def __init__(self, basevars, tritium_exposure, tritium_activation,
mass_of_detector, flat_background_rate):
BaseModel.__init__(self, basevars)
# Set up the tritium decay
min_time = self.basevars.get_time().getMin()
max_time = self.basevars.get_time().getMax()
tritium_events = (tritium_exposure * tritium_activation *
mass_of_detector *
(math.exp(-math.log(2) * min_time / 12.36) -
math.exp(-math.log(2) * max_time / 12.36)))
self.beta_decay = BetaDecayModel(basevars, 18.6, 12.36)
self.beta_model = self.beta_decay.get_model()
# We have to grab the integration of the full spectrum to know how much is being
# requested
min_cache = self.basevars.get_energy().getMin()
max_cache = self.basevars.get_energy().getMax()
self.basevars.get_energy().setMax(18.6)
self.basevars.get_energy().setMin(0)
total_integral = self.beta_model.createIntegral(
ROOT.RooArgSet(basevars.get_energy())).getVal()
# Now resetting
self.basevars.get_energy().setMax(max_cache)
self.basevars.get_energy().setMin(min_cache)
sub_integral = self.beta_model.createIntegral(
ROOT.RooArgSet(basevars.get_energy())).getVal()
self.beta_model_amp = ROOT.RooRealVar(
"tritium_amplitude", "Tritium Amplitude",
tritium_events * sub_integral / total_integral, 1e-15,
3 * tritium_events)
self.beta_model_extend = ROOT.RooExtendPdf("tritium_extend_model",
"Tritium Extended Model",
self.beta_model,
self.beta_model_amp)
total_flat_events = (flat_background_rate * (max_cache - min_cache) *
mass_of_detector * (max_time - min_time) * 365.25)
self.flat_background = FlatModel(basevars)
self.flat_amp = ROOT.RooRealVar("flat_amplitude",
"Flat Background amplitude",
total_flat_events, 1e-15,
3 * total_flat_events)
self.flat_model = self.flat_background.get_model()
self.flat_model_extend = ROOT.RooExtendPdf("flat_extend_model",
"Flat Extended Model",
self.flat_model,
self.flat_amp)
self.total_background = ROOT.RooAddPdf(
"total_tritium_background", "Total Background (Tritium Model)",
ROOT.RooArgList(self.flat_model_extend, self.beta_model_extend))
def __init__(self,
basevars,
tritium_exposure,
tritium_activation,
mass_of_detector,
flat_background_rate):
BaseModel.__init__(self, basevars)
# Set up the tritium decay
min_time = self.basevars.get_time().getMin()
max_time = self.basevars.get_time().getMax()
tritium_events = (tritium_exposure*tritium_activation*mass_of_detector*
(math.exp(-math.log(2)*min_time/12.36) -
math.exp(-math.log(2)*max_time/12.36)))
self.beta_decay = BetaDecayModel(basevars, 18.6, 12.36)
self.beta_model = self.beta_decay.get_model()
# We have to grab the integration of the full spectrum to know how much is being
# requested
min_cache = self.basevars.get_energy().getMin()
max_cache = self.basevars.get_energy().getMax()
self.basevars.get_energy().setMax(18.6)
self.basevars.get_energy().setMin(0)
total_integral = self.beta_model.createIntegral(ROOT.RooArgSet(basevars.get_energy())).getVal()
# Now resetting
self.basevars.get_energy().setMax(max_cache)
self.basevars.get_energy().setMin(min_cache)
sub_integral = self.beta_model.createIntegral(ROOT.RooArgSet(basevars.get_energy())).getVal()
self.beta_model_amp = ROOT.RooRealVar("tritium_amplitude",
"Tritium Amplitude",
tritium_events*sub_integral/total_integral,
1e-15, 3*tritium_events)
self.beta_model_extend = ROOT.RooExtendPdf("tritium_extend_model",
"Tritium Extended Model",
self.beta_model, self.beta_model_amp)
total_flat_events = (flat_background_rate*(max_cache - min_cache)*
mass_of_detector*(max_time - min_time)*365.25)
self.flat_background = FlatModel(basevars)
self.flat_amp = ROOT.RooRealVar("flat_amplitude", "Flat Background amplitude",
total_flat_events, 1e-15, 3*total_flat_events)
self.flat_model = self.flat_background.get_model()
self.flat_model_extend = ROOT.RooExtendPdf("flat_extend_model",
"Flat Extended Model",
self.flat_model, self.flat_amp)
self.total_background = ROOT.RooAddPdf("total_tritium_background",
"Total Background (Tritium Model)",
ROOT.RooArgList(self.flat_model_extend,
self.beta_model_extend))
class TritiumDecayModel(BaseModel):
"""
This class returns a 2-D tritium decay spectrum with
a flat background. Inputs are:
- tritium_exposure: Tritium Exposure time (days)
- tritium_activation: Tritium activation rate in atoms/kg/day
- mass_of_detector: Mass of the detector
- flat_background_rate: Flat background rate, in counts/kg/keV/day
It returns an extended model with the relative amounts are set correctly (but allowed to float)
This means that if you are doing toy model fitting with the returned model before to generate
the events (RooFit will automatically generate the correct number of events from an extended pdf)
and SAVE all the variables.
# Save the values of the parameters to reset at the end
var_cache = ROOT.ostringstream()
model.getVariables().writeToStream(var_cache, False)
data = model.generate()
...
... (Fitting)
# Reset the variables
model.getVariables().readFromStream(ROOT.istringstream(var_cache.str()), False)
"""
def __init__(self, basevars, tritium_exposure, tritium_activation,
mass_of_detector, flat_background_rate):
BaseModel.__init__(self, basevars)
# Set up the tritium decay
min_time = self.basevars.get_time().getMin()
max_time = self.basevars.get_time().getMax()
tritium_events = (tritium_exposure * tritium_activation *
mass_of_detector *
(math.exp(-math.log(2) * min_time / 12.36) -
math.exp(-math.log(2) * max_time / 12.36)))
self.beta_decay = BetaDecayModel(basevars, 18.6, 12.36)
self.beta_model = self.beta_decay.get_model()
# We have to grab the integration of the full spectrum to know how much is being
# requested
min_cache = self.basevars.get_energy().getMin()
max_cache = self.basevars.get_energy().getMax()
self.basevars.get_energy().setMax(18.6)
self.basevars.get_energy().setMin(0)
total_integral = self.beta_model.createIntegral(
ROOT.RooArgSet(basevars.get_energy())).getVal()
# Now resetting
self.basevars.get_energy().setMax(max_cache)
self.basevars.get_energy().setMin(min_cache)
sub_integral = self.beta_model.createIntegral(
ROOT.RooArgSet(basevars.get_energy())).getVal()
self.beta_model_amp = ROOT.RooRealVar(
"tritium_amplitude", "Tritium Amplitude",
tritium_events * sub_integral / total_integral, 1e-15,
3 * tritium_events)
self.beta_model_extend = ROOT.RooExtendPdf("tritium_extend_model",
"Tritium Extended Model",
self.beta_model,
self.beta_model_amp)
total_flat_events = (flat_background_rate * (max_cache - min_cache) *
mass_of_detector * (max_time - min_time) * 365.25)
self.flat_background = FlatModel(basevars)
self.flat_amp = ROOT.RooRealVar("flat_amplitude",
"Flat Background amplitude",
total_flat_events, 1e-15,
3 * total_flat_events)
self.flat_model = self.flat_background.get_model()
self.flat_model_extend = ROOT.RooExtendPdf("flat_extend_model",
"Flat Extended Model",
self.flat_model,
self.flat_amp)
self.total_background = ROOT.RooAddPdf(
"total_tritium_background", "Total Background (Tritium Model)",
ROOT.RooArgList(self.flat_model_extend, self.beta_model_extend))
def get_model(self):
return self.total_background
class TritiumDecayModel(BaseModel):
"""
This class returns a 2-D tritium decay spectrum with
a flat background. Inputs are:
- tritium_exposure: Tritium Exposure time (days)
- tritium_activation: Tritium activation rate in atoms/kg/day
- mass_of_detector: Mass of the detector
- flat_background_rate: Flat background rate, in counts/kg/keV/day
It returns an extended model with the relative amounts are set correctly (but allowed to float)
This means that if you are doing toy model fitting with the returned model before to generate
the events (RooFit will automatically generate the correct number of events from an extended pdf)
and SAVE all the variables.
# Save the values of the parameters to reset at the end
var_cache = ROOT.ostringstream()
model.getVariables().writeToStream(var_cache, False)
data = model.generate()
...
... (Fitting)
# Reset the variables
model.getVariables().readFromStream(ROOT.istringstream(var_cache.str()), False)
"""
def __init__(self,
basevars,
tritium_exposure,
tritium_activation,
mass_of_detector,
flat_background_rate):
BaseModel.__init__(self, basevars)
# Set up the tritium decay
min_time = self.basevars.get_time().getMin()
max_time = self.basevars.get_time().getMax()
tritium_events = (tritium_exposure*tritium_activation*mass_of_detector*
(math.exp(-math.log(2)*min_time/12.36) -
math.exp(-math.log(2)*max_time/12.36)))
self.beta_decay = BetaDecayModel(basevars, 18.6, 12.36)
self.beta_model = self.beta_decay.get_model()
# We have to grab the integration of the full spectrum to know how much is being
# requested
min_cache = self.basevars.get_energy().getMin()
max_cache = self.basevars.get_energy().getMax()
self.basevars.get_energy().setMax(18.6)
self.basevars.get_energy().setMin(0)
total_integral = self.beta_model.createIntegral(ROOT.RooArgSet(basevars.get_energy())).getVal()
# Now resetting
self.basevars.get_energy().setMax(max_cache)
self.basevars.get_energy().setMin(min_cache)
sub_integral = self.beta_model.createIntegral(ROOT.RooArgSet(basevars.get_energy())).getVal()
self.beta_model_amp = ROOT.RooRealVar("tritium_amplitude",
"Tritium Amplitude",
tritium_events*sub_integral/total_integral,
1e-15, 3*tritium_events)
self.beta_model_extend = ROOT.RooExtendPdf("tritium_extend_model",
"Tritium Extended Model",
self.beta_model, self.beta_model_amp)
total_flat_events = (flat_background_rate*(max_cache - min_cache)*
mass_of_detector*(max_time - min_time)*365.25)
self.flat_background = FlatModel(basevars)
self.flat_amp = ROOT.RooRealVar("flat_amplitude", "Flat Background amplitude",
total_flat_events, 1e-15, 3*total_flat_events)
self.flat_model = self.flat_background.get_model()
self.flat_model_extend = ROOT.RooExtendPdf("flat_extend_model",
"Flat Extended Model",
self.flat_model, self.flat_amp)
self.total_background = ROOT.RooAddPdf("total_tritium_background",
"Total Background (Tritium Model)",
ROOT.RooArgList(self.flat_model_extend,
self.beta_model_extend))
def get_model(self):
return self.total_background