| // 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)))); | 
 |   } | 
 | } |