Coverage for python/lsst/ap/verify/testPipeline.py: 44%
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1#
2# This file is part of ap_verify.
3#
4# Developed for the LSST Data Management System.
5# This product includes software developed by the LSST Project
6# (http://www.lsst.org).
7# See the COPYRIGHT file at the top-level directory of this distribution
8# for details of code ownership.
9#
10# This program is free software: you can redistribute it and/or modify
11# it under the terms of the GNU General Public License as published by
12# the Free Software Foundation, either version 3 of the License, or
13# (at your option) any later version.
14#
15# This program is distributed in the hope that it will be useful,
16# but WITHOUT ANY WARRANTY; without even the implied warranty of
17# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
18# GNU General Public License for more details.
19#
20# You should have received a copy of the GNU General Public License
21# along with this program. If not, see <http://www.gnu.org/licenses/>.
22#
25# These classes exist only to be included in a mock pipeline, and don't need
26# to be public for that.
27__all__ = []
30import numpy as np
31import pandas
33import lsst.geom as geom
34import lsst.afw.image as afwImage
35import lsst.afw.math as afwMath
36import lsst.afw.table as afwTable
37from lsst.pipe.base import PipelineTask, Struct
38from lsst.ip.isr import IsrTaskConfig
39from lsst.ip.diffim import GetTemplateConfig, AlardLuptonSubtractConfig, DetectAndMeasureConfig
40from lsst.pipe.tasks.characterizeImage import CharacterizeImageConfig
41from lsst.pipe.tasks.calibrate import CalibrateConfig
42from lsst.ap.association import TransformDiaSourceCatalogConfig, DiaPipelineConfig
45class MockIsrTask(PipelineTask):
46 """A do-nothing substitute for IsrTask.
47 """
48 ConfigClass = IsrTaskConfig
49 _DefaultName = "notIsr"
51 def run(self, ccdExposure, *, camera=None, bias=None, linearizer=None,
52 crosstalk=None, crosstalkSources=None,
53 dark=None, flat=None, ptc=None, bfKernel=None, bfGains=None, defects=None,
54 fringes=Struct(fringes=None), opticsTransmission=None, filterTransmission=None,
55 sensorTransmission=None, atmosphereTransmission=None,
56 detectorNum=None, strayLightData=None, illumMaskedImage=None,
57 deferredCharge=None,
58 ):
59 """Accept ISR inputs, and produce ISR outputs with no processing.
61 Parameters
62 ----------
63 ccdExposure : `lsst.afw.image.Exposure`
64 The raw exposure that is to be run through ISR. The
65 exposure is modified by this method.
66 camera : `lsst.afw.cameraGeom.Camera`, optional
67 The camera geometry for this exposure. Required if
68 one or more of ``ccdExposure``, ``bias``, ``dark``, or
69 ``flat`` does not have an associated detector.
70 bias : `lsst.afw.image.Exposure`, optional
71 Bias calibration frame.
72 linearizer : `lsst.ip.isr.linearize.LinearizeBase`, optional
73 Functor for linearization.
74 crosstalk : `lsst.ip.isr.crosstalk.CrosstalkCalib`, optional
75 Calibration for crosstalk.
76 crosstalkSources : `list`, optional
77 List of possible crosstalk sources.
78 dark : `lsst.afw.image.Exposure`, optional
79 Dark calibration frame.
80 flat : `lsst.afw.image.Exposure`, optional
81 Flat calibration frame.
82 ptc : `lsst.ip.isr.PhotonTransferCurveDataset`, optional
83 Photon transfer curve dataset, with, e.g., gains
84 and read noise.
85 bfKernel : `numpy.ndarray`, optional
86 Brighter-fatter kernel.
87 bfGains : `dict` of `float`, optional
88 Gains used to override the detector's nominal gains for the
89 brighter-fatter correction. A dict keyed by amplifier name for
90 the detector in question.
91 defects : `lsst.ip.isr.Defects`, optional
92 List of defects.
93 fringes : `lsst.pipe.base.Struct`, optional
94 Struct containing the fringe correction data, with
95 elements:
96 - ``fringes``: fringe calibration frame (`afw.image.Exposure`)
97 - ``seed``: random seed derived from the ccdExposureId for random
98 number generator (`uint32`)
99 opticsTransmission: `lsst.afw.image.TransmissionCurve`, optional
100 A ``TransmissionCurve`` that represents the throughput of the
101 optics, to be evaluated in focal-plane coordinates.
102 filterTransmission : `lsst.afw.image.TransmissionCurve`
103 A ``TransmissionCurve`` that represents the throughput of the
104 filter itself, to be evaluated in focal-plane coordinates.
105 sensorTransmission : `lsst.afw.image.TransmissionCurve`
106 A ``TransmissionCurve`` that represents the throughput of the
107 sensor itself, to be evaluated in post-assembly trimmed detector
108 coordinates.
109 atmosphereTransmission : `lsst.afw.image.TransmissionCurve`
110 A ``TransmissionCurve`` that represents the throughput of the
111 atmosphere, assumed to be spatially constant.
112 detectorNum : `int`, optional
113 The integer number for the detector to process.
114 isGen3 : bool, optional
115 Flag this call to run() as using the Gen3 butler environment.
116 strayLightData : `object`, optional
117 Opaque object containing calibration information for stray-light
118 correction. If `None`, no correction will be performed.
119 illumMaskedImage : `lsst.afw.image.MaskedImage`, optional
120 Illumination correction image.
122 Returns
123 -------
124 result : `lsst.pipe.base.Struct`
125 Result struct with components:
127 ``exposure``
128 The fully ISR corrected exposure (`afw.image.Exposure`).
129 ``outputExposure``
130 An alias for ``exposure`` (`afw.image.Exposure`).
131 ``ossThumb``
132 Thumbnail image of the exposure after overscan subtraction
133 (`numpy.ndarray`).
134 ``flattenedThumb``
135 Thumbnail image of the exposure after flat-field correction
136 (`numpy.ndarray`).
137 - ``outputStatistics`` : mapping [`str`]
138 Values of the additional statistics calculated.
139 """
140 return Struct(exposure=afwImage.ExposureF(),
141 outputExposure=afwImage.ExposureF(),
142 ossThumb=np.empty((1, 1)),
143 flattenedThumb=np.empty((1, 1)),
144 preInterpExposure=afwImage.ExposureF(),
145 outputOssThumbnail=np.empty((1, 1)),
146 outputFlattenedThumbnail=np.empty((1, 1)),
147 outputStatistics={},
148 )
151class MockCharacterizeImageTask(PipelineTask):
152 """A do-nothing substitute for CharacterizeImageTask.
153 """
154 ConfigClass = CharacterizeImageConfig
155 _DefaultName = "notCharacterizeImage"
157 def __init__(self, refObjLoader=None, schema=None, **kwargs):
158 super().__init__(**kwargs)
159 self.outputSchema = afwTable.SourceCatalog()
161 def runQuantum(self, butlerQC, inputRefs, outputRefs):
162 inputs = butlerQC.get(inputRefs)
163 if 'idGenerator' not in inputs.keys():
164 inputs['idGenerator'] = self.config.idGenerator.apply(butlerQC.quantum.dataId)
165 outputs = self.run(**inputs)
166 butlerQC.put(outputs, outputRefs)
168 def run(self, exposure, background=None, idGenerator=None):
169 """Produce characterization outputs with no processing.
171 Parameters
172 ----------
173 exposure : `lsst.afw.image.Exposure`
174 Exposure to characterize.
175 background : `lsst.afw.math.BackgroundList`, optional
176 Initial model of background already subtracted from exposure.
177 idGenerator : `lsst.meas.base.IdGenerator`, optional
178 Object that generates source IDs and provides random number
179 generator seeds.
181 Returns
182 -------
183 result : `lsst.pipe.base.Struct`
184 Struct containing these fields:
186 ``characterized``
187 Characterized exposure (`lsst.afw.image.Exposure`).
188 ``sourceCat``
189 Detected sources (`lsst.afw.table.SourceCatalog`).
190 ``backgroundModel``
191 Model of background subtracted from exposure (`lsst.afw.math.BackgroundList`)
192 ``psfCellSet``
193 Spatial cells of PSF candidates (`lsst.afw.math.SpatialCellSet`)
194 """
195 # Can't persist empty BackgroundList; DM-33714
196 bg = afwMath.BackgroundMI(geom.Box2I(geom.Point2I(0, 0), geom.Point2I(16, 16)),
197 afwImage.MaskedImageF(16, 16))
198 return Struct(characterized=exposure,
199 sourceCat=afwTable.SourceCatalog(),
200 backgroundModel=afwMath.BackgroundList(bg),
201 psfCellSet=afwMath.SpatialCellSet(exposure.getBBox(), 10),
202 )
205class MockCalibrateTask(PipelineTask):
206 """A do-nothing substitute for CalibrateTask.
207 """
208 ConfigClass = CalibrateConfig
209 _DefaultName = "notCalibrate"
211 def __init__(self, astromRefObjLoader=None,
212 photoRefObjLoader=None, icSourceSchema=None,
213 initInputs=None, **kwargs):
214 super().__init__(**kwargs)
215 self.outputSchema = afwTable.SourceCatalog()
217 def runQuantum(self, butlerQC, inputRefs, outputRefs):
218 inputs = butlerQC.get(inputRefs)
219 inputs['idGenerator'] = self.config.idGenerator.apply(butlerQC.quantum.dataId)
221 if self.config.doAstrometry:
222 inputs.pop('astromRefCat')
223 if self.config.doPhotoCal:
224 inputs.pop('photoRefCat')
226 outputs = self.run(**inputs)
228 if self.config.doWriteMatches and self.config.doAstrometry:
229 normalizedMatches = afwTable.packMatches(outputs.astromMatches)
230 if self.config.doWriteMatchesDenormalized:
231 # Just need an empty BaseCatalog with a valid schema.
232 outputs.matchesDenormalized = afwTable.BaseCatalog(outputs.outputCat.schema)
233 outputs.matches = normalizedMatches
234 butlerQC.put(outputs, outputRefs)
236 def run(self, exposure, background=None,
237 icSourceCat=None, idGenerator=None):
238 """Produce calibration outputs with no processing.
240 Parameters
241 ----------
242 exposure : `lsst.afw.image.Exposure`
243 Exposure to calibrate.
244 background : `lsst.afw.math.BackgroundList`, optional
245 Background model already subtracted from exposure.
246 icSourceCat : `lsst.afw.table.SourceCatalog`, optional
247 A SourceCatalog from CharacterizeImageTask from which we can copy some fields.
248 idGenerator : `lsst.meas.base.IdGenerator`, optional
249 Object that generates source IDs and provides random number
250 generator seeds.
252 Returns
253 -------
254 result : `lsst.pipe.base.Struct`
255 Struct containing these fields:
257 ``outputExposure``
258 Calibrated science exposure with refined WCS and PhotoCalib
259 (`lsst.afw.image.Exposure`).
260 ``outputBackground``
261 Model of background subtracted from exposure
262 (`lsst.afw.math.BackgroundList`).
263 ``outputCat``
264 Catalog of measured sources (`lsst.afw.table.SourceCatalog`).
265 ``astromMatches``
266 List of source/refObj matches from the astrometry solver
267 (`list` [`lsst.afw.table.ReferenceMatch`]).
268 """
269 # Can't persist empty BackgroundList; DM-33714
270 bg = afwMath.BackgroundMI(geom.Box2I(geom.Point2I(0, 0), geom.Point2I(16, 16)),
271 afwImage.MaskedImageF(16, 16))
272 return Struct(outputExposure=exposure,
273 outputBackground=afwMath.BackgroundList(bg),
274 outputCat=afwTable.SourceCatalog(),
275 astromMatches=[],
276 )
279class MockGetTemplateTask(PipelineTask):
280 """A do-nothing substitute for GetTemplateTask.
281 """
282 ConfigClass = GetTemplateConfig
283 _DefaultName = "notGetTemplate"
285 def runQuantum(self, butlerQC, inputRefs, outputRefs):
286 inputs = butlerQC.get(inputRefs)
287 # Mock GetTemplateTask.getOverlappingExposures
288 results = Struct(coaddExposures=[],
289 dataIds=[],
290 )
291 inputs["coaddExposures"] = results.coaddExposures
292 inputs["dataIds"] = results.dataIds
293 outputs = self.run(**inputs)
294 butlerQC.put(outputs, outputRefs)
296 def run(self, coaddExposures, bbox, wcs, dataIds, **kwargs):
297 """Warp coadds from multiple tracts to form a template for image diff.
299 Where the tracts overlap, the resulting template image is averaged.
300 The PSF on the template is created by combining the CoaddPsf on each
301 template image into a meta-CoaddPsf.
303 Parameters
304 ----------
305 coaddExposures : `list` of `lsst.afw.image.Exposure`
306 Coadds to be mosaicked
307 bbox : `lsst.geom.Box2I`
308 Template Bounding box of the detector geometry onto which to
309 resample the coaddExposures
310 wcs : `lsst.afw.geom.SkyWcs`
311 Template WCS onto which to resample the coaddExposures
312 dataIds : `list` of `lsst.daf.butler.DataCoordinate`
313 Record of the tract and patch of each coaddExposure.
314 **kwargs
315 Any additional keyword parameters.
317 Returns
318 -------
319 result : `lsst.pipe.base.Struct` containing
320 - ``template`` : a template coadd exposure assembled out of patches
321 """
322 return Struct(template=afwImage.ExposureF(),
323 )
326class MockAlardLuptonSubtractTask(PipelineTask):
327 """A do-nothing substitute for AlardLuptonSubtractTask.
328 """
329 ConfigClass = AlardLuptonSubtractConfig
330 _DefaultName = "notAlardLuptonSubtract"
332 def run(self, template, science, sources, finalizedPsfApCorrCatalog=None, visitSummary=None):
333 """PSF match, subtract, and decorrelate two images.
335 Parameters
336 ----------
337 template : `lsst.afw.image.ExposureF`
338 Template exposure, warped to match the science exposure.
339 science : `lsst.afw.image.ExposureF`
340 Science exposure to subtract from the template.
341 sources : `lsst.afw.table.SourceCatalog`
342 Identified sources on the science exposure. This catalog is used to
343 select sources in order to perform the AL PSF matching on stamp
344 images around them.
345 finalizedPsfApCorrCatalog : `lsst.afw.table.ExposureCatalog`, optional
346 Exposure catalog with finalized psf models and aperture correction
347 maps to be applied if config.doApplyFinalizedPsf=True. Catalog
348 uses the detector id for the catalog id, sorted on id for fast
349 lookup. Deprecated in favor of ``visitSummary``, and will be
350 removed after v26.
351 visitSummary : `lsst.afw.table.ExposureCatalog`, optional
352 Exposure catalog with external calibrations to be applied. Catalog
353 uses the detector id for the catalog id, sorted on id for fast
354 lookup. Ignored (for temporary backwards compatibility) if
355 ``finalizedPsfApCorrCatalog`` is provided.
357 Returns
358 -------
359 results : `lsst.pipe.base.Struct`
360 ``difference`` : `lsst.afw.image.ExposureF`
361 Result of subtracting template and science.
362 ``matchedTemplate`` : `lsst.afw.image.ExposureF`
363 Warped and PSF-matched template exposure.
364 ``backgroundModel`` : `lsst.afw.math.Function2D`
365 Background model that was fit while solving for the
366 PSF-matching kernel
367 ``psfMatchingKernel`` : `lsst.afw.math.Kernel`
368 Kernel used to PSF-match the convolved image.
369 """
370 return Struct(difference=afwImage.ExposureF(),
371 matchedTemplate=afwImage.ExposureF(),
372 backgroundModel=afwMath.NullFunction2D(),
373 psfMatchingKernel=afwMath.FixedKernel(),
374 )
377class MockDetectAndMeasureConfig(DetectAndMeasureConfig):
379 def setDefaults(self):
380 super().setDefaults()
381 # Avoid delegating to lsst.obs.base.Instrument specialization for the
382 # data ID packing algorithm to use, since test code often does not use a
383 # real Instrument in its data IDs.
384 self.idGenerator.packer.name = "observation"
387class MockDetectAndMeasureTask(PipelineTask):
388 """A do-nothing substitute for DetectAndMeasureTask.
389 """
390 ConfigClass = MockDetectAndMeasureConfig
391 _DefaultName = "notDetectAndMeasure"
393 def __init__(self, **kwargs):
394 super().__init__(**kwargs)
395 self.outputSchema = afwTable.SourceCatalog()
397 def runQuantum(self, butlerQC, inputRefs, outputRefs):
398 inputs = butlerQC.get(inputRefs)
399 idFactory = afwTable.IdFactory.makeSimple()
401 outputs = self.run(inputs['science'],
402 inputs['matchedTemplate'],
403 inputs['difference'],
404 idFactory=idFactory)
405 butlerQC.put(outputs, outputRefs)
407 def run(self, science, matchedTemplate, difference,
408 idFactory=None):
409 """Detect and measure sources on a difference image.
411 Parameters
412 ----------
413 science : `lsst.afw.image.ExposureF`
414 Science exposure that the template was subtracted from.
415 matchedTemplate : `lsst.afw.image.ExposureF`
416 Warped and PSF-matched template that was used produce the
417 difference image.
418 difference : `lsst.afw.image.ExposureF`
419 Result of subtracting template from the science image.
420 idFactory : `lsst.afw.table.IdFactory`, optional
421 Generator object to assign ids to detected sources in the difference image.
423 Returns
424 -------
425 results : `lsst.pipe.base.Struct`
426 ``subtractedMeasuredExposure`` : `lsst.afw.image.ExposureF`
427 Subtracted exposure with detection mask applied.
428 ``diaSources`` : `lsst.afw.table.SourceCatalog`
429 The catalog of detected sources.
430 """
431 return Struct(subtractedMeasuredExposure=difference,
432 diaSources=afwTable.SourceCatalog(),
433 )
436class MockTransformDiaSourceCatalogTask(PipelineTask):
437 """A do-nothing substitute for TransformDiaSourceCatalogTask.
438 """
439 ConfigClass = TransformDiaSourceCatalogConfig
440 _DefaultName = "notTransformDiaSourceCatalog"
442 def __init__(self, initInputs, **kwargs):
443 super().__init__(**kwargs)
445 def runQuantum(self, butlerQC, inputRefs, outputRefs):
446 inputs = butlerQC.get(inputRefs)
447 idGenerator = self.config.idGenerator.apply(butlerQC.quantum.dataId)
448 inputs["ccdVisitId"] = idGenerator.catalog_id
449 inputs["band"] = butlerQC.quantum.dataId["band"]
451 outputs = self.run(**inputs)
453 butlerQC.put(outputs, outputRefs)
455 def run(self, diaSourceCat, diffIm, band, ccdVisitId, funcs=None):
456 """Produce transformation outputs with no processing.
458 Parameters
459 ----------
460 diaSourceCat : `lsst.afw.table.SourceCatalog`
461 The catalog to transform.
462 diffIm : `lsst.afw.image.Exposure`
463 An image, to provide supplementary information.
464 band : `str`
465 The band in which the sources were observed.
466 ccdVisitId : `int`
467 The exposure ID in which the sources were observed.
468 funcs, optional
469 Unused.
471 Returns
472 -------
473 results : `lsst.pipe.base.Struct`
474 Results struct with components:
476 ``diaSourceTable``
477 Catalog of DiaSources (`pandas.DataFrame`).
478 """
479 return Struct(diaSourceTable=pandas.DataFrame(),
480 )
483class MockDiaPipelineConfig(DiaPipelineConfig):
485 def setDefaults(self):
486 super().setDefaults()
487 # Avoid delegating to lsst.obs.base.Instrument specialization for the
488 # data ID packing algorithm to use, since test code often does not use a
489 # real Instrument in its data IDs.
490 self.idGenerator.packer.name = "observation"
493class MockDiaPipelineTask(PipelineTask):
494 """A do-nothing substitute for DiaPipelineTask.
495 """
496 ConfigClass = MockDiaPipelineConfig
497 _DefaultName = "notDiaPipe"
499 def runQuantum(self, butlerQC, inputRefs, outputRefs):
500 inputs = butlerQC.get(inputRefs)
501 inputs["idGenerator"] = self.config.idGenerator.apply(butlerQC.quantum.dataId)
502 # Need to set ccdExposureIdBits (now deprecated) to None and pass it,
503 # since there are non-optional positional arguments after it.
504 inputs["ccdExposureIdBits"] = None
505 inputs["band"] = butlerQC.quantum.dataId["band"]
506 if not self.config.doSolarSystemAssociation:
507 inputs["solarSystemObjectTable"] = None
509 outputs = self.run(**inputs)
511 butlerQC.put(outputs, outputRefs)
513 def run(self,
514 diaSourceTable,
515 solarSystemObjectTable,
516 diffIm,
517 exposure,
518 template,
519 ccdExposureIdBits,
520 band,
521 idGenerator=None):
522 """Produce DiaSource and DiaObject outputs with no processing.
524 Parameters
525 ----------
526 diaSourceTable : `pandas.DataFrame`
527 Newly detected DiaSources.
528 solarSystemObjectTable : `pandas.DataFrame`
529 Expected solar system objects in the field of view.
530 diffIm : `lsst.afw.image.ExposureF`
531 Difference image exposure in which the sources in ``diaSourceCat``
532 were detected.
533 exposure : `lsst.afw.image.ExposureF`
534 Calibrated exposure differenced with a template to create
535 ``diffIm``.
536 template : `lsst.afw.image.ExposureF`
537 Template exposure used to create diffIm.
538 ccdExposureIdBits : `int`
539 Number of bits used for a unique ``ccdVisitId``. Deprecated in
540 favor of ``idGenerator``, and ignored if that is present. Pass
541 `None` explicitly to avoid a deprecation warning (a default is
542 impossible given that later positional arguments are not
543 defaulted).
544 band : `str`
545 The band in which the new DiaSources were detected.
546 idGenerator : `lsst.meas.base.IdGenerator`, optional
547 Object that generates source IDs and random number generator seeds.
548 Will be required after ``ccdExposureIdBits`` is removed.
550 Returns
551 -------
552 results : `lsst.pipe.base.Struct`
553 Results struct with components:
555 ``apdbMarker``
556 Marker dataset to store in the Butler indicating that this
557 ccdVisit has completed successfully (`lsst.dax.apdb.ApdbConfig`).
558 ``associatedDiaSources``
559 Catalog of newly associated DiaSources (`pandas.DataFrame`).
560 """
561 return Struct(apdbMarker=self.config.apdb.value,
562 associatedDiaSources=pandas.DataFrame(),
563 diaForcedSources=pandas.DataFrame(),
564 diaObjects=pandas.DataFrame(),
565 longTrailedSources=pandas.DataFrame(),
566 )