Book Image

NumPy Beginner's Guide - Second Edition

By : Ivan Idris
Book Image

NumPy Beginner's Guide - Second Edition

By: Ivan Idris

Overview of this book

NumPy is an extension to, and the fundamental package for scientific computing with Python. In today's world of science and technology, it is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy Beginner's Guide will teach you about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, is free and open source. Write readable, efficient, and fast code, which is as close to the language of mathematics as is currently possible with the cutting edge open source NumPy software library. Learn all the ins and outs of NumPy that requires you to know basic Python only. Save thousands of dollars on expensive software, while keeping all the flexibility and power of your favourite programming language.You will learn about installing and using NumPy and related concepts. At the end of the book we will explore some related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. Through examples, you will also learn about plotting with Matplotlib and the related SciPy project. NumPy Beginner's Guide will help you be productive with NumPy and have you writing clean and fast code in no time at all.
Table of Contents (19 chapters)
Numpy Beginner's Guide Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Time for action – writing a unit test


We will write tests for a simple factorial function. The tests will check for the so called happy path and for abnormal conditions.

  1. We start by writing the factorial function

    def factorial(n):
      if n == 0:
        return 1
    
      if n < 0:
        raise ValueError, "Unexpected negative value"
    
      return np.arange(1, n+1).cumprod()

    The code is using the arange and cumprod functions we have already seen to create arrays and calculate the cumulative product, but we added a few checks for boundary conditions.

  2. Now we will write the unit test. Let's write a class that will contain the unit tests. It extends the TestCase class from the unittest module which is part of standard Python. We test for calling the factorial function with:

    • a positive number, the happy path

    • boundary condition 0

    • negative numbers, which should result in an error

      class FactorialTest(unittest.TestCase):
        def test_factorial(self):
          #Test for the factorial of 3 that should pass.
          self.assertEqual(6...