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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

Comparing arrays


Comparing two arrays is not as simple as it may seem. Consider the following code, which is intended to check whether two matrices are close to each other:

A = array([0.,0.])
B = array([0.,0.])
if abs(B-A) < 1e-10: # an exception is raised here
    print("The two arrays are close enough")

This code raises the exception when the if statement is executed:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

In this section, we explain why this is so and how to remedy this state of affairs.

Boolean arrays

Boolean arrays are useful for advanced array indexing (refer to section Indexing with Boolean arrays). A Boolean array is simply an array for which the entries have the type bool:

A = array([True,False]) # Boolean array
A.dtype # dtype('bool')

Any comparison operator acting on arrays will create a Boolean array instead of a simple Boolean:

M = array([[2, 3],
           [1, 4]])
M > 2 # array([[False...
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