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misc cleaning

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This commit is contained in:
Thomas Capricelli 2010-02-28 02:51:35 +01:00
parent 27f5250258
commit eb3a3351cc
2 changed files with 17 additions and 3 deletions
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8
unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
View File

@ -194,6 +194,8 @@ template<typename FunctorType, typename Scalar>
HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(FVectorType &x)
{
assert(x.size()==n); // check the caller is not cheating us
int j;
std::vector<PlanarRotation<Scalar> > v_givens(n), w_givens(n);
@ -350,6 +352,8 @@ HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solve(FVectorType &x)
{
HybridNonLinearSolverSpace::Status status = solveInit(x);
if (status==HybridNonLinearSolverSpace::ImproperInputParameters)
return status;
while (status==HybridNonLinearSolverSpace::Running)
status = solveOneStep(x);
return status;
@ -429,6 +433,8 @@ template<typename FunctorType, typename Scalar>
HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(FVectorType &x)
{
assert(x.size()==n); // check the caller is not cheating us
int j;
std::vector<PlanarRotation<Scalar> > v_givens(n), w_givens(n);
@ -587,6 +593,8 @@ HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(FVectorType &x)
{
HybridNonLinearSolverSpace::Status status = solveNumericalDiffInit(x);
if (status==HybridNonLinearSolverSpace::ImproperInputParameters)
return status;
while (status==HybridNonLinearSolverSpace::Running)
status = solveNumericalDiffOneStep(x);
return status;

12
unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
View File

@ -161,6 +161,8 @@ LevenbergMarquardtSpace::Status
LevenbergMarquardt<FunctorType,Scalar>::minimize(FVectorType &x)
{
LevenbergMarquardtSpace::Status status = minimizeInit(x);
if (status==LevenbergMarquardtSpace::ImproperInputParameters)
return status;
do {
status = minimizeOneStep(x);
} while (status==LevenbergMarquardtSpace::Running);
@ -214,7 +216,7 @@ template<typename FunctorType, typename Scalar>
LevenbergMarquardtSpace::Status
LevenbergMarquardt<FunctorType,Scalar>::minimizeOneStep(FVectorType &x)
{
int j;
assert(x.size()==n); // check the caller is not cheating us
/* calculate the jacobian matrix. */
int df_ret = functor.df(x, fjac);
@ -235,7 +237,7 @@ LevenbergMarquardt<FunctorType,Scalar>::minimizeOneStep(FVectorType &x)
/* to the norms of the columns of the initial jacobian. */
if (iter == 1) {
if (!useExternalScaling)
for (j = 0; j < n; ++j)
for (int j = 0; j < n; ++j)
diag[j] = (wa2[j]==0.)? 1. : wa2[j];
/* on the first iteration, calculate the norm of the scaled x */
@ -255,7 +257,7 @@ LevenbergMarquardt<FunctorType,Scalar>::minimizeOneStep(FVectorType &x)
/* compute the norm of the scaled gradient. */
gnorm = 0.;
if (fnorm != 0.)
for (j = 0; j < n; ++j)
for (int j = 0; j < n; ++j)
if (wa2[permutation.indices()[j]] != 0.)
gnorm = std::max(gnorm, ei_abs( fjac.col(j).head(j+1).dot(qtf.head(j+1)/fnorm) / wa2[permutation.indices()[j]]));
@ -431,6 +433,8 @@ template<typename FunctorType, typename Scalar>
LevenbergMarquardtSpace::Status
LevenbergMarquardt<FunctorType,Scalar>::minimizeOptimumStorageOneStep(FVectorType &x)
{
assert(x.size()==n); // check the caller is not cheating us
int i, j;
bool sing;
@ -606,6 +610,8 @@ LevenbergMarquardtSpace::Status
LevenbergMarquardt<FunctorType,Scalar>::minimizeOptimumStorage(FVectorType &x)
{
LevenbergMarquardtSpace::Status status = minimizeOptimumStorageInit(x);
if (status==LevenbergMarquardtSpace::ImproperInputParameters)
return status;
do {
status = minimizeOptimumStorageOneStep(x);
} while (status==LevenbergMarquardtSpace::Running);