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further cleaning/ goto removing
This commit is contained in:
Thomas Capricelli
parent
92a5bb4539
commit
312ab1abb3
@ -20,7 +20,7 @@ void ei_dogleg(
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assert(n==qtb.size());
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assert(n==x.size());
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/* first, calculate the gauss-newton direction. */
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/* first, calculate the gauss-newton direction. */
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jj = n * (n + 1) / 2;
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for (k = 0; k < n; ++k) {
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@ -39,17 +39,15 @@ void ei_dogleg(
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/* Computing MAX */
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temp = std::max(temp,ei_abs(r[l]));
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l = l + n - i;
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/* L30: */
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}
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temp = epsmch * temp;
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if (temp == 0.) {
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if (temp == 0.)
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temp = epsmch;
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}
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}
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x[j] = (qtb[j] - sum) / temp;
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}
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/* test whether the gauss-newton direction is acceptable. */
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/* test whether the gauss-newton direction is acceptable. */
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wa1.fill(0.);
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wa2 = diag.cwise() * x;
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@ -57,8 +55,8 @@ void ei_dogleg(
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if (qnorm <= delta)
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return;
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/* the gauss-newton direction is not acceptable. */
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/* next, calculate the scaled gradient direction. */
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/* the gauss-newton direction is not acceptable. */
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/* next, calculate the scaled gradient direction. */
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l = 0;
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for (j = 0; j < n; ++j) {
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@ -70,17 +68,17 @@ void ei_dogleg(
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wa1[j] /= diag[j];
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}
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/* calculate the norm of the scaled gradient and test for */
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/* the special case in which the scaled gradient is zero. */
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/* calculate the norm of the scaled gradient and test for */
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/* the special case in which the scaled gradient is zero. */
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gnorm = wa1.stableNorm();
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sgnorm = 0.;
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alpha = delta / qnorm;
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if (gnorm == 0.)
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goto L120;
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goto algo_end;
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/* calculate the point along the scaled gradient */
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/* at which the quadratic is minimized. */
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/* calculate the point along the scaled gradient */
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/* at which the quadratic is minimized. */
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wa1.cwise() /= diag*gnorm;
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l = 0;
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@ -97,16 +95,15 @@ void ei_dogleg(
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temp = wa2.stableNorm();
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sgnorm = gnorm / temp / temp;
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/* test whether the scaled gradient direction is acceptable. */
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/* test whether the scaled gradient direction is acceptable. */
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alpha = 0.;
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if (sgnorm >= delta) {
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goto L120;
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}
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if (sgnorm >= delta)
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goto algo_end;
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/* the scaled gradient direction is not acceptable. */
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/* finally, calculate the point along the dogleg */
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/* at which the quadratic is minimized. */
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/* the scaled gradient direction is not acceptable. */
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/* finally, calculate the point along the dogleg */
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/* at which the quadratic is minimized. */
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bnorm = qtb.stableNorm();
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temp = bnorm / gnorm * (bnorm / qnorm) * (sgnorm / delta);
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@ -114,10 +111,10 @@ void ei_dogleg(
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temp = temp - delta / qnorm * ei_abs2(sgnorm / delta) + ei_sqrt(ei_abs2(temp - delta / qnorm) + (1.-ei_abs2(delta / qnorm)) * (1.-ei_abs2(sgnorm / delta)));
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/* Computing 2nd power */
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alpha = delta / qnorm * (1. - ei_abs2(sgnorm / delta)) / temp;
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L120:
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algo_end:
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/* form appropriate convex combination of the gauss-newton */
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/* direction and the scaled gradient direction. */
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/* form appropriate convex combination of the gauss-newton */
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/* direction and the scaled gradient direction. */
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temp = (1.-alpha) * std::min(sgnorm,delta);
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x = temp * wa1 + alpha * x;
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@ -30,8 +30,8 @@ void ei_lmpar(
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Matrix< Scalar, Dynamic, 1 > wa1(n), wa2(n);
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/* compute and store in x the gauss-newton direction. if the */
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/* jacobian is rank-deficient, obtain a least squares solution. */
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/* compute and store in x the gauss-newton direction. if the */
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/* jacobian is rank-deficient, obtain a least squares solution. */
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nsing = n-1;
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for (j = 0; j < n; ++j) {
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@ -54,39 +54,40 @@ void ei_lmpar(
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x[l] = wa1[j];
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}
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/* initialize the iteration counter. */
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/* evaluate the function at the origin, and test */
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/* for acceptance of the gauss-newton direction. */
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/* initialize the iteration counter. */
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/* evaluate the function at the origin, and test */
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/* for acceptance of the gauss-newton direction. */
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iter = 0;
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wa2 = diag.cwise() * x;
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dxnorm = wa2.blueNorm();
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fp = dxnorm - delta;
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if (fp <= Scalar(0.1) * delta)
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goto L220;
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if (fp <= Scalar(0.1) * delta) {
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par = 0;
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return;
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}
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/* if the jacobian is not rank deficient, the newton */
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/* step provides a lower bound, parl, for the zero of */
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/* the function. otherwise set this bound to zero. */
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/* if the jacobian is not rank deficient, the newton */
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/* step provides a lower bound, parl, for the zero of */
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/* the function. otherwise set this bound to zero. */
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parl = 0.;
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if (nsing < n-1)
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goto L120;
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for (j = 0; j < n; ++j) {
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l = ipvt[j];
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wa1[j] = diag[l] * (wa2[l] / dxnorm);
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if (nsing >= n-1) {
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for (j = 0; j < n; ++j) {
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l = ipvt[j];
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wa1[j] = diag[l] * (wa2[l] / dxnorm);
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}
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for (j = 0; j < n; ++j) {
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sum = 0.;
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for (i = 0; i < j; ++i)
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sum += r(i,j) * wa1[i];
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wa1[j] = (wa1[j] - sum) / r(j,j);
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}
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temp = wa1.blueNorm();
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parl = fp / delta / temp / temp;
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}
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for (j = 0; j < n; ++j) {
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sum = 0.;
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for (i = 0; i < j; ++i)
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sum += r(i,j) * wa1[i];
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wa1[j] = (wa1[j] - sum) / r(j,j);
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}
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temp = wa1.blueNorm();
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parl = fp / delta / temp / temp;
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L120:
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/* calculate an upper bound, paru, for the zero of the function. */
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/* calculate an upper bound, paru, for the zero of the function. */
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for (j = 0; j < n; ++j) {
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sum = 0.;
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@ -97,89 +98,82 @@ L120:
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}
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gnorm = wa1.stableNorm();
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paru = gnorm / delta;
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if (paru == 0.) {
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if (paru == 0.)
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paru = dwarf / std::min(delta,Scalar(0.1));
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}
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/* if the input par lies outside of the interval (parl,paru), */
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/* set par to the closer endpoint. */
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/* if the input par lies outside of the interval (parl,paru), */
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/* set par to the closer endpoint. */
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par = std::max(par,parl);
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par = std::min(par,paru);
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if (par == 0.)
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par = gnorm / dxnorm;
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/* beginning of an iteration. */
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/* beginning of an iteration. */
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L150:
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++iter;
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while (true) {
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++iter;
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/* evaluate the function at the current value of par. */
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/* evaluate the function at the current value of par. */
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if (par == 0.)
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par = std::max(dwarf,Scalar(.001) * paru); /* Computing MAX */
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if (par == 0.)
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par = std::max(dwarf,Scalar(.001) * paru); /* Computing MAX */
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temp = ei_sqrt(par);
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wa1 = temp * diag;
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temp = ei_sqrt(par);
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wa1 = temp * diag;
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ipvt.cwise()+=1; // qrsolv() expects the fortran convention (as qrfac provides)
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ei_qrsolv<Scalar>(n, r.data(), r.rows(), ipvt.data(), wa1.data(), qtb.data(), x.data(), sdiag.data(), wa2.data());
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ipvt.cwise()-=1;
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ipvt.cwise()+=1; // qrsolv() expects the fortran convention (as qrfac provides)
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ei_qrsolv<Scalar>(n, r.data(), r.rows(), ipvt.data(), wa1.data(), qtb.data(), x.data(), sdiag.data(), wa2.data());
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ipvt.cwise()-=1;
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wa2 = diag.cwise() * x;
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dxnorm = wa2.blueNorm();
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temp = fp;
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fp = dxnorm - delta;
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wa2 = diag.cwise() * x;
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dxnorm = wa2.blueNorm();
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temp = fp;
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fp = dxnorm - delta;
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/* if the function is small enough, accept the current value */
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/* of par. also test for the exceptional cases where parl */
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/* is zero or the number of iterations has reached 10. */
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/* if the function is small enough, accept the current value */
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/* of par. also test for the exceptional cases where parl */
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/* is zero or the number of iterations has reached 10. */
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if (ei_abs(fp) <= Scalar(0.1) * delta || (parl == 0. && fp <= temp && temp < 0.) || iter == 10)
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break;
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/* compute the newton correction. */
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for (j = 0; j < n; ++j) {
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l = ipvt[j];
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wa1[j] = diag[l] * (wa2[l] / dxnorm);
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/* L180: */
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}
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for (j = 0; j < n; ++j) {
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wa1[j] /= sdiag[j];
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temp = wa1[j];
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for (i = j+1; i < n; ++i)
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wa1[i] -= r(i,j) * temp;
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}
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temp = wa1.blueNorm();
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parc = fp / delta / temp / temp;
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/* depending on the sign of the function, update parl or paru. */
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if (fp > 0.)
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parl = std::max(parl,par);
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if (fp < 0.)
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paru = std::min(paru,par);
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/* compute an improved estimate for par. */
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/* Computing MAX */
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par = std::max(parl,par+parc);
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/* end of an iteration. */
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if (ei_abs(fp) <= Scalar(0.1) * delta || (parl == 0. && fp <= temp && temp < 0.) ||
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iter == 10) {
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goto L220;
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}
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/* compute the newton correction. */
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/* termination. */
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for (j = 0; j < n; ++j) {
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l = ipvt[j];
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wa1[j] = diag[l] * (wa2[l] / dxnorm);
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/* L180: */
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}
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for (j = 0; j < n; ++j) {
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wa1[j] /= sdiag[j];
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temp = wa1[j];
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for (i = j+1; i < n; ++i)
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wa1[i] -= r(i,j) * temp;
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}
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temp = wa1.blueNorm();
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parc = fp / delta / temp / temp;
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/* depending on the sign of the function, update parl or paru. */
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if (fp > 0.) {
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parl = std::max(parl,par);
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}
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if (fp < 0.) {
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paru = std::min(paru,par);
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}
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/* compute an improved estimate for par. */
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/* Computing MAX */
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par = std::max(parl,par+parc);
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/* end of an iteration. */
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goto L150;
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L220:
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/* termination. */
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if (iter == 0) {
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if (iter == 0)
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par = 0.;
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}
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return;
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}
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