PNe statistics v 5

PNe statistics, part 5

We are still attempting the same general idea as before, but now looking at light distributions around PNe vs. not around them. As before, we are breaking the image up into small square regions and addressing the data in each of them.

NEW THING: Regions are now selected according to this method:
-find the distance between every PN pair
-for those pairs that can fit in the same box (width specified by 2*range + 1), place a box halfway between them
-do NOT eliminate any boxes just because they overlap

To select our regions we used three methods:
1) (magenta) pick each region so that there are 2 or more PNe in it
2) (red) center each region on a PN, so that there are as many regions as PNe
3) (green) center each region randomly in the image, but only select as many regions as there are PNe, for consistency
4) (blue) select each region randomly but make sure that it contains exactly ZERO (0) PNe

These three methods are applied on the masked and unmasked images (side by side) with ranges (related to size of region) of 20, 25, 30, 35, 40.

For each field (masked or unmasked), the median of each method was also determined and is shown on the graph as "med=##"

The masked images are masked with our best mask, down to u = 25, as shown on this earlier page.

These medians are collected and plotted as a function of range, shown at the bottom of this page.

This was performed on 3.fits, 4.fits, and 7.fits, using PNe catalog data from Feldmeier.

Old difference: now, with the PNe >= 2 histogram, the curious humps in the graphs are made clearer with images that are also included showing where each histogram randomly chose its PNe >= 2 regions. These follow each pair of histograms

code: PNe4.sm PNe4 <-- goes through and does computations, preps data for graphing, and stores median values in different file for each field/range and calls PNe4g, see next line
          PNe4.sm PNe4g <-- goes through and generates all the .ps files as shown converted to .gif below
          PNe4.sm PNe4m <-- takes data file meds.dat and generates bottom two figures
          cat.sm      cat       <-- takes all the .med files generated by PNe4 and makes them into a big collection that PNe4m can read and graph Deltas
          Feld.sm FeldOld <-- converts .2found.dat files to .reg files for displaying as region files in ds9 and getting the .jpgs that show regions and PNe together

This bunch of files has gotten ridiculously long, so here's a handy index to get to where you might (or might not) want to go:
3.fits      4.fits      7.fits             Plots of Delta as functions of Range
    R10      R10      R10               Delta(2,0) = PNe(2) - PNe(0)
    R15      R15      R15                  3.fits - unmasked
    R20      R20      R20                  3m.fits - masked
    R25      R25      R25                  4.fits -   unmasked
    R30      R30      R30                  4m.fits - masked
    R35      R35      R35                  7.fits -   unmasked
    R40      R40      R40                  7m.fits - masked
    R45      R45      R45               Delta(1,0) = PNe(2) - PNe(1)
    R50      R50      R50                  3.fits -   unmasked
    R55      R55    R55                  3m.fits - masked
    R60      R60      R60                  4.fits -   unmasked
    R65      R65      R65                  4m.fits - masked
    R70      R70      R70                  7.fits -   unmasked
    R75      R75      R75                  7m.fits - masked
    R80      R80      R80
    R85      R85      R85
test line:
Deltas

3.fits