Computing signal construction

In this section, we will see the signal constructions on how to develop the functions.

How to do it…

1. 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), and sawtooth and square (for the waveforms with those names).
2. 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.
3. Let's take a look into the following code snippet that 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...