From 34530401b2069e47d9852fcd72c07bca698b27f9 Mon Sep 17 00:00:00 2001 From: Lukas Heinrich Date: Fri, 3 Mar 2023 17:48:03 +0100 Subject: [PATCH] first attempt --- src/pyhf/infer/calculators.py | 59 ++++++++++++++++++++++++----------- 1 file changed, 41 insertions(+), 18 deletions(-) diff --git a/src/pyhf/infer/calculators.py b/src/pyhf/infer/calculators.py index ed9642e085..18c8d078a7 100644 --- a/src/pyhf/infer/calculators.py +++ b/src/pyhf/infer/calculators.py @@ -674,6 +674,7 @@ def __init__( test_stat="qtilde", ntoys=2000, track_progress=True, + skip_failing_toys = False, ): r""" Toy-based Calculator. @@ -704,6 +705,7 @@ def __init__( ~pyhf.infer.calculators.ToyCalculator: The calculator for toy-based quantities. """ + self.skip_failing_toys = skip_failing_toys self.ntoys = ntoys self.data = data self.pdf = pdf @@ -753,6 +755,9 @@ def distributions(self, poi_test, track_progress=None): Tuple (~pyhf.infer.calculators.EmpiricalDistribution): The distributions under the hypotheses. """ + + print('skip?',self.skip_failing_toys) + tensorlib, _ = get_backend() sample_shape = (self.ntoys,) @@ -791,29 +796,47 @@ def distributions(self, poi_test, track_progress=None): signal_teststat = [] for sample in tqdm.tqdm(signal_sample, **tqdm_options, desc='Signal-like'): - signal_teststat.append( - teststat_func( - poi_test, - sample, - self.pdf, - self.init_pars, - self.par_bounds, - self.fixed_params, + try: + value = teststat_func( + poi_test, + sample, + self.pdf, + self.init_pars, + self.par_bounds, + self.fixed_params, + ) + except RuntimeError: + if self.skip_failing_toys: + value = None + else: + raise + + if (value is not None) and (tensorlib.isfinite(value)): + signal_teststat.append( + value ) - ) bkg_teststat = [] for sample in tqdm.tqdm(bkg_sample, **tqdm_options, desc='Background-like'): - bkg_teststat.append( - teststat_func( - poi_test, - sample, - self.pdf, - self.init_pars, - self.par_bounds, - self.fixed_params, + try: + value = teststat_func( + poi_test, + sample, + self.pdf, + self.init_pars, + self.par_bounds, + self.fixed_params, + ) + except RuntimeError: + if self.skip_failing_toys: + value = None + else: + raise + + if (value is not None) and (tensorlib.isfinite(value)): + bkg_teststat.append( + value ) - ) s_plus_b = EmpiricalDistribution(tensorlib.astensor(signal_teststat)) b_only = EmpiricalDistribution(tensorlib.astensor(bkg_teststat))