Overview of this book

Learning SciPy for Numerical and Scientific Computing Second Edition
Credits
www.PacktPub.com
Preface
Free Chapter
Introduction to SciPy
Working with the NumPy Array As a First Step to SciPy
SciPy for Linear Algebra
SciPy for Numerical Analysis
SciPy for Signal Processing
SciPy for Data Mining
SciPy for Computational Geometry
Interaction with Other Languages
Index

Filters

A filter is an operation on signals that either removes features or extracts some component. SciPy has a complete set of known filters as well as the tools to allow construction of new ones. The complete list of filters in SciPy is long, and we encourage the reader to explore the help documents of the `scipy.signal` and `scipy.ndimage` modules for the complete picture. We will introduce in these pages, as an exposition, some of the most used filters in the treatment of audio or image processing.

We start by creating a signal worth filtering:

```>>> from numpy import sin, cos, pi, linspace
>>> f=lambda t: cos(pi*t) + 0.2*sin(5*pi*t+0.1) + 0.2*sin(30*pi*t) + 0.1*sin(32*pi*t+0.1) + 0.1*sin(47* pi*t+0.8)
>>> t=linspace(0,4,400); signal=f(t)
```

First, we test the classical smoothing filter of Wiener and Kolmogorov, `wiener`. We present in a `plot` the original signal (in black) and the corresponding filtered data, with a choice of Wiener window of size 55 samples (in blue)...