diff options
43 files changed, 158 insertions, 158 deletions
diff --git a/Eigen/src/Cholesky/LDLT.h b/Eigen/src/Cholesky/LDLT.h index d0f292634..de17f830c 100644 --- a/Eigen/src/Cholesky/LDLT.h +++ b/Eigen/src/Cholesky/LDLT.h @@ -194,7 +194,7 @@ LDLT<MatrixType>& LDLT<MatrixType>::compute(const MatrixType& a) { // Find largest diagonal element int index_of_biggest_in_corner; - biggest_in_corner = m_matrix.diagonal().end(size-j).cwise().abs() + biggest_in_corner = m_matrix.diagonal().tail(size-j).cwise().abs() .maxCoeff(&index_of_biggest_in_corner); index_of_biggest_in_corner += j; @@ -227,12 +227,12 @@ LDLT<MatrixType>& LDLT<MatrixType>::compute(const MatrixType& a) if (j == 0) { m_matrix.row(0) = m_matrix.row(0).conjugate(); - m_matrix.col(0).end(size-1) = m_matrix.row(0).end(size-1) / m_matrix.coeff(0,0); + m_matrix.col(0).tail(size-1) = m_matrix.row(0).tail(size-1) / m_matrix.coeff(0,0); continue; } - RealScalar Djj = ei_real(m_matrix.coeff(j,j) - m_matrix.row(j).start(j) - .dot(m_matrix.col(j).start(j))); + RealScalar Djj = ei_real(m_matrix.coeff(j,j) - m_matrix.row(j).head(j) + .dot(m_matrix.col(j).head(j))); m_matrix.coeffRef(j,j) = Djj; // Finish early if the matrix is not full rank. @@ -244,13 +244,13 @@ LDLT<MatrixType>& LDLT<MatrixType>::compute(const MatrixType& a) int endSize = size - j - 1; if (endSize > 0) { - _temporary.end(endSize).noalias() = m_matrix.block(j+1,0, endSize, j) - * m_matrix.col(j).start(j).conjugate(); + _temporary.tail(endSize).noalias() = m_matrix.block(j+1,0, endSize, j) + * m_matrix.col(j).head(j).conjugate(); - m_matrix.row(j).end(endSize) = m_matrix.row(j).end(endSize).conjugate() - - _temporary.end(endSize).transpose(); + m_matrix.row(j).tail(endSize) = m_matrix.row(j).tail(endSize).conjugate() + - _temporary.tail(endSize).transpose(); - m_matrix.col(j).end(endSize) = m_matrix.row(j).end(endSize) / Djj; + m_matrix.col(j).tail(endSize) = m_matrix.row(j).tail(endSize) / Djj; } } diff --git a/Eigen/src/Cholesky/LLT.h b/Eigen/src/Cholesky/LLT.h index ad737aaeb..02645b23f 100644 --- a/Eigen/src/Cholesky/LLT.h +++ b/Eigen/src/Cholesky/LLT.h @@ -166,7 +166,7 @@ template<> struct ei_llt_inplace<LowerTriangular> Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k); RealScalar x = ei_real(mat.coeff(k,k)); - if (k>0) x -= mat.row(k).start(k).squaredNorm(); + if (k>0) x -= mat.row(k).head(k).squaredNorm(); if (x<=RealScalar(0)) return false; mat.coeffRef(k,k) = x = ei_sqrt(x); diff --git a/Eigen/src/Core/MatrixBase.h b/Eigen/src/Core/MatrixBase.h index 593108522..467172777 100644 --- a/Eigen/src/Core/MatrixBase.h +++ b/Eigen/src/Core/MatrixBase.h @@ -459,11 +459,11 @@ template<typename Derived> class MatrixBase VectorBlock<Derived> segment(int start, int size); const VectorBlock<Derived> segment(int start, int size) const; - VectorBlock<Derived> start(int size); - const VectorBlock<Derived> start(int size) const; + VectorBlock<Derived> head(int size); + const VectorBlock<Derived> head(int size) const; - VectorBlock<Derived> end(int size); - const VectorBlock<Derived> end(int size) const; + VectorBlock<Derived> tail(int size); + const VectorBlock<Derived> tail(int size) const; typename BlockReturnType<Derived>::Type corner(CornerType type, int cRows, int cCols); const typename BlockReturnType<Derived>::Type corner(CornerType type, int cRows, int cCols) const; @@ -478,11 +478,11 @@ template<typename Derived> class MatrixBase template<int CRows, int CCols> const typename BlockReturnType<Derived, CRows, CCols>::Type corner(CornerType type) const; - template<int Size> VectorBlock<Derived,Size> start(void); - template<int Size> const VectorBlock<Derived,Size> start() const; + template<int Size> VectorBlock<Derived,Size> head(void); + template<int Size> const VectorBlock<Derived,Size> head() const; - template<int Size> VectorBlock<Derived,Size> end(); - template<int Size> const VectorBlock<Derived,Size> end() const; + template<int Size> VectorBlock<Derived,Size> tail(); + template<int Size> const VectorBlock<Derived,Size> tail() const; template<int Size> VectorBlock<Derived,Size> segment(int start); template<int Size> const VectorBlock<Derived,Size> segment(int start) const; diff --git a/Eigen/src/Core/StableNorm.h b/Eigen/src/Core/StableNorm.h index fa1e095ca..3ebd7282b 100644 --- a/Eigen/src/Core/StableNorm.h +++ b/Eigen/src/Core/StableNorm.h @@ -67,7 +67,7 @@ MatrixBase<Derived>::stableNorm() const { bi = ei_first_aligned(&const_cast_derived().coeffRef(0), n); if (bi>0) - ei_stable_norm_kernel(start(bi), ssq, scale, invScale); + ei_stable_norm_kernel(head(bi), ssq, scale, invScale); } for (; bi<n; bi+=blockSize) ei_stable_norm_kernel(VectorBlock<Derived,Dynamic,Alignment>(derived(),bi,std::min(blockSize, n - bi)), ssq, scale, invScale); diff --git a/Eigen/src/Core/VectorBlock.h b/Eigen/src/Core/VectorBlock.h index 65268b626..15b3a2aa5 100644 --- a/Eigen/src/Core/VectorBlock.h +++ b/Eigen/src/Core/VectorBlock.h @@ -161,16 +161,16 @@ MatrixBase<Derived>::segment(int start, int size) const */ template<typename Derived> inline VectorBlock<Derived> -MatrixBase<Derived>::start(int size) +MatrixBase<Derived>::head(int size) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return VectorBlock<Derived>(derived(), 0, size); } -/** This is the const version of start(int).*/ +/** This is the const version of head(int).*/ template<typename Derived> inline const VectorBlock<Derived> -MatrixBase<Derived>::start(int size) const +MatrixBase<Derived>::head(int size) const { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return VectorBlock<Derived>(derived(), 0, size); @@ -193,16 +193,16 @@ MatrixBase<Derived>::start(int size) const */ template<typename Derived> inline VectorBlock<Derived> -MatrixBase<Derived>::end(int size) +MatrixBase<Derived>::tail(int size) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return VectorBlock<Derived>(derived(), this->size() - size, size); } -/** This is the const version of end(int).*/ +/** This is the const version of tail(int).*/ template<typename Derived> inline const VectorBlock<Derived> -MatrixBase<Derived>::end(int size) const +MatrixBase<Derived>::tail(int size) const { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return VectorBlock<Derived>(derived(), this->size() - size, size); @@ -254,17 +254,17 @@ MatrixBase<Derived>::segment(int start) const template<typename Derived> template<int Size> inline VectorBlock<Derived,Size> -MatrixBase<Derived>::start() +MatrixBase<Derived>::head() { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return VectorBlock<Derived,Size>(derived(), 0); } -/** This is the const version of start<int>().*/ +/** This is the const version of head<int>().*/ template<typename Derived> template<int Size> inline const VectorBlock<Derived,Size> -MatrixBase<Derived>::start() const +MatrixBase<Derived>::head() const { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return VectorBlock<Derived,Size>(derived(), 0); @@ -284,17 +284,17 @@ MatrixBase<Derived>::start() const template<typename Derived> template<int Size> inline VectorBlock<Derived,Size> -MatrixBase<Derived>::end() +MatrixBase<Derived>::tail() { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return VectorBlock<Derived, Size>(derived(), size() - Size); } -/** This is the const version of end<int>.*/ +/** This is the const version of tail<int>.*/ template<typename Derived> template<int Size> inline const VectorBlock<Derived,Size> -MatrixBase<Derived>::end() const +MatrixBase<Derived>::tail() const { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return VectorBlock<Derived, Size>(derived(), size() - Size); diff --git a/Eigen/src/Core/products/SelfadjointRank2Update.h b/Eigen/src/Core/products/SelfadjointRank2Update.h index 69cf1896c..1c0e503e6 100644 --- a/Eigen/src/Core/products/SelfadjointRank2Update.h +++ b/Eigen/src/Core/products/SelfadjointRank2Update.h @@ -41,8 +41,8 @@ struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,LowerTriangular> for (int i=0; i<size; ++i) { Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i+i, size-i) += - (alpha * ei_conj(u.coeff(i))) * v.end(size-i) - + (alpha * ei_conj(v.coeff(i))) * u.end(size-i); + (alpha * ei_conj(u.coeff(i))) * v.tail(size-i) + + (alpha * ei_conj(v.coeff(i))) * u.tail(size-i); } } }; @@ -55,8 +55,8 @@ struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,UpperTriangular> const int size = u.size(); for (int i=0; i<size; ++i) Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i, i+1) += - (alpha * ei_conj(u.coeff(i))) * v.start(i+1) - + (alpha * ei_conj(v.coeff(i))) * u.start(i+1); + (alpha * ei_conj(u.coeff(i))) * v.head(i+1) + + (alpha * ei_conj(v.coeff(i))) * u.head(i+1); } }; diff --git a/Eigen/src/Eigenvalues/ComplexEigenSolver.h b/Eigen/src/Eigenvalues/ComplexEigenSolver.h index 86206ce79..40cbb50e6 100644 --- a/Eigen/src/Eigenvalues/ComplexEigenSolver.h +++ b/Eigen/src/Eigenvalues/ComplexEigenSolver.h @@ -133,7 +133,7 @@ void ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix) for (int i=0; i<n; i++) { int k; - m_eivalues.cwise().abs().end(n-i).minCoeff(&k); + m_eivalues.cwise().abs().tail(n-i).minCoeff(&k); if (k != 0) { k += i; diff --git a/Eigen/src/Eigenvalues/EigenSolver.h b/Eigen/src/Eigenvalues/EigenSolver.h index 73d240de0..f98e54712 100644 --- a/Eigen/src/Eigenvalues/EigenSolver.h +++ b/Eigen/src/Eigenvalues/EigenSolver.h @@ -620,7 +620,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) // Overflow control t = ei_abs(matH.coeff(i,n)); if ((eps * t) * t > 1) - matH.col(n).end(nn-i) /= t; + matH.col(n).tail(nn-i) /= t; } } } @@ -708,7 +708,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) // in this algo low==0 and high==nn-1 !! if (i < low || i > high) { - m_eivec.row(i).end(nn-i) = matH.row(i).end(nn-i); + m_eivec.row(i).tail(nn-i) = matH.row(i).tail(nn-i); } } diff --git a/Eigen/src/Eigenvalues/HessenbergDecomposition.h b/Eigen/src/Eigenvalues/HessenbergDecomposition.h index 49a2469be..636b2f4f7 100644 --- a/Eigen/src/Eigenvalues/HessenbergDecomposition.h +++ b/Eigen/src/Eigenvalues/HessenbergDecomposition.h @@ -150,7 +150,7 @@ void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVector int remainingSize = n-i-1; RealScalar beta; Scalar h; - matA.col(i).end(remainingSize).makeHouseholderInPlace(h, beta); + matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); matA.col(i).coeffRef(i+1) = beta; hCoeffs.coeffRef(i) = h; @@ -159,11 +159,11 @@ void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVector // A = H A matA.corner(BottomRight, remainingSize, remainingSize) - .applyHouseholderOnTheLeft(matA.col(i).end(remainingSize-1), h, &temp.coeffRef(0)); + .applyHouseholderOnTheLeft(matA.col(i).tail(remainingSize-1), h, &temp.coeffRef(0)); // A = A H' matA.corner(BottomRight, n, remainingSize) - .applyHouseholderOnTheRight(matA.col(i).end(remainingSize-1).conjugate(), ei_conj(h), &temp.coeffRef(0)); + .applyHouseholderOnTheRight(matA.col(i).tail(remainingSize-1).conjugate(), ei_conj(h), &temp.coeffRef(0)); } } @@ -178,7 +178,7 @@ HessenbergDecomposition<MatrixType>::matrixQ() const for (int i = n-2; i>=0; i--) { matQ.corner(BottomRight,n-i-1,n-i-1) - .applyHouseholderOnTheLeft(m_matrix.col(i).end(n-i-2), ei_conj(m_hCoeffs.coeff(i)), &temp.coeffRef(0,0)); + .applyHouseholderOnTheLeft(m_matrix.col(i).tail(n-i-2), ei_conj(m_hCoeffs.coeff(i)), &temp.coeffRef(0,0)); } return matQ; } diff --git a/Eigen/src/Eigenvalues/Tridiagonalization.h b/Eigen/src/Eigenvalues/Tridiagonalization.h index 58adb38e8..e43605b0f 100644 --- a/Eigen/src/Eigenvalues/Tridiagonalization.h +++ b/Eigen/src/Eigenvalues/Tridiagonalization.h @@ -202,19 +202,19 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& int remainingSize = n-i-1; RealScalar beta; Scalar h; - matA.col(i).end(remainingSize).makeHouseholderInPlace(h, beta); + matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); // Apply similarity transformation to remaining columns, - // i.e., A = H A H' where H = I - h v v' and v = matA.col(i).end(n-i-1) + // i.e., A = H A H' where H = I - h v v' and v = matA.col(i).tail(n-i-1) matA.col(i).coeffRef(i+1) = 1; - hCoeffs.end(n-i-1) = (matA.corner(BottomRight,remainingSize,remainingSize).template selfadjointView<LowerTriangular>() - * (ei_conj(h) * matA.col(i).end(remainingSize))); + hCoeffs.tail(n-i-1) = (matA.corner(BottomRight,remainingSize,remainingSize).template selfadjointView<LowerTriangular>() + * (ei_conj(h) * matA.col(i).tail(remainingSize))); - hCoeffs.end(n-i-1) += (ei_conj(h)*Scalar(-0.5)*(hCoeffs.end(remainingSize).dot(matA.col(i).end(remainingSize)))) * matA.col(i).end(n-i-1); + hCoeffs.tail(n-i-1) += (ei_conj(h)*Scalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); matA.corner(BottomRight, remainingSize, remainingSize).template selfadjointView<LowerTriangular>() - .rankUpdate(matA.col(i).end(remainingSize), hCoeffs.end(remainingSize), -1); + .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), -1); matA.col(i).coeffRef(i+1) = beta; hCoeffs.coeffRef(i) = h; @@ -242,7 +242,7 @@ void Tridiagonalization<MatrixType>::matrixQInPlace(MatrixBase<QDerived>* q) con for (int i = n-2; i>=0; i--) { matQ.corner(BottomRight,n-i-1,n-i-1) - .applyHouseholderOnTheLeft(m_matrix.col(i).end(n-i-2), ei_conj(m_hCoeffs.coeff(i)), &aux.coeffRef(0,0)); + .applyHouseholderOnTheLeft(m_matrix.col(i).tail(n-i-2), ei_conj(m_hCoeffs.coeff(i)), &aux.coeffRef(0,0)); } } diff --git a/Eigen/src/Geometry/OrthoMethods.h b/Eigen/src/Geometry/OrthoMethods.h index d16b72c43..0e890505b 100644 --- a/Eigen/src/Geometry/OrthoMethods.h +++ b/Eigen/src/Geometry/OrthoMethods.h @@ -173,7 +173,7 @@ struct ei_unitOrthogonal_selector<Derived,3> if((!ei_isMuchSmallerThan(src.x(), src.z())) || (!ei_isMuchSmallerThan(src.y(), src.z()))) { - RealScalar invnm = RealScalar(1)/src.template start<2>().norm(); + RealScalar invnm = RealScalar(1)/src.template head<2>().norm(); perp.coeffRef(0) = -ei_conj(src.y())*invnm; perp.coeffRef(1) = ei_conj(src.x())*invnm; perp.coeffRef(2) = 0; @@ -184,7 +184,7 @@ struct ei_unitOrthogonal_selector<Derived,3> */ else { - RealScalar invnm = RealScalar(1)/src.template end<2>().norm(); + RealScalar invnm = RealScalar(1)/src.template tail<2>().norm(); perp.coeffRef(0) = 0; perp.coeffRef(1) = -ei_conj(src.z())*invnm; perp.coeffRef(2) = ei_conj(src.y())*invnm; diff --git a/Eigen/src/Geometry/Quaternion.h b/Eigen/src/Geometry/Quaternion.h index 861eff19c..24772089e 100644 --- a/Eigen/src/Geometry/Quaternion.h +++ b/Eigen/src/Geometry/Quaternion.h @@ -77,10 +77,10 @@ public: inline Scalar& w() { return this->derived().coeffs().coeffRef(3); } /** \returns a read-only vector expression of the imaginary part (x,y,z) */ - inline const VectorBlock<Coefficients,3> vec() const { return coeffs().template start<3>(); } + inline const VectorBlock<Coefficients,3> vec() const { return coeffs().template head<3>(); } /** \returns a vector expression of the imaginary part (x,y,z) */ - inline VectorBlock<Coefficients,3> vec() { return coeffs().template start<3>(); } + inline VectorBlock<Coefficients,3> vec() { return coeffs().template head<3>(); } /** \returns a read-only vector expression of the coefficients (x,y,z,w) */ inline const typename ei_traits<Derived>::Coefficients& coeffs() const { return derived().coeffs(); } diff --git a/Eigen/src/Geometry/Transform.h b/Eigen/src/Geometry/Transform.h index 363fa9dc4..f91891d7b 100644 --- a/Eigen/src/Geometry/Transform.h +++ b/Eigen/src/Geometry/Transform.h @@ -1102,7 +1102,7 @@ struct ei_transform_right_product_impl<Other,AffineCompact, Dim,HDim, HDim,1> static ResultType run(const TransformType& tr, const Other& other) { ResultType res; - res.template start<HDim>() = tr.matrix() * other; + res.template head<HDim>() = tr.matrix() * other; res.coeffRef(Dim) = other.coeff(Dim); } }; @@ -1120,7 +1120,7 @@ struct ei_transform_right_product_impl<Other,Mode, Dim,HDim, Dim,Dim> res.matrix().col(Dim) = tr.matrix().col(Dim); res.linearExt() = (tr.linearExt() * other).lazy(); if(Mode==Affine) - res.matrix().row(Dim).template start<Dim>() = tr.matrix().row(Dim).template start<Dim>(); + res.matrix().row(Dim).template head<Dim>() = tr.matrix().row(Dim).template head<Dim>(); return res; } }; diff --git a/Eigen/src/Geometry/Umeyama.h b/Eigen/src/Geometry/Umeyama.h index 551a69e5b..5be098d77 100644 --- a/Eigen/src/Geometry/Umeyama.h +++ b/Eigen/src/Geometry/Umeyama.h @@ -170,8 +170,8 @@ umeyama(const MatrixBase<Derived>& src, const MatrixBase<OtherDerived>& dst, boo // Eq. (41) // Note that we first assign dst_mean to the destination so that there no need // for a temporary. - Rt.col(m).start(m) = dst_mean; - Rt.col(m).start(m).noalias() -= c*Rt.corner(TopLeft,m,m)*src_mean; + Rt.col(m).head(m) = dst_mean; + Rt.col(m).head(m).noalias() -= c*Rt.corner(TopLeft,m,m)*src_mean; if (with_scaling) Rt.block(0,0,m,m) *= c; diff --git a/Eigen/src/Householder/HouseholderSequence.h b/Eigen/src/Householder/HouseholderSequence.h index 25e962001..26e0f6a88 100644 --- a/Eigen/src/Householder/HouseholderSequence.h +++ b/Eigen/src/Householder/HouseholderSequence.h @@ -105,10 +105,10 @@ template<typename VectorsType, typename CoeffsType> class HouseholderSequence { if(m_trans) dst.corner(BottomRight, length-k, length-k) - .applyHouseholderOnTheRight(m_vectors.col(k).end(length-k-1), m_coeffs.coeff(k), &temp.coeffRef(0)); + .applyHouseholderOnTheRight(m_vectors.col(k).tail(length-k-1), m_coeffs.coeff(k), &temp.coeffRef(0)); else dst.corner(BottomRight, length-k, length-k) - .applyHouseholderOnTheLeft(m_vectors.col(k).end(length-k-1), m_coeffs.coeff(k), &temp.coeffRef(k)); + .applyHouseholderOnTheLeft(m_vectors.col(k).tail(length-k-1), m_coeffs.coeff(k), &temp.coeffRef(k)); } } @@ -122,7 +122,7 @@ template<typename VectorsType, typename CoeffsType> class HouseholderSequence { int actual_k = m_trans ? vecs-k-1 : k; dst.corner(BottomRight, dst.rows(), length-actual_k) - .applyHouseholderOnTheRight(m_vectors.col(actual_k).end(length-actual_k-1), m_coeffs.coeff(actual_k), &temp.coeffRef(0)); + .applyHouseholderOnTheRight(m_vectors.col(actual_k).tail(length-actual_k-1), m_coeffs.coeff(actual_k), &temp.coeffRef(0)); } } @@ -136,7 +136,7 @@ template<typename VectorsType, typename CoeffsType> class HouseholderSequence { int actual_k = m_trans ? k : vecs-k-1; dst.corner(BottomRight, length-actual_k, dst.cols()) - .applyHouseholderOnTheLeft(m_vectors.col(actual_k).end(length-actual_k-1), m_coeffs.coeff(actual_k), &temp.coeffRef(0)); + .applyHouseholderOnTheLeft(m_vectors.col(actual_k).tail(length-actual_k-1), m_coeffs.coeff(actual_k), &temp.coeffRef(0)); } } diff --git a/Eigen/src/LU/FullPivLU.h b/Eigen/src/LU/FullPivLU.h index 1358c9490..4dabe54d8 100644 --- a/Eigen/src/LU/FullPivLU.h +++ b/Eigen/src/LU/FullPivLU.h @@ -451,9 +451,9 @@ FullPivLU<MatrixType>& FullPivLU<MatrixType>::compute(const MatrixType& matrix) // bottom-right corner by Gaussian elimination. if(k<rows-1) - m_lu.col(k).end(rows-k-1) /= m_lu.coeff(k,k); + m_lu.col(k).tail(rows-k-1) /= m_lu.coeff(k,k); if(k<size-1) - m_lu.block(k+1,k+1,rows-k-1,cols-k-1).noalias() -= m_lu.col(k).end(rows-k-1) * m_lu.row(k).end(cols-k-1); + m_lu.block(k+1,k+1,rows-k-1,cols-k-1).noalias() -= m_lu.col(k).tail(rows-k-1) * m_lu.row(k).tail(cols-k-1); } // the main loop is over, we still have to accumulate the transpositions to find the @@ -537,8 +537,8 @@ struct ei_kernel_retval<FullPivLU<_MatrixType> > m(dec().matrixLU().block(0, 0, rank(), cols)); for(int i = 0; i < rank(); ++i) { - if(i) m.row(i).start(i).setZero(); - m.row(i).end(cols-i) = dec().matrixLU().row(pivots.coeff(i)).end(cols-i); + if(i) m.row(i).head(i).setZero(); + m.row(i).tail(cols-i) = dec().matrixLU().row(pivots.coeff(i)).tail(cols-i); } m.block(0, 0, rank(), rank()); m.block(0, 0, rank(), rank()).template triangularView<StrictlyLowerTriangular>().setZero(); @@ -558,7 +558,7 @@ struct ei_kernel_retval<FullPivLU<_MatrixType> > m.col(i).swap(m.col(pivots.coeff(i))); // see the negative sign in the next line, that's what we were talking about above. - for(int i = 0; i < rank(); ++i) dst.row(dec().permutationQ().indices().coeff(i)) = -m.row(i).end(dimker); + for(int i = 0; i < rank(); ++i) dst.row(dec().permutationQ().indices().coeff(i)) = -m.row(i).tail(dimker); for(int i = rank(); i < cols; ++i) dst.row(dec().permutationQ().indices().coeff(i)).setZero(); for(int k = 0; k < dimker; ++k) dst.coeffRef(dec().permutationQ().indices().coeff(rank()+k), k) = Scalar(1); } diff --git a/Eigen/src/LU/PartialPivLU.h b/Eigen/src/LU/PartialPivLU.h index 577daa345..e65b057ae 100644 --- a/Eigen/src/LU/PartialPivLU.h +++ b/Eigen/src/LU/PartialPivLU.h @@ -229,7 +229,7 @@ struct ei_partial_lu_impl { int row_of_biggest_in_col; RealScalar biggest_in_corner - = lu.col(k).end(rows-k).cwise().abs().maxCoeff(&row_of_biggest_in_col); + = lu.col(k).tail(rows-k).cwise().abs().maxCoeff(&row_of_biggest_in_col); row_of_biggest_in_col += k; if(biggest_in_corner == 0) // the pivot is exactly zero: the matrix is singular @@ -256,8 +256,8 @@ struct ei_partial_lu_impl { int rrows = rows-k-1; int rsize = size-k-1; - lu.col(k).end(rrows) /= lu.coeff(k,k); - lu.corner(BottomRight,rrows,rsize).noalias() -= lu.col(k).end(rrows) * lu.row(k).end(rsize); + lu.col(k).tail(rrows) /= lu.coeff(k,k); + lu.corner(BottomRight,rrows,rsize).noalias() -= lu.col(k).tail(rrows) * lu.row(k).tail(rsize); } } return true; diff --git a/Eigen/src/QR/ColPivHouseholderQR.h b/Eigen/src/QR/ColPivHouseholderQR.h index 1b2472a99..3e33fadbf 100644 --- a/Eigen/src/QR/ColPivHouseholderQR.h +++ b/Eigen/src/QR/ColPivHouseholderQR.h @@ -359,14 +359,14 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const { // first, we look up in our table colSqNorms which column has the biggest squared norm int biggest_col_index; - RealScalar biggest_col_sq_norm = colSqNorms.end(cols-k).maxCoeff(&biggest_col_index); + RealScalar biggest_col_sq_norm = colSqNorms.tail(cols-k).maxCoeff(&biggest_col_index); biggest_col_index += k; // since our table colSqNorms accumulates imprecision at every step, we must now recompute // the actual squared norm of the selected column. // Note that not doing so does result in solve() sometimes returning inf/nan values // when running the unit test with 1000 repetitions. - biggest_col_sq_norm = m_qr.col(biggest_col_index).end(rows-k).squaredNorm(); + biggest_col_sq_norm = m_qr.col(biggest_col_index).tail(rows-k).squaredNorm(); // we store that back into our table: it can't hurt to correct our table. colSqNorms.coeffRef(biggest_col_index) = biggest_col_sq_norm; @@ -379,7 +379,7 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const if(biggest_col_sq_norm < threshold_helper * (rows-k)) { m_nonzero_pivots = k; - m_hCoeffs.end(size-k).setZero(); + m_hCoeffs.tail(size-k).setZero(); m_qr.corner(BottomRight,rows-k,cols-k) .template triangularView<StrictlyLowerTriangular>() .setZero(); @@ -396,7 +396,7 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const // generate the householder vector, store it below the diagonal RealScalar beta; - m_qr.col(k).end(rows-k).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta); + m_qr.col(k).tail(rows-k).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta); // apply the householder transformation to the diagonal coefficient m_qr.coeffRef(k,k) = beta; @@ -406,10 +406,10 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const // apply the householder transformation m_qr.corner(BottomRight, rows-k, cols-k-1) - .applyHouseholderOnTheLeft(m_qr.col(k).end(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1)); + .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1)); // update our table of squared norms of the columns - colSqNorms.end(cols-k-1) -= m_qr.row(k).end(cols-k-1).cwise().abs2(); + colSqNorms.tail(cols-k-1) -= m_qr.row(k).tail(cols-k-1).cwise().abs2(); } m_cols_permutation.setIdentity(cols); diff --git a/Eigen/src/QR/FullPivHouseholderQR.h b/Eigen/src/QR/FullPivHouseholderQR.h index ae4e4aa4d..f32fb168f 100644 --- a/Eigen/src/QR/FullPivHouseholderQR.h +++ b/Eigen/src/QR/FullPivHouseholderQR.h @@ -306,7 +306,7 @@ FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(cons m_rows_transpositions.coeffRef(k) = row_of_biggest_in_corner; cols_transpositions.coeffRef(k) = col_of_biggest_in_corner; if(k != row_of_biggest_in_corner) { - m_qr.row(k).end(cols-k).swap(m_qr.row(row_of_biggest_in_corner).end(cols-k)); + m_qr.row(k).tail(cols-k).swap(m_qr.row(row_of_biggest_in_corner).tail(cols-k)); ++number_of_transpositions; } if(k != col_of_biggest_in_corner) { @@ -315,11 +315,11 @@ FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(cons } RealScalar beta; - m_qr.col(k).end(rows-k).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta); + m_qr.col(k).tail(rows-k).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta); m_qr.coeffRef(k,k) = beta; m_qr.corner(BottomRight, rows-k, cols-k-1) - .applyHouseholderOnTheLeft(m_qr.col(k).end(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1)); + .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1)); } m_cols_permutation.setIdentity(cols); @@ -360,7 +360,7 @@ struct ei_solve_retval<FullPivHouseholderQR<_MatrixType>, Rhs> int remainingSize = rows-k; c.row(k).swap(c.row(dec().rowsTranspositions().coeff(k))); c.corner(BottomRight, remainingSize, rhs().cols()) - .applyHouseholderOnTheLeft(dec().matrixQR().col(k).end(remainingSize-1), + .applyHouseholderOnTheLeft(dec().matrixQR().col(k).tail(remainingSize-1), dec().hCoeffs().coeff(k), &temp.coeffRef(0)); } @@ -400,7 +400,7 @@ typename FullPivHouseholderQR<MatrixType>::MatrixQType FullPivHouseholderQR<Matr for (int k = size-1; k >= 0; k--) { res.block(k, k, rows-k, rows-k) - .applyHouseholderOnTheLeft(m_qr.col(k).end(rows-k-1), ei_conj(m_hCoeffs.coeff(k)), &temp.coeffRef(k)); + .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), ei_conj(m_hCoeffs.coeff(k)), &temp.coeffRef(k)); res.row(k).swap(res.row(m_rows_transpositions.coeff(k))); } return res; diff --git a/Eigen/src/QR/HouseholderQR.h b/Eigen/src/QR/HouseholderQR.h index 95496b943..8add0dcd5 100644 --- a/Eigen/src/QR/HouseholderQR.h +++ b/Eigen/src/QR/HouseholderQR.h @@ -197,12 +197,12 @@ HouseholderQR<MatrixType>& HouseholderQR<MatrixType>::compute(const MatrixType& int remainingCols = cols - k - 1; RealScalar beta; - m_qr.col(k).end(remainingRows).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta); + m_qr.col(k).tail(remainingRows).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta); m_qr.coeffRef(k,k) = beta; // apply H to remaining part of m_qr from the left m_qr.corner(BottomRight, remainingRows, remainingCols) - .applyHouseholderOnTheLeft(m_qr.col(k).end(remainingRows-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1)); + .applyHouseholderOnTheLeft(m_qr.col(k).tail(remainingRows-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1)); } m_isInitialized = true; return *this; @@ -226,7 +226,7 @@ struct ei_solve_retval<HouseholderQR<_MatrixType>, Rhs> // Note that the matrix Q = H_0^* H_1^*... so its inverse is Q^* = (H_0 H_1 ...)^T c.applyOnTheLeft(householderSequence( dec().matrixQR().corner(TopLeft,rows,rank), - dec().hCoeffs().start(rank)).transpose() + dec().hCoeffs().head(rank)).transpose() ); dec().matrixQR() diff --git a/Eigen/src/SVD/JacobiSVD.h b/Eigen/src/SVD/JacobiSVD.h index 5792c5767..d2cd8e478 100644 --- a/Eigen/src/SVD/JacobiSVD.h +++ b/Eigen/src/SVD/JacobiSVD.h @@ -342,7 +342,7 @@ JacobiSVD<MatrixType, Options>& JacobiSVD<MatrixType, Options>::compute(const Ma for(int i = 0; i < diagSize; i++) { int pos; - m_singularValues.end(diagSize-i).maxCoeff(&pos); + m_singularValues.tail(diagSize-i).maxCoeff(&pos); if(pos) { pos += i; diff --git a/Eigen/src/SVD/SVD.h b/Eigen/src/SVD/SVD.h index 0ec41e36d..c1b14128c 100644 --- a/Eigen/src/SVD/SVD.h +++ b/Eigen/src/SVD/SVD.h @@ -205,7 +205,7 @@ SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix) g = s = scale = 0.0; if (i < m) { - scale = A.col(i).end(m-i).cwise().abs().sum(); + scale = A.col(i).tail(m-i).cwise().abs().sum(); if (scale != Scalar(0)) { for (k=i; k<m; k++) @@ -219,18 +219,18 @@ SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix) A(i, i)=f-g; for (j=l-1; j<n; j++) { - s = A.col(j).end(m-i).dot(A.col(i).end(m-i)); + s = A.col(j).tail(m-i).dot(A.col(i).tail(m-i)); f = s/h; - A.col(j).end(m-i) += f*A.col(i).end(m-i); + A.col(j).tail(m-i) += f*A.col(i).tail(m-i); } - A.col(i).end(m-i) *= scale; + A.col(i).tail(m-i) *= scale; } } W[i] = scale * g; g = s = scale = 0.0; if (i+1 <= m && i+1 != n) { - scale = A.row(i).end(n-l+1).cwise().abs().sum(); + scale = A.row(i).tail(n-l+1).cwise().abs().sum(); if (scale != Scalar(0)) { for (k=l-1; k<n; k++) @@ -242,13 +242,13 @@ SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix) g = -sign(ei_sqrt(s),f); h = f*g - s; A(i,l-1) = f-g; - rv1.end(n-l+1) = A.row(i).end(n-l+1)/h; + rv1.tail(n-l+1) = A.row(i).tail(n-l+1)/h; for (j=l-1; j<m; j++) { - s = A.row(i).end(n-l+1).dot(A.row(j).end(n-l+1)); - A.row(j).end(n-l+1) += s*rv1.end(n-l+1).transpose(); + s = A.row(i).tail(n-l+1).dot(A.row(j).tail(n-l+1)); + A.row(j).tail(n-l+1) += s*rv1.tail(n-l+1).transpose(); } - A.row(i).end(n-l+1) *= scale; + A.row(i).tail(n-l+1) *= scale; } } anorm = std::max( anorm, (ei_abs(W[i])+ei_abs(rv1[i])) ); @@ -265,12 +265,12 @@ SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix) V(j, i) = (A(i, j)/A(i, l))/g; for (j=l; j<n; j++) { - s = V.col(j).end(n-l).dot(A.row(i).end(n-l)); - V.col(j).end(n-l) += s * V.col(i).end(n-l); + s = V.col(j).tail(n-l).dot(A.row(i).tail(n-l)); + V.col(j).tail(n-l) += s * V.col(i).tail(n-l); } } - V.row(i).end(n-l).setZero(); - V.col(i).end(n-l).setZero(); + V.row(i).tail(n-l).setZero(); + V.col(i).tail(n-l).setZero(); } V(i, i) = 1.0; g = rv1[i]; @@ -282,7 +282,7 @@ SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix) l = i+1; g = W[i]; if (n-l>0) - A.row(i).end(n-l).setZero(); + A.row(i).tail(n-l).setZero(); if (g != Scalar(0.0)) { g = Scalar(1.0)/g; @@ -290,15 +290,15 @@ SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix) { for (j=l; j<n; j++) { - s = A.col(j).end(m-l).dot(A.col(i).end(m-l)); + s = A.col(j).tail(m-l).dot(A.col(i).tail(m-l)); f = (s/A(i,i))*g; - A.col(j).end(m-i) += f * A.col(i).end(m-i); + A.col(j).tail(m-i) += f * A.col(i).tail(m-i); } } - A.col(i).end(m-i) *= g; + A.col(i).tail(m-i) *= g; } else - A.col(i).end(m-i).setZero(); + A.col(i).tail(m-i).setZero(); ++A(i,i); } // Diagonalization of the bidiagonal form: Loop over @@ -408,7 +408,7 @@ SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix) for (int i=0; i<n; i++) { int k; - W.end(n-i).maxCoeff(&k); + W.tail(n-i).maxCoeff(&k); if (k != 0) { k += i; @@ -451,8 +451,8 @@ struct ei_solve_retval<SVD<_MatrixType>, Rhs> aux.coeffRef(i) /= si; } const int minsize = std::min(dec().rows(),dec().cols()); - dst.col(j).start(minsize) = aux.start(minsize); - if(dec().cols()>dec().rows()) dst.col(j).end(cols()-minsize).setZero(); + dst.col(j).head(minsize) = aux.head(minsize); + if(dec().cols()>dec().rows()) dst.col(j).tail(cols()-minsize).setZero(); dst.col(j) = dec().matrixV() * dst.col(j); } } diff --git a/bench/btl/libs/eigen2/eigen2_interface.hh b/bench/btl/libs/eigen2/eigen2_interface.hh index f14c8c383..1166a37a1 100644 --- a/bench/btl/libs/eigen2/eigen2_interface.hh +++ b/bench/btl/libs/eigen2/eigen2_interface.hh @@ -153,14 +153,14 @@ public : else dst.copyCoeff(index, j, src); } - //dst.col(j).end(N-j) = src.col(j).end(N-j); + //dst.col(j).tail(N-j) = src.col(j).tail(N-j); } } static EIGEN_DONT_INLINE void syr2(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){ // ei_product_selfadjoint_rank2_update<real,0,LowerTriangularBit>(N,A.data(),N, X.data(), 1, Y.data(), 1, -1); for(int j=0; j<N; ++j) - A.col(j).end(N-j) += X[j] * Y.end(N-j) + Y[j] * X.end(N-j); + A.col(j).tail(N-j) += X[j] * Y.tail(N-j) + Y[j] * X.tail(N-j); } static EIGEN_DONT_INLINE void ger(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){ diff --git a/disabled/Householder.h b/disabled/Householder.h index 874b812db..9b5f56360 100644 --- a/disabled/Householder.h +++ b/disabled/Householder.h @@ -16,8 +16,8 @@ void ei_compute_householder(const InputVector& x, OutputVector *v, typename Outp typedef typename OutputVector::RealScalar RealScalar; ei_assert(x.size() == v->size()+1); int n = x.size(); - RealScalar sigma = x.end(n-1).squaredNorm(); - *v = x.end(n-1); + RealScalar sigma = x.tail(n-1).squaredNorm(); + *v = x.tail(n-1); // the big assumption in this code is that ei_abs2(x->coeff(0)) is not much smaller than sigma. if(ei_isMuchSmallerThan(sigma, ei_abs2(x.coeff(0)))) { diff --git a/doc/AsciiQuickReference.txt b/doc/AsciiQuickReference.txt index 6c1c4fbd8..86f77a66b 100644 --- a/doc/AsciiQuickReference.txt +++ b/doc/AsciiQuickReference.txt @@ -41,8 +41,8 @@ A.setIdentity(); // Fill A with the identity. // Eigen // Matlab x.start(n) // x(1:n) x.start<n>() // x(1:n) -x.end(n) // N = rows(x); x(N - n: N) -x.end<n>() // N = rows(x); x(N - n: N) +x.tail(n) // N = rows(x); x(N - n: N) +x.tail<n>() // N = rows(x); x(N - n: N) x.segment(i, n) // x(i+1 : i+n) x.segment<n>(i) // x(i+1 : i+n) P.block(i, j, rows, cols) // P(i+1 : i+rows, j+1 : j+cols) diff --git a/doc/C01_QuickStartGuide.dox b/doc/C01_QuickStartGuide.dox index 7c4aa8f76..2240ed8b1 100644 --- a/doc/C01_QuickStartGuide.dox +++ b/doc/C01_QuickStartGuide.dox @@ -493,7 +493,7 @@ Read-write access to sub-vectors: <td></td> <tr><td>\code vec1.start(n)\endcode</td><td>\code vec1.start<n>()\endcode</td><td>the first \c n coeffs </td></tr> -<tr><td>\code vec1.end(n)\endcode</td><td>\code vec1.end<n>()\endcode</td><td>the last \c n coeffs </td></tr> +<tr><td>\code vec1.tail(n)\endcode</td><td>\code vec1.tail<n>()\endcode</td><td>the last \c n coeffs </td></tr> <tr><td>\code vec1.segment(pos,n)\endcode</td><td>\code vec1.segment<n>(pos)\endcode</td> <td>the \c size coeffs in \n the range [\c pos : \c pos + \c n [</td></tr> <tr style="border-style: dashed none dashed none;"><td> diff --git a/doc/echelon.cpp b/doc/echelon.cpp index 49b719ff2..c95be6f3b 100644 --- a/doc/echelon.cpp +++ b/doc/echelon.cpp @@ -27,8 +27,8 @@ struct unroll_echelon m.row(k).swap(m.row(k+rowOfBiggest)); m.col(k).swap(m.col(k+colOfBiggest)); m.template corner<CornerRows-1, CornerCols>(BottomRight) - -= m.col(k).template end<CornerRows-1>() - * (m.row(k).template end<CornerCols>() / m(k,k)); + -= m.col(k).template tail<CornerRows-1>() + * (m.row(k).template tail<CornerCols>() / m(k,k)); } }; @@ -59,7 +59,7 @@ struct unroll_echelon<Derived, Dynamic> m.row(k).swap(m.row(k+rowOfBiggest)); m.col(k).swap(m.col(k+colOfBiggest)); m.corner(BottomRight, cornerRows-1, cornerCols) - -= m.col(k).end(cornerRows-1) * (m.row(k).end(cornerCols) / m(k,k)); + -= m.col(k).tail(cornerRows-1) * (m.row(k).tail(cornerCols) / m(k,k)); } } }; diff --git a/doc/snippets/MatrixBase_end_int.cpp b/doc/snippets/MatrixBase_end_int.cpp index aaa54b668..03c54a931 100644 --- a/doc/snippets/MatrixBase_end_int.cpp +++ b/doc/snippets/MatrixBase_end_int.cpp @@ -1,5 +1,5 @@ RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; -cout << "Here is v.end(2):" << endl << v.end(2) << endl; -v.end(2).setZero(); +cout << "Here is v.tail(2):" << endl << v.tail(2) << endl; +v.tail(2).setZero(); cout << "Now the vector v is:" << endl << v << endl; diff --git a/doc/snippets/MatrixBase_start_int.cpp b/doc/snippets/MatrixBase_start_int.cpp index eb43a5dc7..c261d2b4e 100644 --- a/doc/snippets/MatrixBase_start_int.cpp +++ b/doc/snippets/MatrixBase_start_int.cpp @@ -1,5 +1,5 @@ RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; -cout << "Here is v.start(2):" << endl << v.start(2) << endl; -v.start(2).setZero(); +cout << "Here is v.head(2):" << endl << v.head(2) << endl; +v.head(2).setZero(); cout << "Now the vector v is:" << endl << v << endl; diff --git a/doc/snippets/MatrixBase_template_int_end.cpp b/doc/snippets/MatrixBase_template_int_end.cpp index 0908c0305..f5ccb00f6 100644 --- a/doc/snippets/MatrixBase_template_int_end.cpp +++ b/doc/snippets/MatrixBase_template_int_end.cpp @@ -1,5 +1,5 @@ RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; -cout << "Here is v.end(2):" << endl << v.end<2>() << endl; -v.end<2>().setZero(); +cout << "Here is v.tail(2):" << endl << v.tail<2>() << endl; +v.tail<2>().setZero(); cout << "Now the vector v is:" << endl << v << endl; diff --git a/doc/snippets/MatrixBase_template_int_start.cpp b/doc/snippets/MatrixBase_template_int_start.cpp index 231fc3299..d336b3716 100644 --- a/doc/snippets/MatrixBase_template_int_start.cpp +++ b/doc/snippets/MatrixBase_template_int_start.cpp @@ -1,5 +1,5 @@ RowVector4i v = RowVector4i::Random(); cout << "Here is the vector v:" << endl << v << endl; -cout << "Here is v.start(2):" << endl << v.start<2>() << endl; -v.start<2>().setZero(); +cout << "Here is v.head(2):" << endl << v.head<2>() << endl; +v.head<2>().setZero(); cout << "Now the vector v is:" << endl << v << endl; diff --git a/test/geo_homogeneous.cpp b/test/geo_homogeneous.cpp index 48d8cbcdf..781913553 100644 --- a/test/geo_homogeneous.cpp +++ b/test/geo_homogeneous.cpp @@ -67,7 +67,7 @@ template<typename Scalar,int Size> void homogeneous(void) VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized()); hm0.row(Size-1).setRandom(); for(int j=0; j<Size; ++j) - m0.col(j) = hm0.col(j).start(Size) / hm0(Size,j); + m0.col(j) = hm0.col(j).head(Size) / hm0(Size,j); VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized()); T1MatrixType t1 = T1MatrixType::Random(); diff --git a/test/geo_orthomethods.cpp b/test/geo_orthomethods.cpp index 54a6febab..9f1113559 100644 --- a/test/geo_orthomethods.cpp +++ b/test/geo_orthomethods.cpp @@ -66,7 +66,7 @@ template<typename Scalar> void orthomethods_3() v41 = Vector4::Random(), v42 = Vector4::Random(); v40.w() = v41.w() = v42.w() = 0; - v42.template start<3>() = v40.template start<3>().cross(v41.template start<3>()); + v42.template head<3>() = v40.template head<3>().cross(v41.template head<3>()); VERIFY_IS_APPROX(v40.cross3(v41), v42); } @@ -88,8 +88,8 @@ template<typename Scalar, int Size> void orthomethods(int size=Size) if (size>=3) { - v0.template start<2>().setZero(); - v0.end(size-2).setRandom(); + v0.template head<2>().setZero(); + v0.tail(size-2).setRandom(); VERIFY_IS_MUCH_SMALLER_THAN(v0.unitOrthogonal().dot(v0), Scalar(1)); VERIFY_IS_APPROX(v0.unitOrthogonal().norm(), RealScalar(1)); diff --git a/test/geo_transformations.cpp b/test/geo_transformations.cpp index 84b3c5355..3f368b141 100644 --- a/test/geo_transformations.cpp +++ b/test/geo_transformations.cpp @@ -118,7 +118,7 @@ template<typename Scalar, int Mode> void transformations(void) t0.scale(v0); t1.prescale(v0); - VERIFY_IS_APPROX( (t0 * Vector3(1,0,0)).template start<3>().norm(), v0.x()); + VERIFY_IS_APPROX( (t0 * Vector3(1,0,0)).template head<3>().norm(), v0.x()); //VERIFY(!ei_isApprox((t1 * Vector3(1,0,0)).norm(), v0.x())); t0.setIdentity(); @@ -290,12 +290,12 @@ template<typename Scalar, int Mode> void transformations(void) // translation * vector t0.setIdentity(); t0.translate(v0); - VERIFY_IS_APPROX((t0 * v1).template start<3>(), Translation3(v0) * v1); + VERIFY_IS_APPROX((t0 * v1).template head<3>(), Translation3(v0) * v1); // AlignedScaling * vector t0.setIdentity(); t0.scale(v0); - VERIFY_IS_APPROX((t0 * v1).template start<3>(), AlignedScaling3(v0) * v1); + VERIFY_IS_APPROX((t0 * v1).template head<3>(), AlignedScaling3(v0) * v1); // test transform inversion t0.setIdentity(); diff --git a/test/householder.cpp b/test/householder.cpp index 6e480c0de..4e4c78863 100644 --- a/test/householder.cpp +++ b/test/householder.cpp @@ -53,7 +53,7 @@ template<typename MatrixType> void householder(const MatrixType& m) v1.makeHouseholder(essential, beta, alpha); v1.applyHouseholderOnTheLeft(essential,beta,tmp); VERIFY_IS_APPROX(v1.norm(), v2.norm()); - VERIFY_IS_MUCH_SMALLER_THAN(v1.end(rows-1).norm(), v1.norm()); + VERIFY_IS_MUCH_SMALLER_THAN(v1.tail(rows-1).norm(), v1.norm()); v1 = VectorType::Random(rows); v2 = v1; v1.applyHouseholderOnTheLeft(essential,beta,tmp); @@ -63,7 +63,7 @@ template<typename MatrixType> void householder(const MatrixType& m) m2(rows, cols); v1 = VectorType::Random(rows); - if(even) v1.end(rows-1).setZero(); + if(even) v1.tail(rows-1).setZero(); m1.colwise() = v1; m2 = m1; m1.col(0).makeHouseholder(essential, beta, alpha); @@ -74,7 +74,7 @@ template<typename MatrixType> void householder(const MatrixType& m) VERIFY_IS_APPROX(ei_real(m1(0,0)), alpha); v1 = VectorType::Random(rows); - if(even) v1.end(rows-1).setZero(); + if(even) v1.tail(rows-1).setZero(); SquareMatrixType m3(rows,rows), m4(rows,rows); m3.rowwise() = v1.transpose(); m4 = m3; diff --git a/test/product_selfadjoint.cpp b/test/product_selfadjoint.cpp index 2e9f8be80..2f3833a02 100644 --- a/test/product_selfadjoint.cpp +++ b/test/product_selfadjoint.cpp @@ -68,9 +68,9 @@ template<typename MatrixType> void product_selfadjoint(const MatrixType& m) if (rows>1) { m2 = m1.template triangularView<LowerTriangular>(); - m2.block(1,1,rows-1,cols-1).template selfadjointView<LowerTriangular>().rankUpdate(v1.end(rows-1),v2.start(cols-1)); + m2.block(1,1,rows-1,cols-1).template selfadjointView<LowerTriangular>().rankUpdate(v1.tail(rows-1),v2.head(cols-1)); m3 = m1; - m3.block(1,1,rows-1,cols-1) += v1.end(rows-1) * v2.start(cols-1).adjoint()+ v2.start(cols-1) * v1.end(rows-1).adjoint(); + m3.block(1,1,rows-1,cols-1) += v1.tail(rows-1) * v2.head(cols-1).adjoint()+ v2.head(cols-1) * v1.tail(rows-1).adjoint(); VERIFY_IS_APPROX(m2, m3.template triangularView<LowerTriangular>().toDenseMatrix()); } } diff --git a/test/redux.cpp b/test/redux.cpp index c075c1393..3293fd54e 100644 --- a/test/redux.cpp +++ b/test/redux.cpp @@ -68,10 +68,10 @@ template<typename VectorType> void vectorRedux(const VectorType& w) minc = std::min(minc, ei_real(v[j])); maxc = std::max(maxc, ei_real(v[j])); } - VERIFY_IS_APPROX(s, v.start(i).sum()); - VERIFY_IS_APPROX(p, v.start(i).prod()); - VERIFY_IS_APPROX(minc, v.real().start(i).minCoeff()); - VERIFY_IS_APPROX(maxc, v.real().start(i).maxCoeff()); + VERIFY_IS_APPROX(s, v.head(i).sum()); + VERIFY_IS_APPROX(p, v.head(i).prod()); + VERIFY_IS_APPROX(minc, v.real().head(i).minCoeff()); + VERIFY_IS_APPROX(maxc, v.real().head(i).maxCoeff()); } for(int i = 0; i < size-1; i++) @@ -85,10 +85,10 @@ template<typename VectorType> void vectorRedux(const VectorType& w) minc = std::min(minc, ei_real(v[j])); maxc = std::max(maxc, ei_real(v[j])); } - VERIFY_IS_APPROX(s, v.end(size-i).sum()); - VERIFY_IS_APPROX(p, v.end(size-i).prod()); - VERIFY_IS_APPROX(minc, v.real().end(size-i).minCoeff()); - VERIFY_IS_APPROX(maxc, v.real().end(size-i).maxCoeff()); + VERIFY_IS_APPROX(s, v.tail(size-i).sum()); + VERIFY_IS_APPROX(p, v.tail(size-i).prod()); + VERIFY_IS_APPROX(minc, v.real().tail(size-i).minCoeff()); + VERIFY_IS_APPROX(maxc, v.real().tail(size-i).maxCoeff()); } for(int i = 0; i < size/2; i++) diff --git a/test/regression.cpp b/test/regression.cpp index 0e2323bf6..6fad26bad 100644 --- a/test/regression.cpp +++ b/test/regression.cpp @@ -51,7 +51,7 @@ void makeNoisyCohyperplanarPoints(int numPoints, { cur_point = VectorType::Random(size)/*.normalized()*/; // project cur_point onto the hyperplane - Scalar x = - (hyperplane->coeffs().start(size).cwise()*cur_point).sum(); + Scalar x = - (hyperplane->coeffs().head(size).cwise()*cur_point).sum(); cur_point *= hyperplane->coeffs().coeff(size) / x; } while( cur_point.norm() < 0.5 || cur_point.norm() > 2.0 ); diff --git a/test/submatrices.cpp b/test/submatrices.cpp index 75b0fde4b..9cd6f3fab 100644 --- a/test/submatrices.cpp +++ b/test/submatrices.cpp @@ -127,15 +127,15 @@ template<typename MatrixType> void submatrices(const MatrixType& m) if (rows>2) { // test sub vectors - VERIFY_IS_APPROX(v1.template start<2>(), v1.block(0,0,2,1)); - VERIFY_IS_APPROX(v1.template start<2>(), v1.start(2)); - VERIFY_IS_APPROX(v1.template start<2>(), v1.segment(0,2)); - VERIFY_IS_APPROX(v1.template start<2>(), v1.template segment<2>(0)); + VERIFY_IS_APPROX(v1.template head<2>(), v1.block(0,0,2,1)); + VERIFY_IS_APPROX(v1.template head<2>(), v1.head(2)); + VERIFY_IS_APPROX(v1.template head<2>(), v1.segment(0,2)); + VERIFY_IS_APPROX(v1.template head<2>(), v1.template segment<2>(0)); int i = rows-2; - VERIFY_IS_APPROX(v1.template end<2>(), v1.block(i,0,2,1)); - VERIFY_IS_APPROX(v1.template end<2>(), v1.end(2)); - VERIFY_IS_APPROX(v1.template end<2>(), v1.segment(i,2)); - VERIFY_IS_APPROX(v1.template end<2>(), v1.template segment<2>(i)); + VERIFY_IS_APPROX(v1.template tail<2>(), v1.block(i,0,2,1)); + VERIFY_IS_APPROX(v1.template tail<2>(), v1.tail(2)); + VERIFY_IS_APPROX(v1.template tail<2>(), v1.segment(i,2)); + VERIFY_IS_APPROX(v1.template tail<2>(), v1.template segment<2>(i)); i = ei_random(0,rows-2); VERIFY_IS_APPROX(v1.segment(i,2), v1.template segment<2>(i)); diff --git a/unsupported/Eigen/AlignedVector3 b/unsupported/Eigen/AlignedVector3 index a1510f19d..37018bfc6 100644 --- a/unsupported/Eigen/AlignedVector3 +++ b/unsupported/Eigen/AlignedVector3 @@ -106,7 +106,7 @@ template<typename _Scalar> class AlignedVector3 { inline static void run(AlignedVector3& dest, const XprType& src) { - dest.m_coeffs.template start<3>() = src; + dest.m_coeffs.template head<3>() = src; dest.m_coeffs.w() = Scalar(0); } }; @@ -190,7 +190,7 @@ template<typename _Scalar> class AlignedVector3 template<typename Derived> inline bool isApprox(const MatrixBase<Derived>& other, RealScalar eps=dummy_precision<Scalar>()) const { - return m_coeffs.template start<3>().isApprox(other,eps); + return m_coeffs.template head<3>().isApprox(other,eps); } }; diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h b/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h index eb7c71eed..c5acdc2c0 100644 --- a/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h +++ b/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h @@ -344,7 +344,7 @@ typename MatrixFunction<MatrixType,1>::DynMatrixType MatrixFunction<MatrixType,1 if (i == m - 1) { AX = 0; } else { - Matrix<Scalar,1,1> AXmatrix = A.row(i).end(m-1-i) * X.col(j).end(m-1-i); + Matrix<Scalar,1,1> AXmatrix = A.row(i).tail(m-1-i) * X.col(j).tail(m-1-i); AX = AXmatrix(0,0); } @@ -353,7 +353,7 @@ typename MatrixFunction<MatrixType,1>::DynMatrixType MatrixFunction<MatrixType,1 if (j == 0) { XB = 0; } else { - Matrix<Scalar,1,1> XBmatrix = X.row(i).start(j) * B.col(j).start(j); + Matrix<Scalar,1,1> XBmatrix = X.row(i).head(j) * B.col(j).head(j); XB = XBmatrix(0,0); } diff --git a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h index 2cf96eb14..dfc2672f3 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h +++ b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h @@ -533,7 +533,7 @@ LevenbergMarquardt<FunctorType,Scalar>::minimizeOptimumStorageOneStep( sing = true; } ipvt[j] = j; - wa2[j] = fjac.col(j).start(j).stableNorm(); + wa2[j] = fjac.col(j).head(j).stableNorm(); } if (sing) { ipvt.cwise()+=1; diff --git a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h index b723a7e0a..e5b66c0d7 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h +++ b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h @@ -87,7 +87,7 @@ void ei_lmpar( /* calculate an upper bound, paru, for the zero of the function. */ for (j = 0; j < n; ++j) - wa1[j] = r.col(j).start(j+1).dot(qtb.start(j+1)) / diag[ipvt[j]]; + wa1[j] = r.col(j).head(j+1).dot(qtb.head(j+1)) / diag[ipvt[j]]; gnorm = wa1.stableNorm(); paru = gnorm / delta; |