File nuts_hmc_walk.hpp

struct NutsHamiltonianMonteCarloWalk

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, bool burn_in_phase = true)

inline void burnin(RandomNumberGenerator &rng, unsigned int N = 1000, unsigned int walk_length = 1)

inline void apply(RandomNumberGenerator &rng, unsigned int walk_length = 1, bool burnin = false)

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

inline NT get_eta_solver()

inline void disable_adaptive()

inline void enable_adaptive()

inline void reset_num_runs()

inline NT get_ratio_acceptance()

Public Members

parameters<NT, NegativeGradientFunctor> &params

Solver *solver

unsigned int dim

long num_runs = 0

long total_acceptance = 0

NT average_acceptance = 0

Point x

Point v

Point v_pl

Point v_min

Point v_min_j

Point v_pl_j

Point X_pl

Point X_pl_j

Point X_min

Point X

Point X_rnd_j

Point X_min_j

Point x_pl_min

NegativeGradientFunctor &F

bool accepted

NT eps_step

NT mu

NT log_tilde_eps

NT H_tilde

NT alpha

NT na

const NT delta = NT(0.65)

const NT Delta_max = NT(1000)

const NT gamma = NT(0.05)

const NT t0 = NT(10)

const NT kk = NT(0.85)

NegativeLogprobFunctor &f