A simple MCMC code for cosmological parameter estimation where only expansion history matters. Written by Anže Slosar and Jose Vazquez.

This is the github version, based off internal BOSS svn. It should work, but feel free to complain to me (Anže Slosar).

This code is not intendent as a replacement of CosmoMC. It simply reimplements the homogeneus part of cosmomc code. This allows one to fit BAO data, etc. in the spirit of arxiv:xxxx for any bat-shit crazy model without much hassle and very quickly. One just needs to define how Hubble parameter varies with redshift. It might also be useful for pedagogical reasons.

py - analysis code
Run - actual executables - you should read them like scripts
data - data files
chains - empty directory to store chains
example - a simple example to see how the code works
tools - various tools we use for plotting, etc.
attick - various hacks and tests

A quick start with the code, try:

examples/TestRun.py
and then, after a few minutes
examples/TestPlot.py

But this is now how we normally run the code. To fit for LCDM using BOSS BAO without assuming you know what rd is, say something

Run/driver.py pre LCDM BBAO

To fit for oLCDM using Lyman-alpha BAO and LyaCross BAO +Planck say

Run/driver.py phy oLCDM LBAO+Planck

Run/driver.py will print all possible options

It was supposed to be minimal, allowing any one to add models, without being spaghetti.

There are three basic kind of objects:

Cosmology objects that define models. These are based on BaseCosmology.py

Likelihood objects that calculate Likelihood given some theory predictions from Cosmoloy. These are based on BaseLikelihood. You tell them the theory you want to use with setTheory and then you can ask them about loglikelihood(). They can also tell you which Parameters they have with freeParameters. These are based on Parameter.py and are really simple -- name defines the parameter (like white socks define an american).

Analyzers -- these take likelihoods and do something with it (see below)

To see how data is used, start with BOSSLikelihoods.py This defines objects that actually correspond to real likelihoods. These are then chucked into one single CompositeLikelihood as seen in Run/TestRun.py.

To see how models are created, have a look, for example at LCDMCosmology.py and oLCDMCosmology.py.

Parameters and priors are defined in ParamDefs.py

LCDMCosmology inherits BaseCosmology and defines three functions:

freeParameters - here we announced what are the parameters in this model

updateParameters - here we process a request to update parameters. Here we store parameters, but must also update rs of the BaseCosmogy if it is affected. At the moment we keep rs constant.

HSSquared_a - this is the relative Hubble parameter squared, in simple ternms H(a)2/H02

BaseCosmology deals with integrating the above to various distance moduli. It also handles the prefactors of the form c/(H0rs). We can either have h=H0/100 as a parameter and then believe that rs is whatever it is, or have the entire phenomenological prefactor c/(H0rs) as a free parameter. One can switch this on as demonstrated in Run/TestRun.py with T.setVaryPrefactor().

RadiationAndNeutrinos.py deals with, well, radiation and neutrino components. NuDensity.py calculates the annoying neutrino integral.

So, one can then create a composite Likelihood by saying e.g.

L=CompositeLikelihood([ DR11LOWZ(), DR11CMASS(), DR11LyaAuto(), DR11LyaCross() ])

and then connect it to a theory, like L.setTheory(oLCDMCosmology())

This is now a nice package: L.freeParameters() will tell you which parameters you can jiggle. L.updateParams() allows you to update them. L.loglike() returns the total log likelihood.

Different Analyzers can use this interface to do different things with this likelihood, without knowing anything about the underlying theory. There are two attached:

MaxLikeAnalyzer - finds the maximum and then uses second derivative to get errors, only that that doesn't quite work and I think this is due to linear interpolation in the chi2 tables

MCMCAnalyzer - a vanilla MCMC samples compatible with CosmoMC format

tools/cosmich.py is an archaic ugly script that I use for plotting.