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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014-2015 Gael Guennebaud <gael.guennebaud@inria.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/.
template<typename MatrixType> void svd_fill_random(MatrixType &m, int Option = 0) { typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; typedef typename MatrixType::Index Index; Index diagSize = (std::min)(m.rows(), m.cols()); RealScalar s = std::numeric_limits<RealScalar>::max_exponent10/4; s = internal::random<RealScalar>(1,s); Matrix<RealScalar,Dynamic,1> d = Matrix<RealScalar,Dynamic,1>::Random(diagSize); for(Index k=0; k<diagSize; ++k) d(k) = d(k)*std::pow(RealScalar(10),internal::random<RealScalar>(-s,s));
bool dup = internal::random<int>(0,10) < 3; bool unit_uv = internal::random<int>(0,10) < (dup?7:3); // if we duplicate some diagonal entries, then increase the chance to preserve them using unitary U and V factors
// duplicate some singular values
if(dup) { Index n = internal::random<Index>(0,d.size()-1); for(Index i=0; i<n; ++i) d(internal::random<Index>(0,d.size()-1)) = d(internal::random<Index>(0,d.size()-1)); } Matrix<Scalar,Dynamic,Dynamic> U(m.rows(),diagSize); Matrix<Scalar,Dynamic,Dynamic> VT(diagSize,m.cols()); if(unit_uv) { // in very rare cases let's try with a pure diagonal matrix
if(internal::random<int>(0,10) < 1) { U.setIdentity(); VT.setIdentity(); } else { createRandomPIMatrixOfRank(diagSize,U.rows(), U.cols(), U); createRandomPIMatrixOfRank(diagSize,VT.rows(), VT.cols(), VT); } } else { U.setRandom(); VT.setRandom(); } Matrix<Scalar,Dynamic,1> samples(7); samples << 0, 5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324, -1./NumTraits<RealScalar>::highest(), 1./NumTraits<RealScalar>::highest(); if(Option==Symmetric) { m = U * d.asDiagonal() * U.transpose(); // randomly nullify some rows/columns
{ Index count = internal::random<Index>(-diagSize,diagSize); for(Index k=0; k<count; ++k) { Index i = internal::random<Index>(0,diagSize-1); m.row(i).setZero(); m.col(i).setZero(); } if(count<0) // (partly) cancel some coeffs
if(!(dup && unit_uv)) { Index n = internal::random<Index>(0,m.size()-1); for(Index k=0; k<n; ++k) { Index i = internal::random<Index>(0,m.rows()-1); Index j = internal::random<Index>(0,m.cols()-1); m(j,i) = m(i,j) = samples(internal::random<Index>(0,samples.size()-1)); } } } } else { m = U * d.asDiagonal() * VT; // (partly) cancel some coeffs
if(!(dup && unit_uv)) { Index n = internal::random<Index>(0,m.size()-1); for(Index i=0; i<n; ++i) m(internal::random<Index>(0,m.rows()-1), internal::random<Index>(0,m.cols()-1)) = samples(internal::random<Index>(0,samples.size()-1)); } } }
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