[PIPE2D-627] Characterize changes in FRD from near-focus or in-focus images Created: 01/Sep/20 Updated: 13/Jan/23 |
|
| Status: | In Progress |
| Project: | DRP 2-D Pipeline |
| Component/s: | None |
| Affects Version/s: | None |
| Fix Version/s: | None |
| Type: | Story | Priority: | Normal |
| Reporter: | Brent Belland | Assignee: | Brent Belland |
| Resolution: | Unresolved | Votes: | 0 |
| Labels: | None | ||
| Remaining Estimate: | Not Specified | ||
| Time Spent: | Not Specified | ||
| Original Estimate: | Not Specified | ||
| Attachments: |
|
||||||||||||||||||||||||
| Issue Links: |
|
||||||||||||||||||||||||
| Sprint: | 2DDRP-2021 A | ||||||||||||||||||||||||
| Description |
|
From Jim's notes during discussion on Friday (August 29): "The notion is that we will have images with high S/N from some standard 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. |
| Comments |
| Comment by Brent Belland [ 15/Sep/20 ] |
|
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. (https://numpy.org/doc/stable/reference/generated/numpy.linalg.lstsq.html) 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. |