图论——Dijkstra+prim算法涉及到的优先队列(二叉堆)
【0】README
0.1)为什么有这篇文章?因为 Dijkstra算法的优先队列实现 涉及到了一种新的数据结构,即优先队列(二叉堆)的操作需要更改以适应这种新的数据结构,我们暂且吧它定义为Distance, 而不是单纯的int类型;
0.2)本文源代码均为原创, int类型的优先队列(二叉堆)的操作实现,参见http://blog.csdn.net/PacosonSWJTU/article/details/49498255, (并比较他们的打印结果,很有必要)
【1】因为 Dijkstra算法的优先队列实现, 需要用到二叉堆的相关操作,但是操作的元素类型(ElementType 不是 单纯的int类型), 而是如下:
struct Distance
{
int vertexIndex; //当前顶点下标
int distance; //初始顶点到当前顶点的distance
};
【2】看个荔枝
2.1)需要特别说明的是: indexOfVertexInHeap 数组记录的是顶点vertex在 heap中的位置, 如 indexOfVertexInHeap [1] = 4;表明heap的第4个位置记录这 编号为1的vertex;
2.2)优先队列的insert和deleteMin 的执行演示(请将我的手动演示结果同我的代码打印结果做对比,经过对比,你发现它们的效果是一致的,恰好说明了我的代码的可行性):
Attention)
- A1)其实本文中的二叉堆优先队列的实现源代码和 int类型的优先队列源代码类似,只不过它们操作的数据类型不一样罢了,当然, 这只需要简单的修改即可;
- A2)打印结果在文末,可以看到,ElementType采用int 和 Distance的打印效果一样,这正证明了我们采用Distance结构体对源码的修改是无误的,相比于单纯的int 类型,只不过Distance又多了一个 顶点下标vertexIndex成员变量而已;
【3】source code + printing results
3.1)download source code:
https://github.com/pacosonTang/dataStructure-algorithmAnalysis/tree/master/chapter9/binaryHeap_dijkstra_prim
3.2)source code at a glance:(for complete code , please click the given link above)
1st file:distance.h
#include <stdio.h>
#define Error(str) printf("\n error: %s \n",str)
struct Distance;
typedef struct Distance *Distance;
struct Distance
{
int vertexIndex;
int distance;
};
Distance makeEmptyDistance();
2nd file:distance.c
#include "distance.h"
#include <malloc.h>
// allocate the memory for Distance struct
Distance makeEmptyDistance()
{
Distance element;
element = (Distance)malloc(sizeof(struct Distance));
if(!element)
{
Error("out of space ,from func makeEmptyDistance");
return NULL;
}
return element;
}
3rd file:binaryheap.h
#include <stdio.h>
#include <malloc.h>
#include "distance.h"
#define ElementType Distance
#define Error(str) printf("\n error: %s \n",str)
struct BinaryHeap;
typedef struct BinaryHeap *BinaryHeap;
void swap(ElementType x, ElementType y);
BinaryHeap initBinaryHeap(int capacity);
void insert(ElementType value, BinaryHeap bh, int*);
ElementType deleteMin(BinaryHeap, int*);
int isFull(BinaryHeap bh);
int isEmpty(BinaryHeap bh);
void percolateUp(int index, BinaryHeap bh);
void percolateDownFromOne(int index, BinaryHeap bh, int*);
void printBinaryHeap(BinaryHeap bh);
void printBinaryHeapFromZero(BinaryHeap bh);
struct BinaryHeap
{
int capacity;
int size;
ElementType *elements;
};
4th file:binaryheap.c
#include "binaryheap.h"
#include <math.h>
#define MaxInt (int)pow(2, 16)
//judge whether the BinaryHeap is full or not , also 1 or 0
int isFull(BinaryHeap bh)
{
return bh->size == bh->capacity - 1;
}
//judge whether the BinaryHeap is empty or not , also 1 or 0
int isEmpty(BinaryHeap bh)
{
return bh->size == 0;
}
// get the left child of node under index with startup 1
int leftChildFromOne(int index)
{
return index * 2;
}
void printBinaryHeap(BinaryHeap bh)
{
int i;
ElementType *temp;
if(!bh)
Error("printing execution failure, for binary heap is null, from func printBinaryHeap");
temp = bh->elements;
for(i = 1; i < bh->capacity; i++)
{
printf("\n\t heap[%d] = ", i);
if(i <= bh->size)
printf("vertex[%d] + distance[%d]", bh->elements[i]->vertexIndex+1, bh->elements[i]->distance);
else
printf("NULL");
}
printf("\n");
}
//print the binary heap who starts from index 0
void printBinaryHeapFromZero(BinaryHeap bh)
{
int i;
ElementType *temp;
if(!bh)
Error("printing execution failure, for binary heap is null, from func printBinaryHeap");
temp = bh->elements;
for(i = 0; i < bh->capacity; i++)
{
printf("\n\t index[%d] = ", i);
if(i < bh->size)
printf("%d", bh->elements[i]->distance);
else
printf("NULL");
}
printf("\n");
}
void swap(ElementType x, ElementType y)
{
struct Distance temp;
temp = *x;
*x = *y;
*y = temp;
}
ElementType deleteMin(BinaryHeap bh, int* heapIndexRecord)
{
ElementType minimum;
ElementType *data;
if(isEmpty(bh))
{
Error("failed deleting minimum , for the BinaryHeap is empty, from func deleteMin !");
return NULL;
}
data = bh->elements;
minimum = data[1];
swap(data[1], data[bh->size]);
bh->size-- ; // size-- occurs prior to percolateDownFromOne
percolateDownFromOne(1, bh, heapIndexRecord) ;
return minimum;
}
// percolating down the element when its value is greater than children (minimal heap)
//Attention: all of bh->elements starts from index 1
void percolateDownFromOne(int index, BinaryHeap bh, int* heapIndexRecord)
{
ElementType *data;
int size;
struct Distance temp;
int child;
data = bh->elements;
size = bh->size;
for(temp = *data[index]; leftChildFromOne(index) <= size; index = child)
{
child = leftChildFromOne(index);
if(child < size && data[child]->distance > data[child+1]->distance)
child++;
if(temp.distance > data[child]->distance)
{
*data[index] = *data[child];
heapIndexRecord[bh->elements[index]->vertexIndex] = index; //update the heapIndexRecord
}
else
break;
}
*data[index] = temp;
heapIndexRecord[bh->elements[index]->vertexIndex] = index; //update the heapIndexRecord
}
// Attention, the index of the heap starts from 1
// return the index the element inserted into the binary heap
void insert(ElementType value, BinaryHeap bh, int* heapIndexRecord)
{
int i;
if(isFull(bh))
{
Error("failed insertion , for the BinaryHeap is full, from func insert!");
return ;
}
if(!isEmpty(bh))
for(i = ++bh->size; bh->elements[i/2]->distance > value->distance; i /= 2)
{
//copyElement(bh->elements[i/2], bh->elements[i]);
*bh->elements[i] = *bh->elements[i/2];
heapIndexRecord[bh->elements[i]->vertexIndex] = i; //update the heapIndexRecord
}
else
i = ++bh->size;
*bh->elements[i] = *value;
heapIndexRecord[bh->elements[i]->vertexIndex] = i; //update the heapIndexRecord
}
BinaryHeap initBinaryHeap(int capacity)
{
BinaryHeap bh;
ElementType *temp;
int i;
bh = (BinaryHeap)malloc(sizeof(struct BinaryHeap));
if(!bh) {
Error("out of space, from func initBinaryHeap");
return NULL;
}
bh->capacity = capacity;
bh->size = 0;
temp = (ElementType*)malloc(capacity * sizeof(Distance));
if(!temp) {
Error("out of space, from func initBinaryHeap");
return NULL;
}
bh->elements = temp;
for(i=0; i < capacity; i++)
{
temp[i] = (ElementType)malloc(sizeof(struct Distance));
if(!temp[i]) {
Error("out of space, from func initBinaryHeap");
return NULL;
}
}
return bh;
}
// allocate the memory for storing index of vertex in heap and let every element -1
int *makeEmptyArray(int size)
{
int *array;
int i;
array = (int*)malloc(size * sizeof(int));
if(!array)
{
Error("out of space ,from func makeEmptyArray");
return NULL;
}
for(i=0; i<size; i++)
array[i] = -1;
return array;
}
void printIndexOfVertexInHeap(int size, int *array)
{
int i;
for(i=0; i<size; i++)
printf("\tindexOfVertexInHeap[%d] = %d\n", i+1, array[i]);
}
int main()
{
int data[] = {85, 80, 40, 30, 10, 70, 110}; // P141
int buildHeapData[] = {150, 80, 40, 30, 10, 70, 110, 100, 20, 90, 60, 50, 120, 140, 130};
BinaryHeap bh;
int size;
int i;
int capacity;
Distance tempDisStruct;
int *indexOfVertexInHeap;
printf("\n\t=== test for inserting the binary heap with {85, 80, 40, 30, 10, 70, 110} in turn ===\n");
capacity = 14;
bh = initBinaryHeap(capacity);
size = 7;
tempDisStruct = makeEmptyDistance();
indexOfVertexInHeap = makeEmptyArray(size);
for(i = 0; i < size; i++)
{
tempDisStruct->distance = data[i];
tempDisStruct->vertexIndex = i;
insert(tempDisStruct, bh, indexOfVertexInHeap);
}
printBinaryHeap(bh);
printIndexOfVertexInHeap(bh->size, indexOfVertexInHeap);
printf("\n\t=== test for inserting the binary heap with element {100, 20, 90} in turn ===\n");
tempDisStruct->distance = 100;
tempDisStruct->vertexIndex = size;
insert(tempDisStruct, bh, indexOfVertexInHeap);
printBinaryHeap(bh);
tempDisStruct->distance = 20;
tempDisStruct->vertexIndex = size+1;
insert(tempDisStruct, bh, indexOfVertexInHeap);
printBinaryHeap(bh);
tempDisStruct->distance = 90;
tempDisStruct->vertexIndex = size+2;
insert(tempDisStruct, bh, indexOfVertexInHeap);
printBinaryHeap(bh);
printIndexOfVertexInHeap(bh->size, indexOfVertexInHeap);
printf("\n\t=== test for inserting the binary heap with 5 ===\n");
tempDisStruct->distance = 5;
tempDisStruct->vertexIndex = size+3;
insert(tempDisStruct, bh, indexOfVertexInHeap);
printBinaryHeap(bh);
printf("\n\t=== test for 3 deletings towards the minimum in binary heap ===\n");
deleteMin(bh, indexOfVertexInHeap);
printBinaryHeap(bh);
deleteMin(bh, indexOfVertexInHeap);
printBinaryHeap(bh);
deleteMin(bh, indexOfVertexInHeap);
printBinaryHeap(bh);
}
3.3)printing results:
图论——Dijkstra+prim算法涉及到的优先队列(二叉堆)的更多相关文章
- POJ 3635 - Full Tank? - [最短路变形][手写二叉堆优化Dijkstra][配对堆优化Dijkstra]
题目链接:http://poj.org/problem?id=3635 题意题解等均参考:POJ 3635 - Full Tank? - [最短路变形][优先队列优化Dijkstra]. 一些口胡: ...
- PriorityBlockingQueue优先队列的二叉堆实现
转载请注明原创地址http://www.cnblogs.com/dongxiao-yang/p/6293807.html java.util.concurrent.PriorityBlockingQu ...
- 【数据结构与算法Python版学习笔记】树——利用二叉堆实现优先级队列
概念 队列有一个重要的变体,叫作优先级队列. 和队列一样,优先级队列从头部移除元素,不过元素的逻辑顺序是由优先级决定的. 优先级最高的元素在最前,优先级最低的元素在最后. 实现优先级队列的经典方法是使 ...
- 最短路径——Dijkstra算法以及二叉堆优化(含证明)
一般最短路径算法习惯性的分为两种:单源最短路径算法和全顶点之间最短路径.前者是计算出从一个点出发,到达所有其余可到达顶点的距离.后者是计算出图中所有点之间的路径距离. 单源最短路径 Dijkstra算 ...
- 《Algorithms算法》笔记:优先队列(2)——二叉堆
二叉堆 1 二叉堆的定义 堆是一个完全二叉树结构(除了最底下一层,其他层全是完全平衡的),如果每个结点都大于它的两个孩子,那么这个堆是有序的. 二叉堆是一组能够用堆有序的完全二叉树排序的元素,并在数组 ...
- 数据结构与算法——优先队列类的C++实现(二叉堆)
优先队列简单介绍: 操作系统表明上看着是支持多个应用程序同一时候执行.其实是每一个时刻仅仅能有一个进程执行,操作系统会调度不同的进程去执行. 每一个进程都仅仅能执行一个固定的时间,当超过了该时间.操作 ...
- 【算法与数据结构】二叉堆和优先队列 Priority Queue
优先队列的特点 普通队列遵守先进先出(FIFO)的规则,而优先队列虽然也叫队列,规则有所不同: 最大优先队列:优先级最高的元素先出队 最小优先队列:优先级最低的元素先出队 优先队列可以用下面几种数据结 ...
- 优先队列之二叉堆与d-堆
二叉堆简介 平时所说的堆,若没加任何修饰,一般就是指二叉堆.同二叉树一样,堆也有两个性质,即结构性和堆序性.正如AVL树一样,对堆的以此操作可能破坏者两个性质中的一个,因此,堆的操作必须要到堆的所有性 ...
- 纯数据结构Java实现(6/11)(二叉堆&优先队列)
堆其实也是树结构(或者说基于树结构),一般可以用堆实现优先队列. 二叉堆 堆可以用于实现其他高层数据结构,比如优先队列 而要实现一个堆,可以借助二叉树,其实现称为: 二叉堆 (使用二叉树表示的堆). ...
随机推荐
- android intent打开各种文件的方法
android intent打开各种文件的方法 1./** * 检测是否安装了某个软件 * * @param pkgName "com.bill99.kuaishua" ...
- C#的多线程——使用async和await来完成异步编程(Asynchronous Programming with async and await)
https://msdn.microsoft.com/zh-cn/library/mt674882.aspx 侵删 更新于:2015年6月20日 欲获得最新的Visual Studio 2017 RC ...
- 【java初学者】理解,从面向过程 到 面向对象,面向接口,面向切面
http://blog.csdn.net/ssh159/article/details/52516986
- JQuery插件开发格式
原地址 一.jQuery扩展 1.$.extend(object) 类似于.Net的扩展方法,用于扩展jQuery.然后就可以用$.的方式调用. $(function(){ $.extend({ fu ...
- virtualenv 环境安装
# Python 2.7.6:wget http://python.org/ftp/python/2.7.6/Python-2.7.6.tar.xztar xf Python-2.7.6.tar. ...
- display:inline-block;在各浏览器下的问题和终极兼容办法
display:inline-block;在各浏览器下的问题和终极兼容办法 一.IE 5.5.6.7 .8(Q)中display:inline-block;失效 兼容办法: IE 5.5.6.7 .8 ...
- JS方面重点摘要(一)
1.获取样式(1)style只能获取到行间样式的属性(2)火狐getComputedStyle(obj,null)[attr],IE:obj.currentStyle[attr] 2.ready.on ...
- log4j教程 6、Logger方法
Logger类提供了多种方法来处理日志活动. Logger类不允许实例化一个新的记录器实例,但它提供了两个静态方法获得一个 Logger 对象: public static Logger getRoo ...
- 最简单简洁高效的Json数据解析
一.无图无真相 二.主要代码 1.导入jar包 拷贝fastjson.jar包到projectlibs包下 2.封装工具类JsonUtil.java package com.example.parse ...
- 编译和安装在Windows上橡胶树 (Compiling and Installing Yate on Windows)
编译和安装在Windows上橡胶树 有两种方法来安装橡胶树下窗口: 下载并安装橡胶树 下载后页面设置. 另一个选择是下载橡胶树从SVN并编译它. 内容 ( 隐藏] 1 安装使用设置橡胶树 2 ...