/
CompareRuns.py
executable file
·383 lines (356 loc) · 21.2 KB
/
CompareRuns.py
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#!/usr/bin/env python
import ROOT as ro
import numpy as np
import ipdb, os
import itertools as itt
from TransparentGrid import TransparentGrid
from TestAreas import TestAreas
from optparse import OptionParser
from Utils import *
from ConfigParser import ConfigParser
color_index = 0
hspace = 0.1
vspace = 0.0
class CompareRuns:
def __init__(self, config_file=''):
self.config_file = config_file
# self.runlist = []
self.outdir = '.'
self.runs_path = {}
self.runs_settings = {}
self.run_numbers = []
self.runs_subidr = {}
# self.col_pitch = col_pitch
# self.numstrips = numstrips
self.testnum = 0
self.ReadCompareConfig()
self.subdir = 'test' + str(self.testnum)
self.do_fit = False
self.min_sat_ev, self.min_not_sat_ev, self.min_sat_norm, self.min_not_sat_norm, self.min_sat_tnorm, self.min_not_sat_tnorm = -1, -1, -1, -1, -1, -1
self.max_sat_ev, self.max_not_sat_ev, self.max_sat_norm, self.max_not_sat_norm, self.max_sat_tnorm, self.max_not_sat_tnorm = -1, -1, -1, -1, -1, -1
# self.ReadRunList()
self.runs_ta = {}
self.canvas = {}
self.histo = {}
self.sat_adc_dic = {}
self.bias_dic = {}
self.stuff = []
self.LoadRuns()
self.run_colors = {run: ro.TColor(color_index + run, ReturnRGB(run, min(self.run_numbers), max(self.run_numbers))[0], ReturnRGB(run, min(self.run_numbers), max(self.run_numbers))[1], ReturnRGB(run, min(self.run_numbers), max(self.run_numbers))[2]) for run in self.run_numbers}
self.numruns = len(self.run_numbers)
self.run_pairs_comb = [[run1, run2] for run1, run2 in itt.combinations(self.run_numbers, 2)]
# self.CompareAllPairs('ph1_{t}'.format(t=self.subdir))
# self.CompareAllPairs('ph1_{t}'.format(t=self.subdir), do_norm=True)
# self.CompareAllPairs('ph2_{t}'.format(t=self.subdir))
# self.CompareAllPairs('ph2_{t}'.format(t=self.subdir), do_norm=True)
# self.CompareAllPairs('PH_Saturated_Events')
# self.CompareAllPairs('PH_Saturated_Events', do_norm=True)
# self.SaveCanvasInList(self.canvas.keys())
def ReadCompareConfig(self):
if os.path.isfile(self.config_file):
pars = ConfigParser()
pars.read(self.config_file)
print 'Reading config file for comparing runs...', ; sys.stdout.flush()
if pars.has_section('RUNS'):
if pars.has_option('RUNS', 'rundirs'):
temp_dirs = pars.get('RUNS', 'rundirs')
elements = temp_dirs.replace('{', '').replace('}', '')
elements = elements.split(',')
temp_runs_path = [Correct_Path(element) for element in elements if os.path.isdir(Correct_Path(element)) and (len(element) > 2)]
self.run_numbers = np.array([int(runpath.split('/')[-1]) for runpath in temp_runs_path], 'uint32')
self.runs_path = {self.run_numbers[i]: temp_runs_path[i] for i in xrange(len(temp_runs_path))}
self.runs_subidr = {run: path.split('/' + str(run))[0] for run, path in self.runs_path.iteritems()}
if pars.has_option('RUNS', 'settings'):
temp_setts = pars.get('RUNS', 'settings')
elements = temp_setts.replace('{', '').replace('}', '')
elements = elements.split(',')
self.runs_settings = [Correct_Path(element) for element in elements if os.path.isfile(Correct_Path(element)) and (len(element) > 2)]
if pars.has_option('RUNS', 'outdir'):
temp_outdir = pars.get('RUNS', 'outdir')
self.outdir = Correct_Path(temp_outdir)
if pars.has_option('RUNS', 'do_fit'):
self.do_fit = pars.getboolean('RUNS', 'do_fit')
if pars.has_option('RUNS', 'testnum'):
self.testnum = pars.getint('RUNS', 'testnum')
if pars.has_section('SATURATION'):
if pars.has_option('SATURATION', 'min_sat_ev'):
self.min_sat_ev = pars.getfloat('SATURATION', 'min_sat_ev')
if pars.has_option('SATURATION', 'min_not_sat_ev'):
self.min_not_sat_ev = pars.getfloat('SATURATION', 'min_not_sat_ev')
if pars.has_option('SATURATION', 'min_sat_norm'):
self.min_sat_norm = pars.getfloat('SATURATION', 'min_sat_norm')
if pars.has_option('SATURATION', 'min_not_sat_norm'):
self.min_not_sat_norm = pars.getfloat('SATURATION', 'min_not_sat_norm')
if pars.has_option('SATURATION', 'min_sat_tnorm'):
self.min_sat_tnorm = pars.getfloat('SATURATION', 'min_sat_tnorm')
if pars.has_option('SATURATION', 'min_not_sat_tnorm'):
self.min_not_sat_tnorm = pars.getfloat('SATURATION', 'min_not_sat_tnorm')
if pars.has_option('SATURATION', 'max_sat_ev'):
self.max_sat_ev = pars.getfloat('SATURATION', 'max_sat_ev')
if pars.has_option('SATURATION', 'max_not_sat_ev'):
self.max_not_sat_ev = pars.getfloat('SATURATION', 'max_not_sat_ev')
if pars.has_option('SATURATION', 'max_sat_norm'):
self.max_sat_norm = pars.getfloat('SATURATION', 'max_sat_norm')
if pars.has_option('SATURATION', 'max_not_sat_norm'):
self.max_not_sat_norm = pars.getfloat('SATURATION', 'max_not_sat_norm')
if pars.has_option('SATURATION', 'max_sat_tnorm'):
self.max_sat_tnorm = pars.getfloat('SATURATION', 'max_sat_tnorm')
if pars.has_option('SATURATION', 'max_not_sat_tnorm'):
self.max_not_sat_tnorm = pars.getfloat('SATURATION', 'max_not_sat_tnorm')
print 'Done'
def LoadRuns(self):
for run in self.run_numbers:
if os.path.isdir(self.runs_path[run]):
# self.runs_ta[run] = TestAreas(self.testnum, self.numstrips, self.runs_subidr[it], run, self.col_pitch, self.do_fit)
self.runs_ta[run] = TestAreas(self.runs_settings[0], run)
self.runs_ta[run].SetTransparentGrid()
self.runs_ta[run].SetTest()
self.runs_ta[run].trans_grid.LoadPlotsInSubdir()
self.sat_adc_dic[run] = self.runs_ta[run].saturated_ADC
self.bias_dic[run] = self.runs_ta[run].bias
def CompareAllPairs(self, histoname='ph2_test1', do_norm=False, plot_option='e hist'):
for it, (run1, run2) in enumerate(self.run_pairs_comb):
self.PlotPairs(run1, run2, histoname, do_norm, plot_option)
def PlotPairs(self, run1, run2, histoname='ph2_test1', do_norm=False, plot_option='e hist'):
tg1, tg2 = self.runs_ta[run1].trans_grid, self.runs_ta[run2].trans_grid
suffix = '' if not do_norm else '_norm'
if tg1.histo.has_key(histoname) and tg2.histo.has_key(histoname):
new_name = histoname + '_{r1}_&_{r2}'.format(r1=run1, r2=run2) + suffix
histo1name = histoname + '_' + str(run1)
histo2name = histoname + '_' + str(run2)
if not self.histo.has_key(histo1name):
histo1 = tg1.histo[histoname]
histo1.SetNameTitle(histo1name, histo1name)
self.histo[histo1name] = histo1
if not self.histo.has_key(histo2name):
histo2 = tg2.histo[histoname]
histo2.SetNameTitle(histo2name, histo2name)
self.histo[histo2name] = histo2
histo1 = self.histo[histo1name].Clone(histoname + '_{r1}_not{r2}'.format(r1=run1, r2=run2) + suffix)
histo2 = self.histo[histo2name].Clone(histoname + '_{r2}_not{r1}'.format(r1=run1, r2=run2) + suffix)
if do_norm:
histo1.Sumw2(True)
histo2.Sumw2(True)
histo1.Scale(1.0 / histo1.Integral())
histo2.Scale(1.0 / histo2.Integral())
histo1.GetYaxis().SetTitle('norm. to 1')
histo2.GetYaxis().SetTitle('norm. to 1')
histo1.SetLineColor(self.run_colors[run1].GetNumber())
histo1.SetMarkerColor(self.run_colors[run1].GetNumber())
histo2.SetLineColor(self.run_colors[run2].GetNumber())
histo2.SetMarkerColor(self.run_colors[run2].GetNumber())
self.canvas[new_name] = ro.TCanvas('c_' + new_name, 'c_' + new_name, 1)
self.canvas[new_name].SetGridx()
self.canvas[new_name].SetGridy()
self.canvas[new_name].SetTicky()
ro.gStyle.SetOptTitle(0)
hmax = histo1.GetBinContent(histo1.GetMaximumBin()) if histo1.GetBinContent(histo1.GetMaximumBin()) >= histo2.GetBinContent(histo2.GetMaximumBin()) else histo2.GetBinContent(histo2.GetMaximumBin())
histo1.Draw(plot_option)
histo2.Draw(plot_option + 'sames')
# histo1.GetYaxis().SetRangeUser(0, 0.8 * hmax / ((1 - vspace - 0.3) - 0.1))
histo1.GetYaxis().SetRangeUser(0, 0.8 * hmax / ((0.9) * 0.8))
histo2.GetYaxis().SetRangeUser(0, 0.8 * hmax / ((0.9) * 0.8))
histo2.FindObject('stats').SetY2NDC(0.6)
histo2.FindObject('stats').SetY1NDC(0.3)
ro.gPad.Update()
legend = self.canvas[new_name].BuildLegend()
ro.gPad.Update()
legend.SetX1NDC(0.6)
legend.SetX2NDC(0.9)
legend.SetY1NDC(0.2)
legend.SetY2NDC(0.3)
ro.gPad.Update()
self.stuff.append(histo1)
self.stuff.append(histo2)
def PlotSaturationEvents(self):
tg_dic = {run: self.runs_ta[run].trans_grid for run in self.run_numbers}
saturated = {}
saturated_err = {}
not_saturated = {}
not_saturated_err = {}
all_cells_hits = {}
all_cells_hits_err = {}
saturated_norm = {}
saturated_err_norm = {}
not_saturated_norm = {}
not_saturated_err_norm = {}
saturated_norm_tracks = {}
saturated_norm_tracks_err = {}
not_saturated_norm_tracks = {}
not_saturated_norm_tracks_err = {}
saturated_cuts = {}
not_saturated_cuts = {}
for run, tg in tg_dic.iteritems():
num_strips_tree = int(tg.trans_tree.GetMaximum('numStrips'))
satChs = '(' + '||'.join(['(diaChADC[clusterChannel{i}]==4095)'.format(i=i) for i in xrange(num_strips_tree)]) + ')'
notSatChs = '(' + '&&'.join(['(diaChADC[clusterChannel{i}]<4095)'.format(i=i) for i in xrange(num_strips_tree)]) + ')'
areaCut = '({c})'.format(c=tg.gridAreas.goodAreasCutNames_simplified_diamond)
allCells = '(({c})||({nc}))'.format(c=tg.gridAreas.goodAreasCutNames_simplified_diamond, nc=tg.gridAreas.badAreasCutNames_simplified_diamond)
listSat = ['(transparentEvent)', satChs, areaCut]
listNoSat = ['(transparentEvent)', notSatChs, areaCut]
listAllCells = ['(transparentEvent)', allCells]
saturated[run] = tg.trans_tree.Draw('clusterChargeN', '(' + '&&'.join(listSat) + ')', 'goff')
saturated_err[run] = np.sqrt(saturated[run])
not_saturated[run] = tg.trans_tree.Draw('clusterChargeN', '(' + '&&'.join(listNoSat) + ')', 'goff')
not_saturated_err[run] = np.sqrt(not_saturated[run])
all_cells_hits[run] = tg.trans_tree.Draw('clusterChargeN', '(' + '&&'.join(listAllCells) + ')', 'goff')
all_cells_hits_err[run] = np.sqrt(all_cells_hits[run])
saturated_norm[run] = np.divide(saturated[run], saturated[run] + not_saturated[run], dtype='f8')
saturated_err_norm[run] = np.divide(np.sqrt(np.power(not_saturated[run] * saturated_err[run], 2, dtype='f8') + np.power(saturated[run] * not_saturated_err[run], 2, dtype='f8'), dtype='f8'), np.power(saturated[run] + not_saturated[run], 2), dtype='f8')
not_saturated_norm[run] = np.divide(not_saturated[run], saturated[run] + not_saturated[run], dtype='f8')
not_saturated_err_norm[run] = np.divide(np.sqrt(np.power(not_saturated[run] * saturated_err[run], 2, dtype='f8') + np.power(saturated[run] * not_saturated_err[run], 2, dtype='f8'), dtype='f8'), np.power(saturated[run] + not_saturated[run], 2), dtype='f8')
saturated_norm_tracks[run] = np.divide(saturated[run], all_cells_hits[run], dtype='f8')
saturated_norm_tracks_err[run] = np.divide(np.sqrt(np.power(saturated_err[run], 2, dtype='f8') + np.power(np.divide(saturated[run] * all_cells_hits_err[run], all_cells_hits[run], dtype='f8'), 2, dtype='f8'), dtype='f8'), all_cells_hits[run], dtype='f8')
not_saturated_norm_tracks[run] = np.divide(not_saturated[run], all_cells_hits[run], dtype='f8')
not_saturated_norm_tracks_err[run] = np.divide(np.sqrt(np.power(not_saturated_err[run], 2, dtype='f8') + np.power(np.divide(not_saturated[run] * all_cells_hits_err[run], all_cells_hits[run], dtype='f8'), 2, dtype='f8'), dtype='f8'), all_cells_hits[run], dtype='f8')
xvals = np.array([self.bias_dic[run] for run in self.run_numbers], 'f8')
y_sat_values = np.array([saturated[run] for run in self.run_numbers], 'f8')
y_sat_values_err = np.array([saturated_err[run] for run in self.run_numbers], 'f8')
y_not_sat_values = np.array([not_saturated[run] for run in self.run_numbers], 'f8')
y_not_sat_values_err = np.array([not_saturated_err[run] for run in self.run_numbers], 'f8')
y_sat_values_norm = np.array([saturated_norm[run] for run in self.run_numbers], 'f8')
y_sat_values_err_norm = np.array([saturated_err_norm[run] for run in self.run_numbers], 'f8')
y_not_sat_values_norm = np.array([not_saturated_norm[run] for run in self.run_numbers], 'f8')
y_not_sat_values_err_norm = np.array([not_saturated_err_norm[run] for run in self.run_numbers], 'f8')
y_sat_values_tracks_norm = np.array([saturated_norm_tracks[run] for run in self.run_numbers], 'f8')
y_sat_values_err_tracks_norm = np.array([saturated_norm_tracks_err[run] for run in self.run_numbers], 'f8')
y_not_sat_values_tracks_norm = np.array([not_saturated_norm_tracks[run] for run in self.run_numbers], 'f8')
y_not_sat_values_err_tracks_norm = np.array([not_saturated_norm_tracks_err[run] for run in self.run_numbers], 'f8')
max0 = np.max([y_sat_values.max() + 2 * y_sat_values_err.max(), y_not_sat_values.max() + 2 * y_not_sat_values_err.max()])
min0 = 0
# maxn = np.min([1, 2 * np.max([y_sat_values_norm.max() + y_sat_values_err_norm.max(), y_not_sat_values_norm.max() + y_not_sat_values_err_norm.max()])])
# minn = np.max([0, 2 * np.min([y_sat_values_norm.min() - y_sat_values_err_norm.max(), y_not_sat_values_norm.min() - y_not_sat_values_err_norm.max()]) - 1])
# maxnt = np.min([1, 2 * np.max([y_sat_values_tracks_norm.max() + y_sat_values_err_tracks_norm.max(), y_not_sat_values_tracks_norm.max() + y_not_sat_values_err_tracks_norm.max()])])
# minnt = np.max([0, 2 * np.min([y_sat_values_tracks_norm.min() - y_sat_values_err_tracks_norm.max(), y_not_sat_values_tracks_norm.min() - y_not_sat_values_err_tracks_norm.max()]) - 1])
maxn = np.min([1, np.max([y_sat_values_norm.max() + 2 * y_sat_values_err_norm.max(), y_not_sat_values_norm.max() + 2 * y_not_sat_values_err_norm.max()])])
minn = np.max([0, np.min([y_sat_values_norm.min() - 2 * y_sat_values_err_norm.max(), y_not_sat_values_norm.min() - 2 * y_not_sat_values_err_norm.max()])])
maxnt = np.min([1, np.max([y_sat_values_tracks_norm.max() + 2 * y_sat_values_err_tracks_norm.max(), y_not_sat_values_tracks_norm.max() + 2 * y_not_sat_values_err_tracks_norm.max()])])
minnt = np.max([0, np.min([y_sat_values_tracks_norm.min() - 2 * y_sat_values_err_tracks_norm.max(), y_not_sat_values_tracks_norm.min() - 2 * y_not_sat_values_err_tracks_norm.max()])])
graph_sat = ro.TGraphErrors(len(self.run_numbers), xvals, y_sat_values, np.zeros(len(self.run_numbers), 'f8'), y_sat_values_err)
satname = 'SaturatedAfterCuts'
graph_sat.SetNameTitle(satname, satname)
graph_sat.GetXaxis().SetTitle('bias [V]')
graph_sat.GetYaxis().SetTitle('# events')
min0sat = min0 if self.min_sat_ev == -1 else self.min_sat_ev
max0sat = max0 if self.max_sat_ev == -1 else self.max_sat_ev
graph_sat.GetYaxis().SetRangeUser(min0sat, max0sat)
graph_sat.SetMarkerStyle(8)
graph_sat.SetMarkerColor(ro.kRed)
graph_sat.SetLineColor(ro.kRed)
graph_nosat = ro.TGraphErrors(len(self.run_numbers), xvals, y_not_sat_values, np.zeros(len(self.run_numbers), 'f8'), y_not_sat_values_err)
notsatname = 'NotSaturatedAfterCuts'
graph_nosat.SetNameTitle(notsatname, notsatname)
graph_nosat.GetXaxis().SetTitle('bias [V]')
graph_nosat.GetYaxis().SetTitle('# events')
min0notsat = min0 if self.min_not_sat_ev == -1 else self.min_not_sat_ev
max0notsat = max0 if self.max_not_sat_ev == -1 else self.max_not_sat_ev
graph_nosat.GetYaxis().SetRangeUser(min0notsat, max0notsat)
graph_nosat.SetMarkerStyle(8)
graph_nosat.SetMarkerColor(ro.kBlue)
graph_nosat.SetLineColor(ro.kBlue)
graph_sat_norm = ro.TGraphErrors(len(self.run_numbers), xvals, y_sat_values_norm, np.zeros(len(self.run_numbers), 'f8'), y_sat_values_err_norm)
satnamenorm = 'SaturatedAfterCutsNorm'
graph_sat_norm.SetNameTitle(satnamenorm, satnamenorm)
graph_sat_norm.GetXaxis().SetTitle('bias [V]')
graph_sat_norm.GetYaxis().SetTitle('norm')
minnsat = minn if self.min_sat_norm == -1 else self.min_sat_norm
maxnsat = maxn if self.max_sat_norm == -1 else self.max_sat_norm
graph_sat_norm.GetYaxis().SetRangeUser(minnsat, maxnsat)
graph_sat_norm.SetMarkerStyle(8)
graph_sat_norm.SetMarkerColor(ro.kRed)
graph_sat_norm.SetLineColor(ro.kRed)
graph_nosat_norm = ro.TGraphErrors(len(self.run_numbers), xvals, y_not_sat_values_norm, np.zeros(len(self.run_numbers), 'f8'), y_not_sat_values_err_norm)
notsatnamenorm = 'NotSaturatedAfterCutsNorm'
graph_nosat_norm.SetNameTitle(notsatnamenorm, notsatnamenorm)
graph_nosat_norm.GetXaxis().SetTitle('bias [V]')
graph_nosat_norm.GetYaxis().SetTitle('norm')
minnnotsat = minn if self.min_not_sat_norm == -1 else self.min_not_sat_norm
maxnnotsat = maxn if self.max_not_sat_norm == -1 else self.max_not_sat_norm
graph_nosat_norm.GetYaxis().SetRangeUser(minnnotsat, maxnnotsat)
graph_nosat_norm.SetMarkerStyle(8)
graph_nosat_norm.SetMarkerColor(ro.kBlue)
graph_nosat_norm.SetLineColor(ro.kBlue)
graph_sat_norm_tracks = ro.TGraphErrors(len(self.run_numbers), xvals, y_sat_values_tracks_norm, np.zeros(len(self.run_numbers), 'f8'), y_sat_values_err_tracks_norm)
satnamenormtracks = 'SaturatedAfterCutsDiaTracksNorm'
graph_sat_norm_tracks.SetNameTitle(satnamenormtracks, satnamenormtracks)
graph_sat_norm_tracks.GetXaxis().SetTitle('bias [V]')
graph_sat_norm_tracks.GetYaxis().SetTitle('dia_tracks_norm')
minntsat = minn if self.min_sat_tnorm == -1 else self.min_sat_tnorm
maxntsat = maxn if self.max_sat_tnorm == -1 else self.max_sat_tnorm
graph_sat_norm_tracks.GetYaxis().SetRangeUser(minntsat, maxntsat)
graph_sat_norm_tracks.SetMarkerStyle(8)
graph_sat_norm_tracks.SetMarkerColor(ro.kRed)
graph_sat_norm_tracks.SetLineColor(ro.kRed)
graph_nosat_norm_tracks = ro.TGraphErrors(len(self.run_numbers), xvals, y_not_sat_values_tracks_norm, np.zeros(len(self.run_numbers), 'f8'), y_not_sat_values_err_tracks_norm)
notsatnamenormtracks = 'NotSaturatedAfterCutsDiaTracksNorm'
graph_nosat_norm_tracks.SetNameTitle(notsatnamenormtracks, notsatnamenormtracks)
graph_nosat_norm_tracks.GetXaxis().SetTitle('bias [V]')
graph_nosat_norm_tracks.GetYaxis().SetTitle('dia_tracks_norm')
minntnotsat = minn if self.min_not_sat_tnorm == -1 else self.min_not_sat_tnorm
maxntnotsat = maxn if self.max_not_sat_tnorm == -1 else self.max_not_sat_tnorm
graph_nosat_norm_tracks.GetYaxis().SetRangeUser(minntnotsat, maxntnotsat)
graph_nosat_norm_tracks.SetMarkerStyle(8)
graph_nosat_norm_tracks.SetMarkerColor(ro.kBlue)
graph_nosat_norm_tracks.SetLineColor(ro.kBlue)
self.canvas[satname] = ro.TCanvas('c_' + satname, 'c_' + satname, 1)
self.canvas[satname].SetGridx()
self.canvas[satname].SetGridy()
self.canvas[satname].SetTicky()
graph_sat.Draw('ALP')
self.canvas[notsatname] = ro.TCanvas('c_' + notsatname, 'c_' + notsatname, 1)
self.canvas[notsatname].SetGridx()
self.canvas[notsatname].SetGridy()
self.canvas[notsatname].SetTicky()
graph_nosat.Draw('ALP')
self.canvas[satnamenorm] = ro.TCanvas('c_' + satnamenorm, 'c_' + satnamenorm, 1)
self.canvas[satnamenorm].SetGridx()
self.canvas[satnamenorm].SetGridy()
self.canvas[satnamenorm].SetTicky()
graph_sat_norm.Draw('ALP')
self.canvas[notsatnamenorm] = ro.TCanvas('c_' + notsatnamenorm, 'c_' + notsatnamenorm, 1)
self.canvas[notsatnamenorm].SetGridx()
self.canvas[notsatnamenorm].SetGridy()
self.canvas[notsatnamenorm].SetTicky()
graph_nosat_norm.Draw('ALP')
self.canvas[satnamenormtracks] = ro.TCanvas('c_' + satnamenormtracks, 'c_' + satnamenormtracks, 1)
self.canvas[satnamenormtracks].SetGridx()
self.canvas[satnamenormtracks].SetGridy()
self.canvas[satnamenormtracks].SetTicky()
graph_sat_norm_tracks.Draw('ALP')
self.canvas[notsatnamenormtracks] = ro.TCanvas('c_' + notsatnamenormtracks, 'c_' + notsatnamenormtracks, 1)
self.canvas[notsatnamenormtracks].SetGridx()
self.canvas[notsatnamenormtracks].SetGridy()
self.canvas[notsatnamenormtracks].SetTicky()
graph_nosat_norm_tracks.Draw('ALP')
self.stuff.append(graph_sat)
self.stuff.append(graph_nosat)
self.stuff.append(graph_sat_norm)
self.stuff.append(graph_nosat_norm)
self.stuff.append(graph_sat_norm_tracks)
self.stuff.append(graph_nosat_norm_tracks)
def SaveCanvasInList(self, list):
if not os.path.isdir('{d}/{sd}'.format(d=self.outdir, sd=self.subdir)):
os.makedirs('{d}/{sd}'.format(d=self.outdir, sd=self.subdir))
for canvas in list:
if self.canvas.has_key(canvas):
if self.canvas[canvas]:
self.canvas[canvas].SaveAs('{d}/{sd}/{c}.png'.format(d=self.outdir, sd=self.subdir, c=canvas))
self.canvas[canvas].SaveAs('{d}/{sd}/{c}.root'.format(d=self.outdir, sd=self.subdir, c=canvas))
if __name__ == '__main__':
parser = OptionParser()
parser.add_option('-c', '--config', dest='config', type='string', help='Path to config file for comparing runs')
# parser.add_option('-r', '--runlist', dest='runlist', type='string', help='Path to the file containing the list of runs')
# parser.add_option('-o', '--outdir', dest='outdir', type='string', default='.' ,help='Path to the directory where the files will be saved')
# parser.add_option('-c', '--col_pitch', dest='col_pitch', type='int', default=50, help='cell size of the square 3D device')
# parser.add_option('-n', '--numstrips', dest='numstrips', type='int', default=2, help='Number of strips to use')
# parser.add_option('-t', '--test', dest='testnumber', type='int', default=1, help='Run a automatically one of the predefined tests')
# parser.add_option('-f', '--dofit', dest='dofit', default=False, action='store_true', help='Enables fitting')
(options, args) = parser.parse_args()
config = str(options.config)
# runlist = str(options.runlist)
# outdir = str(options.outdir)
# col_pitch = int(options.col_pitch)
# numstrips = int(options.numstrips)
# testnum = int(options.testnumber)
# do_fit = bool(options.dofit)
c = CompareRuns(config)