Much of the material in this document is taken from Appendix H.1 in the book A Primer on Scientific Programming with Python, 4th edition, by the same author, published by Springer, 2014.

Required software

The strictly required software packages for working with this document are

Python version 2.7 [1]
Numerical Python (NumPy) [2] [3] for array computing
Matplotlib [4] [5] for plotting

Desired add-on packages are

IPython [6] [7] for interactive computing
SciTools [8] for add-ons to NumPy
ScientificPython [9] for add-ons to NumPy
nose for testing programs
pip for installing Python packages
Cython for compiling Python to C
SymPy [10] for symbolic mathematics
SciPy [11] for advanced scientific computing

There are different ways to get access to Python with the required packages:

Use the RedHat Linux computer system at the Blindern campus, or perform a remote login to this system.
Install the software on your own laptop.
Use a web service.

There are detailed descriptions of remote login at the University of Oslo. In the following, various techniques for installing the necessary mathematical software on your own lap are presented, and we briefly describe web services for Python programming.

Using a web service is very straightforward, but has the disadvantage that you are constrained by the packages that are allowed to install on the service. There are services at the time of this writing that suffice for working with most of this document, but if you are going to solve more complicated mathematical problems, you will need more sophisticated mathematical Python packages, more storage and more computer resources, and then you will benefit greatly from having Python installed on your own computer.

This author's experience is that installation of mathematical software on personal computers quickly becomes a technical challenge. Linux Ubuntu (or any Debian-based Linux version) contains the largest repository today of pre-built mathematical software and makes the installation trivial without any need for particular competence. Despite the user-friendliness of the Mac and Windows systems, getting sophisticated mathematical software to work on these platforms requires considerable competence.