compile_LLT_solve.cpp

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#include <Eigen/Core>
#include <Eigen/LU>
#include <Eigen/QR>
#include <Eigen/Cholesky>
#include <Eigen/Geometry>
#include <Eigen/Jacobi>
#include <Eigen/Eigenvalues>
#include <iostream>

using namespace Eigen;
using namespace std;

int main(int, char**)
{
  cout.precision(3);
  typedef Matrix<float,Dynamic,2> DataMatrix;
// let's generate some samples on the 3D plane of equation z = 2x+3y (with some noise)
DataMatrix samples = DataMatrix::Random(12,2);
VectorXf elevations = 2*samples.col(0) + 3*samples.col(1) + VectorXf::Random(12)*0.1;
// and let's solve samples * [x y]^T = elevations in least square sense:
Matrix<float,2,1> xy
 = (samples.adjoint() * samples).llt().solve((samples.adjoint()*elevations));
cout << xy << endl;

  return 0;
}