Nutze Skyfield fuer praezisere Daemmerungsberechnung

public/py/vendor/skyfield/data/earth_orientation.py

@@ -0,0 +1,46 @@
+# -*- coding: utf-8 -*-
+"""Routines to download Earth orientation data."""
+
+import numpy as np
+import os
+from skyfield.api import load
+from skyfield.timelib import julian_date
+
+def morrison_and_stephenson_2004_table():
+    """Table of smoothed Delta T values from Morrison and Stephenson, 2004."""
+    import pandas as pd
+    f = load.open('http://eclipse.gsfc.nasa.gov/SEcat5/deltat.html')
+    tables = pd.read_html(f.read())
+    df = tables[0]
+    return pd.DataFrame({'year': df[0], 'delta_t': df[1]})
+
+def parse_S15_table(f):
+    """Parse polynomial coefficients from Table S15.
+
+    The table is available at the website of Her Majesty's Nautical
+    Almanac Office, from the paper “Measurement of the Earth's Rotation:
+    720 BC to AD 2015” by L.V. Morrison, F.R. Stephenson, C.Y. Hohenkerk
+    and M. Zawilski 2021.
+
+    """
+    # http://astro.ukho.gov.uk/nao/lvm/Table-S15.2020.txt
+    content = f.read()
+    banner = b'- ' * 36 + b'-\n'
+    sections = content.split(banner)
+    names = sections[1].splitlines()[-1].decode('utf-8').split()
+    table = np.loadtxt(sections[2].splitlines())
+    return names, table.T
+
+def main():
+    thisdir = os.path.dirname(__file__)
+
+    df = morrison_and_stephenson_2004_table()
+    year = df.year.values
+    jd = julian_date(year, 1, 1)
+    delta_t = df.delta_t.values
+    array = np.array((jd, delta_t))
+    np.save(os.path.join(thisdir, 'morrison_stephenson_deltat.npy'),
+            array)
+
+if __name__ == '__main__':
+    main()