def make_graph(a, output):
c1 = TCanvas("c1", "c1", 1000,
1000) # Creates the canvas to draw the bar chart to.
c1.SetGrid() # Adds grid lines to canvas.
leg = TLegend(0.7, 0.6, 0.95, 0.95)
leg.AddEntry(a, "Start", "P")
n0 = TNtuple("n0", "n0",
"x:y:z") # creates ntuple to store the values of x y z
n0.SetMarkerColor(0)
n0.Fill(-4500, -4500, -5700)
n0.Fill(4500, 4500, 5700)
n0.Draw("x:y:z")
#a.SetMarkerColor(1)
#a.SetMarkerStyle(6)
#a.Draw("x:y:z","","same") # Draws the histogram to the canvas.
a.SetMarkerColor(2)
a.SetMarkerStyle(6)
a.Draw("x2:y2:z2", "", "same") # Draws the histogram to the canvas.
#leg.Draw()
c1.Update() # Makes the canvas show the histogram.
img = ROOT.TImage.Create() # creates image
img.FromPad(c1) # takes it from canvas
img.WriteImage(
output) # Saves it to png file with this name in input file directory.
return c1
def get_pos(event): # start position of each particle
a = TNtuple(
"a", "a",
"x:y:z:x2:y2:z2") # creates ntuple to store the values of x y z
mcpart = event.getCollection("MCParticle")
for ding in mcpart:
ptype = ding.getPDG()
if ptype != 11 and ptype != -11:
pos = ding.getVertex()
end = ding.getEndpoint()
x = pos[0]
y = pos[1]
z = pos[2]
x2 = end[0]
y2 = end[1]
z2 = end[2]
print x, "\t", y, "\t", z
a.Fill(x, y, z, x2, y2, z2)
return a
def make_graph(n, output):
c1 = TCanvas() # Creates the canvas to draw the bar chart to.
c1.SetGrid() # Adds grid lines to canvas.
n0 = TNtuple("n0", "n0", "x:y:z")
n0.Fill(-0.1, -0.1, -1)
n0.Fill(0.1, 0.1, 1)
n0.Draw("x:y:z")
n.SetMarkerColor(2)
n.SetMarkerStyle(6)
n.Draw("x:y:z","","same") # Draws the histogram to the canvas.
c1.Update() # Makes the canvas show the histogram.
img = ROOT.TImage.Create() # creates image
img.FromPad(c1) # takes it from canvas
img.WriteImage(output) # Saves it to png file with this name in input file directory.
return c1
def make_ntup(file_name, tree_name, branches, outfile, n_events,
new_tree_name):
if new_tree_name == "":
new_tree_name = tree_name
print file_name
# Get the event tree
tree = TChain(tree_name)
tree.Add(file_name)
if not tree:
print "Error: No tree named %s in %s" % (tree_name, file_name)
sys.exit()
# Check branches exist
branches_avail = [x.GetName() for x in tree.GetListOfBranches()]
for b in branches:
if not b in branches_avail:
print "Error branch '%s' not a branch in input tree" % (b)
print "Branches available are: \n"
print "\t".join(branches_avail)
sys.exit()
# output
out_file = TFile(outfile, "RECREATE")
nt = TNtuple(new_tree_name, "", ":".join(branches))
if (n_events < 0):
n_events = tree.GetEntries()
# loop over events and fill the branches of new ntuple
for index, entry in enumerate(tree):
if index > n_events:
break
vals = array('f', [entry.__getattr__(b) for b in branches])
nt.Fill(vals)
if (index % 100000 == 0):
print index, "/", n_events
# Save
out_file.cd()
nt.Write()
out_file.Close()
print "Written %i entries of branch(es) '%s' \nto tree %s \nin file %s" % (
n_events, ":".join(branches), new_tree_name, outfile)
def FillNTuple(tupname, data, names) :
"""
Create and fill ROOT NTuple with the data sample.
tupname : name of the NTuple
data : data sample
names : names of the NTuple variables
"""
variables = ""
for n in names : variables += "%s:" % n
variables = variables[:-1]
values = len(names)*[ 0. ]
avalues = array.array('f', values)
nt = TNtuple(tupname, "", variables)
for d in data :
for i in range(len(names)) : avalues[i] = d[i]
nt.Fill(avalues)
nt.Write()
def get_mom(event): # Each detector is a 'collection', the No. of Elements are the hits.
k=0
n = TNtuple("n", "n", "x:y:z") # creates ntuple to store the values of x y z
mcpart = event.getCollection("MCParticle") # opens the collection
nbin = mcpart.getNumberOfElements() # gets the number of hits on the beamcal
for ding in mcpart: # for each hit in the beamcal
pos = ding.getMomentum() # gets position in 3 vector array
ptype = ding.getPDG()
if ptype != 11 and ptype != -11:
x = pos[0] # sets value from 3 vector array to single variables
y = pos[1]
z = pos[2]
k+=1
n.Fill(x,y,z) # fills the ntuple
print k
return n
def get_pos(
event
): # Each detector is a 'collection', the No. of Elements are the hits.
xcoord1 = [] # a list for each x coordinate
ycoord1 = []
zcoord1 = []
n = TNtuple("n", "n",
"x:y:z") # creates ntuple to store the values of x y z
BCAL = event.getCollection("BeamCalHits") # opens the collection
nbin = BCAL.getNumberOfElements() # gets the number of hits on the beamcal
for ding in BCAL: # for each hit in the beamcal
pos = ding.getPosition() # gets position in 3 vector array
x = pos[0] # sets value from 3 vector array to single variables
y = pos[1]
z = pos[2]
n.Fill(x, y, z) # fills the ntuple
return n
def get_pos(
event
): # Each detector is a 'collection', the No. of Elements are the hits.
xcoord1 = []
ycoord1 = []
zcoord1 = []
nparts = 0 # counter for number of interesting particles
n = TNtuple("n", "n", "x:y:z") # makes the ntuple to be filled
mcpart = event.getCollection("MCParticle")
for ding in mcpart:
if ding.getPDG() != 11 and ding.getPDG() != -11: # id not e+ or e-
pos = ding.getVertex() # gets the start position as 3 vector array
x = pos[0] # assigns value from array to single variables
y = pos[1]
z = pos[2]
n.Fill(x, y, z) # fills the ntuple
nparts += 1 # counts up for each particle
print nparts
return n
cmd=['lumiCalc.py -n 0.0429 -c frontier://LumiProd/CMS_LUMI_PROD -r ',' -o ','.csvt lumibyls']
a={}
with open(jsonfile) as f:
a = json.load(f)
f.close()
if not os.path.isdir(wdir):
os.system('mkdir '+wdir)
f = TFile(wdir+'/lumis.root','recreate')
ntuple = TNtuple('ntuple','data from ascii file','run:ls:lumiDelivered:lumiReported')
for run, lumis in a.iteritems():
fullcmd=cmd[0]+run+cmd[1]+wdir+'/'+run+cmd[2]
print 'Get luminosity information for run '+run
os.system(fullcmd)
rf=open(wdir+'/'+run+'.csvt','r')
crf=csv.reader(rf)
crf.next()
for row in crf:
ntuple.Fill(int(row[0]),int(row[1]),float(row[2]),float(row[3]))
rf.close()
os.system('rm '+wdir+'/'+run+'.csvt')
f.Write()
f.Close()
print 'Luminosity tree written to working directory ./'+wdir
os.system('cp '+jsonfile+' '+wdir+'/'+jsonfile)
sys.exit()
#!/usr/bin/env python
# Example taken from https://root.cern.ch/how/how-write-ttree-python
# and modified to run...
"""
Creates a simple ROOT file with a tree containing a branch with a large array.
"""
from ROOT import TFile, TNtuple
from array import array
f = TFile('TNtuple.root', 'recreate')
t = TNtuple('n1', 'ntuple with 3 columes', "x:y:z")
x = array('i', [0])
y = array('f', [0])
z = array('d', [0])
for i in range(100):
x[0] = i
y[0] = i + i / 13
z[0] = i + i / 17
t.Fill(x[0], y[0], z[0])
f.Write()
f.Close()
class SimpleJetNTupler(Analyzer):
'''dump very few quantities into a TNtuple for jet resolution studies.'''
### def __init__(self,cfg_ana, cfg_comp, looperName):
### loadLibs()
### super (SimpleJetNTupler, self).__init__(cfg_ana, cfg_comp, looperName)
def declareHandles(self):
super(SimpleJetNTupler, self).declareHandles()
self.handles['jets'] = AutoHandle(*self.cfg_ana.jetCollection)
if self.cfg_ana.useGenLeptons:
self.mchandles['genParticlesPruned'] = AutoHandle(
'genParticlesPruned', 'std::vector<reco::GenParticle>')
else:
self.mchandles['genParticles'] = AutoHandle(
'prunedGen', 'std::vector<reco::GenParticle>')
self.mchandles['genJets'] = AutoHandle(*self.cfg_ana.genJetsCollection)
self.handles['vertices'] = AutoHandle('offlinePrimaryVertices',
'std::vector<reco::Vertex>')
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def beginLoop(self):
super(SimpleJetNTupler, self).beginLoop()
self.file = TFile('/'.join([self.looperName, 'testJetsNT.root']),
'recreate')
if self.cfg_ana.applyPFLooseId:
from ROOT import PFJetIDSelectionFunctor
self.isPFLooseFunc = PFJetIDSelectionFunctor(
0, PFJetIDSelectionFunctor.LOOSE)
## Workaround: for some reason PyROOT does not bind nor PFJetIDSelectionFunctor(Jet)PFJetIDSelectionFunctor.getBitsTemplates
from ROOT import pat
self.isPFLooseFunc.bits = pat.strbitset()
for i in "CHF", "NHF", "CEF", "NEF", "NCH", "nConstituents":
self.isPFLooseFunc.bits.push_back(i)
## /Workaround
self.isPFLoose = lambda x: self.isPFLooseFunc(
x, self.isPFLooseFunc.bits)
else:
self.isPFLoose = lambda x: True
self.myntuple = TNtuple(
self.cfg_ana.ntupleName, self.cfg_ana.ntupleName,
'genPt:recoPt:genEta:recoEta:genPhi:recoPhi:nvtx')
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def process(self, iEvent, event):
#read all the handles defined beforehand
self.readCollections(iEvent)
jetEtaCut = 4.5
# get the vertexes
event.vertices = self.handles['vertices'].product()
# self.h_nvtx.Fill (len (event.vertices))
# get the jets in the jets variable
jets = self.handles['jets'].product()
# filter jets with some selections
event.jets = [
jet for jet in jets
if (abs(jet.eta()) < jetEtaCut and jet.pt() > self.cfg_ana.ptCut
and self.isPFLoose(jet))
]
# get status 2 leptons
if 'genParticlesPruned' in self.mchandles:
event.genLeptons = [
lep for lep in self.mchandles['genParticlesPruned'].product()
if lep.status() == 2 and (abs(lep.pdgId()) == 11 or abs(
lep.pdgId()) == 13 or abs(lep.pdgId()) == 15)
]
else:
event.genLeptons = [
lep for lep in self.mchandles['genParticles'].product()
if lep.status() == 3 and (abs(lep.pdgId()) == 11 or abs(
lep.pdgId()) == 13 or abs(lep.pdgId()) == 15)
]
# @ Pasquale: why level 3 and not level 2?
# event.selGenLeptons = [GenParticle (lep) for lep in event.genLeptons if (lep.pt ()>self.cfg_ana.ptCut and abs (lep.eta ()) < jetEtaCut)]
# get genJets
event.genJets = map(GenJet, self.mchandles['genJets'].product())
# filter genjets as for reco jets
event.selGenJets = [
GenJet(jet) for jet in event.genJets
if (jet.pt() > self.cfg_ana.genPtCut)
]
#FIXME why are there cases in which there's 4 or 6 leptons?
if len(event.genLeptons) != 2:
return
# in case I want to filter out taus
# 11, 13, 15 : e, u, T
# event.genOneLepton = [GenParticle (part) for part in event.genLeptons if abs (part.pdgId ()) == 15]
# remove leptons from jets if closer than 0.2
event.cleanJets = cleanObjectCollection(event.jets, event.genLeptons,
0.2)
event.matchingCleanJets = matchObjectCollection2(
event.cleanJets, event.selGenJets, 0.25)
# assign to each jet its gen match (easy life :))
for jet in event.cleanJets:
jet.gen = event.matchingCleanJets[jet]
event.matchedCleanJets = [
jet for jet in event.matchingCleanJets if jet.gen != None
]
for jet in event.matchedCleanJets:
self.myntuple.Fill(jet.gen.pt(), jet.pt(), jet.gen.eta(),
jet.eta(), jet.gen.phi(), jet.phi(),
len(event.vertices))
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def write(self):
from ROOT import gROOT
gROOT.SetBatch(True)
self.file.cd()
self.myntuple.Write()
self.file.Close()
def make_graph(a, b, c, d, e, f, g, h, i, j, k, l, output):
c1 = TCanvas("c1", "c1", 800,
800) # Creates the canvas to draw the bar chart to.
c1.SetGrid() # Adds grid lines to canvas.
leg = TLegend(0.7, 0.6, 0.95, 0.95)
leg.AddEntry(a, "EcalBarrelHits", "P")
leg.AddEntry(b, "EcalEndcapHits", "P")
leg.AddEntry(c, "HcalBarrelHits", "P")
leg.AddEntry(d, "HcalEndcapHits", "P")
leg.AddEntry(e, "LumiCalHits", "P")
leg.AddEntry(f, "MuonBarrelHits", "P")
leg.AddEntry(g, "MuonEndcapHits", "P")
leg.AddEntry(h, "SiTrackerBarrelHits", "P")
leg.AddEntry(i, "SiTrackerEndcapHits", "P")
leg.AddEntry(j, "SiTrackerForwardHits", "P")
leg.AddEntry(k, "SiVertexBarrelHits", "P")
leg.AddEntry(l, "SiVertexEndcapHits", "P")
n0 = TNtuple("n0", "n0",
"x:y:z") # creates ntuple to store the values of x y z
n0.SetMarkerColor(0)
n0.Fill(-4500, -4500, -5700)
n0.Fill(4500, 4500, 5700)
n0.Draw("x:y:z")
a.SetMarkerColor(1)
a.SetMarkerStyle(6)
a.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
b.SetMarkerColor(2)
b.SetMarkerStyle(6)
b.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
c.SetMarkerColor(3)
c.SetMarkerStyle(6)
c.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
d.SetMarkerColor(4)
d.SetMarkerStyle(6)
d.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
e.SetMarkerColor(5)
e.SetMarkerStyle(6)
e.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
f.SetMarkerColor(6)
f.SetMarkerStyle(6)
f.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
g.SetMarkerColor(7)
g.SetMarkerStyle(6)
g.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
h.SetMarkerColor(8)
h.SetMarkerStyle(6)
h.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
i.SetMarkerColor(9)
i.SetMarkerStyle(6)
i.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
j.SetMarkerColor(30)
j.SetMarkerStyle(6)
j.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
k.SetMarkerColor(40)
k.SetMarkerStyle(6)
k.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
l.SetMarkerColor(28)
l.SetMarkerStyle(6)
l.Draw("x:y:z", "", "same") # Draws the histogram to the canvas.
leg.Draw()
c1.Update() # Makes the canvas show the histogram.
img = ROOT.TImage.Create() # creates image
img.FromPad(c1) # takes it from canvas
img.WriteImage(
output) # Saves it to png file with this name in input file directory.
return c1
def main(argv=None):
start = time.time()
# ROOT batch mode
ROOT.gROOT.SetBatch(1)
'''
# ============================================================
# ArgumentParser
# ============================================================
parser = argparse.ArgumentParser(description='Cosmic Tracks')
parser.add_argument("config_file")
parser.add_argument("data_file", nargs="+")
parser.add_argument("-o", "--out_path")
parser.add_argument("-i", "--uid", type=int, default=0, help="Unique identifier used in output files.")
parser.add_argument("-n", "--max_evts", type=int, default=0, metavar="N", help="Stop after %(metavar)s events.")
parser.add_argument("-n", type=int, default=0, metavar="N", help="Stop after %(metavar)s spills.")
parser.add_argument("-s", "--seed", type=int, help="Set the RNG seed.")
parser.add_argument("-m", "--measure", action="store_true", help="Measure rho, phi and doca for each gamma and fill into histogram.")
parser.add_argument("-a", "--analyse", action="store_true", help="Run analysis.")
parser.add_argument("-d", "--display", action="store_true", help="Save event display CSVs.")
parser.add_argument("-D", "--debug", action="store_true", help="Only one event per spill, fixed vertex position.")
args = parser.parse_args(argv)
'''
# ============================================================
# Set paths
# ============================================================
datapath = '/data/SingleModule_Nov2020/LArPix/dataRuns/rootTrees/combined_with_light'
print(' datapath: ', datapath)
outputpath = '/home/lhep/PACMAN/larpix-analysis/lightCharge_anticorrelation'
print(' outputpath: ', outputpath)
files = sorted(
[os.path.basename(path) for path in glob.glob(datapath + '/*.root')])
print(' datafiles: ')
for f in files:
print(' ', f)
# ============================================================
# Define voxelisation
# ============================================================
n_voxels_x = 70
n_voxels_y = 70
n_voxels_z = 70
pitch_x = 4.434
pitch_y = 4.434
pitch_z = 4.434
x_min = -pitch_x * n_voxels_x / 2. #155.19
x_max = pitch_x * n_voxels_x / 2. #155.19
y_min = -pitch_y * n_voxels_y / 2. #155.19
y_max = pitch_y * n_voxels_y / 2. #155.19
#z_min = - pitch_z * n_voxels_z/2. #155.19
#z_max = pitch_z * n_voxels_z/2. #155.19
#y_min = -155.19
#y_max = 155.19
z_min = 0
z_max = 400
# ============================================================
# Input tree
# ============================================================
#inputFileName = (str(args.data_file)[34:])[:-7] # excludes ending .root
for file_number in range(len(files)):
# Only process specific file(s)
#if files[file_number] != 'datalog_2020_11_29_12_22_02_CET_evd.h5':
# continue
#if not (file_number >= 0 and file_number < 10):
# continue
inputFileName = files[file_number]
print(' -------------------------------------- ')
print(' Processing file', inputFileName)
outFileName = inputFileName[:-7] + '.root'
input_tree = ROOT.TChain("t_out", "t_out")
#for root_file in config["data_files"]:
# input_tree.Add(root_file)
#input_tree.Add( "/path/to.root" )
input_tree.Add(datapath + '/' + inputFileName)
#not_used_files = [13,32,50,61,66,77,81,86,89,92,94,97,99]
#print " Do not use files with numbers in {:} " .format(not_used_files)
# Define if plots are made or not
make_plots = True
if make_plots:
plot_folder = inputFileName[16:-5]
os.system('rm -rf plots/' + str(plot_folder))
os.system('mkdir plots/' + str(plot_folder))
# Turn on all branches
input_tree.SetBranchStatus("*", 1)
# Define Histograms / NTuples
# ---------------------------------------------------------
makePlots = True
h1_trLength = TH1F('h1_trLength', ' ; Track length [mm] ; Entries [-]',
150, 0, 500)
h2_trLength_vs_nHits = TH2F(
'h2_trLength_vs_nHits',
' ; Track Length [mm] ; Number of Hits [-] ; Entries [-]', 100, 0, 500,
100, 0, 500)
h3_event_hits = TH3F('h3_event_hits', ' ; x ; y; z', 70, -155, 155, 70,
-155, 155, 100, -300, 3000)
ntuple = TNtuple('ntuple', 'data from ascii file', 'x:y:z:cont')
plot4d = TH3F('h3_ev_hits', ' ; x ; y; z', 70, -155.19, 155.19, 70,
-155.19, 155.19, 200, -500, 1500)
# Make track selection
# ---------------------------------------------------------
# TODO: Make 3D histogram to test selection goodness
# Event with only 1 track (right?)
# Analyse input tree
# ---------------------------------------------------------
n_tracks = input_tree.GetEntries()
print(' n_tracks: ', n_tracks)
x_min = 100
x_max = -100
y_min = 100
y_max = -100
z_min = 100
z_max = -100
# Loop over all tracks in input_tree
for track_id in range(n_tracks):
input_tree.GetEntry(track_id)
print(' Processing track', track_id, 'of', n_tracks, '...')
if track_id > 5:
break
#print(' t_eventID: ', input_tree.t_eventID)
#print(' t_trackID: ', input_tree.t_trackID)
#print(' t_event_q: ', input_tree.t_event_q)
#print(' t_track_q: ', input_tree.t_track_q)
#print(' t_event_nhits: ', input_tree.t_event_nhits)
#print(' t_track_nhits: ', input_tree.t_track_nhits)
h1_trLength.Fill(input_tree.t_track_length)
h2_trLength_vs_nHits.Fill(input_tree.t_track_length,
input_tree.t_track_nhits)
# Get all hits in the event
voxels = np.zeros((n_voxels_x, n_voxels_y, n_voxels_z))
for hit in range(10): #input_tree.t_event_nhits):
if input_tree.t_event_hits_x[hit] < x_min:
x_min = input_tree.t_event_hits_x[hit]
if input_tree.t_event_hits_x[hit] > x_max:
x_max = input_tree.t_event_hits_x[hit]
if input_tree.t_event_hits_y[hit] < y_min:
y_min = input_tree.t_event_hits_y[hit]
if input_tree.t_event_hits_y[hit] > y_max:
y_max = input_tree.t_event_hits_y[hit]
if input_tree.t_event_hits_z[hit] < z_min:
z_min = input_tree.t_event_hits_z[hit]
if input_tree.t_event_hits_z[hit] > z_max:
z_max = input_tree.t_event_hits_z[hit]
#print(' hit: ', hit, ' \t x: ', input_tree.t_event_hits_x[hit], '\t y: ', input_tree.t_event_hits_y[hit], ' \t z: ', input_tree.t_event_hits_z[hit])
voxel_x = math.floor((input_tree.t_event_hits_x[hit] +
(pitch_x * (n_voxels_x) / 2.)) / pitch_x)
voxel_y = math.floor((input_tree.t_event_hits_y[hit] +
(pitch_y * (n_voxels_y) / 2.)) / pitch_y)
voxel_z = math.floor((input_tree.t_event_hits_z[hit] +
(pitch_z * (n_voxels_z) / 2.)) / pitch_z)
#print(' voxel_x: ', voxel_x, ' \t voxel_y: ', voxel_y, ' \t voxel_z: ', voxel_z)
if voxel_x < n_voxels_x and voxel_y < n_voxels_y and voxel_z < n_voxels_z:
voxels[voxel_x][voxel_y][voxel_z] += input_tree.t_event_hits_q[
hit]
# TODO: make under- and overflow voxel for every coordinate
h3_event_hits.Fill(input_tree.t_event_hits_x[hit],
input_tree.t_event_hits_y[hit],
input_tree.t_event_hits_z[hit],
input_tree.t_event_hits_q[hit])
for vox_x in range(n_voxels_x):
vox_x_middle = x_min + (vox_x + 0.5) * pitch_x
for vox_y in range(n_voxels_y):
vox_y_middle = y_min + (vox_y + 0.5) * pitch_y
for vox_z in range(n_voxels_z):
vox_z_middle = z_min + (vox_z + 0.5) * pitch_z
if voxels[vox_x][vox_y][vox_z] > 0:
ntuple.Fill(vox_x_middle, vox_y_middle, vox_z_middle,
voxels[vox_x][vox_y][vox_z])
#h3_event_hits.Fill(vox_x_middle,vox_y_middle,vox_z_middle,voxels[vox_x][vox_y][vox_z])
if (track_id % 2 == 0):
now = time.time()
print(' Processed', math.floor(track_id * 100 / n_tracks), 'of',
n_tracks, 'tracks. \t Elapsed time:', (now - start),
' seconds ... \r')
print(' x_min: ', x_min)
print(' x_max: ', x_max)
print(' y_min: ', y_min)
print(' y_max: ', y_max)
print(' z_min: ', z_min)
print(' z_max: ', z_max)
c0 = ROOT.TCanvas()
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetOptTitle(0)
ntuple.Draw('x:y:z:cont>>plot4d', '', 'COLZ')
#plot4d.SetLabelSize(0.5)
#plot4d.SetMarkerSize(300)
#ntuple.SetMarkerSize(300)
#ntuple.SetMarkerColor(2)
#ntuple.SetFillColor(38)
#h3_event_hits.Draw("COLZ")
c0.Print('test.png')
# Make plots
# ---------------------------------------------------------
if makePlots:
plot_h1_trLength(h1_trLength, 'h1_trLength', plot_folder)
plot_h2_trLength_vs_nHits(h2_trLength_vs_nHits, 'h2_trLength_vs_nHits',
plot_folder)
plot_h3_event_hits(h3_event_hits, 'h3_event_hits', plot_folder)
def selectEvents(fileName,saveProbes=False,saveSummary=False,outputDir='./',xsec=-1,correctionsMap={}):
gSystem.ExpandPathName(fileName)
file=TFile.Open(fileName)
#exclusivity of triggers per PD
eTriggersOnly = ('SingleEle' in fileName)
muTriggersOnly = ('SingleMu' in fileName)
#normalizations and corrections
origEvents=1.0
puWeightsGr=None
if xsec>0 :
origEvents=file.Get('smDataAnalyzer/cutflow').GetBinContent(1)
if origEvents==0 :
print '[Warning] 0 initial events ?'
#derive pileup weights
origPileup=file.Get('smDataAnalyzer/pileup')
try:
dataPileupFile=TFile.Open(correctionsMap['pu'])
dataPileup=dataPileupFile.Get('pileup')
normF=origPileup.Integral()/dataPileup.Integral()
if normF>0 :
puWeightsGr=TGraph()
for xbin in xrange(1,origPileup.GetXaxis().GetNbins()+1) :
iweight=1.0
if origPileup.GetBinContent(xbin)>0 :
iweight=normF*dataPileup.GetBinContent(xbin)/origPileup.GetBinContent(xbin)
puWeightsGr.SetPoint( puWeightsGr.GetN(), origPileup.GetXaxis().GetBinCenter(xbin), iweight )
dataPileupFile.Close()
except :
print 'No data pileup file provided or other error occurred. If you wish add -w pu,pu_file.root'
jecCorrector=None
jecUncertainty=None
try:
prefix='Data'
if xsec>0 : prefix='MC'
jecDir=correctionsMap['jec']
gSystem.ExpandPathName(jecDir)
jetCorLevels='L1FastJet'
jetCorFiles=jecDir+'/'+prefix+'_L1FastJet_AK5PFchs.txt'
jetCorLevels=jetCorLevels+':L2Relative'
jetCorFiles=jetCorFiles+':'+jecDir+'/'+prefix+'_L2Relative_AK5PFchs.txt'
jetCorLevels=jetCorLevels+':L3Absolute'
jetCorFiles=jetCorFiles+':'+jecDir+'/'+prefix+'_L3Absolute_AK5PFchs.txt'
#if prefix=='Data':
# jetCorLevels=jetCorLevels+':L2L3Residual'
# jetCorFiles=jetCorFiles+':'+jecDir+'/'+prefix+'_L2L3Residual_AK5PFchs.txt'
jecCorrector=FactorizedJetCorrector(jetCorLevels,jetCorFiles)
print 'Jet energy corrector initialized with levels ',jetCorLevels,' for ',prefix
if prefix=='MC':
jecUncertainty=JetCorrectionUncertainty(jecDir+"/"+prefix+"_Uncertainty_AK5PFchs.txt")
print 'Jet uncertainty is ',jecUncertainty
except Exception as e:
print '[Error]',e
tree=file.Get("smDataAnalyzer/data")
nev = tree.GetEntries()
outUrl=outputDir+'/'+os.path.basename(fileName)
monitor=Monitor(outUrl)
#same the initial normalization and cross section
monitor.addValue(origEvents,'iniEvents')
monitor.addValue(xsec,'crossSection')
#some basic histograms
monitor.addHisto('nvtx', ';Vertices;Events', 50,0,50)
monitor.addHisto('nvtxraw', ';Vertices;Events', 50,0,50)
monitor.addHisto('vmass', ';Mass [GeV];Events', 50,0,250)
monitor.addHisto('vmt', ';Transverse mass [GeV];Events', 50,0,250)
monitor.addHisto('vpt', ';Boson transverse momentum [GeV];Events',50,0,250)
monitor.addHisto('leg1pt', ';Transverse momentum [GeV];Events', 50,0,250)
monitor.addHisto('leg2pt', ';Transverse momentum [GeV];Events', 50,0,250)
monitor.addHisto('leg1iso', ';Relative isolation;Events', 50,0,0.5)
monitor.addHisto('leg2iso', ';Relative isolation;Events', 50,0,0.5)
#save a summary ntuple for analysis
summaryTuple=None
if saveSummary :
varList='cat:weight:nvtx:njets'
varList=varList+':v_mass:v_mt:v_pt:genv_mass:genv_pt'
varList=varList+':leg1_pt:leg1_eta:leg1_phi:genleg1_pt:leg1_relIso'
varList=varList+':leg2_pt:leg2_eta:leg2_phi:genleg2_pt:leg2_relIso'
varList=varList+':sumEt:ht'
varList=varList+':met_lesup:met_lesdown:met_jesup:met_jesdown:met_jerup:met_jerdown:met_umetup:met_umetdown'
summaryTuple=TNtuple('data','summary',varList)
summaryTuple.SetDirectory(0)
monitor.addObject(summaryTuple)
#save a dedicated ntuple for Tag and Probe
probesTuple=None
probesId = array.array( 'f', [ 0 ] )
probesPt = array.array( 'f', [ 0 ] )
probesEta = array.array( 'f', [ 0 ] )
probesPhi = array.array( 'f', [ 0 ] )
probesNvtx = array.array( 'f', [ 0 ] )
probesMass = array.array( 'f', [ 0 ] )
probesIsMatched = array.array( 'i', [0] )
probesPassLoose = array.array( 'i', [ 0 ] )
probesPassTight = array.array( 'i', [ 0 ] )
probesFireTrigger = array.array( 'i', [ 0 ] )
if saveProbes :
probesTuple=TTree('tandp','summary for tandp')
probesTuple.Branch( 'id', probesId, 'id/F' )
probesTuple.Branch( 'pt', probesPt, 'pt/F' )
probesTuple.Branch( 'eta', probesEta, 'eta/F' )
probesTuple.Branch( 'phi', probesPhi, 'phi/F' )
probesTuple.Branch( 'nvtx', probesNvtx, 'nvtx/F' )
probesTuple.Branch( 'mass', probesMass, 'mass/F' )
probesTuple.Branch( 'isMatched', probesIsMatched, 'isMatched/I' )
probesTuple.Branch( 'passLoose', probesPassLoose, 'passLoose/I' )
probesTuple.Branch( 'passTight', probesPassTight, 'passTight/I' )
probesTuple.Branch( 'fireTrigger', probesFireTrigger, 'fireTrigger/I' )
probesTuple.SetDirectory(0)
monitor.addObject(probesTuple)
#
# LOOP OVER THE EVENTS
#
for iev in xrange(0,nev):
tree.GetEntry(iev)
if iev%10000 == 0 :
sys.stdout.write("\r[ %d/100 ] completed" %(100.*iev/nev))
sys.stdout.flush()
#check mc truth (select V bosons from the hard process
genBosonP4=TLorentzVector(0,0,0,0)
genNeutP4=TLorentzVector(0,0,0,0)
for g in xrange(0,tree.mcn):
if tree.mc_status[g]!=3 : continue
genP4=TLorentzVector(tree.mc_px[g],tree.mc_py[g],tree.mc_pz[g],tree.mc_en[g])
if abs(tree.mc_id[g])==12 or abs(tree.mc_id[g])==14 or abs(tree.mc_id[g])==14 : genNeutP4=genNeutP4+genP4
if abs(tree.mc_id[g])!=23 and abs(tree.mc_id[g])!=24 : continue
genBosonP4=genP4
#get triggers that fired
eFire,mFire,emFire=decodeTriggerWord(tree.tbits)
if eTriggersOnly : mFire=False
if muTriggersOnly : eFire=False
#select the leptons
leptonCands=[]
validTags=[]
lepSums=[TLorentzVector(0,0,0,0)]*3
lepFlux=TLorentzVector(0,0,0,0)
for l in xrange(0,tree.ln) :
lep=LeptonCand(tree.ln_id[l],tree.ln_px[l],tree.ln_py[l],tree.ln_pz[l],tree.ln_en[l])
if lep.p4.Pt()<20 : continue
if abs(tree.ln_id[l])==11 :
if math.fabs(lep.p4.Eta())>2.5 : continue
if math.fabs(lep.p4.Eta())>1.4442 and math.fabs(lep.p4.Eta())<1.566 : continue
if abs(tree.ln_id[l])==13 :
if math.fabs(lep.p4.Eta())>2.1 : continue
relIso, isLoose, isLooseIso, isTight, isTightIso = selectLepton(tree.ln_id[l],tree.ln_idbits[l],tree.ln_gIso[l],tree.ln_chIso[l],tree.ln_nhIso[l],tree.ln_puchIso[l],lep.p4.Pt())
lep.selectionInfo(relIso,isLoose, isLooseIso, isTight, isTightIso)
lep.triggerInfo(tree.ln_Tbits[l])
#check the generator level information
genMatchIdx=tree.ln_genid[l]
if genMatchIdx < tree.mcn :
lep.genMatch(tree.mc_id[genMatchIdx],tree.mc_px[genMatchIdx],tree.mc_py[genMatchIdx],tree.mc_pz[genMatchIdx],tree.mc_en[genMatchIdx])
else :
lep.genMatch(0,0,0,0,0)
leptonCands.append(lep)
if not saveProbes: continue
if not isTight or not isTightIso or lep.Tbits==0 : continue
if abs(lep.id)==11 and not eFire: continue
if abs(lep.id)==13 and not mFire: continue
validTags.append( len(leptonCands)-1 )
lepSums[1]=lepSums[1]+lep.getP4('lesup')-lep.p4
lepSums[2]=lepSums[2]+lep.getP4('lesdown')-lep.p4
lepFlux=lepFlux+lep.p4
#check if probes tree should be saved
if saveProbes and len(validTags)>0:
# choose a random tag
tagIdx=random.choice(validTags)
tag=leptonCands[tagIdx]
#find probe
probe=None
for l in xrange(0,len(leptonCands)) :
if l==tagIdx: continue
if abs(tag.id)!=abs(leptonCands[l].id) : continue
probe=leptonCands[l]
break
#for electrons save superclusters if probe is not found
matchToEle=1
#if abs(tag.id)==11 and probe is None :
# matchToEle=0
# for sc in xrange(0,tree.scn) :
# sc_en=tree.scn_e[sc]
# sc_eta=tree.scn_eta[sc]
# sc_phi=tree.scn_phi[sc]
# sc_pt=sc_en/math.cosh(sc_eta)
# sc_p4=TLorentzVector(0,0,0,0)
# sc_p4.SetPtEtaPhiE(sc_pt,sc_eta,sc_phi,sc_en)
# lscp4=tag.p4+sc_p4
# if math.fabs(lscp4.M()-91)>30 : continue
# scCand=LeptonCand(tag.id,sc_p4.Px(),sc_p4.Py(),sc_p4.Pz(),sc_p4.E())
# scCand.selectionInfo(0,0,0,0,0)
# scCand.triggerInfo(0)
# probe=scCand
# break
if abs(tag.id)==13 : matchToEle=0
#save info
if probe is not None:
tpp4=tag.p4+probe.p4
if math.fabs(tpp4.M()-91)<30 :
probesId[0]=probe.id
probesPt[0]=probe.p4.Pt()
probesEta[0]=probe.p4.Eta()
probesPhi[0]=probe.p4.Phi()
probesNvtx[0]=tree.nvtx
probesMass[0]=tpp4.M()
probesIsMatched[0]=(probe.genId!=0)
probesPassLoose[0]=(probe.passLoose and probe.passLooseIso)
probesPassTight[0]=(probe.passTight and probe.passTightIso)
probesFireTrigger[0]=(probe.Tbits>0)
probesTuple.Fill()
#jets
selJets=[]
jetSums=[TLorentzVector(0,0,0,0)]*5
jetFlux=TLorentzVector(0,0,0,0)
ht=0
for j in xrange(0,tree.jn) :
jet=JetCand(tree.jn_px[j],tree.jn_py[j],tree.jn_pz[j],tree.jn_en[j],tree.jn_area[j],tree.jn_torawsf[j])
#cross clean with loose isolated leptons
overlapFound=False
for l in leptonCands:
if not l.passLoose or not l.passLooseIso : continue
dR=jet.p4.DeltaR(l.p4)
if dR>0.4 : continue
overlapFound=True
break
if overlapFound: continue
#very loose kinematics cuts
if math.fabs(jet.p4.Eta())>4.7 or jet.p4.Pt()<10 : continue
#save it
jet.genMatch(tree.jn_genpx[j],tree.jn_py[j],tree.jn_pz[j],tree.jn_en[j],tree.jn_genid[j],tree.jn_genflav[j])
jet.updateJEC(jecCorrector,jecUncertainty,tree.rho,tree.nvtx)
selJets.append(jet)
#account for all the corrections you have applied
jetSums[0]=jetSums[0] + jet.getCorrectedJet() - jet.getCorrectedJet('raw')
jetSums[1]=jetSums[1] + jet.getCorrectedJet('jesup') - jet.getCorrectedJet()
jetSums[2]=jetSums[2] + jet.getCorrectedJet('jesdown') - jet.getCorrectedJet()
jetSums[3]=jetSums[3] + jet.getCorrectedJet('jerup') - jet.getCorrectedJet()
jetSums[4]=jetSums[4] + jet.getCorrectedJet('jerdown') - jet.getCorrectedJet()
jetFlux=jetFlux+jet.p4
ht=ht+jet.p4.Pt()
# met
metCand=METCand(tree.met_pt[0]*math.cos(tree.met_phi[0]),tree.met_pt[0]*math.sin(tree.met_phi[0]),0,tree.met_pt[0])
metCand.genMatch(genNeutP4.Px(),genNeutP4.Py(),genNeutP4.Pz(),genNeutP4.E())
metCand.addSumEts(tree.met_sumet[0], tree.met_chsumet[0])
metCand.addJetCorrections(jetSums)
metCand.addLeptonCorrections(lepSums)
unclFlux=-(metCand.p4+lepFlux+jetFlux)
unclSums=[TLorentzVector(0,0,0,0),unclFlux*0.10,unclFlux*(-0.10)]
metCand.addUnclusteredCorrections(unclSums)
#build the candidate
vCand=buildVcand(eFire,mFire,emFire,leptonCands,metCand)
if vCand is None : continue
#prepare to save
weight=1.0
if puWeightsGr is not None:
weight=puWeightsGr.Eval(tree.ngenITpu)
#show isolations
for ileg in [0,1]:
hname='leg'+str(ileg+1)+'iso'
lid=''
if abs(vCand.m_legs[ileg].id)==11 : lid='e'
elif abs(vCand.m_legs[ileg].id)==13 : lid='mu'
else : continue
monitor.fill(hname,[lid],vCand.m_legs[ileg].relIso,weight)
tags=[vCand.tag]
monitor.fill('nvtxraw',tags, tree.nvtx, 1.0)
monitor.fill('nvtx', tags, tree.nvtx, weight)
monitor.fill('vmass', tags, vCand.p4.M(), weight)
monitor.fill('vpt', tags, vCand.p4.Pt(), weight)
monitor.fill('leg1pt', tags, vCand.m_legs[0].p4.Pt(), weight)
monitor.fill('leg2pt', tags, vCand.m_legs[1].p4.Pt(), weight)
for var in ['','lesup','lesdown','jesup','jesdown','jerup','jerdown','umetup','umetdown']:
mtVar=vCand.computeMt(var)
monitor.fill('vmt', [vCand.tag+var], mtVar, weight)
if saveSummary :
values=[
vCand.id, weight, tree.nvtx, len(selJets),
vCand.p4.M(), vCand.mt, vCand.p4.Pt(), genBosonP4.M(), genBosonP4.Pt(),
vCand.m_legs[0].p4.Pt(),vCand.m_legs[0].p4.Eta(),vCand.m_legs[0].p4.Phi(), vCand.m_legs[0].genP4.Pt(), vCand.m_legs[0].relIso,
vCand.m_legs[1].p4.Pt(),vCand.m_legs[1].p4.Eta(),vCand.m_legs[1].p4.Phi(), vCand.m_legs[1].genP4.Pt(), vCand.m_legs[1].relIso,
metCand.sumet, ht,
metCand.p4Vars['lesup'].Pt(),metCand.p4Vars['lesdown'].Pt(),metCand.p4Vars['jesup'].Pt(),metCand.p4Vars['jesdown'].Pt(),metCand.p4Vars['jerup'].Pt(),metCand.p4Vars['jerdown'].Pt(),metCand.p4Vars['umetup'].Pt(),metCand.p4Vars['umetdown'].Pt()
]
summaryTuple.Fill(array.array("f",values))
file.Close()
monitor.close()
# piPlus meson
PiPlus[nPiPlus].SetPxPyPzE(float(word[2]), float(word[3]),
float(word[4]), float(word[5]))
nPiPlus += 1
elif value == 9:
# piMinus meson
PiMinus.SetPxPyPzE(float(word[2]), float(word[3]), float(word[4]),
float(word[5]))
if value == 8 and nPiPlus == 2:
Neutron = Beam + Target - (PiPlus[0] + PiPlus[1] + PiMinus
) #missing neutron vector
n, pip1, pip2, pim = Neutron.Mag(), PiPlus[0].Mag(), PiPlus[1].Mag(
), PiMinus.Mag()
im1, im2, im3, im4, im5, im6, im7, im8 = n + pip1 + pip2 + pim, pip1 + pip2 + pim, pip1 + pim, pip2 + pim, pip1 + pip2, n + pip1, n + pip2, n + pim
IMspectra.Fill(im1, im2, im3, im4, im5, im6, im7,
im8) #filling Ntuple
rootFile.Write() #saving the Ntuple in a root file
IMCanvas = TCanvas("cc", "Invariant mass spectra", 10, 10, 1000,
700) #creating a 2x4 canvas
IMCanvas.Divide(2, 4)
IMCanvas.cd(1) #Navigation and filling of Canvas
IMspectra.Draw("npip1pip2pim")
IMCanvas.cd(2)
IMspectra.Draw("pip1pip2pim")
IMCanvas.cd(3)
IMspectra.Draw("pip1pim")
IMCanvas.cd(4)
IMspectra.Draw("pip2pim")
context = zmq.Context()
socket = context.socket(zmq.SUB)
print("Collecting updates from LTC2983 publisher")
socket.connect("tcp://usop01:5556")
socket.setsockopt(zmq.SUBSCRIBE, '')
print("Storing data on: " + filename)
nsamples = 0
while True:
msg = socket.recv().split('\0')[0]
fval = float(msg)
ntuple.Fill(fval)
ch2plot.Fill(fval)
nsamples = nsamples + 1
if (nsamples % 1000) == 0:
f.Write()
if (nsamples == 5000):
print("Done !")
f.Write()
sys.exit(0)
#ch2plot.Draw()
#c1.Update()
readEvent = False
nPart = 0
nEvents = 0
for line in lines:
if(line == "<mgrwt>\n"): readEvent = False
if(readEvent):
nPart += 1
if(nPart == 1): continue
varList = line.split()
PID = int(varList[0])
Px = float(varList[6])
Py = float(varList[7])
Pz = float(varList[8])
E = float(varList[9])
m = float(varList[10])
if(nPart == 2): eleBeamNtuple.Fill(PID,Px,Py,Pz,E,m)
if(nPart == 4): ApNtuple.Fill(PID,Px,Py,Pz,E,m)
if(nPart == 5): RhoNtuple.Fill(PID,Px,Py,Pz,E,m)
if(nPart == 6): eleRecoilNtuple.Fill(PID,Px,Py,Pz,E,m)
if(nPart == 7): WRecoilNtuple.Fill(PID,Px,Py,Pz,E,m)
if(nPart == 8): posDecayNtuple.Fill(PID,Px,Py,Pz,E,m)
if(nPart == 9): eleDecayNtuple.Fill(PID,Px,Py,Pz,E,m)
if(nPart == 10): PionNtuple.Fill(PID,Px,Py,Pz,E,m)
nEvents += 1
if(nEvents%10000 == 0): print "Adding event number " + str(nEvents)
if(line == "<event>\n"):
readEvent = True
nPart = 0
LHEfile.close()
rootfile.Write()
def main():
if len(sys.argv) < 3:
print("Usage: ToyMC [numberEvents] [randomSeed]")
return
numberEvents = int(sys.argv[1])
seed = int(sys.argv[2])
print(
"==================================== TRAIN ===================================="
)
f = root_open(
"legotrain_350_20161117-2106_LHCb4_fix_CF_pPb_MC_ptHardMerged.root", "read"
)
hJetPt = f.Get("AliJJetJtTask/AliJJetJtHistManager/JetPt/JetPtNFin{:02d}".format(2))
hZ = f.Get("AliJJetJtTask/AliJJetJtHistManager/Z/ZNFin{:02d}".format(2))
FillFakes = False
dummy_variable = True
weight = True
NBINS = 50
LimL = 0.1
LimH = 500
logBW = (TMath.Log(LimH) - TMath.Log(LimL)) / NBINS
LogBinsX = [LimL * math.exp(ij * logBW) for ij in range(0, NBINS + 1)]
hJetPtMeas = Hist(LogBinsX)
hJetPtTrue = Hist(LogBinsX)
myRandom = TRandom3(seed)
fEff = TF1("fEff", "1-0.5*exp(-x)")
jetBinBorders = [5, 10, 20, 30, 40, 60, 80, 100, 150, 500]
hJetPtMeasCoarse = Hist(jetBinBorders)
hJetPtTrueCoarse = Hist(jetBinBorders)
NBINSJt = 64
low = 0.01
high = 10
BinW = (TMath.Log(high) - TMath.Log(low)) / NBINSJt
LogBinsJt = [low * math.exp(i * BinW) for i in range(NBINSJt + 1)]
hJtTrue = Hist(LogBinsJt)
hJtMeas = Hist(LogBinsJt)
hJtFake = Hist(LogBinsJt)
LogBinsPt = jetBinBorders
jetPtBins = [(a, b) for a, b in zip(jetBinBorders, jetBinBorders[1:])]
hJtTrue2D = Hist2D(LogBinsJt, LogBinsPt)
hJtMeas2D = Hist2D(LogBinsJt, LogBinsPt)
hJtFake2D = Hist2D(LogBinsJt, LogBinsPt)
hJtMeasBin = [Hist(LogBinsJt) for i in jetBinBorders]
hJtTrueBin = [Hist(LogBinsJt) for i in jetBinBorders]
response = RooUnfoldResponse(hJtMeas, hJtTrue)
response2D = RooUnfoldResponse(hJtMeas2D, hJtTrue2D)
responseBin = [RooUnfoldResponse(hJtMeas, hJtTrue) for i in jetBinBorders]
responseJetPt = RooUnfoldResponse(hJetPtMeas, hJetPtTrue)
responseJetPtCoarse = RooUnfoldResponse(hJetPtMeasCoarse, hJetPtTrueCoarse)
# Histogram index is jet pT index, Bin 0 is 5-10 GeV
# Histogram X axis is observed jT, Bin 0 is underflow
# Histogram Y axis is observed jet Pt, Bin 0 is underflow
# Histogram Z axis is True jT, Bin 0 is underflow
responses = [Hist3D(LogBinsJt, LogBinsPt, LogBinsJt) for i in jetPtBins]
misses = Hist2D(LogBinsJt, LogBinsPt)
fakes2D = Hist2D(LogBinsJt, LogBinsPt)
outFile = TFile("tuple.root", "recreate")
responseTuple = TNtuple(
"responseTuple", "responseTuple", "jtObs:ptObs:jtTrue:ptTrue"
)
hMultiTrue = Hist(50, 0, 50)
hMultiMeas = Hist(50, 0, 50)
hZMeas = Hist(50, 0, 1)
hZTrue = Hist(50, 0, 1)
hZFake = Hist(50, 0, 1)
responseMatrix = Hist2D(LogBinsJt, LogBinsJt)
numberJets = 0
numberFakes = 0
numberJetsMeasBin = [0 for i in jetBinBorders]
numberJetsTrueBin = [0 for i in jetBinBorders]
numberFakesBin = [0 for i in jetBinBorders]
ieout = numberEvents / 10
if ieout > 10000:
ieout = 10000
fakeRate = 1
start_time = datetime.now()
print("Processing Training Events")
for ievt in range(numberEvents):
tracksTrue = []
tracksMeas = [0 for x in range(100)]
if ievt % ieout == 0 and ievt > 0:
time_elapsed = datetime.now() - start_time
time_left = timedelta(
seconds=time_elapsed.total_seconds()
* 1.0
* (numberEvents - ievt)
/ ievt
)
print(
"Event {} [{:.2f}%] Time Elapsed: {} ETA: {}".format(
ievt,
100.0 * ievt / numberEvents,
fmtDelta(time_elapsed),
fmtDelta(time_left),
)
)
jetTrue = TVector3(0, 0, 0)
jetMeas = TVector3(0, 0, 0)
jetPt = hJetPt.GetRandom()
remainder = jetPt
if jetPt < 5:
continue
nt = 0
nt_meas = 0
while remainder > 0:
trackPt = hZ.GetRandom() * jetPt
if trackPt < remainder:
track = TVector3()
remainder = remainder - trackPt
else:
trackPt = remainder
remainder = -1
if trackPt > 0.15:
track.SetPtEtaPhi(
trackPt, myRandom.Gaus(0, 0.1), myRandom.Gaus(math.pi, 0.2)
)
tracksTrue.append(track)
jetTrue += track
if fEff.Eval(trackPt) > myRandom.Uniform(0, 1):
tracksMeas[nt] = 1
jetMeas += track
nt_meas += 1
else:
tracksMeas[nt] = 0
nt += 1
fakes = []
for it in range(fakeRate * 100):
if myRandom.Uniform(0, 1) > 0.99:
fake = TVector3()
fake.SetPtEtaPhi(
myRandom.Uniform(0.15, 1),
myRandom.Gaus(0, 0.1),
myRandom.Gaus(math.pi, 0.2),
)
fakes.append(fake)
jetMeas += fake
hJetPtMeas.Fill(jetMeas.Pt())
hJetPtTrue.Fill(jetTrue.Pt())
responseJetPt.Fill(jetMeas.Pt(), jetTrue.Pt())
responseJetPtCoarse.Fill(jetMeas.Pt(), jetTrue.Pt())
hMultiTrue.Fill(nt)
hMultiMeas.Fill(nt_meas)
ij_meas = GetBin(jetBinBorders, jetMeas.Pt())
ij_true = GetBin(jetBinBorders, jetTrue.Pt())
if nt < 5 or nt_meas < 5:
continue
numberJets += 1
if ij_meas >= 0:
numberJetsMeasBin[ij_meas] += 1
hJetPtMeasCoarse.Fill(jetMeas.Pt())
if ij_true >= 0:
numberJetsTrueBin[ij_true] += 1
hJetPtTrueCoarse.Fill(jetTrue.Pt())
for track, it in zip(tracksTrue, range(100)):
zTrue = (track * jetTrue.Unit()) / jetTrue.Mag()
jtTrue = (track - scaleJet(jetTrue, zTrue)).Mag()
hZTrue.Fill(zTrue)
if ij_true >= 0:
if weight:
hJtTrue.Fill(jtTrue, 1.0 / jtTrue)
hJtTrueBin[ij_true].Fill(jtTrue, 1.0 / jtTrue)
hJtTrue2D.Fill(jtTrue, jetTrue.Pt(), 1.0 / jtTrue)
else:
hJtTrue.Fill(jtTrue)
hJtTrueBin[ij_true].Fill(jtTrue)
hJtTrue2D.Fill(jtTrue, jetTrue.Pt())
if ij_meas >= 0:
if tracksMeas[it] == 1:
zMeas = (track * jetMeas.Unit()) / jetMeas.Mag()
jtMeas = (track - scaleJet(jetMeas, zMeas)).Mag()
hZMeas.Fill(zMeas)
if weight:
hJtMeasBin[ij_meas].Fill(jtMeas, 1.0 / jtMeas)
hJtMeas.Fill(jtMeas, 1.0 / jtMeas)
hJtMeas2D.Fill(jtMeas, jetMeas.Pt(), 1.0 / jtMeas)
else:
hJtMeas.Fill(jtMeas)
hJtMeasBin[ij_meas].Fill(jtMeas)
hJtMeas2D.Fill(jtMeas, jetMeas.Pt())
response.Fill(jtMeas, jtTrue)
responseBin[ij_true].Fill(jtMeas, jtTrue)
response2D.Fill(jtMeas, jetMeas.Pt(), jtTrue, jetTrue.Pt())
responseMatrix.Fill(jtMeas, jtTrue)
responses[ij_true].Fill(jtMeas, jetMeas.Pt(), jtTrue)
responseTuple.Fill(jtMeas, jetMeas.Pt(), jtTrue, jetTrue.Pt())
else:
response.Miss(jtTrue)
responseBin[ij_true].Miss(jtTrue)
response2D.Miss(jtTrue, jetTrue.Pt())
misses.Fill(jtTrue, jetTrue.Pt())
responseTuple.Fill(-1, -1, jtTrue, jetTrue.Pt())
if ij_meas >= 0:
for fake in fakes:
zFake = (fake * jetMeas.Unit()) / jetMeas.Mag()
jtFake = (fake - scaleJet(jetMeas, zFake)).Mag()
hZMeas.Fill(zFake)
hZFake.Fill(zFake)
if weight:
hJtMeas.Fill(jtFake, 1.0 / jtFake)
hJtMeasBin[ij_meas].Fill(jtFake, 1.0 / jtFake)
hJtMeas2D.Fill(jtFake, jetMeas.Pt(), 1.0 / jtFake)
hJtFake2D.Fill(jtFake, jetMeas.Pt(), 1.0 / jtFake)
hJtFake.Fill(jtFake, 1.0 / jtFake)
else:
hJtMeas.Fill(jtFake)
hJtMeasBin[ij_meas].Fill(jtFake)
hJtMeas2D.Fill(jtFake, jetMeas.Pt())
hJtFake2D.Fill(jtFake, jetMeas.Pt())
hJtFake.Fill(jtFake)
if FillFakes:
response.Fake(jtFake)
responseBin[ij_true].Fake(jtFake)
response2D.Fake(jtFake, jetMeas.Pt())
fakes2D.Fill(jtFake, jetMeas.Pt())
responseTuple.Fill(jtFake, jetMeas.Pt(), -1, -1)
numberFakes += 1
numberFakesBin[ij_true] += 1
response2Dtest = make2Dresponse(
responses, jetPtBins, hJtMeas2D, hJtTrue2D, misses=misses, fakes=fakes2D
)
if dummy_variable:
hJetPtMeas.Reset()
hJetPtTrue.Reset()
hMultiTrue.Reset()
hMultiMeas.Reset()
hJetPtMeasCoarse.Reset()
hJetPtTrueCoarse.Reset()
hZTrue.Reset()
hZMeas.Reset()
hJtTrue.Reset()
hJtTrue2D.Reset()
hJtMeas.Reset()
hJtMeas2D.Reset()
hJtFake.Reset()
hJtFake2D.Reset()
for h, h2 in zip(hJtTrueBin, hJtMeasBin):
h.Reset()
h2.Reset()
numberJetsMeasBin = [0 for i in jetBinBorders]
numberJetsTrueBin = [0 for i in jetBinBorders]
numberJets = 0
print("Create testing data")
start_time = datetime.now()
numberEvents = numberEvents / 2
for ievt in range(numberEvents):
tracksTrue = []
tracksMeas = [0 for x in range(100)]
if ievt % ieout == 0 and ievt > 0:
time_elapsed = datetime.now() - start_time
time_left = timedelta(
seconds=time_elapsed.total_seconds()
* 1.0
* (numberEvents - ievt)
/ ievt
)
print(
"Event {} [{:.2f}%] Time Elapsed: {} ETA: {}".format(
ievt,
100.0 * ievt / numberEvents,
fmtDelta(time_elapsed),
fmtDelta(time_left),
)
)
jetTrue = TVector3(0, 0, 0)
jetMeas = TVector3(0, 0, 0)
jetPt = hJetPt.GetRandom()
remainder = jetPt
if jetPt < 5:
continue
nt = 0
nt_meas = 0
while remainder > 0:
trackPt = hZ.GetRandom() * jetPt
if trackPt < remainder:
track = TVector3()
remainder = remainder - trackPt
else:
trackPt = remainder
remainder = -1
if trackPt > 0.15:
track.SetPtEtaPhi(
trackPt, myRandom.Gaus(0, 0.1), myRandom.Gaus(math.pi, 0.2)
)
tracksTrue.append(track)
jetTrue += track
if fEff.Eval(trackPt) > myRandom.Uniform(0, 1):
tracksMeas[nt] = 1
jetMeas += track
nt_meas += 1
else:
tracksMeas[nt] = 0
nt += 1
fakes = []
for it in range(fakeRate * 100):
if myRandom.Uniform(0, 1) > 0.99:
fake = TVector3()
fake.SetPtEtaPhi(
myRandom.Uniform(0.15, 1),
myRandom.Gaus(0, 0.1),
myRandom.Gaus(math.pi, 0.2),
)
fakes.append(fake)
jetMeas += fake
hJetPtMeas.Fill(jetMeas.Pt())
hJetPtTrue.Fill(jetTrue.Pt())
hMultiTrue.Fill(nt)
hMultiMeas.Fill(nt_meas)
ij_meas = GetBin(jetBinBorders, jetMeas.Pt())
ij_true = GetBin(jetBinBorders, jetTrue.Pt())
if nt < 5 or nt_meas < 5:
continue
numberJets += 1
if ij_meas >= 0:
numberJetsMeasBin[ij_meas] += 1
hJetPtMeasCoarse.Fill(jetMeas.Pt())
if ij_true >= 0:
numberJetsTrueBin[ij_true] += 1
hJetPtTrueCoarse.Fill(jetTrue.Pt())
for track, it in zip(tracksTrue, range(100)):
zTrue = (track * jetTrue.Unit()) / jetTrue.Mag()
jtTrue = (track - scaleJet(jetTrue, zTrue)).Mag()
hZTrue.Fill(zTrue)
if ij_true >= 0:
if weight:
hJtTrue.Fill(jtTrue, 1.0 / jtTrue)
hJtTrueBin[ij_true].Fill(jtTrue, 1.0 / jtTrue)
hJtTrue2D.Fill(jtTrue, jetTrue.Pt(), 1.0 / jtTrue)
else:
hJtTrue.Fill(jtTrue)
hJtTrueBin[ij_true].Fill(jtTrue)
hJtTrue2D.Fill(jtTrue, jetTrue.Pt())
if ij_meas >= 0:
if tracksMeas[it] == 1:
zMeas = (track * jetMeas.Unit()) / jetMeas.Mag()
jtMeas = (track - scaleJet(jetMeas, zMeas)).Mag()
hZMeas.Fill(zMeas)
if weight:
hJtMeasBin[ij_meas].Fill(jtMeas, 1.0 / jtMeas)
hJtMeas.Fill(jtMeas, 1.0 / jtMeas)
hJtMeas2D.Fill(jtMeas, jetMeas.Pt(), 1.0 / jtMeas)
else:
hJtMeas.Fill(jtMeas)
hJtMeasBin[ij_meas].Fill(jtMeas)
hJtMeas2D.Fill(jtMeas, jetMeas.Pt())
if ij_meas >= 0:
for fake in fakes:
zFake = (fake * jetMeas.Unit()) / jetMeas.Mag()
jtFake = (fake - scaleJet(jetMeas, zFake)).Mag()
hZMeas.Fill(zFake)
hZFake.Fill(zFake)
if weight:
hJtMeas.Fill(jtFake, 1.0 / jtFake)
hJtMeasBin[ij_meas].Fill(jtFake, 1.0 / jtFake)
hJtMeas2D.Fill(jtFake, jetMeas.Pt(), 1.0 / jtFake)
hJtFake2D.Fill(jtFake, jetMeas.Pt(), 1.0 / jtFake)
hJtFake.Fill(jtFake, 1.0 / jtFake)
else:
hJtMeas.Fill(jtFake)
hJtMeasBin[ij_meas].Fill(jtFake)
hJtMeas2D.Fill(jtFake, jetMeas.Pt())
hJtFake2D.Fill(jtFake, jetMeas.Pt())
hJtFake.Fill(jtFake)
time_elapsed = datetime.now() - start_time
print(
"Event {} [{:.2f}%] Time Elapsed: {}".format(
numberEvents, 100.0, fmtDelta(time_elapsed)
)
)
if not FillFakes:
hJtMeas.Add(hJtFake, -1)
hJtMeas2D.Add(hJtFake2D, -1)
responseTuple.Print()
outFile.Write()
# printTuple(responseTuple)
hJtMeasProjBin = [
makeHist(hJtMeas2D.ProjectionX("histMeas{}".format(i), i, i), bins=LogBinsJt)
for i in range(1, len(jetBinBorders))
]
hJtMeasProj = makeHist(hJtMeas2D.ProjectionX("histMeas"), bins=LogBinsJt)
hJtTrueProjBin = [
makeHist(hJtTrue2D.ProjectionX("histTrue{}".format(i), i, i), bins=LogBinsJt)
for i in range(1, len(jetBinBorders))
]
hJtTrueProj = makeHist(hJtTrue2D.ProjectionX("histTrue"), bins=LogBinsJt)
hJtFakeProjBin = [
makeHist(hJtFake2D.ProjectionX("histFake{}".format(i), i, i), bins=LogBinsJt)
for i in range(1, len(jetBinBorders))
]
if not FillFakes:
for h, h2 in zip(hJtMeasBin, hJtFakeProjBin):
h.Add(h2, -1)
for h in (
hJtMeasProj,
hJtTrueProj,
hJtMeas,
hJtTrue,
hJtFake,
hZFake,
hZMeas,
hZTrue,
):
h.Scale(1.0 / numberJets, "width")
for meas, true, n_meas, n_true in zip(
hJtMeasBin, hJtTrueBin, numberJetsMeasBin, numberJetsTrueBin
):
if n_meas > 0:
meas.Scale(1.0 / n_meas, "width")
if n_true > 0:
true.Scale(1.0 / n_true, "width")
numberJetsMeasFromHist = [
hJetPtMeasCoarse.GetBinContent(i)
for i in range(1, hJetPtMeasCoarse.GetNbinsX() + 1)
]
numberJetsTrueFromHist = [
hJetPtTrueCoarse.GetBinContent(i)
for i in range(1, hJetPtTrueCoarse.GetNbinsX() + 1)
]
print("Total number of jets: {}".format(numberJets))
print("Total number of fakes: {}".format(numberFakes))
print("Measured jets by bin")
print(numberJetsMeasBin)
print(numberJetsMeasFromHist)
print("True jets by bin")
print(numberJetsTrueBin)
print(numberJetsTrueFromHist)
hRecoJetPtCoarse = unfoldJetPt(hJetPtMeasCoarse, responseJetPtCoarse, jetBinBorders)
numberJetsFromReco = [
hRecoJetPtCoarse.GetBinContent(i)
for i in range(1, hRecoJetPtCoarse.GetNbinsX())
]
print("Unfolded jet numbers by bin:")
print(numberJetsFromReco)
print("Fakes by bin")
print(numberFakesBin)
print(
"==================================== UNFOLD ==================================="
)
unfold = RooUnfoldBayes(response, hJtMeas, 4) # OR
unfoldSVD = RooUnfoldSvd(response, hJtMeas, 20) # OR
unfold2D = RooUnfoldBayes(response2D, hJtMeas2D, 4)
for u in (unfold, unfoldSVD, unfold2D):
u.SetVerbose(0)
# response2Dtest = makeResponseFromTuple(responseTuple,hJtMeas2D,hJtTrue2D)
unfold2Dtest = RooUnfoldBayes(response2Dtest, hJtMeas2D, 4)
unfoldBin = [
RooUnfoldBayes(responseBin[i], hJtMeasBin[i]) for i in range(len(jetBinBorders))
]
for u in unfoldBin:
u.SetVerbose(0)
hRecoBayes = makeHist(unfold.Hreco(), bins=LogBinsJt)
hRecoSVD = makeHist(unfoldSVD.Hreco(), bins=LogBinsJt)
hRecoBin = [
makeHist(unfoldBin[i].Hreco(), bins=LogBinsJt)
for i in range(len(jetBinBorders))
]
hReco2D = make2DHist(unfold2D.Hreco(), xbins=LogBinsJt, ybins=LogBinsPt)
hReco2Dtest = make2DHist(unfold2Dtest.Hreco(), xbins=LogBinsJt, ybins=LogBinsPt)
hRecoJetPt = unfoldJetPt(hJetPtMeas, responseJetPt, LogBinsX)
hReco2DProjBin = [
makeHist(hReco2D.ProjectionX("histReco{}".format(i), i, i), bins=LogBinsJt)
for i in range(1, len(jetBinBorders))
]
hReco2DTestProjBin = [
makeHist(
hReco2Dtest.ProjectionX("histRecoTest{}".format(i), i, i), bins=LogBinsJt
)
for i in range(1, len(jetBinBorders))
]
hReco2DProj = makeHist(hReco2D.ProjectionX("histReco"), bins=LogBinsJt)
hReco2DProj.Scale(1.0 / numberJets, "width")
for h, h2, n in zip(hReco2DProjBin, hReco2DTestProjBin, numberJetsFromReco):
if n > 0:
h.Scale(1.0 / n, "width")
h2.Scale(1.0 / n, "width")
# unfold.PrintTable (cout, hJtTrue)
for h, h2, nj in zip(hJtMeasProjBin, hJtFakeProjBin, numberJetsMeasBin):
if nj > 0:
h.Scale(1.0 / nj, "width")
h2.Scale(1.0 / nj, "width")
# else:
# print("nj is 0 for {}".format(h.GetName()))
for h, nj in zip(hJtTrueProjBin, numberJetsTrueBin):
if nj > 0:
h.Scale(1.0 / nj, "width")
# draw8grid(hJtMeasBin[1:],hJtTrueBin[1:],jetPtBins[1:],xlog = True,ylog = True,name="newfile.pdf",proj = hJtMeasProjBin[2:], unf2d = hReco2DProjBin[2:], unf=hRecoBin[1:])
if numberEvents > 1000:
if numberEvents > 1000000:
filename = "ToyMC_{}M_events.pdf".format(numberEvents / 1000000)
else:
filename = "ToyMC_{}k_events.pdf".format(numberEvents / 1000)
else:
filename = "ToyMC_{}_events.pdf".format(numberEvents)
draw8gridcomparison(
hJtMeasBin,
hJtTrueBin,
jetPtBins,
xlog=True,
ylog=True,
name=filename,
proj=None,
unf2d=hReco2DProjBin,
unf2dtest=hReco2DTestProjBin,
unf=hRecoBin,
fake=hJtFakeProjBin,
start=1,
stride=1,
)
drawQA(
hJtMeas,
hJtTrue,
hJtFake,
hRecoBayes,
hRecoSVD,
hReco2DProj,
hZ,
hZTrue,
hZMeas,
hZFake,
hMultiMeas,
hMultiTrue,
hJetPt,
hJetPtTrue,
hJetPtMeas,
hRecoJetPt,
responseMatrix,
)
outFile.Close()
def main():
"""
Creates a simple summary of the ROI for fast calibration.
"""
fIn = TFile.Open(FLAGS.noPUFile, 'READ')
fOut = TFile(FLAGS.outpath, 'RECREATE')
varnames = ['genen', 'geneta', 'genphi']
for i in range(1,NREG+1):
varnames += ['en_sr{}_ROI'.format(i),
'noise_sr{}_ROI'.format(i)]
for idet in range(1,NSUBDETS+1):
varnames += ['en_sr{}_det{}'.format(i,idet),
'noise_sr{}_det{}'.format(i,idet)]
for il in range(1,NLAYERS+1):
varnames += ['en_sr{}_layer{}'.format(i,il),
'noise_sr{}_layer{}'.format(i,il)]
output_tuples = TNtuple('summary','summary',':'.join(varnames))
tree = fIn.Get('an_mask/CEE_HEF_HEB')
for t in tree:
#define the ROIs
roiList={}
for ir in range(0,t.ROIs.size()):
if t.ROIs[ir].pdgid() < 0 and t.ROIs[ir].pdgid() != -211:
continue
roiList[ir] = ROISummary(t.ROIs[ir].p4(), Nlayers=NLAYERS, PartType='Pion')
for h in t.Hits:
roiIdx = h.associatedROI()
rid = t.ROIs[roiIdx].pdgid()
roiKey = roiIdx if rid>0 or rid==-211 else abs(rid)-1
mipflag = True
en = h.en(mipflag)
subdet = h.subdet()
layer = int(h.layerId()) #originally it is long
isNoise = True if rid<0 and rid!=-211 else False
regIdx = h.signalRegion()
roiList[roiKey].AddHit(en=en, layer=layer, subdet=subdet, isNoise=isNoise, regIdx=regIdx)
for r in roiList:
varvals = []
genP4 = roiList[r].genP4
varvals += [genP4.E(),genP4.Eta(),genP4.Phi()]
for ireg in range(1,NREG+1):
recP4 = roiList[r].RecoP4(ireg)
assert(np.isclose(recP4.E(), ( roiList[r].SubdetEnergyDeposited(ireg, 1) +
roiList[r].SubdetEnergyDeposited(ireg, 2) +
roiList[r].SubdetEnergyDeposited(ireg, 3) ) ))
noiseROI = roiList[r].NoiseInROI(ireg)
varvals += [recP4.E(),noiseROI]
for idet in range(1,NSUBDETS+1):
recEnSubdet = roiList[r].SubdetEnergyDeposited(ireg, idet)
noiseSubdet = roiList[r].SubdetNoiseDeposited(ireg, idet)
varvals += [recEnSubdet, noiseSubdet]
for il in range(1,NLAYERS+1):
recEn = roiList[r].RecoEnergyDeposited(ireg, il)
noiseLayer = roiList[r].NoiseInLayer(ireg, il)
varvals += [recEn, noiseLayer]
output_tuples.Fill(array.array("f", varvals))
fOut.cd()
fOut.Write()
fOut.Close()
nEvBkg)
else:
hMassSB = GetSideBandHisto(hMassData, mean, sigma)
B = GetExpectedBackgroundFromSB(hMassSB, mean, sigma, Nexp, nEvBkg)
if inputCfg['PredForFprompt']['estimateFprompt']:
fprompt = ComputeExpectedFprompt(PtMin[iPt], PtMax[iPt], effPrompt, \
hPredPrompt, effFD, hPredFD, RatioRaaFDPrompt)
else:
fprompt = inputCfg['fprompt']
S = GetExpectedSignal(PtMin[iPt] - PtMax[iPt], sigmaFONLL, Raa, Taa,
effPrompt, Acc, fprompt, BR, fractoD, Nexp)
array4Ntuple.append(PtMin[iPt])
array4Ntuple.append(PtMax[iPt])
array4Ntuple.append(S)
array4Ntuple.append(B)
array4Ntuple.append(S / math.sqrt(S + B))
array4Ntuple.append(S / B)
array4Ntuple.append(effPrompt)
array4Ntuple.append(effFD)
array4Ntuple.append(fprompt)
tSignif.Fill(array.array("f", array4Ntuple))
elapsed_time = time.time() - start_time
print('total elapsed time: %f s' % elapsed_time)
tSignif.Write()
outfile.Close()
# Efficiency
EffAccFDError = np.sqrt((effFDUnc / effFD)**2 +
(preselEffFDUnc / preselEffFD)**2 +
(accUnc / acc)**2) * effTimesAccFD
EffAccPromptError = np.sqrt(
(effPromptUnc / effPrompt)**2 +
(preselEffPromptUnc / preselEffPrompt)**2 +
(accUnc / acc)**2) * effTimesAccPrompt
tupleForNtuple = cutSet + (
ptMin, ptMax, ParCutMin, ParCutMax, EffAccPromptError,
EffAccFDError, errS, errExpBkg, errSignif, errSoverB,
expSignif, expSoverB, expSignal, expBkg, effTimesAccPrompt,
effTimesAccFD, fPrompt[0], fFD[0])
tSignif.Fill(np.array(tupleForNtuple, 'f'))
estValues = {
'Signif': expSignif,
'SoverB': expSoverB,
'S': expSignal,
'B': expBkg,
'EffAccPrompt': effTimesAccPrompt,
'EffAccFD': effTimesAccFD,
'fPrompt': fPrompt[0],
'fFD': fFD[0]
}
estValuesErr = {
'SignifError': errSignif,
'SoverBError': errSoverB,
'SError': errS,
'BError': errExpBkg,
Nbin = (len(lineList)) # get number of bins
Line_string = str(lineList[0])
bin_init, _, _ = Line_string.split()
bin_init = float(bin_init) # get initial bin
Line_string = str(lineList[len(lineList) - 1])
_, bin_final, _ = Line_string.split()
bin_final = float(bin_final) # get final bin
f.seek(0) # reset python read line
hist = TH1D("h1f", "h1f", Nbin, bin_init, bin_final)
ntuple = TNtuple("ntuple", "ntuple", "low_bin:high_bin:bin_contents")
total_e = 0
for i in range(1, Nbin + 1):
Line_string = str(f.readline())
ss, ff, bin_c = Line_string.split()
ss = float(ss)
ff = float(ff)
bin_c = float(bin_c)
hist.SetBinContent(i, bin_c)
total_e = total_e + bin_c
ntuple.Fill(ss, ff, bin_c)
#gStyle.SetOptStat()
hist.Draw()
gPad.Update()
can.Update()
wf = TFile("root_ntuple_from_txt.root", "RECREATE")
hist.Write()
ntuple.Write()
wf.Close()
def LeCroy2Root(directory, outputRootFile):
masterFile = TFile(outputRootFile, "recreate")
print("listing files...")
filesPerChannel = listFilesPerChannel(directory)
## se rellena el ultimo canal en 0:
print len(filesPerChannel)
nMC = len(
filesPerChannel[0]) # number of available measurement per channel
for i in range(4 - len(filesPerChannel)):
filesPerChannel.append([0] * nMC)
#### Get time from CHANNEL n #######################
TimeNch = 1
########################################
nMC = len(
filesPerChannel[0]) # number of available measurement per channel
# formar la tupla con las columnas necesarias:
# measuresLabels = "event:time:C1:C2:C3:C4"
measuresLabels = "event:time:C1:C2:C3"
tup = TNtuple("osc", "LeCroy Readings", measuresLabels)
readingGroup = []
print("loading data..." + str(nMC))
# para cada frame
for i in range(nMC):
# obtener cada canal
for j in range(len(filesPerChannel)):
if (filesPerChannel[j][i] == 0):
readingGroup.append([])
# print "channel: " + str(j) + " empty"
else:
# print "channel: " + str(j) + " ok"
# print directory+filesPerChannel[j][i]
readingGroup.append(readTrc(directory + filesPerChannel[j][i]))
largos = []
for j in range(len(readingGroup)):
if (not (len(readingGroup[j]) in largos)):
if (len(readingGroup[j]) != 0):
largos.append(len(readingGroup[j][0]))
n_data = max(largos)
for j in range(len(readingGroup)):
if (len(readingGroup[j]) == 0):
x_data = [0] * n_data
y_data = [0] * n_data
d_data = [0] * n_data
readingGroup[j] = [x_data, y_data, d_data]
# luego, generar listas a cargar a la tupla
event = i
for [time, c1, c2,
c3] in zip(readingGroup[TimeNch - 1][0], readingGroup[0][1],
readingGroup[1][1], readingGroup[2][1]):
tup.Fill(event, time, c1, c2, c3)
# for [time,c1,c2,c3,c4] in zip(readingGroup[TimeNch-1][0], readingGroup[0][1], readingGroup[1][1], readingGroup[2][1], readingGroup[3][1]): tup.Fill(event,time,c1,c2,c3,c4)
# for [time,c1] in zip(readingGroup[0][0], readingGroup[0][1]):
# tup.Fill(event,time,c1)
# for [time,c2,c3] in zip(readingGroup[0][0], readingGroup[0][1], ):
# tup.Fill(event,time,c2,c3)
readingGroup = []
if (int((float(i * 100) / nMC) * 100) % 100 == 0):
sys.stdout.write(str(float(i * 100) / nMC) + "%" + "\r")
sys.stdout.flush()
tup.Write("", tup.kOverwrite)
masterFile.Close()
sys.stdout.write("\n")
random = TRandom3()
kUPDATE = 1000
for i in xrange(50000):
# Generate random numbers
# px, py = random.gauss(0, 1), random.gauss(0, 1)
px, py = random.Gaus(0, 1), random.Gaus(0, 1)
pz = px * px + py * py
# rnd = random.random()
rnd = random.Rndm(1)
# Fill histograms
hpx.Fill(px)
hpxpy.Fill(px, py)
hprof.Fill(px, pz)
if not _reflex:
ntuple.Fill(px, py, pz, rnd, i)
# Update display every kUPDATE events
if i and i % kUPDATE == 0:
if i == kUPDATE:
hpx.Draw()
c1.Modified(True)
c1.Update()
if gSystem.ProcessEvents(): # allow user interrupt
break
gBenchmark.Show('hsimple')
# Save all objects in this file
rannor, rndm = gRandom.Rannor, gRandom.Rndm
# In[5]:
_px = array('d', [0])
_py = array('d', [0])
for i in range(25000):
# Generate random values.
rannor(_px, _py)
px, py = _px[0], _py[0]
pz = px * px + py * py
random = rndm(1)
# Fill histograms.
hpx.Fill(px)
hpxpy.Fill(px, py)
hprof.Fill(px, pz)
ntuple.Fill(px, py, pz, random, i)
c1 = gROOT.FindObject('c1')
if c1:
c1 = 0
c1 = TCanvas('c1', 'Histogram Example', 200, 10, 700, 500)
c1.SetFillColor(42)
c1.GetFrame().SetFillColor(21)
c1.GetFrame().SetBorderSize(6)
c1.GetFrame().SetBorderMode(-1)
hpx.SetFillColor(48)
hpx.Draw()
c1.Modified()
c1.Update()
# In[ ]:
# In[7]:
gROOT.GetListOfCanvases().Draw()
Paul Eugenio
PHZ4151C
Florida State University
April 2, 2019
"""
from __future__ import division, print_function
import numpy as np
from ROOT import TLorentzVector, TNtuple, TCanvas, TFile
rootFile = TFile("ntp.root", "RECREATE")
def f(x):
return x**2
squares = TNtuple("sqntuple", "Squares", "x:x2")
sqCanvas = TCanvas("cc", "squares", 10, 10, 800, 600)
sqCanvas.Divide(1, 2)
for k in range(1, 10, 1):
squares.Fill(k, f(k))
squares.Draw("x")
sqCanvas.cd(2)
squares.Draw("x2")
rootFile.Write()
def get_pos(
event
): # Each detector is a 'collection', the No. of Elements are the hits.
a = TNtuple("a", "a",
"x:y:z") # creates ntuple to store the values of x y z
b = TNtuple("b", "b",
"x:y:z") # creates ntuple to store the values of x y z
c = TNtuple("c", "c",
"x:y:z") # creates ntuple to store the values of x y z
d = TNtuple("d", "d",
"x:y:z") # creates ntuple to store the values of x y z
e = TNtuple("e", "e",
"x:y:z") # creates ntuple to store the values of x y z
f = TNtuple("f", "f",
"x:y:z") # creates ntuple to store the values of x y z
g = TNtuple("g", "g",
"x:y:z") # creates ntuple to store the values of x y z
h = TNtuple("h", "h",
"x:y:z") # creates ntuple to store the values of x y z
i = TNtuple("i", "i",
"x:y:z") # creates ntuple to store the values of x y z
j = TNtuple("j", "j",
"x:y:z") # creates ntuple to store the values of x y z
k = TNtuple("k", "k",
"x:y:z") # creates ntuple to store the values of x y z
l = TNtuple("l", "l",
"x:y:z") # creates ntuple to store the values of x y z
ECALB = event.getCollection("EcalBarrelHits")
for ding in ECALB:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
a.Fill(x, y, z)
ECALE = event.getCollection("EcalEndcapHits")
for ding in ECALE:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
b.Fill(x, y, z)
HCALB = event.getCollection("HcalBarrelHits")
for ding in HCALB:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
c.Fill(x, y, z)
HCALE = event.getCollection("HcalEndcapHits")
for ding in HCALE:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
d.Fill(x, y, z)
LUMICAL = event.getCollection("LumiCalHits")
for ding in LUMICAL:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
e.Fill(x, y, z)
MUONB = event.getCollection("MuonBarrelHits")
for ding in MUONB:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
f.Fill(x, y, z)
MUONE = event.getCollection("MuonEndcapHits")
for ding in MUONE:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
g.Fill(x, y, z)
SITB = event.getCollection("SiTrackerBarrelHits")
for ding in SITB:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
h.Fill(x, y, z)
SITE = event.getCollection("SiTrackerEndcapHits")
for ding in SITE:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
i.Fill(x, y, z)
SITF = event.getCollection("SiTrackerForwardHits")
for ding in SITF:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
j.Fill(x, y, z)
SIVB = event.getCollection("SiVertexBarrelHits")
for ding in SIVB:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
k.Fill(x, y, z)
SIVE = event.getCollection("SiVertexEndcapHits")
for ding in SIVE:
pos = ding.getPosition()
x = pos[0]
y = pos[1]
z = pos[2]
l.Fill(x, y, z)
return a, b, c, d, e, f, g, h, i, j, k, l
##
## \macro_output
## \macro_code
##
## \author Wim Lavrijsen
import sys, os
from ROOT import TFile, TNtuple, TROOT
ifn = os.path.join(str(TROOT.GetTutorialDir()), 'pyroot', 'aptuple.txt')
ofn = 'aptuple.root'
print('opening file %s ...' % ifn)
infile = open(ifn, 'r')
lines = infile.readlines()
title = lines[0]
labels = lines[1].split()
print('writing file %s ...' % ofn)
outfile = TFile(ofn, 'RECREATE', 'ROOT file with an NTuple')
ntuple = TNtuple('ntuple', title, ':'.join(labels))
for line in lines[2:]:
words = line.split()
row = map(float, words)
ntuple.Fill(*row)
outfile.Write()
print('done')
