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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

When iterators behave as lists


Some list operations also work on iterators. We will now examine the equivalents of list comprehensions and list zipping (refer to section List of Chapter 3, Container Types, for more details).

Generator expression

There is an equivalent of list comprehension for generators. Such a construction is called a generator expression:

g = (n for n in range(1000) if not n % 100)
# generator for  100, 200, ... , 900

This is useful in particular for computing sums or products because those operations are incremental; they only need one element at a time:

sum(n for n in range(1000) if not n % 100) # returns 4500 

In that code, you notice that the sum function is given one argument, which is a generator expression. Note that Python syntax allows us to omit the enclosing parentheses of generators when a generator is used as the only argument of a function.

Let us compute the Riemann zeta function ζ, whose expression is

With a generator expression, we may compute a partial...

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