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Fuhrer Claus - Scientific computing with Python 3 an example-rich, comprehensive guide for all of your Python computational needs

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Fuhrer Claus Scientific computing with Python 3 an example-rich, comprehensive guide for all of your Python computational needs
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An example-rich, comprehensive guide for all of your Python computational needs About This Book Your ultimate resource for getting up and running with Python numerical computations Explore numerical computing and mathematical libraries using Python 3.x code with SciPy and NumPy modules A hands-on guide to implementing mathematics with Python, with complete coverage of all the key concepts Who This Book Is For This book is for anyone who wants to perform numerical and mathematical computations in Python. It is especially useful for developers, students, and anyone who wants to use Python for computation. Readers are expected to possess basic a knowledge of scientific computing and mathematics, but no prior experience with Python is needed. What You Will Learn The principal syntactical elements of Python The most important and basic types in Python The essential building blocks of computational mathematics, linear algebra, and related Python objects Plot in Python using matplotlib to create high quality figures and graphics to draw and visualize your results Define and use functions and learn to treat them as objects How and when to correctly apply object-oriented programming for scientific computing in Python Handle exceptions, which are an important part of writing reliable and usable code Two aspects of testing for scientific programming: Manual and Automatic In Detail Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more. Style and approach This book takes a concept-based approach to the language rather than a systematic introduction. It is a complete Python tutorial and introduces computing principles, using practical examples to and showing you how to correctly implement them in Python. Youll learn to focus on high-level design as well as the intricate details of Python syntax. Rather than providing canned problems to be solved, the exercises have been designed to inspire you to think about your own code and give you real-world insight.

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Scientific Computing with Python 3

Scientific Computing with Python 3

Copyright 2016 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: December 2016

Production reference: 1141216

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-78646-351-7

www.packtpub.com

Credits

Authors

Claus Fhrer

Jan Erik Solem

Olivier Verdier

Copy Editor

Vikrant Phadkay

Sneha Singh

Reviewers

Helmut Podhaisky

Project Coordinator

Nidhi Joshi

Commissioning Editor

Veena Pagare

Proofreader

Safis Editing

Acquisition Editor

Sonali Vernekar

Indexer

Mariammal Chettiyar

Content Development Editor

Aishwarya Pandere

Graphics

Disha Haria

Technical Editor

Karan Thakkar

Production Coordinator

Arvindkumar Gupta

About the Authors

Claus Fhrer is a professor of scientific computations at Lund University, Sweden. He has an extensive teaching record that includes intensive programming courses in numerical analysis and engineering mathematics across various levels in many different countries and teaching environments. Claus also develops numerical software in research collaboration with industry and received Lund Universitys Faculty of Engineering Best Teacher Award in 2016.

Jan Erik Solem is a Python enthusiast, former associate professor, and currently the CEO of Mapillary, a street imagery computer vision company. He has previously worked as a face recognition expert, founder and CTO of Polar Rose, and computer vision team leader at Apple. Jan is a World Economic Forum technology pioneer and won the Best Nordic Thesis Award 2005-2006 for his dissertation on image analysis and pattern recognition. He is also the author of "Programming Computer Vision with Python" (O'Reilly 2012).

Olivier Verdier began using Python for scientific computing back in 2007 and received a PhD in mathematics from Lund University in 2009. He has held post-doctoral positions in Cologne, Trondheim, Bergen, and Ume and is now an associate professor of mathematics at Bergen University College, Norway.

About the Reviewer

Helmut Podhaisky works in the Institute of Mathematics at the Martin Luther University in Halle-Wittenberg, where he teaches mathematics and scientific computing. He has co-authored a book on numerical methods for ordinary differential equations as well as several research papers on numerical methods. For work and fun, he uses Python, Fortran, Octave, Mathematica, and Haskell.

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Acknowledgement

We want to acknowledge the competent and helpful comments and suggestions by Helmut Podhaisky, Halle University, Germany. To have such a partner in the process of writing a book is a big luck and chance for the authors.

We would also like to express our gratitude towards the reviewers of the first edition of this book, , Linda Kann, KTH Stockholm, Hans Petter Langtangen, Simula Research Laboratory, and Alf Inge Wang, NTNU Trondheim.

A book has to be tested in teaching. And here we had fantastic partners: the teaching assistants from the course "Berkningsprogramering med Python" during the years and the colleagues involved in teaching: Najmeh Abiri, Christian Andersson, Dara Maghdid, Peter Meisrimel, Fatemeh Mohammadi, Azahar Monge, Anna-Maria Persson, Alexandros Sopasakis, Tony Stillfjord, Lund University. Najmeh Abiri also tested most of the Jupyter notebook material which you find on the book's webpage.

A book has not only to be written, it has to be published, and in this process Aishwarya Pandere and Karan Thakkar, PACKT Publishing, were always constructive, friendly and helpful partners bridging different time zones and different text processing tools. Thanks.

Claus Fhrer, Jan-Erik Solem, Olivier Verdier Lund, Bergen 2016

Preface

Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.

What this book covers

, Getting Started, addresses the main language elements of Python without going into detail. Here we make a brief tour through all. It is a good starting point for those who want to start directly. It is a quick reference for those readers who want in a later chapter understand an example which uses might use constructs like functions before functions were explained in deep .

, Variables and Basic Types , presents the most important and basic types in Python. Float is the more important datatype in scientific computing together with the special numbers nan and inf. Booleans, integers, complex, and strings are other basic datatypes, which will be used throughout this book.

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