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Renamed derived optimizer verbosity parameters to start with 'verbosity' to make more auto-complete friendly

release/4.3a0
Richard Roberts 2012-05-15 13:33:32 +00:00
parent 68467448a7
commit 7b183d1237
5 changed files with 9 additions and 9 deletions
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2
examples/vSLAMexample/vSFMexample.cpp
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@ -144,7 +144,7 @@ int main(int argc, char* argv[]) {
// Optimize the graph // Optimize the graph
cout << "*******************************************************" << endl; cout << "*******************************************************" << endl;
LevenbergMarquardtParams params; LevenbergMarquardtParams params;
params.lmVerbosity = LevenbergMarquardtParams::DAMPED; params.verbosityLM = LevenbergMarquardtParams::DAMPED;
visualSLAM::Values result = LevenbergMarquardtOptimizer(graph, initialEstimates, params).optimize(); visualSLAM::Values result = LevenbergMarquardtOptimizer(graph, initialEstimates, params).optimize();
// Print final results // Print final results

2
gtsam/nonlinear/DoglegOptimizer.cpp
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@ -37,7 +37,7 @@ void DoglegOptimizer::iterate(void) {
GaussianFactorGraph::Eliminate eliminationMethod = params_.getEliminationFunction(); GaussianFactorGraph::Eliminate eliminationMethod = params_.getEliminationFunction();
// Pull out parameters we'll use // Pull out parameters we'll use
const bool dlVerbose = (params_.dlVerbosity > DoglegParams::SILENT); const bool dlVerbose = (params_.verbosityDL > DoglegParams::SILENT);
// Do Dogleg iteration with either Multifrontal or Sequential elimination // Do Dogleg iteration with either Multifrontal or Sequential elimination
DoglegOptimizerImpl::IterationResult result; DoglegOptimizerImpl::IterationResult result;

6
gtsam/nonlinear/DoglegOptimizer.h
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@ -32,16 +32,16 @@ class DoglegOptimizer;
class DoglegParams : public SuccessiveLinearizationParams { class DoglegParams : public SuccessiveLinearizationParams {
public: public:
/** See DoglegParams::dlVerbosity */ /** See DoglegParams::dlVerbosity */
enum DLVerbosity { enum VerbosityDL {
SILENT, SILENT,
VERBOSE VERBOSE
}; };
double deltaInitial; ///< The initial trust region radius (default: 1.0) double deltaInitial; ///< The initial trust region radius (default: 1.0)
DLVerbosity dlVerbosity; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity VerbosityDL verbosityDL; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity
DoglegParams() : DoglegParams() :
deltaInitial(1.0), dlVerbosity(SILENT) {} deltaInitial(1.0), verbosityDL(SILENT) {}
virtual ~DoglegParams() {} virtual ~DoglegParams() {}

2
gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp
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@ -37,7 +37,7 @@ void LevenbergMarquardtOptimizer::iterate() {
// Pull out parameters we'll use // Pull out parameters we'll use
const NonlinearOptimizerParams::Verbosity nloVerbosity = params_.verbosity; const NonlinearOptimizerParams::Verbosity nloVerbosity = params_.verbosity;
const LevenbergMarquardtParams::LMVerbosity lmVerbosity = params_.lmVerbosity; const LevenbergMarquardtParams::VerbosityLM lmVerbosity = params_.verbosityLM;
// Keep increasing lambda until we make make progress // Keep increasing lambda until we make make progress
while(true) { while(true) {

6
gtsam/nonlinear/LevenbergMarquardtOptimizer.h
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@ -32,7 +32,7 @@ class LevenbergMarquardtOptimizer;
class LevenbergMarquardtParams : public SuccessiveLinearizationParams { class LevenbergMarquardtParams : public SuccessiveLinearizationParams {
public: public:
/** See LevenbergMarquardtParams::lmVerbosity */ /** See LevenbergMarquardtParams::lmVerbosity */
enum LMVerbosity { enum VerbosityLM {
SILENT, SILENT,
LAMBDA, LAMBDA,
TRYLAMBDA, TRYLAMBDA,
@ -44,10 +44,10 @@ public:
double lambdaInitial; ///< The initial Levenberg-Marquardt damping term (default: 1e-5) double lambdaInitial; ///< The initial Levenberg-Marquardt damping term (default: 1e-5)
double lambdaFactor; ///< The amount by which to multiply or divide lambda when adjusting lambda (default: 10.0) double lambdaFactor; ///< The amount by which to multiply or divide lambda when adjusting lambda (default: 10.0)
double lambdaUpperBound; ///< The maximum lambda to try before assuming the optimization has failed (default: 1e5) double lambdaUpperBound; ///< The maximum lambda to try before assuming the optimization has failed (default: 1e5)
LMVerbosity lmVerbosity; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity VerbosityLM verbosityLM; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity
LevenbergMarquardtParams() : LevenbergMarquardtParams() :
lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), lmVerbosity(SILENT) {} lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), verbosityLM(SILENT) {}
virtual ~LevenbergMarquardtParams() {} virtual ~LevenbergMarquardtParams() {}