Implements map and ref for both static & dynamic mode
See merge request oss/rotgen!12
This commit is contained in:
Joel Falcou
parent
aacae1cbb1
commit
6c2b260229
58 changed files with 4121 additions and 1205 deletions
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//==================================================================================================
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/*
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ROTGEN - Runtime Overlay for Eigen
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Copyright : CODE RECKONS
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SPDX-License-Identifier: BSL-1.0
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*/
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//==================================================================================================
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#include "unit/tests.hpp"
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#include <rotgen/rotgen.hpp>
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#include <Eigen/Dense>
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template <typename MatrixType>
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struct MatrixDescriptor
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{
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std::size_t rows, cols;
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std::function<void(MatrixType &, std::size_t, std::size_t)> init_fn;
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};
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template <typename MatrixType>
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void test_matrix_unary_ops(std::size_t rows, std::size_t cols,
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const std::function<void(MatrixType &, std::size_t, std::size_t)> &init_fn)
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{
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MatrixType original(rows, cols);
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MatrixType transposed_matrix(cols, rows);
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for (std::size_t r = 0; r < rows; ++r)
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for (std::size_t c = 0; c < cols; ++c)
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init_fn(original, r, c);
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for (std::size_t r = 0; r < rows; ++r)
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for (std::size_t c = 0; c < cols; ++c)
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transposed_matrix(c, r) = original(r, c);
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TTS_EQUAL(rotgen::transpose(original), transposed_matrix);
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TTS_EQUAL(rotgen::conjugate(original), original);
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TTS_EQUAL(rotgen::adjoint(original), transposed_matrix);
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TTS_EXPECT(verify_rotgen_reentrance(rotgen::transpose(original)));
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TTS_EXPECT(verify_rotgen_reentrance(rotgen::conjugate(original)));
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TTS_EXPECT(verify_rotgen_reentrance(rotgen::adjoint(original)));
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rotgen::transposeInPlace(original);
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TTS_EQUAL(original, transposed_matrix);
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rotgen::transposeInPlace(original);
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rotgen::adjointInPlace(original);
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TTS_EQUAL(original, transposed_matrix);
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}
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template <typename MatrixType>
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void test_matrix_scalar_reductions(std::size_t rows, std::size_t cols,
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const std::function<void(MatrixType&, std::size_t, std::size_t)>& init_fn)
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{
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using EigenMatrix = Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>;
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MatrixType original(rows, cols);
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EigenMatrix ref(rows, cols);
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for (std::size_t r = 0; r < rows; ++r)
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for (std::size_t c = 0; c < cols; ++c)
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{
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init_fn(original, r, c);
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ref(r, c) = original(r, c);
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}
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TTS_EQUAL(rotgen::sum(original), ref.sum());
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TTS_EQUAL(rotgen::prod(original), ref.prod());
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TTS_EQUAL(rotgen::mean(original), ref.mean());
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TTS_EQUAL(rotgen::maxCoeff(original), ref.maxCoeff());
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TTS_EQUAL(rotgen::minCoeff(original), ref.minCoeff());
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TTS_EQUAL(rotgen::trace(original), ref.trace());
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std::ptrdiff_t row, col, ref_row, ref_col;
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double cmin = rotgen::minCoeff(original, &row, &col);
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double rmin = ref.minCoeff(&ref_row, &ref_col);
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TTS_EQUAL(cmin, rmin);
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TTS_EQUAL(row, ref_row);
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TTS_EQUAL(col, ref_col);
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double cmax = rotgen::maxCoeff(original, &row, &col);
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double rmax = ref.maxCoeff(&ref_row, &ref_col);
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TTS_EQUAL(cmax, rmax);
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TTS_EQUAL(row, ref_row);
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TTS_EQUAL(col, ref_col);
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}
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TTS_CASE("Matrix unary operations: transpose, adjoint, conjugate")
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{
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std::vector<MatrixDescriptor<rotgen::matrix<double>>> test_matrices = {
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{3, 3, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = r + 3 * c - 2.5; }},
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{4, 9, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = r*r + 3.12 * c + 6.87; }},
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{2, 7, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = 1.1 * (r - c); }},
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{1, 5, [](auto &m, std::size_t r, std::size_t c) { m(r, c) = 9.99; }},
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{4, 2, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = 0.0; }},
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{3, 3, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = (r == c) ? 1.0 : 0.0; }},
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{2, 2, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = (r + c) * 1e-10; }},
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{2, 2, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = (r + 1) * 1e+10; }},
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};
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for (auto const &desc : test_matrices)
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test_matrix_unary_ops<rotgen::matrix<double>>(desc.rows, desc.cols, desc.init_fn);
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};
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TTS_CASE("Basic arithmetic reduction operations")
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{
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std::vector<MatrixDescriptor<rotgen::matrix<double>>> test_matrices = {
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{3, 3, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = r + c; }},
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{3, 3, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = 0.0; }},
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{2, 4, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = -r -c*c - 1234; }},
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{4, 4, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = 7.0; }},
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{1, 1, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = 42.0; }},
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{4, 2, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = std::sin(r + c); }},
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{1, 5, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = -1.5 * r + 2.56 * c; }},
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{5, 7, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = (r == c ? 1.0 : 0.0); }},
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};
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for (const auto& [rows, cols, init_fn] : test_matrices)
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test_matrix_scalar_reductions<rotgen::matrix<double>>(rows, cols, init_fn);
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};
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@ -1,60 +0,0 @@
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//==================================================================================================
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/*
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ROTGEN - Runtime Overlay for Eigen
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Copyright : CODE RECKONS
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SPDX-License-Identifier: BSL-1.0
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*/
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//==================================================================================================
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#include "unit/tests.hpp"
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#include <rotgen/rotgen.hpp>
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#include <Eigen/Dense>
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template <typename MatrixType>
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struct MatrixDescriptor
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{
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std::size_t rows, cols;
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std::function<void(MatrixType &, std::size_t, std::size_t)> init_fn;
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};
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template <typename MatrixType>
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void test_matrix_norms(std::size_t rows, std::size_t cols,
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const std::function<void(MatrixType &, std::size_t, std::size_t)> &init_fn)
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{
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MatrixType matrix(rows, cols);
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Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> ref(rows, cols);
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for (std::size_t r = 0; r < rows; ++r)
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for (std::size_t c = 0; c < cols; ++c)
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{
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init_fn(matrix, r, c);
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ref(r, c) = matrix(r, c);
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}
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constexpr double epsilon = 1e-10;
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TTS_RELATIVE_EQUAL(rotgen::norm(matrix), ref.norm(), epsilon);
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TTS_RELATIVE_EQUAL(rotgen::squaredNorm(matrix), ref.squaredNorm(), epsilon);
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TTS_RELATIVE_EQUAL(rotgen::lpNorm<1>(matrix), ref.lpNorm<1>(), epsilon);
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TTS_RELATIVE_EQUAL(rotgen::lpNorm<2>(matrix), ref.lpNorm<2>(), epsilon);
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TTS_RELATIVE_EQUAL(rotgen::lpNorm<-1>(matrix), ref.lpNorm<Eigen::Infinity>(), epsilon);
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}
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TTS_CASE("Matrix norm-related operations")
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{
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std::vector<MatrixDescriptor<rotgen::matrix<double>>> test_matrices = {
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{3, 3, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = r + c; }},
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{2, 3, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = 0.0; }},
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{2, 7, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = -r*r*r - c*c - 1.23; }},
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{17, 3, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = r*c + 0.98; }},
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{1, 1, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = 42.0; }},
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{10, 11, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = std::tan(r + c); }},
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{1, 5, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = -1.5*r + 2.56*c + 3.33; }},
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{7, 1, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = (r == c ? 1.0 : 0.0); }},
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{0, 0, [](auto& m, std::size_t r, std::size_t c) { m(r, c) = (r == c ? 1.0 : 0.0); }},
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};
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for (const auto& [rows, cols, init_fn] : test_matrices)
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test_matrix_norms<rotgen::matrix<double>>(rows, cols, init_fn);
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};
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