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https://gitlab.com/libeigen/eigen.git
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merging ei_lmder and lmder_template into ei_lmder() which takes eigen
argument, but still uses f2c code inside.
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parent
6a8b52b3aa
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1715e2cb3b
@ -159,49 +159,6 @@ int ei_lmstr(
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);
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}
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template<typename Functor, typename Scalar>
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int ei_lmder(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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VectorXi &ipvt,
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Matrix< Scalar, Dynamic, 1 > &diag,
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int mode=1,
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Scalar factor = 100.,
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int maxfev = 400,
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Scalar ftol = ei_sqrt(epsilon<Scalar>()),
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Scalar xtol = ei_sqrt(epsilon<Scalar>()),
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Scalar gtol = Scalar(0.),
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int nprint=0
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)
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{
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Matrix< Scalar, Dynamic, 1 >
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qtf(x.size()),
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wa1(x.size()), wa2(x.size()), wa3(x.size()),
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wa4(fvec.size());
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int ldfjac = fvec.size();
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ipvt.resize(x.size());
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fjac.resize(ldfjac, x.size());
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diag.resize(x.size());
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return lmder_template<Scalar>(
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Functor::f, 0,
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fvec.size(), x.size(), x.data(), fvec.data(),
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fjac.data() , ldfjac,
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ftol, xtol, gtol,
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maxfev,
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diag.data(), mode,
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factor,
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nprint,
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nfev, njev,
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ipvt.data(),
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qtf.data(),
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wa1.data(), wa2.data(), wa3.data(), wa4.data()
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);
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}
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template<typename Functor, typename Scalar>
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int ei_lmdif(
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Matrix< Scalar, Dynamic, 1 > &x,
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@ -1,16 +1,29 @@
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template<typename Scalar>
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int lmder_template(minpack_funcder_mn fcn, void *p, int m, int n, Scalar *x,
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Scalar *fvec, Scalar *fjac, int ldfjac, Scalar ftol,
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Scalar xtol, Scalar gtol, int maxfev, Scalar *
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diag, int mode, Scalar factor, int nprint,
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int &nfev, int &njev, int *ipvt, Scalar *qtf,
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Scalar *wa1, Scalar *wa2, Scalar *wa3, Scalar *wa4)
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template<typename Functor, typename Scalar>
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int ei_lmder(
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Matrix< Scalar, Dynamic, 1 > &x,
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Matrix< Scalar, Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Matrix< Scalar, Dynamic, Dynamic > &fjac,
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VectorXi &ipvt,
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Matrix< Scalar, Dynamic, 1 > &diag,
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int mode=1,
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Scalar factor = 100.,
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int maxfev = 400,
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Scalar ftol = ei_sqrt(epsilon<Scalar>()),
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Scalar xtol = ei_sqrt(epsilon<Scalar>()),
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Scalar gtol = Scalar(0.),
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int nprint=0
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)
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{
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/* Initialized data */
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const int m = fvec.size(), n = x.size();
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Matrix< Scalar, Dynamic, 1 > qtf(n), wa1(n), wa2(n), wa3(n), wa4(m);
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int ldfjac = m;
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/* System generated locals */
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int fjac_offset;
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ipvt.resize(n);
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fjac.resize(ldfjac, n);
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diag.resize(n);
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/* Local variables */
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int i, j, l;
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@ -23,18 +36,6 @@ int lmder_template(minpack_funcder_mn fcn, void *p, int m, int n, Scalar *x,
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Scalar fnorm, gnorm, pnorm, xnorm, fnorm1, actred, dirder, prered;
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int info;
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/* Parameter adjustments */
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--wa4;
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--fvec;
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--wa3;
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--wa2;
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--wa1;
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--qtf;
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--ipvt;
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--diag;
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--x;
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fjac_offset = 1 + ldfjac;
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fjac -= fjac_offset;
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/* Function Body */
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@ -52,7 +53,7 @@ int lmder_template(minpack_funcder_mn fcn, void *p, int m, int n, Scalar *x,
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if (mode != 2) {
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goto L20;
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}
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for (j = 1; j <= n; ++j) {
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for (j = 0; j < n; ++j) {
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if (diag[j] <= 0.) {
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goto L300;
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}
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@ -63,12 +64,12 @@ L20:
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/* evaluate the function at the starting point */
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/* and calculate its norm. */
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iflag = (*fcn)(p, m, n, &x[1], &fvec[1], &fjac[fjac_offset], ldfjac, 1);
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iflag = Functor::f(0, m, n, x.data(), fvec.data(), fjac.data(), ldfjac, 1);
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nfev = 1;
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if (iflag < 0) {
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goto L300;
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}
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fnorm = ei_enorm<Scalar>(m, &fvec[1]);
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fnorm = fvec.stableNorm();
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/* initialize levenberg-marquardt parameter and iteration counter. */
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@ -81,20 +82,20 @@ L30:
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/* calculate the jacobian matrix. */
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iflag = (*fcn)(p, m, n, &x[1], &fvec[1], &fjac[fjac_offset], ldfjac, 2);
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iflag = Functor::f(0, m, n, x.data(), fvec.data(), fjac.data(), ldfjac, 2);
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++njev;
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if (iflag < 0) {
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goto L300;
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}
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/* if requested, call fcn to enable printing of iterates. */
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/* if requested, call Functor::f to enable printing of iterates. */
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if (nprint <= 0) {
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goto L40;
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}
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iflag = 0;
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if ((iter - 1) % nprint == 0) {
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iflag = (*fcn)(p, m, n, &x[1], &fvec[1], &fjac[fjac_offset], ldfjac, 0);
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iflag = Functor::f(0, m, n, x.data(), fvec.data(), fjac.data(), ldfjac, 0);
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}
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if (iflag < 0) {
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goto L300;
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@ -103,8 +104,7 @@ L40:
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/* compute the qr factorization of the jacobian. */
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qrfac(m, n, &fjac[fjac_offset], ldfjac, TRUE_, &ipvt[1], n, &wa1[1], &
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wa2[1], &wa3[1]);
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qrfac(m, n, fjac.data(), ldfjac, TRUE_, ipvt.data(), n, wa1.data(), wa2.data(), wa3.data());
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/* on the first iteration and if mode is 1, scale according */
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/* to the norms of the columns of the initial jacobian. */
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@ -115,7 +115,7 @@ L40:
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if (mode == 2) {
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goto L60;
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}
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for (j = 1; j <= n; ++j) {
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for (j = 0; j < n; ++j) {
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diag[j] = wa2[j];
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if (wa2[j] == 0.) {
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diag[j] = 1.;
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@ -127,11 +127,11 @@ L60:
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/* on the first iteration, calculate the norm of the scaled x */
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/* and initialize the step bound delta. */
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for (j = 1; j <= n; ++j) {
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for (j = 0; j < n; ++j) {
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wa3[j] = diag[j] * x[j];
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/* L70: */
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}
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xnorm = ei_enorm<Scalar>(n, &wa3[1]);
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xnorm = wa3.stableNorm();
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delta = factor * xnorm;
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if (delta == 0.) {
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delta = factor;
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@ -141,26 +141,26 @@ L80:
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/* form (q transpose)*fvec and store the first n components in */
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/* qtf. */
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for (i = 1; i <= m; ++i) {
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for (i = 0; i < m; ++i) {
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wa4[i] = fvec[i];
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/* L90: */
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}
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for (j = 1; j <= n; ++j) {
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if (fjac[j + j * ldfjac] == 0.) {
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for (j = 0; j < n; ++j) {
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if (fjac(j,j) == 0.) {
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goto L120;
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}
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sum = 0.;
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for (i = j; i <= m; ++i) {
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sum += fjac[i + j * ldfjac] * wa4[i];
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for (i = j; i < m; ++i) {
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sum += fjac(i,j) * wa4[i];
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/* L100: */
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}
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temp = -sum / fjac[j + j * ldfjac];
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for (i = j; i <= m; ++i) {
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wa4[i] += fjac[i + j * ldfjac] * temp;
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temp = -sum / fjac(j,j);
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for (i = j; i < m; ++i) {
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wa4[i] += fjac(i,j) * temp;
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/* L110: */
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}
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L120:
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fjac[j + j * ldfjac] = wa1[j];
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fjac(j,j) = wa1[j];
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qtf[j] = wa4[j];
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/* L130: */
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}
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@ -171,14 +171,14 @@ L120:
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if (fnorm == 0.) {
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goto L170;
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}
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for (j = 1; j <= n; ++j) {
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l = ipvt[j];
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for (j = 0; j < n; ++j) {
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l = ipvt[j]-1;
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if (wa2[l] == 0.) {
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goto L150;
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}
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sum = 0.;
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for (i = 1; i <= j; ++i) {
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sum += fjac[i + j * ldfjac] * (qtf[i] / fnorm);
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for (i = 0; i <= j; ++i) {
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sum += fjac(i,j) * (qtf[i] / fnorm);
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/* L140: */
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}
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/* Computing MAX */
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@ -203,7 +203,7 @@ L170:
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if (mode == 2) {
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goto L190;
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}
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for (j = 1; j <= n; ++j)
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for (j = 0; j < n; ++j)
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diag[j] = max( diag[j], wa2[j]);
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L190:
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@ -213,18 +213,18 @@ L200:
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/* determine the levenberg-marquardt parameter. */
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lmpar(n, &fjac[fjac_offset], ldfjac, &ipvt[1], &diag[1], &qtf[1], delta,
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&par, &wa1[1], &wa2[1], &wa3[1], &wa4[1]);
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lmpar(n, fjac.data(), ldfjac, ipvt.data(), diag.data(), qtf.data(), delta,
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&par, wa1.data(), wa2.data(), wa3.data(), wa4.data());
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/* store the direction p and x + p. calculate the norm of p. */
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for (j = 1; j <= n; ++j) {
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for (j = 0; j < n; ++j) {
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wa1[j] = -wa1[j];
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wa2[j] = x[j] + wa1[j];
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wa3[j] = diag[j] * wa1[j];
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/* L210: */
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}
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pnorm = ei_enorm<Scalar>(n, &wa3[1]);
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pnorm = wa3.stableNorm();
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/* on the first iteration, adjust the initial step bound. */
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@ -234,12 +234,12 @@ L200:
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/* evaluate the function at x + p and calculate its norm. */
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iflag = (*fcn)(p, m, n, &wa2[1], &wa4[1], &fjac[fjac_offset], ldfjac, 1);
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iflag = Functor::f(0, m, n, wa2.data(), wa4.data(), fjac.data(), ldfjac, 1);
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++nfev;
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if (iflag < 0) {
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goto L300;
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}
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fnorm1 = ei_enorm<Scalar>(m, &wa4[1]);
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fnorm1 = wa4.stableNorm();
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/* compute the scaled actual reduction. */
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@ -250,17 +250,17 @@ L200:
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/* compute the scaled predicted reduction and */
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/* the scaled directional derivative. */
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for (j = 1; j <= n; ++j) {
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for (j = 0; j < n; ++j) {
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wa3[j] = 0.;
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l = ipvt[j];
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l = ipvt[j]-1;
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temp = wa1[l];
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for (i = 1; i <= j; ++i) {
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wa3[i] += fjac[i + j * ldfjac] * temp;
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for (i = 0; i <= j; ++i) {
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wa3[i] += fjac(i,j) * temp;
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/* L220: */
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}
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/* L230: */
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}
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temp1 = ei_abs2(ei_enorm<Scalar>(n, &wa3[1]) / fnorm);
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temp1 = ei_abs2(wa3.stableNorm() / fnorm);
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temp2 = ei_abs2( ei_sqrt(par) * pnorm / fnorm);
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/* Computing 2nd power */
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prered = temp1 + temp2 / p5;
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@ -309,16 +309,16 @@ L260:
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/* successful iteration. update x, fvec, and their norms. */
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for (j = 1; j <= n; ++j) {
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for (j = 0; j < n; ++j) {
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x[j] = wa2[j];
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wa2[j] = diag[j] * x[j];
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/* L270: */
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}
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for (i = 1; i <= m; ++i) {
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for (i = 0; i < m; ++i) {
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fvec[i] = wa4[i];
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/* L280: */
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}
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xnorm = ei_enorm<Scalar>(n, &wa2[1]);
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xnorm = wa2.stableNorm();
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fnorm = fnorm1;
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++iter;
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L290:
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@ -375,7 +375,7 @@ L300:
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}
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iflag = 0;
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if (nprint > 0) {
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iflag = (*fcn)(p, m, n, &x[1], &fvec[1], &fjac[fjac_offset], ldfjac, 0);
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iflag = Functor::f(0, m, n, x.data(), fvec.data(), fjac.data(), ldfjac, 0);
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}
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return info;
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@ -1925,7 +1925,7 @@ void test_NonLinear()
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/*
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* Can be useful for debugging...
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printf("info, nfev, jev : %d, %d, %d\n", info, nfev, njev);
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printf("info, nfev, njev : %d, %d, %d\n", info, nfev, njev);
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printf("x[0] : %.32g\n", x[0]);
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printf("x[1] : %.32g\n", x[1]);
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printf("x[2] : %.32g\n", x[2]);
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