Time-domain Plotting Continued

Summary

In these videos, we cover interactive plotting using matplotlib of signals in the time-domain. Plotting a signal in the time-domain just means that the x-axis in our plots is time. This is probably the way you naturally visualize signals. This is in contrast to the frequency domain, which we will see later in this lesson.

We also practice more complicated visualizations like plotting event detections on top of a continuous signal as well as visually comparing two similar signals.

New Vocabulary

• Time-domain: The typical representation we are used to for signals where the signal is represented by values in time.

Notebook Review

If you wanted to interact with the notebook in the video, you can access it here in the repo /intro-to-dsp/walkthroughs/time-domain-plotting/ or in the workspace below.

Exercise 1: Plotting

Instructions

1. Complete the Offline or Online instructions below.
2. Read through the whole .ipynb.
3. Complete all the code cells that contain ## Your Code Goes Here.

Offline

1. In the repo which you can access here in the repo intro-to-dsp/exercises/1-plotting/ you should find the following files:
   • 1_plotting.ipynb
   • exercise1.npz
   • r_peaks.png
2. Open up the python notebook and associated files in your desired editor.

Note: Instructions can be found in Introduction to Wearable Data's Concept Developer Workflow for how to set up your local environment.

Online

1. Go to the next concept and the 1_plotting.ipynb should be open and the workspace should already contain the appropriate exercise1.npz file. This one will also contain the r_peaks.png file for the instructions in markdown.