Comments (6)
UltraNest
Perhaps useful:
-
ultranest.stepsampler.RegionSliceSampler(2*nparams) -- crashes, worked earlier
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ultranest.stepsampler.RegionSliceSampler(500) -- (8 epochs 2.5d LC) 10^8 evals in 5hrs, VERY GOOD result
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ultranest.stepsampler.RegionSliceSampler(50) -- 21min, nearly identical results
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ultranest.stepsampler.CubeSliceSampler(2*nparams) -- 10min, slightly wrong
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ultranest.stepsampler.CubeSliceSampler(50) -- slightly wrong
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ultranest.stepsampler.CubeSliceSampler(500) - same slightly wrong
Not useful:
- ultranest.stepsampler.RegionBallSliceSampler -- very wrong
- ultranest.stepsampler.BallSliceSampler(nsteps=nsteps) -- slow, wrong
- ultranest.stepsampler.CubeMHSampler(nsteps=nsteps) -- Slow, very wrong
- ultranest.stepsampler.RegionMHSampler(nsteps=nsteps) -- Very fast, very wrong
- ultranest.ReactiveNestedSampler -- very slow (days)
Speed UltraNest MPI
- 1 Thread: 5000/sec
- 4 Threads: 8700/sec
- 8 Threads: 8000/sec
from pandora.
dynesty
Testing with 4 epochs each 2.5 days of LC data
-
Crashes when printing results
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Plotting results OK
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DynamicNestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='single') -- 6min, good results (broad, most correct)
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DynamicNestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi') -- 12min, results worse (multimodal)
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DynamicNestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi', nlive=4000) -- 8min, wrong peak
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DynamicNestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi') -- 1hr 38, nah an der wahren Lösung, bestes Ergebnis bislang
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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
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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
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NestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi') -- 4min, broad good results
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NestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi', nlive=1000) -- 6min, broad, worse results
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NestedSampler(log_likelihood, prior_transform, ndim=ndim, bound='multi', nlive=4000) -- 22min, worse
Speed Dynesty:
- 1 Thread: 5000/sec
- 8 Threads: 17,000/sec (after burn-in)
sample="rslice" -- gets stuck, crashes
sample="rstagger" --
sample="hslice" -- gets stuck, crashes
from pandora.
Nestle
- cancelled after 18 hrs
from pandora.
Zeus
No useful prior transformation concept (?)
from pandora.
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
from pandora.
Test dyPolyChord
from pandora.
Related Issues (20)
- Better pre-check for out of transit data HOT 1
- Make pure C version of eclipse to compare speed HOT 1
- Cornerplot: Customize and Beautify
- Introduce physical boundaries HOT 4
- Planetary mass prior in log?
- Make GPU test version with long array to examine best-case performance
- Faster Kepler equation solver for e_S>0
- Test ellipse_pos_iter_bary with .astype(np.float32) HOT 2
- Add parameter "concentric circles" for video
- change params.b_bary and others to bary
- test float32 performance HOT 1
- ecc_bary
- Nested Folding to visualize
- Analytical calculation of planet-moon occultation when >=1 body touching stellar limb
- Convergence speed mass_ratio versus separate moon mass
- Create example for injection-retrieval workflow with UltraNest
- Crash while using default example.py HOT 2
- Example: Planet-moon injection and retrieval - wrong LD conversion
- Speed issue: Lightkurve / add warning if user provides data format other than array of floats HOT 1
- Question about returned timesteps/cadence HOT 1
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from pandora.