KOKO\Mimi
135 lines
5.1 KiB
C++
135 lines
5.1 KiB
C++
#include "fesa/math/sparse_matrix.h"
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#include <gtest/gtest.h>
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#include <algorithm>
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#include <limits>
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#include <type_traits>
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#include <utility>
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#include <vector>
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#include "fesa/fem/dof_manager.h"
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#include "fesa/math/matrix.h"
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namespace {
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using fesa::CooContribution;
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using fesa::SparseMatrix;
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using fesa::SparsePattern;
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using fesa::Vector;
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static_assert(
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!std::is_base_of_v<fesa::Matrix, SparseMatrix>,
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"SparseMatrix must own CSR storage independently of dense Matrix.");
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TEST(SparseAssembly, ValidatesKnownCsrAndMultiply) {
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const SparsePattern pattern{{0U, 2U, 2U, 4U, 5U}, {0U, 2U, 1U, 3U, 3U}};
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std::vector<CooContribution> contributions{{2U, 3U, 4.0, 2U, 0U},
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{0U, 2U, 2.0, 0U, 1U},
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{3U, 3U, 5.0, 3U, 0U},
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{0U, 0U, 1.0, 0U, 0U},
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{2U, 1U, 3.0, 1U, 0U}};
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auto result =
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SparseMatrix::FromCoo(4U, 4U, std::move(contributions), pattern);
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ASSERT_TRUE(result.HasValue());
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const SparseMatrix& matrix = result.Value();
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EXPECT_EQ(matrix.Rows(), 4U);
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EXPECT_EQ(matrix.Columns(), 4U);
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EXPECT_EQ(matrix.RowOffsets(), pattern.row_offsets);
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EXPECT_EQ(matrix.ColumnIndices(), pattern.column_indices);
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EXPECT_EQ(matrix.Values(), (std::vector<double>{1.0, 2.0, 3.0, 4.0, 5.0}));
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EXPECT_TRUE(matrix.Validate().IsOk());
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Vector rhs{4U};
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rhs[0U] = 1.0;
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rhs[1U] = 2.0;
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rhs[2U] = 3.0;
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rhs[3U] = 4.0;
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const Vector product = matrix.Multiply(rhs);
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ASSERT_EQ(product.Size(), 4U);
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EXPECT_DOUBLE_EQ(product[0U], 7.0);
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EXPECT_DOUBLE_EQ(product[1U], 0.0);
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EXPECT_DOUBLE_EQ(product[2U], 22.0);
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EXPECT_DOUBLE_EQ(product[3U], 20.0);
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EXPECT_THROW(static_cast<void>(matrix.Multiply(Vector{3U})),
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std::invalid_argument);
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}
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TEST(SparseAssembly, ReducesDuplicatesInFixedTupleOrder) {
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const SparsePattern pattern{{0U, 1U}, {0U}};
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const std::vector<CooContribution> contributions{{0U, 0U, 1.0, 2U, 0U},
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{0U, 0U, -1.0e16, 1U, 0U},
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{0U, 0U, 1.0e16, 0U, 0U}};
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auto first = SparseMatrix::FromCoo(1U, 1U, contributions, pattern);
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ASSERT_TRUE(first.HasValue());
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ASSERT_EQ(first.Value().Values().size(), 1U);
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EXPECT_DOUBLE_EQ(first.Value().Values()[0U], 1.0);
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auto reversed_contributions = contributions;
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std::reverse(reversed_contributions.begin(), reversed_contributions.end());
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auto second =
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SparseMatrix::FromCoo(1U, 1U, std::move(reversed_contributions), pattern);
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ASSERT_TRUE(second.HasValue());
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EXPECT_EQ(second.Value().RowOffsets(), first.Value().RowOffsets());
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EXPECT_EQ(second.Value().ColumnIndices(), first.Value().ColumnIndices());
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EXPECT_EQ(second.Value().Values(), first.Value().Values());
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}
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TEST(SparseAssembly, RejectsInvalidIndexPatternAndShape) {
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const SparsePattern one_entry{{0U, 1U}, {0U}};
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const auto expect_failure = [](std::size_t rows, std::size_t columns,
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std::vector<CooContribution> contributions,
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const SparsePattern& pattern) {
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auto result =
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SparseMatrix::FromCoo(rows, columns, std::move(contributions), pattern);
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EXPECT_FALSE(result.HasValue());
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if (!result.HasValue()) {
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EXPECT_FALSE(result.GetStatus().IsOk());
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EXPECT_EQ(result.GetStatus().Category(), fesa::FailureCategory::kModel);
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EXPECT_FALSE(result.GetStatus().Diagnostics().empty());
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}
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};
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expect_failure(2U, 2U, {}, {{0U, 0U}, {}});
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expect_failure(1U, 1U, {}, {{1U, 1U}, {0U}});
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expect_failure(2U, 2U, {}, {{0U, 1U, 0U}, {0U}});
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expect_failure(1U, 2U, {}, {{0U, 2U}, {1U, 0U}});
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expect_failure(1U, 1U, {}, {{0U, 2U}, {0U, 0U}});
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expect_failure(1U, 1U, {}, {{0U, 1U}, {1U}});
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expect_failure(1U, 1U, {{1U, 0U, 1.0, 0U, 0U}}, one_entry);
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expect_failure(1U, 1U, {{0U, 1U, 1.0, 0U, 0U}}, one_entry);
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expect_failure(1U, 2U, {{0U, 1U, 1.0, 0U, 0U}}, {{0U, 1U}, {0U}});
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expect_failure(1U, 1U,
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{{0U, 0U, (std::numeric_limits<double>::infinity)(), 0U, 0U}},
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one_entry);
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expect_failure(1U, 1U,
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{{0U, 0U, (std::numeric_limits<double>::quiet_NaN)(), 0U, 0U}},
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one_entry);
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expect_failure(1U, 1U,
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{{0U, 0U, (std::numeric_limits<double>::max)(), 0U, 0U},
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{0U, 0U, (std::numeric_limits<double>::max)(), 1U, 0U}},
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one_entry);
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}
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TEST(SparseAssembly, PreservesExpectedStructuralZeros) {
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const SparsePattern pattern{{0U, 2U, 4U, 5U}, {0U, 2U, 1U, 2U, 0U}};
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std::vector<CooContribution> contributions{
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{0U, 0U, 2.0, 0U, 0U}, {1U, 1U, 4.0, 0U, 1U}, {1U, 1U, -4.0, 1U, 0U}};
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auto result =
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SparseMatrix::FromCoo(3U, 3U, std::move(contributions), pattern);
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ASSERT_TRUE(result.HasValue());
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EXPECT_EQ(result.Value().RowOffsets(), pattern.row_offsets);
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EXPECT_EQ(result.Value().ColumnIndices(), pattern.column_indices);
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EXPECT_EQ(result.Value().Values(),
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(std::vector<double>{2.0, 0.0, 0.0, 0.0, 0.0}));
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EXPECT_EQ(std::count(result.Value().Values().begin(),
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result.Value().Values().end(), 0.0),
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4);
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}
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} // namespace
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