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＜電子ブック＞
Python Scripting for Computational Science / by Hans Petter Langtangen
(Texts in Computational Science and Engineering. ISSN:2197179X ; 3)

版	2nd ed. 2006.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2006
本文言語	英語
大きさ	XXIV, 736 p. 33 illus : online resource
著者標目	*Langtangen, Hans Petter author SpringerLink (Online service)
件　名	LCSH:Mathematics -- Data processing  全ての件名で検索 LCSH:Mathematical physics LCSH:Software engineering LCSH:Computational intelligence FREE:Computational Science and Engineering FREE:Theoretical, Mathematical and Computational Physics FREE:Software Engineering FREE:Computational Intelligence
一般注記	Getting Started with Python Scripting -- Basic Python -- Numerical Computing in Python -- Combining Python with Fortran, C, and C++ -- to GUI Programming -- Web Interfaces and CGI Programming -- Advanced Python -- Fortran Programming with Numerical Python Arrays -- C and C++ Programming with Numerical Python Arrays -- More Advanced GUI Programming -- Tools and Examples The second edition features new material, reorganization of text, improved examples and software tools, updated information, and correction of errors. This is mainly the result of numerous eager readers around the world who have detected misprints, tested program examples, and suggested alternative ways of doing things. I am greatful to everyone who has sent emails and contributed with improvements. The most important changes in the second edition are brie?y listed below. Already in the introductory examples in Chapter 2 the reader now gets a glimpse of Numerical Python arrays, interactive computing with the IPython shell, debugging scripts with the aid of IPython and Pdb, and turning “?at” scripts into reusable modules (Chapters 2. 2. 5, 2. 2. 6, and 2. 5. 3 are added). Several parts of Chapter 4 on numerical computing have been extended (- pecially Chapters 4. 3. 5, 4. 3. 7, 4. 3. 8, and 4. 4). Many smaller changes have been implemented in Chapter 8; the larger ones concern exemplifying Tar archives instead of ZIP archives in Chapter 8. 3. 4, rewriting of the material on generators in Chapter 8. 9. 4, and an example in in Chapter 8. 6. 13 on adding new methods to a class without touching the original source code and without changing the class name. Revised and additional tips on op- mizing Python code have been included in Chapter 8. 10. 3, while the new Chapter 8. 10 HTTP:URL=https://doi.org/10.1007/3-540-31269-2

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