/ultranest-feedstock

A conda-smithy repository for ultranest.

Primary LanguageShellBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

About ultranest-feedstock

Feedstock license: BSD-3-Clause

Home: https://johannesbuchner.github.io/UltraNest/

Package license: AGPL-3.0-or-later

Summary: Fit and compare complex models reliably and rapidly. Advanced Nested Sampling.

Development: https://github.com/JohannesBuchner/UltraNest

Documentation: https://johannesbuchner.github.io/UltraNest/

When scientific models are compared to data, two tasks are important: 1) contraining the model parameters and 2) comparing the model to other models. Different techniques have been developed to explore model parameter spaces. This package implements a Monte Carlo technique called nested sampling. Nested sampling allows Bayesian inference on arbitrary user-defined likelihoods. In particular, posterior probability distributions on model parameters are constructed, and the marginal likelihood (“evidence”) Z is computed. The former can be used to describe the parameter constraints of the data, the latter can be used for model comparison (via Bayes factors) as a measure of the prediction parsimony of a model. In the last decade, multiple variants of nested sampling have been developed. These differ in how nested sampling finds better and better fits while respecting the priors (constrained likelihood prior sampling techniques), and whether it is allowed to go back to worse fits and explore the parameter space more. This package develops novel, advanced techniques for both (See https://johannesbuchner.github.io/UltraNest/method.html). They are especially remarkable for being free of tuning parameters and theoretically justified. Beyond that, UltraNest has support for Big Data sets and high-performance computing applications. UltraNest is intended for fitting complex physical models with slow likelihood evaluations, with one to hundreds of parameters. UltraNest intends to replace heuristic methods like multi-ellipsoid nested sampling and dynamic nested sampling with more rigorous methods. UltraNest also attempts to provide feature parity compared to other packages (such as MultiNest).

Current build status

Azure
VariantStatus
linux_64_numpy1.22python3.10.____cpython variant
linux_64_numpy1.22python3.8.____cpython variant
linux_64_numpy1.22python3.9.____cpython variant
linux_64_numpy1.23python3.11.____cpython variant
linux_64_numpy1.26python3.12.____cpython variant
osx_64_numpy1.22python3.10.____cpython variant
osx_64_numpy1.22python3.8.____cpython variant
osx_64_numpy1.22python3.9.____cpython variant
osx_64_numpy1.23python3.11.____cpython variant
osx_64_numpy1.26python3.12.____cpython variant
win_64_numpy1.22python3.10.____cpython variant
win_64_numpy1.22python3.8.____cpython variant
win_64_numpy1.22python3.9.____cpython variant
win_64_numpy1.23python3.11.____cpython variant
win_64_numpy1.26python3.12.____cpython variant

Current release info

Name Downloads Version Platforms
Conda Recipe Conda Downloads Conda Version Conda Platforms

Installing ultranest

Installing ultranest from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, ultranest can be installed with conda:

conda install ultranest

or with mamba:

mamba install ultranest

It is possible to list all of the versions of ultranest available on your platform with conda:

conda search ultranest --channel conda-forge

or with mamba:

mamba search ultranest --channel conda-forge

Alternatively, mamba repoquery may provide more information:

# Search all versions available on your platform:
mamba repoquery search ultranest --channel conda-forge

# List packages depending on `ultranest`:
mamba repoquery whoneeds ultranest --channel conda-forge

# List dependencies of `ultranest`:
mamba repoquery depends ultranest --channel conda-forge

About conda-forge

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conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.

A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge anaconda.org channel for Linux, Windows and OSX respectively.

To manage the continuous integration and simplify feedstock maintenance conda-smithy has been developed. Using the conda-forge.yml within this repository, it is possible to re-render all of this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.

For more information please check the conda-forge documentation.

Terminology

feedstock - the conda recipe (raw material), supporting scripts and CI configuration.

conda-smithy - the tool which helps orchestrate the feedstock. Its primary use is in the construction of the CI .yml files and simplify the management of many feedstocks.

conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)

Updating ultranest-feedstock

If you would like to improve the ultranest recipe or build a new package version, please fork this repository and submit a PR. Upon submission, your changes will be run on the appropriate platforms to give the reviewer an opportunity to confirm that the changes result in a successful build. Once merged, the recipe will be re-built and uploaded automatically to the conda-forge channel, whereupon the built conda packages will be available for everybody to install and use from the conda-forge channel. Note that all branches in the conda-forge/ultranest-feedstock are immediately built and any created packages are uploaded, so PRs should be based on branches in forks and branches in the main repository should only be used to build distinct package versions.

In order to produce a uniquely identifiable distribution:

  • If the version of a package is not being increased, please add or increase the build/number.
  • If the version of a package is being increased, please remember to return the build/number back to 0.

Feedstock Maintainers