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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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Toc

Table of Contents (14) Chapters Close

Preface 1. Why Functional Programming? 2. Building Blocks FREE CHAPTER 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

A binomial heap

A heap-ordered binomial tree is one in which every parent value is less than or equal to its children. In other words, a parent value is never greater than its children values.

Here's a diagram illustrating this:

A binomial heap

The diagram shows a binomial heap with 13 nodes. All the binomial trees are linked together in increasing order of their ranks. This linked list of roots is the root list.

Let's start shaping up our code now.

Linking up

Our node is defined as a case class:

  case class Node(rank: Int, v: Int, children: List[Node]) 

The node holds the rank, the value v, and a list of children (possibly empty).

Given this definition, let's see how we could link two binomial trees. We always link trees of equal rank:

  def linkUp(t1: Node, t2: Node) = 
    if (t1.v <= t2.v) 
      Node(t1.rank+1, t1.v, t2 :: t1.children) 
    else 
      Node(t1.rank+1, t2.v, t1 :: t2.children) 

Here is the diagram showing linking up two trees of rank 0:

Linking up

Let's grok this code with...

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