Where are Solar System objects located in TESS FFI data?
|pypi| |pytest| |black| |flake8| |mypy|
.. |pypi| image:: https://img.shields.io/pypi/v/tess-ephem :target: https://pypi.python.org/pypi/tess-ephem .. |pytest| image:: https://github.com/SSDataLab/tess-ephem/workflows/pytest/badge.svg .. |black| image:: https://github.com/SSDataLab/tess-ephem/workflows/black/badge.svg .. |flake8| image:: https://github.com/SSDataLab/tess-ephem/workflows/flake8/badge.svg .. |mypy| image:: https://github.com/SSDataLab/tess-ephem/workflows/mypy/badge.svg
tess-ephem is a user-friendly package which enables users to compute the positions of Solar System objects -- asteroids, comets, and planets --
in the data archive of NASA's TESS Space Telescope.
.. code-block:: bash
python -m pip install tess-ephemtess-ephem allows you to search the entire archive of TESS FFI's for the presence of a known minor planet, and obtain the result as a Pandas DataFrame. The output pixel coordinates (column and row) follow the TESS convention, with (1,1) being the middle of the pixel in the lower left corner of the FFI. For example:
.. code-block:: python
>>> from tess_ephem import ephem
>>> ephem("Sedna")
sector camera ccd column row
time
2458437.5 5 1 4 1540.328759 1102.742761
2458438.5 5 1 4 1542.057935 1102.906116
2458439.5 5 1 4 1543.919678 1102.977150
2458440.5 5 1 4 1545.806011 1103.011147
2458441.5 5 1 4 1547.691635 1103.029184
... ... ... ... ... ...
2460254.5 71 2 4 1984.472509 1004.531966
2460255.5 71 2 4 1984.704905 1002.716266
2460256.5 71 2 4 1984.934016 1000.892089
2460257.5 71 2 4 1985.160431 999.062904
2460258.5 71 2 4 1985.376804 997.240991
[78 rows x 5 columns]You can also obtain the ephemeris for one or more specific times
by passing the time parameter:
.. code-block:: python
>>> ephem("Sedna", time="2018-11-21 17:35:00")
sector camera ccd column row
time
2018-11-21 17:35:00.000 5 1 4 1552.813087 1103.033716
>>> from astropy.time import Time
>>> ephem("Sedna", time=Time([2458441.5,2460258.5], format='jd'))
sector camera ccd column row
time
2458441.5 5 1 4 1547.691635 1103.029184
2460258.5 71 2 4 1985.376804 997.240991Additional physical parameters can be obtained by passing the verbose=True parameter:
.. code-block:: python
>>> ephem("Sedna", time="2018-11-21 17:35:00", verbose=True)
sector camera ccd column row pixels_per_hour ra dec vmag sun_distance obs_distance phase_angle
time
2018-11-21 17:35:00.000 5 1 4 1552.813087 1103.033716 0.074053 57.06362 7.63836 20.812 84.943049 83.975854 0.1419You can alternatively obtain the ephemeris during a specific sector by passing
the sector parameter:
.. code-block:: python
>>> ephem("Sedna", sector=70)
sector camera ccd column row
time
2460208.5 70 4 2 1965.819900 1827.440280
2460209.5 70 4 2 1966.122988 1826.880450
2460210.5 70 4 2 1966.445615 1826.219237
2460211.5 70 4 2 1966.792833 1825.480366
2460212.5 70 4 2 1967.156084 1824.685065
2460213.5 70 4 2 1967.530374 1823.844978
2460214.5 70 4 2 1967.912846 1822.964230
2460215.5 70 4 2 1968.300642 1822.046948
2460216.5 70 4 2 1968.693056 1821.098583
2460217.5 70 4 2 1969.085076 1820.121939
2460218.5 70 4 2 1969.477787 1819.122100
2460219.5 70 4 2 1969.865471 1818.107325
2460220.5 70 4 2 1970.236706 1817.102989
2460221.5 70 4 2 1970.537507 1816.171600
2460222.5 70 4 2 1970.786337 1815.215528
2460223.5 70 4 2 1971.057940 1814.164426
2460224.5 70 4 2 1971.352361 1813.044830
2460225.5 70 4 2 1971.660316 1811.874587
2460226.5 70 4 2 1971.976449 1810.663652
2460227.5 70 4 2 1972.300053 1809.417480
2460228.5 70 4 2 1972.626477 1808.140569
2460229.5 70 4 2 1972.954292 1806.834984
2460230.5 70 4 2 1973.282790 1805.506180
2460231.5 70 4 2 1973.609473 1804.159986
2460232.5 70 4 2 1973.931842 1802.802230When passing the sector parameter, the time_step is by default 1 day.
This can be changed as follows:
>>> ephem("Sedna", sector=70, time_step=0.1)
sector camera ccd column row
time
2460207.6 70 4 2 1965.495431 1827.937212
2460207.7 70 4 2 1965.535648 1827.878206
2460207.8 70 4 2 1965.575019 1827.820108
2460207.9 70 4 2 1965.613392 1827.763020
2460208.0 70 4 2 1965.650616 1827.707041
... ... ... ... ... ...
2460233.0 70 4 2 1974.086940 1802.125478
2460233.1 70 4 2 1974.117634 1801.990490
2460233.2 70 4 2 1974.148118 1801.855903
2460233.3 70 4 2 1974.178192 1801.721961
2460233.4 70 4 2 1974.207660 1801.588906
[259 rows x 5 columns]