Numerical Recipes Guide, Meaning , Facts, Information and Description
Numerical Recipes is the generic term for the following books on algorithms and numerical analysis, all by William Press, Saul Teukolsky, William Vetterling and Brian Flannery:
- Numerical Recipes in C++. The Art of Scientific Computing, ISBN 0-521-75033-4.
- Numerical Recipes in C. The Art of Scientific Computing, ISBN 0-521-43108-5.
- Numerical Recipes in Fortran. The Art of Scientific Computing, ISBN 0-521-43064-X.
- Numerical Recipes in Fortran 90. The Art of Parallel Scientific Computing, ISBN 0-521-57439-0.
The books contain an enormous amount of material on computational methods, and an accompanying disk includes a large amount of computer code and several libraries. The scope is supposed to be "everything up to, but not including, partial differential equations", although the second edition does include a chapter on PDEs that discusses the important concepts in the field and cites the most important papers.
The Numerical Recipes series is notable for its accessibility and general not-too-serious tone. The emphasis is on the understanding of techniques (the authors repeatedly state their suspicion of black-box techniques). Many of the algorithms presented emphasise clarity and practicality as the primary desiderata. From the preface to the first edition:
- If there is a single dominant theme in this book, it is that practical methods of numerical computation can be simultaneously efficient, clever, and---important---clear. The alternative viewpoint, that efficient computational methods must necessarily be so arcane and complex as to be useful only in "black box" form, we firmly reject.
It is inevitable that a book of this scope and importance (the books' sales figures are very high) will attract criticism. The books are especially controversial in the Numerical Analysis community. Negative criticism has centred on the books' unreliability (the first edition contained some mistakes), the exclusion of some algorithms, and the authors' opinion that clear and intelligible programs can be efficient (see the above citation).
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