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Ruby實現(xiàn)的最優(yōu)二叉查找樹算法

 更新時間:2015年05月22日 11:14:33   投稿:junjie  
這篇文章主要介紹了Ruby實現(xiàn)的最優(yōu)二叉查找樹算法,本文直接給出實現(xiàn)代碼,需要的朋友可以參考下

算法導(dǎo)論上的偽碼改寫而成,加上導(dǎo)論的課后練習(xí)第一題的解的構(gòu)造函數(shù)。

復(fù)制代碼 代碼如下:

#encoding: utf-8
=begin
author: xu jin
date: Nov 11, 2012
Optimal Binary Search Tree
to find by using EditDistance algorithm
refer to <<introduction to algorithms>>
example output:
"k2 is the root of the tree."
"k1 is the left child of k2."
"d0 is the left child of k1."
"d1 is the right child of k1."
"k5 is the right child of k2."
"k4 is the left child of k5."
"k3 is the left child of k4."
"d2 is the left child of k3."
"d3 is the right child of k3."
"d4 is the right child of k4."
"d5 is the right child of k5."

The expected cost is 2.75. 
=end

INFINTIY = 1 / 0.0
a = ['', 'k1', 'k2', 'k3', 'k4', 'k5']
p = [0, 0.15, 0.10, 0.05, 0.10, 0.20]
q = [0.05, 0.10, 0.05, 0.05, 0.05 ,0.10]
e = Array.new(a.size + 1){Array.new(a.size + 1)}
root = Array.new(a.size + 1){Array.new(a.size + 1)}

def optimalBST(p, q, n, e, root)
  w = Array.new(p.size + 1){Array.new(p.size + 1)}
  for i in (1..n + 1)
    e[i][i - 1] = q[i - 1]
    w[i][i - 1] = q[i - 1]
  end
  for l in (1..n)
    for i in (1..n - l + 1)
      j = i + l -1
      e[i][j] = 1 / 0.0
      w[i][j] = w[i][j - 1] + p[j] + q[j]
      for r in (i..j)
        t = e[i][r - 1] + e[r + 1][j] + w[i][j]
        if t < e[i][j]
          e[i][j] = t
          root[i][j] = r
        end
      end
    end
  end
end

def printBST(root, i ,j, signal)
  return if i > j
  if signal == 0
   p "k#{root[i][j]} is the root of the tree."
   signal = 1
  end
  r = root[i][j]
  #left child
  if r - 1< i
    p "d#{r - 1} is the left child of k#{r}."
  else
    p "k#{root[i][r - 1]} is the left child of k#{r}."
    printBST(root, i, r - 1, 1 )
  end
  #right child
  if r >= j
     p "d#{r} is the right child of k#{r}."
  else
    p "k#{root[r + 1][j]} is the right child of k#{r}."
    printBST(root, r + 1, j, 1)
  end
 
end

optimalBST(p, q, p.size - 1, e, root)
printBST(root, 1, a.size-1, 0)
puts "\nThe expected cost is #{e[1][a.size-1]}."

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