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cs440-acg/ext/eigen/doc/snippets/JacobiSVD_basic.cpp
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cs440-acg/ext/eigen/doc/snippets/JacobiSVD_basic.cpp
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MatrixXf m = MatrixXf::Random(3,2);
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cout << "Here is the matrix m:" << endl << m << endl;
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JacobiSVD<MatrixXf> svd(m, ComputeThinU | ComputeThinV);
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cout << "Its singular values are:" << endl << svd.singularValues() << endl;
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cout << "Its left singular vectors are the columns of the thin U matrix:" << endl << svd.matrixU() << endl;
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cout << "Its right singular vectors are the columns of the thin V matrix:" << endl << svd.matrixV() << endl;
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Vector3f rhs(1, 0, 0);
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cout << "Now consider this rhs vector:" << endl << rhs << endl;
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cout << "A least-squares solution of m*x = rhs is:" << endl << svd.solve(rhs) << endl;
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