Remove category matrix from implementation

It's a remnant from the Matlab implementation, where it actually
makes sense to use. Here it becomes a significant memory burden
for large datasets, and doesn't provide any speedup

5 files changed, 24 insertions, 120 deletions

diff --git a/include/gensvm_base.h b/include/gensvm_base.h
index ded0149..390a9b6 100644
--- a/include/gensvm_base.h
+++ b/include/gensvm_base.h
@@ -87,9 +87,6 @@ struct GenModel {
 	///< error matrix
 	double *H;
 	///< Huber weighted error matrix
-	double *R;
-	///< 0-1 auixiliary matrix, this matrix is n x K, with for row i a 0 on
-	///< column y[i]-1, and 1 everywhere else.
 	double *rho;
 	///< vector of instance weights
 	double training_error;
diff --git a/include/gensvm_optimize.h b/include/gensvm_optimize.h
index bef9669..3fd9607 100644
--- a/include/gensvm_optimize.h
+++ b/include/gensvm_optimize.h
@@ -22,8 +22,10 @@ void gensvm_optimize(struct GenModel *model, struct GenData *data);
 double gensvm_get_loss(struct GenModel *model, struct GenData *data,
 		double *ZV);
 
-double gensvm_calculate_omega(struct GenModel *model, long i);
-bool gensvm_majorize_is_simple(struct GenModel *model, long i);
+double gensvm_calculate_omega(struct GenModel *model, struct GenData *data,
+		long i);
+bool gensvm_majorize_is_simple(struct GenModel *model, struct GenData *data, 
+		long i);
 void gensvm_calculate_ab_non_simple(struct GenModel *model, long i, long j,
 		double *a, double *b_aq);
 void gensvm_calculate_ab_simple(struct GenModel *model, long i, long j,
@@ -34,8 +36,6 @@ double gensvm_get_Avalue_update_B(struct GenModel *model, long i, double *B);
 
 void gensvm_get_update(struct GenModel *model, struct GenData *data,
 		double *B, double *ZAZ, double *ZAZV, double *ZAZVT);
-void gensvm_category_matrix(struct GenModel *model, struct GenData *data);
-void gensvm_simplex_diff(struct GenModel *model, struct GenData *dataset);
 void gensvm_calculate_errors(struct GenModel *model, struct GenData *data,
 		double *ZV);
 void gensvm_calculate_huber(struct GenModel *model);
diff --git a/src/gensvm_base.c b/src/gensvm_base.c
index 7710fc9..2c30530 100644
--- a/src/gensvm_base.c
+++ b/src/gensvm_base.c
@@ -94,7 +94,6 @@ struct GenModel *gensvm_init_model()
 	model->UU = NULL;
 	model->Q = NULL;
 	model->H = NULL;
-	model->R = NULL;
 	model->rho = NULL;
 	model->data_file = NULL;
 
@@ -123,7 +122,6 @@ void gensvm_allocate_model(struct GenModel *model)
 	model->UU = Calloc(double, n*K*(K-1));
 	model->Q = Calloc(double, n*K);
 	model->H = Calloc(double, n*K);
-	model->R = Calloc(double, n*K);
 	model->rho = Calloc(double, n);
 }
 
@@ -156,9 +154,6 @@ void gensvm_reallocate_model(struct GenModel *model, long n, long m)
 		model->H = Realloc(model->H, double, n*K);
 		Memset(model->H, double, n*K);
 
-		model->R = Realloc(model->R, double, n*K);
-		Memset(model->R, double, n*K);
-
 		model->rho = Realloc(model->rho, double, n);
 		Memset(model->rho, double, n);
 
@@ -197,7 +192,6 @@ void gensvm_free_model(struct GenModel *model)
 	free(model->Q);
 	free(model->H);
 	free(model->rho);
-	free(model->R);
 	free(model->kernelparam);
 	free(model->data_file);
 
diff --git a/src/gensvm_optimize.c b/src/gensvm_optimize.c
index 19e697e..d08f917 100644
--- a/src/gensvm_optimize.c
+++ b/src/gensvm_optimize.c
@@ -68,7 +68,7 @@ void gensvm_optimize(struct GenModel *model, struct GenData *data)
 
 	gensvm_simplex(model->K, model->U);
 	gensvm_simplex_diff(model, data);
-	gensvm_category_matrix(model, data);
+	gensvm_simplex(model);
 
 	L = gensvm_get_loss(model, data, ZV);
 	Lbar = L + 2.0*model->epsilon*L;
@@ -141,9 +141,10 @@ double gensvm_get_loss(struct GenModel *model, struct GenData *data,
 		rowvalue = 0;
 		value = 0;
 		for (j=0; j<K; j++) {
+			if (j == (data->y[i]-1))
+				continue;
 			value = matrix_get(model->H, K, i, j);
 			value = pow(value, model->p);
-			value *= matrix_get(model->R, K, i, j);
 			rowvalue += value;
 		}
 		rowvalue = pow(rowvalue, 1.0/(model->p));
@@ -181,16 +182,18 @@ double gensvm_get_loss(struct GenModel *model, struct GenData *data,
  * @returns 		the value of omega for instance i
  *
  */
-double gensvm_calculate_omega(struct GenModel *model, long i)
+double gensvm_calculate_omega(struct GenModel *model, struct GenData *data,
+		long i)
 {
 	long j;
-	double h, r, omega = 0.0,
+	double h, omega = 0.0,
 	       p = model->p;
 
 	for (j=0; j<model->K; j++) {
+		if (j == (data->y[i]-1))
+			continue;
 		h = matrix_get(model->H, model->K, i, j);
-		r = matrix_get(model->R, model->K, i, j);
-		omega += pow(h, p)*r;
+		omega += pow(h, p);
 	}
 	omega = (1.0/p)*pow(omega, 1.0/p - 1.0);
 
@@ -211,14 +214,16 @@ double gensvm_calculate_omega(struct GenModel *model, long i)
  * @returns 		whether or not we can do simple majorization
  *
  */
-bool gensvm_majorize_is_simple(struct GenModel *model, long i)
+bool gensvm_majorize_is_simple(struct GenModel *model, struct GenData *data,
+		long i)
 {
 	long j;
-	double h, r, value = 0;
+	double h, value = 0;
 	for (j=0; j<model->K; j++) {
+		if (j == (data->y[i]-1))
+			continue;
 		h = matrix_get(model->H, model->K, i, j);
-		r = matrix_get(model->R, model->K, i, j);
-		value += (h*r > 0) ? 1 : 0;
+		value += (h > 0) ? 1 : 0;
 		if (value > 1)
 			return false;
 	}
@@ -572,34 +577,6 @@ void gensvm_get_update(struct GenModel *model, struct GenData *data,
 }
 
 /**
- * @brief Generate the category matrix
- *
- * @details
- * Generate the category matrix R. The category matrix has 1's everywhere
- * except at the column corresponding to the label of instance i, there the
- * element is 0.
- *
- * @param[in,out] 	model 		corresponding GenModel
- * @param[in] 		dataset 	corresponding GenData
- *
- */
-void gensvm_category_matrix(struct GenModel *model, struct GenData *data)
-{
-	long i, j;
-	long n = model->n;
-	long K = model->K;
-
-	for (i=0; i<n; i++) {
-		for (j=0; j<K; j++) {
-			if (data->y[i] != j+1)
-				matrix_set(model->R, K, i, j, 1.0);
-			else
-				matrix_set(model->R, K, i, j, 0.0);
-		}
-	}
-}
-
-/**
  * @brief Generate the simplex difference matrix
  *
  * @details
diff --git a/tests/src/test_gensvm_optimize.c b/tests/src/test_gensvm_optimize.c
index a91ece7..f0947a4 100644
--- a/tests/src/test_gensvm_optimize.c
+++ b/tests/src/test_gensvm_optimize.c
@@ -198,7 +198,6 @@ char *test_gensvm_get_loss_1()
 	gensvm_initialize_weights(data, model);
 	gensvm_simplex(model->K, model->U);
 	gensvm_simplex_diff(model, data);
-	gensvm_category_matrix(model, data);
 
 	matrix_set(model->V, model->K-1, 0, 0, 0.6019309459245683);
 	matrix_set(model->V, model->K-1, 0, 1, 0.0063825200426701);
@@ -297,7 +296,6 @@ char *test_gensvm_get_loss_2()
 	gensvm_initialize_weights(data, model);
 	gensvm_simplex(model->K, model->U);
 	gensvm_simplex_diff(model, data);
-	gensvm_category_matrix(model, data);
 
 	matrix_set(model->V, model->K-1, 0, 0, 0.6019309459245683);
 	matrix_set(model->V, model->K-1, 0, 1, 0.0063825200426701);
@@ -349,7 +347,6 @@ char *test_gensvm_calculate_omega()
 	model->K = K;
 	model->p = 1.213;
 	gensvm_allocate_model(model);
-	gensvm_category_matrix(model, data);
 
 	matrix_set(model->H, model->K, 0, 0, 0.8465725800087526);
 	matrix_set(model->H, model->K, 0, 1, 1.2876921677680249);
@@ -417,7 +414,6 @@ char *test_gensvm_majorize_is_simple()
 	model->K = K;
 	model->p = 1.213;
 	gensvm_allocate_model(model);
-	gensvm_category_matrix(model, data);
 
 	matrix_set(model->H, model->K, 0, 0, 0.8465725800087526);
 	matrix_set(model->H, model->K, 0, 1, 1.2876921677680249);
@@ -436,15 +432,15 @@ char *test_gensvm_majorize_is_simple()
 	matrix_set(model->H, model->K, 4, 2, 0.8184193969741095);
 
 	// start test code //
-	mu_assert(gensvm_majorize_is_simple(model, 0) == false,
+	mu_assert(gensvm_majorize_is_simple(model, data, 0) == false,
 			"Incorrect simple at 0");
-	mu_assert(gensvm_majorize_is_simple(model, 1) == true,
+	mu_assert(gensvm_majorize_is_simple(model, data, 1) == true,
 			"Incorrect simple at 1");
-	mu_assert(gensvm_majorize_is_simple(model, 2) == true,
+	mu_assert(gensvm_majorize_is_simple(model, data, 2) == true,
 			"Incorrect simple at 2");
-	mu_assert(gensvm_majorize_is_simple(model, 3) == true,
+	mu_assert(gensvm_majorize_is_simple(model, data, 3) == true,
 			"Incorrect simple at 3");
-	mu_assert(gensvm_majorize_is_simple(model, 4) == false,
+	mu_assert(gensvm_majorize_is_simple(model, data, 4) == false,
 			"Incorrect simple at 4");
 
 	// end test code //
@@ -599,7 +595,6 @@ char *test_gensvm_update_B()
 	gensvm_allocate_model(model);
 	gensvm_simplex(model->K, model->U);
 	gensvm_simplex_diff(model, data);
-	gensvm_category_matrix(model, data);
 	gensvm_initialize_weights(data, model);
 
 	// start test code //
@@ -716,7 +711,6 @@ char *test_gensvm_get_update()
 	gensvm_initialize_weights(data, model);
 	gensvm_simplex(model->K, model->U);
 	gensvm_simplex_diff(model, data);
-	gensvm_category_matrix(model, data);
 
 	// initialize V
 	matrix_set(model->V, model->K-1, 0, 0, -0.7593642121025029);
@@ -780,63 +774,6 @@ char *test_gensvm_get_update()
 	return NULL;
 }
 
-char *test_gensvm_category_matrix()
-{
-	struct GenModel *model = gensvm_init_model();
-	struct GenData *data = gensvm_init_data();
-
-	int n = 5,
-	    m = 3,
-	    K = 3;
-
-	data->n = n;
-	data->m = m;
-	data->K = K;
-
-	model->n = n;
-	model->m = m;
-	model->K = K;
-
-	gensvm_allocate_model(model);
-	data->y = Calloc(long, data->n);
-	data->y[0] = 1;
-	data->y[1] = 2;
-	data->y[2] = 3;
-	data->y[3] = 2;
-	data->y[4] = 1;
-
-	// start test code //
-
-	gensvm_category_matrix(model, data);
-
-	mu_assert(matrix_get(model->R, K, 0, 0) == 0, "Incorrect R at 0, 0");
-	mu_assert(matrix_get(model->R, K, 0, 1) == 1, "Incorrect R at 0, 1");
-	mu_assert(matrix_get(model->R, K, 0, 2) == 1, "Incorrect R at 0, 2");
-
-	mu_assert(matrix_get(model->R, K, 1, 0) == 1, "Incorrect R at 1, 0");
-	mu_assert(matrix_get(model->R, K, 1, 1) == 0, "Incorrect R at 1, 1");
-	mu_assert(matrix_get(model->R, K, 1, 2) == 1, "Incorrect R at 1, 2");
-
-	mu_assert(matrix_get(model->R, K, 2, 0) == 1, "Incorrect R at 2, 0");
-	mu_assert(matrix_get(model->R, K, 2, 1) == 1, "Incorrect R at 2, 1");
-	mu_assert(matrix_get(model->R, K, 2, 2) == 0, "Incorrect R at 2, 2");
-
-	mu_assert(matrix_get(model->R, K, 3, 0) == 1, "Incorrect R at 3, 0");
-	mu_assert(matrix_get(model->R, K, 3, 1) == 0, "Incorrect R at 3, 1");
-	mu_assert(matrix_get(model->R, K, 3, 2) == 1, "Incorrect R at 3, 2");
-
-	mu_assert(matrix_get(model->R, K, 4, 0) == 0, "Incorrect R at 4, 0");
-	mu_assert(matrix_get(model->R, K, 4, 1) == 1, "Incorrect R at 4, 1");
-	mu_assert(matrix_get(model->R, K, 4, 2) == 1, "Incorrect R at 4, 2");
-
-	// end test code //
-
-	gensvm_free_model(model);
-	gensvm_free_data(data);
-
-	return NULL;
-}
-
 char *test_gensvm_simplex_diff()
 {
 	struct GenData *data = gensvm_init_data();
@@ -1692,7 +1629,6 @@ char *all_tests()
 	mu_run_test(test_gensvm_get_Avalue_update_B);
 
 	mu_run_test(test_gensvm_get_update);
-	mu_run_test(test_gensvm_category_matrix);
 	mu_run_test(test_gensvm_simplex_diff);
 	mu_run_test(test_gensvm_calculate_errors);
 	mu_run_test(test_gensvm_calculate_huber);