| Quellcodebibliothek Statistik Leitseite products/sources/formale Sprachen/C/MySQL/unsupported/Eigen/src/NonLinearOptimization/ (MySQL Server Version 8.1-8.4©) Datei vom 12.11.2025 mit Größe 2 kB |
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Quelle fdjac1.h Sprache: C |
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namespace Eigen {
namespace internal { template<typename FunctorType, typename Scalar> DenseIndex fdjac1( const FunctorType &Functor, Matrix< Scalar, Dynamic, 1 > &x, Matrix< Scalar, Dynamic, 1 > &fvec, Matrix< Scalar, Dynamic, Dynamic > &fjac, DenseIndex ml, DenseIndex mu, Scalar epsfcn) { using std::sqrt; using std::abs; typedef DenseIndex Index; /* Local variables */ Scalar h; Index j, k; Scalar eps, temp; Index msum; int iflag; Index start, length; /* Function Body */ const Scalar epsmch = NumTraits<Scalar>::epsilon(); const Index n = x.size(); eigen_assert(fvec.size()==n); Matrix< Scalar, Dynamic, 1 > wa1(n); Matrix< Scalar, Dynamic, 1 > wa2(n); eps = sqrt((std::max)(epsfcn,epsmch)); msum = ml + mu + 1; if (msum >= n) { /* computation of dense approximate jacobian. */ for (j = 0; j < n; ++j) { temp = x[j]; h = eps * abs(temp); if (h == 0.) h = eps; x[j] = temp + h; iflag = Functor(x, wa1); if (iflag < 0) return iflag; x[j] = temp; fjac.col(j) = (wa1-fvec)/h; } }else { /* computation of banded approximate jacobian. */ for (k = 0; k < msum; ++k) { for (j = k; (msum<0) ? (j>n): (j<n); j += msum) { wa2[j] = x[j]; h = eps * abs(wa2[j]); if (h == 0.) h = eps; x[j] = wa2[j] + h; } iflag = Functor(x, wa1); if (iflag < 0) return iflag; for (j = k; (msum<0) ? (j>n): (j<n); j += msum) { x[j] = wa2[j]; h = eps * abs(wa2[j]); if (h == 0.) h = eps; fjac.col(j).setZero(); start = std::max<Index>(0,j-mu); length = (std::min)(n-1, j+ml) - start + 1; fjac.col(j).segment(start, length) = ( wa1.segment(start, length)-fvec.segment(start, } } } return 0; } } // end namespace internal } // end namespace Eigen ¤ Dauer der Verarbeitung: 0.38 Sekunden (vorverarbeitet) ¤*© Formatika GbR, Deutschland |
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2026-03-28