Annotate Algorithms in Python
Welcome everybody, I just finished a book on Numerical Algorithms in Python: http://www.amazon.com/Annotated-Algorithms-Python-Applications-Physics/dp/09... 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
Very good. I just bought. What other Python based books do you recommend for a Data Structure discipline? 2013/12/18 DiPierro, Massimo <MDiPierro@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/09...
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
_______________________________________________ Edu-sig mailing list Edu-sig@python.org https://mail.python.org/mailman/listinfo/edu-sig
Dear Fernando, As another recommendation, I'll note that I'm coauthor of a new Python-based Data Structures textbook that was published in 2013. Data Structures & Algorithms in Python by Goodrich, Tamassia, and Goldwasser http://www.wiley.com/WileyCDA/WileyTitle/productCd-EHEP002510.html The chapters are: * Python Primer * Object-Oriented Programming * Algorithms Analysis * Recursion * Array-Based Sequences * Stacks, Queues, and Deques * Linked Lists * Trees * Priority Queues * Maps, Hash Tables, and Skip Lists * Search Trees * Sorting and Selection * Text Processing * Graph Algorithms * Memory Management and B-Trees Great to see the increased interest. With regard, Michael On Wednesday December 18, 2013, Fernando Masanori Ashikaga wrote:
Very good. I just bought. What other Python based books do you recommend for a Data Structure discipline?
-- +----------------------------------------------- | Michael H. Goldwasser, Ph.D. | Professor, Director of Computer Science | Dept. Mathematics and Computer Science | Saint Louis University | 220 North Grand Blvd. | St. Louis, MO 63103-2007
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/csc321note... 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@gmail.com] Sent: Wednesday, December 18, 2013 4:36 PM To: DiPierro, Massimo Cc: edu-sig@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@cs.depaul.edu<mailto:MDiPierro@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/09... 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 _______________________________________________ Edu-sig mailing list Edu-sig@python.org<mailto:Edu-sig@python.org> https://mail.python.org/mailman/listinfo/edu-sig
Thanks. Felix P. Muga II, PhD Associate Professor Ateneo de Manila University On Dec 19, 2013 5:50 AM, "DiPierro, Massimo" <MDiPierro@cs.depaul.edu> wrote:
Welcome everybody,
I just finished a book on Numerical Algorithms in Python:
http://www.amazon.com/Annotated-Algorithms-Python-Applications-Physics/dp/09...
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
_______________________________________________ Edu-sig mailing list Edu-sig@python.org https://mail.python.org/mailman/listinfo/edu-sig
Any plans for the electronic version? 2013/12/18 DiPierro, Massimo <MDiPierro@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/09...
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
_______________________________________________ Edu-sig mailing list Edu-sig@python.org https://mail.python.org/mailman/listinfo/edu-sig
I am using amazon create-space for the first time. They have a tool for conversion to electronic format but, when I tried, everything got messed up badly. I will not give up. ;-) ________________________________ From: Fernando Masanori Ashikaga [fmasanori@gmail.com] Sent: Thursday, December 19, 2013 10:17 AM To: DiPierro, Massimo Cc: edu-sig@python.org Subject: Re: [Edu-sig] Annotate Algorithms in Python Any plans for the electronic version? 2013/12/18 DiPierro, Massimo <MDiPierro@cs.depaul.edu<mailto:MDiPierro@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/09... 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 _______________________________________________ Edu-sig mailing list Edu-sig@python.org<mailto:Edu-sig@python.org> https://mail.python.org/mailman/listinfo/edu-sig
participants (4)
-
DiPierro, Massimo -
Felix II P. Muga -
Fernando Masanori Ashikaga -
Michael H. Goldwasser