Merge pull request #2 from wichtounet/master

Fix casts

src/initialization_model.c

@@ -50,7 +50,7 @@ void model_initialization(model_t* model, uint8_t nGaussians, uint8_t nDimension
 	for (int i = 0; i < 2; i++)
 		model->normalisation[i] = (double*)calloc(model->numberDimensions, sizeof(double));
 
-	model->list_D = malloc((model->numberStates - 2)*sizeof(double));
+	model->list_D = (double*)malloc((model->numberStates - 2)*sizeof(double));
 	if (!expanded)
 		for (int i = 0; i < model->numberStates - 2; i++)
 			model->list_D[i] = 1;

src/test_histogram.c

@@ -16,7 +16,7 @@ void test_histogram(model_t * model, double ** test_vect, int sample_length, int
 	// pre-processing operations
 	for (int i = 0; i < model->numberDimensions; i++)
 		for (int j = 0; j < sample_length; j++)
-			test_vect[i][j] = test_vect[i][j] + rand_num(2 * model->noise) - model->noise; 
+			test_vect[i][j] = test_vect[i][j] + rand_num(2 * model->noise) - model->noise;
 
 	// normalization
 	for (int pos = 0; pos < sample_length; pos++)
@@ -28,8 +28,8 @@ void test_histogram(model_t * model, double ** test_vect, int sample_length, int
 	for (int nC = 0; nC < NClasses; nC++){
 
 		// parameter initialization
-		int *X = calloc(sample_length, sizeof(int));
-		double *Pvit = calloc(1, sizeof(double));
+		int *X = (int*)calloc(sample_length, sizeof(int));
+		double *Pvit = (double*)calloc(1, sizeof(double));
 
 		// computation of the X and Prob double
 		viterbi_log(model, test_vect, sample_length, X, Pvit);
@@ -53,4 +53,4 @@ void test_histogram(model_t * model, double ** test_vect, int sample_length, int
 
 	free(Pvit_t);
 
-}
+}

src/test_matrix.c

@@ -16,8 +16,8 @@ int test_matrix(model_t* foo_mat, double **Test_Vect, int T, int NClasses, int *
 		//struct Matrix mat_class = foo_mat[nC];
 
 		// parameter initialization
-		int *X = calloc(T, sizeof(int));
-		double *Pvit = calloc(1, sizeof(double));
+		int *X = (int*)calloc(T, sizeof(int));
+		double *Pvit = (double*)calloc(1, sizeof(double));
 
 		// computation of the X and Prob double
 		viterbi_log(foo_mat, Test_Vect, T, X, Pvit);

src/viterbi_end.c

@@ -21,7 +21,7 @@ void maxx(double *Ar, int dim, double *val, int *pos){
 void viterbi_end(double *FI, int *XX, double *A_Vect, double *LogPdf, double *Pvit, int N, int T){
 
 	// end of viterbi
-	double *temp = calloc(N - 2, sizeof(double));
+	double *temp = (double*)calloc(N - 2, sizeof(double));
 	int n;
 	for (n = 1; n < (N - 1); n++){
 		if (A_Vect[(N - 1)*N + n] == 0)
@@ -33,7 +33,7 @@ void viterbi_end(double *FI, int *XX, double *A_Vect, double *LogPdf, double *Pv
 
 
 	// Allocation of memory
-	int *max_pos = malloc(sizeof(int));
+	int *max_pos = (int*)malloc(sizeof(int));
 	maxx(temp, N - 2, Pvit, max_pos);
 
 

src/viterbi_log.c

@@ -9,34 +9,34 @@
 #include "../include/viterbi_end.h"
 
 void viterbi_log(model_t* mat_class, double **Test_Vect, int T, int *X, double *Pvit){
-	
+
 	int N = mat_class->numberStates;
 	int N_exp = mat_class->numberStates_exp;
 	int D = mat_class->numberDimensions;
 	int K = mat_class->numberGaussians;
 
-	double *LogPdf = calloc(T*(N_exp - 2), sizeof(double));
+	double *LogPdf = (double*)calloc(T*(N_exp - 2), sizeof(double));
 	int n, d, t, k, cnt;
 	cnt = 0;
 	for (n = 1; n < N - 1; n++){
 
-		double * Mu_Vect_Array = malloc(D*K*sizeof(double));
-		double * Sigma_Vect_Array = malloc(D*K*sizeof(double));
-		double * Test_Vect_Array = malloc(D*T*sizeof(double));
-		double * PComp_Vect_Array = malloc(K*sizeof(double));
-		
+		double * Mu_Vect_Array = (double*)malloc(D*K*sizeof(double));
+		double * Sigma_Vect_Array = (double*)malloc(D*K*sizeof(double));
+		double * Test_Vect_Array = (double*)malloc(D*T*sizeof(double));
+		double * PComp_Vect_Array = (double*)malloc(K*sizeof(double));
+
 		for (d = 0; d < D; d++){
 			for (k = 0; k < K; k++){
 				Mu_Vect_Array[k + d*K] = mat_class->mu[d][n][k];
 				Sigma_Vect_Array[k + d*K] = mat_class->sigma[d][n][k];
 			}
 			for (t = 0; t < T; t++)
-				Test_Vect_Array[t + d*T] = Test_Vect[d][t]; 
+				Test_Vect_Array[t + d*T] = Test_Vect[d][t];
 		}
 		for (k = 0; k < K; k++)
 			PComp_Vect_Array[k] = mat_class->weights[n][k];
 
-		double *Log = calloc(T, sizeof(double));
+		double *Log = (double*)calloc(T, sizeof(double));
 
 		// compute the distribution
 		wdensity(Mu_Vect_Array, Sigma_Vect_Array, PComp_Vect_Array, Test_Vect_Array, Log, D, N, K, T);
@@ -55,16 +55,16 @@ void viterbi_log(model_t* mat_class, double **Test_Vect, int T, int *X, double *
 
 		// de-alloc the memory
 		free(Log);
-	}	
+	}
 
 	int n1, n2;
-	double * A_Vect_Array = malloc(N_exp*N_exp*sizeof(double));
+	double * A_Vect_Array = (double*)malloc(N_exp*N_exp*sizeof(double));
 	for (n1 = 0; n1 < N_exp; n1++)
 		for (n2 = 0; n2 < N_exp; n2++)
 			A_Vect_Array[n1 + n2*N_exp] = mat_class->transition[n1][n2];
-		
-	double * FI = calloc(N_exp*T, sizeof(double));
-	int * XX = calloc(N_exp*T, sizeof(int));
+
+	double * FI = (double*)calloc(N_exp*T, sizeof(double));
+	int * XX = (int*)calloc(N_exp*T, sizeof(int));
 
 	viterbi_init(FI, A_Vect_Array, LogPdf, N_exp, T);
 
@@ -77,16 +77,16 @@ void viterbi_log(model_t* mat_class, double **Test_Vect, int T, int *X, double *
 		printf("\n");
 	}
 	*/
-	
-	viterbi_end(FI, XX, A_Vect_Array, LogPdf, Pvit, N_exp, T); 
+
+	viterbi_end(FI, XX, A_Vect_Array, LogPdf, Pvit, N_exp, T);
 
 	free(LogPdf);
 	free(A_Vect_Array);
 	free(FI);
 
 	// backtrace of states and probabilities
 	X[T - 1] = XX[N_exp*T - 1];
-	//Prob[T - 1] = log(A_Vect_Array[X[T - 1]+ N*(N-1)]);  
+	//Prob[T - 1] = log(A_Vect_Array[X[T - 1]+ N*(N-1)]);
 	for (t = T - 2; t > -1; t--){
 		X[t] = XX[(t + 1)*N_exp + X[(t + 1)] - 1];
 		//Prob[t] = log(A_Vect_Array[X[t] -1 + N*(X[t+1] - 1)]);
@@ -95,8 +95,8 @@ void viterbi_log(model_t* mat_class, double **Test_Vect, int T, int *X, double *
 	free(XX);
 
 	if (expanded){
-		// transform the expanded in normal	
-		double * cumsum_List_D = malloc((N - 2 + 1)*sizeof(double));
+		// transform the expanded in normal
+		double * cumsum_List_D = (double*)malloc((N - 2 + 1)*sizeof(double));
 		cumsum_List_D[0] = 1;
 		for (int i = 0; i < N - 2; i++){
  			cumsum_List_D[i + 1] = cumsum_List_D[i] + mat_class->list_D[i];

src/wdensity.c

@@ -9,8 +9,8 @@ void wdensity(double *Mu_Vect, double *Sigma_Vect, double *PComp_Vect, double *T
 	// Parameter initialization
 	double logDetSigma, mahalaD, maxll, temp;
 	int k, t, d;
-	double *LOG = malloc(T * K * sizeof(double));
-	double *LOG_Array = malloc(T * K* sizeof(double));
+	double *LOG = (double*)malloc(T * K * sizeof(double));
+	double *LOG_Array = (double*)malloc(T * K* sizeof(double));
 
 	// first cycle
 	for (k = 0; k < K; k++)
@@ -47,14 +47,14 @@ void wdensity(double *Mu_Vect, double *Sigma_Vect, double *PComp_Vect, double *T
 
 		LOGPDF[t] = log(LOGPDF[t]) + maxll; //BUG
 
-	
+
 	}
-	
+
 	// free the memory
 	free(LOG);
 	free(LOG_Array);
 
 	return;
 
-	
+
 }