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Diffstat (limited to 'eigen/test/permutationmatrices.cpp')
-rw-r--r-- | eigen/test/permutationmatrices.cpp | 116 |
1 files changed, 116 insertions, 0 deletions
diff --git a/eigen/test/permutationmatrices.cpp b/eigen/test/permutationmatrices.cpp new file mode 100644 index 0000000..7b0dbc7 --- /dev/null +++ b/eigen/test/permutationmatrices.cpp @@ -0,0 +1,116 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> +// +// 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/. + +#include "main.h" + +using namespace std; +template<typename MatrixType> void permutationmatrices(const MatrixType& m) +{ + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + 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)) ); + } +} |