gtsam/cpp/gtsam.h

172 lines
4.2 KiB
C++

class Pose2SLAMOptimizer {
Pose2SLAMOptimizer(string dataset_name);
void update(Vector x) const;
Vector optimize() const;
double error() const;
Matrix a1() const;
Matrix a2() const;
Vector b1() const;
Vector b2() const;
};
class SharedGaussian {
SharedGaussian(Matrix covariance);
SharedGaussian(Vector sigmas);
};
class SharedDiagonal {
SharedDiagonal(Vector sigmas);
};
class Ordering {
Ordering();
Ordering(string key);
Ordering subtract(const Ordering& keys) const;
void push_back(string s);
void print(string s) const;
bool equals(const Ordering& ord, double tol) const;
void unique ();
void reverse ();
};
class SymbolicFactor{
SymbolicFactor(const Ordering& keys);
void print(string s) const;
};
class VectorConfig {
VectorConfig();
Vector get(string name) const;
bool contains(string name) const;
size_t size() const;
void insert(string name, Vector val);
void print(string s) const;
bool equals(const VectorConfig& expected, double tol) const;
void clear();
};
class GaussianFactor {
GaussianFactor(string key1,
Matrix A1,
Vector b_in,
const SharedDiagonal& model);
GaussianFactor(string key1,
Matrix A1,
string key2,
Matrix A2,
Vector b_in,
const SharedDiagonal& model);
GaussianFactor(string key1,
Matrix A1,
string key2,
Matrix A2,
string key3,
Matrix A3,
Vector b_in,
const SharedDiagonal& model);
bool empty() const;
Vector get_b() const;
Matrix get_A(string key) const;
double error(const VectorConfig& c) const;
bool involves(string key) const;
void print(string s) const;
bool equals(const GaussianFactor& lf, double tol) const;
pair<Matrix,Vector> matrix(const Ordering& ordering) const;
};
class GaussianFactorSet {
GaussianFactorSet();
void push_back(GaussianFactor* factor);
};
class GaussianConditional {
GaussianConditional();
GaussianConditional(string key,
Vector d,
Matrix R,
Vector sigmas);
GaussianConditional(string key,
Vector d,
Matrix R,
string name1,
Matrix S,
Vector sigmas);
GaussianConditional(string key,
Vector d,
Matrix R,
string name1,
Matrix S,
string name2,
Matrix T,
Vector sigmas);
void print(string s) const;
Vector solve(const VectorConfig& x);
void add(string key, Matrix S);
bool equals(const GaussianConditional &cg, double tol) const;
};
class GaussianBayesNet {
GaussianBayesNet();
void print(string s) const;
bool equals(const GaussianBayesNet& cbn, double tol) const;
void push_back(GaussianConditional* conditional);
void push_front(GaussianConditional* conditional);
};
class GaussianFactorGraph {
GaussianFactorGraph();
size_t size() const;
void push_back(GaussianFactor* ptr_f);
double error(const VectorConfig& c) const;
double probPrime(const VectorConfig& c) const;
void print(string s) const;
bool equals(const GaussianFactorGraph& lfgraph, double tol) const;
void combine(const GaussianFactorGraph& lfg);
GaussianConditional* eliminateOne(string key);
GaussianBayesNet* eliminate_(const Ordering& ordering);
VectorConfig* optimize_(const Ordering& ordering);
pair<Matrix,Vector> matrix(const Ordering& ordering) const;
Matrix sparse(const Ordering& ordering) const;
VectorConfig* steepestDescent_(const VectorConfig& x0) const;
VectorConfig* conjugateGradientDescent_(const VectorConfig& x0) const;
};
class Point2 {
Point2();
Point2(double x, double y);
double x();
double y();
void print(string s) const;
};
class Point3 {
Point3();
Point3(double x, double y, double z);
Point3(Vector v);
Vector vector() const;
double x();
double y();
double z();
void print(string s) const;
};
class Pose2 {
Pose2();
Pose2(const Pose2& pose);
Pose2(double x, double y, double theta);
Pose2(double theta, const Point2& t);
Pose2(const Rot2& r, const Point2& t);
void print(string s) const;
bool equals(const Pose2& pose, double tol) const;
double x() const;
double y() const;
double theta() const;
size_t dim() const;
Pose2 expmap(const Vector& v) const;
Vector logmap(const Pose2& pose) const;
Point2 t() const;
Rot2 r() const;
};