Accurate predictions for the clustering of galaxies in redshift-space in Python

pyRSD is a Python package for computing the theoretical predictions of the redshift-space power spectrum of galaxies. The package also includes functionality for performing Bayesian parameter estimation using the MCMC sampling technique or Maximum a posteriori estimation using the LBFGS algorithm to perform the nonlinear optimization.


The theoretical models used in this paper are described in more detail in Hand et al. 2017. Please cite this work if you use this package in your research.


Getting Started


The RSD module deals with computing the theoretical power spectrum predictions, given an input cosmology specified by the user.


The RSDFit module deals with running parameter estimation using the power spectrum models available in this package and data input by the user.

Get in touch

Report bugs, suggest feature ideas, or view the source code on GitHub.