23Insert fake sources into calexps
26__all__ = [
"ProcessCcdWithFakesConfig",
"ProcessCcdWithFakesTask",
27 "ProcessCcdWithVariableFakesConfig",
"ProcessCcdWithVariableFakesTask"]
35from .insertFakes
import InsertFakesTask
37from lsst.obs.base
import ExposureIdInfo
38from lsst.pipe.base import PipelineTask, PipelineTaskConfig, PipelineTaskConnections
39import lsst.pipe.base.connectionTypes
as cT
46 dimensions=(
"instrument",
"visit",
"detector"),
47 defaultTemplates={
"coaddName":
"deep",
48 "wcsName":
"jointcal",
49 "photoCalibName":
"jointcal",
50 "fakesType":
"fakes_"}):
52 doc=
"Input definition of geometry/bbox and projection/wcs for "
53 "template exposures. Needed to test which tract to generate ",
54 name=BaseSkyMap.SKYMAP_DATASET_TYPE_NAME,
55 dimensions=(
"skymap",),
56 storageClass=
"SkyMap",
60 doc=
"Exposure into which fakes are to be added.",
62 storageClass=
"ExposureF",
63 dimensions=(
"instrument",
"visit",
"detector")
67 doc=
"Set of catalogs of fake sources to draw inputs from. We "
68 "concatenate the tract catalogs for detectorVisits that cover "
70 name=
"{fakesType}fakeSourceCat",
71 storageClass=
"DataFrame",
72 dimensions=(
"tract",
"skymap"),
77 externalSkyWcsTractCatalog = cT.Input(
78 doc=(
"Per-tract, per-visit wcs calibrations. These catalogs use the detector "
79 "id for the catalog id, sorted on id for fast lookup."),
80 name=
"{wcsName}SkyWcsCatalog",
81 storageClass=
"ExposureCatalog",
82 dimensions=(
"instrument",
"visit",
"tract",
"skymap"),
87 externalSkyWcsGlobalCatalog = cT.Input(
88 doc=(
"Per-visit wcs calibrations computed globally (with no tract information). "
89 "These catalogs use the detector id for the catalog id, sorted on id for "
91 name=
"finalVisitSummary",
92 storageClass=
"ExposureCatalog",
93 dimensions=(
"instrument",
"visit"),
96 externalPhotoCalibTractCatalog = cT.Input(
97 doc=(
"Per-tract, per-visit photometric calibrations. These catalogs use the "
98 "detector id for the catalog id, sorted on id for fast lookup."),
99 name=
"{photoCalibName}PhotoCalibCatalog",
100 storageClass=
"ExposureCatalog",
101 dimensions=(
"instrument",
"visit",
"tract"),
106 externalPhotoCalibGlobalCatalog = cT.Input(
107 doc=(
"Per-visit photometric calibrations. These catalogs use the "
108 "detector id for the catalog id, sorted on id for fast lookup."),
109 name=
"finalVisitSummary",
110 storageClass=
"ExposureCatalog",
111 dimensions=(
"instrument",
"visit"),
114 icSourceCat = cT.Input(
115 doc=
"Catalog of calibration sources",
117 storageClass=
"SourceCatalog",
118 dimensions=(
"instrument",
"visit",
"detector")
121 sfdSourceCat = cT.Input(
122 doc=
"Catalog of calibration sources",
124 storageClass=
"SourceCatalog",
125 dimensions=(
"instrument",
"visit",
"detector")
128 outputExposure = cT.Output(
129 doc=
"Exposure with fake sources added.",
130 name=
"{fakesType}calexp",
131 storageClass=
"ExposureF",
132 dimensions=(
"instrument",
"visit",
"detector")
135 outputCat = cT.Output(
136 doc=
"Source catalog produced in calibrate task with fakes also measured.",
137 name=
"{fakesType}src",
138 storageClass=
"SourceCatalog",
139 dimensions=(
"instrument",
"visit",
"detector"),
142 def __init__(self, *, config=None):
143 super().__init__(config=config)
145 if not config.doApplyExternalGlobalPhotoCalib:
146 self.inputs.remove(
"externalPhotoCalibGlobalCatalog")
147 if not config.doApplyExternalTractPhotoCalib:
148 self.inputs.remove(
"externalPhotoCalibTractCatalog")
150 if not config.doApplyExternalGlobalSkyWcs:
151 self.inputs.remove(
"externalSkyWcsGlobalCatalog")
152 if not config.doApplyExternalTractSkyWcs:
153 self.inputs.remove(
"externalSkyWcsTractCatalog")
156class ProcessCcdWithFakesConfig(PipelineTaskConfig,
157 pipelineConnections=ProcessCcdWithFakesConnections):
158 """Config for inserting fake sources
162 The default column names are those from the UW sims database.
165 doApplyExternalGlobalPhotoCalib = pexConfig.Field(
168 doc=
"Whether to apply an external photometric calibration via an "
169 "`lsst.afw.image.PhotoCalib` object. Uses the "
170 "`externalPhotoCalibName` config option to determine which "
171 "calibration to use. Uses a global calibration."
174 doApplyExternalTractPhotoCalib = pexConfig.Field(
177 doc=
"Whether to apply an external photometric calibration via an "
178 "`lsst.afw.image.PhotoCalib` object. Uses the "
179 "`externalPhotoCalibName` config option to determine which "
180 "calibration to use. Uses a per tract calibration."
183 externalPhotoCalibName = pexConfig.ChoiceField(
184 doc=
"What type of external photo calib to use.",
187 allowed={
"jointcal":
"Use jointcal_photoCalib",
188 "fgcm":
"Use fgcm_photoCalib",
189 "fgcm_tract":
"Use fgcm_tract_photoCalib"}
192 doApplyExternalGlobalSkyWcs = pexConfig.Field(
195 doc=
"Whether to apply an external astrometric calibration via an "
196 "`lsst.afw.geom.SkyWcs` object. Uses the "
197 "`externalSkyWcsName` config option to determine which "
198 "calibration to use. Uses a global calibration."
201 doApplyExternalTractSkyWcs = pexConfig.Field(
204 doc=
"Whether to apply an external astrometric calibration via an "
205 "`lsst.afw.geom.SkyWcs` object. Uses the "
206 "`externalSkyWcsName` config option to determine which "
207 "calibration to use. Uses a per tract calibration."
210 externalSkyWcsName = pexConfig.ChoiceField(
211 doc=
"What type of updated WCS calib to use.",
214 allowed={
"jointcal":
"Use jointcal_wcs"}
217 coaddName = pexConfig.Field(
218 doc=
"The name of the type of coadd used",
223 srcFieldsToCopy = pexConfig.ListField(
225 default=(
"calib_photometry_reserved",
"calib_photometry_used",
"calib_astrometry_used",
226 "calib_psf_candidate",
"calib_psf_used",
"calib_psf_reserved"),
227 doc=(
"Fields to copy from the `src` catalog to the output catalog "
228 "for matching sources Any missing fields will trigger a "
229 "RuntimeError exception.")
232 matchRadiusPix = pexConfig.Field(
235 doc=(
"Match radius for matching icSourceCat objects to sourceCat objects (pixels)"),
238 doMatchVisit = pexConfig.Field(
241 doc=
"Match visit to trim the fakeCat"
244 calibrate = pexConfig.ConfigurableField(target=CalibrateTask,
245 doc=
"The calibration task to use.")
247 insertFakes = pexConfig.ConfigurableField(target=InsertFakesTask,
248 doc=
"Configuration for the fake sources")
250 def setDefaults(self):
251 super().setDefaults()
252 self.calibrate.measurement.plugins[
"base_PixelFlags"].masksFpAnywhere.append(
"FAKE")
253 self.calibrate.measurement.plugins[
"base_PixelFlags"].masksFpCenter.append(
"FAKE")
254 self.calibrate.doAstrometry =
False
255 self.calibrate.doWriteMatches =
False
256 self.calibrate.doPhotoCal =
False
257 self.calibrate.doComputeSummaryStats =
False
258 self.calibrate.detection.reEstimateBackground =
False
261class ProcessCcdWithFakesTask(PipelineTask):
262 """Insert fake objects into calexps.
264 Add fake stars and galaxies to the given calexp, specified
in the dataRef. Galaxy parameters are read
in
265 from the specified file
and then modelled using galsim. Re-runs characterize image
and calibrate image to
266 give a new background estimation
and measurement of the calexp.
268 `ProcessFakeSourcesTask` inherits six functions
from insertFakesTask that make images of the fake
269 sources
and then add them to the calexp.
272 Use the WCS information to add the pixel coordinates of each source
273 Adds an ``x``
and ``y`` column to the catalog of fake sources.
275 Trim the fake cat to about the size of the input image.
276 `mkFakeGalsimGalaxies`
277 Use Galsim to make fake double sersic galaxies
for each set of galaxy parameters
in the input file.
279 Use the PSF information
from the calexp to make a fake star using the magnitude information
from the
282 Remove rows of the input fake catalog which have half light radius, of either the bulge
or the disk,
285 Add the fake sources to the calexp.
289 The ``calexp``
with fake souces added to it
is written out
as the datatype ``calexp_fakes``.
292 _DefaultName = "processCcdWithFakes"
293 ConfigClass = ProcessCcdWithFakesConfig
295 def __init__(self, schema=None, butler=None, **kwargs):
296 """Initalize things! This should go above in the class docstring
299 super().__init__(**kwargs)
302 schema = SourceTable.makeMinimalSchema()
304 self.makeSubtask(
"insertFakes")
305 self.makeSubtask(
"calibrate")
307 def runQuantum(self, butlerQC, inputRefs, outputRefs):
308 inputs = butlerQC.get(inputRefs)
309 detectorId = inputs[
"exposure"].getInfo().getDetector().getId()
311 if 'exposureIdInfo' not in inputs.keys():
312 expId, expBits = butlerQC.quantum.dataId.pack(
"visit_detector", returnMaxBits=
True)
313 inputs[
'exposureIdInfo'] = ExposureIdInfo(expId, expBits)
315 expWcs = inputs[
"exposure"].getWcs()
317 if not self.config.doApplyExternalGlobalSkyWcs
and not self.config.doApplyExternalTractSkyWcs:
319 self.log.info(
"No WCS for exposure %s so cannot insert fake sources. Skipping detector.",
320 butlerQC.quantum.dataId)
323 inputs[
"wcs"] = expWcs
324 elif self.config.doApplyExternalGlobalSkyWcs:
325 externalSkyWcsCatalog = inputs[
"externalSkyWcsGlobalCatalog"]
326 row = externalSkyWcsCatalog.find(detectorId)
328 self.log.info(
"No %s external global sky WCS for exposure %s so cannot insert fake "
329 "sources. Skipping detector.", self.config.externalSkyWcsName,
330 butlerQC.quantum.dataId)
332 inputs[
"wcs"] = row.getWcs()
333 elif self.config.doApplyExternalTractSkyWcs:
334 externalSkyWcsCatalogList = inputs[
"externalSkyWcsTractCatalog"]
336 tractId = externalSkyWcsCatalogList[0].dataId[
"tract"]
337 externalSkyWcsCatalog =
None
338 for externalSkyWcsCatalogRef
in externalSkyWcsCatalogList:
339 if externalSkyWcsCatalogRef.dataId[
"tract"] == tractId:
340 externalSkyWcsCatalog = externalSkyWcsCatalogRef.get()
342 if externalSkyWcsCatalog
is None:
343 usedTract = externalSkyWcsCatalogList[-1].dataId[
"tract"]
345 f
"Warning, external SkyWcs for tract {tractId} not found. Using tract {usedTract} "
347 externalSkyWcsCatalog = externalSkyWcsCatalogList[-1].get()
348 row = externalSkyWcsCatalog.find(detectorId)
350 self.log.info(
"No %s external tract sky WCS for exposure %s so cannot insert fake "
351 "sources. Skipping detector.", self.config.externalSkyWcsName,
352 butlerQC.quantum.dataId)
354 inputs[
"wcs"] = row.getWcs()
356 if not self.config.doApplyExternalGlobalPhotoCalib
and not self.config.doApplyExternalTractPhotoCalib:
357 inputs[
"photoCalib"] = inputs[
"exposure"].getPhotoCalib()
358 elif self.config.doApplyExternalGlobalPhotoCalib:
359 externalPhotoCalibCatalog = inputs[
"externalPhotoCalibGlobalCatalog"]
360 row = externalPhotoCalibCatalog.find(detectorId)
362 self.log.info(
"No %s external global photoCalib for exposure %s so cannot insert fake "
363 "sources. Skipping detector.", self.config.externalPhotoCalibName,
364 butlerQC.quantum.dataId)
366 inputs[
"photoCalib"] = row.getPhotoCalib()
367 elif self.config.doApplyExternalTractPhotoCalib:
368 externalPhotoCalibCatalogList = inputs[
"externalPhotoCalibTractCatalog"]
370 tractId = externalPhotoCalibCatalogList[0].dataId[
"tract"]
371 externalPhotoCalibCatalog =
None
372 for externalPhotoCalibCatalogRef
in externalPhotoCalibCatalogList:
373 if externalPhotoCalibCatalogRef.dataId[
"tract"] == tractId:
374 externalPhotoCalibCatalog = externalPhotoCalibCatalogRef.get()
376 if externalPhotoCalibCatalog
is None:
377 usedTract = externalPhotoCalibCatalogList[-1].dataId[
"tract"]
379 f
"Warning, external PhotoCalib for tract {tractId} not found. Using tract {usedTract} "
381 externalPhotoCalibCatalog = externalPhotoCalibCatalogList[-1].get()
382 row = externalPhotoCalibCatalog.find(detectorId)
384 self.log.info(
"No %s external tract photoCalib for exposure %s so cannot insert fake "
385 "sources. Skipping detector.", self.config.externalPhotoCalibName,
386 butlerQC.quantum.dataId)
388 inputs[
"photoCalib"] = row.getPhotoCalib()
390 outputs = self.run(**inputs)
391 butlerQC.put(outputs, outputRefs)
393 def run(self, fakeCats, exposure, skyMap, wcs=None, photoCalib=None, exposureIdInfo=None,
394 icSourceCat=None, sfdSourceCat=None, externalSkyWcsGlobalCatalog=None,
395 externalSkyWcsTractCatalog=None, externalPhotoCalibGlobalCatalog=None,
396 externalPhotoCalibTractCatalog=None):
397 """Add fake sources to a calexp and then run detection, deblending and measurement.
401 fakeCats : `list` of `lsst.daf.butler.DeferredDatasetHandle`
402 Set of tract level fake catalogs that potentially cover
404 exposure : `lsst.afw.image.exposure.exposure.ExposureF`
405 The exposure to add the fake sources to
406 skyMap : `lsst.skymap.SkyMap`
407 SkyMap defining the tracts and patches the fakes are stored over.
409 WCS to use to add fake sources
410 photoCalib : `lsst.afw.image.photoCalib.PhotoCalib`
411 Photometric calibration to be used to calibrate the fake sources
412 exposureIdInfo : `lsst.obs.base.ExposureIdInfo`
415 Catalog to take the information about which sources were used
for calibration
from.
418 Catalog produced by singleFrameDriver, needed to copy some calibration flags
from.
422 resultStruct : `lsst.pipe.base.struct.Struct`
423 contains : outputExposure : `lsst.afw.image.exposure.exposure.ExposureF`
424 outputCat : `lsst.afw.table.source.source.SourceCatalog`
428 Adds pixel coordinates
for each source to the fakeCat
and removes objects
with bulge
or disk half
429 light radius = 0 (
if ``config.cleanCat =
True``). These columns are called ``x``
and ``y``
and are
in
432 Adds the ``Fake`` mask plane to the exposure which
is then set by `addFakeSources` to mark where fake
433 sources have been added. Uses the information
in the ``fakeCat`` to make fake galaxies (using galsim)
434 and fake stars, using the PSF models
from the PSF information
for the calexp. These are then added to
435 the calexp
and the calexp
with fakes included returned.
437 The galsim galaxies are made using a double sersic profile, one
for the bulge
and one
for the disk,
438 this
is then convolved
with the PSF at that point.
440 If exposureIdInfo
is not provided then the SourceCatalog IDs will
not be globally unique.
442 fakeCat = self.composeFakeCat(fakeCats, skyMap)
445 wcs = exposure.getWcs()
447 if photoCalib
is None:
448 photoCalib = exposure.getPhotoCalib()
450 if self.config.doMatchVisit:
451 fakeCat = self.getVisitMatchedFakeCat(fakeCat, exposure)
453 self.insertFakes.run(fakeCat, exposure, wcs, photoCalib)
456 if exposureIdInfo
is None:
457 exposureIdInfo = ExposureIdInfo()
458 returnedStruct = self.calibrate.run(exposure, exposureIdInfo=exposureIdInfo)
459 sourceCat = returnedStruct.sourceCat
461 sourceCat = self.copyCalibrationFields(sfdSourceCat, sourceCat, self.config.srcFieldsToCopy)
463 resultStruct = pipeBase.Struct(outputExposure=exposure, outputCat=sourceCat)
466 def composeFakeCat(self, fakeCats, skyMap):
467 """Concatenate the fakeCats from tracts that may cover the exposure.
471 fakeCats : `list` of `lsst.daf.butler.DeferredDatasetHandle`
472 Set of fake cats to concatenate.
473 skyMap : `lsst.skymap.SkyMap`
474 SkyMap defining the geometry of the tracts and patches.
478 combinedFakeCat : `pandas.DataFrame`
479 All fakes that cover the inner polygon of the tracts
in this
482 if len(fakeCats) == 1:
483 return fakeCats[0].get()
485 for fakeCatRef
in fakeCats:
486 cat = fakeCatRef.get()
487 tractId = fakeCatRef.dataId[
"tract"]
489 outputCat.append(cat[
490 skyMap.findTractIdArray(cat[self.config.insertFakes.ra_col],
491 cat[self.config.insertFakes.dec_col],
495 return pd.concat(outputCat)
497 def getVisitMatchedFakeCat(self, fakeCat, exposure):
498 """Trim the fakeCat to select particular visit
502 fakeCat : `pandas.core.frame.DataFrame`
503 The catalog of fake sources to add to the exposure
504 exposure : `lsst.afw.image.exposure.exposure.ExposureF`
505 The exposure to add the fake sources to
509 movingFakeCat : `pandas.DataFrame`
510 All fakes that belong to the visit
512 selected = exposure.getInfo().getVisitInfo().getId() == fakeCat["visit"]
514 return fakeCat[selected]
516 def copyCalibrationFields(self, calibCat, sourceCat, fieldsToCopy):
517 """Match sources in calibCat and sourceCat and copy the specified fields
522 Catalog from which to copy fields.
524 Catalog to which to copy fields.
526 Fields to copy
from calibCat to SoourceCat.
531 Catalog which includes the copied fields.
533 The fields copied are those specified by `fieldsToCopy` that actually exist
534 in the schema of `calibCat`.
536 This version was based on
and adapted
from the one
in calibrateTask.
540 sourceSchemaMapper = afwTable.SchemaMapper(sourceCat.schema)
541 sourceSchemaMapper.addMinimalSchema(sourceCat.schema,
True)
543 calibSchemaMapper = afwTable.SchemaMapper(calibCat.schema, sourceCat.schema)
546 missingFieldNames = []
547 for fieldName
in fieldsToCopy:
548 if fieldName
in calibCat.schema:
549 schemaItem = calibCat.schema.find(fieldName)
550 calibSchemaMapper.editOutputSchema().addField(schemaItem.getField())
551 schema = calibSchemaMapper.editOutputSchema()
552 calibSchemaMapper.addMapping(schemaItem.getKey(), schema.find(fieldName).getField())
554 missingFieldNames.append(fieldName)
555 if missingFieldNames:
556 raise RuntimeError(f
"calibCat is missing fields {missingFieldNames} specified in "
559 if "calib_detected" not in calibSchemaMapper.getOutputSchema():
560 self.calibSourceKey = calibSchemaMapper.addOutputField(afwTable.Field[
"Flag"](
"calib_detected",
561 "Source was detected as an icSource"))
563 self.calibSourceKey =
None
565 schema = calibSchemaMapper.getOutputSchema()
566 newCat = afwTable.SourceCatalog(schema)
567 newCat.reserve(len(sourceCat))
568 newCat.extend(sourceCat, sourceSchemaMapper)
571 for k, v
in sourceCat.schema.getAliasMap().items():
572 newCat.schema.getAliasMap().set(k, v)
574 select = newCat[
"deblend_nChild"] == 0
575 matches = afwTable.matchXy(newCat[select], calibCat, self.config.matchRadiusPix)
579 numMatches = len(matches)
580 numUniqueSources = len(set(m[1].getId()
for m
in matches))
581 if numUniqueSources != numMatches:
582 self.log.warning(
"%d calibCat sources matched only %d sourceCat sources", numMatches,
585 self.log.info(
"Copying flags from calibCat to sourceCat for %s sources", numMatches)
589 for src, calibSrc, d
in matches:
590 if self.calibSourceKey:
591 src.setFlag(self.calibSourceKey,
True)
596 calibSrcFootprint = calibSrc.getFootprint()
598 calibSrc.setFootprint(src.getFootprint())
599 src.assign(calibSrc, calibSchemaMapper)
601 calibSrc.setFootprint(calibSrcFootprint)
607 ccdVisitFakeMagnitudes = cT.Output(
608 doc=
"Catalog of fakes with magnitudes scattered for this ccdVisit.",
609 name=
"{fakesType}ccdVisitFakeMagnitudes",
610 storageClass=
"DataFrame",
611 dimensions=(
"instrument",
"visit",
"detector"),
615class ProcessCcdWithVariableFakesConfig(ProcessCcdWithFakesConfig,
616 pipelineConnections=ProcessCcdWithVariableFakesConnections):
617 scatterSize = pexConfig.RangeField(
622 doc=
"Amount of scatter to add to the visit magnitude for variable "
627class ProcessCcdWithVariableFakesTask(ProcessCcdWithFakesTask):
628 """As ProcessCcdWithFakes except add variablity to the fakes catalog
629 magnitude in the observed band
for this ccdVisit.
631 Additionally, write out the modified magnitudes to the Butler.
634 _DefaultName = "processCcdWithVariableFakes"
635 ConfigClass = ProcessCcdWithVariableFakesConfig
637 def run(self, fakeCats, exposure, skyMap, wcs=None, photoCalib=None, exposureIdInfo=None,
638 icSourceCat=None, sfdSourceCat=None):
639 """Add fake sources to a calexp and then run detection, deblending and measurement.
643 fakeCat : `pandas.core.frame.DataFrame`
644 The catalog of fake sources to add to the exposure
645 exposure : `lsst.afw.image.exposure.exposure.ExposureF`
646 The exposure to add the fake sources to
647 skyMap : `lsst.skymap.SkyMap`
648 SkyMap defining the tracts and patches the fakes are stored over.
650 WCS to use to add fake sources
651 photoCalib : `lsst.afw.image.photoCalib.PhotoCalib`
652 Photometric calibration to be used to calibrate the fake sources
653 exposureIdInfo : `lsst.obs.base.ExposureIdInfo`
656 Catalog to take the information about which sources were used
for calibration
from.
659 Catalog produced by singleFrameDriver, needed to copy some calibration flags
from.
663 resultStruct : `lsst.pipe.base.struct.Struct`
664 Results Strcut containing:
666 - outputExposure : Exposure
with added fakes
667 (`lsst.afw.image.exposure.exposure.ExposureF`)
668 - outputCat : Catalog
with detected fakes
669 (`lsst.afw.table.source.source.SourceCatalog`)
670 - ccdVisitFakeMagnitudes : Magnitudes that these fakes were
671 inserted
with after being scattered (`pandas.DataFrame`)
675 Adds pixel coordinates
for each source to the fakeCat
and removes objects
with bulge
or disk half
676 light radius = 0 (
if ``config.cleanCat =
True``). These columns are called ``x``
and ``y``
and are
in
679 Adds the ``Fake`` mask plane to the exposure which
is then set by `addFakeSources` to mark where fake
680 sources have been added. Uses the information
in the ``fakeCat`` to make fake galaxies (using galsim)
681 and fake stars, using the PSF models
from the PSF information
for the calexp. These are then added to
682 the calexp
and the calexp
with fakes included returned.
684 The galsim galaxies are made using a double sersic profile, one
for the bulge
and one
for the disk,
685 this
is then convolved
with the PSF at that point.
687 If exposureIdInfo
is not provided then the SourceCatalog IDs will
not be globally unique.
689 fakeCat = self.composeFakeCat(fakeCats, skyMap)
692 wcs = exposure.getWcs()
694 if photoCalib
is None:
695 photoCalib = exposure.getPhotoCalib()
697 if exposureIdInfo
is None:
698 exposureIdInfo = ExposureIdInfo()
700 band = exposure.getFilter().bandLabel
701 ccdVisitMagnitudes = self.addVariablity(fakeCat, band, exposure, photoCalib, exposureIdInfo)
703 self.insertFakes.run(fakeCat, exposure, wcs, photoCalib)
706 returnedStruct = self.calibrate.run(exposure, exposureIdInfo=exposureIdInfo)
707 sourceCat = returnedStruct.sourceCat
709 sourceCat = self.copyCalibrationFields(sfdSourceCat, sourceCat, self.config.srcFieldsToCopy)
711 resultStruct = pipeBase.Struct(outputExposure=exposure,
713 ccdVisitFakeMagnitudes=ccdVisitMagnitudes)
716 def addVariablity(self, fakeCat, band, exposure, photoCalib, exposureIdInfo):
717 """Add scatter to the fake catalog visit magnitudes.
719 Currently just adds a simple Gaussian scatter around the static fake
720 magnitude. This function could be modified to return any number of
725 fakeCat : `pandas.DataFrame`
726 Catalog of fakes to modify magnitudes of.
728 Current observing band to modify.
729 exposure : `lsst.afw.image.ExposureF`
730 Exposure fakes will be added to.
732 Photometric calibration object of ``exposure``.
733 exposureIdInfo : `lsst.obs.base.ExposureIdInfo`
734 Exposure id information
and metadata.
738 dataFrame : `pandas.DataFrame`
739 DataFrame containing the values of the magnitudes to that will
740 be inserted into this ccdVisit.
742 expId = exposureIdInfo.expId
743 rng = np.random.default_rng(expId)
744 magScatter = rng.normal(loc=0,
745 scale=self.config.scatterSize,
747 visitMagnitudes = fakeCat[self.insertFakes.config.mag_col % band] + magScatter
748 fakeCat.loc[:, self.insertFakes.config.mag_col % band] = visitMagnitudes
749 return pd.DataFrame(data={
"variableMag": visitMagnitudes})