25from lsst.pipe.base import (Struct, PipelineTask, PipelineTaskConfig, PipelineTaskConnections)
26import lsst.pipe.base.connectionTypes
as cT
27from lsst.pex.config import Config, Field, ConfigurableField, ChoiceField
29from lsst.meas.base import SingleFrameMeasurementTask, ApplyApCorrTask, CatalogCalculationTask
31from lsst.meas.extensions.scarlet
import ScarletDeblendTask
40from lsst.obs.base
import ExposureIdInfo
43from .mergeDetections
import MergeDetectionsConfig, MergeDetectionsTask
44from .mergeMeasurements
import MergeMeasurementsConfig, MergeMeasurementsTask
45from .multiBandUtils
import CullPeaksConfig, _makeGetSchemaCatalogs
46from .deblendCoaddSourcesPipeline
import DeblendCoaddSourcesSingleConfig
47from .deblendCoaddSourcesPipeline
import DeblendCoaddSourcesSingleTask
48from .deblendCoaddSourcesPipeline
import DeblendCoaddSourcesMultiConfig
49from .deblendCoaddSourcesPipeline
import DeblendCoaddSourcesMultiTask
54* deepCoadd_det: detections from what used to be processCoadd (tract, patch, filter)
55* deepCoadd_mergeDet: merged detections (tract, patch)
56* deepCoadd_meas: measurements of merged detections (tract, patch, filter)
57* deepCoadd_ref: reference sources (tract, patch)
58All of these have associated *_schema catalogs that require no data ID and hold no records.
60In addition, we have a schema-only dataset, which saves the schema for the PeakRecords in
61the mergeDet, meas, and ref dataset Footprints:
62* deepCoadd_peak_schema
68 dimensions=(
"tract",
"patch",
"band",
"skymap"),
69 defaultTemplates={
"inputCoaddName":
"deep",
"outputCoaddName":
"deep"}):
70 detectionSchema = cT.InitOutput(
71 doc=
"Schema of the detection catalog",
72 name=
"{outputCoaddName}Coadd_det_schema",
73 storageClass=
"SourceCatalog",
76 doc=
"Exposure on which detections are to be performed",
77 name=
"{inputCoaddName}Coadd",
78 storageClass=
"ExposureF",
79 dimensions=(
"tract",
"patch",
"band",
"skymap")
81 outputBackgrounds = cT.Output(
82 doc=
"Output Backgrounds used in detection",
83 name=
"{outputCoaddName}Coadd_calexp_background",
84 storageClass=
"Background",
85 dimensions=(
"tract",
"patch",
"band",
"skymap")
87 outputSources = cT.Output(
88 doc=
"Detected sources catalog",
89 name=
"{outputCoaddName}Coadd_det",
90 storageClass=
"SourceCatalog",
91 dimensions=(
"tract",
"patch",
"band",
"skymap")
93 outputExposure = cT.Output(
94 doc=
"Exposure post detection",
95 name=
"{outputCoaddName}Coadd_calexp",
96 storageClass=
"ExposureF",
97 dimensions=(
"tract",
"patch",
"band",
"skymap")
101class DetectCoaddSourcesConfig(PipelineTaskConfig, pipelineConnections=DetectCoaddSourcesConnections):
103 @anchor DetectCoaddSourcesConfig_
105 @brief Configuration parameters
for the DetectCoaddSourcesTask
107 doScaleVariance = Field(dtype=bool, default=True, doc=
"Scale variance plane using empirical noise?")
108 scaleVariance = ConfigurableField(target=ScaleVarianceTask, doc=
"Variance rescaling")
109 detection = ConfigurableField(target=DynamicDetectionTask, doc=
"Source detection")
110 coaddName = Field(dtype=str, default=
"deep", doc=
"Name of coadd")
111 doInsertFakes = Field(dtype=bool, default=
False,
112 doc=
"Run fake sources injection task",
113 deprecated=(
"doInsertFakes is no longer supported. This config will be removed "
115 insertFakes = ConfigurableField(target=BaseFakeSourcesTask,
116 doc=
"Injection of fake sources for testing "
117 "purposes (must be retargeted)",
118 deprecated=(
"insertFakes is no longer supported. This config will "
119 "be removed after v24."))
123 doc=
"Should be set to True if fake sources have been inserted into the input data.",
126 def setDefaults(self):
127 super().setDefaults()
128 self.detection.thresholdType =
"pixel_stdev"
129 self.detection.isotropicGrow =
True
131 self.detection.reEstimateBackground =
False
132 self.detection.background.useApprox =
False
133 self.detection.background.binSize = 4096
134 self.detection.background.undersampleStyle =
'REDUCE_INTERP_ORDER'
135 self.detection.doTempWideBackground =
True
145class DetectCoaddSourcesTask(PipelineTask):
146 """Detect sources on a coadd."""
147 _DefaultName =
"detectCoaddSources"
148 ConfigClass = DetectCoaddSourcesConfig
149 getSchemaCatalogs = _makeGetSchemaCatalogs(
"det")
151 def __init__(self, schema=None, **kwargs):
153 @brief Initialize the task. Create the
@ref SourceDetectionTask_
"detection" subtask.
155 Keyword arguments (
in addition to those forwarded to PipelineTask.__init__):
157 @param[
in] schema: initial schema
for the output catalog, modified-
in place to include all
158 fields set by this task. If
None, the source minimal schema will be used.
159 @param[
in] **kwargs: keyword arguments to be passed to lsst.pipe.base.task.Task.__init__
163 super().__init__(**kwargs)
165 schema = afwTable.SourceTable.makeMinimalSchema()
167 self.makeSubtask(
"detection", schema=self.schema)
168 if self.config.doScaleVariance:
169 self.makeSubtask(
"scaleVariance")
171 self.detectionSchema = afwTable.SourceCatalog(self.schema)
173 def runQuantum(self, butlerQC, inputRefs, outputRefs):
174 inputs = butlerQC.get(inputRefs)
175 exposureIdInfo = ExposureIdInfo.fromDataId(butlerQC.quantum.dataId,
"tract_patch_band")
176 inputs[
"idFactory"] = exposureIdInfo.makeSourceIdFactory()
177 inputs[
"expId"] = exposureIdInfo.expId
178 outputs = self.run(**inputs)
179 butlerQC.put(outputs, outputRefs)
181 def run(self, exposure, idFactory, expId):
183 @brief Run detection on an exposure.
185 First scale the variance plane to match the observed variance
186 using
@ref ScaleVarianceTask. Then invoke the
@ref SourceDetectionTask_
"detection" subtask to
189 @param[
in,out] exposure: Exposure on which to detect (may be backround-subtracted
and scaled,
190 depending on configuration).
191 @param[
in] idFactory: IdFactory to set source identifiers
192 @param[
in] expId: Exposure identifier (integer)
for RNG seed
194 @return a pipe.base.Struct
with fields
195 - sources: catalog of detections
196 - backgrounds: list of backgrounds
198 if self.config.doScaleVariance:
199 varScale = self.scaleVariance.run(exposure.maskedImage)
200 exposure.getMetadata().add(
"VARIANCE_SCALE", varScale)
201 backgrounds = afwMath.BackgroundList()
202 table = afwTable.SourceTable.make(self.schema, idFactory)
203 detections = self.detection.run(table, exposure, expId=expId)
204 sources = detections.sources
205 fpSets = detections.fpSets
206 if hasattr(fpSets,
"background")
and fpSets.background:
207 for bg
in fpSets.background:
208 backgrounds.append(bg)
209 return Struct(outputSources=sources, outputBackgrounds=backgrounds, outputExposure=exposure)
215class DeblendCoaddSourcesConfig(Config):
216 """DeblendCoaddSourcesConfig
218 Configuration parameters for the `DeblendCoaddSourcesTask`.
220 singleBandDeblend = ConfigurableField(target=SourceDeblendTask,
221 doc="Deblend sources separately in each band")
222 multiBandDeblend = ConfigurableField(target=ScarletDeblendTask,
223 doc=
"Deblend sources simultaneously across bands")
224 simultaneous = Field(dtype=bool,
226 doc=
"Simultaneously deblend all bands? "
227 "True uses `multibandDeblend` while False uses `singleBandDeblend`")
228 coaddName = Field(dtype=str, default=
"deep", doc=
"Name of coadd")
229 hasFakes = Field(dtype=bool,
231 doc=
"Should be set to True if fake sources have been inserted into the input data.")
233 def setDefaults(self):
234 Config.setDefaults(self)
235 self.singleBandDeblend.propagateAllPeaks =
True
238class MeasureMergedCoaddSourcesConnections(PipelineTaskConnections, dimensions=(
"tract",
"patch",
"band",
"skymap"),
239 defaultTemplates={
"inputCoaddName":
"deep",
240 "outputCoaddName":
"deep",
241 "deblendedCatalog":
"deblendedFlux"}):
242 warnings.warn(
"MeasureMergedCoaddSourcesConnections.defaultTemplates is deprecated and no longer used. "
243 "Use MeasureMergedCoaddSourcesConfig.inputCatalog.")
244 inputSchema = cT.InitInput(
245 doc=
"Input schema for measure merged task produced by a deblender or detection task",
246 name=
"{inputCoaddName}Coadd_deblendedFlux_schema",
247 storageClass=
"SourceCatalog"
249 outputSchema = cT.InitOutput(
250 doc=
"Output schema after all new fields are added by task",
251 name=
"{inputCoaddName}Coadd_meas_schema",
252 storageClass=
"SourceCatalog"
254 refCat = cT.PrerequisiteInput(
255 doc=
"Reference catalog used to match measured sources against known sources",
257 storageClass=
"SimpleCatalog",
258 dimensions=(
"skypix",),
263 doc=
"Input coadd image",
264 name=
"{inputCoaddName}Coadd_calexp",
265 storageClass=
"ExposureF",
266 dimensions=(
"tract",
"patch",
"band",
"skymap")
269 doc=
"SkyMap to use in processing",
270 name=BaseSkyMap.SKYMAP_DATASET_TYPE_NAME,
271 storageClass=
"SkyMap",
272 dimensions=(
"skymap",),
274 visitCatalogs = cT.Input(
275 doc=
"Source catalogs for visits which overlap input tract, patch, band. Will be "
276 "further filtered in the task for the purpose of propagating flags from image calibration "
277 "and characterization to coadd objects. Only used in legacy PropagateVisitFlagsTask.",
279 dimensions=(
"instrument",
"visit",
"detector"),
280 storageClass=
"SourceCatalog",
283 sourceTableHandles = cT.Input(
284 doc=(
"Source tables that are derived from the ``CalibrateTask`` sources. "
285 "These tables contain astrometry and photometry flags, and optionally "
287 name=
"sourceTable_visit",
288 storageClass=
"DataFrame",
289 dimensions=(
"instrument",
"visit"),
293 finalizedSourceTableHandles = cT.Input(
294 doc=(
"Finalized source tables from ``FinalizeCalibrationTask``. These "
295 "tables contain PSF flags from the finalized PSF estimation."),
296 name=
"finalized_src_table",
297 storageClass=
"DataFrame",
298 dimensions=(
"instrument",
"visit"),
302 inputCatalog = cT.Input(
303 doc=(
"Name of the input catalog to use."
304 "If the single band deblender was used this should be 'deblendedFlux."
305 "If the multi-band deblender was used this should be 'deblendedModel, "
306 "or deblendedFlux if the multiband deblender was configured to output "
307 "deblended flux catalogs. If no deblending was performed this should "
309 name=
"{inputCoaddName}Coadd_{deblendedCatalog}",
310 storageClass=
"SourceCatalog",
311 dimensions=(
"tract",
"patch",
"band",
"skymap"),
313 scarletCatalog = cT.Input(
314 doc=
"Catalogs produced by multiband deblending",
315 name=
"{inputCoaddName}Coadd_deblendedCatalog",
316 storageClass=
"SourceCatalog",
317 dimensions=(
"tract",
"patch",
"skymap"),
319 scarletModels = cT.Input(
320 doc=
"Multiband scarlet models produced by the deblender",
321 name=
"{inputCoaddName}Coadd_scarletModelData",
322 storageClass=
"ScarletModelData",
323 dimensions=(
"tract",
"patch",
"skymap"),
325 outputSources = cT.Output(
326 doc=
"Source catalog containing all the measurement information generated in this task",
327 name=
"{outputCoaddName}Coadd_meas",
328 dimensions=(
"tract",
"patch",
"band",
"skymap"),
329 storageClass=
"SourceCatalog",
331 matchResult = cT.Output(
332 doc=
"Match catalog produced by configured matcher, optional on doMatchSources",
333 name=
"{outputCoaddName}Coadd_measMatch",
334 dimensions=(
"tract",
"patch",
"band",
"skymap"),
335 storageClass=
"Catalog",
337 denormMatches = cT.Output(
338 doc=
"Denormalized Match catalog produced by configured matcher, optional on "
339 "doWriteMatchesDenormalized",
340 name=
"{outputCoaddName}Coadd_measMatchFull",
341 dimensions=(
"tract",
"patch",
"band",
"skymap"),
342 storageClass=
"Catalog",
345 def __init__(self, *, config=None):
346 super().__init__(config=config)
347 if config.doPropagateFlags
is False:
348 self.inputs -= set((
"visitCatalogs",))
349 self.inputs -= set((
"sourceTableHandles",))
350 self.inputs -= set((
"finalizedSourceTableHandles",))
351 elif config.propagateFlags.target == PropagateSourceFlagsTask:
353 self.inputs -= set((
"visitCatalogs",))
355 if not config.propagateFlags.source_flags:
356 self.inputs -= set((
"sourceTableHandles",))
357 if not config.propagateFlags.finalized_source_flags:
358 self.inputs -= set((
"finalizedSourceTableHandles",))
361 self.inputs -= set((
"sourceTableHandles",))
362 self.inputs -= set((
"finalizedSourceTableHandles",))
364 if config.inputCatalog ==
"deblendedCatalog":
365 self.inputs -= set((
"inputCatalog",))
367 if not config.doAddFootprints:
368 self.inputs -= set((
"scarletModels",))
370 self.inputs -= set((
"deblendedCatalog"))
371 self.inputs -= set((
"scarletModels",))
373 if config.doMatchSources
is False:
374 self.outputs -= set((
"matchResult",))
376 if config.doWriteMatchesDenormalized
is False:
377 self.outputs -= set((
"denormMatches",))
380class MeasureMergedCoaddSourcesConfig(PipelineTaskConfig,
381 pipelineConnections=MeasureMergedCoaddSourcesConnections):
383 @anchor MeasureMergedCoaddSourcesConfig_
385 @brief Configuration parameters
for the MeasureMergedCoaddSourcesTask
387 inputCatalog = ChoiceField(
389 default="deblendedCatalog",
391 "deblendedCatalog":
"Output catalog from ScarletDeblendTask",
392 "deblendedFlux":
"Output catalog from SourceDeblendTask",
393 "mergeDet":
"The merged detections before deblending."
395 doc=
"The name of the input catalog.",
397 doAddFootprints = Field(dtype=bool,
399 doc=
"Whether or not to add footprints to the input catalog from scarlet models. "
400 "This should be true whenever using the multi-band deblender, "
401 "otherwise this should be False.")
402 doConserveFlux = Field(dtype=bool, default=
True,
403 doc=
"Whether to use the deblender models as templates to re-distribute the flux "
404 "from the 'exposure' (True), or to perform measurements on the deblender "
406 doStripFootprints = Field(dtype=bool, default=
True,
407 doc=
"Whether to strip footprints from the output catalog before "
409 "This is usually done when using scarlet models to save disk space.")
410 measurement = ConfigurableField(target=SingleFrameMeasurementTask, doc=
"Source measurement")
411 setPrimaryFlags = ConfigurableField(target=SetPrimaryFlagsTask, doc=
"Set flags for primary tract/patch")
412 doPropagateFlags = Field(
413 dtype=bool, default=
True,
414 doc=
"Whether to match sources to CCD catalogs to propagate flags (to e.g. identify PSF stars)"
416 propagateFlags = ConfigurableField(target=PropagateSourceFlagsTask, doc=
"Propagate source flags to coadd")
417 doMatchSources = Field(dtype=bool, default=
True, doc=
"Match sources to reference catalog?")
418 match = ConfigurableField(target=DirectMatchTask, doc=
"Matching to reference catalog")
419 doWriteMatchesDenormalized = Field(
422 doc=(
"Write reference matches in denormalized format? "
423 "This format uses more disk space, but is more convenient to read."),
425 coaddName = Field(dtype=str, default=
"deep", doc=
"Name of coadd")
426 psfCache = Field(dtype=int, default=100, doc=
"Size of psfCache")
427 checkUnitsParseStrict = Field(
428 doc=
"Strictness of Astropy unit compatibility check, can be 'raise', 'warn' or 'silent'",
435 doc=
"Apply aperture corrections"
437 applyApCorr = ConfigurableField(
438 target=ApplyApCorrTask,
439 doc=
"Subtask to apply aperture corrections"
441 doRunCatalogCalculation = Field(
444 doc=
'Run catalogCalculation task'
446 catalogCalculation = ConfigurableField(
447 target=CatalogCalculationTask,
448 doc=
"Subtask to run catalogCalculation plugins on catalog"
454 doc=
"Should be set to True if fake sources have been inserted into the input data."
458 def refObjLoader(self):
459 return self.match.refObjLoader
461 def setDefaults(self):
462 super().setDefaults()
463 self.measurement.plugins.names |= [
'base_InputCount',
465 'base_LocalPhotoCalib',
467 self.measurement.plugins[
'base_PixelFlags'].masksFpAnywhere = [
'CLIPPED',
'SENSOR_EDGE',
469 self.measurement.plugins[
'base_PixelFlags'].masksFpCenter = [
'CLIPPED',
'SENSOR_EDGE',
480class MeasureMergedCoaddSourcesTask(PipelineTask):
481 """Deblend sources from main catalog in each coadd seperately and measure."""
482 _DefaultName =
"measureCoaddSources"
483 ConfigClass = MeasureMergedCoaddSourcesConfig
484 getSchemaCatalogs = _makeGetSchemaCatalogs(
"meas")
486 def __init__(self, butler=None, schema=None, peakSchema=None, refObjLoader=None, initInputs=None,
489 @brief Initialize the task.
491 Keyword arguments (
in addition to those forwarded to PipelineTask.__init__):
492 @param[
in] schema: the schema of the merged detection catalog used
as input to this one
493 @param[
in] peakSchema: the schema of the PeakRecords
in the Footprints
in the merged detection catalog
494 @param[
in] refObjLoader: an instance of LoadReferenceObjectsTasks that supplies an external reference
495 catalog. May be
None if the loader can be constructed
from the butler argument
or all steps
496 requiring a reference catalog are disabled.
497 @param[
in] butler: a butler used to read the input schemas
from disk
or construct the reference
498 catalog loader,
if schema
or peakSchema
or refObjLoader
is None
500 The task will set its own self.schema attribute to the schema of the output measurement catalog.
501 This will include all fields
from the input schema,
as well
as additional fields
for all the
504 super().__init__(**kwargs)
505 self.deblended = self.config.inputCatalog.startswith("deblended")
506 self.inputCatalog =
"Coadd_" + self.config.inputCatalog
507 if initInputs
is not None:
508 schema = initInputs[
'inputSchema'].schema
510 assert butler
is not None,
"Neither butler nor schema is defined"
511 schema = butler.get(self.config.coaddName + self.inputCatalog +
"_schema", immediate=
True).schema
512 self.schemaMapper = afwTable.SchemaMapper(schema)
513 self.schemaMapper.addMinimalSchema(schema)
514 self.schema = self.schemaMapper.getOutputSchema()
516 self.makeSubtask(
"measurement", schema=self.schema, algMetadata=self.algMetadata)
517 self.makeSubtask(
"setPrimaryFlags", schema=self.schema)
518 if self.config.doMatchSources:
519 self.makeSubtask(
"match", butler=butler, refObjLoader=refObjLoader)
520 if self.config.doPropagateFlags:
521 self.makeSubtask(
"propagateFlags", schema=self.schema)
522 self.schema.checkUnits(parse_strict=self.config.checkUnitsParseStrict)
523 if self.config.doApCorr:
524 self.makeSubtask(
"applyApCorr", schema=self.schema)
525 if self.config.doRunCatalogCalculation:
526 self.makeSubtask(
"catalogCalculation", schema=self.schema)
528 self.outputSchema = afwTable.SourceCatalog(self.schema)
530 def runQuantum(self, butlerQC, inputRefs, outputRefs):
531 inputs = butlerQC.get(inputRefs)
533 refObjLoader = ReferenceObjectLoader([ref.datasetRef.dataId
for ref
in inputRefs.refCat],
534 inputs.pop(
'refCat'),
535 name=self.config.connections.refCat,
536 config=self.config.refObjLoader,
538 self.match.setRefObjLoader(refObjLoader)
542 inputs[
'exposure'].getPsf().setCacheCapacity(self.config.psfCache)
545 exposureIdInfo = ExposureIdInfo.fromDataId(butlerQC.quantum.dataId,
"tract_patch")
546 inputs[
'exposureId'] = exposureIdInfo.expId
547 idFactory = exposureIdInfo.makeSourceIdFactory()
549 table = afwTable.SourceTable.make(self.schema, idFactory)
550 sources = afwTable.SourceCatalog(table)
552 if "scarletCatalog" in inputs:
553 inputCatalog = inputs.pop(
"scarletCatalog")
554 catalogRef = inputRefs.scarletCatalog
556 inputCatalog = inputs.pop(
"inputCatalog")
557 catalogRef = inputRefs.inputCatalog
558 sources.extend(inputCatalog, self.schemaMapper)
561 if self.config.doAddFootprints:
562 modelData = inputs.pop(
'scarletModels')
563 if self.config.doConserveFlux:
564 redistributeImage = inputs[
'exposure'].image
566 redistributeImage =
None
567 modelData.updateCatalogFootprints(
569 band=inputRefs.exposure.dataId[
"band"],
570 psfModel=inputs[
'exposure'].getPsf(),
571 redistributeImage=redistributeImage,
572 removeScarletData=
True,
574 table = sources.getTable()
575 table.setMetadata(self.algMetadata)
576 inputs[
'sources'] = sources
578 skyMap = inputs.pop(
'skyMap')
579 tractNumber = catalogRef.dataId[
'tract']
580 tractInfo = skyMap[tractNumber]
581 patchInfo = tractInfo.getPatchInfo(catalogRef.dataId[
'patch'])
586 wcs=tractInfo.getWcs(),
587 bbox=patchInfo.getOuterBBox()
589 inputs[
'skyInfo'] = skyInfo
591 if self.config.doPropagateFlags:
592 if self.config.propagateFlags.target == PropagateSourceFlagsTask:
594 ccdInputs = inputs[
"exposure"].getInfo().getCoaddInputs().ccds
595 inputs[
"ccdInputs"] = ccdInputs
597 if "sourceTableHandles" in inputs:
598 sourceTableHandles = inputs.pop(
"sourceTableHandles")
599 sourceTableHandleDict = {handle.dataId[
"visit"]: handle
600 for handle
in sourceTableHandles}
601 inputs[
"sourceTableHandleDict"] = sourceTableHandleDict
602 if "finalizedSourceTableHandles" in inputs:
603 finalizedSourceTableHandles = inputs.pop(
"finalizedSourceTableHandles")
604 finalizedSourceTableHandleDict = {handle.dataId[
"visit"]: handle
605 for handle
in finalizedSourceTableHandles}
606 inputs[
"finalizedSourceTableHandleDict"] = finalizedSourceTableHandleDict
610 ccdInputs = inputs[
'exposure'].getInfo().getCoaddInputs().ccds
611 visitKey = ccdInputs.schema.find(
"visit").key
612 ccdKey = ccdInputs.schema.find(
"ccd").key
613 inputVisitIds = set()
615 for ccdRecord
in ccdInputs:
616 visit = ccdRecord.get(visitKey)
617 ccd = ccdRecord.get(ccdKey)
618 inputVisitIds.add((visit, ccd))
619 ccdRecordsWcs[(visit, ccd)] = ccdRecord.getWcs()
621 inputCatalogsToKeep = []
622 inputCatalogWcsUpdate = []
623 for i, dataRef
in enumerate(inputRefs.visitCatalogs):
624 key = (dataRef.dataId[
'visit'], dataRef.dataId[
'detector'])
625 if key
in inputVisitIds:
626 inputCatalogsToKeep.append(inputs[
'visitCatalogs'][i])
627 inputCatalogWcsUpdate.append(ccdRecordsWcs[key])
628 inputs[
'visitCatalogs'] = inputCatalogsToKeep
629 inputs[
'wcsUpdates'] = inputCatalogWcsUpdate
630 inputs[
'ccdInputs'] = ccdInputs
632 outputs = self.run(**inputs)
634 sources = outputs.outputSources
635 butlerQC.put(outputs, outputRefs)
637 def run(self, exposure, sources, skyInfo, exposureId, ccdInputs=None, visitCatalogs=None, wcsUpdates=None,
638 butler=None, sourceTableHandleDict=None, finalizedSourceTableHandleDict=None):
639 """Run measurement algorithms on the input exposure, and optionally populate the
640 resulting catalog with extra information.
644 exposure : `lsst.afw.exposure.Exposure`
645 The input exposure on which measurements are to be performed
647 A catalog built
from the results of merged detections,
or
649 skyInfo : `lsst.pipe.base.Struct`
650 A struct containing information about the position of the input exposure within
651 a `SkyMap`, the `SkyMap`, its `Wcs`,
and its bounding box
652 exposureId : `int`
or `bytes`
653 packed unique number
or bytes unique to the input exposure
655 Catalog containing information on the individual visits which went into making
657 sourceTableHandleDict : `dict` [`int`: `lsst.daf.butler.DeferredDatasetHandle`]
658 Dict
for sourceTable_visit handles (key
is visit)
for propagating flags.
659 These tables are derived
from the ``CalibrateTask`` sources,
and contain
660 astrometry
and photometry flags,
and optionally PSF flags.
661 finalizedSourceTableHandleDict : `dict` [`int`: `lsst.daf.butler.DeferredDatasetHandle`], optional
662 Dict
for finalized_src_table handles (key
is visit)
for propagating flags.
663 These tables are derived
from ``FinalizeCalibrationTask``
and contain
664 PSF flags
from the finalized PSF estimation.
665 visitCatalogs : list of `lsst.afw.table.SourceCatalogs`
666 A list of source catalogs corresponding to measurements made on the individual
667 visits which went into the input exposure. If
None and butler
is `
None` then
668 the task cannot propagate visit flags to the output catalog.
669 Deprecated, to be removed
with PropagateVisitFlagsTask.
671 If visitCatalogs
is not `
None` this should be a list of wcs objects which correspond
672 to the input visits. Used to put all coordinates to common system. If `
None`
and
673 butler
is `
None` then the task cannot propagate visit flags to the output catalog.
674 Deprecated, to be removed
with PropagateVisitFlagsTask.
676 This was a Gen2 butler used to load visit catalogs.
677 No longer used
and should
not be set. Will be removed
in the
682 results : `lsst.pipe.base.Struct`
683 Results of running measurement task. Will contain the catalog
in the
684 sources attribute. Optionally will have results of matching to a
685 reference catalog
in the matchResults attribute,
and denormalized
686 matches
in the denormMatches attribute.
688 if butler
is not None:
689 warnings.warn(
"The 'butler' parameter is no longer used and can be safely removed.",
690 category=FutureWarning, stacklevel=2)
693 self.measurement.run(sources, exposure, exposureId=exposureId)
695 if self.config.doApCorr:
696 self.applyApCorr.run(
698 apCorrMap=exposure.getInfo().getApCorrMap()
705 if not sources.isContiguous():
706 sources = sources.copy(deep=
True)
708 if self.config.doRunCatalogCalculation:
709 self.catalogCalculation.run(sources)
711 self.setPrimaryFlags.run(sources, skyMap=skyInfo.skyMap, tractInfo=skyInfo.tractInfo,
712 patchInfo=skyInfo.patchInfo)
713 if self.config.doPropagateFlags:
714 if self.config.propagateFlags.target == PropagateSourceFlagsTask:
716 self.propagateFlags.run(
719 sourceTableHandleDict,
720 finalizedSourceTableHandleDict
724 self.propagateFlags.run(
735 if self.config.doMatchSources:
736 matchResult = self.match.run(sources, exposure.getInfo().getFilter().bandLabel)
737 matches = afwTable.packMatches(matchResult.matches)
738 matches.table.setMetadata(matchResult.matchMeta)
739 results.matchResult = matches
740 if self.config.doWriteMatchesDenormalized:
741 if matchResult.matches:
742 denormMatches = denormalizeMatches(matchResult.matches, matchResult.matchMeta)
744 self.log.warning(
"No matches, so generating dummy denormalized matches file")
745 denormMatches = afwTable.BaseCatalog(afwTable.Schema())
747 denormMatches.getMetadata().add(
"COMMENT",
748 "This catalog is empty because no matches were found.")
749 results.denormMatches = denormMatches
750 results.denormMatches = denormMatches
752 results.outputSources = sources