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Scientific Computing with Python 3

You're reading from  Scientific Computing with Python 3

Product type Book
Published in Dec 2016
Publisher Packt
ISBN-13 9781786463517
Pages 332 pages
Edition 1st Edition
Languages
Authors (3):
Claus Führer Claus Führer
Profile icon Claus Führer
Jan Erik Solem Jan Erik Solem
Olivier Verdier Olivier Verdier
View More author details

Table of Contents (23) Chapters

Scientific Computing with Python 3
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Acknowledgement
Preface
1. Getting Started 2. Variables and Basic Types 3. Container Types 4. Linear Algebra – Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Error Handling 11. Namespaces, Scopes, and Modules 12. Input and Output 13. Testing 14. Comprehensive Examples 15. Symbolic Computations - SymPy References

Iterator objects


As we mentioned earlier, a for loop only needs an iterable object. Lists, in particular, are iterable. This means that a list is able to create an iterator from its contents. In fact, this is true for any object (not only lists): any object may be made iterable.

This is achieved via the __iter__ method, which should return an iterator. Here we give an example where the __iter__ method is a generator:

class OdeStore:
    """
    Class to store results of ode computations
    """
    def __init__(self, data):
        "data is a list of the form [[t0, u0], [t1, u1],...]"
        self.data = data
    
    def __iter__(self):
        "By default, we iterate on the values u0, u1,..."
        for t, u in self.data:
            yield u

store = OdeStore([[0, 1], [0.1, 1.1], [0.2, 1.3]])
for u in store:
    print(u)
# result: 1, 1.1, 1.3
list(store) # [1, 1.1, 1.3]

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