eigen/doc/snippets/class_LU.cpp
Benoit Jacob 414ee1db4b Optimization in LU::solve: when rows<=cols, no need to compute the L matrix
Remove matrixL() and matrixU() methods: they were tricky, returning a Part,
and matrixL() was useless for non-square LU. Also they were untested. This is
the occasion to simplify the docs (class_LU.cpp) removing the most confusing part.
I think that it's better to let the user do his own cooking with Part's.
2009-01-25 16:33:06 +00:00

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typedef Matrix<double, 5, 3> Matrix5x3;
typedef Matrix<double, 5, 5> Matrix5x5;
Matrix5x3 m = Matrix5x3::Random();
cout << "Here is the matrix m:" << endl << m << endl;
Eigen::LU<Matrix5x3> lu(m);
cout << "Here is, up to permutations, its LU decomposition matrix:"
<< endl << lu.matrixLU() << endl;
cout << "Here is the L part:" << endl;
Matrix5x5 l = Matrix5x5::Identity();
l.block<5,3>(0,0).part<StrictlyLowerTriangular>() = lu.matrixLU();
cout << l << endl;
cout << "Here is the U part:" << endl;
Matrix5x3 u = lu.matrixLU().part<UpperTriangular>();
cout << u << endl;
cout << "Let us now reconstruct the original matrix m:" << endl;
Matrix5x3 x = l * u;
Matrix5x3 y;
for(int i = 0; i < 5; i++) for(int j = 0; j < 3; j++)
y(i, lu.permutationQ()[j]) = x(lu.permutationP()[i], j);
cout << y << endl; // should be equal to the original matrix m