Merge pull request #11 from karthikmurakonda/testing-kmeans

added kmeans2

iPDC/inc/Kmeans2.h

@@ -0,0 +1,3 @@
+int *getRandoms(int lower, int upper, int count);
+long double distance(struct Point* A, struct Point* B);
+void Kmeans2(struct data_frame *df);

iPDC/kmeans.csv

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iPDC/plot_kmeans2.py

@@ -0,0 +1,56 @@
+# 0 : 50.284426, 65451.237705
+# 1 : 50.370104, 65476.164948
+# 2 : 50.302515, 65464.320755
+
+import csv
+import numpy as np
+import matplotlib.pyplot as plt
+from sklearn import preprocessing
+x=[]
+y=[]
+x1=[]
+y1=[]
+x2=[]
+y2=[]
+with open('kmeans.csv', mode ='r') as file:
+    csvFile = csv.reader(file)
+    for lines in csvFile:
+        #print(lines)
+        if(int(lines[2])==0):
+            x.append(float(lines[0]))
+            y.append(float(lines[1]))
+        elif(int(lines[2])==1):
+            x1.append(float(lines[0]))
+            y1.append(float(lines[1]))
+        else:
+            x2.append(float(lines[0]))
+            y2.append(float(lines[1]))
+
+x.append(50.284426)
+y.append(65451.237705)
+x1.append(50.370104)
+y1.append(65476.164948)
+x2.append(50.302515)
+y2.append(65464.320755)
+
+x_array = np.array(x+x1+x2)
+y_array = np.array(y+y1+y2)
+# x1_array = np.array(x1)
+# y1_array = np.array(y1)
+# x2_array = np.array(x2)
+# y2_array = np.array(y2)
+
+x_arr = preprocessing.normalize([x_array])
+y_arr = preprocessing.normalize([y_array])
+
+# x1_arr = preprocessing.normalize([x1_array])
+# y1_arr = preprocessing.normalize([y1_array])
+
+# x2_arr = preprocessing.normalize([x2_array])
+# y2_arr = preprocessing.normalize([y2_array])
+
+plt.scatter(x_arr, y_arr)
+# plt.scatter(x1_arr, y1_arr)
+# plt.scatter(x2_arr, y2_arr)
+
+plt.show()

iPDC/src/Kmeans2.c

@@ -0,0 +1,204 @@
+#include "parser.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <string.h>
+#include <stdbool.h>
+
+struct Point
+{
+    long double x, y;    // coordinates
+    int cluster;         // no default cluster
+    long double minDist; // default infinite dist to nearest cluster
+};
+
+int count = 0;
+struct Point *P;
+
+long double distance(struct Point* A, struct Point* B)
+{
+    return (((A->x - B->x) * (A->x - B->x)) + ((A->y - B->y) * (A->y - B->y)));
+}
+
+int *getRandoms(int lower, int upper, int count)
+{
+    srand(time(0));
+    int *p = (int *)malloc(sizeof(int) * count);
+    int track = 0;
+    while (1)
+    {
+        if (track == count)
+        {
+            return p;
+        }
+        int num = (rand() % (upper - lower + 1)) + lower;
+        if (track == 0)
+        {
+            p[track] = num;
+            track++;
+            continue;
+        }
+        int flag = 0;
+        for (int j = 0; j <= track - 1; j++)
+        {
+            if (num == p[j])
+            {
+                flag = 1;
+                break;
+            }
+        }
+        if (flag == 0)
+        {
+            p[track] = num;
+            track++;
+        }
+    }
+}
+
+void Kmeans2(struct data_frame *df)
+{
+    printf("count: %d\n",count);
+    if(count==0)
+    {
+        P = (struct Point *)malloc(sizeof(struct Point) * 500);
+    }
+    if (count != 500)
+    {
+        float CURR_FREQ;
+        if (df->dpmu[0]->fmt->freq == '0')
+        {
+            CURR_FREQ = 50 + to_intconvertor(df->dpmu[0]->freq) * 1e-3;
+        }
+        else
+        {
+            CURR_FREQ = decode_ieee_single(df->dpmu[0]->freq);
+        }
+        float CURR_vol;
+        if (df->dpmu[0]->fmt->phasor == '0')
+        {
+            if (df->dpmu[0]->fmt->polar == '0')
+            {
+                unsigned char s1[2];
+                unsigned char s2[2];
+                strncpy(s1, df->dpmu[0]->phasors[0], 2);
+                strncpy(s2, df->dpmu[0]->phasors[0] + 2, 2);
+                long double v1 = to_intconvertor(s1);
+                long double v2 = to_intconvertor(s2);
+                CURR_vol = sqrt((v1 * v1) + (v2 * v2));
+            }
+            else
+            {
+                unsigned char s1[2];
+                strncpy(s1, df->dpmu[0]->phasors[0], 2);
+                CURR_vol = to_intconvertor(s1);
+            }
+        }
+        else
+        {
+            if (df->dpmu[0]->fmt->polar == '0')
+            {
+                unsigned char s1[4];
+                unsigned char s2[4];
+                strncpy(s1, df->dpmu[0]->phasors[0], 4);
+                strncpy(s2, df->dpmu[0]->phasors[0] + 2, 4);
+                long double v1 = decode_ieee_single(s1);
+                long double v2 = decode_ieee_single(s2);
+                CURR_vol = sqrt((v1 * v1) + (v2 * v2));
+            }
+            else
+            {
+                unsigned char s1[4];
+                strncpy(s1, df->dpmu[0]->phasors[0], 4);
+                CURR_vol = decode_ieee_single(s1);
+            }
+        }
+        P[count].x = CURR_FREQ;
+        P[count].y = CURR_vol;
+        P[count].cluster = -1;
+        P[count].minDist = __DBL_MAX__;
+        count++;
+    }
+    else
+    {
+        int no_of_clusters = 5;
+        int epochs = 20;
+        int *c = getRandoms(0, 499, no_of_clusters);
+        struct Point *Centroids = (struct Point *)malloc(sizeof(struct Point) * no_of_clusters);
+        for (int i = 0; i < no_of_clusters; i++)
+        {
+            Centroids[i].x = P[c[i]].x;
+            Centroids[i].y = P[c[i]].y;
+            Centroids[i].minDist = __DBL_MAX__;
+            Centroids[i].cluster = -1;
+        }
+
+        free(c);
+
+        while (epochs--)
+        {
+            for (int i = 0; i < no_of_clusters; i++)
+            {
+                for (int j = 0; j < 500; j++)
+                {
+                    long double dist = distance(&Centroids[i], &P[j]);
+                    if (P[j].minDist > dist)
+                    {
+                        P[j].minDist = dist;
+                        P[j].cluster = i;
+                    }
+                }
+            }
+
+            int *nPoints = (int *)malloc(sizeof(int) * no_of_clusters);
+            long double *Sumx = (long double *)malloc(sizeof(long double) * no_of_clusters);
+            long double *Sumy = (long double *)malloc(sizeof(long double) * no_of_clusters);
+
+            for (int i = 0; i < no_of_clusters; i++)
+            {
+                nPoints[i] = 0;
+                Sumx[i] = 0;
+                Sumy[i] = 0;
+            }
+
+            for (int i = 0; i < 500; i++)
+            {
+                nPoints[P[i].cluster]++;
+                Sumx[P[i].cluster] += P[i].x;
+                Sumy[P[i].cluster] += P[i].y;
+                P[i].minDist = __DBL_MAX__;
+            }
+
+            for (int i = 0; i < no_of_clusters; i++)
+            {
+                Centroids[i].x = Sumx[i] / nPoints[i];
+                Centroids[i].y = Sumy[i] / nPoints[i];
+            }
+
+            free(nPoints);
+            free(Sumx);
+            free(Sumy);
+        }
+        count = 0;
+        FILE *fp;
+        fp = fopen("kmeans.txt","a");
+        
+        for(int i=0;i<500;i++)
+        {
+            fprintf(fp,"%Lf, %Lf, %d\n",P[i].x,P[i].y,P[i].cluster);
+        }
+        fprintf(fp,"\n\n");
+
+        for(int i=0;i<no_of_clusters;i++)
+        {
+            fprintf(fp,"%d : %Lf, %Lf\n",i,Centroids[i].x,Centroids[i].y);
+        }
+
+        fprintf(fp,"\n\n");
+
+        fclose(fp);
+
+        free(Centroids);
+        free(P);
+    }
+}

iPDC/src/map_vis.c

@@ -13,6 +13,7 @@
 #include "connections.h"
 #include "livechart.h"
 #include "utility_tools.h"
+#include "Kmeans2.h"
 
 
 //  debug
@@ -44,17 +45,17 @@ gboolean update_images(gpointer* pars){
         float lat;
         float lon;
         loops++;
-        printf("loops: %d\n", loops);
+        // printf("loops: %d\n", loops);
         
         id = to_intconvertor(df->idcode);
-        printf("id = %d\n",id);
+        // printf("id = %d\n",id);
         pthread_mutex_lock(&mutex_cfg);
         temp_cfg = cfgfirst;
         // Check for the IDCODE in Configuration Frame
         while(temp_cfg != NULL){
             if(id == to_intconvertor(temp_cfg->idcode)){
                 cfg_match = 1;
-                printf("Matched - id : %d\n",id);
+                // printf("Matched - id : %d\n",id);
                 freq_fmt = temp_cfg->pmu[0]->fmt->freq;
                 anal_fmt = temp_cfg->pmu[0]->fmt->analog;
                 phas_fmt = temp_cfg->pmu[0]->fmt->phasor;
@@ -69,7 +70,7 @@ gboolean update_images(gpointer* pars){
         // get data from df.
         if(freq_fmt == '1'){
             freq = decode_ieee_single(df->dpmu[i]->freq);
-            printf("freq = %f\n",freq);
+            // printf("freq = %f\n",freq);
         }else{
             freq = to_intconvertor(df->dpmu[i]->freq)*1e-6+50;
         }
@@ -80,15 +81,15 @@ gboolean update_images(gpointer* pars){
         strncpy(last2bytes, df->dpmu[i]->phasors[0]+2, 2);
         vol_magnitude = to_intconvertor(first2bytes);
         float imaginary = to_intconvertor(last2bytes);
-        printf("vol = %f imag = %f\n",vol_magnitude, imaginary);
+        // printf("vol = %f imag = %f\n",vol_magnitude, imaginary);
 
         vis_ptr = vis_data_head;
         match = 0;
         while(vis_ptr != NULL){
-            printf("vis_ptr->id = %d\n",vis_ptr->id);
+            // printf("vis_ptr->id = %d\n",vis_ptr->id);
             if(vis_ptr->id == id){
                 match = 1;
-                printf("Matched - id : %d\n",id);
+                // printf("Matched - id : %d\n",id);
                 break;
             }
             vis_ptr = vis_ptr->next;
@@ -102,7 +103,7 @@ gboolean update_images(gpointer* pars){
         live_chart_serie_add(vis_ptr->serie_dfreq, dfreq);
 
         if(match == 1 && cfg_match == 1){
-            printf("lat = %f, lon = %f, freq = %f\n",lat,lon,freq);
+            // printf("lat = %f, lon = %f, freq = %f\n",lat,lon,freq);
             if(vis_ptr->last_image != 0){
                 osm_gps_map_image_remove(parameters->util_map, vis_ptr->last_image);
             }
@@ -153,7 +154,7 @@ gboolean update_images(gpointer* pars){
                 }else if (algorithm==1 && dimmension == 1){
 
                 }else if (algorithm==1 && dimmension == 2){
-
+                    Kmeans2(df);
                 }else if (algorithm==2 && dimmension == 0){
                     if(!DTWvolDistance(df)){
                         vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_red_image);