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.
Editors Timothy J. Barth Michael Griebel David E. Keyes Risto M. Nieminen Dirk Roose Tamar Schlick Are Magnus Bruaset Aslak Tveito (Eds.) Numerical Solution of Partial Differential Equations on Parallel Computers With 201 Figures and 42 Tables ABC Editors Are Magnus Bruaset Aslak Tveito Simula Research Laboratory P.O. Box 134 1325 Lysaker, Fornebu, Norway email:
[email protected] [email protected] The second editor of this book has received financial support from the NFF – Norsk faglitterær forfatter- og oversetterforening