def main(args):
""" Script to set 90% CL on all four Majoron-emitting modes.
"""
# Load signal spectra
signals = []
for signal_hdf5 in args.signals:
spectrum = store.load(signal_hdf5)
print spectrum._name
print "Num decays:", spectrum._num_decays
print "events:", spectrum.sum()
signals.append(spectrum)
# Load background spectra
floating_backgrounds = []
Te130_2n2b = store.load(args.two_nu)
print Te130_2n2b._name
Te130_2n2b._num_decays = Te130_2n2b.sum() # Sum not raw events
print "Num decays:", Te130_2n2b._num_decays
print "events:", Te130_2n2b.sum()
floating_backgrounds.append(Te130_2n2b)
B8_Solar = store.load(args.b8_solar)
print B8_Solar._name
B8_Solar._num_decays = B8_Solar.sum() # Sum not raw events
print "Num decays:", B8_Solar._num_decays
print "events:", B8_Solar.sum()
floating_backgrounds.append(B8_Solar)
# Apply FV and livetime cuts
fv_radius = constants._fv_radius
livetime = 1.0
for spectrum in signals:
spectrum.cut(time_low=0.0, time_high=livetime) # cut to livetime
spectrum.shrink(radial_low=0.0, radial_high=fv_radius) # shrink to FV
spectrum.shrink_to_roi(0.5, 3.0, 0) # shrink to ROI
for spectrum in floating_backgrounds:
spectrum.cut(time_low=0.0, time_high=livetime) # cut to livelime
spectrum.shrink(radial_low=0.0, radial_high=fv_radius) # shrink to FV
spectrum.shrink_to_roi(0.5, 3.0, 0) # shrink to ROI
# Signal configuration
signal_configs_np = [] # no penalty term
signal_configs = []
prior = 0.0
Te130_0n2b_n1_counts = numpy.linspace(signals[0]._num_decays,
0.0, 100, False)
# endpoint=False in linspace arrays
Te130_0n2b_n1_config_np = limit_config.LimitConfig(prior,
Te130_0n2b_n1_counts)
Te130_0n2b_n1_config = limit_config.LimitConfig(prior,
Te130_0n2b_n1_counts)
signal_configs_np.append(Te130_0n2b_n1_config_np)
signal_configs.append(Te130_0n2b_n1_config)
Te130_0n2b_n2_counts = numpy.linspace(signals[1]._num_decays,
0.0, 100, False)
Te130_0n2b_n2_config_np = limit_config.LimitConfig(prior,
Te130_0n2b_n2_counts)
Te130_0n2b_n2_config = limit_config.LimitConfig(prior,
Te130_0n2b_n2_counts)
signal_configs_np.append(Te130_0n2b_n2_config_np)
signal_configs.append(Te130_0n2b_n2_config)
Te130_0n2b_n3_counts = numpy.linspace(signals[2]._num_decays,
0.0, 100, False)
Te130_0n2b_n3_config_np = limit_config.LimitConfig(prior,
Te130_0n2b_n3_counts)
Te130_0n2b_n3_config = limit_config.LimitConfig(prior,
Te130_0n2b_n3_counts)
signal_configs_np.append(Te130_0n2b_n3_config_np)
signal_configs.append(Te130_0n2b_n3_config)
Te130_0n2b_n7_counts = numpy.linspace(signals[3]._num_decays,
0.0, 100, False)
Te130_0n2b_n7_config_np = limit_config.LimitConfig(prior,
Te130_0n2b_n7_counts)
Te130_0n2b_n7_config = limit_config.LimitConfig(prior,
Te130_0n2b_n7_counts)
signal_configs_np.append(Te130_0n2b_n7_config_np)
signal_configs.append(Te130_0n2b_n7_config)
# Background configuration
# Te130_2n2b
Te130_2n2b_prior = 3.7396e6 # Based on NEMO-3 T_1/2, for 1 year livetime
# Since we used cut method to cut to livetime
# No penalty term
Te130_2n2b_counts_np = numpy.array([Te130_2n2b_prior])
Te130_2n2b_config_np = limit_config.LimitConfig(Te130_2n2b_prior,
Te130_2n2b_counts_np)
# With penalty term
Te130_2n2b_counts = numpy.linspace(0.8*Te130_2n2b_prior,
1.2*Te130_2n2b_prior, 51)
# 51 bins to make sure midpoint (no variation from prior) is included
# to use in penalty term (20%, Andy's document on systematics)
sigma = 0.2 * Te130_2n2b_prior
Te130_2n2b_config = limit_config.LimitConfig(Te130_2n2b_prior,
Te130_2n2b_counts, sigma)
# B8_Solar
# from integrating whole spectrum scaled to Valentina's number
B8_Solar_prior = 1252.99691
# No penalty term
B8_Solar_counts_np = numpy.array([B8_Solar_prior])
B8_Solar_config_np = limit_config.LimitConfig(B8_Solar_prior,
B8_Solar_counts_np)
# With penalty term
B8_Solar_counts = numpy.linspace(0.96*B8_Solar_prior,
1.04*B8_Solar_prior, 11)
# 11 bins to make sure midpoint (no variation from prior) is included
sigma = 0.04 * B8_Solar_prior # 4% To use in penalty term
B8_Solar_config = limit_config.LimitConfig(B8_Solar_prior,
B8_Solar_counts, sigma)
# DBIsotope converter information - constant across modes
isotope_name = "Te130"
atm_weight_iso = 129.906229
atm_weight_nat = 127.6
abundance = 0.3408
# Make a list of associated nuclear physics info
nuclear_params = []
# n=1:
phase_space = 5.94e-16
matrix_element = 3.97 # Averaged
nuclear_params.append((phase_space, matrix_element))
# n=2:
phase_space = None
matrix_element = None
nuclear_params.append((phase_space, matrix_element))
# n=1:
phase_space = 1.06e-17 # Assuming two Majorons emitted
matrix_element = 1.e-3
nuclear_params.append((phase_space, matrix_element))
# n=1:
phase_space = 4.83e-17
matrix_element = 1.e-3
nuclear_params.append((phase_space, matrix_element))
# chi squared calculator
calculator = chi_squared.ChiSquared()
# Set output location
output_dir = echidna.__echidna_base__ + "/results/snoplus/"
for signal, signal_config_np, nuclear_param in zip(signals,
signal_configs_np,
nuclear_params):
print signal._name
# Create no penalty limit setter
set_limit_np = limit_setting.LimitSetting(
signal, floating_backgrounds=floating_backgrounds)
# Configure signal
set_limit_np.configure_signal(signal_config_np)
# Configure 2n2b
set_limit_np.configure_background(Te130_2n2b._name,
Te130_2n2b_config_np)
# Configure B8
set_limit_np.configure_background(B8_Solar._name, B8_Solar_config_np)
# Set converter
phase_space, matrix_element = nuclear_param
roi_efficiency = signal.get_roi(0).get("efficiency")
converter = decay.DBIsotope(
isotope_name, atm_weight_iso, atm_weight_nat, abundance,
phase_space, matrix_element, roi_efficiency=roi_efficiency)
# Set chi squared calculator
set_limit_np.set_calculator(calculator)
# Get limit
try:
limit = set_limit_np.get_limit()
print "-----------------------------------"
print "90% CL at " + str(limit) + " counts"
half_life = converter.counts_to_half_life(limit, livetime=livetime)
print "90% CL at " + str(half_life) + " yr"
print "-----------------------------------"
except IndexError as detail:
print "-----------------------------------"
print detail
print "-----------------------------------"
for i, signal_config_np in enumerate(signal_configs_np):
store.dump_ndarray(output_dir+signals[i]._name+"_np.hdf5",
signal_config_np)
raw_input("RETURN to continue")
signal_num = 0
for signal, signal_config, nuclear_param in zip(signals, signal_configs,
nuclear_params):
print signal._name
# Create limit setter
set_limit = limit_setting.LimitSetting(
signal, floating_backgrounds=floating_backgrounds)
# Configure signal
set_limit.configure_signal(signal_config)
# Configure 2n2b
set_limit.configure_background(Te130_2n2b._name, Te130_2n2b_config,
plot_systematic=True)
# Configure B8
set_limit.configure_background(B8_Solar._name, B8_Solar_config,
plot_systematic=True)
# Set converter
phase_space, matrix_element = nuclear_param
roi_efficiency = signal.get_roi(0).get("efficiency")
converter = decay.DBIsotope(
isotope_name, atm_weight_iso, atm_weight_nat, abundance,
phase_space, matrix_element, roi_efficiency=roi_efficiency)
# Set chi squared calculator
set_limit.set_calculator(calculator)
# Get limit
try:
limit = set_limit.get_limit()
print "-----------------------------------"
print "90% CL at " + str(limit) + " counts"
half_life = converter.counts_to_half_life(limit, livetime=livetime)
print "90% CL at " + str(half_life) + " yr"
print "-----------------------------------"
except IndexError as detail:
print "-----------------------------------"
print detail
print "-----------------------------------"
# Dump SystAnalysers to hdf5
for syst_analyser in set_limit._syst_analysers.values():
store.dump_ndarray(output_dir+syst_analyser._name+str(signal_num)+".hdf5",
syst_analyser)
signal_num += 1
# Dump configs to hdf5
for i, signal_config in enumerate(signal_configs):
store.dump_ndarray(output_dir+signals[i]._name+".hdf5", signal_config)
store.dump_ndarray(output_dir+"Te130_2n2b_config.hdf5", Te130_2n2b_config)
store.dump_ndarray(output_dir+"B8_Solar_config.hdf5", B8_Solar_config)
def main(args):
""" Script to set 90% CL on all four Majoron-emitting modes.
"""
# Load signal spectra
signals = []
for signal_hdf5 in args.signals:
spectrum = store.load(signal_hdf5)
print spectrum._name
print "Num decays:", spectrum._num_decays
print "events:", spectrum.sum()
signals.append(spectrum)
# Load background spectra
floating_backgrounds = []
Te130_2n2b = store.load(args.two_nu)
print Te130_2n2b._name
Te130_2n2b._num_decays = Te130_2n2b.sum() # Sum not raw events
print "Num decays:", Te130_2n2b._num_decays
print "events:", Te130_2n2b.sum()
floating_backgrounds.append(Te130_2n2b)
B8_Solar = store.load(args.b8_solar)
print B8_Solar._name
B8_Solar._num_decays = B8_Solar.sum() # Sum not raw events
print "Num decays:", B8_Solar._num_decays
print "events:", B8_Solar.sum()
floating_backgrounds.append(B8_Solar)
# Apply FV and livetime cuts
fv_radius = constants._fv_radius
livetime = 1.0
for spectrum in signals:
spectrum.cut(time_low=0.0, time_high=livetime) # cut to livetime
spectrum.shrink(radial_low=0.0, radial_high=fv_radius) # shrink to FV
spectrum.shrink_to_roi(0.5, 3.0, 0) # shrink to ROI
for spectrum in floating_backgrounds:
spectrum.cut(time_low=0.0, time_high=livetime) # cut to livelime
spectrum.shrink(radial_low=0.0, radial_high=fv_radius) # shrink to FV
spectrum.shrink_to_roi(0.5, 3.0, 0) # shrink to ROI
# Signal configuration
signal_configs_np = [] # no penalty term
signal_configs = []
prior = 0.0
Te130_0n2b_n1_counts = numpy.linspace(signals[0]._num_decays, 0.0, 100,
False)
# endpoint=False in linspace arrays
Te130_0n2b_n1_config_np = limit_config.LimitConfig(prior,
Te130_0n2b_n1_counts)
Te130_0n2b_n1_config = limit_config.LimitConfig(prior,
Te130_0n2b_n1_counts)
signal_configs_np.append(Te130_0n2b_n1_config_np)
signal_configs.append(Te130_0n2b_n1_config)
Te130_0n2b_n2_counts = numpy.linspace(signals[1]._num_decays, 0.0, 100,
False)
Te130_0n2b_n2_config_np = limit_config.LimitConfig(prior,
Te130_0n2b_n2_counts)
Te130_0n2b_n2_config = limit_config.LimitConfig(prior,
Te130_0n2b_n2_counts)
signal_configs_np.append(Te130_0n2b_n2_config_np)
signal_configs.append(Te130_0n2b_n2_config)
Te130_0n2b_n3_counts = numpy.linspace(signals[2]._num_decays, 0.0, 100,
False)
Te130_0n2b_n3_config_np = limit_config.LimitConfig(prior,
Te130_0n2b_n3_counts)
Te130_0n2b_n3_config = limit_config.LimitConfig(prior,
Te130_0n2b_n3_counts)
signal_configs_np.append(Te130_0n2b_n3_config_np)
signal_configs.append(Te130_0n2b_n3_config)
Te130_0n2b_n7_counts = numpy.linspace(signals[3]._num_decays, 0.0, 100,
False)
Te130_0n2b_n7_config_np = limit_config.LimitConfig(prior,
Te130_0n2b_n7_counts)
Te130_0n2b_n7_config = limit_config.LimitConfig(prior,
Te130_0n2b_n7_counts)
signal_configs_np.append(Te130_0n2b_n7_config_np)
signal_configs.append(Te130_0n2b_n7_config)
# Background configuration
# Te130_2n2b
Te130_2n2b_prior = 3.7396e6 # Based on NEMO-3 T_1/2, for 1 year livetime
# Since we used cut method to cut to livetime
# No penalty term
Te130_2n2b_counts_np = numpy.array([Te130_2n2b_prior])
Te130_2n2b_config_np = limit_config.LimitConfig(Te130_2n2b_prior,
Te130_2n2b_counts_np)
# With penalty term
Te130_2n2b_counts = numpy.linspace(0.8 * Te130_2n2b_prior,
1.2 * Te130_2n2b_prior, 51)
# 51 bins to make sure midpoint (no variation from prior) is included
# to use in penalty term (20%, Andy's document on systematics)
sigma = 0.2 * Te130_2n2b_prior
Te130_2n2b_config = limit_config.LimitConfig(Te130_2n2b_prior,
Te130_2n2b_counts, sigma)
# B8_Solar
# from integrating whole spectrum scaled to Valentina's number
B8_Solar_prior = 1252.99691
# No penalty term
B8_Solar_counts_np = numpy.array([B8_Solar_prior])
B8_Solar_config_np = limit_config.LimitConfig(B8_Solar_prior,
B8_Solar_counts_np)
# With penalty term
B8_Solar_counts = numpy.linspace(0.96 * B8_Solar_prior,
1.04 * B8_Solar_prior, 11)
# 11 bins to make sure midpoint (no variation from prior) is included
sigma = 0.04 * B8_Solar_prior # 4% To use in penalty term
B8_Solar_config = limit_config.LimitConfig(B8_Solar_prior, B8_Solar_counts,
sigma)
# DBIsotope converter information - constant across modes
isotope_name = "Te130"
atm_weight_iso = 129.906229
atm_weight_nat = 127.6
abundance = 0.3408
# Make a list of associated nuclear physics info
nuclear_params = []
# n=1:
phase_space = 5.94e-16
matrix_element = 3.97 # Averaged
nuclear_params.append((phase_space, matrix_element))
# n=2:
phase_space = None
matrix_element = None
nuclear_params.append((phase_space, matrix_element))
# n=1:
phase_space = 1.06e-17 # Assuming two Majorons emitted
matrix_element = 1.e-3
nuclear_params.append((phase_space, matrix_element))
# n=1:
phase_space = 4.83e-17
matrix_element = 1.e-3
nuclear_params.append((phase_space, matrix_element))
# chi squared calculator
calculator = chi_squared.ChiSquared()
# Set output location
output_dir = echidna.__echidna_base__ + "/results/snoplus/"
for signal, signal_config_np, nuclear_param in zip(signals,
signal_configs_np,
nuclear_params):
print signal._name
# Create no penalty limit setter
set_limit_np = limit_setting.LimitSetting(
signal, floating_backgrounds=floating_backgrounds)
# Configure signal
set_limit_np.configure_signal(signal_config_np)
# Configure 2n2b
set_limit_np.configure_background(Te130_2n2b._name,
Te130_2n2b_config_np)
# Configure B8
set_limit_np.configure_background(B8_Solar._name, B8_Solar_config_np)
# Set converter
phase_space, matrix_element = nuclear_param
roi_efficiency = signal.get_roi(0).get("efficiency")
converter = decay.DBIsotope(isotope_name,
atm_weight_iso,
atm_weight_nat,
abundance,
phase_space,
matrix_element,
roi_efficiency=roi_efficiency)
# Set chi squared calculator
set_limit_np.set_calculator(calculator)
# Get limit
try:
limit = set_limit_np.get_limit()
print "-----------------------------------"
print "90% CL at " + str(limit) + " counts"
half_life = converter.counts_to_half_life(limit, livetime=livetime)
print "90% CL at " + str(half_life) + " yr"
print "-----------------------------------"
except IndexError as detail:
print "-----------------------------------"
print detail
print "-----------------------------------"
for i, signal_config_np in enumerate(signal_configs_np):
store.dump_ndarray(output_dir + signals[i]._name + "_np.hdf5",
signal_config_np)
raw_input("RETURN to continue")
signal_num = 0
for signal, signal_config, nuclear_param in zip(signals, signal_configs,
nuclear_params):
print signal._name
# Create limit setter
set_limit = limit_setting.LimitSetting(
signal, floating_backgrounds=floating_backgrounds)
# Configure signal
set_limit.configure_signal(signal_config)
# Configure 2n2b
set_limit.configure_background(Te130_2n2b._name,
Te130_2n2b_config,
plot_systematic=True)
# Configure B8
set_limit.configure_background(B8_Solar._name,
B8_Solar_config,
plot_systematic=True)
# Set converter
phase_space, matrix_element = nuclear_param
roi_efficiency = signal.get_roi(0).get("efficiency")
converter = decay.DBIsotope(isotope_name,
atm_weight_iso,
atm_weight_nat,
abundance,
phase_space,
matrix_element,
roi_efficiency=roi_efficiency)
# Set chi squared calculator
set_limit.set_calculator(calculator)
# Get limit
try:
limit = set_limit.get_limit()
print "-----------------------------------"
print "90% CL at " + str(limit) + " counts"
half_life = converter.counts_to_half_life(limit, livetime=livetime)
print "90% CL at " + str(half_life) + " yr"
print "-----------------------------------"
except IndexError as detail:
print "-----------------------------------"
print detail
print "-----------------------------------"
# Dump SystAnalysers to hdf5
for syst_analyser in set_limit._syst_analysers.values():
store.dump_ndarray(
output_dir + syst_analyser._name + str(signal_num) + ".hdf5",
syst_analyser)
signal_num += 1
# Dump configs to hdf5
for i, signal_config in enumerate(signal_configs):
store.dump_ndarray(output_dir + signals[i]._name + ".hdf5",
signal_config)
store.dump_ndarray(output_dir + "Te130_2n2b_config.hdf5",
Te130_2n2b_config)
store.dump_ndarray(output_dir + "B8_Solar_config.hdf5", B8_Solar_config)
# (SNO+-doc-2593-v8) for 5 year livetime
# Note extrapolating here to 10 years
Te130_0n2b_penalty_config = limit_config.LimitConfig(Te130_0n2b_prior,
Te130_0n2b_counts)
set_limit.configure_signal(Te130_0n2b_penalty_config)
# Set new configs this time with more counts
Te130_2n2b_counts = numpy.arange(8.7e6, 13.3e6, 0.1e6, dtype=float)
sigma = 2.2647e6 # To use in penalty term (20%, Andy's document on
# systematics)
Te130_2n2b_penalty_config = limit_config.LimitConfig(Te130_2n2b_prior,
Te130_2n2b_counts,
sigma)
set_limit.configure_background(Te130_2n2b._name, Te130_2n2b_penalty_config,
plot_systematic=True)
B8_Solar_counts = numpy.arange(12.0e3, 13.0e3, 0.1e3, dtype=float)
sigma = 501.1988 # To use in penalty term
B8_Solar_penalty_config = limit_config.LimitConfig(B8_Solar_prior,
B8_Solar_counts, sigma)
set_limit.configure_background(B8_Solar._name, B8_Solar_penalty_config,
plot_systematic=True)
# Calculate confidence limit
print "90% CL at: " + str(set_limit.get_limit()) + " counts"
plot_chi_squared.chi_squared_vs_signal(Te130_0n2b_config,
penalty=Te130_0n2b_penalty_config)
for syst_analyser in set_limit._syst_analysers.values():
store.dump_ndarray(syst_analyser._name+".hdf5", syst_analyser)
# Note extrapolating here to 10 years
Te130_0n2b_penalty_config = limit_config.LimitConfig(
Te130_0n2b_prior, Te130_0n2b_counts)
set_limit.configure_signal(Te130_0n2b_penalty_config)
# Set new configs this time with more counts
Te130_2n2b_counts = numpy.arange(8.7e6, 13.3e6, 0.1e6, dtype=float)
sigma = 2.2647e6 # To use in penalty term (20%, Andy's document on
# systematics)
Te130_2n2b_penalty_config = limit_config.LimitConfig(
Te130_2n2b_prior, Te130_2n2b_counts, sigma)
set_limit.configure_background(Te130_2n2b._name,
Te130_2n2b_penalty_config,
plot_systematic=True)
B8_Solar_counts = numpy.arange(12.0e3, 13.0e3, 0.1e3, dtype=float)
sigma = 501.1988 # To use in penalty term
B8_Solar_penalty_config = limit_config.LimitConfig(B8_Solar_prior,
B8_Solar_counts, sigma)
set_limit.configure_background(B8_Solar._name,
B8_Solar_penalty_config,
plot_systematic=True)
# Calculate confidence limit
print "90% CL at: " + str(set_limit.get_limit()) + " counts"
plot_chi_squared.chi_squared_vs_signal(Te130_0n2b_config,
penalty=Te130_0n2b_penalty_config)
for syst_analyser in set_limit._syst_analysers.values():
store.dump_ndarray(syst_analyser._name + ".hdf5", syst_analyser)
# Set chi squared calculator
set_limit.set_calculator(calculator)
# Calculate confidence limit
sig_num_decays = set_limit.get_limit()
half_life = converter.counts_to_half_life(sig_num_decays)
print ("90% CL with Te130_2n2b floating at: " +
str(sig_num_decays) + " ROI counts")
print "90% CL with Te130_2n2b floating at: " + str(half_life) + " y"
fig1 = plot_chi_squared.chi_squared_vs_signal(Te130_0n2b_config)
fig1.Draw("AP")
raw_input("RETURN to continue")
for syst_analyser in set_limit._syst_analysers.values():
store.dump_ndarray(syst_analyser._name+"_2.hdf5", syst_analyser)
# 3/ Fix no backgrounds and float all#
Te130_0n2b = store.load(args.signal)
# Reload background spectra
Te130_2n2b = store.load(args.two_nu)
B8_Solar = store.load(args.b8_solar)
# Need to reset all of these for correct scaling
Te130_0n2b._num_decays = Te130_0n2b.sum()
Te130_0n2b._raw_events = 200034
Te130_2n2b._num_decays = Te130_2n2b.sum()
print "Te130_2n2b._num_decays:", Te130_2n2b._num_decays
Te130_2n2b._raw_events = 75073953
B8_Solar._num_decays = B8_Solar.sum()
print "B8_Solar._num_decays:", B8_Solar._num_decays
# Set chi squared calculator
set_limit.set_calculator(calculator)
# Calculate confidence limit
sig_num_decays = set_limit.get_limit()
half_life = converter.counts_to_half_life(sig_num_decays)
print("90% CL with Te130_2n2b floating at: " + str(sig_num_decays) +
" ROI counts")
print "90% CL with Te130_2n2b floating at: " + str(half_life) + " y"
fig1 = plot_chi_squared.chi_squared_vs_signal(Te130_0n2b_config)
fig1.Draw("AP")
raw_input("RETURN to continue")
for syst_analyser in set_limit._syst_analysers.values():
store.dump_ndarray(syst_analyser._name + "_2.hdf5", syst_analyser)
# 3/ Fix no backgrounds and float all#
Te130_0n2b = store.load(args.signal)
# Reload background spectra
Te130_2n2b = store.load(args.two_nu)
B8_Solar = store.load(args.b8_solar)
# Need to reset all of these for correct scaling
Te130_0n2b._num_decays = Te130_0n2b.sum()
Te130_0n2b._raw_events = 200034
Te130_2n2b._num_decays = Te130_2n2b.sum()
print "Te130_2n2b._num_decays:", Te130_2n2b._num_decays
Te130_2n2b._raw_events = 75073953
B8_Solar._num_decays = B8_Solar.sum()
print "B8_Solar._num_decays:", B8_Solar._num_decays
def main(args):
""" Script to set 90% CL on all four Majoron-emitting modes.
"""
# Load signal spectra
signals = []
for signal_hdf5 in args.signals:
spectrum = store.load(signal_hdf5)
print spectrum._name
print "Num decays:", spectrum._num_decays
print "raw events:", spectrum._raw_events
print "events:", spectrum.sum()
signals.append(spectrum)
# Load background spectra
floating_backgrounds = []
Xe136_2n2b = store.load(args.two_nu)
print Xe136_2n2b._name
print "Num decays:", Xe136_2n2b._num_decays
print "raw events:", Xe136_2n2b._raw_events
print "events:", Xe136_2n2b.sum()
floating_backgrounds.append(Xe136_2n2b)
B8_Solar = store.load(args.b8_solar)
print B8_Solar._name
B8_Solar._num_decays = B8_Solar.sum() # Sum not raw events
print "Num decays:", B8_Solar._num_decays
print "raw events:", B8_Solar._raw_events
print "events:", B8_Solar.sum()
floating_backgrounds.append(B8_Solar)
# Apply FV and livetime cuts
fv_radius = 1200.0 # 1.2m PRC 86, 021601 (2012)
livetime = 1.0
for spectrum in signals:
spectrum.cut(time_low=0.0, time_high=livetime) # cut to livetime
spectrum.shrink(radial_low=0.0, radial_high=fv_radius) # shrink to FV
spectrum.shrink_to_roi(0.5, 3.0, 0) # shrink to ROI
for spectrum in floating_backgrounds:
spectrum.cut(time_low=0.0, time_high=livetime) # cut to livetime
spectrum.shrink(radial_low=0.0, radial_high=fv_radius) # shrink to FV
spectrum.shrink_to_roi(0.5, 3.0, 0) # shrink to ROI
# Signal configuration
signal_configs_np = [] # no penalty term
signal_configs = []
prior = 0.0
Xe136_0n2b_n1_counts = numpy.linspace(signals[0]._num_decays,
0.0, 100, False)
# endpoint=False in linspace arrays
Xe136_0n2b_n1_config_np = limit_config.LimitConfig(prior,
Xe136_0n2b_n1_counts)
Xe136_0n2b_n1_config = limit_config.LimitConfig(prior,
Xe136_0n2b_n1_counts)
signal_configs_np.append(Xe136_0n2b_n1_config_np)
signal_configs.append(Xe136_0n2b_n1_config)
Xe136_0n2b_n2_counts = numpy.linspace(signals[1]._num_decays,
0.0, 100, False)
Xe136_0n2b_n2_config_np = limit_config.LimitConfig(prior,
Xe136_0n2b_n2_counts)
Xe136_0n2b_n2_config = limit_config.LimitConfig(prior,
Xe136_0n2b_n2_counts)
signal_configs_np.append(Xe136_0n2b_n2_config_np)
signal_configs.append(Xe136_0n2b_n2_config)
Xe136_0n2b_n3_counts = numpy.linspace(signals[2]._num_decays,
0.0, 100, False)
Xe136_0n2b_n3_config_np = limit_config.LimitConfig(prior,
Xe136_0n2b_n3_counts)
Xe136_0n2b_n3_config = limit_config.LimitConfig(prior,
Xe136_0n2b_n3_counts)
signal_configs_np.append(Xe136_0n2b_n3_config_np)
signal_configs.append(Xe136_0n2b_n3_config)
Xe136_0n2b_n7_counts = numpy.linspace(signals[3]._num_decays,
0.0, 100, False)
Xe136_0n2b_n7_config_np = limit_config.LimitConfig(prior,
Xe136_0n2b_n7_counts)
Xe136_0n2b_n7_config = limit_config.LimitConfig(prior,
Xe136_0n2b_n7_counts)
signal_configs_np.append(Xe136_0n2b_n7_config_np)
signal_configs.append(Xe136_0n2b_n7_config)
# Background configuration
# Xe136_2n2b
Xe136_2n2b_prior = 1.132e6 # Based on KLZ T_1/2, for 1 years
# Since we used cut method to cut to livetime
# No penalty term
Xe136_2n2b_counts_np = numpy.array([Xe136_2n2b_prior])
Xe136_2n2b_config_np = limit_config.LimitConfig(Xe136_2n2b_prior,
Xe136_2n2b_counts_np)
# With penalty term
Xe136_2n2b_counts = numpy.linspace(0.947*Xe136_2n2b_prior,
1.053*Xe136_2n2b_prior, 51)
# 51 bins to make sure midpoint (no variation from prior) is included
# to use in penalty term (5.3% PRC 86, 021601 (2012))
sigma = 0.053 * Xe136_2n2b_prior
Xe136_2n2b_config = limit_config.LimitConfig(Xe136_2n2b_prior,
Xe136_2n2b_counts, sigma)
# B8_Solar
# Assume same rate as SNO+ for now
B8_Solar_prior = 1252.99691
# No penalty term
B8_Solar_counts_np = numpy.array([B8_Solar_prior])
B8_Solar_config_np = limit_config.LimitConfig(B8_Solar_prior,
B8_Solar_counts_np)
# With penalty term
B8_Solar_counts = numpy.linspace(0.96*B8_Solar_prior,
1.04*B8_Solar_prior, 10)
# 11 bins to make sure midpoint (no variation from prior) is included
sigma = 0.04 * B8_Solar_prior # 4% To use in penalty term
B8_Solar_config = limit_config.LimitConfig(B8_Solar_prior,
B8_Solar_counts, sigma)
# DBIsotope converter information - constant across modes
Xe136_atm_weight = 135.907219 # Molar Mass Calculator, http://www.webqc.org/mmcalc.php, 2015-05-07
Xe134_atm_weight = 133.90539450 # Molar Mass Calculator, http://www.webqc.org/mmcalc.php, 2015-06-03
# We want the atomic weight of the enriched Xenon
XeEn_atm_weight = 0.9093*Xe136_atm_weight + 0.0889*Xe134_atm_weight
Xe136_abundance = 0.089 # Xenon @ Periodic Table of Chemical Elements, http://www/webqc.org/periodictable-Xenon-Xe.html, 05/07/2015
loading = 0.0244 # PRC 86, 021601 (2012)
ib_radius = 1540. # mm, PRC 86, 021601 (2012)
scint_density = 7.5628e-7 # kg/mm^3, calculated by A Back 2015-07-28
# Make a list of associated nuclear physics info
nuclear_params = []
# n=1:
phase_space = 6.02e-16
matrix_element = 2.57 # Averaged
nuclear_params.append((phase_space, matrix_element))
# n=2:
phase_space = None
matrix_element = None
nuclear_params.append((phase_space, matrix_element))
# n=1:
phase_space = 1.06e-17 # Assuming two Majorons emitted
matrix_element = 1.e-3
nuclear_params.append((phase_space, matrix_element))
# n=1:
phase_space = 4.54e-17
matrix_element = 1.e-3
nuclear_params.append((phase_space, matrix_element))
# chi squared calculator
calculator = chi_squared.ChiSquared()
livetime = 112.3 / 365.25 # y, KamLAND-Zen 112.3 live days
# Set output location
output_dir = echidna.__echidna_base__ + "/results/snoplus/"
for signal, signal_config_np, nuclear_param in zip(signals,
signal_configs_np,
nuclear_params):
print signal._name
# Create no penalty limit setter
set_limit_np = limit_setting.LimitSetting(
signal, floating_backgrounds=floating_backgrounds)
# Configure signal
set_limit_np.configure_signal(signal_config_np)
# Configure 2n2b
set_limit_np.configure_background(Xe136_2n2b._name,
Xe136_2n2b_config_np)
# Configure B8
set_limit_np.configure_background(B8_Solar._name, B8_Solar_config_np)
# Set converter
phase_space, matrix_element = nuclear_param
roi_efficiency = signal.get_roi(0).get("efficiency")
converter = decay.DBIsotope(
"Xe136", Xe136_atm_weight, XeEn_atm_weight, Xe136_abundance,
phase_space, matrix_element, loading=loading, fv_radius=fv_radius,
outer_radius=ib_radius, scint_density=scint_density,
roi_efficiency=roi_efficiency)
# Set chi squared calculator
set_limit_np.set_calculator(calculator)
# Get limit
try:
limit = set_limit_np.get_limit()
print "-----------------------------------"
print "90% CL at " + str(limit) + " counts"
half_life = converter.counts_to_half_life(limit, livetime=livetime)
print "90% CL at " + str(half_life) + " yr"
print "-----------------------------------"
except IndexError as detail:
print "-----------------------------------"
print detail
print "-----------------------------------"
for i, signal_config_np in enumerate(signal_configs_np):
store.dump_ndarray(output_dir+signals[i]._name+"_np.hdf5",
signal_config_np)
raw_input("RETURN to continue")
signal_num = 0
for signal, signal_config, nuclear_param in zip(signals, signal_configs,
nuclear_params):
print signal._name
# Create limit setter
set_limit = limit_setting.LimitSetting(
signal, floating_backgrounds=floating_backgrounds)
# Configure signal
set_limit.configure_signal(signal_config)
# Configure 2n2b
set_limit.configure_background(Xe136_2n2b._name, Xe136_2n2b_config,
plot_systematic=True)
# Configure B8
set_limit.configure_background(B8_Solar._name, B8_Solar_config,
plot_systematic=True)
# Set converter
phase_space, matrix_element = nuclear_param
roi_efficiency = signal.get_roi(0).get("efficiency")
converter = decay.DBIsotope(
"Xe136", Xe136_atm_weight, XeEn_atm_weight, Xe136_abundance,
phase_space, matrix_element, loading=loading, fv_radius=fv_radius,
outer_radius=ib_radius, scint_density=scint_density,
roi_efficiency=roi_efficiency)
# Set chi squared calculator
set_limit.set_calculator(calculator)
# Get limit
try:
limit = set_limit.get_limit()
print "-----------------------------------"
print "90% CL at " + str(limit) + " counts"
half_life = converter.counts_to_half_life(limit, livetime=livetime)
print "90% CL at " + str(half_life) + " yr"
print "-----------------------------------"
except IndexError as detail:
print "-----------------------------------"
print detail
print "-----------------------------------"
# Dump SystAnalysers to hdf5
for syst_analyser in set_limit._syst_analysers.values():
store.dump_ndarray(output_dir+syst_analyser._name+str(signal_num)+".hdf5",
syst_analyser)
signal_num += 1
# Dump configs to hdf5
for i, signal_config in enumerate(signal_configs):
store.dump_ndarray(output_dir+signals[i]._name+".hdf5", signal_config)
store.dump_ndarray(output_dir+"Xe136_2n2b_config.hdf5", Xe136_2n2b_config)
store.dump_ndarray(output_dir+"B8_Solar_config.hdf5", B8_Solar_config)
