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cleaning, removing goto's, uniformization (try to reduce diff between

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hybr[dj].h  or lm[der,dif,str].h as much as possible), for future merging.
This commit is contained in:
Thomas Capricelli 2009-08-24 16:05:57 +02:00
parent 91a2145cb3
commit 63071ac968
5 changed files with 493 additions and 640 deletions
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66
unsupported/Eigen/src/NonLinear/hybrd.h
View File

@ -89,7 +89,7 @@ int ei_hybrd(
while (true) {
jeval = true;
/* calculate the jacobian matrix. */
/* calculate the jacobian matrix. */
iflag = ei_fdjac1<Functor,Scalar>(x, fvec, fjac,
nb_of_subdiagonals, nb_of_superdiagonals, epsfcn, wa1, wa2);
@ -97,12 +97,12 @@ int ei_hybrd(
if (iflag < 0)
break;
/* compute the qr factorization of the jacobian. */
/* compute the qr factorization of the jacobian. */
ei_qrfac<Scalar>(n, n, fjac.data(), fjac.rows(), false, iwa, 1, wa1.data(), wa2.data());
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
if (iter == 1) {
if (mode != 2)
@ -112,8 +112,8 @@ int ei_hybrd(
diag[j] = 1.;
}
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
wa3 = diag.cwise() * x;
xnorm = wa3.stableNorm();
@ -122,7 +122,7 @@ int ei_hybrd(
delta = factor;
}
/* form (q transpose)*fvec and store in qtf. */
/* form (q transpose)*fvec and store in qtf. */
qtf = fvec;
for (j = 0; j < n; ++j)
@ -135,7 +135,7 @@ int ei_hybrd(
qtf[i] += fjac(i,j) * temp;
}
/* copy the triangular factor of the qr factorization into r. */
/* copy the triangular factor of the qr factorization into r. */
sing = false;
for (j = 0; j < n; ++j) {
@ -150,20 +150,20 @@ int ei_hybrd(
sing = true;
}
/* accumulate the orthogonal factor in fjac. */
/* accumulate the orthogonal factor in fjac. */
ei_qform<Scalar>(n, n, fjac.data(), fjac.rows(), wa1.data());
/* rescale if necessary. */
/* rescale if necessary. */
/* Computing MAX */
if (mode != 2)
diag = diag.cwise().max(wa2);
/* beginning of the inner loop. */
/* beginning of the inner loop. */
while (true) {
/* if requested, call Functor::f to enable printing of iterates. */
/* if requested, call Functor::f to enable printing of iterates. */
if (nprint > 0) {
iflag = 0;
@ -173,23 +173,23 @@ int ei_hybrd(
goto L300;
}
/* determine the direction p. */
/* determine the direction p. */
ei_dogleg<Scalar>(R, diag, qtf, delta, wa1);
/* store the direction p and x + p. calculate the norm of p. */
/* store the direction p and x + p. calculate the norm of p. */
wa1 = -wa1;
wa2 = x + wa1;
wa3 = diag.cwise() * wa1;
pnorm = wa3.stableNorm();
/* on the first iteration, adjust the initial step bound. */
/* on the first iteration, adjust the initial step bound. */
if (iter == 1)
delta = std::min(delta,pnorm);
/* evaluate the function at x + p and calculate its norm. */
/* evaluate the function at x + p and calculate its norm. */
iflag = Functor::f(wa2, wa4);
++nfev;
@ -197,13 +197,13 @@ int ei_hybrd(
goto L300;
fnorm1 = wa4.stableNorm();
/* compute the scaled actual reduction. */
/* compute the scaled actual reduction. */
actred = -1.;
if (fnorm1 < fnorm) /* Computing 2nd power */
actred = 1. - ei_abs2(fnorm1 / fnorm);
/* compute the scaled predicted reduction. */
/* compute the scaled predicted reduction. */
l = 0;
for (i = 0; i < n; ++i) {
@ -219,14 +219,14 @@ int ei_hybrd(
if (temp < fnorm) /* Computing 2nd power */
prered = 1. - ei_abs2(temp / fnorm);
/* compute the ratio of the actual to the predicted */
/* reduction. */
/* compute the ratio of the actual to the predicted */
/* reduction. */
ratio = 0.;
if (prered > 0.)
ratio = actred / prered;
/* update the step bound. */
/* update the step bound. */
if (ratio < Scalar(.1)) {
ncsuc = 0;
@ -242,10 +242,10 @@ int ei_hybrd(
}
}
/* test for successful iteration. */
/* test for successful iteration. */
if (ratio >= Scalar(1e-4)) {
/* successful iteration. update x, fvec, and their norms. */
/* successful iteration. update x, fvec, and their norms. */
x = wa2;
wa2 = diag.cwise() * x;
fvec = wa4;
@ -254,7 +254,7 @@ int ei_hybrd(
++iter;
}
/* determine the progress of the iteration. */
/* determine the progress of the iteration. */
++nslow1;
if (actred >= Scalar(.001))
@ -264,14 +264,14 @@ int ei_hybrd(
if (actred >= Scalar(.1))
nslow2 = 0;
/* test for convergence. */
/* test for convergence. */
if (delta <= xtol * xnorm || fnorm == 0.)
info = 1;
if (info != 0)
goto L300;
/* tests for termination and stringent tolerances. */
/* tests for termination and stringent tolerances. */
if (nfev >= maxfev)
info = 2;
@ -285,14 +285,14 @@ int ei_hybrd(
if (info != 0)
goto L300;
/* criterion for recalculating jacobian approximation */
/* by forward differences. */
/* criterion for recalculating jacobian approximation */
/* by forward differences. */
if (ncfail == 2)
break;
/* calculate the rank one modification to the jacobian */
/* and update qtf if necessary. */
/* calculate the rank one modification to the jacobian */
/* and update qtf if necessary. */
for (j = 0; j < n; ++j) {
sum = wa4.dot(fjac.col(j));
@ -302,17 +302,17 @@ int ei_hybrd(
qtf[j] = sum;
}
/* compute the qr factorization of the updated jacobian. */
/* compute the qr factorization of the updated jacobian. */
ei_r1updt<Scalar>(n, n, R.data(), R.size(), wa1.data(), wa2.data(), wa3.data(), &sing);
ei_r1mpyq<Scalar>(n, n, fjac.data(), fjac.rows(), wa2.data(), wa3.data());
ei_r1mpyq<Scalar>(1, n, qtf.data(), 1, wa2.data(), wa3.data());
/* end of the inner loop. */
/* end of the inner loop. */
jeval = false;
}
/* end of the outer loop. */
/* end of the outer loop. */
}
L300:
/* termination, either normal or user imposed. */

64
unsupported/Eigen/src/NonLinear/hybrj.h
View File

@ -78,19 +78,19 @@ int ei_hybrj(
while (true) {
jeval = true;
/* calculate the jacobian matrix. */
/* calculate the jacobian matrix. */
iflag = Functor::df(x, fjac);
++njev;
if (iflag < 0)
break;
/* compute the qr factorization of the jacobian. */
/* compute the qr factorization of the jacobian. */
ei_qrfac<Scalar>(n, n, fjac.data(), fjac.rows(), false, iwa, 1, wa1.data(), wa2.data());
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
if (iter == 1) {
if (mode != 2)
@ -100,8 +100,8 @@ int ei_hybrj(
diag[j] = 1.;
}
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
wa3 = diag.cwise() * x;
xnorm = wa3.stableNorm();
@ -110,7 +110,7 @@ int ei_hybrj(
delta = factor;
}
/* form (q transpose)*fvec and store in qtf. */
/* form (q transpose)*fvec and store in qtf. */
qtf = fvec;
for (j = 0; j < n; ++j)
@ -123,7 +123,7 @@ int ei_hybrj(
qtf[i] += fjac(i,j) * temp;
}
/* copy the triangular factor of the qr factorization into r. */
/* copy the triangular factor of the qr factorization into r. */
sing = false;
for (j = 0; j < n; ++j) {
@ -138,20 +138,20 @@ int ei_hybrj(
sing = true;
}
/* accumulate the orthogonal factor in fjac. */
/* accumulate the orthogonal factor in fjac. */
ei_qform<Scalar>(n, n, fjac.data(), fjac.rows(), wa1.data());
/* rescale if necessary. */
/* rescale if necessary. */
/* Computing MAX */
if (mode != 2)
diag = diag.cwise().max(wa2);
/* beginning of the inner loop. */
/* beginning of the inner loop. */
while (true) {
/* if requested, call Functor::f to enable printing of iterates. */
/* if requested, call Functor::f to enable printing of iterates. */
if (nprint > 0) {
iflag = 0;
@ -161,23 +161,23 @@ int ei_hybrj(
goto L300;
}
/* determine the direction p. */
/* determine the direction p. */
ei_dogleg<Scalar>(R, diag, qtf, delta, wa1);
/* store the direction p and x + p. calculate the norm of p. */
/* store the direction p and x + p. calculate the norm of p. */
wa1 = -wa1;
wa2 = x + wa1;
wa3 = diag.cwise() * wa1;
pnorm = wa3.stableNorm();
/* on the first iteration, adjust the initial step bound. */
/* on the first iteration, adjust the initial step bound. */
if (iter == 1)
delta = std::min(delta,pnorm);
/* evaluate the function at x + p and calculate its norm. */
/* evaluate the function at x + p and calculate its norm. */
iflag = Functor::f(wa2, wa4);
++nfev;
@ -185,13 +185,13 @@ int ei_hybrj(
goto L300;
fnorm1 = wa4.stableNorm();
/* compute the scaled actual reduction. */
/* compute the scaled actual reduction. */
actred = -1.;
if (fnorm1 < fnorm) /* Computing 2nd power */
actred = 1. - ei_abs2(fnorm1 / fnorm);
/* compute the scaled predicted reduction. */
/* compute the scaled predicted reduction. */
l = 0;
for (i = 0; i < n; ++i) {
@ -207,14 +207,14 @@ int ei_hybrj(
if (temp < fnorm) /* Computing 2nd power */
prered = 1. - ei_abs2(temp / fnorm);
/* compute the ratio of the actual to the predicted */
/* reduction. */
/* compute the ratio of the actual to the predicted */
/* reduction. */
ratio = 0.;
if (prered > 0.)
ratio = actred / prered;
/* update the step bound. */
/* update the step bound. */
if (ratio < Scalar(.1)) {
ncsuc = 0;
@ -230,10 +230,10 @@ int ei_hybrj(
}
}
/* test for successful iteration. */
/* test for successful iteration. */
if (ratio >= Scalar(1e-4)) {
/* successful iteration. update x, fvec, and their norms. */
/* successful iteration. update x, fvec, and their norms. */
x = wa2;
wa2 = diag.cwise() * x;
fvec = wa4;
@ -242,7 +242,7 @@ int ei_hybrj(
++iter;
}
/* determine the progress of the iteration. */
/* determine the progress of the iteration. */
++nslow1;
if (actred >= Scalar(.001))
@ -252,14 +252,14 @@ int ei_hybrj(
if (actred >= Scalar(.1))
nslow2 = 0;
/* test for convergence. */
/* test for convergence. */
if (delta <= xtol * xnorm || fnorm == 0.)
info = 1;
if (info != 0)
goto L300;
/* tests for termination and stringent tolerances. */
/* tests for termination and stringent tolerances. */
if (nfev >= maxfev)
info = 2;
@ -273,13 +273,13 @@ int ei_hybrj(
if (info != 0)
goto L300;
/* criterion for recalculating jacobian. */
/* criterion for recalculating jacobian. */
if (ncfail == 2)
break;
/* calculate the rank one modification to the jacobian */
/* and update qtf if necessary. */
/* calculate the rank one modification to the jacobian */
/* and update qtf if necessary. */
for (j = 0; j < n; ++j) {
sum = wa4.dot(fjac.col(j));
@ -289,17 +289,17 @@ int ei_hybrj(
qtf[j] = sum;
}
/* compute the qr factorization of the updated jacobian. */
/* compute the qr factorization of the updated jacobian. */
ei_r1updt<Scalar>(n, n, R.data(), R.size(), wa1.data(), wa2.data(), wa3.data(), &sing);
ei_r1mpyq<Scalar>(n, n, fjac.data(), fjac.rows(), wa2.data(), wa3.data());
ei_r1mpyq<Scalar>(1, n, qtf.data(), 1, wa2.data(), wa3.data());
/* end of the inner loop. */
/* end of the inner loop. */
jeval = false;
}
/* end of the outer loop. */
/* end of the outer loop. */
}
L300:
/* termination, either normal or user imposed. */

55
unsupported/Eigen/src/NonLinear/lmder.h
View File

@ -46,8 +46,7 @@ int ei_lmder(
/* check the input parameters for errors. */
if (n <= 0 || m < n || ftol < 0. || xtol < 0. ||
gtol < 0. || maxfev <= 0 || factor <= 0.)
if (n <= 0 || m < n || ftol < 0. || xtol < 0. || gtol < 0. || maxfev <= 0 || factor <= 0.)
goto L300;
if (mode == 2)
@ -70,16 +69,16 @@ int ei_lmder(
/* beginning of the outer loop. */
while(true) {
while (true) {
/* calculate the jacobian matrix. */
/* calculate the jacobian matrix. */
iflag = Functor::df(x, fjac);
++njev;
if (iflag < 0)
break;
/* if requested, call Functor::f to enable printing of iterates. */
/* if requested, call Functor::f to enable printing of iterates. */
if (nprint > 0) {
iflag = 0;
@ -89,13 +88,13 @@ int ei_lmder(
break;
}
/* compute the qr factorization of the jacobian. */
/* compute the qr factorization of the jacobian. */
ei_qrfac<Scalar>(m, n, fjac.data(), fjac.rows(), true, ipvt.data(), n, wa1.data(), wa2.data());
ipvt.cwise()-=1; // qrfac() creates ipvt with fortran convetion (1->n), convert it to c (0->n-1)
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
if (iter == 1) {
if (mode != 2)
@ -104,8 +103,10 @@ int ei_lmder(
if (wa2[j] == 0.)
diag[j] = 1.;
}
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
wa3 = diag.cwise() * x;
xnorm = wa3.stableNorm();
delta = factor * xnorm;
@ -113,8 +114,8 @@ int ei_lmder(
delta = factor;
}
/* form (q transpose)*fvec and store the first n components in */
/* qtf. */
/* form (q transpose)*fvec and store the first n components in */
/* qtf. */
wa4 = fvec;
for (j = 0; j < n; ++j) {
@ -130,7 +131,7 @@ int ei_lmder(
qtf[j] = wa4[j];
}
/* compute the norm of the scaled gradient. */
/* compute the norm of the scaled gradient. */
gnorm = 0.;
if (fnorm != 0.)
@ -145,21 +146,21 @@ int ei_lmder(
}
}
/* test for convergence of the gradient norm. */
/* test for convergence of the gradient norm. */
if (gnorm <= gtol) {
if (gnorm <= gtol)
info = 4;
}
if (info != 0)
break;
/* rescale if necessary. */
/* rescale if necessary. */
if (mode != 2) /* Computing MAX */
diag = diag.cwise().max(wa2);
/* beginning of the inner loop. */
/* beginning of the inner loop. */
do {
/* determine the levenberg-marquardt parameter. */
ei_lmpar<Scalar>(fjac, ipvt, diag, qtf, delta, par, wa1, wa2);
@ -173,9 +174,8 @@ int ei_lmder(
/* on the first iteration, adjust the initial step bound. */
if (iter == 1) {
if (iter == 1)
delta = std::min(delta,pnorm);
}
/* evaluate the function at x + p and calculate its norm. */
@ -198,9 +198,8 @@ int ei_lmder(
for (j = 0; j < n; ++j) {
l = ipvt[j];
temp = wa1[l];
for (i = 0; i <= j; ++i) {
for (i = 0; i <= j; ++i)
wa3[i] += fjac(i,j) * temp;
}
}
temp1 = ei_abs2(wa3.stableNorm() / fnorm);
temp2 = ei_abs2(ei_sqrt(par) * pnorm / fnorm);
@ -227,12 +226,9 @@ int ei_lmder(
/* Computing MIN */
delta = temp * std::min(delta, pnorm / Scalar(.1));
par /= temp;
}
else {
if (!(par != 0. && ratio < Scalar(.75))) {
delta = pnorm / Scalar(.5);
par = Scalar(.5) * par;
}
} else if (!(par != 0. && ratio < Scalar(.75))) {
delta = pnorm / Scalar(.5);
par = Scalar(.5) * par;
}
/* test for successful iteration. */
@ -272,12 +268,11 @@ int ei_lmder(
goto L300;
/* end of the inner loop. repeat if iteration unsuccessful. */
} while (ratio < Scalar(1e-4));
/* end of the outer loop. */
/* end of the outer loop. */
}
L300:
/* termination, either normal or user imposed. */
if (iflag < 0)
info = iflag;
if (nprint > 0)

458
unsupported/Eigen/src/NonLinear/lmdif.h
View File

@ -45,10 +45,8 @@ int ei_lmdif(
/* check the input parameters for errors. */
if (n <= 0 || m < n || ftol < 0. || xtol < 0. ||
gtol < 0. || maxfev <= 0 || factor <= 0.) {
if (n <= 0 || m < n || ftol < 0. || xtol < 0. || gtol < 0. || maxfev <= 0 || factor <= 0.)
goto L300;
}
if (mode == 2)
for (j = 0; j < n; ++j)
if (diag[j] <= 0.) goto L300;
@ -58,9 +56,8 @@ int ei_lmdif(
iflag = Functor::f(x, fvec);
nfev = 1;
if (iflag < 0) {
if (iflag < 0)
goto L300;
}
fnorm = fvec.stableNorm();
/* initialize levenberg-marquardt parameter and iteration counter. */
@ -70,283 +67,214 @@ int ei_lmdif(
/* beginning of the outer loop. */
L30:
while (true) {
/* calculate the jacobian matrix. */
/* calculate the jacobian matrix. */
iflag = ei_fdjac2<Functor,Scalar>(x, fvec, fjac, epsfcn, wa4);
nfev += n;
if (iflag < 0) {
goto L300;
}
iflag = ei_fdjac2<Functor,Scalar>(x, fvec, fjac, epsfcn, wa4);
nfev += n;
if (iflag < 0)
break;
/* if requested, call Functor::f to enable printing of iterates. */
/* if requested, call Functor::f to enable printing of iterates. */
if (nprint <= 0) {
goto L40;
}
iflag = 0;
if ((iter - 1) % nprint == 0) {
iflag = Functor::debug(x, fvec);
}
if (iflag < 0) {
goto L300;
}
L40:
/* compute the qr factorization of the jacobian. */
ei_qrfac<Scalar>(m, n, fjac.data(), fjac.rows(), true, ipvt.data(), n, wa1.data(), wa2.data());
ipvt.cwise()-=1; // qrfac() creates ipvt with fortran convetion (1->n), convert it to c (0->n-1)
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
if (iter != 1) {
goto L80;
}
if (mode == 2) {
goto L60;
}
for (j = 0; j < n; ++j) {
diag[j] = wa2[j];
if (wa2[j] == 0.) {
diag[j] = 1.;
if (nprint > 0) {
iflag = 0;
if ((iter - 1) % nprint == 0)
iflag = Functor::debug(x, fvec);
if (iflag < 0)
break;
}
/* L50: */
}
L60:
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
/* compute the qr factorization of the jacobian. */
wa3 = diag.cwise() * x;
xnorm = wa3.stableNorm();
delta = factor * xnorm;
if (delta == 0.) {
delta = factor;
}
L80:
ei_qrfac<Scalar>(m, n, fjac.data(), fjac.rows(), true, ipvt.data(), n, wa1.data(), wa2.data());
ipvt.cwise()-=1; // qrfac() creates ipvt with fortran convetion (1->n), convert it to c (0->n-1)
/* form (q transpose)*fvec and store the first n components in */
/* qtf. */
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
wa4 = fvec;
for (j = 0; j < n; ++j) {
if (fjac(j,j) == 0.) {
goto L120;
if (iter == 1) {
if (mode != 2)
for (j = 0; j < n; ++j) {
diag[j] = wa2[j];
if (wa2[j] == 0.)
diag[j] = 1.;
}
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
wa3 = diag.cwise() * x;
xnorm = wa3.stableNorm();
delta = factor * xnorm;
if (delta == 0.)
delta = factor;
}
sum = 0.;
for (i = j; i < m; ++i) {
sum += fjac(i,j) * wa4[i];
/* L100: */
/* form (q transpose)*fvec and store the first n components in */
/* qtf. */
wa4 = fvec;
for (j = 0; j < n; ++j) {
if (fjac(j,j) != 0.) {
sum = 0.;
for (i = j; i < m; ++i)
sum += fjac(i,j) * wa4[i];
temp = -sum / fjac(j,j);
for (i = j; i < m; ++i)
wa4[i] += fjac(i,j) * temp;
}
fjac(j,j) = wa1[j];
qtf[j] = wa4[j];
}
temp = -sum / fjac(j,j);
for (i = j; i < m; ++i) {
wa4[i] += fjac(i,j) * temp;
/* L110: */
}
L120:
fjac(j,j) = wa1[j];
qtf[j] = wa4[j];
/* L130: */
/* compute the norm of the scaled gradient. */
gnorm = 0.;
if (fnorm != 0.)
for (j = 0; j < n; ++j) {
l = ipvt[j];
if (wa2[l] != 0.) {
sum = 0.;
for (i = 0; i <= j; ++i)
sum += fjac(i,j) * (qtf[i] / fnorm);
/* Computing MAX */
gnorm = std::max(gnorm, ei_abs(sum / wa2[l]));
}
}
/* test for convergence of the gradient norm. */
if (gnorm <= gtol)
info = 4;
if (info != 0)
break;
/* rescale if necessary. */
if (mode != 2) /* Computing MAX */
diag = diag.cwise().max(wa2);
/* beginning of the inner loop. */
do {
/* determine the levenberg-marquardt parameter. */
ei_lmpar<Scalar>(fjac, ipvt, diag, qtf, delta, par, wa1, wa2);
/* store the direction p and x + p. calculate the norm of p. */
wa1 = -wa1;
wa2 = x + wa1;
wa3 = diag.cwise() * wa1;
pnorm = wa3.stableNorm();
/* on the first iteration, adjust the initial step bound. */
if (iter == 1)
delta = std::min(delta,pnorm);
/* evaluate the function at x + p and calculate its norm. */
iflag = Functor::f(wa2, wa4);
++nfev;
if (iflag < 0)
goto L300;
fnorm1 = wa4.stableNorm();
/* compute the scaled actual reduction. */
actred = -1.;
if (Scalar(.1) * fnorm1 < fnorm) /* Computing 2nd power */
actred = 1. - ei_abs2(fnorm1 / fnorm);
/* compute the scaled predicted reduction and */
/* the scaled directional derivative. */
wa3.fill(0.);
for (j = 0; j < n; ++j) {
l = ipvt[j];
temp = wa1[l];
for (i = 0; i <= j; ++i)
wa3[i] += fjac(i,j) * temp;
}
temp1 = ei_abs2(wa3.stableNorm() / fnorm);
temp2 = ei_abs2(ei_sqrt(par) * pnorm / fnorm);
/* Computing 2nd power */
prered = temp1 + temp2 / Scalar(.5);
dirder = -(temp1 + temp2);
/* compute the ratio of the actual to the predicted */
/* reduction. */
ratio = 0.;
if (prered != 0.)
ratio = actred / prered;
/* update the step bound. */
if (ratio <= Scalar(.25)) {
if (actred >= 0.)
temp = Scalar(.5);
if (actred < 0.)
temp = Scalar(.5) * dirder / (dirder + Scalar(.5) * actred);
if (Scalar(.1) * fnorm1 >= fnorm || temp < Scalar(.1))
temp = Scalar(.1);
/* Computing MIN */
delta = temp * std::min(delta, pnorm / Scalar(.1));
par /= temp;
} else if (!(par != 0. && ratio < Scalar(.75))) {
delta = pnorm / Scalar(.5);
par = Scalar(.5) * par;
}
/* test for successful iteration. */
if (ratio >= Scalar(1e-4)) {
/* successful iteration. update x, fvec, and their norms. */
x = wa2;
wa2 = diag.cwise() * x;
fvec = wa4;
xnorm = wa2.stableNorm();
fnorm = fnorm1;
++iter;
}
/* tests for convergence. */
if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1.)
info = 1;
if (delta <= xtol * xnorm)
info = 2;
if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1. && info == 2)
info = 3;
if (info != 0)
goto L300;
/* tests for termination and stringent tolerances. */
if (nfev >= maxfev)
info = 5;
if (ei_abs(actred) <= epsilon<Scalar>() && prered <= epsilon<Scalar>() && Scalar(.5) * ratio <= 1.)
info = 6;
if (delta <= epsilon<Scalar>() * xnorm)
info = 7;
if (gnorm <= epsilon<Scalar>())
info = 8;
if (info != 0)
goto L300;
/* end of the inner loop. repeat if iteration unsuccessful. */
} while (ratio < Scalar(1e-4));
/* end of the outer loop. */
}
/* compute the norm of the scaled gradient. */
gnorm = 0.;
if (fnorm == 0.) {
goto L170;
}
for (j = 0; j < n; ++j) {
l = ipvt[j];
if (wa2[l] != 0.) {
sum = 0.;
for (i = 0; i <= j; ++i)
sum += fjac(i,j) * (qtf[i] / fnorm);
/* Computing MAX */
gnorm = std::max(gnorm, ei_abs(sum / wa2[l]));
}
}
L170:
/* test for convergence of the gradient norm. */
if (gnorm <= gtol) {
info = 4;
}
if (info != 0) {
goto L300;
}
/* rescale if necessary. */
if (mode == 2) {
goto L190;
}
/* Computing MAX */
diag = diag.cwise().max(wa2);
L190:
/* beginning of the inner loop. */
L200:
/* determine the levenberg-marquardt parameter. */
ei_lmpar<Scalar>(fjac, ipvt, diag, qtf, delta, par, wa1, wa2);
/* store the direction p and x + p. calculate the norm of p. */
wa1 = -wa1;
wa2 = x + wa1;
wa3 = diag.cwise() * wa1;
pnorm = wa3.stableNorm();
/* on the first iteration, adjust the initial step bound. */
if (iter == 1) {
delta = std::min(delta,pnorm);
}
/* evaluate the function at x + p and calculate its norm. */
iflag = Functor::f(wa2, wa4);
++nfev;
if (iflag < 0) {
goto L300;
}
fnorm1 = wa4.stableNorm();
/* compute the scaled actual reduction. */
actred = -1.;
if (Scalar(.1) * fnorm1 < fnorm) /* Computing 2nd power */
actred = 1. - ei_abs2(fnorm1 / fnorm);
/* compute the scaled predicted reduction and */
/* the scaled directional derivative. */
wa3.fill(0.);
for (j = 0; j < n; ++j) {
l = ipvt[j];
temp = wa1[l];
for (i = 0; i <= j; ++i) {
wa3[i] += fjac(i,j) * temp;
/* L220: */
}
/* L230: */
}
temp1 = ei_abs2(wa3.stableNorm() / fnorm);
temp2 = ei_abs2(ei_sqrt(par) * pnorm / fnorm);
/* Computing 2nd power */
prered = temp1 + temp2 / Scalar(.5);
dirder = -(temp1 + temp2);
/* compute the ratio of the actual to the predicted */
/* reduction. */
ratio = 0.;
if (prered != 0.) {
ratio = actred / prered;
}
/* update the step bound. */
if (ratio > Scalar(.25)) {
goto L240;
}
if (actred >= 0.) {
temp = Scalar(.5);
}
if (actred < 0.) {
temp = Scalar(.5) * dirder / (dirder + Scalar(.5) * actred);
}
if (Scalar(.1) * fnorm1 >= fnorm || temp < Scalar(.1))
temp = Scalar(.1);
/* Computing MIN */
delta = temp * std::min(delta, pnorm / Scalar(.1));
par /= temp;
goto L260;
L240:
if (par != 0. && ratio < Scalar(.75)) {
goto L250;
}
delta = pnorm / Scalar(.5);
par = Scalar(.5) * par;
L250:
L260:
/* test for successful iteration. */
if (ratio < Scalar(1e-4)) {
goto L290;
}
/* successful iteration. update x, fvec, and their norms. */
x = wa2;
wa2 = diag.cwise() * x;
fvec = wa4;
xnorm = wa2.stableNorm();
fnorm = fnorm1;
++iter;
L290:
/* tests for convergence. */
if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1.) {
info = 1;
}
if (delta <= xtol * xnorm) {
info = 2;
}
if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1. && info
== 2) {
info = 3;
}
if (info != 0) {
goto L300;
}
/* tests for termination and stringent tolerances. */
if (nfev >= maxfev) {
info = 5;
}
if (ei_abs(actred) <= epsilon<Scalar>() && prered <= epsilon<Scalar>() && Scalar(.5) * ratio <= 1.) {
info = 6;
}
if (delta <= epsilon<Scalar>() * xnorm) {
info = 7;
}
if (gnorm <= epsilon<Scalar>()) {
info = 8;
}
if (info != 0) {
goto L300;
}
/* end of the inner loop. repeat if iteration unsuccessful. */
if (ratio < Scalar(1e-4)) {
goto L200;
}
/* end of the outer loop. */
goto L30;
L300:
/* termination, either normal or user imposed. */
if (iflag < 0) {
if (iflag < 0)
info = iflag;
}
iflag = 0;
if (nprint > 0) {
if (nprint > 0)
iflag = Functor::debug(x, fvec);
}
return info;
}

490
unsupported/Eigen/src/NonLinear/lmstr.h
View File

@ -46,22 +46,19 @@ int ei_lmstr(
/* check the input parameters for errors. */
if (n <= 0 || m < n || ftol < 0. || xtol < 0. ||
gtol < 0. || maxfev <= 0 || factor <= 0.) {
if (n <= 0 || m < n || ftol < 0. || xtol < 0. || gtol < 0. || maxfev <= 0 || factor <= 0.)
goto L340;
}
if (mode == 2)
for (j = 0; j < n; ++j)
if (diag[j] <= 0.) goto L300;
if (diag[j] <= 0.) goto L340;
/* evaluate the function at the starting point */
/* and calculate its norm. */
iflag = Functor::f(x, fvec);
nfev = 1;
if (iflag < 0) {
if (iflag < 0)
goto L340;
}
fnorm = fvec.stableNorm();
/* initialize levenberg-marquardt parameter and iteration counter. */
@ -71,297 +68,230 @@ int ei_lmstr(
/* beginning of the outer loop. */
L30:
while (true) {
/* if requested, call Functor::f to enable printing of iterates. */
/* if requested, call Functor::f to enable printing of iterates. */
if (nprint <= 0) {
goto L40;
}
iflag = 0;
if ((iter - 1) % nprint == 0) {
iflag = Functor::debug(x, fvec, wa3);
}
if (iflag < 0) {
goto L340;
}
L40:
/* compute the qr factorization of the jacobian matrix */
/* calculated one row at a time, while simultaneously */
/* forming (q transpose)*fvec and storing the first */
/* n components in qtf. */
qtf.fill(0.);
fjac.fill(0.);
iflag = 2;
for (i = 0; i < m; ++i) {
if (Functor::df(x, wa3, iflag) < 0)
goto L340;
temp = fvec[i];
ei_rwupdt<Scalar>(n, fjac.data(), fjac.rows(), wa3.data(), qtf.data(), &temp, wa1.data(), wa2.data());
++iflag;
}
++njev;
/* if the jacobian is rank deficient, call qrfac to */
/* reorder its columns and update the components of qtf. */
sing = false;
for (j = 0; j < n; ++j) {
if (fjac(j,j) == 0.) {
sing = true;
if (nprint > 0) {
iflag = 0;
if ((iter - 1) % nprint == 0)
iflag = Functor::debug(x, fvec, wa3);
if (iflag < 0)
break;
}
ipvt[j] = j;
wa2[j] = fjac.col(j).start(j).stableNorm();
}
if (! sing)
goto L130;
ipvt.cwise()+=1;
ei_qrfac<Scalar>(n, n, fjac.data(), fjac.rows(), true, ipvt.data(), n, wa1.data(), wa2.data());
ipvt.cwise()-=1; // qrfac() creates ipvt with fortran convetion (1->n), convert it to c (0->n-1)
for (j = 0; j < n; ++j) {
if (fjac(j,j) == 0.)
goto L110;
sum = 0.;
for (i = j; i < n; ++i) {
sum += fjac(i,j) * qtf[i];
/* compute the qr factorization of the jacobian matrix */
/* calculated one row at a time, while simultaneously */
/* forming (q transpose)*fvec and storing the first */
/* n components in qtf. */
qtf.fill(0.);
fjac.fill(0.);
iflag = 2;
for (i = 0; i < m; ++i) {
if (Functor::df(x, wa3, iflag) < 0)
break;
temp = fvec[i];
ei_rwupdt<Scalar>(n, fjac.data(), fjac.rows(), wa3.data(), qtf.data(), &temp, wa1.data(), wa2.data());
++iflag;
}
temp = -sum / fjac(j,j);
for (i = j; i < n; ++i) {
qtf[i] += fjac(i,j) * temp;
++njev;
/* if the jacobian is rank deficient, call qrfac to */
/* reorder its columns and update the components of qtf. */
sing = false;
for (j = 0; j < n; ++j) {
if (fjac(j,j) == 0.) {
sing = true;
}
ipvt[j] = j;
wa2[j] = fjac.col(j).start(j).stableNorm();
}
L110:
fjac(j,j) = wa1[j];
/* L120: */
}
L130:
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
if (iter != 1) {
goto L170;
}
if (mode == 2) {
goto L150;
}
for (j = 0; j < n; ++j) {
diag[j] = wa2[j];
if (wa2[j] == 0.) {
diag[j] = 1.;
if (sing) {
ipvt.cwise()+=1;
ei_qrfac<Scalar>(n, n, fjac.data(), fjac.rows(), true, ipvt.data(), n, wa1.data(), wa2.data());
ipvt.cwise()-=1; // qrfac() creates ipvt with fortran convetion (1->n), convert it to c (0->n-1)
for (j = 0; j < n; ++j) {
if (fjac(j,j) != 0.) {
sum = 0.;
for (i = j; i < n; ++i)
sum += fjac(i,j) * qtf[i];
temp = -sum / fjac(j,j);
for (i = j; i < n; ++i)
qtf[i] += fjac(i,j) * temp;
}
fjac(j,j) = wa1[j];
}
}
/* L140: */
}
L150:
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
/* on the first iteration and if mode is 1, scale according */
/* to the norms of the columns of the initial jacobian. */
wa3 = diag.cwise() * x;
xnorm = wa3.stableNorm();
delta = factor * xnorm;
if (delta == 0.) {
delta = factor;
}
L170:
if (iter == 1) {
if (mode != 2)
for (j = 0; j < n; ++j) {
diag[j] = wa2[j];
if (wa2[j] == 0.)
diag[j] = 1.;
}
/* compute the norm of the scaled gradient. */
/* on the first iteration, calculate the norm of the scaled x */
/* and initialize the step bound delta. */
gnorm = 0.;
if (fnorm == 0.) {
goto L210;
}
for (j = 0; j < n; ++j) {
l = ipvt[j];
if (wa2[l] != 0.) {
sum = 0.;
for (i = 0; i <= j; ++i)
sum += fjac(i,j) * (qtf[i] / fnorm);
/* Computing MAX */
gnorm = std::max(gnorm, ei_abs(sum / wa2[l]));
wa3 = diag.cwise() * x;
xnorm = wa3.stableNorm();
delta = factor * xnorm;
if (delta == 0.)
delta = factor;
}
/* compute the norm of the scaled gradient. */
gnorm = 0.;
if (fnorm != 0.)
for (j = 0; j < n; ++j) {
l = ipvt[j];
if (wa2[l] != 0.) {
sum = 0.;
for (i = 0; i <= j; ++i)
sum += fjac(i,j) * (qtf[i] / fnorm);
/* Computing MAX */
gnorm = std::max(gnorm, ei_abs(sum / wa2[l]));
}
}
/* test for convergence of the gradient norm. */
if (gnorm <= gtol)
info = 4;
if (info != 0)
break;
/* rescale if necessary. */
if (mode != 2) /* Computing MAX */
diag = diag.cwise().max(wa2);
/* beginning of the inner loop. */
do {
/* determine the levenberg-marquardt parameter. */
ei_lmpar<Scalar>(fjac, ipvt, diag, qtf, delta, par, wa1, wa2);
/* store the direction p and x + p. calculate the norm of p. */
wa1 = -wa1;
wa2 = x + wa1;
wa3 = diag.cwise() * wa1;
pnorm = wa3.stableNorm();
/* on the first iteration, adjust the initial step bound. */
if (iter == 1)
delta = std::min(delta,pnorm);
/* evaluate the function at x + p and calculate its norm. */
iflag = Functor::f(wa2, wa4);
++nfev;
if (iflag < 0)
goto L340;
fnorm1 = wa4.stableNorm();
/* compute the scaled actual reduction. */
actred = -1.;
if (Scalar(.1) * fnorm1 < fnorm) /* Computing 2nd power */
actred = 1. - ei_abs2(fnorm1 / fnorm);
/* compute the scaled predicted reduction and */
/* the scaled directional derivative. */
wa3.fill(0.);
for (j = 0; j < n; ++j) {
l = ipvt[j];
temp = wa1[l];
for (i = 0; i <= j; ++i)
wa3[i] += fjac(i,j) * temp;
}
temp1 = ei_abs2(wa3.stableNorm() / fnorm);
temp2 = ei_abs2(ei_sqrt(par) * pnorm / fnorm);
/* Computing 2nd power */
prered = temp1 + temp2 / Scalar(.5);
dirder = -(temp1 + temp2);
/* compute the ratio of the actual to the predicted */
/* reduction. */
ratio = 0.;
if (prered != 0.)
ratio = actred / prered;
/* update the step bound. */
if (ratio <= Scalar(.25)) {
if (actred >= 0.)
temp = Scalar(.5);
if (actred < 0.)
temp = Scalar(.5) * dirder / (dirder + Scalar(.5) * actred);
if (Scalar(.1) * fnorm1 >= fnorm || temp < Scalar(.1))
temp = Scalar(.1);
/* Computing MIN */
delta = temp * std::min(delta, pnorm / Scalar(.1));
par /= temp;
} else if (!(par != 0. && ratio < Scalar(.75))) {
delta = pnorm / Scalar(.5);
par = Scalar(.5) * par;
}
/* test for successful iteration. */
if (ratio >= Scalar(1e-4)) {
/* successful iteration. update x, fvec, and their norms. */
x = wa2;
wa2 = diag.cwise() * x;
fvec = wa4;
xnorm = wa2.stableNorm();
fnorm = fnorm1;
++iter;
}
/* tests for convergence. */
if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1.)
info = 1;
if (delta <= xtol * xnorm)
info = 2;
if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1. && info == 2)
info = 3;
if (info != 0)
goto L340;
/* tests for termination and stringent tolerances. */
if (nfev >= maxfev)
info = 5;
if (ei_abs(actred) <= epsilon<Scalar>() && prered <= epsilon<Scalar>() && Scalar(.5) * ratio <= 1.)
info = 6;
if (delta <= epsilon<Scalar>() * xnorm)
info = 7;
if (gnorm <= epsilon<Scalar>())
info = 8;
if (info != 0)
goto L340;
/* end of the inner loop. repeat if iteration unsuccessful. */
} while (ratio < Scalar(1e-4));
/* end of the outer loop. */
}
L210:
/* test for convergence of the gradient norm. */
if (gnorm <= gtol) {
info = 4;
}
if (info != 0) {
goto L340;
}
/* rescale if necessary. */
if (mode == 2) {
goto L230;
}
/* Computing MAX */
diag = diag.cwise().max(wa2);
L230:
/* beginning of the inner loop. */
L240:
/* determine the levenberg-marquardt parameter. */
ei_lmpar<Scalar>(fjac, ipvt, diag, qtf, delta, par, wa1, wa2);
/* store the direction p and x + p. calculate the norm of p. */
wa1 = -wa1;
wa2 = x + wa1;
wa3 = diag.cwise() * wa1;
pnorm = wa3.stableNorm();
/* on the first iteration, adjust the initial step bound. */
if (iter == 1) {
delta = std::min(delta,pnorm);
}
/* evaluate the function at x + p and calculate its norm. */
iflag = Functor::f(wa2, wa4);
++nfev;
if (iflag < 0) {
goto L340;
}
fnorm1 = wa4.stableNorm();
/* compute the scaled actual reduction. */
actred = -1.;
if (Scalar(.1) * fnorm1 < fnorm) /* Computing 2nd power */
actred = 1. - ei_abs2(fnorm1 / fnorm);
/* compute the scaled predicted reduction and */
/* the scaled directional derivative. */
wa3.fill(0.);
for (j = 0; j < n; ++j) {
l = ipvt[j];
temp = wa1[l];
for (i = 0; i <= j; ++i) {
wa3[i] += fjac(i,j) * temp;
/* L260: */
}
/* L270: */
}
temp1 = ei_abs2(wa3.stableNorm() / fnorm);
temp2 = ei_abs2(ei_sqrt(par) * pnorm / fnorm);
/* Computing 2nd power */
prered = temp1 + temp2 / Scalar(.5);
dirder = -(temp1 + temp2);
/* compute the ratio of the actual to the predicted */
/* reduction. */
ratio = 0.;
if (prered != 0.) {
ratio = actred / prered;
}
/* update the step bound. */
if (ratio > Scalar(.25)) {
goto L280;
}
if (actred >= 0.) {
temp = Scalar(.5);
}
if (actred < 0.) {
temp = Scalar(.5) * dirder / (dirder + Scalar(.5) * actred);
}
if (Scalar(.1) * fnorm1 >= fnorm || temp < Scalar(.1))
temp = Scalar(.1);
/* Computing MIN */
delta = temp * std::min(delta, pnorm / Scalar(.1));
par /= temp;
goto L300;
L280:
if (par != 0. && ratio < Scalar(.75)) {
goto L290;
}
delta = pnorm / Scalar(.5);
par = Scalar(.5) * par;
L290:
L300:
/* test for successful iteration. */
if (ratio < Scalar(1e-4)) {
goto L330;
}
/* successful iteration. update x, fvec, and their norms. */
x = wa2;
wa2 = diag.cwise() * x;
fvec = wa4;
xnorm = wa2.stableNorm();
fnorm = fnorm1;
++iter;
L330:
/* tests for convergence. */
if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1.) {
info = 1;
}
if (delta <= xtol * xnorm) {
info = 2;
}
if (ei_abs(actred) <= ftol && prered <= ftol && Scalar(.5) * ratio <= 1. && info
== 2) {
info = 3;
}
if (info != 0) {
goto L340;
}
/* tests for termination and stringent tolerances. */
if (nfev >= maxfev) {
info = 5;
}
if (ei_abs(actred) <= epsilon<Scalar>() && prered <= epsilon<Scalar>() && Scalar(.5) * ratio <= 1.) {
info = 6;
}
if (delta <= epsilon<Scalar>() * xnorm) {
info = 7;
}
if (gnorm <= epsilon<Scalar>()) {
info = 8;
}
if (info != 0) {
goto L340;
}
/* end of the inner loop. repeat if iteration unsuccessful. */
if (ratio < Scalar(1e-4)) {
goto L240;
}
/* end of the outer loop. */
goto L30;
L340:
/* termination, either normal or user imposed. */
if (iflag < 0) {
if (iflag < 0)
info = iflag;
}
iflag = 0;
if (nprint > 0) {
if (nprint > 0)
iflag = Functor::debug(x, fvec, wa3);
}
return info;
}