gtsam/gtsam/linear/Sampler.cpp

77 lines
2.3 KiB
C++

/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file Sampler.cpp
* @author Alex Cunningham
*/
#include <boost/random/normal_distribution.hpp>
#include <boost/random/variate_generator.hpp>
#include <gtsam/linear/Sampler.h>
namespace gtsam {
/* ************************************************************************* */
Sampler::Sampler(const noiseModel::Diagonal::shared_ptr& model, int32_t seed)
: model_(model), generator_(static_cast<unsigned>(seed))
{
}
/* ************************************************************************* */
Sampler::Sampler(const Vector& sigmas, int32_t seed)
: model_(noiseModel::Diagonal::Sigmas(sigmas, true)), generator_(static_cast<unsigned>(seed))
{
}
/* ************************************************************************* */
Sampler::Sampler(int32_t seed)
: generator_(static_cast<unsigned>(seed))
{
}
/* ************************************************************************* */
Vector Sampler::sampleDiagonal(const Vector& sigmas) {
size_t d = sigmas.size();
Vector result(d);
for (size_t i = 0; i < d; i++) {
double sigma = sigmas(i);
// handle constrained case separately
if (sigma == 0.0) {
result(i) = 0.0;
} else {
typedef boost::normal_distribution<double> Normal;
Normal dist(0.0, sigma);
boost::variate_generator<boost::minstd_rand&, Normal> norm(generator_, dist);
result(i) = norm();
}
}
return result;
}
/* ************************************************************************* */
Vector Sampler::sample() {
assert(model_.get());
const Vector& sigmas = model_->sigmas();
return sampleDiagonal(sigmas);
}
/* ************************************************************************* */
Vector Sampler::sampleNewModel(const noiseModel::Diagonal::shared_ptr& model) {
assert(model.get());
const Vector& sigmas = model->sigmas();
return sampleDiagonal(sigmas);
}
/* ************************************************************************* */
} // \namespace gtsam