| /external/eigen/doc/snippets/ |
| D | 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
16 << ces.eigenvectors() * ces.eigenvalues().asDiagonal() * ces.eigenvectors().inverse() << endl;
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| D | 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;
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| D | 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;
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| D | 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;
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| D | HouseholderSequence_HouseholderSequence.cpp | 2 cout << "The matrix v is:" << endl;
3 cout << v << endl;
6 cout << "The first Householder vector is: v_0 = " << v0.transpose() << endl;
8 cout << "The second Householder vector is: v_1 = " << v1.transpose() << endl;
10 cout << "The third Householder vector is: v_2 = " << v2.transpose() << endl;
13 cout << "The Householder coefficients are: h = " << h.transpose() << endl;
16 cout << "The first Householder reflection is represented by H_0 = " << endl;
17 cout << H0 << endl;
19 cout << "The second Householder reflection is represented by H_1 = " << endl;
20 cout << H1 << endl;
[all …]
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| D | JacobiSVD_basic.cpp | 2 cout << "Here is the matrix m:" << endl << m << endl;
4 cout << "Its singular values are:" << endl << svd.singularValues() << endl;
5 …"Its left singular vectors are the columns of the thin U matrix:" << endl << svd.matrixU() << endl;
6 …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;
9 cout << "A least-squares solution of m*x = rhs is:" << endl << svd.solve(rhs) << endl;
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| D | Vectorwise_reverse.cpp | 2 cout << "Here is the matrix m:" << endl << m << endl;
3 cout << "Here is the rowwise reverse of m:" << endl << m.rowwise().reverse() << endl;
4 cout << "Here is the colwise reverse of m:" << endl << m.colwise().reverse() << endl;
6 cout << "Here is the coefficient (1,0) in the rowise reverse of m:" << endl
7 << m.rowwise().reverse()(1,0) << endl;
8 cout << "Let us overwrite this coefficient with the value 4." << endl;
10 cout << "Now the matrix m is:" << endl << m << endl;
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| D | 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;
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| D | RealSchur_RealSchur_MatrixType.cpp | 2 cout << "Here is a random 6x6 matrix, A:" << endl << A << endl << endl;
5 cout << "The orthogonal matrix U is:" << endl << schur.matrixU() << endl;
6 cout << "The quasi-triangular matrix T is:" << endl << schur.matrixT() << endl << endl;
10 cout << "U * T * U^T = " << endl << U * T * U.transpose() << endl;
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| D | Tridiagonalization_Tridiagonalization_MatrixType.cpp | 3 cout << "Here is a random symmetric 5x5 matrix:" << endl << A << endl << endl;
6 cout << "The orthogonal matrix Q is:" << endl << Q << endl;
8 cout << "The tridiagonal matrix T is:" << endl << T << endl << endl;
9 cout << "Q * T * Q^T = " << endl << Q * T * Q.transpose() << endl;
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| D | 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;
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| D | MatrixBase_transpose.cpp | 2 cout << "Here is the matrix m:" << endl << m << endl;
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;
8 cout << "Now the matrix m is:" << endl << m << endl;
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| D | MatrixBase_reverse.cpp | 2 cout << "Here is the matrix m:" << endl << m << endl;
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;
8 cout << "Now the matrix m is:" << endl << m << endl;
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| D | class_FullPivLU.cpp | 4 cout << "Here is the matrix m:" << endl << m << endl;
7 << endl << lu.matrixLU() << endl;
8 cout << "Here is the L part:" << endl;
11 cout << l << endl;
12 cout << "Here is the U part:" << endl;
14 cout << u << endl;
15 cout << "Let us now reconstruct the original matrix m:" << endl;
16 cout << lu.permutationP().inverse() * l * u * lu.permutationQ().inverse() << endl;
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| D | Tridiagonalization_decomposeInPlace.cpp | 3 cout << "Here is a random symmetric 5x5 matrix:" << endl << A << endl << endl;
8 cout << "The orthogonal matrix Q is:" << endl << A << endl;
9 cout << "The diagonal of the tridiagonal matrix T is:" << endl << diag << endl;
10 cout << "The subdiagonal of the tridiagonal matrix T is:" << endl << subdiag << endl;
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| D | EigenSolver_pseudoEigenvectors.cpp | 2 cout << "Here is a random 6x6 matrix, A:" << endl << A << endl << endl;
7 cout << "The pseudo-eigenvalue matrix D is:" << endl << D << endl;
8 cout << "The pseudo-eigenvector matrix V is:" << endl << V << endl;
9 cout << "Finally, V * D * V^(-1) = " << endl << V * D * V.inverse() << endl;
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| /external/eigen/bench/btl/data/ |
| D | mean.cxx | 109 cout << "<TABLE BORDER CELLPADDING=2>" << endl ; in main()
110 cout << " <TR>" << endl ; in main()
111 cout << " <TH ALIGN=CENTER> " << argv[1] << " </TH>" << endl ; in main()
112 …TH ALIGN=CENTER> <a href=""#mean_marker""> in cache <BR> mean perf <BR> Mflops </a></TH>" << endl ; in main()
113 cout << " <TH ALIGN=CENTER> in cache <BR> % best </TH>" << endl ; in main()
114 …LIGN=CENTER> <a href=""#mean_marker""> out of cache <BR> mean perf <BR> Mflops </a></TH>" << endl ; in main()
115 cout << " <TH ALIGN=CENTER> out of cache <BR> % best </TH>" << endl ; in main()
116 cout << " <TH ALIGN=CENTER> details </TH>" << endl ; in main()
117 cout << " <TH ALIGN=CENTER> comments </TH>" << endl ; in main()
118 cout << " </TR>" << endl ; in main()
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| /external/eigen/unsupported/doc/examples/ |
| D | PolynomialSolver1.cpp | 13 cout << "Roots: " << roots.transpose() << endl; in main()
18 cout << "Complex roots: " << psolve.roots().transpose() << endl; in main()
23 cout << "Real roots: " << mapRR.transpose() << endl; in main()
25 cout << endl; in main()
26 cout << "Illustration of the convergence problem with the QR algorithm: " << endl; in main()
27 cout << "---------------------------------------------------------------" << endl; in main()
31 cout << "Hard case polynomial defined by floats: " << hardCase_polynomial.transpose() << endl; in main()
33 cout << "Complex roots: " << psolvef.roots().transpose() << endl; in main()
36 …< "Norms of the evaluations of the polynomial at the roots: " << evals.transpose() << endl << endl; in main()
38 cout << "Using double's almost always solves the problem for small degrees: " << endl; in main()
[all …]
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| /external/libcxxabi/test/ |
| D | test_fallback_malloc.pass.cpp | 73 std::cout << "Constant exhaustion tests" << std::endl; in exhaustion_test1()
77 std::cout << "Allocated " << ptrs.size () << " 32 byte chunks" << std::endl; in exhaustion_test1()
82 std::cout << "----" << std::endl; in exhaustion_test1()
86 std::cout << "Allocated " << ptrs.size () << " 32 byte chunks" << std::endl; in exhaustion_test1()
90 std::cout << "----" << std::endl; in exhaustion_test1()
94 std::cout << "Allocated " << ptrs.size () << " 32 byte chunks" << std::endl; in exhaustion_test1()
104 std::cout << "Growing exhaustion tests" << std::endl; in exhaustion_test2()
108 …:cout << "Allocated " << ptrs.size () << " { 32, 48, 72, 108, 162 ... } byte chunks" << std::endl; in exhaustion_test2()
113 std::cout << "----" << std::endl; in exhaustion_test2()
118 …:cout << "Allocated " << ptrs.size () << " { 32, 48, 72, 108, 162 ... } byte chunks" << std::endl; in exhaustion_test2()
[all …]
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| /external/eigen/doc/examples/ |
| D | Tutorial_ArrayClass_interop_matrix.cpp | 19 cout << "-- Matrix m*n: --" << endl << result << endl << endl; in main()
21 cout << "-- Array m*n: --" << endl << result << endl << endl; in main()
23 cout << "-- With cwiseProduct: --" << endl << result << endl << endl; in main()
25 cout << "-- Array m + 4: --" << endl << result << endl << endl; in main()
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| D | Tutorial_BlockOperations_block_assignment.cpp | 13 cout << "Here is the array a:" << endl << a << endl << endl; in main()
15 cout << "Here is now a with m copied into its central 2x2 block:" << endl << a << endl << endl; in main()
17 …is now a with bottom-right 2x3 block copied into top-left 2x2 block:" << endl << a << endl << endl; in main()
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| /external/eigen/unsupported/bench/ |
| D | bench_svd.cpp | 42 cout << " Only compute Singular Values" <<endl; in bench_svd()
61 cout << " || " << " BDC : " << timerBDC.value() << "s " <<endl <<endl; in bench_svd()
64 …< "KO : BDC is " << timerJacobi.value() / timerBDC.value() << " times faster than Jacobi" <<endl; in bench_svd()
66 …< "OK : BDC is " << timerJacobi.value() / timerBDC.value() << " times faster than Jacobi" <<endl; in bench_svd()
69 cout << " =================" <<endl; in bench_svd()
70 std::cout<< std::endl; in bench_svd()
73 cout << " Computes rotaion matrix" <<endl; in bench_svd()
92 cout << " || " << " BDC : " << timerBDC.value() << "s " <<endl <<endl; in bench_svd()
95 …< "KO : BDC is " << timerJacobi.value() / timerBDC.value() << " times faster than Jacobi" <<endl; in bench_svd()
97 …< "OK : BDC is " << timerJacobi.value() / timerBDC.value() << " times faster than Jacobi" <<endl; in bench_svd()
[all …]
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| /external/eigen/bench/ |
| D | check_cache_queries.cpp | 15 << (int*)(abcd[2]) << " " << (int*)(abcd[3]) << " " << std::endl; \
20 cout << "Eigen's L1 = " << internal::queryL1CacheSize() << endl; in main()
21 cout << "Eigen's L2/L3 = " << internal::queryTopLevelCacheSize() << endl; in main()
24 cout << "Eigen's L1, L2, L3 = " << l1 << " " << l2 << " " << l3 << endl; in main()
38 cout << endl; in main()
39 cout << "vendor id = " << string_char << endl; in main()
40 cout << endl; in main()
44 cout << "Eigen's intel codes L1, L2, L3 = " << l1 << " " << l2 << " " << l3 << endl; in main()
48 cout << "Eigen's intel direct L1, L2, L3 = " << l1 << " " << l2 << " " << l3 << endl; in main()
51 cout << "Eigen's amd L1, L2, L3 = " << l1 << " " << l2 << " " << l3 << endl; in main()
[all …]
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| /external/zlib/src/contrib/iostream2/ |
| D | zstream_test.cpp | 17 cout << x << endl << y << endl << z << endl; in main()
20 out << setw(50) << setfill('#') << setprecision(20) << x << endl << y << endl << z << endl; in main()
21 out << z << endl << y << endl << x << endl; in main()
22 out << 1.1234567890123456789 << endl; in main()
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| /external/lzma/CPP/7zip/UI/Console/ |
| D | MainAr.cpp | 62 (*g_StdStream) << endl << kUserBreak; in main()
67 (*g_StdStream) << kExceptionErrorMessage << e << endl; in main()
79 (*g_StdStream) << endl << kUserBreak; in main()
84 (*g_StdStream) << endl << endl << "System error:" << endl << message << endl; in main()
89 (*g_StdStream) << kInternalExceptionMessage << exitCode << endl; in main()
101 (*g_StdStream) << kExceptionErrorMessage << s << endl; in main()
106 (*g_StdStream) << kExceptionErrorMessage << s << endl; in main()
111 (*g_StdStream) << kExceptionErrorMessage << s << endl; in main()
116 (*g_StdStream) << kInternalExceptionMessage << t << endl; in main()
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