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  1. Data Management
  2. DM-240

meas_base plugins for CModel magnitudes

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      Create meas_base Plugins for single-frame and forced measurement that uses the model-fitting primitives in meas_multifit to implement SDSS-style CModel magnitudes, in which we fit an exp and dev model separately and then fit the linear combination with ellipse parameters held fixed.

      An old-style plugin has already been implemented on the HSC fork, and should be used as a guide; this issue involves adapting that implementation to meas_base and potentially cleaning it up a bit. Note that the HSC implementation cannot be transferred directly to the LSST side because the meas_algorithms APIs are slightly different on the two forks.

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            jbosch Jim Bosch created issue -
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            Assignee Yusra AlSayyad [ yusra ] Jim Bosch [ jbosch ]
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            jbosch Jim Bosch added a comment -

            Sending this to Bob Armstrong for review. He doesn't have a JIRA account yet, but he does have a GitHub account, and we'll do the review there anyway, and I'll paste a summary back here when we're done.

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            jbosch Jim Bosch added a comment - Sending this to Bob Armstrong for review. He doesn't have a JIRA account yet, but he does have a GitHub account, and we'll do the review there anyway, and I'll paste a summary back here when we're done.
            jbosch Jim Bosch made changes -
            Status In Progress [ 3 ] In Review [ 10004 ]
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            jbosch Jim Bosch added a comment -

            Review completed on GitHub. Most comments were just requests for clarification.

            Biggest outcome was noticing an incorrect factor (2 instead of pi) in SoftenedLinearPrior normalization, which spurred an improvement in the unit test coverage for that class, uncovering a larger bug in prior evaluation. Neither of these problems would have affected the code as it is configured by default, but would have affected mode unusual configurations of the prior.

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            jbosch Jim Bosch added a comment - Review completed on GitHub. Most comments were just requests for clarification. Biggest outcome was noticing an incorrect factor (2 instead of pi) in SoftenedLinearPrior normalization, which spurred an improvement in the unit test coverage for that class, uncovering a larger bug in prior evaluation. Neither of these problems would have affected the code as it is configured by default, but would have affected mode unusual configurations of the prior.
            jbosch Jim Bosch made changes -
            Status In Review [ 10004 ] Review Complete [ 10101 ]
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            Resolution Done [ 10000 ]
            Status Review Complete [ 10101 ] Done [ 10002 ]
            ktl Kian-Tat Lim made changes -
            Component/s meas_modelfit [ 11411 ]
            Component/s meas_multifit [ 10739 ]
            swinbank John Swinbank made changes -
            Team Princeton [ 10301 ]

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              jbosch Jim Bosch
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              jbosch Jim Bosch
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              Jim Bosch
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