dynesty

library3.0.0pypypi✓ verified 85d ago

A dynamic nested sampling package for computing Bayesian posteriors and evidences. Current version 3.0.0 (released 2024-06-10). Requires Python >=3.8. Active development with major refactoring in v3.0.0 for extensibility and speed.

ai-ml data

pip install dynesty

github ↗package ↗

INSTALL

IMPORT

SIG · DYNESTY

dynesty

ai-mlpythonv3.0.0

harness data pending

Install & Compatibility

Where this runs

No compatibility data collected yet for this library.

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

NestedSampler

✓ from dynesty import NestedSampler

DynamicNestedSampler

✓ from dynesty import DynamicNestedSampler

results

✓ from dynesty import results

utils

✓ from dynesty import utils

pool

✓ from dynesty import pool

Basic nested sampling run with Gaussian likelihood and uniform prior.

import numpy as np from dynesty import NestedSampler, utils # Define a simple prior transform (uniform in [0,1]^2) def prior_transform(u): return 10 * u - 5 # shift to [-5, 5] # Define a simple Gaussian log-likelihood def loglikelihood(x): return -0.5 * np.sum(x**2) # Run nested sampling sampler = NestedSampler(loglikelihood, prior_transform, ndim=2) sampler.run_nested(dlogz=0.5) results = sampler.results # Compute evidence and posterior samples log_z = results.logz[-1] weights = np.exp(results.logwt - results.logz[-1]) samples = utils.resample_equal(results.samples, weights) print(f"log Z = {log_z:.2f}")

Debug

Known issues

breakingv3.0.0 refactored the sampler API: custom samplers now need to be provided as class instances (e.g., NestedSampler(sample=RWalkSampler(walks=44))). The previous string-based specification (sample='rwalk') is deprecated.

fix

Use sampler classes: from dynesty.sampling import RWalkSampler; NestedSampler(..., sample=RWalkSampler(walks=44))

affects: >=3.0.0

deprecatedThe 'npdim' option has been removed since v2.1.4. Prior transforms must return vectors of same dimension as input.

fix

Remove npdim parameter; ensure prior_transform returns array of length ndim.

affects: >=2.1.4

gotchaResuming a run from a checkpoint created with dynesty <2.1.3 is not possible after v2.1.4. The checkpoint format changed.

fix

If you need to resume, finish the run with an older version or restart from scratch.

affects: >=2.1.4

gotchaWhen using blob=True, live_points must be a tuple of 4 elements (u, v, logl, blobs). Omitting blobs will cause an error.

fix

Provide all four entries when specifying live_points with blobs.

affects: >=2.0.0

Errors

Common errors & fixes

AttributeError: module 'dynesty' has no attribute 'NestedSampler'

Import path incorrect or old dynesty version (<1.0).

fix

Use correct import: from dynesty import NestedSampler

ValueError: The prior transform must return an array of shape (ndim,) or (npoints, ndim)

Prior transform returns wrong shape (e.g., scalar or higher dimension).

fix

Ensure prior_transform returns a 1D array of length ndim.

TypeError: run_nested() missing 1 required positional argument: 'dlogz'

In dynesty v2+, dlogz must be passed as keyword argument (not positional).

fix

Use sampler.run_nested(dlogz=0.5) or other kwargs.

dynesty.pool.Pool is deprecated

The dynesty.pool module was removed in v3.0.0.

fix

Use multiprocessing.Pool directly: pool = multiprocessing.Pool(); sampler = NestedSampler(..., pool=pool)

Upgrade

Version history

3.0.0latest on PyPI · released Oct 4, 2025

Audit

Dependencies

numpyrequiredCore dependency for numerical arrays and random sampling

scipyoptionalOptional: used for some bounding methods (e.g., ellipsoid)

Agent activity

14 hits · last 30 days

node

Amazon

OpenAI (training)

Resources

githubhttps://github.com/joshspeagle/dynesty ↗

packagehttps://pypi.org/project/dynesty/ ↗