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

The polynomial class


Let's now design a polynomial base class based on a monomial formulation of the polynomial. The polynomial can be initialized either by giving its coefficients with respect to the monomial basis or by giving a list of interpolation points, as follows:

import scipy.linalg as sl

class PolyNomial:
    base='monomial'
    def __init__(self,**args):
        if 'points' in args:
            self.points = array(args['points'])
            self.xi = self.points[:,0]
            self.coeff = self.point_2_coeff()
            self.degree = len(self.coeff)-1
        elif 'coeff' in args:
            self.coeff = array(args['coeff'])
            self.degree = len(self.coeff)-1
            self.points = self.coeff_2_point()
        else:
            self.points = array([[0,0]])
            self.xi = array([1.])
            self.coeff = self.point_2_coeff()
            self.degree = 0

The __init__...