def _generate(self):
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 3.28229 - 0.219904 * T + 0.00981048 * T**2 - 0.0105927 * T**3 + 0.00151589 * T**4 - 7.66537e-05 * T**5 + 1.31912e-06 * T**6
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(1.0 / spectrum.GetSumOfWeights())
spectrum.SetName(self.get_name())
return spectrum
def _generate(self):
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 3.28229 - 0.219904 * T + 0.00981048 * T**2 - 0.0105927 * T**3 + 0.00151589 * T**4 - 7.66537e-05 * T**5 + 1.31912e-06 * T**6
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(1.0 / spectrum.GetSumOfWeights())
spectrum.SetName(self.get_name())
return spectrum
def _generate(self):
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
if T <= 0.65 + spectrum.GetBinWidth(energy_bin):
Ne = 3439.38 - 1531.56 * T + 654.453 * T**2
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(1.0 / spectrum.GetSumOfWeights())
spectrum.SetName(self.get_name())
return spectrum
def _generate(self):
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
if T <= 1.2 + spectrum.GetBinWidth(energy_bin):
Ne = 100 - 23.85 * T + 6.84 * T**2
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(1.0 / spectrum.GetSumOfWeights())
spectrum.SetName(self.get_name())
return spectrum
def _generate(self):
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
if T <= 1.2 + spectrum.GetBinWidth(energy_bin):
Ne = 100 - 23.85 * T + 6.84 * T**2
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(1.0 / spectrum.GetSumOfWeights())
spectrum.SetName(self.get_name())
return spectrum
def _generate(self):
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
if T <= 0.65 + spectrum.GetBinWidth(energy_bin):
Ne = 3439.38 - 1531.56 * T + 654.453 * T**2
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(1.0 / spectrum.GetSumOfWeights())
spectrum.SetName(self.get_name())
return spectrum
def neutrinoless_double_beta(q, probability):
""" Return a neutrinoless double beta spectrum of probability."""
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
# Delta function at end point
if math.fabs(T - q) < spectrum.GetBinWidth(energy_bin):
Ne = 1
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(probability / spectrum.GetSumOfWeights())
return spectrum
def neutrinoless_double_beta(q, probability):
""" Return a neutrinoless double beta spectrum of probability."""
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
# Delta function at end point
if math.fabs(T - q) < spectrum.GetBinWidth(energy_bin):
Ne = 1
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(probability / spectrum.GetSumOfWeights())
return spectrum
def alpha(q_alpha, probability):
""" Return an alpha spectrum of probability."""
q_alpha = q_alpha / alpha_util.quenching_factor(q_alpha) # Quench the alpha energy
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
# Delta function at end point
if math.fabs(T - q_alpha) < spectrum.GetBinWidth(energy_bin):
Ne = 1
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(probability / spectrum.GetSumOfWeights())
return spectrum
def alpha(q_alpha, probability):
""" Return an alpha spectrum of probability."""
q_alpha = q_alpha / alpha_util.quenching_factor(q_alpha) # Quench the alpha energy
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
# Delta function at end point
if math.fabs(T - q_alpha) < spectrum.GetBinWidth(energy_bin):
Ne = 1
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(probability / spectrum.GetSumOfWeights())
return spectrum
def _generate(self):
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
if T <= 1.0 + spectrum.GetBinWidth(energy_bin):
Ne = 382.649 - 191.188 * T - 459.082 * T**2 + 307.816 * T**3
elif T <= 1.5 + spectrum.GetBinWidth(energy_bin):
Ne = 332.084 - 423.353 * T + 134.585 * T**2
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(1.0 / spectrum.GetSumOfWeights())
spectrum.SetName(self.get_name())
return spectrum
def _generate(self):
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
if T <= 1.0 + spectrum.GetBinWidth(energy_bin):
Ne = 382.649 - 191.188 * T - 459.082 * T**2 + 307.816 * T**3
elif T <= 1.5 + spectrum.GetBinWidth(energy_bin):
Ne = 332.084 - 423.353 * T + 134.585 * T**2
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(1.0 / spectrum.GetSumOfWeights())
spectrum.SetName(self.get_name())
return spectrum
def beta(q_beta, probability):
""" Return a beta spectrum of probability."""
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
if T <= q_beta + spectrum.GetBinWidth(energy_bin):
bin_fraction = 1.0 # Fraction of bin to fill
if T > q_beta: # Allow for bin widths
bin_fraction = 1.0 - (T - q_beta) / spectrum.GetBinWidth(energy_bin)
T = q_beta
Ne = bin_fraction * math.sqrt(T**2 + 2 * T * constants.me) * (q_beta - T)**2 * (T + constants.me)
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(probability / spectrum.GetSumOfWeights())
return spectrum
def beta(q_beta, probability):
""" Return a beta spectrum of probability."""
spectrum = spectrum_util.default_energy()
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
Ne = 0
if T <= q_beta + spectrum.GetBinWidth(energy_bin):
bin_fraction = 1.0 # Fraction of bin to fill
if T > q_beta: # Allow for bin widths
bin_fraction = 1.0 - (T - q_beta) / spectrum.GetBinWidth(energy_bin)
T = q_beta
Ne = bin_fraction * math.sqrt(T**2 + 2 * T * constants.me) * (q_beta - T)**2 * (T + constants.me)
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(probability / spectrum.GetSumOfWeights())
return spectrum
def double_beta(q, probability):
""" Return a double beta spectrum of probability."""
spectrum = spectrum_util.default_energy()
q = q / constants.me
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
T = T / constants.me
Ne = 0
if T <= q + spectrum.GetBinWidth(energy_bin):
binFraction = 1.0 # Fraction of bin to fill
if T > q: # Allow for bin widths
binFraction = 1.0 - (T - q) / spectrum.GetBinWidth(energy_bin)
T = q
Ne = binFraction * T * (q - T)**5 * (1 + 2 * T + 4 * T**2 / 3 + T**3 / 3 + T**4 / 30)
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(probability / spectrum.GetSumOfWeights())
return spectrum
def double_beta(q, probability):
""" Return a double beta spectrum of probability."""
spectrum = spectrum_util.default_energy()
q = q / constants.me
for energy_bin in range(1, spectrum.GetNbinsX() + 1):
T = spectrum.GetBinCenter(energy_bin)
T = T / constants.me
Ne = 0
if T <= q + spectrum.GetBinWidth(energy_bin):
binFraction = 1.0 # Fraction of bin to fill
if T > q: # Allow for bin widths
binFraction = 1.0 - (T - q) / spectrum.GetBinWidth(energy_bin)
T = q
Ne = binFraction * T * (q - T)**5 * (1 + 2 * T + 4 * T**2 / 3 + T**3 / 3 + T**4 / 30)
spectrum.SetBinContent(energy_bin, Ne)
spectrum.Scale(probability / spectrum.GetSumOfWeights())
return spectrum
def plot(self, low_energy, high_energy):
""" Plot the data."""
ROOT.gROOT.SetStyle("Plain")
ROOT.gStyle.SetCanvasBorderMode(0)
ROOT.gStyle.SetPadBorderMode(0)
ROOT.gStyle.SetPadColor(0)
ROOT.gStyle.SetCanvasColor(0)
ROOT.gStyle.SetOptTitle(0)
ROOT.gStyle.SetLabelSize(0.06, "xyz")
ROOT.gStyle.SetTitleSize(0.06, "xyz")
ROOT.gStyle.SetOptStat(0)
self._canvas = ROOT.TCanvas()
self._canvas.Divide(2, 1) # Two columns, separate legend canvas
self._legend = ROOT.TLegend(0.05, 0.05, 0.95, 0.95)
self._legend.SetFillColor(ROOT.kWhite)
self._histograms = [] # All plotted histograms, to store in memory
frame = spectrum_util.default_energy()
self._histograms.append(frame)
vc1 = self._canvas.cd(1)
vc1.SetLeftMargin(0.155)
vc1.SetBottomMargin(0.15)
vc1.SetTopMargin(0.05)
vc1.SetRightMargin(0.05)
frame.Draw()
frame.GetXaxis().SetRangeUser(low_energy, high_energy)
frame.GetXaxis().SetTitle("Energy [MeV]")
frame.GetXaxis().SetTitleOffset(1.0)
frame.GetYaxis().SetTitle("Events per %0.2f MeV" %
frame.GetXaxis().GetBinWidth(1))
frame.GetYaxis().SetTitleOffset(1.3)
# Create summed background and bg + signal histograms
self._summed_bg = spectrum_util.default_energy("Sum BG")
self._sum_bg_signal = spectrum_util.default_energy("Sum BG + Signal")
maxCounts = 0.0 # For rescaling the histogram axis
file = open("Te15load.txt", "w")
# file = open("ALL_BG_PU_limited.txt","w")
# OUTPUT FOR THE SIGNAL
low_energy_FWHM = self._signal.GetXaxis().FindBin(2.485)
high_energy_FWHM = self._signal.GetXaxis().FindBin(2.733)
# low_energy_PWHM = self._signal.GetXaxis().FindBin(2.529)
# high_energy_PWHM = self._signal.GetXaxis().FindBin(2.664)
low_energy_per = self._signal.GetXaxis().FindBin(2.492)
high_energy_per = self._signal.GetXaxis().FindBin(2.675)
Integral_per = self._signal.Integral(low_energy_per, high_energy_per)
Integral_FWHM = self._signal.Integral(low_energy_FWHM,
high_energy_FWHM)
# Integral_PWHM = self._signal.Integral(low_energy_PWHM, high_energy_PWHM)
Tot_integral = self._signal.Integral()
Weight = self._signal.GetSumOfWeights()
print str("!!!!!!!!!ATTENTION!!!!!!!!!!!!")
print self._signal
print str("Integral BIS MSB FWHM from 2.485 MeV to 2.733 MeV")
print Integral_FWHM
print str("Integral PERYLENE FWHM from 2.492 MeV to 2.675 MeV")
print Integral_per
print str("total number of events")
print Tot_integral
print str("WEIGHTS")
print Weight
file.write(str("SIGNAL") + "\n")
file.write(
str("Integral BIS MSB FWHM from 2.485 MeV to 2.733 MeV") + "\n")
file.write(str(Integral_FWHM) + "\n")
file.write(
str("Integral PERYLENE FWHM from 2.492 MeV to 2.675 MeV") + "\n")
file.write(str(Integral_per) + "\n")
file.write(str("total number of events") + "\n")
file.write(str(Tot_integral) + "\n")
file.write(str("") + "\n")
# THE END OF THE OUTPUT
# Draw backgrounds and signal and summed histograms
for bg in self._backgrounds:
print bg.GetName()
hist = bg
hist.SetLineWidth(1)
hist.Draw("SAME")
# THE OUTPUT FOR THE BACKGROUND
low_energy_FWHM = hist.GetXaxis().FindBin(2.485)
high_energy_FWHM = hist.GetXaxis().FindBin(2.733)
# low_energy_PWHM = hist.GetXaxis().FindBin(2.529)
# high_energy_PWHM = hist.GetXaxis().FindBin(2.664)
Integral_FWHM = hist.Integral(low_energy_FWHM, high_energy_FWHM)
# Integral_PWHM = hist.Integral(low_energy_PWHM, high_energy_PWHM)
Tot_integral = hist.Integral()
Weight = hist.GetSumOfWeights()
low_energy_per = hist.GetXaxis().FindBin(2.492)
high_energy_per = hist.GetXaxis().FindBin(2.675)
Integral_per = hist.Integral(low_energy_per, high_energy_per)
print str("!!!!!!!!!ATTENTION!!!!!!!!!!!!")
print bg
print str("Integral BIS MSB FWHM from 2.485 MeV to 2.733 MeV")
print Integral_FWHM
print str("Integral PERYLENE FWHM from 2.492 MeV to 2.675 MeV")
print Integral_per
print str("total number of events")
print Tot_integral
print str("WEIGHTS")
print Weight
file.write(str("") + "\n")
file.write(str(bg.GetName()) + "\n")
file.write(
str("Integral BIS MSB FWHM from 2.485 MeV to 2.733 MeV") +
"\n")
file.write(str(Integral_FWHM) + "\n")
file.write(
str("Integral PERYLENE FWHM from 2.492 MeV to 2.675 MeV") +
"\n")
file.write(str(Integral_per) + "\n")
file.write(str("total number of events") + "\n")
file.write(str(Tot_integral) + "\n")
#THE END OF THE OUTPUT
hist.SetLineColor(self._colours.get_colour(bg.GetName()))
hist.SetLineStyle(self._lines.get_style(bg.GetName()))
self._histograms.append(hist)
self._summed_bg.Add(hist)
# Add to legend if visible in the energy domain
countsInDomain = hist.Integral(
hist.GetXaxis().FindBin(low_energy),
hist.GetXaxis().FindBin(high_energy))
if countsInDomain > 1:
self._legend.AddEntry(hist, bg.GetName(), "l")
maxCounts = max([maxCounts, countsInDomain])
self._canvas.Update()
# Rescale the histogram axis
frame.GetYaxis().SetRangeUser(1e-1, maxCounts)
# Draw the signal first
self._sum_bg_signal.Add(self._summed_bg)
self._signal.SetLineColor(
self._colours.get_colour(self._signal.GetName()))
self._signal.SetLineStyle(self._lines.get_style(
self._signal.GetName()))
self._signal.SetLineWidth(1)
self._signal.Draw("SAME")
self._legend.AddEntry(self._signal,
self._signal.GetName() + " : Sig", "l")
self._histograms.append(self._signal)
self._sum_bg_signal.Add(self._signal)
# Now draw the summed histograms
self._summed_bg.SetLineWidth(2)
self._summed_bg.Draw("SAME")
print str("Summed_bg")
print self._summed_bg.Integral()
self._legend.AddEntry(self._summed_bg, "Sum BG", "l")
self._sum_bg_signal.SetLineWidth(3)
self._sum_bg_signal.SetLineStyle(1)
self._sum_bg_signal.Draw("SAME")
print str("Sum_bg_signal")
print self._sum_bg_signal.Integral()
self._legend.AddEntry(self._sum_bg_signal, "Sum BG + Sig", "l")
self._canvas.cd(1).SetLogy()
self._canvas.cd(2)
# Draw the legend on a different canvas
self._legend.SetNColumns(self._legend.GetNRows() / 50 + 1)
self._legend.Draw()
self._canvas.cd()
file.close()
return self._canvas
def plot(self, low_energy, high_energy):
""" Plot the data."""
ROOT.gROOT.SetStyle("Plain")
ROOT.gStyle.SetCanvasBorderMode(0)
ROOT.gStyle.SetPadBorderMode(0)
ROOT.gStyle.SetPadColor(0)
ROOT.gStyle.SetCanvasColor(0)
ROOT.gStyle.SetOptTitle(0)
ROOT.gStyle.SetLabelSize(0.06, "xyz")
ROOT.gStyle.SetTitleSize(0.06, "xyz")
ROOT.gStyle.SetOptStat(0)
self._canvas = ROOT.TCanvas()
self._canvas.Divide(2, 1) # Two columns, separate legend canvas
self._legend = ROOT.TLegend(0.05, 0.05, 0.95, 0.95)
self._legend.SetFillColor(ROOT.kWhite)
self._histograms = [] # All plotted histograms, to store in memory
frame = spectrum_util.default_energy()
self._histograms.append(frame)
vc1 = self._canvas.cd(1)
vc1.SetLeftMargin(0.155)
vc1.SetBottomMargin(0.15)
vc1.SetTopMargin(0.05)
vc1.SetRightMargin(0.05)
frame.Draw()
frame.GetXaxis().SetRangeUser(low_energy, high_energy)
frame.GetXaxis().SetTitle("Energy [MeV]")
frame.GetXaxis().SetTitleOffset(1.0)
frame.GetYaxis().SetTitle("Events per %0.2f MeV" % frame.GetXaxis().GetBinWidth(1))
frame.GetYaxis().SetTitleOffset(1.3)
# Create summed background and bg + signal histograms
self._summed_bg = spectrum_util.default_energy("Sum BG")
self._sum_bg_signal = spectrum_util.default_energy("Sum BG + Signal")
maxCounts = 0.0 # For rescaling the histogram axis
# Draw backgrounds and signal and summed histograms
for bg in self._backgrounds:
print bg.GetName()
hist = bg
hist.Draw("SAME")
hist.SetLineColor(self._colours.get_colour(bg.GetName()))
hist.SetLineStyle(self._lines.get_style(bg.GetName()))
self._histograms.append(hist)
self._summed_bg.Add(hist)
# Add to legend if visible in the energy domain
countsInDomain = hist.Integral(hist.GetXaxis().FindBin(low_energy), hist.GetXaxis().FindBin(high_energy))
if countsInDomain > 1:
self._legend.AddEntry(hist, bg.GetName(), "l")
maxCounts = max([maxCounts, countsInDomain])
self._canvas.Update()
# Rescale the histogram axis
frame.GetYaxis().SetRangeUser(1e-1, maxCounts)
# Draw the signal first
self._sum_bg_signal.Add(self._summed_bg)
self._signal.SetLineColor(self._colours.get_colour(self._signal.GetName()))
self._signal.SetLineStyle(self._lines.get_style(self._signal.GetName()))
self._signal.Draw("SAME")
self._legend.AddEntry(self._signal, self._signal.GetName() + " : Sig", "l")
self._histograms.append(self._signal)
self._sum_bg_signal.Add(self._signal)
# Now draw the summed histograms
self._summed_bg.SetLineWidth(3)
self._summed_bg.Draw("SAME")
self._legend.AddEntry(self._summed_bg, "Sum BG", "l")
self._sum_bg_signal.SetLineWidth(4)
self._sum_bg_signal.SetLineStyle(2)
self._sum_bg_signal.Draw("SAME")
self._legend.AddEntry(self._sum_bg_signal, "Sum BG + Sig", "l")
self._canvas.cd(1).SetLogy()
self._canvas.cd(2)
# Draw the legend on a different canvas
self._legend.SetNColumns(self._legend.GetNRows() / 50 + 1)
self._legend.Draw()
self._canvas.cd()
return self._canvas
