Book Image

Scientific Computing with Python 3

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

Scientific Computing with Python 3

By: Claus Führer, Jan Erik Solem, Olivier Verdier

Overview of this book

Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.
Table of Contents (23 chapters)
Scientific Computing with Python 3
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Acknowledgement
Preface
References

Attributes and methods


One of the main reasons for working with classes is that objects can be grouped together and bound to a common object. We saw this already when looking at rational numbers; denominator and numerator are two objects which we bound to an instance of the RationalNumber class. They are called attributes of the instance. The fact that an object is an attribute of a class instance becomes apparent from the way they are referenced, which we have used tacitly before:

<object>.attribute

Here are some examples of instantiation and attribute reference:

q = RationalNumber(3, 5) # instantiation
q.numerator     # attribute access
q.denominator

a = array([1, 2])    # instantiation
a.shape

z = 5 + 4j    # instantiation
z.imag

Once an instance is defined we can set, change or delete attributes of that particular instance. The syntax is the same as for regular variables:

q = RationalNumber(3, 5) 
r = RationalNumber(7, 3)
q.numerator...