Python packages needed/recommended

Most modern laptops already have Python installed, so always check, if that is the case!

However, we will mainly/also be running Python through a Jupyter notebook on the science faculty server ERDA, so in principle a browser is enough. But in order to be able to run your Python code independently of network, we strongly recommend, that you also have Python 3.6+ installed on your laptop (possibly through an Anaconda environment, if you for some reason also need Python 2.7).

Python is often used with packages, which enables new (and often extremely useful) features possible in your programs. We will of course make use of packages (the most common ones, and a few specific for statistics), which in this course are:

  • scipy - A collection of tools for scientific computing.
  • numpy - Numerical Python, with powerful N-dim arrays and linear algebra commands.
  • matplotlib - The Python standard for plotting graphs and histograms.
  • iminuit - The Python interface to the minimisation package Minuit.
  • probfit - Functions for constructing complex fits (used with iMinuit). All packages can be installed through "pip" directly, with the exception of propfit, for which we recommend doing the following:
  • git clone git://github.com/iminuit/probfit.git
  • cd probfit
  • pip install cython --user
  • pip install . --user If the above doesn't work, please write us.
    Last updated 13th of November 2018.