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)¶