A Processor which contains a vector of simpler processors Useful for applying same cleaners on a set of features, for example. More...

#include <FeatureProcess.h>

Inheritance diagram for MultiFeatureProcessor:

Public Member Functions
string	select_learn_matrix (const vector< string > &matrix_tags) const
	Will be called before learn to create new version for the matrix if needed - in parallel of existing matrix.

void	init_defaults ()

void	clear ()

int	init (map< string, string > &mapper)
	The parsed fields from init command.

virtual void	copy (FeatureProcessor *processor)

int	Learn (MedFeatures &features, unordered_set< int > &ids)

int	_apply (MedFeatures &features, unordered_set< int > &ids, bool learning)

int	_conditional_apply (MedFeatures &features, unordered_set< int > &ids, unordered_set< string > &req_features, bool learning)

virtual void	get_feature_names (vector< string > &feature_names)

void	add_processors_set (FeatureProcessorTypes type, vector< string > &features)

void	add_processors_set (FeatureProcessorTypes type, vector< string > &features, string init_string)

int	filter (unordered_set< string > &features)
	Filter according to a subset of features.

void	dprint (const string &pref, int fp_flag)

bool	are_features_affected (unordered_set< string > &out_req_features)
	check if a set of features is affected by the current processor

void	update_req_features_vec (unordered_set< string > &out_req_features, unordered_set< string > &in_req_features)
	update sets of required as input according to set required as output to processor

Public Member Functions inherited from FeatureProcessor
void	init_defaults ()

virtual void	set_feature_name (const string &feature_name)

virtual string	get_feature_name ()

int	learn (MedFeatures &features)
	PostProcess of MedFeatures - on all ids.

int	learn (MedFeatures &features, unordered_set< int > &ids)

virtual int	_apply (MedFeatures &features, unordered_set< int > &ids)

int	apply (MedFeatures &features, bool learning)
	PostProcess of MedFeatures - on all or a subset of the ids calls virtaul function "_apply/_conditional_apply" for the specific implementation.

int	apply (MedFeatures &features, unordered_set< string > &req_features, bool learning)

int	apply (MedFeatures &features, unordered_set< int > &ids, bool learning)

int	apply (MedFeatures &features, unordered_set< int > &ids, unordered_set< string > &req_features, bool learning)

int	apply (MedFeatures &features)

int	apply (MedFeatures &features, unordered_set< string > &req_features)

int	apply (MedFeatures &features, unordered_set< int > &ids)

int	apply (MedFeatures &features, unordered_set< int > &ids, unordered_set< string > &req_features)

virtual int	init (void *processor_params)

string	resolve_feature_name (MedFeatures &features, string substr)
	Utility : get corresponding name in MedFeatures.

virtual bool	is_selector ()
	allows testing if this feature processor is a selector

void *	new_polymorphic (string derived_class_name)
	for polymorphic classes that want to be able to serialize/deserialize a pointer * to the derived class given its type one needs to implement this function to return a new to the derived class given its type (as in my_type)

size_t	get_processor_size ()

size_t	processor_serialize (unsigned char *blob)

Public Member Functions inherited from SerializableObject
virtual int	version () const
	Relevant for serializations.

virtual string	my_class_name () const
	For better handling of serializations it is highly recommended that each SerializableObject inheriting class will implement the next method.

virtual void	serialized_fields_name (vector< string > &field_names) const
	The names of the serialized fields.

virtual void	pre_serialization ()

virtual void	post_deserialization ()

virtual size_t	get_size ()
	Gets bytes sizes for serializations.

virtual size_t	serialize (unsigned char *blob)
	Serialiazing object to blob memory. return number ob bytes wrote to memory.

virtual size_t	deserialize (unsigned char *blob)
	Deserialiazing blob to object. returns number of bytes read.

size_t	serialize_vec (vector< unsigned char > &blob)

size_t	deserialize_vec (vector< unsigned char > &blob)

virtual size_t	serialize (vector< unsigned char > &blob)

virtual size_t	deserialize (vector< unsigned char > &blob)

virtual int	read_from_file (const string &fname)
	read and deserialize model

virtual int	write_to_file (const string &fname)
	serialize model and write to file

virtual int	read_from_file_unsafe (const string &fname)
	read and deserialize model without checking version number - unsafe read

int	init_from_string (string init_string)
	Init from string.

int	init_params_from_file (string init_file)

int	init_param_from_file (string file_str, string &param)

int	update_from_string (const string &init_string)

virtual int	update (map< string, string > &map)
	Virtual to update object from parsed fields.

virtual string	object_json () const

Data Fields
FeatureProcessorTypes	members_type

string	init_string

int	duplicate

string	tag

bool	use_parallel_learn

bool	use_parallel_apply

vector< FeatureProcessor * >	processors

Data Fields inherited from FeatureProcessor
string	feature_name = "unset_feature_name"
	Feature name ( + name as appears in MedFeatures) ;.

string	resolved_feature_name

FeatureProcessorTypes	processor_type = FTR_PROCESS_LAST

int	learn_nthreads

int	clean_nthreads

Additional Inherited Members
Static Public Member Functions inherited from FeatureProcessor
static FeatureProcessor *	make_processor (string processor_name)

static FeatureProcessor *	make_processor (FeatureProcessorTypes type)

static FeatureProcessor *	make_processor (string processor_name, string params)

static FeatureProcessor *	make_processor (FeatureProcessorTypes type, string params)

Detailed Description

A Processor which contains a vector of simpler processors Useful for applying same cleaners on a set of features, for example.

To Use this selector specify "multi" or multi_processor in the fp_type

Member Function Documentation

◆ _apply()

int MultiFeatureProcessor::_apply	(	MedFeatures &	features,
		unordered_set< int > &	ids,
		bool	learning
	)

virtual

Reimplemented from FeatureProcessor.

◆ _conditional_apply()

int MultiFeatureProcessor::_conditional_apply	(	MedFeatures &	features,
		unordered_set< int > &	ids,
		unordered_set< string > &	req_features,
		bool	learning
	)

virtual

Reimplemented from FeatureProcessor.

◆ are_features_affected()

bool MultiFeatureProcessor::are_features_affected ( unordered_set< string > & out_req_features )

virtual

check if a set of features is affected by the current processor

Reimplemented from FeatureProcessor.

◆ clear()

void MultiFeatureProcessor::clear ( )

virtual

Reimplemented from FeatureProcessor.

◆ copy()

void MultiFeatureProcessor::copy ( FeatureProcessor * processor )

virtual

Reimplemented from FeatureProcessor.

◆ dprint()

void MultiFeatureProcessor::dprint	(	const string &	pref,
		int	fp_flag
	)

virtual

Reimplemented from FeatureProcessor.

◆ filter()

int MultiFeatureProcessor::filter ( unordered_set< string > & features )

virtual

Filter according to a subset of features.

Reimplemented from FeatureProcessor.

◆ get_feature_names()

void MultiFeatureProcessor::get_feature_names ( vector< string > & feature_names )

virtual

Reimplemented from FeatureProcessor.

◆ init()

int MultiFeatureProcessor::init ( map< string, string > & mapper )

virtual

The parsed fields from init command.

        if (field == "tag") tag = entry.second;
        if (field == "init_string") { init_string = entry.second;  has_init_str = true; }
        if (field == "members_type") { members_type = (FeatureProcessorTypes)med_stoi(entry.second); has_type = true; }
        if (field == "use_parallel_learn") use_parallel_learn = med_stoi(entry.second) > 0;
        if (field == "use_parallel_apply") use_parallel_apply = med_stoi(entry.second) > 0;

[MultiFeatureProcessor::init]

Reimplemented from FeatureProcessor.

◆ Learn()

int MultiFeatureProcessor::Learn	(	MedFeatures &	features,
		unordered_set< int > &	ids
	)

virtual

Reimplemented from FeatureProcessor.

◆ select_learn_matrix()

string MultiFeatureProcessor::select_learn_matrix ( const vector< string > & matrix_tags ) const

virtual

Will be called before learn to create new version for the matrix if needed - in parallel of existing matrix.

Reimplemented from FeatureProcessor.

◆ update_req_features_vec()

void MultiFeatureProcessor::update_req_features_vec	(	unordered_set< string > &	out_req_features,
		unordered_set< string > &	in_req_features
	)

virtual

update sets of required as input according to set required as output to processor

Reimplemented from FeatureProcessor.

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

Internal/MedProcessTools/MedProcessTools/FeatureProcess.h
Internal/MedProcessTools/MedProcessTools/FeatureProcess.cpp

Public Member Functions

Data Fields

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ _apply()

◆ _conditional_apply()

◆ are_features_affected()

◆ clear()

◆ copy()

◆ dprint()

◆ filter()

◆ get_feature_names()

◆ init()

◆ Learn()

◆ select_learn_matrix()

◆ update_req_features_vec()