361 """Construct a calibration from a dictionary of properties.
362 Must be implemented by the specific calibration subclasses.
367 Dictionary of properties.
371 calib : `lsst.ip.isr.PhotonTransferCurveDataset`
372 Constructed calibration.
377 Raised if the supplied dictionary is for a different
381 if calib._OBSTYPE != dictionary[
'metadata'][
'OBSTYPE']:
382 raise RuntimeError(f
"Incorrect Photon Transfer Curve dataset supplied. "
383 f
"Expected {calib._OBSTYPE}, found {dictionary['metadata']['OBSTYPE']}")
384 calib.setMetadata(dictionary[
'metadata'])
385 calib.ptcFitType = dictionary[
'ptcFitType']
386 calib.covMatrixSide = dictionary[
'covMatrixSide']
387 calib.covMatrixSideFullCovFit = dictionary[
'covMatrixSideFullCovFit']
388 calib.badAmps = np.array(dictionary[
'badAmps'],
'str').tolist()
392 covMatrixSide = calib.covMatrixSide
393 covMatrixSideFullCovFit = calib.covMatrixSideFullCovFit
395 covDimensionsProduct = len(np.array(list(dictionary[
'covariances'].values())[0]).ravel())
396 nSignalPoints = int(covDimensionsProduct/(covMatrixSide*covMatrixSide))
398 for ampName
in dictionary[
'ampNames']:
399 calib.ampNames.append(ampName)
400 calib.inputExpIdPairs[ampName] = dictionary[
'inputExpIdPairs'][ampName]
401 calib.expIdMask[ampName] = np.array(dictionary[
'expIdMask'][ampName])
402 calib.rawExpTimes[ampName] = np.array(dictionary[
'rawExpTimes'][ampName], dtype=np.float64)
403 calib.rawMeans[ampName] = np.array(dictionary[
'rawMeans'][ampName], dtype=np.float64)
404 calib.rawVars[ampName] = np.array(dictionary[
'rawVars'][ampName], dtype=np.float64)
405 calib.gain[ampName] = float(dictionary[
'gain'][ampName])
406 calib.gainErr[ampName] = float(dictionary[
'gainErr'][ampName])
407 calib.noise[ampName] = float(dictionary[
'noise'][ampName])
408 calib.noiseErr[ampName] = float(dictionary[
'noiseErr'][ampName])
409 calib.histVars[ampName] = np.array(dictionary[
'histVars'][ampName], dtype=np.float64)
410 calib.histChi2Dofs[ampName] = np.array(dictionary[
'histChi2Dofs'][ampName], dtype=np.float64)
411 calib.kspValues[ampName] = np.array(dictionary[
'kspValues'][ampName], dtype=np.float64)
412 calib.ptcFitPars[ampName] = np.array(dictionary[
'ptcFitPars'][ampName], dtype=np.float64)
413 calib.ptcFitParsError[ampName] = np.array(dictionary[
'ptcFitParsError'][ampName],
415 calib.ptcFitChiSq[ampName] = float(dictionary[
'ptcFitChiSq'][ampName])
416 calib.ptcTurnoff[ampName] = float(dictionary[
'ptcTurnoff'][ampName])
417 if nSignalPoints > 0:
419 calib.covariances[ampName] = np.array(dictionary[
'covariances'][ampName],
420 dtype=np.float64).reshape(
421 (nSignalPoints, covMatrixSide, covMatrixSide))
422 calib.covariancesModel[ampName] = np.array(
423 dictionary[
'covariancesModel'][ampName],
424 dtype=np.float64).reshape(
425 (nSignalPoints, covMatrixSideFullCovFit, covMatrixSideFullCovFit))
426 calib.covariancesSqrtWeights[ampName] = np.array(
427 dictionary[
'covariancesSqrtWeights'][ampName],
428 dtype=np.float64).reshape(
429 (nSignalPoints, covMatrixSide, covMatrixSide))
430 calib.aMatrix[ampName] = np.array(dictionary[
'aMatrix'][ampName],
431 dtype=np.float64).reshape(
432 (covMatrixSideFullCovFit, covMatrixSideFullCovFit))
433 calib.bMatrix[ampName] = np.array(dictionary[
'bMatrix'][ampName],
434 dtype=np.float64).reshape(
435 (covMatrixSideFullCovFit, covMatrixSideFullCovFit))
436 calib.covariancesModelNoB[ampName] = np.array(
437 dictionary[
'covariancesModelNoB'][ampName], dtype=np.float64).reshape(
438 (nSignalPoints, covMatrixSideFullCovFit, covMatrixSideFullCovFit))
439 calib.aMatrixNoB[ampName] = np.array(
440 dictionary[
'aMatrixNoB'][ampName],
441 dtype=np.float64).reshape((covMatrixSideFullCovFit, covMatrixSideFullCovFit))
442 calib.noiseMatrix[ampName] = np.array(
443 dictionary[
'noiseMatrix'][ampName],
444 dtype=np.float64).reshape((covMatrixSideFullCovFit, covMatrixSideFullCovFit))
445 calib.noiseMatrixNoB[ampName] = np.array(
446 dictionary[
'noiseMatrixNoB'][ampName],
447 dtype=np.float64).reshape((covMatrixSideFullCovFit, covMatrixSideFullCovFit))
450 calib.covariances[ampName] = np.array([], dtype=np.float64)
451 calib.covariancesModel[ampName] = np.array([], dtype=np.float64)
452 calib.covariancesSqrtWeights[ampName] = np.array([], dtype=np.float64)
453 calib.aMatrix[ampName] = np.array([], dtype=np.float64)
454 calib.bMatrix[ampName] = np.array([], dtype=np.float64)
455 calib.covariancesModelNoB[ampName] = np.array([], dtype=np.float64)
456 calib.aMatrixNoB[ampName] = np.array([], dtype=np.float64)
457 calib.noiseMatrix[ampName] = np.array([], dtype=np.float64)
458 calib.noiseMatrixNoB[ampName] = np.array([], dtype=np.float64)
460 calib.finalVars[ampName] = np.array(dictionary[
'finalVars'][ampName], dtype=np.float64)
461 calib.finalModelVars[ampName] = np.array(dictionary[
'finalModelVars'][ampName], dtype=np.float64)
462 calib.finalMeans[ampName] = np.array(dictionary[
'finalMeans'][ampName], dtype=np.float64)
463 calib.photoCharges[ampName] = np.array(dictionary[
'photoCharges'][ampName], dtype=np.float64)
465 for key, value
in dictionary[
'auxValues'].items():
466 calib.auxValues[key] = np.atleast_1d(np.array(value, dtype=np.float64))
468 calib.updateMetadata()
472 """Return a dictionary containing the calibration properties.
473 The dictionary should be able to be round-tripped through
479 Dictionary of properties.
485 outDict[
'metadata'] = metadata
487 def _dictOfArraysToDictOfLists(dictOfArrays):
489 for key, value
in dictOfArrays.items():
490 dictOfLists[key] = value.ravel().tolist()
498 outDict[
'badAmps'] = self.
badAmps
500 outDict[
'expIdMask'] = _dictOfArraysToDictOfLists(self.
expIdMask)
501 outDict[
'rawExpTimes'] = _dictOfArraysToDictOfLists(self.
rawExpTimes)
502 outDict[
'rawMeans'] = _dictOfArraysToDictOfLists(self.
rawMeans)
503 outDict[
'rawVars'] = _dictOfArraysToDictOfLists(self.
rawVars)
504 outDict[
'gain'] = self.
gain
505 outDict[
'gainErr'] = self.
gainErr
506 outDict[
'noise'] = self.
noise
511 outDict[
'ptcFitPars'] = _dictOfArraysToDictOfLists(self.
ptcFitPars)
512 outDict[
'ptcFitParsError'] = _dictOfArraysToDictOfLists(self.
ptcFitParsError)
515 outDict[
'covariances'] = _dictOfArraysToDictOfLists(self.
covariances)
516 outDict[
'covariancesModel'] = _dictOfArraysToDictOfLists(self.
covariancesModel)
518 outDict[
'aMatrix'] = _dictOfArraysToDictOfLists(self.
aMatrix)
519 outDict[
'bMatrix'] = _dictOfArraysToDictOfLists(self.
bMatrix)
520 outDict[
'noiseMatrix'] = _dictOfArraysToDictOfLists(self.
noiseMatrix)
522 outDict[
'aMatrixNoB'] = _dictOfArraysToDictOfLists(self.
aMatrixNoB)
523 outDict[
'noiseMatrixNoB'] = _dictOfArraysToDictOfLists(self.
noiseMatrixNoB)
524 outDict[
'finalVars'] = _dictOfArraysToDictOfLists(self.
finalVars)
525 outDict[
'finalModelVars'] = _dictOfArraysToDictOfLists(self.
finalModelVars)
526 outDict[
'finalMeans'] = _dictOfArraysToDictOfLists(self.
finalMeans)
527 outDict[
'photoCharges'] = _dictOfArraysToDictOfLists(self.
photoCharges)
528 outDict[
'auxValues'] = _dictOfArraysToDictOfLists(self.
auxValues)