| /external/eigen/unsupported/Eigen/src/LevenbergMarquardt/ |
| LMpar.h | 55 VectorType wa1, wa2; local
62 wa1 = qtb;
63 wa1.tail(n-rank).setZero();
65 wa1.head(rank) = s.topLeftCorner(rank,rank).template triangularView<Upper>().solve(qtb.head(rank));
67 x = qr.colsPermutation()*wa1;
86 wa1 = qr.colsPermutation().inverse() * diag.cwiseProduct(wa2)/dxnorm;
87 s.topLeftCorner(n,n).transpose().template triangularView<Lower>().solveInPlace(wa1);
88 temp = wa1.blueNorm();
94 wa1[j] = s.col(j).head(j+1).dot(qtb.head(j+1)) / diag[qr.colsPermutation().indices()(j)];
96 gnorm = wa1.stableNorm()
[all...] |
| /external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
| lmpar.h | 36 Matrix< Scalar, Dynamic, 1 > wa1, wa2; local
41 wa1 = qtb;
46 wa1[j] = 0.;
49 wa1[j] /= r(j,j);
50 temp = wa1[j];
52 wa1[i] -= r(i,j) * temp;
56 x[ipvt[j]] = wa1[j];
77 wa1[j] = diag[l] * (wa2[l] / dxnorm);
84 sum += r(i,j) * wa1[i];
85 wa1[j] = (wa1[j] - sum) / r(j,j)
193 Matrix< Scalar, Dynamic, 1 > wa1, wa2; local
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| 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);
237 internal::dogleg<Scalar>(R, diag, qtf, delta, wa1);
240 wa1 = -wa1;
241 wa2 = x + wa1;
242 pnorm = diag.cwiseProduct(wa1).stableNorm();
260 wa3 = R.template triangularView<Upper>()*wa1 + qtf;
326 wa1 = diag.cwiseProduct( diag.cwiseProduct(wa1)/pnorm )
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| LevenbergMarquardt.h | 122 FVectorType wa1, wa2, wa3, wa4; member in class:Eigen::LevenbergMarquardt
176 wa1.resize(n); wa2.resize(n); wa3.resize(n);
275 internal::lmpar2<Scalar>(qrfac, diag, qtf, delta, par, wa1);
278 wa1 = -wa1;
279 wa2 = x + wa1;
280 pnorm = diag.cwiseProduct(wa1).stableNorm();
299 wa3 = fjac.template triangularView<Upper>() * (qrfac.colsPermutation().inverse() *wa1);
390 wa1.resize(n); wa2.resize(n); wa3.resize(n);
473 wa1 = fjac.diagonal()
[all...] |
