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Learning Functional Data Structures and Algorithms

You're reading from   Learning Functional Data Structures and Algorithms Learn functional data structures and algorithms for your applications and bring their benefits to your work now

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781785888731
Length 318 pages
Edition 1st Edition
Languages
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Authors (2):
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Raju Kumar Mishra Raju Kumar Mishra
Author Profile Icon Raju Kumar Mishra
Raju Kumar Mishra
Atul S. Khot Atul S. Khot
Author Profile Icon Atul S. Khot
Atul S. Khot
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Table of Contents (14) Chapters Close

Preface 1. Why Functional Programming? FREE CHAPTER 2. Building Blocks 3. Lists 4. Binary Trees 5. More List Algorithms 6. Graph Algorithms 7. Random Access Lists 8. Queues 9. Streams, Laziness, and Algorithms 10. Being Lazy - Queues and Deques 11. Red-Black Trees 12. Binomial Heaps 13. Sorting

Some algorithms on stream


We have found that streams are infinite sequence. Hence, streams are used to create mathematical sequences. We find many mathematical series, which are used in day-to-day simulations and mathematical modeling. Some of mathematical series are as follows:

  • Arithmetic progression

  • Geometric progression

  • Harmonic progression

  • Fibonacci series

Brownian motion path

Let us explore some mathematical series using lazy sequences. I should start with the Arithmetic series.

Arithmetic progression

Arithmetic progression is a mathematical sequence where the difference between two consecutive elements is constant:

2, 5, 8, 11, 14, 17,...

The preceding mathematical sequence is an arithmetic progression, and the difference between any two consecutive elements is three. This constant difference is known as common difference. First term of the series is known as initial term. If 1 is the initial term of an arithmetic progression, then the nth term an is calculated as follows:

an = a1 + (n-1...

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