| /external/eigen/doc/snippets/ |
| H A D | MatrixBase_identity_int_int.cpp | 1 cout << MatrixXd::Identity(4, 3) << endl;
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| H A D | MatrixBase_operatorNorm.cpp | 0 MatrixXd ones = MatrixXd::Ones(3,3);
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| H A D | EigenSolver_eigenvalues.cpp | 0 MatrixXd ones = MatrixXd::Ones(3,3);
2 EigenSolver<MatrixXd> es(ones, false);
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| H A D | EigenSolver_eigenvectors.cpp | 0 MatrixXd ones = MatrixXd::Ones(3,3);
2 EigenSolver<MatrixXd> es(ones);
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| H A D | SelfAdjointEigenSolver_eigenvalues.cpp | 0 MatrixXd ones = MatrixXd::Ones(3,3);
2 SelfAdjointEigenSolver<MatrixXd> es(ones);
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| H A D | SelfAdjointEigenSolver_eigenvectors.cpp | 0 MatrixXd ones = MatrixXd::Ones(3,3);
2 SelfAdjointEigenSolver<MatrixXd> es(ones);
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| H A D | SelfAdjointView_operatorNorm.cpp | 0 MatrixXd ones = MatrixXd::Ones(3,3);
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| H A D | SelfAdjointEigenSolver_operatorSqrt.cpp | 0 MatrixXd X = MatrixXd::Random(4,4);
2 MatrixXd A = X * X.transpose();
5 SelfAdjointEigenSolver<MatrixXd> es(A);
6 MatrixXd sqrtA = es.operatorSqrt();
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| H A D | SelfAdjointEigenSolver_compute_MatrixType2.cpp | 0 MatrixXd X = MatrixXd::Random(5,5);
2 MatrixXd A = X * X.transpose();
3 X = MatrixXd::Random(5,5);
4 MatrixXd B = X * X.transpose();
6 GeneralizedSelfAdjointEigenSolver<MatrixXd> es(A,B,EigenvaluesOnly);
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| H A D | MatrixBase_cwiseAbs.cpp | 0 MatrixXd m(2,3);
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| H A D | MatrixBase_cwiseAbs2.cpp | 0 MatrixXd m(2,3);
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| H A D | MatrixBase_cwiseInverse.cpp | 0 MatrixXd m(2,3);
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| H A D | MatrixBase_eigenvalues.cpp | 0 MatrixXd ones = MatrixXd::Ones(3,3);
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| H A D | SelfAdjointView_eigenvalues.cpp | 0 MatrixXd ones = MatrixXd::Ones(3,3);
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| H A D | SelfAdjointEigenSolver_operatorInverseSqrt.cpp | 0 MatrixXd X = MatrixXd::Random(4,4);
2 MatrixXd A = X * X.transpose();
5 SelfAdjointEigenSolver<MatrixXd> es(A);
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| H A D | EigenSolver_pseudoEigenvectors.cpp | 0 MatrixXd A = MatrixXd::Random(6,6);
4 EigenSolver<MatrixXd> es(A);
5 MatrixXd D = es.pseudoEigenvalueMatrix();
6 MatrixXd V = es.pseudoEigenvectors();
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| H A D | PartialPivLU_solve.cpp | 0 MatrixXd A = MatrixXd::Random(3,3);
2 MatrixXd B = MatrixXd::Random(3,2);
5 MatrixXd X = A.lu().solve(B);
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| H A D | RealSchur_RealSchur_MatrixType.cpp | 0 MatrixXd A = MatrixXd::Random(6,6);
4 RealSchur<MatrixXd> schur(A);
8 MatrixXd U = schur.matrixU();
9 MatrixXd T = schur.matrixT();
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| H A D | Tridiagonalization_Tridiagonalization_MatrixType.cpp | 0 MatrixXd X = MatrixXd::Random(5,5);
2 MatrixXd A = X + X.transpose();
4 Tridiagonalization<MatrixXd> triOfA(A);
5 MatrixXd Q = triOfA.matrixQ();
7 MatrixXd T = triOfA.matrixT();
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| H A D | LLT_example.cpp | 0 MatrixXd A(3,3);
5 LLT<MatrixXd> lltOfA(A); // compute the Cholesky decomposition of A
6 MatrixXd L = lltOfA.matrixL(); // retrieve factor L in the decomposition
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| H A D | Tutorial_AdvancedInitialization_ThreeWays.cpp | 2 MatrixXd mat1(size, size);
3 mat1.topLeftCorner(size/2, size/2) = MatrixXd::Zero(size/2, size/2);
4 mat1.topRightCorner(size/2, size/2) = MatrixXd::Identity(size/2, size/2);
5 mat1.bottomLeftCorner(size/2, size/2) = MatrixXd::Identity(size/2, size/2);
6 mat1.bottomRightCorner(size/2, size/2) = MatrixXd::Zero(size/2, size/2);
9 MatrixXd mat2(size, size);
16 MatrixXd mat3(size, size);
17 mat3 << MatrixXd::Zero(size/2, size/2), MatrixXd::Identity(size/2, size/2),
18 MatrixXd
[all...] |
| /external/eigen/doc/examples/ |
| H A D | TutorialLinAlgExComputeSolveError.cpp | 9 MatrixXd A = MatrixXd::Random(100,100);
10 MatrixXd b = MatrixXd::Random(100,50);
11 MatrixXd x = A.fullPivLu().solve(b);
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| H A D | QuickStart_example.cpp | 4 using Eigen::MatrixXd;
8 MatrixXd m(2,2);
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| H A D | QuickStart_example2_dynamic.cpp | 9 MatrixXd m = MatrixXd::Random(3,3);
10 m = (m + MatrixXd::Constant(3,3,1.2)) * 50;
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| /external/eigen/unsupported/doc/examples/ |
| H A D | MatrixSine.cpp | 8 MatrixXd A = MatrixXd::Random(3,3);
11 MatrixXd sinA = A.sin();
14 MatrixXd cosA = A.cos();
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