def states_to_lightcurve(obs_vecs, sun_vecs, attitudes, spacecraft_geometry,
Exposure_Time):
'''
@param times list of dates at which each observation was taken
@param obs_vecs array of vectors from the observer to the spacecraft
@param sun_vecs array of vectors from the sun to the spacecraft
@param attitudes array of modified rodriguez parameters describing the spacecraft attitude
@param spacecraft_geometry a Spacecraft Geometry object describing the spacecraft geometry
'''
lightcurve = []
iters = len(obs_vecs)
count = 0
for obs_vec, sun_vec, attitude in zip(obs_vecs, sun_vecs, attitudes):
dcm_body2eci = CF.mrp2dcm(attitude)
sun_vec_body = dcm_body2eci.T @ sun_vec
obs_vec_body = dcm_body2eci.T @ obs_vec
power = spacecraft_geometry.calc_reflected_power(
obs_vec_body, sun_vec_body, Exposure_Time)
lightcurve.append(power)
count += 1
loading_bar(count / iters, 'Simulating Lightcurve')
lightcurve = hstack(lightcurve)
return lightcurve
def mrp_measurement_function(state, obsvec, sunvec, exposure_time, Geometry):
mrps = state[0:3]
dcm_body2eci = CF.mrp2dcm(mrps)
obs_vec_body = dcm_body2eci.T @ obsvec
sun_vec_body = dcm_body2eci.T @ sunvec
return array([
Geometry.calc_reflected_power(obs_vec_body, sun_vec_body,
exposure_time)
])
obs_vecs = load(truth_dir + '/obsvec.npy')[::50]
sun_vecs = load(truth_dir + '/sunvec.npy')[::50]
attitudes = load(truth_dir + '/mrps' + result_num + '.npy')[::50]
Exposure_Time = Simulation_Configuration['Exposure Time']
num_frames = len(obs_vecs)
START_INDEX = -5000
frames = []
count = 0
max_val = 0
for mrps, obs_vec, sun_vec in zip(attitudes[START_INDEX:],
obs_vecs[START_INDEX:],
sun_vecs[START_INDEX:]):
dcm_eci2body = CF.mrp2dcm(mrps).T
#dcm_eci2body = CF.mrp2dcm(mrps).T
image = RF.generate_image(Geometry,
dcm_eci2body @ obs_vec,
dcm_eci2body @ sun_vec,
Exposure_Time,
win_dim=(6, 6),
dpm=20)
im_max = amax(image)
if im_max > max_val:
max_val = im_max
frames.append(image)
count += 1
loading_bar(count / num_frames, 'Rendering gif')
frames = [frame / max_val for frame in frames]
true_lightcurve = load(os.path.join(passfile, 'lightcurve'+run_number+'.npy'))
true_mrps = load(os.path.join(passfile, 'mrps'+run_number+'.npy'))
true_rates = load(os.path.join(passfile, 'angular_rate'+run_number+'.npy'))
obs_vecs = load(os.path.join(passfile, 'obsvec.npy'))
sun_vecs = load(os.path.join(passfile, 'sunvec.npy'))
est_lightcurve = load(os.path.join(result_dir, 'results'+run_number+'_estimated_curve.npy'))
means = load(os.path.join(result_dir, 'results'+run_number+'_raw_means.npy'))
covariances = load(os.path.join(result_dir, 'results'+run_number+'_raw_covariance.npy'))
residuals = load(os.path.join(result_dir, 'results'+run_number+'_raw_residuals.npy'))
stp = int(floor(1/DT))
eci_rate_true = vstack(list([CF.mrp2dcm(m)@rate for m, rate in zip(true_mrps, true_rates)]))
eci_rate_ests = []
for est, tru in zip(means, eci_rate_true):
eci_rate_est = CF.mrp2dcm(est[0:3])@est[3:6]
a = norm(eci_rate_est - tru)
b = norm(-eci_rate_est - tru)
if b < a:
eci_rate_ests.append(-eci_rate_est)
else:
eci_rate_ests.append(eci_rate_est)
eci_rate_ests = vstack(eci_rate_ests)
obs_frame_true_rate = []
obs_frame_est_rate = []
for obs, sun, truth, est in zip(obs_vecs, sun_vecs, eci_rate_true, eci_rate_ests):
est_lightcurve = load(
os.path.join(result_dir,
'results' + run_number + '_estimated_curve.npy'))
means = load(
os.path.join(result_dir,
'results' + run_number + '_raw_means.npy'))
covariances = load(
os.path.join(result_dir,
'results' + run_number + '_raw_covariance.npy'))
residuals = load(
os.path.join(result_dir,
'results' + run_number + '_raw_residuals.npy'))
eci_rate_ests = []
for est in means:
eci_rate_est = CF.mrp2dcm(est[0:3]) @ est[3:6]
eci_rate_ests.append(eci_rate_est)
eci_rate_ests = vstack(eci_rate_ests)
obs_frame_est_rate = []
for obs, sun, est in zip(obs_vecs, sun_vecs, eci_rate_ests):
x = obs / norm(obs)
z = cross(sun, obs) / norm(cross(sun, obs))
y = cross(z, x)
eci2obs = vstack([x, y, z])
obs_frame_est_rate.append(eci2obs @ est)
obs_frame_est_rate = vstack(obs_frame_est_rate)
'results' + run_number + '_estimated_curve.npy'))
means = load(
os.path.join(result_dir,
'results' + run_number + '_raw_means.npy'))
covariances = load(
os.path.join(result_dir,
'results' + run_number + '_raw_covariance.npy'))
residuals = load(
os.path.join(result_dir,
'results' + run_number + '_raw_residuals.npy'))
stp = int(floor(1 / DT))
eci_rate_true = vstack(
list([
CF.mrp2dcm(true_mrps[0]) @ true_rates[0]
for m, rate in zip(true_mrps, true_rates)
]))
eci_rate_ests = []
for est, tru in zip(means, eci_rate_true):
eci_rate_est = CF.mrp2dcm(est[0:3]) @ est[3:6]
a = norm(eci_rate_est - tru)
b = norm(-eci_rate_est - tru)
if b < a:
eci_rate_ests.append(-eci_rate_est)
else:
eci_rate_ests.append(eci_rate_est)
eci_rate_ests = vstack(eci_rate_ests)
obs_frame_true_rate = []
obs_frame_est_rate = []