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Fixing the FrequentistCalculator module #178

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Fixing the FrequentistCalculator module #178

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40d9b13
initial fix for frequentist calculator
tmombaecher Apr 24, 2025
9faf126
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Apr 24, 2025
560e744
Merge branch 'main' into tmombach_fixfreqcalculator
eduardo-rodrigues Aug 28, 2025
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2 changes: 1 addition & 1 deletion src/hepstats/hypotests/calculators/frequentist_calculator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,7 @@ def qnull(
>>> poialt = POI(mean, 1.2)
>>> q = calc.qnull(poinull, poialt)
"""
toysresults = self.get_toys_null(poinull, poialt, qtilde)
toysresults = self.get_toys_null(poinull, poinull, qtilde)
ret = {}

for p in poinull:
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8 changes: 3 additions & 5 deletions src/hepstats/hypotests/hypotests_object.py
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Expand Up @@ -201,7 +201,6 @@ def sampler(self):

>>> sampler = calc.sampler()
"""
self.set_params_to_bestfit()
nevents = []
for m, d in zip(self.loss.model, self.loss.data):
nevents_data = get_nevents(d)
Expand Down Expand Up @@ -251,8 +250,7 @@ def toys_loss(self, parameter_name: str):
Example with `zfit`:
>>> loss = calc.toys_loss(zfit.Parameter("mean"))
"""
if parameter_name not in self._toys_loss:
parameter = self.get_parameter(parameter_name)
sampler = self.sampler()
self._toys_loss[parameter.name] = self.lossbuilder(self.model, sampler)
parameter = self.get_parameter(parameter_name)
sampler = self.sampler()
self._toys_loss[parameter.name] = self.lossbuilder(self.model, sampler)
return self._toys_loss[parameter_name]
11 changes: 9 additions & 2 deletions src/hepstats/hypotests/toyutils.py
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Expand Up @@ -232,11 +232,18 @@ def generate_and_fit_toys( # TODO PROFILE THIS
poieval: POI values to evaluate the loss function
"""

self.set_params_to_bestfit()

minimizer = self.minimizer
param = poigen.parameter

# generate toys from best fit at profile point
param.set_value(poigen.value)
is_poi_floating = param.floating
param.floating = False
profile_minimum = minimizer.minimize(loss=self.loss)
if not profile_minimum.valid:
print(poigen, "PROBLEM: profile fit not valid, toys won't be either")
param.floating = is_poi_floating

toys_loss = self.toys_loss(poigen.name)
sampler = toys_loss.data

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