#### 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

## Signal construction

To aid the construction of signals with predetermined properties, the `scipy.signal` module has a nice collection of the most frequent one-dimensional waveforms in the literature – `chirp` and `sweep_poly` (for the frequency-swept cosine generator), `gausspulse` (a Gaussian modulated sinusoid), `sawtooth` and `square` (for the waveforms with those names). They all take as their main parameter a one-dimensional `ndarray` representing the times at which the signal is to be evaluated. Other parameters control the design of the signal according to frequency or time constraints. Let's take a look into the following code snippet which illustrates the use of these one dimensional waveforms that we just discussed:

```>>> import numpy
>>> from scipy.signal import chirp, sawtooth, square, gausspulse
>>> import matplotlib.pyplot as plt
>>> t=numpy.linspace(-1,1,1000)
>>> plt.subplot(221); plt.ylim([-2,2])
>>> plt.plot(t,chirp(t,f0=100,t1=0.5,f1...```