#include "fesa/math/matrix.h" #include #include #include #include #include namespace fesa { namespace { TEST(DenseMath, RowMajorMatrixMatchesKnownGemvGemm) { const std::size_t wraparound_rows = (std::numeric_limits::max)() / 2U + 1U; EXPECT_THROW(static_cast(Matrix{wraparound_rows, 2}), std::length_error); Matrix zero_rows{0, 3}; Vector three_values{3, 2.0}; const Vector zero_row_product = zero_rows.Multiply(three_values); EXPECT_EQ(zero_row_product.Size(), 0U); Matrix zero_columns{2, 0}; const Vector zero_column_product = zero_columns.Multiply(Vector{0}); ASSERT_EQ(zero_column_product.Size(), 2U); EXPECT_DOUBLE_EQ(zero_column_product[0], 0.0); EXPECT_DOUBLE_EQ(zero_column_product[1], 0.0); Matrix zero_inner_right{0, 3}; const Matrix zero_inner_product = zero_columns.Multiply(zero_inner_right); EXPECT_EQ(zero_inner_product.Rows(), 2U); EXPECT_EQ(zero_inner_product.Columns(), 3U); for (std::size_t row = 0; row < zero_inner_product.Rows(); ++row) { for (std::size_t column = 0; column < zero_inner_product.Columns(); ++column) { EXPECT_DOUBLE_EQ(zero_inner_product(row, column), 0.0); } } Matrix left{2, 3}; left(0, 0) = 1.0; left(0, 1) = 2.0; left(0, 2) = 3.0; left(1, 0) = 4.0; left(1, 1) = 5.0; left(1, 2) = 6.0; EXPECT_EQ(&left(0, 0) + 1, &left(0, 1)); EXPECT_EQ(&left(0, 0) + 2, &left(0, 2)); EXPECT_EQ(&left(0, 0) + 3, &left(1, 0)); const Matrix& const_left = left; EXPECT_DOUBLE_EQ(const_left(1, 2), 6.0); Matrix copied{left}; copied(0, 0) = 42.0; EXPECT_DOUBLE_EQ(left(0, 0), 1.0); Matrix copy_assigned{0, 0}; copy_assigned = left; copy_assigned(1, 2) = -7.0; EXPECT_DOUBLE_EQ(left(1, 2), 6.0); Matrix moved{std::move(copied)}; EXPECT_EQ(copied.Rows(), 0U); EXPECT_EQ(copied.Columns(), 0U); EXPECT_EQ(moved.Rows(), 2U); EXPECT_EQ(moved.Columns(), 3U); EXPECT_DOUBLE_EQ(moved(0, 0), 42.0); EXPECT_NO_THROW(static_cast(copied.Multiply(Vector{0}))); Matrix move_assigned{1, 1, -1.0}; move_assigned = std::move(copy_assigned); EXPECT_EQ(copy_assigned.Rows(), 0U); EXPECT_EQ(copy_assigned.Columns(), 0U); EXPECT_EQ(move_assigned.Rows(), 2U); EXPECT_EQ(move_assigned.Columns(), 3U); EXPECT_DOUBLE_EQ(move_assigned(1, 2), -7.0); Vector vector{3}; vector[0] = 7.0; vector[1] = 8.0; vector[2] = 9.0; const Vector matrix_vector_product = left.Multiply(vector); ASSERT_EQ(matrix_vector_product.Size(), 2U); EXPECT_DOUBLE_EQ(matrix_vector_product[0], 50.0); EXPECT_DOUBLE_EQ(matrix_vector_product[1], 122.0); Matrix right{3, 2}; right(0, 0) = 7.0; right(0, 1) = 8.0; right(1, 0) = 9.0; right(1, 1) = 10.0; right(2, 0) = 11.0; right(2, 1) = 12.0; const Matrix matrix_product = left.Multiply(right); ASSERT_EQ(matrix_product.Rows(), 2U); ASSERT_EQ(matrix_product.Columns(), 2U); EXPECT_DOUBLE_EQ(matrix_product(0, 0), 58.0); EXPECT_DOUBLE_EQ(matrix_product(0, 1), 64.0); EXPECT_DOUBLE_EQ(matrix_product(1, 0), 139.0); EXPECT_DOUBLE_EQ(matrix_product(1, 1), 154.0); EXPECT_THROW(static_cast(left(2, 0)), std::out_of_range); EXPECT_THROW(static_cast(left(0, 3)), std::out_of_range); EXPECT_THROW(static_cast(const_left(2, 0)), std::out_of_range); EXPECT_THROW(static_cast(left.Multiply(Vector{2})), std::invalid_argument); EXPECT_THROW(static_cast(left.Multiply(Matrix{4, 1})), std::invalid_argument); } TEST(DenseMath, MatrixContiguousScaleAndRobustNorm) { Matrix matrix{2U, 3U}; const double entries[]{1.0, -2.0, 3.0, -4.0, 5.0, -6.0}; for (std::size_t i = 0; i < 6U; ++i) matrix.Data()[i] = entries[i]; const Matrix& immutable = matrix; EXPECT_EQ(immutable.Data() + 3, &immutable(1U, 0U)); EXPECT_NEAR(matrix.Norm(), std::sqrt(91.0), 2.0e-15); matrix.Scale(-2.0); for (std::size_t i = 0; i < 6U; ++i) EXPECT_DOUBLE_EQ(matrix.Data()[i], -2.0 * entries[i]); EXPECT_DOUBLE_EQ(immutable(1U, 2U), 12.0); Matrix huge{1U, 2U, 1.0e308}; EXPECT_NEAR(huge.Norm() / 1.0e308, std::sqrt(2.0), 4.0e-16); Matrix tiny{2U, 1U, 1.0e-300}; EXPECT_NEAR(tiny.Norm() / 1.0e-300, std::sqrt(2.0), 4.0e-16); Matrix empty{0U, (std::numeric_limits::max)()}; EXPECT_DOUBLE_EQ(empty.Norm(), 0.0); EXPECT_NO_THROW(empty.Scale(3.0)); } TEST(DenseMath, MatrixProductKeepsShapeAndFiniteValidationOrder) { const double nan = (std::numeric_limits::quiet_NaN)(); Matrix matrix{1U, 2U, nan}; try { static_cast(matrix.Multiply(Vector{1U})); FAIL() << "Shape mismatch was accepted"; } catch (const std::invalid_argument& failure) { EXPECT_STREQ(failure.what(), "Matrix-vector multiplication has incompatible dimensions."); } EXPECT_THROW(static_cast(matrix.Multiply(Vector{2U})), std::invalid_argument); EXPECT_THROW(static_cast(matrix.Multiply(Matrix{2U, 0U})), std::invalid_argument); EXPECT_THROW(static_cast(Matrix{0U, 2U}.Multiply(Vector{2U, nan})), std::invalid_argument); const Matrix finite{2U, 2U, 3.0}; const auto square = finite.Multiply(finite); EXPECT_DOUBLE_EQ(square(0U, 0U), 18.0); EXPECT_DOUBLE_EQ(finite(0U, 0U), 3.0); } TEST(DenseMath, MatrixSelfAssignmentPreservesShapeAndStorage) { Matrix matrix{2U, 1U, 7.0}; const Matrix* same = &matrix; matrix = *same; EXPECT_EQ(matrix.Rows(), 2U); EXPECT_EQ(matrix.Columns(), 1U); EXPECT_DOUBLE_EQ(matrix(1U, 0U), 7.0); Matrix* mutable_same = &matrix; matrix = std::move(*mutable_same); EXPECT_EQ(matrix.Rows(), 2U); EXPECT_DOUBLE_EQ(matrix(1U, 0U), 7.0); } } // namespace TEST(DenseMath, MatrixProductsRejectNonfiniteOperandsAndPreserveValidReuse) { Matrix left{2U, 2U, 1.0}; Matrix right{2U, 1U, 2.0}; Vector rhs{2U, 2.0}; rhs[1U] = std::numeric_limits::infinity(); EXPECT_THROW(static_cast(left.Multiply(rhs)), std::invalid_argument); rhs[1U] = 2.0; left(0U, 1U) = std::numeric_limits::quiet_NaN(); EXPECT_THROW(static_cast(left.Multiply(rhs)), std::invalid_argument); EXPECT_THROW(static_cast(left.Multiply(right)), std::invalid_argument); left(0U, 1U) = 1.0; right(1U, 0U) = std::numeric_limits::infinity(); EXPECT_THROW(static_cast(left.Multiply(right)), std::invalid_argument); right(1U, 0U) = 2.0; EXPECT_DOUBLE_EQ(left.Multiply(rhs)[0U], 4.0); EXPECT_DOUBLE_EQ(left.Multiply(right)(1U, 0U), 4.0); } } // namespace fesa