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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
Author Profile Icon Jan Erik Solem
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

9.3.4 Generators of recursive sequences

Assume that a sequence is given by an induction formula. For instance, consider the Fibonacci sequence, defined by the recurrence formula: 

.

This sequence depends on two initial values, namely  and , although for the standard Fibonacci sequence those numbers are taken as 0 and 1 respectively. A nifty way of programming the generation of such a sequence is by using generators, as follows:

def fibonacci(u0, u1):
    """
    Infinite generator of the Fibonacci sequence.
    """
    yield u0
    yield u1
    while True:
        u0, u1 = u1, u1 + u0  
# we shifted the elements and compute the new one yield u1

This may then be used, for instance, like this:

# sequence of the 100 first Fibonacci numbers:
list(itertools.islice(fibonacci(0, 1), 100))
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