matplotlib Plotting Cookbook

Discover how easy it can be to create great scientific visualizations with Python. This cookbook includes over sixty matplotlib recipes together with clarifying explanations to ensure you can produce plots of high quality.

matplotlib Plotting Cookbook

Cookbook
Alexandre Devert

Discover how easy it can be to create great scientific visualizations with Python. This cookbook includes over sixty matplotlib recipes together with clarifying explanations to ensure you can produce plots of high quality.
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Book Details

ISBN 139781849513265
Paperback222 pages

About This Book

  • Learn plotting with self-contained, practical examples that cover common use cases
  • Build your own solutions with the orthogonal recipes
  • Learn to customize and combine basic plots to make sophisticated figures

Who This Book Is For

If you are an engineer or scientist who wants to create great visualizations with Python, rather than yet another specialized language, this is the book for you. While there are several very competent plotting packages, matplotlib is “just” a Python module. Thus, if you know some Python already, you will feel at home from the first steps on. In case you are an application writer, you won't be left out since the integration of matplotlib is covered.

Table of Contents

Chapter 1: First Steps
Introduction
Installing matplotlib
Plotting one curve
Using NumPy
Plotting multiple curves
Plotting curves from file data
Plotting points
Plotting bar charts
Plotting multiple bar charts
Plotting stacked bar charts
Plotting back-to-back bar charts
Plotting pie charts
Plotting histograms
Plotting boxplots
Plotting triangulations
Chapter 2: Customizing the Color and Styles
Introduction
Defining your own colors
Using custom colors for scatter plots
Using custom colors for bar charts
Using custom colors for pie charts
Using custom colors for boxplots
Using colormaps for scatter plots
Using colormaps for bar charts
Controlling a line pattern and thickness
Controlling a fill pattern
Controlling a marker's style
Controlling a marker's size
Creating your own markers
Getting more control over markers
Creating your own color scheme
Chapter 3: Working with Annotations
Introduction
Adding a title
Using LaTeX-style notations
Adding a label to each axis
Adding text
Adding arrows
Adding a legend
Adding a grid
Adding lines
Adding shapes
Controlling tick spacing
Controlling tick labeling
Chapter 4: Working with Figures
Introduction
Compositing multiple figures
Scaling both the axes equally
Setting an axis range
Setting the aspect ratio
Inserting subfigures
Using a logarithmic scale
Using polar coordinates
Chapter 5: Working with a File Output
Introduction
Generating a PNG picture file
Handling transparency
Controlling the output resolution
Generating PDF or SVG documents
Handling multiple-page PDF documents
Chapter 6: Working with Maps
Introduction
Visualizing the content of a 2D array
Adding a colormap legend to a figure
Visualizing nonuniform 2D data
Visualizing a 2D scalar field
Visualizing contour lines
Visualizing a 2D vector field
Visualizing the streamlines of a 2D vector field
Chapter 7: Working with 3D Figures
Introduction
Creating 3D scatter plots
Creating 3D curve plots
Plotting a scalar field in 3D
Plotting a parametric 3D surface
Embedding 2D figures in a 3D figure
Creating a 3D bar plot
Chapter 8: User Interface
Introduction
Making a user-controllable plot
Integrating a plot to a Tkinter user interface
Integrating a plot to a wxWidgets user interface
Integrating a plot to a GTK user interface
Integrating a plot in a Pyglet application

What You Will Learn

  • Discover how to create all the common plots you need
  • Enrich your plots with annotations and sophisticated legends
  • Take control of your plots and master colors, linestyle, and scales
  • Add a dimension to your plots and go 3D
  • Integrate your graphics into your applications
  • Automate your work and generate a large batch of graphics
  • Create interactive plots with matplotlib
  • Combine your plots to create sophisticated visualizations

In Detail

matplotlib is part of the Scientific Python modules collection. matplotlib provides a large library of customizable plots and a comprehensive set of backends. It tries to make easy things easy and hard things possible. You can generate plots, add dimensions to the plots, and also make the plots interactive with just a few lines of code with matplotlib. Also, matplotlib integrates well with all common GUI modules.

This book is a head-first, hands-on journey into matplotlib, the complete and definite plotting package for Python. You will learn about the basic plots, how to customize them, and combine them to make sophisticated figures. Along with basic plots, you will also learn to make professional scientific plots.

In this book, you will start with the common figures that are offered by most plotting packages. You will learn how to add annotations, and play with styles, colors, scales, and shapes so that you can add personality and visual punch to your graphics. You will also see how to combine several graphics. With this book you will learn how to create sophisticated visualizations with simple code. Finally, you can make your plots interactive.

After reading "matplotlib Plotting Cookbook", you will be able to create the highest quality plots.

Authors

Table of Contents

Chapter 1: First Steps
Introduction
Installing matplotlib
Plotting one curve
Using NumPy
Plotting multiple curves
Plotting curves from file data
Plotting points
Plotting bar charts
Plotting multiple bar charts
Plotting stacked bar charts
Plotting back-to-back bar charts
Plotting pie charts
Plotting histograms
Plotting boxplots
Plotting triangulations
Chapter 2: Customizing the Color and Styles
Introduction
Defining your own colors
Using custom colors for scatter plots
Using custom colors for bar charts
Using custom colors for pie charts
Using custom colors for boxplots
Using colormaps for scatter plots
Using colormaps for bar charts
Controlling a line pattern and thickness
Controlling a fill pattern
Controlling a marker's style
Controlling a marker's size
Creating your own markers
Getting more control over markers
Creating your own color scheme
Chapter 3: Working with Annotations
Introduction
Adding a title
Using LaTeX-style notations
Adding a label to each axis
Adding text
Adding arrows
Adding a legend
Adding a grid
Adding lines
Adding shapes
Controlling tick spacing
Controlling tick labeling
Chapter 4: Working with Figures
Introduction
Compositing multiple figures
Scaling both the axes equally
Setting an axis range
Setting the aspect ratio
Inserting subfigures
Using a logarithmic scale
Using polar coordinates
Chapter 5: Working with a File Output
Introduction
Generating a PNG picture file
Handling transparency
Controlling the output resolution
Generating PDF or SVG documents
Handling multiple-page PDF documents
Chapter 6: Working with Maps
Introduction
Visualizing the content of a 2D array
Adding a colormap legend to a figure
Visualizing nonuniform 2D data
Visualizing a 2D scalar field
Visualizing contour lines
Visualizing a 2D vector field
Visualizing the streamlines of a 2D vector field
Chapter 7: Working with 3D Figures
Introduction
Creating 3D scatter plots
Creating 3D curve plots
Plotting a scalar field in 3D
Plotting a parametric 3D surface
Embedding 2D figures in a 3D figure
Creating a 3D bar plot
Chapter 8: User Interface
Introduction
Making a user-controllable plot
Integrating a plot to a Tkinter user interface
Integrating a plot to a wxWidgets user interface
Integrating a plot to a GTK user interface
Integrating a plot in a Pyglet application

Book Details

ISBN 139781849513265
Paperback222 pages
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