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Blanco-Silva Francisco - Learning SciPy for Numerical and Scientific Computing

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Blanco-Silva Francisco Learning SciPy for Numerical and Scientific Computing

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Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy In Detail SciPy is an open source Python library used to perform scientific computing. The SciPy (Scientific Python) package extends the functionality of NumPy with a substantial collection of useful algorithms. The book starts with a brief description of the SciPy libraries, followed by a chapter that is a fun and fast-paced primer on array creation, manipulation, and problem-solving. You will also learn how to use SciPy in linear algebra, which includes topics such as computation of eigenvalues and eigenvectors. Furthermore, the book is based on interesting subjects such as definition and manipulation of functions, computation of derivatives, integration, interpolation, and regression. You will also learn how to use SciPy in signal processing and how applications of SciPy can be used to collect, organize, analyze, and interpret data. By the end of the book, you will have fast, accurate, and easy-to-code solutions for numerical and scientific computing applications. What You Will Learn Get to know the benefits of using the combination of Python, NumPy, SciPy, and matplotlib as a programming environment for scientific purposes Create and manipulate an object array used by SciPy Use SciPy with large matrices to compute eigenvalues and eigenvectors Focus on construction, acquisition, quality improvement, compression, and feature extraction of signals Make use of SciPy to collect, organize, analyze, and interpret data, with examples taken from statistics and clustering Acquire the skill of constructing a triangulation of points, convex hulls, Voronoi diagrams, and many similar applications Find out ways that SciPy can be used with other languages such as C/C++, Fortran, and MATLAB/Octave Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

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Learning SciPy for Numerical and Scientific Computing Second Edition

Learning SciPy for Numerical and Scientific Computing Second Edition

Copyright 2015 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: February 2013

Second edition: February 2015

Production reference: 1200215

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78398-770-2

www.packtpub.com

Credits

Authors

Sergio J. Rojas G.

Erik A Christensen

Francisco J. Blanco-Silva

Reviewers

Dr. Robert Clewley

Nicolas Fauchereau

Valentin Haenel

Andy Ray Terrel

Commissioning Editor

Kartikey Pandey

Acquisition Editors

Kartikey Pandey

Meeta Rajani

Content Development Editor

Shweta Pant

Technical Editor

Rahul C. Shah

Copy Editors

Roshni Banerjee

Puja Lalwani

Merilyn Pereira

Project Coordinator

Shipra Chawhan

Proofreaders

Paul Hindle

Clyde Jenkins

Indexers

Monica Ajmera Mehta

Priya Sane

Graphics

Sheetal Aute

Valentina D'silva

Abhinash Sahu

Production Coordinator

Nitesh Thakur

Cover Work

Nitesh Thakur

About the Authors

Sergio J. Rojas G. is currently a full professor of physics at Universidad Simn Bolvar, Venezuela. Regarding his formal studies, in 1991, he earned a BS in physics with his thesis on numerical relativity from the Universidad de Oriente, Estado Sucre, Venezuela, and then, in 1998, he earned a PhD in physics from the Department of Physics at City College of the City University of New York, where he worked on the applications of fluid dynamics in the flow of fluids in porous media, gaining and developing since then a vast experience in programming as an aid to scientific research via Fortran77/90 and C/C++. In 2001, he also earned a master's degree in computational finance from the Oregon Graduate Institute of Science and Technology.

Sergio's teaching activities involve lecturing undergraduate and graduate physics courses at his home university, Universidad Simn Bolvar, Venezuela, including a course on Monte Carlo methods and another on computational finance. His research interests include physics education research, fluid flow in porous media, and the application of the theory of complex systems and statistical mechanics in financial engineering. More recently, Sergio has been involved in machine learning and its applications in science and engineering via the Python programming language.

I am deeply grateful to my mother, Eufemia del Valle Rojas Gonzlez, a beloved woman whose given steps were always in favor of showing and upraising the best of a human being.

Erik A Christensen is a quant analyst/developer in finance and creative industries. He has a PhD from the Technical University of Denmark, with postdoctoral studies at the Levich Institute at the City College of the City University of New York and the Courant Institute of Mathematical Sciences at New York University. His interests in technology span from Python to F# and Cassandra/Spark. He is active in the meet-up communities in London!

I would like to thank my family and friends for their support during this work!

Francisco J. Blanco-Silva is the owner of a scientific consulting companyTizona Scientific Solutionsand adjunct faculty in the Department of Mathematics of the University of South Carolina. He obtained his formal training as an applied mathematician at Purdue University. He enjoys problem solving, learning, and teaching. Being an avid programmer and blogger, when it comes to writing, he relishes finding that common denominator among his passions and skills and making it available to everyone. He coauthored Modeling Nanoscale Imaging in Electron Microscopy , Springer along with Peter Binev, Wolfgang Dahmen, and Thomas Vogt.

About the Reviewers

Dr. Robert Clewley is a polymath scientist and educator. He has been a faculty member at Georgia State University, Atlanta, GA. He specializes in computational and mathematical modeling methods for complex adaptive systems and has published a diverse range of academic journals involving applications in epilepsy, cancer, cardiology, and biomechanics. His research has been supported by federal grants from NSF and the Army Research Laboratory. From the high school level to graduate degree level, he has developed and taught a variety of courses spanning mathematics, computer science, physics, biological sciences, and philosophy of science. Dr. Clewley also develops the open source PyDSTool modeling software that is used internationally in many scientific and engineering fields.

Nicolas Fauchereau is a climate scientist at the National Institute for Water and Atmospheric Research (NIWA Ltd.) based in Auckland, New Zealand.

After obtaining his PhD in France in 2004, he spent 7 years in South Africa working at the University of Cape Town and then at the Council for Scientific and Industrial Research, before joining NIWA in 2012.

He uses statistics, data mining, and machine learning to try and make sense of climate and environmental data and to develop solutions to help people anticipate and adapt to climate variability and change.

He's been using the Python scientific stack for about 10 years and is a passionate advocate for the use of Python in environmental and earth sciences.

A water sports enthusiast, he likes to spend his free time either surfing, kite surfing, or sailing with his wife and two kids.

Valentin Haenel is a software engineer interested in the architectures of high-performance number crunching with Python. Specifically, he is interested in low-level aspects such as interfacing Python with C code, strategies for efficient memory allocation, avoiding redundant memory copies, and exploiting the memory hierarchy for accelerated computation. He spends some of his spare time working on Blosc (http://blosc.org), an extremely fast and multi threaded meta-codec. Occasionally, he flirts with machine learning.

In the past, he had worked on psychophysics data analysis, large-scale brain simulations, analytical engines for business intelligence, and large-scale data-center monitoring. He wrote a book about using the Git version control system and has contributed to a diverse selection of over 50 open source projects. He currently resides in Berlin and works as a freelance software engineer, consultant, and trainer.

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