/external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
lmpar.h | 34 Matrix< Scalar, Dynamic, 1 > wa1, wa2; local 60 wa2 = diag.cwiseProduct(x); 61 dxnorm = wa2.blueNorm(); 75 wa1[j] = diag[l] * (wa2[l] / dxnorm); 117 wa2 = diag.cwiseProduct(x); 118 dxnorm = wa2.blueNorm(); 131 wa1[j] = diag[l] * (wa2[l] / dxnorm); 189 Matrix< Scalar, Dynamic, 1 > wa1, wa2; local 206 wa2 = diag.cwiseProduct(x); 207 dxnorm = wa2.blueNorm() [all...] |
HybridNonLinearSolver.h | 113 FVectorType wa1, wa2, wa3, wa4; member in class:Eigen::HybridNonLinearSolver 147 wa1.resize(n); wa2.resize(n); wa3.resize(n); wa4.resize(n); 200 wa2 = fjac.colwise().blueNorm(); 207 diag[j] = (wa2[j]==0.) ? 1. : wa2[j]; 231 diag = diag.cwiseMax(wa2); 239 wa2 = x + wa1; 247 if ( functor(wa2, wa4) < 0) 287 x = wa2; 288 wa2 = diag.cwiseProduct(x) [all...] |
LevenbergMarquardt.h | 115 FVectorType wa1, wa2, wa3, wa4; member in class:Eigen::LevenbergMarquardt 169 wa1.resize(n); wa2.resize(n); wa3.resize(n); 221 wa2 = fjac.colwise().blueNorm(); 231 diag[j] = (wa2[j]==0.)? 1. : wa2[j]; 251 if (wa2[permutation.indices()[j]] != 0.) 252 gnorm = (std::max)(gnorm, internal::abs( fjac.col(j).head(j+1).dot(qtf.head(j+1)/fnorm) / wa2[permutation.indices()[j]])); 260 diag = diag.cwiseMax(wa2); 269 wa2 = x + wa1; 277 if ( functor(wa2, wa4) < 0 [all...] |