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author | Jan Blechta <blechta@karlin.mff.cuni.cz> | 2015-02-10 14:24:39 +0100 |
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committer | Jan Blechta <blechta@karlin.mff.cuni.cz> | 2015-02-10 14:24:39 +0100 |
commit | c3f3580b8f7e4af89f4c7cdbe036ac1cac750128 (patch) | |
tree | db9f2d437f101f33e1535cc479b136df25836aec /Eigen/src/IterativeLinearSolvers/ConjugateGradient.h | |
parent | deecff97edfb6f75e7613e1db97a1e3e5504e971 (diff) |
Fix bug #733: step by step solving is not a good example for solveWithGuess
Diffstat (limited to 'Eigen/src/IterativeLinearSolvers/ConjugateGradient.h')
-rw-r--r-- | Eigen/src/IterativeLinearSolvers/ConjugateGradient.h | 15 |
1 files changed, 1 insertions, 14 deletions
diff --git a/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h b/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h index 4857dd9e9..1e819fc9f 100644 --- a/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h +++ b/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h @@ -137,20 +137,7 @@ struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> > * \endcode * * By default the iterations start with x=0 as an initial guess of the solution. - * One can control the start using the solveWithGuess() method. Here is a step by - * step execution example starting with a random guess and printing the evolution - * of the estimated error: - * * \code - * x = VectorXd::Random(n); - * cg.setMaxIterations(1); - * int i = 0; - * do { - * x = cg.solveWithGuess(b,x); - * std::cout << i << " : " << cg.error() << std::endl; - * ++i; - * } while (cg.info()!=Success && i<100); - * \endcode - * Note that such a step by step excution is slightly slower. + * One can control the start using the solveWithGuess() method. * * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner */ |