Coverage for python/lsst/fgcmcal/fgcmBuildStarsTable.py: 18%
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« prev ^ index » next coverage.py v6.4.1, created at 2022-06-24 02:58 -0700
1# See COPYRIGHT file at the top of the source tree.
2#
3# This file is part of fgcmcal.
4#
5# Developed for the LSST Data Management System.
6# This product includes software developed by the LSST Project
7# (https://www.lsst.org).
8# See the COPYRIGHT file at the top-level directory of this distribution
9# for details of code ownership.
10#
11# This program is free software: you can redistribute it and/or modify
12# it under the terms of the GNU General Public License as published by
13# the Free Software Foundation, either version 3 of the License, or
14# (at your option) any later version.
15#
16# This program is distributed in the hope that it will be useful,
17# but WITHOUT ANY WARRANTY; without even the implied warranty of
18# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
19# GNU General Public License for more details.
20#
21# You should have received a copy of the GNU General Public License
22# along with this program. If not, see <https://www.gnu.org/licenses/>.
23"""Build star observations for input to FGCM using sourceTable_visit.
25This task finds all the visits and sourceTable_visits in a repository (or a
26subset based on command line parameters) and extracts all the potential
27calibration stars for input into fgcm. This task additionally uses fgcm to
28match star observations into unique stars, and performs as much cleaning of the
29input catalog as possible.
30"""
32import time
34import numpy as np
35import collections
37import lsst.pex.config as pexConfig
38import lsst.pipe.base as pipeBase
39from lsst.pipe.base import connectionTypes
40import lsst.afw.table as afwTable
41from lsst.meas.algorithms import ReferenceObjectLoader, LoadReferenceObjectsConfig
43from .fgcmBuildStarsBase import FgcmBuildStarsConfigBase, FgcmBuildStarsBaseTask
44from .utilities import computeApproxPixelAreaFields, computeApertureRadiusFromName
45from .utilities import lookupStaticCalibrations
47__all__ = ['FgcmBuildStarsTableConfig', 'FgcmBuildStarsTableTask']
50class FgcmBuildStarsTableConnections(pipeBase.PipelineTaskConnections,
51 dimensions=("instrument",),
52 defaultTemplates={}):
53 camera = connectionTypes.PrerequisiteInput(
54 doc="Camera instrument",
55 name="camera",
56 storageClass="Camera",
57 dimensions=("instrument",),
58 lookupFunction=lookupStaticCalibrations,
59 isCalibration=True,
60 )
62 fgcmLookUpTable = connectionTypes.PrerequisiteInput(
63 doc=("Atmosphere + instrument look-up-table for FGCM throughput and "
64 "chromatic corrections."),
65 name="fgcmLookUpTable",
66 storageClass="Catalog",
67 dimensions=("instrument",),
68 deferLoad=True,
69 )
71 sourceSchema = connectionTypes.InitInput(
72 doc="Schema for source catalogs",
73 name="src_schema",
74 storageClass="SourceCatalog",
75 )
77 refCat = connectionTypes.PrerequisiteInput(
78 doc="Reference catalog to use for photometric calibration",
79 name="cal_ref_cat",
80 storageClass="SimpleCatalog",
81 dimensions=("skypix",),
82 deferLoad=True,
83 multiple=True,
84 )
86 sourceTable_visit = connectionTypes.Input(
87 doc="Source table in parquet format, per visit",
88 name="sourceTable_visit",
89 storageClass="DataFrame",
90 dimensions=("instrument", "visit"),
91 deferLoad=True,
92 multiple=True,
93 )
95 visitSummary = connectionTypes.Input(
96 doc=("Per-visit consolidated exposure metadata. These catalogs use "
97 "detector id for the id and must be sorted for fast lookups of a "
98 "detector."),
99 name="visitSummary",
100 storageClass="ExposureCatalog",
101 dimensions=("instrument", "visit"),
102 deferLoad=True,
103 multiple=True,
104 )
106 background = connectionTypes.Input(
107 doc="Calexp background model",
108 name="calexpBackground",
109 storageClass="Background",
110 dimensions=("instrument", "visit", "detector"),
111 deferLoad=True,
112 multiple=True,
113 )
115 fgcmVisitCatalog = connectionTypes.Output(
116 doc="Catalog of visit information for fgcm",
117 name="fgcmVisitCatalog",
118 storageClass="Catalog",
119 dimensions=("instrument",),
120 )
122 fgcmStarObservations = connectionTypes.Output(
123 doc="Catalog of star observations for fgcm",
124 name="fgcmStarObservations",
125 storageClass="Catalog",
126 dimensions=("instrument",),
127 )
129 fgcmStarIds = connectionTypes.Output(
130 doc="Catalog of fgcm calibration star IDs",
131 name="fgcmStarIds",
132 storageClass="Catalog",
133 dimensions=("instrument",),
134 )
136 fgcmStarIndices = connectionTypes.Output(
137 doc="Catalog of fgcm calibration star indices",
138 name="fgcmStarIndices",
139 storageClass="Catalog",
140 dimensions=("instrument",),
141 )
143 fgcmReferenceStars = connectionTypes.Output(
144 doc="Catalog of fgcm-matched reference stars",
145 name="fgcmReferenceStars",
146 storageClass="Catalog",
147 dimensions=("instrument",),
148 )
150 def __init__(self, *, config=None):
151 super().__init__(config=config)
153 if not config.doReferenceMatches:
154 self.prerequisiteInputs.remove("refCat")
155 self.prerequisiteInputs.remove("fgcmLookUpTable")
157 if not config.doModelErrorsWithBackground:
158 self.inputs.remove("background")
160 if not config.doReferenceMatches:
161 self.outputs.remove("fgcmReferenceStars")
164class FgcmBuildStarsTableConfig(FgcmBuildStarsConfigBase, pipeBase.PipelineTaskConfig,
165 pipelineConnections=FgcmBuildStarsTableConnections):
166 """Config for FgcmBuildStarsTableTask"""
168 referenceCCD = pexConfig.Field(
169 doc="Reference CCD for checking PSF and background",
170 dtype=int,
171 default=40,
172 )
174 def setDefaults(self):
175 super().setDefaults()
177 # The names here correspond to the post-transformed
178 # sourceTable_visit catalogs, which differ from the raw src
179 # catalogs. Therefore, all field and flag names cannot
180 # be derived from the base config class.
181 self.instFluxField = 'apFlux_12_0_instFlux'
182 self.localBackgroundFluxField = 'localBackground_instFlux'
183 self.apertureInnerInstFluxField = 'apFlux_12_0_instFlux'
184 self.apertureOuterInstFluxField = 'apFlux_17_0_instFlux'
185 self.psfCandidateName = 'calib_psf_candidate'
187 sourceSelector = self.sourceSelector["science"]
189 fluxFlagName = self.instFluxField[0: -len('instFlux')] + 'flag'
191 sourceSelector.flags.bad = ['pixelFlags_edge',
192 'pixelFlags_interpolatedCenter',
193 'pixelFlags_saturatedCenter',
194 'pixelFlags_crCenter',
195 'pixelFlags_bad',
196 'pixelFlags_interpolated',
197 'pixelFlags_saturated',
198 'centroid_flag',
199 fluxFlagName]
201 if self.doSubtractLocalBackground:
202 localBackgroundFlagName = self.localBackgroundFluxField[0: -len('instFlux')] + 'flag'
203 sourceSelector.flags.bad.append(localBackgroundFlagName)
205 sourceSelector.signalToNoise.fluxField = self.instFluxField
206 sourceSelector.signalToNoise.errField = self.instFluxField + 'Err'
208 sourceSelector.isolated.parentName = 'parentSourceId'
209 sourceSelector.isolated.nChildName = 'deblend_nChild'
211 sourceSelector.unresolved.name = 'extendedness'
214class FgcmBuildStarsTableTask(FgcmBuildStarsBaseTask):
215 """
216 Build stars for the FGCM global calibration, using sourceTable_visit catalogs.
217 """
218 ConfigClass = FgcmBuildStarsTableConfig
219 _DefaultName = "fgcmBuildStarsTable"
221 canMultiprocess = False
223 def __init__(self, initInputs=None, **kwargs):
224 super().__init__(initInputs=initInputs, **kwargs)
225 if initInputs is not None:
226 self.sourceSchema = initInputs["sourceSchema"].schema
228 def runQuantum(self, butlerQC, inputRefs, outputRefs):
229 inputRefDict = butlerQC.get(inputRefs)
231 sourceTableHandles = inputRefDict['sourceTable_visit']
233 self.log.info("Running with %d sourceTable_visit handles",
234 len(sourceTableHandles))
236 sourceTableHandleDict = {sourceTableHandle.dataId['visit']: sourceTableHandle for
237 sourceTableHandle in sourceTableHandles}
239 if self.config.doReferenceMatches:
240 # Get the LUT handle
241 lutHandle = inputRefDict['fgcmLookUpTable']
243 # Prepare the reference catalog loader
244 refConfig = LoadReferenceObjectsConfig()
245 refConfig.filterMap = self.config.fgcmLoadReferenceCatalog.filterMap
246 refObjLoader = ReferenceObjectLoader(dataIds=[ref.datasetRef.dataId
247 for ref in inputRefs.refCat],
248 refCats=butlerQC.get(inputRefs.refCat),
249 log=self.log,
250 config=refConfig)
251 self.makeSubtask('fgcmLoadReferenceCatalog',
252 refObjLoader=refObjLoader,
253 refCatName=self.config.connections.refCat)
254 else:
255 lutHandle = None
257 # Compute aperture radius if necessary. This is useful to do now before
258 # any heave lifting has happened (fail early).
259 calibFluxApertureRadius = None
260 if self.config.doSubtractLocalBackground:
261 try:
262 calibFluxApertureRadius = computeApertureRadiusFromName(self.config.instFluxField)
263 except RuntimeError as e:
264 raise RuntimeError("Could not determine aperture radius from %s. "
265 "Cannot use doSubtractLocalBackground." %
266 (self.config.instFluxField)) from e
268 visitSummaryHandles = inputRefDict['visitSummary']
269 visitSummaryHandleDict = {visitSummaryHandle.dataId['visit']: visitSummaryHandle for
270 visitSummaryHandle in visitSummaryHandles}
272 camera = inputRefDict['camera']
273 groupedHandles = self._groupHandles(sourceTableHandleDict,
274 visitSummaryHandleDict)
276 if self.config.doModelErrorsWithBackground:
277 bkgHandles = inputRefDict['background']
278 bkgHandleDict = {(bkgHandle.dataId.byName()['visit'],
279 bkgHandle.dataId.byName()['detector']): bkgHandle for
280 bkgHandle in bkgHandles}
281 else:
282 bkgHandleDict = None
284 visitCat = self.fgcmMakeVisitCatalog(camera, groupedHandles,
285 bkgHandleDict=bkgHandleDict)
287 rad = calibFluxApertureRadius
288 fgcmStarObservationCat = self.fgcmMakeAllStarObservations(groupedHandles,
289 visitCat,
290 self.sourceSchema,
291 camera,
292 calibFluxApertureRadius=rad)
294 butlerQC.put(visitCat, outputRefs.fgcmVisitCatalog)
295 butlerQC.put(fgcmStarObservationCat, outputRefs.fgcmStarObservations)
297 fgcmStarIdCat, fgcmStarIndicesCat, fgcmRefCat = self.fgcmMatchStars(visitCat,
298 fgcmStarObservationCat,
299 lutHandle=lutHandle)
301 butlerQC.put(fgcmStarIdCat, outputRefs.fgcmStarIds)
302 butlerQC.put(fgcmStarIndicesCat, outputRefs.fgcmStarIndices)
303 if fgcmRefCat is not None:
304 butlerQC.put(fgcmRefCat, outputRefs.fgcmReferenceStars)
306 def _groupHandles(self, sourceTableHandleDict, visitSummaryHandleDict):
307 """Group sourceTable and visitSummary handles.
309 Parameters
310 ----------
311 sourceTableHandleDict : `dict` [`int`, `str`]
312 Dict of source tables, keyed by visit.
313 visitSummaryHandleDict : `dict` [int, `str`]
314 Dict of visit summary catalogs, keyed by visit.
316 Returns
317 -------
318 groupedHandles : `dict` [`int`, `list`]
319 Dictionary with sorted visit keys, and `list`s with
320 `lsst.daf.butler.DeferredDataSetHandle`. The first
321 item in the list will be the visitSummary ref, and
322 the second will be the source table ref.
323 """
324 groupedHandles = collections.defaultdict(list)
325 visits = sorted(sourceTableHandleDict.keys())
327 for visit in visits:
328 groupedHandles[visit] = [visitSummaryHandleDict[visit],
329 sourceTableHandleDict[visit]]
331 return groupedHandles
333 def fgcmMakeAllStarObservations(self, groupedHandles, visitCat,
334 sourceSchema,
335 camera,
336 calibFluxApertureRadius=None):
337 startTime = time.time()
339 if self.config.doSubtractLocalBackground and calibFluxApertureRadius is None:
340 raise RuntimeError("Must set calibFluxApertureRadius if doSubtractLocalBackground is True.")
342 # To get the correct output schema, we use the legacy code.
343 # We are not actually using this mapper, except to grab the outputSchema
344 sourceMapper = self._makeSourceMapper(sourceSchema)
345 outputSchema = sourceMapper.getOutputSchema()
347 # Construct mapping from ccd number to index
348 ccdMapping = {}
349 for ccdIndex, detector in enumerate(camera):
350 ccdMapping[detector.getId()] = ccdIndex
352 approxPixelAreaFields = computeApproxPixelAreaFields(camera)
354 fullCatalog = afwTable.BaseCatalog(outputSchema)
356 visitKey = outputSchema['visit'].asKey()
357 ccdKey = outputSchema['ccd'].asKey()
358 instMagKey = outputSchema['instMag'].asKey()
359 instMagErrKey = outputSchema['instMagErr'].asKey()
360 deltaMagAperKey = outputSchema['deltaMagAper'].asKey()
362 # Prepare local background if desired
363 if self.config.doSubtractLocalBackground:
364 localBackgroundArea = np.pi*calibFluxApertureRadius**2.
366 columns = None
368 k = 2.5/np.log(10.)
370 for counter, visit in enumerate(visitCat):
371 expTime = visit['exptime']
373 handle = groupedHandles[visit['visit']][-1]
375 if columns is None:
376 inColumns = handle.get(component='columns')
377 columns, detColumn = self._get_sourceTable_visit_columns(inColumns)
378 df = handle.get(parameters={'columns': columns})
380 goodSrc = self.sourceSelector.selectSources(df)
382 # Need to add a selection based on the local background correction
383 # if necessary
384 if self.config.doSubtractLocalBackground:
385 localBackground = localBackgroundArea*df[self.config.localBackgroundFluxField].values
386 use, = np.where((goodSrc.selected)
387 & ((df[self.config.instFluxField].values - localBackground) > 0.0))
388 else:
389 use, = np.where(goodSrc.selected)
391 tempCat = afwTable.BaseCatalog(fullCatalog.schema)
392 tempCat.resize(use.size)
394 tempCat['ra'][:] = np.deg2rad(df['ra'].values[use])
395 tempCat['dec'][:] = np.deg2rad(df['decl'].values[use])
396 tempCat['x'][:] = df['x'].values[use]
397 tempCat['y'][:] = df['y'].values[use]
398 # The "visit" name in the parquet table is hard-coded.
399 tempCat[visitKey][:] = df['visit'].values[use]
400 tempCat[ccdKey][:] = df[detColumn].values[use]
401 tempCat['psf_candidate'] = df[self.config.psfCandidateName].values[use]
403 with np.warnings.catch_warnings():
404 # Ignore warnings, we will filter infinites and nans below
405 np.warnings.simplefilter("ignore")
407 instMagInner = -2.5*np.log10(df[self.config.apertureInnerInstFluxField].values[use])
408 instMagErrInner = k*(df[self.config.apertureInnerInstFluxField + 'Err'].values[use]
409 / df[self.config.apertureInnerInstFluxField].values[use])
410 instMagOuter = -2.5*np.log10(df[self.config.apertureOuterInstFluxField].values[use])
411 instMagErrOuter = k*(df[self.config.apertureOuterInstFluxField + 'Err'].values[use]
412 / df[self.config.apertureOuterInstFluxField].values[use])
413 tempCat[deltaMagAperKey][:] = instMagInner - instMagOuter
414 # Set bad values to illegal values for fgcm.
415 tempCat[deltaMagAperKey][~np.isfinite(tempCat[deltaMagAperKey][:])] = 99.0
417 if self.config.doSubtractLocalBackground:
418 # At the moment we only adjust the flux and not the flux
419 # error by the background because the error on
420 # base_LocalBackground_instFlux is the rms error in the
421 # background annulus, not the error on the mean in the
422 # background estimate (which is much smaller, by sqrt(n)
423 # pixels used to estimate the background, which we do not
424 # have access to in this task). In the default settings,
425 # the annulus is sufficiently large such that these
426 # additional errors are are negligibly small (much less
427 # than a mmag in quadrature).
429 # This is the difference between the mag with local background correction
430 # and the mag without local background correction.
431 tempCat['deltaMagBkg'] = (-2.5*np.log10(df[self.config.instFluxField].values[use]
432 - localBackground[use]) -
433 -2.5*np.log10(df[self.config.instFluxField].values[use]))
434 else:
435 tempCat['deltaMagBkg'][:] = 0.0
437 # Need to loop over ccds here
438 for detector in camera:
439 ccdId = detector.getId()
440 # used index for all observations with a given ccd
441 use2 = (tempCat[ccdKey] == ccdId)
442 tempCat['jacobian'][use2] = approxPixelAreaFields[ccdId].evaluate(tempCat['x'][use2],
443 tempCat['y'][use2])
444 scaledInstFlux = (df[self.config.instFluxField].values[use[use2]]
445 * visit['scaling'][ccdMapping[ccdId]])
446 tempCat[instMagKey][use2] = (-2.5*np.log10(scaledInstFlux) + 2.5*np.log10(expTime))
448 # Compute instMagErr from instFluxErr/instFlux, any scaling
449 # will cancel out.
450 tempCat[instMagErrKey][:] = k*(df[self.config.instFluxField + 'Err'].values[use]
451 / df[self.config.instFluxField].values[use])
453 # Apply the jacobian if configured
454 if self.config.doApplyWcsJacobian:
455 tempCat[instMagKey][:] -= 2.5*np.log10(tempCat['jacobian'][:])
457 fullCatalog.extend(tempCat)
459 deltaOk = (np.isfinite(instMagInner) & np.isfinite(instMagErrInner)
460 & np.isfinite(instMagOuter) & np.isfinite(instMagErrOuter))
462 visit['deltaAper'] = np.median(instMagInner[deltaOk] - instMagOuter[deltaOk])
463 visit['sources_read'] = True
465 self.log.info(" Found %d good stars in visit %d (deltaAper = %0.3f)",
466 use.size, visit['visit'], visit['deltaAper'])
468 self.log.info("Found all good star observations in %.2f s" %
469 (time.time() - startTime))
471 return fullCatalog
473 def _get_sourceTable_visit_columns(self, inColumns):
474 """
475 Get the sourceTable_visit columns from the config.
477 Parameters
478 ----------
479 inColumns : `list`
480 List of columns available in the sourceTable_visit
482 Returns
483 -------
484 columns : `list`
485 List of columns to read from sourceTable_visit.
486 detectorColumn : `str`
487 Name of the detector column.
488 """
489 if 'detector' in inColumns:
490 # Default name for Gen3.
491 detectorColumn = 'detector'
492 else:
493 # Default name for Gen2 conversions (including test data).
494 detectorColumn = 'ccd'
495 # Some names are hard-coded in the parquet table.
496 columns = ['visit', detectorColumn,
497 'ra', 'decl', 'x', 'y', self.config.psfCandidateName,
498 self.config.instFluxField, self.config.instFluxField + 'Err',
499 self.config.apertureInnerInstFluxField, self.config.apertureInnerInstFluxField + 'Err',
500 self.config.apertureOuterInstFluxField, self.config.apertureOuterInstFluxField + 'Err']
501 if self.sourceSelector.config.doFlags:
502 columns.extend(self.sourceSelector.config.flags.bad)
503 if self.sourceSelector.config.doUnresolved:
504 columns.append(self.sourceSelector.config.unresolved.name)
505 if self.sourceSelector.config.doIsolated:
506 columns.append(self.sourceSelector.config.isolated.parentName)
507 columns.append(self.sourceSelector.config.isolated.nChildName)
508 if self.config.doSubtractLocalBackground:
509 columns.append(self.config.localBackgroundFluxField)
511 return columns, detectorColumn