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Learning NumPy Array

You're reading from   Learning NumPy Array Supercharge your scientific Python computations by understanding how to use the NumPy library effectively

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783983902
Length 164 pages
Edition 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 (14) Chapters Close

Learning NumPy Array
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with NumPy FREE CHAPTER 2. NumPy Basics 3. Basic Data Analysis with NumPy 4. Simple Predictive Analytics with NumPy 5. Signal Processing Techniques 6. Profiling, Debugging, and Testing 7. The Scientific Python Ecosystem Index

Introducing the Sunspot data


Sunspots are dark spots visible on the Sun's surface. This phenomenon has been studied for many centuries by astronomers. Evidence has been found for periodic sunspot cycles. We can download up-to-date annual sunspot data from http://www.quandl.com/SIDC/SUNSPOTS_A-Sunspot-Numbers-Annual. This is provided by the Belgian Solar Influences Data Analysis Center. The data goes back to 1700 and contains more than 300 annual averages. In order to determine sunspot cycles, scientists successfully used the Hilbert-Huang transform (refer to http://en.wikipedia.org/wiki/Hilbert%E2%80%93Huang_transform). A major part of this transform is the so-called Empirical Mode Decomposition (EMD) method. The entire algorithm contains many iterative steps, and we will cover only some of them here. EMD reduces data to a group of Intrinsic Mode Functions (IMF). You can compare this to the way Fast Fourier Transform decomposes a signal in a superposition of sine and cosine terms.

Extracting...

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