def J(t0, tof):
ep1 = pk.epoch(t0)
ep2 = pk.epoch(t0 + tof)
r1, v1 = p1.eph(ep1)
r2, v2 = p2.eph(ep2)
resJ = []
for lw in [False, True]:
prob = pk.lambert_exposin(r1, r2, tof * pk.DAY2SEC, pk.MU_SUN, lw, n,
k2)
for i in range(prob.num_solutions()):
exps = prob.get_exposins()[i]
dv1 = Vector.mag(Vector.sub(prob.get_v1()[i], v1))
dv2 = Vector.mag(Vector.sub(prob.get_v2()[i], v2))
dvlt = exps.get_delta_v(pk.MU_SUN)
resJ.append(1.0 - math.exp(-(dv1 + dv2) / 9.81 / isp_chem -
dvlt / 9.81 / isp_lt))
if len(resJ) == 0:
return numpy.nan
else:
return numpy.nanmin(resJ)
Check the state vector of an exposin for discrepancies
'''
import PyKEP
earth = PyKEP.planet.jpl_lp('earth')
mars = PyKEP.planet.jpl_lp('mars')
k2 = 0.6
n = 1
t0 = 250.0
tof = 520.0
lw = True
r1, v1 = earth.eph(PyKEP.epoch(t0, "mjd2000"))
r2, v2 = mars.eph(PyKEP.epoch(t0 + tof, "mjd2000"))
prob = PyKEP.lambert_exposin(r1, r2, tof * PyKEP.DAY2SEC, PyKEP.MU_SUN, lw, n,
k2)
print prob
'''
To look for discrepancies in propagated state, we find v by propagation as well as the implemented analytical v
'''
import random
import Vector
exps = prob.get_exposins()[0]
# any random progress into the trajectory
rand_psi = random.uniform(0.0, exps.get_psi())
r, v, a = exps.get_state(rand_psi, PyKEP.MU_SUN)
# we take the angular variation of r using given v
dpsi = Vector.mag(Vector.scale(Vector.cross(r, v), 1.0 / Vector.mag(r)**2))