LMOptimizerAngular

class ssapy.rvsampler.LMOptimizerAngular(probfn, initGuess, initObsPos, initObsVel, fracstep=[1e-07, 1e-07, 1e-07, 1e-07, 1e-07, 1e-07], absstep=[2.7777777777777775e-06, 2.7777777777777775e-06, 1, 2.7777777777777776e-09, 2.7777777777777776e-09, 0.01], orbitattr=None)

Bases: object

Optimizer that employs Levenberg-Marquardt least-squares fitting. Instead of rv, works in angle/proper motion/range/range rate of initial obs.

Parameters:

• probfn (RVProbability) – The RVProbability object that has both an epoch attribute to use for the orbit fitting model, and a chi method to use for the fit evaluation.

• initGuess (array_like (6,)) – Initial guess. (ra, dec, range, pmra, pmdec, rangerate). (rad, rad, m, rad/s, rad/s, m/s)

• initObsPos (array_like (3,)) – Position of observer at probfn.epoch.

• initObsVel (array_like (3,)) – Position of observer at probfn.epoch.

result

Most recently run result object. Could be useful for inspecting error estimates or success/failure conditions.

Type:

lmfit.MinimizerResult

optimize()

Return the optimized parameters list [r, v]

Methods Summary

optimize([usejac])

Run the optimizer and return the resulting fit parameters.

Methods Documentation

optimize(usejac=True, **fit_kws)

Run the optimizer and return the resulting fit parameters.

Returns:

fit – Least-squares fit as [ra, dec, slant, raRate, decRate, slantRate] in rad, rad, m, rad/s, rad/s, m/s.

Return type:

(6,) array_like