Coverage for python/lsst/pipe/tasks/processCcdWithFakes.py: 18%
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1# This file is part of pipe_tasks.
2#
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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
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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/>.
22"""
23Insert fake sources into calexps
24"""
26__all__ = ["ProcessCcdWithFakesConfig", "ProcessCcdWithFakesTask",
27 "ProcessCcdWithVariableFakesConfig", "ProcessCcdWithVariableFakesTask"]
29import numpy as np
30import pandas as pd
32import lsst.pex.config as pexConfig
33import lsst.pipe.base as pipeBase
35from .insertFakes import InsertFakesTask
36from lsst.afw.table import SourceTable
37from lsst.meas.base import IdGenerator, DetectorVisitIdGeneratorConfig
38from lsst.pipe.base import PipelineTask, PipelineTaskConfig, PipelineTaskConnections
39import lsst.pipe.base.connectionTypes as cT
40import lsst.afw.table as afwTable
41from lsst.skymap import BaseSkyMap
42from lsst.pipe.tasks.calibrate import CalibrateTask
45class ProcessCcdWithFakesConnections(PipelineTaskConnections,
46 dimensions=("instrument", "visit", "detector"),
47 defaultTemplates={"coaddName": "deep",
48 "wcsName": "gbdesAstrometricFit",
49 "photoCalibName": "jointcal",
50 "fakesType": "fakes_"}):
51 skyMap = cT.Input(
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",
57 )
59 exposure = cT.Input(
60 doc="Exposure into which fakes are to be added.",
61 name="calexp",
62 storageClass="ExposureF",
63 dimensions=("instrument", "visit", "detector")
64 )
66 fakeCats = cT.Input(
67 doc="Set of catalogs of fake sources to draw inputs from. We "
68 "concatenate the tract catalogs for detectorVisits that cover "
69 "multiple tracts.",
70 name="{fakesType}fakeSourceCat",
71 storageClass="DataFrame",
72 dimensions=("tract", "skymap"),
73 deferLoad=True,
74 multiple=True,
75 )
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"),
83 deferLoad=True,
84 multiple=True,
85 )
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 "
90 "fast lookup."),
91 name="finalVisitSummary",
92 storageClass="ExposureCatalog",
93 dimensions=("instrument", "visit"),
94 )
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"),
102 deferLoad=True,
103 multiple=True,
104 )
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"),
112 )
114 icSourceCat = cT.Input(
115 doc="Catalog of calibration sources",
116 name="icSrc",
117 storageClass="SourceCatalog",
118 dimensions=("instrument", "visit", "detector")
119 )
121 sfdSourceCat = cT.Input(
122 doc="Catalog of calibration sources",
123 name="src",
124 storageClass="SourceCatalog",
125 dimensions=("instrument", "visit", "detector")
126 )
128 outputExposure = cT.Output(
129 doc="Exposure with fake sources added.",
130 name="{fakesType}calexp",
131 storageClass="ExposureF",
132 dimensions=("instrument", "visit", "detector")
133 )
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"),
140 )
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
160 Notes
161 -----
162 The default column names are those from the UW sims database.
163 """
165 doApplyExternalGlobalPhotoCalib = pexConfig.Field(
166 dtype=bool,
167 default=False,
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."
172 )
174 doApplyExternalTractPhotoCalib = pexConfig.Field(
175 dtype=bool,
176 default=False,
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."
181 )
183 externalPhotoCalibName = pexConfig.ChoiceField(
184 doc="What type of external photo calib to use.",
185 dtype=str,
186 default="jointcal",
187 allowed={"jointcal": "Use jointcal_photoCalib",
188 "fgcm": "Use fgcm_photoCalib",
189 "fgcm_tract": "Use fgcm_tract_photoCalib"}
190 )
192 doApplyExternalGlobalSkyWcs = pexConfig.Field(
193 dtype=bool,
194 default=False,
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."
199 )
201 doApplyExternalTractSkyWcs = pexConfig.Field(
202 dtype=bool,
203 default=False,
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."
208 )
210 externalSkyWcsName = pexConfig.ChoiceField(
211 doc="What type of updated WCS calib to use.",
212 dtype=str,
213 default="gbdesAstrometricFit",
214 allowed={"gbdesAstrometricFit": "Use gbdesAstrometricFit_wcs"}
215 )
217 coaddName = pexConfig.Field(
218 doc="The name of the type of coadd used",
219 dtype=str,
220 default="deep",
221 )
223 srcFieldsToCopy = pexConfig.ListField(
224 dtype=str,
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.")
230 )
232 matchRadiusPix = pexConfig.Field(
233 dtype=float,
234 default=3,
235 doc=("Match radius for matching icSourceCat objects to sourceCat objects (pixels)"),
236 )
238 doMatchVisit = pexConfig.Field(
239 dtype=bool,
240 default=False,
241 doc="Match visit to trim the fakeCat"
242 )
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 idGenerator = DetectorVisitIdGeneratorConfig.make_field()
252 def setDefaults(self):
253 super().setDefaults()
254 self.calibrate.measurement.plugins["base_PixelFlags"].masksFpAnywhere.append("FAKE")
255 self.calibrate.measurement.plugins["base_PixelFlags"].masksFpCenter.append("FAKE")
256 self.calibrate.doAstrometry = False
257 self.calibrate.doWriteMatches = False
258 self.calibrate.doPhotoCal = False
259 self.calibrate.doComputeSummaryStats = False
260 self.calibrate.detection.reEstimateBackground = False
263class ProcessCcdWithFakesTask(PipelineTask):
264 """Insert fake objects into calexps.
266 Add fake stars and galaxies to the given calexp, specified in the dataRef. Galaxy parameters are read in
267 from the specified file and then modelled using galsim. Re-runs characterize image and calibrate image to
268 give a new background estimation and measurement of the calexp.
270 `ProcessFakeSourcesTask` inherits six functions from insertFakesTask that make images of the fake
271 sources and then add them to the calexp.
273 `addPixCoords`
274 Use the WCS information to add the pixel coordinates of each source
275 Adds an ``x`` and ``y`` column to the catalog of fake sources.
276 `trimFakeCat`
277 Trim the fake cat to about the size of the input image.
278 `mkFakeGalsimGalaxies`
279 Use Galsim to make fake double sersic galaxies for each set of galaxy parameters in the input file.
280 `mkFakeStars`
281 Use the PSF information from the calexp to make a fake star using the magnitude information from the
282 input file.
283 `cleanCat`
284 Remove rows of the input fake catalog which have half light radius, of either the bulge or the disk,
285 that are 0.
286 `addFakeSources`
287 Add the fake sources to the calexp.
289 Notes
290 -----
291 The ``calexp`` with fake souces added to it is written out as the datatype ``calexp_fakes``.
292 """
294 _DefaultName = "processCcdWithFakes"
295 ConfigClass = ProcessCcdWithFakesConfig
297 def __init__(self, schema=None, butler=None, **kwargs):
298 """Initalize things! This should go above in the class docstring
299 """
301 super().__init__(**kwargs)
303 if schema is None:
304 schema = SourceTable.makeMinimalSchema()
305 self.schema = schema
306 self.makeSubtask("insertFakes")
307 self.makeSubtask("calibrate")
309 def runQuantum(self, butlerQC, inputRefs, outputRefs):
310 inputs = butlerQC.get(inputRefs)
311 detectorId = inputs["exposure"].getInfo().getDetector().getId()
313 if 'idGenerator' not in inputs.keys():
314 inputs['idGenerator'] = self.config.idGenerator.apply(butlerQC.quantum.dataId)
316 expWcs = inputs["exposure"].getWcs()
317 tractId = None
318 if not self.config.doApplyExternalGlobalSkyWcs and not self.config.doApplyExternalTractSkyWcs:
319 if expWcs is None:
320 self.log.info("No WCS for exposure %s so cannot insert fake sources. Skipping detector.",
321 butlerQC.quantum.dataId)
322 return None
323 else:
324 inputs["wcs"] = expWcs
325 elif self.config.doApplyExternalGlobalSkyWcs:
326 externalSkyWcsCatalog = inputs["externalSkyWcsGlobalCatalog"]
327 row = externalSkyWcsCatalog.find(detectorId)
328 if row is None:
329 self.log.info("No %s external global sky WCS for exposure %s so cannot insert fake "
330 "sources. Skipping detector.", self.config.externalSkyWcsName,
331 butlerQC.quantum.dataId)
332 return None
333 inputs["wcs"] = row.getWcs()
334 elif self.config.doApplyExternalTractSkyWcs:
335 externalSkyWcsCatalogList = inputs["externalSkyWcsTractCatalog"]
336 if tractId is None:
337 tractId = externalSkyWcsCatalogList[0].dataId["tract"]
338 externalSkyWcsCatalog = None
339 for externalSkyWcsCatalogRef in externalSkyWcsCatalogList:
340 if externalSkyWcsCatalogRef.dataId["tract"] == tractId:
341 externalSkyWcsCatalog = externalSkyWcsCatalogRef.get()
342 break
343 if externalSkyWcsCatalog is None:
344 usedTract = externalSkyWcsCatalogList[-1].dataId["tract"]
345 self.log.warn(
346 f"Warning, external SkyWcs for tract {tractId} not found. Using tract {usedTract} "
347 "instead.")
348 externalSkyWcsCatalog = externalSkyWcsCatalogList[-1].get()
349 row = externalSkyWcsCatalog.find(detectorId)
350 if row is None:
351 self.log.info("No %s external tract sky WCS for exposure %s so cannot insert fake "
352 "sources. Skipping detector.", self.config.externalSkyWcsName,
353 butlerQC.quantum.dataId)
354 return None
355 inputs["wcs"] = row.getWcs()
357 if not self.config.doApplyExternalGlobalPhotoCalib and not self.config.doApplyExternalTractPhotoCalib:
358 inputs["photoCalib"] = inputs["exposure"].getPhotoCalib()
359 elif self.config.doApplyExternalGlobalPhotoCalib:
360 externalPhotoCalibCatalog = inputs["externalPhotoCalibGlobalCatalog"]
361 row = externalPhotoCalibCatalog.find(detectorId)
362 if row is None:
363 self.log.info("No %s external global photoCalib for exposure %s so cannot insert fake "
364 "sources. Skipping detector.", self.config.externalPhotoCalibName,
365 butlerQC.quantum.dataId)
366 return None
367 inputs["photoCalib"] = row.getPhotoCalib()
368 elif self.config.doApplyExternalTractPhotoCalib:
369 externalPhotoCalibCatalogList = inputs["externalPhotoCalibTractCatalog"]
370 if tractId is None:
371 tractId = externalPhotoCalibCatalogList[0].dataId["tract"]
372 externalPhotoCalibCatalog = None
373 for externalPhotoCalibCatalogRef in externalPhotoCalibCatalogList:
374 if externalPhotoCalibCatalogRef.dataId["tract"] == tractId:
375 externalPhotoCalibCatalog = externalPhotoCalibCatalogRef.get()
376 break
377 if externalPhotoCalibCatalog is None:
378 usedTract = externalPhotoCalibCatalogList[-1].dataId["tract"]
379 self.log.warn(
380 f"Warning, external PhotoCalib for tract {tractId} not found. Using tract {usedTract} "
381 "instead.")
382 externalPhotoCalibCatalog = externalPhotoCalibCatalogList[-1].get()
383 row = externalPhotoCalibCatalog.find(detectorId)
384 if row is None:
385 self.log.info("No %s external tract photoCalib for exposure %s so cannot insert fake "
386 "sources. Skipping detector.", self.config.externalPhotoCalibName,
387 butlerQC.quantum.dataId)
388 return None
389 inputs["photoCalib"] = row.getPhotoCalib()
391 outputs = self.run(**inputs)
392 butlerQC.put(outputs, outputRefs)
394 def run(self, fakeCats, exposure, skyMap, wcs=None, photoCalib=None, exposureIdInfo=None,
395 icSourceCat=None, sfdSourceCat=None, externalSkyWcsGlobalCatalog=None,
396 externalSkyWcsTractCatalog=None, externalPhotoCalibGlobalCatalog=None,
397 externalPhotoCalibTractCatalog=None, idGenerator=None):
398 """Add fake sources to a calexp and then run detection, deblending and
399 measurement.
401 Parameters
402 ----------
403 fakeCats : `list` of `lsst.daf.butler.DeferredDatasetHandle`
404 Set of tract level fake catalogs that potentially cover this
405 detectorVisit.
406 exposure : `lsst.afw.image.exposure.exposure.ExposureF`
407 The exposure to add the fake sources to.
408 skyMap : `lsst.skymap.SkyMap`
409 SkyMap defining the tracts and patches the fakes are stored over.
410 wcs : `lsst.afw.geom.SkyWcs`, optional
411 WCS to use to add fake sources.
412 photoCalib : `lsst.afw.image.photoCalib.PhotoCalib`, optional
413 Photometric calibration to be used to calibrate the fake sources.
414 exposureIdInfo : `lsst.obs.base.ExposureIdInfo`, optional
415 Object that carries ID information for this image/catalog.
416 Deprecated in favor of ``idGenerator``.
417 icSourceCat : `lsst.afw.table.SourceCatalog`, optional
418 Catalog to take the information about which sources were used for
419 calibration from.
420 sfdSourceCat : `lsst.afw.table.SourceCatalog`, optional
421 Catalog produced by singleFrameDriver, needed to copy some
422 calibration flags from.
423 externalSkyWcsGlobalCatalog : `lsst.afw.table.ExposureCatalog`, \
424 optional
425 Exposure catalog with external skyWcs to be applied per config.
426 externalSkyWcsTractCatalog : `lsst.afw.table.ExposureCatalog`, optional
427 Exposure catalog with external skyWcs to be applied per config.
428 externalPhotoCalibGlobalCatalog : `lsst.afw.table.ExposureCatalog`, \
429 optional
430 Exposure catalog with external photoCalib to be applied per config
431 externalPhotoCalibTractCatalog : `lsst.afw.table.ExposureCatalog`, \
432 optional
433 Exposure catalog with external photoCalib to be applied per config.
434 idGenerator : `lsst.meas.base.IdGenerator`, optional
435 Object that generates Source IDs and random seeds.
437 Returns
438 -------
439 resultStruct : `lsst.pipe.base.struct.Struct`
440 Result struct containing:
442 - outputExposure: `lsst.afw.image.exposure.exposure.ExposureF`
443 - outputCat: `lsst.afw.table.source.source.SourceCatalog`
445 Notes
446 -----
447 Adds pixel coordinates for each source to the fakeCat and removes
448 objects with bulge or disk half light radius = 0 (if ``config.cleanCat
449 = True``). These columns are called ``x`` and ``y`` and are in pixels.
451 Adds the ``Fake`` mask plane to the exposure which is then set by
452 `addFakeSources` to mark where fake sources have been added. Uses the
453 information in the ``fakeCat`` to make fake galaxies (using galsim) and
454 fake stars, using the PSF models from the PSF information for the
455 calexp. These are then added to the calexp and the calexp with fakes
456 included returned.
458 The galsim galaxies are made using a double sersic profile, one for the
459 bulge and one for the disk, this is then convolved with the PSF at that
460 point.
461 """
462 fakeCat = self.composeFakeCat(fakeCats, skyMap)
464 if wcs is None:
465 wcs = exposure.getWcs()
467 if photoCalib is None:
468 photoCalib = exposure.getPhotoCalib()
470 if self.config.doMatchVisit:
471 fakeCat = self.getVisitMatchedFakeCat(fakeCat, exposure)
473 self.insertFakes.run(fakeCat, exposure, wcs, photoCalib)
475 # detect, deblend and measure sources
476 if idGenerator is None:
477 if exposureIdInfo is not None:
478 idGenerator = IdGenerator._from_exposure_id_info(exposureIdInfo)
479 else:
480 idGenerator = IdGenerator()
481 returnedStruct = self.calibrate.run(exposure, idGenerator=idGenerator)
482 sourceCat = returnedStruct.sourceCat
484 sourceCat = self.copyCalibrationFields(sfdSourceCat, sourceCat, self.config.srcFieldsToCopy)
486 resultStruct = pipeBase.Struct(outputExposure=exposure, outputCat=sourceCat)
487 return resultStruct
489 def composeFakeCat(self, fakeCats, skyMap):
490 """Concatenate the fakeCats from tracts that may cover the exposure.
492 Parameters
493 ----------
494 fakeCats : `list` of `lsst.daf.butler.DeferredDatasetHandle`
495 Set of fake cats to concatenate.
496 skyMap : `lsst.skymap.SkyMap`
497 SkyMap defining the geometry of the tracts and patches.
499 Returns
500 -------
501 combinedFakeCat : `pandas.DataFrame`
502 All fakes that cover the inner polygon of the tracts in this
503 quantum.
504 """
505 if len(fakeCats) == 1:
506 return fakeCats[0].get()
507 outputCat = []
508 for fakeCatRef in fakeCats:
509 cat = fakeCatRef.get()
510 tractId = fakeCatRef.dataId["tract"]
511 # Make sure all data is within the inner part of the tract.
512 outputCat.append(cat[
513 skyMap.findTractIdArray(cat[self.config.insertFakes.ra_col],
514 cat[self.config.insertFakes.dec_col],
515 degrees=False)
516 == tractId])
518 return pd.concat(outputCat)
520 def getVisitMatchedFakeCat(self, fakeCat, exposure):
521 """Trim the fakeCat to select particular visit
523 Parameters
524 ----------
525 fakeCat : `pandas.core.frame.DataFrame`
526 The catalog of fake sources to add to the exposure
527 exposure : `lsst.afw.image.exposure.exposure.ExposureF`
528 The exposure to add the fake sources to
530 Returns
531 -------
532 movingFakeCat : `pandas.DataFrame`
533 All fakes that belong to the visit
534 """
535 selected = exposure.getInfo().getVisitInfo().getId() == fakeCat["visit"]
537 return fakeCat[selected]
539 def copyCalibrationFields(self, calibCat, sourceCat, fieldsToCopy):
540 """Match sources in calibCat and sourceCat and copy the specified fields
542 Parameters
543 ----------
544 calibCat : `lsst.afw.table.SourceCatalog`
545 Catalog from which to copy fields.
546 sourceCat : `lsst.afw.table.SourceCatalog`
547 Catalog to which to copy fields.
548 fieldsToCopy : `lsst.pex.config.listField.List`
549 Fields to copy from calibCat to SoourceCat.
551 Returns
552 -------
553 newCat : `lsst.afw.table.SourceCatalog`
554 Catalog which includes the copied fields.
556 The fields copied are those specified by `fieldsToCopy` that actually exist
557 in the schema of `calibCat`.
559 This version was based on and adapted from the one in calibrateTask.
560 """
562 # Make a new SourceCatalog with the data from sourceCat so that we can add the new columns to it
563 sourceSchemaMapper = afwTable.SchemaMapper(sourceCat.schema)
564 sourceSchemaMapper.addMinimalSchema(sourceCat.schema, True)
566 calibSchemaMapper = afwTable.SchemaMapper(calibCat.schema, sourceCat.schema)
568 # Add the desired columns from the option fieldsToCopy
569 missingFieldNames = []
570 for fieldName in fieldsToCopy:
571 if fieldName in calibCat.schema:
572 schemaItem = calibCat.schema.find(fieldName)
573 calibSchemaMapper.editOutputSchema().addField(schemaItem.getField())
574 schema = calibSchemaMapper.editOutputSchema()
575 calibSchemaMapper.addMapping(schemaItem.getKey(), schema.find(fieldName).getField())
576 else:
577 missingFieldNames.append(fieldName)
578 if missingFieldNames:
579 raise RuntimeError(f"calibCat is missing fields {missingFieldNames} specified in "
580 "fieldsToCopy")
582 if "calib_detected" not in calibSchemaMapper.getOutputSchema():
583 self.calibSourceKey = calibSchemaMapper.addOutputField(afwTable.Field["Flag"]("calib_detected",
584 "Source was detected as an icSource"))
585 else:
586 self.calibSourceKey = None
588 schema = calibSchemaMapper.getOutputSchema()
589 newCat = afwTable.SourceCatalog(schema)
590 newCat.reserve(len(sourceCat))
591 newCat.extend(sourceCat, sourceSchemaMapper)
593 # Set the aliases so it doesn't complain.
594 for k, v in sourceCat.schema.getAliasMap().items():
595 newCat.schema.getAliasMap().set(k, v)
597 select = newCat["deblend_nChild"] == 0
598 matches = afwTable.matchXy(newCat[select], calibCat, self.config.matchRadiusPix)
599 # Check that no sourceCat sources are listed twice (we already know
600 # that each match has a unique calibCat source ID, due to using
601 # that ID as the key in bestMatches)
602 numMatches = len(matches)
603 numUniqueSources = len(set(m[1].getId() for m in matches))
604 if numUniqueSources != numMatches:
605 self.log.warning("%d calibCat sources matched only %d sourceCat sources", numMatches,
606 numUniqueSources)
608 self.log.info("Copying flags from calibCat to sourceCat for %s sources", numMatches)
610 # For each match: set the calibSourceKey flag and copy the desired
611 # fields
612 for src, calibSrc, d in matches:
613 if self.calibSourceKey:
614 src.setFlag(self.calibSourceKey, True)
615 # src.assign copies the footprint from calibSrc, which we don't want
616 # (DM-407)
617 # so set calibSrc's footprint to src's footprint before src.assign,
618 # then restore it
619 calibSrcFootprint = calibSrc.getFootprint()
620 try:
621 calibSrc.setFootprint(src.getFootprint())
622 src.assign(calibSrc, calibSchemaMapper)
623 finally:
624 calibSrc.setFootprint(calibSrcFootprint)
626 return newCat
629class ProcessCcdWithVariableFakesConnections(ProcessCcdWithFakesConnections):
630 ccdVisitFakeMagnitudes = cT.Output(
631 doc="Catalog of fakes with magnitudes scattered for this ccdVisit.",
632 name="{fakesType}ccdVisitFakeMagnitudes",
633 storageClass="DataFrame",
634 dimensions=("instrument", "visit", "detector"),
635 )
638class ProcessCcdWithVariableFakesConfig(ProcessCcdWithFakesConfig,
639 pipelineConnections=ProcessCcdWithVariableFakesConnections):
640 scatterSize = pexConfig.RangeField(
641 dtype=float,
642 default=0.4,
643 min=0,
644 max=100,
645 doc="Amount of scatter to add to the visit magnitude for variable "
646 "sources."
647 )
650class ProcessCcdWithVariableFakesTask(ProcessCcdWithFakesTask):
651 """As ProcessCcdWithFakes except add variablity to the fakes catalog
652 magnitude in the observed band for this ccdVisit.
654 Additionally, write out the modified magnitudes to the Butler.
655 """
657 _DefaultName = "processCcdWithVariableFakes"
658 ConfigClass = ProcessCcdWithVariableFakesConfig
660 def run(self, fakeCats, exposure, skyMap, wcs=None, photoCalib=None, exposureIdInfo=None,
661 icSourceCat=None, sfdSourceCat=None, idGenerator=None):
662 """Add fake sources to a calexp and then run detection, deblending and
663 measurement.
665 Parameters
666 ----------
667 fakeCat : `pandas.core.frame.DataFrame`
668 The catalog of fake sources to add to the exposure.
669 exposure : `lsst.afw.image.exposure.exposure.ExposureF`
670 The exposure to add the fake sources to.
671 skyMap : `lsst.skymap.SkyMap`
672 SkyMap defining the tracts and patches the fakes are stored over.
673 wcs : `lsst.afw.geom.SkyWcs`, optional
674 WCS to use to add fake sources.
675 photoCalib : `lsst.afw.image.photoCalib.PhotoCalib`, optional
676 Photometric calibration to be used to calibrate the fake sources.
677 exposureIdInfo : `lsst.obs.base.ExposureIdInfo`, optional
678 Object that carries ID information for this image/catalog.
679 Deprecated in favor of ``idGenerator``.
680 icSourceCat : `lsst.afw.table.SourceCatalog`, optional
681 Catalog to take the information about which sources were used for
682 calibration from.
683 sfdSourceCat : `lsst.afw.table.SourceCatalog`, optional
684 Catalog produced by singleFrameDriver, needed to copy some
685 calibration flags from.
686 idGenerator : `lsst.meas.base.IdGenerator`, optional
687 Object that generates Source IDs and random seeds.
689 Returns
690 -------
691 resultStruct : `lsst.pipe.base.struct.Struct`
692 Results struct containing:
694 - outputExposure : Exposure with added fakes
695 (`lsst.afw.image.exposure.exposure.ExposureF`)
696 - outputCat : Catalog with detected fakes
697 (`lsst.afw.table.source.source.SourceCatalog`)
698 - ccdVisitFakeMagnitudes : Magnitudes that these fakes were
699 inserted with after being scattered (`pandas.DataFrame`)
701 Notes
702 -----
703 Adds pixel coordinates for each source to the fakeCat and removes
704 objects with bulge or disk half light radius = 0 (if ``config.cleanCat
705 = True``). These columns are called ``x`` and ``y`` and are in pixels.
707 Adds the ``Fake`` mask plane to the exposure which is then set by
708 `addFakeSources` to mark where fake sources have been added. Uses the
709 information in the ``fakeCat`` to make fake galaxies (using galsim) and
710 fake stars, using the PSF models from the PSF information for the
711 calexp. These are then added to the calexp and the calexp with fakes
712 included returned.
714 The galsim galaxies are made using a double sersic profile, one for the
715 bulge and one for the disk, this is then convolved with the PSF at that
716 point.
719 """
720 fakeCat = self.composeFakeCat(fakeCats, skyMap)
722 if wcs is None:
723 wcs = exposure.getWcs()
725 if photoCalib is None:
726 photoCalib = exposure.getPhotoCalib()
728 if idGenerator is None:
729 if exposureIdInfo is not None:
730 idGenerator = IdGenerator._from_exposure_id_info(exposureIdInfo)
731 else:
732 idGenerator = IdGenerator()
734 band = exposure.getFilter().bandLabel
735 ccdVisitMagnitudes = self.addVariability(
736 fakeCat,
737 band,
738 exposure,
739 photoCalib,
740 idGenerator.catalog_id,
741 )
743 self.insertFakes.run(fakeCat, exposure, wcs, photoCalib)
745 # detect, deblend and measure sources
746 returnedStruct = self.calibrate.run(exposure, idGenerator=idGenerator)
747 sourceCat = returnedStruct.sourceCat
749 sourceCat = self.copyCalibrationFields(sfdSourceCat, sourceCat, self.config.srcFieldsToCopy)
751 resultStruct = pipeBase.Struct(outputExposure=exposure,
752 outputCat=sourceCat,
753 ccdVisitFakeMagnitudes=ccdVisitMagnitudes)
754 return resultStruct
756 def addVariability(self, fakeCat, band, exposure, photoCalib, rngSeed):
757 """Add scatter to the fake catalog visit magnitudes.
759 Currently just adds a simple Gaussian scatter around the static fake
760 magnitude. This function could be modified to return any number of
761 fake variability.
763 Parameters
764 ----------
765 fakeCat : `pandas.DataFrame`
766 Catalog of fakes to modify magnitudes of.
767 band : `str`
768 Current observing band to modify.
769 exposure : `lsst.afw.image.ExposureF`
770 Exposure fakes will be added to.
771 photoCalib : `lsst.afw.image.PhotoCalib`
772 Photometric calibration object of ``exposure``.
773 rngSeed : `int`
774 Random number generator seed.
776 Returns
777 -------
778 dataFrame : `pandas.DataFrame`
779 DataFrame containing the values of the magnitudes to that will
780 be inserted into this ccdVisit.
781 """
782 rng = np.random.default_rng(rngSeed)
783 magScatter = rng.normal(loc=0,
784 scale=self.config.scatterSize,
785 size=len(fakeCat))
786 visitMagnitudes = fakeCat[self.insertFakes.config.mag_col % band] + magScatter
787 fakeCat.loc[:, self.insertFakes.config.mag_col % band] = visitMagnitudes
788 return pd.DataFrame(data={"variableMag": visitMagnitudes})