PyMC

Monte Carlo Markov Chain sampler for a given function

Edit testfunc.py to implement your own model.

Purpose

To generate most likely values for cosmological parameters $\large \Omega_bh^2, \Omega_mh^2, \Omega_{\Lambda}, n_s$ by running MCMC with physical model and Planck data.

Current physical model calculates the theoretical peak spacing of the CMB angular Power Spectrum using theory in Hu, Sugiyama 1994 and M. Doran, M.Lilley et. al. 2001 and fitting formulas given in M. Doran and M. Lilley, 2002. This is comapred with the peak spacing data in Planck satellite 2015 release.

Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
Input		Input
Output		Output
libmc		libmc
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
config.ini		config.ini
driver.py		driver.py
testfunc.py		testfunc.py