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LSST Data Management Base Package
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fgcmBuildStarsTable.py
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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.
24
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"""
31
32import time
33import warnings
34
35import numpy as np
36import collections
37
38import lsst.pex.config as pexConfig
39import lsst.pipe.base as pipeBase
40from lsst.pipe.base import connectionTypes
41import lsst.afw.table as afwTable
42from lsst.meas.algorithms import ReferenceObjectLoader, LoadReferenceObjectsConfig
43
44from .fgcmBuildStarsBase import FgcmBuildStarsConfigBase, FgcmBuildStarsBaseTask
45from .utilities import computeApproxPixelAreaFields, computeApertureRadiusFromName
46
47__all__ = ['FgcmBuildStarsTableConfig', 'FgcmBuildStarsTableTask']
48
49
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 isCalibration=True,
59 )
60
61 fgcmLookUpTable = connectionTypes.PrerequisiteInput(
62 doc=("Atmosphere + instrument look-up-table for FGCM throughput and "
63 "chromatic corrections."),
64 name="fgcmLookUpTable",
65 storageClass="Catalog",
66 dimensions=("instrument",),
67 deferLoad=True,
68 )
69
70 sourceSchema = connectionTypes.InitInput(
71 doc="Schema for source catalogs",
72 name="src_schema",
73 storageClass="SourceCatalog",
74 )
75
76 refCat = connectionTypes.PrerequisiteInput(
77 doc="Reference catalog to use for photometric calibration",
78 name="cal_ref_cat",
79 storageClass="SimpleCatalog",
80 dimensions=("skypix",),
81 deferLoad=True,
82 multiple=True,
83 )
84
85 sourceTable_visit = connectionTypes.Input(
86 doc="Source table in parquet format, per visit",
87 name="sourceTable_visit",
88 storageClass="DataFrame",
89 dimensions=("instrument", "visit"),
90 deferLoad=True,
91 multiple=True,
92 )
93
94 visitSummary = connectionTypes.Input(
95 doc=("Per-visit consolidated exposure metadata. These catalogs use "
96 "detector id for the id and must be sorted for fast lookups of a "
97 "detector."),
98 name="visitSummary",
99 storageClass="ExposureCatalog",
100 dimensions=("instrument", "visit"),
101 deferLoad=True,
102 multiple=True,
103 )
104
105 fgcmVisitCatalog = connectionTypes.Output(
106 doc="Catalog of visit information for fgcm",
107 name="fgcmVisitCatalog",
108 storageClass="Catalog",
109 dimensions=("instrument",),
110 )
111
112 fgcmStarObservations = connectionTypes.Output(
113 doc="Catalog of star observations for fgcm",
114 name="fgcmStarObservations",
115 storageClass="Catalog",
116 dimensions=("instrument",),
117 )
118
119 fgcmStarIds = connectionTypes.Output(
120 doc="Catalog of fgcm calibration star IDs",
121 name="fgcmStarIds",
122 storageClass="Catalog",
123 dimensions=("instrument",),
124 )
125
126 fgcmStarIndices = connectionTypes.Output(
127 doc="Catalog of fgcm calibration star indices",
128 name="fgcmStarIndices",
129 storageClass="Catalog",
130 dimensions=("instrument",),
131 )
132
133 fgcmReferenceStars = connectionTypes.Output(
134 doc="Catalog of fgcm-matched reference stars",
135 name="fgcmReferenceStars",
136 storageClass="Catalog",
137 dimensions=("instrument",),
138 )
139
140 def __init__(self, *, config=None):
141 super().__init__(config=config)
142
143 if not config.doReferenceMatches:
144 self.prerequisiteInputs.remove("refCat")
145 self.prerequisiteInputs.remove("fgcmLookUpTable")
146
147 if not config.doReferenceMatches:
148 self.outputs.remove("fgcmReferenceStars")
149
151 return ("visitSummary",)
152
153
154class FgcmBuildStarsTableConfig(FgcmBuildStarsConfigBase, pipeBase.PipelineTaskConfig,
155 pipelineConnections=FgcmBuildStarsTableConnections):
156 """Config for FgcmBuildStarsTableTask"""
157
158 referenceCCD = pexConfig.Field(
159 doc="Reference CCD for checking PSF and background",
160 dtype=int,
161 default=40,
162 )
163
164 def setDefaults(self):
165 super().setDefaults()
166
167 # The names here correspond to the post-transformed
168 # sourceTable_visit catalogs, which differ from the raw src
169 # catalogs. Therefore, all field and flag names cannot
170 # be derived from the base config class.
171 self.instFluxFieldinstFluxField = 'apFlux_12_0_instFlux'
172 self.localBackgroundFluxFieldlocalBackgroundFluxField = 'localBackground_instFlux'
175 self.psfCandidateNamepsfCandidateName = 'calib_psf_candidate'
176
177 sourceSelector = self.sourceSelector["science"]
178
179 fluxFlagName = self.instFluxFieldinstFluxField[0: -len('instFlux')] + 'flag'
180
181 sourceSelector.flags.bad = ['pixelFlags_edge',
182 'pixelFlags_interpolatedCenter',
183 'pixelFlags_saturatedCenter',
184 'pixelFlags_crCenter',
185 'pixelFlags_bad',
186 'pixelFlags_interpolated',
187 'pixelFlags_saturated',
188 'centroid_flag',
189 fluxFlagName]
190
192 localBackgroundFlagName = self.localBackgroundFluxFieldlocalBackgroundFluxField[0: -len('instFlux')] + 'flag'
193 sourceSelector.flags.bad.append(localBackgroundFlagName)
194
195 sourceSelector.signalToNoise.fluxField = self.instFluxFieldinstFluxField
196 sourceSelector.signalToNoise.errField = self.instFluxFieldinstFluxField + 'Err'
197
198 sourceSelector.isolated.parentName = 'parentSourceId'
199 sourceSelector.isolated.nChildName = 'deblend_nChild'
200
201 sourceSelector.requireFiniteRaDec.raColName = 'ra'
202 sourceSelector.requireFiniteRaDec.decColName = 'dec'
203
204 sourceSelector.unresolved.name = 'extendedness'
205
206 sourceSelector.doRequirePrimary = True
207
208
210 """
211 Build stars for the FGCM global calibration, using sourceTable_visit catalogs.
212 """
213 ConfigClass = FgcmBuildStarsTableConfig
214 _DefaultName = "fgcmBuildStarsTable"
215
216 canMultiprocess = False
217
218 def __init__(self, initInputs=None, **kwargs):
219 super().__init__(initInputs=initInputs, **kwargs)
220 if initInputs is not None:
221 self.sourceSchema = initInputs["sourceSchema"].schema
222
223 def runQuantum(self, butlerQC, inputRefs, outputRefs):
224 inputRefDict = butlerQC.get(inputRefs)
225
226 sourceTableHandles = inputRefDict['sourceTable_visit']
227
228 self.log.info("Running with %d sourceTable_visit handles",
229 len(sourceTableHandles))
230
231 sourceTableHandleDict = {sourceTableHandle.dataId['visit']: sourceTableHandle for
232 sourceTableHandle in sourceTableHandles}
233
234 if self.config.doReferenceMatches:
235 # Get the LUT handle
236 lutHandle = inputRefDict['fgcmLookUpTable']
237
238 # Prepare the reference catalog loader
239 refConfig = LoadReferenceObjectsConfig()
240 refConfig.filterMap = self.config.fgcmLoadReferenceCatalog.filterMap
241 refObjLoader = ReferenceObjectLoader(dataIds=[ref.datasetRef.dataId
242 for ref in inputRefs.refCat],
243 refCats=butlerQC.get(inputRefs.refCat),
244 name=self.config.connections.refCat,
245 log=self.log,
246 config=refConfig)
247 self.makeSubtask('fgcmLoadReferenceCatalog',
248 refObjLoader=refObjLoader,
249 refCatName=self.config.connections.refCat)
250 else:
251 lutHandle = None
252
253 # Compute aperture radius if necessary. This is useful to do now before
254 # any heave lifting has happened (fail early).
255 calibFluxApertureRadius = None
256 if self.config.doSubtractLocalBackground:
257 try:
258 calibFluxApertureRadius = computeApertureRadiusFromName(self.config.instFluxField)
259 except RuntimeError as e:
260 raise RuntimeError("Could not determine aperture radius from %s. "
261 "Cannot use doSubtractLocalBackground." %
262 (self.config.instFluxField)) from e
263
264 visitSummaryHandles = inputRefDict['visitSummary']
265 visitSummaryHandleDict = {visitSummaryHandle.dataId['visit']: visitSummaryHandle for
266 visitSummaryHandle in visitSummaryHandles}
267
268 camera = inputRefDict['camera']
269 groupedHandles = self._groupHandles(sourceTableHandleDict,
270 visitSummaryHandleDict)
271
272 visitCat = self.fgcmMakeVisitCatalog(camera, groupedHandles)
273
274 rad = calibFluxApertureRadius
275 fgcmStarObservationCat = self.fgcmMakeAllStarObservationsfgcmMakeAllStarObservations(groupedHandles,
276 visitCat,
277 self.sourceSchema,
278 camera,
279 calibFluxApertureRadius=rad)
280
281 butlerQC.put(visitCat, outputRefs.fgcmVisitCatalog)
282 butlerQC.put(fgcmStarObservationCat, outputRefs.fgcmStarObservations)
283
284 fgcmStarIdCat, fgcmStarIndicesCat, fgcmRefCat = self.fgcmMatchStars(visitCat,
285 fgcmStarObservationCat,
286 lutHandle=lutHandle)
287
288 butlerQC.put(fgcmStarIdCat, outputRefs.fgcmStarIds)
289 butlerQC.put(fgcmStarIndicesCat, outputRefs.fgcmStarIndices)
290 if fgcmRefCat is not None:
291 butlerQC.put(fgcmRefCat, outputRefs.fgcmReferenceStars)
292
293 def _groupHandles(self, sourceTableHandleDict, visitSummaryHandleDict):
294 """Group sourceTable and visitSummary handles.
295
296 Parameters
297 ----------
298 sourceTableHandleDict : `dict` [`int`, `str`]
299 Dict of source tables, keyed by visit.
300 visitSummaryHandleDict : `dict` [int, `str`]
301 Dict of visit summary catalogs, keyed by visit.
302
303 Returns
304 -------
305 groupedHandles : `dict` [`int`, `list`]
306 Dictionary with sorted visit keys, and `list`s with
307 `lsst.daf.butler.DeferredDataSetHandle`. The first
308 item in the list will be the visitSummary ref, and
309 the second will be the source table ref.
310 """
311 groupedHandles = collections.defaultdict(list)
312 visits = sorted(sourceTableHandleDict.keys())
313
314 for visit in visits:
315 groupedHandles[visit] = [visitSummaryHandleDict[visit],
316 sourceTableHandleDict[visit]]
317
318 return groupedHandles
319
320 def fgcmMakeAllStarObservations(self, groupedHandles, visitCat,
321 sourceSchema,
322 camera,
323 calibFluxApertureRadius=None):
324 startTime = time.time()
325
326 if self.config.doSubtractLocalBackground and calibFluxApertureRadius is None:
327 raise RuntimeError("Must set calibFluxApertureRadius if doSubtractLocalBackground is True.")
328
329 # To get the correct output schema, we use the legacy code.
330 # We are not actually using this mapper, except to grab the outputSchema
331 sourceMapper = self._makeSourceMapper(sourceSchema)
332 outputSchema = sourceMapper.getOutputSchema()
333
334 # Construct mapping from ccd number to index
335 ccdMapping = {}
336 for ccdIndex, detector in enumerate(camera):
337 ccdMapping[detector.getId()] = ccdIndex
338
339 approxPixelAreaFields = computeApproxPixelAreaFields(camera)
340
341 fullCatalog = afwTable.BaseCatalog(outputSchema)
342
343 visitKey = outputSchema['visit'].asKey()
344 ccdKey = outputSchema['ccd'].asKey()
345 instMagKey = outputSchema['instMag'].asKey()
346 instMagErrKey = outputSchema['instMagErr'].asKey()
347 deltaMagAperKey = outputSchema['deltaMagAper'].asKey()
348
349 # Prepare local background if desired
350 if self.config.doSubtractLocalBackground:
351 localBackgroundArea = np.pi*calibFluxApertureRadius**2.
352
353 columns = None
354
355 k = 2.5/np.log(10.)
356
357 for counter, visit in enumerate(visitCat):
358 expTime = visit['exptime']
359
360 handle = groupedHandles[visit['visit']][-1]
361
362 if columns is None:
363 inColumns = handle.get(component='columns')
364 columns = self._get_sourceTable_visit_columns(inColumns)
365 df = handle.get(parameters={'columns': columns})
366
367 goodSrc = self.sourceSelector.selectSources(df)
368
369 # Need to add a selection based on the local background correction
370 # if necessary
371 if self.config.doSubtractLocalBackground:
372 localBackground = localBackgroundArea*df[self.config.localBackgroundFluxField].values
373 use, = np.where((goodSrc.selected)
374 & ((df[self.config.instFluxField].values - localBackground) > 0.0))
375 else:
376 use, = np.where(goodSrc.selected)
377
378 tempCat = afwTable.BaseCatalog(fullCatalog.schema)
379 tempCat.resize(use.size)
380
381 tempCat['ra'][:] = np.deg2rad(df['ra'].values[use])
382 tempCat['dec'][:] = np.deg2rad(df['dec'].values[use])
383 tempCat['x'][:] = df['x'].values[use]
384 tempCat['y'][:] = df['y'].values[use]
385 # The "visit" name in the parquet table is hard-coded.
386 tempCat[visitKey][:] = df['visit'].values[use]
387 tempCat[ccdKey][:] = df['detector'].values[use]
388 tempCat['psf_candidate'] = df[self.config.psfCandidateName].values[use]
389
390 with warnings.catch_warnings():
391 # Ignore warnings, we will filter infinites and nans below
392 warnings.simplefilter("ignore")
393
394 instMagInner = -2.5*np.log10(df[self.config.apertureInnerInstFluxField].values[use])
395 instMagErrInner = k*(df[self.config.apertureInnerInstFluxField + 'Err'].values[use]
396 / df[self.config.apertureInnerInstFluxField].values[use])
397 instMagOuter = -2.5*np.log10(df[self.config.apertureOuterInstFluxField].values[use])
398 instMagErrOuter = k*(df[self.config.apertureOuterInstFluxField + 'Err'].values[use]
399 / df[self.config.apertureOuterInstFluxField].values[use])
400 tempCat[deltaMagAperKey][:] = instMagInner - instMagOuter
401 # Set bad values to illegal values for fgcm.
402 tempCat[deltaMagAperKey][~np.isfinite(tempCat[deltaMagAperKey][:])] = 99.0
403
404 if self.config.doSubtractLocalBackground:
405 # At the moment we only adjust the flux and not the flux
406 # error by the background because the error on
407 # base_LocalBackground_instFlux is the rms error in the
408 # background annulus, not the error on the mean in the
409 # background estimate (which is much smaller, by sqrt(n)
410 # pixels used to estimate the background, which we do not
411 # have access to in this task). In the default settings,
412 # the annulus is sufficiently large such that these
413 # additional errors are are negligibly small (much less
414 # than a mmag in quadrature).
415
416 # This is the difference between the mag with local background correction
417 # and the mag without local background correction.
418 tempCat['deltaMagBkg'] = (-2.5*np.log10(df[self.config.instFluxField].values[use]
419 - localBackground[use]) -
420 -2.5*np.log10(df[self.config.instFluxField].values[use]))
421 else:
422 tempCat['deltaMagBkg'][:] = 0.0
423
424 # Need to loop over ccds here
425 for detector in camera:
426 ccdId = detector.getId()
427 # used index for all observations with a given ccd
428 use2 = (tempCat[ccdKey] == ccdId)
429 tempCat['jacobian'][use2] = approxPixelAreaFields[ccdId].evaluate(tempCat['x'][use2],
430 tempCat['y'][use2])
431 scaledInstFlux = (df[self.config.instFluxField].values[use[use2]]
432 * visit['scaling'][ccdMapping[ccdId]])
433 tempCat[instMagKey][use2] = (-2.5*np.log10(scaledInstFlux) + 2.5*np.log10(expTime))
434
435 # Compute instMagErr from instFluxErr/instFlux, any scaling
436 # will cancel out.
437 tempCat[instMagErrKey][:] = k*(df[self.config.instFluxField + 'Err'].values[use]
438 / df[self.config.instFluxField].values[use])
439
440 # Apply the jacobian if configured
441 if self.config.doApplyWcsJacobian:
442 tempCat[instMagKey][:] -= 2.5*np.log10(tempCat['jacobian'][:])
443
444 fullCatalog.extend(tempCat)
445
446 deltaOk = (np.isfinite(instMagInner) & np.isfinite(instMagErrInner)
447 & np.isfinite(instMagOuter) & np.isfinite(instMagErrOuter))
448
449 visit['deltaAper'] = np.median(instMagInner[deltaOk] - instMagOuter[deltaOk])
450 visit['sources_read'] = True
451
452 self.log.info(" Found %d good stars in visit %d (deltaAper = %0.3f)",
453 use.size, visit['visit'], visit['deltaAper'])
454
455 self.log.info("Found all good star observations in %.2f s" %
456 (time.time() - startTime))
457
458 return fullCatalog
459
460 def _get_sourceTable_visit_columns(self, inColumns):
461 """
462 Get the sourceTable_visit columns from the config.
463
464 Parameters
465 ----------
466 inColumns : `list`
467 List of columns available in the sourceTable_visit
468
469 Returns
470 -------
471 columns : `list`
472 List of columns to read from sourceTable_visit.
473 """
474 # Some names are hard-coded in the parquet table.
475 columns = ['visit', 'detector',
476 'ra', 'dec', 'x', 'y', self.config.psfCandidateName,
477 self.config.instFluxField, self.config.instFluxField + 'Err',
478 self.config.apertureInnerInstFluxField, self.config.apertureInnerInstFluxField + 'Err',
479 self.config.apertureOuterInstFluxField, self.config.apertureOuterInstFluxField + 'Err']
480 if self.sourceSelector.config.doFlags:
481 columns.extend(self.sourceSelector.config.flags.bad)
482 if self.sourceSelector.config.doUnresolved:
483 columns.append(self.sourceSelector.config.unresolved.name)
484 if self.sourceSelector.config.doIsolated:
485 columns.append(self.sourceSelector.config.isolated.parentName)
486 columns.append(self.sourceSelector.config.isolated.nChildName)
487 if self.sourceSelector.config.doRequirePrimary:
488 columns.append(self.sourceSelector.config.requirePrimary.primaryColName)
489 if self.config.doSubtractLocalBackground:
490 columns.append(self.config.localBackgroundFluxField)
491
492 return columns
fgcmMatchStars(self, visitCat, obsCat, lutHandle=None)
fgcmMakeAllStarObservations(self, groupedHandles, visitCat, sourceSchema, camera, calibFluxApertureRadius=None)
fgcmMakeAllStarObservations(self, groupedHandles, visitCat, sourceSchema, camera, calibFluxApertureRadius=None)
_groupHandles(self, sourceTableHandleDict, visitSummaryHandleDict)