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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 – plotting the sinc function

We will plot the sinc() function:

  1. Compute evenly spaced values with the NumPy linspace() function:
    x = np.linspace(0, 4, 100)
  2. Call the NumPy sinc() function:
    vals = np.sinc(x)
  3. Plot the sinc() function with matplotlib:
    plt.plot(x, vals)
    plt.show()

    The sinc() function will have the following output:

    Time for action – plotting the sinc function

    The sinc2d() function requires a two-dimensional array. We can create it with the outer() function, resulting in this plot (code is in the following section):

    Time for action – plotting the sinc function

What just happened?

We plotted the well-known sinc function with the NumPy sinc() function (see plot_sinc.py):

import numpy as np
import matplotlib.pyplot as plt


x = np.linspace(0, 4, 100)
vals = np.sinc(x)

plt.plot(x, vals)
plt.title('Sinc function')
plt.xlabel('x')
plt.ylabel('y')
plt.grid()
plt.show()

We did the same for two dimensions (see sinc2d.py):

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 4, 100)
xx = np.outer(x, x)
vals = np.sinc...
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