# CModel priors are weighted incorrectly relative to likelihood

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## Details

• Type: Bug
• Status: Done
• Priority: Undefined
• Resolution: Done
• Fix Version/s: None
• Component/s:
• Labels:
• Templates:
• Story Points:
2
• Sprint:
DRP S17-4
• Team:
Data Release Production

## Description

When per-pixel variances are turned off, CModel likelihoods are computed without using the variance at all. This would not matter in a pure likelihood fit, but it means the prior and likelihood are not given the appropriate relative weights - and the relative weighting is not even consistent; it depends on the noise level of the image.

Since the typical effect of this is to make the prior much more informative, there is some danger that fixing this bug will cause other problems due to poorly-constrained fits. To avoid this, I'll add a configuration option to tune the relative weighting of the prior via a constant (which we could set to the typical variance level of the images to get behavior like what we have now without the inconsistency).

## Attachments

1. meanVariance.py
3 kB
2. psf_vs_cmodel.png
409 kB

## People

• Assignee:
Jim Bosch
Reporter:
Jim Bosch
Reviewers:
Paul Price
Watchers:
Jim Bosch, Paul Price