TDSS Repeat Quasar Spectroscopy (RQS) Vi

TDSS Vi creates one (1) plot for each of the variable stars in the program sample. These plots are designed to help summarize as much information about each star as possible, and to aid in classification. Each plot currently contains:

1. CSS Light curve (in raw form if logProb_Per > -10.0, and in folded phase if logProb_Per <= -10.0)
2. Some general population plot based on if the star is periodic or not:
   • Plot from Palaversa et al. (2013) if periodic. This is log10(P/days) on the x-axis and log10(Amp/mag) on the y-axis with light curve skewness as the colorbar.
   • Generic heat map of a95 vs log10($\chi^2$) if star is non-periodic.
3. Color-Magnitude diagram based on SDSS colors and Gaia DR2 distances.
4. SDSS spectrum with properties printed (this includes information from PyHammer)

These plots are created using the Vi code written by Ben Roulston (BU/SAO). In addition to these plots, the Vi code also creates a .csv file that contains information about the light curves for each star from the Vartools program. The Vartools program also saves the phase folded light curve for EVERY star as well (even though it is not plotted or used for every star).

The main functions of the program (which call Vartools and creates the figures) are in the VarStar_Vi_plot_functions.py file. This notebook shows how this Vi program should be run. In order to run this Vi program, the following items are needed and MUST be downloaded/created/known before any figures can be made.

1. CSS light curves for every star.
2. File connecting the CSS_ID to the RA and DEC for each star. (A simple .csv that is just `[ra, dec, css_id] works fine and is what is used here.
3. SDSS spectrum for every star.
   • If the star has been in a public data release, then the SDSS .fits format is fine (i.e. spec-MJD-PLATE-FIBERID.fits)
   • If the star has NOT been in a public data release (i.e. is proprietary) then you need to download the spPlate-PLATE-MJD.fits for each. Then pull out the spectra and save them in ASCII format.
4. Know where all data is stored and make sure the directories in the code are up to date (this is VERY important).
5. Property table which links ALL spALL data with Gaia DR2 data and CSS data.
6. Installation of the Vartools program for analyzing light curves.

Once all of this is ready, the Vi program can be run.

Vi uses the Vartools program, which was created by @joeldhartman and more information can be found here. The GitHub repo can also be found here