Python for Scientists
1st Edition
Published on 28. July 2014
235 pages
978-1-139-95067-1 (ISBN)
Description
Python is a free, open source, easy-to-use software tool that offers a significant alternative to proprietary packages such as MATLAB (R) and Mathematica (R). This book covers everything the working scientist needs to know to start using Python effectively. The author explains scientific Python from scratch, showing how easy it is to implement and test non-trivial mathematical algorithms and guiding the reader through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the program's capabilities. In particular, readers are shown how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. Instead of exercises the book contains useful snippets of tested code which the reader can adapt to handle problems in their own field, allowing students and researchers with little computer expertise to get up and running as soon as possible.
Reviews / Votes
'... the practitioner who wants to learn Python will love it. This is the type of book I have been looking for to learn Python ... concise, yet practical.' European Mathematical Society (euro-math-soc.eu)More details
Language
English
Place of publication
Cambridge
United Kingdom
Publishing group
Cambridge University Press
Target group
Professional and scholarly
College/higher education
Illustrations
12 Halftones, unspecified; 24 Line drawings, unspecified
File size
5309,74 MB
ISBN-13
978-1-139-95067-1 (9781139950671)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
John M. Stewart
Python for Scientists
Book
07/2014
Cambridge University Press
€39.60
Article exhausted; check for reprint
John M. Stewart
Python for Scientists
Book
07/2014
Cambridge University Press
€89.13
Article exhausted; check for reprint
Person
John M. Stewart is Emeritus Reader in Gravitational Physics at the University of Cambridge, and a Life Fellow at King's College, Cambridge.
Content
Preface; 1. Introduction; 2. Getting started with IPython; 3. A short Python tutorial; 4. Numpy; 5. Two-dimensional graphics; 6. Three-dimensional graphics; 7. Ordinary differential equations; 8. Partial differential equations: a pseudospectral approach; 9. Case study: multigrid; 10. Appendix A. Installing a Python environment; Appendix B. Fortran77 subroutines for pseudospectral methods; References; Index.
