def make_observer_table(n_samples=5):
"""Generate table of observers.
TODO: use real observatory positions instead.
A small list of observers (lon, lat, altitude, time in various formats).
This list will be used as input for the horizontal coordinate conversion tests.
Columns:
- lon : longitude in deg
- lat : latitude in deg
- altitude : altitude in km
- time : UTC time string
- time_mjd : time in MJD scale
- time_tdb : time in TDB scale
"""
np.random.seed(12345)
# Sample uniformly on the unit sphere
lon = np.random.uniform(0., 360., n_samples)
lat = np.degrees(np.arcsin(np.random.uniform(-1., 1., n_samples)))
# Sample of heights (distances from the Earth's center) in km
height = np.array([6e3, 10e3], dtype='float64')
# Sample of UTC times
time = [
'1970-01-01', '1980-01-01', '1990-01-01', '2000-01-01', '2010-01-01'
]
# Some coordinate packages need time input on another scale
# We use astropy.time to do the conversion and store several times in the ascii file.
time_mjd = Time(time, scale='utc').mjd
time_mjd = time_mjd.astype('int') # these are actually ints, I checked.
time_tdb = Time(time, scale='utc').tdb.value
# For each longitude, create an observer at each height and time
# This is a cartesian product:
# http://docs.python.org/2/library/itertools.html#itertools.product
table = list(
itertools.product(zip(lon, lat), height, zip(time, time_mjd,
time_tdb)))
table = [(_[0][0], _[0][1], _[1], _[2][0], _[2][1], _[2][2])
for _ in table]
cols = 'lon lat height time time_mjd time_tdb'.split()
table = Table(rows=table, names=cols)
for cols in ['lon', 'lat', 'height']:
table[cols].format = utils.FLOAT_FORMAT_INPUT
return table
def make_observer_table(n_samples=5):
"""Generate table of observers.
TODO: use real observatory positions instead.
A small list of observers (lon, lat, altitude, time in various formats).
This list will be used as input for the horizontal coordinate conversion tests.
Columns:
- lon : longitude in deg
- lat : latitude in deg
- altitude : altitude in km
- time : UTC time string
- time_mjd : time in MJD scale
- time_tdb : time in TDB scale
"""
np.random.seed(12345)
# Sample uniformly on the unit sphere
lon = np.random.uniform(0., 360., n_samples)
lat = np.degrees(np.arcsin(np.random.uniform(-1., 1., n_samples)))
# Sample of heights (distances from the Earth's center) in km
height = np.array([6e3, 10e3], dtype='float64')
# Sample of UTC times
time = ['1970-01-01', '1980-01-01', '1990-01-01', '2000-01-01', '2010-01-01']
# Some coordinate packages need time input on another scale
# We use astropy.time to do the conversion and store several times in the ascii file.
time_mjd = Time(time, scale='utc').mjd
time_mjd = time_mjd.astype('int') # these are actually ints, I checked.
time_tdb = Time(time, scale='utc').tdb.value
# For each longitude, create an observer at each height and time
# This is a cartesian product:
# http://docs.python.org/2/library/itertools.html#itertools.product
table = list(itertools.product(zip(lon, lat), height, zip(time, time_mjd, time_tdb)))
table = [(_[0][0], _[0][1], _[1], _[2][0], _[2][1], _[2][2]) for _ in table]
cols = 'lon lat height time time_mjd time_tdb'.split()
table = Table(rows=table, names=cols)
for cols in ['lon', 'lat', 'height']:
table[cols].format = utils.FLOAT_FORMAT_INPUT
return table
