21 """Base class for BuildStars using src tables or sourceTable_visit tables.
31 import lsst.daf.persistence
as dafPersist
32 import lsst.pex.config
as pexConfig
33 import lsst.pipe.base
as pipeBase
34 import lsst.afw.table
as afwTable
35 import lsst.geom
as geom
36 from lsst.daf.base
import PropertyList
37 from lsst.daf.base.dateTime
import DateTime
38 from lsst.meas.algorithms.sourceSelector
import sourceSelectorRegistry
40 from .utilities
import computeApertureRadiusFromDataRef
41 from .fgcmLoadReferenceCatalog
import FgcmLoadReferenceCatalogTask
45 REFSTARS_FORMAT_VERSION = 1
47 __all__ = [
'FgcmBuildStarsConfigBase',
'FgcmBuildStarsRunner',
'FgcmBuildStarsBaseTask']
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"),
57 default=
'slot_CalibFlux_instFlux',
59 minPerBand = pexConfig.Field(
60 doc=
"Minimum observations per band",
64 matchRadius = pexConfig.Field(
65 doc=
"Match radius (arcseconds)",
69 isolationRadius = pexConfig.Field(
70 doc=
"Isolation radius (arcseconds)",
74 densityCutNside = pexConfig.Field(
75 doc=
"Density cut healpix nside",
79 densityCutMaxPerPixel = pexConfig.Field(
80 doc=
"Density cut number of stars per pixel",
84 randomSeed = pexConfig.Field(
85 doc=
"Random seed for high density down-sampling.",
90 matchNside = pexConfig.Field(
91 doc=
"Healpix Nside for matching",
95 coarseNside = pexConfig.Field(
96 doc=
"Healpix coarse Nside for partitioning matches",
103 physicalFilterMap = pexConfig.DictField(
104 doc=
"Mapping from 'physicalFilter' to band.",
109 requiredBands = pexConfig.ListField(
110 doc=
"Bands required for each star",
114 primaryBands = pexConfig.ListField(
115 doc=(
"Bands for 'primary' star matches. "
116 "A star must be observed in one of these bands to be considered "
117 "as a calibration star."),
121 visitDataRefName = pexConfig.Field(
122 doc=
"dataRef name for the 'visit' field, usually 'visit'.",
126 ccdDataRefName = pexConfig.Field(
127 doc=
"dataRef name for the 'ccd' field, usually 'ccd' or 'detector'.",
131 doApplyWcsJacobian = pexConfig.Field(
132 doc=
"Apply the jacobian of the WCS to the star observations prior to fit?",
136 doModelErrorsWithBackground = pexConfig.Field(
137 doc=
"Model flux errors with background term?",
141 psfCandidateName = pexConfig.Field(
142 doc=
"Name of field with psf candidate flag for propagation",
144 default=
"calib_psf_candidate"
146 doSubtractLocalBackground = pexConfig.Field(
147 doc=(
"Subtract the local background before performing calibration? "
148 "This is only supported for circular aperture calibration fluxes."),
152 localBackgroundFluxField = pexConfig.Field(
153 doc=
"Full name of the local background instFlux field to use.",
155 default=
'base_LocalBackground_instFlux'
157 sourceSelector = sourceSelectorRegistry.makeField(
158 doc=
"How to select sources",
161 apertureInnerInstFluxField = pexConfig.Field(
162 doc=(
"Full name of instFlux field that contains inner aperture "
163 "flux for aperture correction proxy"),
165 default=
'base_CircularApertureFlux_12_0_instFlux'
167 apertureOuterInstFluxField = pexConfig.Field(
168 doc=(
"Full name of instFlux field that contains outer aperture "
169 "flux for aperture correction proxy"),
171 default=
'base_CircularApertureFlux_17_0_instFlux'
173 doReferenceMatches = pexConfig.Field(
174 doc=
"Match reference catalog as additional constraint on calibration",
178 fgcmLoadReferenceCatalog = pexConfig.ConfigurableField(
179 target=FgcmLoadReferenceCatalogTask,
180 doc=
"FGCM reference object loader",
182 nVisitsPerCheckpoint = pexConfig.Field(
183 doc=
"Number of visits read between checkpoints",
190 sourceSelector.setDefaults()
192 sourceSelector.doFlags =
True
193 sourceSelector.doUnresolved =
True
194 sourceSelector.doSignalToNoise =
True
195 sourceSelector.doIsolated =
True
197 sourceSelector.signalToNoise.minimum = 10.0
198 sourceSelector.signalToNoise.maximum = 1000.0
202 sourceSelector.unresolved.maximum = 0.5
206 """Subclass of TaskRunner for FgcmBuildStars tasks
208 fgcmBuildStarsTask.run() and fgcmBuildStarsTableTask.run() take a number of
209 arguments, one of which is the butler (for persistence and mapper data),
210 and a list of dataRefs extracted from the command line. Note that FGCM
211 runs on a large set of dataRefs, and not on single dataRef/tract/patch.
212 This class transforms the process arguments generated by the ArgumentParser
213 into the arguments expected by FgcmBuildStarsTask.run(). This runner does
214 not use any parallelization.
219 Return a list with one element: a tuple with the butler and
223 return [(parsedCmd.butler, parsedCmd.id.refList)]
229 args: `tuple` with (butler, dataRefList)
233 exitStatus: `list` with `lsst.pipe.base.Struct`
234 exitStatus (0: success; 1: failure)
236 butler, dataRefList = args
238 task = self.TaskClass(config=self.config, log=self.log)
242 task.runDataRef(butler, dataRefList)
245 task.runDataRef(butler, dataRefList)
246 except Exception
as e:
248 task.log.fatal(
"Failed: %s" % e)
249 if not isinstance(e, pipeBase.TaskError):
250 traceback.print_exc(file=sys.stderr)
252 task.writeMetadata(butler)
255 return [pipeBase.Struct(exitStatus=exitStatus)]
259 Run the task, with no multiprocessing
263 parsedCmd: `lsst.pipe.base.ArgumentParser` parsed command line
268 if self.precall(parsedCmd):
270 resultList = self(targetList[0])
277 Base task to build stars for FGCM global calibration
281 butler : `lsst.daf.persistence.Butler`
283 def __init__(self, initInputs=None, butler=None, **kwargs):
286 self.makeSubtask(
"sourceSelector")
288 self.sourceSelector.log.setLevel(self.sourceSelector.log.WARN)
291 def _getMetadataName(self):
297 Cross-match and make star list for FGCM Input
301 butler: `lsst.daf.persistence.Butler`
302 dataRefs: `list` of `lsst.daf.persistence.ButlerDataRef`
303 Source data references for the input visits.
307 RuntimeErrror: Raised if `config.doReferenceMatches` is set and
308 an fgcmLookUpTable is not available, or if computeFluxApertureRadius()
309 fails if the calibFlux is not a CircularAperture flux.
311 datasetType = dataRefs[0].butlerSubset.datasetType
312 self.log.info(
"Running with %d %s dataRefs", len(dataRefs), datasetType)
314 if self.config.doReferenceMatches:
315 self.makeSubtask(
"fgcmLoadReferenceCatalog", butler=butler)
317 if not butler.datasetExists(
'fgcmLookUpTable'):
318 raise RuntimeError(
"Must have fgcmLookUpTable if using config.doReferenceMatches")
321 calibFluxApertureRadius =
None
322 if self.config.doSubtractLocalBackground:
325 self.config.instFluxField)
326 except RuntimeError
as e:
327 raise RuntimeError(
"Could not determine aperture radius from %s. "
328 "Cannot use doSubtractLocalBackground." %
329 (self.config.instFluxField))
from e
331 camera = butler.get(
'camera')
339 visitCatDataRef = butler.dataRef(
'fgcmVisitCatalog')
340 filename = visitCatDataRef.get(
'fgcmVisitCatalog_filename')[0]
341 if os.path.exists(filename):
343 inVisitCat = visitCatDataRef.get()
344 if len(inVisitCat) != len(groupedDataRefs):
345 raise RuntimeError(
"Existing visitCatalog found, but has an inconsistent "
346 "number of visits. Cannot continue.")
351 visitCatDataRef=visitCatDataRef,
352 inVisitCat=inVisitCat)
355 visitCatDataRef.put(visitCat)
357 starObsDataRef = butler.dataRef(
'fgcmStarObservations')
358 filename = starObsDataRef.get(
'fgcmStarObservations_filename')[0]
359 if os.path.exists(filename):
360 inStarObsCat = starObsDataRef.get()
364 rad = calibFluxApertureRadius
365 sourceSchemaDataRef = butler.dataRef(
'src_schema')
366 sourceSchema = sourceSchemaDataRef.get(
'src_schema', immediate=
True).schema
371 calibFluxApertureRadius=rad,
372 starObsDataRef=starObsDataRef,
373 visitCatDataRef=visitCatDataRef,
374 inStarObsCat=inStarObsCat)
375 visitCatDataRef.put(visitCat)
376 starObsDataRef.put(fgcmStarObservationCat)
379 if self.config.doReferenceMatches:
380 lutDataRef = butler.dataRef(
'fgcmLookUpTable')
383 fgcmStarIdCat, fgcmStarIndicesCat, fgcmRefCat = self.
fgcmMatchStarsfgcmMatchStars(visitCat,
384 fgcmStarObservationCat,
385 lutDataRef=lutDataRef)
388 butler.put(fgcmStarIdCat,
'fgcmStarIds')
389 butler.put(fgcmStarIndicesCat,
'fgcmStarIndices')
390 if fgcmRefCat
is not None:
391 butler.put(fgcmRefCat,
'fgcmReferenceStars')
394 def _findAndGroupDataRefsGen2(self, butler, camera, dataRefs):
396 Find and group dataRefs (by visit); Gen2 only.
400 butler : `lsst.daf.persistence.Butler`
402 camera : `lsst.afw.cameraGeom.Camera`
403 Camera from the butler.
404 dataRefs : `list` of `lsst.daf.persistence.ButlerDataRef`
405 Data references for the input visits.
409 groupedDataRefs : `dict` [`int`, `list`]
410 Dictionary with sorted visit keys, and `list`s of
411 `lsst.daf.persistence.ButlerDataRef`
413 raise NotImplementedError(
"_findAndGroupDataRefsGen2 not implemented.")
419 calibFluxApertureRadius=None,
420 visitCatDataRef=None,
424 Compile all good star observations from visits in visitCat. Checkpoint files
425 will be stored if both visitCatDataRef and starObsDataRef are not None.
429 groupedDataRefs : `dict` of `list`s
430 Lists of `~lsst.daf.persistence.ButlerDataRef` or
431 `~lsst.daf.butler.DeferredDatasetHandle`, grouped by visit.
432 visitCat : `~afw.table.BaseCatalog`
433 Catalog with visit data for FGCM
434 sourceSchema : `~lsst.afw.table.Schema`
435 Schema for the input src catalogs.
436 camera : `~lsst.afw.cameraGeom.Camera`
437 calibFluxApertureRadius : `float`, optional
438 Aperture radius for calibration flux.
439 visitCatDataRef : `~lsst.daf.persistence.ButlerDataRef`, optional
440 Dataref to write visitCat for checkpoints
441 starObsDataRef : `~lsst.daf.persistence.ButlerDataRef`, optional
442 Dataref to write the star observation catalog for checkpoints.
443 inStarObsCat : `~afw.table.BaseCatalog`
444 Input observation catalog. If this is incomplete, observations
445 will be appended from when it was cut off.
449 fgcmStarObservations : `afw.table.BaseCatalog`
450 Full catalog of good observations.
454 RuntimeError: Raised if doSubtractLocalBackground is True and
455 calibFluxApertureRadius is not set.
457 raise NotImplementedError(
"fgcmMakeAllStarObservations not implemented.")
460 visitCatDataRef=None, inVisitCat=None):
462 Make a visit catalog with all the keys from each visit
466 camera: `lsst.afw.cameraGeom.Camera`
467 Camera from the butler
468 groupedDataRefs: `dict`
469 Dictionary with visit keys, and `list`s of
470 `lsst.daf.persistence.ButlerDataRef`
471 bkgDataRefDict: `dict`, optional
472 Dictionary of gen3 dataRefHandles for background info.
473 visitCatDataRef: `lsst.daf.persistence.ButlerDataRef`, optional
474 Dataref to write visitCat for checkpoints
475 inVisitCat: `afw.table.BaseCatalog`, optional
476 Input (possibly incomplete) visit catalog
480 visitCat: `afw.table.BaseCatalog`
483 self.log.info(
"Assembling visitCatalog from %d %ss" %
484 (len(groupedDataRefs), self.config.visitDataRefName))
488 if inVisitCat
is None:
491 visitCat = afwTable.BaseCatalog(schema)
492 visitCat.reserve(len(groupedDataRefs))
493 visitCat.resize(len(groupedDataRefs))
495 visitCat[
'visit'] = list(groupedDataRefs.keys())
497 visitCat[
'sources_read'] =
False
499 visitCat = inVisitCat
504 bkgDataRefDict=bkgDataRefDict,
505 visitCatDataRef=visitCatDataRef)
509 def _fillVisitCatalog(self, visitCat, groupedDataRefs, bkgDataRefDict=None,
510 visitCatDataRef=None):
512 Fill the visit catalog with visit metadata
516 visitCat : `afw.table.BaseCatalog`
517 Visit catalog. See _makeFgcmVisitSchema() for schema definition.
518 groupedDataRefs : `dict`
519 Dictionary with visit keys, and `list`s of
520 `lsst.daf.persistence.ButlerDataRef` or
521 `lsst.daf.butler.DeferredDatasetHandle`
522 visitCatDataRef : `lsst.daf.persistence.ButlerDataRef`, optional
523 Dataref to write ``visitCat`` for checkpoints. Gen2 only.
524 bkgDataRefDict : `dict`, optional
525 Dictionary of Gen3 `lsst.daf.butler.DeferredDatasetHandle`
528 bbox = geom.BoxI(geom.PointI(0, 0), geom.PointI(1, 1))
530 for i, visit
in enumerate(groupedDataRefs):
537 if visitCat[
'used'][i]:
540 if (i % self.config.nVisitsPerCheckpoint) == 0:
541 self.log.info(
"Retrieving metadata for %s %d (%d/%d)" %
542 (self.config.visitDataRefName, visit, i, len(groupedDataRefs)))
544 if visitCatDataRef
is not None:
545 visitCatDataRef.put(visitCat)
547 dataRef = groupedDataRefs[visit][0]
548 if isinstance(dataRef, dafPersist.ButlerDataRef):
551 exp = dataRef.get(datasetType=
'calexp_sub', bbox=bbox)
552 visitInfo = exp.getInfo().getVisitInfo()
553 label = dataRef.get(datasetType=
'calexp_filterLabel')
554 physicalFilter = label.physicalLabel
556 psfSigma = psf.computeShape().getDeterminantRadius()
559 summary = dataRef.get()
561 summaryRow = summary.find(self.config.referenceCCD)
562 if summaryRow
is None:
564 summaryRow = summary[0]
566 summaryDetector = summaryRow[
'id']
567 visitInfo = summaryRow.getVisitInfo()
568 physicalFilter = summaryRow[
'physical_filter']
570 goodSigma, = np.where(summary[
'psfSigma'] > 0)
571 if goodSigma.size > 2:
572 psfSigma = np.median(summary[
'psfSigma'][goodSigma])
574 psfSigma = np.mean(summary[
'psfSigma'][goodSigma])
580 rec[
'physicalFilter'] = physicalFilter
584 radec = visitInfo.getBoresightRaDec()
585 rec[
'telra'] = radec.getRa().asDegrees()
586 rec[
'teldec'] = radec.getDec().asDegrees()
587 rec[
'telha'] = visitInfo.getBoresightHourAngle().asDegrees()
588 rec[
'telrot'] = visitInfo.getBoresightRotAngle().asDegrees()
589 rec[
'mjd'] = visitInfo.getDate().get(system=DateTime.MJD)
590 rec[
'exptime'] = visitInfo.getExposureTime()
593 rec[
'pmb'] = visitInfo.getWeather().getAirPressure() / 100
597 rec[
'scaling'][:] = 1.0
599 rec[
'deltaAper'] = 0.0
600 rec[
'psfSigma'] = psfSigma
602 if self.config.doModelErrorsWithBackground:
604 if isinstance(dataRef, dafPersist.ButlerDataRef):
606 det = dataRef.dataId[self.config.ccdDataRefName]
607 if dataRef.datasetExists(datasetType=
'calexpBackground'):
608 bgList = dataRef.get(datasetType=
'calexpBackground')
614 bkgRef = bkgDataRefDict[(visit, summaryDetector)]
615 bgList = bkgRef.get()
621 bgStats = (bg[0].getStatsImage().getImage().array
623 rec[
'skyBackground'] = sum(np.median(bg[np.isfinite(bg)])
for bg
in bgStats)
625 self.log.warning(
'Sky background not found for visit %d / ccd %d' %
627 rec[
'skyBackground'] = -1.0
629 rec[
'skyBackground'] = -1.0
633 def _makeSourceMapper(self, sourceSchema):
635 Make a schema mapper for fgcm sources
639 sourceSchema: `afwTable.Schema`
640 Default source schema from the butler
644 sourceMapper: `afwTable.schemaMapper`
645 Mapper to the FGCM source schema
649 sourceMapper = afwTable.SchemaMapper(sourceSchema)
652 sourceMapper.addMapping(sourceSchema[
'coord_ra'].asKey(),
'ra')
653 sourceMapper.addMapping(sourceSchema[
'coord_dec'].asKey(),
'dec')
654 sourceMapper.addMapping(sourceSchema[
'slot_Centroid_x'].asKey(),
'x')
655 sourceMapper.addMapping(sourceSchema[
'slot_Centroid_y'].asKey(),
'y')
661 sourceMapper.addMapping(sourceSchema[self.config.psfCandidateName].asKey(),
664 sourceMapper.editOutputSchema().addField(
665 "psf_candidate", type=
'Flag',
666 doc=(
"Flag set if the source was a candidate for PSF determination, "
667 "as determined by the star selector."))
670 sourceMapper.editOutputSchema().addField(
671 "visit", type=np.int32, doc=
"Visit number")
672 sourceMapper.editOutputSchema().addField(
673 "ccd", type=np.int32, doc=
"CCD number")
674 sourceMapper.editOutputSchema().addField(
675 "instMag", type=np.float32, doc=
"Instrumental magnitude")
676 sourceMapper.editOutputSchema().addField(
677 "instMagErr", type=np.float32, doc=
"Instrumental magnitude error")
678 sourceMapper.editOutputSchema().addField(
679 "jacobian", type=np.float32, doc=
"Relative pixel scale from wcs jacobian")
680 sourceMapper.editOutputSchema().addField(
681 "deltaMagBkg", type=np.float32, doc=
"Change in magnitude due to local background offset")
687 Use FGCM code to match observations into unique stars.
691 visitCat: `afw.table.BaseCatalog`
692 Catalog with visit data for fgcm
693 obsCat: `afw.table.BaseCatalog`
694 Full catalog of star observations for fgcm
695 lutDataRef: `lsst.daf.persistence.ButlerDataRef` or
696 `lsst.daf.butler.DeferredDatasetHandle`, optional
697 Data reference to fgcm look-up table (used if matching reference stars).
701 fgcmStarIdCat: `afw.table.BaseCatalog`
702 Catalog of unique star identifiers and index keys
703 fgcmStarIndicesCat: `afwTable.BaseCatalog`
704 Catalog of unique star indices
705 fgcmRefCat: `afw.table.BaseCatalog`
706 Catalog of matched reference stars.
707 Will be None if `config.doReferenceMatches` is False.
711 visitFilterNames = np.zeros(len(visitCat), dtype=
'a30')
712 for i
in range(len(visitCat)):
713 visitFilterNames[i] = visitCat[i][
'physicalFilter']
716 visitIndex = np.searchsorted(visitCat[
'visit'],
719 obsFilterNames = visitFilterNames[visitIndex]
721 if self.config.doReferenceMatches:
723 lutCat = lutDataRef.get()
725 stdFilterDict = {filterName: stdFilter
for (filterName, stdFilter)
in
726 zip(lutCat[0][
'physicalFilters'].split(
','),
727 lutCat[0][
'stdPhysicalFilters'].split(
','))}
728 stdLambdaDict = {stdFilter: stdLambda
for (stdFilter, stdLambda)
in
729 zip(lutCat[0][
'stdPhysicalFilters'].split(
','),
730 lutCat[0][
'lambdaStdFilter'])}
737 self.log.info(
"Using the following reference filters: %s" %
738 (
', '.join(referenceFilterNames)))
742 referenceFilterNames = []
745 starConfig = {
'logger': self.log,
746 'filterToBand': self.config.physicalFilterMap,
747 'requiredBands': self.config.requiredBands,
748 'minPerBand': self.config.minPerBand,
749 'matchRadius': self.config.matchRadius,
750 'isolationRadius': self.config.isolationRadius,
751 'matchNSide': self.config.matchNside,
752 'coarseNSide': self.config.coarseNside,
753 'densNSide': self.config.densityCutNside,
754 'densMaxPerPixel': self.config.densityCutMaxPerPixel,
755 'randomSeed': self.config.randomSeed,
756 'primaryBands': self.config.primaryBands,
757 'referenceFilterNames': referenceFilterNames}
760 fgcmMakeStars = fgcm.FgcmMakeStars(starConfig)
768 conv = obsCat[0][
'ra'].asDegrees() / float(obsCat[0][
'ra'])
769 fgcmMakeStars.makePrimaryStars(obsCat[
'ra'] * conv,
770 obsCat[
'dec'] * conv,
771 filterNameArray=obsFilterNames,
775 fgcmMakeStars.makeMatchedStars(obsCat[
'ra'] * conv,
776 obsCat[
'dec'] * conv,
779 if self.config.doReferenceMatches:
780 fgcmMakeStars.makeReferenceMatches(self.fgcmLoadReferenceCatalog)
787 fgcmStarIdCat = afwTable.BaseCatalog(objSchema)
788 fgcmStarIdCat.reserve(fgcmMakeStars.objIndexCat.size)
789 for i
in range(fgcmMakeStars.objIndexCat.size):
790 fgcmStarIdCat.addNew()
793 fgcmStarIdCat[
'fgcm_id'][:] = fgcmMakeStars.objIndexCat[
'fgcm_id']
794 fgcmStarIdCat[
'ra'][:] = fgcmMakeStars.objIndexCat[
'ra']
795 fgcmStarIdCat[
'dec'][:] = fgcmMakeStars.objIndexCat[
'dec']
796 fgcmStarIdCat[
'obsArrIndex'][:] = fgcmMakeStars.objIndexCat[
'obsarrindex']
797 fgcmStarIdCat[
'nObs'][:] = fgcmMakeStars.objIndexCat[
'nobs']
801 fgcmStarIndicesCat = afwTable.BaseCatalog(obsSchema)
802 fgcmStarIndicesCat.reserve(fgcmMakeStars.obsIndexCat.size)
803 for i
in range(fgcmMakeStars.obsIndexCat.size):
804 fgcmStarIndicesCat.addNew()
806 fgcmStarIndicesCat[
'obsIndex'][:] = fgcmMakeStars.obsIndexCat[
'obsindex']
808 if self.config.doReferenceMatches:
811 fgcmRefCat = afwTable.BaseCatalog(refSchema)
812 fgcmRefCat.reserve(fgcmMakeStars.referenceCat.size)
814 for i
in range(fgcmMakeStars.referenceCat.size):
817 fgcmRefCat[
'fgcm_id'][:] = fgcmMakeStars.referenceCat[
'fgcm_id']
818 fgcmRefCat[
'refMag'][:, :] = fgcmMakeStars.referenceCat[
'refMag']
819 fgcmRefCat[
'refMagErr'][:, :] = fgcmMakeStars.referenceCat[
'refMagErr']
822 md.set(
"REFSTARS_FORMAT_VERSION", REFSTARS_FORMAT_VERSION)
823 md.set(
"FILTERNAMES", referenceFilterNames)
824 fgcmRefCat.setMetadata(md)
829 return fgcmStarIdCat, fgcmStarIndicesCat, fgcmRefCat
831 def _makeFgcmVisitSchema(self, nCcd):
833 Make a schema for an fgcmVisitCatalog
838 Number of CCDs in the camera
842 schema: `afwTable.Schema`
845 schema = afwTable.Schema()
846 schema.addField(
'visit', type=np.int32, doc=
"Visit number")
847 schema.addField(
'physicalFilter', type=str, size=30, doc=
"Physical filter")
848 schema.addField(
'telra', type=np.float64, doc=
"Pointing RA (deg)")
849 schema.addField(
'teldec', type=np.float64, doc=
"Pointing Dec (deg)")
850 schema.addField(
'telha', type=np.float64, doc=
"Pointing Hour Angle (deg)")
851 schema.addField(
'telrot', type=np.float64, doc=
"Camera rotation (deg)")
852 schema.addField(
'mjd', type=np.float64, doc=
"MJD of visit")
853 schema.addField(
'exptime', type=np.float32, doc=
"Exposure time")
854 schema.addField(
'pmb', type=np.float32, doc=
"Pressure (millibar)")
855 schema.addField(
'psfSigma', type=np.float32, doc=
"PSF sigma (reference CCD)")
856 schema.addField(
'deltaAper', type=np.float32, doc=
"Delta-aperture")
857 schema.addField(
'skyBackground', type=np.float32, doc=
"Sky background (ADU) (reference CCD)")
859 schema.addField(
'deepFlag', type=np.int32, doc=
"Deep observation")
860 schema.addField(
'scaling', type=
'ArrayD', doc=
"Scaling applied due to flat adjustment",
862 schema.addField(
'used', type=np.int32, doc=
"This visit has been ingested.")
863 schema.addField(
'sources_read', type=
'Flag', doc=
"This visit had sources read.")
867 def _makeFgcmObjSchema(self):
869 Make a schema for the objIndexCat from fgcmMakeStars
873 schema: `afwTable.Schema`
876 objSchema = afwTable.Schema()
877 objSchema.addField(
'fgcm_id', type=np.int32, doc=
'FGCM Unique ID')
879 objSchema.addField(
'ra', type=np.float64, doc=
'Mean object RA (deg)')
880 objSchema.addField(
'dec', type=np.float64, doc=
'Mean object Dec (deg)')
881 objSchema.addField(
'obsArrIndex', type=np.int32,
882 doc=
'Index in obsIndexTable for first observation')
883 objSchema.addField(
'nObs', type=np.int32, doc=
'Total number of observations')
887 def _makeFgcmObsSchema(self):
889 Make a schema for the obsIndexCat from fgcmMakeStars
893 schema: `afwTable.Schema`
896 obsSchema = afwTable.Schema()
897 obsSchema.addField(
'obsIndex', type=np.int32, doc=
'Index in observation table')
901 def _makeFgcmRefSchema(self, nReferenceBands):
903 Make a schema for the referenceCat from fgcmMakeStars
907 nReferenceBands: `int`
908 Number of reference bands
912 schema: `afwTable.Schema`
915 refSchema = afwTable.Schema()
916 refSchema.addField(
'fgcm_id', type=np.int32, doc=
'FGCM Unique ID')
917 refSchema.addField(
'refMag', type=
'ArrayF', doc=
'Reference magnitude array (AB)',
918 size=nReferenceBands)
919 refSchema.addField(
'refMagErr', type=
'ArrayF', doc=
'Reference magnitude error array',
920 size=nReferenceBands)
924 def _getReferenceFilterNames(self, visitCat, stdFilterDict, stdLambdaDict):
926 Get the reference filter names, in wavelength order, from the visitCat and
927 information from the look-up-table.
931 visitCat: `afw.table.BaseCatalog`
932 Catalog with visit data for FGCM
933 stdFilterDict: `dict`
934 Mapping of filterName to stdFilterName from LUT
935 stdLambdaDict: `dict`
936 Mapping of stdFilterName to stdLambda from LUT
940 referenceFilterNames: `list`
941 Wavelength-ordered list of reference filter names
945 filterNames = np.unique(visitCat.asAstropy()[
'physicalFilter'])
948 stdFilterNames = {stdFilterDict[filterName]
for filterName
in filterNames}
951 referenceFilterNames = sorted(stdFilterNames, key=stdLambdaDict.get)
953 return referenceFilterNames
def fgcmMatchStars(self, visitCat, obsCat, lutDataRef=None)
def _makeFgcmVisitSchema(self, nCcd)
def _getReferenceFilterNames(self, visitCat, stdFilterDict, stdLambdaDict)
def runDataRef(self, butler, dataRefs)
def _makeFgcmObjSchema(self)
def _fillVisitCatalog(self, visitCat, groupedDataRefs, bkgDataRefDict=None, visitCatDataRef=None)
def fgcmMakeAllStarObservations(self, groupedDataRefs, visitCat, sourceSchema, camera, calibFluxApertureRadius=None, visitCatDataRef=None, starObsDataRef=None, inStarObsCat=None)
def __init__(self, initInputs=None, butler=None, **kwargs)
def _makeFgcmObsSchema(self)
def fgcmMakeVisitCatalog(self, camera, groupedDataRefs, bkgDataRefDict=None, visitCatDataRef=None, inVisitCat=None)
def _findAndGroupDataRefsGen2(self, butler, camera, dataRefs)
def _makeFgcmRefSchema(self, nReferenceBands)
def getTargetList(parsedCmd)
def computeApertureRadiusFromDataRef(dataRef, fluxField)