def cirs_to_altaz(cirs_coo, altaz_frame):
if np.any(cirs_coo.obstime != altaz_frame.obstime):
# the only frame attribute for the current CIRS is the obstime, but this
# would need to be updated if a future change allowed specifying an
# Earth location algorithm or something
cirs_coo = cirs_coo.transform_to(CIRS(obstime=altaz_frame.obstime))
# we use the same obstime everywhere now that we know they're the same
obstime = cirs_coo.obstime
# if the data are UnitSphericalRepresentation, we can skip the distance calculations
is_unitspherical = (isinstance(cirs_coo.data, UnitSphericalRepresentation) or
cirs_coo.cartesian.x.unit == u.one)
if is_unitspherical:
usrepr = cirs_coo.represent_as(UnitSphericalRepresentation)
cirs_ra = usrepr.lon.to_value(u.radian)
cirs_dec = usrepr.lat.to_value(u.radian)
else:
# compute an "astrometric" ra/dec -i.e., the direction of the
# displacement vector from the observer to the target in CIRS
loccirs = altaz_frame.location.get_itrs(cirs_coo.obstime).transform_to(cirs_coo)
diffrepr = (cirs_coo.cartesian - loccirs.cartesian).represent_as(UnitSphericalRepresentation)
cirs_ra = diffrepr.lon.to_value(u.radian)
cirs_dec = diffrepr.lat.to_value(u.radian)
lon, lat, height = altaz_frame.location.to_geodetic('WGS84')
xp, yp = get_polar_motion(obstime)
# first set up the astrometry context for CIRS<->AltAz
jd1, jd2 = get_jd12(obstime, 'utc')
astrom = erfa.apio13(jd1, jd2,
get_dut1utc(obstime),
lon.to_value(u.radian), lat.to_value(u.radian),
height.to_value(u.m),
xp, yp, # polar motion
# all below are already in correct units because they are QuantityFrameAttribues
altaz_frame.pressure.value,
altaz_frame.temperature.value,
altaz_frame.relative_humidity.value,
altaz_frame.obswl.value)
az, zen, _, _, _ = erfa.atioq(cirs_ra, cirs_dec, astrom)
if is_unitspherical:
rep = UnitSphericalRepresentation(lat=u.Quantity(PIOVER2 - zen, u.radian, copy=False),
lon=u.Quantity(az, u.radian, copy=False),
copy=False)
else:
# now we get the distance as the cartesian distance from the earth
# location to the coordinate location
locitrs = altaz_frame.location.get_itrs(obstime)
distance = locitrs.separation_3d(cirs_coo)
rep = SphericalRepresentation(lat=u.Quantity(PIOVER2 - zen, u.radian, copy=False),
lon=u.Quantity(az, u.radian, copy=False),
distance=distance,
copy=False)
return altaz_frame.realize_frame(rep)
def _erfa_check(ira, idec, astrom):
"""
This function does the same thing the astropy layer is supposed to do, but
all in erfa
"""
cra, cdec = erfa.atciq(ira, idec, 0, 0, 0, 0, astrom)
az, zen, ha, odec, ora = erfa.atioq(cra, cdec, astrom)
alt = np.pi / 2 - zen
cra2, cdec2 = erfa.atoiq('A', az, zen, astrom)
ira2, idec2 = erfa.aticq(cra2, cdec2, astrom)
dct = locals()
del dct['astrom']
return dct
def _erfa_check(ira, idec, astrom):
"""
This function does the same thing the astropy layer is supposed to do, but
all in erfa
"""
cra, cdec = erfa.atciq(ira, idec, 0, 0, 0, 0, astrom)
az, zen, ha, odec, ora = erfa.atioq(cra, cdec, astrom)
alt = np.pi/2-zen
cra2, cdec2 = erfa.atoiq('A', az, zen, astrom)
ira2, idec2 = erfa.aticq(cra2, cdec2, astrom)
dct = locals()
del dct['astrom']
return dct
def cirs_to_altaz(cirs_coo, altaz_frame):
if np.any(cirs_coo.obstime != altaz_frame.obstime):
# the only frame attribute for the current CIRS is the obstime, but this
# would need to be updated if a future change allowed specifying an
# Earth location algorithm or something
cirs_coo = cirs_coo.transform_to(CIRS(obstime=altaz_frame.obstime))
# we use the same obstime everywhere now that we know they're the same
obstime = cirs_coo.obstime
# if the data are UnitSphericalRepresentation, we can skip the distance calculations
is_unitspherical = (isinstance(cirs_coo.data, UnitSphericalRepresentation)
or cirs_coo.cartesian.x.unit == u.one)
if is_unitspherical:
usrepr = cirs_coo.represent_as(UnitSphericalRepresentation)
cirs_ra = usrepr.lon.to_value(u.radian)
cirs_dec = usrepr.lat.to_value(u.radian)
else:
# compute an "astrometric" ra/dec -i.e., the direction of the
# displacement vector from the observer to the target in CIRS
loccirs = altaz_frame.location.get_itrs(
cirs_coo.obstime).transform_to(cirs_coo)
diffrepr = (
cirs_coo.cartesian -
loccirs.cartesian).represent_as(UnitSphericalRepresentation)
cirs_ra = diffrepr.lon.to_value(u.radian)
cirs_dec = diffrepr.lat.to_value(u.radian)
lon, lat, height = altaz_frame.location.to_geodetic('WGS84')
xp, yp = get_polar_motion(obstime)
# first set up the astrometry context for CIRS<->AltAz
jd1, jd2 = get_jd12(obstime, 'utc')
astrom = erfa.apio13(
jd1,
jd2,
get_dut1utc(obstime),
lon.to_value(u.radian),
lat.to_value(u.radian),
height.to_value(u.m),
xp,
yp, # polar motion
# all below are already in correct units because they are QuantityFrameAttribues
altaz_frame.pressure.value,
altaz_frame.temperature.value,
altaz_frame.relative_humidity.value,
altaz_frame.obswl.value)
az, zen, _, _, _ = erfa.atioq(cirs_ra, cirs_dec, astrom)
if is_unitspherical:
rep = UnitSphericalRepresentation(lat=u.Quantity(PIOVER2 - zen,
u.radian,
copy=False),
lon=u.Quantity(az,
u.radian,
copy=False),
copy=False)
else:
# now we get the distance as the cartesian distance from the earth
# location to the coordinate location
locitrs = altaz_frame.location.get_itrs(obstime)
distance = locitrs.separation_3d(cirs_coo)
rep = SphericalRepresentation(lat=u.Quantity(PIOVER2 - zen,
u.radian,
copy=False),
lon=u.Quantity(az, u.radian, copy=False),
distance=distance,
copy=False)
return altaz_frame.realize_frame(rep)