eigen

问题 I have an array of doubles, and I want to create a 4-by-4 matrix using the Eigen library. I also want to specify that the data is stored in row-major order. How can I do this? I have tried the following, but it does not compile: double data[16]; Eigen::Matrix4d M = Eigen::Map<Eigen::Matrix4d>(data, 4, 4, Eigen::RowMajor); 回答1: You need to pass a row-major matrix type to Map, e.g.: Map<Matrix<double,4,4,RowMajor> > M(data); then you can use M as an Eigen matrix, and the values of data will be

问题 I have a question about Eigen library in C++. Actually, I want to calculate inverse matrix of sparse matrix. When I used Dense matrix in Eigen, I can use .inverse() operation to calculate inverse of dense matrix. But in Sparse matrix, I cannot find inverse operation anywhere. Does anyone who know to calculate inverse of sparse matrix? help me. 回答1: You cannot do it directly, but you can always calculate it, using one of the sparse solvers. The idea is to solve A*X=I , where I is the identity

问题 Chances are this is a very stupid question but I spent a pretty absurd amount of time looking for it on the documentation, to no avail. in MATLAB, the find() function gives me an array with the indices of nonzero elements. Numpy's np.nonzero function does something similar. How do I do this in the C++ Eigen library? I have a Boolean array of typedef <bool, 10, 1> foobar = MatrixA < MatrixB; so far. Thanks! 回答1: It is reasonable to expect Eigen to have a find() function. Unfortunately, Eigen

问题 I started a similar question on another thread, but then I was focusing on how to use OpenCV. Having failed to achieve what I originally wanted, I will ask here exactly what I want. I have two matrices. Matrix a is 2782x128 and Matrix b is 4000x128, both unsigned char values. The values are stored in a single array. For each vector in a, I need the index of the vector in b with the closest euclidean distance. Ok, now my code to achieve this: #include <windows.h> #include <stdlib.h> #include

问题 I need a class to have an Eigen::Ref variable as a static member which would be initialized through an init static method. Something like this: class CostFunction { public: static Eigen::Ref<Eigen::VectorXd> data; static void init(const Eigen::Ref<Eigen::VectorXd>& d) { data = d; } CostFunction() {} }; int main() { Eigen::VectorXd data = Eigen::VectorXd::Random(30); CostFunction cf; cf.init(data); return 0; } This doesn't compile. I get an error which looks like this: /var/tmp/doNotRemove

问题 I am trying to return a block of a matrix as an lvalue of a function. Let's say my function looks like this: Block<Derived> getBlock(MatrixXd & m, int i, int j, int row, int column) { return m.block(i,j,row,column); } As it turns out, it seems that C++ compiler understands that block() operator gives only temporary value and so returning it as an lvalue is prohibited by the compiler. However, in Eigen documentation there is some example that we can use Eigen as an lvalue (http://eigen

问题 To me this should just work , so the fact it does not, almost certainly means I am the one in the wrong. Even though in principle a Transform< double, 3, Affine > is the same as a Matrix< double, 4, 4 >, they cannot be used together sensibly: Affine3d rotMat( AngleAxisd( 45.0, ( Vector3d() << 0.0, 1.0, 0.0 ).finished() ) ); Matrix4d m; m << 1.0, 0.0, 0.0, 6.0, 0.0, 1.0, 0.0, 6.0, 0.0, 0.0, 1.0, 6.0, 0.0, 0.0, 0.0, 1.0; m = m * rotMat; Results in a 'no match for operator=' error on the last

问题 I am having some trouble figuring out how to set the rows and columns of a MatrixXd at runtime in Eigen. Can anyone point me to some documentation or give some pointer on how to do this? Thanks. 回答1: You can define a MatrixXd size at runtime by using the method resize(nrow, ncol) . You can read more about resizing a dynamic matrix in this link and its API definition here. 来源： https://stackoverflow.com/questions/19821144/eigen-dynamic-matrix-initialization

问题 I'm using RcppEigen to write some C++ functions for my R code, and I'd like to optimize their compilation as much as possible. When I've used Eigen in the past, I've gotten a significant boost from -O3 and -fopenmp. Following Dirk's advice, I edited ~/.R/Makevars so that my Eigen code would be compiled with these flags: CPPFLAGS=-O3 -fopenmp This works--when I check what's happening during compilation (ps ax | grep cpp) I see: 27097 pts/6 R+ 0:00 /usr/libexec/gcc/x86_64-redhat-linux/4.4.7

问题 I'm trying to sort an Eigen VectorXf x in ascending order. This sorts it in descending order: std::sort(x.data(),x.data()+x.size()); and this doesn't work: bool myfunction (int i,int j) { return (i<j); } std::sort(x.data(),x.data()+x.size(),myfunction); any ideas? 回答1: Preface Since the original question turned out to be a misunderstanding, and the code in it is already the proper answer, I decided to write up and post a bit about using std::sort in general. std::sort sorts range in ascending