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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// 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/.
// discard stack allocation as that too bypasses malloc
#define EIGEN_STACK_ALLOCATION_LIMIT 0
#define EIGEN_RUNTIME_NO_MALLOC
#include "main.h"
#include <Eigen/SVD>
#define SVD_DEFAULT(M) JacobiSVD<M>
#define SVD_FOR_MIN_NORM(M) JacobiSVD<M,ColPivHouseholderQRPreconditioner>
#define SVD_STATIC_OPTIONS(M, O) JacobiSVD<M, O>
#include "svd_common.h"
template<typename MatrixType>
void jacobisvd_method()
{
enum { Size = MatrixType::RowsAtCompileTime };
typedef typename MatrixType::RealScalar RealScalar;
typedef Matrix<RealScalar, Size, 1> RealVecType;
MatrixType m = MatrixType::Identity();
VERIFY_IS_APPROX(m.jacobiSvd().singularValues(), RealVecType::Ones());
VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixU());
VERIFY_RAISES_ASSERT(m.jacobiSvd().matrixV());
VERIFY_IS_APPROX(m.template jacobiSvd<ComputeFullU | ComputeFullV>().solve(m), m);
VERIFY_IS_APPROX(m.template jacobiSvd<ComputeFullU | ComputeFullV>().transpose().solve(m), m);
VERIFY_IS_APPROX(m.template jacobiSvd<ComputeFullU | ComputeFullV>().adjoint().solve(m), m);
}
template <typename MatrixType>
void jacobisvd_all_options(const MatrixType& input = MatrixType()) {
MatrixType m(input.rows(), input.cols());
svd_fill_random(m);
svd_option_checks<MatrixType, 0>(m);
svd_option_checks<MatrixType, ColPivHouseholderQRPreconditioner>(m);
svd_option_checks<MatrixType, HouseholderQRPreconditioner>(m);
svd_option_checks_full_only<MatrixType, FullPivHouseholderQRPreconditioner>(
m); // FullPiv only used when computing full unitaries
}
template <typename MatrixType>
void jacobisvd_verify_assert(const MatrixType& input = MatrixType()) {
MatrixType m(input.rows(), input.cols());
svd_fill_random(m);
svd_verify_assert<MatrixType, 0>(m);
svd_verify_assert<MatrixType, ColPivHouseholderQRPreconditioner>(m);
svd_verify_assert<MatrixType, HouseholderQRPreconditioner>(m);
svd_verify_assert_full_only<MatrixType, FullPivHouseholderQRPreconditioner>(m);
svd_verify_constructor_options_assert<JacobiSVD<MatrixType>>(m);
svd_verify_constructor_options_assert<JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>>(m);
svd_verify_constructor_options_assert<JacobiSVD<MatrixType, HouseholderQRPreconditioner>>(m);
svd_verify_constructor_options_assert<JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>>(m);
}
template <typename MatrixType>
void jacobisvd_verify_inputs(const MatrixType& input = MatrixType()) {
// check defaults
typedef JacobiSVD<MatrixType> DefaultSVD;
MatrixType m(input.rows(), input.cols());
svd_fill_random(m);
DefaultSVD defaultSvd(m);
VERIFY((int)DefaultSVD::QRPreconditioner == (int)ColPivHouseholderQRPreconditioner);
VERIFY(!defaultSvd.computeU());
VERIFY(!defaultSvd.computeV());
// ColPivHouseholderQR is always default in presence of other options.
VERIFY(((int)JacobiSVD<MatrixType, ComputeThinU>::QRPreconditioner == (int)ColPivHouseholderQRPreconditioner));
VERIFY(((int)JacobiSVD<MatrixType, ComputeThinV>::QRPreconditioner == (int)ColPivHouseholderQRPreconditioner));
VERIFY(((int)JacobiSVD<MatrixType, ComputeThinU | ComputeThinV>::QRPreconditioner ==
(int)ColPivHouseholderQRPreconditioner));
VERIFY(((int)JacobiSVD<MatrixType, ComputeFullU | ComputeFullV>::QRPreconditioner ==
(int)ColPivHouseholderQRPreconditioner));
VERIFY(((int)JacobiSVD<MatrixType, ComputeThinU | ComputeFullV>::QRPreconditioner ==
(int)ColPivHouseholderQRPreconditioner));
VERIFY(((int)JacobiSVD<MatrixType, ComputeFullU | ComputeThinV>::QRPreconditioner ==
(int)ColPivHouseholderQRPreconditioner));
}
namespace Foo {
// older compiler require a default constructor for Bar
// cf: https://stackoverflow.com/questions/7411515/
class Bar {public: Bar() {}};
bool operator<(const Bar&, const Bar&) { return true; }
}
// regression test for a very strange MSVC issue for which simply
// including SVDBase.h messes up with std::max and custom scalar type
void msvc_workaround()
{
const Foo::Bar a;
const Foo::Bar b;
const Foo::Bar c = std::max EIGEN_NOT_A_MACRO (a,b);
EIGEN_UNUSED_VARIABLE(c)
}
EIGEN_DECLARE_TEST(jacobisvd)
{
CALL_SUBTEST_1((jacobisvd_verify_inputs<Matrix4d>()));
CALL_SUBTEST_1((jacobisvd_verify_inputs(Matrix<float, 5, Dynamic>(5, 6))));
CALL_SUBTEST_1((jacobisvd_verify_inputs<Matrix<std::complex<double>, 7, 5>>()));
CALL_SUBTEST_2((jacobisvd_verify_assert<Matrix3f>()));
CALL_SUBTEST_2((jacobisvd_verify_assert<Matrix4d>()));
CALL_SUBTEST_2((jacobisvd_verify_assert<Matrix<float, 10, 12>>()));
CALL_SUBTEST_2((jacobisvd_verify_assert<Matrix<float, 12, 10>>()));
CALL_SUBTEST_2((jacobisvd_verify_assert<MatrixXf>(MatrixXf(10, 12))));
CALL_SUBTEST_2((jacobisvd_verify_assert<MatrixXcd>(MatrixXcd(7, 5))));
CALL_SUBTEST_3(svd_all_trivial_2x2(jacobisvd_all_options<Matrix2cd>));
CALL_SUBTEST_4(svd_all_trivial_2x2(jacobisvd_all_options<Matrix2d>));
for (int i = 0; i < g_repeat; i++) {
int r = internal::random<int>(1, 30),
c = internal::random<int>(1, 30);
TEST_SET_BUT_UNUSED_VARIABLE(r)
TEST_SET_BUT_UNUSED_VARIABLE(c)
CALL_SUBTEST_5((jacobisvd_all_options<Matrix3f>()));
CALL_SUBTEST_6((jacobisvd_all_options<Matrix4d>()));
CALL_SUBTEST_7((jacobisvd_all_options<Matrix<float, 2, 3>>()));
CALL_SUBTEST_8((jacobisvd_all_options<Matrix<double, 4, 7>>()));
CALL_SUBTEST_9((jacobisvd_all_options<Matrix<double, 7, 4>>()));
CALL_SUBTEST_10((jacobisvd_all_options<Matrix<double, Dynamic, 5>>(Matrix<double, Dynamic, 5>(r, 5))));
CALL_SUBTEST_11((jacobisvd_all_options<Matrix<double, 5, Dynamic>>(Matrix<double, 5, Dynamic>(5, c))));
CALL_SUBTEST_12((jacobisvd_all_options<MatrixXf>(MatrixXf(r, c))));
CALL_SUBTEST_13((jacobisvd_all_options<MatrixXcd>(MatrixXcd(r, c))));
CALL_SUBTEST_14((jacobisvd_all_options<MatrixXd>(MatrixXd(r, c))));
CALL_SUBTEST_15((jacobisvd_all_options<Matrix<double, 5, 7, RowMajor>>()));
CALL_SUBTEST_16((jacobisvd_all_options<Matrix<double, 7, 5, RowMajor>>()));
MatrixXcd noQRTest = MatrixXcd(r, r);
svd_fill_random(noQRTest);
CALL_SUBTEST_17((svd_option_checks<MatrixXcd, NoQRPreconditioner>(noQRTest)));
CALL_SUBTEST_18((
svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, ColMajor, 13, 15>, ColPivHouseholderQRPreconditioner>(
r, c)));
CALL_SUBTEST_18(
(svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, ColMajor, 15, 13>, HouseholderQRPreconditioner>(r,
c)));
CALL_SUBTEST_18((
svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, RowMajor, 13, 15>, ColPivHouseholderQRPreconditioner>(
r, c)));
CALL_SUBTEST_18(
(svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, RowMajor, 15, 13>, HouseholderQRPreconditioner>(r,
c)));
// Test on inf/nan matrix
CALL_SUBTEST_19((svd_inf_nan<MatrixXf>()));
CALL_SUBTEST_19((svd_inf_nan<MatrixXd>()));
CALL_SUBTEST_20((jacobisvd_verify_assert<Matrix<double, 6, 1>>()));
CALL_SUBTEST_20((jacobisvd_verify_assert<Matrix<double, 1, 6>>()));
CALL_SUBTEST_20((jacobisvd_verify_assert<Matrix<double, Dynamic, 1>>(Matrix<double, Dynamic, 1>(r))));
CALL_SUBTEST_20((jacobisvd_verify_assert<Matrix<double, 1, Dynamic>>(Matrix<double, 1, Dynamic>(c))));
}
CALL_SUBTEST_21((jacobisvd_all_options<MatrixXd>(
MatrixXd(internal::random<int>(EIGEN_TEST_MAX_SIZE / 4, EIGEN_TEST_MAX_SIZE / 2),
internal::random<int>(EIGEN_TEST_MAX_SIZE / 4, EIGEN_TEST_MAX_SIZE / 2)))));
CALL_SUBTEST_22((jacobisvd_all_options<MatrixXcd>(
MatrixXcd(internal::random<int>(EIGEN_TEST_MAX_SIZE / 4, EIGEN_TEST_MAX_SIZE / 3),
internal::random<int>(EIGEN_TEST_MAX_SIZE / 4, EIGEN_TEST_MAX_SIZE / 3)))));
// test matrixbase method
CALL_SUBTEST_23(( jacobisvd_method<Matrix2cd>() ));
CALL_SUBTEST_23(( jacobisvd_method<Matrix3f>() ));
// Test problem size constructors
CALL_SUBTEST_24( JacobiSVD<MatrixXf>(10,10) );
// Check that preallocation avoids subsequent mallocs
CALL_SUBTEST_25( svd_preallocate<void>() );
CALL_SUBTEST_26( svd_underoverflow<void>() );
msvc_workaround();
}