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255 lines
10 KiB
C
255 lines
10 KiB
C
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/*****************************************************************************/
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/*IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. */
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/*By downloading, copying, installing or using the software you agree */
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/*to this license. If you do not agree to this license, do not download, */
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/*install, copy or use the software. */
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/* */
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/* */
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/*Copyright (c) 2005 Northwestern University */
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/*All rights reserved. */
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/*Redistribution of the software in source and binary forms, */
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/*with or without modification, is permitted provided that the */
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/*following conditions are met: */
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/* */
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/*1 Redistributions of source code must retain the above copyright */
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/* notice, this list of conditions and the following disclaimer. */
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/* */
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/*2 Redistributions in binary form must reproduce the above copyright */
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/* notice, this list of conditions and the following disclaimer in the */
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/* documentation and/or other materials provided with the distribution.*/
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/* */
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/*3 Neither the name of Northwestern University nor the names of its */
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/* contributors may be used to endorse or promote products derived */
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/* from this software without specific prior written permission. */
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/* */
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/*THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ``AS */
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/*IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED */
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/*TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, NON-INFRINGEMENT AND */
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/*FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL */
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/*NORTHWESTERN UNIVERSITY OR ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, */
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/*INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES */
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/*(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR */
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/*SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) */
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/*HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, */
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/*STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN */
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/*ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE */
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/*POSSIBILITY OF SUCH DAMAGE. */
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/******************************************************************************/
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/*************************************************************************/
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/** File: example.c **/
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/** Description: Takes as input a file: **/
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/** ascii file: containing 1 data point per line **/
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/** binary file: first int is the number of objects **/
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/** 2nd int is the no. of features of each **/
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/** object **/
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/** This example performs a fuzzy c-means clustering **/
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/** on the data. Fuzzy clustering is performed using **/
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/** min to max clusters and the clustering that gets **/
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/** the best score according to a compactness and **/
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/** separation criterion are returned. **/
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/** Author: Wei-keng Liao **/
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/** ECE Department Northwestern University **/
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/** email: wkliao@ece.northwestern.edu **/
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/** **/
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/** Edited by: Jay Pisharath **/
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/** Northwestern University. **/
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/** **/
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/** ================================================================ **/
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/** **/
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/** Edited by: Sang-Ha Lee **/
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/** University of Virginia **/
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/** **/
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/** Description: No longer supports fuzzy c-means clustering; **/
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/** only regular k-means clustering. **/
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/** Simplified for main functionality: regular k-means **/
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/** clustering. **/
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/** **/
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/*************************************************************************/
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include <limits.h>
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#include <math.h>
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#include <sys/types.h>
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#include <fcntl.h>
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#include <omp.h>
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#include "getopt.h"
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#include "kmeans.h"
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extern double wtime(void);
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/*---< usage() >------------------------------------------------------------*/
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void usage(char *argv0)
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{
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char *help =
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"Usage: %s [switches] -i filename\n"
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" -i filename : file containing data to be clustered\n"
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" -b :input file is in binary format\n"
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" -k : number of clusters (default is 8) \n"
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" -t threshold : threshold value\n";
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fprintf(stderr, help, argv0);
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exit(-1);
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}
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/*---< main() >-------------------------------------------------------------*/
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int main(int argc, char **argv)
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{
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int opt;
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extern char *optarg;
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extern int optind;
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int nclusters = 5;
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char *filename = 0;
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float *buf;
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float **attributes;
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float **cluster_centres = NULL;
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int i, j;
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int numAttributes;
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int numObjects;
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char line[1024];
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int isBinaryFile = 0;
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int nloops;
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float threshold = 0.001;
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double timing;
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while ((opt = getopt(argc, argv, "i:k:t:b")) != EOF)
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{
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switch (opt)
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{
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case 'i':
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filename = optarg;
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break;
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case 'b':
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isBinaryFile = 1;
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break;
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case 't':
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threshold = atof(optarg);
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break;
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case 'k':
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nclusters = atoi(optarg);
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break;
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case '?':
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usage(argv[0]);
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break;
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default:
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usage(argv[0]);
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break;
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}
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}
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if (filename == 0)
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usage(argv[0]);
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numAttributes = numObjects = 0;
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/* from the input file, get the numAttributes and numObjects ------------*/
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if (isBinaryFile)
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{
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int infile;
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if ((infile = open(filename, O_RDONLY, "0600")) == -1)
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{
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fprintf(stderr, "Error: no such file (%s)\n", filename);
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exit(1);
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}
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read(infile, &numObjects, sizeof(int));
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read(infile, &numAttributes, sizeof(int));
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/* allocate space for attributes[] and read attributes of all objects */
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buf = (float *)malloc(numObjects * numAttributes * sizeof(float));
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attributes = (float **)malloc(numObjects * sizeof(float *));
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attributes[0] = (float *)malloc(numObjects * numAttributes * sizeof(float));
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for (i = 1; i < numObjects; i++)
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attributes[i] = attributes[i - 1] + numAttributes;
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read(infile, buf, numObjects * numAttributes * sizeof(float));
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close(infile);
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}
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else
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{
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FILE *infile;
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if ((infile = fopen(filename, "r")) == NULL)
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{
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fprintf(stderr, "Error: no such file (%s)\n", filename);
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exit(1);
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}
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while (fgets(line, 1024, infile) != NULL)
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if (strtok(line, " \t\n") != 0)
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numObjects++;
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rewind(infile);
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while (fgets(line, 1024, infile) != NULL)
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{
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if (strtok(line, " \t\n") != 0)
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{
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/* ignore the id (first attribute): numAttributes = 1; */
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while (strtok(NULL, " ,\t\n") != NULL)
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numAttributes++;
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break;
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}
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}
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/* allocate space for attributes[] and read attributes of all objects */
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buf = (float *)malloc(numObjects * numAttributes * sizeof(float));
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attributes = (float **)malloc(numObjects * sizeof(float *));
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attributes[0] = (float *)malloc(numObjects * numAttributes * sizeof(float));
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for (i = 1; i < numObjects; i++)
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attributes[i] = attributes[i - 1] + numAttributes;
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rewind(infile);
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i = 0;
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while (fgets(line, 1024, infile) != NULL)
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{
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if (strtok(line, " \t\n") == NULL)
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continue;
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for (j = 0; j < numAttributes; j++)
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{
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buf[i] = atof(strtok(NULL, " ,\t\n"));
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i++;
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}
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}
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fclose(infile);
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}
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nloops = 1;
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printf("I/O completed\n");
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memcpy(attributes[0], buf, numObjects * numAttributes * sizeof(float));
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timing = omp_get_wtime();
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for (i = 0; i < nloops; i++)
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{
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cluster_centres = NULL;
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cluster(numObjects,
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numAttributes,
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attributes, /* [numObjects][numAttributes] */
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nclusters,
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threshold,
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&cluster_centres);
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}
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timing = omp_get_wtime() - timing;
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printf("number of Clusters %d\n", nclusters);
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printf("number of Attributes %d\n\n", numAttributes);
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/*printf("Cluster Centers Output\n");
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printf("The first number is cluster number and the following data is arribute value\n");
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printf("=============================================================================\n\n");
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for (i=0; i<nclusters; i++) {
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printf("%d: ", i);
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for (j=0; j<numAttributes; j++)
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printf("%f ", cluster_centres[i][j]);
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printf("\n\n");
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}*/
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printf("Time for process: %f\n", timing);
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free(attributes);
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free(cluster_centres[0]);
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free(cluster_centres);
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free(buf);
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return (0);
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}
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