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 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_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
c2.Draw()
# In[14]:
c3 = gROOT.FindObject('c3')
if c3:
c3 = 0
c3 = TCanvas('c3', 'c3', 200, 10, 700, 500)
hprof.Draw()
c3.Modified()
c3.Update()
c3.Draw()
# In[15]:
c4 = gROOT.FindObject('c4')
if c4:
c4 = 0
c4 = TCanvas('c4', 'c4', 200, 10, 700, 500)
c4.Divide(2, 2)
c4.cd(1)
ntuple.Draw("pz:px")
c4.cd(2)
ntuple.Draw("pz:py")
c4.cd(3)
ntuple.Draw("pz:px*px + py*py")
c4.cd(4)
ntuple.Draw("pz:sqrt(px*px + py*py)")
c4.Modified()
c4.Update()
c4.Draw()
# In[16]:
hfile.Write()
# In[ ]:
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")
IMCanvas.cd(5)
IMspectra.Draw("pip1pip2")
IMCanvas.cd(6)
IMspectra.Draw("npip1")
IMCanvas.cd(7)
IMspectra.Draw("npip2")
IMCanvas.cd(8)
IMspectra.Draw("npim")
tSignif.GetMinimum('Signif') * 0.8,
tSignif.GetMaximum(est) * 1.2,
tSignif.GetMaximum('Signif') * 1.2,
f";{estNames[est]};{estNames['Signif']}")
hFrame.GetXaxis().SetDecimals()
hFrame.GetYaxis().SetDecimals()
hSignifVsRest[iPt][est] = (TH2F(
(f'hSignifVs{est}_pT{ptMin}-{ptMax}_{ParCutsName}'
f'{ParCutMin}-{ParCutMax}'),
f";{estNames[est]};{estNames['Signif']}", 50,
tSignif.GetMinimum(est) * 0.8,
tSignif.GetMaximum(est) * 1.2, 50,
tSignif.GetMinimum('Signif') * 0.8,
tSignif.GetMaximum('Signif') * 1.))
tSignif.Draw(
f'Signif:{est}>>hSignifVs{est}_pT{ptMin}-{ptMax}_{ParCutsName}{ParCutMin}-{ParCutMax}',
f'PtMin == {ptMin} && PtMax == {ptMax}', 'colz same')
cSignifVsRest[counter].Update()
cSignifVsRest[counter].Modified()
outDirPlotsPt[iPt].cd(f'{ParCutsName}{ParCutMin}-{ParCutMax}')
hSignifVsRest[iPt][est].Write()
outDirPlotsPt[iPt].cd(f'{ParCutsName}{ParCutMin}-{ParCutMax}')
cSignifVsRest[counter].Write()
if 1 <= len(varNames) <= 2:
if len(varNames) == 1:
cEstimVsCut.append(
TCanvas(
f'cEstimVsCut_pT{ptMin}-{ptMax}_{ParCutsName}{ParCutMin}-{ParCutMax}',
f'cEstimVsCut_pT{ptMin}-{ptMax}_{ParCutsName}{ParCutMin}-{ParCutMax}',
800, 1000))
cEstimVsCut[counter].Divide(2, 4)
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 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)
