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Removed Permuted views to simplify a lot of code - all objects that need to be permuted now have their data rearranged instead of using the "Permuted" indirection class.

release/4.3a0
Richard Roberts 2012-06-30 01:45:21 +00:00
parent 5431d74573
commit 57ca7d77db
15 changed files with 189 additions and 469 deletions
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83
gtsam/inference/Permutation.h
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@ -26,7 +26,7 @@
namespace gtsam { namespace gtsam {
/** /**
* A permutation reorders variables, for example to reduce fill-in during * A permutation reorders variables, for example to reduce fill-in during
* elimination. To save computation, the permutation can be applied to * elimination. To save computation, the permutation can be applied to
* the necessary data structures only once, then multiple computations * the necessary data structures only once, then multiple computations
@ -151,8 +151,8 @@ public:
*/ */
Permutation::shared_ptr inverse() const; Permutation::shared_ptr inverse() const;
const_iterator begin() const { return rangeIndices_.begin(); } ///<TODO: comment const_iterator begin() const { return rangeIndices_.begin(); } ///< Iterate through the indices
const_iterator end() const { return rangeIndices_.end(); } ///<TODO: comment const_iterator end() const { return rangeIndices_.end(); } ///< Iterate through the indices
/// @} /// @}
@ -167,8 +167,8 @@ public:
*/ */
Permutation::shared_ptr partialPermutation(const Permutation& selector, const Permutation& partialPermutation) const; Permutation::shared_ptr partialPermutation(const Permutation& selector, const Permutation& partialPermutation) const;
iterator begin() { return rangeIndices_.begin(); } ///<TODO: comment iterator begin() { return rangeIndices_.begin(); } ///< Iterate through the indices
iterator end() { return rangeIndices_.end(); } ///<TODO: comment iterator end() { return rangeIndices_.end(); } ///< Iterate through the indices
protected: protected:
void check(Index variable) const { assert(variable < rangeIndices_.size()); } void check(Index variable) const { assert(variable < rangeIndices_.size()); }
@ -176,77 +176,4 @@ protected:
/// @} /// @}
}; };
/**
* Syntactic sugar for accessing another container through a permutation.
* Allows the syntax:
* Permuted<Container> permuted(permutation, container);
* permuted[index1];
* permuted[index2];
* which is equivalent to:
* container[permutation[index1]];
* container[permutation[index2]];
* but more concise.
*/
template<typename CONTAINER>
class Permuted {
Permutation permutation_;
CONTAINER& container_;
public:
typedef typename CONTAINER::iterator::value_type value_type;
/** Construct as a permuted view on the Container. The permutation is copied
* but only a reference to the container is stored.
*/
Permuted(const Permutation& permutation, CONTAINER& container) : permutation_(permutation), container_(container) {}
/** Construct as a view on the Container with an identity permutation. Only
* a reference to the container is stored.
*/
Permuted(CONTAINER& container) : permutation_(Permutation::Identity(container.size())), container_(container) {}
/** Print */
void print(const std::string& str = "") const {
std::cout << str;
permutation_.print(" permutation: ");
container_.print(" container: ");
}
/** Access the container through the permutation */
value_type& operator[](size_t index) { return container_[permutation_[index]]; }
/** Access the container through the permutation (const version) */
const value_type& operator[](size_t index) const { return container_[permutation_[index]]; }
/** Assignment operator for cloning in ISAM2 */
Permuted<CONTAINER> operator=(const Permuted<CONTAINER>& other) {
permutation_ = other.permutation_;
container_ = other.container_;
return *this;
}
/** Permute this view by applying a permutation to the underlying permutation */
void permute(const Permutation& permutation) { assert(permutation.size() == this->size()); permutation_ = *permutation_.permute(permutation); }
/** Access the underlying container */
CONTAINER* operator->() { return &container_; }
/** Access the underlying container (const version) */
const CONTAINER* operator->() const { return &container_; }
/** Size of the underlying container */
size_t size() const { return container_.size(); }
/** Access to the underlying container */
CONTAINER& container() { return container_; }
/** Access to the underlying container (const version) */
const CONTAINER& container() const { return container_; }
/** Access the underlying permutation */
Permutation& permutation() { return permutation_; }
const Permutation& permutation() const { return permutation_; }
};
} }

52
gtsam/inference/VariableIndex.cpp
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@ -18,37 +18,12 @@
#include <iostream> #include <iostream>
#include <gtsam/inference/VariableIndex.h> #include <gtsam/inference/VariableIndex.h>
#include <gtsam/inference/Permutation.h>
namespace gtsam { namespace gtsam {
using namespace std; using namespace std;
/* ************************************************************************* */
VariableIndex::VariableIndex(const VariableIndex& other) :
index_(indexUnpermuted_) {
*this = other;
}
/* ************************************************************************* */
VariableIndex& VariableIndex::operator=(const VariableIndex& rhs) {
index_ = rhs.index_;
nFactors_ = rhs.nFactors_;
nEntries_ = rhs.nEntries_;
return *this;
}
/* ************************************************************************* */
void VariableIndex::permute(const Permutation& permutation) {
#ifndef NDEBUG
// Assert that the permutation does not leave behind any non-empty variables,
// otherwise the nFactors and nEntries counts would be incorrect.
for(Index j=0; j<this->index_.size(); ++j)
if(find(permutation.begin(), permutation.end(), j) == permutation.end())
assert(this->operator[](j).empty());
#endif
index_.permute(permutation);
}
/* ************************************************************************* */ /* ************************************************************************* */
bool VariableIndex::equals(const VariableIndex& other, double tol) const { bool VariableIndex::equals(const VariableIndex& other, double tol) const {
if(this->nEntries_ == other.nEntries_ && this->nFactors_ == other.nFactors_) { if(this->nEntries_ == other.nEntries_ && this->nFactors_ == other.nFactors_) {
@ -66,17 +41,13 @@ bool VariableIndex::equals(const VariableIndex& other, double tol) const {
/* ************************************************************************* */ /* ************************************************************************* */
void VariableIndex::print(const string& str) const { void VariableIndex::print(const string& str) const {
cout << str << "\n"; cout << str;
cout << "nEntries = " << nEntries() << ", nFactors = " << nFactors() << "\n"; cout << "nEntries = " << nEntries() << ", nFactors = " << nFactors() << "\n";
Index var = 0; for(Index var = 0; var < size(); ++var) {
BOOST_FOREACH(const Factors& variable, index_.container()) { cout << "var " << var << ":";
Permutation::const_iterator rvar = find(index_.permutation().begin(), index_.permutation().end(), var); BOOST_FOREACH(const size_t factor, index_[var])
assert(rvar != index_.permutation().end());
cout << "var " << (rvar-index_.permutation().begin()) << ":";
BOOST_FOREACH(const size_t factor, variable)
cout << " " << factor; cout << " " << factor;
cout << "\n"; cout << "\n";
++ var;
} }
cout << flush; cout << flush;
} }
@ -85,7 +56,7 @@ void VariableIndex::print(const string& str) const {
void VariableIndex::outputMetisFormat(ostream& os) const { void VariableIndex::outputMetisFormat(ostream& os) const {
os << size() << " " << nFactors() << "\n"; os << size() << " " << nFactors() << "\n";
// run over variables, which will be hyper-edges. // run over variables, which will be hyper-edges.
BOOST_FOREACH(const Factors& variable, index_.container()) { BOOST_FOREACH(const Factors& variable, index_) {
// every variable is a hyper-edge covering its factors // every variable is a hyper-edge covering its factors
BOOST_FOREACH(const size_t factor, variable) BOOST_FOREACH(const size_t factor, variable)
os << (factor+1) << " "; // base 1 os << (factor+1) << " "; // base 1
@ -94,4 +65,15 @@ void VariableIndex::outputMetisFormat(ostream& os) const {
os << flush; os << flush;
} }
/* ************************************************************************* */
void VariableIndex::permuteInPlace(const Permutation& permutation) {
// Create new index and move references to data into it in permuted order
vector<VariableIndex::Factors> newIndex(this->size());
for(Index i = 0; i < newIndex.size(); ++i)
newIndex[i].swap(this->index_[permutation[i]]);
// Move reference to entire index into the VariableIndex
index_.swap(newIndex);
}
} }

49
gtsam/inference/VariableIndex.h
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@ -22,10 +22,12 @@
#include <boost/foreach.hpp> #include <boost/foreach.hpp>
#include <gtsam/base/FastList.h> #include <gtsam/base/FastList.h>
#include <gtsam/inference/Permutation.h> #include <gtsam/base/types.h>
namespace gtsam { namespace gtsam {
class Permutation;
/** /**
* The VariableIndex class computes and stores the block column structure of a * The VariableIndex class computes and stores the block column structure of a
* factor graph. The factor graph stores a collection of factors, each of * factor graph. The factor graph stores a collection of factors, each of
@ -44,8 +46,7 @@ public:
typedef Factors::const_iterator Factor_const_iterator; typedef Factors::const_iterator Factor_const_iterator;
protected: protected:
std::vector<Factors> indexUnpermuted_; std::vector<Factors> index_;
Permuted<std::vector<Factors> > index_; // Permuted view of indexUnpermuted.
size_t nFactors_; // Number of factors in the original factor graph. size_t nFactors_; // Number of factors in the original factor graph.
size_t nEntries_; // Sum of involved variable counts of each factor. size_t nEntries_; // Sum of involved variable counts of each factor.
@ -55,7 +56,7 @@ public:
/// @{ /// @{
/** Default constructor, creates an empty VariableIndex */ /** Default constructor, creates an empty VariableIndex */
VariableIndex() : index_(indexUnpermuted_), nFactors_(0), nEntries_(0) {} VariableIndex() : nFactors_(0), nEntries_(0) {}
/** /**
* Create a VariableIndex that computes and stores the block column structure * Create a VariableIndex that computes and stores the block column structure
@ -70,16 +71,6 @@ public:
*/ */
template<class FactorGraph> VariableIndex(const FactorGraph& factorGraph); template<class FactorGraph> VariableIndex(const FactorGraph& factorGraph);
/**
* Copy constructor
*/
VariableIndex(const VariableIndex& other);
/**
* Assignment operator
*/
VariableIndex& operator=(const VariableIndex& rhs);
/// @} /// @}
/// @name Standard Interface /// @name Standard Interface
/// @{ /// @{
@ -120,9 +111,6 @@ public:
/// @name Advanced Interface /// @name Advanced Interface
/// @{ /// @{
/** Access a list of factors by variable */
Factors& operator[](Index variable) { checkVar(variable); return index_[variable]; }
/** /**
* Augment the variable index with new factors. This can be used when * Augment the variable index with new factors. This can be used when
* solving problems incrementally. * solving problems incrementally.
@ -137,11 +125,8 @@ public:
*/ */
template<typename CONTAINER, class FactorGraph> void remove(const CONTAINER& indices, const FactorGraph& factors); template<typename CONTAINER, class FactorGraph> void remove(const CONTAINER& indices, const FactorGraph& factors);
/** /// Permute the variables in the VariableIndex according to the given permutation
* Apply a variable permutation. Does not rearrange data, just permutes void permuteInPlace(const Permutation& permutation);
* future lookups by variable.
*/
void permute(const Permutation& permutation);
protected: protected:
Factor_iterator factorsBegin(Index variable) { checkVar(variable); return index_[variable].begin(); } ///<TODO: comment Factor_iterator factorsBegin(Index variable) { checkVar(variable); return index_[variable].begin(); } ///<TODO: comment
@ -150,13 +135,13 @@ protected:
Factor_const_iterator factorsBegin(Index variable) const { checkVar(variable); return index_[variable].begin(); } ///<TODO: comment Factor_const_iterator factorsBegin(Index variable) const { checkVar(variable); return index_[variable].begin(); } ///<TODO: comment
Factor_const_iterator factorsEnd(Index variable) const { checkVar(variable); return index_[variable].end(); } ///<TODO: comment Factor_const_iterator factorsEnd(Index variable) const { checkVar(variable); return index_[variable].end(); } ///<TODO: comment
///TODO: comment /// Internal constructor to allocate a VariableIndex of the requested size
VariableIndex(size_t nVars) : indexUnpermuted_(nVars), index_(indexUnpermuted_), nFactors_(0), nEntries_(0) {} VariableIndex(size_t nVars) : index_(nVars), nFactors_(0), nEntries_(0) {}
///TODO: comment /// Internal check of the validity of a variable
void checkVar(Index variable) const { assert(variable < index_.size()); } void checkVar(Index variable) const { assert(variable < index_.size()); }
///TODO: comment /// Internal function to populate the variable index from a factor graph
template<class FactorGraph> void fill(const FactorGraph& factorGraph); template<class FactorGraph> void fill(const FactorGraph& factorGraph);
/// @} /// @}
@ -183,7 +168,7 @@ void VariableIndex::fill(const FactorGraph& factorGraph) {
/* ************************************************************************* */ /* ************************************************************************* */
template<class FactorGraph> template<class FactorGraph>
VariableIndex::VariableIndex(const FactorGraph& factorGraph) : VariableIndex::VariableIndex(const FactorGraph& factorGraph) :
index_(indexUnpermuted_), nFactors_(0), nEntries_(0) { nFactors_(0), nEntries_(0) {
// If the factor graph is empty, return an empty index because inside this // If the factor graph is empty, return an empty index because inside this
// if block we assume at least one factor. // if block we assume at least one factor.
@ -200,8 +185,7 @@ VariableIndex::VariableIndex(const FactorGraph& factorGraph) :
} }
// Allocate array // Allocate array
index_.container().resize(maxVar+1); index_.resize(maxVar+1);
index_.permutation() = Permutation::Identity(maxVar+1);
fill(factorGraph); fill(factorGraph);
} }
@ -210,7 +194,7 @@ VariableIndex::VariableIndex(const FactorGraph& factorGraph) :
/* ************************************************************************* */ /* ************************************************************************* */
template<class FactorGraph> template<class FactorGraph>
VariableIndex::VariableIndex(const FactorGraph& factorGraph, Index nVariables) : VariableIndex::VariableIndex(const FactorGraph& factorGraph, Index nVariables) :
indexUnpermuted_(nVariables), index_(indexUnpermuted_), nFactors_(0), nEntries_(0) { index_(nVariables), nFactors_(0), nEntries_(0) {
fill(factorGraph); fill(factorGraph);
} }
@ -233,10 +217,7 @@ void VariableIndex::augment(const FactorGraph& factors) {
// Allocate index // Allocate index
Index originalSize = index_.size(); Index originalSize = index_.size();
index_.container().resize(std::max(index_.size(), maxVar+1)); index_.resize(std::max(index_.size(), maxVar+1));
index_.permutation().resize(index_.container().size());
for(Index var=originalSize; var<index_.permutation().size(); ++var)
index_.permutation()[var] = var;
// Augment index mapping from variable id to factor index // Augment index mapping from variable id to factor index
size_t orignFactors = nFactors_; size_t orignFactors = nFactors_;

36
gtsam/linear/GaussianConditional.cpp
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@ -182,34 +182,18 @@ JacobianFactor::shared_ptr GaussianConditional::toFactor() const {
return JacobianFactor::shared_ptr(new JacobianFactor(*this)); return JacobianFactor::shared_ptr(new JacobianFactor(*this));
} }
/* ************************************************************************* */
template<class VALUES>
inline static void doSolveInPlace(const GaussianConditional& conditional, VALUES& x) {
// Helper function to solve-in-place on a VectorValues or Permuted<VectorValues>,
// called by GaussianConditional::solveInPlace(VectorValues&) and by
// GaussianConditional::solveInPlace(Permuted<VectorValues>&).
static const bool debug = false;
if(debug) conditional.print("Solving conditional in place");
Vector xS = internal::extractVectorValuesSlices(x, conditional.beginParents(), conditional.endParents());
xS = conditional.get_d() - conditional.get_S() * xS;
Vector soln = conditional.get_R().triangularView<Eigen::Upper>().solve(xS);
if(debug) {
gtsam::print(Matrix(conditional.get_R()), "Calling backSubstituteUpper on ");
gtsam::print(soln, "full back-substitution solution: ");
}
internal::writeVectorValuesSlices(soln, x, conditional.beginFrontals(), conditional.endFrontals());
}
/* ************************************************************************* */ /* ************************************************************************* */
void GaussianConditional::solveInPlace(VectorValues& x) const { void GaussianConditional::solveInPlace(VectorValues& x) const {
doSolveInPlace(*this, x); // Call helper version above static const bool debug = false;
} if(debug) this->print("Solving conditional in place");
Vector xS = internal::extractVectorValuesSlices(x, this->beginParents(), this->endParents());
/* ************************************************************************* */ xS = this->get_d() - this->get_S() * xS;
void GaussianConditional::solveInPlace(Permuted<VectorValues>& x) const { Vector soln = this->get_R().triangularView<Eigen::Upper>().solve(xS);
doSolveInPlace(*this, x); // Call helper version above if(debug) {
gtsam::print(Matrix(this->get_R()), "Calling backSubstituteUpper on ");
gtsam::print(soln, "full back-substitution solution: ");
}
internal::writeVectorValuesSlices(soln, x, this->beginFrontals(), this->endFrontals());
} }
/* ************************************************************************* */ /* ************************************************************************* */

17
gtsam/linear/GaussianConditional.h
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@ -196,23 +196,6 @@ public:
*/ */
void solveInPlace(VectorValues& x) const; void solveInPlace(VectorValues& x) const;
/**
* Solves a conditional Gaussian and writes the solution into the entries of
* \c x for each frontal variable of the conditional (version for permuted
* VectorValues). The parents are assumed to have already been solved in
* and their values are read from \c x. This function works for multiple
* frontal variables.
*
* Given the Gaussian conditional with log likelihood \f$ |R x_f - (d - S x_s)|^2,
* where \f$ f \f$ are the frontal variables and \f$ s \f$ are the separator
* variables of this conditional, this solve function computes
* \f$ x_f = R^{-1} (d - S x_s) \f$ using back-substitution.
*
* @param x VectorValues structure with solved parents \f$ x_s \f$, and into which the
* solution \f$ x_f \f$ will be written.
*/
void solveInPlace(Permuted<VectorValues>& x) const;
// functions for transpose backsubstitution // functions for transpose backsubstitution
/** /**

40
gtsam/linear/VectorValues.cpp
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@ -17,10 +17,12 @@
*/ */
#include <gtsam/base/FastVector.h> #include <gtsam/base/FastVector.h>
#include <gtsam/inference/Permutation.h>
#include <gtsam/linear/VectorValues.h> #include <gtsam/linear/VectorValues.h>
using namespace std; using namespace std;
using namespace gtsam;
namespace gtsam {
/* ************************************************************************* */ /* ************************************************************************* */
VectorValues::VectorValues(const VectorValues& other) { VectorValues::VectorValues(const VectorValues& other) {
@ -166,20 +168,24 @@ void VectorValues::operator+=(const VectorValues& c) {
} }
/* ************************************************************************* */ /* ************************************************************************* */
VectorValues& VectorValues::operator=(const Permuted<VectorValues>& rhs) { VectorValues VectorValues::permute(const Permutation& permutation) const {
if(this->size() != rhs.size()) // Create result and allocate space
throw std::invalid_argument("VectorValues assignment from Permuted<VectorValues> requires pre-allocation, see documentation."); VectorValues lhs;
for(size_t j=0; j<this->size(); ++j) { lhs.values_.resize(this->dim());
if(exists(j)) { lhs.maps_.reserve(this->size());
SubVector& l(this->at(j));
const SubVector& r(rhs[j]); // Copy values from this VectorValues to the permuted VectorValues
if(l.rows() != r.rows()) size_t lhsPos = 0;
throw std::invalid_argument("VectorValues assignment from Permuted<VectorValues> requires pre-allocation, see documentation."); for(size_t i = 0; i < this->size(); ++i) {
l = r; // Map the next LHS subvector to the next slice of the LHS vector
} else { lhs.maps_.push_back(SubVector(lhs.values_, lhsPos, this->at(permutation[i]).size()));
if(rhs.container().exists(rhs.permutation()[j])) // Copy the data from the RHS subvector to the LHS subvector
throw std::invalid_argument("VectorValues assignment from Permuted<VectorValues> requires pre-allocation, see documentation."); lhs.maps_[i] = this->at(permutation[i]);
} // Increment lhs position
} lhsPos += lhs.maps_[i].size();
return *this; }
return lhs;
}
} }

13
gtsam/linear/VectorValues.h
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@ -19,7 +19,6 @@
#include <gtsam/base/Vector.h> #include <gtsam/base/Vector.h>
#include <gtsam/base/types.h> #include <gtsam/base/types.h>
#include <gtsam/inference/Permutation.h>
#include <boost/lexical_cast.hpp> #include <boost/lexical_cast.hpp>
#include <boost/foreach.hpp> #include <boost/foreach.hpp>
@ -29,6 +28,9 @@
namespace gtsam { namespace gtsam {
// Forward declarations
class Permutation;
/** /**
* This class represents a collection of vector-valued variables associated * This class represents a collection of vector-valued variables associated
* each with a unique integer index. It is typically used to store the variables * each with a unique integer index. It is typically used to store the variables
@ -288,10 +290,11 @@ namespace gtsam {
*/ */
void operator+=(const VectorValues& c); void operator+=(const VectorValues& c);
/** Assignment operator from Permuted<VectorValues>, requires the dimensions /**
* of the assignee to already be properly pre-allocated. * Permute the entries of this VectorValues, returns a new VectorValues as
*/ * the result.
VectorValues& operator=(const Permuted<VectorValues>& rhs); */
VectorValues permute(const Permutation& permutation) const;
/// @} /// @}

49
gtsam/linear/tests/testGaussianConditional.cpp
View File

@ -267,55 +267,6 @@ TEST( GaussianConditional, solve_multifrontal )
} }
/* ************************************************************************* */
TEST( GaussianConditional, solve_multifrontal_permuted )
{
// create full system, 3 variables, 2 frontals, all 2 dim
Matrix full_matrix = Matrix_(4, 7,
1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 0.1,
0.0, 1.0, 0.0, 2.0, 0.0, 3.0, 0.2,
0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.3,
0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.4);
// 3 variables, all dim=2
vector<size_t> dims; dims += 2, 2, 2, 1;
GaussianConditional::rsd_type matrices(full_matrix, dims.begin(), dims.end());
Vector sigmas = ones(4);
vector<size_t> cgdims; cgdims += _x_, _x1_, _l1_;
GaussianConditional cg(cgdims.begin(), cgdims.end(), 2, matrices, sigmas);
EXPECT(assert_equal(Vector_(4, 0.1, 0.2, 0.3, 0.4), cg.get_d()));
// partial solution
Vector sl1 = Vector_(2, 9.0, 10.0);
// elimination order; _x_, _x1_, _l1_
VectorValues actualUnpermuted(vector<size_t>(3, 2));
Permutation permutation(3);
permutation[0] = 2;
permutation[1] = 0;
permutation[2] = 1;
Permuted<VectorValues> actual(permutation, actualUnpermuted);
actual[_x_] = Vector_(2, 0.1, 0.2); // rhs
actual[_x1_] = Vector_(2, 0.3, 0.4); // rhs
actual[_l1_] = sl1; // parent
VectorValues expectedUnpermuted(vector<size_t>(3, 2));
Permuted<VectorValues> expected(permutation, expectedUnpermuted);
expected[_x_] = Vector_(2, -3.1,-3.4);
expected[_x1_] = Vector_(2, -11.9,-13.2);
expected[_l1_] = sl1;
// verify indices/size
EXPECT_LONGS_EQUAL(3, cg.size());
EXPECT_LONGS_EQUAL(4, cg.dim());
// solve and verify
cg.solveInPlace(actual);
EXPECT(assert_equal(expected.container(), actual.container(), tol));
}
/* ************************************************************************* */ /* ************************************************************************* */
TEST( GaussianConditional, solveTranspose ) { TEST( GaussianConditional, solveTranspose ) {
static const Index _y_=1; static const Index _y_=1;

59
gtsam/linear/tests/testVectorValues.cpp
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@ -421,52 +421,31 @@ TEST(VectorValues, hasSameStructure) {
EXPECT(!v1.hasSameStructure(VectorValues())); EXPECT(!v1.hasSameStructure(VectorValues()));
} }
/* ************************************************************************* */ /* ************************************************************************* */
TEST(VectorValues, permuted_combined) { TEST(VectorValues, permute) {
Vector v1 = Vector_(3, 1.0,2.0,3.0);
Vector v2 = Vector_(2, 4.0,5.0);
Vector v3 = Vector_(4, 6.0,7.0,8.0,9.0);
vector<size_t> dims(3); dims[0]=3; dims[1]=2; dims[2]=4; VectorValues original;
VectorValues combined(dims); original.insert(0, Vector_(1, 1.0));
combined[0] = v1; original.insert(1, Vector_(2, 2.0, 3.0));
combined[1] = v2; original.insert(2, Vector_(2, 4.0, 5.0));
combined[2] = v3; original.insert(3, Vector_(2, 6.0, 7.0));
Permutation perm1(3); VectorValues expected;
perm1[0] = 1; expected.insert(0, Vector_(2, 4.0, 5.0)); // from 2
perm1[1] = 2; expected.insert(1, Vector_(1, 1.0)); // from 0
perm1[2] = 0; expected.insert(2, Vector_(2, 6.0, 7.0)); // from 3
expected.insert(3, Vector_(2, 2.0, 3.0)); // from 1
Permutation perm2(3); Permutation permutation(4);
perm2[0] = 1; permutation[0] = 2;
perm2[1] = 2; permutation[1] = 0;
perm2[2] = 0; permutation[2] = 3;
permutation[3] = 1;
Permuted<VectorValues> permuted1(combined); VectorValues actual = original.permute(permutation);
CHECK(assert_equal(v1, permuted1[0]))
CHECK(assert_equal(v2, permuted1[1]))
CHECK(assert_equal(v3, permuted1[2]))
permuted1.permute(perm1); EXPECT(assert_equal(expected, actual));
CHECK(assert_equal(v1, permuted1[2]))
CHECK(assert_equal(v2, permuted1[0]))
CHECK(assert_equal(v3, permuted1[1]))
permuted1.permute(perm2);
CHECK(assert_equal(v1, permuted1[1]))
CHECK(assert_equal(v2, permuted1[2]))
CHECK(assert_equal(v3, permuted1[0]))
Permuted<VectorValues> permuted2(perm1, combined);
CHECK(assert_equal(v1, permuted2[2]))
CHECK(assert_equal(v2, permuted2[0]))
CHECK(assert_equal(v3, permuted2[1]))
permuted2.permute(perm2);
CHECK(assert_equal(v1, permuted2[1]))
CHECK(assert_equal(v2, permuted2[2]))
CHECK(assert_equal(v3, permuted2[0]))
} }
/* ************************************************************************* */ /* ************************************************************************* */

65
gtsam/nonlinear/ISAM2-impl.cpp
View File

@ -29,8 +29,8 @@ namespace gtsam {
/* ************************************************************************* */ /* ************************************************************************* */
void ISAM2::Impl::AddVariables( void ISAM2::Impl::AddVariables(
const Values& newTheta, Values& theta, Permuted<VectorValues>& delta, const Values& newTheta, Values& theta, VectorValues& delta,
Permuted<VectorValues>& deltaNewton, Permuted<VectorValues>& deltaGradSearch, vector<bool>& replacedKeys, VectorValues& deltaNewton, VectorValues& deltaGradSearch, vector<bool>& replacedKeys,
Ordering& ordering, Base::Nodes& nodes, const KeyFormatter& keyFormatter) { Ordering& ordering, Base::Nodes& nodes, const KeyFormatter& keyFormatter) {
const bool debug = ISDEBUG("ISAM2 AddVariables"); const bool debug = ISDEBUG("ISAM2 AddVariables");
@ -40,28 +40,21 @@ void ISAM2::Impl::AddVariables(
std::vector<Index> dims(newTheta.dims(*newTheta.orderingArbitrary())); std::vector<Index> dims(newTheta.dims(*newTheta.orderingArbitrary()));
if(debug) cout << "New variables have total dimensionality " << accumulate(dims.begin(), dims.end(), 0) << endl; if(debug) cout << "New variables have total dimensionality " << accumulate(dims.begin(), dims.end(), 0) << endl;
const size_t newDim = accumulate(dims.begin(), dims.end(), 0); const size_t newDim = accumulate(dims.begin(), dims.end(), 0);
const size_t originalDim = delta->dim(); const size_t originalDim = delta.dim();
const size_t originalnVars = delta->size(); const size_t originalnVars = delta.size();
delta.container().append(dims); delta.append(dims);
delta.container().vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim)); delta.vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim));
delta.permutation().resize(originalnVars + newTheta.size()); deltaNewton.append(dims);
deltaNewton.container().append(dims); deltaNewton.vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim));
deltaNewton.container().vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim)); deltaGradSearch.append(dims);
deltaNewton.permutation().resize(originalnVars + newTheta.size()); deltaGradSearch.vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim));
deltaGradSearch.container().append(dims);
deltaGradSearch.container().vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim));
deltaGradSearch.permutation().resize(originalnVars + newTheta.size());
{ {
Index nextVar = originalnVars; Index nextVar = originalnVars;
BOOST_FOREACH(const Values::ConstKeyValuePair& key_value, newTheta) { BOOST_FOREACH(const Values::ConstKeyValuePair& key_value, newTheta) {
delta.permutation()[nextVar] = nextVar;
deltaNewton.permutation()[nextVar] = nextVar;
deltaGradSearch.permutation()[nextVar] = nextVar;
ordering.insert(key_value.key, nextVar); ordering.insert(key_value.key, nextVar);
if(debug) cout << "Adding variable " << keyFormatter(key_value.key) << " with order " << nextVar << endl; if(debug) cout << "Adding variable " << keyFormatter(key_value.key) << " with order " << nextVar << endl;
++ nextVar; ++ nextVar;
} }
assert(delta.permutation().size() == delta.container().size());
assert(ordering.nVars() == delta.size()); assert(ordering.nVars() == delta.size());
assert(ordering.size() == delta.size()); assert(ordering.size() == delta.size());
} }
@ -82,7 +75,7 @@ FastSet<Index> ISAM2::Impl::IndicesFromFactors(const Ordering& ordering, const N
} }
/* ************************************************************************* */ /* ************************************************************************* */
FastSet<Index> ISAM2::Impl::CheckRelinearizationFull(const Permuted<VectorValues>& delta, const Ordering& ordering, FastSet<Index> ISAM2::Impl::CheckRelinearizationFull(const VectorValues& delta, const Ordering& ordering,
const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter) { const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter) {
FastSet<Index> relinKeys; FastSet<Index> relinKeys;
@ -110,7 +103,7 @@ FastSet<Index> ISAM2::Impl::CheckRelinearizationFull(const Permuted<VectorValues
} }
/* ************************************************************************* */ /* ************************************************************************* */
void CheckRelinearizationRecursiveDouble(FastSet<Index>& relinKeys, double threshold, const Permuted<VectorValues>& delta, const ISAM2Clique::shared_ptr& clique) { void CheckRelinearizationRecursiveDouble(FastSet<Index>& relinKeys, double threshold, const VectorValues& delta, const ISAM2Clique::shared_ptr& clique) {
// Check the current clique for relinearization // Check the current clique for relinearization
bool relinearize = false; bool relinearize = false;
@ -131,7 +124,7 @@ void CheckRelinearizationRecursiveDouble(FastSet<Index>& relinKeys, double thres
} }
/* ************************************************************************* */ /* ************************************************************************* */
void CheckRelinearizationRecursiveMap(FastSet<Index>& relinKeys, const FastMap<char,Vector>& thresholds, const Permuted<VectorValues>& delta, const Ordering::InvertedMap& decoder, const ISAM2Clique::shared_ptr& clique) { void CheckRelinearizationRecursiveMap(FastSet<Index>& relinKeys, const FastMap<char,Vector>& thresholds, const VectorValues& delta, const Ordering::InvertedMap& decoder, const ISAM2Clique::shared_ptr& clique) {
// Check the current clique for relinearization // Check the current clique for relinearization
bool relinearize = false; bool relinearize = false;
@ -163,7 +156,7 @@ void CheckRelinearizationRecursiveMap(FastSet<Index>& relinKeys, const FastMap<c
} }
/* ************************************************************************* */ /* ************************************************************************* */
FastSet<Index> ISAM2::Impl::CheckRelinearizationPartial(const ISAM2Clique::shared_ptr& root, const Permuted<VectorValues>& delta, const Ordering& ordering, FastSet<Index> ISAM2::Impl::CheckRelinearizationPartial(const ISAM2Clique::shared_ptr& root, const VectorValues& delta, const Ordering& ordering,
const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter) { const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter) {
FastSet<Index> relinKeys; FastSet<Index> relinKeys;
@ -201,8 +194,8 @@ void ISAM2::Impl::FindAll(ISAM2Clique::shared_ptr clique, FastSet<Index>& keys,
} }
/* ************************************************************************* */ /* ************************************************************************* */
void ISAM2::Impl::ExpmapMasked(Values& values, const Permuted<VectorValues>& delta, const Ordering& ordering, void ISAM2::Impl::ExpmapMasked(Values& values, const VectorValues& delta, const Ordering& ordering,
const vector<bool>& mask, boost::optional<Permuted<VectorValues>&> invalidateIfDebug, const KeyFormatter& keyFormatter) { const vector<bool>& mask, boost::optional<VectorValues&> invalidateIfDebug, const KeyFormatter& keyFormatter) {
// If debugging, invalidate if requested, otherwise do not invalidate. // If debugging, invalidate if requested, otherwise do not invalidate.
// Invalidating means setting expmapped entries to Inf, to trigger assertions // Invalidating means setting expmapped entries to Inf, to trigger assertions
// if we try to re-use them. // if we try to re-use them.
@ -304,7 +297,7 @@ ISAM2::Impl::PartialSolve(GaussianFactorGraph& factors,
toc(4,"ccolamd permutations"); toc(4,"ccolamd permutations");
tic(5,"permute affected variable index"); tic(5,"permute affected variable index");
affectedFactorsIndex.permute(*affectedColamd); affectedFactorsIndex.permuteInPlace(*affectedColamd);
toc(5,"permute affected variable index"); toc(5,"permute affected variable index");
tic(6,"permute affected factors"); tic(6,"permute affected factors");
@ -354,25 +347,13 @@ inline static void optimizeInPlace(const boost::shared_ptr<ISAM2Clique>& clique,
} }
/* ************************************************************************* */ /* ************************************************************************* */
size_t ISAM2::Impl::UpdateDelta(const boost::shared_ptr<ISAM2Clique>& root, std::vector<bool>& replacedKeys, Permuted<VectorValues>& delta, double wildfireThreshold) { size_t ISAM2::Impl::UpdateDelta(const boost::shared_ptr<ISAM2Clique>& root, std::vector<bool>& replacedKeys, VectorValues& delta, double wildfireThreshold) {
size_t lastBacksubVariableCount; size_t lastBacksubVariableCount;
if (wildfireThreshold <= 0.0) { if (wildfireThreshold <= 0.0) {
// Threshold is zero or less, so do a full recalculation // Threshold is zero or less, so do a full recalculation
// Collect dimensions and allocate new VectorValues internal::optimizeInPlace(root, delta);
vector<size_t> dims(delta.size());
for(size_t j=0; j<delta.size(); ++j)
dims[j] = delta->dim(j);
VectorValues newDelta(dims);
// Optimize full solution delta
internal::optimizeInPlace(root, newDelta);
// Copy solution into delta
delta.permutation() = Permutation::Identity(delta.size());
delta.container() = newDelta;
lastBacksubVariableCount = delta.size(); lastBacksubVariableCount = delta.size();
} else { } else {
@ -380,8 +361,8 @@ size_t ISAM2::Impl::UpdateDelta(const boost::shared_ptr<ISAM2Clique>& root, std:
lastBacksubVariableCount = optimizeWildfire(root, wildfireThreshold, replacedKeys, delta); // modifies delta_ lastBacksubVariableCount = optimizeWildfire(root, wildfireThreshold, replacedKeys, delta); // modifies delta_
#ifndef NDEBUG #ifndef NDEBUG
for(size_t j=0; j<delta.container().size(); ++j) for(size_t j=0; j<delta.size(); ++j)
assert(delta.container()[j].unaryExpr(ptr_fun(isfinite<double>)).all()); assert(delta[j].unaryExpr(ptr_fun(isfinite<double>)).all());
#endif #endif
} }
@ -394,7 +375,7 @@ size_t ISAM2::Impl::UpdateDelta(const boost::shared_ptr<ISAM2Clique>& root, std:
/* ************************************************************************* */ /* ************************************************************************* */
namespace internal { namespace internal {
void updateDoglegDeltas(const boost::shared_ptr<ISAM2Clique>& clique, std::vector<bool>& replacedKeys, void updateDoglegDeltas(const boost::shared_ptr<ISAM2Clique>& clique, std::vector<bool>& replacedKeys,
const VectorValues& grad, Permuted<VectorValues>& deltaNewton, Permuted<VectorValues>& RgProd, size_t& varsUpdated) { const VectorValues& grad, VectorValues& deltaNewton, VectorValues& RgProd, size_t& varsUpdated) {
// Check if any frontal or separator keys were recalculated, if so, we need // Check if any frontal or separator keys were recalculated, if so, we need
// update deltas and recurse to children, but if not, we do not need to // update deltas and recurse to children, but if not, we do not need to
@ -433,7 +414,7 @@ void updateDoglegDeltas(const boost::shared_ptr<ISAM2Clique>& clique, std::vecto
/* ************************************************************************* */ /* ************************************************************************* */
size_t ISAM2::Impl::UpdateDoglegDeltas(const ISAM2& isam, double wildfireThreshold, std::vector<bool>& replacedKeys, size_t ISAM2::Impl::UpdateDoglegDeltas(const ISAM2& isam, double wildfireThreshold, std::vector<bool>& replacedKeys,
Permuted<VectorValues>& deltaNewton, Permuted<VectorValues>& RgProd) { VectorValues& deltaNewton, VectorValues& RgProd) {
// Get gradient // Get gradient
VectorValues grad = *allocateVectorValues(isam); VectorValues grad = *allocateVectorValues(isam);

16
gtsam/nonlinear/ISAM2-impl.h
View File

@ -46,8 +46,8 @@ struct ISAM2::Impl {
* @param nodes Current BayesTree::Nodes index to be augmented with slots for new variables * @param nodes Current BayesTree::Nodes index to be augmented with slots for new variables
* @param keyFormatter Formatter for printing nonlinear keys during debugging * @param keyFormatter Formatter for printing nonlinear keys during debugging
*/ */
static void AddVariables(const Values& newTheta, Values& theta, Permuted<VectorValues>& delta, static void AddVariables(const Values& newTheta, Values& theta, VectorValues& delta,
Permuted<VectorValues>& deltaNewton, Permuted<VectorValues>& deltaGradSearch, std::vector<bool>& replacedKeys, VectorValues& deltaNewton, VectorValues& deltaGradSearch, std::vector<bool>& replacedKeys,
Ordering& ordering, Base::Nodes& nodes, const KeyFormatter& keyFormatter = DefaultKeyFormatter); Ordering& ordering, Base::Nodes& nodes, const KeyFormatter& keyFormatter = DefaultKeyFormatter);
/** /**
@ -68,7 +68,7 @@ struct ISAM2::Impl {
* @return The set of variable indices in delta whose magnitude is greater than or * @return The set of variable indices in delta whose magnitude is greater than or
* equal to relinearizeThreshold * equal to relinearizeThreshold
*/ */
static FastSet<Index> CheckRelinearizationFull(const Permuted<VectorValues>& delta, const Ordering& ordering, static FastSet<Index> CheckRelinearizationFull(const VectorValues& delta, const Ordering& ordering,
const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter = DefaultKeyFormatter); const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter = DefaultKeyFormatter);
/** /**
@ -82,7 +82,7 @@ struct ISAM2::Impl {
* @return The set of variable indices in delta whose magnitude is greater than or * @return The set of variable indices in delta whose magnitude is greater than or
* equal to relinearizeThreshold * equal to relinearizeThreshold
*/ */
static FastSet<Index> CheckRelinearizationPartial(const ISAM2Clique::shared_ptr& root, const Permuted<VectorValues>& delta, const Ordering& ordering, static FastSet<Index> CheckRelinearizationPartial(const ISAM2Clique::shared_ptr& root, const VectorValues& delta, const Ordering& ordering,
const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter = DefaultKeyFormatter); const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter = DefaultKeyFormatter);
/** /**
@ -115,9 +115,9 @@ struct ISAM2::Impl {
* recalculate its delta. * recalculate its delta.
* @param keyFormatter Formatter for printing nonlinear keys during debugging * @param keyFormatter Formatter for printing nonlinear keys during debugging
*/ */
static void ExpmapMasked(Values& values, const Permuted<VectorValues>& delta, static void ExpmapMasked(Values& values, const VectorValues& delta,
const Ordering& ordering, const std::vector<bool>& mask, const Ordering& ordering, const std::vector<bool>& mask,
boost::optional<Permuted<VectorValues>&> invalidateIfDebug = boost::optional<Permuted<VectorValues>&>(), boost::optional<VectorValues&> invalidateIfDebug = boost::none,
const KeyFormatter& keyFormatter = DefaultKeyFormatter); const KeyFormatter& keyFormatter = DefaultKeyFormatter);
/** /**
@ -137,10 +137,10 @@ struct ISAM2::Impl {
static PartialSolveResult PartialSolve(GaussianFactorGraph& factors, const FastSet<Index>& keys, static PartialSolveResult PartialSolve(GaussianFactorGraph& factors, const FastSet<Index>& keys,
const ReorderingMode& reorderingMode, bool useQR); const ReorderingMode& reorderingMode, bool useQR);
static size_t UpdateDelta(const boost::shared_ptr<ISAM2Clique>& root, std::vector<bool>& replacedKeys, Permuted<VectorValues>& delta, double wildfireThreshold); static size_t UpdateDelta(const boost::shared_ptr<ISAM2Clique>& root, std::vector<bool>& replacedKeys, VectorValues& delta, double wildfireThreshold);
static size_t UpdateDoglegDeltas(const ISAM2& isam, double wildfireThreshold, std::vector<bool>& replacedKeys, static size_t UpdateDoglegDeltas(const ISAM2& isam, double wildfireThreshold, std::vector<bool>& replacedKeys,
Permuted<VectorValues>& deltaNewton, Permuted<VectorValues>& RgProd); VectorValues& deltaNewton, VectorValues& RgProd);
}; };

4
gtsam/nonlinear/ISAM2-inl.h
View File

@ -37,7 +37,7 @@ VALUE ISAM2::calculateEstimate(Key key) const {
namespace internal { namespace internal {
template<class CLIQUE> template<class CLIQUE>
void optimizeWildfire(const boost::shared_ptr<CLIQUE>& clique, double threshold, void optimizeWildfire(const boost::shared_ptr<CLIQUE>& clique, double threshold,
std::vector<bool>& changed, const std::vector<bool>& replaced, Permuted<VectorValues>& delta, int& count) { std::vector<bool>& changed, const std::vector<bool>& replaced, VectorValues& delta, int& count) {
// if none of the variables in this clique (frontal and separator!) changed // if none of the variables in this clique (frontal and separator!) changed
// significantly, then by the running intersection property, none of the // significantly, then by the running intersection property, none of the
// cliques in the children need to be processed // cliques in the children need to be processed
@ -114,7 +114,7 @@ void optimizeWildfire(const boost::shared_ptr<CLIQUE>& clique, double threshold,
/* ************************************************************************* */ /* ************************************************************************* */
template<class CLIQUE> template<class CLIQUE>
int optimizeWildfire(const boost::shared_ptr<CLIQUE>& root, double threshold, const std::vector<bool>& keys, Permuted<VectorValues>& delta) { int optimizeWildfire(const boost::shared_ptr<CLIQUE>& root, double threshold, const std::vector<bool>& keys, VectorValues& delta) {
std::vector<bool> changed(keys.size(), false); std::vector<bool> changed(keys.size(), false);
int count = 0; int count = 0;
// starting from the root, call optimize on each conditional // starting from the root, call optimize on each conditional

30
gtsam/nonlinear/ISAM2.cpp
View File

@ -41,7 +41,6 @@ static const double batchThreshold = 0.65;
/* ************************************************************************* */ /* ************************************************************************* */
ISAM2::ISAM2(const ISAM2Params& params): ISAM2::ISAM2(const ISAM2Params& params):
delta_(deltaUnpermuted_), deltaNewton_(deltaNewtonUnpermuted_), RgProd_(RgProdUnpermuted_),
deltaDoglegUptodate_(true), deltaUptodate_(true), params_(params) { deltaDoglegUptodate_(true), deltaUptodate_(true), params_(params) {
if(params_.optimizationParams.type() == typeid(ISAM2DoglegParams)) if(params_.optimizationParams.type() == typeid(ISAM2DoglegParams))
doglegDelta_ = boost::get<ISAM2DoglegParams>(params_.optimizationParams).initialDelta; doglegDelta_ = boost::get<ISAM2DoglegParams>(params_.optimizationParams).initialDelta;
@ -49,15 +48,13 @@ ISAM2::ISAM2(const ISAM2Params& params):
/* ************************************************************************* */ /* ************************************************************************* */
ISAM2::ISAM2(): ISAM2::ISAM2():
delta_(deltaUnpermuted_), deltaNewton_(deltaNewtonUnpermuted_), RgProd_(RgProdUnpermuted_),
deltaDoglegUptodate_(true), deltaUptodate_(true) { deltaDoglegUptodate_(true), deltaUptodate_(true) {
if(params_.optimizationParams.type() == typeid(ISAM2DoglegParams)) if(params_.optimizationParams.type() == typeid(ISAM2DoglegParams))
doglegDelta_ = boost::get<ISAM2DoglegParams>(params_.optimizationParams).initialDelta; doglegDelta_ = boost::get<ISAM2DoglegParams>(params_.optimizationParams).initialDelta;
} }
/* ************************************************************************* */ /* ************************************************************************* */
ISAM2::ISAM2(const ISAM2& other): ISAM2::ISAM2(const ISAM2& other) {
delta_(deltaUnpermuted_), deltaNewton_(deltaNewtonUnpermuted_), RgProd_(RgProdUnpermuted_) {
*this = other; *this = other;
} }
@ -308,12 +305,12 @@ boost::shared_ptr<FastSet<Index> > ISAM2::recalculate(
// Reorder // Reorder
tic(2,"permute global variable index"); tic(2,"permute global variable index");
variableIndex_.permute(*colamd); variableIndex_.permuteInPlace(*colamd);
toc(2,"permute global variable index"); toc(2,"permute global variable index");
tic(3,"permute delta"); tic(3,"permute delta");
delta_.permute(*colamd); delta_ = delta_.permute(*colamd);
deltaNewton_.permute(*colamd); deltaNewton_ = deltaNewton_.permute(*colamd);
RgProd_.permute(*colamd); RgProd_ = RgProd_.permute(*colamd);
toc(3,"permute delta"); toc(3,"permute delta");
tic(4,"permute ordering"); tic(4,"permute ordering");
ordering_.permuteWithInverse(*colamdInverse); ordering_.permuteWithInverse(*colamdInverse);
@ -429,12 +426,12 @@ boost::shared_ptr<FastSet<Index> > ISAM2::recalculate(
// re-eliminate. The reordered variables are also mentioned in the // re-eliminate. The reordered variables are also mentioned in the
// orphans and the leftover cached factors. // orphans and the leftover cached factors.
tic(3,"permute global variable index"); tic(3,"permute global variable index");
variableIndex_.permute(partialSolveResult.fullReordering); variableIndex_.permuteInPlace(partialSolveResult.fullReordering);
toc(3,"permute global variable index"); toc(3,"permute global variable index");
tic(4,"permute delta"); tic(4,"permute delta");
delta_.permute(partialSolveResult.fullReordering); delta_ = delta_.permute(partialSolveResult.fullReordering);
deltaNewton_.permute(partialSolveResult.fullReordering); deltaNewton_ = deltaNewton_.permute(partialSolveResult.fullReordering);
RgProd_.permute(partialSolveResult.fullReordering); RgProd_ = RgProd_.permute(partialSolveResult.fullReordering);
toc(4,"permute delta"); toc(4,"permute delta");
tic(5,"permute ordering"); tic(5,"permute ordering");
ordering_.permuteWithInverse(partialSolveResult.fullReorderingInverse); ordering_.permuteWithInverse(partialSolveResult.fullReorderingInverse);
@ -723,8 +720,7 @@ void ISAM2::updateDelta(bool forceFullSolve) const {
tic(2, "Copy dx_d"); tic(2, "Copy dx_d");
// Update Delta and linear step // Update Delta and linear step
doglegDelta_ = doglegResult.Delta; doglegDelta_ = doglegResult.Delta;
delta_.permutation() = Permutation::Identity(delta_.size()); // Dogleg solves for the full delta so there is no permutation delta_ = doglegResult.dx_d; // Copy the VectorValues containing with the linear solution
delta_.container() = doglegResult.dx_d; // Copy the VectorValues containing with the linear solution
toc(2, "Copy dx_d"); toc(2, "Copy dx_d");
} }
@ -739,7 +735,7 @@ Values ISAM2::calculateEstimate() const {
Values ret(theta_); Values ret(theta_);
toc(1, "Copy Values"); toc(1, "Copy Values");
tic(2, "getDelta"); tic(2, "getDelta");
const Permuted<VectorValues>& delta(getDelta()); const VectorValues& delta(getDelta());
toc(2, "getDelta"); toc(2, "getDelta");
tic(3, "Expmap"); tic(3, "Expmap");
vector<bool> mask(ordering_.nVars(), true); vector<bool> mask(ordering_.nVars(), true);
@ -756,7 +752,7 @@ Values ISAM2::calculateBestEstimate() const {
} }
/* ************************************************************************* */ /* ************************************************************************* */
const Permuted<VectorValues>& ISAM2::getDelta() const { const VectorValues& ISAM2::getDelta() const {
if(!deltaUptodate_) if(!deltaUptodate_)
updateDelta(); updateDelta();
return delta_; return delta_;
@ -829,7 +825,7 @@ void optimizeGradientSearchInPlace(const ISAM2& isam, VectorValues& grad) {
tic(3, "Compute minimizing step size"); tic(3, "Compute minimizing step size");
// Compute minimizing step size // Compute minimizing step size
double RgNormSq = isam.RgProd_.container().vector().squaredNorm(); double RgNormSq = isam.RgProd_.vector().squaredNorm();
double step = -gradientSqNorm / RgNormSq; double step = -gradientSqNorm / RgNormSq;
toc(3, "Compute minimizing step size"); toc(3, "Compute minimizing step size");

32
gtsam/nonlinear/ISAM2.h
View File

@ -347,26 +347,16 @@ protected:
/** VariableIndex lets us look up factors by involved variable and keeps track of dimensions */ /** VariableIndex lets us look up factors by involved variable and keeps track of dimensions */
VariableIndex variableIndex_; VariableIndex variableIndex_;
/** The linear delta from the last linear solution, an update to the estimate in theta */ /** The linear delta from the last linear solution, an update to the estimate in theta
VectorValues deltaUnpermuted_; *
* This is \c mutable because it is a "cached" variable - it is not updated
* until either requested with getDelta() or calculateEstimate(), or needed
* during update() to evaluate whether to relinearize variables.
*/
mutable VectorValues delta_;
/** The permutation through which the deltaUnpermuted_ is mutable VectorValues deltaNewton_;
* referenced. mutable VectorValues RgProd_;
*
* Permuting Vector entries would be slow, so for performance we
* instead maintain this permutation through which we access the linear delta
* indirectly
*
* This is \c mutable because it is a "cached" variable - it is not updated
* until either requested with getDelta() or calculateEstimate(), or needed
* during update() to evaluate whether to relinearize variables.
*/
mutable Permuted<VectorValues> delta_;
VectorValues deltaNewtonUnpermuted_;
mutable Permuted<VectorValues> deltaNewton_;
VectorValues RgProdUnpermuted_;
mutable Permuted<VectorValues> RgProd_;
mutable bool deltaDoglegUptodate_; mutable bool deltaDoglegUptodate_;
/** Indicates whether the current delta is up-to-date, only used /** Indicates whether the current delta is up-to-date, only used
@ -497,7 +487,7 @@ public:
Values calculateBestEstimate() const; Values calculateBestEstimate() const;
/** Access the current delta, computed during the last call to update */ /** Access the current delta, computed during the last call to update */
const Permuted<VectorValues>& getDelta() const; const VectorValues& getDelta() const;
/** Access the set of nonlinear factors */ /** Access the set of nonlinear factors */
const NonlinearFactorGraph& getFactorsUnsafe() const { return nonlinearFactors_; } const NonlinearFactorGraph& getFactorsUnsafe() const { return nonlinearFactors_; }
@ -555,7 +545,7 @@ void optimizeInPlace(const ISAM2& isam, VectorValues& delta);
/// @return The number of variables that were solved for /// @return The number of variables that were solved for
template<class CLIQUE> template<class CLIQUE>
int optimizeWildfire(const boost::shared_ptr<CLIQUE>& root, int optimizeWildfire(const boost::shared_ptr<CLIQUE>& root,
double threshold, const std::vector<bool>& replaced, Permuted<VectorValues>& delta); double threshold, const std::vector<bool>& replaced, VectorValues& delta);
/** /**
* Optimize along the gradient direction, with a closed-form computation to * Optimize along the gradient direction, with a closed-form computation to

111
tests/testGaussianISAM2.cpp
View File

@ -139,112 +139,69 @@ TEST_UNSAFE(ISAM2, AddVariables) {
// Create initial state // Create initial state
Values theta; Values theta;
theta.insert((0), Pose2(.1, .2, .3)); theta.insert(0, Pose2(.1, .2, .3));
theta.insert(100, Point2(.4, .5)); theta.insert(100, Point2(.4, .5));
Values newTheta; Values newTheta;
newTheta.insert((1), Pose2(.6, .7, .8)); newTheta.insert(1, Pose2(.6, .7, .8));
VectorValues deltaUnpermuted; VectorValues delta;
deltaUnpermuted.insert(0, Vector_(3, .1, .2, .3)); delta.insert(0, Vector_(3, .1, .2, .3));
deltaUnpermuted.insert(1, Vector_(2, .4, .5)); delta.insert(1, Vector_(2, .4, .5));
Permutation permutation(2); VectorValues deltaNewton;
permutation[0] = 1; deltaNewton.insert(0, Vector_(3, .1, .2, .3));
permutation[1] = 0; deltaNewton.insert(1, Vector_(2, .4, .5));
Permuted<VectorValues> delta(permutation, deltaUnpermuted); VectorValues deltaRg;
deltaRg.insert(0, Vector_(3, .1, .2, .3));
VectorValues deltaNewtonUnpermuted; deltaRg.insert(1, Vector_(2, .4, .5));
deltaNewtonUnpermuted.insert(0, Vector_(3, .1, .2, .3));
deltaNewtonUnpermuted.insert(1, Vector_(2, .4, .5));
Permutation permutationNewton(2);
permutationNewton[0] = 1;
permutationNewton[1] = 0;
Permuted<VectorValues> deltaNewton(permutationNewton, deltaNewtonUnpermuted);
VectorValues deltaRgUnpermuted;
deltaRgUnpermuted.insert(0, Vector_(3, .1, .2, .3));
deltaRgUnpermuted.insert(1, Vector_(2, .4, .5));
Permutation permutationRg(2);
permutationRg[0] = 1;
permutationRg[1] = 0;
Permuted<VectorValues> deltaRg(permutationRg, deltaRgUnpermuted);
vector<bool> replacedKeys(2, false); vector<bool> replacedKeys(2, false);
Ordering ordering; ordering += 100, (0); Ordering ordering; ordering += 100, 0;
ISAM2::Nodes nodes(2); ISAM2::Nodes nodes(2);
// Verify initial state // Verify initial state
LONGS_EQUAL(0, ordering[100]); LONGS_EQUAL(0, ordering[100]);
LONGS_EQUAL(1, ordering[(0)]); LONGS_EQUAL(1, ordering[0]);
EXPECT(assert_equal(deltaUnpermuted[1], delta[ordering[100]])); EXPECT(assert_equal(delta[0], delta[ordering[100]]));
EXPECT(assert_equal(deltaUnpermuted[0], delta[ordering[(0)]])); EXPECT(assert_equal(delta[1], delta[ordering[0]]));
// Create expected state // Create expected state
Values thetaExpected; Values thetaExpected;
thetaExpected.insert((0), Pose2(.1, .2, .3)); thetaExpected.insert(0, Pose2(.1, .2, .3));
thetaExpected.insert(100, Point2(.4, .5)); thetaExpected.insert(100, Point2(.4, .5));
thetaExpected.insert((1), Pose2(.6, .7, .8)); thetaExpected.insert(1, Pose2(.6, .7, .8));
VectorValues deltaUnpermutedExpected; VectorValues deltaExpected;
deltaUnpermutedExpected.insert(0, Vector_(3, .1, .2, .3)); deltaExpected.insert(0, Vector_(3, .1, .2, .3));
deltaUnpermutedExpected.insert(1, Vector_(2, .4, .5)); deltaExpected.insert(1, Vector_(2, .4, .5));
deltaUnpermutedExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0)); deltaExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0));
Permutation permutationExpected(3); VectorValues deltaNewtonExpected;
permutationExpected[0] = 1; deltaNewtonExpected.insert(0, Vector_(3, .1, .2, .3));
permutationExpected[1] = 0; deltaNewtonExpected.insert(1, Vector_(2, .4, .5));
permutationExpected[2] = 2; deltaNewtonExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0));
Permuted<VectorValues> deltaExpected(permutationExpected, deltaUnpermutedExpected); VectorValues deltaRgExpected;
deltaRgExpected.insert(0, Vector_(3, .1, .2, .3));
VectorValues deltaNewtonUnpermutedExpected; deltaRgExpected.insert(1, Vector_(2, .4, .5));
deltaNewtonUnpermutedExpected.insert(0, Vector_(3, .1, .2, .3)); deltaRgExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0));
deltaNewtonUnpermutedExpected.insert(1, Vector_(2, .4, .5));
deltaNewtonUnpermutedExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0));
Permutation permutationNewtonExpected(3);
permutationNewtonExpected[0] = 1;
permutationNewtonExpected[1] = 0;
permutationNewtonExpected[2] = 2;
Permuted<VectorValues> deltaNewtonExpected(permutationNewtonExpected, deltaNewtonUnpermutedExpected);
VectorValues deltaRgUnpermutedExpected;
deltaRgUnpermutedExpected.insert(0, Vector_(3, .1, .2, .3));
deltaRgUnpermutedExpected.insert(1, Vector_(2, .4, .5));
deltaRgUnpermutedExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0));
Permutation permutationRgExpected(3);
permutationRgExpected[0] = 1;
permutationRgExpected[1] = 0;
permutationRgExpected[2] = 2;
Permuted<VectorValues> deltaRgExpected(permutationRgExpected, deltaRgUnpermutedExpected);
vector<bool> replacedKeysExpected(3, false); vector<bool> replacedKeysExpected(3, false);
Ordering orderingExpected; orderingExpected += 100, (0), (1); Ordering orderingExpected; orderingExpected += 100, 0, 1;
ISAM2::Nodes nodesExpected( ISAM2::Nodes nodesExpected(3, ISAM2::sharedClique());
3, ISAM2::sharedClique());
// Expand initial state // Expand initial state
ISAM2::Impl::AddVariables(newTheta, theta, delta, deltaNewton, deltaRg, replacedKeys, ordering, nodes); ISAM2::Impl::AddVariables(newTheta, theta, delta, deltaNewton, deltaRg, replacedKeys, ordering, nodes);
EXPECT(assert_equal(thetaExpected, theta)); EXPECT(assert_equal(thetaExpected, theta));
EXPECT(assert_equal(deltaUnpermutedExpected, deltaUnpermuted)); EXPECT(assert_equal(deltaExpected, delta));
EXPECT(assert_equal(deltaExpected.permutation(), delta.permutation())); EXPECT(assert_equal(deltaNewtonExpected, deltaNewton));
EXPECT(assert_equal(deltaNewtonUnpermutedExpected, deltaNewtonUnpermuted)); EXPECT(assert_equal(deltaRgExpected, deltaRg));
EXPECT(assert_equal(deltaNewtonExpected.permutation(), deltaNewton.permutation()));
EXPECT(assert_equal(deltaRgUnpermutedExpected, deltaRgUnpermuted));
EXPECT(assert_equal(deltaRgExpected.permutation(), deltaRg.permutation()));
EXPECT(assert_container_equality(replacedKeysExpected, replacedKeys)); EXPECT(assert_container_equality(replacedKeysExpected, replacedKeys));
EXPECT(assert_equal(orderingExpected, ordering)); EXPECT(assert_equal(orderingExpected, ordering));
} }