Coverage for tests/test_diaPipe.py: 99%
396 statements
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1# This file is part of ap_association.
2#
3# Developed for the LSST Data Management System.
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
10# it under the terms of the GNU General Public License as published by
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/>.
22import contextlib
23import tempfile
24import unittest
25from unittest.mock import patch, MagicMock, DEFAULT
26import warnings
28import numpy as np
29import pandas as pd
30import astropy.table as tb
32import lsst.afw.table as afwTable
33import lsst.dax.apdb as daxApdb
34from lsst.meas.base import IdGenerator
35import lsst.pex.config as pexConfig
36import lsst.pipe.base as pipeBase
37import lsst.utils.tests
38from lsst.pipe.base.testUtils import assertValidOutput
40from lsst.ap.association import DiaPipelineTask
41from lsst.pipe.tasks.schemaUtils import convertDataFrameToSdmSchema
42from utils_tests import makeExposure, makeDiaObjects, makeDiaSources, makeDiaForcedSources, \
43 makeSolarSystemSources
46def _makeMockDataFrame():
47 """Create a new mock of a DataFrame.
49 Returns
50 -------
51 mock : `unittest.mock.Mock`
52 A mock guaranteed to accept all operations used by `pandas.DataFrame`.
53 """
54 with warnings.catch_warnings():
55 # spec triggers deprecation warnings on DataFrame, but will
56 # automatically adapt to any removals.
57 warnings.simplefilter("ignore", category=DeprecationWarning)
58 return MagicMock(spec=pd.DataFrame())
61def _makeMockTable():
62 """Create a new mock of a Table.
64 Returns
65 -------
66 mock : `unittest.mock.Mock`
67 A mock guaranteed to accept all operations used by `astropy.table.Table`.
68 """
69 with warnings.catch_warnings():
70 # spec triggers deprecation warnings on DataFrame, but will
71 # automatically adapt to any removals.
72 warnings.simplefilter("ignore", category=DeprecationWarning)
73 return MagicMock(spec=tb.Table())
76class TestDiaPipelineTask(unittest.TestCase):
78 @classmethod
79 def _makeDefaultConfig(cls, config_file, **kwargs):
80 config = DiaPipelineTask.ConfigClass()
81 config.apdb_config_url = config_file
82 config.update(**kwargs)
83 return config
85 def setUp(self):
86 # Create an instance of random generator with fixed seed.
87 rng = np.random.default_rng(1234)
88 self.rng = rng
90 # schemas are persisted in both Gen 2 and Gen 3 butler as prototypical catalogs
91 srcSchema = afwTable.SourceTable.makeMinimalSchema()
92 srcSchema.addField("base_PixelFlags_flag", type="Flag")
93 srcSchema.addField("base_PixelFlags_flag_offimage", type="Flag")
94 self.srcSchema = afwTable.SourceCatalog(srcSchema)
95 self.exposure = makeExposure(False, False)
96 self.diffim = makeExposure(False, False)
97 self.template = makeExposure(False, False)
98 self.diaObjects = makeDiaObjects(20, self.exposure, rng)
99 self.diaSources = makeDiaSources(
100 100, self.diaObjects["diaObjectId"].to_numpy(), self.exposure, rng)
101 self.diaForcedSources = makeDiaForcedSources(
102 200, self.diaObjects["diaObjectId"].to_numpy(), self.exposure, rng)
103 self.ssSources = makeSolarSystemSources(
104 20, self.diaObjects["diaObjectId"].to_numpy(), self.exposure, rng)
106 sqlite_file = tempfile.NamedTemporaryFile()
107 self.addCleanup(sqlite_file.close)
108 self.config_file = tempfile.NamedTemporaryFile()
109 self.addCleanup(self.config_file.close)
110 apdb_config = daxApdb.ApdbSql.init_database(db_url=f"sqlite:///{sqlite_file.name}")
111 apdb_config.save(self.config_file.name)
113 def testRun(self):
114 """Test running while creating and packaging alerts.
115 """
116 self._testRun(doPackageAlerts=True, doSolarSystemAssociation=True, doReloadDiaObjects=False)
118 def testRunWithSolarSystemAssociation(self):
119 """Test running while creating and packaging alerts.
120 """
121 self._testRun(doPackageAlerts=False, doSolarSystemAssociation=True, doReloadDiaObjects=False)
123 def testRunWithAlerts(self):
124 """Test running while creating and packaging alerts.
125 """
126 self._testRun(doPackageAlerts=True, doSolarSystemAssociation=False, doReloadDiaObjects=False)
128 def testRunWithoutAlertsOrSolarSystem(self):
129 """Test running without creating and packaging alerts.
130 """
131 self._testRun(doPackageAlerts=False, doSolarSystemAssociation=False, doReloadDiaObjects=False)
133 def testRunWithReload(self):
134 """Test running with reloading DiaObjects.
135 """
136 self._testRun(doPackageAlerts=False, doSolarSystemAssociation=False, doReloadDiaObjects=True)
138 def testRunWithReloadAndSolarSystem(self):
139 """Test running with solar system association and reloading DiaObjects.
140 """
141 self._testRun(doPackageAlerts=False, doSolarSystemAssociation=True, doReloadDiaObjects=True)
143 def testRunWithReloadAndAlerts(self):
144 """Test running with reloading DiaObjects while creating and packaging alerts.
145 """
146 self._testRun(doPackageAlerts=True, doSolarSystemAssociation=False, doReloadDiaObjects=True)
148 def testRunDisableDeprecatedDoRunForcedMeasurement(self):
149 """Test running with forced sources disabled.
150 """
151 self._testRun(doPackageAlerts=True, doSolarSystemAssociation=False, doReloadDiaObjects=True,
152 doRunForcedMeasurement=False, subtasksToMock=["diaCalculation", ]
153 )
155 def _testRun(self, doPackageAlerts=False, doSolarSystemAssociation=False,
156 doReloadDiaObjects=False, subtasksToMock=None, **kwargs):
157 """Test the normal workflow of each ap_pipe step.
158 """
159 config = self._makeDefaultConfig(
160 config_file=self.config_file.name,
161 doPackageAlerts=doPackageAlerts,
162 doSolarSystemAssociation=doSolarSystemAssociation,
163 doReloadDiaObjects=doReloadDiaObjects,
164 **kwargs
165 )
166 task = DiaPipelineTask(config=config)
167 # Set DataFrame index testing to always return False. Mocks return
168 # true for this check otherwise.
169 task.testDataFrameIndex = lambda x: False
170 diaSrc = _makeMockDataFrame()
171 ssObjects = _makeMockTable()
173 # Each of these subtasks should be called once during diaPipe
174 # execution. We use mocks here to check they are being executed
175 # appropriately.
176 if subtasksToMock is None:
177 subtasksToMock = ["diaCalculation", "diaForcedSource", ]
178 if doPackageAlerts:
179 subtasksToMock.append("alertPackager")
180 else:
181 self.assertFalse(hasattr(task, "alertPackager"))
183 if not doSolarSystemAssociation:
184 self.assertFalse(hasattr(task, "solarSystemAssociator"))
186 def concatMock(_data, **_kwargs):
187 return _makeMockDataFrame()
189 # Mock out the run() methods of these Tasks to ensure they
190 # return data in the correct form.
191 def solarSystemAssociator_run(unAssocDiaSources, solarSystemObjectTable, visitInfo,
192 bbox, wcs):
193 return lsst.pipe.base.Struct(nTotalSsObjects=42,
194 nAssociatedSsObjects=30,
195 ssoAssocDiaSources=_makeMockTable(),
196 unAssocDiaSources=_makeMockTable(),
197 associatedSsSources=_makeMockTable(),
198 unassociatedSsObjects=_makeMockTable())
200 def associator_run(table, diaObjects, schema=None):
201 return lsst.pipe.base.Struct(nUpdatedDiaObjects=2, nUnassociatedDiaObjects=3,
202 matchedDiaSources=_makeMockDataFrame(),
203 unAssocDiaSources=_makeMockDataFrame())
205 def loadObjects_run(region, preloadedDiaObjects):
206 task.metadata['loadRefreshedDiaObjectsStartUtc'] = 1.234
207 task.metadata['loadRefreshedDiaObjectsEndUtc'] = 5.678
208 return self.diaObjects
210 def updateObjectTableMock(diaObjects, diaSources):
211 pass
213 def _selectGoodDiaObjects(diaObjectCat, mergedDiaSourceHistory):
214 return diaObjectCat.copy(deep=True)
216 # apdb isn't a subtask, but still needs to be mocked out for correct
217 # execution in the test environment.
218 with patch.multiple(task, **{task: DEFAULT for task in subtasksToMock + ["apdb"]}), \
219 patch('lsst.ap.association.diaPipe.pd.concat', side_effect=concatMock), \
220 patch('lsst.ap.association.diaPipe.DiaPipelineTask.updateObjectTable',
221 side_effect=updateObjectTableMock), \
222 patch('lsst.ap.association.diaPipe.DiaPipelineTask._selectGoodDiaObjects',
223 side_effect=_selectGoodDiaObjects), \
224 patch('lsst.ap.association.diaPipe.DiaPipelineTask.loadRefreshedDiaObjects',
225 side_effect=loadObjects_run), \
226 patch('lsst.ap.association.association.AssociationTask.run',
227 side_effect=associator_run) as mainRun, \
228 patch('lsst.pipe.tasks.ssoAssociation.SolarSystemAssociationTask.run',
229 side_effect=solarSystemAssociator_run) as ssRun:
231 result = task.run(diaSrc,
232 None,
233 self.diffim,
234 self.exposure,
235 self.template,
236 preloadedDiaObjects=self.diaObjects,
237 preloadedDiaSources=self.diaSources,
238 preloadedDiaForcedSources=self.diaForcedSources,
239 band="g",
240 idGenerator=IdGenerator(),
241 solarSystemObjectTable=ssObjects)
242 for subtaskName in subtasksToMock:
243 getattr(task, subtaskName).run.assert_called_once()
244 assertValidOutput(task, result)
245 # Exact type and contents of apdbMarker are undefined.
246 self.assertIsInstance(result.apdbMarker, pexConfig.Config)
247 meta = task.getFullMetadata()
248 # Check that the expected metadata has been set.
249 self.assertEqual(meta["diaPipe.numUpdatedDiaObjects"], 2)
250 self.assertEqual(meta["diaPipe.numUnassociatedDiaObjects"], 3)
251 # and that associators ran once or not at all.
252 mainRun.assert_called_once()
253 if doSolarSystemAssociation:
254 ssRun.assert_called_once()
255 else:
256 ssRun.assert_not_called()
258 def test_tooManyDiaObjectsError(self):
259 maxNewDiaObjects = 100
261 nDiaSources = maxNewDiaObjects + 1
262 diaSources = makeDiaSources(nDiaSources, np.zeros(nDiaSources), self.exposure, self.rng)
264 def runAndTestWithContextManager(threshold):
265 config = self._makeDefaultConfig(config_file=self.config_file.name,
266 doSolarSystemAssociation=False,
267 filterUnAssociatedSources=False,
268 maxNewDiaObjects=threshold,
269 )
270 task = DiaPipelineTask(config=config)
271 contextManager = self.assertRaises(pipeBase.AlgorithmError) if nDiaSources > threshold > 0 \
272 else contextlib.nullcontext()
273 with contextManager:
274 task.associateDiaSources(
275 diaSources,
276 None,
277 None,
278 self.diaObjects,
279 )
280 # Test cases at, above, and below the threshold as well as at 0.
281 runAndTestWithContextManager(0)
282 runAndTestWithContextManager(maxNewDiaObjects - 1)
283 runAndTestWithContextManager(maxNewDiaObjects)
284 runAndTestWithContextManager(maxNewDiaObjects + 1)
286 def test_createDiaObjects(self):
287 """Test that creating new DiaObjects works as expected.
288 """
289 nSources = 5
290 config = self._makeDefaultConfig(config_file=self.config_file.name, doPackageAlerts=False)
291 task = DiaPipelineTask(config=config)
292 diaSources = pd.DataFrame(data=[
293 {"ra": 0.04*idx, "dec": 0.04*idx,
294 "diaSourceId": idx + 1 + nSources, "diaObjectId": 0,
295 "ssObjectId": 0}
296 for idx in range(nSources)])
298 result = task.createNewDiaObjects(convertDataFrameToSdmSchema(task.schema, diaSources, "DiaSource",
299 skipIndex=True))
300 self.assertEqual(nSources, len(result.newDiaObjects))
301 self.assertTrue(np.all(np.equal(
302 result.diaSources["diaObjectId"].to_numpy(),
303 result.diaSources["diaSourceId"].to_numpy())))
304 self.assertTrue(np.all(np.equal(
305 result.newDiaObjects["diaObjectId"].to_numpy(),
306 result.diaSources["diaSourceId"].to_numpy())))
308 def test_purgeDiaObjects(self):
309 """Remove diaOjects that are outside an image's bounding box.
310 """
312 config = self._makeDefaultConfig(config_file=self.config_file.name, doPackageAlerts=False)
313 task = DiaPipelineTask(config=config)
314 exposure = makeExposure(False, False)
315 nObj0 = 20
317 # Create diaObjects
318 diaObjects = makeDiaObjects(nObj0, exposure, self.rng)
319 # Shrink the bounding box so that some of the diaObjects will be outside
320 bbox = exposure.getBBox()
321 size = np.minimum(bbox.getHeight(), bbox.getWidth())
322 bbox.grow(-size//4)
323 exposureCut = exposure[bbox]
324 sizeCut = np.minimum(bbox.getHeight(), bbox.getWidth())
325 buffer = 10
326 bbox.grow(buffer)
328 def check_diaObjects(bbox, wcs, diaObjects):
329 raVals = diaObjects.ra.to_numpy()
330 decVals = diaObjects.dec.to_numpy()
331 xVals, yVals = wcs.skyToPixelArray(raVals, decVals, degrees=True)
332 selector = bbox.contains(xVals, yVals)
333 return selector
335 selector0 = check_diaObjects(bbox, exposureCut.getWcs(), diaObjects)
336 nIn0 = np.count_nonzero(selector0)
337 nOut0 = np.count_nonzero(~selector0)
338 self.assertEqual(nObj0, nIn0 + nOut0)
340 # Add an ID that is not in the diaObject table. It should not get removed.
341 diaObjectIds0 = diaObjects["diaObjectId"].copy(deep=True)
342 diaObjectIds0[max(diaObjectIds0.index) + 1] = 999
343 diaObjects1, objIds = task.purgeDiaObjects(exposureCut.getBBox(), exposureCut.getWcs(), diaObjects,
344 diaObjectIds=diaObjectIds0, buffer=buffer)
345 diaObjectIds1 = diaObjects1["diaObjectId"]
346 # Verify that the bounding box was not changed
347 sizeCheck = np.minimum(exposureCut.getBBox().getHeight(), exposureCut.getBBox().getWidth())
348 self.assertEqual(sizeCut, sizeCheck)
349 selector1 = check_diaObjects(bbox, exposureCut.getWcs(), diaObjects1)
350 nIn1 = np.count_nonzero(selector1)
351 nOut1 = np.count_nonzero(~selector1)
352 nObj1 = len(diaObjects1)
353 self.assertEqual(nObj1, nIn0)
354 # Verify that not all diaObjects were removed
355 self.assertGreater(nObj1, 0)
356 # Check that some diaObjects were removed
357 self.assertLess(nObj1, nObj0)
358 # Verify that no objects outside the bounding box remain
359 self.assertEqual(nOut1, 0)
360 # Verify that no objects inside the bounding box were removed
361 self.assertEqual(nIn1, nIn0)
362 # The length of the updated object IDs should equal the number of objects
363 # plus one, since we added an extra ID.
364 self.assertEqual(nObj1 + 1, len(objIds))
365 # All of the object IDs extracted from the catalog should be in the pruned object IDs
366 self.assertTrue(set(objIds).issuperset(diaObjectIds1))
367 # The pruned object IDs should contain entries that are not in the catalog
368 self.assertFalse(set(diaObjectIds1).issuperset(objIds))
369 # Some IDs should have been removed
370 self.assertLess(len(objIds), len(diaObjectIds0))
372 def test_filterDiaObjects(self):
373 """Unassociated diaSources that are filtered should have good reliability and SNR.
374 Glint trail sources should also be filtered out.
375 """
377 config = self._makeDefaultConfig(config_file=self.config_file.name,
378 doPackageAlerts=False,
379 filterUnAssociatedSources=True)
381 configBadFilter = self._makeDefaultConfig(config_file=self.config_file.name,
382 doPackageAlerts=False,
383 filterUnAssociatedSources=True,
384 newObjectFluxField="notAFlux")
385 configBadFlag = self._makeDefaultConfig(config_file=self.config_file.name,
386 doPackageAlerts=False,
387 filterUnAssociatedSources=True,
388 newObjectBadFlags=("junkSource", "notUsed"))
389 with self.assertRaises(pipeBase.InvalidQuantumError):
390 DiaPipelineTask(config=configBadFilter)
391 with self.assertRaises(pipeBase.InvalidQuantumError):
392 DiaPipelineTask(config=configBadFlag)
393 task = DiaPipelineTask(config=config)
394 nUnassociatedDiaSources = 234
396 # Create diaSources
397 diaSources = makeDiaSources(nUnassociatedDiaSources,
398 np.zeros(nUnassociatedDiaSources),
399 self.exposure,
400 self.rng,
401 flagList=task.config.newObjectBadFlags)
402 reliability = self.rng.random(nUnassociatedDiaSources)
403 flux = (self.rng.random(nUnassociatedDiaSources)**2)*100
404 fluxErr = np.sqrt(flux)
405 glint_trail = np.zeros(nUnassociatedDiaSources, dtype=bool)
406 glint_trail[12:16] = True # add 4 glint trail sources
407 diaSources["reliability"] = reliability
408 diaSources["reliabilityVersion"] = '99.42'
409 diaSources[config.newObjectFluxField] = flux
410 diaSources[config.newObjectFluxField + "Err"] = fluxErr
411 diaSources["glint_trail"] = glint_trail
412 badFlagName = task.config.newObjectBadFlags[0]
413 badFlags = np.zeros(nUnassociatedDiaSources, dtype=bool)
414 nBadFlags = 20
415 badFlags[0:nBadFlags] = True
416 diaSources[badFlagName] = badFlags
418 def runAndCheckFilter(diaSources, snrThreshold=None, lowReliabilitySnrThreshold=None,
419 reliabilityThreshold=None, lowSnrReliabilityThreshold=None,
420 badFlags=None,
421 ):
423 filterResults = task.filterSources(
424 diaSources.copy(deep=True),
425 snrThreshold=snrThreshold,
426 lowReliabilitySnrThreshold=lowReliabilitySnrThreshold,
427 reliabilityThreshold=reliabilityThreshold,
428 lowSnrReliabilityThreshold=lowSnrReliabilityThreshold,
429 badFlags=badFlags,
430 )
431 self.assertEqual(len(filterResults.goodSources) + len(filterResults.badSources),
432 nUnassociatedDiaSources)
433 goodFlux = filterResults.goodSources[config.newObjectFluxField]
434 goodFluxErr = filterResults.goodSources[config.newObjectFluxField + "Err"]
435 goodSnr = np.array(goodFlux/goodFluxErr)
436 self.assertTrue(np.all(goodSnr > snrThreshold))
437 goodReliability = np.array(filterResults.goodSources["reliability"])
438 self.assertTrue(np.all(goodReliability > reliabilityThreshold))
439 goodLowSnrFlag = goodSnr < lowReliabilitySnrThreshold
440 lowSnrReliability = goodReliability[goodLowSnrFlag]
441 self.assertTrue(np.all(lowSnrReliability > lowSnrReliabilityThreshold))
442 glintTrailSources = np.array(filterResults.goodSources["glint_trail"])
443 self.assertTrue(not any(glintTrailSources))
445 # No sources should be removed if the thresholds are turned off
446 runAndCheckFilter(diaSources,
447 snrThreshold=0, lowReliabilitySnrThreshold=0,
448 reliabilityThreshold=0, lowSnrReliabilityThreshold=0)
449 runAndCheckFilter(diaSources,
450 snrThreshold=0, lowReliabilitySnrThreshold=0,
451 reliabilityThreshold=0, lowSnrReliabilityThreshold=0,
452 badFlags=[badFlagName])
453 runAndCheckFilter(diaSources,
454 snrThreshold=2, lowReliabilitySnrThreshold=8,
455 reliabilityThreshold=0, lowSnrReliabilityThreshold=0)
456 runAndCheckFilter(diaSources,
457 snrThreshold=2, lowReliabilitySnrThreshold=8,
458 reliabilityThreshold=0, lowSnrReliabilityThreshold=0.5)
459 runAndCheckFilter(diaSources,
460 snrThreshold=0, lowReliabilitySnrThreshold=0,
461 reliabilityThreshold=0.1, lowSnrReliabilityThreshold=0.5)
462 runAndCheckFilter(diaSources,
463 snrThreshold=2, lowReliabilitySnrThreshold=8,
464 reliabilityThreshold=0.1, lowSnrReliabilityThreshold=0.5)
465 runAndCheckFilter(diaSources,
466 snrThreshold=2, lowReliabilitySnrThreshold=8,
467 reliabilityThreshold=0.1, lowSnrReliabilityThreshold=0.5,
468 badFlags=[badFlagName])
470 def testRunWithForcedMeasurement(self):
471 """Test running association with forced photometry."""
473 reliabilityThreshold = 0.5
474 trailLengthThreshold = 1.0
475 config = self._makeDefaultConfig(config_file=self.config_file.name,
476 doPackageAlerts=False,
477 forcedReliabilityThreshold=reliabilityThreshold,
478 forcedTrailLengthThreshold=trailLengthThreshold)
479 task = DiaPipelineTask(config=config)
480 nDeepObjects = 20
481 nShallowObjects = 20
482 nGoodDiaSourcesDeep = 100
483 nGoodDiaSourcesShallow = nShallowObjects
484 nGoodDiaSources = nGoodDiaSourcesDeep + nGoodDiaSourcesShallow
485 nBadDiaSources = 200
487 # Create diaObjects
488 diaObjectsDeep = makeDiaObjects(nDeepObjects, self.exposure, self.rng, startId=1)
489 diaObjectsShallow = makeDiaObjects(nShallowObjects, self.exposure, self.rng, startId=1 + nDeepObjects)
490 diaObjects = task.mergeCatalogs(diaObjectsDeep, diaObjectsShallow, tableName="DiaObject")
492 diaSourcesGoodDeep = makeDiaSources(nGoodDiaSourcesDeep, diaObjectsDeep["diaObjectId"].to_numpy(),
493 self.exposure, self.rng, startId=1,
494 flagList=config.forcedBadFlags)
495 diaSourcesGoodShallow = makeDiaSources(nGoodDiaSourcesShallow,
496 diaObjectsShallow["diaObjectId"].to_numpy(),
497 self.exposure, self.rng, startId=1 + nGoodDiaSourcesDeep,
498 flagList=config.forcedBadFlags)
500 diaSourcesGoodDeep = convertDataFrameToSdmSchema(task.schema, diaSourcesGoodDeep,
501 tableName="DiaSource", skipIndex=True)
502 diaSourcesGood = task.mergeCatalogs(diaSourcesGoodDeep, diaSourcesGoodShallow, tableName="DiaSource")
504 diaSourcesBad = makeDiaSources(nBadDiaSources, diaObjects["diaObjectId"].to_numpy(), self.exposure,
505 self.rng, randomizeObjects=True, startId=1 + nGoodDiaSources,
506 flagList=config.forcedBadFlags)
507 diaSourcesGood['reliability'] = (self.rng.random(nGoodDiaSources)*(1 - reliabilityThreshold)
508 + reliabilityThreshold)
509 diaSourcesGood['reliabilityVersion'] = '99.42'
510 diaSourcesGood['trailLength'] = self.rng.random(nGoodDiaSources)*trailLengthThreshold
511 diaSourcesBad = convertDataFrameToSdmSchema(task.schema, diaSourcesBad,
512 tableName="DiaSource", skipIndex=True)
514 # Set some "bad" diaSources to have bad reliability, some good
515 diaSourcesBad['reliability'] = self.rng.random(nBadDiaSources)
516 diaSourcesBad['reliabilityVersion'] = '99.42'
517 # Set some "bad" diaSources to have too long trail lengths, some acceptible
518 diaSourcesBad['trailLength'] = self.rng.random(nBadDiaSources)*trailLengthThreshold + 0.5
519 missingBadFlags = ((diaSourcesBad['reliability'] > reliabilityThreshold)
520 & (diaSourcesBad['trailLength'] < trailLengthThreshold)
521 )
522 for badFlag in config.forcedBadFlags:
523 # Set a fraction of the bad diaSources to have each flag, assigned randomly
524 diaSourcesBad[badFlag] = self.rng.random(nBadDiaSources) > 0.8
525 missingBadFlags &= ~diaSourcesBad[badFlag]
526 # Catch any "bad" diaSources that have not yet been flagged
527 if np.any(missingBadFlags): 527 ↛ 529line 527 didn't jump to line 529 because the condition on line 527 was always true
528 diaSourcesBad[badFlag] |= missingBadFlags
529 diaObjectsForcedGoodOnly = task._selectGoodDiaObjects(diaObjects, diaSourcesGood)
530 diaObjectsForcedBadOnly = task._selectGoodDiaObjects(diaObjects, diaSourcesBad)
531 # None of the diaObjects should be selected if only given the bad diaSources
532 self.assertTrue(diaObjectsForcedBadOnly.empty)
534 diaSources = task.mergeCatalogs(diaSourcesGood, diaSourcesBad, tableName="DiaSource")
535 diaObjectsForced = task._selectGoodDiaObjects(diaObjects, diaSources)
536 # The number of diaObjects selected should be the same regardless of
537 # whether the bad diaSources are included
538 self.assertEqual(len(diaObjectsForced), len(diaObjectsForcedGoodOnly))
539 # All of the deep diaObjects should be selected, and none of the shallow
540 self.assertEqual(len(diaObjectsForced), nDeepObjects)
541 fSrc = task.runForcedMeasurement(diaObjectsForced, diaObjectsForced, self.exposure, self.exposure,
542 IdGenerator())
543 self.assertEqual(set(fSrc['diaObjectId']), set(diaObjectsDeep['diaObjectId']))
545 def test_selectGoodObjects(self):
546 """Test the diaObject selection funtion used for forced photometry.
547 """
548 reliabilityThreshold = 0.5
549 trailLengthThreshold = 1.0
550 config = self._makeDefaultConfig(config_file=self.config_file.name,
551 doPackageAlerts=False,
552 forcedReliabilityThreshold=reliabilityThreshold,
553 forcedTrailLengthThreshold=trailLengthThreshold)
554 task = DiaPipelineTask(config=config)
555 nObjects = 20
556 nDiaSources = 100
558 # Create diaObjects
559 diaObjects = makeDiaObjects(nObjects, self.exposure, self.rng, startId=1)
561 diaSources = makeDiaSources(nDiaSources, diaObjects["diaObjectId"].to_numpy(),
562 self.exposure, self.rng, startId=1,
563 flagList=config.forcedBadFlags)
564 # Since flagList is not specified, the columns will be missing, and added and filled with NaNs
565 # when put through convertDataFrameToSdmSchema.
566 diaSourcesMissingColumns = makeDiaSources(nDiaSources, diaObjects["diaObjectId"].to_numpy(),
567 self.exposure, self.rng, startId=1 + nDiaSources)
568 # Should raise an error if run before adding the required columns
569 with self.assertRaises(RuntimeError):
570 task._selectGoodDiaObjects(diaObjects, diaSources)
572 diaSources['reliability'] = (self.rng.random(nDiaSources)*(1 - reliabilityThreshold)
573 + reliabilityThreshold)
574 diaSources['reliabilityVersion'] = '99.42'
575 diaSources['trailLength'] = self.rng.random(nDiaSources)*trailLengthThreshold
577 diaSourcesMissingColumns['reliability'] = (self.rng.random(nDiaSources)*(1 - reliabilityThreshold)
578 + reliabilityThreshold)
579 diaSourcesMissingColumns['trailLength'] = self.rng.random(nDiaSources)*trailLengthThreshold
581 diaSourcesNotMatched = makeDiaSources(nDiaSources, diaObjects["diaObjectId"].to_numpy() + 999,
582 self.exposure, self.rng, startId=1)
584 diaSourcesNotMatched['reliability'] = (self.rng.random(nDiaSources)*(1 - reliabilityThreshold)
585 + reliabilityThreshold)
586 diaSourcesNotMatched['reliabilityVersion'] = '99.42'
587 diaSourcesNotMatched['trailLength'] = self.rng.random(nDiaSources)*trailLengthThreshold
589 diaSources = convertDataFrameToSdmSchema(task.schema, diaSources,
590 tableName="DiaSource", skipIndex=True)
591 diaSourcesMissingColumns = convertDataFrameToSdmSchema(task.schema, diaSourcesMissingColumns,
592 tableName="DiaSource", skipIndex=True)
593 diaSourcesNotMatched = convertDataFrameToSdmSchema(task.schema, diaSourcesNotMatched,
594 tableName="DiaSource", skipIndex=True)
596 # Run the method with missing flags
597 diaObjectsSelected = task._selectGoodDiaObjects(diaObjects, diaSources)
598 diaObjectsBadSelection = task._selectGoodDiaObjects(diaObjects, diaSourcesNotMatched)
599 diaObjectsNaNSelection = task._selectGoodDiaObjects(diaObjects, diaSourcesMissingColumns)
600 # The matched catalog of good diaSources should not drop any diaObjects
601 self.assertTrue(diaObjects.equals(diaObjectsSelected))
602 # The mis-matched catalog of good diaSources should drop every diaObject
603 self.assertTrue(diaObjectsBadSelection.empty)
604 # All diaObjects should be dropped for the diaSource catalog that has all NaN values for the flags
605 self.assertTrue(diaObjectsNaNSelection.empty)
607 def test_selectGoodObjectsWithWrongFlags(self):
608 """Test the diaObject selection funtion used for forced photometry.
609 """
610 reliabilityThreshold = 0.5
611 trailLengthThreshold = 1.0
612 config = self._makeDefaultConfig(config_file=self.config_file.name,
613 doPackageAlerts=False,
614 forcedReliabilityThreshold=reliabilityThreshold,
615 forcedTrailLengthThreshold=trailLengthThreshold,
616 forcedBadFlags=['foo', 'bar'])
617 task = DiaPipelineTask(config=config)
618 nObjects = 20
619 nDiaSources = 100
621 # Create diaObjects
622 diaObjects = makeDiaObjects(nObjects, self.exposure, self.rng, startId=1)
624 diaSources = makeDiaSources(nDiaSources, diaObjects["diaObjectId"].to_numpy(),
625 self.exposure, self.rng, startId=1)
627 diaSources['reliability'] = (self.rng.random(nDiaSources)*(1 - reliabilityThreshold)
628 + reliabilityThreshold)
629 diaSources['reliabilityVersion'] = '99.42'
630 diaSources['trailLength'] = self.rng.random(nDiaSources)*trailLengthThreshold
632 diaSourcesNotMatched = makeDiaSources(nDiaSources, diaObjects["diaObjectId"].to_numpy() + 999,
633 self.exposure, self.rng, startId=1)
635 diaSourcesNotMatched['reliability'] = (self.rng.random(nDiaSources)*(1 - reliabilityThreshold)
636 + reliabilityThreshold)
637 diaSourcesNotMatched['reliabilityVersion'] = '99.42'
638 diaSourcesNotMatched['trailLength'] = self.rng.random(nDiaSources)*trailLengthThreshold
640 diaSources = convertDataFrameToSdmSchema(task.schema, diaSources,
641 tableName="DiaSource", skipIndex=True)
642 diaSourcesNotMatched = convertDataFrameToSdmSchema(task.schema, diaSourcesNotMatched,
643 tableName="DiaSource", skipIndex=True)
645 # Verify that the flags are in fact missing
646 for flag in config.forcedBadFlags:
647 self.assertNotIn(flag, diaSources.columns)
648 # Run the method with missing flags
649 diaObjectsSelected = task._selectGoodDiaObjects(diaObjects, diaSources)
650 diaObjectsBadSelection = task._selectGoodDiaObjects(diaObjects, diaSourcesNotMatched)
651 # The matched catalog of good diaSources should not drop any diaObjects
652 self.assertTrue(diaObjects.equals(diaObjectsSelected))
653 # The mis-matched catalog of good diaSources should drop every diaObject
654 self.assertTrue(diaObjectsBadSelection.empty)
656 def test_mergeEmptyCatalog(self):
657 """Test that a catalog is unchanged if it is merged with an empty
658 catalog.
659 """
660 diaSourcesBase = self.diaSources
662 config = self._makeDefaultConfig(config_file=self.config_file.name, doPackageAlerts=False)
663 task = DiaPipelineTask(config=config)
664 # Include some but not all columns that should be in diaSourcesBase, and some that are mis-matched
665 diaSourcesEmpty = pd.DataFrame(columns=["ra", "dec", "foo"])
666 diaSourcesTest = task.mergeCatalogs(diaSourcesBase, diaSourcesEmpty, tableName="DiaSource")
667 self.assertTrue(diaSourcesBase.equals(diaSourcesTest))
669 def test_mergeCatalogs(self):
670 """Test that a merged catalog is concatenated correctly.
671 """
672 config = self._makeDefaultConfig(config_file=self.config_file.name, doPackageAlerts=False)
673 task = DiaPipelineTask(config=config)
675 diaSourcesBase = convertDataFrameToSdmSchema(task.schema, self.diaSources, "DiaSource",
676 skipIndex=True)
677 nBase = len(diaSourcesBase)
678 nNew = int(nBase/2)
680 diaSourcesNew = makeDiaSources(nNew, self.diaObjects["diaObjectId"].to_numpy(), self.exposure,
681 self.rng)
682 diaSourcesNew = convertDataFrameToSdmSchema(task.schema, diaSourcesNew, "DiaSource", skipIndex=True)
683 diaSourcesTest = task.mergeCatalogs(diaSourcesBase, diaSourcesNew, tableName="DiaSource")
684 self.assertEqual(len(diaSourcesTest), nBase + nNew)
685 diaSourcesExtract1 = diaSourcesTest.iloc[:nBase]
686 diaSourcesExtract2 = diaSourcesTest.iloc[nBase:]
688 pd.testing.assert_frame_equal(diaSourcesBase, diaSourcesExtract1)
689 pd.testing.assert_frame_equal(diaSourcesNew, diaSourcesExtract2)
691 def test_updateObjectTable(self):
692 """Test that the diaObject record is updated with the number of
693 diaSources.
694 """
695 config = self._makeDefaultConfig(config_file=self.config_file.name, doPackageAlerts=False)
696 task = DiaPipelineTask(config=config)
697 nObjects = 20
698 nSrcPerObject = 10
699 nExtraSources = 5
700 nSources = nSrcPerObject*nObjects + nExtraSources
701 expectedSourcesPerObject = nSrcPerObject*np.ones(nObjects)
702 expectedSourcesPerObject[:nExtraSources] += 1
703 diaObjects = makeDiaObjects(nObjects, self.exposure, self.rng)
704 diaSources = makeDiaSources(nSources, diaObjects["diaObjectId"].to_numpy(), self.exposure, self.rng)
705 updatedDiaObjects = task.updateObjectTable(diaObjects, diaSources)
706 self.assertTrue(np.all(updatedDiaObjects.nDiaSources.values == expectedSourcesPerObject))
708 def test_diaCalculationAllBands(self):
709 """Test that the full DiaPipelineTask.run computes per-band
710 psfFluxMean for all bands with source data and NaN where absent.
711 """
712 config = self._makeDefaultConfig(
713 config_file=self.config_file.name,
714 doPackageAlerts=False,
715 doSolarSystemAssociation=False,
716 )
717 task = DiaPipelineTask(config=config)
718 task.testDataFrameIndex = lambda x: False
720 nObjects = 3
721 diaObjects = makeDiaObjects(nObjects, self.exposure, self.rng)
722 diaObjectIds = diaObjects["diaObjectId"].to_numpy()
724 # Synthesize preloadedDiaSources in g, r, and i bands with known
725 # psfFlux values. These represent the historical source catalog.
726 bands_with_data = ["g", "r", "i"]
727 rows = []
728 srcId = 1
729 for band in bands_with_data:
730 for i, objId in enumerate(diaObjectIds):
731 nSrc = 3
732 for j in range(nSrc):
733 rows.append({
734 "diaSourceId": srcId,
735 "diaObjectId": objId,
736 "band": band,
737 "ra": diaObjects.iloc[i]["ra"],
738 "dec": diaObjects.iloc[i]["dec"],
739 "midpointMjdTai": 58000.0 + srcId,
740 "psfFlux": 1000.0 + srcId * 10,
741 "psfFluxErr": 10.0,
742 })
743 srcId += 1
744 preloadedDiaSources = pd.DataFrame(rows)
745 preloadedDiaSources = convertDataFrameToSdmSchema(
746 task.schema, preloadedDiaSources, "DiaSource", skipIndex=True
747 )
748 preloadedDiaSources.set_index(
749 ["diaObjectId", "band", "diaSourceId"], inplace=True, drop=False
750 )
752 # The new diaSourceTable for this visit (band=g) needs to associate
753 # with existing objects. Use the same positions as the diaObjects.
754 newSrcRows = []
755 for i, objId in enumerate(diaObjectIds):
756 newSrcRows.append({
757 "diaSourceId": srcId,
758 "diaObjectId": 0,
759 "ssObjectId": 0,
760 "band": "g",
761 "ra": diaObjects.iloc[i]["ra"],
762 "dec": diaObjects.iloc[i]["dec"],
763 "midpointMjdTai": 58100.0,
764 "psfFlux": 1500.0,
765 "psfFluxErr": 15.0,
766 })
767 srcId += 1
768 diaSourceTable = pd.DataFrame(newSrcRows)
770 preloadedDiaForcedSources = pd.DataFrame(
771 columns=["diaObjectId", "diaForcedSourceId"]
772 ).set_index(["diaObjectId", "diaForcedSourceId"], drop=False)
774 with patch.multiple(task, apdb=DEFAULT, diaForcedSource=DEFAULT):
775 result = task.run(
776 diaSourceTable,
777 None,
778 self.diffim,
779 self.exposure,
780 self.template,
781 preloadedDiaObjects=diaObjects,
782 preloadedDiaSources=preloadedDiaSources,
783 preloadedDiaForcedSources=preloadedDiaForcedSources,
784 band="g",
785 idGenerator=IdGenerator(),
786 )
788 outputDiaObjects = result.diaObjects
790 # Bands with data should have finite psfFluxMean.
791 for band in bands_with_data:
792 col = f"{band}_psfFluxMean"
793 self.assertIn(col, outputDiaObjects.columns)
794 vals = outputDiaObjects[col].to_numpy()
795 self.assertTrue(
796 np.all(np.isfinite(vals)),
797 f"{col} should be finite for all objects but got {vals}"
798 )
800 # Bands without data should have NaN psfFluxMean.
801 bands_without_data = [b for b in config.validBands
802 if b not in bands_with_data]
803 for band in bands_without_data:
804 col = f"{band}_psfFluxMean"
805 if col in outputDiaObjects.columns: 805 ↛ 803line 805 didn't jump to line 803 because the condition on line 805 was always true
806 vals = outputDiaObjects[col].to_numpy()
807 self.assertTrue(
808 np.all(np.isnan(vals)),
809 f"{col} should be NaN (no data in {band}) but got {vals}"
810 )
813class MemoryTester(lsst.utils.tests.MemoryTestCase):
814 pass
817def setup_module(module):
818 lsst.utils.tests.init()
821if __name__ == "__main__": 821 ↛ 822line 821 didn't jump to line 822 because the condition on line 821 was never true
822 lsst.utils.tests.init()
823 unittest.main()