('refMag', type='ArrayF', doc='Reference magnitude array (AB)',
912 size=nReferenceBands)
913 refSchema.addField('refMagErr', type='ArrayF', doc='Reference magnitude error array',
914 size=nReferenceBands)
916 return refSchema
918 def _getReferenceFilterNames(self, visitCat, stdFilterDict, stdLambdaDict):
919 """
920 Get the reference filter names, in wavelength order, from the visitCat and
921 information from the look-up-table.
923 Parameters
924 ----------
925 visitCat: `afw.table.BaseCatalog`
926 Catalog with visit data for FGCM
927 stdFilterDict: `dict`
928 Mapping of filterName to stdFilterName from LUT
929 stdLambdaDict: `dict`
930 Mapping of stdFilterName to stdLambda from LUT
932 Returns
933 -------
934 referenceFilterNames: `list`
935 Wavelength-ordered list of reference filter names
936 """
938 # Find the unique list of filter names in visitCat
939 filterNames = np.unique(visitCat.asAstropy()['physicalFilter'])
941 # Find the unique list of "standard" filters
942 stdFilterNames = {stdFilterDict[filterName] for filterName in filterNames}
944 # And sort these by wavelength
945 referenceFilterNames = sorted(stdFilterNames, key=stdLambdaDict.get)
947 return referenceFilterNames