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The highly anticipated, updated version of my go-to-for-everything book on gnuplot.
Gnuplot in Action, Second Edition is a major revision of this popular and authoritative guide for developers, engineers, and scientists who want to learn and use gnuplot effectively. Fully updated for gnuplot version 5, the book includes four pages of color illustrations and four bonus appendixes available in the eBook.
About the Technology
Gnuplot is an open-source graphics program that helps you analyze, interpret, and present numerical data. Available for Unix, Mac, and Windows, it is well-maintained, mature, and totally free.
About the book
Gnuplot in Action, Second Edition is a major revision of this authoritative guide for developers, engineers, and scientists. The book starts with a tutorial introduction, followed by a systematic overview of gnuplot's core features and full coverage of gnuplot's advanced capabilities. Experienced readers will appreciate the discussion of gnuplot 5?s features, including new plot types, improved text and color handling, and support for interactive, web-based display formats. The book concludes with chapters on graphical effects and general techniques for understanding data with graphs. It includes four pages of color illustrations. 3D graphics, false-color plots, heatmaps, and multivariate visualizations are covered in chapter-length appendixes available in the eBook.
Table of Contents takes you straight to the bookdetailed table of contents
preface
acknowledgments
about this book
about the authors
author online
about the cover illustration
Part 1 Getting started
1. Prelude: Understanding data with gnuplot
1.1. A busy weekend
1.1.1. Planning a marathon
1.1.2. Determining the future
1.2. What is graphical analysis?
1.2.1. Why graphical analysis?
1.2.2. Limitations of graphical analysis
1.3. What is gnuplot?
1.3.1. Gnuplot isn’t GNU
1.3.2. Why gnuplot?
1.3.3. Limitations
1.3.4. Gnuplot 5: the best gnuplot there ever was!
1.4. Summary
2. Tutorial: Essential gnuplot
2.1. Simple plots
2.1.1. Invoking gnuplot and first plots
2.1.2. Plotting data from a file
2.1.3. Abbreviations and defaults
2.2. Saving commands and exporting graphics
2.2.1. Saving and loading commands
2.2.2. Exporting graphs
2.2.3. One-step export script
2.3. Managing options with set and show
2.4. Getting help
2.5. Summary
3. The heart of the matter: the plot command
3.1. Plotting functions and data
3.1.1. Plotting functions
3.1.2. Plotting data
3.2. Math with gnuplot
3.2.1. Mathematical expressions
3.2.2. Built-in functions
3.2.3. User-defined variables and functions
3.2.4. functions
3.2.5. Mathematically undefined values and NaN (Not-a-Number)
3.3. Data transformations
3.3.1. Simple data transformations
3.4. Logarithmic plots
3.4.1. Digression: How do logarithmic plots work?
3.5. Smooth interpolation and approximation
3.5.1. Interpolation curves
3.5.2. Point distributions
3.5.3. Deduping repeated entries
3.6. Summary
Part 2 Creating graphs
4. Managing data sets and files
4.1. Quickstart: The standard data file format
4.1.1. Comments and header lines
4.1.2. Selecting columns
4.2. Managing structured data sets
4.2.1. Multiple data sets per file: index
4.2.2. Records spanning multiple lines: every
4.3. File format options in detail
4.3.1. Number formats
4.3.2. Comments
4.3.3. Field separator
4.3.4. Missing values
4.3.5. Strings in data files
4.4. Accessing columns and pseudocolumns
4.4.1. Accessing columns by position or name
4.4.2. Pseudocolumns
4.4.3. Column access functions
4.5. Pseudofiles
4.5.1. Reading data from standard input
4.5.2. Heredocs
4.5.3. Reading data from a subprocess
4.5.4. Writing to a pipe
4.5.5. Generating data
4.6. Metadata in data files
4.7. Other file formats
4.8. Summary
5. Practical matters: strings, loops, history
5.1. Strings
5.1.1. Quotes
5.1.2. String operations
5.1.3. String applications
5.1.4. Crazy example: plotting the Unix password file
5.1.5. Digression: Unicode and UTF-8
5.2. String macros
5.3. Generating textual output
5.3.1. The print command
5.3.2. The set table option
5.4. Simplifying work with inline loops
5.4.1. Loops over numbers
5.4.2. Loops over strings
5.4.3. Summary of inline loops
5.5. Gnuplot’s internal variables
5.6. Inspecting compile-time options
5.7. Command history
5.7.1. Redrawing a graph
5.7.2. The general history feature
5.7.3. Restoring session defaults
5.8. Summary
6. A catalog of styles
6.1. Why use different plot styles?
6.2. Styles and aspects
6.2.1. Choosing styles inline through with
6.2.2. The default sequence
6.2.3. Customizing graph elements
6.3. A catalog of plotting styles
6.3.1. Core styles: lines and points
6.3.2. Indicating uncertainty: styles with errorbars or ranges
6.3.3. Styles with steps and boxes
6.3.4. Filled styles
6.3.5. Beyond lines and points: multivariate visualization
6.4. Putting it together
6.5. Other styles
6.6. Summary
7. Decorations
7.1. Quick start: minimal context for data
7.2. Digression: layers and locations
7.2.1. Locations
7.2.2. Layers
7.3. Additional graph elements: decorations
7.3.1. Common conventions
7.3.2. Arrows
7.3.3. Text labels
7.3.4. Shapes or "Objects"
7.4. The graph’s legend or key
7.4.1. Turning the key on and off
7.4.2. Placement
7.4.3. Layout
7.4.4. Appearance
7.4.5. Explanations
7.4.6. Default settings
7.5. Worked example: features of a spectrum
7.6. Summary
8. All about axes
8.1. Multiple axes
8.1.1. Terminology
8.1.2. Plotting with two coordinate systems
8.1.3. Sidebar: Should you do it?
8.1.4. Linking axes
8.2. Selecting plot ranges
8.2.1. What you need to know for interactive work
8.2.2. What you might want to know for batch processing
8.3. Tic marks
8.3.1. Overview and common conventions
8.3.2. Tic mark appearance and placement
8.3.3. Tic labels
8.3.4. Tic mark location and frequency
8.3.5. Reading tic labels from file
8.3.6. Grid and zero axis
8.4. Special case: Time series
8.4.1. Digression: Locales
8.4.2. Turning numbers into names: months and weekdays
8.4.3. General time series: the gory details
8.4.4. Beyond tic labels: processing date/time information
8.5. Summary
Part 3 Mastering technicalities
9. Color, style, and appearance
9.1. Color
9.1.1. Explicit colors
9.1.2. Alpha shading and transparency
9.1.3. Selecting a color through indexed lookup
9.1.4. Mapping a value into a continuous gradient
9.1.5. Using data-dependent colors
9.1.6. The built-in color sequences
9.1.7. Tips and tricks
9.2. Lines and points
9.2.1. Point types and shapes
9.2.2. Dash pattern
9.3. Customizing color, dash, and point sequences
9.3.1. Customizing line types
9.3.2. Special line types
9.4. Global styles
9.4.1. Data and function styles
9.4.2. Line styles
9.4.3. Arrow styles
9.4.4. Fill styles
9.4.5. Other global styles
9.5. Overall appearance: aspect ratio and borders
9.5.1. Size and aspect ratio
9.5.2. Borders
9.5.3. Margins
9.5.4. Internal variables
9.6. Summary
10. Terminals in depth
10.1. The terminal abstraction
10.1.1. Historical digression
10.1.2. The terminal workflow
10.1.3. Terminal capabilities and the test command
10.1.4. Gnuplot terminals today
10.2. Font selection and enhanced text mode
10.2.1. Font selection
10.2.2. Font resolution
10.2.3. Enhanced text mode
10.3. Generating PNG and PDF with Cairo-based terminals
10.3.1. Scaling a complete plot up or down
10.4. Using gnuplot with LaTeX
10.4.1. Including a graph in a LaTeX document
10.4.2. Using the cairolatex terminal
10.4.3. Letting LaTeX generate the graph
10.5. Scalable graphics for the Web with SVG and HTML5
10.5.1. The svg terminal
10.5.2. The canvas terminal
10.6. Interactive terminals
10.6.1. Common options
10.6.2. The wxt and qt terminals
10.6.3. Aqua
10.6.4. Windows
10.7. Other terminals
10.8. Summary
11. Automation, scripting, and animation
11.1. Loops and conditionals
11.1.1. Worked example: making graph paper
11.1.2. Worked examples: iterating over files
11.1.3. Worked examples: Taylor series and Newton’s method
11.2. Command files
11.2.1. Scripts as subroutines
11.2.2. Worked example: export script
11.3. Batch processing
11.3.1. Using gnuplot in shell pipelines
11.4. Calling gnuplot from other programs
11.4.1. Worked example: calling gnuplot from Perl
11.4.2. Worked example: calling gnuplot from Python
11.4.3. Helpful hints
11.5. Animations
11.5.1. Introducing a delay
11.5.2. Waiting for a user event
11.5.3. Further examples
11.6. Case study: continuously monitoring a live data stream
11.6.1. Using gnuplot to monitor a file
11.6.2. Using a driver to monitor arbitrary data sources
11.7. Summary
12. Beyond the defaults: workflow and styles
12.1. The standard interactive workflow
12.1.1. Extracting specifics from command files
12.1.2. Extending the command set
12.1.3. Session variables, loops, and macros
12.2. Using external editors and viewers
12.3. Invoking shell commands from gnuplot
12.3.1. Worked example: plotting each file in a directory
12.4. Hot keys and mousing
12.4.1. Default hot keys
12.4.2. Mousing
12.4.3. Custom hot keys
12.4.4. Capturing mouse events
12.4.5. Case study: placing arrows and labels with the mouse
12.5. Startup configurations and initialization
12.5.1. Startup and initialization files
12.5.2. Environment variables
12.5.3. Gnuplot command-line flags
12.6. Stylesheets
12.6.1. Worked example: stylesheets
12.7. Summary
Part 4 Understanding data
13. Basic techniques of graphical analysis
13.1. Representing relationships
13.1.1. Scatter plots
13.1.2. Highlighting trends
13.2. Logarithmic plots
13.2.1. Large variations in data
13.2.2. Power-law behavior
13.3. Point distributions
13.3.1. Summary statistics and box plot
13.3.2. Jitter plots and histograms
13.3.3. Kernel density estimates and rug plots
13.3.4. Cumulative distribution functions
13.4. Ranked data
13.5. Pie charts
13.6. Organizational issues
13.6.1. The lifecycle of a graph
13.6.2. Input data files
13.6.3. Output files
13.7. Presentation graphics
13.8. Summary
14. Topics in graphical analysis
14.1. Techniques for time-series plots
14.1.1. Plotting an Apache webserver log
14.1.2. Smoothing and differencing
14.1.3. Monitoring and control charts
14.1.4. Changing composition and stacked curves
14.2. Graphical techniques for multivariate data sets
14.2.1. Introduction
14.2.2. Distribution of values by attribute
14.2.3. Distribution by level
14.2.4. Scatter plot matrix
14.2.5. Parallel-coordinates plot
14.3. Visual Perception
14.3.1. Banking
14.3.2. Judging lengths and distances
14.3.3. Plot ranges and whether to always include zero
14.4. Summary
15. Coda: Understanding data with graphs
Appendixes
Appendix A: Obtaining, building, and installing gnuplot
Appendix B: Resources
The following bonus appendixes are available in the eBook
Appendix C: Surface and contour plots
Appendix D: Paletes and false-color plots
Appendix E: Special plots
Appendix F: Higher math
What's inside
- Creating different types of graphs in detail
- Animations, scripting, batch operations
- Extensive discussion of terminals
- Updated to cover gnuplot version 5
