def morrison_and_stephenson_2004_table():
"""Table of smoothed Delta T values from Morrison and Stephenson, 2004."""
import pandas as pd
f = load('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 morrison_and_stephenson_2004_table():
"""Table of smoothed Delta T values from Morrison and Stephenson, 2004."""
import pandas as pd
f = load('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 usno_monthly_delta_t():
import pandas as pd
f = load('http://maia.usno.navy.mil/ser7/deltat.data')
return pd.read_table(f,
sep=r' +',
engine='python',
names=['year', 'month', 'day', 'delta_t'])
def usno_predicted_delta_t():
import pandas as pd
f = load('http://maia.usno.navy.mil/ser7/deltat.preds')
df = pd.read_table(f, sep=r' +', engine='python')
return pd.DataFrame({
'year': df['YEAR'],
'delta_t': df['TT-UT PREDICTION']
})
def usno_historic_delta_t():
import pandas as pd
f = load('http://maia.usno.navy.mil/ser7/historic_deltat.data')
df = pd.read_table(f, sep=r' +', engine='python', skiprows=[1])
return pd.DataFrame({'year': df['Year'], 'delta_t': df['TDT-UT1']})
def usno_predicted_delta_t():
import pandas as pd
f = load('http://maia.usno.navy.mil/ser7/deltat.preds')
df = pd.read_table(f, sep=r' +', engine='python')
return pd.DataFrame({'year': df['YEAR'],
'delta_t': df['TT-UT PREDICTION']})
def usno_monthly_delta_t():
import pandas as pd
f = load('http://maia.usno.navy.mil/ser7/deltat.data')
return pd.read_table(f, sep=r' +', engine='python',
names=['year', 'month', 'day', 'delta_t'])
def usno_historic_delta_t():
import pandas as pd
f = load('http://maia.usno.navy.mil/ser7/historic_deltat.data')
df = pd.read_table(f, sep=r' +', engine='python', skiprows=[1])
return pd.DataFrame({'year': df['Year'], 'delta_t': df['TDT-UT1']})
def load(match_function):
"""Yield the Hipparcos stars for which `match_function(line)` is true."""
with iokit.load(url) as f:
for line in gzip.GzipFile(fileobj=f):
if match_function(line):
yield parse(line)
