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- I can process data and produce plots now. Here are some light curves:
Thursday, 20 June
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- Plotted the color diagram for all the objects in stacked gpc1v3. The diagram gets too cluttered if I plot all the objects, so I limited it to points where the error bars are small (<0.002 mag).
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Stubbs comments, June 30 2013.
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Anyhow, I'm pretty sure the code is working, so I'm going to go ahead and look at the NCP data. Identifying a common set of stars from that data is probably going to be more difficult because we don't have stacked images, but my idea now is to look for a few "good" images taken in photometric conditions and identifies the stars from there. Will try this tomorrow.
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So I have been playing around with MDF data for a while more because the stacked data from photpipe produces a nice catalogue, and that trims down the amount of data I have churn through by a lot. Anyway I found the color residue (I used instrumental colors minus the colors calibrated using SLR) against g-r calibrated color. There does not seem to be much of a trend at all:
I limited the data to only points with small error bars, but still there's no trend:
So this seems to suggest that the error in color is not a function of stellar color? I will try this again with unstacked ipp data soon.
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Data access on Odyssey:
- Run JAuth.jar to get login key
- ssh -Y into to odyssey.fas.harvard.edu, or herophysics.fas.harvard.edu, using the electronic key.
- run tcsh
- source .myrcstubbs
- data are at /n/panlfs/data/MIRROR/ps1-md/gpc1/
- nightly science uses individually warped images, nightly stacks run on stacked frames
- image types: wrp is warped.
- see available modules with "module avail"
- load a module with "module load hpc/ds9-5.6"
- photometry is in .cmf files, as FITS tables.
- in python:
- import pyfits as p
- p.open('filename')
- print a[0].header
- or, imhead on command line
- a[1].data.AP_MAG for aperture magnitudes
- PSF_RA and PSF_DEC are in the skycell files.
- make a scratch directory for data in /n/panlfs
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