Book Image

Scientific Computing with Python - Second Edition

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python - Second Edition

By: Claus Führer, Jan Erik Solem, Olivier 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)
20
About Packt
22
References

8.4.1 Class attributes

Attributes specified in the class declaration are called class attributes. Consider the following example:

class Newton:
    tol = 1e-8 # this is a class attribute
    def __init__(self,f):
        self.f = f # this is not a class attribute
    ...

Class attributes are useful for simulating default values and can be used if values have to be reset:

N1 = Newton(f)
N2 = Newton(g)

Both instances have an attribute, tol, with the value initialized in the class definition:

N1.tol # 1e-8
N2.tol # 1e-8

Altering the class attribute automatically affects all the corresponding attributes of all instances:

Newton.tol = 1e-10
N1.tol # 1e-10
N2.tol # 1e-10

Altering tol for one instance does not affect the other instance:

N2.tol = 1.e-4
N1.tol  # still 1.e-10

But now, N2.tol is detached from the class attribute. Changing Newton.tol no longer has any effect on N2.tol:

Newton.tol = 1e-5 
# now all instances of the Newton classes have tol=1e-5 N1.tol # 1.e-5 N2.tol # 1.e-4
# N2.tol...