|  | // 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" | 
|  |  | 
|  | template<typename PermutationVectorType> | 
|  | void randomPermutationVector(PermutationVectorType& v, typename PermutationVectorType::Index size) | 
|  | { | 
|  | typedef typename PermutationVectorType::Index Index; | 
|  | typedef typename PermutationVectorType::Scalar Scalar; | 
|  | v.resize(size); | 
|  | for(Index i = 0; i < size; ++i) v(i) = Scalar(i); | 
|  | if(size == 1) return; | 
|  | for(Index n = 0; n < 3 * size; ++n) | 
|  | { | 
|  | Index i = ei_random<Index>(0, size-1); | 
|  | Index j; | 
|  | do j = ei_random<Index>(0, size-1); while(j==i); | 
|  | std::swap(v(i), v(j)); | 
|  | } | 
|  | } | 
|  |  | 
|  | 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 PermutationMatrix<Cols> RightPermutationType; | 
|  | typedef Matrix<int, Cols, 1> RightPermutationVectorType; | 
|  |  | 
|  | 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((lp*lp.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); | 
|  |  | 
|  | 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 = ei_random<Index>(0, rows-1); | 
|  | Index j; | 
|  | do j = ei_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 = ei_random<Index>(0, cols-1); | 
|  | do j = ei_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)) ); | 
|  | } | 
|  | } |