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Make SharedNoiseModel as optional parameter, remove hardcoded verbosity, and silence test.

release/4.3a0
Varun Agrawal 2020-09-17 21:36:34 -04:00
parent 0043120a8a
commit aa67e3c276
3 changed files with 13 additions and 8 deletions
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5
gtsam/sfm/TranslationRecovery.cpp
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@ -45,9 +45,8 @@ NonlinearFactorGraph TranslationRecovery::buildGraph() const {
} }
void TranslationRecovery::addPrior(const double scale, void TranslationRecovery::addPrior(const double scale,
NonlinearFactorGraph *graph) const { NonlinearFactorGraph *graph,
//TODO(akshay-krishnan): make this an input argument const SharedNoiseModel &priorNoiseModel) const {
auto priorNoiseModel = noiseModel::Isotropic::Sigma(3, 0.01);
auto edge = relativeTranslations_.begin(); auto edge = relativeTranslations_.begin();
graph->emplace_shared<PriorFactor<Point3> >(edge->key1(), Point3(0, 0, 0), priorNoiseModel); graph->emplace_shared<PriorFactor<Point3> >(edge->key1(), Point3(0, 0, 0), priorNoiseModel);
graph->emplace_shared<PriorFactor<Point3> >(edge->key2(), scale * edge->measured().point3(), graph->emplace_shared<PriorFactor<Point3> >(edge->key2(), scale * edge->measured().point3(),

9
gtsam/sfm/TranslationRecovery.h
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@ -68,9 +68,7 @@ class TranslationRecovery {
*/ */
TranslationRecovery(const TranslationEdges &relativeTranslations, TranslationRecovery(const TranslationEdges &relativeTranslations,
const LevenbergMarquardtParams &lmParams = LevenbergMarquardtParams()) const LevenbergMarquardtParams &lmParams = LevenbergMarquardtParams())
: relativeTranslations_(relativeTranslations), params_(lmParams) { : relativeTranslations_(relativeTranslations), params_(lmParams) {}
params_.setVerbosityLM("Summary");
}
/** /**
* @brief Build the factor graph to do the optimization. * @brief Build the factor graph to do the optimization.
@ -84,8 +82,11 @@ class TranslationRecovery {
* *
* @param scale scale for first relative translation which fixes gauge. * @param scale scale for first relative translation which fixes gauge.
* @param graph factor graph to which prior is added. * @param graph factor graph to which prior is added.
* @param priorNoiseModel the noise model to use with the prior.
*/ */
void addPrior(const double scale, NonlinearFactorGraph *graph) const; void addPrior(const double scale, NonlinearFactorGraph *graph,
const SharedNoiseModel &priorNoiseModel =
noiseModel::Isotropic::Sigma(3, 0.01)) const;
/** /**
* @brief Create random initial translations. * @brief Create random initial translations.

7
python/gtsam/tests/test_TranslationRecovery.py
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@ -40,7 +40,12 @@ class TestTranslationRecovery(unittest.TestCase):
def test_run(self): def test_run(self):
gt_poses = ExampleValues() gt_poses = ExampleValues()
measurements = SimulateMeasurements(gt_poses, [[0, 1], [0, 2], [1, 2]]) measurements = SimulateMeasurements(gt_poses, [[0, 1], [0, 2], [1, 2]])
algorithm = gtsam.TranslationRecovery(measurements)
# Set verbosity to Silent for tests
lmParams = gtsam.LevenbergMarquardtParams()
lmParams.setVerbosityLM("silent")
algorithm = gtsam.TranslationRecovery(measurements, lmParams)
scale = 2.0 scale = 2.0
result = algorithm.run(scale) result = algorithm.run(scale)