2012-06-20 15:28:32 +08:00
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#include <Eigen/Sparse>
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#include <vector>
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#include <QImage>
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typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double
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typedef Eigen::Triplet<double> T;
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void insertCoefficient(int id, int i, int j, double w, std::vector<T>& coeffs,
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Eigen::VectorXd& b, const Eigen::VectorXd& boundary)
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{
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int n = boundary.size();
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int id1 = i+j*n;
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2013-08-12 19:37:47 +08:00
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if(i==-1 || i==n) b(id) -= w * boundary(j); // constrained coefficient
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else if(j==-1 || j==n) b(id) -= w * boundary(i); // constrained coefficient
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2012-06-20 15:28:32 +08:00
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else coeffs.push_back(T(id,id1,w)); // unknown coefficient
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}
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void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n)
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{
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b.setZero();
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Eigen::ArrayXd boundary = Eigen::ArrayXd::LinSpaced(n, 0,M_PI).sin().pow(2);
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for(int j=0; j<n; ++j)
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{
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for(int i=0; i<n; ++i)
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{
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int id = i+j*n;
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insertCoefficient(id, i-1,j, -1, coefficients, b, boundary);
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insertCoefficient(id, i+1,j, -1, coefficients, b, boundary);
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insertCoefficient(id, i,j-1, -1, coefficients, b, boundary);
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insertCoefficient(id, i,j+1, -1, coefficients, b, boundary);
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insertCoefficient(id, i,j, 4, coefficients, b, boundary);
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}
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}
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}
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void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename)
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{
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Eigen::Array<unsigned char,Eigen::Dynamic,Eigen::Dynamic> bits = (x*255).cast<unsigned char>();
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QImage img(bits.data(), n,n,QImage::Format_Indexed8);
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img.setColorCount(256);
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for(int i=0;i<256;i++) img.setColor(i,qRgb(i,i,i));
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img.save(filename);
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}
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