k_means.h

#ifndef __K_MEANS_H
#define __K_MEANS_H

#include <stdlib.h>
#include <assert.h>
#include <stdio.h>
#include<mpi.h>

/*<>Measures the Euclidean distance between two vectors v1, v2 with dim components<>*/
float euclidDistance(int dim,  	//no. dimensions 
								float *v1,   //[numdims] 
							    float *v2);  //[numdims]

/*<>Returns the index of the cluster that is closest to the given vector<>*/
int getNearestClusterIndex(int   numClusters, 	//no. clusters 
											int   numCoords,   	//no. coordinates 
											float  *vector,      //[numCoords] 
											float **clusters);    //[numClusters][numCoords]

/*<>Computes K clusters and stores them in **clusters based on vectorial group 
**vectors and the limit - maximun number of algorithm iterations allowed<>*/
int k_means(float    **vectors,     			 //in: [numVectors][numDims]
					 int        numDims,   				 //num of coordinates in vector 
					 int        numVectors,   
					 int        numClusters, 
					 float      limit,   			 	 //max num of iterations	
					 int       *vectorToClusterRelevance, //out: [numVectors] 
					 float    **clusters,    			 //out: [numClusters][numDims] 
					 MPI_Comm   comm);



#endif //__K_MEANS_H