This module compares tracks generated by some pattern recognition algorithm for PXD, SVD and CDC to ideal Monte Carlo tracks and performs a matching from the former to the underlying MCParticles. More...

#include <MCRecoTracksMatcherModule.h>

Inheritance diagram for MCRecoTracksMatcherModule:

Public Types
enum	EModulePropFlags { c_Input = 1 , c_Output = 2 , c_ParallelProcessingCertified = 4 , c_HistogramManager = 8 , c_InternalSerializer = 16 , c_TerminateInAllProcesses = 32 , c_DontCollectStatistics = 64 }
	Each module can be tagged with property flags, which indicate certain features of the module. More...

typedef ModuleCondition::EAfterConditionPath	EAfterConditionPath
	Forward the EAfterConditionPath definition from the ModuleCondition.

Public Member Functions
	MCRecoTracksMatcherModule ()
	Constructor setting up the parameter.

void	initialize () final
	Signal the beginning of the event processing.

void	event () final
	Process the event.

virtual std::vector< std::string >	getFileNames (bool outputFiles)
	Return a list of output filenames for this modules.

virtual void	beginRun ()
	Called when entering a new run.

virtual void	endRun ()
	This method is called if the current run ends.

virtual void	terminate ()
	This method is called at the end of the event processing.

const std::string &	getName () const
	Returns the name of the module.

const std::string &	getType () const
	Returns the type of the module (i.e.

const std::string &	getPackage () const
	Returns the package this module is in.

const std::string &	getDescription () const
	Returns the description of the module.

void	setName (const std::string &name)
	Set the name of the module.

void	setPropertyFlags (unsigned int propertyFlags)
	Sets the flags for the module properties.

LogConfig &	getLogConfig ()
	Returns the log system configuration.

void	setLogConfig (const LogConfig &logConfig)
	Set the log system configuration.

void	setLogLevel (int logLevel)
	Configure the log level.

void	setDebugLevel (int debugLevel)
	Configure the debug messaging level.

void	setAbortLevel (int abortLevel)
	Configure the abort log level.

void	setLogInfo (int logLevel, unsigned int logInfo)
	Configure the printed log information for the given level.

void	if_value (const std::string &expression, const std::shared_ptr< Path > &path, EAfterConditionPath afterConditionPath=EAfterConditionPath::c_End)
	Add a condition to the module.

void	if_false (const std::shared_ptr< Path > &path, EAfterConditionPath afterConditionPath=EAfterConditionPath::c_End)
	A simplified version to add a condition to the module.

void	if_true (const std::shared_ptr< Path > &path, EAfterConditionPath afterConditionPath=EAfterConditionPath::c_End)
	A simplified version to set the condition of the module.

bool	hasCondition () const
	Returns true if at least one condition was set for the module.

const ModuleCondition *	getCondition () const
	Return a pointer to the first condition (or nullptr, if none was set)

const std::vector< ModuleCondition > &	getAllConditions () const
	Return all set conditions for this module.

bool	evalCondition () const
	If at least one condition was set, it is evaluated and true returned if at least one condition returns true.

std::shared_ptr< Path >	getConditionPath () const
	Returns the path of the last true condition (if there is at least one, else reaturn a null pointer).

Module::EAfterConditionPath	getAfterConditionPath () const
	What to do after the conditional path is finished.

std::vector< std::shared_ptr< Path > >	getAllConditionPaths () const
	Return all condition paths currently set (no matter if the condition is true or not).

bool	hasProperties (unsigned int propertyFlags) const
	Returns true if all specified property flags are available in this module.

bool	hasUnsetForcedParams () const
	Returns true and prints error message if the module has unset parameters which the user has to set in the steering file.

const ModuleParamList &	getParamList () const
	Return module param list.

template<typename T >
ModuleParam< T > &	getParam (const std::string &name) const
	Returns a reference to a parameter.

bool	hasReturnValue () const
	Return true if this module has a valid return value set.

int	getReturnValue () const
	Return the return value set by this module.

std::shared_ptr< PathElement >	clone () const override
	Create an independent copy of this module.

std::shared_ptr< boost::python::list >	getParamInfoListPython () const
	Returns a python list of all parameters.

Static Public Member Functions
static void	exposePythonAPI ()
	Exposes methods of the Module class to Python.

Protected Member Functions
virtual void	def_initialize ()
	Wrappers to make the methods without "def_" prefix callable from Python.

virtual void	def_beginRun ()
	Wrapper method for the virtual function beginRun() that has the implementation to be used in a call from Python.

virtual void	def_event ()
	Wrapper method for the virtual function event() that has the implementation to be used in a call from Python.

virtual void	def_endRun ()
	This method can receive that the current run ends as a call from the Python side.

virtual void	def_terminate ()
	Wrapper method for the virtual function terminate() that has the implementation to be used in a call from Python.

void	setDescription (const std::string &description)
	Sets the description of the module.

void	setType (const std::string &type)
	Set the module type.

template<typename T >
void	addParam (const std::string &name, T &paramVariable, const std::string &description, const T &defaultValue)
	Adds a new parameter to the module.

template<typename T >
void	addParam (const std::string &name, T &paramVariable, const std::string &description)
	Adds a new enforced parameter to the module.

void	setReturnValue (int value)
	Sets the return value for this module as integer.

void	setReturnValue (bool value)
	Sets the return value for this module as bool.

void	setParamList (const ModuleParamList &params)
	Replace existing parameter list.

Private Types
using	NDF = int
	Descriptive type defintion for a number of degrees of freedom.

Private Member Functions
std::list< ModulePtr >	getModules () const override
	no submodules, return empty list

std::string	getPathString () const override
	return the module name.

void	setParamPython (const std::string &name, const boost::python::object &pyObj)
	Implements a method for setting boost::python objects.

void	setParamPythonDict (const boost::python::dict &dictionary)
	Implements a method for reading the parameter values from a boost::python dictionary.

Private Attributes
std::string	m_prRecoTracksStoreArrayName
	Parameter : Name of the RecoTracks StoreArray from pattern recognition.

std::string	m_mcRecoTracksStoreArrayName
	Parameter : Name of the RecoTracks StoreArray from MC track finding.

std::string	m_TracksStoreArrayName
	Parameter : Name of the Tracks StoreArray.

bool	m_usePXDHits
	Parameter : Switch whether PXDHits should be used in the matching.

bool	m_useSVDHits
	Parameter : Switch whether SVDHits should be used in the matching.

bool	m_useCDCHits
	Parameter : Switch whether CDCHits should be used in the matching.

bool	m_useOnlyAxialCDCHits
	Parameter : Switch whether only axial CDCHits should be used.

bool	m_useFittedTracks = true
	Use fitted tracks for matching.

double	m_minimalPurity
	Parameter : Minimal purity of a PRTrack to be considered matchable to a MCTrack.

double	m_minimalEfficiency
	Parameter : Minimal efficiency for a MCTrack to be considered matchable to a PRTrack.

StoreArray< MCParticle >	m_MCParticles
	StoreArray containing MCParticles.

StoreArray< RecoTrack >	m_PRRecoTracks
	StoreArray containing PR RecoTracks.

StoreArray< RecoTrack >	m_MCRecoTracks
	StoreArray containing MC RecoTracks.

StoreArray< PXDCluster >	m_PXDClusters
	StoreArray containing PXDClusters.

StoreArray< SVDCluster >	m_SVDClusters
	StoreArray containing SVDClusters.

StoreArray< CDCHit >	m_CDCHits
	StoreArray containing CDCHits.

bool	m_mcParticlesPresent = false
	Flag to indicated whether the Monte Carlo track are on the DataStore.

std::map< int, NDF >	m_ndf_by_detId = {{Const::PXD, 2}, {Const::SVD, 1}, {Const::CDC, 1}}
	Map storing the standard number degrees of freedom for a single hit by detector *‍/.

std::string	m_name
	The name of the module, saved as a string (user-modifiable)

std::string	m_type
	The type of the module, saved as a string.

std::string	m_package
	Package this module is found in (may be empty).

std::string	m_description
	The description of the module.

unsigned int	m_propertyFlags
	The properties of the module as bitwise or (with \|) of EModulePropFlags.

LogConfig	m_logConfig
	The log system configuration of the module.

ModuleParamList	m_moduleParamList
	List storing and managing all parameter of the module.

bool	m_hasReturnValue
	True, if the return value is set.

int	m_returnValue
	The return value.

std::vector< ModuleCondition >	m_conditions
	Module condition, only non-null if set.

Detailed Description

This module compares tracks generated by some pattern recognition algorithm for PXD, SVD and CDC to ideal Monte Carlo tracks and performs a matching from the former to the underlying MCParticles.

To achieve this it evaluates and saves the purities and efficiencies from the pattern recognition track to Monte-Carlo tracks, which can than also be used by a subsequent evaluation modules.

In order to match the tracks the module takes two StoreArrays of RecoTracks, which should be compared.

One of them contains RecoTracks composed by the patter recognition algorithm to be assessed. They are refered to as PRTracks.

The second StoreArray holds the reference tracks, which should ideally be reconstructed. These are refered to as MCTracks and should generally be composed by the MCTrackingModule. (Design note : We use the tracks composed by the MCTrackFinder as reference, because the mere definition of what a trackable particle and what the best achievable track is, lies within the implementation of the MCTrackFinder. If we did not use the tracks from the MCTrackFinder as input, it would mean a double implementation of great parts of that logic.)

If the pattern recognition only covers a part of the tracking detectors, the matching can be constrained to specific subdetectors by switching of the appropriate usePXDHits, useSVDHits or useCDCHits parameters.

As a result the module

creates a RelationArray from the PRTracks to the MCTracks, which will be called the purity relation,
creates a RelationArray from the MCTracks to the PRTracks, which will be called the efficiency relation,
assigns the McTrackId property of the PRTracks and
creates a RelationArray from the PRTracks to the MCParticles.

The RelationArray for purity and efficiency generally store only the single highest purity and the single highest efficiency for a given PRTrack, MCTrack respectivelly. However these values are stored with a minus sign if the PRTrack is a clone, or the MCTrack is merged into another PRTrack. The McTrackId is either set to the index of the MCParticle or to some negative value indicating the severity of the mismatch. (Classification details below).

Moreover, only PRTracks that exceed the minimal purity requirement and a minimal efficiency requirement will have their purity/efficiency stored and will take part in the matching. The minimal purity can be choosen by the minimalPurity parameter (default 2.0/3.0). The minimal efficiency can be choosen by the minimalEfficiency parameter (default 0.05).

Last but not least a RelationArray from matched PRTracks to MCParticles is build and the McTrackId property of the PRTrack is set to the StoreArray index of the MCParticle (similar as the MCTrackFinder does it for the MCTracks). By default clone tracks are also assigned to their MCParticle. This behaviour can be switched off by the relateClonesToMCParticles.

In the following a more detailed explaination is given for the matching and the classification of PRTracks and MCTracks.

The PRTracks can be classified into six categories:

UNDEFINED
- Status of the track before any real status has been set.
- If the track status is still UNDEFINED after matching, something went wrong.
MATCHED
- The highest efficiency PRTrack of the highest purity MCTrack to this PRTrack is the same as this PRTrack.
- In addition, the charge of the PRTrack and the one of the MCTrack are the same.
- This means the PRTrack contains a high contribution of only one MCTrack and is also the best of all PRTracks describing this MCTrack (including the charge).
- The McTrackId property of matched PRTrack is set to the MCTrackId property of the MCTrack, which is usually the index of the MCParticle in its corresponding StoreArray.
- Also the relation from PRTrack to MCParticle is added.
- The purity relation is setup from the PRTrack to the MCTrack with the (positive) purity as weight.
WRONG CHARGE
- The highest efficiency PRTrack of the highest purity MCTrack to this PRTrack is the same as this PRTrack.
- But, the charge of the PRTrack and the one of the MCTrack are NOT the same.
- This means the PRTrack contains a high contribution of only one MCTrack and is also the best of all PRTracks describing this MCTrack, but the charge is wrong.
- The McTrackId property of matched PRTrack is set to the MCTrackId property of the MCTrack, which is usually the index of the MCParticle in its corresponding StoreArray.
- Also the relation from PRTrack to MCParticle is added.
- The purity relation is setup from the PRTrack to the MCTrack with the (positive) purity as weight.
CLONE
- The highest purity MCTrack has a different highest efficiency PRTrack than this track.
- Anyway, the charge of the PRTrack and the one of the MCTrack are the same.
- This means the PRTrack contains high contributions of only one MCTrack but a different other PRTrack contains an even higher contribution to this MCTrack.
- Only if the relateClonesToMCParticles parameter is active The McTrackId property of cloned PRTracks is set to the MCTrackId property of the MCTrack. Else it will be set to -9.
- Also the relation from PRTrack to MCParticle is added, only if the relateClonesToMCParticles parameter is active.
- The purity relation is always setup from the PRTrack to the MCTrack with the negative purity as weight, to be able to distinguish them from the matched tracks.
CLONE WRONG CHARGE
- The highest purity MCTrack has a different highest efficiency PRTrack than this track.
- Moreover, the charge of the PRTrack and the one of the MCTrack are NOT the same.
- This means the PRTrack contains high contributions of only one MCTrack but a different other PRTrack contains an even higher contribution to this MCTrack.
- Only if the relateClonesToMCParticles parameter is active The McTrackId property of cloned PRTracks is set to the MCTrackId property of the MCTrack. Else it will be set to -9.
- Also the relation from PRTrack to MCParticle is added, only if the relateClonesToMCParticles parameter is active.
- The purity relation is always setup from the PRTrack to the MCTrack with the negative purity as weight, to be able to distinguish them from the matched tracks.
BACKGROUND
- The PRTrack contains mostly hits, which are not part of any MCTrack.
- This normally means, that this PRTracks is made of beam background hits.
- If one constrains the MCTracks in the MCTrackFinder to some specific particles, say the tag side, also all signal side tracks end up in this category (in case of reasonable tracking performance). In this case the background rate is somewhat less meaningful.
- For background tracks the McTrackId of the PRTrack is set to -99.
- No relation from the PRTrack to the MCParticle is inserted.
- PRTracks classified as background are not entered in the purity RelationArray.
GHOST
- The highest purity MCTrack to this PRTrack has a purity lower than the minimal purity given in the parameter minimalPurity or
- has an efficiency lower than the efficiency given in the parameter minimalEfficiency.
- This means that the PRTrack does not contain a significat number of a specific MCTrack nor can it considered only made of background.
- For ghost tracks the McTrackId of the RecoTracks is set to -999.
- No relation from the PRTrack to the MCParticle is inserted.
- PRTracks classified as ghost are not entered in the purity RelationArray.

MCTracks are classified into five categories:

UNDEFINED
- Status of the track before any real status has been set.
- If the track status is still UNDEFINED after matching, something went wrong.
MATCHED
- The highest purity MCTrack of the highest efficiency PRTrack of this MCTrack is the same as this MCTrack.
- In addition, the charge of the MCTrack and the one of the PRTrack are the same.
- This means the MCTrack is well described by a PRTrack and this PRTrack has only a significant contribution from this MCTrack.
- The efficiency relation is setup from the MCTrack to the PRTrack with the (positive) efficiency as weight.
WRONG CHARGE
- The highest purity MCTrack of the highest efficiency PRTrack of this MCTrack is the same as this MCTrack.
- But, the charge of the MCTrack and the one of the PRTrack are NOT the same.
- This means the MCTrack is well described by a PRTrack and this PRTrack has only a significant contribution from this MCTrack.
- The efficiency relation is setup from the MCTrack to the PRTrack with the (positive) efficiency as weight.
MERGED
- The highest purity MCTrack of the highest efficiency PRTrack of this MCTrack is not the same as this MCTrack.
- Anyway, the charge of this MCTrack and the one of the PRTrack are the same.
- This means this MCTrack is mostly contained in a PRTrack, which in turn however better describes a MCTrack different form this.
- The efficiency relation is setup from the MCTrack to the PRTrack with the negative efficiency as weight, to be able to distinguish them from the matched tracks.
MERGED WRONG CHARGE
- The highest purity MCTrack of the highest efficiency PRTrack of this MCTrack is not the same as this MCTrack.
- Moreover, the charge of this MCTrack and the one of the PRTrack are NOT the same.
- This means this MCTrack is mostly contained in a PRTrack, which in turn however better describes a MCTrack different form this.
- The efficiency relation is setup from the MCTrack to the PRTrack with the negative efficiency as weight, to be able to distinguish them from the matched tracks.
MISSING
- There is no highest efficiency PRTrack to this MCTrack, which also fullfills the minimal purity requirement.
- For this category no efficiency relation is inserted.

Definition at line 175 of file MCRecoTracksMatcherModule.h.

Member Typedef Documentation

◆ EAfterConditionPath

typedef ModuleCondition::EAfterConditionPath EAfterConditionPath

inherited

Forward the EAfterConditionPath definition from the ModuleCondition.

Definition at line 88 of file Module.h.

◆ NDF

using NDF = int

private

Descriptive type defintion for a number of degrees of freedom.

Definition at line 239 of file MCRecoTracksMatcherModule.h.

Member Enumeration Documentation

◆ EModulePropFlags

enum EModulePropFlags

inherited

Each module can be tagged with property flags, which indicate certain features of the module.

Enumerator
c_Input	This module is an input module (reads data).
c_Output	This module is an output module (writes data).
c_ParallelProcessingCertified	This module can be run in parallel processing mode safely (All I/O must be done through the data store, in particular, the module must not write any files.)
c_HistogramManager	This module is used to manage histograms accumulated by other modules.
c_InternalSerializer	This module is an internal serializer/deserializer for parallel processing.
c_TerminateInAllProcesses	When using parallel processing, call this module's terminate() function in all processes(). This will also ensure that there is exactly one process (single-core if no parallel modules found) or at least one input, one main and one output process.
c_DontCollectStatistics	No statistics is collected for this module.

Definition at line 77 of file Module.h.

                          {
      c_Input                       = 1,  
      c_Output                      = 2,  
      c_ParallelProcessingCertified = 4,  
      c_HistogramManager            = 8, 
      c_InternalSerializer          = 16,  
      c_TerminateInAllProcesses     = 32,  
      c_DontCollectStatistics       = 64,  
    };

Constructor & Destructor Documentation

◆ MCRecoTracksMatcherModule()

MCRecoTracksMatcherModule ( )

Constructor setting up the parameter.

Definition at line 131 of file MCRecoTracksMatcherModule.cc.

  : Module()
{
  setDescription("This module compares reconstructed tracks generated by some pattern recognition "
                 "algorithm for PXD, SVD and/or CDC to ideal Monte Carlo tracks and performs a "
                 "matching from the former to the underlying MCParticles.");
 
  setPropertyFlags(c_ParallelProcessingCertified);
 
  //Parameter definition
  // Inputs
  addParam("prRecoTracksStoreArrayName",
           m_prRecoTracksStoreArrayName,
           "Name of the collection containing the tracks as generate a patter recognition algorithm to be evaluated ",
           std::string(""));
 
  addParam("mcRecoTracksStoreArrayName",
           m_mcRecoTracksStoreArrayName,
           "Name of the collection containing the reference tracks as generate by a Monte-Carlo-Tracker (e.g. MCTrackFinder)",
           std::string("MCGFTrackCands"));
 
  addParam("TracksStoreArrayName",
           m_TracksStoreArrayName,
           "Name of the Tracks StoreArray to be used when checking fitted tracks.",
           std::string(""));
 
  // Hit content to be evaluated
  addParam("UsePXDHits",
           m_usePXDHits,
           "Set true if PXDHits or PXDClusters should be used in the matching in case they are present",
           true);
 
  addParam("UseSVDHits",
           m_useSVDHits,
           "Set true if SVDHits or SVDClusters should be used in the matching in case they are present",
           true);
 
  addParam("UseCDCHits",
           m_useCDCHits,
           "Set true if CDCHits should be used in the matching in case they are present",
           true);
 
  addParam("UseOnlyAxialCDCHits",
           m_useOnlyAxialCDCHits,
           "Set true if only the axial CDCHits should be used",
           false);
 
  addParam("MinimalPurity",
           m_minimalPurity,
           "Minimal purity of a PRTrack to be considered matchable to a MCTrack. "
           "This number encodes how many correct hits are minimally need to compensate for a false hits. "
           "The default 2.0 / 3.0 suggests that for each background hit can be compensated by two correct hits.",
           2.0 / 3.0);
 
  addParam("MinimalEfficiency",
           m_minimalEfficiency,
           "Minimal efficiency of a MCTrack to be considered matchable to a PRTrack. "
           "This number encodes which fraction of the true hits must at least be in the reconstructed track. "
           "The default 0.05 suggests that at least 5% of the true hits should have been picked up.",
           0.05);
 
  addParam("useFittedTracks",
           m_useFittedTracks,
           "If true, it uses fitted tracks for matching. Note that the charge of the track can be different from\
           the seed charge (that is provided by the pattern recognition) since the DAF can flip tracks.",
           m_useFittedTracks);
}

Member Function Documentation

◆ beginRun()

virtual void beginRun ( void )

inlinevirtualinherited

Called when entering a new run.

Called at the beginning of each run, the method gives you the chance to change run dependent constants like alignment parameters, etc.

This method can be implemented by subclasses.

Definition at line 147 of file Module.h.

147{};

◆ clone()

std::shared_ptr< PathElement > clone ( ) const

overridevirtualinherited

Create an independent copy of this module.

Note that parameters are shared, so changing them on a cloned module will also affect the original module.

Implements PathElement.

Definition at line 179 of file Module.cc.

{
  ModulePtr newModule = ModuleManager::Instance().registerModule(getType());
  newModule->m_moduleParamList.setParameters(getParamList());
  newModule->setName(getName());
  newModule->m_package = m_package;
  newModule->m_propertyFlags = m_propertyFlags;
  newModule->m_logConfig = m_logConfig;
  newModule->m_conditions = m_conditions;
 
  return newModule;
}

◆ def_beginRun()

virtual void def_beginRun ( )

inlineprotectedvirtualinherited

Wrapper method for the virtual function beginRun() that has the implementation to be used in a call from Python.

Reimplemented in PyModule.

Definition at line 426 of file Module.h.

426{ beginRun(); }

Belle2::Module::beginRun

virtual void beginRun()

Called when entering a new run.

Definition: Module.h:147

◆ def_endRun()

virtual void def_endRun ( )

inlineprotectedvirtualinherited

This method can receive that the current run ends as a call from the Python side.

For regular C++-Modules that forwards the call to the regular endRun() method.

Reimplemented in PyModule.

Definition at line 439 of file Module.h.

439{ endRun(); }

Belle2::Module::endRun

virtual void endRun()

This method is called if the current run ends.

Definition: Module.h:166

◆ def_event()

virtual void def_event ( )

inlineprotectedvirtualinherited

Wrapper method for the virtual function event() that has the implementation to be used in a call from Python.

Reimplemented in PyModule.

Definition at line 432 of file Module.h.

432{ event(); }

Belle2::Module::event

virtual void event()

This method is the core of the module.

Definition: Module.h:157

◆ def_initialize()

virtual void def_initialize ( )

inlineprotectedvirtualinherited

Wrappers to make the methods without "def_" prefix callable from Python.

Overridden in PyModule. Wrapper method for the virtual function initialize() that has the implementation to be used in a call from Python.

Reimplemented in PyModule.

Definition at line 420 of file Module.h.

420{ initialize(); }

Belle2::Module::initialize

virtual void initialize()

Initialize the Module.

Definition: Module.h:109

◆ def_terminate()

virtual void def_terminate ( )

inlineprotectedvirtualinherited

Wrapper method for the virtual function terminate() that has the implementation to be used in a call from Python.

Reimplemented in PyModule.

Definition at line 445 of file Module.h.

445{ terminate(); }

Belle2::Module::terminate

virtual void terminate()

This method is called at the end of the event processing.

Definition: Module.h:176

◆ endRun()

virtual void endRun ( void )

inlinevirtualinherited

This method is called if the current run ends.

Use this method to store information, which should be aggregated over one run.

This method can be implemented by subclasses.

Definition at line 166 of file Module.h.

166{};

◆ evalCondition()

bool evalCondition ( ) const

inherited

If at least one condition was set, it is evaluated and true returned if at least one condition returns true.

If no condition or result value was defined, the method returns false. Otherwise, the condition is evaluated and true returned, if at least one condition returns true. To speed up the evaluation, the condition strings were already parsed in the method if_value().

Returns: True if at least one condition and return value exists and at least one condition expression was evaluated to true.

Definition at line 96 of file Module.cc.

{
  if (m_conditions.empty()) return false;
 
  //okay, a condition was set for this Module...
  if (!m_hasReturnValue) {
    B2FATAL("A condition was set for '" << getName() << "', but the module did not set a return value!");
  }
 
  for (const auto& condition : m_conditions) {
    if (condition.evaluate(m_returnValue)) {
      return true;
    }
  }
  return false;
}

◆ event()

void event ( void )

finalvirtual

Process the event.

Reimplemented from Module.

Definition at line 240 of file MCRecoTracksMatcherModule.cc.

{
  // Skip in the case there are no MC particles present.
  if (not m_mcParticlesPresent) {
    B2DEBUG(23, "Skipping MC Track Matcher as there are no MC Particles registered in the DataStore.");
    return;
  }
 
  B2DEBUG(23, "########## MCRecoTracksMatcherModule ############");
 
  int nMCRecoTracks = m_MCRecoTracks.getEntries();
  int nPRRecoTracks = m_PRRecoTracks.getEntries();
 
  B2DEBUG(23, "Number patter recognition tracks is " << nPRRecoTracks);
  B2DEBUG(23, "Number Monte-Carlo tracks is " << nMCRecoTracks);
 
  if (not nMCRecoTracks or not nPRRecoTracks) {
    // Neither no pattern recognition tracks
    // or no Monte Carlo tracks are present in this event
    // Cannot perform matching.
    return;
  }
 
  // ### Build a detector_id hit_id to reco track map for easier lookup later ###
  std::multimap<DetHitIdPair, WeightedRecoTrackId > mcId_by_hitId;
  fillIDsFromStoreArray(mcId_by_hitId, m_MCRecoTracks);
 
  //  Use set instead of multimap to handel to following situation
  //  * One hit may be assigned to multiple tracks should contribute to the efficiency of both tracks
  //  * One hit assigned twice or more to the same track should not contribute to the purity multiple times
  //  The first part is handled well by the multimap. But to enforce that one hit is also only assigned
  //  once to a track we use a set.
  std::set<std::pair<DetHitIdPair, WeightedRecoTrackId>> prId_by_hitId;
  fillIDsFromStoreArray(prId_by_hitId, m_PRRecoTracks);
 
  // ### Get the number of relevant hits for each detector ###
  // Since we are mostly dealing with indices in this module, this is all we need from the StoreArray
  // Silently skip store arrays that are not present in reduced detector setups.
  std::map<DetId, int> nHits_by_detId;
 
  // PXD
  if (m_usePXDHits) {
    nHits_by_detId[Const::PXD] = m_PXDClusters.getEntries();
  }
 
  // SVD
  if (m_useSVDHits) {
    nHits_by_detId[Const::SVD] = m_SVDClusters.getEntries();
  }
 
  // CDC
  if (m_useCDCHits) {
    nHits_by_detId[Const::CDC] = m_CDCHits.getEntries();
  }
 
  //### Build the confusion matrix ###
 
  // Reserve enough space for the confusion matrix
  // The last row is meant for hits not assigned to a mcRecoTrack (aka background hits)
  Eigen::MatrixXd confusionMatrix = Eigen::MatrixXd::Zero(nPRRecoTracks, nMCRecoTracks + 1);
  Eigen::MatrixXd weightedConfusionMatrix = Eigen::MatrixXd::Zero(nPRRecoTracks, nMCRecoTracks + 1);
 
  // Accumulated the total number of hits/ndf for each Monte-Carlo track separately to avoid double counting,
  // in case patter recognition tracks share hits.
  Eigen::RowVectorXd totalNDF_by_mcId = Eigen::RowVectorXd::Zero(nMCRecoTracks + 1);
  Eigen::RowVectorXd totalWeight_by_mcId = Eigen::RowVectorXd::Zero(nMCRecoTracks + 1);
 
  // Accumulated the total number of hits/ndf for each pattern recognition track separately to avoid double counting,
  // in case Monte-Carlo tracks share hits.
  Eigen::VectorXd totalNDF_by_prId = Eigen::VectorXd::Zero(nPRRecoTracks);
 
  // Column index for the hits not assigned to any MCRecoTrack
  const int mcBkgId = nMCRecoTracks;
 
  // for each detector examine every hit to which mcRecoTrack and prRecoTrack it belongs
  // if the hit is not part of any mcRecoTrack put the hit in the background column.
  for (const std::pair<const DetId, NDF>& detId_nHits_pair : nHits_by_detId) {
 
    DetId detId = detId_nHits_pair.first;
    int nHits = detId_nHits_pair.second;
    NDF ndfForOneHit = m_ndf_by_detId[detId];
 
    for (HitId hitId = 0; hitId < nHits; ++hitId) {
      DetHitIdPair detId_hitId_pair(detId, hitId);
 
      if (m_useOnlyAxialCDCHits and detId == Const::CDC) {
        StoreArray<CDCHit> cdcHits;
        const CDCHit* cdcHit = cdcHits[hitId];
        if (cdcHit->getISuperLayer() % 2 != 0) {
          // Skip stereo hits
          continue;
        }
      }
 
      // Seek all Monte Carlo tracks with the given hit
      const auto mcIds_for_detId_hitId_pair =
        as_range(mcId_by_hitId.equal_range(detId_hitId_pair));
 
      // Seek all pattern recognition tracks with the given hit
      const auto prIds_for_detId_hitId_pair =
        as_range(std::equal_range(prId_by_hitId.begin(),
                                  prId_by_hitId.end(),
                                  detId_hitId_pair,
                                  CompDetHitIdPair()));
 
      // Assign the hits/ndf to the total ndf vector separately to avoid double counting,
      // if patter recognition track share hits.
      if (mcIds_for_detId_hitId_pair.empty()) {
        // If the hit is not assigned to any mcRecoTrack
        // The hit is assigned to the background column
        RecoTrackId mcId = mcBkgId;
        double mcWeight = 1;
        totalNDF_by_mcId(mcId) += ndfForOneHit;
        totalWeight_by_mcId(mcId) += ndfForOneHit * mcWeight;
      } else {
        for (const auto& detId_hitId_pair_and_mcId : mcIds_for_detId_hitId_pair) {
          int mcId = detId_hitId_pair_and_mcId.second;
          double mcWeight = detId_hitId_pair_and_mcId.second.weight;
          totalNDF_by_mcId(mcId) += ndfForOneHit;
          totalWeight_by_mcId(mcId) += ndfForOneHit * mcWeight;
        }
      }
 
      // Assign the hits/ndf to the total ndf vector separately here to avoid double counting,
      // if Monte-Carlo track share hits.
      for (const auto& detId_hitId_pair_and_prId : prIds_for_detId_hitId_pair) {
        RecoTrackId prId = detId_hitId_pair_and_prId.second;
        totalNDF_by_prId(prId) += ndfForOneHit;
      }
 
      // Fill the confusion matrix
      for (const auto& detId_hitId_pair_and_prId : prIds_for_detId_hitId_pair) {
        int prId = detId_hitId_pair_and_prId.second;
        if (mcIds_for_detId_hitId_pair.empty()) {
          int mcId = mcBkgId;
          double mcWeight = 1;
          confusionMatrix(prId, mcId) += ndfForOneHit;
          weightedConfusionMatrix(prId, mcId) += ndfForOneHit * mcWeight;
        } else {
          for (const auto& detId_hitId_pair_and_mcId : mcIds_for_detId_hitId_pair) {
            int mcId = detId_hitId_pair_and_mcId.second;
            double mcWeight = detId_hitId_pair_and_mcId.second.weight;
            confusionMatrix(prId, mcId) += ndfForOneHit;
            weightedConfusionMatrix(prId, mcId) += ndfForOneHit * mcWeight;
          }
        }
      } // end for
    } // end for hitId
  } // end for detId
 
  B2DEBUG(24, "Confusion matrix of the event : " << std::endl <<  confusionMatrix);
  B2DEBUG(24, "Weighted confusion matrix of the event : " << std::endl <<  weightedConfusionMatrix);
 
  B2DEBUG(24, "totalNDF_by_mcId : " << std::endl << totalNDF_by_mcId);
  B2DEBUG(24, "totalWeight_by_mcId : " << std::endl << totalWeight_by_mcId);
 
  B2DEBUG(24, "totalNDF_by_prId : " << std::endl << totalNDF_by_prId);
 
  Eigen::MatrixXd purityMatrix = confusionMatrix.array().colwise() / totalNDF_by_prId.array();
  Eigen::MatrixXd efficiencyMatrix = confusionMatrix.array().rowwise() / totalNDF_by_mcId.array();
  Eigen::MatrixXd weightedEfficiencyMatrix = weightedConfusionMatrix.array().rowwise() / totalWeight_by_mcId.array();
 
  B2DEBUG(23, "Purities");
  B2DEBUG(23, purityMatrix);
 
  B2DEBUG(23, "Efficiencies");
  B2DEBUG(23, efficiencyMatrix);
 
  B2DEBUG(23, "Weighted efficiencies");
  B2DEBUG(23, weightedEfficiencyMatrix);
 
  // ### Building the Monte-Carlo track to highest efficiency patter recognition track relation ###
  // Weighted efficiency
  using Efficiency = float;
  using Purity = float;
 
  struct MostWeightEfficientPRId {
    RecoTrackId id;
    Efficiency weightedEfficiency;
    // cppcheck-suppress unusedStructMember
    Efficiency efficiency;
  };
  std::vector<MostWeightEfficientPRId> mostWeightEfficientPRId_by_mcId(nMCRecoTracks);
  for (RecoTrackId mcId = 0; mcId < nMCRecoTracks; ++mcId) {
    Eigen::VectorXd efficiencyCol = efficiencyMatrix.col(mcId);
    Eigen::VectorXd weightedEfficiencyCol = weightedEfficiencyMatrix.col(mcId);
 
    RecoTrackId bestPrId = 0;
    Efficiency bestWeightedEfficiency = weightedEfficiencyCol(0);
    Efficiency bestEfficiency = efficiencyCol(0);
    Purity bestPurity = purityMatrix.row(0)(mcId);
 
    // Reject efficiency smaller than the minimal one
    if (bestWeightedEfficiency < m_minimalEfficiency) {
      bestWeightedEfficiency = 0;
    }
 
    // In case of a tie in the weighted efficiency we use the regular efficiency to break it.
    for (RecoTrackId prId = 1; prId < nPRRecoTracks; ++prId) {
      Eigen::RowVectorXd purityRow = purityMatrix.row(prId);
 
      Efficiency currentWeightedEfficiency = weightedEfficiencyCol(prId);
      Efficiency currentEfficiency = efficiencyCol(prId);
      Purity currentPurity = purityRow(mcId);
 
      // Reject efficiency smaller than the minimal one
      if (currentWeightedEfficiency < m_minimalEfficiency) {
        currentWeightedEfficiency = 0;
      }
 
      if (std::tie(currentWeightedEfficiency, currentEfficiency, currentPurity) >
          std::tie(bestWeightedEfficiency, bestEfficiency, bestPurity)) {
        bestPrId = prId;
        bestEfficiency = currentEfficiency;
        bestWeightedEfficiency = currentWeightedEfficiency;
        bestPurity = currentPurity;
      }
    }
 
    bestWeightedEfficiency = weightedEfficiencyCol(bestPrId);
    bestEfficiency = efficiencyCol(bestPrId);
    mostWeightEfficientPRId_by_mcId[mcId] = {bestPrId, bestWeightedEfficiency, bestEfficiency};
  }
 
  // ### Building the patter recognition track to highest purity Monte-Carlo track relation ###
  // Unweighted purity
  struct MostPureMCId {
    RecoTrackId id;
    Purity purity;
  };
 
  std::vector<MostPureMCId> mostPureMCId_by_prId(nPRRecoTracks);
  for (int prId = 0; prId < nPRRecoTracks; ++prId) {
    Eigen::RowVectorXd purityRow = purityMatrix.row(prId);
 
    int mcId;
    Purity highestPurity = purityRow.maxCoeff(&mcId);
 
    mostPureMCId_by_prId[prId] = {mcId, highestPurity};
  }
 
  // Log the  Monte-Carlo track to highest efficiency patter recognition track relation
  // Weighted efficiency
  {
    RecoTrackId mcId = -1;
    B2DEBUG(24, "MCTrack to highest weighted efficiency PRTrack relation");
    for (const auto& mostWeightEfficientPRId_for_mcId : mostWeightEfficientPRId_by_mcId) {
      ++mcId;
      const Efficiency& weightedEfficiency = mostWeightEfficientPRId_for_mcId.weightedEfficiency;
      const RecoTrackId& prId = mostWeightEfficientPRId_for_mcId.id;
      B2DEBUG(24,
              "mcId : " << mcId << " ->  prId : " << prId << " with weighted efficiency "
              << weightedEfficiency);
    }
  }
 
  // Log the patter recognition track to highest purity Monte-Carlo track relation
  // Unweighted purity
  {
    RecoTrackId prId = -1;
    B2DEBUG(24, "PRTrack to highest purity MCTrack relation");
    for (const auto& mostPureMCId_for_prId : mostPureMCId_by_prId) {
      ++prId;
      const RecoTrackId& mcId = mostPureMCId_for_prId.id;
      const Purity& purity = mostPureMCId_for_prId.purity;
      B2DEBUG(24, "prId : " << prId << " ->  mcId : " << mcId << " with purity " << purity);
    }
  }
 
  // Count the categories
  int nMatched{}, nWrongCharge{}, nBackground{}, nClones{}, nClonesWrongCharge{}, nGhost{};
 
  // ### Classify the patter recognition tracks ###
  // Means saving the highest purity relation to the data store
  // + setup the PRTrack to MCParticle relation
  // + save the set the MatchingStatus
  for (RecoTrackId prId = 0; prId < nPRRecoTracks; ++prId) {
    RecoTrack* prRecoTrack = m_PRRecoTracks[prId];
 
    const MostPureMCId& mostPureMCId = mostPureMCId_by_prId[prId];
 
    const RecoTrackId& mcId = mostPureMCId.id;
    const Purity& purity = mostPureMCId.purity;
 
    // GHOST
    if (not(purity > 0) or not(purity >= m_minimalPurity)) {
      prRecoTrack->setMatchingStatus(RecoTrack::MatchingStatus::c_ghost);
 
      B2DEBUG(23, "Stored PRTrack " << prId << " as ghost because of too low purity");
      ++nGhost;
      continue;
    }
 
    // BACKGROUND
    if (mcId == mcBkgId) {
      prRecoTrack->setMatchingStatus(RecoTrack::MatchingStatus::c_background);
 
      B2DEBUG(23, "Stored PRTrack " << prId << " as background because of too low purity.");
      ++nBackground;
      continue;
    }
 
    // After the classification for bad purity and background we examine,
    // whether the highest purity Monte-Carlo track has in turn the highest efficiency
    // patter recognition track equal to this track.
    // All extra patter recognition tracks are marked as clones.
 
    RecoTrack* mcRecoTrack = m_MCRecoTracks[mcId];
    MCParticle* mcParticle = mcRecoTrack->getRelated<MCParticle>();
 
    B2ASSERT("No relation from MCRecoTrack to MCParticle.", mcParticle);
 
    const MostWeightEfficientPRId& mostWeightEfficientPRId_for_mcId =
      mostWeightEfficientPRId_by_mcId[mcId];
 
    const RecoTrackId& mostWeightEfficientPRId = mostWeightEfficientPRId_for_mcId.id;
    const Efficiency& weightedEfficiency = mostWeightEfficientPRId_for_mcId.weightedEfficiency;
    // const Efficiency& efficiency = mostWeightEfficientPRId_for_mcId.efficiency;
 
    // find the true charge and reconstructed charge
    const short MCParticleTrackCharge = mcParticle->getCharge() > 0 ? 1 : -1;
    short foundTrackCharge = prRecoTrack->getChargeSeed();
    if (m_useFittedTracks) {
      const RelationVector<Track> fittedTracks = prRecoTrack->getRelationsFrom<Track>(m_TracksStoreArrayName);
      short nPositiveCharges = 0;
      short nNegativeCharges = 0;
 
 
 
      if (fittedTracks.size() > 0) {
 
        for (const auto& fittedTrack : fittedTracks) {
 
          // catch rare case we track long lived non-chargedStable particles (e.g. Sigma)
          try {
            const TrackFitResult* trackFitResult = fittedTrack.getTrackFitResultWithClosestMass(Const::ChargedStable(std::abs(
                                                     mcParticle->getPDG())));
            trackFitResult->getChargeSign() > 0 ? nPositiveCharges++ : nNegativeCharges++;
          } catch (...) {
            const TrackFitResult* trackFitResult = fittedTrack.getTrackFitResultWithClosestMass(Const::pion);
            trackFitResult->getChargeSign() > 0 ? nPositiveCharges++ : nNegativeCharges++;
          }
        }
      }
      if (nPositiveCharges > 0 and nNegativeCharges > 0) {
        B2DEBUG(23,
                "There are different charges attributed to the same track, this shouldn't happen. Continue with the majority of positive or negative charges");
      }
      // Only use nPositiveCharges and nNegativeCharges to assign a new value to foundTrackCharge if at least one fitted Tracks exists
      // and at least one of the two values is > 0
      if (fittedTracks.size() > 0 and (nPositiveCharges > 0 or nNegativeCharges > 0)) {
        foundTrackCharge = nPositiveCharges > nNegativeCharges ? 1 : -1;
      }
    }
 
    // Note : The matched category may also contain higher order clones recognisable by their low
    // absolute efficiency
 
    // MATCHED
    if (prId == mostWeightEfficientPRId) {
      if (foundTrackCharge != MCParticleTrackCharge) {
        prRecoTrack->setMatchingStatus(RecoTrack::MatchingStatus::c_matchedWrongCharge);
        ++nWrongCharge;
      } else {
        prRecoTrack->setMatchingStatus(RecoTrack::MatchingStatus::c_matched);
        ++nMatched;
      }
      // Setup the relation purity relation
      // regardless of the charge matching
      prRecoTrack->addRelationTo(mcRecoTrack, purity);
 
      // Add the mc matching relation
      prRecoTrack->addRelationTo(mcParticle, purity);
 
      B2DEBUG(23, "Stored PRTrack " << prId << " as matched.");
      B2DEBUG(23, "MC Match prId " << prId << " to mcPartId " << mcParticle->getArrayIndex());
      B2DEBUG(23, "Purity rel: prId " << prId << " -> mcId " << mcId << " : " << purity);
      continue;
    }
 
    // GHOST
    // Pattern recognition track fails the minimal efficiency requirement to be matched.
    // We might want to introduce a different classification here, if we see problems
    // with too many ghosts and want to investigate the specific source of the mismatch.
    if (not(weightedEfficiency >= m_minimalEfficiency)) {
      prRecoTrack->setMatchingStatus(RecoTrack::MatchingStatus::c_ghost);
      B2DEBUG(23, "Stored PRTrack " << prId << " as ghost because of too low efficiency.");
      ++nGhost;
      continue;
    }
 
    // Final category
    // CLONE
    if (foundTrackCharge != MCParticleTrackCharge) {
      prRecoTrack->setMatchingStatus(RecoTrack::MatchingStatus::c_cloneWrongCharge);
      ++nClonesWrongCharge;
    } else {
      prRecoTrack->setMatchingStatus(RecoTrack::MatchingStatus::c_clone);
      ++nClones;
    }
    // Setup the relation purity relation
    // regardless whether the charge is correctly reconstructed or not
    prRecoTrack->addRelationTo(mcRecoTrack, -purity);
    prRecoTrack->addRelationTo(mcParticle, -purity);
 
    // Add the mc matching relation to the mc particle
    B2DEBUG(23, "Stored PRTrack " << prId << " as clone.");
    B2DEBUG(23, "MC Match prId " << prId << " to mcPartId " << mcParticle->getArrayIndex());
    B2DEBUG(23, "Purity rel: prId " << prId << " -> mcId " << mcId << " : " << -purity);
  } // end for prId
 
 
 
  B2DEBUG(23, "Number of matches " << nMatched);
  B2DEBUG(23, "Number of wrongCharge " << nWrongCharge);
  B2DEBUG(23, "Number of clones " << nClones);
  B2DEBUG(23, "Number of clones wrongCharge " << nClonesWrongCharge);
  B2DEBUG(23, "Number of bkg " << nBackground);
  B2DEBUG(23, "Number of ghost " << nGhost);
 
  // ### Classify the Monte-Carlo tracks ###
  // Meaning save the highest weighted efficiency relation to the data store.
  for (RecoTrackId mcId = 0; mcId < nMCRecoTracks; ++mcId) {
    RecoTrack* mcRecoTrack = m_MCRecoTracks[mcId];
    MCParticle* mcParticle = mcRecoTrack->getRelated<MCParticle>();
 
    const MostWeightEfficientPRId& mostWeightEfficiencyPRId = mostWeightEfficientPRId_by_mcId[mcId];
 
    const RecoTrackId& prId = mostWeightEfficiencyPRId.id;
    const Efficiency& weightedEfficiency = mostWeightEfficiencyPRId.weightedEfficiency;
    // const Efficiency& efficiency = mostWeightEfficiencyPRId.efficiency;
 
    B2ASSERT("Index of pattern recognition tracks out of range.", prId < nPRRecoTracks and prId >= 0);
 
    RecoTrack* prRecoTrack = m_PRRecoTracks[prId];
 
    const MostPureMCId& mostPureMCId_for_prId = mostPureMCId_by_prId[prId];
    const RecoTrackId& mostPureMCId = mostPureMCId_for_prId.id;
 
    // MATCHED
    if (mcId == mostPureMCId and
        (prRecoTrack->getMatchingStatus() == RecoTrack::MatchingStatus::c_matched or
         prRecoTrack->getMatchingStatus() == RecoTrack::MatchingStatus::c_matchedWrongCharge or
         prRecoTrack->getMatchingStatus() == RecoTrack::MatchingStatus::c_clone or
         prRecoTrack->getMatchingStatus() == RecoTrack::MatchingStatus::c_cloneWrongCharge)) {
      // Setup the relation with positive weighted efficiency for this case.
      mcRecoTrack->addRelationTo(prRecoTrack, weightedEfficiency);
      mcParticle->addRelationTo(prRecoTrack, weightedEfficiency);
      B2DEBUG(23, "Efficiency rel: mcId " << mcId  << " -> prId " << prId << " : " << weightedEfficiency);
      continue;
    }
 
    // MERGED
    // This MCTrack has a significant portion of hits in a PRTrack
    // which in turn better describes a MCTrack different form this.
    // Setup the relation with negative weighted efficiency for this case.
    bool isMergedMCRecoTrack =
      (weightedEfficiency >= m_minimalEfficiency) and
      (prRecoTrack->getMatchingStatus() == RecoTrack::MatchingStatus::c_matched or
       prRecoTrack->getMatchingStatus() == RecoTrack::MatchingStatus::c_matchedWrongCharge or
       prRecoTrack->getMatchingStatus() == RecoTrack::MatchingStatus::c_clone or
       prRecoTrack->getMatchingStatus() == RecoTrack::MatchingStatus::c_cloneWrongCharge);
 
    if (isMergedMCRecoTrack) {
      mcRecoTrack->addRelationTo(prRecoTrack, -weightedEfficiency);
      mcParticle->addRelationTo(prRecoTrack, -weightedEfficiency);
      B2DEBUG(23, "Efficiency rel: mcId " << mcId << " -> prId " << prId << " : " << -weightedEfficiency);
      continue;
    }
 
    // MISSING
    // No related pattern recognition track
    // Do not create a relation.
    B2DEBUG(23, "mcId " << mcId << " is missing. No relation created.");
    B2DEBUG(23, "is Primary " << m_MCRecoTracks[mcId]->getRelatedTo<MCParticle>()->isPrimaryParticle());
    B2DEBUG(23, "best prId " << prId << " with purity " << mostPureMCId_for_prId.purity << " -> " << mostPureMCId);
    B2DEBUG(23, "MC Total ndf " << totalNDF_by_mcId[mcId]);
    B2DEBUG(23, "MC Total weight " << totalWeight_by_mcId[mcId]);
    B2DEBUG(23, "MC Overlap ndf\n " << confusionMatrix.col(mcId).transpose());
    B2DEBUG(23, "MC Overlap weight\n " << weightedConfusionMatrix.col(mcId).transpose());
    B2DEBUG(23, "MC Efficiencies for the track\n" << efficiencyMatrix.col(mcId).transpose());
    B2DEBUG(23, "MC Weighted efficiencies for the track\n" << weightedEfficiencyMatrix.col(mcId).transpose());
  } // end for mcId
 
  B2DEBUG(23, "########## End MCRecoTracksMatcherModule ############");
 
} //end event()

◆ exposePythonAPI()

void exposePythonAPI ( )

staticinherited

Exposes methods of the Module class to Python.

Definition at line 325 of file Module.cc.

{
  // to avoid confusion between std::arg and boost::python::arg we want a shorthand namespace as well
  namespace bp = boost::python;
 
  docstring_options options(true, true, false); //userdef, py sigs, c++ sigs
 
  void (Module::*setReturnValueInt)(int) = &Module::setReturnValue;
 
  enum_<Module::EAfterConditionPath>("AfterConditionPath",
                                     R"(Determines execution behaviour after a conditional path has been executed:
 
.. attribute:: END
 
  End processing of this path after the conditional path. (this is the default for if_value() etc.)
 
.. attribute:: CONTINUE
 
  After the conditional path, resume execution after this module.)")
  .value("END", Module::EAfterConditionPath::c_End)
  .value("CONTINUE", Module::EAfterConditionPath::c_Continue)
  ;
 
  /* Do not change the names of >, <, ... we use them to serialize conditional pathes */
  enum_<Belle2::ModuleCondition::EConditionOperators>("ConditionOperator")
  .value(">", Belle2::ModuleCondition::EConditionOperators::c_GT)
  .value("<", Belle2::ModuleCondition::EConditionOperators::c_ST)
  .value(">=", Belle2::ModuleCondition::EConditionOperators::c_GE)
  .value("<=", Belle2::ModuleCondition::EConditionOperators::c_SE)
  .value("==", Belle2::ModuleCondition::EConditionOperators::c_EQ)
  .value("!=", Belle2::ModuleCondition::EConditionOperators::c_NE)
  ;
 
  enum_<Module::EModulePropFlags>("ModulePropFlags",
                                  R"(Flags to indicate certain low-level features of modules, see :func:`Module.set_property_flags()`, :func:`Module.has_properties()`. Most useful flags are:
 
.. attribute:: PARALLELPROCESSINGCERTIFIED
 
    This module can be run in parallel processing mode safely (All I/O must be done through the data store, in particular, the module must not write any files.)
 
.. attribute:: HISTOGRAMMANAGER
 
  This module is used to manage histograms accumulated by other modules
 
.. attribute:: TERMINATEINALLPROCESSES
 
  When using parallel processing, call this module's terminate() function in all processes. This will also ensure that there is exactly one process (single-core if no parallel modules found) or at least one input, one main and one output process.
)")
  .value("INPUT", Module::EModulePropFlags::c_Input)
  .value("OUTPUT", Module::EModulePropFlags::c_Output)
  .value("PARALLELPROCESSINGCERTIFIED", Module::EModulePropFlags::c_ParallelProcessingCertified)
  .value("HISTOGRAMMANAGER", Module::EModulePropFlags::c_HistogramManager)
  .value("INTERNALSERIALIZER", Module::EModulePropFlags::c_InternalSerializer)
  .value("TERMINATEINALLPROCESSES", Module::EModulePropFlags::c_TerminateInAllProcesses)
  ;
 
  //Python class definition
  class_<Module, PyModule> module("Module", R"(
Base class for Modules.
 
A module is the smallest building block of the framework.
A typical event processing chain consists of a Path containing
modules. By inheriting from this base class, various types of
modules can be created. To use a module, please refer to
:func:`Path.add_module()`.  A list of modules is available by running
``basf2 -m`` or ``basf2 -m package``, detailed information on parameters is
given by e.g. ``basf2 -m RootInput``.
 
The 'Module Development' section in the manual provides detailed information
on how to create modules, setting parameters, or using return values/conditions:
https://confluence.desy.de/display/BI/Software+Basf2manual#Module_Development
 
)");
  module
  .def("__str__", &Module::getPathString)
  .def("name", &Module::getName, return_value_policy<copy_const_reference>(),
       "Returns the name of the module. Can be changed via :func:`set_name() <Module.set_name()>`, use :func:`type() <Module.type()>` for identifying a particular module class.")
  .def("type", &Module::getType, return_value_policy<copy_const_reference>(),
       "Returns the type of the module (i.e. class name minus 'Module')")
  .def("set_name", &Module::setName, args("name"), R"(
Set custom name, e.g. to distinguish multiple modules of the same type.
 
>>> path.add_module('EventInfoSetter')
>>> ro = path.add_module('RootOutput', branchNames=['EventMetaData'])
>>> ro.set_name('RootOutput_metadata_only')
>>> print(path)
[EventInfoSetter -> RootOutput_metadata_only]
 
)")
  .def("description", &Module::getDescription, return_value_policy<copy_const_reference>(),
       "Returns the description of this module.")
  .def("package", &Module::getPackage, return_value_policy<copy_const_reference>(),
       "Returns the package this module belongs to.")
  .def("available_params", &_getParamInfoListPython,
       "Return list of all module parameters as `ModuleParamInfo` instances")
  .def("has_properties", &Module::hasProperties, (bp::arg("properties")),
       R"DOCSTRING(Allows to check if the module has the given properties out of `ModulePropFlags` set.
 
>>> if module.has_properties(ModulePropFlags.PARALLELPROCESSINGCERTIFIED):
>>>     ...
 
Parameters:
  properties (int): bitmask of `ModulePropFlags` to check for.
)DOCSTRING")
  .def("set_property_flags", &Module::setPropertyFlags, args("property_mask"),
       "Set module properties in the form of an OR combination of `ModulePropFlags`.");
  {
    // python signature is too crowded, make ourselves
    docstring_options subOptions(true, false, false); //userdef, py sigs, c++ sigs
    module
    .def("if_value", &Module::if_value,
         (bp::arg("expression"), bp::arg("condition_path"), bp::arg("after_condition_path")= Module::EAfterConditionPath::c_End),
         R"DOCSTRING(if_value(expression, condition_path, after_condition_path=AfterConditionPath.END)
 
Sets a conditional sub path which will be executed after this
module if the return value set in the module passes the given ``expression``.
 
Modules can define a return value (int or bool) using ``setReturnValue()``,
which can be used in the steering file to split the Path based on this value, for example
 
>>> module_with_condition.if_value("<1", another_path)
 
In case the return value of the ``module_with_condition`` for a given event is
less than 1, the execution will be diverted into ``another_path`` for this event.
 
You could for example set a special return value if an error occurs, and divert
the execution into a path containing :b2:mod:`RootOutput` if it is found;
saving only the data producing/produced by the error.
 
After a conditional path has executed, basf2 will by default stop processing
the path for this event. This behaviour can be changed by setting the
``after_condition_path`` argument.
 
Parameters:
  expression (str): Expression to determine if the conditional path should be executed.
      This should be one of the comparison operators ``<``, ``>``, ``<=``,
      ``>=``, ``==``, or ``!=`` followed by a numerical value for the return value
  condition_path (Path): path to execute in case the expression is fulfilled
  after_condition_path (AfterConditionPath): What to do once the ``condition_path`` has been executed.
)DOCSTRING")
    .def("if_false", &Module::if_false,
         (bp::arg("condition_path"), bp::arg("after_condition_path")= Module::EAfterConditionPath::c_End),
         R"DOC(if_false(condition_path, after_condition_path=AfterConditionPath.END)
 
Sets a conditional sub path which will be executed after this module if
the return value of the module evaluates to False. This is equivalent to
calling `if_value` with ``expression=\"<1\"``)DOC")
    .def("if_true", &Module::if_true,
         (bp::arg("condition_path"), bp::arg("after_condition_path")= Module::EAfterConditionPath::c_End),
         R"DOC(if_true(condition_path, after_condition_path=AfterConditionPath.END)
 
Sets a conditional sub path which will be executed after this module if
the return value of the module evaluates to True. It is equivalent to
calling `if_value` with ``expression=\">=1\"``)DOC");
  }
  module
  .def("has_condition", &Module::hasCondition,
       "Return true if a conditional path has been set for this module "
       "using `if_value`, `if_true` or `if_false`")
  .def("get_all_condition_paths", &_getAllConditionPathsPython,
       "Return a list of all conditional paths set for this module using "
       "`if_value`, `if_true` or `if_false`")
  .def("get_all_conditions", &_getAllConditionsPython,
       "Return a list of all conditional path expressions set for this module using "
       "`if_value`, `if_true` or `if_false`")
  .add_property("logging", make_function(&Module::getLogConfig, return_value_policy<reference_existing_object>()),
                &Module::setLogConfig)

◆ getAfterConditionPath()

Module::EAfterConditionPath getAfterConditionPath ( ) const

inherited

What to do after the conditional path is finished.

(defaults to c_End if no condition is set)

Definition at line 133 of file Module.cc.

{
  if (m_conditions.empty()) return EAfterConditionPath::c_End;
 
  //okay, a condition was set for this Module...
  if (!m_hasReturnValue) {
    B2FATAL("A condition was set for '" << getName() << "', but the module did not set a return value!");
  }
 
  for (const auto& condition : m_conditions) {
    if (condition.evaluate(m_returnValue)) {
      return condition.getAfterConditionPath();
    }
  }
 
  return EAfterConditionPath::c_End;
}

◆ getAllConditionPaths()

std::vector< std::shared_ptr< Path > > getAllConditionPaths ( ) const

inherited

Return all condition paths currently set (no matter if the condition is true or not).

Definition at line 150 of file Module.cc.

{
  std::vector<std::shared_ptr<Path>> allConditionPaths;
  for (const auto& condition : m_conditions) {
    allConditionPaths.push_back(condition.getPath());
  }
 
  return allConditionPaths;
}

◆ getAllConditions()

const std::vector< ModuleCondition > & getAllConditions ( ) const

inlineinherited

Return all set conditions for this module.

Definition at line 324 of file Module.h.

    {
      return m_conditions;
    }

◆ getCondition()

const ModuleCondition * getCondition ( ) const

inlineinherited

Return a pointer to the first condition (or nullptr, if none was set)

Definition at line 314 of file Module.h.

    {
      if (m_conditions.empty()) {
        return nullptr;
      } else {
        return &m_conditions.front();
      }
    }

◆ getConditionPath()

std::shared_ptr< Path > getConditionPath ( ) const

inherited

Returns the path of the last true condition (if there is at least one, else reaturn a null pointer).

Definition at line 113 of file Module.cc.

{
  PathPtr p;
  if (m_conditions.empty()) return p;
 
  //okay, a condition was set for this Module...
  if (!m_hasReturnValue) {
    B2FATAL("A condition was set for '" << getName() << "', but the module did not set a return value!");
  }
 
  for (const auto& condition : m_conditions) {
    if (condition.evaluate(m_returnValue)) {
      return condition.getPath();
    }
  }
 
  // if none of the conditions were true, return a null pointer.
  return p;
}

◆ getDescription()

const std::string & getDescription ( ) const

inlineinherited

Returns the description of the module.

Definition at line 202 of file Module.h.

202{return m_description;}

Belle2::Module::m_description

std::string m_description

The description of the module.

Definition: Module.h:511

◆ getFileNames()

virtual std::vector< std::string > getFileNames ( bool outputFiles )

inlinevirtualinherited

Return a list of output filenames for this modules.

This will be called when basf2 is run with "--dry-run" if the module has set either the c_Input or c_Output properties.

If the parameter outputFiles is false (for modules with c_Input) the list of input filenames should be returned (if any). If outputFiles is true (for modules with c_Output) the list of output files should be returned (if any).

If a module has sat both properties this member is called twice, once for each property.

The module should return the actual list of requested input or produced output filenames (including handling of input/output overrides) so that the grid system can handle input/output files correctly.

This function should return the same value when called multiple times. This is especially important when taking the input/output overrides from Environment as they get consumed when obtained so the finalized list of output files should be stored for subsequent calls.

Reimplemented in RootInputModule, StorageRootOutputModule, and RootOutputModule.

Definition at line 134 of file Module.h.

    {
      return std::vector<std::string>();
    }

◆ getLogConfig()

LogConfig & getLogConfig ( )

inlineinherited

Returns the log system configuration.

Definition at line 225 of file Module.h.

225{return m_logConfig;}

◆ getModules()

std::list< ModulePtr > getModules ( ) const

inlineoverrideprivatevirtualinherited

no submodules, return empty list

Implements PathElement.

Definition at line 506 of file Module.h.

506{ return std::list<ModulePtr>(); }

◆ getName()

const std::string & getName ( ) const

inlineinherited

Returns the name of the module.

This can be changed via e.g. set_name() in the steering file to give more useful names if there is more than one module of the same type.

For identifying the type of a module, using getType() (or type() in Python) is recommended.

Definition at line 187 of file Module.h.

187{return m_name;}

Belle2::Module::m_name

std::string m_name

The name of the module, saved as a string (user-modifiable)

Definition: Module.h:508

◆ getPackage()

const std::string & getPackage ( ) const

inlineinherited

Returns the package this module is in.

Definition at line 197 of file Module.h.

197{return m_package;}

◆ getParamInfoListPython()

std::shared_ptr< boost::python::list > getParamInfoListPython ( ) const

inherited

Returns a python list of all parameters.

Each item in the list consists of the name of the parameter, a string describing its type, a python list of all default values and the description of the parameter.

Returns: A python list containing the parameters of this parameter list.

Definition at line 279 of file Module.cc.

{
  return m_moduleParamList.getParamInfoListPython();
}

◆ getParamList()

const ModuleParamList & getParamList ( ) const

inlineinherited

Return module param list.

Definition at line 363 of file Module.h.

363{ return m_moduleParamList; }

◆ getPathString()

std::string getPathString ( ) const

overrideprivatevirtualinherited

return the module name.

Implements PathElement.

Definition at line 192 of file Module.cc.

{
 
  std::string output = getName();
 
  for (const auto& condition : m_conditions) {
    output += condition.getString();
  }
 
  return output;
}

◆ getReturnValue()

int getReturnValue ( ) const

inlineinherited

Return the return value set by this module.

This value is only meaningful if hasReturnValue() is true

Definition at line 381 of file Module.h.

381{ return m_returnValue; }

◆ getType()

const std::string & getType ( ) const

inherited

Returns the type of the module (i.e.

class name minus 'Module')

Definition at line 41 of file Module.cc.

{
  if (m_type.empty())
    B2FATAL("Module type not set for " << getName());
  return m_type;
}

◆ hasCondition()

bool hasCondition ( ) const

inlineinherited

Returns true if at least one condition was set for the module.

Definition at line 311 of file Module.h.

311{ return not m_conditions.empty(); };

◆ hasProperties()

bool hasProperties ( unsigned int propertyFlags ) const

inherited

Returns true if all specified property flags are available in this module.

Parameters

propertyFlags Ored EModulePropFlags which should be compared with the module flags.

Definition at line 160 of file Module.cc.

{
  return (propertyFlags & m_propertyFlags) == propertyFlags;
}

◆ hasReturnValue()

bool hasReturnValue ( ) const

inlineinherited

Return true if this module has a valid return value set.

Definition at line 378 of file Module.h.

378{ return m_hasReturnValue; }

◆ hasUnsetForcedParams()

bool hasUnsetForcedParams ( ) const

inherited

Returns true and prints error message if the module has unset parameters which the user has to set in the steering file.

Definition at line 166 of file Module.cc.

{
  auto missing = m_moduleParamList.getUnsetForcedParams();
  std::string allMissing = "";
  for (const auto& s : missing)
    allMissing += s + " ";
  if (!missing.empty())
    B2ERROR("The following required parameters of Module '" << getName() << "' were not specified: " << allMissing <<
            "\nPlease add them to your steering file.");
  return !missing.empty();
}

◆ if_false()

void if_false	(	const std::shared_ptr< Path > &	path,
		EAfterConditionPath	afterConditionPath = `EAfterConditionPath::c_End`
	)

inherited

A simplified version to add a condition to the module.

Please note that successive calls of this function will add more than one condition to the module. If more than one condition results in true, only the last of them will be used.

Please be careful: Avoid creating cyclic paths, e.g. by linking a condition to a path which is processed before the path where this module is located in.

It is equivalent to the if_value() method, using the expression "<1". This method is meant to be used together with the setReturnValue(bool value) method.

Parameters

path	Shared pointer to the Path which will be executed if the return value is false.
afterConditionPath	What to do after executing 'path'.

Definition at line 85 of file Module.cc.

{
  if_value("<1", path, afterConditionPath);
}

◆ if_true()

void if_true	(	const std::shared_ptr< Path > &	path,
		EAfterConditionPath	afterConditionPath = `EAfterConditionPath::c_End`
	)

inherited

A simplified version to set the condition of the module.

Please note that successive calls of this function will add more than one condition to the module. If more than one condition results in true, only the last of them will be used.

Please be careful: Avoid creating cyclic paths, e.g. by linking a condition to a path which is processed before the path where this module is located in.

It is equivalent to the if_value() method, using the expression ">=1". This method is meant to be used together with the setReturnValue(bool value) method.

Parameters

path	Shared pointer to the Path which will be executed if the return value is true.
afterConditionPath	What to do after executing 'path'.

Definition at line 90 of file Module.cc.

{
  if_value(">=1", path, afterConditionPath);
}

◆ if_value()

void if_value	(	const std::string &	expression,
		const std::shared_ptr< Path > &	path,
		EAfterConditionPath	afterConditionPath = `EAfterConditionPath::c_End`
	)

inherited

Add a condition to the module.

Please note that successive calls of this function will add more than one condition to the module. If more than one condition results in true, only the last of them will be used.

See https://confluence.desy.de/display/BI/Software+ModCondTut or ModuleCondition for a description of the syntax.

Please be careful: Avoid creating cyclic paths, e.g. by linking a condition to a path which is processed before the path where this module is located in.

Parameters

expression	The expression of the condition.
path	Shared pointer to the Path which will be executed if the condition is evaluated to true.
afterConditionPath	What to do after executing 'path'.

Definition at line 79 of file Module.cc.

{
  m_conditions.emplace_back(expression, path, afterConditionPath);
}

◆ initialize()

void initialize ( void )

finalvirtual

Signal the beginning of the event processing.

Reimplemented from Module.

Definition at line 199 of file MCRecoTracksMatcherModule.cc.

{
  if (m_MCParticles.isOptional()) {
    m_mcParticlesPresent = true;
 
    // Require both RecoTrack arrays and the MCParticles to be present in the DataStore
    m_MCParticles.isRequired();
    m_PRRecoTracks.isRequired(m_prRecoTracksStoreArrayName);
    m_MCRecoTracks.isRequired(m_mcRecoTracksStoreArrayName);
 
    // Purity relation - for each PRTrack to store the purest MCTrack
    m_PRRecoTracks.registerRelationTo(m_MCRecoTracks);
 
    // Efficiency relation - for each MCTrack to store the most efficient PRTrack
    m_MCRecoTracks.registerRelationTo(m_PRRecoTracks);
 
    // MCParticle matching relation - purity
    m_PRRecoTracks.registerRelationTo(m_MCParticles);
 
    // MCParticle matching relation - efficiency
    m_MCParticles.registerRelationTo(m_PRRecoTracks);
 
    // Announce optional store arrays to the hits or clusters in case they should be used
    // We make them optional in case of limited detector setup.
    // PXD
    if (m_usePXDHits) {
      m_PXDClusters.isOptional();
    }
 
    // SVD
    if (m_useSVDHits) {
      m_SVDClusters.isOptional();
    }
 
    // CDC
    if (m_useCDCHits) {
      m_CDCHits.isOptional();
    }
  }
}

◆ setAbortLevel()

void setAbortLevel ( int abortLevel )

inherited

Configure the abort log level.

Definition at line 67 of file Module.cc.

{
  m_logConfig.setAbortLevel(static_cast<LogConfig::ELogLevel>(abortLevel));
}

◆ setDebugLevel()

void setDebugLevel ( int debugLevel )

inherited

Configure the debug messaging level.

Definition at line 61 of file Module.cc.

{
  m_logConfig.setDebugLevel(debugLevel);
}

◆ setDescription()

void setDescription ( const std::string & description )

protectedinherited

Sets the description of the module.

Parameters

description A description of the module.

Definition at line 214 of file Module.cc.

{
  m_description = description;
}

◆ setLogConfig()

void setLogConfig ( const LogConfig & logConfig )

inlineinherited

Set the log system configuration.

Definition at line 230 of file Module.h.

230{m_logConfig = logConfig;}

◆ setLogInfo()

void setLogInfo	(	int	logLevel,
		unsigned int	logInfo
	)

inherited

Configure the printed log information for the given level.

Parameters

logLevel	The log level (one of LogConfig::ELogLevel)
logInfo	What kind of info should be printed? ORed combination of LogConfig::ELogInfo flags.

Definition at line 73 of file Module.cc.

{
  m_logConfig.setLogInfo(static_cast<LogConfig::ELogLevel>(logLevel), logInfo);
}

◆ setLogLevel()

void setLogLevel ( int logLevel )

inherited

Configure the log level.

Definition at line 55 of file Module.cc.

{
  m_logConfig.setLogLevel(static_cast<LogConfig::ELogLevel>(logLevel));
}

◆ setName()

void setName ( const std::string & name )

inlineinherited

Set the name of the module.

Note: The module name is set when using the REG_MODULE macro, but the module can be renamed before calling process() using the set_name() function in your steering file.

Parameters

name	The name of the module

Definition at line 214 of file Module.h.

214{ m_name = name; };

◆ setParamList()

void setParamList ( const ModuleParamList & params )

inlineprotectedinherited

Replace existing parameter list.

Definition at line 501 of file Module.h.

501{ m_moduleParamList = params; }

◆ setParamPython()

void setParamPython	(	const std::string &	name,
		const boost::python::object &	pyObj
	)

privateinherited

Implements a method for setting boost::python objects.

The method supports the following types: list, dict, int, double, string, bool The conversion of the python object to the C++ type and the final storage of the parameter value is done in the ModuleParam class.

Parameters

name	The unique name of the parameter.
pyObj	The object which should be converted and stored as the parameter value.

Definition at line 234 of file Module.cc.

{
  LogSystem& logSystem = LogSystem::Instance();
  logSystem.updateModule(&(getLogConfig()), getName());
  try {
    m_moduleParamList.setParamPython(name, pyObj);
  } catch (std::runtime_error& e) {
    throw std::runtime_error("Cannot set parameter '" + name + "' for module '"
                             + m_name + "': " + e.what());
  }
 
  logSystem.updateModule(nullptr);
}

◆ setParamPythonDict()

void setParamPythonDict ( const boost::python::dict & dictionary )

privateinherited

Implements a method for reading the parameter values from a boost::python dictionary.

The key of the dictionary has to be the name of the parameter and the value has to be of one of the supported parameter types.

Parameters

dictionary The python dictionary from which the parameter values are read.

Definition at line 249 of file Module.cc.

{
 
  LogSystem& logSystem = LogSystem::Instance();
  logSystem.updateModule(&(getLogConfig()), getName());
 
  boost::python::list dictKeys = dictionary.keys();
  int nKey = boost::python::len(dictKeys);
 
  //Loop over all keys in the dictionary
  for (int iKey = 0; iKey < nKey; ++iKey) {
    boost::python::object currKey = dictKeys[iKey];
    boost::python::extract<std::string> keyProxy(currKey);
 
    if (keyProxy.check()) {
      const boost::python::object& currValue = dictionary[currKey];
      setParamPython(keyProxy, currValue);
    } else {
      B2ERROR("Setting the module parameters from a python dictionary: invalid key in dictionary!");
    }
  }
 
  logSystem.updateModule(nullptr);
}

◆ setPropertyFlags()

void setPropertyFlags ( unsigned int propertyFlags )

inherited

Sets the flags for the module properties.

Parameters

propertyFlags bitwise OR of EModulePropFlags

Definition at line 208 of file Module.cc.

{
  m_propertyFlags = propertyFlags;
}

◆ setReturnValue() [1/2]

void setReturnValue ( bool value )

protectedinherited

Sets the return value for this module as bool.

The bool value is saved as an integer with the convention 1 meaning true and 0 meaning false. The value can be used in the steering file to divide the analysis chain into several paths.

Parameters

value The value of the return value.

Definition at line 227 of file Module.cc.

{
  m_hasReturnValue = true;
  m_returnValue = value;
}

◆ setReturnValue() [2/2]

void setReturnValue ( int value )

protectedinherited

Sets the return value for this module as integer.

The value can be used in the steering file to divide the analysis chain into several paths.

Parameters

value The value of the return value.

Definition at line 220 of file Module.cc.

{
  m_hasReturnValue = true;
  m_returnValue = value;
}

◆ setType()

void setType ( const std::string & type )

protectedinherited

Set the module type.

Only for use by internal modules (which don't use the normal REG_MODULE mechanism).

Definition at line 48 of file Module.cc.

{
  if (!m_type.empty())
    B2FATAL("Trying to change module type from " << m_type << " is not allowed, the value is assumed to be fixed.");
  m_type = type;
}

◆ terminate()

virtual void terminate ( void )

inlinevirtualinherited

This method is called at the end of the event processing.

This method is called only once after the event processing finished. Use this method for cleaning up, closing files, etc.

double m_minimalEfficiency

private

Parameter : Minimal efficiency for a MCTrack to be considered matchable to a PRTrack.

This number encodes which fraction of the true hits must at least be in the reconstructed track. The default 0.05 suggests that at least 5% of the true hits should have been picked up.

Definition at line 226 of file MCRecoTracksMatcherModule.h.

◆ m_minimalPurity

double m_minimalPurity

tracking/modules/mcMatcher/include/MCRecoTracksMatcherModule.h
tracking/modules/mcMatcher/src/MCRecoTracksMatcherModule.cc

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Private Types

Private Member Functions

Private Attributes

Detailed Description

Member Typedef Documentation

◆ EAfterConditionPath

◆ NDF

Member Enumeration Documentation

◆ EModulePropFlags

Constructor & Destructor Documentation

◆ MCRecoTracksMatcherModule()

Member Function Documentation

◆ beginRun()

◆ clone()

◆ def_beginRun()

◆ def_endRun()

◆ def_event()

◆ def_initialize()

◆ def_terminate()

◆ endRun()

◆ evalCondition()

◆ event()

◆ exposePythonAPI()

◆ getAfterConditionPath()

◆ getAllConditionPaths()

◆ getAllConditions()

◆ getCondition()

◆ getConditionPath()

◆ getDescription()

◆ getFileNames()

◆ getLogConfig()

◆ getModules()

◆ getName()

◆ getPackage()

◆ getParamInfoListPython()

◆ getParamList()

◆ getPathString()

◆ getReturnValue()

◆ getType()

◆ hasCondition()

◆ hasProperties()

◆ hasReturnValue()

◆ hasUnsetForcedParams()

◆ if_false()

◆ if_true()

◆ if_value()

◆ initialize()

◆ setAbortLevel()

◆ setDebugLevel()

◆ setDescription()

◆ setLogConfig()

◆ setLogInfo()

◆ setLogLevel()

◆ setName()

◆ setParamList()

◆ setParamPython()

◆ setParamPythonDict()

◆ setPropertyFlags()

◆ setReturnValue() [1/2]

◆ setReturnValue() [2/2]

◆ setType()

◆ terminate()

Member Data Documentation

◆ m_CDCHits

◆ m_conditions

◆ m_description

◆ m_hasReturnValue

◆ m_logConfig

◆ m_MCParticles

◆ m_mcParticlesPresent

◆ m_MCRecoTracks

◆ m_mcRecoTracksStoreArrayName

◆ m_minimalEfficiency

◆ m_minimalPurity

◆ m_moduleParamList

◆ m_name