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Daya Bay Offline Software User Manual November 5, 2015

1. Field Type Null Key Default Extra 4 SEQNO int 11 NO PRI NULL ROW_COUNTER int 11 NO PRI NULL LedId int 11 YES NULL Voltage float YES NULL l Frequency float YES NULL ChannelId int 11 YES NULL ErrorCode int 11 YES NULL l 7 rows in set 0 02 sec name dbtype codetype description code2db LedId int int IOW_CAL_LED_ID Voltage float float IOW_CAL_LED_ID_Voltage Frequency float float IOW_CAL_LED_ID_Frequency ChannelId int int IOW_CAL_Channel_ID ErrorCode int int IOW_CAL_ErrorCode Table 19 35 DBI Table specification for class GDcsMuonCalib which corresponds to table DesMuonCalib 35http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDcsMuonCalib spec 19 36 DCSPMTHV 223 19 36 DcsPmtHv Table specification source dybgaudi trunk Database DybDbi spec GDcsPmtHv spec PMT High Voltage monitoring table mysql amp gt describe DcsPmtHv 4 Field Type Null Key Default Extra SEQNO int 11 NO PRI ROW_COUNTER int 11 NO PRI NULL auto_increment ladder
2. dtLastTrigger dt i me Se E Y AAA 97 711 3 09 X Old ROOT Object Browser S f Entries We Eile View Options Help E 104 Mean 6 439e 05 EEY dal Sel aloe 0 Option Y E RMS 7 119e 05 all Folders Contents of ROOT Filesstest_dtrooVEventvUserData Dt 1 E J root B UserData_Dt Ap dtLastTrigger EI PROOF Sessions 10 E E eliza1 6 dayabay users dandwye E 3 ROOT Files A H a E test_dt root E 4 Sy Event 10 a Random 1 E 3 E Readout 1 E 3 E Registration Sequer A qj 4S User Data A f g 2am 10 AAA ANA iani aAa 4 0 1000 2000 3000 4000 5000 6000 2 Objects atLastTrigger dtLastTrigger ns Figure 3 7 Example of browsing and histogramming user defined data in ROOT To add your own variables copy and modify the module Tutorial Quickstart python Quickstart Dt Data py See section 3 4 8 for general advice on modifying an existing job module Currently single integers single floating point decimal numbers and arrays of each can be added as user defined variables 3 4 4 Adding User defined Variables to Tagged Events The Tagging UserTagging package provides some convenient tools for simultaneously applying tags and adding user data for those tagged events Following the example described in section 3 4 2 user data can be added in parallel to an event tag In the initTagList function you can define user data associated with the tag lmyTag self addTag MySpecialEvent Event UserTag MySpecial
3. PMT High Voltage monitoring table for AD mysql amp gt describe DcsAdPmtHv 4 4 4 4 Field Type Null Key Default Extra SEQNO int 11 NO PRI ROW_COUNTER int 11 NO PRI NULL auto_increment ladder tinyint 4 YES NULL col tinyint 4 YES NULL ring tinyint 4 YES NULL voltage float YES NULL pw tinyint 4 YES NULL 4 7 rows in set 0 07 sec name dbtype codetype description code2db Ladder tinyint 4 int PMT ladder Column tinyint 4 int PMT column Ring tinyint 4 int PMT ring Voltage float float PMT Voltage Pw tinyint 4 int PMT Power ON OFF Table 19 31 DBI Table specification for class GDcsAdPmtHv which corresponds to table DcsAdPmtHv 31http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDcsAdPmtHv spec 19 32 DCSADTEMP 19 32 Table specification source dybgaudi trunk Database DybDbi spec GDcsAdTemp spec DcsAd Temp AD Temperature monitoring table mysql amp gt describe DcsAdTemp 4 Field SEQNO l ROW_COUNTER Temp_PT1 Temp_PT2 Temp_PT3 Temp_PT4 poi a a aaa m ga int 11 int 11 float flo
4. lhistorian TrackSelection pdg 20022 or prescale by 100 This example will select any track created by a neutron capture likely gamma rays 1 lhistorian TrackSelection CreatorProcess G4NeutronCapture This should be contrasted with this example which will save vertices with a neutron capture This means the vertex saved will be a neutron capture vertex and is only valid for neutron tracks 1historian VertexSelection Process G4NeutronCapture This example is slightly tricksy but useful for muon induced showers It will select muons and particles that came off the muon but not sub particles of those This lets you see delta rays or muon induced neutrons for example but not record the entire shower lhistorian Track AncestorTrackPdg 13 or AncestorTrackPdg 13 2 and AncestorIndirection lt 2 3 or pdg 13 or pdg 13 This example selects only vertices which are inside the oil volume or sub volume of the oil at the LingAo detector 1 i e in oil AVs or scintillator volumes lhistorian VertexSelection DetElem in dd Structure AD la oil1 This example selects vertices which are in the oil not any subvolumes 1historian VertexSelection DetectorElementName dd Structure AD la oil1 This example saves only start and end vertices as well as vertices that change materials 1historian VertexSelection IsStopping 1 and M
5. Data is written out using a DybStorageSvc The service is given a RS and will write it out through the converter for the RS This conversion will also trigger writing out all data that the RS points to When to write out In principle one can write a simple algorithm that uses DybStorageSvc and is placed at the end of the chain of top level algorithms As a consequence data will be forced to be written out at the end of each execution cycle This is okay for simple analysis but if one wants to filter out records from the recent past and still in the AES based on the current record it will be too late as they will be already written to file Instead to be completely correct data must not be written out until every chance to use it and thus filter it has been exhausted This is done by giving the job of using DybStorageSvc to the agent that is responsible for clearing out data from the AES after they have fallen outside the analysis window 8 5 4 Reading data in Just as with output input is controlled by the RS objects In Gaudi it is the jobs of the event selector to navigate input When the application says go to the next event it is the job of the event selector to interpret that command In the Daya Bay software this is done by DybI0 DybEvtSelector which is a specialization of the generic RootI0Svc RootI0EvtSelector This selector will interpret next event as next RegistrationSequence Loading the next RS from fil
6. Plot AD 2 virtual StatusCode plotAD DayaBay Detector det 3 double chrg 8 24 double time 8 24 4 const char chrgunit 0 const char timeunit 0 5 const charx info 0 0 6 7 8 10 11 12 13 14 16 CHAPTER 2 QUICK START double chrg 9 24 2 double time 9 24 2 const char chrgunit 0 const char timeunit 0 const charx info 0 0 A pause method for user After this all displayed stuff will be flushed virtual StatusCode pause 0 where for AD chrg and time are arrays indexed by ring 1 and column 1 while for water pool chrg and time arrays are indexed by wall 1 spot 1 and inward 2 13 RECONSTRUCTION 2 13 Reconstruction 17 18 CHAPTER 2 QUICK START 2 14 Database The content of this quickstart has been migrated to sop Shttp dayabay bn1 gov oum sop 2 14 DATABASE 19 20641 900905801 UND 0000 SHOS LL 1102 das p UNS SUS eg LUN NOpeoyqres siega seprnon s CELLET 00 00 19 1 peones SL0O0rFIOOZtocot 00 ES clus OZ Pett vo o r o oroy rrrnrssss seeeenees TTIKIEI soeeeeney a arsu 90 0909901 110 0000 SPOS LL LOZ des Li UNS 0 Huang ez Lebu InopEOHdiES sMOMeqedeg A S od A 1 Figure 2 1 A snapshot for EvtDsp for a muon event which passed outer and inner water pool and struck AD No 2 while AD No 1 was quiet The time and charge patterns of the AD and water pool hits are clearly seen Chapter 3 Anal
7. To make NuWa use your modified package run the following commands in a new clean shell ishell gt pushd NuWa trunk 2shell gt source setup sh 3shell gt export CMTPROJECTPATH path to myProjects CMTPROJECTPATH 4shell gt cd dybgaudi DybRelease cmt 5shell gt source setup sh 6shell gt popd 7shell gt pushd myNuWa CenterOfChargePos cmt 8shell gt source setup sh source setup sh This shell will now use your modified code instead of the original version in NuWa 1shell gt nuwa py n 1 m Quickstart Calibrate m Quickstart Reconstruct 2 o recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3 daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root After you have verified that your changes are correct you can commit your changes 1shell gt cd CenterOfChargePos 2shell gt svn diff 3 Review the changes you have made 4shell gt svn commit m I fixed a bug 3 4 11 Using Services Another advantage of using NuWa is that it provides a set of useful Services Services give you access to other data in addition to the event data such as cable mappings calibration parameters geometry information etc Services can also provide other useful tasks Table 3 3 gives lists some common services Section 3 5 14 gives detailed descriptions of the common services Multiple versions of the same service can exists For example StaticCalibDataSvc loads the PMT calibration parameters from a text table while Dbi
8. esp ThisStageName Electronic esp LowerStageName Detector tesp DutputLevel 2 self stage_cfg ElectronicSequence Members append esp from ElecSim ElecSimConf import EsIdealFeeTool feetool EsIdealFeeTool feetool EnableNonlinearity False return ANI anP WwNRrFTKDKT AN DAA PWN BS There is nothing new here regarding about Fifteen package configuration except that name of this stage is Electronic and lower stage is Detector The simulation chain is setup in this way Here a non linearity option is turn off to demonstrate how to configure the real working tool For completeness the configuration of TrigReadProc and SingleLoader are included def configureTrigRead self gt Configure the Trigger and Readout stage from TrigReadProc TrigReadProcConf import TrigReadProc tsp TrigReadProc tsp ThisStageName TrigRead tsp LowerStageName Electronic aa e wn e 00 300 0BpB 4ouaNr Oocoso0o N o 0 3D 0 4u NR OANOUMPWBNRrRFP THO WAN DAT PWN FB N o 142 CHAPTER 15 SIMULATION PROCESSING MODELS wi tsp TrigTools tsp RoTools tsp OutputLevel 2 self stage_cfg TrigReadSequence Members append tsp return def configureSinglelLoader self gt Configure the SingleLoader stage from SingleLoader SingleLoaderConf import SingleLoader sll SingleLoader sll ThisStageName SingleLoader sll LowerStageName TrigRead s11 QOutputLevel
9. if energyStatus 1 amp amp energy gt 0 Reconstruction was successful if detector 1 AD 1 chargeVsEnergyAD1H gt Fill energy nominalCharge energy else if detector 2 40 41 42 43 44 45 46 000 JO O0aAGUuN RP TOWANDA PWN XAO O0p pouoNnN A 2 3 32 CHAPTER 3 ANALYSIS BASICS AD 2 chargeVsEnergyAD2H gt Fill energy nominalCharge energy J Y End loop over AD triggers in the multiplet Y End loop over AD coincidence multiplets Using TTree Draw with Unfriendly Trees The previous example script allowed us to correlate and histogram data between the unfriendly Coincidence and CalibStats trees This example required that we manually loop on the individual entries in the Coincidence tree and fill the histograms entry by entry An alternate approach is to reformat the data from the unfriendly CalibStats tree into a friendly format Once in this friendly format we can return to simple calls to TTree Draw to place cuts and histogram data This approach is more technical to setup but can be useful if you want to continue to use TCuts or if you want to repeatedly histogram the data to explore the variations of cuts As discussed this approach relies on reformatting the data from an unfriendly tree into a friendly format The example script dybTreeDrawUnfriendly C generates the same histograms as the previous example dybTreeGetLeafUnfriendly
10. lnttps wiki bn1 gov dayabay index php title Cluster_Account_Setup 63 64 CHAPTER 5 INSTALLATION AND WORKING WITH THE SOURCE CODE 5 2 Instalation of a Release If you work on a cluster it is best to use a previously existing release If you do want to install your own copy it is time and disk consuming but relatively easy A script called dybinst takes care of everything First you must download the script It is best to get a fresh copy whenever you start an installation The following examples show how to install the trunk branch which holds the most recent development shell gt svn export http dayabay ihep ac cn svn dybsvn installation trunk dybinst dybinst Now let it do its work shell gt dybinst trunk all Expect it to take about 3 4 hours depending on your computer s disk CPU and network speed It will also use several GBs of storage some of which can be reclaimed when the install is over 5 3 Anatomy of a Release external holds 3 party binary libraries and header files under PACKAGE VERSION sub directories NuWa RELEASE holds the projects and their packages that make up a release lcgemt build information for using 3 party external packages gaudi the Gaudi framework lhcb packages adopted from the LHCb experiment dybgaudi packages specific to Daya Bay offline software relax packages providing dictionaries for CLHEP and other HEP libraries 5 3 1 Release Projects and Packages e What i
11. m Tagger CalibStats 3 m Quickstart Reconstruct m SmartFilter Clear m SmartFilter KeepRecon o recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root A O au 1 Generate Spallation only data files 2shell gt nuwa py n 1 A 0 2s m Quickstart Calibrate m Tagger CalibStats 3 m Quickstart Reconstruct m Tagger MuonTagger MuonTag m Tagger MuonTagger SpallData m SimpleFilter Keep Event Data Muon Spallation o spall NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root NO op 3 5 CHEAT SHEETS 47 1 Generate ADCoincidence only data files 2shell gt nuwa py n 1 m Quickstart Calibrate m Tagger CalibStats 3 m Quickstart Reconstruct m Tagger CoincTagger ADCoincTag m Tagger CoincTagger ADCoincData m SimpleFilter Keep Event Data Coinc ADiCoincData Event Data Coinc AD2CoincData o coinc NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root NO 1 f daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 1 Generate ODM figures 2shell gt nuwa py n 1 output stats file1l odmHistograms 3 m AdBasicFigs MakeFigs m Quickstart Calibrate m Tagger CalibStats m AdBasicFigs MakeCalibFigs m MuonBasicFigs MakeCalibFigs m Quickstart Reconstruct m AdBasicFigs MakeReconFigs daq NoTag 0005773 Physi
12. the advanced example dybTreeGetLeafUnfriendly C generates a histogram with data from both the Coincidence Shttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Tutorial Quickstart OMAN OA FF WN hehe NF Oo OAN AM PWNH RF THK WAN AAT PWN EBE Www wwwwwwnwwnn nnd nvndvnnnnn OANA TA RWNHrRFDOHOAN DOA BFWN FO 3 2 DAYA BAY DATA FILES 31 and CalibStats data The first step in this process is to create an index to allow a unique look up of an entry from the CalibStats tree Disable pre existing index in the calib stats trees Another reason ROOT is frustrating we must manually do this calibStatsT GetEntries Long64_tx firstEntry calibStatsT GetTreeOffset for int treeIdx 0 treeIdx lt calibStatsT GetNtrees treeIdx calibStatsT LoadTree firstEntry treeldx calibStatsT GetTree gt SetTreeIndex 0 Build a new look up index for the unfriendly tree Trigger number and detector id uniquely identify an entry calibStatsT BuildIndex triggerNumber context mDetld Once this index is available we can manually load a specific CalibStats entry with the call Look up corresponding entry in calib stats int status calibStatsT GetEntryWithIndex triggerNumber detector Now that we are prepared we can step through each entry in the Coincidence tree For each Coincidence multiplet we can look up all of the corresponding entries from the CalibStats tree Here is the m
13. All ranges that start between this time and that time hence the term Extended Context Further during the retrieval of data from the main table addition restrictions can be imposed The result of an Extended Context query is a collection of rows that will not normally represent the state of the detector at a single moment in time and it is up to the user to interpret the results meaningfully However it does allow the user the power of raw SQL queries 17 2 7 SimFlag Association As explained in the preceding section the interface finds the database data that best matches the context of the data There are occasions when this matching needs to be changed for example there can be times when Monte Carlo data needs to be treated exactly as if it were event data and this includes the way it retrieves from the database To support this the user can specify for any type of data an associated list of data types If this is done then instead of using the current type each of the alternative types are tried until a match is found This matching takes precedence over the cascade i e all associated types are tried on the first database in the cascade before moving on to the second and subsequent cascade members This ensures that higher members which might even refer back to the ORACLE database at FNAL are only tried as a last resort 17 2 8 Authorising Databases and Global Sequence Numbers As explained in the previous section sequence num
14. root wz Per Header Object detector E direction Quality direction Status EN dt PROOF Sessions Bax Ray dh dz Bi energy Be energy Quality ielza7idayabsay scratchidanciwy amp energy Status Fh error Matrix Be error MatrixDim position Quality positionStatus a ROOT Files site Ret Xh trigger Number BR triggerTimeNanasec P triggerTimesec recon NoTag 0005773 Physics BP triggerType EN EW En 2 E Event DReadout 1 CalibReadout 1 fe AdSimple 1 2 CON 3 A Registration Sequence 1 E AJobHeader 1 j A RunhHeader 1 Figure 3 2 Example Reconstructed Data The Draw function allows the addition of selection cuts For example we can draw the reconstructed energy for all events where the reconstruction was successful by selecting events with energyStatus 1 and energy lt 15 MeV 1root 2 AdSimple gt Draw energy energyStatus 1 amp amp energy lt 15 Two and three dimensional histograms can be drawn by separating the variables with a colon The third colz argument will use a color scale for a two dimensional histogram Fig 3 3 shows the resulting histograms 24 CHAPTER 3 ANALYSIS BASICS 1root 3 AdSimple gt Draw z sqrt x x y y positionStatus 1 colz energy energyStatus 1 amp amp energy lt 15 z sqrt x x y y positionStatus 1 htem A A AE AAA LOMP 2000 7 300 20000 Entries 105018 E 18000 Mean 2 677 H 4 E RMS 3 287
15. 2 8 1 Particle History As particles are tracked through the simulation information on where they traveled and what they encoun tered can be recorded The particle history is constructed with tracks SimTrack objects and vertices SimVertex objects Conceptually these may mean slightly different things than what one may expect A vertex is a 4 location when something interesting happened This could be an interaction a scatter or a boundary crossing Tracks are then the connection between two vertices Because saving all particle history would often produce unmanageably large results rules are applied by the user to specify some fraction of the total to save This means the track vertex hierarchy is in general truncated 2 8 2 Unobservable Statistics One can also collect statistics on unobservable values such as number of photons created number of photon backscatters and energy deposited in different ADs The sum the square of the sum and the number of times the value is recorded are stored to allow mean and RMS to be calculated The same type of rules that limit the particle histories can be used to control how these statistics are collected 2 8 3 Configuring Truth Information The rules that govern how the particle histories and unobservable statistics are collected are simple logical statements using a C like operators and some predefined variables Configuring Particle Histories The hierarchy of the history is built by s
16. Name of the particle Geant4 name Name of process that created this particle Tracks same as Pro cessName Special matches if the detec tor element specified supports the Track Vertex volume Energy deposited in current step Energy deposited by ionization in current step Quenched energy Valid only for scintillator Step length Step duration 11 4 TRUTH PARAMETERS Name amp Synonyms Step_dAngle dAngle Ex E_weighted_x By E_weighted_y Ez E_weighted_z Et E_weighted_t qEx qE_weighted_x quenched _weighted_x qEy qE weighted y quenched_weighted_y qEz qE_weighted_z quenched_weighted _z qEt qE_weighted_t quenched_weighted_t IsStopping stop End IsStarting start begin StepNumber VolumeChanged NewVolume MaterialChanged NewMaterial ParentPdg AncestorPdg Ancestor ParentIndirection AncestorIndirection GrandParentPdg GrandParent GrandParentIndirection distanceFromLast Vertex Type double double double double double double double double double double double double double double double double double double double Track gt Vertex gt p lt gt Stats gt p lt Description Change in particle angle be fore after this Step degrees Energy weighted global position X Energy weighted global position y Energy weighted global position Z Energy weighted global time Quenched energy weigh
17. Rpc2of4Counts int 11 int RPC 2 out of 4 Trigger Type Events Counts Rpc3of4Counts int 11 int RPC 3 out of 4 Trigger Type Events Counts Table 19 51 DBI Table specification for class GDqTriggerCounts which corresponds to table DqTrigger Counts 51nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqTriggerCounts spec 19 52 DQWPMONITORING 19 52 DqWPMonitoring 239 Table specification source dybgaudi trunk Database DybDbi spec GDqWPMonitoring spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number Detectorld int 11 int Detector ID MuonNhit float double Muon Pmt Nhit MuonNhitErr float double Muon Pmt Nhit Error MuonPESum float double Muon Pmt PE Sum MuonPESumErr float double Muon Pmt PE Sum Error Table 19 52 DBI Table specification for class GDqWPMonitoring which corresponds to table DqWPMoni toring 52nttp dayabay ihnep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqWPMonitoring spec 240 19 53 EnergyPositionCorr CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GEnergyPositionCorr spec 3 docstring name dbtype codetype description code2db NonUniformCorri float double nonuniformity parameter 1 NonUniformCorr2 float double nonuniformity parameter 2 NonUniformCorr3 float double nonuniformity parameter 3 NonUniformCorr4 float doubl
18. Type Null Key Default Extra SEQNO int 11 NO PRI NULL l ROW_COUNTER int 11 NO PRI NULL HvChannelld int 11 YES NULL HvSetting float YES NULL 4 rows in set 0 00 sec name dbtype codetype description code2db HvChannelId int 11 DayaBay HvChannelld Packed HV Channel ID fullPackedData HvSetting float float Requested HV Value Table 19 3 DBI Table specification for class GAdWpHvSetting which corresponds to table AdWpHvSetting 3http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GAdWpHvSetting spec 19 4 ADWPHVTOFEE 191 19 4 AdWpHvToFee Table specification source dybgaudi trunk Database DybDbi spec GAdWpHvToFee spec Map from HV board channel to FEE channel ID mysql amp gt describe AdWpHvToFee Field Type Null Key Default Extra SEQNO int 11 NO PRI NULL ROW_COUNTER int 11 NO PRI NULL HvChannelld int 11 YES NULL FeeChannelId int 11 YES NULL 4 rows in set 0 00 sec name dbtype codetype description code2db HvChanne
19. conventions Hardware h This usage is mirrored in the ctor getters setters of the generated class As these cannot be directly stored into the DB conversions are performed on writing and reading On writing to DB the that can be persisted in the DB 14 code2db defined call is used to convert the specialized type into integers On reading from the DB the one argument codetype ctors are used to convert the persisted integer back into the specialized types name dbtype codetype description code2d FeeChannelld int 11 DayaBay FeeChannelld Front end electronics channel fullPa FeeChannelDesc varchar 30 string String of decribing FEE channel FeeHardwareld int 11 DayaBay FeeHardwareId Identify a physical FEE board id ChanHrdwDesc varchar 30 string String of decribing FEE board position Sensorld int 11 DayaBay DetectorSensor PMT Sensor ID in detector fullPa SensorDesc varchar 30 string String of decribing PMT sensor id PmtHardwareId int 11 DayaBay PmtHardwareId Identify a physical PMT position idQ PmtHrdwDesc varchar 30 string String of decribing PMT position Table 19 55 DBI Table specification for class GFeeCableMap which corresponds to table FeeCableMap 55http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GFeeCableMap spec P y y P y yog y P p sp 19 56 GOODRUNLIST 243 19 56 GoodRunList Table specification source dybgaudi trunk Database D
20. dtLastMu_ms dtNextMu_ms hitAD1 hitAD2 hitAD3 hitAD4 hitIWS hitOWS hitRPC triggerNumber_AD1 trigger Number_AD2 triggerNumber_AD3 triggerNumber_AD4 triggerNumber_IWS triggerNumber_OWS triggerNumber_RPC triggerType_AD1 triggerT ype AD2 triggerType AD3 triggerType_AD4 triggerType_IWS trigger Type_OWS triggerType_RPC dtAD1_ms dtAD2_ms dtAD3_ms dtAD4_ms dtIWS_ms dtOWS_ms dtRPC_ms calib nPESum_AD1 calib nPESum_AD2 calib nPESum_AD3 calib nPESum_AD4 calibnPESum IWS calib nPESum_OWS nRetriggers detectorId_rt nRetriggers dtRetrigger_ms nRetriggers triggerNumber_rt nRetriggers triggerType _rt nRetriggers calib nPESum_rt nRetriggers nSpall detectorId_sp nSpall triggerNumber_sp nSpall triggerType sp nSpall dtSpall_ms nSpall energyStatus_sp nSpall energy sp n Spall positionStatus_sp nSpall x_sp nSpall y sp nSpall z sp nSpall Timestamp of this muon event seconds part Timestamp of this muon event nanoseconds part Time since previous muon event ms Time to next muon event ms Did AD1 have a prompt trigger for this muon Did AD2 have a prompt trigger for this muon Did AD3 have a prompt trigger for this muon Did AD4 have a prompt trigger for this muon Did the Inner water pool have a prompt trigger for this muon Did the Outer water pool have a prompt trigger for this muon Did the RPC have a prompt trigger for this muon Trigger number of prompt AD1 muon trigger i
21. handle_error 12Gaudi XYZPoint localPoint de gt geometry gt toLocal globalPoint 9 4 XML Files Schema conventions 9 5 Transient Detector Store In a subclass of GaudiAlgorithm you can simply access the Transient Detector Store TDS using getDet templated method or the SmartDataPtr smart pointer 1 2 if in a GaudiAlgorithm can use getDet 3DetectorElement de getDet lt DetectorElement gt dd Structure DayaBay 4LVolumex lv getDet lt LVolume gt dd Geometry AD 1vOIL 5 6 or if not in a GaudiAlgorithm do it more directly 7IDataProviderSvcx detSvc 0 8StatusCode sc service DetectorDataSvc detSvc true gif sc isFailure handle_error 10 11SmartDataPtr lt IDetectorElement gt topDE detSvc dd Structure DayaBay 12if topDE return handle_error 13 14 use topD 15 16 detSvc gt release E 9 6 Configuring the Detector Description The detector description is automatically configured for the user in nuwa py 9 7 PMT Lookups Information about PMTs can be looked up using the PmtGeomInfoSvc You can do the lookup using one of these types of keys Structure path which is the dd Structure path of the PMT PMT id the PMT id that encodes what PMT in what detector at what site the PMT is DetectorElement the pointer to the DetectorElement that embodies the PMT The resulting PmtGeomInfo object gives access to global and local PMT positions and di
22. name dbtype codetype description code2db PositionR float float r position of source mm PositionZ float float z position of source mm PositionPhi float float phi position of source degrees RunNo int 11 int run number associated with this position Table 19 59 DBI Table specification for class GMcsPos which corresponds to table McsPos 59nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GMcsPos spec 19 60 PHYSAD 247 19 60 PhysAd Table specification source dybgaudi trunk Database DybDbi spec GPhysAd spec This table can be read written using py class DybDbi AdLogicalPhysical adapted from Dan Zhimin email 2011 01 17 There are two ways to identify an AD in the experiment Location SAB AD1 FAR AD4 Physical ID AD1 AD2 AD8 rubric Convention references Convention Reference DCS docdb 3198 DAQ docdb 3442 page 6 The Offline convention can be found from dybgaudi DataModel Conventions Conventions Site h dybgaudi DataModel Conventions Conventions Detectorld h Here is a summary of the Location names IDs that each system uses rubric Site Name and ID DCS DAQ Offline DAQ_ID Offline_ID DBNS DBN DayaBay 0x10 0x01 LANS LAN LingAo 0x20 0x02 FARS FAR Far 0x30 0x04 MIDS MID Mid 0x08 A Aberdeen 0x10 SAB SAB SAB 0x60 0x20 PMTBenchTest 0x40 LSH rubric Detector MainSys Name and ID 60http
23. optical UseScintillation False 3 optical CerenPhotonScaleWeight 3 5 4 optical UseCerenkov False 5 optical ScintPhotonScaleWeight 3 5 6 7 from DetSimProc DetSimProcConf import DetSimProc 8 dsp DetSimProc 9 dsp ThisStageName Detector 20 dsp LowerStageName Kinematic 21 tdsp DutputLevel 2 22 self stage_cfg DetectorSequence Members append dsp 23 24 ds historian trackSelection pdg 2112 vertexSelection pdg 2112 25 return The above example shows how detector simulation part is configured Usually DetSim works in a normal gaudi manner here the option usepushalgs False will stop adding its to top algorithm list The lines assigning stage names lower stage and this stage tells where the input data is from and what the current stage is Then this DetSimProc algorithm was added to the stage tool Detector In the rest the physics list is customized and both cerenkov and scintillation light are pre scaled From this example and the above one for generator it is already very obvious that Fifteen package just uses the simulation tools as others It doesn t create another set of tools All setting of them can be directly moved to here Next we will see how electronic simulation is set up def configureElectronic self gt gt Configure the Electronics stage import ElecSim es ElecSim Configure use_push_algs False from ElecSimProc ElecSimProcConf import ElecSimProc esp ElecSimProc
24. tinyint 4 YES NULL col tinyint 4 YES NULL ring tinyint 4 YES NULL voltage decimal 6 2 YES NULL pw tinyint 4 YES NULL 4 7 rows in set 0 07 sec name dbtype codetype description code2db Ladder tinyint 4 int PMT ladder Column tinyint 4 int PMT column Ring tinyint 4 int PMT ring Voltage float float PMT Voltage Pw tinyint 4 int PMT Power ON OFF Table 19 36 DBI Table specification for class GDcsPmtHv which corresponds to table DesPmtHv 36http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDcsPmtHv spec 224 CHAPTER 19 DATABASE TABLES 19 37 DcsRpcHv Table specification source dybgaudi trunk Database DybDbi spec GDcsRpcHv spec PMT High Voltage monitoring table mysql amp gt describe DcsRpcHv 4 4 4 4 4 Field Type Null Key Default Extra SEQNO int 11 NO PRI NULL ROW_COUNTER int 11 NO PRI NULL LocationId char 3 YES NULL VoltagePos float YES NULL l VoltageNeg float YES NULL name dbtype codetype description code2db LocationId char 3 string Location ID VoltagePos flo
25. triggerNumber multiplicity triggerType multiplicity t_s multiplicity tns multiplicity dt_ns multiplicity energyStatus multiplicity multiplicity ositionStatus multiplicity multiplicity multiplicity multiplicity mult mult 1 2 mult mult 1 2 dtLastAD1_ms multiplicity dtLastAD2_ms multiplicity dtLastIWS_ms multiplicity dtLastOWS_ms multiplicity xD Oo SAN dtLast_ADMuon_ms dtLast_ADShower_ms ELast_ADShower_pe calib_nHit multiplicity calib nPEMedian multiplicity calib nPERMS multiplicity calib nPESum multiplicity calib nPulseMedian multiplicity calib_nPulseRMS multiplicity calib_nPulseSum multiplicity calib_tEarliest multiplicity calib_tLatest multiplicity calib tMean multiplicity calib_tMedian multiplicity calib_tRMS multiplicity gen_count multiplicity gen e multiplicity gen_execNumber multiplicity gen_pid multiplicity gen_px multiplicity gen_py multiplicity gen pz multiplicity gen type multiplicity gen lastDaughterPid multiplicity Number of AD events within coincidence window Trigger number of event Trigger type of event Timestamp of event seconds part Timestamp of event nanoseconds part Time relative to first event in multiplet Status of AD energy reconstruction Reconstructed energy MeV Status of AD position reconstruction AD Reconstructed X position mm AD Reconstructed Y position mm AD Reconstructed Z position mm Promp
26. usr bin env python a Configure the full chain of simulation from kinematics to readouts and with multiple kinematics types mixed together usage nuwa py n50 o fifteen root m FullChainSimple T SingleLoader gt log T Optional stages are Kinematic Detector Electronic TrigRead or SingleLoader More options are available like w wall clock starting time F time format s seed for IBD generator ence es Aside This is a copy of MDCO9b runIBD15 FullChain however with less options less generators configured and less truth info saved FLLI ta 15 2 FIFTEEN 139 This is the first part of this script In the first line it declares the running environment What follows quoted by are a brief introduction of this script and usage of this script It tells that this script will configure a full chain of simulation It also includes a command line which can be used right away to start Before looking into the script it also explains what arguments can be set and what are their options These arguments will explained later Next I will follow the order of how this script is going to be executed in nuwa Then it will bring us to the end of the script 1def configure argv 2 cfc ConfigureFullChain argv 3 cfc configure 4 return 5 6if __name__ __main__ 7 configure 8 pass A python script is executable in a shell environment when it has if __name__ __main__ Like this FullChai
27. 1 AD PMTs The primary PMTs in an AD are numbered sequentially as well as by which ring and column they are in Rings count from 1 to 8 starting at the bottom and going upwards Columns count from 1 to 24 starting at the column just above the X axis and continuing counter clockwise if looking down at the AD The sequential ID number can be calculated by column 24 ring 1 1We may create a separate PMT logical volume for the AD and one or two for the Pool to handle differences in PMT models actually in use 2Here the X axis points to the exit of the hall 9 3 COORDINATE SYSTEM 93 Besides the 192 primary PMTs there are 6 calibration PMTs Their ID numbers are assigned 193 198 as 192 1 top target viewing 2 bottom target viewing top gamma catcher viewing bottom gamma catcher viewing top mineral oil viewing Ss nS See g bottom mineral oil viewing FIXME Add figures showing PMT row and column counts orientation of ADs in Pool AD numbers coordinate system w r t pool 9 2 2 Pool PMTs Pool PMT counting coordinate system w r t hall 9 2 3 RPC RPC sensor id convention Coordinate system w r t hall 9 3 Coordinate System As described above every mother volume provides a coordinate system with which to place daughters For human consumption there are three canonical coordinate system conventions They are Global Th global coordinate system has its origin at the mid site with X pointing East Y p
28. 83 Detector Description 91 ul Siete oe we ek he BR a OM a ee SE Be ee Gon ee SR we a a 91 o a i s icy a a a oh ee ee eh eee SEL Bee ee ele a ante See ee 92 Oo Coordinate Syste a a aa ge a ba eB ee a ew po eae e e 93 OA Si Files s ea pt pe Rae be eee REE SAEED ELEM a ERE A ww 94 OS Transient Detector Store cee pk eh e Dae ee RK Dee RE ES 4 94 9 6 Configuring the Detector Description lt s se 425486 BY Yee ee eee Pewee ed 94 ON PMT Lookups aa a ee eS Ye hee MoO ee Tee Bea eawa es 94 a ee ee deers gang ee BE xe at Bt BD he a ae ee ee Sree amp amp S 94 Kinematic Generators 97 ULT trocear BRR Hee eo x 97 10 2 Generator OU ss a a A Ske a AAA EA RR e a 97 113 Generator ToS s ai aa dd ee eee be eh de wees oa ede 97 10 4 Generator Packases seas le ai Gf ee ee EE eRe ew A ea 97 10 5 Types or Gen Tools socias a ee Re we aes weet eee ee GS 97 LE ROMS RIOR Sa eee AA A A eee DEE OE BLS 98 TT HOR o A eo Bae Be et Gh a A es ee ee a Se eee ee Sa 101 Detector Simulation 105 TLI A NN 106 112 Comeunas DoS osa A A aa 106 ULA Trata MOrmRdOn 22 ess dais ara dd o 107 MA Tath Ets os ra cn di a A ARA AA ae a e ed dd 117 Electronics Simulation 121 Contents 3 TEN TO PORC ic he de a a A AAA E a A aS 121 PO IRC ecos a e RR AAA OE Ha 121 O A EY ART a DAA A a Be AA a a 121 124 Simulation Consta oe a ee das peda a Bde ES 123 13 Trigger Simulation 127 LEE Mirout eea a e a a A a ee 127 AIR OA y e a a ee ae ss AAA ES de Rd Ge po we 127 Tas Curent USO
29. A a G 194 198 CORB PREG oeu iaa RR o DAA E A os 195 19 9 CallbEsespecieanp o dema Gee ee bee ee ee eee eR ee ee oa es 196 IG DOCS ADP Furl ees a kK KARR DES RG ORES Ea RE Eu 197 19 11CalibPmtHighGain coa ek a a OR EA ERA RRR A 198 TS 12CalbPmtiiehtsanPake o be ee DE OO ee ee eee Oe 199 Contents 10 taCalbPatilegG abarca 2 ke ae he RD Ra eee ee RRR eS 200 IS 14CalibPimitlowGam oca ee EEO eee eR eH ie Y 201 Na age Qk ao a GRE be Sob 46 ba we AAN 202 Ea AE 203 a il TO 5h tie ee ee NA 204 1S ane ih Pie a ek ee E es i ee ee Pe 205 TE TC ADS DOSPES ce a a ee kk eh oe SU a ae ee ee eee eR ewe Oe a 206 E IE 207 E IA 208 TOO CoomdinaleBicaci f lt sso reru A eee A a a A ea 209 19 ZiDagCalibRunido ocios cai a a Ee ed eS 210 10a Waqhaw Daal Mee a a RR SA RES eR OD EE re ee hee 211 a AAA 212 1920D Cul Detector ose ea e a AR A A A ER REE 213 19 2 DataQuest ORAL 6k ee ra A a be 4 214 LE 2o ON sai RR o SW a ae ee ee ee eR we ed a 215 TODAS alte 2c hak dar Ede ee eee heheh a we ae 64 oP 216 19 UDstaGually Eger ease SS a ea A RR Ee Dw GE SR Boa G Y 217 INSIDE ACP o kA a RR ORE RE A Rw aa 218 TS Scar Venn i ee ao ida a eR we a Dw Oe ee PE de dea a 219 1933 Des Ad W POE nica A OHS AA AAA CARDED ES DREDGE HS 220 19 34DesAd W py hunted o c 4 640045 e odo dd ba dd A a Ge eS 221 A e AA E 222 Ed EE 223 IA DESENCADENA oe a 224 IMD prue 6 6 ocd eae G4 ee hd kee eee bebe dd wea 64 of y 225 PORE dona OR RAR eee heh Bo Kae he he ee OR
30. C but uses this alternate approach The following lines shows this in practice Create friendly version of data from CalibStats std string mainEntriesName multiplicity std vector lt string gt calibVarNames variable names to copy from CalibStats calibVarNames push_back MaxQ calibVarNames push_back NominalCharge std string indexMajorName triggerNumber std string indexMinorName context mDetId TTree calibStatsFriendlyT makeFriendTree amp adCoincT amp calibStatsT mainEntriesName calibVarNames indexMajorName indexMinorName if calibStatsFriendlyT std cout lt lt Failed to create friendly tree lt lt std endl return Add new friendly tree to coincidence tree adCoincT AddFriend calibStatsFriendlyT calibStats Once this friendly tree has been generated we can use TTree Draw with the CalibStats variables Fill histograms AD 1 adCoincT Draw calibStats NominalCharge e e gt gt chargeVsEnergyAD1H context mDetld 1 amp amp energyStatus 1 amp amp e gt 0 colz AD 2 adCoincT Draw calibStats NominalCharge e e gt gt chargeVsEnergyAD2H context mDetld 2 amp amp energyStatus 1 amp amp e gt 0 colz The reformatted CalibStats data is available in the newly created tree calibStatsFriendlyT which is dynamically created and kept in memory Once you close your ROOT session this tree will be deleted If you wish to keep thi
31. CHAPTER 17 DATABASE 17 7 ASCII Flat Files and Catalogues 17 7 1 Overview ASCII flat files and catalogues provide a convenient way to temporarily augment a database with additional tables under your control A flat file is a file that contains in human readable form the definition of a table and its data It can be made an entry in a cascade and by placing before other entries allows you to effectively modify the database just for the duration of a single job As has already been explained for each Main Data Table there is also an auxiliary Context Range Table so you need 2 entries in the cascade for each table you want to introduce The problem with this scheme is that if introducing a number of tables the cascade could get rather large To avoid this catalogues are used A catalogue is actually nothing more that a special ASCII flat file but each row of its data is a URLs for another ASCII flat file that becomes part of the same cascade entry In this way a single cascade entry can consist of an arbitrary number of files 17 7 2 Flat Files An ASCII flat file defines a single database table Format The format is sometimes referred to as Comma Separated Value CSV Each line in the file corresponds to a row in the table As you might suspect values are separated by commas although you can add additional white space tabs and spaces to improve readability but heed the caution in section 17 7 4 The first row is special it contains
32. CHAPTER 8 DATA I O if m_perSimHeader return StatusCode SUCCESS RootIOBaseCnvx other this gt otherConverter SimHeader classID if other return StatusCode FAILURE const RootIOBaseObject base other gt getBaseDbject if base return StatusCode FAILURE const PerSimHeaderx pgh dynamic_cast lt const PerSimHeader gt base if pgh return StatusCode FAILURE m_perSimHeader pgh return StatusCode SUCCESS A few points e This done in initialize as the pointer to the persistent object we get in the end will not change throughout the life of the job so it can be cached by the converter e It is important to call the base class s initialize method as on line 7 e Next get the other converter is looked up by class ID number on line 12 e Its persistent object as a RootIOBase0bj is found and dynamic_cast to the concrete class on lines 15 and 18 e Finally it is stored in a data member for later use during conversion at line 21 8 6 6 CMT requirements File The CMT requirements file needs lpac e Usual list of use lines e Define the headers and linker library for the public data classes e Define the component library e Define the dictionary for the public data classes Here is the example for PerGenEvent kage PerGenEvent 2version vO 3 4use 5use 6use 7use guse guse 0 6 Context Vx DataModel BaseEvent vx DataModel GenEvent vx DataModel ROOT vx LCG_Int
33. GDataQualityRpc spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number RpcSensorld int DayaBay RpcSensor ID of RPC sensor for layer fullPackedData Efficiency float double Efficiency of one RPC layer EfficiencyErr float double Efficiency error of one RPC layer NoiseRate float double Noise rate of one RPC layer NoiseRateErr float double Noise rate error of one RPC layer Table 19 29 DBI Table specification for class GDataQualityRpc which corresponds to table DataQualityRpc 29http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDataQualityRpc spec 19 30 DATAQUALITYTRIGGER 19 30 DataQualityTrigger Table specification source dybgaudi trunk Database DybDbi spec GDataQualityTrigger spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number Detectorld int 11 int Detector ID TrigRate float double Trigger Rate FlasherRate float double Flasher Rate BlockTrigFrac float double Blocked Trigger Fraction Table 19 30 DBI Table specification for class GDataQuality Trigger which corresponds to table DataQual ity Trigger 30http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDataQualityTrigger spec 218 CHAPTER 19 DATABASE TABLES 19 31 DcsAdPmtHv Table specification source dybgaudi trunk Database DybDbi spec GDesAdPmtHv spec
34. GenTools helpers described above is 1from GenTools Helpers import Gun 2gunner Gun 3 4import GaudiKernel System0fUnits as units 5gunner timerator LifeTime int 60 units second 6 7import GenTools 8gt GenTools Configure gun Particle Gun helper gunner 9gt helper positioner Position 0 0 0 In the first two lines a Gun helper class is imported and constructed with defaults This helper will set up the tools needed to implement a particle gun based generator It chooses a bunch of defaults such as particle type momentum etc which you probably don t want so you can change them later For example the mean life time is set in line 5 Finally the package is configured and this helper is passed in The configuration creates a GtGenerator algorithm that will drive the GenTools implementing the gun based kinematics generation After the Configure object is made it can be used to make more configuration changes This specific example was for GenTools Other package will do different things that make sense for them To learn what each package does you can read the Configure and or helper code or you can read its inlined documentation via the pydoc program Some related examples of this latter method 1shell gt pydoc GenTools Helpers 2Help on module GenTools Helpers in GenTools 3 4NAME 5 GenTools Helpers 6 7FILE 8 path to NuWa trunk dybgaudi InstallArea python GenTools Helpers py 9 ODESCRIPTION 1 Sev
35. To get started copy the example template Python algorithm to your local directory 1shell gt mkdir mywork 2shell gt cd mywork 3shell gt cp QUICKSTARTROOT python Quickstart Template py myAlg py Alternatively you can copy PrintRawData py PrintCalibData py or PrintReconData py if you want to specifically process the readout calibrated or reconstructed data Each of these files is a combination of a Python algorithm and a nuwa Python Job Module To run this module and algorithm you can call it in the following way 1shell gt nuwa py n 1 m myAlg recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root Inside this file you can find a Python algorithm It is a Python class that defines three key functions e initialize Called once at job start e execute Called once for each event e finalize Called once at job end You should edit these functions so that the algorithm will do the task you want There are a few common tasks for algorithms One is to print to the screen some data from the event 1def execute self 2 evt self evtSvc 3 reconHdr evt Event Rec RecHeader 4 print Energy MeV reconHdr recResult energy units MeV Another common task is to histogram some data from the event idef initialize self 2 A Define the histogram 3 self stats file1 myhists energy TH1F energy 4 Reconstructed energy for each trigger 5 100 0 10 6 7def execute self 8 evt self evtSv
36. a pointer to a single SimParticleHistory object A SimParticleHistory object contains a list of primary tracks which act as entrance points to the history for those who wish to navigate from first causes to final state Alternatively you may instead start with SimHit objects which each contain a SimTrackReference The references point back to the particles that created 110 Track 2 Track 3 f Track 3 CHAPTER 11 DETECTOR SIMULATION Figure 11 4 History Pruning The first figure shows a hypothetical case before pruning The second case shows the links after pruning Track 2 The dotted lines indicate that the data objects record that the links are indirect 11 3 TRUTH INFORMATION 111 the hit e g optical photons in the case of a PMT or the ancestor of that particle if its been pruned from the output Creation Rules The Historian module makes use of the BOOST Spirit parser to build rules to select whether particles get saved as tracks and vertices The user provides two selection strings one for vertices and one for tracks At initialization these strings are parsed to create a set of fast Rule objects that are used to quickly and efficiently select whether candidate G4Tracks and G4StepPoints get turned into SimTracks or SimVertices respectively The selection strings describe the criteria neccessary for acceptance not for rejection Thus the default strings are both none indicating that no tracks or
37. almost certainly contain some rows in common unless all component aggregates have context ranges that end on the boundary you are crossing See the next section for a way to detect changes to data using the DbiResult GetID method Simple Optimisation The first and most important level of optimisation is done within the Databaselnterface itself Each time it retrieves data from the database it places the data in an internal cache This is then checked during subsequent queries and reused as appropriate So the first request for a large table of calibration constants may require a lot of I O However the constants may remain valid for an entire job and in which case there is no further I O for this table Although satisfying repeat requests for the same data is quick it still requires the location of the appro priate cache and then a search through it looking for a result that it is suitable for the current event There are situations when even this overhead can be a burden when processing many rows in a single event Take for example the procedure of applying calibration Here every digitization needs to be calibrated using its corresponding row in the database The naive way to do this would be to loop over the digits instantiating a DbiResultPtr for each extracting the appropriate row and applying the calibration However it would be far more efficient to create a little calibration object something like this 160 CHAPTER 17 DATABASE cla
38. assigned Every database that is a source of data has a GlobalSeqNo table that is used to generate sequence numbers Each time one is allocated the count is incremented in the table For each database the table operates in a different range of numbers hence ensuring that all are unique dbmjob moves data in Validity Packets i e a single row in the auxiliary table and all its associated data rows The insertion date and SeqNo on the auxiliary row allow dbmjob to support incremental updates and avoid data duplication All this implies a very important restriction on dbmjob dbmjob can only distribute Dbi compliant database tables i e ones that come in pairs the main data table and an auxiliary validity range table 18 2 Building and Running dbmjob 18 2 1 Building The DatabaseMaintenance package is a standard Framework package and the dbmjob application is build in the standard way cd SRT_PUBLIC_CONTEXT gmake DatabaseMaintenance all 18 2 2 Running Before running a Database cascade must be defined using the ENV_TSQL_ variables as described in Alternatively use the d u and p switches that are also described there or use the ENV_TSQL_UPDATE_ e g ENV_TSQL_UPDATE_USER set of variables Where they exist they will take precedence over the equivalent ENV_TSQL_ variable This allows for a safe read only setting of the ENV_TSQL_ variables that can be shared by a group with just the local database manager also having th
39. ca a ein ll de de dd a hae e e e dd ee ee BEERS 128 13 4 Adding a mew Trigger 002cc cooooccrrrraaa coc 129 14 Readout 131 TAD Marois ocio o eo A EEE a DE Se Be 131 112 Resdomtteader lt i eh oe ee RRR HS A OE Re SRS BES RE 2 AE 131 14 3 Simkeadombleader coco ee hae a y EE a eh we Be de gee ee Bae 132 14 4 Readout Algorithms 0 2665 5 bee EEE a 132 dae Resdaut Tople a a A See A A ee eR eS 133 15 Simulation Processing Models 135 ThA Introduce a a A as ee PE ORR REE ad 4 4 135 VEA POE oe ee kee ela aa AG SRR 8 6 Dae AAA ee A OG SAREE oe x 135 16 Reconstruction 145 17 Database 147 ITA Database ASES o A Se A ee OES ES Bae eo ew a 147 a o IEEE 147 173 AUN ua a A A AR A AA A e amp 153 ITA Accessing Existing Tables oso ica dd REE 156 Vid Creatine New Tables os a a a A E RR ew a 163 17 5 Filing Tables oes ogar e ra a a A 169 17 7 ASCH Flat Files and Catalogues o occocuscors ss ee eee ew Y 176 TT DAG SOE OE oaoaraa hy A RE ee Sk a BR a a ee OR eS 178 IO Performante 2 ke bebe eee ee eee EDR a ee ae Ge ee 180 18 Database Maintanence 183 131 Ue A eR a A ee on Be A OEE ww BE AK 183 182 Building and Rimming dhmjeb ecc ae ee PR Se es weed ere eG 184 19 Database Tables 187 TO Dee ok a De ee PR ERE RES Be HER BAS Gene Bee oS 188 19 2 Ra Were ocak ke RA ee WADA RRR RAR PARRA Re 189 11 3 PW pac Cir ia a a OO ee PE bd eS 190 19 4 RaW ob TORee cuco a aa AAA RR a AOR AA a e EES 191 1p Cableado dd dl adds e 192 ae o AAN 193 17 CaP eee oct ra a E A
40. converter classes 8 3 Packages The I O mechanism is provided by the packages in the Root 10 area of the repository The primary package is RootI0Svc which provides the low level Gaudi classes In particular it provides an event selector for navigating input as well as a conversion service to facilitate converting between transient and persistent representations It also provides the file and stream manipulation classes and the base classes for the data converters The concrete converters and persistent data classes are found in packages with a prefix Per under RootI0 There is a one to one correspondence between these packages and those in DataModel holding the transient data classes The RootI0OSvc is generic in the sense that it does not enforce any policy regarding how data is sent through I O In order to support Daya Bay s unique needs there are additional classes in DybSvc DybI0 In particular DybEvtSelector and DybStorageSvc The first enforces the policy that the next event means to advance to the next RegistrationSequence and read in the objects that it references The second also enforces this same policy but for the output 8 4 I O Related Job Configuration I O related configuration is handled by nuwa py You can set the input and output files on the command line See section 6 5 6 for details 8 5 How the I O Subsystem Works This section describes how the bits flow from memory to file and back again It isn t stri
41. direction 0 outward 1 inward 00 30 030uNe o a fF U Ne 16 17 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 3 5 CHEAT SHEETS 51 Calibrated data in NuWa Here is a cheat sheet for processing calibrated data in Python These lines can be used in the execute function of a Python algorithm evt self evtSvc Access the Calib Readout Header This is a container for calibrated data calibHdr evt Event CalibReadout CalibReadoutHeader if calibHdr None self error Failed to get current calib readout header return FAILURE Access the Readout This is the calibrated data from one trigger calibReadout calibHdr calibReadout if calibReadout None self error Failed to get calibrated readout from header return FAILURE Get the detector ID for this trigger detector calibReadout detector detector detName Trigger Type This is an integer of the type for this trigger calibReadout triggerType Trigger Number A count of the trigger according to the DAQ calibReadout triggerNumber Trigger Time Absolute time of trigger for this calibrated data triggerTime calibReadout triggerTime A Loop over each channel data in this trigger for channel in calibReadout channelReadout sensorld channel pmtSensorId if detector isAD pmtId AdPmtSensor sensorId fullPackedData pmtId detName
42. extended ones break all the rules and have to pay a price 17 4 4 Error Handling Response to Errors All DbiResultPtr constructors except the default constructor have a optional argument Dbi AbortTest abortTest Dbi kTableMissing Left at its default value any query that attempts to access a non existent table will abort the job The other values that can be supplied are kDisabled Never abort This value is used for the default constructor kDataMissing Abort if the query returns no data Use this option with care and only if further processing is impossible Currently aborting means just that there is no graceful shut down and saving of existing results You have been warned Error Logging Errors from the database are recorded in a DbiExceptionLog There is a global version of that records all errors The contents can be printed as follows ttinclude DatabaseInterface DbiExceptionLog h LOGINFO mylog lt lt Contents of the Global Exception Log An lt lt DbiExceptionLog GetGELog 17 5 CREATING NEW TABLES 163 Query results are held in a DbiResult and each of these also holds a DbiExceptionLog of the errors if any recorded when the query was made If myResPtr is a DbiResultPtr then to check and print associated errors const DbiExceptionLog amp el myResPtr GetResult gt GetExceptionLog if el Size 0 LOGINFO mylog lt lt No errors found lt lt endl else LOGINFO mylog lt lt Fol
43. in SPE Mean ADC value low gain Table 19 14 DBI Table specification for class GCalibPmtLowGain which corresponds to table CalibPmt LowGain lMhttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibPmtLowGain spec 202 19 15 CalibPmtPedBias CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GCalibPmtPedBias spec docstring name dbtype codetype description Sensorld int 11 DayaBay DetectorSensor packed sensor ID of this PMT Amp_b double double y intercept of ADC dependence of Gaussian amplitude Amp_m double double slope of ADC dependence of Gaussian amplitude Mean_amp double double amplitude of Gaussian portion of GausLine for pulses Mean_mean double double mean of Gaussian portion of GausLine for pulsek 39 s Mean_sigma double double sigma of Gaussian portion of GausLine for pulsesk 39 Mean_offset double double offset of Gaussian portion of GausLine for pulsesk 39 Mean_b double double y intercept of linear portion of GausLine for pulses amp Mean_m double double slope of linear portion of GausLine for the pulsesk 3 Sigma_amp double double amplitude of Gaussian portion of GausLine for pulses amp Sigma_mean double double mean of Gaussian portion of GausLine for pulsek 39 s Sigma_sigma double double sigma of Gaussian portion of GausLine for pulsesk 39 Sigma_offset double double offset of Gaussian portion of GausLine for pulsesk 39 Sigma_b dou
44. is effectively a slice of the underlying database table Each row of the results table is an object the type of which is table specific These table row objects give access to the data from one row but can hide the way the database table is organised So changes to the physical layout of a database table should only effect its table row object not the end users of the data Note that a single request only ever accesses a single table the interface does not support retrieval of data from multiple database tables simultaneously If the request for data fails for some reason then the resulting table will be empty otherwise it will have a single row for Simple organisation and more than one row for Compound and Aggregated The user can ask how many rows the table has and can directly access any of them The physical ordering of the rows in the table reflects the way the data was originally written so for Aggregated data the ordering is not optimised for retrieval To deal with this each table row object can declare a natural index independent of its physical position and this natural index can be used to retrieve data 17 2 CONCEPTS 149 17 2 4 A Cascade of Databases The Databaselnterface can access data for more than one database During initialisation it is given a list of database URLs The list order reflects priority the interface first looks for data in the first database in the list but if that fails tries the others in turn until all h
45. low gain ADC channel TimeOffset float double Relative transit time offset TimeSpread float double Transit time spread Efficiency float double Absolute efficiency PrePulseProb float double Probability of prepulsing AfterPulseProb float double Probability of afterpulsing DarkRate float double Dark Rate Table 19 16 DBI Table specification for class GCalibPmtSpec which corresponds to table CalibPmtSpec 16nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibPmtSpec spec 204 19 17 CalibPmtTimOff CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GCalibPmtTimOff spec docstring name dbtype codetype description code2db Channelld int 11 DayaBay FeeChannelld unique id of the channel connected to this pmt fullPac Offset float double Time offset ns OffsetError float double Time offset error ns Table 19 17 DBI Table specification for class GCalibPmtTimOff which corresponds to table CalibPmtTi mOff lThttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibPmtTimOff spec 19 18 CALIBPMTTIMING 205 19 18 CalibPmtTiming Table specification source dybgaudi trunk Database DybDbi spec GCalibPmt Timing spec docstring name dbtype codetype description code2d ChannelId int 11 DayaBay FeeChannelId unique id of the channel connected to this pmt fullPa Status tinyint 4 int Status of thi
46. of parent class to its converter The rest of this section walks through writing a converter using the GenHeaderCnv as an example Converter Header File First the header file l include RootIOSvc RootI0TypedCnv h 2 include PerGenEvent PerGenHeader h 3 include Event GenHeader h 4 5class GenHeaderCnv public RootI0TypedCnv lt PerGenHeader 6 DayaBay GenHeader gt The converter inherits from a base class that is templated on the persistent and transient class types This base class hides away much of Gaudi the machinery Next some required Gaudi boilerplate 1public 2 static const CLID amp classID 3 return DayaBay CLID_GenHeader 1 5 6 GenHeaderCnv ISvcLocator svc 7 virtual GenHeaderCnv The transient class ID number is made available and constructors and destructors are defined Next the initial copy methods are defined Note that they take the same types as given in the templated base class 86 CHAPTER 8 DATA I O 1StatusCode PerToTran const PerGenHeader amp per_obj 2 DayaBay GenHeader z tran_obj 3 4StatusCode TranToPer const DayaBay GenHeader amp per_obj 5 PerGenHeader amp tran_obj Finally the fill methods can be defined These are only needed if your classes make reference to objects that are not subobjects of your header class 1 StatusCode fillRepRefs IOpaqueAddress addr DataObject dobj 2 StatusCode fill0ObjRefs IOpaqueAddress addr DataObject dobj F
47. one will want to do to write analysis It includes accessing the data making histograms reading writing files Look at the Python modules under python DivingIn Most provide instructions on how to run them in comments at the top of the file There is a companion presentation available as DocDB 3131 2http dayabay ihep ac cn cgi bin DocDB ShowDocument docid 3131 Chapter 8 Data I O Gaudi clearly separates transient data representations in memory from those that persist on disk The transient representations are described in the previous section Here the persistency mechanism is described from the point of view of configuring jobs to read and write input output I O files and how to extend it to new data 8 1 Goal The goal of the I O subsystem is to persist or preserve the state of the event store memory beyond the life time of the job that produced it and to allow this state to be restored to memory in subsequent jobs As a consequence any algorithms that operate on any particular state of memory should not depend nor even be able to recognize that this state was restored from persistent files or was generated on the fly by other upstream algorithms Another consequence of this is that users should not need to understand much about the file I O subsys tem except basics such as deciding what to name the files This is described in the section on configuration below Of course experts who want to add new data types to the
48. overhead as typically there are several major database reads at the start of a production job after which little or no further database I O occurs However if you require the connection to remain open throughout the job then you can force any entry in the cascade to be permanent The following code sets entry 0 in the cascade to have a permanent connection include DatabaseInterface DbiCascader h ttinclude DatabaseInterface DbiTableProxyRegistry h Ask the singleton DbiTableProxyRegistry for the DbiCascader const DbiCascader amp cascader DbiTableProxyRegistry Instance GetCascader Request that entry O is permanently open cascader SetPermanent 0 Note that this won t open the connection but will prevent it from closing after its next use If you want all connections to remain open this can be set through the configuration parameter Make ConnectionsPermanent See section 17 3 2 17 9 PERFORMANCE 181 17 9 2 Truncated Validity Ranges Standard context specific queries are first trimmed to a time window to limit the number of Vld records that have to be analysed Having established the best data a further 4 calls to query the Vld table is made to determine the full validity For data with long validities these extra calls are worthwhile as they can significantly increase the lifetime of the results However there are two cases where these should not be use e For data that changes at high frequency minutes or hou
49. parent to this track int parentParticle const Reference to the parent or ancestor of this track const DayaBay SimTrackReference amp ancestorTrack const Reference to the parent or ancestor of this track const DayaBay SimVertexReference amp ancestorVertex const Pointer to the ancestor primary kinematics particle const HepMC GenParticlex primaryParticle const Pointers to the vertices along this track Not owned const vertex_list amp vertices const Get number of unrecordeds for given pdg type unsigned int unrecordedDescendants int pdg const Figure 11 2 SimVertex Accessors A list of accessible data from the SimVertex object 1class SimVertex e U N 003 O sg const const double Gaudi double Gaudi double double const SimTrackReference amp track const SimProcess amp process const time const XYZPoint position const totalEnergy const XYZVector momentum const mass const Approximate from 4 momentum kineticEnergy const Approximate from 4 momentun std vector lt SimTrackReference gt amp secondaries const 11 3 TRUTH INFORMATION 109 Figure 11 3 Relationship between SimTrack and SimVertex Track 1 represents a primary SimTrack and Track 2 a secondary particle created at the end of Track 1s first step Thus the position time volume and process may be the same for the two highlighted vertices Tr
50. pmtId ring pmtId column elif detector isWaterShield pmtId PoolPmtSensor sensorld fullPackedData pmtId detName pmtId wallNumber pmtId wallSpot pmtId inwardFacing Calibrated hit data for this channel for hitIdx in range channel size Hit time is in units of ns and is relative to trigger time hitTime channel time hitldx A Hit charge is in units of photoelectrons hitCharge channel charge hitIdx 3 5 10 Calibrated Statistics Data Calibrated statistics data in ROOT The following table summarizes the calibrated statistics data for each event visible directly in ROOT Array items have their length given in the brackets i e name length ROOT will automatically draw all entries in the array given the array name See the ROOT User s Guide for more details on working with Trees http root cern ch download doc 12Trees pdf 52 CHAPTER 3 ANALYSIS BASICS ROOT Variable Description dtLastAD1_ms dtLastAD2_ms dtLastIWS_ms dtLastOWS_ms dtLast_A DMuon_ms dtLast_A DShower_ms ELast_ADShower_pe nHit nPEMedian nPERMS nPESum nPulseMedian nPulseRMS nPulseSum tEarliest tLatest tMean tMedian tRMS charge_sum_flasher_max time_PSD time_PSD1 time_PSD_local_RMS Ql Q2 Q3 flasher_flag EarlyCharge LateCharge NominalCharge MaxQ maxqRing maxqCol QuadrantQ 1 QuadrantQ2 QuadrantQ3 QuadrantQ4 Quadrant MainPeakRMS SecondPeakRMS PeakRMS RingKurtosis ColumnKurtos
51. skipped and the generation of spallation background can be fully controled and fully simulated by Geant4 10 7 2 Generation Mechanism Firstly it starts from a muon track with initial vertex and momentum The intersections of the muon track with each sub detectors surface and track lengths in each segment are calculated Low energy muon could stop in detector according to a calculation based on an average dE dx According to its track length in water and whether it crossed RPC and user configuration it will determine whether this track is going to be triggered Spallation neutron and cosmogenic background generation rate is usually a function of muon s energy track length and material density According to a few empirical formulas from early test beam and neutrino experiments spallation neutron and or radioactive isotopes are generated around the muon track Because water is not sensitive to radioactive isotopes and their initial momentum is very low they are only generated in AD Muon is always tagged as don t need simulation by a trick in Geant4 However neutron and radioactive isotope are left for full Geant4 simulation 102 CHAPTER 10 KINEMATIC GENERATORS 10 7 3 Code Organisation Besides the big structure determined by the motivation most parts of the codes are loosely bound together Under MuonProphet src functions all generation probabity functions vertex and energy distribution func tions are included They can easily be mo
52. subsystem must learn some things which are described in the section below on adding new data classes 8 2 Features The I O subsystem supports these features Streams Streams are time ordered data of a particular type and are named In memory this name is the location in the Transient Event Store TES where the data will be accessed On disk this name is the directory in the ROOT TFile where the TTree that stores the stream of data is located Serial Files A single stream can be broken up into sequential files On input an ordered list of files can be given and they will be navigated in order transparently On output files closed and new ones opened based on certain criteria FIXME This is not yet implemented But it is easy to do so the hooks are there Parallel Files Different streams from one job need not be stored all together in the same file Rather they can be spread among one or more files The mapping from stream name to file is user configurable more on this below Navigation Input streams can be navigated forward backward and random access The key is the entry number which simply counts the objects in the stream independent of any potential file breaks 1Correct filling of the Archive Event Service is only guaranteed when using simple forward navigation 81 82 CHAPTER 8 DATA I O Policy The I O subsystem allows for various I O policies to be enforced by specializing some of its classes and through the
53. the best way to read this is using the pydoc program which takes the full Python name For example 100 CHAPTER 10 KINEMATIC GENERATORS shell gt pydoc GenTools Helpers Gun Help on class Gun in GenTools Helpers GenTools Helpers Gun class Gun Configure a particle gun based kinematics Methods defined here sinit Cosas l l Lo Remember that __init_ is the constructor in Python The rest of this section gives the full Python name and a general description of the available helpers Again use pydoc to see the reference information GenTools Helpers Gun takes a volume and a gun positioner timerator and a transformer to set up a GtGunGenTool based generator GenTools Helpers DiffuserBall as above but sets up a diffuser ball It also takes an AutoPositionerTool to modify the location of the diffuser ball in the geometry GenTools Helpers HepEVT takes a source of HepEVT formatted data and positioner timerator and trans former tools GenDecay Helpers Decay takes a volume and decayerator positioner and timerator tools 10 6 3 Gnrtr Configure and its Stages Currently the so called pull mode or Fifteen style of mixing of different types of events configuration mechanisms need work 10 6 4 GenTools Dumper Algorithm The GenTools package provides an algorithm to dump the contents of the generator output to the log It can be included in the job by creating an instance of the GenTools Dumper class The al
54. the current job or saved to the output file and used at a later time Here is a Python example of checking the tag 1 Check tag 2tag evt Event UserTag MySpecialEvent 3if tag 4 This event is tagged Do something 5 Tags can also be used to produce filtered data sets as shown in section 3 4 6 http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Tagging UserTagging python UserTagging UserTag DetectorTag py 5http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Tagging UserTagging python UserTagging UserTag DetectorTag py 38 CHAPTER 3 ANALYSIS BASICS 3 4 3 Add Variables to a NuWa File A common task is to add a new user defined variable for each event For example the time since the previous trigger can be calculated and added to each event This is a task for UserData The example job module Tutorial Quickstart python Quickstart DtData py shows the example of adding the time since the previous trigger to each event This example can be run 1shell gt nuwa py n 1 no history m Quickstart DtData 2 o daqPlus NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3 daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root After completion the output file can be opened in ROOT and the new data variables can be viewed and histogrammed Fig 3 7 The file can also be read back into another NuWa job and the user data will still be accessible
55. their validity expires However this means that the physical layout may not be convenient for access To deal with this table row objects which all inherit from DbiTableRow are obliged to return a Natural Table Index if the physical ordering is not a natural one for access Tables can then be accessed by this index 17 2 13 Task Task will provide a way to further select the type of data retrieved For example e There might be nominal set of geometry offsets or a jittered geometry to test for systematic effects e Detector Configuration data could have two tasks one for raw calibration and another for refined calibration The aim is that Task will allow a particular database table to be sub divided according to the mode of use Currently Task is a data type defined in Dbi i e Dbi Task and is implemented as an integer The default value is zero 17 2 14 Sub Site Sub Site can be used like the Task to disambiguate things at a single site For example this can be used to distinguish between antineutrino detector modules between electronics crates etc Currently SubSite is a data type defined in Dbi i e Dbi SubSite and is implemented as an integer The default value is zero 17 2 15 Level 2 disk Cache Loading a large table from the database is a lot of work 1 The query has to be applied and the raw data loaded 2 The row objects have to be individually allocated on the heap 3 Each data word of each row object has to be ind
56. this date for all future queries The hours minutes and seconds can be omitted and default to 00 00 00 Rollback can be more selective specifying either a single table or a group of tables with a common prefix For example theApp service DbiSvc RollbackDates 2002 09 01 theApp service DbiSvc RollbackDates Cal 2002 08 01 theApp service DbiSvc RollbackDates CalPmtGain 2002 07 01 Now the table CalPmtGain is frozen at July 2002 other Cal tables at August and all other tables at September The ordering of the commands is not important the interface always picks the most specific one to apply to each table Rollback only applies to future queries it does not invalidate any existing query result in the cache which are still available to satisfy future requests So impose rollback conditions at the start of the program to ensure they apply consistently MakeConnectionsPermanent By default the DatabaseInterface closes connection to the database between queries to minimise use of resources see section 17 9 1 If the job is doing a lot of database I O for example creating calibration constants then this may degrade performance in which case all connections can be made permanent by theApp service DbiSvc MakeConnectionsPermanent true Ordering Context Query Results By default when the Databaselnterface retrieves the data for a Context Query it does not impose an order on th
57. times GenHeader Generator level information Reference Time Defined by the generator output It is the first or primary signal event interaction time Time Extent Defined to encompass all primary vertices Will typically be infinitesimally small Precision Times Currently there no precision times in the conventional sense Each primary vertex in an event may have a unique time which is absolute and stored as a double SimHeader Detector Simulation output Reference Time This is identical to the reference time for the GenHeader that was used to as input to the simulation lBefore 2038 someone had better increase the size what stores the seconds 7 3 EXAMPLES OF USING THE DATA MODEL OBJECTS 79 Time Extent Defined to contain the times of all SimHits from all detectors Precision Times Each RPC PMT SimHit has a time measured from the reference time FIXME Need to check on times used in the Historian ElecHeader TrigHeader Readout 7 3 Examples of using the Data Model objects Please write more about me 7 3 1 Tutorial examples Good examples are provided by the tutorial project which is located under NuWa RELEASE tutorial Each package shoudl provide a simple self contained example but note that sometimes they get out of step with the rest of the code or may show less than ideal older ways of doing things Some good examples to look at are available in the DivingIn tutorial package It shows how to do almost all things
58. to apply GenName sets a label for this generator Location sets where in the event store to place the results Each tool is configured with its own specific properties For the most up to date documentation on them use the properties py tool Common or important properties are described Volume names a volume specifically a Detector Element in the geometry The name is of the form dd Structure Detector SomElement Position sets a local position relative to a volume s coordinate system Spread alone or as a modifier is used to specify some distribution width Strategy or Mode alone or as a modifier is used to modify some behavior of the tool GenDecay Configurables The GenDecay package provides a GtDecayerator tool which has the following properties ParentNuclide names the nuclide that begins the decay chain of interest It can use any libmore supported form such as U 238 or 238U and is case insensitive ParentAbundance the abundance of this nuclide that is the number of nuclides of this type AbundanceMap a map of abundances for all nuclides that are found in the chain starting at and including the parent If the parent is listed and ParentAbundance is set the latter takes precedence SecularEquilibrium Tf true default set abundances of uncorrelated daughter nuclides see Correlation Time property to be in secular equilibrium with the parent If any values are given by the Abun danceMap property they
59. to the component Gaudi has two main ways of setting such configuration Initially a text based C like language was used Daya Bay does not use this but instead uses the more modern Python based configuration With this it is possible to write a main Python program to configure everything and start the Gaudi main loop to run some number of executions of the top level algorithm chain The configuration mechanism described below was introduced after release 0 5 0 6 5 1 Overview of configuration mechanism Configure and Helper classes Configurables Figure 6 1 Cartoon of the layers of configuration code The configuration mechanism is a layer of Python code As one goes up the layer one goes from basic Gaudi configuration up to user interaction The layers are pictured in Fig 6 1 The four layers are described from lowest to highest in the next sections 6 5 2 Configurables All higher layers may make use of Configurables They are Python classes that are automatically generated for all components Algorithms Tools Services etc They hold all the properties that the component defines and include their default values and any documentation strings They are named the same as the component that they represent and are available in Python using this pattern 1from PackageName PackageNameConf import MyComponent 2mc MyComponent 3mc SomeProperty 42 You can find out what properties any component has using the properties py scr
60. vertices meet the criteria In fact the Historian knows to always record primary SimTracks and the first SimVertex on every track as the minimal set Selection strings may be None Only the default items are selected All All items are created An expression which is interpreted left to right Expressions consist of comparisons which are separated by boolean operators grouped by parentheses For example a valid selection string could be pdg 20022 and totalEnergy lt 10 eV or materialName Mineral0il Each comparison must be of the form lt PARAMETER OPERATOR CONSTANT UNIT gt A list of valid PARAMETERs is given in table 11 4 Valid OPERATORs consist of gt gt lt lt for numerical parameters and for string parameters A few parameters accept custom operators such as in for the detector element relational parameter For numerical operators CONSTANT is a floating point number For string paramters CONSTANT should be of the form CaseSensitiveString using a single quote to delimit the string For numerical parameters the user may should use the optional UNIT Units include all the standard CLHEP defined constants All parameters and unit names are case insensitive Boolean operators must come only in pairs Use parentheses to limit them This is a limitation of the parser For instance a lt 2 and b gt 2 and c 1 will fail but a lt 2 and b gt 2 and c 1 will be acceptable This ensur
61. very close to the muon in time their hits will overlap and their hits are not distinguishable For example some fast background following muon won t be triggered separately User should do the background trigger efficiency calculation based on the understanding of the real Daya Bay electronics 10 7 6 Trigger Bits Although the output got from MuonProphet simulation is empty i e no hit but the trigger information is set according to the fast simulation result According to the geometry input it could have RPC and waterpool trigger 10 7 7 Quick Start There is one example already installed with nuwa After you get into nuwa environment you can start with gt nuwa py n50 o fifteen root m MuonProphet FullChain gt log It will invoke the FastMuon py Chapter 11 Detector Simulation 105 106 CHAPTER 11 DETECTOR SIMULATION 11 1 Introduction The detector simulation performs a Monte Carlo integration by tracking particles through the materials of our detectors and their surroundings until any are registered hit sensitive elements PMTs RPCs The main package that provides this is called DetSim DetSim provides the following e Glue Geant4 into Gaudi through GiGa e Takes initial kinematics from a generator converts them to a format Geant4 understands e Takes the resulting collection of hits and optionally any unobservable statistics or particle histories and saves them to the event data store e Modified impro
62. will take precedence CorrelationTime Any nuclide in the chain that has a decay branch with a half life total nuclide halflife branching fraction shorter than this correlation time will be considered correlated with the parent s that produced it and the resulting kinematics will include both parent and child decays together and with a time chosen based on the parent abundance Otherwise the decay of the nuclide is considered dependent from its parent and will decay based on its own abundance 10 6 2 GenTools Configure The GenTools package s Configure object will take care of setting up a GtGenerator and adding it to the list of top algorithms The Configure object requires a helper object to provide the tools There are several helpers provided by GenTools and one provided by GenDecay that cover most require ments If a job must be configured in a way that no helper provides then a new helper can be written using the existing ones as examples The only requirement is that a helper object provides a tools method that returns a list of the tools to add to a GtGenerator algorithm Each helper described below takes a number of arguments in its constructor They are given default values so a default helper can be constructed to properly set up the job to do something but it may not be what you want After construction the objects are available as object members taking the same name as the argument Helpers are self documented and
63. with its associated auxiliary validity range table Note that files names must be absolute but can begin with an environmental variable URL The URL is identical to any other flat file with one additional constraint the extension must be cat or db For example nysql coop phy bnl gov dyb_offline home dyb work MyCatalogue db 17 7 4 Example The stand alone testing of the Database Interface includes an example of an ASCII Catalogue The URL of the cascade entry is nysql coop phy bnl gov dyb_test DATABASEINTERFACE_ROOT DbiTest scriptsDemoASCIICatalogue db If you look at the file DATABASEINTERFACE_ROOT DbiTest scripts DemoASCIICatalogue db you will see it contains 4 lines defining the tables DEMOASCIIDATA a Detector Descriptions table and DEMOASCIICONFIG Algorithm Configurations table file DBITESTROOT scripts DEMOASCIIDATA csv file DBITESTROOT scripts DEMOASCIIDATAV1d csv file DBITESTROOT scripts DEMOASCIICONFIG csv file DBITESTROOT scripts DEMOASCIICONFIGV1d csv In both cases the auxiliary validity range table defines a single validity range although there is no reason why it could not have defined any number For the DEMOASCIIDATA there are 5 rows a header row followed by 4 rows of data SEQNO INT UNWANTED INT PEDESTAL FLOAT SUBSYSTEM INT GAIN1 FLOAT GAIN2 FLOAT 1 99 1 0 0 10 100 1 99 1 1 1 11 110 1 99 1 2 2 12 120 1 99 1 3 3 13 130 For the DEMOASCIICONFIG table there are only
64. 2 self stage_cfg SingleLoaderSequence Members append sll In the end the top pulling algorithm Sim15 is added to gaudi top algorithm list Its only job is to bring up the initial request from top stage tool def configureSimi5 self from Stage StageConf import Simi5 simi5 Simi5 simi5 TopStage self opts top_stage from Gaudi Configuration import ApplicationMgr theApp ApplicationMgr theApp TopAlg append simi5 Example for LoadingProc LoadingProc is another input stream for SimHeader So the configuration of LoadingProc should be a replacement for configureDetector in the above example A working example can be found in Fifteen Load ingProc aileron testAll py Here the configuration after stage Detector will not be repeated Only the part for LoadingProc is shown In that example two input files are specified Each one is set to a new start time and a new event rate Details are shown below As usual the chain of simulation line are set up and input file are specified as expected def configureLoadingProc self from LoadingProc LoadingProcConf import LoadingProc load LoadingProc LoadingProc Oxygen18 load StartSec 0 load StartNano 0 load Distribution Exponential load Distribution Periodic load Rate 1 0 assembler_name 0x18Assem load HsAssembler assembler_name load OutputLevel 2 assem Assembler toolname assembler_name filename input root This and lower stage load Th
65. 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 54 CHAPTER 3 ANALYSIS BASICS return FAILURE result reconHdr recTrigger Get the detector ID for this trigger detector result detector detector detName Trigger Type This is an integer of the type for this trigger result triggerType Trigger Number A count of the trigger according to the DAQ result triggerNumber Trigger Time Absolute time of trigger for this raw data triggerTime result triggerTime Energy information result energyStatus result energy result energyQuality Position information result positionStatus result position x result position y result position z result positionQuality Direction information for tracks result directionStatus result direction x result direction y result direction z result directionQuality Covariance Matrix if one is generated result errorMatrix 3 5 12 Spallation Data Spallation data in ROOT The following table summarizes the spallation data visible directly in ROOT Array items have their length given in the brackets i e name length ROOT will automatically draw all entries in the array given the array name See the ROOT User s Guide for more details on working with Trees http root cern ch download doc 12Trees pdf 3 5 CHEAT SHEETS ROOT Variable Description tMu s tMu_ns
66. 55
67. 6 name dbtype codetype description AdNo tinyint int AdNo defined in docdb 6375 Figure 1 Detector int DayaBay Detector source dybgaudi trunk DataModel Conventions Conventions Detecto X double double coordinate X in meters Y double double coordinate Y in meters Z double double coordinate Z in meters Table 19 21 DBI Table specification for class GCoordinateAd which corresponds to table CoordinateAd 21nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCoordinateAd spec 19 22 COORDINATEREACTOR 209 19 22 CoordinateReactor Table specification source dybgaudi trunk Database DybDbi spec GCoordinateReactor spec Coordinates for reactors see docdb 6375 TABLE II rubric convention in Offline and docdb 6375 name ReactorId docdb 6375 DayaBayA 0x01 D1 DayaBayB 0x02 D2 LingAoIA 0x04 L1 LingAoIB 0x08 L2 LingAoIIA 0x10 L3 LingAoIIB 0x20 L4 name dbtype codetype description code ReactorId int int source dybgaudi trunk DataModel Conventions Conventions Reactor h X double double coordinate X in meters Y double double coordinate Y in meters Z double double coordinate Z in meters Table 19 22 DBI Table specification for class GCoordinateReactor which corresponds to table Coordi nateReactor 22http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCoordinateReactor spec 210 CHAPTER 19 DATABASE TABLES 19 23 DaqCali
68. 7 4 ACCESSING EXISTING TABLES 159 Int_t fSubSystem Float_t fPedestal Float_t fGaini Float_t fGain2 which it is content to expose fully Int_t GetSubSystem const return fSubSystem Float_t GetPedestal const return fPedestal Float_t GetGaini const return fGaini Float_t GetGain2 const return fGain2 Its worth pointing out though that it is the job of the table row object to hide the physical layout of the database table and so shield its clients from changes to the underlying database Its just another example of data encapsulation Making Further Queries Even though a DbiResultPtr is lightweight it is also reusable you can make a fresh query using the NewQuery method UInt_t NewQuery Context vc Dbi Task task 0 which returns the number of rows found in the new query For example DbiResultPtr lt DbiDemoDatal gt myResPtr vc Context newVc myResPtr NewQuery newVc Having made a query you can also step forwards or backwards to the adjacent validity range using the method UInt_t NextQuery Bool_t forwards kTRUE supply a false value to step backwards This method can be used to scan through a database table for example to study calibration constants changes as a function of time To use this efficiently you need to request accurate validity ranges for your initial query although this is the default see section 17 9 2 For aggregated data stepping to a neighbouring range will
69. 9 LoadingProc The only chance that events of different type can overlap and produce some impact is in electronic simulation Hits from different events which are close in time may not be distinguished in electronics A correct mixing approaching with pre simulated sample should happen before it goes into electronic simulation Another idea is to re use some geant4 pre simulated sample Like for muon events it has a high frequency and is extremely time consuming We care a lot more about its influence on its adjacent events than its own topology LoadingProc is created on this background It accepts a pre simulated file which must contain SimHead ers as an input stream and output them to Stage Detector tool At the same time it can be configured to reset the event rate i e time of the generated events It also simplify the process if any trigger or electronic simulation parameter needs to be adjusted since don t have to waste time to redo the longest geant4 simulation 15 2 10 Algorithm Sim15 Algorithm Sim15 is a simple Gaudi algorithm which is inserted into Gaudi top algorithm list It runs once every execution cycle It sends out the initial request for generating MC events 15 2 11 Customize Your Simulation Job A General Example This part will explain how exactly to write your own simulation script with Fifteen package The example is from dybgaudi Tutorial Sim15 aileron FullChainSimple py which implements all the basic elements
70. CalibDataSvc loads the PMT calibration parameters from the database To access a Service from a Python algorithm you should load the service in the initialize function 3 4 NUWA RECIPES 43 self calibDataSvc self svc ICalibDataSvc StaticCalibDataSvc if self calibDataSvc None self error Failed to get ICalibDataSvc StaticCalibDataSvc return FAILURE BONA When requesting a service you provide the type of the service ICalibDataSvc followed by the specific version you wish to use StaticCalibDataSvc Loading the service in C is similar ICalibDataSvc calibDataSvc svc lt ICalibDataSvc gt StaticCalibDataSvc true if calibDataSvc error lt lt Failed to get ICalibDataSvc StaticCalibDataSvc lt lt endreq return StatusCode FAILURE oF WN 44 CHAPTER 3 ANALYSIS BASICS 3 5 Cheat Sheets 3 5 1 Loading the NuWa software On the computer clusters you must load the software each time you log on You can load the NuWa software using the nuwaenv command 1shell gt nuwaenv r trunk 0 The nuwaenv command can incorporate both shared releases and personal projects For more information on using and configuring nuwaenv see https wiki bnl gov dayabay index php title Environment_ Management_with_nuwaenv In the end nuwaenv is a way of automating the sourcing of the following shell commands The examples given are for the pdsf cluster 1 bash shell 2shell gt cd common dayabay r
71. Counts int 11 int Positron Like Event Number NLikeCounts int 11 int Neutron Like Event Number DtNegCounts int 11 int Number of Events with Dt_trigger amp lt 12 5ns DtLargeGapCounts int 11 int Large Dt Gap Event Number NHitCountsGt int 11 int NHit Trigger Counts With Energy gt 0 7MeV ESumCountsGt int 11 int ESum Trigger Counts With Energy4 gt 0 7MeV Table 19 47 DBI Table specification for class GDqDetectorNew which corresponds to table DqDetectorNew 47nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqDetectorNew spec 19 48 DQLIVETIME 19 48 DqLiveTime 235 Table specification source dybgaudi trunk Database DybDbi spec GDqLiveTime spec docstring name dbtype codetype description code2d RunNo int 11 int Run Number FileNo int 11 int File Number Detectorld int 11 int Detector ID IntegralRunTime double double DAQ Running Time ms IntegralLiveTimeBlocked double double DAQ runtime with blocked trigger correction ms IntegralLiveTimeBuffer double double DAQ runtime with buffer full correction ms Table 19 48 DBI Table specification for class GDqLive Time which corresponds to table DqLive Time 48nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqLiveTime spec 236 19 49 DqPmt CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GDqPmt spec docstring name dbtype codetype des
72. Daya Bay Offline Software User Manual 13 December 17 2015 Daya Bay Contents Contents 1 Introduction 1 1 Titended Audience coca csm iaa a a A a a dd 12 Document Organization ca sisi das RI A A Ae L3 COMU ou io aeee a a A A ER 14 Building Documentation 4 o uh O E RR ew a 15 Typographical Conventions lt lt co bce we ee ee eee ewe eee ees 2 Quick Start 21 Cilia Intrastoiciate ce ee a ee eA Re ee eh ew 2 2 Installation and Working with the Source Code oo 23 UiBline Framework s acer ei es a a e A A a a E 24 Data Model cc eee ba a eek a a a a RO E a e 25 Detector Description lt lt eee s a a bee ee a T e AA 26 Kinematic Generators socca aswea k ibaa aa A a ee g 27 Detector SinmlatioN o es a 64 46 aaa aa aa a a e e g h e ee 28 Quick Start with Truth Intonation cocoa ad RE aala ORE A 20 Plena Smodlaka cesa a AER a aran amas Bw 4 210 Teipger Simulali i on oca a AA A A eee ee A A se RS ars Ga SE Hee eee We ae dod eee eas amp amp 21 EN a cht te Sven SG ME a I AAP EREP A GER GE ES 213 POBRORBUMGIOR geen x a Se A ee Re ARA a A Ae Sold WRU AE 3 Analysis Basics Sok o EEN 32 Daya Bay Date Piles careca eee se ee EA OS Oe a ae a o si iaee a ee we ee Ree eee er ee hae we oa ee MEN LAOS o a A GE ORO ee PAA eee ee Sh ee ee G Oo Chear Shorts aa ee Oe ee ELAS ewe RE Rema ee GEE EES 3 6 Hands on Exercises a nana tida daua kaaa rerea naai 4 Offline Infrastructure AI Meal MiSs oaceae
73. DbiTableProxy Must Provide Services to its Clients There would not be much point in its existence otherwise would there However its not necessarily the case that all its does is to provide direct access to all the data that came from the table This subject is explored in the next section The Dictionary files FIXME Need to include instructions for properly doing dict h and dict xml files describing table rows DbiResultPtr and DbiWriter if I ever figure out how Data Encapsulation A table row object is the gateway between a database table and the end users who want to use the data it contains Like any good OO design the aim should be to hide implementation and only expose the abstraction There is nothing wrong in effectively giving a 1 1 mapping between the columns of the database table and the getters in the table row object if that is appropriate For example a table that gives the position of each PMT in a detector is going to have an X Y and Z both in the database and in the getter However at the other extreme there is calibration Its going to be well into detector operation before the best form of calibration has been found but it would be bad design to constantly change the table row getters Its far better to keep the data in the database table very generic for example SeqNo int SubSystem int CalibForm int parm0O float parmi float parm2 float The significance of parm0 depends on CalibForm The table row obj
74. E 2 bash gt source setup sh 3 tcsh gt source setup csh Any directories holding your own projects should then be prepended to this colon separated CMTPROJECTPATH variable 2 2 4 Packages A package is a directory with a cmt requirements file Packages are located by the CMTPATH environment variable which is automatically set for you based on CMTPROJECTPATH You should not set it by hand 2 2 5 Environment Every package has a setup script that will modify your environment as needed For example shell gt cd path to NuWa RELEASE dybgaudi DybRelease cmt shell gt cmt config needed only if no setup scripts exist bash gt source setup sh tcsh gt source setup csh Bw nN lhttp dayabay ihep ac cn svn dybsvn installation trunk dybinst dybinst https wiki bn1 gov dayabay index php title Category 0ffline_Software_Releases Shttps wiki bnl gov dayabay index php title Getting_Started_With_0ffline_Software 6 CHAPTER 2 QUICK START 2 3 Offline Framework 2 4 DATA MODEL 2 4 Data Model 8 CHAPTER 2 QUICK START 2 5 Detector Description 2 6 KINEMATIC GENERATORS 2 6 Kinematic Generators 10 CHAPTER 2 QUICK START 2 7 Detector Simulation 2 8 Quick Start with Truth Information Besides hits DetSim through the Historian package can provide detailed truth information in the form of particle histories and unobservable statistics These are briefly described next and in detail later in this chapter
75. EAT SHEETS 45 Now you can create new packages under the directory myNuWa and use them in addition to an existing NuWa installation See section 3 4 9 for more details You can also replace an existing NuWa package with you own modified version in myNuWa See sec tion 3 4 10 for more details 3 5 4 Standard Data Files A set of standard Daya Bay data files are available on the computer clusters The following table provides the location of these files on each cluster Type Location Onsite Farm daq data dyb spade rawdata daq 2 PDSF daq data In HPSS Archive daq eliza16 dayabay nuwaData exp sim dataTag daq calib eliza16 dayabay nuwaData exp sim dataTag calib recon eliza16 dayabay nuwaData exp sim dataTag recon coinc eliza16 dayabay nuwaData exp sim dataTag coinc spall eliza16 dayabay nuwaData exp sim data Tag spall THEP daq data daq recon coinc spall BNL daq data daq recon coinc spall Using the Catalog A Catalog tool is provided to locate the raw data files Be sure to load NuWa before running this example see section 3 5 1 Here is a simple example to locate the raw data files for a run 1shell gt python 2Python 2 7 r27 82500 Jan 6 2011 05 00 16 3 Gcc 3 4 6 20060404 Red Hat 3 4 6 8 on linux2 4Type help copyright credits or license for more information 5 gt gt gt import DybPython Catalog 6 gt g
76. Event 2myData myTag addData MySpecialData Event UserData MySpecialData 3myData addInt myInt In the check function you should set the variable value before calling tagIt 1if tagThisEvent 2 Keep track of the reconstructed data you are tagging 3 self getTag MySpecialEvent setInputHeaders recHdr 4 myData self getTag MySpecialEvent getData MySpecialData Shttp dayabay inep ac cn tracs dybsvn browser dybgaudi trunk Tutorial Quickstart python Quickstart DtData py Thttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Tutorial Quickstart python Quickstart DtData py Shttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Tagging UserTagging 3 4 NUWA RECIPES 39 5 myData set myInt 12345 6 self tagIt MySpecialEvent 3 4 5 Copy Data Paths to a New File There may be situations where you would like to filter only some paths of data to a smaller file The job module SimpleFilter Keep can be used for this purpose The following example shows how to create an output file which contains only the AdSimple reconstructed data 1shell gt nuwa py n 1 m SimpleFilter Keep Event Rec AdSimple 2 o adSimple NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3 recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root This module can take multiple arguments to save more paths to the same file 1shell gt nuwa py n 1 m SimpleFilt
77. Event Gen and Event Sim are generally not synchronized with the data trees since one simulated event may produce an arbitary number of triggered readouts 1root 1 TTreex CalibReadoutHeader TTreex f Get Event CalibReadout CalibReadoutHeader 2root 2 TTreex AdSimple TTreex f Get Event Rec AdSimple 3root 3 AdSimple gt AddFriend CalibReadoutHeader 4root 4 AdSimple gt Draw energy nHitsAD detector 2 colz See the ROOT User s Guide for more details on working with Trees http root cern ch download doc 12Trees pdf 3 2 5 Analysis Examples or A Treatise on Cat skinning What is the best simplest fastest way for me to examine event data and generate my histograms If this is your question then please read this section As discussed in the preceding sections you can directly use ROOT to inspect NuWa event data files Within ROOT there are a few different methods to process event data Alternatively you can use the full power NuWa to process data To demonstrate these different methods a set of example scripts will be discussed in this section Each example script generates the exact same histogram of number of hit PMTs versus reconstructed energy in the AD but uses a different methods Each ROOT script shows how to chain trees from multiple files and how to friend data trees from the same file All example scripts can be found in the Tutorial Quickstart software package e dybTre
78. FullTimeWindow see section 17 9 2 Accessing the Results Table Having got a pointer to the table the first thing you will want to know is how many rows it has Do this using the method Ulnt_t GetNumRows const 158 CHAPTER 17 DATABASE If the query failed then the number of rows returned will be zero This could either be the result of some catastrophic failure for example the database could not be opened or simply that no appropriate data exists for the current event If you want to know which of these it is you can use the const DbiValidityRec GetValidityRec const If this returns a null pointer then the failure was a major one see 17 4 4 If not then the DbiValidityRec tells you about the validity of the gap Its method const ContextRange amp k GetContextRange const returns a Context package ContextRange object that can yield the start and end times of the gap Due to the way the Databaselnterface forms the query this may be an underestimate but never an overestimate If the table has rows then the GetContextRange will give you an object that tells you the range of the data Again the range may be an underestimate To get to the data itself use the method const T GetRow UInt_t i const where T DbiDemoDatal in this case This gives you a const pointer to the it row where i is in the range 0 lt i lt GetNumRows FIXME Need complete example here including DataModel object Putting this all tog
79. HeaderCnv TranToPer const DayaBay GenHeader z tranobj 5 PerGenHeader amp perobj 64 7 StatusCode sc HeaderObjectCnv toPer tranobj perobj 8 if sc isFailure return sc 9 20 rest of specific t gt p copying 21 22 return StatusCode SUCCESS 23 8 6 ADDING NEW DATA CLASSES 87 For filling references to other object you implement the low level Gaudi methods fillRepRefs to fill references in the persistent object and fi110bjRefs for the transient Like above you should first delegate the filling of the HeaderObject part to HeaderObjectCnv 1StatusCode GenHeaderCnv fillRepRefs I0paqueAddress Datalbjectx dobj 24 3 GenHeader gh dynamic_cast lt GenHeaderx gt dobj StatusCode sc HeaderObjectCnv fillPer m_rioSvc gh m_perobj if sc isFailure handle error fill GenHeader references if there were any here return sc FOO WON DH A 2StatusCode GenHeaderCnv fillObjRefs IOpaqueAddress DataDbjectx dobj 34 A HeaderObject hobj dynamic_cast lt Header0Object gt dobj 5 StatusCode sc HeaderObjectCnv fillTran m_rioSvc m_perobj x hobj 6 if sc isFailure handle error T 8 fill GenHeader references if there were any here 9 20 return sc 21 Register Converter with Gaudi One must tell Gaudi about your converter by adding two files Both are named after the package and with entries cc and _load cc suff
80. IXME This is a low level method We should clean it up so that at least the needed dynamic_cast lt gt on the DataObject is done in the base class Converter Implementation File This section describes what boilerplate each converter needs to implement It doesn t go through the actual copying code Look to the actual code such as GenHeaderCnv cc for examples First the initial boilerplate and constructors destructors 1 include GenHeaderCnv h 2 include PerBaseEvent HeaderObjectCnv h 3 4using namespace DayaBay 5using namespace std 6 7GenHeaderCnv GenHeaderCnv ISvcLocator svc 8 RootIOTypedCnv lt PerGenHeader GenHeader gt PerGenHeader 9 classID svc 104 11GenHeaderCnv GenHeaderCnv 2 Note that the name of the persistent class the class ID number and the ISvcLocator all must be passed to the parent class constructor One must get the persistent class name correct as it is used by ROOT to locate this class s dictionary When doing the direct copies first delegate copying the HeaderObject part to its converter 1 From Persistent to Transient 2StatusCode GenHeaderCnv PerToTran const PerGenHeader amp perobj 3 DayaBay GenHeader amp tranobj 44 ar StatusCode sc HeaderObjectCnv toTran perobj tranobj 6 if sc isFailure return sc 7 8 rest of specific p gt t copying 9 0 return StatusCode SUCCESS 1 3 From Transient to Persistent 4StatusCode Gen
81. Master Database Soudan Primary Data flo GlobalSeqNo Data flow Database Database Distribution Figure 18 1 The flow of data is shown schematically in diagram 18 1 At the heart of the system is the Master Database at Soudan Most database updates enter the database realm here At regular intervals dbmjob is used to export all recently updated data and these export files are distributed to all other databases where the data is imported if not already present This is done by the local database manager again using dbmjob These primary data flows are shown in red Smaller amounts of data come from secondary databases e g at CalDet and these are exported up to the Master Database where they join other updates for distribution This system relies on the ability to 183 184 CHAPTER 18 DATABASE MAINTANENCE e Record the insertion date so that updates can be incremental e Uniquely identify data so that it is not accidentally duplicated if attempting import more than once For example updates to a secondary database might be reflected back if exporting all recent changes However such data is ignored as duplicated data when resubmitted to the Master dbmjob exploits the fact that all Dbi compliant database tables come in pairs the main data table and an auxiliary validity range table The auxiliary table records insertion dates and have globally unique SeqNos Sequence Numbers The diagram shows how globally unique numbers are
82. Muon Counts WSTaggedCounts int 11 int WS Combined Tagged AD Muon Counts Vari float double Place Holder Var2 float double Place Holder Var3 float double Place Holder Var4 float double Place Holder Varb float double Place Holder Var6 float double Place Holder Var7 float double Place Holder Var8 float double Place Holder Var9 float double Place Holder Var10 float double Place Holder Table 19 46 DBI Table specification for class GDqDetectorExt which corresponds to table DqDetectorExt 46nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqDetectorExt spec 234 19 47 DqDetectorNew CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GDqDetectorNew spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number Detectorld int 11 int Detector ID TriggerCounts int 11 int Trigger Counts FlasherCounts int 11 int Flasher Counts MuonCounts int 11 int Muon Counts IbdCounts int 11 int IBD Number SpnCounts int 11 int Spallation Neutron Number BlockTrigCounts int 11 int Blocked Trigger Number SpnEnergy float double Spallation Neutron Energy SpnEnergySigma float double Sigma of Spallation Neutron Energy K40Energy float double K40 Peak Energy K40EnergyErr float double Error of K40 Peak Energy T1208Energy float double T1208 Peak Energy T1208EnergyErr float double Error of T1208 Peak Energy PLike
83. R 17 DATABASE 17 6 2 Aggregate Numbers As explained in Concepts see section 17 2 some types of data are written for the entire detector as a single logical block For example the way PMT pixels map to electronics channels might be written this way On the other hand if it is written in smaller sub detector chunks then it is Aggregated For example light injection constants come from pulser data and it is quite possible that a calibration run will only pulse some LEDs and so only part of a full detector set of constants gets written to the database for the run Each chunk is called an aggregate and given an aggregate number which defines the sub section of the detector 1t represents For pulser data the aggregate number will probably be the logical positional LED number A single DbiWriter can only write a single aggregate at a time for every aggregate can in principle have a different validity range For unaggregated data the aggregate number is 1 for aggregated data numbers start at 0 1 2 The way that the DatabaseInterface assembles all valid data for a given context is as follows e First if finds all aggregate records that are currently valid e For each aggregate number it finds the best most recently created record and loads all data associated with it This has two consequences e For a given table the regime whereby the data is organised into aggregates should remain constant throughout all records in the table If absol
84. Re Ree RO i 226 ID ADDISON e cigarra ee ee EAA AA OR See a eee ee y 227 MADERO a ora aa aaah ROSY ae oa Dee Be OS oye eR Mae aes ee o 228 IA CA E Oe REE ee eee eee ee a BRR ae 229 19A Da CbannelPacked 424 444 da AA a td ee OO GEES 230 10 AalgChannelStatus 2 kk eR RRR AR ES Ee SRD a Lhe ae 231 MARQUE ntOL ba 2 8 oe ne Sr de Oe ee ee eh ee we ee ee Eee eS 232 TOAGDI DETE oe OR ee ERE YR RRR A RE Ye we ead amp S 233 Te A DolistectarNem 2 sc aca bode ee dk ow bao PEERY Oe ede ee oe ed 234 TIAS Le TB a AR eee heh So Re EE ee oT Re eee G 235 E Mb 2 etd ae ee ee a ee be he eee DR eee eee a et ee ey a A 236 IED UNS gay yee a a eb A a ee Oe SY A we x 237 IB bIDoirisver A Be Se RRR EE ERE EEE REG SESE ES 238 Rs AA IP hh ROS OS RE Ee SAS ee Rie e AS 239 19 SMEMCra Position Corr lt a Aa ee ek A EEE EE Pe e ee eS 240 Te e EA ee ee were he he Oa a 241 TO OBS aba E a Re eR ee ee ee ea a a e 242 10 GGoodRanlist ona ee RAE EE AERA SS EER Oe eee Gd ES 243 1G erie ately o cognac A e ee ee RRA A A ee SAKA AS 244 a A a ee ee ee ee eee OEE BSR ee al ee a aaa ae ye eS 245 SEC OMICS ORS oeri e ete aS ae Ga ee oe RE DES Ba eS e ee Sa ewan ae oe e 246 ID GOP Ia Ad ociosa rada 247 Il Sa oc ig SG OR AR eR hh DD Ra RR ERR OH OIE Bea RE OAS 249 IPS MBE e ceso ee Re eS oR ee SG Reha a Fe 250 ase a AA 251 Contents 19 64TimeLatency 20 Bibliography Bibliography Chapter 1 Introduction 1 1 Intended Audience This manual describes how Daya Bay coll
85. ResultPtr lt DbuSubRunSummary gt runs DBUSUBRUNSUMMARY context Dbi kAnyTask RUNTYPENAME NormalData This query reads the DBUSUBRUNSUMMARY table and besides imposing the context query also demands that the data rows satisfies a constraint on RUNTYPENAME 162 CHAPTER 17 DATABASE const string amp fillOpts This is a string that can be retrieved from DbiResultSet when filling each row so could be used to program the way an object fills itself e g by only filling certain columns The Databaselnterface plays no part here it merely provides this way to communicate between the query maker and the the author of the class that is being filled Accessing the Results Table Accessing the results of an Extended Context query are essentially the same as for a standard query but with following caveats e If the method const DbiValidityRec GetValidityRec const DbiTableRow row 0 const is used with the default argument then the global validity of the set i e the overlap of all the rows is returned Given the nature of Extended Queries there may be no overlap at all In general it is far better to call this method and pass a pointer to a specific row for in this case you will get that validity of that particular row e The method const T GetRowByIndex UInt_t index const will not be able to access all the data in the table if two or more rows have the same Natural Index This is prohibited in a standard query but
86. Sim ADC Generation 12 4 Simulation Constant 123 Simulation constants based on electronics hardware is defined in dybgaudi DataModel Conventions Con ventions Electronics h Table 12 3 summaries the major vaiables defined and their hardwired values 124 CHAPTER 12 ELECTRONICS SIMULATION Algorithm Name Property Defualt SimLocation SimHeaderLocationDefault Detectors DayaBayAD1 2 3 4 PmtTool EsPmtEffectPulseTool EsFrontEndAlg RpcTool EsIdealPulseTool FeeTool EsIdealFeeTool FecTool EsIdealFecTool MaxSimulationTime 50 us Table 12 1 Algorithms and their properties Property Default CableSvcName StaticCableSvc SimDataSvcName StaticSimDataSve TriggerWindowCycles Dayabay TriggerWindowCylces NoiseBool true NoiseAmp 0 5mV Table 12 2 Properties declared in EsIdealFeeTool 12 4 SIMULATION CONSTANT 125 rawSignal SimSamples tdcSignal tdcSamples tdcValues EstdeatFeeToot sample EsidealFeeToot discriminate Based on CLK numbers in tdcValues hitSignal hitSamples For tdcSignal points over threshold Convert hitSignal to hitSyne hitSync hitSamples hitHold hitSamples Convert hitSync to hitHold Figure 12 3 hitHold signal generation sequence Analog Signals are shown in the black box And ditigal signals are shown in blue boxes On the right hand side related functions or comments are listed to specify the convertion between different s
87. Sim within the dybgaudi project It uses SimTrigCommand s and ElecCrate s to produce readouts The produced readouts are held within a SimReadoutHeader object An addition ReadoutHeader object exists to satify the requirement that only one 1 readout be produced each execution cycle The details of the header objects are shown in figures 14 2 and 14 1 14 2 ReadoutHeader The ReadoutHeader contains a single readout which consists of the following detector Detector uniquely identifying the subsystem that was readout to produce this object triggerNumber unsigned int enumerating triggers triggerTime TimeStamp of trigger issuance triggerType TriggerType_t enum which constructs a bitmap to define the trigger type readoutHeader A pointer back to the ReadoutHeader which contains this object Two flavors of Readouts exist ReadoutPmtCrate and ReadoutRpcCrate The ReadoutPmtCrate contains a map of FeeChannelld s to ReadoutPmtChannel s and the ReadoutRpcCrate contains a similar map of FeeChannelId s to ReadoutRpcChannel s The ReadoutPmtChannel Contains channelld FeeChannelld uniquely identifying the channel that was read out tdc a vector of tdc values adc a map of adc values keyed with their clock cycle adcGain FeeGain_t denoting either that the high or low gain was read out readout pointer back to the ReadoutPmtCrate which contains this channel readout The ReadoutRpcChannel contains channelld FeeChannelld uniquely identifying the cha
88. Types of Data Besides the data from the detector itself off line software requires additional types of data Some possible examples Detector Description i e data that describes the construction of the detector and how it responds to the passage of particles through it The geometry the cabling map and calibration constants are all examples of this type of data Reactor Data i e reactor power fuel makeup or extrapolated neutrino spectra Physics Data i e cross section tables optical constants etc It is the purpose of the Databaselnterface to provide simple and efficient access to such data and to provide a framework in which new types of data can be added with minimal effort 147 148 CHAPTER 17 DATABASE 17 2 2 Simple Compound and Aggregated Within the database data is organised into tables When the user requests data from a table the Databa selnterface collect rows of data from the appropriate table From the perspective of the interface there are 3 types of organisation Simple A single row is retrieved Algorithm Configuration data is always simple even if multiple configu rations are possible only one can be selected at a time Detector Description on the other hand is almost never Simple Compound Multiple rows are retrieved Each row represents a single sub system and the request retrieves data for a complete set of sub systems For example a request for PMT positions will produce a set of rows one for eac
89. Value double energy reconT GetLeaf energy gt GetValue int nHit int reconT GetLeaf calibStats nHit gt GetValue Fill histograms if energyStatus 1 Reconstruction was successful if detector 1 AD 1 nhitVsEnergyAD1H gt Fill energy nHit else if detector 2 AD 2 nhitVsEnergyAD2H gt Fill energy nHit dybTreeSetBranch C Use this approach only if you really need the fastest speed for generating your histograms and cuts cannot be expressed in a simple TTree Draw command The example script relies on TTree SetBranchAddress to explicitly manage the event data location in memory By avoiding reading data unnecessary data from the file it also demonstrates how to achieve the highest speed Advantages e Fastest method to histogram data e Allows chaining and friending of data Disadvantages e Requires some careful programming e No access to geometry database other external data e Cannot be integrated with production analysis job To run this example use the following approach root 0 L dybTreeSetBranch C root 1 dybTreeSetBranch recon root The key lines from the script are Enable only necessary data branches reconT SetBranchStatus 0 Disable all calibStatsT SetBranchStatus 0 Disable all Must reenable execNumber since the tree indexing requires it reconT SetBranchStatus execNumber kTRUE reconT SetBranchStatus ca
90. a crucial role in resolving which set of data to use later creation dates take priority over earlier ones This scheme assumes that constants from earlier runs are created before constants from later runs but this isn t always true When improving e g calibration constants it s quite normal to recalibrate recent runs before going back and fixing earlier ones and then simply to use the date when the constants were created would mean that the constants from earlier runs would take priority over any later runs they overlapped To allow constants to be created in any order the interface provides a system for deducing the best creation dates for any constants as follows e A query is made using as the context the start of the validity for the new constants e If the query finds no data the creation date of the new constants is set to its validity start date e If the query finds data the creation date of the new data is set to be 1 minute greater than the creation date of the found data i e just late enough to replace it The scheme means that creation dates always follow that dates of the runs that they correspond to rather than the dates when their constants were created When using the scheme its probably better to consider the dates to be version numbers 17 2 10 Rollback The database changes almost constantly to reflect the state of the detector particularly with regard to the calibration constants However this can mean that ru
91. a transfer While synchronizing many generation sources they generate many data in the same time same execution cycle For dybgaudi they are held by AES and input Headers The time sequence in which they are generated is disordered Stage tool is put in charge of managing all the processors in one simulation stage it manages the execution of them i e only run them when data is needed and it caches the data from all processors sorts them and output them in time order A bad metaphor might be stage tool works like a central train station It controls the incoming stream of all the trains to avoid possible crushing It has some ability to let train stop for some period then let them leave on time 15 2 4 Gnrtr Gnrtr stands for Generator For one type of events one generator needs to be specified The type here is not limited to its physics generation mechanism The same type of event in different volume or geometry structure may have different event rates so they should be specified as two different Gnrtr For example a type of radioactive background have different abundance in two types of material then it will have different 15 2 FIFTEEN 137 event rate While running Gnrtr will invoke each GenTools it owns i e a real generator timrator positioner etc User needs to specify all these tools for it 15 2 5 DetSimProc One of DetSimProc s main functions is to call the real simulation tool Geant4 through its Gaudi interface GiGa T
92. abase Writing data is as normal by means of a DbiWriter however before you write data you must locate a database in the cascade that will accept temporary tables and pass it a description of the table This is done using the DbiCascader method CreateTemporaryTable You can access the cascader by first locating the singleton DbiTableProxyRegister which is in overall charge of the Databaselnterface The following code fragment shows how you can define a new table for DbiDemoDatal ttinclude DatabaseInterface DbiCascader h ttinclude DatabaseInterface DbiTableProxyRegistry h Ask the singleton DbiTableProxyRegistry for the DbiCascader const DbiCascader amp cascader DbiTableProxyRegistry Instance GetCascader Define the table string tableDescr SEQNO INT SUBSYSTEM INT PEDESTAL FLOAT GAIN1 FLOAT GAIN2 FLOAT Ask the cascader to find a database that will accept it Int_t dbNoTemp cascader CreateTemporaryTable DbiDemoDatai tableDescr 17 6 FILLING TABLES 175 if dbNoTemp lt 0 cout lt lt No database to will accept temporary tables lt lt endl You pass CreateTemporaryTable the name of the table and its description The description is a paren thesised comma separated list It follows the syntax of the MYSQL CREATE TABLE command see section 17 8 In principle not every database in the cascade will accept temporary tables so the cascader starts with the highest priority one and wo
93. abase DybDbi spec GDemoBit spec GDemoBit See dybgaudi Database DybDbi tests test_demo_bitfield py warning Due to a DBI ROOT reading limitation restrict the bit fields to avoid the most significant name dbtype codetype description code2db Gain double double demonstration double Id int 11 int demonstration identity MaskO int 11 Int_t demonstration BitField Maski int 11 Int_t demonstration BitField Mask2 int 11 Int_t demonstration BitField Mask3 int 11 Int_t demonstration BitField Mask4 int 11 Int_t demonstration BitField Mask5b int 11 Int_t demonstration BitField Table 19 41 DBI Table specification for class GDemoBit which corresponds to table DemoBit lnttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDemoBit spec 19 42 DQCHANNEL 19 42 DqChannel 229 Table specification source dybgaudi trunk Database DybDbi spec GDqChannel spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number Channelld int 11 DayaBay FeeChannelld Unique id of the channel connected to a pmt fullPackedDa Occupancy float double Channel Occupancy DAdcMean float double Delta Adc Mean DAdcRMS float double Delta Adc RMS HvMean float double HV mean value within the file HvRMS float double HV RMS value within the file Table 19 42 DBI Table specification for class GDqChannel which corresponds to table DqChan
94. aborators can run offine software jobs extend existing functionality and write novel software components Despite also being programmers such individuals are considered users of the software What is not described are internal details of how the offline software works which are not directly pertinent to users This document covers the software written to work with the Gaudi framework Some earlier software was used during the Daya Bay design stage and is documented elsewhere 1 1 2 Document Organization The following chapter contains a one to two page summary or quick start for each major element of the offline You can try to use this chapter to quickly understand the most important aspects of a major offline element or refer back to them later to remind you how to do something Each subsequent chapter gives advanced details describes less used aspects or expand on items for which there is not room in the quick start section 1 3 Contributing Experts and users are welcome to contribute corrections or additions to this documentation by commiting tex or rst sources However Ensure latex compiles before committing into dybsun 1 4 Building Documentation To build the plain latex documentation 1cd SITEROOT dybgaudi Documentation OfflineUserManual tex 2make plain HH alternatively pdflatex main To build the Sphinx derived latex and html renderings of the documentation some non standard python packages must first b
95. ac cn svn dybsvn people wangzhe Start 3shell gt svn export http dayabay ihep ac cn svn dybsvn people wangzhe ProjRename 4shell gt ProjRename Start MyNewAlg 5shell gt 1s 6MyNewAlg ProjRename 7shell gt emacs MyNewAlg src components MyNewAlg cc amp At this point you should edit the empty algorithm in MyNewAlg src components MyNewAlg cc In particular you should add your analysis code into the initialize execute and finalize functions To compile your new algorithm you should do the following in a new clean shell ishell gt pushd NuWa trunk 2shell gt source setup sh 3shell gt export CMTPROJECTPATH path to myProjects CMTPROJECTPATH 4shell gt popd 5shell gt cd myNuWa MyNewAlg cmt 6shell gt cmt config cmt make Now you should setup a separate running shell for you to run and test your new algorithm Staring with a clean shell run the following 1ishell gt pushd NuWa trunk 2shell gt source setup sh 3shell gt export CMTPROJECTPATH path to myProjects CMTPROJECTPATH 4shell gt cd dybgaudi DybRelease cmt 5shell gt source setup sh 6shell gt popd 7shell gt pushd myNuWa MyNewAlg cmt 8shell gt source setup sh source setup sh Now you should be set up and ready to run your new NuWa algorithm in this shell 1shell gt nuwa py n 1 m MyNewAlg run recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root Remember to commit your new algorithm to SVN 3 4 10 Modify Part of NuWa Sometime
96. ack 2 contains a link both to its parent track Track 1 and to its parent vertex Vertex 2 of Track 1 There is also a forward link from Vertex 2 of Track 1 to Track 2 Not shown is that every SimVertex has pointer to its parent SimTrack and each SimTrack has a list of its daughter SimVertices guaranteed to have at least one vertex the start vertex for that particle so all of these references eventually hand somewhere An example of this pruning is shown in Figure To keep track of this indirect parentage links to a SimTrack or SimVertex actually use lightweight objects called SimTrackReference and SimVertexReference These objects record not only a pointer to the object in question but also a count of how indirect the reference is i e how many intervening tracks were removed during the pruning process Because pruning necessarily throws away information some detail is kept in the parent track about those daughters that were pruned This is kept as map by pdg code of Unrecorded Descendents This allows the user to see for instance how many optical photons came from a given track when those photons are not recorded with their own SimTracks The only information recorded is the number of tracks pruned for more elaborate information users are advised to try Unobservable Statistics To get ahold of Particle Histories you need to get the SimHeader Each running of the Geant simulation creates a single SimHeader object which contains
97. ack start step Level of match for Detector Ele ment 0 perfect postive inside ID number 4 byte best associ ated with DetElem Detector ID number 4 byte Site ID number 4 byte Site number 1 16 AD number 1 4 Momentum at vertex track start step Energy at track start or vertex 117 118 Name amp Synonyms KE kineticEnergy VX dir x u vy dir y vV VZ dir_z W ProcessType Process ProcessName pdg pdgcode particle charge ParticleCharge q id trackid creatorPdg creator mass m ParticleName CreatorProcessName CreatorProcess DetElem in DetectorElement in Step_dE dE Step_dE_Ion de_ion ionization Step qDE quenched dE qdE Step_dx StepLength dx Step_dt StepDuration dt Type double double double double double string double double double double double string string custom double double double double double gt Track gt Vertex va mM va gt Stats vas wm MM va CHAPTER 11 DETECTOR SIMULATION Description Kinetic energy at vertex track start step X direction cosine Y direction cosine Z direction cosine Type of process see below Name of current process via G4VProcess gt GetProcessName PDG code of particle Note that opticalphoton 20022 Charge of particle Geant TrackID of particle Useful for debugging PDG code for the immediate par ent particle Mass of the particle
98. adout object pointer points to the same object a SimReadoutHeader points to 14 4 1 ROsSequencerAlg ROsSequencerAlg tries to fix the many to one readouts to execution cycle mismatch The sequencer fill the ReadoutHeader object with only the first ReadoutEvent produced during each execution cycle 14 4 2 ROsReadoutAlg ROsReadoutAlg is the driving algorithm for ReadoutSim This algorithm applies each tool specified in the RoTools property for each trigger event It is up to the tool to decide if it should act or not The default setup is as follows import ReadoutSim rosim ReadoutSim Configure import ReadoutSim ReadoutSimConf as ROsConf ROsConf ROsReadoutAlg RoTools ROsFecReadoutTool ROsFeeReadoutTool ROsConf ROsReadoutAlg RoName ReadoutAlg ROsConf ROsReadoutAlg TrigLocation Event SimTrig SimTrigHeader ROsConf ROsReadoutAlg ElecLocation Event Elec ElecHeader 14 5 Readout Tools ReadoutSim currently has 5 tools described below which can be used to customize readout 14 5 1 ROsFeeReadoutTool ROsFeeReadoutTool handles reading out pmt based detectors By default this tool acts on all trigger commands associated with a pmt based detector To specify different parameters for specific pmt based detectors create multiple instances of this tool and specify DetectorsToProcess appropriately in each The default configuration is shown below import ReadoutSim ReadoutSimConf as ROsConf ROsConf ROsFeeReadou
99. ain loop over Coincidence entries from the example script demonstrating how to fill a histogram with data from these unfriendly trees Process each coincidence set int maxEntries adCoincT GetEntries for int entry 0 entry lt maxEntries entry Get next coincidence set adCoincT GetEntry entry Get multiplet data int multiplicity int adCoincT GetLeaf multiplicity gt GetValue int detector int adCoincT GetLeaf context mDetId gt GetValue std vector lt int gt amp triggerNumberV getLeafVectorI triggerNumber amp adCoincT std vector lt int gt amp energyStatusV getLeafVectorI energyStatus amp adCoincT std vector lt float gt amp energyV getLeafVectorF e amp adCoincT Loop over AD events in multiplet for int multIdx 0 multldx lt multiplicity multldx Get data for each AD trigger in the multiplet int triggerNumber triggerNumberV multldx int energyStatus energyStatusV multldx float energy energyV multldx Look up corresponding entry in calib stats int status calibStatsT GetEntryWithIndex triggerNumber detector if status lt 0 std cout lt lt Failed to find calib stats for trigger number lt lt triggerNumber lt lt and detector ID lt lt detector lt lt std endl continue Get data from matching calib stats entry double nominalCharge calibStatsT GetLeaf NominalCharge gt GetValue Fill histograms
100. all the muons in the event We could do this above by turning on SimTracks for all muons and turning on all the SimVertecies at which the muon changed material historian TrackSelection pdg 13 or pdg 13 historian VertexSelection pdg 13 or pdg 13 and MaterialChanged gt 0 Then after the event had been completed we would need to go through all the saved SimTracks and look for the tracks that were muons For each muon SimTrack we would need to go through each pair of adjacent SimVertices and find the distance between each pair where the first Sim Vertex was in water Then we would need to add up all these distances This would get us exactly what we wanted but considerable code would need to be written and we ve cluttered up memory with a lot of SimVertices that we re only using for one little task To do the same job with the Unobserverable Statistics method we need only run the Unobserver SteppingTask and give it the following configuration UnObserver Stats mu_track_length_in_water dx pdg 13 or pdg 13 and MaterialName Water This creates a new statistic with the name mu_track_length_in_water and fills it with exactly what we want to know This method is very powerful and allows the description of some sophisticated analysis questions at run time However compiling many of these Statistics can be time consuming during the execution of the simulaton For serious repea
101. ania dda a aaa ee a a a et ee e eee bdo eS Be DDG A A RN A WAS 2 a iaa a le a OR A da a Aa amp dd Trac bug Waker oo reaa OG EEE ORSAY PO ODE AAA wee awe 5 Installation and Working with the Source Code 21 21 21 34 36 44 59 61 61 61 61 61 63 10 11 12 Contents 5 1 Using pre installed release o e e a 63 52 Instalation of a Release ooo a ee ee ee EEE a 64 56 3 Anatomy of a Release oa a eaor ee A A Ra eR ee ek we ex 64 54A Version Control Your Cade ss s ca asa aaeeea a eke eS eee EDL EMG EE EES ee 65 55 Technical Detalla of the Installation lt lt lt u sceso maaari aai ee ee 65 Offline Framework 67 Di rodicom ias a AAA E E ee ae ae ek Be ww 67 6 2 Framework Components and Interfaces 00 2 eee ee 67 6 3 Common types of Components 68 Ga Writing your own GOMmipONeth cs a A a a e e a E E a 68 Go Properties and Conbeurati n o soe oe bho aaa a a RAR AS a e 70 Data Model 77 A PI EEN 77 E Se eg ee ee eee ee eee ee Oe ee Bee eee eee ews 78 7 3 Examples of using the Data Model objects o 79 Data I O 81 el Gual soni a a ee RR eee eee a 4 81 Ad PERMAN EA ARA 2 So 81 Gat Package feb be a aaua a eR be ee Ge a Oa oS 82 24 I O Related Job Configuration lt s oo 44446 5204 phe RRA me ee ee 82 66 How the VO Subsystem Works o ctra a esasen e pa JUAN da ee eee eae eS 82 8 amp 6 Adding New Data Classes 2 0606 06 ce eee Pe eee eee eee
102. any new simulated result SimHeader won t go before this GenHeader i e the previous SimHeader 15 2 6 ElecSimProc ElecSimProc maintains a pipeline of SimHits which are sorted by time Normal geant4 simulated PMT and RPC hits from all kinds of sources are kept in this pipeline The first thing to do every time execute ElecSimProc is to find a time gap between two successive hits in this hit pipeline The size of the gap is determined by DayaBay preTimeTolerance DayaBay postTimeTolerance which should be actually corresponding to the time period where a prepulse or a afterpulse exist Then in the real electronics simulation prepulses and afterpulse can be inserted into these places Certainly as explained in previous sections when a time gap is found the time of the gap stop must be less the current time of detector simulation stage This is the only way to know there won t be any hits from later simulation will fool into this gap The chunk of hits before the gap start are packed together and made a new hit collection then sent to electronic simulation So hits of all kinds of sources have a chance to mix and overlap Electronics simulation tools will take over the job and each sub detector will process its part separately For each fast simualted MuonProphet muon a fake hit is created and put into this pipeline Instead of going into a full eletronics simulation they are pushed into a fast electronics simulation They are always 100 perce
103. at float float 6 rows in set 0 08 sec Null Key Default Extra NO PRI NO PRI NULL auto_increment YES NULL l YES NULL l YES NULL l YES NULL DBI read must explicitly give Site SubSite Detectold DBI write must explicitly give SiteMask SubSite name dbtype codetype description code2db Tempi float float AD _temp_pt1 Temp2 float float AD _temp_pt2 Temp3 float float AD _temp_pt3 Temp4 float float AD _temp_pt4 219 Table 19 32 DBI Table specification for class GDcsAdTemp which corresponds to table DcsAdTemp 32http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDcsAdTemp spec 220 CHAPTER 19 DATABASE TABLES 19 33 DcsAdWpHv Table specification source dybgaudi trunk Database DybDbi spec GDcsAdWpHv spec 3 PMT High Voltage monitoring table mysql amp gt describe DcsAdWpHv 4 Field Type Null Key Default Extra 4 SEQNO int 11 NO PRI NULL l ROW_COUNTER int 11 NO PRI NULL LocationId char 6 YES NULL Voltage float YES NULL name dbtype codetyp
104. at float Positive RPC Voltage VoltageNeg float float Negative RPC Voltage Table 19 37 DBI Table specification for class GDcsRpcHv which corresponds to table DesRpcHv 37http dayabay inep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDcsRpcHv spec 19 38 DCSWPPMTHV 225 19 38 DcsWpPmtHv Table specification source dybgaudi trunk Database DybDbi spec G Des WpPmtHv spec 8 PMT High Voltage monitoring table for water pool PMT naming in water pool XXXXNN 4 letters number or letter number Where ist letter experiment site D L F 2nd letter water pool V outer pool C inner pool 3rd letter PMT direction I facing toward the center of the pool 0 facing away from the center of 4th letter wall A B C D E F G H floor treated like another wall U 1st number letter row number counting from bottom up or F for floor PMT within the wall 2nd number column number counting from left to right when facing the wall standing in the middle of name dbtype codetype description code2db Direction char 1 char PMT facing direction Wall char 1 char PMT wall PmtRow tinyint 4 int PMT row PmtColumn tinyint 4 int PMT column Voltage float float PMT Voltage Pw tinyint 4 int PMT Power ON OFF Table 19 38 DBI Table specification for class GDcsWpPmtHv which corresponds to table DesWpPmtHv ttp ayabay ihep ac cn tracs svn browser audi trun atabase i spec cs mtHv spe
105. aterialChanged gt 0 This example saves a vertex about every 20 cm or if the track direction changes by more than 15 degrees lhistorian VertexSelection distanceFromLastVertex gt 20 cm or AngleFromLastVertex gt 15 deg Users should fill out more useful examples here 11 3 3 Unobservable Statistics Description Although users may be able to answer nearly any question about the history of an event with the Particle Histories it may be awkward or time consuming to compile certain variables To this end users may request Unobservable statistics to be compiled during the running of the code 11 3 TRUTH INFORMATION 113 Figure 11 5 SimStatistic A Statistic object used for Unobservable Statistics ub 00 N DT FW WN te ill el re te od Nou PpPpWNR OO 18 class SimStatistic SimStatistic m_count 0 m_sun 0 m_squaredsum 0 double count const double sum const double squaredsum const double mean const double rms const Counts of increment call Total of x over all counts Total of x 2 over all counts sum count Root mean square UA ARS SOR s S a S void increment double x count 1 sum x sum2 x x private double m_count lt No of increments double m_sum lt Total of x over all counts double m_squaredsum lt Total of x 2 over all counts For instance let us say we want to know how many meters of water were traversed by
106. ationship between SimVertices and SimTracks is shown in Figure 11 3 1 The user may decide which vertices or tracks get saved as described in Sec 11 3 1 If a SimVertex is pruned from the output then any references that should have gone to that SimVertex instead point to the SimVertex preceeding it on the Track If a SimTrack is pruned from the output then any references that would have pointed to that track in fact point back to that track s parent The output is guaranteed to have at least one SimTrack created for each primary particle that the generator makes and each SimTrack is 1 Another way to describe this is that a SimTrack corresponds to a single G4Trajectory and SimVertex corresponds to a single G4TrajectoryPoint The G4Trajectory objects however are relatively lightweight objects that are used by nothing other than the Geant visualization It was decided not to use the G4Trajectory objects as our basis so as to remain Geant independent in our output files The similarity between the Particle Histories output and the G4Trajectories is largely the product of convergent evolution 108 CHAPTER 11 DETECTOR SIMULATION Figure 11 1 SimTrack Accessors A list of accessible data from the SimTrack object 1class SimTrack e wh 0003 sg 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Geant4 track ID int trackId const PDG code of this track int particle const PDG code of the immediate
107. ave been tried or data is found This scheme allows a user to override parts of the official database by creating a mini database with their own data and then placing it in the list ahead of the official database The concept of a set of overlaying databases is called a cascade 17 2 5 Context Sensitive In principle any of the data retrieved by the interface could depend on the the current event being processed Clearly Detector Descriptions such as calibration constants will change with time and the interface has to retrieve the right ones for the current event For this reason all requests for data through the interface must supply information about the e The type of data real or Monte Carlo e The site of the detector Daya Bay Ling Ao Mid Far or Aberdeen e The date and times of the event Collectively this information is called the Context and is represented by the Context class of the Context package Note that in common with event data and times All Database date and times are in UTC In the database all data is tagged by a Context Range which identifies the types of data and detector and the ranges of date times for which it is valid This is represented by the ContextRange class of the Context package Some data is universal the same database data can be used for any event Others may be very specific to a single type of data and detector and a limited date time range Note that the Context Range of the data defines the cont
108. bRunInfo Table specification source dybgaudi trunk Database DybDbi spec GDaqCalibRunInfo spec Calibration run information recorded in DAQ database from IS ACU This information can also be accessed from raw data file recorded as dybgaudi DaqFormat FileReadoutFormat FileTraits h References docdb 3442 docdb 3603 name dbtype codetype description RunNo int 11 int Run number Detectorld int 11 int OxPQ P site Q pit number AdNo int 11 int AD Number 1 8 SourceldA int 11 int source dybgaudi trunk DataModel Conventions Conventions Calibration t ZPositionA int 11 int Z position in mm of ACU A relative to target center SourceIdB int 11 int source in ACU B ZPositionB int 11 int Z position in ACU B SourceldC int 11 int source in ACU C ZPositionC int 11 int Z position in ACU C Duration int 11 int Duration of DAQ run in seconds LedNumber1 int 11 int ID number of the first LED being pulsed 1 6 LedNumber2 int 11 int ID number of the second LED being pulsed 1 6 LedVoltage1 int 11 int Voltage in mV for first LED LedVoltage2 int 11 int Voltage in mV for second LED LedFreq int 11 int LED pulsing frequency in Hz LedPulseSep int 11 int Seperation time in ns for double LED run LtbMode int 11 int LTB trigger mode True Forced HomeA int 11 int True if the selected source in ACU A is at home HomeB int 11 int True if the selected source in ACU B is at home HomeC int 11 int True if the s
109. base server port port number database name of database options string key value s separated by or amp Example mysql myhost 3306 test Trace Yes TraceFile qq log DBCONF_USER Pattern that yields database user name Only needs to be set if you require different names for different databases in the cascade then this can be a semi colon separated list in the same order as DBCONF_URL If the list is shorter than that list then the first entry is used for the missing entries DBCONF_PSWD Pattern that yields database password As with DBCONF_USER it can be a semi colon separated list with the first entry providing the default if the list is shorter than DBCONF_URL It only needs to be set if you require different passwords for the different databases in a cascade Security risks are avoided by never using actual passwords in this envvar but rather using a pattern such as 4 pass1 s pass2 s that will be filled in using the parameters from the config file section identified by DBCONF Setting it to null will mean that it will be prompted for when the interface initializes These variable should be set for the standard read only configuration These variables can be trivially overridden for specific jobs by resetting the environment variables in the python script Note that using setdefault allows the config to be overridded without editing the file import os os environ setdefault DBCONF dyb_offline pri
110. be stack based and passed by value thus reducing the risk of a memory leak 152 CHAPTER 17 DATABASE 2 During construction of the pointer a request for data is passed down through the interface and the results table which could be large is created on the heap The interface places the table in its cache and the user s pointer is attached to the table but the table is owned by the interface not the user 3 Each request for data is first sent to the cache and if already present then the table is reused 4 Each table knows how many user pointers are connected to it As each pointer is discarded by its owner it disconnects itself from the table it points to 5 Once a table has no pointers left it is a candidate for being dropped by its cache However this is not done at once as between events there are likely to be no user pointers so just because a table is not currently being pointed to it doesn t mean that it won t be needed again 17 2 12 Natural Table Index For Detector Description data tables can be large and the user will require direct access to every row However the way the table is arranged in memory reflects the way the data was originally written to the database For Simple and Compound data the table designer can control this organisation as complete sets are written as a single unit For Aggregated data the layout reflects the way aggregates are written This allows the interface to replace individual aggregates as
111. bers in the Context Range Table are unique However this can present a problem if the same type of data is being entered into several different databases For example calibration constants will be created in the Near Far and Calibration detectors Eventually the tables will be merged but it is essential that there is no conflict in the sequence numbers To solve this problem certain databases are special they are able to produce globally unique sequences numbers They do this as each is allocated a unique block of 10 000 000 sequence numbers which is enough to allow a new entry to be made every minute for 20 years These blocks are recorded in a special table GLOBALSEQNO that holds the last used sequence number for each table The block 1 9 999 999 is used for local sequence numbers i e ones that are only guaranteed unique within the current database table By default permanent data written to an authorising database will be written with global sequence numbers For temporary data or if writing to a non authorising database local sequence numbers are used and in this case a LOCALSEQNO table is generated automatically if required Important Merging database tables that have local sequence numbers will require a special procedure to avoid con flicts GLOBALSEQNO and LOCALSEQNO tables must never be propagated between databases 17 2 9 Validity Management For constants that change with time if that is not a contradiction in terms it make
112. biTableRow All table row objects must publicly inherit from the abstract classDbiTableRow DbiTableRow does provide some default methods even though it is abstract Must provide a public default constructor e g DbiDemoDatai DbiDemoDatai The Databaselnterface needs to keep a object of every type of table row class Must implement CreateTableRow method e g virtual DbiTableRow CreateTableRow const The DatabaseInterface uses this method to populate results tables return new DbiDemoDatal May overload the GetIndex method As explained in section 17 4 2 the ordering of rows in a table is determined by the way data is written to the database Where that does not form a natural way to access it table row objects can declare their own index using 166 CHAPTER 17 DATABASE Ulnt_t GetIndex Ulnt_t defIndex const DbiDemoData2 provides a rather artificial example UInt_t GetIndex UInt_t defIndex const return fSubSystem 10 and is just meant to demonstrate how a unique index could be extracted from some packed identification word The following is required of an index e The number must be unique within the set e It must fit within 4 bytes GetIndex returns an unsigned integer as the sign bit has no special significance but its O K to derive the index from a signed value for example Int_t PlexStripEndId GetEncoded const would be a suitable index for tables indexed by strip end Must i
113. ble double y intercept of linear portion of GausLine for pulsesd Sigma_m double double slope of linear portion of GausLine for the pulsesk 3 AO_b double double y intercept of line used to model ADC dependence of c AO_m double double slope of line used to model ADC dependence of constan Ai_b double double y intercept of line used to model ADC dependence of 1 Ai_m double double slope of line used to model ADC dependence of linear A2_b double double y intercept of line used to model ADC dependence of q A2_m double double slope of line used to model ADC dependence of linear A3_b double double y intercept of line used to model ADC dependence of c A3_m double double slope of line used to model ADC dependence of linear Table 19 15 DBI Table specification for class GCalibPmtPedBias which corresponds to table CalibPmtPed Bias l5http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibPmtPedBias spec P y y P y yog y P P 19 16 CALIBPMTSPEC 203 19 16 CalibPmtSpec Table specification source dybgaudi trunk Database DybDbi spec GCalibPmtSpec spec docstring name dbtype codetype description code2db PmtId int 11 int Describ varchar 27 string String of decribing PMT position Status tinyint 4 int Status check on the PMT SpeHigh float double Single photoelectron mean ADC value high gain SigmaSpeHigh float double Single p e 1 sigma peak width high gain SpeLow float double ADC per P E ratio for
114. bleMapFix spec Testing fix for dybsvn ticket 948 The Cable Map provides the data for lookups between a sensorID and a channelID The ID numbers are packed integers ready for consumption by the sensor classes from Detectors h and channel classes from Electronics h from the Conventions package This table handles sensors and electronics for PMTs AD and Pool and RPCs Read context must explicitly give Site SimFlag and DetectorId SubSite Write context must explicitly give SiteMask SimMask and SubSite name dbtype codetype description code2db SensorId int 11 DayaBay DetectorSensor Packed Sensor ID fullPackedData Channelld int 11 DayaBay ElecChannelld Packed Channel ID fullPackedData Table 19 6 DBI Table specification for class GCableMapFix which corresponds to table CableMap Shttp dayabay inep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCableMapFix spec 194 19 7 CalibFeeGainConv CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GCalibFeeGainConv spec docstring name dbtype codetype description Channelld int 11 DayaBay FeeChannelId unique id of this fee channel Status tinyint 4 int status of this gain ratio FineCoarseRatio float double gain ratio of fine over coarse adc FineCoarseRatioErr float double error of gain ratio FRLineSlope float double slope of partial linear fit to fine range FRLineErr float double error of fi
115. c 9 reconHdr evt Event Rec RecHeader 10 if reconHdr recResult energyStatus ReconStatus kGood BH Fill the histogram self stats file1 myhists energy Fill reconHdr recResult energy units MeV BH bo 3 4 NUWA RECIPES 41 Although these examples are simple algorithms can perform complex calculations on the data that are not possible directly from ROOT For cheat sheets of the data available in NuWa see the following sections Readout data 3 5 8 Calibrated hit data 3 5 9 Reconstructed data 3 5 11 Remember to commit your new algorithm to SVN The wiki section SVN_Repository Guidelines pro vides some tips on committing new software to SVN 3 4 9 Write a C analysis Algorithm A drawback of using Python algorithms is that they will usually run slower than an algorithm written in C If you wish to run your algorithm as part of data production or if you just want it to run faster then you should convert it to C Adding a C algorithm to Gaudi is a more complex task The first step is to create your own Project Your own Project allows you to write and run your own C analysis software with NuWa See section 3 5 3 for how to prepare this Once you have your own project you should prepare your own package for your new algorithm A tool has been provided to help you with this The following commands will set up your own package 1shell gt cd myNuWa 2shell gt svn export http dayabay ihep
116. c are supposed to give the biggest systematic uncertainty The vast majority of muons are very easy to identify due to its distinguishable characteristic in reality Usually its long trajectory in water pool or AD will leave a huge amount of light and different time pattern rather than a point source The simulation of muon in Geant4 is quite time consuming The hugh amount of optical photons propargation in detector usually over a few million can bring any computer to its knee One CPU has to spend 20 30 minutes for a muon track sometimes The real muon rate requires to simulate is a few hundred to a thousand per second In the end people realized that they only need to know whether a muon has passed the detector and tagged while not really care too much about how light are generated and distributed in water pool and AD Beside that it is technically impossible to finish all these muon simulation the physics model of radioative isotope s generation in Geant4 is not very reliable Photon nuclear process triggered by virturl or real photon pion nucleus interaction nucleon nucleus interaction etc are all possible be responsible to spallation background generation They are poorly described in Genat4 Tuning the generation rate of some background is very difficult since they are usually very low then it is very inefficient to do MC study Based on these consideration MuonProphet is designed so that the tiresome optical photon simulation can be
117. c 38http dayabay ihep dybsvn b dybgaudi k Database DybDbi spec GDcsWpPmtHv sp 226 CHAPTER 19 DATABASE TABLES 19 39 Demo Table specification source dybgaudi trunk Database DybDbi spec GDemo spec Simple Class Table for demonstration of DybDbi DBI features name dbtype codetype description code2db Gain double double demonstration double Id int 11 int demonstration identity Table 19 39 DBI Table specification for class GDemo which corresponds to table Demo 39 nttp dayabay ihnep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDemo spec 19 40 DEMOAGG 227 19 40 DemoAgg Table specification source dybgaudi trunk Database DybDbi spec GDemoA gg spec Simple Class Table for demonstration of DybDbi DBI features modified to be an aggregate type with some template handling for meta key aggrow Adding meta key aggrow Id to add the GetAggregateNo method which returns m_Id to provide th which must be 0 1 2 3 4 name dbtype codetype description code2db Gain double double demonstration double Id int 11 int demonstration identity Table 19 40 DBI Table specification for class GDemoAgg which corresponds to table DemoAgg http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDemoAgg spec 228 CHAPTER 19 DATABASE TABLES 19 41 DemoBit Table specification source dybgaudi trunk Dat
118. cache the user specifies a directory to which they have read write access For example to make the current working directory the cache theApp service DbiSvc Level2Cache Cache files all have the extension dbi_cache Not all tables are suitable for Level 2 caching the Databa selnterface will only cache the ones that are Cache files can be shared between users at a site to maximise the benefit In this case the local Database Manager must set up a directory to which the group has read write access Management is trivial should the cache become too large it can simply be erased and then the next few jobs that run will re populate it with the currently hot queries Note that Cache performance is achieved by doing raw binary I O so the cache files are platform specific so if running in a heterogeneous cluster the Database Manager should designate a platform specific directory To simplify this the name of the directory used by the cache can include environmental variables e g theApp service DbiSvc Level2Cache DBI_L2CACHE Output Level The verbosity of the error log from the Databaselnterface can be controlled by theApp service DbiSvc OutputLevel 3 The output levels are standard Gaudi levels 17 4 Accessing Existing Tables 17 4 1 Introduction To access database data the user specifies the database table to be accessed and supplies a context for the query The context describes t
119. change the properties through the TrigSimConf module as follows import TrigSim trigsim TrigSim Configure import TrigSim TrigSimConf as TsConf TsConf TsTriggerAlg TrigTools TsExternalTriggerTool The TrigTools property takes a list as an argument allowing multiple triggers to be specified Once implemented the user could apply multiple triggers as follows import TrigSim trigsim TrigSim Configure import TrigSim TrigSimConf as TsConf TsConf TsTriggerAlg TrigTools TsMultTriggerTool TsEsumTriggerTool TsCrossTriggerTool 14 CHAPTER 2 QUICK START 2 11 Readout The default setup for Readout Sim used the ROsFecReadoutTool and ROsFeeReadoutTool tools to do the FEC and FEE readouts respectivly The default setup is as follows import ReadoutSim rosim ReadoutSim Configure import ReadoutSim ReadoutSimConf as ROsConf ROsConf ROsReadoutAlg RoTools ROsFecReadoutTool ROsFeeReadoutTool ROsConf ROsFeeReadoutTool AdcTool ROsFeeAdcPeakOnlyTool ROsConf ROsFeeReadoutTool TdcTool ROsFeeTdcTool where the Fee will be read out using the tools specified via the TdcTool and AdcTool properties Cur rently the only alternate readout tool is the ROsFeeAdcMultiTool which readout the cycles specified in the ReadoutCycles relative to the readout window start The selection and configuration of this alternate tool 1S ROsConf ROsFeeReadoutTool AdcTool ROsFeeAdcMultiTool ROsCon
120. cification for class GCalibPmtHighGainFake which corresponds to table Cal ibPmtHighGainFake 12nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibPmtHighGainFake spec 200 19 13 CalibPmtHighGainPariah CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GCalibPmtHighGainPariah spec Handling of input table not conforming to SOP norms see dybsvn ticket 1228 name dbtype codetype description code2db Sensorld int 11 DayaBay DetectorSensor unique id of this pmt fullPacke SpeHigh float double SPE mean ADC value high gain SpeHighError float double error in SPE Mean ADC value high gain SigmaSpeHigh float double SPE 1 sigma peak width high gain SpeHighFitQual float double SPE fit quality in chi2 ndf high gain Table 19 13 DBI Table specification for class GCalibPmtHighGainPariah which corresponds to table Cal ibPmtHighGainPariah 135http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec P y y P y yog Hi P GCalibPmtHighGainPariah spec 19 14 CALIBPMTLOWGAIN 201 19 14 CalibPmtLowGain Table specification source dybgaudi trunk Database DybDbi spec GCalibPmtLowGain spec docstring name dbtype codetype description code2db Sensorld int 11 DayaBay DetectorSensor unique id of this pmt fullPackedDat SpeLow float double SPE mean ADC value low gain SpeLowError float double error
121. clearer Any number of statistics may be defined at the cost of run time during the simulation The statistics are filled as follows At each step of the simulation the current G4Step is tested against each EXPRESSION rule to see if the current step is valid for that statistic If it is then the VARIABLE is computed and the Statistic object is incremented with the value of the variable 11 3 4 Examples Tips Trucks Statistics are per step For example UnObserver Stats x_vertex global_x pdg 13 or pdg 13 will yield a statistic n entries where n is the number of steps taken by the muon with each entry being that step s global X coordinate However you can do something like the following UnObserver Stats x_vertex global_x pdg 13 or pdg 13 and IsStarting 1 which will select only the start points for muon tracks If you know that there will be at most one muon per event this will yield a statistic with one entry at the muon start vertex However this solution is not generally useful because a second muon in the event will confuse the issue all you will be able to retrieve is the mean X start position which is not usually informative For specific queries of this kind users are advised to use Particle Histories Users should fill out more useful examples here 11 3 5 Parameter Reference The Particle History parser and the Unobservable Statistics parser recognize the
122. cription RunNo int 11 int Run Number FileNo int 11 int File Number PmtId int 11 DayaBay DetectorSensor Packed PMT ID Status tinyint int Fitting Resutls Status Chi2ndf float double Chi2 ndf for gain fitting Gain float double Single photoelectron mean ADC value high gain GainErr float double Gain Error DarkRate float double Dark Rate DarkRateErr float double Dark Rate Error ElecNoiseRate float double Electronics Noise Rate ElecNoiseRateErr float double Electronics Noise Rate Error PreAdc float double Pre Adc PreAdcErr float double Pre Adc Error AdcMean float double Adc Mean AdcRMS float double Adc RMS TdcMean float double Tdc Mean TdcRMS float double Tdc RMS FlashingCounts int 11 int Flashing Counts DNCountsForced int 11 int Dark Noise Counts Calculated from Forced Trigger Quality tinyint int Quality Flag for a Pmt Channel Table 19 49 DBI Table specification for class GDqPmt which corresponds to table DqPmt 49nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDgPmt spec 19 50 DQPMTNEW 237 19 50 DqPmtNew Table specification source dybgaudi trunk Database DybDbi spec GDqPmtNew spec docstring name dbtype codetype description RunNo int 11 int Run Number FileNo int 11 int File Number Channelld int 11 DayaBay FeeChannelld Unique id of the channel connected to a pmt Status tinyint int Fitting Resutls Status Chi2ndf float double Chi2 ndf for gain fitting Gain float double Sin
123. cs SAB AD2 SFO 1 _0001 root oonan e 3 5 7 Conventions and Context The following sections summarizes the conventions for sites detectors software root y and other items used in the analysis Sites The site ID identifies the site location within the experiment Site C Python Name Number Description Unknown kUnknown 0x00 Undefined Site Daya Bay kDayaBay 0x01 Daya Bay Near Hall EH 1 Ling Ao kLingAo 0x02 Ling Ao Near Hall EH 2 Far kFar 0x04 Far Hall EH 3 Mid kMid 0x08 Mid Hall Doesn t exist Aberdeen kAberdeen 0x10 Aberdeen tunnel SAB kSAB 0x20 Surface Assembly Building PMT Bench Test kPMTBenchTest 0x40 PMT Bench Test at Dong Guan All kAll Logical OR of all sites All sites To access the site labels from Python you can use the commands 1from GaudiPython import gbl 2gbl DayaBay Detector Access any class in library 3Site gbl Site 4print Site kDayaBay For C the site labels can be accessed 1 include Conventions Site h 2std cout lt lt Site kDayaBay lt lt std endl The Site convention is defined in DataModel Conventions Conventions Site h Detectors The detector ID identifies the detector location within the site 12http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk DataModel Conventions Conventions Site h 48 CHAPTER 3 ANALYSIS BASICS Detector C Python Name Number Description Unknown kUnknown 0 Undefined De
124. ctly needed but will help understand the big picture 8 5 1 Execution Cycle vs Event Daya Bay does not have a well defined concept of event Some physics interactions can lead overlapping collections of hits and others can trigger multiple detectors To correctly simulate this reality it is required to allow for multiple results from an algorithm in any given run through the chain of algorithms This run is called a top level execution cycle which might simplify to an event in other experiments 8 5 2 Registration Sequence In order to record this additional dimension to our data we use a class called RegistrationSequence RS There is one RS created for each execution cycle Each time new data is added to the event store it is also recorded to the current RS along with a unique and monotonically increasing sequence number or index The RS also hold flags that can be interpreted later In particular it holds a flag saying whether or not any of its data should be saved to file These flags can be manipulated by algorithms in order to implement a filtering mechanism Finally the RS like all data in the analysis time window has a time span It is set to encompass the time spans of all data that it contains Thus RS captures the results of one run through the top level algorithms 2FIXME This needs to be described in the Data Model chapter and a reference added here 8 6 ADDING NEW DATA CLASSES 83 8 5 3 Writing data out
125. cycle They may take input from the TES and may produce output They are meant to encapsulate complexity in a way that allows them to be combined in a high level manner They can be combined in a serial chain to run one by one or they can run other algorithms as sub algorithms It is also possible to set up high level branch decisions that govern whether or not sub chains run 6 3 2 Tools Tools contain utility code or parts of algorithm code that can be shared Tool instances can be public in which case any other code may use it or they may be private Multiple instances of a private tool may be created A tool may be created at any time during a job and will be deleted once no other code references it 6 3 3 Services Service is very much like a public tool of which there is a single instance created Services are meant to be created at the beginning of the job and live for its entire life They typically manage major parts of the framework or some external service such as a database 6 4 Writing your own component 6 4 1 Algorithms One of the primary goals of Gaudi is to provide the concept of an Algorithm which is the main entry point for user code All other parts of the framework exist to allow users to focus on writing algorithms An algorithm provide three places for users to add their own code 1Nick names default to the class name 6 4 WRITING YOUR OWN COMPONENT 69 initialize This method is called once at the beginnin
126. d e Upon construction in _init_ provide a sensible if maybe incomplete default configuration for the general features the package provides e Store any and all configurables it creates in the instance Python s self variable for the user to later access In addition the package author is encouraged to provide one or more helper classes that can be used to simplify non default configuration Helper objects can either operate on the Configure object or can be passed in to Configure or both To see an example of helpers are written look at 1 SITEROOT dybgaudi InstallArea python GenTools Helpers py Package authors should write these classes and all higher layers may make use of these classes 6 5 PROPERTIES AND CONFIGURATION 73 6 5 4 User Job Option Scripts The next layer consists of job option scripts These are short Python scripts that use the lower layers to provide non default configuration that makes the user s job unique However these are not main program files and do not execute on their own see next section Users can configure an entire job in one file or spread parts of the configuration among multiple files The former case is useful for bookkeeping and the latter is if the user wants to run multiple jobs that differ in only a small part of their configuration In this second case they can separate invariant configuration from that which changes from run to run An example of a job script using the
127. d go in PerXxx src lib All converter files should go in PerXxx src components See the PerGenHeader package for example 8 6 2 Guidelines for Writing Persistent Data Classes In writing such classes follow these guidelines which differ from normal best practices 3This is actually done in Root lOTest DybStorageAlg 84 CHAPTER 8 DATA I O Do not include any methods beyond constructors destructors Make a default constructor no arguments as well as one that can set the data members to non default values Use public and not private data members Name them with simple but descriptive names Don t decorate them with m f or other prefixes traditionally used in normal classes 8 6 3 Steps to Follow 1 10 11 12 Your header class should inherit from PerHeaderObject all sub object should in general not inherit from anything special Must provide a default constructor convenient to define a constructor that passes in initial values Must initialize all data members in any constructor Must add each header file into dict headers h file file name must match what is in requirements file below Must add a line in dict classes xml for every class and any STL containers or other required instan tiated templates of these classes If the code crashes inside low level ROOT I O related T classes it is likely because you forgot to declare a class or template in classes xml Run a RootIOTest scrip
128. data files This section provides a short description of the nuwa py program Job Modules and analysis algorithms This is followed by a series of recipes for common analysis tasks 3 3 1 The nuwa py Command The nuwa py command is the main command to use the Daya Bay analysis software A command has a structure similar to 1shell gt nuwa py n lt numberO0fEntries gt m lt Module gt lt inputFile gt A complete list of options is given in Sec An example is 1shell gt nuwa py n 100 m Quickstart PrintRawData daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root In this simple example the first 100 triggered readouts are read from the input file and their data is printed to the screen The n option specifies the number of entries to process The n 1 option will process all events in the input file s The m option specifies how the job should be configured Sec 3 3 2 discusses job configuration using Job Modules An arbitrary number of input files can be given and will be processed in sequence 1shell gt nuwa py n lt numberO0fEntries gt m lt Module gt lt inputFilei gt lt inputFile2 gt The o option can be used to write the event data to a NuWa output file 1shell gt nuwa py n lt number0fEntries gt m lt Module gt o lt outputFile gt lt inputFile gt Some other useful options are e no history Do not print out job configuration information to the screen e 1 n Set the minim
129. data to any temporary database for it could end up being used by anyone who includes the database for temporary tables Database managers may delete any permanent tables in temporary databases without warning in order to prevent such problems 17 6 7 Clearing the Cache Normally you would not want to clear the cache after all its there to improve performance However if you have just created a temporary table as described above and it replaces an existing table then clearing the cache is necessary to ensure that future requests for data are not satisfied from the now out of date cache Another reason why you may want to clear the cache is to study database I O performance Although this section is entitled Clearing the Cache you cannot actually do that as the data in the cache may already be in use and must not be erased until its clients have gone away Instead the data is marked as stale which is to say that it will ignored for all future requests Further you don t clear the entire cache just the cache associated with the table that you want to refresh Each table is managed by a DbiTableProxy that owns a DbiCache Both DbiWriter and DbiResultPtr have a TableProxy method to access the associated DbiTableProxy The following code fragment shows how to set up a writer and mark its associated cache as stale DbiWriter lt DbiDemoDatal gt writer range aggNo writer SetDbNo dbNoTemp writer TableProxy GetCache gt SetStale 176
130. dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GPhysAd spec 248 CHAPTER 19 DATABASE TABLES DCS DAQ Offline DAQ_ID Offline_ID AD1 AD1 AD1 0x01 0x01 AD2 AD2 AD2 0x02 0x02 AD3 AD3 AD3 0x03 0x03 AD4 AD4 AD4 0x04 0x04 IWP WPI IWS 0x05 0x05 OWP WPO OWS 0x06 0x06 RPC RPC RPC 0x07 0x07 Muon GAS PMT FEE SIS name dbtype codetype description code2db PhysAdId tinyint int ID of physical AD counts 1 to 8 Table 19 60 DBI Table specification for class GPhysAd which corresponds to table PhysAd 19 61 QSUMCALIB 249 19 61 QSumCalib Table specification source dybgaudi trunk Database DybDbi spec GQSumCalib spec Calibration constant for QSum Reconstruction name dbtype codetype description code2db PeYield float double PE yield per MeV Uncertainty float double uncertainty of PE yield Table 19 61 DBI Table specification for class GQSumCalib which corresponds to table QSumCalib Slnttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GQSumCalib spec 250 19 62 SimPmtSpec CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GSimPmtSpec spec docstring name dbtype codetype description code2db PmtId int 11 DayaBay DetectorSensor PMT sensor ID sensorld Describ varchar 27 string String of decribing PMT position Gain float double Relative gain for pmt mean 1 SigmaGain float double 1 sigma spr
131. dified and replaced Under MuonProphet src components MpGe ometry cc is dedicated to geometry related calculation MpTrigger cc is for trigger prediction MpNeutron cc and MpSpallation cc handle the production of neutron and other isotopes respectively All of them are controlled by MuonProphet mutate like a usual gentool It will make use of other radioactive background generators so no need for extra code development 10 7 4 Configuration Here one example is given for 9Li or 8He background configuration It will create a gentool prophet This tool should be attached after muon GtPositionerTool GtTimeratorTool and GtTransformTool like demonstrated in MuonProphet python MuonProphet FastMuon py According the formulas in DocDB 4153 DocDB 4441 a set of four parameters including a gentool for an isotope background yield the energy where the yield is measured and lifetime must supplied Following is a snippet of python code from FastMuon py showing how it is configured muonprophet prophet MuonProphet prophet Site DayaBay spallation background The tool to generate 9Li or 8He background According to the formula refered in DocDB 4153 DocDB 4441 every isotope need a set of four parameters prophet GenTools Li9He8Decayerator Li9He8 There is a measurement of yield 2 2e 7 cm2 g for 260 GeV muon then we can extrapolate the yield to other energy point prophet GenYi
132. e writer lt lt row0 writer lt lt rowl writer lt lt row2 DbiWriter calls the table row s Store method see the next section It also performs some basic sanity checks The row s aggregate number matches its own The type of the data written is compatible with database table If either check fails then an error message is output and the data marked as bad and the subsequent Close method will not produce any output 17 6 FILLING TABLES 173 e Once all rows for the current aggregate have been passed to DbiWriter the data can be output using Bool_t Close which returns true if the data is successfully output Alternatively you can write out the data as a DBMauto update file by passing the name of the file to the Close command Close my_dbmauto_update_file dbm e On output a new sequence number is chosen automatically By default if writing permanent data to an authorising database or if writing to a file a global sequence number will be allocated In all other cases a local sequence number will be be used For database I O as opposed to file I O you can change this behaviour with void SetRequireGlobalSeqno Int_t requireGlobal Where requireGlobal gt 0 Must be global 0 Must be global if writing permanent data to an authorising database lt 0 Must be local e At any time before issuing the Close command you can cancel the I O by either Destroying the DbiWriter Using
133. e ENV_TSQL_UPDATE_ set for write access Note that the job switches take priority over everything else To run just type dbmjob dbmjob enters interactive mode For help type Help and to quit type Quit The following illustrate simple exporting and importing For more detail consult the Help command Exporting Data dbmjob always exports data from the first database in the cascade To export data use the Export command The syntax is Export Since lt date gt lt table gt lt file gt This exports the contents of lt table gt into lt file gt which can subsequently be imported into another database using the Import command lt table gt can be a specific table e g PlexPixelSpotToStripEnd or for all tables For example 18 2 BUILDING AND RUNNING DBMJOB 185 Export full_backup dat Export since 2001 09 27 12 00 00 PlexPixelSpotToStripEnd update dat The first updates the entire database whilst the second just records updates to PlexPixelSpot ToStripEnd since midday on the 27 September 2001 Importing Data By default dbmjob always imports into the first database in the cascade but this can be overridden To Import data use the Import command The syntax is Import Test DatabaseNumber lt no gt lt file gt This imports the contents lt file gt into the database The insertion dates in the file s validity records are replaced by the current date and time so that the insertion dates in the database re
134. e data beyond requiring that it be in sequence number order When an ordering is not imposed the database server is under no obligation to return data in a particular order This means that the same job running twice connected to the same database could end up with result sets that contain the same data but with different ordering Normally this doesn t matter the ordering of rows is not significant However results from two such jobs may not be identical as floating point calculations can change at machine level precision if their ordering is changed There are situations where it is required that the results be identical For example 156 CHAPTER 17 DATABASE e When bug hunting e When checking compatibility between two databases that should be identical and for such occasions it is possible to completely specify the ordering of rows within a sequence number by forcing sub ordering by ROW_COUNTER a column that should be present in all Main Data tables theApp service DbiSvc OrderContextQuery true Level 2 Cache Enabling the Level 2 Cache allows certain large tables query results to be written to disk from which they can be reloaded by subsequent jobs saving as much as an order of magnitude in load time Data in the cache will not prevent changes in the database from taking affect for the Databaselnterface does an initial lightweight query of the database to confirm that the data in the cache is not stale To enable the
135. e description code2db LocationId char 6 string PMT Location ID Voltage float float PMT Voltage Table 19 33 DBI Table specification for class GDcsAdWpHv which corresponds to table DcsAdWpHv 33nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDcsAdWpHv spec 19 34 DCSADWPHVSHUNTED 221 19 34 DcsAdWpHvShunted Table specification source dybgaudi trunk Database DybDbi spec GDcsAdWpHvShunted spec 4 PMT High Voltage monitoring table mysql amp gt describe DcsAdWpHv 4 Field Type Null Key Default Extra 4 SEQNO int 11 NO PRI NULL l ROW_COUNTER int 11 NO PRI NULL LocationId char 6 YES NULL Voltage float YES NULL name dbtype codetype description code2db LocationId char 6 string PMT Location ID Voltage float float PMT Voltage Table 19 34 DBI Table specification for class GDcsAdWpHvShunted which corresponds to table DesAdW pHvShunted 34nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDcsAdWpHvShunted spec 222 CHAPTER 19 DATABASE TABLES 19 35 DcsMuonCalib Table specification source dybgaudi trunk Database DybDbi spec GDcsMuonCalib spec
136. e first database in the ENV_TSQL_URL dummy CreateDatabaseTables db In outline the filling procedure is as follows 1 Decide the validity range of the data to be written and store it in a ContextRange object 2 Instantiate a DbiWriter object using this ContextRange object together with an aggregate number and task Aggregate numbers are discussed below 3 Pass filled DbiTableRow sub class objects e g DbiDemoData1 to the DbiWriter It in turn will send these objects their Store message that performs the inverse of the Fill message DbiWriter caches the data but performs no database I O at this stage 4 Finally send the DbiWriter its Close message which triggers the output of the data to the database The fact that I O does not occur until all data has been collected has a couple of consequences e It minimises the chances of writing bad data If you discover a problem with the data while DbiWriter is assembling it you use DbiWriter s Abort method to cancel the I O Likewise if DbiWriter detects an error it will not perform output when Close is invoked Destroying a DbiWriter before using Close also aborts the output e Although DbiWriter starts life as very lightweight it grows as the table rows are cached Be very sure that you delete the DbiWriter once you have finished with it or you will have a serious memory leak To cut down the risk of a memory leak you cannot copy construct or assign to DbiWriter objects 170 CHAPTE
137. e installed as described docs After this the Sphinx documentation can be build with 1 v docs bin activate tt v docs path points to where the docs virtualpython is created 2cd SITEROOT dybgaudi Documentation OfflineUserManual tex 3make 1See chapter 6 http dayabay bn1 gov oum docs 2 CHAPTER 1 INTRODUCTION 1 5 Typographical Conventions This is bold text Chapter 2 Quick Start This chapter holds brief quick start information about each major offline software element 4 CHAPTER 2 QUICK START 2 1 Offline Infrastructure 2 2 INSTALLATION AND WORKING WITH THE SOURCE CODE 5 2 2 Installation and Working with the Source Code 2 2 1 Installing a Release 1 Download dybinst 2 Runit dybinst RELEASE all The RELEASE string is trunk to get the latest software or X Y Z for a numbered release The wiki topic Category Oflline_Software_Releases documents avilable releases 2 2 2 Using an existing release The easiest way to get started is to use a release of the software that someone else has compiled for you Each cluster maintains a prebuilt release that you can just use See the wiki topic Getting Started With Offline Software for details 3 2 2 3 Projects A project is a directory with a cmt project cmt file Projects are located by the CMTPROJECTPATH environ ment variable This variable is initialized to point at a released set of projects by running 1 shell gt cd path to NuWa RELEAS
138. e nonuniformity parameter 4 Table 19 53 DBI Table specification for class GEnergyPositionCorr which corresponds to table EnergyPo sitionCorr 53http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GEnergyPositionCorr spec 19 54 ENERGYRECON 241 19 54 EnergyRecon Table specification source dybgaudi trunk Database DybDbi spec GEnergyRecon spec docstring name dbtype codetype description code2db PeEvis float double pe per mev value PeEvisUnc float double pe per mev uncertainty Table 19 54 DBI Table specification for class GEnergyRecon which corresponds to table EnergyRecon 54nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GEnergyRecon spec 242 19 55 FeeCableMap CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GFeeCableMap spec Data members field by the codetype column of instances of the generated class use codetype API ref DayaBay FeeChannelId py class DybDbi DayaBay FeeHardwareld py class DybDbi DayaBay DetectorSensor lt py class DybDbi DayaBay PmtHardwareld py class DybDbi specialized types which are specified for each defined FeeChannelld conventions Electronics h FeeHardwareld conventions Hardware h DetectorSensor conventions Detectors h i PmtHardwareld
139. e to memory triggers loading all the data it referenced The TES and thus AES are now back to the state they were in when the RS was written to file in the first place 8 6 Adding New Data Classes For the I O subsystem to support new data classes one needs to write a persistent version of the transient class and a converter class that can copy information between the two 8 6 1 Class Locations and Naming Conventions The persistent data and converters classes are placed in a package under RootI0 named with the prefix Per plus the name of the corresponding DataModel package For example DataModel GenEvent gt RootI0 PerGenEvent Likewise the persistent class names themselves should be formed by adding Per to the their tran sient counterparts For example GenEvent s GenVertex transient class has a persistent counterpart in PerGenEvent with the name PerGenVertex Finally one writes a converter for each top level data class that is a subclass of DataObject with a unique Class ID number and the converters name is formed by the transient class name with Cnv appended For example the class that converts between GenHeader and PerGenHeader is called GenHeaderCnv The Per package should produce both a linker library holding data classes and a component library holding converters As such the data classes header h files should go in the usual PerXxx PerXxx subdirectory and the implementation cc files shoul
140. e total charge within 1650 and 1250 of PMTs for the rest of columns other t I time_PSD 1 time_PSD1 Q3 Q2 2 nPEMax nPESum time_PSD local The charge sum in time window tj 1650ns The charge sum in time window t 1250ns The charge sum in time window 1650nsjtj 1250ns See Doc6926 The largest charge fraction of PMTs The ring number of the MaxQ PMT The column number of the MaxQ PMT Total charge of PMTs with column number in maxqCol 2 maxqCol 3 For the gt Total charge of PMTs with column number in maxqCol 6 2 maxqCol 6 3 Total Charge of PMTs with column number in maxq 12 2 maxqCol 12 3 Total Charge of PMTs with column number in maxq 18 2 maxqCol 18 3 The ratio of QuadrantQ3 QuadrantQ2 QuadrantQ4 According to the location of MaxQ PMT divide 24 columns into two clusters Mai See description in MainPeakRMS The sum of MainPeakRMS and SecondPeakRMS Kurtosis of charge weighted distance in the Ring dimension for the MainPeak clust Kurtosis of charge weighted distance in the Column dimension for the MainPeak cl Sum of RingKurtosis and ColumnKurtosis RMS of PMT first hit time in the time window 1650ns 1250ns This time wind DAQ Running time from the start of the file up to the current trigger DAQ Livetime from the start of the file up to the current trigger The DAQ Live DAQ Livetime using an alternate correction for blocked trigger periods A count of the blocked trigge
141. eDraw C ROOT script using TTree Draw e dybTreeGetLeaf C ROOT script using TTree GetLeaf e dybTreeSetBranch C ROOT script using TTree SetBranchAddress e dybNuWaHist py NuWa algorithm using the complete data classes The example dybTreeDraw C is the simplest approach it is recommended that you try this method first when generating your histograms If you plan to include your algorithm as part of standard data production you will eventually need to use a NuWa algorithm such as dybNuWaHist py The other two methods are only recommended for special circumstances A detailed description of the advantages and disadvantages of each approach are provided in the following sections 2http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Tutorial Quickstart 3 2 DAYA BAY DATA FILES 27 dybTreeDraw C This is the easiest approach and usually requires the least programming Please consider using this approach first if possible Advantages Simple to run Requires the least programming e Easy for others to understand and reproduce e Allows chaining and friending of data files Disadvantages e Slower when you need to make many histograms e Some cuts or variables cannot be expressed in a draw command e No access to geometry database other external data e Cannot be integrated with production analysis job To run this example use the following approach 1 root 0 L dybTreeDraw C 2 root 1 dybTreeDraw recon roo
142. ead of S P E response TimeOffset float double Relative transit time offset TimeSpread float double Transit time spread Efficiency float double Absolute efficiency PrePulseProb float double Probability of prepulsing AfterPulseProb float double Probability of afterpulsing DarkRate float double Dark Rate Table 19 62 DBI Table specification for class GSimPmtSpec which corresponds to table SimPmtSpec 62http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GSimPmtSpec spec 19 63 SUPERNOVATRIGGER 19 63 SupernovaTrigger 251 Table specification source dybgaudi trunk Database DybDbi spec GSupernovaTrigger spec Supernova Trigger Table DocDB 8854 rubric Detector convention in Offline and AdNo we define AD name fullPackedData AdNo DayaBayAD1 16842752 1 DayaBayAD2 16908288 2 LingAoAD1 33619968 3 LingAoAD2 33685504 4 FarAD1 67174400 5 FarAD2 67239936 6 FarAD3 67305472 7 FarAD4 67371008 8 name dbtype codetype description detector int 11 DayaBay Detector source dybgaudi trunk DataModel Conventions Conventions Detec runNo int 11 int physics run number fileNo int 11 int raw data file number of a certain physics run pTriggerNo int 11 int prompt signal trigger number pEnergy double double prompt signal energy MeV after a simple recon pTime_s int 11 int prompt signal time stamp sec pTime_nano int 11 int prompt signal time stamp nano pVertex_x double double prompt signal vertex x pos
143. ect could then provide a calibration service Float_t Calibrate Float_t rawValue const 17 6 FILLING TABLES 169 rather than expose parm0 Calibrate would have code that tests the value of CalibForm and then uses the appropriate formula involving parm0 Of course some validation code will want to look at the quality of the calibration by looking at the calibration constants themselves but this too could be abstracted into a set of values that hide the details of the form of the calibration However it is strongly advised to make the raw table values available to the user 17 6 Filling Tables 17 6 1 Overview Databaselnterface can be used to write back into any table from which it can read To do this you need the services of a DbiWriter which is a templated class like DbiResultPtr For example to write DbiDemoDatal rows you need an object of the class DbiWriter lt DbiDemoDatal gt DbiWriter only fills tables it does not create them Always create new tables with mysql before attempting to fill them If you want to create the tables within the same job as the one that fills it then you can do so as follows Create a single instance of the database row and use it to prime the database This needs only be done once It will do nothing if the tables already exist MyRowClass dummy Inherits from DbiTableRow int db 0 DB number If 0 this data is put into the first database in the cascade i e th
144. ectly For details see the README org file under 1cgcmt LCG_builders directory Some details are given for specific builders data A select sampling of data files are installed under the data external package These are intended for input to unit tests or for files that are needed as input but are too large to be conveniently placed in SVN For the conventions that must be followed to add new files see the comments in the data cmt requirements file under the builder area 2http git or cz Chapter 6 Offline Framework 6 1 Introduction When writing software it is important to manage complexity One way to do that is to organize the software based on functionality that is generic to many specific although maybe similar applications The goal is to develop software which does everything except those specific things that make the application unique If done well this allows unique applications to be implemented quickly and in a way that is robust against future development but still flexible to allow the application to be taken in novel directions This can be contrasted with the inverted design of a toolkit Here one focuses on units of functionality with no initial regards of integration One builds libraries of functions or objects that solve small parts of the whole design and after they are developed find ways to glue them all together This is a useful design particularly when there are ways to glue disparate toolkit
145. eger is currently given to store each time scale While providing absolute time they are not suitable for recording times to a precision less than 1 ns TimeStamp objects can be implicitly converted to a double but will suffer a loss of precision of 100s of usec when holding modern times 7 2 2 Relative Time Relative times simply count seconds from some absolute time and are stored as a double 7 2 3 Reference times Each HeaderObject holds an absolute reference time as a TimeStamp How each is defined depends on the algorithms that produced the HeaderObject Sub object precision times Some HeaderObjects such as SimHeader hold sub objects that need precision times eg SimHits These are stored as doubles and are measured from the reference time of the HeaderObject holding the sub objects 7 2 4 Time Extents Each Temporal0bject and thus each HeaderObject has a time extent represented by an earliest TimeS tamp followed by a latest one These are used by the window based analysis window implemented by the Archive Event Store to determine when objects fall outside the window and can be purged How each earliest latest pair is defined depends on the algorithm that produced the object but are typically chosen to just contain the times of all sub objects held by the HeaderObject 7 2 5 How Some Times are Defined This list how some commonly used times are defined The list is organized by the top level Data0Dbject where you may find the
146. elds 2 2e 7 units cm2 units g prophet GenYieldMeasuredAt 260 units GeV The lifetime of them is set to 0 002 second prophet GenLifetimes 0 002 units s trigger related configuration Any muon track with a track length in water above 20 cm will be tagged as triggered prophet TrkLengthInWaterThres 20 units cm We can also assign a trigger efficiency even it passed above track length cut prophet WaterPoolTriggerEff 0 9999 10 7 5 Output Geant4 will skip the muon simulation and do full simulation for neutron and other isotopes The rest of the simulation chain in Fifteen is set up to be able to respond that correctly Electronic simulation will only simulate the hits from spallation background and only pass a empty ElecHeader for the muon to the next simulation stage If muon is tagged triggered then trigger simulation will pop out a trigger header for the muon otherwise it will be dropped there like the real system In the final output of readout stream user should expect the following situations a Only muon is triggered There will be an empty ReadoutHeader for muon User can trace back to the original GenHeader to confirm the situaion b Only spallation background is triggered c Both muon and background induced by this muon are triggered There will be a empty ReadoutHeader for muon and another one with hits for the background d No trigger 10 7 MUONPROPHET 103 In reality if there is something
147. eleases NuWa trunk opt NuWa trunk 3shell gt source setup sh 4shell gt cd dybgaudi DybRelease cmt 5shell gt source setup sh 1 c shell 2shell gt cd common dayabay releases NuWa trunk opt NuWa trunk 3shell gt source setup csh 4shell gt cd dybgaudi DybRelease cmt 5shell gt source setup csh 3 5 2 Installing the NuWa software For the brave you can attempt to install NuWa on your own computer Try the following ishell gt mkdir nuwa 2shell gt cd nuwa 3shell gt svn export http dayabay ihep ac cn svn dybsvn installation trunk dybinst dybinst 4shell gt dybinst trunk all If you are very lucky it will work Otherwise send questions to theta13 offline dayabay 1b1 gov Your chance of success will be much greater if your try to install NuWa on a computer running Scientific Linux or OS X 3 5 3 Making your own Project If you want add or modify a part of NuWa you should create your own Project This will allow you to create your own packages to add or replace those in NuWa The first step is to create a subdirectory for your packages in some directory path to myProjects 1shell gt mkdir p path to myProjects myNuWa cmt Create two files under myNuWa cmt with the following content 1shell gt more project cmt 2project myNuWa 3 4use dybgaudi 5 6build_strategy with_installarea 7structure_strategy without_version_directory 8setup_strategy root 1shell gt more version cmt 2v0 3 5 CH
148. elected source in ACU C is at home Table 19 23 DBI Table specification for class GDaqCalibRunInfo which corresponds to table DaqCalibRun Info 23http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDaqCalibRunInfo spec P y y P y yog y P ql P 19 24 DAQRAWDATAFILEINFO 211 19 24 DaqRawDataFilelInfo Table specification source dybgaudi trunk Database DybDbi spec GDaqRawDataFilelnfo spec docstring name dbtype codetype description code2db RunNo int 10 unsigned int FileNo int 10 unsigned int FileName tinytext string StreamType varchar 32 string Stream varchar 32 string FileState varchar 32 string FileSize int 11 int CheckSum varchar 64 string TransferState varchar 32 string Table 19 24 DBI Table specification for class GDaqRawDataFileInfo which corresponds to table DaqRaw DataFileInfo 24nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDaqRawDataFileInfo spec 212 CHAPTER 19 DATABASE TABLES 19 25 DaqRunInfo Table specification source dybgaudi trunk Database DybDbi spec GDaqRunInfo spec docstring name dbtype codetype description code2db RunNo int 11 int TriggerType bigint 20 int RunType varchar 32 string DetectorMask int 11 int PartitionName varchar 255 string SchemaVersion int 11 int DataVersion int 11 int BaseVersion int 11 int Table 19 25 DBI Table specificati
149. er Keep Event Rec AdSimple Event Rec AdQmlf 2 o myRecData NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3 recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3 4 6 Write Tagged Data to a New File There may be situations where you would like to filter only some events to a smaller data file The SmartFilter package provides some tools for this purpose The first step is to define your own tag for the events you wish to keep as discussed in section 3 4 2 The following example shows how to create an output file which contains only the events you have tagged as MySpecialEvents 1shell gt nuwa py n 1 m MySpecialTagger m SmartFilter Keep Event UserTag MySpecialEvents 2 o mySpecialEvents NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3 recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root The output file will contain your tag Event UserTag MySpecialEvents plus any data that your tag refers to such as Event Rec AdSimple Event Readout ReadoutHeader etc To create more advanced data filters copy and modify the job module Filtering SmartFilter python S martFilter Example py 3 4 7 Change an Existing Job Module This section describes how to change an existing module with name PACKAGE MODULE First copy this Job Module to your local directory You can locate a module using the environment variable PACKAGE ROOT 1shell gt mkdir mywork 2shell gt cd mywork 3shell gt cp lt PACKAGE gt ROOT pytho
150. erObject There is one special class in each package which inherits from HeaderObject All other objects that a pro cessing stage produces will be held directly or indirectly by the HeaderObject for the stage HeaderObjects also hold a some book keeping items such as TimeStamp giving a single reference time for this object and any subobjects it may hold See below for details on what kind of times the data model makes use of Execution Number counts the number of times the algorithm s execution method has been called starting at 1 This can be thought of as an event number in more traditional experiments Random State holds the stage of the random number generator engine just before the algorithm that produced the HeaderObject was run It can be used to re run the algorithm in order to reproduce and arbitrary output Input HeaderObjects that were used to produce this one are referenced in order to determine providence Time Extent records the time this data spans It is actually stored in the TemporalData0bject base class 77 78 CHAPTER 7 DATA MODEL 7 2 Times There are various times recorded in the data Some are absolute but imprecise integral number of ns and others are relative but precise sub ns 7 2 1 Absolute Time Absolute time is stored in TimeStamp objects from the Conventions package under DataModel They store time as seconds from the Unix Epoch Jan 1 1970 UTC and nanoseconds w in a second A 32 bit int
151. eral helper classes to assist in configuring GenTools They 12 assume geometry has already been setup The helper classes that 3 produce tools need to define a tools method that returns an 4 ordered list of what tools it created Users of these helper classes 5 should use them like 6 7 CLASSES 8 Gun 19 HepEVT 20 28 21 22shell gt pydoc GenTools Helpers Gun 23Help on class Gun in GenTools Helpers 24 25GenTools Helpers Gun class Gun 26 Configure a particle gun based kinematics 27 28 Methods defined here 29 30 31 32 33 34 35 36 37 38 39 40 41 42 74 CHAPTER 6 OFFLINE FRAMEWORK s Mt self Construct the configuration Coustom configured tools can be passed in or customization can be done after construction using the data members gun positioner timerator transformer The GtGenerator alg is available from the generatorAlg member They can be accessed for additional direct configuration 43 6 5 5 User Job Option Modules A second complimentary high level configuration method is to collect lower level code into a user job module These are normal Python modules and as such are defined in a file that exist in the users current working in the packages python sub directory or otherwise in a location in the user s PYTHONPATH Any top level code will be evaluated as the module is imported in the context of configuration same as job option scripts But these modu
152. erfaces CLHEP Vx LCG_Interfaces PerBaseEvent vx RootI0 1 public code 2include_dirs PERGENEVENTROOT 3apply_pattern install_more_includes more PerGenEvent 4library PerGenEventLib lib x cc 1sapply_pattern linker_library library PerGenEventLib 7 component code 8library PerGenEvent components x cc 8 6 ADDING NEW DATA CLASSES 19apply_pattern component_library library PerGenEvent 20 21 22 dictionary for persistent classes 23apply_pattern reflex_dictionary dictionary PerGenEvent 24 headerfiles PERGENEVENTROOT dict headers h 25 selectionfile dict classes xml 89 Chapter 9 Detector Description 9 1 Introduction The Detector Description or DetDesc for short provides multiple partially redundant hierarchies of information about the detectors reactors and other physical parts of the experiment The description has three main sections Materials defines the elements isotopes and materials and their optical properties that make up the de tectors and the reactors Geometry describes the volumes along with their solid shape relative positioning materials and sensitivity and any surface properties making up the detectors and reactors The geometry like that of Geant4 consists of logical volumes containing other placed or physical logical volumes Logical volumes only know of their children Structure describes a hierarchy of distinct placed touchable volumes Geant4 nomenclature also kn
153. es the raw data that is accessible directly from ROOT All ROOT variables must be preceded by daqPmtCrate trigger type triggerType trigger time triggerTime GetSeconds TDC time tdes board connector adcGain values ADC charge adcs board connector adcGain values gains board connector values preAdcRaws board connector adcGain values Channel pre ADC raw values peaks board connector adc Gain values Clock cycle in 25ns of ADC peak relative to TDC hit Item ROOT Variable Description site detector site Site ID number detector detector detectorld Detector ID number All active triggers logically OR d Complete trigger time seconds Channel TDC values Channel ADC values Channel ADC Gain 1 Fine ADC 2 Coarse ADC DetectorId h 3http ayabay ihep ac cn tracs svn browser audi trun ataMode onventions Conventions 13http dayabay ihep dybsvn b dybgaudi k DataModel1 C Fis OANOTREWNHrRFOHOAN OU PWN A e A A A Fe FwWwwWwwwwwwnwnwn nn ndnnnnnyp Now PpWwNrF TOKO AN AA PWwNHRrRF TOK AN AA PWN rH OC 48 3 5 CHEAT SHEETS 49 Readout data in NuWa Here is a cheat sheet for processing raw data in Python These lines can be used in the execute function of a Python algorithm evt self evtSvc Access the Readout Header This is a container for the readout data readoutHdr evt Event Readout ReadoutHeader if readoutHdr None self error Failed
154. es the user has grouped his and and or operators correctly Because these selections are applied to every single G4Track and every single G4Step having efficient selection improves simulation time After compilation selection is evaluated in the same order as provided by the user left to right Efficient selection is obtained if the user puts the easiest to compute parameters early in the selection The slowest parameters to evaluate are those that derive from DetectorElement including NichelD Niche DetectorId Siteld Site AD AdNumber local_ xyz DetectorElementName etc The fastest parameters are those that are already in the G4 data structures such as particle code IDs energy global position etc String comparisons are of medium speed 11 3 2 Examples Tips Tricks Choosing specific particle types is easy For instance the following selects all particles except for optical photons This is an excellent use case for low energy events like IBD lhistorian TrackSelection pdg 20022 112 CHAPTER 11 DETECTOR SIMULATION Here is a brief list of the more important PDG codes A complete list can be found at the PDG website e 11 pr 13 y 22 optical photon 20022 neutron 2112 proton 2212 n 111 T 211 This example will save all tracks that are not optical photons plus save one out of every 100 optical photons This might be nice for an event viewer Antiparticles are denoted by negative numbers
155. et run number EXECUTION execution EXECUTION Set the starting execution number visualize Run in visualize mode DETECTOR detector DETECTOR List 70 Specify a non default top level geometry file Each job option py file that you pass on the command line will be evaluated in turn and the list of root files will be appended to the default input stream Any non option argument that does not end in py or root is assumed to be a Python module which will be loaded as described in the previous section If you would like to pass command line arguments to your module instead of simply listing them on the command line you must m or module The module name and arguments must be surrounded by shell quotes For example 1shell gt nuwa py n1 m DybPython TestMod1 a foo bar 2 m DybPython TestMod2 3 DybPython TestMod3 In this example only DybPython TestMod1 takes arguments TestMod2 does not but can still be specified with m As the help output states modules and job script files are all loaded in the order in which they are listed on the command line All non option arguments must follow options 6 5 7 Example Configuring DetSimValidation During the move from the legacy G4dyb simulation to the Gaudi based one an extensive validation process was done The code to do this is in the package DetSimValidation in the Validation area It is provides a full featured configuration example Like GenTools t
156. ether suppose you have a CandDigitListHandle object cdlh and you want to loop over all DbiDemoDatal objects that are valid for it the code is DbiTest DbiDemoDatai h DatabaseInterface DbiResultPtr h DbiResultPtr lt DbiDemoDatai gt myResPtr cdlh GetContext for UInt_t irow 0 irow lt myResPtr GetNumRows ires const DbiDemoDatai dddi myResPtr GetRow irow Process row GetRow is guaranteed to return a non zero pointer if the row number is within range otherwise it returns zero The ordering of rows reflects the way the data was written to the database For some types of data this layout is not well suited for access For example for pulser data all the strip ends illuminated by an LED will appear together in the table To deal with this table row object are obliged to return a Natural Table Index if the physical ordering is not a natural one for access You get rows from a table according to their index using the method const T GetRowByIndex UInt_t index const You should always check the return to ensure that its non zero when using this method unless you are absolutely certain that the entry must be present Getting Data from a Row Having got to the table row you want the last job is to get its data Its up to the table row objects themselves to determine how they will present the database table row they represent In our example the DbiDemoDatal is particularly dumb Its internal state is 1
157. ext at for which the data will be accessed NOT where data is generated For example reactor data will be associated with all detector sites not assigned to a reactor site Physically the way to associate the Context Range metadata with the actual data is to have a pair of tables Context Range Table This table consists of rows of ContextRange objects each with a unique sequence number which is used as a key into the Main Data Table Main Data Table Each row has a sequence number corresponding to an entry in the Context Range Table The interface first finds a match in the Context Range Table for the current context and then retrieves all rows in the Main Data Table that match its sequence number The reasons for this two step approach are e To simplify the task of Context Management e To avoid repeated data For Compound and Aggregated data many rows can share a single Context Range So this range only appears once and only a simple sequence number has to be repeated in the main table 150 CHAPTER 17 DATABASE 17 2 6 Extended Context The primary function of Databaselnterface is to provide the best information for a specific context but it can also retrieve information for much more general queries The query is still broken into two parts the context which is matched to the Context Range Table and then the data from the main table is taken for the selected sequence number s However the user can supply a context such as
158. f ROsFeeAdcMultiTool ReadoutCycles 0 4 8 2 12 EVENT DISPLAY 15 2 12 Event Display 2 12 1 A Plain Event Display EvtDsp A plain event display module EvtDsp is available for users It makes use of the basic graphic features of the ROOT package to show the charge and time distributions of an event within one plot One example is shown in Fig 2 1 A lot of features of ROOT are immediately available like save as a postscript file All PMTs are projected to a 2 D plain Each PMT is represented by a filled circle The radii of them characterize the relative charge differences The colors of them show the times of them i e the red indicates the smallest time and the blue indicates the largest time Simple Mode One can use a default simple algorithm to invoke the EvtDsp module The charge and time of the first hit of each channel will be shown Once setting up the nuwa environment the following commands can be used to show events 1 shell gt nuwa py n 1 m EvtDsp DayaBayDataFile data 2 shell gt nuwa py dbconf offline_db n 1 m EvtDsp C DayaBayDataFile data 3 shell gt nuwa py n 1 m EvtDsp S DayaBaySimulatedFile root where the first one by default will show the raw information i e delta ADC ADC preADC and TDC distributions from ReadoutHeader the second one will show calibrated result CalibReadoutHeader in PE and ns as seen in Fig 2 1 and the last line is for SimHeader i e i
159. f exists Trigger number of prompt AD2 muon trigger if exists Trigger number of prompt AD3 muon trigger if exists Trigger number of prompt AD4 muon trigger if exists Trigger number of prompt IWS muon trigger if exists Trigger number of prompt OWS muon trigger if exists Trigger number of prompt RPC muon trigger if exists Trigger type of prompt AD1 muon trigger if exists Trigger type of prompt AD2 muon trigger if exists Trigger type of prompt AD3 muon trigger if exists Trigger type of prompt AD4 muon trigger if exists Trigger type of prompt IWS muon trigger if exists Trigger type of prompt IWS muon trigger if exists Trigger type of prompt IWS muon trigger if exists Time since first prompt muon trigger ms Time since first prompt muon trigger ms Time since first prompt muon trigger ms Time since first prompt muon trigger ms Time since first prompt muon trigger ms Time since first prompt muon trigger ms Time since first prompt muon trigger ms CalibStats charge sum from prompt muon trigger CalibStats charge sum from prompt muon trigger CalibStats charge sum from prompt muon trigger CalibStats charge sum from prompt muon trigger CalibStats charge sum from prompt muon trigger CalibStats charge sum from prompt muon trigger Total number of possible retriggers Possible retrigger detector ID Time of retrigger relative to first prompt muon trigger Trigger number of retrigger Trigger type of retrigger Total charge sum of
160. flect the local insertion date Any SeqNo already present will be skipped but the associated data is compared to the corresponding entries in the database to confirm that they are identical neglecting differences in insertion dates For example Import full_backup dat Export DatabaseNumber 1 update dat Import Test full_backup dat The first updates the first database Cascade number 0 whilst the second updates the second database in the cascade The last does not import at all but still does comparisons so is a convenient way to compare a database to an import file Chapter 19 Database Tables 187 188 19 1 AdMass CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GAdMass spec Masses of detector liquids as measured from filling data name dbtype codetype description code2db AdNo int 11 int AD Number 1 8 GdMass double double GdLS mass in AD in kg GdUnct double double GdLS mass uncertainty in kg GdBlind tinyint int Indicate whether GdLS mass is blind 1 or not 0 LsMass double double LS mass in AD in kg LsUnct double double LS mass uncertainty in kg MoMass double double MO mass in AD in kg MoUnct double double Mo mass uncertainty in kg Table 19 1 DBI Table specification for class GAdMass which corresponds to table AdMass Inttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GAdMass spec 19 2 ADWPHVMAP 189 192 AdWpH
161. g DbiWriter e The DbiWriter s constructor is DbiWriter const ContextRange amp vr Int_t aggNo Dbi SubSite subsite 0 Dbi Task task 0 TimeStamp versiondate TimeStamp 0 0 UInt_t dbNo 0 const std stringk LogComment const std stringk tableName The first argument determines the validity range of the data to be written i e what set of Contexts it is suitable for You can control the date range as well as the type s of data and detector 172 CHAPTER 17 DATABASE The second argument is the aggregate number For unaggregated data it is 1 for aggregated data its a number in the range 0 n 1 where n is the number of aggregates The third argument is the SubSite of the data It has a default of 0 The third argument is the Task of the data It has a default of 0 The fourth argument supplies the data s version date The default is a special date and time which signifies that DbiWriter is to use Overlay Version Dates see Concepts section 17 2 9 Alternatively at any time before writing data use the method void SetOverlayVersionDate to ensure that DbiWriter uses Overlay Version Dates The fifth argument defines which entry in the database cascade the data is destined for By default it is entry 0 i e the highest priority one Caution Supplying the entry number assumes that at execution time the cascade is defined in a way that is consistent with the code that is us
162. g of the job It is optional but can be used to apply any properties that the algorithm supports or to look up and cache pointers to services tools or other components or any other initializations that require the Gaudi framework execute This method is called once every execution cycle event Here is where user code does imple ments whatever algorithm the user creates finalize This method is called once at the end of the job It is optional but can be used to release any cached pointers to services or tools or do any other cleaning up that requires the Gaudi framework When writing an algorithm class the user has three possible classes to use as a basis Algorithm is a low level class that does not provide many useful features and is probably best to ignore GaudiAlgorithm inherits from Algorithm and provide many useful general features such as access to the message service via info and related methods as well as methods providing easy access to the TES and TDS eg get and getDet O This is a good choice for many types of algorithms DybAlgorithm inherits from GaudiAlgorithm and adds Daya Bay specific features related to producing objects from the DataModel It should only be considered for algorithms that need to add new data to the TES An algorithm may be based on GaudiAlgorithm and still add data to the TES but some object bookkeeping will need to be done manually Subclasses of DybAlgorithm should provide initiali
163. ger Possible retriggering due to muon event Event Data CalibStats Extra statistics calculated from calibrated data Event Data Coinc ADCoinc Summary data for sets of AD time coincident events Event Data Muon Spallation Summary data for muon events and subsequent AD events Event UserTags User defined event tags Event UserData User defined data variables Simulated Data Only Event Gen GenHeader True initial position and momenta of simulated particles Event Sim SimHeader Simulated track interactions and PMT RPC hits Geant Event Elec ElecHeader Simulated signals in the electronics system Event Trig TrigHeader Simulated signals in the trigger system Event SimReadout SimHeader Simulated raw data 3 5 6 Common NuWa Commands This section provides a list of common nuwa py commands You must load the NuWa software before you can run these commands see section 3 5 1 1 Wrap raw DAQ files in ROOT tree 2shell gt nuwa py n 1 m ProcessTools LoadReadout 3 o daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 4 daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 data 1 Generate Calibration Data 2shell gt nuwa py n 1 m Quickstart Calibrate m Tagger CalibStats 3 o calib NoTag 0005773 Physics SAB AD2 SFO0 1 _0001 root 4 daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 1 Generate Reconstruction only data files 2shell gt nuwa py n 1 A 0 2s m Quickstart Calibrate
164. ggerAlg Name of the main trigger algorithm for bookkeeping ElecLocation Default Event Electroincs ElecHeader Path of ElecSimHeader in the TES currently the default is picked up from ElecSimHeader h The user can change the properties through the TrigSimConf module as follows import TrigSim trigsim TrigSim Configure import TrigSim TrigSimConf as TsConf TsConf TsTriggerAlg O TrigTools TsExternalTriggerTool The TrigTools property takes a list as an argument allowing multiple triggers to be specified The user can apply multiple triggers as follows import TrigSim trigsim TrigSim Configure import TrigSim TrigSimConf as TsConf TsConf TsTriggerAlg TrigTools TsMultTriggerTool TsEsumTriggerTool TsCrossTriggerTool The mutate method within each tool will be called once per event in the order in which they are listed 13 3 Current Triggers This section will describe specific trigger implementations Most implementations will have properties which can be set like this INSERT EXAMPLE 13 3 1 TsMultTriggerTool A Multiplicity Trigger implementation This will issue a local trigger when a specified number of channels are go over threshold within a given time window This tool has two properties DetectorsToProcess is a list of detectors for this trigger to work on The default value for this property is a list containing all pmt based detectors This tool loops over all detectors within
165. gh gain ADC is recorded by default If the high gain ADC is saturated near 4095 then the low gain ADC is recorded instead For the Mini Dry Run data one PMT photoelectron makes about 20 high gain ADC counts and about 1 low gain ADC count There is an offset Pedestal for each ADC of FE FR SE SR SR SR FR SR SR FR SR HR 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 50 adc channel adc hitldx preAdc channel preAdcAvg hitIdx channel peakCycle hitIdx channel isHighGainAdc hitIdx peakCycle isHighGain 3 5 9 Calibrated Data Calibrated data in ROOT 70 ADC 70 ADC counts ie no signal 790 ADC 2 p e 110 ADC etc the peak ADC ADC Gain Unknown 0 A High 1 Low 2 CHAPTER 3 ANALYSIS BASICS 1 photoelectron The ADC peal cycle is a record of the clock cycle which had Here is a description of ADC gain for these values The following table summarizes the calibrated data visible directly in ROOT Array items have their length given in the brackets i e name length ROOT will automatically draw all entries in the array given the array name See the ROOT User s Guide for more details on working with Trees http root cern ch download doc 12Trees pdf timeAD nHitsAD chargeAD nHitsAD hitCountAD nHitsAD ring nHitsAD column nHitsAD nHitsAD_calib timeAD_calib nHitsAD_calib chargeAD_calib nHitsAD _calib hitCou
166. gle photoelectron mean ADC value high gain GainErr float double Gain Error DarkRate float double Dark Rate DarkRateErr float double Dark Rate Error ElecNoiseRate float double Electronics Noise Rate ElecNoiseRateErr float double Electronics Noise Rate Error PreAdc float double Pre Adc PreAdcErr float double Pre Adc Error AdcMean float double Adc Mean AdcRMS float double Adc RMS TdcMean float double Tdc Mean TdcRMS float double Tdc RMS FlashingCounts int 11 int Flashing Counts DNCountsForced int 11 int Dark Noise Counts Calculated from Forced Trigger Quality tinyint int Quality Flag for a Pmt Channel Table 19 50 DBI Table specification for class GDqPmtNew which corresponds to table DgPmtNew 50nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqPmtNew spec 238 19 51 DqTriggerCounts CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GDqTriggerCounts spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number Detectorld int 11 int Detector ID CrossInCounts int 11 int Cross In Trigger Type Events Counts PeriodicCounts int 11 int Periodic Trigger Type Events Counts CalibCounts int 11 int Calib Trigger Type Events Counts RandomCounts int 11 int Random Trigger Type Events Counts NhitCounts int 11 int NHit Trigger Type Events Counts EsumCounts int 11 int ESum Trigger Type Events Counts
167. gorithm can be accessed through the resulting object via its dumper member From that you can set the properties Location in the event store to find the kinematics to dump StandardDumper set to True to use the dumper that HepMC provides By default it will use one imple mented in the algorithm 10 6 5 GenTools Job Option Modules The GenTools package provides a GenTools Test Job Option Module which gives command line access to some of the helpers It is used in its unit test test_gentools py It takes various command line options of its own which can be displayed via shell gt nuwa py m GenTools Test help Importing modules GenTools Test help Trying to call configure on GenTools Test Usage This module can be used from nuwa py to run GenTools in a few canned way as a test 10 7 MUONPROPHET 101 It is run as a unit test in GenTools tests test_gentools py Options h help show this help message and exit a HELPER helper HELPER Define a helper to help set up GenTools is gun diffuser or hepevt v VOLUME volume VOLUME Define a volume to focus on s DATA_SOURCE data source DATA_SOURCE Define the data source to use for HepEVT helper 10 7 MuonProphet 10 7 1 Motivation MuonProphet DocDB 4153 DocDB 4441 is designed to address the simulation of muon which will be a major background source of Daya Bay neutrino experiment Spallation neutrons and cosmogenic background namely 9Li 8He et
168. h PMT Aggregated A special form of Compound depending on the way new data is added to the database e If data for the entire detector is written as a single logical block then it is Compound A table that describes the way PMTs to electronics channels might be compound a complete description is written as a single unit e If it is written in smaller chunks called aggregates then it is Aggregated For example it might be possible to calibrate individual electronics cards independently of the rest of the detectors at on sit When calibrated you will want to update only a subset of the calibrations in the database One of the jobs of the interface is to reassemble these aggregates so that the user only ever sees a complete set There are two types of aggregation Complete In this type the number of aggregates present at any time is constant with the possible exception of detector construction periods during which the number increases with time This is the normal form and is used to describe a set of sub systems that are permanently present e g the set of steel planes Sparse In this type the number of aggregates present at any time is variable there could even be none This form is used to describe abnormal conditions such as alarms 17 2 3 Tables of Data The Databaselnterface provides a simple uniform concept regardless of the data being accessed Each request for data produces a pointer giving read access to a results table which
169. h it is the slowest method it may still be fast enough for your specific needs Advantages e Full data classes and methods are available e Full access to geometry database other external data e Can be integrated with production analysis job Disadvantages e Slowest method to histogram data e Requires some careful programming e Requires a NuWa software installation To run this example use the following approach 1 shell gt nuwa py n 1 m Quickstart dybNuWaHist recon root The key lines from the script are OMAN Oa FPF wWN eH wWwWwwwwwwwwwnn nd NNNNNNN FP FP RP BP RP RP RP BP PB OANA TAF WwWwNHrFR TOO AN AA BPWNHrFOTKOKOCAN DH FP WN Fr OC 30 CHAPTER 3 ANALYSIS BASICS def execute self Process each event evt self evtSvc Access the reconstructed data reconHdr evt Event Rec AdSimple if reconHdr None self error Failed to get current recon header return FAILURE Access the calibrated data statistics calibStatsHdr evt Event Data CalibStats if reconHdr None self error Failed to get current calib stats header return FAILURE Check for antineutrino detector detector reconHdr context GetDetId if detector DetectorId kAD1 or detector Detectorld kAD2 A Found an AD Get reconstructed trigger recTrigger reconHdr recTrigger if not recTrigger No Reconstructed information self warning No reconstructed data for AD event return FAILURE Get
170. hannelStatus which corresponds to table DqChannel Status http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqChannelStatus spec 232 19 45 DqDetector CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GDqDetector spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number Detectorld int 11 int Detector ID TriggerCounts int 11 int Trigger Counts FlasherCounts int 11 int Flasher Counts MuonCounts int 11 int Muon Counts IbdCounts int 11 int IBD Number SpnCounts int 11 int Spallation Neutron Number BlockTrigCounts int 11 int Blocked Trigger Number SpnEnergy float double Spallation Neutron Energy SpnEnergySigma float double Sigma of Spallation Neutron Energy Table 19 45 DBI Table specification for class GDqDetector which corresponds to table DqDetector http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqDetector spec 19 46 DQDETECTOREXT 19 46 DqDetectorExt 233 Table specification source dybgaudi trunk Database DybDbi spec GDqDetectorExt spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number Detectorld int 11 int Detector ID ADMuonCounts int 11 int AD Muon Counts IWSTaggedCounts int 11 int IWS Tagged AD Muon Counts OWSTaggedCounts int 11 int OWS Tagged AD
171. he big cube This shows the 3 sites You can drill down them further until you get to the AD pmt arrays Finally note that there is still a lot of non DayaBay cruft that should be cleaned out so many menu items are not particularly useful 96 CHAPTER 9 DETECTOR DESCRIPTION DetectorElement gt GeometryInfo Figure 9 1 Logical Physical and Touchable volumes Chapter 10 Kinematic Generators 10 1 Introduction Generators provide the initial kinematics of events to be further simulated They must provide a 4 position 4 momentum and a particle type for every particle to be tracked through the detector simulation They may supply additional information particles that are otherwise ignored The incoming neutrino or radioactive decay parent are two examples of such particles 10 2 Generator output Each generated event is placed in the event store at the default location Event Gen GenHeader but when multiple generators are active in a single job they will place their data in other locations under Event Gen The data model for this object is in DataModel GenEvent The GenHeader object is simply a thin wrapper that holds a pointer to a HepMC GenEvent object See HepMC documentation for necessary details on using this and related objects 10 3 Generator Tools A GenEvent is built from one or more special Gaudi Tools called GenTools Each GenToo1 is responsible for constructing part of the kinematic information and mult
172. he configuration is split up into modules providing helper classes In this case there is a module for each detector and a class for each type of validation run For example test of uniformly distributed positrons can be configured like from DetSimValidation AD import UniformPositron up UniformPositron Chapter 7 Data Model e Over all structure of data One package per processing stage Single header object as direct TES DataObject Providence e Tour of DataModel packages 7 1 Overview The data model is the suite of classes used to describe almost all of the information used in our analysis of the experimental results This includes simulated truth real and simulated DAQ data calibrated data reconstructed events or other quantities Just about anything that an algorithm might produce is a candidate for using existing or requiring new classes in the data model It does not include some information that will be stored in a database reactor power calibration constants nor any analysis ntuples In this last case it is important to strive to keep results in the form of data model classes as this will allow interoperability between different algorithms and a common language that we can use to discuss our analysis The classes making up the data model are found in the DataModel area of a release There is one package for each related collection of classes that a particular analysis stage produces 7 1 1 Head
173. he other important feature is to output each simheader in time order Imagine two GenHeaders times are very close the first one in time is far away to any PMTs while the second one is close to one PMT it is possible that because of the time of light propagation light from the second event will generate a PMT hit first The chance of this to happen is small but it is serious enough to cause whole simulation process to crush and all the following electronic and trigger logic to fail DetSimProc asks data input from simulation stage Kinematic As promised by stage tool all the kinematic information out of stage Kinematic are in time order earliest to latest no violation Then DetSimProc take this advantage to ensure its output is also in time order After DetSimProc got a GenHeader to simulate it finished the detector simulation for that GenHeader first That is it can know the earliest hit time of this SimHeader DetSimProc keeps asking GenHeader from its lower stage and doing their detector simulation until a time comparison test is success DetSimProc caches all the information of processed GenHeaders and SimHeaders It compares the earliest time of all SimHeaders and the time of the last GenHeader When the time of a SimHeader is less than the last GenHeader it claims safe for output for that SimHeader Because the causality of event development since the last GenHeader time is already bigger than the time of a previous SimHeader
174. he type and date time of the current event This is stored in a Context package Context object FIXME Need a description here of how to get a Context from a Data Model object It should be something like Context GetContext const methods to get their context The Databaselnterface uses the context to extract all the rows from the database table that are valid for this event It forms the result into a table in memory and returns a object that acts like a pointer to it 17 4 ACCESSING EXISTING TABLES 157 You are NOT responsible for deleting the table the Database Interface will do that when the table is no longer needed You have random access to any row of the results table Each row is an object which is specific to that table The key to understanding how to get data from a database table is study the class that represent a row of it results table 17 4 2 Accessing Detector Descriptions Making the Query As explained above the key to getting data is to locate the class that represents one row in a database table To understand how this all works look at one of the sample tables included in the DbiTest package and imaginatively called DbiDemoData1 DbiDemoData2 and DbiDemodata3 For purposes of illustration we will pick the first of these Its header can be found in DbiTest DbiDemoDatai h To make a query you create a DbiResultPtr object Its header can be found in DatabaseInterface DatabaseInterface DbiResultPtr h This i
175. her s coordinate system The combination of a trans formation and a logical volume is called a physical volume Example The 192 placed PMTs in the AD oil logical volume 9 1 3 Touchable XML lt detelem gt C DetectorElement Description Logical volumes can be reused by placing them multiple times Any physical daughter volumes are also reused when their mother is placed multiple times A touchable volume is the trail from the top level world volume down the logical physical hiearchy to a specific volume In Geant4 this trail is stored as a vector of physical volumes G4TouchableHistory On the other hand in Gaudi only local information is stored Each DetectorElement holds a pointer to the mother DetectorElement that supports it as well as pointers to all child DetectorElements that it supports Example The 8 x 192 1536 AD PMTs in the whole experiment Scope of Detector Description basics of geometry structure and materials Include diagrams showing geometry containment and structure s detector element geometry info relationships 9 2 Conventions The numbering conventions reserve 0 to signify an error PMTs and RPCs are addressed using a single bit packed integer that also records the site and detector ID The packing is completely managed by classes in Conventions Detectors h The site ID is in Conventions Site h and the detector ID type is in Conventions Detectorld h These are all in the DataModel area 9 2
176. ies 52998 14000 gt Mean 381 6 200005 Mean 974 8 E RMS 347 6 18000 RMS _59 45 12000 E J E J 16000 10000 y 14000 a saoo 4 120005 E 4 10000 6000 a 8000 E 4000 4 60005 aa E q 40005 A 2000 all 3 E J 2000 H obi pad PANA AAA AAA odia ddd al add 0 500 1000 1500 2000 2500 3000 3500 400 500 600 700 800 900 1000 1100 1200 daqPmtCrate adcs 6 5 1 value daqPmtCrate tdcs 6 5 1 value Figure 3 6 Histograms of Raw fine range ADC and TDC values from PMT FEE board 6 connector 5 26 CHAPTER 3 ANALYSIS BASICS 3 2 4 Some ROOT Tree Tricks A ROOT TChain can be used to combine the trees of the same path from multiple files into one large tree For example if a data run produced two files you can combine the trees from these files 1root 0 TChain AdSimple Event Rec AdSimple 2ro0t 1 AdSimple Add recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3root 2 AdSimple Add recon NoTag 0005773 Physics SAB AD2 SFO 1 _0002 root 4root 3 AdSimple Draw energy energyStatus 1 amp amp detector 2 To combine all the variables from trees at different data paths into a single tree you can use the TTree AddFriend function This can be used to histogram or select using variables from both trees This should only be done for trees that are synchronized The raw calibrated and reconstructed data are generally synchronized as long as the data has not been filtered The simulated truth trees at
177. iggerTimeSec triggerTimeNanoSec 1e 9 Figure 3 5 The calibrated charge in photoelectrons for one PMT and for the sum of all PMTs versus trigger time 3 2 3 Histogramming Raw DAQ data To properly histogram raw DAQ data from Event Readout you will need to use part of the Daya Bay software in addition to ROOT You must load the NuWa software as described in Sec 3 5 1 Running load C will allow you to call functions in your Draw command For example you can call the function to draw the raw fine range ADC and TDC distributions for PMT electronics board 6 connector 5 Fig 3 6 The selection on context mDetId 2 selects the detector AD2 Sec 3 5 7 lists the allowed detector and site IDs If you have a raw data file produced by the DAQ see section 3 5 8 to wrap it in a ROOT tree so that you can directly histogram the raw data 1root 0 2root 1 3root 2 4root 3 5root 4 x ROOTIOTESTROOT share load C TFile f daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root TTreex ReadoutHeader TTreex f Get Event Readout ReadoutHeader ReadoutHeader gt Draw daqPmtCrate adcs 6 5 1 value context mDetId 2 ReadoutHeader gt Draw daqPmtCrate tdcs 6 5 1 value context mDetId 2 daqPmtCrate adcs 6 5 1 value context mDetld 2 daqPmtCrate tdcs 6 5 1 value context mDetld 2 htemp htemp 16000 Toot tt E Entries 52998 22000 Entr
178. ignals 126 CHAPTER 12 ELECTRONICS SIMULATION E tdcSignal Analog gt EN Threshold 1 25 mV E hitSignal Digital 1 0 3 hitSync Digital 1 0 2 hitHold Digital 1 0 E o 40 60 80 100 120 Clock Cycle 640Mhz Period 1 5625ns Figure 12 4 An example of convertions from tdcSignal to hitHold Signal The the label in Y axis is only for the analog signal tdcSignal and the Threshold line Variable Defined Value BaseFrequency 40 LE6 hz TdcCycle 16 AdcCycle 1 EsumCycle 5 NhitCycle 2 preTimeTolerance 300ns postTimeTolerance 10us Trigger WindowCycle 8 Table 12 3 Chapter 13 Trigger Simulation 13 1 Introduction The Trigger Simulation is implemented in the TrigSim package TrigSim takes an ElecHeader as input and produces a SimTrigHeader See Figure 13 1 SimTrigHeader SimTrigComandHeader SimTrigComandCollection 0 N SimTrigCommand detector type clockCycle Figure 13 1 SimTrigHeader contains a single SimTrigCommandHeader which in turn potentially con tains a SimTrigCommandCollection for each detector Each SimTrigCommandCollection contains SimTrigCommands which correspond to an actual trigger 13 2 Configuration The main algorithm in TrigSim TsTriggerAlg has 3 properties which can be specified by the user TrigTools Default TsMultTriggerTool List of Tools to run 127 128 CHAPTER 13 TRIGGER SIMULATION TrigName Default Tri
179. iles on the command line 2Code is at dybgaudi Simulation GenTools python GenTools Test py 3Code is at tutorial DivingIn python DivingIn Example py 6 5 PROPERTIES AND CONFIGURATION 75 Geometry Use or not of the archive event store Access to visualization Running of user job option scripts and or loading of modules After setting up your environment in the usual way the nuwa py script should be in your execution PATH You can get a short help screen by just typing 1shell gt nuwa py help 2Usage 3 This is the main program to run NuWa offline jobs 4 5 It provides a job with a minimal standard setup Non standard 6 behavior can made using command line options or providing additional 7 configuration in the form of python files or modules to load 8 9 Usage 0 1 nuwa py options m module mod ule mod arg Y 12 configi py config2 py 3 mod ulel mod ule2 Y 4 inputi root input2 root 5 6 Python modules can be specified with m module options and may 7 include any per module arguments by enclosing them in shell quotes 8 as in the above usage Modules that do not take arguments may 9 also be listed as non option arguments Modules may supply the 20 following functions 21 22 configure argv if exists executed at configuration time 23 24 run theApp if exists executed at run time with theApp set to 25 the AppMgr 26 27 Additionally
180. illing Tables The following commands add data from the file DemoDatal dat to an existing table load data local infile DemoDatal dat into table DbiDemoDatal Each line of the file corresponds to a row in the table Columns should be separated with tabs Table 17 2 shows typical formats of the various data types 180 CHAPTER 17 DATABASE MySQL Type Table Row Type CHAR a TINYINT 128 SMALLINT 32768 INT or INTEGER 2147483647 FLOAT 1 234567e 20 DOUBLE 1 23456789012345e 200 TEXT This is a string DATETIME 2001 12 31 04 05 06 Table 17 2 Example data formats 17 8 8 Making Queries Here is a sample query select from DbiDemoData2Validity where TimeStart lt 2001 01 11 12 00 00 and TimeEnd gt 2000 12 22 12 00 00 and SiteMask amp 4 order by TimeStart desc 17 9 Performance 17 9 1 Holding Open Connections Connections to the database are either permanent i e open all the time or temporary i e they are closed as soon as a I O operation is complete A connection is made permanent if e Connecting to a ASCII flat file database as re opening such a database would involve re loading all the data e Temporary data is written to the database for such data would be lost if the connection were closed In all other cases the connection is temporary so as to minimise resources and in the case ORACLE resources that have to be paid for For normal operations this adds little
181. imulation stages asking output Stage tools are firstly set up in the following OMAN AWM PWN RFP TH ANAT FWD EBE N o OMAN ODAATPWNH RF TH ANAT PWD FB NNN NN NNN WN aN aarp wnr O 140 CHAPTER 15 SIMULATION PROCESSING MODELS def configure self from Stage import Configure as StageConfigure self stage_cfg StageConfigure stagedic Kinematic 1 Detector 2 Electronic 3 TrigRead 4 SingleLoader 5 if stagedic self opts top_stage gt 1 self configureKinematic if stagedic self opts top_stage gt 2 self configureDetector if stagedic self opts top_stage gt 3 self configureElectronic if stagedic self opts top_stage gt 4 self configureTrigRead if stagedic self opts top_stage gt 5 self configureSingleLoader self configureSimi5 According to the top simulation stage all required lower stage tools are created For example if top stage is set to be Detector then only stage tool Kinematic and Detector will be added In the end the algorithm Sim15 is configured Correspondingly Sim15 will ask data from stage tool Detector Next we will see the configuration of Gnrtr In this example two generators IBD and K40 are added to work at the same time def configureKinematic self IBD from Gnrtr IBD import EvtGenerator from IBD import EvtGenerator ibd_gds EvtGenerator name IBD_gds seed self opts seed volume dd Structu
182. ing the DbiWriter As an alternative you can supply the database name e g offline if you know it and are certain it will appear in the cascade The sixth argument supplies a comment for the update Alternatively at any time before writing data use the method void SetLogComment const std string LogComment Update comments are ignored unless writing to a Master database i e one used as a source database e g the database at FNAL and in this case a non blank comment is mandatory unless the table is exempt Currently only DBI DCS and PULSER tables are exempt If the first character on the string is the character then the rest of the string will be treated as the name of a file that contains the comment If using DbiWriter to write multiple records to the same table as part of a single update then only create a single DbiWriter and use the Open method to initialise for the second and subsequent records That way a single database log entry will be written to cover all updates The last argument supplies the name of the table to be written to Leaving it blank will mean that the default table will be used i e the one whose name matches apart from case the name of object being stored Only use this feature if the same object can be used to fill more than one table e Having instantiated a DbiWriter filled table row objects must be passed using the operator DbiWriter lt T gt amp operator lt lt const T amp row for exampl
183. ion of the raw data The final job the current running job is printing the job information to the screen 3 4 2 Tag Events in a NuWa File Event tags are used to identify a subset of events These can be used to separate events into classes such as muons inverse beta decay noise etc In general tags be used to identify any set of events of interest The job module Tagging UserTagging python UserTagging UserTag DetectorTag py is a simple ex ample of tagging readouts by detector type The tag can be applied by adding the module to a NuWa job 1shell gt nuwa py n 1 no history m UserTagging UserTag DetectorTag 2 daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root To add your own tag follow the steps for modifing an existing python module section 3 4 8 Use Tagging UserTagging python UserTagging UserTag DetectorTag py as a starting point You should add your own tag in the initTagList function 1self addTag MySpecialEvent Event UserTag MySpecialEvent In the check function you should retrieve event data and decide if you want to tag it 1 Get reconstructed data 2recHdr evt Event Rec AdSimple 3 Add your calculation decision here 4 5 6if tagThisEvent 7 A Keep track of the reconstructed data you are tagging 8 self getTag MySpecialEvent setInputHeaders recHdr 9 self tagIt MySpecialEvent Once a tag has been set it can be used by later analysis algorithms in
184. iple entries in the unfriendlyT tree These are the variables triggerNumber and context mDetId Note that one or both of these index variables must be an array in the mainT tree to properly describe the unfriendly one to many relationship between entries in mainT and unfriendlyT This helper function may require some slight modification for your specific case It assumes that the branches have the following types e mainEntriesName integer in mainT e friendVarNames float in unfriendlyT e indexMajorName vector lt int gt in mainT and int in unfriendlyT e indexMinorName int in both mainT and unfriendlyT This helper function could be extended to dynamically check these variable types eg float int vector lt float gt vector lt int gt etc and then respond accordingly This is left as an exercise for the analyzer 34 CHAPTER 3 ANALYSIS BASICS 3 3 NuWa Basics If you wish to do more analysis than histogramming data from files you must use NuWa NuWa is the name given to the analysis software written for the Daya Day experiment It is installed and available on the computer clusters To load the software on one of the clusters see Sec 3 5 1 To install NuWa on another computer see Sec 3 5 2 NuWa analysis allows you to e Access all event data e Relate data at different paths ie Event Rec to Event Readout e Access non event data ie PMT positions cable mapping etc e Do more complex calculations e Write NuWa
185. iple tools work in concert to produce a fully described event This lets the user easily swap in different tools to get different results 10 4 Generator Packages There are a number of packages providing GenTools The primary package is called GenTools and provides basic tools as well as the GtGenerator algorithm that ties the tools together Every execution cycle the algorithm will run through its tools in order and place the resulting event in the event data store A separate package GenDecay provides GenTools that will produce kinematics for various radioactive nuclear decays The GtGenerator is suitable only for linear jobs that only simulate a single type of event In order to mix multiple events together the so called Fifteen suite of packages see Ch are used To configure for this type of job the Gnrt package s Configure is used 10 5 Types of GenTools The available GenTools and a sample of their properties are given You can query their full properties with properties py ToolName 97 98 CHAPTER 10 KINEMATIC GENERATORS 10 5 1 GenTools package GtPositionerTool provides a local vertex 3 position It does it by placing the vertex at its given point or distributing it about its given volume in various ways GtTransformTool provides global vertex 3 position and 3 direction given local ones This will take existing an position and direction interpret them as being defined in the given volume and transform them into g
186. ipt which should be installed in your PATH 1shell gt properties py 2GtGenerator 6 5 PROPERTIES AND CONFIGURATION 71 GenName Name of this generator for book keeping purposes GenTools Tools to generate HepMC GenEvents GlobalTimeOffset None Location TES path location for the HeaderObject this algorithm produces N Qa e O A special configurable is the ApplicationMgr Most users will need to use this to include their algorithms into the TopAlg list Here is an example 1 2from Gaudi Configuration import ApplicationMgr 3theApp ApplicationMgr 4 5from MyPackage MyPackageConf import MyAlgorithm 6ma MyAlgorithm 7ma SomeProperty harder faster stronger 8theApp TopAlg append ma Configurables and Their Names It is important to understand how configurables eventually pass properties to instantiated C objects Behind the scenes Gaudi maintains a catalog that maps a key name to a set of properties Normally no special attention need be given to the name If none is given the configurable will take a name based on its class 1 gets name MyAlgorithm 2generic MyAlgorithm 3 gets name algi 4specific MyAlgorithm algi 5 6theApp TopAlg append generic 7theApp TopAlg append specific 8 TopAlg now holds MyAlgorithm MyAlgorithm MyAlgorithm algi Naming Gaudi Tool Configurables In the case of Gaudi Tools things become more complex Tools themselves can and sh
187. is Kurtosis Middle TimeRMS integralRunTime_ms integralLiveTime_buffer full_ms integralLiveTime_blocked_trigger_ms blocked trigger buffer_full_flag Time since previous AD1 trigger ms Time since previous AD2 trigger ms Time since previous Inner water pool trigger ms Time since previous Outer water pool trigger ms Time since previous AD event with greater than 20 MeV ms Time since previous AD event with greater than 1 GeV ms Energy of last AD event with greater than 1 GeV pe Total number of hit 8 inch PMTS Median charge number of photoelectrons on PMTs RMS of charge number of photoelectrons on PMTs Total sum of charge number of photoelectrons on all PMTs Median number of hits on PMTs Median number of hits on PMTs Total Sum of number of hits on all PMTs Earliest hit time on all PMTs ns Latest hit time on all PMTS ns Mean hit time on all PMTS ns Median hit time on all PMTS ns RMS of hit time on all PMTS ns The maxima total charge collected for one PMT in one readout PE sum over all For hits in each AD for time window between 1650 and 1250 ns Set 1450 at_1650 1250 For hits in each AD for time window between 1650 and 1250 ns Toso ne The RMS of the time of the first hit also must be within 1650 and 1250 for 5x5 The total charge within 1650 and 1250 of nearby 3 columns PMTs total 7 cc The total charge within 1650 and 1250 of 4 9 and 4 9 columns PMTs Th
188. isStageName Detector load LowerStageName Add this processor to Gaudi sequencer self stage_cfg DetectorSequence Members append load return 15 2 FIFTEEN 143 15 2 12 Reminders and Some Common Errors AES must be used to use Fifteen to generate simulation sample The number of events specified on the command line is the number of execution cycles If asking readout as the final output then the initial number of GenHeader varies depending on trigger efficiency Chapter 16 Reconstruction 145 Chapter 17 Database 17 1 Database Interface This chapter is organized into the following sections Concepts is an introduction to the basic concepts behind the Databaselnterface You can skip this section if you are in a hurry but reading it will help you understand the package Installing and Running provides a few tips on building running programs that use the DatabaseInterface Accessing Existing Tables tells you how you write code to retrieve data from existing tables Creating New Tables describes how new tables are added to the database and the corresponding classes that serve the data are designed Filling Tables explains how new data is added to existing tables in the database MySQL Crib gives the bare minimum necessary to use MySQL to manage a database The Databaseln terface runs directly on top ROOT under which MySql and flat ASCII files are used to implement a hierarchical database 17 2 Concepts 17 2 1
189. ition mm after a simple recon pVertex_y double double prompt signal vertex y position mm after a simple recon pVertex_z double double prompt signal vertex z position mm after a simple recon dTriggerNo int 11 int delayed signal trigger number dEnergy double double delayed signal energy MeV after a simple recon dTime_s int 11 int delayed signal time stamp sec dTime_nano int 11 int delayed signal time stamp nano dVertex_x double double delayed signal vertex x position mm after a simple recon dVertex_y double double delayed signal vertex y position mm after a simple recon dVertex_z double double delayed signal vertex z position mm after a simple recon Table 19 63 DBI Table specification for class GSupernova Trigger which corresponds to table Supernova Trigger 63http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GSupernovaTrigger spec 252 CHAPTER 19 DATABASE TABLES 19 64 TimeLatency Table specification source dybgaudi trunk Database DybDbi spec GTimeLatency spec docstring name dbtype codetype description code2db Latency float double time latency relative to a specific detector in one EH Table 19 64 DBI Table specification for class GTimeLatency which corresponds to table TimeLatency http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GTimeLatency spec Chapter 20 Bibliography 253 Bibliography 1 Reference target needed for g4dyb 2
190. ividually converted through several layers of the support database software from the raw data 17 3 RUNNING 153 Now as the detector configuration changes slowly with time identically the same process outlined above is repeated many times in many jobs that process the data so the obvious solution is to cache the results to disk in some way that can be reloaded rapidly when required The technique essentially involves making an image copy of the table to disk It can only be applied to some tables but these include the Calibration tables which represent the largest database I O load and for these tables loading times can be reduced by an order of magnitude 17 3 Running 17 3 1 Setting up the Environment The interface needs a list of Database URLs a user name and a password This was previously done using envvars ENV_TSQL_URL ENV_TSQL_USER ENV_TSQL_PSWD that directly contained this configuration information As this approach resulted in the configuration information being duplicated many times a new DBCONF approach has now been adopted The DBCONF approach is based on the standard mysql configuration file HOME my cnf which has the form testdb host dybdb1 ihep ac cn user dayabay password youknowit database testdb dyb_cascade host dybdb1 ihep ac cn user dayabay password youknowit database dbi offline_db db2 dyb_temp Typical configurations can be communicated via the setting of a single environmen
191. ixes First the load file is very short 1 include GaudiKernel LoadFactoryEntries h 2LOAD_FACTORY_ENTRIES PerGenEvent Note one must use the package name in the CPP macro Next the entries file has an entry for each converter or other Gaudi component defined in the package l include GaudiKernel DeclareFactoryEntries h 2 include GenHeaderCnv h 3 DECLARE_CONVERTER_FACTORY GenHeaderCnv Resolving references The Data Model allows for object references and the I O code needs to support persisting and restoring them In general the Data Model will reference an object by pointer while the persistent class must reference an object by an index into some container To convert pointers to indices and back the converter must have access to the transient data and the persistent container Converting references can be additionally complicated when an object held by one HeaderObject refer ences an object held by another HeaderObject In this case the converter of the first must be able to look up the converter of the second and obtain its persistent object This can be done as illustrated in the following example 1 include Event SimHeader h 2 include PerSimEvent PerSimHeader h 3StatusCode ElecHeaderCnv initialize a 5 MsgStream log msgSvc ElecHeaderCnv initialize 7 StatusCode sc RootIOBaseCnv initialize 00 if sc isFailure return sc o 88 13 14 003 sg 20 21 22 23 24
192. jects within the same HeaderObject hierarchy e Pointers to objects in a different HeaderObject hierarchy e Pointers to objects in a different execution cycle e Pointers to isolated objects or to those stored in a collection The PerBaseEvent package provides some persistent classes than can assist the converter in resolving references PerRef Holds a TES TFile path and an entry number PerRefInd Same as above but also an array index In many cases the transient objects form a hierarchy of references The best strategy to store such a structure is to collect all the objects into like class arrays and then store the relationships as indices into these arrays The PerGenHeader classes give an example of this in how the hierarchy made up of vertices and tracks are stored 8 6 5 Writing Converters The converter is responsible for copying information between transient and persistent representations This copy happens in two steps The first allows the converter to copy information that does not depend on the conversion of other top level objects The second step lets the converter fill in anything that required the other objects to be copied such as filling in references A Converter operates on a top level DataObject subclass and any subobjects it may contain In Daya Bay software almost all such classes will inherit from HeaderObject The converter needs to directly copy only the data in the subclass of HeaderObject and can delegate the copying
193. lId int 11 DayaBay HvChannelId Packed HV Channel ID fullPackedData FeeChannelId int 11 DayaBay FeeChannelId Packed FEE Channel ID fullPackedData Table 19 4 DBI Table specification for class GAdWpHvToFee which corresponds to table AdWpHvToFee nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GAdWpHvToFee spec 192 CHAPTER 19 DATABASE TABLES 19 5 CableMap Table specification source dybgaudi trunk Database DybDbi spec GCableMap spec The Cable Map provides the data for lookups between a sensorID and a channel1D The 1D numbers are packed integers ready for consumption by the sensor classes from Detectors h and channel classes from Electronics h from the Conventions package This table handles sensors and electronics for PMTs AD and Pool and RPCs Read context must explicitly give Site SimFlag and DetectorId SubSite Write context must explicitly give SiteMask SimMask and SubSite name dbtype codetype description code2db SensorId int 11 DayaBay DetectorSensor Packed Sensor ID fullPackedData Channelld int 11 DayaBay ElecChannelld Packed Channel ID fullPackedData Table 19 5 DBI Table specification for class GCableMap which corresponds to table CableMap 5http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCableMap spec 19 6 CABLEMAPFIX 193 19 6 CableMapFix Table specification source dybgaudi trunk Database DybDbi spec GCa
194. le Histories package crudely corresponds to these structures There are two main data objects SimTrack which corresponds to G4Track and SimVertex which corresponds to a G4StepPoint So each particle that is simulated in by Geant can create a SimTrack If the particle takes n steps in the Geant simulation then it can create at most n 1 SimVertex objects one at the start and one for each step thereafter If all vertices are saved then this represents the finest granularity possible for saving the history of the simulation The data saved in a Track or Vertex is shown in Figures 11 3 1 and 11 3 1 Generally speaking a SimTrack simply holds the PDG code for the particle while a SimVertex holds a the state position time volume momentum energy and the process appropriate for that point in the simulation Other information may be derived from these variables For instance the properties of a particle may be derived by looking up the PDG code via the ParticlePropertiesSvc and the material of a step may be looked up by accessing the IPVolume pointer If there are two vertices with different materials the material in between is represented by the first vertex This is not true if vertices have been pruned Each track contains a list of vertices that correspond to the state of the particle at different locations in it s history Each track contains at least one vertex the start vertex Each Vertex has a pointer to it s parent Track The rel
195. les can supply some methods named by convention that can allow additional functionality configure argv This method can hold all the same type of configuration code that the job option scripts do This method will be called just after the module is imported Any command line options given to the module will be available in argv list run appMgr This method can hold code that is to be executed after the configuration stage has finished and all configuration has been applied to the actual underlying C objects In particular you can define pure Python algorithms and add them to the TopAlg list There are many examples Job Option Modules in the code Here are some specific ones GenTools Test this module gives an example of a configure argv function that parses command line options Following it will allow users to access the command line usage by simply running nuwa py m GenTools Test help DivingIn Example this module gives an example of a Job Option Module that takes no command line arguments and configures a Python Algorithm class into the job 6 5 6 The nuva py main script Finally there is the layer on top of it all This is a main Python script called nuwa py which collects all the layers below This script provides the following features e A single main script everyone uses e Configures framework level things Python interactive vs batch Logging level and color File I O specify input or output f
196. libStats execNumber kTRUE int detector 0 3 2 DAYA BAY DATA FILES 29 0 reconT SetBranchStatus context mDetId kTRUE 1 reconT SetBranchAddress context mDetld detector 2 3 int energyStatus 0 4 reconT SetBranchStatus energyStatus kTRUE 5 reconT SetBranchAddress energyStatus amp energyStatus 6 7 float energy 1 8 reconT SetBranchStatus energy kTRUE 9 reconT SetBranchAddress energy amp energy 20 21 int nHit 1 22 reconT SetBranchStatus calibStats nHit kTRUE 23 reconT SetBranchAddress calibStats nHit amp nHit 24 25 Process each event 26 int maxEntries reconT GetEntries 27 for int entry 0 entry lt maxEntries entry 28 29 Get next event 30 reconT GetEntry entry 31 32 Fill histograms 33 if energyStatus 1 Reconstruction was successful 34 if detector 1 35 AD 1 36 nhitVsEnergyAD1H gt Fill energy nHit 37 else if detector 2 38 AD 2 39 nhitVsEnergyAD2H gt Fill energy nHit 40 41 42 dybNuWaHist py This example uses a full NuWa algorithm to generate the histogram Use this approach when you need complete access to the event data object class methods geometry information database and any other external data You must also use this approach if you want your algorithm to be included in the standard production analysis job It is the most powerful approach to analysis of the data but it is also the slowest Althoug
197. lled but not that it is physically the same object If there have been intervening queries the original object may have been deleted but this should not matter unless the cache holds pointers back to the DbiResult In this case the result ID should be used Initialise with Int_t MyResultID myResPtr GetResultID and then check as follows if MyResultID myResPtr GetResultID recreate the cache data MyResultID myResPtr GetResultID 17 4 3 Extended Context Queries Making the Query The constructor of a DbiResultPtr for an Extended Context Query is DbiResultPtr const string amp tableName const DbiSqlContext amp context const Dbi SubSite amp subsite Dbi kAnySubSite const Dbi Task amp task Dbi kAnyTask const stringg data const stringg fillOpts 17 4 ACCESSING EXISTING TABLES 161 Dealing with each of these arguments in turn const string amp tableName The name of the table that is to be accessed This allows any type of DbiTableRow to be loaded from any type of table but see section 17 6 on filling if you are going to play tricks const DbiSqlContext z context This argument provides the extended context through the utility class DbiSqlContext Consider the following code Construct the extended context FarDet data that starts on Sept 1 2003 note then end time stamp is exclusive TimeStamp tsStart 2003 9 1 0 0 0 TimeStamp tsEnd 2003 9 2 0 0 0 DbiSqlContex
198. lobal coordinates needed for further simulation It can optionally transform only position or direction GtTimeratorTool provides a vertex time Based on a given lifetime rate it can distribute times exponen tially or uniformly It can also set the time in an Absolut spelling intentional or Relative manner The former will set the time unconditionally and the latter will add the generated time to any existing value GtGunGenTool provides a local 4 momentum It simulates a virtual particle gun that will shoot a given particle type in various ways It can be set to point in a given direction or spray particles in a few patterns It can select a fixed or distributed momentum GtBeamerTool provides a global 3 vertex and a global 4 momentum It produces a parallel beam of circular cross section pointed at some detector element and starting from a given direction and distance away GtDiffuserBallTool provides a relative 3 vertex and local 4 momentum It simulates the diffuser balls used in calibration Subsequent positioner and transform tools are needed to place it at some non origin position relative to an actual volume GtHepEvtGenTool provides a local 4 momentum It is used to read in kinematics in HepEVT format either from a file or through a pipe from a running executable Depending on the HepEVT source it may need to be followed by positioner timerator or transform tools 10 5 2 GenDecay Package The GenDecay package simula
199. lowing errors found lt lt el lt lt endl 17 5 Creating New Tables 17 5 1 Choosing Table Names The general rule is that a table name should match the DbiTableRow subclass object that it is used to fill For example the table CalPmtGain corresponds to the class CalPmtGain The rules are e Use only upper and lower case characters e Avoid common names such as VIEW and MODE are used by ORACLE A good list of names to avoid can be found at http home fnal gov 7Edbox SQL_API Portability html These restrictions also apply to column names Moreover column names should be all capital letters 17 5 2 Creating Detector Descriptions A Simple Example Creating new Detector Descriptions involves the creation of a database table and the corresponding table row Class The main features can be illustrated using the example we have already studied DbiDemoDatal Recall that its state data is Int_t fSubSystem Float_t fPedestal Float_t fGainl Float_t fGain2 Its database table which bears the same name is defined in MySQL as CREATE TABLE DBIDEMODATA1 SEQNO INTEGER not null ROW_COUNTER INTEGER not null SUBSYSTEM INT PEDESTAL FLOAT GAIN1 FLOAT GAIN2 FLOAT primary key SEQNO ROW_COUNTER as you can see there is a simple 1 1 correspondence between them except that the database table has two additional leading entries SEQNO INTEGER not null ROW_COUNTER INTEGER not null and a trailing entry primary ke
200. lute trigger time you must add these two counts Figure 3 5 shows a histogram of the calibrated PMT hit charges versus trigger time The ROOT Sum function will histogram the sum of a quantity for each event it can be used to histogram the sum of charge over all AD PMTs 1root 2 CalibReadoutHeader gt Draw chargeAD triggerTimeSec triggerTimeNanoSec le 9 2 detector 2 amp amp ring 4 amp amp column 15 amp amp chargeAD gt 3 amp amp chargeAD lt 7 3 Lege 1The trigger time can be converted to a readable Beijing local time format using the lines described in Sec 3 5 16 3 2 DAYA BAY DATA FILES 25 4root 3 5 CalibReadoutHeader gt Draw Sum chargeAD triggerTimeSec triggerTimeNanoSec le 9 detector 2 kg Sum chargeAD lt 1500 colz i I h H i H i I H 1 E E H 1 H i 4 Sumr chargeAD triggerTimeSec triggerTimeWanoSec e 9 context mDetid 2 8 Suns chargeAD lt 1500 a c Jg 51600 3 g F J 1000 6 4 91400 7 z 4 a E J 5 205 F 7 E J 1200 4 4 7 5 E E 7 N 1000 E J750 E J aK 4 800 4 C J 00 600 4 oH i E qJ E J 400 q ab gt 2 T A A 3 E ES p E J Ey i 1 1 y h 1 i 1 1 1 i i oE Ms e a 2 no i g 13 55 00 3 55 20 55 40 13 56 00 o 13 55 00 13 55 20 13 55 40 13 56 00 21 09 2010 21 09 2010 21 09 2010 21 09 2010 21 09 2010 21 09 2010 21 09 2010 21 09 2010 triggerTimeSec triggerTimeNanoSec 1e 9 tr
201. m15 aileron after type in nuwa py n50 o fifteen root m FullChainSimple T SingleLoader gt log it will generate 50 readouts from IBD and K40 events 15 2 2 Simulation Stage Simulation is separated into a few stages Kinematic Detector Electronic TrigRead and SingleLoader Kinematic stage generates kinematic information including time position particle and its momentum etc Detector stage is to geant4 to do detector response simulation like scattering cerenkov and scintillation light At the end it will generate hit number P E in each PMT and hit information on RPC Electronic simulation convert these physics hit into electronic signal For example hits on PMT are converted to pulses TrigRead will do trigger judgement based on user setting like NHit 10 which means number of fired PMTs must be above 10 When an event is triggered it also produces readout That means it will output ADC and TDC instead of a raw PMT pulse The real data acquisition system works like a pipe line it outputs its result one by one in time order SingleLoader is designed for this purpose The above description can be summarized in Fig 15 1 135 136 CHAPTER 15 SIMULATION PROCESSING MODELS Figure 15 1 Simulation stages 15 2 3 Stage Tool Stage as explained in previous sections is an abstract concept in dividing all simulation components For Fifteen package stage tool physically separates each simulation tools but also is a media in dat
202. me In the constructor a ToolSvc is appended since there was no in the name Since the tool is public the final value 3 will be used by both algi and alg2 An example of how private tools work 1mt MyTool foo 2mt getName gt ToolSvc foo 3 4mt Cut 1 5algi privtool mt 6 algi gets algi foo configured with Cut 1 7mt Cut 2 8alg2 privtool mt 9 for now alg2 gets alg2 foo configured with Cut 2 10 11 after assignment can get renamed copy 12from Gaudi Configuration import Configurable 13mt2 Configurable allConfigurables alg2 foo 14mt2 Cut 3 15 now really alg2 gets alg2 foo configured with Cut 3 Again the same tool configurable is created and implicitly renamed An initial cut of 1 is set and the tool configurable is given to algl Guadi makes a copy and the ToolSvc foo name of the original is changed to alg1 foo in the copy The original then as the cut changed to 2 and given to alg2 Alg1 s tool s cut is still 1 Finally the copied MyTool configurable is looked up using the name alg2 foo This can be used if you need to configure the tool after it has been assigned to alg2 6 5 3 The Package Configure Class and Optional Helper Classes Every package that needs any but the most trivial configuration should provide a Configure class By convention this class should be available from the module named after the package When it is instantiated it shoul
203. mplement Fill method This is the way table row objects get filled from a DbiResultSet that acts like an input stream We have seen a simple example in DbiDemoDatal void DbiDemoData1 Fill DbiResultSet amp rs const DbiValidityRec vrec 4 rs gt gt fSubSystem gt gt fPedestal gt gt fGaini gt gt fGain2 However filling can be more sophisticated DbiResultSet provides the following services string DbiResultSet CurColName const UInt_t DbiResultSet CurColNum const UInt_t DbiResultSet NumCols const DbiFieldType DbiResultSet CurColFieldType const The first 3 give you the name of the current column its number numbering starts at one and the total number of columns in the row DbiFieldType can give you information about the type concept and size of the data in this column In particular you can see if two are compatible i e of the same type Bool_t DbiFieldType IsCompatible DbiFieldType amp other const and if they are of the same capacity i e size Bool_t DbiFieldType IsSmaller DbiFieldType amp other const You can create DbiFieldType objects e g DbiFieldType myFldType Dbi kInt 17 5 CREATING NEW TABLES 167 see enum Dbi Data Types for a full list to compare with the one obtained from the current row In this way filling can be controlled by the names numbers and types of the columns The Fill method of DbiDemoDatal contains both a dumb take the data as it comes and a sma
204. ms There are two algorithms They are listed in table 12 1 12 3 Tools Tools are declared as properties in the algorithms in the previous section Two kinds of tools are present in the EleSim package They are e Hit tools these types of tools take SimHitHeader as input and generate ElecPulseHeader e FEE FEC tools these tools takes the output from hit tools in ElecPulseHeader and create ElecCrate The foundation of these tools are the hardware of FEE for AD and FEC Front end Card for RPC electronics 12 3 1 Hit Tools 12 3 2 FEE Tool EsIdealFeeTool The properties is summaried in table 12 2 Pulses ElecPulse generated in HitTools are first mapped to channels in each FEE board via CableSvc service For each channel pulses are then converted and time sequenced to create two analog signals to simulate real signals in FEE The two major analog signals are RawSignal and shapedSignal The following shows the generation steps e pmt Analog Signal m_pmtPulse nSample vector lt double gt each pulse ElePulse is converted to a pmt analog signal m_pmtPulse nSample according to an ideal pmt waveform parametrization given in equation 12 1 e Shaped PMT Signal m_shapedPmtPulse nSample the pmt analog signal m_pmtPulse nSample is convoluted with shaper transfer function to get the shaper output analog singal shapedP mtPulse nSample 121 122 CHAPTER 12 ELECTRONICS SIMULATION Simulation Chain Partial Only Elec Sim Proce
205. n lt PACKAGE gt lt MODULE gt py myModule py Once you have a copy of the Job Module open it with your favorite text editor The module is written in the Python language http www python org see the Python website for a good tutorial on this language Job Modules are composed of two functions configure and run 1def configure argv 2 A description of your module here 3 nun 4 Most job configuration commands here 5 return 6 7def run app 8 Specific run time configuration nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Filtering SmartFilter python SmartFilter Example py 40 CHAPTER 3 ANALYSIS BASICS 9 Some specific items must go here Python algorithms add libraries etc 10 pass For advice on what lines to modify in the module send your request to the offline software mailing list thetal3 offline dayabay 1bl gov To run your modified version of the module call it in the nuwa py command without the PACKAGE prefix in the module name With no prefix modules from the current directory will be used 1shell gt ls 2myModule py 3shell gt nuwa py n 1 m myModule recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3 4 8 Write a Python analysis Algorithm If you wish to add your own algorithm to NuWa a good place to start is by writing a prototype algorithm in Python Writing your algorithm in Python is much easier than C and does not require you to compile
206. n tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibPmtFineGain spec 198 CHAPTER 19 DATABASE TABLES 19 11 CalibPmtHighGain Table specification source dybgaudi trunk Database DybDbi spec GCalibPmtHighGain spec docstring name dbtype codetype description code2db Sensorld int 11 DayaBay DetectorSensor unique id of this pmt fullPacke SpeHigh float double SPE mean ADC value high gain SpeHighError float double error in SPE Mean ADC value high gain SigmaSpeHigh float double SPE 1 sigma peak width high gain SpeHighFitQual float double SPE fit quality in chi2 ndf high gain Table 19 11 DBI Table specification for class GCalibPmtHighGain which corresponds to table Cal ibPmtHighGain Unttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibPmtHighGain spec 19 12 CALIBPMTHIGHGAINFAKE 199 19 12 CalibPmtHighGainFake Table specification source dybgaudi trunk Database DybDbi spec GCalibPmtHighGainFake spec Expediant table class used to fake the old table see dybsvn ticket 1228 name dbtype codetype description code2db Sensorld int 11 DayaBay DetectorSensor unique id of this pmt fullPacke SpeHigh float double SPE mean ADC value high gain SpeHighError float double error in SPE Mean ADC value high gain SigmaSpeHigh float double SPE 1 sigma peak width high gain SpeHighFitQual float double SPE fit quality in chi2 ndf high gain Table 19 12 DBI Table spe
207. nSimple py you can directly type FullChainSimple py in a tcsh or bash see what happens It is often used to test the configuration needed before running nuwa When nuwa is loading a python module it will check whether it has a configure method User s gaudi algorithms services and tools should go into there Here an object about Fifteen is created and some parameters argv are passed to it Next we will see some details in Fifteen package configuration 1class ConfigureFullChain def __init__ self argv def paradores algo def A A def A def squtipiveditestesaie ssl def contivivetvigtesd sele def contiguas et def configureSimi5 self NoouPwnrooeaaAanoaanpp wn def configure self Oo 00 Now all the details are stripped out and only the skeleton are left indicates the real working code are omitted for a second A class ConfigureFullChain is defined _init__ self argv is always called when a data object is created The useful interface invoked by nuwa will be con figure sel f Note don t confuse with the con figure argu mentioned previously Apparently it has configure functions for Kinematic Detector Electronic TrigRead SingleLoader simu lation stages It also can handle some parameters to be more user friendly in parse rgs The configureSim15 will create an algorithm called Sim15 which is the diver of the simulation job Algorithm Sim15 sits on the top of all the s
208. ne range slope CRLineSlope float double slope of partial linear fit to coarse range CRLineErr float double error of coarse range slope Table 19 7 DBI Table specification for class GCalibFeeGainConv which corresponds to table CalibFeeGain Conv Thttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibFeeGainConv spec 19 8 CALIBFEESPEC 19 8 CalibFeeSpec 195 Table specification source dybgaudi trunk Database DybDbi spec GCalibFeeSpec spec docstring name dbtype codetype description Channelld int 10 unsigned DayaBay FeeChannelId Electronics channel ID number Status int 10 unsigned int Channel status AdcPedestalHigh double double Measured high gain Pedestal ADC value AdcPedestalHighSigma double double high gain Pedestal ADC sigma AdcPedestalLow double double Measured low gain Pedestal ADC value AdcPedestalLowSigma double double low gain Pedestal ADC sigma AdcThresholdHigh double double Channel threshold as measured in ADC AdcThresholdLow double double Channel threshold as measured in ADC Table 19 8 DBI Table specification for class GCalibFeeSpec which corresponds to table CalibFeeSpec Shttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibFeeSpec spec 196 19 9 CalibFeeSpecCleanup CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GCalibFeeSpecCleanup spec docstring name dbtype codet
209. nel 2nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqChannel spec 230 CHAPTER 19 DATABASE TABLES 19 43 DqChannelPacked Table specification source dybgaudi trunk Database DybDbi spec GDqChannelPacked spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number MaskO int 11 Int_t Mask0 bit packing of channel status Mask1 int 11 Int_t Mask1 bit packing of channel status Mask2 int 11 Int_t Mask2 bit packing of channel status Mask3 int 11 Int_t Mask3 bit packing of channel status Mask4 int 11 Int_t Mask4 bit packing of channel status Mask5 int 11 Int_t Mask5 bit packing of channel status Mask6 int 11 Int_t Mask6 bit packing of channel status Table 19 43 DBI Table specification for class GDqChannelPacked which corresponds to table DqChannel Packed http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDqChannelPacked spec 19 44 DQCHANNELSTATUS 231 19 44 DqChannelStatus Table specification source dybgaudi trunk Database DybDbi spec GDqChannelStatus spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number Channelld int 11 DayaBay FeeChannelld Unique id of the channel connected to a pmt fullPackedDa Status tinyint int Channel status good bad Table 19 44 DBI Table specification for class GDqC
210. neutron rate normal or not Reactor tinyint int Reactor normal or not GOOD tinyint int Indicate whether a good run for physics analysis or not Table 19 27 DBI Table specification for class GDataQualityGoodRun which corresponds to table DataQual ityGoodRun 27http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDataQualityGoodRun spec 19 28 DATAQUALITYPMT 19 28 DataQualityPmt 215 Table specification source dybgaudi trunk Database DybDbi spec GDataQualityPmt spec docstring name dbtype codetype description RunNo int 11 int Run Number FileNo int 11 int File Number PmtId int 11 DayaBay DetectorSensor Packed PMT ID Status tinyint int Fitting Resutls Status Chi2ndf float double Chi2 ndf for gain fitting Gain float double Single photoelectron mean ADC value high gain GainErr float double Gain Error DarkRate float double Dark Rate DarkRateErr float double Dark Rate Error ElecNoiseRate float double Electronics Noise Rate ElecNoiseRateErr float double Electronics Noise Rate Error PreAdc float double Pre Adc PreAdcErr float double Pre Adc Error Table 19 28 DBI Table specification for class GDataQualityPmt which corresponds to table DataQuali tyPmt 28nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDataQualityPmt spec 216 19 29 DataQualityRpc CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec
211. nformation is directly extracted from MC truth A simple readouts grouping was implemented Readouts with delta trigger times within 2s are consid ered as one event and shown together But an event only allows one readout for one detector For example a very close retrigger after an energetic muon in the same AD will start a new event This algorithm also works for calibReadout and simHeader Advance Mode One can also directly call the Gaudi Tool EvtDsp and plot the charges and times calculated in a different manner In the simple mode no selection is applied to select hits however this is not the best choice in some cases for example some hits times are out of the physically allowed window like the blue hit in the inner water shield in Fig 2 1 seems like a noise hit One can also make a selection in an analysis algorithm to show only a fraction of interesting events or have a different event grouping algorithm To use this feature one need to follow the standard Gaudi procedure to locate a tool EvtDsp first i e add use EvtDsp module in cmt requirements file 1 use EvtDsp v Visualization then get access to this tool finclude EvtDsp IEvtDsp h 1 2 3 IEvtDsp x m_evtDsp 4 StatusCode sc toolSvc gt retrieveTool EvtDsp EvtDsp m_evtDsp After this three simple interfaces are available and they can be plugged into anywhere of a user code Plot pool virtual StatusCode plotPool DayaBay Detector det 1
212. nnel that was read out hit a boolean value indicating a hit readout a pointer back to the ReadoutRpcCrate which contains this channel readout 131 132 CHAPTER 14 READOUT ReadoutEvent Modified on Wed Dec 10 2008 ReadoutHeader o Readout detector Detector triggerNumber unsigned int triggerTime TimeStamp triggerType Trigger TriggerType_t header ReadoutHeader ReadoutPmiCrate channelReadout std map lt FeeChannelld ReadoutPmtChannet gt lo channelld FeeChannelld tdo std wector lt int gt adc std map lt int int adcGain FeeGain FeeGain_t readout ReadoutPmtCrate channelReadout std map lt FeeChannelld ReadoutRpcChannelt lo ReadoutRpcChanne channelld FeeChannelld hit bool readout ReadoutRpcCrate Figure 14 1 The ReadoutHeader contains a single Readout The two flavors of readouts are discussed in 14 2 14 3 SimReadout Header The SimReadoutHeader contains all the readout headers produced during a single execution cycle This can include 0 N readouts for each detector 14 4 Readout Algorithms ReadoutSim currently has two Algorithms described below 14 5 READOUT TOOLS 133 SimReadoutEvent Madified on Wed Dec 10 2008 SimReadoutHeader readouts std vector lt DayaBay SimReadout gt header SimReadoutHeader readout Readout Figure 14 2 The SimReadoutHeader holds multiple SimReadout s which in turn contain a pointer to a single Readout object The Re
213. nning the same job twice can produce different results if database updates that have occurred between the two runs For certain tasks e g validation its necessary to decouple jobs from recent updates and this requires database rollback i e restoring the database to a previous state Rollback works by exploiting the fact that data is not in general ever deleted from the database Instead new data is added and by the rules of Ambiguity Resolution see the previous section supersede the old data All data is tagged by the date it was inserted into the local database so rollback is implemented by imposing an upper limit on the insertion date effectively masking out all updates made after this limit 17 2 11 Lightweight Pointers to Heavyweight Data One of the interface s responsibilities is to minimise I O Some requests particularly for Detector Configu ration can pull in large amounts of data but users must not load it once at the start of the job and then use it repeatedly it may not be valid for all the data they process Also multiple users may want access to the same data and it would be wasteful for each to have their own copy To deal with both of the above the interface reuses the concept of a handle or proxy that appears in other packages such as Candidate The system works as follows 1 When the user wants to access a particular table they construct a table specific pointer object This object is very small and is suitable to
214. nt Using Database Config s os environ DBCONF For framework jobs when write access to the database is required or other special configuration is desired a less flexible approach is preferred With a comment pointing out that some special configuration in my cnf is required Be careful not to disclose real passwords passwords do not belong in repositories nun NB requires section of my cnf dyb_off line host dybdb1 ihep ac cn user dayabay password youknowit dbi dyb_offline db2 dyb_other nun import os os environ DBCONF dyb_offline os environ DBCONF_URL mysql host s db1 s mysql host s db2 s print Using Database Config s os environ DBCONF 17 3 RUNNING 155 17 3 2 Configuring The database can be configured through a Gaudi Service before starting your job Once the job is running you can configure the DatabaseInterface via the DbiSve from gaudimodule import theApp AppMgr theApp Dlls Conventions theApp Dlls Context theApp Dlls DatabaseInterface theApp createSvc DbiSvc dbisvc theApp service DbiSvc dbisvc lt property gt lt newvalue gt dbisvc lt property gt lt newvalue gt Rollback To impose a global rollback date to say September 27th 2002 theApp service DbiSvc RollbacDates 2002 09 27 00 00 00 This will ensure that the interface ignores data inserted after
215. nt PullEvent 4 DrawHistoryAlg DrawHistory DumpUnobservableStatisticsAlg DumpUnobserved The DrawHistoryAlg produces two dot files which can be processed by the GraphViz application A very nice user friendly version of this exists for the Mac The dot files describe the inter relation of the output objects so that they can be drawn in tree like structures Sample output is shown in Figures 11 3 6 and 11 3 6 The DrawHistoryAlg can be configured like so o a lapp algorithm DrawHistory do_hits 0 2app algorithm DrawHistory track_filename tracks_ d dot 3app algorithm DrawHistory trackandvertex_filename vertices_and_tracks_ d dot The filename configuration is for two output files Using d indicates that the event number should be used to output one file per event The do_hits option indicates whether SimHits should be shown on the plot For scintillator events this often generates much too much detail The DumpUnobservableStatisticsAlg algorithm simply prints out the counts sum mean and rms for each statistic that was declared for each event This is useful for simple debugging 116 CHAPTER 11 DETECTOR SIMULATION Figure 11 7 Output of tracks and vertices file for a single 1 MeV position Boxes represent SimTracks and circles repre
216. nt accepted even they didn t passed trigger Since they are also in the pipeline their time is synchronized to the other geant4 simulated hits User won t obeserve a big delay between fast simulated muon and other events 15 2 7 TrigReadProc Trigger simulation and Readout simulation are combined together into one simulation stage because they all needs input from electronic simulation i e pulses information In electronic simulation there is no such requirement that only some detector can join the simulation so in the same way trigger will work for all required detectors In principle the different delay from different electronic channel can flip the time order between different events however the time gap requirement is at the scale of 10us It is believed that the possible time flip pa 2 3 4 5 6 7 a fF WN KF OO O 0 ona O 20 138 CHAPTER 15 SIMULATION PROCESSING MODELS caused by electronic simulation will never go beyond that and there is no physics concern in simulating such a effect so there is no complex time comparison in TrigReadProc 15 2 8 SingleLoader Triggers and readouts found in ElecHeader are packed into one SimReadoutHeader Certainly it is also possible that no trigger is found since there are many low energy background events SingleLoader caches all the triggers and readouts and output them one by one When its own buffer is empty it will automatically ask data from lower stage 15 2
217. ntAD_calib nHitsAD calib topOrBottom nHitsAD_calib acuColumn nHitsAD_calib nHitsPool timePool nHitsPool chargePool nHitsPool hitCountPool nHitsPool wallNumber nHitsPool wallSpot nHitsPool Calib PMT hits Water Pool PMT hits inwardFacing nHitsPool Item ROOT Variable Description site site Site ID number detector detector Detector ID number event number event Number Unique ID number for each triggered event in a run trigger type triggerType All active triggers logically OR d trigger time triggerTimeSec Trigger time seconds from Jan 1970 unixtime trigger TimeNanoSec Trigger time nanoseconds from last second AD PMT hits nHitsAD Number of AD PMT hits Calibrated time ns of PMT hit relative to trigger time Calibrated charge photoelectrons of PMT hit Index of this hit for this PMT 0 1 2 PMT ring in AD counts 1 to 8 from AD bottom PMT column in AD counts 1 to 24 counterclockwise Number of AD calibration PMT 2 inch hits Calibrated time ns of PMT hit relative to trigger time Calibrated charge photoelectrons of PMT hit Index of this hit for this PMT 0 1 2 PMT vertical position 1 AD top 2 AD bottom PMT radial position ACU axis A 1 B 2 C 3 Number of Water Pool PMT hits Calibrated time ns of PMT hit relative to trigger time Calibrated charge photoelectrons of PMT hit Index of this hit for this PMT 0 1 2 PMT wall number PMT spot number in wall PMT
218. nvolves registering a factory class with Gaudi that knows how to produce instances of the component given the name of the class This registration happens when the 67 68 CHAPTER 6 OFFLINE FRAMEWORK component library is linked and this linking can be done dynamically given the class name and the magic of generated rootmap files As a result C or Python code can request a component or Python shadow class given its class name At the same time as the request the resulting instance is registered with Gaudi using a nick name This nick name lets you configure multiple instances of one component class in different ways For example one might want to have a job with two competing instances of the same algorithm class run on the same data but configured with two different sets of properties 6 3 Common types of Components The main three types of Gaudi components are Algorithms Tools and Services 6 3 1 Algorithms e Inherit from GaudiAlgorithm or if you will produce data from DybAlgorithm e execute initialize finalize and associated requirements eg calling GaudiAlgorithm initialize e TES access with get and put or getTes and putTES if implementing DybAlgorithm There is also getAES to access the archive event store e Logging with info etc e required boilerplate _entries amp load files cpp macros e some special ones sequencer others Algorithms contain code that should be run once per execution
219. ob Module Sec 3 4 7 e Write your own analysis Algorithm Python Sec 3 4 8 e Write your own analysis Algorithm C Sec 3 4 9 e Modify an existing part of NuWa C Sec 3 4 10 3 4 1 See the history of a NuWa File Before using a NuWa data file you may want to see what processing has already been done on the file The following command will print the history of all NuWa jobs that have been run to produce this file 1shell gt nuwa py n 0 no history m JobInfoSvc Dump 2 recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root You will see much information printed to the screen including the following sections which summarize the NuWa jobs that have been run on this file iG 2 3 4 al FwoONrF OO WON O 5C 61 7 8 9 20 21 22 23 24 25 26 27 28 ached Job Information jobId daf3a684 6190 11e0 82f7 003048c51482 cmtConfig x86_64 s1c4 gcc34 opt command eliza7 dayabay scratch dandwyer NuWa trunk opt dybgaudi InstallArea scripts nuwa py n 0 no history mJobInfoSvc Dump recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root hostid 931167014 jobTime Fri 08 Apr 2011 03 32 40 0000 nuwaPath elizai6 dayabay users dandwyer installs trunk_2011_03_30_opt NuWa trunk revision 11307 11331 username dandwyer ached Job Information jobId 6 5c02f4 6190 11e0 897b 003048 c51482 cmtConfig x86_64 s1c4 gcc34 op
220. of unobservable statistics 11 3 1 Particle Histories Geant 4 is good at simulating particles efficiently To this end it uses a continually evolving stack of particles that require processing As particles are simulated they are permanently removed from the stack This allows many particles to be simulated in a large event without requiring the entire event to be stored at one time However users frequently wish to know about more than simply the input primary particles and output hits of a simulation and instead want to know about the intermediate particles But simply storing all intermediate particles is problematic for the reason above too many particles will bring a computer s virtual memory to it s knees Particle Histories attempts to give the user tools to investigate event evolution without generating too much extraneous data The philosophy here is to generate only what the user requests up to the granularity of the simulation and to deliver the output in a Geant agnostic way so that data may be persisted and used outside the Geant framework Particle History Data Objects Let us briefly review how Geant operates A particle is taken off the stack and a G4Track object is initialized to hold it s data The particle is then moved forward a step with an associated G4Step object to hold the relevant information In particular a G4Step holds two G4StepPoint representing the start and end states of the that particle The Partic
221. ointing North and Z pointing up It is this system in which Geant4 works Site Each site has a local coordinate system with X pointing towards the exit and Z pointing up Looking down the X Y origin is at the center of the tank mid way between the center of the ADs The Z origin is at the floor level which is also the nominal water surface This makes the Pools and ADs at negative Z the RPCs at positive Z AD Each AD has an even more local coordinate system The Z origin is mid way between the inside top and bottom of the Stainless Steal vessel This Z4p 0 origin is nominally at Zgite 5m 7 5mm The Z axis is collinear with the AD cylinder axis and the X and Y are parallel to X and Y of the Site coordinate system respectively The Site and AD coordinate systems are related to each other by translation alone Site coordinate systems are translated and rotated with respect to the Global system Given a global point the local Site or AD coordinate system can be found using the CoordSysSvc service like 1 Assumed in a GaudiAlgorithm 2IServicex isvec 0 3StatusCode sc service CoordSysSvc isvc true 4if sc isFailure handle_error 5ICoordSvcx icss 0 6sc isvc gt queryInterface IID_ICoordSysSvc void amp icss 7if sc isFailure handle_error 94 CHAPTER 9 DETECTOR DESCRIPTION 8 9 Gaudi XYZPoint globalPoint 10 IDetectorElement de icss gt coordSysDE globalPoint 11if de
222. on for class GDaqRunInfo which corresponds to table DaqRunInfo http ayabay ihep ac cn tracs svn browser audi trun atabase i spec aqRunInfo spec 25http dayabay ihep dybsvn b dybgaudi k Database DybDbi spec GDaqRunInfo sp 19 26 DATAQUALITYDETECTOR 19 26 DataQualityDetector 213 Table specification source dybgaudi trunk Database DybDbi spec GDataQualityDetector spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number Detectorld int 11 int Detector ID SinglesRate float double Singles Rate IBDRate float double IBD rate number SPNRate float double Spallation neutron rate MuonRate float double Muon Rate Table 19 26 DBI Table specification for class GDataQualityDetector which corresponds to table DataQual ity Detector 26http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GDataQualityDetector spec 214 19 27 DataQualityGoodRun CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GDataQualityGoodRun spec docstring name dbtype codetype description code2db RunNo int 11 int Run Number FileNo int 11 int File Number PmtHealth tinyint int PMT condition of this file RpcHealth tinyint int RPC condition of this file TriggerHealth tinyint int Trigger condition of this file Singles tinyint int Singles Rate normal or not IBD tinyint int IBD rate number normal or not SPN tinyint int Spallation
223. ould be configured through configurables But there are a few things to be aware of or else one can become easily tricked e Tool configurables can be public or private A public tool configurable is owned by ToolSvc and shared by all parents a private one is owned by a single parent and not shared e By default a tool configurable is public e Ownership is indicated by prepending the parent s name plus a dot to the a simple name e Ownership is set either when creating the tool configurable by prepending the parent s name or during assignment of it to the parent configurable e During assignment to the parent a copy will be made if the tool configurable name is not consistent with the parent name plus a dot prepended to a simple name What this means is that you may end up with different final configurations depending on e the initial name you give the tool configurable e when you assign it to the parent e if the parent uses the tool as a private or a public one 72 CHAPTER 6 OFFLINE FRAMEWORK e when you assign the tool s properties To best understand how things work some examples are given An example of how public tools work 1mt MyTool foo 2mt getName gt ToolSvc foo 3 4mt Cut 1 5algi pubtool mt 6mt Cut 2 7alg2 pubtool mt smt Cut 3 9 algi and alg2 will have same tool both with cut 3 Here a single MyTool configurable is created with a simple na
224. owStream ors const rather than a DbiResultSet reference Both these classes inherit from DbiRowStream so the same set of methods string DbiResultSet CurColName const UInt_t DbiResultSet CurColNum const UInt_t DbiResultSet NumCols const DbiFieldType DbiResultSet CurColFieldType const UInt_t DbiResultSet CurRowNum const string DbiResultSet TableName are available So as with the Fill method there is scope for Store to be smart The quotes are there because it often does not pay to be too clever Also like the Fill method its passed a DbiValidityRec pointer which is only zero when filling DbiValidityRec objects so that the validity of the row can be accessed if required 17 6 6 Creating and Writing Temporary Tables It is possible to create and write temporary tables during execution Temporary tables have the following properties e For the remainder of the job they look like any other database table but they are deleted when the job ends e They completely obscure all data from any permanent table with the same name in the same database Contrast this with the cascade which only obscures data with the same validity e They are local to the process that creates them Even the same user running another job using the same executable will not see these tables Temporary tables are a good way to try out new types of table or different types of data for an existing table without modifying the dat
225. own as Detector Elements Gaudi nomenclature Not all volumes are directly referenced in this hiearchy only those that are considered important The data making up the description exists in a variety of forms XML files The definitive source of ideal geometry is stored in XML files following a well defined DTD schema DetDesc TDS objects In memory the description is accessed as objects from the DetDesc package stored in the Transient Detector Store These objects are largely built from the XML files but can have additional information added such as offsets from ideal locations Geant4 geometry Objects in the Materials and Geometry sections can be converted into Geant4 geometry objects for simulation purposes 9 1 1 Volumes There are three types of volumes in the description Figure 9 1 describes the objects that store logical physical and touchable volume information Logical XML lt logvol gt C ILVolume 91 92 CHAPTER 9 DETECTOR DESCRIPTION Description The logical volume is the basic building block It combines a shape and a material and zero or more daughter logical volumes fully contained inside the shape Example The single PMT logical volume placed as a daughter in the AD oil and Pool inner outer water shields 9 1 2 Physical XML lt physvol gt C IPVolume Description Daughters are placed inside a mother with a transformation matrix giving the daughters translation and rotation with respect to the mot
226. parameter names listed in table 11 4 11 3 TRUTH INFORMATION 115 event 0 process_id 0 e KE 611 997 keV SimTrack 1 e 1 KE 611 997 keV with 5 vertices 6253 skipped of type opticalphoton SimTrack 6245 gamma 4 annihil KE 510 999 keV with 25 vertices 2425 skipped of type opticalphoton SimTrack 6246 gamma 4 annihil KE 510 999 keV with 23 vertices 1770 skipped of type opticalphoton SimTrack 12367 SimTrack 16155 e 4 LowEnCompton KE 231 767 keV with 5 vertices 2395 skipped of type opticalphoto SimTrack 11055 e 4 LowEnPhotoElec KE 30 0467 keV with 2 vertices 278 skipped of type opticalphoton SimTrack 6633 e 4 LowEnCompton KE 296 055 keV with 5 vertices 3040 skipped of type opticalphoton e 4 LowEnPhotoElec KE 29 9338 keV with 2 vertices 310 skipped of type opticalphoton Figure 11 6 Output of tracks file for a single 1 MeV positron Circles denote SimTracks values listed are starting values In this example do_hits was set to zero 11 3 6 The DrawHistoryAlg Algorithm These lines in your python script will allow you to run the DrawHistoryAlg and the DumpUnobservableStatis ticsAlg which provide a straightforward way of viewing the output of the Particle Histories and Unobserv ables respectively 1simseq Members GiGaInputStream GGInStream 2 DsPushKine PushKine 3 DsPullEve
227. pecifying selection rules for the tracks and the vertices Only those that pass the rules will be included By default only primary tracks are saved Here are some examples of a track selection Make tracks for everything that s not an optical photon trackSelection pdg 20022 Or make tracks only for things that start in the GD scintillator and have an energy gt 1Mev trackSelection MaterialName dd Materials GdDopedLS and E gt 1 MeV And here are some examples of a vertex selection Make all vertices one vertex per Step vertexSelection any Make vertices only when a particle crosses a volume boundary vertexSelection VolumeChanged 1 2 8 QUICK START WITH TRUTH INFORMATION 11 As an aside one particular application of the Particle Histories is to draw a graphical representation of the particles using a package called GraphViz To do this put the DravHistoryAlg algorithm in your sequence This will generate files in your current directory named tracks_N dot and tracks_and_vertices_N dot where N is the event number These files can be converted to displayable files with GraphViz s dot program Configuring Unobservable Statistics What statistics are collected and when they are collected is controlled by a collection of triples 1 A name for the statistics for later reference 2 An algebraic formula of predefined variables defining the value to collect 3 A rule stating what condi
228. python job scripts may be specified 28 29 Modules and scripts are loaded in the order they are specified on 30 the command line 31 32 Finally input ROOT files may be specified These will be read in 33 the order they are specified and will be assigned to supplying 34 streams not specificially specified in any input stream map 35 36 The listing of modules job scripts and or ROOT files may be 37 interspersed but must follow all options 38 39 40 410ptions 42 h help show this help message and exit 43 A no aes Do not use the Archive Event Store 44 1 LOG_LEVEL log level L0OG_LEVEL 45 Set output log level 46 C COLOR color COLOR 47 Use colored logs assuming given background light or 48 dark 49 i interactive Enter interactive ipython shell after the run 50 completes def is batch 51 8 phow includes Show printout of included files 52 m MODULE module MODULE 4 Actual output may differ slightly 76 F G CHAPTER 6 OFFLINE FRAMEWORK Load given module and pass optional argument EXECUTIONS executions EXECUTIONS Number of times to execute list of top level algorithms OUTPUT output 0UTPUT Output filename OUTPUT_STREAMS output streams 0UTPUT_STREAMS Output file map INPUT_STREAMS input streams INPUT_STREAMS Input file map HOSTID hostid HOSTID Force given hostid RUN run RUN S
229. r must be the first two columns in the database table but are not reflected in the table row class Filling a table row object from the database is done using the class s Fill method For our example void DbiDemoDatal Fill DbiResultSet rs const DbiValidityRec vrec 4 rs gt gt fSubSystem gt gt fPedestal gt gt fGaini gt gt fGain2 the table row object is passed a DbiResultSet which acts rather like an input stream The sequence number has already been stripped off the class just has to fill its own data member The Databaselnterface does type checking see the next section but does not fail if there is a conflict it just produces a warning message and puts default data into the variable to be filled The second argument is a DbiValidityRec which can if required be interrogated to find out the validity of the row For example const ContextRange amp range vrec gt GetContextRange vrec may be zero but only when filling DbiValidityRec objects themselves On all other occasions vrec should be set Creating a Database Table The previous section gave a simple MySQL example of how a database table is defined There is a bit more about MySql in section 17 8 The table name normally must match the name of the table row class that it corresponds to There is a strict mapping between database column types and table row data members although in a few cases one column type can be used to load more than one type of table ro
230. re AD db 0111 strategy Material material GdDopedLS mode Uniform lifetime 78 4 units second daya bay wallTime self start_time_seconds ibd_gds ThisStageName Kinematic self stage_cfg KinematicSequence Members append ibd_gds from Gnrtr Radioact import Radioact K40 k40_gds Radioact name K40_gds volume dd Structure AD db oili nuclide K40 abundance 3 0lei7 strategy Material material GdDopedLS start_time self start_time_seconds k40_gds ThisStageName Kinematic self stage_cfg KinematicSequence Members append k40_gds site Basically only one line command is needed to specify one type of event In the end their stage names are all assigned to be Kinematic and it generator algorithms are also added to stage tool Kinematic i e the connection between stage tool and processors are built up For details about generators configuration user can refer to previous sections and they also need to have the knowledge of detector geometry and material def configureDetector self gt Configure the Detector stage 15 2 FIFTEEN 141 4 import DetSim 5 ds DetSim Configure physlist DetSim physics_list_basic DetSim physics_list_nuclear 6 site dayabay 7 use_push_algs False 8 9 QuantumEfficiency CollectionEfficiency QEScale 0 24 1 0 9 0 from DetSim DetSimConf import DsPhysConsOptical 1 optical DsPhysConsOptical 2
231. re method Similar to the Fill method a row must know how to store itself in the database Again this is usually simple you simply stream out the row elements to the stream provided void DbiDemoDatal Storel DbiOutRowStream amp ors const DbiValidityRec vrec const ors lt lt fSubSystem lt lt fPedestal lt lt fGaini lt lt fGain2 must impliment the GetDatabaseLayout method This method is used by a user wanting to do first time creation of the databases from within the code Doing this simplifies the table creation process slightly simply list the columns that this class requires 168 CHAPTER 17 DATABASE std string DbiDemoDatal GetDatabaseLayout std string table_format SUBSYSTEM int y PEDESTAL float GAIN1 float n GAIN2 float ts return table_format May overload the CanL2Cache method As explained in section 17 2 the Level 2 cache allows table loading to be speeded up by caching the query results as disk files Only certain tables support this option which by default is disabled To enable it the table row object overrides this method as follows Bool_t CanL2Cache const return kTRUE Only table row classes who data members are built in data types ints floats and chars should do this Table rows having objects or dynamic data e g string or pointers must not claim to support L2 caching Note the table row doesn t need code to save restore to the cache this is handled by the
232. reconstructed values energyStatus recTrigger energyStatus energy recTrigger energy nHit calibStatsHdr getInt nHit A Fill the histograms if energyStatus ReconStatus kGood if detector DetectorId kAD1 self nhitVsEnergyAD1H Fill energy units MeV nHit elif detector Detectorld kAD2 self nhitVsEnergyAD2H Fill energy units MeV nHit return SUCCESS The next section provides more information on data analysis using NuWa Sec 3 3 3 2 6 Advanced Examples The following section presents advanced examples of working with Daya Bay data files All example scripts can be found in the Tutorial Quickstart software package Combining Unfriendly Trees The examples in the previous section show how to histogram data by friending trees Trees can only be friended if there is a natural relationship between the trees The Coincidence and Spallation trees collect data from multiple triggers into one entry As a consequence you cannot friend these trees with the trees which contain data with one trigger per entry e g CalibStats AdSimple etc For example you may want to histogram data in the Coincidence tree but you want to apply a cut on a variable that is only present in CalibStats It is possible to combine data from these unfriendly trees The approach is to manually look up the data for the corresponding entries between the unfriendly trees By building on the example dybTreeGetLeaf C
233. rections 9 8 Visualization Visualization can be done using our version of LHCb s PANORAMIX display This display is started by running 1shell gt nuwa py V 9 8 VISUALIZATION 95 Take this tour First note that in the tree viewer on the left hand side if you click on a folder icon it opens but if you click on a folder name nothing happens The opposite is true for the leaf nodes Clicking on a leaf s name adds the volume to the viewer Try openning dd Geometry PMT IvHemiPmt You may see a tiny dot in the middle of the viewer or nothing because it is too small Next click on the yellow blue eyeball icon on the right This should zoom you to the PMT You can then rotate with a mouse drag or the on screen rollers If you have a mouse with a wheel it will zoom in out Cntl drag or Shift drag pans Click on the red arrow and you can pick volumes A Ctrl pick will delete a volume A Shift click will restore it note some display artifacts can occur during these delete restores Go back to the Michael Jackson glove to do 3D moves You can clear the scene with Scene Scene Clear You will likely want to do this before displaying any new volumes as each new volume is centered at the same point Scene Frame m is useful thing to add Materials can t be viewed but dd Structure can be Another thing to try Click on dd Structure DayaBay select the yellow blue eye then the red arror and Ctri click away t
234. retrigger Number of AD triggers between this muon and next muon Detector ID of AD trigger Trigger number of AD trigger Trigger type of AD trigger Time between AD trigger and first prompt muon trigger ms AD energy reconstruction status AD reconstructed energy MeV AD position reconstruction status AD reconstructed X position mm AD reconstructed Y position mm AD reconstructed Z position mm 55 OomMA NOUN FF WN Ke Pe o 56 CHAPTER 3 ANALYSIS BASICS Spallation data in NuWa Here is a cheat sheet for processing spallation data in Python These lines can be used in the execute function of a Python algorithm evt self evtSvc Access the Spallation Data Header A This is a container for muon spallation data spallData evt Event Data Muon Spallation if spallData None self debug No spallation data this cycle return SUCCESS Access the spallation data nSpall spall get nSpall value 3 5 13 Coincidence Data Coincidence data in ROOT The following table summarizes the coincidence data visible directly in ROOT Array items have their length given in the brackets i e name length ROOT will automatically draw all entries in the array given the array name See the ROOT User s Guide for more details on working with Trees http root cern ch download doc 12Trees pdf 3 5 CHEAT SHEETS ROOT Variable Description multiplicity
235. rks done until it finds one returning its number in the cascade It returns 1 if it fails For this to work properly the first entry in the cascade must accept it so that it will be taken in preference to the true database It is recommended that the first entry be the temp database for everyone has write access to that and write access is needed to create even temporary tables So a suitable cascade might be setenv ENV_TSQL_URL mysql pplx2 physics ox ac uk temp mysql pp1x2 physics ox ac uk offline Having found a database and defined the new or replacement table you can now create a DbiWriter and start writing data as describe in section 17 6 You have to make sure that the DbiWriter will output to the correct database which you can either do by specifying it using the 5th arg of its constructor DbiWriter const ContextRange amp vr Int_t aggNo Dbi Task task 0 TimeStamp versionDate TimeStamp UInt_t dbNo 0 or alternatively you can set it after construction DbiWriter lt DbiDemoDatal gt writer range aggNo writer SetDbNo dbNoTemp As soon as the table has been defined it will as explained above completely replace any permanent table in the same database with the same name However if there is already data in the cache for the permanent table then it may satisfy further requests for data To prevent this from happening you can clear the cache as described in the next section Do NOT write permanent
236. rs immediately preceding the current trigger When This flag is true if the electronics memory buffers filled immediately preceding this 00 NODA PWN HK Roe o aa e won Fe 3 5 CHEAT SHEETS 53 Calibrated statistics data in NuWa Here is a cheat sheet for processing calibrated statistics data in Python These lines can be used in the execute function of a Python algorithm evt self evtSvc Access the Calibrated Statistics Data Header This is a container for calibrated statistics data calibStats evt Event Data CalibStats if calibStats None self debug No calibrated statistics return FAILURE Access the Calibrated statistics data nPESum calibStats get nPESum value 3 5 11 Reconstructed Data Reconstructed data in ROOT The following table summarizes the reconstructed data visible directly in ROOT Reconstruction can op tionally estimate an energy a position and or a track direction The status variables should be checked to determine whether reconstruction has successfully set any of these quantities Item ROOT Variable Description site site Site ID number detector detector Detector ID number trigger type triggerType All active triggers logically added trigger time triggerTimeSec Trigger time count in seconds from Jan 1970 unixtime triggerTimeNanoSec Trigger time count of nanoseconds from last second energy energyStatus Statu
237. rs rather than days it may waste time doing the extra searches although the results would be valid e For sparse aggregation see 17 2 2 The algorithm opens up the window on the basis of the aggregates present at the supplied context so won t take account of aggregates not present and might over estimate the time window The following DbiResultPtr methods support this request DbiResultPtr const Context amp vc Dbi Task task Dbi kDefaultTask Dbi AbortTest abortTest Dbi kTableMissing Bool_t findFullTimeWindow true DbiResultPtr const string amp tableName const Contextk vc Dbi fgDefaultContext Dbi Task task Dbi kDefaultTask Dbi AbortTest abortTest Dbi kTableMissing Bool_t findFullTimeWindow true UInt_t NewQuery Context vc Dbi Task task 0 Bool_t findFullTimeWindow true It is selected by passing in the value false for findFullTimeWindow 17 9 3 Timing DbiTimerManager is a static object that provides performance printout when enabled By default it is enabled but can be disabled by DbiTimerManager gTimerManager Enable false Chapter 18 Database Maintanence 18 1 Introduction The DatabaseMaintenance package produces a single binary application dbmjob that provides very basic database maintenance support Specifically its current function is only as a tool to distribute data between databases GlobalSeqNo provides globally unique SeqNo Update
238. rt look at the column name code Here is the latter Int_t numCol rs NumCols The first column SeqNo has already been processed for Int_t curCol 2 curCol lt numCol curCol 4 string colName rs CurColName if colName SubSystem rs gt gt fSubSystem else if colName Pedestal rs gt gt fPedestal else if colName Gain1 rs gt gt fGainl else if colName Gain2 rs gt gt fGain2 else LOGDEBUG1 dbi lt lt Ignoring column lt lt curCol lt lt lt lt colName lt lt lt lt not part of DbiDemoDatai lt lt endl rs IncrementCurCol Being smart comes at a price if your table has many rows valid at at time defensive programming like this can cost performance In such cases and if the table only exists is a few variants its better to determine the variant and then branch to code that hardwires that form Other services that DbiResultSet offers are UInt_t DbiResultSet CurRowNum const Bool_t DbiResultSet IsExhausted const string DbiResultSet TableName These tell you the current row number whether there is no data left and the name of the table Also note that it is not a rule that database columns and class data members have to be in a 1 1 correspondence So long as the table row can satisfy its clients see below it can store information derived from the database table rather than the data itself Must impliment the Sto
239. s friendly tree around for later reuse then you should write it to a file TFile outputFile friendlyCalibStats root RECREATE calibStatsFriendlyT SetDirectory amp outputFile calibStatsFriendlyT Write The generation of this reformatted friendly tree relies on the fairly complex helper function makeFriendTree 3 2 DAYA BAY DATA FILES 33 1TTree makeFriendTree TChain mainT 2 TChainx unfriendlyT const string amp mainEntriesName const std vector lt string gt amp friendVarNames const string amp indexMajorName const string amp indexMinorName a a e Ww One entry in the tree mainT corresponds to multiple entries in the unfriendlyT tree these are the Coincidence and CalibStats trees respectively in our example mainEntriesName is the name of the branch in mainT that tells us the count of unfriendlyT entries that correspond to the current mainT entry This is the variable multiplicity in our example which tells us how many AD triggers are in the current coincidence multiplet The variables names given in friendVarNames are reformatted from single numbers i e float friendVar in the unfriendlyT tree to arrays i e float friendVar multiplicity in the new friendly tree returned by the function For our example these are the CalibStat variables MaxQ and NominalCharge The indexMajorName and indexMinorName variables are present in both trees and are used to correlate one entry in the mainT with mult
240. s a class that is templated on the table row class so in this case the instantiated class is DbiResultPtr lt DbiDemoDatal gt and to instantiate an object of this class you just need a Context object Suppose vc is such an object then this creates the pointer DbiResultPtr lt DbiDemoDatai gt myResPtr vc This statement creates a DbiResultPtr for DbiDemoDatal class First it searches through the database for all DbiDemoDatal objects that are valid for vc then it assembles them into a table and finally passes back a pointer to it Not bad for one statement The constructor can take a second argument DbiResultPtr Context vc Dbi SubSite subsite 0 Dbi Task task 0 Dbi SubSite is an optional parameter that sub divides a table to select a specific component at a given detector Site e g an antineutrino detector Dbi Task offers a way to sub divided a table according to the mode of operation For example a Detector Configuration data could have two modes one for raw calibration and another for refined calibration If the concept of a subsite or task is not relevant for a particular database table then the parameter should be left at its default value of 0 Otherwise data should be allocated a unique positive number and then selection will only pick rows with the required value of task The constructor can take further arguments which can normally be left at their default values a Dbi AbortTest see section 17 4 4 and a Bool_t find
241. s a release For now see https wiki bn1 gov dayabay index php title Category 0ffline_ Software_Releases e What is a package For now see https wiki bnl gov dayabay index php title CMT_Packages e What is a project For now see https wiki bnl1 gov dayabay index php title CMT_Projects 5 3 2 Personal Projects e Using a personal project with projects from a NuWa release e CMTPROJECTPATH For now see https wiki bnl1 gov dayabay index php title CMT_Projects 5 4 VERSION CONTROL YOUR CODE 65 5 4 Version Control Your Code 5 4 1 Using SVN to Contribute to a Release 5 4 2 Using GIT with SVN Advanced developers may consider using git to interface with the SVN repository Reasons to do this include being able to queue commits advanced branching and merging sharing code with other git users or with yourself on other computers with the need to commit to SVN In particular git is used to track the projects gaudi etc while retaining the changes Daya Bay makes For more information see https wiki bnl gov dayabay index php title Synchronizing_Repositories 5 5 Technical Details of the Installation 5 5 1 LCGCMT The LCGCMT package is for defining platform tags basic CMT macros building external packages and glueing them into CMT Builders The builders are CMT packages that handle downloading configuring compiling and installing external packages in a consistent manner They are used by dybinst or can be run dir
242. s entry Paro float double Parameter 0 for time correction Pari float double Parameter 1 for time correction Par2 float double Parameter 2 for time correction Par3 float double Parameter 3 for time correction Par4 float double Parameter 4 for time correction Par5 float double Parameter 5 for time correction FitQual float double Fit quality could be chi2 ndf for instance Table 19 18 DBI Table specification for class GCalibPmtTiming which corresponds to table CalibPmtTim ing ttp ayabay ihep ac cn tracs svn browser audi trun atabase i spec alibPmtTiming spec 18http dayabay ihep dybsvn b dybgaudi k Database DybDbi spec GCalibPmtTiming sp 206 19 19 CalibRpcSpec CHAPTER 19 DATABASE TABLES Table specification source dybgaudi trunk Database DybDbi spec GCalibRpeSpec spec Calibration data for RPC layers warning the attributes PanelRow PanelColumn and Layer duplicate information within RpcSens name dbtype codetype description code2db RpcSensorld int DayaBay RpcSensor ID of RPC sensor for layer fullPackedData Efficiency float double Efficiency of one RPC layer EfficiencyError float double Efficiency error of one RPC layer NoiseRate float double Noise rate of one RPC layer NoiseRateError float double Noise rate error of one RPC layer Table 19 19 DBI Table specification for class GCalibRpcSpec which corresponds to table CalibRpcSpec 19http dayabay ihep ac cn tracs dyb
243. s of energy reconstruction 0 unknown 1 good gt 1 failures energy reconstructed energy MeV energyQuality Measure of fit quality x likelihood etc position positionStatus Status of position reconstruction 0 unknown 1 good gt 1 failures x reconstructed x position mm in AD Water Pool or RPC coordinates y reconstructed y position mm in AD Water Pool or RPC coordinates Zz reconstructed z position mm in AD Water Pool or RPC coordinates positionQuality Measure of fit quality x likelihood etc direction directionStatus Status of track reconstruction 0 unknown 1 good gt 1 failures dx reconstructed dx track direction in AD Water Pool or RPC coordinates dy reconstructed dy track direction in AD Water Pool or RPC coordinates dz reconstructed dz track direction in AD Water Pool or RPC coordinates directionQuality Measure of fit quality x likelihood etc error matrix errorMatrixDim Dimension of error matrix 0 if not set error Matrix Array of error matrix elements Reconstructed data in NuWa Here is a cheat sheet for processing reconstructed data in Python These lines can be used in the execute function of a Python algorithm evt Access the Recon Header self evtSvc This is a container for the reconstructed data reconHdr evt Event Rec AdSimple if reconHdr None self error Failed to get current recon header 10 11 12 13 14 15 16 17 18 19 20 21 22
244. s return again 17 8 MYSQL CRIB 179 17 8 4 System Administration This also has to be done as root As system administrator MySQL allows you to control access on a user by user basis to databases Here are some example commands create database dyb_offline grant all on dyb_offline to smart coop bnl phy gov grant all on dyb_offline to smart grant select dyb_offline Boring to dumb coop bnl phy gov q e The first lines creates a new database called dyb_offline With MySQL you can have multiple databases e The next two lines grants user smart either logged in locally to the server or remotely from anywhere on the network all privileges to all tables in that database e The next line grants user dumb who has to be logged in locally select i e read access to the table Boring in the same database 17 8 5 Selecting a Database Before you can use mysql to create fill or examine a database table you have to tell it what database to use For example use dyb_offline use is one of the few commands that does not have a trailing semi colon 17 8 6 Creating Tables The following commands create or recreate a table and display a description of it drop table if exists DbiDemoDatal create table DbiDemoData1 SeqNo int SubSystem int Pedestal float Gain1 float Gain2 float D3 describe DbiDemoData1 See table 17 1 for a list of MySQL types that the Databaselnterface currently supports 17 8 7 F
245. s sense to have overlapping Context Ranges For example suppose we know that a certain sort of calibration constants drifts with time and that once determined is only satisfactory for the next week s worth of data A sensible procedure would be to limit its validity to a week when writing to the database but to determine new constants every few days to ensure that the constants are always fresh and that there is no danger that there will be a gap However this means that the interface has to perform two types of Validity Management 17 2 CONCEPTS 151 Ambiguity Resolution When faced with two or more sets of data the interface has to pick the best It does this simply by picking the one with the latest creation date time Context Range Trimming Having found the best set the interface wants to know how long it will remain the best Any set whose creation date is later will be better according to the above rule and so the retrieved data has its range trimmed so as not to overlap it This reduced Context Range is called the Effective Context Range This only happens in memory the database itself is not modified but it does mean that the interface does not need to check the database again for this set of data until the Effective Context Ranges has expired This trimming also applies between databases in a cascade with sets in higher priority databases trimming those in lower ones Overlay Version Dates As explained above creation dates play
246. s together but can lead to redundant development and inter operational problems Finally there is the middle ground where a single monolithic application is built from the ground up When unforeseen requirements are found their solution is bolted on in whatever the most expedient way can be found This can be useful for quick initial results but eventually will not be maintainable without growing levels of effort 6 2 Framework Components and Interfaces Gaudi components are special classes that can be used by other code without explicitly compiling against them They can do this because they inherit from and implement one or more special classes called interface classes or just interfaces These are light weight and your code compiles against them Which actual implementation that is used is determined at run time by looking them up by name Gaudi Interfaces are special for a few reasons Pure virtual all methods are declared 0 so that implementations are required to provide them This is the definition of an interface class Being pure virtual also allows for an implementation class to inherit from multiple interfaces without problem References counted all interfaces must implement reference counting memory management ID number all interface implementations must have a unique identifying number Fast casting all interfaces must implement the fast queryInterface dynamic cast mechanism Part of a components implementation i
247. s you may want to modify an existing part of NuWa and test the changes you have made First you must setup your own Project as shown in section 3 5 3 Next you should checkout the package into your Project lOhttps wiki bnl gov dayabay index php title SVN_RepositoryitGuidelines 42 CHAPTER 3 ANALYSIS BASICS Table 3 3 Some Common Services ICableSvc Electronics cable connection maps and hardware serial numbers ICalibDataSvc PMT and RPC calibration parameters ISimDataSvc PMT Electronics input parameters for simulation IJobInfoSvc NuWa Job History Information command line software version etc TRunDataSvc DAQ Run information run number configuration etc IPmtGeomInfoSvc Nominal PMT positions IStatisticsSvc Saving user defined histograms ntuples trees etc to output files 1shell gt cd myNuWa 2shell gt svn checkout http dayabay ihep ac cn svn dybsvn dybgaudi trunk Reconstruction Center0fChargePos 3shell gt Ils 4CenterOfChargePos 5shell gt emacs CenterOfChargePos src components Center0fChargePosTool cc amp After you have made your changes you should compile and test your modifications To compile the modified package you should run the following commands in a clean shell 1ishell gt pushd NuWa trunk 2shell gt source setup sh 3shell gt export CMTPROJECTPATH path to myProjects CMTPROJECTPATH 4shell gt popd 5shell gt cd myNuWa CenterOfChargePos cmt 6shell gt cmt config cmt make
248. sent SimVertecies 11 4 TRUTH PARAMETERS 11 4 Truth Parameters Name amp Synonyms time t ES global_x y global_y Z global_z r radius pos_r lx local_x det_x ly local_y det_y lz local_z det_z lr local_r det_r Volume VolumeName LogicalVolume Material MaterialName DetectorElementName Match DetectorElement Match Nicheld Niche Detectorld Siteld Site AD AdNumber momentum p E totEnergy TotalEnergy Type double double double double double double double double double string string double double double double double double double double double gt Track gt Si KO K gt Si gt gt Vertex gt ps KO K SOS gt va gt gt Stats gt Ps KO K gt Si Description Time of the start step Global X position of the vertex track start step Global Y position of the vertex track start step Global Z position of the vertex track start step Global sqrt X X Y Y position of the vertex step start vertex track X Position relative to the local physical volume Y Position relative to the local physical volume Z Position relative to the local physical volume sqrt X X Y Y position relative to the local physical volume Name of the logical volume of ver tex track start step Name of material at vertex track start step Name of best match Detector El ement at vertex tr
249. should go in DocDB e how to access Major features Basic instructions how to get help 4 3 Wikis Content what should go in DocDB e How to access Basic markup help Conventions types of topics Using categories 4 4 Trac bug tracker when to use it roles and responsibilities 61 Chapter 5 Installation and Working with the Source Code 5 1 Using pre installed release All major clusters should have existing releases installed and ready to use Specific information on different clusters is available in the wiki topic Cluster Account Setup The key piece of information to know is where the release is installed Configuring your environment to use an installed release progresses through several steps 5 1 1 Basic setup Move to the top level release directory and source the main setup script shell gt cd path to NuWa RELEASE bash gt source setup sh tcsh gt source setup csh Replace RELEASE with trunk or the release label of a frozen release 5 1 2 Setup the dybgaudi project Projects are described more below To set up your environment to use our software project dybgaudi and the other projects on which it depends to must enter a so called release package and source its setup script shell gt cd path to NuWa RELEASE bash gt source setup sh tcsh gt source setup csh You are now ready to run some software Try shell gt cd HOME shell gt nuwa py help
250. ss Data Store Raw Signals ElecCrate Trigger Tool Figure 12 1 Electronics Simulation Chain e RawSignal RawSignal simSamples vector lt double gt represents the time sequenced pmt signal with gaussian distributed noises included This RawSignal is sent to discriminator to form multiplicit and TDC values Analogsum is also based on this RawSignal e shapedSignal shapedSignal SimSample vector lt double gt is composed of time sequenced shapedPMTsig nals shapedPmtPulse e7t to gr V t VoltageScale _ _ ____ t to 12 1 to 3 6ns ty 5 4ns Multiplicity Generation and TDC Multiplicity at hit Clock i for one FEE board is the sum of the hitHold signal hitHold vector lt int gt at the hit Clock hitHold i for all the hitted channels in the FEE channel Figure 12 3 shows the flow on how the hitHold signals are generated One example of two 1 p e pulses are shown in figure 12 4 12 4 SIMULATION CONSTANT Location dybgaudi DataModel ElecEvent Current as of r4061 ElecHeader pulseHeader crateHeader ElecPulseHeader header pulseCollection ElecCrateHeader crates ElecCrate EA 5 header detector pulses ElecFecCrate channelData pulse Container nHit time eSum channelld amplitute ElecFeeChannel nHit adcHigh adcLow energy ElecRpcPulse tdc ME ElecPmtPulse Pe Figure 12 2 UML for data model in Elec
251. ss MyCalibrator public MyCalibrator const Context vc fResPtr vc Float_t Calibrate DataObject amp thing Use fResPtr to calibrate thing private DbiResultPtr lt DbiDemoDatai gt fResPtr 3 MyCalibrator is a lightweight object holding only a pointer to a results table It is created with a Context object which it uses to prime its pointer After that it can be passed Data0bject objects for which it returns calibrated results using its Calibrate method Now the loop over all digitizations can use this object without any calls to the Databaselnterface at all Being lightweight MyCalibrator is fine as a stack object staying in scope just long enough to do its job Another optimisation strategy involves caching results derived from a query In this case it is important to identify changes in the query results so that the cached data can be refreshed To aid this each DbiResult is given an key which uniquely identifies it This key can be obtained and stored as follows DbiResultKey MyResultKey myResPtr GetKey This should be stored by value the DbiResultKey pointed to by GetKey will be deleted when the results expire as part of the cache and checked each time a change is possible if MyResultKey IsEqualTo myResPtr GetKey 4 recreate the cache data MyResultKey myResPtr GetKey Caution This tests to see that the current DbiResult has exactly the same data as that used when the cached was fi
252. svn ticket 948 The Hardware ID table maps a Hardwareld from Conventions Hardware h to either a DetectorSensor Conventions Detectors h or an ElecChannelld Conventions Electronics h depending on the harddware type For the code note the DetectorSensor and ElecChannelld are stored in the form of the base class DayaBay Detector name dbtype codetype description code2db ChanOrSens int 11 DayaBay Detector Packed Channel Sensor ID fullPackedData HardwareId int 11 DayaBay HardwareId Packed Hardware ID fullPackedData Table 19 58 DBI Table specification for class GHardwareIDFix which corresponds to table HardwareID 58nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GHardwareIDFix spec 246 CHAPTER 19 DATABASE TABLES 19 59 McsPos Table specification source dybgaudi trunk Database DybDbi spec GMcsPos spec Source position for MCS mysql amp gt describe McsPos Field Type Null Key Default Extra SEQNO int 11 NO PRI NULL l ROW_COUNTER int 11 NO PRI NULL PositionR float YES NULL PositionZ float YES NULL PositionPhi float YES NULL RunNo int 11 YES NULL 4 6 rows in set 0 02 sec
253. svn browser dybgaudi trunk Database DybDbi spec GCalibRpcSpec spec 19 20 CALIBSRCENERGY 207 19 20 CalibSrcEnergy Table specification source dybgaudi trunk Database DybDbi spec GCalibSrcEnergy spec docstring This is for energy scale calibration constants from calibration sources name dbtype codetype description SourcePeakType int 11 int source dybgaudi trunk DataModel Conventions Conventions Calibrat XSrcPosition float double X position of calibration source YSrcPosition float double Y position of calibration source ZSrcPosition float double Z position of calibration source PEPeak float double peak PE value of Ge source PEPeakUnc float double uncertainty in peak value PEPeakFitQuality float double quality of peak fit Table 19 20 DBI Table specification for class GCalibSrcEnergy which corresponds to table CalibSrcEnergy 20http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibSrcEnergy spec 208 CHAPTER 19 DATABASE TABLES 19 21 CoordinateAd Table specification source dybgaudi trunk Database DybDbi spec GCoordinateAd spec Coordinates for AD support platforms in meters see docdb 6375 TABLE II rubric Detector convention in Offline and docdb 6375 AD name fullPackedData AdNo DayaBayAD1i 16842752 1 DayaBayAD2 16908288 2 LingAoAD1 33619968 3 LingAoAD2 33685504 4 FarAD1 67174400 5 FarAD2 67239936 7 FarAD3 67305472 8 FarAD4 67371008
254. t The key lines from the script are 1 Fill histograms 2 AD 1 3 reconT Draw calibStats nHit energy gt gt nhitVsEnergyAD1H 4 context mDetld 1 amp amp energyStatus 1 5 AD 2 6 reconT Draw calibStats nHit energy gt gt nhitVsEnergyAD2H 7 context mDetld 2 amp amp energyStatus 1 dybGetLeaf C There are some cases where the variables and cuts cannot be expressed in a simple TTree Draw command Is this case using TTree GetLeaf O is an alternative This is also a better alternative for those familiar with TSelector or TTree MakeClass since it allows chaining and friending of data files Advantages e Fairly simple to run e Requires some minimal programming e Allows chaining and friending of data files Disadvantages e No access to geometry database other external data e Cannot be integrated with production analysis job To run this example use the following approach 1 root 0 L dybTreeGetLeaf C 2 root 1 dybTreeGetLeaf recon root 00 Z ON0a pA WHR THAN DA PWN Be N N NNN BwoON RO om NOTA FF WN 28 CHAPTER 3 ANALYSIS BASICS The key lines from the script are Process each event int maxEntries reconT GetEntries for int entry 0 entry lt maxEntries entry Get next event reconT GetEntry entry Get event data int detector int reconT GetLeaf context mDetId gt GetValue int energyStatus int reconT GetLeaf energyStatus gt Get
255. t command eliza7 dayabay scratch dandwyer NuWa trunk opt dybgaudi InstallArea scripts nuwa py A None n 1 no history random off mQuickstart DryRunTables mQuickstart Calibrate mQuickstart Reconstruct o recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root hostid 931167014 jobTime Fri 08 Apr 2011 03 29 39 0000 nuwaPath eliza16 dayabay users dandwyer installs trunk_2011_03_30_opt Nula trunk revision 11307 11331 username dandwyer 3 4 NUWA RECIPES 37 29 30 31Cached Job Information 32 jobId 22c6620e 6190 11e0 84ac 003048c51482 33 cmtConfig x86_64 s1c4 gcc34 opt 34 command eliza7 dayabay scratch dandwyer NuWa trunk opt dybgaudi InstallArea scripts nuva py 35 A None n 1 no history random off mProcessTools LoadReadout 36 o daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 37 eliza7 dayabay data exp dayabay 2010 TestDAQ NoTag 0922 daq NoTag 0005773 Physics SAB AD2 SFO 38 hostid 931167014 39 jobTime Fri 08 Apr 2011 03 27 31 0000 40 nuwaPath elizal6 dayabay users dandwyer installs trunk_2011_03_30_opt NuWa trunk 41 revision 11307 11331 42 username dandwyer 43 The jobs are displayed in reverse chronological order The first job converted the raw daq data file to a NuWa root file The second job ran an example calibration and reconstruct
256. t gt DybPython Catalog runs 8000 7 eliza16 dayabay data exp dayabay 2011 TestDAQ NoTag 0430 daq NoTag 8 gt gt gt DybPython Catalog runs 8001 9 eliza16 dayabay data exp dayabay 2011 TestDAQ NoTag 0430 daq NoTag 10 gt gt gt DybPython Catalog runs 8002 11 eliza16 dayabay data exp dayabay 2011 TestDAQ NoTag 0430 daq NoTag 0008000 Physics EHi Merged SFO 1 _00 0008001 Physics EHi Merged SFO 1 _00 0008002 Pedestal EH1 WPI SFO 1 _0001 For more information refer to the Catalog description https wiki bnl gov dayabay index php title Accessing Data_in_a lMhttps wiki bnl gov dayabay index php title https wiki bnl gov dayabay index php title Accessing_Data_ in_a_Warehouse 46 CHAPTER 3 ANALYSIS BASICS 3 5 5 Data File Contents The table below lists the known data paths and provides a short description of their contents Path Name Description Real and Simulated Data Event Readout ReadoutHeader Raw data produced by the experiment Event CalibReadout CalibReadoutHeader Calibrated times and charges of PMT and RPC hits Event Rec AdSimple Toy AD energy and position reconstruction AdQm1f AD Maximum likelihood light model reconstruction Event Tags Standard tags for event identification Event Tags Coinc ADCoinc Tagged set of AD time coincident events Event Tags Muon MuonAny Single muon trigger from any detector Muon FirstMuonTrigger First trigger from a prompt set of muon triggers Retrig
257. t context DbiSqlContext kStarts tsStart tsEnd Site kFar SimFlag kData You supply the type of context in this case DbiSql1Context kStarts the date range and the detector type and sim flag Other types of context are kEnds and kThroughout See DatabaseInterface DbiSqlContext h for the complete list You are not limited to the contexts that DbiSqlContext provides If you know the SQL string you want to apply then you can create a DbiSqlContext with the WHERE clause you require e g DbiSqlContext myContext SITEMASK amp 4 which would access every row that is suitable for the CalDet detector const Dbi Task amp task The task is as for other queries but with the default value of Dbi kAnyTask which results in the task being omitted from the context query and also allows for more general queries anything that is is valid after the where is permitted For example DbiSqlContext myContext versiondate gt 2004 01 01 00 00 00 order by versiondate limit 1 The SQL must have a where condition but if you don t need one create a dummy that is always true e g DbiSqlContext myContext 1 1 order by timeend desc limit 1 const string amp data This is an SQL fragment that if not empty the default value is used to extend the WHERE clause that is applied when querying the main table For example consider DbiSqlContext context DbiSqlContext kStarts tsStart tsEnd Site kFar SimFlag kData Dbi
258. t helper array for ROOT histogramming Delayed helper array for ROOT histogramming Time since last muon in AD1 ms Time since last muon in AD2 ms Time since last muon in Inner water pool ms Time since last muon in Outer water pool ms Time since previous AD event above 3200 pe 20 MeV ms Time since previous AD event above 160000 pe 1 GeV ms Energy of last AD event with greater than 160000 pe pe CalibStats data CalibStats data CalibStats data CalibStats data CalibStats data CalibStats data CalibStats data CalibStats data CalibStats data CalibStats data CalibStats data CalibStats data Monte Carlo truth generator data Monte Carlo truth generator data Monte Carlo truth generator data Monte Carlo truth generator data Monte Carlo truth generator data Monte Carlo truth generator data Monte Carlo truth generator data Monte Carlo truth generator data Monte Carlo truth generator data Coincidence data in NuWa 57 Here is a cheat sheet for processing coincidence data in Python These lines can be used in the execute function of a Python algorithm evt self evtSvc Access the Coincidence Data Header 58 CHAPTER 3 ANALYSIS BASICS 4 This is a container for AD coincidence data 5 coincHdr evt Event Data Coinc ADiCoinc 6 if coincHdr None 7 self debug No coincidence header this cycle 8 return SUCCESS 9 10 Access the Coincidence Data 11 dt_ms coinc get dt_ms val
259. t to generate trial output Read the file with bare root the load C script Look for ROOT reporting any undefined objects or missing streamers This indicates missing entries in dict classes xml Browse the tree using a TBrowser You should be able to drill down through the data structure Anything missing or causes a crash means missing dict classes xml entries or incorrect incomplete conversion Read the file back in using the RootI0OTest script Check for any crash search for Break or error in the logs Use the diff_out py script to diff the output and intput logs and check for unexplained differences this may require you to improve fillStream methods in the DataModel classes 8 6 4 Difficulties with Persistent Data Classes Due to limitations in serializing transient objects into persistent ones care must be taken in how the persistent class is designed The issues of concern are Redundancy Avoid storing redundant transient information that is either immaterial or that can be reconstructed by other saved information when the object is read back in Referencing One can not directly store pointers to other objects and expect them to be correct when the data is read back in The Referencing problem is particularly difficult Pointers can refer to other objects across different boundaries in memory For example 8 6 ADDING NEW DATA CLASSES 85 Pointers to subobjects within the same object Pointers to ob
260. t variable DBCONF that points to a named section in the configuration file Other envvars can also be used to change the default behaviour allowing more complex configurations such as cascades of multiple databases to be configured envvar default notes DBCONF name of section in config file DBCONF_URL mysql host s database s DBCONF_USER user s DBCONF_PSWD password s DBCONF_HOST host s DBCONF_DB database s DBCONF_PATH etc my cnf SITEROOT my cnf my cnf list of config file paths The defaults are python patterns that are filled in using the context variables obtained from the section of the config The meanings are as follows DBCONF_PATH Colon delimited list of paths which can include envvars such as SITEROOT and the home directory tilde symbol Non existing paths are silently ignored and sections from the later config files override sections from prior files Using the default paths shown in the table allows the system administrator to manage config in etc my cnf which is overridden by the dybinst administrator managed SITEROOT my cnf 154 CHAPTER 17 DATABASE Users only need to create their own config file in HOME my cnf if they need to override the standard configuration DBCONF_URL This is a semi colon separated list of URLs Each URL takes the form protocol host port database options where protocol DBMS type e g mysql etc host host name or IP address of data
261. tTool DetectorsToProcess DayaBayAD1 DayaBayAD2 DayaBayIWS DayaBay0WS LingAoAD1 LingAoAD2 X LingAoIWS LingAo0WS FarAD1 FarAD2 134 CHAPTER 14 READOUT FarAD3 FarAD4 FarIWS Far0WS ROsConf ROsFeeReadoutTool AdcToo1 ROsFeeAdcPeakOnlyToo1 ROsConf ROsFeeReadoutTool TdcTool ROsFeeTdcTool ROsConf ROsFeeReadoutTool ReadoutLength 12 ROsConf ROsFeeReadoutTool Trigger0ffset 2 14 5 2 ROsFecReadoutTool ROsFecReadoutTool handles reading out the rpc based detectors By default this acts on all rpc based detectors This is the only property currently available as seen below in the default setup import ReadoutSim ReadoutSimConf as ROsConf ROsConf ROsFeeReadoutTool detectorsToProcess DayaBayRPC LingAoRPC FarRPC 14 5 3 ROsFeeAdcMultiTool ROsFeeAdcMultiTool reads out samples the adc values in the readout window based on the readout window start The user specifies the ReadoutCycles with 0 corresponding the adc value at the beginning of the readout window ROsConf ROsFeeReadoutTool AdcTool ROsFeeAdcMultiTool ROsConf ROsFeeAdcMultiTool ReadoutCycles 0 2 3 4 8 14 5 4 ROsFeeAdcPeakOnly Tool ROsFeeAdcPeakOnlyTool reads out the peak adc value in the readout window ROsConf ROsFeeReadoutTool AdcToo1 ROsFeeAdcPeakOnlyToo1 14 5 5 ROsFeeTdcTool ROsFeeTdcTool readout the tdc values during the readout window The user has the option to readout multiple
262. tdc values but changing the UseMultiHitTdc property ROsConf ROsFeeReadoutTool TdcTool ROsFeeTdcTool ROsConf ROsFeeTdcTool UseMultiHitTdc False ROsConf ROsFeeTdcTool TdcResetCycles True Chapter 15 Simulation Processing Models 15 1 Introduction To properly simulate Daya Bay experiment events from different event classifications must be properly mixed with any overlapping in space and time properly handled To do this is complex and so a simpler simulation that only considers a single event type at a time is also desired The former model goes by the name of pull mode or Fifteen minutes style simulation The latter is known as push mode or linear style simulation 15 2 Fifteen Fifteen package successfully extends gaudi frame work to another level It makes use of many advance features of dybgaudi like AES inputHeaders and using Stage tool to handle data transfer Fifteen package is designed to handle the max complexity in simulation It has sophisticated consideration on all kinds of possible physics scenario event time information handling and data management After two years usage and the feedback from users it s already absorbed a lot of ideas like mixing pre simulated events and reusing and has gone into a mature stage 15 2 1 Quick Start After you get into nuwa environment you are ready to start to generate your own simulation sample In NuWa trunk dbg NuWa trunk dybgaudi Tutorial Si
263. tector AD stand 1 kAD1 1 Anti neutrino detector on stand 1 AD stand 2 kAD2 2 Anti neutrino detector on stand 2 AD stand 3 kAD3 3 Anti neutrino detector on stand 3 AD stand 4 kAD4 4 Anti neutrino detector on stand 4 Inner water pool kIWS 5 Inner water pool Outer water pool kOWS 6 Outer water pool RPC kRPC T Complete RPC assembly All kAll 8 All detectors To access the detector labels from Python you can use the commands 1from GaudiPython import gbl 2gbl DayaBay Detector Access any class 3DetectorId gbl DetectorId 4print Detectorld kAD1 For C the detector labels can be accessed 1 include Conventions DetectorId h 2std cout lt lt DetectorId kAD1 lt lt std endl in library then ENUMs are available The Detector convention is defined in DataModel Conventions Conventions DetectorId h 3 3 5 8 Raw DAQ Data Conversion from data The raw DAQ file can be wrapped in a ROOT tree This allows you to histogram the raw data directly from ROOT as shown in section 3 2 3 The following command will wrap the data In addition ROOT will compress the raw data by almost half the original size The file still contains the raw binary data no event data conversion is performed 1shell gt nuwa py n 1 m ProcessTools LoadReadout 2 o daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 3 daq NoTag 0005773 Physics SAB AD2 SFO 1 _0001 data Raw data in ROOT The following table summariz
264. ted analyses using the Particle Histories may yield better results in the long run Unobservable Statistic Objects Unobservable Statistics are stored in a SimStatistic object shown in Figure 11 3 3 These statistic objects are stored in a map referenced by name in the SimUnobservableStatisticsHeader This object in turn is stored in the SimHeader once per simulated event 114 CHAPTER 11 DETECTOR SIMULATION Creation Rules The Unobserver module operates using the same principles as the Particle History selector above At initialization a selection string and variable string is parsed into a set of Rule objects that can be rapidly evaluated on the current G4Step The user supplies a list of Statistics to the module Each Statistic is defined as follows STATNAME VARIABLE EXPRESSION or STATNAME_1 VARIABLE_1 STATNAME_2 VARIABLE_2 STATNAME_3 VARIABLE_3 EXPRESSION Here STATNAME is a string of the user s choosing that describes the statistic and is used to name the statistic in the SimUnobservableStatisticsHeader for later retrieval VARIABLE is a parameter listed in Table 11 4 that is the actual value to be filled Only numeric parameters may be used as variables EXPRESSION is a selection string as described in Sec 11 3 1 In the second form of listing several different variables may be defined using the same selection string to improve runtime performance and make the configuration
265. ted global position x Quenched energy weighted global position y Quenched energy weighted global position z Quenched energy weighted global time 1 if particle is stopping 0 otherwise 1 if particle is starting this is the first step 0 otherwise Number of steps completed for this particle 1 if the particle is entering a new volume 0 otherwise 1 if the particle is entering a new material 0 otherwise PDG code of the last ancestor where a SimTrack was created Generations passed since the last ancestor was created PDG code of the immediate an cestor s ancestor Indirection to the immediate an cestor s ancestor Distance from the last created Sim Vertex 119 120 CHAPTER 11 DETECTOR SIMULATION Name amp Synonyms Type E gt amp Description TimeSinceLast Vertex double X Time since the last created SimVertex EnergyLostSinceLastVertex double X Energy difference sine the last created SimVertex AngleFromLast Vertex double X Change in direction since the last created SimVertex degrees Chapter 12 Electronics Simulation 12 1 Introduction The Electronics Simulation is in the ElecSim package It takes an SimHeader as input and produces an ElecHeader which will be read in by the Trigger Simulation package The position where ElecSim fit in the full simulation chain is given in figure 12 1 The data model used in ElecSim is summarized in the UML form in figure 12 2 12 2 Algorith
266. the ElecHeader and checks it against those in the list If the detector is in the list the tool issues all applicable triggers for that detector If the detector is not found in the DetectorsToProcess list the detector is ignored Recovery Time sets the number of nhit clock cycles to wait after a trigger is issued before potentially issuing another trigger The default value is 24 which corresponds to 300ns for the 80MHz clock 13 3 2 TsExternalTriggerTool An External Trigger implementation This will issue a local triggers at a specified frequency Currently used with the dark rate module for the MDCO0O8 The properties are DetectorsToProcess Same as TsMultTriggerTool in section 13 3 1 Trigger Offset Frequency AutoSet 13 4 ADDING A NEW TRIGGER 129 13 4 Adding a new Trigger To add a new trigger type create a new class which inherets from GaudiTool and ITsTriggerTool as shown here class TsMyTriggerTool public GaudiTool virtual public ITsTriggerTool public TsMyTriggerTool const std string amp type const std string amp name const IInterface parent virtual TsMyTriggerTool virtual StatusCode mutate DayaBay SimTrigHeader trigHeader const DayaBay ElecHeader amp elecHeader virtual StatusCode initialize virtual StatusCode finalize private std vector lt std string gt m_detectorsToProcess 3 Chapter 14 Readout 14 1 Introduction ReadoutSim is located in Simulation Readout
267. the column names and types The types must valid MySQL types see table 17 1 for some examples If the special row is omitted or is invalid then the column names are set to Cl C2 etc and all types are set to string TEXT Here is a simple example of a CSV file SeqNo int Pedestal float SubSystem int Gaini float Gain2 float 1 0 0 10 100 i 1 1 1 11 110 1 1 2 2 12 120 1 1 3 3 13 130 Its in a convention to use the file extension csv but it is not compulsory If any value is a string or a date it must be delimited by double quotes URL The database URL is based on the standard one extended by adding the suffix absolute path to file For example mysql coop phy bnl gov temp path to MyTable csv The table name is derived from the file name after stripping off the extension In this example the table name will be MyTable 17 7 3 Catalogues These are special types of ASCII Flat File Their data are URLs to other flat files You cannot nest them i e one catalogue cannot contain a URL that is itself catalogue 17 7 ASCII FLAT FILES AND CATALOGUES 177 Format The first line of the file just contains the column name name The remaining lines are URLs of the flat files Here is a simple example name file home dyb work MyData csv file home dyb work MyDataVld csv file MY_ENV MyDataToo csv file MY_ENV MyDataTooVld csv This catalogue defines two tables MyData and MyDataToo each
268. the contents of the file as shown in Fig 3 1 Event data is found under the path Event as summarized in Table 3 1 A section on each data type is included in this document Simulated data files may include additional data paths containing truth information A complete list of data paths are given in Sec 3 5 5 e088 IX Old ROOT Object Browser File View Options Help Ey Event gt 2a E lt lel al Option All Folders Contents of recon NoTag 0005773 Physics SAB 4D2 5FO 1 _0001 root Event 1 root CalibReadout 1 Readout Registration Sequence 1 PROOF Sessions E eliza7 dayabay scratchidandwy ROOT Files 3recon NoTag 0005773 Physics 2 BEN Readout 1 Y CaibReadout 1 E Rec 1 E Registration Sequence 1 i AJobHeader 1 A FunHeader 1 Figure 3 1 Data File Contents A set of standard data ROOT files will be maintained on the clusters The file prefix is used to identify the contents of the file as shown in Table 3 2 The location of these files on each cluster are listed in Section 3 5 4 Each data paths in the ROOT file contains ROOT trees You can directly access a ROOT tree 1root 0 TFile f recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root 2root 1 TTreex AdSimple TTreex f Get Event Rec AdSimple Table 3 1 Standard paths for Event Data Real and Simulated Data Event Readout Raw data produced by the experiment Sec 3 5 8 Event CalibReado
269. the method void Abort e If you want to you can reuse a DbiWriter by using Bool_t Open const ContextRange amp vr Int_t aggNo Dbi Task task O TimeStamp versionDate TimeStamp Ulnt_t dbNo 0 The arguments have the same meaning as for the constructor An alternative form of the Open statement allows the database name to be supplied instead of its number If the DbiWriter is already assembling data then the Close method is called internally to complete the I O The method returns true if successful As explained above the Open method must be used if writing multiple records to the same table as part of a single update for then a single database log entry will be written to cover all updates 17 6 5 Table Row Responsibilities All DbiTableRow sub class objects must support the input interface accessed through DbiResultPtr The responsibilities that this implies are itemised in section 17 5 2 The output interface is optional the respon sibilities listed here apply only if you want to write data to the database using this interface Must override GetAggregateNo method if aggregated DbiTableRow supplies a default that returns 1 The GetAggregateNo method is used to check that table row objects passed to a particular DbiWriter have the right aggregate number 174 CHAPTER 17 DATABASE Must override Store Method The Store method is the inverse to Fill although it is passed a Dbi0utRowStream reference void Store DbiDutR
270. tion radioactive decay of nuclei It relies on Evaluated Nuclear Structure Data File ENSDF data sets maintained by National Nuclear Data Center NNDC located at BNL It is fully data driven in that all information on branching fractions half lifes and radiation type are taken from the ENSDF data sets GenDecay will set up a hierarchy of mothers and daughters connected by a decay radiation When it is asked to perform a decay it does so by walking this hierarchy and randomly selecting branches to follow It will apply a correlation time to the lifetime of every daughter state to determine if it should force that state to decay along with its mother The abundances of all uncorrelated nuclear states must be specified by the user The GenDecay package provides a single tool called GtDecayerator which provides a local 4 vertex and 4 momentum for all products It should be followed up by positioner and transformer tools 10 6 Configuration General configuration is described in Ch 6 The GenTools and related packages follow these conventions This section goes from low level to high level configuration 10 6 1 Configurables As described above a GtGenerator algorithm is used to collect It is configured with the following properties 10 6 CONFIGURATION 99 TimeStamp sets an absolute starting time in integral number of seconds Note the unit is implicit do not multiple by seconds from the system of units GenTools sets the ordered list of tools
271. tions must be true to allow the collection An example of some statistic definitions stats PhotonsCreated E StepNumber 1 and pdg 20022 Photon_bounce_radius r pdg 20022 and dAngle gt 90 edep ad1 dE pdg 20022 and MaterialName dd Materials LiquidScintillator or MaterialName dd Materials GdDopedLS and AD 1 2 8 4 Accessing the resulting truth information The resulting Truth information is stored in the SimHeader object which is typically found at Event Sim SimHeader in the event store It can be retrieved by your algorithm like so DayaBay SimHeader header 0 if exist lt DayaBay SimHeader gt evtSvc m_location header get lt DayaBay SimHeader gt m_location const SimParticleHistory h header gt particleHistory const SimUnobservableStatisticsHeader h header gt unobservableStatistics 4nttp graphviz org 12 CHAPTER 2 QUICK START 2 9 Electronics Simulation 2 10 TRIGGER SIMULATION 13 2 10 Trigger Simulation The main algorithm in TrigSim TsTriggerAlg has 3 properties which can be specified by the user TrigTools Default TsMultTriggerTool List of Tools to run TrigName Default TriggerAlg Name of the main trigger algorithm for bookkeeping ElecLocation Default Event Electroincs ElecHeader Path of ElecSimHeader in the TES currently the default is picked up from ElecSimHeader h The user can
272. to get current readout header return FAILURE Access the Readout This is the data from one trigger readout readoutHdr daqCrate asPmtCrate if readout None self info No readout this cycle return SUCCESS Get the detector ID for this trigger detector readout detector detector detName Trigger Type This is an integer of the type for this trigger readout triggerType Event Number A count of the trigger according to the DAQ readout eventNumber Trigger Time Absolute time of trigger for this raw data triggerTime readout triggerTime Loop over each channel data in this trigger for channel in readout channelReadouts channelld channel channelld The channel ID contains the detector ID electronics board number and the connector number on the board channelld detName channelld board channelId connector A Loop over hits for this channel for hitIdx in range channel hitCount TDC data for this channel The TDC is an integer count of the time between the time the PMT pulse arrived at the channel and the time the trigger reads out the data Therefore a larger TDC earlier time One TDC count 1 5625 nanoseconds a Fh RE SR SR IR a a channel tdc hitIdx ADC data for this channel The ADC is an integer count of the charge of the PMT pulse It is 12 bits 0 to 4095 There are two ADCs for every PMT channel High gain and Low gain Only the hi
273. two rows SEQNO INT CONFIGSTRING TEXT 1 mybool 1 mydouble 1 23456789012345678e 200 mystring This is a string myint 12345 Caution Note don t have any white space between the comma and the leading double quote of the configuration string 178 CHAPTER 17 DATABASE 17 8 MySQL Crib This provides the absolute bare minimum to install manage and use a MySQL database in the context of the Databaselnterface 17 8 1 Introduction The following are useful URLs e MySQL home page http www mysql com e from which you can reach a documentation page http www mysql com documentation index html e and the downloads for 3 23 http www mysql com downloads mysql 3 23 html A good book on MySQL is MySQL by Paul DuBois Michael Widenius New Riders Publishing ISBN 0 7357 0921 1 17 8 2 Installing See https wiki bnl gov dayabay index php title Database https wiki bnl gov dayabay index php title MySQL_Installation 17 8 3 Running mysql mysql is a utility used both by system administrators and users to interact with MySQL database The command syntax is mysql h host_name u user_name pyour_pass if you are running on the server machine with you Unix login name and no password then mysql is sufficient To exit type q Note most mysql commands are terminated with a semi colon If nothing happens when you type a command the chances are that mysql is still waiting for it so type it and pres
274. ud pe q 4250 16000 J E 14000 E J 4200 12000 J J 10000 4 E K 8000 A z E J 3 4100 6000F q E 4000F E E so 2000 ak J 5 Ely ra AA E AI y 0 2 4 6 8 10 12 14 16 2500 o 3 3 Q lt Figure 3 3 Example Histograms A weighting can be added to each entry in histogram by multiplying your selection by the weighting factor i e weight selection This can be used to draw the calibrated PMT charge distribution in AD2 Fig The charge distribution for a specfic event can be selected using the event number 1root 1 TTreex CalibReadoutHeader TTreex f Get Event CalibReadout CalibReadoutHeader 2root 2 CalibReadoutHeader Draw ring column 3 chargeAD detector 2 colz 4root 3 CalibReadoutHeader gt Draw ring column 5 chargeAD detector 2 amp amp eventNumber 12345 colz ring column chargeAD context mDetld 2 ring column chargeAD context mDetld 2 amp amp eventNumber 12345 x10 I A pao 2 OE y E E 3 E E q 25 400 de 3 7E Y J 350 E 2 M 3 300 6 E S250 5 15 3 200 4 E J J 10 q 150 3 q q 2 q 1 50 TE oE J JM oE fi i J J E 0 5 10 15 20 25 0 5 10 15 20 25 column column Figure 3 4 The calibrated PMT charge in photoelectrons for all events and for an individual event The trigger time is divided into two parts a count of seconds from January 1970 i e unixtime and a precise count of nanoseconds from the last second To draw the abso
275. ue 3 5 14 NuWa Services Add documentation for common services here 3 5 15 Computer Clusters Add details for each computer cluster here 3 5 16 Miscellaneous Time Axes in ROOT The following lines will display a time axis in a human readable format using Beijing local time 1root 3 htemp gt GetXaxis gt SetTimeDisplay 1 2root 4 htemp gt GetXaxis gt SetTimeFormat splitline H 4M S Zd Am 4 Y 3root 5 htemp gt GetXaxis gt SetNdivisions 505 4root 6 htemp gt GetXaxis gt SetTimeOffset 8 60 60 5root 7 htemp gt Draw colz 3 6 3 6 HANDS ON EXERCISES 59 Hands on Exercises Find the AD Dry Run data files from run 5773 on PDSF Convert the first file of this run from data to root Generate a calibrated data file from this data Plot the AD charge map figures shown in Fig 3 4 Generate a reconstructed data file from this data Plot the calibrated AD charge sum vs the AD reconstructed energy From the first simulation file from run 29000 generate a spallation file and plot the time from each AD event to the last muon From the first simulation file from run 29000 generate an AD coincidence file and plot the prompt vs delayed reconstructed energy Chapter 4 Offline Infrastructure 4 1 Mailing lists existing lists their purposes offline list expected topics subscribing archives how to get help 4 2 DocDB Content what
276. um level of logging output printed to the screen 1 VERBOSE 2 DEBUG 3 INFO 4 WARNING 5 ERROR e A n s Keep events for the past n seconds available for correlation studies with the current event e help Print nuwa py usage including descriptions of all options 3 3 NUWA BASICS 35 3 3 2 NuWa Job Modules Job modules are used to configure simulation and analysis tasks Specifically Job modules are scripts which do the following e Add analysis Algorithms and Tools to the job e Configure Algorithms Tools and Services used by the job Job Modules are used with the nuwa py command as follows 1shell gt nuwa py n 100 m lt Module1 gt m lt Module2 gt lt inputFile gt You can put as many modules as you like on the command line Some modules can take arguments these should be placed inside the quotes immediately after the module name 1shell gt nuwa py n 100 m lt Modulei gt a argA b argB lt inputFile gt 36 CHAPTER 3 ANALYSIS BASICS 3 4 NuWa Recipes Many NuWa analysis tasks rely on a standard or familiar approach This section provides a list of recipes for common analysis tasks such as e See the history of a NuWa file Sec 3 4 1 e Tag a set of events in a NuWa file Sec 3 4 2 e Add your own variables to the NuWa file Sec 3 4 3 e Copy all the data at a path to a new file Sec 3 4 5 e Write tagged data to a new file Sec 3 4 6 e Change the configuration of an existing J
277. ut Calibrated times and charges of PMT and RPC hits Sec 3 5 9 Event Rec Reconstructed vertex and track data Sec 3 5 11 Simulated Data Only Event Gen True initial position and momenta of simulated particles Event Sim Simulated track interactions and PMT RPC hits Geant Event Elec Simulated signals in the electronics system Event Trig Simulated signals in the trigger system Event SimReadout Simulated raw data 3 2 DAYA BAY DATA FILES 23 Table 3 2 Standard NuWa Event Data files File Prefix Readout CalibReadout Rec Coinc Spall Simulation Truth Gen Sim daq yes optional calib optional yes optional recon some events some events yes optional coinc some events some events some events yes optional spall some events some events some events yes optional The next section gives examples of working with these ROOT Trees See the ROOT User s Guide for more details on working with Trees http root cern ch download doc 12Trees pdf 3 2 2 Histogramming data Data can be histogrammed by selecting items in the TBrowser or by using the Draw function of the tree For example Figure 3 2 shows the data contained in a reconstructed event 000 X Old ROOT Object Browser File View Options Help E Rec_AdSimple El 2af 7 al lel E Option All Folders Contents of recon NoTag 0005773 Physics SAB AD2 SFO 1 _0001 root Event 1 Rec 1 AdSimple 1 Rec_AdSim
278. utely necessary the regime can be changed but no records must have validities that span the boundary between one regime and another Were that to be the case the same entry could appear in two valid records with different aggregates numbers and end up appearing in the table multiple times The system checks to see that this does not happen by asking each row to confirm it s aggregate number on input e For any given context it is not necessary for all detector elements to be present just the ones that are really in the detector at that time For example the Far detector will grow steadily over more than a year and this will be reflected in some database tables with the number of valid aggregates similarly growing with time What aggregates are present can appear in any order in the database tables the interface will assemble them into the proper order as it loads them Its perfectly possible that a calibration procedure might produce database data for multiple aggregates at a single pass If you are faced with this situation and want to write all aggregates in parallel then simply have a vector of DbiWriter s indexed by aggregate number and pass rows to the appropriate one See DbiValidate Test_6 for an example of this type of parallel processing 17 6 3 Simple Example We will use the class DbiDemoDatal1 to illustrate each of the above steps 1 Set up ContextRange object Typically the ContextRange will be based on the Context for the e
279. vMap Table specification source dybgaudi trunk Database DybDbi spec GAdWpHvMap spec High voltage cable map table mysql amp gt describe AdWpHvMap 4 4 4 Field Type Null Key Default Extra 4 4 4 4 SEQNO int 11 NO PRI NULL ROW_COUNTER int 11 NO PRI NULL LocationId char 6 YES NULL l HvChannelId int 11 YES NULL DcBoard tinyint 1 YES NULL l DcChannel tinyint 2 YES NULL l 4 4 6 rows in set 0 00 sec name dbtype codetype description code2db LocationId char 6 string PMT Location ID HvChannelId int 11 DayaBay HvChannelId Packed HV Channel ID fullPackedData DcBoard tinyint 1 int Decoupler Board DcChannel tinyint 2 int Decoupler Channel Table 19 2 DBI Table specification for class GAdWpHvMap which corresponds to table AdWpHvMap 2http dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GAdWpHvMap spec 190 CHAPTER 19 DATABASE TABLES 193 AdWpHvSetting Table specification source dybgaudi trunk Database DybDbi spec GAdWpHvsSetting spec Table of high voltage requested values mysql amp gt describe AdWpHvSetting 4 Field
280. ved Geant4 classes such as those enacting Cherenkov and scintillation processes The collection of unobservable statistics and particle histories is a fairly unique ability and is de scribed more below 11 2 Configuring DetSim The DetSim package can be extensively configured A default is set up done like limport DetSim 2detsim DetSim Configure You can provide various options to DetSim s Configure site indicating which site s geometry should be loaded This can be far the default or one of the two near sites dayabay or lingao or you can combine them if you wish to load more than one physics list gives the list of modules of Physics processes to load There are two lists provided by the configure class physics_list_basic and physics_list_nuclear By default both are loaded You can also configure the particle Historian and the UnObserver unobservable statistics collector Here is a more full example limport DetSim configure 2 only load basic physics 3detsim DetSim configure physics_list DetSim configure physics_list_basic 4detsim historian trackSelection vertexSelection 5detsim unobserver stats Details of how to form trackSelection vertexSelection and stats are given below 11 3 TRUTH INFORMATION 107 11 3 Truth Information Besides hits information on the true simulated quantities is available in the form of a particle history and a collection
281. vent data that was used to generate the database data that is to be stored For our example we will assume that DbiDemoData1 represents calibration data derived from event data It will be valid for 1 week from the date of the current event and be suitable for the same type of data Context now Event context e g CandHandle GetContext TimeStamp start now GetTimeStamp Add 7 days in secs to get end date time_t vcSec start GetSec 7 24 60 60 17 6 FILLING TABLES 171 TimeStamp end vcSec 0 Construct the ContextRange ContextRange range now GetDetector now GetSimFlag start end Demo 2 Instantiate a DbiWriter Create a DbiDemoDatal writer for unaggregated data task 0 Int_t aggNo 1 Dbi SubSite subsite 0 Dbi Task task 0 Decide a creation date default value is now TimeStamp create DbiWriter lt DbiDemoDatal gt writer range aggNo subsite task create 3 Pass filled DbiDemoDatal objects Create some silly data DbiDemoDatal row0 0 10 20 30 DbiDemoDatal row1 0 11 21 31 DbiDemoDatal row2 0 12 22 32 Store the silly data writer lt lt row0 writer lt lt rowl writer lt lt row2 The DbiWriter will call DbiDemoData1 s Store method Again notice that the SeqNo which is part of the table row but not part of the class data is silently handled by the system 4 Send the DbiWriter its Close message writer Close 17 6 4 Usin
282. w member The table 17 1 gives the recommended mapping between table row and MySQL column type Notes 17 5 CREATING NEW TABLES Table Row Type MySQL Type Comments Bool_t CHAR Char_t CHAR Char_t CHAR n n lt 4 n lt 4 Char_t TEXT n gt 3 string TEXT Short _t TINYINT 8 bit capacity Short _t SMALLINT 16 bit capacity Intt TINYINT 8 bit capacity Intt SMALLINT 16 bit capacity Intt INT or INTEGER 32 bit capacity Float_t FLOAT Double_t DOUBLE TimeStamp DATETIME Table 17 1 Recommended table row and database column type mappings 165 1 To save table space select CHAR n for characters strings with 3 or less characters and select the smallest capacity for integers 2 The long 64 bit integer forms are not supported as on some Intel processors they are only 4 bytes long 3 Although MySQL supports unsigned values we banned them when attempting to get a previous inter face to work with ORACLE so unsigned in database column type should be avoided It is allowed to have unsigned in the table row when a signed value is not appropriate and the interface will correctly handle I O to the signed value in the database even if the most significant bit is set i e the signed value in the database is negative It is unfortunate that the signed value in the database will look odd in such cases Designing a Table Row Class Here is a list of the requirements for a table row class Must inherit from D
283. y SEQNO ROW_COUNTER 164 CHAPTER 17 DATABASE ROW_COUNTER is a column whose value is generated by the interface it isn t part of table row class Its sole purpose is to ensure that every row in the table is unique an import design constraint for any database This is achieved by ensuring that for a given SEQNO each row has a different value of ROW_COUNTER This allows the combination of these two values to form a primary unique key which is declared in the trailing entry All database tables supported by the Databaselnterface have an auxiliary Context Range Tables that defines validity ranges for them Each validity range is given a unique sequence number that acts as a key and corresponds to SeqNo In our case indeed every case apart from the table name the definition is create table DbiDemoData1V1d SEQNO integer not null primary key TIMESTART datetime not null TIMEEND datetime not null SITEMASK tinyint 4 SIMMASK tinyint 4 TASK integer AGGREGATENO integer VERSIONDATE datetime not null INSERTDATE datetime not null key TIMESTART TIMESTART key TIMEEND TIMEEND When the Databaselnterface looks for data that is acceptable for a give validity it 1 Matches the validity to an entry in the appropriate Context Range Table and gets its SeqNo 2 Uses SeqNo as a key into the main table to get all the rows that match that key So as a designer you need to be aware of the sequence number and the row counte
284. ybDbi spec GGoodRunList spec List of runs files suitable for analysis name dbtype codetype description code2db RunNo int int Run number FileNo int int File sequence number StreamId int int Output stream Table 19 56 DBI Table specification for class GGoodRunList which corresponds to table GoodRunList 56nttp dayabay inep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GGoodRunList spec 244 CHAPTER 19 DATABASE TABLES 19 57 HardwarelD Table specification source dybgaudi trunk Database DybDbi spec GHardwarelD spec The Hardware ID table maps a Hardwareld from Conventions Hardware h to either a DetectorSensor Conventions Detectors h or an ElecChannelld Conventions Electronics h depending on the harddware type For the code note the DetectorSensor and ElecChannelld are stored in the form of the base class DayaBay Detector name dbtype codetype description code2db ChanOrSens int 11 DayaBay Detector Packed Channel Sensor ID fullPackedData HardwareId int 11 DayaBay HardwareId Packed Hardware ID fullPackedData Table 19 57 DBI Table specification for class GHardwareID which corresponds to table HardwareID 5Thttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GHardwarelD spec 19 58 HARDWAREIDFIX 245 19 58 HardwareIDFix Table specification source dybgaudi trunk Database DybDbi spec GHardwareIDFix spec Testing fix for dyb
285. ype description Channelld int 10 unsigned DayaBay FeeChannelId Electronics channel ID number Status int 10 unsigned int Channel status AdcPedestalHigh double double Measured high gain Pedestal ADC value AdcPedestalHighSigma double double high gain Pedestal ADC sigma AdcPedestalLow double double Measured low gain Pedestal ADC value AdcPedestalLowSigma double double low gain Pedestal ADC sigma AdcThresholdHigh double double Channel threshold as measured in ADC AdcThresholdLow double double Channel threshold as measured in ADC Table 19 9 DBI Table specification for class GCalibFeeSpecCleanup which corresponds to table Cal ibFeeSpecCleanup nttp dayabay ihep ac cn tracs dybsvn browser dybgaudi trunk Database DybDbi spec GCalibFeeSpecCleanup spec 19 10 CALIBPMTFINEGAIN 197 19 10 CalibPmtFineGain Table specification source dybgaudi trunk Database DybDbi spec GCalibPmtFineGain spec docstring name dbtype codetype description code2db Channelld int 11 DayaBay FeeChannelld unique id of the channel connected to a pmt fullPac SpeHigh float double SPE mean ADC value high gain SpeHighError float double error in SPE Mean ADC value high gain SigmaSpeHigh float double SPE 1 sigma peak width high gain SpeHighFitQual float double SPE fit quality in chi2 ndf high gain Table 19 10 DBI Table specification for class GCalibPmtFineGain which corresponds to table Cal ibPmtFineGain l0http dayabay ihep ac c
286. ysis Basics 3 1 Introduction This guide will help you analyze Daya Bay data It contains a short description of the Daya Bay data and analysis software called NuWa It is not a detailed technical manual In this document you can learn how to Open a data file and see what it contains Sec 3 2 1 Draw histograms of the data in the file Sec 3 2 2 Use NuWa to do more detailed calculations with the data Sec 3 3 Write your own NuWa analysis module Sec 3 4 7 Write your own NuWa analysis algorithm Sec 3 4 8 Select events using tags Sec 3 4 2 e Add your own data variables to the data file Sec 3 4 3 e Filter data based on data path or tag Sec 3 4 5 A set of cheat sheets are included These give short descriptions of the data and other NuWa features 3 2 Daya Bay Data Files Daya Bay uses ROOT files for data analysis Basic analysis can be done with these files using only the ROOT program http root cern ch For more complex analysis see the Section 3 3 on using NuWa If you do not have ROOT installed on your computer you can access it on the computer clusters as part of the NuWa software Sec 3 5 1 3 2 1 Opening data files Daya Bay data files can be opened using the ROOT program 1shell gt root 2root 0 TFile f recon NoTag 0002049 Physics DayaBay SFO 1 _0001 root 3root 1 TBrowser b 4root 1 b BrowseObject amp f 21 22 CHAPTER 3 ANALYSIS BASICS The ROOT browser window will display
287. ze execute and finalize methods as they would if they use the other two algorithm base classes DybAlgorithm is templated by the DataModel data type that it will produce and this type is specified when a subclass inherits from it Instances of the object should be created using the MakeHeaderObject method Any input objects that are needed should be retrieved from the data store using getTES or getAES Finally the resulting data object is automatically put into the TES at the location specified by the Location property which defaults to that specified by the DataModel class being used This will assure bookkeeping such as the list of input headers the random state and other things are properly set 6 4 2 Tools e examples e Implementing existing tool interface e writing new interface e required boilerplate _entries amp load files cpp macros 6 4 3 Services e common ones provided how to access in C e Implementing existing service interface e writing new interface Include difference between tools and service required boilerplate _entries amp load files cpp macros 70 CHAPTER 6 OFFLINE FRAMEWORK 6 4 4 Generalized Components 6 5 Properties and Configuration Just about every component that Gaudi provides or those that Daya Bay programmers will write one or more properties A property has a name and a value and is associated with a component Users can set properties that will then get applied by the framework

Daya Bay Offline Software User Manual November 5, 2015

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