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(Results
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/external/eigen/doc/snippets/
LLT_example.cpp
3
cout
<< "The matrix A is" << endl << A << endl;
9
cout
<< "The Cholesky factor L is" << endl << L << endl;
10
cout
<< "To check this, let us compute L * L.transpose()" << endl;
11
cout
<< L * L.transpose() << endl;
12
cout
<< "This should equal the matrix A" << endl;
Matrix_resize_int_int.cpp
3
cout
<< "here's the 2x3 matrix m:" << endl << m << endl;
4
cout
<< "let's resize m to 3x2. This is a conservative resizing because 2*3==3*2." << endl;
6
cout
<< "here's the 3x2 matrix m:" << endl << m << endl;
7
cout
<< "now let's resize m to size 2x2. This is NOT a conservative resizing, so it becomes uninitialized:" << endl;
9
cout
<< m << endl;
TopicAliasing_cwise.cpp
3
cout
<< "Here is the matrix mat:\n" << mat << endl << endl;
6
cout
<< "After 'mat = 2 * mat', mat = \n" << mat << endl << endl;
10
cout
<< "After the subtraction, it becomes\n" << mat << endl << endl;
15
cout
<< "After squaring, it becomes\n" << arr << endl << endl;
20
cout
<< "Doing everything at once yields\n" << mat << endl << endl;
Tridiagonalization_diagonal.cpp
3
cout
<< "Here is a random self-adjoint 4x4 matrix:" << endl << A << endl << endl;
7
cout
<< "The tridiagonal matrix T is:" << endl << T << endl << endl;
9
cout
<< "We can also extract the diagonals of T directly ..." << endl;
11
cout
<< "The diagonal is:" << endl << diag << endl;
13
cout
<< "The subdiagonal is:" << endl << subdiag << endl;
ComplexEigenSolver_compute.cpp
2
cout
<< "Here is a random 4x4 matrix, A:" << endl << A << endl << endl;
6
cout
<< "The eigenvalues of A are:" << endl << ces.eigenvalues() << endl;
7
cout
<< "The matrix of eigenvectors, V, is:" << endl << ces.eigenvectors() << endl << endl;
10
cout
<< "Consider the first eigenvalue, lambda = " << lambda << endl;
12
cout
<< "If v is the corresponding eigenvector, then lambda * v = " << endl << lambda * v << endl;
13
cout
<< "... and A * v = " << endl << A * v << endl << endl;
15
cout
<< "Finally, V * D * V^(-1) = " << endl
EigenSolver_EigenSolver_MatrixType.cpp
2
cout
<< "Here is a random 6x6 matrix, A:" << endl << A << endl << endl;
5
cout
<< "The eigenvalues of A are:" << endl << es.eigenvalues() << endl;
6
cout
<< "The matrix of eigenvectors, V, is:" << endl << es.eigenvectors() << endl << endl;
9
cout
<< "Consider the first eigenvalue, lambda = " << lambda << endl;
11
cout
<< "If v is the corresponding eigenvector, then lambda * v = " << endl << lambda * v << endl;
12
cout
<< "... and A * v = " << endl << A.cast<complex<double> >() * v << endl << endl;
16
cout
<< "Finally, V * D * V^(-1) = " << endl << V * D * V.inverse() << endl;
SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.cpp
3
cout
<< "Here is a random symmetric 5x5 matrix, A:" << endl << A << endl << endl;
6
cout
<< "The eigenvalues of A are:" << endl << es.eigenvalues() << endl;
7
cout
<< "The matrix of eigenvectors, V, is:" << endl << es.eigenvectors() << endl << endl;
10
cout
<< "Consider the first eigenvalue, lambda = " << lambda << endl;
12
cout
<< "If v is the corresponding eigenvector, then lambda * v = " << endl << lambda * v << endl;
13
cout
<< "... and A * v = " << endl << A * v << endl << endl;
17
cout
<< "Finally, V * D * V^(-1) = " << endl << V * D * V.inverse() << endl;
SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType2.cpp
3
cout
<< "Here is a random symmetric matrix, A:" << endl << A << endl;
6
cout
<< "and a random postive-definite matrix, B:" << endl << B << endl << endl;
9
cout
<< "The eigenvalues of the pencil (A,B) are:" << endl << es.eigenvalues() << endl;
10
cout
<< "The matrix of eigenvectors, V, is:" << endl << es.eigenvectors() << endl << endl;
13
cout
<< "Consider the first eigenvalue, lambda = " << lambda << endl;
15
cout
<< "If v is the corresponding eigenvector, then A * v = " << endl << A * v << endl;
16
cout
<< "... and lambda * B * v = " << endl << lambda * B * v << endl << endl;
Tutorial_Map_using.cpp
13
cout
<< "m1: " << m1 << endl;
14
cout
<< "m2: " << m2 << endl;
15
cout
<< "Squared euclidean distance: " << (m1-m2).squaredNorm() << endl;
16
cout
<< "Squared euclidean distance, using map: " <<
19
cout
<< "Updated m2: " << m2 << endl;
20
cout
<< "m2 coefficient 2, constant accessor: " << m2mapconst(2) << endl;
ColPivHouseholderQR_solve.cpp
3
cout
<< "Here is the matrix m:" << endl << m << endl;
4
cout
<< "Here is the matrix y:" << endl << y << endl;
8
cout
<< "Here is a solution x to the equation mx=y:" << endl << x << endl;
FullPivHouseholderQR_solve.cpp
3
cout
<< "Here is the matrix m:" << endl << m << endl;
4
cout
<< "Here is the matrix y:" << endl << y << endl;
8
cout
<< "Here is a solution x to the equation mx=y:" << endl << x << endl;
FullPivLU_image.cpp
5
cout
<< "Here is the matrix m:" << endl << m << endl;
6
cout
<< "Notice that the middle column is the sum of the two others, so the "
8
cout
<< "Here is a matrix whose columns have the same span but are linearly independent:"
HouseholderQR_solve.cpp
4
cout
<< "Here is the matrix m:" << endl << m << endl;
5
cout
<< "Here is the matrix y:" << endl << y << endl;
9
cout
<< "Here is a solution x to the equation mx=y:" << endl << x << endl;
MatrixBase_fixedBlock_int_int.cpp
2
cout
<< "Here is the matrix m:" << endl << m << endl;
3
cout
<< "Here is m.fixed<2, 2>(2, 2):" << endl << m.block<2, 2>(2, 2) << endl;
5
cout
<< "Now the matrix m is:" << endl << m << endl;
/external/eigen/unsupported/doc/examples/
PolynomialUtils1.cpp
10
cout
<< "Roots: " << roots.transpose() << endl;
13
cout
<< "Polynomial: ";
14
for( int i=0; i<4; ++i ){
cout
<< polynomial[i] << ".x^" << i << "+ "; }
15
cout
<< polynomial[4] << ".x^4" << endl;
19
cout
<< "Evaluation of the polynomial at the roots: " << evaluation.transpose();
/external/eigen/doc/examples/
TutorialLinAlgComputeTwice.cpp
13
cout
<< "Here is the matrix A:\n" << A << endl;
14
cout
<< "Here is the right hand side b:\n" << b << endl;
15
cout
<< "Computing LLT decomposition..." << endl;
17
cout
<< "The solution is:\n" << llt.solve(b) << endl;
19
cout
<< "The matrix A is now:\n" << A << endl;
20
cout
<< "Computing LLT decomposition..." << endl;
22
cout
<< "The solution is now:\n" << llt.solve(b) << endl;
tut_arithmetic_matrix_mul.cpp
11
std::
cout
<< "Here is mat*mat:\n" << mat*mat << std::endl;
12
std::
cout
<< "Here is mat*u:\n" << mat*u << std::endl;
13
std::
cout
<< "Here is u^T*mat:\n" << u.transpose()*mat << std::endl;
14
std::
cout
<< "Here is u^T*v:\n" << u.transpose()*v << std::endl;
15
std::
cout
<< "Here is u*v^T:\n" << u*v.transpose() << std::endl;
16
std::
cout
<< "Let's multiply mat by itself" << std::endl;
18
std::
cout
<< "Now mat is mat:\n" << mat << std::endl;
TutorialLinAlgExSolveColPivHouseholderQR.cpp
13
cout
<< "Here is the matrix A:\n" << A << endl;
14
cout
<< "Here is the vector b:\n" << b << endl;
16
cout
<< "The solution is:\n" << x << endl;
TutorialLinAlgExSolveLDLT.cpp
12
cout
<< "Here is the matrix A:\n" << A << endl;
13
cout
<< "Here is the right hand side b:\n" << b << endl;
15
cout
<< "The solution is:\n" << x << endl;
TutorialLinAlgSVDSolve.cpp
10
cout
<< "Here is the matrix A:\n" << A << endl;
12
cout
<< "Here is the right hand side b:\n" << b << endl;
13
cout
<< "The least-squares solution is:\n"
TutorialLinAlgSelfAdjointEigenSolver.cpp
11
cout
<< "Here is the matrix A:\n" << A << endl;
14
cout
<< "The eigenvalues of A are:\n" << eigensolver.eigenvalues() << endl;
15
cout
<< "Here's a matrix whose columns are eigenvectors of A \n"
Tutorial_BlockOperations_corner.cpp
13
cout
<< "m.leftCols(2) =" << endl << m.leftCols(2) << endl << endl;
14
cout
<< "m.bottomRows<2>() =" << endl << m.bottomRows<2>() << endl << endl;
16
cout
<< "After assignment, m = " << endl << m << endl;
Tutorial_BlockOperations_vector.cpp
10
cout
<< "v.head(3) =" << endl << v.head(3) << endl << endl;
11
cout
<< "v.tail<3>() = " << endl << v.tail<3>() << endl << endl;
13
cout
<< "after 'v.segment(1,4) *= 2', v =" << endl << v << endl;
Tutorial_PartialLU_solve.cpp
14
cout
<< "Here is the matrix A:" << endl << A << endl;
15
cout
<< "Here is the vector b:" << endl << b << endl;
17
cout
<< "The solution is:" << endl << x << endl;
tut_arithmetic_dot_cross.cpp
11
cout
<< "Dot product: " << v.dot(w) << endl;
13
cout
<< "Dot product via a matrix product: " << dp << endl;
14
cout
<< "Cross product:\n" << v.cross(w) << endl;
Completed in 115 milliseconds
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