A c++ implementation of the concepts demonstrated in the python repository LTB-model. The purpose of this repository is to have a generic tool that solves the background and geodesic equations in the inhomogeneous Lemaître–Tolman cosmological model. There are a few libraries written in Fortran and python that do exactly the above, but they rely on exact analytical forms for the Mass function M(r), and Energy function E(r) which is a handicap. Here these functions are solved numerically and splined which can in fact speed up execution time. One thing different that I am doing here is that I evolve the background equations forward in time and use a series solution to set the initial conditions. The general practice has been to evolve backwards in time starting starting from the current age of the universe or use exact analytical form for the background solutions altogether. then analytical

To perform parameter constraints, the code relies on the python implementation (see http://dan.iel.fm/emcee/current/) of the affine invariant algorithm, see http://msp.org/camcos/2010/5-1/p04.xhtml. The algorithm performs much better then traditional samplers such as Metropolis-Hastings. For parameter estimation the speed bottleneck will not be because of the python interface but rather how fast one can calculate the likelihood function that one is maximizing or minimizing. You will also need Daniel et al.'s https://github.com/dfm/triangle.py to make the triangle plots.

A three parameter toy model for the dipole magnitude is used to test the code.

On linux do the following:

• python setup.py build_ext --inplace

• place cmb.o and scipy_tools.o produced from the first step in the working directory containing the rest of the code

• compile the Makefile with the make command

• compiling with OpenMP for parallel programing crashes (while performing MCMC) on some systems.
• error and exception handling needs to be implemented to conform to c++ standard