tess-ephem 0.5.0

Installation

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. 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:

>>> 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:

>>> 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   997.240991

Additional physical parameters can be obtained by passing the verbose=True parameter:

>>> 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       0.1419

You can alternatively obtain the ephemeris during a specific sector by passing the sector parameter:

>>> 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  1802.802230

When 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]