Dirichlet Process class for Bayesian nonparametric clustering. More...

#include <DP.hpp>

Inheritance diagram for DP:

Public Member Functions
	DP (Data &d, Params &p)
	Constructor for the Dirichlet Process.
void	update_params () override
	Updates the parameters of the Dirichlet Process.
Gibbs Sampling Methods
double	gibbs_prior_existing_cluster (int cls_idx, int obs_idx=0) const override
	Computes the log prior probability of assigning a data point to an existing cluster.
Eigen::VectorXd	gibbs_prior_existing_clusters (int obs_idx) const override
	Computes the log prior probabilities of assigning a data point to all existing clusters.
double	gibbs_prior_new_cluster () const override
	Computes the log prior probability of assigning a data point to a new cluster.
Split-Merge Algorithm Methods
double	prior_ratio_split (int ci, int cj) const override
	Computes the prior ratio for a split operation in a split-merge MCMC algorithm.
double	prior_ratio_merge (int size_old_ci, int size_old_cj) const override
	Computes the prior ratio for a merge operation in a split-merge MCMC algorithm.
double	prior_ratio_shuffle (int size_old_ci, int size_old_cj, int ci, int cj) const override
	Computes the prior ratio for a shuffle operation in a split-merge MCMC algorithm.
Public Member Functions inherited from Process
	Process (Data &d, const Params &p)
	Constructor initializing process with data and parameters.
virtual double	gibbs_prior_new_cluster_obs (int obs_idx) const
	Compute prior probability for creating a new cluster for a specific observation.
void	set_old_allocations (const Eigen::VectorXi &new_allocations)
	Store current allocations for potential rollback.
void	set_old_cluster_members (const std::unordered_map< int, std::vector< int > > &new_cluster_members)
	Store current cluster members for potential rollback.
void	set_old_K (int new_K)
	Store current number of clusters for potential rollback.
void	restore_state ()
	Restores the cached state into the data object.
const Eigen::VectorXi &	old_allocations_view () const
	Provides read-only access to the stored previous allocations.
void	set_idx_i (int i)
	Set index of first observation in split-merge pair.
void	set_idx_j (int j)
	Set index of second observation in split-merge pair.
virtual	~Process ()
	Virtual destructor for proper cleanup of derived classes.

Additional Inherited Members
Protected Member Functions inherited from Process
const std::unordered_map< int, std::vector< int > > &	old_cluster_members_view () const
	Provides read-only access to the stored previous cluster members.
Protected Attributes inherited from Process
Data &	data
	Reference to the data object containing observations and allocations.
const Params &	params
	Reference to the parameters object containing process hyperparameters.
Eigen::VectorXi	old_allocations
	Storage for previous allocations to enable rollback in case of rejection or for computation requiring it.
std::unordered_map< int, std::vector< int > >	old_cluster_members
	Storage for previous cluster members to enable rollback in case of rejection or for computation requiring it.
int	old_K = 0
	Number of clusters associated with the stored previous state.
int	idx_i
	Index of first observation involved in split-merge move.
int	idx_j
	Index of second observation involved in split-merge move.
const double	log_a = log(params.a)
	Precomputed logarithm of total mass parameter for efficiency.

Detailed Description

Dirichlet Process class for Bayesian nonparametric clustering.

This class implements a Dirichlet Process (DP) that inherits from the Process base class. It provides methods for Gibbs sampling and split-merge algorithms used in clustering.

Constructor & Destructor Documentation

◆ DP()

DP::DP	(	Data &	d,
		Params &	p )

inline

Constructor for the Dirichlet Process.

Parameters

d	Reference to the data object.
p	Reference to the parameters object.

Member Function Documentation

◆ gibbs_prior_existing_cluster()

double DP::gibbs_prior_existing_cluster	(	int	cls_idx,
		int	obs_idx = 0 ) const

nodiscardoverridevirtual

Computes the log prior probability of assigning a data point to an existing cluster.

Parameters

cls_idx	The index of the cluster.
obs_idx	The index of the observation (default: 0).

Returns: The log prior probability of assigning the data point to the existing cluster.

Computes the log prior probability of assigning a data point to an existing cluster.

Parameters

cls_idx	The index of the cluster.
obs_idx	The index of the observation (unused in this implementation).

Returns: The log prior probability of assigning the data point to its current cluster.

Implements Process.

Reimplemented in DPx.

◆ gibbs_prior_existing_clusters()

Eigen::VectorXd DP::gibbs_prior_existing_clusters ( int obs_idx ) const

nodiscardoverridevirtual

Computes the log prior probabilities of assigning a data point to all existing clusters.

Parameters

obs_idx The index of the observation.

Returns: A vector of log prior probabilities for all existing clusters.

Computes the log prior probabilities of assigning a data point to all existing clusters.

Parameters

obs_idx The index of the observation (unused in this implementation).

Returns: A vector of log prior probabilities for all existing clusters.

Implements Process.

Reimplemented in DPx.

◆ gibbs_prior_new_cluster()

double DP::gibbs_prior_new_cluster ( ) const

nodiscardoverridevirtual

Computes the log prior probability of assigning a data point to a new cluster.

Returns: The log prior probability of assigning the data point to a new cluster.

Computes the log prior probability of assigning a data point to a new cluster.

Returns: The log prior probability of assigning the data point to a new cluster.

Implements Process.

Reimplemented in DPx.

◆ prior_ratio_merge()

double DP::prior_ratio_merge	(	int	size_old_ci,
		int	size_old_cj ) const

nodiscardoverridevirtual

Computes the prior ratio for a merge operation in a split-merge MCMC algorithm.

Parameters

size_old_ci	The size of the first cluster before the merge.
size_old_cj	The size of the second cluster before the merge.

Returns: The log prior ratio for the merge operation.

Computes the prior ratio for a merge operation in a split-merge MCMC algorithm.

Parameters

size_old_ci	The size of the first cluster before the merge.
size_old_cj	The size of the second cluster before the merge.

Returns: The log prior ratio for the merge operation.

Implements Process.

Reimplemented in DPx.

◆ prior_ratio_shuffle()

double DP::prior_ratio_shuffle	(	int	size_old_ci,
		int	size_old_cj,
		int	ci,
		int	cj ) const

nodiscardoverridevirtual

Computes the prior ratio for a shuffle operation in a split-merge MCMC algorithm.

Parameters

size_old_ci	The size of the first cluster before the shuffle.
size_old_cj	The size of the second cluster before the shuffle.
ci	The first cluster index involved in the shuffle.
cj	The second cluster index involved in the shuffle.

Returns: The log prior ratio for the shuffle operation.

Computes the prior ratio for a shuffle operation in a split-merge MCMC algorithm.

Parameters

size_old_ci	The size of the first cluster before the shuffle.
size_old_cj	The size of the second cluster before the shuffle.
ci	The first cluster index involved in the shuffle.
cj	The second cluster index involved in the shuffle.

Returns: The log prior ratio for the shuffle operation.

Implements Process.

Reimplemented in DPx.

◆ prior_ratio_split()

double DP::prior_ratio_split	(	int	ci,
		int	cj ) const

nodiscardoverridevirtual

Computes the prior ratio for a split operation in a split-merge MCMC algorithm.

Parameters

ci	The first cluster index involved in the split.
cj	The second cluster index involved in the split.

Returns: The log prior ratio for the split operation.

Computes the prior ratio for a split operation in a split-merge MCMC algorithm.

Parameters

ci	The first cluster index involved in the split.
cj	The second cluster index involved in the split.

Returns: The log prior ratio for the split operation.

Implements Process.

Reimplemented in DPx.

◆ update_params()

void DP::update_params ( )

inlineoverridevirtual

Updates the parameters of the Dirichlet Process.

This is a null implementation as the Dirichlet Process has no parameters to update.

Implements Process.

Reimplemented in DPx.

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

src/processes/DP.hpp
src/processes/DP.cpp

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ DP()

Member Function Documentation

◆ gibbs_prior_existing_cluster()

◆ gibbs_prior_existing_clusters()

◆ gibbs_prior_new_cluster()

◆ prior_ratio_merge()

◆ prior_ratio_shuffle()

◆ prior_ratio_split()

◆ update_params()