'''

This function is used to load all kernels needed in an operation.

Comment out kernels not in use and add the ones in use.

Arguments: NA

Returns: NA

'''

spice.kclear()

spice.furnsh('naif0008.tls.txt')

if k == '310+341+435':

spice.furnsh('jup310.bsp')

spice.furnsh('jup341.bsp')

spice.furnsh('de435.bsp')

elif k == '310+341':

spice.furnsh('jup310.bsp')

spice.furnsh('jup341.bsp')

elif k == '310+435':

spice.furnsh('de435.bsp')

spice.furnsh('jup310.bsp')

elif k == '341+435':

spice.furnsh('jup341.bsp')

spice.furnsh('de435.bsp')

elif k == '310':

spice.furnsh('jup310.bsp')

elif k == '341':

spice.furnsh('jup341.bsp')

elif k == '435':

spice.furnsh('de435.bsp')

"""

This wrapper function automates the creation of objects through the JPL Horizons database.

Arguments:

name: str

Stipulates the target object in Horizons. The major bodies in the Solar System have an id based on their position.

Hence '5' refers to Jupiter and '3' to Earth. A single number designator refers to a barycenter and a designator

such as '599' to the planetary center. For minor bodies in the Solar System, the id_type in the Horizons

must be changed to "minorbody"

cor: str

Refers to the type of correction that the object has. Available arguments are 'NONE', 'LT','LT+S'

loc: str

Designates the location of observation. Names that start with "g@#" refer to barycenters where the number designates the

body that the observer is based at. Hence "g@0" refers to the Solar System barycenter. Also takes Earth location designators.

Observatories are named after their code. Hence, Pan-Starrs observatory is referred as "f51"

Returns:

get_target_xyz function

"""

def get_target_xyz(t):

"""

Returns the vectors of the Horizons body at a certain time t.

Arguments:

t: days

Julian date of observation

Returns:

xyz: numpy array

A position vector of the observed object

uvw: numpy array

An instantaneous velocity vector of the observed object

radec: numpy array

The right ascension and declination of the observed object

"""

state,lighttime = spice.spkezr(name,t,'J2000',cor,loc)

pos,lighttime = spice.spkpos(name,t,'J2000',cor,loc)

range,ra,dec = spice.recrad(pos)

xyz = np.array([state[0],state[1],state[2]])/149597870.7#6.68459e-9

uvw = np.array([state[3],state[4],state[5]])/149597870.7*24.*3600.#*6.68459e-9

radec = np.array([ra,dec])

return xyz,uvw,radec*180/np.pi

"""

This wrapper function automates the creation of objects through the JPL Horizons database.

Arguments:

name: str

Stipulates the target object in Horizons. The major bodies in the Solar System have an id based on their position.

Hence '5' refers to Jupiter and '3' to Earth. A single number designator refers to a barycenter and a designator

such as '599' to the planetary center. For minor bodies in the Solar System, the id_type in the Horizons

must be changed to "minorbody"

cor: str

Refers to the type of correction that the object has. Available arguments are "geometric","astrometric" and

"apparent"

loc: str

Designates the location of observation. Names that start with "g@#" refer to barycenters where the number designates the

body that the observer is based at. Hence "g@0" refers to the Solar System barycenter. Also takes Earth location designators.

Observatories are named after their code. Hence, Pan-Starrs observatory is referred as "f51"

Returns:

get_target_xyz function

"""

def get_target_xyz(t):

"""

Returns the vectors of the Horizons body at a certain time t.

Arguments:

t: days

Julian date of observation

Returns:

xyz: numpy array

A position vector of the observed object

uvw: numpy array

An instantaneous velocity vector of the observed object

"""

obj = Horizons(id = name, location = loc, epochs = t, id_type = 'majorbody')

obj1 = obj.vectors(aberrations = cor, refplane = 'earth')

xyz = np.array([float(obj1['x']),float(obj1['y']),float(obj1['z'])])

uvw = np.array([float(obj1['vx']),float(obj1['vy']),float(obj1['vz'])])

obj2 = obj.ephemerides(refsystem = 'J2000', extra_precision = True)

radec = np.array([float(obj2['RA']),float(obj2['DEC']),float(obj1['range'])])

return xyz,uvw,radec

'''

This function takes in a position vector of a body relative to an observer and returns a radec.

Arguments:

xyz: numpy array

Should be three values, the x,y,z of the position vector

Returns:

radec: numpy array

Two values, the first for right ascension and the second for declination

'''

DEC = -(np.arccos(xyz[2]/np.linalg.norm(xyz))-np.pi/2)

RA = (np.arctan2(xyz[1],xyz[0]))

while (RA > 2*np.pi):

RA -= 2*np.pi

while (RA < 0):

RA += 2*np.pi

'''

Finds the radec of objects in the jovian system from the pansstars observatory. Used to test the correspondence

of spice and Horizons.

Arguments:

name: str

The name of the object in spice documentation. See Summary_Names.txt

t: float

A julian date

'''

thor = Time(t, format='jd', scale='utc')

thor = thor.tt.value

tstr = "jd " + str(t) + " utc"

ts = spice.str2et(tstr)

get_earth = get_astroquery_function('0','geometric','f51')

get_jup = get_spice_function(name,"NONE","0")

exyz = get_earth(thor)

jxyz = get_jup(ts)

fxyz = LT(ts, -exyz[0], get_jup)

vectors = fxyz[0] + exyz[0]

'''

Finds the radec of objects in the jovian system from the pansstars observatory from the Horizons data base.

Arguments:

name: str

The name of the object in spice documentation. See Summary_Names.txt

t: float

A julian date

'''

thor = Time(t, format='jd', scale='utc')

thor = thor.tt.value

get_pans = get_astroquery_function(name,'astrometric','f51')

vecs2 = get_pans(thor)

'''

Starts the simulation. Adds all particles

Arguments:

bsolar: list of strs

The names of the bodies added. Typically: '1','2','3','4', 'Jupiter','Io','Ananke'. 'Jupiter' must be added

last followed by the satellites in the system

msolar: list of floats

The masses of the bodies in bsolar. Must be at the order of bsolar

iJovian: list, int

The indexes (+1) that the satellites in the solar system have in bsolar

'''

sim = rebound.Simulation()

k = np.sqrt(Ms*10**9)*(1.49597870700*10**11)**(-1.5) *86400.00000

sim.G = k**2

sim.add(m=1.)

for i in range(0,len(bsolar)):

get_planet = get_spice_function(bsolar[i],'NONE','SUN')

xyz,uvw,radec = get_planet(t)

xyz = xyz

#uvw = (uvw*24*3600)

sim.add(m=msolar[i],x=xyz[0],y=xyz[1],z=xyz[2],vx=uvw[0],vy=uvw[1],vz=uvw[2])

ps = sim.particles

len(ps)

for i in range(0,len(arr)):

sim.add(a=arr[i][0],e=arr[i][1],inc=arr[i][2],Omega=arr[i][3],omega=arr[i][4],f=arr[i][5],primary=ps[bsolar.index('Jupiter')+1])

sim.n_active = len(bsolar)+1

sim.move_to_com()

'''

Integrates the system. If body1 or body2 refer to the Jupiter Barycenter, while there are bodies in the Jovian system

teh function will compute the barycenter in the simulation

Arguments:

bsolar

msolar

iJovian

body1 and body2: name in str

The spice names of the bodies that we want to look into to check the error of our integrator

'''

sim = SimStart2(t,bsolar,msolar,iJovian,Ms,arr)

year = 365.25 # days

tmax = (ten - t)/86400

sim.integrate(tmax)

'''

Finds the radec of objects in the jovian system from the pansstars observatory a number of years before

the time of observation and integrates it to the time of observation using rebound.

Arguments:

name: str

The name of the object in spice documentation. See Summary_Names.txt

t: float

A julian date

'''

thor = Time(t, format='jd', scale='utc')

thor = thor.tt.value

tstr = "jd " + str(t) + " utc"

ts = spice.str2et(tstr)

get_earth = get_astroquery_function('0','geometric','f51')

sec_year = 86400*365.25

sim = Integrator(ts - years*sec_year,ts,['1','2','3','4','6','7','8',

'Jupiter','Io','Europa','Ganymede','Callisto'],[MMercuryB,MVenusB,

MEarthB,MMarsB,MSaturnB,MUranusB,MNeptuneB,MJupiter,MIo,MEuropa,MGanymede,

MCallisto],[9,10,11,12,13,14,15],GMSun,arr)

ttemp = ts

radec = []

for j in range(0,len(times)):

temp = "jd " + str(times[j]) + " utc"

ttemp2 = spice.str2et(temp)

k = sim.t + (ttemp2-ttemp)/86400

ttemp = ttemp2

sim.integrate(k)

thor = Time(times[j], format='jd', scale='utc')

thor = thor.tt.value

ps = sim.particles

dist = np.sqrt((ps[-1].x-ps[3].x)**2 + (ps[-1].y-ps[3].y)**2 + (ps[-1].z-ps[3].z)**2)

ltime = float(((dist*u.AU).to(u.m)/c)/u.s)

k = sim.t - ltime/(24*3600)

sim.integrate(k)

ps = sim.particles

AnSun = np.array([float(ps[-1].x),float(ps[-1].y),float(ps[-1].z)])

#F51Sun = get_earth(thor)

#vecs.append(F51Sun[0])

vectors = AnSun + vecs[j][0]

radec.append(np.array([CordConv(vectors),times[j],IDs[j]]))

k = sim.t + ltime/(24*3600)

sim.integrate(k)

mags = []

for i in range(0,n):

mags.append(random.uniform(18,28))