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DM-34922: Report ptc turnoff in ptcDataset from cpPtcSolve #213

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May 26, 2022
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DM-34922: Report ptc turnoff in ptcDataset from cpPtcSolve #213

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abcd241
Add PTC turnoff to ptc dataset
plazas May 25, 2022
e6781f7
Update tests with PTC turnoff
plazas May 25, 2022
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24 changes: 17 additions & 7 deletions python/lsst/ip/isr/ptcDataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -101,6 +101,9 @@ class PhotonTransferCurveDataset(IsrCalib):
ptcFitChiSq : `dict`, [`str`, `list`]
Dictionary keyed by amp names containing the reduced chi squared
of the fit for ptcFitTye in ["POLYNOMIAL", "EXPAPPROXIMATION"].
ptcTurnoff : `float`
Flux value (in ADU) where the variance of the PTC curve starts
decreasing consistently.
covariances : `dict`, [`str`, `list`]
Dictionary keyed by amp names containing a list of measured
covariances per mean flux.
Expand Down Expand Up @@ -176,6 +179,7 @@ def __init__(self, ampNames=[], ptcFitType=None, covMatrixSide=1, **kwargs):
self.ptcFitPars = {ampName: [] for ampName in ampNames}
self.ptcFitParsError = {ampName: [] for ampName in ampNames}
self.ptcFitChiSq = {ampName: np.nan for ampName in ampNames}
self.ptcTurnoff = {ampName: np.nan for ampName in ampNames}

self.covariances = {ampName: [] for ampName in ampNames}
self.covariancesModel = {ampName: [] for ampName in ampNames}
Expand All @@ -192,18 +196,18 @@ def __init__(self, ampNames=[], ptcFitType=None, covMatrixSide=1, **kwargs):
super().__init__(**kwargs)
self.requiredAttributes.update(['badAmps', 'inputExpIdPairs', 'expIdMask', 'rawExpTimes',
'rawMeans', 'rawVars', 'gain', 'gainErr', 'noise', 'noiseErr',
'ptcFitPars', 'ptcFitParsError', 'ptcFitChiSq', 'aMatrixNoB',
'covariances', 'covariancesModel', 'covariancesSqrtWeights',
'covariancesModelNoB',
'ptcFitPars', 'ptcFitParsError', 'ptcFitChiSq', 'ptcTurnoff',
'aMatrixNoB', 'covariances', 'covariancesModel',
'covariancesSqrtWeights', 'covariancesModelNoB',
'aMatrix', 'bMatrix', 'finalVars', 'finalModelVars', 'finalMeans',
'photoCharge'])

def setAmpValues(self, ampName, inputExpIdPair=[(np.nan, np.nan)], expIdMask=[np.nan],
rawExpTime=[np.nan], rawMean=[np.nan], rawVar=[np.nan], photoCharge=[np.nan],
gain=np.nan, gainErr=np.nan, noise=np.nan, noiseErr=np.nan, ptcFitPars=[np.nan],
ptcFitParsError=[np.nan], ptcFitChiSq=np.nan, covArray=[], covArrayModel=[],
covSqrtWeights=[], aMatrix=[], bMatrix=[], covArrayModelNoB=[], aMatrixNoB=[],
finalVar=[np.nan], finalModelVar=[np.nan], finalMean=[np.nan]):
ptcFitParsError=[np.nan], ptcFitChiSq=np.nan, ptcTurnoff=np.nan, covArray=[],
covArrayModel=[], covSqrtWeights=[], aMatrix=[], bMatrix=[], covArrayModelNoB=[],
aMatrixNoB=[], finalVar=[np.nan], finalModelVar=[np.nan], finalMean=[np.nan]):
"""Function to initialize an amp of a PhotonTransferCurveDataset.

Notes
Expand Down Expand Up @@ -238,7 +242,8 @@ def setAmpValues(self, ampName, inputExpIdPair=[(np.nan, np.nan)], expIdMask=[np
self.noiseErr[ampName] = noiseErr
self.ptcFitPars[ampName] = ptcFitPars
self.ptcFitParsError[ampName] = ptcFitParsError
self.ptcFitChiSq[ampName]
self.ptcFitChiSq[ampName] = ptcFitChiSq
self.ptcTurnoff[ampName] = ptcTurnoff
self.covariances[ampName] = covArray
self.covariancesSqrtWeights[ampName] = covSqrtWeights
self.covariancesModel[ampName] = covArrayModel
Expand Down Expand Up @@ -315,6 +320,7 @@ def fromDict(cls, dictionary):
calib.ptcFitPars[ampName] = np.array(dictionary['ptcFitPars'][ampName]).tolist()
calib.ptcFitParsError[ampName] = np.array(dictionary['ptcFitParsError'][ampName]).tolist()
calib.ptcFitChiSq[ampName] = np.array(dictionary['ptcFitChiSq'][ampName]).tolist()
calib.ptcTurnoff[ampName] = np.array(dictionary['ptcTurnoff'][ampName]).tolist()
calib.covariances[ampName] = np.array(dictionary['covariances'][ampName]).reshape(
(nSignalPoints, covMatrixSide, covMatrixSide)).tolist()
calib.covariancesModel[ampName] = np.array(
Expand Down Expand Up @@ -370,6 +376,7 @@ def toDict(self):
outDict['ptcFitPars'] = self.ptcFitPars
outDict['ptcFitParsError'] = self.ptcFitParsError
outDict['ptcFitChiSq'] = self.ptcFitChiSq
outDict['ptcTurnoff'] = self.ptcTurnoff
outDict['covariances'] = self.covariances
outDict['covariancesModel'] = self.covariancesModel
outDict['covariancesSqrtWeights'] = self.covariancesSqrtWeights
Expand Down Expand Up @@ -419,6 +426,7 @@ def fromTable(cls, tableList):
inDict['ptcFitPars'] = dict()
inDict['ptcFitParsError'] = dict()
inDict['ptcFitChiSq'] = dict()
inDict['ptcTurnoff'] = dict()
inDict['covariances'] = dict()
inDict['covariancesModel'] = dict()
inDict['covariancesSqrtWeights'] = dict()
Expand Down Expand Up @@ -450,6 +458,7 @@ def fromTable(cls, tableList):
inDict['ptcFitPars'][ampName] = record['PTC_FIT_PARS']
inDict['ptcFitParsError'][ampName] = record['PTC_FIT_PARS_ERROR']
inDict['ptcFitChiSq'][ampName] = record['PTC_FIT_CHI_SQ']
inDict['ptcTurnoff'][ampName] = record['PTC_TURNOFF']
inDict['covariances'][ampName] = record['COVARIANCES']
inDict['covariancesModel'][ampName] = record['COVARIANCES_MODEL']
inDict['covariancesSqrtWeights'][ampName] = record['COVARIANCES_SQRT_WEIGHTS']
Expand Down Expand Up @@ -507,6 +516,7 @@ def toTable(self):
'PTC_FIT_PARS': np.array(self.ptcFitPars[ampName]).tolist(),
'PTC_FIT_PARS_ERROR': np.array(self.ptcFitParsError[ampName]).tolist(),
'PTC_FIT_CHI_SQ': self.ptcFitChiSq[ampName],
'PTC_TURNOFF': self.ptcTurnoff[ampName],
'COVARIANCES': np.pad(np.array(self.covariances[ampName]),
((0, nPadPoints[ampName]), (0, 0), (0, 0)),
'constant', constant_values=np.nan).reshape(
Expand Down
3 changes: 3 additions & 0 deletions tests/test_ptcDataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,6 +95,8 @@ def test_ptcDatset(self):
localDataset.ptcFitPars[ampName] = np.array([10.0, 1.5, 1e-6]).tolist()
localDataset.ptcFitParsError[ampName] = np.array([1.0, 0.2, 1e-7]).tolist()
localDataset.ptcFitChiSq[ampName] = 1.0
localDataset.ptcTurnoff[ampName] = localDataset.rawMeans[ampName][-1]

localDataset.covariances[ampName] = np.full(
(nSignalPoints, nSideCovMatrix, nSideCovMatrix), np.nan).tolist()
localDataset.covariancesModel[ampName] = np.full(
Expand All @@ -112,6 +114,7 @@ def test_ptcDatset(self):
localDataset.ptcFitPars[ampName] = np.array([np.nan, np.nan]).tolist()
localDataset.ptcFitParsError[ampName] = np.array([np.nan, np.nan]).tolist()
localDataset.ptcFitChiSq[ampName] = np.array([np.nan, np.nan]).tolist()
localDataset.ptcTurnoff[ampName] = np.array([np.nan, np.nan]).tolist()

localDataset.covariances[ampName] = np.full(
(nSignalPoints, nSideCovMatrix, nSideCovMatrix), 105.0).tolist()
Expand Down