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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

2) Copy __init__.py and kids450_qe_likelihood_public.data from this repository into a folder named kids450_qe_likelihood_public within /your/path/to/montepython_public/montepython/likelihoods/.

(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 *.param-file.)

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 fiducial_3zbins.params).

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.

Refer to 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!