def main():
file_names = glob.glob(
'/Users/liberulo/kek/csibpm/data/20170825/hot_pixel/L_foc/*.root')
# file_names += glob.glob('/Users/liberulo/kek/csibpm/data/20170828/hot_pixel/*.root')
print '{} files are found.'.format(len(file_names))
#
hx = []
mean = []
for fname in file_names:
hx.append(
itst.get_projection(fname,
250,
700,
isDraw=False,
isRoundAndCenterd=False))
mean.append(get_mean(fname))
for h in hx:
h[0].Rebin(16)
ymin = min([x[0].GetMinimum() for x in hx])
ymax = max([x[0].GetMaximum() for x in hx])
# Fitting
ff = itst.get_gausses(file_names, mean=mean)
for i, f in enumerate(ff):
hx[i][0].Fit(f, 'r', 'goff')
ff2 = itst.get_2gausses(file_names, ff)
for i, f in enumerate(ff2):
hx[i][0].Fit(f, 'r +', 'goff')
# Tree production
Fout = r.TFile('~/kek/csibpm/data/diff_L.root', 'recreate')
tout = itst.get_tree(hx, ff, ff2)
print 'The tree contains {} entries.'.format(tout.GetEntries())
tout.Write()
Fout.Close()
def main():
sett = 'one'
sett = 'all'
if sett == 'one':
file_names = glob.glob('data/2017081?/hot_pixel/*min*40cm2.root')
elif sett == 'all':
file_names = glob.glob('data/201708[12]?/hot_pixel/*min*.root')
file_names.remove(
'data/20170817/hot_pixel/5min1pic40cm.root') # light leak
file_names.remove(
'data/20170817/hot_pixel/10min1pic40cm.root') # light leak
else:
return 1
#
hx = []
for fname in file_names:
hx.append(itst.get_projection(fname, 400, 800, isDraw=False))
for h in hx:
h[0].Rebin(16)
ymin = min([x[0].GetMinimum() for x in hx])
ymax = max([x[0].GetMaximum() for x in hx])
# Fitting
ff = itst.get_gausses(file_names)
for i, f in enumerate(ff):
hx[i][0].Fit(f, 'r', 'goff')
# subtract_baseline(hx[i][0], f.GetParameter(3))
# f.SetParameter(3, 0.)
ff2 = itst.get_2gausses(file_names, ff)
for i, f in enumerate(ff2):
hx[i][0].Fit(f, 'r +', 'goff')
# Drawing
c1 = r.TCanvas('c1', 'x projections', 800, 600)
hx[0][0].Draw('e')
for h in hx[1:]:
h[0].Draw('e same')
lat = r.TLatex()
lat.SetTextSize(.025)
for i, hh in enumerate(hx):
lat.SetTextColor(itst.clrs[i])
lat.DrawLatexNDC(.65, .95 - .04 * i, hh[0].GetName())
ax, ay = hx[0][0].GetXaxis(), hx[0][0].GetYaxis()
ay.SetRangeUser(ymin, ymax * 1.05)
for f in ff:
f.Draw('same')
for f in ff2:
f.Draw('same')
c1.Update()
# Print results
# c2 = itst.get_trend_plot(ff, 1, 'mean')
# c3 = itst.get_trend_plot(ff, 2, 'sigma')
# c4 = itst.get_trend_plot(ff, 0, 'Amplitude')
# I vs L
c_I_vs_L = itst.get_intensity_vs_distance(hx)
raw_input('Press ENTER to continue, please.')
def main():
file_names = glob.glob('data/20170823/hot_pixel/*min*.root')
#
hx = []
for fname in file_names:
hx.append( itst.get_projection(fname, 350, 800, isDraw=False) )
for h in hx:
h[0].Rebin(16)
ymin = min([x[0].GetMinimum() for x in hx])
ymax = max([x[0].GetMaximum() for x in hx])
# Fitting
ff = itst.get_gausses(file_names)
for i, f in enumerate(ff):
hx[i][0].Fit(f, 'r', 'goff')
ff2 = itst.get_2gausses(file_names, ff)
for i, f in enumerate(ff2):
hx[i][0].Fit(f, 'r +', 'goff')
# Tree production
Fout = r.TFile('data/kinetic_alpha.root', 'recreate')
tout = itst.get_tree(hx, ff, ff2)
tout.Write()
Fout.Close()
def main():
# file_names = glob.glob('/Users/liberulo/kek/csibpm/data/20170808/hot_pixel/*.root')
# file_names += glob.glob('/Users/liberulo/kek/csibpm/data/20170809/hot_pixel/*.root')
file_names = glob.glob('data/20170821/hot_pixel/*_s*.root')
print '{} files are found.'.format(len(file_names))
#
hx = []
mean = []
for fname in file_names:
# hx.append( itst.get_projection(fname, 500, 1100, isDraw=False,
hx.append(
itst.get_projection(
fname,
550,
800,
isDraw=False,
# isRoundAndCenterd=True) )
isRoundAndCenterd=False))
mean.append(get_mean(fname))
for h in hx:
h[0].Rebin(16)
ymin = min([x[0].GetMinimum() for x in hx])
ymax = max([x[0].GetMaximum() for x in hx])
# Fitting
ff = itst.get_gausses(file_names, mean=mean)
for i, f in enumerate(ff):
print bcolors.HEADER + 'Fit', f.GetName(), bcolors.ENDC
hx[i][0].Fit(f, 'r', 'goff')
ff2 = itst.get_2gausses(file_names, ff)
for i, f in enumerate(ff2):
hx[i][0].Fit(f, 'r +', 'goff')
# Tree production
# Fout = r.TFile('~/kek/csibpm/data/diff_exp_time.root', 'recreate')
Fout = r.TFile('data/stat_error.root', 'recreate')
tout = itst.get_tree(hx, ff, ff2)
print 'The tree contains {} entries.'.format(tout.GetEntries())
tout.Write()
Fout.Close()
def main():
if len(sys.argv) > 1:
file_names = sys.argv[1:]
else:
file_names = glob.glob('data/2017081?/hot_pixel/*min*.root')
file_names.remove('data/20170817/hot_pixel/5min1pic40cm.root')# light leak
file_names += glob.glob('data/20170821/hot_pixel/*min*.root')
file_names += glob.glob('data/20170808/hot_pixel/*min*cm*.root')
#
hx = []
for fname in file_names:
hx.append( itst.get_projection(fname, 400, 800, isDraw=False) )
for h in hx:
h[0].Rebin(16)
ymin = min([x[0].GetMinimum() for x in hx])
ymax = max([x[0].GetMaximum() for x in hx])
# Fitting
ff = itst.get_gausses(file_names)
for i, f in enumerate(ff):
hx[i][0].Fit(f, 'r', 'goff')
# subtract_baseline(hx[i][0], f.GetParameter(3))
# f.SetParameter(3, 0.)
ff2 = itst.get_2gausses(file_names, ff)
for i, f in enumerate(ff2):
hx[i][0].Fit(f, 'r +', 'goff')
# Drawing
c1 = r.TCanvas('c1', 'x projections', 800, 600)
hx[0][0].Draw('e')
for h in hx[1:]:
h[0].Draw('e same')
lat = r.TLatex()
lat.SetTextSize(.03)
for i, hh in enumerate(hx):
lat.SetTextColor(itst.clrs[i])
lat.DrawLatexNDC(.75, .95-.04*i, hh[0].GetName())
ax, ay = hx[0][0].GetXaxis(), hx[0][0].GetYaxis()
ay.SetRangeUser(ymin, ymax*1.05)
ay.SetTitle('Number of CCD electrons')
ax.SetTitle('X direction, pixels')
line = r.TLine()
line.SetLineWidth(1)
# Drawing constant lines
for i, f in enumerate(ff):
f.Draw('same')
ff2[i].Draw('same')
line.SetLineColor(itst.clrs[i])
line.SetLineStyle(1)
p = f.GetParameters()
line.DrawLine(p[1]-3*p[2], p[3], p[1]+3*p[2], p[3])
line.SetLineStyle(2)
p = ff2[i].GetParameters()
line.DrawLine(p[1]-3*(p[2]+p[5]), p[6], p[1]+3*(p[2]+p[5]), p[6])
#
itst.time_stamp()
c1.Update()
# Print results
# c2 = itst.get_trend_plot(ff, 1, 'mean')
# c3 = itst.get_trend_plot(ff, 2, 'sigma')
c4 = itst.get_trend_plot(ff, 0, 'Amplitude')
c5 = itst.get_trend_plot(ff2, [0, 3], 'Amplitude2')
# I vs L
# c_I_vs_L = itst.get_intensity_vs_distance(hx)
c_I_vs_t = itst.get_intensity_vs_time(hx)
c_bl_vs_t = itst.get_baseline_vs_time(hx)
Fout = r.TFile('data/signal_rms.root', 'recreate')
tout = itst.get_tree(hx, ff, ff2)
tout.Write()
Fout.Close()
raw_input('Press ENTER to continue, please.')