Narayan Kamath | c981c48 | 2012-11-02 10:59:05 +0000 | [diff] [blame] | 1 | // This file is part of Eigen, a lightweight C++ template library |
| 2 | // for linear algebra. |
| 3 | // |
| 4 | // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> |
| 5 | // |
| 6 | // This Source Code Form is subject to the terms of the Mozilla |
| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed |
| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| 9 | |
| 10 | #include "main.h" |
| 11 | |
| 12 | using namespace std; |
| 13 | template<typename MatrixType> void permutationmatrices(const MatrixType& m) |
| 14 | { |
| 15 | typedef typename MatrixType::Index Index; |
| 16 | typedef typename MatrixType::Scalar Scalar; |
Narayan Kamath | c981c48 | 2012-11-02 10:59:05 +0000 | [diff] [blame] | 17 | enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime, |
| 18 | Options = MatrixType::Options }; |
| 19 | typedef PermutationMatrix<Rows> LeftPermutationType; |
| 20 | typedef Matrix<int, Rows, 1> LeftPermutationVectorType; |
| 21 | typedef Map<LeftPermutationType> MapLeftPerm; |
| 22 | typedef PermutationMatrix<Cols> RightPermutationType; |
| 23 | typedef Matrix<int, Cols, 1> RightPermutationVectorType; |
| 24 | typedef Map<RightPermutationType> MapRightPerm; |
| 25 | |
| 26 | Index rows = m.rows(); |
| 27 | Index cols = m.cols(); |
| 28 | |
| 29 | MatrixType m_original = MatrixType::Random(rows,cols); |
| 30 | LeftPermutationVectorType lv; |
| 31 | randomPermutationVector(lv, rows); |
| 32 | LeftPermutationType lp(lv); |
| 33 | RightPermutationVectorType rv; |
| 34 | randomPermutationVector(rv, cols); |
| 35 | RightPermutationType rp(rv); |
| 36 | MatrixType m_permuted = lp * m_original * rp; |
| 37 | |
| 38 | for (int i=0; i<rows; i++) |
| 39 | for (int j=0; j<cols; j++) |
| 40 | VERIFY_IS_APPROX(m_permuted(lv(i),j), m_original(i,rv(j))); |
| 41 | |
| 42 | Matrix<Scalar,Rows,Rows> lm(lp); |
| 43 | Matrix<Scalar,Cols,Cols> rm(rp); |
| 44 | |
| 45 | VERIFY_IS_APPROX(m_permuted, lm*m_original*rm); |
| 46 | |
| 47 | VERIFY_IS_APPROX(lp.inverse()*m_permuted*rp.inverse(), m_original); |
| 48 | VERIFY_IS_APPROX(lv.asPermutation().inverse()*m_permuted*rv.asPermutation().inverse(), m_original); |
| 49 | VERIFY_IS_APPROX(MapLeftPerm(lv.data(),lv.size()).inverse()*m_permuted*MapRightPerm(rv.data(),rv.size()).inverse(), m_original); |
| 50 | |
| 51 | VERIFY((lp*lp.inverse()).toDenseMatrix().isIdentity()); |
| 52 | VERIFY((lv.asPermutation()*lv.asPermutation().inverse()).toDenseMatrix().isIdentity()); |
| 53 | VERIFY((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv.data(),lv.size()).inverse()).toDenseMatrix().isIdentity()); |
| 54 | |
| 55 | LeftPermutationVectorType lv2; |
| 56 | randomPermutationVector(lv2, rows); |
| 57 | LeftPermutationType lp2(lv2); |
| 58 | Matrix<Scalar,Rows,Rows> lm2(lp2); |
| 59 | VERIFY_IS_APPROX((lp*lp2).toDenseMatrix().template cast<Scalar>(), lm*lm2); |
| 60 | VERIFY_IS_APPROX((lv.asPermutation()*lv2.asPermutation()).toDenseMatrix().template cast<Scalar>(), lm*lm2); |
| 61 | VERIFY_IS_APPROX((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv2.data(),lv2.size())).toDenseMatrix().template cast<Scalar>(), lm*lm2); |
| 62 | |
| 63 | LeftPermutationType identityp; |
| 64 | identityp.setIdentity(rows); |
| 65 | VERIFY_IS_APPROX(m_original, identityp*m_original); |
| 66 | |
| 67 | // check inplace permutations |
| 68 | m_permuted = m_original; |
| 69 | m_permuted = lp.inverse() * m_permuted; |
| 70 | VERIFY_IS_APPROX(m_permuted, lp.inverse()*m_original); |
| 71 | |
| 72 | m_permuted = m_original; |
| 73 | m_permuted = m_permuted * rp.inverse(); |
| 74 | VERIFY_IS_APPROX(m_permuted, m_original*rp.inverse()); |
| 75 | |
| 76 | m_permuted = m_original; |
| 77 | m_permuted = lp * m_permuted; |
| 78 | VERIFY_IS_APPROX(m_permuted, lp*m_original); |
| 79 | |
| 80 | m_permuted = m_original; |
| 81 | m_permuted = m_permuted * rp; |
| 82 | VERIFY_IS_APPROX(m_permuted, m_original*rp); |
| 83 | |
| 84 | if(rows>1 && cols>1) |
| 85 | { |
| 86 | lp2 = lp; |
| 87 | Index i = internal::random<Index>(0, rows-1); |
| 88 | Index j; |
| 89 | do j = internal::random<Index>(0, rows-1); while(j==i); |
| 90 | lp2.applyTranspositionOnTheLeft(i, j); |
| 91 | lm = lp; |
| 92 | lm.row(i).swap(lm.row(j)); |
| 93 | VERIFY_IS_APPROX(lm, lp2.toDenseMatrix().template cast<Scalar>()); |
| 94 | |
| 95 | RightPermutationType rp2 = rp; |
| 96 | i = internal::random<Index>(0, cols-1); |
| 97 | do j = internal::random<Index>(0, cols-1); while(j==i); |
| 98 | rp2.applyTranspositionOnTheRight(i, j); |
| 99 | rm = rp; |
| 100 | rm.col(i).swap(rm.col(j)); |
| 101 | VERIFY_IS_APPROX(rm, rp2.toDenseMatrix().template cast<Scalar>()); |
| 102 | } |
| 103 | } |
| 104 | |
| 105 | void test_permutationmatrices() |
| 106 | { |
| 107 | for(int i = 0; i < g_repeat; i++) { |
| 108 | CALL_SUBTEST_1( permutationmatrices(Matrix<float, 1, 1>()) ); |
| 109 | CALL_SUBTEST_2( permutationmatrices(Matrix3f()) ); |
| 110 | CALL_SUBTEST_3( permutationmatrices(Matrix<double,3,3,RowMajor>()) ); |
| 111 | CALL_SUBTEST_4( permutationmatrices(Matrix4d()) ); |
| 112 | CALL_SUBTEST_5( permutationmatrices(Matrix<double,40,60>()) ); |
| 113 | CALL_SUBTEST_6( permutationmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 30)) ); |
| 114 | CALL_SUBTEST_7( permutationmatrices(MatrixXcf(15, 10)) ); |
| 115 | } |
| 116 | } |