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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

15.2.6 Float comparisons

Two floating-point numbers should not be compared with the == comparison, because the result of a computation is often slightly off due to rounding errors. There are numerous tools to test the equality of floats for testing purposes.

First, allclose checks that two arrays are almost equal. It can be used in a test function, as shown:

self.assertTrue(allclose(computed, expected))

Here, self refers to a unittest.Testcase instance. There are also testing tools in the numpy package testing. These are imported by using:

import numpy.testing

Testing that two scalars or two arrays are equal is done using numpy.testing.assert_array_allmost_equal or numpy.testing.assert_allclose. These methods differ in the way they describe the required accuracy, as shown in the preceding table, Table 15.1.

 factorization decomposes a given matrix into a product of an orthogonal matrix  and an upper triangular...

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