madminer.limits module¶
-
class
madminer.limits.
AsymptoticLimits
(filename=None, include_nuisance_parameters=False)[source]¶ Bases:
madminer.analysis.DataAnalyzer
Functions to calculate observed and expected constraints, using asymptotic properties of the likelihood ratio as test statistics.
Parameters: - filename : str
Path to MadMiner file (for instance the output of madminer.delphes.DelphesProcessor.save()).
- include_nuisance_parameters : bool, optional
If True, nuisance parameters are taken into account. Default value: False.
Methods
event_loader
(self[, start, end, batch_size, …])Yields batches of events in the MadMiner file. weighted_events
(self[, theta, nu, …])Returns all events together with the benchmark weights (if theta is None) or weights for a given theta. xsec_gradients
(self, thetas[, nus, events, …])Returns the gradient of total cross sections with respect to parameters. xsecs
(self[, thetas, nus, events, …])Returns the total cross sections for benchmarks or parameter points. asymptotic_p_value expected_limits observed_limits