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一、二叉搜索树概览
二叉搜索树(又名二叉查找树、二叉排序树)是一种可提供良好搜寻效率的树形结构,支持动态集合操作,所谓动态集合操作,就是Search、Maximum、Minimum、Insert、Delete等操作,二叉搜索树可以保证这些操作在对数时间内完成。当然,在最坏情况下,即所有节点形成一种链式树结构,则需要O(n)时间。这就说明,针对这些动态集合操作,二叉搜索树还有改进的空间,即确保最坏情况下所有操作在对数时间内完成。这样的改进结构有AVL(Adelson-Velskii-Landis) tree、RB(红黑)tree和AA-tree。AVL树和红黑树相对应用较多,我们在后面的章节中在做整理。
在二叉搜索树中,任何一个节点的键值一定大于其左子树中的每一个节点的键值,并小于其右子树中每一个节点的键值。我们结合书本的理论对二叉搜索树的动态集合操作做编程实现。其中除了Delete操作稍稍复杂之外,其余的操作都是非常简单的。
二、二叉搜索树动态集合操作
1、查询二叉搜索树
查询包括查找某一个元素,查找最大、最小关键字元素,查找前驱和后继,根据二叉搜索树的性质:左子树 < 根 < 右子树,这样的操作很容易实现。如下:
查找某元素:
1 //@brief 查找元素 2 //@return 是否查找成功 3 bool BinarySearchTree::Search(const int search_value) const 4 { 5 return _Search(m_pRoot, search_value) != NULL; 6 } 7 8 //@brief 真正的查找操作 9 //非递归查找 10 BinarySearchTree::_Node * BinarySearchTree::_Search(_Node *node, const int search_value) const 11 { 12 //递归 13 // if (node == NULL || search_value = node->m_nValue) 14 // return node; 15 // if (search_value < node->m_nValue) 16 // return _Search(node->m_pLeft); 17 // else 18 // return _Search(node->m_pRight); 19 20 //非递归 21 while(node && search_value != node->m_nValue) { 22 if (search_value < node->m_nValue) 23 node = node->m_pLeft; 24 else 25 node = node->m_pRight; 26 } 27 return node; 28 }
查找最大、最小关键字元素:
1 //@brief 得到以node为根节点的子树中的最大关键字节点 2 BinarySearchTree::_Node * BinarySearchTree::_GetMaximum(_Node *node) const 3 { 4 while(node->m_pRight) { 5 node = node->m_pRight; 6 } 7 return node; 8 } 9 10 //@brief 得到以node为根节点的子树中的最小关键字节点 11 BinarySearchTree::_Node * BinarySearchTree::_GetMinimum(_Node *node) const 12 { 13 while(node->m_pLeft) { 14 node = node->m_pLeft; 15 } 16 return node; 17 }
查找前驱和后继:
1 //@brief 得到一个同时存在左右子树的节点node的前驱 2 BinarySearchTree::_Node * BinarySearchTree::_GetPredecessor(_Node *node) const 3 { 4 if (node->m_pLeft) 5 return _GetMinimum(node); 6 7 _Node *pTemp = node->m_pParent; 8 while (pTemp && node == pTemp->m_pLeft) { 9 node = pTemp; 10 pTemp = pTemp->m_pParent; 11 } 12 return pTemp; 13 } 14 15 //@brief 得到一个同时存在左右子树的节点node的后继 16 BinarySearchTree::_Node * BinarySearchTree::_GetSuccessor(_Node *node) const 17 { 18 if(node->m_pRight) 19 return _GetMaximum(node); 20 21 _Node *pTemp = node->m_pParent; 22 while (pTemp && node == pTemp->m_pRight ) { 23 node = pTemp; 24 pTemp = pTemp->m_pParent; 25 } 26 return pTemp; 27 }
2、插入和删除
插入操作:通过不断的遍历,找到待插入元素应该处的位置,即可进行插入,代码如下:包括递归和非递归的版本:
1 //@brief 插入元素 2 //@return 是否插入成功 3 bool BinarySearchTree::Insert(const int new_value) 4 { 5 //非递归 6 if (Search(new_value)) 7 return false; 8 9 _Node *pTemp = NULL; 10 _Node *pCurrent = m_pRoot; 11 while ( pCurrent ) { 12 pTemp = pCurrent; 13 if ( new_value < pCurrent->m_nValue ) 14 pCurrent = pCurrent->m_pLeft; 15 else 16 pCurrent = pCurrent->m_pRight; 17 18 } 19 _Node *pInsert = new _Node(); 20 pInsert->m_nValue = new_value; 21 pInsert->m_pParent = pTemp; 22 23 if ( !pTemp ) //空树 24 m_pRoot = pInsert; 25 else if ( new_value < pTemp->m_nValue ) 26 pTemp->m_pLeft = pInsert; 27 else 28 pTemp->m_pRight = pInsert; 29 return true; 30 } 31 32 //递归 33 BinarySearchTree::_Node * BinarySearchTree::Insert_Recur(_Node *&node, const int new_value) 34 { 35 if ( node == NULL ) { 36 _Node *pInsert = new _Node(); 37 pInsert->m_nValue = new_value; 38 node = pInsert; 39 } 40 else if ( new_value < node->m_nValue ) 41 node->m_pLeft = Insert_Recur( node->m_pLeft, new_value ); 42 else 43 node->m_pRight = Insert_Recur( node->m_pRight, new_value ); 44 return node; 45 }
删除操作:有点小复杂,总共分为四种情况:
1)如果待删除节点没有子节点,则直接删除即可,并更改其父节点的指向;
2)如果待删除的节点只有一个子节点,其中,如果为左子树节点,则用左子树节点替换之;反之用右子树节点替换之;
3)如果待删除节点 z 有两个子节点,这个时候分两种情况考虑,第一种情况:z 的后继即为 z 的右孩子节点,则将 z 的有孩子节点替换之;
4)第二种情况: z 的后继不是 z 的有孩子节点,则首先用 z 的后继的有孩子节点替换 z 的后继,再用 z 的后继替换 z 。
没有图形作为辅助,实属难以表述和透彻理解,详细的过程和分析见书本上。
注意:在《算法导论》前几版的实现中,该过程的实现略有不同,相较上面这个过程,要简单一些,做法是:不是用 z 的后继 y 替换节点 z,而是删除节点 y,但复制 y 的关键字到节点 z 中来实现。但是这种做法,作者在最新这一版中明确提出,那种方法的缺陷是:会造成实际被删除的节点并不是被传递到删除过程中的那个节点,会有一些已删除节点的“过时”指针带来不必要的影响,总之复制删除的方法不是好的。代码实现如下:
//@brief 删除元素 //@return 是否删除成功 bool BinarySearchTree::Delete(const int delete_value) { _Node *delete_node = _Search(m_pRoot, delete_value); //未找到该节点 if (!delete_node) return false; else { _DeleteNode(delete_node); return true; } } //@brief 真正的删除操作 void BinarySearchTree::_DeleteNode(_Node *delete_node) { if (delete_node->m_pLeft == NULL) _Delete_Transplant(delete_node, delete_node->m_pRight); else if (delete_node->m_pRight == NULL) _Delete_Transplant(delete_node, delete_node->m_pLeft); else { _Node *min_node = _GetMinimum(delete_node->m_pRight); if (min_node->m_pParent != delete_node) { _Delete_Transplant(min_node, min_node->m_pRight); min_node->m_pRight = delete_node->m_pRight; min_node->m_pRight->m_pParent = min_node; } _Delete_Transplant(delete_node, min_node); min_node->m_pLeft = delete_node->m_pLeft; min_node->m_pLeft->m_pParent = min_node; } } void BinarySearchTree::_Delete_Transplant(_Node *unode, _Node *vnode) { if (unode->m_pParent == NULL) m_pRoot = vnode; else if (unode == unode->m_pParent->m_pLeft) unode->m_pParent->m_pLeft = vnode; else unode->m_pParent->m_pRight = vnode; if (vnode) vnode->m_pParent = unode->m_pParent; }
这里增加了一个函数Transplant()来实现替换操作,使代码较简洁。
完整的代码如下:
//BinarySearchTree.h #ifndef _BINARY_SEARCH_TREE_ #define _BINARY_SEARCH_TREE_ class BinarySearchTree { private: struct _Node { int m_nValue; _Node *m_pParent; _Node *m_pLeft; _Node *m_pRight; }; public: BinarySearchTree(_Node *pRoot = NULL):m_pRoot(pRoot){} ~BinarySearchTree(); //@brief 插入元素 //@return 是否插入成功 bool Insert(const int new_value); //递归 _Node * Insert_Recur(_Node *&node, const int new_value); //@brief 删除元素 //@return 是否删除成功 bool Delete(const int delete_value); //@brief 查找元素 //@return 是否查找成功 bool Search(const int search_value) const; //@brief 使用dot描述当前二叉查找树 void Display() const; //@brief 树的遍历 void Inorder() const {Inorder_Tree_Walk(m_pRoot);} void Preorder() const {Preorder_Tree_Walk(m_pRoot);} void Postorder() const {Postorder_Tree_Walk(m_pRoot);} private: //@brief 真正的删除操作 void _DeleteNode(_Node *delete_node); void _Delete_Transplant(_Node *unode, _Node *vnode); //@brief 得到以node为根节点的子树中的最大关键字节点 _Node * _GetMaximum(_Node *node) const; //@brief 得到以node为根节点的子树中的最小关键字节点 _Node * _GetMinimum(_Node *node) const; //@brief 得到一个同时存在左右子树的节点node的前驱 _Node * _GetPredecessor(_Node *node) const; //@brief 得到一个同时存在左右子树的节点node的后继 _Node * _GetSuccessor(_Node *node) const; //@brief 真正的查找操作 //非递归查找 _Node * _Search(_Node *node, const int search_value) const; //@brief 显示一棵二叉搜索树 void _Display(/*iostream &ss, */_Node *node) const; //@brief 递归释放节点 void _RecursiveReleaseNode(_Node *node); void ShowGraphvizViaDot(const string &dot) const; //@brief 树的遍历 void Inorder_Tree_Walk(_Node *node) const; void Preorder_Tree_Walk(_Node *node) const; void Postorder_Tree_Walk(_Node *node) const; private: _Node *m_pRoot; }; #endif//_BINARY_SEARCH_TREE_ //BinarySearchTree.cpp #include <iostream> #include <string> #include <iomanip> #include <ctime> using namespace std; #include "BinarySearchTree.h" BinarySearchTree::~BinarySearchTree() { _RecursiveReleaseNode(m_pRoot); } //@brief 插入元素 //@return 是否插入成功 bool BinarySearchTree::Insert(const int new_value) { //非递归 if (Search(new_value)) return false; _Node *pTemp = NULL; _Node *pCurrent = m_pRoot; while ( pCurrent ) { pTemp = pCurrent; if ( new_value < pCurrent->m_nValue ) pCurrent = pCurrent->m_pLeft; else pCurrent = pCurrent->m_pRight; } _Node *pInsert = new _Node(); pInsert->m_nValue = new_value; pInsert->m_pParent = pTemp; if ( !pTemp ) //空树 m_pRoot = pInsert; else if ( new_value < pTemp->m_nValue ) pTemp->m_pLeft = pInsert; else pTemp->m_pRight = pInsert; return true; // //该元素已经存在 // if (Search(new_value)) // return false; // // //空树,插入第1个节点 // if (!m_pRoot) { // m_pRoot = new _Node(); // m_pRoot->m_nValue = new_value; // return true; // } // // //非第一个节点 // _Node *current_node = m_pRoot; // while( current_node ) { // _Node *&next_node_pointer = (new_value < current_node->m_nValue ? current_node->m_pLeft:current_node->m_pRight); // if ( next_node_pointer ) // current_node = next_node_pointer; // else { // next_node_pointer = new _Node(); // next_node_pointer->m_nValue = new_value; // next_node_pointer->m_pParent = current_node; // break; // } // } // return true; } //递归 BinarySearchTree::_Node * BinarySearchTree::Insert_Recur(_Node *&node, const int new_value) { if ( node == NULL ) { _Node *pInsert = new _Node(); pInsert->m_nValue = new_value; node = pInsert; } else if ( new_value < node->m_nValue ) node->m_pLeft = Insert_Recur( node->m_pLeft, new_value ); else node->m_pRight = Insert_Recur( node->m_pRight, new_value ); return node; } //@brief 删除元素 //@return 是否删除成功 bool BinarySearchTree::Delete(const int delete_value) { _Node *delete_node = _Search(m_pRoot, delete_value); //未找到该节点 if (!delete_node) return false; else { _DeleteNode(delete_node); return true; } } //@brief 查找元素 //@return 是否查找成功 bool BinarySearchTree::Search(const int search_value) const { return _Search(m_pRoot, search_value) != NULL; } //@brief 使用dot描述当前二叉查找树 void BinarySearchTree::Display() const { _Display(m_pRoot); } //@brief 树的遍历 //中序 void BinarySearchTree::Inorder_Tree_Walk(_Node *node) const { if (node) { Inorder_Tree_Walk(node->m_pLeft); cout << node->m_nValue << " "; Inorder_Tree_Walk(node->m_pRight); } } //前序 void BinarySearchTree::Preorder_Tree_Walk(_Node *node) const { if (node) { cout << node->m_nValue << " "; Preorder_Tree_Walk(node->m_pLeft); Preorder_Tree_Walk(node->m_pRight); } } //后序 void BinarySearchTree::Postorder_Tree_Walk(_Node *node) const { if (node) { Postorder_Tree_Walk(node->m_pLeft); Postorder_Tree_Walk(node->m_pRight); cout << node->m_nValue << " "; } } //@brief 真正的删除操作 void BinarySearchTree::_DeleteNode(_Node *delete_node) { if (delete_node->m_pLeft == NULL) _Delete_Transplant(delete_node, delete_node->m_pRight); else if (delete_node->m_pRight == NULL) _Delete_Transplant(delete_node, delete_node->m_pLeft); else { _Node *min_node = _GetMinimum(delete_node->m_pRight); if (min_node->m_pParent != delete_node) { _Delete_Transplant(min_node, min_node->m_pRight); min_node->m_pRight = delete_node->m_pRight; min_node->m_pRight->m_pParent = min_node; } _Delete_Transplant(delete_node, min_node); min_node->m_pLeft = delete_node->m_pLeft; min_node->m_pLeft->m_pParent = min_node; } } void BinarySearchTree::_Delete_Transplant(_Node *unode, _Node *vnode) { if (unode->m_pParent == NULL) m_pRoot = vnode; else if (unode == unode->m_pParent->m_pLeft) unode->m_pParent->m_pLeft = vnode; else unode->m_pParent->m_pRight = vnode; if (vnode) vnode->m_pParent = unode->m_pParent; } //@brief 得到以node为根节点的子树中的最大关键字节点 BinarySearchTree::_Node * BinarySearchTree::_GetMaximum(_Node *node) const { while(node->m_pRight) { node = node->m_pRight; } return node; } //@brief 得到以node为根节点的子树中的最小关键字节点 BinarySearchTree::_Node * BinarySearchTree::_GetMinimum(_Node *node) const { while(node->m_pLeft) { node = node->m_pLeft; } return node; } //@brief 得到一个同时存在左右子树的节点node的前驱 BinarySearchTree::_Node * BinarySearchTree::_GetPredecessor(_Node *node) const { if (node->m_pLeft) return _GetMinimum(node); _Node *pTemp = node->m_pParent; while (pTemp && node == pTemp->m_pLeft) { node = pTemp; pTemp = pTemp->m_pParent; } return pTemp; } //@brief 得到一个同时存在左右子树的节点node的后继 BinarySearchTree::_Node * BinarySearchTree::_GetSuccessor(_Node *node) const { if(node->m_pRight) return _GetMaximum(node); _Node *pTemp = node->m_pParent; while (pTemp && node == pTemp->m_pRight ) { node = pTemp; pTemp = pTemp->m_pParent; } return pTemp; } //@brief 真正的查找操作 //非递归查找 BinarySearchTree::_Node * BinarySearchTree::_Search(_Node *node, const int search_value) const { //递归 // if (node == NULL || search_value = node->m_nValue) // return node; // if (search_value < node->m_nValue) // return _Search(node->m_pLeft); // else // return _Search(node->m_pRight); //非递归 while(node && search_value != node->m_nValue) { if (search_value < node->m_nValue) node = node->m_pLeft; else node = node->m_pRight; } return node; } //@brief 显示一棵二叉搜索树 void BinarySearchTree::_Display(/*iostream &ss, */_Node *node) const { if ( node ) { cout << node->m_nValue << " "; if ( node->m_pLeft ) { _Display( node->m_pLeft ); } if ( node->m_pRight ) { _Display( node->m_pRight ); } } } //@brief 递归释放节点 void BinarySearchTree::_RecursiveReleaseNode(_Node *node) { if (node) { _RecursiveReleaseNode(node->m_pLeft); _RecursiveReleaseNode(node->m_pRight); delete node; } } int main() { srand((unsigned)time(NULL)); BinarySearchTree bst; //用随机值生成一棵二叉查找树 for (int i= 0; i < 10; i ++) { bst.Insert( rand() % 100 ); } bst.Display(); cout << endl; //中序遍历 // bst.Inorder(); // cout << endl; //删除所有的奇数值结点 for ( int i = 1; i < 100; i += 2 ) { if( bst.Delete( i ) ) { cout << "### Deleted [" << i << "] ###" << endl; } } //验证删除的交换性 // bst.Delete(2); // bst.Delete(1); // bst.Display(); // cout << endl; //查找100以内的数,如果在二叉查找树中,则显示 cout << endl; for ( int i = 0; i < 10; i += 1 ) { if ( bst.Search( i ) ) { cout << "搜索[" << i << "]元素:\t成功" << endl; } } cout << endl; //中序遍历 bst.Inorder(); return 0; }
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原文地址:http://www.cnblogs.com/bakari/p/4892558.html