Author: Behrouz Safari
License: MIT

Analysis data of the International Earth Rotation and Reference Systems Service (IERS)

Install the latest version of iers from PyPI:

pip install iers 

Requirements are numpy and pandas and will be installed automatically if needed.

Let's get parameters for the Julian Date 2460556.5 and print the results.

from iers import EOP dc = EOP().get_eop(2460556.5) print(dc)

Output:

{'px': 0.211611, 'py': 0.44424, 'ut1_utc': 0.0531643, 'dx': 0.349, 'dy': 0.088} 

Currently, this package can retrieve Earth Orientation Parameters from four files. It should be indicated with kind argument of EOP class. The first kind, which is default, gets daily data from 1973-01-02 until a few month after current date. The second kind is daily data from 1962-01-01 until a few days before the current date. The third kind is from 1846 until now, but its is not daily. It is 0.1 year interval (from 1846 from 1889) and 0.05 year interval (from 1890 to now). The fourth kind is longterm historical table from 2000 B.C. until 2015.

You should create an instance of the EOP class by passing the kind of table you want to kind argument. Then you can get the table with 'table' attribute.

from iers import EOP eop = EOP(kind=1) print(eop.table)

Output:

 mjd px_A py_A ut1_utc_A ... py_B ut1_utc_B dx_B dy_B 0 41684.0 0.120733 0.136966 0.808418 ... 0.137 0.8075 -18.637 -3.667 1 41685.0 0.118980 0.135656 0.805616 ... 0.134 0.8044 -18.636 -3.571 2 41686.0 0.117227 0.134348 0.802790 ... 0.131 0.8012 -18.669 -3.621 3 41687.0 0.115473 0.133044 0.799873 ... 0.128 0.7981 -18.751 -3.769 4 41688.0 0.113717 0.131746 0.796814 ... 0.126 0.7949 -18.868 -3.868 ... ... ... ... ... ... ... ... ... ... 19236 60920.0 0.179201 0.355850 0.104524 ... NaN NaN NaN NaN 19237 60921.0 0.179305 0.355138 0.105691 ... NaN NaN NaN NaN 19238 60922.0 0.179391 0.354423 0.106704 ... NaN NaN NaN NaN 19239 60923.0 0.179458 0.353706 0.107474 ... NaN NaN NaN NaN 19240 60924.0 0.179507 0.352987 0.107948 ... NaN NaN NaN NaN [19241 rows x 11 columns] 

Let's use another kind:

from iers import EOP eop = EOP(kind=2) print(eop.table)

Output:

 mjd px py ut1_utc lod dx dy 0 37665.0 -0.012700 0.213000 0.032634 0.001723 0.000000 0.000000 1 37666.0 -0.015900 0.214100 0.032055 0.001669 0.000000 0.000000 2 37667.0 -0.019000 0.215200 0.031553 0.001582 0.000000 0.000000 3 37668.0 -0.021999 0.216301 0.031144 0.001496 0.000000 0.000000 4 37669.0 -0.024799 0.217301 0.030815 0.001416 0.000000 0.000000 ... ... ... ... ... ... ... ... 22856 60521.0 0.157404 0.478195 0.023001 -0.000948 0.000321 -0.000074 22857 60522.0 0.159281 0.477650 0.024048 -0.001134 0.000357 -0.000077 22858 60523.0 0.161188 0.477331 0.025258 -0.001283 0.000402 -0.000092 22859 60524.0 0.163634 0.476656 0.026573 -0.001325 0.000448 -0.000106 22860 60525.0 0.166545 0.476250 0.027893 -0.001291 0.000413 -0.000105 

You can get the available parameters for a desired moment by passing the time as datetime or Julian Date or string to the .get_eop() method. If the kind is 1, it will use bulletin B if there is available data, otherwise uses bulletin A. You can check which bulletin has been used for interpolation with bulletin attribute.

from iers import EOP eop = EOP(kind=1) dc = eop.get_eop('2024-05-02 21:37:50') print(dc) print('Bulletin used:', eop.bulletin)

Output:

{'px': 0.0069811804398159285, 'py': 0.40801708148148286, 'ut1_utc': -0.01803119438657428, 'dx': 0.2808885416666599, 'dy': -0.16251909722223354} Bulletin used: B 

The files will be downloaded automatically and saved in Documents folder of user, so the next time you do not need to download the file again. Any file that is older than 7 days, will be downloaded automatically. By the way, if you want newer versions of a file, you can use the .download() method to download it again.

from iers import EOP eop = EOP(kind=1) eop.download()

To get leap seconds for a given time, pass the time as datetime or Julian Date or string to the leap_seconds function.

from iers import leap_seconds r = leap_seconds('2012-01-15 15:40:33') print(r)

Output:

34 

See more at https://behrouzz.github.io/astrodatascience/