Download - Bender v15r0 as your analysis environment

Bender v15r0 as your analysis environment

Vanya BELYAEV

mailto:[email protected]?subject=Bender%20Tutorial%20v7r0

Vanya BELYAEV 217 Sep 2k+10 LHCb Software Week

References• Bender Pages and Bender pages by

Lena Mayatskaya• Bender mailing list• Bender Savannah portal ( news, bugs, tasks, …)• Bender Tutorial TWiki• Bender HyperNews, TWiki, FAQ, User Guide and Manual : • not yet. still in the bottle of inc

• Phys/BenderExample & Tutorial/BenderTutor package

• “[email protected]”• 13-1-018 at CERN • +41 (0) 22 767 40 24

http://cern.ch/LHCb-release-area/DOC/bender

http://lhcb-comp.web.cern.ch/lhcb-comp/Analysis/Bender/index.html



mailto:[email protected]?subject=Bender%20pages

mailto:[email protected]?subject=Bender



http://savannah.cern.ch/projects/bender

http://savannah.cern.ch/news/?group=bender

https://savannah.cern.ch/bugs/?group=bender

https://savannah.cern.ch/task/?group=bender

https://twiki.cern.ch/twiki/bin/view/LHCb/BenderTutorial


http://building.web.cern.ch/map/building?bno=1




Vanya BELYAEV 3

When use Bender

• Python: perfect for prototyping• e.g. develop the cuts for preselection/stripping

• Interactive: perfect for “short” (“supervising”) tasks

• resolutions, efficiencies,• spectra• “reflections”

• Flexible & Friendly: • good for “the final” analysis of small data sets• combine with Root, Panoramix, RooFit,…

17 Sep 2k+10 LHCb Software Week

Vanya BELYAEV 4

When no Bender

• Stripping does not support Bender.• Reasons?

• Some CPU penalty for Bender selections vs LoKi selections is unavoidable (Python vs C++)

• could be visible/sizeable for “minimal” job• mainly comes from the explicit loops, N-Tuples and explicit

manipulations with dictionaries:sqrt(p.px()*p.px()+p.py()*p.py())

• usually negligible for realistic selection • And of course for well-coded lines

Totally negligible with patterns (C++)


Beer offer: Everyone who demonstrates visible CPU penalty with the proper usage of Bender with respect to the similar code using e.g.

DaVinci/LoKi/CombineParticles etc.

Vanya BELYAEV 5

The goal

• To be able in one hour to make following steps• selection of particles• extraction of the basic information• fill the histograms• looping over the particles• fill N-Tuples• save interesting combinations• Match to Monte Carlo truth

Covers >95% of functionality needed for event selection


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Bender


> SetupProject Bender v15r0


Minimal Bender script from Bender.Main import *

from Configurables import DaVinci

DaVinci ( DataType = ‘2010’ , )

gaudi = appMgr()

run(10)$BENDERTUTORROOT/solution/Minimalistic_0.py

BUT:Take care about input data!!

Well, It is not Bender, it is

Configurables +

GaudiPython


Minimal Bender module from Bender.Main import *def configure( files ,catalogs = []) : from Configurable import DaVinci DaVinci ( … ) setData ( files , catalogs )

gaudi=appMgr() … return SUCCESS

if __name__ == ‘__main__’ : inputfiles = …

configure( inputfiles )run(100)

$BENDERTUTORROOT/solution/Minimalistic.py

Application and Components Configuration

Job steering

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Scripts vs modules

• Dilemma in Python: scripts vs modules• Scripts are a bit more intuitive and a bit easier to write

• Problems with reusing • Modules require some discipline & conventions

• Full power of OO, including classes & extensions • Easy to import and reuse • The only way to assemble “large” application

from pieces• Be friendly: code modules

• loose nothing • gain a lot


Ganga assumes that you code is

module

Vanya BELYAEV 10

Scripts versus modules

• Script above: import myscript

Execute everything out of control.To change something – copy, cut-n-paste(and of course duplicate your colleague’s bugs +

introduce some of your own)• Module above – easy reusable by your

colleagues:import mymodule mymodule.config( inputdata )gaudi.run(100)



“Hello, World!” (I)

• The simplest possible BENDER “algorithm”• Follow LoKi’s style:

• inherit the algorithm from useful base class • (re)implement the “analyse” method

class HelloWorld(Algo) :def analyse( self ) :

print ‘Hello, World!’return SUCCESS

$BENDERTUTORROOT/solution/HelloWorld.py


“Hello, World!” (II)

• One needs to instatiate the algorithm: alg = HelloWorld( ‘Hello’ )

• Add it to the list of ‘active’ algorithms (TopAlg)

gaudi.addAlgorithm ( alg ) • Or:• Substitute the current list of algorithms:

gaudi.setAlgorithms ( [alg] )

• Execute run(10)

$BENDERTUTORROOT/solution/HelloWorld.py


Access to the data (LoKi-style)

• C++: GaudiAlgorithm/LoKi const LHCb::MCParticle::Container* mcps

=get<LHCb::MCParticle::Container>( “MC/Particles”)

• Python: Bender / GaudiAlgs

mcps = self.get( ‘MC/Particles’)

• Mnemonic rule: this-> → self.

$BENDERTUTORROOT/solution/DataAccess.py


Access to the data using service

• Inside the algorithm dataSvc = self.evtSvc() hdr = dataSvc[‘Header’] print ‘Event #’, hdr.evtNum()

• Outside algorithm-I (script) dataSvc = gaudi.evtSvc() hdr = dataSvc[’Header’] print ‘Run #’, hdr.runNum()

• Outside algorithm-II (script), shortcut hdr = get(‘Header’)


Attributes and (python) loops

for p in mcps :print ‘ID=‘ , name( p )print ‘PX=‘ , p.momentum().px()print ‘PY=‘ , p.momentum().py()print ‘decay: ’ , p.decay( True )

• All containers from Transient Event store are iterable

$BENDERTUTORROOT/solution/DataAccess.py

From Dictionaries

MCParticle


Help! And Attributes• To know the available attributes:

help( obj ) help( type( obj ) ) dir (), dir ( cpp ), dir ( LoKi ), dir ( LHCb )

• ON-LINE help for ALL Python/Bender functions/classes, sometimes it is VERY useful

• Doxygen pages:

>>> import LoKiCore.doxygenurl as doxy

>>> o = …

>>> doxy.browse ( o )

>>> doxy.browse ( ‘LHCb::MCParticle’ )


Decorations• Objects in python are “more rich:

>>> from Bender.MainMC import *>>> help(LHCb.MCParticle)>>> doxy.browser( LHCb.MCParticle )

• Many new methods (added “on-flight” by Bender):• child, children, parents, mother, ascendents, descendent, printDecay, …

• Uniform with LHCb.Particle & HepMC.GenParticle

p = …

for c in p.children() :

print c

c1 = p.child(1)

p = …

for c in children( p ) :

print c

c1 = child( p , 1)

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Lets start with physics analysis

• <Almost> all of LoKi’s idioms are in Bender• (No need to write the separate manual)

• The semantics is very similar• Inspite of DIFFERENT languages• Few “obvious” exceptions

• In the game• All functors (functions/predicates) “cuts”• All (v,mc,mcv,g)select methods • Loops,plots• For nTuples the functionality is a bit limited

• A lack of templated methods


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The Simplest case: make KS

• Select pions according to some criteria• Track quality• (Kinematical properties)• (Pointing criteria)

• Combine p+p- pairs • Vertex quality• Pointing criteria• Flight distance


$BENDERTUTORROOT/solution/MakeKs.py

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1. Select pions pi_plus = self.select ( ‘MyGoodPi+’ , ( ‘pi+’ == ID ) & ( TRCHI2DOF < 10 ) ) pi_minus = self.select ( ‘MyGoodPi-’ , ( ‘pi-’ == ID ) & ( TRCHI2DOF < 10 ) ) print “# pi+ : ”, len(pi_plus) for pi in pi_plus : print pi.pname() , pi.pt()


pions = self.select ( ‘GoodPi’ ,

( ‘pi+’ == ABSID ) & ( TRCHI2DOF < 10 ) )

pi_plus = self.select ( ‘MyGoodPi+’ , pions , Q > 0 )

pi_minus = self.select ( ‘MyGoodPi-’ , pions , Q < 0 )

Select p+

& p-

c2

(track)/nDoF<10

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2. Combine p+p- pairs # define the looping rules: components & the result

v0s = self.loop ( ‘MyGoodPi+ MyGoodPi-’, ‘KS0’ )

for k0 in v0s :

# fast check of mass from the sum of 4-momenta: m12 = k0.mass(1,2) / MeV if not 300 < m12 < 800 : continue # check vertex-fit chi2 (fit if not done yet): chi2vx = VCHI2 ( k0 ) if not 0 <= chi2vx <= 100 : continue self.plot ( M ( k0 ) , ‘mass K0S’ , 400 , 600 )


c2

(vertex)<10 0

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(2a. Apply more cuts in loop)

# get the best primary vertex from DaVinci bpv = self.bestVertex( k0.particle() ) if not bpv : continue

# calculate the lifetime of Ks-candidate: ctau = LTIME( self.lifetimeFitter() , bpv ) * c_light if ctau ( k0 ) < 5 * mm : continue

# calculate the chi2(IP) for Ks-candidate: chi2ip = IPCHI2 ( bpv , self.geo() ) if ch2ip ( k0 ) > 9 : continue

self.plot ( M ( k0 ) , ‘mass K0S’ , 400 , 600 )


ct > 5mm

c2

(IP)<9

Vanya BELYAEV 23

(2b. Apply cuts before loop)

# get all primary vertices: primaries = self.vselect( ‘pv’ , PRIMARY ) if primaries.empty() : continue

# create functor for evaluation of min(chi2ip) mips = MIPCHI2( primaries , self.geo() ) # BEFORE LOOP: … = self.select ( … , … & ( mips > 9 ) )

# INSIDE THE LOOP: pi1 = k0(1) pi2 = k0(2) if mips( pi1 ) < 9 or mips(pi2) < 9 : continue


Access to the individual loop

components

c2

(IP)>9

c2

(IP)>9

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Combine everything together

from Bender.Main import *class MakeKs(Algo): def analyse ( self ) : … return SUCCESSdef configure ( inputdata , catalogs = [] ) : … if ‘__main__’ == __name__ : configure ( … ) run ( 1000 )


$BENDERTUTORROOT/solution/MakeKs.py

Vanya BELYAEV 25

Simple case-II: strip DSTs

• Use V0.DST, Reco05-Stripping09• Stripping Line:

“StrippingK0SLine”• Stripping Decision

“StirppingL0SLineDecision”• OutputLocation:

“/Event/V0/Phys/StrippingK0S”• Get candidates from DST

• Specific configuration• Analyse them


Vanya BELYAEV 26

3. Select Ks

ks_1 = self.select ( ‘MyKs’ , ‘KS0’ == ID ) ks_2 = self.select ( ‘MyGoodKs’ , ks_1 , PT > 1 * GeV ) print “# Ks : ”, len(ks_1)

for Ks in ks1_2 : print Ks.decay() , Ks.pt() print PT ( Ks ) self.plot ( M( Ks ) , ‘Mass Ks’ , 400 , 600 )


$BENDERTUTORROOT/solution/SelectK0S(_1,_2).py

Vanya BELYAEV 27

Simple case-III: mDSTs

• Use mDST produced to test “PromptCharm” lines from CHARM.DST, Reco04-Stripping07• OutputLocation:

• Root-On-TES“/Event/MicroDST/PromptCharm”

• Locations“Sel(Dstar,D,Ds,LambdaC)ForPromtCharm”

• Get candidates from DST• Specific configuration• Analyse them


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4. Get D*+ decays # select from TES the interesting decays

dstars = self.select ( ‘MyD*’, ‘[ D*(2010)+ -> ( D0 -> K- pi+) pi+]CC’ )

Dm = M – M1

for D in dstars: m1 = M1 ( D ) # mass of the first particle dm = Dm ( D ) if abs ( dm – 145 * MeV ) < 2.5 * MeV : self.plot ( m1 , ‘mass D0’ , 1.8 , 1.9 )


Use decay descriptor

Cut on |dDM|<1.5 MeV/c2

$BENDERTUTORROOT/solution/SelectDstar.py

Vanya BELYAEV 29

(4a. Loop D*+ decays) ltFit = self.lifetimeFitter()

# loop for D*+ decays: for D in dstars : # get daughter particle by index: D0 = D.child ( 1 ) # get related primary vertex pv = self.bestVertex ( D0 ) # create the functor: ctauFun = LTIME ( ltFit , pv ) * c_light # evaluate c*tau ctau = ctauFun ( D0 ) # make histogram self.plot ( ctau , ‘c*#tau for D^{0} ’ , 0. , 1.0 )


Vanya BELYAEV 30

Simple case-IV: mDSTs

• CHARM.DST, Reco05-Stripping07• Sum of D+/Ds

+ lines by Conor&Rio

• Get candidates from DST• Specific configuration• Analyse them

• The same mDST produced to test “PromptCharm” lines from CHARM.DST, Reco04-Stripping07


Vanya BELYAEV 31

5 Get D+/Ds+ decays

# select from input particles according to the decay pattern:d_1 = self.select(‘d1’ , “[ D+ -> K- pi+ pi+]CC" )ds_1 = self.select(‘ds1’, “[ D_s+ -> K- K+ pi+]CC“ )ds_2 = self.select(‘ds2’, ”[ D_s+ -> ( phi(1020) -> K- K+ ) pi+]CC” )

for d in d_1 : self.plot ( M(d) , 'D+ -> K pi pi' , 1800 , 1900 , 100 ) pv = self.bestVertex( d ) fun = LTIME ( self.lifetimeFitter() , pv ) * c_light ctau = fun ( d ) if 0.1 < ctau < 1.0 : self.plot ( ctau , 'c*tau for D+', 0 , 1 )

for d in ds_1 : self.plot ( M(d) , 'D+/Ds+ -> Kkpi ' , 1800 , 2050 , 250 )

for d in ds_2 : self.plot ( M(d) , 'Ds+ -> phi pi+' ,1770,2070,300 )


$BENDERTUTORROOT/solution/SelectDplus(_1).py

Vanya BELYAEV 32

(5a What about N-tuples?)# select from input particles according to the decay pattern:

d_1 = self.select(‘d1’ , “[ D+ -> K- pi+ pi+]CC" )

# retrive (book-n-demand) N-tuple object

tup = self.nTuple(‘MyN-tuple’)for d in d_1 : …

# add the columns to n-tuple tup.column ( ‘m’ , M ( d ) ) tup.column ( ‘pt’ , PT ( d ) ) tup.column ( ‘ctau’ , ctau )

# commit the row: tup.write()


$BENDERTUTORROOT/solution/SelectDplus(_1).py

Vanya BELYAEV 33

The last step: MC-truth match

• The simplest case: check if RC particles originates form certain MC-(sub)tree:• The most frequent case

• Check for efficiency• Resolution

• The opposite case ( RC ↔ MC ) • similar MCTRUTH ↔ RCTRUTH

NB: LoKi ( and therefore Bender) uses own

concept of MC loose matching


Vanya BELYAEV 34

Select MC-particles# select Monte Carlo particles according to the decay pattern:

mcD = self.mcselect ( ‘myD’ , “[ D+ => K- pi+ pi+]CC" )# select Monte Carlo particles according to kinematics :

mcD1 = self.mcselect (‘myGoodD’ , ( MCPT > 1 * GeV ) & in_range ( 1.0 , MCY , 5.0 ) )

# use marked decay descriptors:

K = self.mcselect( ‘K’ , mcD1 , “[ D+ => ^K- pi+ pi+]CC” )Pi = self.mcselect( ‘Pi’ , mcD1 , “[ D+ => K- ^pi+ ^pi+]CC” )

# loop over selected true D+

for D in mcD1 : print D.decay() , MCE( D )


$BENDERTUTORROOT/solution/SelectDplusMC(_1).py

Vanya BELYAEV 35

MC-Truth matching functions

# retrieve Monte Carlo Truth matcher

match = self.mcTruth (‘My MC-truth matcher’)

# prepare MC-Truth matching functors

trueK = MCTRUTH ( match , K )truePi = MCTRUTH ( match , Pi )trueD = MCTRUTH ( match , mcD1 )



# get the reconstructed particle

particle = …

# check MC-truth:

Ok = trueK ( particle )

Vanya BELYAEV 36

Use MC-Truth functors (1)# select only MC-truth matched kaons

kaons = self.select (‘k’ , (‘K+’ == ABSID ) & trueK ) kplus = self.select ( ‘K+’ , kaons , Q > 0 )kminus = self.select ( ‘K-’ , kaons , Q < 0 )

# select only MC-truth matched pions

pions = self.select ( ‘pi’ , (‘pi+’ == ABSID ) & truePi )

for k in kplus : print PT ( k )

for p in pions : print PT ( pi )



Vanya BELYAEV 37

Use MC-Truth functors (2)# in loop over particles:

D = self.loop ( ‘ K- K+ pi‘ , ‘D+’ ) for d in D :

# get the loop components kaon1 = d(1) kaon2 = d(2) pion = d(3) # check MC-Truth: ok1 = trueK ( kaon1 ) ok2 = trueK ( kaon2 ) ok3 = truePi ( pion ) ok4 = trueD ( d )



Vanya BELYAEV 38

Few ‘interactive’ hints I

• Get application manager: gaudi = appMgr()

• List the content of Event Transient Store ls () ls (‘/Event’)

• Get an object from Transient Store obj = get(‘/Event/Hlt/DecReports’)

• Run “n” events run ( n )


Vanya BELYAEV 39

Few ‘interactive’ hints - II

• List the histograms in HTS: hsvc = gaudi.histSvc() hsvc.dump()

• Get the histogram by ID (==title): h = hsvc[‘Phi/K+K- mass ’]

• Visualize the histogram as ROOT histo: h.plot() h.Draw()


import ROOT

Vanya BELYAEV 40

Few ‘interactive’ hints - III

• Get the map of all histograma by the given component (algorithm or tool) cmp = gaudi.algorithm ( ‘AlgName’) histos = cmp.Histos() for id in histos : histo = histos[id]

• Get the histogram from component (algorithm or tool) by ID id = … histo = cmt.Histos (id)


Vanya BELYAEV 41

Few ‘interactive’ hints - IV

• ASCII dump of the histogram ## Width , Height, Plot errors print histo.dump( 70 , 20 , True )

• AACII dump for all histogram of the given component (algorithm or tool) cmp = … cmt.dumpHistos ( 50 , 15 , True )

• AACII dump for all histogram of the given component by name: dumpHistos ( ‘MyAlg’ , 70, 50 , True )


Vanya BELYAEV 42

Few ‘interactive’ hints - V

• Get all tools, acquired by given component tools = cmp.Tools() for t in tools : print t.OutputLevel

• Dump all properties of given component cmp = … cmp.PropertiesPrint = True

• Dump the summary of counters for the given component cmp = … cmp.StatPrint = True


Vanya BELYAEV 43

Few ‘interactive’ hints - VI

• Dump the summary of histograms cmp = … cmt.HistoPrint = True

• Dump the summary of N-tuples cmp = … cmp.NTuplePrint = True

• Dump the summary of ETCs cmp = … cmp.EvtColsPrint = True


Vanya BELYAEV 44

Few ‘interactive’ hints - VII

• ‘Easy’ browser for (s,r,m,x,..)DSTs content:

dst_explorer [opts] file1 [ file2 [ …


>>> ls()

>>> ls (‘/Event’)

>>> ls (‘/Event/Dimuon’)

>>> ls (‘/Event/Dimuon/Phys’)

Vanya BELYAEV 45

Other features, out of scope

• Nice printout of trees, particles, events• Various “extractors” and metafunctions• HepMC + HepMCParticleMaker• Jets • Tools for background origin studies • Patterns• and much much more… As concerns the functionality needed for

analysis, Bender is full scale application, widely used for many

physics studies. 17 Sep 2k+10 LHCb Software Week

Vanya BELYAEV 46

Next (obvious) steps

• Integrate with DIRAC/Ganga• Integrate with Panoramix•More, more and more “on-flight” decorations:

p.name() , name(p), …p.printDecay() , printDecay(p) , …



References again…• Bender Pages and Bender pages by

Lena Mayatskaya• Bender mailing list• Bender Savannah portal ( news, bugs, tasks, …)• Bender Tutorial TWiki • Regular informal “hands-on” tutorials

• You know whom to ask…• Bender Examples • “[email protected]”

• 13-R-018 at CERN • +41 (0) 22 767 40 24

http://cern.ch/LHCb-release-area/DOC/bender




mailto:[email protected]?subject=Bender%20pages




http://savannah.cern.ch/projects/bender

http://savannah.cern.ch/news/?group=bender

https://savannah.cern.ch/bugs/?group=bender

https://savannah.cern.ch/task/?group=bender






