void TestMatrixExtras::test_add_DD() {
size_t n = 10;
size_t m = 15;
size_t repetitions = 20;
for (size_t r = 0; r < repetitions; r++) {
Matrix A = MatrixFactory::MakeRandomMatrix(n, m, 2.0, 1.0);
Matrix B = MatrixFactory::MakeRandomMatrix(n, m, 2.0, 1.0);
double alpha = 2.0 * static_cast<double> (std::rand()) / static_cast<double> (RAND_MAX);
double gamma = -0.5 + static_cast<double> (std::rand()) / static_cast<double> (RAND_MAX);
Matrix A_copy(A);
Matrix B_copy(B);
// A = gamma*A + alpha*B
int status = Matrix::add(A, alpha, B, gamma);
_ASSERT_EQ(ForBESUtils::STATUS_OK, status);
_ASSERT_EQ(B_copy, B);
A_copy *= gamma;
B_copy *= alpha;
Matrix C = A_copy + B_copy;
_ASSERT_EQ(C, A);
}
}
void TestMatrixExtras::test_add_STST() {
size_t repetitions = 300;
for (size_t r = 0; r < repetitions; r++) {
size_t n = 10;
size_t m = 15;
size_t nnz = 70;
Matrix A = MatrixFactory::MakeRandomSparse(n, m, nnz, 2.0, 1.0);
Matrix B = MatrixFactory::MakeRandomSparse(n, m, nnz, 2.0, 1.0);
double alpha = 2.0 * static_cast<float> (std::rand()) / static_cast<float> (RAND_MAX);
double gamma = -0.5 + static_cast<float> (std::rand()) / static_cast<float> (RAND_MAX);
Matrix A_copy(A);
Matrix B_copy(B);
A.transpose();
B.transpose();
int status = Matrix::add(A, alpha, B, gamma); // A' = gamma*A' + alpha*B
_ASSERT_EQ(ForBESUtils::STATUS_OK, status);
_ASSERT_EQ(m, A.getNrows());
_ASSERT_EQ(n, A.getNcols());
for (size_t i = 0; i < m; i++) {
for (size_t j = 0; j < n; j++) {
_ASSERT_EQ(gamma * A_copy.get(j, i) + alpha * B_copy.get(j, i), A.get(i, j));
}
}
}
}
void TestMatrixExtras::test_add_DST() {
for (size_t n = 11; n < 40; n += 5) {
for (size_t m = 13; m < 30; m += 3) {
size_t nnz = 100;
Matrix A = MatrixFactory::MakeRandomMatrix(n, m, 2.0, 1.0);
Matrix B = MatrixFactory::MakeRandomSparse(m, n, nnz, 2.0, 1.0);
Matrix A_copy(A);
Matrix B_copy(B);
B.transpose();
double alpha = -1.0 + 2.0 * static_cast<double> (std::rand()) / static_cast<double> (RAND_MAX);
double gamma = -0.5 + static_cast<double> (std::rand()) / static_cast<double> (RAND_MAX);
const double tol = 1e-8;
int status = Matrix::add(A, alpha, B, gamma); // A = gamma * A + alpha * B
_ASSERT_EQ(ForBESUtils::STATUS_OK, status);
_ASSERT_EQ(n, A.getNrows());
for (size_t i = 0; i < n; i++) {
for (size_t j = 0; j < m; j++) {
_ASSERT_NUM_EQ(gamma * A_copy.get(i, j) + alpha * B_copy.get(j, i), A.get(i, j), tol);
}
}
}
}
}
MatrixViewType
top_block (const MatrixViewType& A, const bool contiguous_cache_blocks) const
{
typedef typename MatrixViewType::ordinal_type ordinal_type;
const ordinal_type nrows_top =
strategy_.top_block_split_nrows (A.nrows(), ncols(),
nrows_cache_block());
MatrixViewType A_copy (A);
return A_copy.split_top (nrows_top, contiguous_cache_blocks);
}
MatrixViewType
top_block (const MatrixViewType& A, const bool contiguous_cache_blocks) const
{
typedef typename MatrixViewType::ordinal_type ordinal_type;
// Ignore the number of columns in A, since we want to block all
// matrices using the same cache blocking strategy.
const ordinal_type nrows_top =
strategy_.top_block_split_nrows (A.nrows(), ncols(),
nrows_cache_block());
MatrixViewType A_copy (A);
return A_copy.split_top (nrows_top, contiguous_cache_blocks);
}
int main()
{
//Test some constructors
Vector<int> A_size(10);
Vector<int> A_default; Vector<int> B_default;
std::initializer_list<int> list; Vector<int> A_list(list);
Vector<int> A_copy(A_default);
for(int i = 0; i < 10; i++)
{
A_default.push_back(i);
}
return 0;
}
void TestMatrixExtras::test_add_SST() {
size_t n = 10;
size_t m = 15;
size_t nnz = std::ceil(n * m / 2);
size_t repetitions = 300;
for (size_t r = 0; r < repetitions; r++) {
Matrix A = MatrixFactory::MakeRandomSparse(n, m, nnz, 2.0, 1.0);
Matrix B = MatrixFactory::MakeRandomSparse(m, n, nnz, 2.0, 1.0);
double alpha = 2.0 * static_cast<float> (std::rand()) / static_cast<float> (RAND_MAX);
double gamma = -0.5 + static_cast<float> (std::rand()) / static_cast<float> (RAND_MAX);
Matrix B_copy(B);
B.transpose();
Matrix A_copy(A);
int status = Matrix::add(A, alpha, B, gamma); // A = gamma*A + alpha*B'
_ASSERT_EQ(ForBESUtils::STATUS_OK, status);
_ASSERT_EQ(n, A.getNrows());
_ASSERT_EQ(m, A.getNcols());
for (size_t i = 0; i < n; i++) {
for (size_t j = 0; j < m; j++) {
_ASSERT_NUM_EQ(gamma * A_copy.get(i, j) + alpha * B_copy.get(j, i), A.get(i, j), 1e-8);
}
}
Matrix S(A_copy);
S *= gamma;
Matrix T(B);
T *= alpha;
S += T;
_ASSERT_EQ(S, A);
}
}
