| /external/eigen/unsupported/test/ |
| D | NonLinearOptimization.cpp | 18 int fcn_chkder(const VectorXd &x, VectorXd &fvec, MatrixXd &fjac, int iflag) in fcn_chkder() argument
23 assert(15 == fvec.size()); in fcn_chkder()
39 fvec[i] = y[i] - (x[0] + tmp1/(x[1]*tmp2 + x[2]*tmp3)); in fcn_chkder()
64 VectorXd x(n), fvec(m), xp, fvecp(m), err; in testChkder() local
72 internal::chkder(x, fvec, fjac, xp, fvecp, 1, err); in testChkder()
73 fcn_chkder(x, fvec, fjac, 1); in testChkder()
74 fcn_chkder(x, fvec, fjac, 2); in testChkder()
76 internal::chkder(x, fvec, fjac, xp, fvecp, 2, err); in testChkder()
78 fvecp -= fvec; in testChkder()
101 VERIFY_IS_APPROX(fvec, fvec_ref); in testChkder()
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| D | levenberg_marquardt.cpp | 32 int operator()(const VectorXd &x, VectorXd &fvec) const in operator ()()
43 fvec[i] = y[i] - (x[0] + tmp1/(x[1]*tmp2 + x[2]*tmp3)); in operator ()()
85 VERIFY_IS_APPROX(lm.fvec().blueNorm(), 0.09063596); in testLmder1()
114 fnorm = lm.fvec().blueNorm(); in testLmder()
144 int operator()(const VectorXd &x, VectorXd &fvec) const in operator ()()
152 assert(fvec.size()==15); in operator ()()
160 fvec[i] = y[i] - (x[0] + tmp1/(x[1]*tmp2 + x[2]*tmp3)); in operator ()()
171 VectorXd x(n), fvec(15); in testLmdif1() local
186 functor(x, fvec); in testLmdif1()
187 VERIFY_IS_APPROX(fvec.blueNorm(), 0.09063596); in testLmdif1()
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| D | NumericalDiff.cpp | 37 int operator()(const VectorXd &x, VectorXd &fvec) const in operator ()()
48 fvec[i] = y[i] - (x[0] + tmp1/(x[1]*tmp2 + x[2]*tmp3)); in operator ()()
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| /external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
| D | chkder.h | 11 const Matrix< Scalar, Dynamic, 1 > &fvec, in chkder()
30 const Index m = fvec.size(), n = x.size(); in chkder()
53 if (fvec[i] != 0. && fvecp[i] != 0. && abs(fvecp[i] - fvec[i]) >= epsf * abs(fvec[i])) in chkder()
54 … temp = eps * abs((fvecp[i] - fvec[i]) / eps - err[i]) / (abs(fvec[i]) + abs(fvecp[i])); in chkder()
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| D | HybridNonLinearSolver.h | 91 FVectorType fvec, qtf, diag; variable
148 fvec.resize(n); in solveInit()
170 if ( functor(x, fvec) < 0) in solveInit()
172 fnorm = fvec.stableNorm(); in solveInit()
229 qtf = fjac.transpose() * fvec; in solveOneStep()
291 fvec = wa4; in solveOneStep()
390 fvec.resize(n); in solveNumericalDiffInit()
410 if ( functor(x, fvec) < 0) in solveNumericalDiffInit()
412 fnorm = fvec.stableNorm(); in solveNumericalDiffInit()
441 …if (internal::fdjac1(functor, x, fvec, fjac, parameters.nb_of_subdiagonals, parameters.nb_of_super… in solveNumericalDiffOneStep()
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| D | fdjac1.h | 9 Matrix< Scalar, Dynamic, 1 > &fvec, in fdjac1()
30 eigen_assert(fvec.size()==n); in fdjac1()
48 fjac.col(j) = (wa1-fvec)/h; in fdjac1()
70 … fjac.col(j).segment(start, length) = ( wa1.segment(start, length)-fvec.segment(start, length))/h; in fdjac1()
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| D | LevenbergMarquardt.h | 107 FVectorType fvec, qtf, diag; variable
178 fvec.resize(m); in minimizeInit()
201 if ( functor(x, fvec) < 0) in minimizeInit()
203 fnorm = fvec.stableNorm(); in minimizeInit()
253 wa4 = fvec; in minimizeOneStep()
332 fvec = wa4; in minimizeOneStep()
392 fvec.resize(m); in minimizeOptimumStorageInit()
420 if ( functor(x, fvec) < 0) in minimizeOptimumStorageInit()
422 fnorm = fvec.stableNorm(); in minimizeOptimumStorageInit()
453 internal::rwupdt<Scalar>(fjac, wa3, qtf, fvec[i]); in minimizeOptimumStorageOneStep()
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| /external/lmfit/man/ |
| D | lmmin.pod | 22 constS< >void *>I<data>B<, double *>I<fvec>B<, int *>I<userbreak>B<),
36 B<lmmin()> determines a vector I<par> that minimizes the sum of squared elements of a vector I<fvec…
56 On output, it contains the solution found to minimize ||I<fvec>||.
60 Length of vector I<fvec>.
71 Pointer to a user-supplied function that computes I<m_dat> elements of vector I<fvec> for a given p…
89 Recommended setting: somewhat above machine precision; less if I<fvec> is computed with reduced acc…
104 Recommended setting: as I<ftol>, but definitely less than the accuracy of I<fvec>.
149 Norm of the vector I<fvec>;
213 const void *data, double *fvec, int *userbreak )
221 fvec[i] = D->y[i] - D->f( D->tx[i], D->tz[i], par );
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| /external/eigen/test/ |
| D | denseLM.cpp | 56 int operator()(const VectorType& uv, VectorType& fvec) in operator ()()
63 eigen_assert(fvec.size() == m); in operator ()()
69 fvec(j) = m_y(j); in operator ()()
72 fvec(j) -= u(i) *std::exp(-(m_x(j)-i)*(m_x(j)-i)/(v(i)*v(i))); in operator ()()
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| D | sparseLM.cpp | 59 int operator()(const VectorType& uv, VectorType& fvec) in operator ()()
68 fvec = m_y; in operator ()()
77 fvec(j) -= u(i)*std::pow((1-coeff), 2); in operator ()()
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| /external/lmfit/lib/ |
| D | lmcurve.c | 31 const double* par, const int m_dat, const void* data, double* fvec, in lmcurve_evaluate() argument
37 fvec[i] = D->y[i] - D->f(D->t[i], par); in lmcurve_evaluate()
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| D | lmcurve_tyd.c | 26 const double* par, const int m_dat, const void* data, double* fvec, in lmcurve_tyd_evaluate() argument
32 fvec[i] = ( D->y[i] - D->f(D->t[i], par) ) / D->dy[i]; in lmcurve_tyd_evaluate()
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| D | lmmin.c | 124 const void* data, double* fvec, int* userbreak), in lmmin() argument
205 double* fvec = (double*)pws; in lmmin() local
235 (*evaluate)(x, m, data, fvec, &(S->userbreak)); in lmmin()
238 fprintf(msgfile, " fvec[%4i] = %18.8g\n", i, fvec[i]); in lmmin()
242 fnorm = lm_enorm(m, fvec); in lmmin()
268 fjac[j*m+i] = (wf[i] - fvec[i]) / step; in lmmin()
309 wf[i] = fvec[i]; in lmmin()
484 fvec[i] = wf[i]; in lmmin()
532 S->fnorm = lm_enorm(m, fvec); in lmmin()
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| D | lmmin.h | 34 const void* data, double* fvec, int* userbreak),
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| /external/lmfit/demo/ |
| D | surface1.c | 37 double *fvec, int *info ) in evaluate_surface() argument
45 fvec[i] = D->y[i] - D->f( D->tx[i], D->tz[i], par ); in evaluate_surface()
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| /external/eigen/unsupported/Eigen/src/LevenbergMarquardt/ |
| D | LevenbergMarquardt.h | 219 FVectorType& fvec() {return m_fvec; } in fvec() function
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