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DM-38029: Fix PTC errors and warnings when there is a NaN input flat pair. #173

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merged 4 commits into from
Feb 15, 2023
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DM-38029: Fix PTC errors and warnings when there is a NaN input flat pair. #173

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5da596e
Add test for when one of the ptc means is a NaN.
erykoff Feb 15, 2023
be6fb4b
Add filter for bad means/variances.
erykoff Feb 15, 2023
6872c4c
Fix read noise median call to filter nans.
erykoff Feb 15, 2023
e4a2e5d
Improve specificity of logging when masking edge pixels.
erykoff Feb 15, 2023
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6 changes: 3 additions & 3 deletions python/lsst/cp/pipe/ptc/cpExtractPtcTask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -331,8 +331,8 @@ def run(self, inputExp, inputDims, taskMetadata):

if self.config.numEdgeSuspect > 0:
isrTask = IsrTask()
self.log.info("Masking %d pixels from the edges of all exposures as SUSPECT.",
self.config.numEdgeSuspect)
self.log.info("Masking %d pixels from the edges of all %ss as SUSPECT.",
self.config.numEdgeSuspect, self.config.edgeMaskLevel)

# Depending on the value of config.matchExposuresType
# 'expTime' can stand for exposure time, flux, or ID.
Expand Down Expand Up @@ -820,7 +820,7 @@ def getReadNoiseFromMetadata(self, taskMetadata, ampName):
readNoises.append(overscanNoise)

if len(readNoises):
readNoise = np.median(np.array(readNoises))
readNoise = np.nanmedian(np.array(readNoises))
else:
self.log.warning("Median readout noise from ISR metadata for amp %s "
"could not be calculated." % ampName)
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3 changes: 3 additions & 0 deletions python/lsst/cp/pipe/ptc/cpSolvePtcTask.py
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Expand Up @@ -755,6 +755,9 @@ def _getInitialGoodPoints(means, variances, minVarPivotSearch, consecutivePoints
goodPoints[pivotIndex+1:] = False
break

# Finally, we filter out any infinities or NaNs.
goodPoints[(~np.isfinite(means)) | (~np.isfinite(variances))] = False

return goodPoints

def _makeZeroSafe(self, array, substituteValue=1e-9):
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7 changes: 7 additions & 0 deletions tests/test_ptc.py
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Expand Up @@ -167,6 +167,13 @@ def test_covAstier(self):

resultsExtract = extractTask.run(inputExp=expDict, inputDims=expIds,
taskMetadata=[self.metadataContents])

# Force the last PTC dataset to have a NaN, and ensure that the
# task runs (DM-38029). This is a minor perturbation and does not
# affect the output comparison.
resultsExtract.outputCovariances[-2].rawMeans['C:0,0'] = [np.nan]
resultsExtract.outputCovariances[-2].rawVars['C:0,0'] = [np.nan]

resultsSolve = solveTask.run(resultsExtract.outputCovariances,
camera=FakeCamera([self.flatExp1.getDetector()]))

Expand Down