def _compute_DV_DT_incipit(self,x): """ This method computes, for each leg, all the velocity increments coming from deep space manoeuvres and all the transfer times. Use: DV,DT = prob.compute_DV_DT(x) * x: trajectory encoding """ from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian from math import pi, acos,cos,sin,sqrt from scipy.linalg import norm #1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience T = x[3::4] n_legs = len(x)/4 seq = self.get_sequence() common_mu = seq[0].mu_central_body #2 - We compute the epochs and ephemerides of the planetary encounters t_P = list([None] * (n_legs)) r_P = list([None] * (n_legs)) v_P = list([None] * (n_legs)) DV = list([None] * (n_legs)) for i,planet in enumerate(seq): t_P[i] = epoch(x[0]+sum(T[:i+1])) r_P[i],v_P[i] = seq[i].eph(t_P[i]) #3 - We start with the first leg: a lambert arc theta = 2*pi*x[1] phi = acos(2*x[2]-1)-pi/2 r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection r = [JR*1000*d for d in r] l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,common_mu, False, False) #Lambert arc to reach seq[1] v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #First DSM occuring at the very beginning (will be cancelled by the optimizer) DV[0] = abs(norm(v_beg_l) - 3400) #4 - And we proceed with each successive leg for i in xrange(1,n_legs): #Fly-by v_out = fb_prop(v_end_l,v_P[i-1],x[1+4*i]*seq[i-1].radius,x[4*i],seq[i-1].mu_self) #s/c propagation before the DSM r,v = propagate_lagrangian(r_P[i-1],v_out,x[4*i+2]*T[i]*DAY2SEC,common_mu) #Lambert arc to reach Earth during (1-nu2)*T2 (second segment) dt = (1-x[4*i+2])*T[i]*DAY2SEC l = lambert_problem(r,r_P[i],dt,common_mu, False, False) v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #DSM occuring at time nu2*T2 DV[i] = norm([a-b for a,b in zip(v_beg_l,v)]) return (DV,T)
def _objfun_impl(self, x):
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs))
r_P = list([None] * (self.__n_legs))
v_P = list([None] * (self.__n_legs))
DV = list([None] * (self.__n_legs))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = self.seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
r = [cos(phi) * sin(theta),
cos(phi) * cos(theta),
sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, self.common_mu, False,
False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
#4 - And we proceed with each successive leg
for i in xrange(1, self.__n_legs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i - 1],
x[1 + 4 * i] * self.seq[i - 1].radius, x[4 * i],
self.seq[i - 1].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i - 1], v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
self.common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, self.common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
return (sum(DV), )
def run_example2():
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP import epoch, DAY2SEC, planet_ss, AU, MU_SUN, lambert_problem
from PyKEP.orbit_plots import plot_planet, plot_lambert
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d')
t1 = epoch(0)
t2 = epoch(640)
dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC
ax.scatter([0], [0], [0], color='y')
pl = planet_ss('earth')
plot_planet(ax, pl, t0=t1, color=(0.8, 0.8, 1), legend=True, units=AU)
rE, vE = pl.eph(t1)
pl = planet_ss('mars')
plot_planet(ax, pl, t0=t2, color=(0.8, 0.8, 1), legend=True, units=AU)
rM, vM = pl.eph(t2)
l = lambert_problem(rE, rM, dt, MU_SUN)
plot_lambert(ax, l, color='b', legend=True, units=AU)
plot_lambert(ax, l, sol=1, color='g', legend=True, units=AU)
plot_lambert(ax, l, sol=2, color='g', legend=True, units=AU)
plt.show()
def opt_dt(tt1, tt2):
t1 = epoch(tt1)
t2 = epoch(tt2)
dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC
rE, vE = plEarth.eph(t1)
vE = array(vE)
rM, vM = plMars.eph(t2)
vM = array(vM)
l = lambert_problem(rE, rM, dt, MU_SUN)
vEl = array(l.get_v1()[0])
dvE = vEl - vE
vMl = array(l.get_v2()[0])
dvM = vMl - vM
"""
print ""
print " detlal-V at Earth: "
print " Earth: ",vE
print " Ship: ",vEl
print " delta ", dvE, linalg.norm(dvE)
print ""
print " detlal-V at Mars : "
print " Mars: ", vM
print " Ship: ", vMl
dvM = (vM - vMl)
print " delta ", dvM, linalg.norm(dvM)
print " total delta-v ", linalg.norm(dvM)+linalg.norm(dvE)
"""
print " dt ", (tt2 - tt1), " dv ", linalg.norm(dvM) + linalg.norm(dvE)
plot_planet(ax, plMars, t0=t2, color=(0.8, 0.8, 1), units=AU)
plot_lambert(ax, l, color=(1, 0, 0), units=AU)
def run_example2():
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP import epoch, DAY2SEC, planet_ss, AU, MU_SUN, lambert_problem
from PyKEP.orbit_plots import plot_planet, plot_lambert
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d')
t1 = epoch(0)
t2 = epoch(640)
dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC
ax.scatter([0],[0],[0], color='y')
pl = planet_ss('earth')
plot_planet(ax,pl, t0=t1, color=(0.8,0.8,1), legend=True, units = AU)
rE,vE = pl.eph(t1)
pl = planet_ss('mars')
plot_planet(ax,pl, t0=t2, color=(0.8,0.8,1), legend=True, units = AU)
rM, vM = pl.eph(t2)
l = lambert_problem(rE,rM,dt,MU_SUN)
plot_lambert(ax,l, color='b', legend=True, units = AU)
plot_lambert(ax,l,sol=1, color='g', legend=True, units = AU)
plot_lambert(ax,l,sol=2, color='g', legend=True, units = AU)
plt.show()
def opt_dt(tt1, tt2):
t1 = epoch(tt1)
t2 = epoch(tt2)
dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC
rE, vE = plEarth.eph(t1)
vE = array(vE)
rM, vM = plMars.eph(t2)
vM = array(vM)
l = lambert_problem(rE, rM, dt, MU_SUN)
vEl = array(l.get_v1()[0])
dvE = (vEl - vE)
vMl = array(l.get_v2()[0])
dvM = (vMl - vM)
'''
print ""
print " detlal-V at Earth: "
print " Earth: ",vE
print " Ship: ",vEl
print " delta ", dvE, linalg.norm(dvE)
print ""
print " detlal-V at Mars : "
print " Mars: ", vM
print " Ship: ", vMl
dvM = (vM - vMl)
print " delta ", dvM, linalg.norm(dvM)
print " total delta-v ", linalg.norm(dvM)+linalg.norm(dvE)
'''
print " dt ", (tt2 - tt1), " dv ", linalg.norm(dvM) + linalg.norm(dvE)
plot_planet(ax, plMars, t0=t2, color=(0.8, 0.8, 1), units=AU)
plot_lambert(ax, l, color=(1, 0, 0), units=AU)
def _get_score_data_part(self, x):
from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian
from math import pi, acos, cos, sin, sqrt
from scipy.linalg import norm
from copy import deepcopy
"""
This method returns the data needed to compute the score of a trajectory.
"""
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
nlegs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
t0 = self.t0.mjd2000
vinf_in = deepcopy(self.vinf_in)
#2 - We compute the epochs and ephemerides of the planetary encounters
ep_list = list([None] * (nlegs + 1))
t_P = list([None] * (nlegs + 1))
r_P = list([None] * (nlegs + 1))
v_P = list([None] * (nlegs + 1))
DV = list([None] * nlegs)
for i, planet in enumerate(seq):
ep_list[i] = t0 + sum(T[:i])
t_P[i] = epoch(t0 + sum(T[:i]))
r_P[i], v_P[i] = seq[i].eph(t_P[i])
#init lists for fly-by parameters
vinf_list = []
rp_list = []
beta_list = []
v_end_l = [a + b for a, b in zip(vinf_in, v_P[0])]
#3 - And we proceed with each successive leg
for i in xrange(nlegs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i], x[1 + 4 * i] * seq[i].radius,
x[4 * i], seq[i].mu_self)
vinf_list.append([a - b for a, b in zip(v_end_l, v_P[i])])
rp_list.append(x[1 + 4 * i] * seq[i].radius)
beta_list.append(x[4 * i])
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
vinf_list.append([a - b for a, b in zip(v_end_l, v_P[-1])])
rp_list.append(None)
beta_list.append(None)
return zip(ep_list, seq, vinf_list, rp_list, beta_list)
def _mga_part_plot(self, x):
"""
Plots the trajectory represented by the decision vector x
Example::
prob.plot(x)
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams["legend.fontsize"] = 10
fig = plt.figure()
ax = fig.gca(projection="3d", aspect="equal")
ax.scatter(0, 0, 0, color="y")
JR = 71492000.0
legs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
start_mjd2000 = self.t0.mjd2000
# 1 - we 'decode' the chromosome recording the various times of flight (days) in the list T
T = x[3::4]
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (legs + 1))
r_P = list([None] * (legs + 1))
v_P = list([None] * (legs + 1))
for i, planet in enumerate(seq):
t_P[i] = epoch(start_mjd2000 + sum(T[:i]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(ax, planet, t0=t_P[i], color=(0.8, 0.6, 0.8), legend=True, units=JR)
v_end_l = [a + b for a, b in zip(v_P[0], self.vinf_in)]
# 4 - And we iterate on the legs
for i in xrange(0, legs):
# Fly-by
v_out = fb_prop(v_end_l, v_P[i], x[1 + 4 * i] * seq[i - 1].radius, x[4 * i], seq[i].mu_self)
# s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out, x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
plot_kepler(
ax, r_P[i], v_out, x[4 * i + 2] * T[i] * DAY2SEC, common_mu, N=500, color="b", legend=False, units=JR
)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, common_mu, False, False)
plot_lambert(ax, l, sol=0, color="r", legend=False, units=JR, N=500)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
plt.show()
return ax
def planet_planet(start_planet, arrive_planet, tlaunch, tarrive, rev, N):
# Create PyKEP epoch objects and calculate flight time
t1 = epoch(tlaunch)
t2 = epoch(tarrive)
dt = (tarrive - tlaunch) * DAY2SEC
OBJ1 = planet_ss(start_planet)
OBJ2 = planet_ss(
arrive_planet) # Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
# Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[0]
mu = l.get_mu()
#define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
#traj = [t, x, y, z]
vin = l.get_v1()[rev]
vout = l.get_v2()[rev]
#dV=fb_vel(vin,vout,planet_ss(arrive_planet))
#dV=np.sqrt( np.square(vin[0]/vout[0])+np.square(vin[1]/vout[1])+np.square(vin[2]/vout[2]))
#dV=np.sqrt( np.square(vin[0]-v1[0])+np.square(v1[1]-vin[1])+np.square(v1[2]-vin[2]))
#dV=np.sqrt( np.square(v2[0]-vout[0])+np.square(v2[1]-vout[1])+np.square(v2[2]-vout[2]))
#dV=np.sqrt( np.square(v1[0]/vin[0])+np.square(v1[1]/vin[1])+np.square(v1[2]/vin[2]))
C3_launch = (np.sqrt(
np.square(vin[0] - v1[0]) + np.square(vin[1] - v1[1]) +
np.square(vin[2] - v1[2])))**2
C3_arrive = (np.sqrt(
np.square(vout[0] - v2[0]) + np.square(vout[1] - v2[1]) +
np.square(vout[2] - v2[2])))**2
C3 = np.sqrt((C3_arrive**2) + (C3_launch**2))
return C3
def _mga_1dsm_tof_plot(self, x):
"""
Plots the trajectory represented by the decision vector x
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.scatter(0, 0, 0, color='y')
seq = self.get_sequence()
# 2 - We plot the first leg
r_P0, v_P0 = seq[0].eph(epoch(x[0]))
plot_planet(ax,
seq[0],
t0=epoch(x[0]),
color=(0.8, 0.6, 0.8),
legend=True,
units=AU)
r_P1, v_P1 = seq[1].eph(epoch(x[0] + x[5]))
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
v0 = [a + b for a, b in zip(v_P0, [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(r_P0, v0, x[4] * x[5] * DAY2SEC,
seq[0].mu_central_body)
plot_kepler(ax,
r_P0,
v0,
x[4] * x[5] * DAY2SEC,
seq[0].mu_central_body,
N=100,
color='b',
legend=False,
units=AU)
# Lambert arc to reach seq[1]
dt = (1 - x[4]) * x[5] * DAY2SEC
l = lambert_problem(r, r_P1, dt, seq[0].mu_central_body)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=AU)
v_end_l = l.get_v2()[0]
vinf_in = [a - b for a, b in zip(v_end_l, v_P1)]
_part_plot(x[6:], AU, ax, seq[1:], x[0] + x[5], vinf_in)
return ax
def _part_plot(x, units, ax, seq, start_mjd2000, vinf_in):
"""
Plots the trajectory represented by a decision vector x = [beta,rp,eta,T] * N
associated to a sequence seq, a start_mjd2000 and an incoming vinf_in
"""
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
legs = len(x) / 4
common_mu = seq[0].mu_central_body
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T
T = x[3::4]
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (legs + 1))
r_P = list([None] * (legs + 1))
v_P = list([None] * (legs + 1))
for i, planet in enumerate(seq):
t_P[i] = epoch(start_mjd2000 + sum(T[:i]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(ax,
planet,
t0=t_P[i],
color=(0.8, 0.6, 0.8),
legend=True,
units=units)
v_end_l = [a + b for a, b in zip(v_P[0], vinf_in)]
# 4 - And we iterate on the legs
for i in range(0, legs):
# Fly-by
v_out = fb_prop(v_end_l, v_P[i], x[1 + 4 * i] * seq[i].radius,
x[4 * i], seq[i].mu_self)
# s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
plot_kepler(ax,
r_P[i],
v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
common_mu,
N=500,
color='b',
legend=False,
units=units)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, common_mu, False, False)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=units, N=500)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
def _get_score_data_part(self,x):
from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian
from math import pi, acos,cos,sin,sqrt
from scipy.linalg import norm
from copy import deepcopy
"""
This method returns the data needed to compute the score of a trajectory.
"""
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
nlegs = len(x)/4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
t0 = self.t0.mjd2000
vinf_in = deepcopy(self.vinf_in)
#2 - We compute the epochs and ephemerides of the planetary encounters
ep_list = list([None] * (nlegs+1))
t_P = list([None] * (nlegs+1))
r_P = list([None] * (nlegs+1))
v_P = list([None] * (nlegs+1))
DV = list([None] * nlegs)
for i,planet in enumerate(seq):
ep_list[i] = t0+sum(T[:i])
t_P[i] = epoch(t0+sum(T[:i]))
r_P[i],v_P[i] = seq[i].eph(t_P[i])
#init lists for fly-by parameters
vinf_list = []
rp_list = []
beta_list = []
v_end_l = [a+b for a,b in zip(vinf_in, v_P[0])]
#3 - And we proceed with each successive leg
for i in xrange(nlegs):
#Fly-by
v_out = fb_prop(v_end_l,v_P[i],x[1+4*i]*seq[i].radius,x[4*i],seq[i].mu_self)
vinf_list.append( [a-b for a,b in zip(v_end_l,v_P[i])] )
rp_list.append(x[1+4*i]*seq[i].radius)
beta_list.append(x[4*i])
#s/c propagation before the DSM
r,v = propagate_lagrangian(r_P[i],v_out,x[4*i+2]*T[i]*DAY2SEC,common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1-x[4*i+2])*T[i]*DAY2SEC
l = lambert_problem(r,r_P[i+1],dt,common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
vinf_list.append([a-b for a,b in zip(v_end_l,v_P[-1])])
rp_list.append(None)
beta_list.append(None)
return zip(ep_list, seq, vinf_list, rp_list, beta_list)
def _mga_1dsm_tof_plot(self, x):
"""
Plots the trajectory represented by the decision vector x
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.scatter(0, 0, 0, color='y')
seq = self.get_sequence()
# 2 - We plot the first leg
r_P0, v_P0 = seq[0].eph(epoch(x[0]))
plot_planet(ax, seq[0], t0=epoch(x[0]), color=(
0.8, 0.6, 0.8), legend=True, units = AU)
r_P1, v_P1 = seq[1].eph(epoch(x[0] + x[5]))
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
v0 = [a + b for a, b in zip(v_P0, [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(
r_P0, v0, x[4] * x[5] * DAY2SEC, seq[0].mu_central_body)
plot_kepler(
ax,
r_P0,
v0,
x[4] *
x[5] *
DAY2SEC,
seq[0].mu_central_body,
N=100,
color='b',
legend=False,
units=AU)
# Lambert arc to reach seq[1]
dt = (1 - x[4]) * x[5] * DAY2SEC
l = lambert_problem(r, r_P1, dt, seq[0].mu_central_body)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=AU)
v_end_l = l.get_v2()[0]
vinf_in = [a - b for a, b in zip(v_end_l, v_P1)]
_part_plot(x[6:], AU, ax, seq[1:], x[0] + x[5], vinf_in)
return ax
def _objfun_impl(self,x): #1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience T = x[3::4] #2 - We compute the epochs and ephemerides of the planetary encounters t_P = list([None] * (self.__n_legs)) r_P = list([None] * (self.__n_legs)) v_P = list([None] * (self.__n_legs)) DV = list([None] * (self.__n_legs)) for i,planet in enumerate(self.seq): t_P[i] = epoch(x[0]+sum(T[:i+1])) r_P[i],v_P[i] = self.seq[i].eph(t_P[i]) #3 - We start with the first leg: a lambert arc theta = 2*pi*x[1] phi = acos(2*x[2]-1)-pi/2 r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection r = [JR*1000*d for d in r] l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,self.common_mu, False, False) #Lambert arc to reach seq[1] v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #First DSM occuring at the very beginning (will be cancelled by the optimizer) DV[0] = abs(norm(v_beg_l) - 3400) #4 - And we proceed with each successive leg for i in xrange(1,self.__n_legs): #Fly-by v_out = fb_prop(v_end_l,v_P[i-1],x[1+4*i]*self.seq[i-1].radius,x[4*i],self.seq[i-1].mu_self) #s/c propagation before the DSM r,v = propagate_lagrangian(r_P[i-1],v_out,x[4*i+2]*T[i]*DAY2SEC,self.common_mu) #Lambert arc to reach Earth during (1-nu2)*T2 (second segment) dt = (1-x[4*i+2])*T[i]*DAY2SEC l = lambert_problem(r,r_P[i],dt,self.common_mu, False, False) v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #DSM occuring at time nu2*T2 DV[i] = norm([a-b for a,b in zip(v_beg_l,v)]) return (sum(DV),)
def getLambert(r):
R2 = R20 * r
a = NAN
try:
lambert_result = lambert_problem(R1, R2, dt)
if lambert_result.is_reliable():
a = lambert_result.get_a()[0]
except:
a = NAN
#print " r,a ", r,a
return a
def getLambert(r): R2 = R1 + R20*r a = NAN try: lambert_result =lambert_problem(R1,R2,dt ) if lambert_result.is_reliable(): a = lambert_result.get_a()[0] except: a= NAN #print " r,a ", r,a return a
def planet_planet(start_planet, arrive_planet, tlaunch, tarrive, rev, N):
# Create PyKEP epoch objects and calculate flight time
t1 = epoch(tlaunch)
t2 = epoch(tarrive)
dt = (tarrive - tlaunch) * DAY2SEC
OBJ1 = planet_ss(start_planet)
OBJ2 = planet_ss(arrive_planet) # Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
# Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[0]
mu = l.get_mu()
#define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
#traj = [t, x, y, z]
vin = l.get_v1()[rev]
vout = l.get_v2()[rev]
#dV=fb_vel(vin,vout,planet_ss(arrive_planet))
#dV=np.sqrt( np.square(vin[0]/vout[0])+np.square(vin[1]/vout[1])+np.square(vin[2]/vout[2]))
#dV=np.sqrt( np.square(vin[0]-v1[0])+np.square(v1[1]-vin[1])+np.square(v1[2]-vin[2]))
#dV=np.sqrt( np.square(v2[0]-vout[0])+np.square(v2[1]-vout[1])+np.square(v2[2]-vout[2]))
#dV=np.sqrt( np.square(v1[0]/vin[0])+np.square(v1[1]/vin[1])+np.square(v1[2]/vin[2]))
C3_launch = (np.sqrt(np.square(vin[0] - v1[0]) + np.square(vin[1] - v1[1]) + np.square(vin[2] - v1[2]))) ** 2
C3_arrive = (np.sqrt(np.square(vout[0] - v2[0]) + np.square(vout[1] - v2[1]) + np.square(vout[2] - v2[2]))) ** 2
C3 = np.sqrt((C3_arrive ** 2) + (C3_launch ** 2))
return C3
def _part_plot(x, units, axis, seq, start_mjd2000, vinf_in):
"""
Plots the trajectory represented by a decision vector x = [beta,rp,eta,T] * N
associated to a sequence seq, a start_mjd2000 and an incoming vinf_in
"""
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
legs = len(x) // 4
common_mu = seq[0].mu_central_body
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T
T = x[3::4]
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (legs + 1))
r_P = list([None] * (legs + 1))
v_P = list([None] * (legs + 1))
for i, planet in enumerate(seq):
t_P[i] = epoch(start_mjd2000 + sum(T[:i]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(planet, t0=t_P[i], color=(
0.8, 0.6, 0.8), legend=True, units = units, ax=axis)
v_end_l = [a + b for a, b in zip(v_P[0], vinf_in)]
# 4 - And we iterate on the legs
for i in range(0, legs):
# Fly-by
v_out = fb_prop(v_end_l,
v_P[i],
x[1 + 4 * i] * seq[i].radius,
x[4 * i],
seq[i].mu_self)
# s/c propagation before the DSM
r, v = propagate_lagrangian(
r_P[i], v_out, x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
plot_kepler(r_P[i], v_out, x[4 * i + 2] * T[i] * DAY2SEC,
common_mu, N=500, color='b', legend=False, units=units, ax=axis)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, common_mu, False, False)
plot_lambert(
l, sol=0, color='r', legend=False, units=units, N=500, ax=axis)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
def opt_dt(tt1,tt2): t1 = epoch(tt1) t2 = epoch(tt2) #print t1 dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC rE, vE = plEarth.eph(t1); vE=array(vE) rM, vM = plMars .eph(t2); vM=array(vM) l = lambert_problem(rE,rM,dt,MU_SUN) vEl = array(l.get_v1()[0]); dvE = (vEl - vE) vMl = array(l.get_v2()[0]); dvM = (vMl - vM) dvMTot = linalg.norm(dvM); dvETot= linalg.norm(dvE) dvTot = dvMTot+dvETot print " t1 " ,tt1," t2 ", tt2," dt ",(tt2-tt1)," dv ", dvTot return vE, vM, vEl, vMl
def _mga_incipit_plot(self, x, plot_leg_0=False):
"""
Plots the trajectory represented by the decision vector x
Example::
prob.plot(x)
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d', aspect='equal')
ax.scatter(0, 0, 0, color='y')
JR = 71492000.0
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
r_P, v_P = seq[0].eph(epoch(x[0] + x[3]))
# 3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
# phi close to zero is in the moon orbit plane injection
r = [cos(phi) * sin(theta), cos(phi) * cos(theta), sin(phi)]
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P, x[3] * DAY2SEC, common_mu, False, False)
if (plot_leg_0):
plot_lambert(ax, l, sol=0, color='k', legend=False, units=JR, N=500)
# Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
vinf_in = [a - b for a, b in zip(v_end_l, v_P)]
_part_plot(x[4:], JR, ax, seq, x[0] + x[3], vinf_in)
return ax
def _mga_incipit_plot(self, x, plot_leg_0=False):
"""
Plots the trajectory represented by the decision vector x
Example::
prob.plot(x)
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d', aspect='equal')
ax.scatter(0, 0, 0, color='y')
JR = 71492000.0
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
r_P, v_P = seq[0].eph(epoch(x[0] + x[3]))
# 3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
# phi close to zero is in the moon orbit plane injection
r = [cos(phi) * sin(theta), cos(phi) * cos(theta), sin(phi)]
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P, x[3] * DAY2SEC, common_mu, False, False)
if (plot_leg_0):
plot_lambert(ax, l, sol=0, color='k', legend=False, units=JR, N=500)
# Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
vinf_in = [a - b for a, b in zip(v_end_l, v_P)]
_part_plot(x[4:], JR, ax, seq, x[0] + x[3], vinf_in)
return ax
def opt_dt(tt1, tt2):
t1 = epoch(tt1)
t2 = epoch(tt2)
#print t1
dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC
rE, vE = plEarth.eph(t1)
vE = array(vE)
rM, vM = plJupiter.eph(t2)
vM = array(vM)
l = lambert_problem(rE, rM, dt, MU_SUN)
vEl = array(l.get_v1()[0])
dvE = (vEl - vE)
vMl = array(l.get_v2()[0])
dvM = (vMl - vM)
dvMTot = linalg.norm(dvM)
dvETot = linalg.norm(dvE)
dvTot = dvMTot + dvETot
print " t1 ", tt1, " t2 ", tt2, " dt ", (tt2 - tt1), " dv ", dvTot
return vE, vM, vEl, vMl
def pretty(self, x):
"""
Prints human readable information on the trajectory represented by the decision vector x
Example::
prob.pretty(x)
"""
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs))
r_P = list([None] * (self.__n_legs))
v_P = list([None] * (self.__n_legs))
DV = list([None] * (self.__n_legs))
close_d = list([None] * (self.__n_legs))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = self.seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
r = [cos(phi) * sin(theta),
cos(phi) * cos(theta),
sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, self.common_mu, False,
False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
close_d[0] = closest_distance(r, v_beg_l, r_P[0], v_end_l,
self.common_mu)[0] / JR
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
print "\nFirst Leg: 1000JR to " + self.seq[0].name
print "\tDeparture: " + str(t_P[0]) + " (" + str(
t_P[0].mjd2000) + " mjd2000) "
print "\tDuration: " + str(T[0]) + "days"
print "\tInitial Velocity Increment (m/s): " + str(DV[0])
print "\tArrival relative velocity at " + self.seq[
0].name + " (m/s): " + str(
norm([a - b for a, b in zip(v_end_l, v_P[0])]))
print "\tClosest approach distance: " + str(close_d[0])
#4 - And we proceed with each successive leg
for i in xrange(1, self.__n_legs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i - 1],
x[1 + 4 * i] * self.seq[i - 1].radius, x[4 * i],
self.seq[i - 1].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i - 1], v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
self.common_mu)
tmp, ra = closest_distance(r_P[i - 1], v_out, r, v, self.common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, self.common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
tmp2, ra2 = closest_distance(r, v_beg_l, r_P[i], v_end_l,
self.common_mu)
if tmp < tmp2:
close_d[i] = tmp / JR
ra = ra / JR
else:
close_d[i] = tmp2 / JR
ra = ra2 / JR
#DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
print "\nleg no. " + str(i + 1) + ": " + self.seq[
i - 1].name + " to " + self.seq[i].name
print "\tDuration (days): " + str(T[i])
print "\tFly-by epoch: " + str(t_P[i]) + " (" + str(
t_P[i].mjd2000) + " mjd2000) "
print "\tFly-by altitude (km): " + str(
(x[4 * i + 1] * self.seq[i - 1].radius -
self.seq[i - 1].radius) / 1000)
print "\tDSM after (days): " + str(x[4 * i + 2] * T[i])
print "\tDSM magnitude (m/s): " + str(DV[i])
print "\tClosest approach distance: " + str(close_d[i])
print "\tApoapsis at closest distance: " + str(ra)
print "\nArrival at " + self.seq[-1].name
vel_inf = [a - b for a, b in zip(v_end_l, v_P[-1])]
print "Arrival epoch: " + str(t_P[-1]) + " (" + str(
t_P[-1].mjd2000) + " mjd2000) "
print "Arrival Vinf (m/s): " + vel_inf.__repr__() + " - " + str(
norm(vel_inf))
print "Total mission time (days): " + str(sum(T))
def ic_from_mga_1dsm(self, x):
"""
x_lt = prob.ic_from_mga_1dsm(x_mga)
- x_mga: compatible trajectory as encoded by an mga_1dsm problem
Returns an initial guess for the low-thrust trajectory, converting the mga_1dsm solution x_dsm. The user
is responsible that x_mga makes sense (i.e. it is a viable mga_1dsm representation). The conversion is done by importing in the
low-thrust encoding a) the launch date b) all the legs durations, c) the in and out relative velocities at each planet.
All throttles are put to zero.
Example::
x_lt= prob.ic_from_mga_1dsm(x_mga)
"""
from math import pi, cos, sin, acos
from scipy.linalg import norm
from PyKEP import propagate_lagrangian, lambert_problem, DAY2SEC, fb_prop
retval = list([0.0] * self.dimension)
# 1 - we 'decode' the chromosome recording the various times of flight (days) in the list T
T = list([0] * (self.__n_legs))
for i in range(len(T)):
T[i] = log(x[2 + 4 * i])
total = sum(T)
T = [x[1] * time / total for time in T]
retval[0] = x[0]
for i in range(self.__n_legs):
retval[1 + 8 * i] = T[i]
retval[2 + 8 * i] = self.__sc.mass
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs + 1))
r_P = list([None] * (self.__n_legs + 1))
v_P = list([None] * (self.__n_legs + 1))
DV = list([None] * (self.__n_legs + 1))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[0:i]))
r_P[i], v_P[i] = self.seq[i].eph(t_P[i])
# 3 - We start with the first leg
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
retval[3:6] = [Vinfx, Vinfy, Vinfz]
v0 = [a + b for a, b in zip(v_P[0], [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(r_P[0], v0, x[4] * T[0] * DAY2SEC, MU_SUN)
# Lambert arc to reach seq[1]
dt = (1 - x[4]) * T[0] * DAY2SEC
l = lambert_problem(r, r_P[1], dt, MU_SUN)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
retval[6:9] = [a - b for a, b in zip(v_end_l, v_P[1])]
# 4 - And we proceed with each successive leg
for i in range(1, self.__n_legs):
# Fly-by
v_out = fb_prop(v_end_l, v_P[i], x[7 + (i - 1) * 4] * self.seq[i].radius, x[6 + (i - 1) * 4], self.seq[i].mu_self)
retval[3 + i * 8:6 + i * 8] = [a - b for a, b in zip(v_out, v_P[i])]
# s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out, x[8 + (i - 1) * 4] * T[i] * DAY2SEC, MU_SUN)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[8 + (i - 1) * 4]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, MU_SUN)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
retval[6 + i * 8:9 + i * 8] = [a - b for a, b in zip(v_end_l, v_P[i + 1])]
return retval
def getTraj_simple(start_planet, arrive_planet, tlaunch, tarrive, N):
'''
Finds a trajectory between two objects orbiting the Sun
USAGE: traj = getTraj(K1, K2, tlaunch, tarrive)
K: array of object parameters.
epoch: epoch of Keplerian orbital elements (JD)
a: semimajor axis (AU)
e: eccentricity (none)
i: inclination (deg)
om: longitude of the ascending node (deg)
w: argument of perihelion (deg)
ma: mean anomaly at epoch (deg)
mass: mass of object (kg)
r: radius of object (m)
sr: safe radius to approach object (m)
K1: [epoch1,a1,e1,i1,om1,w1,ma1,mass1,r1,sr1]
K2: [epoch2,a2,e2,i2,om2,w2,ma2,mass2,r2,sr2]
tlaunch: launch time (JD)
tarrive: arrival time (JD)
N: number of points in calculated trajectory
'''
import numpy as np
from PyKEP import epoch, DAY2SEC, SEC2DAY, AU, DEG2RAD, MU_SUN, planet_ss, lambert_problem, propagate_lagrangian, fb_vel
# Create PyKEP epoch objects and calculate flight time
t1 = epoch(tlaunch)
t2 = epoch(tarrive)
dt = (tarrive - tlaunch) * DAY2SEC
rev = 0 #number of revolutions before intercept
OBJ1 = planet_ss(start_planet)
OBJ2 = planet_ss(
arrive_planet) # Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
#Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[0]
mu = l.get_mu()
#define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
#traj = [t, x, y, z]
vin = l.get_v1()[rev]
vout = l.get_v2()[rev]
dV = fb_vel(vin, vout, planet_ss(arrive_planet))
#dV=np.sqrt( np.square(vout[0])+np.square(vout[1])+np.square(vout[2]))-np.sqrt( np.square(vin[0])+np.square(vin[1])+np.square(vin[2]))
return dV
def planet_asteroid(start_planet, target_name, tlaunch, tarrive, rev, N):
# Create PyKEP epoch objects and calculate flight time
t1 = epoch(tlaunch)
t2 = epoch(tarrive)
dt = (tarrive - tlaunch) * DAY2SEC
import py.AsteroidDB as asteroidDB
neo_db = asteroidDB.neo
target = (item for item in neo_db if item["name"] == target_name).next()
ep = epoch(target["epoch_mjd"], epoch.epoch_type.MJD)
a = target["a"] * AU
e = target["e"]
i = target["i"] * DEG2RAD
om = target["om"] * DEG2RAD
w = target["w"] * DEG2RAD
ma = target["ma"] * DEG2RAD
as_mu = 1E17 * 6.67384E-11 # maybe need to calculate actual mass from density and radius
r = (target["diameter"] / 2) * 1000
sr = r * 1.1
OBJ2 = planet(ep, (a, e, i, om, w, ma), MU_SUN, as_mu, r, sr)
OBJ1 = planet_ss(start_planet) # Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
# Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[rev]
mu = l.get_mu()
#define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
#traj = [t, x, y, z]
vin = l.get_v1()[rev]
vout = l.get_v2()[rev]
#dV=fb_vel(vin,vout,planet_ss(arrive_planet))
#dV=np.sqrt( np.square(vin[0]/vout[0])+np.square(vin[1]/vout[1])+np.square(vin[2]/vout[2]))
#dV=np.sqrt( np.square(vin[0]-v1[0])+np.square(v1[1]-vin[1])+np.square(v1[2]-vin[2]))
#dV=np.sqrt( np.square(v2[0]-vout[0])+np.square(v2[1]-vout[1])+np.square(v2[2]-vout[2]))
#dV=np.sqrt( np.square(v1[0]/vin[0])+np.square(v1[1]/vin[1])+np.square(v1[2]/vin[2]))
C3_launch = (np.sqrt(np.square(vin[0] - v1[0]) + np.square(vin[1] - v1[1]) + np.square(vin[2] - v1[2]))) ** 2
C3_arrive = (np.sqrt(np.square(vout[0] - v2[0]) + np.square(vout[1] - v2[1]) + np.square(vout[2] - v2[2]))) ** 2
C3 = np.sqrt((C3_arrive ** 2) + (C3_launch ** 2))
return C3
def _mga_incipit_plot_old(self, x, plot_leg_0=False):
"""
Plots the trajectory represented by the decision vector x
Example::
prob.plot(x)
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d', aspect='equal')
ax.scatter(0, 0, 0, color='y')
JR = 71492000.0
legs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T
T = x[3::4]
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * legs)
r_P = list([None] * legs)
v_P = list([None] * legs)
DV = list([None] * legs)
for i, planet in enumerate(seq):
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(ax,
planet,
t0=t_P[i],
color=(0.8, 0.6, 0.8),
legend=True,
units=JR)
# 3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
# phi close to zero is in the moon orbit plane injection
r = [cos(phi) * sin(theta), cos(phi) * cos(theta), sin(phi)]
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, common_mu, False, False)
if (plot_leg_0):
plot_lambert(ax, l, sol=0, color='k', legend=False, units=JR, N=500)
# Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# 4 - And we proceed with each successive leg
for i in range(1, legs):
# Fly-by
v_out = fb_prop(v_end_l, v_P[i - 1], x[1 + 4 * i] * seq[i - 1].radius,
x[4 * i], seq[i - 1].mu_self)
# s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i - 1], v_out,
x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
plot_kepler(ax,
r_P[i - 1],
v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
common_mu,
N=500,
color='b',
legend=False,
units=JR)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, common_mu, False, False)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=JR, N=500)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
plt.show()
return ax
def getTraj_simple(start_planet, arrive_planet, tlaunch, tarrive, N):
'''
Finds a trajectory between two objects orbiting the Sun
USAGE: traj = getTraj(K1, K2, tlaunch, tarrive)
K: array of object parameters.
epoch: epoch of Keplerian orbital elements (JD)
a: semimajor axis (AU)
e: eccentricity (none)
i: inclination (deg)
om: longitude of the ascending node (deg)
w: argument of perihelion (deg)
ma: mean anomaly at epoch (deg)
mass: mass of object (kg)
r: radius of object (m)
sr: safe radius to approach object (m)
K1: [epoch1,a1,e1,i1,om1,w1,ma1,mass1,r1,sr1]
K2: [epoch2,a2,e2,i2,om2,w2,ma2,mass2,r2,sr2]
tlaunch: launch time (JD)
tarrive: arrival time (JD)
N: number of points in calculated trajectory
'''
import numpy as np
from PyKEP import epoch, DAY2SEC, SEC2DAY, AU, DEG2RAD, MU_SUN, planet, lambert_problem, propagate_lagrangian, fb_vel
# Create PyKEP epoch objects and calculate flight time
t1 = epoch(tlaunch)
t2 = epoch(tarrive)
dt = (tarrive - tlaunch) * DAY2SEC
rev=0 #number of revolutions before intercept
OBJ1 = planet.jpl_lp(start_planet)
OBJ2 = planet.jpl_lp(arrive_planet) # Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
#Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[0]
mu = l.get_mu()
#define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
#traj = [t, x, y, z]
vin=l.get_v1()[rev]
vout=l.get_v2()[rev]
dV=fb_vel(vin,vout,planet.jpl_lp(arrive_planet))
#dV=np.sqrt( np.square(vout[0])+np.square(vout[1])+np.square(vout[2]))-np.sqrt( np.square(vin[0])+np.square(vin[1])+np.square(vin[2]))
return dV
def _get_penalty_data(self, x):
""" getTrajectory takes a genome x, and returns a Trajectory variable that is a list of all r, v, and time of flights
Trajectory = [[r0, v0_out, r1, v1_in, tof, rp, ra, Trev, vinf], [r1, v1_out, r2, v2_in, tof, rp, ra, Trev, vinf], [...]]
tof in days
"""
from PyKEP import epoch, lambert_problem, propagate_lagrangian, fb_prop, DAY2SEC
from math import pi, acos, cos, sin
import numpy as np
from _mass_penalty import get_rp_ra_Trev
Trajectory = []
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
# reconstruct properties that are known in _mga_incipit:
self.seq = self.get_sequence()
self.__n_legs = len(self.seq)
self.common_mu = self.seq[0].mu_central_body
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs))
r_P = list([None] * (self.__n_legs))
v_P = list([None] * (self.__n_legs))
DV = list([None] * (self.__n_legs))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = self.seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
r = [cos(phi) * sin(theta),
cos(phi) * cos(theta),
sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, self.common_mu, False,
False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
Tr = [tuple(r), v_beg_l, r_P[0], v_end_l, T[0] * DAY2SEC]
rPvec = np.asarray(r_P[0])
vPvec = np.asarray(v_end_l)
Tr = Tr + get_rp_ra_Trev(rPvec, vPvec)
vinf = vPvec - np.asarray(v_P[0])
Tr = Tr + [vinf]
Trajectory.append(Tr)
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(np.linalg.norm(v_beg_l) - 3400)
#4 - And we proceed with each successive leg
for i in xrange(1, self.__n_legs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i - 1],
x[1 + 4 * i] * self.seq[i - 1].radius, x[4 * i],
self.seq[i - 1].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i - 1], v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
self.common_mu)
# append r, v, etc. to the Trajectory:
Tr = [r_P[i - 1], v_out, r, v, x[4 * i + 2] * T[i] * DAY2SEC]
rPvec = np.asarray(r)
vPvec = np.asarray(v)
Tr = Tr + get_rp_ra_Trev(rPvec, vPvec)
vinf = []
Tr = Tr + [vinf]
Trajectory.append(Tr)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, self.common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# append r, v, etc. to the Trajectory:
Tr = [
r, v_beg_l, r_P[i], v_end_l, (1 - x[4 * i + 2]) * T[i] * DAY2SEC
]
rPvec = np.asarray(r_P[i])
vPvec = np.asarray(v_end_l)
Tr = Tr + get_rp_ra_Trev(rPvec, vPvec)
vinf = vPvec - np.asarray(v_P[i])
Tr = Tr + [vinf]
Trajectory.append(Tr)
#DSM occuring at time nu2*T2
DV[i] = np.linalg.norm([a - b for a, b in zip(v_beg_l, v)])
return Trajectory
def _objfun_impl(self,x): #1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience T = list([0]*(self.__n_legs)) #sum_alpha = 0 #for i in range(self.__n_legs-1): # sum_alpha = sum_alpha+x[4+4*i] #for i in xrange(self.__n_legs-1): # T[i] = (x[4+4*i]/sum_alpha)*x[3] for i in xrange(0,self.__n_legs): T[i] = (x[4+4*i]/sum(x[4::4]))*x[3] #print "\tDuration: " + str(T) + "days" #return(T,) #2 - We compute the epochs and ephemerides of the planetary encounters t_P = list([None] * (self.__n_legs)) r_P = list([None] * (self.__n_legs)) v_P = list([None] * (self.__n_legs)) DV = list([None] * (self.__n_legs)) for i,planet in enumerate(self.seq): t_P[i] = epoch(x[0]+sum(T[:i+1])) r_P[i],v_P[i] = self.seq[i].eph(t_P[i]) #3 - We start with the first leg: a lambert arc theta = 2*pi*x[1] phi = acos(2*x[2]-1)-pi/2 r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection r = [JR*1000*d for d in r] l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,self.common_mu, False, False) #Lambert arc to reach seq[1] v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #First DSM occuring at the very beginning (will be cancelled by the optimizer) DV[0] = abs(norm(v_beg_l) - 3400) #4 - And we proceed with each successive leg for i in xrange(1,self.__n_legs): #Fly-by v_out = fb_prop(v_end_l,v_P[i-1],x[6+(i-1)*4]*self.seq[i-1].radius,x[5+(i-1)*4],self.seq[i-1].mu_self) #s/c propagation before the DSM r,v = propagate_lagrangian(r_P[i-1],v_out,x[7+(i-1)*4]*T[i]*DAY2SEC,self.common_mu) #Lambert arc to reach Earth during (1-nu2)*T2 (second segment) dt = (1-x[7+(i-1)*4])*T[i]*DAY2SEC l = lambert_problem(r,r_P[i],dt,self.common_mu, False, False) v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] tmp2, ra2 = closest_distance(r,v_beg_l, r_P[i], v_end_l, self.common_mu) if tmp < tmp2: close_d[i] = tmp/JR ra = ra/JR else: close_d[i] = tmp2/JR ra = ra2/JR #DSM occuring at time nu2*T2 DV[i] = norm([a-b for a,b in zip(v_beg_l,v)]) coeff = 0.3 for i in xrange(0,self.__n_legs): ratio[i] = (DV[i]/(T[i]*DAY2SEC)) DV_2rj[i] = DV[i] + max((2.0-close_d[i]),0.0)*1000 + max((ratio[i]-coeff*(0.1/2000)),0.0)*100 T_2rj[i] = T[i] + max((2.0-close_d[i]),0.0)*1000 + max((ratio[i]-coeff*(0.1/2000)),0.0)*100 #if self.f_dimension == 1: # return (sum(DV) #else: # return (sum(DV), sum(T)) if self.f_dimension == 1: return (sum(DV_2rj)) else: return (sum(DV_2rj), sum(T_2rj))
def plot(self, x):
"""
Plots the trajectory represented by the decision vector x
Example::
prob.plot(x)
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.scatter(0, 0, 0, color='y')
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T
T = list([0] * (self.__n_legs))
#a[-i] = x[-1-(i-1)*4]
for i in xrange(self.__n_legs - 1):
j = i + 1
T[-j] = (x[5] - sum(T[-(j - 1):])) * x[-1 - (j - 1) * 4]
T[0] = x[5] - sum(T)
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs + 1))
r_P = list([None] * (self.__n_legs + 1))
v_P = list([None] * (self.__n_legs + 1))
DV = list([None] * (self.__n_legs + 1))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[0:i]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(ax,
planet,
t0=t_P[i],
color=(0.8, 0.6, 0.8),
legend=True,
units=AU)
#3 - We start with the first leg
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
v0 = [a + b for a, b in zip(v_P[0], [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(r_P[0], v0, x[4] * T[0] * DAY2SEC,
self.common_mu)
plot_kepler(ax,
r_P[0],
v0,
x[4] * T[0] * DAY2SEC,
self.common_mu,
N=100,
color='b',
legend=False,
units=AU)
#Lambert arc to reach seq[1]
dt = (1 - x[4]) * T[0] * DAY2SEC
l = lambert_problem(r, r_P[1], dt, self.common_mu, False, False)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=AU)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#First DSM occuring at time nu1*T1
DV[0] = norm([a - b for a, b in zip(v_beg_l, v)])
#4 - And we proceed with each successive leg
for i in range(1, self.__n_legs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i],
x[7 + (i - 1) * 4] * self.seq[i].radius,
x[6 + (i - 1) * 4], self.seq[i].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
self.common_mu)
plot_kepler(ax,
r_P[i],
v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
self.common_mu,
N=100,
color='b',
legend=False,
units=AU)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[8 + (i - 1) * 4]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, self.common_mu, False,
False)
plot_lambert(ax,
l,
sol=0,
color='r',
legend=False,
units=AU,
N=1000)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
plt.show()
def plot(self,x): """ Plots the trajectory represented by the decision vector x Example:: prob.plot(x) """ import matplotlib as mpl from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler mpl.rcParams['legend.fontsize'] = 10 fig = plt.figure() ax = fig.gca(projection='3d') ax.scatter(0,0,0, color='y') #1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience T = list([0]*(self.__n_legs)) for i in xrange(self.__n_legs): T[i] = (x[4+4*i]/sum(x[4::4]))*x[3] #2 - We compute the epochs and ephemerides of the planetary encounters t_P = list([None] * (self.__n_legs)) r_P = list([None] * (self.__n_legs)) v_P = list([None] * (self.__n_legs)) DV = list([None] * (self.__n_legs)) for i,planet in enumerate(self.seq): t_P[i] = epoch(x[0]+sum(T[:i+1])) r_P[i],v_P[i] = self.seq[i].eph(t_P[i]) plot_planet(ax, planet, t0=t_P[i], color=(0.8,0.6,0.8), legend=True, units = JR) #3 - We start with the first leg: a lambert arc theta = 2*pi*x[1] phi = acos(2*x[2]-1)-pi/2 r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection r = [JR*1000*d for d in r] l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,self.common_mu, False, False) plot_lambert(ax,l, sol = 0, color='k', legend=False, units = JR, N=500) #Lambert arc to reach seq[1] v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #First DSM occuring at the very beginning (will be cancelled by the optimizer) DV[0] = abs(norm(v_beg_l) - 3400) #4 - And we proceed with each successive leg for i in xrange(1,self.__n_legs): #Fly-by v_out = fb_prop(v_end_l,v_P[i-1],x[6+(i-1)*4]*self.seq[i-1].radius,x[5+(i-1)*4],self.seq[i-1].mu_self) #s/c propagation before the DSM r,v = propagate_lagrangian(r_P[i-1],v_out,x[4*i+3]*T[i]*DAY2SEC,self.common_mu) plot_kepler(ax,r_P[i-1],v_out,x[7+(i-1)*4]*T[i]*DAY2SEC,self.common_mu,N = 500, color='b', legend=False, units = JR) #Lambert arc to reach Earth during (1-nu2)*T2 (second segment) dt = (1-x[7+(i-1)*4])*T[i]*DAY2SEC l = lambert_problem(r,r_P[i],dt,self.common_mu, False, False) plot_lambert(ax,l, sol = 0, color='r', legend=False, units = JR, N=500) v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #DSM occuring at time nu2*T2 DV[i] = norm([a-b for a,b in zip(v_beg_l,v)]) plt.show()
def stats(self,x):
import matplotlib as mpl
import matplotlib.pyplot as plt
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = list([0]*(self.__n_legs))
for i in xrange(self.__n_legs):
T[i] = (x[4+4*i]/sum(x[4::4]))*x[3]
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs))
r_P = list([None] * (self.__n_legs))
v_P = list([None] * (self.__n_legs))
DV = list([None] * (self.__n_legs))
close_d = list([None] * (self.__n_legs))
for i,planet in enumerate(self.seq):
t_P[i] = epoch(x[0]+sum(T[:i+1]))
r_P[i],v_P[i] = self.seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2*pi*x[1]
phi = acos(2*x[2]-1)-pi/2
r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR*1000*d for d in r]
l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,self.common_mu, False, False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
close_d[0] = closest_distance(r,v_beg_l, r_P[0], v_end_l, self.common_mu)[0] / JR
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
#4 - And we proceed with each successive leg
for i in xrange(1,self.__n_legs):
#Fly-by
v_out = fb_prop(v_end_l,v_P[i-1],x[6+(i-1)*4]*self.seq[i-1].radius,x[5+(i-1)*4],self.seq[i-1].mu_self)
#s/c propagation before the DSM
r,v = propagate_lagrangian(r_P[i-1],v_out,x[7+(i-1)*4]*T[i]*DAY2SEC,self.common_mu)
tmp, ra = closest_distance(r_P[i-1],v_out, r,v, self.common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1-x[7+(i-1)*4])*T[i]*DAY2SEC
l = lambert_problem(r,r_P[i],dt,self.common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
tmp2, ra2 = closest_distance(r,v_beg_l, r_P[i], v_end_l, self.common_mu)
if tmp < tmp2:
close_d[i] = tmp/JR
ra = ra/JR
else:
close_d[i] = tmp2/JR
ra = ra2/JR
#DSM occuring at time nu2*T2
DV[i] = norm([a-b for a,b in zip(v_beg_l,v)])
#print "Total mission time (days): " + str(sum(T))
#print "Total DV (m/s): " + str(sum(DV))
symbol_dict = {
'io' : 'yo',
'europa' : 'bo',
'ganymede' : 'ro',
'callisto' : 'ko' }
#for i in xrange(0,self.__n_legs):
# plt.plot(sum(DV), sum(T), symbol_dict[self.seq[0].name])
#n = 0
ratio = list([0]*(self.__n_legs))
coeff = 0.3
for i in xrange(0,self.__n_legs):
ratio[i] = (DV[i]/(T[i]*DAY2SEC))
if close_d[0] >= 2:
if close_d[1] >= 2:
if close_d[2] >= 2:
if close_d[3] >= 2:
if ratio[1] <= coeff*(0.1/2000):
if ratio[2] <= coeff*(0.1/2000):
if ratio[3] <= coeff*(0.1/2000):
if ratio[0] <= coeff*(0.1/2000):
plt.plot(sum(DV), sum(T), symbol_dict[self.seq[0].name])
#for i in xrange(0,self.__n_legs):
# if close_d[i] > 2:
# plt.plot(sum(DV), sum(T), symbol_dict[self.seq[0].name])
# else:
# print "\n the closest distance is less than 2*Rj "
#print "\n number of sequences that do not crash " + str(n)
plt.show()
def pretty(self,x):
"""
Prints human readable information on the trajectory represented by the decision vector x
Example::
prob.pretty(x)
"""
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = list([0]*(self.__n_legs))
for i in xrange(self.__n_legs):
T[i] = (x[4+4*i]/sum(x[4::4]))*x[3]
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs))
r_P = list([None] * (self.__n_legs))
v_P = list([None] * (self.__n_legs))
DV = list([None] * (self.__n_legs))
close_d = list([None] * (self.__n_legs))
for i,planet in enumerate(self.seq):
t_P[i] = epoch(x[0]+sum(T[:i+1]))
r_P[i],v_P[i] = self.seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2*pi*x[1]
phi = acos(2*x[2]-1)-pi/2
r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR*1000*d for d in r]
l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,self.common_mu, False, False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
close_d[0] = closest_distance(r,v_beg_l, r_P[0], v_end_l, self.common_mu)[0] / JR
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
print "\nFirst Leg: 1000JR to " + self.seq[0].name
print "\tDeparture: " + str(t_P[0]) + " (" + str(t_P[0].mjd2000) + " mjd2000) "
print "\tDuration: " + str(T[0]) + "days"
print "\tInitial Velocity Increment (m/s): " + str(DV[0])
print "\tArrival relative velocity at " + self.seq[0].name +" (m/s): " + str(norm([a-b for a,b in zip(v_end_l,v_P[0])]))
print "\tClosest approach distance: " + str(close_d[0])
#4 - And we proceed with each successive leg
for i in xrange(1,self.__n_legs):
#Fly-by
v_out = fb_prop(v_end_l,v_P[i-1],x[6+(i-1)*4]*self.seq[i-1].radius,x[5+(i-1)*4],self.seq[i-1].mu_self)
#s/c propagation before the DSM
r,v = propagate_lagrangian(r_P[i-1],v_out,x[7+(i-1)*4]*T[i]*DAY2SEC,self.common_mu)
tmp, ra = closest_distance(r_P[i-1],v_out, r,v, self.common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1-x[7+(i-1)*4])*T[i]*DAY2SEC
l = lambert_problem(r,r_P[i],dt,self.common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
tmp2, ra2 = closest_distance(r,v_beg_l, r_P[i], v_end_l, self.common_mu)
if tmp < tmp2:
close_d[i] = tmp/JR
ra = ra/JR
else:
close_d[i] = tmp2/JR
ra = ra2/JR
#DSM occuring at time nu2*T2
DV[i] = norm([a-b for a,b in zip(v_beg_l,v)])
print "\nleg no. " + str(i+1) + ": " + self.seq[i-1].name + " to " + self.seq[i].name
print "\tDuration (days): " + str(T[i])
print "\tFly-by epoch: " + str(t_P[i]) + " (" + str(t_P[i].mjd2000) + " mjd2000) "
print "\tFly-by altitude (km): " + str((x[6+(i-1)*4]*self.seq[i-1].radius-self.seq[i-1].radius)/1000)
print "\tDSM after (days): " + str(x[7+(i-1)*4]*T[i])
print "\tDSM magnitude (m/s): " + str(DV[i])
print "\tClosest approach distance: " + str(close_d[i])
print "\tApoapsis at closest distance: " + str(ra)
print "\tV in (m/s): " + str(v_end_l)
print "\tV out (m/s): " + str(v_out)
print "\nArrival at " + self.seq[-1].name
vel_inf = [a-b for a,b in zip(v_end_l,v_P[-1])]
print "Arrival epoch: " + str(t_P[-1]) + " (" + str(t_P[-1].mjd2000) + " mjd2000) "
print "Arrival Vinf (m/s): " + vel_inf.__repr__() + " - " + str(norm(vel_inf))
print "Total mission time (days): " + str(sum(T))
print "Total DV (m/s): " + str(sum(DV))
def getTraj(K1, K2, tlaunch, tarrive, N):
'''
Finds a trajectory between two objects orbiting the Sun
USAGE: traj = getTraj(K1, K2, tlaunch, tarrive)
K: array of object parameters.
epoch: epoch of Keplerian orbital elements (JD)
a: semimajor axis (AU)
e: eccentricity (none)
i: inclination (deg)
om: longitude of the ascending node (deg)
w: argument of perihelion (deg)
ma: mean anomaly at epoch (deg)
mass: mass of object (kg)
r: radius of object (m)
sr: safe radius to approach object (m)
K1: [epoch1,a1,e1,i1,om1,w1,ma1,mass1,r1,sr1]
K2: [epoch2,a2,e2,i2,om2,w2,ma2,mass2,r2,sr2]
tlaunch: launch time (JD)
tarrive: arrival time (JD)
N: number of points in calculated trajectory
'''
import numpy as np
from PyKEP import epoch, DAY2SEC, SEC2DAY, AU, DEG2RAD, MU_SUN, planet, lambert_problem, propagate_lagrangian
#Create PyKEP epoch objects and calculate flight time
t1 = epoch(tlaunch, epoch.epoch_type.JD)
t2 = epoch(tarrive, epoch.epoch_type.JD)
dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC
#First object
K1[0] = epoch(K1[0],
epoch.epoch_type.JD) #convert epoch to PyKEP epoch object
K1[1] = K1[1] * AU #convert AU to meters
K1[3] = K1[3] * DEG2RAD #convert angles from degrees to radians
K1[4] = K1[4] * DEG2RAD
K1[5] = K1[5] * DEG2RAD
K1[6] = K1[6] * DEG2RAD
K1[7] = K1[7] * 6.67384E-11 #convert mass to gravitational parameter mu
OBJ1 = planet(K1[0], K1[1:7], MU_SUN, K1[7], K1[8], K1[9])
#Second object
K2[0] = epoch(K2[0],
epoch.epoch_type.JD) #convert epoch to PyKEP epoch object
K2[1] = K2[1] * AU #convert AU to meters
K2[3] = K2[3] * DEG2RAD #convert angles from degrees to radians
K2[4] = K2[4] * DEG2RAD
K2[5] = K2[5] * DEG2RAD
K2[6] = K2[6] * DEG2RAD
K2[7] = K2[7] * 6.67384E-11 #convert mass to gravitational parameter mu
OBJ2 = planet(K2[0], K2[1:7], MU_SUN, K2[7], K2[8], K2[9])
#Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
#Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[0]
mu = l.get_mu()
#define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
traj = [t, x, y, z]
return traj
t1 = epoch(0)
t2 = epoch(740)
dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC
ax.scatter(0, 0, 0, color='y')
pl = planet_ss('earth')
plot_planet(ax, pl, t0=t1, color=(0.8, 0.8, 1), legend=True, units=AU)
rE, vE = pl.eph(t1)
pl = planet_ss('mars')
plot_planet(ax, pl, t0=t2, color=(0.8, 0.8, 1), legend=True, units=AU)
rM, vM = pl.eph(t2)
l = lambert_problem(rE, rM, dt, MU_SUN)
nmax = l.get_Nmax()
print "max number of revolutions", nmax
plot_lambert(ax, l, color=(1, 0, 0), legend=True, units=AU)
for i in range(1, nmax * 2 + 1):
print i
plot_lambert(ax,
l,
sol=i,
color=(1, 0, i / float(nmax * 2)),
legend=True,
units=AU)
def _get_score_data_incipit(self,x):
from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian
from math import pi, acos,cos,sin,sqrt
from scipy.linalg import norm
"""
This method returns the data needed to compute the score of a trajectory.
"""
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
nlegs = len(x)/4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
#2 - We compute the epochs and ephemerides of the planetary encounters
ep_list = list([None] * nlegs)
t_P = list([None] * nlegs)
r_P = list([None] * nlegs)
v_P = list([None] * nlegs)
DV = list([None] * nlegs)
for i,planet in enumerate(seq):
ep_list[i] = x[0]+sum(T[:i+1])
t_P[i] = epoch(x[0]+sum(T[:i+1]))
r_P[i],v_P[i] = seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2*pi*x[1]
phi = acos(2*x[2]-1)-pi/2
r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR*1000*d for d in r]
l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,common_mu, False, False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#init lists for fly-by parameters
vinf_list = []
rp_list = []
beta_list = []
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
#4 - And we proceed with each successive leg
for i in xrange(1,nlegs):
#Fly-by
v_out = fb_prop(v_end_l,v_P[i-1],x[1+4*i]*seq[i-1].radius,x[4*i],seq[i-1].mu_self)
vinf_list.append( [a-b for a,b in zip(v_end_l,v_P[i-1])] )
rp_list.append(x[1+4*i]*seq[i-1].radius)
beta_list.append(x[4*i])
#s/c propagation before the DSM
r,v = propagate_lagrangian(r_P[i-1],v_out,x[4*i+2]*T[i]*DAY2SEC,common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1-x[4*i+2])*T[i]*DAY2SEC
l = lambert_problem(r,r_P[i],dt,common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
vinf_list.append([a-b for a,b in zip(v_end_l,v_P[-1])])
rp_list.append(None)
beta_list.append(None)
return zip(ep_list, seq, vinf_list, rp_list, beta_list)
def traj_planet_asteroid(source, dest, tlaunch, tarrive, rev, N):
t1 = epoch(tlaunch)
t2 = epoch(tarrive)
dt = (tarrive - tlaunch) * DAY2SEC
target = source['orbit']
ep = epoch(jd_to_mjd(tlaunch), epoch.epoch_type.MJD)
a = target["a"] * AU
e = target["e"]
i = target["i"] * DEG2RAD
om = target["om"] * DEG2RAD
w = target["w"] * DEG2RAD
ma = target["ma"] * DEG2RAD
as_mu = 1E17 * 6.67384E-11 # maybe need to calculate actual mass from density and radius
r = (10 / 2) * 1000
sr = r * 1.1
OBJ1 = planet(ep, (a, e, i, om, w, ma), MU_SUN, as_mu, r, sr)
target = dest['orbit']
ep = epoch(jd_to_mjd(tarrive), epoch.epoch_type.MJD)
a = target["a"] * AU
e = target["e"]
i = target["i"] * DEG2RAD
om = target["om"] * DEG2RAD
w = target["w"] * DEG2RAD
ma = target["ma"] * DEG2RAD
as_mu = 1E17 * 6.67384E-11 # maybe need to calculate actual mass from density and radius
r = (10 / 2) * 1000
sr = r * 1.1
OBJ2 = planet(ep, (a, e, i, om, w, ma), MU_SUN, as_mu, r, sr)
# Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
#Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[0]
mu = l.get_mu() #define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
traj = [t.tolist(), x.tolist(), y.tolist(), z.tolist()]
return traj
def _objfun_impl(self, x):
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T
T = list([0] * (self.__n_legs))
for i in xrange(self.__n_legs - 1):
j = i + 1
T[-j] = (x[5] - sum(T[-(j - 1):])) * x[-1 - (j - 1) * 4]
T[0] = x[5] - sum(T)
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs + 1))
r_P = list([None] * (self.__n_legs + 1))
v_P = list([None] * (self.__n_legs + 1))
DV = list([0.0] * (self.__n_legs + 1))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[0:i]))
r_P[i], v_P[i] = self.seq[i].eph(t_P[i])
#3 - We start with the first leg
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
v0 = [a + b for a, b in zip(v_P[0], [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(r_P[0], v0, x[4] * T[0] * DAY2SEC,
self.common_mu)
#Lambert arc to reach seq[1]
dt = (1 - x[4]) * T[0] * DAY2SEC
l = lambert_problem(r, r_P[1], dt, self.common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#First DSM occuring at time nu1*T1
DV[0] = norm([a - b for a, b in zip(v_beg_l, v)])
#4 - And we proceed with each successive leg
for i in range(1, self.__n_legs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i],
x[7 + (i - 1) * 4] * self.seq[i].radius,
x[6 + (i - 1) * 4], self.seq[i].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
self.common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[8 + (i - 1) * 4]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, self.common_mu, False,
False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
#Last Delta-v
if self.__add_vinf_arr:
DV[-1] = norm([a - b for a, b in zip(v_end_l, v_P[-1])])
if self.__add_vinf_dep:
DV[0] += x[3]
if self.f_dimension == 1:
return (sum(DV), )
else:
return (sum(DV), sum(T))
def planet_asteroid(start_planet, target_name, tlaunch, tarrive, rev, N):
# Create PyKEP epoch objects and calculate flight time
t1 = epoch(tlaunch)
t2 = epoch(tarrive)
dt = (tarrive - tlaunch) * DAY2SEC
import py.AsteroidDB as asteroidDB
neo_db = asteroidDB.neo
target = (item for item in neo_db if item["name"] == target_name).next()
ep = epoch(target["epoch_mjd"], epoch.epoch_type.MJD)
a = target["a"] * AU
e = target["e"]
i = target["i"] * DEG2RAD
om = target["om"] * DEG2RAD
w = target["w"] * DEG2RAD
ma = target["ma"] * DEG2RAD
as_mu = 1E17 * 6.67384E-11 # maybe need to calculate actual mass from density and radius
r = (target["diameter"] / 2) * 1000
sr = r * 1.1
OBJ2 = planet(ep, (a, e, i, om, w, ma), MU_SUN, as_mu, r, sr)
OBJ1 = planet_ss(
start_planet) # Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
# Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[rev]
mu = l.get_mu()
#define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
#traj = [t, x, y, z]
vin = l.get_v1()[rev]
vout = l.get_v2()[rev]
#dV=fb_vel(vin,vout,planet_ss(arrive_planet))
#dV=np.sqrt( np.square(vin[0]/vout[0])+np.square(vin[1]/vout[1])+np.square(vin[2]/vout[2]))
#dV=np.sqrt( np.square(vin[0]-v1[0])+np.square(v1[1]-vin[1])+np.square(v1[2]-vin[2]))
#dV=np.sqrt( np.square(v2[0]-vout[0])+np.square(v2[1]-vout[1])+np.square(v2[2]-vout[2]))
#dV=np.sqrt( np.square(v1[0]/vin[0])+np.square(v1[1]/vin[1])+np.square(v1[2]/vin[2]))
C3_launch = (np.sqrt(
np.square(vin[0] - v1[0]) + np.square(vin[1] - v1[1]) +
np.square(vin[2] - v1[2])))**2
C3_arrive = (np.sqrt(
np.square(vout[0] - v2[0]) + np.square(vout[1] - v2[1]) +
np.square(vout[2] - v2[2])))**2
C3 = np.sqrt((C3_arrive**2) + (C3_launch**2))
return C3
def plot(self, x):
"""
Plots the trajectory represented by the decision vector x
Example::
prob.plot(x)
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.scatter(0, 0, 0, color='y')
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T
T = x[3::4]
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs))
r_P = list([None] * (self.__n_legs))
v_P = list([None] * (self.__n_legs))
DV = list([None] * (self.__n_legs))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = self.seq[i].eph(t_P[i])
plot_planet(ax,
planet,
t0=t_P[i],
color=(0.8, 0.6, 0.8),
legend=True,
units=JR)
#3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
r = [cos(phi) * sin(theta),
cos(phi) * cos(theta),
sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, self.common_mu, False,
False)
plot_lambert(ax, l, sol=0, color='k', legend=False, units=JR, N=500)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
#4 - And we proceed with each successive leg
for i in xrange(1, self.__n_legs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i - 1],
x[1 + 4 * i] * self.seq[i - 1].radius, x[4 * i],
self.seq[i - 1].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i - 1], v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
self.common_mu)
plot_kepler(ax,
r_P[i - 1],
v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
self.common_mu,
N=500,
color='b',
legend=False,
units=JR)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, self.common_mu, False, False)
plot_lambert(ax,
l,
sol=0,
color='r',
legend=False,
units=JR,
N=500)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
plt.show()
return ax
def _get_lt_problem(self, x, n_seg=[10, 10], high_fidelity=True):
"""
This method returns the equivalent low-thrust problem of an incipit
"""
from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian
from PyGMO import population
from math import pi, acos, cos, sin, sqrt, exp
from scipy.linalg import norm
retval = []
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
n_legs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (n_legs))
r_P = list([None] * (n_legs))
v_P = list([None] * (n_legs))
DV = list([None] * (n_legs))
for i, planet in enumerate(seq):
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
r = [cos(phi) * sin(theta),
cos(phi) * cos(theta),
sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, common_mu, False, False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#We start appending in the lt chromosome (see mga_incipit_lt)
retval.append(theta)
retval.append(phi)
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
#Start of the first lt leg encoding
retval.append(T[0])
retval.append(exp(-DV[0] / 9.80665 / 2000) * 2000) #Tsiolkowsky
retval.extend(v_beg_l)
retval.extend([a - b for a, b in zip(v_end_l, v_P[0])])
#4 - And we proceed with each successive leg
for i in xrange(1, n_legs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i - 1], x[1 + 4 * i] * seq[i - 1].radius,
x[4 * i], seq[i - 1].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i - 1], v_out,
x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
#lt encoding of all legs
retval.append(T[i])
retval.append(exp(-sum(DV[:i + 1]) / 9.80665 / 2000) *
2000) #Tsiolkowsky
retval.extend([a - b for a, b in zip(v_out, v_P[i - 1])])
if i != n_legs - 1:
retval.extend([a - b for a, b in zip(v_end_l, v_P[i])])
retval = retval + [0] * sum(n_seg) * 3
prob = mga_incipit_lt(high_fidelity=high_fidelity,
seq=seq,
n_seg=n_seg,
tf=epoch(x[0] + sum(T)),
vf=[a - b for a, b in zip(v_end_l, v_P[i])])
# solves the problem of chemical trajectories wanting higher launch dv
ub = list(prob.ub)
lb = list(prob.lb)
ub[4:7] = [5000, 5000, 5000]
lb[4:7] = [-5000, -5000, -5000]
prob.set_bounds(lb, ub)
pop = population(prob)
pop.push_back(retval)
return (prob, pop)
def traj_planet_asteroid(source, dest, tlaunch, tarrive, rev, N):
t1 = epoch(tlaunch)
t2 = epoch(tarrive)
dt = (tarrive - tlaunch) * DAY2SEC
target = source['orbit']
ep = epoch(jd_to_mjd(tlaunch), epoch.epoch_type.MJD)
a = target["a"] * AU
e = target["e"]
i = target["i"] * DEG2RAD
om = target["om"] * DEG2RAD
w = target["w"] * DEG2RAD
ma = target["ma"] * DEG2RAD
as_mu = 1E17 * 6.67384E-11 # maybe need to calculate actual mass from density and radius
r = (10 / 2) * 1000
sr = r * 1.1
OBJ1 = planet(ep, (a, e, i, om, w, ma), MU_SUN, as_mu, r, sr)
target = dest['orbit']
ep = epoch(jd_to_mjd(tarrive), epoch.epoch_type.MJD)
a = target["a"] * AU
e = target["e"]
i = target["i"] * DEG2RAD
om = target["om"] * DEG2RAD
w = target["w"] * DEG2RAD
ma = target["ma"] * DEG2RAD
as_mu = 1E17 * 6.67384E-11 # maybe need to calculate actual mass from density and radius
r = (10 / 2) * 1000
sr = r * 1.1
OBJ2 = planet(ep, (a, e, i, om, w, ma), MU_SUN, as_mu, r, sr)
# Calculate location of objects in flight path
r1, v1 = OBJ1.eph(t1)
r2, v2 = OBJ2.eph(t2)
#Find trajectory
l = lambert_problem(r1, r2, dt, MU_SUN)
#extract relevant information from solution
r = l.get_r1()
v = l.get_v1()[0]
mu = l.get_mu() #define the integration time
dtn = dt / (N - 1)
dtn_days = dtn * SEC2DAY
#alocate the cartesian components for r
t = np.array([0.0] * N)
x = np.array([0.0] * N)
y = np.array([0.0] * N)
z = np.array([0.0] * N)
#calculate the spacecraft position at each dt
for i in range(N):
t[i] = tlaunch + dtn_days * i
x[i] = r[0] / AU
y[i] = r[1] / AU
z[i] = r[2] / AU
r, v = propagate_lagrangian(r, v, dtn, mu)
traj = [t.tolist(), x.tolist(), y.tolist(), z.tolist()]
return traj
def _mga_incipit_plot_old(self, x, plot_leg_0=False):
"""
Plots the trajectory represented by the decision vector x
Example::
prob.plot(x)
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d', aspect='equal')
ax.scatter(0, 0, 0, color='y')
JR = 71492000.0
legs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T
T = x[3::4]
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * legs)
r_P = list([None] * legs)
v_P = list([None] * legs)
DV = list([None] * legs)
for i, planet in enumerate(seq):
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(ax, planet, t0=t_P[i], color=(
0.8, 0.6, 0.8), legend=True, units = JR)
# 3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
# phi close to zero is in the moon orbit plane injection
r = [cos(phi) * sin(theta), cos(phi) * cos(theta), sin(phi)]
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, common_mu, False, False)
if (plot_leg_0):
plot_lambert(ax, l, sol=0, color='k', legend=False, units=JR, N=500)
# Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# 4 - And we proceed with each successive leg
for i in range(1, legs):
# Fly-by
v_out = fb_prop(v_end_l,
v_P[i - 1],
x[1 + 4 * i] * seq[i - 1].radius,
x[4 * i],
seq[i - 1].mu_self)
# s/c propagation before the DSM
r, v = propagate_lagrangian(
r_P[i - 1], v_out, x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
plot_kepler(ax,
r_P[i - 1],
v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
common_mu,
N=500,
color='b',
legend=False,
units=JR)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, common_mu, False, False)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=JR, N=500)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
plt.show()
return ax
def _mga_1dsm_tof_plot_old(self, x):
"""
Plots the trajectory represented by the decision vector x
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.scatter(0, 0, 0, color='y')
seq = self.get_sequence()
n = (len(seq) - 1)
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T
T = x[5::4]
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (n + 1))
r_P = list([None] * (n + 1))
v_P = list([None] * (n + 1))
DV = list([None] * (n + 1))
for i, planet in enumerate(seq):
t_P[i] = epoch(x[0] + sum(T[0:i]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(ax,
planet,
t0=t_P[i],
color=(0.8, 0.6, 0.8),
legend=True,
units=AU)
# 3 - We start with the first leg
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
v0 = [a + b for a, b in zip(v_P[0], [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(r_P[0], v0, x[4] * T[0] * DAY2SEC,
seq[0].mu_central_body)
plot_kepler(ax,
r_P[0],
v0,
x[4] * T[0] * DAY2SEC,
seq[0].mu_central_body,
N=100,
color='b',
legend=False,
units=AU)
# Lambert arc to reach seq[1]
dt = (1 - x[4]) * T[0] * DAY2SEC
l = lambert_problem(r, r_P[1], dt, seq[0].mu_central_body)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=AU)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# First DSM occuring at time nu1*T1
DV[0] = norm([a - b for a, b in zip(v_beg_l, v)])
# 4 - And we proceed with each successive leg
for i in range(1, n):
# Fly-by
v_out = fb_prop(v_end_l, v_P[i], x[7 + (i - 1) * 4] * seq[i].radius,
x[6 + (i - 1) * 4], seq[i].mu_self)
# s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
seq[0].mu_central_body)
plot_kepler(ax,
r_P[i],
v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
seq[0].mu_central_body,
N=100,
color='b',
legend=False,
units=AU)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[8 + (i - 1) * 4]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, seq[0].mu_central_body)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=AU)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# DSM occurring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
return ax
r1 = np.array([6778136,0,0])
# r2 = np.array([-6978136,0.00007,0])
r2 = np.array([0,6043243.047,3489068])
v0 = np.array([0,7668.558733,0])
# v3 = np.array([0.000000008,-7557.86574,0])
v3 = np.array([-7557.86574,0,0])
r1a = math.sqrt(r1[0]**2+r1[1]**2+r1[2]**2)
MU_EARTH = 3.986004418e14
dt = 3.1415926535* math.sqrt((r1a+100000)**3/MU_EARTH) # seconds
l = lambert_problem(r1, r2, dt*.5, MU_EARTH)
fig2 = plt.figure(2)
axis2 = fig2.gca(projection='3d')
axis2.scatter([0], [0], [0], color='y')
plot_lambert(l, sol=0, ax=axis2, color='r')
# plot_lambert(l, sol=1, ax=axis2, color='r')
x0 = l.get_x()[0]
plot_kepler(r1, v0, dt*2, MU_EARTH, N=600, units=1, color='b',legend=False, ax=axis2)
plot_kepler(r2, v3, dt*2.2, MU_EARTH, N=600, units=1, color='b',legend=False, ax=axis2)
axis2.set_ylim3d(-1.2*6378000,1.2*6378000)
axis2.set_xlim3d(-1.2*6378000,1.2*6378000)
plt.xlabel('X coordinate [m]')
plt.ylabel('Y coordinate [m]')
# plt.zlabel('Z coordinate [m]')
# plt.ylabel('DV [m/s]')
plt.title('Lambert transfers for 200km altitude increase with different time of flight')
def _mga_part_plot_old(self, x):
"""
Plots the trajectory represented by the decision vector x
Example::
prob.plot(x)
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d', aspect='equal')
ax.scatter(0, 0, 0, color='y')
JR = 71492000.0
legs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
start_mjd2000 = self.t0.mjd2000
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T
T = x[3::4]
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (legs + 1))
r_P = list([None] * (legs + 1))
v_P = list([None] * (legs + 1))
for i, planet in enumerate(seq):
t_P[i] = epoch(start_mjd2000 + sum(T[:i]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(ax,
planet,
t0=t_P[i],
color=(0.8, 0.6, 0.8),
legend=True,
units=JR)
v_end_l = [a + b for a, b in zip(v_P[0], self.vinf_in)]
# 4 - And we iterate on the legs
for i in range(0, legs):
# Fly-by
v_out = fb_prop(v_end_l, v_P[i], x[1 + 4 * i] * seq[i - 1].radius,
x[4 * i], seq[i].mu_self)
# s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
plot_kepler(ax,
r_P[i],
v_out,
x[4 * i + 2] * T[i] * DAY2SEC,
common_mu,
N=500,
color='b',
legend=False,
units=JR)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, common_mu, False, False)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=JR, N=500)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
plt.show()
return ax
def _objfun_impl(self,x):
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T
T = list([0]*(self.__n))
#a[-i] = x[-1-(i-1)*4]
for i in xrange(self.__n-1):
j = i+1;
T[-j] = (x[5] - sum(T[-(j-1):])) * x[-1-(j-1)*4]
T[0] = x[5] - sum(T)
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n+1))
r_P = list([None] * (self.__n+1))
v_P = list([None] * (self.__n+1))
DV = list([None] * (self.__n+1))
for i,planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[0:i]))
r_P[i],v_P[i] = self.seq[i].eph(t_P[i])
#3 - We start with the first leg
theta = 2*pi*x[1]
phi = acos(2*x[2]-1)-pi/2
Vinfx = x[3]*cos(phi)*cos(theta)
Vinfy = x[3]*cos(phi)*sin(theta)
Vinfz = x[3]*sin(phi)
v0 = [a+b for a,b in zip(v_P[0], [Vinfx,Vinfy,Vinfz])]
r,v = propagate_lagrangian(r_P[0], v0, x[4]*T[0]*DAY2SEC, MU_SUN)
#Lambert arc to reach seq[1]
dt = (1-x[4])*T[0]*DAY2SEC
l = lambert_problem(r,r_P[1],dt,MU_SUN)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#First DSM occuring at time nu1*T1
DV[0] = norm([a-b for a,b in zip(v_beg_l, v)])
#4 - And we proceed with each successive leg
for i in range(1,self.__n):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i] ,x[7+(i-1)*4]*self.seq[i].radius, x[6+(i-1)*4], self.seq[i].mu_self)
#s/c propagation before the DSM
r,v = propagate_lagrangian(r_P[i], v_out, x[8+(i-1)*4]*T[i]*DAY2SEC, MU_SUN)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1-x[8+(i-1)*4])*T[i]*DAY2SEC
l = lambert_problem(r, r_P[i+1], dt, MU_SUN)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#DSM occuring at time nu2*T2
DV[i] = norm([a-b for a,b in zip(v_beg_l, v)])
#Last Delta-v
DV[-1] = norm([a-b for a,b in zip(v_end_l,v_P[-1])])
#moje
Eh56500 = 61933310.95
#Eh100000 = 61517435.56
entry_Vel = (DV[-1]**2 + 2*Eh56500)**0.5
entry_Vel2 = entry_Vel
#axtl = 23.43929*DEG2RAD
#DEC = abs(asin( sin(axtl)*cos(phi)*sin(theta) + cos(axtl)*sin(phi) ))*RAD2DEG # deklinacja asymptoty ucieczkowej
sum_dv = sum(DV[:-1])
eff_C3 = (x[3])**2
if entry_Vel < self.entry_vel_barrier:
entry_Vel2 = 0.0
del DV[-1]
#~ if eff_C3 < self.C3_barrier:
#~ #eff_C3 = 0
#~ pass
if sum_dv < self.dsm_dv_barrier:
sum_dv = 0+entry_Vel2
else:
sum_dv = sum(DV)
if self.f_dimension == 1:
return (sum_dv,)
else:
return (sum_dv, eff_C3, entry_Vel2) #,
def _mga_1dsm_tof_plot_old(self, x):
"""
Plots the trajectory represented by the decision vector x
"""
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PyKEP.orbit_plots import plot_planet, plot_lambert, plot_kepler
from PyKEP import epoch, propagate_lagrangian, lambert_problem, fb_prop, AU, MU_SUN, DAY2SEC
from math import pi, acos, cos, sin
from scipy.linalg import norm
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.scatter(0, 0, 0, color='y')
seq = self.get_sequence()
n = (len(seq) - 1)
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T
T = x[5::4]
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (n + 1))
r_P = list([None] * (n + 1))
v_P = list([None] * (n + 1))
DV = list([None] * (n + 1))
for i, planet in enumerate(seq):
t_P[i] = epoch(x[0] + sum(T[0:i]))
r_P[i], v_P[i] = planet.eph(t_P[i])
plot_planet(ax, planet, t0=t_P[i], color=(
0.8, 0.6, 0.8), legend=True, units = AU)
# 3 - We start with the first leg
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
v0 = [a + b for a, b in zip(v_P[0], [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(
r_P[0], v0, x[4] * T[0] * DAY2SEC, seq[0].mu_central_body)
plot_kepler(
ax,
r_P[0],
v0,
x[4] *
T[0] *
DAY2SEC,
seq[0].mu_central_body,
N=100,
color='b',
legend=False,
units=AU)
# Lambert arc to reach seq[1]
dt = (1 - x[4]) * T[0] * DAY2SEC
l = lambert_problem(r, r_P[1], dt, seq[0].mu_central_body)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=AU)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# First DSM occuring at time nu1*T1
DV[0] = norm([a - b for a, b in zip(v_beg_l, v)])
# 4 - And we proceed with each successive leg
for i in range(1, n):
# Fly-by
v_out = fb_prop(v_end_l,
v_P[i],
x[7 + (i - 1) * 4] * seq[i].radius,
x[6 + (i - 1) * 4],
seq[i].mu_self)
# s/c propagation before the DSM
r, v = propagate_lagrangian(
r_P[i], v_out, x[8 + (i - 1) * 4] * T[i] * DAY2SEC, seq[0].
mu_central_body)
plot_kepler(ax,
r_P[i],
v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
seq[0].mu_central_body,
N=100,
color='b',
legend=False,
units=AU)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[8 + (i - 1) * 4]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, seq[0].mu_central_body)
plot_lambert(ax, l, sol=0, color='r', legend=False, units=AU)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# DSM occurring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
return ax
t1 = epoch(0)
t2 = epoch(740)
dt = (t2.mjd2000 - t1.mjd2000) * DAY2SEC
ax.scatter(0,0,0, color='y')
pl = planet_ss('earth')
plot_planet(ax,pl, t0=t1, color=(0.8,0.8,1), legend=True, units = AU)
rE,vE = pl.eph(t1)
pl = planet_ss('mars')
plot_planet(ax,pl, t0=t2, color=(0.8,0.8,1), legend=True, units = AU)
rM, vM = pl.eph(t2)
l = lambert_problem(rE,rM,dt,MU_SUN)
nmax = l.get_Nmax()
print "max number of revolutions",nmax
plot_lambert(ax,l , color=(1,0,0), legend=True, units = AU)
for i in range(1,nmax*2+1):
print i
plot_lambert(ax,l,sol=i, color=(1,0,i/float(nmax*2)), legend=True, units = AU)
def axisEqual3D(ax):
extents = np.array([getattr(ax, 'get_{}lim'.format(dim))() for dim in 'xyz'])
sz = extents[:,1] - extents[:,0]
centers = np.mean(extents, axis=1)
def _compute_DV_DT_incipit(self, x):
"""
This method computes, for each leg, all the velocity increments coming from
deep space manoeuvres and all the transfer times.
Use:
DV,DT = prob.compute_DV_DT(x)
* x: trajectory encoding
"""
from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian
from math import pi, acos, cos, sin, sqrt
from scipy.linalg import norm
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
n_legs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (n_legs))
r_P = list([None] * (n_legs))
v_P = list([None] * (n_legs))
DV = list([None] * (n_legs))
for i, planet in enumerate(seq):
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
r = [cos(phi) * sin(theta),
cos(phi) * cos(theta),
sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, common_mu, False, False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
#4 - And we proceed with each successive leg
for i in xrange(1, n_legs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i - 1], x[1 + 4 * i] * seq[i - 1].radius,
x[4 * i], seq[i - 1].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i - 1], v_out,
x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
return (DV, T)
def ic_from_mga_1dsm(self, x):
"""
x_lt = prob.ic_from_mga_1dsm(x_mga)
- x_mga: compatible trajectory as encoded by an mga_1dsm problem
Returns an initial guess for the low-thrust trajectory, converting the mga_1dsm solution x_dsm. The user
is responsible that x_mga makes sense (i.e. it is a viable mga_1dsm representation). The conversion is done by importing in the
low-thrust encoding a) the launch date b) all the legs durations, c) the in and out relative velocities at each planet.
All throttles are put to zero.
Example::
x_lt= prob.ic_from_mga_1dsm(x_mga)
"""
from math import pi, cos, sin, acos
from scipy.linalg import norm
from PyKEP import propagate_lagrangian, lambert_problem, DAY2SEC, fb_prop
retval = list([0.0] * self.dimension)
# 1 - we 'decode' the chromosome recording the various times of flight (days) in the list T
T = list([0] * (self.__n_legs))
for i in range(len(T)):
T[i] = log(x[2 + 4 * i])
total = sum(T)
T = [x[1] * time / total for time in T]
retval[0] = x[0]
for i in range(self.__n_legs):
retval[1 + 8 * i] = T[i]
retval[2 + 8 * i] = self.__sc.mass
# 2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs + 1))
r_P = list([None] * (self.__n_legs + 1))
v_P = list([None] * (self.__n_legs + 1))
DV = list([None] * (self.__n_legs + 1))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[0:i]))
r_P[i], v_P[i] = self.seq[i].eph(t_P[i])
# 3 - We start with the first leg
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
retval[3:6] = [Vinfx, Vinfy, Vinfz]
v0 = [a + b for a, b in zip(v_P[0], [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(r_P[0], v0, x[4] * T[0] * DAY2SEC, MU_SUN)
# Lambert arc to reach seq[1]
dt = (1 - x[4]) * T[0] * DAY2SEC
l = lambert_problem(r, r_P[1], dt, MU_SUN)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
retval[6:9] = [a - b for a, b in zip(v_end_l, v_P[1])]
# 4 - And we proceed with each successive leg
for i in range(1, self.__n_legs):
# Fly-by
v_out = fb_prop(v_end_l, v_P[i],
x[7 + (i - 1) * 4] * self.seq[i].radius,
x[6 + (i - 1) * 4], self.seq[i].mu_self)
retval[3 + i * 8:6 +
i * 8] = [a - b for a, b in zip(v_out, v_P[i])]
# s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
MU_SUN)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[8 + (i - 1) * 4]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, MU_SUN)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
retval[6 + i * 8:9 +
i * 8] = [a - b for a, b in zip(v_end_l, v_P[i + 1])]
return retval
def _get_penalty_data(self,x): """ getTrajectory takes a genome x, and returns a Trajectory variable that is a list of all r, v, and time of flights Trajectory = [[r0, v0_out, r1, v1_in, tof, rp, ra, Trev, vinf], [r1, v1_out, r2, v2_in, tof, rp, ra, Trev, vinf], [...]] tof in days """ from PyKEP import epoch, lambert_problem, propagate_lagrangian, fb_prop, DAY2SEC; from math import pi, acos, cos, sin; import numpy as np; from _mass_penalty import get_rp_ra_Trev Trajectory = []; #1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience T = x[3::4] # reconstruct properties that are known in _mga_incipit: self.seq = self.get_sequence(); self.__n_legs = len(self.seq); self.common_mu = self.seq[0].mu_central_body #2 - We compute the epochs and ephemerides of the planetary encounters t_P = list([None] * (self.__n_legs)) r_P = list([None] * (self.__n_legs)) v_P = list([None] * (self.__n_legs)) DV = list([None] * (self.__n_legs)) for i,planet in enumerate(self.seq): t_P[i] = epoch(x[0]+sum(T[:i+1])) r_P[i],v_P[i] = self.seq[i].eph(t_P[i]) #3 - We start with the first leg: a lambert arc theta = 2*pi*x[1] phi = acos(2*x[2]-1)-pi/2 r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection r = [JR*1000*d for d in r] l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,self.common_mu, False, False) #Lambert arc to reach seq[1] v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] Tr = [tuple(r), v_beg_l, r_P[0], v_end_l, T[0]*DAY2SEC]; rPvec = np.asarray(r_P[0]); vPvec = np.asarray(v_end_l); Tr = Tr + get_rp_ra_Trev(rPvec, vPvec); vinf = vPvec - np.asarray(v_P[0]); Tr = Tr + [vinf]; Trajectory.append(Tr); #First DSM occuring at the very beginning (will be cancelled by the optimizer) DV[0] = abs(np.linalg.norm(v_beg_l) - 3400) #4 - And we proceed with each successive leg for i in xrange(1,self.__n_legs): #Fly-by v_out = fb_prop(v_end_l,v_P[i-1],x[1+4*i]*self.seq[i-1].radius,x[4*i],self.seq[i-1].mu_self) #s/c propagation before the DSM r,v = propagate_lagrangian(r_P[i-1],v_out,x[4*i+2]*T[i]*DAY2SEC,self.common_mu) # append r, v, etc. to the Trajectory: Tr = [r_P[i-1], v_out, r, v, x[4*i+2]*T[i]*DAY2SEC]; rPvec = np.asarray(r); vPvec = np.asarray(v); Tr = Tr + get_rp_ra_Trev(rPvec, vPvec); vinf = []; Tr = Tr + [vinf]; Trajectory.append(Tr); #Lambert arc to reach Earth during (1-nu2)*T2 (second segment) dt = (1-x[4*i+2])*T[i]*DAY2SEC l = lambert_problem(r,r_P[i],dt,self.common_mu, False, False) v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] # append r, v, etc. to the Trajectory: Tr = [r, v_beg_l, r_P[i], v_end_l, (1-x[4*i+2])*T[i]*DAY2SEC]; rPvec = np.asarray(r_P[i]); vPvec = np.asarray(v_end_l); Tr = Tr + get_rp_ra_Trev(rPvec, vPvec); vinf = vPvec - np.asarray(v_P[i]); Tr = Tr + [vinf]; Trajectory.append(Tr); #DSM occuring at time nu2*T2 DV[i] = np.linalg.norm([a-b for a,b in zip(v_beg_l,v)]) return Trajectory;
def _get_penalty_data_part(self, x):
from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian
from math import pi, acos, cos, sin, sqrt
from scipy.linalg import norm
from copy import deepcopy
from _mass_penalty import get_rp_ra_Trev
import numpy as np
"""
This method returns the data needed to compute the score of a trajectory.
"""
Trajectory = []
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
nlegs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
t0 = self.t0.mjd2000
vinf_in = deepcopy(self.vinf_in)
#2 - We compute the epochs and ephemerides of the planetary encounters
ep_list = list([None] * (nlegs + 1))
t_P = list([None] * (nlegs + 1))
r_P = list([None] * (nlegs + 1))
v_P = list([None] * (nlegs + 1))
DV = list([None] * nlegs)
for i, planet in enumerate(seq):
ep_list[i] = t0 + sum(T[:i])
t_P[i] = epoch(t0 + sum(T[:i]))
r_P[i], v_P[i] = seq[i].eph(t_P[i])
v_end_l = [a + b for a, b in zip(vinf_in, v_P[0])]
#3 - And we proceed with each successive leg
for i in xrange(nlegs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i], x[1 + 4 * i] * seq[i].radius,
x[4 * i], seq[i].mu_self)
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
# append r, v, etc. to the Trajectory:
Tr = [r_P[i - 1], v_out, r, v, x[4 * i + 2] * T[i] * DAY2SEC]
rPvec = np.asarray(r)
vPvec = np.asarray(v)
Tr = Tr + get_rp_ra_Trev(rPvec, vPvec)
vinf = []
Tr = Tr + [vinf]
Trajectory.append(Tr)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# append r, v, etc. to the Trajectory:
Tr = [
r, v_beg_l, r_P[i], v_end_l, (1 - x[4 * i + 2]) * T[i] * DAY2SEC
]
rPvec = np.asarray(r_P[i])
vPvec = np.asarray(v_end_l)
Tr = Tr + get_rp_ra_Trev(rPvec, vPvec)
vinf = vPvec - np.asarray(v_P[i])
Tr = Tr + [vinf]
Trajectory.append(Tr)
return Trajectory
def _get_penalty_data_part(self,x):
from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian
from math import pi, acos,cos,sin,sqrt
from scipy.linalg import norm
from copy import deepcopy
from _mass_penalty import get_rp_ra_Trev
import numpy as np
"""
This method returns the data needed to compute the score of a trajectory.
"""
Trajectory = [];
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
nlegs = len(x)/4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
t0 = self.t0.mjd2000
vinf_in = deepcopy(self.vinf_in)
#2 - We compute the epochs and ephemerides of the planetary encounters
ep_list = list([None] * (nlegs+1))
t_P = list([None] * (nlegs+1))
r_P = list([None] * (nlegs+1))
v_P = list([None] * (nlegs+1))
DV = list([None] * nlegs)
for i,planet in enumerate(seq):
ep_list[i] = t0+sum(T[:i])
t_P[i] = epoch(t0+sum(T[:i]))
r_P[i],v_P[i] = seq[i].eph(t_P[i])
v_end_l = [a+b for a,b in zip(vinf_in, v_P[0])]
#3 - And we proceed with each successive leg
for i in xrange(nlegs):
#Fly-by
v_out = fb_prop(v_end_l,v_P[i],x[1+4*i]*seq[i].radius,x[4*i],seq[i].mu_self)
#s/c propagation before the DSM
r,v = propagate_lagrangian(r_P[i],v_out,x[4*i+2]*T[i]*DAY2SEC,common_mu)
# append r, v, etc. to the Trajectory:
Tr = [r_P[i-1], v_out, r, v, x[4*i+2]*T[i]*DAY2SEC];
rPvec = np.asarray(r);
vPvec = np.asarray(v);
Tr = Tr + get_rp_ra_Trev(rPvec, vPvec);
vinf = [];
Tr = Tr + [vinf];
Trajectory.append(Tr);
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1-x[4*i+2])*T[i]*DAY2SEC
l = lambert_problem(r,r_P[i+1],dt,common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
# append r, v, etc. to the Trajectory:
Tr = [r, v_beg_l, r_P[i], v_end_l, (1-x[4*i+2])*T[i]*DAY2SEC];
rPvec = np.asarray(r_P[i]);
vPvec = np.asarray(v_end_l);
Tr = Tr + get_rp_ra_Trev(rPvec, vPvec);
vinf = vPvec - np.asarray(v_P[i]);
Tr = Tr + [vinf];
Trajectory.append(Tr);
return Trajectory;
def pretty(self, x):
"""
Prints human readable information on the trajectory represented by the decision vector x
Example::
prob.pretty(x)
"""
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T
T = list([0] * (self.__n_legs))
#a[-i] = x[-1-(i-1)*4]
for i in xrange(self.__n_legs - 1):
j = i + 1
T[-j] = (x[5] - sum(T[-(j - 1):])) * x[-1 - (j - 1) * 4]
T[0] = x[5] - sum(T)
#2 - We compute the epochs and ephemerides of the planetary encounters
t_P = list([None] * (self.__n_legs + 1))
r_P = list([None] * (self.__n_legs + 1))
v_P = list([None] * (self.__n_legs + 1))
DV = list([None] * (self.__n_legs + 1))
for i, planet in enumerate(self.seq):
t_P[i] = epoch(x[0] + sum(T[0:i]))
r_P[i], v_P[i] = self.seq[i].eph(t_P[i])
#3 - We start with the first leg
print "First Leg: " + self.seq[0].name + " to " + self.seq[1].name
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
Vinfx = x[3] * cos(phi) * cos(theta)
Vinfy = x[3] * cos(phi) * sin(theta)
Vinfz = x[3] * sin(phi)
print "Departure: " + str(t_P[0]) + " (" + str(
t_P[0].mjd2000) + " mjd2000) "
print "Duration: " + str(T[0]) + "days"
print "VINF: " + str(x[3] / 1000) + " km/sec"
v0 = [a + b for a, b in zip(v_P[0], [Vinfx, Vinfy, Vinfz])]
r, v = propagate_lagrangian(r_P[0], v0, x[4] * T[0] * DAY2SEC,
self.common_mu)
print "DSM after " + str(x[4] * T[0]) + " days"
#Lambert arc to reach seq[1]
dt = (1 - x[4]) * T[0] * DAY2SEC
l = lambert_problem(r, r_P[1], dt, self.common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#First DSM occuring at time nu1*T1
DV[0] = norm([a - b for a, b in zip(v_beg_l, v)])
print "DSM magnitude: " + str(DV[0]) + "m/s"
#4 - And we proceed with each successive leg
for i in range(1, self.__n_legs):
print "\nleg no. " + str(
i + 1) + ": " + self.seq[i].name + " to " + self.seq[i +
1].name
print "Duration: " + str(T[i]) + "days"
#Fly-by
v_out = fb_prop(v_end_l, v_P[i],
x[7 + (i - 1) * 4] * self.seq[i].radius,
x[6 + (i - 1) * 4], self.seq[i].mu_self)
print "Fly-by epoch: " + str(t_P[i]) + " (" + str(
t_P[i].mjd2000) + " mjd2000) "
print "Fly-by radius: " + str(x[7 +
(i - 1) * 4]) + " planetary radii"
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i], v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
self.common_mu)
print "DSM after " + str(x[8 + (i - 1) * 4] * T[i]) + " days"
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[8 + (i - 1) * 4]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i + 1], dt, self.common_mu, False,
False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#DSM occuring at time nu2*T2
DV[i] = norm([a - b for a, b in zip(v_beg_l, v)])
print "DSM magnitude: " + str(DV[i]) + "m/s"
#Last Delta-v
print "\nArrival at " + self.seq[-1].name
DV[-1] = norm([a - b for a, b in zip(v_end_l, v_P[-1])])
print "Arrival epoch: " + str(t_P[-1]) + " (" + str(
t_P[-1].mjd2000) + " mjd2000) "
print "Arrival Vinf: " + str(DV[-1]) + "m/s"
print "Total mission time: " + str(sum(T) / 365.25) + " years"
def _get_lt_problem(self,x,n_seg=[10,10], high_fidelity=True): """ This method returns the equivalent low-thrust problem of an incipit """ from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian from PyGMO import population from math import pi, acos,cos,sin,sqrt, exp from scipy.linalg import norm retval = [] #1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience T = x[3::4] n_legs = len(x)/4 seq = self.get_sequence() common_mu = seq[0].mu_central_body #2 - We compute the epochs and ephemerides of the planetary encounters t_P = list([None] * (n_legs)) r_P = list([None] * (n_legs)) v_P = list([None] * (n_legs)) DV = list([None] * (n_legs)) for i,planet in enumerate(seq): t_P[i] = epoch(x[0]+sum(T[:i+1])) r_P[i],v_P[i] = seq[i].eph(t_P[i]) #3 - We start with the first leg: a lambert arc theta = 2*pi*x[1] phi = acos(2*x[2]-1)-pi/2 r = [cos(phi)*sin(theta), cos(phi)*cos(theta), sin(phi)] #phi close to zero is in the moon orbit plane injection r = [JR*1000*d for d in r] l = lambert_problem(r,r_P[0],T[0]*DAY2SEC,common_mu, False, False) #Lambert arc to reach seq[1] v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #We start appending in the lt chromosome (see mga_incipit_lt) retval.append(theta) retval.append(phi) #First DSM occuring at the very beginning (will be cancelled by the optimizer) DV[0] = abs(norm(v_beg_l) - 3400) #Start of the first lt leg encoding retval.append(T[0]) retval.append(exp(-DV[0]/9.80665/2000)*2000) #Tsiolkowsky retval.extend(v_beg_l) retval.extend([a-b for a,b in zip(v_end_l,v_P[0])]) #4 - And we proceed with each successive leg for i in xrange(1,n_legs): #Fly-by v_out = fb_prop(v_end_l,v_P[i-1],x[1+4*i]*seq[i-1].radius,x[4*i],seq[i-1].mu_self) #s/c propagation before the DSM r,v = propagate_lagrangian(r_P[i-1],v_out,x[4*i+2]*T[i]*DAY2SEC,common_mu) #Lambert arc to reach Earth during (1-nu2)*T2 (second segment) dt = (1-x[4*i+2])*T[i]*DAY2SEC l = lambert_problem(r,r_P[i],dt,common_mu, False, False) v_end_l = l.get_v2()[0] v_beg_l = l.get_v1()[0] #DSM occuring at time nu2*T2 DV[i] = norm([a-b for a,b in zip(v_beg_l,v)]) #lt encoding of all legs retval.append(T[i]) retval.append(exp(-sum(DV[:i+1])/9.80665/2000)*2000) #Tsiolkowsky retval.extend([a-b for a,b in zip(v_out,v_P[i-1])]) if i != n_legs-1: retval.extend([a-b for a,b in zip(v_end_l,v_P[i])]) retval = retval + [0]*sum(n_seg)*3 prob = mga_incipit_lt(high_fidelity=high_fidelity,seq=seq, n_seg = n_seg,tf = epoch(x[0]+sum(T)), vf = [a-b for a,b in zip(v_end_l,v_P[i])]) # solves the problem of chemical trajectories wanting higher launch dv ub = list(prob.ub) lb = list(prob.lb) ub[4:7] = [5000,5000,5000] lb[4:7] = [-5000,-5000,-5000] prob.set_bounds(lb, ub) pop = population(prob) pop.push_back(retval) return (prob,pop)
from PyKEP import lambert_problem xs = arange(-2,2,0.05); nx=len(xs); ys = arange(-2,2,0.05); ny=len(ys); R1 = array([0.0,1.0,0.0]) R2 = array([0.0,0.0,0.0]) dt =0.7 axy = zeros((nx,ny)) for ix in range(nx): for iy in range(ny): R2[0] = xs[ix]; R2[1] = ys[iy]; try: lambert_result =lambert_problem(R1,R2,dt ) except: continue #lambert_result = lambert_problem([1,0,0],[0,1,0],5 * pi / 2. ) if lambert_result.is_reliable(): a = lambert_result.get_a()[0] axy[ix,iy]= a print ix,iy," R2= ",R2," a= ", a else: print ix,iy," R2= ",R2," failed " imshow( axy, vmax=2.5,vmin=0, interpolation='nearest' ) colorbar() show()
xs = arange(-2, 2, 0.05)
nx = len(xs)
ys = arange(-2, 2, 0.05)
ny = len(ys)
R1 = array([0.0, 1.0, 0.0])
R2 = array([0.0, 0.0, 0.0])
dt = 0.7
axy = zeros((nx, ny))
for ix in range(nx):
for iy in range(ny):
R2[0] = xs[ix]
R2[1] = ys[iy]
try:
lambert_result = lambert_problem(R1, R2, dt)
except:
continue
#lambert_result = lambert_problem([1,0,0],[0,1,0],5 * pi / 2. )
if lambert_result.is_reliable():
a = lambert_result.get_a()[0]
axy[ix, iy] = a
print ix, iy, " R2= ", R2, " a= ", a
else:
print ix, iy, " R2= ", R2, " failed "
imshow(axy, vmax=2.5, vmin=0, interpolation='nearest')
colorbar()
show()
'''
def _get_score_data_incipit(self, x):
from PyKEP import epoch, lambert_problem, DAY2SEC, fb_prop, propagate_lagrangian
from math import pi, acos, cos, sin, sqrt
from scipy.linalg import norm
"""
This method returns the data needed to compute the score of a trajectory.
"""
#1 - we 'decode' the chromosome recording the various times of flight (days) in the list T for convenience
T = x[3::4]
nlegs = len(x) / 4
seq = self.get_sequence()
common_mu = seq[0].mu_central_body
#2 - We compute the epochs and ephemerides of the planetary encounters
ep_list = list([None] * nlegs)
t_P = list([None] * nlegs)
r_P = list([None] * nlegs)
v_P = list([None] * nlegs)
DV = list([None] * nlegs)
for i, planet in enumerate(seq):
ep_list[i] = x[0] + sum(T[:i + 1])
t_P[i] = epoch(x[0] + sum(T[:i + 1]))
r_P[i], v_P[i] = seq[i].eph(t_P[i])
#3 - We start with the first leg: a lambert arc
theta = 2 * pi * x[1]
phi = acos(2 * x[2] - 1) - pi / 2
r = [cos(phi) * sin(theta),
cos(phi) * cos(theta),
sin(phi)] #phi close to zero is in the moon orbit plane injection
r = [JR * 1000 * d for d in r]
l = lambert_problem(r, r_P[0], T[0] * DAY2SEC, common_mu, False, False)
#Lambert arc to reach seq[1]
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
#init lists for fly-by parameters
vinf_list = []
rp_list = []
beta_list = []
#First DSM occuring at the very beginning (will be cancelled by the optimizer)
DV[0] = abs(norm(v_beg_l) - 3400)
#4 - And we proceed with each successive leg
for i in xrange(1, nlegs):
#Fly-by
v_out = fb_prop(v_end_l, v_P[i - 1], x[1 + 4 * i] * seq[i - 1].radius,
x[4 * i], seq[i - 1].mu_self)
vinf_list.append([a - b for a, b in zip(v_end_l, v_P[i - 1])])
rp_list.append(x[1 + 4 * i] * seq[i - 1].radius)
beta_list.append(x[4 * i])
#s/c propagation before the DSM
r, v = propagate_lagrangian(r_P[i - 1], v_out,
x[4 * i + 2] * T[i] * DAY2SEC, common_mu)
#Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[4 * i + 2]) * T[i] * DAY2SEC
l = lambert_problem(r, r_P[i], dt, common_mu, False, False)
v_end_l = l.get_v2()[0]
v_beg_l = l.get_v1()[0]
vinf_list.append([a - b for a, b in zip(v_end_l, v_P[-1])])
rp_list.append(None)
beta_list.append(None)
return zip(ep_list, seq, vinf_list, rp_list, beta_list)
