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Well done, this is good progress!
 

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Gautham's response to Stubbs comments, June 30 (extracted by Kewei from email)

Chris in his response suggests choosing stars with good signal in all passbands. This may not actually be possible (since astrophysics ensures that the blue stars won't have much signal in the red, while the red stars don't have much signal in blue, and the PS1 telescope and camera ensures that the brightest stars which will give you good signal for the blue stars in the red, will saturate for the blue stars in the blue).
You also don't want a strong cut based on errors, since closer stars are brighter, and so have smaller errors, and you might not probe how the population varies fully by only selecting these.
I'd guess long term, you'll want a cut based on colors, but you'll have to try several things.

What I'm suggesting is to do a test in the regular **Medium Deep Fields** before going to the NCP, because we have more data in the Medium deep fields (all the photpipe measurements + stable astrometry)

Comments on Stubbs suggested conditions (italicized)

1. 1. unambiguous matches from the object catalogs, i.e. no nearby companions (like within 20 arcsec or so)
      This is fine, but you can be more aggressive with the matching tolerance, since you already know these objects are stars, and the photpipe dumps are from the stacked images, and therefore are deeper. if the stars are isolated in the photpipe dcmps from the stacked images, they will be isolated in the unstacked images.
   2. high signal to noise ratio in r band, i.e. median uncertainties less than, say, 0.005 mag. 
      Yes - we'll have to plot light curves of the stars for a few CMF files over 2-3 nights and actually look and make sure your code is behaving here too.
   3. no evidence for temporal variability: reduced chi-squared of a fit to a straight line of order one. 
      Very hard to get because of astrophysics, and the dynamic range of the telescope - you can test how well you do from the stacks themselves, but you'll only really have 5 magnitudes of dynamic range to work with in the unstacked images, and "good signal" (high-significance detection - small errors - is going to be hard to get in all those passbands at once). Again, good reason to work with the MDS data that is better characterized than hit your head against the wall with the NCP data.
   4. good signal in all passbands (g,r,i,z,y).
      This is easy in the Medium Deep Fields, and we can even check these against existing data.
      This should be possible in the NCP as long as the PS1 astrometry is good and we can match up at least 20-30 image catalogs.
   5. good temporal coverage, like 20-30 data points per band (depends on how many images we actually have)
      Again, helpful to use MDS before NCP, because if it's not consistent with a galaxy in the dcmp catalogs, it can be safely treated as a star.
   6. PSF FWHM consistent with stars, not galaxies. But note the FWHM for stars varies from frame to frame due to changes in atmospheric turbulence
      I'd not impose this cut until later. Magnitude error cuts can give you very odd subsets of the full population.

Once you have a list of magnitudes, I've code that does robust 3-sigma clipping, which will nicely clean up the catalog.

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Data access on Odyssey:

1. Run JAuth.jar to get login key
2. ssh -Y into to odyssey.fas.harvard.edu, or herophysics.fas.harvard.edu, using the electronic key. 
3. run tcsh
4. source .myrcstubbs
5. data are at /n/panlfs/data/MIRROR/ps1-md/gpc1/
6. nightly science uses individually warped images, nightly stacks run on stacked frames
7. image types: wrp is warped. 
8. see available modules with "module avail"
9. load a module with "module load hpc/ds9-5.6"
10. photometry is in .cmf files, as FITS tables. 
11. in python: 
    1. import pyfits as p
    2. p.open('filename')
    3. print a[0].header
12. or, imhead on command line
13. a[1].data.AP_MAG for aperture magnitudes
14. PSF_RA and PSF_DEC are in the skycell files. 
15. make a scratch directory for data in /n/panlfs

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