Matplotlib is a popular 2-dimensional plotting library used with Python. While Matplotlib is fairly powerful, I have always had trouble figuring out how to do what I needed from the documentation. I have found the online Matplotlib documentation adequate as a reference, but not very good for getting started (especially since Matplotlib uses some terms in what I would call a “non-standard” way).

Matplotlib for Python Developers by Sandro Tosi is a welcome addition to my bookshelf. It focuses on embedding Matplotlib in applications in GTK+, Qt 4, wxWidgets, and even various web frameworks such as Pylons and Django. But the fundamental elements of the scientific Python tool chain, such as NumPy and IPython, as well as a thorough tutorial of Matplotlib itself are discussed. Both the pylab/pyplot procedural interface (useful for interactive plotting) and object-oriented interface (useful for fine-tuning and more advanced usage) are covered. Over 2000 lines of example code are downloadable from the book site.

Seeing as I don’t use Matplotlib regularly, I’m sure I will using this book frequently to brush up on Matplotlib basics. And this book would have saved me a lot of time when I was writing my only major Python project, a PyQt 4 application which embedded interactive Matplotlib graphics. While this book doesn’t cover every detail of Matplotlib (the online docs are good for that), it will get you started no matter how you are using it.

The publisher has made a sample chapter on embedding Matplotlib in Qt4 available for download. More information, such as a full table of contents, is also available on the publisher’s site.

Full disclosure: I received a review copy of this book.

From the CRC Press site for Image Analysis, Classification, and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL, Second Edition:

This popular introduction to the processing of remote sensing imagery has been updated to include coverage of the latest versions of the ENVI software environment. This new edition covers support vector machines and other kernel-based methods. Illustrating many programming examples in the array-oriented language ID, the text includes coverage of basic Fourier, wavelet, principal components and minimum noise fraction transformations; convolution filters, topographic modeling, image-to-image registration and ortho-rectification; image fusion; supervised and unsupervised land cover classification with neural networks; hyperspectral analysis; multivariate change detection.

I was excited to hear that GPULib was used in this version of the book. Mort says:

In the text I discuss routines for nonlinear principal component analysis, supervised classification and nonlinear clustering, and explain that they can take advantage of GPULib/CUDA, if installed. (I use your routine GPU_DETECT() to check for GPULib).

Full disclosure: I work for Tech-X Corporation and worked on the IDL bindings and examples for GPULib.

xkcd, the great geek webcomic that I have mentioned before, has a printed book available for sale. Grab the mousepad depicting the fight with red spiders from the book’s back cover while you’re there.

Another good one from xkcd (well, they are all pretty good, but this one just hits close to home).

Here are some other math/stats related xkcd comics.

I just received a copy of IDL Primer by Ronn Kling. (Full disclousre: I received a free copy because Ronn used my Periodic Table of IDL Operators on the back cover.) It’s a pocket sized “quick reference” that provides a quick introduction to the main functional areas of IDL: the IDL Environment (DE is covered, get Kling’s Navigating the Workbench for coverage of the Workbench), syntax, array operations, program flow, 2D and 3D graphics, image processing, object graphics, file I/O, mapping, and animation. I have found it to be a quite handy reference, particularly the list of “Important Routines by Function” at the back (similar to the Functional List of IDL Routines in the online help).

I finally got a copy of Information Visualization by Colin Ware and started reading it. Information Visualization and Readings in Information Visualization edited by Stuart Card, Jock Mackinlay, and Ben Schneiderman are considered the classics in the field of Information Visualization (or InfoVis).

In Information Visualization, Ware evaluates visualizations using the scientific methods of psychology. Perception, vision, color, etc. are discussed and used to reach conclusions for creating visualizations.

The section on various flow visualization techniques was very useful since I’ve been thinking about line-integral convolutions (LIC) lately. There were also discussions of choosing colors, using texture maps, 3D shading, and a few plot types that have changed the way I will do some types of visualizations in the future.

In summary, I would say this is a useful book if you are serious about improving your visualizations. (Colin Ware has a new book coming out this April that looks interesting as well.)

I went to a talk titled “Effective Flow Visualization” by Colin Ware at NOAA last Friday. Dr. Ware works on issues of scientific visualization from an angle that was new to me: he studies human perception of visualizations. An interesting aspect of this study is that he tries to objectively measure the effectiveness of a given visualization. To do these tests he has people try to do common tasks with a visualization, like predict a dropped particle’s path in a flow visualization, and compares their answers to the computed answer. I haven’t read his book Information Visualization: Perception for Design, but his talk has motivated me to read it.

Dr. Ware is the Director of the Data Visualization Research Lab part of the Center for Coastal and Ocean Mapping at the University of New Hampshire.

The largest of the four books in this series by Edward Tufte, Beautiful Evidence is a welcome addition. It includes excellent examples of graphical excellence, in equally excellent production, which lead to general principles of presentation of data. I encourage you to take Tufte’s own advice about consuming evidence presentations; skip this second hand discussion of his book (i.e. the rest of this post) and go straight to the primary resource, Beautiful Evidence itself.

My favorite aspect of Tufte’s books are the examples: both good and bad. The good for examples to emulate; the bad for the humor.Beautiful Evidence is no exception, there are hundreds of images, graphs, diagrams, tables, and arrows in this book. The most notable bad examples come from the chapter on PowerPoint presentations (available as a separate pamphlet). The most notable good example is the extended discussion of Minard’s data-map of the French invasion of Russia, a Tufte favorite. Even the good examples are often dissected to find weaknesses.

Continue reading “Beautiful Evidence by Edward Tufte.”

There aren’t many third party IDL books: David Fanning has one, Liam Gumley has one, and Ronn Kling has three. Now Ken Bowman, a professor at Texas A&M University in the Department of Atmospheric Sciences, enters the fray with An Introduction to Programming with IDL. This book is geared towards a new user of IDL without programming experience. It covers the necessary topics to get started in IDL basic variable concepts, analysis, file input/output, and direct graphics visualizations including many exercises for these topics. It makes it a good fit for the academics market. From the Preface:

This book is intended to be used in an introductory computer programming course for science and engineering students at either the undergraduate or graduate level.

I think it achieves this goal very well, but don’t look here if you want to take your programming beyond basic analysis and visualization.

A major strength of the book are the downloadable example programs with their documentation, data files, and output. To try the examples, make sure to run @startup first to setup your IDL session.

See the book’s website for more information including table of contents, errata, downloadable example programs, and even the Interpolation chapter.

Continue reading “An Introduction to Programming with IDL by Kenneth P. Bowman.”

Edward Tufte’s latest book, Beautiful Evidence can be pre-ordered from Amazon.com or directly from Tufte’s site. Not sure if it means anything, but Amazon says it will be available July 30 and Tufte’s site says May. Mine is on order from his website; I will be sure to post my thoughts once I get my hands on it.

The topics covered in the book have been discussion in the forums on Tufte’s website for the past few years. The Powerpoint chapter has also been available as a pamphlet for a few years. They are:

1. Mapped Pictures: Images as Evidence and Explanation
2. Sparklines: Intense, Simple, Word-Sized Graphics
3. Links and Casual Arrows: Ambiguity in Action
4. The Fundamental Principles of Analytical Design
5. Corruption in Evidence Presentations: A Consumer’s Guide to Effects Without Causes, Cherry Picking, Overreaching, Chartjunk, and the Rage to Conclude
6. The Cognitive Style of Powerpoint: Pitching Out Corrupts Within
7. Sculpture Pedestals: Meaning, Practice, Depedestalization
8. Language Sculptures

Tufte’s previous books include The Visual Display of Quantitative Information, Visual Explanations: Images and Quantities, Evidence and Narrative and Envisioning Information. Every one has been a gem worth the 7-9 years that he has put into creating each one.