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  1. Data Management
  2. DM-15254

Option to normalize warps by Jointcal's PhotoCalib

    Details

    • Type: Story
    • Status: Done
    • Resolution: Done
    • Fix Version/s: None
    • Component/s: None

      Description

      MakeCoaddTempExp delegates zeropoint normalization to the ScaleZeroPointTask. Default is a very simple one constant per calexp. The doApplyUberCal config option will also call meas_mosaic's applyMosaicResults on the exposure to further normalize the image.

      Now that Jointcal's photometric aspect works, it'd be great to get an option to apply jointcal's photcalib objects to the calexps.  Ideally imho, meas-mosaic and jointcal would implement tasks that makeCoaddTempExp could use as retargetable subtasks, but since no one wants to touch meas_mosaic, that's probably not happening.

      Some kind method provided by PhotoCalib or function elsewhere to scale an exposure would be sufficient. 

       

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            yusra Yusra AlSayyad added a comment -

            Yep,  will take it for a spin now. 

            Show
            yusra Yusra AlSayyad added a comment - Yep,  will take it for a spin now. 
            Hide
            yusra Yusra AlSayyad added a comment - - edited

            I confirm it is sufficient. Some things I noticed:

            When I read in files from: '/datasets/hsc/repo/rerun/DM-13666/WIDE' computeImage takes 2 minutes and is of type

            PhotoCalib(FluxFit, order=7 on Box2I(Point2I(0, 0), Extent2I(2048, 4176)) with mean: 1.8912e-12 err: 1.52975e-13)

            When using /datasets/hsc/repo/rerun/RC/w_2018_36/DM-15603-jointcal computeImage takes 2.5 seconds and is of type:
            PhotoCalib(TransformBoundedField on Box2I(Point2I(0, 0), Extent2I(2048, 4176)) with mean: -3.58925e-15 err: 2.8126e-17)}}

            Was DM-13666/WIDE run with an older version? different configuration?

             

            Also, for fun here are three background images (128X128 binned images, taking the median of pixels in each bin without detection or bad mask bits set)

            Middle is the original unscaled background image. 

            Left is the results of jointcal's photocalib.computeImage(), right is meas_mosaic's  applyMosaicResults(dataRef, calexp=exp); imageScaler.scaleMaskedImage(exp.maskedImage)

            Show
            yusra Yusra AlSayyad added a comment - - edited I confirm it is sufficient. Some things I noticed: When I read in files from:  '/datasets/hsc/repo/rerun/ DM-13666 /WIDE' computeImage takes 2 minutes and is of type PhotoCalib(FluxFit, order=7 on Box2I(Point2I(0, 0), Extent2I(2048, 4176)) with mean: 1.8912e-12 err: 1.52975e-13) When using /datasets/hsc/repo/rerun/RC/w_2018_36/ DM-15603 -jointcal computeImage takes 2.5 seconds and is of type: PhotoCalib(TransformBoundedField on Box2I(Point2I(0, 0), Extent2I(2048, 4176)) with mean: -3.58925e-15 err: 2.8126e-17)}} Was DM-13666 /WIDE run with an older version? different configuration?   — Also, for fun here are three background images (128X128 binned images, taking the median of pixels in each bin without detection or bad mask bits set) Middle is the original unscaled background image.  Left is the results of jointcal's photocalib.computeImage(), right is meas_mosaic's   applyMosaicResults(dataRef, calexp=exp); imageScaler.scaleMaskedImage(exp.maskedImage)
            Hide
            Parejkoj John Parejko added a comment -

            FluxFit is the meas_mosaic output.

            I'm not sure what to make of those backgrounds: do we have any way to know which of the jointcal or meas_mosaic ones is "better"?

            Show
            Parejkoj John Parejko added a comment - FluxFit is the meas_mosaic output. I'm not sure what to make of those backgrounds: do we have any way to know which of the jointcal or meas_mosaic ones is "better"?
            Hide
            yusra Yusra AlSayyad added a comment -

            I don't know

            Show
            yusra Yusra AlSayyad added a comment - I don't know
            Hide
            Parejkoj John Parejko added a comment -

            Thanks for the review, Yusra AlSayyad and Krzysztof Findeisen.

            Merged and done.

            Yusra AlSayyad: do you have everything you need to use this output in coadds now?

            Show
            Parejkoj John Parejko added a comment - Thanks for the review, Yusra AlSayyad and Krzysztof Findeisen . Merged and done. Yusra AlSayyad : do you have everything you need to use this output in coadds now?

              People

              • Assignee:
                Parejkoj John Parejko
                Reporter:
                yusra Yusra AlSayyad
                Reviewers:
                Yusra AlSayyad
                Watchers:
                Jim Bosch, John Parejko, Krzysztof Findeisen, Yusra AlSayyad
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                  Updated:
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