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			No commits in common. "9dad2b4885221c9ba37fcbd35e586dfeccf1c519" and "5463e52ff6be2512a0c4fa62e16306afd6e145c3" have entirely different histories.
		
	
	
		
			9dad2b4885
			...
			5463e52ff6
		
	
		| 
						 | 
					@ -3,5 +3,3 @@
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int DTWfreqDistance(struct data_frame *df);
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					int DTWfreqDistance(struct data_frame *df);
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int DTWvolDistance(struct data_frame *df);
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					int DTWvolDistance(struct data_frame *df);
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					 | 
				
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int DTWfreqvolDistance(struct data_frame *df);
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					 | 
				
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						 | 
					@ -1,4 +1,3 @@
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int *getRandoms(int lower, int upper, int count);
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					int *getRandoms(int lower, int upper, int count);
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long double distance(struct Point *A, struct Point *B);
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					long double distance(struct Point* A, struct Point* B);
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bool Kmeans2(struct data_frame *df);
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					bool Kmeans2(struct data_frame *df);
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long double distance2(struct centroid *A, struct Point *B);
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					 | 
				
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| 
						 | 
					@ -76,7 +76,6 @@ gboolean attack_detect_freq(struct data_frame *df)
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                    printf("avg freq: %Lf\n", temp->AVERAGE_OF_FREQUENCY);
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					                    printf("avg freq: %Lf\n", temp->AVERAGE_OF_FREQUENCY);
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                    return TRUE;
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					                    return TRUE;
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                }
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					                }
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                break;
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					 | 
				
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            }
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					            }
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            previous = temp;
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					            previous = temp;
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            temp = temp->next;
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					            temp = temp->next;
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						 | 
					@ -175,7 +174,6 @@ gboolean attack_detect_vol(struct data_frame *df)
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                    printf("avg vol: %Lf\n", temp->AVERAGE_OF_VOLTAGE);
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					                    printf("avg vol: %Lf\n", temp->AVERAGE_OF_VOLTAGE);
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                    return TRUE;
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					                    return TRUE;
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                }
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					                }
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                break;
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					 | 
				
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            }
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					            }
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            previous = temp;
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					            previous = temp;
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            temp = temp->next;
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					            temp = temp->next;
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						 | 
					
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						 | 
					@ -137,7 +137,6 @@ int DTWfreqDistance(struct data_frame *df)
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                    free(DTW);
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					                    free(DTW);
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                    temp->count_track1 = 1;
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					                    temp->count_track1 = 1;
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                }
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					                }
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                return temp->result;
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					 | 
				
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                break;
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					                break;
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            }
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					            }
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            previous = temp;
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					            previous = temp;
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						 | 
					@ -155,6 +154,7 @@ int DTWfreqDistance(struct data_frame *df)
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            previous->next = bring;
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					            previous->next = bring;
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            return 1;
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					            return 1;
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        }
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					        }
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					        return temp->result;
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    }
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					    }
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}
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					}
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						 | 
					@ -293,7 +293,6 @@ int DTWvolDistance(struct data_frame *df)
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                    free(DTW);
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					                    free(DTW);
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                    temp->count_track1 = 1;
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					                    temp->count_track1 = 1;
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                }
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					                }
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                return temp->result;
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					 | 
				
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                break;
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					                break;
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            }
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					            }
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            previous = temp;
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					            previous = temp;
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| 
						 | 
					@ -311,6 +310,7 @@ int DTWvolDistance(struct data_frame *df)
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            previous->next = bring;
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					            previous->next = bring;
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            return 1;
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					            return 1;
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        }
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					        }
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					        return temp->result;
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    }
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					    }
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}
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					}
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						 | 
					
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| 
						 | 
					@ -13,23 +13,12 @@ struct Point
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    long double minDist; // default infinite dist to nearest cluster
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					    long double minDist; // default infinite dist to nearest cluster
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};
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					};
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struct centroid
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					 | 
				
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{
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					 | 
				
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    long double x, y;
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					 | 
				
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    long double max_radius;
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					 | 
				
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    unsigned long long int count;
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					 | 
				
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};
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					 | 
				
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					 | 
				
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struct Kmeans2
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					struct Kmeans2
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{
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					{
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    int idcode;
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					    int idcode;
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    int count;
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					    int count;
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    struct Point *P;
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					    struct Point *P;
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    struct Kmeans2 *next;
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					    struct Kmeans2 *next;
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    struct centroid *C;
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					 | 
				
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    int no_of_clusters;
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					 | 
				
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    int isIntialized;
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					 | 
				
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    bool result;
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					 | 
				
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};
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					};
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struct Kmeans2 *head_of_kmeans2 = NULL;
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					struct Kmeans2 *head_of_kmeans2 = NULL;
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| 
						 | 
					@ -39,11 +28,6 @@ long double distance(struct Point *A, struct Point *B)
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    return (((A->x - B->x) * (A->x - B->x)) + ((A->y - B->y) * (A->y - B->y)));
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					    return (((A->x - B->x) * (A->x - B->x)) + ((A->y - B->y) * (A->y - B->y)));
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}
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					}
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long double distance2(struct centroid *A, struct Point *B)
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					 | 
				
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{
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					 | 
				
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    return (((A->x - B->x) * (A->x - B->x)) + ((A->y - B->y) * (A->y - B->y)));
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					 | 
				
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}
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					 | 
				
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					 | 
				
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int *getRandoms(int lower, int upper, int count)
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					int *getRandoms(int lower, int upper, int count)
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{
 | 
					{
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    srand(time(0));
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					    srand(time(0));
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| 
						 | 
					@ -86,10 +70,8 @@ bool Kmeans2(struct data_frame *df)
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        head_of_kmeans2 = (struct Kmeans2 *)malloc(sizeof(struct Kmeans2));
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					        head_of_kmeans2 = (struct Kmeans2 *)malloc(sizeof(struct Kmeans2));
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        head_of_kmeans2->idcode = to_intconvertor(df->idcode);
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					        head_of_kmeans2->idcode = to_intconvertor(df->idcode);
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        head_of_kmeans2->count = 0;
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					        head_of_kmeans2->count = 0;
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        head_of_kmeans2->isIntialized = 0;
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					 | 
				
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        head_of_kmeans2->next = NULL;
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					        head_of_kmeans2->next = NULL;
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        head_of_kmeans2->P = NULL;
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					        head_of_kmeans2->P = NULL;
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        head_of_kmeans2->result = true;
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					 | 
				
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        return true;
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					        return true;
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    }
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					    }
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    else
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					    else
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| 
						 | 
					@ -100,135 +82,12 @@ bool Kmeans2(struct data_frame *df)
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        {
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					        {
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            if (temp->idcode == to_intconvertor(df->idcode))
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					            if (temp->idcode == to_intconvertor(df->idcode))
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            {
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					            {
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                printf("count: %d\n", temp->count);
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					                printf("count: %d\n",temp->count);
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                if (temp->count == 0)
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					                if (temp->count == 0)
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                {
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					                {
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                    if (temp->isIntialized == 0)
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					                    temp->P = (struct Point *)malloc(sizeof(struct Point) * 500);
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                        temp->P = (struct Point *)malloc(sizeof(struct Point) * 500);
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					 | 
				
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                    else
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					 | 
				
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                        temp->P = (struct Point *)malloc(sizeof(struct Point) * 100);
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					 | 
				
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                }
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					                }
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                if (temp->isIntialized == 1 && temp->count != 100)
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					                if (temp->count != 500)
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                {
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					 | 
				
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                    float CURR_FREQ;
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					 | 
				
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                    if (df->dpmu[0]->fmt->freq == '0')
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					 | 
				
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                    {
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					 | 
				
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                        CURR_FREQ = 50 + to_intconvertor(df->dpmu[0]->freq) * 1e-3;
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					 | 
				
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                    }
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					 | 
				
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                    else
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					 | 
				
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                    {
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					 | 
				
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                        CURR_FREQ = decode_ieee_single(df->dpmu[0]->freq);
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					 | 
				
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                    }
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					 | 
				
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                    float CURR_vol;
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					 | 
				
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                    if (df->dpmu[0]->fmt->phasor == '0')
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					 | 
				
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                    {
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					 | 
				
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                        if (df->dpmu[0]->fmt->polar == '0')
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					 | 
				
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                        {
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					 | 
				
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                            unsigned char s1[2];
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					 | 
				
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                            unsigned char s2[2];
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					 | 
				
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                            strncpy(s1, df->dpmu[0]->phasors[0], 2);
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					 | 
				
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                            strncpy(s2, df->dpmu[0]->phasors[0] + 2, 2);
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					 | 
				
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                            long double v1 = to_intconvertor(s1);
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					 | 
				
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                            long double v2 = to_intconvertor(s2);
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					 | 
				
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                            CURR_vol = sqrt((v1 * v1) + (v2 * v2));
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					 | 
				
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                        }
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					 | 
				
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                        else
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					 | 
				
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                        {
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					 | 
				
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                            unsigned char s1[2];
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					 | 
				
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                            strncpy(s1, df->dpmu[0]->phasors[0], 2);
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					 | 
				
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                            CURR_vol = to_intconvertor(s1);
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					 | 
				
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                        }
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					 | 
				
			||||||
                    }
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					 | 
				
			||||||
                    else
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					 | 
				
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                    {
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					 | 
				
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                        if (df->dpmu[0]->fmt->polar == '0')
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					 | 
				
			||||||
                        {
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					 | 
				
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                            unsigned char s1[4];
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					 | 
				
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                            unsigned char s2[4];
 | 
					 | 
				
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                            strncpy(s1, df->dpmu[0]->phasors[0], 4);
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					 | 
				
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                            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;
 | 
					                    float CURR_FREQ;
 | 
				
			||||||
                    if (df->dpmu[0]->fmt->freq == '0')
 | 
					                    if (df->dpmu[0]->fmt->freq == '0')
 | 
				
			||||||
| 
						 | 
					@ -284,7 +143,7 @@ bool Kmeans2(struct data_frame *df)
 | 
				
			||||||
                    temp->P[temp->count].minDist = __DBL_MAX__;
 | 
					                    temp->P[temp->count].minDist = __DBL_MAX__;
 | 
				
			||||||
                    temp->count++;
 | 
					                    temp->count++;
 | 
				
			||||||
                }
 | 
					                }
 | 
				
			||||||
                else if (temp->isIntialized == 0)
 | 
					                else
 | 
				
			||||||
                {
 | 
					                {
 | 
				
			||||||
                    int no_of_clusters = 5;
 | 
					                    int no_of_clusters = 5;
 | 
				
			||||||
                    int epochs = 20;
 | 
					                    int epochs = 20;
 | 
				
			||||||
| 
						 | 
					@ -340,68 +199,33 @@ bool Kmeans2(struct data_frame *df)
 | 
				
			||||||
                            Centroids[i].y = Sumy[i] / nPoints[i];
 | 
					                            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(nPoints);
 | 
				
			||||||
                        free(Sumx);
 | 
					                        free(Sumx);
 | 
				
			||||||
                        free(Sumy);
 | 
					                        free(Sumy);
 | 
				
			||||||
                    }
 | 
					                    }
 | 
				
			||||||
                    temp->count = 0;
 | 
					                    temp->count = 0;
 | 
				
			||||||
                    // FILE *fp;
 | 
					                    FILE *fp;
 | 
				
			||||||
                    // fp = fopen("kmeans.txt", "a");
 | 
					                    fp = fopen("kmeans.txt", "a");
 | 
				
			||||||
 | 
					
 | 
				
			||||||
                    // for (int i = 0; i < 500; i++)
 | 
					                    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, "%Lf, %Lf, %d\n", temp->P[i].x, temp->P[i].y, temp->P[i].cluster);
 | 
				
			||||||
                    // }
 | 
					                    }
 | 
				
			||||||
                    // fprintf(fp, "\n\n");
 | 
					                    fprintf(fp, "\n\n");
 | 
				
			||||||
 | 
					
 | 
				
			||||||
                    // for (int i = 0; i < no_of_clusters; i++)
 | 
					                    for (int i = 0; i < no_of_clusters; i++)
 | 
				
			||||||
                    // {
 | 
					                    {
 | 
				
			||||||
                    //     fprintf(fp, "%d : %Lf, %Lf\n", i, Centroids[i].x, Centroids[i].y);
 | 
					                        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(Centroids);
 | 
				
			||||||
                    free(temp->P);
 | 
					                    free(temp->P);
 | 
				
			||||||
                    temp->isIntialized = 1;
 | 
					 | 
				
			||||||
                }
 | 
					                }
 | 
				
			||||||
                return temp->result;
 | 
					                return true;
 | 
				
			||||||
                break;
 | 
					                break;
 | 
				
			||||||
            }
 | 
					            }
 | 
				
			||||||
            previous = temp;
 | 
					            previous = temp;
 | 
				
			||||||
| 
						 | 
					@ -413,9 +237,7 @@ bool Kmeans2(struct data_frame *df)
 | 
				
			||||||
            bring->idcode = to_intconvertor(df->idcode);
 | 
					            bring->idcode = to_intconvertor(df->idcode);
 | 
				
			||||||
            bring->count = 0;
 | 
					            bring->count = 0;
 | 
				
			||||||
            bring->next = NULL;
 | 
					            bring->next = NULL;
 | 
				
			||||||
            bring->isIntialized = 0;
 | 
					 | 
				
			||||||
            bring->P = NULL;
 | 
					            bring->P = NULL;
 | 
				
			||||||
            bring->result = true;
 | 
					 | 
				
			||||||
            previous->next = bring;
 | 
					            previous->next = bring;
 | 
				
			||||||
            return true;
 | 
					            return true;
 | 
				
			||||||
        }
 | 
					        }
 | 
				
			||||||
| 
						 | 
					
 | 
				
			||||||
| 
						 | 
					@ -129,13 +129,13 @@ gboolean update_images(gpointer* pars){
 | 
				
			||||||
                }
 | 
					                }
 | 
				
			||||||
            }else if(curr_measurement == 3){
 | 
					            }else if(curr_measurement == 3){
 | 
				
			||||||
                if(algorithm==0 && dimmension == 0){
 | 
					                if(algorithm==0 && dimmension == 0){
 | 
				
			||||||
                    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);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_red_image);
 | 
				
			||||||
                    }else{
 | 
					                    }else{
 | 
				
			||||||
                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
				
			||||||
                    }
 | 
					                    }
 | 
				
			||||||
                }else if (algorithm==0 && dimmension == 1){
 | 
					                }else if (algorithm==0 && dimmension == 1){
 | 
				
			||||||
                    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);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_red_image);
 | 
				
			||||||
                    }else{
 | 
					                    }else{
 | 
				
			||||||
                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
				
			||||||
| 
						 | 
					@ -161,23 +161,19 @@ gboolean update_images(gpointer* pars){
 | 
				
			||||||
                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
				
			||||||
                    }
 | 
					                    }
 | 
				
			||||||
                }else if (algorithm==2 && dimmension == 0){
 | 
					                }else if (algorithm==2 && dimmension == 0){
 | 
				
			||||||
                    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)){
 | 
					                    if(!DTWvolDistance(df)){
 | 
				
			||||||
                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_red_image);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_red_image);
 | 
				
			||||||
                    }else{
 | 
					                    }else{
 | 
				
			||||||
                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
				
			||||||
                    }
 | 
					                    }
 | 
				
			||||||
                }else if (algorithm==2 && dimmension == 2){
 | 
					                }else if (algorithm==2 && dimmension == 1){
 | 
				
			||||||
                    if(!DTWfreqvolDistance(df)){
 | 
					                    if(!DTWfreqDistance(df)){
 | 
				
			||||||
                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_red_image);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_red_image);
 | 
				
			||||||
                    }else{
 | 
					                    }else{
 | 
				
			||||||
                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
					                        vis_ptr->last_image = osm_gps_map_image_add(parameters->util_map,lat, lon, parameters->g_green_image);
 | 
				
			||||||
                    }
 | 
					                    }
 | 
				
			||||||
 | 
					                }else if (algorithm==2 && dimmension == 2){
 | 
				
			||||||
 | 
					
 | 
				
			||||||
                }
 | 
					                }
 | 
				
			||||||
            }
 | 
					            }
 | 
				
			||||||
        }
 | 
					        }
 | 
				
			||||||
| 
						 | 
					
 | 
				
			||||||
		Loading…
	
		Reference in New Issue