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

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...