bdcsvd.cpp

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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>
#include <iostream>
#include <Eigen/LU>
 
 
#define SVD_DEFAULT(M) BDCSVD<M>
#define SVD_FOR_MIN_NORM(M) BDCSVD<M>
#include "svd_common.h"
 
// Check all variants of JacobiSVD
template<typename MatrixType>
void bdcsvd(const MatrixType& a = MatrixType(), bool pickrandom = true)
{
  MatrixType m;
  if(pickrandom) {
    m.resizeLike(a);
    svd_fill_random(m);
  }
  else
    m = a;
 
  CALL_SUBTEST(( svd_test_all_computation_options<BDCSVD<MatrixType> >(m, false)  ));
}
 
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());
  VERIFY_IS_APPROX(m.bdcSvd(ComputeFullU|ComputeFullV).solve(m), m);
  VERIFY_IS_APPROX(m.bdcSvd(ComputeFullU|ComputeFullV).transpose().solve(m), m);
  VERIFY_IS_APPROX(m.bdcSvd(ComputeFullU|ComputeFullV).adjoint().solve(m), m);
}
 
// compare the Singular values returned with Jacobi and Bdc
template<typename MatrixType> 
void compare_bdc_jacobi(const MatrixType& a = MatrixType(), unsigned int computationOptions = 0)
{
  MatrixType m = MatrixType::Random(a.rows(), a.cols());
  BDCSVD<MatrixType> bdc_svd(m);
  JacobiSVD<MatrixType> jacobi_svd(m);
  VERIFY_IS_APPROX(bdc_svd.singularValues(), jacobi_svd.singularValues());
  if(computationOptions & ComputeFullU) VERIFY_IS_APPROX(bdc_svd.matrixU(), jacobi_svd.matrixU());
  if(computationOptions & ComputeThinU) VERIFY_IS_APPROX(bdc_svd.matrixU(), jacobi_svd.matrixU());
  if(computationOptions & ComputeFullV) VERIFY_IS_APPROX(bdc_svd.matrixV(), jacobi_svd.matrixV());
  if(computationOptions & ComputeThinV) VERIFY_IS_APPROX(bdc_svd.matrixV(), jacobi_svd.matrixV());
}
 
EIGEN_DECLARE_TEST(bdcsvd)
{
  CALL_SUBTEST_3(( svd_verify_assert<BDCSVD<Matrix3f>  >(Matrix3f()) ));
  CALL_SUBTEST_4(( svd_verify_assert<BDCSVD<Matrix4d>  >(Matrix4d()) ));
  CALL_SUBTEST_7(( svd_verify_assert<BDCSVD<MatrixXf>  >(MatrixXf(10,12)) ));
  CALL_SUBTEST_8(( svd_verify_assert<BDCSVD<MatrixXcd> >(MatrixXcd(7,5)) ));
  
  CALL_SUBTEST_101(( svd_all_trivial_2x2(bdcsvd<Matrix2cd>) ));
  CALL_SUBTEST_102(( svd_all_trivial_2x2(bdcsvd<Matrix2d>) ));
 
  for(int i = 0; i < g_repeat; i++) {
    CALL_SUBTEST_3(( bdcsvd<Matrix3f>() ));
    CALL_SUBTEST_4(( bdcsvd<Matrix4d>() ));
    CALL_SUBTEST_5(( bdcsvd<Matrix<float,3,5> >() ));
 
    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_6((  bdcsvd(Matrix<double,Dynamic,2>(r,2)) ));
    CALL_SUBTEST_7((  bdcsvd(MatrixXf(r,c)) ));
    CALL_SUBTEST_7((  compare_bdc_jacobi(MatrixXf(r,c)) ));
    CALL_SUBTEST_10(( bdcsvd(MatrixXd(r,c)) ));
    CALL_SUBTEST_10(( compare_bdc_jacobi(MatrixXd(r,c)) ));
    CALL_SUBTEST_8((  bdcsvd(MatrixXcd(r,c)) ));
    CALL_SUBTEST_8((  compare_bdc_jacobi(MatrixXcd(r,c)) ));
 
    // Test on inf/nan matrix
    CALL_SUBTEST_7(  (svd_inf_nan<BDCSVD<MatrixXf>, MatrixXf>()) );
    CALL_SUBTEST_10( (svd_inf_nan<BDCSVD<MatrixXd>, MatrixXd>()) );
  }
 
  // test matrixbase method
  CALL_SUBTEST_1(( bdcsvd_method<Matrix2cd>() ));
  CALL_SUBTEST_3(( bdcsvd_method<Matrix3f>() ));
 
  // Test problem size constructors
  CALL_SUBTEST_7( BDCSVD<MatrixXf>(10,10) );
 
  // Check that preallocation avoids subsequent mallocs
  // Disabled because not supported by BDCSVD
  // CALL_SUBTEST_9( svd_preallocate<void>() );
 
  CALL_SUBTEST_2( svd_underoverflow<void>() );
}