Merge pull request #12 from karthikmurakonda/testing-kmeans

kmeans implmented for all PMUs

iPDC/inc/Kmeans2.h

@@ -1,3 +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);
+bool Kmeans2(struct data_frame *df);

iPDC/src/Kmeans2.c

@@ -13,8 +13,15 @@ struct Point
     long double minDist; // default infinite dist to nearest cluster
 };
 
-int count = 0;
+struct Kmeans2
+{
+    int idcode;
+    int count;
     struct Point *P;
+    struct Kmeans2 *next;
+};
+
+struct Kmeans2 *head_of_kmeans2 = NULL;
 
 long double distance(struct Point *A, struct Point *B)
 {
@@ -56,14 +63,31 @@ int *getRandoms(int lower, int upper, int count)
     }
 }
 
-void Kmeans2(struct data_frame *df)
+bool Kmeans2(struct data_frame *df)
 {
-    printf("count: %d\n",count);
+    if (head_of_kmeans2 == NULL)
-    if(count==0)
     {
-        P = (struct Point *)malloc(sizeof(struct Point) * 500);
+        head_of_kmeans2 = (struct Kmeans2 *)malloc(sizeof(struct Kmeans2));
+        head_of_kmeans2->idcode = to_intconvertor(df->idcode);
+        head_of_kmeans2->count = 0;
+        head_of_kmeans2->next = NULL;
+        head_of_kmeans2->P = NULL;
+        return true;
     }
-    if (count != 500)
+    else
+    {
+        struct Kmeans2 *temp = head_of_kmeans2;
+        struct Kmeans2 *previous = NULL;
+        while (temp != NULL)
+        {
+            if (temp->idcode == to_intconvertor(df->idcode))
+            {
+                printf("count: %d\n",temp->count);
+                if (temp->count == 0)
+                {
+                    temp->P = (struct Point *)malloc(sizeof(struct Point) * 500);
+                }
+                if (temp->count != 500)
                 {
                     float CURR_FREQ;
                     if (df->dpmu[0]->fmt->freq == '0')
@@ -113,11 +137,11 @@ void Kmeans2(struct data_frame *df)
                             CURR_vol = decode_ieee_single(s1);
                         }
                     }
-        P[count].x = CURR_FREQ;
+                    temp->P[temp->count].x = CURR_FREQ;
-        P[count].y = CURR_vol;
+                    temp->P[temp->count].y = CURR_vol;
-        P[count].cluster = -1;
+                    temp->P[temp->count].cluster = -1;
-        P[count].minDist = __DBL_MAX__;
+                    temp->P[temp->count].minDist = __DBL_MAX__;
-        count++;
+                    temp->count++;
                 }
                 else
                 {
@@ -127,8 +151,8 @@ void Kmeans2(struct data_frame *df)
                     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].x = temp->P[c[i]].x;
-            Centroids[i].y = P[c[i]].y;
+                        Centroids[i].y = temp->P[c[i]].y;
                         Centroids[i].minDist = __DBL_MAX__;
                         Centroids[i].cluster = -1;
                     }
@@ -141,11 +165,11 @@ void Kmeans2(struct data_frame *df)
                         {
                             for (int j = 0; j < 500; j++)
                             {
-                    long double dist = distance(&Centroids[i], &P[j]);
+                                long double dist = distance(&Centroids[i], &temp->P[j]);
-                    if (P[j].minDist > dist)
+                                if (temp->P[j].minDist > dist)
                                 {
-                        P[j].minDist = dist;
+                                    temp->P[j].minDist = dist;
-                        P[j].cluster = i;
+                                    temp->P[j].cluster = i;
                                 }
                             }
                         }
@@ -163,10 +187,10 @@ void Kmeans2(struct data_frame *df)
 
                         for (int i = 0; i < 500; i++)
                         {
-                nPoints[P[i].cluster]++;
+                            nPoints[temp->P[i].cluster]++;
-                Sumx[P[i].cluster] += P[i].x;
+                            Sumx[temp->P[i].cluster] += temp->P[i].x;
-                Sumy[P[i].cluster] += P[i].y;
+                            Sumy[temp->P[i].cluster] += temp->P[i].y;
-                P[i].minDist = __DBL_MAX__;
+                            temp->P[i].minDist = __DBL_MAX__;
                         }
 
                         for (int i = 0; i < no_of_clusters; i++)
@@ -179,13 +203,13 @@ void Kmeans2(struct data_frame *df)
                         free(Sumx);
                         free(Sumy);
                     }
-        count = 0;
+                    temp->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, "%Lf, %Lf, %d\n", temp->P[i].x, temp->P[i].y, temp->P[i].cluster);
                     }
                     fprintf(fp, "\n\n");
 
@@ -199,6 +223,23 @@ void Kmeans2(struct data_frame *df)
                     fclose(fp);
 
                     free(Centroids);
-        free(P);
+                    free(temp->P);
+                }
+                return true;
+                break;
+            }
+            previous = temp;
+            temp = temp->next;
+        }
+        if (temp == NULL)
+        {
+            struct Kmeans2 *bring = (struct Kmeans2 *)malloc(sizeof(struct Kmeans2));
+            bring->idcode = to_intconvertor(df->idcode);
+            bring->count = 0;
+            bring->next = NULL;
+            bring->P = NULL;
+            previous->next = bring;
+            return true;
+        }
     }
 }

iPDC/src/map_vis.c

@@ -1,5 +1,6 @@
 #include <stdlib.h>
 #include <stdio.h>
+#include <stdbool.h>
 #include <gtk/gtk.h>
 #include <pthread.h>
 #include "global.h"
@@ -154,7 +155,11 @@ gboolean update_images(gpointer* pars){
                 }else if (algorithm==1 && dimmension == 1){
 
                 }else if (algorithm==1 && dimmension == 2){
-                    Kmeans2(df);
+                    if(!Kmeans2(df)){
+                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_red_image);
+                    }else{
+                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
+                    }
                 }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);