Merge pull request #13 from karthikmurakonda/testing-kmeans

Testing kmeans

iPDC/inc/Dynamic_time_warping.h

@@ -3,3 +3,5 @@
 int DTWfreqDistance(struct data_frame *df);
 
 int DTWvolDistance(struct data_frame *df);
+
+int DTWfreqvolDistance(struct data_frame *df);

iPDC/inc/Kmeans2.h

@@ -1,3 +1,4 @@
 int *getRandoms(int lower, int upper, int count);
-long double distance(struct Point* A, struct Point* B);
+long double distance(struct Point *A, struct Point *B);
 bool Kmeans2(struct data_frame *df);
+long double distance2(struct centroid *A, struct Point *B);

iPDC/src/Attack_detect.c

@@ -76,6 +76,7 @@ gboolean attack_detect_freq(struct data_frame *df)
                     printf("avg freq: %Lf\n", temp->AVERAGE_OF_FREQUENCY);
                     return TRUE;
                 }
+                break;
             }
             previous = temp;
             temp = temp->next;
@@ -174,6 +175,7 @@ gboolean attack_detect_vol(struct data_frame *df)
                     printf("avg vol: %Lf\n", temp->AVERAGE_OF_VOLTAGE);
                     return TRUE;
                 }
+                break;
             }
             previous = temp;
             temp = temp->next;

iPDC/src/Dynamic_time_warping.c

@@ -137,6 +137,7 @@ int DTWfreqDistance(struct data_frame *df)
                     free(DTW);
                     temp->count_track1 = 1;
                 }
+                return temp->result;
                 break;
             }
             previous = temp;
@@ -154,7 +155,6 @@ int DTWfreqDistance(struct data_frame *df)
             previous->next = bring;
             return 1;
         }
-        return temp->result;
     }
 }
 
@@ -293,6 +293,7 @@ int DTWvolDistance(struct data_frame *df)
                     free(DTW);
                     temp->count_track1 = 1;
                 }
+                return temp->result;
                 break;
             }
             previous = temp;
@@ -310,7 +311,6 @@ int DTWvolDistance(struct data_frame *df)
             previous->next = bring;
             return 1;
         }
-        return temp->result;
     }
 }
 

iPDC/src/Kmeans2.c

@@ -13,12 +13,23 @@ struct Point
     long double minDist; // default infinite dist to nearest cluster
 };
 
+struct centroid
+{
+    long double x, y;
+    long double max_radius;
+    unsigned long long int count;
+};
+
 struct Kmeans2
 {
     int idcode;
     int count;
     struct Point *P;
     struct Kmeans2 *next;
+    struct centroid *C;
+    int no_of_clusters;
+    int isIntialized;
+    bool result;
 };
 
 struct Kmeans2 *head_of_kmeans2 = NULL;
@@ -28,6 +39,11 @@ 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)));
 }
 
+long double distance2(struct centroid *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));
@@ -70,8 +86,10 @@ bool Kmeans2(struct data_frame *df)
         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->isIntialized = 0;
         head_of_kmeans2->next = NULL;
         head_of_kmeans2->P = NULL;
+        head_of_kmeans2->result = true;
         return true;
     }
     else
@@ -82,12 +100,135 @@ bool Kmeans2(struct data_frame *df)
         {
             if (temp->idcode == to_intconvertor(df->idcode))
             {
-                printf("count: %d\n",temp->count);
+                printf("count: %d\n", temp->count);
                 if (temp->count == 0)
                 {
-                    temp->P = (struct Point *)malloc(sizeof(struct Point) * 500);
+                    if (temp->isIntialized == 0)
+                        temp->P = (struct Point *)malloc(sizeof(struct Point) * 500);
+                    else
+                        temp->P = (struct Point *)malloc(sizeof(struct Point) * 100);
                 }
-                if (temp->count != 500)
+                if (temp->isIntialized == 1 && temp->count != 100)
+                {
+                    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);
+                        }
+                    }
+                    temp->P[temp->count].x = CURR_FREQ;
+                    temp->P[temp->count].y = CURR_vol;
+                    temp->P[temp->count].cluster = -1;
+                    temp->P[temp->count].minDist = __DBL_MAX__;
+                    temp->count++;
+
+                    bool result = false;
+                    for (int i = 0; i < temp->no_of_clusters; i++)
+                    {
+                        long double dist = distance2(&temp->C[i], &temp->P[temp->count - 1]);
+                        if (dist <= temp->C[i].max_radius && dist < temp->P[temp->count - 1].minDist)
+                        {
+                            temp->P[temp->count - 1].cluster = i;
+                            temp->P[temp->count - 1].minDist = dist;
+                            result = true;
+                        }
+                    }
+                    if (result == false)
+                        temp->P[temp->count - 1].cluster = -1;
+                    temp->result = result;
+                }
+                else if (temp->isIntialized == 1)
+                {
+                    int *nPoints = (int *)malloc(sizeof(int) * temp->no_of_clusters);
+                    long double *Sumx = (long double *)malloc(sizeof(long double) * temp->no_of_clusters);
+                    long double *Sumy = (long double *)malloc(sizeof(long double) * temp->no_of_clusters);
+
+                    for (int i = 0; i < temp->no_of_clusters; i++)
+                    {
+                        nPoints[i] = 0;
+                        Sumx[i] = 0;
+                        Sumy[i] = 0;
+                    }
+
+                    for (int i = 0; i < 100; i++)
+                    {
+                        if (temp->P[i].cluster != -1)
+                        {
+                            nPoints[temp->P[i].cluster]++;
+                            Sumx[temp->P[i].cluster] += temp->P[i].x;
+                            Sumy[temp->P[i].cluster] += temp->P[i].y;
+                        }
+                    }
+
+                    for (int i = 0; i < temp->no_of_clusters; i++)
+                    {
+                        temp->C[i].x = ((temp->C[i].count * temp->C[i].x) + Sumx[i]) / (temp->C[i].count + nPoints[i]);
+                        temp->C[i].y = ((temp->C[i].count * temp->C[i].y) + Sumx[i]) / (temp->C[i].count + nPoints[i]);
+                        temp->C[i].count += nPoints[i];
+                    }
+
+                    for (int i = 0; i < temp->no_of_clusters; i++)
+                    {
+                        for (int j = 0; j < 100; j++)
+                        {
+                            if (temp->P[j].cluster == i)
+                            {
+                                long double dist = distance2(&temp->C[i], &temp->P[j]);
+                                if (temp->C[i].max_radius < dist)
+                                    temp->C[i].max_radius = dist;
+                            }
+                        }
+                    }
+
+                    temp->count = 0;
+                    free(temp->P);
+                    free(Sumx);
+                    free(Sumy);
+                    free(nPoints);
+                }
+                if (temp->count != 500 && temp->isIntialized == 0)
                 {
                     float CURR_FREQ;
                     if (df->dpmu[0]->fmt->freq == '0')
@@ -143,7 +284,7 @@ bool Kmeans2(struct data_frame *df)
                     temp->P[temp->count].minDist = __DBL_MAX__;
                     temp->count++;
                 }
-                else
+                else if (temp->isIntialized == 0)
                 {
                     int no_of_clusters = 5;
                     int epochs = 20;
@@ -199,33 +340,68 @@ bool Kmeans2(struct data_frame *df)
                             Centroids[i].y = Sumy[i] / nPoints[i];
                         }
 
+                        if (epochs == 0)
+                        {
+                            int count_centroids = 0;
+                            for (int i = 0; i < no_of_clusters; i++)
+                            {
+                                if (!isnanl(Centroids[i].x))
+                                    count_centroids++;
+                            }
+
+                            temp->no_of_clusters = count_centroids;
+                            temp->C = (struct centroid *)malloc(sizeof(struct centroid) * count_centroids);
+                            int track = 0;
+                            for (int i = 0; i < no_of_clusters; i++)
+                            {
+                                if (!isnanl(Centroids[i].x))
+                                {
+                                    temp->C[track].x = Centroids[i].x;
+                                    temp->C[track].y = Centroids[i].y;
+                                    temp->C[track].max_radius = 0;
+                                    temp->C[track].count = nPoints[i];
+                                    for (int j = 0; j < 500; j++)
+                                    {
+                                        if (temp->P[j].cluster == i)
+                                        {
+                                            long double dist = distance2(&temp->C[track], &temp->P[j]);
+                                            if (temp->C[track].max_radius < dist)
+                                                temp->C[track].max_radius = dist;
+                                        }
+                                    }
+                                    track++;
+                                }
+                            }
+                        }
+
                         free(nPoints);
                         free(Sumx);
                         free(Sumy);
                     }
                     temp->count = 0;
-                    FILE *fp;
-                    fp = fopen("kmeans.txt", "a");
+                    // FILE *fp;
+                    // fp = fopen("kmeans.txt", "a");
 
-                    for (int i = 0; i < 500; i++)
-                    {
-                        fprintf(fp, "%Lf, %Lf, %d\n", temp->P[i].x, temp->P[i].y, temp->P[i].cluster);
-                    }
-                    fprintf(fp, "\n\n");
+                    // for (int i = 0; i < 500; i++)
+                    // {
+                    //     fprintf(fp, "%Lf, %Lf, %d\n", temp->P[i].x, temp->P[i].y, temp->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);
-                    }
+                    // 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");
+                    // fprintf(fp, "\n\n");
 
-                    fclose(fp);
+                    // fclose(fp);
 
                     free(Centroids);
                     free(temp->P);
+                    temp->isIntialized = 1;
                 }
-                return true;
+                return temp->result;
                 break;
             }
             previous = temp;
@@ -237,7 +413,9 @@ bool Kmeans2(struct data_frame *df)
             bring->idcode = to_intconvertor(df->idcode);
             bring->count = 0;
             bring->next = NULL;
+            bring->isIntialized = 0;
             bring->P = NULL;
+            bring->result = true;
             previous->next = bring;
             return true;
         }

iPDC/src/map_vis.c

@@ -129,13 +129,13 @@ gboolean update_images(gpointer* pars){
                 }
             }else if(curr_measurement == 3){
                 if(algorithm==0 && dimmension == 0){
-                    if (!attack_detect_vol(df)){
+                    if (!attack_detect_freq(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==0 && dimmension == 1){
-                    if (!attack_detect_freq(df)){
+                    if (!attack_detect_vol(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);
@@ -161,19 +161,23 @@ gboolean update_images(gpointer* pars){
                         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);
-                    }else{
-                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
-                    }
-                }else if (algorithm==2 && dimmension == 1){
                     if(!DTWfreqDistance(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 == 1){
+                    if(!DTWvolDistance(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 == 2){
-
+                    if(!DTWfreqvolDistance(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);
+                    }
                 }
             }
         }