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1. ChosenParticle composedOf DecayTree i _ toriginatesFrom RecTrack fom Reconstructed _ 1 __ produces ParticleCandidate 1 VixCandidate A 1 na RecPaticlelD decays Into from Reconstructed TrkParticle NeutParticle CompParticle Figure 35 Data model of analysis event Velo Event ContainedObject from TopLevel DataObject from Kemel arent ER 7 D Level12dTrack Ne Fa 1 N Ys 1 RawveloHit _ VeloCluster _ Level13dTrack Level1 Vertex Level1 Summary 1 1 1 Figure 36 Velo event data model page 207 GAUDI Appendix D LHCb Event Data Model User Guide Version Issue 6 3 Tracking Reconstructed Event TrMCTrack covariance matrix Z position state i Pointer or N associater 44s TrState TrStateQPt TrStateL x y amp ty Q Pt S xy ty _ TrTrack TrMeasurem ent Ee OTHitOnTrack OTHit ITHitOnTrack ITHit Espetially in case of outer tracker measurement depends on which track the hitis on Figure 37 Tracking reconstructed event data model Calorimeters CaloCell
2. vir jet vir vir vir vir vir vir if hf vir vir vir vir TParticlePropertySve interface Create a new particle property Input particle String name of the particle Input geantId Geant ID of the particle Input jetsetId Jetset ID of the particle Input type Particle type Input charge Particle charge e Input mass Particle mass MeV Input tlife Particle lifetime ns Return StatusCode SUCCESS if the particle property was added tual StatusCode push_back const std string amp particle int geantId setId int type double charge double mass double tlife Create a new particle property Input pp a particle property class Return StatusCode SUCCESS if the particle property was added tual StatusCode push_back ParticleProperty pp Get a const reference to the begining of the map tual const_iterator begin const Get a const reference to th nd of the map tual const_iterator end const Get the number of properties in the map tual int size const Retrieve a property by geant id Pointer is 0 if no property found tual ParticleProperty find int geantId Retrieve a property by particle name Pointer is 0 if no property found tual ParticleProperty find const std string name Retrieve a property
3. Algorithm name Option Name Default value Meaning EventCounter Frequency 1 Frequency with which number of events should be reported Prescaler PercentPass 100 0 Percentage of events that should be passed Sequencer Members Names of mambers of the sequence Sequencer StopOverride false If true do not stop sequence if a filter fails page 191 GAUDI Appendix B Options for standard components User Guide Version Issue 6 3 Table B 9 Options available for output streams e g DstWriter Output stream objects are used for writing user created data into data files or databases They are cre ated and named by setting the option ApplicationMgr OutStream For each output stream the following options are available Option name Default value Meaning ItemList The list of data objects to be written to this stream e g Event 1 Event MyTracks 1 EvtDataSve EventDataSvc The service from which to retrieve objects Output Output data stream specification Format DATAFILE mydst root TYP ROOT i t LA C 4i A i l a O Fi un O A b a This option is obsolete Please use the TYP tag of Output option instead b This option is obsolete Please use the DATAFILE tag of the Output option instead Table B 10 Standard Options for the event persistency service PersistencySvc Option name Default value Me
4. a V lt lt EMPTY gt gt material logvol detelemref Figure 12 Content model definition of the catalog and catalogref elements page 80 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 8 5 2 2 Defining detector elements Figure 13 shows the content model definition of the det elem element and its child elements detelem name ID classID CDATA 2 Saa 0 oniy 1 Xl SK 0 1 author version lt lt EMPTY gt gt lt lt EMPTY gt gt lt lt ANY gt gt geo metryin fo detelemref specific D classID CDATA 2 NOTA J D href CDATA t JE N PCDATA i geometryinfo can A y0 1 y0 1 1 be empty ghost lt lt EMPTY gt gt support 2 contain only log vol name lvname name CDATA 3 contain log vol name support info name CDATA oo OR ae 1 a lt lt EMPTY gt gt path npath value CDATA name CDATA Figure 13 Content model definition of the detelem element The detelem element has a sequence of tags which must appear in the same order shown on the diagram author version geometryinfo detelemref specific The child elements author detelemref and specific are optional so if they are not present the content is still valid The PCDAT
5. gmake Nmake Application executable Batch machine Figure 4 Creating a job from the Histogram example application In order for the job to run as desired you must provide the correct configuration information for the executable This is done via entries in the job options file 4 3 The main program An example main program is shown in Listing 2 on page 34 It is constructed as follows Include files These are needed for the creation of the application manager and Smart interface pointers page 32 it GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 Application Manager instantiation Line 38 instantiates an ApplicationMgr object The application manager is essentially the job controller It is responsible for creating and correctly initialising all of the services and algorithms required for looping over the input data events and executing the algorithms specified in the job options file and for terminating the job cleanly Retrieval of Interface pointers The code on lines 40 and 41 retrieves the pointers to the IProperty and LAppMgrUI interfaces of the application manager Setting the application manager s properties The only property which needs to be set explicitly in the main program is the name of the job options file which contains all of the other configuration information needed to run the job This is done on line 46 Program execution All of the code before line 54 is essen
6. The macro needs a few words of explanation the instantiated converters are able to create transient objects of type Event The corresponding persistent type is of a generic type the data are stored as a machine independent byte stream It is mandatory that the Event class implements a streamer method serialize An example of the Event class is shown in Listing 75 The instantiated converter is of the type DoGenericConverter and the instance of the instantiating factory has the instance name DbEventCnvFactory Listing 75 Serialisation of the class Event Serialize the object for writing virtual StreamBuffer amp serialize StreamBuffer amp s const DataObject serialize s return s lt lt m_event lt lt m _ run lt lt m time Serialize the object for reading virtual StreamBuffer amp serialize StreamBuffer s DataObject serialize s return s gt gt m_event gt gt m_run gt gt m_time DnoOUPWNHRFP TOO WAANA oO BWN FP 13 7 1 Non Identifiable Objects Non identifiable objects cannot directly be retrieved stored from the data store Usually they are small and in any case they are contained by a container object Examples are particles class MCParticle hits class MCHitBase and others or vertices class MCVertex These classes can be converted using a generic container converter Container converters exist currently for lists and vectors The co
7. GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 An example use of the MsgSt ream class is shown below Listing 54 Use of a MsgStream object 1 include Gaudi MessageSvc MgsStream h 2 3 StatusCode myAlgo finalize 4 StatusCode status Algorithm finalise 53 MsgStream log msgSvc name 6 if status isFailure 7 Print a two line message in case of failure 8 log lt lt MSG ERROR lt lt Finalize failed lt lt endl gz lt lt Error initializing Base class lt lt endreq 10 11 else 123 log lt lt MSG DEBUG lt lt Finalize completed successfully lt lt endreq ES 14 return status LSG 3 When using the MsgSt ream class just think of it as a configurable output stream whose activation is actually controlled by the first word message level and which actually prints only when endreq is supplied For all other functionality simply refer to the C ostream class The activation level of the MsgSt ream object is controlled by the first expression e g MSG ERROR or MSG DEBUG in the example above Possible values are given by the enumeration below enum MSG Level VERBOUS DEBUG INFO WARNING ERROR FATAL Thus the code in Listing 54 will produce NO output if the print level of the message service is set higher than MSG ERROR In addition if the service s print level is lower than or equal to MSG
8. Listing 33 XML definition of the geometry for the MyDetector element type lt xml version 1 0 gt lt DOCTYPE DDDB SYSTEM xmldb dtd gt lt DDDB gt lt catalog name MyDetector gt lt logvolref href lvMyDe gt lt logvolref href lvMyDeSubMod gt lt logvolref href lvMyDeAnotherMod gt lt catalog gt lt logvol name l1vMyDe material Vacuum gt lt box name lvMyDeBox sizeZ 0 8 amp m sizeY 10 amp m sizeX 10 amp m gt lt paramphysvol number 2 gt lt physvol name ppvMySM logvol dd Geometry MyDetector lvMyDeSubMod gt lt posXYZ x 0 amp mm y 0 amp mm z 300 amp mm gt lt physvol gt lt posXYZ x 0 amp mm y 0 amp mm z 100 amp mm gt lt rotXYZ rotX 0 degree rotY 0 amp degree rotZ 90 amp degree gt lt paramphysvol gt lt physvol name pvMyAnothersM lLogvol dd Geometry MyDetector 1lvMyDeAnotherMod gt lt posXYZ x 0 amp mm y 0 amp mm z 200 amp mm gt lt physvol gt lt logvol gt lt DDDB gt First we define the catalog of all the logical volumes of MyDet ector as shown in Listing 33 This catalog is accessible at run time as dd Geomet ry MyDetector Such a catalog allows modification of the XML detector description database by many people in parallel because all the changes to the geometry structure inside this catalog can be kept local to this catalog without affecting the other subdet
9. The handling of row wise n tuples does not differ However only individual items class NTuple Item can be filled no arrays and no matrices Since the persistent representation of row wise n tuples in HBOOK is done by floats only the first row of each row wise n tuple contains the type information when looking at a row wise n tuple with PAW make sure to start at the second event 10 3 Event Collections Event collections or to be more precise event tag collections are used to minimize data access by performing preselections based on small amounts of data Event tag data contain flexible event classification information according to the physics needs This information could either be stored as flags indicating that the particular event has passed some preselection criteria or as a small set of parameters which describe basic attributes of the event Fast access is required for this type of event data page 104 it GAUDI User Guide Chapter 10 N tuple and Event Collection facilities Version Issue 6 3 Event tag collections can exist in several versions e Collections recorded during event processing stages from the online reconstruction reprocessing etc e Event collections defined by analysis groups with pre computed items of special interest to a given group e Private user defined event collections Starting from this definition an event tag collection can be interpreted as an n tuple which allows to ac
10. enable debug messages page 35 GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 4 5 Algorithms The subject of specialising the Algorithm base class to do something useful will be covered in detail in chapter 5 Here we will limit ourselves to looking at the class HistoAlgorithmin the example just to get an idea of the basics For the full listing of this class refer to the software distribution Here we look only at those parts of the code which do something interesting and leave the technicalities for later 4 5 1 The HistoAlgorithm header file The HistoAlgorithm class definition is shown in Listing 4 Note the following The class is derived from the Algorithm base class as must be all specialised algorithm classes This implies that the Algorithm h file must be included All derived algorithm classes must provide a constructor with the parameters shown in line 8 The first parameter is the name of the algorithm and is used amongst other things to locate any options that may have been specified in the job options file The HistoAlgorithm class has three private data members defined in lines 18 to 21 These are a boolean flag and two pointers to histogram objects The three methods on lines 11 to 13 must be implemented since they are pure virtual in the base class Listing 4 The header file of the class HistoAlgorithm N N N he GO e G S a N e DO a S a OT S a O EF N H
11. GAUDI User Guide Chapter 3 Release notes and software installation Version Issue 6 3 3 4 Availability The application framework is supported on the following platforms e Windows NT 4 using the Developer Studio 6 0 SP2 C environment e RedHat Linux 6 1 certified CERN Linux distribution with SUE and AFS The code documentation and installation instructions are available from the LHCb web site at http cern ch lhcb comp Components html GaudiMain html 3 5 Using the framework on NT with Developer Studio The Framework sources are available via AFS or can be downloaded from the web The libraries for NT are available in the LHCb AFS tree in the Win32Debug subdirectory of each package Instructions for installing the LHCb software environment on NT and for customising MS Visual Studio can be found at http cern chAhcb comp Support html DevStudio default htm 3 6 Using the framework in Unix The framework libraries have been built for various Unix platforms and are available via AFS These libraries have been built using the Configuration Management Tool CMT Therefore using the CMT tool is the recommended way to modify existing packages or re build the examples included in the release Complete and up to date information about using CMT is available at the URL http cern ch lhcb comp Support html cmt htm Here we give only simple instructions on how to get started with the Gaudi software under CMT on Unix Getting a copy of
12. If the Chrono amp Stat Service is not accessible the Chrono object does nothing page 126 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 11 6 3 2 Stat Stat is a small helper class which invokes the st at method in the constructor BwNhN PF Gaudi ChronoStatSvc Stat h PI wer Stat stat chronoSvc StatTag Flag Weight ie re If the Chrono amp Stat Service is not accessible the Stat object does nothing 11 6 4 Performance considerations The implementation of the Chrono amp Stat Service uses two std map containers and could generate a performance penalty for very frequent calls Usually the penalty is small relative to the elapsed time of algorithms but it is worth avoiding both the direct usage of the Chrono amp Stat Service as well as the usage of it through the Chrono or Stat utilities inside internal loops To REL aa 2 begin of the scope 3 Chrono chrono chronoSvc Good Chrono OK 4 long double a 0 5 for long i 0 i lt 1000000 i 6 Ts Chrono chrono svc Bad Chrono not OK 8 some codes Gs a sin cos sin cos long double i 10 end of codes Tiz Stat stat svc Bad Stat a not OK is 13 Stat stat svc Good Stat a OK 14 end of the scope Lot ATE a3 page 127 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3
13. We also describe how to implement new services for use within the Gaudi environment We look at how to code up a service what facilities the Service base class provides and how a service is managed by the application manager 11 2 Requesting and accessing services The Application manager creates a certain number of services by default These are the default data access services EventDataSvc DetectorDataSvc HistogramDataSvc NTupleSvc the default data persistency services EventPersistencySvc DetectorPersistencySvc HistogramPersistencySvc and the framework services described in this chapter and in Chapter 12 JobOptionsSvc MessageSvc ParticlePropertySvc ChronoStatSvc AuditorSvc RndmGenSvc IncidentSvc ToolSvc page 111 GAUDI Chapter 11 Framework services User Guide Version Issue 6 3 Additional services can be requested via the jobOptions file using the property ApplicationMgr ExtSve In the example below this option is used to create a specific type of event selector and the corresponding conversion service Listing 49 Job Option to create additional services ApplicationMgr ExtSve SicbEventCnvSvc v EventSelector Once created services must be accessed via their interface The Algorithm base class provides a number of accessor methods for the standard framework services listed on lines 25 to 35 of Listing 7 on page 44 Other services can be locat
14. generic Converter accesses pre defined entry points in each object The transient object converts itself to an abstract byte stream However for specialized objects specific converters can be built by virtual overrides of the base class Whenever objects must change their representation within Gaudi data converters are involved For the ROOT case the converters must have some knowledge of ROOT internals and the service finally used to migrate ROOT objects gt TOb ject to a file In the same way the converter must be able to translate the functionality of the Dat a0bject component to from the Root storage Within ROOT itself the object is stored as a Binary Large Object BLOB The instantiation of the appropriate converter is done by a macro The macro instantiates also the converter factory used to instantiate the requested converter Hence all other user code is shielded from the implementation and definitions of the ROOT specific code page 158 it GAUDI User Guide Chapter 13 Converters Version Issue 6 3 Listing 74 Implementing a generic converter for the transient class Event 1 Include files 2 include LHCbEvent TopLevel ObjectVector h 3 include LHCbEvent TopLevel ObjectList h 4 include DbCnv DbGenericConverter h 5 6 7 Converter implementation for objects of class Event include LHCbEvent TopLevel Event h _ImplementConverter Event
15. setProperties setMyPropeties nextEvent execute 7 finalize sysFinalize terminate Figure 5 A sequence diagram showing a part of the execution of the example program page 40 GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 The SimpleAnalysisAlgorithmis an example in which pi pi invariant masses are made while requiring the component particles to satisfy some simple kinematic and quality cuts Private containers of the particles satisfying successive cuts are created and filled charged particles detection in the silicon best particle ID Invariant masses are made and corresponding histograms are filled for all combinations of the final private containers for combinations with Pt of both pions greater than a cut value and for combinations with impact parameter of both pions greater then a cut value The Pt and impact parameter cut values are properties of the algorithm and as such can be specified in the jobOptions where the number is taken in Gaudi Units CLHEP vectors classes are used to evaluate transverse momentum and invariant masses as well as to calculate the impact parameter When nominal mass values are required they are retrieved via the ParticlePropertySvc Since a primary vertex is required a dummy algorithm RecPrimaryVertex retrieves the Monte Carlo primary vertex and uses the quantites to fill a MyVert ex object Event MyAxVertices which is then retrieved by the
16. 11 7 The Auditor Service The Auditor Service provides a set of auditors that can be used to provide monitoring of various characteristics of the execution of Algorithms Each auditor is called immediately before and after each call to each Algorithm instance and can track some resource usage of the Algorithm Calls that are thus monitored are initialize execute and finalize although monitoring can be disabled for any of these for particular Algorithm instances Only the execute function monitoring is enabled by default Several examples of auditors are provided These are e NameAuditor This just emits the name of the Algorithm to the Standard Message Service immediately before and after each call It therefore acts as a diagnostic tool to trace program execution e ChronoAuditor This monitors the cpu usage of each algorithm and reports both the total and per event average at the end of job It replaces the explicit Chrono Service monitoring that was implemented in Gaudi release 5 e MemoryAuditor This monitors the state of memory usage during execution of each Algorithm and will warn when memory is allocated within a call without being released on exit Unfortunately this will in fact be the general case for Algorithms that are creating new data and registering them with the various transient stores Such Algorithms will therefore cause warning messages to be emitted However for Algorithms that are just reading data from the
17. 17 Fill the Pt versus P scatterplot 18 Tterate over all tracks in the track container 19 MCParticleVector iterator iterP 0 20 for iterP particles gt begin iterP particles gt end iterPt 21 Get the energy of the track convert it to GeV and histogram it 22 double pt iterP gt fourMomentum perp 234 double p iterP gt fourMomentum rho 24 m_hPtvsP gt fill p GeV pt GeV 1 2s ZOOS lt j The details of the event data store and how data is accessed are discussed in Chapter 6 Finalisation At finalisation the HistoAlgorithm class asks the histogram service to printout the histograms in different formats MsgStream The HistoAlgorithm class makes use of the message service and the MsgSt ream utility class in order to print out some progress information for example MsgStream log msgSvc name log lt lt MSG INFO lt lt finalize lt lt endreq The first line creates a local MsgSt ream object which uses the Algorithm s standard message service via the msgSvc accessor and the algorithm s name via the name accessor The use of these is discussed in more detail in Chapter 11 page 38 GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 4 6 Job execution From the main program and the requirements file we can make an executable This executable together with the file of job options form a job which may be submitted for batch or run int
18. 9 else 10 log lt lt MSG ERROR lt lt Error accessing event lt lt endreq Le return StatusCode FAILURE T2 Tas lt i page 61 GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 The SmartDataPtr class can be thought of as a normal C pointer having a constructor It is used in the same way as a normal C pointer The SmartDataPtr and SmartDataLocator offer a number of possible constructors and operators to cover a wide range of needs when accessing data stores Check the online reference documentation 2 for up to date information concerning the interface of these utilities 6 9 Smart references and Smart reference vectors Smart references and Smart reference vectors are similar to smart pointers they are used within data objects to reference other objects in the transient data store They provide safe data access and automate the loading on demand of referenced data and should be used instead of C pointers For example suppose that MCPart icles are already loaded but MCVertices are not and that an algorithm dereferences a variable pointing to the origin vertex if a smart reference is used the MCVert ices would be loaded automatically and only after that would the variable be dereferenced If a C plain pointer were used instead the program would crash Smart references provide an automatic conversion to a pointer to the object and load the object from the persistent medi
19. NTuplePtr nt ntupleSvc filel First A column wise N tuple NIUPLES FILE1 NT UPLES FILE1 MC 1 if nt Check if already booked nt ntupleSvc gt book NTUPLES FILE1 MC 1 CLID_ColumnWiseTuple Hello World if nt Add an index column status nt gt addItem Ntrack m_ntrk 0 5000 Add a variable size column of type float length length of index col status nt gt addItem px m_ntrk m px status nt gt addItem py m_ntrk m py status nt gt addItem pz m_ntrk m pz Another one but this time of type bool status nt gt addItem flg m_ntrk m flag Another one type integer numerical numbers must be within 0 5000 status nt gt addItem idx m_ntrk m_index 0 5000 Add 2 dim column 0 m_ntrk 0 2 numerical numbers within 0 8 status nt gt addItem hit m_ntrk m hits 2 0 8 else did not manage to book the N tuple return StatusCode FAILURE Tags which are not declared to the n tuple are invalid and will cause an access violation at run time 10 2 2 3 Filling the N tuple Tags are usable just like normal data items where W page 101 GAUDI Chapter 10 N tuple and Event Collection facilities User Guide Version Issue 6 3 e Items lt TYPE gt are the equivalent of numbers bool long float e Array lt TYPE gt are equivalent to 1 d
20. 0 virtual StatusCode afterExecut IAlgorithm theAlg 0 virtual StatusCode beforeFinalize IAlgorithm theAlg 0 virtual StatusCode afterFinalize IAlgorithm theAlg 0 A new Auditor should inherit from the Auditor base class and override the appropriate functions from the Auditor abstract interface The following code fragment is taken from the ChronoAuditor include Gaudi Auditor Auditor h class ChronoAuditor virtual public Auditor public ChronoAuditor const std string amp name ISvcLocator pSvcLocator virtual ChronoAuditor virtual StatusCode beforeInitialize IAlgorithm alg virtual StatusCode afterInitialize IAlgorithm alg virtual StatusCode beforeExecute IAlgorithm alg virtual StatusCode afterExecute IAlgorithm alg virtual StatusCode beforeFinalize IAlgorithm alg virtual StatusCode afterFinalize IAlgorithm alg page 129 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 11 8 The Random Numbers Service When generating random numbers two issues must be considered e reproducibility and e randomness of the generated numbers In order to ensure both Gaudi implements a single service ensuring that these criteria are met The encapsulation of the actual random generator into a service has several advantages e Random seeds are set by the framework When debugging the detector simulation
21. Appendix A References Appendix B Options for standard components Appendix C Job Options Grammar and Error Codes C 1 The EBNF grammar of the Job Options files C 2 Job Options Error Codes and Error Messages Appendix D LHCb Event Data Model 167 171 171 171 171 172 172 173 173 174 181 181 181 182 184 187 189 197 197 199 203 page 6 GAUDI User Guide Chapter 1 Introduction Version Issue 6 3 Chapter 1 Introduction 1 1 Purpose of the document This document is intended as a combination of user guide and tutorial for the use of the Gaudi application framework software It is complemented principally by two other documents the Architecture Design Document ADD 1 and the online auto generated reference documentation 2 A third document 3 lists the User Requirements and Scenarios that were used as input and validation of the architecture design All these documents and other information about Gaudi including this user guide are available from the Gaudi home page http cern ch lhcb comp Components html GaudiMain html The ADD contains a discussion of the architecture of the framework the major design choices taken in arriving at this architecture and some of the reasons for these choices It should be of interest to anyone who wishes to write anything other than private analysis code As discussed in the ADD the application
22. O i oajuwF wn EF w w N he QO at OAT ae a r H CU WANA PWN FE N H O D w oO 23s 34 393 36 Shs 38 39 40 41 42 43 44 45 46 47 HREREREE HE HE HEHE EH HEE HE HH HEHE HE FE EH HH HE HE HE HE HE FE HE HE HEE HE Histograms job options file Et include SSTDOPTS Common txt Private Application Configuration options ApplicationMgr DLLs RootHistCnv ApplicationMgr TopAlg HistoAlgorithm Specify ROOT or HBOOK persistency HBOOK is default ApplicationMgr HistogramPersistency ROOT Set output level threshold 2 DEBUG 3 INFO 4 WARNING 5 ERROR 6 FATAL MessageSvc OutputLevel 3 Event related parameters Number of events to be processed default is all events ApplicationMgr EvtMax 100 Print event number every event EventSelector PrintFregq 1 Input file Th EventSelector Input FILE SSITEROOT lhcb data mc sicb_bpipi_v233_100ev dst1 EventSelector Input JOBID 16434 las Histogram output file las Specify Histogram Persistency Output File HistogramPersistencySvc OutputFile histo rt HistogramPersistencySvc OutputFile histo hbook ee Algorithms Private Options A ee ier eas HistoAlgorithm HistogramFlag true false no histograms produced HistoAlgorithm OutputLevel 3
23. Thus the idea of having essentially mathematical objects such as vectors points etc and these being distinct from the more complex beasts which manipulate them e g fitting algorithms etc is still valid This is the reason why the Gaudi application framework makes a clear distinction between data objects and algorithm objects Anything which has as its origin a concept such as hit point vector trajectory i e a clear quantity like entity should be implemented by deriving a class from the Dat aOb ject base class On the other hand anything which is essentially a procedure i e a set of rules for performing transformations on more data like objects or for creating new data like objects should be designed as a class derived from the Algorithm base class Further more you should not have objects derived from Dat aOb ject performing long complex algorithmic procedures The intention is that these objects are small Tracks which fit themselves are of course possible you could have a constructor which took a list of hits as a parameter but they are silly Every track object would now have to contain all of the parameters used to perform the track fit making it far from a simple object Track fitting is an algorithmic procedure a track is probably best represented by a point and a vector or perhaps a set of points and vectors They are different 2 4 Main components The principle functionality of an algorit
24. see the next step page 87 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 Step 2 Define your detector element in XML In this step one needs to define all the new XML tags for the detector element specific data that the user wants to access from the XML data file The definition of the new XML tags is done inside the so called local DTD section This is needed validation purposes With this definition the XML parser is then able check whether the syntax of the user defined XML tags is valid or not The next step is to provide information about the geometry Actually here we do not do the full geometry description but only create the association telling the converter where to look for full geometrical information about this detector element The definition of the geometry is shown at the next step Finally the user has to define sub detectors or sub modules if any An example XML definition of the MyDetector element type is shown in Listing 32 in which two new XML tags are defined AluminiumPlateThickness and CellSize They are the used inside the lt specific gt section filled with the concrete data Listing 32 XML definition of MyDetector element type lt xml version 1 0 encoding UTF 8 gt lt DOCTYPE DDDB SYSTEM xmldb dtd lt i yDetector cell siz gt lt ELEMENT CellSize EMPTY gt lt ATTLIST CellSize n CDATA REQUIRED gt lt Thickness of the Aluminum pl
25. staging data from DSTs converting SICB data for use by Gaudi algorithms accessing the magnetic field map accessing the SICB geometry description the use of the SUINIT SUANAL and SULAST routines from within the Gaudi framework and handling event pileup in Gaudi When using the geometry and magnetic field descriptions described here you should not forget that they are a temporary solution and that they will disappear at some point in the future Gaudi includes already the machinery to provide any algorithm with the detector data stored in XML format Investing some time now to describe your detector in XML may be in many cases more convenient than using the old SICB routines to access detector description data If for any reason you have to use the old tools use them only to populate some pre defined class which can then be used in your algorithms In this way when you decide to move to the new detector description tools in Gaudi the required changes in your code will be confined to the parts which access the geometry 14 2 Reading tapes There are three ways to specify a SICB input data file in Gaudi page 161 GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 1 Read one or more files on disk by setting the appropriate option of the Event Selector in the job options file EventSelector Input FILE SSITEROOT lLhcb data mc sicb_mbias_v233_10ev dst2 SSITEROOT lhcb data mc sicbh_bpip
26. string amp name const virtual bool isExecuted const virtual StatusCode setExecuted bool state virtual StatusCode resetExecuted virtual bool isEnabled const virtual bool filterPassed const virtual StatusCode setFilterPassed bool state template lt class Svc gt StatusCode service const std string amp svcName Svc amp theSvc IMessageSvc msgSvc void setOutputLevel int level IDataProviderSvc eventSvc IConversionSvc eventCnvSvc IDataProviderSvc detSvc IConversionSvc detCnvSvc THistogramSvc histoSvc INtupleSvc ntupleSvc TIChronoStatSvc chronoSvc IRndmGenSvc randSvc ISvcLocator serviceLocator StatusCode createSubAlgorithm const std string amp type std vector virtual Sta ithm virtual public IAlgorithm virtual public IProperty tor and destructor const std string amp name ISvcLocator svcloc gorithm const std string amp name lt Algorithm gt subAlgorithms Algorithm pSubAlg const tusCode setProperty const Property amp p virtual StatusCode getProperty Property p const const Property amp getProperty const std string amp name const const std vector lt Property gt amp getProperties const StatusCode setProperties StatusCode declareProperty const std string amp name int amp reference StatusCode declareProperty const std string amp name floa
27. 41 42 43 44 45 46 47 48 49 50 51 3 52 3 53 3 54 55x StatusCode SoDetElemCnv createRep DataObject aObject IOpaqueAddress amp DetectorElement d dynamic_cast lt DetectorElement gt aObject TLVolume lv de gt geometry gt lvolume SolidBox box dynamic_cast lt SolidBox gt lv gt solid gt coverTop SoSeparator separator new SoSeparator SoDrawStyle drawStyle new SoDrawStyle SoMaterial material new SoMaterial separator gt addChild drawStyle separator gt addChild material set drawing styles drawStyl gt style setValue SoDrawStyle LINES drawStyl gt linePattern setValue 0xFFFF material gt diffuseColor setValue SbColor 0 1 0 Code related to the transformation SoTransform trans new SoTransform separator gt addChild trans SoCube cube new SoCube cube gt widt N box gt xHalfLength cube gt heig N 2 t box gt yHalfLength 2 2 cube gt dept N box gt zHalfLength separator gt addChild cube m_pSo gt add ode separator return StatusCode SUCCESS page 179 GAUDI Chapter 16 Visualization Facilities User Guide Version Issue 6 3 page 180 GAUDI User Guide Chapter 17 Design considerations Version Issue 6 3 Chapter 17 Design considerations 17 1 Generalities In this chap
28. DEBUG the Finalize completed successfully message will be printed assuming of course it was successful User interface What follows is a technical description of the part of the MsgSt ream user interface most often seen by application developers Please refer to the header file for the complete interface Insertion Operator The MsgStream class overloads the lt lt operator as described below MsgStream amp operator lt lt TYPE arg Insertion operator for various types The argument is only formatted by the stream object if the print level is sufficiently high and the stream is active Otherwise the insertion operators simply return Through this mechanism extensive debug printout does not cause large run time overheads All common base types such as char unsigned char int float etc are supported page 120 it GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 MsgStream amp operator lt lt MSG Level level This insertion operator does not format any output but rather de activates the stream s formatting and forwarding engine depending on the value of level Accepted Stream Manipulators The MsgSt ream specific manipulators are presented below e g endreq MsgStream amp endreg MsgStream amp stream Besides these the common ost ream and ios manipulators such as std ends std endl are also accepted endl Inserts a newline sequence Opposite to the ostrea
29. GaudiLab uses the OnX ML package to drive interactivity From an XML description of the graphical user interface GUI OnX creates an application GUI by using various toolkits like Motif Win32 GTK It permits also to handle various scripting languages currently tcl CINT KUIP in the GUI XML files to describe the behaviour of the GUI pieces The graphics are handled by Open Inventor The Inventor viewers being part of the GUI are created by OnX from a placement in the application GUI XML files page 174 it GAUDI User Guide Chapter 16 Visualization Facilities Version Issue 6 3 Connection to Gaudi is done through the wrapping of Gaudi C code to scripting languages For example the Next event button executes the tcl script eraseEvent gaudiLab nextEvent The eraseEvent is a tcl script that erases the event Inventor scene graph but not the detector Inventor scene graph gaudiLab nextEvent executes the Gaudi ApplicationMgr nextEvent 1 method through an instance of the main GaudiLab class dynamically loaded by OnX tools Inventor modeling of the LHCb detector and event data is driven by the Lab service LabSvc class The Lab service from a textual request coming from the GUI like visualize dd Structure LHCb Muon drives the adequate Gaudi Inventor converters the So lt xxx gt Cnv classes to produce Inventor scene graphs The SoDetElemCnv and SoLVolumeCnv build the Inventor scene gr
30. If all objects were treated on an equal footing then there would be many more accesses to the persistent store to retrieve very small objects By grouping objects together like this we are able to have fewer accesses with each access retrieving bigger objects 6 5 Using object containers The code fragment below shows the creation of an object container This container can contain pointers to objects of type MCTrackingHit and only to objects of this type including derived types An object of the required type is created on the heap i e via a call to new and is added to the container with the standard STL call ObjectVector lt MCTrackingHit gt hitContainer MCTrackingHit hl new MCTrackingHit hitContainer push_back h1 After the call to push_back the hit object belongs to the container If the container is registered into the store the hits that it contains will go with it Note in particular that if you delete the container you will also delete its contents i e all of the objects pointed to by the pointers in the container Removing an object from a container may be done in two semantically different ways The difference being whether on removal from a container the object is also deleted or not Removal with deletion may be achieved in several ways following previous code fragment hitContainer pop_back hitContainer erase end delete hl The method pop_back removes the last el
31. SimpleAnalysisAlgorithm Since the MyVertex object is created and registered in the Transient Event store by the RecPrimaryVertex algorithm the sequencing of RecPrimaryVertex and SimpleAnalysisAlgorithm in the jobOptions file is very important A protection is put in place so that the SimpleAnalysisAlgorithm will return a failure code if not all of the necessary input data exist in the store When doing physics analysis on Monte Carlo data it is necessary to compare the reconstructed decay with the Monte Carlo truth in order to calculate efficiencies The MCDecayF inder algorithm is an example of how to find any one step decay The parent of the decay and the list of its direct descendants are properties of the algorithm and can be specified in the jobOptions file If no decay is specified in the jobOptions this example will look for a BO gt pi pi decay The Algorithm will retrieve the particle Geant3 ID from the ParticlePropertySvc the identifying particleID in MCPart icles and search the MCParticles to find the requested parent and that is has the correct type and number of decay products If a decay is found kinematic variables are stored in an ntuple that can be accessed by PAW In addition the Algorithm uses the Message service with DEBUG or INFO levels to print a summary of its behaviour for each event as well as for the job page 41 GAUDI Chapter 4 Getting started User Guide Version Issue 6 3 4 8 Other example
32. Smart reference vectors to reference themselves 6 10 Saving data to a persistent store Suppose that you have defined your own data type as discussed in section 6 7 Suppose futhermore that you have an algorithm which uses say SicB data to create instances of your object type which you then register into the transient event store How can you save these objects for use at a later date You must do the following e Write the appropriate converter see Chapter 13 e Put some instructions i e options into the job option file see Listing 17 e Register your object in the store us usual typically in the execute method of your algorithm myAlg implementation file StatusCode myAlg execute Create a UDO object and register it into the event data store UDO p new UDO ventSvc gt registerObject Event myStuff myUDO p page 63 GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 In order to actually trigger the conversion and saving of the objects at the end of the current event processing it is necessary to inform the application manager This requires some options to be specified in the job options file Listing 17 Job options for output to persistent storage ApplicationMgr OutStream DstWriter DstWriter ItemList Event 1 Event MyTracks 1 DstWriter EvtDataSvc EventDataSvc DstWriter Output DATAFILE result root
33. a package Suppose you want to build the latest released version of the GaudiExamples package 1 cd mycmt 2 getpack GaudiExamples following versions are available v6 v5rl v5 v4 v3 Enter version number lt CR gt v6 gt page 27 GAUDI User Guide Chapter 3 Release notes and software installation Version Issue 6 3 Building and running an example Now that you have the code suppose you want to modify the Histograms example then build it and run it 3 cd GaudiExamples v6 Histograms 4 emacs HistoAlgorithm cpp SSSs5 Make your modification then 5 cd mgr 6 emacs requirements So SSS Uncomment Histograms and comment all the others 7 gmake cd emacs jobOptions txt ig Histograms See Make any modification if needed 10 SCMTCONFIG Histograms exe Modifying a library and rerunning the example Suppose now you want to modify one of the Gaudi libraries build it then relink the Histograms example and run it 11 cd S HOME mycmt 12 getpack HbookCnv v5 13 cd HbookCnv v5 HbookCnv 14 emacs Make your modification 15 cd mgr 16 gmake 17 cd S HOME mycmt GaudiExamples v6 mgr 18 cmt show uses ake sure that you are using the modified version v5 of HbookCnv If not edit the requirements file to use this version 19 gmake 20 cd Histograms 21 SCMTCONFIG Histograms exe 3 7 Work
34. algorithm Must be a member variable of the parent class std string type Type of sub algorithm std string name Name to be given to subAlgorithm StatusCode sc Status code returned by the call sc createSubAlgorithm type name Algorithm amp m_pSubAlgorithm The algorithm type i e class name string is used by the application manager to decide which factory should create the algorithm object The execution of the sub algorithm is entirely the responsibility of the parent algorithm whereas the initialize and finalize methods are invoked automatically by the framework as shown in Figure 6 Similarly the properties of a sub algorithm are also automatically set by the framework Note that the createSubAlgorithm method returns a pointer to an Algorithm object not an Algorithm interface This means that you have access to the methods of both the IAlgorithmand Property interfaces and consequently as well as being able to call execute etc you can also explicitly call the setProperty Property method of the sub algorithm as is done in the following code fragment For this reason with nested algorithms you are not restricted to calling set Property only at initialization You may also change the properties of a sub algorithm during the main event loop Algorithm m_pSubAlgorithm sc createSubAlgorithm type name Algorithm amp m_pSubAlgorithm IntegerProperty p Counter 1024 m_pSubAlg
35. any of the listed reasons occured in your case Warning 001 File already included by another file The file was already included by another file and will not be included a second time The compiler will ignore this include directive and will continue with the next state ment Remove the include directive Error 002 syntax error Object expected The compiler expected an object at the given position Maybe you mistyped the name of the object or the object contains unknown characters or does not fit the given rules Error 003 syntax error Miss ing dot between Object and Propertyname The compiler expect a dot between the Object and the Propertyname Check if the dot between the Object and the Propertyname is missing Error 004 syntax error Iden tifier expected The compiler expected an identifier at the given posi tion Maybe you mistyped the name of the identifier or the identifier contains unknown characters or does not fit the given rules Error 005 syntax error Miss ing operator or The compiler expected an operator between the Proper tyname and the value Check if there is a valid opera tor after the Propertyname Note that a blank or tab is not allowed between page 199 Appendix C Job Options Grammar and Error Codes User Guide Version Issue 6 3 Table 12 Possible Error Codes Error Code Reason How t
36. const double my_height 170 cm const double my_weight 75 kg Note that the user should not care about the numerical value of the numbers my_height and my_weight Internally these numbers are represented as 1700 and 4 68e 26 respectively but the user does not need to know 3 All output of dimensioned quantities should be converted to the required units by dividing by the units defined in the CLHEP Units SystemOfUnits h header file For example my_hist histoSvc gt book stat diet corpulence kg m 2 30 10 40 double my_corpulence my_weight my_height my_height my_hist gt fill my_corpulence kg m2 1 which for a healthy person should plot a number between 19 and 25 4 Physical constants should not be defined in user code They should be taken directly from the CLHEP Units PhysicalConstants h header file For example float my_rest_energy my_weight c_squared 5 Users may wish to use a different set of units for specific purposes e g when the default units may lead to precision problems In this case algorithms can renormalise their private copy of the data as shown in the last line of the rule 3 example for internal use but making sure that any data subsequently published to the public data stores is converted back to the CLHEP units page 9 GAUDI User Guide Chapter 1 Introduction Version Issue 6 3 1 2 2 Coding Conventions The Gaudi sof
37. double string vector vector vectorvalue vectorvalue vectorvalue boolean integer double string boolean true false integer prefix scientificdigit double prefix lt digit gt scientificdigit prefix scientificdigit string Na char NT scientificdigit lt digit gt e CE lt digit gt digit lt figure gt prefix Var bee 4 figure SAT ae IRs MDE LAT SAF MAE 6 Be ALG VRT YO char any character from the ASCII Code letter set of all capital and non capital letter page 198 GAUDI Appendix C Job Options Grammar and Error Codes User Guide Version Issue 6 3 C 2 Job Options Error Codes and Error Messages The table below lists the error codes and error messages that the Job Options compiler may generate their reason and how to avoid them Table 12 Possible Error Codes Error Code Reason How to avoid it Error 000 Internal compiler error This code normally should never appear If this code is shown there is maybe a prob lem with your memory your disk space or the prop erty file is corrupted Error 001 Included prop erty file does not exists or can not be opened wrong path in include directive wrong file or mistyped filename file is exclusively locked by another application no memory available to open this file Please check if
38. double or single quotes In the content can appear text data or other properly nested elements The text data and nested elements can be mixed inside the content 8 5 1 3 Well formed versus Valid XML documents A well formed XML document is any XML document which follows the rules described in the previous section However this is not sufficient in some cases Inside an XML document you can have any XML tag you can imagine This is not harmful to XML itself but makes it impossible to process such a document with a computer program and makes it very hard to maintain the program to keep it synchronised with all the new tags users invent For a well formed XML document is not possible to check or validate that the document contains only the tags which make sense or have valid content For that purpose there exists a notation called Document Type Definition DTD which comes from SGML world This notation permits the definition of a grammar a valid set of tags their contents and attributes which allows then to perform the validation of XML documents i e whether the document contains the XML tags which belong to the set of tags defined by its associated DTD In addition the validating application can check whether the tags contain only allowed tags or text data and whether the tags use only attributes defined for them by the DTD The validation process can can also perform normalization of attributes i e assign default values to attributes that the use
39. dynamically at run time and not statically The latter would imply linking with all the available libraries producing huge executables And in certain applications and environments some of the libraries will surely never be used This release provides support for dynamic libraries for the NT and Linux platforms 3 3 Changes in the new release There are changes in current release with respect to the version 5 of the framework in interfaces and base classes therefore the end user applications will need to be re compiled and re linked In general there is no need to do any change in the user code algorithms tools and converters The only known incompatible changes are in the JobOptions to specify the input and output files page 25 GAUDI User Guide Chapter 3 Release notes and software installation Version Issue 6 3 3 3 1 Incompatible changes JobOptions for n tuple input and output files The way of specifying the input and output n tuple file has changed The Input property can be associated to files in different formats The old way NTupleSvc Input MC ntuplel hbook USER tuple2 hbook NTupleSvc Type 6 HBOOK The new way NTupleSvc Input FILE DATAFILE tuple mdb OPT NEW TYP MS Access FILE2 DATAFILE tuple hbook OPT NEW TYP HBOOK JobOptions for EventSelector The E
40. evt SmartDataPtr lt Event gt evt eventSvc Event Some data analysis deciding wether to keep th vent or not keep_event true if ev setFilterPassed keep_ev nt should be written to event collection YA oO PWN EP m_evtAddrColl evt gt address nt 10 3 1 3 Writing out the Event Collection The event collection is written out by an EvtCollectionStream EvtCollectionStream which is the last member of the event collection Sequencer Listing 44 which is taken from the job options of EvtCollection example shows how to set up such a sequence consisting of a user written Selector algorithm which could for example contain the code in Listing 43 and of the Listing 44 Job options for writing out an event collection 1 ApplicationMgr OutStream Sequencer EvtCollection OPT NEW TYP ROOT EvtCollection Members EvtCollectionWrite Selector EvtCollectionStream Writer 4 Writer ItemList NTUPLES EvtColl Collection D8 TupleSvc Output EvtColl DATAFILE MyEvtCollection root page 106 GAUDI User Guide Chapter 10 N tuple and Event Collection facilities Version Issue 6 3 10 3 2 Reading Events using Event Collections Reading event collections as the input for further event processing in Gaudi is transparent The main change is the specification
41. gSystem gt Load D mycmt DbCnv v3 Win32Debug libTBlobShr root 1 L v8 NTuples interactive Cc root 2 interactive v8 NTuples tuple root More detailed explanations can found in the ROOT tutorials ittp root cern ch Listing 47 Interactive analysis of ROOT n tuples interactive C 1 void interactive const char fname 2i TFile input new TFile fname 33 TTE XEYE TTree input gt Get lt local gt _MC_ROW_WISE_2 4 if 0 tree 53 printf Cannot find the requested tr in the root file n 6 return 7 8 INE E ID OBJSIZE NUMLINK NUMSYMB 9 TBlob BUFFER 0 0 Float_t PX PY PZ 1 tree gt SetBranchAddress ID amp ID 2 tree gt SetBranchAddress OBJSIZE amp OBJSIZE 3 tree gt SetBranchAddress NUMLINK amp NUMLINRE 4 tree gt SetBranchAddress NUMSYMB amp NUMSYMB 5 tree gt SetBranchAddress BUFFER amp BUFFER 6 tree gt SetBranchAddress px amp PxX 7 tree gt SetBranchAddress py amp py 8 tree gt SetBranchAddress pz amp pz 9 Int_t nbytes 0 20 for Int_t i 0 nentries cr gt GetEntries i lt nentries it 21 nbytes tr gt GetEntry i 22 8 printf Trk d PX Sf PY f PZ Sf n i px Py PZ 23 24 printf I have read a total of d Bytes n nbytes 25 delete input ZO 7 10 4 3 ODBC Open DataBase Connectivity ODBC developed by Microsoft allows to access a very wide range of relational databases using the sa
42. histo TrackCount lt lt endreq het 8 m_PtvsP histoSvc gt book stat simple2D 3 Pt versus P 100 0 200 100 0 5 9i if 0 m_PtvsP 10 log lt lt MSG ERROR lt lt Cannot register histo Pt versus P lt lt endreq Li 12 execution The execute method is where most of the real action takes place This method is called by the application manager once for every event The HistoAlgorithm class accesses the event data store to retrieve a container of track objects see Listing 6 line 2 It then fills one of the two previously created histograms with the number of particles line 15 page 37 GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 In order to use the objects within the container an iterator is defined line 19 and the second histogram is filled with the momentum of the tracks line 24 Listing 6 execute method of the class HistoAlgorithm 1 MCParticle 2 SmartDataPtr lt MCParticleVector gt particles eventSvc 3 Event MC MCParticles 4 5 if particles 6 log lt lt MSG ERROR lt lt Unable to retrieve MCParticles lt lt endreq F return 0 8 9 log lt lt MSG INFO lt lt MCParticles retrieved lt lt endreq 10 11 Histograms 12 if m produceHistogram IESi 14 Fill the track count histogram 15 m_hTrackCount gt fill particles gt size 1 16
43. is the meaning of the data items encoded in XML Thus one can easily recognize the data items and guess what they mean On the other hand it is relatively easy to instruct a computer program what to do with the given data item according to the XML markup elements it is encapsulated in Let us analyse the example shown above 8 5 1 2 XML components XML declaration must be at the beginning of each XML document It is the first line in the example It says that this file is an XML file conforming to the XML standard version 1 0 and is encoded in UTF 8 encoding The encoding is very important because XML has been designed to describe data using the Unicode standard for text encoding This means that all XML documents are treated as 16 bit Unicode characters instead of usual ASCII So even if you write your XML files using 7 or 8 bit ASCII all the XML applications will work with it as with 16 bit Unicode XML data The encoding information is important for example when an XML document is transferred over the Internet to some other country where a different encoding is used If the receiving application can guess the XML encoding from the received file it can apply transcoding methods to convert the file into proper local encoding thus preserving readability of the data XML comments look like comments in SGML or HTML They start with lt and end with gt Comments in XML cannot be nested XML elements are the markup components describing data
44. m_sum4p 9 if sc isFailure 10 log lt lt MSG FATAL lt lt Unable to create AddFourMom tool lt lt endreq ds return sc LAs i 13 Example of private tool 14 sc toolsvc gt retrieveTool ImpactPar m_ip this 15 if sc isFailure 16 log lt lt MSG FATAL lt lt Unable to create ImpactPar tool lt lt endreq 17 return sc 18 gt 12 4 GaudiTools In general concrete tools are specific to applications or detectors code but there are some tools of common utility for which interfaces and base classes can be provided The Associators described below and contained in the GaudiTools package are one of such tools GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 12 4 1 Associators When working with Monte Carlo data it is often necessary to compare the results of reconstruction or physics analysis with the original corresponding Monte Carlo quantities on an event by event basis as well as on a statistical level Various approaches are possible to implement navigation from reconstructed simulated data back to the Monte Carlo truth information Each of the approaches has its advantages and could be more suited for a given type of event data or data sets In addition the reconstruction and physics analysis code should treat simulated data in an identical way to real data In order to shield the code from the details of the navigation procedure an
45. not known to the Application Mgr Format lt Type gt lt Name gt lt Type2 gt lt Name2 gt OutStream Declares an output stream object for writing data to a persistent store e g DstWriter See also Table B 9 Dlls Search list of DLLs for dynamic loading NT only Format lt dll1 gt lt dll2 gt DetStorageType 0 Detector database storage type 7 XML DetDbLocation empty Detector database location filename URL If empty then the environment valiable XMLDDDBROOT is used DetDbRootName empty Name of the root node of the detector transient store HistogramPersistency HBOOK Histogram persistency mechanism Available options are HBOOK and ROOT Auditors i List of Auditors to be loaded and to be used page 189 GAUDI Appendix B Options for standard components User Guide Version Issue 6 3 Table B 1 Standard Options for the Application manager ApplicationMgr Option name Default value Meaning The last two options define the source of the job options file and so they cannot be defined in the job options file itself There are two possibilities to set these options the first one is using a environment variable called JOBOPTPATH or setting the option to the application manager directly from the main program The coded option takes precedence JobOptionsType FILE Type of file FILE implies ascii JobOptionsPath jobOpt
46. oO Oo include Gaudi Algorithm Algorithm h Required for inheritance class IHistogram1D Forward declaration class IHistogram2D Forward declaration class HistoAlgorithm public Algorithm public Constructor of this form must be provided HistoAlgorithm const std string amp name ISvcLocator pSvcLocator Three mandatory member functions of any algorithm StatusCode initialize StatusCode execute StatusCode finalize private These data members are used in the execution of this algorithm They are set in the initialisation phase by the job options service bool m_produceHistogram Two histograms used if m_produceHistogram 1 true IHistogram1D m_hTrackCount THistogram2D m_hPtvsP page 36 GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 4 5 2 The HistoAlgorithm implementation file The implementation file contains the actual code for the constructor and for the methods initialize execute and finalize It also contains two lines of code for the HistoAlgorithm factory which we will discuss in section 5 3 1 The constructor must call the base class constructor passing on its two arguments As usual member variables should be initialised Here we set the m_produceHistogranm flag to false and set the histogram pointers to zero This is also the place to declare any member variables that you wish to be set by the job options service Thi
47. object from the store 1 std string objectPath Event RawData 2 DataObject pObject 3 StatusCode sc 4 5 sc eventSvc gt retrieveObject objectPath pObject 6 7 IdataDirectory dir pObject gt directory 8 IdataDirectory DirIterator it 9 for it dir gt begin it dir gt end it 10 Tis DataObject pDo 12 sc retrieveObject pObject it gt localPath pDo 13 14 Do something with pDo Lo A The last two methods shown in Listing 12 are for registering objects into the store Suppose that an algorithm creates objects of type UDO from say objects of type MCParticle and wishes to place these into the store for use by other algorithms Code to do this might look something like Listing 14 Registering of objects into the event data store 1 UDO po Pointer to an object of type UDO derived from DataObject 2 StatusCode sc 33 4 pO new UDO 5 sc eventSvc gt registerObject Event Recon tmp OK pO 6 7 THE NEXT LINE IS AN ERROR THE OBJECT NOW BELONGS TO THE STORE 8 delete pO gz 10 UDO autopo 11 ERROR AUTOMATIC OBJECTS MAY NOT BE REGISTERED 12 sc eventSvc gt registerObject Event Recon tmp notOK autopO Once an object is registered into the store the algorithm which created it relinquishe
48. ourMomentum LorentzVector loscillationFlag bool false BB ituaiMass Figure 39 Tracking model of hits page 209 GAUDI Appendix D LHCb Event Data Model User Guide Version Issue 6 3 Object Containers DataObject from Kernel T ObjectContainerBase from TopLevel PobjectContainerBase Ihas NewerVersion E parent setParent 1 1 py T l ObjectList from TopLevel BBobjectList Pbegin PSvegin Mend Bend Erbegin Eerbegin push_front pop_front release T Object Vector from TopLevel BBobjectVector Bvegin Pvegin end Bend Eerbegin Ffrbegin rend 4 vector T from TopLevel operator reserve ContainedObject from TopLevel popeo BXparent Es etParent Figure D 3 Object containers for the event model page 210 GAUDI Index User Guide Version Issue 6 3 Index A AIDA 171 Algorithm 14 Base class 15 43 branches 50 Concrete 43 46 Constructor 45 47 Declaring properties 45 Execution 37 47 Filters 50 Finalisation 38 49 Initialisation 37 45 47 49 Nested 49 sequences 50 Setting properties 45 Algorithms EventCounter 51 113 Prescaler 51 Sequencer 50 Application Manager 15 instantiation 33
49. package installation see OnX doc to try some stand alone examples e GaudiLab installation e LHCb environment variables e The DISPLAY environment variable If all seem ok contact the GaudiLab support G Barrand barrand lal in2p3 fr Note that the GaudiLab package is at the top of a whole chain of packages and that a good behaviour relies on a good installation of the underlying packages 16 2 2 3 Starting the programs not being owner of the GaudiLab installation If you are not the owner of the GaudiLab installation for example wotking with the GaudiLab installed at CERN UNIX gt cd UNIX gt mkdir tmp UNIX gt cd tmp csh gt source lt path gt lt GaudiLab gt lt version gt cmt login_cern csh csh gt source lt path gt lt GaudiLab gt lt version gt cmt setup csh UNIX gt cp R GAUDILABROOT user UNIX gt cd user csh gt setenv ONXUI ogtk xml csh gt ogtk to start OnX gtk GUI manager On NT from a DOS prompt DOS gt mkdir tmp DOS gt cd tmp DOS gt call lt path gt lt GaudiLab gt lt version gt cmt setup bat DOS gt xcopy GAUDILABROOTS user DOS gt cd user DOS gt Sowin32 to start OnX Win32 GUI manager or if working with gtk today the most advanced GUI DOS gt set ONXUI ogtk xml DOS gt Sogtk to start OnX gtk GUI manager 16 2 3 Customization The user directory the GaudiLab one or a local copy contains the GaudiLab txt ogtk xml xml GUI file for gtk a
50. ppl log lt lt MSG INFO lt lt ppl lt lt endreq log lt lt MSG INFO lt lt Trying to find properties by name lt lt endreq ParticleProperty pp2 m_ppSvc gt find e if pp2 log lt lt MSG INFO lt lt pp2 lt lt endreq log lt lt MSG INFO lt lt Trying to find properties by StdHep ID lt lt endreq ParticleProperty pp3 m_ppSvc gt findByStdHepID 521 if pp3 log lt lt MSG INFO lt lt pp3 lt lt endreq Listing 57 Code fragment showing how to use the map iterators to access particle properties List all properties log lt lt MSG DEBUG lt lt Listing all properties lt lt endreq for IParticlePropertySvc const_iterator i m_ppSvc gt begin i m_ppSvc gt end i if i log lt lt i lt lt endreq page 124 GAUDI Chapter 11 Framework services User Guide Version Issue 6 3 11 6 The Chrono amp Stat service The Chrono amp Stat service provides a facility to do time profiling of code Chrono part and to do some statistical monitoring of simple quantities Stat part The service is created by default by the Application Manager with the name ChronoStatSvc and service ID extern const CLID amp IID _IChronoStatSvc To access the service from inside an algorithm the member function chronoSvc is provided The job Options to configure this service are described in Appendix B T
51. reading and writing Ntuples ParticleProperties Access the Particle Properties service to retrieve Particle Properties RandomNumber Example of use of the Random Number service Rio Example1 Two examples reading and writing persistent data with ROOT I O SimpleAnalysis A realistic example of using the framework for a physics analysis including access to Monte Carlo data creation of reconstructed data and filling an n tuple ToolsAnalysis Example of use of framework tools in an analysis page 42 GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 Chapter 5 Writing algorithms 5 1 Overview As mentioned previously the framework makes use of the inheritance mechanism for specialising the Algorithm component In other words a concrete algorithm class must inherit from be derived from in C parlance extend in Java the Algorithm base class In this chapter we first look at the base class itself We then discuss what is involved in creating concrete algorithms specifically how to declare properties what to put into the methods of the Algorithm interface the use of private objects and how to nest algorithms Finally we look at how to set up sequences of algorithms and how to control processing through the use of branches and filters 5 2 Algorithm base class Since a concrete algorithm object is an Algorithm object it may use all of the public methods of the Algorithm base class The ba
52. s access to data whether the data is coming from or going to a persistent store or whether it is coming from or going to another algorithm is always via one of the data store components The IDataProviderSvc interface allows algorithms to access data in the store and to add new data to the store It is discussed further in chapter 6 where we consider the data store components in more detail The histogram service is another type of data store intended for the storage of histograms and other statistical objects i e data objects with a lifetime of longer than a single event Access is via the IHistogramSvc which is an extension to the IDat aProviderSvc interface and is discussed in chapter 9 The n tuple service is similar with access via the INtupleSvc extension to the IDataProviderSvc interface as discussed in Chapter 10 In general an algorithm will be configurable It will require certain parameters such as cut offs upper limits on the number of iterations convergence criteria etc to be initialised before the algorithm may be executed These parameters may be specified at run time via the job options mechanism This is done by the job options service Though it is not explicitly shown in the figure this component makes use of the Property interface which is implemented by the Algorithm base class page 16 it GAUDI User Guide Chapter 2 The framework architecture Version Issue 6 3 During its execution an algorithm may
53. such an interface if it is derived from it for example class ConcreteComponent public PureAbstractClass method1 method2 A component which implements more than one interface does so via multiple inheritance however since the interfaces are pure abstract classes the usual problems associated with multiple inheritance do not occur These interfaces are identified by a unique number which is available via a global constant of the form IID_InterfaceType such as for example IID_IDataProviderSve Using these it is possible to enquire what interfaces a particular component implements as shown for example through the use queryInterface in the finalize method of the SimpleAnalysis example Within the framework every component e g services and algorithms has two qualities e A concrete component class e g TrackFinderAlgorithm or MessageSvc e Itsname e g KalmanFitAlgorithm or stdMessageService page 17 GAUDI User Guide Chapter 2 The framework architecture Version Issue 6 3 2 5 Package structure L Gaudi package L External package applications Package dependency E Optional dependency For large software systems such as ours it is clearly important to decompose the system into hierarchies of smaller and more manageable entities This decomposition can have important consequences for implementation related issues such as compile time link depend
54. tag collection as input data to his her application and perform sophisticated selections using the facilities existing in the data storage technology 1 Abstract Interfaces for Data Analysis http Avwwinfo cern ch asd lhc AIDA index html page 24 GAUDI User Guide Chapter 3 Release notes and software installation Version Issue 6 3 Detector description and geometry The framework provides facilities for describing the logical structure of the detector in terms of a hierarchy of detector elements and also the basic geometry description in terms of volumes solids and materials Facilities for customizing the generic description to many specific detector needs are also provided This should allow to develop detector specific code which can provide geometry answers to questions from the physics algorithms simulation reconstruction and analysis The persistent representation of the detector description is based on text files in XML format An XML editor that understands the detector description semantics has been developed A detailed description can be found in Chapter 8 A transport service is provided to estimate the amount of material between 2 arbitrary points in the detector setup Analysis services A number of facilities and services are included in the current release to facilitate writing physics analysis code The GaudiAlg package is a collection of general purpose algorithms including a sequencer which uses the new filtering
55. the ErrorMax limit set in the job option The framework the Algorithm base class calls the execute method within a try catch clause This means that any exception not handled in the execution of an Algorithm will be page 48 it GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 caught at the level of sysExecute implemented in the base class The behaviour on these exceptions is identical to that described above for errors Finalization The finalize method is called at the end of the job It can be used to analyse statistics fit histograms or whatever you like Similarly to initialization the framework invokes a sysFinalize method which in turn invokes the finalize method of the algorithm and of any sub algorithms Monitoring of the execution e g cpu usage of each Algorithm instance is performed by auditors under control of the Auditor service described in Chapter 11 This monitoring can be turned on or off with the boolean properties AuditInitialize AuditExecute AuditFinalize The following is a list of things to do when implementing an algorithm e Derive your algorithm from the Algorithm base class e Provide the appropriate constructor and the three methods initialize execute and finalize e Make sure you have implemented a factory by adding the magic two lines of code see 5 3 1 5 4 Nesting algorithms The application manager is responsible for initializing executing o
56. the banks and to convert the data into the appropriate classes This needs some initialization but not every SICB initialization step is followed The standard stream file and setup cdf are read in from the standard locations The program will have access to the data in the cdf files which were used to produce the DST e Sicb dat is not read in If you need to change the running conditions of your program do it using the jobOptions txt file or write your own cards file and read it in SUINIT e In Finclude you will find all the NAME _BANK INC and NAME_FUNC INC include files This means that you have access to the bank data with the usual utilities provided by SICB For example to access the momentum of the reconstructed track one can use as in SICB P AXTK P NOBJ e Futio includes most of the UT and UB routines which can therefore be used by FORTRAN code within Gaudi e Initialize the histogram files yourself in SUINIT Gaudi initializes the histogram service but this can be accessed only from C code 14 7 Handling pile up in Gaudi In this section we explain the pile up structure implemented in the Gaudi framework see Figure 30 Pile up in Gaudi is performed by a pile up algorithm An example PileUpAlg can be found in the package SicbCnv The pile up algorithm creates a second instance of the event selector which has to be configured in the job options file The leading event will be read in from the EventSelector
57. the corresponding Monte Carlo truth information that can appear explicitly in the event data model are pointers going from Raw data digitisings to the corresponding Monte Carlo hits Furthermore it has been decided that simulated raw data classes must inherit from the corresponding real data classes adding to the real data class a pointer to the Monte Carlo truth information The name of the derived simulation class is the same as that of the corresponding real data class prefixed by MC 7 4 Raw event The Raw event sub tree should contain the raw data collected by the data acquisition and simulated data in the same format i e with detector and electronics response applied The include files for the contained classes can be found in LHCbEvent Raw h with obvious names Currently only the classes RawInnerTrackerMeas and RawOuterTrackerMeas are implemented which are for the time being copies of the SicB banks WIDG and WODG Table 7 Raw Event data model Logical Path Container Type 7 Event Raw RawOuterTrackerMeas RawOuterTrackerMeas Vector 7 Event Raw RawInnerTrackerMeas RawiInnerTrackerMeas Vector 7 5 Reconstructed event The Reconstructed event sub tree is meant to contain the output of the reconstruction program It is currently empty page 67 GAUDI Chapter 7 LHCb Event Data Model User Guide Version Issue 6 3 7 6 Analysis event The Analysis event sub tree should contain the ob
58. the data services is simple but extensive status checking and other things tend to make the code difficult to read It would be more convenient to access data items in the store in a similar way to accessing objects with a C pointer This is achieved with smart pointers which hide the internals of the data services 6 8 1 Using SmartDataPtr SmartDataLocator objects The SmartDataPtr anda SmartDataLocator are smart pointers that differ by the access to the data store SnartDataPtr first checks whether the requested object is present in the transient store and loads it if necessary similar to the ret rieveOb ject method of IDataProviderSvc SmartDataLocator only checks for the presence of the object but does not attempt to load it similar to findObject Both SmartDataPtr and SmartDataLocator objects use the data service to get hold of the requested object and deliver it to the user Since both objects have similar behaviour and the same user interface in the following only the SmartDataPtr is discussed An example use of the SmartDataPtr class is shown below Listing 16 Use of a SmartDataPtr object 1 StatusCode myAlgo execute 2 MsgStream log msgSvc name 3 SmartDataPtr lt Event gt evt eventSvc Event 4 if evt J A 5s Print the event number 6 log lt lt MSG INFO lt lt Run lt lt evt gt run Fe lt lt Event lt lt evt gt event lt lt endreq 8
59. the sub detector in question and uses a set of common services The detector description we are providing in Gaudi is nothing else than a framework for developers to provide the specific detector information to algorithms by using as much as possible common or generic services In the following sections we begin with an overview of the DDDB We then discuss how to access the detector description data in the Gaudi transient detector data store This is followed by a discussion of the logical structure of the Gaudi detector description We then describe in detail how the detector decription can be built and made persistent using the XML markup language and finish with an introduction to an XML editing tools which allows browsing and modification of the DDDB Please note that some new features of the detector description available in this release of Gaudi e g the SolidTrap volume have not yet been documented in this chapter 8 2 Detector Description Database The detector description database DDDB see Figure 9 includes a physical and a logical description of the detector The physical description covers dimensions shape and material of the different types of elements from which the detector is constructed There is also page 69 it GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 information which corresponds to each element which is actually manufactured and assembled into a detector for example the position
60. which the component will be informed of the incident in case several components are listeners of the same named incident This parameter is used by the Incident Svc to sort the listeners in order of priority 11 9 1 Known Incidents Table 11 Table of known named incidents I Incident Type Source Description BeginEvent ApplicationMgr The ApplicationMegr is starting processing of anew physics event This incident can be use to clear caches of the previous event in Serv ices and Tools EndEvent ApplicationMgr The ApplicationMegr has finished processing the physics event The Event data store is not yet purged at this moment page 133 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 11 10 Developing new services 11 10 1 The Service base class Within Gaudi we use the term Service to refer to a class whose job is to provide a set of facilities or utilities to be used by other components In fact we mean more than this because a concrete service must derive from the Service base class and thus has a certain amount of predefined behaviour for example it has initialize and finalize methods which are invoked by the application manager at well defined times Figure 23 shows the inheritance structure for an example service called SpecificService The key idea is that a service should derive from the Service base class and additionally implement one or more pure abstract classe
61. 1 and updated for Calo The current status is presented in Chapter 7 Event data persistent storage The current version supports event data files or tapes as input produced by SICB in ZEBRA format RZ The ZEBRA banks are converted to C objects by specialized fragments of code SICB converters This conversion is available in the framework for a number of SICB banks Adding more converters is possible and will be done on request The event data produced by the application can be stored in ROOT files and retrieved later This also requires to write specialized converters The DBCnv package is included to help the user to make objects persistent Refer to Chapter 13 for more details Histograms amp N tuples The framework provides facilities for creating histograms 1 and 2 dimensional and n tuples row and column wise from user algorithms The histogram interface is the AIDA common interface Saving histograms and n tuples is currently implemented using the HROOK and ROOT format The interface to histograms and n tuples from the user code should not be affected if the persistency representation is changed later Details of the histogram and n tuple facilities can be found in Chapter 9 and 10 respectively Event tag collections The framework provides facilities for creating and using collections of event tags for fast direct access to physics events The event tag collections are based on an n tuples implementation The user can specify an event
62. 143 UNIQUE within LHCb page 135 GAUDI Chapter 11 Framework services User Guide Version Issue 6 3 Listing 61 A minimal service implementation include Gaudi Kernel Service h include IConcreteSvcTypel h include IConcreteSvcType2 h class SpecificService public Service virtual public IConcreteSvcTypel virtual public IConcreteSvcType2 public Constructor of this form required SpecificService const std string amp name ISvcLocator sl queryInterface constIID amp riid void ppvIF Factory for instantiation of service objects static SvcFactory lt SpecificService gt s_factory const ISvcFactory amp SpecificServiceFactory s_factory UNIQUE Interface identifiers defined elsewher extern const IID amp IID_IConcreteSvcTypel extern const IID amp IID_IConcreteSvcType2 queryInterface StatusCode SpecificService queryInterface const IID amp riid if IID_IConcreteSvcTypel riid xppvIF dynamic_cast lt IConcreteSvcTypel gt this return StatusCode SUCCESS else if IID_IConcreteSvcType2 riid xppvIF dynamic_cast lt IConcreteSvcType2 gt this return StatusCode SUCCESS else return Service queryInterface riid ppvIF StatusCode SpecificService initialize StatusCode SpecificService finalize Implement the specifics SpecificService methodl SpecificService met
63. 3 Chapter 7 LHCb Event Data Model In this chapter we present the structure of the LHCb Event Data model For the moment only a small part of the model is implemented in the public release Various sub detector specific parts are under development and are implemented in private code The table at http cern ch lhcb comp Support html ConvertedSICBBanks htm shows the current implementation status by comparison with SICB banks 7 1 Glossary Event data is logically subdivided in sub events that are the results of a processing step The following glossary is extracted from reference 6 MC Event is the output of the physics event simulation This typically includes MC Particles and MC Vertices MC Hits are the output of the GEANT tracking step They typically include detector entrance and exit point energy loss etc FE data is the simulated output of the detector front end as seen by the hardware triggers when this is different from Raw data Raw data is the output of the digitisation step of the detector simulation and the output of the data acquisition system for real data For example ADC and TDC counts Coordinates are the output of the reconstruction program when applied to detector hits This typically consists of hit coordinates calorimeter clusters etc Reconstructed data is the final output of the reconstruction program This typically consists of tracks particle ID energy flow objects etc Analysis data is the ou
64. 8 Listing 58 Example of the use of the random number generator to fill a histogram with a Gaussian distribution within a standard Gaudi algorithm Rndm Numbers gauss randSvc Rndm Gauss 0 5 0 2 if gauss THistogram1D his histoSvc gt book stat 2 Gaussian 40 0 3 for long i 0 i lt 5000 i his gt fill gauss 1 0 Du FPF WN EP e One or several random numbers are required for the processing of every event An example is shown in Listing 59 Listing 59 Example of the use of the random number generator within a standard Gaudi algorithm for use at every event The wrapper to the generator is part of the Algorithm itself and must be initialized before being used Afterwards the usage is identical to the example described in Listing 58 include Gaudi RandmGenSvc RndmGenerators h Constructor class myAlgorithm public Algorithm Rndm Numbers m_gaussDist Initialisation StatusCode myAlgorithm initialize ere DNAOBRWNHFPRPOOCO AND VU BKRWNeE StatusCode sc m_gaussDist initialize randSvc Rndm Gauss 0 5 0 2 if status isSuccess put error handling code here There are a few points to be mentioned in order to ensure the reproducibility e Do not keep numbers across events If you need a random number ask for it Usually caching does more harm than good If there is a performance penalty it is better to find a more generic solution e
65. 8 064 COMP 2 GAUDI online code documentation http cern ch LHCbSoft GaudiSys v6 doc html index html 3 GAUDI User Requirements Document LHCb 98 065 COMP 4 LHCb Physical Units Convention http cern ch lhcb comp Reconstruction Conventions units pdf 5 LHCb coding conventions LHCb 98 049 COMP 6 LHCb Event Data Model Conventions http cern ch lhcb comp Reconstruction Conventions DataModel Event Data pdf page 187 GAUDI Appendix A References User Guide Version Issue 6 3 page 188 GAUDI Appendix B Options for standard components User Guide Version Issue 6 3 Appendix B Options for standard components The following is a list of options that may be set for the standard components e g data files for input print out level for the message service etc The options are listed in tabular form for each component along with the default value and a short explanation The component name is given in the table caption thus ComponentName Table B 1 Standard Options for the Application manager ApplicationMgr Option name Default value Meaning EvtSel ik NONE if no event input EvtMax 1 Maximum number of events to process The default is 1 infinite unless EvtSel NONE in which case it is 10 TopAlg List of top level algorithms Format lt Type gt lt Name gt lt Type2 gt lt Name2 gt ExtSve List of external services names
66. A stands for parsed character data which is text Listing 24 shows the XML definition of the Vertex detector containing the author of this definition the version geometry information about the associated logical volume and two sub detectors of the LHCb detector The example shows that the definition of the VertexStation sub detectors can be found in the file vertex xml The standard class ID for detector element is 2 but here the class ID is set to 9999 which means that this sub detector is customized by the user and contains specific information in which XML tags to describe specific features the detector have been defined by the user The customizing of detector elements is described in section 8 5 3 The geomet ryinfo element definition says that the Vertex detector has an associated logical volume with the given name on the transient store The logical volume should be defined somewhere else in the XML and is retrieved automatically when the user asks for it via the IGeometryInterface returned by the geomet ry accessor method There two more tags in the geometryinfo definition They are supporting detector element and its replica path The supporting detector element is one of the parent detector elements sitting on the same 1 Text format of PCDATA content in XML is verbatim so all white space characters are preserved page 81 GAUDI Chapter 8 Detector Description User Guide Version Issue 6 3
67. AILURE if idTo MCParticle classID objTo 0 return StatusCode FAILURE ara OF WN EF The i_retrieveInverse method providing the one to many association returns a failure while a fake implementation of the one to many i_ret riveDirect method is implemented in the example to show how an Algorithm can use such method In the AxPart2MCParticleAsct example the inverse table is kept locally and both the buildiInverse and flushCache methods are overridden In the example the choice has been made to implement an additional method buildDirect to retrieve the direct navigational information on a first request per event basis In Listing 72 it is shown how a monitoring Algorithm can get an associator from the ToolSvc and use it to retrieve associated objects through the template interfaces page 148 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 I Listing 72 Extracted code from the AsctExampleAlgorithm 1 include GaudiTools IAssociator h 2 Example of retrieving an associator 3 IAssociator 4 StatusCode sc toolsvc gt retrieveTool AxPart2MCParticleAsct m_pAsct Ss if sc isFanlure y p 6 log lt lt MSG FATAL lt lt Unable to create Associator tool lt lt endreq 73 return sc 8 9 Example of retrieving inverse one to one information from an 10 associator 11 SmartDataPtr lt MCParticleVector gt vmcparts
68. AILURE Report the material and its radiation length ILVolume stvol vs gt geometry gt lvolume log lt lt MSG INFO lt lt vs gt fullpath lt lt is made of lt lt stvol gt materialName lt lt with radiation length lt lt stvol gt material gt radiationLength lt lt endreq Retrieve the shape information const ISolid stsolid stvol gt solid Get the rotation and translation HepTransform3D sttrans vs gt geometry gt matrixiInv HepRotation strot sttrans getRotation Hep3Vector stvec sttrans getTranslation 8 4 General features of the geometry tree The construction of the geometry tree within the Gaudi framework is based on the following postulates e The geometry tree is constructed from Logical Volumes and Physical Volumes 1 This operation can be time consuming page 73 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 e There are no up links in the geometry tree It means that each node has no information about the up or parent mother node e Each Logical Volume has a information about its down children nodes represented by Physical Volumes e Each Logical Volume has information about its shape and dimensions Solid e Each Logical Volume has access to information about the material content e Neither Logical Volumes nor Physical Volumes have any information ab
69. ApplicationMgr See Application Manager Architecture 13 Associators 145 Example 147 B Branches 50 C Casting of DataObjects 55 Changes in the new release 25 incompatible in this release 26 Checklist for implementing algorithms 49 Class identifier CLID 60 CLHEP 171 Units 8 page 211 GAUDI Index User Guide Version Issue 6 3 CMTPATH to get development version of packages 29 Component 13 Library 20 ContainedObject 57 Conventions 8 Coding 9 Naming 10 of MC truth classes 67 Units 8 used in this this document 10 Converters 151 SICB Converters 163 D Data Model LHCb 53 Data Store 53 Detector data 71 Event data 66 finding objects in 55 61 Histograms 95 registering objects into 56 DataObject 15 53 55 56 ownership 56 E Editor of XML detector descripton files 92 endreq MsgStream manipulator 121 Event Collections 104 Filling 106 Reading Events with 106 Writing 105 Event Data Model 65 EventCounter algorithm See Algorithms Example Application Main program 32 Trace of execution 33 Examples Associator 147 distributed with Gaudi 42 HistoAlgorithm 36 Simple Analysis 39 Exception when casting 55 F Factory for a concrete algorithm 45 page 212 GAUDI Index User Guide Version Issue 6 3 Filters 50 FORTRAN 14 linking with 21 G GaudiLab 174 GEANT4 units 8 Glossary Event Data 65 H HBOOK Constrain
70. CALenergyCuts push_back 0 0 16 m_ECALenergyCuts push_back 0 6 Tihs Lot declareProperty PassAllMode m_passAllMode Loe declareProperty MuonCandidateCut m_muonCandidateCut 20 declareProperty ECALEnergyCuts m_ECALEnergyCuts Zils i 22 23 StatusCode TriggerDecision initialize 24 page 46 GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 The default values for the variables are set within the constructor within an initializer list as per normal To declare them as properties it suffices to call the declareProperty method This method is overloaded to take an std string as the first parameter and a variety of different types for the second parameter The first parameter is the name by which this member variable shall be referred to and the second parameter is a reference to the member variable itself In the example we associate the name PassAl1Mode to the member variable m_passAllMode and the name MuonCandidateCut to m_muonCandidateCut The first is of type boolean and the second an integer If the job options service described in Chapter 11 finds an option in the job options file belonging to this algorithm and whose name matches one of the names associated with a member variable then that member variable will be set to the value specified in the job options file 5 3 3 Implementing lAlgorithm In order to implement IAlgorithm you
71. Check if the statement ends with a semicolon Runtime Error 012 Cannot append to object because it does not exists The compiler cannot append the values to the object prop ertyname because the object does not exist Check if the refered object is defined in one of the included files if so check if you writed the object name exactly like in the include file Runtime Error 013 Cannot append to object because Property does not exists The compiler cannot append the values to the object prop ertyname because the prop erty does not exist Check if there was already something assigned to the ref ered property in the include file or in the current file If not then modify the append statement into a assign statement If there was already some thing assigned check if the object name and the prop erty name are typed correctly GAUDI Appendix C Job Options Grammar and Error Codes User Guide Version Issue 6 3 Table 12 Possible Error Codes Error Code Reason How to avoid it Error 014 Elements in the vector are not of the same type One or more elements in the vector have a different type than the first element in the vector All elements must have the same type like the first declarated element Check declaration of vector check the types and check if maybe a value is mistyped Error 015 Value s expected The compiler didn t find val ues
72. CnvSvcName AUTH login For SICB data FILE xxxxx JOBID yyyy FirstEvent 1 First event to process allows skipping of preceding events EvtMax All events on Application Maximum number of events to process Mgr EvtSel input stream PrintFreq 10 Frequency with which event number is reported JobInput Ace String of input files same format as ApplicationMgr EvtSel used only for pileup event selector s Table B 14 Event Tag Collection Selector EventCollectionSelector Option name Default value Meaning CnvService EvtTupleSve Conversion service to be used Authentication m Authentication to be used Container B2PiPi Container name Item Address Item name Criteria att Selection criteria DB hg Database name DbType a Database type Function NTuple Selector Selection function Table B 15 Standard Options for Sicb Pileup Algorithm PileUpAlg Option name Default value Meaning PileUpMode wi Pileup mode Possible values LUMISIGNAL Luminosity weighted for signal leading event LUMIMINBIAS LUMI Luminosity weighted for minimum bias lead ing event Table B 16 Standard Options for Particle Property Service ParticlePropertySvc Option name Default value Meaning ParticlePropertiesFile LHCBDBASE cdf particle cdf Particle properties database location page 193 GAUDI A
73. D are derived from IHistogram and use by reference the IAxis interface Users can book their 1D or 2D histograms in the histogram data store in the same type of tree structure as the event data Concrete 1D and 2D histograms derive from the Dat aOb ject in order to be storable page 95 GAUDI Chapter 9 Histogram facilities User Guide Version Issue 6 3 Histograms IHistogram IHistogram1D IHistogram2D AN TYPE TYPE L1D_ F L2D_ GenHisto1D DataQblect GenHisto2D 12 eat Q 1 1 1 IA xis a J BX 1 S iN 5 Axis TYPE1D AS H1D and H1DVar are currently H1D the only two implem ented specializations of GenHisto1D H1iDVar H2D is currently the only one implemented specialization of GenHisto2D TYPE2D Figure 21 Histograms data model 9 2 The Histogram service An instance of the histogram data service is created by the application manager After the service has been initialised the histogram data store will contain a root directory stat in which users may book histograms and or create sub directories for example in the code fragment below the histogram is stored in the subdirectory stat simple A suggested naming convention for the sub dire
74. Do not access the RndmEngine directly e Do not manipulate the engine The random seeds should only be set by the framework on an event by event basis page 132 GAUDI Chapter 11 Framework services User Guide Version Issue 6 3 11 9 The Incident Service The Incident service provides synchronization facilities to components in a Gaudi application Incidents are named software events that are generated by software components and that are delivered to other components that have requested to be informed when that incident happens The Gaudi components that want to use this service need to implement the IIncident Listener interface which has only one method handle Incident and they need to add themselves as Listeners to the IncidentSvc The following code fragment works inside Algorithms class MyAlgorithm MyAlgorithm Initialize IIncidentSvc incsvc public Algorithm virtual public IIncidentListener StatusCode sc servic int priority 100 if sc isSuccess incsvc gt addListener incsvc gt addListener lt lt generated by MyAlgorithm handle Incident amp inc log lt lt Got informed of incident IncidentSvc incsvc this this BeginEvent End priority Event lt lt inc type lt lt inc source lt lt endreq The third argument in method addListener is for specifying the priority by
75. GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 e Do not delete objects that you have registered e Do not delete objects that are contained within an object that you have registered e Do not register local objects i e objects NOT created with the new operator e Do not delete objects which you got from the store via findObject or retrieveObject e Do delete objects which you create on the heap i e by a call to new and which you do not register into a store 6 7 Defining new data types Most of the data types which will be used within Gaudi will be used by everybody and thus packaged and documented centrally However for your own private development work you may wish to create objects of your own types which of course you can always do with C or Java However if you wish to place these objects within a store either so as to pass them between algorithms or to have them later saved into a database or file then you must derive your type from either the Dat aObject or ContainedOb ject base class Consider the example below const static CLID CLID_UDO 135 Collaboration wide Unique number class UDO public DataObject public UDO DataObject m_n 0 static const CLID amp classID return CLID_UDO virtual const CLID amp clID const return classID int n return m_n void setN int n mn n private int m_n This defines a class
76. Issue 6 3 Listing 2 The example main program 21 Include files 22 include Gaudi Kernel SmartIF h 23 include Gaudi Kernel Bootstrap h 24 include Gaudi Interfaces IAppMgrUI h 25 include Gaudi Interfaces IProperty h 26 include Gaudi JobOptionsSvc Property h Zhao off 28 Package Gaudi Examples 29 Description Main Program 30 31 32 Example main program 33 int main int argc char argv 34 39 8 StatusCode status StatusCode SUCCESS 36 37 Create an instance of an application manager 38 IInterface iface Gaudi createApplicationMgr 39 40 Smart IF lt IProperty gt propMgr IID_IProperty iface 41 SmartIF lt IAppMgrUI gt appMgr IID_IAppMgrUI iface 42 43 Set properties of algorithms and services 44 if propMgr iface 453 std string opts argce gt 1 argv 1 jobOptions txt 46 status propMgr gt setProperty StringProperty JobOptionsPath JobOptions txt Als 48 else 49 exit 0 50 51 2 52 Run the application manager and process events bat if appMgr 54 status appMgr gt run 55 564 else Bit return 0 58 59 60 All done exit 6f return 0 62 page 34 GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 Listing 3 The job options file for the Histograms example application NNN NNNN DN LDH
77. Jan 01 Add first two lines of code listing 76 page 2 GAUDI Table of Contents User Guide Version Issue 6 3 Table of Contents Document Control Sheet 2 Document Status Sheet 2 Chapter 1 Introduction 7 1 1 Purpose of the document 7 1 2 Conventions 8 1 3 Reporting problems 10 1 4 Editor s note 11 Chapter 2 The framework architecture 13 2 1 Overview 13 2 2 Why architecture 13 2 3 Data versus code 14 2 4 Main components 15 2 5 Package structure 17 Chapter 3 Release notes and software installation 23 3 1 Release History 23 3 2 Current Functionality 23 3 3 Changes in the new release 25 3 4 Availability 27 3 5 Using the framework on NT with Deisienee Studio 27 3 6 Using the framework in Unix 27 3 7 Working with development releases 28 Chapter 4 Getting started 31 4 1 Overview 31 4 2 Creating a job 31 4 3 The main program 32 4 4 Configuring the job 33 4 5 Algorithms 36 4 6 Job execution 39 4 8 Other examples cibus with Gaudi 42 Chapter 5 Writing algorithms 43 5 1 Overview 43 page 3 GAUDI Table of Contents User Guide Version Issue 6 3 5 2 Algorithm base class 5 3 Derived algorithm classes 5 4 Nesting algorithms Pye 5 5 Algorithm sequences beaches ai filters Chapter 6 Accessing data 6 1 Overview 6 2 Using the data stores 6 3 Using data objects 6 4 Object containers 6 5 Using object containers 6 6 Dat
78. LAST in finalize Implementing these three routines allows you to write code in FORTRAN and have it called from within Gaudi in particular to import routines already written in SICB Note however that there are some points that should be kept in mind when importing SICB code into Gaudi The following list is far from being complete but we hope that it will help anyone using the Fort ranAlgorithm It may be updated in the future with the user s experiences and our own findings e Gaudi is linked with only two sub packages of SICB Finclude and Fut io This means that taking some code from SICB and running it successfully in Gaudi will not always be straight forward Every case will have to be studied separately In some cases you may find that the effort required to make the code compatible with Gaudi page 166 it GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 is comparable to writing it directly in C For some pieces of code the integration into Gaudi may be very simple The difficulties will come mainly from dependencies of the code you want to include on other parts of SICB For instance there may be common blocks which your code needs but which are never initialized e As most of SICB is not executed you will have either to include and execute the required initialization or to try to eliminate those dependencies e Gaudi uses SICB to access the data in the DST s to extract the information from
79. LHCb GAUDI LHCb Data Processing Applications Framework User Guide Version 6 Issue 3 Edition 0 Status ID Date 8 January 2001 European Laboratory for Particle Physics Laboratoire Europ en pour la Physique des Particules m CH 1211 Gen ve 23 Suisse GAUDI 8 January 2001 User Guide Version Issue 6 3 Document Control Sheet Table 1 Document Control Sheet Document Title GAUDI User Guide Version 6 Issue 3 Edition 0 ID Date 8 January 2001 Keywords Tools DTP System Adobe FrameMaker Version 5 5 Layout Software Documentation Version V1 15 January 1999 Template Layout Templates Authorship Coordinator M Cattaneo from October 1999 P Maley until September 1999 Document Status Sheet Table 2 Document Status Sheet Title GAUDI User Guide ID Version Issue Date Reason for change 1 0 7 Feb 99 First official non draft version 1 1 10 Feb 99 Minor corrections to installation chapter 2 0 18 Jun 99 Release of version 2 of the GAUDI framework 3 0 24 Nov 99_ Release of version 3 of the GAUDI framework 4 1 14 Apr 00 Release of version 4 of the GAUDI framework 5 0 24 Jul 00 Release of version 5 of the GAUDI framework 5 1 26 Jul 00 Corrections to chapters 4 and 5 6 0 15 Nov 00 Release of version 6 of the GAUDI framework 6 1 27 Nov 00 Update chapter 8 and section 3 3 1 6 2 5 Dec 00 Corrections to section 6 10 Appendix B 6 3 8
80. Listing 24 Example of a detector element definition in XML lt xml version 1 0 lt DOCTYPE DDDB SYSTEM lt DDDB gt lt author gt Author lt geometryinfo gt ncoding UTF 8 gt xmldb dtd gt ame lt author gt lt version gt 0 1 lt version gt lt lvnam lt support gt lt geometryinfo gt lt detelem gt lt DDDB gt lt detelemref classID lt detelemref classID 9999 9999 name dd Geometry lvVertex gt lt support name dd Structure LHCb gt lt npath value pvVertex gt lt detelem classID 2 name Vertex type passive gt href vertex xml VertexStation01 gt href vertex xml VertexStation02 gt branch in the logical detector description hierarchy It can be a direct parent or a detector element 3 levels up Its role is to help in finding of physical volume location in the geometry hierarchy for the detector element which is referring to it The replica path is a sequence of numbers which is used by the algorithm looking for the physical volume location in the geometry hierarchy This sequence is composed of the number of daughter volume IDs which must be followed from a logical volume of supporting detector elements down through the hierarchy If it is in numeric form rpath then it must start counting from 0 If it is in the literal form npath it can be a text label but it must be unique inside the mother logical volume where it is defined and used
81. Ou StatusCode finalize 10 private 11 IntegerProperty m_frequency 12 int m_skip 13 int m_total Las J page 113 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 Listing 53 EventCounter cpp AANA UOUPWNHR CU WANA UO fPWN EF ND t Or O 21s 22 23 24 29 26 Zs include GaudiAlg EventCounter h include Gaudi MessageSvc MsgStream h include Gaudi Kernel AlgFactory h static const AlgFactory lt EventCounter gt Factory const IAlgFactory amp EventCounterFactory Factory EventCounter EventCounter const std string amp amp name ISvcLocator pSvcLocator Algorithm name pSvcLocator m_skip 0 m_total 0 declareProperty Frequency m_frequency 1 1 m_frequency setBounds 0 1000 2 StatusCode EventCounter initialize MsgStream log msgSvc name log lt lt MSG INFO lt lt name lt lt EventCounter initialize Frequency lt lt m frequency lt lt endreq 3 return StatusCode SUCCESS Notes 1 A default value may be specified when the property is declared 2 Optional upper and lower bounds may be set see later 3 The value of the property is accessible directly using the property itself In the Algorithm constructor when calling declareProperty you can optionally set the bounds using any of setBounds const T amp lower const T amp uppe
82. Output File Specification in a number of storage technologies In following line in the job options file Conversion services exist to convert n tuple objects into a form suitable for persistent storage order to use this facility it is necessary to add the 11 DATAF FI FILE2 NTupleSvc Output r FILE muse TYP HBOOK OPT NI Ew ILE tuples hbook where lt tuples hbook gt should be replaced by the name of the file to which you wish to write the n tuple FILE1 is the logical name of the output file it could be any other string A similar option NIupleSvc Input exists for n tuple input The following is a complete overview of all possible options DATAFILE lt file specs gt Specifies the datafile file name of the output stream TYP lt typ spec gt Specifies the type of the output stream Currently supported types are MS Access Write as a HBOOK Write in HBOOK RZ format ROOT Write as a ROOT tree Microsoft Access database There is also weak support for the following database types SQL Server page 103 GAUDI User Guide Chapter 10 N tuple and Event Collection facilities Version Issue 6 3 e MySQL e Oracle ODBC These database technologies are supported through their ODBC interface They were tested privately on local installations However all these types need special setup to grant access to the database Except
83. RootCnv v2 HbookCnv v4 DestDesc v1 GaudiExamples v5 vl 5 2 1999 Gaudi v1 LHCbEvent v1 SicbCnv v1 HbookCnv v1 GaudiExam ples v1 3 2 Current Functionality We use an incremental and iterative approach for producing the Gaudi software We started in the first release with very basic functionality and we plan to expand its capabilities release by release The basic functionality offered in the first release allowed you to read the already generated SICB Monte Carlo data sets ZEBRA files The data in these files is used to build C objects which can be used as input for the new software page 23 GAUDI User Guide Chapter 3 Release notes and software installation Version Issue 6 3 Release v3 incorporated most of the essential features which are needed for developing data processing applications reconstruction analysis etc This functionality was enhanced in Releases v4 and v5 and has been further enhanced in the current release The functionality list that follows is organized by categories Interfaces A set of interfaces that facilitates the interaction between the different components of the framework Mainly these are interfaces to services Basic framework services This set of services offer the minimal functionality needed for constructing applications They are described in detail in Chapter 11 The message service is used to send and format messages generated in the code with an associate
84. Svc specific interface providing methods to retrieve tools The interface has two ret rieve methods that differ in their parameters signature as shown in Listing 65 Listing 65 The IToolSvc interface methods 1 virtual StatusCode retrieve const std string amp type IAlgTool amp tool const IInterface parent 0 bool createlIf true 0 2 virtual StatusCode retrieve const std string amp type const std string amp name IAlgTool tool const IInterface parent 0 bool createlIf true 0 The arguments of the method shown in Listing 65 line 1 are the tool type i e the class and the IAlgTool interface of the returned tool In addition there are two arguments with default values one is the I Interface of the component requesting the tool the other a boolean creation flag If the component requesting a tool passes a pointer to itself as the third argument it declares to the Tool Svc that is asking a private instance of the tool By default a shared instance is provided In general if the requested instance of a Tool does not exist the ToolSvc will create it This behaviour can be changed by setting to false the last argument of the method The method shown in Listing 65 line 2 differs from the one shown in line 1 by an extra argument a string specifying the tool dependent part of the full tool name This enables a component to request two separately configurable instances of the sa
85. TYP ROOT ApplicationMgr DLLs ApplicationMgr ExtSvc DbConverters RootDb DbEventCnvSvc RootEvtCnvSvc EventPersistencySvc CnvServices RootEvtCnvSvc RootEvtCnvSvc DbType ROOT The first option tells the application manager that you wish to create an output stream called DstWriter You may create as many output streams as you like and give them whatever name you prefer For each output stream object which you create you must set several properties The ItemList option specifies the list of paths to the objects which you wish to write to this output stream The number after the symbol denotes the number of directory levels below the specified path which should be traversed The optional EvtDataSvc option specifies in which transient data service the output stream should search for the objects in the ItemList the default is the standard transient event data service EventDataSvc The Output option specifies the name of the output data file and the type of persistency technology ROOT in this example The last three options are needed to tell the Application manager to instantiate the RootEvtCnvSvc and to associate the ROOT persistency type to this service An example of saving data to a ROOT persistent data store is available in the Rio Examplel distributed with the framework page 64 GAUDI User Guide Chapter 7 LHCb Event Data Model Version Issue 6
86. This label is internally converted into its proper numeric equivalent at run time 8 5 2 3 Defining logical volumes To define a logical volume in XML the logvol element is used see Figure 14 union 1 DI 0 physvol name ID S T i cee logvol gt name ID gee logvol CDATA subtraction OR _ name ID i name ID i OR _ Sareea CDATA 1100 paramphysvol ao material CDATA aes 0 number CDATA intersection K OR M D A OR i 1 S lt OR 7 OR OR name ID we Sy lt 1y 1 Nd Sd box cons trd tubs SY sphere name ID name ID name ID name ID name 1D sizeX CDATA sizeZ CDATA si Z CDATA szeZ CDATA sizeZ CDATA sizeY CDATA outerRadiusPZ CDATA si X1 CDATA startPhiAngk C DATA o terRadius GDATA sizeZ CDATA innerRadiusPZ CDATA si X2 CDATA deltaPhiAngle CDATA innerRadius CDATA startPhiAngle CDATA si Y1 CDATA outerRadius CDATA startPhiAngle CDATA outerRadiusMZ CDATA si Y2 CDATA innerRadius CDATA deltaPhiAngle CDATA innerRadiusMZ CDATA startThetaAngle CDATA deltaPhiAngle CDATA deltaThetaAngle CDATA Figure 14 Content model definition of logvol element page 82 it User Guide Chapter 8 Detector Description Version Issue 6 3 The complete logical volume definition includes the n
87. UDO which since it derives from Dat aOb ject may be registered into say the event data store The class itself is not very useful as its sole attribute is a single integer and it has no behaviour The thing to note here is that if the appropriate converter is supplied as discussed in Chapter 13 then this class may also be saved into a persistent store e g a ROOT file or an Objectivity database and read back at a later date In order for the persistency to work the following are required the unique class identifier number CLID_UDO in the example and the cl ID and classID methods which return this identifier page 60 it GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 The procedure for allocating unique class identifiers in LHCb and the list of already allocated identifiers are available at http cern ch lhcb comp Support html CLID htm Types which are derived from ContainedOb ject are implemented in the same way and must have a CLID in the range of an unsigned short Contained objects may only reside in the store when they belong to a container e g an Ob ject Vector lt T gt which is registered into the store The class identifier of a concrete object container class is calculated at run time from the type of the objects which it contains by setting bit 16 The static classID method is required because the container may be empty 6 8 The SmartDataPtr SmartDataLocator utilities The usage of
88. XML definition of a material compound and mixture lt xml version 1 0 encoding UTF 8 gt lt DOCTYPE DDDB SYSTEM materials dtd gt lt DDDB gt lt material name Water density 1 0000 amp g amp cm3 gt lt materialref href Hydrogen gt lt natoms value 2 gt lt materialref gt lt materialref href Oxygen gt lt natoms value 1 gt lt materialref gt lt material gt lt material name Argon_CF_4 CO_2 density 2 14160 amp g amp cm3 gt lt materialref href CO_2 gt lt fractionmass value lt material gt lt DDDB gt E 3 lt materialref href CF_4 gt lt fractionmass value 0 2 gt lt materialref gt 0 5 gt lt materialref gt lt materialref href Argon gt lt fractionmass value 0 3 gt lt materialref gt page 86 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 8 5 3 Customizing a detector element The specific detector description can be made available to algorithms by customizing the generic detector element Customizing is done by inheriting the specific detector class from the generic DetectorElement The sub detector specialist can provide specific answers to algorithms based on a combination of common parameters general geometry material etc and some specific parameters For example an algorithm may want to know what are the coordina
89. a access checklist 6 7 Defining new data types 6 8 The SmartDataPtr sin avs Data neat aliis 6 9 Smart references and Smart reference vectors 6 10 Saving data to a persistent store Chapter 7 LHCb Event Data Model 7 1 Glossary bbe 7 2 Top level event data structures 7 3 Monte Carlo event 7 4 Raw event 7 5 Reconstructed event 7 6 Analysis event 7 7 Utilities Chapter 8 Detector Description 8 1 Overview 8 2 Detector DERO DRD 8 3 Using the Detector Data transient store 8 4 General features of the geometry tree 8 5 Persistent representation Chapter 9 Histogram facilities 9 1 Overview 9 2 The Histogram service 9 3 Using histograms and the histogram service 9 4 Persistent storage of histograms Chapter 10 N tuple and Event Collection facilities 43 45 49 50 53 53 53 55 56 58 59 60 61 61 62 65 65 66 66 67 67 68 68 69 69 69 71 73 75 95 95 96 97 98 99 page 4 GAUDI Table of Contents User Guide Version Issue 6 3 10 1 Overview 99 10 2 N tuples and the N Japie S 99 10 3 Event Collections 2 104 10 4 Interactive Analysis using Nedapies 108 10 5 Known Problems 110 Chapter 11 Framework services 111 11 1 Overview f 111 11 2 Requesting and accessing services 111 11 3 The Job Options Service 113 11 4 The Standard Message Service 119 11 5 The Particle Properties Service 122 11 6 The Chrono amp Stat se
90. able B 19 11 6 1 Code profiling Profiling is performed by using the chronoStart and chronoStop methods inside the codes to be profiled e g IChronoStatSvc svc chronoSvc start svc gt chronoStart Some Tag here some user code are placed stop svc gt chronoStop SomeTag The profiling information accumulates under the tag name given as argument to these methods The service measures the time elapsed between subsequent calls of chronoStart and chronoStop with the same tag The latter is important since in the sequence of calls below only the elapsed time between lines 3 and 5 lines and between lines 7 and 9 lines would be accumulated 1 svce gt chronoStop Tag 2 svce gt chronoStop Tag 3 svc gt chronoStart Tag 4 sve gt chronoStart Tag 5 sve gt chronoStop Tag 6 svce gt chronoStop Tag 7 svce gt chronoStart Tag 8 svc gt chronoStart Tag 9 svce gt chronoStop Tag The profiling information could be printed either directly using the chronoPrint method of the service or in the summary table of profiling information at the end of the job Note that this method of code profiling should be used only for fine grained monitoring inside algorithms To profile a complete algorithm you should use the Auditor service as described in section 11 7 page 125 GAUDI User Guide Chapter 11 Framew
91. ach event having page 183 GAUDI User Guide Chapter 17 Design considerations Version Issue 6 3 find seeds geometry ee Geometry store pad hits seeds Event Data store geometry form refine station hits track segment tracks geometry proto tracks station hits extrapolate produce to next tracks station proto track proto tracks proto tracks select discard proto track Figure 32 Hypothetical decomposition of a tracking algorithm based on a Kalman filter using a Data flow Diagram page 184 W GAUDI User Guide Chapter 17 Design considerations Version Issue 6 3 references to the original hits For that it would be required to have another Algorithm whose role is to prepare these new data objects see Figure 33 The master Algorithm Tracking Alg is in charge of setting up the other algorithms and scheduling their execution It is the only one that has a global view but it does not need to know the details of how the different parts of the algorithm have been implemented The application manager of the framework only interacts with the master algorithm and does not need to know that in fact the tracking algorithm is implemented by a collaboration of Algorithms 17 4 2 Defining Data Objects The input output and intermediate data objects need to be specified Typically the input and output are specifie
92. alize and finalize methods should be implemented After initialization the service should be in a state where it may be used by other components The service base class offers a number of facilities itself which may be used by derived concrete service classes e Properties are provided for services just as for algorithms Thus concrete services may be fine tuned by setting options in the job options file e A serviceLocator method is provided which allows a component to request the use of other services which it may need e Amessage service 11 10 2 Implementation details The following is essentially a checklist of the minimal code required for a service Define the interfaces Derive the concrete service class from the Service base class 1 2 3 Implement the queryInterface method 4 Implement the initialize method Within this method you should make a call to Service initialize as the first statement in the method and also make an explicit call to setProperties in order to read the service s properties from the job options note that this is different from Algorithms where the call to setProperties is done in the base class Listing 60 An interface class include Gaudi interfaces IInterface h class IConcreteSvcTypel virtual public IInterface public void methodl 0 int method2 0 include IConcreteSvcTypel h const IID amp IID_IConcreteSvcTypel
93. ame of the logical volume its material its class ID may be omitted because the DTD defines its fixed value its solid shape and list of daughter volumes represented by physical volumes or parametric physical volumes The content model definitions of physical and parametric physical volumes is shown in Figure 15 and Figure 16 The diagram in Figure 14 shows all attributes for solids Figure 17 and Listing 26 show how to define solids Listing 25 shows an example of a logical volume in XML lt lt EMPTY gt gt posxYZ 1 physvol x CDATA lt lt AHname ID y CDATA lt lt EMPTY gt gt OR y logvol CDATA gt z CDATA posRPhiZ e on E 1 lt lt EMPTY gt gt r CDATA 1 YA a gt rotAxis phi CDATA lt lt EMPTY gt gt A lt lt EMPTY gt gt axTheta CDATA z CDATA posRThPhi rotXYZ axPhi CDATA r CDATA rox CDATA angle CDATA theta CDATA rotY CDATA phi CDATA rotZ CDATA physvol can contain either position only or position and rotation together ESS rotation without position makes no sense Figure 15 Content model definition for physical volume element lt lt EMPTY gt gt physvol rotAxis aramphysvol is name ID lt gt er D axTheta CDATA logvol CDATA 1 ee OR 1 JaxPhi CDATA E
94. an be used by applications Do not forget to use GaudiConf v in your application to set up the necessary logical names page 118 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 11 4 The Standard Message Service One of the components directly visible to an algorithm object is the message service The purpose of this service is to provide facilities for the logging of information warnings errors etc The advantage of introducing such a component as opposed to using the standard std cout and std cerr streams available in C is that we have more control over what is printed and where it is printed These considerations are particularly important in an online environment The Message Service is configurable via the job options file to only output messages if their activation level is equal to or above a given output level The output level can be configured with a global default for the whole application Set output level threshold 2 DEBUG 3 INFO 4 WARNING 5 ERROR 6 FATAL MessageSvc OutputLevel 4 and or locally for a given client object e g myAlgorithm myAlgorithm OutputLevel 2 Any object wishing to print some output should must use the message service A pointer to the IMessageSvc interface of the message service is available to an algorithm via the accessor method msgSvc see section 5 2 It is of course possible to use this interface dir
95. andard Options for all services lt myService gt Any service derived from the Service base class can override the global MessageSvc OutputLevel thus Option Default name value Meaning OutputLevel 0 Message Service Verboseness threshold level 0 NIL 1 VERBOSE 2 DEBUG 3 INFO 4 WARNING 5 ERROR 6 FATAL Table B 5 Standard Options for all Tools lt myTool gt Any tool derived from the AlgTool base class can override the global MessageSvc OutputLevel thus Option Default name value Meaning OutputLevel 0 Message Service Verboseness threshold level 0 NIL 1 VERBOSE 2 DEBUG 3 INFO 4 WARNING 5 ERROR 6 FATAL Table B 6 Standard Options for all Associators lt myAssociator gt Option name Default value Meaning FollowLinks true Instruct the associator to follow the links instead of using cached informa tion DataLocation Location where to get association information in the data store Table B 7 Standard Options for all Auditors lt myAuditor gt Any Auditor derived from the Auditor base class can override the global Auditor options thus Default Option name value Meaning OutputLevel 0 Message Service Verboseness threshold level 0 NIL 1 VERBOSE 2 DEBUG 3 INFO 4 WARNING 5 ERROR 6 FATAL Enable true If false application manager skips execution of this algorithm Table B 8 Options of Algorithms in GaudiAlg package
96. aning CnvServices 1 Sets up the event persistency service Possible values are RootEventCnvSvc SicbEventCnvSvc or both together Table B 11 Standard Options for the histogram service HistogramPersistencySvc Option name Default value Meaning OutputFile m Output file for histograms No output if not defined Table B 12 Standard Options for the N tuple service NTupleSvc Option name Default value Meaning Input Input file s for n tuples Format FILE1 DATAFILE tuple hbook OPT OLD TYP HBOOK FILE2 DATAFILE tuple root OPT OLD TYP ROOT Output Output file fInput file s for n tuples Format FILE1 DATAFILE tuple hbook OPT NEW TYP HBOOkK FILE2 DATAFILE tuple root OPT NEW TYP ROOT Fype 6 Sterage type 6 HBOOK a This option is obsolete Please use the TYP tag of the Input and Output options instead page 192 GAUDI User Guide Appendix B Options for standard components Version Issue 6 3 Table B 13 Standard Options for the Sicb event selector EventSelector Option name Default value Meaning Input Input data stream specification Format lt tagname gt lt tagvalue gt lt opt gt Possible lt tagname gt DATAFILE filename TYP technology type OPT new update old SVC
97. aph for the detector The other ones like SoMCPart icleCnv build Inventor scene graphs for event data 16 2 2 Getting Started 16 2 2 1 Preparing the environment GaudiLab requires the standard LHCb environment At CERN this is set up automatically when you login If you do not work at CERN you can look at the GaudiLab cmt login_lal csh file to have an idea of which environment variables are needed for a local installation of everything 16 2 2 2 Starting the programs being owner of the GaudiLab installation If you are the owner of the GaudiLab installation i e you have write access to the GaudiLab user directory you should be able to type the following UNIX gt cd lt path gt lt GaudiLab gt lt version gt cmt csh gt source login_cern csh csh gt source setup csh csh gt cd user csh gt setenv DISPLAY csh gt setenv ONXUI ogtk xml csh gt ogtk to start OnX gtk GUI manager On NT from a DOS prompt DOS gt cd lt path gt lt GaudiLab gt lt version gt cmt DOS gt call setup bat DOS gt cd user DOS gt Sowin32 to start OnX Win32 GUI manager or if working with gtk today the most advanced GUI DOS gt set ONXUI ogtk xml DOS gt Sogtk to start OnX gtk GUI manager page 175 GAUDI User Guide Chapter 16 Visualization Facilities Version Issue 6 3 A main panel should appear If not you are in a mess check e LHCb software installation try the GaudiExamples e OnX
98. as those required for visualisation or those which serve as input into other packages e g Geant4 Figure 27 shows the interfaces classes with names beginning in I which must be implemented in order for the conversion process to function IConverter createObj updateObj fillObjRefs Converter IConversionSvc AConverter1 i AConverter2 AConversionSvc AConverter3 lOpaqueAddress AOpaqueAddress clIID svcType Figure 27 The classes and interfaces collaborating in the conversion process The conversion process is essentially a collaboration between the following types e I ConversionSvec page 153 GAUDI User Guide Chapter 13 Converters Version Issue 6 3 IConverter e IOpaqueA Address For each persistent technology or non transient representation a specific conversion service is required This is illustrated in the figure by the class AConversionSvc which implements the IConversionSvc interface A given conversion service will have at its disposal a set of converters These converters are both type and technology specific In other words a converter knows how to convert a single transient type e g MuonHit into a single persistent type e g RootMuonHit and vice versa Specific converters implement the IConverter interface possibly by extending an existing converter base class A third collaborator in this process are the opaque address objects A concrete o
99. asy to work with the development version of packages without needing to make a private copy of the head revision of a package On Unix it is sufficient to modify the CMTPATH environment variable to include the development area setenv CMTPATH SHOME mycmt SLHCBDEV Packages will then be searched first in your private CMT area then on LHCBDEV and finally on LHCBSOFT Note that this will always give you the latest working version of all packages If you only need a specific development version of one package while keeping the production version of all other packages it would be better to leave CMTPATH pointing only to your private area and making a logical link to the appropriate development package For example cd SHOME mycmt Gaudi ln fs SLHCBDEV Gaudi h000626 v7 This would allow you to use the development version of Gaudi built on 26th June 2000 while using the released version of everything else On NT only the first option is available due to the absence of logical links You can make a search list for your CMTPATH by simply adding a second path to the HKEY_CURRENT_USER SOFTWARE CMT path registry key If you only want the development version of a specific package the only option is currently to copy the appropriate package development subdirectory into your private CMT area page 29 GAUDI Chapter 3 Release notes and software installation User Guide Version Issue 6 3 page 30 GAUDI U
100. at aOb jects can be of two types e Simple classes which contain the data of a single SICB bank These classes are of type DataObject An example is the Event class containing the data of the PASS bank e Container classes which contain data from multiple SICB banks An example is the Ob ject Vector lt MCParticle gt which contains Monte Carlo particles with data from the ATMC bank Template files exist in the directory LHCBSOFT SicbCnv lt version gt doc for both types of converters to ease the creation of user converters e SicbCnv Class Template cpp and SicbCnv Class Template h to be used when writing a converter for a single class e SicbCnv Class Container cppand SicbCnv Container Template htobe used when writing a container of an object container If you intend to write your own SICB converter follow the instructions below e Copy SicbCnv xxxx Template h to Sicb lt your class gt Cnv h where lt your class gt is the name of your persistent class e Copy SicbCnv xxxx Template cpp to Sicb lt your class gt Cnv cpp e Now customize the header and the implementation file e Follow TODO instructions in Sicb lt your class gt Cnv h e Follow TODO instructions in Sicb lt your class gt Cnv cpp page 163 GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 e The converter factory must be made known to the system This in fact depends on the linking mechanism If the converter is l
101. ates gt lt ELEMENT AluminiumPlateThickness PCDATA gt q gt lt DDDB gt lt detelem classID 7001 name MyDetectorModule gt lt author gt RCH lt author gt lt version gt 0 1 lt version gt lt geometryinfo gt lt lvname name dd Geometry MyDetector lvMyDetector gt lt support name dd Structure LHCb gt lt npath value MDM_0 gt lt support gt lt geometryinfo gt lt detelemref classID 7002 href mysubmodule xml MySubModule01 gt lt detelemref classID 7002 href mysubmodule xml MySubModule02 gt lt detelemref 7003 href anothermodule xml AnotherSubModule gt lt specific gt lt CellSize n 56 7 amp cm gt lt AluminiumPlateThickness gt 4 53 amp mm lt AluminiumPlateThickness gt lt specific gt lt detelem gt lt DDDB gt The CellSize tag is defined as an empty tag with one attribute n The tag AluminiumPlateThickness has no attribute but has content In step 4 we will show how properly retrieve information out if these tags by methods of a user defined XML converter Step 3 Define the geometry of your detector element In the previous step the association to the geometry has defined but the actual geometry does not exist yet This step will fill the gap by providing all the needed information in XML page 88 MX GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3
102. atic variable used to collect all of the characters inside the content of the AluminiumPlateThickness tag Listing 37 Implementation of callbacks needed to process content model based XML tag void XmlMyDetectorCnv uCharacters const char const chars const unsigned int length s_collector chars void XmlMyDetectorCnv ulgnorableWhitespace const char const chars const unsigned int length s_collector chars void XmlMyDetectorCnv uEndElement const char const name std string tagName name if tagName AluminiumPlateThickness m_dataObj gt setAluminiumPlateThickness xmlSvc gt eval s_collector Listing 37 shows how we process PCDATA content of our XML tag by collecting all of the characters and inside the uEndElement callback we finally evaluate the string expression we have collected and set the corresponding property of our detector element 8 5 4 Numerical expressions parser This is a simple parser for evaluation of numerical expressions It is available for Gaudi framework converters as well as for the user defined converters The only difference is that in user defined converters the parser is not instantiated explicitly by the user but is accessed through the IXm1Svc interface instead See Listing 37 for an example of its use The numerical expressions recognized by the parser can be composed of integers and floating point numbers assuming one of the for
103. ble to first follow this link and invoke the release method to remove the object from the first container before adding it into the second In general your first exposure to object containers is likely to be when retrieving data from the event data store The sample code in Listing 15 shows how once you have retrieved an object container from the store you may iterate over its contents just as with an STL vector Listing 15 Use of the ObjectVector templated class typedef ObjectVector lt MCParticle gt MCParticleVector MCParticleVector tracks MCParticleVector iterator it for it tracks gt begin it tracks gt end it Get the energy of the track and histogram it doubl nergy it gt fourMomentum e m_hEnergyDist gt fill energy 1 CoO e OP WBN FP The variable t racks is set to point to an object in the event data store of type Ob ject Vector lt MCParticle gt with a dynamic cast not shown above An iterator i e a pointer like object for looping over the contents of the container is defined on line 3 and this is used within the loop to point consecutively to each of the contained objects In this case the objects contained within the Object Vector are of type pointer to MCParticle The iterator returns each object in turn and in the example the energy of the object is used to fill a histogram 6 6 Data access checklist A little reminder page 59
104. by GEANT4 This system is fully documented in the CLHEP web pages at the URL http wwwinfo cern ch asd lhc clhep manual UserGuide Units units html The list of basic units is reproduced in table 3 Note that this differs from the convention used in SICB where the basic units of length time and energy are respectively centimetre GeV second Users should not actually need to know what units are used in the internal representation of the data as long as they are consistent throughout the Gaudi data stores What they care about is that they can define and plot quantities with the correct units In some specialised algorithms they may also wish to renormalise the data to a different set of units if the default set would lead to numerical precision problems We therefore propose the following rules which are discussed more fully in reference 4 page 8 it GAUDI User Guide Chapter 1 Introduction Version Issue 6 3 I Table 3 CLHEP system of units I Quantity Unit Length millimetre Time nanosecond I Energy MeV Electric charge positron charge I Temperature Kelvin I Amount of substance mole I Plane angle radian 1 All dimensioned quantities in the Gaudi data stores shall conform to the CLHEP system of units 2 All definitions of dimensioned quantities shall be dimensioned by multiplying by the units defined in the CLHEP Units SystemOfUnits h header file For example
105. by StdHep id Pointer is 0 if no property found tual ParticleProperty findByStdHepID int stdHepId Erase a property by geant id tual StatusCode erase int geantId Erase a property by particle name tual StatusCode erase const std string amp name Erase a property by StdHep id tual StatusCod raseByStdHepID int stdHeplId int page 123 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 The IParticlePropertySvc interface also provides some typedefs for easier coding typedef ParticleProperty mapped_type typedef std map lt int mapped_type std less lt int gt gt MapID typedef std map lt std string mapped_type std less lt std string gt gt MapName typedef std map lt int mapped_type std less lt int gt gt MapStdHepID typedef IParticlePropertySvc VectPP VectPP typedef IParticlePropertySvc const_iterator const_iterator typedef IParticlePropertySvc iterator iterator 11 5 4 Examples Below are some extracts of code from the example in GaudiExamples ParticleProperties to show how one might use the service Listing 56 Code fragment to find particle properties by particle name Try finding particles by the different methods log lt lt MSG INFO lt lt Trying to find properties by Geant3 ID lt lt endreq ParticleProperty ppl m_ppSvc gt find 1 if
106. can be used for parsing and analysing as it is an industry standard In the future we expect to replace the text files by an object persistency based on an object oriented database for example ObjectivityDB but the data will continue to be described in XML page 75 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 8 5 1 Brief introduction to XML 8 5 1 1 XML Basics XML is extendible meaning that a user can define his own markup language with his own tags The tags define the meaning of the data they represent or contain They act as data describers For example Listing 21 shows the XML file which describes an e mail Listing 21 Simple XML file describing an e mail lt xml version 1 0 encoding UTF 8 gt lt This is an example of XML gt lt Email gt lt TimeStamp time 11 38 43 date 22 11 1999 gt lt Sender gt sender cern ch lt Sender gt lt Recipient gt recipient cern ch lt Recipient gt lt Subject gt Lunch lt Subject gt lt Body gt Could we meet at 14 00 lt Signature gt Sender s signature lt Signature gt lt Body gt lt Email gt At first look this markup language looks like screwed up HTML This is because both HTML and XML have their roots in SGML but they are used for different purposes From the example above it s not clear how to present the data described there nor how to visualize them What is clear however
107. capability of algorithms to manage the execution of algorithm sequences in a filtering application as discussed in section 5 5 The Particle Properties service section 11 5 provides the properties of all the elementary particles Access to the CLHEP and NAG C libraries Chapter 15 provides numerical utilities for writing physics algorithms Visualization services The framework provides facilities at a prototype level for visualization of event and detector data These services are currently based on the packages that constitute the Open Scientist suite OpenGL OpenInventor soFree Lab An event and geometry display application has been built using these facilities SICB services A number of services are included in the current release to facilitate the access to SICB data detector description magnetic field etc and to facilitate re using existing Fortran code with the framework These services can be extended to accommodate new concrete requests when integrating big parts of the current legacy code SICB In the latest release there full support for event pile up It is possible to read events from two input data streams and merge them before any processing is done Refer to Chapter 14 for more details Dynamic loading of libraries The framework will be used to implement different data processing applications for different environments It is important that the services and their concrete implementations are extendable and configurable
108. ce gt E coz gt E sio_2 gt fe CF_4 E Argon_CF_4 Vertex geometry xml Vertex Rich1 geometry xml Rich1 Magnet geometry xml Magnet Shield geometry xml Shield Tracker geometry xml Tracker Rich2 geometry xml Rich2 9 9 9 9 9 2 9 SPD geometry xml SPD rMessages Figure 19 GUI of the XML Editor Besides that some specificities of the detector description have been taken into account First you can see that most of the important elements detector element logical volumes catalogs and materials have a specific icon that allows the user to distinguish them easily Then the detector description XML uses references across files via tags like lt catalogref gt These are also taken into account When a reference is displayed it is not dereferenced by default in order not to load the whole detector description database in every case It is displayed using a special icon the one of the normal object plus an arrow on the top If the user wants to dereference it he can double click on it and the corresponding file will be loaded and displayed Even when dereferenced a reference keeps a specific icon the normal one plus a little arrow on top The different icons used for a catalog are shown in Figure 20 No reference Reference Dereferenced IE dd Z structure xml Structure pa Structure Figure 20 Icons us
109. cess the data used to create the n tuple Using this approach any n tuple which allows access to the data is an event collection Event collections allow pre selections of event data These pre selections depend on the underlying storage technology First stage pre selections based on scalar components of the event collection First stage preselection is not necessarily executed on your computer but on a database server e g when using ORACLE Only the accessed columns are read from the event collection If the criteria are fulfilled the n tuple data are returned to the user process Preselection criteria are set through a job options as described in section 10 3 2 The second stage pre selection is triggered for all items which passed the first stage pre selection criteria For this pre selection which is performed on the client computer all data in the n tuple can be used The further preselection is implemented in a user defined function object functor as described in section 10 3 2 Gaudi algorithms are called only when this pre selector also accepts the event and normal event processing can start 10 3 1 Writing Event Collections Event collections are written to the data file using a Gaudi sequencer A sequencer calls a series of algorithms as discussed in section 5 5 The execution of these algorithms may terminate at any point of the series and the event not selected for the collection if one of the algorithms in the sequence fa
110. copy of a debugged detector description the init tcl file These files control the run time environment and could be edited for strong customization of things page 176 GAUDI User Guide Chapter 16 Visualization Facilities Version Issue 6 3 16 2 4 The available GUI menus The ogtk xml or main xml if working with Motif or Win32 contains a set of menus All these could be customized by editing the XML file The default menus are e File e Console map the output console e Exec tcl map a file chooser to pick a tcl file and execute it e Session tcl execute if it exisists the session tcl found in the current directory e stdout redirect output from console to stdout e Continue exit from a secondary GUI event loop e Exit exit the program e Viewer for manipulation in the current viewer or page e 1x1 2x2 1x2 2x1 set a grid of viewport regions in the current viewer e next set the current active viewport region the one with a red border to the neightbourg one left to rigth top to bottom e Region page map the current region to the whole viewer e 2D 3D prepare the region for a 2D for exa histo plotting or 3D rendering e black white grey back set background color of the current region e view all map the viewport camera viewing to match the bounding box scene e GIF xv produce a out gif GIF file of the viewer spawn xv over the out gif file e PS gv for 2D scen
111. created by the ApplicationMgr The piled up events are read in from the second instance created by the pile up algorithm There are two different iterators one for each EventSelector instance which loop over these two data streams When reading the ZEBRA files produced by SICB the events are merged at the level of the ZEBRA common blocks by a call to the Futio routine REMERGE Every C algorithm requesting data from one of the converted banks will get the merged data Every FORTRAN algorithm using the SICB banks will also read the merged data as SICBDST does PileUpAlg must be the first algorithm called other algorithms will access the merged events when they retrieve some data from the store The pile up algorithm controls the number of events which have to be piled up to every leading event PileUpAlg uses a C version of the SICB routine RELUMI to get the number of pile up events as a function of the luminosity page 167 GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 and some other beam parameters Those parameters are currently read in from the beam cdf file The C version of RELUMI uses the random number service in Gaudi Other implementations of the algorithm for instance to return a fix number of pile up events every time may be implemented if they are needed IProperty SicbEventSelector TEventSelector ApplicationMgr SicbPileupAlg l SicbPileupSvc TDataManag
112. cted and Analysis event sub trees are all container classes containing instances of classes that inherit directly or indirectly from the class ContainedOb ject 7 3 Monte Carlo event The Monte Carlo event sub tree contains output from the event generators and from the Monte Carlo tracking The include files for the contained classes can be found in LHCbEvent MonteCarlo h with obvious names Table 6 Monte Carlo Event data model Logical Path Container Type Event MC MCParticles MCParticleVector 7Event MC MCVertices MC Vertex Vector 7Event MC MCtTrackerHits MCTrackingHitVector 7Event MC MCVertexHits MCTrackingHitVector Event MC MCVertexPileUpHits MCTrackingHitVector page 66 GAUDI User Guide Chapter 7 LHCb Event Data Model Version Issue 6 3 Table 6 Monte Carlo Event data model Logical Path Container Type Event MC MCMuonHits MCTrackingHitVector 7Event MC MCRichRadiatorHits MCRichRadiatorHitVector Event MC MCRichPhotodetectorHits MCRichPhotodetectorHitVector Event MC MCECalHits MCCalorimeterHitVector 7Event MC MCHCalHits MC CalorimeterHitVector 7Event MC MCPreshowerHits MC CalorimeterHitVector 7 3 1 Association to Monte Carlo truth As discussed in detail in reference 6 we have adopted a convention whereby the only navigational links between simulated real data classes and
113. ctories is given in Section 1 2 3 As discussed in section 5 2 the Algorithm base class defines a member function IHistogramSvc histoSvc page 96 GAUDI User Guide Chapter 9 Histogram facilities Version Issue 6 3 which returns a pointer to the IHistogramSvc interface of the standard histogram data service Access to any other non standard histogram data service if one exists must be sought via the ISvcLocator interface of the application manager as discussed in section 11 2 9 3 Using histograms and the histogram service An example code fragment illustrating how to book a 1D histogram and place it in a directory within the histogram data store and a simple statement which fills that histogram is shown here Book 1D histogram in the histogram data store m_hTrackCount histoSvc gt book stat simple 1 TrackCount 100 0 3000 SmartDataPtr lt MCParticleVector gt particles eventSvc Event MC MCParticles if 0 particles Filling the track count histogram m_hTrackCount gt fill particles gt size 1 The parameters of the book function are the directory in which to store the histogram in the data store the histogram identifier the histogram title the number of bins and the lower and upper limits of the X axis 1D histograms with fixed and variable binning are available In the case of 2D histograms the book method requires in additi
114. cture To fulfil the XML basic rule that each XML document must have only the one root XML element we have defined the element DDDB see Figure 11 DDDB eee TOR FN ORS OS catalog Y 1 material 1 OR OR from Materials 1 Tax lt lt EMPTY gt gt logvol catalogref detelem from Geometry from Structure Figure 11 Content model definition of the root element for detector description This element must be present in each of the XML files created for the detector description This element is so defined that it can contain all the important elements needed for detector description and thus the database can be spread over multiple XML files The DDDB element can contain one or more of the following elements catalog catalogref detelem logvol material Each of these elements will be described in detail later The detector description in XML requires a bootstrap file which contains a definition of the database root and a definition of the top level catalogs mentioned above This done in a flexible way to make it possible to have multiple bootstrap files This can be done in the job options by setting the application manager properties DetDbLocation and DetDbRootName They allow to switch from one bootstrap file to another and to switch between root nodes The bootstrap file must have defined the root node catalog as the only c
115. d The limitation of this feature is that after the generic conversion the returned reference points to a Detec torElement object and not to the user defined class This means that SmartDataPtr class can be pa rameterized only by DetectorElement class and not by the user defined class page 195 GAUDI Appendix B Options for standard components User Guide Version Issue 6 3 page 196 GAUDI User Guide Appendix C Job Options Grammar and Error Codes Version Issue 6 3 Appendix C Job Options Grammar and Error Codes C 1 The EBNF grammar of the Job Options files The syntax of the Job Options File is defined through the following EBNF Grammar Job Options File Statements Statements Include Statement Assign Statement Append Statement Platform Dependency AssertableStatements Include Statement Assign Statement Append Statement AssertionStatement ifdef ifndef Platform Dependency AssertionStatement WIN32 lt AsertableStatements gt else lt Asserta bleStatements gt endif Include Statement include string Assign Statement Identifier Identifier value Append Statement Identifier Identifier value page 197 GAUDI Appendix C Job Options Grammar and Error Codes User Guide Version Issue 6 3 Identifier letter letter digit value boolean integer
116. d severity that is used for filtering and dispatching them The job options service allows the configuration of the application by end users assigning values to properties defined within the code properties can be basic types float bool int string or extended with bounds checking hierarchical lists and immediate callback from string commands The Random Numbers service makes available several random number distributions via a standard interface and ensures that applications use a unique random number engine in a reproducible fashion The Chrono service offers the functionality for measuring elapsed time and job execution statistics Auditors and AuditorSvc provide monitoring of various characteristics of the execution of Algorithms Auditors are called before and after invocation of any Algorithm method The Incident service provides a synchronization between objects within the Application by using named incidents that are communicated to listener clients The Tools service which provides management of Tools is discussed in Chapter 12 Tools are lightweight objects which can be requested and used many times by other components to perform well defined tasks A base class for associator tools has been added in this release Data services provide the access to the transient data objects event detector and statistical data The data services are described in chapters 6 to 10 Event data model The event model has been extended to Velo LO L
117. d string name std vector lt double gt amp reference 29 StatusCode declareProperty const std string name std vector lt bool gt amp reference 30 StatusCode declareProperty const std string name std vector lt std string gt amp reference gT 32 protected 33 Standard destructor 34 virtual AlgTool Access to Services A serviceLocator method is provided to enable the derived tools to locate the services necessary to perform their jobs Since concrete Too1s are instantiated by the ToolSvc upon request all Services created by the framework prior to the creation of a tool are available In addition access to the message service is provided via the msgSvc method Both pointers are retrieved from the parent of the tool Declaring Properties A set of methods for declaring properties similarly to Algorithms is provided This allows tuning of data members used by the Tools via JobOptions files The ToolSvc takes care of calling the setProperties method of the AlgToo1 base class after having instantiated a tool Properties need to be declared in the constructor of a Tool The property output Level is declared in the base class and is identically set to that of the parent component For details on Properties see section 11 3 1 page 139 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 Constructor The base class has a single constructor which takes three arguments The
118. d handler const std string amp value 0 eee Thus subclasses should override the handler member function which will be called whenever the property value changes A future development is expected to be a ParsableProperty or something similar that would offer support for parsing the string 11 3 2 Job options file format The job options file has a well defined syntax similar to a simplified C Syntax without datatypes The data types are recognised by the Job Options Compiler which interprets the job options file according to the syntax described in Appendix C together with possible compiler error codes The job options file is an ASCII File composed logically of a series of statements The end of a Ms statement is signaled by a semicolon as in C Comments are the same as in C with until the end of the line or between and There are four constructs which can be used in a job options file e Assignment statement e Append statement e Include directive e Platform dependent excution directive page 115 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 Assignment statement An assignment statement assigns a certain value or a vector of values to a property of an object or identifier An assignment statement has the following structure lt Object Identifier gt lt Propertyname gt lt value gt The firs
119. d if it doesn t already exist If a tool instance exists the ToolSvc will not create a new identical one but pass to the algorithm the existing instance Tools are created on a first request basis the first Algorithm requesting a tool will prompt its creation The relationship between an algorithm the ToolSvc and Tools is shown in Figure 25 IToolSve yore Lane 7 IAlgTool pea ToolSve k gt i i IProperty Alg Tool T i IToolFactory a ToolFactory lt T gt a a ConcreteAlgorithm N ConcreteTool Figure 25 ToolSvc design diagram page 142 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 The ToolSvec will hold a tool until it is no longer used by any component or until the finalize method of the tool service is called Algorithms can inform the Tool Svc they are not going to use a tool previously requested via the releaseTool method of the IToo1Sve interface The ToolSvc is created by default by the ApplicationMgr and algorithms wishing to use the service can retrieve it using the service accessor method of the Algorithm base class as shown in the lines below include Gaudi Interfaces IToolSvc h IToolSvc toolSvc 0 StatusCode sc service ToolSvc toolSvc if sc isFailure 12 3 1 Retrieval of tools via the IToo1Svc interface The IToolSvc interface is the Tool
120. d in Chapter 11 Filtering The methods in lines 14 to 19 are used by sequencers and filters to access the state of the algorithm as discussed in section 5 5 5 3 Derived algorithm classes In order for an algorithm object to do anything useful it must be specialised i e it must extend inherit from be derived from the Algorithm base class In general it will be necessary to implement the methods of the Algorithm interface and declare the algorithm s properties to the property management machinery of the Algorithm base class Additionally there is one non obvious technical matter to cover namely algorithm factories 5 3 1 Creation and algorithm factories As mentioned before a concrete algorithm class must specify a single constructor with the same parameter signature as the constructor of the base class page 45 GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 In addition to this a concrete algorithm factory must be provided This is a technical matter which permits the application manager to create new algorithm objects without having to include all of the concrete algorithm header files From the point of view of an algorithm developer it implies adding two lines into the implementation file of the form static const AlgFactory lt ConcreteAlgorithm gt s_factory const IAlgFactory ConcreteAlgorithmFactory s_factory where ConcreteAlgorithm should be replaced by the name of
121. d in a more general way algorithm independent and basically are pure data objects This is because they can be used by a range of different algorithms We could have various types of tracking algorithm all using the same data as input and producing similar data as output On the contrary the intermediate data types can be designed to be very algorithm dependent The way we have chosen to communicate between the different Algorithms which constitute our physics algorithm is by using the transient event data store This allows us to have low coupling between them but other ways could be easily envisaged For instance we could implement specific methods in the algorithms and allow other friend algorithms to use them directly Concerning the relationships between data objects it is strongly discouraged to have links from the input data objects to the newly produced ones i e links from hits to tracks In the other direction this should not be a problem i e from tracks to constituent hits For data types that we would like to save permanently we need to implement a specific Converter One converter is required for each type of data and each kind of persistency technology that we wish to use This is not the case for the data types that are used as intermediate data since this data is completely transient 17 4 3 Mathematics and other utilities It is clear that to implement any algorithm we will need the help of a series of utility class
122. d to provide a uniform interface to the user code a set of Gaudi Tools called Associators has been introduced The user can navigate between any two arbitrary classes in the Event Model using the same interface as long as a corresponding associator has been implemented Since an Associator retrieves existing navigational information its actual implementation depends on the Event Model and how the navigational information is stored For some specific Associators in addition it can depend on some algorithmic choices consider as an example a physics analysis particle and a possible originating Monte Carlo particle where the associating discriminant could be the fractional number of hits used in the reconstruction of the tracks An advantage of this approach is that the implementation of the navigation can be modified without affecting the reconstruction and analysis algorithms because it would affect only the associators In addition short cuts or complete navigational information can be provided to the user in a transparent way By limiting the use of such associators to dedicated monitoring algorithms where the comparison between raw reconstructed data and MC truth is done one could ensure that the reconstruction and analysis code treat simulated and real data in an identical way Associators must implement a common interface called I Associator AnAssociator base class providing at the same time common functionality and some facilities to help in th
123. dObject amp objTo const CLID idFrom const CLID idTo 0 2 virtual StatusCode i_retrieveDirect ContainedObject ob jFrom std vector lt ContainedObject gt amp vObjTo const CLID idFrom const CLID idTo 0 3 virtual StatusCode i_retrieveInverse ContainedObject objFrom ContainedObject amp objTo const CLID idFrom const CLID idTo 0 4 virtual StatusCode i_retrieveInverse ContainedObject ob jFrom std vector lt ContainedObject gt amp vObjTo cons LID idFrom LID idTo 0 ct ie const Cl ct of the type requested Some reconstructed quantities will have only one possible Monte Carlo associated object of a certain type some will have many others will have many out of whicha best associated object can be extracted If one of the two methods is not valid for a concrete associator such method must return a failure The third and fourth parameters are the class IDs of the objects for which the association is requested This allows to verify at run time if the objects types are those the concrete associator has been implemented for The two i_retrieveInverse methods are complementary and are for retrieving the association between the same two classes but in the opposite direction to that of the links in the data from Monte Carlo particles to reconstructed particles The different name is intended to alert the user that navigation in this direction may be a costly ope
124. de XML documents are preserved and the decision is left up to the application which should either ignore them or process them Let us move back to writing our XML converter The ustartElement is called always when XML parser jumps onto the next XML tag inside the lt specific gt section The implementation of this callback is shown in Listing 36 There is a clear action there for the tag Ce11size We get the value of the attribute n by name and we evaluate its content by numerical expressions parser with checking for CLHEP units enabled and finally we set the m_ce11Size property of our detector element page 90 it GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 Listing 36 Implementation of the callback invoked at start of each XML tag inside lt specific gt section static std string s_collector void XmlMyDetectorCnv uStartElement const char const name XmlCnvAttributeList amp attributes std string tagName name if tagName CellSize std string nval attributes getValue n m_dataObj gt setCellSize xmlSvc gt eval nval else if tagName AluminiumPlateThickness s_collector erase else Unknown tag a warning message can be issued here For the tag AluminiumPlateThickness however we can t do much at this this time because its content has not been parsed yet What we do here is initialization of the st
125. dentifier which allows the persistency service to choose a conversion service The request to load an object or objects is then passed onto a specific conversion service This service then invokes another method of the IOpaqueAddress interface cl ID in order to decide which converter will actually perform the conversion The opaque address is then passed onto the concrete converter who knows how to decode it and create the appropriate transient object The converter is specific to a specific type thus it may immediately create an object of that type with the new operator The converter must now unpack the opaque address i e make use of accessor methods specific to the address type in order to get the necessary information from the persistent store page 154 it GAUDI User Guide Chapter 13 Converters Version Issue 6 3 createObj OA createObj OA unpack O pointers into persistent file DB new DataObject access es data to build transient object setX setY return reference tp DataObject Ci DataObject O 2 _O Figure 28 A trace of the creation of a new transient object For example a SICB converter might get the name of a bank from the address and use that to locate the required information in the SICB common block On the other hand a ROOT converter may extract a file name the names of a ROOT TT ree and an index from the address and use these to load an obj
126. done exclusively using the LD_LIBRARY_PATH for Linux and PATH for NT page 20 GAUDI User Guide Chapter 2 The framework architecture Version Issue 6 3 2 5 3 3 Building the libraries Using CMT we have simplified to way these two different types of libraries are built The proper linker flags are predefined with the macros component shr_linkopts and libraryshr_linkopts for component and linker libraries respectively The macro xxxxx_Shlibflags needs to be built as shown in the private part of the requirements file below Listing 1 Defining CMT macros for building component and linker libraries package Package version v999 use library CompLib Components cpp library LinkLib Library cpp include_path PACKAGEROOT PACKAGEROOT BINDIR PackageDir libLinkLib so macro PackageDir wS macro Package_linkopts Visualc PackageDir libLinkLib lib macro Package_stamps PackageDir LinkLib stamp private macro CompLib_shlibflags S componentshr_linkopts use_linkopts macro LinkLib_shlibflags libraryshr_linkopts use_linkopts Visualc S libraryshr_linkopts use_linkopts def PackageDir libLinkLib def a ET Ol NPPRPPP PPP PY SOMIDUHRWNEFP OW AIA BWNPE 2 5 3 4 Linking FORTRAN code Any library containing FORTRAN code more specifically code that references COMMON blocks must be linked statically This is because COMMON blocks are by def
127. e 6 3 The AxPart2MCParticleAsct provides association between physics analysis particles AxPartCandidate and the corresponding Monte Carlo particles MCParticle The direct navigational information is stored in the persistent data as short cuts and is retrieved in the form of a SnartRefTab1e in the Transient Event Store This choice is specific to AxPart2MCParticleAsct any associator can use internally a different navigational mechanism The location in the Event Store where the navigational information can be found is set in the jobOptions via the setting of the Dat aLocation property as shown in Listing 70 Listing 70 Example of setting properties for an associator via jobOptions ToolSvc AxPart2MCParticleAsct DataLocation Event Anal AxPart2MCParticle In the current LHCb data model only a single MCPart icle can be associated to one AxPartCandidate and vice versa only one or no AxPartCandidate can be associated to one MCParticle For this reason only the i_retrieveDirect and i_retrievelInvers methods providing one to one association are meaningful Both methods verify that the objects passed are of the correct type before attempting to retrieve the information as show in Listing 71 When an association is not found a StatusCode FAILURE is returned Listing 71 Checking if objects to be associated are of the correct type if idFrom AxPartCandidate classID objTo 0 return StatusCode F
128. e Appendix D LHCb Event Data Model Version Issue 6 3 Appendix D LHCb Event Data Model In this Appendix we present the UML diagrams relating the Transient Event Data model page 203 GAUDI User Guide Appendix D LHCb Event Data Model Version Issue 6 3 Top Level LHCb Event Structures Data Object from Kernel RecEvent RawEvent fromMC bool false lerrorStatus long 0 highVoltageMask long 0 ObjectContainerBase Event ObjectContainerBase E ent long 0 jhasNewerVersion tun long 0 has TheSameVersion isetParent MCE PAR Bpievp long 0 Ga at 1 4 i 1A time YA 4 4 4processingVersion TimeStamp Ss trom Utilities i striggerPatt ern subMCEv ent yt SubMCEvent TriggerPattern ide tec torC haracteris tics long from Utilities imary Vertex Point3D ight double A Classification A x i from Utilities triggerPattern randomNumberSeed classification v Random NumberSeed ProcessingVersion DetectorDataObject tom Utilifes trom Utilities fom Utilites ry AnaEvent eS N randomNumbe
129. e Chapter 2 The framework architecture Version Issue 6 3 2 5 1 Package Layout Figure 3 shows the recommended layout for Gaudi packages and for other LHCb software packages such as sub detector software Note that the binaries directories are not in CVS they are created by CMT when building a package packA PACKAROOT on pr cmt src doc i386 Linuxdbx Win32 nux Debug a aM binaries external include files include packA xxx h Avoid many levels internal include files and source code Avoid many levels Figure 3 Recommended layout of LHCb software packages 2 5 2 Packaging Guidelines for sub detectors Packaging is an important architectural issue for the Gaudi framework but also for the sub detector software packages based on Gaudi Typically sub detector packages consist of e Specific event model e Specific detector description e Sets of algorithms digitisation reconstruction etc The packaging should be such as to minimise the dependencies between packages and must absolutely avoid cyclic dependencies The granularity should not be too small or too big Care should be taken to identify the external interfaces of packages if the same interfaces are shared by many packages they should be promoted to a more basic package that the others would then depend on Finally it is a good idea to discuss your packaging with the librarian and or arch
130. e implementation of concrete Associators is provided A first version of these classes as well as an example of a concrete implementation are provided in the current release of Gaudi 12 4 1 1 The IAssociator Interface As already mentioned Associators must implement the IAssociator interface In order for Associators to be retrieved from the ToolSvc only via the I Associator interface the interface itself inherits from the IAlgToo1 interface While the implementation of the IAlgTool interface is done in the AlgTool base class that of the IAssociator interface is the full responsibility of concrete associators The four methods of the I Associator interface that a concrete Associator must implement are show in Listing 68 Two i_retrieveDirect methods must be implemented for retrieving associated classes following the same direction as the links in the data for example from reconstructed particles to Monte Carlo particles The first parameter is a pointer to the object for which the associated Monte Carlo quantity ies is requested The second parameter the discriminating signature between the two methods is one or a vector of pointers to the associated Monte Carlo objects page 145 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 Listing 68 Methods of the lAssociator Interface that must be implemented by concrete associators 1 virtual StatusCode i_retrieveDirect ContainedObject objFrom Containe
131. e of the basic components of an application and their interfaces and therefore it also specifies the places where concrete physics algorithms and concrete data types will fit in with the rest of the program The consequences of this are on one hand that the physicists designing the algorithms do not have complete freedom in the way algorithms may be implemented but on the other hand neither do they need worry about some of the basic functionalities such as getting end user options reporting messages accessing event and detector data independently of the underlying storage technology etc In other words the framework imposes some constraints in terms of interfaces to basic services and the interfaces the algorithm itself is implementing towards the rest of the application The definition of these interfaces establishes the so called master walls of the data processing application in which the concrete physics code will be deployed Besides some general services provided by the framework this approach also guarantees that later integration will be possible of many small algorithms into a much larger program for example the LHCb reconstruction program In any case there is still a lot of room for design creativity when developing physics code within the framework and this is what we want to illustrate in the next sections To design a physics algorithm within the framework you need to know very clearly what it should do the requirements I
132. e solids needed for the detector simulation etc CI dd Geometry CS LHCb tak lvMuon ti lvMuonS tation lvVertex lvVertexS tation E a Materials tal Boron_10 CA C4 tak Oxygen i Structure E E LHCb E l Muon l Vertex CS StationO1 S Station02 Figure 10 The structure of part of the LHCb detector data transient store 8 3 2 Accessing detector data on the transient store An algorithm that needs to access a given detector part uses the detector data service to locate the relevant DetectorElement This operation of locating the required detector description object can be generally done during the initialization phase of the algorithm Contrary to the Event Data the Detector Data store is not cleared for each event and the references to detector elements remain valid and are updated automatically during the execution of the program Locating the relevant detector element is done using the standard IDataProviderSvc interface via the det Svc accessor as shown in Listing 18 page 71 User Guide Chapter 8 Detector Description Version Issue 6 3 Listing 18 Retrieving a detector element by using smart pointers SmartDataPtr lt DetectorElement gt vertex detSvc dd Structure Vertex VStation01 if vertex Error detector element has not been retrieved Similarly the user can retrieve an array of such references The following c
133. e trying to load a component library e g Comp the framework will look for a library in various places following this sequence Try to find an environment variable with the name of the library suffixedby Shr e g CompShr If the environment variable exists then it should translate to the absolute location of the library without the file type suffix that is platform dependent e g LibCompShr SLHCBSOFT packA v1 i386_linux22 libComp Try to locate the file 1ibComp so for Linux or 1ibCompShr d11 for NT using the LD_LIBRARY_PATH for Linux and PATH for NT 2 5 3 2 Linker libraries These are libraries containing implementation classes For example libraries containing code of a number of base classes or specific classes without abstract interfaces etc These libraries contrary to the component libraries export all the symbols and are needed during the linking phase in the application building These libraries can be linked to the application statically or dynamically requiring a different file format In the first case the code is added physically to the executable file In this case changes in these libraries require the application to be re linked even if these changes do not affect the interfaces In the second case the linker only adds into the executable minimal information required for loading the library and resolving the symbols at run time Locating and loading the proper shareable library at run time is
134. e values CLID_UDO defined in the UDO class and Objectivity_StorageType which is also defined elsewhere The first two extern statements simply state that these two identifiers are defined elsewhere All of the book keeping can now be done by the Converter base class It only remains to fill in the guts of the converter If objects of type UDO have no links to other objects then it suffices to implement the methods createRep for conversion from the transient form to Objectivity in this case and createObj for the conversion to the transient form If the object contains links to other objects then it is also necessary to implement the methods fillRepRefs and i1110bjRefs page 156 GAUDI User Guide Chapter 13 Converters Version Issue 6 3 Listing 73 An example converter class Converter for class UDO extern const CLID amp CLID_UDO extern unsigned char OBJY_StorageType static CnvFactory lt UDOCnv gt s_factory const ICnvFactory amp UDOCnvFactory s_factory class UDOCnv public Converter public UDOCnv ISvcLocator svcLoc Converter Objectivity_StorageType CLID_UDO svcLoc createRep DataObject pO IOpaqueAddress amp a createObj IOpaqueAddress pa DataObject amp pO fillObjRefs fillRepRefs 13 6 Storing Data using the ROOT I O Engine One possibility for storing data is to use the ROOT I O engine to write ROOT files Although ROOT by itself i
135. e with the STL containers is that the type T cannot be anything you like It must be a type derived from the ContainedOb ject base class see Figure 8 In this way all contained objects have a pointer back to their containing object This is required in particular by the converters for dealing with links between objects A ramification of this is that container objects may not contain other container objects without the use of multiple inheritance DataObject A ObjectContainerBase ContainedObject parent ObjectVector Figure 8 The relationship between the DataObject ObjectVector and ContainedObject classes As mentioned above objects which are contained within one of these container objects may not be located or registered individually within the store Only the container object may be located via a call to findObject or retrieveObject Thus with regard to interaction with the data stores a container object and the objects that it contains behave as a single object page 57 GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 The intention is that small objects such as clusters hits tracks etc are derived from the ContainedOb ject base class and that in general algorithms will take object containers as their input data and produce new object containers of a different type as their output The reason behind this is essentially one of optimization
136. eVector tv 0 Oe Ey A 10 tv dynamic_cast lt MCParticleVector gt pObject 11 cateh 4 12 Print out an error message and return Logt 14 tv may now be manipulated The typedef on line 1 is just to save typing typedefs of this kind are defined for all ObjectVectors in the LHCb data model in what follows we will use the two syntaxes interchangeably After the dynamic_cast on line 10 all of the methods of the MCParticleVector class become available In the event that the object which is returned from the store does not match the type to which you try to cast it an exception will be thrown If you do not catch this exception it will be caught by the algorithm base class and the program will stop probably with an obscure message A more elegant way to retrieve the data involves the use os Smart Pointers this is discussed in section 6 8 As mentioned earlier a certain amount of run time investigation may be done into what data is available in the store For example suppose that we have various sets of testbeam data and each data set was taken with a different number of detectors If the raw data is saved on a page 55 GAUDI Chapter 6 Accessing data User Guide Version Issue 6 3 per detector basis the number of sets will vary The code fragment in Listing 13 illustrates how an algorithm may loop over the data sets without knowing a priori how many there are Listing 13 Code fragment for accessing an
137. ect from a ROOT file The converter would then use the accessor methods of this persistent object in order to extract the information necessary to build the transient object We can see that the detailed steps performed within a converter depend very much on the nature of the non transient data and to a lesser extent on the type of the object being built If all transient objects were independent i e if there were no references between objects then the job would be finished However in general objects in the transient store do contain references to other objects These references can be of two kinds page 155 GAUDI User Guide Chapter 13 Converters Version Issue 6 3 i Macroscopic references appear as separate leafs in the data store They have to be registered with a separate opaque address structure in the data directory of the object being converted This must be done after the object was registered in the data store in the method i110bjRefs ii Internal references must be handled differently There are two possibilities for resolving internal references 1 Load on demand If the object the reference points to should only be loaded when accessed the pointer must no longer be a raw C pointer but rather a smart pointer object containing itself the information for later resolution of the reference This is the preferred solution for references to objects within the same data store e g referenc
138. ected to the n tuple service Its purpose is to store user created objects that have a lifetime of more than a single event As with the other data stores all access to data is via a service interface In this case it is via the INTupleSvc interface which extends the IDataProviderSvc interface In addition the interface to the n tuple service provides methods for creating n tuples saving the current row of an n tuple or retrieving n tuples from a file The n tuples are derived from Dat aOb ject in order to be storable and are stored in the same type of tree structure as the event data This inheritance allows to load and locate n tuples on the store with the same smart pointer mechanism as is available for event data items c f Chapter 6 page 99 GAUDI User Guide Chapter 10 N tuple and Event Collection facilities Version Issue 6 3 10 2 1 Access to the N tuple Service from an Algorithm The Algorithm base class defines a member function INTupleSvc ntupleSvc which returns a pointer to the INTupleSvc interface The n tuple service provides methods for the creation and manipulation of n tuples and the location of n tuples within the persistent store The top level directory of the n tuple transient data store is called NTUPLES The next directory layer is connected to the different output streams e g NTUPLES FILE1 where FILE1 is the logical name of the requested output file for a given strea
139. ectly The accessor method geomet ry gives access to geometry information offered by the interface of type IGeomet ryInfo This interface allows the retrieval of a reference to a logical volume associated with the given detector element its material property the position in the geometrical hierarchy In addition to that you can ask it questions like it GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 Transformation matrix from the Global to the Local Reference system Transformation matrix from the Local to the Global Reference system Perform transformation of point from the Global to Local Reference system Perform transformation of point from the Local to Global Reference system Name of daughter volume of current volume which contains given global point Get a pointer to daughter volume which contains given global point Name of daughter volume at deeper hierarchical level which contains given point Get a pointer to daughter volume on deeper level to which contains given point SO 908 ONS oO Rn Oa No Get the exact full geometry location 9 Whether the given point is inside the associated logical volume or not 11 A pointer to the associated logical volume For example Listing 20 Getting pointer to a logical volume and retrieving its various properties SmartDataPtr lt DetectorElement gt vs detSvc dd Structure LHCb Vertex VStation01 if vs return StatusCode F
140. ectly but a utility class called MsgSt ream is provided which should be used instead 11 4 1 The MsgStream utility The MsgSt ream class is responsible for constructing a Message object which it then passes onto the message service Where the message is ultimately sent to is decided by the message service In order to avoid formatting messages which will not be sent because the verboseness level is too high aMsgSt ream object first checks to see that a message will be printed before actually constructing it However the threshold for a MsgSt ream object is not dynamic i e it is set at creation time and remains the same Thus in order to keep synchronized with the message service which in principle could change its printout level at any time MsgSt ream objects should be made locally on the stack when needed For example if you look at the listing of the HistoAlgorithm class see also Listing 54 below you will note that MsgSt ream objects are instantiated locally i e not using new in all three of the Algorithm methods and thus are destructed when the methods return If this is not done messages may be lost or too many messages may be printed The MsgSt ream class has been designed to resemble closely a normal stream class such as std cout and in fact internally uses an ost rst ream object All of the MsgSt ream member functions write unformatted data formatted output is handled by the insertion operators page 119
141. ectors It also makes the structure on the transient store more clear and similar to the logical structure of the detector The catalog contains only references to logical volumes defined in the same file Next we have defined the logical volume for our MyDetector element with its shape as box and 3 daughter volumes The first two daughter volumes are represented by parametric physical volume and the third one by normal physical volume The definition of the remaining two logical volumes is missing from Listing 33 but these are defined in a similar way to the one shown Step 4 Write the XML converter for your detector element As a first step we need to create instance of the user level XML converter for MyDetector element type This done by inheritance from xmlUserDeCnv lt gt templated class which is parametrized by our MyDetector element type see Listing 34 What is important here is to define the corresponding converter factory otherwise this converter will not be invoked page 89 GAUDI Chapter 8 Detector Description User Guide Version Issue 6 3 Listing 34 Making an instance of user defined XML converter for MyDetector element type include DetDesc XmlCnvSvc XmlUserDeCnv h include MyDetector h class XmlMyDetectorCnv public XmlUserDeCnv lt MyDetector gt public XmlMyDetectorCnv ISvcLocator svc XmlMyDetectorCnv virtual void uStartElement const char const name XmlCnvAttributeList a
142. ects from the transient store have to be converted to objects understandable by ROOT The following sections are an introduction to the machinery provided by the Gaudi framework to achieve the migration of transient objects to persistent objects The ROOT specific aspects are not discussed here the documentation of the ROOT I O engine can be page 157 GAUDI User Guide Chapter 13 Converters Version Issue 6 3 d Event 3E Me C MCECalFacePlaneHits Map of data store items 9 MCEcalHits to ROOT tree names 9 MCHcalHits Event H E MCMuorHits Event MC C MCPatticles Event MC MCECalFacePlaneHits MCRichPhotodectorHits Event MC MCECalHits C MCRichRadiatoHits fo ore MCTrackerHits C MCVertexHits E MCVertexPileUpHits MCVettices J RawEvent Figure 29 The Transient data store and its mapping in the Root file Note that the used within the data store to identify separate layers are converted to since the within ROOT denominates directory entries found at the ROOT web site http root cern ch Note that Gaudi only uses the I O engine not all ROOT classes are available Within Gaudi the ROOT I O engine is implemented in the DbCnv package 13 7 The Conversion from Transient Objects to ROOT Objects As for any conversion of data from one representation to another within the Gaudi framework conversion to from ROOT objects is based on Converters The support of a
143. ed for references in the case of a catalog element 8 5 5 3 Customization of the GUI The Option menu gives some possibilities e Value as attribute deals with the display of text nodes Text nodes are actually values of their parent node as in this example lt author gt Kraan dms Keach gt page 93 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 Smith alee aen SEN lt author gt In such a case the selection of the Value as attribute option will make the text node containing Smith appear as an attribute of the node author with Value as attribute name e Display comments no big deal here if it is selected comments will appear as comment nodes in the tree if not selected they are hidden e Attribute Displaying this allows the user to select the attributes he wants to display on the right panel and those he wants to hide Clicking on this option displays a little window where you can choose for each element in the dtd which are the attributes to be displayed Since this function is related to the dtd it has some limitations First it is not available if no dtd was found or if the one found is not valid Then the modifications you make in this option are only applied to the nodes that are using the current dtd it means the dtd of the node selected Maybe other nodes are using some other dtd because they are in another file referenced here and their display won t cha
144. ed using the templated service function In the example below we use this function to return the IParticlePropertySve interface of the Particle Properties Service Listing 50 Code to access the ParticlePropertySvc interface from an Algorithm include Gaudi Interfaces IParticlePropertySvc h IParticlePropertySvc m_ppSvc StatusCode sc service ParticlePropertySvc m_ppSvc if sc isFailure In components other than Algorithms which do not provide the service function you can locate a service using the serviceLocator function Listing 51 include Gaudi Interfaces IParticlePropertySvc h IParticlePropertySvc m_ppSvc StatusCode sc serviceLocator gt getService ParticlePropertySvc IID_IParticlePropertySvc reinterpret_cast lt IInterface amp gt m_ppSvc if sc isFailure page 112 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 11 3 The Job Options Service The Job Options Service is a mechanism which allows to configure an application at run time without the need to recompile or relink The options or properties are set via a job options file which is read in when the Job Options Service is initialised by the Application Manager In what follows we describe the format of the job options file including some examples 11 3 1 Algorithm Tool and Service Properties In general a concrete Algorithm Tool or Service will have sev
145. elements and material compounds and mixtures in XML Listing 27 Example of an isotope definition in XML lt xml version 1 0 encoding UTF 8 gt lt DOCTYPE DDDB SYSTEM materials dtd gt lt DDDB gt lt isotope name Bor_10 A 10 000 amp g amp mole Z 5 000 N 10 density 2 3400 amp g amp cm3 radlen 0 0000e 00 amp cm lambda 0 0000e 00 amp cm gt lt DDDB gt Listing 28 Example of XML definition of an element composed by isotopes lt xml version 1 0 encoding UTF 8 gt lt DOCTYPE DDDB SYSTEM materials dtd gt lt DDDB gt lt element name Boron symbol B density 2 3400 amp g amp cm3 radlen 0 00 amp cm lambda 0 00 amp cm gt lt element gt lt DDDB gt lt materialref href Bor_10 gt lt fractionmass value 0 20 gt lt materialref gt lt materialref href Bor_11 gt lt fractionmass value 0 80 gt lt materialref gt Listing 29 Example of a simple element definition in XML lt xml version 1 0 encoding UTF 8 gt lt DOCTYPE DDDB SYSTEM materials dtd gt lt DDDB gt lt element name Oxygen symbol O density 0 14300e 02 amp g amp cm3 radlen 23944 0 amp cm lambda 63636 0 amp cm gt lt atom A 15 999 amp g amp mole Zeff 8 0000 gt lt element gt lt DDDB gt Listing 30 Example of
146. elong to the filling algorithm and hence should be provided in the Algorithm s header file Currently the following data types are supported bool long float and double double types Fortran REAL 8 need special attention if using HBOOK for persistency the n tuple structure must be defined in a way that aligns double types to 8 page 100 it GAUDI Chapter 10 N tuple and Event Collection facilities User Guide Version Issue 6 3 byte boundaries otherwise HBOOK will complain In addition PAW cannot understand double types Listing 38 illustrates how to define n tuple tags Listing 38 Definition of n tuple tags from the Ntuples WriteAlg h example header file oO PWN FP NTuple Item lt long gt m_ntrk NTuple Array lt bool gt m_flag NTuple Array lt long gt m_index NTuple Array lt float gt m_px m_py NTuple Matrix lt long gt m_hits A scalar item Vector items number M_pZ Two dimensional tag 10 2 2 2 Booking and Declaring Tags to the N tuple When booking the n tuple the previously defined tags must be declared to the n tuple Before booking the proper output stream file must be accessed The target directory is defined automatically Listing 39 Creation of an n tuple in a specified directory and file YA oO BP WN EP ara oF WN EF CO WO CO N H O 21 3 22 23 24 25 Access the output file NTupleFilePtr filel ntupleSvc if
147. ement in the container whereas erase maybe used to remove any other element via an iterator In the code fragment above it is used to remove the last element also Deleting a contained object the third option above will automatically trigger its removal from the container This is done by the destructor of the ContainedOb ject base class If you wish to remove an object from the container without destroying it the second possible semantic use the release method hitContainer release hl page 58 GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 Since the fate of a contained object is so closely tied to that of its container life would become more complex if objects could belong to more than one container Suppose that an object belonged to two containers one of which was deleted Should the object be deleted and removed from the second container or not deleted To avoid such issues an object is allowed to belong to a single container only If you wish to move an object from one container to another you must first remove it from one and then add to the other However the first operation is done implicitly for you when you try to add an object to a second container containerl push_back hl Add to fist container container2 push_back h1 Move to second container Internally invokes release Since the object h1 has a link back to its container the push_back method is a
148. ementation of derived tools page 138 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 Listing 62 The definition of the AlgTool Base class 1 class AlgTool public virtual IAlgTool 2 public virtual IProperty 33 4 public 5 Standard Constructor 6 AlgTool const std string amp type const std string name const IInterface parent hes 8 virtual const std string amp name const 9 virtual const std string amp type const 10 virtual const IInterface parent const das 12 virtual StatusCode setProperty const Property amp p 13 virtual StatusCode getProperty Property p const 14 virtual const Property amp getProperty const std string amp name const 15 virtual const std vector lt Property gt amp getProperties const 16 17 ISvcLocator serviceLocator 18 IMessageSvc msgSvc 19 IMessageSvc msgSvc const 20 21 StatusCode setProperties 22 23 StatusCode declareProperty const std string amp name int amp reference 24 StatusCode declareProperty const std string amp name double amp reference 25 StatusCode declareProperty const std string amp name bool reference 26 StatusCode declareProperty const std string amp name std string amp reference 27 StatusCode declareProperty const std string amp name std vector lt int gt amp reference 28 StatusCode declareProperty const st
149. emonstrating filtering ApplicationMgr DLLs GaudiAlg ApplicationMgr TopAlg Sequencer TopSequence Setup the next level sequencers and their members TopSequence StopOverride true Sequencel Members Prescaler Prescalerl HelloWorld EventCounter Counterl1 8 Sequence2 Members Prescaler Prescaler2 HelloWorld EventCounter Counter2 YHA OB WNP 9i 10 Prescalerl PercentPass 50 11 Prescaler2 PercentPass 10 TopSequence Members Sequencer Sequencel Sequencer Sequence2 5 5 2 Sequence branching Listing 8 illustrates the use of explicit branching The BranchMembers property of the Sequencer specifies some algorithms to be executed if the algorithm that is the first member of the branch which is common to both the main and branch membership lists indicates a filter failure In this example the Event Counter instance Counter1 will report seeing 80 of the events whereas Counter2 will report seeing 20 Listing 10 Example jobOptions using Sequencers demonstrating branching 1 ApplicationMgr DLLs GaudiAlg 2 ApplicationMgr TopAlg Sequencer 3 4 Setup the next level sequencers and their members 5 Sequencer Members HelloWorld Prescaler EventCounter Counterl 6 Sequencer BranchMembers Prescaler EventCounter Counter2 7 8 Prescaler PercentPass 80
150. en of preselecting rows of the n tuple according to given criteria This option is only possible if supported by the underlying database used to make the n tuple persistent Currently it is possible to preselect rows from n tuples written in ROOT format and from relational databases using ODBC Note that the syntax of the query is also affected by the underlying technology while an ODBC database will accept any SOL query the ROOT implentation understands only the And and Or SQL operators but it does understand the full C syntax an example is given in section 10 3 2 page 102 GAUDI Chapter 10 N tuple and Event Collection facilities User Guide Version Issue 6 3 I Listing 41 Reading an n tuple at NTuplePtr nt ntupleSvc NTUPLES FILE1 ROW_WISE 2 2 if nt 3 long count 0 4 NTuple Item lt float gt px py pz G status nt gt item px px 6 status nt gt item py py 7 status nt gt item pz pz 8 nt gt attachSelector new SelectStatement pz gt 0O And px gt 0 9 Access the N tuple row by row and print the first 10 tracks 10 while ntupleSvc gt readRecord nt ptr isSuccess LEs log lt lt MSG INFO lt lt Entry lt lt countt lt lt J 123 log lt lt Px _ lt lt px lt lt Py lt lt py lt lt Pz lt lt pz 133 lt lt endreq 14 Los 10 2 3 N tuple Persistency 10 2 3 1 Input and
151. encies configuration management etc For that we need to introduce the concept of package as the grouping of related components together into a cohesive physical entity A package is also the minimal unit of software release We have decomposed the LHCb data processing software into the packages shown in Figure 2 At the lower level we find Gaudi which is the framework itself and does not depend on any external packages In the second level there are the packages containing standard framework components GaudiSvc GaudiTools GaudiAlg Auditors as well as the detector description tools Det Desc and the LHCb specific event data model LHCbEvent These packages depend on the framework and on widely available foundation libraries such as CLHEP and HTL In the same level we have specific implementations of the histogram persistency service based on HBOOK HbookCnv and ROOT Root HistCnv At the next level we will have packages consisting of implementations of event and detector data persistency services and converters In this release we have an LHCb specific one based on SICB and ZEBRA SicbCnv and a generic one DbCnv which currently understands ROOT and ODBC compliant databases and is being tested with Objectivity DB Finally at the top level we find the applications GaudiExamples DBCnv converters oe i GaudiAlg Auditors model pee a Figure 2 Current package structure of the LHCb software page 18 GAUDI User Guid
152. entity to replace it by the value displayed This will change in the next release page 94 it GAUDI User Guide Chapter 9 Histogram facilities Version Issue 6 3 Chapter 9 Histogram facilities 9 1 Overview The histogram data store is one of the data stores discussed in chapter 2 Its purpose is to store statistics based data and user created objects that have a lifetime of more than a single event e g histograms As with the other data stores all access to data is via a service interface In this case it is via the IHistogramSvc interface which is derived from the IDataProviderSvc interface discussed in chapter 6 The user asks the Histogram Service to book a histogram and register it in the histogram data store The service returns a pointer to the histogram which can then be used to fill and manipulate the histogram The histograms themselves are booked and manipulated using four interfaces as defined by the AIDA Abstract Interfaces for Data Analysis project These interfaces are documented on the AIDA web pages http wwwinfo cern ch asd lIhc AIDA index html The Gaudi implementation uses the transient part of HTL Histogram Template Library provided by LHC The histogram data model is shown in Figure 21 The interface Histogram is a base class which is used for management purposes It is not a complete histogram interface it should not be used by the users Both interfaces IHistogram1D and IHistogram2
153. er Sve EventDataSve EventDataSvc TDataProviderSve SICB specific DataProvider Svc EventDataSve PileupDataSvc TDataManager Svc SicbEventSelector PEA TSURSerSereEy TEventSelector The Algorithm and Nomnecdedran Service are merged RO IProperty into one Algorithm for the Sibc version Figure 30 Pile up in Gaudi In the future the two event selectors will use two different data services to access different data stores There could be several different pile up algorithms using a pile up service provided in the framework including all the common functionality needed by the different pile up algorithms The current implementation is very dependent on SICB and does not use any pile up service The following job options are necessary to instantiate the current implementation of the pile up structure First tell the ApplicationMgr to create a second SicbEventSelector called PileUpSelector ApplicationMgr ExtSvc SicbEventSelector PileUpSelector The application manager should know that the pile up algorithm should be run and the user has to configure how this algorithm works That configuration depends on the concrete implementation of the algorithm In the current PleUpAlg the user can select between two different implementations to get the number of pile up events for signal and minimum bias leading even
154. eractively Figure 5 shows a trace of an example program execution The diagram is not intended to be complete merely to illustrate a few of the points mentioned earlier in the chapter 1 The application manager instantiates the required services and initialises them The message service is done first to allow the other services to use it and the job options service is second so that the other services may be configured at run time 2 The algorithms which have been declared to the application manager within the job options via the TopAlg option are created We denote these algorithms top level as they are the only ones controlled directly by the application manager For illustration purposes we instantiate also an Empt yAlgorithmas well as the HistoAlgorithm of the example 3 The top level algorithms are initialised They may request that their properties if they have any are set and may make use of the message service If any algorithm fails to initialise the job is aborted 4 The application manager now starts to loop over events After each event is read it executes each of the top level algorithms in order The order of execution of the algorithms is the order in which they appear in the TopAlg option This will continue until the required number of events has been processed If a particular algorithm returns a FAILURE status code more than a configurable maximum number of times the application manager will decide that this al
155. eral data members which are used to control the execution of the service or algorithm These data members can be of a basic data type int float etc or class Property that encapsulates some common behaviour and higher level of functionality 11 3 1 1 SimpleProperties Simple properties are a set of classes that act as properties directly in their associated Algorithm Tool or Service replacing the corresponding basic data type instance The primary motivation for this is to allow optional bounds checking to be applied and to ensure that the Algorithm Tool or Service itself doesn t violate those bounds Available SimpleProperties are e int gt IntegerProperty or SimpleProperty lt int gt e double gt DoubleProperty or SimpleProperty lt double gt e bool gt BooleanProperty or SimpleProperty lt bool gt e std string gt StringProperty or SimpleProperty lt std string gt and the equivalent vector classes e std vector lt int gt gt IntegerArrayProperty or SimpleProperty lt std vector lt int gt gt e etc The use of these classes is illustrated by the Event Counter class Listing 52 EventCounter h 1 include Gaudi Algorithm Algorithm h 2 include Gaudi JobOptionsSvc Property h 3 class EventCounter public Algorithm 4 public Sit EventCounter const std string amp name ISvcLocator pSvcLocator 6 EventCounter TR StatusCode initialize 8 StatusCode execute
156. ertiesFile This string property is the name of the database file that should be used by the service to build up its list of particle properties The default value of this property on all platforms is SLHCBDBASE cdf particle cdf 11 5 3 Service Interface The service implements the IParticlePropertySvc interface which must be included when a client wishes to use the service the file to include is Gaudi Interfaces IParticlePropertySvc h The service itself consists of one STL vector to access all of the existing particle properties and three STL maps one to map particles by name one to map particles by Geant3 ID and one to map particles by stdHep ID Although there are three maps there is only one copy of each particle property and thus each property must have a unique particle name and a unique Geant3 ID The third map does not contain all particles contained in the other two maps this is because there are particles known to Geant but not to stdHep such as Deuteron or Cerenkov Although retrieving particles by name should be sufficient the second and third maps are there because most of the data generated by SICb stores a particle s Geant3 ID or stdHep ID and not the particle s name These maps speed up searches using the IDs page 122 GAUDI Chapter 11 Framewo User Guide rk services Version Issue 6 3 The IParticlePropertySvc interface provides the following functions Listing 55 The ParticlePropertySvc interface
157. es Some of these classes are very generic and they can be found in common class libraries For example the standard template library Other utilities will be more high energy physics specific especially in cases like fitting error treatment etc We envisage making as much use of these kinds of utility classes as possible Some algorithms or algorithm parts could be designed in a way that allows them to be reused in other similar physics algorithms For example perhaps fitting or clustering algorithms could be designed in a generic way such that they can be used in various concrete algorithms During design is the moment to identify this kind of re usable component or to identify existing ones that could be used instead and adapt the design to make possible their usage page 185 GAUDI Chapter 17 Design considerations User Guide Version Issue 6 3 HitPreprocessor TrackingAlg SeedFinder AI StationProcessor Tracker lAlgorithm nHitSet ProtoTrack Set K O PTrack Track Set Event Data Store Figure 33 Object diagram a and class diagram b showing how the complete example tracking algorithm could be decomposed into a set of specific algorithms that collaborate to perform the complete task page 186 W GAUDI User Guide Appendix A References Version Issue 6 3 Appendix A References 1 GAUDI Architecture Design Report LHCb 9
158. es produce a out ps PS file of the viewer spawn ghostview over the out ps file e reset page reset to a 1x1 viewer e erase page clear the regions e erase region clear only the current region e erase static delete the static scene graph of the current region In principle detector representations are put under the static scene graph Then erase static will clear the detector representations e erase dynamic delete the dynamic scene graph of the current region In principle event data representations are put under the dynamic scene graph Then erase dynamic will clear the detector representations e Page title on off set remove global page title e Color map a color chooser to set current modeling color usefull when working with Tree vis e Detector visualize various parts of the detector page 177 GAUDI User Guide Chapter 16 Visualization Facilities Version Issue 6 3 e Event e Next event bring a new event in memory at startup no event is loaded e MCParticle visualize event data e Tree if the GUI for exa gtk permits a tree visualization of the event the item under this pulldown menu permits action over the selected item in the tree GUI widget e Vis visualize the selected item in the tree widget e Viewers list of viewers Permit to change the active one 16 2 5 3D controls 3D Inventor examiner viewer controls are e right mouse button popup menu e r
159. es from the Monte Carlo tracks to the Monte Carlo vertices Please see in the corresponding SICB converter implementations how to construct these smart pointer objects Late loading is highly preferable compared to the second possibility 2 Filling of raw C pointers Here things are a little more complicated and introduces the need for a second step in the process This is only necessary if the object points to an object in another store e g the detector data store To resolve the reference a converter has to retrieve the other object and set the raw pointer These references should be set in the i110bjRefs method This of cousre is more complicated because it must be ensured that both objects are present at the time the reference is accessed i e when the pointer is actually used 13 5 Converter implementation general considerations After covering the ground work in the preceding sections let us look exactly what needs to be implemented in a specific converter class The starting point is the Converter base class from which a user converter should be derived For concreteness let us partially develop a converter for the UDO class of Chapter 6 The converter shown in Listing 73 is responsible for the conversion of UDO type objects into objects that may be stored into an Objectivity database and vice versa The UDOCnv constructor calls the Converter base class constructor with two arguments which contain this information These are th
160. etal le OR OR l a angle CDATA i A ly 1 lt EMPTY gt gt lt lt EMPTY gt gt Z lt lt EMPTY gt gt lt lt EMPTY gt gt rotXYZ posxYZ posRPhiZ posRThPhi 1 rotX CDATA x CDATA r CDATA r CDATA rotY CDATA y CDATA phi CDATA theta CDATA rotZ CDATA z CDATA z CDATA phi CDATA param physvol must contain one physvol initial position and then one of the positions and one LS of the rotations for transformation step Figure 16 Content model definition for parametric physical volume element The example shows two logical volumes 1vLHCb and lvVertex The former volume is made of the material Vacuum and its solid is defined as a box with dimensions 50 x 50 x 60 meters Then it has ascribed one daughter volume lvVertex positioned inside the lvLHCb volume without rotation and shifted along the z axis by 200 millimetres The 1vVertex volume is made of material Silicon and its shape is defined by the solid tubs cylinder and has one parametric physical volume which places 6 daughter volumes of lvVStation The initial position of the first daughter volume is placed 200 millimeters backwards along the Z axis relative to the center ofthe 1vVertex mother volume The remaining daughter volumes are then shifted by 50 millimeters along Z axis one by one relative to the previous one without rotation page 83 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 Listing 25 Example of a lo
161. evt MC MCParticles 12 for MCParticleVector iterator itm vmcparts gt begin vmcparts gt end itm itmt 133 AxPartCandidate mptry 0 Las StatusCode sc m_pAsct gt retrieveInverse itm mptry L552 if sc isSuccess 16 else Tes x 18 Example of retrieving direct one to many information from an 19 associator 20 SmartDataPtr lt AxPartCandidateVector gt candidates evt Anal AxPartCandidates 21 std vector lt ContainedObject gt pptry 22 AxPartCandidate itP candidates gt begin 23 StatusCode sa m_pAsct gt retrieveDirect itP pptry MCParticle classID 24 if sa isFailure 25 else 26 for std vector lt ContainedObject gt iterator it pptry begin pptry end it it 27 MCParticle imc dynamic_cast lt MCParticle gt it 28 ZOe oi page 149 GAUDI Chapter 12 Tools and ToolSvc User Guide Version Issue 6 3 page 150 GAUDI User Guide Chapter 13 Converters Version Issue 6 3 Chapter 13 Converters 13 1 Overview Consider a small piece of the LHCb detector a silicon wafer for example This object will appear in many contexts it may be drawn in an event display it may be traversed by particles in a Geant4 simulation its position and orientation may be stored in a database the layout of its strips may be queried in an analysis program etc All of these uses o
162. f a Physical Volume are in the local reference system of its parent Logical Volume Sometimes one needs a more efficient way of extracting information from the geometry tree or to compute the unique location of a point in the geometry tree For these purposes a simplified detector description tree is introduced into the Gaudi framework The next subsections give brief details of the implementations of Logical Volumes Physics Volumes and Solids in Gaudi More detailed documentation can be found at http cern ch lhcb comp Components html GaudiReference htm 1 This is equivalent to the absence of the MANY flag in the GEANTS toolkit 2 Within the Geant4 toolkit there exist two approaches for solving the same problem Read Out Geometry Tree and Navigator Our approach is quite close to the combined usage of both page 74 it GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 8 4 1 Logical Volumes The notion of Logical Volume is implemented in Gaudi by the class LVolume LVolume is an identifiable object and therefore inherits from class DataObject and can be identified in the transient data store by a unique name its path It implements the ILVolume and IValidity interfaces 8 4 2 Physical Volumes The notion of Physical Volume in the Gaudi geometry is extremely primitive it is just a Logical volume which is positioned inside its mother Logical Volume It consists of the name of the Logical Volume to be positi
163. first is the type i e the class of the Tool object being instantiated the second is the full name of the object and the third is a pointer to the IInterface of the parent component The name is used for the identification of the tool instance as described below The parent interface is used by the tool to access for example the output Level of the parent IAlgTool Interface It consists of three accessor methods for the identification and managment of the tools type name and parent These methods are all implemented by the base class and should not be overridden 12 2 2 2 Tools identification A tool instance is identified by its full name The name consist of the concatenation of the parent name a dot and a tool dependent part The tool dependent part can be specified by the user when not specified the tool type i e the class is automatically taken as the tool dependent part of the name Examples of tool names are RecPrimaryVertex VertexSmearer a private tool and ToolSvc AddFourMom a shared tool The full name of the tool has to be used in the jobOptions file to set its properties 12 2 2 3 Concrete tools classes Operational functionalities of tools must be provided in the derived tool classes A concrete tool class must inherit directly or indirectly from the AlgToo1 base class to ensure that it has the predefined behaviour needed for management by the Tool Svc The inheritance structure of derived tools is shown in Fi
164. for the HBOOK data format you need to specify the use of the DoCnv package in your CMT requirements file and to load explicitly in the job options the DLLs DbConverters and either Root Db or OdbcDb These DLLs contain the specific database access drivers implementations e OPT lt opt spec gt e NEW CREATE WRITE Create a new data file Not all implementations allow to over write existing files e OLD READ Access an existing file for read purposes e UPDATE Open an existing file and add records It is not possible to update already existing records e SVC lt service spec gt optional Connect this file directly to an existing conversion service This option however needs special care It should only be used to replace default services e AUTHENTICATION lt authentication specs gt optional For protected datafiles e g Microsoft Access it can happen that the file is password protected In this case the authentication string allows to connect to these databases The connection string in this case is the string that must be passed to ODBC for example AUTH SERVER server_host UID user_name PWD my_password e All other options are passed without any interpretation directly to the conversion service responsible to handle the specified output file For all options at most three leading characters are significant DATAFILE lt gt DATABASE lt gt or simply DATA lt gt would lead to the same result
165. framework should be usable for implementing the full range of offline computing tasks the generation of events simulation of the detector event reconstruction testbeam data analysis detector alignment visualisation etc etc In this document we present the main components of the framework which are available in the current release of the software It is intended to increment the functionality of the software at each release so this document will also develop as the framework increases in functionality Having said that physicist users and developers actually see only a small fraction of the framework code in the form of a number of key interfaces These interfaces should change very little if at all and the user of the framework cares very little about what goes on in the background The document is arranged as follows Chapter 2 is a short resume of the framework architecture presented from an Algorithm centric point of view and re iterating only a part of what is presented in the ADD Chapter 3 contains a summary of the functionality which is present in the current release and details of how to obtain and install the software page 7 GAUDI User Guide Chapter 1 Introduction Version Issue 6 3 Chapter 4 discusses in some detail an example which comes with the framework library It covers the main program some of the basic aspects of implementing algorithms the specification of job options and takes a look at how
166. g 102 Service 99 O Object Container 56 and STL 57 ObjectList 57 ObjectVector 57 ODBC For N Tuple analysis 109 P Package 17 Guidelines for sub detectors 19 Internal layout 19 structure of LHCb software 17 PAW for N Tuple analysis 108 Persistency of histograms 98 of N tuples 103 Persistent store saving data to 62 Pile up 167 Platform 27 Available platforms 27 Prescaler algorithm See Algorithms Problems Reporting 10 Profiling of execution time using the Chrono amp Stat service 125 of execution time with the Auditor service 128 of memory usage with the Auditor service 128 R Random numbers generating 130 Service 130 Release notes 23 Reporting problems 10 Retrieval 143 ROOT 172 for histogram persistency 98 for N Tuple analysis 108 page 215 GAUDI Index User Guide Version Issue 6 3 S Saving data 62 Sequencer algorithm See Algorithms Sequences 50 Services 15 Auditor Service 128 Chrono amp Stat service 125 Histogram Persistency Services 98 Incident service 133 Job Options service 113 Magnetic Field Service 164 Message Service 119 N tuples Service 99 Particle Properties Service 122 Random numbers service 130 requesting and accessing 111 ToolSvc 137 142 vs Tools 137 SmartDataLocator 61 SmartDataPtr 61 SmartRef 61 StatusCode 47 Sub detectors Software packaging guidelines 19 T Tools 137 Associators 145 provided in Gaud
167. gical volume definition in XML lt xml version 1 0 encoding UTF 8 gt lt DOCTYPE DDDB SYSTEM xmldb dtd gt lt DDDB gt lt logvol name l1vLHCb material Vacuum gt lt box name caveBox sizeX 50 amp m sizeY 50 amp m sizeZ 60 amp m gt lt physvol name VertexSubsystem logvol dd Geometry lvVertex gt lt posXYZ x 0 amp mm y 0 amp mm z 200 amp mm gt lt physvol gt lt logvol gt lt logvol name lvVertex material Silicon gt lt tubs name vertexTubs sizeZ 6 amp m innerRadius 0 amp mm outerRadius 20 mm startPhiAngle 0 amp degree deltaPhiAngle 360 amp degree gt lt paramphysvol number 6 gt lt physvol name pvStation logvol dd Geometry lvVStation gt lt posXYZ x 0 amp mm y 0 amp mm z 200 amp mm gt lt physvol gt lt posXYZ x 0 amp mm y 0 amp mm z 50 amp mm gt lt rotXYZ rotX 0 amp mm rotY 0 amp mm rotZ 0 amp mm gt lt paramphysvol gt lt logvol gt lt DDDB gt Simple solids Simple solids are based on the concept of Constructive Solid Geometry CSG This concept is nothing new it has been used already by GEANT3 and Geant4 and by the other frameworks There are defined the solids of the basic 3D volumes such as sphere box cylinder conus toroid The solid definition is fundamental property of a logical
168. gorithm is badly configured and jump to the finalisation stage before all events have been processed 5 After the required data sample has been read the application manager finalises each top level algorithm 6 Services are finalised 7 All objects are deleted and resources freed The program terminates 4 7 Simple Physics Analysis Example An example of how to do some very simple physics analysis is provided in the GaudiExamples package The algorithms in the example use many of the Gaudi Services that someone would want to be able to utilize while doing physics analysis histograms ntuples creating and retrieving private transient data retrieving particle properties like mass values etc Detailed examples on how to use the specific services are provided in the topical examples but in the SimpleAnalysis example they are combined together Tools to make physics analysis in a more elegant and complex way are under development and their concrete implementation will be part of the OO Physics Analysis Program A trivial implementation of an algorithm similar to that of the SimpleAnalysisAlgorithm implemented using tools is provided in the ToolAnalysis example page 39 GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 configure create initialize MessageSvc create initialize JobOptionsSvc create EmptyAlgorithm create HistoAlgorithm declarePropefty syslnitialize initialize
169. gure 24 ConcreteTool1 implements one additional abstract interface while ConcreteTool3 and ConcreteTool14 derive from a base class SubTool that provides them with additional common functionality TAlgTool P T IProperty AlgTool A O ConcreteTool1 Concrete Tool2 SubTool IConcreteTool1 ISubTool A Concrete Tool3 Concrete Tool4 Figure 24 Tools classes hierarchy The idea is that concrete tools could implement additional interfaces specific to the task a tool is designed to perform Specialised tools intended to perform similar tasks can be derived from a common base class that will provide the common functionality and implement the common interface Consider as example the vertexing of particles where separate tools can page 140 it GAUDI Chapter 12 Tools and ToolSvc User Guide Version Issue 6 3 implement different algorithms but the arguments passed are the same If a specialized tool is only accessed via the additional interface the interface itself must inherit from the I AlgTool interface in order for the tool to be correctly managed by the Tool Svc 12 2 2 4 Implementation of concrete tools An example minimal implementation of a concrete tool is shown in Listing 63 and Listing 64 taken from the ToolsAnalysis example application distributed with the Gaudi framework Listing 63 Example of a concrete tool mini
170. h change should be recorded as a different version of the detector element Additionally it should be possible to capture for an entire description a version of each of the elements and to associate a name to that set This is similar to the way CVS allows one to tag a set of files so that one does not need to know the independent version numbers for each file in the set page 70 it GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 8 3 Using the Detector Data transient store 8 3 1 Structure of the transient store The transient representation of the detector description is implemented as a standard Gaudi data store Refer to Chapter 6 for general information on how to access data in stores The structure of the detector transient store is represented in Figure 10 There are various branches in the hierarchical tree structure and probably there will be more of them defined in the future At present there are three top level catalogs in the transient store The main catalog called Structure contains the logical structure of the detector identified by the setup name i e LHCb containing the description of the detector and this catalog is used for identification and navigation purposes Other catalogs are the palette of logical volumes and solids called Geometry used for the geometry description and the palette of materials called Materials used to describe the material properties of th
171. he current implementation allows to create boolean solids as a union intersection or subtraction of several simple solids The content model is shown in Figure 18 union name ID EI TISON A S e cons 1 W a sphere name sizeZ CDATA tubs pox ODATA outerRadiusPZ CDATA name ID name ID name ID outerRadius CDATA innerRadiusPZ CDATA sizeZ CDATA sizeZ CDATA sizeX CDATA innerRadius CDATA startP hiA ngle CDATA sizeX1 CDATA startPhiAngle CDATA sizeY CDATA startPhiA ngle CDATA outerRadiusMZ CDATA sizeX2 CDATA deltaPhiAngle CDATA sizeZ CDATA deltaPhiA ngle CDATA innerRadiusMZ CDATA sizeY1 CDATA outerRadius CDATA startThetaA ngle CDATA deltaPhiA ngle CDATA sizeY2 CDATA innerRadius CDATA deltaThetaA ngle CDATA Figure 18 Content model definition of a union boolean solid applies to all boolean solids The user has to start with the so called main solid and all the other solids participating in the boolean solid are positioned relative to the main solid In this context the position and rotation attributes of solids are applied together with their dimensions attributes Listing 26 shows how to create a simple union of solids Listing 26 Example of boolean solid in XML lt xml version 1 0 encoding UTF 8 gt lt DOCTYPE DDDB SYSTEM xmldb dtd gt lt DDDB g
172. hild of the DDDB element Inside the root node catalog the top level catalogs can be defined according to the required content See Listing 23 for an example Listing 23 Example of a boostrap file for the detector description lt xml version 1 0 encoding UTF 8 gt lt DOCTYPE DDDB SYSTEM DTD structure dtd gt lt DDDB gt lt catalog name dd gt lt catalogref href structure xml Structure gt lt catalogref href geometry xml Geometry gt lt catalogref href materials materials xml Materials gt lt catalog gt lt DDDB gt In the example the root nodes catalog dd and its three top level catalogs for logical detector description geometry and materials are defined Note that the catalog and catalogref tags have not specified the classID attribute This shows how the validation can reduce the amount of the text in XML because these values are automatically included after the page 79 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 document has been validated against the DTD file structure dtd specified in the DOCTYPE section The catalog and catalogrefs are used as bookshelves or references to bookshelves respectively to achieve a possibility to split the XML database into logical partitions The catalogref element acts as forward reference saying where to find the given catalog definition This tag is one of the XML references defined for the detector de
173. hm is to take input data manipulate it and produce new output data Figure 1 shows how a concrete algorithm object interacts with the rest of the application framework to achieve this The figure shows the four main services that algorithm objects use e The event data store e The detector data store e The histogram service e The message service The particle property service is an example of additional services that are available to an algorithm The job options service see Chapter 11 is used by the Algorithm base class but is not usually explicitly seen by a concrete algorithm page 15 GAUDI User Guide Chapter 2 The framework architecture Version Issue 6 3 ISvcLocator ApplicationManager Oe MessageService DW ESES TE SVE A aa e a ParticlePropertySve I ParticleProperty Svc Ay yaliicattion Figure 1 The main components of the framework as seen by an algorithm object Each of these services is provided by a component and the use of these components is via an interface The interface used by algorithm objects is shown in the figure e g for both the event data and detector data stores it is the IDataProviderSvc interface In general a component implements more than one interface For example the event data store implements another interface IDat aManager which is used by the application manager to clear the store before a new event is read in An algorithm
174. hod2 SpecificService method3 SpecificService method4 aA man ee aS GS ee void ppvIF page 136 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 Chapter 12 Tools and ToolSvc 12 1 Overview Tools are light weight objects whose purpose is to help other components perform their work A framework service the Too1Svc is responsible for creating and managing Tools An Algorithm requests the tools it needs to the Too1Svc specifying if requesting a private instance by declaring itself as the parent Since Tools are managed by the Too1Svc any component can request a tool Only Algorithms and Services can declare themselves as Tools parents In this chapter we first describe these objects and the difference between private and shared tools We then look at the AlgToo1 base class and show how to write concrete Tools In section 12 3 we describe the Tool Svc and show how a component can retrieve Tools via the service Finally we describe Associators common utility GaudiTools for which we provide the interface and base class 12 2 Tools and Services As mentioned elsewhere Algorithms make use of framework services to perform their work In general the same instance of a service is used by many algorithms and Services are setup and initialized once at the beginning of the job by the framework Algorithms also delegate some of their work to sub algor
175. i 144 vs Services 137 ToolSvc see Services U Units 8 Convention 8 V Visualization 173 GaudiLab 174 WwW Windows NT 27 page 216 GAUDI Index User Guide Version Issue 6 3 X XML converter 89 detector description 77 Editor 92 introduction to 76 page 217 GAUDI Index User Guide Version Issue 6 3 page 218
176. i_v233_100ev dst1 2 Specify a data set by giving the job identification numbers in the book keeping data base as was done in SICB The framework will query the ORACLE database in order to find the corresponding tape and then stage it in The access to the database is through the oraweb01 web server at CERN as for the mcst agein script The job IDs are specified in the job options file as follows EventSelector Input JOBID 16434 16435 3 Read one or more tape files even if they are not in the LHCb production book keeping database for example test beam data The user should tell the Event Selector which tape s and file s to read in the following way EventSelector Input TAPE Y21221 7 Y21223 24 The format is lt Volume serial number of the tape gt lt File sequence number gt When a Gaudi job requires to stage more than one tape the program waits for the first tape to be staged The rest of the required tapes are staged while the first file is processed Once the program ends reading the first file it will check if the next file is ready before continuing If the tape is not staged yet the program writes a message and waits until the file is in the staging disk pools Skipping events When reading SICB data one may wish to skip some events This can be done by setting the property Event Selector FirstEvent For example to start process
177. ic field service one should modify the jobOptions txt file to include the following ApplicationMgr ExtSve MagneticFieldSvc Any algorithm which requires the use of the service makes a request via the service method of the Algorithm base class IMagneticFieldSvc pIMF 0 StatusCode sc service MagneticFieldSvc pIMF The service provides a method StatusCode fieldVector HepPoint3D amp Pos HepVector3D amp field page 164 GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 which gives a magnetic field vector at a given point in space for example HepPoint3D P 10 cm 10 cm 120 cm HepVector3D B pIMF gt fieldVector P B The magnetic field service uses a new version of the SICB routine GUF LD In this new version the best possible description of the magnet geometry and the field are assumed in order to eliminate dependencies with other parts of SICB Technically in SICB this corresponds to ll ws IMAGLEV IUVERS IFLDLEV IUVERS EOM MAGN EOM MFLD ws These two parameters have been fixed to 4 in the production since a few months before the Technical Proposal version 111 of SICB Thus this seems to be a reasonable restriction until the field map is provided in the detector description database For an example of the use of this serv
178. ice see the sub algorithm readMagField in the example FieldGeom distributed with the release 14 5 Accessing the SICB detector geometry from Gaudi As discussed previously the detector geometry will be included along with the field map in the XML detector description database Currently only a part of the LHCb detector is in the new database However the detector geometry used in the production of the data can be accessed by calling a function in the SicbFortran name space this function is just a wrapper for the FORTRAN function of similar name void SichFortran utdget const std string amp al const std string amp a2 int amp nParam int data nParam should be set to the number of data words required and on return from the function will contain the number of data words actually copied into the array data The first string contains the name of the sub detector whose geometry is being requested and the second string is a list of options V version G geometry description parameters default C calculated geometry not in cdf hit description parameters D digitization parameters R reconstruction parameters F floating point parameters default T integer parameters N take parameters from the cdf file page 165 GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 L ZEBRA pointer to the beginning of the parameter
179. ich algorithms to run what properties of which algorithm to inspect and modify etc This interaction can be implemented using a graphical user interface or by using a scripting language The User interface service is also in charge of managing one or more GUI windows where views of the graphical representations are going to be displayed Interactive User Interface xxLabSvc a SoCnvSvc Transient Event Data Graphical AM Scene S4 gt 4 SoXXCnv Transient Detector Data Figure 31 Components for visualization The other main component is a Conversion Service that handles the conversion of objects into their graphical representation This service requires the help of a number of specialized converters one for each type of data object that needs to be graphically displayed The transient store of graphical representations is shared by the conversion service together with the converters and the user interface component The form of this transient store depends on the choice of graphics package Typically it is the user interface component that would trigger the conversion service to start the conversion of a number of objects next event but this service can also be triggered by any algorithm that would like to display some objects 16 2 The GaudiLab service 16 2 1 Design layout
180. ight popup decorations enable the Inventor decorations not available for all GUD e decoration pointer pass pointer in picking mode e decoration hand pass pointer in viewing mode e popup viewing toggle pointer mode viewing to picking e decoration eye or popup view all map the scene to the window size e decoration home or popup home return to home position e decoration home pointer or popup Set home set home position to be the current one e decoration target or popup Seek ask for picking and center the scene over a picked point e left ptr move permits to rotate the scene e left middle ptr move permit to scale the scene e ctrl shift left ptr move permits to scale the scene e ctrl left ptr move permits to pane the scene e middle ptr move permit to pane the scene 16 2 6 Writing graphic converters The role of each converter So lt xxx gt Cnv is to produce an Open Inventor node that represents the object The following fragment of code shows how this is done for the geometry of a detector element The code has been simplyfied to be more illustrative The 3D graphical objects that are created are standard OpenInventor objects in bold page 178 it GAUDI Chapter 16 Visualization Facilities User Guide Version Issue 6 3 Listing 77 Fragment of SoDetectorElementCnv Zo Dae ie 28 29 30 g1 B28 33 34 35 36 Bhs 38 BO 40
181. ils to pass a filter 10 3 1 1 Defining the Address Tag The event data is accessed using a special n tuple tag of the type NTuple Item lt IOpaqueAddress gt m_evtAddress It is defined in the algorithm s header file in addition to any other ordinary n tuple tags as described in section 10 2 2 1 When booking the n tuple the address tag must be declared like any other tag as shown in Listing 42 It is recommended to use the name Address for this tag The usage of this tag is identical to any other tag except that it only accepts variables of type IOpaqueAddress the information necessary to retrieve the event data page 105 GAUDI Chapter 10 N tuple and Event Collection facilities User Guide Version Issue 6 3 Listing 42 Connecting an address tag to an n t uple NTuplePtr nt ntupleSvc Book N tuple E WN FH Add an event address column StatusCode status nt gt addItem Address m_evtAddress NTUPLES EvtColl Collection 10 3 1 2 Filling the Event Collection At fill time the address of the event must out to the event collection be supplied to the Address item Otherwise the n tuple may be written but the information to retrieve the corresponding event data later will be lost Listing 43 also demonstrates the setting of a filter to steer whether the event is written Listing 43 Fill the address tag of an n tuple at execution time if
182. imensional arrays bool size long size float size e Matrix lt TYPE gt are equivalent to an array of arrays or matrix bool dim1 dim2 There is no implicit bounds checking possible without a rather big overhead at run time Hence it is up to the user to ensure the arrays do not overflow When all entries are filled the row must be committed i e the record of the n tuple must be written Listing 40 Filling an n tuple 1 m_ntrk 0 2 for MCParticleVector iterator i mctracks gt begin i mctracks gt end i 3 3 const HepLorentzVector amp mom4 i gt fourMomentum 4 m_px m_ntrk mom4 px AS m_py m_ntrk mom4 py b3 m_pz m_ntrk mom4 pz Ts m_index m_ntrk cnt 8 m_flag m_ntrk m_ntrk 2 0 true false Ors m_hits m_ntrk 0 0 10 m_hits m_ntrk 1 1 La m_ntrk 12 Make sure the array s do not overflow 3s if m_ntrk gt m_ntrk gt range distance break 14 15 Commit N tuple row 16 status ntupleSvc gt writeRecord NTUPLES FILE1 MC 1 17 if status isSuccess 18 log lt lt MSG ERROR lt lt Cannot fill id 1 lt lt endreq 19 ZOee oh 10 2 2 4 Reading N tuples Although n tuples intended for interactive analysis they can also be read by a regular program An example of reading back such an n tuple is given in Listing 41 Notice line 8 where an example is giv
183. in XML In the example we had the following XML elements Email TimeStamp Sender Recipient Subject Body Signature The very basic and mandatory rule of XML is that all XML element tags page 76 it GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 must nest properly and there must be only one root XML element at the top level of each XML document which contains all the others Proper nesting means that each XML element has its opening and closing tag and the closing tag must appear before the parent element s closing tag as shown in Listing 22 Following these rules one can always produce well formed XML documents Listing 22 XML elements syntax and proper vs invalid nesting lt xml version 1 0 encoding UTF 8 standalone yes gt lt Root tag is top level root element of XML file gt lt Root gt lt Elements which are empty gt lt EmptyElement gt lt EmptyWithAttributes attrl first attr2 second gt lt Elements having content model gt lt ProperNesting gt lt Something gt In lt Something gt lt ProperNesting gt lt WRONGNESTING gt lt BADTHING gt huhu lt WRONGNESTING gt lt BADTHING gt lt Root gt XML elements can have attributes and a content Attributes usually describe the properties of the given element The value of the attribute follows the assignment operator and is enclosed inside
184. ing at event 109 add the following job option EventSelector FirstEvent 109 The algorithms will run only after reading that event Note that Gaudi will take a few seconds to reach the requested event as it has to read all the records in the Zebra file before the one requested page 162 GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 14 3 Populating the GAUDI transient data store SICB Converters 14 3 1 General considerations Access to the SICB data sets is basically via wrappers to the FORTRAN code A complete event is read into the Zebra common block and then the conversion to transient objects is done on request by specialised converters As mentioned in Chapter 13 a converter must implement the Converter interface by deriving from a specific base class In this way any actions which are in common to all converters of a specific technology may be implemented in a single place In the following section we give detailed instructions on how to implement converters within the SicbCnv package These are intended primarily for Gaudi developers themselves 14 3 2 Implementing converters in the SicbCnv package SICB converters are available for reading most SICB banks the full list of converted banks is available at http cern chAhcb comp Support html ConvertedSICBBanks htm Writing back into persistent storage ZEBRA files is under development for a few banks Typically GAUDI D
185. ing of each element Both active and passive elements should be included The description of active elements should allow for the specification of deficiencies dead channels alignment corrections etc and also detector response characteristics e g energy normalization in calorimeters drift velocity in gas chambers Data Processing Application Projection view version amp event time Transient detector Conversion store services Other representations Update persistency Figure 9 Overview of the Detector Description model The logical description provides two main functions The first is a simplified access to particular parts of a physical detector description This could be a hierarchical description where a given detector setup is composed of various sub detectors each of which is made up of a number stations modules or layers etc and there would be a simple way for a client to use this description to navigate to the information of interest The second function of the logical description is to provide a means of detector element identification This allows for different sets of information which are correlated to specific detector elements to be correctly associated with each other In a detector description the definition of the detector elements and of the data associated to their physical description may vary over time for instance due to real or hypothetical changes to the detector Each suc
186. ing with development releases This User Guide corresponds to release 6 of the Gaudi software Subsequent to this release new features may be added to the CVS repository which will not become generally available and documented until the next release Should you wish to use some of these new features before then you can pick them up from the development release area 3 7 1 The development release area Development releases of packages are made periodically into the AFS directory tree below afs cern ch lhcb software DEV pointed to by the LHCBDEV environment variable on Unix by checking out and building the CVS head revision of modified packages The directory structure of LHCBDEV is analogous to LHCBSOFT there is a subdirectory per package below which there are subdirectories for each development release version of that page 28 it GAUDI User Guide Chapter 3 Release notes and software installation Version Issue 6 3 package These subdirectories have a name which reflects the date of the build e g 1000626 was built on 26th June 2000 The most recent successful build is pointed to by a logical link whose version number is the current release version number In this way if the area LHCBDEV is before LHCBSOFT in the CMTPATH the head revision in DEV will be used for the packages that can be found there 3 7 2 Using the development version of packages The directory structure described above was designed to make it e
187. inition static entities When mixing C code with FORTRAN it is recommended to build separate libraries for the C and FORTRAN and to write the code in such a way that communication between the C and FORTRAN world is done exclusively via wrappers as is done for example in the SicbCnv package see in particular the file SicbCnv TopLevel SicbFortran cpp In this way it is possible to build shareable libraries for the C code even if it calls FORTRAN code internally page 21 GAUDI Chapter 2 The framework architecture User Guide Version Issue 6 3 page 22 GAUDI User Guide Chapter 3 Release notes and software installation Version Issue 6 3 Chapter 3 Release notes and software installation 3 1 Release History Version Date Package List v6 10 11 2000 Gaudi v8 GaudiSvc v4 GaudiAlg v1r1 LHCbEvent v8 SicbCnv v9 DbCnv v3 HbookCnv v7 DestDesc v5 GaudiExamples v9 Audi tors v1 GaudiTools v1 RootHistCnv 1 XmlEditor v1 GaudiLab v2 v5 24 07 2000 Gaudi v7 GaudiSvc v3 GaudiAlg v1 LHCbEvent v7r1 SicbCnv v8 DbCnv v2 HbookCnv v6rl DestDesc v4 GaudiExamples v8 v4 14 04 2000 Gaudi v6 GaudiSve v2 LHCbEvent v7 SicbCnv v7 DbCnv v1 HbookCnv v6 DestDesc v3 GaudiExamples v7 v3 19 11 1999 Gaudi v5 LHCbEvent v6 SicbCnv v6 RootCnv v3 HbookCnv v5 DestDesc v2 GaudiLab v1 GaudiExamples v6 v2 18 6 1999 Gaudi v4 LHCbEvent v5 SicbCnv v5
188. inked into the executable as an object file no action is necessary However usually the converter code resides in a shared or archive library In this case the library must have an initialisation routine which creates an artificial reference to the created converter and forces the linker to include the code in the executable An example of creating such a reference can be found in the file SLHCBSOFT SicbCnv lt version gt SicbCnv SicbCnvD11 SicbCnv_load cpp The convention for these initialization files is the following for any other package replace the string SicbCnv with OtherPackage e Compile link debug e Once the converter works remove unnecessary TODO comments 14 4 Access to the Magnetic Field The magnetic field map will be accessible in the future via the transient detector store For the time being as this is not implemented and as access to the magnetic field has been requested we have provided a magnetic field service Again this is effectively just a wrapper which uses SICB routines to read the information from a cdf file The location of the field cdf file is provided by the standard stream file which is read in by a SICB routine called from Gaudi This file is in the data base area LHCBDBASE standard streamin AFS For every version the file used in the production is read in The location of the standard stream file will be taken from an environment variable as per normal SICB operation To use the Magnet
189. ions txt Path for job options source a The EvtSel property of ApplicationMegr is replaced by the property Input of EventSelector Only the value NONE is still valid I b A basic DataObject object is created as event root Event c The setting of properties from the main program is discussed in chapter 4 Table B 2 Standard Options for the message service MessageSvc Option name Default value Meaning OutputLevel 0 Verboseness threshold level 0 NIL 1 VERBOSE 2 DEBUG 3 INFO 4 WARNING 5 ERROR 6 FATAL Format Yo FRIBW S 7WPRVT YOW M Format string Table B 3 Standard Options for all algorithms lt myAlgorithm gt Any algorithm derived from the Algorithm base class can override the global Algorithm options thus Default Option name value Meaning OutputLevel 0 Message Service Verboseness threshold level 0 NIL 1 VERBOSE 2 DEBUG 3 INFO 4 WARNING 5 ERROR 6 FATAL Enable true If false application manager skips execution of this algorithm ErrorMax 1 Job stops when this number of errors is reached ErrorCount 0 Current error count I AuditInitialize false Enable Disable auditing of Algorithm initialisation I AuditExecute true Enable Disable auditing of Algorithm execution I AuditFinalize false Enable Disable auditing of Algorithm finalisation page 190 Appendix B Options for standard components User Guide Version Issue 6 3 Table B 4 St
190. itect page 19 GAUDI User Guide Chapter 2 The framework architecture Version Issue 6 3 Note that sub detectors are expected to organise their own project releases for internal group consumption and integration tests using the LHCBDEV development area described in Section 3 7 1 Once the code is ready for public collaboration wide use it should be released by the librarian in the public release area LHCBSOFT 2 5 3 Libraries in Gaudi In the Gaudi framework development environment we can distinguish two different types of libraries component libraries and linker libraries These libraries are used for different purposes and built in different ways Here we mention their characteristics 2 5 3 1 Component libraries These are libraries containing one or many software components implementing a number of abstract interfaces For example this is the case for Gaudi libraries containing Algorithms Services Tools etc These libraries do not export symbols they export only one which is used internally by the framework to discover what the library contains These libraries are not needed for linking the application they are used eventually if we explicitly load them at runtime This is done by the property Applicat ionMgr DLLs which is the list of component libraries that the framework should load dynamically Obviously changes in these libraries implementations never require an application to be re linked When th
191. ithms Creation and execution of sub algorithms are the responsibilities of the parent algorithm whereas the initialize and finalize methods are invoked automatically by the framework while initializing the parent algorithm 1 In this chapter we will use an Algorithm as example component requesting tools page 137 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 12 2 1 12 2 2 12 2 2 1 The properties of a sub algorithm are automatically set by the framework but the parent algorithm can change them during execution Sharing of data between nested algorithms is done via the Transient Event Store Both Services and Algorithms are created during the initialization stage of a job and live until the jobs ends Sometimes an encapsulated piece of code needs to be executed only for specific events in which case it is desirable to create it only when necessary On other occasions the same piece of code needs to be executed many times per event Moreover it can be necessary to execute a sub algorithm on specific contained objects that are selected by the parent algorithm or have the sub algorithm produce new contained objects that may or may not be put in the Transient Store Finally different algorithms may wish to configure the same piece of code slightly differently or share it as is with other algorithms To provide this kind of functionality we have introduced a category of processing objects that encapsu
192. jects created and used during data analysis The include files for the contained classes can be found in LHCbEvent Analysis h with obvious names Currently only the class AxPartCandidate is implemented derived from the SICB bank AXTK Table 8 Analysis Event data model Logical Path Container Type 7 Event Anal AxPartCandidates AxPartCandidateVector 7 7 Utilities A series of utility classes are defined e DetectorDataObject CLH EPStreams TimeStamp Classification ProcessingVersion Cellid ParticlelId TriggerPattern RandomNumberSeed SummaryPID used in several places in the LHCb event data model and SummarySeesDetectors These are page 68 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 Chapter 8 Detector Description 8 1 Overview In this chapter we describe how we make available to the physics application developed using the framework the information related to the detector that resides in the detector description database DDDB The DDDB is the persistent storage for all the versions of the detector data needed to describe and qualify the detecting apparatus in order to interpret the event data The final clients of the detector description are the algorithms that need this information in order to perform their job reconstruction simulation etc To provide this information there needs to be a sub detector specific part that understands
193. lD 1 energy double 0 ContainedObject rom T opLevel MCParticle rom Monte Carlo Sparent AsetParent fourMomentum LorentzVector oscillationFlag bool false CaloDigit L MCCaloDigit oa virtualmass O MCCalo SummedDeposit MCCaloDeposit Ec double 0 otalE double 0 ra J EE double 0 totalE double 0 Figure 38 Event data model for Calorimeters page 208 GAUDI Appendix D LHCb Event Data Model User Guide Version Issue 6 3 Tracking Model of Hits TOTLayer TriTLay er Q DetectionCell roy Also needs to kno w about true resolution of drift i ambiguity OTHit OTDigi 5 C from Tracking Tracts ITHit 7 j OTDetectionCell ITDetectionCel from Tracking Tracks gt X 1 7 ta 7 ITMCHit ITMCDigi OTMCDigi OCH J MCTrackingHit from MonteCarlo exit Poit3D ys MCHitBase MCParticle from MonteCarlo _ from MonteCarlo lentry Point3D depositedEnergy double 0 timeOf Flight double 0 track ffi
194. late these light algorithms We have called this category Tools Some examples of possible tools are single track fitters association to Monte Carlo truth information vertexing between particles smearing of Monte Carlo quantities Private and Shared Tools Algorithms can share instances of Tools with other Algorithms if the configuration of the tool is suitable In some cases however an Algorithm will need to customize a tool ina specific way in order to use it This is possible by requesting the Tool Svc to provide a private instance of a tool If an Algorithm passes a pointer to itself when it asks the Tool Svc to provide it with a tool it is declaring itself as the parent and a private instance is supplied Private instances can be configured according to the needs of each particular Algorithm via jobOptions As mentioned above many Algorithms can use a tool as is in which case only one instance ofa Tool is created configured and passed by the Too1Svc to the different algorithms This is called a shared instance The parent of shared tools is the ToolSvc The Tool classes The AlgTool base class The main responsibilities of the AlgToo1 base class see Listing 62 are the identification of the tools instances the initialisation of certain internal pointers when the tool is created and the management of the tools properties The AlgToo1 base class also offers some facilities to help in the impl
195. lity We may summarise the main benefits we gain from this approach Flexibility This approach gives flexibility because components may be plugged together in different ways to perform different tasks Simplicity Software for using for example an object data base is in general fairly complex and time consuming to learn Most of the detail is of little interest to someone who just wants to read data or store results A data access component would have an interface which provided to the user only the required functionality Additionally the interface would be the same independently of the underlying storage technology Robustness As stated above a component can hide the underlying technology As well as offering simplicity this has the additional advantage that the underlying technology may be changed without the user even needing to know It is intended that almost all software written by physicists in the collaboration whether for event generation reconstruction or analysis will be in the form of specialisations of a few specific components Here specialisation means taking a standard component and adding to its functionality while keeping the interface the same Within the application framework this is done by deriving new classes from one of the base classes e DataObject e Algorithm e Converter In the rest of this chapter we will briefly consider the first two of these components and in particular the subject of the separati
196. m There can be several output streams connected to the service In case of persistency using HBOOK FILE1 corresponds to the top level RZ directory of the file the name given to HROPEN From then on the tree structure is reflected with normal RZ directories caveat HBOOK only accepts directory names with less than 8 characters It is recommended to keep directory names to less than 8 characters even when using another technology e g ROOT for persistency to make the code independent of the persistency choice 10 2 2 Using the N tuple Service When defining an n tuple the following steps must be performed e The n tuple tags must be defined e The n tuple must be booked and the tags must be declared to the n tuple e The n tuple entries have to be filled e The filled row of the n tuple must be committed e Persistent aspects are steered by the job options In the following an attempt is made to explain the different steps Please note that when using HBOOK for persistency the n tuple number must be unique and in particular that it must be different from any histogram number This is a limitation imposed by HBOOK It is recommended to keep this number unique even when using another technology e g ROOT for persistency to make the code independent of the persistency choice 10 2 2 1 Defining N tuple tags When creating an n tuple it is necessary to first define the tags to be filled in the n tuple Typically the tags b
197. m Empty Hopefully what is intended will be clear from the context 1 3 Reporting problems Users of the Gaudi software are encouraged to report problems and requests for new features via the LHCb problem reporting system This system is integrated in the CERN Problem page 10 W GAUDI User Guide Chapter 1 Introduction Version Issue 6 3 Report Management System CPRMS provided by IT division based on the Action Request System software from Remedy Corporation To report a new problem go to the LHCb CPRMS home page http cern ch hep service prms lhcb html click on the Submit button and fill in the form This will add the report to the system and notify the developers by E mail You will receive E mail notification of any changes in the status of your report To view the list of current problems and their status click the Query button on the LHCb CPRMS home page Active developers of the Gaudi software are encouraged to use the gaudi developers mailing list for discussion of Gaudi features and future developments This list is not primarily intended for bug reports In order to send mail to gaudi developers listbox cern ch you must fist subscribe to the list using the form at http vwwlistbox cern ch mowgli full_list server listboxG group Glist gaudi developers The archive of the mailing list is publically accessible on the Web at http home cern ch majordom news gaudi developers index html 1 4 Edit
198. m behaviour this manipulator does not flush the buffer Full name MsgStream amp endl MsgStreams amp s ends Inserts a null character to terminate a string Full name MsgSt reams ends MsgStream amp s flush Flushes the stream s buffer but does not produce any output Full name MsgSt ream amp flush MsgStream s endreq Terminates the current message formatting and forwards the message to the message service If no message service is assigned the output is sent to std cout Full name MsgStream amp endreq MsgStream amp s page 121 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 11 5 The Particle Properties Service The Particle Property service is a utility to find information about a named particle s Geant3 ID Jetset Pythia ID Geant3 tracking type charge mass or lifetime The database used by the service can be changed but by default is the same as that used by SICb Note that the units conform to the CLHEP convention in particular MeV for masses and ns for lifetimes Any comment to the contrary in the code is just a leftover which has been overlooked 11 5 1 Initialising and Accessing the Service This service is created by default by the application manager with the name ParticlePropertySvc Listing 50 on page 112 shows how to access this service from within an algorithm 11 5 2 Service Properties The Particle Property Service currently only has one property ParticleProp
199. mGenSvc m_randSvc enced The creation of concrete tools is similar to that of Algorithms making use of a Factory Method As for Algorithms Tool factories enable their creator to instantiate new tools without having to include any of the concrete tools header files A template factory is provided and a it page 141 GAUDI Chapter 12 Tools and ToolSvc User Guide Version Issue 6 3 tool developer will only need to add the concrete factory in the implementation file as shown in lines 1 to 4 of Listing 64 In addition a concrete tool class must specify a single constructor with the same parameter signatures as the constructor of the AlgTool1 base class as shown in line 5 of Listing 63 Below is the minimal checklist of the code necessary when developing a Tool 1 Derive the tool class from the AlgTool base class 2 Provide the constructor 3 Implement the factory adding the lines of code shown in Listing 64 In addition if the tool is implementing an additional interface you may need to 1 Define the specific interface inheriting from the IAlgTool1 interface 2 Implement the queryInterface method 3 Implement the specific interface methods J 12 3 The ToolSvc The ToolSvc manages Tools It is its responsibility to create tools and make them available to Algorithms or Services The ToolSve verifies if a tool type is available and creates the necessary instance after having verifie
200. mal implementation header file include Gaudi Kernel AlgTool h class VertexSmearer public AlgTool public Constructor Oa PWN PF VertexSmearer const std string amp type const IInterface parent Standard Destructor virtual VertexSmearer specific method of this tool StatusCode smear MyAxVertex pvertex POND const std string amp name Listing 64 Example of a concrete tool minimal implementation file include Gaudi Kernel ToolFactory h Static factory for instantiation of algtool objects ToolFactory lt VertexSmearer gt s_factory s_factory static const IToolFactory amp VertexSmearerFactory Standard Constructor VertexSmearer VertexSmearer const std string amp type YA OB WN FP const std string name const IInterface parent parent AlgTool type name Locate service n m_randSvc 0 if serviceLocator StatusCode sc StatusCode FAILURE serviceLocator gt getService RndmGenSvc ded by the specific tool GI WN FO WoO SEn IInterface amp Declar declareProperty dxVtx declareProperty dyVtx 4 5 properties of the specific tool 6 TT 18 declareProperty dzvtx 9 0 i m_dxVtx m_dyVtx m_dzVtx 9 micrometer 9 micrometer 38 micrometer Implement the specific method StatusCode VertexSmearer smear MyAxVertex pvertex IID_IRnd
201. mats page 91 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 100 100 05 O 1 1 34 e12 23 Supported operations are unary exponent Parenthesized expressions 1 4 23 4 e12 1 8 Operator precedence is unary I SA ES In addition the parser understands CLHEP units The result is always evaluated to double value The check for the presence of CLHEP units inside expressions is enabled by default To suppress this behavior the call of the eval method must look like xmlSvc gt eval 2 34 5 1 23 e4 false 8 5 5 XmlEditor This is a tool provided to edit the XML files of the detector description database without having to learn the XML syntax It is provided as a separate Gaudi package and was written in Java 8 5 5 1 Installing and launching XmlEditor way and compiles and runs both under Windows and Linux The only trick is the way you run the application The package actually contains a script subdirectory where two executables are located xmlEditor and xmlEditor bat the first running under Linux and the second under Windows You just have to launch one of them after compilation of the package Note that you must provide a Java runtime environment to use XmlEditor This has to be version 1 2 2 or later It wasn t actually tested on other versions of Java Anyway the I The installation of XmlEditor is similar to that of any Gaudi package It uses CMT i
202. me callable interface A Gaudi interface to store and retrieve data from ODBC tables was developed and offers the entire range of MS Office applications to access these data The small Visual Basic program in Listing 48 shows how to page 109 GAUDI Chapter 10 N tuple and Event Collection facilities User Guide Version Issue 6 3 fill an Excel spreadsheet using n tuple data from an Access database Apparently access to ODBC compliant databases using ROOT is also possible but this was not tested Listing 48 Feed n tuple data from MS Access into an Excel spreadsheet using Visual Basic Zs 28 29 30 31 32 333 34 30 36 37 38 39 40 41 42 43 44 45 46 47 48 49 503 51 52 Sub FillSpreadSheet Dim dbs As Database rst As Recordset Dim sglString as String Const conPath D mycmt GaudiExamples v8 Visual tuple mdb the_sheet_name ActiveSheet Nam Sheets the_sheet_name Select If IsEmpty Selection Then GoTo Done End If r Set dbs DBEngine Workspaces 0 OpenDatabase conPath Open database and return reference to Database object sqlString SELECT px py pz FROM lclMCRWWS2 ORD Open dynaset type recordset Set rst dbs OpenRecordset sqlString dbOpenDynaset bin 1 Do Until rst EOF Cells bin A A rst px Cells bin B B rst py Cells bin C C rst pz bin bin 1 rst MoveNext Loop r
203. me tool 1 The releaseTool method is not available in this release page 143 User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 To help the retrieval of concrete tools two template functions as shown in Listing 66 are provided in the IToolSvc interface file Listing 66 The IToolSvc template methods 1 template lt class T gt 2 StatusCode retrieveTool const std string type T amp tool const IInterface parent 0 bool createlIf true 3 template lt class T gt 4 StatusCode retrieveTool const std string type const std string amp name T amp tool const IInterface parent 0 bool createlIf true The two template methods correspond to the IToo1Svc retrieve methods but have the tool returned as a template parameter Using these methods the component retrieving a tool avoids explicit dynamic casting to specific additional interfaces or to derived classes Listing 67 shows an example of retrieval of a shared and of a common tool Listing 67 Example of retrieval of a shared tool in line 8 and of a private tool in line 14 1 IToolSvc toolsve 0 2 sc service ToolSvc toolsve 3 if sc isFailure 4 log lt lt MSG FATAL lt lt Unable to locate Tool Service lt lt endreq return sc 5 6 Example of tool belonging to the ToolSvc and shared between 7 algorithms 8 sc toolsvc gt retrieveTool AddFourMom
204. mp attributes virtual void uEndElement char const name virtual void uCharacters const char const chars const unsigned int length virtual void ulgnorableWhitespace const char const chars const unsigned int length static CnvFactory lt XmlMyDetectorCnv gt myde_factory const ICnvFactory amp XmlMyDetectorCnvFactory myde_factory XmlMyDetectorCnv XmlMyDetectorCnv ISvcLocator svc XmlUserDeCnv lt MyDetector gt svc XmlMyDetectorCnv As the next step is actual implementation of the callbacks of the UserSax8BitDocHandler interface This interface is defined as shown in Listing 35 Listing 35 IUserSax8BitDocHandler interface methods virtual void uStartDocument 0 virtual void uEndDocument 0 virtual void uCharacters const char const chars const unsigned int length 0 virtual void ulIgnorableWhitespace const char const chars const unsigned int length virtual void uStartElement const char const name virtual void uEndElement const char const name 0 XmlCnvAttributeList amp attributes 0 0 The names of the methods are self descriptive but two of them may need more detailed explanation The methods ulgnorableWhitespace and uCharacters are called for PCDATA contents of an XML tag The reason why there are two methods instead of one is that the XML specification says that white characters insi
205. must implement its three pure virtual methods initialize execute and finalize Fora top level algorithm i e one controlled directly by the application manager the methods are invoked as is described in section 4 6 This dictates what it is useful to put into each of the methods Initialization In a standard job the application manager will initialize all top level algorithms exactly once before reading any event data It does this by invoking the sysInitialize method of each top level algorithm in turn in which the framework takes care of setting up internal references to standard services and to set the algorithm properties by calling the method setProperties This causes the job options service to make repeated calls to the setProperty method of the algorithm which actually assigns values to the member variables Finally sysInitialize calls the initialize method which can be used to do such things as creating histograms or creating sub algorithms if required see section 5 4 If an algorithm fails to initialize it should return St atusCode FAILURE This will cause the job to terminate Figure 6 shows an example trace of the initialization phase Sub algorithms are discussed in section 5 4 Execution The guts of the algorithm class is in the execute method For top level algorithms this will be called once per event for each algorithm object in the order in which they were declared to the application manager Fo
206. n about the calling algorithm and without filtering on severity level A facility is provided by Gaudi to redirect these messages to the Gaudi MessageSvc This is documented at http cern ch Ihcb comp Components html GaudiNagC html 15 5 ROOT ROOT is used by Gaudi for I O and as a persistency solution for event data histograms and n tuples In addition it can be used for interactive analysis as discussed in Chapter 10 Information about ROOT can be found at http root cern ch page 172 GAUDI User Guide Chapter 16 Visualization Facilities Version Issue 6 3 Chapter 16 Visualization Facilities 16 1 Overview In this chapter we describe how visualization facilities are provided to the applications based on the Gaudi framework We present how we interface the physics event data objects detector components or statistical objects to their graphical representation One example of an application that uses the visualization services is an event display program With this program we display graphically the event data from files or being acquired by the data acquisition Another example could be an interactive analysis program that combines in the same application histogramming or manipulation of statistical entities event display and full interactive control by the end user of the data objects and algorithms of the application In the current release these visualization services are at the level of a prototype We have implemented
207. n include other job option files The compiler checks itself whether the include file is already included or not so there is no need for ifndef statements as in C or C to check for multiple including Sometimes it is necessary to over ride a value defined previously maybe in an include file This is done by using an assign statement with the same object and propertyname The last value assigned is the valid value 11 3 2 1 Platform dependent execution The possibility exists to execute statements only according to the used platform Statements within platform dependent clauses are only executed if they are asserted to the current used platform ifdef WIN32 Platform Dependent Statement else optional Platform Dependent Statement fendif Only the variable WIN32 is defined An ifdef WIN32 will check if the used platform is a Windows platform If so it will execute the statements until an endif or an optional else On non Windows platforms it will execute the code within else and endif Alternatively one directly can check for a non Windows platform by using the ifndef WIN32 clause I 11 3 2 2 Example We have already seen an example of a job options file in Listing 3 on page 35 The use of the include statement is demonstrated on line 6 the logical name STDOPTS is defined in the GaudiConf package which contains a number of standard job options include files that c
208. n particular you need to know the following e What is the input data to the algorithm What is the relationship of these data to other data e g event or detector data e What new data is going to be produced by the algorithm e What s the purpose of the algorithm and how is it going function Document this in terms of mathematical expressions and plain english e What does the algorithm need in terms of configuration parameters e How can the algorithm be partitioned structured into smaller algorithm chunks that make it easier to develop design code test and maintain e What data is passed between the different chunks How do they communicate e How do these chunks collaborate together to produce the desired final behaviour Is there a controlling object Are they self organizing Are they triggered by the existence of some data e How is the execution of the algorithm and its performance monitored messages histograms etc e Who takes the responsibility of bootstrapping the various algorithm chunks For didactic purposes we would like to illustrate some of these design considerations using a hypothetical example Imagine that we would like to design a tracking algorithm for LHCb based on a Kalman filter algorithm 1 Catalan is also acceptable page 182 GAUDI User Guide Chapter 17 Design considerations Version Issue 6 3 17 3 Analysis Phase As mentioned before we need to understand in detail
209. n the same javax swing facilities must be provided 8 5 5 2 Using XmlEditor XmlEditor is an Explorer like application that is able to display an XML document as a tree Each node of this tree represents an element in the XML document A snapshot of the GUI of the XmlEditor is shown in Figure 19 The menu of the main window is very simple you can only open a new XML file close all opened files or save them all You can of course open several files and edit them at the same time When working on a file basic functionalities are very similar to those of Explorer double click to open or close a node click to select it click to edit it when selected and so on The drag and drop functionnalities are not implemented at this time but will be in the next version The content of the node i e its attributes are displayed for the selected node on the right of the screen Every attribute is editable page 92 it GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 tteratorView fhome seb CMT XmIDDDB v4 DDDB materials materials xml File Option rTree View pope Attributes Values Ba materials classID 3 Bor_10 X fiteratorView fhaome seb CMT XmIDDDB v4 DDDB dddb xm Ff nor Uy File Option oa fe Boron Tree View fe Oxygen C3 pope Attributes Values fe Hydrogen BA version 3 0 oR Carbon a Pf structure oR Fluorine LHCb E Silicon Geometry fe Argon pa LHCb fe Iron o Fgh emn
210. nce per event and finalizing the set of top level algorithms i e the set of algorithms specified in the job options file However such a simple linear structure is very limiting You may wish to execute some algorithms only for specific types of event or you may wish to loop over an algorithm s execute method Within the Gaudi application framework the way to have such control is via the nesting of algorithms or through algorithm sequences described in section 5 5 A nested or sub algorithm is one which is created by and thus belongs to and is controlled by another algorithm its parent as opposed to the application manager In this section we discuss a number of points which are specific to sub algorithms In the first place the parent algorithm will need a member variable of type Algorithm see the code fragment below in which to store a pointer to the sub algorithm The sub algorithm itself is created by invoking the createSubAlgorithm method of the Algorithm base class The parameters passed are the type of the algorithm its name and a reference to the pointer which will be set to point to the newly created sub algorithm Note that the name passed into the createSubAlgorithm method is the same name that should be used within the job options file for specifying algorithm properties page 49 GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 Algorithm m_pSubAlgorithm Pointer to the sub
211. ndependent of any external package The documentation for CLHEP can be found on WWW at http wwwinfo cern ch asd lhc clhep index html CLHEP is used extensively inside Gaudi in particular in the GaudiSvc LHCbEvent and SicbCnv packages 15 3 HTL HTL Histogram Template Library is used internally in Gaudi GaudiSvc package to provide histogramming functionality It is accessed through its abstract AIDA compliant interfaces Gaudi uses only the transient part of HTL Histogram persistency is available with ROOT or HBOOK The documentation on HTL is available at http wwwinfo cern ch asd lhc HTL index html Documentation on AIDA can be found at http Avwwinfo cern ch asd lhc AIDA index html page 171 GAUDI User Guide Chapter 15 Analysis utilities Version Issue 6 3 15 4 NAG C The NAG C library is a commercial mathematical library providing a similar functionality to the FORTRAN mathlib part of CERNLIB It is organised into chapters each chapter devoted to a branch of numerical or statistical computation A full list of the functions is available at http wwwinfo cern ch asd lhc Nag_C html doc html NAG C is not explicitly used in the Gaudi framework but developers are encouraged to use it for mathematical computations Instructions for linking NAG C with Gaudi can be found at http cern ch lhcb comp Components html nagC html Some NAG C functions print error messages to stdout by default without any informatio
212. nergy InCell double 0 MC RichPhotodetectorHit Vector3D direction absoluteMomentum double 0 arentRadiator long 0 Figure D 2 Class definitions of Monte Carlo event page 205 GAUDI Appendix D LHCb Event Data Model User Guide Version Issue 6 3 Reconstructed Event from TopLev el Contained Object parent isetP arent RecVertex RecPaticleID RecRichRing RecHit _ hit RecT rack constituent RecConstituent 0 0 EX A RecTrackingSegment RecCalorimeterCluster RecRichHit RecCalorimeterCell RecTrackingHit RecVertexSegment RecTrackerSegment RecMuonSegment RecVertexCluster RecinnerT rackerHit RecOuterT rackerHit RecMuonHit Figure 34 Data model of reconstructed event page 206 GAUDI Appendix D LHCb Event Data Model User Guide Version Issue 6 3 Analysis Event ContainedObje ct rom TopLevel arent isetParent
213. ng possibilities given by the object persistency technology This is done by designing the appropriate set of Converters Finally we need to identify utility classes which will help to implement the various algorithm chunks 17 4 1 Defining Algorithms Most of the steps of the algorithm have been identified in the analysis phase We need at this moment to see if those steps can be realized as framework Algorithms Remember that an Algorithm from the view point of the framework is basically a quite simple interface initialize execute finalize with a few facilities to access the basic services In the case of our hypothetical algorithm we could decide to have a master Algorithm which will orchestrate the work of a number of sub Algorithms This master Algorithm will be also be in charge of bootstraping them Then we could have an Algorithm in charge of finding the tracking seeds plus a set of others each one associated to a different tracking station in charge of propagating a proto track to the next station and deciding whether the proto track needs to be kept or not Finally we could introduce another Algorithm in charge of producing the final tracks from the surviving proto tracks It is interesting perhaps in this type of algorithm to distribute parts of the calculations extrapolations etc to more sophisticated hits than just the unintelligent original ones This could be done by instantiating new data types clever hits for e
214. nge It seems normal and trivial but it is surprising when both dtd are defining the same kind of node author for example e SubElement Displaying it is in a way the parallel of the Attribute displaying option for elements When using this option the user gets two different possibilities for each subelement of an element The first one is whether he wants to display the attribute in the tree or not The second one is a bit more tricky It only concerns nodes that are attribute like These are nodes that have no attributes and no subnodes except a text node that is their value Such a node looks like this in the XML file lt detelem gt lt author gt Smith lt author gt lt detelem gt In such a case the user can choose to make the author node appear as an attribute of the detelem node He does that by checking the corresponding box in the second column of the SubElement Displaying dialog 8 5 5 4 Editor functionality The current release of the XmlEditor ie the first release does not provide many editor functionalities Briefly you can change everything existing in the file you are looking for but you cannot create anything new You can edit what exists in the Explorer like way click on the content you want to edit when it is selected Just take care when you are editing nodes that use entities You can notice that these are expanded in the XmlEditor This means that a modification will remove the use of the
215. ns Except for JAS only proprietary data formats are understood For this reason the choice of the output format of the data depends on the preferred analysis tool viewer In the following an overview is given over the possible data formats In the examples below the output of the GaudiExample NTuple write program was used 10 4 1 HBOOK This data format is used by PAW PAW can understand this and only this data format Files of this type can be converted to the ROOT format using the h2 root data conversion program The use of PAW in the long term is deprecated 10 4 2 ROOT This data format is used by the interactive ROOT program Using the helper library TBlobShr located in the package DbCnv it is possible to interactively analyse the n tuples written in ROOT format However access is only possible to scalar items int float not to arrays Analysis is possible through directly plotting variables root 1 gSystem gt Load D mycmt DbCnv v3 Win32Debug libTBlobShr root 2 TFile f new TFile tuple root page 108 it Chapter 10 N tuple and Event Collection facilities User Guide Version Issue 6 3 root 3 TTree t TTree f gt Get lt local gt _MC_ROW_WISE_2 root 4 t gt Draw pz or using a ROOT macro interpreted by ROOT s C C interpreter see for example the code fragment interactive C shown in Listing 47 root 0
216. ntainers rely on the serialize mothods of the contained objects The serialisation is able to understand smart references to other objects within the same data store e g the reference from the MCParticle to the MCVertex Listing 76 shows an example of the serialize methods of the MCParticle class Please refer to the Gaudi example Rio Example1 for further details how to store objects in ROOT files page 159 GAUDI User Guide Chapter 13 Converters Version Issue 6 3 Listing 76 Serialisation of the class Event 1 include DbCnv DbContainerConverter h 2 _ImplementContainerConverters MCParticle 38 4 Serialize the object for writing 5 inline StreamBuffer amp MCParticle serialize StreamBuffer amp s const 6 ContainedObject serialize s 7 unsigned char u m_oscillationFlag 1 0 8 return s 9 2 lt lt m_fourMomentum 10 lt lt m_particleID 11 lt lt m_flavourHistory 12 LA 6 13 lt lt m_originMCVertex this Stream a reference to another object 143 lt lt m_decayMCVertices this Stream a vector of references PSs P 16 Serialize the object for reading 17 inline StreamBuffer amp MCParticle serialize StreamBuffer s 18 ContainedObject serialize s 198 unsigned char u 20 s gt gt m_fourMomentum 21 gt gt m_particleID 22 gt gt m_flavourHistory 23 gt gt u 24 gt gt m_originMCVertex this Stream a reference to an
217. o avoid it Error 006 String is not termi nated by a A string value was not ter minated by a Check if all your strings are beginning and ending with Note that the position given by the compiler can be wrong because the compiler may thought that following state ments are part of the string Error 007 syntax error include statement is not cor rect The next token after the include is not a string Make sure that after the include directive there is specified the file to include The file must be defined as a string Error 008 syntax error include does not end with a The include directive was ter minated by a Remove the after the include directive Error 009 syntax error Val ues must be separated with One or more values within a vector were not separated with a or one ore more val ues within a vector are mistyped Check if every value in the vector is separated by a If so the reason for this message may result in mistyped val ues in the vector maybe there is a blank or tab between numbers Error 010 syntax error Vector must end with The closing bracket is missing or the vector is not terminated correctly Check if the vector ends with a and if there is no semico lon before the ending bracket Error 011 syntax error State ment must end with a The statement is not termi nated correctly
218. o cout rather than MessageSvc ChronoPrintLevel 3 Print level for profiling values as for MessageSvc ChronoTableToBeOrdered true Switch to order printed table StatPrintOutTable true Global switch for statistics printout StatDestinationCout false If true printout goes to cout rather than MessageSvc StatPrintLevel 3 Print level for profiling values as for MessageSvc StatTableToBeOrdered true Switch to order printed table page 194 GAUDI User Guide Appendix B Options for standard components Version Issue 6 3 Table B 20 Standard Options for XML conversion service XmlICnvSvc Option name Default value Meaning AllowGenericConversion false Switch for generic detector element conversion a The XML conversion service allows the possibility to convert user defined detector elements to generic detector elements This means that only the generic part of the detector element and its associated geom etry will be converted but not the user defined detector element data This feature can be used when the user defined detector element data are not needed e g visualization or when the corresponding user defined XML converters are not available testing When this feature is switched ON the Gaudi appli cation will run successfully with an information message saying that this feature is enabled and will print out the information about all the detector elements to which this generic conversion is applie
219. ode fragment can be used to prepare an array with pointers to all of the Muon stations Here we use an STL vector of pointers to DeMuonSt ation objects to store the retrieved Muon stations Listing 19 Retrieving a vector of detector elements using smart references std vector lt DeMuonStation gt d_stations SmartDataPtr lt DetectorElement gt stations detSvc dd Structure LHCb Muon Stations if stations return StatusCode FAILURE Loop over all the muon stations found in the detector model for DataObject DirIterator d stations gt dirBegin d stations gt dirEnd d SmartDataPtr lt DeMuonStation gt s detSvc d gt fullpath bE sao A return sc d_stations push_back s 8 3 3 Using the DetectorElement class The DetectorElement class implements the IDetectorElement interface Currently only the geomet ry accessor method is implemented The rest of the interface will be implemented in the next releases of the detector description package In addition DetectorElement implements the Validity interface This interface is used to check if the detector element is synchronized with the current event If the detector element contains information no longer valid at the time the current event was generated its content must be updated from the persistent storage In the current implementation it is not foreseen for end users to use this interface dir
220. of the input data to the event selector Listing 45 Connecting an address tag to an n tuple EventSelector Input COLLECTION Collection ADDRESS Address DATAFILE MyEvtCollection root TYP ROOT SEL Ntrack gt 80 FUN EvtCollectionSelector These tags need some explanation COLLECTION Specifies the sub path of the n tuple used to write the collection If the n tuple which was written was called e g NTUPLES FILE1 Collection the value of this tag must be Collection ADDRESS optional Specifies the name of the n tuple tag which was used to store the opaque address to be used to retrieve the event data later This is an optional tag the default value is Address Please use this default value when writing conventions are useful SEL optional Specifies the selection string used for the first stage pre selection The syntax depends on the database implementaion it can be e SQL like if the event collection was written using ODBC Example NIrack gt 200 AND Energy gt 200 e C like if the event collection was written using ROOT Example NIrack gt 200 amp amp Energy gt 200 Note that event collections written with ROOT also accept the SQL operators AND instead of amp amp as well as OR instead of Other SQL operators are not supported FUN optional Specifies the name of a function object used for the second stage pre
221. on of data and algorithm They will be covered in more depth in chapters 5 and 6 The third base class Converter exists more for technical necessity than anything else and will be discussed in chapter 13 Following this we give a brief outline of the main components that a physicist developer will come into contact with 2 3 Data versus code Broadly speaking tasks such as physics analysis and event reconstruction consist of the manipulation of mathematical or physical quantities points vectors matrices hits momenta etc by algorithms which are generally specified in terms of equations and natural language The mapping of this type of task into a programming language such as FORTRAN is very natural since there is a very clear distinction between data and code Data consists of variables such as integer n real p 3 and code which may consist of a simple statement or a set of statements collected together into a function or procedure real function innerProduct pl p2 page 14 it GAUDI User Guide Chapter 2 The framework architecture Version Issue 6 3 real p1 3 p2 3 innerProduct pl 1 p2 1 pl 2 p2 2 pl 3 p2 3 end Thus the physical and mathematical quantities map to data and the algorithms map to a collection of functions A priori we see no reason why moving to a language which supports the idea of objects such as C should change the way we think of doing physics analysis
222. on the number of bins and lower and upper limits of the Y axis If using HBOOK for persistency the histogram identifier should be a valid HBOOK histogram identifier number must be unique and in particular must be different from any n tuple number Even if using another persistency solution e g ROOT it is recommended to comply with the HBOOK constraints in order to make the code independent of the persistency choice The call to histoSvc gt book returns a pointer to an object of type IHistogram1D or IHistogram2D in the case of a 2D histogram All the methods of this interface can be used to further manipulate the histogram and in particular to fill it as shown in the example Note that this pointer is guaranteed to be non null the algorithm would have failed the initialisation step if the histogram data service could not be found On the contrary the user variable particles may be null in case of absence of Monte Carlo particles in the transient data store and in the persistent storage and the fill statement would fail so the value of particles must be checked before using it Algorithms that create histograms will in general keep pointers to those histograms which they may use for filling operations However it may be that you wish to share histograms between different algorithms Maybe one algorithm is responsible for filling the histogram and another algorithm is responsible for fitting it at the end of the job In this ca
223. oned inside the mother Logical Volume together with the transformation matrix from the local reference system of the mother Logical Volume to the local reference system of the daughter Logical Volume This is implemented in Gaudi by the class PVolume PVolume is not identifiable and implements the IPVolume interface 8 4 3 Solids All solids implement the ISo1id interface Currently five types of primitive solids are implemented Boxes Trapezoids Tube segments Conical tube segments and Sphere segments These were chosen from the most frequently used shapes in the GEANT3 and Geant4 toolkits more shapes can be implemented if necessary In addition Boolean Solids have been defined which allow Subtraction Union and Intersection operations on solids to build complex shapes 8 5 Persistent representation The Gaudi detector description is based on text files whose structure is described by XML eXtendable Markup Language a standard language which allows the definition of custom tags unlike the fixed set of tags of HTML used for WWW XML files are understandable by humans as well as computers Data in XML are self descriptive so that by looking at the XML data one can easily guess what the data mean Unlike the HTML tags tags in XML do not define how to render or visualize the data This is left to an application which understands the data and can visualize them if wanted An advantage of XML is that there exists plenty of software which
224. or s note This document is a snapshot of the Gaudi software at the time of the release of version 6 We have made every effort to ensure that the information it contains is correct but in the event of any discrepancies between this document and information published on the Web the latter should be regarded as correct since it is maintained between releases and in the case of code documentation it is automatically generated from the code We encourage our readers to provide feedback about the structure contents and correctness of this document and of other Gaudi documentation Please send your comments to the editor Marco Cattaneo cern ch page 11 GAUDI Chapter 1 Introduction User Guide Version Issue 6 3 page 12 GAUDI User Guide Chapter 2 The framework architecture Version Issue 6 3 Chapter 2 The framework architecture 2 1 Overview In this chapter we would like to briefly re visit some of those issues addressed in the Architecture Design Document which are of particular interest to physicists wishing to use the framework We also try to define a few of the words that are thrown around in the rest of the document and end with some practical guidelines on software packaging A more complete view of the architecture along with a discussion of the main design choices and the reasons for these choices may be found in reference 1 2 2 Why architecture The basic requirement of the physicis
225. orithm gt setProperty p Note also that the vector of pointers to the sub algorithms is available via the subAlgorithms method 5 5 Algorithm sequences branches and filters A physics application may wish to execute different algorithms depending on the physics signature of each event which might be determined at run time as a result of some reconstruction This capability is supported in Gaudi through sequences branches and filters A sequence is a list of Algorithms Each Algorithm may make a filter decision based on some characteristics of the event which can either allow or bypass processing of the downstream algorithms in the sequence The filter decision may also cause a branch whereby a different downstream sequence of Algorithms will be executed for events that pass the filter decision relative to those that fail it Eventually the particular set of sequences filters and branches might be used to determine which of multiple output destinations each event is written to if at all This capability is not yet implemented but is planned for a future release of Gaudi page 50 it GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 A Sequencer class is available in the GaudiAlg package which manages algorithm sequences using filtering and branching protocols which are implemented in the Algorithm class itself The list of Algorithms in a Sequencer is specified through the Members property Algorithm
226. ork services Version Issue 6 3 11 6 2 Statistical monitoring Statistical monitoring is performed by using the stat method inside user code 1 Flag and Weight to be accumulated 2 svc gt stat Number of Tracks Flag Weight The statistical information contains the accumulated flag which is the sum of all Flags for the given tag and the accumulated weight which is the product of all Weights for the given tag The information is printed in the final table of statistics In some sense the profiling could be considered as statistical monitoring where the variable Flag equals the elapsed time of the process 11 6 3 Chrono and Stat helper classes To simplify the usage of the Chrono amp Stat Service two helper classes were developed class Chrono and class Stat Using these utilities one hides the communications with Chrono amp Stat Service and provides a more friendly environment 11 6 3 1 Chrono Chrono is a small helper class which invokes the chronoStart method in the constructor and the chronoStop method in the destructor It must be used as an automatic local object It performs the profiling of the code between its own creation and the end of the current scope e g 1 include Gaudi ChronoStatSvc Chrono h 2 Sele dias 3 begin of the scope 4 Chrono chrono chronoSvc ChronoTag D some codes 6 SAR 7 8 end of the scope Dee Sil itt
227. other object 25 gt gt m_decayMCVertices this Stream a vector of references 26 m_oscillationFlag u true false 2s return s 28 f 13 8 Storing Data using other I O Engines Once objects are stored as BLOBs it is possible to adopt any storage technology supporting this datatype This is the case not only for ROOT but also for e Objectivity DB e most relational databases which support an ODBC interface like e Microsoft Access e Microsoft SQL Server e MySQL e ORACLE and others Note that although storing objects using these technologies is possible there is currently no experiment wide policy on how to use Objectivity or other client server based technologies For this reason only the example to store data using Microsoft Access is described in the example Rio Example1 All other technologies are currenly not supported If you desperately want to use SQL Server MySQL or Objectivity please contact Markus Frank Markus Frank cern ch page 160 W GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 Chapter 14 Accessing SICB facilities 14 1 Overview In order to facilitate the transition towards C based code we have implemented a number of features into the Gaudi framework whose purpose is to allow access to facilities existing within SICB but not yet existing within the framework itself Gaudi also can read data produced with SICBMC or SICBDST In this chapter we cover
228. out their absolute position in the space e Logical Volumes have no information about their own position relative to other Logical Volumes e Each Physical Volume has a information about its position inside the mother parent Logical Volume This is the only geometry information available in the whole tree e All boolean operations on Logical Volumes and Physical Volumes are strictly forbidden Boolean operations should be performed at the level of Solids This is one of the most essential postulates of the Gaudi geometry structure The geometry tree which fulfils all these postulates represents a very effective simple and convenient tool for description of the geometry Such a tree is easily formalized It has many features which are similar to the features of the geometry tree used within the Geant4 toolkit and could easily be transformed to the Geant4 geometry description Some consequences of these postulates are e The top level Logical Volume presumably the experimental hall or cave or the whole LHCb detector defines the absolute coordinate reference system In other words the null point 0 0 0 in the so called Global Reference System is just the center of the top Logical Volume e All geometry calculations computations inputs and outputs performed with the usage of a Logical Volume are in the local reference system of this Logical Volume e All geometry calculations computations inputs and outputs performed with the usage o
229. page 52 GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 Listing 9 illustrates the use of inverted logic It achieves the same goal as the example in listing 8 through use of two sequences with the same instance of a Prescaler filter but where the second sequence contains inverted logic for the single instance Listing 11 Example jobOptions using Sequencers demonstrating inverted logic ApplicationMgr DLLs GaudiAlg ApplicationMgr TopAlg Sequencer Seql Sequencer Seq2 Seql Members HelloWorld Prescaler EventCounter Counterl Seq2 Members HelloWorld Prescaler invert EventCounter Counter2 1 2 3 4 Setup the next level sequencers and their members 5 6 co y Prescaler PercentPass 80 page 53 GAUDI Chapter 5 Writing algorithms User Guide Version Issue 6 3 page 54 GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 Chapter 6 Accessing data 6 1 Overview The data stores are a key component in the application framework All data which comes from persistent storage or which is transferred between algorithms or which is to be made persistent must reside within a data store In this chapter we look at how to access data within the stores and also at the Dat aOb ject base class and some classes related to it We also cover how to define your own data types and the steps necessary to sa
230. paque address class must implement the IOpaqueAddress interface This interface allows the address to be passed around between the transient data service the persistency service and the conversion services without any of them being able to actually decode the address Opaque address objects are also technology specific The internals of a SicBAddress object are different from those of a RootAddress object Only the converters themselves know how to decode an opaque address In other words only converters are permitted to invoke those methods of an opaque address object which do not form a part of the L OpaqueAddress interface Converter objects must be registered with the conversion service in order to be usable For the standard converters this will be done automatically For user defined converters for user defined types this registration must be done at initialisation time see Chapter 6 13 4 The conversion process As an example see Figure 28 we consider a request from the event data service to the persistency service for an object to be loaded from a data file As we saw previously the persistency service has one conversion service slave for each persistent technology in use The persistency service receives the request in the form of an opaque address object The svcType method of the IOpaqueAddress interface is invoked to decide which conversion service the request should be passed onto This returns a technology i
231. ppendix B Options for standard components User Guide Version Issue 6 3 Table B 17 Standard Options for Random Numbers Generator Service RndmGenSvc Option name Default value Meaning Engine HepRndm Engine lt RanluxEngine gt Random number generator engine Seeds Table of generator seeds Column 0 Number of columns in seed table 1 Row 1 Number of rows in seed table 1 Luxury 3 Luxury value for the generator UseTable false Switch to use seeds table Table B 18 Standard Options for Transport Service TransportSvc Option name Default value Meaning ChronoStatService ChronoStatSvc Name of the Chrono Service to be used MagneticFieldService MagneticFieldSvc Name of the Magnetic Field Service to be used DetectorDataService DetectorDataSvc Name of the Detector Data Service to be used StandardGeometryTop dd Structure LHCb Location of the top node of the detector geom etry in the transient detector data store Table B 19 Standard Options for Chrono and Stat Service ChronoStatSvc Option name Default value Meaning ChronoPrintOutTable true Global switch for profiling printout PrintUserTime true Switch to print User Time PrintSystemTime false Switch to print System Time PrintEllapsedTime false Switch to print Elapsed time Note typo in option name ChronoDestinationCout false If true printout goes t
232. ptions compiler itself tests if the object or identifier already exists i e has already been defined in an included file and the type of the existing property If the type is compatible and the object exists the compiler appends the value to the existing property If the property does not exists then the append operation behaves as assignment operation un Including other Job Option Files It is possible to include other job option files in order to use pre defined options for certain objects This is done using the include directive include filename ext The filename ext can also contain the path where this file is located The include directive can be placed anywhere in the job option file but it is strongly recommended to place it at the very top of the file as in C It is possible to use environment variables in the include statement either standalone or as part of a string Both Unix style Senvironment variable and Windows style Senvironmentvariable are understood on both platforms As mentioned above you can append values to vectors defined in an included job option file The interpreter creates these vectors at the moment he interprets the included file so you can only append elements defined in a file included before the append statement page 117 GAUDI Chapter 11 Framework services User Guide Version Issue 6 3 As in C C an included job option file ca
233. r setLower const T amp lower setUpper const T amp upper There are similar selectors and modifiers to determine whether a bound has been set etc or to clear a bound bool hasLower _ bool hasUpper T lower upper void clearBounds void clearLower void clearUpper rot You can set the value using the operator or the set functions page 114 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 bool set const T amp value bool setValue const T amp value The function value indicates whether the new value was within any bounds and was therefore successfully updated In order to access the value of the property use m_property value In addition there s a cast operator so you can also use m_property directly instead of m_property value 11 3 1 2 CommandProperty CommandProperty is a subclass of StringProperty that has a handler that is called whenever the value of the property is changed Currently that can happen only during the job initialization so it is not terribly useful Alternatively an Algorithm could set the property of one of its sub algorithms However it is envisaged that Gaudi will be extended with a scripting language such that properties can be modified during the course of execution The relevant portion of the interface to CommandProperty is class CommandProperty public StringProperty public Leh virtual voi
234. r has omitted because they are described as optional or with a fixed value in the DTD Important note the default behaviour of the validating application recommended by the XML standard is to stop parsing of an XML document in case of an error This is because the XML files describe data and an error in XML means corrupted data page 77 User Guide Version Issue 6 3 GAUDI Chapter 8 Detector Description 8 5 2 Working with the persistent detector description in XML In this section we describe how to create or update the XML data files used by the detector description database We will go through all available XML elements defined for the detector description explain their XML syntax and show how to use them For convenience we have included pseudo UML diagrams showing content model definitions of the XML tags This approach has been chosen because it is easier to understand the graphical form than raw DTD definitions Here follows a brief explanation how to read these pseudo UML diagrams e Elements are represented as boxes containing their name and optionally the specification of their content above the name inside lt lt gt gt brackets which can be EMPTY or ANY e The directed arrows are used to describe the containment relation The containing element has the diamond of an arrow attached to it and the contained element is at the pointed end of the arrow A multiplicity see Table 9 is specified at the end of the arro
235. r methods are for retrieving a pointer to an object that is already in the store How the object got into the store whether it has been read in from a persistent store or added to the store by an algorithm is irrelevant The find and retrieve methods come in two versions One version uses a full path name as an object identifier the other takes a pointer to a previously retrieved object and the name of the object to look for below that node in the tree Additionally the find and retrieve methods differ in one important respect the find method will look in the store to see if the object is present i e in memory and if it is not will return a null pointer The retrieve method however will attempt to load the object from a persistent store database or file if it is not found in memory Only if it is not found in the persistent data store will the method return a null pointer and a bad status code of course 6 3 Using data objects Whatever the concrete type of the object you have retrieved from the store the pointer which you have is a pointer to a Dat aOb ject so before you can do anything useful with that object you must cast it to the correct type for example 1 typedef ObjectVector lt MCParticle gt MCParticleVector 2 DataObject pObject 32 4 StatusCode sc eventSvc gt retrieveObject Event MC MCParticles pObject 5 if sc isFailure 6 return sc Te 8 MCParticl
236. r sub algorithms see section 5 4 the control flow may be as you like you may call the execute method once many times or not at all Just because an algorithm derives from the Algorithm base class does not mean that it is limited to using or overriding only the methods defined by the base class In general your code will be much better structured i e understandable maintainable etc if you do not for example implement the execute method as a single block of 100 lines but instead define your own utility methods and classes to better structure the code If an algorithm fails in some manner e g a fit fails to converge or its data is nonsense it should return from the execute method with St atusCode FAILURE This will cause the application manager to stop processing events and end the job This default behaviour can be modified by setting the lt myAlgorithm gt ErrorMax job option to something greater than page 47 GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 Algorithm syslnitialize setProperties createSubAlgorithm create SubAlgorithm lt gt createSubAlgorithm syslnitialize setProperties syslnitialize setProperties Figure 6 Algorithm initialization 1 In this case a message will be printed but the job will continue as if there had been no error and just increment an error count The job will only stop if the error count reaches
237. r views of the silicon wafer will require code How to encompass the need for these different views within Gaudi was one of the key issues in the design of the framework In this chapter we outline the design adopted for the framework and look at how the conversion process works This is followed by two sections which deal with the technicalities of writing converters for reading SICB data and for reading from and writing to ROOT files 13 2 Persistency converters Gaudi gives the possibility to read in event data either from Zebra or from ROOT files and to write data back to disk in ROOT files This data may then of course be read again at a later date Figure 26 is a schematic illustrating how converters fit into the transient persistent translation of event data We will not discuss in detail how the transient data store e g the event data service or the persistency service work but simply look at the flow of data in order to understand how converters are used One of the issues considered when designing the Gaudi framework was the capability for users to create their own data types and save objects of those types along with references to already existing objects A related issue was the possibility of having links between objects which reside in different stores i e files and databases and even between objects in different types of store page 151 GAUDI User Guide Chapter 13 Converters Version Issue 6 3 Transien
238. rSeed WEE WE M ObjectVector ObjectList 2 Run runTy pe long 0 riggerTy pe long 0 nabledTriggerMask long 0 nabledDetectorMask long 0 luminosity double 0 illNumber long 0 eneratorTy pe long 0 vector DataObject from Kernel ContainedObject rent tParent Figure D 1 Class diagram of the LHCb top level event classes page 204 GAUDI Appendix D LHCb Event Data Model User Guide Version Issue 6 3 Monte Carlo Event ContainedObject from TopLevel arent etParent Particleld from Utilities Wig long MBP articleld A Tat particleld MC Partic le fourMomentum ioscillationFlag bool false LorentzVector By irtualMass l stra ck MCHitBase ntry Point3D epositedEnergy double im eOfFlight double 0 oA MC Vertex Point3D osition imeOfFlight double 0 40 riginVe rt ex Fot MC TrackingH it Bex t Point3D MC VeloHit M BiwaferNumber long 0 MC RichR adiatorHit xit b s olut eMom e ntu m Point3D double 0 MCECalFacePlaneHit direction Vector3D unseenE
239. ration Four corresponding template methods are implemented in Associator to facilitate the use of Associators by Algorithms see Listing 69 Using these methods the component retrieving a tool avoids some explicit dynamic casting as well as the setting of class IDs An example of how to use such methods is described in section 12 4 1 3 Listing 69 Template methods of the IAssociator interface 1 template lt class Tl class T2 gt StatusCode retrieveDirect T1 from T2 amp to 2 template lt class T1 gt StatusCode retrieveDirect T1 from std vector lt ContainedObject gt amp objVTo const CLID 2dTo J asis 3 template lt class T1 class T2 gt StatusCode retrievelInverse T1 from T2 amp to 4 template lt class T1 gt StatusCode retrievelInverse FIX from std vector lt ContainedObject gt amp objVTo const CLID idTo y te page 146 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issue 6 3 12 4 1 2 The Associator base class Anassociator is a type of AlgTool so the Associator base class inherits from the AlgTool base class This allows for Associators to be created and managed as AlgToo1s by the ToolSve Since all the methods of the AlgToo1 base class as described in section 12 2 2 1 are available in the Associator base class only the additional functionality is described here Access to Event Data Service An eventSvc method is provided
240. re used internally by the framework The latter three methods are not virtual and may not be overridden Service accessor methods Lines 21 to 35 declare accessor methods which return pointers to key service interfaces These methods are available for use only after the Algorithm base class has been initialized i e they may not be used from within a concrete algorithm constructor but may be used from within the initialize method see 5 3 3 The services and interface types to which they point are self explanatory see also Chapter 2 Services may be located by name using the templated service function in lines 21 and 22 or by using the serviceLocator accessor method on line 35 as described in section 11 2 of Chapter 11 Line 26 declares a facility to modify the message output level from within the code the message service is described in detail in section 11 4 of Chapter 11 Creation of sub algorithms The methods on lines 37 to 39 are intended to be used by a derived class to manage sub algorithms as discussed in section 5 4 Declaration and setting of properties As mentioned above one of the responsibilities of the base class is the management of properties The methods in lines 41 to 45 are used by the framework to set properties as defined in the job options file The declareProperty methods lines 47 to 53 are intended to be used by a derived class to declare its properties This is discussed in more detail in section 5 3 2 an
241. rvice 125 11 7 The Auditor Service 2 128 11 8 The Random Numbers TA 130 11 9 The Incident Service 133 11 10 Developing new services 134 Chapter 12 Tools and ToolSvc 137 12 1 Overview 137 12 2 Tools and Services 137 12 3 The ToolSvc 142 12 4 GaudiTools 144 Chapter 13 Converters 151 13 1 Overview 151 13 2 Persistency converters 151 13 3 Collaborators in the conversion process 152 13 4 The conversion process Bde E lt a She 154 13 5 Converter implementation general considerations 156 13 6 Storing Data using the ROOT I O Engine f 157 13 7 The Conversion from Transient Objects to ROOT Objects 158 13 8 Storing Data using other I O Engines 160 Chapter 14 Accessing SICB facilities 161 14 1 Overview 161 14 2 Reading tapes 161 14 3 Populating the GAUDI transient dita store SICB Canvetions 163 14 4 Access to the Magnetic Field 164 14 5 Accessing the SICB detector geometry ee Gaudi 165 14 6 Using FORTRAN code in Gaudi 166 page 5 GAUDI Table of Contents User Guide Version Issue 6 3 14 7 Handling pile up in Gaudi Chapter 15 Analysis utilities 15 1 Overview 15 2 CLHEP 15 3 HTL 15 4 NAG C 15 5 ROOT Chapter 16 Visualization Facilities 16 1 Overview uo ae 16 2 The GaudiLab service Chapter 17 Design considerations 17 1 Generalities G tats ast 17 2 Designing within the Framework 17 3 Analysis Phase 17 4 Design Phase
242. s interfaces such as IConcreteSvcTypel and IConcreteSvcType2 in the figure lInterface query InterfaceQ Service IProperty set Property get Property a fi Concrete SvcType2 Specific Service Figure 23 Implementation of a concrete service class Though not shown in the figure both of the IConcreteSvcType interfaces are derived from IInterface i method3 Q method4 As discussed above it is necessary to derive from the Service base class so that the concrete service may be made accessible to other Gaudi components The actual facilities provided by the service are available via the interfaces that it provides For example the ParticleProperties service implements an interface which provides methods for retrieving for example the mass of a given particle In figure 23 the service implements two interfaces each of two methods A component which wishes to make use of a service makes a request to the application manager Services are requested by a combination of name and interface type i e an algorithm would request specifically either ICconcreteSvcTypel or IConcreteSvcType2 page 134 it GAUDI Chapter 11 Framework services User Guide Version Issue 6 3 The identification of what interface types are implemented by a particular class is done via the queryInterface method of the IInterface interface This method must be implemented in the concrete service class In addition the initi
243. s ownership In other words the object should not be deleted This is also true for objects which are contained within other objects such as those derived from or instantiated from the Ob ject Vector class see the following section Furthermore objects which are to be registered into the store must be created on the heap i e they must be created with the new operator page 56 GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 6 4 Object containers As mentioned before all objects which can be placed directly within one of the stores must be derived from the Dat aOb ject class There is however another indirect way to store objects within a store This is by putting a set of objects themselves not derived from Dat abject and thus not directly storable into an object which is derived from Dat aObject and which may thus be registered into a store An object container base class is implemented within the framework and a number of templated object container classes may be implemented in the future For the moment two concrete container classes are implemented Object Vector lt T gt and ObjectList lt T gt These classes are based upon the STL classes and provide mostly the same interface Unlike the STL containers which are essentially designed to hold objects the container classes within the framework contain only pointers to objects thus avoiding a lot of memory to memory copying A further differenc
244. s can call setFilterPassed true false during their execute function Algorithms in the membership list downstream of one that sets this flag to false will not be executed unless the StopOverride property of the Sequencer has been set or the filtering algorithm itself is of type Sequencer and its BranchMembers property specifies a branch with downstream members Please note that if a sub algorithm is of type Sequencer the parent algorithm must call the resetExecuted method of the sub algorithm before calling the execute method otherwise the sequence will only be executed once in the lifetime of the job An algorithm instance is executed only once per event even if it appears in multiple sequences It may also be enabled or disabled being enabled by default This is controlled by the Enable property Enabling and disabling of algorithm instances is a capability that is designed for a future release of Gaudi that will include an interactive scripting language The filter passed or failed logic for a particular Algorithm instance in a sequence may be inverted by specifying the invert optional flag in the Members list for the Sequencer in the JobOptions file A Sequencer will report filter success if either of its main and branch member lists succeed The two cases may be differentiated using the Sequencer branchFilterPassed boolean function If this is set true then the branch filter was passed otherwise both it and the main
245. s distributed with Gaudi A number of examples is included in the current release of the framework The intention is that each example exercises and shows to an end user how to make use of some part of the functionality of the framework The following table shows the list of available examples Table 4 List of available examples in current release Example Name Target Functionality AlgSequencer Illustrating the use of the sequencer algorithm provided in the GaudiAlg package Associator Illustrating the use of the AxPart2MCParticleAsct associator tool to navi gate between reconstructed tracks and Monte Carlo particles Common Actually not a complete example contains main program used by many examples AlgSequencer DDexample DumpEvent FieldGeom FortranAl gorithm Histograms MCPrimary Vertex ParticleProperties SimpleAnaly sis ToolsAnalysis and system specific Job Options include files common to all examples DDexample Illustrating the use of the detector description DumpEvent Navigation of the LHCb transient event data model FieldGeom Making available existing Sicb magnetic field and geometry data to Gaudi algorithms Example of nested algorithms FortranAlgorithm Wrapping Fortran code in Gaudi Histograms Basic functionality of the framework to execute a simple algorithm access event data and fill histograms MCPrimaryVertex Retrieve data using SmartDataPtr Ntuples Two examples
246. s is done by making a call to the declareProperty method HistoAlgorithm HistoAlgorithm const std string name ISvcLocator pSvcLocator Algorithm name pSvcLocator m_hTrackCount 0 m_hPtvsP 0 Declare the algorithm s properties declareProperty HistogramFlag m_produceHistogram false nAnufsS WN HF Initialisation The application manager invokes the sysInitialize method of the algorithm base class which in turn invokes the initialize method of the base class the setProperties method and finally the initialize method of the concrete algorithm class As a consequence all of an algorithm s properties will have been set before its initialize method is invoked and all of the standard services such as the message service are available This is discussed in more detail in chapter 5 Looking at the code in the example we see that depending on the value of the histogram flag the HistoAlgorithmclass may also create two histograms at initialisation and declare them to the histogram data service see Chapter 9 for details on the use of histograms in Gaudi Listing 5 Example of creation of histograms 1 if m_produceHistogram 23 log lt lt MSG INFO lt lt Histograms will be produced lt lt endreq 3S 4 m_hTrackCount histoSvc gt book stat simplelD 1 TrackCount 100 0 3000 De if 0 m_hTrackCount 6 log lt lt MSG ERROR lt lt Cannot register
247. s not an object oriented database with modest effort a structure can be built on top to allow the Converters to emulate this behaviour In particular the issue of object linking had to be solved in order to resolve pointers in the transient world The concept of ROOT supporting paged tuples called trees and branches is adequate for storing bulk event data Trees split into one or several branches containing individual leaves with data The data structure within the Gaudi data store is tree like see Figure 29 In the transient world Gaudi objects are sub class instances of the DataObject The DataObject offers some basic functionality like the implicit data directory which allows e g to browse a data store This tree structure will be mapped to a flat structure in the ROOT file resulting in a separate tree representing each leaf of the data store Each data tree contains a single branch containing objects of the same type The Gaudi tree is split up into individual ROOT trees in order to give easy access to individual items represented in the transient model without the need of loading complete events from the root file i e to allow for selective data retrieval The feature of ROOT supporting selective data reading using split trees seemed not to be too attractive since generally complete nodes in the transient store should be made available in one go However ROOT expects ROOT objects they must inherit from TObject Therefore the obj
248. s storage is returned in IARRAY 1 An algorithm requiring this access should include the header file include SicbCnv TopLevel SicbFortran h and call it so float rpar 300 SicbFortran utdget WDRF D mpar int rpar log lt lt MSG INFO lt lt wdpar lt lt j lt lt lt lt vf j lt lt endreq Note that the data returned by the function is written into an integer array However we can also read floating point numbers as in the code fragment above by casting a float array One should notice that the geometry returned by this function is that which was used in the production of the data and not that which is in the current version of the cdf files Only if the option N is specified are the cdf files read in from the standard location In order to be able to use the array of parameters returned one has to know in advance the organization of these data in the cdf file since the data are stored in an array and not in a common block with named variables The sub algorithm readTRackerGeom in the example F ieldGeom extracts and writes out some digitization and geometry parameters of the outer tracker 14 6 Using FORTRAN code in Gaudi Existing FORTRAN code can be used within a Gaudi application by using the FortranAlgorithm class This is a standard Gaudi algorithm which calls the FORTRAN routines SUINITin the initialize method SUANAL in the execute method for each event and SU
249. scription All of them have almost the same usage and syntax The common things they have are attributes for class ID and hyperlink reference The difference is the value of the class ID of the objects they point to also some of them may contain other elements The hyperlink is in general specified using the format protocol hostname path to the file xml ObjectID or ObjectID The protocol and hostname parts can be omitted if the file resides on the local host It is possible to write a hyperlink without the full path name in case one needs to refer to an XML object residing inside another file In this case the relative path will be appended to the location of the currently parsed XML file For example having the current file location full path to current xml and inside this file a hyperlink as href next file xml NextOID the hyperlink will be resolved as full path to next file xml NextoOID If the hyperlink has the form 0b ject ID this means that the referred object is located in the same file For content model definitions of the catalog and catalogref elements see Figure 12 Lee me lt lt EMPTY gt gt catalog catalogref lt 7 oname ID C AR classID CDATA 3 OR __ ClassID CDATA 3 eee al lt lt EMPTY gt gt href CDATA we P Q Q N OR 1 logvolref ge OR ope OR OR detdem 1 va gt A 1 1 materialref
250. se class has no protected methods or data members and no public data members so in fact these are the only methods that are available Most of these methods are in fact provided solely to make the implementation of derived algorithms easier The base class has two main responsibilities the initialization of certain internal pointers and the management of the properties of derived algorithm classes A part of the Algorithm base class definition is shown in Listing 7 Include directives forward declarations and private member variables have all been suppressed It declares a constructor and destructor the three key methods of the Algorithm interface several accessors to services that a concrete algorithm will almost certainly require a method to create a sub algorithm the two methods of the IProperty interface and a whole series of methods for declaring properties page 43 GAUDI Chapter 5 Writing algorithms User Guide Version Issue 6 3 Listing 7 The definition of the Algorithm base class auw wnnwnnnwu B PF Se PS PSP SP BWWwWBWWWWWWWWwTon nN NNN NNN WN LDH AHN OBPWNHNRFP TOU WANA AHP WBNHRP DO WAATAADAAKFPWBNHRF DO AWAATA oO BPWN EF OC AANA UOUBPWNHR CU WAN DU fPWN EF ie class Algor public Construc Algorithm virtual Al StatusCode sysInitialize StatusCode initialize StatusCode sysExecute StatusCode execute StatusCode sysFinalize StatusCode finalize const std
251. se it may be necessary to look for histograms within the store The mechanism for doing this is identical to the method for locating event data objects within the event data store namely via the IDataProviderSvc interface as discussed in section 6 2 page 97 GAUDI User Guide Chapter 9 Histogram facilities Version Issue 6 3 SmartDataPtr lt IHistogramlD gt hist1D histoSvc stat simple 1 if 0 hist1D Print the found histogram histoSvc gt print hist1D 9 4 Persistent storage of histograms 9 4 1 HBOOK persistency An HBOOK conversion service exists which can convert objects of types IHistogram1D and IHistogram2D into a form suitable for storage in a standard HBOOK file In order to use it you need to use HbookCnv v in the CMT requirements file of your application and specify the following the job options Specify shared library for HBOOK Histogram persistency support ApplicationMgr DLLs HbookCnv Specify Histogram Persistency Output File with the file extension appropriate for the particular persistency type HistogramPersistencySvc OuputFile histo hbook ApplicationMgr DLLs HbookCnv 9 4 2 ROOT persistency The default implementation of the histogram persistency service uses HBOOK An alternate implementation using ROOT files is now available To use this alternative you need to use RootHistCnv v in the CMT requiremen
252. selection An example of a such an function object is shown in Listing 46 Please note that the factory declaration at line 16 is mandatory in order to allow Gaudi to instantiate the function object The DATAFILE and TYP tags as well as additional optional tags have the same meaning and syntax as for n tuples as described in section 10 2 3 1 page 107 GAUDI User Guide Chapter 10 N tuple and Event Collection facilities Version Issue 6 3 Listing 46 Example of a function object for second stage pre selections class EvtCollectionSelector public NTuple Selector Tuple Item lt long gt m_ntrack public EvtCollectionSelector IInterface svc NTuple Selector svc virtual EvtCollectionSelector Initialization virtual StatusCode initialize NTuple Tuple nt return nt gt item Ntrack m_ntrack Specialized callback for NTuples virtual bool operator NTuple Tuple nt return m_ntrack gt cut 1 2 3 4 5 6 7 8 9 8 0 E 2 3 4 5 6 ObjectFactory lt EvtCollectionSelector gt EvtCollectionSelectorFactory 10 4 Interactive Analysis using N tuples n tuples are of special interest to the end user because they can be accessed using commonly known tools such as PAW ROOT or Java Analysis Studio JAS In the past it was not a particular strength of the software used in HEP to plug into many possible persistent data representatio
253. sequence indicated failure The following examples illustrate the use of sequences with filtering and branching 5 5 1 Filtering example Listing 9 is an extract of the job options file of the AlgSequencer example a Sequencer instance is created line 2 with two members line 5 each member is itself a Sequencer implementing the sequences set up in lines 7 and 8 which consist of Prescaler EventCounter and HelloWorld algorithms The St opOverride property of the TopSequence is set to true which causes both sequences to be executed even if the first one indicates a filter failure The Prescaler and EventCounter classes are example algorithms distributed with the GaudiAlg package The Prescaler class acts as a filter passing the fraction of events specified by the PercentPass property as a percentage The Event Counter class just prints each event as it is encountered and summarizes at the end of job how many events were seen Thus at the end of job the Count er1 instance will report seeing 50 of the events while the Counter2 instance will report seeing 10 page 51 GAUDI Chapter 5 Writing algorithms User Guide Version Issue 6 3 Note the same instance of the HelloWorld class appears in both sequences It will be executed in Sequencel if Prescaler1 passes the event It will be executed in Sequence2 if Prescaler2 passes the event only if Prescaler failed it Listing 9 Example jobOptions using Sequencers d
254. ser Guide Chapter 4 Getting started Version Issue 6 3 Chapter 4 Getting started 4 1 Overview In this chapter we walk through one of the example applications Histograms which are distributed with the framework We look briefly at the different files and go over the steps needed to compile and execute the code We also outline where various subjects are covered in more detail in the remainder of the document Finally we cover briefly the other example applications which are distributed and say a few words on what each one is intended to demonstrate 4 2 Creating a job Traditionally a job is the running of a program on a specified set of input data to produce a set of output data usually in batch For the example applications supplied this is essentially a two step process First the executable must be produced and secondly the necessary environment variables must be set and the required job options specified as illustrated in Figure 4 The example applications consist of a number of source code files which together allow you to generate an executable program These are e The main program e Header and implementation files for each of the concrete algorithm classes e ACMT requirements file e The set of Gaudi libraries page 31 GAUDI User Guide Chapter 4 Getting started Version Issue 6 3 requirements HistoAlgorithm h HistoAlgorithm cpp Gaudi Library _ A makefile project_
255. setInverseFlag bool help in keeping track of the status of the locally kept inverse information The method buildiInverse has to be overridden by concrete associators since they choose in which form to keep the information and should be called by the associator when receiving the first request during the processing of an event Locally kept information An associator needs to reset its status to the same conditions as those after having been created when a new event is processed In order to be notified of such an incident happening the Associator base class implements the IListener interface and in the constructor register itself with the Incident Service see section 11 9 for details of the Incident Service The associator s flushCache method is called in the implementation of the Listener interface in the Associator base class This method must be overridden by concrete associators wanting to do a meaningful reset of the their initial status 12 4 1 3 A concrete example With the current release of Gaudi an example implementation of a specific associator is provided in the Associator example of the GaudiExamples package Some of the choices in the example are related to the specific classes for which the associator AxPart 2MCParticleAsct has been implemented and on how the information is available in the data files and should be regarded as such page 147 GAUDI User Guide Chapter 12 Tools and ToolSvc Version Issu
256. st Close Close recordset and database dbs Close Done End Sub ER BY ID 10 5 Known Problems Nothing is perfect and there are always things to be sorted out An HBOOK histogram file must be opened to ensure HBOOK initialization when writing n tuples using HBOOK When building the DoCnv package on Linux using CMT you must first set up the ROOT environment by sourcing the setup csh file page 110 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 Chapter 11 Framework services 11 1 Overview Services are generally sizeable components that are setup and initialized once at the beginning of the job by the framework and used by many algorithms as often as they are needed It is not desirable in general to require more than one instance of each service Services cannot have a state because there are many potential users of them so it would not be possible to guarantee that the state is preserved in between calls In this chapter we give describe how services are created and accessed and then give an overview of the various services other than the data access services which are available for use within the Gaudi framework The Job Options service the Message service the Particle Properties service the Chrono amp Stat service the Auditor service the Random Numbers service and the Incident service are available in this release The Tools service is described in Chapter 12
257. t lt logvol name lvSampleBoolean material Vacuum gt lt union name BoxUnion gt lt box name MainBox sizeX 10 amp mm sizeY 10 amp mm sizeZ 10 amp mm gt lt posXYZ x 0 amp mm y 0 amp mm z 5 amp mm gt lt box gt lt box name Box2 sizeX 10 amp mm sizeY 10 amp mm sizeZ 10 amp mm gt lt posXYZ x 0 amp mm y 0 amp mm z 10 amp mm gt lt box gt lt union gt lt logvol gt lt DDDB gt The example shows the union of two boxes where the first one is the main solid and the second one is positioned just next to the main solid along the z axis 8 5 2 4 Defining materials in XML Material is another important attribute of the logical volumes Materials can be defined as isotopes elements or mixtures The elements can be optionally composed of isotopes Mixtures can be composed of elements or of other mixtures Composition of elements is done always by specifying the fraction of the mass for each of the isotopes of the element For a mixture the user can specify either composition by number of atoms of by fraction of the mass for each of the elements or mixtures It is not allowed to page 85 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 mix composition by fraction of the mass and by atoms inside the same definition of a mixture The XML code listings 27 28 29 and 30 show how to define Gaudi isotopes
258. t Data Store ROOT converter I Figure 26 Persistency conversion services in Gaudi The Gaudi framework gives the possibility to save data objects into ROOT based files Thus since our principal store of data for the moment is still SICB data in Zebra files we see immediately an application of the issues mentioned above Figure 26 shows that data may be read from SICB files and ROOT files into the transient event data store and that data may be written into ROOT files It is the job of the persistency service to orchestrate this transfer of data between memory and disk The figure shows two slave services the SICB conversion service and the ROOT I O service These services are responsible for managing the conversion of objects between their transient and persistent representations Each one has a number of converter objects which are actually responsible for the conversion itself As illustrated by the figure a particular converter object converts between the transient representation and one other form here either Zebra or ROOT 13 3 Collaborators in the conversion process In general the conversion process occurs between the transient representation of an object and some other representation In this chapter we will be using persistent forms but it should be page 152 W GAUDI Chapter 13 Converters User Guide Version Issue 6 3 borne in mind that this could be any other transient form such
259. t amp reference StatusCode declareProperty const std string amp name double amp reference StatusCode declareProperty const std string amp name bool amp reference StatusCode declareProperty const std string amp name Vectors private Data members not shown Algorithm c Algorithm std of properties not shown string amp reference NO COPY ALLOWED NO ASSIGNMENT ALLOWED onst Algorithm amp a operator const Algorithm amp rhs page 44 GAUDI User Guide Chapter 5 Writing algorithms Version Issue 6 3 Constructor and Destructor The base class has a single constructor which takes two arguments The first is the name that will identify the algorithm object being instantiated and the second is a pointer to one of the interfaces implemented by the application manager ISvcLocator This interface may be used to request special services that an algorithm may wish to use but which are not available via the standard accessor methods below The IAlgorithm interface Principally this consists of the three pure virtual methods that must be implemented by a derived algorithm initialize execute and finalize These are where the algorithm does its useful work and discussed in more detail in section 5 3 Other methods of the interface are the accessor name which returns the algorithm s identifying name and sysInitialize sysFinalize sysExecute which a
260. t token Object Identifier specifies the name of the object whose property is to be set This must be followed by a dot The next token Propert yname is the name of the option to be set as declared in the declareProperty method of the IProperty interface This must be followed by an assign symbol The final token value is the value to be assigned to the property It can be a vector of values in which case the values are enclosed in array brackets and separated by commas The token must be terminated by a semicolon The type of the value s must match that of the variable whose value is to be set as declared in declareProperty The following types are recognised Boolean type written as true or false e g true false Integer type written as an integer value containing one or more of the digits 0 1 2 3 5 6 7 8 9 e g 123 923 or in scientific notation e g 12e2 Real type similar to double in C written as a real value containing one or more of the digits 0 1 2 3 4 5 0 7 8 9 followed by a dot and optionally one or more of digits again e g 123 123 45 or in scientific notation e g 12 5e7 String type written within a pair of double quotes e g I am a string Note strings without double quotes are not allowed Vector of the types above within array bracke
261. ter we look at how you might actually go about designing and implementing a real physics algorithm It includes points covering various aspects of software development process and in particular e The need for more thinking before coding when using an OO language like C e Emphasis on the specification and analysis of an algorithm in mathematical and natural language rather than trying to force it into unnatural object orientated thinking e The use of OO in the design phase i e how to map the concepts identified in the analysis phase into data objects and algorithm objects e The identification of classes which are of general use These could be implemented by the computing group thus saving you work e The structuring of your code by defining private utility methods within concrete classes When designing and implementing your code we suggest the your priorities should be as follows 1 Correctness 2 Clarity 3 Efficiency and very low in the scale OOness Tips about specific use of the C language can be found in the coding rules document 5 or specialized literature 17 2 Designing within the Framework A physicist designing a real physics algorithm does not start with a white sheet of paper The fact that he or she is using a framework imposes some constraints on the possible or allowed page 181 GAUDI User Guide Chapter 17 Design considerations Version Issue 6 3 designs The framework defines som
262. tes of a given cell or wire number in the local reference system The specialist can code the answer by using a minimal number of parameters specific to the detector structure Step 1 Define your detector element type This means providing the C definition of your specific detector module as shown in Listing 31 The actual implementation of all the methods is done inside MyDetector cpp file Listing 31 The C definition of the user defined detector element type MyDetector include Gaudi DetectorDataSvc DetectorElement h extern const CLID amp CLID_MyDetector class MyDetector public DetectorElement public double cellSize x y void setCellSize double size double AlPlateThickness void setAlPlateThickness double thick inline const CLID amp clID return MyDetector classID static const CLID amp classID return CLID_MyDetector private double m_cellSize double m_AlPlateThickness At first the user must obtain the unique class ID for his her own detector element type The class ID is needed for conversion service and the corresponding converter The methods returning the class ID must be supplied exactly as shown in the example The example shows further that the new detector element type will have its specific data e g detector cell size For this information we will create a user defined XML tag inside the lt specific gt section of detector element XML tag
263. the code is actually executed The subject of coding algorithms is treated in more depth in chapter 5 Chapter 6 discusses the use of the framework data stores Chapters 7 8 9 10 discuss the different types of data accessible via these stores event data detector description data material and geometry histogram data and n tuples Chapter 11 deals with services available in the framework job options messages particle properties random numbers and also has a section on developing new services Framework tools are discussed in Chapter 12 A rather more technical subject that of the use and implementation of converter classes is discussed in Chapter 13 The use of certain SicB facilities from within Gaudi and the use of FORTRAN code is discussed in Chapter 14 Chapter 15 gives pointers to the documentation for class libraries which we are recommending to be used within Gaudi Chapter 16 describes an implementation of visualisation facilities inside Gaudi Finally Chapter 17 is a small guide to designing classes that are to be used in conjunction with the application framework Appendix A contains a list of references Appendix B lists the options which may be specified for the standard components available in the current release Appendix C gives the details of the syntax and possible error messages of the job options compiler 1 2 Conventions 1 2 1 Units We have decided to adopt the same system of units as CLHEP as used also
264. the derived algorithm class see for example lines 10 and 11 in Listing 8 below 5 3 2 Declaring properties In general a concrete algorithm class will have several data members which are used in the execution of the algorithm proper These data members should of course be initialized in the constructor but if this was the only mechanism available to set their value it would be necessary to recompile the code every time you wanted to run with different settings In order to avoid this the framework provides a mechanism for setting the values of member variables at run time The mechanism comes in two parts the declaration of properties and the setting of their values As an example consider the class TriggerDecision in Listing 8 which has a number of variables whose value we would like to set at run time Listing 8 Declaring member variables as properties Les Af gt In the header fil z z 2 class TriggerDecision public Algorithm 3 4 private Sx bool m passAllMode 6 int m_muonCandidateCut 7 std vector m_ECALEnergyCuts 8 92 yya In the implementation fil EE a E 10 static const AlgFactory lt TriggerDecision gt s_factory 11 const IAlgFactory amp TriggerDecisionFactory s_factory T2 13 TriggerDecision TriggerDecision std string name ISvcLocator pSL 14 Algorithm name pSL m passAllMode false m_muonCandidateCut 0 15 m_E
265. the mechanism of converting event and detector objects into their graphical representation and built one example application This application can serve as a proof of concept and can also be used to help in the development of physics algorithms e g pattern recognition or in the verification of the detector geometry 16 1 1 The data visualization model The Gaudi architecture envisaged implementing data visualization using a similar pattern to data persistency We do not want to implement visualization methods in each data object In other words we do not want to tell an object to draw itself Instead we would implement converters as separate entities that are able to create specific graphical representations for each type of data object and for each graphical package that we would like to use In that way as for the persistency case we decouple the definition and behaviour of the data objects from the various technologies for graphics We could configure at run time to have 2D or 3D graphics depending on the needs of the end user at that moment Figure 31 illustrates the components that need to be included in an application to make it capable of visualizing data objects The interactive user interface is a Service which allows the page 173 GAUDI User Guide Chapter 16 Visualization Facilities Version Issue 6 3 end user to interact with all the components of the application The user could select which objects to display wh
266. the program could start at any event independent of the events simulated before Unlike the random number generators that were known from CERNLIB the state of modern generators is no longer defined by one or two numbers but rather by a fairly large set of numbers To ensure reproducibility the random number generator must be initialized for every event e The distribution of the random numbers generated is independent of the random number engine behind Any distribution can be generated starting from a flat distribution e The actual number generator can easily be replaced if at some time in the future better generators become available without affecting any user code The implementation of both generators and random number engines are taken from CLHEP The default random number engine used by Gaudi is the RanLux engine of CLHEP with a luxury level of 3 which is also the default for Geant4 so as to use the same mechanism to generate random numbers as the detector simulation Figure 22 shows the general architecture of the Gaudi random number service The client interacts with the service in the following way e The client requests a generator from the service which is able to produce a generator according to a requested distribution The client then retrieves the requested generator e Behind the scenes the generator service creates the requested generator and initializes the object according to the parameters The service also supplies
267. the shared random number engine to the generator e After the client has finished using the generator the object must be released in order to inhibit resource leaks RndmGenSvc Distribution Gauss owns RndmGen ees RndmEngine Figure 22 The architecture of the random number service The client requests from the service a random number generator satisfying certain criteria owns amp initializes page 130 it GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 There are many different distributions available The shape of the distribution must be supplied as a parameter when the generator is requested by the user Currently implemented distributions include the following see also the header file Gaudi RndmGenSvc RandomGenerators h fora description of the parameters to be supplied e Generate random bit patterns with parameters Rndm Bit e Generate a flat distribution with boundaries min max with parameters Rndm Flat double min double max e Generate a gaussian distribution with parameters Rndm Gauss double mean double sigma e Generate a poissonian distribution with parameters Rndm Poisson double mean e Generate a binomial distribution according to n tests with a probability p with parameters Rndm Binomial long n double p e Generate an exponential distribution with parameters ndm Exponential double mean enerate a Chi 2 dis
268. tially for setting up the job Once this is done a call to ApplicationMgr run is all that is needed to start the job proper The steps that occur within this method are discussed briefly in section 4 6 4 4 Configuring the job The application framework makes use of a job options file or possibly a database in future for job configuration The job options file of the Hist ograms example application is shown in Listing 3 on page 35 The format of an options file is discussed fully in Chapter 11 Options may be set both for algorithms and services and the list of available options for standard components is given in Appendix B For the moment we look briefly at one of the options The option TopAlg of the application manager is a list of algorithms that will be created and controlled directly by the application manager the so called top level algorithms The syntax is a list of the form ApplicationMgr TopAlg Typel Namel Type2 Name2 The line above instructs the application manager to make two top level algorithms One of type Typel called Name1 and one of type Type2 called Name2 In the case where the name of the algorithm is the same as the algorithm s type i e class only the class name is necessary Thus in the example in Listing 3 line 13 an instance of the class HistoAlgorithm will be created with name HistoAlgorithm page 33 GAUDI Chapter 4 Getting started User Guide Version
269. to access the Event Data Service since most concrete associators will need to access data in particular if accessing navigational short cuts Associator Properties Two properties are declared in the constructor and can be set in the jobOptions FollowLinks and DataLocation They are respectively a bool with initial value true and a std string with initial value set to The first is foreseen to be used by an associator when it is possible to either follow links between classes or retrieve navigational short cuts from the data A user can choose to set either behaviour at run time The second property contains the location in the data where the stored navigational information is located Currently it must be set via the jobOptions when necessary as shown in Listing 70 for particular implementation provided in the Associator example Two corresponding methods are provided for using the information from these properties followLinks and whichTable Inverse Association Retrieving information in the direction opposite to that of the links in the data is in general a time consuming operation that implies checking all the direct associations to access the inverse relation for a specified object For this reason Associators should keep a local copy of the inverse associations after receiving the first request for an event A few methods are provided to facilitate the work of Associators in this case The methods inverseExist and
270. to append or assign Check the statement if there exists values and if they are written correctly Maybe this error is a result of a previous error Error 016 Specified prop erty file does not exist or can not be resolved The compiler was not able to include a property file or didn t found the file A reason can be that the com piler was not able to resolve an environment variable which points to the location of the property file Check if you are using enviornment variables to resolve the file if they are mistyped wether in the sys tem or in the include direc tive or not set correctly Error 017 ifdef not followed by an identifier The ifdef statement is not fol lowed by the assertion identi fier WIN32 Add WIN322 after the ifdef statement Error 018 identifier in ifdef ifndef not known The assertion identifier used in the ifdef ifndef state ment is not known At the moment there can only be used WIN32 Change identifier to WIN32 Error 019 ifdef ifndef else endif doesn t end with a A semicolon was found after the ifdef ifndef else endif statement These state ments don t end with a semi colon Remove the semicolon after the ifdef ifndef else endif statement page 201 GAUDI Appendix C Job Options Grammar and Error Codes User Guide Version Issue 6 3 page 202 GAUDI User Guid
271. tput of specialised analysis algorithms page 65 GAUDI Chapter 7 LHCb Event Data Model User Guide Version Issue 6 3 7 2 Top level event data structures The event data objects are located in the event data store which is one of the stores described in Chapter 6 The data in the store are arranged in a tree This facilitates the location of objects within the store by human readable identifiers The tree structure consists of an Event root branching four sub trees roughly corresponding to the processing steps Monte Carlo event Raw event Reconstructed event and Analysis event A fifth branch for FrontEnd FE has been implemented in private code available under L1 VELO CVS tree Retrieving an identifiable object see Chapter 6 from the store is based on the knowledge of the logical path The paths so far implented are shown in the tables that follow They are defined in the files HCbEvent TopLevel EventModel h HCbEvent TopLevel EventModel cpp Table 5 Top level Event data model Logical Path Type Event Event Event MC MCEvent Event Raw RawEvent Ewvent Rec RecEvent Event Anal AnalEvent The LHCbEvent TopLevel directory also contains the include files for the top level event classes which are all derived from Dat aObject and are therefore identifiable The identifiable objects in the MonteCarlo Raw Reconstru
272. transient stores these warnings will provide an indication of a possible memory leak Note that currently the MemoryAuditor is only available for Linux 11 7 1 Enabling the Auditor Service and specifying the enabled Auditors The Auditor Service is enabled by the following line in the Job Options file Enable the Auditor Service ApplicationMgr DLLs Auditors Specifying which auditors are enabled is illustrated by the following example Enable the NameAuditor and ChronoAuditor AuditorSvc Auditors NameAuditor ChronoAuditor page 128 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 11 7 2 Overriding the default Algorithm monitoring By default only monitoring of the Algorithm execute function is enabled by default This default can be overridden for individual Algorithms by use of the following Algorithm properties Enable initialize and finalize auditing amp disable execute auditing for the myAlgorithm Algorithm myAlgorithm AuditInitialize true myAlgorithm AuditExecut false myAlgorithm AuditFinalize true 11 7 3 Implementing new Auditors The relevant portion of the Auditor abstract interface is shown below virtual StatusCode beforeInitialize IAlgorithm theAlg 0 virtual StatusCode afterInitialize IAlgorithm theAlg 0 virtual StatusCode beforeExecut IAlgorithm theAlg
273. tribution with n_dof degrees of freedom with parameters ndm Chi2 long n_dof enerate a Breit Wigner distribution with parameters dm BreitWigner double mean double gamma enerate a Breit Wigner distribution with a cut off with parameters ndm BreitWignerCutOff mean gamma cut off enerate a Landau distribution with parameters ndm Landau double mean double sigma DO PO PO ZO DB e Generate a user defined distribution The probability density function is given by a set of descrete points passed as a vector of doubles Rndm DefinedPdf const std vector lt double gt amp pdf long intpol Clearly the supplied list of possible parameters is not exhaustive but probably represents most needs The list only represents the present content of generators available in CLHEP and can be updated in case other distributions will be implemented Since there is a danger that the interfaces are not released a wrapper is provided that automatically releases all resources once the object goes out of scope This wrapper allows the use of the random number service in a simple way Typically there are two different usages of this wrapper page 131 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 e Within the user code a series of numbers is required only once i e not every event In this case the object is used locally and resources are released immediately after use This example is shown in Listing 5
274. ts separated by a comma e g true false true e g 124 124 135e2 e g 123 53 23 53 123 12 5e2 e g String 1 String 2 String 3 A single element which should be stored in a vector must be within array brackets without a comma e g true e g String Please note that it is not necessary any more to define in the job options file the type for the value which is used The job options compiler will recognize by itself the type of the value and will handle this type correctly page 116 GAUDI User Guide Chapter 11 Framework services Version Issue 6 3 Append Statement Because of the possibility of including other job option files see below it is sometimes necessary to extend a vector of values already defined in the other job option file This functionality is provided be the append statement An append statement has the following syntax lt Object Identifier gt lt Propertyname gt lt value gt The only difference from the assignment statement is that the append statement requires the symbol instead of the symbol to separate the Propert yname and value tokens The value must be an array of one or more values e g true e g String e g true false true e g 124 124 135e2 e g 123 53 23 53 123 12 5e2 eg String 1 String 2 String 3 The job o
275. ts To select pile up for signal or minimum bias one can use the pile up algorithm page 168 GAUDI User Guide Chapter 14 Accessing SICB facilities Version Issue 6 3 property PileUpMode which can be set to LUMISIGNAL or LUMIMINBIAS In both cases the number of Pile up events depends on the luminosity ApplicationMgr TopAlg PileUpAlg Algl1 Alg2 PileUpAlg PileUpMode LUMISIGNAL Finally the second event selector should be configured the input data source for the pile up events has to be defined with the PileUpSelector JobInput property This property accepts JOBID s FILE names or TAPEs note that the format of this option is different to the format explained in section 14 2 for the property of the main event selector PileUpSelector JobInput JOBID 12933 page 169 GAUDI Chapter 14 Accessing SICB facilities User Guide Version Issue 6 3 page 170 GAUDI User Guide Chapter 15 Analysis utilities Version Issue 6 3 Chapter 15 Analysis utilities 15 1 Overview In this chapter we give pointers to some of the third party software libraries that we use within Gaudi or recommend for use by algorithms implemented in Gaudi 15 2 CLHEP CLHEP Class Library for High Energy Physics is a set of HEP specific foundation and utility classes such as random generators physics vectors geometry and linear algebra It is structured in a set of packages i
276. ts file of your application and specify the following job options Specify shared library for ROOT Histogram persistency support ApplicationMgr DLLs RootHistSvc Specify ROOT or HBOOK persistency HBOOK is the default ApplicationMgr HistogramPersistency ROOT Specify Histogram Persistency Output File with the file extension appropriate for the particular persistency type HistogramPersistencySvc OuputFile histo rt page 98 GAUDI User Guide Chapter 10 N tuple and Event Collection facilities Version Issue 6 3 Chapter 10 N tuple and Event Collection facilities 10 1 Overview In this chapter we describe facilities available in Gaudi to create and retrieve n tuples We discuss how Event Collections which can be considered an extension of n tuples can be used to make preselections of event data Finally we explore some possible tools for the interactive analysis of n tuples 10 2 N tuples and the N tuple Service User data so called n tuples are very similar to event data Of course the scope may be different a row of an n tuple may correspond to a track an event or complete runs Nevertheless user data must be accessible by interactive tools such as PAW or ROOT Gaudi n tuples allow to freely format structures Later during the running phase of the program data are accumulated and written to disk The transient image of an n tuple is stored in a Gaudi data store which is conn
277. ts in the collaboration is a set of programs for doing event simulation reconstruction visualisation etc and a set of tools which facilitate the writing of analysis programs Additionally a physicist wants something that is easy to use and though he or she may claim otherwise is extremely flexible The purpose of the Gaudi application framework is to provide software which fulfils these requirements but which additionally addresses a larger set of requirements including the use of some of the software online If the software is to be easy to use it must require a limited amount of learning on the part of the user In particular once learned there should be no need to re learn just because technology has moved on You do not need to re take your licence every time you buy a new car Thus one of the principal design goals was to insulate users physicist developers and physicist analysists from irrelevant details such as what software libraries we use for data I O or for graphics We have done this by developing an architecture An architecture consists of the specification of a number of components and their interactions with each other A component is a block of software which has a well specified interface and functionality page 13 GAUDI User Guide Chapter 2 The framework architecture Version Issue 6 3 An interface is a collection of methods along with a statement of what each method actually does i e its functiona
278. ts on histograms 97 For histogram persistency 98 Limitations on N tuples 100 104 Histograms HTL 171 Naming convention for 10 Persistency service 98 HTL 171 I Inheritance 43 Installation of the framework 23 Interactive Analysis of N tuples 108 Interface 13 and multiple inheritance 17 Identifier 17 In C 17 page 213 GAUDI Index User Guide Version Issue 6 3 Interfaces L AIDA 171 Algorithm 16 43 45 47 IAlgTool 140 IAppMgrUI 33 IAssociator 145 IAuditor 129 IDataManager 15 IDataProviderSvc 15 53 54 99 IDetectorElement 72 IGeometryInfo 72 IHistogramSvc 16 53 IncidentListener 133 ILVolume 74 IMessageSvc 16 INTupleSvc 53 99 INtupleSvc 16 IParticlePropertySvc 122 IProperty 16 33 43 IPVolume 75 ISolid 75 ISvcLocator 45 IToolSvc 143 Validity 72 74 IXmlSvc 91 Libraries Building 21 Component 20 containing FORTRAN code 21 Linker 20 Linux 27 M Magnetic Field See Services Message service 119 Monitoring of algorithm calls with the Auditor service 128 statistical using the Chrono amp stat service 126 Monte Carlo truth association to 67 navigation using Associators 145 MsgStream 38 N NAG C 172 page 214 GAUDI Index User Guide Version Issue 6 3 N tuples 99 Booking and declaring tags 101 filling 101 Interactive Analysis of 108 Limitations imposed by HBOOK 100 104 persistency 103 readin
279. tware follows or should follow the LHCb C coding conventions described in reference 5 One consequence is that the specification of the C classes is done in two parts the header or h file and the implementation or cpp file 1 2 3 Naming Conventions Histograms In order to avoid clashes in histogram identifiers we suggest that histograms are placed in named subdirectories of the transient histogram store The top level subdirectory should be the name of a sub detector group e g st at VELO Below this users are free to define their own structure One possibility is to group all histograms produced by a given algorithm into a directory named after the algorithm Event data Naming conventions for LHCb data are discussed in Chapter 7 and more fully in reference 6 1 2 4 Conventions of this document Angle brackets are used in two contexts To avoid confusion we outline the difference with an example The definition of a templated class uses angle brackets These are required by C syntax so in the instantiation of a templated class the angle brackets are retained AlgFactory lt UserDefinedAlgorithm gt s_factory This is to be contrasted with the use of angle brackets to denote replacement such as in the specification of the string lt concreteAlgorithmType gt lt algorithmName gt which implies that the string should look like v EmptyAlgorith
280. ue 6 3 of all valid paths may be deduced at run time by making repeated queries to the event data service but this is unlikely to be useful in general since the structure will be largely fixed Anal Object Vector lt AxPartCandidate gt es cS AxPartCandidates MC Camaran a MCParticles Corana d MCVertices MCEcalHits MCHcalHits MCVertexHits MCMuonHits MCTrackerHits Raw Cer Figure 7 The structure of a part of the LHCb event data model As stated above all interactions between the data stores and algorithms should be via the IDataProviderSvc interface The key methods for this interface are shown in Listing 12 Listing 12 Some of the key methods of the IDataProviderSvc interface S S v vuv nw ta ta tusCode tusCode findObject const std string amp path DataObject amp pObject findObject DataObject node const std string amp path DataObject amp pObject tusCod retrieveObject const std string path DataObject amp pObject retrieveObject DataObject node const std string amp path tusCod DataObject amp pObject tusCod registerObject const std string path DataObject amp pObject tusCod gisterObject DataObject node DataObject amp pObject K page 54 GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 The first fou
281. um during the conversion process Smart references and Smart reference vectors are declared inside a class as include Gaudi Kernel SmartRef h include Gaudi Kernel SmartRefVector h class MCParticle private Smart reference to origin vertex SmartRef lt MCVertex gt m_originMCVertex Vector of smart references to decay vertices SmartRefVector lt MCVertex gt m_decayMCVertices public Access the origin Vertex Note When the smart reference is converted to MCVertex the object will be loaded from the persistent medium MCVertex originMCVertex return m_originMCVertex page 62 GAUDI User Guide Chapter 6 Accessing data Version Issue 6 3 The syntax of usage of smart references is identical to plain C pointers The Algorithm only sees a pointer to the MCVertex object include Gaudi DataSvc SmartDataPtr h Use a SmartDataPtr to get the MC particles from the event store SmartDataPtr lt MCParticleVector gt particles eventSvc Event MC MCParticles MCParticleVector const_iterator iter Loop over the particles to access the MCVertex via the SmartRef for iter particles gt begin iter particles gt end itert MCVertex originVtx iter gt originMCVertex if 0 originVtx std cout lt lt Origin vertex lt lt iter lt lt std endl All LHCbEvent data types use the Smart references and
282. ve newly created objects to disk files The writing of the converters necessary for the latter is covered in chapter 13 6 2 Using the data stores There are four data stores currently implemented within the Gaudi framework the event data store the detector data store the histogram store and the n tuple store They are described in chapters 7 8 9 and 10 respectively The stores themselves are no more than logical constructs with the actual access to the data being via the corresponding services Both the event data service and the detector data service implement the same IDat aProviderSvc interface which can be used by algorithms to retrieve and store data The histogram and n tuple services implement extended versions of this interface IHistogramSvc INTupleSvc which offer methods for creating and manipulating histograms and n tuples in addition to the data access methods provided by the other two stores Only objects of a type derived from the Dat aOb ject base class may be placed directly within a data store Within the store the objects are arranged in a tree structure just like a Unix file system As an example consider Figure 7 which shows a part of the LHCb transient data model An object is identified by its position in the tree expressed as a string such as Event or Event MC MCParticles In principle the structure of the tree i e the set page 53 GAUDI Chapter 6 Accessing data User Guide Version Iss
283. vent Selector input and output file specifications have changed in the same way as for n tuples Notice that the Evt Se1 property is now a property of EventSelector The old way ApplicationMgr EvtSel FILE afs data rawh ApplicationMgr EvtSel JOBID 16434 The new way EventSelector EvtMax 5 EventSelector Input PILE afs sicb_bpipi_v233_100ev dstl1 JOBID 16434 DATAFILE D data selected_events root TYP ROOT Possible tags are FILE and JOBID for SICB data DATAF ILE for file name TYP for technology identifier OPT for new update SVC for conversion service name and AUTH for extra authentication information if needed by the technology Detector Element no longer has a default constructor One must be provided explicitly IOpaqueAddress Implementations of IOpaqueAddress no longer return the full path of an object with the function ob ject Name only the name To get the full path use directory gt fullpath instead 3 3 2 Deprecated features Accessors names in Algorithm Use the service accessors with short names e g msgSvc instead of the long equivalent ones e g messageService Access to extra services from Algorithms Use the templated method service instead of using the serviceLocator together with the queryInterface to get a reference toa service interface page 26 it
284. volume object and thus is needed to capture this information inside XML as well For that purpose there are defined the XML tags for the solids of the basic 3D volumes such as sphere box cylinder conus toroid The diagram in Figure 17 shows the content model definition of the simple solids An example of XML is shown in Listing 26 Note that simple solids canott contain position and rotation definitions in the context of logical volume When used inside logical volume the transformation makes no sense On the other hand when used in the context of boolean solids the transformation tags are needed in order to specify the position of the solids according to each other box lt lt EMPTY gt gt name ID posxYZ 1 ey sizeX CDATAY x CDATA __ OR sizeY CDATA K gt ao CDATA 4 sizeZ CDATA OR 0 1 lt lt EMPTY gt gt lt lt EMPTY gt gt lt ee rotAxis CDATA i 1 2 TH posRPhiZ f1 OR f 0 1 axTheta CDATA r CDATA axPhi CDATA gt lt lt gt gt i phi CDATA lt lt EMPTY gt gt BUT a ngie CDATA z CDATA posRThPhi rotXYZ r CDATA rotX CDATA theta CDATA rotY CDATA phi CDATA rotZ CDATA N x lt Figure 17 Content model definition of the box XML element applies to all simple solids page 84 GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 Boolean solids T
285. w to say how many of the elements can be placed inside the parent element This is very important for validation purposes Table 9 Multiplicity used in the content model definitions Diagram notation DTD notation Description 1 Exactly one 0 1 Optional one or zero i One or more 0 Zero or more e The OR keyword in the diagram means that the element may or may not contain the child elements connected to it by arrows If the keyword is missing in the diagram then the sequence of the child elements from left to right is assumed and multiplicity can play important role in this context e Attributes of elements are shown as data members with their type specified and optionally a valid or default values The type can be any of the types shown in the Table 10 This is not the complete list of attribute types available just those used by the detector description Table 10 Attribute types Type Description ID Unique identifier IDREF Reference to a unique identifier ENUM Enumeration type CDATA Character data string e The DTD also specifies whether the attribute is optional required or has fixed or default value This information is not shown in the diagrams and the user has to look at the concrete DTD file in order to get this information page 78 W GAUDI User Guide Chapter 8 Detector Description Version Issue 6 3 8 5 2 1 Defining the top level stru
286. what the algorithm is supposed to do before we start designing it and of course before we start producing lines of C code One old technique for that is to think in terms of data flow diagrams as illustrated in Figure 32 where we have tried to decompose the tracking algorithm into various processes or steps In the analysis phase we identify the data which is needed as input event data geometry data configuration parameters etc and the data which is produced as output We also need to think about the intermediate data Perhaps this data may need to be saved in the persistency store to allow us to run a part of the algorithm without starting always from the beginning We need to understand precisely what each of the steps of the algorithm is supposed to do In case a step becomes too complex we need to sub divide it into several ones Writing in plain english and using mathematics whenever possible is extremely useful The more we understand about what the algorithm has to do the better we are prepared to implement it 17 4 Design Phase We now need to decompose our physics algorithm into one or more Algorithms as framework components and define the way in which they will collaborate After that we need to specify the data types which will be needed by the various Algorithms and their relationships Then we need to understand if these new data types will be required to be stored in the persistency store and how they will map to the existi
287. wish to make reports on its progress or on errors that occur All communication with the outside world should go through the message service component via the IMessageSvc interface Use of this interface is discussed in Chapter 11 As mentioned above by virtue of its derivation from the Algorithm base class any concrete algorithm class implements the Algorithmand IProperty interfaces except for the three methods initialize execute and finalize which must be explicitly implemented by the concrete algorithm IAlgorithm is used by the application manager to control top level algorithms IProperty is usually used only by the job options service The figure also shows that a concrete algorithm may make use of additional objects internally to aid it in its function These private objects do not need to inherit from any particular base class so long as they are only used internally These objects are under the complete control of the algorithm object itself and so care is required to avoid memory leaks etc We have used the terms interface and implements quite freely above Let us be more explicit about what we mean We use the term interface to describe a pure virtual C class i e a class with no data members and no implementation of the methods that it declares For example class PureAbstractClass virtual methodl 0 virtual method2 0 is a pure abstract class or interface We say that a class implements

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