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Belle II Software
release-05-02-19
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4 #include <trg/grl/dataobjects/GRLMLP.h>
5 #include <framework/datastore/StoreArray.h>
6 #include <framework/datastore/StoreObjPtr.h>
7 #include <framework/database/DBObjPtr.h>
54 std::vector<float> i_cdc_sector;
57 std::vector<float> i_ecl_sector;
73 void save(
const std::string& filename,
const std::string& arrayname =
"MLPs");
79 bool load(
const std::string& filename,
const std::string& arrayname =
"MLPs");
107 std::vector<float>
runMLP(
unsigned isector,
const std::vector<float>& input);
110 std::vector<float>
runMLPFix(
unsigned isector,
const std::vector<float>& input);
unsigned n_cdc_sector
Number of CDC sectors.
std::vector< GRLMLP > m_MLPs
List of networks.
bool targetresult
train result as output
std::vector< float > runMLP(unsigned isector, const std::vector< float > &input)
Run an expert MLP.
bool multiplyHidden
If true, multiply nHidden with number of input nodes.
Class to keep all parameters of an expert MLP for the neuro trigger.
Class to represent the GRL Neuro.
unsigned nSectors() const
return number of neural networks
unsigned n_ecl_sector
Number of ECL sectors.
std::vector< float > runMLPFix(unsigned isector, const std::vector< float > &input)
Run an expert MLP with fixed point arithmetic.
Struct to keep neurotrigger parameters.
const GRLMLP & operator[](unsigned index) const
return const reference to a neural network
unsigned nMLP
Number of networks.
void save(const std::string &filename, const std::string &arrayname="MLPs")
Save MLPs to file.
Abstract base class for different kinds of events.
virtual ~GRLNeuro()
Default destructor.
std::vector< std::vector< float > > outputScale
Output scale for all networks.
GRLMLP & operator[](unsigned index)
set the hit collection and event time to required and store the hit collection name
void setPrecision(const std::vector< unsigned > &precision)
Loads parameters from the geometry and precalculates some constants that will be needed.
bool load(const std::string &filename, const std::string &arrayname="MLPs")
Load MLPs from file.
GRLNeuro()
Default constructor.
void initialize(const Parameters &p)
Set parameters and get some network independent parameters.
void addMLP(const GRLMLP &newMLP)
add an MLP to the list of networks
std::vector< unsigned > m_precision
Fixed point precision in bit after radix point.
std::vector< std::vector< float > > nHidden
Number of nodes in each hidden layer for all networks or factor to multiply with number of inputs.