GRLMLPData Class Reference

Struct for training data of a single MLP for the neuro trigger. More...

#include <GRLMLPData.h>

Inheritance diagram for GRLMLPData:

Collaboration diagram for GRLMLPData:

Public Member Functions
	GRLMLPData ()
	default constructor.
	~GRLMLPData ()
	destructor, empty because we don't allocate memory anywhere.
void	addSample (const std::vector< float > &input, const std::vector< float > &target)
	add a pair of input and target
unsigned	getNumberOfSamples () const
	get number of samples (same for input and target)
const std::vector< float > &	getInput (unsigned i) const
	get input vector of sample i
const std::vector< float > &	getTarget (unsigned i) const
	get target value of sample i

Private Member Functions
	ClassDef (GRLMLPData, 1)
	Needed to make the ROOT object storable.

Private Attributes
std::vector< std::vector< float > >	m_inputSamples
	list of input vectors for network training.
std::vector< std::vector< float > >	m_targetSamples
	list of target values for network training.

Detailed Description

Struct for training data of a single MLP for the neuro trigger.

Definition at line 20 of file GRLMLPData.h.

Constructor & Destructor Documentation

GRLMLPData()

GRLMLPData ( )

inline

default constructor.

Definition at line 23 of file GRLMLPData.h.

: m_inputSamples(), m_targetSamples() { }

~GRLMLPData()

~GRLMLPData ( )

inline

destructor, empty because we don't allocate memory anywhere.

Definition at line 25 of file GRLMLPData.h.

{ }

Member Function Documentation

addSample()

void addSample ( const std::vector< float > &  input, const std::vector< float > &  target  )

inline

add a pair of input and target

Definition at line 28 of file GRLMLPData.h.

    {
      m_inputSamples.push_back(input);
      m_targetSamples.push_back(target);
    }

getInput()

const std::vector< float > & getInput ( unsigned  i ) const

inline

get input vector of sample i

Definition at line 37 of file GRLMLPData.h.

{ return m_inputSamples[i]; }

getNumberOfSamples()

unsigned getNumberOfSamples ( ) const

inline

get number of samples (same for input and target)

Definition at line 35 of file GRLMLPData.h.

{ return m_targetSamples.size(); }

getTarget()

const std::vector< float > & getTarget ( unsigned  i ) const

inline

get target value of sample i

Definition at line 39 of file GRLMLPData.h.

{ return m_targetSamples[i]; }

Member Data Documentation

m_inputSamples

std::vector<std::vector<float> > m_inputSamples

private

list of input vectors for network training.

Definition at line 43 of file GRLMLPData.h.

m_targetSamples

std::vector<std::vector<float> > m_targetSamples

private

list of target values for network training.

Definition at line 45 of file GRLMLPData.h.

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

• trg/grl/dataobjects/include/GRLMLPData.h