Inheritance diagram for jobOption.MyParticleSampler:

Collaboration diagram for jobOption.MyParticleSampler:

Public Member Functions
def	__init__ (self)

def	shoot (self)

def	__init__ (self)

def	shoot (self)

Public Attributes
	mom1

	ip

Detailed Description

A special sampler to generate single particles flat in 1/pT and in
impact parameter to the beam, with flat z0.

Definition at line 10 of file jobOption.ParticleGun_correlated.py.

Constructor & Destructor Documentation

◆ init() [1/2]

def jobOption.MyParticleSampler.__init__ ( self )

Definition at line 13 of file jobOption.ParticleGun_correlated.py.

     def __init__(self):
         self.mom1 = PG.PtEtaMPhiSampler(pt=25000, eta=[-2,2])
  

◆ init() [2/2]

def jobOption.MyParticleSampler.__init__ ( self )

Definition at line 16 of file jobOption.ParticleGun_flatcurvature_flatip.py.

     def __init__(self):
         psamp = PG.PtEtaMPhiSampler(pt=PG.InvSampler(4000, 400000), eta=[0.1,0.3], phi=[0.3, 0.5])
         xsamp = PG.PosSampler(0, 0, [-150,150], 0)
         PG.ParticleSampler.__init__(self, pid={13,-13}, mom=psamp, pos=xsamp)
         self.ip = PG.mksampler([-2,2])
  

Member Function Documentation

◆ shoot() [1/2]

def jobOption.MyParticleSampler.shoot ( self )

Definition at line 16 of file jobOption.ParticleGun_correlated.py.

     def shoot(self):
         "Return a vector of sampled particles"
         p1 = PG.SampledParticle(11, self.mom1.shoot())
         eta1 = p1.mom.Eta()
         phi1 = p1.mom.Phi()
         # TODO: will phi be properly wrapped into range?
         mom2 = PG.PtEtaMPhiSampler(pt=25000,
                                    eta=[eta1-0.5, eta1+0.5],
                                    phi=[phi1-0.5, phi1+0.5])
         p2 = PG.SampledParticle(11, mom2.shoot())
         return [p1, p2]
  

◆ shoot() [2/2]

def jobOption.MyParticleSampler.shoot ( self )

Definition at line 22 of file jobOption.ParticleGun_flatcurvature_flatip.py.

     def shoot(self):
         "Return a vector of sampled particles"
         ps = PG.ParticleSampler.shoot(self)
         assert len(ps) == 1
         p = ps[0]
         from math import sqrt
         m = -p.mom.X() / p.mom.Y() #< gradient of azimuthal IP sampling line, perp to mom
         x = self.ip() / sqrt(1 + m**2) #< just decomposing sampled IP into x component...
         y = m*x #< ... and y-component
         p.pos.SetX(x)
         p.pos.SetY(m*x)
         return [p]
  