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Numpy Beginner's Guide (Update)

You're reading from   Numpy Beginner's Guide (Update) Build efficient, high-speed programs using the high-performance NumPy mathematical library

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781785281969
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. NumPy Quick Start FREE CHAPTER 2. Beginning with NumPy Fundamentals 3. Getting Familiar with Commonly Used Functions 4. Convenience Functions for Your Convenience 5. Working with Matrices and ufuncs 6. Moving Further with NumPy Modules 7. Peeking into Special Routines 8. Assuring Quality with Testing 9. Plotting with matplotlib 10. When NumPy Is Not Enough – SciPy and Beyond 11. Playing with Pygame A. Pop Quiz Answers B. Additional Online Resources C. NumPy Functions' References
Index

Time for action – executing doctests

Let's write a simple example that is supposed to calculate the well-known factorial, but doesn't cover all of the possible boundary conditions. In other words, some tests will fail.

  1. The docstring will look like text you would see in a Python shell (including a prompt). Rig one of the tests to fail, just to see what will happen:
    """
    Test for the factorial of 3 that should pass.
    >>> factorial(3)
    6
    Test for the factorial of 0 that should fail.
    >>> factorial(0)
    1
    """
    
  2. Write the following line of NumPy code:
    return np.arange(1, n+1).cumprod()[-1]

    We want this code to fail from time to time for demonstration purposes.

  3. Run the doctest by calling the rundocs() function of the numpy.testing module, for instance, in the Python shell:
    >>> from numpy.testing import rundocs
    >>> rundocs('docstringtest.py')
    Traceback (most recent call last):
      File "<stdin>", line...
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