Python Tutorial for signal processing

This tutorial will help you get started using python for doing signal processing work for ELEC-301 case studies, and even doing some cool course projects!

Python Installations

Before you start, you need to set up a working Python environment on your PC. If you are on Mac or Linux system, you might already have a system Python installed. But, for signal processing applications you will need some specific Python packages (numPy, sciPy, matplotlib, and iPython), which are not installed by default. Though it is not at all difficult to install these on your system, we recommend these two approaches for ease, uniformity and predictability in system environments.

Install on your system Anaconda Python distribution (https://store.continuum.io/cshop/anaconda/).

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Use DataJoy's online scientific python (https://www.getdatajoy.com)

IPython Notebooks

The IPython Notebook is an interactive computational environment, in which you can combine code execution, rich text, mathematics, plots and rich media. Anaconda's scientific python distribution comes with the latest version of IPython notebook preconfigured and ready to go! DataJoy is also based around the idea of IPython notebook in the cloud.

For further details, visit IPython.

Working with the tutorials

All the tutorial files here are actually iPython notebooks which you can directly download and open within your browser-based IPython notebook environment (Anaconda's). You can also copy paste the code from the tutorial to IPython terminal on your system (Anaconda's) or online (dataJoy's). Whatever works best for you!

Table of contents

1. Basic Python tutorial for signal processing (3 parts)

• Part 1: Python background: Lists, list comprehension, functions, signal processing related libraries.
• Part 2: Introduction to numpy, nd-arrays (1D vector, 2D matrix) data types and linear algebra routines.
• Part 3: Plotting using matplotlib, defining time & frequency axis appropriately.