10#include <framework/datastore/StoreArray.h>
11#include <framework/datastore/StoreObjPtr.h>
12#include <framework/dataobjects/EventMetaData.h>
13#include <framework/core/ModuleParam.templateDetails.h>
14#include <framework/gearbox/Unit.h>
15#include <framework/utilities/FileSystem.h>
16#include <analysis/utility/PCmsLabTransform.h>
17#include <trg/ecl/TrgEclMapping.h>
18#include <trg/ecl/dataobjects/TRGECLCluster.h>
19#include <trg/grl/dataobjects/GRLMLPData.h>
20#include <trg/grl/dataobjects/TRGGRLInfo.h>
21#include "trg/grl/dataobjects/TRGGRLUnpackerStore.h"
22#include "trg/grl/modules/trggrlneuralnet/GRLNeuroModule.h"
43 "The NeuroTrigger module of the GRL.\n"
44 "Takes CDC track and ECL cluster to prepare input data\n"
45 "for the training of a neural network.\n"
46 "Networks are trained after the event loop and saved."
51 "Name of the StoreArray holding the information of tracks and clusters from cdc ecl klm.",
52 string(
"TRGGRLObjects"));
54 "Name of the root file saving the output histogram.",
57 "Save the output histogram to root file.",
60 "Number of expert MLPs.", 1u);
62 "Number of expert CDC MLPs.", 0u);
64 "Number of expert ECL MLPs.", 1u);
66 "#cdc track of expert MLPs.", {0});
68 "#ecl cluster of expert MLPs.", {24});
70 "Number of nodes in each hidden layer for all networks "
71 "or factor to multiply with number of inputs (1 list or nMLP lists). "
72 "The number of layers is derived from the shape.",
74 addParam(
"multiplyHidden", m_parameters.multiplyHidden,
75 "If true, multiply nHidden with number of input nodes.",
false);
76 addParam(
"outputScale", m_parameters.outputScale,
77 "Output scale for all networks (1 value list or nMLP value lists). "
78 "Output[i] of the MLP is scaled from [-1, 1] "
79 "to [outputScale[2*i], outputScale[2*i+1]]. "
80 "(units: z[cm] / theta[degree])",
82 addParam(
"weightFiles", m_weightFileNames,
83 "Name of the file where the weights of MLPs are saved. "
84 "the default file is $BELLE2_LOCAL_DIR/data/trg/grl/weights.dat",
86 addParam(
"biasFiles", m_biasFileNames,
87 "Name of the file where the biases of MLPs are saved. "
88 "the default file is $BELLE2_LOCAL_DIR/data/trg/grl/bias.dat",
90 addParam(
"TRGECLClusters", m_TrgECLClusterName,
91 "Name of the StoreArray holding the information of trigger ecl clusters ",
92 string(
"TRGECLClusters"));
93 addParam(
"MVACut", m_nn_thres,
94 "Cut value applied to the MLP output",
96 addParam(
"useDB", m_useDB,
97 "Flag to use database to set config",
true);
106 for (
int tc = 1; tc <= 576; tc++) {
113 for (
int tc = 1; tc <= 576; tc++) {
116 ROOT::Math::XYZVector CellPosition = trgecl_obj->
getTCPosition(tc);
117 ROOT::Math::PxPyPzEVector CellLab;
118 CellLab.SetPx(CellPosition.Unit().X());
119 CellLab.SetPy(CellPosition.Unit().Y());
120 CellLab.SetPz(CellPosition.Unit().Z());
123 TCThetaLab.push_back(CellLab.Theta()*TMath::RadToDeg());
124 TCPhiLab.push_back(CellLab.Phi()*TMath::RadToDeg() + 180.0);
138 B2FATAL(
"No database for TRG GRL config. exp " << evtMetaData->getExperiment() <<
" run "
139 << evtMetaData->getRun());
152 for (
unsigned int isector = 0; isector <
m_parameters.nMLP; isector++) {
154 B2ERROR(
"weight of GRL ecltaunn could not be loaded correctly.");
161 for (
unsigned int isector = 0; isector <
m_parameters.nMLP; isector++) {
162 h_target.push_back(
new TH1D((
"h_target_" + to_string(isector)).c_str(),
163 (
"h_target_" + to_string(isector)).c_str(), 100, 0.0, 1.0));
178 std::vector<std::tuple<float, float, float, float>> eclClusters;
181 for (
int ic = 0; ic < necl; ic++) {
182 int TC = eclTrgClusterArray[ic]->getMaxTCId();
183 float energy = eclTrgClusterArray[ic]->getEnergyDep() * 1000.0;
186 float time = eclTrgClusterArray[ic]->getTimeAve();
187 eclClusters.emplace_back(energy, theta, phi, time);
190 std::sort(eclClusters.begin(), eclClusters.end(),
191 [](
const std::tuple<float, float, float, float>& a,
192 const std::tuple<float, float, float, float>& b) {
193 return std::get<0>(a) > std::get<0>(b);
197 std::vector<float> MLPinput;
199 MLPinput.assign(24, 0);
201 for (
size_t i = 0; i < std::min(eclClusters.size(),
size_t(6)); i++) {
202 MLPinput[i] = std::get<0>(eclClusters[i]);
203 MLPinput[6 + i] = std::get<1>(eclClusters[i]);
204 MLPinput[12 + i] = std::get<2>(eclClusters[i]);
205 MLPinput[18 + i] = std::get<3>(eclClusters[i]);
216 float LSB_ADC = 1 / 5.5;
217 float LSB_angle = 1 / 1.6025;
219 std::for_each(MLPinput.begin() + 0, MLPinput.begin() + 6, [LSB_ADC](
float & x) { x = std::ceil(x * LSB_ADC); });
220 std::for_each(MLPinput.begin() + 6, MLPinput.begin() + 12, [LSB_angle](
float & x) { x = std::ceil(x * LSB_angle);});
221 std::for_each(MLPinput.begin() + 12, MLPinput.begin() + 18, [LSB_angle](
float & x) { x = std::ceil(x * LSB_angle); });
232 float target =
m_GRLNeuro.runMLP(0, MLPinput);
237 trgInfo->setTauNN(
true);
238 }
else trgInfo->setTauNN(
false);
247 for (
unsigned int isector = 0; isector <
m_parameters.nMLP; isector++) {
static std::string findFile(const std::string &path, bool silent=false)
Search for given file or directory in local or central release directory, and return absolute path if...
std::vector< double > TCThetaLab
Polar angle of a given TRGcluster.
DBObjPtr< TRGGRLConfig > m_db_trggrlconfig
dbobject to store grl config
std::vector< double > TCPhiLab
Azimuthal angle of a given TRGcluster.
std::string m_HistFileName
Name of root file to save the histogram.
virtual void initialize() override
Initialize the module.
std::string m_TrgECLClusterName
Name of the StoreArray containing the ECL clusters.
std::vector< int > TCThetaID
TCID of a given TRGcluster.
GRLNeuro m_GRLNeuro
Instance of the NeuroTrigger.
virtual void event() override
Called once for each event.
GRLNeuro::Parameters m_parameters
Parameters for the NeuroTrigger.
GRLNeuroModule()
Constructor, for setting module description and parameters.
virtual void terminate() override
This method is called at the end of the event processing.
virtual void beginRun() override
Register run-dependent DataStore arrays.
std::string m_TrgGrlInformationName
name of TRG GRL information object
bool m_saveHist
save the output histogram
std::vector< float > m_nn_thres
cut on MVA to separate signal
std::vector< TH1D * > h_target
Histograms to save the NN classifiers.
bool m_useDB
flag to use database to load config
Class to represent the GRL Neuro.
void setDescription(const std::string &description)
Sets the description of the module.
void setPropertyFlags(unsigned int propertyFlags)
Sets the flags for the module properties.
@ c_ParallelProcessingCertified
This module can be run in parallel processing mode safely (All I/O must be done through the data stor...
Accessor to arrays stored in the data store.
int getEntries() const
Get the number of objects in the array.
Type-safe access to single objects in the data store.
int getTCThetaIdFromTCId(int)
get [TC Theta ID] from [TC ID]
ROOT::Math::XYZVector getTCPosition(int)
TC position (cm)
void addParam(const std::string &name, T ¶mVariable, const std::string &description, const T &defaultValue)
Adds a new parameter to the module.
#define REG_MODULE(moduleName)
Register the given module (without 'Module' suffix) with the framework.
Abstract base class for different kinds of events.