https://pfspipe.ipmu.jp/jira This file is an XML representation of an issue en-us 8.3.4 803005 13-09-2019 https://pfspipe.ipmu.jp/jira/browse/PIPE2D-627 DRP 2-D Pipeline <p>From Jim's notes during discussion on Friday (August 29):</p> <p>"The notion is that we will have images with high S/N from some standard<br/> configuration which can be used as a template and for which we have<br/> PSFs.  When we are on the sky with some different configuration, we need<br/> to be able to measure the delta `FRD' to predict the PSFs in this<br/> configuration."</p> <p>This combines all of the work that I've done so far into a compact deliverable. In particular, the purpose of this ticket is to deliver code that takes in a base fiber configurations' PSFs and corresponding FRD values as well as the current fiber configurations' PSFs to output FRD values for all of the current fiber configurations.</p> PIPE2D-627

Characterize changes in FRD from near-focus or in-focus images

Story Normal In Progress Unresolved Brent Belland Brent Belland Mon, 31 Aug 2020 23:09:05 +0000 Fri, 13 Jan 2023 01:31:34 +0000 0 1 <p>I worked on characterizing the maximum variation in PSF as a change in FRD with a linear combination of Zernike coefficients Z4-Z22. BasicFit.png displays the maximum 2D variation as a function of detector position, the corresponding best fit from a linear algebra least squares solution. (<a href="https://numpy.org/doc/stable/reference/generated/numpy.linalg.lstsq.html)" class="external-link" rel="nofollow">https://numpy.org/doc/stable/reference/generated/numpy.linalg.lstsq.html)</a> Unfortunately this fit does not describe the structure in much detail at all. This indicates that algorithms I develop should have data for each relevant position as inputs rather than deriving PSFs from wavefront alone.</p> Relates PIPE2D-628 PIPE2D-630 PIPE2D-629 PIPE2D-549 PIPE2D-574 Development Rank 0|zzst9o:zzr Sprint 2DDRP-2021 A