Installation instructions
Setup python environment:
See the installation instructions.
Update conda python environment
New python packages can simply be installed with pip or conda. However, in order to reproduce the environment for someone else (including all dependencies), it is better to include them in the environment.yml file.
Suppose that you already have a working environment, but that you receive an updated environment file. You can then update your outdated conda environment by the following sequence (where ‘path/to/environment.yml’ is the path to the directory that contains the environment file, which in our case is the root of your copy of the course github repository)
conda deactivate
conda env update -f path/to/environment.yml
conda activate talent-env
Test your installation by opening a jupyter notebook, or a python session, and check that you can import the new modules without any error messages. E.g., having added GPy, pymc3, and pymultinest, to your environment you should try
>>> import GPy
>>> import pymc3
>>> import pymultinest
Install multinest
In order to use pymultinestwithin python you need to have a working version of multinestinstalled and the path to its library setup correctly. The following set of commands should work
git clone https://github.com/JohannesBuchner/MultiNest
cd MultiNest/build
cmake ..
make
sudo make install
if you have cmake and fortran compilers on your system. In case the import of the module still fails (with an error message about not finding the multinest library file) you can try setting the library path. With the bash shell you can do
export LD_LIBRARY_PATH="/path/to/lib:$LD_LIBRARY_PATH"
where /path/to/lib is the path to the lib directory of your Multinest build that should contain the library file. You might consider putting this command in your .bashrc file so that it is done automatically.
You can also read the full set of instructions at the PyMultinest installation guide.