External likelihoods for SPT experiment using cobaya. These are python
implementation of original Fortran
code for CosmoMC
sampler.
The package includes the following likelihoods:
sptpol_2017
relates to SPTPol EETE likelihood used in Henning et al., 2017. The originalFortran
code is available here or in LAMBDA.spt3g_2020
relates to SPT3G EETE likelihood used in Dutcher et al., 2021. The originalFortran
code is available here.
spt_hiell_2020
relates to SPT-SZ TT likelihood used in Reichardt et al., 2020. The originalFortran
code is available in LAMBDA.
spt3g_2022
relates to SPT3G TT, TE and EE likelihood used in Balkenhol et al., 2022. The originalFortran
code is available here.
You can install the following code by just typing
$ pip install git+https://github.com/xgarrido/spt_likelihoods.git
If you plan to develop/modify the code, the easiest way is to clone this repository to some location
$ git clone https://github.com/xgarrido/spt_likelihoods.git /where/to/clone
Then you can install the likelihoods and its dependencies via
$ pip install -e /where/to/clone
The -e
option allow the developer to make changes within the spt
directory without having
to reinstall at every changes. If you plan to just use the likelihood and do not develop it, you can
remove the -e
option.
SPT data are stored in LAMBDA. You can download them
by yourself but you can also use the cobaya-install
binary and let it do the installation
job. For instance, if you do the next command
$ cobaya-install /where/to/clone/examples/spt3g_example.yaml -p /where/to/put/packages
data for SPT3G and code such as CAMB will be downloaded and
installed within the /where/to/put/packages
directory. For more details, you can have a look to
cobaya
documentation.
You can test the SPT
likelihoods by doing
$ test-spt
It will perform basic Χ² checks over the three different likelihoods.
You can also run MCMC chains with
$ cobaya-run /where/to/clone/examples/spt3g_example.yaml -p /where/to/put/packages