lklcom 0.4.1.post30

Clone Repository with Git

Clone the LikelihoodCombiner repository:

cd </installation/path>
git clone https://github.com/TjarkMiener/likelihood_combiner

Install Package with Anaconda

Next, download and install Anaconda, or, for a minimal installation, Miniconda. Create a new conda environment that includes all the dependencies for LikelihoodCombiner:

conda env create -f </installation/path>/likelihood_combiner/environment.yml

Finally, install LikelihoodCombiner into the new conda environment with pip:

conda activate lklcom
cd </installation/path>/likelihood_combiner
pip install --upgrade .

NOTE for developers: If you wish to fork/clone the respository and make changes to any of the LikelihoodCombiner modules, the package must be reinstalled for the changes to take effect.

Installing as a conda package

To install it as a conda package, first install Anaconda by following the instructions here: https://www.anaconda.com/distribution/.

Then, create and enter a new Python 3.8 environment with:

conda create -n [ENVIRONMENT_NAME] python=3.8
source activate [ENVIRONMENT_NAME]

From the environment, add the necessary channels for all dependencies:

conda config --add channels conda-forge
conda config --add channels menpo

Install the package:

conda install -c tmiener likelihood_combiner

This should automatically install all dependencies (NOTE: this may take some time, as by default MKL is included as a dependency of NumPy and it is very large).

If you want to import any functionality from LikelihoodCombiner into your own Python scripts, then you are all set. However, if you wish to make use of any of the scripts in likelihood_combiner/scripts (like {local/cluster}.py), you should also clone the repository locally and checkout the corresponding tag (i.e. for version v0.4.1):

git clone https://github.com/TjarkMiener/likelihood_combiner
git checkout v0.4.1

LikelihoodCombiner should already have been installed in your environment by Conda, so no further installation steps (i.e. with setuptools or pip) are necessary and you should be able to run scripts/{local/cluster}.py directly.

Dependencies

• Python 3.8.X

• NumPy

• SciPy

• Pandas

• PyTables

• PyYAML

• Matplotlib

Mock data

The data you can find in the LikelihoodCombiner, where produced with gLike using the mock data. These txt files don’t correspond to IACT observations of Segue 1 or Ursa Major II and are only included for testing the code framework.

Remove Anaconda Environment

First, remove the conda environment in which LikelihoodCombiner is installed and all its dependencies:

conda remove --name lklcom --all

Remove LikelihoodCombiner

Next, completely remove LikelihoodCombiner from your system:

rm -rf </installation/path>/likelihood_combiner