Rating: 
Summary: A Useful Tool, but Know its Limitations
Review: Numerical Recipes is the perfect book for a programmer who took the required math classes and has since forgotten much of the material. Here you will encounter brief, theoretical discussions about how to solve common numerical problems, followed by implementations in C, and finished off with a few suggestions for further reading.I've actually found the explanations about how to solve problems more useful than the code they provide. Their C coding style seems to harken back to FORTRAN days. I've also translated from C to MatLab and IDL in some instances (on one occasion, translating the MatLab routine back to C a few years later!) Elsewhere on the net, mathematical critiques can be found. If you're trying to solve a critical problem, hunt these down. It bothered me to find vectors referenced from 1 to n as opposed to 0 to n-1, the way I'm used to seeing them in C code. But, for practical use, this book is difficult to beat. It makes, at the very least, a great starting point, especially for those of us who last took a math class 18 years ago and find the details foggy. Kind of like The Joy of Cooking. A good, basic reference to keep around, but not the final word on gourmet programming.
Rating:
Summary: Useful tool, good background reference
Review: Numerical Recipes offers a routine to address many applications I find myself needing for my dissertation work. I'm certain it will continue to be a valuable resource as I get out into the "real" world, as well. I have found myself many times going to the book for quick, comprehensible explanations of techniques which are explained in a much less intuitive fashion in some of my standard texts and references; if I need to know how something works, I'm more likely to understand what Press et al. say about it than what my Inverse Theory textbook has to say. I do find the programming style itself a little klunky, and although I am self-taught as both a FORTRAN and C programmer, enough of "classic" C-style has been drilled into me to share the annoyance of other reviewers regarding the array indexing in NR routines. Particularly difficult to call them from a larger driver program where I have already indexed everything beginning with zero. On the other hand, they're a cinch to adapt into Matlab for development and testing of new algorithms, since Matlab indexes from zero (which makes my own routines more difficult to translate). Optimization is not a feature of the NR routines, so for anything amounting to serious volumes of data, duct tape is needed. But for a good basic collection of applications and for someone like me who does better starting with something rather than nothing (or can never remember the formula for something) the routines are a Godsend, and the explanations in the book are invaluable.
Rating:
Summary: Useful tool, good background reference
Review: Numerical Recipes offers a routine to address many applications I find myself needing for my dissertation work. I'm certain it will continue to be a valuable resource as I get out into the "real" world, as well. I have found myself many times going to the book for quick, comprehensible explanations of techniques which are explained in a much less intuitive fashion in some of my standard texts and references; if I need to know how something works, I'm more likely to understand what Press et al. say about it than what my Inverse Theory textbook has to say. I do find the programming style itself a little klunky, and although I am self-taught as both a FORTRAN and C programmer, enough of "classic" C-style has been drilled into me to share the annoyance of other reviewers regarding the array indexing in NR routines. Particularly difficult to call them from a larger driver program where I have already indexed everything beginning with zero. On the other hand, they're a cinch to adapt into Matlab for development and testing of new algorithms, since Matlab indexes from zero (which makes my own routines more difficult to translate). Optimization is not a feature of the NR routines, so for anything amounting to serious volumes of data, duct tape is needed. But for a good basic collection of applications and for someone like me who does better starting with something rather than nothing (or can never remember the formula for something) the routines are a Godsend, and the explanations in the book are invaluable.
Rating: 
Summary: Tasteful recipes
Review: Simply the best book on numerical calculations. The source code is similar to recipes in cooking. Never taste a recipe itself... but start cooking.
Rating: 
Summary: The code is garbage.
Review: The algorithms are very well explained but there is no need for this book if you have the FORTRAN book. Just terrible C code. Like indexes starting at 1 instead of 0, just like in FORTRAN. No pointers just arrays. C'mon....
Rating:
Summary: He knows his stuff!
Review: The author's writing style seems a bit condescending towards computer engineers, but he knows his stuff. Skip the criticism, and look at his concepts. The material is introduced concisely and thoroughly and is explained well enough to let you explore the concept on your own. A must have if you're at all interested in the topic!
Rating:
Summary: Code IS compliant with ANSI and IS in ASCII format
Review: The code you purchase separately IS definitely in ASCII format. For the Windows version, the authors have provided a "browser" (yes, some kind of .dll file) that allows you to look at individual routines before saving them to your disk. This method is much easier than just dumping 400-500 routines (including example driver programs) to your hard disk. As the authors point out in the help file, there are numerous routines where they WANT you to change things (e.g., platform-dependent definitions of machine epsilon), or at least inspect, for your application. The idea that the code would not be provided in a format that can be edited is completely at odds with what the authors talk about in the Preface (1st ed.), as well as other places in the book. You're SUPPOSED to tear it apart and put it back together. If the above-referenced reviewer's diskettes really do not have the ability to extract ASCII files, like mine, then they are surely defective. Second, the code IS ANSI-C compliant, which is stated quite clearly in the book. The fact that it is different for different platforms probably (I'm guessing) has to do with the unwrapping program used to navigate through the source files. The Windows browsing file mentioned above is really just a clever application of the standard Windows ".hlp" file format. Obviously, you can't use that on Mac or UNIX. I saw yet another way to do it on DOS platforms with the first edition diskettes. There is no reason to suspect that the actual code is not IDENTICAL on all platforms, except, of course, that each platform defines a newline differently. That said, it is a clear violation of the user license to be porting the code between platforms. Now, if anyone cares about my opinion of the book... I am not a numerical analyst by trade. I'm just an engineer who finds myself doing numerical analysis sometimes. If this description fits you, or you are a graduate student doing engineering/physics (especially experimental work) that sometimes requires numerical analysis, then this may be the only book you need. It is DEFINITELY the first book you should BUY. Yes, you get all the source code in the book and that's great. But, you get an outstanding introduction, all in one place, to techniques of numerical analysis for all different kinds of applications. It is not a text book, so you don't have to waste the first three chapters proving a bunch of junk about converging series and Rolle's theorem and blah blah blah. (Blah blah blah gives you insight, no doubt. Far be it from me to trash the academic approach. I'm just sayin' that sometimes people in the real world have deadlines with large sums of money at stake and they have to take their best shot with or without the right background.) I signed up for, and promptly dropped, a numerical analysis course on three different occasions during my graduate career. It was just too boring. This book is fun, and usually gives me enough background to get going on a problem. (I'm sure numerical purists think it's incomplete; but, the authors are usually careful to tell you when they're giving you the "lite" version of some derivation. In those cases, they give you plenty of references.) I'm not a geek (at least I hope not), but I do find myself reading this book from time to time late at night just for the heck of it. My copy is well-worn and falling apart. Yes, some of the code is hard to follow, and sometimes it looks like they're making it that way just to be fancy. A couple of spaces here and there wouldn't hurt, and just because C lets you write stuff that can't be read by other people doesn't mean you have do it that way. And, yes, even though my one programming course was FORTRAN 77, I don't care at all for arrays that start at 1 in a language that fundamentally doesn't want to do it that way (even though it can). But, the authors give you a way around this (for 1D arrays, anyway...still waiting for a way to do it for 2D arrays.) It is not a big deal for many of the routines to just convert them to the zero-based assumption. I've there is definitely a productivity argument to be made (not just typing, but debugging). It's really not a big deal to type the code in (as I did for several years) IF you are careful, so you have to decide for yourself if you want to spend your OWN money on the source code.
Rating:
Summary: Truly horrible book
Review: The title of this book should be "Numerical Recipes in C: How NOT to Write Good Code". I hate this book. I really hate this book. The mathematical discussions are for the most part accurate, but they are written at a very high level, and sometimes poorly presented. For instance, I am well aware of how to perform Gauss-Jordan elimination on a matrix, but I was completely lost in their "explanation" of the technique. There is no chance anyone who did not already understand G-J elimination could possibly learn it from this rotten book. Now, the code. This book is full of THE WORST code I have ever had the misfortune of laying eyes on. C arrays are indexed from 1 instead of 0. What the hell is that? Find me ONE competent C programmer who would ever DREAM of doing something like that! The variables have informative names, such as'qqc', 'bma', 'ho', and 'hp'. It is completely hopeless to attempt to modify any of this miserable code to suit your application. If you are in any way considering this book, DON'T!!!!
Rating:
Summary: Truly horrible book
Review: The title of this book should be "Numerical Recipes in C: How NOT to Write Good Code". I hate this book. I really hate this book. The mathematical discussions are for the most part accurate, but they are written at a very high level, and sometimes poorly presented. For instance, I am well aware of how to perform Gauss-Jordan elimination on a matrix, but I was completely lost in their "explanation" of the technique. There is no chance anyone who did not already understand G-J elimination could possibly learn it from this rotten book. Now, the code. This book is full of THE WORST code I have ever had the misfortune of laying eyes on. C arrays are indexed from 1 instead of 0. What the hell is that? Find me ONE competent C programmer who would ever DREAM of doing something like that! The variables have informative names, such as'qqc', 'bma', 'ho', and 'hp'. It is completely hopeless to attempt to modify any of this miserable code to suit your application. If you are in any way considering this book, DON'T!!!!
Rating:
Summary: caveat emptor..........
Review: There are very many bad opinions about this series. Most of them do deserve a hearing. If u want something that shows u an implementation of algorithm.. helps you get started.. this is the book to look for. Be warned there are caveats. I used one of their routines and was left scratching my head for a week... because i failed to notice that it only accepted datas of length which are power of 2. The book said it somewhere.. but the code just failed with no warning. It is a good place to start, but a bad place to get stuck with. This book is a must if you deal with large data sets and find matlab very slow. You can quickly whip up something up in C pretty fast. I would say that their fortran 90 implementation is much cleaner than C. And so it is up to you.. do whatever u want to but don't use the codes blindly..for you will get burnt badly..
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