def _compute_dvs(self, x: List[float]) -> Tuple[
float, # DVlaunch
List[float], # DVs
float, # DVarrival,
List[Any], # Lambert legs
float, #DVlaunch_tot
List[float], # T
List[Tuple[List[float], List[float]]], # ballistic legs
List[float], # epochs of ballistic legs
]:
# 1 - we 'decode' the times of flights and compute epochs (mjd2000)
T: List[float] = self._decode_tofs(x) # [T1, T2 ...]
ep = np.insert(T, 0, x[0]) # [t0, T1, T2 ...]
ep = np.cumsum(ep) # [t0, t1, t2, ...]
# 2 - we compute the ephemerides
r = [0] * len(self.seq)
v = [0] * len(self.seq)
for i in range(len(self.seq)):
r[i], v[i] = self.seq[i].eph(float(ep[i]))
l = list()
ballistic_legs: List[Tuple[List[float], List[float]]] = []
ballistic_ep: List[float] = []
# 3 - we solve the lambert problems
vi = v[0]
for i in range(self._n_legs):
lp = lambert_problem_multirev(
vi,
lambert_problem(r[i], r[i + 1], T[i] * DAY2SEC,
self._common_mu, False, self.max_revs))
l.append(lp)
vi = lp.get_v2()[0]
ballistic_legs.append((r[i], lp.get_v1()[0]))
ballistic_ep.append(ep[i])
# 4 - we compute the various dVs needed at fly-bys to match incoming
# and outcoming
DVfb = list()
for i in range(len(l) - 1):
vin = [a - b for a, b in zip(l[i].get_v2()[0], v[i + 1])]
vout = [a - b for a, b in zip(l[i + 1].get_v1()[0], v[i + 1])]
DVfb.append(fb_vel(vin, vout, self.seq[i + 1]))
# 5 - we add the departure and arrival dVs
DVlaunch_tot = np.linalg.norm(
[a - b for a, b in zip(v[0], l[0].get_v1()[0])])
DVlaunch = max(0, DVlaunch_tot - self.vinf)
DVarrival = np.linalg.norm(
[a - b for a, b in zip(v[-1], l[-1].get_v2()[0])])
if self.orbit_insertion:
# In this case we compute the insertion DV as a single pericenter
# burn
DVper = np.sqrt(DVarrival * DVarrival +
2 * self.seq[-1].mu_self / self.rp_target)
DVper2 = np.sqrt(2 * self.seq[-1].mu_self / self.rp_target -
self.seq[-1].mu_self / self.rp_target *
(1. - self.e_target))
DVarrival = np.abs(DVper - DVper2)
return (DVlaunch, DVfb, DVarrival, l, DVlaunch_tot, T, ballistic_legs,
ballistic_ep)
def pretty(self, x):
"""
prob.plot(x)
- x: encoded trajectory
Prints human readable information on the trajectory represented by the decision vector x
Example::
print(prob.pretty(x))
"""
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T and the cartesian components of vinf
T, Vinfx, Vinfy, Vinfz = self._decode_times_and_vinf(x)
# 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 in range(len(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)
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_multirev(
v,
lambert_problem(r,
r_P[1],
dt,
self.common_mu,
cw=False,
max_revs=self.max_revs))
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_multirev(
v,
lambert_problem(r,
r_P[i + 1],
dt,
self.common_mu,
cw=False,
max_revs=self.max_revs))
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")
if self._orbit_insertion:
# In this case we compute the insertion DV as a single pericenter
# burn
DVper = np.sqrt(DV[-1] * DV[-1] +
2 * self._seq[-1].mu_self / self._rp_target)
DVper2 = np.sqrt(2 * self._seq[-1].mu_self / self._rp_target -
self._seq[-1].mu_self / self._rp_target *
(1. - self._e_target))
DVinsertion = np.abs(DVper - DVper2)
print("Insertion DV: " + str(DVinsertion) + "m/s")
print("Total mission time: " + str(sum(T) / 365.25) + " years (" +
str(sum(T)) + " days)")
def plot(self, x, ax=None):
"""
ax = prob.plot(x, ax=None)
- x: encoded trajectory
- ax: matplotlib axis where to plot. If None figure and axis will be created
- [out] ax: matplotlib axis where to plot
Plots the trajectory represented by a decision vector x on the 3d axis ax
Example::
ax = 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
if ax is None:
mpl.rcParams['legend.fontsize'] = 10
fig = plt.figure()
axis = fig.gca(projection='3d')
else:
axis = ax
axis.scatter(0, 0, 0, color='y')
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T and the cartesian components of vinf
T, Vinfx, Vinfy, Vinfz = self._decode_times_and_vinf(x)
# 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(planet,
t0=t_P[i],
color=(0.8, 0.6, 0.8),
legend=True,
units=AU,
axes=axis,
N=150)
# 3 - We start with the first leg
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(r_P[0],
v0,
x[4] * T[0] * DAY2SEC,
self.common_mu,
N=100,
color='b',
units=AU,
axes=axis)
# Lambert arc to reach seq[1]
dt = (1 - x[4]) * T[0] * DAY2SEC
l = lambert_problem_multirev(
v,
lambert_problem(r,
r_P[1],
dt,
self.common_mu,
cw=False,
max_revs=self.max_revs))
plot_lambert(l, sol=0, color='r', units=AU, axes=axis)
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(r_P[i],
v_out,
x[8 + (i - 1) * 4] * T[i] * DAY2SEC,
self.common_mu,
N=100,
color='b',
units=AU,
axes=axis)
# Lambert arc to reach Earth during (1-nu2)*T2 (second segment)
dt = (1 - x[8 + (i - 1) * 4]) * T[i] * DAY2SEC
l = lambert_problem_multirev(
v,
lambert_problem(r,
r_P[i + 1],
dt,
self.common_mu,
cw=False,
max_revs=self.max_revs))
plot_lambert(l,
sol=0,
color='r',
legend=False,
units=AU,
N=1000,
axes=axis)
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 axis
def fitness(self, x):
# 1 - we 'decode' the chromosome recording the various times of flight
# (days) in the list T and the cartesian components of vinf
T, Vinfx, Vinfy, Vinfz = self._decode_times_and_vinf(x)
# 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 in range(len(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
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_multirev(
v,
lambert_problem(r,
r_P[1],
dt,
self.common_mu,
cw=False,
max_revs=self.max_revs))
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_multirev(
v,
lambert_problem(r,
r_P[i + 1],
dt,
self.common_mu,
cw=False,
max_revs=self.max_revs))
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._orbit_insertion:
# In this case we compute the insertion DV as a single pericenter
# burn
DVper = np.sqrt(DV[-1] * DV[-1] +
2 * self._seq[-1].mu_self / self._rp_target)
DVper2 = np.sqrt(2 * self._seq[-1].mu_self / self._rp_target -
self._seq[-1].mu_self / self._rp_target *
(1. - self._e_target))
DV[-1] = np.abs(DVper - DVper2)
if self._add_vinf_dep:
DV[0] += x[3]
if not self._multi_objective:
return (sum(DV), )
else:
return (sum(DV), sum(T))