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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "main.h"
using namespace std;
template<typename MatrixType> void permutationmatrices(const MatrixType& m)
{
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime,
Options = MatrixType::Options };
typedef PermutationMatrix<Rows> LeftPermutationType;
typedef Matrix<int, Rows, 1> LeftPermutationVectorType;
typedef Map<LeftPermutationType> MapLeftPerm;
typedef PermutationMatrix<Cols> RightPermutationType;
typedef Matrix<int, Cols, 1> RightPermutationVectorType;
typedef Map<RightPermutationType> MapRightPerm;
Index rows = m.rows();
Index cols = m.cols();
MatrixType m_original = MatrixType::Random(rows,cols);
LeftPermutationVectorType lv;
randomPermutationVector(lv, rows);
LeftPermutationType lp(lv);
RightPermutationVectorType rv;
randomPermutationVector(rv, cols);
RightPermutationType rp(rv);
MatrixType m_permuted = lp * m_original * rp;
for (int i=0; i<rows; i++)
for (int j=0; j<cols; j++)
VERIFY_IS_APPROX(m_permuted(lv(i),j), m_original(i,rv(j)));
Matrix<Scalar,Rows,Rows> lm(lp);
Matrix<Scalar,Cols,Cols> rm(rp);
VERIFY_IS_APPROX(m_permuted, lm*m_original*rm);
VERIFY_IS_APPROX(lp.inverse()*m_permuted*rp.inverse(), m_original);
VERIFY_IS_APPROX(lv.asPermutation().inverse()*m_permuted*rv.asPermutation().inverse(), m_original);
VERIFY_IS_APPROX(MapLeftPerm(lv.data(),lv.size()).inverse()*m_permuted*MapRightPerm(rv.data(),rv.size()).inverse(), m_original);
VERIFY((lp*lp.inverse()).toDenseMatrix().isIdentity());
VERIFY((lv.asPermutation()*lv.asPermutation().inverse()).toDenseMatrix().isIdentity());
VERIFY((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv.data(),lv.size()).inverse()).toDenseMatrix().isIdentity());
LeftPermutationVectorType lv2;
randomPermutationVector(lv2, rows);
LeftPermutationType lp2(lv2);
Matrix<Scalar,Rows,Rows> lm2(lp2);
VERIFY_IS_APPROX((lp*lp2).toDenseMatrix().template cast<Scalar>(), lm*lm2);
VERIFY_IS_APPROX((lv.asPermutation()*lv2.asPermutation()).toDenseMatrix().template cast<Scalar>(), lm*lm2);
VERIFY_IS_APPROX((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv2.data(),lv2.size())).toDenseMatrix().template cast<Scalar>(), lm*lm2);
LeftPermutationType identityp;
identityp.setIdentity(rows);
VERIFY_IS_APPROX(m_original, identityp*m_original);
// check inplace permutations
m_permuted = m_original;
m_permuted = lp.inverse() * m_permuted;
VERIFY_IS_APPROX(m_permuted, lp.inverse()*m_original);
m_permuted = m_original;
m_permuted = m_permuted * rp.inverse();
VERIFY_IS_APPROX(m_permuted, m_original*rp.inverse());
m_permuted = m_original;
m_permuted = lp * m_permuted;
VERIFY_IS_APPROX(m_permuted, lp*m_original);
m_permuted = m_original;
m_permuted = m_permuted * rp;
VERIFY_IS_APPROX(m_permuted, m_original*rp);
if(rows>1 && cols>1)
{
lp2 = lp;
Index i = internal::random<Index>(0, rows-1);
Index j;
do j = internal::random<Index>(0, rows-1); while(j==i);
lp2.applyTranspositionOnTheLeft(i, j);
lm = lp;
lm.row(i).swap(lm.row(j));
VERIFY_IS_APPROX(lm, lp2.toDenseMatrix().template cast<Scalar>());
RightPermutationType rp2 = rp;
i = internal::random<Index>(0, cols-1);
do j = internal::random<Index>(0, cols-1); while(j==i);
rp2.applyTranspositionOnTheRight(i, j);
rm = rp;
rm.col(i).swap(rm.col(j));
VERIFY_IS_APPROX(rm, rp2.toDenseMatrix().template cast<Scalar>());
}
}
void test_permutationmatrices()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( permutationmatrices(Matrix<float, 1, 1>()) );
CALL_SUBTEST_2( permutationmatrices(Matrix3f()) );
CALL_SUBTEST_3( permutationmatrices(Matrix<double,3,3,RowMajor>()) );
CALL_SUBTEST_4( permutationmatrices(Matrix4d()) );
CALL_SUBTEST_5( permutationmatrices(Matrix<double,40,60>()) );
CALL_SUBTEST_6( permutationmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 30)) );
CALL_SUBTEST_7( permutationmatrices(MatrixXcf(15, 10)) );
}
}
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