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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

16.4 Substitutions

Let's first consider a simple symbolic expression:

x, a = symbols('x a')
b = x + a

What happens if we set x = 0 ? We observe that b did not change. What we did was that we changed the Python variable x. It now no longer refers to the symbol object but to the integer object 0. The symbol represented by the string 'x' remains unaltered, and so does b.

Instead, altering an expression by replacing symbols with numbers, other symbols, or expressions is done by a special substitution method, which can be seen in the following code:

x, a = symbols('x a')
b = x + a
c = b.subs(x,0)
d = c.subs(a,2*a)
print(c, d) # returns (a, 2a)

This method takes one or two arguments. The following two statements are equivalent:

b.subs(x,0)
b.subs({x:0}) # a dictionary as argument

Dictionaries as arguments allow us to make several substitutions in one step:

b.subs({x:0, a:2*a})  # several substitutions...

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