| /external/eigen/doc/snippets/ |
| MatrixBase_inverse.cpp | 2 cout << "Here is the matrix m:" << endl << m << endl; variable
3 cout << "Its inverse is:" << endl << m.inverse() << endl;
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| MatrixBase_random.cpp | 1 cout << 100 * Matrix2i::Random() << endl;
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| MatrixBase_random_int.cpp | 1 cout << VectorXi::Random(2) << endl;
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| MatrixBase_ones.cpp | 1 cout << Matrix2d::Ones() << endl;
2 cout << 6 * RowVector4i::Ones() << endl;
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| MatrixBase_ones_int.cpp | 1 cout << 6 * RowVectorXi::Ones(4) << endl;
2 cout << VectorXf::Ones(2) << endl;
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| MatrixBase_zero.cpp | 1 cout << Matrix2d::Zero() << endl;
2 cout << RowVector4i::Zero() << endl;
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| MatrixBase_zero_int.cpp | 1 cout << RowVectorXi::Zero(4) << endl;
2 cout << VectorXf::Zero(2) << endl;
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| ComplexSchur_matrixU.cpp | 2 cout << "Here is a random 4x4 matrix, A:" << endl << A << endl << endl; variable
4 cout << "The unitary matrix U is:" << endl << schurOfA.matrixU() << endl;
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| RealSchur_RealSchur_MatrixType.cpp | 2 cout << "Here is a random 6x6 matrix, A:" << endl << A << endl << endl; variable
5 cout << "The orthogonal matrix U is:" << endl << schur.matrixU() << endl;
6 cout << "The quasi-triangular matrix T is:" << endl << schur.matrixT() << endl << endl; variable
10 cout << "U * T * U^T = " << endl << U * T * U.transpose() << endl;
[all...] |
| Tridiagonalization_Tridiagonalization_MatrixType.cpp | 3 cout << "Here is a random symmetric 5x5 matrix:" << endl << A << endl << endl; variable
6 cout << "The orthogonal matrix Q is:" << endl << Q << endl; variable
8 cout << "The tridiagonal matrix T is:" << endl << T << endl << endl; variable
9 cout << "Q * T * Q^T = " << endl << Q * T * Q.transpose() << endl;
[all...] |
| SelfAdjointEigenSolver_operatorSqrt.cpp | 3 cout << "Here is a random positive-definite matrix, A:" << endl << A << endl << endl; variable
7 cout << "The square root of A is: " << endl << sqrtA << endl; variable
8 cout << "If we square this, we get: " << endl << sqrtA*sqrtA << endl; variable
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| EigenSolver_pseudoEigenvectors.cpp | 2 cout << "Here is a random 6x6 matrix, A:" << endl << A << endl << endl; variable
7 cout << "The pseudo-eigenvalue matrix D is:" << endl << D << endl; variable
8 cout << "The pseudo-eigenvector matrix V is:" << endl << V << endl; variable
9 cout << "Finally, V * D * V^(-1) = " << endl << V * D * V.inverse() << endl;
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| MatrixBase_reverse.cpp | 2 cout << "Here is the matrix m:" << endl << m << endl; variable
3 cout << "Here is the reverse of m:" << endl << m.reverse() << endl;
4 cout << "Here is the coefficient (1,0) in the reverse of m:" << endl
5 << m.reverse()(1,0) << endl;
6 cout << "Let us overwrite this coefficient with the value 4." << endl; variable
8 cout << "Now the matrix m is:" << endl << m << endl; variable
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| MatrixBase_transpose.cpp | 2 cout << "Here is the matrix m:" << endl << m << endl; variable
3 cout << "Here is the transpose of m:" << endl << m.transpose() << endl;
4 cout << "Here is the coefficient (1,0) in the transpose of m:" << endl
5 << m.transpose()(1,0) << endl;
6 cout << "Let us overwrite this coefficient with the value 0." << endl; variable
8 cout << "Now the matrix m is:" << endl << m << endl; variable
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| Tridiagonalization_decomposeInPlace.cpp | 3 cout << "Here is a random symmetric 5x5 matrix:" << endl << A << endl << endl; variable
8 cout << "The orthogonal matrix Q is:" << endl << A << endl; variable
9 cout << "The diagonal of the tridiagonal matrix T is:" << endl << diag << endl; variable
10 cout << "The subdiagonal of the tridiagonal matrix T is:" << endl << subdiag << endl; variable
|
| JacobiSVD_basic.cpp | 2 cout << "Here is the matrix m:" << endl << m << endl; variable
4 cout << "Its singular values are:" << endl << svd.singularValues() << endl;
5 cout << "Its left singular vectors are the columns of the thin U matrix:" << endl << svd.matrixU() << endl;
6 cout << "Its right singular vectors are the columns of the thin V matrix:" << endl << svd.matrixV() << endl;
8 cout << "Now consider this rhs vector:" << endl << rhs << endl; variable
[all...] |
| ComplexEigenSolver_compute.cpp | 2 cout << "Here is a random 4x4 matrix, A:" << endl << A << endl << endl; variable
6 cout << "The eigenvalues of A are:" << endl << ces.eigenvalues() << endl;
7 cout << "The matrix of eigenvectors, V, is:" << endl << ces.eigenvectors() << endl << endl; variable
10 cout << "Consider the first eigenvalue, lambda = " << lambda << endl; variable
12 cout << "If v is the corresponding eigenvector, then lambda * v = " << endl << lambda * v << endl variable
13 cout << "... and A * v = " << endl << A * v << endl << endl; variable
[all...] |
| Cwise_cube.cpp | 2 cout << v.cube() << endl;
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| Cwise_exp.cpp | 2 cout << v.exp() << endl;
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| Cwise_inverse.cpp | 2 cout << v.inverse() << endl;
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| Cwise_log.cpp | 2 cout << v.log() << endl;
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| Cwise_minus.cpp | 2 cout << v-5 << endl;
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| /external/opencv3/3rdparty/tbb/ |
| version_string.tmp | 2 "TBB: BUILD_HOST Unknown" ENDL \
3 "TBB: BUILD_OS Android" ENDL \
4 "TBB: BUILD_KERNEL Unknown" ENDL \
5 "TBB: BUILD_GCC gcc version 4.4.3" ENDL \
6 "TBB: BUILD_GLIBC Unknown" ENDL \
7 "TBB: BUILD_LD Unknown" ENDL \
8 "TBB: BUILD_TARGET Unknown" ENDL \
9 "TBB: BUILD_COMMAND use cv::getBuildInformation() for details" ENDL
|
| version_string.ver | 2 #N": BUILD_HOST Unknown" ENDL \
3 #N": BUILD_OS Android" ENDL \
4 #N": BUILD_KERNEL Unknown" ENDL \
5 #N": BUILD_GCC gcc version 4.4.3" ENDL \
6 #N": BUILD_GLIBC Unknown" ENDL \
7 #N": BUILD_LD Unknown" ENDL \
8 #N": BUILD_TARGET Unknown" ENDL \
9 #N": BUILD_COMMAND use cv::getBuildInformation() for details" ENDL
|
| /external/eigen/doc/examples/ |
| Tutorial_ArrayClass_interop_matrix.cpp | 19 cout << "-- Matrix m*n: --" << endl << result << endl << endl; local
21 cout << "-- Array m*n: --" << endl << result << endl << endl; local
23 cout << "-- With cwiseProduct: --" << endl << result << endl << endl; local
25 cout << "-- Array m + 4: --" << endl << result << endl << endl local
[all...] |
