Book Image

gnuplot Cookbook

By : Lee Phillips
Book Image

gnuplot Cookbook

By: Lee Phillips

Overview of this book

gnuplot is the world's finest technical plotting software, used by scientists, engineers, and others for many years. It is in constant development and runs on practically every operating system, and can produce output in almost any format. The quality of its 3d plots is unmatched and its ability to be incorporated into computer programs and document preparation systems is excellent. gnuplot Cookbook ñ it will help you master gnuplot. Start using gnuplot immediately to solve your problems in data analysis and presentation. Quickly find a visual example of the graph you want to make and see a complete, working script for producing it. Learn how to use the new features in gnuplot 4.4. Find clearly explained, working examples of using gnuplot with LaTeX and with your own computer programming language. You will master all the ins and outs of gnuplot through gnuplot Cookbook. You will learn to plot basic 2d to complex 3d plots, annotate from simple labels to equations, integrate from simple scripts to full documents and computer progams. You will be taught to annotate graphs with equations and symbols that match the style of the rest of your text, thus creating a seamless, professional document. You will be guided to create a web page with an interactive graph, and add graphical output to your simulation or numerical analysis program. Start using all of gnuplot's simple to complex features to suit your needs, without studying its 200 page manual through this Cookbook.
Table of Contents (18 chapters)
gnuplot Cookbook
About the Author
About the Reviewers
Finding Help and Information

Using kdensity smoothing to improve on histograms [new]

In Chapter 1, Plotting Curves, Boxes, Points, and more, we saw how to plot histograms, which are a type of statistical plot that show how a set of data is distributed: how many samples lie within each range of values, or bin. There are problems with histograms, venerable as they are, however. For example, the apparent shape of the distribution depends in part on how big we make our bins. Histogram plots can be misleading, and do not always serve the statistical purpose for which they were intended.

For these reasons and others, statisticians have invented other ways to calculate and display information about the distribution of a collection of data. One of these is called the kernel density estimate, which may be thought of as a kind of smoothed, bin-independent histogram. This is built into gnuplot as a plotting style—an option to the smooth style. This is a new feature in gnuplot version 4.4.

Getting ready

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