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, dataanalysis, 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. Shows how to develop tailored, flexible, and human-efficient working environments using the easy-to-learn, high-level Python language Focuses on examples and applications ofpractical use to computational scientists Compatible with the new NumPy implementation and features updated information, correction of errors, and improvedassociated software tools All the tools and examples in the book are open source codes
- ISBN: 978-3-540-73915-9
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 756
- Fecha Publicación: 01/01/2009
- Nº Volúmenes: 1
- Idioma: Inglés