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port the QR module to PermutationMatrix
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@ -594,7 +594,8 @@ struct ei_image_retval<FullPivLU<_MatrixType> >
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pivots.coeffRef(p++) = i;
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ei_internal_assert(p == rank());
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dst.block(0,0,dst.rows(),rank()) = (originalMatrix()*dec().permutationQ()).block(0,0,dst.rows(),rank());
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for(int i = 0; i < rank(); ++i)
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dst.col(i) = originalMatrix().col(dec().permutationQ().indices().coeff(pivots.coeff(i)));
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}
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};
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@ -630,8 +631,7 @@ struct ei_solve_retval<FullPivLU<_MatrixType>, Rhs>
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typename Rhs::PlainMatrixType c(rhs().rows(), rhs().cols());
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// Step 1
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for(int i = 0; i < rows; ++i)
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c.row(dec().permutationP().indices().coeff(i)) = rhs().row(i);
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c = dec().permutationP() * rhs();
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// Step 2
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dec().matrixLU()
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@ -57,10 +57,9 @@ template<typename _MatrixType> class ColPivHouseholderQR
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typedef typename MatrixType::RealScalar RealScalar;
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typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime> MatrixQType;
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typedef Matrix<Scalar, DiagSizeAtCompileTime, 1> HCoeffsType;
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typedef PermutationMatrix<ColsAtCompileTime> PermutationType;
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typedef Matrix<int, 1, ColsAtCompileTime> IntRowVectorType;
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typedef Matrix<int, RowsAtCompileTime, 1> IntColVectorType;
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typedef Matrix<Scalar, 1, ColsAtCompileTime> RowVectorType;
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typedef Matrix<Scalar, RowsAtCompileTime, 1> ColVectorType;
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typedef Matrix<RealScalar, 1, ColsAtCompileTime> RealRowVectorType;
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typedef typename HouseholderSequence<MatrixType,HCoeffsType>::ConjugateReturnType HouseholderSequenceType;
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@ -117,7 +116,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
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ColPivHouseholderQR& compute(const MatrixType& matrix);
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const IntRowVectorType& colsPermutation() const
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const PermutationType& colsPermutation() const
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{
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ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
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return m_cols_permutation;
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@ -230,7 +229,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
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protected:
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MatrixType m_qr;
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HCoeffsType m_hCoeffs;
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IntRowVectorType m_cols_permutation;
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PermutationType m_cols_permutation;
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bool m_isInitialized;
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RealScalar m_precision;
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int m_rank;
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@ -271,7 +270,6 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
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m_precision = epsilon<Scalar>() * size;
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IntRowVectorType cols_transpositions(matrix.cols());
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m_cols_permutation.resize(matrix.cols());
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int number_of_transpositions = 0;
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RealRowVectorType colSqNorms(cols);
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@ -314,9 +312,9 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
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colSqNorms.end(cols-k-1) -= m_qr.row(k).end(cols-k-1).cwise().abs2();
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}
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for(int k = 0; k < matrix.cols(); ++k) m_cols_permutation.coeffRef(k) = k;
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m_cols_permutation.setIdentity(cols);
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for(int k = 0; k < size; ++k)
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std::swap(m_cols_permutation.coeffRef(k), m_cols_permutation.coeffRef(cols_transpositions.coeff(k)));
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m_cols_permutation.applyTranspositionOnTheLeft(k, cols_transpositions.coeff(k));
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m_det_pq = (number_of_transpositions%2) ? -1 : 1;
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m_isInitialized = true;
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@ -368,8 +366,7 @@ struct ei_solve_retval<ColPivHouseholderQR<_MatrixType>, Rhs>
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.template triangularView<UpperTriangular>()
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.solveInPlace(c.corner(TopLeft, dec().rank(), c.cols()));
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for(int i = 0; i < dec().rank(); ++i) dst.row(dec().colsPermutation().coeff(i)) = c.row(i);
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for(int i = dec().rank(); i < cols; ++i) dst.row(dec().colsPermutation().coeff(i)).setZero();
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dst = dec().colsPermutation() * c;
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}
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};
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@ -58,6 +58,7 @@ template<typename _MatrixType> class FullPivHouseholderQR
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typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime> MatrixQType;
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typedef Matrix<Scalar, DiagSizeAtCompileTime, 1> HCoeffsType;
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typedef Matrix<int, 1, ColsAtCompileTime> IntRowVectorType;
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typedef PermutationMatrix<ColsAtCompileTime> PermutationType;
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typedef Matrix<int, RowsAtCompileTime, 1> IntColVectorType;
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typedef Matrix<Scalar, 1, ColsAtCompileTime> RowVectorType;
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typedef Matrix<Scalar, RowsAtCompileTime, 1> ColVectorType;
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@ -112,7 +113,7 @@ template<typename _MatrixType> class FullPivHouseholderQR
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FullPivHouseholderQR& compute(const MatrixType& matrix);
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const IntRowVectorType& colsPermutation() const
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const PermutationType& colsPermutation() const
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{
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ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
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return m_cols_permutation;
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@ -231,7 +232,7 @@ template<typename _MatrixType> class FullPivHouseholderQR
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MatrixType m_qr;
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HCoeffsType m_hCoeffs;
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IntColVectorType m_rows_transpositions;
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IntRowVectorType m_cols_permutation;
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PermutationType m_cols_permutation;
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bool m_isInitialized;
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RealScalar m_precision;
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int m_rank;
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@ -273,7 +274,6 @@ FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(cons
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m_rows_transpositions.resize(matrix.rows());
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IntRowVectorType cols_transpositions(matrix.cols());
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m_cols_permutation.resize(matrix.cols());
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int number_of_transpositions = 0;
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RealScalar biggest(0);
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@ -322,9 +322,9 @@ FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(cons
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.applyHouseholderOnTheLeft(m_qr.col(k).end(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1));
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}
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for(int k = 0; k < matrix.cols(); ++k) m_cols_permutation.coeffRef(k) = k;
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m_cols_permutation.setIdentity(cols);
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for(int k = 0; k < size; ++k)
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std::swap(m_cols_permutation.coeffRef(k), m_cols_permutation.coeffRef(cols_transpositions.coeff(k)));
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m_cols_permutation.applyTranspositionOnTheRight(k, cols_transpositions.coeff(k));
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m_det_pq = (number_of_transpositions%2) ? -1 : 1;
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m_isInitialized = true;
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@ -379,8 +379,8 @@ struct ei_solve_retval<FullPivHouseholderQR<_MatrixType>, Rhs>
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.template triangularView<UpperTriangular>()
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.solveInPlace(c.corner(TopLeft, dec().rank(), c.cols()));
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for(int i = 0; i < dec().rank(); ++i) dst.row(dec().colsPermutation().coeff(i)) = c.row(i);
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for(int i = dec().rank(); i < cols; ++i) dst.row(dec().colsPermutation().coeff(i)).setZero();
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for(int i = 0; i < dec().rank(); ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
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for(int i = dec().rank(); i < cols; ++i) dst.row(dec().colsPermutation().indices().coeff(i)).setZero();
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}
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};
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@ -51,11 +51,8 @@ template<typename MatrixType> void qr()
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// FIXME need better way to construct trapezoid
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for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) if(i>j) r(i,j) = Scalar(0);
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MatrixType b = qr.matrixQ() * r;
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MatrixType c = qr.matrixQ() * r * qr.colsPermutation().inverse();
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MatrixType c = MatrixType::Zero(rows,cols);
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for(int i = 0; i < cols; ++i) c.col(qr.colsPermutation().coeff(i)) = b.col(i);
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VERIFY_IS_APPROX(m1, c);
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MatrixType m2 = MatrixType::Random(cols,cols2);
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