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

Recursive functions


In mathematics, many functions are defined recursively. In this section, we will show how this concept can be used even when programming a function. This makes the relation of the program to its mathematical counterpart very clear, which may ease the readability of the program.

Nevertheless, we recommend that you use this programming technique with care, especially within scientific computing. In most applications, the more straightforward iterative approach is more efficient. This will become immediately clear from the following example.

Chebyshev polynomials are defined by a three-term recursion:

Such a recursion needs to be initialized, that is, T0(x) =1, T1(x) = x.

In Python, this three term recursion can be realized by the following function definition:

def chebyshev(n, x):
    if n == 0:
        return 1.
    elif n == 1:
        return x
    else:
        return 2. * x * chebyshev(n - 1, x) 
                      - chebyshev(n...