FANNExpert Class Reference

Expert for the FANN MVA method. More...

#include <FANN.h>

Inheritance diagram for FANNExpert:

Collaboration diagram for FANNExpert:

Public Member Functions
virtual	~FANNExpert ()
	Destructor of FANN Expert.
virtual void	load (Weightfile &weightfile) override
	Load the expert from a Weightfile.
virtual std::vector< float >	apply (Dataset &test_data) const override
	Apply this expert onto a dataset.
virtual std::vector< std::vector< float > >	applyMulticlass (Dataset &test_data) const
	Apply this m_expert onto a dataset.

Protected Attributes
GeneralOptions	m_general_options
	General options loaded from the weightfile.

Private Attributes
FANNOptions	m_specific_options
	Method specific options.
struct fann *	m_ann = nullptr
	Pointer to FANN expert.

Detailed Description

Expert for the FANN MVA method.

Definition at line 109 of file FANN.h.

Constructor & Destructor Documentation

~FANNExpert()

~FANNExpert ( )

virtual

Destructor of FANN Expert.

Definition at line 312 of file FANN.cc.

    {
      if (m_ann) {
        fann_destroy(m_ann);
      }
    }

Member Function Documentation

apply()

std::vector< float > apply ( Dataset &  test_data ) const

overridevirtual

Apply this expert onto a dataset.

Parameters

test_data

dataset

Implements Expert.

Definition at line 333 of file FANN.cc.

    {
 
      std::vector<fann_type> input(test_data.getNumberOfFeatures());
      std::vector<float> probabilities(test_data.getNumberOfEvents());
      for (unsigned int iEvent = 0; iEvent < test_data.getNumberOfEvents(); ++iEvent) {
        test_data.loadEvent(iEvent);
        for (unsigned int iFeature = 0; iFeature < test_data.getNumberOfFeatures(); ++iFeature) {
          input[iFeature] = test_data.m_input[iFeature];
        }
        if (m_specific_options.m_scale_features) fann_scale_input(m_ann, input.data());
        probabilities[iEvent] = fann_run(m_ann, input.data())[0];
      }
      if (m_specific_options.m_scale_target) fann_descale_output(m_ann, probabilities.data());
      return probabilities;
    }

applyMulticlass()

virtual std::vector< std::vector< float > > applyMulticlass ( Dataset &  test_data ) const

inlinevirtualinherited

Apply this m_expert onto a dataset.

Multiclass mode. Not pure virtual, since not all derived classes to re-implement this.

Parameters

test_data

dataset.

Returns

vector of size N=test_data.getNumberOfEvents() with N=m_classes.size() scores for each event in the dataset.

Reimplemented in PythonExpert, TMVAExpertMulticlass, and TrivialExpert.

Definition at line 56 of file Expert.h.

      {
 
        B2ERROR("Attempted to call applyMulticlass() of the abstract base class MVA::Expert. All methods that support multiclass classification should override this definition.");
        (void) test_data;
 
        return std::vector<std::vector<float>>();
      };

load()

void load ( Weightfile &  weightfile )

overridevirtual

Load the expert from a Weightfile.

Parameters

weightfile

containing all information necessary to build the expert

Implements Expert.

Definition at line 319 of file FANN.cc.

    {
 
      std::string custom_weightfile = weightfile.generateFileName();
      weightfile.getFile("FANN_Weightfile", custom_weightfile);
 
      if (m_ann) {
        fann_destroy(m_ann);
      }
      m_ann = fann_create_from_file(custom_weightfile.c_str());
 
      weightfile.getOptions(m_specific_options);
    }

Member Data Documentation

m_ann

struct fann* m_ann = nullptr

private

Pointer to FANN expert.

Definition at line 132 of file FANN.h.

m_general_options

GeneralOptions m_general_options

protectedinherited

General options loaded from the weightfile.

Definition at line 70 of file Expert.h.

m_specific_options

FANNOptions m_specific_options

private

Method specific options.

Definition at line 131 of file FANN.h.

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

• mva/methods/include/FANN.h
• mva/methods/src/FANN.cc