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我要写三种可并堆,然后讲解它们.
1. 二项堆
2. 配对堆
3. RP堆
这三种堆都有一个共同特点,就是用一棵半满的树表示子堆,用一系列子堆表示整个堆(当然子堆是有限制的).那么我们可以很方便的进行合并两个堆等操作.
这三种堆里最简单的就是二项堆了(Binomial Heap).为什么称为二项堆呢?二项堆这个小婊杂特别有趣,它的每个子堆大小都为2的幂.因此,它每次合并两个大小相等的堆,方法就像下面这张图.
那么手玩一下就可以得知,合并后两棵树其中的一棵向下偏了一位,层数多了一层.
那么深度为一时每层节点数是1(就一层)
深度为二时 1 1
3) 1 2 1
4) 1 3 3 1
5) 1 4 6 4 1
似曾相识?就是杨辉三角形.杨辉三角形的本质是什么?二项式.那么这个就被称为二项堆了.
二项堆的合并不难.我们只需要把所有深度相同的堆合并就可以了(还要用sibling指针串起来).
新建一个二项堆,与原二项堆合并即可.
我们只需要边合并边维护即可.
我们把以min为root的子堆提取出来,在原堆中删去,注意这是一棵只有左子节点的树.我们将左子结点这棵树当成二项堆,其中右子结点路径当成sibling指针(其实完全不用`当成‘),合并就行了.
http://dsqiu.iteye.com/blog/1714961 这位大神实现了这三种堆(Bino,Fib,Pairing),但是我不建议看这个.
他的代码
#include<iostream>
#include<cstdio>
#include<cstring>
#include<cstdlib>
#include<climits>
using namespace std;
typedef struct BinHeapNode BinNode;
typedef struct BinHeapNode * BinHeap;
typedef struct BinHeapNode * Position;
//结点ADT
struct BinHeapNode {
int key;
int degree;
Position parent;
Position leftChild;
Position sibling;
};
//用数组内的值建堆
BinHeap MakeBinHeapWithArray(int keys[], int n);
//两个堆合并
BinHeap BinHeapUnion(BinHeap &H1, BinHeap &H2);
//将H1, H2的根表合并成一个按度数的单调递增次序排列的链表
BinHeap BinHeapMerge(BinHeap &H1, BinHeap &H2);
//使H2成为H1的父节点
void BinLink(BinHeap &H1, BinHeap &H2);
//返回最小根节点的指针
BinHeap BinHeapMin(BinHeap heap);
//减少关键字的值
void BinHeapDecreaseKey(BinHeap heap, BinHeap x, int key);
//删除一个关键字
BinHeap BinHeapDelete(BinHeap &heap, int key);
//找出一个关键字
BinHeap BinHeapFind(BinHeap &heap, int key);
//打印输出堆结构
void PrintBinHeap(BinHeap heap);
//销毁堆
void DestroyBinHeap(BinHeap &heap);
//用数组内的值建堆
BinHeap MakeBinHeapWithArray(int keys[], int n) {
BinHeap heap = NULL, newHeap = NULL;
for (int i = 0; i < n; i++) {
newHeap = (BinHeap) malloc(sizeof(BinNode));
if (newHeap == NULL) {
puts("Out of the Space");
exit(1);
}
memset(newHeap, 0, sizeof(BinNode));
newHeap->key = keys[i];
if (NULL == heap) {
heap = newHeap;
} else {
heap = BinHeapUnion(heap, newHeap);
newHeap = NULL;
}
}
return heap;
}
//两个堆合并
BinHeap BinHeapUnion(BinHeap &H1, BinHeap &H2) {
Position heap = NULL, pre_x = NULL, x = NULL, next_x = NULL;
heap = BinHeapMerge(H1, H2);
if (heap == NULL) {
return heap;
}
pre_x = NULL;
x = heap;
next_x = x->sibling;
while (next_x != NULL) {
if ((x->degree != next_x->degree) ||//Cases 1 and 2
((next_x->sibling != NULL) && (next_x->degree == next_x->sibling->degree))) {
pre_x = x;
x = next_x;
} else if (x->key <= next_x->key) {//Cases 3
x->sibling = next_x->sibling;
BinLink(next_x, x);
} else {//Cases 4
if (pre_x == NULL) {
heap = next_x;
} else {
pre_x->sibling = next_x;
}
BinLink(x, next_x);
x = next_x;
}
next_x = x->sibling;
}
return heap;
}
//将H1, H2的根表合并成一个按度数的单调递增次序排列的链表
BinHeap BinHeapMerge(BinHeap &H1, BinHeap &H2) {
//heap->堆的首地址,H3为指向新堆根结点
BinHeap heap = NULL, firstHeap = NULL, secondHeap = NULL,
pre_H3 = NULL, H3 = NULL;
if (H1 != NULL && H2 != NULL){
firstHeap = H1;
secondHeap = H2;
//整个while,firstHeap, secondHeap, pre_H3, H3都在往后顺移
while (firstHeap != NULL && secondHeap != NULL) {
if (firstHeap->degree <= secondHeap->degree) {
H3 = firstHeap;
firstHeap = firstHeap->sibling;
} else {
H3 = secondHeap;
secondHeap = secondHeap->sibling;
}
if (pre_H3 == NULL) {
pre_H3 = H3;
heap = H3;
} else {
pre_H3->sibling = H3;
pre_H3 = H3;
}
if (firstHeap != NULL) {
H3->sibling = firstHeap;
} else {
H3->sibling = secondHeap;
}
}//while
} else if (H1 != NULL) {
heap = H1;
} else {
heap = H2;
}
H1 = H2 = NULL;
return heap;
}
//使H2成为H1的父节点
void BinLink(BinHeap &H1, BinHeap &H2) {
H1->parent = H2;
H1->sibling = H2->leftChild;
H2->leftChild = H1;
H2->degree++;
}
//返回最小根节点的指针
BinHeap BinHeapMin(BinHeap heap) {
Position y = NULL, x = heap;
int min = INT_MAX;
while (x != NULL) {
if (x->key < min) {
min = x->key;
y = x;
}
x = x->sibling;
}
return y;
}
//抽取有最小关键字的结点
BinHeap BinHeapExtractMin(BinHeap &heap) {
BinHeap pre_y = NULL, y = NULL, x = heap;
int min = INT_MAX;
while (x != NULL) {
if (x->key < min) {
min = x->key;
pre_y = y;
y = x;
}
x = x->sibling;
}
if (y == NULL) {
return NULL;
}
if (pre_y == NULL) {
heap = heap->sibling;
} else {
pre_y->sibling = y->sibling;
}
//将y的子结点指针reverse
BinHeap H2 = NULL, p = NULL;
x = y->leftChild;
while (x != NULL) {
p = x;
x = x->sibling;
p->sibling = H2;
H2 = p;
p->parent = NULL;
}
heap = BinHeapUnion(heap, H2);
return y;
}
//减少关键字的值
void BinHeapDecreaseKey(BinHeap heap, BinHeap x, int key) {
if(key > x->key) {
puts("new key is greaer than current key");
exit(1); //不为降键
}
x->key = key;
BinHeap z = NULL, y = NULL;
y = x;
z = x->parent;
while(z != NULL && z->key > y->key) {
swap(z->key, y->key);
y = z;
z = y->parent;
}
}
//删除一个关键字
BinHeap BinHeapDelete(BinHeap &heap, int key) {
BinHeap x = NULL;
x = BinHeapFind(heap, key);
if (x != NULL) {
BinHeapDecreaseKey(heap, x, INT_MIN);
return BinHeapExtractMin(heap);
}
return x;
}
//找出一个关键字
BinHeap BinHeapFind(BinHeap &heap, int key) {
Position p = NULL, x = NULL;
p = heap;
while (p != NULL) {
if (p->key == key) {
return p;
} else {
if((x =BinHeapFind(p->leftChild, key)) != NULL) {
return x;
}
p = p->sibling;
}
}
return NULL;
}
//打印输出堆结构
void PrintBinHeap(BinHeap heap) {
if (NULL == heap) {
return ;
}
Position p = heap;
while (p != NULL) {
printf(" (");
printf("%d", p->key);
//显示其孩子
if(NULL != p->leftChild) {
PrintBinHeap(p->leftChild);
}
printf(") ");
p = p->sibling;
}
}
int kp1[8] = {12,
7, 25,
15, 28, 33, 41};
int kp2[20] = {18,
3, 37,
6, 8, 29, 10, 44, 30, 23, 2, 48, 31, 17, 45, 32, 24, 50, 55};
int kp4[23] = {37, 41,
10, 28, 13, 77,
1, 6, 16, 12, 25, 8, 14, 29, 26, 23, 18, 11, 17, 38, 42, 27};
int main() {
BinHeap H1 = NULL;
H1 = MakeBinHeapWithArray(kp1, 7);
puts("第一个二叉堆H1:");
PrintBinHeap(H1);
BinHeap H2 = NULL;
H2 = MakeBinHeapWithArray(kp2, 19);
puts("\n\n第二个二叉堆H2:");
PrintBinHeap(H2);
BinHeap H3 = NULL;
H3 = BinHeapUnion(H1, H2);
puts("\n\n合并H1,H2后,得到H3:");
PrintBinHeap(H3);
BinHeap H4 = NULL;
H4 = MakeBinHeapWithArray(kp4, 22);
puts("\n\n用于测试提取和删除的二叉堆H4:");
PrintBinHeap(H4);
BinHeap extractNode = BinHeapExtractMin(H4);
if (extractNode != NULL) {
printf("\n\n抽取最小的值%d后:\n", extractNode->key);
PrintBinHeap(H4);
}
extractNode = BinHeapExtractMin(H4);
if (extractNode != NULL) {
printf("\n\n抽取最小的值%d后:\n", extractNode->key);
PrintBinHeap(H4);
}
extractNode = BinHeapExtractMin(H4);
if (extractNode != NULL) {
printf("\n\n抽取最小的值%d后:\n", extractNode->key);
PrintBinHeap(H4);
}
BinHeapDelete(H4, 12);
puts("\n\n删除12后:");
PrintBinHeap(H4);
return 0;
}
这份代码很长,而且其逻辑并不清晰.
我的代码
其实二项堆很好写的,只要你理解了,它需要考虑的细节甚至比二叉堆还少.
typedef struct heapNode hpn; typedef struct heapNode* hpp; typedef struct heapManager_simple hsimple; struct heapNode{ int value,rank; hpp child,sibling,parent; }; inline hpp hnalloc(){ return malloc(sizeof hpn); } struct heapManager_simple{ hpp root,min,rank[22]; inline hpp makeHeap(int n){ root=min=hnalloc(); memset(root,0,sizeof root); root->value=n; rank[0]=root; } inline hpp extract_min(){ return min; } inline void assign(hpp rt){//this method requires a O(log n) search for the min root memset(rank,0,sizeof rank); root=min=rt; while(rt){ rank[rt->rank]=rt; if(rt->value < min->value) min=y; rt=rt->sibling; } } inline hpp link(hpp a,hpp b){ if(b->value < a->value) std::swap(a,b); ++a->rank; b->parent=a; b->sibling=a->child; a->child=b; return a; } inline hpp merge(hpp A){ hpp b=A; while(A){ A=A->sibling; while(rank[b->rank]){ b=link(rank[b->rank],b); if(!min || min->value > b->value) min=b; rank[b->rank]=NULL; } } return root; } inline void gen_sibling(){ root=NULL; for(int i=21;~i;--i){ if(rank[i]){ rank[i]->sibling=root; root=rank[i]; } } } hpp insert(int n){ hpp b=hnalloc(); memset(b,0,sizeof b); b->value=n; merge(b); gen_sibling(); return b; } hpp delete_top(){ rank[min->rank]=NULL; hpp a=min->child; free(min); min=NULL; merge(a); gen_sibling(); } };
我的代码用了一种特殊的维护方法.我们知道每个子堆的大小是2rank,那么我们就可以直接用数组存不同rank的子堆,每次操作完再用gen_sibling统一生成sibling指针.用这个技巧可以省掉很多代码,而且可以简化逻辑,处理掉细节.
二项堆是严格log n的,可以可持久化,可以拿来搞K短路.时间复杂度$V\log{V}+E+K\log{k}$.
Decrease_key很好写,就和二叉堆差不多,就不写代码了.(其实是我忘记加了)
配对堆是一种自适应的可并堆.
配对堆的思想基于对于一个堆来说,树越高则效率越好(假设有堆的限制).如果变成一条链,那就已经排好序了.
配对堆的合并方法与rank值无关.从这点上来说,配对堆就好像可并堆中的Splay.
配对堆可以与Dijkstra很好地配合,时间复杂度$O(E+V\log{V})$.
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原文地址:http://www.cnblogs.com/tmzbot/p/4470349.html