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A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering) (Englisch) Gebundene Ausgabe – 4. August 2009


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Produktinformation

  • Gebundene Ausgabe: 694 Seiten
  • Verlag: Springer; Auflage: 1 (4. August 2009)
  • Sprache: Englisch
  • ISBN-10: 3642024742
  • ISBN-13: 978-3642024740
  • Größe und/oder Gewicht: 24,8 x 19,8 x 4 cm
  • Durchschnittliche Kundenbewertung: 5.0 von 5 Sternen  Alle Rezensionen anzeigen (3 Kundenrezensionen)
  • Amazon Bestseller-Rang: Nr. 296.136 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
  • Komplettes Inhaltsverzeichnis ansehen

Mehr über den Autor

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Produktbeschreibungen

Pressestimmen

From the reviews:

“This book is an introduction to computer programming using the Python programming language. It focuses on numerical methods as the context for examples, exercises, and assignments. … Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. … Summing Up: Highly recommended. Upper-division undergraduates through professionals; general readers.” (F. H. Wild III, Choice, Vol. 47 (8), April, 2010)

“It is an authoritative and almost monumental work that covers most aspects of the Python language and its numerical modules. It definitely has a prominent place on my bookshelf. … The text is well written … . In summary, this is the book (the only book) to have if you are an aspiring Python programmer of scientific applications.” (Jaan Kiusalaas, SIAM Review, Vol. 52 (3), September, 2010)

“The book’s title reflects its content accurately, the content is substantively scientific and the book is a very good programming book. … This excellent book is quite rich mathematically, numerical methods, differential equations, treatments of shape, and a variety of exercises and projects are included. It will also impart a deep knowledge of python, one of today’s most useful languages. I have learned a great deal from this book and recommend it highly.” (George Hacken, ACM Computing Reviews, September, 2010)

Über den Autor und weitere Mitwirkende

Hans Petter Langtangen is a professor of computer science at the University of Oslo. He has formely been a professor of mechanics and is now the director of a Norwegian Center of Excellence: "Center for Biomedical Computing", at Simula Research Laboratory. Langtangen has published over 100 scientific publications and written several books, including papers and a book on Python's potential for scientific computing. He has also developed open source and commercial software systems for computational sciences.


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Die hilfreichsten Kundenrezensionen

1 von 1 Kunden fanden die folgende Rezension hilfreich Von S. Fotopoulou am 6. November 2009
Format: Gebundene Ausgabe
This book illustrates basic concepts of programming with Python in a very clear and concise way. Great introduction to object oriented programming using mathematical examples.

I would recommend it to scientists who are looking for an introduction to Python.
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Von Erwin P. am 12. Dezember 2011
Format: Gebundene Ausgabe Verifizierter Kauf
The book is a very well written and rich introduction to scientific programming with Python.
To be honest, the book could have been a bit more concise. But better too much than too less.
It has to be mentioned that this book is not a introduction to Python!
Even though the main concepts get a short review I would recommend it only to those you are familiar to the concepts of
this programming language. If thats the case I can only recommend buying this book.
And by the way: It really proofs much easier to do all the programming and computong on Linux since it is somewhat cumbersome to install all the required components on Windows, besides some features wont work on Windows!
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Von -cron- am 17. Mai 2010
Format: Gebundene Ausgabe
There are several well written textbooks on how to start with Python.

Unlike other introductions this one is focussing on the elements of the language, that are important to write programs in a scientific or engineering environment.

H.P. Langtangen did his job very well and professional.
This book is structured, descriptive, full of examples and exercises.

The student receives a considerable amount of knowledge how to cope with even some complex math and engineering tasks in Python and how to visualize results.

... that's what I expected from the book's title and that's what I got.

The quality of cover and paper of this book are also excellent.

If I would not own this book already, I'd order it without hesitation.

Kudos!
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Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)

Amazon.com: 13 Rezensionen
42 von 43 Kunden fanden die folgende Rezension hilfreich
An excellent introduction to numerical methids using Python. 14. Dezember 2009
Von Howard R. Hansen - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
Don't be fooled by the title or the first chapter, this book provides
a solid introduction for using Python in scientific applications. The
main application areas covered are calculating the value of functions,
both built in and user supplied, plotting data, finding the roots of
equations, difference equations, numerical differentiation, numerical
integration and the solution to differential equations by numerical
methods.

Along the way you will learn how to use lists, tuples, dictionaries,
loops, list comprehension, lambda functions, Numpy arrays, file I/O
and Python Classes for programming scientific applications. Two
main highlights of the book are the thorough explanations the author
provides on how to use most of the features of Python and the copious
number of examples with answers. Other features are an example on how
to extract data from a Web Page and scitools. Scitools provides a
Matlab type of interface to gnuplot. About the only thing missing is
a summary on how to install Numpy, Scipy, Scitools, gunplot, and
gnuplot.py.
23 von 24 Kunden fanden die folgende Rezension hilfreich
excelent textbook 17. Februar 2010
Von Beltran Gonzalez Carlos - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
This is a textbook which origins come from a course in an university. On the
one hand, this makes the author to explain things absolutely obvious, clearly
oriented to students in the first years of their technical degree. On the
other hand, some of these explanations become handy if you have to teach this
material or even, sometimes, to learn the origins of something that you have
accepted as obvious without knowing exactly why is so. This is particularly
relevant in those parts dealing with mathematics (many in the book). The book
probably is of no use for an expert on SciPy/Numpy, but it is definitely useful for
people, like me, that is starting to discover the enormous capabilities of
these python language extensions. I clearly recommend this book for such
target users. The book is also excellently well written, with a clear and
concise style. Errors seem to be absent from the text and exercises are very
well targeted to the area of scientific computation.
16 von 16 Kunden fanden die folgende Rezension hilfreich
Helpful book for me. 18. Juni 2010
Von A. Anderson - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
I've always done scientific computing using Fortran but got curious and did some projects with Python. I learned Python using online references. Now as I read through this Primer I realize how many essential details I missed by gathering information randomly off the internet. This book presents material clearly and in a comprehensive and logical manner.

Note that the emphasis is on teaching Python rather than numerical methods. If your main focus is to learn techniques for scientific computing then you should look for a different book.

Python is a good language for learning to use object-oriented programming (OOP) and this book will make that easy. On the other hand, the author didn't quite convince me that this approach is useful for scientific programming (but OOP is clearly quite useful elsewhere).

Overall I found the book very helpful - highly recommended.
6 von 6 Kunden fanden die folgende Rezension hilfreich
Excellent introduction to both scientific programming and Python in general 7. April 2011
Von A. P. Chamberlain - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
I bought this looking for an accessible introduction to numerical methods such as matrix math and numerical integration. The book's great for that. As a side benefit I realized as soon as I opened the book that I also now had a clearer tutorial for Python than any other I've seen. Like many of the other posters here, I originally tried to learn Python from looking at bits and pieces of code online and at various reference manuals, but didn't get very far. Nor have I found any of the other introductory books, even O'Reilly's canonical Learning Python, to be much help. This book filled in what I was missing. Much as with Perl, Python is a deceptively simple language, and many people are productive in it just by tweaking code they have found on the Web a bit and deploying it; but beyond this level is an extraordinarily powerful tool with a number of unique features that can only be appreciated and put to good use with a bit of hand-holding and careful walkthroughs of well-crafted code. You could almost see this book as providing that kind of clear, comprehensive understanding of the language, with numerical programming as simply a vehicle by which to accomplish that.
3 von 3 Kunden fanden die folgende Rezension hilfreich
For the mathematically minded, a nice way to learn Python 30. März 2012
Von David Ohlemacher - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
The book's title says it all. While this is a primer, it is not one where the reader is expected to read a hundred page project which is being used as an example. That type of book (e.g. Lippman's C++ Primer, 3rd ed.) never leaves my bookshelf. The concepts are explained with nicely sized examples. It is still serving me well as a reference.

There are many interesting exercises for every chapter. I appreciated this. I find it hard to learn a language without writing some code and this gave me something non trivial to write.

Python is now often my first choice for a task. Still love C++ though.
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