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https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
Merged in lukier/eigen (pull request PR-234)
Enabling CUDA in Geometry
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@@ -554,7 +554,7 @@ struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
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for(Index inner = alignedEnd; inner<innerSize ; ++inner)
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kernel.assignCoeffByOuterInner(outer, inner);
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alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
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alignedStart = numext::mini((alignedStart+alignedStep)%packetSize, innerSize);
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}
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}
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};
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@@ -752,7 +752,7 @@ struct setIdentity_impl<Derived, true>
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static EIGEN_STRONG_INLINE Derived& run(Derived& m)
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{
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m.setZero();
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const Index size = (std::min)(m.rows(), m.cols());
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const Index size = numext::mini(m.rows(), m.cols());
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for(Index i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
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return m;
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}
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@@ -290,12 +290,11 @@ MatrixBase<Derived>::asDiagonal() const
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template<typename Derived>
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bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
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{
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using std::abs;
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if(cols() != rows()) return false;
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RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
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for(Index j = 0; j < cols(); ++j)
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{
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RealScalar absOnDiagonal = abs(coeff(j,j));
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RealScalar absOnDiagonal = numext::abs(coeff(j,j));
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if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
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}
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for(Index j = 0; j < cols(); ++j)
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@@ -399,12 +399,14 @@ template<typename Derived> class MatrixBase
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EIGEN_DEVICE_FUNC
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inline PlainObject unitOrthogonal(void) const;
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EIGEN_DEVICE_FUNC
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inline Matrix<Scalar,3,1> eulerAngles(Index a0, Index a1, Index a2) const;
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// put this as separate enum value to work around possible GCC 4.3 bug (?)
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enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1&&RowsAtCompileTime==1 ? ((internal::traits<Derived>::Flags&RowMajorBit)==RowMajorBit ? Horizontal : Vertical)
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: ColsAtCompileTime==1 ? Vertical : Horizontal };
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typedef Homogeneous<Derived, HomogeneousReturnTypeDirection> HomogeneousReturnType;
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EIGEN_DEVICE_FUNC
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inline HomogeneousReturnType homogeneous() const;
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enum {
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@@ -414,7 +416,7 @@ template<typename Derived> class MatrixBase
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internal::traits<Derived>::ColsAtCompileTime==1 ? SizeMinusOne : 1,
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internal::traits<Derived>::ColsAtCompileTime==1 ? 1 : SizeMinusOne> ConstStartMinusOne;
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typedef EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(ConstStartMinusOne,Scalar,quotient) HNormalizedReturnType;
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EIGEN_DEVICE_FUNC
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inline const HNormalizedReturnType hnormalized() const;
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////////// Householder module ///////////
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@@ -916,8 +916,8 @@ struct conservative_resize_like_impl
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{
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// The storage order does not allow us to use reallocation.
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typename Derived::PlainObject tmp(rows,cols);
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const Index common_rows = (std::min)(rows, _this.rows());
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const Index common_cols = (std::min)(cols, _this.cols());
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const Index common_rows = numext::mini(rows, _this.rows());
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const Index common_cols = numext::mini(cols, _this.cols());
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tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
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_this.derived().swap(tmp);
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}
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@@ -950,8 +950,8 @@ struct conservative_resize_like_impl
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{
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// The storage order does not allow us to use reallocation.
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typename Derived::PlainObject tmp(other);
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const Index common_rows = (std::min)(tmp.rows(), _this.rows());
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const Index common_cols = (std::min)(tmp.cols(), _this.cols());
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const Index common_rows = numext::mini(tmp.rows(), _this.rows());
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const Index common_cols = numext::mini(tmp.cols(), _this.cols());
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tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
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_this.derived().swap(tmp);
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}
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@@ -641,21 +641,20 @@ MatrixBase<Derived>::triangularView() const
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template<typename Derived>
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bool MatrixBase<Derived>::isUpperTriangular(const RealScalar& prec) const
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{
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using std::abs;
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RealScalar maxAbsOnUpperPart = static_cast<RealScalar>(-1);
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for(Index j = 0; j < cols(); ++j)
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{
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Index maxi = (std::min)(j, rows()-1);
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Index maxi = numext::mini(j, rows()-1);
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for(Index i = 0; i <= maxi; ++i)
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{
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RealScalar absValue = abs(coeff(i,j));
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RealScalar absValue = numext::abs(coeff(i,j));
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if(absValue > maxAbsOnUpperPart) maxAbsOnUpperPart = absValue;
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}
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}
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RealScalar threshold = maxAbsOnUpperPart * prec;
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for(Index j = 0; j < cols(); ++j)
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for(Index i = j+1; i < rows(); ++i)
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if(abs(coeff(i, j)) > threshold) return false;
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if(numext::abs(coeff(i, j)) > threshold) return false;
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return true;
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}
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@@ -667,20 +666,19 @@ bool MatrixBase<Derived>::isUpperTriangular(const RealScalar& prec) const
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template<typename Derived>
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bool MatrixBase<Derived>::isLowerTriangular(const RealScalar& prec) const
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{
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using std::abs;
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RealScalar maxAbsOnLowerPart = static_cast<RealScalar>(-1);
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for(Index j = 0; j < cols(); ++j)
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for(Index i = j; i < rows(); ++i)
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{
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RealScalar absValue = abs(coeff(i,j));
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RealScalar absValue = numext::abs(coeff(i,j));
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if(absValue > maxAbsOnLowerPart) maxAbsOnLowerPart = absValue;
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}
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RealScalar threshold = maxAbsOnLowerPart * prec;
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for(Index j = 1; j < cols(); ++j)
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{
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Index maxi = (std::min)(j, rows()-1);
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Index maxi = numext::mini(j, rows()-1);
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for(Index i = 0; i < maxi; ++i)
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if(abs(coeff(i, j)) > threshold) return false;
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if(numext::abs(coeff(i, j)) > threshold) return false;
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}
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return true;
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}
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@@ -893,7 +891,7 @@ struct triangular_assignment_loop<Kernel, Mode, Dynamic, SetOpposite>
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{
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for(Index j = 0; j < kernel.cols(); ++j)
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{
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Index maxi = (std::min)(j, kernel.rows());
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Index maxi = numext::mini(j, kernel.rows());
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Index i = 0;
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if (((Mode&Lower) && SetOpposite) || (Mode&Upper))
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{
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@@ -625,6 +625,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
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/////////// Geometry module ///////////
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typedef Homogeneous<ExpressionType,Direction> HomogeneousReturnType;
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EIGEN_DEVICE_FUNC
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HomogeneousReturnType homogeneous() const;
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typedef typename ExpressionType::PlainObject CrossReturnType;
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@@ -654,6 +655,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
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Direction==Horizontal ? HNormalized_SizeMinusOne : 1> >
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HNormalizedReturnType;
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EIGEN_DEVICE_FUNC
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const HNormalizedReturnType hnormalized() const;
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protected:
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@@ -266,7 +266,7 @@ struct scalar_hypot_op<Scalar,Scalar> : binary_op_base<Scalar,Scalar>
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// typedef typename NumTraits<Scalar>::Real result_type;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
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{
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using std::sqrt;
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EIGEN_USING_STD_MATH(sqrt)
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Scalar p, qp;
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if(_x>_y)
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{
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@@ -321,7 +321,7 @@ struct functor_traits<scalar_log1p_op<Scalar> > {
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*/
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template<typename Scalar> struct scalar_log10_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_log10_op)
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EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::log10; return log10(a); }
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EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { EIGEN_USING_STD_MATH(log10) return log10(a); }
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template <typename Packet>
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EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog10(a); }
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};
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