Book Image

Matplotlib for Python Developers

Book Image

Matplotlib for Python Developers

Overview of this book

Providing appealing plots and graphs is an essential part of various fields such as scientific research, data analysis, and so on. Matplotlib, the Python 2D plotting library, is used to produce publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. This book explains creating various plots, histograms, power spectra, bar charts, error charts, scatter-plots and much more using the powerful Matplotlib library to get impressive out-of-the-box results. This book gives you a comprehensive tour of the key features of the Matplotlib Python 2D plotting library, right from the simplest concepts to the most advanced topics. You will discover how easy it is to produce professional-quality plots when you have this book to hand. The book introduces the library in steps. First come the basics: introducing what the library is, its important prerequisites (and terminology), installing and configuring Matplotlib, and going through simple plots such as lines, grids, axes, and charts. Then we start with some introductory examples, and move ahead by discussing the various programming styles that Matplotlib allows, and several key features. Further, the book presents an important section on embedding applications. You will be introduced to three of the best known GUI libraries 'GTK+, Qt, and wxWidgets' and presented with the steps to implement to include Matplotlib in an application written using each of them. You will learn through an incremental approach: from a simple example that presents the peculiarities of the GUI library, to more complex ones, using GUI designer tools. Because the Web permeates all of our activities, a part of the book is dedicated to showing how Matplotlib can be used in a web environment, and another section focuses on using Matplotlib with common Python web frameworks, namely, Pylons and Django. Last, but not least, you will go through real-world examples, where you will see some real situations in which you can use Matplotlib.
Table of Contents (14 chapters)
Matplotlib for Python Developers
About the Author
About the Reviewers

Real-time update of a Matplotlib graph

In this section, we will present a simple application—a CPU usage monitor, where we will update the Matplotlib graph in real-time (once every second over a period of 30 seconds).

As there are several indicators of CPU usage in a modern operating system, we decided to restrict our graph to the four main ones:

  • user: The time consumed by processes executed by the users of the machine

  • nice: The time consumed by processes executed by users but with a lower priority

  • system: The time consumed by system tasks

  • idle: The time consumed waiting for something to execute

The ignored indicators contribute for just a minimal part of the CPU usage, so their exclusion doesn't disturb the validity of the example.

Of those four indicators, what we will plot is the percentage of each of them against the total CPU usage.

Here we start:

import sys
from PyQt4 import QtGui

These are the modules for command-line parameters and for Python bindings of the QtGui submodule.