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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 – plotting a polynomial function

To illustrate how plotting works, let's display some polynomial graphs. We will use the NumPy polynomial function poly1d() to create a polynomial.

  1. Take the standard input values as polynomial coefficients. Use the NumPy poly1d() function to create a polynomial:
    func = np.poly1d(np.array([1, 2, 3, 4]).astype(float))
  2. Create the x values with the NumPy the linspace() function. Use the range -10 to 10 and create 30 even spaced values:
    x = np.linspace(-10, 10, 30)
  3. Calculate the polynomial values using the polynomial we created in the first step:
    y = func(x)
  4. Call the plot() function; this does not immediately display the graph:
    plt.plot(x, y)
  5. Add a label to the x axis with the xlabel() function:
    plt.xlabel('x')
  6. Add a label to the y axis with the ylabel() function:
    plt.ylabel('y(x)')
  7. Call the show() function to display the graph:
    plt.show()

    The following is a plot with polynomial coefficients 1, 2, 3, and 4:

    Time for action – plotting a polynomial function

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