
Numerical-Analysis-Examples - ergenekonyigit
https://github.com/ergenekonyigit/Numerical-Analysis-Examples
======
StefanKarpinski
Note the GPL license. Nothing wrong with that but if you copy one of these
into a code base you're developing, GPL applies to the whole "derived work".
If you're sufficiently cautious about legal matters it may be be best to avoid
looking at this code at all if you plan to implement any of these techniques
in a non-GPL project.

~~~
ergenekonyigit
I changed license.

~~~
StefanKarpinski
Excellent!

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elcapitan
Is that based on a common book on numerical analysis?

Because one thing I'd miss in the examples would be a few lines of comments -
if they're meant to be illustrative of a book that's ok, but learning the
other way (looking at source code, structure and comments) is also a good way
for many people to understand. If you're well read in source code, you can
read it to understand the math better.

~~~
chestervonwinch
Check out "Analysis of Numerical Methods" by Isaacson and Keller. It's a nice
book, and cheap, too.

~~~
elcapitan
Thanks - what I meant was whether the chapter-like structure of the examples
follows one particular book.

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alephnil
In terms of education this makes sense. You can read the code of common
numerical algorithms, written for clarity rather than speed, and learn how
they works. Not very comprehensive yet, but it can get there. Also,
contributing to this repo is a good way to learn.

That said, for actually getting the job done, you would probably use a library
like numpy instead of a library like this, as it is more powerful, both in
terms of execution speed and speed of development.

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projectramo
This has to be one of the easiest open source projects you can contribute to
if you are looking to do so.

Each contribution is small and modular, so you don't have to learn several
thousand lines of code.

The "real world" knowledge you have to learn is pretty specific and easy to
convert into code (compared to, say, legal opinions or object recognition).

~~~
dagss
But that is for good reason -- it seems to exist mainly for pedagogical
reasons. It is more like contributing to a textbook. Contributing to the "real
world" software (NumPY, OpenBLAS, etc) which is optimized and battle-hardened
is tougher exactly for that reason.

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frostirosti
Hey, I did a lot of these while I was learning Haskell

[https://github.com/Marcus-Rosti/numerical-methods](https://github.com/Marcus-
Rosti/numerical-methods)

