O'Reilly just published a new book, the Mathematica Cookbook, about Wolfram Research's flagship product. This book contains many interesting examples from various different disciplines. Most of these are derived from freely available examples written by other people (primarily from Wolfram Research's original Mathematica Book and also the excellent Wolfram Demonstrations Project) but the author has simplified some of the programs to make them more accessible.

However, the density of the information in this book is incredibly low. Most pages are filled with superfluous Mathematica output that is often not even described in the text:

- Dozens of triples on page 15.
- Page 58 lists hundreds of numbers but the text does not even describe their significance.
- Page 205 lists all of the words with a subset of the letters "thanksgiv".
- Page 226 is raw XML data.
- Pages 264-265 are solid code that renders a snowman with circles and some dots for snow (all in black and white).
- Pages 303-304 are two more pages of code to plot a snowman in 3D.
- Page 321 lists all of the properties in Mathematica's polyhedron database and page 322 draws 20 polyhedra before page 324 enumerates exactly the same polyhedron properties again.
- Pages 334-335 enumerate image data numerically (three times).
- Page 359 displays quadrant swapping with 25x more matrix elements than necessary.
- Page 360 is the Fourier transform of an image and page 361 is an apparently identical one.
- Page 507 lists every chemical element and page 571 lists every property of them.
- Page 553 lists every property available for financial data and page 554 lists them all over again.
- Page 572 contains an empty graph.
- and so on...

Many pages are devoted to TreeForm plots of trees that convey no useful information, e.g. the trees drawn on page 129 in the section about red-black trees:

Would have been nice to see red and black colored nodes or even learn how to do that using Mathematica (assuming it is possible). In particular, half of page 115 is a TreeForm view so badly laid out by Mathematica that it is unreadable.

There are also some problems with the technical content itself. For example, the section on red-black trees is a simple translation from Okasaki's excellent book "Purely functional data structures". The only new functionality Sal Mangano added is a remove function but his implementation is completely wrong.

The book is chocked full of advice about optimization. This is both good and bad. Good because Mathematica users need all the help they can get with performance because Mathematica is so slow. Bad because the best advice for a Mathematica user when performance is even vaguely relevant is to ditch Mathematica in favor of a more modern tool with better performance. For example, section 14.10 "Compiling an Implementation of Explicit Trinomial for Fast Pricing of American Options" states that "You need a very fast pricer for American options" but the fastest Mathematica code given can be a whopping 960× slower than a comparably-simple F# solution. Furthermore, it turns out that this was not written by Sal Mangano (the author of the book) but by Andreas Lauschke (a Mathematica and Java consultant) and it is a translation of MATLAB code written by Ansgar Jüngel (an academic).

There are several multi-page program listings written as plain Mathematica code with embedded comments that are difficult to read (they are not even spaced out, let alone typeset properly!) instead of prose. Page 265 is a block of code, for example:

Although the book does contain a frustrating amount of blatant filler, it is very cheap (O'Reilly) and does contain several thought-provoking examples. Whether you use Mathematica or not, you'll probably learn something useful about the state-of-the-art in the Mathematica world by skimming this book. On a higher level, you will probably learn a lot more about business if you consider what this book and the army of Mathematica devotees behind it represent. After all, there is a lot of money in starting a religion!

FWIW, here are the interesting references from the book to original sources:

- Interval Computations.
- Sequential and parallel sorting algorithms.
- Interactive data structure visualizations.
- How to write a spelling corrector by Peter Norvig (of Google).
- Data structures and efficient algorithms in Mathematica by Daniel Lichtblau.
- Packrat parsing.
- Twisted architecture by Chris Carlson.
- Histogram equalization.
- The Yale face database.
- A tutorial on Principal Components Analysis by Lindsay I Smith.
- Generatingfunctionology by Hilbert S Wilf.
- Predator-Prey dynamics with type-2 functional response by Wilfried Gabriel.
- Theory of Finite Element Analysis.
- Finance-related Mathematica resources from Weber & Partner.

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