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Scientific Computing with Python - Second Edition

You're reading from  Scientific Computing with Python - Second Edition

Product type Book
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Pages 392 pages
Edition 2nd 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

Preface Getting Started Variables and Basic Types Container Types Linear Algebra - Arrays Advanced Array Concepts Plotting Functions Classes Iterating Series and Dataframes - Working with Pandas Communication by a Graphical User Interface Error and Exception Handling Namespaces, Scopes, and Modules Input and Output Testing Symbolic Computations - SymPy Interacting with the Operating System Python for Parallel Computing Comprehensive Examples About Packt Other Books You May Enjoy References

5.2.2 Checking for array equality

Checking the equality of two float arrays is not straightforward, because two floats may be very close without being equal. In NumPy, it is possible to check for equality with allclose. This function checks for the equality of two arrays up to a given precision:

data = random.rand(2)*1e-3
small_error = random.rand(2)*1e-16
data == data + small_error # False
allclose(data, data + small_error, rtol=1.e-5, atol=1.e-8)   # True

The tolerance is given in terms of a relative tolerance bound, rtol, and an absolute error bound, atol. The command allclose is a short form of: 

(abs(A-B) < atol+rtol*abs(B)).all()

Note that allclose can be also applied to scalars:

data = 1e-3
error = 1e-16
data == data + error # False
allclose(data, data + error, rtol=1.e-5, atol=1.e-8)  #True
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