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eigenization of ei_r1updt()

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This commit is contained in:
Thomas Capricelli 2010-01-28 04:28:52 +01:00
parent 40eac2d8a0
commit 27cf1b3a97
2 changed files with 48 additions and 47 deletions
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4
unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
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@ -359,7 +359,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
wa2 = (wa2-wa3)/pnorm; wa2 = (wa2-wa3)/pnorm;
/* compute the qr factorization of the updated jacobian. */ /* compute the qr factorization of the updated jacobian. */
ei_r1updt<Scalar>(R, wa1.data(), v_givens, w_givens, wa2.data(), wa3.data(), &sing); ei_r1updt<Scalar>(R, wa1, v_givens, w_givens, wa2, wa3, &sing);
ei_r1mpyq<Scalar>(n, n, fjac.data(), v_givens, w_givens); ei_r1mpyq<Scalar>(n, n, fjac.data(), v_givens, w_givens);
ei_r1mpyq<Scalar>(1, n, qtf.data(), v_givens, w_givens); ei_r1mpyq<Scalar>(1, n, qtf.data(), v_givens, w_givens);
@ -608,7 +608,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
wa2 = (wa2-wa3)/pnorm; wa2 = (wa2-wa3)/pnorm;
/* compute the qr factorization of the updated jacobian. */ /* compute the qr factorization of the updated jacobian. */
ei_r1updt<Scalar>(R, wa1.data(), v_givens, w_givens, wa2.data(), wa3.data(), &sing); ei_r1updt<Scalar>(R, wa1, v_givens, w_givens, wa2, wa3, &sing);
ei_r1mpyq<Scalar>(n, n, fjac.data(), v_givens, w_givens); ei_r1mpyq<Scalar>(n, n, fjac.data(), v_givens, w_givens);
ei_r1mpyq<Scalar>(1, n, qtf.data(), v_givens, w_givens); ei_r1mpyq<Scalar>(1, n, qtf.data(), v_givens, w_givens);

91
unsupported/Eigen/src/NonLinearOptimization/r1updt.h
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@ -1,9 +1,13 @@
template <typename Scalar> template <typename Scalar>
void ei_r1updt(Matrix< Scalar, Dynamic, Dynamic > &s, const Scalar *u, void ei_r1updt(
Matrix< Scalar, Dynamic, Dynamic > &s,
const Matrix< Scalar, Dynamic, 1> &u,
std::vector<PlanarRotation<Scalar> > &v_givens, std::vector<PlanarRotation<Scalar> > &v_givens,
std::vector<PlanarRotation<Scalar> > &w_givens, std::vector<PlanarRotation<Scalar> > &w_givens,
Scalar *v, Scalar *w, bool *sing) Matrix< Scalar, Dynamic, 1> &v,
Matrix< Scalar, Dynamic, 1> &w,
bool *sing)
{ {
/* Local variables */ /* Local variables */
const int m = s.rows(); const int m = s.rows();
@ -15,71 +19,68 @@ void ei_r1updt(Matrix< Scalar, Dynamic, Dynamic > &s, const Scalar *u,
// ei_r1updt had a broader usecase, but we dont use it here. And, more // ei_r1updt had a broader usecase, but we dont use it here. And, more
// importantly, we can not test it. // importantly, we can not test it.
assert(m==n); assert(m==n);
assert(u.size()==m);
assert(v.size()==n);
assert(w.size()==n);
/* Parameter adjustments */ /* move the nontrivial part of the last column of s into w. */
--w; w[n-1] = s(n-1,n-1);
--u;
--v;
/* move the nontrivial part of the last column of s into w. */ /* rotate the vector v into a multiple of the n-th unit vector */
w[n] = s(n-1,n-1); /* in such a way that a spike is introduced into w. */
for (j=n-2; j>=0; --j) {
/* rotate the vector v into a multiple of the n-th unit vector */
/* in such a way that a spike is introduced into w. */
for (j=n-1; j>=1; --j) {
w[j] = 0.; w[j] = 0.;
if (v[j] != 0.) { if (v[j] != 0.) {
/* determine a givens rotation which eliminates the */ /* determine a givens rotation which eliminates the */
/* j-th element of v. */ /* j-th element of v. */
givens.makeGivens(-v[n], v[j]); givens.makeGivens(-v[n-1], v[j]);
/* apply the transformation to v and store the information */ /* apply the transformation to v and store the information */
/* necessary to recover the givens rotation. */ /* necessary to recover the givens rotation. */
v[n] = givens.s() * v[j] + givens.c() * v[n]; v[n-1] = givens.s() * v[j] + givens.c() * v[n-1];
v_givens[j-1] = givens; v_givens[j] = givens;
/* apply the transformation to s and extend the spike in w. */ /* apply the transformation to s and extend the spike in w. */
for (i = j; i <= m; ++i) { for (i = j; i < m; ++i) {
temp = givens.c() * s(j-1,i-1) - givens.s() * w[i]; temp = givens.c() * s(j,i) - givens.s() * w[i];
w[i] = givens.s() * s(j-1,i-1) + givens.c() * w[i]; w[i] = givens.s() * s(j,i) + givens.c() * w[i];
s(j-1,i-1) = temp; s(j,i) = temp;
} }
} }
} }
/* add the spike from the rank 1 update to w. */ /* add the spike from the rank 1 update to w. */
for (i = 1; i <= m; ++i) w += v[n-1] * u;
w[i] += v[n] * u[i];
/* eliminate the spike. */ /* eliminate the spike. */
*sing = false; *sing = false;
for (j = 1; j <= n-1; ++j) { for (j = 0; j < n-1; ++j) {
if (w[j] != 0.) { if (w[j] != 0.) {
/* determine a givens rotation which eliminates the */ /* determine a givens rotation which eliminates the */
/* j-th element of the spike. */ /* j-th element of the spike. */
givens.makeGivens(-s(j-1,j-1), w[j]); givens.makeGivens(-s(j,j), w[j]);
/* apply the transformation to s and reduce the spike in w. */ /* apply the transformation to s and reduce the spike in w. */
for (i = j; i <= m; ++i) { for (i = j; i < m; ++i) {
temp = givens.c() * s(j-1,i-1) + givens.s() * w[i]; temp = givens.c() * s(j,i) + givens.s() * w[i];
w[i] = -givens.s() * s(j-1,i-1) + givens.c() * w[i]; w[i] = -givens.s() * s(j,i) + givens.c() * w[i];
s(j-1,i-1) = temp; s(j,i) = temp;
} }
/* store the information necessary to recover the */ /* store the information necessary to recover the */
/* givens rotation. */ /* givens rotation. */
w_givens[j-1] = givens; w_givens[j] = givens;
} }
/* test for zero diagonal elements in the output s. */ /* test for zero diagonal elements in the output s. */
if (s(j-1,j-1) == 0.) { if (s(j,j) == 0.) {
*sing = true; *sing = true;
} }
} }
/* move w back into the last column of the output s. */ /* move w back into the last column of the output s. */
s(n-1,n-1) = w[n]; s(n-1,n-1) = w[n-1];
if (s(j-1,j-1) == 0.) { if (s(j,j) == 0.) {
*sing = true; *sing = true;
} }
return; return;