ssapy.correlate_tracks

Provides classes and functions for orbital tracking, hypothesis testing, angle wrapping, and fitting satellite observations to orbital models.

Functions

combinatoric_lnprior(nsat, ntrack, ndet)	Prior probability of assigning detections to tracks of satellites.
data_for_satellite(data, satIDList)	Extract data for specific satID.
fit_arc(arc, guess[, verbose, propagator, ...])	Fit an orbit to an arc.
fit_arc_blind(arc[, verbose, mode, priors, ...])	Fit an orbit to an arc.
fit_arc_blind_via_track(arc[, propagator, ...])	Fit a series of detections using the Track interface.
fit_arc_with_gaussian_prior(arc, mu, cinvcholfac)	Fit an orbit to an arc.
iterate_mht(data, oldmht[, nminlength, trimends])	Iterates and refines the Multiple Hypothesis Tracking (MHT) process by updating tracks and generating new hypotheses.
make_optimizer(mode, param[, lsq])	Creates and returns an optimizer object or function for orbital parameter estimation based on the specified mode and configuration.
make_param_guess(rvguess, arc[, mode, orbitattr])	Generates an initial parameter guess for orbital estimation based on the provided mode, observation arc, and optional orbital attributes.
norm(arr)	Compute the Euclidean norm of an array over the last axis while preserving leading axes.
normSq(arr)	Compute the squared norm of an array over the last axis while preserving leading axes.
normed(arr)	Normalize an array along the last axis to have unit length.
orbit_to_param(orbit[, mode, orbitattr, ...])	Convert Orbits to parameters.
param_to_orbit(param[, mode, orbitattr])	Convert parameters to Orbits.
radeczn(orbit, arc, **kw)	Computes right ascension, declination, range, proper motions, range rate, and mean anomaly wrap for a given orbit and observation arc.
summarize_tracklet(arc)	Compute mean ra/dec, uncertainty in mean, proper motion, uncertainty for a short arc.
summarize_tracklets(data[, posuncfloor, ...])	Add fields to default data set to accommodate MHT fitting.
time_ordered_satIDs(data[, with_time, order])	Give satIDs in data in order of observation.
wrap_angle_difference(dl, wrap[, center])	Wraps an angle difference to a specified range.

Classes

CircVelocityPrior([sigma])	Gaussian prior that log(GM/r/v^2) = 0.
GaussPrior(mu, cinvcholfac, translator)	Gaussian prior on parameters.
Hypothesis(tracks[, nsat])	Assignment of detections to multiple tracks.
MHT(data[, nsat, truth, hypotheses, ...])	Multiple Hypothesis Tracking of many hypotheses explaining data.
Time(val[, val2, format, scale, precision, ...])	Represent and manipulate times and dates for astronomy.
Track(satIDs, data[, guess, initial_lnprob, ...])	Set of observations to be fit as an object moving through space.
TrackBase(satIDs, data[, volume, mode, ...])	Set of observations fit together as an orbital track.
TrackGauss(satIDs, data, param, covar, chi2)	Set of observations to be fit as an object moving through space.
VolumeDistancePrior([scale])	Prior on range like r^2*exp(-r/scale), preferring larger distances where there is more volume.
ZeroRadialVelocityPrior([sigma])	Gaussian prior that v_R = 0.
lazy_property(fget)	meant to be used for lazy evaluation of an object attribute.
partial	partial(func, *args, **keywords) - new function with partial application of the given arguments and keywords.

Class Inheritance Diagram