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This book is published open access under a CC BY 4.0 license. This
book presents computer programming as a key method for solving
mathematical problems. This second edition of the well-received
book has been extensively revised: All code is now written in
Python version 3.6 (no longer version 2.7). In addition, the two
first chapters of the previous edition have been extended and split
up into five new chapters, thus expanding the introduction to
programming from 50 to 150 pages. Throughout the book, the
explanations provided are now more detailed, previous examples have
been modified, and new sections, examples and exercises have been
added. Also, a number of small errors have been corrected. The book
was inspired by the Springer book TCSE 6: A Primer on Scientific
Programming with Python (by Langtangen), but the style employed is
more accessible and concise, in keeping with the needs of
engineering students. The book outlines the shortest possible path
from no previous experience with programming to a set of skills
that allows students to write simple programs for solving common
mathematical problems with numerical methods in the context of
engineering and science courses. The emphasis is on generic
algorithms, clean program design, the use of functions, and
automatic tests for verification.
This book is open access under a CC BY 4.0 license. This
easy-to-read book introduces the basics of solving partial
differential equations by means of finite difference methods.
Unlike many of the traditional academic works on the topic, this
book was written for practitioners. Accordingly, it especially
addresses: the construction of finite difference schemes,
formulation and implementation of algorithms, verification of
implementations, analyses of physical behavior as implied by the
numerical solutions, and how to apply the methods and software to
solve problems in the fields of physics and biology.
This book presents computer programming as a key method for solving
mathematical problems. There are two versions of the book, one for
MATLAB and one for Python. The book was inspired by the Springer
book TCSE 6: A Primer on Scientific Programming with Python (by
Langtangen), but the style is more accessible and concise, in
keeping with the needs of engineering students. The book outlines
the shortest possible path from no previous experience with
programming to a set of skills that allows the students to write
simple programs for solving common mathematical problems with
numerical methods in engineering and science courses. The emphasis
is on generic algorithms, clean design of programs, use of
functions, and automatic tests for verification.
This book is open access under a CC BY 4.0 license. This
easy-to-read book introduces the basics of solving partial
differential equations by means of finite difference methods.
Unlike many of the traditional academic works on the topic, this
book was written for practitioners. Accordingly, it especially
addresses: the construction of finite difference schemes,
formulation and implementation of algorithms, verification of
implementations, analyses of physical behavior as implied by the
numerical solutions, and how to apply the methods and software to
solve problems in the fields of physics and biology.
This book presents computer programming as a key method for solving
mathematical problems. There are two versions of the book, one for
MATLAB and one for Python. The book was inspired by the Springer
book TCSE 6: A Primer on Scientific Programming with Python (by
Langtangen), but the style is more accessible and concise, in
keeping with the needs of engineering students. The book outlines
the shortest possible path from no previous experience with
programming to a set of skills that allows the students to write
simple programs for solving common mathematical problems with
numerical methods in engineering and science courses. The emphasis
is on generic algorithms, clean design of programs, use of
functions, and automatic tests for verification.
This book presents computer programming as a key method for solving
mathematical problems. There are two versions of the book, one for
MATLAB and one for Python. The book was inspired by the Springer
book TCSE 6: A Primer on Scientific Programming with Python (by
Langtangen), but the style is more accessible and concise, in
keeping with the needs of engineering students. The book outlines
the shortest possible path from no previous experience with
programming to a set of skills that allows the students to write
simple programs for solving common mathematical problems with
numerical methods in engineering and science courses. The emphasis
is on generic algorithms, clean design of programs, use of
functions, and automatic tests for verification.
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