Chapter 1, Introducing Interactive Plotting, covers basic figure-axes-artist hierarchy and other Matplotlib essentials such as displaying the plot. It also introduces you to the interactive Matplotlib figure.

Chapter 2, Using Events and Callbacks, provides Matplotlib's events and a callback system to bring your figures to life. It also explains how you can extend it with custom events, making the application truly interactive.

Chapter 3, Animations, deals with ArtistAnimation, FuncAnimation, and timers to make animations of all types. It also deals with animations that can be saved as movies.

Chapter 4, Widgets, covers built-in widgets such as buttons, checkboxes, selectors, lassos, and sliders, which are all explained and demonstrated. Here, you'll also learn about other useful third-party widgets and tools.

Chapter 5, Embedding Matplotlib, teaches you how to add GUI elements to an existing Matplotlib application. Here you'll also see how to add your interactive Matplotlib figure to an existing GUI application. Identical examples are presented using GTK, Tkinter, wxWidgets, and Qt.

At the absolute least, you will need the following Python packages installed on your system: NumPy, SciPy, Basemap, and (of course) Matplotlib. To work on the instructions presented in Chapter 5, Embedding Matplotlib, you will want to have at least one of the following GUI toolkits installed: GTK, Tkinter (should come with Python), wxWidgets, or Qt (version 4 is preferred; version 5 is supported only recently for Matplotlib version 1.4). You will also need the corresponding Python bindings for the GUI toolkits (some come with them by default).

If you are a Python programmer who wants to do more than just see your data, this is the book for you. It will explain the SciPy stack (that is, NumPy and Matplotlib) and provide pointers to install them. Experience with GUI toolkits, such as wxPython, Qt, or GTK+, is also not required, so this book can be an excellent complement to other GUI programming resources. To understand the examples and explanations, you need to know basic object-oriented programming terms and concepts.

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."

A block of code is set as follows:

import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from tutorial import track_loader
tracks = track_loader('polygons.shp')
# Filter out non-tracks (unassociated polygons given trackID of -9)
tracks = {tid: t for tid, t in tracks.items() if tid != -9}

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

    polys = [p for p in cells.polygons] 
    for p in polys: 
        p.set_visible(True) 
        p.set_alpha(0.0) 

    def update(frame, polys): 
        for i, p in enumerate(polys): 
            alpha = 0.0 if i > frame else 1.0 / ((frame - i + 1)**2) 
            p.set_alpha(alpha) 

    ax.set_xlabel("Longitude")
    ax.set_ylabel("Latitude")
    strmanim = FuncAnimation(fig, update, frameCnt, 
                             fargs=(polys,)) 
    plt.show()

Any command-line input or output is written as follows:

$ pip install matplotlib

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Now click on the Selection radio button and you will find that you can select a polygon again."

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