// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2009 Benoit Jacob // // 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 . #ifndef EIGEN_INVERSE_H #define EIGEN_INVERSE_H /******************************************************************** *** Part 1 : optimized implementations for fixed-size 2,3,4 cases *** ********************************************************************/ template inline void ei_compute_inverse_size2_helper( const MatrixType& matrix, const typename ResultType::Scalar& invdet, ResultType& result) { result.coeffRef(0,0) = matrix.coeff(1,1) * invdet; result.coeffRef(1,0) = -matrix.coeff(1,0) * invdet; result.coeffRef(0,1) = -matrix.coeff(0,1) * invdet; result.coeffRef(1,1) = matrix.coeff(0,0) * invdet; } template inline void ei_compute_inverse_size2(const MatrixType& matrix, ResultType& result) { typedef typename ResultType::Scalar Scalar; const Scalar invdet = typename MatrixType::Scalar(1) / matrix.determinant(); ei_compute_inverse_size2_helper(matrix, invdet, result); } template inline void ei_compute_inverse_and_det_size2_with_check( const MatrixType& matrix, const typename MatrixType::RealScalar& absDeterminantThreshold, ResultType& inverse, typename ResultType::Scalar& determinant, bool& invertible ) { typedef typename ResultType::Scalar Scalar; determinant = matrix.determinant(); invertible = ei_abs(determinant) > absDeterminantThreshold; if(!invertible) return; const Scalar invdet = Scalar(1) / determinant; ei_compute_inverse_size2_helper(matrix, invdet, inverse); } template void ei_compute_inverse_size3_helper( const MatrixType& matrix, const typename ResultType::Scalar& invdet, const Matrix& cofactors_col0, ResultType& result) { result.row(0) = cofactors_col0 * invdet; result.coeffRef(1,0) = -matrix.minor(0,1).determinant() * invdet; result.coeffRef(1,1) = matrix.minor(1,1).determinant() * invdet; result.coeffRef(1,2) = -matrix.minor(2,1).determinant() * invdet; result.coeffRef(2,0) = matrix.minor(0,2).determinant() * invdet; result.coeffRef(2,1) = -matrix.minor(1,2).determinant() * invdet; result.coeffRef(2,2) = matrix.minor(2,2).determinant() * invdet; } template void ei_compute_inverse_size3( const MatrixType& matrix, ResultType& result) { typedef typename ResultType::Scalar Scalar; Matrix cofactors_col0; cofactors_col0.coeffRef(0) = matrix.minor(0,0).determinant(); cofactors_col0.coeffRef(1) = -matrix.minor(1,0).determinant(); cofactors_col0.coeffRef(2) = matrix.minor(2,0).determinant(); const Scalar det = (cofactors_col0.cwise()*matrix.col(0)).sum(); const Scalar invdet = Scalar(1) / det; ei_compute_inverse_size3_helper(matrix, invdet, cofactors_col0, result); } template void ei_compute_inverse_and_det_size3_with_check( const MatrixType& matrix, const typename MatrixType::RealScalar& absDeterminantThreshold, ResultType& inverse, typename ResultType::Scalar& determinant, bool& invertible ) { typedef typename ResultType::Scalar Scalar; Matrix cofactors_col0; cofactors_col0.coeffRef(0) = matrix.minor(0,0).determinant(); cofactors_col0.coeffRef(1) = -matrix.minor(1,0).determinant(); cofactors_col0.coeffRef(2) = matrix.minor(2,0).determinant(); determinant = (cofactors_col0.cwise()*matrix.col(0)).sum(); invertible = ei_abs(determinant) > absDeterminantThreshold; if(!invertible) return; const Scalar invdet = Scalar(1) / determinant; ei_compute_inverse_size3_helper(matrix, invdet, cofactors_col0, inverse); } template void ei_compute_inverse_size4_helper(const MatrixType& matrix, ResultType& result) { /* Let's split M into four 2x2 blocks: * (P Q) * (R S) * If P is invertible, with inverse denoted by P_inverse, and if * (S - R*P_inverse*Q) is also invertible, then the inverse of M is * (P' Q') * (R' S') * where * S' = (S - R*P_inverse*Q)^(-1) * P' = P1 + (P1*Q) * S' *(R*P_inverse) * Q' = -(P_inverse*Q) * S' * R' = -S' * (R*P_inverse) */ typedef Block XprBlock22; typedef typename MatrixBase::PlainMatrixType Block22; Block22 P_inverse; ei_compute_inverse_size2(matrix.template block<2,2>(0,0), P_inverse); const Block22 Q = matrix.template block<2,2>(0,2); const Block22 P_inverse_times_Q = P_inverse * Q; const XprBlock22 R = matrix.template block<2,2>(2,0); const Block22 R_times_P_inverse = R * P_inverse; const Block22 R_times_P_inverse_times_Q = R_times_P_inverse * Q; const XprBlock22 S = matrix.template block<2,2>(2,2); const Block22 X = S - R_times_P_inverse_times_Q; Block22 Y; ei_compute_inverse_size2(X, Y); result.template block<2,2>(2,2) = Y; result.template block<2,2>(2,0) = - Y * R_times_P_inverse; const Block22 Z = P_inverse_times_Q * Y; result.template block<2,2>(0,2) = - Z; result.template block<2,2>(0,0) = P_inverse + Z * R_times_P_inverse; } template void ei_compute_inverse_size4(const MatrixType& _matrix, ResultType& result) { typedef typename ResultType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; // we will do row permutations on the matrix. This copy should have negligible cost. // if not, consider working in-place on the matrix (const-cast it, but then undo the permutations // to nevertheless honor constness) typename MatrixType::PlainMatrixType matrix(_matrix); // let's extract from the 2 first colums a 2x2 block whose determinant is as big as possible. int good_row0=0, good_row1=1; RealScalar good_absdet(-1); // this double for loop shouldn't be too costly: only 6 iterations for(int row0=0; row0<4; ++row0) { for(int row1=row0+1; row1<4; ++row1) { RealScalar absdet = ei_abs(matrix.coeff(row0,0)*matrix.coeff(row1,1) - matrix.coeff(row0,1)*matrix.coeff(row1,0)); if(absdet > good_absdet) { good_absdet = absdet; good_row0 = row0; good_row1 = row1; } } } // do row permutations to move this 2x2 block to the top matrix.row(0).swap(matrix.row(good_row0)); matrix.row(1).swap(matrix.row(good_row1)); // now applying our helper function is numerically stable ei_compute_inverse_size4_helper(matrix, result); // Since we did row permutations on the original matrix, we need to do column permutations // in the reverse order on the inverse result.col(1).swap(result.col(good_row1)); result.col(0).swap(result.col(good_row0)); } template void ei_compute_inverse_and_det_size4_with_check( const MatrixType& matrix, const typename MatrixType::RealScalar& absDeterminantThreshold, ResultType& result, typename ResultType::Scalar& determinant, bool& invertible ) { determinant = matrix.determinant(); invertible = ei_abs(determinant) > absDeterminantThreshold; if(invertible) ei_compute_inverse_size4(matrix, result); } /*********************************************** *** Part 2 : selectors and MatrixBase methods *** ***********************************************/ template struct ei_compute_inverse { static inline void run(const MatrixType& matrix, ResultType& result) { result = matrix.partialLu().inverse(); } }; template struct ei_compute_inverse { static inline void run(const MatrixType& matrix, ResultType& result) { typedef typename MatrixType::Scalar Scalar; result.coeffRef(0,0) = Scalar(1) / matrix.coeff(0,0); } }; template struct ei_compute_inverse { static inline void run(const MatrixType& matrix, ResultType& result) { ei_compute_inverse_size2(matrix, result); } }; template struct ei_compute_inverse { static inline void run(const MatrixType& matrix, ResultType& result) { ei_compute_inverse_size3(matrix, result); } }; template struct ei_compute_inverse { static inline void run(const MatrixType& matrix, ResultType& result) { ei_compute_inverse_size4(matrix, result); } }; /** \lu_module * * \returns the matrix inverse of this matrix. * * For small fixed sizes up to 4x4, this method uses ad-hoc methods (cofactors up to 3x3, Euler's trick for 4x4). * In the general case, this method uses class PartialLU. * * \note This matrix must be invertible, otherwise the result is undefined. If you need an * invertibility check, do the following: * \li for fixed sizes up to 4x4, use computeInverseAndDetWithCheck(). * \li for the general case, use class LU. * * Example: \include MatrixBase_inverse.cpp * Output: \verbinclude MatrixBase_inverse.out * * \sa computeInverseAndDetWithCheck() */ template inline const typename MatrixBase::PlainMatrixType MatrixBase::inverse() const { EIGEN_STATIC_ASSERT(NumTraits::HasFloatingPoint,NUMERIC_TYPE_MUST_BE_FLOATING_POINT) ei_assert(rows() == cols()); typedef typename MatrixBase::PlainMatrixType ResultType; ResultType result(rows(), cols()); // for 2x2, it's worth giving a chance to avoid evaluating. // for larger sizes, evaluating has negligible cost and limits code size. typedef typename ei_meta_if< RowsAtCompileTime == 2, typename ei_cleantype::type>::type, PlainMatrixType >::ret MatrixType; ei_compute_inverse::run(derived(), result); return result; } /******************************************** * Compute inverse with invertibility check * *******************************************/ template struct ei_compute_inverse_and_det_with_check {}; template struct ei_compute_inverse_and_det_with_check { static inline void run( const MatrixType& matrix, const typename MatrixType::RealScalar& absDeterminantThreshold, ResultType& result, typename ResultType::Scalar& determinant, bool& invertible ) { determinant = matrix.coeff(0,0); invertible = ei_abs(determinant) > absDeterminantThreshold; if(invertible) result.coeffRef(0,0) = typename ResultType::Scalar(1) / determinant; } }; template struct ei_compute_inverse_and_det_with_check { static inline void run( const MatrixType& matrix, const typename MatrixType::RealScalar& absDeterminantThreshold, ResultType& result, typename ResultType::Scalar& determinant, bool& invertible ) { ei_compute_inverse_and_det_size2_with_check (matrix, absDeterminantThreshold, result, determinant, invertible); } }; template struct ei_compute_inverse_and_det_with_check { static inline void run( const MatrixType& matrix, const typename MatrixType::RealScalar& absDeterminantThreshold, ResultType& result, typename ResultType::Scalar& determinant, bool& invertible ) { ei_compute_inverse_and_det_size3_with_check (matrix, absDeterminantThreshold, result, determinant, invertible); } }; template struct ei_compute_inverse_and_det_with_check { static inline void run( const MatrixType& matrix, const typename MatrixType::RealScalar& absDeterminantThreshold, ResultType& result, typename ResultType::Scalar& determinant, bool& invertible ) { ei_compute_inverse_and_det_size4_with_check (matrix, absDeterminantThreshold, result, determinant, invertible); } }; /** \lu_module * * Computation of matrix inverse and determinant, with invertibility check. * * This is only for fixed-size square matrices of size up to 4x4. * * \param inverse Reference to the matrix in which to store the inverse. * \param determinant Reference to the variable in which to store the inverse. * \param invertible Reference to the bool variable in which to store whether the matrix is invertible. * \param absDeterminantThreshold Optional parameter controlling the invertibility check. * The matrix will be declared invertible if the absolute value of its * determinant is greater than this threshold. * * \sa inverse() */ template template inline void MatrixBase::computeInverseAndDetWithCheck( ResultType& inverse, typename ResultType::Scalar& determinant, bool& invertible, const RealScalar& absDeterminantThreshold ) const { // i'd love to put some static assertions there, but SFINAE means that they have no effect... ei_assert(rows() == cols()); // for 2x2, it's worth giving a chance to avoid evaluating. // for larger sizes, evaluating has negligible cost and limits code size. typedef typename ei_meta_if< RowsAtCompileTime == 2, typename ei_cleantype::type>::type, PlainMatrixType >::ret MatrixType; ei_compute_inverse_and_det_with_check::run (derived(), absDeterminantThreshold, inverse, determinant, invertible); } #endif // EIGEN_INVERSE_H