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MyMiniAnalysis

In cache mode, this simple example

• demonstrates how to access Monte Carlo truth information associated with a given BtaCandidate;
• optionally prints out information about BtaCandidates on a specified list;
• illustrates how to set up a tag-level filter.

The underlying analysis TCL file BetaMiniUser/MyMiniAnalysis.tcl contains instructions on how to set up a tag-level filter.

Table 5: MyMiniAnalysis module parmaeters.

Module parameter	Description	Default value
eventInfoList	EventInfoList key	Default
btaMicroList	input list key	BtaMicroCandidates
btaTruthMap	Monte Carlo truth map key	GHit
btaListToPrint	key of BtaCandidate list to print	NoListToPrint

Table 6: myMiniAnalysisJob.tcl snippet example

set ConfigPatch MC 
set levelOfDetail cache
set BetaMiniTuple hbook
set histFileName myMiniAnalysisJob.hbk

## "NEvent" specifies the number of events to process. If omitted, process all events
##
set NEvent 1000

## specify input collections. 
## 
source SP-B0B0bar-Run4.tcl

## add any job-specific module parameters to the module talk stanza below, e.g.:
# module talk MyMiniAnalysis
#   btaMicroListToPrint set ChargedTracks
# exit

sourceFoundFile BetaMiniUser/MyMiniAnalysis.tcl

The MyMiniAnalysis module parameters are described in Table  5.

Table 6 shows an example TCL snippet needed to configure MyMiniAnalysis, including both the TCL and module parameters.

To run this example, copy the contents of this table to workdir/myMiniAnalysisJob.tcl, set the TCL and module parameters to their desired values, and then type the command

        BetaMiniApp myMiniAnalysisJob.tcl

Doing so will produce a histogram file with this example's histograms in directory MYMINIANALYSIS.

Notes:

• In the myMiniAnalysisJob.tcl file listed in Table 6, the number of events to process is specified by the command

          set NEevent <number>
  

  If this TCL variable is not set, then all data in the input collections become available for processing.
• The file containing the input collections, SP-B0B0bar-Run4.tcl, was generated by the bookkeeping command

          BbkDatasetTcl --datasets SP-B0B0bar-Run4
  

Figure: (left:) difference between reconstructed and Monte Carlo truth BtaCandidate momentum, charged tracks and (right:) charged track momentum distribution, both from an SP6 Monte Carlo dataset of generic events.

Figure 1(left) shows the difference between the reconstructed and Monte Carlo truth momenta for charged tracks from a 1000 event sample of SP6 generic events Monte Carlo events simulated in release 14.4.0c.

In the same sample, Table 7 shows the number of reco BtaCandidates with and without a Monte Carlo truth BtaCandidate match as a function of the charge of the reconstructed BtaCandidate:

Table: Number of reconstructed BtaCandidates with and without a corresponding Monte Carlo truth BtaCandidate match in an SP6 Monte Carlo dataset of generic events simulated in release 14.4.0c.

charge:	$-1$	$0$	$+1$
match:	$5712$	$15184$	$5871$
no match:	$63$	$2204$	$43$