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								/* ----------------------------------------------------------------------------
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								 * GTSAM Copyright 2010, Georgia Tech Research Corporation,
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								 * Atlanta, Georgia 30332-0415
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								 * All Rights Reserved
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								 * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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								 * See LICENSE for the license information
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								 * -------------------------------------------------------------------------- */
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								/**
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								 * @file    matlab.h
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								 * @brief   Contains *generic* global functions designed particularly for the matlab interface
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								 * @author  Stephen Williams
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								 */
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								#pragma once
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								#include <gtsam/slam/ProjectionFactor.h>
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								#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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								#include <gtsam/nonlinear/NonlinearFactor.h>
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								#include <gtsam/nonlinear/Values.h>
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								#include <gtsam/geometry/Point2.h>
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								#include <gtsam/geometry/Point3.h>
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								#include <gtsam/geometry/Pose2.h>
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								#include <gtsam/geometry/Pose3.h>
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								#include <gtsam/geometry/Cal3_S2.h>
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								#include <gtsam/geometry/SimpleCamera.h>
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								#include <exception>
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								namespace gtsam {
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								  namespace utilities {
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								    /// Extract all Point2 values into a single matrix [x y]
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								    Matrix extractPoint2(const Values& values) {
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								      size_t j=0;
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								      Values::ConstFiltered<Point2> points = values.filter<Point2>();
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								      Matrix result(points.size(),2);
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								      BOOST_FOREACH(const Values::ConstFiltered<Point2>::KeyValuePair& key_value, points)
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								        result.row(j++) = key_value.value.vector();
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								      return result;
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								    }
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								    /// Extract all Point3 values into a single matrix [x y z]
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								    Matrix extractPoint3(const Values& values) {
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								      Values::ConstFiltered<Point3> points = values.filter<Point3>();
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								      Matrix result(points.size(),3);
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								      size_t j=0;
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								      BOOST_FOREACH(const Values::ConstFiltered<Point3>::KeyValuePair& key_value, points)
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								        result.row(j++) = key_value.value.vector();
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								      return result;
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								    }
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								    /// Extract all Pose2 values into a single matrix [x y theta]
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								    Matrix extractPose2(const Values& values) {
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								      Values::ConstFiltered<Pose2> poses = values.filter<Pose2>();
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								      Matrix result(poses.size(),3);
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								      size_t j=0;
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								      BOOST_FOREACH(const Values::ConstFiltered<Pose2>::KeyValuePair& key_value, poses)
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								        result.row(j++) << key_value.value.x(), key_value.value.y(), key_value.value.theta();
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								      return result;
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								    }
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								    /// Extract all Pose3 values
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								    Values allPose3s(const Values& values) {
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								      return values.filter<Pose3>();
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								    }
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								    /// Extract all Pose3 values into a single matrix [r11 r12 r13 r21 r22 r23 r31 r32 r33 x y z]
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								    Matrix extractPose3(const Values& values) {
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								      Values::ConstFiltered<Pose3> poses = values.filter<Pose3>();
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								      Matrix result(poses.size(),12);
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								      size_t j=0;
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								      BOOST_FOREACH(const Values::ConstFiltered<Pose3>::KeyValuePair& key_value, poses) {
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								        result.row(j).segment(0, 3) << key_value.value.rotation().matrix().row(0);
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								        result.row(j).segment(3, 3) << key_value.value.rotation().matrix().row(1);
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								        result.row(j).segment(6, 3) << key_value.value.rotation().matrix().row(2);
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								        result.row(j).tail(3) = key_value.value.translation().vector();
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								        j++;
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								      }
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								      return result;
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								    }
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								    /// Perturb all Point2 values using normally distributed noise
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								    void perturbPoint2(Values& values, double sigma, int32_t seed = 42u) {
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								      noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(2,sigma);
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								      Sampler sampler(model, seed);
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								      BOOST_FOREACH(const Values::ConstFiltered<Point2>::KeyValuePair& key_value, values.filter<Point2>()) {
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								        values.update(key_value.key, key_value.value.retract(sampler.sample()));
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								      }
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								    }
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								    /// Perturb all Pose2 values using normally distributed noise
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								    void perturbPose2(Values& values, double sigmaT, double sigmaR, int32_t seed = 42u) {
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								      noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Sigmas(
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								          Vector3(sigmaT, sigmaT, sigmaR));
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								      Sampler sampler(model, seed);
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								      BOOST_FOREACH(const Values::ConstFiltered<Pose2>::KeyValuePair& key_value, values.filter<Pose2>()) {
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								        values.update(key_value.key, key_value.value.retract(sampler.sample()));
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								      }
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								    }
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								    /// Perturb all Point3 values using normally distributed noise
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								    void perturbPoint3(Values& values, double sigma, int32_t seed = 42u) {
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								      noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(3,sigma);
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								      Sampler sampler(model, seed);
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								      BOOST_FOREACH(const Values::ConstFiltered<Point3>::KeyValuePair& key_value, values.filter<Point3>()) {
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								        values.update(key_value.key, key_value.value.retract(sampler.sample()));
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								      }
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								    }
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								    /// Insert a number of initial point values by backprojecting
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								    void insertBackprojections(Values& values, const SimpleCamera& camera, const Vector& J, const Matrix& Z, double depth) {
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								      if (Z.rows() != 2) throw std::invalid_argument("insertBackProjections: Z must be 2*K");
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								      if (Z.cols() != J.size()) throw std::invalid_argument("insertBackProjections: J and Z must have same number of entries");
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								      for(int k=0;k<Z.cols();k++) {
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								        Point2 p(Z(0,k),Z(1,k));
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								        Point3 P = camera.backproject(p, depth);
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								        values.insert(J(k), P);
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								      }
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								    }
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								    /// Insert multiple projection factors for a single pose key
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								    void insertProjectionFactors(NonlinearFactorGraph& graph, Key i, const Vector& J, const Matrix& Z,
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								        const SharedNoiseModel& model, const Cal3_S2::shared_ptr K, const Pose3& body_P_sensor = Pose3()) {
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								      if (Z.rows() != 2) throw std::invalid_argument("addMeasurements: Z must be 2*K");
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								      if (Z.cols() != J.size()) throw std::invalid_argument(
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								            "addMeasurements: J and Z must have same number of entries");
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								      for (int k = 0; k < Z.cols(); k++) {
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								        graph.push_back(
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								            boost::make_shared<GenericProjectionFactor<Pose3, Point3> >
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								            (Point2(Z(0, k), Z(1, k)), model, i, Key(J(k)), K, body_P_sensor));
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											2012-08-06 07:52:47 +08:00
										 
									 
								 
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								      }
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								    }
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											2014-05-06 12:23:20 +08:00
										 
									 
								 
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								    /// Calculate the errors of all projection factors in a graph
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											2012-07-30 23:40:58 +08:00
										 
									 
								 
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								    Matrix reprojectionErrors(const NonlinearFactorGraph& graph, const Values& values) {
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								      // first count
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								      size_t K = 0, k=0;
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								      BOOST_FOREACH(const NonlinearFactor::shared_ptr& f, graph)
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								        if (boost::dynamic_pointer_cast<const GenericProjectionFactor<Pose3, Point3> >(f)) ++K;
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								      // now fill
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								      Matrix errors(2,K);
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								      BOOST_FOREACH(const NonlinearFactor::shared_ptr& f, graph) {
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								        boost::shared_ptr<const GenericProjectionFactor<Pose3, Point3> > p = boost::dynamic_pointer_cast<const GenericProjectionFactor<Pose3, Point3> >(f);
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								        if (p) errors.col(k++) = p->unwhitenedError(values);
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								      }
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								      return errors;
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								    }
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								  }
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								}
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