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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 – calculating the Gaussian integral

The Gaussian integral is related to the error() function (also known in mathematics as erf), but has no finite limits. It evaluates to the square root of pi.

Time for action – calculating the Gaussian integral

Let's calculate the integral with the quad() function (for the imports check the file in the code bundle):

print("Gaussian integral", np.sqrt(np.pi),integrate.quad(lambda x: np.exp(-x**2), -np.inf, np.inf))

The return value is the outcome and its error would be as follows:

Gaussian integral 1.77245385091 (1.7724538509055159, 1.4202636780944923e-08)

What just happened?

We calculated the Gaussian integral with the quad() function.

Have a go hero – experiment a bit more

Try out other integration functions from the same package. It should just be a matter of replacing one function call. We should get the same outcome, so you may also want to read the documentation to learn more.

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