TMVAEvaluator.cc

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#include "CommonTools/MVAUtils/interface/GBRForestTools.h"
#include "CommonTools/MVAUtils/interface/TMVAEvaluator.h"
#include "CommonTools/MVAUtils/interface/TMVAZipReader.h"
 
#include "CondFormats/DataRecord/interface/GBRWrapperRcd.h"
#include "FWCore/Framework/interface/ESHandle.h"
#include "FWCore/MessageLogger/interface/MessageLogger.h"
 
TMVAEvaluator::TMVAEvaluator() : mIsInitialized(false), mUsingGBRForest(false), mUseAdaBoost(false) {}
 
void TMVAEvaluator::initialize(const std::string& options,
                               const std::string& method,
                               const std::string& weightFile,
                               const std::vector<std::string>& variables,
                               const std::vector<std::string>& spectators,
                               bool useGBRForest,
                               bool useAdaBoost) {
  // initialize the TMVA reader
  mReader.reset(new TMVA::Reader(options.c_str()));
  mReader->SetVerbose(false);
  mMethod = method;
 
  // add input variables
  for (std::vector<std::string>::const_iterator it = variables.begin(); it != variables.end(); ++it) {
    mVariables.insert(std::make_pair(*it, std::make_pair(it - variables.begin(), 0.)));
    mReader->AddVariable(it->c_str(), &(mVariables.at(*it).second));
  }
 
  // add spectator variables
  for (std::vector<std::string>::const_iterator it = spectators.begin(); it != spectators.end(); ++it) {
    mSpectators.insert(std::make_pair(*it, std::make_pair(it - spectators.begin(), 0.)));
    mReader->AddSpectator(it->c_str(), &(mSpectators.at(*it).second));
  }
 
  // load the TMVA weights
  reco::details::loadTMVAWeights(mReader.get(), mMethod, weightFile);
 
  if (useGBRForest) {
    mGBRForest = createGBRForest(weightFile);
 
    // now can free some memory
    mReader.reset(nullptr);
 
    mUsingGBRForest = true;
    mUseAdaBoost = useAdaBoost;
  }
 
  mIsInitialized = true;
}
 
void TMVAEvaluator::initializeGBRForest(const GBRForest* gbrForest,
                                        const std::vector<std::string>& variables,
                                        const std::vector<std::string>& spectators,
                                        bool useAdaBoost) {
  // add input variables
  for (std::vector<std::string>::const_iterator it = variables.begin(); it != variables.end(); ++it)
    mVariables.insert(std::make_pair(*it, std::make_pair(it - variables.begin(), 0.)));
 
  // add spectator variables
  for (std::vector<std::string>::const_iterator it = spectators.begin(); it != spectators.end(); ++it)
    mSpectators.insert(std::make_pair(*it, std::make_pair(it - spectators.begin(), 0.)));
 
  // do not take ownership if getting GBRForest from an external source
  mGBRForest = std::shared_ptr<const GBRForest>(gbrForest, [](const GBRForest*) {});
 
  mIsInitialized = true;
  mUsingGBRForest = true;
  mUseAdaBoost = useAdaBoost;
}
 
void TMVAEvaluator::initializeGBRForest(const edm::EventSetup& iSetup,
                                        const std::string& label,
                                        const std::vector<std::string>& variables,
                                        const std::vector<std::string>& spectators,
                                        bool useAdaBoost) {
  edm::ESHandle<GBRForest> gbrForestHandle;
 
  iSetup.get<GBRWrapperRcd>().get(label.c_str(), gbrForestHandle);
 
  initializeGBRForest(gbrForestHandle.product(), variables, spectators, useAdaBoost);
}
 
float TMVAEvaluator::evaluateTMVA(const std::map<std::string, float>& inputs, bool useSpectators) const {
  // default value
  float value = -99.;
 
  // TMVA::Reader is not thread safe
  std::lock_guard<std::mutex> lock(m_mutex);
 
  // set the input variable values
  for (auto it = mVariables.begin(); it != mVariables.end(); ++it) {
    if (inputs.count(it->first) > 0)
      it->second.second = inputs.at(it->first);
    else
      edm::LogError("MissingInputVariable")
          << "Input variable " << it->first
          << " is missing from the list of inputs. The returned discriminator value might not be sensible.";
  }
 
  // if using spectator variables
  if (useSpectators) {
    // set the spectator variable values
    for (auto it = mSpectators.begin(); it != mSpectators.end(); ++it) {
      if (inputs.count(it->first) > 0)
        it->second.second = inputs.at(it->first);
      else
        edm::LogError("MissingSpectatorVariable")
            << "Spectator variable " << it->first
            << " is missing from the list of inputs. The returned discriminator value might not be sensible.";
    }
  }
 
  // evaluate the MVA
  value = mReader->EvaluateMVA(mMethod.c_str());
 
  return value;
}
 
float TMVAEvaluator::evaluateGBRForest(const std::map<std::string, float>& inputs) const {
  // default value
  float value = -99.;
 
  std::unique_ptr<float[]> vars(new float[mVariables.size()]);  // allocate n floats
 
  // set the input variable values
  for (auto it = mVariables.begin(); it != mVariables.end(); ++it) {
    if (inputs.count(it->first) > 0)
      vars[it->second.first] = inputs.at(it->first);
    else
      edm::LogError("MissingInputVariable")
          << "Input variable " << it->first
          << " is missing from the list of inputs. The returned discriminator value might not be sensible.";
  }
 
  // evaluate the MVA
  if (mUseAdaBoost)
    value = mGBRForest->GetAdaBoostClassifier(vars.get());
  else
    value = mGBRForest->GetGradBoostClassifier(vars.get());
 
  return value;
}
 
float TMVAEvaluator::evaluate(const std::map<std::string, float>& inputs, bool useSpectators) const {
  // default value
  float value = -99.;
 
  if (!mIsInitialized) {
    edm::LogError("InitializationError") << "TMVAEvaluator not properly initialized.";
    return value;
  }
 
  if (useSpectators && inputs.size() < (mVariables.size() + mSpectators.size())) {
    edm::LogError("MissingInputs") << "Too few inputs provided (" << inputs.size() << " provided but "
                                   << mVariables.size() << " input and " << mSpectators.size()
                                   << " spectator variables expected).";
    return value;
  } else if (inputs.size() < mVariables.size()) {
    edm::LogError("MissingInputVariable(s)") << "Too few input variables provided (" << inputs.size()
                                             << " provided but " << mVariables.size() << " expected).";
    return value;
  }
 
  if (mUsingGBRForest) {
    if (useSpectators)
      edm::LogWarning("UnsupportedFunctionality")
          << "Use of spectator variables with GBRForest is not supported. Spectator variables will be ignored.";
    value = evaluateGBRForest(inputs);
  } else
    value = evaluateTMVA(inputs, useSpectators);
 
  return value;
}