Python is a popular, powerful programming language that is often used in scientific computing. It is a good language for those of you new to programming, and is a powerful tool for experienced users.
You can use it as a scripting language for data analysis and file format conversion. Use it to set up cluster jobs, and to automate complex processing pipelines. Many simulators and analysis tools use Python as their scripting language. Python comes with a large suite of packages covering a wide range of programming and data processing tasks.
The numerical and plotting libraries for Python are comprehensive and powerful. It is a full suite of tools that include regular and sparse matrices, statistics, equation solvers, optimization, signal processing and much more. You can write applications or use it interactively for exploratory analysis in the same way you use R or Matlab.
This course is aimed at those of you with some limited experience programming in other languages, such as simple Matlab scripts or R. If you are completely new to programming you will still be able to follow along. The training is split into three 2-hour sessions:
Introduction to Python.
We go through the main parts of the Python 3 language. There are a few short interactive sections that we do on the Deigo cluster, although you can do them on your own laptop with Python 3 installed.
Practical Examples
We will introduce the Python package system; show you how to install new Python packages for your own use on the clusters; and go through a couple of interactive examples on how to make use of Python on the clusters. This will be mostly hands-on, with you working through the example tasks.
Numpy, Scipy and matplotlib
These are the main libraries for numericla computing using Python. We will introduce these libraries where we learn the basics of Numpy usage, how to use Scipy and Matplotlib and briefly touch on a few common use cases.
TBD
Make sure you have access to Deigo (apply here), and bring a laptop.
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Session 1
Session 2
Session 3