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NumPy Beginner's Guide

You're reading from   NumPy Beginner's Guide An action packed guide using real world examples of the easy to use, high performance, free open source NumPy mathematical library.

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Product type Paperback
Published in Apr 2013
Publisher Packt
ISBN-13 9781782166085
Length 310 pages
Edition 2nd 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 (19) Chapters Close

Numpy Beginner's Guide Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. NumPy Quick Start FREE CHAPTER 2. Beginning with NumPy Fundamentals 3. Get in Terms with Commonly Used Functions 4. Convenience Functions for Your Convenience 5. Working with Matrices and ufuncs 6. Move Further with NumPy Modules 7. Peeking into Special Routines 8. Assure Quality with Testing 9. Plotting with Matplotlib 10. When NumPy is Not Enough – SciPy and Beyond 11. Playing with Pygame Pop Quiz Answers Index

Time for action – calculating the average true range


To calculate the average true range, perform the following steps:

  1. The ATR is based on the low and high price of N days, usually the last 20 days.

    N = int(sys.argv[1])
    h = h[-N:]
    l = l[-N:]
  2. We also need to know the close price of the previous day.

    previousclose = c[-N -1: -1]

    For each day, we calculate the following:

    • h – l: The daily range (the difference between high and low price)

    • h – previousclose: The difference between high price and previous close

    • previousclose – l: The difference between the previous close and the low price

  3. The max function returns the maximum of an array. Based on those three values, we calculate the so-called true range, which is the maximum of these values. We are now interested in the element-wise maxima across arrays—meaning the maxima of the first elements in the arrays, the second elements in the arrays, and so on. Use the NumPy maximum function instead of the max function for this purpose.

    truerange = np.maximum...
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