12345qiupeng
/
gtsam
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

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
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
examples/vSLAMexample/vSFMexample.cpp
View File

@ -144,7 +144,7 @@ int main(int argc, char* argv[]) {
// Optimize the graph
cout << "*******************************************************" << endl;
LevenbergMarquardtParams params;
params.lmVerbosity = LevenbergMarquardtParams::DAMPED;
params.verbosityLM = LevenbergMarquardtParams::DAMPED;
visualSLAM::Values result = LevenbergMarquardtOptimizer(graph, initialEstimates, params).optimize();
// Print final results

2
gtsam/nonlinear/DoglegOptimizer.cpp
View File

@ -37,7 +37,7 @@ void DoglegOptimizer::iterate(void) {
GaussianFactorGraph::Eliminate eliminationMethod = params_.getEliminationFunction();
// 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
DoglegOptimizerImpl::IterationResult result;

6
gtsam/nonlinear/DoglegOptimizer.h
View File

@ -32,16 +32,16 @@ class DoglegOptimizer;
class DoglegParams : public SuccessiveLinearizationParams {
public:
/** See DoglegParams::dlVerbosity */
enum DLVerbosity {
enum VerbosityDL {
SILENT,
VERBOSE
};
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() :
deltaInitial(1.0), dlVerbosity(SILENT) {}
deltaInitial(1.0), verbosityDL(SILENT) {}
virtual ~DoglegParams() {}

2
gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp
View File

@ -37,7 +37,7 @@ void LevenbergMarquardtOptimizer::iterate() {
// Pull out parameters we'll use
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
while(true) {

6
gtsam/nonlinear/LevenbergMarquardtOptimizer.h
View File

@ -32,7 +32,7 @@ class LevenbergMarquardtOptimizer;
class LevenbergMarquardtParams : public SuccessiveLinearizationParams {
public:
/** See LevenbergMarquardtParams::lmVerbosity */
enum LMVerbosity {
enum VerbosityLM {
SILENT,
LAMBDA,
TRYLAMBDA,
@ -44,10 +44,10 @@ public:
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 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() :
lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), lmVerbosity(SILENT) {}
lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), verbosityLM(SILENT) {}
virtual ~LevenbergMarquardtParams() {}