{eigen_internal_assert(index >=0&& index <size());derived().templatewritePacket<StoreMode>(index, other.derived().templatepacket<LoadMode>(index)); } writePacket()和packet()是什么。 首先,这里的writePacket()是左侧VectorXf的一个方法。他的定义在src/Core/Matrix.h中: template<intStoreMode>inli...
eigen_internal_assert(index >= 0 && index < size()); derived().template writePacket<StoreMode>(index, other.derived().template packet<LoadMode>(index)); } \endcode OK, what are writePacket() and packet() here? First, writePacket() here is a method on the left-hand side V...
assert((int)J.minCoeff() >=0); assert(I.size() == J.size()); assert(J.size() == V.size());// Really we just need .size() to be the same, but this is saferassert(I.rows() == J.rows()); assert(J.rows() == V.rows()); assert(I.cols() == J.cols()); assert...
assert( M.size() == I0.size() ); assert( M.size() == I0.size() );constunsignednbodies{static_cast<unsigned>( I0.size() ) };constunsignednvdofs{6* nbodies }; SparseMatrixsc Mbody{static_cast<SparseMatrixsc::Index>( nvdofs ),static_cast<SparseMatrixsc::Index>( nvdofs ) };...
EIGEN_NO_STATIC_ASSERT如果定义了,编译时静态断言将被运行时断言替换;这节省了编译时间。默认情况下未定义。 EIGEN_ASSERT这是一个带有一个参数的宏,用于在Eigen中进行断言。默认情况下,它基本上被定义为assert,如果断言被违反,则会终止程序。如果希望执行其他操作(如引发异常),请重新定义此宏。
int a=2;Eigen::Tensor<int,3>t(a,a,3);t.setConstant(2);cout<<t<<endl<<endl;constEigen::Tensor<int,1>::Dimensionsd(2);Eigen::array<Eigen::Index,3>offsets={0,0,0};Eigen::array<Eigen::Index,3>extents={2,2,2};t.slice(offsets,extents).setZero();cout<<t;-->2222222222220020...
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size( yi, 2 ) 转译为 yi.cols() 3.随机矩阵生成 Matlab : M= rand( 1, nPointsRand )-0.5; //生成从0到1的nPointsRand个随机数,再减去0.5即:(-0.5,.0.5) 翻译为Eigen: X= Eigen::MatrixXf::Random(1,nPointsRand) //默认生成 1行 nPointsRand列,率属于(-0.5,.0.5)的随机数 ...
using Base::size;^ /usr/include/eigen3/Eigen/src/Core/DenseBase.h:85:17: error: using-declarationfornon-member at class scope using Base::rowIndexByOuterInner;^ /usr/include/eigen3/Eigen/src/Core/DenseBase.h:86:17: error: using-declarationfornon-member at class scope ...
coeffs, double x); Eigen::VectorXd polyfit(Eigen::VectorXd xvals, Eigen...MPCNode::polyeval(Eigen::VectorXd coeffs, double x) { double result = 0.0; for (int i = 0;...::VectorXd MPCNode::polyfit(Eigen::VectorXd xvals, Eigen::VectorXd yvals, int order) { assert(xvals.s...