The Python 3 code used in this course uses the following external libraries:
The most straightforward way to install Python and the required library and any operating system (Windows, OSX, linux) is to use a scientific distribution called Anaconda. Go to the following link https://www.continuum.io/downloads and download the installer corresponding to your system. Be sure to choose Python 3 and not Python 2.
There are installation instruction online:
To check your install has worked correctly open:
python and press
Enter. This should display a screen that looks something like:
Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul 2 2016, 17:53:06) [GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux Type "help", "copyright", "credits" or "license" for more information.
The version numbers might look different but the word
Anaconda should be there.
Once you've done that, type
exit() and press
Enter to exit the Python prompt.
You now have Python along with Sympy, Numpy, Scipy and a number of other useful libraries.
To install Nashpy and Axelrod:
pip install nashpy
pip install axelrod
After each one of those press
Enter. This should download and install the required software.
If you are using a machine for which you do not have administrative rights (for example a University lab computer) instead you should type:
pip install --user nashpy
pip install --user axelrod
To use Python I recommend using the Jupyter notebook (a popular tool in scientific computation - and also the tool used to build this course).
There are various ways to run the Jupyter server, one is to type:
in the Anaconda Prompt/Terminal.
Note that all chapters are available as jupyter notebooks (
.ipynb files). You can download them and modify/execute the code.
If you want to learn more Python there are a number of great resources online, you can also take a look at my Computing for Mathematics course which is an introduction to Python for mathematicians: http://vknight.org/cfm