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  • Book Overview & Buying Scientific Computing with Python 3
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Scientific Computing with Python 3

Scientific Computing with Python 3

By : Claus Führer, Claus Fuhrer, Jan Erik Solem, Olivier Verdier
4 (2)
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Scientific Computing with Python 3

Scientific Computing with Python 3

4 (2)
By: Claus Führer, Claus Fuhrer, 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 (17 chapters)
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16
References

Using unittest package

The standard unittest Python package greatly facilitates automated testing. This package requires that we rewrite our tests to be compatible. The first test would have to be rewritten in a class, as follows:

from bisection import bisect
import unittest

class TestIdentity(unittest.TestCase):
    def test(self):
        result = bisect(lambda x: x, -1.2, 1.,tol=1.e-8)
        expected = 0.
        self.assertAlmostEqual(result, expected)

if __name__=='__main__':
    unittest.main()

Let's examine the differences to the previous implementation. First, the test is now a method and a part of a class. The class must inherit from unittest.TestCase. The test method's name must start with test. Note that we may now use one of the assertion tools of the unittest package, namely assertAlmostEqual. Finally, the tests are run using unittest.main. We recommend to write the tests in a file separate from the code to be tested. That is why it starts with...

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