fix problems with dense ZV computation when data->n < model->n

1 files changed, 140 insertions, 4 deletions

diff --git a/tests/src/test_gensvm_zv.c b/tests/src/test_gensvm_zv.c
index 21dd897..9fd206d 100644
--- a/tests/src/test_gensvm_zv.c
+++ b/tests/src/test_gensvm_zv.c
@@ -25,7 +25,7 @@
 #include "minunit.h"
 #include "gensvm_zv.h"
 
-char *test_zv_dense()
+char *test_zv_dense_1()
 {
 	int n = 8,
 	    m = 3,
@@ -129,7 +129,71 @@ char *test_zv_dense()
 	return NULL;
 }
 
-char *test_zv_sparse()
+char *test_zv_dense_2()
+{
+	int n = 8,
+	    m = 3,
+	    K = 3;
+
+	struct GenModel *model = gensvm_init_model();
+	model->n = n;
+	model->m = m;
+	model->K = K;
+	model->V = Calloc(double, (m+1)*(K-1));
+	matrix_set(model->V, model->K-1, 0, 0, 0.9025324416711976);
+	matrix_set(model->V, model->K-1, 0, 1, 0.9776784486541952);
+	matrix_set(model->V, model->K-1, 1, 0, 0.8336347240271171);
+	matrix_set(model->V, model->K-1, 1, 1, 0.1213543508830703);
+	matrix_set(model->V, model->K-1, 2, 0, 0.9401310852208050);
+	matrix_set(model->V, model->K-1, 2, 1, 0.7407478086613410);
+	matrix_set(model->V, model->K-1, 3, 0, 0.9053353815353901);
+	matrix_set(model->V, model->K-1, 3, 1, 0.8056059951641629);
+
+	struct GenData *data = gensvm_init_data();
+	data->n = 3;
+	data->m = m;
+	data->K = K;
+	data->Z = Calloc(double, data->n*(data->m+1));
+	matrix_set(data->Z, data->m+1, 0, 0, 1.0000000000000000);
+	matrix_set(data->Z, data->m+1, 0, 1, 0.4787662921736276);
+	matrix_set(data->Z, data->m+1, 0, 2, 0.7983044792882817);
+	matrix_set(data->Z, data->m+1, 0, 3, 0.4273006962165122);
+	matrix_set(data->Z, data->m+1, 1, 0, 1.0000000000000000);
+	matrix_set(data->Z, data->m+1, 1, 1, 0.7160319769123790);
+	matrix_set(data->Z, data->m+1, 1, 2, 0.5233066338418962);
+	matrix_set(data->Z, data->m+1, 1, 3, 0.4063256860579537);
+	matrix_set(data->Z, data->m+1, 2, 0, 1.0000000000000000);
+	matrix_set(data->Z, data->m+1, 2, 1, 0.3735389652435536);
+	matrix_set(data->Z, data->m+1, 2, 2, 0.8156214578257802);
+	matrix_set(data->Z, data->m+1, 2, 3, 0.6928367712901857);
+
+	// start test code //
+	double *ZV = Calloc(double, data->n*(K-1));
+	double eps = 1e-14;
+	gensvm_calculate_ZV(model, data, ZV);
+
+	mu_assert(fabs(matrix_get(ZV, K-1, 0, 0) - 2.4390099428102818) < eps,
+			"Incorrect ZV at 0, 0");
+	mu_assert(fabs(matrix_get(ZV, K-1, 0, 1) - 1.9713571175527906) < eps,
+			"Incorrect ZV at 0, 1");
+	mu_assert(fabs(matrix_get(ZV, K-1, 1, 0) - 2.3592794147310747) < eps,
+			"Incorrect ZV at 1, 0");
+	mu_assert(fabs(matrix_get(ZV, K-1, 1, 1) - 1.7795486953777246) < eps,
+			"Incorrect ZV at 1, 1");
+	mu_assert(fabs(matrix_get(ZV, K-1, 2, 0) - 2.6079682228282564) < eps,
+			"Incorrect ZV at 2, 0");
+	mu_assert(fabs(matrix_get(ZV, K-1, 2, 1) - 2.1853322915140310) < eps,
+			"Incorrect ZV at 2, 1");
+
+	free(ZV);
+	// end test code //
+	gensvm_free_data(data);
+	gensvm_free_model(model);
+
+	return NULL;
+}
+
+char *test_zv_sparse_1()
 {
 	int n = 8,
 	    m = 3,
@@ -239,11 +303,83 @@ char *test_zv_sparse()
 	return NULL;
 }
 
+char *test_zv_sparse_2()
+{
+	int n = 8,
+	    m = 3,
+	    K = 3;
+
+	struct GenModel *model = gensvm_init_model();
+	model->n = n;
+	model->m = m;
+	model->K = K;
+	model->V = Calloc(double, (m+1)*(K-1));
+	matrix_set(model->V, model->K-1, 0, 0, 0.9025324416711976);
+	matrix_set(model->V, model->K-1, 0, 1, 0.9776784486541952);
+	matrix_set(model->V, model->K-1, 1, 0, 0.8336347240271171);
+	matrix_set(model->V, model->K-1, 1, 1, 0.1213543508830703);
+	matrix_set(model->V, model->K-1, 2, 0, 0.9401310852208050);
+	matrix_set(model->V, model->K-1, 2, 1, 0.7407478086613410);
+	matrix_set(model->V, model->K-1, 3, 0, 0.9053353815353901);
+	matrix_set(model->V, model->K-1, 3, 1, 0.8056059951641629);
+
+	struct GenData *data = gensvm_init_data();
+	data->n = 3;
+	data->m = m;
+	data->K = K;
+	data->Z = Calloc(double, data->n*(data->m+1));
+	matrix_set(data->Z, data->m+1, 0, 0, 1.0000000000000000);
+	matrix_set(data->Z, data->m+1, 0, 1, 0.4787662921736276);
+	matrix_set(data->Z, data->m+1, 0, 2, 0.7983044792882817);
+	matrix_set(data->Z, data->m+1, 0, 3, 0.4273006962165122);
+	matrix_set(data->Z, data->m+1, 1, 0, 1.0000000000000000);
+	matrix_set(data->Z, data->m+1, 1, 1, 0.7160319769123790);
+	matrix_set(data->Z, data->m+1, 1, 2, 0.5233066338418962);
+	matrix_set(data->Z, data->m+1, 1, 3, 0.4063256860579537);
+	matrix_set(data->Z, data->m+1, 2, 0, 1.0000000000000000);
+	matrix_set(data->Z, data->m+1, 2, 1, 0.3735389652435536);
+	matrix_set(data->Z, data->m+1, 2, 2, 0.8156214578257802);
+	matrix_set(data->Z, data->m+1, 2, 3, 0.6928367712901857);
+
+	// convert Z to sparse matrix
+	data->spZ = gensvm_dense_to_sparse(data->Z, data->n, data->m+1);
+	free(data->Z);
+	data->RAW = NULL;
+	data->Z = NULL;
+
+	// start test code //
+	double *ZV = Calloc(double, data->n*(data->K-1));
+	double eps = 1e-14;
+	gensvm_calculate_ZV(model, data, ZV);
+
+	mu_assert(fabs(matrix_get(ZV, K-1, 0, 0) - 2.4390099428102818) < eps,
+			"Incorrect ZV at 0, 0");
+	mu_assert(fabs(matrix_get(ZV, K-1, 0, 1) - 1.9713571175527906) < eps,
+			"Incorrect ZV at 0, 1");
+	mu_assert(fabs(matrix_get(ZV, K-1, 1, 0) - 2.3592794147310747) < eps,
+			"Incorrect ZV at 1, 0");
+	mu_assert(fabs(matrix_get(ZV, K-1, 1, 1) - 1.7795486953777246) < eps,
+			"Incorrect ZV at 1, 1");
+	mu_assert(fabs(matrix_get(ZV, K-1, 2, 0) - 2.6079682228282564) < eps,
+			"Incorrect ZV at 2, 0");
+	mu_assert(fabs(matrix_get(ZV, K-1, 2, 1) - 2.1853322915140310) < eps,
+			"Incorrect ZV at 2, 1");
+
+	free(ZV);
+	// end test code //
+	gensvm_free_data(data);
+	gensvm_free_model(model);
+
+	return NULL;
+}
+
 char *all_tests()
 {
 	mu_suite_start();
-	mu_run_test(test_zv_dense);
-	mu_run_test(test_zv_sparse);
+	mu_run_test(test_zv_dense_1);
+	mu_run_test(test_zv_dense_2);
+	mu_run_test(test_zv_sparse_1);
+	mu_run_test(test_zv_sparse_2);
 
 	return NULL;
 }