406 lines
12 KiB
C++
406 lines
12 KiB
C++
/* ----------------------------------------------------------------------------
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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 testBAD.cpp
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* @date September 18, 2014
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* @author Frank Dellaert
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* @brief unit tests for Block Automatic Differentiation
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*/
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#include <gtsam/nonlinear/NonlinearFactor.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/slam/GeneralSFMFactor.h>
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#include <gtsam/inference/Key.h>
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#include <gtsam/base/Testable.h>
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#include <boost/make_shared.hpp>
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#include <boost/foreach.hpp>
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#include <CppUnitLite/TestHarness.h>
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namespace gtsam {
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///-----------------------------------------------------------------------------
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/// Expression node. The superclass for objects that do the heavy lifting
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/// An Expression<T> has a pointer to an ExpressionNode<T> underneath
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/// allowing Expressions to have polymorphic behaviour even though they
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/// are passed by value. This is the same way boost::function works.
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/// http://loki-lib.sourceforge.net/html/a00652.html
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template<class T>
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class ExpressionNode {
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public:
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ExpressionNode(){}
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virtual ~ExpressionNode(){}
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virtual void getKeys(std::set<Key>& keys) const = 0;
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virtual T value(const Values& values,
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boost::optional<std::map<Key, Matrix>&> = boost::none) const = 0;
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virtual ExpressionNode<T>* clone() const = 0;
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};
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/// Constant Expression
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template<class T>
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class ConstantExpression : public ExpressionNode<T> {
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T value_;
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public:
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typedef T type;
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/// Constructor with a value, yielding a constant
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ConstantExpression(const T& value) :
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value_(value) {
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}
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virtual ~ConstantExpression(){}
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virtual void getKeys(std::set<Key>& /* keys */) const {}
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virtual T value(const Values& values,
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boost::optional<std::map<Key, Matrix>&> jacobians = boost::none) const {
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return value_;
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}
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virtual ExpressionNode<T>* clone() const { return new ConstantExpression(*this); }
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};
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//-----------------------------------------------------------------------------
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/// Leaf Expression
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template<class T>
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class LeafExpression : public ExpressionNode<T> {
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Key key_;
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public:
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typedef T type;
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/// Constructor with a single key
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LeafExpression(Key key) :
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key_(key) {
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}
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virtual ~LeafExpression(){}
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virtual void getKeys(std::set<Key>& keys) const { keys.insert(key_); }
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virtual T value(const Values& values,
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boost::optional<std::map<Key, Matrix>&> jacobians = boost::none) const {
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const T& value = values.at<T>(key_);
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if( jacobians ) {
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std::map<Key, Matrix>::iterator it = jacobians->find(key_);
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if(it != jacobians->end()) {
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it->second += Eigen::MatrixXd::Identity(value.dim(), value.dim());
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} else {
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(*jacobians)[key_] = Eigen::MatrixXd::Identity(value.dim(), value.dim());
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}
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}
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return value;
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}
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virtual ExpressionNode<T>* clone() const { return new LeafExpression(*this); }
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};
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//-----------------------------------------------------------------------------
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/// Unary Expression
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template<class T, class E>
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class UnaryExpression : public ExpressionNode<T> {
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public:
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typedef T (*function)(const E&, boost::optional<Matrix&>);
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private:
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boost::shared_ptr< ExpressionNode<E> > expression_;
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function f_;
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public:
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typedef T type;
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/// Constructor with a single key
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UnaryExpression(function f, const ExpressionNode<E>& expression) :
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expression_(expression.clone()), f_(f) {
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}
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virtual ~UnaryExpression(){}
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virtual void getKeys(std::set<Key>& keys) const{ expression_->getKeys(keys); }
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virtual T value(const Values& values,
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boost::optional<std::map<Key, Matrix>&> jacobians = boost::none) const {
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T value;
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if(jacobians) {
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Eigen::MatrixXd H;
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value = f_(expression_->value(values, jacobians), H);
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std::map<Key, Matrix>::iterator it = jacobians->begin();
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for( ; it != jacobians->end(); ++it) {
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it->second = H * it->second;
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}
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} else {
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value = f_(expression_->value(values), boost::none);
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}
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return value;
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}
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virtual ExpressionNode<T>* clone() const { return new UnaryExpression(*this); }
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};
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//-----------------------------------------------------------------------------
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/// Binary Expression
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template<class T, class E1, class E2>
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class BinaryExpression : public ExpressionNode<T> {
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public:
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typedef T (*function)(const E1&, const E2&,
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boost::optional<Matrix&>, boost::optional<Matrix&>);
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private:
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boost::shared_ptr< ExpressionNode<E1> > expression1_;
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boost::shared_ptr< ExpressionNode<E2> > expression2_;
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function f_;
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public:
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typedef T type;
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/// Constructor with a single key
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BinaryExpression(function f, const ExpressionNode<E1>& expression1, const ExpressionNode<E2>& expression2) :
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expression1_(expression1.clone()), expression2_(expression2.clone()), f_(f) {
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}
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virtual ~BinaryExpression(){}
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virtual void getKeys(std::set<Key>& keys) const{
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expression1_->getKeys(keys);
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expression2_->getKeys(keys);
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}
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virtual T value(const Values& values,
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boost::optional<std::map<Key, Matrix>&> jacobians = boost::none) const {
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T val;
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if(jacobians) {
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std::map<Key, Matrix> terms1;
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std::map<Key, Matrix> terms2;
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Matrix H1, H2;
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val = f_(expression1_->value(values, terms1), expression2_->value(values, terms2), H1, H2);
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// TODO: both Jacobians and terms are sorted. There must be a simple
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// but fast algorithm that does this.
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typedef std::pair<Key, Matrix> Pair;
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BOOST_FOREACH(const Pair& term, terms1) {
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std::map<Key, Matrix>::iterator it = jacobians->find(term.first);
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if(it != jacobians->end()) {
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it->second += H1 * term.second;
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} else {
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(*jacobians)[term.first] = H1 * term.second;
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}
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}
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BOOST_FOREACH(const Pair& term, terms2) {
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std::map<Key, Matrix>::iterator it = jacobians->find(term.first);
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if(it != jacobians->end()) {
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it->second += H2 * term.second;
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} else {
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(*jacobians)[term.first] = H2 * term.second;
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}
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}
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} else {
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val = f_(expression1_->value(values), expression2_->value(values),
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boost::none, boost::none);
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}
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return val;
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}
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virtual ExpressionNode<T>* clone() const { return new BinaryExpression(*this); }
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};
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template<typename T>
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class Expression {
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public:
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Expression(const ExpressionNode<T>& root) {
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root_.reset(root.clone());
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}
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// Initialize a constant expression
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Expression(const T& value) :
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root_(new ConstantExpression<T>(value)){ }
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// Initialize a leaf expression
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Expression(const Key& key) :
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root_(new LeafExpression<T>(key)) {}
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/// Initialize a unary expression
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template<typename E>
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Expression(typename UnaryExpression<T,E>::function f,
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const Expression<E>& expression) {
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// TODO Assert that root of expression is not null.
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root_.reset(new UnaryExpression<T,E>(f, *expression.root()));
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}
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/// Initialize a binary expression
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template<typename E1, typename E2>
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Expression(typename BinaryExpression<T,E1,E2>::function f,
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const Expression<E1>& expression1,
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const Expression<E2>& expression2) {
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// TODO Assert that root of expressions 1 and 2 are not null.
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root_.reset(new BinaryExpression<T,E1,E2>(f, *expression1.root(),
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*expression2.root()));
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}
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void getKeys(std::set<Key>& keys) const { root_->getKeys(keys); }
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T value(const Values& values,
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boost::optional<std::map<Key, Matrix>&> jacobians = boost::none) const {
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return root_->value(values, jacobians);
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}
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const boost::shared_ptr<ExpressionNode<T> >& root() const{ return root_; }
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private:
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boost::shared_ptr<ExpressionNode<T> > root_;
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};
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//-----------------------------------------------------------------------------
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void printPair(std::pair<Key, Matrix> pair) {
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std::cout << pair.first << ": " << pair.second << std::endl;
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}
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// usage: std::for_each(terms.begin(), terms.end(), printPair);
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//-----------------------------------------------------------------------------
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/// AD Factor
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template<class T>
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class BADFactor: NonlinearFactor {
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const T measurement_;
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const Expression<T> expression_;
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/// get value from expression and calculate error with respect to measurement
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Vector unwhitenedError(const Values& values) const {
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const T& value = expression_.value(values);
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return value.localCoordinates(measurement_);
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}
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public:
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/// Constructor
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BADFactor(const T& measurement, const Expression<T>& expression) :
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measurement_(measurement), expression_(expression) {
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}
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/// Constructor
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BADFactor(const T& measurement, const ExpressionNode<T>& expression) :
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measurement_(measurement), expression_(expression) {
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}
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/**
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* Calculate the error of the factor.
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* This is the log-likelihood, e.g. \f$ 0.5(h(x)-z)^2/\sigma^2 \f$ in case of Gaussian.
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* In this class, we take the raw prediction error \f$ h(x)-z \f$, ask the noise model
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* to transform it to \f$ (h(x)-z)^2/\sigma^2 \f$, and then multiply by 0.5.
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*/
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virtual double error(const Values& values) const {
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if (this->active(values)) {
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const Vector e = unwhitenedError(values);
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return 0.5 * e.squaredNorm();
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} else {
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return 0.0;
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}
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}
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/// get the dimension of the factor (number of rows on linearization)
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size_t dim() const {
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return 0;
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}
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/// linearize to a GaussianFactor
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boost::shared_ptr<GaussianFactor> linearize(const Values& values) const {
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// We will construct an n-ary factor below, where terms is a container whose
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// value type is std::pair<Key, Matrix>, specifying the
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// collection of keys and matrices making up the factor.
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std::map<Key, Matrix> terms;
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expression_.value(values, terms);
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Vector b = unwhitenedError(values);
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SharedDiagonal model = SharedDiagonal();
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return boost::shared_ptr<JacobianFactor>(
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new JacobianFactor(terms, b, model));
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}
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};
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}
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using namespace std;
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using namespace gtsam;
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/* ************************************************************************* */
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Point3 transformTo(const Pose3& x, const Point3& p,
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boost::optional<Matrix&> Dpose, boost::optional<Matrix&> Dpoint) {
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return x.transform_to(p, Dpose, Dpoint);
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}
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Point2 project(const Point3& p, boost::optional<Matrix&> Dpoint) {
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return PinholeCamera<Cal3_S2>::project_to_camera(p, Dpoint);
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}
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template<class CAL>
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Point2 uncalibrate(const CAL& K, const Point2& p, boost::optional<Matrix&> Dcal,
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boost::optional<Matrix&> Dp) {
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return K.uncalibrate(p, Dcal, Dp);
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}
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/* ************************************************************************* */
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TEST(BAD, test) {
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// Create some values
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Values values;
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values.insert(1, Pose3());
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values.insert(2, Point3(0, 0, 1));
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values.insert(3, Cal3_S2());
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// Create old-style factor to create expected value and derivatives
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Point2 measured(-17, 30);
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SharedNoiseModel model = noiseModel::Unit::Create(2);
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GeneralSFMFactor2<Cal3_S2> old(measured, model, 1, 2, 3);
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double expected_error = old.error(values);
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GaussianFactor::shared_ptr expected = old.linearize(values);
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// Create leaves
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Expression<Pose3> x(1);
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Expression<Point3> p(2);
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Expression<Cal3_S2> K(3);
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// Create expression tree
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Expression<Point3> p_cam(transformTo, x, p);
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Expression<Point2> projection(project, p_cam);
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Expression<Point2> uv_hat(uncalibrate, K, projection);
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// Check getKeys
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std::set<Key> keys;
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uv_hat.getKeys(keys);
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EXPECT_LONGS_EQUAL(3, keys.size());
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// Create factor
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BADFactor<Point2> f(measured, uv_hat);
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// Check value
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EXPECT_DOUBLES_EQUAL(expected_error, f.error(values), 1e-9);
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// Check dimension
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EXPECT_LONGS_EQUAL(0, f.dim());
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// Check linearization
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boost::shared_ptr<GaussianFactor> gf = f.linearize(values);
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EXPECT( assert_equal(*expected, *gf, 1e-9));
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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/* ************************************************************************* */
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