1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <Eigen/Sparse> 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <vector> 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <QImage> 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtypedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtypedef Eigen::Triplet<double> T; 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid insertCoefficient(int id, int i, int j, double w, std::vector<T>& coeffs, 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Eigen::VectorXd& b, const Eigen::VectorXd& boundary) 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int n = boundary.size(); 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int id1 = i+j*n; 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 147faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez if(i==-1 || i==n) b(id) -= w * boundary(j); // constrained coefficient 157faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez else if(j==-1 || j==n) b(id) -= w * boundary(i); // constrained coefficient 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath else coeffs.push_back(T(id,id1,w)); // unknown coefficient 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n) 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath b.setZero(); 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Eigen::ArrayXd boundary = Eigen::ArrayXd::LinSpaced(n, 0,M_PI).sin().pow(2); 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int j=0; j<n; ++j) 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int i=0; i<n; ++i) 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int id = i+j*n; 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath insertCoefficient(id, i-1,j, -1, coefficients, b, boundary); 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath insertCoefficient(id, i+1,j, -1, coefficients, b, boundary); 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath insertCoefficient(id, i,j-1, -1, coefficients, b, boundary); 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath insertCoefficient(id, i,j+1, -1, coefficients, b, boundary); 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath insertCoefficient(id, i,j, 4, coefficients, b, boundary); 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename) 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Eigen::Array<unsigned char,Eigen::Dynamic,Eigen::Dynamic> bits = (x*255).cast<unsigned char>(); 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath QImage img(bits.data(), n,n,QImage::Format_Indexed8); 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath img.setColorCount(256); 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int i=0;i<256;i++) img.setColor(i,qRgb(i,i,i)); 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath img.save(filename); 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 45