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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

Anonymous functions - the  lambda keyword


The keyword lambda is used in Python to define anonymous functions, that is; functions without a name and described by a single expression. You might just want to perform an operation on a function that can be expressed by a simple expression without naming this function and without defining this function by a lengthy def block.

Note

The name lambda originates from a special branch of calculus and mathematical logic, the -calculus.

For instance, to compute the following expression, we may use SciPy’s function quad, which requires the function to be integrated as its first argument and the integration bounds as the next two arguments:

Here, the function to integrate is just a simple one-liner and we use the lambda keyword to define it:

import scipy.integrate as si
si.quad(lambda x: x ** 2 + 5, 0, 1)

The syntax is as follows:

lambda parameter_list: expression

The definition of the lambda function can only consist of a single expression and in particular...

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