Add functionality for cv_util for sparse matrices

1 files changed, 168 insertions, 3 deletions

diff --git a/tests/src/test_gensvm_cv_util.c b/tests/src/test_gensvm_cv_util.c
index 5cbf174..2d6ecb7 100644
--- a/tests/src/test_gensvm_cv_util.c
+++ b/tests/src/test_gensvm_cv_util.c
@@ -90,8 +90,7 @@ char *test_make_cv_split_2()
 	return NULL;
 }
 
-
-char *test_get_tt_split()
+char *test_get_tt_split_dense()
 {
 	struct GenData *full = gensvm_init_data();
 	full->K = 3;
@@ -132,6 +131,7 @@ char *test_get_tt_split()
 	matrix_set(full->RAW, full->m+1, 8, 2, 9.0);
 	matrix_set(full->RAW, full->m+1, 9, 1, 10.0);
 	matrix_set(full->RAW, full->m+1, 9, 2, 10.0);
+	full->Z = full->RAW;
 
 	long *cv_idx = Calloc(long, full->n);
 	cv_idx[0] = 1;
@@ -243,13 +243,178 @@ char *test_get_tt_split()
 	return NULL;
 }
 
+char *test_get_tt_split_sparse()
+{
+	struct GenData *full = gensvm_init_data();
+	full->K = 3;
+	full->n = 10;
+	full->m = 2;
+	full->r = 2;
+
+	full->y = Calloc(long, full->n);
+	full->y[0] = 1;
+	full->y[1] = 2;
+	full->y[2] = 3;
+	full->y[3] = 1;
+	full->y[4] = 2;
+	full->y[5] = 3;
+	full->y[6] = 1;
+	full->y[7] = 2;
+	full->y[8] = 3;
+	full->y[9] = 1;
+
+	full->RAW = Calloc(double, full->n * (full->m+1));
+	matrix_set(full->RAW, full->m+1, 0, 1, 1.0);
+	matrix_set(full->RAW, full->m+1, 0, 2, 1.0);
+	matrix_set(full->RAW, full->m+1, 1, 1, 2.0);
+	matrix_set(full->RAW, full->m+1, 1, 2, 2.0);
+	matrix_set(full->RAW, full->m+1, 2, 1, 3.0);
+	matrix_set(full->RAW, full->m+1, 2, 2, 3.0);
+	matrix_set(full->RAW, full->m+1, 3, 1, 4.0);
+	matrix_set(full->RAW, full->m+1, 3, 2, 4.0);
+	matrix_set(full->RAW, full->m+1, 4, 1, 5.0);
+	matrix_set(full->RAW, full->m+1, 4, 2, 5.0);
+	matrix_set(full->RAW, full->m+1, 5, 1, 6.0);
+	matrix_set(full->RAW, full->m+1, 5, 2, 6.0);
+	matrix_set(full->RAW, full->m+1, 6, 1, 7.0);
+	matrix_set(full->RAW, full->m+1, 6, 2, 7.0);
+	matrix_set(full->RAW, full->m+1, 7, 1, 8.0);
+	matrix_set(full->RAW, full->m+1, 7, 2, 8.0);
+	matrix_set(full->RAW, full->m+1, 8, 1, 9.0);
+	matrix_set(full->RAW, full->m+1, 8, 2, 9.0);
+	matrix_set(full->RAW, full->m+1, 9, 1, 10.0);
+	matrix_set(full->RAW, full->m+1, 9, 2, 10.0);
+	full->Z = full->RAW;
+
+	// convert Z to a sparse matrix to test the sparse functions
+	full->spZ = gensvm_dense_to_sparse(full->RAW, full->n, full->m+1);
+	free(full->RAW);
+	full->RAW = NULL;
+	full->Z = NULL;
+
+	long *cv_idx = Calloc(long, full->n);
+	cv_idx[0] = 1;
+	cv_idx[1] = 0;
+	cv_idx[2] = 1;
+	cv_idx[3] = 0;
+	cv_idx[4] = 1;
+	cv_idx[5] = 2;
+	cv_idx[6] = 3;
+	cv_idx[7] = 2;
+	cv_idx[8] = 3;
+	cv_idx[9] = 2;
+
+	struct GenData *train = gensvm_init_data();
+	struct GenData *test = gensvm_init_data();
+
+	// start test code //
+	gensvm_get_tt_split(full, train, test, cv_idx, 0);
+
+	mu_assert(train->n == 8, "train_n incorrect.");
+	mu_assert(test->n == 2, "test_n incorrect.");
+
+	mu_assert(train->m == 2, "train_m incorrect.");
+	mu_assert(test->m == 2, "test_m incorrect.");
+
+	mu_assert(train->K == 3, "train_K incorrect.");
+	mu_assert(test->K == 3, "test_K incorrect.");
+
+	mu_assert(train->y[0] == 1, "train y incorrect.");
+	mu_assert(train->y[1] == 3, "train y incorrect.");
+	mu_assert(train->y[2] == 2, "train y incorrect.");
+	mu_assert(train->y[3] == 3, "train y incorrect.");
+	mu_assert(train->y[4] == 1, "train y incorrect.");
+	mu_assert(train->y[5] == 2, "train y incorrect.");
+	mu_assert(train->y[6] == 3, "train y incorrect.");
+	mu_assert(train->y[7] == 1, "train y incorrect.");
+
+	mu_assert(test->y[0] == 2, "test y incorrect.");
+	mu_assert(test->y[1] == 1, "test y incorrect.");
+
+	// check the train GenSparse struct
+	mu_assert(train->spZ->nnz == 16, "train nnz incorrect");
+	mu_assert(train->spZ->n_row == 8, "train n_row incorrect");
+	mu_assert(train->spZ->n_col == 3, "train n_col incorrect");
+
+	mu_assert(train->spZ->values[0] == 1.0, "Wrong train value at 0");
+	mu_assert(train->spZ->values[1] == 1.0, "Wrong train value at 1");
+	mu_assert(train->spZ->values[2] == 3.0, "Wrong train value at 2");
+	mu_assert(train->spZ->values[3] == 3.0, "Wrong train value at 3");
+	mu_assert(train->spZ->values[4] == 5.0, "Wrong train value at 4");
+	mu_assert(train->spZ->values[5] == 5.0, "Wrong train value at 5");
+	mu_assert(train->spZ->values[6] == 6.0, "Wrong train value at 6");
+	mu_assert(train->spZ->values[7] == 6.0, "Wrong train value at 7");
+	mu_assert(train->spZ->values[8] == 7.0, "Wrong train value at 8");
+	mu_assert(train->spZ->values[9] == 7.0, "Wrong train value at 9");
+	mu_assert(train->spZ->values[10] == 8.0, "Wrong train value at 10");
+	mu_assert(train->spZ->values[11] == 8.0, "Wrong train value at 11");
+	mu_assert(train->spZ->values[12] == 9.0, "Wrong train value at 12");
+	mu_assert(train->spZ->values[13] == 9.0, "Wrong train value at 13");
+	mu_assert(train->spZ->values[14] == 10.0, "Wrong train value at 14");
+	mu_assert(train->spZ->values[15] == 10.0, "Wrong train value at 15");
+
+	mu_assert(train->spZ->ia[0] == 0, "Wrong train ia at 0");
+	mu_assert(train->spZ->ia[1] == 2, "Wrong train ia at 1");
+	mu_assert(train->spZ->ia[2] == 4, "Wrong train ia at 2");
+	mu_assert(train->spZ->ia[3] == 6, "Wrong train ia at 3");
+	mu_assert(train->spZ->ia[4] == 8, "Wrong train ia at 4");
+	mu_assert(train->spZ->ia[5] == 10, "Wrong train ia at 5");
+	mu_assert(train->spZ->ia[6] == 12, "Wrong train ia at 6");
+	mu_assert(train->spZ->ia[7] == 14, "Wrong train ia at 7");
+	mu_assert(train->spZ->ia[8] == 16, "Wrong train ia at 8");
+
+	mu_assert(train->spZ->ja[0] == 1, "Wrong train ja at 0");
+	mu_assert(train->spZ->ja[1] == 2, "Wrong train ja at 1");
+	mu_assert(train->spZ->ja[2] == 1, "Wrong train ja at 2");
+	mu_assert(train->spZ->ja[3] == 2, "Wrong train ja at 3");
+	mu_assert(train->spZ->ja[4] == 1, "Wrong train ja at 4");
+	mu_assert(train->spZ->ja[5] == 2, "Wrong train ja at 5");
+	mu_assert(train->spZ->ja[6] == 1, "Wrong train ja at 6");
+	mu_assert(train->spZ->ja[7] == 2, "Wrong train ja at 7");
+	mu_assert(train->spZ->ja[8] == 1, "Wrong train ja at 8");
+	mu_assert(train->spZ->ja[9] == 2, "Wrong train ja at 9");
+	mu_assert(train->spZ->ja[10] == 1, "Wrong train ja at 10");
+	mu_assert(train->spZ->ja[11] == 2, "Wrong train ja at 11");
+	mu_assert(train->spZ->ja[12] == 1, "Wrong train ja at 12");
+	mu_assert(train->spZ->ja[13] == 2, "Wrong train ja at 13");
+	mu_assert(train->spZ->ja[14] == 1, "Wrong train ja at 14");
+	mu_assert(train->spZ->ja[15] == 2, "Wrong train ja at 15");
+
+	// check the test GenSparse struct
+	mu_assert(test->spZ->nnz == 4, "test nnz incorrect");
+	mu_assert(test->spZ->n_row == 2, "test n_row incorrect");
+	mu_assert(test->spZ->n_col == 3, "test n_col incorrect");
+
+	mu_assert(test->spZ->values[0] == 2.0, "Wrong test value at 0");
+	mu_assert(test->spZ->values[1] == 2.0, "Wrong test value at 1");
+	mu_assert(test->spZ->values[2] == 4.0, "Wrong test value at 2");
+	mu_assert(test->spZ->values[3] == 4.0, "Wrong test value at 3");
+
+	mu_assert(test->spZ->ia[0] == 0, "Wrong test ia at 0");
+	mu_assert(test->spZ->ia[1] == 2, "Wrong test ia at 1");
+	mu_assert(test->spZ->ia[2] == 4, "Wrong test ia at 2");
+
+	mu_assert(test->spZ->ja[0] == 1, "Wrong test ja at 0");
+	mu_assert(test->spZ->ja[1] == 2, "Wrong test ja at 1");
+	mu_assert(test->spZ->ja[2] == 1, "Wrong test ja at 2");
+	mu_assert(test->spZ->ja[3] == 2, "Wrong test ja at 3");
+
+	// end test code //
+	gensvm_free_data(full);
+	gensvm_free_data(train);
+	gensvm_free_data(test);
+	free(cv_idx);
+
+	return NULL;
+}
 
 char *all_tests()
 {
 	mu_suite_start();
 	mu_run_test(test_make_cv_split_1);
 	mu_run_test(test_make_cv_split_2);
-	mu_run_test(test_get_tt_split);
+	mu_run_test(test_get_tt_split_dense);
+	mu_run_test(test_get_tt_split_sparse);
 
 	return NULL;
 }