icecube.segmented_spline_reco.SegSplineReco_emcee module

class icecube.segmented_spline_reco.SegSplineReco_emcee.MapSpecs(parspecs, nsteps, stepsize)

Bases: object

class icecube.segmented_spline_reco.SegSplineReco_emcee.SegSplineRecoEMCEE(ctx)

Bases: I3ConditionalModule

Likelihood space visualization

This module displays (or save PNGs for) the two-dimensional slices of the likelihood space around the seed.

Configure((I3ConditionalModule)arg1) None :
C++ signature :

void Configure(PythonModule<I3ConditionalModule> {lvalue})

property Filename

Output filename base for plots; if None, run interactively.

property LogLikelihood

LogLikelihood service to use

property NIterations

Number of iterations for emcee

property NSteps

Number of steps to take along each dimension

property NWalkers

Number of walkers for emcee

property Parametrization

Parametrization service to use

Physics((I3ConditionalModule)arg1, (I3Frame)arg2) None :
C++ signature :

void Physics(PythonModule<I3ConditionalModule> {lvalue},boost::shared_ptr<I3Frame>)

property SeedService

Seed service to use

property StepSize

Size of each step in unit of the parametrization’s step size

property WithGradients

Plot LogLikelihood gradients along with function values.

emcee_ensamble(specs, nwalkers=24, niter=1000, start_covar=None)
is_posdef(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

plot_pb_contour(frame, pos, specs)