streamcluster_optimized.cpp

/*
 * Copyright (C) 2008 Princeton University
 * All rights reserved.
 * Authors: Jia Deng, Gilberto Contreras
 *
 * streamcluster - Online clustering algorithm
 *
 */

/*
 * Modified by Ioannis E. Venetis for use as an assignment in the course:
 * 
 * Parallel Computing
 * Computer Engineering and Informatics Department
 * University of Patras, Greece
 */
#include <stdio.h>
#include <iostream>
#include <fstream>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <math.h>
#include <sys/resource.h>
#include <sys/time.h>
#include <limits.h>
#include <omp.h>

using namespace std;

#define MAXNAMESIZE 1024 // max filename length
#define SEED 1
/* increase this to reduce probability of random error */
/* increasing it also ups running time of "speedy" part of the code */
/* SP = 1 seems to be fine */
#define SP 1 // number of repetitions of speedy must be >=1

/* higher ITER --> more likely to get correct # of centers */
/* higher ITER also scales the running time almost linearly */
#define ITER 3 // iterate ITER* k log k times; ITER >= 1

#define CACHE_LINE 32 // cache line in byte

/* this structure represents a point */
/* these will be passed around to avoid copying coordinates */
typedef struct {
	float weight;
	float *coord;
	long assign;  /* number of point where this one is assigned */
	float cost;  /* cost of that assignment, weight*distance */
} Point;

/* this is the array of points */
typedef struct {
	long num; /* number of points; may not be N if this is a sample */
	int dim;  /* dimensionality */
	Point *p; /* the array itself */
} Points;

static bool *switch_membership; //whether to switch membership in pgain
static bool* is_center; //whether a point is a center
static int* center_table; //index table of centers

float dist ( Point p1, Point p2, int dim );

/******************************************************************************/

int isIdentical ( float *i, float *j, int D )
// tells whether two points of D dimensions are identical
{
	int a = 0;
	int equal = 1;
	while ( equal && a < D ) {
		if ( i[a] != j[a] ) equal = 0;
		else a++;
	}
	if ( equal ) return 1;
	else return 0;

}

/******************************************************************************/

/* shuffle points into random order */
void shuffle ( Points *points )
{
	long i, j;
	Point temp; 

	for ( i=0; i<points->num-1; i++ ) {
		j= ( lrand48() % ( points->num - i ) ) + i;
		temp = points->p[i];
		points->p[i] = points->p[j];
		points->p[j] = temp;
	}
}

/******************************************************************************/

/* shuffle an array of integers */
void intshuffle ( int *intarray, int length )
{
	long i, j;
	int temp;
	
	for ( i=0; i<length; i++ ) {
		j= ( lrand48() % ( length - i ) ) +i;
		temp = intarray[i];
		intarray[i]=intarray[j];
		intarray[j]=temp;
	}
	
}

/******************************************************************************/

/* compute Euclidean distance squared between two points */
float dist ( Point p1, Point p2, int dim )
{
	int i;
	float result=0.0;
	#pragma omp simd reduction ( + : result )
	for ( i=0; i<dim; i++ )
		result += ( p1.coord[i] - p2.coord[i] ) * ( p1.coord[i] - p2.coord[i] );
	return ( result );
}

/******************************************************************************/

float pspeedy ( Points *points, float z, long *kcenter )
{
	static double totalcost;
	static double costs = 0;
	static int i;
	bool to_open;

	*kcenter = 1;
	
	/* create center at first point, send it to itself */
	#pragma omp simd 
	for ( int k = 0; k < points->num; k++ )    {
		float distance = dist ( points->p[k],points->p[0],points->dim );
		points->p[k].cost = distance * points->p[k].weight;
		points->p[k].assign=0;
	}
	
	
	for ( i = 1; i < points->num; i++ )  {
		to_open = ( ( float ) lrand48() / ( float ) INT_MAX ) < ( points->p[i].cost/z );
		if ( to_open )  {
			( *kcenter ) ++;
			#pragma omp parallel for shared (points) schedule (static)		
			for ( int k = 0; k < points->num; k++ )  {
				float distance = dist ( points->p[i],points->p[k],points->dim );
				if ( distance*points->p[k].weight < points->p[k].cost )  {
					points->p[k].cost = distance * points->p[k].weight;
					points->p[k].assign=i;
				}
			}
		}
	}
	
	//#pragma omp simd reduction ( +: costs )
	for ( int k = 0; k < points->num; k++ )  {
		costs += points->p[k].cost;
	}
	
		totalcost = costs + z * ( *kcenter );
	
	return ( totalcost );
}
/******************************************************************************/

/* For a given point x, find the cost of the following operation:
 * -- open a facility at x if there isn't already one there,
 * -- for points y such that the assignment distance of y exceeds dist(y, x),
 *    make y a member of x,
 * -- for facilities y such that reassigning y and all its members to x
 *    would save cost, realize this closing and reassignment.
 *
 * If the cost of this operation is negative (i.e., if this entire operation
 * saves cost), perform this operation and return the amount of cost saved;
 * otherwise, do nothing.
 */

/* numcenters will be updated to reflect the new number of centers */
/* z is the facility cost, x is the number of this point in the array
   points */
double pgain ( long x, Points *points, double z, long int *numcenters )
{
	int i;
	int number_of_centers_to_close = 0;

	static double *work_mem;
	static double gl_cost_of_opening_x;
	static int gl_number_of_centers_to_close;

	int stride = *numcenters + 2;
	//make stride a multiple of CACHE_LINE
	int cl = CACHE_LINE/sizeof ( double );
	if ( stride % cl != 0 ) {
		stride = cl * ( stride / cl + 1 );
	}
	int K = stride - 2 ; // K==*numcenters

	//my own cost of opening x
	double cost_of_opening_x = 0;

	work_mem = ( double* ) malloc ( 2 * stride * sizeof ( double ) );
	gl_cost_of_opening_x = 0;
	gl_number_of_centers_to_close = 0;

	/*
	 * For each center, we have a *lower* field that indicates
	 * how much we will save by closing the center.
	 */
	int count = 0;
	#pragma omp simd
	for ( int i = 0; i < points->num; i++ ) {
		if ( is_center[i] ) {
			center_table[i] = count++;
		}
	}
	work_mem[0] = 0;

	//now we finish building the table. clear the working memory.

	memset ( switch_membership, 0, points->num * sizeof ( bool ) );
	memset ( work_mem, 0, stride*sizeof ( double ) );
	memset ( work_mem+stride,0,stride*sizeof ( double ) );
	//my *lower* fields
	double* lower = &work_mem[0];
	//global *lower* fields
	double* gl_lower = &work_mem[stride];
	#pragma omp parallel for reduction(+ : cost_of_opening_x)
	for ( i = 0; i < points->num; i++ ) {
		float x_cost = dist ( points->p[i], points->p[x], points->dim ) * points->p[i].weight;
		float current_cost = points->p[i].cost;

		if ( x_cost < current_cost ) {

			// point i would save cost just by switching to x
			// (note that i cannot be a median,
			// or else dist(p[i], p[x]) would be 0)

			switch_membership[i] = 1;
			cost_of_opening_x += x_cost - current_cost;

		} else {

			// cost of assigning i to x is at least current assignment cost of i

			// consider the savings that i's **current** median would realize
			// if we reassigned that median and all its members to x;
			// note we've already accounted for the fact that the median
			// would save z by closing; now we have to subtract from the savings
			// the extra cost of reassigning that median and its members
			int assign = points->p[i].assign;
			
			lower[center_table[assign]] += current_cost - x_cost;
		}
	}

	// at this time, we can calculate the cost of opening a center
	// at x; if it is negative, we'll go through with opening it
	#pragma omp parallel for schedule (static) reduction ( -: cost_of_opening_x )
	for ( int i = 0; i < points->num; i++ ) {
		if ( is_center[i] ) {
			double low = z + work_mem[center_table[i]];
			gl_lower[center_table[i]] = low;
			if ( low > 0 ) {
				// i is a median, and
				// if we were to open x (which we still may not) we'd close i

				// note, we'll ignore the following quantity unless we do open x
				++number_of_centers_to_close;
				cost_of_opening_x -= low;
			}
		}
	}
	//use the rest of working memory to store the following
	work_mem[K] = number_of_centers_to_close;
	work_mem[K+1] = cost_of_opening_x;

	gl_number_of_centers_to_close = ( int ) work_mem[K];
	gl_cost_of_opening_x = z + work_mem[K+1];

	// Now, check whether opening x would save cost; if so, do it, and
	// otherwise do nothing
	
	if ( gl_cost_of_opening_x < 0 ) {
		//  we'd save money by opening x; we'll do it
		#pragma omp parallel shared (points,gl_lower,center_table,switch_membership,x)
			{ 
				# pragma omp  for  schedule (static)
		for ( int i = 0; i < points->num; i++ ) {
			bool close_center = gl_lower[center_table[points->p[i].assign]] > 0 ;
			if ( switch_membership[i] || close_center ) {
				// Either i's median (which may be i itself) is closing,
				// or i is closer to x than to its current median
				points->p[i].cost = points->p[i].weight * dist ( points->p[i], points->p[x], points->dim );
				points->p[i].assign = x;
			}
		}
			
		for ( int i = 0; i < points->num; i++ ) {
			if ( is_center[i] && gl_lower[center_table[i]] > 0 ) {
				is_center[i] = false;
			}
		}
			}
		if ( x >= 0 && x < points->num ) {
			is_center[x] = true;
		}

		*numcenters = *numcenters + 1 - gl_number_of_centers_to_close;
	} else {
		gl_cost_of_opening_x = 0;  // the value we'll return
	}

	free ( work_mem );

	return -gl_cost_of_opening_x;
}

/******************************************************************************/

/* facility location on the points using local search */
/* z is the facility cost, returns the total cost and # of centers */
/* assumes we are seeded with a reasonable solution */
/* cost should represent this solution's cost */
/* halt if there is < e improvement after iter calls to gain */
/* feasible is an array of numfeasible points which may be centers */
float pFL ( Points *points, int *feasible, int numfeasible, float z, long *k, double cost, long iter, float e )
{
	long i;
	long x;
	double change;

	change = cost;
	/* continue until we run iter iterations without improvement */
	/* stop instead if improvement is less than e */
	while ( change/cost > 1.0*e ) {
		change = 0.0;
		/* randomize order in which centers are considered */

		intshuffle ( feasible, numfeasible );
		#pragma omp simd reduction ( +: change )
		for ( i=0; i<iter; i++ ) {
			x = i%numfeasible;
			change += pgain ( feasible[x], points, z, k );
		}
		cost -= change;
	}
	return ( cost );
}

/******************************************************************************/

int selectfeasible_fast ( Points *points, int **feasible, int kmin )
{
	int numfeasible = points->num;
	if ( numfeasible > ( ITER*kmin*log ( ( double ) kmin ) ) )
		numfeasible = ( int ) ( ITER*kmin*log ( ( double ) kmin ) );
	*feasible = ( int * ) malloc ( numfeasible*sizeof ( int ) );

	float* accumweight;
	float totalweight;
	long k1 = 0;
	long k2 = numfeasible;
	float w;
	int l,r,k;

	/* not many points, all will be feasible */
	
	if ( numfeasible == points->num ) {
		
		for ( int i=k1; i<k2; i++ )
			( *feasible ) [i] = i;
		return numfeasible;
	}
	accumweight= ( float* ) malloc ( sizeof ( float ) *points->num );

	accumweight[0] = points->p[0].weight;
	totalweight=0;
	for ( int i = 1; i < points->num; i++ ) {
		accumweight[i] = accumweight[i-1] + points->p[i].weight;
	}
	totalweight=accumweight[points->num-1];

	for ( int i=k1; i<k2; i++ ) {
		w = ( lrand48() / ( float ) INT_MAX ) *totalweight;
		//binary search
		l=0;
		r=points->num-1;
		if ( accumweight[0] > w )  {
			( *feasible ) [i]=0;
			continue;
		}
		while ( l+1 < r ) {
			k = ( l+r ) /2;
			if ( accumweight[k] > w ) {
				r = k;
			} else {
				l=k;
			}
		}
		( *feasible ) [i]=r;
	}

	free ( accumweight );

	return numfeasible;
}

/******************************************************************************/

/* compute approximate kmedian on the points */
float pkmedian ( Points *points, long kmin, long kmax, long* kfinal )
{
	int i;
	double cost;
	double hiz, loz, z;

	static long k;
	static int *feasible;
	static int numfeasible;

	hiz = loz = 0.0;
	long ptDimension = points->dim;
		#pragma omp simd
	for ( long kk = 0; kk < points->num; kk++ ) {
		hiz += dist ( points->p[kk], points->p[0], ptDimension ) * points->p[kk].weight;
	}

	loz=0.0;
	z = ( hiz+loz ) /2.0;
	/* NEW: Check whether more centers than points! */
	if ( points->num <= kmax ) {
	
		/* just return all points as facilities */
		
		for ( long kk = 0; kk < points->num; kk++ ) {
			points->p[kk].assign = kk;
			points->p[kk].cost = 0;
		}
		cost = 0;
		*kfinal = k;

		return cost;
	}

	shuffle ( points );
	cost = pspeedy ( points, z, &k );

	i=0;
	/* give speedy SP chances to get at least kmin/2 facilities */
	while ( ( k < kmin ) && ( i<SP ) ) {
		cost = pspeedy ( points, z, &k );
		i++;
	}

	/* if still not enough facilities, assume z is too high */
	while ( k < kmin ) {
		if ( i >= SP ) {
			hiz=z;
			z= ( hiz+loz ) /2.0;
			i=0;
		}
		shuffle ( points );
		cost = pspeedy ( points, z, &k );
		i++;
	}

	/* now we begin the binary search for real */
	/* must designate some points as feasible centers */
	/* this creates more consistancy between FL runs */
	/* helps to guarantee correct # of centers at the end */

	numfeasible = selectfeasible_fast ( points, &feasible, kmin );
	
	for ( int i = 0; i< points->num; i++ ) {
		is_center[points->p[i].assign]= true;
	}

	while ( 1 ) {
		/* first get a rough estimate on the FL solution */
		cost = pFL ( points, feasible, numfeasible, z, &k, cost, ( long ) ( ITER*kmax*log ( ( double ) kmax ) ), 0.1 );

		/* if number of centers seems good, try a more accurate FL */
		if ( ( ( k <= ( 1.1 ) *kmax ) && ( k >= ( 0.9 ) *kmin ) ) || ( ( k <= kmax+2 ) && ( k >= kmin-2 ) ) ) {

			/* may need to run a little longer here before halting without
			improvement */
			cost = pFL ( points, feasible, numfeasible, z, &k, cost, ( long ) ( ITER*kmax*log ( ( double ) kmax ) ), 0.001 );
		}

		if ( k > kmax ) {
			/* facilities too cheap */
			/* increase facility cost and up the cost accordingly */
			loz = z;
			z = ( hiz+loz ) /2.0;
			cost += ( z-loz ) *k;
		}
		if ( k < kmin ) {
			/* facilities too expensive */
			/* decrease facility cost and reduce the cost accordingly */
			hiz = z;
			z = ( hiz+loz ) /2.0;
			cost += ( z-hiz ) *k;
		}

		/* if k is good, return the result */
		/* if we're stuck, just give up and return what we have */
		if ( ( ( k <= kmax ) && ( k >= kmin ) ) || ( ( loz >= ( 0.999 ) *hiz ) ) ) {
			break;
		}
	}

	//clean up...
	free ( feasible );
	*kfinal = k;

	return cost;
}

/******************************************************************************/

/* compute the means for the k clusters */
int contcenters ( Points *points )
{
	long i, ii;
	float relweight;

	for ( i=0; i<points->num; i++ ) {
		/* compute relative weight of this point to the cluster */
		if ( points->p[i].assign != i ) {
			relweight=points->p[points->p[i].assign].weight + points->p[i].weight;
			relweight = points->p[i].weight / relweight;
			for ( ii=0; ii<points->dim; ii++ ) {
				points->p[points->p[i].assign].coord[ii] *= 1.0-relweight;
				points->p[points->p[i].assign].coord[ii] += points->p[i].coord[ii]*relweight;
			}
			points->p[points->p[i].assign].weight += points->p[i].weight;
		}
	}

	return 0;
}

/******************************************************************************/

/* copy centers from points to centers */
void copycenters ( Points *points, Points* centers, long* centerIDs, long offset )
{
	long i;
	long k;

	bool *is_a_median = ( bool * ) calloc ( points->num, sizeof ( bool ) );

	/* mark the centers */
	#pragma omp simd
	for ( i = 0; i < points->num; i++ ) {
		is_a_median[points->p[i].assign] = 1;
	}

	k=centers->num;
	
	/* count how many  */

	for ( i = 0; i < points->num; i++ ) {
		if ( is_a_median[i] ) {
			memcpy ( centers->p[k].coord, points->p[i].coord, points->dim * sizeof ( float ) );
			centers->p[k].weight = points->p[i].weight;
			centerIDs[k] = i + offset;
			k++;
		}
	}

	centers->num = k;

	free ( is_a_median );
}

/******************************************************************************/

class PStream {
public:
	virtual size_t read ( float* dest, int dim, int num ) = 0;
	virtual int ferror() = 0;
	virtual int feof() = 0;
	virtual ~PStream() {
	}
};

//synthetic stream
class SimStream : public PStream {
public:
	SimStream ( long n_ ) {
		n = n_;
	}
	size_t read ( float* dest, int dim, int num ) {
		size_t count = 0;
		
		for ( int i = 0; i < num && n > 0; i++ ) {
			for ( int k = 0; k < dim; k++ ) {
				dest[i*dim + k] = lrand48() / ( float ) INT_MAX;
			}
			n--;
			count++;
		}
		return count;
	}
	int ferror() {
		return 0;
	}
	int feof() {
		return n <= 0;
	}
	~SimStream() {
	}
private:
	long n;
};

class FileStream : public PStream {
public:
	FileStream ( char* filename ) {
		fp = fopen ( filename, "rb" );
		if ( fp == NULL ) {
			fprintf ( stderr,"error opening file %s\n.",filename );
			exit ( 1 );
		}
	}
	size_t read ( float* dest, int dim, int num ) {
		return std::fread ( dest, sizeof ( float ) *dim, num, fp );
	}
	int ferror() {
		return std::ferror ( fp );
	}
	int feof() {
		return std::feof ( fp );
	}
	~FileStream() {
		fprintf ( stderr,"closing file stream\n" );
		fclose ( fp );
	}
private:
	FILE* fp;
};

/******************************************************************************/

void outcenterIDs ( Points* centers, long* centerIDs, char* outfile )
{
	FILE* fp = fopen ( outfile, "w" );
	if ( fp==NULL ) {
		fprintf ( stderr, "error opening %s\n",outfile );
		exit ( 1 );
	}
	int* is_a_median = ( int* ) calloc ( sizeof ( int ), centers->num );
       	
                for ( int i =0 ; i< centers->num; i++ ) {
		is_a_median[centers->p[i].assign] = 1;
	}
	
	for ( int i = 0; i < centers->num; i++ ) {
		if ( is_a_median[i] ) {
			fprintf ( fp, "%ld\n", centerIDs[i] );
			fprintf ( fp, "%lf\n", centers->p[i].weight );
			
			for ( int k = 0; k < centers->dim; k++ ) {
				fprintf ( fp, "%lf ", centers->p[i].coord[k] );
			}
			fprintf ( fp,"\n\n" );
		}
	}
	fclose ( fp );
}

/******************************************************************************/

void streamCluster ( PStream* stream, long kmin, long kmax, int dim, long chunksize, long centersize, char* outfile )
{

	float* block = ( float* ) malloc ( chunksize*dim*sizeof ( float ) );
	float* centerBlock = ( float* ) malloc ( centersize*dim*sizeof ( float ) );
	long* centerIDs = ( long* ) malloc ( centersize*dim*sizeof ( long ) );
	double  ElapsedTime = 0.0;
	struct timeval Start, End;

	if ( block == NULL ) {
		fprintf ( stderr,"not enough memory for a chunk!\n" );
		exit ( 1 );
	}
	
			
	Points points;
	points.dim = dim;
	points.num = chunksize;
	points.p = ( Point * ) malloc ( chunksize*sizeof ( Point ) );
	
		
	for ( int i = 0; i < chunksize; i++ ) {
		points.p[i].coord = &block[i*dim];
	}
	
	Points centers;
	centers.dim = dim;
	centers.p =
	     ( Point * ) malloc ( centersize*sizeof ( Point ) );
	centers.num = 0;
	#pragma omp simd
	for ( int i = 0; i< centersize; i++ ) {
		centers.p[i].coord = &centerBlock[i*dim];
		centers.p[i].weight = 1.0;
	}
		
	long IDoffset = 0;
	long kfinal;
	while ( 1 ) {

		size_t numRead  = stream->read ( block, dim, chunksize );
		fprintf ( stderr,"read %lu points\n",numRead );

		if ( stream->ferror() || ( ( numRead < ( unsigned int ) chunksize ) && ( !stream->feof() ) ) ) {
			fprintf ( stderr, "error reading data!\n" );
			exit ( 1 );
		}

		points.num = numRead;
		for ( int i = 0; i < points.num; i++ ) {
			points.p[i].weight = 1.0;
		}

		switch_membership = ( bool* ) malloc ( points.num*sizeof ( bool ) );
		is_center = ( bool* ) calloc ( points.num,sizeof ( bool ) );
		center_table = ( int* ) malloc ( points.num*sizeof ( int ) );

		//fprintf(stderr,"center_table = 0x%08x\n",(int)center_table);
		//fprintf(stderr,"is_center = 0x%08x\n",(int)is_center);

		gettimeofday(&Start, NULL);

		pkmedian ( &points, kmin, kmax, &kfinal );

		//fprintf(stderr,"finish local search\n");
		contcenters ( &points ); /* sequential */
		if ( kfinal + centers.num > centersize ) {
			//here we don't handle the situation where # of centers gets too large.
			fprintf ( stderr,"oops! no more space for centers\n" );
			exit ( 1 );
		}

		copycenters ( &points, &centers, centerIDs, IDoffset ); /* sequential */

		gettimeofday(&End, NULL);

		ElapsedTime += (double)(End.tv_sec * 1000000 + End.tv_usec - (Start.tv_sec * 1000000 + Start.tv_usec))/1000000.0;

		IDoffset += numRead;

		free ( is_center );
		free ( switch_membership );
		free ( center_table );

		if ( stream->feof() ) {
			break;
		}
	}

	//finally cluster all temp centers
	switch_membership = ( bool* ) malloc ( centers.num*sizeof ( bool ) );
	is_center = ( bool* ) calloc ( centers.num,sizeof ( bool ) );
	center_table = ( int* ) malloc ( centers.num*sizeof ( int ) );

	gettimeofday(&Start, NULL);

	pkmedian ( &centers, kmin, kmax ,&kfinal );
	contcenters ( &centers );
	
	gettimeofday(&End, NULL);

	ElapsedTime += (double)(End.tv_sec * 1000000 + End.tv_usec - (Start.tv_sec * 1000000 + Start.tv_usec))/1000000.0;

	printf("Time elapsed was %.6f seconds\n", ElapsedTime);

	outcenterIDs ( &centers, centerIDs, outfile );
}

/******************************************************************************/

int main ( int argc, char **argv )
{
	char *outfilename = new char[MAXNAMESIZE];
	char *infilename = new char[MAXNAMESIZE];
	long kmin, kmax, n, chunksize, clustersize;
	int dim;

	if ( argc != 9 ) {
		fprintf ( stderr,"usage: %s k1 k2 d n chunksize clustersize infile outfile\n", argv[0] );
		fprintf ( stderr,"  k1:          Min. number of centers allowed\n" );
		fprintf ( stderr,"  k2:          Max. number of centers allowed\n" );
		fprintf ( stderr,"  d:           Dimension of each data point\n" );
		fprintf ( stderr,"  n:           Number of data points\n" );
		fprintf ( stderr,"  chunksize:   Number of data points to handle per step\n" );
		fprintf ( stderr,"  clustersize: Maximum number of intermediate centers\n" );
		fprintf ( stderr,"  infile:      Input file (if n<=0)\n" );
		fprintf ( stderr,"  outfile:     Output file\n" );
		fprintf ( stderr,"\n" );
		fprintf ( stderr, "if n > 0, points will be randomly generated instead of reading from infile.\n" );
		exit ( 1 );
	}

	kmin = atoi ( argv[1] );
	kmax = atoi ( argv[2] );
	dim = atoi ( argv[3] );
	n = atoi ( argv[4] );
	chunksize = atoi ( argv[5] );
	clustersize = atoi ( argv[6] );
	strcpy ( infilename, argv[7] );
	strcpy ( outfilename, argv[8] );
			
	
	srand48 ( SEED );
	PStream* stream;
	if ( n > 0 ) {
		stream = new SimStream ( n );
	} else {
		stream = new FileStream ( infilename );
	}

	streamCluster ( stream, kmin, kmax, dim, chunksize, clustersize, outfilename );

	delete stream;

	return 0;
}