Inheritance diagram for NeuroTriggerParameters:

Collaboration diagram for NeuroTriggerParameters:

[legend]

Public Member Functions
	NeuroTriggerParameters (std::string &filename)

int	to_intTiming (const std::string &text) const

const std::string	to_strTiming (const unsigned &i) const

const std::string	et_option () const
	return the string variant ov the et option

void	loadconfigtxt (const std::string &filename)
	load the configuration from a file

void	saveconfigtxt (const std::string &filename)
	save the configuration to a file

template<typename X >
std::string	print2dArray (const std::string &name, std::vector< std::vector< NNTParam< X >>> vecvec)
	this is a class for piping the output of a 2d array to a string with brackets

template<typename X >
std::string	print1dArray (const std::string &name, std::vector< NNTParam< X >> vecvec)
	this is a class for piping the output of a 1d array to a string with brackets

template<typename X >
std::vector< std::vector< X > >	tcastvector (const std::vector< std::vector< NNTParam< X >>> vec) const
	the parameters stored in the parameterset are not advanced enough to be vectors, they can only be single data types. More...

template<typename X >
std::vector< X >	tcastvector (const std::vector< NNTParam< X >> vec) const

Public Attributes
NNTParam< unsigned >	nInput
	Network parameters. More...

NNTParam< unsigned >	nOutput
	number of output nodes

NNTParam< unsigned >	nMLP
	Number of networks. More...

NNTParam< bool >	targetZ
	train z as output

NNTParam< bool >	targetTheta
	train theta as output

NNTParam< bool >	multiplyHidden
	If true, multiply nHidden with number of input nodes.

NNTParam< unsigned >	tMax
	Maximal drift time, identical for all networks.

NNTParam< bool >	rescaleTarget
	flag to allow for target tracks lying out of the output range to be rescaled during training.

NNTParam< bool >	cutSum
	only used in the idhist module. More...

NNTParam< double >	relevantCut
	only used in the idhist module. More...

NNTParam< unsigned >	ETOption
	Determine, how the event time should be obtained. More...

std::vector< std::vector< NNTParam< float > > >	phiRangeUse
	Phi region for which MLP is used in degree for all networks.

std::vector< std::vector< NNTParam< float > > >	thetaRangeUse
	Theta region for which MLP is used in degree for all networks.

std::vector< std::vector< NNTParam< float > > >	invptRangeUse
	Charge / Pt region for which MLP is used in 1/GeV for all networks.

std::vector< std::vector< NNTParam< float > > >	phiRangeTrain
	Phi region for which MLP is trained in degree for all networks. More...

std::vector< std::vector< NNTParam< float > > >	thetaRangeTrain
	Theta region for which MLP is trained in degree for all networks. More...

std::vector< std::vector< NNTParam< float > > >	invptRangeTrain
	Charge / Pt region for which MLP is trained in 1/GeV for all networks. More...

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

std::vector< std::vector< NNTParam< float > > >	outputScale
	Output scale for all networks.

std::vector< NNTParam< unsigned short > >	maxHitsPerSL
	Maximum number of hits in a single super layer for all networks.

std::vector< NNTParam< unsigned long > >	SLpattern
	Super layer pattern for which MLP is trained for all networks. More...

std::vector< NNTParam< unsigned long > >	SLpatternMask
	Super layer pattern mask for which MLP is trained for all networks. More...

std::vector< NNTParam< unsigned > >	precision
	precision used for the hardware simulation

std::vector< std::vector< NNTParam< float > > >	IDRanges
	relative ID range of the relevant wire IDs of the track segments that are taken into consideration when determining the best fitting track segments.

Private Member Functions
template<typename X >
bool	checkarr (std::vector< std::vector< NNTParam< X >>> vec)
	check, if a vector is already set. More...

template<typename X >
bool	checkarr (std::vector< NNTParam< X >> vec)
	check, if a vector is already set. More...

template<typename X >
std::vector< std::vector< NNTParam< X > > >	read2dArray (std::string keyx, bool locked)
	fill the array from a given string that looks like: [[1,2],[3, 4]]

template<typename X >
std::vector< NNTParam< X > >	read1dArray (std::string keyx, bool locked)
	fill the array from a given string that looks like: [1,2,3]

Detailed Description

Definition at line 70 of file NeuroTriggerParameters.h.

Member Function Documentation

◆ checkarr() [1/2]

bool checkarr ( std::vector< NNTParam< X >> vec )

private

check, if a vector is already set.

this is done by just checking the first member of the vector.

Definition at line 147 of file NeuroTriggerParameters.cc.

 {
   // check, if a vector is already set. this is done by just checking the first member of the vector.
   if (vec.size() < 1) {return false;}
   else {return vec[0].isSet();}
 }

◆ checkarr() [2/2]

bool checkarr ( std::vector< std::vector< NNTParam< X >>> vec )

private

check, if a vector is already set.

this is done by just checking the first member of the vector.

Definition at line 138 of file NeuroTriggerParameters.cc.

◆ tcastvector()

std::vector<std::vector<X> > tcastvector ( const std::vector< std::vector< NNTParam< X >>> vec ) const

inline

the parameters stored in the parameterset are not advanced enough to be vectors, they can only be single data types.

the workaround was to make every variable contained in the (nested) vector an NNTParam. for the further use, those have to be converted to float vecors, which is done by the tcastvector function.

Definition at line 126 of file NeuroTriggerParameters.h.

Member Data Documentation

◆ cutSum

NNTParam<bool> cutSum

only used in the idhist module.

it defines wether to use a cutsum or not

Definition at line 173 of file NeuroTriggerParameters.h.

◆ ETOption

NNTParam<unsigned> ETOption

Determine, how the event time should be obtained.

The options are: fastestpriority fastest2d etf etf_or_fastestpriority etf_or_fastest2d etf_only etfcc etfhwin etfcc_or_fastestpriority min_etf_fastestpriority min_etfcc_fastestpriority

Definition at line 189 of file NeuroTriggerParameters.h.

◆ invptRangeTrain

std::vector<std::vector<NNTParam<float> > > invptRangeTrain

Charge / Pt region for which MLP is trained in 1/GeV for all networks.

Can be larger than use range to avoid edge effects.

Definition at line 205 of file NeuroTriggerParameters.h.

◆ nHidden

std::vector<std::vector<NNTParam<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 210 of file NeuroTriggerParameters.h.

◆ nInput

NNTParam<unsigned> nInput

Network parameters.

number of input nodes

Definition at line 153 of file NeuroTriggerParameters.h.

◆ nMLP

NNTParam<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 161 of file NeuroTriggerParameters.h.

◆ phiRangeTrain

std::vector<std::vector<NNTParam<float> > > phiRangeTrain

Phi region for which MLP is trained in degree for all networks.

Can be larger than use range to avoid edge effects.

Definition at line 199 of file NeuroTriggerParameters.h.

◆ relevantCut

NNTParam<double> relevantCut

only used in the idhist module.

it defines the how much of the idrange is cut off after making the histogram

Definition at line 175 of file NeuroTriggerParameters.h.

◆ SLpattern

std::vector<NNTParam<unsigned long> > SLpattern

Super layer pattern for which MLP is trained for all networks.

Binary pattern of 9 * maxHitsPerSL bits (on/off for each hit). 0 in bit : hits from super layer are not used. 1 in bit : hits from super layer are used. SLpattern = 0: use any hits present, don't check the pattern.

Definition at line 220 of file NeuroTriggerParameters.h.

◆ SLpatternMask

std::vector<NNTParam<unsigned long> > SLpatternMask

Super layer pattern mask for which MLP is trained for all networks.

Binary pattern of 9 * maxHitsPerSL bits (on/off for each hit). 0 in bit : super layer may or may not have a hit. 1 in bit : super layer

must have a hit if SLpattern bit = 1
must not have a hit if SLpattenr bit = 0

Definition at line 227 of file NeuroTriggerParameters.h.

◆ thetaRangeTrain

std::vector<std::vector<NNTParam<float> > > thetaRangeTrain

Theta region for which MLP is trained in degree for all networks.

Can be larger than use range to avoid edge effects.

Definition at line 202 of file NeuroTriggerParameters.h.

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

trg/cdc/include/NeuroTriggerParameters.h
trg/cdc/src/NeuroTriggerParameters.cc

Public Member Functions

Public Attributes

Private Member Functions

Detailed Description

Member Function Documentation

◆ checkarr() [1/2]

◆ checkarr() [2/2]

◆ tcastvector()

Member Data Documentation

◆ cutSum

◆ ETOption

◆ invptRangeTrain

◆ nHidden

◆ nInput

◆ nMLP

◆ phiRangeTrain

◆ relevantCut

◆ SLpattern

◆ SLpatternMask

◆ thetaRangeTrain