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Analysis_SiPM_Tile.py
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import numpy as np
import os, re, shutil
import argparse
import itertools
from prettytable import PrettyTable
import ROOT as rt
from root_numpy import tree2array, tree2rec
from lib.histo_utilities import create_TH1D, create_TH2D, quantile, rootTH2_to_np
from lib.cebefo_style import cebefo_style, Set_2D_colz_graphics
donotdelete = []
def parsing():
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--input_file", type=str, help="input root file, if -N is given XX is replaced with runNumber", nargs='+')
parser.add_argument("-C", "--config", type=str, default='config/FNAL_TB_1811/VME_SiPM.txt', help="Config file")
parser.add_argument("-S", "--save_loc", type=str, default='./out_plots/', help="Saving location")
parser.add_argument("-B", "--batch", default=True, action='store_false', help="Root batch mode")
parser.add_argument("-v", "--verbose", default=False, action='store_true', help="Verbose mode")
parser.add_argument("-N", "--runs_interval", default=None, help="Runs to run", nargs='+')
args = parser.parse_args()
return args
class Config:
def __init__(self, infile):
self.raw_conf = open(infile, 'r').readlines()
self.channel = {}
self.ch_ordered = []
self.plots = []
self.labels = []
self.xy_center = [0,0, 15]
for i, l in enumerate(self.raw_conf):
if l[0] == '#':
continue
l = l[0:-1].split()
if '-->Print' in l[0]:
self.plots = l[1:]
elif '-->XYcenter' in l[0]:
self.xy_center = [float(l[1]), float(l[2]), float(l[3])]
elif '-->SpaceBinSize' in l[0]:
self.space_bin_size = float(l[1])
elif '-->TracksCleaning' in l[0]:
self.TracksCleaning = {}
cuts = ''
for aux in l[1:]:
if aux[:7] == 'CutOnCh':
self.TracksCleaning['ch'] = int(aux[7:])
print 'Cuts from ch', int(aux[7:]), 'will be used for cleaning tracks'
else:
cuts += aux + ' && '
if len(cuts) > 3:
self.TracksCleaning['cuts'] = cuts[:-4]
print 'Cleaning tracks with:', cuts[:-4]
else:
self.TracksCleaning['cuts'] = ''
elif '-->TracksConsistency' in l[0]:
self.TracksConsistency = {}
self.TracksConsistency['Bad'] = 0
self.TracksConsistency['Checked'] = 0
for aux in l[1:]:
if aux[:5] == 'RefCh':
self.TracksConsistency['RefCh'] = int(aux[5:])
# print 'Tracks consistency: ch', int(aux[5:]), 'will be checked'
if aux == 'List':
self.TracksConsistency['List'] = 1
elif '-->Var' in l[0]:
if not hasattr(self, 'Var'):
self.Var = {}
self.Var[l[0][7:-1]] = l[1:]
elif len(self.labels) == 0:
self.labels = l[1:]
else:
n = int(l[0])
self.ch_ordered.append(n)
l = l[1:]
self.channel[n] = {}
for k, val in zip(self.labels, l):
if 'idx' in k:
self.channel[n][k] = int(val)
else:
self.channel[n][k] = val
class Bauble:
def __init__(self):
pass
def define_range_around_peak(h, perc = [0.4, 0.4], Range=[0.0, 99999.0]):
h_aux = h.Clone('h_aux')
for i in range(1, h_aux.GetNbinsX()+1):
if h_aux.GetBinCenter(i) < Range[0] or h_aux.GetBinCenter(i) > Range[1]:
h_aux.SetBinContent(i, 0.)
SS = rt.TSpectrum()
n_pks = SS.Search(h_aux, 2, "", 0.2)
i_max = 0
max = -1
y = SS.GetPositionY()
x = SS.GetPositionX()
found = False
for i in range(n_pks):
if y[i] > max and x > Range[0] and x < Range[1]:
max = y[i]
i_max = i
found = True
if found:
n_pk = h.FindBin(SS.GetPositionX()[i_max])
else:
n_pk = h_aux.GetMaximumBin()
thr = perc[0] * h.GetBinContent(n_pk)
n_low = n_pk
while h.GetBinContent(n_low) > thr and n_low > 1:
n_low -= 1
x_low = h.GetBinLowEdge(n_low)
thr = perc[1] * h.GetBinContent(n_pk)
n_up = n_pk
while h.GetBinContent(n_up) > thr and n_up < h.GetNbinsX():
n_up += 1
x_up = h.GetBinLowEdge(n_up) + h.GetBinWidth(n_up)
return x_low, x_up, n_pk
def fill_TimeResHisto(k, dt, h2D, out_list, tagin, title_tag, canvas, save_canvas=True):
q_up, e_up = quantile(1000*dt, 0.15)
q_dwn, e_dwn = quantile(1000*dt, 0.85)
if q_up == None or q_dwn == None:
print '[WARNING] Quantile estimation failed'
return
disp_est = 0.5*np.abs(q_up - q_dwn)
disp_unc = 0.5*np.hypot(e_up, e_dwn)
out_list.append([disp_est, disp_unc])
ix = h2D.GetXaxis().FindBin(0.5*(xu+xd))
iy = h2D.GetYaxis().FindBin(0.5*(yu+yd))
ig = h2D.GetBin(ix, iy)
h2D.SetBinContent(ig, disp_est)
h2D.SetBinError(ig, disp_unc)
if save_canvas:
median = np.percentile(dt, 50)
width = np.abs(np.percentile(dt, 10) - np.percentile(dt, 90))
tag = tagin+'_'+str(k)+'_'+str(ib)
h = create_TH1D(dt, 'h_'+tag,
title_tag + ' time resolution - x #in [{:.1f}, {:.1f}], y #in [{:.1f}, {:.1f}]'.format(xd, xu, yd, yu),
binning = [ None, median-2*width, median+2*width],
axis_title = [var_dT + ' [ns]', 'Events'])
canvas['c_'+tag] = rt.TCanvas('c_'+tag, 'c_'+tag, 800, 600)
h.Fit('gaus', 'LQR','', np.percentile(dt, 20), np.percentile(dt, 98))
h = h.DrawCopy('LE')
l = rt.TLatex()
l.SetTextSize(0.04);
l.DrawLatexNDC(0.15, 0.85, 'Unbiased dispersion: {:.1f} #pm {:.1f}'.format(disp_est, disp_unc))
canvas['c_'+tag].Update()
canvas['c_'+tag].SaveAs(out_dir + '/'+tagin+'_ch{:02d}/'.format(k)+tag+'.png')
if __name__ == '__main__':
cebefo_style()
rt.gErrorIgnoreLevel = 6000
args = parsing()
if args.batch:
rt.gROOT.SetBatch()
configurations = Config(args.config)
if args.runs_interval==None:
aux = re.search(r'Run[0-9]+', args.input_file[0])
flag = aux.group(0)[3:]
if len(args.input_file) > 1:
aux = re.search(r'Run[0-9]+', args.input_file[-1])
flag += '_'+aux.group(0)[3:]
elif len(args.runs_interval)==1 and not args.runs_interval[0].endswith('.txt'):
N = args.runs_interval[0]
args.input_file = [args.input_file[0].replace('XXX', str(N))]
flag = '_'+str(N)
else:
if args.runs_interval[0].endswith('.txt'):
runs = np.sort(np.loadtxt(args.runs_interval[0]).astype(np.int))
runs = list(runs)
elif len(args.runs_interval)==2 and args.runs_interval[0] < args.runs_interval[1]:
runs = range(int(args.runs_interval[0]), int(args.runs_interval[1])+1)
else:
runs = args.runs_interval
file_template = args.input_file[0]
args.input_file = map(lambda x: file_template.replace('XXX', str(x)), runs)
if len(runs) > 1:
flag = '_' + str(runs[0]) + '-' + str(runs[-1])
else:
flag = '_' + str(runs[0])
save_loc = args.save_loc
if os.path.isdir(save_loc):
if save_loc[-1] != '/':
save_loc += '/'
out_dir = save_loc + 'Run' + str(flag) + '_' + os.path.basename(args.config[:-4])
if not os.path.exists(out_dir):
os.mkdir(out_dir)
shutil.copy('lib/index.php', out_dir+'/index.php')
else:
print 'Save location not existing:', save_loc
raise Exception(' ')
chain = rt.TChain('pulse')
chain.tree_name = tree_name = 'pulse'
for i, f in enumerate(args.input_file):
root_file = rt.TFile.Open( f,"READ");
if not root_file:
print "[ERROR]: Input file not found:", f
continue
tree_name = root_file.GetListOfKeys().At(0).GetName()
if i == 0:
if tree_name != 'pulse':
print 'Change'
chain = rt.TChain(tree_name)
chain.tree_name = tree_name
elif tree_name != chain.tree_name:
print 'Skipping', f, ' for tree name incompatibility'
continue
chain.Add(f)
canvas = {}
canvas['amp'] = {}
canvas['int'] = {}
canvas['risetime'] = {}
canvas['wave'] = {}
canvas['pos'] = {}
canvas['pos_sel'] = {}
canvas['amp_w_pos'] = {}
canvas['int_w_pos'] = {}
canvas['t_res_raw'] = {}
canvas['space_corr'] = {}
canvas['t_res_space'] = {}
canvas['dt_vs_amp'] = {}
canvas['dtcorr_vs_amp'] = {}
canvas['dt_corr'] = {}
rt.gStyle.SetStatY(0.95)
rt.gStyle.SetStatX(0.85)
rt.gStyle.SetStatW(0.15)
rt.gStyle.SetStatH(0.1)
rt.gStyle.SetHistLineWidth(2)
'''=========================== AllTracks ==========================='''
if 'AllTracks' in configurations.plots:
name = 'h_alltracks'
title = 'All tracks at z_DUT[0]'
var = 'y_dut[0]:x_dut[0]'
dy = configurations.xy_center[1]
dx = configurations.xy_center[0]
width = configurations.xy_center[2]
h = rt.TH2D(name, title, 100, -width+dx, width+dx, 100, -width+dy, width+dy)
h.SetXTitle('x [mm]')
h.SetYTitle('y [mm]')
sel = ''
if hasattr(configurations, 'TracksCleaning'):
sel += configurations.TracksCleaning['cuts']
chain.Project(name, var, sel)
canvas['AllTracks'] = rt.TCanvas('c_allTracks', 'c_allTracks', 800, 600)
h.DrawCopy('colz')
canvas['AllTracks'].Update()
canvas['AllTracks'].SaveAs(out_dir + '/AllTracks.png')
print '\n======================= Channels selection loop ==========================='
for k in configurations.ch_ordered:
print '---> Channel', k
conf = configurations.channel[k]
line = rt.TLine()
line.SetLineColor(6)
line.SetLineWidth(2)
line.SetLineStyle(10)
selection = '(amp[{nch}] != 0 && integral[{nch}] != 0)'.format(nch=k)
'''=========================== Amplitude ==========================='''
if 'Amp' in configurations.plots:
name = 'h_amp_'+str(k)
title = 'Amplitude channel '+str(k)
amp_aux = np.concatenate(list(tree2array( chain, 'amp['+str(k)+']')))
h = rt.TH1D(name, title, 80, np.percentile(amp_aux, 1), min(990., np.percentile(amp_aux, 99.99)))
h.SetXTitle('Peak amplitude [mV]')
h.SetYTitle('Events / {:.1f} mV'.format(h.GetBinWidth(1)))
chain.Project(name, 'amp['+str(k)+']')
Range = [0.0, 9999999.0]
if 'cut' in conf.keys():
if conf['cut'][0] in ['a', 'A']:
if 'min' in conf.keys():
Range[0] = float(conf['min'])
if 'max' in conf.keys():
Range[1] = float(conf['max'])
x_low, x_up, n_pk = define_range_around_peak(h, [0.2, 0.2], Range)
canvas['amp'][k] = rt.TCanvas('c_amp_'+str(k), 'c_amp_'+str(k), 800, 600)
h.DrawCopy('E')
gr = rt.TGraph(1)
gr.SetPoint(0, h.GetBinCenter(n_pk), h.GetBinContent(n_pk))
gr.SetMarkerStyle(23)
gr.SetMarkerColor(2)
gr.Draw("P")
if h.GetMaximum() > 5*h.GetBinContent(n_pk):
canvas['amp'][k].SetLogy()
if 'cut' in conf.keys():
if conf['cut'][0] in ['a', 'A']:
selection += ' && (amp[{}]>{} && amp[{}]<{})'.format(k, x_low, k, x_up)
line.DrawLine(x_low, 0, x_low, h.GetMaximum())
line.DrawLine(x_up, 0, x_up, h.GetMaximum())
canvas['amp'][k].Update()
canvas['amp'][k].SaveAs(out_dir + '/Amp_ch{:02d}.png'.format(k))
'''=========================== Integral ==========================='''
if 'Int' in configurations.plots:
canvas['int'][k] = rt.TCanvas('c_int_'+str(k), 'c_int_'+str(k), 800, 600)
name = 'h_int_'+str(k)
title = 'Integral channel '+str(k)
int_aux = -np.concatenate(list(tree2array(chain, 'integral['+str(k)+']', 'integral['+str(k)+'] != 0')))
h = rt.TH1D(name, title, 100, np.percentile(int_aux, 0.1), np.max(int_aux))
h.SetXTitle('Integral [pC]')
h.SetYTitle('Events / {:.1f} pC'.format(h.GetBinWidth(1)))
chain.Project(name, '-integral['+str(k)+']', '-integral['+str(k)+'] != 0')
Range = [0.0, 9999999.0]
if 'cut' in conf.keys():
if conf['cut'][0] in ['i', 'I']:
if 'min' in conf.keys():
Range[0] = float(conf['min'])
if 'max' in conf.keys():
Range[1] = float(conf['max'])
x_low, x_up, n_pk = define_range_around_peak(h, [0.25, 0.3], Range)
h.DrawCopy('E')
gr = rt.TGraph(1)
gr.SetPoint(0, h.GetBinCenter(n_pk), h.GetBinContent(n_pk))
gr.SetMarkerStyle(23)
gr.SetMarkerColor(2)
gr.Draw("P")
if(h.GetMaximum() - h.GetMinimum() > 5000):
canvas['int'][k].SetLogy()
if 'cut' in conf.keys():
if conf['cut'][0] in ['i', 'I']:
selection += ' && (-integral[{}]>{} && -integral[{}]<{})'.format(k, x_low, k, x_up)
line.DrawLine(x_low, 0, x_low, h.GetMaximum())
line.DrawLine(x_up, 0, x_up, h.GetMaximum())
canvas['int'][k].Update()
canvas['int'][k].SaveAs(out_dir + '/Int_ch{:02d}.png'.format(k))
'''=========================== Risetime ======================================='''
if 'Risetime' in configurations.plots:
print '\tRisetime'
canvas['risetime'][k] = rt.TCanvas('c_risetime_'+str(k), 'c_int_'+str(k), 800, 600)
nbins = 100
name = 'h_risetime_' + str(k)
title = 'Risetime ch' + str(k)
rise_aux = (tree2array(chain, 'risetime['+str(k)+']').view(np.recarray).T)[0]
bin_w = 200.0/1024
lower_bound = np.percentile(rise_aux, 5) - bin_w*0.5
upper_bound = np.percentile(rise_aux, 99) + bin_w*0.5
N_bins = (upper_bound - lower_bound) / bin_w
h = rt.TH1D(name, title, int(N_bins), lower_bound, upper_bound)
h.SetXTitle('Risetime [ns]')
h.SetYTitle('Events / {:.1f} ns'.format(h.GetBinWidth(1)))
if conf['idx_ref'] == -1:#do not apply cut again on reference channels
cut = selection
else:
cut = selection + '&&' + configurations.channel[conf['idx_ref']]['sel']
chain.Project(name, 'risetime['+str(k)+']', cut)
if (h.GetMaximum() - h.GetMinimum() > 50000):
canvas['risetime'][k].SetLogy()
##ploting histogram
h.DrawCopy('lE')
canvas['risetime'][k].Update()
canvas['risetime'][k].SaveAs(out_dir+'/risetime_ch{:02d}.png'.format(k))
'''=========================== Waveform color chart ==========================='''
if 'WaveColor' in configurations.plots:
name = 'h_wave_'+str(k)
title = 'Waveform color chart channel '+str(k)
h = rt.TH2D(name, title, 250, 0, 210, 250, -1100, 500)
h.SetXTitle('Time [ns]')
h.SetYTitle('Voltage [mV]')
N_max = chain.GetEntries()
N_max = max(500, int(N_max*0.1))
chain.Project(name, 'channel[{}]:time[{}]'.format(k,conf['idx_time'], 'Entry$ < {}'.format(N_max)))
h.SetStats(0)
canvas['wave'][k] = rt.TCanvas('c_wave_'+str(k), 'c_wave_'+str(k), 800, 600)
if(h.GetMaximum() - h.GetMinimum() > 5000):
canvas['wave'][k].SetLogz()
h.DrawCopy('colz')
canvas['wave'][k].Update()
canvas['wave'][k].SaveAs(out_dir + '/Waveform_ch{:02d}.png'.format(k))
'''=========================== Track position ==========================='''
if conf['idx_dut'] >= 0:
if hasattr(configurations, 'TracksCleaning'):
selection += ' && ' + configurations.TracksCleaning['cuts']
if 'ch' in configurations.TracksCleaning.keys():
ch = configurations.TracksCleaning['ch']
if ch < k:
selection += ' && ' + configurations.channel[ch]['sel']
var = 'y_dut[{}]:x_dut[{}]'.format(conf['idx_dut'], conf['idx_dut'])
dy = configurations.xy_center[1]
dx = configurations.xy_center[0]
width = configurations.xy_center[2]
N_bins = [70, 70]
if 'PosRaw' in configurations.plots:
name = 'h_pos_'+str(k)
title = 'Track position at z_DUT[' + str(conf['idx_dut']) + '], for channel {} selected event'.format(k)
h = rt.TH2D(name, title, N_bins[0], -width+dx, width+dx, N_bins[1], -width+dy, width+dy)
h.SetXTitle('x [mm]')
h.SetYTitle('y [mm]')
chain.Project(name, var, selection)
canvas['pos'][k] = rt.TCanvas('c_pos_'+str(k), 'c_pos_'+str(k), 800, 600)
h.DrawCopy('colz')
rt.gPad.SetRightMargin(0.15)
canvas['pos'][k].Update()
canvas['pos'][k].SaveAs(out_dir + '/PositionXY_raw_ch{:02d}.png'.format(k))
if ('PosSel' in configurations.plots) or ('PosSel+' in configurations.plots):
canvas['pos_sel'][k] = rt.TCanvas('c_pos_sel_'+str(k), 'c_pos_sel_'+str(k), 800, 600)
name = 'h_pos_sel'
title = 'Events average selection efficiency'
h = rt.TH3D(name, title, N_bins[0], -width+dx, width+dx, N_bins[1], -width+dy, width+dy, 2, -0.5, 1.5)
chain.Project(name, selection + ':' + var, configurations.TracksCleaning['cuts'])
h = h.Project3DProfile('yx')
h.SetYTitle('y [mm]')
h.SetXTitle('x [mm]')
h.DrawCopy('colz')
if ('PosSel+' in configurations.plots) and ('shape' in conf.keys()):
if not conf['shape'] == 'None':
size = conf['shape'].split('x')
x = h.GetXaxis().GetBinCenter(1) - h.GetXaxis().GetBinWidth(1)*0.51 + float(size[0])
nbx = h.GetXaxis().FindBin(x)
y = h.GetYaxis().GetBinCenter(1) - h.GetYaxis().GetBinWidth(1)*0.51 + float(size[1])
nby = h.GetYaxis().FindBin(y)
arr_h, pos_h = rootTH2_to_np(h, cut=0.2)
# print arr_h
p_max = 0
idx_max = [0, 0]
for iy in range(0, arr_h.shape[0]-nby):
for ix in range(0, arr_h.shape[1]-nbx):
p = np.sum(arr_h[iy:iy+nby, ix:ix+nbx])
if p > p_max:
p_max = p
idx_max = [iy, ix]
avg_prob = p_max/(nbx*nby)
iy, ix = idx_max
x_start = h.GetXaxis().GetBinCenter(ix+1) - 0.5*h.GetXaxis().GetBinWidth(ix+1)
x_stop = h.GetXaxis().GetBinCenter(ix+nbx) + 0.5*h.GetXaxis().GetBinWidth(ix+nbx)
y_start = h.GetYaxis().GetBinCenter(iy+1) - 0.5*h.GetYaxis().GetBinWidth(iy+1)
y_stop = h.GetYaxis().GetBinCenter(iy+nby) + 0.5*h.GetYaxis().GetBinWidth(iy+nby)
best_theta = 0
cx = 0.5*(x_stop + x_start)
cy = 0.5*(y_stop + y_start)
x = '(x_dut[{}] - {})'.format(conf['idx_dut'], cx)
y = '(y_dut[{}] - {})'.format(conf['idx_dut'], cy)
var_template = '{c}*{y} - {s}*{x} + {cy}:{c}*{x} + {s}*{y} + {cx}'
for theta in np.arange(-0.1, 0.1, 0.005):
var_aux = var_template.format(x=x, y=y, c=np.cos(theta), s=np.sin(theta), cy=cy, cx=cx)
h = rt.TH3D('h_aux', title, N_bins[0], -width+dx, width+dx, N_bins[1], -width+dy, width+dy, 2, -0.5, 1.5)
chain.Project('h_aux', selection + ':' + var_aux, configurations.TracksCleaning['cuts'])
h = h.Project3DProfile('yx')
arr_h, pos_h = rootTH2_to_np(h, cut=0.2)
p = np.sum(arr_h[iy:iy+nby, ix:ix+nbx])
if p > p_max:
p_max = p
best_theta = theta
conf['theta_z'] = best_theta
conf['x_rot'] = '{c}*{x} + {s}*{y} + {cx}'.format(x=x, y=y, c=np.cos(best_theta), s=np.sin(best_theta), cx=cx)
conf['y_rot'] = '{c}*{y} - {s}*{x} + {cy}'.format(x=x, y=y, c=np.cos(best_theta), s=np.sin(best_theta), cy=cy)
var = conf['y_rot']+':'+conf['x_rot']
h = rt.TH3D('h_aux', title, N_bins[0], -width+dx, width+dx, N_bins[1], -width+dy, width+dy, 2, -0.5, 1.5)
chain.Project('h_aux', selection + ':' + var, configurations.TracksCleaning['cuts'])
h = h.Project3DProfile('yx')
h.SetYTitle('y [mm]')
h.SetXTitle('x [mm]')
h.DrawCopy('colz')
line.SetLineStyle(9)
line.SetLineColor(6)
line.SetLineWidth(2)
line.DrawLine(x_start, y_start, x_stop, y_start)
line.DrawLine(x_start, y_stop, x_stop, y_stop)
line.DrawLine(x_start, y_start, x_start, y_stop)
line.DrawLine(x_stop, y_start, x_stop, y_stop)
conf['space_sel'] = {}
conf['space_sel']['limits'] = [x_start, x_stop, y_start, y_stop]
conf['space_sel']['cut'] = '({y} < {h} && {y} > {l}'.format(y=conf['y_rot'], l=y_start, h=y_stop)
conf['space_sel']['cut'] += ' && {x} < {h} && {x} > {l})'.format(x=conf['x_rot'], l=x_start, h=x_stop)
Set_2D_colz_graphics()
canvas['pos_sel'][k].Update()
canvas['pos_sel'][k].SaveAs(out_dir + '/PositionXY_sel_ch{:02d}.png'.format(k))
if 'PosWeight' in configurations.plots:
h = rt.TH2D('h_amp_aux'+str(k), title, N_bins[0], -width+dx, width+dx, N_bins[1], -width+dy, width+dy)
chain.Project('h_amp_aux'+str(k), var, selection)
''' -------------Avg amp-----------'''
name = 'h_amp_weight_pos_'+str(k)
title = 'Average peak amplitude channel {} in selected event'.format(k)
h_w = rt.TH2D(name, title, N_bins[0], -width+dx, width+dx, N_bins[1], -width+dy, width+dy)
h_w.SetXTitle('x [mm]')
h_w.SetYTitle('y [mm]')
h_w.SetZTitle('Average Amplitude [mV]')
weights = '('+ selection +') * amp[' + str(k) + ']'
chain.Project(name, var, weights)
h_w.Divide(h)
h_w.GetZaxis().SetRangeUser(h_w.GetMinimum(10), h_w.GetMaximum())
h_w.SetStats(0)
can = rt.TCanvas('c_w_pos', 'c_w_pos', 1200, 500)
if 'space_sel' in conf.keys():
can.Divide(2,1)
pad = can.cd(1)
h_w.DrawCopy('colz')
rt.gPad.SetRightMargin(0.15)
if not conf['SiPM'] == 'None':
size = conf['SiPM'].split('x')
x = h_w.GetXaxis().GetBinCenter(1) - h_w.GetXaxis().GetBinWidth(1)*0.51 + float(size[0])
nbx = h_w.GetXaxis().FindBin(x)
y = h_w.GetYaxis().GetBinCenter(1) - h_w.GetYaxis().GetBinWidth(1)*0.51 + float(size[1])
nby = h_w.GetYaxis().FindBin(y)
arr_h, pos_h = rootTH2_to_np(h_w, cut=100)
p_max = 0
idx_max = [0, 0]
for iy in range(0, arr_h.shape[0]-nby):
for ix in range(0, arr_h.shape[1]-nbx):
p = np.sum(arr_h[iy:iy+nby, ix:ix+nbx])
if p > p_max:
p_max = p
idx_max = [iy, ix]
avg_prob = p_max/(nbx*nby)
iy, ix = idx_max
# if k == 24:
# ix -= 2
x_start = h.GetXaxis().GetBinCenter(ix+1) - 0.5*h.GetXaxis().GetBinWidth(ix+1)
x_stop = h.GetXaxis().GetBinCenter(ix+nbx) + 0.5*h.GetXaxis().GetBinWidth(ix+nbx)
y_start = h.GetYaxis().GetBinCenter(iy+1) - 0.5*h.GetYaxis().GetBinWidth(iy+1)
y_stop = h.GetYaxis().GetBinCenter(iy+nby) + 0.5*h.GetYaxis().GetBinWidth(iy+nby)
line.SetLineStyle(9)
line.SetLineColor(46)
line.SetLineWidth(2)
line.DrawLine(x_start, y_start, x_stop, y_start)
line.DrawLine(x_start, y_stop, x_stop, y_stop)
line.DrawLine(x_start, y_start, x_start, y_stop)
line.DrawLine(x_stop, y_start, x_stop, y_stop)
conf['SiPM_sel'] = {}
conf['SiPM_sel']['limits'] = [x_start, x_stop, y_start, y_stop]
conf['SiPM_sel']['cut'] = '({y} < {h} && {y} > {l}'.format(y=conf['y_rot'], l=y_start, h=y_stop)
conf['SiPM_sel']['cut'] += ' && {x} < {h} && {x} > {l})'.format(x=conf['x_rot'], l=x_start, h=x_stop)
if 'space_sel' in conf.keys():
x_start, x_stop, y_start, y_stop = conf['space_sel']['limits']
y_sec, y_step = np.linspace(y_start, y_stop, 6, retstep=True)
leg = rt.TLegend(0.7,0.7,0.98,0.93)
can.obj = [leg]
for i_s, (yd, yu) in enumerate(zip(y_sec[:-1], y_sec[1:])):
pad = can.cd(1)
line.SetLineColor(16)
line.SetLineStyle(2)
line.DrawLine(-width+dx, yu, width+dx, yu)
if i_s == 0:
line.DrawLine(-width+dx, yd, width+dx, yd)
h_aux = rt.TProfile('h_aux_strip_'+str(i_s), 'Average amplitude in selected events', N_bins[0], -width+dx, width+dx)
h_aux.SetXTitle('x [mm]')
h_aux.SetYTitle('Average amplitude [mV]')
var_x = var[var.find(':')+1:]
var_y = var[:var.find(':')]
tmp_sel = selection + ' && {y}<{u} && {y}>{d}'.format(y=var_y, u=yu, d=yd)
tmp_sel += ' && {x}<{u} && {x}>{d}'.format(x=var_x, u=x_stop, d=x_start)
chain.Project('h_aux_strip_'+str(i_s), 'amp[' + str(k) + ']' + ':' + var_x, tmp_sel, 'prof')
h_aux.SetStats(0)
h_aux.GetYaxis().SetRangeUser(h_w.GetMinimum(10), 1.15*h_aux.GetMaximum())
pad = can.cd(2)
opt = 'PLC PMC'
if i_s != 0:
opt += ' SAME'
h_aux.Draw(opt)
leg.AddEntry(h_aux, ' y #in [{:.1f}, {:.1f}]'.format(yd, yu), 'l')
can.obj.append(h_aux)
leg.Draw()
can.Update()
can.SaveAs(out_dir + '/PositionXY_amp_weight_ch{:02d}.png'.format(k))
''' -------------Avg integral-----------'''
name = 'h_int_weight_pos_'+str(k)
title = 'Average integral channel {} in selected event'.format(k)
h_w = rt.TH2D(name, title, N_bins[0], -width+dx, width+dx, N_bins[1], -width+dy, width+dy)
h_w.SetXTitle('x [mm]')
h_w.SetYTitle('y [mm]')
h_w.SetZTitle('Average integral [pC]')
weights = '('+ selection +') * -integral[' + str(k) + ']'
chain.Project(name, var, weights)
h_w.Divide(h)
arr, pos = rootTH2_to_np(h_w)
arr = arr[arr!=0]
h_w.GetZaxis().SetRangeUser(np.percentile(arr,10), np.percentile(arr,99))
h_w.SetStats(0)
canvas['int_w_pos'][k] = rt.TCanvas('c_int_w_pos_'+str(k), 'c_int_w_pos_'+str(k), 800, 600)
h_w.DrawCopy('colz')
Set_2D_colz_graphics()
canvas['int_w_pos'][k].Update()
canvas['int_w_pos'][k].SaveAs(out_dir + '/PositionXY_int_weight_ch{:02d}.png'.format(k))
''' -------------Avg risetime-----------'''
name = 'h_risetime_weight_pos_'+str(k)
title = 'Average risetime channel {} in selected event'.format(k)
h_w = rt.TH2D(name, title, N_bins[0], -width+dx, width+dx, N_bins[1], -width+dy, width+dy)
h_w.SetXTitle('x [mm]')
h_w.SetYTitle('y [mm]')
h_w.SetZTitle('Average risetime [mV/ns]')
weights = '('+ selection +') * -risetime[' + str(k) + ']'
chain.Project(name, var, weights)
h_w.Divide(h)
arr, pos = rootTH2_to_np(h_w)
arr = arr[arr!=0]
h_w.GetZaxis().SetRangeUser(np.percentile(arr,10), np.percentile(arr,99))
h_w.SetStats(0)
canvas['int_w_pos'][k] = rt.TCanvas('c_risetime_w_pos_'+str(k), 'c_risetime_w_pos_'+str(k), 800, 600)
h_w.DrawCopy('colz')
Set_2D_colz_graphics()
if not conf['SiPM'] == 'None':
x_start, x_stop, y_start, y_stop = conf['SiPM_sel']['limits']
line.SetLineStyle(9)
line.SetLineColor(46)
line.SetLineWidth(2)
line.DrawLine(x_start, y_start, x_stop, y_start)
line.DrawLine(x_start, y_stop, x_stop, y_stop)
line.DrawLine(x_start, y_start, x_start, y_stop)
line.DrawLine(x_stop, y_start, x_stop, y_stop)
canvas['int_w_pos'][k].Update()
canvas['int_w_pos'][k].SaveAs(out_dir + '/PositionXY_risetime_weight_ch{:02d}.png'.format(k))
'''=========================== End Selections ==========================='''
conf['sel'] = selection
# print conf['sel']
# if 'space_sel' in conf.keys():
# print conf['space_sel']['cut']
'''End of channels selection loop'''
print '\n\n======================= Timing performances loop ==========================='
headout_dir = out_dir
best_result = {}
for k in configurations.ch_ordered:
conf = configurations.channel[k]
if (not 'time' in conf['type']) or conf['idx_ref'] < 0:
continue
print '---> Channel', k
results = []
file_results = open(headout_dir+'/TimeResolution_ch{}.txt'.format(k),'w')
ln = '#avg_time_res, d_avg_time_res, var_time, var_ref, AmpCorrection\n'
file_results.write(ln)
best_result[k] = Bauble()
best_result[k].dT = [-1, -1]
best_result[k].var = [None, None]
best_result[k].AmpCorr = False
ref_type = configurations.channel[conf['idx_ref']]['type']
for v_ref, v_time in itertools.product(configurations.Var[ref_type], configurations.Var['time']):
print 'Running on:', v_time, v_ref
time_var_chref = v_ref+'[{}]'.format(conf['idx_ref'])
time_var = v_time + '[{}]'.format(k)
out_dir = '{}/{}_{}'.format(headout_dir, v_time, v_ref)
if not os.path.exists(out_dir):
os.mkdir(out_dir)
shutil.copy('lib/index.php', out_dir + '/index.php')
var_dT = time_var + ' - ' + v_ref+'[{}]'.format(conf['idx_ref'])
selection = conf['sel'] +' && ' + configurations.channel[conf['idx_ref']]['sel'] + ' && {} != 0'.format(time_var) +' && ' + conf['space_sel']['cut']
if 'TimeRes2DAmp' in configurations.plots:
for kk in configurations.ch_ordered:
if 'amp'+str(k) in configurations.channel[kk]['type']:
conf['amp_channel'] = kk
selection += ' && ' + configurations.channel[kk]['sel']
''' ---- Removing SiPM border ----'''
x1, x2, y1, y2 = configurations.channel[kk]['SiPM_sel']['limits']
s1 = '{y} < {y2}+{d} && {y} > {y1}-{d} && {x} < {x2}+{d} && {x} > {x1}-{d}'
s2 = '{y} < {y2}-{d} && {y} > {y1}+{d} && {x} < {x2}-{d} && {x} > {x1}+{d}'
s = '!({} && !({}))'.format(s1, s2)
# s = '!({})'.format(s1)
# selection += ' && ' + s.format(x=conf['x_rot'], y = conf['y_rot'], d=0.25, x1=x1, x2=x2, y1=y1, y2=y2)
# selection += ' && ' + configurations.channel[kk]['SiPM_sel']['cut']
if args.verbose:
print 'x_var:', conf['x_rot']
print 'y_var:', conf['y_rot']
if chain.GetEntries(selection) < 5:
print 'Not enought stat ({})'.format(chain.GetEntries(selection))
continue
'''=========================== Raw time resolution ==========================='''
if 'TimeResRaw' in configurations.plots:
delta_t = tree2array(chain, var_dT, selection).flatten()
if ( len(delta_t) ==0):
print 'Empty delta'
continue
if os.uname()[1].startswith('lxplus'):
median = np.percentile(delta_t, 50)[0]
width = np.abs(np.percentile(delta_t, 10) - np.percentile(delta_t, 90))[0]
else:
median = np.percentile(delta_t, 50)
width = np.abs(np.percentile(delta_t, 10) - np.percentile(delta_t, 90))
name = 'h_delta_t_raw_'+str(k)
if width == 0:
width = np.std(delta_t)
if width == 0 or np.isnan(width):
width = 0.1
if np.isnan(median):
continue
title = 'Time resolution for channel '+str(k)+', width 10-90 = {:.2f} ns'.format(width)
h = create_TH1D(delta_t, name, title,
binning = [ None, median-2*width, median+2*width],
axis_title = [var_dT + ' [ns]', 'Events'])
rt.gStyle.SetStatX(1.)
canvas['t_res_raw'][k] = rt.TCanvas('c_t_res_raw_'+str(k), 'c_t_res_raw_'+str(k), 800, 600)
h.Fit('gaus', 'LQR','', median-width, median+width)
h = h.DrawCopy('LE')
canvas['t_res_raw'][k].Update()
canvas['t_res_raw'][k].SaveAs(out_dir + '/TimeResolution_raw_ch{:02d}.png'.format(k))
selection += '&& ({v} < {h} && {v} > {l})'.format(v=var_dT, h=median+2*width, l=median-2*width)
if args.verbose:
print 'selection:', selection
'''=========================== Time resolution 2D ==========================='''
if 'TimeResRaw2D' in configurations.plots:
if not 'shape' in conf.keys():
print 'Please specify a shape for ch', k, 'in order to print TimeResRaw2D'
continue
b = [var_dT, conf['x_rot'], conf['y_rot']]
if 'TimeRes2DAmp' in configurations.plots:
for kk in configurations.ch_ordered:
if 'amp'+str(k) in configurations.channel[kk]['type']:
b += ['amp[{}]'.format(kk)]
if len(b) == 3:
b += ['amp[{}]'.format(k)]
data_raw = tree2array(chain, b, selection).view(np.recarray)
data = np.zeros((data_raw.shape[0],3))
if 'TimeRes2DAmp' in configurations.plots:
data = np.zeros((data_raw.shape[0],4))
for iev, d in enumerate(data_raw):
data[iev] = [d[0][0], d[1], d[2], d[3]]
else:
for iev, d in enumerate(data_raw):
data[iev] = [d[0][0], d[1], d[2]]
if ( len(data) ==0):
print 'Empty delta'
continue
bin_width = configurations.space_bin_size
lim = np.array(conf['space_sel']['limits']).astype(np.float)
size = np.array(conf['shape'].split('x')).astype(np.float)
x_sec, x_step = np.linspace(lim[0], lim[1], 1+int(size[0]/bin_width), retstep=True)
y_sec, y_step = np.linspace(lim[2], lim[3], 1+int(size[1]/bin_width), retstep=True)
if lim[1]-lim[0]+2*x_step >= lim[3]-lim[2]+2*y_step:
b = [x_sec.shape[0]+1, lim[0]-x_step, lim[1]+x_step]
space_diff = lim[1]-lim[0]+2*x_step - (lim[3]-lim[2])
adding_steps = int(space_diff/y_step)
if adding_steps%2 == 1:
adding_steps +=1
b += [y_sec.shape[0]-1+adding_steps, lim[2]-y_step*adding_steps/2, lim[3]+y_step*adding_steps/2]
else:
b = [y_sec.shape[0]+1, lim[2]-y_step, lim[3]+y_step]
space_diff = lim[3]-lim[2]+2*y_step - (lim[1]-lim[0])
adding_steps = int(space_diff/x_step)
if adding_steps%2 == 1:
adding_steps +=1
b = [x_sec.shape[0]-1+adding_steps, lim[0]-x_step*adding_steps/2, lim[1]+x_step*adding_steps/2] + b
name = 'h_TimeResRaw2D_ch{:02d}'.format(k)
title = 'Raw time res breakdown ch{:02d}'.format(k)
h_2D_res_raw = rt.TH2D(name, title, b[0], b[1], b[2], b[3], b[4], b[5])
ResRaw = []
if 'TimeRes2DAmp' in configurations.plots:
name = 'h_TimeRes2DAmp_ch{:02d}'.format(k)
title = 'Time resolution amplitude corrected breakdown ch{:02d}'.format(k)
h_2D_res_amp = rt.TH2D(name, title, b[0], b[1], b[2], b[3], b[4], b[5])
ResAmp = []
it = itertools.product(zip(x_sec[:-1], x_sec[1:]), zip(y_sec[:-1], y_sec[1:]))
if not os.path.exists(out_dir + '/TimeResRaw2D_ch{:02d}'.format(k)):
os.mkdir(out_dir + '/TimeResRaw2D_ch{:02d}'.format(k))
shutil.copy('lib/index.php', out_dir + '/TimeResRaw2D_ch{:02d}'.format(k)+'/index.php')
if 'TimeRes2DAmp' in configurations.plots and not os.path.exists(out_dir + '/TimeRes2DAmp_ch{:02d}'.format(k)):
os.mkdir(out_dir + '/TimeRes2DAmp_ch{:02d}'.format(k))
shutil.copy('lib/index.php', out_dir + '/TimeRes2DAmp_ch{:02d}'.format(k)+'/index.php')
for ib, ((xd, xu), (yd, yu)) in enumerate(it):
selx = np.logical_and(data[:,1]>xd, data[:,1]<xu)
sely = np.logical_and(data[:,2]>yd, data[:,2]<yu)
sel = np.logical_and(selx, sely)
if np.sum(sel) < 10:
continue
aux_d = data[sel]
dt = aux_d[:,0]
fill_TimeResHisto(k, dt,
h_2D_res_raw,
ResRaw, 'TimeResRaw2D',
'Raw',
canvas,
not ('TimeRes2DAmp' in configurations.plots))
if 'TimeRes2DAmp' in configurations.plots:
dt_sel = np.logical_and(dt>median-2*width, dt<median+2*width)
amp = aux_d[:,3]
inputs = np.column_stack((np.ones_like(amp), amp, amp**2))
coeff, r, rank, s = np.linalg.lstsq(inputs[dt_sel], dt[dt_sel], rcond=None)
b = [None, None, None, None, median-2*width, median+2*width]
h_TvsA = create_TH2D(np.column_stack((amp, dt)),
'h_TvsA', 'Channel '+str(k),
binning=b,
axis_title=['Amp [mV]', var_dT + ' [ns]']
)
canvas['dt_vs_amp'][k] = rt.TCanvas('dt_vs_amp'+str(k), 'dt_vs_amp'+str(k), 800, 600)
h_TvsA.DrawCopy('colz')
prof = h_TvsA.ProfileX('prof_amp')
prof.SetLineColor(6)
prof.SetLineWidth(2)
prof.DrawCopy('SAMEE1')
f = rt.TF1('amp_fit'+str(k),'[0]+[1]*x+[2]*x^2', np.min(amp), np.max(amp))
for j,a in enumerate(coeff):
f.SetParameter(j, a)
f.SetLineColor(6)
f.SetLineStyle(9)
f.DrawCopy('SAMEL')
canvas['dt_vs_amp'][k].Update()
canvas['dt_vs_amp'][k].SaveAs(out_dir + '/TimeRes2DAmp_ch{:02d}'.format(k)+'/TvsAmp_{}.png'.format(ib))
dt_corr = dt - np.dot(inputs, coeff)
fill_TimeResHisto(k, dt_corr,
h_2D_res_amp,
ResAmp, 'TimeRes2DAmp',
'Amplitude corrected',
canvas)
ResRaw = np.array(ResRaw)
tag = 'TimeResRaw2D_ch{:02d}'.format(k)
canvas['c_'+tag] = rt.TCanvas('c_'+tag, 'c_'+tag, 800, 600)
Set_2D_colz_graphics()
h_2D_res_raw.GetZaxis().SetRangeUser(0.9*np.min(ResRaw[:,0]), 1.1*np.max(ResRaw[:,0]))
h_2D_res_raw.SetStats(0)
h_2D_res_raw.SetYTitle('y [mm]')
h_2D_res_raw.SetXTitle('x [mm]')
h_2D_res_raw.SetZTitle(var_dT+' [ps]')
h_2D_res_raw.DrawCopy('colz')
rt.gStyle.SetPaintTextFormat(".1f");
h_2D_res_raw.DrawCopy('TEXT SAME ERROR')
avg_time_res = np.average(ResRaw[:,0], weights=1./np.square(ResRaw[:,1]))
d_avg_time_res = 1./np.sqrt(np.sum(1./np.square(ResRaw[:,1])))
results.append([avg_time_res, d_avg_time_res, v_time, v_ref, False])
ln = '{:.2f} {:.2f} {} {} {}\n'.format(avg_time_res, d_avg_time_res, v_time, v_ref, False)
file_results.write(ln)
if best_result[k].dT[0] < 0 or best_result[k].dT[0] > avg_time_res:
best_result[k].dT = [avg_time_res, d_avg_time_res]
best_result[k].var = [v_time, v_ref]
best_result[k].AmpCorr = False
msg = 'Avg raw resolution: {:.1f} +/- {:.1f} ps'.format(avg_time_res, d_avg_time_res)
print msg
l = rt.TLatex()
l.SetTextSize(0.04);
l.DrawLatexNDC(0.15, 0.89, msg.replace('+/-', '#pm'))
canvas['c_'+tag].Update()
canvas['c_'+tag].SaveAs(out_dir + '/TimeResRaw2D_ch{:02d}.png'.format(k))
if 'TimeRes2DAmp' in configurations.plots:
ResAmp = np.array(ResAmp)
tag = 'TimeRes2DAmp_ch{:02d}'.format(k)
canvas['c_'+tag] = rt.TCanvas('c_'+tag, 'c_'+tag, 800, 600)
Set_2D_colz_graphics()
h_2D_res_amp.SetStats(0)
h_2D_res_amp.SetYTitle('y [mm]')
h_2D_res_amp.SetXTitle('x [mm]')
h_2D_res_amp.SetZTitle(var_dT+' [ps]')
h_2D_res_amp.Draw('colz')
rt.gStyle.SetPaintTextFormat(".1f");
h_2D_res_amp.DrawCopy('TEXT SAME ERROR')
median = np.percentile(ResAmp[:, 0], 50)
width = np.percentile(ResAmp[:, 0], 90) - np.percentile(ResAmp[:, 0], 10)
sel = np.logical_and(ResAmp[:, 0] < median+2*width, ResAmp[:, 0] > median-2*width)
if np.sum(np.logical_not(sel)):
print 'Discarting outlayers'
print ResAmp[np.logical_not(sel),0]
ResAmp = ResAmp[sel]
h_2D_res_amp.GetZaxis().SetRangeUser(0.9*np.min(ResAmp[:,0]), 1.1*np.max(ResAmp[:,0]))
avg_time_res = np.average(ResAmp[:,0], weights=1./np.square(ResAmp[:,1]))
d_avg_time_res = 1./np.sqrt(np.sum(1./np.square(ResAmp[:,1])))