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@ -22,13 +22,6 @@
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#include <gtsam/base/Testable.h>
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#ifdef GTSAM_USE_BOOST_FEATURES
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#include <boost/concept_check.hpp>
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#include <boost/concept/requires.hpp>
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#include <boost/type_traits/is_base_of.hpp>
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#include <boost/static_assert.hpp>
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#endif
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#include <utility>
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namespace gtsam {
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@ -19,9 +19,10 @@
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#include <gtsam/base/debug.h>
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#include <gtsam/base/timing.h>
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#include <algorithm>
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#include <cassert>
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#include <cmath>
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#include <cstddef>
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#include <cassert>
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#include <iomanip>
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#include <iostream>
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#include <map>
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@ -19,16 +19,11 @@
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#pragma once
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#include <gtsam/dllexport.h>
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#ifdef GTSAM_USE_BOOST_FEATURES
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#include <boost/concept/assert.hpp>
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#include <boost/range/concepts.hpp>
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#endif
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#include <gtsam/config.h> // for GTSAM_USE_TBB
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#include <gtsam/dllexport.h>
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#include <cstddef>
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#include <cstdint>
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#include <exception>
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#include <string>
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@ -29,10 +29,6 @@
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#include <Eigen/Core> // for Eigen::aligned_allocator
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#ifdef GTSAM_USE_BOOST_FEATURES
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#include <boost/assign/list_inserter.hpp>
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#endif
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#ifdef GTSAM_ENABLE_BOOST_SERIALIZATION
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#include <boost/serialization/nvp.hpp>
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#include <boost/serialization/vector.hpp>
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@ -53,45 +49,6 @@ class BayesTree;
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class HybridValues;
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/** Helper */
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template <class C>
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class CRefCallPushBack {
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C& obj;
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public:
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explicit CRefCallPushBack(C& obj) : obj(obj) {}
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template <typename A>
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void operator()(const A& a) {
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obj.push_back(a);
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}
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};
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/** Helper */
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template <class C>
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class RefCallPushBack {
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C& obj;
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public:
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explicit RefCallPushBack(C& obj) : obj(obj) {}
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template <typename A>
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void operator()(A& a) {
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obj.push_back(a);
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}
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};
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/** Helper */
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template <class C>
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class CRefCallAddCopy {
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C& obj;
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public:
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explicit CRefCallAddCopy(C& obj) : obj(obj) {}
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template <typename A>
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void operator()(const A& a) {
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obj.addCopy(a);
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}
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};
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/**
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* A factor graph is a bipartite graph with factor nodes connected to variable
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* nodes. In this class, however, only factor nodes are kept around.
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@ -215,17 +172,26 @@ class FactorGraph {
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push_back(factor);
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}
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#ifdef GTSAM_USE_BOOST_FEATURES
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/// `+=` works well with boost::assign list inserter.
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/// Append factor to factor graph
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template <class DERIVEDFACTOR>
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typename std::enable_if<
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std::is_base_of<FactorType, DERIVEDFACTOR>::value,
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boost::assign::list_inserter<RefCallPushBack<This>>>::type
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typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value,
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This>::type&
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operator+=(std::shared_ptr<DERIVEDFACTOR> factor) {
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return boost::assign::make_list_inserter(RefCallPushBack<This>(*this))(
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factor);
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push_back(factor);
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return *this;
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}
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/**
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* @brief Overload comma operator to allow for append chaining.
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*
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* E.g. fg += factor1, factor2, ...
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*/
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template <class DERIVEDFACTOR>
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typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value, This>::type& operator,(
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std::shared_ptr<DERIVEDFACTOR> factor) {
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push_back(factor);
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return *this;
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}
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#endif
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/// @}
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/// @name Adding via iterators
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@ -276,18 +242,15 @@ class FactorGraph {
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push_back(factorOrContainer);
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}
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#ifdef GTSAM_USE_BOOST_FEATURES
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/**
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* Add a factor or container of factors, including STL collections,
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* BayesTrees, etc.
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*/
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template <class FACTOR_OR_CONTAINER>
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boost::assign::list_inserter<CRefCallPushBack<This>> operator+=(
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const FACTOR_OR_CONTAINER& factorOrContainer) {
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return boost::assign::make_list_inserter(CRefCallPushBack<This>(*this))(
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factorOrContainer);
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This& operator+=(const FACTOR_OR_CONTAINER& factorOrContainer) {
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push_back(factorOrContainer);
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return *this;
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}
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#endif
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/// @}
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/// @name Specialized versions
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@ -281,6 +281,18 @@ void Ordering::print(const std::string& str,
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cout.flush();
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}
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/* ************************************************************************* */
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Ordering::This& Ordering::operator+=(Key key) {
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this->push_back(key);
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return *this;
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}
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/* ************************************************************************* */
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Ordering::This& Ordering::operator,(Key key) {
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this->push_back(key);
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return *this;
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}
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/* ************************************************************************* */
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Ordering::This& Ordering::operator+=(KeyVector& keys) {
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this->insert(this->end(), keys.begin(), keys.end());
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@ -25,10 +25,6 @@
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#include <gtsam/inference/MetisIndex.h>
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#include <gtsam/base/FastSet.h>
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#ifdef GTSAM_USE_BOOST_FEATURES
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#include <boost/assign/list_inserter.hpp>
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#endif
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#include <algorithm>
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#include <vector>
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Base(keys.begin(), keys.end()) {
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}
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#ifdef GTSAM_USE_BOOST_FEATURES
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/// Add new variables to the ordering as ordering += key1, key2, ... Equivalent to calling
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/// push_back.
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boost::assign::list_inserter<boost::assign_detail::call_push_back<This> > operator+=(
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Key key) {
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return boost::assign::make_list_inserter(
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boost::assign_detail::call_push_back<This>(*this))(key);
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}
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#endif
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/// Add new variables to the ordering as
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/// `ordering += key1, key2, ...`.
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This& operator+=(Key key);
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/// Overloading the comma operator allows for chaining appends
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// e.g. keys += key1, key2
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This& operator,(Key key);
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/**
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* @brief Append new keys to the ordering as `ordering += keys`.
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@ -196,6 +196,20 @@ TEST(Ordering, csr_format_3) {
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EXPECT(adjExpected == adjAcutal);
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}
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/* ************************************************************************* */
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TEST(Ordering, AppendKey) {
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using symbol_shorthand::X;
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Ordering actual;
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actual += X(0);
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Ordering expected1{X(0)};
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EXPECT(assert_equal(expected1, actual));
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actual += X(1), X(2), X(3);
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Ordering expected2{X(0), X(1), X(2), X(3)};
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EXPECT(assert_equal(expected2, actual));
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}
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/* ************************************************************************* */
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TEST(Ordering, AppendVector) {
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using symbol_shorthand::X;
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@ -70,6 +70,28 @@ TEST(GaussianFactorGraph, initialization) {
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EQUALITY(expectedIJS, actualIJS);
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}
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/* ************************************************************************* */
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TEST(GaussianFactorGraph, Append) {
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// Create empty graph
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GaussianFactorGraph fg;
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SharedDiagonal unit2 = noiseModel::Unit::Create(2);
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auto f1 =
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make_shared<JacobianFactor>(0, 10 * I_2x2, -1.0 * Vector::Ones(2), unit2);
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auto f2 = make_shared<JacobianFactor>(0, -10 * I_2x2, 1, 10 * I_2x2,
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Vector2(2.0, -1.0), unit2);
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auto f3 = make_shared<JacobianFactor>(0, -5 * I_2x2, 2, 5 * I_2x2,
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Vector2(0.0, 1.0), unit2);
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fg += f1;
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fg += f2;
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EXPECT_LONGS_EQUAL(2, fg.size());
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fg = GaussianFactorGraph();
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fg += f1, f2, f3;
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EXPECT_LONGS_EQUAL(3, fg.size());
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}
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/* ************************************************************************* */
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TEST(GaussianFactorGraph, sparseJacobian) {
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// Create factor graph:
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