File hamiltonian_monte_carlo_walk.hpp

struct HamiltonianMonteCarloWalk

template<typename NT, typename OracleFunctor> struct parameters

Public Functions

inline parameters(OracleFunctor const &F, unsigned int dim, NT epsilon_ = 2)

Public Members

NT epsilon

NT eta

template<typename Point, typename Polytope, typename RandomNumberGenerator, typename NegativeGradientFunctor, typename NegativeLogprobFunctor, typename Solver> struct Walk

Public Types

typedef std::vector<Point> pts

typedef Point::FT NT

typedef std::vector<Polytope*> bounds

Public Functions

inline Walk(Polytope *P, Point &p, NegativeGradientFunctor &neg_grad_f, NegativeLogprobFunctor &neg_logprob_f, parameters<NT, NegativeGradientFunctor> &param)

inline void apply(RandomNumberGenerator &rng, int walk_length = 1, bool metropolis_filter = true)

inline NT hamiltonian(Point &pos, Point &vel) const

inline void disable_adaptive()

inline void enable_adaptive()

Public Members

parameters<NT, NegativeGradientFunctor> &params

Solver *solver

unsigned int dim

long total_discarded_samples = 0

long num_runs = 0

float discard_ratio = 0

float total_acceptance_log_prob = 0

float average_acceptance_log_prob = 0

Point x

Point v

Point x_tilde

Point v_tilde

NegativeGradientFunctor &F

bool accepted

NT H

NT H_tilde

NT log_prob

NT u_logprob

NegativeLogprobFunctor &f