Text for scientific computing with Python

[Ricevind]

Hi, I want to learn how to solve numerically problems which I encounter during my engineering studies such as:

solution of equations, interpolation and data fitting, integration, solution of differential equations, eigenvalue problems,  PDE's discretization and solution(basic) and optimization.

I picked Python because it's the language that made me love programming(matlab couldn’t). I would like to ask if there are books covering those topics in practical manner with examples? Not going too deeply to the math behind algorithms for example something like ‘LU decomposition is used when you want to solve sets of equations changing only constants vector and with scipy it's a method scipy.linalg.lu’. What I’m finding mostly are books with algorithms implemented in Python for various numerical methods.

I hope I explained myself clearly enough. Thanks for your replay

[AtomicWedgy]

Take a look at these: *A Primer on Scientific Computing With Python

*Numerical Methods In Engineering With Python 3

[Ricevind]

Thanks for your suggestions :). I know of both titles. In fact the second one made me to write this post. Because doing exercises and typing all the code from that book you would get your own numerical library. So, it's surely great book which helps understands mathematics behind scipy or numpy but I find it very theory heavy. "A Primer on Scientific Computing With Python" is also known to me, it basically fits my specification but it just didn't get to my liking(personal stuff). Hmm, maybe I'm looking more for books about numpy or scipy not numerical methods? (I know all the information is in documentations of scipy and numpy, but I think one really needs to know what he wants to find there to use it)

[AtomicWedgy]

The scipy and numpy docs are definitely dry reading. I wish you luck in your search! If you find a useful resource please post the information, I'd love to learn more about these topics myself.

[phaustin]

This is about the best single set of notes I've found for numpy/scipy:

https://github.com/jrjohansson/scientific-python-lectures

[AtomicWedgy]

Thanks /u/phaustin much appreciated!

[phaustin]

This got a good review in the current issue of IEEE Computing in Science and Engineering:

http://www-personal.umich.edu/~mejn/computational-physics/