12 #include <framework/logging/Logger.h>
15 #include <mva/interface/Weightfile.h>
21 #include <TParameter.h>
24 #include <boost/algorithm/string/predicate.hpp>
27 #include <unordered_map>
55 for (
auto dimensionBinEdges : binEdges) {
56 m_nBins.push_back(dimensionBinEdges.size() - 1);
73 for (
unsigned int i = 0; i < binIndices.size(); i++) {
74 if (binIndices[i] < 0)
return -1;
76 globalBin = binIndices[i];
78 globalBin = globalBin *
m_nBins[i] + binIndices[i];
93 std::vector<int> binIndices(
m_binEdges.size());
95 for (
unsigned int i = 0; i <
m_binEdges.size(); i++) {
96 std::vector<float> dimBinEdges =
m_binEdges[i];
97 auto it = std::upper_bound(dimBinEdges.begin(), dimBinEdges.end(), values[i]);
98 if (it == dimBinEdges.end()) {
101 int index = std::distance(dimBinEdges.begin(), it) - 1;
102 binIndices[i] = index;
169 const std::unordered_map<unsigned int, unsigned int>& mvaIndexForHypothesis) :
177 if (boost::ends_with(weightfilePath,
".root")) {
179 }
else if (boost::ends_with(weightfilePath,
".xml")) {
182 B2WARNING(
"Unkown file extension for file: " << weightfilePath <<
", fallback to xml...");
185 std::stringstream ss;
214 const TF1*
getPDF(
const unsigned int iMVAResponse,
const unsigned int hypoPDG)
const
216 return &
m_pdfs.at(iMVAResponse).at(hypoPDG);
224 const TH1F*
getCDF(
const unsigned int iMVAResponse,
const int hypoPDG)
const
226 return &
m_cdfs.at(iMVAResponse).at(hypoPDG);
242 void setCDFs(std::vector<std::unordered_map<unsigned int, TH1F>> cdfs) {
m_cdfs = cdfs;}
249 void setPDFs(std::vector<std::unordered_map<unsigned int, TF1>>& pdfs) {
m_pdfs = pdfs;}
340 std::vector<std::unordered_map<unsigned int, TF1>>
m_pdfs;
353 std::vector<std::unordered_map<unsigned int, TH1F>>
m_cdfs;
395 void storeMVAWeights(std::unordered_map<unsigned int, ECLChargedPIDPhasespaceCategory>& phasespaceCategories)
418 if (linearBinIndex < 0)
return false;
432 B2FATAL(
"No N dimensional grid was found in the ECLChargedPIDMVA DB payload. This should not happen! Abort...");
Class to contain payload of everything needed for MVA based charged particle identification.
const ECLChargedPIDPhasespaceCategory * getPhasespaceCategory(const unsigned int idx) const
Returns the ith ECLChargedPIDPhasespaceCategory.
ECLChargedPIDMVAWeights()
Default constructor, necessary for ROOT to stream the object.
void setBinningVariables(std::vector< std::string > &binningVariables)
Set string definitions of the variables used in defining the phasespace categories.
const std::unordered_map< unsigned int, ECLChargedPIDPhasespaceCategory > * getPhasespaceCategories() const
Returns the map of phasespaceCategories.
std::vector< std::string > m_binningVariables
Stores the list of variables used to define the phasespace binning.
~ECLChargedPIDMVAWeights()
Destructor.
std::vector< std::string > getBinningVariables() const
Returns string definitions of the variables used in defining the phasespace categories.
bool isPhasespaceCovered(const int linearBinIndex) const
Returns bool whether or not the given values are within the phasespace covered by the trainings in th...
ECLChargedPIDPhasespaceBinning * m_categories
An N Dimensional binning whose bins define the boundaries of the categories for which the training is...
unsigned int getLinearisedCategoryIndex(std::vector< float > values) const
Returns the flattened 1D index of the N dimensional phasespace category grid.
void setWeightCategories(ECLChargedPIDPhasespaceBinning *h)
Set the N dimensional grid representing the categories for which weightfiles are defined.
ClassDef(ECLChargedPIDMVAWeights, 1)
ClassDef
std::unordered_map< unsigned int, ECLChargedPIDPhasespaceCategory > m_phasespaceCategories
Stores the ECLChargedPIDPhasespaceCategory object for all the N dimensional categories.
void storeMVAWeights(std::unordered_map< unsigned int, ECLChargedPIDPhasespaceCategory > &phasespaceCategories)
Store the ECLChargedPIDPhasespaceCategory objects into the payload.
Class to store the N dimensional phasespace binning of the MVA categorical training.
std::vector< int > m_nBins
Vector of number of bins per dimension.
std::vector< int > getBinIndices(const std::vector< float > values)
Maps the vector of input values to their bin index in N dimensions.
int getLinearisedBinIndex(const std::vector< float > values)
Maps the vector of input values to a global bin index.
std::vector< std::vector< float > > m_binEdges
Vector of bin edges.
ECLChargedPIDPhasespaceBinning()
Default Constructor.
ClassDef(ECLChargedPIDPhasespaceBinning, 1)
ClassDef.
~ECLChargedPIDPhasespaceBinning()
Destructor.
ECLChargedPIDPhasespaceBinning(const std::vector< std::vector< float >> binEdges)
Constructor.
Stores all required information for the ECLChargedPIDMVA for a phasespace category.
unsigned int getMVAIndexForHypothesis(const unsigned int hypoPDG) const
Maps a charged stable pdg code to an index of the MVA response.
MVAResponseTransformMode m_mvaResponseTransformMode
Stores which transformation mode to apply to the mva responses.
~ECLChargedPIDPhasespaceCategory()
Destructor.
const std::string getSerialisedWeight() const
Getter for serialised weightfile.
void setCDFs(std::vector< std::unordered_map< unsigned int, TH1F >> cdfs)
Set the cdfs.
TParameter< float > m_max_possible_response_value
Max possible value of the mva response.
const std::vector< float > * getDecorrelationMatrix(const int hypoPDG) const
Gets the decorrelation matrix for a given particle hypothesis.
void setMaxPossibleResponseValue(const float &offset)
Set the max possible response value, used in log transformation of the responses.
ECLChargedPIDPhasespaceCategory()
Default constructor, necessary for ROOT to stream the object.
std::vector< std::unordered_map< unsigned int, TH1F > > m_cdfs
CDFs for each mva return value for each hypothesis.
MVAResponseTransformMode getTransformMode() const
Getter for the MVA transform mode.
float getMaxPossibleResponseValue() const
Get the max possible response value, used in log transformation of the responses.
ClassDef(ECLChargedPIDPhasespaceCategory, 1)
ClassDef.
void setDecorrelationMatrixMap(std::unordered_map< unsigned int, std::vector< float >> decorrelationMatrices)
Set the decorrelation matrices.
std::unordered_map< unsigned int, std::vector< float > > m_decorrelationMatrices
Decorrelation matrices.
const TH1F * getCDF(const unsigned int iMVAResponse, const int hypoPDG) const
Gets the cdf for the hypothesis pdg for a given response value.
std::unordered_map< unsigned int, unsigned int > m_mvaIndexForHypothesis
Unordered map of abs(pdg_code) for the 6 charged stable hypotheses to index of the MVA response vecto...
void setTemperature(const float &temperature)
Set the temperature parameter used to calibrate the MVA.
void setPDFs(std::vector< std::unordered_map< unsigned int, TF1 >> &pdfs)
Set the pdfs.
ECLChargedPIDPhasespaceCategory(const std::string weightfilePath, const MVAResponseTransformMode &mvaResponeTransformMode, const std::unordered_map< unsigned int, unsigned int > &mvaIndexForHypothesis)
Useful constructor.
float getTemperature() const
Getter for the temperature.
TParameter< float > m_temperature
calibration factor for MVA responses.
std::vector< std::unordered_map< unsigned int, TF1 > > m_pdfs
A vector of unodered maps.
TParameter< float > m_log_transform_offset
Small offset to avoid mva response values of 1.0 being log transformed to NaN.
std::string m_weight
Serialsed MVA weightfile.
float getLogTransformOffset() const
Getter for the log transform offset.
MVAResponseTransformMode
Enum of implemented transformations which can be applied to the MVA response.
@ c_LogTransformSingle
Log transform the mva responses.
@ c_LogMVAResponse
Take the log of the MVA response.
@ c_DirectMVAResponse
Directly take the MVA response as the logL, useful if we train neural nets to learn the logL.
@ c_LogTransform
Log transform the mva responses.
@ c_DecorrelationTransform
Decorrelation transform of the gaussian transformed mva responses.
@ c_GaussianTransform
Gaussian transform of the log transformed mva response.
const TF1 * getPDF(const unsigned int iMVAResponse, const unsigned int hypoPDG) const
Getter for pdfs.
void setlogTransformOffset(const float &offset)
Set the offset used in the log transformation to be consistent with the offset used when generating t...
The Weightfile class serializes all information about a training into an xml tree.
static Weightfile loadFromXMLFile(const std::string &filename)
Static function which loads a Weightfile from a XML file.
static Weightfile loadFromROOTFile(const std::string &filename)
Static function which loads a Weightfile from a ROOT file.
static void saveToStream(Weightfile &weightfile, std::ostream &stream)
Static function which serializes a Weightfile to a stream.
Abstract base class for different kinds of events.