icecube.segmented_spline_reco.SVN module¶
- class icecube.segmented_spline_reco.SVN.SVN(name='SVN', num_particles=30, kernel_type='mean', max_iter=50, start_sigma=0.1, stepsize=1.0, decr_rand_scale=0.2, perm_rand_scale=0.01)¶
Bases:
I3MinimizerImplementation of SVN ``
- Parameters:
name (string, optional) – String for the Gulliver module to identify the minimizer
tolerance (float, optional) – Tolerance for finding the minimum
- CheckLimits(positions)¶
- GetMedianPWDist(points)¶
- GetName()¶
- Minimize((I3Minimizer)arg1, (I3GulliverBase)arg2, (I3FitParameterInitSpecsSeries)arg3) I3MinimizerResult :¶
- C++ signature :
I3MinimizerResult Minimize(I3MinimizerBase {lvalue},I3GulliverBase {lvalue},std::__1::vector<I3FitParameterInitSpecs, std::__1::allocator<I3FitParameterInitSpecs>>)
Minimize( (I3Minimizer)arg1, (I3GulliverBase)arg2, (I3FitParameterInitSpecsSeries)arg3) -> None :
- C++ signature :
void Minimize(I3MinimizerWrapper {lvalue},I3GulliverBase {lvalue},std::__1::vector<I3FitParameterInitSpecs, std::__1::allocator<I3FitParameterInitSpecs>>)
- UsesGradient((I3Minimizer)arg1) bool :¶
- C++ signature :
bool UsesGradient(I3MinimizerBase {lvalue})
- UsesHessian((I3Minimizer)arg1) bool :¶
- C++ signature :
bool UsesHessian(I3MinimizerBase {lvalue})
- get_kernel_n_grad(particle_id, all_particle_positions, kernel_mat)¶
- isPD(B)¶
Returns true when input is positive-definite, via Cholesky
- nearestPD(A)¶
Find the nearest positive-definite matrix to input
A Python/Numpy port of John D’Errico’s nearestSPD MATLAB code [1], which credits [2].
[1] https://www.mathworks.com/matlabcentral/fileexchange/42885-nearestspd
[2] N.J. Higham, “Computing a nearest symmetric positive semidefinite matrix” (1988): https://doi.org/10.1016/0024-3795(88)90223-6
