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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2013 Gauthier Brun <brun.gauthier@gmail.com>
// Copyright (C) 2013 Nicolas Carre <nicolas.carre@ensimag.fr>
// Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr>
// Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr>
//
// 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) BDCSVD<M>
#define SVD_FOR_MIN_NORM(M) BDCSVD<M>
#define SVD_STATIC_OPTIONS(M, O) BDCSVD<M, O>
#include "svd_common.h"
template <typename MatrixType>
void bdcsvd_method() {
enum { Size = MatrixType::RowsAtCompileTime };
typedef typename MatrixType::RealScalar RealScalar;
typedef Matrix<RealScalar, Size, 1> RealVecType;
MatrixType m = MatrixType::Identity();
VERIFY_IS_APPROX(m.bdcSvd().singularValues(), RealVecType::Ones());
VERIFY_RAISES_ASSERT(m.bdcSvd().matrixU());
VERIFY_RAISES_ASSERT(m.bdcSvd().matrixV());
}
// compare the Singular values returned with Jacobi and Bdc
template <typename MatrixType>
void compare_bdc_jacobi(const MatrixType& a = MatrixType(), int algoswap = 16, bool random = true) {
MatrixType m = random ? MatrixType::Random(a.rows(), a.cols()) : a;
BDCSVD<MatrixType> bdc_svd(m.rows(), m.cols());
bdc_svd.setSwitchSize(algoswap);
bdc_svd.compute(m);
JacobiSVD<MatrixType> jacobi_svd(m);
VERIFY_IS_APPROX(bdc_svd.singularValues(), jacobi_svd.singularValues());
}
// Verifies total deflation is **not** triggered.
void compare_bdc_jacobi_instance(bool structure_as_m, int algoswap = 16) {
MatrixXd m(4, 3);
if (structure_as_m) {
// The first 3 rows are the reduced form of Matrix 1 as shown below, and it
// has nonzero elements in the first column and diagonals only.
m << 1.056293, 0, 0, -0.336468, 0.907359, 0, -1.566245, 0, 0.149150, -0.1, 0, 0;
} else {
// Matrix 1.
m << 0.882336, 18.3914, -26.7921, -5.58135, 17.1931, -24.0892, -20.794, 8.68496, -4.83103, -8.4981, -10.5451,
23.9072;
}
compare_bdc_jacobi(m, algoswap, false);
}
template <typename MatrixType>
void bdcsvd_thin_options(const MatrixType& input = MatrixType()) {
svd_thin_option_checks<MatrixType, 0>(input);
}
template <typename MatrixType>
void bdcsvd_full_options(const MatrixType& input = MatrixType()) {
svd_option_checks_full_only<MatrixType, 0>(input);
}
template <typename MatrixType>
void bdcsvd_verify_assert(const MatrixType& input = MatrixType()) {
svd_verify_assert<MatrixType>(input);
svd_verify_constructor_options_assert<BDCSVD<MatrixType>>(input);
}
template <typename MatrixType>
void bdcsvd_check_convergence(const MatrixType& input) {
BDCSVD<MatrixType, Eigen::ComputeThinU | Eigen::ComputeThinV> svd(input);
VERIFY(svd.info() == Eigen::Success);
MatrixType D = svd.matrixU() * svd.singularValues().asDiagonal() * svd.matrixV().transpose();
VERIFY_IS_APPROX(input, D);
}
EIGEN_DECLARE_TEST(bdcsvd) {
CALL_SUBTEST_1((bdcsvd_verify_assert<Matrix3f>()));
CALL_SUBTEST_2((bdcsvd_verify_assert<Matrix4d>()));
CALL_SUBTEST_3((bdcsvd_verify_assert<Matrix<float, 10, 7>>()));
CALL_SUBTEST_4((bdcsvd_verify_assert<Matrix<float, 7, 10>>()));
CALL_SUBTEST_5((bdcsvd_verify_assert<Matrix<std::complex<double>, 6, 9>>()));
CALL_SUBTEST_6((svd_all_trivial_2x2(bdcsvd_thin_options<Matrix2cd>)));
CALL_SUBTEST_7((svd_all_trivial_2x2(bdcsvd_full_options<Matrix2cd>)));
CALL_SUBTEST_8((svd_all_trivial_2x2(bdcsvd_thin_options<Matrix2d>)));
CALL_SUBTEST_9((svd_all_trivial_2x2(bdcsvd_full_options<Matrix2d>)));
for (int i = 0; i < g_repeat; i++) {
int r = internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2), c = internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2);
TEST_SET_BUT_UNUSED_VARIABLE(r)
TEST_SET_BUT_UNUSED_VARIABLE(c)
CALL_SUBTEST_10((compare_bdc_jacobi<MatrixXf>(MatrixXf(r, c))));
CALL_SUBTEST_11((compare_bdc_jacobi<MatrixXd>(MatrixXd(r, c))));
CALL_SUBTEST_12((compare_bdc_jacobi<MatrixXcd>(MatrixXcd(r, c))));
// Test on inf/nan matrix
CALL_SUBTEST_13((svd_inf_nan<MatrixXf>()));
CALL_SUBTEST_14((svd_inf_nan<MatrixXd>()));
// Verify some computations using all combinations of the Options template parameter.
CALL_SUBTEST_15((bdcsvd_thin_options<Matrix3f>()));
CALL_SUBTEST_16((bdcsvd_full_options<Matrix3f>()));
CALL_SUBTEST_17((bdcsvd_thin_options<Matrix<float, 2, 3>>()));
CALL_SUBTEST_18((bdcsvd_full_options<Matrix<float, 2, 3>>()));
CALL_SUBTEST_19((bdcsvd_thin_options<MatrixXd>(MatrixXd(20, 17))));
CALL_SUBTEST_20((bdcsvd_full_options<MatrixXd>(MatrixXd(20, 17))));
CALL_SUBTEST_21((bdcsvd_thin_options<MatrixXd>(MatrixXd(17, 20))));
CALL_SUBTEST_22((bdcsvd_full_options<MatrixXd>(MatrixXd(17, 20))));
CALL_SUBTEST_23((bdcsvd_thin_options<Matrix<double, Dynamic, 15>>(Matrix<double, Dynamic, 15>(r, 15))));
CALL_SUBTEST_24((bdcsvd_full_options<Matrix<double, Dynamic, 15>>(Matrix<double, Dynamic, 15>(r, 15))));
CALL_SUBTEST_25((bdcsvd_thin_options<Matrix<double, 13, Dynamic>>(Matrix<double, 13, Dynamic>(13, c))));
CALL_SUBTEST_26((bdcsvd_full_options<Matrix<double, 13, Dynamic>>(Matrix<double, 13, Dynamic>(13, c))));
CALL_SUBTEST_27((bdcsvd_thin_options<MatrixXf>(MatrixXf(r, c))));
CALL_SUBTEST_28((bdcsvd_full_options<MatrixXf>(MatrixXf(r, c))));
CALL_SUBTEST_29((bdcsvd_thin_options<MatrixXcd>(MatrixXcd(r, c))));
CALL_SUBTEST_30((bdcsvd_full_options<MatrixXcd>(MatrixXcd(r, c))));
CALL_SUBTEST_31((bdcsvd_thin_options<MatrixXd>(MatrixXd(r, c))));
CALL_SUBTEST_32((bdcsvd_full_options<MatrixXd>(MatrixXd(r, c))));
CALL_SUBTEST_33((bdcsvd_thin_options<Matrix<double, Dynamic, Dynamic, RowMajor>>(
Matrix<double, Dynamic, Dynamic, RowMajor>(20, 27))));
CALL_SUBTEST_34((bdcsvd_full_options<Matrix<double, Dynamic, Dynamic, RowMajor>>(
Matrix<double, Dynamic, Dynamic, RowMajor>(20, 27))));
CALL_SUBTEST_35((bdcsvd_thin_options<Matrix<double, Dynamic, Dynamic, RowMajor>>(
Matrix<double, Dynamic, Dynamic, RowMajor>(27, 20))));
CALL_SUBTEST_36((bdcsvd_full_options<Matrix<double, Dynamic, Dynamic, RowMajor>>(
Matrix<double, Dynamic, Dynamic, RowMajor>(27, 20))));
CALL_SUBTEST_37((
svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, ColMajor, 20, 35>, ColPivHouseholderQRPreconditioner>(
r, c)));
CALL_SUBTEST_38(
(svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, ColMajor, 35, 20>, HouseholderQRPreconditioner>(r,
c)));
CALL_SUBTEST_39((
svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, RowMajor, 20, 35>, ColPivHouseholderQRPreconditioner>(
r, c)));
CALL_SUBTEST_40(
(svd_check_max_size_matrix<Matrix<float, Dynamic, Dynamic, RowMajor, 35, 20>, HouseholderQRPreconditioner>(r,
c)));
}
// test matrixbase method
CALL_SUBTEST_41((bdcsvd_method<Matrix2cd>()));
CALL_SUBTEST_42((bdcsvd_method<Matrix3f>()));
// Test problem size constructors
CALL_SUBTEST_43(BDCSVD<MatrixXf>(10, 10));
// Check that preallocation avoids subsequent mallocs
// Disabled because not supported by BDCSVD
// CALL_SUBTEST_9( svd_preallocate<void>() );
CALL_SUBTEST_44(svd_underoverflow<void>());
// Without total deflation issues.
CALL_SUBTEST_45((compare_bdc_jacobi_instance(true)));
CALL_SUBTEST_46((compare_bdc_jacobi_instance(false)));
// With total deflation issues before, when it shouldn't be triggered.
CALL_SUBTEST_47((compare_bdc_jacobi_instance(true, 3)));
CALL_SUBTEST_48((compare_bdc_jacobi_instance(false, 3)));
// Convergence for large constant matrix (https://gitlab.com/libeigen/eigen/-/issues/2491)
CALL_SUBTEST_49(bdcsvd_check_convergence<MatrixXf>(MatrixXf::Constant(500, 500, 1)));
}