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1 | #include <Eigen/Sparse>
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2 | #include <vector>
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3 |
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4 | typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double
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5 | typedef Eigen::Triplet<double> T;
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6 |
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7 | void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n);
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8 | void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename);
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9 |
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10 | int main(int argc, char** argv)
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11 | {
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12 | int n = 300; // size of the image
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13 | int m = n*n; // number of unknows (=number of pixels)
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14 |
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15 | // Assembly:
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16 | std::vector<T> coefficients; // list of non-zeros coefficients
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17 | Eigen::VectorXd b(m); // the right hand side-vector resulting from the constraints
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18 | buildProblem(coefficients, b, n);
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19 |
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20 | SpMat A(m,m);
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21 | A.setFromTriplets(coefficients.begin(), coefficients.end());
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22 |
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23 | // Solving:
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24 | Eigen::SimplicialCholesky<SpMat> chol(A); // performs a Cholesky factorization of A
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25 | Eigen::VectorXd x = chol.solve(b); // use the factorization to solve for the given right hand side
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26 |
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27 | // Export the result to a file:
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28 | saveAsBitmap(x, n, argv[1]);
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29 |
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30 | return 0;
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31 | }
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32 |
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