Comments (1)
Looks like you are probably hitting limitations of floating points. Between +0.1999999999 and +0.2000000001, there aren't a lot of values, so the proposal procedure may have difficulty finding new, unique points with higher likelihood. You could try reparametrizing the problem. Is it possible that the likelihood is a bit unrealistic (too informative)?
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Related Issues (20)
- store dimensionality in points file HOT 1
- refine slow warning
- Ultranest 3.6.1 does not install in new .venv environment HOT 14
- Difficulty installing Ultranest versions prior to 3.6.2 HOT 4
- Feature request/bug: returning float32 from log-likelihood fn with PopulationSliceSampler HOT 7
- MPI fails with likelihoods that have plateaus HOT 4
- Access chains / intermediary results for run in progess? HOT 1
- `saved_logwt_bs` error after completion HOT 1
- How to Resume Execution with Only the results/points.hdf5 File? HOT 1
- Vectorised sampling and memory consumption HOT 4
- [Question] Constant efficiency mode HOT 2
- tregion argument is not supported by dychmc dychmc __next__ function HOT 5
- Reproducibility of UltraNest fits HOT 2
- Missing documentation for results dictionary HOT 4
- Conda installer does not work for Apple OSX-arm64
- Ultranest version 4 HOT 4
- Add ESS calculation to static version results HOT 2
- ARM bug: overflow from excessive live points HOT 8
- 4.1.6 performs worse HOT 18
- num_live_points_missing error when running ultranest in parallel via mpiexec HOT 8
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