Belle II Software  release-08-01-10
GRLNeuro.h
1 /**************************************************************************
2  * basf2 (Belle II Analysis Software Framework) *
3  * Author: The Belle II Collaboration *
4  * *
5  * See git log for contributors and copyright holders. *
6  * This file is licensed under LGPL-3.0, see LICENSE.md. *
7  **************************************************************************/
8 
9 #ifndef GRLNEURO_H
10 #define GRLNEURO_H
11 
12 #include <trg/grl/dataobjects/GRLMLP.h>
13 #include <framework/datastore/StoreArray.h>
14 #include <framework/datastore/StoreObjPtr.h>
15 #include <framework/database/DBObjPtr.h>
16 //#include <trg/cdc/dbobjects/CDCTriggerNeuroConfig.h>
17 //#include <framework/dataobjects/BinnedEventT0.h>
18 
19 namespace Belle2 {
35  class GRLNeuro {
36  public:
41  struct Parameters {
47  unsigned nMLP;
52  std::vector<std::vector<float>> nHidden;
54  bool targetresult = true;
56  bool multiplyHidden = false;
58  std::vector<std::vector<float>> outputScale = {{ -1., 1.}};
59 
61  unsigned n_cdc_sector;
62  std::vector<float> i_cdc_sector;
64  unsigned n_ecl_sector;
65  std::vector<float> i_ecl_sector;
66  };
67 
68 
69 
71  GRLNeuro() {}
72 
74  virtual ~GRLNeuro() {}
75 
77  void initialize(const Parameters& p);
79  //void initialize(const std::vector<float>& nodes);
80 
82  GRLMLP& operator[](unsigned index) { return m_MLPs[index]; }
84  const GRLMLP& operator[](unsigned index) const { return m_MLPs[index]; }
86  unsigned nSectors() const { return m_MLPs.size(); }
87 
89  float relu(float x);
90 
92  float float_to_fixed(float num, int m, int n);
93 
95  float mysigmiod(float num);
100  void save(const std::string& filename, const std::string& arrayname = "MLPs");
106  bool load(unsigned isector, const std::string& wfilename, const std::string& bfilename);
107 
112  float runMLP(unsigned isector, const std::vector<float>& input);
113 
114  private:
116  std::vector<GRLMLP> m_MLPs = {};
117 
118  };
120 }
121 #endif
Class to keep all parameters of an expert MLP for the neuro trigger.
Definition: GRLMLP.h:21
Class to represent the GRL Neuro.
Definition: GRLNeuro.h:35
void initialize(const Parameters &p)
Set parameters and get some network independent parameters.
Definition: GRLNeuro.cc:29
virtual ~GRLNeuro()
Default destructor.
Definition: GRLNeuro.h:74
bool load(unsigned isector, const std::string &wfilename, const std::string &bfilename)
Load MLPs from file.
Definition: GRLNeuro.cc:154
float mysigmiod(float num)
discrete sigmoid activation function (1024 bins)
Definition: GRLNeuro.cc:245
void save(const std::string &filename, const std::string &arrayname="MLPs")
Save MLPs to file.
float runMLP(unsigned isector, const std::vector< float > &input)
Run an expert MLP.
Definition: GRLNeuro.cc:87
GRLNeuro()
Default constructor.
Definition: GRLNeuro.h:71
const GRLMLP & operator[](unsigned index) const
return const reference to a neural network
Definition: GRLNeuro.h:84
std::vector< GRLMLP > m_MLPs
List of networks.
Definition: GRLNeuro.h:116
GRLMLP & operator[](unsigned index)
Set parameters and get some network independent parameters.
Definition: GRLNeuro.h:82
float relu(float x)
ReLu activation function.
Definition: GRLNeuro.cc:79
float float_to_fixed(float num, int m, int n)
change the percision of number, m = number of integer bits, n = number of decimal
Definition: GRLNeuro.cc:216
unsigned nSectors() const
return number of neural networks
Definition: GRLNeuro.h:86
Abstract base class for different kinds of events.
Struct to keep neurotrigger parameters.
Definition: GRLNeuro.h:41
std::vector< std::vector< float > > outputScale
Output scale for all networks.
Definition: GRLNeuro.h:58
bool multiplyHidden
If true, multiply nHidden with number of input nodes.
Definition: GRLNeuro.h:56
unsigned nMLP
Number of networks.
Definition: GRLNeuro.h:47
bool targetresult
train result as output
Definition: GRLNeuro.h:54
unsigned n_ecl_sector
Number of ECL sectors.
Definition: GRLNeuro.h:64
std::vector< std::vector< float > > nHidden
Number of nodes in each hidden layer for all networks or factor to multiply with number of inputs.
Definition: GRLNeuro.h:52
unsigned n_cdc_sector
Number of CDC sectors.
Definition: GRLNeuro.h:61