Python Scripting for Computational Science
(Sprache: Englisch)
The goal of this book is to demonstrate how to develop tailored, flexible working environments built from small programs (scripts) written in the easy-to-learn, high-level language Python. The focus is on applications relevant to computational scientists.
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The goal of this book is to demonstrate how to develop tailored, flexible working environments built from small programs (scripts) written in the easy-to-learn, high-level language Python. The focus is on applications relevant to computational scientists.
Klappentext zu „Python Scripting for Computational Science “
With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.
The goal of this book is to teach computational scientists how to develop tailored, flexible, and human-efficient working environments built from small programs (scripts) written in the easy-to-learn, high-level language Python. The focus is on examples and applications of relevance to computational scientists: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping old programs with graphical user interfaces; making computational Web applications; and creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran. In short, scripting with Python makes you much more productive, increases the reliability of your scientific work and lets you have more fun - on Unix, Windows and Macintosh. All the tools and examples in this book are open source codes. The third edition is compatible with the new NumPy implementation and features updated information, correction of errors, and improved associated software tools.
Inhaltsverzeichnis zu „Python Scripting for Computational Science “
- 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 NumPy Arrays
- C and C++ Programming with NumPy Arrays
- More Advanced GUI Programming
- Tools and Examples
Autoren-Porträt von Hans Petter Langtangen
Prof. H. Petter Langtangen is the director of Center for Biomedical Computing, a Norwegian Center of Excellence at Simula Research Laboratory, and a professor of computer science at the University of Oslo. His research concerns numerical methods and software tools for continuum mechanical problems. Langtangen has been an active developer of open source and commercial software systems for computational sciences. He is a member of the European Academy of Sciences and serves on the editorial board of five leading international journals. Bibliographische Angaben
- Autor: Hans Petter Langtangen
- 2009, 3rd ed. Corr. 2nd printing., 756 Seiten, 62 Abbildungen, Maße: 16 x 24,1 cm, Gebunden, Englisch
- Verlag: Springer
- ISBN-10: 3540739157
- ISBN-13: 9783540739159
Sprache:
Englisch
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