Namespace that contains types and functions for internal computations. More...

Namespaces
	bld_mult
	Namespace containing bld_mult update functions (CUDA/non-CUDA).

	online_EM
	Namespace containing online_EM algorithm related functions.

Classes
class	CollapsedGibbsComputer
	Computer type that will compute the next collapsed gibbs sample when its operator() is invoked. More...

class	SampleOnesNoReplaceComputer
	Computer type that will compute the next sample from a given matrix without replacement when its operator() is invoked. More...

class	SampleOnesReplaceComputer
	Computer type that will compute the next sample from a given matrix with replacement when its operator() is invoked. More...

class	TotalMarginalCalculator
	Class to compute total \(p(X\|\Theta) = \sum_S p(X\|S)p(S\|\Theta)\) for all possible allocation tensors while storing shared state between function invocations. More...

Functions
template<typename T , typename Scalar >
double	compute_first_term (const tensor_t< T, 3 > &S, const std::vector< Scalar > &alpha)
	Compute the first term of the sum when calculating log marginal of S. More...

template<typename T , typename Scalar >
double	compute_second_term (const tensor_t< T, 3 > &S, const std::vector< Scalar > &beta)
	Compute the second term of the sum when calculating log marginal of S. More...

template<typename T , typename Scalar >
double	compute_third_term (const tensor_t< T, 3 > &S, Scalar a, Scalar b)
	Compute the third term of the sum when calculating log marginal of S. More...

template<typename T >
double	compute_fourth_term (const tensor_t< T, 3 > &S)
	Compute the fourth term of the sum when calculating log marginal of S. More...

template<typename T >
void	update_X_hat (const matrix_t< T > &nu, const matrix_t< T > &mu, matrix_t< T > &X_hat)

template<typename T >
void	update_orig_over_appr (const matrix_t< T > &X, const matrix_t< T > &X_hat, const matrix_t< T > &eps_mat, matrix_t< T > &orig_over_appr)

template<typename T >
void	update_orig_over_appr_squared (const matrix_t< T > &X, const matrix_t< T > &X_hat, const matrix_t< T > &eps_mat, matrix_t< T > &orig_over_appr_squared)

template<typename T >
void	update_S (const matrix_t< T > &orig_over_appr, const matrix_t< T > &nu, const matrix_t< T > &mu, tensor_t< T, 3 > &S)

template<typename T >
void	update_alpha_eph (const vector_t< T > &alpha, const tensor_t< T, 3 > &S, matrix_t< T > &alpha_eph)

template<typename T >
void	update_beta_eph (const vector_t< T > &beta, const tensor_t< T, 3 > &S, matrix_t< T > &beta_eph)

template<typename T >
void	update_grad_plus (const matrix_t< T > &beta_eph, const tensor_t< T, 3 > &S, tensor_t< T, 3 > &grad_plus)

template<typename T >
void	update_grad_minus (const matrix_t< T > &alpha_eph, matrix_t< T > &grad_minus)

template<typename T >
void	update_nu (const matrix_t< T > &orig_over_appr, const matrix_t< T > &orig_over_appr_squared, const matrix_t< T > &mu, const tensor_t< T, 3 > &grad_plus, const matrix_t< T > &grad_minus, double eps, matrix_t< T > &nu)

template<typename T >
static void	update_mu (const matrix_t< T > &orig_over_appr, const matrix_t< T > &orig_over_appr_squared, const matrix_t< T > &nu, const tensor_t< T, 3 > &grad_plus, const matrix_t< T > &grad_minus, double eps, matrix_t< T > &mu)

template<typename T , typename Scalar >
void	check_bld_params (const matrix_t< T > &X, size_t z, const alloc_model::Params< Scalar > &model_params)
	Do parameter checks on BLD computing function parameters and throw an assertion error if the parameters are incorrect. More...

template<typename T , typename Scalar >
void	check_EM_params (const matrix_t< T > &X, const std::vector< alloc_model::Params< Scalar >> &param_vec)
	Do parameter checks on EM algorithms for solving the BLD problem. More...

template<typename Real >
Real	gsl_psi_wrapper (Real x)
	A template wrapper function around gsl_sf_psi. More...

template<typename T >
void	check_sample_ones_params (const matrix_t< T > &X)

template<typename IntIterator >
void	right_partition (IntIterator begin, IntIterator end, IntIterator all_begin, IntIterator all_end, std::vector< std::pair< size_t, size_t >> &change_indices)
	Partition the number stored at the beginning of the given sequence towards the end of the sequence by computing new partitions using exactly one increment and one decrement operations. More...

template<typename IntIterator >
void	left_partition (IntIterator begin, IntIterator end, IntIterator all_begin, IntIterator all_end, std::vector< std::pair< size_t, size_t >> &change_indices)
	Partition the number stored at the end of the given sequence towards the beginning of the sequence by computing new partitions using exactly one increment and one decrement operations. More...

Detailed Description

Namespace that contains types and functions for internal computations.

Functions and classes in this namespace are not meant for direct usage by the users of bnmf-algs library; hence, behaviours of some functions may not be as expected. Additionally, some of these functions and types are not directly tested, and their behaviour is verified through correct behaviour of the API functions and types using them.

Function Documentation

template<typename T , typename Scalar >

void bnmf_algs::details::check_bld_params	(	const matrix_t< T > &	X,
		size_t	z,
		const alloc_model::Params< Scalar > &	model_params
	)

Do parameter checks on BLD computing function parameters and throw an assertion error if the parameters are incorrect.

Template Parameters

T	Type of the matrix/tensor entries.
Scalar	Type of the scalars used as model parameters.

Remarks: Throws assertion error if the parameters are incorrect.

template<typename T , typename Scalar >

void bnmf_algs::details::check_EM_params	(	const matrix_t< T > &	X,
		const std::vector< alloc_model::Params< Scalar >> &	param_vec
	)

Do parameter checks on EM algorithms for solving the BLD problem.

Template Parameters

T	type of the matrix entries.
Scalar	Type of the scalars used as model parameters.

Remarks: Throws assertion error if the parameters are incorrect.

template<typename T >

void bnmf_algs::details::check_sample_ones_params ( const matrix_t< T > & X )

template<typename T , typename Scalar >

double bnmf_algs::details::compute_first_term	(	const tensor_t< T, 3 > &	S,
		const std::vector< Scalar > &	alpha
	)

Compute the first term of the sum when calculating log marginal of S.

Template Parameters

Scalar	Type of the model parameters.
T	Value type of the tensor S.

Parameters

S	Tensor S.
alpha	Parameter vector of Dirichlet prior for matrix \(W\) of size \(x\).

Returns: Value of the first term

template<typename T >

double bnmf_algs::details::compute_fourth_term ( const tensor_t< T, 3 > & S )

Compute the fourth term of the sum when calculating log marginal of S.

Template Parameters

T	Value type of tensor S.

Parameters

S Tensor S.

Returns: Value of the fourth term

template<typename T , typename Scalar >

double bnmf_algs::details::compute_second_term	(	const tensor_t< T, 3 > &	S,
		const std::vector< Scalar > &	beta
	)

Compute the second term of the sum when calculating log marginal of S.

Template Parameters

Scalar	Type of the model parameters.
T	Value type of tensor S.

Parameters

S	Tensor S.
beta	Parameter vector of Dirichlet prior for matrix \(H\) of size \(z\).

Returns: Value of the second term

template<typename T , typename Scalar >

double bnmf_algs::details::compute_third_term	(	const tensor_t< T, 3 > &	S,
		Scalar	a,
		Scalar	b
	)

Compute the third term of the sum when calculating log marginal of S.

Template Parameters

Scalar	Type of the model parameters.
T	Value type of tensor S.

Parameters

S	Tensor S.
a	Shape parameter of Gamma distribution.
b	Rate parameter of Gamma distribution.

Returns: Value of the third term

template<typename Real >

Real bnmf_algs::details::gsl_psi_wrapper ( Real x )

A template wrapper function around gsl_sf_psi.

gsl_sf_psi can only be called with double arguments. This function wraps gsl_sf_psi using static casts. Argument type is cast to double, gsl_sf_psi is called and the resulting double is cast back to argument type.

Template Parameters

Real	Type of the input.

Parameters

x Input.

Returns: Output of gsl_sf_psi with the same type as the parameter.

template<typename IntIterator >

void bnmf_algs::details::left_partition	(	IntIterator	begin,
		IntIterator	end,
		IntIterator	all_begin,
		IntIterator	all_end,
		std::vector< std::pair< size_t, size_t >> &	change_indices
	)

Partition the number stored at the end of the given sequence towards the beginning of the sequence by computing new partitions using exactly one increment and one decrement operations.

This function partitions the number given at the end of the given sequence, *(end - 1) , towards the beginning, *begin . The indices of the values incremented/decremented to compute a new partition is pushed to the back of the given output vector, change_indices.

For n = *(end - 1) and k = end - begin , this function stores exactly \({n + k - 1}\choose{k - 1}\) different partitions between begin and end iterators. Increment/decrement indices of each partition is stored in the given output vector.

Template Parameters

Integer Integer type to use.

Parameters

begin	Beginning (leftmost iterator) of the sequence to store the partitions of the rightmost number.
end	End (rightmost past one) of the sequence to store the partitions of the rightmost number. The number to partition must reside on the iterator before end.
all_begin	Beginning of the whole sequence that stores complete partitions. This is the beginning iterator of the original vector that is modified to store various partitions of the original number.
all_end	End of the whole sequence that stores complete partitions.
change_indices	Output vector that stores increment/decrement index pairs to compute the next partition from previous one.

template<typename IntIterator >

void bnmf_algs::details::right_partition	(	IntIterator	begin,
		IntIterator	end,
		IntIterator	all_begin,
		IntIterator	all_end,
		std::vector< std::pair< size_t, size_t >> &	change_indices
	)

Partition the number stored at the beginning of the given sequence towards the end of the sequence by computing new partitions using exactly one increment and one decrement operations.

This function partitions the number given at the beginning of the given sequence, *begin , towards the end, *(end - 1) . The indices of the values incremented/decremented to compute a new partition is pushed to the back of the given output vector, change_indices.

For n = *begin and k = end - begin , this function stores exactly \({n + k - 1}\choose{k - 1}\) different partitions between begin and end iterators. Increment/decrement indices of each partition is stored in the given output vector.

Template Parameters

Integer Integer type to use.

Parameters

begin	Beginning (leftmost iterator) of the sequence to store the partitions of the leftmost number. (*begin)
end	End (rightmost past one) of the sequence to store the partitions of the rightmost number.
all_begin	Beginning of the whole sequence that stores complete partitions. This is the beginning iterator of the original vector that is modified to store various partitions of the original number.
all_end	End of the whole sequence that stores complete partitions.
change_indices	Output vector that stores increment/decrement index pairs to compute the next partition from previous one.

template<typename T >

void bnmf_algs::details::update_alpha_eph	(	const vector_t< T > &	alpha,
		const tensor_t< T, 3 > &	S,
		matrix_t< T > &	alpha_eph
	)

template<typename T >

void bnmf_algs::details::update_beta_eph	(	const vector_t< T > &	beta,
		const tensor_t< T, 3 > &	S,
		matrix_t< T > &	beta_eph
	)

template<typename T >

void bnmf_algs::details::update_grad_minus	(	const matrix_t< T > &	alpha_eph,
		matrix_t< T > &	grad_minus
	)

template<typename T >

void bnmf_algs::details::update_grad_plus	(	const matrix_t< T > &	beta_eph,
		const tensor_t< T, 3 > &	S,
		tensor_t< T, 3 > &	grad_plus
	)

template<typename T >

static void bnmf_algs::details::update_mu	(	const matrix_t< T > &	orig_over_appr,
		const matrix_t< T > &	orig_over_appr_squared,
		const matrix_t< T > &	nu,
		const tensor_t< T, 3 > &	grad_plus,
		const matrix_t< T > &	grad_minus,
		double	eps,
		matrix_t< T > &	mu
	)

static

template<typename T >

void bnmf_algs::details::update_nu	(	const matrix_t< T > &	orig_over_appr,
		const matrix_t< T > &	orig_over_appr_squared,
		const matrix_t< T > &	mu,
		const tensor_t< T, 3 > &	grad_plus,
		const matrix_t< T > &	grad_minus,
		double	eps,
		matrix_t< T > &	nu
	)

template<typename T >

void bnmf_algs::details::update_orig_over_appr	(	const matrix_t< T > &	X,
		const matrix_t< T > &	X_hat,
		const matrix_t< T > &	eps_mat,
		matrix_t< T > &	orig_over_appr
	)

template<typename T >

void bnmf_algs::details::update_orig_over_appr_squared	(	const matrix_t< T > &	X,
		const matrix_t< T > &	X_hat,
		const matrix_t< T > &	eps_mat,
		matrix_t< T > &	orig_over_appr_squared
	)

template<typename T >

void bnmf_algs::details::update_S	(	const matrix_t< T > &	orig_over_appr,
		const matrix_t< T > &	nu,
		const matrix_t< T > &	mu,
		tensor_t< T, 3 > &	S
	)

template<typename T >

void bnmf_algs::details::update_X_hat	(	const matrix_t< T > &	nu,
		const matrix_t< T > &	mu,
		matrix_t< T > &	X_hat
	)

Namespaces

Classes

Functions

Detailed Description

Function Documentation