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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 2. Beginning with NumPy Fundamentals FREE CHAPTER 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 – computing Fibonacci numbers

A matrix can represent the Fibonacci recurrence relation. We can express the calculation of Fibonacci numbers as a repeated matrix multiplication:

  1. Create the Fibonacci matrix as follows:
    F = np.matrix([[1, 1], [1, 0]])
    print("F", F)

    The Fibonacci matrix appears as follows:

    F [[1 1]
      [1 0]]
    
  2. Calculate the 8th Fibonacci number (ignoring 0), by subtracting 1 from 8 and taking the power of the matrix. The Fibonacci number then appears on the diagonal:
    print("8th Fibonacci", (F ** 7)[0, 0])

    The Fibonacci number is as follows:

    8th Fibonacci 21
    
  3. The golden ratio formula, better known as Binet's formula, allows us to calculate Fibonacci numbers with a rounding step at the end. Calculate the first eight Fibonacci numbers:
    n = np.arange(1, 9)
    sqrt5 = np.sqrt(5)
    phi = (1 + sqrt5)/2
    fibonacci = np.rint((phi**n - (-1/phi)**n)/sqrt5)
    print("Fibonacci", fibonacci)

    The first eight Fibonacci numbers are as follows:

    Fibonacci [...
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