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)