| /external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
| lmpar.h | 34 Matrix< Scalar, Dynamic, 1 > wa1, wa2; local
39 wa1 = qtb;
44 wa1[j] = 0.;
47 wa1[j] /= r(j,j);
48 temp = wa1[j];
50 wa1[i] -= r(i,j) * temp;
54 x[ipvt[j]] = wa1[j];
75 wa1[j] = diag[l] * (wa2[l] / dxnorm);
82 sum += r(i,j) * wa1[i];
83 wa1[j] = (wa1[j] - sum) / r(j,j)
189 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);
235 internal::dogleg<Scalar>(R, diag, qtf, delta, wa1);
238 wa1 = -wa1;
239 wa2 = x + wa1;
240 pnorm = diag.cwiseProduct(wa1).stableNorm();
258 wa3 = R.template triangularView<Upper>()*wa1 + qtf;
324 wa1 = diag.cwiseProduct( diag.cwiseProduct(wa1)/pnorm )
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| LevenbergMarquardt.h | 115 FVectorType wa1, wa2, wa3, wa4; member in class:Eigen::LevenbergMarquardt
169 wa1.resize(n); wa2.resize(n); wa3.resize(n);
265 internal::lmpar2<Scalar>(qrfac, diag, qtf, delta, par, wa1);
268 wa1 = -wa1;
269 wa2 = x + wa1;
270 pnorm = diag.cwiseProduct(wa1).stableNorm();
289 wa3 = fjac.template triangularView<Upper>() * (qrfac.colsPermutation().inverse() *wa1);
380 wa1.resize(n); wa2.resize(n); wa3.resize(n);
460 wa1 = fjac.diagonal()
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