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About camb-feedstock

Feedstock license: BSD-3-Clause

Home: https://camb.info/

Package license: LicenseRef-modified-LGPL

Summary: Code for Anisotropies in the Microwave Background

Development: https://github.com/cmbant/CAMB

Documentation: https://camb.info/readme.html

Code for Anisotropies in the Microwave Background by Antony Lewis and Anthony Challinor

Features:

  • Support for closed, open and flat models
  • Scalar, vector and tensor modes including polarization
  • Output Cl, matter transfer functions, matter power spectrum and σ8
  • Fast computation to ~0.3-0.1% accuracy, with controllable accuracy level
  • Relatively structured and easily extendable Fortran 90 code
  • Efficient support for massive neutrinos
  • Absolute computations from correctly normalized initial power spectra
  • Computation of lensed CMB power spectra and lensing potential power spectrum
  • Internally parallelized for fast execution on multi-processor machines
  • Use CAMB with CosmoMC for Monte-Carlo parameter estimation
  • Constant equation of state quintessence (or variable PPF)
  • Support for general correlated adiabatic/isocurvature initial conditions
  • Accurate full-sky calculation of lensed power spectra (astro-ph/0502425)
  • Integrated interface to HALOFIT for non-linear fitting
  • support for arbitrary neutrino mass splittings
  • For 21cm, lensing and number count power spectra see this extension
  • For perturbed recombination and effect on small-scale baryons see this extension
  • Calculation of local primordial and CMB lensing bispectra
  • Easy-to-use Python wrapper

Current build status

Azure
VariantStatus
linux_64_python3.10.____cpython variant
linux_64_python3.11.____cpython variant
linux_64_python3.12.____cpython variant
linux_64_python3.13.____cp313 variant
linux_64_python3.9.____cpython variant
osx_64_python3.10.____cpython variant
osx_64_python3.11.____cpython variant
osx_64_python3.12.____cpython variant
osx_64_python3.13.____cp313 variant
osx_64_python3.9.____cpython variant
osx_arm64_python3.10.____cpython variant
osx_arm64_python3.11.____cpython variant
osx_arm64_python3.12.____cpython variant
osx_arm64_python3.13.____cp313 variant
osx_arm64_python3.9.____cpython variant
win_64_python3.10.____cpython variant
win_64_python3.11.____cpython variant
win_64_python3.12.____cpython variant
win_64_python3.13.____cp313 variant
win_64_python3.9.____cpython variant

Current release info

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

Installing camb

Installing camb 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, camb can be installed with conda:

conda install camb

or with mamba:

mamba install camb

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

conda search camb --channel conda-forge

or with mamba:

mamba search camb --channel conda-forge

Alternatively, mamba repoquery may provide more information:

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

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

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

About conda-forge

Powered by NumFOCUS

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 camb-feedstock

If you would like to improve the camb 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/camb-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