Disabled external gits
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cs440-acg/ext/eigen/test/permutationmatrices.cpp
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cs440-acg/ext/eigen/test/permutationmatrices.cpp
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#define TEST_ENABLE_TEMPORARY_TRACKING
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#include "main.h"
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using namespace std;
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template<typename MatrixType> void permutationmatrices(const MatrixType& m)
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{
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typedef typename MatrixType::Scalar Scalar;
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enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime,
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Options = MatrixType::Options };
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typedef PermutationMatrix<Rows> LeftPermutationType;
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typedef Transpositions<Rows> LeftTranspositionsType;
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typedef Matrix<int, Rows, 1> LeftPermutationVectorType;
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typedef Map<LeftPermutationType> MapLeftPerm;
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typedef PermutationMatrix<Cols> RightPermutationType;
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typedef Transpositions<Cols> RightTranspositionsType;
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typedef Matrix<int, Cols, 1> RightPermutationVectorType;
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typedef Map<RightPermutationType> MapRightPerm;
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Index rows = m.rows();
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Index cols = m.cols();
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MatrixType m_original = MatrixType::Random(rows,cols);
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LeftPermutationVectorType lv;
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randomPermutationVector(lv, rows);
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LeftPermutationType lp(lv);
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RightPermutationVectorType rv;
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randomPermutationVector(rv, cols);
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RightPermutationType rp(rv);
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LeftTranspositionsType lt(lv);
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RightTranspositionsType rt(rv);
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MatrixType m_permuted = MatrixType::Random(rows,cols);
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VERIFY_EVALUATION_COUNT(m_permuted = lp * m_original * rp, 1); // 1 temp for sub expression "lp * m_original"
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for (int i=0; i<rows; i++)
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for (int j=0; j<cols; j++)
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VERIFY_IS_APPROX(m_permuted(lv(i),j), m_original(i,rv(j)));
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Matrix<Scalar,Rows,Rows> lm(lp);
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Matrix<Scalar,Cols,Cols> rm(rp);
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VERIFY_IS_APPROX(m_permuted, lm*m_original*rm);
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted = lp * m_permuted * rp, 1);
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VERIFY_IS_APPROX(m_permuted, lm*m_original*rm);
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VERIFY_IS_APPROX(lp.inverse()*m_permuted*rp.inverse(), m_original);
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VERIFY_IS_APPROX(lv.asPermutation().inverse()*m_permuted*rv.asPermutation().inverse(), m_original);
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VERIFY_IS_APPROX(MapLeftPerm(lv.data(),lv.size()).inverse()*m_permuted*MapRightPerm(rv.data(),rv.size()).inverse(), m_original);
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VERIFY((lp*lp.inverse()).toDenseMatrix().isIdentity());
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VERIFY((lv.asPermutation()*lv.asPermutation().inverse()).toDenseMatrix().isIdentity());
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VERIFY((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv.data(),lv.size()).inverse()).toDenseMatrix().isIdentity());
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LeftPermutationVectorType lv2;
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randomPermutationVector(lv2, rows);
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LeftPermutationType lp2(lv2);
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Matrix<Scalar,Rows,Rows> lm2(lp2);
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VERIFY_IS_APPROX((lp*lp2).toDenseMatrix().template cast<Scalar>(), lm*lm2);
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VERIFY_IS_APPROX((lv.asPermutation()*lv2.asPermutation()).toDenseMatrix().template cast<Scalar>(), lm*lm2);
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VERIFY_IS_APPROX((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv2.data(),lv2.size())).toDenseMatrix().template cast<Scalar>(), lm*lm2);
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LeftPermutationType identityp;
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identityp.setIdentity(rows);
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VERIFY_IS_APPROX(m_original, identityp*m_original);
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// check inplace permutations
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted.noalias()= lp.inverse() * m_permuted, 1); // 1 temp to allocate the mask
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VERIFY_IS_APPROX(m_permuted, lp.inverse()*m_original);
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted.noalias() = m_permuted * rp.inverse(), 1); // 1 temp to allocate the mask
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VERIFY_IS_APPROX(m_permuted, m_original*rp.inverse());
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted.noalias() = lp * m_permuted, 1); // 1 temp to allocate the mask
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VERIFY_IS_APPROX(m_permuted, lp*m_original);
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m_permuted = m_original;
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VERIFY_EVALUATION_COUNT(m_permuted.noalias() = m_permuted * rp, 1); // 1 temp to allocate the mask
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VERIFY_IS_APPROX(m_permuted, m_original*rp);
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if(rows>1 && cols>1)
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{
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lp2 = lp;
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Index i = internal::random<Index>(0, rows-1);
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Index j;
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do j = internal::random<Index>(0, rows-1); while(j==i);
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lp2.applyTranspositionOnTheLeft(i, j);
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lm = lp;
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lm.row(i).swap(lm.row(j));
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VERIFY_IS_APPROX(lm, lp2.toDenseMatrix().template cast<Scalar>());
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RightPermutationType rp2 = rp;
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i = internal::random<Index>(0, cols-1);
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do j = internal::random<Index>(0, cols-1); while(j==i);
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rp2.applyTranspositionOnTheRight(i, j);
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rm = rp;
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rm.col(i).swap(rm.col(j));
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VERIFY_IS_APPROX(rm, rp2.toDenseMatrix().template cast<Scalar>());
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}
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{
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// simple compilation check
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Matrix<Scalar, Cols, Cols> A = rp;
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Matrix<Scalar, Cols, Cols> B = rp.transpose();
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VERIFY_IS_APPROX(A, B.transpose());
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}
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m_permuted = m_original;
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lp = lt;
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rp = rt;
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VERIFY_EVALUATION_COUNT(m_permuted = lt * m_permuted * rt, 1);
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VERIFY_IS_APPROX(m_permuted, lp*m_original*rp.transpose());
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VERIFY_IS_APPROX(lt.inverse()*m_permuted*rt.inverse(), m_original);
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}
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template<typename T>
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void bug890()
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{
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typedef Matrix<T, Dynamic, Dynamic> MatrixType;
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typedef Matrix<T, Dynamic, 1> VectorType;
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typedef Stride<Dynamic,Dynamic> S;
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typedef Map<MatrixType, Aligned, S> MapType;
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typedef PermutationMatrix<Dynamic> Perm;
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VectorType v1(2), v2(2), op(4), rhs(2);
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v1 << 666,667;
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op << 1,0,0,1;
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rhs << 42,42;
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Perm P(2);
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P.indices() << 1, 0;
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MapType(v1.data(),2,1,S(1,1)) = P * MapType(rhs.data(),2,1,S(1,1));
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VERIFY_IS_APPROX(v1, (P * rhs).eval());
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MapType(v1.data(),2,1,S(1,1)) = P.inverse() * MapType(rhs.data(),2,1,S(1,1));
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VERIFY_IS_APPROX(v1, (P.inverse() * rhs).eval());
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}
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void test_permutationmatrices()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( permutationmatrices(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( permutationmatrices(Matrix3f()) );
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CALL_SUBTEST_3( permutationmatrices(Matrix<double,3,3,RowMajor>()) );
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CALL_SUBTEST_4( permutationmatrices(Matrix4d()) );
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CALL_SUBTEST_5( permutationmatrices(Matrix<double,40,60>()) );
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CALL_SUBTEST_6( permutationmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 30)) );
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CALL_SUBTEST_7( permutationmatrices(MatrixXcf(15, 10)) );
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}
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CALL_SUBTEST_5( bug890<double>() );
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}
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