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Scientific Computing with Python

You're reading from   Scientific Computing with Python High-performance scientific computing with NumPy, SciPy, and pandas

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Length 392 pages
Edition 2nd Edition
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Authors (4):
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Olivier Verdier Olivier Verdier
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Olivier Verdier
Jan Erik Solem Jan Erik Solem
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Jan Erik Solem
Claus Führer Claus Führer
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Claus Führer
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
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Table of Contents (23) Chapters Close

Preface 1. Getting Started 2. Variables and Basic Types FREE CHAPTER 3. Container Types 4. Linear Algebra - Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Series and Dataframes - Working with Pandas 11. Communication by a Graphical User Interface 12. Error and Exception Handling 13. Namespaces, Scopes, and Modules 14. Input and Output 15. Testing 16. Symbolic Computations - SymPy 17. Interacting with the Operating System 18. Python for Parallel Computing 19. Comprehensive Examples 20. About Packt 21. Other Books You May Enjoy 22. References

Methods mimicking function calls and iterables

Using a class instance together with parentheses or brackets, () or [], invokes a call to one of the special methods __call__ or __getitem__, giving the instance the behavior of a function or of an iterable; see also Table 8.1.

class Polynomial:
    ...
    def __call__(self, x):
        return self.eval(x)

Which now may be used as follows:

p = Polynomial(...)    # Creating a polynomial object
p(3.) # value of p at 3.

The special method __getitem__ makes sense if the class provides an iterator (it is recommended that you review Section 9.2.1: Generators before you consider the following example).

The recursion is called a three-term recursion. It plays an important role in applied mathematics, in particular in the construction of orthogonal polynomials. We can set up a three-term recursion as a class in the following way:

import itertools

class  Recursion3Term:
    def __init__(self, a0, a1, u0, u1):
        self.coeff = [a1, a0]
     ...
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