Closed hippke closed 2 years ago
UltraNest
Perhaps useful:
ultranest.stepsampler.RegionSliceSampler(2*nparams) -- crashes, worked earlier
ultranest.stepsampler.RegionSliceSampler(500) -- (8 epochs 2.5d LC) 10^8 evals in 5hrs, VERY GOOD result
ultranest.stepsampler.RegionSliceSampler(50) -- 21min, nearly identical results
ultranest.stepsampler.CubeSliceSampler(2*nparams) -- 10min, slightly wrong
ultranest.stepsampler.CubeSliceSampler(50) -- slightly wrong
ultranest.stepsampler.CubeSliceSampler(500) - same slightly wrong
Not useful:
Speed UltraNest MPI
dynesty Testing with 4 epochs each 2.5 days of LC data
Crashes when printing results
Plotting results OK
DynamicNestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='single') -- 6min, good results (broad, most correct)
DynamicNestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi') -- 12min, results worse (multimodal)
DynamicNestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi', nlive=4000) -- 8min, wrong peak
DynamicNestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi') -- 1hr 38, nah an der wahren Lösung, bestes Ergebnis bislang
DynamicNestedSampler( log_likelihood, prior_transform, ndim=ndim, bound='multi', sample='hslice', slices=10) ==> 10hrs, 2.5e8 evals, 6,950 evals/sec! Result very bad (tight, wrong peaks)
Current raw throughput (prange Pandora segments, 10 epochs, 2.5d, Kepler cadence) is 8000 models /sec
DynamicNestedSampler( log_likelihood, prior_transform, ndim=ndim, bound='none', sample='hslice', slices=10, gradient=gradient) ==> 7h 1.7e8 evals, alles total falsch
NestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='single') -- 3min, broad good results
NestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi') -- 4min, broad good results
NestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi', nlive=1000) -- 6min, broad, worse results
NestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi', nlive=4000) -- 22min, worse
Speed Dynesty:
sample="rslice" -- gets stuck, crashes sample="rstagger" -- sample="hslice" -- gets stuck, crashes
Nestle
Zeus No useful prior transformation concept (?)
UltraNest
sampler.stepsampler = ultranest.stepsampler.RegionSliceSampler(
nsteps=4000,
adaptive_nsteps='move-distance'
)
result = sampler.run(min_num_live_points=4000)
fig_retrieval_v4.pdf
Results: logZ = -1802.250 40h runtime, 414m evals near-perfect lightcurve per_moon: wrong peak
Test dyPolyChord
Nestle has best speed (efficient samples per time) in some online comparisons