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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

By : Ivan Idris
2 (1)
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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

2 (1)
By: Ivan Idris

Overview of this book

This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.
Table of Contents (16 chapters)
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14
C. NumPy Functions' References
15
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 abnormal conditions.

  1. Start by writing the factorial function:
    import numpy as np
    import unittest
    
    
    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 uses the arange() and cumprod() functions 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. Test for calling the factorial function with the following three attributes:
    • 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):
        ...

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