#include <LOTHypothesis.h>

Inheritance diagram for LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >:

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Collaboration diagram for LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >:

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Public Types
typedef Bayesable< _datum_t, _data_t >::datum_t	datum_t

typedef Bayesable< _datum_t, _data_t >::data_t	data_t

using	Grammar_t = _Grammar_t

using	input_t = _input_t

using	output_t = _output_t

using	VirtualMachineState_t = _VirtualMachineState_t

using	ProposalType = std::optional< std::pair< this_t, double > >

Public Types inherited from Bayesable< Args... >
typedef Args...	datum_t

typedef std::vector< Args... >	data_t

Public Member Functions
	LOTHypothesis ()

	LOTHypothesis (Node &x)

	LOTHypothesis (Node &&x)

	LOTHypothesis (std::string s)

	LOTHypothesis (const LOTHypothesis &c)

	LOTHypothesis (const LOTHypothesis &&c)

LOTHypothesis &	operator= (const LOTHypothesis &c)

LOTHypothesis &	operator= (const LOTHypothesis &&c)

virtual ProposalType	propose () const override
	Default proposal is rational-rules style regeneration. More...

virtual this_t	restart () const override
	This is used to restart chains, sampling from prior but ONLY for nodes that are can_resample. More...

Node &	get_value ()

const Node &	get_value () const

void	set_value (Node &v, bool should_compile=true)
	Set the value to v. (NOTE: This compiles into a program) More...

void	set_value (Node &&v, bool should_compile=true)

Grammar_t *	get_grammar () const

virtual double	compute_prior () override
	Compute the prior – defaultly just the PCFG (grammar) prior. More...

virtual double	compute_single_likelihood (const datum_t &datum) override

void	compile ()

virtual void	push_program (Program< VirtualMachineState_t > &s) override
	This puts the code from my node onto s. Used internally in e.g. recursion. More...

virtual std::string	string (std::string prefix="") const override

virtual std::string	string (std::string prefix, bool usedot) const

virtual size_t	hash () const override

virtual bool	operator== (const this_t &h) const override
	Equality is checked on equality of values; note that greater-than is still on posteriors. More...

virtual void	complete () override
	Modify this hypothesis's value by (randomly) filling in all the gaps. More...

virtual int	neighbors () const override
	Count the number of neighbors that are possible. (This should be size_t but int is more convenient.) More...

virtual void	expand_to_neighbor (int k) override
	Modify this hypothesis to become the k'th neighbor. NOTE This does not compile since it might not be complete. More...

virtual double	neighbor_prior (int k) override
	What is the prior of the k'th neighbor? This does not need to return the full prior, only relative (among ks) More...

virtual bool	is_evaluable () const override
	A node is "evaluable" if it is complete (meaning no null subnodes) More...

size_t	recursion_count ()
	Count up how many times I use recursion – we keep a list of recursion here. More...

virtual std::string	serialize () const override
	Convert this into a string which can be written to a file. More...

Public Member Functions inherited from MCMCable< this_t, _datum_t, _data_t >
	MCMCable ()

virtual bool	operator!= (const this_t &h) const

Public Member Functions inherited from Bayesable< Args... >
	Bayesable ()

virtual double	compute_single_likelihood (const datum_t &datum)
	Compute the likelihood of a single data point. More...

virtual void	clear_bayes ()

virtual double	compute_likelihood (const data_t &data, const double breakout=-infinity)
	Compute the likelihood of a collection of data, by calling compute_single_likelihood on each. This stops if our likelihood falls below breakout. More...

virtual double	compute_posterior (const data_t &data, const std::pair< double, double > breakoutpair=std::make_pair(-infinity, 1.0))
	Compute the posterior, by calling prior and likelihood. This includes only a little bit of fanciness, which is that if our prior is -inf, then we don't both computing the likelihood. More...

virtual double	at_temperature (double t) const

auto	operator (const Bayesable< datum_t, data_t > &other) const

virtual void	show (std::string prefix="")

Public Member Functions inherited from Searchable< this_t, _input_t, _output_t >
virtual this_t	make_neighbor (int k) const
	Return a new hypothesis which is the k'th neighbor (just calls expand_to_neighbor) NOTE This does not compile since it might not be complete. More...

Public Member Functions inherited from ProgramLoader< _VirtualMachineState_t >
virtual void	push_program (Program< _VirtualMachineState_t > &s, const short a)

virtual void	push_program (Program< _VirtualMachineState_t > &s, const int a)

virtual void	push_program (Program< _VirtualMachineState_t > &s, const std::string k)

Static Public Member Functions
static this_t	sample ()

static this_t	from_string (Grammar_t *g, std::string s)

static this_t	deserialize (const std::string &s)
	Convert this from a string which was in a file. More...

Static Public Member Functions inherited from MCMCable< this_t, _datum_t, _data_t >
static this_t	sample ()
	Static function for making a hypothesis. Be careful using this with references because they may not foward right (for reasons that are unclear to me) More...

Static Public Member Functions inherited from Serializable< this_t >
static this_t	deserialize (const std::string &)

Public Attributes
unsigned long	total_instruction_count_last_call

unsigned long	total_vms_steps

Program< VirtualMachineState_t >	program

Public Attributes inherited from Bayesable< Args... >
double	prior

double	likelihood

double	posterior

uintmax_t	born

size_t	born_chain_idx

Public Attributes inherited from ProgramLoader< _VirtualMachineState_t >
bool	was_called

Static Public Attributes
static const char	SerializationDelimiter = '\t'

static const size_t	MAX_NODES = 64

Protected Attributes
Node	value

Detailed Description

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>
class LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >

Author: piantado

Date: 05/05/20

Member Typedef Documentation

◆ data_t

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

typedef Bayesable<_datum_t,_data_t>::data_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::data_t

◆ datum_t

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

typedef Bayesable<_datum_t,_data_t>::datum_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::datum_t

◆ Grammar_t

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

using LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::Grammar_t = _Grammar_t

◆ input_t

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

using LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::input_t = _input_t

◆ output_t

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

using LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::output_t = _output_t

◆ ProposalType

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

using LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::ProposalType = std::optional<std::pair<this_t,double> >

◆ VirtualMachineState_t

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

using LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::VirtualMachineState_t = _VirtualMachineState_t

Constructor & Destructor Documentation

◆ LOTHypothesis() [1/6]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::LOTHypothesis ( )

inline

◆ LOTHypothesis() [2/6]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::LOTHypothesis ( Node & x )

inline

◆ LOTHypothesis() [3/6]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::LOTHypothesis ( Node && x )

inline

◆ LOTHypothesis() [4/6]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::LOTHypothesis ( std::string s )

inline

◆ LOTHypothesis() [5/6]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::LOTHypothesis ( const LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t > & c )

inline

◆ LOTHypothesis() [6/6]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::LOTHypothesis ( const LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t > && c )

inline

Member Function Documentation

◆ compile()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

void LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::compile ( )

inline

◆ complete()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual void LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::complete ( )

inlineoverridevirtual

Modify this hypothesis's value by (randomly) filling in all the gaps.

Implements Searchable< this_t, _input_t, _output_t >.

◆ compute_prior()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual double LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::compute_prior ( )

inlineoverridevirtual

Compute the prior – defaultly just the PCFG (grammar) prior.

Returns

Implements Bayesable< Args... >.

Reimplemented in MyHypothesis, MyHypothesis, InnerHypothesis, MyHypothesis, and InnerHypothesis.

◆ compute_single_likelihood()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual double LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::compute_single_likelihood ( const datum_t & datum )

inlineoverridevirtual

Reimplemented in MyHypothesis, MyHypothesis, and MyHypothesis.

◆ deserialize()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

static this_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::deserialize ( const std::string & s )

inlinestatic

Convert this from a string which was in a file.

Parameters

s

Returns

◆ expand_to_neighbor()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual void LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::expand_to_neighbor ( int k )

inlineoverridevirtual

Modify this hypothesis to become the k'th neighbor. NOTE This does not compile since it might not be complete.

Parameters

k

Implements Searchable< this_t, _input_t, _output_t >.

◆ from_string()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

static this_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::from_string	(	Grammar_t *	g,
		std::string	s
	)

inlinestatic

◆ get_grammar()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

Grammar_t* LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::get_grammar ( ) const

inline

◆ get_value() [1/2]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

Node& LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::get_value ( )

inline

◆ get_value() [2/2]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

const Node& LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::get_value ( ) const

inline

◆ hash()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual size_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::hash ( ) const

inlineoverridevirtual

Implements Bayesable< Args... >.

◆ is_evaluable()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual bool LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::is_evaluable ( ) const

inlineoverridevirtual

A node is "evaluable" if it is complete (meaning no null subnodes)

Returns

Implements Searchable< this_t, _input_t, _output_t >.

◆ neighbor_prior()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual double LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::neighbor_prior ( int k )

inlineoverridevirtual

What is the prior of the k'th neighbor? This does not need to return the full prior, only relative (among ks)

Parameters

k

Implements Searchable< this_t, _input_t, _output_t >.

◆ neighbors()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual int LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::neighbors ( ) const

inlineoverridevirtual

Count the number of neighbors that are possible. (This should be size_t but int is more convenient.)

Implements Searchable< this_t, _input_t, _output_t >.

◆ operator=() [1/2]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

LOTHypothesis& LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::operator= ( const LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t > & c )

inline

◆ operator=() [2/2]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

LOTHypothesis& LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::operator= ( const LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t > && c )

inline

◆ operator==()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual bool LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::operator== ( const this_t & h ) const

inlineoverridevirtual

Equality is checked on equality of values; note that greater-than is still on posteriors.

Parameters

h

Returns

Implements MCMCable< this_t, _datum_t, _data_t >.

◆ propose()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual ProposalType LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::propose ( ) const

inlineoverridevirtual

Default proposal is rational-rules style regeneration.

Returns

Implements MCMCable< this_t, _datum_t, _data_t >.

Reimplemented in MyHypothesis, InnerHypothesis, and InnerHypothesis.

◆ push_program()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual void LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::push_program ( Program< VirtualMachineState_t > & s )

inlineoverridevirtual

This puts the code from my node onto s. Used internally in e.g. recursion.

Parameters

s
k

Reimplemented from ProgramLoader< _VirtualMachineState_t >.

◆ recursion_count()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

size_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::recursion_count ( )

inline

Count up how many times I use recursion – we keep a list of recursion here.

Returns

◆ restart()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual this_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::restart ( ) const

inlineoverridevirtual

This is used to restart chains, sampling from prior but ONLY for nodes that are can_resample.

Returns

Implements MCMCable< this_t, _datum_t, _data_t >.

◆ sample()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

static this_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::sample ( )

inlinestatic

◆ serialize()

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual std::string LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::serialize ( ) const

inlineoverridevirtual

Convert this into a string which can be written to a file.

Returns

Implements Serializable< this_t >.

◆ set_value() [1/2]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

void LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::set_value	(	Node &	v,
		bool	should_compile = `true`
	)

inline

Set the value to v. (NOTE: This compiles into a program)

Parameters

v

◆ set_value() [2/2]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

void LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::set_value	(	Node &&	v,
		bool	should_compile = `true`
	)

inline

◆ string() [1/2]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual std::string LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::string ( std::string prefix = "" ) const

inlineoverridevirtual

Implements Bayesable< Args... >.

Reimplemented in MyHypothesis.

◆ string() [2/2]

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

virtual std::string LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::string	(	std::string	prefix,
		bool	usedot
	)		const

inlinevirtual

Member Data Documentation

◆ MAX_NODES

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

const size_t LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::MAX_NODES = 64

static

◆ program

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

Program<VirtualMachineState_t> LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::program

◆ SerializationDelimiter

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

const char LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::SerializationDelimiter = '\t'

static

◆ total_instruction_count_last_call

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

unsigned long LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::total_instruction_count_last_call

◆ total_vms_steps

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

unsigned long LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::total_vms_steps

◆ value

template<typename this_t, typename _input_t, typename _output_t, typename _Grammar_t, _Grammar_t * grammar, typename _datum_t = defaultdatum_t<_input_t, _output_t>, typename _data_t = std::vector<_datum_t>, typename _VirtualMachineState_t = typename _Grammar_t::VirtualMachineState_t>

Node LOTHypothesis< this_t, _input_t, _output_t, _Grammar_t, grammar, _datum_t, _data_t, _VirtualMachineState_t >::value

protected

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

src/Hypotheses/LOTHypothesis.h

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ data_t

◆ datum_t

◆ Grammar_t

◆ input_t

◆ output_t

◆ ProposalType

◆ VirtualMachineState_t

Constructor & Destructor Documentation

◆ LOTHypothesis() [1/6]

◆ LOTHypothesis() [2/6]

◆ LOTHypothesis() [3/6]

◆ LOTHypothesis() [4/6]

◆ LOTHypothesis() [5/6]

◆ LOTHypothesis() [6/6]

Member Function Documentation

◆ compile()

◆ complete()

◆ compute_prior()

◆ compute_single_likelihood()

◆ deserialize()

◆ expand_to_neighbor()

◆ from_string()

◆ get_grammar()

◆ get_value() [1/2]

◆ get_value() [2/2]

◆ hash()

◆ is_evaluable()

◆ neighbor_prior()

◆ neighbors()

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ operator==()

◆ propose()

◆ push_program()

◆ recursion_count()

◆ restart()

◆ sample()

◆ serialize()

◆ set_value() [1/2]

◆ set_value() [2/2]

◆ string() [1/2]

◆ string() [2/2]

Member Data Documentation

◆ MAX_NODES

◆ program

◆ SerializationDelimiter

◆ total_instruction_count_last_call

◆ total_vms_steps

◆ value