KOKO\Mimi
113 lines
3.8 KiB
C++
113 lines
3.8 KiB
C++
#include "math/dense_blas_internal.h"
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#include <gtest/gtest.h>
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#include <array>
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#include <cmath>
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#include <cstddef>
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#include <limits>
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#include <stdexcept>
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namespace fesa::dense_blas_internal {
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namespace {
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TEST(DenseBlasInternal, CDup003ConvertsZeroNormalAndOverflowLengths) {
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const auto zero = ToMklSize(0U);
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ASSERT_TRUE(zero.HasValue());
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EXPECT_EQ(zero.Value(), 0);
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const auto normal = ToMklSize(3U);
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ASSERT_TRUE(normal.HasValue());
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EXPECT_EQ(normal.Value(), 3);
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const std::size_t overflow =
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static_cast<std::size_t>((std::numeric_limits<MKL_INT>::max)()) + 1U;
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const auto rejected = ToMklSize(overflow);
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EXPECT_FALSE(rejected.HasValue());
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EXPECT_FALSE(rejected.GetStatus().IsOk());
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}
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TEST(DenseBlasInternal, CDup003CopiesZeroAndNonzeroContiguousValues) {
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EXPECT_NO_THROW(CopyValues(nullptr, 0U, nullptr));
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const std::array<double, 3U> source{1.25, -2.5, 4.0};
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std::array<double, 3U> destination{};
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CopyValues(source.data(), source.size(), destination.data());
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EXPECT_EQ(destination, source);
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}
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TEST(DenseBlasInternal, TransposeProductChecksShapeAndKnownRectangularAction) {
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Matrix left{3U, 2U};
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Matrix right{3U, 1U};
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for (std::size_t row = 0; row < 3U; ++row) {
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left(row, 0U) = static_cast<double>(row + 1U);
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left(row, 1U) = 2.0;
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right(row, 0U) = static_cast<double>(row);
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}
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const auto product = MultiplyTransposeLeft(left, right);
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ASSERT_EQ(product.Rows(), 2U);
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ASSERT_EQ(product.Columns(), 1U);
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EXPECT_DOUBLE_EQ(product(0U, 0U), 8.0);
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EXPECT_DOUBLE_EQ(product(1U, 0U), 6.0);
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EXPECT_THROW(static_cast<void>(MultiplyTransposeLeft(left, Matrix{2U, 1U})),
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std::invalid_argument);
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const auto empty = MultiplyTransposeLeft(Matrix{0U, 2U}, Matrix{0U, 3U});
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EXPECT_EQ(empty.Rows(), 2U);
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EXPECT_EQ(empty.Columns(), 3U);
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EXPECT_DOUBLE_EQ(empty(1U, 2U), 0.0);
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}
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TEST(DenseBlasInternal, DiagonalProductKeepsEntrywiseCancellationAndChecks) {
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Vector diagonal{3U};
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diagonal[0U] = 4;
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diagonal[1U] = 2;
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diagonal[2U] = -1;
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Vector input{3U};
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const double large = std::ldexp(1.0, 56);
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input[0U] = 1;
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input[1U] = -large;
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input[2U] = 2 * large;
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const auto product = MultiplyDiagonal(diagonal, input);
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EXPECT_DOUBLE_EQ(product[0U] + (product[1U] - product[2U]), 4);
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EXPECT_EQ(MultiplyDiagonal(Vector{0U}, Vector{0U}).Size(), 0U);
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EXPECT_THROW(static_cast<void>(MultiplyDiagonal(diagonal, Vector{2U})),
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std::invalid_argument);
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input[0U] = std::numeric_limits<double>::infinity();
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EXPECT_THROW(static_cast<void>(MultiplyDiagonal(diagonal, input)),
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std::invalid_argument);
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input[0U] = 1;
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diagonal[0U] = std::numeric_limits<double>::quiet_NaN();
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EXPECT_THROW(static_cast<void>(MultiplyDiagonal(diagonal, input)),
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std::invalid_argument);
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}
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TEST(DenseBlasInternal, CholeskyAndInverseMatchKnownFactorsAndKeepFailedOutput) {
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Matrix matrix{2U, 2U};
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matrix(0U, 0U) = 4;
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matrix(0U, 1U) = 2;
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matrix(1U, 0U) = 2;
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matrix(1U, 1U) = 5;
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Matrix lower{0U, 0U}, inverse{0U, 0U};
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ASSERT_TRUE(CholeskyLowerAndInverse(matrix, lower, inverse));
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EXPECT_DOUBLE_EQ(lower(0U, 0U), 2);
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EXPECT_DOUBLE_EQ(lower(1U, 0U), 1);
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EXPECT_DOUBLE_EQ(lower(1U, 1U), 2);
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EXPECT_DOUBLE_EQ(lower(0U, 1U), 0);
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EXPECT_DOUBLE_EQ(inverse(0U, 0U), .5);
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EXPECT_DOUBLE_EQ(inverse(1U, 0U), -.25);
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EXPECT_DOUBLE_EQ(inverse(1U, 1U), .5);
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matrix(1U, 1U) = 0;
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EXPECT_FALSE(CholeskyLowerAndInverse(matrix, lower, inverse));
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EXPECT_DOUBLE_EQ(lower(1U, 1U), 2);
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EXPECT_DOUBLE_EQ(inverse(1U, 1U), .5);
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EXPECT_THROW(static_cast<void>(CholeskyLowerAndInverse(
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Matrix{2U, 1U}, lower, inverse)), std::invalid_argument);
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matrix(0U, 0U) = std::numeric_limits<double>::quiet_NaN();
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EXPECT_THROW(static_cast<void>(CholeskyLowerAndInverse(matrix, lower, inverse)),
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std::invalid_argument);
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}
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} // namespace
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} // namespace fesa::dense_blas_internal
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