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Haskell Data Analysis cookbook

You're reading from   Haskell Data Analysis cookbook Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783286331
Length 334 pages
Edition 1st Edition
Languages
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Author (1):
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Nishant Shukla Nishant Shukla
Author Profile Icon Nishant Shukla
Nishant Shukla
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Hunt for Data FREE CHAPTER 2. Integrity and Inspection 3. The Science of Words 4. Data Hashing 5. The Dance with Trees 6. Graph Fundamentals 7. Statistics and Analysis 8. Clustering and Classification 9. Parallel and Concurrent Design 10. Real-time Data 11. Visualizing Data 12. Exporting and Presenting Index

Traversing a graph depth-first


Using depth-first search, one can traverse a graph to view the nodes in the desired order. Implementing a topological sort, solving mazes, and finding connected components are all examples of useful algorithms that rely on a depth-first traversal of a graph.

How to do it...

Start editing a new source file, which we will name Main.hs:

  1. Import the required packages:

    import Data.Graph
    import Data.Array ((!))
  2. Construct the graph from the adjacency list:

    graph :: (Graph, Vertex -> (Int, Int, [Int]))
    
    graph = graphFromEdges'  [ (1, 1, [3, 4] )
                             , (2, 2, [3, 4]) 
                             , (3, 3, [4])
                             , (4, 4, []) ]
  3. Scan the graph depth-first:

    depth g i = depth' g [] i
    depth' g2(gShape, gMapping) seen i = 
      key : concat (map goDeeper adjacent)
      where goDeeper v = if v `elem` seen 
                          then [] 
                          else depth' g (i:seen) v
             adjacent = gShape ! i
             (_, key, _) = gMapping...
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