LANGTANGEN PYTHON SCRIPTING FOR COMPUTATIONAL SCIENCE PDF

PDF | On Jan 1, , H P Langtangen and others published Python Scripting for Computational Science. Python Scripting for Computational Science. Hans Petter Langtangen. Simula Research Laboratory and. Department of Informatics. University of Oslo. Texts in Computational Science and Engineering. Free Preview. © Python Scripting for Computational Science. Authors: Langtangen, Hans Petter.

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Box Lysaker, Norway hpl simula. Department of Informatics University of Oslo P. Box Blindern Oslo, Norway http: This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or partsthereof is permitted onlyunder the provisionsof theGerman CopyrightLaw of September 9,in its current version, and permission for use must always be obtained from Springer.

Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. The major change between the second and third editions, however, is caused by the new implementation of Numerical Python, now called numpy.

Since Numerical Python functionality appears in a lot of places in the book, there are hence a huge number of updates to the new suggested numpy syntax, especially in Chapters 4, 9, and The second edition was based on Python version 2. Recent Python features, such as generator expressions Chapter 8.

Chapters 5 and 10 have been extended with new material. For example, F2PY and the Instant tool are very convenient for interfacing C code, and this topic is treated in detail in Chapters 5.

Installation of Python itself and the many add-on modules have become increasingly simpler over the years with setup. The py4cs package with software tools associated with this book has undergone a major revision and extension, and the package is now maintained under the name scitools and distributed separately.

The new scitools package is backward compatible with py4cs from the second edition. Several people has helped me with preparing the new edition. Ring, and Rolv E. Bredesen are highly appreciated. 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.

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I am greatful to everyone who has sent emails and contributed with improvements.

Python Scripting For Computational Science

Several parts of Chapter 4 on numerical computing have been extended especially Chapters 4. Many smaller changes have been implemented in Chapter 8; the larger ones concern exemplifying Tar archives instead of ZIP archives in Chapter 8. Revised and additional tips on optimizing Python code have been included in Chapter 8. To optimize Python code, we now also introduce the Psyco and Weave tools see Chapters 8.

To reduce complexity of the principal software example in Chapters 9 and 10, I have removed fot of string formulas. Instead, one can use the revised StringFunction tool from Chapter Numerous sections or paragraphs have been expanded, condensed, or removed. The sequence of chapters is hardly changed, but a couple of sections have been moved. The numbering of the exercises is altered as a result of both adding and removing exerises.

The primary purpose of this book is to help scientists and engineers working intensively with computers to become more productive, have more fun, and sciecne the reliability of their investigations.

Scripting in the Python programming language can be a key tool for reaching these goals [27,29].

Perl, Python, Ruby, Scheme, and Tcl are examples of languages supporting such high-level programming or scripting. So, although Matlab is perhaps the scripting language of choice in computational science today, my use of the term scripting goes beyond typical Matlab scripts. Python stands out as the language of choice for scripting in computational science because of its very clean syntax, rich modularization features, good support for numerical computing, and rapidly growing popularity.

What Scripting is About. The simplest application of scripting is to write short programs scripts that automate manual interaction with the computer. That is, scripts copmutational glue stand-alone applications and operating system commands. A primary example is automating simulation and visualization: In fact, the high-level programming style and tools used in scripts open up new possibilities you would hardly consider as a Fortran or C programmer.

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The interest in scripting with Python has exploded among Internet service developers and computer system administrators. With Python and the techniques explained in this book, you can actually create your own easy-to-use computational environment, which mirrors the working style of Matlab-like tools, but tailored to your own number crunching codes and favorite visualization systems. Special Features of This Book.

Instead, they want to get quickly started with examples from their own world of applications and learn the tools while using them. The present book is written in this spirit — we dive into simple yet useful examples and learn about syntax and programming techniques during dissection of the examples.

The idea is to get the reader started such that further development of the examples towards langtangeen applications can be done with the aid of online manuals or Python reference books.

Chapter 1 gives an introduction to what scripting is and what it can be good for in a computational science context. A quick introduction to scripting with Python, using examples of relevance to computational scientists and engineers, is provided in Chapter 2. A quick tutorial on building graphical user interfaces computxtional in Chapter 6, while Chapter 7 builds the same user interfaces as interactive Web pages.

Barth Michael Griebel David E. Apostila Dcripting Apostila sobre python.

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