Merge pull request #1558 from borglab/ordering-helpers

Overload `+=`, `,` operator
release/4.3a0
Varun Agrawal 2023-07-17 02:37:11 -04:00 committed by GitHub
commit ef7bab834c
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8 changed files with 78 additions and 84 deletions

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@ -22,13 +22,6 @@
#include <gtsam/base/Testable.h>
#ifdef GTSAM_USE_BOOST_FEATURES
#include <boost/concept_check.hpp>
#include <boost/concept/requires.hpp>
#include <boost/type_traits/is_base_of.hpp>
#include <boost/static_assert.hpp>
#endif
#include <utility>
namespace gtsam {

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@ -19,9 +19,10 @@
#include <gtsam/base/debug.h>
#include <gtsam/base/timing.h>
#include <algorithm>
#include <cassert>
#include <cmath>
#include <cstddef>
#include <cassert>
#include <iomanip>
#include <iostream>
#include <map>

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@ -19,16 +19,11 @@
#pragma once
#include <gtsam/config.h> // for GTSAM_USE_TBB
#include <gtsam/dllexport.h>
#ifdef GTSAM_USE_BOOST_FEATURES
#include <boost/concept/assert.hpp>
#include <boost/range/concepts.hpp>
#endif
#include <gtsam/config.h> // for GTSAM_USE_TBB
#include <cstddef>
#include <cstdint>
#include <exception>
#include <string>

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@ -29,10 +29,6 @@
#include <Eigen/Core> // for Eigen::aligned_allocator
#ifdef GTSAM_USE_BOOST_FEATURES
#include <boost/assign/list_inserter.hpp>
#endif
#ifdef GTSAM_ENABLE_BOOST_SERIALIZATION
#include <boost/serialization/nvp.hpp>
#include <boost/serialization/vector.hpp>
@ -53,45 +49,6 @@ class BayesTree;
class HybridValues;
/** Helper */
template <class C>
class CRefCallPushBack {
C& obj;
public:
explicit CRefCallPushBack(C& obj) : obj(obj) {}
template <typename A>
void operator()(const A& a) {
obj.push_back(a);
}
};
/** Helper */
template <class C>
class RefCallPushBack {
C& obj;
public:
explicit RefCallPushBack(C& obj) : obj(obj) {}
template <typename A>
void operator()(A& a) {
obj.push_back(a);
}
};
/** Helper */
template <class C>
class CRefCallAddCopy {
C& obj;
public:
explicit CRefCallAddCopy(C& obj) : obj(obj) {}
template <typename A>
void operator()(const A& a) {
obj.addCopy(a);
}
};
/**
* A factor graph is a bipartite graph with factor nodes connected to variable
* nodes. In this class, however, only factor nodes are kept around.
@ -215,17 +172,26 @@ class FactorGraph {
push_back(factor);
}
#ifdef GTSAM_USE_BOOST_FEATURES
/// `+=` works well with boost::assign list inserter.
/// Append factor to factor graph
template <class DERIVEDFACTOR>
typename std::enable_if<
std::is_base_of<FactorType, DERIVEDFACTOR>::value,
boost::assign::list_inserter<RefCallPushBack<This>>>::type
typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value,
This>::type&
operator+=(std::shared_ptr<DERIVEDFACTOR> factor) {
return boost::assign::make_list_inserter(RefCallPushBack<This>(*this))(
factor);
push_back(factor);
return *this;
}
/**
* @brief Overload comma operator to allow for append chaining.
*
* E.g. fg += factor1, factor2, ...
*/
template <class DERIVEDFACTOR>
typename std::enable_if<std::is_base_of<FactorType, DERIVEDFACTOR>::value, This>::type& operator,(
std::shared_ptr<DERIVEDFACTOR> factor) {
push_back(factor);
return *this;
}
#endif
/// @}
/// @name Adding via iterators
@ -276,18 +242,15 @@ class FactorGraph {
push_back(factorOrContainer);
}
#ifdef GTSAM_USE_BOOST_FEATURES
/**
* Add a factor or container of factors, including STL collections,
* BayesTrees, etc.
*/
template <class FACTOR_OR_CONTAINER>
boost::assign::list_inserter<CRefCallPushBack<This>> operator+=(
const FACTOR_OR_CONTAINER& factorOrContainer) {
return boost::assign::make_list_inserter(CRefCallPushBack<This>(*this))(
factorOrContainer);
This& operator+=(const FACTOR_OR_CONTAINER& factorOrContainer) {
push_back(factorOrContainer);
return *this;
}
#endif
/// @}
/// @name Specialized versions

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@ -281,6 +281,18 @@ void Ordering::print(const std::string& str,
cout.flush();
}
/* ************************************************************************* */
Ordering::This& Ordering::operator+=(Key key) {
this->push_back(key);
return *this;
}
/* ************************************************************************* */
Ordering::This& Ordering::operator,(Key key) {
this->push_back(key);
return *this;
}
/* ************************************************************************* */
Ordering::This& Ordering::operator+=(KeyVector& keys) {
this->insert(this->end(), keys.begin(), keys.end());

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@ -25,10 +25,6 @@
#include <gtsam/inference/MetisIndex.h>
#include <gtsam/base/FastSet.h>
#ifdef GTSAM_USE_BOOST_FEATURES
#include <boost/assign/list_inserter.hpp>
#endif
#include <algorithm>
#include <vector>
@ -61,15 +57,13 @@ public:
Base(keys.begin(), keys.end()) {
}
#ifdef GTSAM_USE_BOOST_FEATURES
/// Add new variables to the ordering as ordering += key1, key2, ... Equivalent to calling
/// push_back.
boost::assign::list_inserter<boost::assign_detail::call_push_back<This> > operator+=(
Key key) {
return boost::assign::make_list_inserter(
boost::assign_detail::call_push_back<This>(*this))(key);
}
#endif
/// Add new variables to the ordering as
/// `ordering += key1, key2, ...`.
This& operator+=(Key key);
/// Overloading the comma operator allows for chaining appends
// e.g. keys += key1, key2
This& operator,(Key key);
/**
* @brief Append new keys to the ordering as `ordering += keys`.

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@ -196,6 +196,20 @@ TEST(Ordering, csr_format_3) {
EXPECT(adjExpected == adjAcutal);
}
/* ************************************************************************* */
TEST(Ordering, AppendKey) {
using symbol_shorthand::X;
Ordering actual;
actual += X(0);
Ordering expected1{X(0)};
EXPECT(assert_equal(expected1, actual));
actual += X(1), X(2), X(3);
Ordering expected2{X(0), X(1), X(2), X(3)};
EXPECT(assert_equal(expected2, actual));
}
/* ************************************************************************* */
TEST(Ordering, AppendVector) {
using symbol_shorthand::X;

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@ -70,6 +70,28 @@ TEST(GaussianFactorGraph, initialization) {
EQUALITY(expectedIJS, actualIJS);
}
/* ************************************************************************* */
TEST(GaussianFactorGraph, Append) {
// Create empty graph
GaussianFactorGraph fg;
SharedDiagonal unit2 = noiseModel::Unit::Create(2);
auto f1 =
make_shared<JacobianFactor>(0, 10 * I_2x2, -1.0 * Vector::Ones(2), unit2);
auto f2 = make_shared<JacobianFactor>(0, -10 * I_2x2, 1, 10 * I_2x2,
Vector2(2.0, -1.0), unit2);
auto f3 = make_shared<JacobianFactor>(0, -5 * I_2x2, 2, 5 * I_2x2,
Vector2(0.0, 1.0), unit2);
fg += f1;
fg += f2;
EXPECT_LONGS_EQUAL(2, fg.size());
fg = GaussianFactorGraph();
fg += f1, f2, f3;
EXPECT_LONGS_EQUAL(3, fg.size());
}
/* ************************************************************************* */
TEST(GaussianFactorGraph, sparseJacobian) {
// Create factor graph: