def longitude_radius_low(jd):
"""Return geometric longitude and radius vector.
Low precision. The longitude is accurate to 0.01 degree. The latitude
should be presumed to be 0.0. [Meeus-1998: equations 25.2 through 25.5
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- longitude in radians
- radius in au
"""
jd = np.atleast_1d(jd)
T = jd_to_jcent(jd)
L0 = polynomial(_kL0, T)
M = polynomial(_kM, T)
er = polynomial((0.016708634, -0.000042037, -0.0000001267), T)
C = polynomial(_kC, T) * np.sin(M) \
+ (_ck3 - _ck4 * T) * np.sin(2 * M) \
+ _ck5 * np.sin(3 * M)
L = modpi2(L0 + C)
v = M + C
R = 1.000001018 * (1 - er * er) / (1 + er * np.cos(v))
return L, R
def longitude_radius_low(jd):
"""Return geometric longitude and radius vector.
Low precision. The longitude is accurate to 0.01 degree. The latitude
should be presumed to be 0.0. [Meeus-1998: equations 25.2 through 25.5
Parameters:
jd : Julian Day in dynamical time
Returns:
longitude in radians
radius in au
"""
T = jd_to_jcent(jd)
L0 = polynomial(_kL0, T)
M = polynomial(_kM, T)
e = polynomial((0.016708634, -0.000042037, -0.0000001267), T)
C = polynomial(_kC, T) * sin(M) \
+ (_ck3 - _ck4 * T) * sin(2 * M) \
+ _ck5 * sin(3 * M)
L = modpi2(L0 + C)
v = M + C
R = 1.000001018 * (1 - e * e) / (1 + e * cos(v))
return L, R
def longitude_radius_low(jd):
"""Return geometric longitude and radius vector.
Low precision. The longitude is accurate to 0.01 degree. The latitude
should be presumed to be 0.0. [Meeus-1998: equations 25.2 through 25.5
Parameters:
jd : Julian Day in dynamical time
Returns:
longitude in radians
radius in au
"""
T = jd_to_jcent(jd)
L0 = polynomial(_kL0, T)
M = polynomial(_kM, T)
e = polynomial((0.016708634, -0.000042037, -0.0000001267), T)
C = polynomial(_kC, T) * sin(M) \
+ (_ck3 - _ck4 * T) * sin(2 * M) \
+ _ck5 * sin(3 * M)
L = modpi2(L0 + C)
v = M + C
R = 1.000001018 * (1 - e * e) / (1 + e * cos(v))
return L, R
def longitude_radius_low(jd):
"""Return geometric longitude and radius vector.
Low precision. The longitude is accurate to 0.01 degree. The latitude
should be presumed to be 0.0. [Meeus-1998: equations 25.2 through 25.5
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- longitude in radians
- radius in au
"""
jd = np.atleast_1d(jd)
T = jd_to_jcent(jd)
L0 = polynomial(_kL0, T)
M = polynomial(_kM, T)
er = polynomial((0.016708634, -0.000042037, -0.0000001267), T)
C = polynomial(_kC, T) * np.sin(M) \
+ (_ck3 - _ck4 * T) * np.sin(2 * M) \
+ _ck5 * np.sin(3 * M)
L = modpi2(L0 + C)
v = M + C
R = 1.000001018 * (1 - er * er) / (1 + er * np.cos(v))
return L, R
def _constants(T):
"""Return some values needed for both nut_in_lon() and nut_in_obl()"""
D = modpi2(polynomial(_kD, T))
M = modpi2(polynomial(_kM, T))
M1 = modpi2(polynomial(_kM1, T))
F = modpi2(polynomial(_kF, T))
omega = modpi2(polynomial(_ko, T))
return D, M, M1, F, omega
def _constants(T):
"""Return some values needed for both nutation_in_longitude() and
nutation_in_obliquity()"""
D = modpi2(polynomial(kD, T))
M = modpi2(polynomial(kM, T))
M1 = modpi2(polynomial(kM1, T))
F = modpi2(polynomial(kF, T))
omega = modpi2(polynomial(ko, T))
return D, M, M1, F, omega
def _constants(T):
"""Return some values needed for both nutation_in_longitude() and
nutation_in_obliquity()"""
D = modpi2(polynomial(kD, T))
M = modpi2(polynomial(kM, T))
M1 = modpi2(polynomial(kM1, T))
F = modpi2(polynomial(kF, T))
omega = modpi2(polynomial(ko, T))
return D, M, M1, F, omega
def equinox_approx(yr, season):
"""Returns the approximate time of a solstice or equinox event.
The year must be in the range -1000...3000. Within that range the
the error from the precise instant is at most 2.16 minutes.
Parameters:
yr : year
season : one of ("spring", "summer", "autumn", "winter")
Returns:
Julian Day of the event in dynamical time
"""
if not (-1000 <= yr <= 3000):
raise Error, "year is out of range"
if season not in astronomia.globals.season_names:
raise Error, "unknown season =" + season
yr = int(yr)
if -1000 <= yr <= 1000:
Y = yr / 1000.0
tbl = _approx_1000
else:
Y = (yr - 2000) / 1000.0
tbl = _approx_3000
jd = polynomial(tbl[season], Y)
T = jd_to_jcent(jd)
W = d_to_r(35999.373 * T - 2.47)
delta_lambda = 1 + 0.0334 * cos(W) + 0.0007 * cos(2 * W)
jd += 0.00001 * sum([A * cos(B + C * T) for A, B, C in _terms]) / delta_lambda
return jd
def vsop_to_fk5(jd, L, B):
"""Convert VSOP to FK5 coordinates.
This is required only when using the full precision of the
VSOP model.
[Meeus-1998: pg 219]
Parameters:
jd : Julian Day in dynamical time
L : longitude in radians
B : latitude in radians
Returns:
corrected longitude in radians
corrected latitude in radians
"""
T = jd_to_jcent(jd)
L1 = polynomial([L, _k0, _k1], T)
cosL1 = cos(L1)
sinL1 = sin(L1)
deltaL = _k2 + _k3 * (cosL1 + sinL1) * tan(B)
deltaB = _k3 * (cosL1 - sinL1)
return modpi2(L + deltaL), B + deltaB
def mean_longitude(self, jd):
"""Return mean longitude.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- Longitude in radians
"""
jd = np.atleast_1d(jd)
T = jd_to_jcent(jd)
# From astrolabe
#X = polynomial((d_to_r(100.466457),
# d_to_r(36000.7698278),
# d_to_r(0.00030322),
# d_to_r(0.000000020)), T)
# From AA, Naughter
# Takes T/10.0
X = polynomial((d_to_r(100.4664567),
d_to_r(360007.6982779),
d_to_r(0.03032028),
d_to_r(1.0/49931),
d_to_r(-1.0/15300),
d_to_r(-1.0/2000000)), T/10.0)
X = modpi2(X + np.pi)
return _scalar_if_one(X)
def mean_longitude(self, jd):
"""Return mean longitude.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- Longitude in radians
"""
jd = np.atleast_1d(jd)
T = jd_to_jcent(jd)
# From astrolabe
#X = polynomial((d_to_r(100.466457),
# d_to_r(36000.7698278),
# d_to_r(0.00030322),
# d_to_r(0.000000020)), T)
# From AA, Naughter
# Takes T/10.0
X = polynomial(
(d_to_r(100.4664567), d_to_r(360007.6982779), d_to_r(0.03032028),
d_to_r(1.0 / 49931), d_to_r(-1.0 / 15300), d_to_r(
-1.0 / 2000000)), T / 10.0)
X = modpi2(X + np.pi)
return _scalar_if_one(X)
def vsop_to_fk5(jd, L, B):
"""Convert VSOP to FK5 coordinates.
This is required only when using the full precision of the
VSOP model.
[Meeus-1998: pg 219]
Parameters:
jd : Julian Day in dynamical time
L : longitude in radians
B : latitude in radians
Returns:
corrected longitude in radians
corrected latitude in radians
"""
T = jd_to_jcent(jd)
L1 = polynomial([L, _k0, _k1], T)
cosL1 = cos(L1)
sinL1 = sin(L1)
deltaL = _k2 + _k3*(cosL1 + sinL1)*tan(B)
deltaB = _k3*(cosL1 - sinL1)
return modpi2(L + deltaL), B + deltaB
def mean_longitude_perigee(self, jd):
"""Return mean longitude of lunar perigee
"""
T = jd_to_jcent(jd)
X = polynomial(
(d_to_r(83.3532465), d_to_r(4069.0137287), d_to_r(-0.0103200),
d_to_r(-1. / 80053), d_to_r(1. / 18999000)), T)
return modpi2(X)
def _constants(T):
"""Calculate values required by several other functions"""
L1 = modpi2(polynomial(_kL1, T))
D = modpi2(polynomial(_kD, T))
M = modpi2(polynomial(_kM, T))
M1 = modpi2(polynomial(_kM1, T))
F = modpi2(polynomial(_kF, T))
A1 = modpi2(polynomial(_kA1, T))
A2 = modpi2(polynomial(_kA2, T))
A3 = modpi2(polynomial(_kA3, T))
E = polynomial([1.0, -0.002516, -0.0000074], T)
E2 = E * E
return L1, D, M, M1, F, A1, A2, A3, E, E2
def _constants(T):
"""Calculate values required by several other functions"""
L1 = modpi2(polynomial(kL1, T))
D = modpi2(polynomial(kD, T))
M = modpi2(polynomial(kM, T))
M1 = modpi2(polynomial(kM1, T))
F = modpi2(polynomial(kF, T))
A1 = modpi2(polynomial(_kA1, T))
A2 = modpi2(polynomial(_kA2, T))
A3 = modpi2(polynomial(_kA3, T))
E = polynomial([1.0, -0.002516, -0.0000074], T)
E2 = E*E
return L1, D, M, M1, F, A1, A2, A3, E, E2
def deltaT_seconds(jd):
"""Return deltaT as seconds of time.
For a historical range from 1620 to a recent year, we interpolate from a
table of observed values. Outside that range we use formulae.
Parameters:
jd : Julian Day number
Returns:
deltaT in seconds
"""
yr, mo, day = jd_to_cal(jd)
#
# 1620 - 20xx
#
if _tbl_start < yr < _tbl_end:
idx = bisect(_tbl, (jd, 0))
jd1, secs1 = _tbl[idx]
jd0, secs0 = _tbl[idx-1]
# simple linear interpolation between two values
return ((jd - jd0) * (secs1 - secs0) / (jd1 - jd0)) + secs0
t = (yr - 2000) / 100.0
#
# before 948 [Meeus-1998: equation 10.1]
#
if yr < 948:
return polynomial([2177, 497, 44.1], t)
#
# 948 - 1620 and after 2000 [Meeus-1998: equation 10.2)
#
result = polynomial([102, 102, 25.3], t)
#
# correction for 2000-2100 [Meeus-1998: pg 78]
#
if _tbl_end < yr < 2100:
result += 0.37 * (yr - 2100)
return result
def deltaT_seconds(jd):
"""Return deltaT as seconds of time.
For a historical range from 1620 to a recent year, we interpolate from a
table of observed values. Outside that range we use formulae.
Parameters:
jd : Julian Day number
Returns:
deltaT in seconds
"""
yr, mo, day = jd_to_cal(jd)
#
# 1620 - 20xx
#
if _tbl_start < yr < _tbl_end:
idx = bisect(_tbl, (jd, 0))
jd1, secs1 = _tbl[idx]
jd0, secs0 = _tbl[idx - 1]
# simple linear interpolation between two values
return ((jd - jd0) * (secs1 - secs0) / (jd1 - jd0)) + secs0
t = (yr - 2000) / 100.0
#
# before 948 [Meeus-1998: equation 10.1]
#
if yr < 948:
return polynomial([2177, 497, 44.1], t)
#
# 948 - 1620 and after 2000 [Meeus-1998: equation 10.2)
#
result = polynomial([102, 102, 25.3], t)
#
# correction for 2000-2100 [Meeus-1998: pg 78]
#
if _tbl_end < yr < 2100:
result += 0.37 * (yr - 2100)
return result
def argument_of_latitude(self, jd):
"""Return geocentric mean longitude.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- argument of latitude in radians
"""
T = jd_to_jcent(jd)
return modpi2(polynomial(kF, T))
def mean_anomaly(self, jd):
"""Return geocentric mean anomaly.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- mean anomaly in radians
"""
T = jd_to_jcent(jd)
return modpi2(polynomial(kM1, T))
def mean_elongation(self, jd):
"""Return geocentric mean elongation.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- mean elongation in radians
"""
T = jd_to_jcent(jd)
return modpi2(polynomial(kD, T))
def mean_elongation(self, jd):
"""Return geocentric mean elongation.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- mean elongation in radians
"""
T = jd_to_jcent(jd)
return modpi2(polynomial(kD, T))
def mean_anomaly(self, jd):
"""Return geocentric mean anomaly.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- mean anomaly in radians
"""
T = jd_to_jcent(jd)
return modpi2(polynomial(kM1, T))
def argument_of_latitude(self, jd):
"""Return geocentric mean longitude.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- argument of latitude in radians
"""
T = jd_to_jcent(jd)
return modpi2(polynomial(kF, T))
def mean_longitude(self, jd):
"""Return geocentric mean longitude.
Parameters:
jd : Julian Day in dynamical time
Returns:
longitude in radians
"""
T = jd_to_jcent(jd)
L1 = modpi2(polynomial(_kL1, T))
return L1
def mean_longitude(self, jd):
"""Return geocentric mean longitude.
Parameters:
jd : Julian Day in dynamical time
Returns:
longitude in radians
"""
T = jd_to_jcent(jd)
L1 = modpi2(polynomial(_kL1, T))
return L1
def mean_longitude_perigee(self, jd):
"""Return mean longitude of lunar perigee
"""
T = jd_to_jcent(jd)
X = polynomial(
(d_to_r(83.3532465),
d_to_r(4069.0137287),
d_to_r(-0.0103200),
d_to_r(-1./80053),
d_to_r(1./18999000)
),
T)
return modpi2(X)
def obliquity(jd):
"""Return the mean obliquity of the ecliptic.
Low precision, but good enough for most uses. [Meeus-1998: equation 22.2].
Accuracy is 1" over 2000 years and 10" over 4000 years.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- obliquity, in radians
"""
T = jd_to_jcent(jd)
return polynomial(_el0, T)
def obliquity(jd):
"""Return the mean obliquity of the ecliptic.
Low precision, but good enough for most uses. [Meeus-1998: equation 22.2].
Accuracy is 1" over 2000 years and 10" over 4000 years.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- obliquity, in radians
"""
T = jd_to_jcent(jd)
return polynomial(_el0, T)
def mean_longitude_perigee(self, jd):
"""Return mean longitude of solar perigee.
Parameters:
jd : Julian Day in dynamical time
Returns:
Longitude of solar perigee in radians
"""
T = jd_to_jcent(jd)
X = polynomial((1012395.0, 6189.03, 1.63, 0.012), (T + 1)) / 3600.0
X = d_to_r(X)
X = modpi2(X)
return X
def obliquity_hi(jd):
"""Return the mean obliquity of the ecliptic.
High precision [Meeus-1998: equation 22.3].
Accuracy is 0.01" between 1000 and 3000, and "a few arc-seconds
after 10,000 years".
Parameters:
jd : Julian Day in dynamical time
Returns:
obliquity, in radians
"""
U = jd_to_jcent(jd) / 100
return polynomial(_el1, U)
def obliquity_hi(jd):
"""Return the mean obliquity of the ecliptic.
High precision [Meeus-1998: equation 22.3].
Accuracy is 0.01" between 1000 and 3000, and "a few arc-seconds
after 10,000 years".
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- obliquity, in radians
"""
U = jd_to_jcent(jd) / 100
return polynomial(_el1, U)
def mean_longitude_perigee(self, jd):
"""Return mean longitude of solar perigee.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- Longitude of solar perigee in radians
"""
jd = np.atleast_1d(jd)
T = jd_to_jcent(jd)
X = polynomial((1012395.0, 6189.03, 1.63, 0.012), (T + 1)) / 3600.0
X = d_to_r(X)
X = modpi2(X)
return _scalar_if_one(X)
def mean_longitude_ascending_node(self, jd):
"""Return mean longitude of ascending node
Another equation from:
* This routine is part of the International Astronomical Union's
* SOFA (Standards of Fundamental Astronomy) software collection.
* Fundamental (Delaunay) arguments from Simon et al. (1994)
* Arcseconds to radians
DOUBLE PRECISION DAS2R
PARAMETER ( DAS2R = 4.848136811095359935899141D-6 )
* Milliarcseconds to radians
DOUBLE PRECISION DMAS2R
PARAMETER ( DMAS2R = DAS2R / 1D3 )
* Arc seconds in a full circle
DOUBLE PRECISION TURNAS
PARAMETER ( TURNAS = 1296000D0 )
* Mean longitude of the ascending node of the Moon.
OM = MOD ( 450160.398036D0 -6962890.5431D0*T, TURNAS ) * DAS2R
Current implemention in astronomia is from:
PJ Naughter (Web: www.naughter.com, Email: [email protected])
Look in nutation.py for calculation of omega
_ko = (d_to_r(125.04452), d_to_r( -1934.136261), d_to_r( 0.0020708), d_to_r( 1.0/450000))
Though the last term was left off...
Will have to incorporate better...
"""
T = jd_to_jcent(jd)
X = polynomial(
(d_to_r(125.0445479),
d_to_r(-1934.1362891),
d_to_r(0.0020754),
d_to_r(1.0/467441.0),
d_to_r(1.0/60616000.0)
),
T)
return modpi2(X)
def mean_longitude(self, jd):
"""Return mean longitude.
Parameters:
jd : Julian Day in dynamical time
Returns:
Longitude in radians
"""
T = jd_to_jcent(jd)
# From astrolabe
#X = polynomial((d_to_r(100.466457), d_to_r(36000.7698278), d_to_r(0.00030322), d_to_r(0.000000020)), T)
# From AA, Naughter
# Takes T/10.0
X = polynomial((d_to_r(100.4664567), d_to_r(360007.6982779), d_to_r(0.03032028), d_to_r(1.0/49931), d_to_r(-1.0/15300), d_to_r(-1.0/2000000)), T/10.0)
X = modpi2(X + pi)
return X
def mean_longitude_perigee(self, jd):
"""Return mean longitude of solar perigee.
Arguments:
- `jd` : Julian Day in dynamical time
Returns:
- Longitude of solar perigee in radians
"""
jd = np.atleast_1d(jd)
T = jd_to_jcent(jd)
X = polynomial((1012395.0,
6189.03,
1.63,
0.012), (T + 1))/3600.0
X = d_to_r(X)
X = modpi2(X)
return _scalar_if_one(X)
def mean_longitude_perigee(self, jd):
"""Return mean longitude of solar perigee.
Parameters:
jd : Julian Day in dynamical time
Returns:
Longitude of solar perigee in radians
"""
T = jd_to_jcent(jd)
X = polynomial((1012395.0,
6189.03 ,
1.63 ,
0.012 ), (T + 1))/3600.0
X = d_to_r(X)
X = modpi2(X)
return X
def equinox_approx(yr, season):
"""Returns the approximate time of a solstice or equinox event.
The year must be in the range -1000...3000. Within that range the
the error from the precise instant is at most 2.16 minutes.
Parameters:
yr : year
season : one of ("spring", "summer", "autumn", "winter")
Returns:
Julian Day of the event in dynamical time
"""
if not (-1000 <= yr <= 3000):
raise Error, "year is out of range"
if season not in astronomia.globals.season_names:
raise Error, "unknown season =" + season
yr = int(yr)
if -1000 <= yr <= 1000:
Y = yr / 1000.0
tbl = _approx_1000
else:
Y = (yr - 2000) / 1000.0
tbl = _approx_3000
jd = polynomial(tbl[season], Y)
T = jd_to_jcent(jd)
W = d_to_r(35999.373 * T - 2.47)
delta_lambda = 1 + 0.0334 * cos(W) + 0.0007 * cos(2 * W)
jd += 0.00001 * sum([A * cos(B + C * T)
for A, B, C in _terms]) / delta_lambda
return jd
def vsop_to_fk5(jd, L, B):
"""Convert VSOP to FK5 coordinates.
This is required only when using the full precision of the
VSOP model. [Meeus-1998: pg 219]
Arguments:
- `jd` : Julian Day in dynamical time
- `L` : longitude in radians
- `B` : latitude in radians
Returns:
- corrected longitude in radians
- corrected latitude in radians
"""
jd = np.atleast_1d(jd)
T = jd_to_jcent(jd)
L1 = polynomial([L, _k0, _k1], T)
cosL1 = np.cos(L1)
sinL1 = np.sin(L1)
deltaL = _k2 + _k3 * (cosL1 + sinL1) * np.tan(B)
deltaB = _k3 * (cosL1 - sinL1)
return _scalar_if_one(modpi2(L + deltaL)), _scalar_if_one(B + deltaB)
def mean_longitude_ascending_node(self, jd):
"""Return mean longitude of ascending node
Another equation from:
* This routine is part of the International Astronomical Union's
* SOFA (Standards of Fundamental Astronomy) software collection.
* Fundamental (Delaunay) arguments from Simon et al. (1994)
* Arcseconds to radians
DOUBLE PRECISION DAS2R
PARAMETER ( DAS2R = 4.848136811095359935899141D-6 )
* Milliarcseconds to radians
DOUBLE PRECISION DMAS2R
PARAMETER ( DMAS2R = DAS2R / 1D3 )
* Arc seconds in a full circle
DOUBLE PRECISION TURNAS
PARAMETER ( TURNAS = 1296000D0 )
* Mean longitude of the ascending node of the Moon.
OM = MOD ( 450160.398036D0 -6962890.5431D0*T, TURNAS ) * DAS2R
Current implemention in astronomia is from:
PJ Naughter (Web: www.naughter.com, Email: [email protected])
Look in nutation.py for calculation of omega
_ko = (d_to_r(125.04452), d_to_r( -1934.136261), d_to_r( 0.0020708), d_to_r( 1.0/450000))
Though the last term was left off...
Will have to incorporate better...
"""
T = jd_to_jcent(jd)
X = polynomial(
(d_to_r(125.0445479), d_to_r(-1934.1362891), d_to_r(0.0020754),
d_to_r(1.0 / 467441.0), d_to_r(1.0 / 60616000.0)), T)
return modpi2(X)
def mean_longitude_ascending_node(self, jd):
"""Return mean longitude of ascending node
Another equation from:
This routine is part of the International Astronomical Union's
SOFA (Standards of Fundamental Astronomy) software collection.
Fundamental (Delaunay) arguments from Simon et al. (1994)
* Arcseconds to radians
DOUBLE PRECISION DAS2R
PARAMETER ( DAS2R = 4.848136811095359935899141D-6 )
* Milliarcseconds to radians
DOUBLE PRECISION DMAS2R
PARAMETER ( DMAS2R = DAS2R / 1D3 )
* Arc seconds in a full circle
DOUBLE PRECISION TURNAS
PARAMETER ( TURNAS = 1296000D0 )
* Mean longitude of the ascending node of the Moon.
OM = MOD ( 450160.398036D0 -6962890.5431D0*T, TURNAS ) * DAS2R
Keeping above for documentation, but...
Current implemention in astronomia is from:
PJ Naughter (Web: www.naughter.com, Email: [email protected])
Arguments:
- `jd` : julian Day
Returns:
- mean longitude of ascending node
"""
T = jd_to_jcent(jd)
return modpi2(polynomial(ko, T))
def mean_longitude(self, jd):
"""Return mean longitude.
Parameters:
jd : Julian Day in dynamical time
Returns:
Longitude in radians
"""
T = jd_to_jcent(jd)
# From astrolabe
#X = polynomial((d_to_r(100.466457), d_to_r(36000.7698278), d_to_r(0.00030322), d_to_r(0.000000020)), T)
# From AA, Naughter
# Takes T/10.0
X = polynomial(
(d_to_r(100.4664567), d_to_r(360007.6982779), d_to_r(0.03032028),
d_to_r(1.0 / 49931), d_to_r(-1.0 / 15300), d_to_r(
-1.0 / 2000000)), T / 10.0)
X = modpi2(X + pi)
return X
def mean_longitude_ascending_node(self, jd):
"""Return mean longitude of ascending node
Another equation from:
This routine is part of the International Astronomical Union's
SOFA (Standards of Fundamental Astronomy) software collection.
Fundamental (Delaunay) arguments from Simon et al. (1994)
* Arcseconds to radians
DOUBLE PRECISION DAS2R
PARAMETER ( DAS2R = 4.848136811095359935899141D-6 )
* Milliarcseconds to radians
DOUBLE PRECISION DMAS2R
PARAMETER ( DMAS2R = DAS2R / 1D3 )
* Arc seconds in a full circle
DOUBLE PRECISION TURNAS
PARAMETER ( TURNAS = 1296000D0 )
* Mean longitude of the ascending node of the Moon.
OM = MOD ( 450160.398036D0 -6962890.5431D0*T, TURNAS ) * DAS2R
Keeping above for documentation, but...
Current implemention in astronomia is from:
PJ Naughter (Web: www.naughter.com, Email: [email protected])
Arguments:
- `jd` : julian Day
Returns:
- mean longitude of ascending node
"""
T = jd_to_jcent(jd)
return modpi2(polynomial(ko, T))
def vsop_to_fk5(jd, L, B):
"""Convert VSOP to FK5 coordinates.
This is required only when using the full precision of the
VSOP model. [Meeus-1998: pg 219]
Arguments:
- `jd` : Julian Day in dynamical time
- `L` : longitude in radians
- `B` : latitude in radians
Returns:
- corrected longitude in radians
- corrected latitude in radians
"""
jd = np.atleast_1d(jd)
T = jd_to_jcent(jd)
L1 = polynomial([L, _k0, _k1], T)
cosL1 = np.cos(L1)
sinL1 = np.sin(L1)
deltaL = _k2 + _k3*(cosL1 + sinL1)*np.tan(B)
deltaB = _k3*(cosL1 - sinL1)
return _scalar_if_one(modpi2(L + deltaL)), _scalar_if_one(B + deltaB)
