Struct to keep neurotrigger parameters. More...

#include <GRLNeuro.h>

Public Attributes
unsigned	nMLP
	Number of networks.

std::vector< std::vector< float > >	nHidden
	Number of nodes in each hidden layer for all networks or factor to multiply with number of inputs.

bool	targetresult = true
	train result as output

bool	multiplyHidden = false
	If true, multiply nHidden with number of input nodes.

std::vector< std::vector< float > >	outputScale = {{ -1., 1.}}
	Output scale for all networks.

unsigned	n_cdc_sector
	Number of CDC sectors.

std::vector< float >	i_cdc_sector

unsigned	n_ecl_sector
	Number of ECL sectors.

std::vector< float >	i_ecl_sector

Detailed Description

Struct to keep neurotrigger parameters.

Contains all information that is needed to initialize several expert MLPs (not including values determined during training).

Definition at line 41 of file GRLNeuro.h.

Member Data Documentation

◆ i_cdc_sector

std::vector<float> i_cdc_sector

Definition at line 62 of file GRLNeuro.h.

◆ i_ecl_sector

std::vector<float> i_ecl_sector

Definition at line 65 of file GRLNeuro.h.

◆ multiplyHidden

bool multiplyHidden = false

If true, multiply nHidden with number of input nodes.

Definition at line 56 of file GRLNeuro.h.

◆ n_cdc_sector

unsigned n_cdc_sector

Number of CDC sectors.

Definition at line 61 of file GRLNeuro.h.

◆ n_ecl_sector

unsigned n_ecl_sector

Number of ECL sectors.

Definition at line 64 of file GRLNeuro.h.

◆ nHidden

std::vector<std::vector<float> > nHidden

Number of nodes in each hidden layer for all networks or factor to multiply with number of inputs.

The number of layers is derived from the shape.

Definition at line 52 of file GRLNeuro.h.

◆ nMLP

unsigned nMLP

Number of networks.

For network specific parameters you can give either a list with values for each network, or a single value that will be used for all. The ranges are also valid if nPhi * nPt * nTheta * nPattern = nMLPs

Definition at line 47 of file GRLNeuro.h.

◆ outputScale

std::vector<std::vector<float> > outputScale = {{ -1., 1.}}

Output scale for all networks.

Definition at line 58 of file GRLNeuro.h.

◆ targetresult

bool targetresult = true

train result as output

Definition at line 54 of file GRLNeuro.h.

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

trg/grl/include/GRLNeuro.h

Public Attributes