Details
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Type:
Story
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Status: Done
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Resolution: Done
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Fix Version/s: None
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Component/s: ip_diffim
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Labels:
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Story Points:8
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Epic Link:
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Sprint:AP F19-1, AP F19-4 (2H September), AP F19-5 (October), AP F19-6 (November)
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Team:Alert Production
Description
Yusra AlSayyad identified in the June '19 False Positive Sprint that the variances were wrong by 10-15% (
https://nbviewer.jupyter.org/github/yalsayyad/dm_notebooks/blob/master/examples/DiaSourceCensusCcdVisitNight-HSC-RC2.ipynb). This is likely due to pixel covariances introduced by coaddition and warping. This ticket is to investigate rescaling the variances appropriately with ScaleVariance.
I understood that this was primarily a correction for the template, an empirical workaround for the low variance introduced by coaddition. The template variance may (slightly) affect the image PSF matching itself.
Considering the variance propagation through image differencing, I think we have two issues:
DM-21702), so it may make sense to do empirical correction. I think we can consider a doDiffimVarianceScale option once the Gen3 image differencing has taken shape.I think we can return to this question once the Gen3 image differencing has taken shape.