mcSchool

Online running with Jupyter

You can explore the Jupyter notebooks using nbViewer or run them on the online cluster Mybinder. Check and run the Jupyter notebooks here: nbViewer myBinder
Or the executed version: nbViewer myBinder

You can try to run in the new experimental Jupyter Lab environment jupyterLab

Offline running with Jupyter

In case that Docker is installed on you computer the only thing is to run the command in file runNotebook or for the new Lab environment runLab.

If you want to have better control over the files, first download the git repository, by

Use

git clone [email protected]:zleba/mcSchool.git

or download the archive.

wget https://github.com/zleba/mcSchool/archive/master.zip
unzip master.zip

Then run script ./runNotebook or ./runLab, the environment will be ready in the browser under localhost address. The temp directory is link to the local machine so one can edit and run the local files in the browser.

Offline running of the Python programs

Clone the git repository as above and run any command through docker, like:

cd exercisePy
./rd python -i exercise-1.py

The -i is for interactive mode, which can be useful if some plots needs to be shown.

Offline running of the C++ programs

The c++ programs are longer and need to be compiled but run faster.

Compile in the standard way using make and run afterwards, all in the docker environment rd

cd exerciseCpp
./rd make
./rd ./example-1

For the local running you may need to install docker on your computer (in case of Ubuntu):

sudo apt install docker.io

Offline running of the programs without docker on system with access to CVMFS file system

In this case you can use ROOT and LHAPDF libraries installed by CERN on CVMFS. Just call

source setupCVMFS.sh

to setup the environment and then simple run Python or C++ programs as above, but without ./rd in front.

Offline running without access to CVMFS

Without the Docker image and access to CVMFS the ROOT and LHAPDF needs to be installed which can take take some time.

Good luck.