Python

Python

Python is a popular scripting language. It is on the top 10 of the TIOBE index, and is often used in scientific programming outside of the major commercial platforms like Matlab or Mathematica.

• Check out the Python website for more information

Installation

• Windows: The MPR module uses Python(x,y). This is a distribution which supplies a full scientific programming environment. If that local link does not work, look for a Python(x,y) executable installer here or download directly from the Python(x,y) website. Note that the Anaconda distribution is probably a lot better. There is a local mirror of that here. Use Anaconda3.
• Linux: Install python along with Matplotlib and Numpy/Scipy
• Mac: Use Anaconda.

Python 2 vs Python 3

Python 3 came out in 2008. The problem was that it was not backwards compatible with all Python 2 programs. This delayed adoption, especially in the scientific community. There is probably no reason to use Python 2 any more.

Scientific computing

Numeric calculations are done using the NumPy or SciPy modules. Here is a handy starting point for someone used to Matlab/Octave to get into NumpPy/Scipy.

• Numpy/SciPy for Matlab/Octave users. Like a Rosetta stone.
• More detailed SciPy lectures

Plotting is done using the matplotlib library. The website contains documentation as well as a large gallery of examples.

The SciPy website also has a lot of examples in their Cookbook. Topical ones include

• Solving nonlinear equations
• Optimisation
• Fitting data
• Numerical integration of ODEs

The department also maintains a small cookbook notebook.

Thermo-Physical Properties of Materials

Have a look at CoolProp. It is a thermo-physical property database with properties of many common pure substances. It has a python package as well as an Excel add-in.

Symbolic computing

The sympy module is a very capable symbolic module for Python. It plays well with the IPython notebook