icecube.segmented_spline_reco.nd_paraboloid module¶
- class icecube.segmented_spline_reco.nd_paraboloid.nd_paraboloid(ctx)¶
Bases:
I3ConditionalModule
Code to fit “n-d” paraboloids given a bunch of sample points. The standard application is 6-d (x,y,z,dir1,dir2,t) input given by samples, but it can really work in any dimension .. although it is not optimized to work in higher than 10-d or so. Standard applicataion is within SegmentedSplineReco, where the 6-d fit is performed on the samples, the hesse matrix is converted into a covariance matrix, and one obtains the covariance in the desired dimensions (marginalization) just by picking out the dimensions of interest. It is independent of the precise reconstruction, parametrization, or gulliver.
- Configure((I3ConditionalModule)arg1) None : ¶
- C++ signature :
void Configure(PythonModule<I3ConditionalModule> {lvalue})
- Physics((I3ConditionalModule)arg1, (I3Frame)arg2) None : ¶
- C++ signature :
void Physics(PythonModule<I3ConditionalModule> {lvalue},boost::shared_ptr<I3Frame>)
- find_best(res_vector)¶
- find_best_logs()¶
- form_cov_m1(params)¶
- form_triang(params)¶
- get_minim_fn(least_squares=True)¶
- minimize(algo='least_squares', maxcalls=10000, loss='linear', lq_method='lm', gradient=True, printMode=0, n_trials=1, restart_each_time=True, random_state=None)¶