ISBN-10:
110742822X
ISBN-13:
9781107428225
Pub. Date:
02/04/2016
Publisher:
Cambridge University Press
Learning Scientific Programming with Python

Learning Scientific Programming with Python

by Christian Hill

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Overview

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.

Product Details

ISBN-13: 9781107428225
Publisher: Cambridge University Press
Publication date: 02/04/2016
Edition description: New Edition
Pages: 458
Sales rank: 1,038,770
Product dimensions: 6.85(w) x 9.72(h) x 0.87(d)

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.

Table of Contents

1. Introduction; 2. The core Python language I; 3. Interlude: simple plotting with pylab; 4. The core Python language II; 5. IPython and IPython notebook; 6. NumPy; 7. Matplotlib; 8. SciPy; 9. General scientific programming; Appendix A. Solutions; Index.

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