(12104) Chesley orbit determination test

import grss
prop = grss.prop
fit = grss.fit

import numpy as np
np.set_printoptions(precision=40, linewidth=np.inf)

body_id = '12104'
init_sol, init_cov, nongrav_info = fit.get_sbdb_info(body_id)
de_kernel = 440

add_gaia_obs = True
optical_obs_file = None
t_min_tdb = None
t_max_tdb = None
debias_lowres = True
deweight = True
eliminate = False
num_obs_per_night = 4
verbose = True
obs_df = fit.get_optical_obs(body_id, optical_obs_file, t_min_tdb, t_max_tdb, debias_lowres, deweight, eliminate, num_obs_per_night, verbose)
obs_df = fit.add_radar_obs(obs_df, t_min_tdb, t_max_tdb, verbose)
if add_gaia_obs:
    gaia_dr = 'gaiafpr'
    obs_df = fit.add_gaia_obs(obs_df, t_min_tdb, t_max_tdb, gaia_dr, verbose)

Read in 5586 observations from the MPC.
        WARNING: At least one unknown observation mode in the data.
        WARNING: At least one deprecated star catalog in the data.
        Filtered to 5586 observations that satisfy the time range and accepted observatory constraints.
Applying Eggl et al. (2020) debiasing scheme to the observations.
        Unknown star catalog: UNK
        No debiasing needed for 4275 observations.
        Debiased 1289 observations.
        No bias information for 22 observations.
Applying Vereš et al. (2017) weighting scheme to the observations.
        Using 3412 CCD observations with station-specific weight rules.
Applying sqrt(N/4) deweighting scheme.
        Deweighted 2666 observations.
Read in 459 Gaia observations from gaiafpr
        Filtered to 459 observations that satisfy the time range constraints.

n_iter_max = 10
fit_sim = fit.FitSimulation(init_sol, obs_df, init_cov, n_iter_max=n_iter_max, de_kernel=de_kernel, nongrav_info=nongrav_info)

fit_sim.filter_lsq()

Iteration               Unweighted RMS          Weighted RMS            Chi-squared             Reduced Chi-squared
1                        0.743                   0.481                   2796.509                        0.231
2                        0.743                   0.481                   2796.493                        0.231
Converged without rejecting outliers. Starting outlier rejection now...
3                        0.710                   0.444                   2380.245                        0.198
Converged after rejecting outliers. Rejected 28 out of 6045 optical observations.

fit_sim.print_summary()

Summary of the orbit fit calculations after postfit pass:
==============================================================
RMS unweighted: 0.7100073609712477
RMS weighted: 0.4437084445063534
chi-squared: 2380.2451512503344
reduced chi-squared: 0.1978920145701974
square root of reduced chi-squared: 0.44485055307394794
--------------------------------------------------------------
Solution Time: MJD 58109.000 TDB = 2017-12-22 00:00:00.000 TDB
Solution Observation Arc: 17721.12 days (48.52 years)
--------------------------------------------------------------
Fitted Variable         Initial Value                   Uncertainty                     Fitted Value                    Uncertainty                     Change                          Change (sigma)
e                       2.44816486409e-02               7.34900205607e-10               2.44816485814e-02               7.08199972529e-10               -5.95493029887e-11              -0.084
q                       2.93647839282e+00               3.41979009324e-09               2.93647839313e+00               3.30350765028e-09               +3.09278380684e-10              +0.094
tp                      5.87280922146e+04               6.74725614320e-06               5.87280922144e+04               6.52056400355e-06               -1.99121132027e-07              -0.031
om                      7.80639799441e+01               1.25578195231e-07               7.80639799398e+01               1.18110127018e-07               -4.26469171089e-09              -0.036
w                       1.83028382329e+02               1.33596794753e-06               1.83028382285e+02               1.29283963673e-06               -4.46623857897e-08              -0.035
i                       1.11526213075e+01               2.98302297593e-08               1.11526213090e+01               2.84552962656e-08               +1.55920787392e-09              +0.055

fit_sim.plot_summary(auto_close=True)

fit_sim.iters[-1].plot_iteration_summary(title='Postfit Residuals', auto_close=True)

mean_0 = np.array(list(init_sol.values())[1:])
cov_0 = init_cov
mean_f = np.array(list(fit_sim.x_nom.values()))
cov_f = fit_sim.covariance

maha_dist_f, maha_dist_0, bhattacharya, bhatt_coeff = fit.get_similarity_stats(mean_0, cov_0, mean_f, cov_f)
print(f'Mahalonobis distance between JPL and GRSS solution: {maha_dist_f:0.2f}')
print(f'Mahalonobis distance between GRSS and JPL solution: {maha_dist_0:0.2f}')
print(f'Bhattacharya distance between JPL and GRSS solution: {bhattacharya:0.4f}')
print(f'Bhattacharya coefficient between JPL and GRSS solution: {bhatt_coeff:0.4f}')

Mahalonobis distance between JPL and GRSS solution: 0.12
Mahalonobis distance between GRSS and JPL solution: 0.13
Bhattacharya distance between JPL and GRSS solution: 0.0033
Bhattacharya coefficient between JPL and GRSS solution: 0.9967

assert maha_dist_f < 5.0
assert maha_dist_0 < 5.0
assert bhattacharya < 0.10
assert bhatt_coeff > 0.90