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A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering) ReviewDon't be fooled by the title or the first chapter, this book providesa 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.A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering) Overview
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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