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Turned off verbosity

release/4.3a0
dellaert 2015-02-18 08:22:22 +01:00
parent 5ed0c6cc49
commit 06643d4616
1 changed files with 28 additions and 17 deletions
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43
tests/testGradientDescentOptimizer.cpp
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@ -25,7 +25,6 @@
#include <boost/shared_ptr.hpp> #include <boost/shared_ptr.hpp>
#include <boost/tuple/tuple.hpp> #include <boost/tuple/tuple.hpp>
using namespace std; using namespace std;
using namespace gtsam; using namespace gtsam;
@ -33,31 +32,40 @@ using namespace gtsam;
boost::tuple<NonlinearFactorGraph, Values> generateProblem() { boost::tuple<NonlinearFactorGraph, Values> generateProblem() {
// 1. Create graph container and add factors to it // 1. Create graph container and add factors to it
NonlinearFactorGraph graph ; NonlinearFactorGraph graph;
// 2a. Add Gaussian prior // 2a. Add Gaussian prior
Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin
SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas(Vector3(0.3, 0.3, 0.1)); SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas(
Vector3(0.3, 0.3, 0.1));
graph += PriorFactor<Pose2>(1, priorMean, priorNoise); graph += PriorFactor<Pose2>(1, priorMean, priorNoise);
// 2b. Add odometry factors // 2b. Add odometry factors
SharedDiagonal odometryNoise = noiseModel::Diagonal::Sigmas(Vector3(0.2, 0.2, 0.1)); SharedDiagonal odometryNoise = noiseModel::Diagonal::Sigmas(
graph += BetweenFactor<Pose2>(1, 2, Pose2(2.0, 0.0, 0.0 ), odometryNoise); Vector3(0.2, 0.2, 0.1));
graph += BetweenFactor<Pose2>(1, 2, Pose2(2.0, 0.0, 0.0), odometryNoise);
graph += BetweenFactor<Pose2>(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise); graph += BetweenFactor<Pose2>(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
graph += BetweenFactor<Pose2>(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise); graph += BetweenFactor<Pose2>(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
graph += BetweenFactor<Pose2>(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise); graph += BetweenFactor<Pose2>(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
// 2c. Add pose constraint // 2c. Add pose constraint
SharedDiagonal constraintUncertainty = noiseModel::Diagonal::Sigmas(Vector3(0.2, 0.2, 0.1)); SharedDiagonal constraintUncertainty = noiseModel::Diagonal::Sigmas(
graph += BetweenFactor<Pose2>(5, 2, Pose2(2.0, 0.0, M_PI_2), constraintUncertainty); Vector3(0.2, 0.2, 0.1));
graph += BetweenFactor<Pose2>(5, 2, Pose2(2.0, 0.0, M_PI_2),
constraintUncertainty);
// 3. Create the data structure to hold the initialEstimate estimate to the solution // 3. Create the data structure to hold the initialEstimate estimate to the solution
Values initialEstimate; Values initialEstimate;
Pose2 x1(0.5, 0.0, 0.2 ); initialEstimate.insert(1, x1); Pose2 x1(0.5, 0.0, 0.2);
Pose2 x2(2.3, 0.1,-0.2 ); initialEstimate.insert(2, x2); initialEstimate.insert(1, x1);
Pose2 x3(4.1, 0.1, M_PI_2); initialEstimate.insert(3, x3); Pose2 x2(2.3, 0.1, -0.2);
Pose2 x4(4.0, 2.0, M_PI ); initialEstimate.insert(4, x4); initialEstimate.insert(2, x2);
Pose2 x5(2.1, 2.1,-M_PI_2); initialEstimate.insert(5, x5); Pose2 x3(4.1, 0.1, M_PI_2);
initialEstimate.insert(3, x3);
Pose2 x4(4.0, 2.0, M_PI);
initialEstimate.insert(4, x4);
Pose2 x5(2.1, 2.1, -M_PI_2);
initialEstimate.insert(5, x5);
return boost::tie(graph, initialEstimate); return boost::tie(graph, initialEstimate);
} }
@ -69,19 +77,22 @@ TEST(NonlinearConjugateGradientOptimizer, Optimize) {
Values initialEstimate; Values initialEstimate;
boost::tie(graph, initialEstimate) = generateProblem(); boost::tie(graph, initialEstimate) = generateProblem();
cout << "initial error = " << graph.error(initialEstimate) << endl ; // cout << "initial error = " << graph.error(initialEstimate) << endl;
NonlinearOptimizerParams param; NonlinearOptimizerParams param;
param.maxIterations = 500; /* requires a larger number of iterations to converge */ param.maxIterations = 500; /* requires a larger number of iterations to converge */
param.verbosity = NonlinearOptimizerParams::ERROR; param.verbosity = NonlinearOptimizerParams::SILENT;
NonlinearConjugateGradientOptimizer optimizer(graph, initialEstimate, param); NonlinearConjugateGradientOptimizer optimizer(graph, initialEstimate, param);
Values result = optimizer.optimize(); Values result = optimizer.optimize();
cout << "cg final error = " << graph.error(result) << endl; // cout << "cg final error = " << graph.error(result) << endl;
EXPECT_DOUBLES_EQUAL(0.0, graph.error(result), 1e-4); EXPECT_DOUBLES_EQUAL(0.0, graph.error(result), 1e-4);
} }
/* ************************************************************************* */ /* ************************************************************************* */
int main() { TestResult tr; return TestRegistry::runAllTests(tr); } int main() {
TestResult tr;
return TestRegistry::runAllTests(tr);
}
/* ************************************************************************* */ /* ************************************************************************* */