The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.
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Review
From the reviews:
“This book is an introduction to computer programming using the Python programming language. It focuses on numerical methods as the context for examples, exercises, and assignments. … Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. … Summing Up: Highly recommended. Upper-division undergraduates through professionals; general readers.” (F. H. Wild III, Choice, Vol. 47 (8), April, 2010)
“It is an authoritative and almost monumental work that covers most aspects of the Python language and its numerical modules. It definitely has a prominent place on my bookshelf. … The text is well written … . In summary, this is the book (the only book) to have if you are an aspiring Python programmer of scientific applications.” (Jaan Kiusalaas, SIAM Review, Vol. 52 (3), September, 2010)
“The book’s title reflects its content accurately, the content is substantively scientific and the book is a very good programming book. … This excellent book is quite rich mathematically, numerical methods, differential equations, treatments of shape, and a variety of exercises and projects are included. It will also impart a deep knowledge of python, one of today’s most useful languages. I have learned a great deal from this book and recommend it highly.” (George Hacken, ACM Computing Reviews, September, 2010)
About the Author
Hans Petter Langtangen is a professor of computer science at the University of Oslo. He has formely been a professor of mechanics and is now the director of a Norwegian Center of Excellence: "Center for Biomedical Computing", at Simula Research Laboratory. Langtangen has published over 100 scientific publications and written several books, including papers and a book on Python's potential for scientific computing. He has also developed open source and commercial software systems for computational sciences.
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Customer Reviews
a solid introduction for using Python in scientific applications. The
main application areas covered are calculating the value of functions,
both built in and user supplied, plotting data, finding the roots of
equations, difference equations, numerical differentiation, numerical
integration and the solution to differential equations by numerical
methods.
Along the way you will learn how to use lists, tuples, dictionaries,
loops, list comprehension, lambda functions, Numpy arrays, file I/O
and Python Classes for programming scientific applications. Two
main highlights of the book are the thorough explanations the author
provides on how to use most of the features of Python and the copious
number of examples with answers. Other features are an example on how
to extract data from a Web Page and scitools. Scitools provides a
Matlab type of interface to gnuplot. About the only thing missing is
a summary on how to install Numpy, Scipy, Scitools, gunplot, and
gnuplot.py.
one hand, this makes the author to explain things absolutely obvious, clearly
oriented to students in the first years of their technical degree. On the
other hand, some of these explanations become handy if you have to teach this
material or even, sometimes, to learn the origins of something that you have
accepted as obvious without knowing exactly why is so. This is particularly
relevant in those parts dealing with mathematics (many in the book). The book
probably is of no use for an expert on SciPy/Numpy, but it is definitely useful for
people, like me, that is starting to discover the enormous capabilities of
these python language extensions. I clearly recommend this book for such
target users. The book is also excellently well written, with a clear and
concise style. Errors seem to be absent from the text and exercises are very
well targeted to the area of scientific computation.
Note that the emphasis is on teaching Python rather than numerical methods. If your main focus is to learn techniques for scientific computing then you should look for a different book.
Python is a good language for learning to use object-oriented programming (OOP) and this book will make that easy. On the other hand, the author didn't quite convince me that this approach is useful for scientific programming (but OOP is clearly quite useful elsewhere).
Overall I found the book very helpful - highly recommended.
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