如果想进行矩阵的element-wise计算,可以把矩阵当作array来计算,通过调用array()方法 // Square each element of the matrix cout << M1 . array () . square () << endl ; // Multiply two matrices element - wise cout << M1 . array () * Matrix4f :: Identity () . array () << endl ; /...
(6.45) that any eigenvector {z¯} could be multiplied by any overall factor and still satisfy the equations, so only the relative sizes of the elements can be found. There are two standard methods for normalizing the size of eigenvectors: (a) The element having the largest absolute value...
以及为了防止重复实现,使用了CRTP这种设计模式。不过这种优化仅限于element-wise的操作,矩阵乘法就不行了。所以eigen对于乘法做了2件事,第一是把常见的乘法操作提取出来,提取为: 单独进行优化。然后因为矩阵乘法需要得到中间变量,所以为了更好的利用expression template,eigen用tree optimizer把矩阵乘法运算往后移。tree op...
Eigen内置Single-Instruction-Multiple-Data(SIMD)指令集，对稠密矩阵有很好的优化，如果能触发CPU SIMD的...
In order to exploit effectively the power of array and vector processors for the numerical solution of linear algebraic problems it is desirable to express algorithms principally in terms of vector and matrix operations. Algorithms which manipulate vectors and matrices at component level are best ...
(IV,IF); Eigen::MatrixXd FN,VN,EN; Eigen::MatrixXi E; Eigen::VectorXi EMAP; WindingNumberAABB< Eigen::Vector3d, Eigen::MatrixXd, Eigen::MatrixXi > hier; switch(sign_type) { default: assert(false && "Unknown SignedDistanceType"); case SIGNED_DISTANCE_TYPE_UNSIGNED: // do nothing ...
template<typenamePointT,typenameScalar>inlinevoidpcl::computeNDCentroid (constpcl::PointCloud<PointT> &cloud,conststd::vector<int> &indices, Eigen::Matrix<Scalar, Eigen::Dynamic,1> ¢roid) {typedeftypenamepcl::traits::fieldList<PointT>::type FieldList;// Get the size of the fieldscentroid...
如果想进行矩阵的element-wise计算,可以把矩阵当作array来计算,通过调用array()方法 代码语言:javascript 复制 // Square each element of the matrixcout<<M1.array().square()<<endl;// Multiply two matrices element - wisecout<<M1.array()*Matrix4f::Identity().array()<<endl;// All relational operato...
The probability distribution of the result can be computed directly as \begin{equation*} P=\psi_f\,\psi_f^* \end{equation*} where $\psi_f\,\psi_f^*$ is the Hadamard (element-wise) product of vector $\psi_f$ and its complex conjugate. Result $P$ is a vector such that ...
Vector i+1 element x(i) x(i) last element x(end) x.tail(1) x(-1) 1 to i elements x(seq(i)) i+1 to END elements x(seq(i, end)) i1+1 to i2+1 elements x(seq(i1, i2)) i1+1 to i2+1 elements by step x(seq(i1, i2, step)) Matrix i+1 element R...