def test_regression_5085():
"""
PR #5085 was put in place to fix the following issue.
Issue: https://github.com/astropy/astropy/issues/5069
At root was the transformation of Ecliptic coordinates with
non-scalar times.
"""
times = Time(["2015-08-28 03:30", "2015-09-05 10:30", "2015-09-15 18:35"])
latitudes = Latitude([3.9807075, -5.00733806, 1.69539491] * u.deg)
longitudes = Longitude([311.79678613, 72.86626741, 199.58698226] * u.deg)
distances = u.Quantity([0.00243266, 0.0025424, 0.00271296] * u.au)
coo = GeocentricTrueEcliptic(lat=latitudes,
lon=longitudes,
distance=distances,
equinox=times)
# expected result
ras = Longitude([310.50095400, 314.67109920, 319.56507428] * u.deg)
decs = Latitude([-18.25190443, -17.1556676, -15.71616522] * u.deg)
distances = u.Quantity([1.78309901, 1.710874, 1.61326649] * u.au)
expected_result = GCRS(ra=ras,
dec=decs,
distance=distances,
obstime="J2000").cartesian.xyz
actual_result = coo.transform_to(GCRS(obstime="J2000")).cartesian.xyz
assert_quantity_allclose(expected_result, actual_result)
def termtime(daytime,daytime2,code,unit='hour'):
if unit=='hour':
times=daytime+np.linspace(0.,1.,25)*(daytime2-daytime)
elif unit=='minute':
times=daytime+np.linspace(0.,1.,61)*(daytime2-daytime)
else:
times=daytime+np.linspace(0.,1.,61)*(daytime2-daytime)
gmttimes=times-eighthours
if type=='jieqi':
diflongitudes=get_body('sun', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
else:
sunlongitudes=get_body('sun', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
moonlongitudes=get_body('moon', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
diflongitudes=(moonlongitudes-sunlongitudes)%360
difcode=diflongitudes // sec
difcode=[int(difcode[i]) for i in range(len(difcode))]
for i in range(len(difcode)-1):
if difcode[i+1]!=code:
if unit=='hour':
return termtime(times[i],times[i+1],code,"minute")
else:
if unit=='minute':
return termtime(times[i],times[i+1],code,"second")
else:
return ((code+1) % (360//sec),(times[i]+0.5*(times[i+1]-times[i])).value)
return (-1,"")
def CCTerm(start,end,type):
eighthours=TimeDelta(8*3600,format='sec')
def termtime(daytime,daytime2,code,unit='hour'):
if unit=='hour':
times=daytime+np.linspace(0.,1.,25)*(daytime2-daytime)
elif unit=='minute':
times=daytime+np.linspace(0.,1.,61)*(daytime2-daytime)
else:
times=daytime+np.linspace(0.,1.,61)*(daytime2-daytime)
gmttimes=times-eighthours
if type=='jieqi':
diflongitudes=get_body('sun', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
else:
sunlongitudes=get_body('sun', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
moonlongitudes=get_body('moon', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
diflongitudes=(moonlongitudes-sunlongitudes)%360
difcode=diflongitudes // sec
difcode=[int(difcode[i]) for i in range(len(difcode))]
for i in range(len(difcode)-1):
if difcode[i+1]!=code:
if unit=='hour':
return termtime(times[i],times[i+1],code,"minute")
else:
if unit=='minute':
return termtime(times[i],times[i+1],code,"second")
else:
return ((code+1) % (360//sec),(times[i]+0.5*(times[i+1]-times[i])).value)
return (-1,"")
start=Time(Time(start,out_subfmt='date').iso)
end=Time(Time(end,out_subfmt='date').iso)
daycount=int(round((Time(end)-Time(start)).value))
# print(start,end,daycount)
# print(daycount)
times=Time(start)+np.linspace(0.,1.,daycount+1)*(end-start+TimeDelta(3,format='sec')) # 考量潤秒，故加上3秒
times=Time(Time(times,out_subfmt='date').iso)
gmttimes=times-TimeDelta(8*3600,format='sec')
if type=='jieqi':
diflongitudes= get_body('sun', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
sec=15
else:
sunlongitudes=get_body('sun', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
moonlongitudes=get_body('moon', gmttimes, ephemeris='jpl').\
transform_to(GeocentricTrueEcliptic(equinox=gmttimes)).lon.deg
diflongitudes=(moonlongitudes-sunlongitudes)%360
sec=90
res=[]
difcode=diflongitudes // sec
difcode=[int(difcode[i]) for i in range(len(difcode))]
for i in range(len(difcode)-1):
if difcode[i]!=difcode[i+1]:
res.append(termtime(times[i],times[i+1],difcode[i],'hour'))
return res
def relative_brightness(self, position, time):
"""
Calculate the Zodiacal Light surface brightness relative to that at the ecliptic poles for a given sky position and observing time.
Args:
position: sky position(s) in the form of either an astropy.coordinates.SkyCoord
object or a string that can be converted into one.
time: time of observation in the form of either an astropy.time.Time
or a string that can be converted into one.
Returns:
rel_SB: relative sky brightness of the Zodiacal light
"""
# Convert position(s) to SkyCoord if not already one
if not isinstance(position, SkyCoord):
position = SkyCoord(position)
if len(position.shape) == 2:
shape = position.shape
else:
shape = False
# Convert time to a Time if not already one
if not isinstance(time, Time):
time = Time(time)
# Convert to ecliptic coordinates at current epoch
position = position.transform_to(GeocentricTrueEcliptic(equinox=time))
# Get position of the Sun
sun = get_sun(time).transform_to(GeocentricTrueEcliptic(equinox=time))
# Ecliptic latitude, remapped to range 0 to 180 degrees, in radians
beta = (Angle(90 * u.degree) - position.lat).radian
# Ecliptic longitude minus Sun's ecliptic longitude, remapped to
# range 0 to 360 degrees, in radians
llsun = (position.lon - sun.lon).wrap_at(360 * u.degree).radian
rl = self._spatial(beta, llsun, grid=False)
if shape:
rl = rl.reshape((shape[1], shape[0]))
rl = rl.T
return rl
def get_zodiacal_light_scale(coord, time):
"""Get the scale factor for zodiacal light compared to "high" conditions.
Estimate the ratio between the zodiacal light at a specific sky position
and time, and its "high" value, by interpolating Table 6.2 of the STIS
Instrument Manual.
Parameters
----------
coord : astropy.coordinates.SkyCoord
The coordinates of the object under observation. If the coordinates do
not specify a distance, then the object is assumed to be a fixed star
at infinite distance for the purpose of calculating its helioecliptic
position.
time : astropy.time.Time
The time of the observation.
Returns
-------
float
The zodiacal light scale factor.
References
----------
https://hst-docs.stsci.edu/stisihb/chapter-6-exposure-time-calculations/6-5-detector-and-sky-backgrounds
"""
obj = SkyCoord(coord).transform_to(GeocentricTrueEcliptic(equinox=time))
sun = get_sun(time).transform_to(GeocentricTrueEcliptic(equinox=time))
# Wrap angles and look up in table
lat = np.abs(obj.lat.deg)
lon = np.abs((obj.lon - sun.lon).wrap_at(180 * u.deg).deg)
result = _zodi_angular_dependence(np.stack((lon, lat), axis=-1))
# When interp2d encounters infinities, it returns nan. Fix that up here.
result = np.where(np.isnan(result), -np.inf, result)
# Fix up shape
if obj.isscalar:
result = result.item()
result -= _zodi_angular_dependence([180, 0]).item()
return u.mag(1).to_physical(result)
def test_regression_5085():
"""
PR #5085 was put in place to fix the following issue.
Issue: https://github.com/astropy/astropy/issues/5069
At root was the transformation of Ecliptic coordinates with
non-scalar times.
"""
times = Time(["2015-08-28 03:30", "2015-09-05 10:30", "2015-09-15 18:35"])
latitudes = Latitude([3.9807075, -5.00733806, 1.69539491]*u.deg)
longitudes = Longitude([311.79678613, 72.86626741, 199.58698226]*u.deg)
distances = u.Quantity([0.00243266, 0.0025424, 0.00271296]*u.au)
coo = GeocentricTrueEcliptic(lat=latitudes,
lon=longitudes,
distance=distances, equinox=times)
# expected result
ras = Longitude([310.50095400, 314.67109920, 319.56507428]*u.deg)
decs = Latitude([-18.25190443, -17.1556676, -15.71616522]*u.deg)
distances = u.Quantity([1.78309901, 1.710874, 1.61326649]*u.au)
expected_result = GCRS(ra=ras, dec=decs,
distance=distances, obstime="J2000").cartesian.xyz
actual_result = coo.transform_to(GCRS(obstime="J2000")).cartesian.xyz
assert_quantity_allclose(expected_result, actual_result)
def apparent_latitude(t='now'):
"""
Returns the Sun's apparent latitude, referred to the true equinox of date. Corrections for
nutation and aberration (for Earth motion) are included.
Parameters
----------
t : {parse_time_types}
Time to use in a parse-time-compatible format
"""
time = parse_time(t)
sun = SkyCoord(0*u.deg, 0*u.deg, 0*u.AU, frame='hcrs', obstime=time)
coord = sun.transform_to(GeocentricTrueEcliptic(equinox=time))
# Astropy's GeocentricTrueEcliptic includes both aberration and nutation
lat = coord.lat
return Latitude(lat)
def apparent_longitude(t='now'):
"""
Returns the Sun's apparent longitude, referred to the true equinox of date. Corrections for
nutation and aberration (for Earth motion) are included.
Parameters
----------
t : {parse_time_types}
Time to use in a parse-time-compatible format
Notes
-----
The nutation model is IAU 2000A nutation with adjustments to match IAU 2006 precession.
"""
time = parse_time(t)
sun = SkyCoord(0*u.deg, 0*u.deg, 0*u.AU, frame='hcrs', obstime=time)
coord = sun.transform_to(GeocentricTrueEcliptic(equinox=time))
# Astropy's GeocentricTrueEcliptic includes both aberration and nutation
lon = coord.lon
return Longitude(lon)
def accumoon(time, obs) : # ,geolat,lst) :
# More accurate (but more elaborate and slower) lunar
# ephemeris, from Jean Meeus' *Astronomical Formulae For Calculators*,
# pub. Willman-Bell. Includes all the terms given there. */
# a run of comparisons every 3 days through 2018 shows that this
# agrees with the more accurate astropy positions with an RMS of
# 0.007 degrees.
time_tt = time.tt # important to use correct time argument for this!!
T = (time_tt.jd - 2415020.) / 36525. # this based around 1900 ... */
Tsq = T * T;
Tcb = Tsq * T;
Lpr = 270.434164 + 481267.8831 * T - 0.001133 * Tsq + 0.0000019 * Tcb
M = 358.475833 + 35999.0498*T - 0.000150*Tsq - 0.0000033*Tcb
Mpr = 296.104608 + 477198.8491*T + 0.009192*Tsq + 0.0000144*Tcb
D = 350.737486 + 445267.1142*T - 0.001436 * Tsq + 0.0000019*Tcb
F = 11.250889 + 483202.0251*T -0.003211 * Tsq - 0.0000003*Tcb
Om = 259.183275 - 1934.1420*T + 0.002078*Tsq + 0.0000022*Tcb
Lpr = Lpr % 360.
Mpr = Mpr % 360.
M = M % 360.
D = D % 360.
F = F % 360.
Om = Om % 360.
sinx = np.sin(np.deg2rad(51.2 + 20.2 * T))
Lpr = Lpr + 0.000233 * sinx
M = M - 0.001778 * sinx
Mpr = Mpr + 0.000817 * sinx
D = D + 0.002011 * sinx
sinx = 0.003964 * np.sin(np.deg2rad(346.560+132.870*T -0.0091731*Tsq))
Lpr = Lpr + sinx;
Mpr = Mpr + sinx;
D = D + sinx;
F = F + sinx;
sinx = np.sin(np.deg2rad(Om))
Lpr = Lpr + 0.001964 * sinx
Mpr = Mpr + 0.002541 * sinx
D = D + 0.001964 * sinx
F = F - 0.024691 * sinx
F = F - 0.004328 * np.sin(np.deg2rad(Om + 275.05 -2.30*T))
e = 1 - 0.002495 * T - 0.00000752 * Tsq;
M = np.deg2rad(M) # these will all be arguments ... */
Mpr = np.deg2rad(Mpr)
D = np.deg2rad(D)
F = np.deg2rad(F)
lambd = Lpr + 6.288750 * np.sin(Mpr) \
+ 1.274018 * np.sin(2*D - Mpr) \
+ 0.658309 * np.sin(2*D) \
+ 0.213616 * np.sin(2*Mpr) \
- e * 0.185596 * np.sin(M) \
- 0.114336 * np.sin(2*F) \
+ 0.058793 * np.sin(2*D - 2*Mpr) \
+ e * 0.057212 * np.sin(2*D - M - Mpr) \
+ 0.053320 * np.sin(2*D + Mpr) \
+ e * 0.045874 * np.sin(2*D - M) \
+ e * 0.041024 * np.sin(Mpr - M) \
- 0.034718 * np.sin(D) \
- e * 0.030465 * np.sin(M+Mpr) \
+ 0.015326 * np.sin(2*D - 2*F) \
- 0.012528 * np.sin(2*F + Mpr) \
- 0.010980 * np.sin(2*F - Mpr) \
+ 0.010674 * np.sin(4*D - Mpr) \
+ 0.010034 * np.sin(3*Mpr) \
+ 0.008548 * np.sin(4*D - 2*Mpr) \
- e * 0.007910 * np.sin(M - Mpr + 2*D) \
- e * 0.006783 * np.sin(2*D + M) \
+ 0.005162 * np.sin(Mpr - D)
# /* And furthermore.....*/
lambd = lambd + e * 0.005000 * np.sin(M + D) \
+ e * 0.004049 * np.sin(Mpr - M + 2*D) \
+ 0.003996 * np.sin(2*Mpr + 2*D) \
+ 0.003862 * np.sin(4*D) \
+ 0.003665 * np.sin(2*D - 3*Mpr) \
+ e * 0.002695 * np.sin(2*Mpr - M) \
+ 0.002602 * np.sin(Mpr - 2*F - 2*D) \
+ e * 0.002396 * np.sin(2*D - M - 2*Mpr) \
- 0.002349 * np.sin(Mpr + D) \
+ e * e * 0.002249 * np.sin(2*D - 2*M) \
- e * 0.002125 * np.sin(2*Mpr + M) \
- e * e * 0.002079 * np.sin(2*M) \
+ e * e * 0.002059 * np.sin(2*D - Mpr - 2*M) \
- 0.001773 * np.sin(Mpr + 2*D - 2*F) \
- 0.001595 * np.sin(2*F + 2*D) \
+ e * 0.001220 * np.sin(4*D - M - Mpr) \
- 0.001110 * np.sin(2*Mpr + 2*F) \
+ 0.000892 * np.sin(Mpr - 3*D) \
- e * 0.000811 * np.sin(M + Mpr + 2*D) \
+ e * 0.000761 * np.sin(4*D - M - 2*Mpr) \
+ e * e * 0.000717 * np.sin(Mpr - 2*M) \
+ e * e * 0.000704 * np.sin(Mpr - 2 * M - 2*D) \
+ e * 0.000693 * np.sin(M - 2*Mpr + 2*D) \
+ e * 0.000598 * np.sin(2*D - M - 2*F) \
+ 0.000550 * np.sin(Mpr + 4*D) \
+ 0.000538 * np.sin(4*Mpr) \
+ e * 0.000521 * np.sin(4*D - M) \
+ 0.000486 * np.sin(2*Mpr - D)
B = 5.128189 * np.sin(F) \
+ 0.280606 * np.sin(Mpr + F) \
+ 0.277693 * np.sin(Mpr - F) \
+ 0.173238 * np.sin(2*D - F) \
+ 0.055413 * np.sin(2*D + F - Mpr) \
+ 0.046272 * np.sin(2*D - F - Mpr) \
+ 0.032573 * np.sin(2*D + F) \
+ 0.017198 * np.sin(2*Mpr + F) \
+ 0.009267 * np.sin(2*D + Mpr - F) \
+ 0.008823 * np.sin(2*Mpr - F) \
+ e * 0.008247 * np.sin(2*D - M - F) \
+ 0.004323 * np.sin(2*D - F - 2*Mpr) \
+ 0.004200 * np.sin(2*D + F + Mpr) \
+ e * 0.003372 * np.sin(F - M - 2*D) \
+ 0.002472 * np.sin(2*D + F - M - Mpr) \
+ e * 0.002222 * np.sin(2*D + F - M) \
+ e * 0.002072 * np.sin(2*D - F - M - Mpr) \
+ e * 0.001877 * np.sin(F - M + Mpr) \
+ 0.001828 * np.sin(4*D - F - Mpr) \
- e * 0.001803 * np.sin(F + M) \
- 0.001750 * np.sin(3*F) \
+ e * 0.001570 * np.sin(Mpr - M - F) \
- 0.001487 * np.sin(F + D) \
- e * 0.001481 * np.sin(F + M + Mpr) \
+ e * 0.001417 * np.sin(F - M - Mpr) \
+ e * 0.001350 * np.sin(F - M) \
+ 0.001330 * np.sin(F - D) \
+ 0.001106 * np.sin(F + 3*Mpr) \
+ 0.001020 * np.sin(4*D - F) \
+ 0.000833 * np.sin(F + 4*D - Mpr)
# /* not only that, but */
B = B + 0.000781 * np.sin(Mpr - 3*F) \
+ 0.000670 * np.sin(F + 4*D - 2*Mpr) \
+ 0.000606 * np.sin(2*D - 3*F) \
+ 0.000597 * np.sin(2*D + 2*Mpr - F) \
+ e * 0.000492 * np.sin(2*D + Mpr - M - F) \
+ 0.000450 * np.sin(2*Mpr - F - 2*D) \
+ 0.000439 * np.sin(3*Mpr - F) \
+ 0.000423 * np.sin(F + 2*D + 2*Mpr) \
+ 0.000422 * np.sin(2*D - F - 3*Mpr) \
- e * 0.000367 * np.sin(M + F + 2*D - Mpr) \
- e * 0.000353 * np.sin(M + F + 2*D) \
+ 0.000331 * np.sin(F + 4*D) \
+ e * 0.000317 * np.sin(2*D + F - M + Mpr) \
+ e * e * 0.000306 * np.sin(2*D - 2*M - F) \
- 0.000283 * np.sin(Mpr + 3*F)
om1 = 0.0004664 * np.cos(np.deg2rad(Om))
om2 = 0.0000754 * np.cos(np.deg2rad(Om + 275.05 - 2.30*T))
beta = B * (1. - om1 - om2);
pie = 0.950724 + 0.051818 * np.cos(Mpr) \
+ 0.009531 * np.cos(2*D - Mpr) \
+ 0.007843 * np.cos(2*D) \
+ 0.002824 * np.cos(2*Mpr) \
+ 0.000857 * np.cos(2*D + Mpr) \
+ e * 0.000533 * np.cos(2*D - M) \
+ e * 0.000401 * np.cos(2*D - M - Mpr) \
+ e * 0.000320 * np.cos(Mpr - M) \
- 0.000271 * np.cos(D) \
- e * 0.000264 * np.cos(M + Mpr) \
- 0.000198 * np.cos(2*F - Mpr) \
+ 0.000173 * np.cos(3*Mpr) \
+ 0.000167 * np.cos(4*D - Mpr) \
- e * 0.000111 * np.cos(M) \
+ 0.000103 * np.cos(4*D - 2*Mpr) \
- 0.000084 * np.cos(2*Mpr - 2*D) \
- e * 0.000083 * np.cos(2*D + M) \
+ 0.000079 * np.cos(2*D + 2*Mpr) \
+ 0.000072 * np.cos(4*D) \
+ e * 0.000064 * np.cos(2*D - M + Mpr) \
- e * 0.000063 * np.cos(2*D + M - Mpr) \
+ e * 0.000041 * np.cos(M + D) \
+ e * 0.000035 * np.cos(2*Mpr - M) \
- 0.000033 * np.cos(3*Mpr - 2*D) \
- 0.000030 * np.cos(Mpr + D) \
- 0.000029 * np.cos(2*F - 2*D) \
- e * 0.000029 * np.cos(2*Mpr + M) \
+ e * e * 0.000026 * np.cos(2*D - 2*M) \
- 0.000023 * np.cos(2*F - 2*D + Mpr) \
+ e * 0.000019 * np.cos(4*D - M - Mpr);
beta = Angle(np.deg2rad(beta), unit = u.rad)
lambd = Angle(np.deg2rad(lambd), unit = u.rad)
dist = Distance(1./np.sin(np.deg2rad(pie)) * thorconsts.EQUAT_RAD)
# place these in a skycoord in ecliptic coords of date. Handle distance
# separately since it does not transform properly for some reason.
eq = 'J%7.2f' % (2000. + (time.jd - thorconsts.J2000) / 365.25)
fr = GeocentricTrueEcliptic(equinox = eq)
inecl = SkyCoord(lon = Angle(lambd, unit=u.rad), lat = Angle(beta,unit=u.rad), frame=fr)
# Transform into geocentric equatorial.
geocen = inecl.transform_to(currentgeocentframe(time))
# Do the topo correction yourself. First form xyz coords in equatorial syst of date
x = dist * np.cos(geocen.ra) * np.cos(geocen.dec)
y = dist * np.sin(geocen.ra) * np.cos(geocen.dec)
z = dist * np.sin(geocen.dec)
# Now compute geocentric location of the observatory in a frame aligned with the
# equatorial system of date, which one can do simply by replacing the west longitude
# with the sidereal time
(xobs, yobs, zobs) = geocent(lpsidereal(time,obs),obs.lat,2000. * u.m) # don't have obs.height yet
# recenter moon's cartesian coordinates on position of obs
x = x - xobs
y = y - yobs
z = z - zobs
# form the toposcentric ra and dec and bundle them into a skycoord of epoch of date.
topodist = np.sqrt(x**2 + y**2 + z**2)
raout = np.arctan2(y,x)
decout = np.arcsin(z / topodist)
topocen = SkyCoord(raout, decout, unit = u.rad, frame = currentgeocentframe(time))
return topocen,topodist
def test_astroby_skyfield_horizons():
"""
### Astropy 與 Skyfield 取得太陽座標對照表
* 基本上，Astropy 的 get_obj 會得到從地心看太陽的 GCRS 赤道座標，對應於 Skyfield 的 earth.at(t).observe(sun).apparent()。
* Astropy 用 gcrscoord.transform_to(GeocentricTrueEcliptic(equinox = t)) 將 GCRS 赤道座標轉成真時黃道座標(true ecliptic)，
對應於 Skyfield 的 gcrscoord.frame_latlon(ecliptic_frame)。
"""
timestr = "2021-4-20 9:37"
t_astropy = Time(timestr, scale='utc')
solar_system_ephemeris.set('de430.bsp')
sun_astropy_apparent = get_body('sun', t_astropy)
t_skyfield = ts.utc(2021, 4, 20, 9, 37)
sun_skyfield_astrometric = earth.at(t_skyfield).observe(sun).radec()
sun_skyfield_apparent = earth.at(t_skyfield).observe(sun).apparent()
# print(sun_skyfield_astrometric)
print("\n比較 GCRS astrometric")
print("sun_skyfield_astrometric", sun_skyfield_astrometric[0]._degrees,
sun_skyfield_astrometric[1]._degrees, sun_skyfield_astrometric[2].km)
# 比較 GCRS
print("\n比較 GCRS apparent")
print(sun_astropy_apparent)
print('sun_astropy_apparent in (deg,deg,km) :',
sun_astropy_apparent.ra.deg, sun_astropy_apparent.dec.deg,
sun_astropy_apparent.distance.km)
radec_skyfield = sun_skyfield_apparent.radec()
print('sun_skyfield_apparent in (deg,deg,km) :',
radec_skyfield[0]._degrees, radec_skyfield[1]._degrees,
radec_skyfield[2].km)
# 比較 GeocentricTrueEcliptic
print('\n比較 GeocentricTrueEcliptic')
sun_ecliptic_astropy = sun_astropy_apparent.transform_to(
GeocentricTrueEcliptic(equinox=t_astropy))
sun_ecliptic_skyfield = sun_skyfield_apparent.frame_latlon(ecliptic_frame)
print(sun_ecliptic_astropy)
print(sun_ecliptic_skyfield[1]._degrees, sun_ecliptic_skyfield[0]._degrees,
sun_ecliptic_skyfield[2].km)
# 比較 TETE
print('\n比較 TreeEclipticTrueEquator(TETE)')
sun_tete_astropy = sun_astropy_apparent.transform_to(
TETE(obstime=t_astropy))
sun_tete_skyfield = sun_skyfield_apparent.radec(epoch='date')
print(sun_tete_astropy)
print(sun_tete_skyfield[0]._degrees, sun_tete_skyfield[1]._degrees,
sun_tete_skyfield[2].km)
sun_by_earth = Horizons(id='10',
id_type='majorbody',
location='500',
epochs={
'start': "2021-4-20 9:37",
'stop': "2021-4-20 9:38",
'step': '1'
})
sun_by_earth_ephem = sun_by_earth.ephemerides(quantities='1,2,4,20,31')
print("jpl 資料")
print(sun_by_earth_ephem['RA', 'DEC', 'RA_app', 'DEC_app', 'delta',
'ObsEclLon', 'ObsEclLat'])
# 比較 AltAz
print("\n比較 AltAz")
location_astropy = EarthLocation(lon=121 * u.deg,
lat=25 * u.deg,
height=0 * u.m)
moon_taipei_astropy = get_body('moon', t_astropy, location_astropy)
# print(moon_taipei_astropy)
_altaz_astropy = AltAz(obstime=t_astropy, location=location_astropy)
moon_taipei_altaz_astropy = moon_taipei_astropy.transform_to(
_altaz_astropy)
print("moon_taipei_altaz_astropy: ", moon_taipei_altaz_astropy)
taipei = earth + wgs84.latlon(25 * N, 121 * E, elevation_m=0)
moon_taipei_skyfield = taipei.at(t_skyfield).observe(moon).apparent()
alt, az, distance = moon_taipei_skyfield.altaz()
print("moon_taipei_altaz_skyfield: ", az._degrees, alt._degrees,
distance.km)
moon_by_taipei = Horizons(id='301',
id_type='majorbody',
location={
'lon': 121,
'lat': 25,
'elevation': 0
},
epochs={
'start': "2021-4-20 9:37",
'stop': "2021-4-20 9:38",
'step': '1'
})
moon_by_taipei_ephem = moon_by_taipei.ephemerides(quantities='1,2,4,20,31')
print("moon_taipei_jpl (AZ EL)", moon_by_taipei_ephem['AZ', 'EL'])
def squiggle_plot(RA, RAerr, Dec, Decerr, pmRA, pmRAerr, pmDec, pmDecerr, parallax, parallaxerr, ref_date, \
obsdate, obs_RAs, obs_RAs_err, obs_Decs, obs_Decs_err, labels, \
ref_RA_offset = 0,
ref_Dec_offset = 0,
time_interval = [12,12],
n_times = 5000,
plt_xlim=[-200,200],
plt_ylim=[-200,200],
marker = ['^','o'],
marker_size = [100,100],
figsize = (8,8)
):
''' Test for common proper motion of a candidate companion by plotting the track the cc would have
been observed on if it were a background object and not graviationally bound.
Inputs:
RA/Dec + errors [deg] (flt): RA/Dec of host star
pmRA, pmDec + errors [mas/yr] (flt): - proper motion of host star. Use the negative of reported
values because we treat the star as unmoving and will observe the apparent motion of the cc
parallax + erro [mas] (flt): parallax
ref_date [decimal year] (astropy Time object): reference date
obsdate [decimal year] (array): array of dates of observations
obs_RAs, obs_Decs + errors [mas] (array): array of observed RA/Dec offsets of companion to host star
labels (str array): strings to label plot points
ref_RA_offset, ref_Dec_offset [mas] (flt): 'zero point' reference RA/Dec offset for for companion
to host
time_interval [yrs] (array): Number of years [below,above] reference date to compute plot
n_times (int): number of time points to compute values for plot
plt_xlim, plt_ylim [mas] (array): axis limits [min,max]
marker (array): markers to use for prediction points [0] and observed points [1]
marker_size (array): size of markers for predicition points [0] and observed points [1]
Returns:
fig (matplotlib figure): plot of proper motion track
pred_dRA_total, pred_dDec_total (flt): predicted RA/Dec offsets if cc were a background object
'''
deg_to_mas = 3600000.
mas_to_deg = 1. / 3600000.
############### Compute track: ###################
# Define a time span around reference date:
delta_time = np.linspace(-time_interval[0], time_interval[1],
n_times) * u.yr
times = ref_date + delta_time
# Compute change in RA/Dec during time interval due to proper motion only:
dRA, dDec = (pmRA) * (delta_time.value), (pmDec) * (delta_time.value)
# Compute motion in the ecliptic coords due to parallactic motion:
# Make a sky coord object in RA/Dec:
obj = SkyCoord(ra=RA, dec=Dec, frame='icrs', unit='deg', obstime=time)
# Convert to ecliptic lon/lat:
gteframe = GeocentricTrueEcliptic()
obj_ecl = obj.transform_to(gteframe)
# Angle array during a year:
theta = (delta_time.value % 1) * 2 * np.pi
#Parallel to ecliptic:
x = parallax * np.sin(theta)
#Perp to ecliptic
y = parallax * np.sin(obj_ecl.lat.rad) * np.cos(theta)
# Compute ecliptic motion to equatorial motion:
print 'Plotting... this part may take a minute.'
new_RA, new_Dec = ecliptic_to_equatorial(obj_ecl.lon.deg+x*mas_to_deg, \
obj_ecl.lat.deg+y*mas_to_deg)
# Compute change in RA/Dec for each time point in mas:
delta_RA, delta_Dec = (new_RA - RA) * deg_to_mas, (new_Dec -
Dec) * deg_to_mas
#Put it together:
dRA_total = delta_RA + dRA + ref_RA_offset
dDec_total = delta_Dec + dDec + ref_Dec_offset
############# Compute prediction: #############
### Where the object would have been observed were it a background object
# Compute how far into each year the observation occured:
pred_time_delta = (obsdate - np.floor(obsdate))
pred_theta = (pred_time_delta) * 2 * np.pi
# Compute ecliptic motion:
pred_x = parallax * np.sin(pred_theta) #Parallel to ecliptic
pred_y = parallax * np.sin(obj_ecl.lat.rad) * np.cos(
pred_theta) #Perp to ecliptic
# Convert to RA/Dec:
pred_new_RA, pred_new_Dec = ecliptic_to_equatorial(obj_ecl.lon.deg+pred_x*mas_to_deg, \
obj_ecl.lat.deg+pred_y*mas_to_deg)
pred_delta_RA, pred_delta_Dec = (pred_new_RA - RA) * deg_to_mas, (
pred_new_Dec - Dec) * deg_to_mas
# Compute location due to proper motion:
pred_dRA, pred_dDec = (pmRA) * (obsdate - ref_date.value), (pmDec) * (
obsdate - ref_date.value)
# Put it together:
pred_dRA_total = -pred_delta_RA + pred_dRA + ref_RA_offset
pred_dDec_total = -pred_delta_Dec + pred_dDec + ref_Dec_offset
#################### Draw plot: #################
plt.rcParams['ytick.labelsize'] = tick_labelsize
plt.rcParams['xtick.labelsize'] = tick_labelsize
fig = plt.figure(figsize=figsize)
plt.plot(dRA_total,
dDec_total,
lw=3,
color='lightgrey',
alpha=0.5,
zorder=0)
plt.plot(dRA_total, dDec_total, zorder=1)
for i in range(len(pred_dRA)):
plt.scatter(pred_dRA_total[i],
pred_dDec_total[i],
marker=marker[0],
s=marker_size[0],
zorder=2,
edgecolors='black')
plt.annotate(labels[i],
xy=(pred_dRA_total[i], pred_dDec_total[i]),
xytext=(-10, 10),
textcoords='offset points',
ha='right',
va='bottom',
fontsize=labelsize)
for i in range(len(obs_RAs)):
plt.scatter(obs_RAs[i],
obs_Decs[i],
edgecolors="black",
marker=marker[1],
s=marker_size[1],
zorder=10)
plt.errorbar(obs_RAs[i],
obs_Decs[i],
xerr=obs_RAs_err[i],
yerr=obs_Decs_err[i],
ls='none',
elinewidth=1,
capsize=0,
ecolor='black',
zorder=10)
plt.ylim(plt_ylim[0], plt_ylim[1])
plt.xlim(plt_xlim[0], plt_xlim[1])
plt.xlabel(r'$\Delta$ RA [mas]', fontsize=fontsize)
plt.ylabel(r'$\Delta$ Dec [mas]', fontsize=fontsize)
plt.grid(ls=':')
plt.tight_layout()
return fig, pred_dRA_total, pred_dDec_total
def lonofobj(objname, t):
# t = Time({'year':year, 'month': month, 'day': day, 'hour': hour, 'minute': minute, 'second': second})
with solar_system_ephemeris.set('jpl'):
obj = get_body(objname, t)
obj_ecliptic = obj.transform_to(GeocentricTrueEcliptic(equinox=t))
return obj_ecliptic.lon.value
try:
coord = SkyCoord.from_name(coord)
except NameResolveError:
try:
coord = SkyCoord(coord)
except ValueError:
st.sidebar.error('Did not understand coordinate format')
st.stop()
st.sidebar.success(f'Resolved to ' +
coord.to_string('hmsdms', format='latex') + ' (' +
coord.to_string('decimal') + ')')
else:
lat = {'Low': 90, 'Medium': 30, 'High': 0}[zodi]
time = Time('2025-03-01')
sun = get_sun(time).transform_to(GeocentricTrueEcliptic(equinox=time))
coord = SkyCoord(sun.lon + 180 * u.deg,
lat * u.deg,
frame=GeocentricTrueEcliptic(equinox=time))
st.markdown('## Source')
spectrum = st.radio('Spectrum',
('Thermal', 'Flat in frequency (AB mag = const)',
'Flat in wavelength (ST mag = const)'))
if spectrum == 'Thermal':
temperature = st.number_input('Temperature (K)', 0, 20000, 10000, 1000)
source = synphot.SourceSpectrum(synphot.BlackBodyNorm1D,
temperature=temperature * u.K)
elif spectrum == 'Flat in frequency (AB mag = const)':
from astropy import units as u
from astropy.coordinates import SkyCoord, Galactic, GeocentricTrueEcliptic
print('> Testing transformation from Galactic to Ecliptic coordinate frame')
c_gal = SkyCoord(l=180 * u.degree, b=0 * u.degree, frame='galactic')
c_epl_g = c_gal.geocentrictrueecliptic
c_epl_b = c_gal.barycentrictrueecliptic
print(c_gal)
print(c_epl_g.lon.deg, c_epl_g.lat.deg)
print(c_epl_b.lon.deg, c_epl_b.lat.deg)
print('> Testing inverse transformation, from Eclptic to Galactic')
lon, lat = c_epl_g.lon.deg, c_epl_g.lat.deg
c_epl_g = GeocentricTrueEcliptic(lon=lon * u.degree, lat=lat * u.degree)
c_gal = SkyCoord(c_epl_g).galactic # this is fine
# c_gal = Galactic(c_epl_g) # this does not work!
print(c_epl_g.lon.deg, c_epl_g.lat.deg)
print(c_gal)