def __init__(self, fpath, palantir=True):
"""
Constructor of the statistics object. Used to reconstruct trajectory with all its data.
@param fpath relative filepath to the saved trajectory
"""
if palantir: # trajectory format from palantir-search
with open( fpath, 'rb') as f:
prob, x, ms = cPickle.load(f)
else:
# get trajectory
try:
best, x = load_trajectory( fpath )
except:
raise Exception('ERROR: could not load trajectory')
# reconstruct a problem instance
try:
prob = mga_incipit( seq=[fb.moon for fb in best.traj]+[best.next_moon.moon], tof = [ [0,300] ]*(len(x)/4) )
except:
raise Exception('ERROR: could not instantiate problem')
params = lambertization(prob, x)
self.seq, self.common_mu, self.n_legs, self.initial, self.T, self.t_P, self.r_P, self.v_P, self.DV, self.close_d = lambertization(prob, x)
if palantir:
self.best = None
else:
self.best = best
self.x = x
self.prob = prob
def trajectory_file_load(fpath, verbose=False):
""" used to load a trajectory file dump from tree search module """
# get trajectory
try:
best, x = load_trajectory( fpath )
except:
raise Exception('ERROR: could not load trajectory')
# reconstruct a problem instance
try:
prob = mga_incipit( seq=[fb.moon for fb in best.traj]+[best.next_moon.moon], tof = [ [0,300] ]*(len(x)/4) )
except:
raise Exception('ERROR: could not instantiate problem')
pop = population(prob)
pop.push_back(x)
return incipit_stats(pop.champion, fpath.split('/')[-1], 0, *lambertization(prob, x))
