如何进行Java最优二叉树的哈夫曼算法的简单实现

这篇文章将为大家详细讲解有关如何进行Java最优二叉树的哈夫曼算法的简单实现,文章内容质量较高,因此小编分享给大家做个参考,希望大家阅读完这篇文章后对相关知识有一定的了解。

最优二叉树也称哈夫曼树,讲的直白点就是每个结点都带权值,我们让大的值离根近、小的值离根远,实现整体权值(带权路径长度)最小化。

哈夫曼算法的思想我认为就是上面讲的,而它的算法实现思路是这样的:从根结点中抽出权值最小的两个(涉及排序,但是我这个实现代码没做严格的排序,只有比较)合并出新的根结点重新加入排序(被抽出来的两个自然是变成非根结点了啊),就这样循环下去,直到合并完成,我们得到一颗最优二叉树——哈夫曼树。

说明:(1)哈夫曼树有n个叶子结点,则我们可以推出其有n-1个分支结点。因此我在定义名为huffmanTree的HuffmanNode类型数组时定义长度为2*n-1。(2)这里排序相关没有做得很好,只是为了实现而实现,以后慢慢完善。(3)理论上讲哈夫曼树应该是不仅仅局限于数值,能compare就行,但这里只用int表示。

下面是代码:

首先定义哈夫曼树结点

public class HuffmanNode {    

private int weight = -1;    

private int parent = -1;    

private int left = -1;    

private int right = -1;  

public HuffmanNode(int weight) {    super();    

this.weight = weight;  }  

public HuffmanNode(int weight, int left, int right) {    super();    

this.weight = weight;    

this.left = left;    

this.right = right;  }  

public int getWeight() {    

return weight;  }  

public void setWeight(int weight) {    

this.weight = weight;  }  

public int getParent() {   

 return parent;  }  

public void setParent(int parent) {    

this.parent = parent;  }  

public int getLeft() {    

return left;  }  

public void setLeft(int left) {   

 this.left = left;  }  

public int getRight() {    

return right;  }  public void setRight(int right) {    

this.right = right;  }  @Override  

public String toString() {   

 return "HuffmanNode [weight=" + weight + ", parent=" + parent + ","        + " left=" + left + ", right=" + right + "]";

  }

}

定义一下哈夫曼树的异常类

public class TreeException extends RuntimeException {    

private static final long serialVersionUID = 1L; 

 public TreeException() {}  

public TreeException(String message) {    

super(message);

  }}

编码实现(做的处理不是那么高效)

public class HuffmanTree {    

protected HuffmanNode[] huffmanTree;   

 public HuffmanTree(int[] leafs) {    

//异常条件判断    if (leafs.length <= 1) {      

throw new TreeException("叶子结点个数小于2,无法构建哈夫曼树");    }   

 //初始化储存空间    huffmanTree = new HuffmanNode[leafs.length*2-1];    

//构造n棵只含根结点的二叉树    for (int i = 0; i < leafs.length; i++) {      

HuffmanNode node = new HuffmanNode(leafs[i]);      

huffmanTree[i] = node;    }    

//构造哈夫曼树的选取与合并    for (int i = leafs.length; i < huffmanTree.length; i++) {     

 //获取权值最小的结点下标      int miniNum_1 = selectMiniNum1();     

 //获取权值次小的结点下标      int miniNum_2 = selectMiniNum2();      

if (miniNum_1 == -1 || miniNum_2 == -1) {        return;

      }     

 //两个权值最小的结点合并为新节点     

 HuffmanNode node = new HuffmanNode(huffmanTree[miniNum_1].getWeight() +      huffmanTree[miniNum_2].getWeight(), miniNum_1, miniNum_2);     

 huffmanTree[i] = node;      huffmanTree[miniNum_1].setParent(i);      

huffmanTree[miniNum_2].setParent(i);

    }  }   

 /**   * 获取权值最小的结点下标   

* @return   */  private int selectMiniNum1() {    

//最小值    int min = -1;   

 //最小值下标    int index = -1;   

 //是否完成最小值初始化    boolean flag = false;   

 //遍历一遍    for (int i = 0; i < huffmanTree.length; i++) {      

//排空、只看根结点,否则跳过      

if (huffmanTree[i] == null || huffmanTree[i].getParent() != -1) {       

 continue;      } 

else if (!flag) {   //没初始化先初始化然后跳过        

//初始化        min = huffmanTree[i].getWeight();       

 index = i;       

 //以后不再初始化min        flag = true;       

 //跳过本次循环        continue;  

    }      int tempWeight = huffmanTree[i].getWeight();      

//低效比较      if (tempWeight < min) {       

 min = tempWeight;        

index = i;    

  }    

}    return index;  }    

/**   * 获取权值次小的结点下标   * @return   */  private int selectMiniNum2() {    

//次小值    int min = -1;    

//是否完成次小值初始化    boolean flag = false;    

//最小值下标(调用上面的方法)    int index = selectMiniNum1();   

 //最小值都不存在,则次小值也不存在    if (index == -1) {     

 return -1;    }    

//次小值下标    int index2 = -1;   

 //遍历一遍    for (int i = 0; i < huffmanTree.length; i++) {      

//最小值不要、排空、只看根结点,否则跳过     

 if (index == i || huffmanTree[i] == null || huffmanTree[i].getParent() != -1) {        

continue; 

     } 

else if (!flag) {  

 //没初始化先初始化然后跳过        

//初始化        min = huffmanTree[i].getWeight();       

 index2 = i;       

 //以后不再初始化min        flag = true;        

//跳过本次循环        continue;    

  }      int tempWeight = huffmanTree[i].getWeight();     

 //低效比较      if (tempWeight < min) {        min = tempWeight;       

 index2 = i;    

  }   

 }    return index2;

  }

}

测试类1

public class HuffmanTreeTester {  

public static void main(String[] args) {    

int[] leafs = {1, 3, 5, 6, 2, 22, 77, 4, 9};    

HuffmanTree tree = new HuffmanTree(leafs);    

HuffmanNode[] nodeList = tree.huffmanTree;    

for (HuffmanNode node : nodeList) {      System.out.println(node);

    } 

 }

}

测试结果1

HuffmanNode [weight=1, parent=9, left=-1, right=-1]HuffmanNode [weight=3, parent=10, left=-1, right=-1]HuffmanNode [weight=5, parent=11, left=-1, right=-1]HuffmanNode [weight=6, parent=12, left=-1, right=-1]HuffmanNode [weight=2, parent=9, left=-1, right=-1]HuffmanNode [weight=22, parent=15, left=-1, right=-1]HuffmanNode [weight=77, parent=16, left=-1, right=-1]HuffmanNode [weight=4, parent=11, left=-1, right=-1]HuffmanNode [weight=9, parent=13, left=-1, right=-1]HuffmanNode [weight=3, parent=10, left=0, right=4]HuffmanNode [weight=6, parent=12, left=1, right=9]HuffmanNode [weight=9, parent=13, left=7, right=2]HuffmanNode [weight=12, parent=14, left=3, right=10]HuffmanNode [weight=18, parent=14, left=8, right=11]HuffmanNode [weight=30, parent=15, left=12, right=13]HuffmanNode [weight=52, parent=16, left=5, right=14]HuffmanNode [weight=129, parent=-1, left=15, right=6]

图形表示:

测试类2

public class HuffmanTreeTester {  public static void main(String[] args) {    int[] leafs = {2, 4, 5, 3};    HuffmanTree tree = new HuffmanTree(leafs);    HuffmanNode[] nodeList = tree.huffmanTree;    for (HuffmanNode node : nodeList) {      System.out.println(node);    }  }}

测试结果2

HuffmanNode [weight=2, parent=4, left=-1, right=-1]HuffmanNode [weight=4, parent=5, left=-1, right=-1]HuffmanNode [weight=5, parent=5, left=-1, right=-1]HuffmanNode [weight=3, parent=4, left=-1, right=-1]HuffmanNode [weight=5, parent=6, left=0, right=3]HuffmanNode [weight=9, parent=6, left=1, right=2]HuffmanNode [weight=14, parent=-1, left=4, right=5]

关于如何进行Java最优二叉树的哈夫曼算法的简单实现就分享到这里了,希望以上内容可以对大家有一定的帮助,可以学到更多知识。如果觉得文章不错,可以把它分享出去让更多的人看到。