最小生成树——Prim（普利姆）算法

【0】README

0.1） 本文总结于 数据结构与算法分析， 源代码均为原创， 旨在 理解Prim算法的idea 并用 源代码加以实现；

0.2）最小生成树的基础知识，参见 http://blog.csdn.net/pacosonswjtu/article/details/49947085

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【1】Prim算法相关

1.1）计算最小生成树的一种方法是使其连续地一步一步长成。在每一步， 都要吧一个节点当做根并往上加边，这样也就把相关联的顶点加到增长中的树上；

1.2）在算法中的任一时刻， 我们都可以看到一个已经添加到树上的顶点集， 而其余顶点尚未加到这颗树中。此时， 算法在每一阶段都可以通过选择边（u, v），使得（u, v）的值是所有u 在树上但v不在树上的边的值中的最小者， 而找出一个新的顶点并吧它添加到这颗树中；

1.3）具体步骤概括为：

• step1）给定一个顶点为根节点；
• step2）每一步加一条边和一个顶点； （这也迎合了 顶点个数-边个数=1 ）；

1.4）看个荔枝：



对上图的分析（Analysis）：

A1）可以看到， 其实Prim算法基本上和求最短路径的 Dijkstra算法一样， 因此和前面一样，我们对每一个顶点保留值 Dv和Pv 以及一个指标，指示该顶点是已知的还是未知的。这里，Dv是连接v 到已知顶点的最短边的权， 而 Pv则是导致Dv改变的最后的顶点。

A2）算法的其余部分一样， 唯一不同的是： ** 由于Dv的定义不同， 因此它的更新法则不一样。事实上，Prim算法的更新法则比 Dijkstra算法简单：在每一个顶点ｖ被选取后，　对于每一个与　ｖ　邻接的未知的w， Dw=min（Dw, Cw,v）；



对上图的分析（Analysis）：

A1）该算法整个的实现实际上和 Dijkstra算法的实现是一样的， 对于 Dijkstra算法分析所做的每一件事都可以用到这里。 不过要注意， Prim算法是在无向图上运行的， 因此当编写代码的时候要记住要吧每一条变都要放到两个邻接表中。

A2）**不用堆时的运行时间为O(|V|^2)， 它对于稠密图来说是最优的； 使用二叉堆的运行时间为 O（|E|log|V|）， 它对于稀疏图是一个好的界限；

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【2】source code + printing results（将我的代码打印结果 同 上图中的手动模拟的prim算法的结果进行比较，你会发现， 它们的结果完全相同，这也证实了我的代码的可行性）

2.1）download source code： https://github.com/pacosonTang/dataStructure-algorithmAnalysis/tree/master/chapter9/p237_prim

2.2）source code at a glance（for complete code , please click the given link above）：

#include "prim.h"

//allocate the memory for initializing unweighted table
WeightedTable *initWeightedTable(int size)
{
	WeightedTable* table;
	int i;

	table = (WeightedTable*)malloc(sizeof(WeightedTable) * size);
	if(!table)
	{
		Error("out of space ,from func initWeightedTable");
		return NULL;
	}

	for(i = 0; i < size; i++)
	{
		table[i] = makeEmptyWeightedTable();
		if(!table[i])
			return NULL;
	}

	return table;
} 

// allocate the memory for every element in unweighted table
WeightedTable makeEmptyWeightedTable()
{
	WeightedTable element;

	element = (WeightedTable)malloc(sizeof(struct WeightedTable));
	if(!element)
	{
		Error("out of space ,from func makeEmptyWeightedTable");
		return NULL;
	}
	element->known = 0; // 1 refers to accessed , also 0 refers to not accessed
	element->distance = MaxInt;
	element->path = -1; // index starts from 0 and -1 means the startup vertex unreaches other vertexs

	return element;
}

// 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;
}

//computing the unweighted shortest path between the vertex under initIndex and other vertexs
void prim(AdjTable* adj, int size, int startVertex, BinaryHeap bh)
{
	int adjVertex;
	int tempDistance;
	WeightedTable* table;
	int vertex;
	AdjTable temp;
	Distance tempDisStruct;
	int *indexOfVertexInHeap;
	int indexOfHeap;

	table = initWeightedTable(size);
	tempDisStruct = makeEmptyDistance();
	indexOfVertexInHeap = makeEmptyArray(size);

	tempDisStruct->distance = table[startVertex-1]->distance;
    tempDisStruct->vertexIndex = startVertex-1;
	insert(tempDisStruct, bh, indexOfVertexInHeap); // insert the (startVertex-1) into the binary heap	

	table[startVertex-1]->distance = 0;// update the distance
	table[startVertex-1]->path = 0;// update the path of starting vertex

	while(!isEmpty(bh))
	{
		vertex = deleteMin(bh, indexOfVertexInHeap).vertexIndex; // return the minimal element in binary heap
		//printBinaryHeap(bh);

 		table[vertex]->known = 1; // update the vertex as accessed, also let responding known be 1
		temp = adj[vertex]->next;
		while(temp)
		{
			adjVertex = temp->index;
			if(table[adjVertex]->known == 1) // judge whether table[adjVertex]->known is 1 or not
			{
				temp = temp->next;
				continue;
			}

			//tempDistance = table[vertex]->distance + temp->weight; // update the distance
			tempDistance = temp->weight;
			if(tempDistance < table[adjVertex]->distance)
			{
				table[adjVertex]->distance = tempDistance;
				table[adjVertex]->path = vertex; //update the path of adjVertex, also responding path evaluated as vertex							

				// key, we should judge whether adjVertex was added into the binary heap
				//if true , obviously the element has been added into the binary heap(so we can't add the element into heap once again)
				if(indexOfVertexInHeap[adjVertex] != -1)
				{
					indexOfHeap = indexOfVertexInHeap[adjVertex];
					bh->elements[indexOfHeap]->distance = tempDistance; // update the distance of corresponding vertex in binary heap
				}
				else // if not ture
				{
					tempDisStruct->distance = table[adjVertex]->distance;
					tempDisStruct->vertexIndex = adjVertex;
					insert(tempDisStruct, bh, indexOfVertexInHeap); // insert the adjVertex into the binary heap
				}
			}
			temp = temp->next;
		}
		printPrim(table, size, startVertex);
		printBinaryHeap(bh);
		printf("\n");
	}		

	printf("\n");
} 

//print unweighted table
void printPrim(WeightedTable* table, int size, int startVertex)
{
	int i;
	char *str[4] =
	{
		"vertex",
		"known",
		"distance",
		"path"
	};

	printf("\n\t === storage table related to Prim alg as follows: === ");
	printf("\n\t %6s%6s%9s%5s", str[0], str[1], str[2], str[3]);
	for(i=0; i<size; i++)
	{
		if(i != startVertex-1 && table[i]->path!=-1)
			printf("\n\t %-3d   %3d   %5d      v%-3d  ", i+1, table[i]->known, table[i]->distance, table[i]->path+1);
		else if(table[i]->path == -1)
			printf("\n\t %-3d   %3d   %5d      %-3d  ", i+1, table[i]->known, table[i]->distance, table[i]->path);
		else
			printf("\n\t *%-3d  %3d   %5d      %-3d  ", i+1, table[i]->known, table[i]->distance, 0);
	}
}

int main()
{
	AdjTable* adj;
	BinaryHeap bh;
	int size = 7;
	int capacity;
	int i;
	int j;
	int startVertex;

	int adjTable[7][7] =
	{
		{0, 2, 4, 1, 0, 0, 0},
		{2, 0, 0, 3, 10, 0, 0},
		{4, 0, 0, 2, 0, 5, 0},
		{1, 3, 2, 0, 7, 8, 4},
		{0, 10, 0, 7, 0, 0, 6},
		{0, 0, 5, 8, 0, 0, 1},
		{0, 0, 0, 4, 6, 1, 0},
	};

	printf("\n\n\t ====== test for Prim alg finding weighted shortest path from adjoining table ======\n");
	adj = initAdjTable(size);		

	printf("\n\n\t ====== the initial weighted adjoining table is as follows:======\n");
	for(i = 0; i < size; i++)
	 	for(j = 0; j < size; j++)
			if(adjTable[i][j])
				insertAdj(adj, j, i, adjTable[i][j]); // insertAdj the adjoining table over

	printAdjTable(adj, size);	

	capacity = 7;
	bh = initBinaryHeap(capacity+1);
	//conducting prim alg to find minimum spanning tree(MST)
	startVertex = 1; // you should know our index for storing vertex starts from 0
	prim(adj, size, startVertex, bh);	

	return 0;
} 

2.3）printing results：