/** Deallocate a matrix.
*
* \ingroup allocate_group
*
* \param A The matrix.
*/
void
bml_deallocate_ellpack(
bml_matrix_ellpack_t * A)
{
bml_free_memory(A->value);
bml_free_memory(A->index);
bml_free_memory(A->nnz);
bml_free_memory(A);
}
int TYPED_FUNC(
test_copy) (
const int N,
const bml_matrix_type_t matrix_type,
const bml_matrix_precision_t matrix_precision,
const int M)
{
bml_matrix_t *A = NULL;
bml_matrix_t *B = NULL;
bml_matrix_t *C = NULL;
REAL_T *A_dense = NULL;
REAL_T *B_dense = NULL;
REAL_T *C_dense = NULL;
A = bml_random_matrix(matrix_type, matrix_precision, N, M);
B = bml_copy_new(A);
C = bml_zero_matrix(matrix_type, matrix_precision, N, M);
bml_copy(B, C);
A_dense = bml_convert_to_dense(A, dense_row_major);
B_dense = bml_convert_to_dense(B, dense_row_major);
C_dense = bml_convert_to_dense(C, dense_row_major);
bml_print_dense_matrix(N, matrix_precision, dense_row_major, A_dense, 0,
N, 0, N);
bml_print_dense_matrix(N, matrix_precision, dense_row_major, B_dense, 0,
N, 0, N);
bml_print_dense_matrix(N, matrix_precision, dense_row_major, C_dense, 0,
N, 0, N);
for (int i = 0; i < N * N; i++)
{
if (ABS(A_dense[i] - B_dense[i]) > 1e-12 ||
ABS(A_dense[i] - C_dense[i]) > 1e-12)
{
LOG_ERROR("matrices are not identical; A[%d] = %e\n", i,
A_dense[i]);
return -1;
}
}
bml_free_memory(A_dense);
bml_free_memory(B_dense);
bml_free_memory(C_dense);
bml_deallocate(&A);
bml_deallocate(&B);
bml_deallocate(&C);
LOG_INFO("copy matrix test passed\n");
return 0;
}
int
test_function(
const int N,
const bml_matrix_type_t matrix_type,
const bml_matrix_precision_t matrix_precision,
const int M)
{
bml_matrix_t *A = NULL;
bml_matrix_t *B = NULL;
double *A_gbnd = NULL;
double *B_gbnd = NULL;
REAL_T *A_dense = NULL;
REAL_T *B_dense = NULL;
double scale_factor = 2.5;
double threshold = 0.0;
A = bml_identity_matrix(matrix_type, matrix_precision, N, M);
bml_scale_inplace(scale_factor, A);
A_gbnd = bml_gershgorin(A);
A_dense = bml_export_to_dense(A, dense_row_major);
A_dense[0] = scale_factor * scale_factor;
B = bml_import_from_dense(matrix_type, matrix_precision, dense_row_major,
N, A_dense, threshold, M);
B_gbnd = bml_gershgorin(B);
bml_free_memory(A_dense);
A_dense = bml_export_to_dense(A, dense_row_major);
B_dense = bml_export_to_dense(B, dense_row_major);
bml_print_dense_matrix(N, matrix_precision, dense_row_major, A_dense, 0,
N, 0, N);
bml_print_dense_matrix(N, matrix_precision, dense_row_major, B_dense, 0,
N, 0, N);
bml_normalize(B, B_gbnd[0], B_gbnd[1]);
bml_free_memory(B_dense);
B_dense = bml_export_to_dense(B, dense_row_major);
bml_print_dense_matrix(N, matrix_precision, dense_row_major, B_dense, 0,
N, 0, N);
if ((fabs(A_gbnd[0] - scale_factor)) > REL_TOL || A_gbnd[1] > REL_TOL)
{
LOG_ERROR
("incorrect maxeval or maxminusmin; maxeval = %e maxminusmin = %e\n",
A_gbnd[0], A_gbnd[1]);
return -1;
}
if ((fabs(B_gbnd[0] - scale_factor * scale_factor)) > REL_TOL ||
(fabs(B_gbnd[1] - (scale_factor * scale_factor - scale_factor))) >
REL_TOL)
{
LOG_ERROR
("incorrect maxeval or maxminusmin; maxeval = %e maxminusmin = %e\n",
B_gbnd[0], B_gbnd[1]);
return -1;
}
if (fabs(B_dense[0]) > REL_TOL)
{
LOG_ERROR
("normalize error, incorrect maxeval or maxminusmin; maxeval = %e maxminusmin = %e\n",
B_gbnd[0], B_gbnd[1]);
return -1;
}
LOG_INFO("normalize matrix test passed\n");
bml_free_memory(A_dense);
bml_free_memory(B_dense);
bml_free_memory(A_gbnd);
bml_free_memory(B_gbnd);
bml_deallocate(&A);
bml_deallocate(&B);
return 0;
}
