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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

General mechanism

We have seen how to add a function and a scalar and how to build a function of two variables from two functions of one variable. Let's now focus on the general mechanism that makes this possible. The general mechanism consists of two steps: reshaping and extending.

First, the function  is reshaped to the function , which takes two arguments. One of these arguments is a dummy argument, which we take to be zero, as a convention:

Mathematically, the domain of the definition of is now  Then the function  is reshaped in a way similar to:

Now both and  take two arguments, although one of them is always zero. We proceed to the next step, extending. It is the same step that converted a constant into a constant function.

The function  is extended to:

 

The function  is extended to:

Now the function of two variables, , which was sloppily defined by , may be defined without reference to its arguments:

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