This repository contains the likelihood module for the KiDS-450 shear power spectrum measurements (derived using a quadratic estimator) from Köhlinger et al. 2017 (MNRAS, 471, 4412). The module will be working 'out-of-the-box' within a MontePython and CLASS (version >= 2.6!) setup. The required data files can be downloaded from 'http://kids.strw.leidenuniv.nl/sciencedata.php' and the parameter files for reproducing the fiducial results of the paper are supplied in the subfolder 'input' within this repository.
Assuming that MontePython (with CLASS version >= 2.6) is set up (we recommend to use the MultiNest sampler!), please proceed as follows:
1) Clone this repository
git clone https://bitbucket.org/fkoehlin/kids450_qe_likelihood_public.git
kids450_qe_likelihood_public.data from this repository into a folder named
(you can rename the folder to whatever you like, but you must use this name then consistently for the whole likelihood which implies to rename the
*.data-file, including the prefixes of the parameters defined in there, the name of the likelihood in the
__init__.py-file and also in the
3) Set the path to the data folder (
data_for_likelihood from the tarball available at the KiDS webpage listed above) in
kids450_qe_likelihood_public.data and modify parameters as you please (note that everything is set up to repeat the fiducial 3 z-bin analysis with
3) Start your runs using e.g. the
fiducial_<n>zbins.params (<n>=2, 3) supplied in the subfolder
input within this repository.
4) Contribute your developments/bugfixes to this likelihood (please use a dedicated branch per fix/feature).
5) If you publish your results based on using this likelihood (and data), please cite Köhlinger et al. 2017 (MNRAS, 471, 4412) and all relevant references for MontePython and CLASS.
run_fiducial_with_multinest.sh within the subfolder
input for all MultiNest-related settings that were used for the fiducial runs.
For questions/comments please use the issue-tracking system!