-
Notifications
You must be signed in to change notification settings - Fork 29
/
Copy pathBSTMap.java
217 lines (173 loc) · 5.63 KB
/
BSTMap.java
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
package map;
import set.FileOperation;
import java.util.ArrayList;
/**
* 映射 Map
* 1)、存储 Key:value 数据对的数据结构。
* 2)、根据 Key,寻找 Value。
*
* 非常容易使用链表或者二分搜索树来实现。
* LinkedListMap BSTMap 平均 最差
* add、remove、set、get、contains O(n) O(h) O(logn) O(n)
*/
public class BSTMap<K extends Comparable<K>, V> implements Map<K, V> {
private class Node {
private K key;
private V value;
private Node left;
private Node right;
public Node(K key, V value) {
this.key = key;
this.value = value;
this.left = null;
this.right = null;
}
}
private Node root;
private int size;
public BSTMap() {
this.root = null;
this.size = 0;
}
// 向二分搜索树中添加新的元素(key,value)
@Override
public void add(K key, V value) {
root = add(root, key, value);
}
// 向以 Node 为根节点的二分搜索树中插入元素(key,value),递归算法
// 返回插入新节点后二分搜索树的根
private Node add(Node node, K key, V value) {
if (node == null) {
size ++;
return new Node(key, value);
}
if (key.compareTo(node.key) < 0) {
node.left = add(node.left, key, value);
} else if (key.compareTo(node.key) > 0) {
node.right = add(node.right, key, value);
} else {
node.value = value;
}
return node;
}
// 返回以 Node 为根节点的二分搜索树中,key 所在的节点
private Node getNode(Node node, K key) {
if (node == null) {
return null;
}
if (node.key.equals(key)) {
return node;
} else if (key.compareTo(node.key) < 0) {
return getNode(node.left, key);
} else {
return getNode(node.right, key);
}
}
// 从二分搜索树中删除键为 key 的节点
@Override
public V remove(K key) {
Node node = getNode(root, key);
if (node != null) {
root = remove(root, key);
return node.value;
}
return null;
}
private Node remove(Node node, K key) {
if (node == null) {
return null;
}
if (key.compareTo(node.key) < 0) {
node.left = remove(node.left, key);
return node;
} else if (key.compareTo(node.key) > 0) {
node.right = remove(node.right, key);
return node;
} else {
// 待删除节点左子树为空的情况
if (node.left == null) {
Node rightNode = node.right;
node.right = null;
size --;
return rightNode;
}
// 待删除节点右子树为空的情况
if (node.right == null) {
Node leftNode = node.left;
node.left = null;
size --;
return leftNode;
}
// 待删除节点左右子树都为空的情况
// 找到比待删除节点大的最小节点,即待删除节点右子树的最小节点
// 用这个节点顶替待删除节点的位置
Node successor = minimum(node.right);
successor.right = removeMin(node.right);
successor.left = node.left;
node.left = node.right = null;
return successor;
}
}
// 返回以 Node 为根的二分搜索树的最小值所在的节点
private Node minimum(Node node) {
if (node.left == null) {
return node;
}
return minimum(node.left);
}
// 删除掉以 Node 为根的二分搜索树中的最小节点
// 返回删除节点后新的二分搜索树的根
private Node removeMin(Node node) {
if (node.left == null) {
Node rightNode = node.right;
node.right = null;
size --;
return rightNode;
}
node.left = removeMin(node.left);
return node;
}
@Override
public boolean contains(K key) {
return getNode(root, key) != null;
}
@Override
public V get(K key) {
Node node = getNode(root, key);
return node == null ? null:node.value;
}
@Override
public void set(K key, V newValue) {
Node node = getNode(root, key);
if (node == null) {
throw new IllegalArgumentException(key + " on exist~");
}
node.value = newValue;
}
@Override
public int getSize() {
return size;
}
@Override
public boolean isEmpty() {
return size == 0;
}
public static void main(String[] args){
System.out.println("Pride and Prejudice");
ArrayList<String> words = new ArrayList<>();
if(FileOperation.readFile("pride-and-prejudice.txt", words)) {
System.out.println("Total words: " + words.size());
BSTMap<String, Integer> map = new BSTMap<>();
for (String word : words) {
if (map.contains(word))
map.set(word, map.get(word) + 1);
else
map.add(word, 1);
}
System.out.println("Total different words: " + map.getSize());
System.out.println("Frequency of PRIDE: " + map.get("pride"));
System.out.println("Frequency of PREJUDICE: " + map.get("prejudice"));
}
System.out.println();
}
}