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update namespace mEstimator for unittests

release/4.3a0
Duy-Nguyen Ta 2013-02-08 00:47:52 +00:00
parent e035b6e4bf
commit 6eafc9420e
4 changed files with 9 additions and 9 deletions
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6
gtsam/linear/NoiseModel.cpp
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@ -552,7 +552,7 @@ Null::shared_ptr Null::Create()
Fair::Fair(const double c, const ReweightScheme reweight) Fair::Fair(const double c, const ReweightScheme reweight)
: Base(reweight), c_(c) { : Base(reweight), c_(c) {
if ( c_ <= 0 ) { if ( c_ <= 0 ) {
cout << "MEstimator Fair takes only positive double in constructor. forced to 1.0" << endl; cout << "mEstimator Fair takes only positive double in constructor. forced to 1.0" << endl;
c_ = 1.0; c_ = 1.0;
} }
} }
@ -583,7 +583,7 @@ Fair::shared_ptr Fair::Create(const double c, const ReweightScheme reweight)
Huber::Huber(const double k, const ReweightScheme reweight) Huber::Huber(const double k, const ReweightScheme reweight)
: Base(reweight), k_(k) { : Base(reweight), k_(k) {
if ( k_ <= 0 ) { if ( k_ <= 0 ) {
cout << "MEstimator Huber takes only positive double in constructor. forced to 1.0" << endl; cout << "mEstimator Huber takes only positive double in constructor. forced to 1.0" << endl;
k_ = 1.0; k_ = 1.0;
} }
} }
@ -636,7 +636,7 @@ Tukey::shared_ptr Tukey::Create(const double c, const ReweightScheme reweight) {
return shared_ptr(new Tukey(c, reweight)); return shared_ptr(new Tukey(c, reweight));
} }
} // namespace MEstimator } // namespace mEstimator
/* ************************************************************************* */ /* ************************************************************************* */
// Robust // Robust

4
gtsam/linear/NoiseModel.h
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@ -571,7 +571,7 @@ namespace gtsam {
}; };
// TODO: should not really exist // TODO: should not really exist
/// The MEstimator namespace contains all robust error functions (not models) /// The mEstimator namespace contains all robust error functions (not models)
namespace mEstimator { namespace mEstimator {
//--------------------------------------------------------------------------------------- //---------------------------------------------------------------------------------------
@ -678,7 +678,7 @@ namespace gtsam {
Tukey(){} Tukey(){}
}; };
} ///\namespace MEstimator } ///\namespace mEstimator
/// Base class for robust error models /// Base class for robust error models
class Robust : public Base { class Robust : public Base {

4
gtsam/linear/tests/testNoiseModel.cpp
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@ -294,7 +294,7 @@ TEST(NoiseModel, WhitenInPlace)
TEST(NoiseModel, robustFunction) TEST(NoiseModel, robustFunction)
{ {
const double k = 5.0, error1 = 1.0, error2 = 10.0; const double k = 5.0, error1 = 1.0, error2 = 10.0;
const MEstimator::Huber::shared_ptr huber = MEstimator::Huber::Create(k); const mEstimator::Huber::shared_ptr huber = mEstimator::Huber::Create(k);
const double weight1 = huber->weight(error1), const double weight1 = huber->weight(error1),
weight2 = huber->weight(error2); weight2 = huber->weight(error2);
DOUBLES_EQUAL(1.0, weight1, 1e-8); DOUBLES_EQUAL(1.0, weight1, 1e-8);
@ -308,7 +308,7 @@ TEST(NoiseModel, robustNoise)
Matrix A = Matrix_(2, 2, 1.0, 10.0, 100.0, 1000.0); Matrix A = Matrix_(2, 2, 1.0, 10.0, 100.0, 1000.0);
Vector b = Vector_(2, error1, error2); Vector b = Vector_(2, error1, error2);
const Robust::shared_ptr robust = Robust::Create( const Robust::shared_ptr robust = Robust::Create(
MEstimator::Huber::Create(k, MEstimator::Huber::Scalar), mEstimator::Huber::Create(k, mEstimator::Huber::Scalar),
Unit::Create(2)); Unit::Create(2));
robust->WhitenSystem(A,b); robust->WhitenSystem(A,b);

4
tests/testNonlinearOptimizer.cpp
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@ -261,10 +261,10 @@ TEST(NonlinearOptimizer, MoreOptimizationWithHuber) {
NonlinearFactorGraph fg; NonlinearFactorGraph fg;
fg.add(PriorFactor<Pose2>(0, Pose2(0,0,0), noiseModel::Isotropic::Sigma(3,1))); fg.add(PriorFactor<Pose2>(0, Pose2(0,0,0), noiseModel::Isotropic::Sigma(3,1)));
fg.add(BetweenFactor<Pose2>(0, 1, Pose2(1,0,M_PI/2), fg.add(BetweenFactor<Pose2>(0, 1, Pose2(1,0,M_PI/2),
noiseModel::Robust::Create(noiseModel::MEstimator::Huber::Create(2.0), noiseModel::Robust::Create(noiseModel::mEstimator::Huber::Create(2.0),
noiseModel::Isotropic::Sigma(3,1)))); noiseModel::Isotropic::Sigma(3,1))));
fg.add(BetweenFactor<Pose2>(1, 2, Pose2(1,0,M_PI/2), fg.add(BetweenFactor<Pose2>(1, 2, Pose2(1,0,M_PI/2),
noiseModel::Robust::Create(noiseModel::MEstimator::Huber::Create(3.0), noiseModel::Robust::Create(noiseModel::mEstimator::Huber::Create(3.0),
noiseModel::Isotropic::Sigma(3,1)))); noiseModel::Isotropic::Sigma(3,1))));
Values init; Values init;