Most Helpful Customer Reviews
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82 of 87 people found the following review helpful:
4.0 out of 5 stars
Check GNU Scientific Library first, September 21, 2003
By A Customer
I give the book 4 stars to maintain the current level. I own a Fortran copy of NR, but like the other authors, I like NR for the explanations of algorithms, but not for the code. There is a VERY good alternative to Numerical Recipes in C, namely GNU Scientific Library. You can find the source code and manual from: http://sources.redhat.com/gsl/ or http://www.gnu.org/software/gsl As typical GNU software, GSL is licensed under GNU General Public License, so it is ABSOLUTELY free ! You can download it, modify it, linked it with your own code, without feeling guilty of copyright violation (Not in the case of NR, NR comes with a copyright license to prohibit modification and linking). GSL is written in C from scratch by its author. The design is modern, much better than NR in C, and also allowed linking with C++ or modern scripting language like Python. Some of the leading authors have background in theoretical physics and astrophysics, just like NR authors. Check it out. You lose nothing to check GSL first, you may ended up saving some $$$.
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31 of 31 people found the following review helpful:
4.0 out of 5 stars
Proprietary source the Achilles' heel for non-students, December 4, 2002
By A Customer
I first bought the FORTRAN version of this text in 1994 while doing scientific programming for graduate school work. I've been able to do a lot of basic research quickly with NR codes, and I still occasionally use NR's routines. The authors have certainly done a good job assimilating a lot of material in the NR series. Since other reviewers have done well to highlight the importance and utility of this landmark series, there is no need to repeat those sentiments here. I also agree with earlier reviewers applauding this title more as a survey or reference work and less as a library of source code. However, to this title's detriment, the authors actually consider the NR series to be a proprietary library of source code more valuable than the explanatory text surrounding it (one can in fact download the text on-line from the publisher though it's hardly worth the hassle). This perception is ironic since the authors confess that "the lineage of many programs in common circulation is often unclear," and many details of presentation, ideas, and algorithms are clearly "borrowed" from other excellent (some now out-of-print) numerical methods books or journals.Unfortunately, much of the source code in the 1993 C edition appears FORTRANish and is not very efficient as far as the C language goes (one would hope that improvements are coming in the new C edition, ISBN 0521574382). However, even the original FORTRAN NR routines occasionally adopted bizarre and/or obviously inefficient programming structures - over time I decided that this was probably done to make these algorithms appear as so not to obviously plagerize other published material. Many programmers try to get around this by reworking the NR codes. Apparently the authors consider modification of their sometimes inefficient code "derivative works" (even bug fixes) which cannot be legally redistributed or even used on more than one machine at a time without purchasing a new license or book. As a student, NR's legal disclaimers regarding derivative works never bothered me and I was willing to overlook the sometimes unpolished source code insofar as it functioned properly. But as a professional, I now find the lack of fair-use provisions on uncompiled, derivative source way too restrictive to rely on them in good conscience. I have since expanded my numerical methods library to other references supporting true public-domain codes. With an expanded basis of comparison, I regret to say that I am becoming less and less impressed with NR's implementations and explanations. I am finding some of NR's algorithms to be inefficient or unnecessarily approximate, and - on rare occasion - buggy. There have been quite a few bugs uncovered over the years, although the NR web site has done a good job of keeping track of them. In closing, this book is excellent for students wanting a good reference for quick and dirty types of analyses or scientific computing. Professional programmers, scientists, engineers, specialists or analysts performing research would be well advised to reference this title, but ultimately they will likely need to rely other resources if they require efficient and/or unrestricted (public-domain) source codes for their work.
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33 of 34 people found the following review helpful:
4.0 out of 5 stars
A Useful Tool, but Know its Limitations, March 18, 2001
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.
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Most Recent Customer Reviews
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by Richard Hamming
by William H. Press
