def __init__(self):
#interaction cross section, mb
self.sigma_tot = 0.
#instantaneous luminosity, cm^-2 sec^-1
self.lumi_cmsec = 0.
#number of bunches
self.nbunch = 0.
#electron beam energy, GeV
self.Ee = 0.
#coincidence selection
self.emin = 1. # GeV
#collider circumference, speed of light, electron mass
self.circ = 3834. # m
self.cspeed = 299792458. # m sec^-1
self.me = TDatabasePDG.Instance().GetParticle(11).Mass() # GeV
#input
self.tree = TChain("DetectorTree")
#geometry
self.geo = None
#output file name
self.outfile = "hits_spect.root"
def __init__(self,
funcName,
minMass,
maxMass,
numSigmaSideBands=0.,
peakMass=0.,
peakSigma=0.,
secPeakMass=0.,
secPeakSigma=0.):
if funcName not in self.__implFunc:
raise ValueError(f'Function \'{funcName}\' not implemented')
self.funcName = funcName
self.minMass = minMass
self.maxMass = maxMass
self.peakMass = peakMass
self.peakDelta = peakSigma * numSigmaSideBands
self.secPeakMass = secPeakMass
self.secPeakDelta = secPeakSigma * numSigmaSideBands
self.funcSBCallable = None
self.funcFullCallable = None
self.removePeak = False
self.removeSecPeak = False
if self.peakMass > 0. and self.peakDelta > 0.:
self.removePeak = True
if self.secPeakMass > 0. and self.secPeakDelta > 0.:
self.removeSecPeak = True
self.mPi = TDatabasePDG.Instance().GetParticle(211).Mass()
def decayTree(self, genparticles):
db = TDatabasePDG()
theString = ""
for part in genparticles:
if part.M1==-1 and part.M2==-1:
theString += part.printDecay(db, genparticles)
return theString
def __init__(self, parse, tree, hepmc_attrib):
#minumum and maximum energy, GeV
self.emin = parse.getfloat("main", "emin")
self.emax = parse.getfloat("main", "emax")
print("emin =", self.emin)
print("emax =", self.emax)
#pdg for generated particle, electron or photon
self.pdg = 22
if parse.has_option("main", "pdg"):
self.pdg = parse.getint("main", "pdg")
print("pdg =", self.pdg)
#angular range, electrons for now
self.theta_min = 0.
self.theta_max = 0.
#angles as mlt = -log_10(pi - theta)
if parse.has_option("main", "mlt_min"):
mlt_min = parse.getfloat("main", "mlt_min")
mlt_max = parse.getfloat("main", "mlt_max")
print("mlt_min =", mlt_min)
print("mlt_max =", mlt_max)
self.theta_min = TMath.Pi() - 10.**(-mlt_min)
self.theta_max = TMath.Pi() - 10.**(-mlt_max)
print("theta_min =", self.theta_min)
print("theta_max =", self.theta_max)
#generator functions for photons and electrons
self.gen_func = {}
self.gen_func[22] = self.gen_phot
self.gen_func[11] = self.gen_el
#test for pdg
if self.gen_func.get(self.pdg) is None:
print("Fatal: pdg", self.pdg, "is not supported")
raise KeyError
#uniform generator
self.rand = TRandom3()
self.rand.SetSeed(5572323)
#electron mass
self.me = TDatabasePDG.Instance().GetParticle(11).Mass()
#set the output tree
if self.pdg == 22:
tnam = ["gen_E"]
if self.pdg == 11:
tnam = ["true_el_pT", "true_el_theta", "true_el_phi", "true_el_E"]
self.out = self.make_tree(tree, tnam)
#event attributes for hepmc
self.hepmc_attrib = hepmc_attrib
print("Uniform generator initialized")
def __init__(self, filename, exclude_noise, save_plot, max_spill_count):
self.filename = filename
self.exclude_noise = exclude_noise
self.save_plot = save_plot
self.data_dir = os.path.dirname(self.filename)
if not self.data_dir:
self.data_dir = '.'
self.file_basename = os.path.basename(self.filename)
self.max_spill_count = max_spill_count
self.pdg = TDatabasePDG()
self.delta_x = 1.4 # mm
self.delta_y = 8.6 # mm
self.delta_z = 0. # mm
# self.delta_x = 1375.9 # mm
# self.delta_y = -67.5 # mm
# self.delta_z = -14617.4 # mm
self.angle_rotation_y_axis = -0.349 * pi / 180. # rad
def __init__(self, parse):
#energy of electron beam, GeV
self.Ee = parse.getfloat("main", "Ee")
#proton beam, GeV
self.Ep = parse.getfloat("main", "Ep")
print("Ee =", self.Ee, "GeV")
print("Ep =", self.Ep, "GeV")
#minimal photon energy, GeV
self.emin = parse.getfloat("main", "emin")
print("emin =", self.emin)
#electron and proton mass
self.me = TDatabasePDG.Instance().GetParticle(11).Mass()
self.mp = TDatabasePDG.Instance().GetParticle(2212).Mass()
self.mep = self.me * self.mp
#CMS energy squared, GeV^2
self.s = 2 * self.Ee * self.Ep + self.me**2 + self.mp**2
self.s += 2 * TMath.Sqrt(self.Ee**2 -
self.me**2) * TMath.Sqrt(self.Ep**2 -
self.mp**2)
print("s =", self.s, "GeV^2")
#normalization, 4 alpha r_e^2
self.ar2 = 4 * 7.297 * 2.818 * 2.818 * 1e-2 # m barn
#parametrizations for dSigma/dy and dSigma/dtheta
gRandom.SetSeed(5572323)
self.eq1par = self.eq1(self)
self.dSigDy = TF1("dSigDy", self.eq1par, self.emin / self.Ee, 1)
tmax = 1.5e-3 #maximal photon angle
self.eq3par = self.eq3(self)
self.dSigDtheta = TF1("dSigDtheta", self.eq3par, 0, tmax)
#uniform generator for azimuthal angles
self.rand = TRandom3()
self.rand.SetSeed(5572323)
print("H1 parametrization initialized")
print("Total cross section: " +
str(self.dSigDy.Integral(self.emin / self.Ee, 1)) + " mb")
def get_scale(Ni):
#scale for event rate in Hz per one simulated interaction
#Ni is number of simulated interactions
#interaction cross section, mb
sigma_tot = 171.29 # 18x275
#sigma_tot = 123.83 # 10x100
#sigma_tot = 79.18 # 5x41
#instantaneous luminosity, cm^-2 sec^-1
lumi_cmsec = 1.54e33 # 18x275
#lumi_cmsec = 4.48e33 # 10x100
#lumi_cmsec = 0.44e33 # 5x41
#number of bunches
nbunch = 290 # 18x275
#nbunch = 1160 # 10x100
#nbunch = 1160 # 5x41
#electron beam energy, GeV
#Ee = 18. # GeV
#Ee = 10. # GeV
Ee = 5. # GeV
#collider circumference, speed of light, electron mass
circ = 3834. # m
cspeed = 299792458. # m sec^-1
me = TDatabasePDG.Instance().GetParticle(11).Mass() # GeV
#beam velocity (units of c)
beta = np.sqrt(Ee**2 - me**2) / Ee
print("Beta:", beta)
print("Orbit period (micro sec):", 1e6 * circ / (beta * cspeed))
#bunch spacing, sec
Tb = circ / (beta * cspeed * nbunch)
print("Bunch spacing (micro sec):", 1e6 * Tb)
print("Bunch frequency (MHz):", 1e-6 / Tb)
#luminosity per bunch crossing, mb^-1
Lb = lumi_cmsec * 1e-27 * Tb
print("Luminosity per bunch crossing, mb^-1:", Lb)
print("Mean number of interactions per bunch crossing:", sigma_tot * Lb)
print("Probability for at least one interaction in bunch crossing:",
(1. - np.e**(-sigma_tot * Lb)))
scale = {}
scale["lambda"] = sigma_tot * Lb
scale["Tb"] = Tb # sec
#rate per one simulated interaction, Hz
#return (1./Ni)*sigma_tot*1e-27*lumi_cmsec
return scale
def __init__(self, parse):
#electron beam, GeV
self.Ee = parse.getfloat("main", "Ee")
#proton beam, GeV
self.Ep = parse.getfloat("main", "Ep")
print("Ee =", self.Ee, "GeV")
print("Ep =", self.Ep, "GeV")
#minimal photon energy, GeV
self.emin = parse.getfloat("main", "emin")
print("emin =", self.emin)
#maximal photon angle
self.tmax = 1.5e-3
if parse.has_option("main", "tmax"):
self.tmax = parse.getfloat("main", "tmax")
#electron and proton mass
self.me = TDatabasePDG.Instance().GetParticle(11).Mass()
self.mp = TDatabasePDG.Instance().GetParticle(2212).Mass()
self.mep = self.me * self.mp
#normalization, 4 alpha r_e^2
self.ar2 = 4*7.297*2.818*2.818*1e-2 # m barn
#parametrizations for dSigma/dE_gamma and dSigma/dtheta
gRandom.SetSeed(5572323)
self.eq1par = self.eq1(self)
self.dSigDe = TF1("dSigDe", self.eq1par, self.emin, self.Ee)
self.theta_const = 1e-11 # constant term in theta formula
self.eq2par = self.eq2(self)
self.dSigDtheta = TF1("dSigDtheta", self.eq2par, 0, self.tmax)
#uniform generator for azimuthal angles
self.rand = TRandom3()
self.rand.SetSeed(5572323)
print("ZEUS parametrization initialized")
print("Total cross section: "+str(self.dSigDe.Integral(self.emin, self.Ee))+" mb")
def __init__(self, en, pdg, zsign):
#energy, pdg, sign of z-momentum
particle.__init__(self, pdg)
self.pdg = pdg
#status code for beam particles
self.stat = 201
#set kinematics for beam particle
m = TDatabasePDG.Instance().GetParticle(pdg).Mass()
pz = zsign * sqrt(en**2 - m**2)
self.vec.SetPxPyPzE(0, 0, pz, en)
def get_s(self, Ee, Ep):
#calculate the CMS squared s
#proton mass
mp = TDatabasePDG.Instance().GetParticle(2212).Mass()
#CMS energy squared s, GeV^2
s = 2.*Ee*Ep + self.me**2 + mp**2
s += 2*TMath.Sqrt(Ee**2 - self.me**2) * TMath.Sqrt(Ep**2 - mp**2)
#print "sqrt(s):", TMath.Sqrt(s)
return s
def __init__(self, en, theta, phi):
particle.__init__(self, 11)
#transverse momentum
m = TDatabasePDG.Instance().GetParticle(11).Mass()
pt = sqrt(0.5 * (en**2 - m**2) * (1. - cos(2. * theta)))
#pseudorapidity, rotate the theta for pz negative
theta = pi - theta
eta = -log(tan(theta / 2.))
#set the electron Lorentz vector
self.vec.SetPtEtaPhiE(pt, eta, phi, en)
#status for the final particle
self.stat = 1
def q2_calc_vec_from_kine(en, theta, phi):
#create Lorentz vector from electron kinematics loaded from the tree
#transverse momentum
m = TDatabasePDG.Instance().GetParticle(11).Mass()
pt = sqrt(0.5 * (en**2 - m**2) * (1. - cos(2. * theta)))
#pseudorapidity
eta = -log(tan(theta / 2.))
#set the Lorentz vector
vec = TLorentzVector()
vec.SetPtEtaPhiE(pt, eta, phi, en)
return vec
def __init__(self, parse):
#electron beam energy, GeV
self.Ee = parse.getfloat("main", "Ee")
print("Ee =", self.Ee)
#energy spread from input relative energy spread
self.espread = None
if parse.has_option("main", "espread"):
sig_e = self.Ee * parse.getfloat("main", "espread")
self.espread = TF1("espread", "gaus", -12 * sig_e, 12 * sig_e)
self.espread.SetParameters(1, 0, sig_e)
#electron mass
self.me = TDatabasePDG.Instance().GetParticle(11).Mass()
print("Electron beam initialized")
def __init__(self, pdg):
#particle Lorentz vector
self.vec = TLorentzVector()
#index in particle list
self.idx = 0
#status code
self.stat = 0
#pdg code
self.pdg = pdg
#particle database for pass and codes
self.pdgdat = TDatabasePDG.Instance()
#mass, GeV
self.mass = self.pdgdat.GetParticle(self.pdg).Mass()
#parent particle id
self.parent_id = 0
#vertex coordinates, mm
self.vx = 0.
self.vy = 0.
self.vz = 0.
#precision for momentum and energy
self.pxyze_prec = 6
# result_1Bn_ecut_5.root 1E9 with Ecut > 5 GeV
# result_0.1Bn_ecut_0.5.root 1E8 with Ecut > 0.5 GeV
Yandex = False # False
Yandex2 = False # summer 2015 production, 10B, Ecut>10GeV, Mo/W/ target
Yandex3 = True # spring 2016 production, 10B, Ecut>10GeV, Mo/W/ target, record start of track
afterHadronAbsorber = False
JPsi = False # True
MoTarget = False
Tau = False
import ROOT, os
from array import array
from ROOT import TDatabasePDG, TMath, gDirectory
from rootUtils import *
pdg = TDatabasePDG()
mu = pdg.GetParticle(13)
Mmu = mu.Mass()
Mmu2 = Mmu * Mmu
if Yandex:
stats = {5.: [1E9, 1E9], 0.5: [1E8]}
files = {
5.: [
'$SHIPSOFT/data/result_1Bn_ecut_5.root',
'$SHIPSOFT/data/result_1Bn_ecut_5-v02.root'
],
0.5: ['$SHIPSOFT/data/result_0.1Bn_ecut_0.5.root']
}
fnew = 'pythia8_Geant4_total_Yandex.root'
if Yandex2:
def main():
#input
inp = TFile.Open("pC.root")
tree = inp.Get("DetectorTree")
#input generated particles
gen_pdg = std.vector(int)()
gen_en = std.vector(float)()
tree.SetBranchAddress("gen_pdg", gen_pdg)
tree.SetBranchAddress("gen_en", gen_en)
#layer hits
lay10_hit_edep = std.vector(float)()
lay11_hit_edep = std.vector(float)()
lay12_hit_edep = std.vector(float)()
lay13_hit_edep = std.vector(float)()
lay20_hit_edep = std.vector(float)()
lay21_hit_edep = std.vector(float)()
lay22_hit_edep = std.vector(float)()
lay23_hit_edep = std.vector(float)()
tree.SetBranchAddress("lay10_HitEdep", lay10_hit_edep)
tree.SetBranchAddress("lay11_HitEdep", lay11_hit_edep)
tree.SetBranchAddress("lay12_HitEdep", lay12_hit_edep)
tree.SetBranchAddress("lay13_HitEdep", lay13_hit_edep)
tree.SetBranchAddress("lay20_HitEdep", lay20_hit_edep)
tree.SetBranchAddress("lay21_HitEdep", lay21_hit_edep)
tree.SetBranchAddress("lay22_HitEdep", lay22_hit_edep)
tree.SetBranchAddress("lay23_HitEdep", lay23_hit_edep)
#output
out = TFile("events.root", "recreate")
otree = TTree("event", "event")
ekin = c_float(0)
lay10_edep = c_float(0)
lay11_edep = c_float(0)
lay12_edep = c_float(0)
lay13_edep = c_float(0)
lay20_edep = c_float(0)
lay21_edep = c_float(0)
lay22_edep = c_float(0)
lay23_edep = c_float(0)
otree.Branch("ekin", ekin, "ekin/F") # kinetic energy, MeV
otree.Branch("lay10_edep", lay10_edep, "lay10_edep/F") # deposited energy, MeV
otree.Branch("lay11_edep", lay11_edep, "lay11_edep/F")
otree.Branch("lay12_edep", lay12_edep, "lay12_edep/F")
otree.Branch("lay13_edep", lay13_edep, "lay13_edep/F")
otree.Branch("lay20_edep", lay20_edep, "lay20_edep/F")
otree.Branch("lay21_edep", lay21_edep, "lay21_edep/F")
otree.Branch("lay22_edep", lay22_edep, "lay22_edep/F")
otree.Branch("lay21_edep", lay23_edep, "lay23_edep/F")
#number of events
nev = tree.GetEntries()
#nev = 100000
#event loop
for iev in range(nev):
tree.GetEntry(iev)
if iev%100000 == 0:
print("Event: ", iev)
#deposited energy, MeV
lay10_edep.value = 0.
lay11_edep.value = 0.
lay12_edep.value = 0.
lay13_edep.value = 0.
lay20_edep.value = 0.
lay21_edep.value = 0.
lay22_edep.value = 0.
lay23_edep.value = 0.
#hit loops for layers
nhit = 0
nhit += get_edep_lay(lay10_hit_edep, lay10_edep)
nhit += get_edep_lay(lay11_hit_edep, lay11_edep)
nhit += get_edep_lay(lay12_hit_edep, lay12_edep)
nhit += get_edep_lay(lay13_hit_edep, lay13_edep)
nhit += get_edep_lay(lay20_hit_edep, lay20_edep)
nhit += get_edep_lay(lay21_hit_edep, lay21_edep)
nhit += get_edep_lay(lay22_hit_edep, lay22_edep)
nhit += get_edep_lay(lay23_hit_edep, lay23_edep)
#events with hits
if nhit <= 0:
continue
#generated kinetic energy, MeV
egen = gen_en.at(0)
mass = TDatabasePDG.Instance().GetParticle(gen_pdg.at(0)).Mass()
ekin.value = (egen-mass)*1e3 # MeV
#fill the output tree
otree.Fill()
#finish
otree.Write()
out.Close()
def comp_fit_pars(do_ratio=False, meson='Ds'): #pylint: disable-msg=too-many-statements,too-many-locals
inputdir = '../../AnalysisNonPromptDpp2017/Dplus/outputs/rawyields'
input_files = ['RawYieldsDplus_pp5TeV_prompt_central.root', 'RawYieldsDplus_pp5TeV_FD_central_freesigma.root']
input_files_MC = ['RawYieldsDplusMC_pp5TeV_prompt_central.root', 'RawYieldsDplusMC_pp5TeV_FD_central.root']
colors = [kOrange+7, kAzure+2, kRed+1, kAzure+4]
markers = [kOpenCircle, kOpenSquare, kFullCircle, kFullSquare]
legendnames = ['MC - prompt enhanced', 'MC - FD enhanced', 'data - prompt enhanced', 'data - FD enhanced']
suffix = 'CompMCData'
min_pt = 2.
max_pt = 16.
SetGlobalStyle(padleftmargin=0.18, padtopmargin=0.05, padbottommargin=0.14,
titleoffsety=1.6, titlesize=0.045, labelsize=0.04)
hMean, hSigma = [], []
input_files = input_files_MC + input_files
if meson == 'Ds':
massD = TDatabasePDG.Instance().GetParticle(431).Mass()
elif meson == 'Dplus':
massD = TDatabasePDG.Instance().GetParticle(411).Mass()
lineMass = TLine(min_pt, massD, max_pt, massD)
lineMass.SetLineWidth(2)
lineMass.SetLineColor(kBlack)
lineMass.SetLineStyle(9)
legSigma = TLegend(0.2, 0.78, 0.8, 0.93)
legSigma.SetFillStyle(0)
legSigma.SetBorderSize(0)
legSigma.SetTextSize(0.04)
legMean = TLegend(0.4, 0.73, 0.7, 0.93)
legMean.SetFillStyle(0)
legMean.SetBorderSize(0)
legMean.SetTextSize(0.04)
legMean.AddEntry(lineMass, "PDG", 'l')
for file_path, color, marker, legend_name in zip(input_files, colors, markers, legendnames):
input_file = TFile(f'{inputdir}/{file_path}')
histo_mean = input_file.Get('hRawYieldsMean')
histo_sigma = input_file.Get('hRawYieldsSigma')
histo_mean.SetDirectory(0)
histo_sigma.SetDirectory(0)
SetObjectStyle(histo_mean, linecolor=color, markercolor=color, markerstyle=marker)
SetObjectStyle(histo_sigma, linecolor=color, markercolor=color, markerstyle=marker)
legMean.AddEntry(histo_mean, legend_name, 'p')
legSigma.AddEntry(histo_sigma, legend_name, 'p')
hMean.append(histo_mean)
hSigma.append(histo_sigma)
if do_ratio:
mean_num_list = list(hMean)
mean_num_list.pop(0)
mean_den_hist = hMean[0]
mean_ratio_list = []
for histo in mean_num_list:
mean_ratio_list.append(ComputeRatioDiffBins(histo, mean_den_hist))
cMeanRatio = TCanvas('cMeanRatio', '', 800, 800)
cMeanRatio.DrawFrame(min_pt, 0.99, max_pt, 1.01, ';#it{p}_{T} (GeV/#it{c}); peak mean / peak mean MC')
lineRatio = TLine(min_pt, 1., max_pt, 1.)
lineRatio.SetLineWidth(2)
lineRatio.SetLineColor(kBlack)
lineRatio.SetLineStyle(9)
legMeanRatio = TLegend(0.4, 0.73, 0.7, 0.93)
legMeanRatio.SetFillStyle(0)
legMeanRatio.SetBorderSize(0)
legMeanRatio.SetTextSize(0.04)
for hist, color, marker, legend_name in zip(mean_ratio_list, colors[1:],
markers[1:], legendnames[1:]):
SetObjectStyle(hist, linecolor=color, markercolor=color, markerstyle=marker)
hist.Draw('same')
legMeanRatio.AddEntry(hist, legend_name, 'p')
lineRatio.Draw()
legMeanRatio.Draw()
sigma_num_list = list(hSigma)
sigma_num_list.pop(0)
sigma_den_hist = hSigma[0]
sigma_ratio_list = []
for histo in sigma_num_list:
sigma_ratio_list.append(ComputeRatioDiffBins(histo, sigma_den_hist))
cSigmaRatio = TCanvas('cSigmaRatio', '', 800, 800)
hFrameSigma = cSigmaRatio.DrawFrame(min_pt, 0.6, max_pt, 1.8,
';#it{p}_{T} (GeV/#it{c}); peak width / peak width MC')
hFrameSigma.GetYaxis().SetDecimals()
legSigmaRatio = TLegend(0.4, 0.73, 0.7, 0.93)
legSigmaRatio.SetFillStyle(0)
legSigmaRatio.SetBorderSize(0)
legSigmaRatio.SetTextSize(0.04)
for hist, color, marker, legend_name in zip(sigma_ratio_list, colors[1:],
markers[1:], legendnames[1:]):
SetObjectStyle(hist, linecolor=color, markercolor=color, markerstyle=marker)
hist.Draw('same')
legSigmaRatio.AddEntry(hist, legend_name, 'p')
lineRatio.Draw()
legSigmaRatio.Draw()
cMeanRatio.SaveAs(f'{inputdir}/MeanRatio_{suffix}.pdf')
cSigmaRatio.SaveAs(f'{inputdir}/SigmaRatio_{suffix}.pdf')
cMean = TCanvas('cMean', '', 800, 800)
hFrameMean = cMean.DrawFrame(min_pt, massD*0.995, max_pt, massD*1.01,
';#it{p}_{T} (GeV/#it{c}); peak mean (GeV/#it{c}^{2})')
hFrameMean.GetYaxis().SetDecimals()
lineMass.Draw("same")
for histo_mean in hMean:
histo_mean.Draw('same')
legMean.Draw()
cSigma = TCanvas('cSigma', '', 800, 800)
cSigma.DrawFrame(min_pt, 0., max_pt, 0.025, ';#it{p}_{T} (GeV/#it{c}); peak width (GeV/#it{c}^{2})')
for histo_sigma in hSigma:
histo_sigma.Draw('same')
legSigma.Draw()
cMean.SaveAs(f'{inputdir}/Mean_{suffix}.pdf')
cSigma.SaveAs(f'{inputdir}/Sigma_{suffix}.pdf')
input('Press enter to exit')
def print_evt(event_filter=">= 0"):
pdg_db = TDatabasePDG()
ev_df = df.Filter(f"fIndexMcCollisions {event_filter}")
npy = ev_df.AsNumpy()
print()
lastmother = 0
for i, part_index in enumerate(npy["part_index"]):
ev = npy["fIndexMcCollisions"][i]
count("events", ev)
if 0:
m0 = npy["fMother0"][i]
m1 = npy["fMother1"][i]
d0 = npy["fDaughter0"][i]
d1 = npy["fDaughter1"][i]
else:
m_arr = npy["fIndexArray_Mothers"][i]
d_arr = npy["fIndexSlice_Daughters"][i]
m_size = npy["fIndexArray_Mothers_size"][i]
# print(m_size)
# print("Mothers", m_arr)
# print("Daughters", d_arr)
if len(m_arr) == 0:
m0 = -1
m1 = -1
else:
m0 = m_arr[0]
m1 = m_arr[int(m_size) - 1]
d0 = d_arr[0]
d1 = d_arr[1]
# print(d_arr)
pdg = npy["fPdgCode"][i]
px = npy["fPx"][i]
py = npy["fPy"][i]
pz = npy["fPz"][i]
eta = npy["eta"][i]
is_ps = bool(npy["isPhysicalPrimary"][i])
is_pt = bool(npy["isProducedByTransport"][i])
process = npy["fStatusCode"][i]
def getpname(pdg_code):
p = pdg_db.GetParticle(int(pdg_code))
if p:
p = p.GetName()
else:
p = "Undef"
return p
part = getpname(pdg)
summary_line = f" ({part_index}) ev {ev} m0 {m0} m1 {m1}, d0 {d0} d1 {d1}, pdg {pdg} '{part}', physical primary {is_ps}, in transport {is_pt}, process {process}"
if abs(pdg) not in [21, 2101, 2103, 2203, 1, 2, 3, 4, 5
] and m0 > -1:
if lastmother != m0 and count("mothers", m0):
raise ValueError("Duplicate mothers for ", summary_line)
lastmother = m0
if d1 > -1 and d0 > d1:
if not continue_on_inconsistency:
raise ValueError("d0 > d1:", summary_line)
else:
warning_msg("d0 > d1 for", part_index)
def get_the_daughters():
idaughters = []
if d0 > -1 and d1 > -1:
for j in range(d0, d1 + 1):
entry = numpy.where(npy["part_index"] == j)[0]
if len(entry) > 1:
raise ValueError("Entry size is too high!")
if len(entry) == 0:
raise ValueError("Entry size is too low!")
entry = entry[0]
if 0:
d_m0 = npy["fMother0"][entry]
d_m1 = npy["fMother1"][entry]
else:
d_m0 = npy["fIndexArray_Mothers"][entry][0]
d_m1 = npy["fIndexArray_Mothers"][entry][
int(npy["fIndexArray_Mothers_size"][entry]) -
1]
if d_m0 != part_index and d_m1 != part_index:
if not continue_on_inconsistency:
raise ValueError("Daughter", j,
"has a different mother!",
"d_m0", d_m0, "d_m1", d_m1,
"w.r.t.", part_index)
else:
warning_msg("Daughter", j,
"has a different mother!", "d_m0",
d_m0, "d_m1", d_m1, "w.r.t.",
part_index)
if d_m0 == d_m1 and 0:
raise ValueError("Daughter has same mother!", d_m0,
d_m1)
idaughters.append(entry)
if len(idaughters) == 0:
warning_msg("Found no daughters")
return idaughters
# Checking that indices are increasing
if sorted(idaughters) != idaughters:
raise ValueError("Daughters are not in order!")
# Checking that indices have no holes
if idaughters != [*range(idaughters[0], idaughters[-1] + 1)]:
raise ValueError("Daughters have hole in indices!",
idaughters)
return idaughters
def daughters_pxpypz(daughters):
d_px = 0
d_py = 0
d_pz = 0
if len(daughters) == 0:
return None
for j in daughters:
d_px += npy["fPx"][j]
d_py += npy["fPy"][j]
d_pz += npy["fPz"][j]
return d_px, d_py, d_pz
def daughters_pdg(daughters):
d_pdgs = []
for j in daughters:
d_pdgs.append(npy["fPdgCode"][j])
return d_pdgs
def check_momentum(daughters):
d_p = daughters_pxpypz(daughters)
if d_p is None:
return
m_p = [px, py, pz]
m_p_d = {0: "Px", 1: "Py", 2: "Pz"}
momentum_format = "(px={:.5f}, py={:.5f}, pz={:.5f})"
for j in enumerate(m_p):
if abs(j[1] - d_p[j[0]]) > 0.001:
e_msg = [
"Non-closure in", m_p_d[j[0]], "=",
momentum_format.format(*d_p)
]
if not continue_on_inconsistency:
raise ValueError(*e_msg)
else:
warning_msg(*e_msg)
warning_msg(" mother =",
momentum_format.format(*m_p))
def is_decay_channel(desired_pdg_codes,
daughters,
fill_counter=True,
min_prongs=0,
max_prongs=10):
d_pdgs = daughters_pdg(daughters)
if len(daughters) >= min_prongs and len(
daughters) <= max_prongs:
print(pdg, part, "decaying in", len(d_pdgs), "particles")
for i, j in enumerate(d_pdgs):
if 0:
this_m0 = npy["fMother0"][daughters[i]]
this_m1 = npy["fMother1"][daughters[i]]
else:
this_m0 = npy["fIndexArray_Mothers"][
daughters[i]][0]
this_m1 = npy["fIndexArray_Mothers"][daughters[i]][
int(npy["fIndexArray_Mothers_size"][
daughters[i]]) - 1]
print(" >", j, getpname(j), "index", daughters[i],
npy["part_index"][daughters[i]], "m0", this_m0,
"m1", this_m1, " -> physical primary",
npy["isPhysicalPrimary"][daughters[i]])
if desired_pdg_codes is not None:
for i in desired_pdg_codes:
if i not in d_pdgs:
return False
if fill_counter:
count(
f"{bcolors.BOKGREEN} {pdg} {part} {bcolors.ENDC} in {d_pdgs}",
part_index)
return True
extra = []
if m0 < 0 and m1 < 0 and d0 < 1 and d1 < 0:
extra.append("Sterile")
if d1 < 0 and d1 != d0:
extra.append(bcolors.BWARNING + "Problematic" + bcolors.ENDC)
if pdg in pdg_of_interest:
extra.append(", px={:.3f} py={:.2f} pz={:.2f}".format(
px, py, pz))
extra.append(", eta={:.4f}".format(eta))
extra.append(bcolors.BOKGREEN + "PDG of interest" +
bcolors.ENDC)
extra = " ".join(extra)
extra = extra.strip()
count(part, part_index)
if verbose or pdg in pdg_of_interest:
print(summary_line, extra)
if pdg in pdg_of_interest:
daughters = get_the_daughters()
check_momentum(daughters)
is_decay_channel(None, daughters=daughters, fill_counter=True)
"""
This module contains names for the various PDG particle ID codes.
The names are the same as in EventKernel/PdtPdg.h.
This module also contains a dictionary pdgid_names mapping ID codes
back to printable strings, and a function pdgid_to_name to do this
conversion. Similarly, root_names and pdgid_to_root_name translate to
strings with root markup.
"""
from __future__ import absolute_import
from ROOT import TDatabasePDG
from pkg_resources import resource_filename
import os
db = TDatabasePDG()
db.ReadPDGTable(resource_filename('rootpy', 'etc/pdg_table.txt'))
def GetParticle(id):
return db.GetParticle(id)
# Table to translate from PDG IDs to printable strings.
pdgid_names = {}
# Table to translate from PDG IDs to strings with root markup.
root_names = {}
def id_to_name(id):
ptBinsArr))
SetObjectStyle(hRawYieldsSignalDiffSigma[iS],
color=kBlack,
markerstyle=kFullCircle)
SetObjectStyle(hRawYieldsBkgDiffSigma[iS],
color=kBlack,
markerstyle=kFullCircle)
SetObjectStyle(hRawYieldsSoverBDiffSigma[iS],
color=kBlack,
markerstyle=kFullCircle)
SetObjectStyle(hRawYieldsSignifDiffSigma[iS],
color=kBlack,
markerstyle=kFullCircle)
# fit histos
massDplus = TDatabasePDG.Instance().GetParticle(411).Mass()
massDs = TDatabasePDG.Instance().GetParticle(431).Mass()
massLc = TDatabasePDG.Instance().GetParticle(4122).Mass()
massDstar = TDatabasePDG.Instance().GetParticle(
413).Mass() - TDatabasePDG.Instance().GetParticle(421).Mass()
massD0 = TDatabasePDG.Instance().GetParticle(421).Mass()
if particleName == 'Dplus':
massForFit = massDplus
elif particleName == 'Ds':
massForFit = massDs
elif particleName == 'Dstar':
massForFit = massDstar
elif particleName == 'D0':
massForFit = massD0
else:
class EventGenerator:
EVENT_TIME_DURATION = 50.e3 # ns, 50 us per event
def __init__(self, filename, exclude_noise, save_plot, max_spill_count):
self.filename = filename
self.exclude_noise = exclude_noise
self.save_plot = save_plot
self.data_dir = os.path.dirname(self.filename)
if not self.data_dir:
self.data_dir = '.'
self.file_basename = os.path.basename(self.filename)
self.max_spill_count = max_spill_count
self.pdg = TDatabasePDG()
self.delta_x = 1.4 # mm
self.delta_y = 8.6 # mm
self.delta_z = 0. # mm
# self.delta_x = 1375.9 # mm
# self.delta_y = -67.5 # mm
# self.delta_z = -14617.4 # mm
self.angle_rotation_y_axis = -0.349 * pi / 180. # rad
def rotate_y_axis(self, z, x):
# angle > 0 if the coordinate system rotates counterclockwise
# angle < 0 if the coordinate system rotates clockwise
z_prime = cos(self.angle_rotation_y_axis) * z + sin(
self.angle_rotation_y_axis) * x
x_prime = -sin(self.angle_rotation_y_axis) * z + cos(
self.angle_rotation_y_axis) * x
return z_prime, x_prime
def translate(self, x, y, z):
return x + self.delta_x, y + self.delta_y, z + self.delta_z
def run(self):
particles = []
particle_count = 0
spill_count = 0
f_beam = TFile(self.filename)
spills = [key.GetName() for key in gDirectory.GetListOfKeys()]
for spill in spills:
spill_count += 1
if self.max_spill_count and spill_count > self.max_spill_count:
spill_count -= 1
break
print('spill = {}'.format(spill))
for track in f_beam.Get(spill):
particle_count += 1
pass_all = track.TrackPresenttof_us and \
track.TrackPresentwire_chamber_1_detector and \
track.TrackPresentwire_chamber_2_detector and \
track.TrackPresentwire_chamber_3_detector and \
track.TrackPresentwire_chamber_4_detector and \
track.TrackPresentcherenkov and \
track.TrackPresenttof_ds and \
track.TrackPresentnova
is_noise = not pass_all
if self.exclude_noise and is_noise is True:
continue
pdg_id = int(track.PDGidnova)
x, y, z = self.translate(track.xnova, track.ynova,
track.znova) # mm
# z, x = self.rotate_y_axis(z, x)
t = track.tnova # s
px = track.Pxnova # MeV
py = track.Pynova # MeV
pz = track.Pznova # MeV
# pz, px = self.rotate_y_axis(pz, px)
px /= 1000. # GeV
py /= 1000. # GeV
pz /= 1000. # GeV
x /= 10. # cm
y /= 10. # cm
z /= 10. # cm
t *= 1.e9 # ns
mass = self.pdg.GetParticle(pdg_id).Mass()
energy = (mass**2 + px**2 + py**2 + pz**2)**0.5
particle = [
is_noise, 1, pdg_id, 0, 0, 0, 0, px, py, pz, energy, mass,
x, y, z, t
]
particles.append(particle)
particle_count += 1
if particle_count % 1e6 == 0:
print('particle_count = {}'.format(particle_count))
print('spill_count = {}'.format(spill_count))
f_beam.Close()
particles = sorted(particles, key=lambda p: p[-1])
events = []
event_end_time = 0.
event_start_time = 0.
event_particles = []
for particle in particles:
is_noise = particle[0]
time = particle[-1] # time
if time > event_end_time:
if event_particles:
events.append(event_particles)
event_particles = []
if not is_noise:
particle[-1] = 0.
event_particles = [particle]
event_start_time = time
event_end_time = time + EventGenerator.EVENT_TIME_DURATION # ns
else:
particle[-1] -= event_start_time
event_particles.append(particle)
if event_particles:
events.append(event_particles)
txt_filename = 'text_gen.{}{}.txt'.format(
self.file_basename, '.exclude_noise' if self.exclude_noise else '')
with open('{}/{}'.format(self.data_dir, txt_filename), 'w') as f_txt:
for event in events:
f_txt.write('0 {}\n'.format(len(event)))
for particle in event:
f_txt.write(' '.join(map(str, particle[1:])) + '\n')
if self.save_plot:
self.make_plot(events)
def make_plot(self, events):
f_det = TFile(
'{}/text_gen.{}{}.root'.format(
self.data_dir, self.file_basename,
'.exclude_noise' if self.exclude_noise else ''), 'RECREATE')
multiple_particle_event_count = 0
h_count = TH1D('h_count', 'h_count', 100, -0.5, 99.5)
h_timing = TH1D('h_timing', 'h_timing', 5000, 0., 50.e3) # ns
h_xy = TH2D('h_xy', 'h_xy', 600, -150, 150, 600, -150, 150) # cm
h_z = TH1D('h_z', 'h_z', 500, -1, 1) # cm
for i, event in enumerate(events):
h_count.Fill(len(event))
if len(event) > 1:
multiple_particle_event_count += 1
for particle in event:
h_timing.Fill(particle[-1])
is_noise = particle[0]
if is_noise:
continue
x = particle[-4]
y = particle[-3]
z = particle[-2]
h_xy.Fill(x, y)
h_z.Fill(z)
print('len(events) = {}'.format(len(events)))
print('multiple_particle_event_count = {}'.format(
multiple_particle_event_count))
h_count.Write('h_particle_count_per_event')
h_timing.Write('h_timing')
h_xy.Write('h_xy')
h_z.Write('h_z')
f_det.Close()
parser.add_argument('outFileName', metavar='text', default='outFileName.root',
help='output root file name')
args = parser.parse_args()
#config with input file details
with open(args.cfgFileName, 'r') as ymlCfgFile:
inputCfg = yaml.load(ymlCfgFile, yaml.FullLoader)
inFileNames = inputCfg['filename']
if not isinstance(inFileNames, list):
inFileNames = [inFileNames]
isMC = inputCfg['isMC']
#define mass binning
meson = inputCfg['tree']['meson']
if meson == 'Ds':
mD = TDatabasePDG.Instance().GetParticle(431).Mass()
elif meson == 'Dplus':
mD = TDatabasePDG.Instance().GetParticle(411).Mass()
else:
print('Error: only Dplus and Ds mesons supported. Exit!')
exit()
#selections to be applied
with open(args.cutSetFileName, 'r') as ymlCutSetFile:
cutSetCfg = yaml.load(ymlCutSetFile, yaml.FullLoader)
cutVars = cutSetCfg['cutvars']
selToApply = []
for iPt, _ in enumerate(cutVars['Pt']['min']):
selToApply.append('')
for iVar, varName in enumerate(cutVars):
if varName == 'InvMass':
def print_evt(event_filter=">= 0"):
pdg_db = TDatabasePDG()
ev_df = df.Filter(f"fMcCollisionsID {event_filter}")
npy = ev_df.AsNumpy()
print()
lastmother = 0
for i, part_index in enumerate(npy["part_index"]):
ev = npy["fMcCollisionsID"][i]
count("events", ev)
m0 = npy["fMother0"][i]
m1 = npy["fMother1"][i]
d0 = npy["fDaughter0"][i]
d1 = npy["fDaughter1"][i]
pdg = npy["fPdgCode"][i]
px = npy["fPx"][i]
py = npy["fPy"][i]
pz = npy["fPz"][i]
def getpname(pdg_code):
p = pdg_db.GetParticle(int(pdg_code))
if p:
p = p.GetName()
else:
p = "Undef"
return p
part = getpname(pdg)
summary_line = f" ({part_index}) ev {ev} m0 {m0} m1 {m1}, d0 {d0} d1 {d1}, pdg {pdg} '{part}'"
if abs(pdg) not in [21, 2101, 2103, 2203, 1, 2, 3, 4, 5
] and m0 > -1:
if lastmother != m0 and count("mothers", m0):
raise ValueError("Duplicate mothers for ", summary_line)
lastmother = m0
if d1 > -1 and d0 > d1:
raise ValueError("d0 < d1:", summary_line)
def daughters():
idaughters = []
if d0 > -1 and d1 > -1:
for j in range(d0, d1 + 1):
entry = numpy.where(npy["part_index"] == j)[0]
if len(entry) > 1:
raise ValueError("Entry size is too high!")
if len(entry) == 0:
raise ValueError("Entry size is too low!")
entry = entry[0]
d_m0 = npy["fMother0"][entry]
d_m1 = npy["fMother1"][entry]
if d_m0 != part_index and d_m1 != part_index:
raise ValueError(
"Daughter has a different mother!", d_m0, d_m1,
"w.r.t.", part_index)
if d_m0 == d_m1:
raise ValueError("Daughter has same mother!", d_m0,
d_m1)
idaughters.append(entry)
# Checking that indices are increasing
if sorted(idaughters) != idaughters:
raise ValueError("Daughters are not in order!")
# Checking that indices have no holes
if idaughters != [*range(idaughters[0], idaughters[-1] + 1)]:
raise ValueError("Daughters have hole in indices!",
idaughters)
return idaughters
def daughters_pxpypz():
d_px = 0
d_py = 0
d_pz = 0
d = daughters()
for j in d:
d_px += npy["fPx"][j]
d_py += npy["fPy"][j]
d_pz += npy["fPz"][j]
return d_px, d_py, d_pz
def daughters_pdg():
d = daughters()
d_pdgs = []
for j in d:
d_pdgs.append(npy["fPdgCode"][j])
return d_pdgs
def check_momentum():
d_p = daughters_pxpypz()
m_p = [px, py, pz]
for j in enumerate(m_p):
if (j[1] - d_p[j[0]]) > 0.001:
raise ValueError("Wrong P", j, "with", d_p)
def is_decay_channel(desired_pdg_codes,
fill_counter=True,
min_prongs=0,
max_prongs=10):
d = daughters()
d_pdgs = daughters_pdg()
if len(d) >= min_prongs and len(d) <= max_prongs:
print(pdg, part, "decaying in")
for i, j in enumerate(d_pdgs):
print(" >", j, getpname(j), "index", d[i],
npy["part_index"][d[i]], "m0",
npy["fMother0"][d[i]], "m1",
npy["fMother1"][d[i]])
if desired_pdg_codes is not None:
for i in desired_pdg_codes:
if i not in d_pdgs:
return False
if fill_counter:
count(
f"{bcolors.BOKGREEN} {pdg} {part} {bcolors.ENDC} in {d_pdgs}",
part_index)
return True
extra = []
if m0 < 0 and m1 < 0 and d0 < 1 and d1 < 0:
extra.append("Sterile")
if d1 <= d0 and d1 > -1:
extra.append(bcolors.BWARNING + "Problematic" + bcolors.ENDC)
if pdg in pdg_of_interest:
extra.append(bcolors.BOKGREEN + "PDG of interest" +
bcolors.ENDC)
extra = " ".join(extra)
count(part, part_index)
if verbose or pdg in pdg_of_interest:
print(summary_line, extra)
if pdg in pdg_of_interest:
check_momentum()
is_decay_channel(None, fill_counter=True)
def __init__(self, parse, tree):
#electron and proton energy, GeV
self.Ee = parse.getfloat("main", "Ee")
self.Ep = parse.getfloat("main", "Ep")
print("Ee, GeV =", self.Ee)
print("Ep, GeV =", self.Ep)
#A and Z of the nucleus
self.A = 1
self.Z = 1
if parse.has_option("main", "A"):
self.A = parse.getint("main", "A")
if parse.has_option("main", "Z"):
self.Z = parse.getint("main", "Z")
print("A:", self.A)
print("Z:", self.Z)
#minimal photon energy, GeV
self.emin = parse.getfloat("main", "emin")
print("emin, GeV =", self.emin)
#alpha r_e^2
self.ar2 = 7.297 * 2.818 * 2.818 * 1e-2 # m barn
#electron and nucleus mass
self.me = TDatabasePDG.Instance().GetParticle(11).Mass()
self.mp = TDatabasePDG.Instance().GetParticle(2212).Mass()
self.mn = self.A * self.mp
#nucleus beam vector
nvec = TLorentzVector()
pz_a = TMath.Sqrt(self.Ep**2 - self.mp**2) * self.Z
en_a = TMath.Sqrt(pz_a**2 + self.mn**2)
nvec.SetPxPyPzE(0, 0, pz_a, en_a)
print("Nucleus beam gamma:", nvec.Gamma())
#boost vector of nucleus beam
self.nbvec = nvec.BoostVector()
#electron beam vector
evec = TLorentzVector()
evec.SetPxPyPzE(0, 0, -TMath.Sqrt(self.Ee**2 - self.me**2), self.Ee)
print("Electron beam gamma:", evec.Gamma())
#electron beam energy in nucleus beam rest frame
evec.Boost(-self.nbvec.x(), -self.nbvec.y(), -self.nbvec.z())
self.Ee_n = evec.E()
print("Ee_n, GeV:", self.Ee_n)
#minimal photon energy in nucleus rest frame
eminv = TLorentzVector()
eminv.SetPxPyPzE(0, 0, -self.emin, self.emin)
eminv.Boost(-self.nbvec.x(), -self.nbvec.y(), -self.nbvec.z())
emin_n = eminv.E()
print("emin_n, GeV:", emin_n)
#maximal delta in nucleus frame
dmax_n = 100.
if parse.has_option("main", "dmax_n"):
dmax_n = parse.getfloat("main", "dmax_n")
print("dmax_n:", dmax_n)
#cross section formula
self.eqpar = self.eq(self)
self.dSigDwDt = TF2("dSigDwDt", self.eqpar, emin_n, self.Ee_n, 0,
dmax_n)
self.dSigDwDt.SetNpx(2000)
self.dSigDwDt.SetNpy(2000)
gRandom.SetSeed(5572323)
#total integrated cross section over all delta (to 1e5)
dSigInt = TF2("dSigInt", self.eqpar, emin_n, self.Ee_n, 0, 1e5)
sigma_tot = dSigInt.Integral(emin_n, self.Ee_n, 0, 1e5)
print("Total cross section, mb:", sigma_tot)
#uniform generator for azimuthal angles
self.rand = TRandom3()
self.rand.SetSeed(5572323)
#tree output from the generator
tlist = ["true_phot_w", "true_phot_delta", "true_phot_theta_n"]
tlist += ["true_phot_theta", "true_phot_phi", "true_phot_E"]
tlist += ["true_el_theta", "true_el_phi", "true_el_E"]
self.tree_out = self.set_tree(tree, tlist)
print("Lifshitz_93p16 parametrization initialized")
markerstyle=markersData[cut])
hEffPtIntMC = TH1F('hEffPtIntMC', ';|#Delta#it{M}(KK)| selection; efficiency',
21, 4.5, 25.5)
hEffPtIntData = TH1F('hEffPtIntData',
';|#Delta#it{M}(KK)| selection; efficiency', 21, 4.5,
25.5)
SetObjectStyle(hEffPtIntMC,
color=kRed + 1,
fillstyle=0,
markerstyle=kFullSquare)
SetObjectStyle(hEffPtIntData,
color=kAzure + 4,
fillstyle=0,
markerstyle=kFullCircle)
massPhi = TDatabasePDG.Instance().GetParticle(333).Mass()
massK = TDatabasePDG.Instance().GetParticle(321).Mass()
widthPhi = TDatabasePDG.Instance().GetParticle(333).Width()
for iPt in range(nPtBinsMC):
if iPt < nPtBinsMC - 1:
ptMin = ptLims[iPt]
ptMax = ptLims[iPt + 1]
else:
ptMin = ptLims[0]
ptMax = ptLims[-1]
# get massKK distributions in signal region
massLowLimit = mean[iPt] - args.nSigma * sigma[iPt]
massHighLimit = mean[iPt] + args.nSigma * sigma[iPt]
binLow = hMassKKvsMassKKpiMC[iPt].GetXaxis().FindBin(massLowLimit * 1.0001)
import enum
from ROOT import TDatabasePDG
db = TDatabasePDG()
db.GetParticle(0) # initialize list
all_particles = list(db.ParticleList())
data = {p.GetName(): p.PdgCode() for p in all_particles}
ParticleID = enum.IntEnum('ParticleID', data)
def main():
for pid in ParticleID:
print(
f"{pid.__class__.__name__}({pid.value}) == {pid.__class__.__name__}['{pid.name}']"
)
if __name__ == "__main__":
main()
def __init__(self, parse, tree, hepmc_attrib):
print("Quasi-real configuration:")
#electron and proton beam energy, GeV
self.Ee = parse.getfloat("main", "Ee")
self.Ep = parse.getfloat("main", "Ep")
print("Ee =", self.Ee, "GeV")
print("Ep =", self.Ep, "GeV")
#electron and proton mass
self.me = TDatabasePDG.Instance().GetParticle(11).Mass()
mp = TDatabasePDG.Instance().GetParticle(2212).Mass()
#boost vector pbvec of proton beam
pbeam = TLorentzVector()
pbeam.SetPxPyPzE(0, 0, TMath.Sqrt(self.Ep**2-mp**2), self.Ep)
self.pbvec = pbeam.BoostVector()
#electron beam energy Ee_p in proton beam rest frame
ebeam = TLorentzVector()
ebeam.SetPxPyPzE(0, 0, -TMath.Sqrt(self.Ee**2-self.me**2), self.Ee)
ebeam.Boost(-self.pbvec.x(), -self.pbvec.y(), -self.pbvec.z()) # transform to proton beam frame
self.Ee_p = ebeam.E()
#center-of-mass squared s, GeV^2
self.s = self.get_s(self.Ee, self.Ep)
print("s =", self.s, "GeV^2")
print("sqrt(s) =", TMath.Sqrt(self.s), "GeV")
#range in x
xmin = parse.getfloat("main", "xmin")
xmax = parse.getfloat("main", "xmax")
print("xmin =", xmin)
print("xmax =", xmax)
#range in u = log_10(x)
umin = TMath.Log10(xmin)
umax = TMath.Log10(xmax)
print("umin =", umin)
print("umax =", umax)
#range in y
ymin = parse.getfloat("main", "ymin")
ymax = parse.getfloat("main", "ymax")
#range in W
wmin = -1.
wmax = -1.
if parse.has_option("main", "Wmin"):
wmin = parse.getfloat("main", "Wmin")
print("Wmin =", wmin)
if parse.has_option("main", "Wmax"):
wmax = parse.getfloat("main", "Wmax")
print("Wmax =", wmax)
#adjust range in y according to W
if wmin > 0 and ymin < wmin**2/self.s:
ymin = wmin**2/self.s
if wmax > 0 and ymax > wmax**2/self.s:
ymax = wmax**2/self.s
print("ymin =", ymin)
print("ymax =", ymax)
#range in v = log_10(y)
vmin = TMath.Log10(ymin)
vmax = TMath.Log10(ymax)
print("vmin =", vmin)
print("vmax =", vmax)
#range in Q2
self.Q2min = parse.getfloat("main", "Q2min")
self.Q2max = parse.getfloat("main", "Q2max")
print("Q2min =", self.Q2min)
print("Q2max =", self.Q2max)
#constant term in the cross section
self.const = TMath.Log(10)*TMath.Log(10)*(1./137)/(2.*math.pi)
#cross section formula for d^2 sigma / dxdy, Eq. II.6
#transformed as x -> u = log_10(x) and y -> v = log_10(y)
self.eq_II6_uv_par = self.eq_II6_uv(self)
self.eq = TF2("d2SigDuDvII6", self.eq_II6_uv_par, umin, umax, vmin, vmax)
self.eq.SetNpx(1000)
self.eq.SetNpy(1000)
#uniform generator for azimuthal angles
self.rand = TRandom3()
self.rand.SetSeed(5572323)
#generator event variables in output tree
tnam = ["gen_u", "gen_v", "true_x", "true_y", "true_Q2", "true_W2"]
tnam += ["true_el_Q2"]
tnam += ["true_el_pT", "true_el_theta", "true_el_phi", "true_el_E"]
#create the tree variables
tcmd = "struct gen_out { Double_t "
for i in tnam:
tcmd += i + ", "
tcmd = tcmd[:-2] + ";};"
gROOT.ProcessLine( tcmd )
self.out = rt.gen_out()
#put zero to all variables
for i in tnam:
exec("self.out."+i+"=0")
#set the variables in the tree
if tree is not None:
for i in tnam:
tree.Branch(i, addressof(self.out, i), i+"/D")
#event attributes for hepmc
self.hepmc_attrib = hepmc_attrib
#counters for all generated and selected events
self.nall = 0
self.nsel = 0
#print generator statistics at the end
atexit.register(self.show_stat)
#total integrated cross section
self.sigma_tot = self.eq.Integral(umin, umax, vmin, vmax)
print("Total integrated cross section for a given x and y range:", self.sigma_tot, "mb")
print("Quasi-real photoproduction initialized")
markerstyle=kFullSquare)
SetObjectStyle(hRawYieldsSigmaRatioSecondFirstPeak,
color=kRed,
markerstyle=kFullSquare)
SetObjectStyle(hRawYieldsSoverBSecPeak, color=kRed, markerstyle=kFullSquare)
SetObjectStyle(hRawYieldsSignalSecPeak, color=kRed, markerstyle=kFullSquare)
SetObjectStyle(hRawYieldsBkgSecPeak, color=kRed, markerstyle=kFullSquare)
SetObjectStyle(hRawYieldsTrue, color=kRed, markerstyle=kFullSquare)
SetObjectStyle(hRawYieldsSecPeakTrue, color=kRed, markerstyle=kFullSquare)
SetObjectStyle(hRelDiffRawYieldsFitTrue, color=kRed, markerstyle=kFullSquare)
SetObjectStyle(hRelDiffRawYieldsSecPeakFitTrue,
color=kRed,
markerstyle=kFullSquare)
# fit histos
massDplus = TDatabasePDG.Instance().GetParticle(411).Mass()
massDs = TDatabasePDG.Instance().GetParticle(431).Mass()
massForFit = massDplus if fitConfig[cent]['Meson'] == 'Dplus' else massDs
cMass = TCanvas("cMass", "cMass", 1920, 1080)
DivideCanvas(cMass, nPtBins)
cResiduals = TCanvas("cResiduals", "cResiduals", 1920, 1080)
DivideCanvas(cResiduals, nPtBins)
massFitter = []
for iPt, (hM, ptMin, ptMax, reb, sgn, bkg, secPeak, massMin, massMax) in enumerate(zip(
hMass, ptMins, ptMaxs, fitConfig[cent]['Rebin'], SgnFunc, BkgFunc, \
inclSecPeak, fitConfig[cent]['MassMin'], fitConfig[cent]['MassMax'])):
hMassForFit.append(TH1F())
AliVertexingHFUtils.RebinHisto(hM, reb).Copy(
1 2 3 4 5 6 7 8 9 10 11 12 13 14
ID - type Part ID - - px py pz - - vx vy vz
1=active
"""
# all the not useful fields will be filled with 99
from ROOT import TGenPhaseSpace, TLorentzVector, TDatabasePDG, TMath, TVector3
import math
from random import random as rndm
from array import array
from random import gauss
dbpdg = TDatabasePDG()
# chose motherParticle
PDGmother = 3122
MotherMass = dbpdg.GetParticle(PDGmother).Mass()
# chose daughters
PDGs = [2212, -211]
DaughterMass = [dbpdg.GetParticle(i).Mass() for i in PDGs]
# Settings
# ========
NEVENTS = 50000
BeamPolarization = -1 # not useful
from ROOT import TLorentzVector, TDatabasePDG, TH1F, TH2F, TCanvas, TVector3
from math import *
import sys
with open(sys.argv[-1]) as fin:
content = fin.readlines()
pdg = TDatabasePDG()
h0 = TH1F("m0", "", 200, 0, 3)
h1 = TH1F("m", "", 200, 0, 3)
h2t = TH2F("theta", "", 180, 0, 180, 90, 0, 180)
h2p = TH2F("phi", "", 180, -180, 180, 180, -180, 180)
i = 0
while i < len(content):
line = content[i].strip().split()
if len(line) == 10:
g0line = content[i + 1].strip().split()
g1line = content[i + 2].strip().split()
g2line = content[i + 3].strip().split()
g0d = [float(a) for a in g0line[6:9]]
g1d = [float(a) for a in g1line[6:9]]
g2d = [float(a) for a in g2line[6:9]]
m0 = pdg.GetParticle(int(g0line[3])).Mass()
m1 = pdg.GetParticle(int(g1line[3])).Mass()
m2 = pdg.GetParticle(int(g2line[3])).Mass()
