eigen

问题 I was wondering if there is a more efficient way to remove columns or rows that are all zero elements. I am sure there is using the functions in the eigen library but I do not know how. Right now I am doing it like so, with the idea of the while loop being used in case there are multiple rows/columns that sum to zero I dont want to exceed range limits or pass any zero rows. void removeZeroRows() { int16_t index = 0; int16_t num_rows = rows(); while (index < num_rows) { double sum = row(index)

问题 I have the following problem: I have an Eigen::SparseMatrix I need to send over the network, and my network library only supports sending arrays of primitive types. I can retrieve the pointers to the backing arrays of my SparseMatrix by doing something like (here's the backing object's code): // Get pointers to the indices and values, send data over the network int num_items = sparse_matrix.nonZeros() auto values_ptr = sparse_matrix.data().valuePtr() auto index_ptr = sparse_matrix.data()

问题 I am really new with C++ but here is what I am trying to do. I have a 4 by 3 matrix: 100 109.523 119.096 100 89.7169 76.256 100 96.0822 103.246 100 101.084 85.0639 I want to take calculate the mean of each row and store it in some vector. I am using the Eigen library. I cannot think of anything to do this efficiently. Here is my code thus far: MatrixXd SS(N,n+1); MatrixXd Z = generateGaussianNoise(N,n); for(int i = 0; i < N; i++){ SS(i,0) = S0; for(int j = 1; j <= n; j++){ SS(i,j) = SS(i,j-1)

问题 I can't quite figure out the syntax for this when using Eigen's rowwise operations... I have an Eigen matrix, and I want to divide each row by the last row. So if we started with a matrix r = [ 0, 1 2, 3 4, 5 ] then after this transform, I want to have r = [ 0, .2 .5, .6 1, 1 ] Preferably the operation would happen in place, overwriting r . Furthermore, I will not be using the values in the last row, so it doesn't matter if the last row is actually 1's after the transform. Here are some

问题 What happens When I try to add an Eigen::Vector3f into an std::vector following the tutorial on Eigen website like this: #include <Eigen/Core> #include <Eigen/StdVector> #include <iostream> template <class EigenT> using EigenStdVector = std::vector<EigenT, Eigen::aligned_allocator<EigenT>>; int main() { EigenStdVector<Eigen::Vector3f> vec; vec.emplace_back(1.0f, 1.0f, 1.0f); std::cerr << vec.back().transpose() << std::endl; return 0; } I get the following warning: In file included from /usr

问题 Eigen::Matrix has a setRandom() method which will set all coefficients of the matrix to random values. However, is there a built in way to set all the matrix coefficients to random values while specifying the distribution to use. Is there a way to achieve something like the following: Eigen::Matrix3f myMatrix; std::tr1::mt19937 gen; std::tr1::uniform_int<int> dist(0,MT_MAX); myMatrix.setRandom(dist(gen)); 回答1: You can do what you want using Boost and unaryExpr. The function you pass to

问题 3 simple questions about the usage and future of the excellent eigen library: Does it have a reason why the access to Matrices is not possible via matrix[i][j] , but only via matrix(i,j) ? Are there plans to implement such a syntax? Will there be an implementation of multidimensional arrays matrix[n][m]...[l] ? I really like the eigen library, it is fast and easy to use. The only thing missing for me are really multidimensional arrays. 回答1: I can't speak for the eigen library because I've

问题 I wonder is there any good way to extract blocks/ROIs from Eigen::SparseMatrix? More precisely, what I want to extract is inner vectors . What I want to do is like: typedef Eigen::SparseMatrix<double,Eigen::RowMajor> SpMat; // Prepare some sparse matrix SpMat spmat; // Extract lines from it const SpMat& row_i = spmat.innerVector(i); const SpMat& row_j = spmat.innerVector(j); // Some calculation with row_i and row_j... As I tested, the data of row_i and row_j is copied (!!) from spmat .

问题 This question was asked in haste. The error in my original program, was not the typo in the code that is displayed here. The error was that in my program v was not getting populated due to some conditions. The more useful takeaway from this thread is the demonstration of copying a std::vector to all rows or columns of an Eigen Matrix, in the accepted answer. I want to copy vectors into the columns of a matrix, like the following: #include <Eigen/Dense> #include <vector> #include <iostream>

问题 How to extract a block from a Eigen::SparseMatrix<double> . It seems there aren't the methods I used for the dense ones. ‘class Eigen::SparseMatrix<double>’ has no member named ‘topLeftCorner’ ‘class Eigen::SparseMatrix<double>’ has no member named ‘block’ There is a way to extract a block as a Eigen::SparseMatrix<double> ? 回答1: I made this function to extract blocks from a Eigen::SparseMatrix<double,ColMaior> typedef Triplet<double> Tri; SparseMatrix<double> sparseBlock(SparseMatrix<double