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Python Scripting for Computational Science

Python Scripting for Computational Science
Catalogue Information
Field name Details
Dewey Class 004
Title Python Scripting for Computational Science ([EBook] /) / by Hans Petter Langtangen.
Author Langtangen, Hans Petter
Other name(s) SpringerLink (Online service)
Publication Berlin, Heidelberg : : Springer Berlin Heidelberg : : Imprint: Springer, , 2004.
Physical Details XXII, 732 p. 446 illus. : online resource.
Series Texts in computational science and engineering 1611-0994 ; ; 3
ISBN 9783662054505
Summary Note The primary purpose of this book is to help scientists and engineers work­ ing intensively with computers to become more productive, have more fun, and increase the reliability of their investigations. Scripting in the Python programming language can be a key tool for reaching these goals [27,29]. The term scripting means different things to different people. By scripting I mean developing programs of an administering nature, mostly to organize your work, using languages where the abstraction level is higher and program­ ming is more convenient than in Fortran, C, C++, or Java. Perl, Python, Ruby, Scheme, and Tel are examples of languages supporting such high-level programming or scripting. To some extent Matlab and similar scientific com­ puting environments also fall into this category, but these environments are mainly used for computing and visualization with built-in tools, while script­ ing aims at gluing a range of different tools for computing, visualization, data analysis, file/directory management, user interfaces, and Internet communi­ cation. So, although Matlab is perhaps the scripting language of choiee in computational science today, my use of the term scripting goes beyond typi­ cal Matlab scripts. Python stands out as the language of choice for scripting in computational science because of its very elean syntax, rieh modulariza­ tion features, good support for numerical computing, and rapidly growing popularity. What Scripting is About.:
Contents note 1 Introduction -- 2 Getting Started with Python Scripting -- 3 Basic Python -- 4 Numerical Computing in Python -- 5 Combining Python with Fortran, C, and C++ -- 6 Introduction to GUI Programming -- 7 Web Interfaces and CGI Programming -- 8 Advanced Python -- 9 Fortran Programming with NumPy Arrays -- 10 C and C++ Programming with NumPy Arrays -- 11 More Advanced GUI Programming -- 12 Tools and Examples -- A Setting up the Required Software Environment -- A.1 Installation on Unix Systems -- A.1.1 A Suggested Directory Structure -- A.1.2 Setting Some Environment Variables -- A.1.3 Installing Tcl/Tk and Additional Modules -- A.1.4 Installing Python -- A.1.5 Installing Python Modules -- A.1.6 Installing Gnuplot -- A.1.7 Installing SWIG -- A.1.8 Summary of Environment Variables -- A.1.9 Testing the Installation of Scripting Utilities -- A.2 Installation on Windows Systems -- B Elements of Software Engineering -- B.1 Building and Using Modules -- B.1.1 Single-File Modules -- B.1.2 Multi-File Modules -- B.1.3 Debugging and Troubleshooting -- B.2 Tools for Documenting Python Software -- B.2.1 Doc Strings -- B.2.2 Tools for Automatic Documentation -- B.3 Coding Standards -- B.3.1 Style Guide -- B.3.2 Pythonic Programming -- B.4 Verification of Scripts -- B.4.1 Automating Regression Tests -- B.4.2 Implementing a Tool for Regression Tests -- B.4.3 Writing a Test Script -- B.4.4 Verifying Output from Numerical Computations -- B.4.5 Automatic Doc String Testing -- B.4.6 Unit Testing -- B.5 Version Control Management -- B.5.1 Getting Started with CVS -- B.5.2 Building Scripts to Simplify the Use of CVS -- B.6 Exercises.
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site http://dx.doi.org/10.1007/978-3-662-05450-5
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