This page refers to an older version of CosmoSIS. The new repository is now at https://github.com/joezuntz/cosmosis with documentation at https://cosmosis.readthedocs.io/en/latest/

Welcome

Welcome to CosmoSIS.

CosmoSIS is a cosmological parameter estimation code. It is now at version 1.6

It is a framework for structuring cosmological parameter estimation in a way that eases re-usability, debugging, verifiability, and code sharing in the form of calculation modules.

It consolidates and connects together existing code for predicting cosmic observables, and makes mapping out experimental likelihoods with a range of different techniques much more accessible

CosmoSIS is described in Zuntz et al.: http://arxiv.org/abs/1409.3409 If you make use of it in your research, please cite that paper and include the URL of this repository in your acknowledgments. Thanks!

Webinars

Webinar 1 recording and slides

Webinar 2 recording and slides

Mailing Lists

Sign up for the CosmoSIS announcements email list (for announcements by core team) by emailing listserv@fnal.gov with the subject line and message text: subscribe cosmosis_messages.

Sign up for the CosmoSIS users email list (for discussion among users) by emailing listserv@fnal.gov with the subject line and message text: subscribe cosmosis_users.

Install CosmoSIS

CosmoSIS needs a 64-bit operating system.

• Recommended: Automatic Installation on Scientific Linux / CentOS 6 and 7, and Ubuntu 14.04, 16.04 or 18.04 LTS
• Install on a Mac
• Install on Ubunbtu
• Install on Linux
• Automatic Installation on any OS using Docker (requires root)
• CosmoSIS at NERSC

Try some short demos

These demos illustrate basic CosmoSIS concepts in action.

• Demo 1: Get standard cosmological functions for a given cosmology

• Demo 2: Get the Planck and BICEP likelihood for a given cosmology

• Demo 3: Get a slice through the BICEP likelihood in r_T

• Demo 4: Find the best fit cosmological parameters for a Planck likelihood

• Demo 5: Running an MCMC analysis of supernova data

• Demo 6: Get the CFHTLenS likelihood for a given cosmology

• Demo 7: Get a 2D likelihood grid from BOSS DR9 measurements of f*sigma_8

• Demo 8: Compare CAMB with Eisenstein & Hu; get growth factors; tweak plots

• Demo 9: Get Bayesian evidence with Multinest; make scatter and custom plots

• Demo 10: Compare constraints with two different halofit models for nonlinear power, sampling sigma_8 instead of A_s

• Demo 11: Slice through constraints on modified gravity with isItGR and CFHTLenS; save full data for all grid points to file

• Demo 12: Get the PDF for extreme cluster masses using the Tinker mass function

• Demo 13: A fast grid sampling of the JLA supernovae using the Snake sampler

• Demo 14: The Kombine sampler applied to cluster gas fraction measurements; advanced postprocessing options

• Demo 15: More Galaxy Two-Point Correlation Functions

• Demo 16: Robust maximum-posteriors with the Minuit sampler

• Demo 17: A Fisher Matrix for the Dark Energy Survey SV cosmic shear

• Demo 18: Chain two samplers one after another

• Demo 19: A time delay SN example

• Demo 20: Using the Importance sampler to split Demo5 into two parts

• Demo 21: Sampling the prior only with the apriori sampler

• Demo 22: Generating likelihood slices with the star sampler

Longer demos

These longer examples show realistic parameter constraint pipelines.

• Example A: Simple CosmoMC-like Metropolis-Hastings analysis for WMAP9
• Example B: Multinest analysis of CFHTLenS with intrinsic alignments
• Example C: Emcee analysis of an extreme mass cluster to constrain omega_m
• The DES Year 1 Likelihood

Modules

All the scientific code in CosmoSIS is organized into independent modules. CosmoSIS ships with a standard library of modules doing most standard cosmology calculations (stored in a separate repository), and if you want to build or modify a pipeline you can use them:

• Standard library modules that come with CosmoSIS
• Understanding modules
• Creating new modules
• Where to put your own modules
• Modifying CAMB - an example tutorial on merging a modified camb into CosmoSIS

Input Files

A CosmoSIS run is specified with up two or three parameter files. The first two are required and the third (priors) is optional:

• Building your pipeline with the parameter file
• Setting input parameter ranges with the values file
• Adding priors with the priors file

[In development] The further postprocessing stage, to produce graphical plots of the results, may be specified entirely on the postprocess command-line, or preferably in a file:

• Defining graphical output with the postprocess parameter file

Samplers

CosmoSIS comes with a range of samplers suitable for different likelihoods spaces.

Simple:

• test sampler Evaluate a single parameter set
• list sampler Re-run existing chain samples
• a-priori sampler [In development] Sample at points according to given distribution

Classic:

• metropolis sampler Classic Metropolis-Hastings sampling
• importance sampler Importance sampling
• fisher sampler Fisher Matrices

Max-Like:

• maxlike sampler Find the maximum likelihood using various methods in scipy
• gridmax sampler Naive grid maximum-posterior
• minuit sampler MPI-aware maxlike sampler from the ROOT package.

Ensemble:

• emcee sampler Ensemble walker sampling
• kombine sampler Clustered KDE
• pmc sampler Adaptive Importance Sampling

Nested:

• multinest sampler Nested sampling
• polychord sampler Nested chordal sampling

Grid:

• grid sampler Regular posterior grid
• snake sampler Intelligent Grid exploration

Debugging:

• star sampler 1D slices in each dimension

Helper tools

• Self-Updater Get a newer/older version of CosmoSIS
• Error reporter Create a full error report to help diagnose problems
• Module Creator Create a new project and collection of modules
• Module Downloader Download a module from an internet repository
• Repository checker Check for unsaved changes in all your module repositories

Parallelize

• Using MPI to speed up sampling
• Using OpenMP to speed up modules

Debugging modules

• Debugging C/Fortran/C++ modules

Reference

• Running the programs
• Running cosmosis

• Running postprocess : Making plots and summary stats from chains

• Pre-defined data sections in CosmoSIS

• Configuring the pipeline

• Scripting CosmoSIS

Survey-specific code

• Dark Energy Survey

Changes

• Log of past changes
• Development version
• Roadmap of future plans

Get help

• Frequently asked questions
• Ask the CosmoSIS users mailing list (see above)
• Email the authors of the module you're using
• Open an issue with CosmoSIS