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  • Book Overview & Buying Scientific Computing with Python 3
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Scientific Computing with Python 3

Scientific Computing with Python 3

By : Claus Führer, Claus Fuhrer, Olivier Verdier, Jan Erik Solem
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Scientific Computing with Python 3

Scientific Computing with Python 3

4 (2)
By: Claus Führer, Claus Fuhrer, Olivier Verdier, Jan Erik Solem

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 (17 chapters)
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16
References

Encapsulation


Sometimes the use of inheritance is impractical or even impossible. This motivates the use of encapsulation. We will explain the concept of encapsulation by considering Python functions, that is, objects of the Python type function, which we encapsulate in a new class, Function, and provide with some relevant methods:

class Function:
    def __init__(self, f):
        self.f = f
    def __call__(self, x):
        return self.f(x)
    def __add__(self, g):
        def sum(x):
            return self(x) + g(x)
        return type(self)(sum) 
    def __mul__(self, g): 
        def prod(x):
            return self.f(x) * g(x)
        return type(self)(prod)
    def __radd__(self, g):
        return self + g
    def __rmul__(self, g):
        return self * g

Note that the __add__ and __mul__ operations should return an instance of the same class. This is achieved by the return type(self)(sum) statement...

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