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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

Explaining the missing parts

In this section, we are going to show the implementations of the class methods. We begin with the insert() function of the iSAX class, which should not be confused with the insert() function of the Node class. In Python and many other programming languages, classes are independent entities, which means they can have methods with the same name as long as they are unique inside the class namespace.

We are going to present the code of Node.insert() in eight parts. The method accepts two parameters – apart from self, which denotes the current Node object – which are the subsequences we are trying to insert and the iSAX index that the Node instance belongs to.

Why do we need an iSAX instance as a parameter? We need that in order to be able to add new nodes to the iSAX index by accessing iSAX.ht.

The first part of insert() is the following:

    # Follow algorithm from iSAX paper
    def insert...
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