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NonLinearOptimization : clean 'mode' handling from the old minpack code :

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* this is actually a boolean, not an int
* use a better name
* can be set at initialization time instead of bloating all methods signatures
This commit is contained in:
Thomas Capricelli
2010-02-21 12:41:37 +01:00
parent 608959aa6f
commit a7d085eb4e
3 changed files with 68 additions and 141 deletions
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108
unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
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@@ -57,7 +57,7 @@ class HybridNonLinearSolver
{
public:
HybridNonLinearSolver(FunctorType &_functor)
: functor(_functor) { nfev=njev=iter = 0; fnorm= 0.; }
: functor(_functor) { nfev=njev=iter = 0; fnorm= 0.; useExternalScaling=false;}
struct Parameters {
Parameters()
@@ -84,36 +84,18 @@ public:
const Scalar tol = ei_sqrt(NumTraits<Scalar>::epsilon())
);
HybridNonLinearSolverSpace::Status solveInit(
FVectorType &x,
const int mode=1
);
HybridNonLinearSolverSpace::Status solveOneStep(
FVectorType &x,
const int mode=1
);
HybridNonLinearSolverSpace::Status solve(
FVectorType &x,
const int mode=1
);
HybridNonLinearSolverSpace::Status solveInit(FVectorType &x);
HybridNonLinearSolverSpace::Status solveOneStep(FVectorType &x);
HybridNonLinearSolverSpace::Status solve(FVectorType &x);
HybridNonLinearSolverSpace::Status hybrd1(
FVectorType &x,
const Scalar tol = ei_sqrt(NumTraits<Scalar>::epsilon())
);
HybridNonLinearSolverSpace::Status solveNumericalDiffInit(
FVectorType &x,
const int mode=1
);
HybridNonLinearSolverSpace::Status solveNumericalDiffOneStep(
FVectorType &x,
const int mode=1
);
HybridNonLinearSolverSpace::Status solveNumericalDiff(
FVectorType &x,
const int mode=1
);
HybridNonLinearSolverSpace::Status solveNumericalDiffInit(FVectorType &x);
HybridNonLinearSolverSpace::Status solveNumericalDiffOneStep(FVectorType &x);
HybridNonLinearSolverSpace::Status solveNumericalDiff(FVectorType &x);
void resetParameters(void) { parameters = Parameters(); }
Parameters parameters;
@@ -124,6 +106,7 @@ public:
int njev;
int iter;
Scalar fnorm;
bool useExternalScaling;
private:
FunctorType &functor;
int n;
@@ -160,18 +143,13 @@ HybridNonLinearSolver<FunctorType,Scalar>::hybrj1(
parameters.maxfev = 100*(n+1);
parameters.xtol = tol;
diag.setConstant(n, 1.);
return solve(
x,
2
);
useExternalScaling = true;
return solve(x);
}
template<typename FunctorType, typename Scalar>
HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveInit(
FVectorType &x,
const int mode
)
HybridNonLinearSolver<FunctorType,Scalar>::solveInit(FVectorType &x)
{
n = x.size();
@@ -179,9 +157,9 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveInit(
fvec.resize(n);
qtf.resize(n);
fjac.resize(n, n);
if (mode != 2)
if (!useExternalScaling)
diag.resize(n);
assert( (mode!=2 || diag.size()==n) || "When using mode==2, the caller must provide a valid 'diag'");
assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
/* Function Body */
nfev = 0;
@@ -190,7 +168,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveInit(
/* check the input parameters for errors. */
if (n <= 0 || parameters.xtol < 0. || parameters.maxfev <= 0 || parameters.factor <= 0. )
return HybridNonLinearSolverSpace::ImproperInputParameters;
if (mode == 2)
if (useExternalScaling)
for (int j = 0; j < n; ++j)
if (diag[j] <= 0.)
return HybridNonLinearSolverSpace::ImproperInputParameters;
@@ -214,10 +192,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveInit(
template<typename FunctorType, typename Scalar>
HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
FVectorType &x,
const int mode
)
HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(FVectorType &x)
{
int j;
std::vector<PlanarRotation<Scalar> > v_givens(n), w_givens(n);
@@ -231,10 +206,10 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
wa2 = fjac.colwise().blueNorm();
/* on the first iteration and if mode is 1, scale according */
/* on the first iteration and if external scaling is not used, scale according */
/* to the norms of the columns of the initial jacobian. */
if (iter == 1) {
if (mode != 2)
if (!useExternalScaling)
for (j = 0; j < n; ++j)
diag[j] = (wa2[j]==0.) ? 1. : wa2[j];
@@ -260,7 +235,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
qtf = fjac.transpose() * fvec;
/* rescale if necessary. */
if (mode != 2)
if (!useExternalScaling)
diag = diag.cwiseMax(wa2);
while (true) {
@@ -372,14 +347,11 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(
template<typename FunctorType, typename Scalar>
HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solve(
FVectorType &x,
const int mode
)
HybridNonLinearSolver<FunctorType,Scalar>::solve(FVectorType &x)
{
HybridNonLinearSolverSpace::Status status = solveInit(x, mode);
HybridNonLinearSolverSpace::Status status = solveInit(x);
while (status==HybridNonLinearSolverSpace::Running)
status = solveOneStep(x, mode);
status = solveOneStep(x);
return status;
}
@@ -403,18 +375,13 @@ HybridNonLinearSolver<FunctorType,Scalar>::hybrd1(
parameters.xtol = tol;
diag.setConstant(n, 1.);
return solveNumericalDiff(
x,
2
);
useExternalScaling = true;
return solveNumericalDiff(x);
}
template<typename FunctorType, typename Scalar>
HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffInit(
FVectorType &x,
const int mode
)
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffInit(FVectorType &x)
{
n = x.size();
@@ -425,10 +392,9 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffInit(
qtf.resize(n);
fjac.resize(n, n);
fvec.resize(n);
if (mode != 2)
if (!useExternalScaling)
diag.resize(n);
assert( (mode!=2 || diag.size()==n) || "When using mode==2, the caller must provide a valid 'diag'");
assert( (!useExternalScaling || diag.size()==n) || "When useExternalScaling is set, the caller must provide a valid 'diag'");
/* Function Body */
nfev = 0;
@@ -437,7 +403,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffInit(
/* check the input parameters for errors. */
if (n <= 0 || parameters.xtol < 0. || parameters.maxfev <= 0 || parameters.nb_of_subdiagonals< 0 || parameters.nb_of_superdiagonals< 0 || parameters.factor <= 0. )
return HybridNonLinearSolverSpace::ImproperInputParameters;
if (mode == 2)
if (useExternalScaling)
for (int j = 0; j < n; ++j)
if (diag[j] <= 0.)
return HybridNonLinearSolverSpace::ImproperInputParameters;
@@ -461,10 +427,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffInit(
template<typename FunctorType, typename Scalar>
HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
FVectorType &x,
const int mode
)
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(FVectorType &x)
{
int j;
std::vector<PlanarRotation<Scalar> > v_givens(n), w_givens(n);
@@ -480,10 +443,10 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
wa2 = fjac.colwise().blueNorm();
/* on the first iteration and if mode is 1, scale according */
/* on the first iteration and if external scaling is not used, scale according */
/* to the norms of the columns of the initial jacobian. */
if (iter == 1) {
if (mode != 2)
if (!useExternalScaling)
for (j = 0; j < n; ++j)
diag[j] = (wa2[j]==0.) ? 1. : wa2[j];
@@ -509,7 +472,7 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
qtf = fjac.transpose() * fvec;
/* rescale if necessary. */
if (mode != 2)
if (!useExternalScaling)
diag = diag.cwiseMax(wa2);
while (true) {
@@ -621,14 +584,11 @@ HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(
template<typename FunctorType, typename Scalar>
HybridNonLinearSolverSpace::Status
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(
FVectorType &x,
const int mode
)
HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiff(FVectorType &x)
{
HybridNonLinearSolverSpace::Status status = solveNumericalDiffInit(x, mode);
HybridNonLinearSolverSpace::Status status = solveNumericalDiffInit(x);
while (status==HybridNonLinearSolverSpace::Running)
status = solveNumericalDiffOneStep(x, mode);
status = solveNumericalDiffOneStep(x);
return status;
}