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NumCosmo

NumCosmo is a numerical cosmology library. It contains a comprehensive set of tools for calculating cosmology observables and to analyze statistical models.

Build Status

Description

The library is written in C, but since it uses the GObject framework, it is developed in a object oriented fashion. Additionally, it has automatic bindings for every language which supports GObject introspection (Perl, Python, etc. For a complete list see https://wiki.gnome.org/Projects/GObjectIntrospection/Users ).

The available observables objects are:

  • Type Ia Supernovae
  • Baryon Acoustic Oscillations
  • Cosmic Microwave Background
  • Cluster number counts
  • Cluster pseudo number counts
  • Hubble data H(z)

Currently it has the following statistical tools:

  • Monte Carlo (NcmFitMC) -- resampling and fitting.
  • Monte Carlo Bootstrap (NcmFitMCBS) -- resampling/bootstraping and fitting.
  • Markov Chain Monte Carlo -- MCMC with the Metropolis-Hastings sampler, it supports general samplers through transtion kernel object NcmMSetTransKern.
  • Ensemble Sampler MCMC -- Ensemble Markov Chain Monte Carlo consists in every point of the MCMC chain being a emsemble of points in the parameter space. It implements an affine invariant move method (stretch move).

All methods above generate a catalog using the NcmMSetCatalog which provide a unified way to analyze the results. Besides, the use of a catalog provides the support for restarting the algorithms from a previous crash or to extend the precision.

Links:

The Savannah project page can be found here. The NumCosmo homepage is here, it contains the documentation and some examples.

Building from repository:

To build from a release package, for which the configure script is ready, run:

  • ./configure (--help to see options)
  • make
  • make install (optional step)

To build from the git repository, run:

For a generic installation instructions, see INSTALL.

The requirements below can be found on most Linux distribution, see here for a list of packages names for some distributions.

A pre-compiled version of NumCosmo can be found here

Requirements:

Optional packages: