diff options
Diffstat (limited to 'unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h')
| -rw-r--r-- | unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h | 36 |
1 files changed, 18 insertions, 18 deletions
diff --git a/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h b/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h index 3308a4a34..a4863700e 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h +++ b/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h @@ -65,7 +65,7 @@ public: Parameters() : factor(Scalar(100.)) , maxfev(1000) - , xtol(ei_sqrt(NumTraits<Scalar>::epsilon())) + , xtol(internal::sqrt(NumTraits<Scalar>::epsilon())) , nb_of_subdiagonals(-1) , nb_of_superdiagonals(-1) , epsfcn(Scalar(0.)) {} @@ -83,7 +83,7 @@ public: HybridNonLinearSolverSpace::Status hybrj1( FVectorType &x, - const Scalar tol = ei_sqrt(NumTraits<Scalar>::epsilon()) + const Scalar tol = internal::sqrt(NumTraits<Scalar>::epsilon()) ); HybridNonLinearSolverSpace::Status solveInit(FVectorType &x); @@ -92,7 +92,7 @@ public: HybridNonLinearSolverSpace::Status hybrd1( FVectorType &x, - const Scalar tol = ei_sqrt(NumTraits<Scalar>::epsilon()) + const Scalar tol = internal::sqrt(NumTraits<Scalar>::epsilon()) ); HybridNonLinearSolverSpace::Status solveNumericalDiffInit(FVectorType &x); @@ -246,7 +246,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(FVectorType &x) while (true) { /* determine the direction p. */ - ei_dogleg<Scalar>(R, diag, qtf, delta, wa1); + internal::dogleg<Scalar>(R, diag, qtf, delta, wa1); /* store the direction p and x + p. calculate the norm of p. */ wa1 = -wa1; @@ -266,14 +266,14 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(FVectorType &x) /* compute the scaled actual reduction. */ actred = -1.; if (fnorm1 < fnorm) /* Computing 2nd power */ - actred = 1. - ei_abs2(fnorm1 / fnorm); + actred = 1. - internal::abs2(fnorm1 / fnorm); /* compute the scaled predicted reduction. */ wa3 = R.template triangularView<Upper>()*wa1 + qtf; temp = wa3.stableNorm(); prered = 0.; if (temp < fnorm) /* Computing 2nd power */ - prered = 1. - ei_abs2(temp / fnorm); + prered = 1. - internal::abs2(temp / fnorm); /* compute the ratio of the actual to the predicted reduction. */ ratio = 0.; @@ -290,7 +290,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(FVectorType &x) ++ncsuc; if (ratio >= Scalar(.5) || ncsuc > 1) delta = std::max(delta, pnorm / Scalar(.5)); - if (ei_abs(ratio - 1.) <= Scalar(.1)) { + if (internal::abs(ratio - 1.) <= Scalar(.1)) { delta = pnorm / Scalar(.5); } } @@ -342,9 +342,9 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(FVectorType &x) wa2 = (wa2-wa3)/pnorm; /* compute the qr factorization of the updated jacobian. */ - ei_r1updt<Scalar>(R, wa1, v_givens, w_givens, wa2, wa3, &sing); - ei_r1mpyq<Scalar>(n, n, fjac.data(), v_givens, w_givens); - ei_r1mpyq<Scalar>(1, n, qtf.data(), v_givens, w_givens); + internal::r1updt<Scalar>(R, wa1, v_givens, w_givens, wa2, wa3, &sing); + internal::r1mpyq<Scalar>(n, n, fjac.data(), v_givens, w_givens); + internal::r1mpyq<Scalar>(1, n, qtf.data(), v_givens, w_givens); jeval = false; } @@ -447,7 +447,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(FVectorType if (parameters.nb_of_superdiagonals<0) parameters.nb_of_superdiagonals= n-1; /* calculate the jacobian matrix. */ - if (ei_fdjac1(functor, x, fvec, fjac, parameters.nb_of_subdiagonals, parameters.nb_of_superdiagonals, parameters.epsfcn) <0) + if (internal::fdjac1(functor, x, fvec, fjac, parameters.nb_of_subdiagonals, parameters.nb_of_superdiagonals, parameters.epsfcn) <0) return HybridNonLinearSolverSpace::UserAksed; nfev += std::min(parameters.nb_of_subdiagonals+parameters.nb_of_superdiagonals+ 1, n); @@ -487,7 +487,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(FVectorType while (true) { /* determine the direction p. */ - ei_dogleg<Scalar>(R, diag, qtf, delta, wa1); + internal::dogleg<Scalar>(R, diag, qtf, delta, wa1); /* store the direction p and x + p. calculate the norm of p. */ wa1 = -wa1; @@ -507,14 +507,14 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(FVectorType /* compute the scaled actual reduction. */ actred = -1.; if (fnorm1 < fnorm) /* Computing 2nd power */ - actred = 1. - ei_abs2(fnorm1 / fnorm); + actred = 1. - internal::abs2(fnorm1 / fnorm); /* compute the scaled predicted reduction. */ wa3 = R.template triangularView<Upper>()*wa1 + qtf; temp = wa3.stableNorm(); prered = 0.; if (temp < fnorm) /* Computing 2nd power */ - prered = 1. - ei_abs2(temp / fnorm); + prered = 1. - internal::abs2(temp / fnorm); /* compute the ratio of the actual to the predicted reduction. */ ratio = 0.; @@ -531,7 +531,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(FVectorType ++ncsuc; if (ratio >= Scalar(.5) || ncsuc > 1) delta = std::max(delta, pnorm / Scalar(.5)); - if (ei_abs(ratio - 1.) <= Scalar(.1)) { + if (internal::abs(ratio - 1.) <= Scalar(.1)) { delta = pnorm / Scalar(.5); } } @@ -583,9 +583,9 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(FVectorType wa2 = (wa2-wa3)/pnorm; /* compute the qr factorization of the updated jacobian. */ - ei_r1updt<Scalar>(R, wa1, v_givens, w_givens, wa2, wa3, &sing); - ei_r1mpyq<Scalar>(n, n, fjac.data(), v_givens, w_givens); - ei_r1mpyq<Scalar>(1, n, qtf.data(), v_givens, w_givens); + internal::r1updt<Scalar>(R, wa1, v_givens, w_givens, wa2, wa3, &sing); + internal::r1mpyq<Scalar>(n, n, fjac.data(), v_givens, w_givens); + internal::r1mpyq<Scalar>(1, n, qtf.data(), v_givens, w_givens); jeval = false; } |