Python Scripting for Computational Science / by Hans Petter Langtangen.

Por:

Langtangen, Hans Petter [autor]

Colaborador(es):

SpringerLink (Servicio en línea)

Tipo de material: Texto

TextoSeries Texts in Computational Science and Engineering ; 3Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006Edición: Second EditionDescripción: xxiv, 736 páginas 62 ilustraciones recurso en líneaTipo de contenido:

texto

Tipo de medio:

computadora

Tipo de portador:

recurso en línea

ISBN:

9783540312697

Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:

QA71-90

Recursos en línea:

Conectar a Springer E-Books (Para consulta externa se requiere previa autentificaciÃ³n en Biblioteca Digital UANL)

Contenidos:

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.

Resumen: 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.

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Springer eBooks

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.

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