Sumatra is a great tool for reproducibility and provenance when you are running numerical simulations. Keeping your work reproducible ensures that you and others will be able to check your results at a later time, while provenance is to keep track of where your results came from in the first place.

I won’t get into details about using Sumatra in this post, as its documentation is quite good at describing that already.

Computational Physics members

If you are a member of the Computational Physics group and have access to the computing cluster, Smaug, you don’t have to install anything. Just ssh into our dedicated Sumatra machine, named bender, and run your jobs from there. In the future, all machines will support Sumatra, but for now, we only have one dedicated machine for this task:

ssh bender

On your own machine

Otherwise, or if you want it on your own machine, you will have to install it manually. This is done by cloning the repository and running the setup.py file. This will install Sumatra with all dependencies:

hg clone https://bitbucket.org/apdavison/sumatra
cd sumatra
python setup.py install --user

Adding –user to the final command ensures that all packages are installed to your home directory, under .local/lib, so that  you don’t have to install with sudo privileges, and it makes it a bit easier to remove the package if you don’t want to keep it.

We also need the GitPython and PyYAML modules, which you may install using apt-get:

sudo apt-get install python-git python-yaml

And that’s it! You should now be able to run your projects with Sumatra.