Coverage for tests/test_calibrateImage.py: 16%
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22import unittest
23import tempfile
25import astropy.units as u
26from astropy.coordinates import SkyCoord
27import numpy as np
29import lsst.afw.image as afwImage
30import lsst.afw.table as afwTable
31import lsst.daf.base
32import lsst.daf.butler.tests as butlerTests
33import lsst.geom
34import lsst.meas.algorithms
35from lsst.meas.algorithms import testUtils
36import lsst.meas.extensions.psfex
37import lsst.meas.base.tests
38import lsst.pipe.base.testUtils
39from lsst.pipe.tasks.calibrateImage import CalibrateImageTask
40import lsst.utils.tests
43class CalibrateImageTaskTests(lsst.utils.tests.TestCase):
45 def setUp(self):
46 # Different x/y dimensions so they're easy to distinguish in a plot,
47 # and non-zero minimum, to help catch xy0 errors.
48 bbox = lsst.geom.Box2I(lsst.geom.Point2I(5, 4), lsst.geom.Point2I(205, 184))
49 self.sky_center = lsst.geom.SpherePoint(245.0, -45.0, lsst.geom.degrees)
50 self.photo_calib = 12.3
51 dataset = lsst.meas.base.tests.TestDataset(bbox, crval=self.sky_center, calibration=self.photo_calib)
52 # sqrt of area of a normalized 2d gaussian
53 psf_scale = np.sqrt(4*np.pi*(dataset.psfShape.getDeterminantRadius())**2)
54 noise = 10.0 # stddev of noise per pixel
55 # Sources ordered from faintest to brightest.
56 self.fluxes = np.array((6*noise*psf_scale,
57 12*noise*psf_scale,
58 45*noise*psf_scale,
59 150*noise*psf_scale,
60 400*noise*psf_scale,
61 1000*noise*psf_scale))
62 self.centroids = np.array(((162, 22),
63 (40, 70),
64 (100, 160),
65 (50, 120),
66 (92, 35),
67 (175, 154)), dtype=np.float32)
68 for flux, centroid in zip(self.fluxes, self.centroids):
69 dataset.addSource(instFlux=flux, centroid=lsst.geom.Point2D(centroid[0], centroid[1]))
71 # Bright extended source in the center of the image: should not appear
72 # in any of the output catalogs.
73 center = lsst.geom.Point2D(100, 100)
74 shape = lsst.afw.geom.Quadrupole(8, 9, 3)
75 dataset.addSource(instFlux=500*noise*psf_scale, centroid=center, shape=shape)
77 schema = dataset.makeMinimalSchema()
78 self.truth_exposure, self.truth_cat = dataset.realize(noise=noise, schema=schema)
79 # To make it look like a version=1 (nJy fluxes) refcat
80 self.truth_cat = self.truth_exposure.photoCalib.calibrateCatalog(self.truth_cat)
81 self.ref_loader = testUtils.MockReferenceObjectLoaderFromMemory([self.truth_cat])
82 metadata = lsst.daf.base.PropertyList()
83 metadata.set("REFCAT_FORMAT_VERSION", 1)
84 self.truth_cat.setMetadata(metadata)
86 # TODO: a cosmic ray (need to figure out how to insert a fake-CR)
87 # self.truth_exposure.image.array[10, 10] = 100000
88 # self.truth_exposure.variance.array[10, 10] = 100000/noise
90 # Copy the truth exposure, because CalibrateImage modifies the input.
91 # Post-ISR ccds only contain: initial WCS, VisitInfo, filter
92 self.exposure = afwImage.ExposureF(self.truth_exposure.maskedImage)
93 self.exposure.setWcs(self.truth_exposure.wcs)
94 self.exposure.info.setVisitInfo(self.truth_exposure.visitInfo)
95 # "truth" filter, to match the "truth" refcat.
96 self.exposure.setFilter(lsst.afw.image.FilterLabel(physical='truth', band="truth"))
98 # Test-specific configuration:
99 self.config = CalibrateImageTask.ConfigClass()
100 # We don't have many sources, so have to fit simpler models.
101 self.config.psf_detection.background.approxOrderX = 1
102 self.config.star_detection.background.approxOrderX = 1
103 # Only insert 2 sky sources, for simplicity.
104 self.config.star_sky_sources.nSources = 2
105 # Use PCA psf fitter, as psfex fails if there are only 4 stars.
106 self.config.psf_measure_psf.psfDeterminer = 'pca'
107 # We don't have many test points, so can't match on complicated shapes.
108 self.config.astrometry.matcher.numPointsForShape = 3
109 # ApFlux has more noise than PsfFlux (the latter unrealistically small
110 # in this test data), so we need to do magnitude rejection at higher
111 # sigma, otherwise we can lose otherwise good sources.
112 # TODO DM-39203: Once we are using Compensated Gaussian Fluxes, we
113 # will use those fluxes here, and hopefully can remove this.
114 self.config.astrometry.magnitudeOutlierRejectionNSigma = 9.0
116 # find_stars needs an id generator.
117 self.id_generator = lsst.meas.base.IdGenerator()
119 # Something about this test dataset prefers the older fluxRatio here.
120 self.config.star_catalog_calculation.plugins['base_ClassificationExtendedness'].fluxRatio = 0.925
122 def _check_run(self, calibrate, result):
123 """Test the result of CalibrateImage.run().
125 Parameters
126 ----------
127 calibrate : `lsst.pipe.tasks.calibrateImage.CalibrateImageTask`
128 Configured task that had `run` called on it.
129 result : `lsst.pipe.base.Struct`
130 Result of calling calibrate.run().
131 """
132 # Background should have 4 elements: 3 from compute_psf and one from
133 # re-estimation during source detection.
134 self.assertEqual(len(result.background), 4)
136 # Check that the summary statistics are reasonable.
137 summary = result.output_exposure.info.getSummaryStats()
138 self.assertFloatsAlmostEqual(summary.psfSigma, 2.0, rtol=1e-2)
139 self.assertFloatsAlmostEqual(summary.ra, self.sky_center.getRa().asDegrees(), rtol=1e-7)
140 self.assertFloatsAlmostEqual(summary.dec, self.sky_center.getDec().asDegrees(), rtol=1e-7)
142 # Returned photoCalib should be the applied value, not the ==1 one on the exposure.
143 self.assertFloatsAlmostEqual(result.applied_photo_calib.getCalibrationMean(),
144 self.photo_calib, rtol=2e-3)
145 # Should have flux/magnitudes in the afw and astropy catalogs
146 self.assertIn("slot_PsfFlux_flux", result.stars_footprints.schema)
147 self.assertIn("slot_PsfFlux_mag", result.stars_footprints.schema)
148 self.assertEqual(result.stars["slot_PsfFlux_flux"].unit, u.nJy)
149 self.assertEqual(result.stars["slot_PsfFlux_mag"].unit, u.ABmag)
151 # Should have detected all S/N >= 10 sources plus 2 sky sources, whether 1 or 2 snaps.
152 self.assertEqual(len(result.stars), 7)
153 # Did the psf flags get propagated from the psf_stars catalog?
154 self.assertEqual(result.stars["calib_psf_used"].sum(), 3)
156 # Check that all necessary fields are in the output.
157 lsst.pipe.base.testUtils.assertValidOutput(calibrate, result)
159 def test_run(self):
160 """Test that run() returns reasonable values to be butler put.
161 """
162 calibrate = CalibrateImageTask(config=self.config)
163 calibrate.astrometry.setRefObjLoader(self.ref_loader)
164 calibrate.photometry.match.setRefObjLoader(self.ref_loader)
165 result = calibrate.run(exposures=self.exposure)
167 self._check_run(calibrate, result)
169 def test_run_2_snaps(self):
170 """Test that run() returns reasonable values to be butler put, when
171 passed two exposures to combine as snaps.
172 """
173 calibrate = CalibrateImageTask(config=self.config)
174 calibrate.astrometry.setRefObjLoader(self.ref_loader)
175 calibrate.photometry.match.setRefObjLoader(self.ref_loader)
176 # Halve the flux in each exposure to get the expected visit sum.
177 self.exposure.image /= 2
178 self.exposure.variance /= 2
179 result = calibrate.run(exposures=[self.exposure, self.exposure])
181 self._check_run(calibrate, result)
183 def test_handle_snaps(self):
184 calibrate = CalibrateImageTask(config=self.config)
185 self.assertEqual(calibrate._handle_snaps(self.exposure), self.exposure)
186 self.assertEqual(calibrate._handle_snaps((self.exposure, )), self.exposure)
187 self.assertEqual(calibrate._handle_snaps(self.exposure), self.exposure)
188 with self.assertRaisesRegex(RuntimeError, "Can only process 1 or 2 snaps, not 0."):
189 calibrate._handle_snaps([])
190 with self.assertRaisesRegex(RuntimeError, "Can only process 1 or 2 snaps, not 3."):
191 calibrate._handle_snaps(3*[self.exposure])
193 def test_compute_psf(self):
194 """Test that our brightest sources are found by _compute_psf(),
195 that a PSF is assigned to the expopsure.
196 """
197 calibrate = CalibrateImageTask(config=self.config)
198 psf_stars, background, candidates = calibrate._compute_psf(self.exposure)
200 # Background should have 3 elements: initial subtraction, and two from
201 # re-estimation during the two detection passes.
202 self.assertEqual(len(background), 3)
204 # Only the point-sources with S/N > 50 should be in this output.
205 self.assertEqual(psf_stars["calib_psf_used"].sum(), 3)
206 # Sort in order of brightness, to easily compare with expected positions.
207 psf_stars.sort(psf_stars.getPsfFluxSlot().getMeasKey())
208 for record, flux, center in zip(psf_stars[::-1], self.fluxes, self.centroids[self.fluxes > 50]):
209 self.assertFloatsAlmostEqual(record.getX(), center[0], rtol=0.01)
210 self.assertFloatsAlmostEqual(record.getY(), center[1], rtol=0.01)
211 # PsfFlux should match the values inserted.
212 self.assertFloatsAlmostEqual(record["slot_PsfFlux_instFlux"], flux, rtol=0.01)
214 # TODO: While debugging DM-32701, we're using PCA instead of psfex.
215 # Check that we got a useable PSF.
216 # self.assertIsInstance(self.exposure.psf, lsst.meas.extensions.psfex.PsfexPsf)
217 self.assertIsInstance(self.exposure.psf, lsst.meas.algorithms.PcaPsf)
218 # TestDataset sources have PSF radius=2 pixels.
219 radius = self.exposure.psf.computeShape(self.exposure.psf.getAveragePosition()).getDeterminantRadius()
220 self.assertFloatsAlmostEqual(radius, 2.0, rtol=1e-2)
222 # To look at images for debugging (`setup display_ds9` and run ds9):
223 # import lsst.afw.display
224 # display = lsst.afw.display.getDisplay()
225 # display.mtv(self.exposure)
227 def test_measure_aperture_correction(self):
228 """Test that _measure_aperture_correction() assigns an ApCorrMap to the
229 exposure.
230 """
231 calibrate = CalibrateImageTask(config=self.config)
232 psf_stars, background, candidates = calibrate._compute_psf(self.exposure)
234 # First check that the exposure doesn't have an ApCorrMap.
235 self.assertIsNone(self.exposure.apCorrMap)
236 calibrate._measure_aperture_correction(self.exposure, psf_stars)
237 self.assertIsInstance(self.exposure.apCorrMap, afwImage.ApCorrMap)
239 def test_find_stars(self):
240 """Test that _find_stars() correctly identifies the S/N>10 stars
241 in the image and returns them in the output catalog.
242 """
243 calibrate = CalibrateImageTask(config=self.config)
244 psf_stars, background, candidates = calibrate._compute_psf(self.exposure)
245 calibrate._measure_aperture_correction(self.exposure, psf_stars)
247 stars = calibrate._find_stars(self.exposure, background, self.id_generator)
249 # Background should have 4 elements: 3 from compute_psf and one from
250 # re-estimation during source detection.
251 self.assertEqual(len(background), 4)
253 # Only 5 psf-like sources with S/N>10 should be in the output catalog,
254 # plus two sky sources.
255 self.assertEqual(len(stars), 7)
256 self.assertTrue(stars.isContiguous())
257 # Sort in order of brightness, to easily compare with expected positions.
258 stars.sort(stars.getPsfFluxSlot().getMeasKey())
259 for record, flux, center in zip(stars[::-1], self.fluxes, self.centroids[self.fluxes > 50]):
260 self.assertFloatsAlmostEqual(record.getX(), center[0], rtol=0.01)
261 self.assertFloatsAlmostEqual(record.getY(), center[1], rtol=0.01)
262 self.assertFloatsAlmostEqual(record["slot_PsfFlux_instFlux"], flux, rtol=0.01)
264 def test_astrometry(self):
265 """Test that the fitted WCS gives good catalog coordinates.
266 """
267 calibrate = CalibrateImageTask(config=self.config)
268 calibrate.astrometry.setRefObjLoader(self.ref_loader)
269 psf_stars, background, candidates = calibrate._compute_psf(self.exposure)
270 calibrate._measure_aperture_correction(self.exposure, psf_stars)
271 stars = calibrate._find_stars(self.exposure, background, self.id_generator)
273 calibrate._fit_astrometry(self.exposure, stars)
275 # Check that we got reliable matches with the truth coordinates.
276 sky = stars["sky_source"]
277 fitted = SkyCoord(stars[~sky]['coord_ra'], stars[~sky]['coord_dec'], unit="radian")
278 truth = SkyCoord(self.truth_cat['coord_ra'], self.truth_cat['coord_dec'], unit="radian")
279 idx, d2d, _ = fitted.match_to_catalog_sky(truth)
280 np.testing.assert_array_less(d2d.to_value(u.milliarcsecond), 35.0)
282 def test_photometry(self):
283 """Test that the fitted photoCalib matches the one we generated,
284 and that the exposure is calibrated.
285 """
286 calibrate = CalibrateImageTask(config=self.config)
287 calibrate.astrometry.setRefObjLoader(self.ref_loader)
288 calibrate.photometry.match.setRefObjLoader(self.ref_loader)
289 psf_stars, background, candidates = calibrate._compute_psf(self.exposure)
290 calibrate._measure_aperture_correction(self.exposure, psf_stars)
291 stars = calibrate._find_stars(self.exposure, background, self.id_generator)
292 calibrate._fit_astrometry(self.exposure, stars)
294 stars, matches, meta, photoCalib = calibrate._fit_photometry(self.exposure, stars)
296 # NOTE: With this test data, PhotoCalTask returns calibrationErr==0,
297 # so we can't check that the photoCal error has been set.
298 self.assertFloatsAlmostEqual(photoCalib.getCalibrationMean(), self.photo_calib, rtol=2e-3)
299 # The exposure should be calibrated by the applied photoCalib.
300 self.assertFloatsAlmostEqual(self.exposure.image.array/self.truth_exposure.image.array,
301 self.photo_calib, rtol=2e-3)
302 # PhotoCalib on the exposure must be identically 1.
303 self.assertEqual(self.exposure.photoCalib.getCalibrationMean(), 1.0)
305 # Check that we got reliable magnitudes and fluxes vs. truth, ignoring
306 # sky sources.
307 sky = stars["sky_source"]
308 fitted = SkyCoord(stars[~sky]['coord_ra'], stars[~sky]['coord_dec'], unit="radian")
309 truth = SkyCoord(self.truth_cat['coord_ra'], self.truth_cat['coord_dec'], unit="radian")
310 idx, _, _ = fitted.match_to_catalog_sky(truth)
311 # Because the input variance image does not include contributions from
312 # the sources, we can't use fluxErr as a bound on the measurement
313 # quality here.
314 self.assertFloatsAlmostEqual(stars[~sky]['slot_PsfFlux_flux'],
315 self.truth_cat['truth_flux'][idx],
316 rtol=0.1)
317 self.assertFloatsAlmostEqual(stars[~sky]['slot_PsfFlux_mag'],
318 self.truth_cat['truth_mag'][idx],
319 rtol=0.01)
321 def test_match_psf_stars(self):
322 """Test that _match_psf_stars() flags the correct stars as psf stars
323 and candidates.
324 """
325 calibrate = CalibrateImageTask(config=self.config)
326 psf_stars, background, candidates = calibrate._compute_psf(self.exposure)
327 calibrate._measure_aperture_correction(self.exposure, psf_stars)
328 stars = calibrate._find_stars(self.exposure, background, self.id_generator)
330 # There should be no psf-related flags set at first.
331 self.assertEqual(stars["calib_psf_candidate"].sum(), 0)
332 self.assertEqual(stars["calib_psf_used"].sum(), 0)
333 self.assertEqual(stars["calib_psf_reserved"].sum(), 0)
335 # Reorder stars to be out of order with psf_stars (putting the sky
336 # sources in front); this tests that I get the indexing right.
337 stars.sort(stars.getCentroidSlot().getMeasKey().getX())
338 stars = stars.copy(deep=True)
339 # Re-number the ids: the matcher requires sorted ids: this is always
340 # true in the code itself, but we've permuted them by sorting on
341 # flux. We don't care what the actual ids themselves are here.
342 stars["id"] = np.arange(len(stars))
344 calibrate._match_psf_stars(psf_stars, stars)
346 # Check that the three brightest stars have the psf flags transfered
347 # from the psf_stars catalog by sorting in order of brightness.
348 stars.sort(stars.getPsfFluxSlot().getMeasKey())
349 # sort() above leaves the catalog non-contiguous.
350 stars = stars.copy(deep=True)
351 np.testing.assert_array_equal(stars["calib_psf_candidate"],
352 [False, False, False, False, True, True, True])
353 np.testing.assert_array_equal(stars["calib_psf_used"], [False, False, False, False, True, True, True])
354 # Too few sources to reserve any in these tests.
355 self.assertEqual(stars["calib_psf_reserved"].sum(), 0)
358class CalibrateImageTaskRunQuantumTests(lsst.utils.tests.TestCase):
359 """Tests of ``CalibrateImageTask.runQuantum``, which need a test butler,
360 but do not need real images.
361 """
362 def setUp(self):
363 instrument = "testCam"
364 exposure0 = 101
365 exposure1 = 101
366 visit = 100101
367 detector = 42
369 # Create a and populate a test butler for runQuantum tests.
370 self.repo_path = tempfile.TemporaryDirectory(ignore_cleanup_errors=True)
371 self.repo = butlerTests.makeTestRepo(self.repo_path.name)
373 # A complete instrument record is necessary for the id generator.
374 instrumentRecord = self.repo.dimensions["instrument"].RecordClass(
375 name=instrument, visit_max=1e6, exposure_max=1e6, detector_max=128,
376 class_name="lsst.obs.base.instrument_tests.DummyCam",
377 )
378 self.repo.registry.syncDimensionData("instrument", instrumentRecord)
380 # dataIds for fake data
381 butlerTests.addDataIdValue(self.repo, "exposure", exposure0)
382 butlerTests.addDataIdValue(self.repo, "exposure", exposure1)
383 butlerTests.addDataIdValue(self.repo, "visit", visit)
384 butlerTests.addDataIdValue(self.repo, "detector", detector)
386 # inputs
387 butlerTests.addDatasetType(self.repo, "postISRCCD", {"instrument", "exposure", "detector"},
388 "ExposureF")
389 butlerTests.addDatasetType(self.repo, "gaia_dr3_20230707", {"htm7"}, "SimpleCatalog")
390 butlerTests.addDatasetType(self.repo, "ps1_pv3_3pi_20170110", {"htm7"}, "SimpleCatalog")
392 # outputs
393 butlerTests.addDatasetType(self.repo, "initial_pvi", {"instrument", "visit", "detector"},
394 "ExposureF")
395 butlerTests.addDatasetType(self.repo, "initial_stars_footprints_detector",
396 {"instrument", "visit", "detector"},
397 "SourceCatalog")
398 butlerTests.addDatasetType(self.repo, "initial_stars_detector",
399 {"instrument", "visit", "detector"},
400 "ArrowAstropy")
401 butlerTests.addDatasetType(self.repo, "initial_photoCalib_detector",
402 {"instrument", "visit", "detector"},
403 "PhotoCalib")
404 # optional outputs
405 butlerTests.addDatasetType(self.repo, "initial_pvi_background", {"instrument", "visit", "detector"},
406 "Background")
407 butlerTests.addDatasetType(self.repo, "initial_psf_stars_footprints_detector",
408 {"instrument", "visit", "detector"},
409 "SourceCatalog")
410 butlerTests.addDatasetType(self.repo, "initial_psf_stars_detector",
411 {"instrument", "visit", "detector"},
412 "ArrowAstropy")
413 butlerTests.addDatasetType(self.repo,
414 "initial_astrometry_match_detector",
415 {"instrument", "visit", "detector"},
416 "Catalog")
417 butlerTests.addDatasetType(self.repo,
418 "initial_photometry_match_detector",
419 {"instrument", "visit", "detector"},
420 "Catalog")
422 # dataIds
423 self.exposure0_id = self.repo.registry.expandDataId(
424 {"instrument": instrument, "exposure": exposure0, "detector": detector})
425 self.exposure1_id = self.repo.registry.expandDataId(
426 {"instrument": instrument, "exposure": exposure1, "detector": detector})
427 self.visit_id = self.repo.registry.expandDataId(
428 {"instrument": instrument, "visit": visit, "detector": detector})
429 self.htm_id = self.repo.registry.expandDataId({"htm7": 42})
431 # put empty data
432 self.butler = butlerTests.makeTestCollection(self.repo)
433 self.butler.put(afwImage.ExposureF(), "postISRCCD", self.exposure0_id)
434 self.butler.put(afwTable.SimpleCatalog(), "gaia_dr3_20230707", self.htm_id)
435 self.butler.put(afwTable.SimpleCatalog(), "ps1_pv3_3pi_20170110", self.htm_id)
437 def tearDown(self):
438 self.repo_path.cleanup()
440 def test_runQuantum(self):
441 task = CalibrateImageTask()
442 lsst.pipe.base.testUtils.assertValidInitOutput(task)
444 quantum = lsst.pipe.base.testUtils.makeQuantum(
445 task, self.butler, self.visit_id,
446 {"exposures": [self.exposure0_id],
447 "astrometry_ref_cat": [self.htm_id],
448 "photometry_ref_cat": [self.htm_id],
449 # outputs
450 "output_exposure": self.visit_id,
451 "stars": self.visit_id,
452 "stars_footprints": self.visit_id,
453 "background": self.visit_id,
454 "psf_stars": self.visit_id,
455 "psf_stars_footprints": self.visit_id,
456 "applied_photo_calib": self.visit_id,
457 "initial_pvi_background": self.visit_id,
458 "astrometry_matches": self.visit_id,
459 "photometry_matches": self.visit_id,
460 })
461 mock_run = lsst.pipe.base.testUtils.runTestQuantum(task, self.butler, quantum)
463 # Ensure the reference loaders have been configured.
464 self.assertEqual(task.astrometry.refObjLoader.name, "gaia_dr3_20230707")
465 self.assertEqual(task.photometry.match.refObjLoader.name, "ps1_pv3_3pi_20170110")
466 # Check that the proper kwargs are passed to run().
467 self.assertEqual(mock_run.call_args.kwargs.keys(), {"exposures", "id_generator"})
469 def test_runQuantum_2_snaps(self):
470 task = CalibrateImageTask()
471 lsst.pipe.base.testUtils.assertValidInitOutput(task)
473 quantum = lsst.pipe.base.testUtils.makeQuantum(
474 task, self.butler, self.visit_id,
475 {"exposures": [self.exposure0_id, self.exposure1_id],
476 "astrometry_ref_cat": [self.htm_id],
477 "photometry_ref_cat": [self.htm_id],
478 # outputs
479 "output_exposure": self.visit_id,
480 "stars": self.visit_id,
481 "stars_footprints": self.visit_id,
482 "background": self.visit_id,
483 "psf_stars": self.visit_id,
484 "psf_stars_footprints": self.visit_id,
485 "applied_photo_calib": self.visit_id,
486 "initial_pvi_background": self.visit_id,
487 "astrometry_matches": self.visit_id,
488 "photometry_matches": self.visit_id,
489 })
490 mock_run = lsst.pipe.base.testUtils.runTestQuantum(task, self.butler, quantum)
492 # Ensure the reference loaders have been configured.
493 self.assertEqual(task.astrometry.refObjLoader.name, "gaia_dr3_20230707")
494 self.assertEqual(task.photometry.match.refObjLoader.name, "ps1_pv3_3pi_20170110")
495 # Check that the proper kwargs are passed to run().
496 self.assertEqual(mock_run.call_args.kwargs.keys(), {"exposures", "id_generator"})
498 def test_runQuantum_no_optional_outputs(self):
499 config = CalibrateImageTask.ConfigClass()
500 config.optional_outputs = None
501 task = CalibrateImageTask(config=config)
502 lsst.pipe.base.testUtils.assertValidInitOutput(task)
504 quantum = lsst.pipe.base.testUtils.makeQuantum(
505 task, self.butler, self.visit_id,
506 {"exposures": [self.exposure0_id],
507 "astrometry_ref_cat": [self.htm_id],
508 "photometry_ref_cat": [self.htm_id],
509 # outputs
510 "output_exposure": self.visit_id,
511 "stars": self.visit_id,
512 "stars_footprints": self.visit_id,
513 "applied_photo_calib": self.visit_id,
514 "background": self.visit_id,
515 })
516 mock_run = lsst.pipe.base.testUtils.runTestQuantum(task, self.butler, quantum)
518 # Ensure the reference loaders have been configured.
519 self.assertEqual(task.astrometry.refObjLoader.name, "gaia_dr3_20230707")
520 self.assertEqual(task.photometry.match.refObjLoader.name, "ps1_pv3_3pi_20170110")
521 # Check that the proper kwargs are passed to run().
522 self.assertEqual(mock_run.call_args.kwargs.keys(), {"exposures", "id_generator"})
524 def test_lintConnections(self):
525 """Check that the connections are self-consistent.
526 """
527 Connections = CalibrateImageTask.ConfigClass.ConnectionsClass
528 lsst.pipe.base.testUtils.lintConnections(Connections)
531def setup_module(module):
532 lsst.utils.tests.init()
535class MemoryTestCase(lsst.utils.tests.MemoryTestCase):
536 pass
539if __name__ == "__main__": 539 ↛ 540line 539 didn't jump to line 540, because the condition on line 539 was never true
540 lsst.utils.tests.init()
541 unittest.main()