DM-26453: Add sqrt(var) as weight to EXPAPPROXIMATION and POLYNOMIAL fit residual in ptc.py #47
Conversation
| meanSignalVector, | ||
| funcPolynomial) | ||
| (parsFit, parsFitErr, | ||
| reducedChiSquaredNonLinearityFit) = fitBootstrap(parsIniNonLinearity, |
There was a problem hiding this comment.
reducedChiSquaredNonLinearityFit is an almost comically long variable name, but I guess it's preexisting...
python/lsst/cp/pipe/utils.py
Outdated
| @@ -313,17 +316,23 @@ def fitLeastSq(initialParams, dataX, dataY, function): | |||
| List with errors for fitted parameters. | |||
|
|
|||
| reducedChiSqSingleLeastSquares : `float` | |||
| Unweighted reduced chi squared | |||
| Reduced chi squared | |||
There was a problem hiding this comment.
Whether it unweighted or not depends on if the optional weight parameter is actually passed, so maybe something like "Reduced chi squared, unweighted if weightsY is not provided."
python/lsst/cp/pipe/utils.py
Outdated
| @@ -374,15 +386,19 @@ def fitBootstrap(initialParams, dataX, dataY, function, confidenceSigma=1.): | |||
| reducedChiSqBootstrap : `float` | |||
| Reduced chi squared. | |||
There was a problem hiding this comment.
Maybe amend this too so it's in keeping with the other one about the optional weighting? Or make the other like this, I think that's actually fine too.
python/lsst/cp/pipe/utils.py
Outdated
| @@ -391,7 +407,7 @@ def errFunc(p, x, y): | |||
| randomDelta = np.random.normal(0., sigmaErrTotal, len(dataY)) | |||
| randomDataY = dataY + randomDelta | |||
| randomFit, _ = leastsq(errFunc, initialParams, | |||
| args=(dataX, randomDataY), full_output=0) | |||
| args=(dataX, randomDataY, 1./np.sqrt(randomDataY)), full_output=0) | |||
There was a problem hiding this comment.
Seems like randomDataY can be negative here - what happens then? I think you end up with a RuntimeWarning and a bunch of nans in the return array, and then I'm not sure what happens downstream...
No description provided.