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README doc for github - how to use this code
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jkrick committed Apr 1, 2020
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# How to use this code

0. Download the pmap_correct.pro code and associated pmap files from the SSC
website (they are too large to include with this github repository)
website (they are too large to include with this github repository) https://irachpp.spitzer.caltech.edu/page/contrib

1. Download your own data from the Spitzer archive. If you want to
use the same data and recreate the plot in Krick et al. 2020, the
download the 10 XO3 eclipse
observations. https://sha.ipac.caltech.edu/applications/Spitzer/SHA/#id=SearchByPosition&RequestClass=ServerRequest&shortDesc=Position%20Search&isBookmarkAble=true&isDrillDownRoot=true
observations.https://sha.ipac.caltech.edu/applications/Spitzer/SHA/

2. Do photometry on the data. To do this, we highly suggest you run
phot_exoplanet_csv.pro included here. If you choose to do the
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4. Further refinements:

a) Included here are two models which both are able to remove
- Included here are two models which both are able to remove
systematics (two .pkl files). They are different and require
different feature sets, but both can be accomodated with the csv
files included or generated by step 2 above. The code is currently
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and comment out the 9 feature line in the fifth code cell where is
says #choose feature set.

b) To tweak the fitting, look in the fourth code cell. Currently
- To tweak the fitting, look in the fourth code cell. Currently
the code only allows fitting of the eclipse depth and the out of
transit linear baselines. However, you can change that to fit any
other parameter you think is warranted. Also hard coded in are
ranges of the parameters allowed, and initial guesses at the
eclipse depth and argument of periastron which are specific to
XO3-b.

c) Plotting is really set up for 10 observations. If you have
- Plotting is really set up for 10 observations. If you have
more/less you will need to adjust those parameters.

d) Running the python code should take maybe a minute for all 10
- Running the python code should take maybe a minute for all 10
observations and plotting. Running the idl photometry code takes longer - and
will depend on how much data there is to be processed.

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