| 790 | | |
| 791 | | |
| | 790 | Possible preliminary improvement: |
| | 791 | |
| | 792 | Sample summary of past LAP run stacks ~mhuber/lapstack20120510_inputtargetpsffwhm.log |
| | 793 | |
| | 794 | past/current ppStack.config for STACK_THREEPI: |
| | 795 | * PSF.INPUT.MAX 12.0 -- anything >12 pixels excluded (3") |
| | 796 | * PSF.INPUT.CLIP.NSIGMA NAN -- not used, but would redefine the INPUT.MAX to be clipped_mean + NSIGMA*clipped_stdev |
| | 797 | |
| | 798 | proposed: |
| | 799 | * PSF.INPUT.MAX 8.0 (or 2", MD deep stack is set for 7.5) |
| | 800 | * PSF.INPUT.CLIP.NSIGMA 2.0 (or 1.0?) |
| | 801 | |
| | 802 | Chris quickly looked at the FWHM of the exposures going into LAP stacks and order 90 percentile are <8 pixels. The NSIGMA is more difficult to quantify, so the general question is do we want to just help trim off more of the poorest inputs to keep the convolved target PSF more regular or be much more restrictive to improve the convolved target PSF at the cost of the number of inputs (maybe 10-30% at times for NSIGMA of 1). Any additional exclusion cuts include images that go into making the unconvolved stack as well. |
| | 803 | |
| | 804 | Adding pass cases for limits on the different minimum number of inputs would require some task modifications in LAP (and nightly science). |