Metadata-Version: 2.1
Name: tess-ephem
Version: 0.2.0
Summary: Where are Solar System objects located in TESS FFI data?
Home-page: https://github.com/SSDataLab/tess-ephem
License: MIT
Keywords: NASA, TESS, Astronomy
Author: Geert Barentsen
Author-email: hello@geert.io
Requires-Python: >=3.7,<4.0
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Astronomy
Requires-Dist: astropy (>=4.1,<5.0)
Requires-Dist: astroquery (>=0.4.1,<0.5.0)
Requires-Dist: numpy (>=1.19.4,<2.0.0)
Requires-Dist: pandas (>=1.1.4,<2.0.0)
Requires-Dist: scipy (>=1.5.4,<2.0.0)
Requires-Dist: tess-locator (>=0.3.0)
Project-URL: Repository, https://github.com/SSDataLab/tess-ephem
Description-Content-Type: text/x-rst

tess-ephem
==========


**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.

Installation
------------

.. code-block:: bash

    python -m pip install tess-ephem


Example use
-----------

tess-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.
For example:

.. code-block:: python

    >>> from tess_ephem import ephem
    >>> ephem("Sedna")
                             sector  camera  ccd       column          row
    time
    2018-11-16 00:00:00.000       5       1    4  1543.312296  1102.821559
    2018-11-17 00:00:00.000       5       1    4  1545.160910  1102.880825
    2018-11-18 00:00:00.000       5       1    4  1547.011351  1102.934375
    ...
    2018-12-09 00:00:00.000       5       1    4  1584.585407  1102.239292
    2018-12-10 00:00:00.000       5       1    4  1586.245261  1102.132304
    2018-12-11 00:00:00.000       5       1    4  1587.906380  1102.012091


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  1553.887838  1103.048431


Additional 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  1553.887838  1103.048431         0.074054  57.05786  7.63721  20.612     84.942885     83.975689       0.1419

