這篇文章將為大家詳細講解有關(guān)如何進行Java最優(yōu)二叉樹的哈夫曼算法的簡單實現(xiàn)，文章內(nèi)容質(zhì)量較高，因此小編分享給大家做個參考，希望大家閱讀完這篇文章后對相關(guān)知識有一定的了解。
成都創(chuàng)新互聯(lián)網(wǎng)站建設(shè)公司是一家服務(wù)多年做網(wǎng)站建設(shè)策劃設(shè)計制作的公司,為廣大用戶提供了成都網(wǎng)站設(shè)計、成都做網(wǎng)站，成都網(wǎng)站設(shè)計，廣告投放平臺，成都做網(wǎng)站選成都創(chuàng)新互聯(lián)，貼合企業(yè)需求，高性價比，滿足客戶不同層次的需求一站式服務(wù)歡迎致電。
最優(yōu)二叉樹也稱哈夫曼樹，講的直白點就是每個結(jié)點都帶權(quán)值，我們讓大的值離根近、小的值離根遠，實現(xiàn)整體權(quán)值（帶權(quán)路徑長度）最小化。
哈夫曼算法的思想我認(rèn)為就是上面講的，而它的算法實現(xiàn)思路是這樣的：從根結(jié)點中抽出權(quán)值最小的兩個（涉及排序，但是我這個實現(xiàn)代碼沒做嚴(yán)格的排序，只有比較）合并出新的根結(jié)點重新加入排序（被抽出來的兩個自然是變成非根結(jié)點了?。瓦@樣循環(huán)下去，直到合并完成，我們得到一顆最優(yōu)二叉樹——哈夫曼樹。
說明：（1）哈夫曼樹有n個葉子結(jié)點，則我們可以推出其有n-1個分支結(jié)點。因此我在定義名為huffmanTree的HuffmanNode類型數(shù)組時定義長度為2*n-1。（2）這里排序相關(guān)沒有做得很好，只是為了實現(xiàn)而實現(xiàn)，以后慢慢完善。（3）理論上講哈夫曼樹應(yīng)該是不僅僅局限于數(shù)值，能compare就行，但這里只用int表示。
下面是代碼：
首先定義哈夫曼樹結(jié)點
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 + "]";
}
}
定義一下哈夫曼樹的異常類
public class TreeException extends RuntimeException {
private static final long serialVersionUID = 1L;
public TreeException() {}
public TreeException(String message) {
super(message);
}}
編碼實現(xiàn)（做的處理不是那么高效）
public class HuffmanTree {
protected HuffmanNode[] huffmanTree;
public HuffmanTree(int[] leafs) {
//異常條件判斷 if (leafs.length <= 1) {
throw new TreeException("葉子結(jié)點個數(shù)小于2，無法構(gòu)建哈夫曼樹"); }
//初始化儲存空間 huffmanTree = new HuffmanNode[leafs.length*2-1];
//構(gòu)造n棵只含根結(jié)點的二叉樹 for (int i = 0; i < leafs.length; i++) {
HuffmanNode node = new HuffmanNode(leafs[i]);
huffmanTree[i] = node; }
//構(gòu)造哈夫曼樹的選取與合并 for (int i = leafs.length; i < huffmanTree.length; i++) {
//獲取權(quán)值最小的結(jié)點下標(biāo) int miniNum_1 = selectMiniNum1();
//獲取權(quán)值次小的結(jié)點下標(biāo) int miniNum_2 = selectMiniNum2();
if (miniNum_1 == -1 || miniNum_2 == -1) { return;
}
//兩個權(quán)值最小的結(jié)點合并為新節(jié)點
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);
} }
/** * 獲取權(quán)值最小的結(jié)點下標(biāo)
* @return */ private int selectMiniNum1() {
//最小值 int min = -1;
//最小值下標(biāo) int index = -1;
//是否完成最小值初始化 boolean flag = false;
//遍歷一遍 for (int i = 0; i < huffmanTree.length; i++) {
//排空、只看根結(jié)點，否則跳過
if (huffmanTree[i] == null || huffmanTree[i].getParent() != -1) {
continue; }
else if (!flag) { //沒初始化先初始化然后跳過
//初始化 min = huffmanTree[i].getWeight();
index = i;
//以后不再初始化min flag = true;
//跳過本次循環(huán) continue;
} int tempWeight = huffmanTree[i].getWeight();
//低效比較 if (tempWeight < min) {
min = tempWeight;
index = i;
}
} return index; }
/** * 獲取權(quán)值次小的結(jié)點下標(biāo) * @return */ private int selectMiniNum2() {
//次小值 int min = -1;
//是否完成次小值初始化 boolean flag = false;
//最小值下標(biāo)（調(diào)用上面的方法） int index = selectMiniNum1();
//最小值都不存在，則次小值也不存在 if (index == -1) {
return -1; }
//次小值下標(biāo) int index2 = -1;
//遍歷一遍 for (int i = 0; i < huffmanTree.length; i++) {
//最小值不要、排空、只看根結(jié)點，否則跳過
if (index == i || huffmanTree[i] == null || huffmanTree[i].getParent() != -1) {
continue;
}
else if (!flag) {
//沒初始化先初始化然后跳過
//初始化 min = huffmanTree[i].getWeight();
index2 = i;
//以后不再初始化min flag = true;
//跳過本次循環(huán) continue;
} int tempWeight = huffmanTree[i].getWeight();
//低效比較 if (tempWeight < min) { min = tempWeight;
index2 = i;
}
} return index2;
}
}
測試類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);
}
}
}
測試結(jié)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]
圖形表示：
測試類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); } }}
測試結(jié)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]
關(guān)于如何進行Java最優(yōu)二叉樹的哈夫曼算法的簡單實現(xiàn)就分享到這里了，希望以上內(nèi)容可以對大家有一定的幫助，可以學(xué)到更多知識。如果覺得文章不錯，可以把它分享出去讓更多的人看到。
重慶分公司
重慶分公司
