class Pose2SLAMOptimizer { Pose2SLAMOptimizer(string dataset_name); void print(string s) const; 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(const Ordering& ordering) const; pair eliminate(string key) 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(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; };