tess-locator 0.5.0

Installation

python -m pip install tess-locator

Example use

Converting celestial coordinates to TESS pixel coordinates:

>>> from tess_locator import locate
>>> locate("Alpha Cen")
List of 3 coordinates
↳[TessCoord(sector=11, camera=2, ccd=2, column=1699.1, row=1860.3, time=None)
  TessCoord(sector=12, camera=2, ccd=1, column=359.9, row=1838.7, time=None)
  TessCoord(sector=38, camera=2, ccd=2, column=941.1, row=1953.7, time=None)]

Obtaining pixel coordinates for a specific time:

>>> locate("Alpha Cen", time="2019-04-28")
List of 1 coordinates
↳[TessCoord(sector=11, camera=2, ccd=2, column=1699.1, row=1860.3, time=2019-04-28 00:00:00)]

Obtaining pixel coordinates for a specific celestial coordinate:

>>> from astropy.coordinates import SkyCoord
>>> crd = SkyCoord(ra=60, dec=70, unit='deg')
>>> locate(crd)
List of 1 coordinates
↳[TessCoord(sector=19, camera=2, ccd=2, column=355.3, row=1045.9, time=None)]

You can access the properties of TessCoord objects using standard list and attribute syntax:

>>> crdlist = locate("Alpha Cen")
>>> crdlist[0].sector, crdlist[0].camera, crdlist[0].ccd, crdlist[0].column, crdlist[0].row
(11, 2, 2, 1699.0540739785683, 1860.2510951146114)

When you have obtained a TessCoord object, you can use it to obtain a list of the TESS Full Frame Images (FFIs) which covered the position:

>>> crdlist[0].list_images()
List of 1248 images
↳[TessImage("tess2019113062933-s0011-2-2-0143-s_ffic.fits")
  TessImage("tess2019113065933-s0011-2-2-0143-s_ffic.fits")
  TessImage("tess2019113072933-s0011-2-2-0143-s_ffic.fits")
  TessImage("tess2019113075933-s0011-2-2-0143-s_ffic.fits")
  ...
  TessImage("tess2019140065932-s0011-2-2-0143-s_ffic.fits")
  TessImage("tess2019140072932-s0011-2-2-0143-s_ffic.fits")
  TessImage("tess2019140075932-s0011-2-2-0143-s_ffic.fits")
  TessImage("tess2019140082932-s0011-2-2-0143-s_ffic.fits")]

Documentation

Please visit the tutorial.

Similar packages

• tess-point is the package being called behind the scenes. Compared to tess-point, we add a user-friendly API and the ability to specify the time, which is important for moving objects.

• astroquery.mast includes the excellent TesscutClass.get_sectors() method which queries a web API. This package provides an offline version of that service, and adds the ability to query by time.

• tess-waldo lets you visualize how a target moves over the detector across sectors. It queries the TessCut service to obtain this information. This package adds the ability to create such plots offline.