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Scientific Computing with Python

Scientific Computing with Python

By : Führer, Claus Fuhrer, Solem, Verdier
4.5 (15)
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Scientific Computing with Python

Scientific Computing with Python

4.5 (15)
By: Führer, Claus Fuhrer, Solem, Verdier

Overview of this book

Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.
Table of Contents (23 chapters)
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20
About Packt
22
References
Classes

In mathematics, when we write , we refer to a mathematical object for which we know many methods from elementary calculus. For example:

  • We might want to evaluate at , that is, compute , which returns a real number.
  • We might want to compute its derivative, which gives us another mathematical object, cos.
  • We might want to compute the first three coefficients of its Taylor polynomial.

These methods may be applied not only to sin but also to other sufficiently smooth functions. There are, however, other mathematical objects, for example, the number 5, for which these methods would make no sense.

Objects that have the same methods are grouped together in abstract classes, for example, functions. Every statement and every method that can be applied to functions in general applies in particular to sin or cos.

Other examples for such classes might be a rational number...

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