TestTreeFits Class Reference

Inheritance diagram for TestTreeFits:

Collaboration diagram for TestTreeFits:

Public Member Functions
def	testFit (self)

Detailed Description

The unit test case for TreeFitter

Definition at line 14 of file treeFit_referenced_charged_tree_2dBeam.py.

Member Function Documentation

testFit()

def testFit

(

self

)

Run the test fit

Definition at line 17 of file treeFit_referenced_charged_tree_2dBeam.py.

    def testFit(self):
        """Run the test fit"""
 
        testFile = tempfile.NamedTemporaryFile()
 
        main = basf2.create_path()
 
        inputfile = b2test_utils.require_file(
            'analysis/1000_B_DstD0Kpi_skimmed.root', 'validation', py_case=self)
        ma.inputMdst('default', inputfile, path=main)
 
        ma.fillParticleList('pi+:a', 'pidProbabilityExpert(211, ALL) > 0.5', path=main)
        ma.fillParticleList('K+:a', 'pidProbabilityExpert(321, ALL) > 0.5', path=main)
 
        ma.reconstructDecay('D0:rec -> K-:a pi+:a', '', 0, path=main)
        ma.reconstructDecay('D*+:rec -> D0:rec pi+:a', '', 0, path=main)
        ma.reconstructDecay('B0:rec -> D*+:rec pi-:a', ' InvM > 5', 0, path=main)
        ma.matchMCTruth('B0:rec', path=main)
 
        conf = 0
        main.add_module('TreeFitter',
                        particleList='B0:rec',
                        confidenceLevel=conf,
                        massConstraintList=[],
                        massConstraintListParticlename=[],
                        expertUseReferencing=True,
                        ipConstraint=True,
                        originDimension=2,
                        updateAllDaughters=False)
 
        ntupler = basf2.register_module('VariablesToNtuple')
        ntupler.param('fileName', testFile.name)
        ntupler.param('variables', ['chiProb', 'M', 'isSignal'])
        ntupler.param('particleList', 'B0:rec')
        main.add_module(ntupler)
 
        basf2.process(main)
 
        ntuplefile = TFile(testFile.name)
        ntuple = ntuplefile.Get('ntuple')
 
        self.assertFalse(ntuple.GetEntries() == 0, "Ntuple is empty.")
 
        allBkg = ntuple.GetEntries("isSignal == 0")
        allSig = ntuple.GetEntries("isSignal > 0")
 
        truePositives = ntuple.GetEntries("(chiProb > 0) && (isSignal > 0)")
        falsePositives = ntuple.GetEntries("(chiProb > 0) && (isSignal == 0)")
 
        mustBeZero = ntuple.GetEntries("(chiProb < {})".format(conf))
 
        print("True fit survivors: {0} out of {1} true candidates".format(truePositives, allSig))
        print("False fit survivors: {0} out of {1} false candidates".format(falsePositives, allBkg))
 
        self.assertFalse(truePositives == 0, "No signal survived the fit.")
 
        self.assertTrue(falsePositives < 1413, f"Background rejection {falsePositives} out of {allBkg}")
 
        self.assertTrue(truePositives > 148, f"Signal rejection too high {truePositives} out of {allSig}")
        self.assertFalse(mustBeZero, "We should have dropped all candidates with confidence level less than {}.".format(conf))
 
        print("Test passed, cleaning up.")
 
 

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The documentation for this class was generated from the following file:

• analysis/tests/treeFit_referenced_charged_tree_2dBeam.py