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Wrapped additional functions in factors and factor graphs, added factor heirarchy, fixed mistake in noisemodel heirarchy

release/4.3a0
Richard Roberts 2012-07-11 18:18:57 +00:00
parent 774fcb5ca9
commit 646457bfb2
1 changed files with 25 additions and 18 deletions
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43
gtsam.h
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@ -720,14 +720,14 @@ virtual class Diagonal : gtsam::noiseModel::Gaussian {
void print(string s) const;
};
virtual class Isotropic : gtsam::noiseModel::Gaussian {
virtual class Isotropic : gtsam::noiseModel::Diagonal {
static gtsam::noiseModel::Isotropic* Sigma(size_t dim, double sigma);
static gtsam::noiseModel::Isotropic* Variance(size_t dim, double varianace);
static gtsam::noiseModel::Isotropic* Precision(size_t dim, double precision);
void print(string s) const;
};
virtual class Unit : gtsam::noiseModel::Gaussian {
virtual class Unit : gtsam::noiseModel::Isotropic {
static gtsam::noiseModel::Unit* Create(size_t dim);
void print(string s) const;
};
@ -782,7 +782,7 @@ class GaussianBayesNet {
void push_front(gtsam::GaussianConditional* conditional);
};
class GaussianFactor {
virtual class GaussianFactor {
void print(string s) const;
bool equals(const gtsam::GaussianFactor& lf, double tol) const;
double error(const gtsam::VectorValues& c) const;
@ -790,7 +790,7 @@ class GaussianFactor {
size_t size() const;
};
class JacobianFactor {
virtual class JacobianFactor : gtsam::GaussianFactor {
JacobianFactor();
JacobianFactor(Vector b_in);
JacobianFactor(size_t i1, Matrix A1, Vector b,
@ -810,7 +810,7 @@ class JacobianFactor {
gtsam::GaussianFactor* negate() const;
};
class HessianFactor {
virtual class HessianFactor : gtsam::GaussianFactor {
HessianFactor(const gtsam::HessianFactor& gf);
HessianFactor();
HessianFactor(size_t j, Matrix G, Vector g, double f);
@ -834,22 +834,19 @@ class GaussianFactorGraph {
GaussianFactorGraph(const gtsam::GaussianBayesNet& CBN);
// From FactorGraph
void push_back(gtsam::GaussianFactor* factor);
void print(string s) const;
bool equals(const gtsam::GaussianFactorGraph& lfgraph, double tol) const;
size_t size() const;
gtsam::GaussianFactor* at(size_t idx) const;
// Building the graph
void add(gtsam::JacobianFactor* factor);
// all these won't work as MATLAB can't handle overloading
// void add(Vector b);
// void add(size_t key1, Matrix A1, Vector b, const gtsam::SharedDiagonal& model);
// void add(size_t key1, Matrix A1, size_t key2, Matrix A2, Vector b,
// const gtsam::SharedDiagonal& model);
// void add(size_t key1, Matrix A1, size_t key2, Matrix A2, size_t key3, Matrix A3,
// Vector b, const gtsam::SharedDiagonal& model);
// void add(gtsam::HessianFactor* factor);
void push_back(gtsam::GaussianFactor* factor);
void add(Vector b);
void add(size_t key1, Matrix A1, Vector b, const gtsam::noiseModel::Diagonal* model);
void add(size_t key1, Matrix A1, size_t key2, Matrix A2, Vector b,
const gtsam::noiseModel::Diagonal* model);
void add(size_t key1, Matrix A1, size_t key2, Matrix A2, size_t key3, Matrix A3,
Vector b, const gtsam::noiseModel::Diagonal* model);
// error and probability
double error(const gtsam::VectorValues& c) const;
@ -951,15 +948,25 @@ class InvertedOrdering {
class NonlinearFactorGraph {
NonlinearFactorGraph();
void print(string s) const;
double error(const gtsam::Values& c) const;
double probPrime(const gtsam::Values& c) const;
gtsam::Ordering* orderingCOLAMD(const gtsam::Values& c) const;
// Ordering* orderingCOLAMDConstrained(const gtsam::Values& c, const std::map<gtsam::Key,int>& constraints) const;
gtsam::GaussianFactorGraph* linearize(const gtsam::Values& c, const gtsam::Ordering& ordering) const;
gtsam::NonlinearFactorGraph clone() const;
};
class NonlinearFactor {
// NonlinearFactor(); // FIXME: don't use this - creates an abstract class
virtual class NonlinearFactor {
void print(string s) const;
void equals(const gtsam::NonlinearFactor& other, double tol) const;
gtsam::KeyVector keys() const;
size_t size() const;
size_t dim() const; // FIXME: Doesn't link
size_t dim() const;
double error(const gtsam::Values& c) const;
bool active(const gtsam::Values& c) const;
gtsam::GaussianFactor* linearize(const gtsam::Values& c, const gtsam::Ordering& ordering) const;
gtsam::NonlinearFactor* clone() const;
// gtsam::NonlinearFactor* rekey(const gtsam::KeyVector& newKeys) const; //FIXME: Conversion from KeyVector to std::vector does not happen
};
class Values {