def date2dict_times(date):
day = Time(date, format='iso')
longitude = '78d57m53s'
latitude = '32d46m44s'
elevation = 4500 * u.m
location = EarthLocation.from_geodetic(longitude, latitude, elevation)
iaohanle = Observer(location=location,
name="IAO",
timezone='Asia/Kolkata',
description="GROWTH-India 70cm telescope")
sunset_iao = iaohanle.sun_set_time(day, which='next')
sunrise_iao = iaohanle.sun_rise_time(day, which='next')
twelve_twil_eve_iao = iaohanle.twilight_evening_nautical(day, which='next')
eighteen_twil_eve_iao = iaohanle.twilight_evening_astronomical(
day, which='next')
twelve_twil_morn_iao = iaohanle.twilight_morning_nautical(day,
which='next')
eighteen_twil_morn_iao = iaohanle.twilight_morning_astronomical(
day, which='next')
dict_times = OrderedDict()
dict_times['Sunset '] = time2utc_ist(sunset_iao)
dict_times['Sunrise '] = time2utc_ist(sunrise_iao)
dict_times['Twelve degree Evening Twilight '] = time2utc_ist(
twelve_twil_eve_iao)
dict_times['Eighteen degree Evening Twilight '] = time2utc_ist(
eighteen_twil_eve_iao)
dict_times['Twelve degree Morning Twilight '] = time2utc_ist(
twelve_twil_morn_iao)
dict_times['Eighteen degree Morning Twilight '] = time2utc_ist(
eighteen_twil_morn_iao)
return dict_times
def nautical_twilight(self,
date_obs,
site_longitude=30.335555,
site_latitude=36.824166,
site_elevation=2500,
site_name="tug",
time_zone="Europe/Istanbul",
which="next"):
# TUG's location info settings
tug = Observer(longitude=site_longitude * u.deg,
latitude=site_latitude * u.deg,
elevation=site_elevation * u.m,
name=site_name,
timezone=time_zone)
# convert date astropy date format
astropy_time = Time(date_obs)
# evening tw calculate
et = tug.twilight_evening_nautical(astropy_time, which=which)
# morning tw calculate
mt = tug.twilight_morning_nautical(astropy_time, which=which)
# localized time conversion
return (tug.astropy_time_to_datetime(mt),
tug.astropy_time_to_datetime(et))
def nautical_twilight(self, date_obs,
site_longitude=30.335555,
site_latitude=36.824166,
site_elevation=2500,
site_name="tug",
time_zone="Europe/Istanbul",
which="next"):
# TUG's location info settings
tug = Observer(longitude=site_longitude*u.deg,
latitude=site_latitude*u.deg,
elevation=site_elevation*u.m,
name=site_name,
timezone=time_zone)
# convert date astropy date format
astropy_time = Time(date_obs)
# evening tw calculate
et = tug.twilight_evening_nautical(astropy_time,
which=which)
# morning tw calculate
mt = tug.twilight_morning_nautical(astropy_time,
which=which)
# localized time conversion
return(tug.astropy_time_to_datetime(mt),
tug.astropy_time_to_datetime(et))
def get_twilights(start, end):
""" Determine sunrise and sunset times """
location = EarthLocation(
lat=+19.53602,
lon=-155.57608,
height=3400,
)
obs = Observer(location=location, name='VYSOS', timezone='US/Hawaii')
sunset = obs.sun_set_time(Time(start), which='next').datetime
sunrise = obs.sun_rise_time(Time(start), which='next').datetime
# Calculate and order twilights and set plotting alpha for each
twilights = [
(start, 'start', 0.0),
(sunset, 'sunset', 0.0),
(obs.twilight_evening_civil(Time(start),
which='next').datetime, 'ec', 0.1),
(obs.twilight_evening_nautical(Time(start),
which='next').datetime, 'en', 0.2),
(obs.twilight_evening_astronomical(Time(start),
which='next').datetime, 'ea', 0.3),
(obs.twilight_morning_astronomical(Time(start),
which='next').datetime, 'ma', 0.5),
(obs.twilight_morning_nautical(Time(start),
which='next').datetime, 'mn', 0.3),
(obs.twilight_morning_civil(Time(start),
which='next').datetime, 'mc', 0.2),
(sunrise, 'sunrise', 0.1),
]
twilights.sort(key=lambda x: x[0])
final = {
'sunset': 0.1,
'ec': 0.2,
'en': 0.3,
'ea': 0.5,
'ma': 0.3,
'mn': 0.2,
'mc': 0.1,
'sunrise': 0.0
}
twilights.append((end, 'end', final[twilights[-1][1]]))
return twilights
def __init__(self, observatory, observations):
self.observatory = observatory
self.observations = observations
#assign unique ids to observations
for observation in self.observations:
observation.id = self.last_id
self.last_id += 1
#uncomment to download the latest for astroplan
logger.debug('Updating Astroplan IERS Bulletin A...')
download_IERS_A()
#get *nearest* sunset and *next* sunrise times
#still not a big fan of this!
observatory_location_obsplan = Observer(longitude=self.observatory.longitude*u.deg, latitude=self.observatory.latitude*u.deg, elevation=self.observatory.altitude*u.m, name=self.observatory.code, timezone=self.observatory.timezone)
self.sunset_time = observatory_location_obsplan.twilight_evening_nautical(Time.now(), which="nearest")
self.sunrise_time = observatory_location_obsplan.twilight_morning_nautical(Time.now(), which="next")
logger.debug('The nearest sunset is %s. The next sunrise is %s.'%(self.sunset_time.iso, self.sunrise_time.iso))
def get_twilights(self, config=None):
""" Determine sunrise and sunset times """
print(' Determining sunrise, sunset, and twilight times')
if config is None:
from pocs.utils.config import load_config as pocs_config
config = pocs_config()['location']
location = EarthLocation(
lat=config['latitude'],
lon=config['longitude'],
height=config['elevation'],
)
obs = Observer(location=location, name='PANOPTES',
timezone=config['timezone'])
sunset = obs.sun_set_time(Time(self.start), which='next').datetime
sunrise = obs.sun_rise_time(Time(self.start), which='next').datetime
# Calculate and order twilights and set plotting alpha for each
twilights = [(self.start, 'start', 0.0),
(sunset, 'sunset', 0.0),
(obs.twilight_evening_civil(Time(self.start),
which='next').datetime, 'ec', 0.1),
(obs.twilight_evening_nautical(Time(self.start),
which='next').datetime, 'en', 0.2),
(obs.twilight_evening_astronomical(Time(self.start),
which='next').datetime, 'ea', 0.3),
(obs.twilight_morning_astronomical(Time(self.start),
which='next').datetime, 'ma', 0.5),
(obs.twilight_morning_nautical(Time(self.start),
which='next').datetime, 'mn', 0.3),
(obs.twilight_morning_civil(Time(self.start),
which='next').datetime, 'mc', 0.2),
(sunrise, 'sunrise', 0.1),
]
twilights.sort(key=lambda x: x[0])
final = {'sunset': 0.1, 'ec': 0.2, 'en': 0.3, 'ea': 0.5,
'ma': 0.3, 'mn': 0.2, 'mc': 0.1, 'sunrise': 0.0}
twilights.append((self.end, 'end', final[twilights[-1][1]]))
return twilights
def get_twilights(start, end, webcfg, nsample=256):
""" Determine sunrise and sunset times """
location = c.EarthLocation(
lat=webcfg['site'].getfloat('site_lat'),
lon=webcfg['site'].getfloat('site_lon'),
height=webcfg['site'].getfloat('site_elevation'),
)
obs = Observer(location=location, name=webcfg['site'].get('name', ''))
sunset = obs.sun_set_time(Time(start), which='next').datetime
sunrise = obs.sun_rise_time(Time(start), which='next').datetime
# Calculate and order twilights and set plotting alpha for each
twilights = [
(start, 'start', 0.0),
(sunset, 'sunset', 0.0),
(obs.twilight_evening_civil(Time(start),
which='next').datetime, 'ec', 0.1),
(obs.twilight_evening_nautical(Time(start),
which='next').datetime, 'en', 0.2),
(obs.twilight_evening_astronomical(Time(start),
which='next').datetime, 'ea', 0.3),
(obs.twilight_morning_astronomical(Time(start),
which='next').datetime, 'ma', 0.5),
(obs.twilight_morning_nautical(Time(start),
which='next').datetime, 'mn', 0.3),
(obs.twilight_morning_civil(Time(start),
which='next').datetime, 'mc', 0.2),
(sunrise, 'sunrise', 0.1),
]
twilights.sort(key=lambda x: x[0])
final = {
'sunset': 0.1,
'ec': 0.2,
'en': 0.3,
'ea': 0.5,
'ma': 0.3,
'mn': 0.2,
'mc': 0.1,
'sunrise': 0.0
}
twilights.append((end, 'end', final[twilights[-1][1]]))
return twilights
def calculate_twilights(date):
""" Determine sunrise and sunset times """
from astropy import units as u
from astropy.time import Time
from astropy.coordinates import EarthLocation
from astroplan import Observer
h = 4.2 * u.km
R = (1.0 * u.earthRad).to(u.km)
d = np.sqrt(h * (2 * R + h))
phi = (np.arccos((d / R).value) * u.radian).to(u.deg)
MK = phi - 90 * u.deg
location = EarthLocation(
lat=19 + 49 / 60 + 33.40757 / 60**2,
lon=-(155 + 28 / 60 + 28.98665 / 60**2),
height=4159.58,
)
obs = Observer(location=location, name='Keck', timezone='US/Hawaii')
date = Time(dt.strptime(f'{date} 18:00:00', '%Y-%m-%d %H:%M:%S'))
t = {}
sunset = obs.sun_set_time(date, which='nearest', horizon=MK).datetime
t['seto'] = sunset
t['ento'] = obs.twilight_evening_nautical(Time(sunset),
which='next').datetime
t['eato'] = obs.twilight_evening_astronomical(Time(sunset),
which='next').datetime
t['mato'] = obs.twilight_morning_astronomical(Time(sunset),
which='next').datetime
t['mnto'] = obs.twilight_morning_nautical(Time(sunset),
which='next').datetime
t['riseo'] = obs.sun_rise_time(Time(sunset), which='next').datetime
t['set'] = t['seto'].strftime('%H:%M UT')
t['ent'] = t['ento'].strftime('%H:%M UT')
t['eat'] = t['eato'].strftime('%H:%M UT')
t['mat'] = t['mato'].strftime('%H:%M UT')
t['mnt'] = t['mnto'].strftime('%H:%M UT')
t['rise'] = t['riseo'].strftime('%H:%M UT')
return t
def calculate_twilights(date):
""" Determine sunrise and sunset times """
from astropy import units as u
from astropy.time import Time
from astropy.coordinates import EarthLocation
from astroplan import Observer
h = 4.2*u.km
R = (1.0*u.earthRad).to(u.km)
d = np.sqrt(h*(2*R+h))
phi = (np.arccos((d/R).value)*u.radian).to(u.deg)
MK = phi - 90*u.deg
location = EarthLocation(
lat=19+49/60+33.40757/60**2,
lon=-(155+28/60+28.98665/60**2),
height=4159.58,
)
obs = Observer(location=location, name='Keck', timezone='US/Hawaii')
date = Time(dt.strptime(f'{date} 18:00:00', '%Y-%m-%d %H:%M:%S'))
t = {}
sunset = obs.sun_set_time(date, which='nearest', horizon=MK).datetime
t['seto'] = sunset
t['ento'] = obs.twilight_evening_nautical(Time(sunset), which='next').datetime
t['eato'] = obs.twilight_evening_astronomical(Time(sunset), which='next').datetime
t['mato'] = obs.twilight_morning_astronomical(Time(sunset), which='next').datetime
t['mnto'] = obs.twilight_morning_nautical(Time(sunset), which='next').datetime
t['riseo'] = obs.sun_rise_time(Time(sunset), which='next').datetime
t['set'] = t['seto'].strftime('%H:%M UT')
t['ent'] = t['ento'].strftime('%H:%M UT')
t['eat'] = t['eato'].strftime('%H:%M UT')
t['mat'] = t['mato'].strftime('%H:%M UT')
t['mnt'] = t['mnto'].strftime('%H:%M UT')
t['rise'] = t['riseo'].strftime('%H:%M UT')
return t
def post_save_night(sender, **kwargs):
if not kwargs.get('raw', False):
night = kwargs['instance']
location = night.location
astropy_time = Time(datetime.combine(night.date, time(12)))
astropy_time_delta = TimeDelta(600.0, format='sec')
# guess if the moon is waxing or waning
if ephem.next_full_moon(night.date) - ephem.Date(night.date) < ephem.Date(night.date) - ephem.previous_full_moon(night.date):
waxing_moon = True
else:
waxing_moon = False
observer = Observer(
longitude=location.longitude,
latitude=location.latitude,
timezone='UTC'
)
moon_phase = observer.moon_phase(astropy_time).value
if waxing_moon:
moon_phase = (math.pi - moon_phase) / (2 * math.pi)
else:
moon_phase = (math.pi + moon_phase) / (2 * math.pi)
times = {
'sunset': observer.sun_set_time(astropy_time, which='next'),
'civil_dusk': observer.twilight_evening_civil(astropy_time, which='next'),
'nautical_dusk': observer.twilight_evening_nautical(astropy_time, which='next'),
'astronomical_dusk': observer.twilight_evening_astronomical(astropy_time, which='next'),
'midnight': observer.midnight(astropy_time, which='next'),
'astronomical_dawn': observer.twilight_morning_astronomical(astropy_time, which='next'),
'nautical_dawn': observer.twilight_morning_nautical(astropy_time, which='next'),
'civil_dawn': observer.twilight_morning_civil(astropy_time, which='next'),
'sunrise': observer.sun_rise_time(astropy_time, which='next'),
}
night.mjd = int(astropy_time.mjd) + 1
night.moon_phase = moon_phase
for key in times:
if times[key].jd > 0:
setattr(night, key, times[key].to_datetime(timezone=utc))
post_save.disconnect(post_save_night, sender=sender)
night.save()
post_save.connect(post_save_night, sender=sender)
moon_positions = []
for i in range(144):
moon_altitude = observer.moon_altaz(astropy_time).alt.degree
moon_position = MoonPosition(
timestamp=astropy_time.to_datetime(timezone=utc),
altitude=moon_altitude,
location=location
)
moon_positions.append(moon_position)
astropy_time += astropy_time_delta
MoonPosition.objects.bulk_create(moon_positions)
n_transits = []
for trial in range(n_trials):
target_inds_observed = set([])
obs_database = {
name: dict(times=[], fluxes=[], model=[], transit=False)
for name in table['spc']
}
for i in range(n_years * 365):
# Simulate weather losses
if np.random.rand() > fraction_cloudy:
time = start_time + i * u.day
night_start = saintex.twilight_evening_nautical(time,
which='previous')
night_end = saintex.twilight_morning_nautical(time, which='next')
night_duration = night_end - night_start
times = time_grid_from_range((night_start, night_end),
time_resolution=1.6 * u.min)
obs_table = observability_table(constraints,
saintex,
targets,
times=times)
# Prevent memory from getting out of hand by clearing out cache:
saintex._altaz_cache = {}
mask_targets_visible_2hrs = obs_table[
'fraction of time observable'] * night_duration > 6 * u.hr
sunsets = observer.sun_set_time(times)
sunsets = np.unique(np.round(sunsets.mjd, decimals=4))
names = [
'night', 'sunset', 'sun_n12_setting', 'sun_n18_setting',
'sun_n18_rising', 'sun_n12_rising', 'sunrise', 'moonrise', 'moonset'
]
types = [int]
types.extend([float] * (len(names) - 1))
almanac = np.zeros(sunsets.size, dtype=list(zip(names, types)))
almanac['sunset'] = sunsets
times = Time(sunsets, format='mjd')
print('evening twilight 1')
almanac['sun_n12_setting'] = observer.twilight_evening_nautical(times).mjd
almanac['sun_n18_setting'] = observer.twilight_evening_astronomical(
times).mjd
almanac['sun_n18_rising'] = observer.twilight_morning_astronomical(
times).mjd
almanac['sun_n12_rising'] = observer.twilight_morning_nautical(times).mjd
almanac['sunrise'] = observer.sun_rise_time(times).mjd
almanac['moonset'] = observer.moon_set_time(times).mjd
print('moonrise')
almanac['moonrise'] = observer.moon_rise_time(times).mjd
results.append(almanac)
almanac = np.concatenate(results)
umjds, indx = np.unique(almanac['sunset'], return_index=True)
almanac = almanac[indx]
almanac['night'] = np.arange(almanac['night'].size)
def plan_when_transits_will_occur(
filename='targets.txt',
observatory='Southern African Large Telescope',
start='2017-06-22',
end='2017-06-28',
airmass_limit=2.5,
moon_distance=10,
do_secondary=True,
method='by_night'):
'''
Plan when targets will be visibile and transiting from a site.
Inputs
------
filename : str
A plain text file with the following columns:
target : The name of the target (e.g. J0555-57).
RA : The right ascension of the target (e.g. 05h55m32.62s).
DEC : The declination of the target (e.g. -57d17m26.1s).
epoch* : The epoch of the transit. Youc can either use:
epoch_HJD-2400000 : HJD - 24500000
epoch_BJD-2455000 : MJD
Period : The period of the system (days).
Secondary : can be True or False depending on whether you want
to see when the secondary transits will be.
observatory : str
The observatory you are observing from. See later for list of available
observatories (accepted by astropy).
start : str
The first night of observation (e.g. 2017-08-31).
end : str
The last night of observation (e.g. 2017-09-10).
airmass_limit : float
The maximum airmass you want to observe through.
moon_distance : float
The closest the target can be t the moon in arcmins.
do_secondary = True:
Look for secondary eclipses assuming circularised orbits.
Available observator names are:
'ALMA',
'Anglo-Australian Observatory',
'Apache Point',
'Apache Point Observatory',
'Atacama Large Millimeter Array',
'BAO',
'Beijing XingLong Observatory',
'Black Moshannon Observatory',
'CHARA',
'Canada-France-Hawaii Telescope',
'Catalina Observatory',
'Cerro Pachon',
'Cerro Paranal',
'Cerro Tololo',
'Cerro Tololo Interamerican Observatory',
'DCT',
'Discovery Channel Telescope',
'Dominion Astrophysical Observatory',
'Gemini South',
'Hale Telescope',
'Haleakala Observatories',
'Happy Jack',
'Jansky Very Large Array',
'Keck Observatory',
'Kitt Peak',
'Kitt Peak National Observatory',
'La Silla Observatory',
'Large Binocular Telescope',
'Las Campanas Observatory',
'Lick Observatory',
'Lowell Observatory',
'Manastash Ridge Observatory',
'McDonald Observatory',
'Medicina',
'Medicina Dish',
'Michigan-Dartmouth-MIT Observatory',
'Mount Graham International Observatory',
'Mt Graham',
'Mt. Ekar 182 cm. Telescope',
'Mt. Stromlo Observatory',
'Multiple Mirror Telescope',
'NOV',
'National Observatory of Venezuela',
'Noto',
'Observatorio Astronomico Nacional, San Pedro Martir',
'Observatorio Astronomico Nacional, Tonantzintla',
'Palomar',
'Paranal Observatory',
'Roque de los Muchachos',
'SAAO',
'SALT',
'SRT',
'Siding Spring Observatory',
'Southern African Large Telescope',
'Subaru',
'Subaru Telescope',
'Sutherland',
'Vainu Bappu Observatory',
'Very Large Array',
'W. M. Keck Observatory',
'Whipple',
'Whipple Observatory',
'aao',
'alma',
'apo',
'bmo',
'cfht',
'ctio',
'dao',
'dct',
'ekar',
'example_site',
'flwo',
'gemini_north',
'gemini_south',
'gemn',
'gems',
'greenwich',
'haleakala',
'irtf',
'keck',
'kpno',
'lapalma',
'lasilla',
'lbt',
'lco',
'lick',
'lowell',
'mcdonald',
'mdm',
'medicina',
'mmt',
'mro',
'mso',
'mtbigelow',
'mwo',
'noto',
'ohp',
'paranal',
'salt',
'sirene',
'spm',
'srt',
'sso',
'tona',
'vbo',
'vla'.
'''
###################
# Try reading table
###################
try:
target_table = Table.read(filename, format='ascii')
except:
raise ValueError(
'I cant open the target file (make sure its ascii with the following first line:\ntarget RA DEC epoch_HJD-2400000 Period Secondary'
)
##############################
# try reading observation site
##############################
try:
observation_site = coord.EarthLocation.of_site(observatory)
observation_handle = Observer(location=observation_site)
observation_handle1 = Observer.at_site(observatory)
except:
print(coord.EarthLocation.get_site_names())
raise ValueError('The site is not understood')
###################################
# Try reading start and end times
###################################
try:
start_time = Time(start + ' 12:01:00', location=observation_site)
end_time = Time(end + ' 12:01:00', location=observation_site)
number_of_nights = int(end_time.jd - start_time.jd)
time_range = Time([start + ' 12:01:00', end + ' 12:01:00'])
print('Number of nights: {}'.format(number_of_nights))
except:
raise ValueError('Start and end times not understood')
#####################
# Now do constraints
#####################
#try:
constraints = [
AltitudeConstraint(0 * u.deg, 90 * u.deg),
AirmassConstraint(3),
AtNightConstraint.twilight_civil()
]
#except:
# raise ValueError('Unable to get set constraints')
if method == 'by_night':
for i in range(number_of_nights):
start_time_tmp = start_time + TimeDelta(
i,
format='jd') # get start time (doesent need to be accurate)
end_time_tmp = start_time + TimeDelta(
i + 1,
format='jd') # get start time (doesent need to be accurate)
print('#' * 80)
start_time_tmpss = start_time_tmp.datetime.ctime().split(
) # ['Fri', 'Dec', '24', '12:00:00', '2010']
print('Night {} - {} {} {} {}'.format(i + 1, start_time_tmpss[0],
start_time_tmpss[2],
start_time_tmpss[1],
start_time_tmpss[-1]))
print('#' * 80)
# Now print Almnac information (sunset and end of evening twilight
print('Almnac:')
sun_set = observation_handle.sun_set_time(start_time_tmp,
which='next')
print('Sunset:\t\t\t\t\t\t\t' + sun_set.utc.datetime.ctime())
twilight_evening_astronomical = observation_handle.twilight_evening_astronomical(
start_time_tmp, which='next') # -18
twilight_evening_nautical = observation_handle.twilight_evening_nautical(
start_time_tmp, which='next') # -12
twilight_evening_civil = observation_handle.twilight_evening_civil(
start_time_tmp, which='next') # -6 deg
print('Civil evening twilight (-6 deg) (U.T.C):\t\t' +
twilight_evening_civil.utc.datetime.ctime())
print('Nautical evening twilight (-12 deg) (U.T.C):\t\t' +
twilight_evening_nautical.utc.datetime.ctime())
print('Astronomical evening twilight (-18 deg) (U.T.C):\t' +
twilight_evening_astronomical.utc.datetime.ctime())
print('\n')
twilight_morning_astronomical = observation_handle.twilight_morning_astronomical(
start_time_tmp, which='next') # -18
twilight_morning_nautical = observation_handle.twilight_morning_nautical(
start_time_tmp, which='next') # -12
twilight_morning_civil = observation_handle.twilight_morning_civil(
start_time_tmp, which='next') # -6 deg
print('Astronomical morning twilight (-18 deg) (U.T.C):\t' +
twilight_morning_astronomical.utc.datetime.ctime())
print('Nautical morning twilight (-12 deg) (U.T.C):\t\t' +
twilight_morning_nautical.utc.datetime.ctime())
print('Civil morning twilight (-6 deg) (U.T.C):\t\t' +
twilight_morning_civil.utc.datetime.ctime())
sun_rise = observation_handle.sun_rise_time(start_time_tmp,
which='next')
print('Sunrise:\t\t\t\t\t\t' + sun_rise.utc.datetime.ctime())
print('\n')
# stuff for creating plot
plot_mids = []
plot_names = []
plot_widths = []
for j in range(len(target_table)):
# Extract information
star_coordinates = coord.SkyCoord('{} {}'.format(
target_table['RA'][j], target_table['DEC'][j]),
unit=(u.hourangle, u.deg),
frame='icrs')
star_fixed_coord = FixedTarget(coord=star_coordinates,
name=target_table['target'][j])
####################
# Get finder image
####################
'''
plt.close()
try:
finder_image = plot_finder_image(star_fixed_coord,reticle=True,fov_radius=10*u.arcmin)
except:
pass
plt.savefig(target_table['target'][j]+'_finder_chart.eps')
'''
P = target_table['Period'][j]
Secondary_transit = target_table['Secondary'][j]
transit_half_width = TimeDelta(
target_table['width'][j] * 60 * 60 / 2,
format='sec') # in seconds for a TimeDelta
# now convert T0 to HJD -> JD -> BJD so we can cout period
if 'epoch_HJD-2400000' in target_table.colnames:
#print('Using HJD-2400000')
T0 = target_table['epoch_HJD-2400000'][j]
T0 = Time(T0 + 2400000, format='jd') # HJD given by WASP
ltt_helio = T0.light_travel_time(star_coordinates,
'heliocentric',
location=observation_site)
T0 = T0 - ltt_helio # HJD -> JD
ltt_bary = T0.light_travel_time(star_coordinates,
'barycentric',
location=observation_site)
T0 = T0 + ltt_bary # JD -> BJD
elif 'epoch_BJD-2455000' in target_table.colnames:
#print('Using BJD-2455000')
T0 = target_table['epoch_BJD-2455000'][j] + 2455000
T0 = Time(T0, format='jd') # BJD
else:
print('\n\n\n\n FAILE\n\n\n\n')
continue
##########################################################
# Now start from T0 and count in periods to find transits
##########################################################
# convert star and end time to BJD
ltt_bary_start_time = start_time_tmp.light_travel_time(
star_coordinates, 'barycentric',
location=observation_site) # + TimeDelta(i,format='jd')
start_time_bary = start_time_tmp + ltt_bary_start_time # + TimeDelta(i,format='jd') # convert start time to BJD
ltt_bary_end_time_tmp = end_time_tmp.light_travel_time(
star_coordinates, 'barycentric',
location=observation_site) # + TimeDelta(i,format='jd')
end_time_bary = end_time_tmp + ltt_bary_start_time #+ TimeDelta(i+1,format='jd') # convert end time to BJD and add 1 day 12pm -> 12pm the next day
elapsed = end_time_bary - start_time_bary # now this is 24 hours from the start day 12:00 pm
# now count transits
time = Time(T0.jd, format='jd') # make a temporary copy
transits = []
primary_count, secondary_count = 0, 0
while time.jd < end_time_bary.jd:
if (time.jd > start_time_bary.jd) and (time.jd <
end_time_bary.jd):
if is_observable(constraints,
observation_handle,
[star_fixed_coord],
times=[time])[0] == True:
transits.append(time)
primary_count += 1
if Secondary_transit == 'yes':
timesecondary = time + TimeDelta(P / 2, format='jd')
if (timesecondary.jd > start_time_bary.jd) and (
timesecondary.jd < end_time_bary.jd):
if is_observable(constraints,
observation_handle,
[star_fixed_coord],
times=[timesecondary])[0] == True:
transits.append(timesecondary)
secondary_count += 1
time = time + TimeDelta(P,
format='jd') # add another P to T0
# Now find visible transits
transits = [
i for i in transits
if is_observable(constraints,
observation_handle, [star_fixed_coord],
times=[i])[0] == True
]
if len(transits) == 0:
message = '{} has no transits.'.format(
target_table['target'][j])
print('-' * len(message))
print(message)
print('-' * len(message))
print('\n')
plt.close()
continue
else:
message = '{} has {} primary transits and {} secondary transits.'.format(
target_table['target'][j], primary_count,
secondary_count)
print('-' * len(message))
print(message)
print('RA: {}'.format(target_table['RA'][j]))
print('DEC: {}'.format(target_table['DEC'][j]))
print('Epoch: 2000')
print('T0 (BJD): {}'.format(T0.jd))
print('Period: {}'.format(P))
print('Transit width (hr): {}'.format(
target_table['width'][j]))
print('-' * len(message))
print('\n')
for i in transits:
# currently transit times are in BJD (need to convert to HJD to check
ltt_helio = i.light_travel_time(star_coordinates,
'barycentric',
location=observation_site)
ii = i - ltt_helio
ltt_helio = ii.light_travel_time(star_coordinates,
'heliocentric',
location=observation_site)
ii = ii + ltt_helio
transit_1 = i - transit_half_width - TimeDelta(
7200, format='sec') # ingress - 2 hr
transit_2 = i - transit_half_width - TimeDelta(
3600, format='sec') # ingress - 2 hr
transit_3 = i - transit_half_width # ingress
transit_4 = i + transit_half_width # egress
transit_5 = i + transit_half_width + TimeDelta(
3600, format='sec') # ingress - 2 hr
transit_6 = i + transit_half_width + TimeDelta(
7200, format='sec') # ingress - 2 hr
if (((i.jd - time.jd) / P) - np.floor(
(i.jd - time.jd) / P) < 0.1) or ((
(i.jd - time.jd) / P) - np.floor(
(i.jd - time.jd) / P) > 0.9):
print('Primary Transit:')
print('-' * len('Primary Transit'))
if 0.4 < ((i.jd - time.jd) / P) - np.floor(
(i.jd - time.jd) / P) < 0.6:
print('Secondary Transit')
print('-' * len('Secondary Transit'))
##################
# now get sirmass
##################
altaz = star_coordinates.transform_to(
AltAz(obstime=transit_1, location=observation_site))
hourangle = observation_handle1.target_hour_angle(
transit_1, star_coordinates)
hourangle = 24 * hourangle.degree / 360
if hourangle > 12:
hourangle -= 24
print('Ingress - 2hr (U.T.C):\t\t\t\t\t' +
transit_1.utc.datetime.ctime() +
'\tAirmass: {:.2f}\tHA:{:.2f}'.format(
altaz.secz, hourangle))
altaz = star_coordinates.transform_to(
AltAz(obstime=transit_2, location=observation_site))
hourangle = observation_handle1.target_hour_angle(
transit_2, star_coordinates)
hourangle = 24 * hourangle.degree / 360
if hourangle > 12:
hourangle -= 24
print('Ingress - 1hr (U.T.C):\t\t\t\t\t' +
transit_2.utc.datetime.ctime() +
'\tAirmass: {:.2f}\tHA:{:.2f}'.format(
altaz.secz, hourangle))
altaz = star_coordinates.transform_to(
AltAz(obstime=transit_3, location=observation_site))
hourangle = observation_handle1.target_hour_angle(
transit_3, star_coordinates)
hourangle = 24 * hourangle.degree / 360
if hourangle > 12:
hourangle -= 24
print('Ingress (U.T.C):\t\t\t\t\t' +
transit_3.utc.datetime.ctime() +
'\tAirmass: {:.2f}\tHA:{:.2f}'.format(
altaz.secz, hourangle))
altaz = star_coordinates.transform_to(
AltAz(obstime=i, location=observation_site))
hourangle = observation_handle1.target_hour_angle(
i, star_coordinates)
hourangle = 24 * hourangle.degree / 360
if hourangle > 12:
hourangle -= 24
print('Mid transit (U.T.C):\t\t\t\t\t' +
i.utc.datetime.ctime() +
'\tAirmass: {:.2f}\tHA:{:.2f}'.format(
altaz.secz, hourangle))
altaz = star_coordinates.transform_to(
AltAz(obstime=transit_4, location=observation_site))
hourangle = observation_handle1.target_hour_angle(
transit_4, star_coordinates)
hourangle = 24 * hourangle.degree / 360
if hourangle > 12:
hourangle -= 24
print('Egress (U.T.C):\t\t\t\t\t\t' +
transit_4.utc.datetime.ctime() +
'\tAirmass: {:.2f}\tHA:{:.2f}'.format(
altaz.secz, hourangle))
altaz = star_coordinates.transform_to(
AltAz(obstime=transit_5, location=observation_site))
hourangle = observation_handle1.target_hour_angle(
transit_5, star_coordinates)
hourangle = 24 * hourangle.degree / 360
if hourangle > 12:
hourangle -= 24
print('Egress + 1hr (U.T.C):\t\t\t\t\t' +
transit_5.utc.datetime.ctime() +
'\tAirmass: {:.2f}\tHA:{:.2f}'.format(
altaz.secz, hourangle))
altaz = star_coordinates.transform_to(
AltAz(obstime=transit_6, location=observation_site))
hourangle = observation_handle1.target_hour_angle(
transit_6, star_coordinates)
hourangle = 24 * hourangle.degree / 360
if hourangle > 12:
hourangle -= 24
print('Egress + 2hr (U.T.C):\t\t\t\t\t' +
transit_6.utc.datetime.ctime() +
'\tAirmass: {:.2f}\tHA:{:.2f}'.format(
altaz.secz, hourangle))
print('HJD {} (to check with http://var2.astro.cz/)\n'.
format(ii.jd))
# append stuff for plots
plot_mids.append(i) # astropy Time
plot_names.append(target_table['target'][j])
plot_widths.append(target_table['width'][j])
# Now plot
plt.close()
if len(plot_mids) == 0:
continue
date_formatter = dates.DateFormatter('%H:%M')
#ax.xaxis.set_major_formatter(date_formatter)
# now load dummy transit lightcurves
xp, yp = np.load('lc.npy')
xs, ys = np.load('lcs.npy')
# x = np.linspace(0, 2*np.pi, 400)
# y = np.sin(x**2)
subplots_adjust(hspace=0.000)
number_of_subplots = len(
plot_names) # number of targets transiting that night
time = sun_set + np.linspace(-1, 14,
100) * u.hour # take us to sunset
for i, v in enumerate(xrange(number_of_subplots)):
# exctract params
width = plot_widths[v]
name = plot_names[v]
mid = plot_mids[v]
# now set up dummy lc plot
x_tmp = mid + xp * (width /
2) * u.hour # get right width in hours
# now set up axis
v = v + 1
ax1 = subplot(number_of_subplots, 1, v)
ax1.xaxis.set_major_formatter(date_formatter)
if v == 1:
ax1.set_title(start)
# plot transit model
ax1.plot_date(x_tmp.plot_date, ys, 'k-')
# plot continuum
#xx =time.plot_date
#xx = [uu for uu in xx if (uu<min(x_tmp.plot_date)) or (uu>max(x_tmp.plot_date))]
#ax1.plot_date(xx, np.ones(len(xx)),'k--', alpha=0.3)
ax1.set_xlim(min(time.plot_date), max(time.plot_date))
#ax1.plot_date(mid.plot_date, 0.5, 'ro')
plt.setp(ax1.get_xticklabels(), rotation=30, ha='right')
ax1.set_ylabel(name, rotation=45, labelpad=20)
twilights = [
(sun_set.datetime, 0.0),
(twilight_evening_civil.datetime, 0.1),
(twilight_evening_nautical.datetime, 0.2),
(twilight_evening_astronomical.datetime, 0.3),
(twilight_morning_astronomical.datetime, 0.4),
(twilight_morning_nautical.datetime, 0.3),
(twilight_morning_civil.datetime, 0.2),
(sun_rise.datetime, 0.1),
]
for ii, twii in enumerate(twilights[1:], 1):
ax1.axvspan(twilights[ii - 1][0],
twilights[ii][0],
ymin=0,
ymax=1,
color='grey',
alpha=twii[1])
ax1.grid(alpha=0.5)
ax1.get_yaxis().set_ticks([])
if v != number_of_subplots:
ax1.get_xaxis().set_ticks([])
plt.xlabel('Time [U.T.C]')
#plt.tight_layout()
#plt.savefig('test.eps',format='eps')
plt.show()
def main(args=None):
p = parser()
opts = p.parse_args(args)
# Late imports
import operator
import sys
from astroplan import Observer
from astroplan.plots import plot_airmass
from astropy.coordinates import EarthLocation, SkyCoord
from astropy.table import Table
from astropy.time import Time
from astropy import units as u
from matplotlib import dates
from matplotlib.cm import ScalarMappable
from matplotlib.colors import Normalize
from matplotlib.patches import Patch
from matplotlib import pyplot as plt
from tqdm import tqdm
import pytz
from ..io import fits
from .. import moc
from .. import plot # noqa
from ..extern.quantile import percentile
if opts.site is None:
if opts.site_longitude is None or opts.site_latitude is None:
p.error('must specify either --site or both '
'--site-longitude and --site-latitude')
location = EarthLocation(lon=opts.site_longitude * u.deg,
lat=opts.site_latitude * u.deg,
height=(opts.site_height or 0) * u.m)
if opts.site_timezone is not None:
location.info.meta = {'timezone': opts.site_timezone}
observer = Observer(location)
else:
if not ((opts.site_longitude is None) and
(opts.site_latitude is None) and (opts.site_height is None) and
(opts.site_timezone is None)):
p.error('argument --site not allowed with arguments '
'--site-longitude, --site-latitude, '
'--site-height, or --site-timezone')
observer = Observer.at_site(opts.site)
m = fits.read_sky_map(opts.input.name, moc=True)
# Make an empty airmass chart.
t0 = Time(opts.time) if opts.time is not None else Time.now()
t0 = observer.midnight(t0)
ax = plot_airmass([], observer, t0, altitude_yaxis=True)
# Remove the fake source and determine times that were used for the plot.
del ax.lines[:]
times = Time(np.linspace(*ax.get_xlim()), format='plot_date')
theta, phi = moc.uniq2ang(m['UNIQ'])
coords = SkyCoord(phi, 0.5 * np.pi - theta, unit='rad')
prob = moc.uniq2pixarea(m['UNIQ']) * m['PROBDENSITY']
levels = np.arange(90, 0, -10)
nlevels = len(levels)
percentiles = np.concatenate((50 - 0.5 * levels, 50 + 0.5 * levels))
airmass = np.column_stack([
percentile(condition_secz(coords.transform_to(observer.altaz(t)).secz),
percentiles,
weights=prob) for t in tqdm(times)
])
cmap = ScalarMappable(Normalize(0, 100), plt.get_cmap())
for level, lo, hi in zip(levels, airmass[:nlevels], airmass[nlevels:]):
ax.fill_between(
times.plot_date,
clip_verylarge(lo), # Clip infinities to large but finite values
clip_verylarge(hi), # because fill_between cannot handle inf
color=cmap.to_rgba(level),
zorder=2)
ax.legend([Patch(facecolor=cmap.to_rgba(level)) for level in levels],
['{}%'.format(level) for level in levels])
# ax.set_title('{} from {}'.format(m.meta['objid'], observer.name))
# Adapted from astroplan
start = times[0]
twilights = [
(times[0].datetime, 0.0),
(observer.sun_set_time(Time(start), which='next').datetime, 0.0),
(observer.twilight_evening_civil(Time(start),
which='next').datetime, 0.1),
(observer.twilight_evening_nautical(Time(start),
which='next').datetime, 0.2),
(observer.twilight_evening_astronomical(Time(start),
which='next').datetime, 0.3),
(observer.twilight_morning_astronomical(Time(start),
which='next').datetime, 0.4),
(observer.twilight_morning_nautical(Time(start),
which='next').datetime, 0.3),
(observer.twilight_morning_civil(Time(start),
which='next').datetime, 0.2),
(observer.sun_rise_time(Time(start), which='next').datetime, 0.1),
(times[-1].datetime, 0.0),
]
twilights.sort(key=operator.itemgetter(0))
for i, twi in enumerate(twilights[1:], 1):
if twi[1] != 0:
ax.axvspan(twilights[i - 1][0],
twilights[i][0],
ymin=0,
ymax=1,
color='grey',
alpha=twi[1],
linewidth=0)
if twi[1] != 0.4:
ax.axvspan(twilights[i - 1][0],
twilights[i][0],
ymin=0,
ymax=1,
color='white',
alpha=0.8 - 2 * twi[1],
zorder=3,
linewidth=0)
# Add local time axis
timezone = (observer.location.info.meta or {}).get('timezone')
if timezone:
tzinfo = pytz.timezone(timezone)
ax2 = ax.twiny()
ax2.set_xlim(ax.get_xlim())
ax2.set_xticks(ax.get_xticks())
ax2.xaxis.set_major_formatter(dates.DateFormatter('%H:%M', tz=tzinfo))
plt.setp(ax2.get_xticklabels(), rotation=-30, ha='right')
ax2.set_xlabel("Time from {} [{}]".format(
min(times).to_datetime(tzinfo).date(), timezone))
if opts.verbose:
# Write airmass table to stdout.
times.format = 'isot'
table = Table(masked=True)
table['time'] = times
table['sun_alt'] = np.ma.masked_greater_equal(
observer.sun_altaz(times).alt, 0)
table['sun_alt'].format = lambda x: '{}'.format(int(np.round(x)))
for p, data in sorted(zip(percentiles, airmass)):
table[str(p)] = np.ma.masked_invalid(data)
table[str(p)].format = lambda x: '{:.01f}'.format(np.around(x, 1))
table.write(sys.stdout, format='ascii.fixed_width')
# Show or save output.
opts.output()
def create_observation_observables(object_id,
object_dir,
since,
name,
epoch,
epoch_low_err,
epoch_up_err,
period,
period_low_err,
period_up_err,
duration,
observatories_file,
timezone,
latitude,
longitude,
altitude,
max_days,
min_altitude,
moon_min_dist,
moon_max_dist,
transit_fraction,
baseline,
error_alert=True):
"""
@param object_id: the candidate id
@param object_dir: the candidate directory
@param since: starting plan date
@param name: the name given to the candidate
@param epoch: the candidate epoch
@param epoch_low_err: the candidate epoch's lower error
@param epoch_up_err: the candidate epoch's upper error
@param period: the candidate period
@param period_low_err: the candidate period's lower error
@param period_up_err: the candidate period's upper error
@param duration: the candidate duration
@param observatories_file: the file containing the observatories file (csv format)
@param timezone: the timezone of the observatory (if observatories_file=None)
@param latitude: the latitude of the observatory (if observatories_file=None)
@param longitude: the longitude of the observatory (if observatories_file=None)
@param altitude: the altitude of the observatory (if observatories_file=None)
@param max_days: the maximum number of days to compute the observables
@param min_altitude: the minimum altitude of the target above the horizon
@param moon_min_dist: the minimum moon distance for moon illumination = 0
@param moon_max_dist: the minimum moon distance for moon illumination = 1
@param transit_fraction: the minimum transit observability (0.25 for at least ingress/egress, 0.5 for ingress/egress
+ midtime, 1 for ingress, egress and midtime).
@param baseline: the required baseline in hours.
@param: error_alert: whether to create the alert date to signal imprecise observations
@return: the generated data and target folders
"""
if observatories_file is not None:
observatories_df = pd.read_csv(observatories_file, comment='#')
else:
observatories_df = pd.DataFrame(
columns=['name', 'tz', 'lat', 'long', 'alt'])
observatories_df = observatories_df.append("Obs-1", timezone, latitude,
longitude, altitude)
# TODO probably convert epoch to proper JD
mission, mission_prefix, id_int = LcBuilder().parse_object_info(object_id)
if mission == "TESS":
primary_eclipse_time = Time(epoch, format='btjd', scale="tdb")
elif mission == "Kepler" or mission == "K2":
primary_eclipse_time = Time(epoch, format='bkjd', scale="tdb")
else:
primary_eclipse_time = Time(epoch, format='jd')
target = FixedTarget(SkyCoord(coords, unit=(u.deg, u.deg)))
n_transits = int(max_days // period)
system = EclipsingSystem(primary_eclipse_time=primary_eclipse_time,
orbital_period=u.Quantity(period, unit="d"),
duration=u.Quantity(duration, unit="h"),
name=name)
observables_df = pd.DataFrame(columns=[
'observatory', 'timezone', 'start_obs', 'end_obs', 'ingress', 'egress',
'midtime', "midtime_up_err_h", "midtime_low_err_h", 'twilight_evening',
'twilight_morning', 'observable', 'moon_phase', 'moon_dist'
])
plan_dir = object_dir + "/plan"
images_dir = plan_dir + "/images"
if os.path.exists(plan_dir):
shutil.rmtree(plan_dir, ignore_errors=True)
os.mkdir(plan_dir)
if os.path.exists(images_dir):
shutil.rmtree(images_dir, ignore_errors=True)
os.mkdir(images_dir)
alert_date = None
for index, observatory_row in observatories_df.iterrows():
observer_site = Observer(latitude=observatory_row["lat"],
longitude=observatory_row["lon"],
elevation=u.Quantity(observatory_row["alt"],
unit="m"))
midtransit_times = system.next_primary_eclipse_time(
since, n_eclipses=n_transits)
ingress_egress_times = system.next_primary_ingress_egress_time(
since, n_eclipses=n_transits)
constraints = [
AtNightConstraint.twilight_nautical(),
AltitudeConstraint(min=min_altitude * u.deg),
MoonIlluminationSeparationConstraint(
min_dist=moon_min_dist * u.deg, max_dist=moon_max_dist * u.deg)
]
moon_for_midtransit_times = get_moon(midtransit_times)
moon_dist_midtransit_times = moon_for_midtransit_times.separation(
SkyCoord(star_df.iloc[0]["ra"], star_df.iloc[0]["dec"],
unit="deg"))
moon_phase_midtransit_times = np.round(
astroplan.moon_illumination(midtransit_times), 2)
transits_since_epoch = np.round(
(midtransit_times - primary_eclipse_time).jd / period)
midtransit_time_low_err = np.round(
(((transits_since_epoch * period_low_err)**2 + epoch_low_err**2)
**(1 / 2)) * 24, 2)
midtransit_time_up_err = np.round(
(((transits_since_epoch * period_up_err)**2 + epoch_up_err**2)
**(1 / 2)) * 24, 2)
low_err_delta = TimeDelta(midtransit_time_low_err * 3600, format='sec')
up_err_delta = TimeDelta(midtransit_time_up_err * 3600, format='sec')
i = 0
for midtransit_time in midtransit_times:
twilight_evening = observer_site.twilight_evening_nautical(
midtransit_time)
twilight_morning = observer_site.twilight_morning_nautical(
midtransit_time)
ingress = ingress_egress_times[i][0]
egress = ingress_egress_times[i][1]
lowest_ingress = ingress - low_err_delta[i]
highest_egress = egress + up_err_delta[i]
if error_alert and (highest_egress - lowest_ingress).jd > 0.33:
alert_date = midtransit_time if (alert_date is None) or (
alert_date is not None
and alert_date >= midtransit_time) else alert_date
break
else:
baseline_low = lowest_ingress - baseline * u.hour
baseline_up = highest_egress + baseline * u.hour
transit_times = baseline_low + (
baseline_up - baseline_low) * np.linspace(0, 1, 100)
observable_transit_times = astroplan.is_event_observable(
constraints, observer_site, target, times=transit_times)[0]
observable_transit_times_true = np.argwhere(
observable_transit_times)
observable = len(observable_transit_times_true) / 100
if observable < transit_fraction:
i = i + 1
continue
start_obs = transit_times[observable_transit_times_true[0]][0]
end_obs = transit_times[observable_transit_times_true[
len(observable_transit_times_true) - 1]][0]
start_plot = baseline_low
end_plot = baseline_up
if twilight_evening > start_obs:
start_obs = twilight_evening
if twilight_morning < end_obs:
end_obs = twilight_morning
moon_dist = round(moon_dist_midtransit_times[i].degree)
moon_phase = moon_phase_midtransit_times[i]
# TODO get is_event_observable for several parts of the transit (ideally each 5 mins) to get the proper observable percent. Also with baseline
if observatory_row["tz"] is not None and not np.isnan(
observatory_row["tz"]):
observer_timezone = observatory_row["tz"]
else:
observer_timezone = get_offset(observatory_row["lat"],
observatory_row["lon"],
midtransit_time.datetime)
observables_df = observables_df.append(
{
"observatory":
observatory_row["name"],
"timezone":
observer_timezone,
"ingress":
ingress.isot,
"start_obs":
start_obs.isot,
"end_obs":
end_obs.isot,
"egress":
egress.isot,
"midtime":
midtransit_time.isot,
"midtime_up_err_h":
str(int(midtransit_time_up_err[i] // 1)) + ":" +
str(int(midtransit_time_up_err[i] % 1 * 60)).zfill(2),
"midtime_low_err_h":
str(int(midtransit_time_low_err[i] // 1)) + ":" +
str(int(midtransit_time_low_err[i] % 1 * 60)).zfill(2),
"twilight_evening":
twilight_evening.isot,
"twilight_morning":
twilight_morning.isot,
"observable":
observable,
"moon_phase":
moon_phase,
"moon_dist":
moon_dist
},
ignore_index=True)
plot_time = start_plot + (end_plot - start_plot) * np.linspace(
0, 1, 100)
plt.tick_params(labelsize=6)
airmass_ax = plot_airmass(target,
observer_site,
plot_time,
brightness_shading=False,
altitude_yaxis=True)
airmass_ax.axvspan(twilight_morning.plot_date,
end_plot.plot_date,
color='white')
airmass_ax.axvspan(start_plot.plot_date,
twilight_evening.plot_date,
color='white')
airmass_ax.axvspan(twilight_evening.plot_date,
twilight_morning.plot_date,
color='gray')
airmass_ax.axhspan(1. / np.cos(np.radians(90 - min_altitude)),
5.0,
color='green')
airmass_ax.get_figure().gca().set_title("")
airmass_ax.get_figure().gca().set_xlabel("")
airmass_ax.get_figure().gca().set_ylabel("")
airmass_ax.set_xlabel("")
airmass_ax.set_ylabel("")
xticks = []
xticks_labels = []
xticks.append(start_obs.plot_date)
hour_min_sec_arr = start_obs.isot.split("T")[1].split(":")
xticks_labels.append("T1_" + hour_min_sec_arr[0] + ":" +
hour_min_sec_arr[1])
plt.axvline(x=start_obs.plot_date, color="violet")
xticks.append(end_obs.plot_date)
hour_min_sec_arr = end_obs.isot.split("T")[1].split(":")
xticks_labels.append("T1_" + hour_min_sec_arr[0] + ":" +
hour_min_sec_arr[1])
plt.axvline(x=end_obs.plot_date, color="violet")
if start_plot < lowest_ingress < end_plot:
xticks.append(lowest_ingress.plot_date)
hour_min_sec_arr = lowest_ingress.isot.split("T")[1].split(":")
xticks_labels.append("T1_" + hour_min_sec_arr[0] + ":" +
hour_min_sec_arr[1])
plt.axvline(x=lowest_ingress.plot_date, color="red")
if start_plot < ingress < end_plot:
xticks.append(ingress.plot_date)
hour_min_sec_arr = ingress.isot.split("T")[1].split(":")
xticks_labels.append("T1_" + hour_min_sec_arr[0] + ":" +
hour_min_sec_arr[1])
plt.axvline(x=ingress.plot_date, color="orange")
if start_plot < midtransit_time < end_plot:
xticks.append(midtransit_time.plot_date)
hour_min_sec_arr = midtransit_time.isot.split("T")[1].split(
":")
xticks_labels.append("T0_" + hour_min_sec_arr[0] + ":" +
hour_min_sec_arr[1])
plt.axvline(x=midtransit_time.plot_date, color="black")
if start_plot < egress < end_plot:
xticks.append(egress.plot_date)
hour_min_sec_arr = egress.isot.split("T")[1].split(":")
xticks_labels.append("T4_" + hour_min_sec_arr[0] + ":" +
hour_min_sec_arr[1])
plt.axvline(x=egress.plot_date, color="orange")
if start_plot < highest_egress < end_plot:
xticks.append(highest_egress.plot_date)
hour_min_sec_arr = highest_egress.isot.split("T")[1].split(":")
xticks_labels.append("T4_" + hour_min_sec_arr[0] + ":" +
hour_min_sec_arr[1])
plt.axvline(x=highest_egress.plot_date, color="red")
airmass_ax.xaxis.set_tick_params(labelsize=5)
airmass_ax.set_xticks([])
airmass_ax.set_xticklabels([])
degrees_ax = get_twin(airmass_ax)
degrees_ax.yaxis.set_tick_params(labelsize=6)
degrees_ax.set_yticks([1., 1.55572383, 2.])
degrees_ax.set_yticklabels([90, 50, 30])
fig = matplotlib.pyplot.gcf()
fig.set_size_inches(1.25, 0.75)
plt.savefig(plan_dir + "/images/" + observatory_row["name"] + "_" +
str(midtransit_time.isot)[:-4] + ".png",
bbox_inches='tight')
plt.close()
i = i + 1
observables_df = observables_df.sort_values(["midtime", "observatory"],
ascending=True)
observables_df.to_csv(plan_dir + "/observation_plan.csv", index=False)
print("Observation plan created in directory: " + object_dir)
return observatories_df, observables_df, alert_date, plan_dir, images_dir
obs.moon_rise(time_obs, which='nearest') # moon set obs.moon_set(time_obs, which='nearest') # The above functions can be called with an `angle` keyword argument to specify # a particular horizon angle for rising or setting, or can be called with # convenience functions for particular morning/evening twilight. # For example, to compute astronomical twilight by specifying the `angle`: obs.sun_set_time(time_obs, which='next', angle=18*u.degree) # evening (astronomical) twilight obs.twilight_evening_astronomical(time_obs) # evening (nautical) twilight obs.twilight_evening_nautical(time_obs) # evening (civil) twilight obs.twilight_evening_civil(time_obs) # morning (nautical) twilight obs.twilight_morning_nautical(time_obs) # morning (civil) twilight obs.twilight_morning_civil(time_obs) # morning (astronomical) twilight obs.twilight_morning_astronomical(time_obs) # what is the moon illumination? # returns a float, which is percentage of the moon illuminated
]
types = [int]
types.extend([float] * (len(names) - 1))
base_al = np.zeros(1, dtype=list(zip(names, types)))
while mjd < (mjd_start + duration):
times = Time(mjd, format='mjd')
sunsets = observer.sun_set_time(times, which='next')
times = sunsets
almanac = base_al.copy()
almanac['sunset'] = sunsets.mjd
almanac['moonset'] = observer.moon_set_time(times, which='next').mjd
almanac['moonrise'] = observer.moon_rise_time(times, which='next').mjd
almanac['sun_n12_setting'] = observer.twilight_evening_nautical(
times, which='next').mjd
times = observer.twilight_evening_astronomical(times, which='next')
almanac['sun_n18_setting'] = times.mjd
almanac['sun_n18_rising'] = observer.twilight_morning_astronomical(
times, which='next').mjd
almanac['sun_n12_rising'] = observer.twilight_morning_nautical(
times, which='next').mjd
almanac['sunrise'] = observer.sun_rise_time(times, which='next').mjd
results.append(almanac)
mjd = almanac['sunrise'] + t_step
progress = (mjd - mjd_start) / duration * 100
text = "\rprogress = %.2f%%" % progress
sys.stdout.write(text)
sys.stdout.flush()
