| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2021 Kolja Brix <kolja.brix@rwth-aachen.de> | |
| // | |
| // This Source Code Form is subject to the terms of the Mozilla | |
| // Public License v. 2.0. If a copy of the MPL was not distributed | |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | |
| #include "main.h" | |
| #include <Eigen/SVD> | |
| template <typename MatrixType> | |
| void check_generateRandomUnitaryMatrix(const Index dim) { | |
| const MatrixType Q = generateRandomUnitaryMatrix<MatrixType>(dim); | |
| // validate dimensions | |
| VERIFY_IS_EQUAL(Q.rows(), dim); | |
| VERIFY_IS_EQUAL(Q.cols(), dim); | |
| VERIFY_IS_UNITARY(Q); | |
| } | |
| template <typename VectorType, typename RealScalarType> | |
| void check_setupRandomSvs(const Index dim, const RealScalarType max) { | |
| const VectorType v = setupRandomSvs<VectorType, RealScalarType>(dim, max); | |
| // validate dimensions | |
| VERIFY_IS_EQUAL(v.size(), dim); | |
| // check entries | |
| for (Index i = 0; i < v.size(); ++i) VERIFY_GE(v(i), 0); | |
| for (Index i = 0; i < v.size() - 1; ++i) VERIFY_GE(v(i), v(i + 1)); | |
| } | |
| template <typename VectorType, typename RealScalarType> | |
| void check_setupRangeSvs(const Index dim, const RealScalarType min, const RealScalarType max) { | |
| const VectorType v = setupRangeSvs<VectorType, RealScalarType>(dim, min, max); | |
| // validate dimensions | |
| VERIFY_IS_EQUAL(v.size(), dim); | |
| // check entries | |
| if (dim == 1) { | |
| VERIFY_IS_APPROX(v(0), min); | |
| } else { | |
| VERIFY_IS_APPROX(v(0), max); | |
| VERIFY_IS_APPROX(v(dim - 1), min); | |
| } | |
| for (Index i = 0; i < v.size() - 1; ++i) VERIFY_GE(v(i), v(i + 1)); | |
| } | |
| template <typename MatrixType, typename RealScalar, typename RealVectorType> | |
| void check_generateRandomMatrixSvs(const Index rows, const Index cols, const Index diag_size, const RealScalar min_svs, | |
| const RealScalar max_svs) { | |
| RealVectorType svs = setupRangeSvs<RealVectorType, RealScalar>(diag_size, min_svs, max_svs); | |
| MatrixType M = MatrixType::Zero(rows, cols); | |
| generateRandomMatrixSvs(svs, rows, cols, M); | |
| // validate dimensions | |
| VERIFY_IS_EQUAL(M.rows(), rows); | |
| VERIFY_IS_EQUAL(M.cols(), cols); | |
| VERIFY_IS_EQUAL(svs.size(), diag_size); | |
| // validate singular values | |
| Eigen::JacobiSVD<MatrixType> SVD(M); | |
| VERIFY_IS_APPROX(svs, SVD.singularValues()); | |
| } | |
| template <typename MatrixType> | |
| void check_random_matrix(const MatrixType &m) { | |
| enum { | |
| Rows = MatrixType::RowsAtCompileTime, | |
| Cols = MatrixType::ColsAtCompileTime, | |
| DiagSize = internal::min_size_prefer_dynamic(Rows, Cols) | |
| }; | |
| typedef typename MatrixType::Scalar Scalar; | |
| typedef typename NumTraits<Scalar>::Real RealScalar; | |
| typedef Matrix<RealScalar, DiagSize, 1> RealVectorType; | |
| const Index rows = m.rows(), cols = m.cols(); | |
| const Index diag_size = (std::min)(rows, cols); | |
| const RealScalar min_svs = 1.0, max_svs = 1000.0; | |
| // check generation of unitary random matrices | |
| typedef Matrix<Scalar, Rows, Rows> MatrixAType; | |
| typedef Matrix<Scalar, Cols, Cols> MatrixBType; | |
| check_generateRandomUnitaryMatrix<MatrixAType>(rows); | |
| check_generateRandomUnitaryMatrix<MatrixBType>(cols); | |
| // test generators for singular values | |
| check_setupRandomSvs<RealVectorType, RealScalar>(diag_size, max_svs); | |
| check_setupRangeSvs<RealVectorType, RealScalar>(diag_size, min_svs, max_svs); | |
| // check generation of random matrices | |
| check_generateRandomMatrixSvs<MatrixType, RealScalar, RealVectorType>(rows, cols, diag_size, min_svs, max_svs); | |
| } | |
| EIGEN_DECLARE_TEST(random_matrix) { | |
| for (int i = 0; i < g_repeat; i++) { | |
| CALL_SUBTEST_1(check_random_matrix(Matrix<float, 1, 1>())); | |
| CALL_SUBTEST_2(check_random_matrix(Matrix<float, 4, 4>())); | |
| CALL_SUBTEST_3(check_random_matrix(Matrix<float, 2, 3>())); | |
| CALL_SUBTEST_4(check_random_matrix(Matrix<float, 7, 4>())); | |
| CALL_SUBTEST_5(check_random_matrix(Matrix<double, 1, 1>())); | |
| CALL_SUBTEST_6(check_random_matrix(Matrix<double, 6, 6>())); | |
| CALL_SUBTEST_7(check_random_matrix(Matrix<double, 5, 3>())); | |
| CALL_SUBTEST_8(check_random_matrix(Matrix<double, 4, 9>())); | |
| CALL_SUBTEST_9(check_random_matrix(Matrix<std::complex<float>, 12, 12>())); | |
| CALL_SUBTEST_10(check_random_matrix(Matrix<std::complex<float>, 7, 14>())); | |
| CALL_SUBTEST_11(check_random_matrix(Matrix<std::complex<double>, 15, 11>())); | |
| CALL_SUBTEST_12(check_random_matrix(Matrix<std::complex<double>, 6, 9>())); | |
| CALL_SUBTEST_13(check_random_matrix( | |
| MatrixXf(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE)))); | |
| CALL_SUBTEST_14(check_random_matrix( | |
| MatrixXd(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE)))); | |
| CALL_SUBTEST_15(check_random_matrix( | |
| MatrixXcf(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE)))); | |
| CALL_SUBTEST_16(check_random_matrix( | |
| MatrixXcd(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE)))); | |
| } | |
| } |