Random Number demos for CoDaS 2019

Getting started

To be able to run the demo, you are going to need a system with Miniconda (a minimal version of Anaconda) and several Python packages installed, or use the resources used for the other CoDaS tutorials at

https://ml-front.nautilus.optiputer.net/index.html

Create a new private JupyterLab with this repo, and select the 'Python [conda env:codas-hep]' environment.

For the Miniconda route, follow these instructions:

Download and install Miniconda

Go to the following website: https://conda.io/miniconda.html download and install the latest Miniconda version for Python 3.7 for your operating system.

wget <http:// link to miniconda>
sh <miniconda .sh>

After that, type:

conda --help

and read the manual.

Check-out the git repository with the exercise

Once Miniconda is ready, checkout the course repository and and proceed with setting up the environment:

git clone https://github.com/dan131riley/RandomDemo.git 

Create isolated Miniconda environment

Change into the course folder, then type:

cd RandomDemo
conda env create -f conda-envt.yml
source activate codas-random

Start jupyter notebook

Finally, start the jupyter notebook, if working on laptop do:

jupyter notebook