[Edu-sig] Annotate Algorithms in Python

[DiPierro, Massimo]

I do not know actually. I have not looked at many Python books on the subject.


In chapter 3 I have a review of some data structures Lists, Queues, Trees, Graphs, and Disjoint Sets with implementation. It includes what I had in these draft notes:


https://github.com/mdipierro/algorithms-animator/blob/master/docs/csc321notes.pdf?raw=true


The data structures and algorithms are implemented in the algorithm animator:


https://vimeo.com/1735226


https://github.com/mdipierro/algorithms-animator


Massimo


________________________________
From: Fernando Masanori Ashikaga [fmasanori at gmail.com]
Sent: Wednesday, December 18, 2013 4:36 PM
To: DiPierro, Massimo
Cc: edu-sig at python.org
Subject: Re: [Edu-sig] Annotate Algorithms in Python

Very good. I just bought. What other Python based books do you recommend for a Data Structure discipline?



2013/12/18 DiPierro, Massimo <MDiPierro at cs.depaul.edu<mailto:MDiPierro at cs.depaul.edu>>
Welcome everybody,


I just finished a book on Numerical Algorithms in Python:


http://www.amazon.com/Annotated-Algorithms-Python-Applications-Physics/dp/0991160401


It covers many algorithms including:

- merge sort

- binary sort

- heap sort

- priority queues

- tree search

- tree traversing

- topological sort

- Dijkstra

- Prim

- disjoint sets

- Huffman encoding

- linear algebra

- Cholesky

- Gauss-Jordan

- sparse matrix inversion (minres, bicgstab)

- Newton solver

- Newton optimizer

- bisection method

- secant method

- golden section method

- multi-dimensional solver

- least squares

- chi square fitting

- numerical integration by quadrature

- Fourier transform and fft

- random number generators

- Monte Carlo simulations

- parallelization with mpi4py, pyOpenCL, and OCL

- Map-Reduce


They all come with examples and applications.

The book contains the entire source code (pure python) and does use numpy.

The point of the book is not teaching existing API but showing/discussing python code.

Most of the code presented in the book can be downloaded here: https://github.com/mdipierro/nlib


Massimo




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