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

Bound and unbound methods


We will now take a closer look at attributes that are methods. Let us consider an example:

class A:
    def func(self,arg):
        pass

A little inspection shows us how the nature of func changes after creating an instance:

A.func  # <unbound method A.func>
instA = A()  # we create an instance
instA.func  #  <bound method A.func of ... >

Calling, for example,  A.func(3) would result in an error message such as this:

TypeError: func() missing 1 required positional argument: 'arg'

instA.func(3) is executed as expected. Upon creation of an instance, the func method is bound to the instance. The self argument gets the instance assigned as its value. Binding a method to an instance makes the method usable as a function. Before that, it is of no use. Class methods, which we will consider later, are different in this aspect.