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Scientific Computing with Python 3

You're reading from   Scientific Computing with Python 3 An example-rich, comprehensive guide for all of your Python computational needs

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Product type Paperback
Published in Dec 2016
Publisher Packt
ISBN-13 9781786463517
Length 332 pages
Edition 1st Edition
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Authors (4):
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Jan Erik Solem Jan Erik Solem
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Jan Erik Solem
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
Olivier Verdier Olivier Verdier
Author Profile Icon Olivier Verdier
Olivier Verdier
Claus Führer Claus Führer
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Claus Führer
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Table of Contents (17) Chapters Close

Preface 1. Getting Started FREE CHAPTER 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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