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Time Series Indexing

You're reading from   Time Series Indexing Implement iSAX in Python to index time series with confidence

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781838821951
Length 248 pages
Edition 1st Edition
Languages
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Author (1):
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Mihalis Tsoukalos Mihalis Tsoukalos
Author Profile Icon Mihalis Tsoukalos
Mihalis Tsoukalos
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Table of Contents (11) Chapters Close

Preface 1. Chapter 1: An Introduction to Time Series and the Required Python Knowledge 2. Chapter 2: Implementing SAX FREE CHAPTER 3. Chapter 3: iSAX – The Required Theory 4. Chapter 4: iSAX – The Implementation 5. Chapter 5: Joining and Comparing iSAX Indexes 6. Chapter 6: Visualizing iSAX Indexes 7. Chapter 7: Using iSAX to Approximate MPdist 8. Chapter 8: Conclusions and Next Steps 9. Index 10. Other Books You May Enjoy

More iSAX index visualizations

We are not done yet! There exist ways to improve the previous visualization by adding more information to the output as well as the ability to compress various parts of it – there is always the danger of putting too much information on a graph or a plot, but we are not going to make that mistake here.

First, we are going to go to the ZoomableTreemap directory in order to try a zoomable structure named Zoomable Treemap, which is better when dealing with large iSAX indexes.

The Zoomable Treemap uses an additional attribute called value. In this case, I had two choices: either change the output of the Python script or change the JavaScript code. I decided to do the latter. So, I changed the value attribute in the JavaScript code to size, which is what the Python script generates. However, in our case, this created a bug in the JavaScript code related to the sum of the presented values, which means that this was not the correct decision.

Therefore...

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