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authorJim Guggemos <jimg@google.com>2012-12-04 16:46:41 -0700
committerJim Guggemos <jimg@google.com>2012-12-04 17:08:38 -0700
commitb015e75e8c7ba1ab4ddb91e9372a57e76f3fd159 (patch)
tree54d1c7d66098154c1d7c5bd414394ef4cf255810 /doc/special_examples/Tutorial_sparse_example.cpp
parent63f67d748682b46d58be31235a0a2d64d81b998c (diff)
parentc981c48f5bc9aefeffc0bcb0cc3934c2fae179dd (diff)
downloadeigen-b015e75e8c7ba1ab4ddb91e9372a57e76f3fd159.tar.gz
Change-Id: Ic9004531328145ea36ba513bb96a23595427f6a4
Diffstat (limited to 'doc/special_examples/Tutorial_sparse_example.cpp')
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diff --git a/doc/special_examples/Tutorial_sparse_example.cpp b/doc/special_examples/Tutorial_sparse_example.cpp
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+++ b/doc/special_examples/Tutorial_sparse_example.cpp
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+#include <Eigen/Sparse>
+#include <vector>
+
+typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double
+typedef Eigen::Triplet<double> T;
+
+void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n);
+void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename);
+
+int main(int argc, char** argv)
+{
+ int n = 300; // size of the image
+ int m = n*n; // number of unknows (=number of pixels)
+
+ // Assembly:
+ std::vector<T> coefficients; // list of non-zeros coefficients
+ Eigen::VectorXd b(m); // the right hand side-vector resulting from the constraints
+ buildProblem(coefficients, b, n);
+
+ SpMat A(m,m);
+ A.setFromTriplets(coefficients.begin(), coefficients.end());
+
+ // Solving:
+ Eigen::SimplicialCholesky<SpMat> chol(A); // performs a Cholesky factorization of A
+ Eigen::VectorXd x = chol.solve(b); // use the factorization to solve for the given right hand side
+
+ // Export the result to a file:
+ saveAsBitmap(x, n, argv[1]);
+
+ return 0;
+}
+