As somebody who came to scientific computing late in life, after spending years as a physicist then an engineer, I will step up to defend NR, if only for fun (a

As somebody who came to scientific computing late in life, after spending years as a physicist then an engineer, I will step up to defend NR, if only for fun (and because I like the book for what it is). At least one commenter here dismissed NR, saying that it is equivalent to an undergraduate numerical analysis book. Well, duh! That's one of its strengths! It is a good book for an audience like me -- somebody with scientific background but with no formal numerical analysis training who needs to write some numerical code. The target reader is an engineer who needs to implement something specific. That's a very common scenario -- you are given the job of implementing some calculation as part of a larger project. You're not an expert in the particular mathematical discipline. You don't want to fool around trying to find an algo in some book since you don't know which of the zillions of numerical analysis books to look at. Also, most books will just give you a general algo, not ready-to-run code. Everybody knows how hard it can be to translate a wordy description of an algo into real code. If you had the budget you'd just hire somebody to do it for you. NR solves your problem -- you use the code and your problem is solved so you can move on to the next step of your project. A different commenter here suggested using Golub and Van Loan instead. That's laughable. First off, as others pointed out, their "Matrix Compuations" book addresses numerical linear algebra exclusively. NR is a general-purpose numerical analysis book, so covers a much larger topic set. But secondly, Matrix Computations is difficult reading for non-mathematicians. Even if I needed to implement some sort of matrix decomposition, I would find it a pain to use that book as a source. (Yes, I am sure some testosterone-soaked HN commenter will now say that they read "Matrix Computations" in 3rd grade as a way to prove how smart they are. Allow me to roll my eyes now.) The real complaint made in the linked post involves the licensing terms of the code in NR. I agree the license stinks by today's standards. But the book was originally written back in the 1980s. My copy is from the early 1990s. Back then the GPL was basically unknown outside of a group of happy hackers at MIT. Software licensing certainly not a topic occupying mindspace of ordinary scientists or engineers. There was some DOS-based "freeware" circulating on 3.5" disks, but the whole "free (libre) software" movement was still in the future -- it needed the internet to become widespread in order to take off. Finally, I can imagine the NR authors wanted some sort of copyright or license which prevented wholesale copying of their work by folks who would try to profit off it. It's reasonable for them to have wanted to get some monetary reward for their hard work. Their license is probably an artifact of its time. In my travels I have seen situations where code used in commercial products incorporates this or that function presented in NR. For example, I saw the FFT algo used in a test widget. (I authored none of the copied code -- I simply observe it in projects done by others.) What's funny is that NR's FFT algo is not particularly great. However, the guys who needed an FFT probably didn't know that. They probably would not have cared anyway -- they just wanted a working solution and that's what they got from NR. I am sure that little violations of the NR license happen all the time. It may not be strictly legal, but I also see people making Xerox copies of copyrighted books and journal articles all the time too. Finally, regarding alternatives like GSL, ccmath, or whatever is available on netlib, those projects post-date NR. In any event, the internet is what made all those things widely available. I bought my copy of NR in a bookstore before that happened.