def __init__(self,
filename,
disable_morphing=False,
include_nuisance_parameters=True):
# Save setup
self.include_nuisance_parameters = include_nuisance_parameters
self.madminer_filename = filename
# Load data
logger.info("Loading data from %s", filename)
(
self.parameters,
self.benchmarks,
self.benchmark_is_nuisance,
self.morphing_components,
self.morphing_matrix,
self.observables,
self.n_samples,
_,
self.reference_benchmark,
self.nuisance_parameters,
self.n_events_generated_per_benchmark,
self.n_events_backgrounds,
) = load_madminer_settings(
filename, include_nuisance_benchmarks=include_nuisance_parameters)
self.n_parameters = len(self.parameters)
self.n_benchmarks = len(self.benchmarks)
self.n_benchmarks_phys = np.sum(
np.logical_not(self.benchmark_is_nuisance))
self.n_observables = 0 if self.observables is None else len(
self.observables)
self.n_nuisance_parameters = 0
if self.nuisance_parameters is not None and include_nuisance_parameters:
self.n_nuisance_parameters = len(self.nuisance_parameters)
else:
self.nuisance_parameters = None
# Morphing
self.morpher = None
if self.morphing_matrix is not None and self.morphing_components is not None and not disable_morphing:
self.morpher = PhysicsMorpher(self.parameters)
self.morpher.set_components(self.morphing_components)
self.morpher.set_basis(self.benchmarks,
morphing_matrix=self.morphing_matrix)
# Nuisance morphing
self.nuisance_morpher = None
if self.nuisance_parameters is not None:
self.nuisance_morpher = NuisanceMorpher(
self.nuisance_parameters, list(self.benchmarks.keys()),
self.reference_benchmark)
else:
self.include_nuisance_parameters = False
# Check event numbers
self._check_n_events()
self._report_setup()
def __init__(self, filename):
# Initialize samples
self.lhe_sample_filenames = []
self.sample_k_factors = []
self.sample_is_backgrounds = []
self.sampling_benchmarks = []
self.sample_systematics = []
# Initialize observables
self.observables = OrderedDict()
self.observables_required = OrderedDict()
self.observables_defaults = OrderedDict()
# Initialize cuts
self.cuts = []
self.cuts_default_pass = []
# Initialize efficiencies
self.efficiencies = []
self.efficiencies_default_pass = []
# Smearing function parameters
self.energy_resolution = {}
self.pt_resolution = {}
self.eta_resolution = {}
self.phi_resolution = {}
pdgids = [1, -1, 2, -2, 3, -3, 4, -4, 5, -5, 6, -6, 9]
pdgids += [
11, -11, 12, -12, 13, -13, 14, -14, 15, -15, 16, -16, 21, 22, 23,
24, -24, 25
]
for pdgid in pdgids:
self.energy_resolution[pdgid] = (0.0, 0.0)
self.pt_resolution[pdgid] = (0.0, 0.0)
self.eta_resolution[pdgid] = (0.0, 0.0)
self.phi_resolution[pdgid] = (0.0, 0.0)
self.pt_resolution["met"] = (0.0, 0.0)
# Initialize samples
self.reference_benchmark = None
self.observations = None
self.weights = None
self.events_sampling_benchmark_ids = None
# Initialize event summary
self.signal_events_per_benchmark = None
self.background_events = None
# Information from .h5 file
self.filename = filename
(parameters, benchmarks, _, _, _, _, _, self.systematics, _, _, _, _,
_, _) = load_madminer_settings(filename,
include_nuisance_benchmarks=False)
self.benchmark_names_phys = list(benchmarks.keys())
self.n_benchmarks_phys = len(benchmarks)
# Initialize nuisance parameters
self.nuisance_parameters = OrderedDict()
def __init__(self, filename):
# Initialize samples
self.hepmc_sample_filenames = []
self.hepmc_sample_weight_labels = []
self.hepmc_sampled_from_benchmark = []
self.hepmc_is_backgrounds = []
self.lhe_sample_filenames = []
self.lhe_sample_filenames_for_weights = []
self.delphes_sample_filenames = []
self.sample_k_factors = []
self.sample_systematics = []
# Initialize observables
self.observables = OrderedDict()
self.observables_required = OrderedDict()
self.observables_defaults = OrderedDict()
# Initialize cuts
self.cuts = []
self.cuts_default_pass = []
# Initialize acceptance cuts
self.acceptance_pt_min_e = None
self.acceptance_pt_min_mu = None
self.acceptance_pt_min_a = None
self.acceptance_pt_min_j = None
self.acceptance_eta_max_e = None
self.acceptance_eta_max_mu = None
self.acceptance_eta_max_a = None
self.acceptance_eta_max_j = None
# Initialize samples
self.reference_benchmark = None
self.observations = None
self.weights = None
self.events_sampling_benchmark_ids = None
# Initialize event summary
self.signal_events_per_benchmark = None
self.background_events = None
# Information from .h5 file
self.filename = filename
(parameters, benchmarks, _, _, _, _, _, self.systematics, _, _, _, _,
_, _) = load_madminer_settings(filename,
include_nuisance_benchmarks=False)
self.benchmark_names_phys = list(benchmarks.keys())
self.n_benchmarks_phys = len(benchmarks)
# Initialize nuisance parameters
self.nuisance_parameters = OrderedDict()
def load(self, filename, disable_morphing=False):
"""
Loads MadMiner setup from a file. All parameters, benchmarks, and morphing settings are overwritten. See `save`
for more details.
Parameters
----------
filename : str
Path to the MadMiner file.
disable_morphing : bool, optional
If True, the morphing setup is not loaded from the file. Default value: False.
Returns
-------
None
"""
# Load data
(
self.parameters,
self.benchmarks,
_,
morphing_components,
morphing_matrix,
_,
_,
self.systematics,
_,
_,
) = load_madminer_settings(filename, include_nuisance_benchmarks=False)
logger.info("Found %s parameters:", len(self.parameters))
for key, values in six.iteritems(self.parameters):
logger.info(
" %s (LHA: %s %s, maximal power in squared ME: %s, range: %s)",
key,
values[0],
values[1],
values[2],
values[3],
)
logger.info("Found %s benchmarks:", len(self.benchmarks))
for key, values in six.iteritems(self.benchmarks):
logger.info(" %s: %s", key, format_benchmark(values))
if self.default_benchmark is None:
self.default_benchmark = key
# Morphing
self.morpher = None
self.export_morphing = False
if morphing_matrix is not None and morphing_components is not None and not disable_morphing:
self.morpher = Morpher(self.parameters)
self.morpher.set_components(morphing_components)
self.morpher.set_basis(self.benchmarks,
morphing_matrix=morphing_matrix)
self.export_morphing = True
logger.info("Found morphing setup with %s components",
len(morphing_components))
else:
logger.info("Did not find morphing setup.")
# Systematics setup
if self.systematics is None:
logger.info("Did not find systematics setup.")
else:
logger.info(
"Found systematics setup with %s nuisance parameter groups",
len(self.systematics))
for key, value in six.iteritems(self.systematics):
logger.debug(" %s: %s", key, value)
def __init__(self,
filename,
disable_morphing=False,
include_nuisance_parameters=True):
# Save setup
self.include_nuisance_parameters = include_nuisance_parameters
self.madminer_filename = filename
logger.info("Loading data from %s", filename)
# Load data
(
self.parameters,
self.benchmarks,
self.benchmark_is_nuisance,
self.morphing_components,
self.morphing_matrix,
self.observables,
self.n_samples,
_,
self.reference_benchmark,
self.nuisance_parameters,
) = load_madminer_settings(
filename, include_nuisance_benchmarks=include_nuisance_parameters)
self.n_parameters = len(self.parameters)
self.n_benchmarks = len(self.benchmarks)
self.n_benchmarks_phys = np.sum(
np.logical_not(self.benchmark_is_nuisance))
self.n_observables = len(self.observables)
self.n_nuisance_parameters = 0
if self.nuisance_parameters is not None and include_nuisance_parameters:
self.n_nuisance_parameters = len(self.nuisance_parameters)
else:
self.nuisance_parameters = None
logger.info("Found %s parameters", self.n_parameters)
for key, values in six.iteritems(self.parameters):
logger.debug(
" %s (LHA: %s %s, maximal power in squared ME: %s, range: %s)",
key,
values[0],
values[1],
values[2],
values[3],
)
if self.nuisance_parameters is not None:
logger.info("Found %s nuisance parameters",
self.n_nuisance_parameters)
for key, values in six.iteritems(self.nuisance_parameters):
logger.debug(" %s (%s)", key, values)
else:
logger.info("Did not find nuisance parameters")
logger.info("Found %s benchmarks, of which %s physical",
self.n_benchmarks, self.n_benchmarks_phys)
for (key, values), is_nuisance in zip(six.iteritems(self.benchmarks),
self.benchmark_is_nuisance):
if is_nuisance:
logger.debug(" %s: systematics", key)
else:
logger.debug(" %s: %s", key, format_benchmark(values))
logger.info("Found %s observables", len(self.observables))
for i, obs in enumerate(self.observables):
logger.debug(" %2.2s %s", i, obs)
logger.info("Found %s events", self.n_samples)
# Morphing
self.morpher = None
if self.morphing_matrix is not None and self.morphing_components is not None and not disable_morphing:
self.morpher = PhysicsMorpher(self.parameters)
self.morpher.set_components(self.morphing_components)
self.morpher.set_basis(self.benchmarks,
morphing_matrix=self.morphing_matrix)
logger.info("Found morphing setup with %s components",
len(self.morphing_components))
else:
logger.info("Did not find morphing setup.")
# Nuisance morphing
self.nuisance_morpher = None
if self.nuisance_parameters is not None:
self.nuisance_morpher = NuisanceMorpher(
self.nuisance_parameters, list(self.benchmarks.keys()),
self.reference_benchmark)
logger.info("Found nuisance morphing setup")
