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DM-38834: Fix ptc covariance weight bug and add associated tests. #183

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Apr 25, 2023
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DM-38834: Fix ptc covariance weight bug and add associated tests. #183

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fd61117
Fix typo which replaced covariancesSqrtWeights with covariances.
erykoff Apr 24, 2023
df26045
Add test for covariance model parameters.
erykoff Apr 25, 2023
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2 changes: 1 addition & 1 deletion python/lsst/cp/pipe/ptc/cpSolvePtcTask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -281,7 +281,7 @@ def run(self, inputCovariances, camera=None, detId=0):
datasetPtc.rawVars[ampName] = datasetPtc.rawVars[ampName][index]
datasetPtc.expIdMask[ampName] = datasetPtc.expIdMask[ampName][index]
datasetPtc.covariances[ampName] = datasetPtc.covariances[ampName][index]
datasetPtc.covariancesSqrtWeights[ampName] = datasetPtc.covariances[ampName][index]
datasetPtc.covariancesSqrtWeights[ampName] = datasetPtc.covariancesSqrtWeights[ampName][index]

if self.config.ptcFitType == "FULLCOVARIANCE":
# Fit the measured covariances vs mean signal to
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29 changes: 23 additions & 6 deletions tests/test_ptc.py
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Expand Up @@ -138,6 +138,10 @@ def test_covAstier(self):
extractConfig = self.defaultConfigExtract
extractConfig.minNumberGoodPixelsForCovariance = 5000
extractConfig.detectorMeasurementRegion = 'FULL'
# Cut off the low-flux point which is a bad fit, and this
# also exercises this functionality and makes the tests
# run a lot faster.
extractConfig.minMeanSignal["ALL_AMPS"] = 2000.0
extractTask = cpPipe.ptc.PhotonTransferCurveExtractTask(config=extractConfig)

solveConfig = self.defaultConfigSolve
Expand Down Expand Up @@ -181,18 +185,31 @@ def test_covAstier(self):
resultsSolve = solveTask.run(resultsExtract.outputCovariances,
camera=FakeCamera([self.flatExp1.getDetector()]))

ptc = resultsSolve.outputPtcDataset

for amp in self.ampNames:
self.assertAlmostEqual(resultsSolve.outputPtcDataset.gain[amp], inputGain, places=2)
for v1, v2 in zip(varStandard[amp], resultsSolve.outputPtcDataset.finalVars[amp]):
self.assertAlmostEqual(ptc.gain[amp], inputGain, places=2)
for v1, v2 in zip(varStandard[amp], ptc.finalVars[amp]):
self.assertAlmostEqual(v1/v2, 1.0, places=1)

# Test various operations on the PTC output from the task.
ptc = resultsSolve.outputPtcDataset
mask = ptc.getGoodPoints(amp)

values = ((ptc.covariancesModel[amp][mask, 0, 0] - ptc.covariances[amp][mask, 0, 0])
/ ptc.covariancesModel[amp][mask, 0, 0])
np.testing.assert_array_less(np.abs(values), 2e-3)

values = ((ptc.covariancesModel[amp][mask, 1, 1] - ptc.covariances[amp][mask, 1, 1])
/ ptc.covariancesModel[amp][mask, 1, 1])
np.testing.assert_array_less(np.abs(values), 0.2)

values = ((ptc.covariancesModel[amp][mask, 1, 2] - ptc.covariances[amp][mask, 1, 2])
/ ptc.covariancesModel[amp][mask, 1, 2])
np.testing.assert_array_less(np.abs(values), 0.2)

expIdsUsed = ptc.getExpIdsUsed("C:0,0")
# Check that these are the same as the inputs, paired up, with the
# final two removed.
self.assertTrue(np.all(expIdsUsed == np.array(expIds).reshape(len(expIds) // 2, 2)[:-1]))
# first two (low flux) and final two (nans) removed.
self.assertTrue(np.all(expIdsUsed == np.array(expIds).reshape(len(expIds) // 2, 2)[1:-1]))
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goodAmps = ptc.getGoodAmps()
self.assertEqual(goodAmps, self.ampNames)
Expand Down