Learning Scientific Programming with Python

Hill, Christian

ISBN 10: 110742822X / ISBN 13: 9781107428225

Published by Cambridge University Press, 2016

About this Item

Gently used. May include previous owner's signature or bookplate on the front endpaper, sticker on back and/or remainder mark on text block.

Seller Inventory # 9781107428225-3

Bibliographic Details

• Title: Learning Scientific Programming with Python
• Publisher: Cambridge University Press
• Publication Date: 2016
• Language: English
• ISBN 10: 110742822X
• ISBN 13: 9781107428225
• Binding: Soft cover
• Condition: very good

About this title

Synopsis

Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students requiring a solid foundation in Python programming.

About the Author

Christian Hill is a physicist and physical chemist at University College London and the University of Oxford. He has over twenty years' experience of programming in the physical sciences and has been programming in Python for ten years. His research uses Python to produce, analyse, process, curate and visualise large data sets for the prediction of the properties of planetary atmospheres.