Overview

This repo contains some tools for understanding what TESS is looking at.

Useful pull requests are gratefully accepted. The focal plane geometry model is not 100% accurate, but it's pretty good.

USAGE

To see if some coordinates are observed:

from astropy.coordinates import SkyCoord
from tessmaps import get_time_on_silicon as gts
coords = SkyCoord([124.532, -68.313], [42.42, -42.42], unit='deg')
df = gts.get_time_on_silicon(coords)

where df is a pandas DataFrame that tells you in which sector the observation occurs, using the pointings given by MIT's TESS Science Office and the focal plane geometry used by Sullivan et al (2015) and Bouma et al (2017).

A separate module accepts sector numbers and coordinates, and makes sky maps with optional annotations of objects on silicon:

# see `tests/check_rectmaps.py` for a worked example
tm.make_rect_map(sector_number, coords, names=names,
                 annotate_bools=is_transiting, title=title,
                 bkgnd_cmap='Blues', savname=savname, savdir=savdir)

The known exoplanets in the first science sector look like this.

The clusters observed in the first science sector look like this.

You can also make all-sky maps, like this.

Take a look at /results/ to see similar plots for the southern hemisphere's survey.

Finally, there's a module that converts this information to text and csv files:

tm.make_sector_list(sector_number, coords, names=names, savname=savname)

the csv files contain TIC IDs, sector properties, coordinates, and optionally the passed names.

You can also use the shell scripts to regenerate everything. (See the docstrings).

INSTALL

Currently the only install is from source. To seemlessly install the virtual environment, use anaconda:

cd $SOME_DIRECTORY
git clone https://github.com/lgbouma/tessmaps
cd tessmaps
conda env create -f environment.yml -n tmaps
source activate tmaps
(tmaps) python setup.py install

A nasaexoplanetarchive query to crossmatch positions to planet names currently (2018/08/06) depends on a bleeding-edge astroquery build. To make that:

cd $SOME_DIRECTORY
git clone https://github.com/astropy/astroquery
cd astroquery
source activate tmaps
(tmaps) python setup.py install

Then you should be ready.

IF YOU WRITE A PAPER WITH THESE TOOLS, PLEASE CITE

• the TESS mission
• The TIC7.1 paper by Stassun et al for coordinates and properties of TIC objects
• Sullivan+ 2015 and Bouma+ 2017 for the focal glame geometry model
• lists appropriate to whatever you overplot:
  • if you use the knownplanets list, cite Stephen Kane
  • if you plot out the Kharchenko+ 2013 catalog clusters, cite them
• astropy
• astroquery

TODO

• implement tm.make_sector_list
• consider making pip installable