Some of the demo programs used in the course, particularly those using a GUI, are written in python. If you want to try this (open source, nice and free alternative to matlab), some tips are gathered below. Please note there is absolutely no requirement to learn about python for the course, the information is simply provided to give a few hints to those who want to try it.
If you are using linux (for instance ubuntu or debian), please use the package manager provided by the system (like synaptic under ubuntu). This will make your life considerably simpler, you just have to mark the different packages below and the system will do the installation for you.
If you are using windows, you can get all packages in one bundle by installing Python(x,y), choose Full installation after download.
If you are using macOSX, a corresponding bundle is provided by Enthought (also available for other platforms). I have not tested it myself, but it is recommended by many others. You should try the Academic or Trial version (the others cost money).
The packages can also be downloaded from their respective web sites (where you may find additional documentation):
- python (the language itself)
- matplotlib (provides most of the "matlab look-a-like" facilities (some tips here), usually pulls with it numpy and scipy below automagically)
- numpy (basic numerical calculations, particularly matrices)
- scipy (scientific libraries, for instance special functions and signal processing)
- wxpython (for GUI-programming, slightly more advanced, also look at tkinter which is bundled with python from scratch)
- mayavi (for 3D-plots using VTK, advanced but powerful)