Parallel tempered Markov Chain Monte Carlo using DEO swapping scheme. More...

#include "sampling/sampler_deo_tempering_MCMC.h"

Inheritance diagram for sampler_deo_tempering_MCMC< S >:

Collaboration diagram for sampler_deo_tempering_MCMC< S >:

Public Member Functions
	sampler_deo_tempering_MCMC (int seed, likelihood_power_tempered &L, std::vector< std::string > var_names, size_t dimension)
	Class constructor, takes a reference to the exploration kernel to be used.

void	set_initial_location (std::vector< double > initial_parameters)

void	run_sampler (int number_of_rounds, int thin, int refresh, int verbosity=0)
	Runs DEO using where you specify the starting run length and adaption parameters. After each round each number if increased by the geometric increase factor specified in set_annealing_schedule. More...

S *	get_sampler ()
	Provides access to the exploration sampler so that you can change options for it. Returns a pointer to the sampler.

int	get_round () const
	Returns the current round of the sampler.

void	set_output_stream (std::string chain_file, std::string state_file, std::string sampler_file, int output_precision=8)
	Sets the output streams for the sampler. This is the same function as for sampler_MCMC_base. More...

void	set_deo_round_params (int initial_length, int swap_stride)
	Sets the annealing schedule to be used. More...

void	set_annealing_schedule (double initial_spacing, int geometric_increase=2)

void	set_annealing_output (std::string annealing_file, std::string annealing_summary_file="")
	Sets the annealing file and summary file names. If using the default for the annealing_summary_file the output will be the annealing_file+".summary".

void	set_cpu_distribution (int num_temperatures, int num_exploration)
	Sets the distribution for the cpu. More...

void	read_initial_ladder (std::string annealing_file)
	Reads in an annealing.dat file and set the initial ladder for the sampler to the ladder from the final round in the annealing file. More...

void	mpi_cleanup ()
	Cleans up the MPI instances of the sampler to gracefully exit;.

void	get_chain_state (std::vector< double > &chain, std::vector< double > &state)

void	set_chain_state (std::vector< double > chain, std::vector< double > state)

std::vector< double >	find_best_fit (std::string chain_file, std::string state_file) const
	Finds the best fit within provided chain file and returns it. More...

std::vector< double >	find_best_fit () const
	Finds the best fit from the chain and state file saved in set_output_stream. More...

void	write_checkpoint (std::string file)

void	write_checkpoint (std::ostream &file)

void	read_checkpoint (std::istream &ckpt_in)
	Loads the ckpt from a stream. This will set the sampler to the state given in the ckpt. More...

void	read_checkpoint (std::string ckpt_file)
	Reads the checkpoint file and restores the sampler to that state. More...

void	set_checkpoint (int ckpt_stride, std::string ckpt_file)

double	estimate_bayesian_evidence (double avg_lklhd[], double beta[])
	Function to estimate the bayesian evidence using the Thermodynamic Integration method. More...

Public Member Functions inherited from sampler_MCMC_base
	sampler_MCMC_base (int seed, likelihood &L, std::vector< std::string > var_names, size_t dimension)

void	set_checkpoint (int ckpt_stride, std::string ckpt_file)
	Sets the checkpoint/restart functionality. More...

virtual void	reset_sampler_step ()

void	reset_likelihood_sum ()

double	get_likelihood_sum ()

virtual double	get_rand ()

virtual void	reset_rng_seed (int seed)

void	set_mpi_communicator (MPI_Comm comm)
	Sets the MPI_Comm to be used for the likelihood evaluation. More...

void	close_streams ()
	Helper function that closes the streams from a sampler.

Private Member Functions
void	initialize_mpi ()

void	initialize_ladder ()

double	update_annealing_params ()

double	find_beta (Interpolator1D &fLambda, int k, double Lambda, double eps=1e-12, int MAX_ITR=1e8)

void	write_annealing_headers ()

void	run_deo_round (int round, int nlength, int thin, int refresh, int verbosity, bool &even_swap, double avg_lklhd[])

void	generate_transitions (int niterations, int start, int finish, int thin, int refresh, int verbosity)

void	deo_swap (const bool even_swap, const int round, const int swap)

double	finish_deo_round (int rank, int round, double avg_lklhd[])

void	write_state ()

Private Attributes
S	_sampler

likelihood_power_tempered *	_L_tmp

int	_b

double	_initial_spacing

int	_TNum

int	_E_Num

int	_ckpt_stride_deo

bool	_default_cpu_distribution

bool	_no_initial_ladder

bool	_write_all

std::vector< double >	_initial

int	_current_round

int	_swap_stride

int	_current_length

bool	_restart

std::vector< double >	_beta

std::vector< double >	_R

MPI_Comm	E_COMM

MPI_Comm	T_COMM

int	T_size

int	T_rank

int	E_size

int	E_rank

MPI_Status	Stat

MPI_Status	Stat2

MPI_Request	Req

MPI_Request	Req2

std::string	_old_annealing_file

std::string	_anneal_file

std::string	_anneal_summary_file

std::ofstream	_anneal_out

std::ofstream	_anneal_summary_out

Additional Inherited Members
Protected Member Functions inherited from sampler_MCMC_base
virtual void	write_chain_header ()

virtual void	write_state_header ()

Protected Attributes inherited from sampler_MCMC_base
int	_seed

Ran2RNG	_rng

std::vector< std::string >	_var_names

size_t	_dimension

size_t	_step_count

likelihood *	_L

std::string	_chain_file

std::string	_state_file

std::string	_sampler_file

std::string	_ckpt_file

std::ofstream	_chain_out

std::ofstream	_state_out

std::ofstream	_sampler_out

int	_output_precision

int	_ckpt_stride

double	_sum_lklhd

MPI_Comm	_comm

int	_rank

Detailed Description

template<class S>
class Themis::sampler_deo_tempering_MCMC< S >

Runs a parallel tempered mcmc chain using a exploration kernel based on the sampler_exploration_mcmc_base class. This uses the parallel tempering scheme from Syed et al. (2020), which is based on the deterministic even-odd swapping scheme, which is a non-reversible markov chain. For more information on the tempering please see Syed 2020).

Member Function Documentation

double estimate_bayesian_evidence	(	double	avg_lklhd[],
		double	beta[]
	)

Parameters

avg_lklhd[]	Vector of likelihood expectations to compute the evidence, using trapezoid rule.
beta[]	Temperatures of a run.

Note: Currently does not work! TODO.

std::vector<double> find_best_fit	(	std::string	chain_file,
		std::string	state_file
	)		const

inlinevirtual

Parameters

chain_file	The file name of the chain.
state_file	The file name of the saved state.

Note: if no chain_file or state_file is provided it will just read in the one that was saved using set_output_stream. This also assumes that the first element of the state vector is the log-likelihood value.

Reimplemented from sampler_MCMC_base.

std::vector<double> find_best_fit ( ) const

inlinevirtual

Note: Only run this after calling run sampler.

Reimplemented from sampler_MCMC_base.

void read_checkpoint ( std::istream & ckpt_in )

inlinevirtual

Parameters

ckpt_in A reference to the input stream.

Implements sampler_MCMC_base.

void read_checkpoint ( std::string ckpt_file )

virtual

Parameters

ckpt_file The file name of the checkpoint file.

Reimplemented from sampler_MCMC_base.

void read_initial_ladder ( std::string annealing_file )

Parameters

annealing_file is the file containing the annealing information for the run. Namely the round, ladder, and rejection rates.

void run_sampler	(	int	number_of_rounds,
		int	thin,
		int	refresh,
		int	verbosity = `0`
	)

virtual

Parameters

number_of_rounds	How many rounds you want to run the sampler for. You can run this many times to build up rounds.
thin	The thinning rate of the chain. Every thin'd step will be saved.
refresh	How often cout is updated. If < 0 it is never updated.
verbosity	If 1 it will save the chain information for all tempering levels.

Note: The total number of samples will be given by start_samples*swap_stride.

Implements sampler_MCMC_base.

void set_annealing_schedule	(	double	initial_spacing,
		int	geometric_increase = `2`
	)

Parameters

initial_spacing	The initial geometric spacing for the ladder. That is, the inverse temperature for the ith rung will be given by 1.0/geometric_increase^i.
geometric_increase	The geometric increase for the number of steps to be used for each round. This should almost always be 2.

void set_cpu_distribution	(	int	num_temperatures,
		int	num_exploration
	)

Parameters

num_temperatures	The number of temperatures for the sampler.
num_exploration	The number of processors to send each exploration sampler.

Note: If this isn't called we use the default distribution which set num_temperatures equal to the number of MPI instances, and num_exploration to 1.

void set_deo_round_params	(	int	initial_length,
		int	swap_stride
	)

Parameters

initial_length	The number of swaps to do in the first round..
swap_stride	The number of steps to take before we swap temperatures. Typically this should be at least 5.

Note: The default is 10 swaps initially and a swap stride of 25. This is probably too short.

void set_output_stream	(	std::string	chain_file,
		std::string	state_file,
		std::string	sampler_file,
		int	output_precision = `8`
	)

virtual

Note: For DEO every chain,state,sampler file will be prefixed with roundXXX_ to denote which deo round it is on.

Reimplemented from sampler_MCMC_base.

The documentation for this class was generated from the following file:

sampling/sampler_deo_tempering_MCMC.h

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

template<class S> class Themis::sampler_deo_tempering_MCMC< S >

Member Function Documentation

template<class S>
class Themis::sampler_deo_tempering_MCMC< S >