Belle II Software development
SingleDataset Class Reference

Wraps the data of a single event into a Dataset. More...

#include <Dataset.h>

Inheritance diagram for SingleDataset:
Dataset

Public Member Functions

 SingleDataset (const GeneralOptions &general_options, const std::vector< float > &input, float target=1.0, const std::vector< float > &spectators=std::vector< float >())
 Constructs a new SingleDataset.
 
virtual unsigned int getNumberOfFeatures () const override
 Returns the number of features in this dataset.
 
virtual unsigned int getNumberOfSpectators () const override
 Returns the number of features in this dataset.
 
virtual unsigned int getNumberOfEvents () const override
 Returns the number of events in this dataset which is always one.
 
virtual void loadEvent (unsigned int) override
 Does nothing in the case of a single dataset, because the only event is already loaded.
 
virtual std::vector< float > getFeature (unsigned int iFeature) override
 Returns all values (in this case only one) of one feature in a std::vector<float>
 
virtual std::vector< float > getSpectator (unsigned int iSpectator) override
 Returns all values (in this case only one) of one spectator in a std::vector<float>
 
virtual float getSignalFraction ()
 Returns the signal fraction of the whole sample.
 
virtual unsigned int getFeatureIndex (const std::string &feature)
 Return index of feature with the given name.
 
virtual unsigned int getSpectatorIndex (const std::string &spectator)
 Return index of spectator with the given name.
 
virtual std::vector< float > getWeights ()
 Returns all weights.
 
virtual std::vector< float > getTargets ()
 Returns all targets.
 
virtual std::vector< bool > getSignals ()
 Returns all is Signals.
 

Public Attributes

GeneralOptions m_general_options
 GeneralOptions passed to this dataset.
 
std::vector< float > m_input
 Contains all feature values of the currently loaded event.
 
std::vector< float > m_spectators
 Contains all spectators values of the currently loaded event.
 
float m_weight
 Contains the weight of the currently loaded event.
 
float m_target
 Contains the target value of the currently loaded event.
 
bool m_isSignal
 Defines if the currently loaded event is signal or background.
 

Detailed Description

Wraps the data of a single event into a Dataset.

Mostly useful if one wants to apply an Expert to a single feature vector

Definition at line 135 of file Dataset.h.

Constructor & Destructor Documentation

◆ SingleDataset()

SingleDataset ( const GeneralOptions general_options,
const std::vector< float > &  input,
float  target = 1.0,
const std::vector< float > &  spectators = std::vector<float>() 
)

Constructs a new SingleDataset.

Parameters
general_optionswhich defines e.g. number of variables
inputfeature values of the single event
spectatorsspectator values of the single event
targettarget value of the single event (defaults to 1, because often this is not known if one wants to apply an expert)

Definition at line 135 of file Dataset.cc.

136 : Dataset(general_options)
137 {
138 m_input = input;
139 m_spectators = spectators;
140 m_target = target;
141 m_weight = 1.0;
142 m_isSignal = std::lround(target) == m_general_options.m_signal_class;
143 }
std::vector< float > m_spectators
Contains all spectators values of the currently loaded event.
Definition: Dataset.h:124
GeneralOptions m_general_options
GeneralOptions passed to this dataset.
Definition: Dataset.h:122
std::vector< float > m_input
Contains all feature values of the currently loaded event.
Definition: Dataset.h:123
Dataset(const GeneralOptions &general_options)
Constructs a new dataset given the general options.
Definition: Dataset.cc:26
bool m_isSignal
Defines if the currently loaded event is signal or background.
Definition: Dataset.h:127
float m_weight
Contains the weight of the currently loaded event.
Definition: Dataset.h:125
float m_target
Contains the target value of the currently loaded event.
Definition: Dataset.h:126
int m_signal_class
Signal class which is used as signal in a classification problem.
Definition: Options.h:88

Member Function Documentation

◆ getFeature()

virtual std::vector< float > getFeature ( unsigned int  iFeature)
inlineoverridevirtual

Returns all values (in this case only one) of one feature in a std::vector<float>

Parameters
iFeaturethe position of the feature to return

Reimplemented from Dataset.

Definition at line 172 of file Dataset.h.

172{ return std::vector<float> {m_input[iFeature]}; }

◆ getFeatureIndex()

unsigned int getFeatureIndex ( const std::string &  feature)
virtualinherited

Return index of feature with the given name.

Parameters
featurename of the feature

Definition at line 50 of file Dataset.cc.

51 {
52
53 auto it = std::find(m_general_options.m_variables.begin(), m_general_options.m_variables.end(), feature);
54 if (it == m_general_options.m_variables.end()) {
55 B2ERROR("Unknown feature named " << feature);
56 return 0;
57 }
58 return std::distance(m_general_options.m_variables.begin(), it);
59
60 }
std::vector< std::string > m_variables
Vector of all variables (branch names) used in the training.
Definition: Options.h:86

◆ getNumberOfEvents()

virtual unsigned int getNumberOfEvents ( ) const
inlineoverridevirtual

Returns the number of events in this dataset which is always one.

Implements Dataset.

Definition at line 161 of file Dataset.h.

161{ return 1; }

◆ getNumberOfFeatures()

virtual unsigned int getNumberOfFeatures ( ) const
inlineoverridevirtual

Returns the number of features in this dataset.

Implements Dataset.

Definition at line 151 of file Dataset.h.

151{ return m_input.size(); }

◆ getNumberOfSpectators()

virtual unsigned int getNumberOfSpectators ( ) const
inlineoverridevirtual

Returns the number of features in this dataset.

Implements Dataset.

Definition at line 156 of file Dataset.h.

156{ return m_spectators.size(); }

◆ getSignalFraction()

float getSignalFraction ( )
virtualinherited

Returns the signal fraction of the whole sample.

Reimplemented in SPlotDataset.

Definition at line 35 of file Dataset.cc.

36 {
37
38 double signal_weight_sum = 0;
39 double weight_sum = 0;
40 for (unsigned int i = 0; i < getNumberOfEvents(); ++i) {
41 loadEvent(i);
42 weight_sum += m_weight;
43 if (m_isSignal)
44 signal_weight_sum += m_weight;
45 }
46 return signal_weight_sum / weight_sum;
47
48 }
virtual unsigned int getNumberOfEvents() const =0
Returns the number of events in this dataset.
virtual void loadEvent(unsigned int iEvent)=0
Load the event number iEvent.

◆ getSignals()

std::vector< bool > getSignals ( )
virtualinherited

Returns all is Signals.

Reimplemented in ReweightingDataset.

Definition at line 122 of file Dataset.cc.

123 {
124
125 std::vector<bool> result(getNumberOfEvents());
126 for (unsigned int iEvent = 0; iEvent < getNumberOfEvents(); ++iEvent) {
127 loadEvent(iEvent);
128 result[iEvent] = m_isSignal;
129 }
130 return result;
131
132 }

◆ getSpectator()

virtual std::vector< float > getSpectator ( unsigned int  iSpectator)
inlineoverridevirtual

Returns all values (in this case only one) of one spectator in a std::vector<float>

Parameters
iSpectatorthe position of the spectator to return

Reimplemented from Dataset.

Definition at line 178 of file Dataset.h.

178{ return std::vector<float> {m_spectators[iSpectator]}; }

◆ getSpectatorIndex()

unsigned int getSpectatorIndex ( const std::string &  spectator)
virtualinherited

Return index of spectator with the given name.

Parameters
spectatorname of the spectator

Definition at line 62 of file Dataset.cc.

63 {
64
65 auto it = std::find(m_general_options.m_spectators.begin(), m_general_options.m_spectators.end(), spectator);
66 if (it == m_general_options.m_spectators.end()) {
67 B2ERROR("Unknown spectator named " << spectator);
68 return 0;
69 }
70 return std::distance(m_general_options.m_spectators.begin(), it);
71
72 }
std::vector< std::string > m_spectators
Vector of all spectators (branch names) used in the training.
Definition: Options.h:87

◆ getTargets()

std::vector< float > getTargets ( )
virtualinherited

Returns all targets.

Reimplemented in RegressionDataSet, and ReweightingDataset.

Definition at line 110 of file Dataset.cc.

111 {
112
113 std::vector<float> result(getNumberOfEvents());
114 for (unsigned int iEvent = 0; iEvent < getNumberOfEvents(); ++iEvent) {
115 loadEvent(iEvent);
116 result[iEvent] = m_target;
117 }
118 return result;
119
120 }

◆ getWeights()

std::vector< float > getWeights ( )
virtualinherited

Returns all weights.

Reimplemented in ROOTDataset, RegressionDataSet, and ReweightingDataset.

Definition at line 98 of file Dataset.cc.

99 {
100
101 std::vector<float> result(getNumberOfEvents());
102 for (unsigned int iEvent = 0; iEvent < getNumberOfEvents(); ++iEvent) {
103 loadEvent(iEvent);
104 result[iEvent] = m_weight;
105 }
106 return result;
107
108 }

◆ loadEvent()

virtual void loadEvent ( unsigned int  )
inlineoverridevirtual

Does nothing in the case of a single dataset, because the only event is already loaded.

Implements Dataset.

Definition at line 166 of file Dataset.h.

166{ };

Member Data Documentation

◆ m_general_options

GeneralOptions m_general_options
inherited

GeneralOptions passed to this dataset.

Definition at line 122 of file Dataset.h.

◆ m_input

std::vector<float> m_input
inherited

Contains all feature values of the currently loaded event.

Definition at line 123 of file Dataset.h.

◆ m_isSignal

bool m_isSignal
inherited

Defines if the currently loaded event is signal or background.

Definition at line 127 of file Dataset.h.

◆ m_spectators

std::vector<float> m_spectators
inherited

Contains all spectators values of the currently loaded event.

Definition at line 124 of file Dataset.h.

◆ m_target

float m_target
inherited

Contains the target value of the currently loaded event.

Definition at line 126 of file Dataset.h.

◆ m_weight

float m_weight
inherited

Contains the weight of the currently loaded event.

Definition at line 125 of file Dataset.h.


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