def __init__(self, name, start_time=None, stop_time=None, step_size=None, center=None):
"""
@rtype: Ephemeris
@param name: Body to build an ephemeris for
@param start_time: start time of the ephemeris
@type start_time: Time
@param stop_time: stop time of the ephemeris
@type stop_time: Time
@param step_size: size of time step for ephemeris
@type step_size: Quantity
"""
self.name = str(name)
# make sure the input quantities are reasonable.
if start_time is None:
start_time = Time.now()
self._start_time = Time(start_time, scale='utc')
if stop_time is None:
stop_time = Time.now() + 1.0 * units.day
self._stop_time = Time(stop_time, scale='utc')
step_size = step_size is None and 1 or step_size
if not isinstance(step_size, Quantity):
step_size *= units.day
self.step_size = step_size
if center is None:
center = 568
self._center = center
self._ephemeris = None
self._elements = None
self._current_time = None
self._data = None
def test_timezone_convenience_methods():
location = EarthLocation(-74.0*u.deg, 40.7*u.deg, 0*u.m)
obs = Observer(location=location,timezone=pytz.timezone('US/Eastern'))
t = Time(57100.3, format='mjd')
assert (obs.astropy_time_to_datetime(t).hour == 3)
dt = datetime.datetime(2015, 3, 19, 3, 12)
assert (obs.datetime_to_astropy_time(dt).datetime ==
datetime.datetime(2015, 3, 19, 7, 12))
assert (obs.astropy_time_to_datetime(obs.datetime_to_astropy_time(dt)).replace(
tzinfo=None) == dt)
# Test ndarray of times:
times = t + np.linspace(0, 24, 10)*u.hour
times_dt_ndarray = times.datetime
assert all((obs.datetime_to_astropy_time(times_dt_ndarray)).jd ==
(times + 4*u.hour).jd)
# Test list of times:
times_dt_list = list(times.datetime)
assert all((obs.datetime_to_astropy_time(times_dt_list)).jd ==
(times + 4*u.hour).jd)
dts = obs.astropy_time_to_datetime(times)
naive_dts = list(map(lambda t: t.replace(tzinfo=None), dts))
assert all(naive_dts == times_dt_ndarray - datetime.timedelta(hours=4))
def _parse_hdus(cls, hdulist):
header = MetaDict(OrderedDict(hdulist[0].header))
# these GBM files have three FITS extensions.
# extn1 - this gives the energy range for each of the 128 energy bins
# extn2 - this contains the data, e.g. counts, exposure time, time of observation
# extn3 - eclipse times?
energy_bins = hdulist[1].data
count_data = hdulist[2].data
misc = hdulist[3].data
# rebin the 128 energy channels into some summary ranges
# 4-15 keV, 15 - 25 keV, 25-50 keV, 50-100 keV, 100-300 keV, 300-800 keV, 800 - 2000 keV
# put the data in the units of counts/s/keV
summary_counts = _bin_data_for_summary(energy_bins, count_data)
# get the time information in datetime format with the correct MET adjustment
gbm_times = Time([fermi.met_to_utc(t) for t in count_data['time']])
gbm_times.precision = 9
gbm_times = gbm_times.isot.astype('datetime64')
column_labels = ['4-15 keV', '15-25 keV', '25-50 keV', '50-100 keV',
'100-300 keV', '300-800 keV', '800-2000 keV']
# Add the units data
units = OrderedDict([('4-15 keV', u.ct / u.s / u.keV), ('15-25 keV', u.ct / u.s / u.keV),
('25-50 keV', u.ct / u.s / u.keV), ('50-100 keV', u.ct / u.s / u.keV),
('100-300 keV', u.ct / u.s / u.keV), ('300-800 keV', u.ct / u.s / u.keV),
('800-2000 keV', u.ct / u.s / u.keV)])
return pd.DataFrame(summary_counts, columns=column_labels, index=gbm_times), header, units
def print_pyephem_parallactic_angle():
lat = 19.826218*u.deg
lon = -155.471999*u.deg
time = Time('2015-01-01 00:00:00')
LST = time.sidereal_time('mean', longitude=lon)
desired_HA_1 = 3*u.hourangle
desired_HA_2 = 19*u.hourangle # = -5*u.hourangle
obs = ephem.Observer()
obs.lat = '19:49:34.3848'
obs.lon = '-155:28:19.1964'
obs.elevation = 0
obs.date = time.datetime
pyephem_target1 = ephem.FixedBody()
pyephem_target1._ra = ephem.degrees((LST - desired_HA_1).to(u.rad).value)
pyephem_target1._dec = ephem.degrees((-30*u.deg).to(u.rad).value)
pyephem_target1.compute(obs)
pyephem_q1 = (float(pyephem_target1.parallactic_angle())*u.rad).to(u.deg)
pyephem_target2 = ephem.FixedBody()
pyephem_target2._ra = ephem.degrees((LST - desired_HA_2).to(u.rad).value)
pyephem_target2._dec = ephem.degrees((-30*u.deg).to(u.rad).value)
pyephem_target2.compute(obs)
pyephem_q2 = (float(pyephem_target2.parallactic_angle())*u.rad).to(u.deg)
print(pyephem_q1, pyephem_q2)
assert (obs.astropy_to_local_time(obs.local_to_astropy_time(dt)).replace(
tzinfo=None) == dt)
def test_precision(self):
"""Set the output precision which is used for some formats. This is
also a test of the code that provides a dict for global and instance
options."""
t = Time("2010-01-01 00:00:00", format="iso", scale="utc")
# Uses initial class-defined precision=3
assert t.iso == "2010-01-01 00:00:00.000"
# Set global precision = 5 XXX this uses private var, FIX THIS
Time._precision = 5
assert t.iso == "2010-01-01 00:00:00.00000"
# Set instance precision to 9
t.precision = 9
assert t.iso == "2010-01-01 00:00:00.000000000"
assert t.tai.utc.iso == "2010-01-01 00:00:00.000000000"
# Restore global to original default of 3, instance is still at 9
Time._precision = 3
assert t.iso == "2010-01-01 00:00:00.000000000"
# Make a new time instance and confirm precision = 3
t = Time("2010-01-01 00:00:00", format="iso", scale="utc")
assert t.iso == "2010-01-01 00:00:00.000"
def seek(self, offset):
"""Move filepointers to given offset
Parameters
----------
offset : float, Quantity, TimeDelta, Time, or str (iso-t)
If float, in units of bytes
If Quantity in time units or TimeDelta, interpreted as offset from
start time, and converted to nearest record
If Time, calculate offset from start time and convert
"""
if isinstance(offset, Time):
offset = offset-self.time0
elif isinstance(offset, str):
offset = Time(offset, scale='utc') - self.time0
try:
offset = offset.to(self.dtsample.unit)
except AttributeError:
pass
except u.UnitsError:
offset = int(offset.to(u.byte).value)
else:
offset = (offset/self.dtsample).to(u.dimensionless_unscaled)
offset = int(round(offset)) * self.recordsize
self._seek(offset)
def get_datetime(from_value):
"""
Ensure datetime values are in MJD. This is meant to handle any odd formats
that telescopes have for datetime values.
Relies on astropy, until astropy fails.
:param from_value:
:return: datetime instance
"""
if from_value is not None:
try:
result = Time(from_value)
result.format = 'mjd'
return result
except ValueError:
try:
# VLASS has a format astropy fails to understand
# from datetime import datetime
result = Time(
dt_datetime.strptime(from_value, '%H:%M:%S'))
result.format = 'mjd'
return result
except ValueError:
logging.error('Cannot parse datetime {}'.format(from_value))
return None
else:
return None
def __init__(
self,
val,
val2=None,
format=None,
scale=None,
precision=None,
in_subfmt=None,
out_subfmt=None,
location=None,
copy=False,
):
# Extend formats list to include TimeLV (LabVIEW format)
self.FORMATS[u"lv"] = TimeLV
astroTime.__init__(
self,
val,
val2,
format=format,
scale=scale,
precision=precision,
in_subfmt=in_subfmt,
out_subfmt=out_subfmt,
location=location,
copy=copy,
)
def check_moon(file, avoid=30.*u.degree):
if not isinstance(avoid, u.Quantity):
avoid = float(avoid)*u.degree
else:
avoid = avoid.to(u.degree)
header = fits.getheader(file)
mlo = EarthLocation.of_site('Keck Observatory') # Update later
obstime = Time(header['DATE-OBS'], format='isot', scale='utc', location=mlo)
moon = get_moon(obstime, mlo)
if 'RA' in header.keys() and 'DEC' in header.keys():
coord_string = '{} {}'.format(header['RA'], header['DEC'])
target = SkyCoord(coord_string, unit=(u.hourangle, u.deg))
else:
## Assume zenith
target = SkyCoord(obstime.sidereal_time('apparent'), mlo.latitude)
moon_alt = moon.transform_to(AltAz(obstime=obstime, location=mlo)).alt.to(u.deg)
if moon_alt < 0*u.degree:
print('Moon is down')
return True
else:
sep = target.separation(moon)
print('Moon is up. Separation = {:.1f} deg'.format(sep.to(u.degree).value))
return (sep > avoid)
def _get_ut1_from_utc(cls, UTC):
"""
Take a numpy array of UTC values and return a numpy array of UT1 and dut1 values
"""
time_list = Time(UTC, scale='utc', format='mjd')
try:
dut1_out = time_list.delta_ut1_utc
ut1_out = time_list.ut1.mjd
except IERSRangeError:
ut1_out = np.copy(UTC)
dut1_out = np.zeros(len(UTC))
warnings.warn("ModifiedJulianData.get_list() was given date values that are outside "
"astropy's range of interpolation for converting from UTC to UT1. "
"We will treat UT1=UTC for those dates, lacking a better alternative.",
category=UTCtoUT1Warning)
from astropy.utils.iers import TIME_BEFORE_IERS_RANGE, TIME_BEYOND_IERS_RANGE
dut1_test, status = time_list.get_delta_ut1_utc(return_status=True)
good_dexes = np.where(np.logical_and(status != TIME_BEFORE_IERS_RANGE,
status != TIME_BEYOND_IERS_RANGE))
if len(good_dexes[0]) > 0:
time_good = Time(UTC[good_dexes], scale='utc', format='mjd')
dut1_good = time_good.delta_ut1_utc
ut1_good = time_good.ut1.mjd
ut1_out[good_dexes] = ut1_good
dut1_out[good_dexes] = dut1_good
return ut1_out, dut1_out
def test_strftime_leapsecond():
time_string = '1995-12-31 23:59:60'
t = Time(time_string)
for format in t.FORMATS:
t.format = format
assert t.strftime('%Y-%m-%d %H:%M:%S') == time_string
def test_strftime_array():
tstrings = ['2010-09-03 00:00:00', '2005-09-03 06:00:00', '1995-12-31 23:59:60']
t = Time(tstrings)
for format in t.FORMATS:
t.format = format
assert t.strftime('%Y-%m-%d %H:%M:%S').tolist() == tstrings
def gmst2gps(day, GMST, type='mean', iterations=10, precision=1e-14):
"""
----------------------------------------------------------------------------
gps=gmst2gps(day, GMST, type='mean', iterations=10, precision=1e-14)
returns the GPS time associated with the GMST/GAST on the given day
type can be 'mean' or 'apparent'
uses a root-find, so not super fast
----------------------------------------------------------------------------
"""
assert type in ['mean','apparent']
gmst=Longitude(GMST,unit='h')
t=Time(day,scale='utc')
iteration=0
siderealday_to_solarday=0.99726958
while iteration < iterations:
error=t.sidereal_time(type,'greenwich')-gmst
if NP.abs(error/gmst).value <= precision:
return t.gps
t=t-TimeDelta((error).hour*u.hour)*siderealday_to_solarday
iteration+=1
return None
def convert_time(analysis):
#analysis is the fits file in the photometry function
t = Time(analysis[0].header['DATE-OBS'])
t.format = 'mjd'
result = t.value
return result
def setup(self):
wht = EarthLocation(342.12*u.deg, 28.758333333333333*u.deg, 2327*u.m)
self.obstime = Time("2013-02-02T23:00", location=wht)
self.obstime2 = Time("2013-08-02T23:00", location=wht)
self.obstimeArr = Time(["2013-02-02T23:00", "2013-08-02T23:00"], location=wht)
self.star = SkyCoord("08:08:08 +32:00:00", unit=(u.hour, u.degree),
frame='icrs')
def __init__(self, TAI=None, UTC=None):
"""
Must specify either:
@param [in] TAI = the International Atomic Time as an MJD
or
@param [in] UTC = Universal Coordinate Time as an MJD
"""
if TAI is None and UTC is None:
raise RuntimeError("You must specify either TAI or UTC to "
"instantiate ModifiedJulianDate")
if TAI is not None:
self._time = Time(TAI, scale='tai', format='mjd')
self._tai = TAI
self._utc = None
else:
self._time = Time(UTC, scale='utc', format='mjd')
self._utc = UTC
self._tai = None
self._tt = None
self._tdb = None
self._ut1 = None
self._dut1 = None
def test_timedelta(fmt, tmpdir):
t1 = Time(Time.now())
t2 = Time(Time.now())
td = TimeDelta(t2 - t1, format=fmt)
tree = dict(timedelta=td)
assert_roundtrip_tree(tree, tmpdir)
def main():
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--ra', type=float, default=25.0,
help='Right Ascension (degrees)')
parser.add_argument('--dec', type=float, default=12.0,
help='Declination (degrees)')
parser.add_argument('--mjd', type=float, default=55000.0,
help='Modified Julien Date (days)')
parser.add_argument('--scan-offset', type=float, default=15.0,
help='Scan offset (hours)')
parser.add_argument('--scan-width', type=float, default=4.0,
help='Scan width (hours)')
parser.add_argument('--scan-steps', type=int, default=100,
help='Number of sampling points')
parser.add_argument('--astropy-apo', action='store_true',
help='User apo observatory from astropy')
args = parser.parse_args()
if args.astropy_apo:
sdss = EarthLocation.of_site('apo')
else:
sdss = EarthLocation(lat=32.7797556*u.deg, lon=-(105+49./60.+13/3600.)*u.deg, height=2797*u.m)
coord = SkyCoord(ra=args.ra*u.degree, dec=args.dec*u.degree, frame='icrs')
# scan of time
hours = args.scan_offset + np.linspace(-0.5*args.scan_width, 0.5*args.scan_width, args.scan_steps)
my_alt = np.zeros((hours.size))
py_alt = np.zeros((hours.size))
py_ha = np.zeros((hours.size))
for i in range(hours.size):
mjd_value = args.mjd*u.day + hours[i]*u.hour
time = Time(val=mjd_value, scale='tai', format='mjd', location=sdss)
# altitude from astropy
py_alt[i] = coord.transform_to(AltAz(obstime=time, location=sdss)).alt.to(u.deg).value
# this is supposed to be the hour angle from astropy
py_ha[i] = time.sidereal_time('apparent').to(u.deg).value - args.ra
# simple rotation to get alt,az based on ha
my_alt[i], az = hadec2altaz(py_ha[i], args.dec, sdss.latitude.to(u.deg).value)
print hours[i], py_ha[i], py_alt[i], my_alt[i]
py_ha = np.array(map(normalize_angle, py_ha.tolist()))
ii = np.argsort(py_ha)
py_ha=py_ha[ii]
py_alt=py_alt[ii]
my_alt=my_alt[ii]
fig = plt.figure(figsize=(8,6))
plt.plot(py_ha, py_alt - my_alt, 'o', c='b')
plt.title('Compare hadec2altaz')
# plt.title('(ra,dec) = (%.2f,%.2f)' % (args.ra, args.dec))
plt.xlabel('Hour Angle [deg]')
plt.ylabel('astropy_alt - rotation_alt [deg]')
plt.grid(True)
plt.show()
def test_strftime_scalar():
"""Test of Time.strftime
"""
time_string = '2010-09-03 06:00:00'
t = Time(time_string)
for format in t.FORMATS:
t.format = format
assert t.strftime('%Y-%m-%d %H:%M:%S') == time_string
def get_member_info(object_name, filtertype='r', imagetype='p'):
"""
Query the ssois ephemeris for images of a given object. Then parse through for desired image type,
filter, exposure time, and telescope instrument
"""
# From the given input, identify the desired filter and rename appropriately Replace this?
if filtertype.lower().__contains__('r'):
filtertype = 'r.MP9601' # this is the old (standard) r filter for MegaCam
if filtertype.lower().__contains__('u'):
filtertype = 'u.MP9301'
# Define time period of image search, basically while MegaCam in operation
search_start_date = Time('2013-01-01', scale='utc') # epoch1=2013+01+01
search_end_date = Time('2017-01-01', scale='utc') # epoch2=2017+1+1
print "----- Searching for images of object {}".format(object_name)
query = Query(object_name, search_start_date=search_start_date, search_end_date=search_end_date)
try:
objects = parse_ssois_return(query.get(), object_name, imagetype, camera_filter=filtertype)
except IOError:
print "Sleeping 30 seconds"
time.sleep(30)
objects = parse_ssois_return(query.get(), object_name, imagetype, camera_filter=filtertype)
# Setup output, label columns
if len(objects)>0:
output = '{}/{}_object_images.txt'.format(_OUTPUT_DIR, object_name)
with open(output, 'w') as outfile:
outfile.write("{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\n".format(
"Object", "Image", "Exp_time", "RA (deg)", "Dec (deg)", "time", "filter", "RA rate (\"/hr)", "Dec rate (\"/hr)"))
mjds = []
for line in objects:
mjds.append(float(line['MJD'])) #Have to convert elements to floats
start_time = Time(min(mjds), format='mjd') - 1.0*units.minute
stop_time = Time(max(mjds), format='mjd') + 1.0*units.minute
#Query Horizons once to establish position values over given time period, then give it a current time which it interpolates withl
body = horizons.Body(object_name, start_time=start_time, stop_time=stop_time, step_size=10 * units.minute)
for line in objects:
with open(output, 'a') as outfile:
time = Time(line['MJD'], format='mjd', scale='utc')
time.format = 'iso'
body.current_time = time
p_ra = body.coordinate.ra.degree
p_dec = body.coordinate.dec.degree
ra_dot = body.ra_rate.to(units.arcsecond/units.hour).value
dec_dot = body.dec_rate.to(units.arcsecond/units.hour).value
try:
outfile.write("{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\n".format(
object_name, line['Image'], line['Exptime'], p_ra, p_dec,
Time(line['MJD'], format='mjd', scale='utc'), line['Filter'], ra_dot, dec_dot))
except Exception, e:
print "Error writing to outfile: {}".format(e)
def test_yday_format(self):
"""Year:Day_of_year format"""
# Heterogeneous input formats with in_subfmt='*' (default)
times = ["2000-12-01", "2001-12-01 01:01:01.123"]
t = Time(times, format="iso", scale="tai")
t.out_subfmt = "date_hm"
assert np.all(t.yday == np.array(["2000:336:00:00", "2001:335:01:01"]))
t.out_subfmt = "*"
assert np.all(t.yday == np.array(["2000:336:00:00:00.000", "2001:335:01:01:01.123"]))
def radec2altaz(ra, dec, obstime, lat=None, long=None, debug=False):
"""
calculates the altitude and azimuth, given an ra, dec, time, and observatory location
:param ra: right ascension of the target (in degrees)
:param dec: declination of the target (in degrees)
:param obstime: an astropy.time.Time object containing the time of the observation.
Can also contain the observatory location
:param lat: The latitude of the observatory. Not needed if given in the obstime object
:param long: The longitude of the observatory. Not needed if given in the obstime object
:return:
"""
if lat is None:
lat = obstime.lat.degree
if long is None:
long = obstime.lon.degree
obstime = Time(obstime.isot, format='isot', scale='utc', location=(long, lat))
# Find the number of days since J2000
j2000 = Time("2000-01-01T12:00:00.0", format='isot', scale='utc')
dt = (obstime - j2000).value # number of days since J2000 epoch
# get the UT time
tstring = obstime.isot.split("T")[-1]
segments = tstring.split(":")
ut = float(segments[0]) + float(segments[1]) / 60.0 + float(segments[2]) / 3600
# Calculate Local Sidereal Time
lst = obstime.sidereal_time('mean').deg
# Calculate the hour angle
HA = lst - ra
while HA < 0.0 or HA > 360.0:
s = -np.sign(HA)
HA += s * 360.0
# convert everything to radians
dec *= np.pi / 180.0
ra *= np.pi / 180.0
lat *= np.pi / 180.0
long *= np.pi / 180.0
HA *= np.pi / 180.0
# Calculate the altitude
alt = np.arcsin(np.sin(dec) * np.sin(lat) + np.cos(dec) * np.cos(lat) * np.cos(HA))
# calculate the azimuth
az = np.arccos((np.sin(dec) - np.sin(alt) * np.sin(lat)) / (np.cos(alt) * np.cos(lat)))
if np.sin(HA) > 0:
az = 2.0 * np.pi - az
if debug:
print "UT: ", ut
print "LST: ", lst
print "HA: ", HA * 180.0 / np.pi
return alt * 180.0 / np.pi, az * 180.0 / np.pi
def test_mask_not_writeable():
t = Time('2000:001')
with pytest.raises(AttributeError) as err:
t.mask = True
assert "can't set attribute" in str(err)
t = Time(['2000:001'])
with pytest.raises(ValueError) as err:
t.mask[0] = True
assert "assignment destination is read-only" in str(err)
def test_time_formatting(self):
mpc_time = "2000 01 01.000001"
iso_time = "2000-01-01 00:00:00.0864"
t1 = Time(mpc_time, format='mpc', scale='utc', precision=6)
t2 = Time(iso_time, format='iso', scale='utc', precision=6)
t3 = t2.replicate(format='mpc')
t3.precision = 6
self.assertEquals(mpc_time, str(t1))
self.assertEquals(t2.jd, t1.jd)
self.assertEquals(mpc_time, str(t3))
def set_lsts_from_time_array(self):
"""Set the lst_array based from the time_array."""
lsts = []
curtime = self.time_array[0]
for ind, jd in enumerate(self.time_array):
if ind == 0 or not np.isclose(jd, curtime, atol=1e-6, rtol=1e-12):
curtime = jd
latitude, longitude, altitude = self.telescope_location_lat_lon_alt_degrees
t = Time(jd, format='jd', location=(longitude, latitude))
lsts.append(t.sidereal_time('apparent').radian)
self.lst_array = np.array(lsts)
def test_strftime_array_2():
tstrings = [['1998-01-01 00:00:01', '1998-01-01 00:00:02'],
['1998-01-01 00:00:03', '1995-12-31 23:59:60']]
tstrings = np.array(tstrings)
t = Time(tstrings)
for format in t.FORMATS:
t.format = format
assert np.all(t.strftime('%Y-%m-%d %H:%M:%S') == tstrings)
assert t.strftime('%Y-%m-%d %H:%M:%S').shape == tstrings.shape
def test_copy(self):
"""Test copy method"""
t = Time("2000:001", format="yday", scale="tai")
t_yday = t.yday
t2 = t.copy()
assert t.yday == t2.yday
# This is not allowed publicly, but here we hack the internal time values
# to show that t and t2 are not sharing references.
t2._time.jd1 += 100.0
assert t.yday != t2.yday
assert t.yday == t_yday # prove that it did not change
def Sidereal(value):#overall gps time ti sidereal time
result= float()
tunix = value +315964800 # gps time to unix time
hour = Time(tunix, format='unix', location=('-68.131389', '-16.353333')) # defines object "hour" needed in astropy
Side = str( hour.sidereal_time('mean') ) #trasform to sidereal time
if Side[1]=='h':
A = Side
result = (float(A[0])*3600)+(float(A[2:4])*60)+(float(A[5:7]))
if Side[2]=='h':
A = Side
result = (float(A[0:2])*3600)+(float(A[3:5])*60)+(float(A[6:8]))
return int(result)
def get_sid_trans(date, longitude):
'''Initialize matplotlib transform for local time - sidereal time conversion'''
midnight = Time(date) #midnight UTC
sidmid = midnight.sidereal_time('mean', longitude)
#offset from local time
offset = sidmid.hour / 24
#used to convert to origin of plot_date coordinates
p0 = midnight.plot_date
#A mean sidereal day is 23 hours, 56 minutes, 4.0916 seconds (23.9344699 hours or 0.99726958 mean solar days)
scale = 366.25 / 365.25
return Affine2D().translate(-p0, 0).scale(scale).translate(p0 + offset, 0)
def _(attr, results):
return set(
it for it in results
if
it.time.end is not None
and
attr.min <= Time.strptime(it.time.end, TIMEFORMAT)
and
it.time.start is not None
and
attr.max >= Time.strptime(it.time.start, TIMEFORMAT)
)
def plot_airmass(ra,
dec,
year,
months,
days,
outfile='plot_airmass.png',
date_idx=-1):
"""
ra = R.A. value of target (e.g. '17:45:40.04')
dec = Dec. value of target (e.g. '-29:00:28.12')
year = int value of year you want to observe
months = array of months (integers) where each month will have a curve.
days = array of days (integers), of same length as months.
observatory = Either 'keck1' or 'keck2'
date_idx = Index of day to use for twilight dashed lines. Defaults to first day.
Notes:
Months are 1-based (i.e. 1 = January). Same for days.
"""
# Setup the target
target = SkyCoord(ra, dec, unit=(u.hour, u.deg), frame='icrs')
# Setup local time.
utc_offset = -7 * u.hour # Pacific Standard Time
month_labels = [
'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct',
'Nov', 'Dec'
]
# Observatory (for symbol)
obs = 'lick'
lick = EarthLocation.of_site('lick')
# Labels and colors for different months.
labels = []
label_fmt = '{0:s} {1:d}, {2:d} (HST)'
for ii in range(len(months)):
label = label_fmt.format(month_labels[months[ii] - 1], days[ii], year)
labels.append(label)
colors = ['r', 'b', 'g', 'c', 'm', 'y']
heights = [1.45, 1.35, 1.25, 1.15]
# Get sunset and sunrise times on the first specified day
midnight = Time('{0:d}-{1:d}-{2:d} 00:00:00'.format(
year, months[date_idx], days[date_idx])) - utc_offset
delta_midnight = np.arange(-12, 12, 0.01) * u.hour
times = midnight + delta_midnight
altaz_frame = AltAz(obstime=times, location=lick)
sun_altaz = get_sun(times).transform_to(altaz_frame)
sun_down = np.where(sun_altaz.alt < -0 * u.deg)[0]
twilite = np.where(sun_altaz.alt < -12 * u.deg)[0]
sunset = delta_midnight[sun_down[0]].value
sunrise = delta_midnight[sun_down[-1]].value
twilite1 = delta_midnight[twilite[0]].value
twilite2 = delta_midnight[twilite[-1]].value
# Get the half-night split times
splittime = twilite1 + ((twilite2 - twilite1) / 2.0)
print('Sunrise %4.1f Sunset %4.1f (hours around midnight HST)' %
(sunrise, sunset))
print('12-degr %4.1f 12-degr %4.1f (hours around midnight HST)' %
(twilite1, twilite2))
plt.close(2)
plt.figure(2, figsize=(7, 7))
plt.clf()
plt.subplots_adjust(left=0.15)
for ii in range(len(days)):
midnight = Time('{0:d}-{1:d}-{2:d} 00:00:00'.format(
year, months[ii], days[ii])) - utc_offset
delta_midnight = np.arange(-7, 7, 0.2) * u.hour
times = delta_midnight.value
target_altaz = target.transform_to(
AltAz(obstime=midnight + delta_midnight, location=lick))
airmass = target_altaz.secz
# Trim out junk where target is at "negative airmass"
good = np.where(airmass > 0)[0]
times = times[good]
airmass = airmass[good]
# Find the points beyond the Nasmyth deck. Also don't bother with anything above sec(z) = 3
transitTime = times[airmass.argmin()]
# FIXME: HOW DOES THIS WORK FOR LICK???????
# belowDeck = (np.where((times >= transitTime) & (airmass >= 1.8)))[0]
# aboveDeck = (np.where(((times >= transitTime) & (airmass < 1.8)) |
# (times < transitTime)))[0]
belowDeck = (np.where((times >= transitTime) & (airmass >= 1.8)))[0]
aboveDeck = (np.where(((times >= transitTime) & (airmass < 1.8))
| (times < transitTime)))[0]
print('belowDeck', belowDeck)
print('aboveDeck', aboveDeck)
print('times[belowDeck]', times[belowDeck])
print('times[aboveDeck]', times[aboveDeck])
plt.plot(times[belowDeck],
airmass[belowDeck],
colors[ii] + 'o',
mfc='w',
mec=colors[ii],
ms=12)
plt.plot(times[aboveDeck],
airmass[aboveDeck],
colors[ii] + 'o',
mec=colors[ii],
ms=12)
plt.plot(times, airmass, colors[ii] + '-')
plt.text(-3.5,
airmass[5] + (ii * 0.1) - 0.65,
labels[ii],
color=colors[ii])
plt.title('Obs. RA = 18:00, DEC = -30:00 from Lick', fontsize=18)
plt.xlabel('Local Time in Hours (0 = midnight)', fontsize=16)
plt.ylabel('Air Mass', fontsize=16)
loAirmass = 1
hiAirmass = 3
# Draw on the 12-degree twilight limits
plt.axvline(splittime, color='k', linestyle='--')
plt.axvline(twilite1 + 0.5, color='k', linestyle='--')
plt.axvline(twilite2, color='k', linestyle='--')
plt.axis([sunset, sunrise, loAirmass, hiAirmass])
plt.savefig(outfile)
def write_event_file(events, parameters, filename, overwrite=False):
from astropy.time import Time, TimeDelta
mylog.info("Writing events to file %s." % filename)
t_begin = Time.now()
dt = TimeDelta(parameters["exposure_time"], format='sec')
t_end = t_begin + dt
col_x = pyfits.Column(name='X', format='D', unit='pixel', array=events["xpix"])
col_y = pyfits.Column(name='Y', format='D', unit='pixel', array=events["ypix"])
col_e = pyfits.Column(name='ENERGY', format='E', unit='eV', array=events["energy"]*1000.)
col_dx = pyfits.Column(name='DETX', format='D', unit='pixel', array=events["detx"])
col_dy = pyfits.Column(name='DETY', format='D', unit='pixel', array=events["dety"])
col_id = pyfits.Column(name='CCD_ID', format='D', unit='pixel', array=events["ccd_id"])
chantype = parameters["channel_type"]
if chantype == "PHA":
cunit = "adu"
elif chantype == "PI":
cunit = "Chan"
col_ch = pyfits.Column(name=chantype.upper(), format='1J', unit=cunit, array=events[chantype])
col_t = pyfits.Column(name="TIME", format='1D', unit='s', array=events['time'])
cols = [col_e, col_x, col_y, col_ch, col_t, col_dx, col_dy, col_id]
coldefs = pyfits.ColDefs(cols)
tbhdu = pyfits.BinTableHDU.from_columns(coldefs)
tbhdu.name = "EVENTS"
tbhdu.header["MTYPE1"] = "sky"
tbhdu.header["MFORM1"] = "x,y"
tbhdu.header["MTYPE2"] = "EQPOS"
tbhdu.header["MFORM2"] = "RA,DEC"
tbhdu.header["TCTYP2"] = "RA---TAN"
tbhdu.header["TCTYP3"] = "DEC--TAN"
tbhdu.header["TCRVL2"] = parameters["sky_center"][0]
tbhdu.header["TCRVL3"] = parameters["sky_center"][1]
tbhdu.header["TCDLT2"] = -parameters["plate_scale"]
tbhdu.header["TCDLT3"] = parameters["plate_scale"]
tbhdu.header["TCRPX2"] = parameters["pix_center"][0]
tbhdu.header["TCRPX3"] = parameters["pix_center"][1]
tbhdu.header["TCUNI2"] = "deg"
tbhdu.header["TCUNI3"] = "deg"
tbhdu.header["TLMIN2"] = 0.5
tbhdu.header["TLMIN3"] = 0.5
tbhdu.header["TLMAX2"] = 2.0*parameters["num_pixels"]+0.5
tbhdu.header["TLMAX3"] = 2.0*parameters["num_pixels"]+0.5
tbhdu.header["TLMIN4"] = parameters["chan_lim"][0]
tbhdu.header["TLMAX4"] = parameters["chan_lim"][1]
tbhdu.header["TLMIN6"] = -0.5*parameters["num_pixels"]
tbhdu.header["TLMAX6"] = 0.5*parameters["num_pixels"]
tbhdu.header["TLMIN7"] = -0.5*parameters["num_pixels"]
tbhdu.header["TLMAX7"] = 0.5*parameters["num_pixels"]
tbhdu.header["EXPOSURE"] = parameters["exposure_time"]
tbhdu.header["TSTART"] = 0.0
tbhdu.header["TSTOP"] = parameters["exposure_time"]
tbhdu.header["HDUVERS"] = "1.1.0"
tbhdu.header["RADECSYS"] = "FK5"
tbhdu.header["EQUINOX"] = 2000.0
tbhdu.header["HDUCLASS"] = "OGIP"
tbhdu.header["HDUCLAS1"] = "EVENTS"
tbhdu.header["HDUCLAS2"] = "ACCEPTED"
tbhdu.header["DATE"] = t_begin.tt.isot
tbhdu.header["DATE-OBS"] = t_begin.tt.isot
tbhdu.header["DATE-END"] = t_end.tt.isot
tbhdu.header["RESPFILE"] = os.path.split(parameters["rmf"])[-1]
tbhdu.header["PHA_BINS"] = parameters["nchan"]
tbhdu.header["ANCRFILE"] = os.path.split(parameters["arf"])[-1]
tbhdu.header["CHANTYPE"] = parameters["channel_type"]
tbhdu.header["MISSION"] = parameters["mission"]
tbhdu.header["TELESCOP"] = parameters["telescope"]
tbhdu.header["INSTRUME"] = parameters["instrument"]
tbhdu.header["RA_PNT"] = parameters["sky_center"][0]
tbhdu.header["DEC_PNT"] = parameters["sky_center"][1]
tbhdu.header["ROLL_PNT"] = parameters["roll_angle"]
tbhdu.header["AIMPT_X"] = parameters["aimpt_coords"][0]
tbhdu.header["AIMPT_Y"] = parameters["aimpt_coords"][1]
if parameters["dither_params"]["dither_on"]:
tbhdu.header["DITHXAMP"] = parameters["dither_params"]["x_amp"]
tbhdu.header["DITHYAMP"] = parameters["dither_params"]["y_amp"]
tbhdu.header["DITHXPER"] = parameters["dither_params"]["x_period"]
tbhdu.header["DITHYPER"] = parameters["dither_params"]["y_period"]
start = pyfits.Column(name='START', format='1D', unit='s',
array=np.array([0.0]))
stop = pyfits.Column(name='STOP', format='1D', unit='s',
array=np.array([parameters["exposure_time"]]))
tbhdu_gti = pyfits.BinTableHDU.from_columns([start,stop])
tbhdu_gti.name = "STDGTI"
tbhdu_gti.header["TSTART"] = 0.0
tbhdu_gti.header["TSTOP"] = parameters["exposure_time"]
tbhdu_gti.header["HDUCLASS"] = "OGIP"
tbhdu_gti.header["HDUCLAS1"] = "GTI"
tbhdu_gti.header["HDUCLAS2"] = "STANDARD"
tbhdu_gti.header["RADECSYS"] = "FK5"
tbhdu_gti.header["EQUINOX"] = 2000.0
tbhdu_gti.header["DATE"] = t_begin.tt.isot
tbhdu_gti.header["DATE-OBS"] = t_begin.tt.isot
tbhdu_gti.header["DATE-END"] = t_end.tt.isot
hdulist = [pyfits.PrimaryHDU(), tbhdu, tbhdu_gti]
pyfits.HDUList(hdulist).writeto(filename, overwrite=overwrite)
def convert_time_pandasSeries(time_string, **kwargs):
return Time(time_string.tolist(), **kwargs)
def load_headers(datlines):
"""
Load the header information for each fits file
Parameters
----------
datlines : list
Input (uncommented) lines specified by the user.
datlines contains the full data path to every
raw exposure listed by the user.
Returns
-------
fitsdict : dict
The relevant header information of all fits files
"""
def generate_updates(dct, keylst, keys, whddict, headarr):
""" Generate a list of settings to be updated
"""
for (key, value) in iteritems(dct):
keys += [str(key)]
if isinstance(value, dict):
generate_updates(value, keylst, keys, whddict, headarr)
else:
try:
tfrhd = int(value.split('.')[0]) - 1
kchk = '.'.join(value.split('.')[1:])
frhd = whddict['{0:02d}'.format(tfrhd)]
hdrval = headarr[frhd][kchk]
if keys[0] not in ["check", "keyword"]:
keylst += [
str(' ').join(keys) + str(" ") +
str("{0}\n".format(hdrval).replace(" ", ""))
]
keylst[-1] = keylst[-1].split()
except (AttributeError, ValueError, KeyError):
pass
del keys[-1]
chks = settings.spect['check'].keys()
keys = settings.spect['keyword'].keys()
fitsdict = dict({'directory': [], 'filename': [], 'utc': []})
whddict = dict({})
for k in keys:
fitsdict[k] = []
allhead = []
headarr = [None for k in range(settings.spect['fits']['numhead'])]
numfiles = len(datlines)
for i in range(numfiles):
# Try to open the fits file
try:
for k in range(settings.spect['fits']['numhead']):
headarr[k] = pyfits.getheader(
datlines[i],
ext=settings.spect['fits']['headext{0:02d}'.format(k + 1)])
whddict['{0:02d}'.format(
settings.spect['fits']['headext{0:02d}'.format(k +
1)])] = k
except:
if settings.argflag['run']['setup']:
msgs.warn("Bad header in extension {0:d} of file:".format(
settings.spect['fits']['headext{0:02d}'.format(k + 1)]) +
msgs.newline() + datlines[i])
msgs.warn(
"Proceeding on the hopes this was a calibration file, otherwise consider removing."
)
else:
msgs.error("Error reading header from extension {0:d} of file:"
.format(settings.spect['fits'][
'headext{0:02d}'.format(k + 1)]) +
msgs.newline() + datlines[i])
# Save
for k in range(settings.spect['fits']['numhead']):
tmp = [head.copy() for head in headarr]
allhead.append(tmp)
# Perform checks on each fits files, as specified in the settings.instrument file.
skip = False
for ch in chks:
tfrhd = int(ch.split('.')[0]) - 1
kchk = '.'.join(ch.split('.')[1:])
frhd = whddict['{0:02d}'.format(tfrhd)]
if settings.spect['check'][ch] != str(headarr[frhd][kchk]).strip():
print(ch, frhd, kchk)
print(settings.spect['check'][ch],
str(headarr[frhd][kchk]).strip())
msgs.warn(
"The following file:" + msgs.newline() + datlines[i] +
msgs.newline() +
"is not taken with the settings.{0:s} detector".format(
settings.argflag['run']['spectrograph']) +
msgs.newline() +
"Remove this file, or specify a different settings file.")
msgs.warn("Skipping the file..")
skip = True
if skip:
numfiles -= 1
continue
# Now set the key values for each of the required keywords
dspl = datlines[i].split('/')
fitsdict['directory'].append('/'.join(dspl[:-1]) + '/')
fitsdict['filename'].append(dspl[-1])
# Attempt to load a UTC
utcfound = False
for k in range(settings.spect['fits']['numhead']):
if 'UTC' in headarr[k].keys():
utc = headarr[k]['UTC']
utcfound = True
break
elif 'UT' in headarr[k].keys():
utc = headarr[k]['UT']
utcfound = True
break
if utcfound:
fitsdict['utc'].append(utc)
else:
fitsdict['utc'].append(None)
msgs.warn("UTC is not listed as a header keyword in file:" +
msgs.newline() + datlines[i])
# Read binning-dependent detector properties here? (maybe read speed too)
#if settings.argflag['run']['spectrograph'] in ['keck_lris_blue']:
# arlris.set_det(fitsdict, headarr[k])
# Now get the rest of the keywords
for kw in keys:
if settings.spect['keyword'][kw] is None:
value = str(
'None') # This instrument doesn't have/need this keyword
else:
ch = settings.spect['keyword'][kw]
try:
tfrhd = int(ch.split('.')[0]) - 1
except ValueError:
value = ch # Keyword given a value. Only a string allowed for now
else:
frhd = whddict['{0:02d}'.format(tfrhd)]
kchk = '.'.join(ch.split('.')[1:])
try:
value = headarr[frhd][kchk]
except KeyError: # Keyword not found in header
msgs.warn(
"{:s} keyword not in header. Setting to None".
format(kchk))
value = str('None')
# Convert the input time into hours
if kw == 'time':
if settings.spect['fits']['timeunit'] == 's':
value = float(value) / 3600.0 # Convert seconds to hours
elif settings.spect['fits']['timeunit'] == 'm':
value = float(value) / 60.0 # Convert minutes to hours
elif settings.spect['fits']['timeunit'] in Time.FORMATS.keys(
): # Astropy time format
if settings.spect['fits']['timeunit'] in ['mjd']:
ival = float(value)
else:
ival = value
tval = Time(ival,
scale='tt',
format=settings.spect['fits']['timeunit'])
# dspT = value.split('T')
# dy,dm,dd = np.array(dspT[0].split('-')).astype(np.int)
# th,tm,ts = np.array(dspT[1].split(':')).astype(np.float64)
# r=(14-dm)/12
# s,t=dy+4800-r,dm+12*r-3
# jdn = dd + (153*t+2)/5 + 365*s + s/4 - 32083
# value = jdn + (12.-th)/24 + tm/1440 + ts/86400 - 2400000.5 # THIS IS THE MJD
value = tval.mjd * 24.0 # Put MJD in hours
else:
msgs.error('Bad time unit')
# Put the value in the keyword
typv = type(value)
if typv is int or typv is np.int_:
fitsdict[kw].append(value)
elif typv is float or typv is np.float_:
fitsdict[kw].append(value)
elif isinstance(value, basestring) or typv is np.string_:
fitsdict[kw].append(value.strip())
elif typv is bool or typv is np.bool_:
fitsdict[kw].append(value)
else:
msgs.bug(
"I didn't expect a useful header ({0:s}) to contain type {1:s}"
.format(kw, typv).replace('<type ', '').replace('>', ''))
msgs.info("Successfully loaded headers for file:" + msgs.newline() +
datlines[i])
# Check if any other settings require header values to be loaded
msgs.info("Checking spectrograph settings for required header information")
# Just use the header info from the last file
keylst = []
generate_updates(settings.spect.copy(), keylst, [], whddict, headarr)
# Convert the fitsdict arrays into numpy arrays
for k in fitsdict.keys():
fitsdict[k] = np.array(fitsdict[k])
msgs.info("Headers loaded for {0:d} files successfully".format(numfiles))
if numfiles != len(datlines):
msgs.warn("Headers were not loaded for {0:d} files".format(
len(datlines) - numfiles))
if numfiles == 0:
msgs.error("The headers could not be read from the input data files." +
msgs.newline() +
"Please check that the settings file matches the data.")
# Return
fitsdict['headers'] = allhead
return fitsdict, keylst
names = [
'mjd', 'sun_RA', 'sun_dec', 'sun_alt', 'sun_az', 'moon_RA', 'moon_dec',
'moon_alt', 'moon_az', 'moon_phase'
]
types = [float] * len(names)
sun_moon_info = np.zeros(mjds.size, dtype=list(zip(names, types)))
sun_moon_info['mjd'] = np.arange(mjd_start - pad_around,
duration + mjd_start + pad_around + t_step,
t_step)
site = Site('LSST')
location = EarthLocation(lat=site.latitude,
lon=site.longitude,
height=site.height)
t_sparse = Time(mjds, format='mjd', location=location)
sun = get_sun(t_sparse)
aa = AltAz(location=location, obstime=t_sparse)
sun_aa = sun.transform_to(aa)
moon = get_moon(t_sparse)
moon_aa = moon.transform_to(aa)
sun_moon_info['sun_RA'] = sun.ra.rad
sun_moon_info['sun_dec'] = sun.dec.rad
sun_moon_info['sun_alt'] = sun_aa.alt.rad
sun_moon_info['sun_az'] = sun_aa.az.rad
sun_moon_info['moon_RA'] = moon.ra.rad
def target_post_save(target, created):
def get(objectId):
url = 'https://mars.lco.global/'
request = {'queries': [{'objectId': objectId}]}
try:
r = requests.post(url, json=request)
results = r.json()['results'][0]['results']
return results
except Exception as e:
return [None, 'Error message : \n' + str(e)]
logger.info('Target post save hook: %s created: %s', target, created)
ztf_name = next((name for name in target.names if 'ZTF' in name), None)
if ztf_name:
alerts = get(ztf_name)
filters = {1: 'g_ZTF', 2: 'r_ZTF', 3: 'i_ZTF'}
for alert in alerts:
if all([
key in alert['candidate']
for key in ['jd', 'magpsf', 'fid', 'sigmapsf']
]):
jd = Time(alert['candidate']['jd'], format='jd', scale='utc')
jd.to_datetime(timezone=TimezoneInfo())
value = {
'magnitude': alert['candidate']['magpsf'],
'filter': filters[alert['candidate']['fid']],
'error': alert['candidate']['sigmapsf']
}
rd, created = ReducedDatum.objects.get_or_create(
timestamp=jd.to_datetime(timezone=TimezoneInfo()),
value=value,
source_name=target.name,
source_location=alert['lco_id'],
data_type='photometry',
target=target)
rd.save()
gaia_name = next((name for name in target.names if 'Gaia' in name), None)
if gaia_name:
base_url = 'http://gsaweb.ast.cam.ac.uk/alerts/alert'
lightcurve_url = f'{base_url}/{gaia_name}/lightcurve.csv'
response = requests.get(lightcurve_url)
data = response._content.decode('utf-8').split('\n')[2:-2]
jd = [x.split(',')[1] for x in data]
mag = [x.split(',')[2] for x in data]
for i in reversed(range(len(mag))):
try:
datum_mag = float(mag[i])
datum_jd = Time(float(jd[i]), format='jd', scale='utc')
value = {
'magnitude': datum_mag,
'filter': 'G_Gaia',
'error': 0 # for now
}
rd, created = ReducedDatum.objects.get_or_create(
timestamp=datum_jd.to_datetime(timezone=TimezoneInfo()),
value=value,
source_name=target.name,
source_location=lightcurve_url,
data_type='photometry',
target=target)
rd.save()
except:
pass
### Craig custom code starts here:
### ----------------------------------
_snex1_address = 'mysql://{}:{}@localhost:3306/supernova'.format(
os.environ['SNEX1_DB_USER'], os.environ['SNEX1_DB_PASSWORD'])
with _get_session(db_address=_snex1_address) as db_session:
Targets = _load_table('targets', db_address=_snex1_address)
Targetnames = _load_table('targetnames', db_address=_snex1_address)
if created == True:
# Insert into SNex 1 db
db_session.add(
Targets(ra0=target__ra,
dec0=target__dec,
lastmodified=target__modified,
datecreated=target__created))
db_session.add(
Targetnames(targetid=target__id,
name=target__name,
datecreated=target__created,
lastmodified=target__modified))
elif created == False:
# Update in SNex 1 db
db_session.query(Targets).filter(
target__id == Targets__id).update({
'ra0':
target__ra,
'dec0':
target__dec,
'lastmodified':
target__modified,
'datecreated':
target__created
})
db_session.add(
Targetnames(targetid=target__id,
name=target__name,
datecreated=target__created,
lastmodified=target__modified))
db_session.commit()
def refine(estimate):
crot_estimate = carrington_rotation_number(
t=Time(estimate, scale='tt', format='jd'))
dcrot = crot - crot_estimate
# Correct the estimate using a linear fraction of the Carrington rotation period
return estimate + (dcrot * _CARRINGTON_ROTATION_PERIOD)
'''A simple Newton-Raphson root finder method to solve Kepler's
equation for the eccentric anomaly.
Me: mean anomaly
ecc: eccentric anomaly '''
E = Me
for i in range(10):
E = E - (E - ecc * m.sin(E) - Me) / (1 - ecc * m.cos(E))
return E
#The epoch (in various time systems) of the given Apophis coordinates
# from Giorgini(2008), September 1 2006 midnight
epoch_JD = 2453979.5
epoch_JD2000_s = (epoch_JD - 2451545.0) * 86400
epoch_time = Time(epoch_JD, format="jd")
#Apophis coordinates, plus calculation of the other anomalies.
a = 0.9222654975186300 * au.value #in metres
e = 0.1910573105
i = 3.33132242244163 #All in DEGREES
asc_node = 204.45996801109067
a_of_p = 126.39643948747843
mean_anomaly = 61.41677858002747
eccentric_anomaly = mean_to_eccentric(m.radians(mean_anomaly), e) #in radians
true_anomaly_r = 2 * m.atan(
((1 + e) / (1 - e))**.5 * m.tan(eccentric_anomaly / 2))
true_anomaly = m.degrees(true_anomaly_r)
'''Conversion 1: TwoBodyOrbit package'''
def __init__(self, value, add_value=None, form='iso'):
self.__time = Time(value, add_value, format=form)
code = 'OH'
list_filt = {
'r cousins': 'R',
'v cousins': 'V'
}
###############################################################
f = open(arquivo, 'r')
dados = f.readlines()
f.close()
erros = np.loadtxt(table, usecols=(2, 3, 25), dtype={'names': ('ra', 'dec', 'time'), 'formats': ('f8', 'f8', 'f16')})
datasgeral = Time(erros['time'], format='jd', scale='utc')
dif = TimeDelta(60*60*6, format='sec')
g = open(output, 'w')
for i in dados:
coord = SkyCoord(i[252:280], frame='icrs', unit=(u.hourangle,u.deg))
time = np.float(i[303:320].strip())
epoch = Time(time, scale='utc', format='jd')
mag = np.float(i[79:86].strip())
filtro = i[326:348].strip().lower()
if filtro not in list_filt.keys():
list_filt[filtro] = 'NAN'
list_novo[filtro] = 'NAN'
filt = list_filt[filtro]
star = []
ra = []
dec = []
for i in range(len(ff)):
k = ff[i].split()
star.append(k[0])
ra.append(float(k[1]))
dec.append(float(k[2]))
ctime = dt.utcnow()
coord = SkyCoord(ra,
dec,
unit="deg",
frame="fk5",
obstime=Time(ctime),
location=nanten2)
planet_altaz = []
for i in planet_list:
planet_coord = get_body(i, time=Time(ctime))
planet_coord.location = nanten2
planet_altaz.append(planet_coord.altaz)
altaz = coord.transform_to(AltAz)
print("*** rising star list [deg] ***")
for i in range(len(altaz)):
if 20 < altaz[i].alt.deg < 80:
print(star[i], " " * (11 - len(star[i])), ": (az, el) = (",
round(altaz[i].az.deg, 4), ", ", round(altaz[i].alt.deg, 4), ")")
print("==============================")
for i in range(len(planet_altaz)):
@given(time_attr())
def test_can_handle_query(time):
LCClient = norh.NoRHClient()
ans1 = LCClient._can_handle_query(time, a.Instrument.norh)
assert ans1 is True
ans1 = LCClient._can_handle_query(time, a.Instrument.norh,
a.Wavelength(10*u.GHz))
assert ans1 is True
ans2 = LCClient._can_handle_query(time)
assert ans2 is False
@pytest.mark.remote_data
@pytest.mark.parametrize("wave", [a.Wavelength(17*u.GHz), a.Wavelength(34*u.GHz)])
@given(time=range_time(Time('1992-6-1')))
@settings(max_examples=2, deadline=50000)
def test_query(time, wave):
LCClient = norh.NoRHClient()
qr1 = LCClient.search(time, a.Instrument.norh, wave)
assert isinstance(qr1, QueryResponse)
# Not all hypothesis queries are going to produce results, and
if qr1:
# There are no observations everyday
# so the results found have to be equal or later than the queried time
# (looking at the date because it may search for miliseconds, but only date is available)
assert qr1.time_range().start.strftime('%Y-%m-%d') >= time.start.strftime('%Y-%m-%d')
# and the end time equal or smaller.
# hypothesis can give same start-end, but the query will give you from start to end (so +1)
assert qr1.time_range().end <= time.end + TimeDelta(1*u.day)
def calc_phasecenter_from_solxy(vis,
timerange='',
xycen=None,
usemsphacenter=True):
'''
return the phase center in RA and DEC of a given solar coordinates
:param vis: input measurement sets file
:param timerange: can be a string or astropy.time.core.Time object, or a 2-element list of string or Time object
:param xycen: solar x-pos and y-pos in arcsec
:param usemsphacenter:
:return:
phasecenter
midtim: mid time of the given timerange
'''
tb.open(vis + '/POINTING')
tst = Time(tb.getcell('TIME_ORIGIN', 0) / 24. / 3600., format='mjd')
ted = Time(tb.getcell('TIME_ORIGIN',
tb.nrows() - 1) / 24. / 3600.,
format='mjd')
tb.close()
datstr = tst.iso[:10]
if isinstance(timerange, Time):
try:
(sttim, edtim) = timerange
except:
sttim = timerange
edtim = sttim
else:
if timerange == '':
sttim = tst
edtim = ted
else:
try:
(tstart, tend) = timerange.split('~')
if tstart[2] == ':':
sttim = Time(datstr + 'T' + tstart)
edtim = Time(datstr + 'T' + tend)
# timerange = '{0}/{1}~{0}/{2}'.format(datstr.replace('-', '/'), tstart, tend)
else:
sttim = Time(qa.quantity(tstart, 'd')['value'],
format='mjd')
edtim = Time(qa.quantity(tend, 'd')['value'], format='mjd')
except:
try:
if timerange[2] == ':':
sttim = Time(datstr + 'T' + timerange)
edtim = sttim
else:
sttim = Time(qa.quantity(timerange, 'd')['value'],
format='mjd')
edtim = sttim
except ValueError:
print("keyword 'timerange' in wrong format")
ms.open(vis)
metadata = ms.metadata()
observatory = metadata.observatorynames()[0]
ms.close()
midtim_mjd = (sttim.mjd + edtim.mjd) / 2.
midtim = Time(midtim_mjd, format='mjd')
eph = read_horizons(t0=midtim)
if observatory == 'EOVSA' or (not usemsphacenter):
print('This is EOVSA data')
# use RA and DEC from FIELD ID 0
tb.open(vis + '/FIELD')
phadir = tb.getcol('PHASE_DIR').flatten()
tb.close()
ra0 = phadir[0]
dec0 = phadir[1]
else:
ra0 = eph['ra'][0]
dec0 = eph['dec'][0]
if not xycen:
# use solar disk center as default
phasecenter = 'J2000 ' + str(ra0) + 'rad ' + str(dec0) + 'rad'
else:
x0 = np.radians(xycen[0] / 3600.)
y0 = np.radians(xycen[1] / 3600.)
p0 = np.radians(eph['p0'][0]) # p angle in radians
raoff = -((x0) * np.cos(p0) - y0 * np.sin(p0)) / np.cos(eph['dec'][0])
decoff = (x0) * np.sin(p0) + y0 * np.cos(p0)
newra = ra0 + raoff
newdec = dec0 + decoff
phasecenter = 'J2000 ' + str(newra) + 'rad ' + str(newdec) + 'rad'
return phasecenter, midtim
def init_times():
"""Generates the initial times"""
return Time("2020-04-10T00:00:00", scale="utc") + np.arange(1, 4) * TimeDelta(
1, format="jd"
)
# Copyright (C) 2020 Egemen Imre
#
# Licensed under GNU GPL v3.0. See LICENSE.rst for more info.
"""
Test `TimeInterval` class and associated methods and functionalities.
"""
import numpy as np
import pytest
from astropy import units as u
from astropy.time import Time, TimeDelta
from satmad.utils.timeinterval import _EPS_TIME, TimeInterval, TimeIntervalList
before = TimeInterval(
Time("2020-04-09T00:00:00", scale="utc"),
Time("2020-04-11T00:00:00", scale="utc"),
end_inclusive=False,
)
within = TimeInterval(
Time("2020-04-11T00:05:00", scale="utc"), Time("2020-04-11T00:08:00", scale="utc")
)
intersect = TimeInterval(
Time("2020-04-10T00:00:00", scale="utc"), Time("2020-04-11T00:08:00", scale="utc")
)
exact = TimeInterval(
Time("2020-04-11T00:00:00", scale="utc"), Time("2020-04-11T00:10:00", scale="utc")
)
after = TimeInterval(
Time("2020-04-11T00:10:00", scale="utc"), Time("2020-04-12T00:00:00", scale="utc")
)
def simulate_a_telescope(name,
altitude,
longitude,
latitude,
filter,
time_start,
time_end,
sampling,
event,
location,
bad_weather_percentage=0.0,
minimum_alt=20,
moon_windows_avoidance=20,
maximum_moon_illumination=100.0):
""" Simulate a telescope. More details in the telescopes module. The observations simulation are made for the
full time windows, then limitation are applied :
- Sun has to be below horizon : Sun< -18
- Moon has to be more than the moon_windows_avoidance distance from the target
- Observations altitude of the target have to be bigger than minimum_alt
:param str name: the name of the telescope.
:param float altitude: the altitude in meters if the telescope
:param float longitude: the longitude in degree of the telescope location
:param float latitude: the latitude in degree of the telescope location
:param str filter: the filter used for observations
:param float time_start: the start of observations in JD
:param float time_end: the end of observations in JD
:param float sampling: the hour sampling.
:param object event: the microlensing event you look at
:param str location: the location of the telescope. If it is 'Space', then the observations are made
continuously given the observing windows and the sampling.
:param float bad_weather_percentage: the percentage of bad nights
:param float minimum_alt: the minimum altitude ini degrees that your telescope can go to.
:param float moon_windows_avoidance: the minimum distance in degrees accepted between the target and the Moon
:param float maximum_moon_illumination: the maximum Moon brightness you allow in percentage
:return: a telescope object
:rtype: object
"""
# fake lightcurve
if location != 'Space':
earth_location = EarthLocation(lon=longitude * astropy.units.deg,
lat=latitude * astropy.units.deg,
height=altitude * astropy.units.m)
target = SkyCoord(event.ra, event.dec, unit='deg')
minimum_sampling = min(4.0, sampling)
ratio_sampling = np.round(sampling / minimum_sampling)
time_of_observations = time_simulation(time_start, time_end,
minimum_sampling,
bad_weather_percentage)
time_convertion = Time(time_of_observations, format='jd').isot
telescope_altaz = target.transform_to(
AltAz(obstime=time_convertion, location=earth_location))
altazframe = AltAz(obstime=time_convertion, location=earth_location)
Sun = get_sun(Time(time_of_observations,
format='jd')).transform_to(altazframe)
Moon = get_moon(Time(time_of_observations,
format='jd')).transform_to(altazframe)
Moon_illumination = moon_illumination(Sun, Moon)
Moon_separation = target.separation(Moon)
observing_windows = np.where(
(telescope_altaz.alt > minimum_alt * astropy.units.deg)
& (Sun.alt < -18 * astropy.units.deg)
& (Moon_separation > moon_windows_avoidance * astropy.units.deg)
& (Moon_illumination < maximum_moon_illumination))[0]
time_of_observations = time_of_observations[observing_windows]
else:
time_of_observations = np.arange(time_start, time_end,
sampling / (24.0))
lightcurveflux = np.ones((len(time_of_observations), 3)) * 42
lightcurveflux[:, 0] = time_of_observations
telescope = telescopes.Telescope(name=name,
camera_filter=filter,
light_curve_flux=lightcurveflux)
return telescope
def jd_to_date(jd):
time = Time(jd, scale='utc', format='jd')
return time.isot
def convert_time_npdatetime64(time_string, **kwargs):
return Time(str(time_string.astype('M8[ns]')), **kwargs)
def moon_table(site, solar_midnight, utc, lst, verbose = False):
"""
Compute Moon data for scheduling period and return '~astropy.table' object.
Example Table
-------------
>>> import astropy.units as u
>>> from astroplan import Observer
>>> site = Observer.at_site('gemini_south')
>>> start = '2018-07-01'
>>> utc_to_local = -4 * u.h
>>> timedata = timetable(site, start, utc_to_local)
>>> print(moon_table(site, timetable['solar_midnight'].data, timetable['utc'].data, timetable['lst'].data))
fraction phase ra_mid dec_mid ra [118] dec [118]
rad deg deg deg deg
--------------- ------------- ------------- ------------- ---------------------------- --------------------------
0.0180504202392 2.87207394213 129.042250359 18.8745316663 124.46942338 .. 133.95157917 19.7627882458 .. 18.410637...
ZD [118] HA [118] AZ [118]
deg hourangle rad
------------------------------ ------------------------------- ------------------------------
...91.7509852667 .. 118.682184103 5.35237289874 .. -7.54773653324 5.09386841498 .. 1.47422033296
Parameters
----------
site : '~astroplan.Observer'
observatory site object
solar_midnight : '~astropy.time.core.Time' array
Solar midnight times for nights in scheduling period.
utc : 'astropy.time.ore.Time' arrays
UTC time grids for nights in scheduling period in format accepted by '~astropy.time'.
lst : arrays of floats
local sidereal time hour angles along time grids of nights in scheduling period.
Returns
-------
'~astropy.table.Table'
Table of Moon data with rows corresponding to nights in scheduling period.
Columns
-------
fraction : float
fraction of moon illuminated at solar midnight on nights of scheduling period.
phase : float (with radian table quantity)
moon phase angle at solar midnight on nights of scheduling period.
ra_mid : float (with degree table quantity)
right ascension at solar midnight on nights of scheduling period.
dec_mid : float (with degree table quantity)
declination at solar midnight on nights of scheduling period.
ra : arrays of float (with degree table quantity)
right ascensions along time grids.
dec : arrays of float (with degree table quantity)
declinations along time grids.
ZD : arrays of float (with degree table quantity)
zenith distances along time grids.
HA : arrays of float (with hourangle table quantity)
hour angles along time grids.
AZ : arrays of float (with radian table quantity)
azimuth angles along time grids.
AM : arrays of float
air masses along time grids.
"""
i_day = np.arange(len(solar_midnight))
# sun_horiz = sun_horizon(site) # angle from zenith at rise/set
# set = Column(Parallel(n_jobs=10)(delayed(get_moon_set_time)
# (site, solar_midnight[i], horizon=sun_horiz) for i in i_day), name='set')
# rise = Column(Parallel(n_jobs=10)(delayed(get_moon_rise_time)
# (site, solar_midnight[i], horizon=sun_horiz) for i in i_day), name='rise')
ncpu = cpu_count()
fraction = Column(Parallel(n_jobs=ncpu)(delayed(get_moon_fraction)(site, solar_midnight[i]) for i in i_day),
name='fraction')
phase = Column(Parallel(n_jobs=ncpu)(delayed(get_moon_phase)(site, solar_midnight[i], degree=True) for i in i_day), name='phase',
unit='deg')
moon_midnight = Parallel(n_jobs=ncpu)(delayed(get_moon)(solar_midnight[i], location=site.location) for i in i_day)
ra_mid = Column([moon_midnight[i].ra.value for i in i_day], name='ra_mid', unit='deg')
dec_mid = Column([moon_midnight[i].dec.value for i in i_day], name='dec_mid', unit='deg')
moon = Parallel(n_jobs=ncpu)(delayed(get_moon)(Time(utc[i]), location=site.location) for i in i_day)
ra = Column([moon[i].ra.value for i in i_day], name='ra', unit='deg')
dec = Column([moon[i].dec.value for i in i_day], name='dec', unit='deg')
ZDHAAZ = Parallel(n_jobs=ncpu)(delayed(calc_zd_ha_az)(lst=lst[i]*u.hourangle, latitude=site.location.lat,
ra=moon[i].ra, dec=moon[i].dec) for i in i_day)
ZD = Column([ZDHAAZ[i][0].value for i in i_day], name='ZD', unit='deg')
HA = Column([ZDHAAZ[i][1].value for i in i_day], name='HA', unit='hourangle')
AZ = Column([ZDHAAZ[i][2].value for i in i_day], name='AZ', unit='deg')
AM = Column([airmass(ZDHAAZ[i][0]) for i in i_day], name='AM')
if verbose:
print('i_day', i_day)
# print(set)
# print(rise)
print(fraction)
print(phase)
print(ra_mid)
print(dec_mid)
print(ra)
print(dec)
print(ZD)
print(HA)
print(AZ)
return Table((fraction, phase, ra_mid, dec_mid, ra, dec, ZD, HA, AZ, AM))
def convert_time_date(time_string, **kwargs):
return Time(time_string.isoformat(), **kwargs)
def convert_time_npndarray(time_string, **kwargs):
if 'datetime64' in str(time_string.dtype):
return Time([str(dt.astype('M8[ns]')) for dt in time_string], **kwargs)
else:
return convert_time.dispatch(object)(time_string, **kwargs)
def read_horizons(t0=None,
dur=None,
vis=None,
observatory=None,
verbose=False):
'''
This function visits JPL Horizons to retrieve J2000 topocentric RA and DEC of the solar disk center
as a function of time.
Keyword arguments:
t0: Referece time in astropy.Time format
dur: duration of the returned coordinates. Default to 2 minutes
vis: CASA visibility dataset (in measurement set format). If provided, use entire duration from
the visibility data
observatory: observatory code (from JPL Horizons). If not provided, use information from visibility.
if no visibility found, use earth center (code=500)
verbose: True to provide extra information
Usage:
>>> from astropy.time import Time
>>> out = read_horizons(t0=Time('2017-09-10 16:00:00'), observatory='-81')
>>> out = read_horizons(vis = 'mydata.ms')
History:
BC (sometime in 2014): function was first wrote, followed by a number of edits by BC and SY
BC (2019-07-16): Added docstring documentation
'''
import urllib2
import ssl
if not t0 and not vis:
t0 = Time.now()
if not dur:
dur = 1. / 60. / 24. # default to 2 minutes
if t0:
try:
btime = Time(t0)
except:
print('input time ' + str(t0) + ' not recognized')
return -1
if vis:
if not os.path.exists(vis):
print('Input ms data ' + vis + ' does not exist! ')
return -1
try:
# ms.open(vis)
# summary = ms.summary()
# ms.close()
# btime = Time(summary['BeginTime'], format='mjd')
# etime = Time(summary['EndTime'], format='mjd')
## alternative way to avoid conflicts with importeovsa, if needed -- more time consuming
if observatory == 'geocentric':
observatory = '500'
else:
ms.open(vis)
metadata = ms.metadata()
if metadata.observatorynames()[0] == 'EVLA':
observatory = '-5'
elif metadata.observatorynames()[0] == 'EOVSA':
observatory = '-81'
elif metadata.observatorynames()[0] == 'ALMA':
observatory = '-7'
ms.close()
tb.open(vis)
btime_vis = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd')
etime_vis = Time(tb.getcell('TIME',
tb.nrows() - 1) / 24. / 3600.,
format='mjd')
tb.close()
if verbose:
print("Beginning time of this scan " + btime_vis.iso)
print("End time of this scan " + etime_vis.iso)
# extend the start and end time for jpl horizons by 0.5 hr on each end
btime = Time(btime_vis.mjd - 0.5 / 24., format='mjd')
dur = etime_vis.mjd - btime_vis.mjd + 1.0 / 24.
except:
print('error in reading ms file: ' + vis +
' to obtain the ephemeris!')
return -1
# default the observatory to geocentric, if none provided
if not observatory:
observatory = '500'
etime = Time(btime.mjd + dur, format='mjd')
try:
cmdstr = "https://ssd.jpl.nasa.gov/horizons_batch.cgi?batch=1&TABLE_TYPE='OBSERVER'&QUANTITIES='1,17,20'&CSV_FORMAT='YES'&ANG_FORMAT='DEG'&CAL_FORMAT='BOTH'&SOLAR_ELONG='0,180'&CENTER='{}@399'&COMMAND='10'&START_TIME='".format(
observatory
) + btime.iso.replace(
' ', ','
) + "'&STOP_TIME='" + etime.iso[:-4].replace(
' ', ','
) + "'&STEP_SIZE='1m'&SKIP_DAYLT='NO'&EXTRA_PREC='YES'&APPARENT='REFRACTED'"
cmdstr = cmdstr.replace("'", "%27")
try:
context = ssl._create_unverified_context()
f = urllib2.urlopen(cmdstr, context=context)
except:
f = urllib2.urlopen(cmdstr)
lines = f.readlines()
f.close()
except:
# todo use geocentric coordinate for the new VLA data
import requests, collections
params = collections.OrderedDict()
params['batch'] = '1'
params['TABLE_TYPE'] = "'OBSERVER'"
params['QUANTITIES'] = "'1,17,20'"
params['CSV_FORMAT'] = "'YES'"
params['ANG_FORMAT'] = "'DEG'"
params['CAL_FORMAT'] = "'BOTH'"
params['SOLAR_ELONG'] = "'0,180'"
if observatory == '500':
params['CENTER'] = "'500'"
else:
params['CENTER'] = "'{}@399'".format(observatory)
params['COMMAND'] = "'10'"
params['START_TIME'] = "'{}'".format(btime.iso[:-4].replace(' ', ','))
params['STOP_TIME'] = "'{}'".format(etime.iso[:-4].replace(' ', ','))
params['STEP_SIZE'] = "'1m'"
params['SKIP_DAYLT'] = "'NO'"
params['EXTRA_PREC'] = "'YES'"
params['APPAENT'] = "'REFRACTED'"
results = requests.get("https://ssd.jpl.nasa.gov/horizons_batch.cgi",
params=params)
lines = [ll for ll in results.iter_lines()]
nline = len(lines)
istart = 0
for i in range(nline):
line = lines[i]
if line[0:5] == '$$SOE': # start recording
istart = i + 1
if line[0:5] == '$$EOE': # end recording
iend = i
newlines = lines[istart:iend]
nrec = len(newlines)
ephem_ = []
t = []
ra = []
dec = []
p0 = []
delta = []
for line in newlines:
items = line.split(',')
t.append(Time(float(items[1]), format='jd').mjd)
ra.append(np.radians(float(items[4])))
dec.append(np.radians(float(items[5])))
p0.append(float(items[6]))
delta.append(float(items[8]))
# convert list of dictionary to a dictionary of arrays
ephem = {'time': t, 'ra': ra, 'dec': dec, 'p0': p0, 'delta': delta}
return ephem
def convert_time_tuple(time_string, **kwargs):
# Make sure there are enough values to unpack
time_string = (time_string + (0, ) * 7)[:7]
return Time('{}-{}-{}T{}:{}:{}.{:06}'.format(*time_string), **kwargs)
def _today():
# Get current day in scale='tai' without going through a scale change
# (so we do not need leap seconds).
s = '{0.year:04d}-{0.month:02d}-{0.day:02d}'.format(datetime.utcnow())
return Time(s, scale='tai', format='iso', out_subfmt='date')
def convert_time_datetime(time_string, **kwargs):
return Time(time_string, **kwargs)
roots = np.apply_along_axis(
np.roots, 0, [r3coeff, r2coeff, hip_data['Plx'] / eplx2, -1 / eplx2])
roots[np.logical_or(np.real(roots) < 0.0,
abs(np.imag(roots)) > 1.0e-6)] = np.nan
parallax_distance = np.nanmin(np.real(roots), 0) * 1000
# prefer cluster distances (e_Dist NULL), otherwise use computed distance
is_cluster_distance = np.logical_and(np.logical_not(hip_data['Dist'].mask),
hip_data['e_Dist'].mask)
hip_data['r_est'] = np.where(is_cluster_distance, hip_data['Dist'],
parallax_distance)
hip_data['r_est'].unit = u.pc
HIP_TIME = Time('J1991.25')
GAIA_TIME = Time('J2015.5')
def update_coordinates(hip_data: Table) -> None:
"""Update the coordinates from J1991.25 to J2015.5 to match Gaia."""
print('Updating coordinates to J2015.5')
coords = SkyCoord(frame=ICRS,
ra=hip_data['RAdeg'],
dec=hip_data['DEdeg'],
pm_ra_cosdec=hip_data['pmRA'],
pm_dec=hip_data['pmDE'],
distance=hip_data['r_est'],
radial_velocity=hip_data['RV'].filled(0),
obstime=HIP_TIME).apply_space_motion(GAIA_TIME)
def convert_time_pandasDatetimeIndex(time_string, **kwargs):
return Time(time_string.tolist(), **kwargs)
from astropy import units as u
from astropy.time import Time
import matplotlib.pyplot as plt
# %%
# YAML representation
# -------------------
# Here is an example YAML file using the model:
from gammapy.modeling.models import (
ExpDecayTemporalModel,
Models,
PowerLawSpectralModel,
SkyModel,
)
t0 = "5 h"
t_ref = Time("2020-10-01")
time_range = [t_ref, t_ref + 1 * u.d]
expdecay_model = ExpDecayTemporalModel(t_ref=t_ref.mjd * u.d, t0=t0)
expdecay_model.plot(time_range)
plt.grid(which="both")
model = SkyModel(
spectral_model=PowerLawSpectralModel(),
temporal_model=expdecay_model,
name="expdecay_model",
)
models = Models([model])
print(models.to_yaml())
def imreg(vis=None,
ephem=None,
msinfo=None,
imagefile=None,
timerange=None,
reftime=None,
fitsfile=None,
beamfile=None,
offsetfile=None,
toTb=None,
sclfactor=1.0,
verbose=False,
p_ang=False,
overwrite=True,
usephacenter=True,
deletehistory=False,
subregion=[],
docompress=False):
'''
main routine to register CASA images
Required Inputs:
vis: STRING. CASA measurement set from which the image is derived
imagefile: STRING or LIST. name of the input CASA image
timerange: STRING or LIST. timerange used to generate the CASA image, must have the same length as the input images.
Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00~2012/03/03/13:00:00'
Optional Inputs:
msinfo: DICTIONARY. CASA MS information, output from read_msinfo. If not provided, generate one from the supplied vis
ephem: DICTIONARY. solar ephem, output from read_horizons.
If not provided, query JPL Horizons based on time info of the vis (internet connection required)
fitsfile: STRING or LIST. name of the output registered fits files
reftime: STRING or LIST. Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00'
offsetfile: optionally provide an offset with a series of solar x and y offsets with timestamps
toTb: Bool. Convert the default Jy/beam to brightness temperature?
sclfactor: scale the image values up by its value (to compensate VLA 20 dB attenuator)
verbose: Bool. Show more diagnostic info if True.
usephacenter: Bool -- if True, correct for the RA and DEC in the ms file based on solar empheris.
Otherwise assume the phasecenter is correctly pointed to the solar disk center
(EOVSA case)
subregion: Region selection. See 'help par.region' for details.
Usage:
>>> from suncasa.utils import helioimage2fits as hf
>>> hf.imreg(vis='mydata.ms', imagefile='myimage.image', fitsfile='myimage.fits',
timerange='2017/08/21/20:21:10~2017/08/21/20:21:18')
The output fits file is 'myimage.fits'
History:
BC (sometime in 2014): function was first wrote, followed by a number of edits by BC and SY
BC (2019-07-16): Added checks for stokes parameter. Verified that for converting from Jy/beam to brightness temperature,
the convention of 2*k_b*T should always be used. I.e., for unpolarized source, stokes I, RR, LL, XX, YY,
etc. in the output CASA images from (t)clean should all have same values of radio intensity
(in Jy/beam) and brightness temperature (in K).
'''
ia = iatool()
if deletehistory:
ms_clearhistory(vis)
if not imagefile:
raise ValueError('Please specify input image')
if not timerange:
raise ValueError('Please specify timerange of the input image')
if type(imagefile) == str:
imagefile = [imagefile]
if type(timerange) == str:
timerange = [timerange]
if not fitsfile:
fitsfile = [img + '.fits' for img in imagefile]
if type(fitsfile) == str:
fitsfile = [fitsfile]
nimg = len(imagefile)
if len(timerange) != nimg:
raise ValueError(
'Number of input images does not equal to number of timeranges!')
if len(fitsfile) != nimg:
raise ValueError(
'Number of input images does not equal to number of output fits files!'
)
nimg = len(imagefile)
if verbose:
print(str(nimg) + ' images to process...')
if reftime: # use as reference time to find solar disk RA and DEC to register the image, but not the actual timerange associated with the image
if type(reftime) == str:
reftime = [reftime] * nimg
if len(reftime) != nimg:
raise ValueError(
'Number of reference times does not match that of input images!'
)
helio = ephem_to_helio(vis,
ephem=ephem,
msinfo=msinfo,
reftime=reftime,
usephacenter=usephacenter)
else:
# use the supplied timerange to register the image
helio = ephem_to_helio(vis,
ephem=ephem,
msinfo=msinfo,
reftime=timerange,
usephacenter=usephacenter)
if toTb:
(bmajs, bmins, bpas, beamunits,
bpaunits) = getbeam(imagefile=imagefile, beamfile=beamfile)
for n, img in enumerate(imagefile):
if verbose:
print('processing image #' + str(n) + ' ' + img)
fitsf = fitsfile[n]
timeran = timerange[n]
# obtain duration of the image as FITS header exptime
try:
[tbg0, tend0] = timeran.split('~')
tbg_d = qa.getvalue(qa.convert(qa.totime(tbg0), 'd'))[0]
tend_d = qa.getvalue(qa.convert(qa.totime(tend0), 'd'))[0]
tdur_s = (tend_d - tbg_d) * 3600. * 24.
dateobs = qa.time(qa.quantity(tbg_d, 'd'), form='fits', prec=10)[0]
except:
print('Error in converting the input timerange: ' + str(timeran) +
'. Proceeding to the next image...')
continue
hel = helio[n]
if not os.path.exists(img):
warnings.warn('{} does not existed!'.format(img))
else:
if os.path.exists(fitsf) and not overwrite:
raise ValueError(
'Specified fits file already exists and overwrite is set to False. Aborting...'
)
else:
p0 = hel['p0']
tb.open(img + '/logtable', nomodify=False)
nobs = tb.nrows()
tb.removerows([i + 1 for i in range(nobs - 1)])
tb.close()
ia.open(img)
imr = ia.rotate(pa=str(-p0) + 'deg')
if subregion is not []:
imr = imr.subimage(region=subregion)
imr.tofits(fitsf, history=False, overwrite=overwrite)
imr.close()
imsum = ia.summary()
ia.close()
ia.done()
# construct the standard fits header
# RA and DEC of the reference pixel crpix1 and crpix2
(imra, imdec) = (imsum['refval'][0], imsum['refval'][1])
# find out the difference of the image center to the CASA phase center
# RA and DEC difference in arcseconds
ddec = degrees((imdec - hel['dec_fld'])) * 3600.
dra = degrees((imra - hel['ra_fld']) * cos(hel['dec_fld'])) * 3600.
# Convert into image heliocentric offsets
prad = -radians(hel['p0'])
dx = (-dra) * cos(prad) - ddec * sin(prad)
dy = (-dra) * sin(prad) + ddec * cos(prad)
if offsetfile:
try:
offset = np.load(offsetfile)
except:
raise ValueError(
'The specified offsetfile does not exist!')
reftimes_d = offset['reftimes_d']
xoffs = offset['xoffs']
yoffs = offset['yoffs']
timg_d = hel['reftime']
ind = bisect.bisect_left(reftimes_d, timg_d)
xoff = xoffs[ind - 1]
yoff = yoffs[ind - 1]
else:
xoff = hel['refx']
yoff = hel['refy']
if verbose:
print(
'offset of image phase center to visibility phase center (arcsec): dx={0:.2f}, dy={1:.2f}'
.format(dx, dy))
print(
'offset of visibility phase center to solar disk center (arcsec): dx={0:.2f}, dy={1:.2f}'
.format(xoff, yoff))
(crval1, crval2) = (xoff + dx, yoff + dy)
# update the fits header to heliocentric coordinates
hdu = pyfits.open(fitsf, mode='update')
hdu[0].verify('fix')
header = hdu[0].header
dshape = hdu[0].data.shape
ndim = hdu[0].data.ndim
(cdelt1,
cdelt2) = (-header['cdelt1'] * 3600., header['cdelt2'] * 3600.
) # Original CDELT1, 2 are for RA and DEC in degrees
header['cdelt1'] = cdelt1
header['cdelt2'] = cdelt2
header['cunit1'] = 'arcsec'
header['cunit2'] = 'arcsec'
header['crval1'] = crval1
header['crval2'] = crval2
header['ctype1'] = 'HPLN-TAN'
header['ctype2'] = 'HPLT-TAN'
header['date-obs'] = dateobs # begin time of the image
if not p_ang:
hel['p0'] = 0
try:
# this works for pyfits version of CASA 4.7.0 but not CASA 4.6.0
if tdur_s:
header.set('exptime', tdur_s)
else:
header.set('exptime', 1.)
header.set('p_angle', hel['p0'])
header.set(
'dsun_obs',
sun.sunearth_distance(Time(dateobs)).to(u.meter).value)
header.set(
'rsun_obs',
sun.solar_semidiameter_angular_size(Time(dateobs)).value)
header.set('rsun_ref', sun.constants.radius.value)
header.set('hgln_obs', 0.)
header.set(
'hglt_obs',
sun.heliographic_solar_center(Time(dateobs))[1].value)
except:
# this works for astropy.io.fits
if tdur_s:
header.append(('exptime', tdur_s))
else:
header.append(('exptime', 1.))
header.append(('p_angle', hel['p0']))
header.append(
('dsun_obs',
sun.sunearth_distance(Time(dateobs)).to(u.meter).value))
header.append(
('rsun_obs',
sun.solar_semidiameter_angular_size(Time(dateobs)).value))
header.append(('rsun_ref', sun.constants.radius.value))
header.append(('hgln_obs', 0.))
header.append(
('hglt_obs',
sun.heliographic_solar_center(Time(dateobs))[1].value))
# check if stokes parameter exist
exist_stokes = False
stokes_mapper = {
'I': 1,
'Q': 2,
'U': 3,
'V': 4,
'RR': -1,
'LL': -2,
'RL': -3,
'LR': -4,
'XX': -5,
'YY': -6,
'XY': -7,
'YX': -8
}
if 'CRVAL3' in header.keys():
if header['CTYPE3'] == 'STOKES':
stokenum = header['CRVAL3']
exist_stokes = True
if 'CRVAL4' in header.keys():
if header['CTYPE4'] == 'STOKES':
stokenum = header['CRVAL4']
exist_stokes = True
if exist_stokes:
stokesstr = stokes_mapper.keys()[stokes_mapper.values().index(
stokenum)]
if verbose:
print('This image is in Stokes ' + stokesstr)
else:
print(
'STOKES Information does not seem to exist! Assuming Stokes I'
)
stokenum = 1
# intensity units to brightness temperature
if toTb:
# get restoring beam info
bmaj = bmajs[n]
bmin = bmins[n]
beamunit = beamunits[n]
data = hdu[
0].data # remember the data order is reversed due to the FITS convension
keys = header.keys()
values = header.values()
# which axis is frequency?
faxis = keys[values.index('FREQ')][-1]
faxis_ind = ndim - int(faxis)
# find out the polarization of this image
k_b = qa.constants('k')['value']
c_l = qa.constants('c')['value']
# Always use 2*kb for all polarizations
const = 2. * k_b / c_l**2
if header['BUNIT'].lower() == 'jy/beam':
header['BUNIT'] = 'K'
header['BTYPE'] = 'Brightness Temperature'
for i in range(dshape[faxis_ind]):
nu = header['CRVAL' +
faxis] + header['CDELT' + faxis] * (
i + 1 - header['CRPIX' + faxis])
if header['CUNIT' + faxis] == 'KHz':
nu *= 1e3
if header['CUNIT' + faxis] == 'MHz':
nu *= 1e6
if header['CUNIT' + faxis] == 'GHz':
nu *= 1e9
if len(bmaj) > 1: # multiple (per-plane) beams
bmajtmp = bmaj[i]
bmintmp = bmin[i]
else: # one single beam
bmajtmp = bmaj[0]
bmintmp = bmin[0]
if beamunit == 'arcsec':
bmaj0 = np.radians(bmajtmp / 3600.)
bmin0 = np.radians(bmintmp / 3600.)
if beamunit == 'arcmin':
bmaj0 = np.radians(bmajtmp / 60.)
bmin0 = np.radians(bmintmp / 60.)
if beamunit == 'deg':
bmaj0 = np.radians(bmajtmp)
bmin0 = np.radians(bmintmp)
if beamunit == 'rad':
bmaj0 = bmajtmp
bmin0 = bmintmp
beam_area = bmaj0 * bmin0 * np.pi / (4. * log(2.))
factor = const * nu**2 # SI unit
jy_to_si = 1e-26
# print(nu/1e9, beam_area, factor)
factor2 = sclfactor
# if sclfactor:
# factor2 = 100.
if faxis == '3':
data[:,
i, :, :] *= jy_to_si / beam_area / factor * factor2
if faxis == '4':
data[
i, :, :, :] *= jy_to_si / beam_area / factor * factor2
header = fu.headerfix(header)
hdu.flush()
hdu.close()
if ndim - np.count_nonzero(np.array(dshape) == 1) > 3:
docompress = False
'''
Caveat: only 1D, 2D, or 3D images are currently supported by
the astropy fits compression. If a n-dimensional image data array
does not have at least n-3 single-dimensional entries,
force docompress to be False
'''
print(
'warning: The fits data contains more than 3 non squeezable dimensions. Skipping fits compression..'
)
if docompress:
fitsftmp = fitsf + ".tmp.fits"
os.system("mv {} {}".format(fitsf, fitsftmp))
hdu = pyfits.open(fitsftmp)
hdu[0].verify('fix')
header = hdu[0].header
data = hdu[0].data
fu.write_compressed_image_fits(fitsf,
data,
header,
compression_type='RICE_1',
quantize_level=4.0)
os.system("rm -rf {}".format(fitsftmp))
if deletehistory:
ms_restorehistory(vis)
return fitsfile
def read_hst_fgs_amudotrep(file=None, version=None):
"""Read HST FGS amu.rep file which contain the TVS matrices.
Parameters
----------
filepath : str
Path to file.
Returns
-------
data : dict
Dictionary that holds the file content ordered by FGS number
"""
if version is None:
version = HST_PRD_VERSION # defaults to 'Latest'
if file is None:
file = os.path.join(HST_PRD_DATA_ROOT, 'amu.rep-{}'.format(version))
# set up regular expressions
# use https://regexper.com to visualise these if required
rx_dict = {
'fgs':
re.compile(r'FGS - (?P<fgs>\d)'),
'n_cones':
re.compile(r'NUMBER OF CONES: (?P<n_cones>\d)'),
'date':
re.compile(
r'(?P<day>[ 123][0-9])-(?P<month>[A-Z][A-Z][A-Z])-(?P<year>[0-9][0-9])'
),
'cone_vector':
re.compile(r'(CONE)*(CONE VECTOR)*(CONE ANGLE)'),
'cone_vector_tel':
re.compile(r'(CONE)*(REVISED CONE VECTOR)*(PREVIOUS CONE VECTOR)'),
'tvs':
re.compile(r'(FGS TO ST TRANSFORMATION MATRICES)'),
}
data = {}
with open(file, 'r') as file_object:
line_index = 0
astropy_table_index = 0
line = file_object.readline()
while line:
# print(line)
# at each line check for a match with a regex
key, match = _parse_line(line, rx_dict)
if key == 'fgs':
fgs_number = int(match.group('fgs'))
# print('FGS {}:'.format(fgs_number))
fgs_id = 'fgs{}'.format(fgs_number)
data[fgs_id] = {}
elif key == 'n_cones':
n_cones = int(match.group('n_cones'))
elif key == 'cone_vector':
table = Table.read(file,
format='ascii.no_header',
delimiter=' ',
data_start=astropy_table_index + 2,
data_end=astropy_table_index + 2 + n_cones,
guess=False,
names=('CONE', 'X', 'Y', 'Z',
'CONE_ANGLE_DEG'))
# table.pprint()
data[fgs_id]['cone_parameters_fgs'] = table
elif key == 'cone_vector_tel':
table = Table.read(file,
format='ascii.no_header',
delimiter=' ',
data_start=astropy_table_index + 2,
data_end=astropy_table_index + 2 + n_cones,
guess=False,
names=('CONE', 'V1', 'V2', 'V3', 'V1_PREV',
'V2_PREV', 'V3_PREV'))
data[fgs_id]['cone_parameters_tel'] = table
elif key == 'tvs':
table = Table.read(file,
format='ascii.no_header',
delimiter=' ',
data_start=astropy_table_index + 2,
data_end=astropy_table_index + 2 + 3,
guess=False,
names=('NEW_1', 'NEW_2', 'NEW_3', 'OLD_1',
'OLD_2', 'OLD_3'))
# table.pprint()
data[fgs_id]['tvs_parameters'] = table
data[fgs_id]['tvs'] = np.zeros((3, 3))
data[fgs_id]['tvs_old'] = np.zeros((3, 3))
for i in range(3):
data[fgs_id]['tvs'][i, :] = [
data[fgs_id]['tvs_parameters']['NEW_{}'.format(j +
1)][i]
for j in range(3)
]
data[fgs_id]['tvs_old'][i, :] = [
data[fgs_id]['tvs_parameters']['OLD_{}'.format(j +
1)][i]
for j in range(3)
]
elif key == 'date':
match.group('day')
match.group('month')
match.group('year')
data[fgs_id]['timestamp'] = Time('20{}-{:02d}-{}'.format(
match.group('year'),
month_name_to_number(match.group('month')),
match.group('year')))
line = file_object.readline()
line_index += 1
if line.strip():
astropy_table_index += 1 # astropy.table.Table.read ignores blank lines
data['ORIGIN'] = file
data['VERSION'] = version
return data