Book Image

Scientific Computing with Python 3

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python 3

By: Claus Führer, Jan Erik Solem, Olivier Verdier

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 (23 chapters)
Scientific Computing with Python 3
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Acknowledgement
Preface
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...