quickclu.cpp

基本的k-means聚类算法c++实现

#include <iostream.h>
#include "KMeans.h"
#include <stdlib.h>
#include <fstream.h>
#include <time.h>
#include <math.h>
#include <string.h>

int main(int argc, char* argv[])
{
	int i,j;

	int number = atoi(argv[2]);
	int dimension = atoi(argv[3]);
	int k = atoi(argv[4]);
	int runtime = atoi(argv[5]);
	int randomNum = atoi(argv[6]);

	if(randomNum == -1)
		randomNum = time(NULL);
	//int randomNum = clock() % 1024;

	cout << endl;
	cout << "Point Num     : " << number << endl;
	cout << "Dimension Num : " << dimension << endl;
	cout << "k             : " << k << endl;
	cout << "Run Time      : " << runtime << endl;
	cout << "Random Number : " << randomNum << endl;
	cout << "Input File    : " << argv[7] << endl;

	ifstream input(argv[7]);

	double** data = new double*[number];

	for(i = 0; i < number; i++)
	{
		data[i] = new double[dimension];
		for(j = 0; j < dimension; j++)
			input >> data[i][j];
	}

	double** solution = new double*[k];
	for(i = 0; i < k; i++)
		solution[i] = new double[dimension];

	//int startTime = clock();
	int startTime = time(NULL);

	if(!strcmp(argv[1], "-s"))
	{
		cout << "Cluster Type  : Standard" << endl;
		KMeans kmeans(data, number, dimension);

		kmeans.Cluster(solution, k, randomNum, runtime);
	}

	if(!strcmp(argv[1], "-a"))
	{
		cout << "Cluster Type  : Accelerated" << endl;
		KMeans kmeans(data, number, dimension);
		kmeans.AccCluster(solution, k, randomNum, runtime);
	}
	cout << "Time : " << time(NULL) - startTime << endl;
	//cout << "Time : " << (double)(clock() - startTime)/CLOCKS_PER_SEC << endl;


	for(i = 0; i < number; i++)
		delete [] data[i];
	delete [] data;

	for(i = 0; i < k; i++)
		delete [] solution[i];
	delete [] solution;

	return 0;
}